United States Environmental Protection Agency Office of Toxic Substances Washington, D.C. 20460 EPA 560/5-85-004 July 1985 PROPERTY OF Toxic Substances _ Methods for Assessing Exposure to Chemical Substances Volume 4 Methods for Enumerating and Characterizing Populations Exposed to Chemical Substances METHODS FOR ASSESS I MG E XPC)SURE TO CHEMICAL SUBSTANCES 4 METHODS FOR ASSESS 1 MG EXPOSLJRE TO CHEMICAL SUBSTANCES 4 EPA 560 5-85 004 ERA 560 5—95 004 Hazardous Waste Research and Information Center Library One East Hazelwood Drive Champaign, IL 61820 217/333-8957 oewco EPA 560/5-85-004 JULY 1985 METHODS FOR ASSESSING EXPOSURE TO CHEMICAL SUBSTANCES Volume 4 Methods for Enumerating and Characterizing Populations Exposed to Chemical Substances by Douglas A. Dixon, Karen A. Hammerstrom, Gina L. Hendrickson, Patricia Jennings, Thompson Chambers, Amy Borensteln, John Dorla, Thomas Faha EPA Contract No. 68-01-6271 Project Officer Michael A. Callahan Exposure Evaluation Division Office of Toxic Substances Washington, DC 20460 U.S. ENVIRONMENTAL PROTECTION AGENCY OFFICE OF PESTICIDES AND TOXIC SUBSTANCES WASHINGTON, DC 20460 Digitized by the Internet Archive in 2018 with funding from University of Illinois Urbana-Champaign Alternates https://archive.org/details/methodsforassessOOdixo DISCLAIMER This document has been reviewed and approved for publication by the Office of Toxic Substances, Office of Pesticides and Toxic Substances, U.S. Environmental Protection Agency. The use of trade names or commercial products does not constitute Agency endorsement or recommendation for use. Ill FOREWORD This document Is one of a series of volumes, developed for the U.S. Environmental Protection Agency (EPA), Office of Toxic Substances (OTS), that provides methods and Information useful for assessing exposure to chemical substances. The methods described In these volumes have been Identified by EPA-OTS as having utility In exposure assessments on existing and new chemicals In the OTS program. These methods are not necessarily the only methods used by OTS, because the state-of-the-art In exposure assessment Is changing rapidly, as Is the availability of methods and tools. There Is no single correct approach to performing an exposure assessment, and the methods In these volumes are accordingly discussed only as options to be considered, rather than as rigid procedures. Perhaps more Important than the optional methods presented In these volumes Is the general Information catalogued. These documents contain a great deal of non-chemlcal-speclf1c data which can be used for many types of exposure assessments. This Information Is presented along with the methods In Individual volumes and appendices. As a set, these volumes should be thought of as a catalog of Information useful In exposure assessment, and not as a "how-to" cookbook on the subject. The definition, background, and discussion of planning exposure assessments are discussed In the Introductory volume of the series (Volume 1). Each subsequent volume addresses only one general exposure setting. Consult Volume 1 for guidance on the proper use and Interrelations of the various volumes and on the planning and Integration of an entire assessment. The titles of the nine basic volumes are as follows: Volume 1 Methods for Assessing Exposure to Chemical Substances (EPA 560/5-85-001) Volume 2 Methods for Assessing Exposure to Chemical Substances In the Ambient Environment (EPA 560/5-85-002) Volume 3 Methods for Assessing Exposure from Disposal of Chemical Substances (EPA 560/5-85-003) Volume 4 Methods for Enumerating and Characterizing Populations Exposed to Chemical Substances (EPA 560/5-85-004) Volume 5 Methods for Assessing Exposure to Chemical Substances In Drinking Water (EPA 560/5-85-005) v Volume 6 Methods for Assessing Occupational Exposure to Chemical Substances (EPA 560/5-85-006) Volume 7 Methods for Assessing Consumer Exposure to Chemical Substances (EPA 560/5-85-007) Volume 8 Methods for Assessing Environmental Pathways of Food Contamination (EPA 560/5-85-008) Volume 9 Methods for Assessing Exposure to Chemical Substances Resulting from Transportation-Related Spills (EPA 560/5-85-009) Because exposure assessment Is a rapidly developing field. Its methods and analytical tools are quite dynamic. EPA-OTS Intends to Issue periodic supplements for Volumes 2 through 9 to describe significant Improvements and updates for the existing Information, as well as adding short monographs to the series on specific areas of Interest. The first four of these monographs are as follows: Volume 10 Methods for Estimating Uncertainties In Exposure Assessments (EPA 560/5-85-014) Volume 11 Methods for Estimating the Migration of Chemical Substances from Solid Matrices (EPA 560/5-85-015) Volume 12 Methods for Estimating the Concentration of Chemical Substances In Indoor Air (EPA 560/5-85-016) Volume 13 Methods for Estimating Retention of Liquids on Hands (EPA 560/5-85-017) Michael A. Callahan, Chief Exposure Assessment Branch Exposure Evaluation Division (TS-798) Office of Toxic Substances v 1 ACKNOWLEDGEMENTS This report was prepared by Versar Inc. of Springfield, Virginia, for the EPA Office of Toxic Substances, Exposure Evaluation Division, Exposure Assessment Branch (EAB) under EPA Contract No. 68-01-6271 (Task 9). The EPA-EAB Task Manager was Karen A. Hammerstrom, the EPA Program Manager was Michael Callahan; their support and guidance Is gratefully acknowledged. Acknowledgement Is also given to Elizabeth Bryan and Loren Hall of EPA-EED, who also took part In this task. A number of Versar personnel have contributed to this task over the three-year period of performance as shown below: Program Management Gayaneh Contos Task Management Douglas Dixon Technical Support Gina Hendrickson Patricia Jennings Thompson Chambers Amy Borensteln John Dorla Thomas Faha Steve Mitchell Michael Neely Editing Juliet Crumrlne Secretarial/Clerical Shirley Harrison Lucy Gentry Donna Barnard TABLE OF CONTENTS Page No . FOREWORD . v ACKNOWLEDGEMENTS . vll TABLE OF CONTENTS. lx LIST OF TABLES. xil LIST OF FIGURES. xv LIST OF METHODS. xvll 1. INTRODUCTION . 1 1.1 Purpose and Scope. 1 1.2 Report Organization . 1 1.3 Framework of Methods . 2 2. POPULATIONS EXPOSED TO CHEMICAL SUBSTANCES IN THE AMBIENT ENVIRONMENT. 5 2.1 Introduction. 5 2.2 Identification of Exposed Populations . 5 2.3 Methods for the Enumeration of Exposed Populations 9 2.3.1 Census of Population . 9 2.3.2 Enumeration of Populations Exposed via Inhalation 35 2.3.3 Enumeration of Populations Exposed via Dermal Contact. 56 2.3.4 Enumeration of Non-Human Populations . 59 2.4 Characterization of Exposed Populations . 61 2.4.1 Populations Exposed via Inhalation . 61 2.4.2 Population Exposed via Dermal Contact. 63 2.5 References. 66 3. POPULATIONS EXPOSED TO CHEMICAL SUBSTANCES IN THE OCCUPATIONAL ENVIRONMENT .... . 69 3.1 Introduction. 69 3.2 Identification of Exposed Populations . 69 3.3 Methods for the Enumeration of Exposed Populations . . 72 ix TABLE OF CONTENTS (Continued) Page No . 3.3.1 Enumeration of Populations Identified by SIC Code. 73 3.3.2 Enumeration of Populations Defined by Occupation and Industry. 77 3.3.3 Enumeration of Site-Specific Populations .... 79 3.4 Characterization of Occupationally Exposed Populations.. 82 3.5 References. 87 4. POPULATIONS EXPOSED TO CHEMICAL SUBSTANCES VIA THE INGESTION OF FOOD. 89 4.1 Introduction. 89 4.2 Identification of Exposed Populations . 89 4.3 Methods for the Enumeration of Exposed Populations. . . 91 4.3.1 Enumeration of Populations Exposed as a Result of Agricultural Practices . 93 4.3.2 Enumeration of the Populations Exposed as a Result of Processing and Packaging . 94 4.3.3 Enumeration of Populations Exposed as a Result of Releases from Other Sources ... 98 4.3.4 Enumeration of Exposed Populations by the Use of Monitoring Data. 106 4.4 Characterization of the Exposed Population . Ill 4.5 References. 115 5. POPULATIONS EXPOSED TO CHEMICAL SUBSTANCES VIA THE USE OF CONSUMER PRODUCTS . 117 5.1 Introduction. 117 5.2 Identification of Exposed Populations. 117 5.3 Methods for the Enumeration of Exposed Populations . . . 120 5.3.1 Enumeration of Exposed Populations via Simmons Market Research Bureau Reports. 120 5.3.2 Enumeration of Exposed Populations via Production and Sales Data. 138 5.3.3 Enumeration of Exposed Populations via Chemical- Specific Information. 138 5.3.4 Enumeration of Consumers Performing Amateur or Hobbyist Activities . 141 5.4 Characterization of Exposed Populations. 142 5.5 References. 146 x TABLE OF CONTENTS (Continued) Page No . 6. POPULATIONS EXPOSED TO CHEMICAL SUBSTANCES VIA THE INGESTION OF DRINKING WATER. 147 6.1 Introduction. 147 6.2 Identification of Exposed Populations. 149 6.3 Methods for the Enumeration of Exposed Populations . . . 149 6.3.1 Enumeration of Populations In Specific Geographic Areas. 151 6.3.2 Enumeration of Populations Exposed via Treatment Methods . 160 6.3.3 Enumeration of Exposed Populations by Type of Distribution System . 163 6.3.4 Enumeration by Use of Monitoring Data. 165 6.4 Characterization of Exposed Populations . 168 6.5 References. 169 APPENDIX A: APPLICATION OF METHODS TO EXAMPLE PROBLEMS . 171 Introduction . 173 A-l. Populations Exposed to Chemical Substances In the Ambient Environment. 174 A-2. Populations Exposed to Chemical Substances In the Occupational Environment. 200 A-3. Populations Exposed to Chemical Substances via the Ingestion of Food. 208 A-4. Populations Exposed to Chemical Substances via the Use of Consumer Products. 214 A-5. Populations Exposed to Chemical Substances via the Ingestion of Drinking Water. 225 APPENDIX B: EXAMPLES OF DATA BASES USED IN OCCUPATIONAL POPULATIONS METHODS SECTION . 233 xi LIST OF TABLES Page No. Table 1 Population Subject Items Included In the 1980 Census . . 10 Table 2 Geographic Units of the Census of Population. 12 Table 3 Information on 1980 Census Reports: Their Geographical Breakdown, Characteristics, and Expected Dates of Release . 20 Table 4 Relationship of 1980 Summary Tape Files. Printed Reports, and Microfiche . 25 Table 5 Summary Tape File Geography (1980). 26 Table 6 Smallest Type of Area on 1980 Census Summary Tape Files. 27 Table 7 Census Outline Maps. 28 Table 8 Population Densities for the Different Census Bureau Area Classifications and Regions . 47 Table 9 Average U.S. Population Size for ATM-SECP0P Concentration Sectors for General Point Sources Located In Urbanized, Metropolitan, and NonmetropolItan Areas . . 48 Table 10 1980 Population Data for the U.S. and Regions by Census Geography . 51 Table 11 Sources of Information on Non-Human Populations .... 62 Table 12 Population of the United States by Age and Sex: April 1 , 1980 64 Table 13 Data Available In the 1977 Economic Censuses. 76 Table 14 Employed Persons by Occupation and Sex, 1979 . 84 Table 15 Age and Sex Distribution of Employment by General Occupation. 86 Table 16 Ranking of Seafood Species by Percent of Individuals Consuming and Projected 1980 Consuming Population . . . 103 xi i LIST OF TABLES (Continued) Page No. Table 17 Percent of Households, U.S. Population, and Household Size In Urban, Rural Non-Farm, and Rural Farm Areas with Home Fruit and Vegetable Garden In 1977 . 107 Table 18 Percent Gardening Households Growing, Freezing, Canning, or Preserving Selected Home Grown Fruits and Vegetables, 1975-77 108 Table 19 Simmons Market Research Bureau Product Categories and Services Provided by Volume . 121 Table 20 Alphabetical Index of Products and Services Measured In the 1980 SMRB Study. 122 Table 21 Product Usage Categorization for SMRB "Heavy," "Medium," and "Light" Designations . 130 Table 22 Example of 1981 SMRB Data: Demographic Variables for Usage of Rug Cleaners Purchased by Female Homemakers . . 131 Table 23 Example of 1981 SMRB Data: Demographic Variables for Types of Rug Cleaners Purchased by Female Homemakers . . 132 Table 24 Example of 1981 SMRB Data: Demographic Variables for Brands of Rug Cleaners Purchased by Female Homemakers . 133 Table 25 Summary of the Number of Households that Can Be Considered To Have at Least One Amateur or Hobbyist With Respect to a Specific Activity. 143 Table 26 Federal Reporting Data System (FRDS) Description of 11 Standard Reports . 158 Table 27 Population Served by Drinking Water Treatment Processes for the U.S. 161 Table 28 Distribution System Components and Potential Contaminants . 164 Table 29 Populations Served by Drinking Water System Size and Source Type xi i i 167 LIST OF TABLES (Continued) Page No. Table 30 Line Source Corridor Distances, Population Density and Population Exposed In Problem 5 197 Table 31 Characterization of Exposed Population for Line Source Problem 5. 199 Table 32 Employment by SIC Code for Producers and Users of Phosphate Fertilizers . 201 Table 33 Rug/Carpet Cleaning Products Market Survey Results . . 219 LIST OF FIGURES Page No . Figure 1 Three-Stage Framework for Identifying, Enumerating, and Characterizing Populations Exposed to Chemical Substances . 3 Figure 2 Three-Stage Framework for Enumerating and Characterizing Populations Exposed to Chemical Substances In the Ambient Environment . 6 Figure 3 Geographic Regions and Divisions of the United States . 11 Figure 4 Geographic Organization of the Major Census Statistical Categories. 16 Figure 5 Breakdown of Census Geography . 17 Figure 6 Census Geography for Metropolitan and NonmetropolItan Counties. 18 Figure 7 Examples of Census Maps. 30 Figure 8 Telephone Contacts for Bureau of the Census Data Users. 31 Figure 9 Wind Rose Sectors for ATM-SECPOP. 37 Figure 10 Sample ATM-SECPOP Output for Concentration, Population, and Population Exposure . 39 Figure 11 Sample ATM-SECPOP Graphic Display: Bar Chart of Population Exposure vs. Distance . 40 Figure 12 Sample ATM-SECPOP Graphic Display: Line Plot of Concentration vs. Distance . 41 Figure 13 Sample ATM-SECPOP Graphic Display: Rose Diagram of Population Exposed . 42 Figure 14 Sample of ATM-SECPOP Mapping of ED/BGs Around a Point Source. 43 Figure 15 Schematic Representation of the Procedure to Enumerate Populations Exposed to Chemical Substances Released from a Line Source. 54 xv LIST OF FIGURES (Continued) Page No . Figure 16 Three-stage Framework for Enumeration and Characterization of Occupationally Exposed Populations . 70 Figure 17 Three-stage Framework for the Enumeration and Characterization of Populations Exposed to Chemical Substances via the Ingestion of Food . 90 Figure 18 Example Data Summary from National Food Consumption Survey of 1977-78 . 112 Figure 19 Three-stage Framework for the Identification, Enumeration, and Characterization of Populations Exposed to Chemical Substances In Consumer Products . . 118 Figure 20 A Page from a Typical 1980 SMRB Marketing Report . . . 134 Figure 21 Three-stage Framework for Enumerating and Characterizing Populations Exposed to Chemical Substances via the Ingestion of Drinking Water .... 148 Figure 22 Example Printout of the Model State Information System - Public Water Supply Inventory for Redmond City, Oregon . 157 xvi LIST OF METHODS Page No . Method 2-1 General Procedure for Identifying Populations Exposed to Chemical Substances In the Ambient Environment ... 7 Method 2-2 Enumeration of Populations Exposed via Inhalation to Atmospheric Concentrations of Chemical Substances Released from Point Sources . 44 Method 2-3 Enumeration of Populations Exposed via Inhalation to Chemical Substances Released from Prototype Point Sources. 49 Method 2-4 Enumeration of Populations Exposed via Inhalation to Atmospheric Concentrations of Chemical Substances Released from Area Sources. 52 Method 2-5 Enumeration of Populations Exposed via Inhalation to Chemical Substances Released from Line Sources .... 57 Method 2-6 Enumeration of Populations Exposed via Dermal Contact . 58 Method 2-7 Characterization of Populations Exposed to Chemical Substances via Inhalation of Ambient Air . 65 Method 3-1 General Procedure for Identifying Populations Exposed In the Workplace. 71 Method 3-2 Enumeration of Populations Identified by SIC Code ... 74 Method 3-3 Enumeration of Populations Identified by Occupation and Industry. 78 Method 3-4 Enumeration of Site-Specific Populations . 80 Method 3-5 Characterization of Occupationally Exposed Populations. 83 Method 4-1 Generalized Procedure for Identifying Populations Exposed to Chemical Substances via the Ingestion of Food. 92 Method 4-2 Enumeration of Populations Exposed as a Result of Agricultural Practices . 95 xvi i LIST OF METHODS Page No . Method 4-3 Enumeration of Populations Exposed as a Result of Packaging and Processing of Food. 97 Method 4-4 Enumeration of Populations Exposed as a Result of Packaging or Processing Procedures Used by a Specific Company. 99 Method 4-5 Enumeration of Populations Exposed as a Result of Consuming Noncommercial Freshwater Fish or Game from a Geographically Defined Area of Contamination . 101 Method 4-6 Enumeration of Populations Exposed as a Result of Consuming Seafood from a Geographically Defined Area of Contamination . 105 Method 4-7 Enumeration of Populations Exposed to Chemical Substances via the Consumption of Home Grown Fruits and Vegetables. 109 Method 4-8 Enumeration of Exposed Populations by the Use of Monitoring Data. 110 Method 4-9 Characterization of Populations Exposed to Chemical Substances In Types of Food. 113 Method 5-1 General Procedure for Identifying Populations Exposed to Chemical Substances In Consumer Products . 119 Method 5-2 Enumeration of Exposed Consumer Populations via the Use of Simmons Market Research Bureau Reports . 136 Method 5-3 Enumeration of Populations Exposed to Chemicals In Consumer Products via the Use of Economic Data .... 139 Method 5-4 Characterization of Populations Exposed to Chemical Substances In Consumer Products . 145 Method 6-1 General Procedure for Identifying Populations Exposed to Chemical Substances In Drinking Water . 150 Method 6-2 Enumeration of Populations Exposed to Chemical Substances In Surface Sources of Drinking Water Using the REACH File. 153 xvi i i LIST OF METHODS Page No . Method 6-3 Enumeration of Populations Exposed to Chemical Substances In Surface Sources of Drinking Water Using the FRDS Data Base . 155 Method 6-4 Enumeration of Populations Exposed to Chemical Substances In Ground Sources of Drinking Water .... 159 Method 6-5 Enumeration of Populations Exposed to Chemical Substances as a Result of Lack of Treatment Processes . 162 Method 6-6 Enumeration of Exposed Populations by the Use of Monitoring Data . 166 XI X INTRODUCTION 1 . This volume Is the fourth In a series of nine volumes presenting methods for assessing exposures to chemical substances; the reports are being developed for the U.S. Environmental Protection Agency (EPA), Office of Toxic Substances (OTS). This volume presents methods and supporting Information for enumerating and characterizing populations exposed to chemical substances In each of the EPA-OTS defined exposure categories. The purpose and scope of this report, the report organization, and the methodological framework are discussed In the following subsections. 1.1 Purpose and Scope This document and the methods that It contains have been prepared to aid In overcoming one of the major difficulties encountered In the preparation of exposure assessments for Individual chemical substances: the enumeration and characterization of specific populations exposed to chemical substances. Each of the seven categories of an exposure assessment has certain populations associated with It, and each population has further subpopulatlons that vary with respect to the concentrations to which they are exposed and the frequency and duration of exposure. While It has often been possible to Identify exposed populations from monitoring or release data. It has rarely been possible to estimate sizes of specific subpopulatlons. The purpose of this report, therefore, Is to catalog pertinent Information, data bases, and tools, and to provide a systematic approach or methods whereby the population exposed to a given chemical substance In each of the exposure categories can be enumerated and characterized according to age and sex at any desired level of detail. 1.2 Report Organization The data sources and methods to enumerate and characterize exposed populations In each of the exposure categories are specific to that exposure category. This report, therefore, Is divided Into separate sections according to the category of exposed populations as follows: • Section 2 - Populations Exposed to Chemical Substances In the Ambient Environment • Section 3 Populations Exposed to Chemical Substances In the Occupational Environment • Section 4 Populations Exposed to Chemical Substances via the Ingestion of Food 1 • Section 5 - Populations Exposed to Chemical Substances via the Use of Consumer Products • Section 6 - Populations Exposed to Chemical Substances via the Ingestion of Drinking Water. Exposures resulting from the disposal and transportation related spills of chemical substances are subsets of exposures occurring In the ambient environment. Populations exposed to chemical substances In these categories are Identified either geographically or by occupation. Section 2 of this report covers the geographic enumeration and characterization of exposed populations, while Section 3 covers the enumeration and characterization of occupationally exposed populations. Finally, demonstrations of the methods contained In each section of this report are presented as example population problems In the Appendix. 1.3 Framework of Methods The framework for enumerating and characterizing exposed populations Is the same for each of the sections and comprises three stages. These stages are: 1. The Identification of the exposed population. 2. The enumeration of the exposed population. 3. The characterization of the exposed population according to age and sex. Figure 1 Is a flow diagram of the three-stage framework. The following paragraphs briefly describe each stage; detailed Information Is provided In each of the sections of this report. The first stage, the Identification of exposed populations, Is a function of the chemical and physical properties, sources of environmental release (l.e., manufacturing, processing, distribution, use, and disposal), and environmental transport and transformation of a chemical substance. Identification and evaluation of these data will Indicate the media (l.e., air, water, soil), exposure route (Inhalation, Ingestion, dermal absorption), exposure category or scenario (e.g., ambient, occupational, drinking water), and the activities that lead to exposure or the microenvironments where exposure occurs. Information on Identifying exposed populations Is contained In Volumes 2 through 9 of this exposure assessment methods report series.. This report only briefly describes the procedures for Identifying exposed populations. 2 IDENTIFICATION OF EXPOSED POPULATIONS • EVALUATE CHEMICAL/PHYSICAL PROPERTIES • IDENTIFY SOURCES & RELEASES • EVALUATE TRANSPORT AND TRANSFORMATION • GATHER MONITORING DATA TO • IDENTIFY MEDIA AND EXPOSURE ROUTE • IDENTIFY EXPOSURE SCENARIOS (i.e., AMBIENT OCCUPATIONAL, CONSUMER, FOOD, DRINKING WATER ) • IDENTIFY MICROENVIRONMENTS AND ACTIVITIES 5 II ENUMERATION OF EXPOSED POPULATIONS DATA SOURCES AND METHODS TO ENUMERATE POPULATIONS EXPOSED TO CHEMICAL SUBSTANCES IN: • THE AMBIENT ENVIRONMENT • THE OCCUPATIONAL ENVIRONMENT • FOOD • DRINKING WATER • CONSUMER PRODUCTS III CHARACTERIZATION OF EXPOSED POPULATIONS DATA SOURCES AND METHODS TO OBTAIN AGE AND/OR SEX CHARACTERISTICS BY USING: • GEOGRAPHIC OR ACTIVITY SPECFIC DATA • GENERIC DATA gure 1. Three-stage Framework for Identifying, Enumerating, and Characterizing Populations Exposed to Chemical Substances 3 The second stage Involves the use of various data sources, computerized data bases, and generic Information to enumerate exposed populations. In the appropriate exposure category sections of this report, data sources are discussed, Including any limitations; the responsible agencies or Individuals who must be contacted to obtain the required Information are also listed. Methods utilizing the various data sources are presented In a step-by-step fashion In each section so that the Investigator or exposure assessment team can enumerate exposed populations efficiently. The final stage describes the data sources and procedures to be used to characterize the exposed population. Characterization of the exposed population Involves determining the numbers of Individuals In particular age and sex classes. The age and sex of the exposed population affect the physiological parameters that determine exposure (1.e., breathing rate, body weight, skin surface area) and Identify sensitive subpopulatlons (e.g., children, women of childbearing age). Detailed exposure assessments may require that populations be described by age and sex distribution. The procedures presented for this stage In each of the exposure category sections direct the Investigator or assessment team In the use of geographic data, activity-specific data, or generic data on age and sex distributions to characterize exposed populations. 4 2. POPULATIONS EXPOSED TO CHEMICAL SUBSTANCES IN THE AMBIENT ENVIRONMENT 2.1 Introduction This section presents methods for enumerating and characterizing populations exposed to chemical substances In the ambient environment. The methods described are applicable to populations exposed as a result of Industrial effluents, non-point or area sources, natural sources, disposal related releases, consumer related releases, spills from transportation or storage activities, and unknown sources. Figure 2 Is a flow diagram of the three-stage framework for enumerating populations exposed to chemical substances In the ambient environment. Included In the diagram are some of the major data sources used In the three stages. The Identification of exposed populations Is discussed only briefly In this section (Subsection 2.2); the ambient exposure assessment methods report (Volume 2) describes the process In detail. The enumeration of the exposed population principally relies on population data collected by the Bureau of the Census, particularly the decennial Census of Population. The most recently conducted Census, the data publication form and document titles, and the use of census data In exposure assessment population studies are discussed In detail In Subsection 2.3. The age and sex of the exposed population affect the physiological parameters that determine exposure (e.g., breathing rate, skin surface area) and Identify sensitive subpopulatlons (e.g., women of child-bearing age, the elderly). Detailed exposure assessments may require that populations be described by age and sex distribution. Subsection 2.4 discusses the data sources and procedures to characterize populations by age and sex distribution. 2.2 Identification of Exposed Populations Populations potentially exposed to a chemical substance In the ambient environment are Identified through an evaluation of the substance's sources, Its behavior In the environment, and applicable monitoring data. Subpopulatlons may be further defined by their participation In specific activities leading to exposure. Method 2-1 summarizes the steps Involved In Identifying populations exposed to chemical substances In the ambient environment. Volume 2 of this series describes the requisite data In detail. 5 r L r n L r in L •NOT CONSIDERED IN THISMETHOO (SEE VOLUME 5 - METHODS FOR ASSESSING EXPOSURE TO CHEMICAL SUBSTANCES IN DRINKING WATER) Figure 2. Three-stage Framework for Enumerating and Characterizing Populations Exposed to Chemical Substances in the Ambient Environment 6 Method 2-1. General Procedure for Identifying Populations Exposed to Chemical Substances in the Ambient Environment Step 1 Identify the locations of chemical release into the environment; define each release to the atmosphere as a point, area, or line source. Using monitoring data and/or environmental fate information, identify the geographic locales and media of concern (air, water, land). Volume 2 of this series catalogs data bases, information sources, and tools that will aid in this process. Step 2 For each medium of interest, evaluate the significance of exposure routes: • Air - inhalation • Water - dermal contact • Land - dermal contact Step 3 Identify exposed populations by listing significant pathways: • Persons breathing ambient air contaminated by atmospheric point, area, or line sources. • Persons swirrming in contaminated surface waters. • Non-human populations of ecological or economic importance residing in the locale and media of concern. • Other populations not specifically addressed in this volume (e.g., children swallowing or chewing objects or playing in soil contaminated with fallout of particulates consisting of or containing the chemical substance). 7 Exposed populations are Initially Identified as those near sources of the substance; modeling and monitoring provide the geographic definition of "near" by defining the levels of exposure In the environment at a given point or general location. Knowledge of a substance's physical and chemical properties, emission characteristics, and environmental transport and transformation helps to Identify the physical state of the chemical and the media (e.g., air, water) Into which It Is released and to which It will partition. The physical state and media In turn determine the potential exposure routes: Inhalation, Ingestion, and dermal contact. In order to enumerate exposed populations. Identification must be refined beyond the determination of exposure route by considering the geographic locations where the chemical Is released and the activities In the ambient environment that result In exposure. Inhalation exposures may result from proximity to: • Point sources - known locations of emissions Identifiable by geographic coordinates (e.g., Industrial discharges, disposal sites). • Area sources - sources related to chemical use or Incidental emission defined by broad geographic boundaries (e.g., urban areas as a source of automotive exhaust). • Line sources - sources of chemical emission, usually assumed to be at a constant rate, that are mobile and move along a pathway or line such as a road, rail, or river. Since breathing Is a constant activity, populations exposed via Inhalation are defined only by the sources listed above. Dermal exposure to a chemical substance may result from contact with ambient air, water, or soil. Dermal exposure to airborne contaminants Is likely to be Insignificant In comparison to Inhalation exposure. The most Important exposure pathways for the dermal route are probably swimming In surface waters and contacting soil during work or play. Only the most significant and common pathways of exposure are considered In this report. There are numerous other exposure pathways In the ambient environment that are not dealt with In this report (e.g.. Ingestion of contaminated soil by children). Identification of these pathways and the exposed populations must be addressed within Individual exposure assessments. The data bases. Information sources, and tools discussed In this report will aid In this process. 8 2.3 Me thods for the Enumeration of Exposed Populations This section discusses the data sources and recommended procedures for enumerating populations exposed to chemical substances In the ambient environment. Because populations exposed to chemical substances In the ambient environment are defined geographically and since the Census of Population Is the major geographic population data base, the first subsection (2.3.1) Is devoted to Its discussion. The methods developed for the enumeration of exposed populations are subsequently discussed according to Inhalation exposure In Subsection 2.3.2 and dermal exposure In Subsection 2.3.3. 2.3.1 Census of Population The U.S. Census, conducted once every decade, determines the size, distribution, and demographic characteristics of the population. The most recent Census was conducted In 1980 and Is divided Into two categories: (1) complete count data for the entire U.S. population (short form) and (2) more detailed population, social, and economic characteristics for 20 percent of the U.S. population (long form). The data collected In each of these categories are listed In Table 1. The data collected In the Census are organized according to geographic areas in the U.S. as Illustrated In Figure 3 and within geographic areas according to census-defined statistical areas and government units as listed In Table 2. Figure 4 Illustrates the geographic organization of the major census statistical areas (1.e., Standard Metropolitan Statistical Areas (SMSAs), urbanized areas, and urban and rural areas). The detailed breakdown of census geography Is Illustrated In Figures 5 and 6. Population data, therefore, are available within SMSAs to the level of the Block and In non-SMSAs to the level of the Enumeration District (ED). Census geography and the population data available for each geographic category are extremely Important throughout this methodology. In this section, and all sections of the methodology, census geography will be used as consistently as possible. It should be noted that many organizations report population data according to what appears to be census geographic categories (e.g., "urban" population, "rural" population). Upon further Investigation, however, sample design and data presentation may not strictly follow the census definition of geographic categories. When using population data not reported by the Bureau of the census, therefore, the Investigator should carefully review the geographic categories of data presentation for consistency with the census classifications. 9 Table 1. Population Subject Items Included in the 1980 Census 100X Items Sample items (201 sample or 1 out of 6 households) • Household relationship • • Sex • • Race • • Age • • Marital status • • Spanish/Hispanic origin • or descent • School enrollment Educational attainment State or foreign country of birth Citizenship and year of immigration Current language and English proficiency Ancestry Place of residence five years ago Activity five years ago Veteran status and period of service Presence of disability or handicap Children ever born Marital history Employment status last week Place of work Travel time to work Means of transportation to work Number of persons in carpool Year last worked Industry Occupation Type of employment Number weeks worked in 1979 Usual hours worked per week in 1979 Number weeks looking for work in 1979 Amount of indome in 1979 by source Source: Bureau of the Census 1979a. 10 Hll\iQ Q z < 11 Figure 3. Geographic Regions and Divisions of the United States Table 2. Geographic Units of the Census of Population Statistical areas Government units • Regions: Regions are large, geographi¬ cally contiguous groups of states (with the exception of the region that includes Alaska and Hawaii). There are four regions: Northeast, North Central, South, and West (see Figure 1). • Divisions: Divisions are groups of states which are subdivisions of regions. There are nine divisions: New England, Middle Atlantic, South Atlantic, East South Central, West South Central, East North Central, West North Central, Mountain, and Pacific (see Figure 1). • Standard Metropolitan Statistical Areas (SMSAs): An SMSA is an integrated economic and social unit with a recognized large population nucleus. Generally, each SMSA consists of one or more entire counties, or county equiva¬ lents, that meet standards pertaining to population and metropolitan character. In New England, towns and cities, rather than counties, are used as the basic geographic units for defining SMSAs. In Alaska, census divisions are used to define SMSAs. Criteria used to delineate the 267 SMSAs for which data were tabulated for the 1972 Economic Censuses specified that an SMSA include at least (1) one city with 50,000 inhabitants, or more or (2) a city having a population of at least 25,000 which, with the addition of the popula¬ tion of contiguous places, incorporated or unincorporated, has a population density of at least 1,000 persons per square mile. Together, they must constitute, for general economic and social purposes, a single community with • The United States • States: The 50 states are the major political units of the United States. The District of Columbia is treated as a state-equivalent. • Counties: Counties are the primary political and administrative divisions of the states. • Minor Civil Divisions (MCDs): These are the primary political and administrative subdivisions of counties; most frequently known as townships, but in some states include towns, precincts, and magisterial districts. • Census County Divisions (CCDs). In 21 states, MCDs were found to be unsuitable for presenting statistics due to area’s small population size, frequent boundary changes, etc. CCDs are defined with boundaries that seldom change and can be easily located (e.g., roads, railroads, power lines, and bridges). • Places: A concentration of population, regardless of the existence of legally prescribed units, powers, or functions. In the 1970 Census, most places are incorporated as cities, towns, villages, or boroughs. - Incorporated places: These are political units incorporated as cities, boroughs (excluding Alaska and New York), villages, and towns (excluding the New England States, New York, and Wisconsin). Most incorporated places are subdivisions of the MCD or CCD in which they are 12 Table 2. (continued) Statistical areas Government units a combined population of at least 50,000, provided that the county or counties in which the city and contiguous places are located has a total population of at least 75,000. • Central cities (of an SMSA): The largest city of an SMSA is always a central city. One or two additional cities may be added to the SMSA title and identified as central cities if: (1) the additional city or cities have a population of one-third or more of that of the largest city and a minimum population of 25,000 or (2) the additional city has at least 250,000 inhabitants. • Standard Consolidated Statistical Areas (SCSAs): Two or more contiguous SMSAs which meet certain criteria of population size, urban character, social and economic integration, and contiguity of urbanized areas. Examples are: Detroit-Ann Arbor, MI, Seattle-Tacoma, WA, San Francisco-Oakland-San Jose, CA. • Urbanized Areas (UAs): Contain a central city (or twin cities) meeting the same criteria as an SMSA, plus the surrounding closely settled incorporated and unincorporated areas which meet certain criteria of population size or density. UAs differ from SMSAs chiefly by excluding the rural portions of counties that make up the SMSAs as well as those places that are separated by rural territory from the densely populated fringe around the central city . located, for example, a village located within and legally part of a township. However, almost 4,000 incorporated places cross MCD and/or county lines, but no incorporated places cross state lines since they are chartered under the laws of a state. There were over 18,500 incorporated places in 1970. • Unincorporated places. These are densely settled population centers without legally defined corporate limits or any other corporate powers or functions. In 1970, statistics were tabulated for each unincorporated place with 5,000 inhabitants or more if located inside an urbanized area, or with 1,000 inhabitants or more if located outside an urbanized area. 13 Table 2. (continued) Statistical areas Government units • Urban and Rural Areas: Urban population comprises all persons living in urbanized areas and in places of 2,500 inhabitants or more outside urbanized areas. The population not classified as urban constitutes the rural population. This is divided into rural-farm (all rural households living on farms) and rural nonfarm (remaining rural population). • Census Designated Place (CDP): for the 1980 Census, CDPs will be used to describe densely settled population centers without legally defined limits or corporate powers. CDPs, like unincorporated places in 1970, contain a dense, city-type street pattern and ideally should have an overall population density of at least 1,000 persons per square mile. In addition, a CDP should be a community that can be identified locally by place name, having developed over the years from a small commercial area or market center, rather than encompassing a residential land subdivision, apartment development, or general urban expansion area. • Census Tracts: Generally, small, relatively permanent areas into which metropolitan and certain other areas are divided. An average tract contains about 4,000 residents. All SMSAs are completely tracted. • Enumeration Districts (EDs): Areas within census tracts, MCDs, and CCDs with an average of about 800 people or 250 housing units. EDs are generally used when block groups are not defined for an area. Together with Block Groups, the ED/BG category covers the entire U.S. 14 Table 2. (continued) Statistical areas Government units • Block Groups (BGs): This area is a combination of contiguous blocks having an average population of about 1,100. BGs are subdivisions of census tracts. • Blocks: A census block is a well-defined piece of land, bounded by streets, roads, railroad tracks, streams, or other features on the ground. Blocks do not cross census tract boundaries, but may cross other boundaries such as city limits. Blocks are the smallest areas for which census data are tabulated. Source: U.S. Bureau of the Census 1979b. 15 STANDARD METROPOLITAN STATISTICAL AREA (SMSA) = URBANIZED AREA. CONSISTS OF CENTRAL CITY AND URBAN FRINGE (MAY IN RARE CASES EXTEND OUTSIDE OF SMSA BOUNDARY). OTHER URBAN AREAS UNSHADED AREAS INSIDE OR OUTSIDE OF SMSA BOUNDARIES ARE CONSIDERED RURAL. Figure 4. Geographic Organization of the Major Census Statistical Categories 16 (SEE TABLE 2 2 FOR DEFINITIONS) | (SEE TABLE 2 2 FOR DEFINITIONS) 1 (SEE TABLE 2 2 FOR DEFINITIONS) 17 SMSA / Metropolitan Counties Nonmetropoiitan County SOURCE: BUREAU OF THE CENSUS 1980a. Figure 6. Census Geography For Metropolitan and Nonmetropolitan Counties 18 The data collected In the 1980 Census of Population are In the process of being released by the Census Bureau. The data are available both In printed documents and on computer tape. Table 3 lists the printed documents that are or will be available In the near future from the Census Bureau. The Number of Inhabitants (Series PC80-1-A) and General Population Characteristics (Series PC80-1-B) are the most useful reports for obtaining population data down to the town or township level. Both documents are available according to state, and each Includes a separate U.S. summary document. Number of Inhabitants provides only population counts (l.e., no age and sex or other demographic data). General Population Characteristics provides population counts by sex and by age and sex as well as the other demographic data listed In Table 3 to the same geographic resolution as Number of Inhabitants . Detailed counts and characteristics within Standard Metropolitan Statistical Areas (SMSAs) are available In Census Tracts (Series PHC80-2) and Block Statistics (PHC80-1). Census Tracts will be Issued with accompanying maps (for tract Identification) and will contain detailed characteristics of the population (e.g., age, sex, race, education). Census Tracts Is available by the photocopied page, and by mld-1983 It will be available on microfiche by SMSA (which Is less expensive) and on computer tape. If further resolution or detail Is required, Block Statistics may be consulted. This has been Issued In microfiche only with accompanying maps both In print and on microfiche. Block Statistics provides population counts only; further Information on population characteristics Is not available on such a detailed level. Detailed demographic Information collected In the 20 percent sample Census (long form) Is available In the series General Social and Economic Characteristics (PC80-1C) and Detailed Population Characteristics (PC80-1-D) . General Social and Economic Characteristics provides demographic data to the town or township level of detail according to states. A U.S. summary report Is also Included In the series. Detailed Population Characteristics Is available by state, U.S. summary, and SMSA. These two reports provide considerable Information on the population characteristics previously listed In Table 1. All of the Information sources previously discussed contain results from the 1980 Census; they are available In most reference libraries. Specific population data that have been collected In 1980 and that have not yet been released may be obtained by calling the Population Division of the Bureau of the Census (202-763-5002 or 5020). 19 Table 3. Information on 1980 Census Reports: Their Geographical Breakdown, Characteristics, and Expected Dates of Release Series Name Geographical Expected dates breakdown Characteristics of release PC80-1-A Number of inhabitants United States Population (complete (U.S. Summary and by Regions counts count data - 100%) state) Divisions States SCSAs, SMSAs Urbanized areas Incorporated places Counties County subdivisions PC80-1-B General Population United States Population (complete Characteristics Regions counts by count data (U.S. Sunmary and by Divisions - 100%) state) States SCSAs, SMSAs Urbanized areas Places & towns/town- ships of 1,000 or more Counties Rural portion of counties Available Available United States States SCSAs, SMSAs Urbanized areas Places & towns/ townships of 10,000 to 50,000 Places & towns/ townships of 2,500 to 10,000 Counties Age and sex, household type & relationship, type of family, and marital status 20 Table 3. (continued) Series Name Geographical Expected dates breakdown Characteristics of release PC80-1-C General Social and United States Population (sample Economic Characteristics Regions counts estimate (U.S. Summary and by Divisions data - 201) state) States SCSAs, SMSAs Urbanized areas Place 4 towns/ townships of 50,000 or more Places 4 towns/ townships of 2,500 to 10,000 counties Mid to late 1983 United States States Counties Population counts for non-rural and rural farms. United States States Age & sex, fertility, household relation¬ ship, education, family composition, nativity and place of birth, residence in 1975, journey to work, disability status, veteran status, labor force status, class of worker, industry and occupation, income and poverty status. States SMSAs d Urbanized areas d Places & towns/ townships of 50,000 or more d Central cities d Places & towns/ townships of 10,000 to 50,000 d Counties Age & sex, fertility, household relation¬ ship, education, family composition, marital status, nativity & place of birth, resi¬ dence in 1975, journey to work, disability status, type of group quarters, veteran status, labor force status, class of worker, industry & occupation, income 4 poverty status. 21 Table 3. (continued) Series Name Geographical breakdown Characteristics Expected dates of release PC80-1-D Detailed Population United States Cross-tabulations Mid to late (sample Characteristics States of social & 1983 estimate (U.S. Summary and by SMSAs of 250,000 economic charac- data - 20%) state) or more teristics by age, sex, etc. States Social and SMSAs of 250,000 economic or more e characteristics PHC80-2 Census Tracts^ SMSAs Population counts Late (sample (U.S. Summary and by Central cities (number of people 1983 estimate SMSA) Counties in each tract by (currently data - 20%) Places of 10,000 SMSA & other available on a or more tracted areas) photocopy Census tracts basis) SMSA C Age and sex, fertility, Counties 0 household relationship, Places of 10,000 education, family com- or more 0 position, marital status, Census tracts 0 nativity, language usage and ability to speak English, residence in 1975, journey to work, disability status, labor force status, industry and occupation, income and poverty status. Structural equipment, financial and household characteristics of housing units. 22 Table 3. (continued) Series Name Geographical breakdown Characteristics Expected dates of release PH80-1 Block Statistics 3 (complete (microfiche only; maps count data printed - U.S. Sunnary - 1001) and by SMSA) Counties County Subdivisions States SMSAs Population counts Available Places Tracts Blocks Note: Data for towns/townships are shown for 11 states only: Maine, New Hampshire, Vermont, Massachusetts, Rhode Island, Connecticut, New York, New Jersey, Pennsylvania, Michigan, and Wisconsin. a Report contains 1001 data; race and Spanish origin data, where presented, are provisional. b Report contains both 1001 and sample data. c Data are shown only for those groups having 400 or more persons in the specific geographic area. d Data for American Indian, Eskimo, and Aleut and Asian and Pacific Islander are shown for the specific geographic area having 1,000 or more persons of the population group. e 0ata are shown only for those groups having 25,000 or more persons in the specific geographic area. Source: Bureau of the Census, Customer Services Branch; Washington, D.C. (202-763-4100). 23 Another source of census Information Is the computerized Summary Tape Files (STFs). There are five basic files. STFs 1 and 2 are derived from the complete-count part of the Census and reflect respondents' answers to questions on the short form. STFs 3, 4, and 5 contain estimates derived from the sample part of the Census (20 percent sample) and cover the full range of topics represented on the long form. Although the source of Information Is the same, the STFs are designed to provide much greater geographic and subject detail (e.g., age, sex, education, marital status) than Is feasible or desirable In printed reports. The STFs are only on magnetic computer tape, with the exception of STF 1A, which Is also available on microfiche. Each of the five STFs Is divided Into Parts A, B, and C. Table 4 Illustrates the relationships between the 1980 printed reports and STFs 1 through 5. Table 5 Illustrates the geography of each file and Its three parts. Table 6 lists the geographical resolution that will appear on the 1980 STFs, as well as the tentative schedule of release for these files. Several other types of computer tape files are also available for population data (Bureau of the Census 1982a). Of particular Importance Is the Master Area Reference File (MARF). MARF contains numeric codes and names of all geographic areas used In the 1980 Census. The file also contains population and housing data for each area In the file. Donnelly Marketing, Incorporated, a subsidiary of Control Data Corporation, has acquired the file and added geographic coordinates (latitude-longitude) to all ED/BGs In MARF. This permits computerized mapping of the population data. This file along with the proprietary geographic coordinate data was recently purchased by EPA-OTS and entered Into Its Graphical Exposure Modeling System (GEMS). EPA-OTS can now access, aggregate, and manipulate 1980 population data as well as display the geographic distribution of the data In conjunction with ambient concentration data predicted by fate models. Details on MARF and Its application as well as GEMS and the computerized concentration prediction models are discussed In the next subsection. The STFs and other computer tape files such as MARF are considerably more expensive than printed reports. One STF reel (approximately one state) costs $140 compared to $5 for comparable printed reports. Computer tape files, however, Increase the versatility of the population data; users can manipulate, aggregate, or otherwise extensively process census data. Another source of population data that can be very useful, partlculary In the study of specific geographic areas, Is census maps. Census outline maps allow the Investigator to determine the geographic distribution of populations In specific areas of Interest. Maps that are available for use with 1980 census data vary according to the resolution needed (refer to Figure 5) and conform to the geographic units already described In Table 2. The census outline maps available for use with 1980 census data are summarized In Table 7. 24 Table 4 . Relationship of 1980 Summary Tape Files, Printed Reports, and Microfiche 05 JZ o o i- u Cl 05 L. “O 05 L. CL O 05 O 00 ro -o a> £ oo U 00 4 -> 03 4 -> OO J* U o ao r— I -f 1 o 8 T UL -i- Q- > ro o 8 8 £ £ < I g O oo -*-> u 03 U 3 00 C CD O CNJ I o 8 CO I CO I *— eg CO U. LL u. ►— 5— 5— uo oo oo g o o 03 u oo 3 c 05 O eg I o 8 00 oo O u • r* oo • r* 4 -» oo -L> oo oo 4 -> c oo 4 -> • r- oo • 1 — 03 c • r- • r* "D u u c 4 -> O u C C 05 oo • r— x • r- • r* 05 X O) fQ 4 -> -*-» -Q 4 -> 00 C 7 J V* 4 -> c oo u L. oo -*-> 03 03 U C O (J 4 -> • r* u r— 03 O • f— c jC r— • r- • r— 03 c oo •r* 03 U Q. -*-> C 3 4 -» 00 4 -> U fl) 3 -*-» 05 03 £ HH 00 03 p 5 10 U jC a: 4 -> c O • r- jC c • r— O o OO u g- Cl l_ X u O i~ u uo T 3 05 o 05 05 05 T? 05 u Q 5 >» > — 4 -> r— -*-> >> > 05 4 -> r—. • f“■ U L. 3 u r 0 U 03 U u s U 03 E c rrj 05 u 03 i_ 03 • r- 03 u o 05 | 05 S- 05 u H 03 U 05 c > i_ C 03 C 03 {. 4 ~> 03 C o "O 3 O 05 JC 05 -C o 3 JZ 05 u < oo < 4 - Z C 3 O C 3 o OO g- o C 3 UJ ao o I 1 o 1 O 1 O PHC 80 1 o 1 o 8 Q_ 8 CL 8 X 8 X 8 05 I I c O a> c to 3 ^25 3 -r- & 0 - T 3 05 r0 -*-> 2 00 c -*-> rrj to u •*- u 05—0 4-> Q -*-> U Q. L5 * O 03 £- i_ t_ fT3 -4-> r0 .C 05 -C L3 X O O I — <\J I I o o 8 8 Q- X 25 Source: Bureau of the Census 1980 b. Table 5. Summary Tape File Geography (1980) 1/3 * CL) . . . to • r— to to 1/3 . t/3 03 -+-> 03 03 03 to 03 4-> c * p— 4-> . 4-> 03 . . • r* . 03 03 D to 03 03 4-> to 03 03 to to t/3 to x-s 4-> O 03 c 4-> c 03 4-> ft- 4-> 03 C 03 03 u. to u 4-> o to 3 4-> to 03 u +J D -*-> 03 3— 03 • r* o ro 03 O 03 r— to r“ . 4-> to p— u 4-> p— *o ftl 4-» U 03 p“ c 10 to p— to C p— 03 4-> • t/3 to C ft- -C o 03 . 03 ISI to to . 03 u c . ft. c c . c . p- , r— c . • r— 4i • r— 4-> to CT> • r— o to ■o C *o Z) p— o to ■o t/3 o 03 03 < C • ^ < C OJ • P’ < c o r“ to to 8 to 4-> to i—« i/» JC r— . c to o p— ft. c D cj c 03 CJ c ft- to • p. 03 u o O O n to O to . o 13 C c to . 03 U- U- <0 • t/3 D • i/» O o to o • • cj ft. . to ft. rt . to ft. . • r» c ft . to o c 03 1 t/3 03 to • 03 to 03 to to O) O ft to • o to 03 a. o < z> Cl 5, < z> a. 03 to 03 t/3 ft < 3 ■O r— 4-> Q to to 03 ft. ft. to c 03 03 03 o o £ • O p— z . Q 4-> ft. 03 z . 03 ft. Li- r“ 4-> o • to to 8 03 to to 0 c O) . Cl 03 to t/3 3 • »“ to o o c ft. c 0 J C 1/3 ft- c . 4-» V4- • r— • o D . o . O 8 C 0 D . o 03 3 r— o to • p- © ft- to • r* o CJ o Q ft- to 4- p— r— r—- *- (V a> eg C7) 0 03 cn . 03 03 03 03 03 . 03 03 • — • t/3 . . 03 03 • < 03 C ft- > ft- i. t. to ft. ft- to ft. to to • r~ o to ft. u t/3 o L»- 03 o 03 03 03 c 03 03 < > 03 C . • r* O > . • > CJ . o > O to • r— U . o t^ 4-> o c+- TD t/3 to O 03 T> t/3 • r- o 03 o T3 ft. OJ T3 to c 03 o 03 c 4-> p— 03 C 4-> to 03 03 c 4-> ft. • r— C V4- N o L3 M- CL M o 03 <4- a. . > Q. N o 03 03 —* O to • r— • ^ • r— o • r— > o . to O •r— > Ql 03 03 c to ft- 03 c to J- 03 to 03 03 C t/3 ft. to U 03 • p- 4-> i/o O) 03 •p> 03 to 03 < 4-> t/3 03 03 • r“ 03 03 O 03 .a > to Q ft- -Q > oo Q ft- to 03 o ft- > t/3 03 03 £ p— u • r» •p* CJ 03 ft. •p. 03 £ z; 4J u 03 ft. 03 ft. CL =3 T3 *o z 3 *u ft- to to z 3 ■O ft. J= •p- t/3 -*-> I to 03 03 *— 03 t- ro 0) Cl Q. 03 u •p“ =3 ft. C ~o 03 . 03 03 03 4-» & 03 03 03 N t/3 p— T3 4-> t- c » • p> < O 03 O 3 to CL “O *5 r— to C to •p. o O 03 03 C 03 03 03 CJ to 03 r— . U u p— M HH tJ U r— jO to a. CO 3 to JD to • 03 03 •p* C 03 03 ft. c tn H >» 03 03 . t/3 l- C . • ft. 3 . 03 • M 03 JD 03 03 t/3 03 Q. 13 03 to t/3 u Cl 3 to •p to u. p— | p— to ft- 03 ft. X) < c ft- •» < "O c 3— 4-» • r" 03 03 o 03 U 03 . ft- to o . C to c o to • r— U. 4-> ft. LU 03 4-3 to . CJ • p— to t/3 o Z HH «r— 03 T? r— to Q t/3 to 4-» 03 o to • r— to 4-» ft- • r~ 4-» 03 CL O 0) . 03 T3 a 03 4-» . 1 0 03 ■D to to ft- . O • r“ C . > O CJ • r— 03 . to > 1 03 . to \ 4-» o to ft- U \ 4-> to 03 ft. 4-3 m u t/3 < t/3 c < 03 t/3 c 3 4-> 03 03 o Q to Q Z3 4-> to t/3 CL O 3 o 03 03 t/3 ft. 3 O Z O o 03 z 03 a O ft ft. 4-> 0) 3 o CO c Z I/O Z o to ft- *rsi z tJ Ol 03 to ft- •o CJ T3 u . o 03 T3 • o to o -o c 03 . t/3 O . o • o U to 03 TD J3 CJ CO to c • p— 03 Q 4-i 03 N CJ 4-» o* < 03 4-> .Q CJ 03 4-> to \ U r— cn 03 03 E CJ 4-» u 4-> t/3 • p— z JD 03 ft. 5 \ to 03 u o (- ft- in 4-> oj c t/3 ft. • P“ CJ 4-> 03 4-> 03 Q . 4-3 ft- z . t/3 > * 03 4-> x-s 3 j* CJ to • 4-» t/3 • p— o t/3 >» t0 Q) c CJ Z 03 . t/3 to . 03 T3 03 < 1 to 03 O to < • r— t^ •p— t/3 • p- 4-> >> 03 \ p— . 4-» 03 t/3 “D 4-> 4-» 03 4-> O 03 -Q 03 to JD to c U z tJ c 03 CJ c c r— | r— CL 4-> =3 03 tn C 03 o C OJ o • r— 03 03 3 . u o o ft- o o o to u_ 4-» t- o t/3 03 u *Ql . 4-> u • p "flu CJ OJ 03 ft. 4-J t- to 4-> t/3 x: 4-> cn U 4-> . . 03 03 . . t/3 • . “O t/3 • p. N to to ft. to to 03 to to 03 4-> ft- 03 4-> 4-> fli CL 03 ft- 0) 4-J 4-> ►H CJ 4-> 03 U U c tJ O) 4-> U u O t^ 03 03 03 =3 5 o 03 C 03 03 (V r— • p— ft- r— ft- o c t- p— o 4-> ft. ft- 00 ■O 03 CL 3— u LU 03 Q. CJ t/3 3— 4-> g O s o C\J Li- 3— in 0) 00 U_ to • C/3 03 to 03 < 4-> 4-> to cn rQ • 03 Z 4-> to •p- in to c o 4-> o c * . :d o O t/3 a> 03 o CJ 8 03 03 ft. 03 t- 4-> O T3 cT «p* . CO C in U to * C ft. r— o • • to 03 OJ • P“ 03 0) > ft- 1/3 tJ (J o 4-> • p* ft- OJ c > o 14- 03 • p- o CL o U T D in 03 > di -Q § OsJ 00 cn to D to c 0) o * 4-> ■s 00 u. h- to 03 to JO D CL ft- O JO 03 03 > 03 O C 00 I oo 26 reimbursable, special tabulation basis. Table 6. Smallest Type of Area on 1980 Census Summary Tape Files File A (state-by-state) File B (state-by-state) File C (national) Tentative dates of release Complete Count: STF 1 BG/ED Blocks/ED County, place of 10,000 or more Available STF 2 Tract Place of 1,000 or more, MCD/CCD County, place of 10,000 or more Available Sample: STF 3 BG/ED County, place of 10,000 or more STF 3A is available STF 3B has been cancelled STF 3C expected in mid 1983 STF 4 Tract Place of 2,500 or more, MCD/CCD County, place of 10,000 or more Mid to late 1983 STF 5 SMSA, County of 50,000 or more, place of 50,000 or more Late 1983 Source: Customer Services Division, Bureau of the Census (202-763-4100). 27 CO CL £ 0) c u -O 03 ro > < 03 Cl 0) lO i co -*-> o- Si o .c co 03 N a. • r- 3 in E CO *4- 4-> O 03 (V U XZ 03 to 1 03 *03 CJ CO CL no co (0 03 C7) CD C L- ro “O L- T3 O CD U N CJ 03 C CO _D CD L •*” 13 U 03 ^4- > O O o o u CD TJ > C O 03 U CO in < LU LO »-« X QC in LU CO v»_ O Q- < co X 03 oj 1 fe »— »-H TJ —i CD 2 .2 O c a: 03 •— JD LU L z: d co CD • r* L. 03 TJ C — D CD O > jQ CD uo J J* to u c o CD *— CJ JO r- CD *— XI 03 4-> C o u. §1 3 XI CO XI CJ 03 CD O in CM CO 03 U 03 C 03 CJ >> c co 03 O >o 4-> -*-> §i U l_ L— 03 O. co 03 • r- LO u fQ CO > 03 E CM II 03 U 03 C 03 CJ Si J= CO CJ 03 03 in OsJ CO o C7) c *5 03 L CJ O 03 CJ •— CJ CL 03 *4- co O 03 •*- 03 l_ N 03 •— > CO CO o. >o 03 <— U r— 03 03 *— C Q. 0 J c u 03 03 CJ CL -3 CM ■M Si JZ to u 03 03 Q. D -L X c/> Cl >> 03 «— 4-> 03 4-> CO * 03 C U 03 03 CJ Q. E OsJ 03 L 03 C 03 CJ >> c * > co 03 CJ • r» L- Q_ O X CL ^r CM CM OsJ 03 *- 03 C 03 CJ C/3 CL >> — < •— in 03 x c in 03 C L 03 03 CJ CL 03 o 0 o Nl u r~ • r— >> 14- i/» co 4-> ii 03 • r— 03 O X O) “ • r— 4-> 03 c f— E 03 CJ) Q. U o c E 4-> • r— o . «. II TJ CJ co aj L. 03 s o TJ 03 • r* r— CJ C C E CJ 03 03 >» 03 OsJ < TJ r— co in 03 03 03 X -*-> co U • r" in U II 03 03 l_ 03 C 03 14- L. r • r- 03 > O 4-> E C3 03 >> TJ 4-> 03 in -*-> 4-» c CJ SL >> LU C c 03 03 TJ o 4-> jQ 3—1 o 3 s_ 03 o 3— (J O CL -*-> 4-> o co to Z 1 u • r- 03 •k 03 5 co in jC C m O 03 4-» CL O CO O o OsJ XI L- CJ o c 4-> c x: CL co 03 14- 03 CO L v>- 1 u. p— L 6 1 o o in TJ o co 03 g 03 4-> in CJ c CL 03 03 > a. c co o £ N CL • r“ • r— i—i . p— « IP- 03 • r- • p— L. 13 in E i/) u 4-> C 03 O' HH u 03 TJ 03 03 55 03 TJ 03 > co (— • ^ LU C p— -O in C »—1 CJ L Z 03 CL 3 £ s_ O) LU 13 TJ o c c 03 >—i CL o c 3— o C CO o • r- TJ _J (/> L O • p— < JO ZD • f“ C 3— 03 O CL O *4- TJ 3— in 4-> TJ 3 L- LU o 03 in to CO 3 C O o L 03 OsJ .C c 03 >- P 03 JO 03 co L 3—3 4-> 10 o • r- • p“ 3— r 3— TJ 4-> Q z c LU 03 4-> z o CO >> o C • r - g < 0) >> 3— ^-> c L- CL g 3 E GO 4-> 03 3—3 C o o C • r— O L. CL X u z O o o E CJ 3— -Q O 3 03 O) ZD u CJ CJ CJ CL X CM CM CO a. 2 3 03 C J- 03 03 CJ CL Si -C to CJ 03 03 O Kf o 00 03 03 (/» CL o o o O 4J c i B L CL 00 00 OsJ • o in OsJ • 3 CJ >> • C Q 03 « L c o o 4-> «k O) OsJ c o x: o CO OsJ • CJ CO • o a CO c m 03 c CJ o 4-J 03 C7) .c C 4-> «p— -C V- 10 o o 03 «k 03 03 L- CJ O GO V»- ^4— • o C o O) c co • p— •p— 4-> > c O L CL CO 03 4-> C3 c • p— > H L 2 03 C_ in 03 > CO s- s 03 CO • 3 in 1 0 3 -*-» 03 • Q 10 4-> » c x: m a H c 5 CJ L- CO s CO 14- 03 o C3 4-> > C J— 03 03 TJ in C 03 (. 4J C P • p“ Q L 03 co Q. 3 Z3 o in L L <4- V4- 03 03 r— p— 3 3 03 03 r— •r— •p— 03 03 > > < < — CM 28 The metropolitan, tract outline, and county subdivision maps are the key census maps for correlating 1980 census data to sites In urban or rural areas. These map series are Issued separately or with specific census publications. Examples of census outline maps for metropolitan and non-metropolitan areas are presented In Figure 7. Additionally, the Census Bureau Issues several series of statistical maps and graphic summaries that display census data In map form. The map series In this category Include the GE-50, GE-70, and GE-80 (Urban Atlas) series. These maps, of varying sizes and scales, utilize color schemes to Illustrate population and other social and economic census data. All printed census matter Is available for purchase through the Government Printing Office (GPO); all series Issued on microfiche, maps, computer tapes, and technical documentation are available directly from the Customer Services Branch at the Bureau of the Census, Department of Commerce, Washington, D.C. These series can be ordered by calling (202) 763-4100 (Customer Services Branch). The Bureau of the Census will also prepare, on a cost reimbursable basis, special tabulations of data from the 1980 Census based on customer specifications. Such tabulations can cover any specific geographic or subject matter area as long as the requests do not violate confidentiality restrictions. These types of reports are expensive and may require considerable time to produce. Standard reports, tapes, and microfiche should be used whenever possible. A complete description of the documents and services available from the Bureau of the Census Is not within the scope of this volume. This subsection has attempted to briefly describe the documents and data files that would be of most use towards enumerating populations exposed to chemical substances In the ambient environment. For more detailed descriptions of the documents and data files previously discussed, or for Information on other services available from the Bureau of the Census, the Investigator should contact: Data User Services Division Bureau of the Census Washington, DC 20233 (202) 763-4100 A detailed list of contacts for census data Information Is provided In Figure 8. The population data discussed In this report reflect Information collected In 1980, and, therefore, are not up-to-date. Population data for large statistical reporting areas or categories (e.g., regions, divisions, states, urban areas, SMSAs) will not have changed 29 C/3 ZD C/3 LU C_3 Hi 81 oc < U cn (X Z o s 5 UJ V C\l o u HI U O CO 30 Figure 7. Examples of Census Maps Source: Bureau of the Census (1980c and 1981a). TELEPHONE CONTACTS FOR DATA USERS BUREAU OF THE CENSUS U.S. Department of Commerce • Bureau of the Census • Washington, D.C. 20233 November 1981 No. 20 Director. Deputy Director Associate Associate Associate Associate Associate Associate Director Director Director D1rector Director Director for Administration. for Demographic Fields. for Economic Fields. for Field Operations. for Information Technology. for Statistical Standards and Methodology... Assistant Assistant Assistant Assistant Assistant Assistant Assistant Director Director Director Director Director Director Director for Administration. for Computer Services. for Demographic Censuses. for Economic and Agriculture Censuses for International Programs. for Processing. for Statistical Research. Congressional Liaison. Data User Services Division Public Information Office.. Bruce Chapman Daniel B. Levine James D. Lincoln Meyer Zitter, Actg. Shirley Kallek C. Louis Kincannon, W. Bruce Ramsay Barbara A. Bailar 0. Bryant Benton Howard Hamilton Peter A. Bounpane Michael G. Farrell Meyer Zitter C. Louis Kincannon Roger H. Moore Pennie Harvison Staff Staff (301)763-5190 763-5192 763-7980 763-5167 763-5274 Actg. 763-7247 763-5180 763-2562 763-2350 763-2360 763-7670 763-7356 763-5167 763-7247 763-3807 763-5360 899-7600 763-4040 DEMOGRAPHIC FIELDS Center for Demographic Studies. Decennial Census Division. Demographic Surveys Division. Foreign Demographic Analysis Division.... Housing Division. International Demographic Data Center.... International Statistical Programs Center Population Division. Statistical Methods Division. CDS James R. Wetzel, Chief 763-7720 DCD Peter Bounpane, Actg. Chief 763-7670 DSD Thomas C. Walsh, Chief 763-2777 FDA Samuel Baum, Actg . Chief 763-4010 HOUS Arthur F. Young, Chief (301 )763-2863 IDDC Samuel Baum, Chief 763-2870 ISPC Robert 0. Bartram i, Chief 763-2832 POP Roger A. Herriot, Chief 763-7646 SMD Charles D. Jones, Chief 763-2672 Population and Housing Subjects Age and Sex: States (age only). United States. A liens. Annexation Population Counts. Apportionment. Births and Birth Expectations: Fertility Statistics. Census Tracts: Boundary Information. Census Data. Citizenship: Foreign Born Persons, Country of Birth; Foreign Stock Persons. Commuting: Means of Transportation; Place of Work. Congressional Districts: Census Data. Address Locations. Population Estimates. Consumer Expenditure Survey. Consumer Purchases and Ownership of Durables. Crime Surveys: Data Analysis and Publication. Victimization, General Information. Current Population Survey. (See detailed listing on page 2 for Population Estimates) Decennial Census: Content and Tabulations. Count Complaints. Genera 1. Minority Statistics Program. POP Marianne Roberts 763-5072 POP Louisa Miller 763-5184 POP Jennifer Marks 763-5184 POP Joel Miller 763-7955 POP Robert Speaker 763-7955 POP Martin O'Connell 763-5303 GEOG Alice Winterfeld 763-7291 POP Johanna Barten 763-5002/5020 POP Elmore Seraile 763-7571 POP Philip Fulton 763-3850 POP Johanna Barten 763-5002/5020 GEOG Ernie Swapshur 763-5437 POP Donald Starsinic 763-5072 DSD Gail Hoff 763-2764 POP Jack McNeil 763-5032 CDS Adolfo Paez 763-1765 DSD Robert Tlnari 763-1735 DSD Gregory Russell 763-2773 DCD Earl Knapp 763-1840 DCD Ann Liddle 763-3814 DCD Rachel F. Brown 763-2748 DCD Alfred Hawkins 763-5987 ■ Figure 3 31 Population and Housing Subjects-Con. Decennial Census—con. Special Tabulations: Population Data. Housing Data. Disability. Education; School Enrollment and Social Stratification. Employment; Unemployment; Labor Force. Farm Population. Health Surveys. Households and Families: Marriage and Divorce. Projections. Size; Number; Social Characteristics. Housing: Annual Housing Survey. Components of Inventory Change Survey. Contract Block Program. Housing Information, Decennial Census. Housing Vacancy Data. Market Absorption. Residential Finance. (See also Economic Subjects—Construction Statistics) Income Statistics: Current Surveys. Decennial Statistics. Household... Revenue Sharing... Incorporated/Unincorporated Places. Industry and Occupation Statistics (See also Economic Fields). Institutional Population. International Population. Language, Current; Mother Tongue. Longitudinal Surveys. Marital Status; Living Arrangements. Metropolitan Areas (see SMSA's) Migration. Neighborhood Statistics. Outlying Areas (Puerto Rico, etc.). Population: General Information; Published Data from Censuses, Surveys, Estimates, and Projections. Population Estimates Methodology: Congressional Districts; SMSA's. Counties; Federal-State Cooperative Program for Local Population Estimates. Estimates Research. Local Areas; Revenue Sharing. States. United States (National). Population Projections Methodology: National. State. Poverty Statistics . Current Surveys. Decennial Census/Poverty Areas. Prisoner Surveys: National Prisoner Statistics. Data Analysis and Publication. Race and Ethnic Statistics:... American Indian Population... Asian Americans. Black Population. Ethnic Populations. Race. Spanish Population. Religion. Revenue Sharing (See Income Statistics; Population: General Information; Population Estimates Methodology; Economic Fields—Governments) POP Paula Schneider 763-7962 HOUS Bill Downs 763-2873 POP Jack McNeil 763-5032 POP Paul Siegel 763-5050 POP T. Palumbo/V. Valdisera 763-2825 POP Diana DeAre 763-7955 DSD Robert Mangold 763-5508 POP James Weed 763-7950 POP Robert Grymes 763-7950 POP Steve Rawlings 763-7950 HOUS Edward Montfort 763-2881 HOUS Elmo Beach 763-1096 HOUS Richard Knapp 763-2873 HOUS Bill Downs 763-2873 HOUS Stanley Rolark 763-2880 HOUS Charles Clark 763-2866 HOUS Peter Fronczek 763-2866 POP M. Henson/E. Welniak 763-5060 POP G. Patterson/R. Sanders 763-5060 POP Robert Cleveland 763-5060 POP Dan Burkhead 763-5060 POP Joel Miller 763-7955 POP John Priebe/Paula Vines 763-5144 POP Arlene Saluter 763-7950 POP Samuel Baum 763-2870 POP Paul Siegel 763-5050 DSD George Gray 763-2764 POP Arlene Saluter 763-7950 POP Kristin Hansen 763-3850 DCD Joanne Eitzen 763-1818 POP Jennifer Marks 763-5184 POP Johanna Barten 763 -5020(TDY)/763-5002 POP Donald Starsinic 763-5072 POP Fred Cavanaugh 763-7722 POP Richard Irwin 763-7883 POP Fred Cavanaugh 763-7722 POP Marianne Roberts 763-5072 POP Louisa Miller 763-5184 POP Gregory Spencer 763-5021 POP Signe Wetrogan 763-5021 POP Arno Winard 763-5790 POP Carol Fendler 763-5790 POP Thomas Gelinne 763-5790 DSD Chester A. Bowie 763-2380 CDS John Wallerstedt 763-7968 POP Nampeo McKenney 763-7890 POP K. Crook/E. Paisano 763-5910/-7572 POP P. Berman/P. Johnson 763-2607 POP D. Johnson/T. King 763-7572 POP Elmore Seraile 763-7571 POP Patricia Berman 763-2607 POP Edward Fernandez 763-5219 POP Elmore Seraile 763-7571 Sampling Methods. Social Indicators. Social Stratification. Special Population Censuses. Special Surveys. SMSA’s: Census and Estimates Data; Current Definitions New Criteria. Travel Surveys. Urban/Rural Residence. Veteran Status. Voting and Registration. Voting Rights. SMD Charles Jones 763-2672 CDS John Deshaies 763-2490 POP Paul Siegel 763-5050 DCD George Hurn 763-5806 DSD Linda R. Murphy 763-2061 POP Johanna Barten 763-5002/5020 POP Richard Forstall 763-5591 DSD Ron Dopkowski 763-1798 POP Diana DeAre 763-7955 POP Mark Littman 753-7962 POP Jerry Jennings 763-5179 POP Gilbert Felton 763-5313 Figure 8 (continued) 32 ECONOMIC FIELDS Agriculture Division. Business Division. Construction Statistics Division Economic Census Staff. Economic Surveys Division. Foreign Trade Division. Governments Division. Industry Division. AGR Arnold Bollenbacher, Chief (301 )763-5230 BUS Vacant 763-7564 CSD Leonora M. Gross, Chief 763-7163 ECS Michae1 G. Farrell, Chief 763-7356 ESD W. Joel Richardson, Chief 763-7735 FTD Emanue1 A. Lipscomb, Chief 763-5342 GOVS John Coleman, Chief 763-7366 IND Roger H . Bugenhagen, Chief 763-5850 Economic Subjects Agriculture: Crop Statistics. Farm Economics.. General Information. Livestock Statistics. Puerto Rico, Guam, etc. Construction Statistics: Census/Industries Surveys. Special Trades; Contractors; General Contractor Built. Construction Authorized by Building Permits (C40 Series) and Residential Demolitions (C45 Series). Current Programs. Expenditures on Residential Additions, Alterations, Maintenance and Repairs, and Replacements (CSO Series). New Residential Construction: Housing Starts (C20 Series). Housing Completions (C22 Series). In Selected SMSA's (C21 Series). Sales of New One-Family Homes (C25 Series). Price Index for New One Family Homes (C27 Series).. Characteristics of New Housing (C25 Annual Report). Value of New Construction Put in Place (C30 Series). County Business Patterns. Employment/Unemployment Statistics. Energy Related Statistics. Enterprise Statistics. Foreign T rade Information. Governments: Criminal Justice Statistics. Eastern States Government Sector. Employment. Finance. Governmental Organization and Special Projects. Revenue Sharing (See also Demographic Fields). Taxation. Western States Government Sector. Industry and Commodities Classification. Manufactures: Census/Annual Survey of Manufactures. Durables. Nondurables. Suhject Reports (Concentration, Production Index, Water, etc.). Current Programs. Durables. Environmental Surveys. Fuels/Electric Energy Consumed by Manufactures. Nondurahles. Origin of Exports. Shipments, Inventories, and Orders. Mineral Industries. Minority Businesses. Puerto Rico: Censuses of Retail Trade, Wholesale Trade, and Selected Service Industries. Retail Trade: Annual Retail Trade Report; Advance Monthly Retail Sales; Monthly Retail Inventories Survey.... Census. Monthly Retail Trade Report: Accounts Receivable; and Monthly Department Store Sales. Service Industries: Census. Current Selected Services Reports. Transportation: Commodity Transportation Survey; Truck Inventory and Use; Domestic Movement of Foreign T rade Data. Wholesale Trade: Census. Current Wholesale Sales and Inventories; Green Coffee Survey; Canned Food Survey. AGR Donald Jahnke 763-1939 AGR John Blackledge 763-5819 AGR Arnold Bollenbacher 763-5170 AGR Thomas Monroe 763-1081 AGR Kenneth Norell 763-5914 CSD Alan Blum 763-5435 CSD Andrew Visnansky 763-7547 CSD David Fondelier 763-7244 CSD William Mittendorf 763-7165 CSD George Roff 763-5717 CSD Barry Rappaport 763-7842 CSD Juliana Van Berkum 763-7843 CSD Diana Farrelly 763-7842 CSD Steve Berman 763-5731 CSD Dorothy Walton 763-7314 CSD Dale Jacobson 763-5732 CSD Allan Meyer 763-5717 ESD Stanley Hyman 763-7642 POP T. Palumbo/V. Valdisera 763-2825 DIRS Elmer S. Biles 763-7184 ESD John Dodds. 763-7086 FTD Juanita Noone 763-5140 GOVS Diana Cull 763-2842 GOVS G. Beaven/G.Speight 763-5017/-2890 GOVS Alan Stevens 763-5086 GOVS Vancil Kane 763-5847 GOVS Muriel Miller 763-5308 GOVS John Coleman 763-5272 GOVS John Behrens 763-2844 GOVS Ulvey Harris 763-5344 ESD Walter Neece 763-1935 IND B. J. Fitzpatrick 763-1503 IND Dale Gordon 763-7304 IND Michael Zampogna 763-2510 IND John Govoni 763-7666 IND John Wikoff 763-7800 IND Malcolm Burnhardt 763-2518 IND Wayne McCaughey 763-5616 IND John -McNamee 763-5938 IND Elinor Champion 763-5911 IND John Govoni 763-7666 IND Ruth Runyan 763-2502 IND John McNamee 763-5938 ESD Jerry McDonald 763-5182 BUS Alvin Barten 763-5282 BUS Irving True 763-7660 BUS Dennis Pike 763-7038 BUS Irving True 763-7660 BUS Sid Marcus 763-7039 BUS Edward Gutbrod 763-7026 ESD Robert Torene 763-5430 BUS John Trimble 763-5281 BUS Ronald Piencykoski 763-7007 Figure 8 (continued) 33 GEOGRAPHY AND STATISTICAL RESEARCH Geography Division. Statistical Research Division Boundaries and Annexations. Census Geography 1970/1980; Geographic Concepts Computer Graphics and Computer Mapping. Congressional District Component Areas, Atlas.. Earth Resources Satellite Technology: International. United States. GBF/DIME System. Area Measurement and Centers of Population. Geographic Statistical Areas. Census Maps. Revenue Sharing Geography. Survey Methodology Information System. GEO Stanley Matchett, Chief (301)763-5636 SRD Roger H. Moore, Chief 763-3807 GEO Brian Scott 763-5437 GEO Staff 763-5720 GEO Frederick Broome 763-7442 GEO Kevin Shaw 763-5437 GEO Robert Durland 763-2034 GEO James Davis 763-5808 GEO Staff 763-7315 GEO Roy Borgstede 763-7856 GEO Staff 763-2364 GEO Staff 763-7818 GEO Bob Bakondi 763-5437 SRD Patricia Fuellhart 763-7600 USER SERVICES Administrative Services Division Data User Services Division. Field Division. Age Search - Access to Personal Census Records Bureau of the Census Catalog.. Census Procedures, History of. Clearinghouse for Census Data Services. College Curriculum Support Project. Computer Tapes. Data User News (Monthly Newsletter). Data User Training: Registration. Seminars, Workshops, Conferences. Directory of Data Files. Exhibits. Guides and Directories. Library. Circulation.. Interlibrary Loan. Out of Print Publications. Reference Service. Map Orders. Microfilm/Microfiche. Public Use Samples (Microdata). Reapportionment/Redistricting. State Data Center Program. Statistical Compendia. Publication Orders (Subscriber Services). User Software (CENSPAC, ADMATCH, etc.). ASD Robert L. Kirkland , Chief 763-5400 DUSD Michael G. Garland , Chief 899-7620 FLD Lawrence T. Love, Chief 763-5000 DUSD Christine Stewart 899-7625 DUSD Ann King 899-7672 DUSD Frederick Bohme 899-7625 DUSD John Kavallunas 899-7732 DUSD Les Solomon 899-7755 DUSD Customer Services 899-7600 DUSD Neil Tillman 899-7670 DUSD Dorothy Chin 899-7645 DUSD Deborah Barrett 899-7645 DUSD Customer Services 899-7600 DUSD Douglas Moyer 899-7665 DUSD Gary Young 899-7670 ASD Betty Baxtresser 763-5040 ASD Jim Thorne 763-1175 ASD Staff 763-1930 ASD Maria Brown 763-5511 ASD Grace Waibel 763-5042 DUSD Customer Services 899-7600 DUSD Customer Services 899-7600 DUSD Paul Zelsset 899-7618 DUSD Cathy Talbert 899-7631 DUSD Larry Carbaugh 899-7732 DUSD Glenn King 899-7650 DUSD Customer Services 899-7600 DUSD Larry Finnegan 899-7634 Regional Assistance • Information Information Census Bureau Services Census Bureau Services Regional Offices Specialists Satellite Offices Specialists Atlanta, GA 404/881-3312 Birmingham, AL 205/254-0040 Boston, MA 617/223-0226 Cincinnati, OH 513/684-2448 Charlotte, NC 704/371-6144 Columbia, SC 803/765-5435 Chicago, IL 312/353-0980 Houston, TX 713/226-5457 Dallas, TX Denver, CO 214/767-0625 303/234-5825 Miami, FL San Antonio, TX 305/350-4064 512/229-6018 Detroit, MI 313/226-4675 San Francisco, CA 415/556-6372 Kansas City, KS 816/374-4601 Washington, DC 301/763-5830 Los Angeles, CA 213/824-7291 New York, NY 212/264-4730 Philadelphia, PA 215/597-8313 Seattle, WA 206/442-1560 Listing of Telephone Contacts for Data Users compiled by Carolyn Grace, User Training Branch, Data User Services Division, Bureau of the Census. Write for additional copies, or call 301/899-7645. Figure 8 (continued) 34 significantly since the data were collected. Population estimates for these areas are published each year In Statistical Abstract of the U.S. (Bureau of the Census 1982b). Population data for detailed geographic areas (e.g., census tracts, enumeration districts, block groups), however, may have changed significantly since the data were collected. The Bureau of the Census does keep records of major population shifts and also has developed procedures and methodologies to estimate populations for periods between the decennial Censuses. A description of the procedures and methodologies Is not within the scope of work of this volume. Information on these subjects may, however, be obtained from the Bureau of the Census at the above listed address. 2.3.2 Enumeration of Populations Exposed via Inhalation As discussed In Subsection 2.2, populations exposed to chemical substances In the ambient environment via the Inhalation route are Identified on the basis of their geographic location with respect to the atmospheric source of the chemical substances. Atmospheric sources Include airborne releases resulting from Industrial processes, consumer products, disposal, Incineration, transportation activities (e.g., spills and vehicular exhausts), stationary combustion processes (e.g., home heating), and airborne releases of unknown origin. For the purposes of predicting ambient concentrations of the chemical substance and for purposes of Identifying the population exposed, these atmospheric sources are divided Into three categories: (1) point sources, (2) area sources, and (3) line sources. The following subsections present methods for enumerating the Identified population In each of these three source categories. The methods have been developed keeping In mind the atmospheric modeling tools available to EPA and the major data bases that contain population Information (discussed In the preceding section). The methods recommended have also been developed after consideration of the strengths and weaknesses of previous enumeration efforts or on-going efforts In other EPA offices. The following discussions, therefore, also Include a review of any historical methods considered relevant to the recommended procedures. (1) Point Sources . This subsection presents a procedure for enumerating populations exposed to atmospheric concentrations of chemical substances released from point sources. This subsection also presents a procedure to enumerate populations around point sources that are too numerous to deal with Individually. These are called prototype point sources or, as frequently cited In the literature, general point procedures Initially rely on the estimate of atmospheric via a computer based atmospheric fate model. The the population data Is, however, operationally different, exposed populations around point sources requires sources. Both concentrations acquisition of Enumeration of 35 site-specific population data. Enumeration of populations around prototype point sources uses population density data for different Census defined geographic statistical categories depending on where the sources are located. The recommended procedure for enumerating exposed populations around point sources Is to use an Integrated computer based fate model and population data retrieval program known as ATM-SECPOP, developed by the EPA Office of Toxic Substances, Exposure Evaluation Division (OTS-EED), and General Software Corporation. ATM-SECPOP Integrates the output of a concentration prediction model, a population distribution data base, and graphic and mapping Information displays. The Integration affords a rapid and efficient means of generating and presenting exposure-related data resulting from the airborne release of chemical substances from point sources. ATM-SECPOP estimates concentrations of chemical substances and enumerates the population exposed to these concentrations around point sources that release the chemical to air. The program combines the output of the Atmospheric Transport Model (ATM) (Patterson et al. 1982) and population data contained In the proprietary 1980 Master Area Reference File (MARE) (1980 Census Data) which Is accessed via a population distribution model called SECPOP. ATM calculates pollutant concentrations around a point source by combining data on the facility location, data on emission source characteristics, physlochemlcal data on the chemical of Interest, and stored data on localized meteorological conditions. Pollutant concentrations are estimated for radial sectors around the point source as delineated by axes running In the 16 compass directions and 10 concentric rings at 0.5, 1, 2, 3, 4, 5, 10, 15, 25, and 50 kilometers from the source (Illustrated In Figure 9). Concentrations are, therefore, calculated for a total of 160 sectors around the source. The user also has the option to specify the ring distances to which concentrations of the chemical substance will be calculated. Detailed Information on the application and data Input requirements of ATM are provided In Volume 2 of this series and In the GEMS Users Manual (GSC 1983). MARF Is a data file released by the Bureau of the Census, as previously discussed In Subsection 2.3.1, to which Donnelly Marketing, Incorporated has added the latitude-longitude coordinates of all ED/BGs In the U.S. The 1980 population and housing data In the file, therefore, may be accessed for geographic exposure analysis. The file contains records for states, counties, county subdivisions, places, census tracts, enumeration districts (EDs) In unblocked areas, and block groups In 36 50 km SEGMENT CONCENTRATION BASED ON AVERAGE OF 4 CONCENTRATIONS WITHIN EACH SECTOR ENE ONE RADIAL SECTOR F i g u re 9. Wind Rose Sectors for ATM-SECPOP 37 blocked areas. Each record shows the total population by five race groups, population of Spanish origin, number of housing units, number of households, and number of families. OTS-EED has recently acquired MARF and entered It Into their Graphical Exposure Modeling System (GEMS) (GSC 1983). The file has been Integrated with ATM via the SECPOP program. The SECPOP program retrieves the number of people or housing units within each radial sector defined by ATM. The concentration and population data are combined to provide tables on the estimated number of people exposed at various concentration levels. Figure 10 Is a sample summary table of the output of an ATM-SECPOP model run. GEMS also has graphic display capabilities. These functions may be used to Illustrate the relationship of variables such as the distribution of exposure or concentration versus distance for any or all directions around a facility. GEMS provides prompts to the user to help In Identifying other variables, which may be graphically displayed. Graphic displays may be In the form of bar charts and scatter plots as Illustrated In Figures 11, and 12. The relative value of variables may also be displayed In "Rose" diagrams as Illustrated In Figure 13. GEMS also has mapping capabilities for use In displaying the geographic distribution of ED/BGs around a facility as Illustrated In Figure 14. A complete description of GEMS' capabilities Is provided In the GEMS Users Manual (GSC 1983). Because of the proprietary nature of the data contained In MARF, ATM-SECPOP's use Is restricted to personnel and contractors of EPA-OTS. Special arrangements for outside parties to use the data are, however, available. Inquiries should be directed to the Chemical Fate Branch Modeling Team of EPA-OTS. Method 2-2 summarizes the data requirements and steps necessary to enumerate populations via the ATM-SECPOP program. A complete sample computer run of ATM-SECPOP for the point source emission of trlchloroethane Is provided In Appendix A-l to this report. The MARF data retrieved by SECPOP do not Include the distribution by age and sex of the populations within the sectors, nor do they contain the additional census data In the 20 percent census count such as occupation. Income, travel time, and form of transportation. This Information must currently be obtained from forthcoming Census Bureau publications or STF 3 as discussed In Section 2.3.1 of this report. Numerous private sources of population data are also available; marketing companies can provide demographic data for particular geographic areas for a fee. Point sources may at times be too numerous to deal with Individually. This must be determined on a case-by-case basis and may be due to financial and manpower limitations or because the specific 38 SOURCE: LAKE CHARLES, LA EMISSION TYPE! 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D fll r- .c 03 c -*-> u hh © 3 or s- 03 l/> {. 01 > c SA c > o c o 03 01 O iA L I -*-> OJ 3 c o u >> r- "D 03 © C o on L. aj Q_ U c OJ u u D o in 51 Method 2-4. Enumeration of Populations Exposed via Inhalation to Atmospheric Concentrations of Chemical Substances Released from Area Sources Step 1 Determine the demographic category and geographic location of the area source from the production, use, and environmental release data for the chemical substance. Demographic categories for which census data are available include: • Urban Areas - urbanized areas - other urban areas • Standard Metropolitan Statistical Areas - central cities - outside central cities • Nonmetropolitan Areas • Rural Areas The nature of the source determines which category should be used to define the area. Urban areas or central cities may be of concern with respect to vehicular exhaust or dry cleaning solvents; rural locations may be area sources of pesticides used in farms and gardens. Step 2 Enumerate the population for demographic and geographic category of interest from Table 10. If more detailed data are required (e.g., census division, state), retrieval of population data in MARF according to specific areas is possible using the GEODATA HANDLING (GH) operation and Census Data (CD) program of GEMS as previously described in subsection (1) and Method 2-2. Population data are also available in the the U.S. summary of Number of Inhabitants or General Population Characteristics . Statistical Abstract of the U.S. will also provide population data for many of the demographic categories listed, based on updates from the 1980 census year. 52 (3) Line Sources . This section presents a method for enumerating populations exposed to chemical substances released from line sources. As defined In Section 2.2, line sources are predominantly sources of airborne release of chemical substances along transportation corridors, such as highway and railroad lines. Other types of releases from line sources also exist, such as the volatilization of chemical substances from waterways and fugitive emissions or spills and leaks that occur along pipelines used to transport chemical substances. These types of releases are not specifically addressed In this section; however, the general principle of the methodology presented Is applicable to them. The only existing method Identified for enumerating populations exposed to chemical substances released from a line source was developed for the U.S. Department of Commerce, Maritime Administration (ADL 1974). The method was developed to calculate the safety hazards resulting from different modes of transportation of hazardous substances. Basically, the method requires data on the length of the line source (or transportation corridor), the width of the area adjoining the line source affected by the release of the chemical substance, and the population densities along the line source. The total area affected by the chemical substance Is calculated by multiplying the length and width of the affected area. Total area affected Is then multiplied by population densities to enumerate the exposed population. The method developed for the Maritime Administration assumes that all line sources of chemical release are straight lines that pass through metropolitan areas, nonmetropolItan areas, or combinations of both. Metropolitan areas are defined as those designated Standard Metropolitan Statistical Areas (SMSA) by the Census Bureau. NonmetropolItan areas are defined as all areas outside SMSAs. For a line source that begins and terminates In an SMSA, the following procedure for calculating the length of the line which passes through metropolitan and nonmetropolItan areas was developed: The SMSA for each principal city along the origin-destination route Is recorded In units of square miles according to census data. This area Is then converted to a circular configuration with the principal city located at Its center. If the line source (the vehicle or transportation corridor) travels completely through an SMSA, then the hypothetical diameter of each SMSA Is assumed to be equivalent to the length of the metropolitan population corridor exposed to the chemical substance of Interest. If the line source originates or terminates In an SMSA, then the length of the metropolitan population corridor Is assumed to be equal to the hypothetical radius of the SMSA. The length of the nonmetropolItan population corridor, therefore, Is equal to the total distance between the beginning and end of the line source minus the calculated length of the metropolitan population corridor. This procedure for calculating metropolitan and nonmetropol1 tan population corridor lengths Is Illustrated In Figure 15. 53 + < II GO z o o a. < o II C /3 < 2 + o < 2 < N t x ™* _ O *— X s * 1 «t X . X O t- 1 , 00 . cc O II II II |±j o. ^ Z o < O u _| a: < < < < hMWIflh tu S S 2 O S M V) CA H 00 z o S 5 a. x z a < X h- _ _J U £ + O 00 CC CM I- + LU - s < z i o u z < s = < S q- -J o o => x z ° LU < I! I < O- - 1 z o o 3 = 0 ; o- H- O UJ CC O OL —J < < ^ 5 t 2 O o o o a. £ Q 2 o a < o cc a. < u cc o 00 o cc < X a UJ a. a. < UJ UJ oo 2 LU o z o p < cc h 00 o to o fO CL CU O O a. s- 3 CU o 4-> CO 03 i- cu a) c LU fO o E +-> o s_ aj Li_ &_ Z 3 TC "O O) cu to <_> fd o cu S- Q_ CU q; cu _£Z to •*-> cu a M— SC O 03 +-> c to o .o •r- 13 4-> to fO +-> I— sc ro cu a CO -I— cu E S_ cu Cl _£C cu o QC o CJ +-> -M T3 ra cu E CO cu o -SC CL U X CO LlJ LO a> S- CJ cn Ll_ 54 The width of the line source is defined according to an appropriate algorithm or model using emissions characteristics of the pollutant and meteorological conditions (wind speed, direction, and atmospheric stability). The total metropolitan area exposed is calculated as the product of the length and width of the metropolitan corridor. The same procedure is followed for calculating the total nonmetropolitan area exposed. The calculated areas are then multiplied by the average metropolitan (SMSA) and nonmetropolitan (non-SMSA) population density, respectively, to enumerate the total exposed population. This procedure for enumerating populations exposed to chemical substances released from a line source is believed to be a suitable approach for the current needs of OTS-EED. One of the main data requirements of the ADL approach is the length of the line source. These data are generally provided on a chemical-specific basis in the exposure assessment process. Detailed Information on methods to calculate the length of line sources related to transportation spills is available in Volume 9 of this series. Statistical Abstract of the U.S. (Bureau of the Census 1982b) is also an excellent source on such generic data as metropolitan and non-metropolitan highway mileage, inter-city bus lines, and railroad mileage for the total U.S. and the individual states. For detailed geographic resolution, the topographic maps published by the U.S. Geological Survey are the recommended tool for obtaining the length of a particular line source. Since most of these maps also Include plots of metropolitan and nonmetropolitan areas, it is also possible to rapidly determine the length of the line in each category. Calculation of the width of the line source corridor requires the use of one of several line source simulation models. Line source simulation models consider emission characteristics and meteorological conditions to determine concentrations at various distances downwind of the source. Currently, OTS-EED does not have any line source models Integrated into GEMS. The UNIVAC version of HIWAY is Included in the EPA-OTS computer file library and, therefore, is available to the OTS-Modeling Team. Additional information on line source models is provided in Volume 2 of this series. The final data requirement for enumerating the exposed population is the population density for the area of Interest. Population densities for all SMSAs are available in the Census summary document Number of Inhabitants (PC-80-1-A). Population densities for cities with 100,000 or more Inhabitants are available in Statistical Abstracts of the U.S. (Bureau of Census 1982b). Population densities for specific urban areas with populations less than 100,000 (but greater than 2,500) are available in the Census summary document General Population Characteristics (PC-80-1-B) . 55 Finally, Table 8, previously presented, lists population densities for the different Census Bureau classifications based on 1980 Census data. The population densities obtained from the above listed documents or from Table 8 are then multiplied by the area of the line source corridor to enumerate the total population. Method 2-5 summarizes the procedure for enumerating populations exposed via Inhalation to chemical substances released from line sources. A demonstration of the method on a theoretical line source problem Is presented In Appendix A-l (Problem 5). 2.3.3 Enumeration of Populations Exposed via Dermal Contact Dermal exposure to chemical substances In the ambient environment may occur through a number of pathways. One activity has been Identified as having the greatest potential for significant exposure: swimming In contaminated surface waters. Methods for estimating the size of the population Involved In that activity are presented In Method 2-6. Approximately 101.7 million persons swim In U.S. surface waters (Bureau of the Census 1982b); this represents 45 percent of the U.S. population. The technique for estimating the number of swimmers contacting water contaminated by a particular substance depends on whether the exposure source was Identified through monitoring data or through examination of the chemical's release Information. Volume 2 of this series discusses Identification of sources of chemicals released to surface water. Geographically defined areas of aquatic exposure, such as river reaches downstream of an Industrial discharge, may be Identified by examining release Information. The exposed population Is therefore the swimmers In those specified receiving waters. The most reliable method for estimating the number of persons exposed to contaminants In surface waters Is to contact regional authorities, such as the state, city, or county department of parks. These authorities can Identify affected recreational areas and estimate the extent to which they are used. Another approach to enumerating that population Is to obtain a figure for the total population for the region using the water body as a source of recreation, then to multiply that total by 45 percent, the fraction of persons who swim. There are limitations to this estimation technique; determining the region that uses a recreational facility, such as a lake or river, Is difficult. Matching that region to a census-defined geography for which population data are available may also present problems. If necessary, the area may be broken Into block groups or 56 Method 2-5. Enumeration of Populations Exposed via Inhalation to Chemical Substances Released from Line Sources Step 1 Calculate the length of the line source as illustrated in Figure 15. Sources of information on the calculation of the length of the line source include Volume 9 of this series Methods for Estimating Exposure to Chemical Substances Resulting from Transportation Related Hazardous Materials Spills and A Modal Economic and Safety Analysis of the Transportation of Hazardous Substances in Bulk (ADL 1974). Generic data for line source lengths can be obtained from Statistical Abstracts of the U.S. (Bureau of the Census 1982b) or from government agencies and associations such as U.S. Department of Transportation - Federal Highway Administration and Federal Railroad Ackninistration; the U.S. Interstate Commerce Commission; Bureau of the Census - Transportation Surveys; Association of American Railroads, Washington, D.C.; American Bus Association, Washington, D.C.; and American Public Transit Association, Washington, D.C. Step 2 Calculate the area affected by the released pollutant. This may be accomplished by calculating the width of the exposed corridor using an appropriate line source model. Data on the emissions characteristics and meteorological conditions are required for most of the available line source models. Exposed area is the product of the length of the line source and the corridor width. Step 3 Enumerate population by multiplying the population density of the exposed area by the calculated area exposed (Step 2). Population densities for specific census divisions, states, and urban areas based on the 1980 Census are available in the Census Report General Population Characteristics: U.S. Summary . Population densities for SMSAs are available in the Census document Number of Inhabitants: U.S. Summary . Table 8 lists generic population density data that would also be valuable where detailed or specific data are not required. If more resolution is required for urban areas, population estimates can be refined by consulting maps of ED/BGs to determine which ones fall into the affected area. Populations can be summed for these ED/BGs to provide a more accurate estimate than that given by the product of area and average density. 57 Method 2-6. Enumeration of Populations Exposed via Dermal Contact Determine the number of swimmers contacting contaminated ambient surface waters. Option 1 - (contamination identified by monitoring data or release information) contact the local authorities to identify impacted recreational areas. Inquire about the area's use to estimate the number of affected persons. Option 2 - (contamination identified by monitoring data). Multiply the frequency of detection in percent by the total population of swimmers, 101.7 million persons. (This option yields a very crude estimate of the exposed population. It assumes that the monitoring data are from a nationwide survey of all potential swimming locations or that they are from a sampling that is statistically representative of all swimming locations.) Option 3 - (contamination identified by release information). Identify the water bodies of concern. Enumerate the total population within a 50 mile radius or corridor, using data in General Population Characteristics for census-defined geographies such as cities, towns, counties, or SMSAs. Multiply the total population of the area by 45 percent, the fraction of persons who swim in surface waters. Option 4 - (contamination identified by monitoring data). If extensive nationwide monitoring data are available, they can be used to identify the affected water bodies. The procedure to enumerate the number of swimmers exposed to the chemical substance is the same as in Option 3. 58 enumeration districts, then reaggregated. It Is reasonable to assume that a body of water within 50 miles of a person (a one-hour drive) may be used as a source of recreation. The Investigator might assume that the population within that radius or corridor Is potentially exposed. The General Population Characteristics for the area should be consulted, and the total population of counties, towns, SMSAs, etc., within the radius or corridor should be totaled. For contaminants Introduced by sources other than point discharges of effluents, geographic definition of potential exposure may not be possible. Monitoring data retrievals from STORET or similar data bases can then be used to Indicate the prevalence of waterborne pollution for a chemical substance. If enough data are available, an estimate of the number of persons dermally exposed via swimming can be obtained by multiplying the frequency of detection of the contaminant In surface water (In percent) by the participating population (101.7 million persons). These population enumeration techniques assume that persons will swim In contaminated waters as often as In noncontamlnated lakes and rivers. Figures obtained by these methods may therefore be overestimates. That assumption Is not, however, unreasonable; low level contamination that may cause human exposure Is not always detectable. 2.3.4 Enumeration of Nonhuman Populations Nonhuman populations are generally more difficult to quantify than are human populations because less Information Is available, and the data that are available are often measured In units other than numbers of organisms; populations may, for example, be expressed as herds or biomass. The adequacy and sources of nonhuman population data vary considerably, depending on the organism. As might be expected, most research effort has been Invested In plant and animal species that have economic significance. In most cases. It Is necessary to gather the data from diverse sources to enumerate nonhuman populations. The major sources available Include journal articles and other publications, federal and state agencies, and selected private agencies. A literature search, using computerized data bases such as the following. Is recommended: AGRICOLA (National Agricultural Library, Beltsvllle, MD) AGRICOLA Is the cataloging and Indexing data base of the National Agriculture Library. It provides comprehensive coverage of worldwide journal and monographic literature on agriculture and related subjects. 59 ASFA (NOAA/Cambrldge Scientific Abstracts, Bethesda, MD) The Aquatic Sciences and Fisheries Abstracts (ASFA) Is a comprehensive data base on life sciences of the seas and Inland waters as well as related legal, political, and social topics. It Includes Information on aquatic biology, oceanography, fisheries, and water pollution. BIOSIS PREVIEWS (Biosciences Information Service, Philadelphia, PA) BIOSIS PREVIEWS provides comprehensive worldwide coverage of research In the life sciences. It contains citations from Biological Abstracts and Biological Abstracts/RRM. Life Sciences Collection (Cambridge Scientific Abstracts, Bethesda, MD) Life Sciences Collection contains abstracts of worldwide journal articles, books, conference proceedings, and report literature. The Information Includes animal behavior, ecology, and entomology. SSIE Current Research (Smithsonian Science Information Exchange, Washington, D.C.) SSIE Current Research contains reports of both government and privately funded scientific research projects either currently In progress or Initiated and completed during the most recent two years. These and other data bases can be accessed through DIALOG Information Retrieval Service (DIS 1982). In addition to these data bases, a retrieval from the Fish and Wildlife Reference Service and a retrieval from the GEOECOLOGY Data Base may be worthwhile. The reference service Is operated by the U.S. Fish and Wildlife Service out of Denver, Colorado. Computerized literature searches, covering the published and unpublished fish and wildlife research reports resulting from federally funded programs, are conducted for a fee of $30. The GE0EC0L0GY Data Base (Olson et al. 1980), maintained by the Oak Ridge National Laboratory, Oak Ridge, Tennessee, Is a compilation of computerized environmental data. The data base Includes, at the county level of resolution, selected data on terrain and soils, water resources, forestry, vegetation, agriculture, land use, wildlife, and endangered species. The wildlife sector Includes Information from the annual Breeding Bird Survey, data on federally designated endangered and threatened species, and the geographic range of various mammals. The Endangered Species File and Code Dictionary of the GE0EC0L0GY data base Is currently available through the EPA-OTS computer library (Files W09 and W10, respectively). Requests for Information or retrievals for the other data Included In GE0EC0L0GY should be directed to: 60 Dick Olsen 6E0EC0L0GY Project Team Oak Ridge National Laboratory PO Box X, Building 1505 Oak Ridge, TN 37830 (615) 574-7819 Estimates of exposed nonhuman population sizes may also be made, If the resources permit, through contact with appropriate state and federal agencies. The two that are of most use are the Fish and Wildlife Service and the U.S. Department of Agriculture's Forest Service. Both maintain regional research offices which may provide published or unpublished population data not available from other sources. Private agencies such as those listed In Table 11 may also be contacted for population Information. The National Wildlife Federation (1980) lists many private organizations with specific wildlife concern which may also be used as Information sources. The Investigator should be aware that, for most species, the population data, If any, are scant and are based on a handful of studies In specific locales. Extrapolating such data to large regions or to the nation Involves considerable uncertainty because uneven spatial distribution and temporal fluctuations are characteristic of many nonhuman populations. Population density Is highly dependent on habitat type, and the population density estimated In one local study may be significantly higher or lower than the average population density for larger areas (e.g., counties, states, regions). 2.4 Ch aracterization of Exposed Populations The average physiological parameters that determine exposure (e.g., breathing rate, body weight, and skin surface area) are age- and sex-specific. Subpopulatlons defined by age or sex, such as the elderly or women of child-bearing age, may be especially susceptible to a chemical substance. Characterization of exposed populations permits the determination of exposure distributions and the enumeration of specific high risk subpopulatlons. Methods for characterizing populations exposed via Inhalation and dermal exposure In the ambient environment are presented In the following subsections. 2.4.1 Populations Exposed via Inhalation The level of geographic resolution necessary to an assessment of atmospheric pollutants dictates the scheme by which characterization proceeds. Populations near point sources for which ATM-SECPOP Is used to determine exposure may be characterized by the use of census data 61 Table 11. Sources of Information on NonHuman Populations National Wildlife Federation 1412 16th Street, NW Washington, DC 20036 (202) 797-6800 National Audubon Society 950 Third Avenue New York, NY 10022 (212) 832-3200 North American Wildlife Foundation 709 Wire Building Washington, DC 20005 (202) 347-1775 Raptor Research Foundation, Inc. c/o Richard R. Olendorff Division of Resources U.S. Bureau of Land Management 2800 Cottage Way Sacramento, CA 95825 The Wildlife Society Suite 611 7101 Wisconsin Avenue, NW Washington, DC 20014 (301) 986-8700 62 specific to the area. For prototype point sources, area sources, and line sources, both site-specific and generic data on the age and sex characteristics of the population may be applicable sources of Information. (1) Point Sources Enumerated by SECPOP . The SECPOP data base enumerates the populations differentially exposed In segments around point sources. Data for geographically-defined areas within the SECPOP radius are available from the Bureau of the Census. Populations enumerated by SECPOP can usually be characterized by consulting the General Population Characteristics series for the area within the model radius. The level of detail achievable through this data source will be sufficient, for all but the most In-depth exposure analyses; Table 2 (Section 2.3.1) lists the census-defined areas for which age and sex data are available from General Population Characteristics. Segments within the model radius can also be segregated Into census tracts If more detail Is required. Series PHC80-2, Census Tracts , presents data by age and sex for populations defined by census tract. (2) Point, Area, and Line Sources . The data sources discussed above ( General Population Characteristics and Census Tracts ) can be used to characterize populations around or within these pollutant sources. Point, area, and line sources are, however, often too numerous to be treated Individually. Table 12 presents the age and sex distribution of the U.S. population as determined by the 1980 Census. These data may be used to estimate the distribution of males and females of different ages In relatively large exposed populations; that distribution would be expected to be similar to the national distribution. Method 2-7 Is a guide to characterizing exposed populations. 2.4.2 Populations Exposed via Dermal Contact Numerous activities In the ambient environment may lead to dermal contact with chemical substances: aquatic recreation, gardening and other contact with the soil, and contact with atmospheric pollutants deposited on the skin surface. Of these, one Is considered to be a potentially significant source of exposure: swimming In contaminated surface waters. As discussed In Section 2.3.4, a large proportion of the population swims In lakes, rivers, and the ocean. It can be assumed that such a large population constitutes a cross section of the U.S. populace and that swimmers can be characterized by the data In Table 12. It Is likely that the actual swimming population Is skewed somewhat toward the young, and that the young swim more frequently, but data to substantiate that premise are not available. 63 Table 12. Population of the United States by Age and Sex: April 1, 1980 Age and sex Population Percent 1. Both sexes All ages 226,504,825 100.00 Under 5 16,344,407 7.22 5-9 16,697,134 7.37 10-14 18,240,919 8.05 15-19 21,161,667 9.34 20-24 21,312,557 9.41 25-34 37,075,629 16.37 35-44 25,631,247 11.32 45-54 22,797,367 10.65 55-64 21,699,765 9.58 65-74 15,577,586 6.88 75-84 7,726,826 3.41 Over 85 2,239,721 .99 Median age 30.0 2. Male All ages 110,032,295 100.00 Under 5 8,360,135 7.59 5-9 8,537,903 7.76 10-14 9,315,055 8.46 15-19 10,751,544 9.77 20-24 10,660,063 9.69 25-34 18,378,764 16.70 35-44 12,567,786 11.42 45-54 11,007,985 10.00 55-64 10,150,459 9.22 65-74 6,755,199 6.14 75-84 2,865,974 2.60 85 + 681,428 0.62 Median age 28.8 3. Females All ages 116,472,530 100.00 Under 5 7,984,272 6.85 5-9 8,159,231 7.00 10-14 8,925,864 7.66 15-19 10,410,123 8.94 20-24 10,652,494 9.15 25-34 18,696,865 16.05 35-44 13,063,461 11.22 45-54 11,789,382 10.12 55-64 11,549,306 9.92 65-74 8,822,387 7.57 75-84 4,860,852 4.17 85 +■ 1,558,293 1.34 Median age 31.3 Source: Personal communication between Mrs. McCoy of the Population Division, Bureau of the Census, and Amy Borenstein, Versar, Inc., July 1982. 64 Method 2-7. Characterization of Populations Exposed to Chemical Substances via Inhalation of Ambient Air For populations near point sources (as enumerated by SECPOP), line sources, or area sources, choose the option providing the desired level of detail. The method of enumeration and the financial and manpower resources allotted will dictate the choice of options. Option 1 - The most detailed characterization is obtained by determining census tracts within the defined radius, area, or corridor and using the age-sex distributions for each (in Census Tracts ) to describe the population. Option 2 - General Population Characteristics for the area (SMSA, county, town, etc.) provides the age and sex characterization for the enumerated population. Option 3 - The generic data in Table 12, describing the U.S. population as a whole, may be used to characterize populations around point, general point, area, or line sources. 65 2.5 References AOL. 1974. Arthur 0. Little, Inc. A modal economic and safety analysis of the transportation of hazardous substances In bulk. Washington, DC: U.S. Department of Commerce, Maritime Administration. Bureau of the Census. 1979a. 1980 Census of population and housing, August 1979. Washington, DC: U.S. Department of Commerce. Bureau of the Census. 1979b. Census geography. Data access descriptions, No. 33. Washington, DC: U.S. Department of Commerce. Bureau of the Census. 1980a. Census '80. Introduction to products and services. Washington, DC: U.S. Department of Commerce. Bureau of the Census. 1980b. Data user news, Volume 15, No. 8, August 1980. Washington, DC: U.S. Department of Commerce. Bureau of the Census. 1980c. Factfinder. No. 8. February 1980. Washington, DC: U.S. Department of Commerce. Bureau of the Census. 1981a. Factfinder. No. 22. September 1981. Washington, DC: U.S. Department of Commerce. Bureau of the Census. 1981b. 1980 Census update, Issue No. 18, April 1981. Washington, DC: U.S. Department of Commerce. Bureau of the Census. 1982a. Directory of data files. Machine readable data available from the Bureau of the Census. Washington, D.C: U.S. Department of Commerce, Subscriber Services Section (Publications). Bureau of the Census. 1982b. Statistical abstract of the United States: 1982 (103rd edition). Washington, DC: U.S. Department of Commerce, U.S. Government Printing Office. Bureau of the Census. 1983a. 1980 Census of population. Number of Inhabitants. U.S. Summary. ( PC80-1-A) Washington, DC: U.S. Department of Commerce. U.S. Government Printing Office. Bureau of the Census. 1983b. 1980 Census of population. General population characteristics. U.S. Summary. (PC80-1-B). Washington, DC: U.S. Department of Commerce. U.S. Government Printing Office. DIS 1982. DIALOG Information Services, Inc. DIALOG Information retrieval service data base catalog. Palo Alto, CA. 66 6SC. 1983. General Software Corporation. Graphical exposure modeling system (GEMS) user's guide. Draft final report. Washington, DC: U.S. Environmental Protection Agency, Office of Toxic Substances. EPA Contract No. 68-01-6618. National Wildlife Federation. 1980. Conservation Directory. 1980. 25th anniversary edition. The National Wildlife Federation. Washington, DC. Olson RJ, Emerson CJ, Nungesser MK. 1980. GE0EC0L0GY: a county level environmental data base for the conterminous United States. Oak Ridge, TN: Oak Ridge National Laboratory. ORNL/TM-7351. Patterson MR, Sworskl TJ, SJoreen AL, Browman MG, Coutant CC, Hetrlcka DM, Murphy BD, Rarldon RJ. 1982. User's manual for UTM-TOX, a unified transport model. Draft report. Oak Ridge, TN: Oak Ridge National Laboratory. ORNL-TM-8182. IEG-AD-89-F-1-3999-0. SAI. 1980. Systems Applications, Inc. Human exposure to atmospheric concentrations of selected chemicals. Research Triangle Park, NC: U.S. Environmental Protection Agency, Office of Air Quality Planning and Standards. EPA Contract No. 68-02-3066. 67 3. POPULATIONS EXPOSED TO CHEMICAL SUBSTANCES IN THE OCCUPATIONAL ENVIRONMENT 3.1 Introduction This section presents methods for enumerating and characterizing occupationally exposed populations. The methods described apply to workers In Industry, trade, and commercial establishments. The data provide various levels of detail that enable the user to produce both preliminary and In-depth assessments. Figure 16 Is a flow diagram of the three-stage method framework. Included In the diagram are some of the major data sources used. The Identification of the exposed population Is discussed only briefly In this section (Subsection 3.2); the occupational exposure assessment methods report (Volume 6) describe the process In detail. The enumeration of the exposed population relies on the direct utilization and combination of numerous data bases. This Information Is largely the result of efforts by the federal government to monitor employment; as such, the data may not be In a format directly applicable to exposure assessments. Subsection 3.3 addresses the limitations of the data and how they can be used for occupational population studies. The age and sex of a worker affect physiological parameters that determine exposure (e.g., breathing rate, skin surface area). Detailed exposure assessments may require that populations be described by age and sex distributions; Subsection 3.4 discusses methods of characterizing workers by age and sex. Examples of the use of the methods In this section of the report are presented In Appendix A-2. 3.2 Identification of Exposed Populations Methods for Identifying occupationally-exposed populations are summarized herein; Volume 6 of this series provides details on these methods. Specific job titles and 4-d1g1t Standard Industrial Classification (SIC) designations are the most common forms by which employment Is listed. Identification should be keyed to this fact when possible. Method 3-1 summarizes the general approach to population Identification. 69 *BLS = BUREAU OF LABOR STATISTICS *10 MATRIX = INDUSTRY-OCCUPATION MATRIX *EIS = ECONOMIC INFORMATION SYSTEMS, INC. Figure 16. Three-stage Framework for Enumeration and Characterization of Occupationally Exposed Populations n r Step 1 Step 2 Step 3 Method 3-1. General Procedure for Identifying Populations Exposed in the Workplace Determine which industries and types of establishments produce, process, use, and sell the chemical substance of concern. Locate major production and use facilities. Identify the applicable SIC codes for all industries and establishments (see Volume 6 of this series). Consult the production, use, and release information and available monitoring data to identify points of chemical release and possible exposure pathways and exposure routes. Identify activities leading to exposure (see Volume 6). For each industry and activity identified in Steps 1 and 2, list the workers potentially exposed by occupation or job title. Use the Industry-Occupation (I—0) matrix as a guide in listing. 71 Employees potentially exposed via Inhalation, Ingestion, and dermal contact may be Identified by examining workplace monitoring data or by considering the workers' process equipment and job activities. Monitoring data are usually available only for a relatively small number of existing chemicals. New chemicals must be Investigated by studying the premanufacturing notice (PMN) submittal and supplementing that Information with knowledge of the process. Analysis of monitoring data and production, use, and release Information may Identify: • Workers exposed In a particular Industry, Identifiable by SIC code. • Persons employed In a specific occupation In an Industry. • Workers exposed by their presence at an Industrial site. • Persons performing certain activities or processes not directly classifiable by occupation (e.g., cleaning, sampling, waste disposal). These groups are enumerated by methods specific to each. The following section discusses the methods by which exposed populations can be enumerated. Most of the methods rely upon direct use of data bases maintained to monitor employment levels. As mentioned previously, the data may not match the Identified populations; adaptation of the Information Is discussed. 3.3 Methods for the Enumeration of Exposed Populations This section presents the recommended procedures and data sources for the enumeration of occupationally-exposed populations. The methods may often be used In combination with each other to achieve the best estimate of workers exposed to chemical substances, though common sense must be used to avoid double-counting subpopulatlons. The method or methods to be used are often dictated by the Identification scheme. This section Is divided Into three subsections, based on the categories for Identifying the exposed populations. Subsection 3.3.1 discusses data bases and methods based on the Standard Industrial Classification (SIC) codes. Populations Identified by occupation and Industry are discussed In Subsection 3.3.2, and Subsection 3.3.3 deals with site-specific worker populations. 72 Some of the methods discussed In this section provide better estimates than others. The greater the level of detail available, the better the estimate of the exposed population; thus, the methods based on specific occupation by Industry or activity data are generally better than the SIC-based method. The limitations of each type of data are discussed In each section. Examples of the data available for many of the methods are Included as Appendix B to this report. Appendix A-2 presents examples of applying the methods In this section. 3.3.1 Enumeration of Populations Identified by SIC Code The method for enumerating workers Identified by SIC code (Method 3-2) Is straightforward and relies on the use of two types of Information: (1) the Bureau of Labor Statistics' Employment and Earnings (U.S. Department of Labor 1981a) and (2) the Economic Census and related reports. All SIC-based data have one major limitation. An establishment may be Involved In activities classifiable under numerous 4-d1g1t SIC codes, but all data are reported under one SIC designation (the "major activity" In which the company Is Involved). This provision simplifies a company's reporting requirements but produces data that may be gross underestimates or gross overestimates when used for exposure assessments. There Is no way to account for such discrepancies In occupational population studies. Another limitation has varying effects on the reported data. Some Industries count only paid employees; establishments staffed by unpaid family members or owner-proprietors will therefore be uncounted or undercounted. A problem with all SIC-based data Is the lack of completeness. The list of 4-d1g1t SIC codes runs nearly 80 pages of print, but data are reported for only a fraction of the established 4-d1g1t codes. Some publications are limited by choice, l.e., only specific codes are reported. More often the limitation Is related to the need to preserve confidentiality of responses when few data are reported for an Industry. (1) Employment and Earnings . The U.S. Department of Labor's Bureau of Labor Statistics (BLS) publishes Employment and Earnings monthly. The data therein are thus the most recent available; the employment figures In each publication are for the previous month. The major limitation In the monthly BLS data Is the lack of completeness. Only a fraction of the 4-d1g1t SIC codes In manufacturing Industries Is represented, and nonmanfacturlng Industries (such as trade, construction, and services) are present at the 3-d1g1t level of resolution at best. Use of data based on the 2- or 3-d1g1t level may result In overestimation of occupational populations, because the broad categories may Include Industries In which no exposure occurs. 73 Method 3-2. Enumeration of Populations Identified by SIC Code Step 1 Determine which source(s) list populations for the SIC codes for which data must be obtained. For nationwide chemical assessments, consult (in order of preference): - Employment and Earnings (most recent data) - The Economic Censuses (fairly complete and readily available) - Other information such as County Business Patterns and the Annual Survey of Manufactures - When enumerating populations in specific geographic areas, consult County Business Patterns (published last in 1981) or the Geographic Series of the Economic Censuses (accessible in hard copy or through GEMS). Step 2 Choose the data most representative of the workers actually exposed. In manufacturing industries, for example, "production workers" is generally a better category for estimating exposures during the process than is total employment for a SIC listing (which includes office workers who may not be exposed). Step 3 Qualify all data by addressing questions of limitations: - Does the SIC code represent the exposed population? If not, are data overestimates or underestimates? - Are data based only on paid employees and therefore possibly underestimates? 74 The BIS establishment data are number of Jobs, not number of workers. If a person holds two jobs, he may be reported twice In Employment and Earnings . This, however, Is rarely a limitation to the data as they are used In exposure assessments; only workers with both Jobs classified under the same SIC code would be double counted In the exposed population for an occupation. (2) Ec onomic Censuses . Eight Economic Censuses are conducted In five-year cycles: 1 . Census of Service Industries 2. Census of Wholesale Trade 3. Census of Retail Trade 4. Census of Manufactures Years ending In 2 and 7 5. Census of Mineral Industries 6 . Census of Construction Industries 7. Census of Transportation 8. Census of Agriculture - Years ending In 8 and 3 All of the censuses contain Information on employment, listed by SIC code. More Information on the censuses Is available from the Research Triangle Insltute (RTI 1982) and U.S. Department of Commerce (USDC 1979); detailed Information on the compilation techniques Is presented In the Census publications associated with each Economic Census. The data available In the first six economic censuses are summarized In Table 13. The Census of Transportation's only employment data are listings of truckers "for hire" and "not for hire" (RTI 1982). Data related to the Economic Censuses Include County Business Patterns and the Annual Survey of Manufactures. The County Business Patterns, last compiled In 1977, provide county-by-county and national summary statistics by SIC code for the full range of 2-, 3-, and 4-dlglt classifications. The reporting requirements and resulting data are similar to those of the Economic Censuses. The Annual Survey of Manufactures Is a yearly update of the Census of Manufactures. Despite their limitations, SIC-based data have proved useful In exposure assessments. This Is especially true for widely used chemicals, such as formaldehyde In textile resins. Data from the Census of Manufactures provided useful estimates of textile mill workers exposed to formaldehyde, and the Censuses of Retail Trade and Wholesale Trade were used to enumerate persons exposed as a result of selling formaldehyde- treated cloth and apparel (Versar 1982). All SIC-based employment data are government-generated and are therefore available to the public. All publications listed In this 75 jQ t- 03 o r— CL • r— CD cr > 03 I i/i 3 ID c 01 a o <1) CD C o 03 C O u u TO O (. a. 03 Q_ -c o 4-> i- >> 3 03 Q. l- U 4-> i/I i/I 03 03 03 03 CM 00 3 \ N CD r— CM T0 L. C 03 HH i/I C C c -*-> .O U ID 03 03 fV **"D •»- o CO CM r— CO \ .a u 3 03 UO ID c (J CL S_ m m m m i/i * X * X i/I ID c CL 03 03 03 O 03 ID t- ID ID 03 03 03 03 3 03 4-> 03 4J 4-> 4-> 4-> • p* u • r— o 03 03 03 S- 0) u r— U 3 u c O O U 4-> ID »— 03 4-> L_ 4-> • r— ID 03 03 • r— 03 •4- U ID 4-> ID II > 3 TO 03 TO 3 03 3 ID 3 u ■D o 4-> 03 C C TO C TO II II 03 C JZ L. 03 L. £ C 8 C \ in •*— 3 4-> cr 4-> ac • r* •*— c X ID CD U c a> i- 03 S- (1) s- I i/I • (D 03 O • L- ID -D U 03 03 • r- r - • 4-» 4-> • r- c • r— 03 03 u > 03 c TO 03 c ID > 03 S- C • 03 o ID ^ u 03 »— U C O L. -*-> o 5 o c 14- 3 ID 03 o •— > lD O 03 •»— 03 > 4-> ID O 03 ID 4-> r— t- 03 4-> C C r- ID »r— 5 03 • r— ID 5 c C 3 “D O -Q i/I 4-> £ <4- 03 03 03 o 03 C L. TO • ID 03 TO C >> 03 C "0 Ol ID 03 r— >> 3 03 03 4-> ID 03 O C C 4-> •f O TO 03 03 >4- • r~ 03 U 4-> <4- 4-> 4-> ID O 03 r— c r— •— 03 u 03 03 -C o TO U 4-> ^4- c U 03 W- O ID o <4- 03 CD 03 C 4-> ID >> u 4-> oo 3 X) c CD c o CD CD — 03 76 Source: Adapted from RTI (1982) and USDC (1979). section can be obtained through the Government Printing Office, and many are available In major D.C. area libraries. The Modeling Team of the Exposure Evaluation Division's Chemical Fate Branch has begun Incorporating the Economic Censuses Into the Graphical Exposure Modeling System (GEMS). GEMS users can extract data for 3- or 4-d1g1t SIC codes from the Geographic Series of the Censuses of Manufactures, Retail Trade, Wholesale Trade, and Service Industries. Total employment, number of establishments, and (where applicable) production workers can be obtained as national totals or by states, counties, SMSAs, or cities. These data can be statistically analyzed and displayed by GEMS In tabular form or In a variety of graphical presentations (e.g., bar graphs and scatterplots). 3.3.2 Enumeration of Populations Defined by Occupation and Industry Occupationally exposed populations will often be Identified by job title, e.g., by occupation and Industry. The most detailed employment Information available, the Industry-Occupation (1-0) matrix (U.S. Department of Labor 1981b), Is presented In this format. The Bureau of the Census also presents data In that style, though at a much more aggregated level reflecting less detail than the 1-0 matrix. A third source of this form of occupational data Is contact with professional organizations and trade associations. The use of these data Is summarized as Method 3-3. Each type of Information Is discussed below. (1) The Industry-Occupation (1-0) Matrix . The 1-0 matrix Is a compilation of data collected regularly from the Bureau of Labor Statistics (BLS), state employment agencies, and the Employment and Training Administration of the Department of Labor. The matrix Is collated for data In three-year cycles (RTI 1982). The data are actually presented as two matrices encompassing 1,615 occupations In 378 Industries. One matrix lists Industries by occupation; the printed output of this matrix Is about 2,500 pages. The more useful listing of occupations by Industry Is 5,000 pages long. Both are available on computer tape from BLS; they can be obtained as paper hardcopy and on microfiche from the National Technical Information Service (NTIS). An example of the 1-0 matrix output Is contained In Appendix B-l. Personnel at the Bureau of Labor Statistics Indicate that the publIcly-avallable 1-0 matrix may be somewhat reduced In scope from Its Initial conception.* The effect of those changes on the usefulness of the data cannot be projected at this time. ♦Personal communication with G. Schweer, Versar, and E. Abramson, BLS, Division of Occupational Outlook, May 1982. 77 Method Option 1 Option 2 Option 3 3-3. Enumeration of Populations Identified by Occupation and Industry Consult the 1-0 matrix directory, and enumerate populations listed therein. Employment is read directly off the matrix; no adjustment or extrapolation is necessary. For very specific or unusual occupations, identify the applicable trade or professional organizations. Contact the organization and ask whether data on the number of member's is representative of total employment in that field. In the absence of all other data, estimate the population by consulting Occupation by Industry . If possible, state qualitatively whether the 1970 data provide overestimates or underestimates (more likely). (2) Bu reau of the Census data . The decennial Census collects detailed employment Information from one In six respondents for publication as the Occupation by Industry series report (Bureau of the Census 1972). The biggest limitation to the use of the data Is that they were last published In 1972, as a result of the 1970 Census. Budget limitations may preclude the publication of Occupation by Industry for the 1980 Census. Data collected In 1980 have not yet been programmed; publication or availability of tapes prior to 1984 Is unlikely.+ Any data derived from the 1970 Census must be used with caution. (3) Co ntact with professional organizations and trade associations . Often the most precise and up-to-date employment figures can be obtained by contacting the organization representing a trade or profession. The following references are useful In locating the relevant organization • Gale's Encyclopedia of Associations (Gale Research 1980) • D.C. area telephone directories The association staffer should be Informed of the reason for the request, so that he or she can provide the most applicable estimate. Data limitations to be aware of Include the possibility that retired or Inactive members no longer Involved In the occupation are still listed, or that the membership lists are simply out-of-date. 3.3.3 Enumeration of Site-Specific Populations Exposure assessments requiring enumeration of workers at specific production facilities may be undertaken by using Method 3-4. This method relies on four sources of Information: 1. Economic data (such as the Economic Information System - EIS - computerized data and printed reports) 2. The State Industrial Directories (State Industrial Directories Corp. 1979) 3. Direct contact with producers 4. State and federal 0SHA Inspection data. +Personal communication between G. Hendrickson, Versar, and P. Vines, Bureau of the Census, December 1982. 79 Method 3-4. Enumeration of Site-Specific Populations Option 1 (Direct Enumeration) Step 1 Determine total employment at plant. Option 1: Retrieve data from EIS. The Line-of-Business reports, available for major manufacturers, list the locations and total employment for facilities. Option 2: Consult the State Industrial Directory. Facilities are listed by city in each state's volume. Option 3: Directly contact the manufacturer. Step 2 Estimate the proportion of total employees involved in production of the chemical in question. Option 2 (Extrapolation of Sample Data) Step 1 Retrieve OSHA inspection data for the chemical substance. Inspections will list the number of workers affected at each plant site. Step 2 Calculate the average number of workers exposed per plant for each type of facility (production, processing, etc.). Step 3 Multiply the average per plant by the total number of plants nationwide to enumerate the total occupational population. Note: The limitations to the use of Option 2 are described in Section 3.3.3. The method can use any or all of the sources above, but It Is best applied to enumerating a limited number of populations; direct enumeration of this type may be expensive and time-consuming. While the data from these sources are reliable, It Is often difficult to ascertain what proportion of workers In a large plant are Involved In the production of the chemical substance of Interest. Extrapolation of data from a few plants to obtain national employment estimates Is possible. There are limitations to the use of sample data. Unless Inspections are (1) representative of Industry-wide conditions and (2) complete (l.e., all exposed workers In each plant were Identified), data from extrapolation may be Inaccurate. An additional problem Is that the majority of Inspections are several years old, and few OSHA Inspections are now done each year. The Economic Information System (EIS) Is a comprehensive computer data base listing a company's facilities and the number of employees at each site. The data are, however, expensive to retrieve ($90 per hour online); the usefulness of the EIS Is therefore restricted. Data can be obtained through the Control Data Corporation's Economic Business Information System (EBIS) or by phone or mall contact: Economic Information Systems, Inc. 310 Madison Avenue New York, N.Y. 10017 (212) 697-6080 The State Industrial Directories Corporation publishes a state-by-state listing of Industrial facilities, arranged by city. The Directory Is published annually and Is available In major libraries. The level of detail reported varies by state; some states record total employment, while some distinguish between office and production workers and characterize the workers by sex. The data recorded In the Directory may, however, be Incomplete since all Information Is supplied to the Corporation voluntarily (State Industrial Directories Corp. 1979). States and smaller government units may also publish their own directories In an effort to attract business. State Departments of Commerce and local Chambers of Commerce are good sources of Information. Contacting a producer directly, either by mall or telephone, often produces the most recent and detailed data on workers. As mentioned previously, one production facility may process any number of chemicals. Knowledge of the total employment at that plant provides only an upper limit for estimating the exposed worker population. Assuming that production techniques for different chemicals are equally labor Intensive, the following may provide an order-of-magnltude estimate of the number of workers Involved In the production of one chemical: 81 where PV a = the production volume of the chemical being assessed PVt = total production at the facility E a = employees producing the chemical being assessed (the exposed population), and Et = total plant employment. 3.4 C haracterization of Occupationally Exposed Populations Method 3-5 summarizes the characterization of occupationally exposed populations. Physiological differences between workers of both sexes and various ages may affect chemical exposure or the resultant risk. The most recent data on the distribution of the work force between men and women are presented In Table 14; the relevant "percent of total employment" figures can be applied to the enumerated population. Table 15 presents the age and sex distributions for major occupational groups. These data are based on the 1970 Census, however, and they should be used with caution. Economic and social evolution of the past decade has produced changes that are readily apparent to one who compares Tables 14 and 15. Women once accounted for less than 17 percent of the managers and administrators; In 1979, over 30 percent of that group were women. The State Industrial Directory series discussed In Section 3.3.3 may also provide the number of male and female workers at specific locations, but those data are only collected for a few states. 32 Method 3-5. Characterization of Occupationally Exposed Populations Step 1 Determine whether age and sex characterization or sex characterization is required. Step 2 Characterize the population. Apply percent distributions to the enumerated population. Option 1: (Age and Sex.) Consult Table 15 for data on general occupations. Be cognizant that data are 12 years old Option 2: (Sex only.) Consult Table 14 for 1979 data on general and specific occupations. Option 3: (Sex only.) Consult data derived from site-specific sources (see Section 3.3.3). 83 Table 14. Employed Persons by Occupation and Sex, 1979 Occupation Percent of total employment Male Female Professional and technical workers 46.0 54.0 Medical and other health 25.2 74.8 Teachers except college 20.6 79.4 Other 64.5 35.5 Managers and administrators, non-farm 68.1 31.9 Salaried 67.5 32.5 Self-employed, retail trade 62.1 37.9 Other self-employed 78.6 21.4 Sales workers 45.9 54.1 Retail trade 31.5 68.5 Other 65.1 34.9 Clerical workers 17.3 82.7 Stenographers, typists, secretaries 1.4 98.6 Other 22.9 77.1 Craft workers 92.6 7.4 Carpenters 100.0 - Construction craftsworkers 98.9 1.1 Mechanics and repairers 98.2 1.8 Metal craftsworkers 95.1 4.9 Blue collar supervisors 85.7 14.3 A11 other 80.0 20.0 Operatives, except transport 51.7 48.3 Durable goods manufacture 57.6 42.4 Nondurable goods manufacture 36.4 63.6 Other industries 55.5 44.5 Transport equipment operators 91.0 9.0 Drivers, motor vehicles 90.1 8.9 A11 others 96.4 3.6 Non-farm laborers 87.0 13.0 Construction 95.3 4.7 Manufacturing 81.8 18.2 Other industries 86.4 13.6 84 Table 14. (continued) Occupation Percent of total Male employment Female Private household workers 1.1 98.9 Service workers, except private household 36.5 63.5 Food service 29.8 70.2 Protective service 85.7 14.3 All other 32.7 67.3 Farmers and farm managers 86.1 13.9 Farm laborers and supervisors 73.3 26.7 Paid 78.8 21.2 Unpaid family 33.6 66.7 Source: Adapted from BLS (1980) Percent of total employed in each category LT) CM CM __ ro to in «3" to • • • • • • • • • • 9 CM o O O o CO r_ ^r VD ro ct i^. o o CT CT CM i • • • • • • • • • • 9 in CM CO in r— CM in r— CM CO CM CO CM r— CM to 07 0— *3 ^r ro cr> (T> CO o r— in r— to to in E i • • • • • • • • • • 9 07 in CO in i— CM to CM CO ro o Lu CM CM CM *3- CSJ in ro «3- r-x CM to r— to in r^. 1 • • • • • • • • • • 9 to t — CT* CM o to o CM f— CO CO r “" CM r “ r— O to *3- to 00 CT o rx. <3- r ~~ ro ro to co in o r _ 00 ^3" CM o to to • • • • • • • • • • 9 CM <3* ro >— CM r— CM CO o ro CM r "" ^3- to O'* CT CM to CO O'* CM > k- o CO CO ro «3- CM CT 0k 0k » •> •k 3 07 r— to CM CM CO in o CO i— in C in CO ro 00 ro r— in CO CO CM o to «3- ro r>» to in CT* «3- CO 00 co r— c 0» * * 0y * 0k 0k * fO o r— to in ro o o CM CO CM CT to 4-> to r* r— f^x o X- h- 07 CL 4-> to k. x- o o CL * 4-» 00 r— "3 C fT3 k- U 4-» ■O i- E •r— 00 TD 07 +-> to s- C •r— C &. o> ro JC C to X) +-> > 4- o •r— c CL •n 07 E lO •r* 07 4-> 4-> 4-> •a k. O *> _x Q- •r— •r- TD to E o r— 07 > k. to k. =D 4-> to C k- k- fT3 -O E •r— o S- o 07 o «3 to •r~ 07 (O U 07 ka 4-> CL 07 O o C3l a) -X ct 4- to •r- S- 4-> *3 to k. •r” o 3 4- fT3 1 03 k. -o 4- l- c o E > O o "O c C r— 07 C « 3 07 rO -O S- k- _J O x- c <-> .x O O H- _l u- OO < 86 Source: Adapted from Bureau of the Census (1972) 3.5 References BLS. 1980. Bureau of Labor Statistics. Handbook of labor statistics. Washington DC: U.S. Department of Labor. BLS Bulletin 2070. Bureau of the Census. 1972. Occupation by Industry: 1970 Census of population. Washington, DC: U.S. Department of Commerce, Social and Economic Statistics Administration. Gale Research Corp. 1980. Encyclopedia of Associations. Michigan: Gale Research Corporation. RTI. 1982. Research Triangle Institute. Identification, analysis, and procurement of data bases for assessing exposed populations. Phase I report. Identification of data bases. Draft. Washington, DC: U.S. Environmental Protection Agency, Office of Toxic Substances. Contract No. 68-01-5848. State Industrial Directories Corp. 1979. State Industrial Directory. New York, NY: State Industrial Directories Corp. USDC. 1979. U.S. Department of Commerce. Mini-guide to the 1977 economic censuses. Washington, DC: Bureau of the Census. U.S. Department of Labor. 1981a. Employment and earnings. October 1981. (Monthly Reports). Washington, DC: Bureau of Labor Statistics. U.S. Department of Labor. 1981b. The national Industry-occupation employment matrix, 1970, 1978, and projected 1990. Volumes I and II. Washington, DC: Bureau of Labor Statistics. Bulletin No. 2086. Versar. 1982. Exposure assessment for formaldehyde. Draft Report. Washington, DC: U.S. Environmental Protection Agency, Office of Toxic Substances. Contract No. 68-01-6271. 87 4. POPULATIONS EXPOSEO TO CHEMICAL SUBSTANCES VIA THE INGESTION OF FOOD 4.1 In troduction This section presents methods for enumerating and characterizing populations exposed to chemical substances via the Ingestion of food. The methods described are applicable to food Items or categories of foods that contain chemical substances as a result of (1) agricultural practices (e.g., use of pesticides, fertilizers), (2) processing (e.g., packaging, canning), (3) contaminants that can be traced to point, area, and line sources, and (4) contaminants of unknown origin detected via monitoring data. The methods that follow rely In many cases on simplifying assumptions In order to enumerate the exposed populations; foods and food products have geographical distributions and processing patterns that fluctuate depending on seasonal demand and availability. Enumeration of the total consuming population for a specific food Is a relatively straightforward process. The exposed population Is, however, some fraction of the consuming population; that fraction Is a function of the source of the chemical substance. The methods presented In this section can be used to estimate the range of the exposed population. Figure 17 Is a flow diagram of the three-stage framework for enumerating and characterizing populations exposed to chemical substances via the Ingestion of food. Each stage Is composed of several methods depending on the source of the exposure or how the exposed population Is Identified In the exposure assessment. Subsection 4.2 briefly describes the procedures for Identifying the exposed population. The enumeration of the exposed population Is the second stage and Is discussed In Subsection 4.3. Subsection 4.3 Is organized according to the source of the chemical substance as Illustrated In Figure 17. The third stage, characterization of the exposed population by age and sex distribution, Is the subject of Subsection 4.4. This stage would only be used If It were determined that a chemical substance had a specific effect on a particular age or sex group or that a particular group was more highly exposed. Examples of the use of the methods In this section of the report are presented In Appendix A-3. 4.2 Identification of Exposed Populations Exposed populations can be Identified either through knowledge of the sources of chemical contamination or by examination of monitoring data. 89 90 Figure 17. Three-stage Framework for the Enumeration and Characterization of Populations Exposed to Chemical Substances via the Consumption of Food The former Is a "materials balance" approach and comprises three types of sources Identifiable by an examination of a substance's use and release Information: 1. Sources that result from agricultural practices (e.g., pesticide application, fertilization, growth hormones). 2 . Sources related to processing and packaging procedures (e.g., contaminants Introduced during canning, contaminants In food preservatives, leaching of contaminants from packing). 3. Other Identifiable sources (e.g., ocean dumping, Industrial effluents, contamination of animal feed during Industrial processing). Monitoring data may Identify food Items with contamination of unknown origin. The "Market Basket Surveys" of the Food and Drug Administration (DHEW 1975) are examples of monitoring data surveys that may Identify contaminated food Items, the consumers of which are the exposed population. Comprehensive population Identification must consider all three source types as well as available monitoring data. This Identification will be conducted on a chemical-specific basis In the exposure assessment process. The general procedure for Identification Is presented In Method 4 - 1 . 4.3 Methods for the Enumeration of Exposed Populations Enumeration of the population eating a particular food Item Is straightforward; however, only a fraction of that population may consume contaminated food. Information on the geographic distribution of food Items following harvest and packaging or processing Is not available. Consequently, enumeration of the actual exposed population Is not possible. Estimation of the population range In which the actual exposed population exists, however. Is possible. The upper limit of the population range Is equal to the total population that consumes a food Item. The lower limit of the population range, based on the assumption that the consuming population Is directly proportional to the quantity of the food Item contaminated, can be estimated by multiplying the upper limit of the range by the percentage of the food Item contaminated (e.g., the percentage of the food Item grown In a particular geographic area, raised by a particular agricultural practice, processed or packaged by a particular procedure). The data bases and Information sources that provide data and the methods to calculate the exposed population range are discussed In the following subsections according to the categories for Identifying the exposed populations. 91 Method 4-1. Generalized Procedure for Identifying Populations Exposed to Chemical Substances via the Ingestion of Food Step 1 Obtain all available monitoring data for the substance being assessed. Monitoring data for food items provide positive identification of exposure; the population that consumes the food item is an exposed population. Step 2 Examine the uses of the substance being assessed. If it is used in an agricultural practice, the food items on which it is used may be contaminated. If it is used in a food processing procedure or in a packaging material, the food items processed or in contact may also be contaminated; the population that consumes the potentially contaminated food item is an exposed population. Step 3 Examine the sources of the substance in the ambient environment. Knowledge of these sources, coupled with knowledge of the fate and transport of the substance in the environment, leads to the identification of the potentially contaminated food item; the population that consumes the food item is an exposed population. 92 4.3.1 Enumeration of Populations Exposed as a Result of Agricultural Practices Enumeration of the population exposed to a chemical substance as the result of consuming a food Item contaminated from an agricultural practice requires two steps. The Investigator must first ascertain the size of the population that consumes the food Item. This Is the upper limit of the range of the exposed population. The percent of the total quantity of the food Item that Is produced via a specific agricultural practice must then be determined. This percentage multiplied by the number for the total consuming population yields an estimate of the lower limit of the range of the exposed population. Values for the percent of the U.S. population that consumes a specific food Item are available for some food Items from the U.S. Department of Agriculture (USDA) Food Consumption Surveys. USDA Food Consumption Surveys are conducted approximately every 10 years. The most recent survey was In 1977-78, but the complete data reports for the 1977-78 survey have not yet been released. Therefore, the Investigator must use data collected In the 1965-66 survey. Food Consumption of Households In the U.S.. Seasons and Year 1965-66 (USDA 1972) presents data on food consumption by households In the 48 conterminous states for the period from April 1965 to March 1966. The percent of 15,112 households using selected food Items for a seven-day period prior to the Interview Is presented. The food Items for which data are available represent a wide range of major food groups. The households surveyed were scientifically selected to represent a self-weighting sample of housekeeping households In each of four census regions during each of the four seasons. Excluded from the survey were those households In which no member ate as many as 10 meals from the household food supply during the seven days preceding the Interview. Food Consumption of Households In the United States. Seasons and Year 1977-78 . the most updated version of the 1972 USDA report. Is expected to become available In mid 1983. Food Consumption of Households In the U.S.. Spring 1977 (USDA 1982) presents preliminary data on food consumption of households In the 48 conterminous states during the period from April to June of 1977. Like the 1965-66 survey, this one presents the percent of 15,000 households using food Items for a period of seven days prior to the survey. Unlike the survey of 1965-66 (USDA 1972), the survey of 1977-78 (USDA 1982) Included households regardless of the number of meals eaten away from home. 93 Information used to obtain values for the percent of a food Item produced via a specific agricultural practice or In a specific geographic area Is available for select food Items from two data sources. The 1978 Census of Agriculture. U.S. Summary (Bureau of the Census 1982a) presents statistics for the leading states and counties for select agricultural products based on data obtained from the Census of Agriculture. More detailed Information was obtained for farms with sales of $2,500 or more than for farms with less gross sales. Statistics on value of agricultural products sold, number of acres harvested, and quantity harvested are Included. Agricultural Statistics 1978 (USDA 1978) also presents data for production and value of select agricultural products and utilization (e.g., fresh, frozen, canned, dried) of quantities sold. Some statistics for states are Included. If the quantity of a food Item harvested from a specific geographic region Is desired and Is not Included In either of these two sources, the Information, If available, can be obtained by contacting the Statistical Reporting Service-Crop Reporting Board of the United States Department of Agriculture ((202) 447-4020). The basic steps for enumerating populations exposed to chemical substances via the Ingestion of food contaminated by some form of agricultural practice Is presented In Method 4-2. The approach can be used for virtually any situation. 4.3.2 Enumeration of the Populations Exposed as a Result of Processing and Packaging The procedures for enumerating the population exposed to a chemical substance as a result of consuming a food contaminated during processing and packaging are similar to the procedure discussed In Section 4.3.1. If a food Is contaminated during a processing procedure (e.g., canning, freezing, drying), the Investigator must determine the percent of the U.S. population that consumes the processed food Item. This percentage Is multiplied by the total 1980 U.S. population to determine the consuming population. If the chemical substance contaminating the processed food Is generic to all methods for producing the processed food Item, then the exposed population Is equal to the consuming population. If, however, the chemical substance Is specific to only certain methods, then the consuming population Is the upper limit of the range of the exposed population. To determine the lower limit of the range of the exposed population, the Investigator must determine the fraction of the food that undergoes the specific processing method; this fraction Is multiplied by the consuming populations. 94 Step 1 Step 2 Step 3 Step 4 Method 4-2. Enumeration of Populations Exposed as a Result of Agricultural Practices Determine the percentage of households that consume a specific food item by consulting Food Consumption of Households in the U.S.. Spring 1977 (USDA 1982) . Statistical evaluation of seasonal data by USDA (1972) indicates that household food consumption at home in the spring is more representative of average consumption during the year than is consumption in the summer, fall, or winter. Food Consumption of Households in the U.S., Seasons and Year 1977-78 . the best information source, will be published in mid 1983. Multiply the percentage determined in Step 1 by the total U.S. resident population in 1980 of 226,500,000 (Bureau of the Census 1982b) to calculate the consuming population or the upper range of the exposed population. Define the contaminated area by county, and determine the percentage of the total quantity of the food item harvested from the geographic area subjected to the agricultural practice by consulting the 1978 Census of Agriculture (Bureau of the Census 1982a) and Agricultural Statistics (USDA 1978). If the information needed is not in this report, contact the USDA, Statistical Reporting Service - Crop Reporting Board ((202) 449-4020). Multiply the fraction derived in Step 3 by the value calculated for the consuming population in Step 2. The resulting value is the estimated lower limit of the exposed population. 95 The technique for enumerating the population exposed to a chemical substance In food as a result of packaging Is the same as that discussed for exposure from processing. The consuming population (l.e., the upper limit of the exposed population) Is estimated first. The Investigator determines what fraction of the food undergoes a specific packaging procedure and then multiplies that fraction by the population estimated to consume the food Item to estimate the lower limit of the range. The following paragraphs discuss the sources of Information for the data needed to perform these calculations. The report Food Consumption of Households In the United States. Spring 1977-78 (USDA 1982) should be used to obtain values for the percentage of the U.S. population that consumes select food Items. This data source has been discussed In detail In the previous subsection. This report also Includes data on processed food consumption for select food Items (e.g., canned peas, frozen peas, powdered milk). There Is no comprehensive source of data reporting the percentage of specific methods and chemicals for processing or packaging materials for specific foods and beverages (e.g., the percentage of meats processed with or without nitrites; the percent of frozen broccoli packaged In cardboard vs. that packaged In plastic film). This Information may be available from the trade association corresponding most closely to the food Item or packaging procedure In question. For a comprehensive listing of trade associations, consult the most recent Issue of the "Encyclopedia of Associations" published by Gale Research, Inc. The procedural steps to enumerate populations exposed to a chemical substance via the Ingestion of food contaminated by processing and packaging are presented In Method 4-3. In some Instances, the contamination from processing or packaging of a specific food Item may result from procedures used by a specific company. The number of people that consume a specific brand of food or beverage can be estimated for select foods and beverages from the Simmons Media Studies Volumes on Food and Food Marketing. Alcoholic Beverages. and Carbonated Soft Drinks and Pet Food (SMRB 1977). EPA-OTS Is In the process of acquiring the latest Simmons Market Research Bureau (SMRB) reports. Volumes for 1976-77 are available In the Washington, D.C. area at the George Mason University Library. The SMRB studies are designed to make It possible for advertisers and agencies to assess the relative values of media In terms of marketing potential for over 500 product and service categories and 3,000 Individual brands. The studies present demographic and lifestyle characteristics, media habits, and product use, based on data collected from one of the largest annual national consumer probability samples taken. Respondents are selected to represent the conterminous U.S. population 18 years of age and older. It should be noted that, for most food Items listed, the number of users Is based on the total U.S. 96 Step 1 Step 2 Step 3 Step 4 Method 4-3. Enumeration of Populations Exposed as a Result of Packaging and Processing of Food Determine the percentage of users of the food from Food Consumption of Households in the U.S. Spring 1977 (USDA 1982). This report contains values for both processed and unprocessed foods. Multiply the percentage (i.e., fraction) obtained in Step 1 by the U.S. population in 1980 of 226,500,000 (Bureau of the Census 1982b) to estimate the consuming population. This is the upper limit of the exposed population. If the chemical substance is generic to all methods for producing the processed food, then the exposed population is equal to the total consuming population. If a chemical substance is introduced to a food item (1) via a specific method for processing or (2) from a packaging procedure or material, investigators must determine what portion of total production for that food item is affected. These data may be difficult to obtain. Food Consumption on Households in the U.S. Spring 1977 (USDA 1977) provides data on the percentage of users of food items prepared by such processes as canning, drying, and freezing. Trade associations that are related to the food item may have this information. Processing and packaging associations (e.g., National Food Processors Association, Washington, D.C.) may also have this information. For a comprehensive listing of trade associations, consult the most recent issue of the "Encyclopedia of Associations" published by Gale Research Corp. Multiply the total consuming population estimated in Step 2 by the percentage determined in Step 3 to estimate the lower limit of the range of the exposed population. If no information on the percentage of the food item packaged or processed by the method causing contamination is obtained in Step 3, the upper limit estimated in Step 2 should be used; however, it should be clearly labeled as a possible overestimate. 97 population of female homemakers (the buyers of the food) and not the total U.S. population 18 years of age and older. The data, however, can be used to approximate household use. Section 5 of this volume, Populations Exposed to Chemical Substances via the Use of Consumer Products, provides greater detail on the use of SMRB data. To enumerate the population exposed as a result of consuming food contaminated by processing or packaging procedures used by a specific company, the general approach described In Method 4-4 should be used. In some cases, data will be reported only for the female homemaker. To extrapolate for the total consuming population, Investigators should (1) refer to SMRB data (which provide the number of persons In the buyer's household) or (2) use a generic multiplication factor of 2.73 persons per household (Bureau of the Census 1982c). 4.3.3 Enumeration of Populations Exposed as a Result of Releases from Other Sources This category Includes all forms of food contamination that are not the result of either an agricultural practice or a processing and packaging procedure. This section concentrates principally, however, on chemical substances Introduced as a result of accidents (e.g., Introduction of PBB to cattle feed In Michigan) and from point source airborne or waterborne effluents (fish contaminated from Industrial discharges, airborne particulates deposited on fruits and vegetables). The source of the chemical substance need not be Identified. The methods In this section also apply to foods from geographically defined areas of contamination which have been Identified from monitoring data. This special case Is discussed In Subsection 4.3.4. The procedure for enumerating the population exposed to a chemical substance as the result of consuming a food Item contaminated from such sources Is similar to the procedures previously discussed. The Investigator must first determine the percent of the U.S. population that consumes the food Item. This percentage Is applied to the total 1980 U.S. population to determine the total consuming population. Next, the percent of the total quantity of the food Item In the U.S. from the geographic area affected by the source of contamination must be ascertained. The product of the total consuming population and the percent of the food Item affected by the source provides an estimate of the lower limit of the exposed population. Four basic food groups may be affected by these sources of contamination: agricultural products, freshwater fish and game, seafood, and home grown foods. The method used to enumerate the exposed population Is different for each of these basic food groups. (1) Agricultural products . To enumerate the U.S. population exposed to a chemical substance as a result of consuming a contaminated agricultural product, the Investigator should use the method for enumerating the population exposed as a result of agricultural practices 98 Method 4-4. Enumeration of Populations Exposed as a Result of Packaging or Processing Procedures Used by a Specific Company Step 1 Identify the affected brand of food, and obtain use data from the Simmons Market Research Bureau reports (SMRB 1977). Users may be reported as total adults or female homemakers. Step 2 Estimate the total consuming population for the food brand. Option 1 - The average number of persons per household is 2.73. Assuming that there is one food shopper per household, multiply the total number of buyers by 2.73 to calculate the exposed population. Option 2 - Simmons data are aggregated by the number of persons in a user's household. (This is fully discussed in Section 5.3.1 of this report.) The calculation is performed as follows: 1 person household = number of buyers x 1 = A 2 person household = number of buyers x 2 = B 3-4 person household = number of buyers x 4 = C 5 or more person household = number of buyers x 6 = D A+B+C+D= total exposed population (estimated conservatively). 99 (see Method 4-2, described In Section 4.3.1). Instead of determining the percent of the total quantity of the food Item harvested from the geographic area subjected to the agricultural practice (Step 3), determine the percent of the food from the geographic area that has been contaminated. (2) Noncommercial fish and game . To enumerate the U.S. population exposed to a chemical substance as a result of consuming contaminated freshwater fish or game, the Investigator can use Information from the fish and game commission of the state In which the contaminated area Is located. The sample population for these surveys comprises hunters and fishermen who have purchased licenses from the state conducting the surveys. Based on Information from the few states contacted, most states conduct surveys of this nature about every five years. An example of the type of survey Information that may be pertinent Is the summary of applicable categories of results Included In the 1975 Fishing Survey conducted by the State of West Virginia (West Virginia ONR 1979). These categories Include: 1 . 2 . Estimated number of fishermen and days fished Estimated number of fishermen and days fished ONR) fished and type of fishing. by type of fishing, by district (WVA 3. Estimated number of fishermen and days fished by river system and major river. 4. Estimated number of fishermen and days fished In lakes and Impoundments. To enumerate the population exposed to a chemical substance as a result of consuming noncommercial freshwater fish or game contaminated, from an Identified source, the Investigator should use Method 4-5. The estimated exposed population obtained In Step 1 of this method underestimates the actual exposed population because It represents the number of licensed hunters or fishermen In a defined geographic area and does not Include all the consumers of the fish or game (such as friends and family members). If It Is assumed that each license represents a household, the exposed population can be estimated, as presented In Step 2, by multiplying the number of licenses by 2.73, the average number of persons per household (Bureau of the Census 1982c). (3) Commercial fish and shellfish . To enumerate the population exposed as a result of consuming seafood contaminated by releases from an Identified source, one must determine the percent of the U.S. population that consumes the food Item. The percent of the total quantity of the food Item from the geographic area affected by the source of contamination must also be ascertained. 100 Step 1 Step 2 Method 4-5. Enumeration of Populations Exposed as a Result of Consuming Noncommercial Freshwater Fish or Game from a Geographically Defined Area of Contamination Obtain the number of licensed fishermen or hunters reported to fish or hunt in the geographically-defined area of contamination by contacting the state fish or game commission. The best source of this information is usually the most recent fish and game survey conducted by the state fish and game commission. Estimate the upper limit of the actual exposed population by assuming that each licensed fisherman or hunter represents a consuming household. Since there are 2.73 persons in the average household (Bureau of the Census 1982c), a rough estimate of the actual exposed population can be calculated by multiplying 2.73 by the number of licensed hunters or fishermen obtained from Step 1. 101 Values for the percent and projected number of Individuals In 1980 who consume the 45 most commonly eaten species of seafood are available In the Report to the National Marine Fisheries Service on Seafood Consumption Patterns by NPD Research Inc. (NPD 1977). Table 16 summarizes the statistics on seafood consumption compiled by NPD (1977). The quantity of the food Item from the geographic area affected by the source of contamination can be obtained from a computerized data base maintained by the National Oceanic and Atmospheric Administration (NOAA) for all states except Maryland. The NOAA data base Includes catch records by NOAA area or by county for oysters, flnflsh, and crabs. Catch records for clams are available only for descriptive areas such as "Mouth of the Patuxent River." Catch records for clams, oysters, and flnflsh are available In the form of dally records for the years 1975 through 1981. Catch records for crabs are available only for 1981. For Information on retrieving data from the NOAA computerized data base, contact Daryl Christensen of the National Marine Fisheries Service at (201) 872-0200. For retrieval of data on seafood catches for the Chesapeake Bay, contact Mike Burch of the Statistics Division of the Maryland Department of Natural Resources at (301) 269-3784. There Is no charge to government agencies for either of these services. For Information on the total quantity of seafood species caught In the United States, the statistics on commercial fishery landings published In Fisheries of the United States. 1980 by the National Marine Fisheries Service of NOAA (NOAA 1981) can be used. The general approach for enumerating the population exposed to a chemical substance as a result of consuming seafood contaminated by releases from an Identified source Is presented In Method 4-6. Table 16 Includes a few freshwater fish species. Method 4-6, however, cannot be used to enumerate the population exposed as a result of consuming these fish species. To obtain such Information, Investigators must ascertain the quantity of freshwater fish caught annually from the geographically defined area of contamination. Although the quantity of select seafood Items caught from a geographically defined area of contamination can be obtained from computerized NOAA data, no similar data base for freshwater fish was found. (4) Home grown fruits and vegetables . In 1977, It was estimated that 44 percent of U.S. households (32 million households) had home gardens (USEPA 1980). Furthermore, 80 percent of these 32 million households had gardens every year, and 40 percent of these 32 million households had had gardens for 11 years or more. The consumption of home grown foods, therefore, may be a significant route of exposure, both short- and long-term, If the garden Is located near a point source of contamination, such as a smelter. 102 Rank 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 Table 16. Ranking of Seafood Species by Percent of Individuals Consuming and Projected 1980 Consuming Population Species Number of Percent Projected number of users of sample total 1980 population size (X 1,000) Total sample 25,947 100.0 226,000 Total seafood 25,165 94.0 204,000 Tuna, light 16,817 64.8 146,000 Shrimp 5,808 22.4 50,600 Flounders 3,327 12.8 28,900 Ocean Perch 2,519 9.7 21,900 Salmon 2,454 9.5 21,500 Clams 2,242 8.6 19,400 Cod 1,492 5.6 12,700 Pollock 1,466 5.6 12,700 Haddock 1,441 5.6 12,700 Herring 1,251 4.8 10,800 Oysters 1,239 4.8 10,800 Crab, other than King 1,168 4.5 10,200 Trout (Freshwater) 970 3.7 8,360 Catfish (Freshwater) 876 3.4 7,680 Bass 826 3.2 7,230 Lobster, Northern 675 2.6 5,880 Mackeral, Other than Jack 616 2.4 5,420 Halibut 574 2.2 4,970 Scallops 526 2.0 4,520 Whitefish 492 1.9 4,290 Snapper 490 1.9 4,290 Hake 392 1.5 3,390 Pike 390 1.5 3,390 Lobster, Spiny 350 1.3 2,940 Smelt 328 1.3 2,940 Perch (Freshwater) 268 1.0 2,260 Bluegills 265 1.0 2,260 Bluefish 236 0.9 2,030 Crappie 228 0.9 2,030 Trout (Marine) 220 0.8 1,810 Bonito 148 0.6 1,360 Crab, King 130 0.5 1,130 Mullet 97 0.4 904 103 Table 16. (Continued) Rank Species Number of Percent Projected number of users of sample total 1980 population size (X 1,000) 34 Spot 91 0.4 904 35 Croaker 76 0.3 678 36 Anchovies 75 0.3 678 37 Rockfish 75 0.3 678 38 Catfish (Marine) 70 0.3 678 39 Groupers 68 0.3 678 40 Carp 64 0.2 452 41 Buffalofish 60 0.2 452 42 Sunfish 60 0.2 452 43 Drums 58 0.2 452 44 Scup 55 0.2 452 45 Other Shellfish 54 0.2 452 46 Abalone 48 0.2 452 47 Squid and Octopi 45 0.2 452 48 Swordfish 41 0.2 452 49 Butterfish 39 0.2 452 50 Shad 39 0.2 452 51 Dolphin 34 0.1 226 52 Tuna, white 22 0.1 226 53 Mackeral, Jack 13 0.1 226 54 Snook 13 0.1 226 55 Tilefish 11 0.1 226 56 Blue Crab 11 0.1 226 57 Pompano 10 0.1 226 58 Kingfish 8 0.1 226 59 Sablefish 7 0.1 226 60 Sharks 3 0.1 226 Source: NPO 1977, NOAA 1978. 104 Step 1 Step 2 Step 3 Method 4-6. Enumeration of Populations Exposed as a Result of Consuming Seafood from a Geographically Defined Area of Contamination Determine the number of users of the seafood by consulting the information in Table 15 on projected number of individuals in 1980 who consumed the seafood item of concern. Determine the percentage of the total quantity of the item caught for sale in the U.S. which is from the geographically defined area of the source of contamination. This can be accomplished by computing the quantity of the seafood caught annually from the geographically defined area of contamination based on computerized NOAA data. Next, the total quantity of the seafood species caught in the United States annually must be obtained from commercial fishery landings published in Fisheries of the United States. 1980 (NOAA 1981). The fraction of the total quantity of the seafood species caught for sale in the U.S. which is from the geographically defined area of the source of contamination can be computed by the following formula: quantity of the seafood item caught from the _geographically defined area of contamination_ total quantity of the seafood item caught in the United States Multiply the fraction computed in Step 2 by the value determined for the consuming population determined in Step 1. 105 Table 17 presents data for the year 1977 on the percent of urban, rural non-farm, and rural farm households with gardens as well as the percent of the U.S. population for each category. These geographic categories are consistent with the census geography of the Bureau of the Census. Table 18 presents data on the percentage of total households growing, freezing, canning, or preserving selected home grown fruits and vegetables. The data presented In these two tables can be used to enumerate local populations exposed to a chemical substance via the consumption of Inadvertently contaminated home grown fruits and vegetables. Method 4-7 presents that procedure. 4.3.4 Enumeration of Exposed Populations by the Use of Monitoring Data The source of contamination of a food Item will frequently be unknown. The fact that contamination exists, however, can be positively confirmed through monitoring data collected. Market Basket Surveys such as those conducted by the Food and Drug Administration (DHEW 1975) exemplify how food contamination can be detected. The consumers of the food Item In which the substance has been detected are the exposed population. Monitoring data can be used to predict the number of people consuming foods containing a chemical substance. The method extrapolates data on the frequency of detection of the substance. The accuracy achieved by this tool depends on the form, representativeness, and sample size of the data. The procedure for enumerating population by use of monitoring data Is presented In Method 4-8. The assumptions Inherent In this very gross estimation Include the assumption that the data are Independent of the source of the contamination or that the data represent the total food supply from all geographic areas. Obviously, these assumptions limit the usefulness of the method; It should only be used In the absence of more refined data. The use of monitoring data to estimate the exposed population Is limited In all cases by two assumptions. The sample size must be large enough that the frequency of detection approximates the frequency of occurrence, and Individuals who consume food containing the chemical at levels below the detection limit are not Included In the exposed population. Exposure below the detection limit may, however, be significant for certain chemicals. 106 Table 17. Percent of Households, U.S. Population, and Household Size in Urban, Rural Non-Farm, and Rural Farm Areas with Home Fruit and Vegetable Garden in 1977 Urbanization Percent households with garden Household size (number of persons) Percent of total U.S. population Urban 43 3.17 32 Rural non-farm 41 3.44 9 Rural farm 84 3.86 3 Source: USEPA (1980). 107 Table 18. Percent Gardening Households Growing, Freezing, Canning, or Preserving Selected Home Grown Fruits and Vegetables, 1975-77 Item 1975 Grown 1976 1977 1975 Frozen 1976 1977 Canned 1975 or Preserved 1976 1977 Vegetables Tomatoes 95 97 91 26 29 26 65 66 58 Beans (green, wax, lima, etc.) 71 69 70 54 49 55 42 35 38 Cucumbers 62 61 59 4 * 2 29 23 29 Peppers 61 60 60 28 28 32 10 11 7 Radishes 59 54 50 * * * * ★ * Green onions (scallions) 58 54 50 2 * 4 1 * * Lettuce 56 55 51 1 * * * * * Onions 52 54 48 3 * ★ 4 * * Carrots 50 46 46 15 12 16 8 9 8 Corn 50 44 49 41 36 39 15 9 11 Squash 45 41 41 21 19 22 8 4 3 Beets 40 42 38 7 7 9 29 29 24 Peas 40 36 38 27 26 31 7 4 7 Turnips 26 25 22 7 6 4 1 1 2 Potatoes 10 37 39 * * ★ * * 3 Cabbage 7 37 40 * * 10 * 2 8 Fruits Strawberries 22 21 22 16 13 14 9 4 3 Apples 20 17 20 11 8 13 15 7 10 Melons 13 15 17 3 * * 1 * * Peaches 13 10 12 7 5 7 10 5 7 Pears 10 7 8 3 * * 10 ★ 1 Rasberries, blackberries, blueberries, etc. 6 10 16 5 7 12 3 4 5 ♦Either not mentioned or mentioned by less than 1 percent of the gardening households surveyed. Source: USEPA (1980). 108 Step 1 Step 2 Step 3 Step 4 Step 5 Method 4-7. Enumeration of Populations Exposed to Chemical Substances via the Consumption of Home Grown Fruits and Vegetables Identify the geographic area contaminated from the source of the chemical substance (e.g., industrial point source, area source). Determine the number of households in the geographic area from General Population Characteristics . Series PC80-1-B (Bureau of the Census 1982b). Multiply the number of households obtained in Step 2 by the percent of households with home fruit and vegetable gardens for the type of urbanization from Table 16. This is the number of households with fruit and vegetable gardens in the area contaminated, the inhabitants of which are the potentially exposed population. Enumerate the exposed population by multiplying the number of households from Step 3 by the household size for the degree of urbanization also available in Table 16. Steps 3 and 4 determined the number of households and individuals that have fruit and vegetable gardens, not the households that grow a specific type of food. If the chemical substance is absorbed by a specific food item, the data in Table 17 can be used. For example, if a pollutant is absorbed specifically by lettuce, the number of households for each population category estimated in Step 3 must be multiplied by 51 percent, the percentage of gardening households that grow lettuce according to the latest available data. These results should then be multiplied by household size (Table 16) to enumerate the exposed population. 109 Step 1 Step 2 Step 3 Step 4 Method 4-8. Enumeration of Exposed Populations by the Use of Monitoring Data Identify the food items contaminated as a result of the monitoring survey results. Enumerate the total consuming population for each of the food items identified. The enumeration procedures of Methods 4-2, 4-5, 4-6, or 4-7 should be used to estimate the consuming population. This is the upper limit of the range of the exposed population (i.e., all consumers of the food item eat some contaminated food). Calculate the frequency of detection from the monitoring data; if detected in 10 of 100 samples, the detection frequency is 10 percent. Multiply the detection frequency by the total consuming population as enumerated in Step 2 to estimate the exposed population. This is the lower limit of the range of the exposed population (i.e., the exposed population consumed only contaminated food). 110 4.4 Ch aracterization of the Exposed Population This subsection describes the data sources and procedures for characterizing the exposed population with respect to age and sex. In most exposure assessments, age and sex characterization will not be necessary. If, however, the chemical substance of Interest has special effects on particular age classes such as children or the elderly, further characterization of the enumerated population Is Indicated. If a chemical substance Is determined to be teratogenic, enumeration of women of child bearing age may be required. Age and sex also Influence the average rate of food Intake and the types of food consumed. Construction of a plausible worst-case exposure scenario for contaminated food may, for Instance, focus on males 19 to 22 years of age; they have the highest average dally food Intake rate (USDA 1980). The simplest and most rapid method of characterizing a large population Is to assume that the age and sex distributions approach those of the total U.S. population. This approach can be used only for very large, generally-defined populations. For example, the population consuming the typical "American Diet" or those who consume groups of major food categories approximate the national distribution. The age and sex distribution by percentage of the total U.S. population has been presented In Table 12 of Section 2.4 of this report (Characterization of Populations Exposed to Chemical Substances In the Ambient Environment). The characterization of populations exposed to chemical substances through the consumption of particular food Items, however, often requires a much more accurate approach; the defined food preferences vary greatly according to particular age and sex, and even by sex within age classes. There are two data sources for characterizing populations exposed to chemical substances via food consumption: USDA's food consumption surveys for Individuals and the Simmons Market Research Bureau reports. The USDA data are applicable to populations eating various types of food, while SMRB marketing Information Is useful for characterizing consumers of specific brands of foods. The Individual food consumption surveys conducted by USDA were designed to be representative of the U.S. population. As a result, the age and sex distribution of the sampled population closely approximates that of the U.S. as a whole. Data on usage are reported for various age and sex groups, as Illustrated In Figure 18, as percentages of the total sample within that group. Percents reported under the column heading for the food of Interest can be applied directly to the total U.S. population for that age/sex classification to characterize the exposed population. Method 4-9 presents the steps to be performed for this type of characterlzatlon. Ill TABLE 1.2b.—MILK, MILK PRODUCTS; EGGS; LEGUMES, NUTS, SEEDS Individuals using 1 in a day, 2 spring 1977 48 States, all urbanizations, all incon.es Sex and age (years) Individuals Milk, milk products Eggs Legumes, nuts, seeds Total ; Milk : Total : , milk drinks : Fluid : Yogurt : milk : : Cream, milk desserts : Cheese Number Males and females Under 1. 3 78 92.2 92.2 60.9 0 6.5 3.6 10.0 14.5 1-2. -264 93.4 90.9 90.5 .6 19.3 21.7 33.3 22.8 3-5. 437 91.7 87.8 85.6 .3 21.8 21.0 33.6 30.7 6-8. 469 93.4 90.5 88.5 1.2 25.0 19.7 24.3 29.4 Males: 9-11. 216 92.9 90.7 87.9 .5 24.3 16.1 26.4 28.0 12-14. 313 90.2 86.3 81.1 .4 23.0 14.5 28.8 27.5 15-18. 400 85.9 77.3 75.7 .7 27.9 20.7 30.4 20.9 19-22. 287 81.6 74.3 69.7 1.3 16.4 26.0 30.1 17.7 23-34. 770 73.8 58.3 53.6 2.9 21.9 28.3 33.7 19.7 35-50. 784 75.8 57.6 56.5 .8 24.1 27.0 39.8 22.5 51-64. 634 77.8 61.8 60.9 1.1 26.2 25.9 40.1 20.5 65-74. 295 81.3 71.2 70.4 .3 29.1 24.8 47.7 15.2 75 and over.... 127 80.7 67.9 66.3 0 25.8 25.2 51.5 20.3 Females: 9-11. 241 92.5 88.8 86.8 0 25.6 16.8 19.7 30.6 12-14. 309 86.6 80.9 76.2 .3 22.7 22.8 23.4 21.0 15-18. 402 85.4 74.7 69.2 2.0 24.2 24.9 25.5 18.0 19-22. 337 78.1 65.1 62.3 1.9 18.3 26.9 27.2 14.3 23-34. 949 74.3 58.6 54.5 3.4 18.8 28.5 31.3 18.2 35-50. 942 73.0 55.2 52.6 2.8 21.4 28.0 28.0 17.4 51-64. 792 73.9 58.2 56.0 2.5 21.1 26.8 33.2 17.1 65-74. 377 80.3 68.4 67.3 2.7 26.9 25.6 32.9 11.7 75 and over.... 197 84.2 73.1 71.4 2.0 28.4 24.5 32.2 9.6 All individuals.. 5 9,620 80.7 68.8 65.9 1.7 22.8 24.7 31.9 20.2 1 User is an individual reporting a specified food item. 2 Based on 24-hour dietary recall of day preceding interview. 3 Excludes 36 breast-fed infants. ^Excludes 4 breast-fed infants. Excludes 4C breast-fed infants. Source: USDA (1980). Figure 18. Example Data Summary from National Food Consumption Survey of 1977-78 112 Step 1 Step 2 Step 3 Method 4-9. Characterization of Populations Exposed to Chemical Substances in Types of Food Locate the food item usage data in the USDA (1972, 1980) food consumption surveys for individuals in one day. The more recent (1980) data should be used whenever possible. Apply the "percent using" value for each age/sex category to the corresponding total population in that category (from Table 13). Compare "percent using" for the total sample as reported in the one-day survey to the "percent using" reported in the USDA (1982) one-week household consumption survey. This comparison will provide a qualitative indicator of the one-day survey’s accuracy. If the data values are significantly different (i.e., the individual consumption data in USDA (1972, 1980) underestimates the consuming population), the total consuming population should be estimated using household data (USDA 1982) as presented in Step 1 of Method 4-2. The percentage of the total consuming population that is in the age or sex group of interest should be determined from the individual survey data (USDA 1972, 1980). This is calculated by aggregating the consumers for each age or sex class and dividing by the total consuming population of the individual sample. This percentage should then be applied to the total consuming population determined from the household data to characterize the exposed population (See Appendix A-3, problem 7). 113 Though the sample population Is representative of the age and sex distribution of the U.S. population, a limitation Inherent In the one-day survey biases the data. Consumption during one day may not be representative of normal eating patterns; this generally results In an underestimate of the number of consumers of specific foods. The one-day survey Is, however, the only source of consumption data that presents the Information by age and sex. Method 4-9 provides an approach to determine the accuracy of the Individual consumption data and a procedure that can be used to eliminate the error. Age and sex distributions of populations that consume specific brand names of food can be derived from the Simmons Market Research Bureau Reports. The most recent version of this report Is available In EPA-OTS. Reports for the years 1977 through 1978 are available In the Washington, D.C., area at the George Mason University Library. SMRB reports present demographic data for most major brand name food Items. Section 5 of this report discusses the use of SMRB data to characterize populations using consumer Items; that discussion Is equally relevant to food consumption. In essence, SMRB presents Information on the frequency that sample households Include children within certain age groups. The ages of the adults In the household are similarly reported as frequencies. A general age distribution can thus be compiled easily for any Item; the proportion of males and females can be assumed. 114 4.5 References Bureau of the Census. 1982a. 1978 Census of Agriculture. Volume 1. United States - State and County Data. Washington, DC: U.S. Department of Commerce. Bureau of the Census. 1982b. 1980 Census of population. General population characteristics, U.S. Summary. Washington, DC: U.S. Department of Commerce. U.S. Government Printing Office. Bureau of the Census. 1982c. Statistical abstract of the United States. National data book and guide to sources. Washington, D.C.: U.S. Department of Commerce. DHEW. 1975. Department of Health, Education and Welfare. Compliance program evaluation. FY 1874 heavy metals In foods survey. Washington, DC: Bureau of Foods. NOAA. 1978. National Oceanic and Atmospheric Administration. Report on the chance of U.S. seafood consumers exceeding the current acceptable dally Intake for mercury and recommended regulatory controls. Washington, DC: U.S. Department of Commerce, National Marine Fisheries Service, Seafood Quality and Inspection Division. NOAA. 1981. National Oceanic and Atmospheric Administration. Fisheries of the United States, 1980. Washington, DC: U.S. Department of Commerce, National Marine Fisheries Service. NPD. 1977. NPD Research. Report to National Marine Fisheries Service on seafood consumption patterns. Washington, D.C. SMRB. 1977. Simmons Market Research Bureau Inc. 1976/1977 Selective markets and media reaching them. New York, NY: Simmons Media Studies. USDA. 1972. U.S. Department of Agriculture. Food consumption of households In the U.S., seasons and year 1965-66. Washington, DC: Agricultural Research Service. USDA. 1978. U.S. Department of Agriculture. Agricultural Statistics 1978. Washington, DC: United States Government Printing Office. USDA. 1980. U.S. Department of Agriculture. Food and nutrient Intakes of Individuals In 1 day In the United States, Spring 1977. Nationwide food consumption survey 1977-78. Preliminary report No. 2. Washington, DC: Science and Education Administration. 115 USDA. 1982. U.S. Department of Agriculture. Food consumptions: households In the United States, Spring 1977. Nationwide food consumption survey 1977-78, report no. H-l. Washington, DC: Consumer Nutrition Center, Human Nutrition Information Service. USEPA. 1980. U.S. Environmental Protection Agency. Dietary consumption distributions of selected food groups for the U.S. population. Washington, DC: Office of Pesticides and Toxic Substances, Office of Testing and Evaluation. EPA 560/11-80-012. West Virginia DNR. 1979. West Virginia Department of Natural Resources. 1975 Fishing Survey. Division of Wildlife Resources. 116 5. POPULATIONS EXPOSED TO CHEMICAL SUBSTANCES VIA THE USE OF CONSUMER PRODUCTS 5.1 I ntroductlon This section presents methods for enumerating and characterizing populations exposed to chemical substances via the use of consumer products. The methods described are applicable to new and existing substances In consumer products. Figure 19 Is a flow diagram of the three-stage method framework. Included In the diagram are some of the major data sources used. The Identification of the exposed population Is discussed only briefly In this report (Subsection 5.2). The process Is straightforward and relies primarily on materials balance Information and data generated by the consumer exposure assessment methods report (Volume 7). Enumeration of exposed populations may Involve one or more steps and a variety of data sources. Subsections within Section 5.3 describe the sources of data applicable to enumeration of consumers and methods for utilizing and refining available data. The age and sex of the exposed consumers affect the physiological parameters (l.e., breathing rate, skin surface area) that determine exposure; they also Identify sensitive subpopulatlons (e.g., women of child-bearing age). Detailed exposure assessments may require that populations be described by age and sex distribution. Subsection 5.4 discusses methods of characterizing exposed consumer populations. Examples of the use of the methods In this section are presented In Appendix A-4 of this report. 5.2 Identification of Exposed Populations The Identification of populations exposed to chemical substances via the use of consumer products (Method 5-1) necessitates a listing of all products containing the chemical In question. The Information needed to compile such a list Is derived from the materials balance for existing chemicals, from Information submitted by Premanufacturing Notice (PMN) petitioners, and through literature searches. Exposure assessments for most existing chemicals Include a materials balance delineating the uses for that chemical, as well as the amount going to each use. A PMN submittal provides the corresponding Information for new chemicals. PMNs are, however, usually Incomplete; use Information Is often general, and not all the potential uses of a new chemical will be considered. Volume 7 of this series (methods for assessing consumer exposure to chemical substances) presents methods to predict uses for new chemicals. 117 1=1 118 Figure 19. Three-stage Framework for the Identification, Enumeration and Characterization of Populations Exposed to Chemical Substances in Consumer Products Method 5-1. General Procedure for Identifying Populations Exposed to Chemical Substances in Consumer Products Step 1 Compile a comprehensive list of the consumer products known to or thought to contain the chemical substance by consulting the materials balance or PMN submittal. Step 2 Determine whether all or a portion of the consumer product class contains the chemical; if possible, identify by brand name to expedite enumeration. Step 3 Identify products obviously intended for use by males or females or specific age groups. Step 4 Evaluate each product (using the guidelines in Volume 7 of this series) to determine whether passive exposure is of concern. Consumer product use patterns will identify the passively exposed population (i.e., family or household members). 119 Many types of consumer products are of varied formulation, and only a fraction of the product class (perhaps Identifiable by brand name) may contain the chemical substance. This fact should be established during the population Identification phase. For example, formaldehyde Is used In some shampoos as a preservative; In order to define and enumerate the population exposed to formaldehyde In shampoo, one must determine what fraction or brands of the product class (shampoo) contain the chemical (formaldehyde). Methods for that purpose are presented In Subsection 5.3. Some products may cause exposure not only to the user (active exposure) but also to others In the vicinity (passive exposure). Volume 7 presents some guidelines for Identifying products that may cause passive exposure. Generally, passive exposure to consumers results from the use of household or personal care products; the passively exposed population Is the household of which the user Is a member. Subsequent sections address the concept of enumerating those passively exposed In households. 5.3 Methods for the Enumeration of Exposed Populations The effort required to enumerate consumers exposed to a particular product depends on two factors: (1) the availability of data specific to that product and (2) whether both active and passive exposure to the substance are Involved. The following subsections guide the assessor In obtaining the available data and present methods for their use. 5.3.1. Enumeration of Exposed Populations via Simmons Market Research Bureau Reports Simmons Market Research Bureau (SMRB) Is a market research corporation that collects Information on the buying habits of the population through questionnaires administered to a nationwide panel of consumers. The Simmons studies, "Selective Markets and the Media Reaching Them" (SMRB 1982), are designed to serve retailers, advertising agencies, and the media by providing up-to-date, comprehensive Information on current and potential sales markets of consumer products. SMRB data applicable to enumerating exposed consumer populations are contained In 29 volumes organized by product category. Table 19 lists the 29 product categories. These volumes contain Information on market share, the number of buyers, and buyer demographics for over 500 consumer products. Table 20 Is an alphabetical Index of Individual products and services Investigated by SMRB. 120 Table 19. Simmons Market Research Bureau Product Categories and Services Provided by Volume Volume Number Volume Title P-1 Automobi les P-2 Cycles, Trucks, Vans & Tires Automotive Products & Services P-4 Travel P-5 Banking Investments, Memberships & Public Activities P-6 Insurance & Credit Cards P-7 Books, Records, Tapes, Stereo & TV P-8 Appliances, Sewing & Garden Care P-9 Home Furnishings & Home Improvements P-10 Sports & Leisure P-11 Restaurants, Stores & Grocery Shopping P-12 At Home Shopping, Yellow Pages, Florists & Telegrams P-13 Jewelry, Wristwatches, Luggage & Men's Apparel P-14 Women's Apparel P-15 Tobacco Products & Photography P-16 Distilled Spirits & Mixes P-17 Malt Beverages & Wine P-18 Coffee, Tea, Soft Drinks, Juices & Bottled Water P-19 Dairy Products, Spreads, Cookies & Desserts P-20 Cereals, Rice, Pasta, Pizza, Fruits & Vegetables P-21 Soup, Meat, Fish, Condiments & Dressings P-22 Chewing Gum, Candy & Snacks P-23 Soap, Laundry & Paper Products & Kitchen Wraps P-24 Household Cleaners, Roan Deodorizers & Pet Foods P-25 Health Care Products & Remedies P-26 Oral Hygiene Products, Skin Care & Deodorants P-27 Hair Care & Shaving Products P-28 Women's Beauty Aids, Cosmetics & Personal Products P-29 Games & Toys, Children's & Babies' Apparel & Specialty Products P-30 Relative Volume of Consumption Source: SMRB 1982. 121 Table 20. Alphabetical Index of Products and in the 1982 SMRB Study A Aches, Muscle, Head or Back Active Participation in Sports Activities, Public Adhesive Bandages Adult Education Courses After Shave Lotion & Cologne Ailments Air Conditioner, Room Air Conditioning, Central Air Filters Air Freshener Sprays & Room Deodorizers Airlines Alarm, Burglar Alarm, Smoke/Fire Detector Ale Allergies Allergy & Cold Remedies Aluminum Foil American/Pasteurized Processed Cheese Ammunition, Factory Loaded Amplifier/Receiver/Tuner, Stereo Annual Mileage Driven Anti-Freeze Anti-Perspirants & Deodorants Aperitif & Specialty Wines Apparel/Men's, Women's & Children's Archery Arthritis or Rheumatism Asthma Relief Remedies Athlete's Foot Athlete's Foot Remedies Attendance at Sports Events Auto Insurance Auto Loan Automatic Dishwasher Automatic Dishwashing Detergent Automatic Drip Coffee Maker Automatic Garage Door Opener Automatic Washing Machine Automobiles Auto Racing or Rallying B Baby Foods Baby Formula, Liquid Baby Lotion S- Babv Oil Baby Nursers Pabv Oil & Baby Lotion Baby Powaer Babv Shampoo Backache Bacupacking/Camoing Equipment Backpacking or Hiking Baggage or Luggage Bags. Garbage & Trash Can Line's, Plastic Bags, Sandwich or Food. Plastic Baked Beans 3anoages Adhesive Banking & Investments Barbecue & Seasoning Sauces, Bottled Bath Oil & Other Bath Additives Bathroom Cleaners (Household Cleaners) Bathroom Plumbing Fixtures Batteries, Car Battery or Electric Shaver Bedroom Furniture Beds Beer Bench/Table Circular Saw Bicycle Bicycling Biscuits or Treats, Dog Blankets, Electric Blankets, Other (Not Electric) Blank Tape Cartridge, Cassette. Reel Bleach Blended or Rye Whiskey Blender, Electric Blouse/Shirt, Women's Blusher Boats Boating Body & Hand Cream, Lotion or Oil Bonds Bonnet-Type Hair Dryer Book Clubs Books Boots, Hiking or Climbing Boots, Leather Boots, Ski Bottled Natural Spring or Mineral Water Bouillon Cubes & Dry Soup Mix Bourbon Whiskey Bowling Bowling Bail Bowling Shoes Brake Lining Pads Brandy & Cognac Brassiere Bread Breakfast Cereals Breakfast Drinks, Powdered Fruit Flavored Breath Fresheners Built in Automatic Dishwasher Burglar Alarm Bus Companies, Domestic 8usmess Club Membership Business Purchase Decisions Bus-Tvpe Motor Home Butter Buvmg Style C Cabinets, Kitcnen Cables. Telegrams & Wires Cake Mixes, Drv Cakes, Pies & Pastries, Frozen Calculator Cameras Services Measured Camper, Tent (Folding) Camper or Travel Trailer, Towable Camper, Truck Mounted Camping/Backpacking Equipment Camping Trips, Overnight Camping Vehicles Canadian Whisky Candy Bars & Packages, Regular Size Candy, Fun, Miniature & Snack Size Candygram Candy, Hard Roll Canned Cat Food Canned Dog Food Canned or jarred Fruits Canned Ham Canned Macaroni & Spaghetti Products Canned Soup Canned Tea Canned Tuna Canned Vegetables, or jarred Canning Jars & Lids Canoe Canvas Shoes Car Batteries Car Leasing Carpeting Carpet Squares Car Polish & Wax Car Rental Cars Cartridges, Blank Tape Cartridges, Pre-Recorded Tape Casseroles & Entrees (Frozen Main Courses) Cassette Deck Cassette, Video Recorder/Player Cassettes, Blank Tape Cassettes, Pre-Recorded Tape Casual/Leisure Suit Cat Food Cat Ownership Catsup CB Base Unit CB Mobile Radio Ceiling, Floor or Wall Insulation Ceiling Tile, Residential Central Air Conditioning Cents-Off Coupons Cereals Certificates of Deposit/Savings Certificates Chain Saw Champagne, Cold Duck & Sparkling Wines Check Guarantee Caro Checking Account Checks, Travelers Cheese Chewing Gum Chewing Tobacco Chilqren s Ciothing Chiidren s Fever Reducers & Pain Relievers Children s Shoes 122 Children's Vitamins China, Fine Chips, Corn & Tortilla, & Snacks Chips, Potato Christmas Club Church Board Membership Cigarette Rolling Paper Cigarettes Cigarillos & Little or Small Cigars Cigars Circular Saw Citizens Band Base Unit Citizens Band Mobile Radio Civic Club Membership Cleaners, Dram Cleaners. Household (Including Bathroom/Kitchen) Cleaners, Oven Cleaners, Rug Cleaners. Toilet Bowl Cleaners, Window Cleansing Creams & Lotions Cleansing Wipes. Pre-Moistened. For Babies Climbing or Hiking Boots Cloth Coat. Women's Cloth Diapers Clothes Dryer Clothing, Men's Clothing, Women's Clothing, Children s Club, Book Club, Civic Club. Country Club, Health Club. Record & Tape Club, Religious Club, Tape Club, Veterans Coats, Men's Coats, Women's Cocktail Mixes. Prepared Cocktail Parties Coffee Coffee Maker Cognac & Brandy Coin Collecting Coins, Gold Coins, Silver Cola Drinks Cold Cuts Cold Duck, Champagne & Sparkling Wines Cold & Allergy Remedies Colds College or School Board Memoership Cologne & After Shave Lotion Cologne & Penume Coloring Products. Hair Comb. Hair-Styling, Electric ComrortersiQuiits Common Stock Comoact or Console Stereo Compactor. Trash. Eiectric Compact Pick-Uo Truck Complete Dinners Frozen (TV Dinners! Complete PacKagea Preoarea Disnes i Dinner Mixes Comoute' Home Console or Compact Ste r eo Constipation Contact Lenses Convection Oven Convenience Stores & Supermarkets Cooker. Pressure Cookies (Ready-to-Eat) Cooking for Fun Cooking or Salad Oil Cooking Spray, Non-Stick Cookware Set, Metal Cordials & Liqueurs Corn & Tortilla Chips & Snacks Costume Jewelry Cottage Cheese Cotton Swabs Cough Drops Coughs Cough Syrup Countries Visited—Foreign Travel Country Club Membership Coupons, Cents-Off Courses For Adult Education Crackers Cream, Lotion or Oil. Hand & Body Cream, Shave Cream Substitutes, Non-Dairy Credit Cards Crystal Ware Cross Country Snow Skiing Cubes, Bouillon, & Dry Soup Mix Cups. Disposable Curler Set, Hair, Electric Curtains/Draperies D Decaffeinated Instant or Freeze-Dried Coffee Deck. Cassette Deck. Eight Track (Record & Play) Dental Insurance Dentures Deodorants & Anti-Perspirants Deodorizers, Room, & Air Freshener Sprays Department Stores & Discount Stores Depilatories Desk Top Calculator Dessert Pies, Cakes & Pastries. Frozen Desserts, Flavored Gelatin Dessert Wines. Port i, Sherry Detector. Smoke/Fire Detergent. Dishwashing Detergents & Soaps. Laundry Dial Face Wnstwatch Diamond Ring Diapers Diarrhea Diesel Fuel & Gasoiine Diet Control Diet or Low Calorie Carbonated Sort Drinks Digital Face Wnstwatch Dining Room Furniture Dinner Mixes. Complete Pacxagea. 4 Dishes Dinner Parties Dinners. Frozen Complete (TV Dinners' Dinnerware Discount Stores & Department Stores Dishwasner Automatic Disnwasher Detergent. Automatic Dishwashing Liquid Disposable Cups Disposable Diapers Disposable Lighters Disposable Razors Disposal, Garbage Dog 8iscuits or Treats Dog Food Dog Ownership Domestic Beer, Light/Low Calorie Domestic Beer, Regular Domestic Travel Domestic Wine Door Opener, Garage Doors, Storm, or Windows Door-to-Door Sales Douches 4 Suppositories, Feminine Hygiene Dough Products, Refrigerated Downhill Snow Skiing Draft Beer Drain Cleaners Draperies/Curtains Drawing, Painting, Sculpting Dresses or Suits, Children's Dresses, Women's Dressing, Salad Dress or Regular Shirt, Men's Drill, Electric Drink Mixers, Prepared, Without Liquor Drinks. Breakfast, Powdered Fruit-Flavored Drinks. Fruit, 4 Juices Drinks, Mixed, Prepared With Liquor Drinks, Soft Drinks, Soft. Powdered Drip Coffee Maker, Automatic Drive-In 4 Fast Food Restaurants Driver's License Driving Driving, Type of Vehicle Driven Dry Cake Mixes Dry Cat Food Dry Dog Food Dryer, Clothes Dryer, Hair Dry Mix Salad Dressing Dry Soup Mix 4 “Bouillon Cubes Dungarees or Jeans. Children s E Eczema Education Courses for Adults Eight Track Deck (Record 4 Play) Electric 4 Battery Shaver Electric Blankets Electric Blender Electric Chain Saw Electric Circular Saw Electric Clothes Drver Electric Cortee Matter Electric Drill Electnc Food Processor Electric c rv Pan Electric Grill Electric Hair Curler Set Electnc Hair Drver Electric Hair-Styling Como Electnc Jig/Saore Saw Electnc iuice r 123 Electric Mixer Electric Power Mower Electric Range or Stove Electric Refrigerator Electric Sander Electric or Battery Shaver Electric Steam Cooker Electric Toothbrush Electric Trash Compacter Electric Typewriter, Portable Encyclopedia Entrees 4 Casseroles (Frozen Main Courses) Exterior House Paint 4 Stains Eyeglasses Eye Liner Eye Shadow F Fabric Softeners Face Powder Facial Moisturizers 4 Cleansing Creams Facial Tissues Factory Loaded Ammunition Family Restaurants 4 Steak Houses Farm Ownership Fast Food 4 Drive-In Restaurants Feminine Hygiene Douches 4 Suppositories Fertilizers Fever Fever Reducers. Children's, 4 Pain Relievers Film Film Processing Filter or Purifier, Water Filters, Air Filters, Oil Fire/Smoke Detector Fishing Fishing Reel Fishing Rod Fixtures, Lighting Fixtures, Plumbing, Bathroom Flatware Flavored Gelatin Desserts Flavored Snack, Saltine 4 Graham Crackers Flea 4 Tick Care Products For Dogs & Cats Floor, Ceiling or Wall Insulation Floonng, Sheet Vinyl Floor Polish & Wax Floor Tile Florists Flowers bv Wire Flower 4 Vegetable Seeds Fluorescent Lighting Flying Private Plane Foil. Aluminum Folding Tent Camper, Towable Food or Sandwich Bags. Plastic Food Processor. Electric Food Stores, Gourmet 4 Health Foreign Travel Formula, Liquid Baby Foundation Makeup Frankfurters & Wieners Fraternal Oraer Membership Freeze-Dried or Instant Conee Freezer Home Fresneners. Air 4 Room Deoaorizers Fresheners, Bream Fresh Fruits Fresh Water Fishing Fresh Water Fishing Reel Fresh Water Fishing Rod Frozen Complete Dinners (TV Dinners) Frozen Dessert Pies, Cakes 4 Pastries Frozen Main Courses (Casseroles 4 Entrees) Frozen Orange )uice Frozen Pizzas Frozen Potato Products Frozen Vegetables Frozen Yogurt Fruit-Flavored Breakfast Drinks, Powdered Fruit luices 4 Drinks Fruits, Canned or Jarred Fruits, Fresh Fry Pan, Electric Fun, Miniature & Snack Size Candy Bars 4 Packages Furnace Furnishings, Household Furniture Furniture Poiish G Games 4 Toys Games, Video Garage Door Opener, Automatic Garbage Bags 4 Trash Can Liners, Plastic Garbage Disposal Gardening Garden Tiller Garden Tractor Gas Chain Saw Gas Clothes Dryer Gas Grill Gasoline & Diesel Fuel Gasoline Additives Gas Power Mower Gas Range or Stove Gelatin Desserts, Flavored Gel or Cream, Shaving Gems 4 Jewelry Gifts by Wire Gin Girdle Gloss. Lip 4 Lipstick Gold/Gold Coins Gold Jewelry Golf Golf Balls Golf Clubs Golf Courses Golf Shoes Gourmet Food Stores Government, Local, Belong To Grill, Electric Grill. Gas Grocerv Shopping, Weeklv Expenditure Grom Irritation Ground Coffee Gum Gun For Target Shooting H Hair Coloring Proaucts Hair Conoitioners Hair Curler Set. Electric Hair Dryer Hair Rinse, Creme Hair Sprays Hair-Styling Comb, Electric Hair Tonic or Dressing Ham, Canned Hand Ball Hand 4 Body Cream, Lotion or Oil Hand-Held Hair Dryer, Electric Hand-Held or Pocket Calculator, Electric Hand Tool Outfit Hard Cover Books Hard Roll Candy Hayfever Headache Remedies 4 Pain Relievers Headaches Head Phones, Stereo Health Club Membership Health Food Stores Health, Hospital or Medical Insurance Heater/Stove, Wood Burning Heater, Water Heating, Solar Heating Unit, Separate Room Heat Pumps Heavyweight Jacket Hemorrhoids Hiking or Backpacking Hiking or Climbing Boots, Men's Home Entertaining Home Freezer Home Improvements Home, Mobile, Towable Home, Motor, Bus-Type & Mini Home Owners or Personal Property Insurance Home. Vacation/Weekend Horseback Riding Hose or Stockings, Women's Hospital Board Membership Hospital, Medical or Health Insurance Hotels & Motels Hot Lather Machine Hot Tub Systems Hot Water Heater Household Cleaners Household Furnishings House Paint Humidifier, Room, Portable Hunting Hunting Rifle I Ice Cream, Ice Milk 4 Sherbert Ice Tea Mix, Instant Ice Skating Illnesses Imported Beer Imoorted Dinner/Table Wines Imorovements. Home Inboard/Outboard Power Boat In-Bowl Toilet Bowl Cleaners Inaigestion Aids 4 Upset Stomach Remeoies Indigestion or Upset Stomach Individual Retirement TRA) or Keogh Plan Inaoor Garaening 4 Plants Inooor Lighting Fixtures Inooor-Outdoor CarDetina intlataoie 6oat 0 124 Insecticides Instant Iced Tea Mix Instant or Freeze-Dried Cortee Instant Potatoes. Packaged Instant Tea Insulation tor Ceiling, Floor or Wall Insurance. Auto Insurance. Dental Insurance. Health, Hospital or Medical Insurance. Home Owners or Personal Property Insurance. Life Insurance, Loss of Income Insurance. Personal Liability Insurance. Travel Insurance. Vision Care In-Tank Toilet Bowl Cleaners Interior Wall Paint Investment Property Investments & Banking Irish Whiskey I Jacket, Heavyweight Jacket, Lightweight Jacket, Sport Jams & Jellies Jarred or Canned Fruits Jarred or Canned Vegetables Jars. Canning & Lids Jeans Jellies & Jams Jewelry, Costume Jewelry & Gems Jewelry, Gold Jig/Sabre Saw Jogging or Running Jogging or Running Shoes Juice, Orange. Frozen Juice, Orange. In Bottles. Cans or Cartons Juicer. Electric Juices & Drinks. Fruit (Not Orange) Juices, Tomato & Vegetable K Keogh Plan or Individual Retirement Plan (IRA) Ketchup (Catsup) Kitchen Cabinets Kitchen Cleaners (Household Cleaners) Kitchen Wrap. Plastic-Type Knee High Hose L Lather Machine. Hot Laundrv Detergents & Soaps Launarv Pre-Soaks & Pre-Cleaners Laundrv Washloads Lawn Mower Lawn/Porch Furniture Lawn Seeo Laxatives Leasing. Car Leathe f Shoes Leisure Activities Leisure/Casuai Suit Lenses. Contact Liaoilitv insurance Personal Lias. Canning, a. Jars Lite Insurance Lighted Make-Up Mirror Lighters. Disposable Lighting Fixtures Lighting, Fluorescent Light/Low Calorie Domestic Beer Lightweight Jacket, Men's Lightweight Summer Suit Liner, Eye Liners. Trash Can. & Garbage Bags. Plastic Lipstick & Lip Gloss Liqueurs & Cordials Liquid Baby Formula Liquid Prepared Salad Dressing Liquor. Malt Living Room Furniture Loan, Auto Loan, Personal Local Government, Belong To Loss or Income Insurance Lotion. After Shave & Cologne Lotion & Oil, Baby Lotion, Shave. Pre-Electric Low Calorie or Diet Carbonated Soft Drinks Lozenges, Throat. Medicated Luggage or Baggage M Macaroni & Spaghetti Products, Canned Mailgram Mail Order Main Courses. Frozen (Casseroles & Entrees) Make-Up, Foundation Make-Up Mirror, Lighted Malt Liquor Margarine Mascara Mattresses Mavonnaise & Mayonnaise-Type Salad Dressing Medical, Hospital or Health Insurance Medicated Skin Care Products Medicated Throat Lozenges Membership, Business Club Membership, Church Board Membership, Civic Club Membership, Country Club Membership, Fraternal Order ■Membership. Health Club Membership. Hospital Board Membership. Religious Club Membership. Regional Development Committee Membership, School or College Board Membership. Union Membersnip. Veterans Club Menstrual or Period Pain Metal Cookware Set Microwave Oven Mileage Driven in Last Year Milk Mineral & Spring Water. Bottled Minibikes or Minicycies Mirror Make-Up. Lighted Mixed Drinks Prepared With Liquor Mixer Electric Mixers. Drink. Preoarea Witnout Liquor Mixes. Caxe Dr- Mixes. Dinner. Complete Packaged. & Dishes Mixes. Iced Tea. Instant Mixes. Prepared Cocktail Mixes. Salad Dressing, Dry Mixes. Soup. Dry, & Bouillon Cubes Mobile Home. Towable Moist Cat Food Moist Dog Food Moisturizers & Cleansing Creams & Lotions. Facial Money by Wire Mopeds Mortgage Motels & Hotels Motion Sickness Motorcycles Motorcycling Motor Home. Bus-Type & Mini Motor Oil Motor Oil Additives Motor. Outboard Motorscooters Mouthwash Movie Cameras Movie Proiector Movies. Attendance Mower Murflers Muscle Aches Mustard Mutual Funds N Nail Polish Napkins & Pads. Sanitary Nasal Sprays Natural Cheese Needlework Nervous Tension Non-Dairy Cream Substitutes Non-Decaffeinated Instant or Freeze-Dried Coffee Notions & Sewing Materials Nursers, Baby O Oil Additives (Motor Oil Additives) Oil & Lotion. Baby Oil, Bath. & Other Bath Additives Oil Filters Oil. Motor Oil. Salad or Cooking Opener. Garage Door, Automatic Orange Juice. Frozen Orange Juice in Bottles. Cans or Cartons Organ Outboard/Inboard Power Boat Outboard Motor OutOoor Gardening Outdoor-Indoor Carpeting Outdoor Lignting Fixtures Outerwear, Children s Oven Cleaners Oven Microwave & Convection Oven. Self/Continuous Cleaning Overcoat-Topcoat Ownership of Cats Ownership ot Dogs 125 p Packaged Dry Cat Food Packaged Dry Dog Food Packaged Instant Potatoes Packaged Moist Cat Food Packaged Moist Dog Food Packaged Prepared Dishes & Dinner Mixes, Complete Paddle Ball Pads, Scouring Pain Relievers, Children's, & Fever Reducers Pain Relievers & Headache Remedies Pain Relieving Rubs & Liquids Paint, Exterior House & Stains Painting, Drawing, Sculpting Paint, Interior Wall Pancake & Table Syrup Paneling, Wall Pan, Fry, Electric Pants Suit, Women's Panty Hose Paperback Books Paper, Cigarette Rolling Paper Cups, Disposable Paper, Toilet Paper Towels Paper, Wall Parties, Cocktail Parties, Dinner Parties, Other (Not Cocktail or Dinner) Party/Pop/Sangria Wines Passports Pastries, Cakes & Pies, Frozen Dessert Pasteurized Processed/American Cheese Patterns, Sewing Peanut Butter Perfume & Cologne Period or Menstrual Pain Personal Liability Insurance Personal Loan From Bank Personal Loan F>om Finance Company Personal Property or Home Owners Insurance Pewter Flatware Piano Pick-Up Trucks Pies. Cakes & Pastries. Frozen Dessert Pillowcases Pipe Tobacco Pizzas, Frozen Plants & Indoor Gardening Plastic Garbage Bags & Trash Can Liners Plastic Sandwich or Food Bags Plastic-Type Kitchen Wrap Platform Tennis Plaver/Recorder, Video Cassette Plumbing Fixtures, Bathroom Pocket or Hand-Held Electronic Calculator Poison Ivy, Oak or Sumac Polish & Wax. Car Polish & Wax. Floor Polish. Furniture Polish. Naii Political Classification Pool. Swimming Porch/Lawn Furniture Porx Sausage; Portable Circular Saw Electric Portable Disnwasner Automatic Portable )ig/Saw, Electric Portable Room Humidifier Portable Typewriter, Electric Port, Sherry & Dessert Wines Potato Chips Potatoes, Frozen Potatoes, Packaged Instant Powder, Baby Powdered Fruit Flavored Breakfast Drinks Powdered Soft Drinks Powder, Face Powder, Scouring Power Boat Power Boating Power Mower Power Yard Trimmer Pre-Cleaners & Pre-Soaks, Laundry Preferred Stock Pre-Moistened Cleansing Wipes for Babies Pre-Soaks & Pre-Cleaners, Laundry Prepared Cocktail Mixes Without Liquor Prepared Dishes & Dinner Mixes, Complete Packaged Prepared Mixed Drinks With Liquor Prepared Salad Dressing, Liquid Pre-Recorded Cassette Tape Pre-Recorded Tape Cartridges Pre-Recorded Tape Reel Pressure Cooker Pretzels Processor, Food, Electric Projector, Movie Proiector, Slide Property, Investment Property, Retirement Psoriasis Psychographics Public Activities Pumps, Heat Purchase of Liquor or Wine By Case Purifier or Filter, Water Q Quilts/Comtorters R Racquet Bail Racquet, Tennis Radial/Arm Saw. Stationary Radio, CB. Base Unit Radio, CB, Mobile Unit Radio Sports, Frequency of Listening Raincoat or All Weather Coat Range or Stove Razor Blades Razors, Disposable Ready Made Draperies/Curtains Real Estate Receiver/Tuner/Amplifier, Stereo Recliner Recorder/Plaver. Video Cassette Records Record & Tape Clubs Records & Tapes: Tvpes Bought Rectal or Vaginal Itching Reel Fishing Reel Taoe, Blank Reei. Taoe. Pre-Recoroeo Reel-To-Ree) Tape Player/Recorder Refrigerator Regional Development Committee Regular Candy Bars & Packages Regular Carbonated Soft Drinks Regular Domestic Beer Regular or Dress Shirt, Men's Regular Tea Religious Club Membership Remedies, Allergy & Cold Remedies, Asthma Remedies, Athlete's Foot Remedies, Children's Remedies, Headache & Pain Relievers Remedies, Indigestion & Upset Stomach Removers, Spot Rental, Car Residential Ceiling Tile Restaurants, Family, & Steak Houses Restaurants, Fast Food & Drive-In Retirement Property Rheumatism or Arthritis Rice Riding, Horseback Rifle For Hunting Ring, Diamond Rinse, Hair, Creme Roll Candy, Hard Roller Skating Rolling Paper, Cigarette Roofing Room Air Conditioners, Separate Room Deodorizers & Air Freshener Sprays Room Heating Unit, Separate Room Humidifier, Portable Rowboat Rubs & Liquids, Pain Relieving Rug Cleaners Rugs Rum Run-Down, Tired Feeling Running, Distance Running or Jogging Running or logging Shoes Rustproofing (Cars) Rye or Blended Whiskey S Sabre/|ig Saw Safe Deposit Box Sailing Salad Dressing Salad Oil or Cooking Oil Salted Crackers & Flavored Snack Crackers Salt Water Fishing Salt Water Fishing Reel Salt Water Fishing Rod Sander. Electnc Sandwich or Food Bags. Plastic Sangria/Pop/Party Wines Sanitarv Naokins & Pads Sauces. Bottled Barbecue & Seasoning Sauce. Spagnetti Sausages. Pork Savings Account Savings Certificates/Certificates ot Deposit 5aw. Arm/Radial. Stationarv Saw. Chain 2 126 Saw, Circular Saw, Jig/Sabre School or College Board Membership Scotch Whisky Scouring Pads Scouring Powder Sculpting, Painting, Drawing Seasoning & Barbecue Sauces, Bottled Second Mortgage Securities Seeds Self-Concept Separate Electric Clothes Dryer Separate Gas Clothes Dryer Separate Home Freezer Separate Microwave Oven Separate Room Air Conditioer Separate Room Heating Unit Sewing Sewing Machine Sewing Materials & Notions Shampoo Shampoo, Baby Shave Lotion (After-Shave) & Cologne Shave Lotion, Pre-Electric Shavers, Disposable Shavers, Electric or Battery Shaving Shaving Cream or Gel Sheets Sheet Vinyl Flooring Sherbet, Ice Cream & Ice Milk Sherry, Port & Dessert Wines Shirt/Blouse, Women's Shirt, Regular or Dress, Men s Shirt, Sport, Men's Shock Absorbers Shoes, Bowling Shoes, Canvas Shoes, Children's Shoes, Golf Shoes, logging or Running Shoes, Leather Shoes, Tennis Shopping, Grocery, Weekly Expenditure Shopping, Supermarket & Food Shotgun For Hunting Silver Flatware Silver/Silver Coins Sinus Congestion Sinus Headache Skating, Ice Skating, Roller Ski Boots Ski Clothes Skiing, Cross Country Snow Skiing, Downhill Snow Skiing, Water Skin Care Proaucts. Medicated Skin Diving or Snorkeling Skirt Skis, Snow Skis. Water Slacks Sleeoiessness Sleeowear Children s Shoe Proiector Siio Smoke/Fire Detector Snack Crackers, Flavored & Salted Crackers Snacks, Corn & Tortilla, & Chips Sneakers Snorkeling or Skin Diving Snow Blower Snowmobile Snow Skiing, Cross Country Snow Skiing, Downhill Snow Skis Snuff Soaps & Detergents for Fine Fabrics Soaps & Detergents for Regular Laundry Soap, Toilet Socks Sofa Bed Soft Drinks. Carbonated Soft Drinks, Powdered Softeners, Fabnc Solar Heating Sore Throats Soup, Canned Soup, Dry Mix, & Bouillon Cubes Spaghetti & Macaroni Products, Canned Spaghetti Sauce Sparkling Wines, Champagne & Cold Duck Spark Plugs Speaker, Stereo Specialty & Aperitif Wines Sporting Goods Sport jacket (Suit Type) Sports Events Attendance Sport Shirt, Men's Sports & Leisure Sports, Radio Listening Sports, TV Watching Sport/Utility Vehicles Spot Removers Sprays, Air Fresheners & Room Deodorizers Spray, Non-Stick Cooking Spread Cheese Spring & Mineral Water, Bottled Squash Stainless Steel Flatware Stain & Paint, Exterior House Stamp Collecting Stationary Bench/Table Circular Saw Stationary Jig/Sabre Saw Stationary Radial/Arm Saw Steak Houses & Family Restaurants Steam Cooker, Electnc Stereo. Compact or Console Stereo Head Phones Stereo Receiver/Tuner/Amplifier (All In One) Stereo Speaker Sterling Silver Flatware Stern Dnve Boat Still Cameras Stockings or Hose Stocks Stomach Remedies & Indigestion Aids Stores, Conveniznce. & SuDermarkets Stores. Deoartment & Discount Stores. Health Food Storm Doors or Windows Stove/Heater Wood 8urmng Stove or Range. Electnc Stove or Range. Gas Sugar, Brown & Granulated White Suit, Leisure or Casual Suit, Lightweight or Summer Suit, Pants, Women's Suits or Dresses, Children's Suit, Swimming Suit, Warm-Up Suit, Winter or All-Year Suit, Women's Sunglasses Sunscreen & Suntan Products Suppositories & Douches, Feminine Hygiene Swabs, Cotton Sweater Swimming Swimming Pool Swim Suit Syrup, Pancake & Table T Table/Bench Circular Saw, Stationary Tampons Tape Cartridges, Blank Tape Cartridges, Pre-Recorded Tape Cassette, Blank Tape Cassette. Pre-Recorded Tape Player/Recorder, Reel-To-Reel Tape & Record Clubs Tape Reel, Blank Tape Reel, Pre-Recorded Tapes & Records: Types Bought Target Gun Target Shooting Tea, Canned Tea, Instant Tea Mix, Iced, Instant Tea, Regular Telegrams & Wires Telephones Television Sets Tennis Tennis Balls Tennis Clothing Tennis Courts Tennis. Platform Tennis Racquet Tennis Shoes Tension, Nervous Tent Camper. Towable Folding Tequila Theme Parks Throat Lozenges, Medicated Tick & Flea Care Products for Dogs & Cats Tile. Ceiling, Residential Tile. Floor Tiller, Garden Tired, Run-Down Feeling Tires. Car. Truck & Van Tissues, Facial Tobacco. Chewing Tobacco. Pipe Toilet Bowl Cleaners Toilet Paoer Toilet Soap Tomato & Vegetable luices Tonic. Hair, or Hair Dressing Tool Outtit. Hana Tootnacne 127 Toothbrush. Electric Toothpaste Topping, Whipped Tortilla & Corn Chips & Snacks Tour Package Towable Folding Tent Camper Towable Mobile Home Towable Travel or Camp Trailer Towels Towels, Paper Toys & Games Tractor, Garden Tractor-Type/Riding Lawn Mower Trailer, Towable Travel or Camper Transmission Services Trash Can Liners & Garbage Bags, Plastic Trash Compactor, Electric Travel Agent Travel, Domestic Travelers Checks Travel, Foreign Travel Insurance Travel or Camper Trailer, Towable Travel, Weekly Treasury Notes Treats. Dog, or Biscuits Trips, Camping Trips, Domestic Travel Trips. Foreign Travel Truck Driving, Reasons For Truck Mounted Camper Trucks Trust Agreement With Bank T-Shirt, Women's Tuna. Canned Tuner/Amplifier/Receiver, Stereo Tupperwear Turntable TV Dinners (Frozen Complete Dinners) TV Sets TV Special Programs, Frequency of Watching TV Sports, Frequency of Watching Typewriter, Electric Portable U Underwear. Children's Union Membership Upset Stomach or Indigestion Upset Stomach Remedies & Indigestion Aids Utility/Sport Vehicle V Vacation/Weekend Home Vaginal or Rectal Itching Vans Vegetable & Flower Seeds Vegetables. Canned or (arreo Vegetables. Frozen (Excluding Potatoes) Vegetable & Tomato (uices Vehicle Camping Vehicle. SDort/Utilitv Vermouth Veterans Club Membership Vioeo Cassette Recorder/Plaver Video Game Vinvl F'ooring, Sheet Vision Care Insurance Vitamins for Children Vitamin Tablets, Capsules & Liquids Vodka Voting W Wall, Floor or Ceiling Insulation Wall Paint, Interior Wall Paneling Wall Paper Wall-To-Wall Carpeting or Room Sized Rugs Warm-Up Suit Washing Machine, Automatic Washloads of Laundry Water Filter or Purifier Water Heater Water, Mineral & Spring, Bottled Water Skiing Water Skis Wax & Polish, Car Wax & Polish, Floor Weekend /Vacation Home Weekly Expenditure on Groceries Weekly Travel Whipped Topping Whiskey, Bourbon Whiskey, Irish Whiskey, Rye or Blended Whiskey, Canadian Whiskey, Scotch Wieners & Frankfurters Window Cleaners Windows, Storm, or Door Wines, Aperitif & Specialty Wines, Dessert, Port & Sherry Wines, Domestic Dinner/Table Wines, Imported Dinner/Table Wines. Pop/Party/Sangria Wines. Sparkling, Champagne & Cold Duck Wipes, Cleansing, Pre-Moistened, For Babies Wires & Telegrams Wood Burning Stove/Heater Woodworking Wrap, Kitchen, Plastic-Type Wnstwatch. Digital Face Wnstwatch. Dial Face Y Yard Trimmer Yellow Pages Yogurt Yogurt. Frozen Source: Reprinted from SMRB 1982. 128 The Information provided for each product In each volume Is divided Into three sections: usage, types, and brands. In each section, demographic Information on the buyer of the product Is presented: age, race, employment, education, place of residence (1.e., metropolitan central city, metropolitan suburban, and non-metropolitan), Income, and household occupant characteristics. Usage of products by Individuals and households Is subdivided Into "heavy," "medium," or "light." Table 21 lists an example of a hypothetical product usage calculation as performed by SMRB. The "heavy," "medium," and "light" designations are not absolute. They are based on the relative frequency of use of each product; the designations therefore vary from product to product. The usage rates are defined by SMRB for each product, and a table such as Table 21 Is generated for each SMRB product. This Information Is particularly valuable for enumerating populations that may have high, medium, or low exposure to chemical substances via the use of consumer products when the same usage rates for product consumption are used to predict exposure levels. Table 22 Is a sample table of SMRB usage data for rug cleaners. SMRB also presents the same demographic data according to product types (e.g., a rug cleaner may be marketed as a liquid, an aerosol, or a powder). Table 23 Is a sample table of SMRB data for different types of rug cleaners purchased by female homemakers. Finally, SMRB also presents demographic data for specific name brands of products. Table 24 Is a sample table of SMRB data for different name brand rug cleaners purchased by female homemakers. SMRB presents data according to the characteristics of the buyer only. For example, for many consumer products the principal purchaser (as determined by the SMRB national consumer panel) may be the "female homemaker."* SMRB therefore only presents data for that product for the female homemaker. Six population groups are assumed to represent principal purchasers: adults, males, females, professlonal/managerlal, female homemakers, and mothers. Furthermore, SMRB only reports data for populations 18 years of age and older. The Implications of these factors cannot always be quantified. Users of a product can be enumerated as the total number of users, or they can be disaggregated by brand or type of product. Figure 20 Illustrates the SMRB presentation of data on usage of toothpaste by females. The first number In Column A under "all users" Indicates that 75,174,000 females use toothpaste; this represents 92.7 percent of all * The term "female homemaker" Is defined by SMRB as adult women who assume responsibility for the maintenance of a household. The term Includes working women and women living alone as well as In families, and represents over 90 percent of adult women. It should be recognized that products bought and used by female homemakers are often purchased and used by males maintaining households. SMRB does not adjust for this limitation; resultant population data may therefore be somewhat underestimated. 129 Table 21. Product Usage Categorization for SMRB "Heavy," "Medium," and "Light" Designations 4-> to r- CO O' CD CVJ m in CM •— ro c t- 03 u S- 03 to D co in r— ro 00 in CD — o 8 Q) Cl. c o O — 4—» £ % CD Z3 O l- C CD O Q- O O O o -o CD CD C o £ §- D CO C o o L) O L. 03 to D 03 £ 03 c 4-> CD jC • r— CD to • r— to 03 < 3 c O • r“ 4—> jO 03 —1 C 21 CD X • r- to 03 ■o 4-> to 03 '— C ,r " 03 •O to r— >> o 03 -C T3 CD to r-» O -C in CO o ro O o r— <— •— o o o CO CM CD - *— CM CO o o d o o o o o o o o m O 00 CD CD O 00 co id uo co r-~ in o o O r~ CO ic ic fl i- O « 3 - CM UO CO O lO CO 4-> O CD r— 00 r— CM CD I- O 'S' CO CM I— to CD 0 ) r— L_ (Q • r 4 -> 03 O C 4 -> C o T 3 • r— C 4 -» 03 to 3 0 ) CD > 03 O p— 4 —> 0 / to to • 4 -> 3 ID c 4 -> CD U T 3 u o C CL o » 03 -Q CO u cc T 3 £ D 01 to -O 4 -> 03 c “D CD • r* 03 03 *D S_ to . r— CD • > CD 03 /—s o 03 CD *— u CL CO Q- CD Q. CD U 03 P— C 03 N —* o E 4 -> 13 4 -> to • r— CO 4 -> > .r- -C 03 cr rn ~o CD to to £ P o c 03 to c jC e o O CL 03 » 4 - ii ii II to 4 -> • • c a; 03 03 ►—1 X X _ 1 a: Q CJ m jd o -o t- 3 O in 130 Table 22. Example of 1982 SMRB Data: Demographic Variables for Usage of Rug Cleaners Purchased by Female Homemakers total All USERS e c HEAVY USERS B C MEDIUM USERS LIGHT USERS B C u s '000 •ooo ACROSS DOMN X INOX •ooo l ACROSS DONN C INOX •ooo X ACROSS DOMN $ 1NDX •ooo s ACROSS DOMN $ INLY T01A. F EMAl E HOMEMAKERS 7 75 OB 36879 100 0 47 6 100 13063 100 0 16 9 100 10034 100 0 12.9 100 13783 100 0 17 8 100 18 - ?4 9335 3750 10. 2 40 2 84 1417 10 8 15 2 90 898 8 9 9 6 74 1435 10 4 16 4 86 :s • 3 j 18029 8934 24 2 49 6 104 3293 25 2 18 3 108 2362 23 5 13 1 101 3279 23 8 18.2 102 3b - 44 13417 7073 19 2 52 7 111 2276 17 4 17.0 101 1945 19 4 14 5 112 2653 20 7 21.3 120 45 - S4 11632 5’53 15. 6 49 5 104 2222 17 0 IS 1 113 1492 14 9 12 8 99 2040 14.8 17.5 99 56 • C4 11263 5679 15 4 50 3 106 1867 14 3 16 5 98 1729 17.2 15 3 118 2084 15 1 18 5 104 65 OR OLDER 13811 5689 15 4 41 2 87 1988 15 2 14 4 85 1608 16 0 11 6 90 2093 15.2 15 2 86 IS - ?4 27364 12685 34 4 46 4 97 4710 36 1 17.2 102 3260 32 5 119 92 4714 34 2 17 2 97 18 • 49 46197 22535 61 1 48 8 103 7966 61.0 17 2 102 5972 59 5 12 9 100 8596 62 4 18 6 105 25 - Si 43078 21760 59 0 50 5 106 7791 59 6 18 1 107 5799 57 8 13.5 104 8171 59 3 19 0 107 35 - 45 18833 9850 26 7 52 3 110 3256 24 9 17.3 103 2712 27 0 14 4 in 3882 28.2 20 6 116 50 OR OLDER 31310 14345 38 9 45 8 96 5096 39 0 16 3 97 4062 40 5 13 0 100 5187 37 6 16 6 93 GRADUATED COLLEGE 9890 5021 13 6 50 8 107 1451 11 1 14 7 87 1209 12.0 12.2 94 2361 17 . 1 23.9 134 A7TEN0EB COLLEGE 12236 5798 15 7 4? 4 100 1878 14 4 15.3 91 1788 17.8 14 6 113 2131 15 5 17 4 9E GRADUATED HIGH SCHOOL 32853 16490 44 7 50 2 105 5649 43 2 17.2 102 4617 46 0 14 1 109 6224 45 2 1E 9 107 DID HOT GRADUATE HIGH SCHOOL 22527 957 1 26 c 42. 5 89 4084 31.3 18 1 108 2420 24 1 10 7 83 3067 22 3 13 6 77 EMPLOYED 37446 18217 49 4 48 6 102 6306 48.3 16 8 100 4618 48 0 12 9 99 7093 61 5 IE 9 107 EMPLOYED FULL-TIME 29717 14 146 38 4 47 6 100 5002 38 3 16 8 100 3638 36 3 12 2 95 5507 40 0 18 5 104 EMPLOYED PART-TIME 7729 407 1 11. 0 52 7 111 1304 10 0 16 9 100 1180 11.8 15 3 ns 1586 11 5 20.5 115 NOT EMPLOYED 40060 18662 50 6 46 6 98 6756 51 7 16 9 100 5216 52 0 13 0 101 6690 48 5 16 7 94 PPOFESSIONAL'MANAGER 10614 5355 14 5 so 5 106 1666 12 8 15 7 93 1446 14 4 13 6 105 2242 16 3 21 1 119 CLERICAL'SALES 14780 6964 18 9 47 1 99 2342 17 9 15 8 94 1863 16 6 12 6 97 2760 20 0 18 7 105 CRAFTSMEN 'FOREMEN 824 •429 1 2 52 1 109 ••166 1.3 20 1 120 • •174 1.7 211 163 ••89 0.6 10 8 61 OTHER EMPLOYED 11229 5468 14 8 48 7 102 2133 16 3 19 0 113 1333 13.3 11 9 92 2002 14 5 17.8 100 SINGLE B267 3220 8 7 39 0 82 1171 9 0 14 2 84 947 9 4 11 5 88 1101 8 0 13.3 75 MARRIEO 50768 25994 70 5 51. 2 108 8935 68 4 17 6 104 6981 69 6 13 8 106 10079 73.1 19.9 112 CIVORCEO/SEPARATED'HIOOHED 1847 1 7666 20 8 41 5 87 2956 22 6 16 0 95 2106 21 0 11 4 88 2603 18.9 14 1 79 PARENTS 31500 162 14 44 0 51 . 5 108 5773 44 2 18 3 109 4400 43.9 14 0 108 6041 43.8 19.2 10E NHITE 67876 32560 88 3 48 0 101 10982 84 1 16 2 96 8830 88 0 13 0 100 12748 92 5 18 8 106 BLACK 8235 3573 9 7 43 4 91 1780 13 6 21.6 128 1007 10 C 12 2 94 786 5.7 9.5 54 OTHER 1395 • 746 2 0 53 5 112 ••301 2.3 216 128 • •197 2.0 14 1 109 ••249 1.8 17 8 100 northeast-census 16922 7815 21 .2 46 ■2 97 2960 22 7 17.5 104 2196 21.9 13.0 100 2660 19 3 16 7 88 NORTH CENTRAL 20200 10219 27 7 50 6 106 3252 24 9 16 1 96 3147 314 15.6 120 3820 27,7 18.9 106 SOUTH 26132 12341 33 5 47. 2 99 4897 37.5 18 7 111 2904 28 9 11 1 86 4540 32.9 17 4 98 NEST 14252 6505 17 6 46 6 96 1955 15 0 13 7 81 1787 17.8 12.5 97 2764 20 1 19.4 109 NORTHEAST-MKTG 17524 7849 21 3 44 . 8 94 2928 22 4 16 7 99 2084 20 8 119 92 2837 20 6 16.2 91 EAST CENTRAL 11814 6552 17 8 55 5 117 2331 17.8 19 7 117 2034 20 3 17.2 133 2188 15 9 18 5 104 NEST CENTRAL 13479 6542 17 7 48 5 102 1862 14.3 13 8 82 2056 20 5 15.3 118 2624 19.0 19 5 109 SOUTH 22875 10727 29 1 46 9 99 4306 33 0 18 8 112 2512 25.0 110 85 3908 28 4 17 1 96 PACIFIC 11814 5210 14 1 44 1 93 1635 12 5 13 8 82 1349 13.4 11 4 88 2226 16.2 18 8 106 COUNTY SIZE A 31229 14084 38 .2 45 1 95 5024 38 5 16 1 95 3540 35.3 113 88 5520 40.0 17.7 99 COUNTY SIZE E 23352 11373 30 8 48 7 102 3958 30 3 16 9 101 3014 30 0 12.9 100 4401 31 9 18 8 106 COUNTY SIZE C 12137 6335 17 _2 52 _ 2 110 2249 1' 2 16.5 110 1887 18.8 15.5 120 2199 16.0 It 1 102 COUNTY SIZE D 10789 5087 13 t . 1 99 1832 14 0 17.0 101 1593 15 9 14 8 114 1663 12 1 15 4 87 METRO CENTRAL CITY 23359 9906 26 9 42 4 89 3558 27.2 15 2 90 2819 28 1 12 1 93 3529 25 6 15 1 85 METRO SUBURBAN 34657 17101 46 4 45 3 104 5690 43 6 16 4 97 4174 41.6 12.0 93 7236 52 5 20 9 117 NON METRO 19491 9872 26 8 50 6 106 3814 29 2 19 6 116 3040 30.3 15 6 120 3018 21 9 15.5 87 TOP 5 AO!'S 17725 7990 21 . 7 45 1 96 3040 23 3 17.2 102 2110 21 0 11.9 92 2840 20 6 16.0 90 TOP 10 ADI’S 25079 1 1418 31 0 45 5 96 4394 33 6 17,5 104 2996 29 9 11.9 92 402P 29 2 16 1 90 TOP 20 ADI'S 35085 16056 43 5 45 8 96 5947 45 5 17 0 101 4114 41 0 11.7 91 5996 43.5 17.1 96 HSHLC INC J40 000 OR MORE 8818 4450 12 1 50 .5 106 1340 10 3 15 2 90 1190 11 9 13 5 104 1920 13 9 218 122 S30 000 OR MORE 18653 9421 25 5 50 5 106 2733 20 9 14 7 87 2614 26 1 14 0 108 4074 29 6 218 123 S25 000 OR MORE 259 1 1 13098 35 5 50 5 106 4094 31 3 15 8 94 3503 34 9 13 5 104 5502 39 9 21 2 119 S20 000 - S24 999 9349 4643 12 6 49 7 104 1562 12 0 16 7 99 1340 13 4 14 3 111 1742 12 6 18 6 105 S15 000 - S19 999 8862 4580 12 4 51 7 109 1543 11 8 17 4 103 1191 119 13 4 104 1846 13 4 20 8 117 S10 000 - $14 999 13844 6572 17 8 47 5 100 2304 17 6 16 6 99 1822 18.2 13 2 102 2447 17.8 17 7 99 UNDER $10 000 19541 7985 21 7 40 .9 86 356 1 27.3 18 2 108 2179 21.7 11.2 86 2246 16.3 11.5 66 HOUSEHOLD OF 1 PERSON 11894 4657 12 6 39 2 82 1722 13.2 14.5 86 1302 13.0 10.9 85 1634 119 13 7 77 2 PEOPLE 25454 11362 30 8 44 6 94 4 102 31 4 16 1 96 2816 28 1 11 1 85 4445 32 2 17.5 98 3 OR 4 PEOPLE 28521 14790 40 . 1 51 9 109 4822 36 9 16 9 100 4378 43 6 15 4 119 5590 40 6 19 6 110 5 OR MORE PEOPLE 11637 6070 16 5 52 .2 110 2418 18 5 20.8 123 1538 15.3 13.2 102 2114 15.3 18 2 102 NO CHILD IN HSHLO 43986 19806 53 7 45 0 95 6936 53.1 IS 8 94 5306 52 9 12 1 93 7564 54 9 17.2 97 CHIlD1 REN • UNDER 2 YRS 565 1 2706 7 3 47 9 101 1022 7.8 18 1 107 723 7.2 12 8 99 961 7.0 17 0 96 2 - 5 YEARS 12521 6469 17 5 51 7 109 2532 19 4 20 2 120 1697 16 9 13 6 105 2240 16.3 17.9 101 6 - 11 YEARS 15766 8603 23 3 54 6 115 3074 23 5 19 5 116 245 1 74 4 15.5 120 3079 22 3 19 5 110 12 - 1* YEARS 16144 8366 22 7 51 8 109 3017 23 1 18 7 111 2200 21 9 13 6 105 3150 22 9 19 5 110 RESIDENCE ONNEC 55460 28352 76 9 51 1 107 9424 72 1 17 0 101 7775 77 5 14 0 108 11154 80 9 20 1 113 VALUE $50 000 OP MORE 28563 14704 39 9 51 5 108 4632 35 5 16 2 96 3769 37 6 13.2 102 6303 46.7 22 1 124 VALUE UNDER $50 000 268S7 13648 37 .0 50 7 107 4792 36 7 17 8 106 4006 39 9 14 9 115 485 1 35 2 18 0 101 Source: SMRB 1982. 131 Table 23. Example of 1982 SMRB Data: Demographic Variables for Types of Rug Cleaners Purchased by Female Homemakers 110U1D AEROSOL PONDER GRANULES TOTAL A E C 0 a e c o a e C 0 U S T ACROSS ACROSS i ACROSS '000 ‘000 DONN *. INOX '000 DONN *. INOX ‘000 DONN : inox TOTAL FEMALE HOMEMAKERS 77506 18939 100 0 24 4 100 13862 100 0 17 9 100 6044 100 0 7 8 100 18 - 24 9335 1706 9 0 18 3 75 1746 12 6 18 7 105 813 13 5 8 7 112 25 - 34 18029 4515 23 8 25 0 102 3855 27 8 21 4 120 1442 23.9 8 0 103 35 - 44 13417 4241 22 4 31 6 129 235 1 17 0 17 5 98 976 16 1 7.3 93 45 - 54 11632 2903 15.3 25 0 102 2232 16 1 19 2 107 842 13 9 7 2 93 55 - E4 11283 2903 15 3 25 7 105 2136 15 4 16 9 106 888 14 7 7 9 101 65 OR OLOER 13811 2673 14 1 15 4 79 1543 11 1 1 1 2 62 1083 17.9 7 8 101 18 - 34 27364 6221 32 8 22 7 93 5601 40 4 20 5 1 14 2255 37 3 8 2 106 18 - 49 46197 11914 62 9 25 8 106 9058 65 3 19 6 110 3598 59 5 7 8 100 25 - 54 43078 11658 61 6 27 1 1 1 1 8437 60 9 19 s 110 3260 53 9 7 6 97 35 - 43 18833 5694 30 1 30 2 124 3458 24 9 18 4 103 1343 22 2 7 1 91 50 OR OLDER 31310 7025 37 1 22 4 92 4803 34 6 15 3 86 2446 40 5 7 8 100 GRADUA7E0 COLLEGE 9890 2535 13 4 25 6 105 2008 14 5 20 3 1 14 772 12 8 7 8 100 ATTENDED COLLEGE 12236 2955 15.6 24 2 99 2719 19 6 22 2 124 911 16 1 7 4 95 GRADUATED HIGH SCHOOL 32853 8311 43 9 25 . 3 104 6521 4*> 0 19 8 111 2718 45 0 8.3 106 DID NOT GRAOUATE HIGH SCHOOL 22527 5139 27 1 22 8 93 2613 18.9 1 1 6 65 1642 27 2 7 3 93 EMPLOYED 37446 9264 48 9 24 7 101 7069 51 0 U 9 106 3178 52 6 8 5 10E EMPLOYED FULL-TIME 29717 7254 38 3 24 4 100 5431 35 2 18 3 102 2346 3E 8 7 9 101 employed part-time 7729 2010 10 6 26 0 106 1638 11 8 21 2 118 832 13 8 10 8 138 NOT EMPLOYED 40060 9676 51 1 24 2 99 6792 49 0 17 0 95 2866 47 4 7 2 92 PROFESSIONAL'MANAGER 10614 2665 14 1 25 1 103 2169 15.6 20 4 1 14 707 11 7 6 7 85 CLERICAL/SAL E S 14780 3542 18 7 24 0 98 2903 20 9 19 6 no 1119 18 5 7 6 97 CRAFTSMEN FOREMEN 824 ••222 1.2 26 9 110 ••125 C 9 15 2 85 • •45 0 7 5 5 70 OTHER EMPLOYED 1 7229 2836 15 0 25 3 103 1872 13 5 16 7 93 1306 21.6 11 6 145 SINGLE 8261 1370 7.2 16 6 6E 1504 10 8 18 2 102 65 7 10 9 7.9 102 MARRIED 50768 13940 73 6 27. 5 112 9881 713 19 5 109 3927 65 0 7 7 99 DIVORCED'SE PARATE D/NlDONED 1847 1 3629 19.2 19 6 80 2477 17.9 13 4 75 1460 24 2 7 9 101 PARENTS 31500 9208 48 6 29 2 120 5946 42.9 IE 9 106 2427 40 2 7 7 95 NHITE 67876 16584 87 6 .74 4 100 12547 90 5 18 5 103 5106 84 5 7.5 96 BLACK 8235 1890 10 0 23 0 94 1128 8 1 13 7 77 713 11.8 ' 8 7 m OTHER 1395 ••465 2.5 33 3 136 ••186 1.3 13 3 75 ••225 3 7 16 1 207 NORTHEAST-CENSUS 16922 4035 21.3 12- 8 98 3054 22.0 18 0 101 1164 19 3 6 9 BE NORTH CENTRAL 20200 5505 29 1 27 3 112 3744 27 0 16 5 104 1481 24 5 7 3 94 SOUTH 26132 6098 32.2 23 3 95 4337 313 16 6 S3 2465 40.8 9 4 121 NEST 14252 3302 17 4 23 2 95 2727 19 7 19 1 107 935 15 5 6 6 84 NORTHE AST-MKTG 17524 3718 19 6 21 2 87 3129 22 6 17 9 100 1276 21 1 7.3 93 EAST CENTRAL 11814 3853 20 3 32 6 133 2259 16 3 19 1 107 922 15.3 7.8 100 NEST CENTRAL 13479 3326 17.6 24 7 101 2410 17 4 17 9 100 963 15 9 7 1 92 SOUTH 22875 5486 29 0 24 0 98 3731 26 9 16 3 91 2138 35 4 9.3 120 PACIFIC 11814 2557 13.5 21 6 89 2333 16 8 19 .7 110 746 12 3 6 3 81 COUNTY SIZE A 31229 6495 34 3 2C 8 85 5905 42 6 18 9 106 2398 39.7 7.7 98 COUNTY SIZE B 23352 5970 31 6 25 6 105 4283 30 9 18 3 103 1922 31.8 8.2 106 COUNTY SIZE C 12137 3645 i9.: 30 0 123 2065 14 «• 17 0 95 893 14.6 7 4 94 COUNTY SIZE D ICS® 2830 14 9 26 2 107 1609 11 6 14 9 83 832 13.8 7.7 99 METRO CENTRAL CITY 23359 4717 24 9 20 83 4027 29 1 17 .2 96 1916 31 7 8.2 105 METRO SUBURBAN 34657 8726 46 1 25 2 103 6521 47.0 18 8 105 2610 43 2 7.5 97 NON METRO 19491 5496 29 0 28 2 115 3313 23 9 17 .0 95 1519 25 1 7.8 100 TOP 5 ADI'S 17725 3820 20.2 21 6 88 3227 23 3 18 2 102 1316 21 8 7.4 95 TOP 10 AO]'S 25079 5347 28 2 21 3 87 4854 35.0 19 4 108 1829 30.3 7.3 94 TOP 20 AD! 'S 35085 7556 39 9 21 .5 88 6725 48 5 19 .2 107 2717 45.0 7.7 99 HSHLO INC $40 000 OR MORE 8818 2487 13.1 28 .2 115 1849 13.3 21 0 117 • 470 7.8 S3 68 $30,000 OR MORE 18653 5129 27 1 27 5 113 3747 27 0 20 1 112 1232 20 4 6 6 85 $25 000 OR MORE 2591 1 6963 36 8 26 .9 110 5491 39 6 21 .2 118 1869 30 9 7 2 92 $20 000 - $24 999 9349 2357 12 4 25 2 103 1964 14 2 21 0 117 685 11.3 7 3 94 $15 000 - $19 999 8862 2571 13 6 29 0 119 1563 11.3 17 6 99 790 13 1 8 9 114 $10 000 - $14 999 13844 3115 16 4 22 5 92 2542 18 3 18 4 103 1023 16 9 7.4 95 UNDER $10 000 19541 3933 20 8 20 1 82 2302 16 6 1 1 8 66 1677 27 7 11 110 HOUSEHOLD OF 1 PERSON 11894 1856 9.8 IS 6 64 1566 11.3 13 .2 74 958 15 9 8 1 103 2 PEOPLE 25454 5550 29 3 21 8 89 4392 31.7 17 .3 96 1862 30 8 7.3 94 3 OR 4 PEOPLE 2852 1 8036 42 4 28 2 115 5878 42 4 20 6 115 2331 38 6 8 2 105 5 OR MORE PEOPLE 11637 3497 18 5 30 1 123 2026 14 6 17 4 97 893 14 8 7.7 98 NO CHILD IN HSHLD 43986 9224 48 7 21 0 86 7685 55 4 17 5 98 3448 57 0 7.8 101 CHILDIREKI UNDER 2 YRS 565 1 1421 7 5 25 . 1 103 1153 8 3 20 4 114 • 367 6 1 6 5 S3 2 - 5 YEARS 12521 3542 18 7 28 3 116 2634 19 0 21 .0 118 890 14 7 7. 1 91 6 - 11 YEARS 15766 5149 27 2 32 7 134 3155 22 8 20 0 112 1193 19.7 7.6 97 12 - 17 YEARS 16144 4940 26 1 30 6 125 2542 18.3 15 7 88 1412 23 4 8.7 112 RESIDENCE ONNE D 55460 15154 80 0 27 3 112 10322 74 5 18 6 104 4313 71 4 7.8 100 VALUE $50,000 OR MORE 28563 7777 41 1 27 2 111 572 1 413 20 .0 112 2066 34.2 7.2 S3 VALUE UNDER $50. 000 26897 7378 39 0 27 4 112 4602 33,2 17 . 1 96 2248 37 2 8 4 107 t 000 e c i ACROSS DOWN *. Source: SMRB 1982. o INOX 132 Table 24. Example of 1982 SMRB Data: Demographic Variables for Brands of Rug Cleaners Purchased by Female Homemakers toial female homemakers IB - 24 25 • 34 35 • 44 45 - 64 55 - 54 65 OR OlOER 18 - 34 18 - 49 25 - 54 35 - 49 50 OR OLDER GRADUATED COLLEGE ATTENDED COLLEGE GRADUATED HIGH SCHOOL DID NOT GRADUATE HIGH SCHOOL EMPLOYED EMPLOYED FULL-TIME EMPLOYED PART-TIME NOT EMPLOYED PROFESSIONAL/MANAGER CLERICAL'SALES CRAFTSMEN'FOREMEN OTHER EMPLOYED SINGLE MARRIED DIVORCEO'SEPARATED/HI DOMED PARENTS NHITE BLACK OTHER NORTHEAST-CENSUS NORTH central SOUTH NEST NORTHEAST-MKTG EAST CENTRAL NEST CENTRAL SPUTH PACIFIC COUNTY SIZE A COUNTY SIZE B COUNTY SIZE C COUNTY SIZE D METRO CENTRAL CITY METRO SUBURBAN NON METRC TOP 5 ADI'S TOP 10 AO!'S TOP 20 AD I'S HSHLO INC S40 000 OR MORE $30 000 OR MORE $25,000 OR MORE $20 000 - $24 999 $15 000 - $19,999 $10 000 - $14 999 UNDER $10 OOO HOUSEHOLD OF 1 PERSON 2 PEOPLE 3 OR 4 PEOPLE 5 OR MORE PEOPLE NO CHILD IN HSHLD CHILDIREN 1 UNDER 2 YRS 2 - 5 YEARS 5 - 11 YEARS 12 - 17 YEARS RESIDENCE OMNEO VALUE $50 000 OR MORE VALUE UNDER $50 000 BLUE LUSTRE GIAMORENE SPRAY *N VAC JOHNSON'S GLORY NOOLITE TOTAL A B C D A e C D A 6 C C A 6 C D US X ACROSS X ACROSS X ACROSS X ACROSS •ooo *000 OONN X INDX •ooo OONN X INOX ■OOO OONN * INDX •ooo OONN X INOX 77506 7924 100 0 10.2 100 3872 100.0 SO 100 4766 100 0 6 1 100 9154 100 0 118 100 9335 799 10 1 8 6 84 • •301 7.8 3.2 65 802 16 8 8 8 140 1061 11 6 11 4 96 18029 1638 20 7 9 1 89 890 23 0 4 9 99 1303 27.3 7 2 118 2313 25 3 12.8 109 13417 1622 20 5 12 1 118 630 16.3 4 7 94 819 17.2 6 1 99 1116 12 2 8 3 70 11632 1363 17.2 117 115 674 17 4 SB 116 602 12 6 S. 2 84 1448 15 8 12 4 105 11283 1347 17.0 119 117 706 18 2 $ 3 125 590 12 4 s. 2 85 1520 16 6 13.5 114 13611 1155 14 6 14 82 672 17.4 4.9 97 650 13 6 4 7 77 1695 18 5 12 3 104 27364 2436 30 7 8 9 87 1190 30 7 4.3 87 2105 44 2 7. 7 125 3374 36 9 12.3 104 46197 4823 60 9 10 4 102 2155 55 7 4.7 93 3268 68 6 7 1 115 5191 56 7 11.2 95 43078 4623 58 3 10 7 105 2194 56 7 S. 1 102 2724 57 2 6 3 103 4877 53 3 113 96 18833 2387 30 1 12 7 124 965 24 9 5.1 103 1163 24 4 6. 2 100 1817 19 8 9 6 82 31310 3101 39 1 9 9 97 1716 44 3 5 5 110 1498 31 4 4 8 78 3963 43. 3 12.7 107 9890 910 11.5 9.2 90 631 16.3 6 4 128 S61 11.8 s 7 92 1287 14 1 13 0 110 12236 1207 15.2 9 9 96 594 15 3 4 9 97 638 13 4 s. 2 85 1715 IB 7 14.0 119 32853 3614 45 6 110 108 1728 44 6 5 3 105 2148 45 1 8 5 108 386 1 42 2 118 100 22527 2194 27.7 9.7 95 920 23.8 4 1 82 1419 29 8 6 3 102 2290 25 0 10 2 86 37446 3998 50 5 10 7 104 1913 49 4 5.1 102 2640 55 4 7 1 115 4086 44 s 10 9 92 297 17 3073 38 8 10 3 101 1523 39 3 5. 1 103 2014 42 3 6. 8 no 3124 34 1 10 5 89 7729 924 11 7 12 0 117 •389 10 0 5 0 101 •626 13 1 8 1 132 961 10 5 12 4 105 40060 3926 49 5 9 8 96 1959 50 6 4.9 98 2126 44 6 5 3 86 5068 55 4 12 7 107 10614 973 12 3 9.2 90 • 604 15 6 S 7 114 S65 119 5 . 3 87 1280 14 0 12 1 102 14780 1610 20 3 10 9 107 743 19 2 5 0 101 1373 28 8 9 3 151 1616 17 7 10 9 93 824 ••201 2 5 24 4 239 ••53 1.4 6 4 129 • • 18 0 3 1 . 9 32 • •64 0 7 7.8 66 11229 1213 15.3 10.8 106 •512 13.2 4 6 91 687 14 4 6 1 99 1126 12 3 10 0 85 8267 630 8 0 7.6 75 •392 10 1 4 7 95 744 15 6 9 0 146 933 10 2 11.3 96 50768 5549 70 0 10.9 107 2623 67.7 5.2 103 3190 66 9 6. 3 102 6171 67 4 12.2 103 18471 1745 22 0 9 4 92 857 22 1 4 6 93 833 17.5 4 5 73 3049 22 4 11.1 94 31500 3519 44 4 11.2 109 1323 34 2 4.2 84 2137 44.8 8 8 110 3415 37 3 10.8 92 67876 7125 89.9 10 5 103 3527 91 1 5 2 104 3932 82 5 5 8 94 8404 91 8 12 4 105 8235 677 8 5 8 2 80 •331 8.5 4 0 80 784 16 4 9 .5 155 634 6 9 7.7 65 1395 ••122 1.5 8 7 86 • •14 0.4 1.0 20 ••SO 1.0 3 6 58 ••116 1 3 8 3 70 16922 1364 17.2 8 1 79 945 24 4 5 6 112 84 1 17 6 5 0 81 1768 19 3 10 4 88 20200 2656 33 5 13 1 129 1038 26 8 5 1 103 1365 28 6 6 8 110 2160 23 6 10 7 91 26132 2853 36 0 10 9 107 1256 32 4 4 8 96 2004 42 0 7 7 125 3349 36 6 12 8 109 14252 1051 13.3 7.4 72 •633 16.3 4 4 89 556 117 3 9 63 1876 20 5 13 2 111 17524 1252 15 8 7. 1 70 985 25 4 5 6 113 814 17 1 4 6 76 1707 18 6 9 7 82 11814 2054 25 9 17 4 170 551 14.2 4.7 93 928 19 5 7 9 128 1326 14 5 112 95 13479 1390 17.5 10 3 101 623 16 1 4 6 93 795 16 7 s 9 96 1427 is 6 10 6 90 22875 2569 32 4 11.2 110 1156 29 9 5 1 101 1831 38 4 8 .0 130 3034 33 1 13 3 112 11614 •659 8 3 5 6 55 •557 14 4 4.7 94 •398 8 4 3 4 55 1660 18 1 14 1 119 31229 2168 27 4 6 9 68 1637 42.3 5.2 105 1534 32.2 4 9 80 3582 39 1 11.5 97 23352 2593 32 7 11 1 109 1161 30 0 5 0 100 1763 37 0 7 5 123 2991 32 7 12 8 108 12137 1614 20 4 13 3 130 •629 16 2 5.2 104 • 617 12.9 5 1 83 1478 16 1 12.2 103 10789 1548 19 5 14 3 140 445 11.5 4 1 83 852 17.9 7 9 128 1 104 12 1 10.2 87 23359 1800 22 7 7 7 75 995 25 7 4 3 85 1527 32.0 E 5 106 2933 32 0 12 6 106 34657 3269 413 9 4 92 1890 48 8 5 5 109 1929 40.5 5 6 91 4101 44 8 11.8 100 19491 2855 36 0 14 6 143 987 25 5 5 1 101 1310 27.S 6 7 109 2119 23 1 10 9 92 17725 1017 12.8 5.7 56 1118 28 9 6 3 126 627 13 2 3 5 58 1871 20 4 10 6 89 25079 1700 215 6 8 66 1472 38 0 5 9 117 1108 23.2 4 4 72 2706 29 6 10 8 91 35085 2621 33 1 7 5 73 1942 50.2 5.5 in 1867 39.2 5 .3 87 3995 43 6 11.4 96 8818 960 12.1 10 9 106 •460 119 5 2 104 • 440 9.2 S 0 81 1208 13 2 13.7 116 18653 2110 26 6 11.3 111 1086 28 0 5 8 117 1071 22 5 5 7 93 2099 22 9 11 3 95 25911 2746 34 7 10 6 104 1649 42 6 6 4 127 1529 32 1 5 9 96 2903 31 7 11.2 95 9349 868 110 9 3 91 • 418 10 8 4 5 89 674 14 1 7 2 117 1242 13 6 13 3 112 8862 1124 14 2 12 7 124 •354 9 1 4 0 80 •438 9.2 4 9 80 1042 11 4 11.8 100 13644 1330 16 8 9 6 94 661 17 1 4 8 96 827 17 4 6 0 97 1818 19 9 13 1 in 19541 1855 23 4 9 5 93 791 20 4 4.0 81 1299 27.3 6 6 108 2149 23 5 11.0 93 11894 960 12.1 8 1 79 532 13 7 4 5 90 674 14. 1 S . 7 92 1668 IB 2 14.0 119 26454 2231 28 2 11 86 1300 33.6 5 1 102 1484 30 7 5 8 94 3221 35 2 12 7 107 28521 3411 43.0 12 0 117 1402 36 2 4 9 98 1932 40 5 6 8 110 2999 32 8 10 5 89 11637 1322 16 7 114 111 •638 16.5 5 5 110 697 14 6 6 0 97 1267 13 8 10.9 92 43986 4153 52 4 9 4 92 2386 61 6 5 4 109 2503 52.5 5 .7 93 5650 61 .7 12 8 109 565 1 •519 IS 9.2 90 ••260 6.7 4 6 92 •375 7.9 6 6 108 692 7 6 12.2 104 12521 1108 14.0 8 8 87 •627 16 2 5 0 100 923 19 4 7 4 120 1409 15 4 11.3 95 15766 1965 24 8 12 5 122 839 21 7 S3 107 1252 26 3 7 9 129 1686 18 4 10 7 91 16144 2230 28 1 13 8 135 646 16 7 4 0 80 961 20.2 6 0 97 1545 16 9 9 6 81 55460 6568 82 9 11 8 118 3000 77 5 5 4 108 3189 66 9 5 8 94 6973 76 2 12 6 106 28563 2893 36 5 10 1 99 1544 39 9 5 4 108 1396 29 3 4 9 79 3766 41 1 13 2 112 26897 3675 46 4 13 7 134 1457 37 6 S 4 108 1793 37 6 6 7 108 3207 35 0 119 101 Source: SMRB 1982. 1 O O TtXnVPASTE: USAGE (FEMALES) TOTAL FEMALES FEMALE HDWEMAKERS EVPLOVED MOTHERS 18 - 24 25-34 35-44 46-54 55-64 65 OR OLDER 18-34 18 - 49 35 - 49 GRADUATED COLLEGE ATTENDED COLLEGE GRADUATED HIGH SCHOOL DID NOT GRADUATE HIGH SCHOOL EVPLOVED EVPLOYED FULL-TIVC EMPLOYED PART-TIKE NOT EVPLOYED PROFESSIONAL/MANAGER CLERICAL/SALES CRAFTSVEN/FOREVEN OTHER EVPLOYED SINGLE MARRIED DIVORCED/SEPARATED/WIDOYED PARENTS WHITE BLACK OTHER NOR TVEAST-CENSUS NORTH CENTRAL SOUTH WEST NORTHEAST -HtCTG. EAST CENTRAL WEST CENTRAL SOUTH PACIFIC COUNTY SIZE A COUNTY SIZE B COUNTY SIZE C COUNTY SIZE D ALL USERS B C X ACROSS 'OOO DOWN X INDX HEAVY USERS 8 C X ACROSS 000 DOWN X INDX MEDIUM USERS LKJTT USERS The percent of all heavy users who are age 35-44. Percents in this column add to 100% vertically. The projected number of people in thousands. This reflects 3,117,000 women A '000 B C 0 X ACROSS DOWN X INDX A '000 BCD X ACROSS DOWN X INDX 38575 hOO.O 47.6 100 1 149361 100.0 18.4 100 35798 92.8 48.1 101 1 139911 93.7 18.8 102 9747 25.3 58.2 122 1 29211 I 19.6 17.4 95 7007 18.2 48.9 103 1 22621 15.1 15.8 86 9125 23.7 52.1 109 1 30891 20.7 17.6 96 6696 17.4 53.6 113 1 22901 15.3 18.3 100 5877 15.2 49.0 103 I 22311 14.9 18.6 101 4881 12.7 44.4 93 1 21581 14.4 19.6 107 4989 12.9 36.3 76 | 2906| 19.5 21.1 115 16133 41.8 50.6 106 | 53521 35. P 125659 66.5 51.3 108 | 87091 c- \9526 24.7 52.4 110 | 3350* 4863 12.6 53.3 112 ! 4 6317 16 V 17013 44 103B2 * This is an index based on the percent in column C. The 25.0% of women age 35-44 who are heavy users is 7% lower than the 26.7% of total women who are heavy users. This yields an index of 93 (25.0%-*- 26.7%). The percent of all women age 35-44 who are heavy users of toothpaste. These percents project to each individual demographic break. KETRO CENTRAL CITY VETRO SUBURBAN NON VETRO age 35-44 who are heavy users of toothpaste. These illustrative data were taken from a 1982 SMRB Marketing Report. The headings HSHLD INC $35,000 OR MORE $25,000 OR MORE $20,000 - $24,999 $15,000 - $19,999 $10,000 - $14,999 $ 5.000 - $ 9.99S UNDER $5,000 HSHLD OF 1 OR 2 PEOPLE 3 OR 4 PEOPLE 5 OR MORE PEOPLE reflect adult female users of toothpaste grouped by total, heavy, medium and light users. Users of individual brands are reported in the same manner as heavy, medium and light users of the product category. NO CHILD IN HSHLD CHILD(REN) UNDER 2 YRS 2-5 YEARS 6-11 YEARS 12 - 17 YEARS RESIDENCE OWNED VALUE: $40,000 OR MORE VALUE: UNDER $40,000 Figure 20. A Page From a Typical 1982 SMRB Marketing Report Source: SMRB 1982 134 females over 18 (Column C). To enumerate all users of toothpaste, one would consult the corresponding table for adults. That total would indicate the number of persons over 18 using toothpaste. The Investigator must use judgment on a case-by-case basis to decide whether "adults" accurately represent the user population. In the case of toothpaste and similar hygiene products, census totals for persons between the ages of 1 and 17 should be added to the adult total derived from SMRB. Examination of Tables 23 and 24 Indicates the ease by which users of different brands or types of products can be enumerated. In most cases, the totals under Column A or the percentages In Column C are directly applicable to enumeration. Distinctions among adult users of different ages are easily made, If such distinction Is required. Subsection 5.4.1 further discusses age and sex characterization of consumers using these data. The SMRB data are clearly Intended to describe the market variability of existing products. Consequently, the data are generally more applicable to existing chemicals and product formulations currently on the market than to new chemical substances. The SMRB data may, however, prove useful to assessments of PMN substances when the new chemical Is Intended for use as a substitute for an existing chemical. If use Information Included In a PMN submittal is sufficiently detailed, the SMRB data can be used to predict the number of exposed consumers. Method 5-2 summarizes the use of SMRB data for any chemical or product. Examples of the use of SMRB data are presented In Appendix A-4. That discussion provides clear methods for estimating the number of product users or the actively exposed population. Those who may be exposed to chemical residuals by their proximity to consumer products are passively exposed and are more difficult to enumerate accurately. Simmons' demographic data for households can be used toward this end, as Illustrated In Method 5-2 and Appendix A-4. The data set used to enumerate a product's users (by usage, type, or brand) also presents the frequency distribution of household size. For example, Table 22 Indicates that 36,879,000 women use rug cleaners (Column A, all users, total female homemakers). Near the bottom of the page, still under Column A, are the numbers of households having 1, 2, 3 or 4, or 5 or more persons; these households also total approximately 36,879,000. To approximate the number of persons living In the 36,879,000 households, apply the frequency distribution and household size. Ranges can be used to accurately estimate the exposed population; use of the high end of the ranges generates a conservative estimate of exposed persons. 135 Method 5-2. Enumeration of Exposed Consumer Populations via the Use of Simmons Market Research Bureau Reports Step 1 From the list of consumer products known to or thought to contain a chemical substance under investigation, identify those for which SMRB collects use data (Table 20). If SMRB does collect data, identify the appropriate product category volume(s) from Table 19. Step 2 Identify applicable tables for enumeration as follows; • If chemical substance is found in all types of products and brand names, the usage tables should be used. • If chemical substance is found in only certain product types (e.g., aerosols versus liquids), the type tables should be used. • If chemical substance is found in only certain brand names, the table on individual brand products should be used. Step 3 Enumerate the actively exposed population as follows; • If the exposed population is all adults and the data are available as such in SMRB, the column for all users (Column A) should be used. If the data are only available as adult males and adult females, the data in column A in each table should be added for the total exposed population. The investigator should decide whether children of less than 18 years of age are also actively exposed. If so, the age bracket should be determined and the total population in the U.S. for the age bracket should be obtained from Table 12 (Section 2.4). The adult percentage of users (Column C) should then be applied to the total number of children in the specified age bracket. The resulting population estimate should then be added to the total adult population for complete population enumeration. • If only one member of the household is actively exposed, then the data for all users as listed for the product buyers (e.g., female homemakers) should be used to enumerate the exposed population. • If the entire household is actively exposed but the SMRB data are only available for the type of buyer, the procedures to enumerate the exposed population are the same as the procedures to enumerate the passively exposed population described in Step 5. 136 Method 5-2. (continued) Step 4 To enumerate the exposed population according to heavy, medium, or light exposure, the same procedures previously discussed are applicable; however, rather than using the column of data for all users, the columns of data for heavy, medium, and light users should be used. This should be done only when exposure levels are derived from the SMRB use patterns. Step 5 To enumerate the passively exposed population, two approaches are possible. The second approach will provide a more accurate estimate. Both approaches assume that the actively exposed population will also be passively exposed. Option 1 - Enumerate the actively exposed population as described in Step 3. Multiply this population by 2.73, which is the average number of members per household in the U.S. Option 2 - Using SMRB collected demographics on the buyer's household size, multiply the household size by the number of buyers and then add the results to estimate the total passively exposed population. For example, to generate a conservative estimate: 1 person household = Number Buyers x 1 = A 2 person household = Number Buyers x 2 = B 3 or 4 person household = Number Buyers x 4 = C 5 or more person household = Number Buyers x 6 = D A+B+C+D= total passively exposed population 137 5.3.2 Enumeration of Exposed Populations via Production and Sales Data Users of consumer products can be enumerated by applying a number of assumptions and estimation techniques to economic data such as chemical production volume, Census of Manufactures output, and retail sales Information. To enumerate the users of a consumer product, the Investigator must estimate the number of units of a product bought by consumers, then apply data on usage patterns to determine the average number of consumers. The result of this calculation will be an estimate, but a fairly valid one; the components of the calculation are reliably predicted. An example of the method (Method 5-3) Is presented In Appendix A-4. The parameters specific to this calculation are the number of units of the product manufactured or sold annually and the annual usage patterns. The first, the number of units, can be derived In the manner described In problem 2 In Appendix A-4 (by assuming an average mass per unit) or by consulting published data. The Census of Manufactures (Bureau of the Census 1980) lists production of very specific products (by seven digit SIC code) In units such as pounds, kilograms, cases, etc. The assessor must assume that production equals sales to consumers. Other data bases containing this type of Information and specific Information on retail sales are listed In the consumer exposure assessment methods report (Volume 7). Use patterns can be either estimated on a product-specific basis or derived from the use Information provided by SMRB data, as detailed In the previous Subsection (5.3.1). It should be noted that this method of population estimation assumes that users are brand-loyal; l.e., for any product, a consumer either always or never uses a brand with the chemical. The result of this assumption is that some consumer populations may be underestimated; some individual exposures may likewise be overestimated. The calculated individual exposure resulting from the use of the product will be higher than if the consumer used various brands or formulations, some of which contained the chemical substance and some of which did not. The information needed to resolve this problem is not available at this time. 5.3.3 Enumeration of Exposed Populations via Chemical-Specific Information Populations exposed to chemical substances in consumer products can be enumerated through the use of various sources of chemical-specific information. The approach is not as methodical as that applied to the use of market research data or economic (production and sales) data; rather, it entails researching information sources each time a chemical is assessed. The various types of information resources and the advantages and limitations of each are discussed below. 138 Method 5-3. Enumeration of Populations Exposed to Chemicals in Consumer Products Via the Use of Economic Data Step 1 Determine the number of units of the product sold or produced annually. Option 1 - consult the Census of Manufactures (Bureau of the Census 1980) to obtain production in unit quantities. Option 2 - estimate the number of units produced by dividing the amount of the chemical destined for that use by the formulation percent and the total mass of product per unit. Option 3 - consult Volume 7 for alternative sources of data (sales information, computerized data). Step 2 Determine use patterns for the product. The SMRB presentation of heavy-medium-1ight use, discussed in Section 5.3.1, provides data for most products. Heavy use may, for example, be defined as 5 or more cans per week; medium use, 3 or 4 cans, and light use, 2 or fewer cans per week. Step 3 Calculate the exposed population by dividing the production volume in units (from Step 1) by the units used per person per year (from Step 2). 139 (1) Direct contact with associations . Associations are able to provide many types of consumer-related Information. Many associations are headquartered In the Washington, D.C., area and can be found In the telephone directory. The most comprehensive list of associations, however, Is In the Encyclopedia of Associations (Gale Research 1980). Although associations can often provide the most accurate and precise estimates of consumer populations, acquiring the data may be time consuming and may therefore limit the usefulness of this method to detailed assessments. When an association Is consulted for population estimates, the contact should be Informed of the reason for the request so that he can provide the best possible data. The representativeness of the data should be questioned; for example, a hobbyist association may be able to provide a membership number and also be able to say that the membership represents 75 percent of the total hobbyists. Although there are some limitations to this approach, It has been used successfully In exposure assessments for many existing chemicals. When sufficient time and use Information Is available, PMN substances can be Investigated In the same manner. Care must be taken to avoid disclosure of confidential business Information (CBI) provided by PMN submitters. (2) Government agencies . The Environmental Protection Agency (EPA), the Consumer Product Safety Commission (CPSC), and the Bureau of the Census can provide pertinent consumer Information. The Information Is available through direct contact with experts In the agencies and the reports they publish. CPSC has collected a great deal of information on recognized hazards such as asbestos. Information provided by CPSC may aid exposure assessments of consumer products containing existing chemicals and new substances Intended as substitutes for recognized hazards. The CPSC, however, limits its data collection efforts largely to substances that have proved harmful. Unless a new chemical Is similar In properties and Is analogous in use to an existing chemical, CPSC's data are of little aid In Investigating new chemicals. The many publications of the Bureau of the Census may contain useful Information. For example, those exposed to formaldehyde by residing in mobile homes were quantified (Versar 1982) by consulting the Annual Housing Survey (Bureau of the Census 1981). The Statistical Abstract of the United States (Bureau of the Census 1982) may also provide activity-related data that are useful in enumerating consumer populations. 140 Studies of existing chemicals are often conducted by more than one EPA Office and by many contractors. An exposure assessment of such a substance will benefit from a review of the published literature (available through the National Technical Information Service). The authors or sponsors of these reports may provide additional data If contacted directly. Some consumer products are so widely used that one can safely assume ' the entire population of the U.S. may be exposed. For Instance, all persons contact plastics and fabrics; common additives to them may cause nationwide exposure. The most recent data available from the Bureau of the Census should be used to enumerate the exposed population. Currently, a total of 226.5 million persons are reported to reside In the U.S. (Bureau of the Census 1982). 5.3.4 Enumeration of Consumers Performing Amateur or Hobbyist Activities Consumers may be exposed to chemical substances In products designed mainly for use by professionals. Persons who do their own automobile maintenance and repair, house painting, lawn care, carpentry and remodeling, or photographic film development may be exposed to a chemical substance In a product that might be overlooked In a consumer exposure assessment. Enumeration of the exposed population may be keyed to the number of people engaged In these activities when other enumeration procedures, as previously discussed, are not possible. This method of enumeration, however, overestimates the exposed population because It assumes that all people who engage In a particular activity use the product or products containing the chemical substance. All of the estimates assume that there Is one amateur per household. The estimates presented below and summarized In Table 25 rely on the Bureau of Census (1982) estimate of 77,330,000 households In the U.S. and the following additional data. (1) Automobile work . The U.S. Department of Energy (1980) estimates that 85 percent (65,700,000) of all households have at least one motor vehicle and that 55 percent of those households change their own oil. Thus, 36,100,000 households are estimated to have at least one person who changes his own oil. (2) Painting . SMRB (1978) reports that 17.5 percent of U.S. households purchased exterior paint and 25.7 percent purchased Interior paint during a one-year period. If It Is assumed that the persons purchasing paint Intended to use It themselves (rather than providing It to a hired professional painter), the potentially exposed population can be estimated. If only one member of each household uses paint, then 13,533,000 persons are actively exposed to exterior paint and 19,874,000 are exposed to Interior paint. The members of each household would experience passive exposure to paint components, probably only In 141 Interior paint. With an average of 2.78 persons per household, the passively exposed population is 55,250,000 persons. (3) Lawn and garden care . The number of people who mow their own lawn provides a fair estimate of people who use fertilizers, pesticides, and other lawn and garden products. SMRB (1978) estimates that 37 percent of households own a lawn mower. Assuming that one person from each household is responsible for lawn care, an estimate of 28,612,000 people tend their own lawns. (4) Carpentry . A rough estimate of the number of people who engage in carpentry can be made based on ownership of electric saws. Anyone seriously Involved in carpentry and, therefore, potentially exposed to chemical substances in carpentry related products, would own this tool. SMRB (1978) estimates that 23 percent of all households own an electric saw. Therefore, at least 17,786,000 households Include amateur carpenters. (5) Remodeling . The number of people potentially exposed to chemical substances as a result of household remodeling activities can also be estimated from SMRB data. SMRB (1978) estimates that 1,132,000 basements, 2,313,000 kitchens, 2,572,000 bathrooms, and 3,898,000 other rooms were remodeled in 1976-77 by a household member. Based on the number of households in 1977 as estimated by SMRB, 74,019,000, the following percentages are derived; 1.5 percent of households had basements remodeled, 3.1 percent of households had kitchens remodeled, 3.5 percent of households had bathrooms remodeled, and 5.3 percent of households had other rooms (e.g., living rooms, bedrooms) remodeled by a household member. Assuming these data are representative of current remodeling activities, the percentages can be applied to the current number of U.S. households to calculate populations. The results are presented in Table 25. (6) Photography . An estimated two to three million people develop their own film (Wolfram Report 1979). This would be 2.6 to 3.9 percent of the U.S. households, assuming that there is only one photographer per household. 5.4 Characterization of Exposed Populations Exposed populations are often characterized by age and sex, since physiological parameters affecting exposure or risk are often age- or sex-dependent. Characterization of consumer populations is especially important, since many products are designed for or used by specific subpopulations. 142 Table 25. Suntnary of the Number of Households That Can Be Considered To Have at Least One Amateur or Hobbyist with Respect to a Specific Activity. Activity Number of households^ Percent of all households Crankcase oil and filter change 36,100,000 47 Lawn and garden maintenance 28,612,000 37 Painting (exterior of house) 13,533,000 17.5 Painting (interior of house) 19,874,000 25.7 Carpentry 17,786,000 23 Remodeling Basement 1,160,000 1.5 Kitchen 2,397,000 3.1 Bathroom 2,707,000 3.5 Other 4,098,000 5.3 Photography 2,500,000 3 ^Based on 77,330,000 households in the U.S. (Bureau of the Census 1982). 143 As was discussed In Subsection 5.3.1, the SMRB data are presented by detailed demographic characteristics. The populations reported as buyers/users of each product, assumed to be the actively exposed populations, are defined by sex and then stratified by age (see Tables 22 to 24). The characteristics of adults actively exposed to consumer products are therefore readily available. Less easily characterized are persons under the age of 18 and passively exposed populations. The SMRB data report only the relative frequency of the presence of children In the age groups of 0 to 2, 2 to 5, 6 to 11, and 12 to 17 years of age In the households with active users. The only data available for characterizing the consumer population under 18 by age and sex are the national distributions presented In Section 2.4 of this volume (Table 12). Should such a characterization of the population be necessary, the assessor must assume that the affected group can be described by those data or a discrete subset thereof (l.e., males or females or some defined age group). As described In Subsection 5.3.1, persons passively exposed In a user's household can be enumerated by use of the relative frequency of household sizes. However, no characteristics of the household members are available; generic data must be used to characterize that population. If It Is assumed that the total population of persons living In households with users of the product represent a cross-section of the total U.S. population, the data (Table 12) In Section 2.4 of this volume can be used to describe the age and sex characteristics of the group. Method 5-4 summarizes the steps to be performed In the characterization of populations exposed to chemical substances In consumer products. 144 Method 5-4. Characterization of Populations Exposed to Chemical Substances in Consumer Products Step 1 If the consumer population was enumerated by the use of SMRB data, use the demographic characteristics reported for buyers/users to characterize the actively exposed population by age and sex. Populations enumerated by other methods can also be characterized by consulting the SMRB report for the product(s) most similar to that being assessed. Step 2 Consult Section 2.4 (Table 12) of this volume to derive generic age and sex characterization for: - Consumer populations under the age of 18 - Passively exposed household members - The entire population of the U.S. 145 5.5 References Bureau of the Census. 1980. 1977 Census of manufactures. Washington, DC: U.S. Department of Commerce. Bureau of the Census. 1981. Annual housing survey. Washington, DC: U.S. Department of Commerce. Bureau of the Census. 1982. Statistical abstract of the United States, 1982-83. 103rd edition. Washington, DC: U.S. Department of Commerce. Gale Research Corp. 1980. Encyclopedia of associations. Michigan: Gale Research Company. SMRB. 1978. Simmons Market Research Bureau. Simmons studies of selective markets and the media reaching them. Volume 29. Home furnishings, remodeling and upkeep. New York, NY. SMRB. 1981. Simmons Market Research Bureau. Simmons studies of selective markets and the media reaching them. New York, NY. SMRB. 1982. Simmons Market Research Bureau. Simmons study of selective markets and the media reaching them. New York, NY. U.S. Department of Energy. 1980. Analysis of potential used oil recovery from Individuals. Final report. Washington, DC: U.S. Department of Energy, D0E/BC/10053-21. Versar. 1982. Exposure assessment for formaldehyde. Draft report. Washington, DC: U.S. Environmental Protection Agency, Office of Toxic Substances. Wolfram Report. 1979. Wolfram report on the photographic Industry. Modern Photography, New York, NY. 146 6. POPULATIONS EXPOSED TO CHEMICAL SUBSTANCES VIA THE INGESTION OF DRINKING WATER 6.1 Introduction This section presents methods for the enumeration and characterization of populations exposed to chemical substances via the Ingestion of drinking water. The methods described are applicable to publicly and privately supplied drinking water that may contain chemical substances as a result of (1) Industrial, commercial, and household effluents to surface and ground water, (2) runoff or seepage from waste disposal sites, (3) non-point source runoff or seepage from agricultural and nonagricultural land uses, (4) drinking water treatment processes, (5) drinking water distribution systems, and (6) pollution of unknown origin. The methods are based on exposure as a result of the voluntary Ingestion of drinking water; as such, the methods do not consider Involuntary Ingestion (e.g., swallowing of water during swimming) or dermal and Inhalation exposure to chemical substances in drinking water. Figure 21 Is a flow diagram of the three-stage method framework for enumerating and characterizing populations exposed to chemical substances via the Ingestion of drinking water. The following paragraphs briefly describe each of the stages; detailed Information is provided in subsequent sections. The first stage, identification of exposed populations, Is accomplished by examining the sources of the chemical substance. Detailed Information on procedures to complete a drinking water exposure assessment, which Include identification of the exposed population, Is Included In Volume 5 of this series, In "Methods for Assessing Exposure to Chemical Substances In Drinking Water." Subsection 6.2, therefore, only briefly describes the procedures for identifying the exposed population. Enumeration of the exposed population is discussed In Subsection 6.3. This stage Involves the use of various computerized data bases that contain Information on drinking water such as the sources of the raw water supply, intake locations, treatment methods, and populations served. Enumeration also Involves the use of generic data on populations served when detailed geographic resolution is not required or when the financial or manpower constraints of the exposure assessment effort do not permit the development of detailed information. The final subsection (6.4) describes the procedures for characterizing the enumerated population according to age and sex. Data sources are presented which will provide age and sex characteristics of 147 o +-> CD CO C CD •r- co M c •I— !-1 S- O) CL) +-> .c: U +-> ra S- ra ra -r- -c > C_) 00 "O CL) sz a ra cz ra CD +J C 00 •r- -O -t-> D ra CO) i_ QJ r— E ra Z 3 O C -I- LlI E a) i- _sr o c_> 4- o -*c +-> o *o 2 QJ CL) co S- E O CD ra a. +-> i- X ro LJ- LlJ 3 CD CO CD CD C C ra O -t- 4 - > -r- -S*C CO +-> C I ra -I— CD .— S- CD D Q 5- CL -C O 4 - I— Q- O C\J CD S- rs CD I = a co CO 5 CO a cc LL. H 148 populations where geographic detail Is required or generic age and sex characteristics for situations where specific detail Is not required. Examples of the use of the methods In this section are presented In Appendix A-5 of this report. 6.2 Identification of Exposed Populations Exposed populations can be Identified either through knowledge of the sources of chemical contamination or by examination of monitoring data. The former Is a "materials balance" approach and comprises three types of sources: 1. Sources that can be geographically defined (e.g., Industrial effluents and non-point sources of water pollution). 2. Sources related to the treatment processes used In production of potable water (e.g., use of chemicals as coagulant aids). 3. Sources within the distribution system (e.g., dissolution of solvents from glued pipe joints). Monitoring data may Identify water sources with contamination of known or unknown origin. Comprehensive Identification must consider all three source types as well as available monitoring data. Identification may be keyed to the geographic location of the water supply, treatment methods, distribu¬ tion system type, or any combination of the three. The procedure for Identification Is presented as Method 6-1. It Is readily apparent that only Step 1 of Method 6-1 provides positive Identification of exposed populations; the materials balance approach outlined In Steps 2 and 3 Identifies those that are potentially exposed. The drinking water exposure assessment methods report (Volume 5) presents detailed methods for Identifying exposed populations. The populations Identified In this stage must subsequently be enumerated. The following subsection discusses the methods for enumerating populations defined by the three types of sources and Identified through monitoring data. 6.3 Methods for the Enumeration of Exposed Populations This section discusses the recommended procedures and data sources for enumerating populations exposed to chemical substances via the Ingestion of drinking water. The section Is divided Into four subsections based on the categories for Identifying the exposed 149 Method 6-1. General Procedure for Identifying Populations Exposed to Chemical Substances in Drinking Water Step 1 Obtain all available monitoring data for the substance being assessed. Monitoring data for finished water provides positive identification of an exposure source; however, it may not identify what the source is. The population served by the utility surveyed is an exposed population. Step 2 Examine the environmental releases of the substance in the ambient environment. Knowledge of these releases, coupled with knowledge of the environmental fate of the substance in the aquatic environment, leads to identification of contaminated aquifers and surface waters. The persons drinking these waters are potentially exposed. Step 3 Examine the uses of the substance. If it is used in the drinking water treatment or distribution systems, the populations served by those systems may be exposed. (NOTE: Detailed information on identifying sources of chemical contamination and exposed populations is provided in Volume 5 of this exposure assessment methods report series.) 150 populations. Subsection 6.3.1 presents the procedures and data sources for enumerating exposed populations that are geographically defined by the sources of the chemical substance of Interest; the procedures In Subsection 6.3.2 enumerate populations exposed to chemical substances as a result of drinking water treatment processes; the procedures In Subsection 6.3.3 enumerate populations exposed to chemical substances from the materials (e.g., pipes) used to distribute drinking water; and the procedures In Subsection 6.3.4 enumerate populations exposed to chemical substances that have been Identified from water quality data collected during drinking water monitoring. The Investigator's choice of an appropriate method should be based on how the exposed population has been Identified. 6.3.1 Enumeration of Populations In Specific Geographic Areas This section presents methods for enumerating populations In specific geographic areas where sources of the chemical substance of Interest are located. These sources may Include Industrial, commercial, or household effluents, Publicly Owned Treatment Works (POTWs), waste disposal sites (e.g., landfills, wastewater lagoons), and transportation related spills. The individual volumes of this series discuss the data sources and procedures for Identifying the sources of a chemical substance. Methods to link geographically-defined point sources with nearby drinking water Intakes are discussed in the drinking water exposure assessment methods report (Volume 5). Identification of the sources of the chemical substance in turn permits the Identification of the affected raw drinking water supplies. Identification of the raw water supplies, therefore. Is the first step required. The type of raw water supply used, either surface water or ground water, determines the data bases that should be used in the population enumeration effort. (1) Surface water . The principal data source for identifying both public and private drinking water utility companies that use surface water as their raw water supply Is the Water Supply Data Base (WSDB). WSDB Is a computerized data base maintained by the EPA Monitoring and Data Support Division, Water Quality Analysis Branch. It contains Information on the location of surface water utilities; the locations of the utilities' treatment plants, Intakes, and sources of raw water; the populations served; and the average and maximum daily production. A complete description of WSDB Is available in Water Supply Data Base: Inventory of Surface Water Supplies and Addendum on a Groundwater Data Base Structure (Versar 1981). The most useful application of WSDB Is the Integration of Its data with data on sources and concentrations of chemical substances contained In other data files maintained by EPA-MDSD, such as the Industrial Facility Discharge (IFD) File and the STORET Water Quality Data Base. The data In each of these files can be accessed via another data base known as the REACH File. A complete description of the REACH File Is not within the scope of this report; essentially, however, the REACH File Is 151 a data source for Information on surface water, rivers, streams, lakes and reservoir segments that are coded within the U.S. Geological Survey's Hydrologic Unit Cataloging System. The drinking water Intake locations In WSDB, the Industrial discharge locations In IFO, and the locations of water quality monitoring stations In STORET are similarly coded with a REACH number. The REACH number, therefore, hydrologically links these files together. EPA-MDSD has developed several software packages to access the data contained In the various files via the use of the REACH number. Population data contained In WSDB may be obtained In this Integrated approach. Method 6-2 lists the procedural steps of the Integrated approach to obtaining Information on sources, affected surface water supplies, and populations served. The drinking water exposure assessment methods report (Volume 5) provides a much more detailed description of WSDB and the other hydrologically linked data bases. (Note: Requests for data base retrieval should be directed to Mr. Phil Taylor, USE PA, Monitoring and Data Support Division, Water Quality Analysis Branch.) The Investigator will now have Identified sources, raw water supplies, drinking water utilities, and populations served In one Integrated process. EPA-MDSD Is further expanding the usefulness of the Integrated approach by assigning river mile Indexes to all discharge points In IFD and Intake points In WSDB. This will facilitate determination of the distances between these points. Distance calculations can then be used to model In-stream water quality dilution and the resultant concentration at drinking water supply intake points. Details on retrieval methods, keywords, and other integrated approaches are available in General Information on IFD, Drinking Water Supplies, Stream Gages, Reach, and Flshkill Files and Retrieval Procedures for Hydroloqically Linked Data Files (USEPA 1981a). The enumeration of populations exposed to chemical substances via surface water supplies contaminated by other sources (e.g., runoff from waste disposal sites, non-point sources) is also straightforward. The recommended approach is presented as Option 2 in Method 6-2. The investigator should be aware of two limitations In WSDB, and they should be noted In the exposure assessment report. First, the intake location coordinates for drinking water utilities that serve populations less than 25,000 are only approximate locations (generally within +10 minutes of latitude and longitude). Location coordinates for utilities serving more than 25,000 people are extremely accurate because they were developed from USGS 7.5-minute topographic maps. The second limitation Is that the population data were collected between 1965 and 1975 and may not reflect current populations. If the data set of identified utilities Is limited, the investigator should contact the drinking water utility supervisor and directly request up-to-date data on populations served by 152 Method 6-2. Enumeration of Populations Exposed to Chemical Substances in Surface Sources of Drinking Water Using the REACH File Option #1 - To be used for surface sources contaminated by industrial and POTW effluents. For detailed information on the following steps, see Volume 5 of this methods series or USEPA (1981a). Step 1 Identify applicable SIC codes for the chemical substance of interest (s-se Volume 2, Methods for Assessing Exposure to Chemical Substances in the Ambient Environment). Step 2 Request retrieval of IFD data for facilities within SIC category (requests should be directed to Mr. Phil Taylor, USEPA, Monitoring and Data Support Division, Water Quality Analysis Branch, Washington, DC). Step 3 Identify receiving water bodies by REACH number and USGS cataloging unit. (Note: The REACH number actually consists of 11 digits and includes the 8-digit USGS cataloging unit and the 3-digit EPA segment number. The segment number is frequently referred to as the REACH number. Retrievals limited to the entire 11-digit REACH number will identify water supply intakes and industrial discharges only on that particular segment. If a retrieval is made according to the USGS cataloging unit only, it will identify all points of interest in the USGS surface water drainage basin.) Step 4 Request a hydrologic tree retrieval (HYDRO) from EPA-MDSD for each REACH number or cataloging unit identified. Include a request for populations served in the data tabulation. HYDRO will list in a tree diagram industrial discharge pipes, water supply monitoring stations, and water supply intake points according to hydrologic order. "Hydrologic ordering" provides stations on the most downstream reach first, and proceeds upstream, reach by reach. Option #2 - To be used for surface sources contaminated by non-industrial effluents (e.g., chemical spills, non-point sources, waste disposal site runoff). Step 1 Identify contaminated raw water supplies by USGS Hydrologic Units (8-digit number) using USGS State Hydrologic Unit Maps. Segment numbers, if desired, can be obtained from Mr. Robert Horn, EPA-MDSD, Monitoring Branch. Step 2 Request WSDB retrievals from EPA-MDSD according to USGS hydrologic units. Include population served and intake name and location as parameters in data tabulation request. Check WSDB retrieval to determine whether listed utilities are withdrawing water directly from or downstream of the water body of concern. 153 the utilities' distribution system. (Note: Drinking water utilities will frequently perform a residential meter count rather than an actual head count of residential customers. If data are provided In this format, the Investigator can assume 2.73 persons/meter based on Census data for the number of persons per household (Bureau of Census 1982a) to enumerate the total population.) The WSDB Is recommended as the primary data source for enumerating populations exposed to chemical substances via the Ingestion of surface supplied drinking water. This Is principally due to the Inclusion of the REACH number In the data base structure. That number facilitates an Integrated process of Identifying sources (I.e., Industrial and POTW dischargers) of chemical substances and enumerating exposed populations as previously described. There Is another data base, however, that Includes surface water populations served and Intake locations. This data base, maintained by the EPA Office of Drinking Water, Is known as the Federal Reporting Data System (FRDS). FRDS, discussed In the subsequent section on ground water, can be used as a source of Information supplementary to that contained In WSDB. It can also be used to check the accuracy of the WSDB-llsted population data. FRDS population data are updated annually by each primary agency (I.e., state or EPA region). As such, the population data Is more accurate than the data stored In the WSDB. Cross-referencing of the two data bases Is straightforward because WSDB listings Include the FRDS utility number In the data structure. FRDS geographic restricted retrievals can be made by state, county (I.e., according to FIPS code), SMSA and US6S hydrologic units. FRDS, however, does not Include EPA developed stream segment numbers for Intake locations; therefore, Integrated data retrievals with other STORET and EPA-MDSD-malntalned data files are not possible. The recommended method for obtaining and using FRDS data Is presented In Method 6-3. (2) Ground water . The principal data source for Identifying either public or private drinking water utilities that use ground water Is the previously mentioned Federal Reporting Data System (FRDS). FRDS Is an Information management system used by both EPA headquarters and regional personnel to monitor program performance In each state. It contains Inventory data as well as the compliance status of each public water supply. Separate data bases are maintained for each *A.W. Marks, EPA-Offlce of Drinking Water, Washington, DC: personal communication with M. Callahan, EPA-Offlce of Toxic Substances; memorandum dated August 2, 1983. 154 Method 6-3. Enumeration of Populations Exposed to Chemical Substances in Surface Sources of Drinking Water Using the FRDS Data Base Step 1 Request FRDS retrieval according to geographic area of interest (e.g., by state and/or county according to FIPS code, by SMSA according to SMSA code, or according to USGS cataloging unit). Note: FRDS retrieval requests should be directed to: Mr. Avrum Marks Manager Computer Systems Staff EPA Office of Drinking Water Washington, DC 20460 Step 2 Scan retrieval for utilities listed that obtain raw water supplies from the water bodies of interest. Step 3 Check for utilities that purchase finished drinking water from another utility. Under "source type," these utilities will be listed with the letter P. When totaling populations served, the investigator should not count population data for these utilities since these are already contained in the population served data for the utility that is processing the raw water. This avoids "double counting" the exposed population. Step 4 Total the data on population served to enmumerate the total population exposed to the chemical substance of interest. 155 fiscal year after 1978 as well as the current year. FRDS became operational during January of 1979. As of April 15, 1980, Information from all 57 states and territories, as well as Information on Indian reservations within four EPA regions, had been received and processed. Four types of data are collected by FRDS, based on regulatory reporting requirements (Marks 1980): 1. Inventory. This Includes public water supply (PWS) capacity, source Information, monitoring requirements, and facility name and address. Figure 22 Is a sample report containing the types of Information available for each PWS. However, since many of the data elements are not required for federal reporting, all of this Information may not be available for each PWS. 2. Violation. This Includes data pertaining to noncompllance with EPA or state standards by a specific water supply. 3. Variance and exemption. This Includes data pertaining to authorized exceptions to the standards which are granted to a specific water supply. 4. Enforcement action. This Includes Information pertaining to actions taken against a public water supply. In addition, summary statistics for each state are generated and maintained within the FRDS data base. The data types of greatest relevance are the Inventory Information and the summary statistics. Besides the ad hoc capabilities of the system, 11 standard reports have been generated. These are summarized In Table 26. The most useful are marked with an asterisk; they Include reports listing data on populations served (number of meters), source location, treatment types (where available), and percentage breakdowns of data for Individual states. The procedure for enumerating populations exposed via ground water Is to define the area of concern as determined by the sources of the chemical substance of Interest (e.g., landfill leachate to ground water In a specific county or state). This step will be completed as part of the overall exposure assessment process. Detailed Information on procedures for completing this step are presented In the drinking water exposure assessment methods report (Volume 5). The procedure Is summarized In steps In Method 6-4. The output of the procedure will be a list of all facilities In the geographic region selected (which may or may not be tapping the aquifer of Interest), together with the population served and treatments used by each facility. The degree to which this Information Is complete depends on the thoroughness of the Input from the particular state. 156 X UJOUIZ OKI 1^1 z Z •) 3 « A 3 09 ■ u 3 Ui fr» A- aa X X C3 •• o o O Z 03 Cal €3 A A Ui Ui aa Aa 2 3 Q X X A CO Ui o Ui aa aa aa O O aa <. 3 mm Ui o O X fra UJ Cl O a A A Aa 3 X Z u > X A X A- 03 9) © o fra < A- O Ui o fr* u. 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X • X CO 2 X A X fra 3 3 •< 3 z A la 3 CJ 9 O 3 mm 3 a- UJ n Ml G aa aa © A c A 3 A» A- Z UJ 3 X _ , aa c X r ■< r fra Z X aa X X aa 3 aa aa aa < c i- < c z 5 X UJ C9 X A* A X CO •— < 3 a X 'd z 3 Q O 3 3 z 3 Uj m © X cO A z u. aa A- A Z • z Z • z m < X AJ o <1 X X aa c CO c c CO 3 a >— © z o 3 C z T T X X X 00 aa n © — X ►- T* 3 cO 3 c J) 3 3 UJ X o © z 2. — — i UJ vO ui UJ n UJ o X CO © «a <3 3 3 ■A X 9 X X 9 X o rvj cO -a A Z U. 3 aa X X 3 UJ z 3 a- «* 3 X 3 X aa A « m I A X 3 aa Q U X X 3 3 3 mt r 3 3 fca c a a X X CO cn u. X la y u I *3X9aooo co A 9) u x A 3 z V X «o <3 z o o z 3 O o Ui X X A 3 X X z z o 3 * A X Z 3 a« uj •— uj z X ~ O X < 3 X 3 a- ~ z o a uj 3 C J 3 3 Z < z IliVOO 3 VP O f\J 3 • • • 19 • • • Z ** •• •• O ft* A4 AJ uj — o <\i 3 O 9 3 • • • a m m ^009 J O O «T O O O Z X • UJ to X < x X 3 z 3 X •< A X 3 a 3 ui © — x o C a- © — 3 0 3 O uJ — Z T UJ a — aj x 9 3 9 X C I UJ -j —• 3 > — X X X 3 X uj uj ^ U X O u. tO uj d o *— «* X u. X I 5 CO 4J O ■ 3 X — > Z < — — — X) < <» x *- CO X O 3 X X « I o X 3 3 CO CO X 3 X u_ i X Z u. 3 uj X 3 3 3 <0 iO O u n x a uj 2 > Z O *5 X J 4J 1 LJ 3 3 I r u j j C 25 persons 2 Pr imarily ground water systems 161 Method 6-5. Enumeration of Populations Exposed to Chemical Substances as a Result of Lack of Treatment Processes Step 1 Identify the treatment process or processes of interest (e.g., coagulation, chlorination, fluoridation). Step 2 Identify the source(s) of raw water (i.e., surface, ground, or both). Step 3 Identify the geographic area of interest (e.g., state, county, SMSA, USGS cataloging unit). Step 4 Request FRDS retrieval from EPA Office of Drinking Water according to the above-identified parameters. Include a listing of the population served in data retrieval request. Exclude utilities that purchase finished or raw drinking water ("P" code) to avoid counting populations twice. NOTE: Reporting of treatment techniques is not required of states by EPA. The sizes of the populations covered by various treatment methods are generally under-reported. FRDS, therefore, provides only an order-of-magnitude estimate of the size of the exposed population. 162 6.3.3 Enumeration of Exposed Populations by Type of Distribution System The distribution system may be a source of exposure to chemical substances. Distribution system components and potential contaminants are listed In Table 28. It would be Ideal to enumerate the populations served by each type of distribution system and component. This approach Is not feasible for two major reasons: • While It Is simple to enumerate the customers served by any distribution system, It Is nearly Impossible to determine the components of any system. Many types of pipe are used In each system, and there Is often no record of the type of piping. • Neither historical nor current data on sales and use of pipe and other components In drinking water distribution systems are available. Some qualitative generalizations about the relative uses of various pipes are possible. The generalizations are based on the applicability of different pipes In different situations. Plastic pipe (usually polyvinyl chloride (PVC)) dominates the market In rural water systems. PVC pipe has long been accepted for drinking water supply, which Is the main water use In rural areas. In urban areas, fire protection Is a major concern, and the high pressures at which water Is piped In cities do not allow the use of PVC. It has been estimated that 11.2 million rural Americans were drinking water from PVC pipes In 1979*. The number of urban users Is unknown but Is thought to be small. The relative proportion of Americans drinking water from PVC pipe Is expected to Increase, since PVC Is used mainly In new construction areas. In urban areas, the market for water pipe Is very competitive. It appears to be fairly evenly split among concrete, ductile Iron, asbestos- cement, and steel pipe In the 16-to 24-Inch size range, and Iron and copper for smaller p1pe.+ It should be noted that the smaller pipe (less than 16 Inches In diameter) accounts for 90 percent of the linear footage of pipe lald.'k *B111 Nesbitt, President, Uni-Bell Plastic Pipe Assn., personal communication with Gina Hendrickson, Versar, Inc., April 1982. +John Capita, American Water Works Assn., personal communication with Gina Hendrickson, Versar, Inc., April 1982. ^Joe Willett, Concrete Pressure Pipe Assn., Personal communication with Gina Hendrickson, Versar, Inc., April 1982. 163 Table 28. Distribution System Components and Potential Contaminants Component Potential contaminant Metal pipe (copper, iron, steel) Metals; microbial products Pipe joint glue Organic solvents Asbestos-cement pipe Asbestos fibers Lined pipe and plastic pipe Plastic monomers, polycyclic aromatic hydrocarbons 164 A very rough estimate of the urban populations served by different types of pipe can be obtained from the preceding Information. In reality, the population exposed via each type may range from less than 25 percent to 100 percent of the urban population, since no two types of pipe are Incompatible and It Is likely that more than one type Is used In a single system. 6.3.4 Enumeration by Use of Monitoring Data Monitoring data can be used to predict the number of persons drinking water containing a chemical substance. The method extrapolates data on the frequency of detection of the substance. The level of detail achieved by this tool depends on the form, representativeness, and sample size of the data. In Its simplest form, the enumeration proceeds as shown In Method 6-6. The assumptions Inherent In this very gross estimation Include the assumption that the data are Independent of the water source (surface or ground water). It must also be assumed that the data represent systems of all sizes, so that the frequency can be applied to the total population. Obviously, these assumptions limit the usefulness of the method; It should only be used In the absence of more refined data. The Investigator can Improve this technique by breaking out the total population Into groups defined by drinking water source or system size. Table 29 lists the populations served by systems of different sizes and source types. If the monitoring data Indicate the source or system size, that information should be used since the following two considerations can greatly affect water quality: • The fate of pollutants In surface and ground waters differ. While a chemical may volatilize from surface water, it may persist In an aquifer. Biodegradation may proceed at a slower rate in ground water because of lack of oxygen. More partitioning to soils and sediments may occur In groundwater because there is larger surface area available for absorption. • Pollution (such as vehicle-generated heavy metal contamination) may be anthropocentric and consequently related to system size. Treatment techniques also vary by size of the system; generally, less sophisticated treatment Is used In systems serving small populations. If a pollutant's frequency of detection can be defined by either system size or source, the frequency can be applied to that subpopulation to derive an accurate estimate of the exposed population. Examples of this method are demonstrated in Appendix A-5. The use of monitoring data to estimate the exposed population Is limited In all cases by two assumptions. The sample size must be large 165 Method 6-6. Enumeration of Exposed Populations by the Use of Monitoring Data Step 1 Calculate the frequency of detection from the monitoring data; if detected in 10 of 100 samples, the detection frequency is 10 percent. Step 2 Multiply the detection frequency by the total population of the U.S. (226.5 million). 166 Table 29. Populations Served by Drinking Water System Size and Source Type' K 3 ^4- o JD r— 00 o0 r»k u -*-> 03 LT) r— r— o on on o CD C 4-> • • • • • • • • 4-> CD O o CM CM on CO r— on CO 8 u -*-> CO z u o> “O Q_ c 0 o o o O O o o 8 8 § o 8 8 g i- 00 o o o o o O O o Or ^4- c «k «k «k «k •» • • «k o o CO 1—■ on CO CO 00 00 ^3- TD 00 CM on on oO r— 00 r~» CM 8 C • L. CM on on on <0 00 00 o o 0) •k • • • • • • • z a o r— on on CM r— 03 r— r— O' r— U CM tV V4- u to on CO r~- CM § CM on r— 0 E 00 cr> CM CM CM o CO uo o 03 CO r— CO CO CM CM r— CO r— •k * •k 00 00 CO CM kO o > CM r— 00 z 00 V4- o -Q on cr> r- on on CO CO • • • • • • • C 03 o r— CO r— o r— 03 4-> r— r— *3“ u o i_ 0) CL 4-> S- o o o o o 8 o 8 o 03 o o o o o o o 4-> o o o o o o o o o 03 00 •k •k » •» 4- F r— on (X 1 cr> CO on on o Q) » •k •k •k *k « «k CM -*-> CM 00 r— CM • 00 CM on c O > L. a> z o 03 jO o*— -*-> r— *3 o0 r** CM CM r— c 03 o CM on CM o • • • 0: 03 4-> • k • • • 00 CO 00 4-> CJ o o o o r—~ CM CO CO on • r~ i_ 4-> z u 03 CD CL 00 • -4-> E O) 03 o o o o o o o o o s c z o o o o o o o o o -*-> kf— oo o o o o o o o o o 00 T3 CD o c c u o CO r— O' P» on on r- CO cT 00 0 eg • 00 CO CO on 00 00 o 8 0 W- o s_ on CX r— on CM on CO l- i- z 03 •k •> * •k «k JO 0 CL CO vT> o ^3“ V 4 - uo 1— CM ■0 0 CD 0- 00 10 QJ 0 L- F O' * 3 - CO o r*- o CO o 00 t T3 o 03 r- 00 Cl CJ CD X -O CD o 0 8 o r— o o o o u »T3 o o o o •k c 4-> o O o on o •k o o • r“ 0 Oi o o » * o o o 4-> M r— on »— CM on * — o 4-> . r— «k 0 4-» 00 ! i 1 1 i 1 1 o C O on o c F r— OO 5 CM o o o o o o _j a> >> r— on o on o o < 5 £ oo «k «k «k a >> r— CM on o o on k— fT3 03 167 Source: Adapted from USEPA (1981b). enough that the frequency of detection approximates the frequency of occurrence. The detection limit Is the lower limit for estimating the exposed population via this method. Exposure below the detection limit may, however, be significant for certain chemicals. 6.4 C haracterization of Exposed Populations This subsection describes the data sources and procedures for characterizing the exposed population with respect to age and sex. In most exposure assessments, age and sex characterization will not be necessary. However, drinking water Intake rates are a function of the Individual's age and sex; characterization may be necessary to obtain a precise exposure distribution. If the chemical substance of Interest has special effects on particular age classes such as children or the elderly, further characterization of the enumerated population Is also Indicated. If, for example, a chemical substance Is determined to be teratogenic, enumeration of women of child-bearing age may be required. The simplest and most rapid method of characterizing a large population Is to assume that the age and sex distributions approach those of the total U.S. population. Table 12 of Section 2.4 of this report depicts the age and sex distributions by percent for the total U.S. population. These percentages should be applied to the population enumerated via the data sources discussed In the previous section In order to characterize the population exposed via drinking water. Characterization within specific geographic areas, such as states, townships, and cities, Is also straightforward and Involves the use of census publications. General Population Characteristics , PC80-1-B Series (Bureau of the Census 1982b) provides the age and sex population data for most defined geographic areas. These data will frequently be provided as total population by age and sex and not as percentages In each age class or sex. The data, therefore, must be converted to a percentage basis. The calculated percentages are then applied to the population enumerated via one of the data sources discussed In the previous section. 168 6.5 References Bureau of the Census. 1982a. Statistical abstract of the United States: 1982 (103rd edition). Washington, DC: U.S. Department of Commerce, U.S. Government Printing Office. Bureau of the Census. 1982b. 1980 Census of population. U.S. summary. General population characteristics. PC80-1-B Series. Washington, DC: U.S. Department of Commerce. Durfor CN, Becker E. 1964. Public water supplies of the 100 largest cities in the United States, 1962. Geological Survey Water-Supply Paper 1812. Washington, DC: U.S. Geological Survey. Marks AW. 1980. EPA's computer systems for drinking water. Washington DC: U.S. Environmental Protection Agency, Office of Drinking Water. USEPA. 1981a. U.S. Environmental Protection Agency. General information on IED, drinking water supplies, stream gages, reach, and fishkill files and retrieval procedures for hydrologically linked data files. Washington, DC: Water Quality Analysis Branch, Monitoring and Data Support Division. USEPA. 1981b. U.S. Environmental Protection Agency. Memorandum from B. Coniglio, 0DW, to ISPC Solvents Work Group No. 2. Washington, DC: U.S. Environmental Protection Agency. Versar Inc. 1981. Water supply data base. Inventory of surface water supplies and addendum on a ground water data base structure. Washington, DC: U.S. Environmental Protection Agency, Monitoring and Data Support Division. 169 APPENDIX A APPLICATION OF METHODS TO EXAMPLE PROBLEMS 171 Introduction The population enumeration methods report Is a compilation of data, information resources, and methods. This appendix to the report is designed to illustrate some of the approaches recommended in the methods already discussed. A perusal of these examples will demonstrate that the methods are not necessarily steps that must be explicitly followed; the investigator must be flexible and creative when choosing among available methods and options. This appendix Is arranged as follows: A-l : A-2: A-3: A-4: A-5: Populations Exposed to Chemical Ambient Environment Populations Exposed to Chemical Occupational Environment Populations Exposed to Chemical Ingestion of Food Populations Exposed to Chemical Use of Consumer Products Populations Exposed to Chemical Ingestion of Drinking Water Substances 1 n the Substances 1 n the Substances via the Substances via the Substances via the In some cases the examples are hypothetical; other problems are based on actual problems encountered during the assessment of exposure to chemical substances. The methods detailed in the became apparent limitations are and data used in the compilation of this appendix are text of the methods report. Whenever data limitations in the course of problem-solving, however, those discussed in the examples. 173 APPENDIX A-l POPULATIONS EXPOSED TO CHEMICAL SUBSTANCES IN THE AMBIENT ENVIRONMENT Problem 1: Attached Is a sample computer run of ATM-SECPOP. The model was used to estimate air concentrations of trlchloroethane as a result of process emissions from a point source located In Texas. The purpose of the printout Is to exemplify procedures used to perform ATM-SECPOP simulation. 174 $ UPGRADE Is this terminal a VT100 (Y/N)? N 175 Enter an operation; AUTOHELP Operations include! FILE MANAGEMENT (EM) GRAPHICS (G) MODELING (I'.> STATISTICS (S) TABULAR OUTPUT (TO) ESTIMATION (E) Enter an operation; MODELING ATM (A) EXAMS SESOII. (S) ENPART ♦UTMTGX (IJ) * Not yet implemented Enter a model n >! ATM Mode) names by media; Air; Water; Soil; Mu Ltimedia; The title of the run can be up to eidhis characters Ions!* (he wordind of the title is left to the user but typically should show whether latitude and I. ond elude t or zipcode t were used to identify the emi ssi on s i te ' s location* E : : a id p 1 es J ♦♦CHEMICAL XV* PLACE ANYWHERE » POPULATION BASED ON ZIPCODE -- 4/7/81** Press RETURN to continuet 176 **CHLM1CAL. F'Q * PLACE SOMEWHERE? I.A I/LONG USED 10/12/79** Enter the title of this run! Site A? 1?1?1 - Trichloroethane The user should enter DhFAULT. (In future versions of the system? users will he able to supply alternatives to the default values)* Entering DEFAULT causes the following values to be used by ATM! Number of concentration points in each of the sixteen wind directions! Number of rings! Ring distances (km)! 40 10 0.5? If 2 ? 3 ? 4 ? 5 ? 10 ? 1ji 2 5? 50 4 Number of concentration points per ring Enter the default status! DEFAULT The name of the point source can be up to twenty-four characters long. Tiiis information must be supplied by the user at present. Enter the name of the point source! Site A Type LAT/LONG or ZIPCODE to indicate the kind of source location identifier you will use. Tire source location identifier is LAT/LONG if the user knows the geographic coordinates of the site? or ZIPCODE if only the xipcode is known. !f both are available? the user should use LAT/LONG. Generally? more accurate results will be obtained if the correct LAT/LONG is used. Press RETURN to continue! 177 Enter the source location identifier! LAT/LONG The latitude is entered in decrees* minutes* and seconds. Each of the components of the latitude should be separated from the others by one space. Example! N 34 32 10 This information must be supplied bu the user at present. Enter latitude in degrees* minutes* and seconds! N 28 59 10 The longitude is entered in degrees* minutes* and seconds. Each of the components of the longitude should be separated from the others by one space. Example! U '/h 54 32 This information must he supplied bw the user at present. Enter longitude in degrees* minutes* and seconds. W 95 24 45 This model uses annual weather data tor the selected locality. The stations within the indicated radius are located in the table below. Choose the station which best represents the source location's weather conditions. If you arc un¬ sure which to choose* it is usually appropriate to select the closest one. Vype the four digit station index number to indicate your choice. Weather stations within 75.0 km of the site! Press RETURN to continue! 178 INDEX STATION NAME LAT / LON PER KID OF SiABK 11 Y DISTANCE NUMBER deg m i n deg m i. n RECORD CLASSES (k ni.) 0065 GALUEST0N/SCH0LES TX N 29 16 / U 94 52 1956-1960 6 61.5 1410 HOUSTON/ELL INM'ON IX N 29 37 / U 95 10 1966-1970 6 BAYNITE 74.0 0062 HOUSTON/HOBBY 129 TX N 29 39 / U 95 17 1964-1968 6 -t> CO Enter the tour digit station index number*. 0065 The name of the emission type may he up to eight characters long. This name will be used to label the model output. The name you choose generally depends on the specific- kind of pollu¬ tant emission at the point source facility. The emission type name must be supplied by the user at present. Examples t PROCESS STORAGE Enter the name of the emission type! PROCESS The source height- defines the release height, of the emission in meters (m). This information must be supplied by the user at f resent,. Enter the PROCESS emissions source height in (m)* 15.24 The vent radius defines the radius in meters (in) of the point source emission through a vent. This information must be supplied by the user at present. Press RETURN to continue* 179 Enter the vent radius for PROCESS emissions in (m) 026 The vent das temperature defines the discharge temperature in decrees Kelvin of the emissions through a vent* This information must be supplied by the user at present. Enter the PROCESS vent gas temp in degrees (K)? 311 The ejection velocity defines the discharge ejection velocity of the emissions in meters per second (m/s). This information must be supplied bv« the user at present. Enter the ejection velocity for PROCESS emissions in (m/s)I 1.524 The emission rate defines the source strength of the emissions in grams per second (S/s). This information must be supplied by the user at present. Enter the PROCESS emission rate in (3/s)? 2.755 The name of the pollutant may be up to ten characters long. It should he selected so that it identifies the chemical uniouely. Example? F'HN 81-XXX This information must be supplied by the user at present. Enter the name of the pollutant? 1>1)>1-TCE Press RETURN to continue? 180 The pollutant state identifier is GAS if the pollutant is gaseous? or PARTICLE if the pollutant is a particulate, This information must be supplied by the user at present, Enter the pollutant state! GAS The molecular weight of the gas must be supplied by the user at present. Enter the molecular weight? 133.4 The atmospheric half life of the pollutant is entered in sec¬ onds. This information must be supplied by the user at present. Please use the format shown in the examples? where *E‘ precedes the exponent in powers of ten, Examples Enter the half life in (s)? 1.577ES Control commands BACK CLEAR EXIT HELP GO will return the user to the previous prompt, will return the user to the Operation prompt will return the user to VAX/VMS, will display the appropriate HELP message, will begin processing of the user's fully specified request, w 11 cause the HELP message to be displayed AUTOHELP Press RETURN to continue? 181 NOAUTOHELP RECAP DATASET for each prompt, will cancel AUTOHELP, will display the session summary, will allow the user to change the current dataset. Enter GO to bed in process mat GO 182 Site A? 1.1.1 - Tr K.hloroethane PASGUILL STABILITIES NOT USED—STABILITIES FOUND IN SUBROUTINE SIGMA BRIGGS DISPERSION VALUES NUMBER UF WIND SPEEDS* 6 NUMBER OF WIND DIRECTIONS- 16 NUMBER OF STABILITIES- 6 STABILITIES USED— 12 3 4 5 6 SIGMAX(M) FOR EACH STABILITY )N THE TABLE STABILITY SIGMAX 1 3200. 6 3 4 1600. 800. 500. 200 . 100 . Press RETURN to continue 183 DISTANCE PROCESS IS. 24 0.08 3,56 293.0 31.1,0 0.026 1,524 WIND SPEEDS (M/S) PUR PROCESS EMISSION HEIGHT AS A FUNCTION OP EACH STABILITY WIND SPEED CLASS 1 n 4. 3 4 cr J 6 * 0,77 2,57 4.37 6.94 9.77 12.35 STABILITY 1 0.79 2.65 4.50 7.15 10.06 1.2,72 STABILITY 2 0.79 2.65 4,50 7.15 1.0,06 12,72 STABILITY 3 0.80 2.68 4.56 7.24 10.19 12,38 STABILITY 4 0.82 2.74 4,66 7.3V 10,41 13,16 STABILITY 5 0.89 2.98 5.06 8.04 11.32 14.31 STABILITY 6 0.97 3.24 5.51 8.75 12.32 15,57 * CENTRAL WIND SPEEDS Af STANDARD 10(h) HEIGHT - (ORNL) GRASS COVER 1,0 AFTERNOON MIXING HFIGHTS(M) = 1345. NOCTURNAL MIXING HEIGH I S< M) ~ 501. DATA EUR A GASEOUS POLLUTANT J 1»1»1-TCE DIFFUSION CONSTANT FOR WASHOUT = 9.419E-06 (M2/S) HALF LIFE = 1.577b+0U (S) EMISSION RATE FROM POINT SOURCE TYPE - PROCESS = 2.755EP00 (G/S) Press RETURN to continue I 185 ATM will now be3in processing the user's input. The luntith of oui red may be several minutes? after which the results of trie mo Or? displayed. ■■me re L o 1 11 b e 186 Site A» liltl - Trichloroethene POLLUTANT i 1.1.1-TCE SOURCE i Site A EMISSION TYPE i PROCESS REPORTED TABULAR VALUES WITHIN INOIVIOUAL SECTOR SEGMENTS ! ANNUAL AVERAGE CONCENTRATION (UG/M3) POPULATION (PKRSOHS) * POPULATION EXPOSURE (UG/TR) » POPULATION EXPOSURE = ANNUAL AVERAGE CONCENTRATION * POPULATION * ANNUAL BREACHING RATE(22M3/DAY * 3 Enter an operation! EXIT Type BACK if you want to save temporary datasets! 189 Ui 00 m u> • • • • • • • (VI IA OJ s I ?! -«i «•» t • i —• i SI * i O I J ►« -« I l-CK j « I -J * I 3 -« 9 CL X I £ 4* I -« i 3 I I I «nlH(0cou)5 r-oooo*<0~tm •^r>^r iaoi MVIUHttOI^CO 00 IA • C\J CU r* ^ ^••09<0^CU oj m 0iss::s8ssss k .. i •^(ur)'ru)0i/ti/t0 I H«4A)IA •-• i i 8! iSSSSSSSSSS k I ••*4(Qn^lO«UMO i -• -*nj ouio»n«T a oo oo < inooooi/>r\)LAOor r ) -J 0u>u> -» r>oo <1 —^ H 3 o a. *- o a. 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K> »A »n •"4 —* — •■4 13 a 3 4| a a X a a X X X X X a a Q a X X X 226 Figure 23. "Hydro Tree" Retrieval for Delaware River Mainstem Between Lambertvi1le, NJ, and Wilmington, DE. Exposed Population Facility Philadelphia Water Dept. 1,950,098 Bristol Water Dept. 30,000 Lower Bucks Water Dept. 90,000 U.S. Steel Water Dept. 8,000 Morrlsvllle Water Dept. 21,000 Lambertvllle Water Dept. 4,400 Trenton Water Dept. 250,000 Keystone Water Dept. 2,616 Total 2,356,114 "Child-bearing age" Is taken as 15 to 44 years of age. The percentage of the U.S. population that Is female and within that age group was calculated from Table 12 of the text. Results are as follows: Age Group Percent of Total U.S. Population 15-19 20-24 25-34 35-44 4.60 4.70 8.25 5.77 Total 23.32 2,356,114 x 0.2332 = 549,446 Therefore, 549,446 women of child-bearing age are potentially exposed to Chemical Q. Problem 2 : Point Source Ground Water - A waste disposal site on the outskirts of Miami, FL, leaches Chemical K to ground water. Monitoring data has detected K In ground water In all directions up to 50 miles from the site. Enumerate the population potentially exposed to K via drinking water from public and private ground water systems In this area. Solution : The solution to this problem Is based on a slight modification of Method 6-4. Step 1 - The first step was the Identification of the counties around Miami affected by the ground water contamination. This was accomplished by the use of a 1° x 2° topographic map of the Miami area. The 50-mlle radius of the waste disposal site basically Includes all of Dade County, Florida. 227 S tep 2 - An FRDS retrieval restricted to drinking water utilities In Dade County was requested from the computer system staff of the EPA-Offlce of Drinking Water. The FRDS retrieval revealed a complex web of public, private, Industrial, and business facilities which use ground water for drinking purposes. A total of 472 systems were listed with the major one being the Miami - Dade County Water and Sewer Authority which serves 500,000 people. A sample of an FRDS printout for this system Is presented In Figure 24. Only one surface water utility serving 9,037 people, however, was listed. It was felt, therefore, that a more accurate enumeration of the exposed population would be obtained by obtaining the current population of Dade County. This avoids counting any populations twice and also Includes those people who have private wells In their home. According to the Census publication, Number of Inhabitants (1980), the total population of Dade County, In which Miami Is located. Is 1,625,781. This Is also the population potentially exposed to the chemical substance. That population which consumes surface supplied drinking water Is Insignificant; It Is also highly probable that they consume ground supplied drinking water at the place of work or other business concerns. Problem 3 : Treatment Method Example - An Industrial plant located In Cincinnati, OH, discharges a non-toxic substance to the Ohio River. This substance, however, reacts with flourlne to produce a toxic chemical. The non-toxic substance has been detected In the Ohio River 100 miles downstream of the plant. Enumerate the population which consumes flourldated drinking water obtained from the Ohio River and Is potentially exposed to the toxic chemical formed. Solution : This problem was solved by using a combination of Method 6-2 (as In Problem 1) and a modification of the approach discussed In Section 6.3.2 of the text. Step 1 - The cataloging units and REACH numbers of the Inclusive section of the Ohio River 100 miles downstream of Cincinnati were Identified from USGS hydrologic unit maps of Ohio and Kentucky and REACH maps on file at the EPA-Monltorlng and Data Support Division. The upstream and downstream cataloging units and REACH numbers are as follows: 05-1402-06-001 (100 miles downstream) 05-09-02-01-001 (Cincinnati) 228 Ftl'tHAL RtPlIPUING DATA SYSTfcM OS/l?/»V PIJHLIi w A T F K 5 YSTtM - COM*- RF nt NS I VF PtPOPT F Y 1 VB t FUliSOI PA(,t ill O O o b- © i O < Z X I aj ^ a: 3 co *\j i © 3 Z o V. 3 D B- x X o X X z X © 3 Z H co BH 3 rv N 3 BH •n 3 3 < 3 Z o O X 3 CO 3 X »— <3 2 2 3 c z z 3 X 2 3 BH X z Z «— 3 X 3 X *— 3 3 2 3 3 <1 CO 3 3 3 < X z < < U 3 3 CO 3 CO z 3 3 >■ >- •• X- 3 BH 3 3 X a: 3 B— 3 X z 3 3 3 X X a- UJ 3 z BH 3 •« X CP a. 3 3 3 X 3 3 3 —4 © © 3 3 3 B— a- 3 z Z X < z z c © X Z 3 V >- 3 3 z 3 3 \ \ 3 CO 3 z BH < 3 3 X > 3 X 3 X c c 3 bh 3 3 BH X X < o © •< z 3 z v o V. 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O Ou 2£ ^ s t f='" 0 i;tf£ wen *■ -C O — — ^ /- % o C 0 p , X * C «-> ^ x “‘•AO 1 a 2 o y !yj : c ^ w» -C Cl C 0—0 — 0 > o - Oi O k. Cl Cl g 2 - c CT ai c c a. c*: . . c E a>i, c c Cl •> o 3 |_» p c S' 0 sis ig? -O »l C c •» 2 0 £ — ov ■2 £ o Z-' z -|- 5 5 c E O — OO 1 o E_ 5 o — = n J S u O ^'-O — - o °l' S U M o ® ^ Wi *«!•» o - E o >vc tof f O _ o_ *i — ~ o - — Ov = r» © _= o 4 i V O IOC WJ 2 O 2 0 o o WO •— O C O CT*0 «i c wo ^ O ^ O -•AW £-0 O .2 c — *5 o >a I a E 3 c E o* o : °-o - tyc C c o 3 Wt *A ^ , — • O O' I Q 9 3 c X 3 Q. a. o ci E • r: 11 r ^ Cl c. o Cl >«£ WO <✓) o — GOO o-S J *; •A « iJS «i -o § ^ 3 c o 3 •» ^ “ E •r* t w» *1—0 Z Oui OCCUPATION BY INDUSTRY 236 lOolo bond on S percent »omplf ut l*al for mtonmg of »»mbol» »tt ftafl “O o I O O' X 4) cn “O c siis.tf f 5 5-1 I * « 6 ° £ ^ 9-•? *, 3 * o-^ ^ o o. y 2 3 * 6 ~ >ao £ * y »» O V. x •— -q — ^ o»t: tj — t> 2 *? C 2 *» o E = °l^ »• <* ** *- 3 ^ •» I§i* o* a. ‘ Jr- "o “o -S § §■ § *, * c wS ^(NCD^ — wo S t T cp'^Q^^'r^- >nn -OcNnrvrv — m ^XNfsfNO co O O « » WO o WO — ntNrv ao O O O -O ao — <0 wo ncon-nn'O — x on - ^eo^ooO'O mn — — — co .© — oooc^cnooo — wO'fltNc^o — ao — x x rvecofs — O w% 04 — •- NOOP- 'fl'A «o — cx cm cx cx noo^Ninn O X CM O — O o ^tNn owi OOWIO x n —nrs- © O >0 'O wo r ex — — wo -o — ■V -OfO-O «(N'moo — « ncNO> nrv »nror^n' 0 'T • O'OCO'OO rp-mfNN-o •) — nrs —m « CO wo i CN(N — -O O' CO «n (Nin> 0 ' 0 >n o — wococoxo — ■ no — O'nTT'^'— rs OCN — O' O O ao wo wi wi wo co x o ■— wo I ’T'An wo x co o x ex — n rv rv — x X O O O — X ♦ > ^moo •>— x ao — o* cx ao o n concN — «o ao -*r o o o CM WO X CX WO — •o cx co rs .— o co-as cn •o — ro x co w-i ro cx o ^ ccaoao x O — COCO X CX x x >o CX wo x wo cx cx co ao wo — x — — wo ao •awo —NWOCN x xcNfXkcro o wo x x o o» O O' O O wo co <0 00 00 x o ao wo — wo— x — n > — -oo- wO x — Npmo fN'TOn^-C O' CO o CW wo CO nwoociO' x 0 040'0'^N icNco>nN rsOrs-roco onaorsMO O' — O' ao — ■— .— co r-. wo O' O' x — ao co wo wo wo cx cx •— x ■— rv CN 'T "O X 30 CO O' ao X wo CO O — wo ao O wo O' x wo ro x cm ro — O ao 'O cx — cx co o- o cx co x — O co f'' O' O' O' O O' X -OOO* X — o-cx wo CO — — w> co -o co co ao x o co -o x cx wo ^35 x x p cx cx co — o*c -OO-r^ao-OOwOt ODX^iCN-o O O' — x CO CX O O •— CO WO O CX — rx wo wo X x o x p x cx X x x — wo ao O co coco O — X wo WO CO O' -O X IX CO CO ao ro ro o x x o O O O — X O X WO c — >o CO CX O' x ao — x co co -o wo CO — — woaowoowowo.— woxwoO' ^-ocxaoO'WO'OX'Oaowo CO wo CO O' O' CO CD X -O CO wo ko cx O' cx -o co ■— co ex cx — xO'OcoxwoaD'x Cx O O XCDCOCOW1N - -o ao x xocxxxcx — -owo X O rx .— 'OOWOCOO'COCX lOO-tXN X WO WO X O — O xrxwocxcO'Orx — co xrx cx co o x — x — cx — O O CO ~0 O WO O — -O O CX »— CX — X — X O IX CD rx CO poO*xworx.orxo ■o>nNN •OXWOX — CX o O O O' w» — ao o wo ■O O O' WO X c». WO 'O *0 O' X O' CO O' — o — cx wo 'O o wo — — wo wo — rx x O r-'. O' rx — rx co o co o cx xx — ao co- co ao co >o o wo co ao wo cx co wo X rx ex wo — co oocowoo- *ox xco«©*— — aoOOO'OOOcorxcO'OwO rx cx — co — wowo — 0000 * rx co CO wo -o O' CD X O x px CO CX O' X -o O' x wo cx cx co O' O wo rx «c X O' O O O x x -o wo o o ao CO cx o CO CO — o cx cx rx cx ao — O' — O — <3 X CD CX 0 X X CX CO CX O' x o cx O' x cx ■O X wo 'O — XX — CX . O'O'XOO'O — GO X cx — — ■—X CO O 'O O' CO CX O'O' wo CO-OO ao cx O— -O WO O — O WO kC»X O X CO CO X X O' X CM CM — CO X '0 — 0' X O O' "OCOXWOXCOOWO CX wo X WO o X ■o x o x x o 'O cx ex o WO CX CX X CD x .— — o O' -O — X WO O' — CX O X o — x O' — CX ao cx O X — oo CO — ex — t O O — CO I CO X WO O' i — ao ao wo cx x wo co 0 x wo x— o ao ao o m 3 wo <5 O' X O' c-rx O CD X xocoro O' ex wo ro-o o ao O cx ro o* cx o x x wo co — ao wo x ao woxfox-O'Oxwo 9-0 xocx-owoo-Oao CM X cx CX id CN O co CX I wo O' ao x O' cx O' wo ao o <3 co cx ao O O' co — — X O' — GO O' X CD O X o WS O O O O WO — — CX O' ■ ao co — wo O' x x x > wo ro coco —OCO'O > >o — CO CO WO X X X — o x co — ao o ao o wo cx O' — -O X X X o — x x x x O' x ao co wo wo O' O' X X X o cx CX CO CO -O -O GO wo ao ao x wo ao o cx CO O CX X X — X O O — ■OCOCXCXO'WO — O' xaon«o-x-'0 x ro — x — — — — l x co wo O' ao co wo co wo — x — M 3 >o WOX'OWOfOO'O o rx -o cx o 0X0 — O X X — CM X O O' cx — cx *o X — CX — XX — OCX — ■ nwo ocO'OO'O'wo wo — x O' O wo CX CO O ocxwo x— cx x wo O' «McocxcoO'COco — wo mxco*©xcxwowox ■O CM — — — — CO CO O ■o 0 - co x cx x woxaocxco — -co —on-o — WO CO — cx cx CM X >0 X x - — rx —. ao x co CO — X O X X ao — cx cx x O' wo co ro wo co o wo O O X O' o WO CO wo x O o co co cx x x O' — ao cx — x O' O — x x O' — x co co — x ro — cx x CO O' X X CO O' p >o x kwo 'O co ao O o -o co co — O' O'Owox — aooo' — ao o oo'ooaoxoxao — coo oo — ooowox — oo o O XOCXO^'OwOWO — cox ooaO'OO'O'XwocxcO'O — X X CO CO — — — CO O •— CX wo cx o cx ao o cx cx o x O' ao X — O' cx co — o cx ■o o cx ao co x x x O' — COCOOX — wo WO X x X CM x -o cx ao ao •o O O X cx O ao O "O X — — X O' WO cm 0 — 'O x m wo cm co >o — cx — a. E a. 3 o w o 3 c -Q o o I at UJ > O Q Q o * * < i o *s% ~o -5 •e * O w» w O o 2 n ^ u u S'S'a.o.’S-S 1 : - O <= y-O c ■ -o 2 ssL 5*25 w v 2 s 3i; * o uujLua Or C ; 9- 2 w» ^ o c ° 5 I i 2 o. %* <-* -U -O »_ Q C K M - w 2 ■. E E ; y o S; §2e -e -o E kl c ° ^ o -c _ w» c' e £■? e e i «/» k- *. . O «• a. t S l-o 5 £ c o- _ c C c w» — «/. o* 2 co wj O vj | II •* y ^ e^or £ ^ "o °iS e “ .£ ! S^-si S g » ? i 3 ** £ Z a Z.-TD ■*o S ^ E 3 «» 2 u 5 . O E C*3 o ° o - *» vJ; J &■£ ■5 ° l o w. E 6 W wk . is-I 4» . O :»;& 2 ° ^ O ■ >r ** « ** J Aw g o a. _«» » fss ^ -c 1 S | e 6 2 _ " ° s = v - o 5 s-= cjt* i ° . . O C . . = •* X 5 5 ^ E o > > TS o o ^ -o ^ 5 ^ C - <3 a - J* ° 5° ° k- O W* a S3 a. £ ° S' Wt 3 T3 2-1 E <-* 5 SL » - iS • c 2 Ieu S v o f 3 O 3 e 1 2 * £ o * 1 s-ll Ji;si 237 OCCUPATION BY INDUSTRY Table 1. Industry Group of Employed Persons by Occupation, Age, arid Sex: 1970- Continued o_* c o o V ° o E -i fE S - f ?c c S' S-E * St ° a u O C ^ 5 1 Je E 2 >- 0.0 «- «, O *> Z Z >"5 r O' — -o ^ » Z- «j c o q rt i z — c ■ ♦ E ^ => = o ^3 C o E 2 2 8-S .E E i_ c e-S' ' .u "O ^ ?_c = goo : -> "ct o. 11 *-• 0-0 & CO. -o o o i 5. O •OCNO'-OQ'O o cm op © >5 ?m ♦ • - O' >6 OfN-MN irs-rvomotn lO-O-m^fN r nt — — vmn -o ©-— © ♦ — f'- ro — © — •■ © O o nt o* — ao -*7 von — co • conincD-- o — ©-r*^ cm «rn®noN® ■o»on>NNn WCO'J o>ono •o ro O' miNiri'O *- nt © © ■— CM o • O-fflN nt — o — o nt © cm oNcorooocN • ^ — CNCNfMCN «no — — m © 'O'O-OO'fMNO 9 © CD O O cm -O r>® nrv •om>o oo-boho-n wnn®N — © ■«nMors®o onoM/vn- O vD TT CD — — CM o 'TtN«nO '0 — •o nwn(N»n-N o 04 — ro © co o- •o co — — *» mr>< © nt c © co '^ew-»rx m © ’fr^no^r O^OOON- P" ♦ co ♦ r-v. cm >o O O' U-> CM — — * 00 ® 0 '- 0 'D < o © © ao — o 4 — © n>^un oncNmcpm*n^ 0 (N ao nt .— rs sr n cni pn. cocmcm ONioaonn i o — pm ocNironNo- «omm ♦ O'OO'-M © — «— — OO — CO — T*- O ON (NINCNCNN © O' CNICNI cni fM ■ON^CO'— NOm | cm©oo©cm©cm© — NT — CO si 0 ' 0 ®ino- i co nt co KHnNon © ro cm ao © ■— ■— •— .— o CM — NTOOONT I — | I o — co cni — ao o rc ao — — ■— nt 9 — — CO I © I co I O — O' CNI — — wn — i wo ao co — co ^TK-'O'O co — cO ao wo ao O' ao — OCJOOCNfNiN rw* pm — wo wo 1 co cp ro o — '-•Ti-oob-o CO cO o CO «no- n-55u 5 ® N ^) .— O — Cm — O NT — CM © ■— NT CO o- O — r-~ S I! — co rv. «o OrN®n^ i — •OO' f\C >0 0 ' — coco #N CO CNI -O — r~- m ■ ao co o co r — cni O' co nonocN CN| — — co — - I — CO I © G ^ CM ro in r 8 O' © nt cm ao o •— r-. co cm nt O' — ao nt NT CO— G I — CM cm nt ao -or ■— — CM *© NTCNaOwOCOCDOOCO — ■o — nr D-oo®Nn ^©©Ny©©©fM. © r*^ cm o ao ao oo co CM O' O' O' O' CM CM ♦ — G G nt > — cO O WO > TN — f"- NT r Pw Cn NT CM N'O'O'O cm co ao ao N — lO lO o> O' oo 9 CO — — o» — G G ■OCOCOCM — eonno CO — NT o NT Nrnon 9— O' CM fN CO 9 CM -O CO CM cm ao nt- co O' co CO CO O' cm — o ao — ao NT NT CM CM co ao co ao ao wo cm — o co «®r noooN^ CM »^aOu~>CMCM NTSO-OmS ^ -otoo-cor - cmoocm •— O CM co - ®lON cMNTaoaO'OOOCMO m nt vo — rs io — o CMCOCO'OCMf'.O'OCD O' oaonO co •— coco »o o co nt 0 o — ao — CM >o ■— o ao O' nt CM ♦ cm*© — aoocMCMn ♦ 0*0 — CM-OOCMCM NN®cnr o-n-co aococMOOr^co — cmn OO CO N CO © NT — 00 ♦ G — lO^NOO® «0 >ON — CO N CM O CM K COCO — — NT CMOCaCOO*OCMCOO ©o-coaoro — nt©© «rtrjNco®n©Nro •— nt ♦ o* © © O O* i ao *o co ao o* — ao co cm cm co — co © — r*» rNOO-CNio o c- © © CM NT CO o © ao co co — o co n o •— O'-© CO CO CO © — CO NT WO © © CO — © N CO o ♦ CO CM CM NT o CO wO O cO ao WO CM O ♦ O' — I I I CM I I ■— — CM ao o CO CO NT O ao O' O — © 0 wo f- © O O Cm CM CO © CM NT © NT o no>D-Nn P-. ao nt wo — co — I NT o I Ncn wO CO O O' CM fM CO CM NT O' © CM NT cm o ao cm o* o — CM — CM CM — — CO O' NT NT O CO o 0 o — O' 0 - cm — o ao — © cn wo co — •— ♦ O NT CM CM f- r nno — © NT ao © OOOCOfMCMCM©©CM wro-cnormr nt ♦ COfM -- O' M. CM NT © NT CO o © — CM — © — •— -— © 0 © cm o ao cnO'-co-NOtw© co cm i— — innK ao O © CO © O' nt ©- co © © © ■— © NT CO CO — CM CO © CO nt O' nt © — co ao m co ao cm o ro cm ao — co © © NT NT OO CO CO 1 CM © NT CM © © CD O' CM CO •— ■— © — O' © CO — CM o cm ao O' o © CM CM O — ®'®o>©NO'nr® mO' rs ©CMOrn® CT CM CM ■— O' O — ^ a- >- c a> wj r> — a ct> ^ -c < o Jr ro CM o O © O © O' GO CM CO CO O CM — O — CM © CM o CO — CM — © CO oo- r ©-n r 9 © CO O' © co o r- ©ffi'CNTC' rv © r r CM'— ©o*©©© ♦ ntntpoCM© 0 © 0 © © © — © O' co — l ©or'©® © ao nt o- cm © — O' o CM CM o r^ co O' — ®NO ao cm © co co wrvCM©fNr'CM©rv C-> © CM © o NT K © K — COCO - NT CO NT CM x NT CO — CM NT © -7 O' © CD O' CM © o © © CD C" O O O © © © CM © O O O O CD © — © CM — — CD CO © © ao NT CM NT © ao O O' NT O CM © — p* O © O' O Mfsrvn — © cm ^ © © NT O' O •— ao cm CD — co ro O >©NTr'®©r^CMCOC~' ' r'DNOO-ON'— ' CO CM o O CO NT — .— CM ' O' O O — © NT O' CM O .rM.©CMOCMNTOaO o n Z < Q < “I 2 i z o ^c- 5 -l • o o t ■e m > e • o Jr, - * i-* ~Z Qj i. I Jr ! i t o £ ® 3 _ * - ® J — **■ ^ vO ?- « •»= & • o W. ® ^ : £ -C wr rr 5 : a. — - O > o ^ z w^ c > 5 > ^ a. > a. -o ^ a>_ c Jr rs“g- * C _ — C-5 X" Soo^c^ uu.za.GO A. ■ ■ ° 5. - o .“•'i “ *r* > ifl _ €S^sj r 1 - ^ ^ = O - = E N E ° s * ?-E- £"5 o o a . Z u u-c o - ■» ° '£■■?« rl a/ o *r» s_ aj -o - c E ° o c: w> — O ^ — O' O' a. a •» cr w o : e * «/> i -o o ^ c — 0,-0 NJ cy, o S o-o « o C w C O SL «/* # o W. 5-F. X •e c m *€ Jr Hr E o ° vo 1 _- t O' w- >• CT> o U oc- 0 *^-ca' a 'O Uuj- 1 -iO.OCXwO «/ = *- C o, w. - -c a» tTU v-C OJ I— O O ao £ E • E u c w i o O' © © ® — ao O o. © w" ■If • *n «fi “ w. — O wr => «, ^ — OCDO-=n ®®uuwlC OCCUPATION BY INDUSTRY 238 CD Z3 o C_J I O hs o X 1) co -a c a o> < c o o a. 3 u u o >» -£> C o ■o 4) >> _o CL E LU CL O w o ai _Q a 239 OCCUPATION BY INDUSTRY 'laciud#* oMocored com not shown seporotely Table 1 Industry Group of Employed Persons by Occupation, Age, and Sex: 1970- Continued OCCUPATION BY INDUSTRY Includes allocated coses not shown seporotely Table I. Industry Group of Employed Persons by Occupation, Age, and Sex: 1970- Continued 6 241 OCCUPATION BY INDUSTRY 'Includes allocated coses not shown seporotely The National PMS U$: Dei Ap/ii M • •* . ; I •]' •*, w . 4< I ; ftf Table 1. Percent distribution or industry employment by occupation, 1970, 1978 and projected 1990 Tota 1 Agricultre, Agriculture all forestry. ind ust ries fisheries 1970 1978 1990 1970 1978 1990 1970 - 1978 1990 Total all occupations 100.00 100.00 100.00 100.00 100.00 100.00 100.00 100.00 100.00 Professional and technical *1 1 J.88 15. 09 14.78 2. 1 3 3.24 4.20 1.38 1.99 2.75 ingineers,technical 1.40 1.2 3 1.24 .06 . 09 . 12 .02 .02 .04 Aoronau tical .OB . 06 .06 .00 .00 .00 .00 .00 . 00 Chemica1 .06 . 06 .06 .00 . 00 . 00 .00 .00 .00 Civil .2 1 . 16 . 17 .04 .06 .07 .01 .01 .02 Fleet rica1 .36 . 32 .32 .00 . 00 . 00 .00 .00 . 00 Industrial .70 . 20 .20 .00 .00 . 00 .00 .00 .00 dec hail ica 1 .24 . 2 1 .20 .01 . 0 1 .02 .00 . 00 . 00 Metallu ryical .02 . 02 .02 .00 . 00 . 00 .00 .00 .00 Petroleum .02 .02 .02 .00 . 00 . 00 .00 .00 . 00 5 a i e:» .09 . 04 .03 .00 . 00 . 00 .00 .00 . 00 Other engineers . 1 / . 15 .16 .01 .02 .02 .0 1 .01 .02 Lite and physical scientists .26 . 30 . 3 1 . 12 .21 . 35 .09 .15 .28 Ag ric ult ura1 .02 . 02 .02 .09 .15 .25 .08 .13 .22 Atmospheric and space .0 1 .01 .01 .00 .01 .00 .00 .00 . 00 Biological .04 . 07 .07 .02 .05 .08 .0 1 .02 .05 Chemists . 14 . 1 3 . 1 3 .01 .01 .02 .00 .01 .02 ideologists . 0 J . 0 1 .04 .00 .00 . 00 .00 .00 .00 Physicists and astronomers .0 3 . 03 .02 . 00 . 00 .00 .00 .00 .00 Mathematical specialists .04 . 05 .05 .00 .00 .00 .00 .00 .00 Act ua r res .0 1 . 0 1 .0 1 .00 . 00 . 00 .00 . 00 . 00 Mathematicians .0 1 . 01 .01 . 00 . 00 . 00 .00 .00 .00 Statisticia ns .0 3 . 02 .03 .00 .00 .00 .00 .00 .00 t.ng meetlny , science technicians 1.04 1.0 3 1.09 . 16 .28 .4 1 . 1 2 .21 . 34 Agricultural,!) iolgcl.exe no a 11 u .08 . 05 .05 . 09 . 16 . 28 .09 . 17 . 28 Chemica1 technicians . 1 0 . 09 . 10 . 00 . 00 .00 .00 .00 . 00 Ll liters . 14 . 3 1 .35 .02 . 0J . 04 .0 1 .02 .02 Electrical and electronic .20 . 2 1 .22 .00 . 0 1 .00 .00 . 00 . 00 Industrial engineering .03 . 03 .03 . 00 . 00 . 00 .00 .00 .00 Mechanical engineering .02 .02 .02 .00 . 00 . 00 .00 .00 .00 Surveyors . Ud . 08 .08 . 02 .03 .03 .01 .01 .01 other engineer ing, sc ierice teen . 2 4 . 24 .25 .02 .04 . 08 .01 . 02 .03 Medical vorkeis.oxc technicians 1. / / 2. 0 t 2.36 . 5 5 . 7 1 . 8 9 .57 . / 4 . 9 1 Oil ILOpt'dCtOl'S .02 . 02 .02 . 00 . 00 .00 .00 . 00 .00 Lentists . 1 2 . 1 3 . 1 4 .00 . 00 .00 .00 .00 .00 Dietitians .04 . 04 .04 . 00 . 00 .00 .00 .00 . 00 Optometr 1 sts .02 . 02 .02 .00 . 00 . 00 .00 . 00 . 00 Pharmacists . 1 8 . 14 . 16 . 00 . 00 . 00 .00 .00 . 00 Pnysicians and osteopatns . 17 .40 .44 .00 . 00 . 00 .00 .00 . 00 Podiatrists .0 1 . 01 .0 1 .00 . 00 . 00 .00 .00 . 00 Kegistered nurses . 9 1 1. 06 1 .28 .01 .00 . 00 .0 1 . 00 .00 Therapists . 1 0 . 17 .20 . 00 . 00 .00 .00 .00 .00 V eter inamns . 0 i . 0 3 .04 .54 . 70 .89 .56 .73 .93 Dealtn technologists,technicians . 3 8 . 54 .59 .01 . 0 1 .02 .01 .01 .02 Clinical lab technologists,tech . 17 . 23 .23 .00 . 00 . 00 .00 .00 . 00 Dental hygienists .02 . 04 .06 .00 . 00 .00 .00 .00 . 00 health record technologist,tech .02 . 02 .02 .00 . 00 .00 .00 .00 .00 Hadiologic technologlsts,teca .07 . 1 1 .12 .00 . 00 . 00 .00 .00 . 00 Other health technicians .OH . 14 .15 .01 . 01 .01 .01 .01 . 01 Tecnnicians,except health . 2 0 . 23 .25 .09 . 1 3 . 19 .07 .10 . 16 Airplane pilots .0b . 08 .09 . 07 . 10 . 16 .07 . 10 . 16 Air traftic controllers .0 3 . 03 .0 3 . 00 .00 .00 .00 . 00 . 00 Flight engineers .0 1 . 01 .0 1 .00 . 00 .00 .00 .00 . 00 riadio operators . 04 . 05 .05 .01 .01 .01 .00 .00 . 00 Other technicians except health .08 . 0b .07 . 0 1 . 02 .02 .00 .00 .00 Computer specialists . 3 6 . 46 .50 .01 .01 .01 .00 . 00 .00 Computer programers • 2. c . 2b .28 .00 . 0 1 . 0 1 .00 .00 . 00 Computer systems analysts . 1 1 . 1 7 . 1 9 .00 .00 . 00 .00 . 00 .00 Other computer specialists . . 03 .03 .00 . 00 . 00 .00 . 00 . 00 Social scientists . 1 b . 28 . 12 .00 .01 .01 .00 . 00 . 00 economists .08 . 1 1 . 1 5 .00 . 01 . 0 1 .00 . 00 .00 Psychologists . 0 4 . 12 . 1 1 .00 . 00 .00 .00 .00 . 00 lit nan and regional planner . . U \ . 07 .02 .00 . 00 . 00 .00 . 00 . 00 244 Table 1. Percent distribution or industry emplojinent by occupation, 1970, 1978 and projected 1990 Metal mini ng Coal mi n 1119 Crude pet t oleum, natural gas I'l/O 19 711 1 99 0 19 70 1 9 /8 1 990 19/0 19 /II 1990 Other cralts, kindred workers 2 .a 1 2. 47 2.32 2. 47 2.47 2. 31 b.46 5.13 2.85 Cl ane, der nek , lio 1 st ope ra tor 1.79 1. 53 1.79 .48 . 4 1 .46 .50 .48 . 75 Inspectors, other . 3b . 37 .20 . 80 .98 1.02 .48 .58 .60 stationary engineers . 57 . 4b .24 1.17 1.06 .84 5.41 4.00 1.43 otner crafts workers . 1 1 . 1 1 .09 .02 . 01 .01 .06 . 07 . 08 opeia 11 ves 9 3.94 39. b4 35.b 8 52. 51 49.53 50. 37 36.51 34.39 36.98 0 per atives,except transport 3 7.17 32. 24 25.06 44.03 40. 91 41.03 32.95 30.65 32.07 semiskilled 11 c t a 1 wor k 1119 3. 35 J. B 1 4.74 1.79 1.87 1.57 1.4 3 1.54 1.82 Punucu t endi 1 , sine 11 is, pouter s .2 i . 24 .20 .00 .00 .00 .00 .00 . 00 U 11 nd 1119 machine operatives . 1 I . 1 1 .09 .04 . 02 .02 . 2 1 .17 . 1 1 lieu lei:,, me 1 a 1 . 0 1 . 01 .02 .00 . 00 .00 .00 .00 . 00 Lal lie,mi 11 1119 mn li o|eiative.i .00 . 00 .00 . 00 . 00 . 00 .06 .04 . 02 *Jt III 1 plet.lslCII IIIUCll lipci llols .00 . 00 .00 . 00 . 00 . 00 .0 1 .01 . 00 welders and 1 lainecut ters 2.1t 3. 45 4.42 1.75 1.84 1.5S 1.15 1 . 12 1.68 other operatives, exc transport 3 3 .62 28. 4 3 20.32 42. 24 39.05 39.46 31.52 29.11 30.25 Assemblers .00 . 00 .00 .03 . 03 .02 . 1 1 .15 .26 blasters .7 1 . 73 .82 1.24 1.27 1.06 .25 .23 . 19 Surveyors' helpers . 10 . 11 . 16 . 1 3 . 16 .23 .06 . 0 b . 06 cutting operatives, other .05 . 0 b .09 2.66 2.85 2.71 .07 . 08 .08 Drillers, earth 4.0b 3. 92 2.84 2.46 2 . 21 1.33 5.7 3 5.96 6.74 Oarage wrkr,gas station at ten . 14 . 10 .07 .00 . 00 .00 .05 .03 .02 Meat cut ter s, t u toners , exc nit J .00 .00 .00 .02 . 01 .01 .00 .00 . 00 Mine opera1 1 ves .other 2 7. 17 2 1.94 14.09 34.16 30. 97 32.69 24.67 21.88 22.03 Mixing operatives .02 . 02 .03 .04 . 05 .07 .04 .04 .04 01 lets, grease rs,exc a u toinobi les 1.13 1. 17 1.11 1. 35 1. 39 1.25 .35 .40 .52 Photographic process workers .00 . 00 .00 .00 .00 .00 .03 .03 .01 Sailors and deckhands .00 . 00 .00 . 00 . 00 .00 . 1 1 . 1 1 . 1 8 . 1.1 w ye 1 s .Oli . 0 b .04 .07 .07 .06 .02 .02 . 06 r'ui nuiri! tciidi,:>tokr,exe me 1.11 . 1 1 . 211 .44 .07 . 04 . 0 1 • OH . 06 . 08 winding upiu a 11 ves, other .00 . 00 .00 . 00 . 00 . 00 .02 .01 . 00 Miscellaneous machine operatves .00 . 00 .00 .0 1 .01 .0 1 .01 .01 . 00 other opera ti ves,exc transport . 0 3 . 03 .03 .01 .01 .01 .01 .01 . 00 transport equipment operatives b. 7a 7. 40 10.6 3 8.48 8.62 9. 34 3.56 3.75 4.92 Moat operator! .00 . OU .00 .00 . 00 .00 . 10 .09 . 07 Delivery and route workers .04 . 04 .05 .13 . 12 . 1 1 .18 .17 . 17 Fork lift,tow notot operative.. . 30 . 3B .44 . J7 . 48 . 57 .07 . 09 . 10 Hall vehicle operators, otner 1.08 1. 00 .70 3. 45 3.24 2.25 .29 .23 . 08 Kailroau brake operators . J b . oa .15 .00 . 00 .00 .00 .00 . 00 Railroad switch operators .0 1 . 01 .0 1 .00 . 00 .00 .01 .01 .01 Taxicab drivers, chauffeurs .04 . 04 .03 .00 . 00 .00 . 04 .04 . 04 Tr uck drivers 5.24 5. 83 9.25 4.53 4. 77 6.42 2.87 3. 1 1 4.45 Service workers 2.3b 2. 22 1 .b4 .99 .94 .70 1.24 1.17 .95 Cleaning soivice workers 1.54 1. 48 1.13 . bO . Sb . 36 .82 .77 .51 bldg interior cleaners, other . 14 . 14 .09 . 08 .08 . 04 . 1 2 . 11 . 05 Janitors and sextons 1.40 1. 34 1.05 . 52 . 48 .31 .71 .66 .46 Food service werkers .05 . 05 .04 . 0 1 .01 .00 .28 .25 . 29 bar renders .0 1 .01 .0 1 .00 . 00 .00 .00 .00 . 00 Cooks,exc private households . 04 . 03 .02 .00 . 00 .00 .20 .16 . 13 Dishwashers .00 . 00 .00 . 00 . 00 .00 .01 .01 .01 Food counter,founta in workers .00 . 00 .00 .00 . 00 .00 .03 . 04 .08 Waiters .00 . 00 .00 .00 . 00 .00 .02 .01 . 02 other food serv wkrs,exc pnvt .01 . 01 .01 .00 . 00 .00 .03 .03 . 04 Healtn service workers .05 . 04 .08 .00 . 00 .00 .00 .00 . 00 Health aides, except nursing .0 1 . 01 .0 1 .00 . 00 . 00 .00 .00 . 00 Nursing aides and orderlies .03 . 02 .05 .00 . 00 . 00 .00 .00 . 00 Practical nurses .02 .01 .0 1 .00 . 00 .00 .00 .00 . 00 245 table 1. r« ,1 i:i , n t ii ist r 1 bu tion or industry employment by occupation, l9/U, 1978 arid projected 1990 Nonmt* 1 ’ .‘.i ■?‘4| * i. .3 ^ / vr,* >,t Kx. h / ■•v iT,' (r- n % n % ■V u ; ' WC 4 h '?L'\ ***<• Vri' IVt W/'M £>'\ N'. -•lit, v 't H' r r 247 •ft- IL- ■'' > JT-4T yfv UUf 1 i\L *-*.L j > >. n u f 0 1 . Ij <'/ . »I t 1 V, i . i V-; my Janie 2. Percent distribution ji occupational employment by industLy, 1970, 1970 a vmil 1 , plan ing and mill lanilant Industrial Classification code 19/0 19/8 1990 Transportation equipment. 1.907 1 2.066 4 2.371 5 Motor vehicles and equipment. 371 804 6 981 6 1,1452 Aircraft and parts. 372 665 9 586 6 5132 Ship, boat building and repair. 373 275 6 282 8 314 3 Railroad equipment. 374 50 6 62 2 63 9 Mobile dwellings. 3791 85 2 110 8 269 0 Cycles misc transportation. 375.3799 25 1 42 4 65 9 Professional scientific instruments 453 9 564 5 683 2 Scientific instruments . 381.2 177 3 196 3 196 0 Optical, health serv supplies. 383.4 5 136 4 206 8 266 6 Photo equipment and supplies 386 108 9 131.1 184 3 Watches and clock devices. 387 31 3 30 3 36 3 Miscellaneous manufacturing . 39 435 5 463 8 503 2 Nondurable goods 8.225 2 8,264 0 9,067 1 Food and kindred products 1,784 2 1./07 7 1,735 9 Meat products 201 344 2 350 6 355 4 Dairy products 202 244 6 186 7 137 3 Canning and preserving. 203 284 1 300 1 363 0 Grainmill products. 204,0713 138 1 146 2 156 6 Bakery products. 205 273 6 232 7 204 8 Confectionery products. 207 82 7 77 5 80 2 Beverages. 208 236 1 227 8 234 4 Miscellaneous food preparation . 206,9 180 7 186 1 204 2 Tobacco manufacturing 21 817 67 3 57 8 Textile mill products 9/8 5 898 9 1,054 9 Knitting mills 225 247 3 235 7 333 9 Dyeing, finishing textiles 226 83 2 78 7 76 9 Floor coverings. 22/ 57 1 61 4 103 4 Yarn and fabric mills 221-4.8 515 9 453 1 458 2 Miscellaneous textile mills 229 74 9 70 0 82 5 Apparel and textile products . 1.392 3 1.342 3 1,557 0 Apparel and accessories . 231 8 1.224 5 1.146 8 1,320 3 Miscellaneous fabricated textiles 239 167 8 195 5 236 7 Paper and allied products. /07 4 696 2 790 4 Pulp, paper, paperboard mills .. .. 261-3.6 291 6 265 1 255 7 Paperboard containers, boxes. 265 226 1 2129 266 5 Miscellaneous paper and pulp. 264 189 7 218 2 268 1 Printing and publishing. 1.161 1 1,259.3 1,342 7 Newspaper publishing, printing. 271 417 2 459 5 531 0 Other printing, exc newspapers 272-9 743 9 799 8 811 7 Chemicals and allied products. 1.031 3 1,078 1 1333 2 Industrial chemicals . 281 318 9 325 6 393 5 Plastics and synthetics. 282 exc 2823.4 101 7 96 2 108 9 Synthetic fibers . 2823.4 108 6 1169 180 8 Drugs and medicines . 283 143 1 185 4 220 7 Soaps and cosmetics . 284 124 8 134 5 166 3 Paints and varnishes. 285 68 4 72 2 92 0 Agricultural chemicals . 287 55 0 61 0 57 1 Miscellaneous chemicals . 286.9 110 7 86 3 1139 Petroleum and coal products. 190 1 208 4 177 8 Petroleum refining. 291 153 5 164 5 121 5 Misc petroleum, coal products . 295,9 366 43 9 563 Rubber and miscellaneous plastics . 577 8 747 8 802 7 Rubber. 301-3,6 288 1 295 9 339 1 Miscellaneous plastics. 307 289 7 451 9 463 7 Leather products. 320 7 258 2 214 7 Leather tanning and finishing . 311 26 1 22 5 13 7 Footwear except rubber. 313.4 225 5 171 7 132 1 All other leather products . 312,5-7.9 69 1 64 0 69 0 Transportation other public utilities 5 025 8 5.749 8 6.332 1 255 Table 5. National 19/8 employment, projected 1990 requirements, and average annual openings, 1978-90, by occupation if Ji II lit '• I II • II I'" I •• I' “ I * Occupation ttj/u employment 1‘JtK) employment 1 ‘orcont change 1978-90 Average a Total anual openings 19 Employment change 78 90 Replacement needs' Total all occupations . 94.372 6 114.000 3 208 5,177.4 1,635.6 3,541.8 Professional and technical. 14,244 6 16.854 2 18.3 675 8 217 5 458 3 Engineers, technical. 1.157 1 1,4180 22 5 47 2 21 7 25 5 Aeronautical.. 58 0 700 20 7 1.9 1 0 9 Chemical. 53 0 63 6 20 0 1 8 9 9 Civil . 155 0 190 3 22 8 7 8 2 9 4 9 Electrical . 300 0 364 4 21.6 10 5 5 4 5 1 Industrial. 185 0 233 1 26 0 8 0 4 0 4 0 Mechanical. 195 0 232 2 19 1 7 5 3.1 4 4 Metallurgical. 165 21 3 29 1 .8 .4 .4 Mining . 6 0 95 58 3 .6 .3 .3 Petroleum . 17 0 23 4 37 6 8 5 .3 Sales. 34 0 32 0 -5 9 .6 - 2 8 Other engineers . 137 6 178 2 29 5 7.0 3 4 36 Life and physical scientists. 280 6 349 8 24 7 12 4 5 8 6 6 Agricultural. 19 7 26 0 32 0 1.2 .5 .7 Atmospheric and space. 12 5 14 0 120 .4 .1 .3 Biological . 62 2 79 0 27 0 2 9 1.4 1.5 Chemists. 122 5 1513 23 5 5.2 2 4 2 8 Geologists. 31 0 43 8 41 3 1.9 1.1 8 Marine . 5 2 63 21 2 2 1 .1 Physicists and astronomers . 24 9 26 4 60 .4 1 3 Other life and physical scientists . 26 30 154 .1 .0 .1 Mathematical specialists. 42 4 54 3 28 1 2.3 1 0 13 Actuaries. 9 0 11 9 32 2 .5 2 .3 Mathematicians. 104 113 8 7 3 .1 .2 Statisticians . 23 0 31 1 35 2 1.5 .7 .8 Engineering and science technicians 967.1 1.241 0 28 3 40 4 22 8 176 Agricultural, biological, exc health 44 7 55 5 24 2 2.2 .9 1.3 Chemical technicans. 88 2 1106 25 4 3.5 1.9 16 Drafters . 296 0 393 0 32 8 134 8 1 5.3 Electrical and electronic. 196 1 253 4 29 2 7.4 4 8 2.6 Industrial engineering. 27 6 35 7 29 3 1.3 7 .6 Mathematical technicians. 1 2 1 9 58 3 1 .1 0 Mechanical engineering. 15 1 199 31 8 7 4 3 Surveyors . 73 8 87 0 17 9 26 1.1 1 5 Other engineering and science technicians . 224 4 284 0 26 6 94 50 4 4 Medical workers, exc technicians 1 915 1 2.688 5 40 4 140 5 64 4 76.1 Chiropractors. 18 0 21 1 17 2 1 5 3 1 2 Dentists . 119 3 155 0 29 9 5 5 3.0 2.5 Dietitians . . 35 0 50 0 42 9 3 1 1.3 1 8 Optometrists. 20 9 26 3 25 8 1 6 5 1.1 Pharmacists . 135 0 185 0 37 0 12 6 4 2 84 Physicians and osteopaths . 375 6 504 0 34 2 16 8 10 7 6.1 Podiatrists. 8 1 12 4 53 1 9 .4 5 Registered nurses. 1,001 7 1,455 0 453 85 0 37 8 47.2 Therapists. 164 4 230 0 39 9 11 4 5.5 5 9 Veterinarians .... 29 6 39 8 34 5 18 9 9 Other medical and health workers 7 6 98 28 9 7 2 5 Health technologists, technicians 510 2 670 8 31 5 30 6 13 4 17 2 Clinical lab technologists, tech 217 9 265 0 21 6 10 6 3 9 6 7 Dental hygienists . 35 0 65 0 85 7 4 3 2 5 1 8 Health record technologists, technicians . 156 20 0 28 2 1 2 4 .8 Radiologic technologists, technicians.. 103 8 1400 34 9 66 3 0 36 Therapy assistants. 7 3 100 37 0 5 2 3 Other health technicians . 130 6 170 8 30 8 7 4 3 4 4 0 256 Table 5. Continued—National 1978 employment, protected 1990 requirements, and average annual openings, 1970-90, by occupation ifjl. i hi i in Hi. mi ni.lM Occupation 1978 employment 1990 employment Percent chanqe 1978-90 Average annual openings 1978-90 Total Employment change Replacement needs' Technicians except health 217 t 283 3 30 5 10 1 5 5 4 6 Airplane} pilots 71 6 99 3 38 7 3 2 2 3 9 Air traffic, controllers 2/ 2 33 2 22 1 9 5 4 Embalmers . SO 50 00 2 0 2 Flight enginers. 5 2 6 7 28 8 2 1 1 Radio operators. 44 3 56 6 27 8 2 7 1 0 1 7 Tool programmers, numerical. 3 8 58 52 6 3 2 1 Other technicians except health 60 0 76 7 27 8 28 1 4 1 4 Computer specialists. 435 8 570 0 30 8 166 11 2 5 4 Computer programmers 247 0 320 0 29 6 92 6 1 3.1 Computer systems analysts. 157 7 217 0 37 6 6.8 4 9 1 9 Other computer specialists. 31 1 33 0 6 1 5 2 3 Social scientists . 264 3 359 6 36 1 14 8 7 9 69 Economists. 122 5 170 0 38 8 7 3 4 0 3 3 Political scientists . 2 9 4 8 65 5 3 2 1 Psychologists. 1100 148 0 34 5 60 3 2 2 8 Sociologists . 39 62 59 0 3 2 1 Urban and regional planners . .. . 17 0 22 0 29 4 7 4 .3 Other social scientists. 80 86 7 5 4 1 3 Teachers. 3.690 0 3.572 9 -3 2 1119 -9 8 121 7 Adult education . 84 1 95 0 13 0 3 6 9 2 7 Colluqu and university 583 2 500 0 -14 3 6 7 -6 9 13 6 Elementary school . 1.355 3 1.580 4 166 76 3 18 8 57 5 Preschool and kindergarten. 237 6 282 0 18 7 126 3 7 8 9 Secondary school 1 197 4 880 0 -26 5 1 2 -26 5 27 7 Other teachers 232 4 235 4 1 3 115 3 112 Writers, artists, entertainers. 1,246 5 1.457 2 169 58 1 17 6 40 5 Actors. 13 4 18 0 34 3 8 4 4 Athletes and kindred workers. 106 6 1152 8 1 3 5 7 2 8 Authors . 43 4 50 0 15 2 2.3 6 1.7 Dancers . 80 11 0 37 5 6 3 3 Designers . 167 1 184 0 10 1 5 8 1 4 4 4 Editors and reporters 190 9 240 0 25 7 11 6 4 1 7 5 Musicians and composers. 154 6 208 0 34 5 10 1 4 5 5.6 Painters and sculptors. 193 0 205 5 6 5 7 2 10 6 2 Photographers . 93 0 107 0 15 1 3 9 1.2 2 7 Public relations specialists . 131 0 163 0 24 4 7 6 2 7 4 9 Radio and TV announcers 27 0 33 5 24 1 8 5 3 Other writers, artists entertainers 1 18 5 122 0 30 3 8 3 3.5 Other professional and technical. . 3,518 4 4.188 9 19 1 1909 55 9 135 0 Accountants. 1.011 8 1.265 0 25 0 58 7 21 1 37 6 Architects . 71.6 114 0 59 2 6 5 3.5 3.0 Archivists and curators . 10 4 120 15 4 6 1 .5 Clergy. 262 0 276 0 5 3 14 1 1 2 12 9 Religious workers, except clergy . 60 0 75 0 25 0 5 1 1 3 3 8 Farm management advisors. 9 3 11 0 18 3 3 .1 2 Foresters and conservatlonsts. 602 700 163 2 5 8 1.7 Home management advisors. 52 5 4 3 8 2 0 2 Judges . 184 20 0 8 7 2 1 1 2.0 Lawyers . 487 0 600 0 23 2 35 8 9 4 26 4 Librarians. 147 4 160 0 8 5 7 7 11 66 Operations and systems research 121.2 139 0 14 7 3 5 1.5 2.0 Personnel labor relations workers 420 3 473 0 125 16 8 4 4 11 4 Other research workers . 126 6 135 0 66 3 4 7 2 7 Recreation workers . 130 1 164 4 26 4 7 0 2 9 4 1 Social workers 399 5 475 0 18 9 20 9 6 3 14 6 Vocation, education counselors .. 177 5 194 0 9 3 66 1 4 5 2 Managers.officials, proprietors 10.105 0 12.203 0 20 8 594 7 174 8 4199 257 EMPLOYMENT AND EARNINGS U S Department of Labor Bureau of Labor Statistics In this issue Establishment data adjusted to new benchmarks June 1983 ESTABLISHMENT DATA EMPLOYMENT B-2. Employee* on nonaflricuttural payroll* by Industry In thounndi) 1*72 SIC Cod* Industry TOTAL 10 101 102 PRIVATE SECTOR MINING METAL MINING Iron ores Copper ores 11 . 12 12 13 131 . 2 138 COAL MINING BITUMINOUS COAL AND LIGNITE MINING OIL AND GAS EXTRACTION Crude petroleum natural gas. and natural gas liquids . Oil and gas field services . 14 142 144 147 NONMETALLIC MINERALS. EXCEPT FUELS Crushed and broken stone Sand and gravel Chemical and fertilizer minerals 15 152 153 154 16 161 162 17 171 172 173 174 175 176 CONSTRUCTION GENERAL BUILDING CONTRACTORS Residential building construction Operative builders Nonresidennal building construction HEAVY CONSTRUCTION CONTRACTORS Highway and street construction Heavy construction except highway SPECIAL TRADE CONTRACTORS Plumbing heating air conditioning Pamtmg paper hanging decorating Electrical work Masonry, stoneworx and plastering Carpentering and flooring Roofing ana sheet metal work MANUFACTURING 24 25 . 32 39 20-23 26 31 DURABLE GOODS NONDURABLE GOODS DURABLE GOOOS 24 241 242 2421 2426 243 2431 2434 2435 2436 244 245 2451 249 LUMBER AND WOOD PRODUCTS Logging camps and logg ng contractors Sawmills and planing mills Sawmills and planmg mills general Hardwood dimension and flooring M llwork, plywood, and structural members Millwork Wood kitchen cabinets Hardwood venee' and plywood Softwood veneer and plywood Wood cont*in*r$ Wooc buildings and mobile homes Mobile homes Miscellaneous wood products 25 251 2511 2512 2514 2515 252 253 254 259 FURNITURE AND FIXTURES Household furniture Wood household furniture Upholstered household furniture Metal household furn-ture Mattresses and bedsprmgs Office furniture Public building and related furniture Partitioni end f-xtures Miscellaneous furniture and fixtures All Mfk>r»M Production Mortars' Apr. 1982 Bay 1982 Bar. 1983 Apr. 1983P Ba y 1983P Apr. 1982 Bay 19e2 far. 1983 Apr. 1983P Bay 1983P 89,938 90,407 88, 172 89.005 89,873 _ _ . - 73,764 74, 228 72, 121 72,971 73, 806 59,521 59,989 57,989 58,780 59,588 1,197 1, 179 996 99 1 1,006 881 863 699 696 711 87.6 79. 7 60. 8 61.2 _ 65.2 58.6 44.2 44.5 - 18.3 17.2 8.5 8.4 - 13.5 13.0 5.6 5.5 - 2 9-8 24. 4 19.9 19.9 * 22.5 17.6 14.4 14.5 25«.9 251.1 204.5 202.6 _ 210.4 20 6.7 163.8 162. 1 - 251.5 247.6 20 1.8 199.9 207.3 203.6 16 1.4 159. 8 “ 7 44.0 734. 3 628. 8 619.2 - 521.7 511.1 415. 5 407. 8 - 273.1 276.0 279.6 278.2 _ 123.4 126.0 129. 4 129. 3 - 670.9 45e. 3 349.2 341.0 - 398.3 385. 1 286. 1 278.5 110.4 113.6 101.6 ioe. 3 _ 63.6 86. 8 75.0 81.9 - 35. 1 37. 3 33.9 37.3 - 27.9 30. 1 26.0 29. 2 - 31.7 32.6 29.2 31 . 9 - - - - 24.3 ?4.1 20.5 20.3 - - ~ ~ 3.800 3,998 3,453 3,649 3,893 2,894 3,088 2, 566 2,752 2,984 965.5 1,007.6 ?91.4 926.2 _ 711.3 751.9 636.4 668.1 - 422.3 4 51.4 406.6 428.5 - 295.7 323.0 277.6 297.4 48.4 4P. 6 48.5 52. 2 - 24.5 24.7 24.9 28. 1 - 494.8 509.6 436.3 445.5 - 391.1 404.2 333.9 342.6 805.4 859.0 902. 1 757.3 _ 632.2 686. 2 537. 8 592.6 - 196.5 234.0 159.8 191.5 - 159.4 196.0 122.3 154.8 6 08.9 625. 0 544. 3 565.8 472.8 490.2 415.5 437. 8 ** 2,0 29.1 2,131.3 1, 659.9 1,965.6 _ 1,55 0.3 1,649.4 1,391.3 1,490.8 - 489.2 6 96.6 464.3 468.0 - 353.6 360. 4 329.0 333.1 - 117.2 1 27.7 103.9 112.3 - 94.3 105. 7 82. 6 90.5 398.9 405. 9 376.4 376. 0 - 303.7 309.5 280. 1 280.2 293.6 3 10.0 274.7 292.3 - 246.3 261.8 227.7 243. 2 98.5 104.5 100.0 105.2 - 10.6 77. 1 73.4 78. 1 148- 1 153.8 129. 8 143. 4 * 116.5 121.6 08. 6 111.5 “ 19,080 19,049 ie, 166 18, 295 16, 455 12, 12,968 12,241 12,370 12,544 11,348 11,305 1 0, 59 0 10.689 10,806 7,562 7,530 6,944 7,039 7.163 7,732 7,744 7, 576 7,606 7,649 5, 4 17 5,420 5, 297 5,331 5,381 593.1 604.6 620.5 640.0 664. 2 484.0 494.4 511.8 529. 3 552. 5 69.0 93.3 72.4 74.6 - 51. 1 55.1 55.3 57.2 178.1 180. 4 186. 2 190.5 - 156. 1 158.4 16 3.8 167.9 1 49.0 151.2 155.7 159.7 - 131.2 133.2 137.3 14 1.2 25.3 25.5 26.6 26.8 - 21.5 21.9 22.0 23.2 17 1.9 175. 4 188.5 193.8 - 138.5 141.5 1 c 4.2 159.2 6 1.6 64. 1 72.6 75. 2 - 47.8 49.9 57.8 60. 3 41.7 42". 6 42.2 43 . R - 32.6 33.4 33.0 34.4 22.5 22.5 21.9 21 . e - 19.6 19.6 IQ. 0 19.0 33.9 33. 3 37.5 38. 1 - 29.6 29.0 33.4 34.0 38.9 38.9 37.5 38.7 - 32.9 32.9 31.3 32.4 - 61.5 63. 3 63.7 68.8 - 44.2 45. 9 47. 5 51.7 45.2 46. 3 46. 1 49.9 - 34.5 35.5 36.0 39. 1 - 73.7 93. 3 72. 2 73.6 * 6 1.2 60.6 59.7 60.9 635.1 4 "* 1 . 3 43 1.3 439.6 44 1.7 344.0 340.8 340. 4 347. 4 350. 0 272.8 2 6°. 6 271.0 276.0 - 224.6 222 . 1 223. 1 227.9 122. 5 121.2 120 . 2 122.5 - 105. 2 104. 0 103.2 105.4 - 82.8 83.3 85.2 87. 1 - 66.1 66.7 68. 1 70. 0 27. 8 26.1 29.4 29.4 - 22.3 20. 9 24.0 24.0 “ 26.0 28. 0 27.8 28.3 - 20.9 20.9 20. 9 21.3 54.0 53.9 53. 5 53. 8 - 4 1.7 4 1.5 40.7 40. 9 * 21.9 21.3 20.5 20 . 6 - 16.3 i*.e 15.0 15. 0 “ 57.6 59.4 54. 0 57.3 - 4 1.9 41.8 40.3 42.0 28. 8 29. 1 31.4 31.9 ~ 19.5 19.6 21.3 21.6 260 ESTABLISHMENT DATA EMPLOYMENT B-2. Employee* on nonagrlcuhtural payroll* by industry — Continued [In thousands] 1t72 SIC Code Industry AJI amptoyaas Production workers' Apt. 1982 Kay 1982 Bar. 1983 Apr. 1983P Bay 1983P Apr. 1982 Ba y 1982 Bar. 1983 Apr. 1O03P Bay 1983P 32 STONE CLAY AND GLASS PRODUCTS 580.4 *88. 5 54 1.9 559.9 574. 3 438.0 445.9 4 08.2 424. 2 438. 7 321 Fiji glut 16.3 16.4 16.9 16.8 12. 5 12. 5 13.3 13.2 * 322 G'ass and glassware. pressed or blown 111.2 110.8 102.6 102 .1 92.7 92.4 85.7 85.9 3221 Glast containers 6 1.9 62. 5 57.4 56.8 54.2 54.8 50.3 49.6 - 3229 Pressed and blown glass, net 49-3 48. 3 45.2 45.9 38.5 37.6 35.4 36. 3 323 Products of purchased glass 91.2 41.6 4 1.0 41.7 “ 27. 3 27. 6 27.4 27. 9 “ 324 Cement hydraulic 27.9 27.7 24. 6 25.5 21.6 21.9 19.1 19. 9 325 Structural clay products 33.8 34.4 33. 2 34.7 - 24.7 25.2 24.6 26. 2 “ 326 Pottery and related products 39.6 39.4 36.5 39.1 32.0 32.0 28.8 30. 0 “ 327 Concrete gypsum and plaster products 177.6 185.6 166.7 178.5 133.2 14 1.0 124.0 134.8 ~ 3271 Concrete block and brick 16.7 17.7 16.8 17.6 11.0 12.0 1 1. 1 11.8 3272 Concrete products, nec 60 .3 61.2 54.7 57.2 44.0 45.2 39.5 41.7 ” 3273 Ready mixed concrete 82.9 99. 1 77.9 86.2 “ 64.0 69. ’ 59. 7 67.4 329 M sc nonmeiallic mineral products 122.6 121.7 110. 3 111.6 85.4 84.7 77.3 78. 3 ~ 3291 Abrasive products 29.4 24.1 21.3 21.4 15.5 15.4 13.6 13. 7 ~ 3292 Asbestos products 13.5 13.4 12.6 12.9 10.0 i 9.9 9.2 9. 5 ~ 3296 Mineral wool 27.0 27.0 25.4 25. 4 “ — — — ' 33 PRIMARY METAL INDUSTRIES 981.5 952. 5 820. 8 829. 6 84 1.7 732.0 708.2 606.8 614.9 627. 6 331 Blast furnace and basic steel products 428.8 4 13. 3 332.6 337.2 319.6 307.4 247.8 251. 3 “ 3312 Blast furnaces and steel mills 354.3 340. 1 273.6 277. 6 “ 264.6 253.3 205. 1 208. 3 ~ 3317 Steel pipe and tubes 29.8 29. 6 21.9 22 .2 22.3 22. 1 15.4 15.6 332 Iron arxt steel foundries 172.0 16 1.9 137. 5 139.1 - 133.2 124.6 1 03.8 105. 7 “ 3321 Gray -ron foundries 103.8 97.2 98.2 89.7 - 82.7 76. 9 6 9.1 70.8 3322 Malleable iron foundries 12.9 12.0 10.6 10.3 9.6 8.8 7. 7 1.4 - 3325 Steei foundries, nec 43. 4 41.1 29.0 29.5 33.0 31.1 20.5 21.0 333 Primary nonferrous metals 58.9 56.7 48.2 48.6 - 42.8 41.1 34.5 34.8 ~ 3334 Primary aluminum 30.5 30.0 24.5 24.8 “ 22.6 22. 4 18.0 18.4 ~ 335 Nonferrous rolling and drawing 193. 1 1 93. 4 18 1.6 182.3 - 136.9 137. 1 127.5 128. 5 - 3351 Copper rolling and d'awing 27.5 27.0 26.0 26.0 20.4 20. 0 1 0. 7 18.8 ~ 3353 A!um:ny~ sheet plate, and foil 31.0 31.2 29.6 30.0 “ 23. 6 23.0 23. 0 23.3 “ 3357 Nonferrous w>-e drawing and insulating 82.1 92.4 76.3 76. 1 - Pfl. 1 5e.2 53.6 53. 5 “ 336 Nonferrous foundr-es . . 82.9 82. 2 80.6 82.0 “ 65.7 64.9 64.0 65. 3 ~ 3361 Aluminum foundries 48.7 48.4 47. P 48.8 “ 3».4 39.0 39.0 40.0 34 FABRICATED METAL PRODUCTS 1,468.6 1,456.9 1,359.7 1,367.3 1 ,378. 5 1,06 1.3 1,051.5 979.4 987.1 997. b 341 Metal cans and Shipping containers 64.9 65.3 62.7 62.6 “ 54. 7 54. 9 53.1 52.9 “ 341 1 52.7 53.0 50.7 50.6 “ 45.2 4 5.4 43.8 43. 6 342 Cutlery, hand tools, and hardware 145.5 142. 3 136.0 136.7 * 107.4 104.7 99.3 100.2 “ 3423.5 Hand and edge tools and hand saws and blades 51 .2 48.4 44.7 44 . 1 38.6 35. 2 32.5 32.1 “ 3429 Hardware nec 81.3 90.8 78.9 80.0 “ 59. 7 59.5 58. 4 59. 5 “ 343 Piumb-ng and heating except electric 60.8 60. 0 60. 1 61.3 * 4 1 . R 41.1 42.2 43.4 ” 3432 Plumbing fittings and brass goods 23.4 23.1 23. 1 23.3 “ 18.4 18. 1 18.0 ie. 0 “ 3433 Heating equipment except electric 28.3 27.4 27.6 28.4 ~ 17.8 17. 0 17.1 18.6 344 Fabricated structura 1 metal products 462.6 460. 2 417. 8 419.3 “ 309.0 307.0 277.0 278. 8 3441 Fabncated structural metal 92.0 91.2 77. 5 76. 5 65.0 e?. e 53. 1 52. 4 “ 3442 Metai doors sash and trim 70.2 72.1 75.5 77.1 49. 9 * 1.6 54.0 55. 5 “ 3443 Fabricated plate work (Doilei shops! 136.2 1 34.0 112. 6 111.1 79.Q 78.8 65. 1 64.3 “ 3444 Sheet meta 1 work 102.1 101.3 Q 6.2 97. 3 73.2 72.5 68. 1 68. 8 3446 Arcmteciura' metal work 26.1 27.8 27.3 27.5 19. 3 IP. 8 1 8.7 18. 8 345 Screw machine products, bolts, etc 94.5 92. 9 84.1 85.3 - 71.1 6°.5 62.3 63.2 ~ 3451 Screw mach nr products 44.0 43. 6 39. 1 39.9 34.7 34.3 30. u 31.0 ~ 34 5 2 Bolts nuts rivets, and washers 5C.5 49.3 45.0 45. 4 36. 4 35.2 31.9 32. 2 346 Metal forgings and stampings 239.1 2 36.3 225.6 226.3 - 167.8 187.5 177. 4 178. 1 ~ 3462 Iron and steel forgings 41.9 40. 0 32. u 32.7 31.8 30.4 23 .e 24. 1 3465 Automotive stampings 84.2 Q1.2 85. 5 85.8 - 70. 7 73.7 72.5 72. 5 “ 3469 Meta! siampmgi nec 101.5 99.6 97.0 97.9 ~ 76.5 14. 7 73.2 74.0 ” 347 Meta! services, nec 97.8 96.9 90.9 92.2 77.6 76.7 . 7 73. 0 “ 3471 Piating and polishing 67. 1 66. 9 64. 5 65.3 - 54.3 54. n 52.1 52. 9 “ 3479 Meta' coaimg and aii-ed services 30.7 30. 1 26.4 26.9 23.3 22.7 1 °. 6 20.1 ~ 348 O'dr.ance and acessones nec 64.6 6 * . 0 65.0 65.4 4 1.8 4 1.7 42. 2 42. 6 “ 3483 Ammunition exc fo' small a"m nec 26.8 27.0 28. 2 28.7 - 17.8 17.7 1 P.7 19.3 349 Misc fabricated meta' products 239.0 236.0 217.5 218.2 - 171.5 168.4 154.2 154.9 “ 3494 Valves and pipe liftings 98.0 95. ° 84.2 84.2 - 65.5 63. 5 c u. 5 54.7 3496 M sc fabncated wire products 50.8 50. 5 49. 3 49.8 “ 38.5 38.0 36.8 37.3 35 MACHINERY EXCEPT ELECTRICAL 2,379.8 2, 354.9 2, 04 4.3 2, 043.7 2,06 5.8 1,463.0 1,445.2 1,164.1 1,185.0 1,209. 1 351 Engines and turbines 119.4 1 17.6 190. 0 98.9 73.6 72.7 58.3 57. 1 * 3511 Turbines and turbine generato' sets 43.3 42. 9 39. 1 38.6 23. 1 22. 8 21.0 20. 6 — 3519 Interna combustion engines nec 76. 1 74.9 60.9 60.3 - 50. 5 49. 9 37.3 36.5 “ 352 Fa»m ar.d garde r machinery 1 49.4 150. 2 130. 1 130.2 * 96. 1 99.7 83.3 84.2 3523 Fa r rr machinery and equipment 129.8 131.4 110.5 112.0 “ 83.5 86.0 69.2 71. 2 353 Construction and dialed machinery 380.9 3 12 .8 253.6 253. 1 243.2 237.4 1 3 f. 1 133.9 3531 Construction machinery 121.1 120.5 73. 6 74.8 74.9 74.8 29.9 29. 6 261 MC77 I 28 F I ..I•••< I Inly I ( JM() Industry Series Industrial Organic Chemicals 2861 Gum and Wood Chemicals 2865 Cyclic Crudes and Intermediates 2869 Industrial Organic Chemicals, N.E.C. U S Department of Commerce Philip M. Klutznick, Secretary Luther H. Hodges, Jr., Deputy Secretary Courtenay M. Slater, Chief Economist BUREAU OF THE CENSUS Vincent P. Barabba, Director 263 USERS' GUIDE IN LOCATING STATISTICS BY TABLE NUMBER (Poi cxplanat ion of terms, sue appendix A) Item 4-digit industry statistics Historical Operating ratios By geographic area 1 Nimibi'i of manulaetui 111 <| establishments 1 a 2 l mployment and payioll 2 Numhi.'i of employees. la 1b 2 J Pay i oil. la 1b 2 4 Supplemental labor costs. b Pioduction woikers. la 1b 2 6 Pioiluction wotkei hours. 1 a 1b 2 / Production woikei wayes. la 1b 2 Shipments, cost of matenals, and value added 8 Value of shipments (4-digit). . la 1b 2 9 Pmduct class shipments (5-digit) . . . 10 Product shipments (7-digit) . . . 11 Value .idded by manufacture . la 1b 2 12 Cost id matei nils. . . la 1b 2 13 Cost of fuels and electric eneryy . 14 Materials consumed by kmil. . . . Invcntoi ics 15 1’ nd of year . la 16 Stage of fabrication. Capital expenditures, assets, rental payments, and purchased services 17 New capital expenditures la 2 18 Used plant and e(|iiipment expcndituies 19 ( J 1 1 >V» jSM.'t. . la 1b 20 IJi pi eCiat ion . 21 Retirements of buildings and machinery. . 22 Rental payments . . 23 Pm chased services . R jtios. 24 Specialization. la 25 Coverage. 1 a 1 Detailed mfoimation shown 264 4 digit nulustiy statistics Con 5 digit product class and 7 digit product statistics By Product Summat y By industry and Materials Industry class by Histor ical and employment (noduct class consumed product Product geographic product supplemental size specialisation by kind analysis shipments area class 1 J.i 4 b»i i 3a 4 5a 2 3a 4 5a 3 ' 3d 4 ' 3a 4 5a 5 1 3a 4 5a 6 3a 4 5a 7 3a 4 5a 5b. 5c 8 5b, 5c 6a 6b 6c 9 6a 10 3a 4 5a 1 1 '3a 4 5d 12 3a 13 7a 14 3a 4 15 3a 16 1 3a. 1 3b 4 5a 17 1 3a. ' 3b 18 1 3b 19 ' 3b 20 '3b 21 ‘3b 22 1 3b 23 3a 5b 24 3a 5 b 25 265 Table la Historical Statistics for the Industry: 1977 and Earlier Years All eslalilifthmentu All ninpInyHes Produi.tion workuin Expenditures and assets Hallos Value New Gross End of Year 1 With 20 added by Value ot capital value of year Spa- employ- manulac- Cost of ship- expend- (mad inven- cial Cover- Com- ees or Num- Payroll Num- Wages ture materials ments itures assets tones nation age pames 2 Total more ber (million ber Hours (million (million (million (million (million (million (million (per- (per- (no.) (no ) (no) (1.000) dollars) (1.000) (millions) dollars) dollars) dollars) dollars) dollars) dollars) dollars) cent) cent) INDUSTRY 2861 GUM AND WOOD CHEMICALS 197/ Census■ 100 119 37 4 b 54 0 3.8 7 8 38 9 185 0 205 3 391 3 270 (NA) 65 7 70 67 1976 A5M S ■ (NA) (NA) (NA) 4 7 47 2 3 7 7 4 35 0 147 2 2108 364 0 320 184 0 71 2 (NA) (NA! 19 75 ASM (NA) (NA) (NA) 4 6 42 6 3 7 b 7 31 9 130 2 196 4 314 2 126 102 1 70 4 NA NA 1974 ASM INA) (NA) (NA) 6 1 44 5 4 2 / 0 34 0 199 5 220 8 403 3 100 140 0 64 6 NA NA 19/3 ASM (NA) (NA) (NA) 5 5 46 6 4 1 8 6 33 5 181 1 170 6 365 4 152 2108 57 4 (NA) (NA) 19/2 ( onsus- 1 18 139 41 59 47 6 4 7 9 4 33 5 155 4 175 9 332 3 11 1 203 1 522 70 75 19/1 ASM (NA) (NA) (NA| 5 2 40 8 4 1 8 2 20 5 1430 144 7 279 4 10 5 167 9 49 7 (NA) (NA! 19/0 ASM (NA (NA) (NA) 5 3 37 9 4 2 8 4 26 0 1163 144 0 201 7 89 185 3 39 3 NA NA 191 >9 ASM (NA) (NA) (NA) 5 8 36 0 4 7 9 3 25 0 102 3 130 0 228 5 93 152 0 47 6 NA NA 1968 ASM (NA) (NA) (Na) 6 7 35 0 4 4 8 7 24 2 11/2 1 14 8 233 3 13 7 147 0 45.8 (NA) (NA) 196/ Census 1 72 184 42 5 9 33 5 4 6 90 23 1 100 0 1153 215 0 20 6 1392 46.3 73 76 1'.l66 ASM 0 (NA) (NA) (NA) 50 31 5 3 8 7 9 21 4 99 2 109 6 208 7 86 (NA) 43 5 (NA) ina; 1965 ASM (NA) (NA) (NA| 5 8 32 1 4 3 8 8 21 9 92 6 112 3 206 2 4.4 (NA) 46 4 NAi NA 1964 ASM - - - - (NA) (NA) (NA) 6 4 32 4 50 10.1 22 4 102 3 lie 9 2220 4 9 118.1 48 9 (NA) Ina! 1963 Census - 229 246 53 68 32 7 5 4 100 22 9 100 3 114.6 212 9 5.6 115 2 53 7 74 77 INDUSTRY 2865, CYCLIC CRUDES AND INTERMEDIATES 1977 Census•• 135 191 127 35 7 631.5 23 4 46 6 369 8 2 214 4 3 453 6 5 637 0 443 1 (NA) 844 4 68 67 1976 ASM - (NA) (NA) (NA) 27 8 441 8 17 9 35 8 262 6 1 798 7 2 956 8 4 677 7 443 6 3 345 4 708.8 (NA) (NA 1975 ASM - - - - (NA) (NA) (NA) 27 8 406 1 17 9 36 4 242 4 1 353.8 2 442 6 3 819.2 432 0 3 111.4 813 9 NA (NA 1 1974 ASM (NA) (NA) (NA) 27 6 365 0 18 4 38 3 222 6 1 465 3 2 078 3 3 413 3 319 9 2 504 3 825 0 (NA NA 1 1973 ASM (NA) (NA) (NA) 29 5 348 0 190 39 4 207 1 1 140.3 1 266 0 2 426.4 200.8 2 356 3 376.1 (NA) (NA) 1972 Census 123 1 74 118 28 2 318 2 18 7 38 4 101 1 929 7 1 1103 2 040 6 168 8 2 174 0 3560 76 65 19/1 ASM (NA) (NA) (NA) 30 0 315 9 20 0 417 105 3 065 4 1 037 4 1 967 6 279 6 2 237 9 371 7 (NAl (NA 1970 A.SM (NA) (NA) INA) 30 2 293 6 19 9 41 3 176 7 855 1 000 3 1 004 0 283 2 2 010 8 317 7 NA NA 1 1969 ARM (NA) (NA) (NA) 30 9 289 8 20 H 43 B 1 79 2 840 7 975 3 1 709 0 140 4 1 806 4 304 1 NA) NA 1 10611 ARM (NA) (NA) (NA) 30 2 285 1 20 5 42 2 164 1 774 6 030 6 1 716 1 90 3 1 096 2 277 0 (NA) Ina) 196/ CuribUS 1 16 1 // 10/ 30 0 251 1 20 3 41 / 152 9 729 5 8/4 5 1 500 8 130 1 1 6126 201 0 73 00 1966 ARM (NA) (NA) (NA) 29 2 240 4 20 1 42 6 150 1 74 1 7 820 3 1 650 3 08 4 INA) 24/3 (NA) (NA 1966 ARM (NA) (NA) (NA) 29 6 232 3 19 9 41 b 141 9 082 3 780 5 1 450 3 91 9 InaS 232 5 NA) NA 1964 ASM (NA) (NA) (NA) 28 2 21 1 3 18 7 38 5 128 5 021 1 888 3 1 289 8 103.5 1 110.4 209 0 NA NA 1 1963 Census 120 141 84 27 7 201 9 10 9 38 6 124 0 605 3 634 1 1 212 8 1000 1 047 8 211.0 (NA) (NA) INDUSTRY 2869, INDUSTRIAL ORGANIC CHEMICALS, N.E.C. 1977 Census - 388 569 346 112 3 2 108 7 70 7 145 7 1 216 5 10 475 7 13 940 8 24 232 8 3 162 6 (NA) 2 942 7 60 84 1976 ASM INA) (NA) (NA) 109 3 1 859 2 68 7 139 0 1 059 0 9 402 6 11 546 5 20 642 6 2 208.6 15 442 9 2 5182 (NA) (NA 1975 ASM (NA) (NA) (NA) 104 9 1 630.3 64 8 129 7 904 2 8 027 4 9 126 7 16 923 3 1 675.2 13 086 8 2 222 B (NA) (NA 19/4 ASM (NA) (NA) (NA) 102 5 1 489 6 65 6 134 8 047 3 7 659 9 8 309 7 15 538.9 1 259.5 11 415.2 1 944 7 (NA) (NA 19/3 ASM (NA) (NA) (NA) 102 8 1 332 4 66.1 135.5 778 1 5 582 3 5 045 8 10 665 9 7890 10 892 0 1 1480 (NA) (NA 1972 Census 349 514 295 102 4 1 248 6 64 5 129 9 713 0 4 988 0 4 228 2 9 223 5 661.7 10 113.0 1 070 1 m 85 19/1 ASM- (NA) (NAl (NA) 100 2 1 140 7 63 8 129.1 649 5 4 530 8 3 656 0 8 214 3 659 4 9 400 7 1 044 2 (NAl (NA 19/0 ASM (NA) (NA) (NA) 104 2 1 099 7 66 4 135 9 629 1 4 225 4 3 607 0 7 739 7 738 1 9 007 9 1 053 3 (NA) NA 1969 ASM (NA) (NAl (NA) 101 6 1 023 0 65 7 137 4 597 4 3 976 6 3 374 6 7 253 2 711 7 8 263 0 936 7 NA NA 1968 ASM (NA) (NA) INA) 98 6 925 4 63 0 131 8 545 4 3 818 6 3 154 6 6 905 8 004 8 7 716 0 017.1 (NA) (NA 1 967 Census - 339 488 268 95 1 844 9 62 4 126 4 499 0 3 575.3 2 849 0 6 377 8 701.2 0 882 3 801 1 72 81 1966 ARM (NA) (NA) (NA) 95 7 833 4 03 b 129 0 491 6 3 641 5 2 953 1 6 541.1 886 2 |NA) 770 1 (NA) (NA 1965 ASM - - INA) (NA) (NA) 91 6 768 0 61 3 125 2 462 5 3 471 7 2 615 7 8 0125 841 2 (NA) 687 8 NA (NA 1964 ASM - (NA) (NA) (NA) 07 1 714 0 57 0 117 6 428 6 2 990 0 2 297 1 5 265 3 496 4 NA) 587 0 (NA) (NA 1963 Census 343 464 241 85 5 677 3 56 4 114 4 405 0 2 727 5 2 105 7 4 840.2 401 0 (NA) 5528 72 81 Represents zero (0) Withneld to avoid disclosing operations of individual companies (NA) Not available nec Not elsewhere classified. r Revised. (S) Withheld because estimate did not meet publication standards (X) Not applicable (2) Less than 50 thousand dollars or hours, under 50 employees 'in annual survey of manufactures (ASM) years data are estimates based on a representative sample of establishments canvassed annually and may differ from results of a complete canvass of all establishments ASM publication shows percentage standard errors Unless otherwise noted, tor data prior to 1963, see 1963 Census of Manufactures, vol II, table 1 of the Industry chapter. 2 For the census a company is defined as a business organization consisting of one establishment or more under common ownership or control, industry was defined or redefined for 1972 Census of Manufactures, so data are available only for years shown 4 Data for 1967 and 1963 were derived from Table 8, General Statistics for EstaDlishments by Industry Specialization and Primary Product Class Specialization, in vol. II of the 1967 and 1963 Censuses of Manufactures Separate data for other years are not available *0ata either have associated standard errors exceeding 15 percent or are not consistent with other census series and related data, thus these estimates may be of limited reliability ^Estimate for new capital expenditures has associated standard error of 15 percent or more and may be of limited reliability Estimates for other data items are of acceptable reliability Minimum percentage, exact percentage withheld to avoid disclosing operations of individual companies ^Relationships are not meaningful bocause of predominance of miscellaneous receipts, particularly receipts for contract and commission work on materials owned by others ^Oata in value of shipments column represent value of production rather than value of shipments Consequently, formula for computing value added by manufacture was modified to exclude any change m finished products inventories betwoen beginning and end of year ,u bata m vaiuo of shipments column represent value of work done rather than value of shipments Consequently, formula for computing value added by manufacture was modified to exclude any change in inventories between beginning and end of year MANUFACTURES—INDUSTRY SERIES 266 INDUSTRIAL ORGANIC CHEMICALS Table 2 Industry Statistics by Geographic Area: 1977 and 1972 Geographic area 19/7 1072 E' All establishments All employees Production workers Value added by manu¬ facture (million dollars) Cost o( materials (million dollars) Value of shipments (million dollars) New capital ex¬ pend¬ itures (million dollars) All employ¬ ees 2 (1.000) Value added by manu¬ facture (million dollars) Tolai (no) With 20 employ ees or more (no) Num¬ ber 2 (1.000) Payroll (million dollars) Number (1.000) Hours (millions) Wages (million dollars) INDUSTRY 2861. GUM AND WOOD CHEMICALS Untied States . - 119 37 4 8 54.0 3 8 7 8 38 9 165.0 206 3 391 3 27 0 5.9 166.4 WoM North (.ontnil Division Mr .'.01111 1 1 2*1 6 (.(. U>) (O) (D) (D) (D) (D) (D) (D) CC (D) North l)|iiiin 1 1 AA o>) (l>> (C> (Cl H 1") (<>) (0) AA PI It 1 1 ii >) id U) O D P D) D) tt P 1 lonifa 9 6 a: (Ui (C) (D) (Dl loi Id) Id) Id) EE Id! Last Sooth Central Division Kentucky . - 1 1 AA (D) (C) (D) (D) (D) (0) (D) (D) AA (D) West South Central Division Arkansas . . 7 2 AA (D) (0) (0) (0) (D) (D) (D) (D) (NA) (NA) Te*oS E3 16 2 02 1 8 0 1 0 3 1 4 4 7 4.4 9,0 07 (NA) (NA) P«n ilic Division Oregon • . * 3 2 BB (D) (D) (D) (D) (D) (D) (D) (D) AA (D) INDUSTRY 2865, CYCLIC CRUDES AND INTERMEDIATES Untied States. - 191 127 36 7 831 6 23 4 48 6 389 8 2 214.4 3 463 6 6 637.0 443.1 26.2 929.7 Now t ngland Division Massachusetts . El 6 2 BH (D) (C| (D) (D| (0) (Dl (D) (D) BB (D) Rhode island. - 2 1 CC (D) (Cl (D) (D) (0) (D) (D) (D) CC (D) Connecticut . - 2 1 BB (D) (D) (D) (Di (D) Idi (D) |0) AA (0) Middle Atlantic Division New York . - 12 6 2 8 44 6 1 9 3 5 28 4 142 5 100 0 242 3 (D) 26 49 1 New Jersey. - 42 30 12 3 237 7 8 6 16 7 141 0 605 6 005 5 1 402 9 (D) 83 234 0 Pennsylvania. - 14 9 1 6 23 8 1.0 22 14 1 110 0 170 2 288 6 (D) 1 8 50 3 East North Central Division < )r i . - 13 10 FF (D) ID) (D) (O) (D) (D) (D) (D) EF (D) ItliniMS . 16 10 26 46 ') 1 / 3 4 29 1 156 4 201) 3 423 7 40 4 2 6 70 5 Michigan 4 :i 0 7 7 9 0 4 0 0 611 21 0 30 6 50 9 20 CC (D) South Atlantic Division 1 n •!,« ware 2 2 CC mi (U| (D) (D) (D) (D) (D) (D) CC (D) Mai»lain J - 3 p CC (0) (C) (C) (D) (D) (D) (D) ID) CC (0) West V ir> )m it.i - 7 5 FF (Cl (D) (D) (C) (D) (Dl ID) (0) EF. (D) North Carolina . - 7 5 EF. (O) (D) (D| (Cl (D) (D) (D) (D) CC (Dl booth Carolina - 8 / CC (0) (D) (D) (D) (D) (D) (D) (D) CC (D) East South Genual Division Kentucky - 1 1 Rb (Cl (C) (0) (Cl (D) (D) (D) (D) (NA) (NA) Tennessee . - 2 2 AA (Dll (D| (D) (0) (D) (D) (D) (D) CC (D) Alabama - 4 4 EE (D) (D) ID) (D) (D) (D) (D) (D) CC (D) West South Central Division i omsiana. . - 3 3 BB (C) (D| (0) (0) (Dl (D) (D) (D) AA (D) Toxas - 13 10 2 7 57 6 1 6 3 4 27 5 440 5 716 9 1 143 4 58 2 EE (D) Pacific Division California - 8 5 Ul) (D) (D) (D) (Cl (D) (D) (D) (D) AA (D) INDUSTRY 2869, INDUSTRIAL ORGANIC CHEMICALS, N E C United States . - 569 346 112.3 2 108 7 70 7 145.7 1 216.5 10 475.7 13 948.6 24 232 8 3 162.6 102.4 4 966 0 New England Division New Hampshire. - 2 2 BB (0) (0| ID| ID) (D) (D) (0) (0) AA (D) Massachusetts. - 10 5 1 2 21 5 0 7 1 5 12 4 48 4 75 9 122 4 33 AA (D) Rhode island .- - - 4 3 CC (0) (0) (D) (Dl (D) (D) (0) ID) CC (D) Connecticut. - 13 0 EE (0) (0) (D) (D) (0) (D) (0) (D) FF (D) Middle Atlantic Division New Cork... - 39 23 4 2 72 4 2 4 5 1 33 0 225 1 226 2 445 6 (D) 6 1 158 6 flew jersey . - 73 45 7 7 130 1 5 1 10 8 03 6 512 3 8100 1 320 7 59 0 13 1 440 2 Pennsylvania . - 23 13 4 3 72 2 2 7 5 3 41 2 171 2 370 2 552 0 22 3 20 32 9 Last North Central Division Ohio .. - 31 17 2 9 52 0 1 6 36 30 6 275 9 376 2 634 2 50 4 3 1 99 6 Indiana - 6 3 CC (D) ID) (0) (0) (D) (0) ID) ID) EE (D) Illinois ... - 28 11 20 32 2 1 3 23 19 7 177 1 1 04 1 354 0 30 4 EE (0) Michigan - 20 13 7 6 141 8 4 7 90 79 5 401 9 340 9 736 7 91 7 FF (D) - 11 6 CC (C| (0) (Dl (D) (0) (0) (D) (D) BB (0) West North Central Division - 3 o CC (D) (D) (Dl ID) (0) (Dl (0) (0) AA ID) Missouri . 11 2 f F (Cl ID) (Dl (01 (D) (D) (O) ID) EF 01 Kansas 6 p AA (Cl III) 101 (D| 1 2 4 6 26 6 29 9 55 8 (17 5) 10 7 100 to 24't employees .... It) (3 2) (38 5) (2 6) (5 0) (2/3) (127 0) (135 9) (265 4) (D) (40 8) 250 lu 411') employees 2 (D) (D) |U) r ovuiM'l |>y administrative monels'* 1 0 54 0 2 2 0 0 2 l) 3 16 60 7 0 13 0 1 1 2 5 INDUSTRY 2865, CYCLIC CRUDES AND INTERMEDIATES Total. - 191 35.7 031.5 23.4 46.6 369.8 2 214.4 3 453 6 5 637.0 443.1 844.4 Establishments with an average of— 1 to 4 employees. - .- - E9 22 U) 0 5 (2) 12) 0.3 0 7 3 3 50 05 0.7 5 to 9 employees.. E4 17 0 1 20 0 1 0 2 1 1 1 2 20 3 21 5 1.0 2 4 10 to 19 employees. . E4 25 03 50 02 04 2,7 18 4 33 4 51 3 60 8 5 20 lo 49 employees . - 34 1 1 16 4 0 7 1 5 100 01 0 159 2 242 2 7 4 20 2 M) to !)9 employees 24 1 7 27 5 1 1 2 3 14 9 96 R 213 5 304 2 23 0 41 5 l 0 lo 249 employees - 29 4 1 60 0 26 5 3 36 9 240 6 395 3 628 6 55 1 109 2 250 to 499 employees . • . - 23 7 9 131 4 4 7 98 75 4 462 0 940 1 1 300 4 80 0 237 6 500 to 999 employees .. . - 11 7 6 137 6 50 9 7 77 2 650 4 979 2 1 632 5 112 1 174 7 l .000 in 2 499 employees . - b (1281 (246 2) 19 0) (175) (161 4) (662 5) (709 3) (1 301 3) (157 4) (241 5) covered by administrative records 2 - . E0 35 0.2 3.7 0.2 0.3 2.2 10 5 19 4 29 8 2 7 4.5 INDUSTRY 2869, INDUSTRIAL ORGANIC CHEMICALS, N E C. Total . - 569 112.3 2 108.7 70.7 145.7 1 216.5 10 475.7 13 948.8 24 232.8 3 182.6 2 942.7 Establishments with an average of— 1 to 4 employees. . E4 117 0 2 29 0 1 03 17 138 21 7 35 7 20 4 5 5 in 9 employees. E4 56 0 4 6 4 0 3 0 5 3 7 25 9 38 6 64 0 4 5 8 3 10 to 19 employees. E2 50 0 7 11 4 0 4 0 9 58 460 60 9 1186 6 9 14 5 20 to 49 employees.. - 83 2 7 42 3 1 6 3 4 21 0 180 6 259 6 440 6 68 3 47 1 b i 99 t'niployoes . - HI 5 9 9/ 4 3 4 6 9 50 6 498 4 752 7 1 241 3 98 9 176 1 1 HJ lu 24j umployoes - 80 13 2 223 5 8 2 17 2 126 7 1 023 3 1 540 1 2 539 2 188 6 352 7 250 lo 499 employees • . - 46 16 0 308 1 106 22 8 180 5 1 852 5 2 730 9 4 350 7 732 4 407 t 500 to 999 employees - 30 20 2 390 1 13 3 27 2 2360 1 074 5 2 339 7 4 178 7 265 6 433 5 ' 000 to 2 4 )9 employees .. 22 (52 3) (1 026 6) (32 6) (68 7) (589 3) (5 180 8) (8 196 8) (11 258.1) (1 794 4) (1 436 9) 2.500 employees or more .. 4 (D) (0) (D) (D) ID) (D) (D) ID) (0) ID) Covered by administrative records 2 . to 130 05 8 6 0 3 06 50 29 1 37 3 66 4 7 2 82 Represents zero iP) Withheld to avoid disclosing opeiations of individual companies Data lor tins item are included in figures in parentheses above (NA) Not available n a c Nol tj.se*here classified Withheld because estimate did not meet publication standards (X) Not applicable (Z) Less than 50 thousand dollars or hours under 50 employees 'Payton and sales daia for small single unit companies with up to 20 employees (cutofl varied by industry) were obtained from administrative rocords of other government agencies rather the 1 from census report forms These data were then used in conjunction with industry averages to estimate the balance of items shown for these small establishments This technique wa9 also used tor a small number of other establishments whose repons were not received at time data were tabulated The following symbols are shown where estimated data based on administrative records data account for 10 percent or more of figures shown El —10 to 19 percent, E2—20 to 29 percent. E3—30 to 39 percent. E4—40 to 49 percent. E5—50 to 59 percent. E6—60 to 69 percent. E7— 70 to 79 percent. Eb—dO to 89 percent, E9—90 to 99 percent; E0—100 percent ^Report forms were not mailed to small single-unit companies with up to 20 employees (cutoff varied by industry) Payroll and sales data for 1 977 were obtained from administrative records supplied by other agencies of the Federal Government These data were then used m conjunction with industry averagos to estimate the balance of items shown Data are also included in respective size classes shown 3 Data in value of shipments column represent value of production rather than value of shipments Consequently, formula for computing value added by manufacture was modified to excude any change in finished products inventories between beginning and end of year 4 Daia m value of shipments column represent value of work done rather than value of shipments Consequently, formula for computing value added by manufacture was modified to exclude any change in inventories between beginning and end of year 5 Four digit industry totals for all items including establishment counts are not equal to sum of 6-digit subindustry figures due to difficulties in classifying a few establishments at subindustry level MANUFACTURES-INDUSTRY SERIES 269 INDUSTRIAL ORGANIC CHEMICALS luhii; !.a Industry Statistics by Industry and Primary Product Class Specialization: 1977 (IdbltJ presents selected statistics lor establishments according to thoir degree ol specialization in products primary to ttieir industry Measures of plant specialization shown are (1) industry specialization ratio ol primary product shipments to total product shipments (primary plus secondary, excluding miscellaneous receipts) tor the establishment, and (2) product class specialization ratio ol largest primary product class shipments to total product shipments (primary plus secondary excluding miscellaneous receipts) for the establishment See appendix for method of computing ratios Statistics for establishments with specialization ratios ot less than 75 percent are included in total linos but are not shown as a separate class In addition, data may not be shown for various reasons, e g . to avoid disclosing operations of individual companies For explanation of terms, see appendix A) Indus All employees Production workers Value New pro duct class Industry or product class by percent ot specialization All establish¬ ments Number Payroll (million Number Hours Wages (million added by manulac lure (million Cost of materials (million Value of shipments (million capital expendi¬ tures (million COdi* (number) (1.000) dollars) (1,000) (millions) dollars) dollars) dollars) dollars) dollars) Zbb t Gum and wood chemicals 1 nine industry 1 19 4 « 54 0 3 8 7 H 38 9 1850 205 3 391 3 27 0 t slablishments with 75 percent specialization or moro 106 2 9 26 1 2 4 4 9 20 2 87 7 98 9 186 0 9 4 28b 1 1 Softwood distillation products Establishments with this product class primary. 9 (D) (D) (D) (D) (0) (D) (D) ID) (D) Establishments with 75 percent specialization or more in class - 7 0.3 3.7 0.2 0.5 2 9 9 1 95 183 1 0 28612 Other gum and wood chemicals Establishments with this product class primary -. 46 2 9 27 9 2 3 4 7 20.7 104 4 125 4 229 9 8 7 Establishments with 75 percent specialization or more in class - 36 2 3 190 1 9 3 9 14 9 664 75 4 141 6 (D) 2865 Cyclic crudes and Intermediates: i ntire industry . 191 35 7 631 5 23 4 46 6 369 8 2 214 4 3 453 6 5 637.0 443 1 Establishments with 75 percent specialization or more. 145 15 4 245 3 9.7 19 4 140 4 822 2 1 678 0 2 495 2 175.1 28651 Cyclic intermediates Establishments with this product class primary -. 58 20 5 400 2 13 4 269 227 9 1 549 1 2 523 0 4 059 4 342.3 Establishments with 75 percent specialization or more in class - 28 4 6 87 4 2.6 56 45.1 390.3 971 9 1 376 4 113 9 28652 Synthetic organic dyes T slablishments with this product class primary - 32 8 7 129 2 58 115 80 8 394 9 414 2 795 9 64 4 Establishments with 75 percent specialization or more in class 24 (D) (D) (D) (D) (D) (D) (D) (D) (D) 2865: i Synthetic organic pigments, lakes, and toners l slablishments with this product class primary 31 4 8 72 3 3 0 5 7 42 0 177 9 255 3 426 2 20 0 1 slablishments with 75 percent specialization or more m class 21 2 3 30 2 1 4 2 8 19 3 83 0 109 4 186 0 98 28655 c yclu (coal tar) crudes Establishments with this product class primary. 19 1.3 23.0 0 9 2.0 15 1 72 3 223 1 296 5 120 L slablishments with 75 percent specialization or more in class 14 0 6 9 7 0 4 09 69 48 0 99 3 147 2 74 2869 Industrial organic chemicals, nec ( nine industry - . - - - 569 112 3 2 108 7 70 7 145 7 1 216 5 10 475 7 13 948 8 24 2328 3 162 6 Establishments witn 75 percent specialization or more - 434 48 2 861 6 31.0 62 4 509 7 4 247 0 6 406 4 10 602 4 1 435 8 28893 Synthetic organic chemicals, nec Establishments with this product class primary.. 65 92 159.0 5.7 11 9 86 9 583 8 878 7 1 445 5 65 9 Establishments with 75 percent specialization or more in class 40 3 1 50 9 2 1 4 2 28 2 213 1 308 6 518 6 17 9 28694 Pcslicides and other organic agricultural rhormcals 1 stahlishments with this prorluc t class primary 21 / / 14 14 5 4 10 8 91 ? y4 7 7 709 0 1 666 1 132 4 1 slablishments with 76 purcuni specialization or muu; in Muss 10 1 8 32 1 1 3 2 5 20 9 401 1 282 0 689 t 34 7 28695 1 thyl alcohol and other industrial organic chemicals, nor 1 slablishments with this produt t < lass primary 62 5 4 80 9 3 1 60 40 9 31 1 3 358 4 659 7 8/ 6 ( slablishments with 75 percent spec ialization or more in class 45 (D) (0) (D) (U) (0) (D) ID) (D) (D) 28696 Miscellaneous end-use chemicals and chemical products, except urea Establishments with this product class primary. 45 17 9 316 2 11 3 23 4 182 9 1 020 2 1 607 3 2 606 5 169 6 Establishments with 75 percent specialization or more in class - 20 36 61 8 2 4 4.7 38 9 265.2 440.2 708 1 35 1 28697 Miscellaneous cyclic and acyclic chemicals and chemical products Establishments with this product class primary. 180 70 4 1 381 2 44 1 91 5 798 8 7 526 2 10 273.5 17 647 1 2 688 2 Establishments with 75 percent specialization or more in class 99 17 0 320.8 10 9 22 4 194 1 1 706 8 3 344 2 5 029 2 479 1 Represents zero (D) Withheld to avoid disclosing operations ot individual companies (NA) Not available n e c Not elsewhere classified (S) Withheld because estimate did not meet publication standards (X) Not applicable (Z) Less than 50 thousand dollars or hours, under 50 employees Data in value of shipments column represent value of production rather than value of shipments Consequently, formula for computing value added by manufacture was modified to exclude any change in finished products inventories between beginning and end of year 2 Data in value of shipments column represent value of work done rather than value of shipments Consequently, formula for computing value added by manufacture was modified to exclude any change in inventories between beginning and end of year INDUSTRIAL ORGANIC CHEMICALS 270 MANUFACTURES—INDUSTRY SERIES Procedures Used to Develop the 1 9 7 8, 1 9 7 9 » 1980, and Projected 1990 0E5 Survey-Based Matrices Introduct i on The Bureau of Labor Statistics converted the National industry-occupational matrix from a Census base to an Occupational Employment Statistics (OES) survey base in 1981. This paper presents a brief overview of the general procedures established to develop OES survey-based matrices and describes the detailed steps used to develop the first National matrices based on OES survey data. In early 1 982, a bulletin will be published presenting the 19 7-8 and 1990 matrices. The 1980 and 1990 matrices are the basis of the analytical statements on employment outlook and job openings for the 1982-83 edition of the Occupational Outlook Handbook . OVERVIEW Because the OES surveys are conducted on a three-year cycle in which each covered industry is only surveyed once in each cycle, a matrix developed for any given reference year must be based on survey data for three different years. Given this data constraint, a matrix for any given year should most accurately describe occupational employment by industry if it were based on data that were at most one year from the reference year. For example, OES survey data for 1978, 1979, and 1930 should provide the most reliable data to construct a 1979 matrix based on OES survey data. The timing in which National OES survey data become available and the established cycle for production of National occupational projections and publication of the Occupational Outlook Handbook , however, have resulted in the development of procedures in which matrices are developed for specific reference years prior to the availability of the most reliable data that will become available. Survey data are generally not available until late December of the year following the survey reference year. For example, 1980 OES survey data will not be available until December 1981. Program commitments, however, required that data for 1980 be presented in the Occupational Outlook Handbook that was completed in mid-1981 and which will be published in 1982. Because staffing patterns do not change significantly over a three-year period, procedures were developed in which a preliminary 1980 matrix was developed using the survey data available at the time the employment estimates presented in the Handbook were developed. The following is a general description of the system that has been designed for developing OES survey-based matrices. Three base year or current matrices will be produced for every 271 OES Survey-Based Matrix Procedures— 2 reference year. They are to be titled I , Preliminary; II, Revised; and III, Final. The preliminary matrix will be based on OES survey data for the three years prior to the reference year. The revised matrix will be based on OES survey data for the reference year and the two previous years. The final matrix will be based on OES survey data for the reference year, the previous year, and the year following the reference year. The 1979-1 matrix, therefore, is based on OES survey data for 1976, 1977, and 1978. The 1979-11 matrix uses 1977, 1978, and 1979 survey data. A 1979—III matrix will be constructed using 1978, 1979, and 1980 data after the latter become available in December 1981. To develop employment data for each reference year's matrix (whether it is a I, II, or III), the staffing patterns from the OES survey data are applied to actual annual average industry employment totals from the Current Employment Survey—CES-- (ES-202 data for industries for which CES data are not available) for the reference year. To develop a matrix that covers all workers, the OES survey-based data are supplemented with data for industries not covered by the OES surveys. Estimates of occupational employment of self-employed persons and unpaid family workers are also developed and added at the total all industries level. DETAILED DESCRIPTION OF PROCEDURES USED TO DEVELOP THE FIRST CURRENT AND PROJECTED NATIONAL OES SURVEY-BASED MATRICES The first National OES survey-based matrices were developed during 1980 and 1981. Matrices were developed for the years 1973, 1979, 1980, and projected 1990. Current or base year matrices produced include a 1978-11, 1 9 7 8-1 1 1, 1979-1, 1979-11, and a 1930-1. For industries covered by the OES surveys, the 1973-11 and 1979-1 have the same staffing patterns and the 1978—III, 1979-11, and 1980-1 have the same staffing patterns. Staffing patterns for the nonsurveyed sectors and the occupational distribution of self-employed persons and unpaid family workers are the same for the three matrices for each reference year, whether a I, II, or III matrix, because the actual source data for the reference year were available at the time the matrix was developed. Current Year Matrices (1978. 1979, and 1980) Industry Controls In all current years, industry controls for wage and salary workers in the 373 industries in the National survey-based matrices are annual averages. Most of the data are from three-digit SIC industry estimates from CES series! data for railroads, education, Federal government, State government, and 272 OES Survey-Based Matrix Procedures— 3 local government are on a two-digit SIC basis. Wage and salary workers in all five of the current matrices discussed in this paper use CES estimates benchmarked to ES-202 data in the spring of 1981. These CES data will be published in August 1981 as Supplement to Employment and Earnings Revised Establishment Data . In some cases, detailed industries are disaggregated from CES series that were combinations of two or more three-digit SIC industries. In these cases, ES-202 data for 1978 were used to disaggregate the 1978 CES data and ES-202 data for 1979 were used to disaggregate the 1979 and 1980 CES data. When the 1980 ES-202 data become available, they will be used to disaggregate the 1980 CES data, where necessary, for the 1980-11 matrix. The ES-202 data for 1978 will be published in the fall of 1981 by the National Technical Information Service (NTIS) and comparable data for 1979 will be published by NTIS in early 1982. In a few cases—agriculturei forestry, and fishing and private househo1ds--industry employment controls were obtained from the CPS. These data are published each year in the January issue of Employment and Earninos following the reference year. 1978 Matrices 1973-11 Matrix . The 1978-11 matrix included Occupational Employment Statistics (OES) surveys salary worker staffing patterns in State government government collected in 1975 (no later data were transportation, communications, and public utilities collected in 1975 and 1976 hospitals, and railroads industries collected in collected in 1978. data from on wage and and local available); industries trade industries, Federal government, collected in 1976; manufacturing 1977; and nonmanufacturing industries A combined data file of all the OES survey staffing patterns within the scope of the 1978-11 matrix was produced and benchmarked to the 1973 industry controls. This benchmarking step was necessary for two reasons : (1) OES survey data represent observations taken in the spring (second quarter) of the survey year, and (2) the combined OES survey file represents observations in different years; benchmarking theoretically unifies the data to a single year. Because of the differences that can occur as a result of benchmarking to annual averages for a single year, different values for any single occupation/industry cell are usually recorded in the matrix and in the actual OES survey. Wage and salary worker staffing patterns for the nonsurveyed industries — agriculture, forestry, and fishing; education; and private households — which were developed from the Census-based matrix and the CPS were also inputed to this combined data file. Details of the development of the estimates for the nonsurveyed r ?ctors are given in a Irter section of this paper. 273 OES Survey-Based Matrix Procedures— 4 Data on employment for some detailed occupations in the OES survey-based matrix are not collected in some OES surveys, generally because employment is believed to be too small to develop reliable survey estimates. Employment in such occupations, however, is included in a broader category in the OES survey, generally in a residual occupation such as "all other professional workers." For many of these occupational cells, a procedure was developed to disaggregate an employment estimate from the appropriate OES survey data based on employment for a similar occupation/industry cell in the Census-based matrix. 1_/ For some occupations included in some OES surveys, however, no procedure was believed to be adequate to disaggregate data for industries in which the occupation was not included in the survey. In such cases, available OES survey data were collapsed into the appropriate residual category in the OES survey-based matrix. In some cases, two or more detailed survey occupations were collapsed into a single occupation that had a Census-based matrix equivalent. In these cases, sufficient information or knowledge was lacking on which to make employment estimates for cells that had not been surveyed and for which analysts felt there should be employment. For other occupations, collapsing survey data to the comparable Census-based matrix occupations enabled analysts to d i ssaggregate employment estimates from the survey-based matrix residuals. In this manner, detailed employment information for a number of specialized kinds of compositors, collected only in the printing industry, was suppressed to the broad title of compositors, which was then disaggregated from the residual all other crafts workers for the missing cells. 2 / Once the wage and salary worker portion of the matrix had been developed, the matrix was listed off in two forms: industry by occupation and occupation by industry (transposed matrix). Staff analysts examined the data to identify cells that were inconsistent with their knowledge about an industry or an occupation. The analysis concentrated on occup ation/i ndustry cells for which employment estimates were developed by disaggregation procedures. For some occupations, analysts who reviewed the matrix believed that employment did exist in industries that showed no employment and recommended that employment be added for these matrix cells. To implement these recommendations necessitated further disaggregation of survey-based matrix residuals. Frequently, more than one occupation had to be disaggregated from the same residual to account for the recommendations. In these cases, three policies were generally followed before the changes in the matrix were made. (1) If the sum of the recommended changes did not exceed the appropriate residual, the changes were accepted. (2) If the sum of the recommended changes did exceed the appropriate residual, the recommendations were prorated so that each cell recommended for change received a portion of the 274 OES Survey-Based Matrix Procedures-- 5 residual. (3) If the designated residual contained no employment, updates were disallowed. One notable exception was made to the latter procedure for data processing machine mechanics. For this occupation, employment estimates were disaggregated, to the limits of the residuals, from all other mechanics, all other engineering technicians, and all other technicians, because it was believed that these workers could have been included in all three categories in the OES surveys. A very detailed procedure was followed to review all update recommendations received from the analytical staff. Recommendations that were accepted were incorporated manually into the matrix. Appropriate residuals were manually adjusted. A total of 4,776 manual updates were made (including updates to residuals). Most updates (about two-thirds) were less than 50 persons in size. 1 / The final step in developing the current employment estimates was to add the separately developed estimates of self-employed persons and unpaid family workers to the updated matrix by detailed occupation at the total all industries level. Details of the methods used to develop these estimates are contained in a later section of this paper. 1 978—III Matrix . This matrix and the 1 9 79-1 1 have the same staffing patterns. The detailed occupational employment values are different only because of the different industry controls used in the two years. A detailed explanation of the development of the staffing patterns for the 1 9 7 8-1 1 I matrix is given below in the section discussing the 1979-11 matrix. 1979 Matrices 1979-1 Matrix . This matrix was developed by first replacing the detailed wage and salary worker occupational employment data for the nonsurveyed sectors with 1979 estimates and then applying the 1979 industry controls to those industries in the 1978-11 matrix where wage and salary worker staffing patterns were based on OES survey data. Detailed occupational employment estimates of self-employed persons and unpaid family workers were prepared for % 1979. Because the 1979-11 matrix was prepared immediately after the 1979-1 matrix, the 1979-1 was not used for any substanative analysis. 1979-11 Matrix . This matrix, which has the same staffing patterns as the 1 973 — III matrix, includes data from OES surveys of hospitals-and railroads collected in 1976 (no later data were available), manufacturing industries and Federal government collected in 1977, nonmanufacturing industries collected in 1973, and balance of n o n m a n u f a c t u r i n g industries collected in 1 979. 4./ Balance of nonmanufacturing was a new designation in 1979, resulting from the combination of surveys, some of which had been conducted in 1975 and others in 1976. Included are 275 OES Survey-Based Matrix Procedures— 6 transportation, communication, and public utilities; wholesale and retail trade; State government; and local government. Although a survey of employment in educational services establishments was conducted for the first time in 1979, summary data were not available at the time that matrix production began. Consequently, employment estimates for education were developed at the National level from secondary sources, as explained in a later section of this paper. Estimates from the 1977 and 1978 OES surveys, along with estimates from the 1975 and 1976 OES surveys, had previously been used to build the 1978-11 National survey-based matrix. The simplest method of producing the 1979-11 matrix was to replace the 1975 and 1976 data with 1979 data for the same industries, leaving the 1977 and 1978 surveyed industry staffing patterns intact. Twenty-four new occupations, 12 of which were in the education survey, that were added for the 1979 round of surveys, were collapsed back to the appropriate survey occupations that appeared in the 1975 and 1976 rounds. In order to duplicate the matrix parameter file, these collapses were done on an industry by industry basis. The application of 1979 industry annual averages from the CES benchmarked all sectors to 1979 employment. Since the 1978-11 matrix that was used in this procedure had already been updated, only the new 1979 estimates were reviewed and updated. The basis for these updates to the new survey data was the updates for the same cells' in the 1978-11 matrix. Similar values were used, to the limit of the appropriate residuals. Manual calculations of the affected residuals were incorporated also. Employment estimates for 1979 for the agriculture, forestry, and fishing, households were developed and added, estimates for self-employed persons and the all industries level (the same as in added to the matrix. The wage and salary worker portion of this 1979-11 matrix for OES survey covered industries was benchmarked to 1978 annual average industry controls from the CES to produce the 1 973—III matrix. Nonsurveyed sectors and self-employed persons and unpaid family workers for 1978 were added. The 1973—III matrix became the base year for the 1990 projected matrix. 1930 Matrix 1930-1 Matrix . As for the 1979-1 matrix, the 1980-1 matrix was developed by replacing the detailed occupational employment data for the nonsurveyed sectors of agriculture, forestry, fishing, education, and private households with 1930 employment estimates that had been developed separately from CPS data. The 1980 annual average industry controls from the CES for wage and salary nonsurveyed sectors of education, and private Occupational employment unpaid family workers at the 1979-1 matrix) were 276 0E5 Survey-Based Matrix Procedures-- 7 workers were used to benchmark the staffing patterns from the 1 9 79- 1 1 matrix to p r e 1 i rrr i n a r y 1 980 staffing patterns. Detailed 1980 occupational employment estimates of self-employed persons and unpaid family workers* developed separately, were added. Thus, the wage and salary worker staffing patterns in the 1978-III, 1979-11, and 1980-1 matrices are the same, having been based on the same set of OES survey rounds. Employment estimates from the 1980-1 matrix will be used in the 1982-83 edition of the Occupational Outlook Handbook . Nonsurveyed Sectors Occupational employment estimates within industry sectors not covered by OES survey data--agriculture, forestry, and fishing; education; and private households--were developed at the 2-digit industry level and incorporated into the matrix estimating system as data files, just as if they had been surveyed. 5 / The primary inputs in developing these estimates were the CPS and the 1978 National Census-based matrix. Agriculture . Staffing patterns for agriculture, forestry, and fishing are based on patterns for private wage and salary workers in the Census-based matrix and the CPS. Using the private wage and salary worker patterns eliminated the double-counting of Federal, State, and local government workers employed in these industries, who were already counted in the detailed government industries. Data from the 1978 Census-based matrix industry, agricultural production, was on a 1967 SIC basis. To use these data in the OES survey-based matrix, which is on a 1972 SIC basis, the Census-based matrix data was divided into the two detailed survey-based matrix industries agricultural production, crops, and agricultural production, livestock. This distribution was made on a 70/30 basis, as a result of discussions held with officials of the Department of Agriculture. All survey-based matrices for the years 1973-1980 reflect this percentage distribution. The staffing pattern in the 1978 Census-based matrix industry, agricultural production, was used for both OES survey-based matrix industries, except for an adjustment to the total employment of athletes in the two survey-based matrix industries to reflect the 80 percent of total athletes in agriculture in the Census-based matrix who were assumed to be horse trainers in the survey-based matrix industry, agricultural production, livestock. An 80/20 adjustment also was made to the control value from the Census-based matrix value for veterinarians to reflect the greater proportion of these workers who would be expected to be found in agricultural production, livestock. After these adjustments, all other cells were forced to the control totals from the CPS for farm workers and for total wage and salary workers for all detailed agriculture, forestry, and fish ng industries. 277 OES Survey-Based Matrix Procedures— 8 Educational Services . Occupational employment estimates in the educational services sector were based on the 1978 Census-based matrix staffing pattern for all wage and salary workers, including private industry and Federal, State, and local government workers. .6/ Government workers were included in this industry because of their significance to total education employment and because of the need to generate employment estimates for education separate from the much larger employment estimates for the government sectors. In these matrices, education workers are not included in the estimates for State and local government. A few further disaggregations of occupations were made based on limited data from one State's OES survey in 1 9 76. !_/ These occupations were refined using ratios from that survey and included college teachers, graduate students, and extension service specialists from college and university teachers; librarians and audio-visual specialists from librarians; three kinds of file clerks; four kinds of food service workers; and a number of other detailed survey occupations, a complete list of which is shown below. Census-Based Matrix Occ. Survey-Based Matrix Occ. S B M Code Biological scientists Eng. and sci. tech., nec Therapists Technicians, nec Teachers, college & univ. Librarians Sales workers Computer operators Bookkeepers File clerks Receptionists Misc. clerical workers Foremen, nec Biological scientists Medical scientists All other engineering techs. Science technicians Speech and hearing clinicians Physical therapists All other therapists All other technicians Technical assts. , library Teachers, voc. ed. & train. Teachers, college Graduate assistants Extension service specialists Librarians Audio-visual specialists Sales clerks Sales reps., agents Computer operators Peripheral equip, operators Accounting clerks Bookkeepers, hand File clerks Personnel clerks Admissions evaluators Receptionists Switchbd. ops./receptionists Mail clerks General clerks, office All other off. clerical wkrs. Supervisors, nonworking 10040601 10040602 10081898 10081899 1 0101803 10101804 10101810 10141404 10141405 10202001 1 0202002 1 0202003 10202004 1 024240 1 10242402 30001802 30001899 40040601 40040602 40060601 40060603 40062601 40062602 40061603 40064802 40064803 40063402 40066312 40066393 50040003 278 OES Survey-Based Matrix Procedures— 9 Craft workers, nec Cooks Waiters and waitresses Food service workers, nec Misc. laborers Supervisors, nonwkg., service Maint. repairers, gen. util. All other skilled workers Cooks, short order Cooks, institutional Hosts and hostesses, rest. Waiters and waitresses Kitchen helpers Fd. prep, wkrs., fast food Pantry, sandwich prep, wk. All other fd. service wkrs. Helpers, trades All other unskilled wkrs. 70200001 50144821 50144899 70040802 70040304 70041601 70041602 70041802 70041804 70041805 70041899 80002833 80002899 Based on information available from the National Center for Educational Statistics (NCES) and other secondary sources, five cells were fixed in the 1978 matrices: Elementary school teachers; technical assistants, library; janitors; secretaries; and typists. All other cells in the educational services sector were forced to the 1978 industry control. The 1978 pattern was used to developed the 1979 and 1980 estimates. Private Households . For each year’s OES survey-based matrix, the CPS annual average employment for each of the five detailed private household worker occupations was used as a fixed cell. The remaining occupations in the private household industry were developed by forcing the remainder of the CPS annual average industry employment into a distribution based on the private household industry in the 1978 Census-based matrix. With the addition of the nonsurveved sectors to the surveyed sectors, total waoe and salary worker matrices were produced, bv occupation and industry . Self-Employed Persons and Unpaid Family Workers Estimates of occupational employment of self-employed persons and unpaid family workers were developed only at the total all industries level, rather than by detailed industry as in the Census-based matrix, because the development of such data would have produced very unreliable estimates. The general procedure was to develop employment estimates of self-employed persons and unpaid family workers for each detailed Census-based matrix occupation and then distribute the employment to related OES survey-based matrix occupations. The 1973 Census-based matrix was the primary source of data used to develop estimates of self-employed persons and unpaid family workers. Data in the 197S Census-based matrix, however, were modified for some occupations where the relationship of self-employed persons and unpaid family workers to total employment were out of line with trends over the 1971-73 period, 279 OES Survey-Based Matrix Procedures--10 based on CPS data. To develop estimates for 1979 and 1930, trends in the relationship of self-employed persons and unpaid family workers to total employment over the 1971-80 period were used to modify the 1978 ratios. These ratios were applied to CPS total employment for each occupation in these years to develop estimates of self-employed persons and unpaid family workers. The resulting data were forced to agree with the CPS 1979 and 1980 annual average employment estimates for each class of wo r k e r . The employment totals for self-employed persons and unpaid family workers in each Census-based matrix occupation were distributed to OES survey-based matrix occupations. A list of OES survey-based matrix occupations that were related to the 400 Census-based matrix occupations was developed. Analysts studied these relationships and distributed the Census-based matrix occupational control totals to OES survey-based matrix occupations. Some occupations were a one-for-one match. For other occupations, however, a distribution was made based on limited information. One of the following procedures was used by individuals making the estimates for each occupation: Cl) The entire Census-based matrix employment of self-employed persons and unpaid family workers was distributed to related OES survey-based matrix occupations based on the distribution of wage and salary workers in those ocupations in the OES survey-based matrix; (2) The entire Census-based matrix employment for each class of worker was distributed on a judgment basis to selected OES survey-based matrix occupations to which it was related; (3) The entire Census-based matrix employment of self-employed persons and unpaid family workers was placed in an appropriate OES survey-based matrix occupational residual; and (4) Any combination of the above that made sense in terms of the analyst's knowledge of the specific occupation(s ) . In using these procedures, the analysis was focused on the 1978 data and then similar procedures were used for 1979 and 1980 for each occupation. In general, the most common procedure followed was to distribute the control totals for self-employed persons and unpaid family workers in the Census-based matrix by the distribution of wage and salary workers in related OES survey-based matrix occupations. Adjustments were made in cases where this distribution did not make analytical sense. For example, no estimate was made for self-employed judges or self-employed claims takers for unemployment insurance benefits, even if the Census-based matrix occupation where these workers were included had some self-employed persons. Summary Tables After employment estimates of self-employed persons and unpaid family workers were developed, they were added to the wage and salary worker employment estimates to produce total employment by occupation at the total all industries level. 280 OES Surve v-Based Matrix Procedures — 11 P’-c'ected v e a r M a t - i c e s (1990) The 1990 occupational projections were developed Bureau's economic and employment projections as part efforts , of the which product , productivity, industry output, and industry employment. The Bureau developed three alternative 1990 projections, each based on different assumptions concerning such factors as labor force growth, defense expenditures, unemployment rate, and productivity trends. The assumptions and related projections are published in the August 1981 issue of the Monthly Labor Rgw ; eui . include projections of the labor force, gross national The basic procedure used to develop o to apply projected staffing patterns survey-based matrix to projected employment in the related indus self-employed persons and unpaid fani for each occupation. These totals wage and salary worker totals for the total employment projection by oc developed for each of the three alter same staffing patterns of indu alternative. The following detailed develop the occupational projections. ccupational projecti for each industry in wage and salary try. Separate tot ly workers were p were added to the p occupation to deve cupat i on . Projecti native scenarios, stries were used procedures were o n s was the OES wo r k e r a 1s for rojected rojected lop the ons were but the in each used to Industry Controls The Bureau's model produces projections for These projections were disaggregated to included in the OES survey-based matrix. In of industry employment for all CES published series developed through regression analysis were used to disaggregate employment 156 industry groups, the 373 industries general, projections i n the 156 sectors Industry employment projections for unpublished CES series were developed by disaggregation of appropriate projected data. CES series on the basis i -e - the the trands in E S - 2 G 2 Occupational Staffing Patterns Surveyed Sectors . I n for industries in data were extrapolate changes. Considerab1 that caused changes i in many changes to ratios. However, a r done just prior to projections, indicate projections was inco intensive effort was OES survey-based matr projecting previous pr d into the e analysis n staffing the me c h eview of th the deve d that the rrect p r oje devoted to ix staffina o c c u p a t ejection future b and r e v i patterns a n i c a 11 y e 1 9 " 5 o lopnent major c c t i o n of research pattern icnal staffing cycles, Decenn ased on decade e w identified t . The analysis developed ex ccupational pr of the most r ause of error occupational r on methods of s . 5/ patterns ial Census to decade he factors resulted trapolated ojections, ecent 1990 s in the a t io s . An project ing 281 OES Survey-Based Matrix Procedures —12 In general, the research tested the merits of a variety of extrapolation techniques. In these tests, use of current staffing patterns in the projected years generally produced better results, on the average, than any extrapolation technique. However, for large occupations that were not affected by any problems related to changes in industry or occupational definitions, the exponential extrapolation technique generally outperformed the constant ratio method. Since the tests were performed on data covering a short period of time and the exponential method worked well for large occupations representina a very significant proportion of employment, this technique was used where possible. The research also indicated that ratios developed through mechanical means must undergo intensive analytical review. The first step in developing the projected staffing patterns for the OES survey-based matrix was to project trends in OES survey data from the last two OES survey rounds for each industry. Unfortunately, because of changes between survey rounds in industry definitions (change from the 1967 SIC to the 1972 SIC), occupational definitions, survey forms, and geographical coverage, many difficulties were encountered in this process. Periodically, the SIC system, used as the basis for OES survey industry definitions, is changed. Such a change occurred between the OES survey round providing data for the current 1973 and 1930 matrices and the OES survey round immediately preceeding that affected several industries. As a result, trends could not be developed because the data were not comparable. In these cases, ratios were held constant at 1978 levels for the initial 1990 projected matrix. Trends were extrapolated only in industries in which 95 percent or more of employment included in the 1972 SIC industry definition was also included in the same industry in the 1967 SIC industry definition. Between the last two survey rounds, definitions were changed for several OES survey occupational categories. Some new occupations were added in the last survey round. With only one observation, trends could not be developed for these new occupations. Additionally, the occupational category that probably included the occupation in the previous round could net be projected because of inconsistent occupational content. Similar situations resulted when occupations were dropped or combined with other occupations in the OES survey. Even though the OES survey has been conducted since 1971 as a Federal-State cooperative program, all States do not participate in the program and the number of States in each OES survey round has varied. Beginning with the 1977 OES survey, the BIS surveyed the nonparticipating States as a whole and National data became available. 9/ Because National data were not available for both of the last two survey rounds in any industry, data from States that participated in both of the last two OES surveys for each 282 OSS Survey-Based Matrix Procedures —13 industry were summed and used as a proxy for National data. The number of States providing data used in developing trends to 1990 was as follows for each survey round: 1974 and 1977 manufacturing, 27; 1975 and 1978 nonmanufacturing, 29; and 1973 and 1976 trade, 19. The development of trends, therefore, excluded seme States that may have had significant employment in a specific occupation. In future projection rounds, this weakness will be eliminated; National data will become available for two points in time beginning with the 1980 OES survey, except for education and railroads. To overcome the problems identified above concerning the comparability of OES survey data in the last two OES survey rounds, only those occupations with consistent definitions that were found in industries with consistent SIC content were projected through the exponential extrapolation technique to 1990. The projected trends in survey occupations were related to appropriate OES survey-based matrix occupations. Adjustments were made to these cells and any other cells in the matrix by analysts who reviewed the data for all industries. The analysis was concentrated, however, on industries that employed over 100,000 workers. Cells that were not projected were held constant in 1990 at the 1978 levels. An iteration procedure forced the distribution patterns in each industry to add to 100 percent. These patterns became the initial 1990 projected staffing patterns. The initial projected staffing pattern in each industry was applied to projected industry employment totals for wage and salary workers to develop the preliminary 1990 occupational projections. These projections were analyzed in detail over a six month period, based on studies of occupations and industries conducted during preparation of the Occupational Outlook Handbook . Factors considered by analysts included changes in production methods, technological changes affecting occupational mix, chances in product mix of industries, changes in average size of establishments in industries, and other economic factors affecting specific occupations. In addition, some occupations were projected independently of the matrix based on the relationship of the occupation to more closely associated variables. For example, projections of elementary school teachers were based on estimates of the school age population and pupil-teacher ratios. Projections developed in this manner were used in the matrix and adjustments in the ratios for other occupations were made when necessary. During the analysis, relationships were established between occupations in the Census-based matrix and the OES survey-based matrix to obtain the benefit of a longer time series. Based on all the analyses described above, changes were made in the initial projected OES survey-based matrix and an iteration procedure assured that the staffing pattern in each industry 283 0E5 Survey-Based Matrix Procedures —14 added to 100 percent. The resulting ratios were applied to total projected employment of wage and salary workers in each industry to develop the final occupational projections of wage and salary workers . Nonsurveved Sectors . The initial projected 1990 occupational ratios for the agriculture, forestry, and fishing, education, and private households industries were taken directly from the 1990 Census-based matrix developed by the Bureau for 1978-90. The ratios were analysed based on CPS data that became available after the Census-based matrix was developed, and a few ratios were adjusted. The occupational distribution in the Census-based matrix was converted to the OES survey-based matrix distribution in the same way described above for the current year matrices. The projected ratios were applied to the 1990 industry projections for the appropriate industries. The results were reviewed in detail. Changes in the staffing patterns resulted from this review were incorporated in the final matrix. Self-Emoloved Persons and Unpaid Family Workers . Based on an analysis of the trends in the 1978-90 Census-based matrix and the 1971-80 CPS data on the ratio of self-employed persons and unpaid family workers to total employment in each occupation, estimates were developed of the percentage of each of these two classes of workers to total employment in each Census-based matrix occupation. These ratios were applied to projected 1990 total employment for each Census-based matrix occupation. The summed result was compared to the 1990 control totals for these two classes of workers, which had been independently projected as part of the Bureau's economic model. Minor adjustments forced the ratios to 100 percent and the individual estimates to the control totals. Using the methods already indicated, the Census-based matrix occupational estimates were disaggregated by Handbook analysts to the full list of survey-based matrix occupations. These were reviewed for consistency with information developed in the course of other occupational research and appropriate changes were made. Total Occupational Employment . To develop total employment projections by occupation, projections of wage and salary workers in the surveyed and nonsurveyed sectors was added to the projected totals of self-employed persons and unpaid family workers. Unlike previous projections of total National employment, the totals in the OES survey-based matrix represent the number of jobs by occupation, not the number of persons employed by occupation. J_0/ These totals are different because one person may have more than one job. The difference between the number of jobs and the number of persons employed in 1990 is estimated at approximately 7 percent. 234 OES Survey-Based Matrix Procedures —15 Footnotes W For a mo-e detailed explanation of these disaggregation techniques* see "Development of the State GES Survey-Based Matrix," OES Matrix/Prcjections Memo No. 12* September 10, 1979. Approximately 4 percent of total occupational employment was developed through disaggregation of residuals. 2/ A total of 1,836 detailed survey occupations were used directly, disaggregated, or collapsed to a final occupational list (after manual updating) containing 1,615 detailed matrix occupations. This same final occupational list was used for all 1978, 1979, and 1930 matrices. These numbers may change in future matrices as the number of OES survey occupations included increases or decreases. Z/ A list of these updates was given to States engaged in developing projections for the interim projections project to use as a guide for updating State matrices. In this list, updates of less that 50 persons were excluded to eliminate possible problems in allocating small numbers among the various States. When these smaller updates were removed from the list, the number of updates dropped to 1,543. 4/ Employment in hospitals was resurveyed in 1980. Employment in railroads has not been surveyed since 1976; there are no immediately plans to resurvey this industry. 5/ Although an OES survey of employment in educational services was conducted in 1979, National data from this survey are not available because 10 States did not participate, one of which was California. Furthermore, a combined estimates file of the 41 States that did participate in the OES education survey was not available in time to use in these first National OES survey-based matrices. Surrogate National estimates, based on data from the 41 States, will be used in the 1930-11 matrix. 6./ See f tn . 5 . !_/ In 1976, Oklahoma became the first State to collect data on employment in educational services. No other data on emoloyment in education were available at the time the matrices discussed in this paper were developed. 3/ For a mere detailed explanation, see "Projected Occupational Staffing Patterns of Industries," BIS technical paper, April 1931. 9./ Funds to do this work were provided to the Bureau by the National Science Foundation. 285 OES Survey-Based Matrix Procedures--U _1_0 / Wage and salary workers in and education were only counted one job because the CPS was the these industries. Similarly, family workers are counted only agriculture, private households, once, even if they held more than source of data on employment in self-employed persons and unpaid once in their primary job. 286 50272 -101 REPORT DOCUMENTATION i._R eport no. 2. page EPA 560/5-85-004 3. Recipient's Accession No. 4 . Title and Subtitle Methods for Assessing Exposure to Chemical Substances - Volume 4: Methods for Enumerating and Characterizing Populations Exposed to Chemical Substances 5. Report Date - . 7/85 6. 7 . Author(s) Douqlas A. Dixon, Karen A. Hammerstrom, Uina L. Hendricksc Amy Borenstein, John J. Doria, Thomas Faha, Patricia Jennings f|. Performing Organization Rept. No. 9. Performing Organization Name and Address Versar Inc. 6850 Versar Center Springfield, Virginia 22151 10. Protect/Task/Work Unit No. Task 9 11. Contract(C) or Grant(G) No.