key: cord-305558-dnvl60ez
authors: Ranjan, Avinash Kumar; Patra, A. K.; Gorai, A. K.
title: Effect of lockdown due to SARS COVID-19 on aerosol optical depth (AOD) over urban and mining regions in India
date: 2020-07-19
journal: Sci Total Environ
DOI: 10.1016/j.scitotenv.2020.141024
sha: 
doc_id: 305558
cord_uid: dnvl60ez

Abstract The Severe Acute Respiratory Syndrome-COronaVirus Diseases 2019 (SARS-COVID-19) pandemic has posed a serious threat to human health (death) and substantial economic losses across the globe. It was however presumed that extreme preventive measures of entire lockdown in India might have reduced the air pollution level and therefore decreased the aerosol optical depth (AOD). The Moderate Resolution Imaging Spectroradiometer (MODIS)-based Multi-angle Implementation of Atmospheric Correction (MAIAC) daily AOD product was deployed to investigate the change in AOD level during lockdown phases across the Indian Territory as compared to the long-term mean AOD level (2000–2019) of the same periods. The key findings of the study revealed that AOD level over the Indian Territory is greatly reduced (~45%) during the lockdown periods as compared to the long-term mean AOD level (2000–2019). Furthermore, a noteworthy negative AOD anomaly (~6 to 37%) was observed across the four metropolitan cities in India during the entire lockdown period (25th March to 15th May 2020). However, coal mining regions of the various coalfields in India showed a positive anomaly (~+11 to 40%) during the lockdown periods due to ongoing mining operations. In a nutshell, the study results indicated a huge drop in the AOD level over Indian Territory during lockdown periods. It is expected that the pandemic can influence some policy decisions to propose air pollution control methods. Lockdown events possibly may play a crucial role as a potential solution for air pollution abatement in the future. It may not be uncommon in future when the governments may implement deliberately selective lockdowns at pollution hotspots to control the pollution level.

(https://www.who.int/emergencies/diseases/en/). The first COVID-19 case was found in the Wuhan region of Central Hubei Province of China on 31 st December 2019 (Shi et al., 2020) . It has rapidly been spreading since then across the globe (Li et al., 2020a) Countless studies have already unveiled the importance of aerosol research, and also demonstrated the direct and indirect contributions of aerosols on the climate change at regional to global scales (Qian and Giorgi, 1999; Menon et al., 2002; Huang et al., 2014) . The aerosol optical depth (AOD) affects the atmospheric stability and precipitation as aerosols disturb the scattering and absorption of solar radiation (Jiang et al., 2016; Shaw and Gorai, 2018) , the hydrological cycle (Prasad et al., 2004) , and vegetation cover and its growth (Lal et al., 2019; Sarkar and Kafatos, 2004) . Apart from climatic effects, aerosol causes many serious healthrelated issues (i.e., asthma, premature death, lung cancer, cardiopulmonary mortality, and pulmonary inflammation) (Prasad et al., 2005; Huang et al. 2012; Mulenga and Siziya, 2019) .

Furthermore, numerous past studies have shown that AOD can be used as a metric to estimate air pollution level, whereas AOD is typically used as a proxy of PM 2.5 and PM 10 concentration estimation (Kumar et al., 2007; Lin et al., 2015) . Thus, study on AOD during lockdown periods can help in understanding the influence anthropogenic activities on the tropospheric aerosol

level. An approximate concentration of particulate matter can also be anticipated. The current J o u r n a l P r e -p r o o f study therefore investigated the impacts of COVID-19 imposed lockdown events on AOD level over the Indian Territory. The overarching objectives of this investigation are (1) to analyze the effect of lockdown due to COVID-19 on the AOD level over the Indian Territory with special emphasize on four metropolitan cities and 10 mining regions in India, and (2) to estimate the AOD anomaly during the lockdown periods (2020) as compared to the long-term (2000 -2019) mean AOD during the same periods. Retrieval and processing of long-term daily AOD data using Google Earth Engine (GEE) cloud platform is the crucial aspect of the present study. This is the maiden study where long-term (2000 -2020) daily AOD were retrieved for the entire Indian Territory with special emphasize on four metropolitan cities and 10 coal mining locations during the lockdown periods.

This paper is structured as follows: Section 1 is the Introduction section, where emergence of COVID-19 pandemic, status of affected countries from COVID-19 pandemic, status of COVID-19 cases in India, literature review on positive impacts of COVID-19 enforced lockdown on environment, importance of AOD study, motivation and objectives of the present investigation have been summarized. Section 2 describes the materials and method that include details of satellite data, details of the study regions, phase-wise data processing, and the data analysis sequence. The key findings of the study, like, phase-wise AOD concentration over the Indian Territory (including four metropolitan cities and 10 coal mine locations), AOD anomaly as compared to last 20 year mean AOD for the same periods, comparison with earlier studies have J o u r n a l P r e -p r o o f

The AOD product of Moderate Resolution Imaging Spectroradiometer (MODIS) satellite sensor (MCD19A2-v6) is used in the present study to retrieve the daily basis AOD over the Indian Territory. MCD19A2 is a MODIS Terra and Aqua combined Multi-angle Implementation of Atmospheric Correction (MAIAC) Land Aerosol Optical Depth (AOD) Level-2 gridded product having a spatial resolution of 1 km. MCD19A2 offers daily-basis AOD for land at two different wavelength bands, i.e., 470 nm (blue band) and 550 nm (green band). AOD at 550 nm (green band) was used in the present study due to its better consistency .

The MCD19A2 product was typically available in sinusoidal grid projection, which was re- Thereafter, phase-wise mean AOD datasets were exported, and further processing, map preparation, assessment, etc. were completed in ArcGIS (v10.5) software.

The present study is focused to analyze the impact of phase-wise nationalwide lockdown on the spatio-temporal pattern of AOD level over the Indian Territory as compared to last 20 years mean AOD level. Furthermore, attention is paid to investigate the variation in AOD level within Furthermore, phase-wise anomaly maps are derived using Eq. 1 to portray the percent changes in AOD level at a particular spatial location during lockdown period as compared to the long-term mean (2000 -2019) AOD for the same time-periods. The self-explanatory flowchart for the methodological workflow is given in Fig 2, wherein the sequence of data acquisition, preprocessing, AOD extraction, phase-wise AOD estimation, and AOD anomaly assessment are presented.

Where, is the phase-wise mean AOD for the year 2020; and ̅ is the phase-wise long-term (2000 -2019) mean AOD.

The phase-wise AOD distribution map of Indian Territory is prepared and presented in period. Additionally, the AOD data of few pixels in those areas are missing for some years and hence the mean AOD level may be lesser than the actual level. Ultimately, it can be concluded that the entire national lockdown has led to the huge decline in AOD value across the Indian state, suggesting corresponding reduction in air pollution (especially PM 2.5 and PM 10 ) level over the Indian Territory.

Phase-wise AOD anomaly was estimated using Eq. 1 and map was prepared to understand the spatial variation in AOD during the lockdown period in India as compared to the long-term mean AOD (2000 AOD ( -2019 . The prepared AOD anomaly map is presented in Fig 4, wherein negative range (green -yellow) shows the decrement and positive range (light bluedark blue) shows the increment in the AOD during different phases of the lockdown as compared to the long-term mean AOD during the same periods.

The prepared AOD anomaly map shows a significant reduction in AOD during lockdown period as compared to long-term mean AOD. During Phase 1, a significant reduction in the AOD as compared to the long-term mean AOD were observed in most of the states, except a few patches in MH, some portion of RJ, MP, CG, OD, TS, and AP states that reported higher AOD value (Fig 4(a) ). During Phase 2, almost all states had negative AOD anomaly percent; only a few small unevenly distributed patches of positive AOD anomaly percent were detected across J o u r n a l P r e -p r o o f the north-east to south-eastern states of India (Fig 4(b) ). However, slightly higher positive AOD anomaly patches were observed during Phase 3. Almost every state was detected with few small spatial patches of positives AOD anomaly; particularly, RJ, UP, BR, all north-east states, JH, WB, MH, TS, AP, and KA were found with relatively higher positive anomaly patches (Fig   4(c) ). Furthermore, AOD anomaly map over the entire lockdown period (25 th March to 15 th May, 2020) is shown in Fig 4(d) . The map indicated that during the lockdown period, the AOD reduced drastically across the Indian Territory (as AOD anomaly percent was found negative across most of the area). Nevertheless, few spatial patches were observed across MP, MH, TS, AP, OD, WB, and AS states where the positive anomaly was detected.

The quantitative analysis of AOD anomaly (state-wise mean AOD anomaly is presented in one is the maiden study which reports a significant reduction in the AOD level over the Indian Territory along with four metropolitan cities and 10 coal mine locations during lockdown periods as compared to same periods of last 20 year mean AOD level. Overall, these studies revealed that COVID-19 pandemic enforced lockdown events resulted in significant improvement of the air quality in highly polluted Indian cities.

Phase-wise AOD anomaly ( However, unusually high positive anomaly over the few mine locations can be due to the spatiotemporal variation in areal coverage of coal mine locations along with the amount of coal extraction. One more possibility is that some of the mines were not functional since 2000 and coal production from these mines started after 2010, which resulted in very less AOD during that time period as compared to recent years. Moreover, inconsistency in the total number of AOD pixels within the 3 km buffer zone of the coal mine location cannot be overlooked. This may be the one of the possible reasons for slightly higher positive AOD anomaly, as we have discussed in section 3.2 and 3.3. No such study was available to compare the AOD level over the mine locations.

In a nutshell, our investigation reports a huge reduction in AOD level across the Indian 

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