key: cord-0688820-7i6vacvu
authors: Sharma, S. K.; Mandal, T. K.; Banoo, R.; Rai, A.; Rani, M.
title: Long-Term Variation in Carbonaceous Components of PM(2.5) from 2012 to 2021 in Delhi
date: 2022-03-23
journal: Bull Environ Contam Toxicol
DOI: 10.1007/s00128-022-03506-6
sha: e51ffa45f43dc2a2e4a49a18d090233059735e29
doc_id: 688820
cord_uid: 7i6vacvu

Carbonaceous species [organic carbon (OC), elemental carbon (EC), elemental matter (EM), primary organic carbon (POC), secondary organic carbon (SOC), total carbon (TC), and total carbonaceous matter (TCM)] of PM(2.5) were analyzed to study the seasonal variability and long-term trend of carbonaceous aerosols (CAs) in megacity Delhi, India from January, 2012 to April, 2021. The average concentrations (± standard deviation) of PM(2.5), OC, EC, TC, EM, TCM, POC and SOC were 127 ± 77, 15.7 ± 11.6, 7.4 ± 5.1, 23.1 ± 16.5, 8.2 ± 5.6, 33.3 ± 23.9, 9.3 ± 6.3 and 6.5 ± 5.3 µg m(−3), respectively during the sampling period (10-year average). The average CAs accounted for 26% of PM(2.5) concentration during the entire sampling period. In addition, the seasonal variations in PM(2.5), OC, EC, POC, SOC, and TCM levels were recorded with maxima in post-monsoon and minima in monsoon seasons. The linear relationship of OC and EC, OC/EC and EC/TC ratios suggested that the vehicular emissions (VE), fossil fuel combustion (FFC) and biomass burning (BB) are the major sources of CAs at megacity Delhi, India. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00128-022-03506-6.

Atmospheric aerosols are complex in their chemical composition (Weagle et al. 2018) , varying spatially and temporally (Sharma et al. 2021a ) and have different effects on local as well as regional air quality (Belis et al. 2013; , visibility, Earth's radiation budget, global climate (Ramanathan et al. 2001 ) and human health (Pope and Dockery 2006; Dockery and Stone 2007; Pope et al. 2009; Fuzzi et al. 2015; Lelieveld et al. 2015; Gauderman et al. 2015; Velali et al. 2016) . Studies reveal that the PM 2.5 was responsible for more than 3 million premature deaths per year worldwide (Jerret 2015; Leliveld et al. 2015) . PM 2.5 consists of organics [organic carbon (OC) and elemental carbon (EC)], elements, sea salt, secondary aerosols, etc. The constituents of carbonaceous species of PM 2.5 have an important impact on regional and global climate along with Earth's atmospheric system (Ramanathan et al. 2001) . Therefore, identifying and quantifying the carbonaceous aerosols (CAs) in PM 2.5 is essential to design the air quality management strategies to control PM 2.5 mass loading in the ambient air through targeted action (Waked et al. 2014) .

Carbonaceous aerosols are the significant sources of atmospheric particulate matter (PM)/aerosols, containing up to 70% of aerosols mass loading (Kanakidou et al. 2005) and its major sources are biomass burning (BB), fossil fuel combustion (FFC) and biogenic emissions (Claeys et al. 2004; Venkataraman et al. 2005) . Several studies have been conducted on CAs and their probable sources in urban Mandal et al. 2014; Sharma et al. 2018; , rural, remote (Begam et al. 2017 ) and high altitude atmosphere (Kaushal et al. 2018; Sharma et al. 2021a, b) of the Indian region on a short-term basis, but a few studies have been carried out on the long-term trend (Sharma et al. 2018; 2021a) . In this paper, we reported the seasonal and annual variability of OC, EC, elemental matter (EM), primary organic carbon (POC), secondary organic carbon (SOC) and total carbonaceous matter (TCM) of PM 2.5 at an urban site of Delhi, India from January, 2012 to April, 2021.

PM 2.5 samples (n = 805) were collected periodically (2 samples/week) at the observational site of CSIR-National Physical Laboratory (28° 38′ N, 77° 10′ E; 218 m amsl), New Delhi from January, 2012 to April, 2021 [except July-December, 2012 and Covid-19 lockdown period (lockdown periods: 25 March, 2020 -31 May, 2020 unlock periods: 1 June, 2020 -31 August, 2020 ]. The sampling site is a typical urban environment surrounded by heavy roadside traffic and an agricultural institute in the southwest direction (Sharma et al. 2018) . Vehicular traffic, FFC, BB, secondary aerosols, minerals and soil dust are the major source of aerosols of Delhi and surrounding areas . During 2020-2021, the total number of registered vehicles in Delhi was 11.8 million (Delhi Statistical Handbook 2021). The meteorology of Delhi is divided into four different seasons: winter (January-February), summer (March-May), monsoon (June-September) and post˗monsoon (October-December). Winter months are chilly (temperature: ~ 3°C) whereas, the summers are generally scorching and dry (temperature: 47°C).

A fine particle sampler (APM 550, Envirotech, Delhi, IN; having a flow rate of 1 m 3 h −1 with accuracy ± 2%) was used to collect the PM 2.5 samples on pre-baked quartz filters (size: 47 mm) for 24 h. The quartz filters were weighed before and after the sampling to determine the gravimetric mass concentration of collected PM 2.5 samples. OC and EC analysis of PM 2.5 samples was performed by a Thermo-optical carbon analyzer (DRI 2001A, Atmoslytic Inc., Calabasas, CA, USA) using IMPROVE-A protocol (Chow et al. 2004) . OC/EC carbon analyzer is working on the preferential oxidation of OC and EC at different temperatures plateaus (140, 280, 480 and 580°C; for OC1, OC2, OC3 and OC4, respectively) in pure He and three temperature plateaus (580, 740 and 840°C for EC1, EC2 and EC3, respectively) in 98% He + 10% O 2 gas (Chow et al. 2004) . A proper punch of ~ 0.536 cm 2 area of the filter was cut and analyzed in triplicate along with field blank filters (> 50 samples during the sampling period). The standard calibration for peak area verification was performed daily using 5% CH 4 + balance helium gas (before and after sample analysis). Calibration of the OC/ EC analyzer was performed by 4.8% of CO 2 + balance He gas along with known amounts of KHP (potassium hydrogen phthalate) and sucrose solution. In the present case, repeatability errors of OC (detection limit: 0.54 µg m −3 ) and EC (detection limit: 0.21 µg m −3 ) analysis were estimated as 3%-7% (Sharma et al. 2021a) . Statistical data analysis of chemical species of PM 2.5 was performed by chi-square method using Monte Carlo statistics (non-parametric test) (Sharma et al. 2018) . TCM is computed by the addition of organic matter (OM = 1.6 × OC) and EM (EM = 1.1 × EC) of PM 2.5 (Malm et al. 2004; Turpin and Lim 2001; Srinivas and Sarin 2014) . The effective carbon ratio (ECR) of CAs provides the information about the formation of SOC in the atmosphere which is calculated as SOC/(POC + EC). SOC cannot be measured directly by a Carbon analyzer, therefore, SOC was computed by the EC tracer method (Castro et al. 1999 ) using the following equations: Figure 1 represents the time series plots of OC, EC and TC of PM 2.5 along with PM 2.5 concentration from January, 2012 to April, 2021. The annual average concentrations of PM 2.5 , OC, EC, TC, EM, TCM, POC and SOC with standard deviation (± SD) were 127 ± 77, 15.7 ± 11.6, 7.4 ± 5.1, 23.1 ± 16.5, 8.2 ± 5.6, 33.3 ± 23.9, 9.3 ± 6.3 and 6.5 ± 5.3 µg m −3 , respectively during 2012-2021 (Table 1) . During the study, a nonsignificant decreasing trend in annual concentration of PM 2.5 (y = − 1.596x + 135.3; R 2 = 0.18) was recorded, whereas the significant decreasing trend in annual concentration of OC (y = − 0.484x + 18.4; R 2 = 0.49), EC (y = − 0.502x + 10.2; R 2 = 0.51) and TC (y = − 0.986x + 28.6; R 2 = 0.54) were recorded ( Fig. S1 ; in supplementary information). In 2017, the highest annual average concentration of PM 2.5 was noted as 143 ± 70 µg m −3 , whereas the minimum concentration of PM 2.5 was obtained in 2021 as 109 ± 53 µg m −3 which are exceeding the National Ambient Air Quality Standards (annual: 40 µg m −3 ). The higher concentrations of OC (19.3 ± 13.9 µg m −3 ), EC (11.4 ± 7.5 µg m −3 ) and TCM (43.3 ± 30.1 µg m −3 ) were observed in 2013. OC, EC and TCM contributed to ~ 12%, ~ 6% and ~ 26%, respectively to PM 2.5 concentrations during 2012-2021 (10-year average). reported similar percentage contributions of OC (~ 12%), EC (~ 5.5%) and TCM (~ 25%) to PM 2.5 at Delhi, whereas Mandal et al. (2014) reported higher percentage contributions of OC (28%) and EC (9%) to PM 2.5 in an industrial area of Delhi. The seasonal variations in the level of OC, EC, TC, TCM, POC and SOC of PM 2.5 and their percentage contribution to PM 2.5 and seasonal differences are summarized in Table 2 . The highest concentrations of PM 2.5 , OC, EC, TCM, POC and SOC were recorded during post-monsoon seasons followed by winter, summer and monsoon seasons (Table 2 ; Fig. S2 , in supplementary information). The higher concentrations of PM 2.5 and its carbonaceous species during 8.5 ± 6.7

3.4 ± 1.9

2.9 ± 1.7

12.4 ± 8. − 5.6 a − 6.5 a post-monsoon and winter seasons could be the source strength of PM 2.5 and prevailing meteorological conditions (temperature, relative humidity, wind speed, wind directions, etc.) as well as the lowering of mixing height of the boundary layer at the sampling site. Regional and long-range transportation of pollutants (from crop residue burning) towards the sampling site also arises from the north-western states of IGP (Punjab, Harayana) of India (Ravindra et al. 2022) . Sharma et al. (2021b) also experienced similar seasonal variations of PM 10 and their chemical constituents in megacity Delhi based on long-term observations (2010) (2011) (2012) (2013) (2014) (2015) (2016) (2017) (2018) (2019) . During all the seasons, the POC value is recorded higher than the SOC level with an ECR value < 1.0 (0.3 to 0.6) which indicates the higher contribution of POC over SOC (Table 2) . Monthly average (pooled estimate of each month of 2012-2021) values of PM 2.5 , OC, EC, TC and TCM from January, 2012 to April, 2021 are represented in Fig. 2 . The highest monthly average concentrations of PM 2.5 , OC, EC and TCM were 226 ± 71; 28.9 ± 12.2; 12.3 ± 6.8 and 59.8 ± 25.7 µg m −3 , respectively during December (postmonsoon) (Fig. 2) , whereas the minimum monthly average levels of PM 2.5 , OC, EC and TCM were 64 ± 23; 6.1 ± 2.4; 2.5 ± 1.3 and 12.4 ± 4.8 µg m −3 , respectively during July (monsoon). Several researchers Bisht et al. 2015; Sharma et al. 2021b ) have reported similar monthly variations in carbonaceous species (OC, EC, TC and TCM) of PM 2.5 at Delhi and IGP of India Srinivas and Sarin 2014; Khaiwal et al. 2021) . The monthly concentration of PM 2.5 has also exceeded the National Ambient Air Quality Standards (NAAQS; 24 h: 60 µg m −3 ; annual: 40 µg m −3 ) of India.

Generally, FFC and BB fuel burning (dungcake, crop residue and wood-burning) contribute appreciably to OC and EC particulates Begum et al. 2011) . A positive linear correlation between OC and EC is usually considered as emissions from the same combustion sources (Salma et al. 2004; Sharma et al. 2014; Jain et al. 2017 ). Whereas, a weakly correlated OC and EC suggest the influence of secondary organic aerosols (SOA) formed through the gas-to-particle conversion of volatile organic compounds (VOCs) (Begum et al. 2004 (Begum et al. , 2006 . In the present study, significant positive linear relationships between OC and EC were observed during winter (R 2 = 0.66), summer (R 2 = 0.74), monsoon (R 2 = 0.62) and post-monsoon (R 2 = 0.67) seasons (Fig. 3) in Delhi, indicating the influence of VE or BB (or both).

The OC/EC ratio has been applied extensively for decoding the sources of CAs around the globe (Novakov et al. Cheng et al. 2006; . The higher OC/ EC value (between 4 and 12) is generally used for BB (Szidat et al. 2006) , whereas, the OC/EC ratio between 1.4 to 4 are used (between 0.3 to 1 used for diesel vehicles) for VE along with BB (mixed type) (Amato et al. 2009; Salameh et al. 2015; . In this study, the average OC/ EC ratio of PM 2.5 were 2.3 ± 0.7, 2.1 ± 0.6, 2.2 ± 0.8 and 2.5 ± 0.8 during winter (range 1.1-5.7), summer (range 1.0-3.9), monsoon (range 1.2-5.9) and post-monsoon (range: 1.1-6.8) seasons, respectively ( Table 2 ). The average OC/EC mass ratio evidenced that the FFC and BB are the dominant sources of CAs at the study site. The seasonal value of the EC/TC ratio also support the emissions of these sources over Delhi. Stable carbon and nitrogen isotopic analysis of PM 2.5 also suggested that the VE and BB are the major sources of PM 2.5 in Delhi (Sharma et al. 2015 . have applied the receptor models on long-term chemical species of PM 2.5 and reported that BB and VE were the major sources of PM 2.5 in Delhi. The average ECR values (Tables 1 and 2) of PM 2.5 demonstrated the abundance of POC (in the present case ECR < 1.0) over SOC and has more warming effects.

Several researchers Singh et al. 2020; Sokhi et al. 2021; Saharan et al. 2022 ) have reported the reduction in concentrations of gaseous (NO, NO 2 , CO, SO 2 , O 3 , NH 3 , benzene, toluene, etc.,) and particulate (PM 2.5 and PM 10 ) pollutants in Delhi, India, and globe during covid-19 lockdown period as compared to pre-lockdown period due to restricted activities. The sampling period of PM 2.5 also falls under the 4 lockdown, and 3 unlock periods in Delhi during 2020 (Table S1 ; in supplementary information). Therefore, analysis of PM 2.5 and its carbonaceous species (OC, EC, TC, and OC/EC) are essential to understand the levels of CAs during this period. During 4 lockdown periods (25 March 2020 to 31 May 2020), the PM 2.5 samples were not collected at the study site due to restricted entry into the laboratory. However, PM 2.5 sample collection was resumed from the unlock-1 period, i.e., 1 June 2020 onwards (Table S1; in supplementary information). Figure 4 shows the time series plots of PM 2.5 , OC, EC, and TC concentrations from pre-lockdown to unlock period (January 2020 to December 2020) in Delhi. The average concentrations of PM 2.5 , OC, EC, and TC were 125, 13.6, 6.6 and 21.1 µg m −3 , respectively during the pre-lockdown period, whereas the average concentrations of PM 2.5 , OC, EC, and TC were 68, 6.0, 3.0 and 9.1 µg m −3 during the unlock-1 period when only government offices were opened with limited capacity (Table S1 ; in supplementary information). The average reduction in mass concentrations of PM 2.5 (reduced by 45%) and its carbonaceous components OC (reduced by 55%), EC (reduced by 53%), and TC (reduced by 54%) were ~ 50% when compared with pre-lockdown to unlock-1 period. Also, the OC/EC ratio is increased up to ~ 50% (2.0 to 3.1), however the sources of CAs still arises from VE and FFC. Singh et al. (2020) reported > 40% reduction in PM 2.5 concentration over Delhi during lockdown period in comparison to unlock period. In contrast, Saharan et al. (2022) reported a 35% reduction in PM 2.5 concentration during the lockdown period compared with the pre-lockdown period in Delhi during 2020. Several researchers in India and the globe reported a similar reduction in pollutants levels (Kotnala et al. 2020; Sokhi et al. 2021) .

The present study demonstrates the seasonal variability and long-term trends with high loading of carbonaceous species (OC, EC, TC, EM, TCM, POC, and SOC) in PM 2.5 over megacity Delhi, India, which is further contaminating the ambient air quality of the region and impact on the level of short-lived climate-forcing pollutants. Seasonal variations in mass concentrations of PM 2.5 , OC, EC, POC, SOC, and TCM were recorded maximum in post-monsoon and minimum in monsoon seasons. The study suggested that the VE, FFC, and BB are the major sources of CAs at megacity Delhi, India. During covid-19 unlock periods, the OC/EC ratio is increased up to ~ 50% (2.0 to 3.1), which shows the sources of CAs arises from VE and FFC. In urban areas, the number of vehicles, industries, and influence of human activities was increasing with time and expected to increase soon, which is believed to augment the abundance of TCM over the region. The CAs have a significant impact on atmospheric chemistry, climate, and environmental transport systems. Hence, there is a need to take necessary mitigation measures to control/cut down the emissions of carbonaceous aerosols from various sources. Fig. 4 Time series plots of PM 2.5 , OC, EC and TC during per-lockdown, lockdown and unlock period during 2020 in Delhi (the data were not collected during the lockdown periods)

Quantification of road dust resuspension in an urban environment by the multilinear engine: a comparison with PMF2

Seasonal characteristics of water-soluble inorganic ions and carbonaceous aerosols in total suspended particulate matter at a rural semi-arid site

Investigation of sources of atmospheric aerosol at urban and semi-urban areas in Bangladesh

Gravimateric analysis of air filters and quality assurance in weighing

Key issues in controlling air pollutants in Dhaka

Critical review and meta-analysis of ambient particulate matter source apportionment using receptor models in Europe

Carbonaceous aerosols and pollutants over Delhi urban environment: temporal evolution, source apportionment and radiative forcing

Carbonaceous aerosol in urban and rural European atmospheres: estimation of secondary organic carbon concentrations

Black carbon measurement in a coastal area of south China

Equivalence of elemental carbon by thermal/optical reflectance and transmittance with different temperature protocols

Formation of secondary organic aerosols from isoprene and its gas-phase oxidation products through reaction with hydrogen peroxide

Delhi Statistical Handbook (2021) Registered vehicles in Delhi. Directorate of Economics and Statistics, Govt of National Capital Delhi

Cardiovascular risks from fine particulate air pollution

Particulate matter, air quality and climate: lessons learned and future needs

Association of improved air quality with lung development in children

Social and travel lockdown impact considering coronavirus disease (COVID-19) on air quality in megacities of India: present benefits, future challenges and way forward

Chemical characteristics and source apportionment of PM2.5 using PCA/ APCS, UNMIX and PMF at an urban site of Delhi

Seasonal characteristics of aerosols (PM 2.5 and PM 10 ) and their source apportionment using PMF: a four-year study over Delhi

Atmospheric science: the death toll from air-pollution sources

Organic aerosol and global climate modelling: a review

Wintertime carbonaceous aerosols over Dhauladhar region of North-Western Himalayas

Emergence of blue sky over Delhi due to coronavirus disease (COVID-19) lockdown implications

The contribution of outdoor air pollution sources to premature mortality on a global scale

Spatial and monthly trends in speciated fine particles concentration in the United States

Origin of carbonaceous aerosols over the tropical Indian Ocean: biomass burning or fossil fuels

Health effects of fine particulate air pollution: lines that connect

Fine-particulate air pollution and life expectancy in the United States

Spatio-temporal variability in atmospheric abundances of EC, OC and WSOC over Northern India

One-year record of carbonaceous aerosols from an urban location (Kanpur) in the Indo-Gangetic Plain: characterization, sources and temporal variability

Aerosols, climate, and the hydrological cycle

Seasonal variations in carbonaceous species of PM 2.5 aerosols at an urban location situated in Indo-Gangetic Plain and its relationship with transport pathways, including the potential sources

Drivers of air pollution variability during second wave of COVID-19 in Delhi

chemical composition in five European Mediterranean cities: a 1-year study

Elemental and organic carbon in urban canyon and background environments in Budapest, Hungary

Variation of OC, EC, WSIC and trace metals of PM 10 in Delhi

Variation of stable carbon and nitrogen isotopes composition of PM 10 over Indo Gangetic Plain of India

Study on ambient air quality of megacity Delhi, India during Odd-Even Strategy

Carbonaceous species of PM 2.5 in megacity Delhi

Seasonal characteristics and sources of carbonaceous components and elements of

Seasonal variation and sources of carbonaceous species and elements of PM 2.5 and PM 10 over the eastern Himalaya

Stable carbon and nitrogen isotopic characteristics of PM 2.5 and PM 10 in Delhi, India

Diurnal and temporal changes in air pollution during COVID-19 strict lockdown over different regions of India

A global observational analysis to understand changes in air quality during exceptionally low anthropogenic emission conditions

PM 2.5 , EC and OC in atmospheric outflow from the Indo-Gangetic Plain: temporal variability and aerosol organic carbon-to-organic mass conversion factor

Contribution of fossil fuel, biomass burning and biogenic emissions to carbonaceous aerosols in Zurich as traced by 14 C

Species contributions to PM2.5 mass concentrations: revisiting common assumptions for estimating organic mass

Cytotoxicity and genotoxicity induced in vitro by solvent extractable organic matter of size-segregated urban particulate matter

Residential biofuels in south Asia: carbonaceous aerosol emissions and climate impacts

Source apportionment of PM 10 in a north-western Europe regional urban background site (Lens, France) using positive matrix factorization and including pri-mary biogenic emissions

Global sources of fine particulate matter: interpretation of PM2.5 chemical composition observed by SPARTAN using a global chemical transport model