Impact of COVID-19 on the Air Quality over China and India Using Long-term (2009-2020) Multi-Satellite Data

We have examined the air quality over China, India and demonstrated marked differences in levels of air pollution resulted from the COVID-19 restrictions during December–April, 2019–20 to that of 11 years mean of 2009–19. The criteria air quality indicators i.e., nitrogen dioxide (NO2), sulphur dioxide (SO2), Aerosol Index (AI) and aerosol optical depth (AOD) data are retrieved from the Ozone Monitoring Instrument (OMI), TROPOspheric Monitoring Instrument (TROPOMI), and MODerate Resolution Imaging Spectroradiometer (MODIS) sensor on the Terra and Aqua satellites, respectively. Over China, during COVID-19 lockdown a significant drop in columnar abundances of tropospheric NO2 (–37%), SO2 (–64%) and AOD (–8%) for 2020 in comparison to 11 years mean (2009–19) has been observed. A noticeable difference in NO2 column burden is seen over SE (–35%), NE (–33%), NW (–13%) and SW (–5%) China. Over the SE and NE China, both NO2 and SO2 levels decreased dramatically in 2020 from that of 2009–19, by more than 40% and 65%, respectively, because of both stricter regulations of emissions and less traffic activity due to reduced social and industrial activities during COVID-19 restrictions. In contrast, the curve of monthly mean tropospheric columnar burden of NO2 and SO2 over India has shown moderate reduction of 16% and 20%, respectively because lockdown came into effect much later in March 2020. The mean NO2 and SO2 over IGP region is found to be 25% higher than whole India’s mean concentration due to large scale urban settlement and crop burning events. The statistical t-test analysis results confirm significant (p < 0.05) improvements in AQ during lockdown. The COVID19 pandemic provided an unprecedented opportunity to investigate such large-scale reduction in emissions of trace gases and aerosols. Therefore, it is important to further strengthen environmental policies to tackle air quality, human health, and climate change in this part of the


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after China due to increasing cases of COVID-19 also started a completed lockdown from 25 th

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5 on air quality status, a considerably long-term pollution dataset needs to be compared with that 119 of the lockdown duration of 2020 and is a major shortcoming in most of such recent studies. The objective of present research work is therefore to examine and quantify the effect 132 of COVID-19 outbreak and restrictions on the air quality over China

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8 spatial resolution of 7 km × 3.5 km. The data is available from 28 th June 2018 to current date.

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In the present study, we have compared 2019 UV Aerosol index with 2020 for the same time.

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Evidently, the spatial plots also depict similar pronounced effects during February and March 267 ( Fig. 3b and

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The increase in anthropogenic emissions due to traffic, increasing power generation, 292 flourishing industries, rapid urbanization, more demand of agricultural products, and more 293 biomass fuel usage are the primary sources of NO2 over China    During the lockdown period, the mean tropospheric NO2 was 2.42±0.67 x10 15 molec.

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The study is further extended by analysing the SO2 column burden by classification as 367 described earlier for China.

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As per NASA OMI satellite, India holds 15% of all SO2 hotspots of the world.

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17%. This reduction is predominantly due to the temporary closure of presence of large 393 number of SO2 emission causing industries and other anthropogenic activities such as 394 vehicular emissions that could be probable reasons of SO2 concentration over India.

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The study is further extended by analysing the SO2 column burden over IGP region of 396 India. Here also, the negative values are discarded while calculating mean. The IGP region of 397 India experiences severe air pollution due to highly polluting thermal power plants.  Fig. 7 shows the TROPOMI UVAI for 2020 (left), 2019 (right). During January 2020 413 (Fig 7(a)

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18 Fig. 8 (a) shows that during the January month the Indo-Gangetic Plains (IGP) and  Fig. 8 (b) shows that during February, AOD2020 is lower as compared to mean AOD2009-  An overall drop by around 8% in AOD has been observed during the lockdown (23 rd 462 January to 08 th April) period with a mean AOD2020 of 0.36 ± 0.12 and AOD 2009-19 of 0.39 ± 463 0.12 over China.

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19 around 12% in mean AOD. For India, the lockdown has started on 25 th March so changes that 467 are more prominent during April. During the peak of confinement measures, the IGP region 468 of India AOD2020 is higher than AOD2009-19.

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The t-test analysis of NO2, SO2 and AOD for China and India during lockdown period are 516 shown in Table 3  and is much more strongly associated with traffic; the effect of country specific lockdown has 538 more prominently seen in NO2 columnar concentration.