COVID-19 and Air Pollution in Indian Cities: World’s Most Polluted Cities

In the present study, pollutants levels from 24 March-31 May in 2020 were compared with the same time period in 2019 to estimate the impact of lockdown on air pollutants levels in 39 different cities of India (including 10 Indian cities considered among the world’s 20 most polluted cities). Data for air pollutants was obtained from the Central Pollution Control Board (CPCB) which was statistically analyzed. Tropospheric NO2 column retrieved from Ozone Monitoring Instrument (OMI) were compared between 2019 and 2020 to compare the NO2 levels. Impact of lockdown measures on Ghaziabad which is the world’s most polluted city and Patiala which showed maximum reduction during the lockdown period in the present study was studied in detail. After the implementation of lockdown measures, air pollution decreased but with substantial variation among pollutants. The most significant reduction was observed for nitrogen dioxide (NO2) (3– 79%) and carbon monoxide (CO) (2–61%), pollutants which are mainly related to traffic emissions. Ozone (O3) showed a mixed trend with increasing levels at some cities which may be attributed to lower titration of O3 by NO. Maximum reduction observed in PM10 and PM2.5 was 58 and 57%, respectively during the lockdown period in 2020 as compared to the previous year. Air quality of the cities also improved in 2020. During the lockdown period in 2020, AQI of only 15% of cities was in the ‘Unhealthy’ category (151–200) while in 2019, 56% of cities were in the ‘Unhealthy’ category. In Ghaziabad and Patiala all the pollutants showed significant reduction after lockdown implementation except O3. Diurnal patterns of PM10, PM2.5, CO and NO2 showed lower values during lockdown period in 2020 with less distinct bimodal patterns as compared to 2019. The present study provides evidence that widespread implementation of air pollution measures can result in immediate air quality benefits.


INTRODUCTION
In late December 2019, novel infectious coronavirus disease  was identified in Wuhan, China which was later on confirmed to be transmitted human to human through respiratory droplets (WHO, 2020). On 30 th January, the first confirmed case of COVID-19 in India was found. As of 23 rd March 2020, the number of COVID-19 cases increased to 499 in India (https://www.worldometers.info/coronavirus/ country/india/) which was still very less than many other countries like US, Italy and China. India being the world's second most populated country with many densely populated cities had chances of spread of the virus at an accelerating rate. To prevent the spread of the COVID-19, the government of India imposed nationwide lockdown from 24 th March to 31 st May. As a result, all non-essential services including schools, colleges, religious worship places, government offices, modes of transport (trains, flights and cabs), public utilities and industrial activities were closed. Citizens were advised to remain at home and to maintain social distancing.
On the basis of annual average of PM2.5 in 2019 IQAir identified most polluted cities in the world with 13 Indian cities among the top 20 polluted cities (IQAir Report, 2019) ( Table 1). Only 1% of the Indian population is exposed to less than the global WHO guideline level of annual mean PM2.5 (10 µg m -3 ) (IEA, 2016). Major sources of PM2.5 in India are anthropogenic activities like fossil fuel combustion, transportation, industrial emission (Venkataraman et al., 2018). High levels of pollutants impose significant health issues (Chowdhury and Dey, 2016). In 2017, 1.24 million deaths in India (12.5% of the total deaths) were attributable to air pollution (Balakrishnan et al., 2019). Therefore, efficient monitoring of air quality at the city level would help in understanding the major contributing sources and the policy making for achieving better air quality. With the implementation of lockdown measures in India, a sudden break on all anthropogenic activities (mainly transportation and industrial activities) improved the air quality. Delhi, the world's most polluted capital city witnessed blue sky with about 49% reduction in air quality index (AQI) during the Recent studies reported on short term exposure to air pollution and COVID-19 infection have found significant positive association of air pollutants with COVID-19 confirmed cases (Suhaimi et al., 2020;Zhu et al., 2020). Suhaimi et al. (2020) found significant positive association between COVID-19 cases and PM10, PM2.5, CO, NO2 and SO2 pollutants in Malaysia however, Zhu et al. (2020) observed positive association between COVID-19 cases and PM10, PM2.5, NO2 and O3 pollutants in China. Similar studies reported in China, Singapore, New York, Norway, Italy, United States, Spain, Turkey and Indonesia have analyzed the association between climate indicators (temperature, rainfall, humidity, air quality) and COVID-19 and found a significant association between them (Bashir et al., 2020;Gupta et al., 2020;Méndez-Arriaga, 2020;Menebo, 2020;Pani et al., 2020;Sahin, 2020;Tobias et al., 2020;Tosepu et al., 2020;Xu et al., 2020;Yao et al., 2020). Temperature which is considered as an important parameter in development, prevention and control of an epidemic showed different correlation in different countries (Tobías and Molina, 2020). A significant positive correlation of COVID-19 cases with temperature is reported over Singapore, New York, Norway, Turkey and Indonesia highlighting the importance of temperature in COVID-19 epidemic whereas a negative correlation is reported over Mexico while no correlation between COVID-19 cases and temperature is observed in China.
Some studies have been reported in India assessing the impact of COVID-19 lockdown on air quality but for limited number of cities and for short time period   April 2020)). The present study was planned to describe the changes in air pollutants levels during the complete lockdown period (24 th March-31 st May) in 39 different cities of India (including 10 Indian cities considered among the world's 20 most polluted cities) by using ground-based and satellite observations.
Mean concentrations of the pollutants for the lockdown period (24 th March-31 st May) in 2019 and 2020 were calculated to assess the variation between both periods having similar meteorology. Independent samples t-test between the mean concentration of all pollutants in 2019 and 2020 at 0.05 significance level was carried out using Statistical Package for Social Sciences (SPSS) software. Most of the cities showed statistical significant difference.

Air Quality Index (AQI)
Air Quality Index (AQI) is a numerical index used to indicate the air quality of a region. AQI ranges in value from 0-500 with greater AQI value suggesting deteriorated air quality and lower AQI (< 100) indicating satisfactory air quality in a region. In the present study, AQI values were derived from 24 h average PM10 and PM2.5, 8 h average CO and O3, 1 h average NO2 and SO2 levels during lockdown period in 2019 and 2020 using the U.S.EPA standard formula (U.S. EPA, 1999;Kumar and Goyal, 2011). The overall AQI considered for a city was the maximum AQI observed for that city.

Tropospheric NO2 Column
Ozone Monitoring Instrument (OMI) daily tropospheric nitrogen dioxide column (OMNO2d version 3) at 0.25° × 0.25° resolution is used in the study. OMI onboard Aura satellite detects the backscattered solar radiation (wavelength range of 270-500 nm) from the Earth and its atmosphere with a spatial resolution of 13 × 24 km (Krotkov et al., 2017).

AQI Values in Different Cities during the Lockdown Period
AQI values were determined for the lockdown period in 2019 and 2020 (24 th March-31 st May) (Fig. 1). In 2019, 56% of cities were in the 'Unhealthy' category (151-200) and only 16 and 28% cities lied in the 'Moderate' (51-100) and the 'Unhealthy for sensitive group' category (101-150) ( Table 1). In 2020, air quality of most of the cities improved with AQI of 36% of cities lying under the 'Moderate' category and 49% of cities in the 'Unhealthy for sensitive group' category. The largest drop in AQI values was observed in Patiala (AQI improved by 74). A relatively higher number of cities in Indo-Gangetic Plain showed lower AQI than cities in other regions of India. Among the 10 most polluted Indian cities AQI in 7 cities reduced to 101-150 range from 151-200 range. This suggests that air quality has improved significantly during the lockdown period in 2020. During 2019 PM2.5 was the dominant pollutant in most of the cities (30 cities), however with reduction in AQI in 2020 the dominant species shifted to O3 and NO2 in some of the cities. For cities lying in the central region (Bhopal, Ahmedabad, Gaya, Kolkata, Jaipur, Ghaziabad and Jind) the dominant pollutant shifted to O3 however in some cities (Mumbai, Ludhiana, Bengaluru, Nagpur) it shifted to NO2. In 2019 dominance of PM2.5 in most of the cities suggests influence on air quality by anthropogenic activities such as fossil fuel combustion in road transport, industries and power generation. With reduction in PM2.5 levels during lockdown period in 2020 the emergence of O3 as the dominant pollutant suggests influence on air quality by secondary pollutants in some of the cities.

Variation in Pollutants Levels during the Lockdown Period in 2019 and 2020
Further, average concentrations of pollutants in all 39 cities were compared during the lockdown period in 2019 and 2020 to determine the impact of the lockdown measures on air pollution levels (Fig. 2). Statistically significant differences in pollutants mean levels during the lockdown period in 2019 and 2020 were observed at 0.05 significance level. During the lockdown period in 2020, all cities showed drop in PM10 levels (except Guwahati and Jorapokhar) with an overall reduction of 44% as compared to 2019. PM10 levels decreased by 8% (Kalaburagi) to 58% (Patiala) in 2020 as compared to 2019. Among the 10 most polluted cities of India, Gurugram showed maximum reduction in PM10 levels (56%). Similar to PM10, PM2.5 levels also reduced during the lockdown period in 2020. Average PM2.5 levels over all the cities decreased from 63.6 to 39.6 µg m -3 (38% reduction). PM2.5 levels showed reduction in all cities ranging from 1% (Guwahati) to 57 % (Patiala) except at Mumbai and Patna. Top 10 most polluted cities showed reduction in the range 33 to 51%. Higher reduction observed in PM10 levels than PM2.5 can be due to the greater contribution of PM10 from anthropogenic activities (Klimont et al., 2017). In China, a reduction by 20-30% in PM2.5 levels during February 2020 (lockdown period) in comparison to monthly averages of February in 2017-2019 based on satellite observation was found (CAMS, 2020). Cities situated in the northern region (mainly in Uttar Pradesh) showed higher reduction in PM10 and PM2.5 levels. Uttar Pradesh contributes the highest share in PM2.5 emission as compared to other states of India (Purohit et al., 2019). The number of cities with daily 24 h mean PM10 and PM2.5 concentrations exceeding the National Ambient Air Quality Standards (NAAQS: PM10 > 100 µg m -3 and PM2.5 > 60 µg m -3 ) during the lockdown period in 2019 and 2020 were compared (NAAQS, 2009). 96% of cities in 2019 exceeded the NAAQS limit for PM10 while in 2020, only 75% of cities violated the limit. Similarly, PM2.5 levels in 2019 were exceeded by 80% of cities however, in 2020, only 53% of cities exceeded the limit during the lockdown period.
NO2 is a primary pollutant which is emitted mainly from vehicular emission and industrial activities (Sahu et al., 2012).  , 2020). To further substantiate the influence of lockdown measures on NO2 levels, satellite-retrieved tropospheric NO2 column was also analyzed for the lockdown period in 2019 and 2020 (Fig. 3) and a reduction in NO2 levels during 2020 was found. Among 39 cities considered in the present study, maximum reduction by 54% in tropospheric NO2 column over Patiala city (similar to ground observation) was observed during the lockdown period in 2020 as compared to 2019. NASA (National Aeronautics and Space Administration) and ESA (European Space Agency) using satellite observations have also reported reduction in NO2 emissions in Wuhan, Spain, Italy and USA by up to 30% during the lockdown period (Muhammad et al., 2020). Tropospheric O3 is a secondary air pollutant which is photo-chemically formed from its precursors CO, nitrogen oxides and volatile organic compounds (Kumari et al., 2018). O3 levels at a site not only depend on precursor's concentration but also on meteorological parameters. Sharma et al. (2020) found that meteorological parameters in India during the lockdown period in 2020 were similar to the analysis period in the previous years. This suggests that O3 levels were mainly influenced by precursor's concentration during the lockdown period in 2020. O3 levels in most of the cities lying in the northern and central India were observed to be increasing (1-27.7 ppb range) during the lockdown period in 2020. This may be attributed by a decrease in NOx levels in VOCs sensitive environment as cities in the northern and central regions are VOC-sensitive (Sharma et al., 2016). The other reasons may be reduction in NO titration of O3 and reduced particulate matter levels as observed by similar study during the lockdown period (Tobias et al., 2020). However, other cities showed reduction in O3 levels during the lockdown  period (range 2 to 89 %). Among the 10 most polluted cities, four cities showed higher levels in 2020 as compared to 2019 with highest increase observed at Jind (47%).
CO is one of the major air pollutants released from biomass burning and incomplete combustion of fossil fuels (Hollaway et al., 2000). Similar to NO2, CO levels also decreased (range 2-61%; overall mean reduction 28%) during the lockdown period in 2020. However, in some of the cities (Delhi, Bhopal, Agra, Greater Noida, Patna, Tirupati, Pune, Kolkata, Noida and Jind) increase in CO levels during 2020 in comparison to 2019 was observed. Reduction in CO levels may be attributed to the restrictions imposed on transportation facilities during the lockdown period in 2020.
SO2 also showed a mixed variation with reduction in most of the cities (range 3-71%; overall mean reduction 40%) and increase at some sites (Hyderabad, Kanpur, Varanasi, Jorapokhar, Thiruvananthapuram, Mumbai, Bengaluru, Ujjain, Gaya, Lucknow, Agra, Bhopal and Jind). In India, 82% of total SO2 emission originates from the industrial sector and thermal power plants (Purohit et al., 2019), however during the lockdown period in 2020 no restrictions were enforced on thermal power plants. Therefore, a decreasing trend in SO2 levels in all cities was not observed.

Ghaziabad: World's Most Polluted City
According to annual PM2.5 levels, Ghaziabad (annual PM2.5 mean 110.2 µg m -3 ) was found to be the world's most polluted city in 2019 (IQAir Report, 2019), therefore an indepth analysis of the impact of lockdown measures on pollutants levels was carried out there (Fig. 4). Ghaziabad is an industrial hub of India and comes in the part of National Capital Region (NCR) of Delhi. During lockdown period in 2020, average levels of PM10 (57%), PM2.5 (48%), CO (41%), SO2 (46%), O3 (6%) and NO2 (59%) showed reduction in comparison to 2019 (Table 3). A significant difference in all pollutants levels during the lockdown period in 2019 and 2020 at p < 0.05 was observed.
The time series plot of PM10, PM2.5, CO and NO2 was similar in I period (1 st February-23 rd March) in both years while O3 showed higher values in 2020 as compared to 2019. SO2 values in 2020 were comparatively lower than 2019 in I period. With the implementation of lockdown measures from 24 th March 2020, a sudden drop in all pollutants levels was observed. During II period (24 th March-31 st May), PM10, PM2.5, CO and NO2 levels in 2020 were lower than 2019 however, O3 and SO2 showed some comparable values. Fig. 5 show the average diurnal patterns of PM10, PM2.5, O3, CO, NO2 and SO2 before (1 st February-23 rd March) and during lockdown period (24 th March-31 st May) in 2019 and   8.2 ± 6.2 12.5 ± 10.7 5.2 ± 6 6.7 ± 8.7 2020 at Ghaziabad. The diurnal patterns of PM10, PM2.5, CO and NO2 were characterized by a bimodal pattern with morning and evening peaks. The morning peak of these pollutants was observed at around 07:00-10:00 h and the evening peak at around 22:00 h. These peaks correspond to peak traffic emission hours. The diurnal pattern of ozone was characterized by minimum value in early morning (07:00 h) and maximum value during afternoon (~14:00 h) due to photochemical formation. On comparing the diurnal patterns of PM10, PM2.5, CO and NO2 during I period (1 st February-23 rd March) in 2019 and 2020, similar patterns of PM10, PM2.5 and CO were observed however, NO2 showed comparatively lower values in 2020. Maximum difference observed in PM10, PM2.5, CO and NO2 diurnal values was 49.1 µg m -3 , 31.7 µg m -3 , 446.4 ppb and 17.4 ppb, respectively. During the II period (24 th March-31 st May), a very large variation in values of PM10, PM2.5, CO and NO2 values was observed. PM10, PM2.5, CO and NO2 diurnal values were 225.8 µg m -3 , 69.5 µg m -3 , 1094.6 ppb and 37.3 ppb, respectively lower in 2020 (during the lockdown period) than 2019. Another significant difference in the diurnal pattern of PM10, PM2.5, CO and NO2 during II period was the reduction in the amplitude of the pattern. The bimodal pattern of these pollutants was less distinct in 2020 II period as compared to other periods. The amplitudes of PM10, PM2.5, CO and NO2 were 61, 50, 68 and 77%, respectively lower in II period in 2020 as compared to 2019. This may be attributed to restrictions imposed on transportation as vehicular emission is an important factor responsible for the bimodal pattern of these pollutants. On the other hand, secondary pollutant O3 showed higher variation in 2020 during I period and similar pattern in both years during II period. The diurnal pattern of O3 depends on the rate of photochemical generation, meteorological parameters: temperature, solar radiation, relative humidity, wind speed, wind direction, planetary boundary layer height and rate of deposition (Kumari et al., 2020). Averaged diurnal variation of SO2 does not show a distinct pattern. Higher diurnal values of SO2 in 2019 during both periods than 2020 were observed.

Patiala: City with Maximum Reduction in Pollution Level
In the present study, Patiala city showed maximum reduction in pollutants levels during the lockdown period in 2020, therefore a detailed analysis of pollutants level was also carried out at Patiala. Patiala is an agriculture-based city situated in the northern Indo-Gangetic Plain. During the lockdown period in 2020, all pollutants showed statistical significant reduction. Average levels of PM10 (58%), PM2.5 (57%), CO (61%), SO2 (13%) and NO2 (79%) showed reduction in lockdown period in 2020 (II) however, O3 showed an increase by 2% in comparison to 2019 (II) ( Table 4). Mean pollutants levels at Patiala were comparatively lower than Ghaziabad during the study period however, comparatively higher reduction during the lockdown period was observed at Patiala.

CONCLUSION
Implementation of the lockdown measures as a preventive step to control the spread of COVID-19 resulted in restrictions on transportation and industrial activities. As a result air pollution levels dropped significantly. The present study provides detail of the impact of lockdown on air pollution in 39 different cities of India. The primary pollutant concentrations (PM10, PM2.5, CO and NO2) showed decreased levels in all cities however, secondary pollutant (O3) showed both increasing and decreasing trends. Overall 44, 38, 28, 42 and 40% reduction was observed in PM10, PM2.5, CO, NO2 and SO2 levels, respectively during the lockdown period in 2020 as compared to 2019. Reduced primary pollutants were mainly attributed to restrictions imposed on transportation and industrial activities as these activities are their primary sources. Increase in O3 levels may be due to reduced NO titration. Though the reduction observed in the pollutants levels during the lockdown period is expected to be short-lived, it provides evidence that widespread implementation of air pollution measures can result in immediate air quality benefits. Therefore, in worst air quality scenario restrictions on vehicles and industries can help in improving the air quality.