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[ Research Article ] |
Asian Journal of Atmospheric Environment - Vol. 14, No. 4 |
Abbreviation: Asian J. Atmos. Environ |
ISSN: 1976-6912
(Print)
2287-1160
(Online)
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Print publication date 31 Dec 2020
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Received 28 May 2020
Revised 11 Aug 2020
Accepted 08 Sep 2020
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DOI: https://doi.org/10.5572/ajae.2020.14.4.378
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COVID-19 Lockdown: Impact on Air Quality of Three Metro Cities in India |
Ashu Chhikara*
; Naveen Kumar1)
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Government PG College, Naraingarh, Ambala, India
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1)Airports Authority of India, New Delhi, India
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Correspondence to : * Tel: +91-9466888566 E-mail: sangwanashu8@gmail.com
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Copyright © 2020 by Asian Association for Atmospheric Environment
This is an open-access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/4.0/), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. |
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Abstract |
Covid-19 health pandemic resulted in nationwide lockdown in India. With the closure of almost everything from educational institutions to industries less no of vehicles came out on roads. As the vehicular emission is one of the reasons of higher rate of pollution in metro cities so this step of lockdown has shown positive impact on environment with decrease in pollution level. Despite various attempts made by the government over the last few years nothing proved fruitful but this forced decision has shown some great results. We have analysed the changes in the quality of air during lockdown period from 25th March to 30th April, 2020 over pre-lockdown period from 1st March to 24th March, 2020 of Delhi, Mumbai and Kolkata which are the polluted cities of India. Seven air pollutants PM2.5, PM10, O3, CO, SO2, NH3, and NO2 have been used to calculate Air Quality Index (AQI) to see the changes in quality of air. The results showed that due to lockdown concentration of various pollutants PM2.5, PM10 and NO2 has decreased significantly. There is a heavy reduction of 42.27%, 69.28% and 74.80% in concentration of NO2 in Delhi, Mumbai and Kolkata respectively. It has been deduced from change in AQI values that there is a significant improvement in quality of air during lockdown in Delhi, Mumbai and Kolkata.
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Keywords: Coronavirus, Air Quality Index (AQI), Pollutants, Concentration, Improvement
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1. INTRODUCTION
In second week of December, 2019 large numbers of viral infection cases were reported in Wuhan city of China (Lu et al., 2020). WHO (World Health Organization) was informed about these cases on 31st December, 2019 and coronavirus was identified. Some of the common symptoms which found in coronavirus patients were fever, cough and breathing problem (Tosepu et al., 2020). On 10th January, 2020, WHO issued technical guidelines to all countries for detecting, testing and advisory for managing potential cases. But all these efforts went in vain as first case outside China was reported in Jan, 2020 in Thailand (WHO, 2020a) and virus kept on spreading across the countries, covering the whole world. On 11th Feb, 2020 WHO declared the disease as Pandemic and named it COVID-19 (The New York Times, 2020). As per the report of WHO dated 15th May, 2020, a total of 4338658 confirmed cases and 297119 deaths have been reported (WHO, 2020b). Even the developed countries like USA, UK, France having good healthcare infrastructure are unable to tackle the spread of COVID-19 and have to deal with unwanted crisis like shortage of ventilators, beds, PPE Kit, masks (Banerjee, 2020).
In India, first case of coronavirus was reported on 30th Jan 2020 in Kerala with travel history to China (Rawat, 2020). In view of increase in cases in China and other countries reporting cases with travel history to China, the travel advisory was issued for Indians to refrain from travelling to China. Even all the existing visas of foreign nationals were cancelled who were travelling from China on 5th Feb 2020 (Ministry of Health & Family Welfare, 2020a). Initially Government started spreading awareness about the disease through media, giving advisory to wash hand regularly, to use sanitizers, mask but these instructions were not enough to control spread of virus. Then to counter the uncontrollable spread some strict measures were taken. On 13th March 2020, all the existing visas of any nationals were cancelled except for some special categories (Ministry of Health & Family Welfare, 2020b). On 16th March Government of India ordered that all the educational institutions, malls, theatre, gym to be shut and any other mass gathering including any religious and social gathering was also prohibited. The Central Government also advised all the states and Union Territories to sanitise Public transport vehicles and terminals. As per the report of Indian council of Medical Research (ICMR) the total number of positive cases on 22nd March rose to 236 (The Economic Times, 2020). As a counteractive measure Janta curfew was declared for 22nd March. As many countries in the world were badly affected by COVID-19 and started lockdown from few days to few months depending upon the situation of COVID-19 (Chakraborty and Maity, 2020). So, learning from the dilemma faced by these countries the Indian government took proactive step and implemented the lockdown on 25th March when the number of cases was only in hundreds. The step of lockdown positively affected the whole world including India in terms of quality of air. Sicard et al. (2020) conducted research in some of the European countries with focus on Ozone (O3) and found that due to lockdown there is decrease in air pollution. Similar results of improvement in quality of air were observed in various countries like USA, China, France, Spain and Italy and there was reduction of NO2 upto 20 to 30% due to restriction on transportation (Wang et al., 2020; Muhammad et al., 2020).
2. LOCKDOWN AND ITS IMPACT
Government implemented lockdown so that they have sufficient time to build healthcare infrastructure and policies to face this circumstance in a better way (The lancet, 2020). On one hand lockdown resulted in negative impact on economy, shutting down of industries, and drastic collapse of almost all sectors (Kumar et al., 2020) while on the other hand lockdown has shown some positive result in the form of giving plenty time to the people to spend with their family, reduction in air pollution, clean rivers due to stoppage of industrial waste. Air pollution has been one of the major problems faced by the government in India. Some of the Indian cities like Delhi, Mumbai, Bangalore are always among most polluted cities of world and has been responsible for changes in our ecosystem (Nasir et al., 2016). Various policies have been framed time to time to reduce pollution like odd-even scheme for vehicles in Delhi, ban on entry of heavy vehicle, stoppage of stubble burning (Chawala and Sandhu, 2020) but did not get satisfactory result. Air quality in these cities has mostly surpassed the ambient air quality standards recommended by Central Pollution Control Board (CPCB) (Mukherjee and Agrawal, 2018). However, lockdown has impacted the quality of air in a big way, making it clean and breathable; due to closure of industries, transportation there is a drastic change in air quality.
3. EVOLUTION OF AQI
With the technological advancement there are a lot of instruments available to provide data on quality of ambient air. But this data is of no use to a common man who is more interested in knowing the status of air as good or bad instead of any data. So, to address the problem index of air quality was introduced and being used effectively in most of the develop countries from last few decades (USEPA, 2014, 1976; Shenfeld, 1970). An AQI may be defined as a scheme which transforms the concentration of all the pollutants of air into a number which depicts the quality of air. In past AQI was introduced in India by using five parameters i.e Sulphur dioxide (SO2), Carbon monoxide (CO), PM10 (Particulate matter with diameter of 10 microns or less), Suspended Particulate Matter (SPM), and Nitrogen oxide (NO2) to give AQI based on maximum sub-index of these five parameters (Sharma et al., 2001). But due to lack of availability of data of pollutants other than SPM, this AQI was dominated by sub-index of SPM. Then Indian Institute of Tropical Meteorology (IITM) Pune came up with an AQI which used sub-index for PM2.5, PM10, NO2, O3 (Ozone) and CO (Beig et al., 2010). In 2009, CPCB revised air quality standards for twelve parameters (PM2.5 (Particulate matter with diameter of 2.5 microns or less), PM10, NO2, O3, SO2, CO, NH3 (Ammonia), Pb (Lead), Ni (Nickel), As (Arsenic), Benzo(a)pyrene, and Benzene). So, there was a need to develop AQI considering this entire standard (NAQI Report, 2015). Another problem was that various agencies proposed AQI scheme which were using different parameters therefore giving confusing air quality output. For e.g. one scheme of AQI giving quality of air as good while other scheme as poor for the same ambient air. So, to overcome this there was a need of one scheme of AQI for the whole nation. That is where National Air Quality Index (NAQI) came into picture. CPCB awarded the work to Indian Institute of Technology, Kanpur to develop NAQI.
3. 1 National Air Quality Index (NAQI) in India
This was the initiative by Ministry of Environment, Forest and Climate Change under Swachh Bharat Mission with IIT Kanpur to develop a uniform AQI to present a clear picture of status of quality of air in various cities of India (PIB, 2014). It is an effective index which transforms complex data on various pollutants of air into a single number to describe the air quality. This index categorised the quality of air into six ways i.e. good, satisfactory, moderately polluted, poor, very poor and severe depending upon the concentration of pollutants and their health breakpoints as shown in Table 1. Each category is expressed in different colour code and each category has some associated health impacts as per Table 2. In this scheme sub-indices of all the eight pollutants (PM2.5, PM10, O3, CO, SO2, NH3, NO2 and Pb) are calculated at the monitoring location using 24-hourly average concentration of each pollutant (8-hourly in case of CO and O3) and health breakpoint concentration range. The AQI of a location is given by the worst sub index. The lower the AQI value, the better is the quality of air. It may be possible that all the pollutants may not be monitored at all the locations. So, AQI can be calculated using three pollutants out of which one must be either PM2.5 or PM10 (CPCB, 2020a).
Table 1.
Various AQI categories, pollutants and their health breakpoints.
AQI category
(Range) |
PM10
24-hr
(μg/m3) |
PM2.5
24-hr
(μg/m3) |
NO2
24-hr
(μg/m3) |
O3
8-hr
(μg/m3) |
CO
8-hr
(mg/m3) |
SO2
24-hr
(μg/m3) |
NH3
24-hr
(μg/m3) |
Pb
24-hr
(μg/m3) |
Good
(0-50) |
0-50 |
0-30 |
0-40 |
0-50 |
0-1.0 |
0-40 |
0-200 |
0-0.5 |
Satisfactory
(51-100) |
51-100 |
31-60 |
41-80 |
51-100 |
1.1-2.0 |
41-80 |
201-400 |
0.5–1.0 |
Moderately polluted
(101-200) |
101-250 |
61-90 |
81-180 |
101-168 |
2.1-10 |
81-380 |
401-800 |
1.1-2.0 |
Poor
(201-300) |
251-350 |
91-120 |
181-280 |
169-208 |
10-17 |
381-800 |
801-1200 |
2.1-3.0 |
Very poor
(301-400) |
351-430 |
121-250 |
281-400 |
209-748* |
17-34 |
801-1600 |
1200-1800 |
3.1-3.5 |
Severe
(401-500) |
430+ |
250+ |
400+ |
748+* |
34+ |
1600+ |
1800+ |
3.5+ |
* One hourly monitoring (for mathematical calculations only)
(PM2.5 stands for Particulate Matter of diameter of less than or equal to 2.5 micrometer, PM10 stands for Particulate Matter of diameter of less than or equal to10 micrometer, NO2 stands for Nitrogen oxide, NH3 stands for Ammonia, SO2 stands for Sulphur dioxide, CO stands for Carbon monoxide)
Table 2.
AQI and their associated health impacts.
AQI |
Colour coding |
Associated health impacts |
Good
(0-50) |
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Minimum Impact on health |
Satisfactory
(51-100) |
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Minor breathing discomfort to sensitive people |
Moderately polluted
(101-200) |
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May cause breathing discomfort to people with lung disease, and discomfort to people with heart disease, children and older adults |
Poor
(201-300) |
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Breathing discomfort to people on prolonged exposure |
Very Poor
(301-400) |
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May cause respiratory illness to the people on prolonged exposure.
More dangerous to people with lung and heart diseases. |
Severe
(401-500) |
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May cause respiratory illness even to healthy people, and serious health impacts on people with lung/heart disease. |
Source - (app.cpcbccr.com/AQI-India)
4. METHODS
4. 1 Study Area
To analyse the quality of air of pre-lockdown period from 1st March to 24th March and during lockdown period from 25th March to 30th April, required data of concentration of seven pollutants is collected for three cities Delhi (data taken for ITO Station), Mumbai (data taken for Chhatrapati Shivaji Intl. Airport T2 Terminal) and Kolkata (data taken for Victoria) from 1st March to 30th April, 2020. Delhi covers an area of 1,484 square kilometres it is the second-highest in India after Mumbai. Being capital of India, it is well connected with metro, railways, international airport and act as a hub to connect to all the places in northern India. Delhi also has many tourist spots like various historical monuments, famous temples attracting tourist from all over India. Delhi and Mumbai also have different types of industries like textile, electronics, leather and pharmaceutical industries (Aggarwal and Toshniwal, 2019). Mumbai is known as the financial centre of India. It is the house of biggest film industry in India. It boasts of major sea-ports of the country. All these factors are responsible for the pollution in Delhi and Mumbai. Similarly, in Kolkata there are a large number of industries like textile, chemical, heavy engineering and ship building which contribute to the pollution of the city.
One thing that is common in all the three cities is their high population density. So, the major source of pollution is the vehicular emission and emission from industries like power plants catering the requirements of huge population. The level of pollution in India is such that in 2015 approximately one million people died due to ambient particulate matter pollution (Guo et al., 2017).
4. 2 Data Collection
The 24-hourly average concentration of seven air pollutants PM2.5, PM10, nitrogen oxide (NO2), ammonia (NH3), sulphur dioxide (SO2) and eight-hourly concentration of two pollutants ozone (O3) and carbon monoxide (CO) are taken from website of Central Pollution Control Board to calculate AQI to check the quality of air of these three cities (CPCB, 2020b).
4. 3 Data Analysis
AQI Calculator given on CPCB website (www.cpcb.nic.in) has been used to calculate AQI values of these cities for these two months. The concentration of pollutants has been plotted on the graph to show the impact on quality of air due to lockdown. The concentration of various Pollutants in three cities (Delhi, Mumbai and Kolkata) has been averaged out for pre-lockdown and lockdown period separately to show the percentage variation in pollutants during lockdown period over pre-lockdown.
5. RESULTS AND DISCUSSION
Fig. 1 shows the comparison of cases in India with other countries having wide spread of COVID-19 till 15th May 2020. This clearly shows that India has controlled the spread in a good manner considering the population density of India. As per Fig. 1 the percentage of deaths with respect to cases is 3.23 only which is least among all the countries shown in figure followed by USA with 6.03%. It shows that in India cases have been tracked down in very early stages and patients have been given proper treatment like drinking warm water, herbal tea, doing yoga and meditation to boost up their immunity. AarogyaSetu app developed by government of India is helping the people in a big way by giving them option for self-health check-up for COVID-19 and helping the government to trace out the possible cases timely (PIB, 2020).
Fig. 1.
Comparison of COVID-19 cases of various countries with India (Source: WHO, 2020b, Accessed on 16 May, 2020).
In this study concentration values of seven pollutants have been analysed in three major cities (Mumbai, Delhi and Kolkata) of India which were declared as most polluted cities (The Week, 2019). Fig. 2 shows that the concentration of various pollutants in Mumbai was higher from 1st March to 21st March but started decreasing as soon as lockdown declared. We can deduce from the figure that PM10 has highest concentration among all the pollutants in Mumbai. In Fig. 2(a) we can see that the concentration of PM10 and PM2.5 has reduced significantly during lockdown period from 25th March to 30th April 2020. The concentration curve of NO2, NH3, O3 and SO2 shown in Fig. 2(b) has shown reducing trend from 20th March and has become almost flat after lockdown. The concentration of NO2 has reduced from 24-hourly average of around 50 to merely average around 15. The restrictions placed on transport sector, industrial and commercial activities is responsible for this reduction in the key air pollutants (PM10, PM2.5 and NO2) in lockdown phase. We can also deduce that the difference between concentration of PM2.5 and PM10 is the highest in Mumbai among all three. The high concentration of PM10 in Mumbai is due to power plants, unpaved roads, open garbage burning, construction of buildings and open burnings in slum areas. In Fig. 3, it is found that PM10 and PM2.5 concentration in Delhi has decreased along with other pollutants during first phase of lockdown upto 14th April but after that concentration of both pollutants increased due to some relaxation given by the government. However, ozone concentration has shown increasing trend due to rise in temperature in Northern India in the month of April. Fig. 4 reveals that due to lockdown all the pollutants have seen a decreasing trend except Ozone which is varying from time to time in lockdown period in Kolkata. As, there is no source of direct emission of ozone, it is formed when NOx, volatile organic compounds (VOCs) and gases react with each other under sunlight and temperature. However, a high level of NOx again reacts with ozone and cleans it up. In Kolkata before lockdown the level of ozone was high due to high amount of NO2 but after lockdown the concentration of NO2 decreased so the process of reacting again with ozone to mop it up was reduced. Hence, the rate of decrease in ozone levels was low in lockdown. The concentration of carbon monoxide (CO) has remained at the same level during the complete period of observation in all the three cities. The concentration of various pollutants from 1st March to 30th April 2020 in Delhi, Mumbai and Kolkata are shown in Tables 3, 4 and 5 respectively. Table 6 depicts the mean concentration of pollutants for the period of pre-lockdown and during lockdown. The mean concentrations are calculated using 24-hourly average of each day and then averaging out these values over the above said period. This table shows that there is marginal increase in pollutant PM2.5 during lockdown in Delhi due to relaxation given to government offices to operate but shows significant decrease of 66.29%, 42.27% and 16.2% in NH3, NO2 and PM10 respectively over pollutant concentration in pre-lockdown period. As source of 80% of NOx (nitrogen oxide) in Delhi is transport sector (TERI, 2018) so the restriction on transportation leads to reduction of 42.27% of NO2. However, the reduction in SO2 is 9.12% only as the main source of SO2 in Delhi are power plants which were kept operational even in lockdown period. In Mumbai there is heavy reduction in pollutants ranging from 29.60% to 69.28%. The highest reduction being of NO2. As major source of NO2 is vehicular emission but due to lockdown vehicles movement was restricted to minimum. Similar trend has been seen in Kolkata with reduction in pollutants ranging from 15.18% to 74.80%. Kolkata has seen highest reduction in PM2.5 (48.10%) and NO2 (74.80%) among the three cities. The reduction in SO2 in Mumbai is 65.55% which is much higher than Kolkata (20.01%) and Delhi (9.12%) indicating that SO2 emission from coal-based power plants in Delhi and Kolkata might be playing a more dominant role as compared to Mumbai. The results which have been obtained in this paper are also supported by the images from the Copernicus Sentinel-5P satellite from European Union Copernicus programme by European Space Agency. Fig. 5 clearly indicates the reduction in NO2 over Delhi, Mumbai and Kolkata in lockdown period as compared to pre-lockdown period from 1st March to 24th March (ESA, 2020). In Figs. 6, 7 and 8 AQI values of three cities are shown which are calculated with the help of AQI calculator given on the website of CPCB. In Mumbai it is observed generally that in the month of March the quality of air creates breathing problem but during lockdown the quality of air has improved lying mainly in good (dark green) or satisfactory (green) range as shown in Table 2, having minimum impact on health of the people. In Kolkata also it is found that quality of air improved over time. However, in Delhi we can see the improvement in the quality of air from 25th March to 14th April 2020 then it started decreasing but again started improving from 28th April.
Fig. 2.
Concentration of various pollutants from 1st March to 30th April 2020 in Mumbai.
Fig. 3.
Concentration of various pollutants from 1st March to 30th April 2020 in Delhi.
Fig. 4.
Concentration of various pollutants from 1st March to 30th April 2020 in Kolkata.
Table 3.
Concentration of various pollutants from 1st March to 30th April, 2020 in Mumbai.
Date |
PM2.5
(μg/m³) |
PM10
(μg/m³) |
NO2
(μg/m³) |
NH3
(μg/m³) |
SO2
(μg/m³) |
CO
(mg/m³) |
O3
(μg/m³) |
01-03-2020 |
52.37 |
162.62 |
62.62 |
42.24 |
4.68 |
0.79 |
22.68 |
02-03-2020 |
55.76 |
176.05 |
47.9 |
31.18 |
5.7 |
0.97 |
17.36 |
03-03-2020 |
45.57 |
166.37 |
54.18 |
34.45 |
2.24 |
0.64 |
19.88 |
04-03-2020 |
42.87 |
158.29 |
54.63 |
27.2 |
2.48 |
0.65 |
17.36 |
05-03-2020 |
34.38 |
140.37 |
41.88 |
27.17 |
2.7 |
0.51 |
18.73 |
06-03-2020 |
24.33 |
133.5 |
34.6 |
25.54 |
1.89 |
0.42 |
14.36 |
07-03-2020 |
30.26 |
171.05 |
46.71 |
23.33 |
1.31 |
0.5 |
23.58 |
08-03-2020 |
31.12 |
148.33 |
51.83 |
20.7 |
2.9 |
0.54 |
30.12 |
09-03-2020 |
45.0 |
167.65 |
55.37 |
23.95 |
2.21 |
0.72 |
25.58 |
10-03-2020 |
71.23 |
159.97 |
31.91 |
25.76 |
1.77 |
1.04 |
21.14 |
11-03-2020 |
17.09 |
88.46 |
43.97 |
21.1 |
1.26 |
0.43 |
20.13 |
12-03-2020 |
19.75 |
110.82 |
44.15 |
19.37 |
1.42 |
0.47 |
21.1 |
13-03-2020 |
27.58 |
149.54 |
55.18 |
17.82 |
3.93 |
0.45 |
36.28 |
14-03-2020 |
40.56 |
167.09 |
58.31 |
18.21 |
5.55 |
0.64 |
45.7 |
15-03-2020 |
68.87 |
225.71 |
56.61 |
21.92 |
13.37 |
1.37 |
40.03 |
16-03-2020 |
72.61 |
233.76 |
82.87 |
25.53 |
20.08 |
1.49 |
33.22 |
17-03-2020 |
82.82 |
251.2 |
68.13 |
31.2 |
17.2 |
1.73 |
37.6 |
18-03-2020 |
72.19 |
221.24 |
44.39 |
36.27 |
11.02 |
1.67 |
11.72 |
19-03-2020 |
36.08 |
129.36 |
16.37 |
46.06 |
2.76 |
0.79 |
7.24 |
20-03-2020 |
25.27 |
117.49 |
10.92 |
44.4 |
3.1 |
0.64 |
6.93 |
21-03-2020 |
24.92 |
77.33 |
13.73 |
43.43 |
2.61 |
0.51 |
7.16 |
22-03-2020 |
19.12 |
60.68 |
15.06 |
32.18 |
1.46 |
0.32 |
7.14 |
23-03-2020 |
23.23 |
71.8 |
14.63 |
27.7 |
1.54 |
0.39 |
7.34 |
24-03-2020 |
42.34 |
102.66 |
15.37 |
25.02 |
1.89 |
0.51 |
7.42 |
25-03-2020 |
32.97 |
78.74 |
10.93 |
22.52 |
2.14 |
0.43 |
7.19 |
26-03-2020 |
29.96 |
66.65 |
13.78 |
21.37 |
2.22 |
0.39 |
7.26 |
27-03-2020 |
28.88 |
70.83 |
12.74 |
18.87 |
1.19 |
0.32 |
7.48 |
28-03-2020 |
33.9 |
64.72 |
16.87 |
18.82 |
0.97 |
0.39 |
7.96 |
29-03-2020 |
30.34 |
68.79 |
15.51 |
19.83 |
0.8 |
0.35 |
7.43 |
30-03-2020 |
28.68 |
67.42 |
11.77 |
20.19 |
1.07 |
0.4 |
7.12 |
31-03-2020 |
33.26 |
63.57 |
13.98 |
19.5 |
1.28 |
0.41 |
7.19 |
01-04-2020 |
18.0 |
64.08 |
15.65 |
20.16 |
1.19 |
0.31 |
7.08 |
02-04-2020 |
NA |
78.6 |
13.44 |
20.32 |
1.37 |
0.36 |
7.23 |
03-04-2020 |
NA |
89.12 |
12.27 |
18.72 |
1.06 |
0.29 |
7.13 |
04-04-2020 |
NA |
79.02 |
11.27 |
18.36 |
1.4 |
0.34 |
6.99 |
05-04-2020 |
NA |
62.26 |
16.59 |
18.6 |
1.72 |
0.35 |
7.08 |
06-04-2020 |
NA |
32.16 |
8.96 |
17.39 |
1.68 |
0.24 |
6.96 |
07-04-2020 |
NA |
71.34 |
10.23 |
17.66 |
1.88 |
0.24 |
7.25 |
08-04-2020 |
NA |
100.88 |
10.56 |
17.02 |
1.84 |
0.23 |
7.06 |
09-04-2020 |
NA |
93.57 |
12.71 |
13.94 |
1.64 |
0.26 |
7.12 |
10-04-2020 |
NA |
78.49 |
16.33 |
13.21 |
1.53 |
0.28 |
6.99 |
11-04-2020 |
NA |
73.34 |
11.21 |
12.26 |
1.41 |
0.32 |
7.07 |
12-04-2020 |
NA |
65.07 |
14.03 |
12.01 |
1.83 |
0.33 |
6.93 |
13-04-2020 |
NA |
64.49 |
15.98 |
11.55 |
2.06 |
0.28 |
6.82 |
14-04-2020 |
NA |
70.29 |
19.89 |
11.21 |
1.96 |
0.31 |
7.06 |
15-04-2020 |
NA |
55.08 |
19.71 |
10.85 |
1.81 |
0.33 |
7.0 |
16-04-2020 |
NA |
47.38 |
10.79 |
10.51 |
1.78 |
0.25 |
6.77 |
17-04-2020 |
NA |
39.14 |
9.83 |
10.28 |
2.01 |
0.22 |
6.82 |
18-04-2020 |
NA |
16.11 |
14.16 |
10.17 |
1.81 |
0.19 |
7.02 |
19-04-2020 |
NA |
57.07 |
14.09 |
9.68 |
1.62 |
0.21 |
7.19 |
20-04-2020 |
NA |
71.9 |
14.8 |
11.32 |
1.9 |
0.35 |
6.98 |
21-04-2020 |
NA |
45.04 |
10.3 |
11.64 |
2.17 |
0.3 |
7.01 |
22-04-2020 |
NA |
42.73 |
10.35 |
10.71 |
2.01 |
0.2 |
6.88 |
23-04-2020 |
NA |
43.31 |
11.41 |
9.82 |
1.88 |
0.18 |
7.02 |
24-04-2020 |
NA |
39.13 |
9.52 |
9.79 |
2.15 |
0.21 |
6.83 |
25-04-2020 |
NA |
27.16 |
15.04 |
9.31 |
1.65 |
0.16 |
6.81 |
26-04-2020 |
NA |
33.18 |
13.84 |
9.94 |
1.67 |
0.2 |
6.82 |
27-04-2020 |
NA |
39.24 |
11.26 |
9.67 |
1.51 |
0.17 |
6.74 |
28-04-2020 |
NA |
43.73 |
15.71 |
9.38 |
1.55 |
0.19 |
6.73 |
29-04-2020 |
NA |
42.38 |
10.86 |
9.22 |
1.62 |
0.23 |
6.75 |
30-04-2020 |
NA |
19.81 |
7.35 |
8.97 |
1.7 |
0.19 |
6.81 |
* NA: Data of PM2.5 from 2nd April, 2020 not available on CPCB website
(PM2.5 stands for Particulate Matter of diameter of less than or equal to 2.5 micrometer, PM10 stands for Particulate Matter of diameter of less than or equal to10 micrometer, NO2 stands for Nitrogen oxide, NH3 stands for Ammonia, SO2 stands for Sulphur dioxide, CO stands for Carbon monoxide)
Table 4.
Concentration of various pollutants from 1st March to 30th April 2020 in Delhi.
Date |
PM2.5
(μg/m³) |
PM10
(μg/m³) |
NO2
(μg/m³) |
NH3
(μg/m³) |
SO2
(μg/m³) |
CO
(mg/m³) |
O3
(μg/m³) |
01-03-2020 |
56.75 |
96.3 |
28.74 |
54.2 |
12.0 |
1.46 |
32.29 |
02-03-2020 |
126.76 |
180.55 |
28.52 |
71.76 |
17.39 |
2.67 |
32.09 |
03-03-2020 |
107.57 |
147.45 |
29.23 |
57.94 |
14.76 |
1.28 |
35.66 |
04-03-2020 |
107.18 |
169.55 |
32.43 |
65.21 |
19.62 |
1.48 |
26.27 |
05-03-2020 |
38.52 |
67.36 |
28.6 |
48.73 |
10.42 |
0.68 |
26.5 |
06-03-2020 |
26.1 |
40.94 |
25.75 |
42.7 |
6.51 |
0.56 |
21.51 |
07-03-2020 |
59.15 |
89.47 |
25.06 |
43.25 |
6.57 |
0.85 |
22.88 |
08-03-2020 |
77.26 |
108.67 |
21.38 |
47.05 |
8.83 |
0.85 |
35.58 |
09-03-2020 |
52.13 |
89.83 |
22.34 |
38.81 |
10.46 |
0.45 |
40.2 |
10-03-2020 |
83.58 |
127.35 |
26.49 |
41.15 |
19.15 |
0.55 |
46.31 |
11-03-2020 |
76.73 |
112.92 |
28.79 |
47.87 |
13.16 |
0.59 |
27.08 |
12-03-2020 |
90.95 |
142.94 |
24.27 |
55.51 |
13.5 |
1.1 |
23.68 |
13-03-2020 |
57.43 |
117.34 |
35.19 |
42.53 |
13.7 |
0.55 |
21.14 |
14-03-2020 |
56.89 |
84.69 |
44.23 |
28.28 |
7.5 |
0.39 |
10.19 |
15-03-2020 |
62.97 |
95.97 |
46.55 |
29.53 |
14.2 |
0.43 |
26.42 |
16-03-2020 |
56.97 |
103.56 |
47.54 |
28.51 |
13.64 |
0.81 |
24.51 |
17-03-2020 |
66.43 |
108.84 |
48.92 |
29.27 |
15.44 |
0.85 |
31.15 |
18-03-2020 |
71.49 |
118.22 |
52.86 |
31.86 |
15.85 |
1.56 |
33.12 |
19-03-2020 |
110.2 |
165.61 |
51.1 |
32.14 |
19.14 |
2.36 |
41.17 |
20-03-2020 |
124.56 |
178.14 |
63.97 |
37.0 |
28.21 |
3.45 |
32.21 |
21-03-2020 |
104.13 |
144.22 |
51.67 |
32.72 |
21.05 |
2.28 |
41.32 |
22-03-2020 |
82.95 |
100.99 |
43.83 |
30.42 |
18.74 |
0.82 |
36.06 |
23-03-2020 |
94.06 |
109.74 |
39.51 |
26.47 |
17.56 |
0.68 |
35.46 |
24-03-2020 |
94.0 |
110.0 |
37.43 |
24.16 |
17.74 |
0.91 |
22.8 |
25-03-2020 |
88.89 |
103.28 |
30.63 |
22.38 |
10.31 |
1.49 |
25.74 |
26-03-2020 |
51.0 |
61.87 |
30.43 |
24.35 |
12.94 |
1.0 |
26.4 |
27-03-2020 |
57.9 |
72.54 |
33.58 |
25.56 |
7.21 |
0.84 |
20.17 |
28-03-2020 |
60.48 |
68.76 |
30.88 |
23.91 |
8.2 |
0.8 |
23.46 |
29-03-2020 |
59.38 |
66.25 |
21.96 |
17.16 |
5.33 |
0.55 |
41.03 |
30-03-2020 |
53.58 |
66.31 |
17.59 |
12.57 |
9.71 |
0.71 |
44.5 |
31-03-2020 |
46.62 |
53.51 |
17.87 |
12.78 |
11.31 |
0.68 |
42.97 |
01-04-2020 |
51.23 |
68.08 |
15.91 |
10.86 |
11.9 |
0.78 |
34.97 |
02-04-2020 |
53.18 |
56.29 |
14.51 |
10.26 |
9.28 |
0.64 |
42.07 |
03-04-2020 |
47.08 |
31.55 |
16.67 |
12.02 |
10.34 |
0.82 |
47.51 |
04-04-2020 |
44.73 |
56.11 |
19.4 |
12.57 |
10.33 |
1.26 |
36.37 |
05-04-2020 |
49.93 |
79.59 |
17.92 |
11.27 |
18.51 |
1.64 |
40.87 |
06-04-2020 |
44.31 |
94.64 |
17.38 |
11.48 |
16.15 |
1.66 |
39.82 |
07-04-2020 |
35.95 |
63.08 |
17.48 |
12.5 |
14.9 |
1.03 |
44.84 |
08-04-2020 |
27.5 |
58.14 |
17.31 |
12.5 |
10.98 |
1.11 |
44.61 |
09-04-2020 |
38.93 |
59.91 |
18.53 |
12.3 |
16.46 |
1.54 |
41.61 |
10-04-2020 |
64.22 |
81.39 |
22.06 |
13.27 |
16.07 |
2.17 |
40.18 |
11-04-2020 |
70.76 |
99.61 |
20.85 |
13.58 |
20.35 |
2.39 |
52.04 |
12-04-2020 |
48.64 |
67.21 |
19.0 |
13.15 |
16.18 |
1.73 |
44.71 |
13-04-2020 |
79.7 |
101.9 |
19.39 |
12.08 |
26.18 |
2.34 |
35.22 |
14-04-2020 |
76.43 |
88.89 |
22.83 |
12.61 |
17.71 |
2.77 |
36.4 |
15-04-2020 |
127.17 |
120.47 |
22.48 |
13.76 |
16.46 |
2.97 |
40.24 |
16-04-2020 |
143.85 |
109.96 |
21.98 |
14.21 |
24.86 |
3.01 |
51.75 |
17-04-2020 |
55.53 |
63.1 |
17.67 |
12.03 |
14.85 |
2.15 |
50.16 |
18-04-2020 |
98.54 |
108.19 |
17.19 |
11.44 |
10.19 |
2.26 |
41.5 |
19-04-2020 |
144.88 |
142.36 |
18.36 |
11.75 |
10.19 |
2.49 |
40.73 |
20-04-2020 |
133.92 |
140.46 |
20.5 |
12.9 |
9.12 |
3.32 |
40.63 |
21-04-2020 |
124.56 |
143.29 |
18.34 |
11.69 |
12.55 |
2.7 |
49.78 |
22-04-2020 |
124.96 |
149.82 |
21.21 |
12.58 |
18.1 |
3.47 |
51.7 |
23-04-2020 |
126.46 |
153.01 |
21.95 |
12.53 |
17.31 |
3.48 |
44.52 |
24-04-2020 |
183.98 |
191.93 |
22.71 |
12.68 |
15.76 |
3.68 |
58.3 |
25-04-2020 |
151.82 |
164.89 |
40.41 |
12.6 |
9.7 |
2.99 |
47.3 |
26-04-2020 |
69.0 |
83.64 |
20.34 |
13.21 |
11.79 |
2.98 |
52.6 |
27-04-2020 |
211.1 |
222.58 |
18.23 |
12.0 |
6.97 |
2.76 |
61.06 |
28-04-2020 |
100.44 |
108.61 |
19.3 |
12.63 |
11.56 |
3.02 |
65.15 |
29-04-2020 |
66.28 |
104.79 |
23.61 |
14.57 |
12.9 |
3.35 |
60.28 |
30-04-2020 |
60.64 |
125.12 |
20.6 |
13.14 |
14.71 |
2.99 |
69.58 |
(PM2.5 stands for Particulate Matter of diameter of less than or equal to 2.5 micrometer, PM10 stands for Particulate Matter of diameter of less than or equal to10 micrometer, NO2 stands for Nitrogen oxide, NH3 stands for Ammonia, SO2 stands for Sulphur dioxide, CO stands for Carbon monoxide)
Table 5.
Concentration of various pollutants from 1st March to 30th April 2020 in Kolkata.
Date |
PM2.5
(μg/m³) |
PM10
(μg/m³) |
NO2
(μg/m³) |
NH3
(μg/m³) |
SO2
(μg/m³) |
CO
(mg/m³) |
O3
(μg/m³) |
01-03-2020 |
93.69 |
191.48 |
79.35 |
20.23 |
10.66 |
2.28 |
65.76 |
02-03-2020 |
97.44 |
208.97 |
74.81 |
21.67 |
13.47 |
2.06 |
59.26 |
03-03-2020 |
77.3 |
146.63 |
58.12 |
25.4 |
10.7 |
1.88 |
65.43 |
04-03-2020 |
46.45 |
82.81 |
44.99 |
23.72 |
11.61 |
1.32 |
52.01 |
05-03-2020 |
30.38 |
65.76 |
53.33 |
22.98 |
9.42 |
1.85 |
43.99 |
06-03-2020 |
32.77 |
73.89 |
46.95 |
26.92 |
9.37 |
1.28 |
30.3 |
07-03-2020 |
30.96 |
56.21 |
41.15 |
27.39 |
8.25 |
1.67 |
36.17 |
08-03-2020 |
36.21 |
72.23 |
47.98 |
24.0 |
8.55 |
1.56 |
48.06 |
09-03-2020 |
54.6 |
111.69 |
57.51 |
24.38 |
9.76 |
1.16 |
69.37 |
10-03-2020 |
64.7 |
133.84 |
66.74 |
26.69 |
11.58 |
1.58 |
78.17 |
11-03-2020 |
51.53 |
102.84 |
54.07 |
29.44 |
14.13 |
1.73 |
76.72 |
12-03-2020 |
56.08 |
111.52 |
53.9 |
30.24 |
13.99 |
1.69 |
50.88 |
13-03-2020 |
55.1 |
104.83 |
65.23 |
24.48 |
13.31 |
1.71 |
57.24 |
14-03-2020 |
43.75 |
95.52 |
28.0 |
33.2 |
11.08 |
1.26 |
92.6 |
15-03-2020 |
23.13 |
55.2 |
42.2 |
27.97 |
15.72 |
1.45 |
66.38 |
16-03-2020 |
57.23 |
119.22 |
64.91 |
22.31 |
23.73 |
1.85 |
60.32 |
17-03-2020 |
61.7 |
128.79 |
70.38 |
22.66 |
13.67 |
1.72 |
74.45 |
18-03-2020 |
76.44 |
163.9 |
84.08 |
29.53 |
12.46 |
2.07 |
67.2 |
19-03-2020 |
74.19 |
166.4 |
79.44 |
23.71 |
16.38 |
1.66 |
65.68 |
20-03-2020 |
34.11 |
80.11 |
54.82 |
26.02 |
18.99 |
1.34 |
88.34 |
21-03-2020 |
36.45 |
75.38 |
37.73 |
26.68 |
18.27 |
1.41 |
82.2 |
22-03-2020 |
14.0 |
28.19 |
25.02 |
26.0 |
11.05 |
1.1 |
86.39 |
23-03-2020 |
23.57 |
52.36 |
27.04 |
24.37 |
12.41 |
1.32 |
86.96 |
24-03-2020 |
28.03 |
51.54 |
19.01 |
24.81 |
13.23 |
1.32 |
74.15 |
25-03-2020 |
40.64 |
72.03 |
22.17 |
24.1 |
16.39 |
1.55 |
64.74 |
26-03-2020 |
28.93 |
55.51 |
18.47 |
23.87 |
8.98 |
1.3 |
75.75 |
27-03-2020 |
41.41 |
82.93 |
20.51 |
25.03 |
16.5 |
1.4 |
91.49 |
28-03-2020 |
38.45 |
73.73 |
19.79 |
26.05 |
13.97 |
1.41 |
92.49 |
29-03-2020 |
32.41 |
63.19 |
17.68 |
26.78 |
11.27 |
1.27 |
105.95 |
30-03-2020 |
33.41 |
57.66 |
21.99 |
26.89 |
12.17 |
1.26 |
108.53 |
31-03-2020 |
35.08 |
73.09 |
27.57 |
27.11 |
11.69 |
1.32 |
100.99 |
01-04-2020 |
42.82 |
75.01 |
14.3 |
26.34 |
15.25 |
1.64 |
108.36 |
02-04-2020 |
35.84 |
56.48 |
13.18 |
23.03 |
10.56 |
1.73 |
85.45 |
03-04-2020 |
39.0 |
66.59 |
17.63 |
21.43 |
10.39 |
1.77 |
88.06 |
04-04-2020 |
49.46 |
74.25 |
19.4 |
24.02 |
12.91 |
1.03 |
97.41 |
05-04-2020 |
41.08 |
62.98 |
12.27 |
25.09 |
10.93 |
0.68 |
66.55 |
06-04-2020 |
33.62 |
59.76 |
17.47 |
22.51 |
10.85 |
0.51 |
55.69 |
07-04-2020 |
38.68 |
64.63 |
11.45 |
22.72 |
13.83 |
0.55 |
68.07 |
08-04-2020 |
25.32 |
32.76 |
12.74 |
20.84 |
10.3 |
0.44 |
68.21 |
09-04-2020 |
21.54 |
32.24 |
15.26 |
21.59 |
13.79 |
0.52 |
85.58 |
10-04-2020 |
19.9 |
27.15 |
8.46 |
20.97 |
8.01 |
0.65 |
50.34 |
11-04-2020 |
20.73 |
30.0 |
7.45 |
19.33 |
8.83 |
0.56 |
38.35 |
12-04-2020 |
24.74 |
39.71 |
7.47 |
19.39 |
7.38 |
0.6 |
36.69 |
13-04-2020 |
25.4 |
36.75 |
6.66 |
18.37 |
9.07 |
0.7 |
35.36 |
14-04-2020 |
27.36 |
50.61 |
5.65 |
17.0 |
6.84 |
0.64 |
30.73 |
15-04-2020 |
24.95 |
52.25 |
8.95 |
16.78 |
10.32 |
0.64 |
31.79 |
16-04-2020 |
29.58 |
57.29 |
13.65 |
18.09 |
8.31 |
0.66 |
30.07 |
17-04-2020 |
22.44 |
44.29 |
7.74 |
18.68 |
10.01 |
0.59 |
32.92 |
18-04-2020 |
20.2 |
29.0 |
9.49 |
17.36 |
12.48 |
0.59 |
29.16 |
19-04-2020 |
13.16 |
31.62 |
8.42 |
18.32 |
8.71 |
0.58 |
42.26 |
20-04-2020 |
15.18 |
29.76 |
8.8 |
17.99 |
9.71 |
0.63 |
28.6 |
21-04-2020 |
11.52 |
29.23 |
16.93 |
18.55 |
6.62 |
0.48 |
35.88 |
22-04-2020 |
15.38 |
27.77 |
13.33 |
20.9 |
11.2 |
0.58 |
31.74 |
23-04-2020 |
15.74 |
29.54 |
11.32 |
20.83 |
7.98 |
0.61 |
24.02 |
24-04-2020 |
11.58 |
31.65 |
9.9 |
20.35 |
9.85 |
0.54 |
32.36 |
25-04-2020 |
15.04 |
31.62 |
10.42 |
19.74 |
9.49 |
0.53 |
40.23 |
26-04-2020 |
16.26 |
33.34 |
10.13 |
19.83 |
8.17 |
0.56 |
41.89 |
27-04-2020 |
11.58 |
31.66 |
10.2 |
21.59 |
6.85 |
0.54 |
28.51 |
28-04-2020 |
9.19 |
33.89 |
12.7 |
22.51 |
6.15 |
0.64 |
25.99 |
29-04-2020 |
17.25 |
32.09 |
14.24 |
24.22 |
7.23 |
0.58 |
30.01 |
30-04-2020 |
15.25 |
31.98 |
12.32 |
25.58 |
11.56 |
0.61 |
33.5 |
(PM2.5 stands for Particulate Matter of diameter of less than or equal to 2.5 micrometer, PM10 stands for Particulate Matter of diameter of less than or equal to10 micrometer, NO2 stands for Nitrogen oxide, NH3 stands for Ammonia, SO2 stands for Sulphur dioxide, CO stands for Carbon monoxide)
Table 6.
Average of various pollutants in three cities.
Pre-lockdown
(1st March to 24th March) |
|
During lockdown
(25th March to 30th April) |
|
% Variation |
Pollutant |
Delhi |
Mumbai |
Kolkata |
Delhi |
Mumbai |
Kolkata |
Delhi |
Mumbai |
Kolkata |
PM2.5
(μg/m³) |
78.53 |
41.89 |
49.99 |
|
83.06 |
29.49 |
25.94 |
|
5.76 |
-29.60 |
-48.10 |
PM10
(μg/m³) |
117.11 |
149.63 |
103.30 |
98.13 |
58.53 |
47.13 |
-16.2 |
-60.8 |
-54.37 |
NO2
(μg/m³) |
36.85 |
42.55 |
53.19 |
21.27 |
13.07 |
13.40 |
-42.27 |
-69.28 |
-74.80 |
SO2
(μg/m³) |
14.79 |
4.79 |
12.99 |
13.44 |
1.65 |
10.39 |
-9.12 |
-65.55 |
-20.01 |
NH3
(μg/m³) |
41.12 |
28.82 |
25.61 |
13.86 |
14.18 |
21.72 |
-66.29 |
-50.79 |
-15.18 |
(PM2.5 stands for Particulate Matter of diameter of less than or equal to 2.5 micrometer, PM10 stands for Particulate Matter of diameter of less than or equal to10 micrometer, NO2 stands for Nitrogen oxide, NH3 stands for Ammonia, SO2 stands for Sulphur dioxide)
Fig. 6.
AQI Values of Mumbai from 1st March to 30th April 2020.
Fig. 7.
AQI Values of Delhi from 1st March to 30th April 2020.
Fig. 8.
AQI Values of Kolkata from 1st March to 30th April 2020.
6. CONCLUSION
COVID-19 hit most of the countries and each country took every possible step to control the spread of coronavirus. One of the major steps taken by most of the countries including India was declaring Lockdown considering it as one of the ways to implement social distancing. The decision of government to declare lockdown had negative consequences in the form of fall in stock market, economic slowdown, affected hospitality, tourism, aviation sector badly and amount of loss is uncountable. But we also experienced some positive result all over the world in this lockdown period as with decrease in the pollutants like PM2.5, NO2 due to non-movement of vehicles, shutting down of industries, no industrial waste emission there is an improvement in air quality. In India air pollution is a major concern as it is in the whole world. Government has been trying their level best by introducing various schemes like odd-even vehicular scheme, subsidising electric vehicles, encouraging construction of green buildings etc., but still unable to get good result. However due to lockdown environment has taken a big leap and has recovered to a large extent. It has been observed that concentration of various pollutants has reduced which has improved the quality of air and people are able to breathe in fresh air. This study will gain attention of policymakers to prepare polices for implementing work from culture to reduce daily commute of the office goers leading less number of vehicles on road and has given an insight that quality of air can be improved by strictly minimizing the vehicular and industrial pollution.