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Does Air Quality Influence the Spread of the SARS - COV2 in Metropolitan Cities? - A Case Study from Urban India

Souradip Basu1 , Rajdeep Das1 , Sohini Gupta2 and Sayak Ganguli3 *

DOI: http://dx.doi.org/10.12944/CWE.16.2.27

COVID 19 pandemic has gradually established itself as the worst pandemic in the last hundred years around the world after initial outbreak in China, including India. To prevent the spread of the infection the Government implemented lockdown measure initially from 24th March to 14th April, 2020 which was later extended to 3rd May, 2020. This lockdown imposed restrictions in human activities, vehicular movements and industrial functioning; resulting in reduced pollution level in the cities. This study was initiated with the objective to identify the change in the air quality of seven megacities in India and to determine any correlation between the active COVID cases with the air quality parameters. Air quality dataset of the most common parameters (PM2.5, PM10, SO2, NO2, NH3, CO and Ozone) along with air quality index for 70 stations of seven megacities (Delhi, Mumbai, Kolkata, Bengaluru, Hyderabad, Chennai and Chandigarh) were analysed. Comparison was made between AQI of pre lockdown and during lockdown periods. The results obtained indicate sufficient improvement in air quality during the period of the lockdown. For the next part of the study active COVID cases during the lockdown were compared to the air quality change of that period. A significant correlation between active COVID case and change in the air quality was observed for Delhi and Kolkata with 0.51 and 0.64 R2 values respectively. A positive correlation was also observed between air pollutant parameters and incidents of COVID cases in this study. Thus from the analysis it was identified that air quality index improved considerably as a result of the nationwide lockdown however, there was no significant impact of this improvement on the infection rate of the prevailing pandemic.

Air Pollutant Parameters; Air Quality Index; COVID-19; Lockdown

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Basu S, Das R, Gupta S, Ganguli S. Does Air Quality Influence the Spread of the SARS - COV2 in Metropolitan Cities? - A Case Study from Urban India. Curr World Environ 2021;16(2). DOI:http://dx.doi.org/10.12944/CWE.16.2.27

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Basu S, Das R, Gupta S, Ganguli S. Does Air Quality Influence the Spread of the SARS - COV2 in Metropolitan Cities? - A Case Study from Urban India. Curr World Environ 2021;16(2). Available From : https://bit.ly/3bNhcEO


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Article Publishing History

Received: 09-09-2020
Accepted: 12-05-2021
Reviewed by: Orcid Orcid Sneha Gautam
Second Review by: Orcid Orcid Sourav Poddar
Final Approval by: Dr. Sabu Joseph


Introduction

The symptoms of the current pandemic were first reported from Wuhan (China) in December 2019, when there was an abrupt increase in the number of fatal pneumonia cases. Gradually as the virus started spreading all around the world through International travel, it was identified to be a novel coronavirus and was nomenclatured as SARS-COV2 due to its homology with the earlier strain of the Severe Acute Respiratory Syndrome (SARS) virus that ravaged the world as an epidemic in the years 2002 and 2003. The disease was named as COVID-19.1-3 The impact of SARS-CoV-2 has been devastating around the world. So far 213 countries, more than 2.5 million people has been affected till date and more than 150,000 individuals have died.4 Initially the disease had spread in Wuhan and later on it spread globally within the first four months.5 Recent data of WHO identify over 2.8 million cases with over 201.000 victims as accessed on April 27, 2020.6-8 As of 6th July, globally the pandemic caused almost 11 million confirmed cases of infection and more than 2 million deaths.5 Most of the countries are trying to fight the spread of the virus by halting all social interactions. Social distancing parameters are being revised as continuous research is providing evidences of fomite, droplet and aerosol transmission in closed social environments without proper ventilation and continuous sanitization routines. In India the first confirm case was detected on January 30th, 2020 and the report of infection has rapidly increased from March 16th continuously. Government had declared the first nationwide lockdown for fourteen hours on March 22nd which was followed by 21 days of lockdown from 24th March. All the places of mass gatherings such as academic institutions, shopping malls, theatres, supermarkets and industries were declared to be closed across the country. This lockdown has mandated reduced transportation and industrial productivity which resulted into reduced automobile and industrial emissions.

As various countries had implemented lockdown measure, climate researchers had predicted that this implementation has the potential to positively impact global environment by cutting down greenhouse gas emission.9 Improved air quality was achieved as a result of reduced vehicular and industrial pollution due to the closure of majority of workshops and factories. A study showed that in France, Germany and Italy the NO2 and greenhouse gas has been reduced significantly after lockdown.10 Europe also reported reduction in air pollution after Government had ordered countrymen to stay at home for preventing the COVID outbreak which halted the factory & industrial work and automobile emissions that showed a drastic reduction in atmospheric NO2 and Particulate matter proportions.11 Studies also showed that the air pollution increased the risk of influenza infection.12 These trends of correlation also have been seen in SARS and MERS.13

The world is a polluted place in terms of air quality with 91% of our fellow citizens living in places with poor and polluted air. 14 Each year the global mortality rate due to lack of good quality air has significantly increased.15 The Global Disease Study showed that outdoor air pollution caused almost 4.2 million premature deaths in 2015.16 In this regard another report of WHO in the year 2016 indicated that in Europe, Asia and Africa air pollution contributed almost 8 % of total death.

Developing countries such as India and other countries around the world has increasingly sacrificed air quality control in favour of deforestation, industrialization and urbanization. This has resulted in severe health issues such as Chronic Obstructive Pulmonary Disease (COPD) increasing in number and in 2015 nearly one million deaths were corelated to particulate matter pollution.17 The World Health Organization and Central Pollution Control Board (CPCB) have established standard for ambient air quality, however major Indian cities have flouted the parameters and have consistently being enlisted in the top 20 most polluted cities of the world in the last few years.18-19

United States, Environmental Protection Agency (EPA), have identified several severe health and environmental hazards to be caused by “criteria pollutant”, such as carbon monoxide, lead, particulate air pollutants and variations in ground ozone level, which have resulted in smog, acid rain etc. All this are covered under the Clean Air Act of 1963. In India monitoring of air pollutant is performed by Central Pollution Control Board (CPCB) which jurisdiction of the Air (Prevention and Control of Pollution) Act, 1981. According to National Air Quality Monitoring Programme (NAMP), regular monitoring is performed for particulate matter (PM10), sulphur dioxide (SO2) and nitrogen dioxide (NO2) at all the monitoring stations. Real time monitoring of air quality is achieved by calculating the Air quality index (AQI) which takes into account various pollutants such as Pb, NH3, SO2, NO2, CO, O3, PM10 and PM2.5 Table 1). Particulate matter (PM), SO2, NO2, NH3, CO and O3 are considered as classical air pollutants to calculate air quality under the programme of NAMP. Few recent studies have reported the importance of air quality and its impact during the period of lockdown in India as a result of the prevalent pandemic. 20-23. In India, Delhi and other metropolitan cities have caused severe air pollution in last few years which was very clear from the recorded air quality previously.24

Table 1: List of Air Pollutants and Their Sources.

Serial Number

Pollutant

Source   

Remarks/Source

1

PM2.5 and PM10

Primary sources are incomplete combustion, automobile emissions, dust and Cooking exhaust. Chemical reactions in the atmosphere also act as a secondary source.

https://doi.org/10.1016/j.atmosenv.2013.01.032 25

2

NO2

Outdoor source- Traffic emissions. Indoor source- (Appliances used for cooking),

(Gas, Oil, Wood etc).

https://www.ncbi.nlm.nih.gov/books/NBK138707/ 26

3

NH3

 Principal source- Ammonia based fertilizer used in agriculture and livestock maintenance.

https://doi.org/10.1007/s11356-013-2051-9 27

4

SO2

Principal source- Fossil fuel burning in thermal power plant and other industry.

https://www.epa.gov/so2-pollution/sulfur-dioxide-basics 28

5

CO

Principal source- Vehicular emissions and burning of fossil fuel.

https://www.epa.gov/co-pollution/basic-information-about-carbon-monoxide-co-outdoor-air-pollution 29

6

Ozone

Sunlight mediated formation of ozone (ground level) by reaction between nitrogen oxide and emitted volatile organic compounds from various urban and industrial sources.

https://www.epa.gov/ground-level-ozone-pollution/ground-level-ozone-basics 30

 


This work focused on the change in AQI and ambient air pollutants during lockdown in selected cities to construct a correlation between the air quality and outbreak of the COVID infection in search of the impact of air pollutants on viral invasion.

Materials and Methods

Study Design


Seven metropolitan cities viz Delhi, Mumbai, Kolkata, Bengaluru, Hyderabad, Chennai (Fig. 1) and over 74 monitoring stations were sampled in this study for a period of three months.

Figure 1: Data Collection Sites (Air Quality Parameter Measuring Stations in Seven Megacities)

Click here to view Figure



The span of 1st February to 20th March was chosen as there was no lockdown imposed by the government and the data could provide clear picture of air pollution in city specific manner. This time span was designated as the pre lockdown period for this analysis. The Government had ordered total lockdown from 22nd March to the end of April, when there was significantly restricted emission of industrial and vehicular pollution. Later in the month of May (Unlock1) and June (Unlock2) there were gradual relaxation of the lockdown norm declared by the government. Thus for this analysis, data up to the month of April was considered appropriate for the post lockdown period (Table 2).

Table 2: Description of Datasets and Periods of Pre and Post Lockdown Considered in the Study.

Serial Number

Nomenclature

Period

Explanation

1

Pre-Lockdown

February-Mid March

Before the enforcement of complete lockdown.

2

Post-Lockdown

Mid-March-April

During the period of complete lockdown without any relaxation activity

 


Data Collection

Data was collected from The Central Pollution Control Board (CPCB) database (https://app.cpcbccr.com/AQI_India) which is under National Air Quality Monitoring programme (NAMP). Pollutants are monitored for a period of twenty-four hour (gaseous pollutant at 4-hour interval and particulate matter at 8-hour interval). This is done twice a week and 104 observations are achieved for a year.31 This study monitored certain pollutants namely particulate matter (PM2.5 & PM10), Sulphur dioxide (SO2), Nitrogen dioxide (NO2), Ammonia (NH3), Carbon monoxide (CO) and Ozone from the month of February to April to evaluate the alterations in air quality. AQI values were also taken into consideration city wise keeping in mind pre-lockdown phase and implemented lockdown phase. Finally, we accumulated all the data (average values with reference to observation days) of three months (Table 3).

Table 3: City Specific AQI Average of Respective Stations.

­Cities

Observation Sites

Prelockdown AQI

Postlockdown AQI

DELHI

Alipur

190.214

103.5

Anand Vihar

218.857

104

Ashok Vihar

212.857

99.4

Aya Nagar

136.785

70.1

Bawana

243.785

122.4

CRRI Mathura Road

190.642

90.3

Dr.Karni Singh Shooting Range

232.214

102.9

DTU

198.285

83.7

Dwarka-Sector 8

242.571

95.8

IGI Airport(T3) Airport

166.285

74.3

IHBAS,Dilshad Garden

184.285

37.5

ITO

216.428

157.8

Jahangirpuri

223.857

108.9

Jawaharlal Nehru Stadium

184.928

78.7

Lodhi Road

149.714

86.1

Major Dhyan Chand National Stadium

189.384

79.5

Mandir Marg

171.785

98

Mundka

233.714

122.2

NSIT Dwarka

224

81.9

Najafgarh

199.071

122.3

Narela

214

130.2

Nehru Nagar

221

87.1

North Campus,DU

167.785

78.9

Okhla Phase-2

202.428

88

Patparganj

173.071

77.5

Punjabi Bagh

201.214

92.4

R K Puram

166.571

80

Rohini

239.857

109.3

Shadipur

160.714

56.5

Sirifort

224.142

82.2

Sonia Vihar

194

87.2

Sri Aurobindo Marg

170.214

79.6

Vivek Vihar

207

89.4

Wazirpur

239.428

98.4

MUMBAI

Bandra - MPCB

118.785

63.9

Borivali East

90.153

65.545

Chatrapati Shivaji international airport

163.571

62.5

Colaba- MPCB

164.928

106.7

Kurla

164.714

92.9

Powai

109.5

72.9

Sion- MPCB

186.142

81.4

Vasai West

124.857

54.5

Worli

138.285

68

KOLKATA

Ballygunge

207

71.6

Bidhannagar

167.857

81.7

Fort william

146.428

80.8

Jadavpur

147.785

66.3

Rabindrabharati university

196.642

77.5

Rabindra sarobar

134.785

70.3

Victoria memorial

185.5

94.6

BENGALURU

BTM Layout

59.846

53.5

BWSSB Kadabesanahalli

104.928

48

Bapuji Nagar

78.571

47

City Railway Station

118.857

85.9

Hebbal

83.214

53.3

Hombegowda Nagar

84.142

63.9

Jayanagar 5th Block

87.5

44.7

Peenya

77

56.5

Sanegurava Halli

71.571

43.8

Silk Board

91.142

48.6

HYDERABAD

Bollaram industrial area, TSPCB

94

60.3

Central university-TSPCB

85.928

58

ICRI SAT, Patancheru

88.142

62.6

IDA, Pashamylaram

91

64.181

Sanath nagar

83.357

53.3

Zoo-Park

115.214

77

CHENNAI

Alandur Bus Depot

68.071

32.7

Manali - CPCB

103

51.2

Velachery Res.Area- CPCB

55.142

43.1

CHANDIGARH

Sector-25- CPCC

71.285

39.4

 


Data Analysis

The study period i.e., overall a tenure of three months was catalogued into two phases viz pre lockdown phase (February-Mid March) and lockdown phase (Late March-April). Due to improper data sampling of the automated air quality monitoring, two spots from Delhi were removed from the analysis due to deficiency in data. The changes in air quality due to lack of vehicular emissions & mass gatherings was evaluated using a descriptive analysis to provide an overview of AQI values & ambient air pollutants among the seven cities of the study.

A linear regression model was constructed to understand the correlation between COVID incidence and AQI values along with all the pollutant parameters considered.  In the analysis COVID-19 incidence cases were considered as a dependent variable and AQI values of seven cities along with seven ambient air pollutant parameters were considered as an independent variable. R2 value for each regression was checked for statistical significance. Pre-lockdown COVID-19 cases were not considered in this regression analysis due to data deficiency. Pre and post-lockdown air quality index parameters were represented through two heat maps respectively.

Results

In this study, meticulous information of AQI values & ambient air pollutants among seven metro cities were enlisted in Table 4; (Figure 2). Furthermore, the entire data of COVID-19 incidence during the lockdown period were collected which included confirmed, active and recovered cases (Figure 3). From the column graph (Figure 4) and heat maps (Figure 5) of AQI and other air pollutant parameters, it was observed that in the post-lockdown period, all the values decreased with few exceptions. For all the cities, AQI summed average value was observed to decrease during lockdown, among which Delhi, Mumbai and Kolkata was most significant. Delhi showed significant rise in AQI values 6789.571 ± 675.834 & 3156 ± 217.198; whereas Chandigarh exhibited lower AQI values 71.825 ± 5.032 & 39.4 ± 2.914 from pre to post lockdown. Mumbai, Kolkata, Bengaluru, and Hyderabad also showed moderate AQI values but Chennai showed apparently lowest values than these cities respectively. Among all the ambient air pollutants PM2.5 & PM10 showed a significant decrease along seven cities during the study period and Chennai had no PM10 value observed in either of periods. NH3 was increased marginally (10.3571 ± 3.002 & 11.7 ± 1.159) in Chennai during post-lockdown. SO2 increased in Mumbai significantly (93.714 ± 18.751 & 122.9 ± 26.455) and marginally in Chandigarh (12.214 ± 2.887 & 13.8 ± 2.149). The level of ozone increased during post lockdown phase in Delhi (682.643 ± 306.626 & 1006.6 ± 283.439), Hyderabad (149.071 ± 29.849 & 156.4 ± 25.426) and Chandigarh (21.285 ± 5.483 & 34.3 ± 11.155).

Table 4: Mean Value of City Specific AQI and Ambient Air Pollutant Parameters. (4A to 4D).

4A:

VARIABLES

DELHI

MUMBAI

 

Pre lockdown

Post lockdown

Pre lockdown

Post lockdown

 

MEAN

SD

MEAN

SD

MEAN

SD

MEAN

SD

AQI

6790

2529

3156

686.8

1258

329.7

670.2

110.9

PM2.5

6499

2635

2498

609.3

935.4

278.7

485.3

171

PM10

5144

1578

2596

600.3

1055

211.8

774.3

146.1

NO2

1925

601

808.5

128.8

444.5

77.41

214.4

84.24

NH3

234.6

28.11

182

17.26

39.79

7.007

28.5

15.31

SO2

489.3

93.2

466.8

71.99

93.71

18.75

122.9

26.46

CO

1679

545.6

1199

173.5

324.9

69.28

232.2

43

OZONE

682.6

306.6

1007

283.4

438.1

164.1

290.4

58.68

 

4B:

VARIABLES

KOLKATA

BENGALURU

 

Pre lockdown

Post lockdown

Pre lockdown

Post lockdown

 

MEAN

SD

MEAN

SD

MEAN

SD

MEAN

SD

AQI

1186

365.260

542.8

180.443

852.5

110.109

545.2

77.516

PM2.5

1083.5

404.702

316.9

163.753

541.214

122.415

319.2

69.183

PM10

927.357

251.956

362.4

138.808

607.857

70.179

351.9

71.894

NO2

494.5

221.955

102.6

28.721

377.071

58.539

152.1

22.961

NH3

48.214

7.495

27.1

4.458

19.142

1.875

17.9

1.791

SO2

120.571

34.892

72.6

16.146

83.642

13.112

74.2

5.050

CO

178.071

35.508

137.4

26.692

488.928

32.824

384.4

39.786

OZONE

647.642

172.138

503.7

147.897

257.785

48.508

210.3

38.294

 


4C:

 

HYDERABAD

CHENNAI

 

Pre lockdown

Post lockdown

Pre lockdown

Post lockdown

 

MEAN

SD

MEAN

SD

MEAN

SD

MEAN

SD

AQI

556.642

119.479

374.1

59.120

226.21

43.24

127

22.568

PM2.5

451.285

133.985

317.8

75.989

211.857

48.22

87.7

44.444

PM10

454.714

71.382

26

71.493

0

0

0

0

NO2

247.428

46.699

157.1

31.858

49.214

16.25

30

13.182

NH3

24.5

12.100

17.6

4.948

10.357

3.002

11.7

1.159

SO2

46.714

14.274

34.8

8.702

42.857

23.131

18.4

4.993

CO

152.428

28.608

140

26.679

114.074

24.972

98.9

13.008

OZONE

149.071

29.849

156.4

25.426

93.357

20.337

66.1

16.616



4D:

VARIABLES

CHANDIGARH

 

Pre lockdown

Post lockdown

 

MEAN

SD

MEAN

SD

AQI

71.285

18.828

39.4

9.215

PM2.5

51.214

22.617

24.2

5.533

PM10

71.285

18.828

38

10.360

NO2

19.214

7.454

14.2

1.873

NH3

12.57

6.284

9.4

1.897

SO2

12.214

2.887

13.8

2.149

CO

25.785

5.451

19.7

4.321

OZONE

21.285

5.483

34.3

11.155

 
 
Figure 2: Comparative Total Air Quality Index Values for the Seven Cities Day Wise (Period of Study).

Click here to view Figure

 

Figure 3: Comparative Representation of the Total Number of Affected, Recovered and Active Cases Per City as Described in the Text for the Period of Study.

Click here to view Figure

 

Figure 4: Mean Values of AQI (a), PM2.5 (b), PM10 (c), NO2 (d), NH3 (e), SO2 (f), CO (g) and Ozone (h). Green and Blue Column Representing Pre and Post Lockdown Phase Respectively.

Click here to view Figure

 

Figure 5: Heat Map Representation of AQI and Ambient Air Quality Parameters During (a) Pre Lockdown and (b) Post Lockdown (During Lockdown Phase) Respectively.

Click here to view Figure



The data exhibited variation in relationship between the AQI values & Post lockdown COVID-19 incidences among the enlisted cities. Kolkata & Delhi exhibited moderate significance (R2=0.64 & 0.51, respectively) at the time of this study, whereas the other cities under consideration displayed weak association in this context (Table 5). Statistically the R2 value ranging from 0.3-0.5 indicated weaker correlation, from 0.5-0.7 indicated moderate effect and above 0.7 was considered to have a strong correlation between the variables.32 Observations from this study depicted that AQI along with ambient air pollutants also manifested different effects on COVID-19 incidences. Amidst all air pollutants in Delhi, PM10 & Ozone had moderate effect; in Mumbai, PM10 & ozone; in Kolkata, SO2, CO & Ozone; in Bengaluru, NO2 & CO had higher association with COVID -19 cases, as inferred from the R2 values tabulated in (Table 5) & graphical representations from (Figure 6).

Table 5: R2 Values Obtained from the Regression Analysis of COVID Incidence with AQI and other Ambient Air Pollutants.

Parameters

R2 Value

 

Delhi

Mumbai

Kolkata

Bengaluru

Hyderabad

Chennai

Chandigarh

AQI

0.518

0.1981

0.6436

0.0156

0.1207

0.0211

0.1101

PM2.5

0.189

0.4626

0.5647

0.001

0.1169

0.0185

0.0005

PM10

0.501

0.9989

0.5936

0.7064

0.0092

0

0.1404

NO2

0.009

0.6867

0.4198

0.8821

0.0957

0.1351

0.063

NH3

0.011

0.0176

0.6447

0.1143

0.1608

0.0121

0.2161

SO2

0.295

0.0453

0.9996

0.0018

0.1286

0

0.7662

CO

0.01

0.3164

1

0.9996

0.1523

0.0042

0.1375

OZONE

0.688

0.9998

1

0.1609

0.4707

0.084

0.0103

 

 

Figure 6.A:

Click here to view Figure

 

Figure 6.B:

Click here to view Figure

 

Figure 6.C:

Click here to view Figure

 

Figure 6.D:

Click here to view Figure

 

Figure 6.E:

Click here to view Figure

 

Figure 6.F:

Click here to view Figure

 

Figure 6.G:

Click here to view Figure



Figure 6: Graphical Representation of Regression Analysis Performed Between COVID Incidence and Air Quality Parameters of Seven Cities. (Fig. 6.A: Delhi; Fig. 6.B: Mumbai; Fig. 6.C: Kolkata; Fig. 6.D: Bengaluru; Fig. 6.E: Hyderabad; Fig. 6.F: Chennai; Fig. 6.G: Chandigarh).

Discussion


From this study it was noticed that the post lockdown period caused a significant reduction of the AQI values of each city by parallel enhancement of air quality due to scarce level of vehicular and industrial air pollutants.

From the heat map, it was observed Chandigarh was independent and out of the cluster of other cities, in the pre lockdown phase. Having only one AQI measuring station, Chandigarh had the least value of all air pollutants except NH3
(Figure 4). Vehicular and industrial pollution emit PM, SO2, NO2 and CO but not NH3, which projected that Chandigarh has different pollution status than the other cities considered in this study. Chandigarh has lesser number of industries (mostly packaging or paper making industries) that emit lesser pollutants which probably contribute towards its position in the heat map.

In the post lockdown phase Delhi, Mumbai, Bengaluru and Hyderabad were in a single cluster as they probably have a similar emission status. This can be justified from the similar industrial and vehicular pollution standard near the air quality measuring stations. Column graphs depicted that Delhi, Mumbai and Bengaluru have significantly higher SO2 and CO level compared to other cities in either of the phase due to the presence of higher number of industries in them
(Figure 4). SO2 and CO were the primary gas emitted from the industries and NO2, PM10 and PM2.5 were principal emission of automobiles (Table 1), which probably ascertain a constant level of air pollutants in the cities clustered together. As Kolkata, Chennai and Chandigarh have very less industries located in the city and lockdown norms restricted the automobile emissions, these cities were clustered separately in the heat map.

There has been previous reports of corelation between air pollution and virus mediated respiratory disorder.33
A study also highlighted considerable potency in enhancement of virulence and infection rate of influenza with the effect of air quality parameters.34 Air pollutants such as PM2.5 and PM10, carbon monoxide, sulphur dioxide, ozone and nitrogen dioxide cause severe respiratory tract infection by enhancing susceptibility.35 Higher percentage of air pollutant may promote greater persistence of air borne virus particles.36 It has the potential to favour a passive diffusion of SARS-CoV-2, in addition to the direct diffusion of the viral particles from individual to individual.37 People living in zones with high concentrations of air pollutants are more susceptible to respiratory diseases.38 In this study, only Kolkata and Delhi showed significant relationship of AQI with COVID-19 incidence with a statistically significant R2 value. Moreover, these two cities also have a significantly higher level of pollution in both the period. Observation are in concurrence to previous studies that enhanced air pollutants in the air might have been a reason for the higher confirmed cases of the viral infection. Chennai and Chandigarh are showing lowest AQI in either of the period which justifies its significantly low confirmed cases of infection as compared to the other cities.

Particulate matters are known for its suspension form in the air and invasion of the respiratory barriers to penetrate the pulmonary tract mucosal layers and directly get in contact with respiratory surfactant causing health hazards. PM2.5 and PM10 particles are having less than 2.5 and 10 micrometres of diameter respectively. PM2.5 and PM10 are the most important air pollutants in correlation to viral particle transmission. Northern Regions of Italy, which were most affected by COVID-19, had significantly higher PM10 and PM2.5 level.37 Study also showed that the viral infection has increased in the presence of abundant particulate matter such as PM10 in air.39 In our study, Delhi, Mumbai, Kolkata and Bengaluru have significantly higher values of PM2.5 and PM10 and also the R2 values suggesting a strong relationship with confirmed COVID cases. This supports the justification that higher particulate matter in air in the locations mentioned has contributed towards higher viral transmission. Moreover, this condition is significantly lesser adverse in other cities due to relatively lesser PM2.5 than PM10.

Increased O3 level has been correlated with reduction of NO2 emissions.40 These results are coherently supported by the recent findings for Milan in Italy41 and for Wuhan area in China.42-44 Experiment showed that the drastic reductions in NO2 and other air pollutants during Milan’s COVID-19 lockdown led to substantial increase in ground level Ozone (O3).41 As a result, atmospheric oxidizing potential was elevated which escalated formation of  secondary aerosols having negative impact on human respiratory tract along with an increase in COVID-19 confirmed cases.41 This trend was also observed in case of Indian metropolitans where NO2 and SO2 levels have decreased in most of the cities with a few insignificant exceptions along with the significant rise in ground level of Ozone after lock-down.23,45-46 In Delhi this observation led to a noticeable impact in the confirmed COVID cases throughout the post-lockdown phase.

In conclusion, lockdown provided a significantly good impact on the improvement of overall air quality of the cities. On the other hand, it was found that the increase of particular pollutants had an impact on the spread of viral infection. Higher confirmed cases in major cities like Delhi and Mumbai could have been due to higher air pollutants present in the air and in the cities like Chandigarh and Chennai, comparatively lower pollutant levels justified the lower rate of confirmed cases of infection.


Conflict of Interest

The authors confirm that there are no known conflicts of interest associated with this publication and there has been no significant financial support for this work that could have influenced its outcome.

Acknowledgement

The authors acknowledge the authorities of their respective institutions for providing the necessary resources and encouragement to conduct this work during the lockdown period.

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