A significant drop in Air Pollution levels across India after about a
month COVID-19 lockdown.
Dr K K Aggarwal and Dr Anil Kumar, President and Director HCFI
The levels of NO2 and Ozone across
India are within the National Ambient Air Quality Standards.
No clear
relationship observed between current Air quality vs Confirmed COVID-19
cases in India.
During COVID-19 pandemic and lockdown
enforced, countries across world have reported a significant drop in air
pollution and witnessed improvement in air quality.
In India, the most significant improvement
in air quality during lockdown was observed in cities across Indo-Gangetic
plain as in most of the normal days, particularly in winter months, particulate
matter (PM10 and PM2.5 levels) and NO2 values are high in Indo-Gangetic plain due
to geographical location and other factors including very high population
density and spread of industrial clusters.
As per an earlier analysis done by Team of HCFI, after 11 days COVID-19
lockdown, the level of particulate
pollution (particulate matter, PM10 and
PM2.5) dropped by nearly 60% in Delhi. PM10
(particulate matter 10 micrometres or less in diameter) and PM2.5 (particulate
matter 2.5 micrometres or less in diameter) are particles present in the air
that are classified as pollutants and can harm human health. The deadliest particle in Delhi's foul air is
PM 2.5 (primarily come from combustion - fires, automobiles and power plants), which
increases the likelihood of respiratory and cardiovascular diseases.
Across the Globe, studies have been conducted to get a clear
relationship between air pollution exposure and COVID-19 confirmed cases as
high levels of air pollution can cause damage to the lungs and thus makes one,
more susceptible to either getting the infection or to getting complications
from COVID-19. The World Economic Forum also
said that people living with poor air quality may be more susceptible to
COVID-19 disease.
A recent study w.r.t. Exposure to air
pollution and COVID-19 mortality in the United States by Xiao Wu et.al of Dept. of Biostatistics, Harvard T.H. Chan
School of Public Health, USA, indicates that Coronavirus patients in areas that
had high levels of air pollution before the pandemic, are more likely to die
from the infection than patients in cleaner parts of the country. This study offers
the first clear link between long-term exposure to pollution & Covid-19 death rates.
The authors in above study found that
an increase of only 1 μg/m3 in PM2.5 is associated with a 15%
increase in the COVID-19 death rate. Results are statistically significant and
robust to secondary and sensitivity analyses. They have concluded that a small
increase in long-term exposure to PM2.5 leads to a large increase in
COVID-19 death rate. The study results underscore the importance of continuing
to enforce existing air pollution regulations to protect human health both
during and after the COVID-19 crisis.
In this
regard, Team of Experts of HCFI have done detailed analysis of air quality data
( Air Quality Index- AQI, PM10, PM2.5, NO2 and Ozone) from about 180 Continuous
Ambient Air Quality Monitoring Stations (CAAQMS) across India and correlated
with Confirmed COVID-19 cases . Status of Confirmed COVID-19 cases of various
States/UTs as on 21-04-2020 and corresponding State/UT wise Air Quality status
( as per average CPCB/SPCB data w.r.t. National Air Quality Index as on
21-04-2020 at 4:00 PM) is given below in the
Table:
State/
UT
|
Confirmed
COVID-19
cases
|
AIR Quality status ( PM10, PM2.5, NO2 and Ozone values in microgram
per meter cube)
|
|||||||
Andhra
Pradesh
|
722
|
AQI range
|
City
|
CAAQMS
Location
|
AQI
|
PM10
|
PM2.5
|
NO2
|
Ozone
|
38-52
|
Amrawati
|
Scretariat
|
52
|
52
|
18
|
30
|
13
|
||
Raja
Mahend-ravaram
|
Aanad Kala
kshetram
|
38
|
16
|
9
|
5
|
38
|
|||
Tirupati
|
Tirumala
|
39
|
13
|
10
|
8
|
39
|
|||
Visakha-patnam
|
GVM
Corporati-on
|
52
|
52
|
18
|
30
|
13
|
|||
Bihar
|
113
|
49-139
|
Gaya
|
Collecto-rate
|
96
|
-
|
48
|
21
|
96
|
Muzaffar-pur
|
Collecto-rate
|
61
|
-
|
34
|
30
|
61
|
|||
Patna
|
Govt. High School
|
108
|
108
|
26
|
11
|
4
|
|||
Muradpur
|
64
|
64
|
40
|
17
|
9
|
||||
Rajbansi
Nagar
|
49
|
49
|
30
|
-
|
21
|
||||
Saman-pura
|
139
|
49
|
47
|
30
|
53
|
||||
Chandi-garh
|
26
|
30
|
Chandi-garh
|
Sector-25
|
30
|
30
|
22
|
15
|
29
|
Delhi
|
2081
|
55-163
|
Delhi
|
Alipur
|
94
|
94
|
54
|
26
|
67
|
Anand vihar
|
84
|
84
|
77
|
21
|
56
|
||||
Aya nagar
|
62
|
62
|
56
|
18
|
26
|
||||
Bawana
|
118
|
118
|
100
|
22
|
89
|
||||
CRRI
|
77
|
77
|
56
|
18
|
14
|
||||
DTU
|
97
|
86
|
61
|
22
|
97
|
||||
Dwarka
Sector-8
|
89
|
84
|
50
|
20
|
89
|
||||
IGI Airport
|
64
|
64
|
45
|
-
|
34
|
||||
IHBAS
|
68
|
-
|
20
|
-
|
-
|
||||
JLN stadium
|
89
|
70
|
43
|
18
|
89
|
||||
Lodi Road
|
64
|
64
|
-
|
-
|
64
|
||||
National stadium
|
66
|
66
|
59
|
19
|
31
|
||||
Mandir marg
|
72
|
72
|
51
|
34
|
20
|
||||
Nehru nagar
|
163
|
79
|
68
|
22
|
163
|
||||
Okhla phase-2
|
89
|
-
|
42
|
19
|
6
|
||||
Patparganj
|
55
|
55
|
41
|
12
|
35
|
||||
Punjabi Bagh
|
77
|
77
|
65
|
34
|
31
|
||||
R.K.Puram
|
63
|
63
|
43
|
25
|
46
|
||||
Rohini
|
98
|
98
|
89
|
11
|
19
|
||||
Shadipur
|
81
|
-
|
26
|
27
|
81
|
||||
Sirifort
|
64
|
64
|
45
|
19
|
60
|
||||
Sri Auro-bind marg
|
121
|
48
|
37
|
6
|
121
|
||||
Vivek vihar
|
87
|
87
|
62
|
30
|
52
|
||||
Wazirpur
|
75
|
75
|
67
|
33
|
45
|
State/
UT
|
Confirmed
COVID-19
cases
|
AIR
Quality status ( PM10, PM2.5, NO2 and Ozone values in microgram per meter
cube)
|
|||||||
Gujrat
|
1939
|
AQI range
|
City
|
CAAQMS
Location
|
AQI
|
PM10
|
PM2.5
|
NO2
|
Ozone
|
51-75
|
Ahmeda-bad
|
Maninagar
|
72
|
72
|
47
|
17
|
60
|
||
Ankleshwar
|
GIDC
|
75
|
75
|
51
|
6
|
47
|
|||
Gandhi Nagar
|
Sector-10
|
56
|
56
|
34
|
4
|
31
|
|||
Nandesari
|
GIDC
|
51
|
49
|
28
|
51
|
-
|
|||
Vatva
|
Phase-4 GIDC
|
69
|
69
|
53
|
31
|
24
|
|||
Haryana
|
254
|
25-165
|
Ambala
|
Patti Mehar
|
42
|
-
|
39
|
21
|
42
|
Bahadurgarh
|
Arya Nagar
|
77
|
77
|
74
|
23
|
58
|
|||
Ballabh garh
|
Nathu
colony
|
74
|
64
|
74
|
11
|
14
|
|||
Bhiwani
|
H.B.Colony
|
62
|
58
|
24
|
18
|
62
|
|||
Daruhera
|
Municipal corporation office
|
63
|
50
|
61
|
13
|
63
|
|||
Farida-bad
|
Sector-30
|
98
|
98
|
19
|
14
|
41
|
|||
Sector-16 A
|
165
|
-
|
48
|
-
|
165
|
||||
Fatehabad
|
Huda sector
|
64
|
59
|
45
|
10
|
64
|
|||
Gurugram
|
NISE Gwal Pahari
|
67
|
67
|
50
|
12
|
35
|
|||
Sector-51
|
118
|
85
|
58
|
19
|
118
|
||||
TERI gram
|
85
|
59
|
56
|
-
|
85
|
||||
Vikas Sadan
|
121
|
-
|
51
|
27
|
121
|
||||
Hisar
|
Urban Estate-II
|
70
|
70
|
46
|
24
|
28
|
|||
JInd
|
Police line
|
64
|
51
|
50
|
19
|
64
|
|||
Kaithal
|
Rishi nagar
|
50
|
50
|
35
|
29
|
22
|
|||
Karnal
|
Sector-12
|
54
|
-
|
54
|
10
|
34
|
|||
Kurshetra
|
Sector-7
|
56
|
40
|
33
|
14
|
56
|
|||
Mandikhera
|
General Hospital
|
64
|
64
|
33
|
-
|
40
|
|||
Maneshar
|
Sector-2 IMT
|
73
|
73
|
25
|
2
|
-
|
|||
Narnaul
|
Shastri nagar
|
53
|
53
|
34
|
-
|
14
|
|||
Palwal
|
Shyam nagar
|
115
|
115
|
94
|
8
|
14
|
|||
Panchkula
|
Sector-6
|
25
|
-
|
25
|
22
|
24
|
|||
Panipat
|
Sector-18
|
91
|
91
|
41
|
70
|
46
|
|||
Rohtak
|
M D Univ.
|
49
|
-
|
49
|
-
|
27
|
|||
Sirsa
|
F Block
|
69
|
69
|
37
|
6
|
24
|
|||
Sonepat
|
Murthal
|
83
|
83
|
32
|
35
|
15
|
|||
Yamuna nagar
|
Govindpura
|
81
|
58
|
44
|
20
|
81
|
|||
Karnataka
|
408
|
31-60
|
Bengaluru
|
BTM layout
|
50
|
32
|
-
|
17
|
36
|
Bapuji nagar
|
51
|
31
|
18
|
9
|
51
|
||||
Hebbal
|
31
|
31
|
18
|
3
|
-
|
||||
Jaya Nagar
|
34
|
29
|
24
|
26
|
34
|
State/
UT
|
Confirmed
COVID-19
cases
|
AIR
Quality status ( PM10, PM2.5, NO2 and Ozone values in microgram per meter
cube)
|
|||||||
Karnataka
(continued)
|
408
|
AQI range
|
City
|
CAAQMS
Location
|
AQI
|
PM10
|
PM2.5
|
NO2
|
Ozone
|
31-60
|
Bengaluru
|
Peenya
|
60
|
-
|
60
|
8
|
-
|
||
Sanegurva
Hill
|
38
|
38
|
-
|
24
|
-
|
||||
Silk board
|
35
|
32
|
23
|
6
|
35
|
||||
Bagalkot
|
Vidayagiri
|
53
|
38
|
-
|
5
|
53
|
|||
Chikkballapur
|
Chikkaballapur rural
|
45
|
33
|
18
|
16
|
45
|
|||
Chickamangaluru
|
Kalyana
nagar
|
52
|
52
|
35
|
25
|
28
|
|||
Mysuru
|
Hebbal Ist stage
|
52
|
35
|
24
|
13
|
52
|
|||
Rama nagara
|
Vijay nagar
|
39
|
39
|
30
|
15
|
9
|
|||
Kerala
|
408
|
33-60
|
Ernakulam
|
Kacherypady
|
60
|
23
|
16
|
-
|
-
|
Kannur
|
Thavakkara
|
59
|
53
|
59
|
18
|
14
|
|||
Kochi
|
Vyttila
|
52
|
27
|
28
|
6
|
2
|
|||
Kolam
|
Polayathode
|
47
|
37
|
47
|
13
|
5
|
|||
Kozhikode
|
Palayam
|
42
|
41
|
42
|
10
|
9
|
|||
Thiruvanthapuram
|
Kanavattorm
|
55
|
39
|
37
|
14
|
55
|
|||
Plammoodu
|
33
|
27
|
12
|
8
|
28
|
||||
Madhya Pradesh
|
1485
|
45-169
|
Bhopal
|
T.T. Nagar
|
109
|
109
|
68
|
12
|
104
|
|
Damoh
|
Shrivastav colony
|
45
|
-
|
45
|
19
|
-
|
||
Dewas
|
Bhopal chauraha
|
110
|
101
|
110
|
22
|
74
|
|||
Gwalior
|
City Centre
|
95
|
44
|
24
|
11
|
95
|
|||
Phool bagh
|
72
|
-
|
72
|
-
|
-
|
||||
Indore
|
Chhoti Gwaltoli
|
100
|
100
|
78
|
61
|
37
|
|||
Jabalpur
|
Marhatal
|
104
|
104
|
55
|
27
|
64
|
|||
Katni
|
Gole Bazar
|
123
|
123
|
62
|
20
|
94
|
|||
Maihar
|
Sahilara
|
64
|
64
|
30
|
43
|
-
|
|||
Mandideep
|
Sector- D Ind. Area
|
59
|
59
|
58
|
16
|
25
|
|||
Pithampur
|
Sector-2 Ind. Area
|
116
|
116
|
78
|
14
|
16
|
|||
Singrauli
|
Vindhyachal
|
169
|
151
|
99
|
33
|
169
|
|||
Ujjain
|
Mahakaleshwar
|
159
|
114
|
159
|
16
|
150
|
|||
Mizoram
|
1
|
24
|
Aizawaa
|
Sikulpuikawn
|
24
|
24
|
-
|
1
|
12
|
Jharkhand
|
46
|
93
|
Jorapokhar
|
Tata stadium
|
93
|
93
|
39
|
14
|
-
|
Assam
|
35
|
35
|
Guwahati
|
Railway colony
|
35
|
35
|
33
|
8
|
32
|
Odisha
|
74
|
99
|
Brajraj Nagar
|
GM office
|
99
|
99
|
95
|
-
|
-
|
State/
UT
|
Confirmed
COVID-19
cases
|
AIR Quality status ( PM10, PM2.5, NO2 and Ozone values in microgram
per meter cube)
|
|||||||
Maharasthra
|
4666
|
AQI range
|
City
|
CAAQMS
Location
|
AQI
|
PM10
|
PM2.5
|
NO2
|
Ozone
|
44-89
|
Aurangabad
|
More chowk Waluj
|
52
|
38
|
33
|
17
|
52
|
||
Chandrapur
|
Chandrapur
|
65
|
65
|
49
|
16
|
24
|
|||
Khutala
|
85
|
34
|
36
|
19
|
85
|
||||
Mumbai
|
Bandra
|
55
|
55
|
27
|
5
|
-
|
|||
Chhatrapati Shivaji Int. Airport
|
60
|
60
|
-
|
7
|
-
|
||||
Colaba
|
44
|
-
|
26
|
3
|
44
|
||||
Kurla
|
76
|
76
|
-
|
20
|
18
|
||||
Powai
|
78
|
62
|
29
|
3
|
26
|
||||
Sion
|
89
|
89
|
50
|
18
|
34
|
||||
Worli
|
52
|
52
|
30
|
5
|
28
|
||||
Nasik
|
Gangapur road
|
56
|
41
|
39
|
26
|
56
|
|||
Navi Mumbai
|
Mahape
|
87
|
87
|
42
|
30
|
42
|
|||
Nerul
|
70
|
69
|
44
|
13
|
28
|
||||
Pune
|
Karve road
|
50
|
35
|
37
|
11
|
20
|
|||
Solapur
|
solapur
|
44
|
44
|
42
|
-
|
36
|
|||
Punjab
|
245
|
30-96
|
Amritsar
|
Golden temple
|
43
|
40
|
17
|
17
|
43
|
Bathinda
|
Hardev nagar
|
96
|
32
|
11
|
23
|
-
|
|||
Jalandhar
|
Civil line
|
36
|
36
|
35
|
11
|
18
|
|||
Khanna
|
Kalal majra
|
33
|
33
|
25
|
8
|
20
|
|||
Ludhiana
|
Punjab Agri. Univ.
|
35
|
25
|
22
|
20
|
35
|
|||
Mandi Govindgarh
|
RIMT univ
|
96
|
32
|
11
|
23
|
96
|
|||
Patiala
|
Model town
|
37
|
37
|
24
|
8
|
17
|
|||
Rup nagar
|
Ratanpura
|
30
|
30
|
24
|
16
|
-
|
|||
Rajasthan
|
1576
|
57-82
|
Alwar
|
Moti Doongri
|
66
|
39
|
35
|
43
|
66
|
Ajmer
|
Civil line
|
77
|
51
|
31
|
11
|
77
|
|||
Bhiwadi
|
RIICO Ind. Area-III
|
74
|
74
|
55
|
15
|
55
|
|||
Jaipur
|
Adarsh nagar
|
82
|
30
|
22
|
15
|
82
|
|||
Police Commissionerate
|
68
|
58
|
43
|
22
|
68
|
||||
Shatri nagar
|
70
|
28
|
22
|
19
|
70
|
||||
Jodhpur
|
Collectorate
|
79
|
79
|
52
|
27
|
53
|
|||
Kota
|
Shrinathpuram
|
57
|
38
|
34
|
17
|
57
|
|||
Pali
|
Indra colony vistar
|
76
|
76
|
51
|
15
|
75
|
|||
Udaipur
|
Ashok nagar
|
81
|
55
|
44
|
15
|
81
|
State/
UT
|
Confirmed
COVID-19
cases
|
AIR Quality status ( PM10, PM2.5, NO2 and Ozone values in microgram
per meter cube)
|
|||||||
Tamilnadu
|
1520
|
AQI range
|
City
|
CAAQMS
Location
|
AQI
|
PM10
|
PM2.5
|
NO2
|
Ozone
|
26-68
|
Chennai
|
Alandur bus depot
|
26
|
-
|
16
|
2
|
26
|
||
Manali village
|
68
|
-
|
16
|
8
|
68
|
||||
Manali
|
40
|
-
|
37
|
9
|
-
|
||||
Velachri res area
|
40
|
-
|
5
|
2
|
30
|
||||
Telangana
|
873
|
41-60
|
Hyderabad
|
Bollaram Ind. area
|
53
|
53
|
42
|
39
|
28
|
Central Univ.
|
45
|
35
|
22
|
45
|
5
|
||||
ICRISAT
|
41
|
41
|
30
|
22
|
20
|
||||
IDA Pasahamylaram
|
50
|
46
|
35
|
50
|
24
|
||||
Sanathnagar
|
49
|
-
|
48
|
12
|
49
|
||||
Zoo park
|
60
|
-
|
60
|
54
|
19
|
||||
Uttar Pradesh
|
1184
|
55-161
|
Agra
|
Sanjay palace
|
114
|
-
|
114
|
64
|
11
|
Bulandshahr
|
Yamunapuram
|
161
|
161
|
137
|
29
|
117
|
|||
Ghaziabad
|
Indirapuram
|
89
|
89
|
57
|
25
|
82
|
|||
Loni
|
123
|
123
|
90
|
16
|
82
|
||||
Sanjay nagar
|
109
|
109
|
95
|
44
|
60
|
||||
Vasundhara
|
89
|
89
|
67
|
51
|
22
|
||||
Greater Noida
|
Knowledge park III
|
113
|
113
|
82
|
-
|
92
|
|||
Knowledge Park V
|
102
|
102
|
-
|
26
|
90
|
||||
Hapur
|
Anand vihar
|
159
|
159
|
83
|
74
|
2
|
|||
Kanpur
|
Nehru nagar
|
62
|
-
|
50
|
13
|
62
|
|||
Lucknow
|
Central School
|
114
|
-
|
114
|
9
|
11
|
|||
Gomti nagar
|
74
|
-
|
74
|
24
|
59
|
||||
Lal bagh
|
55
|
-
|
43
|
22
|
18
|
||||
Talkatora distric centre
|
67
|
-
|
67
|
9
|
-
|
||||
Meerut
|
Ganga nagar
|
92
|
92
|
48
|
24
|
28
|
|||
Pallavpuram phase II
|
113
|
113
|
60
|
16
|
18
|
||||
Mujaffar nagar
|
New mandi
|
103
|
103
|
67
|
7
|
19
|
|||
Noida
|
Sector 62
|
89
|
72
|
89
|
17
|
65
|
|||
Sector 1
|
104
|
104
|
55
|
19
|
83
|
||||
Sector116
|
77
|
-
|
77
|
23
|
46
|
State/
UT
|
Confirmed
COVID-19
cases
|
AIR Quality status ( PM10, PM2.5, NO2 and Ozone values in microgram
per meter cube)
|
|||||||
West Bengal
|
392
|
AQI range
|
City
|
CAAQMS
Location
|
AQI
|
PM10
|
PM2.5
|
NO2
|
Ozone
|
21-69
|
Howrah
|
Belur Math
|
21
|
21
|
14
|
20
|
-
|
||
Ghusuri
|
58
|
42
|
27
|
18
|
56
|
||||
Padmapukar
|
28
|
27
|
28
|
13
|
13
|
||||
Kolkatta
|
Bollygunge
|
52
|
27
|
13
|
6
|
52
|
|||
Bidhan nagar
|
48
|
25
|
20
|
7
|
48
|
||||
Fort Villiam
|
55
|
26
|
23
|
14
|
55
|
||||
Jadavpur
|
27
|
27
|
16
|
11
|
20
|
||||
Ravindra Bharti Univ.
|
69
|
25
|
20
|
25
|
69
|
||||
Rabindra sarobar
|
48
|
21
|
-
|
8
|
48
|
||||
Victoria
|
41
|
31
|
18
|
16
|
41
|
||||
Sliguri
|
Ward 32 Bapupura
|
38
|
32
|
38
|
38
|
22
|
The above data of current Air Quality vs
Confirmed COVID-19 cases in India do not show any clear relationship. However,
long term exposure of higher levels of air pollutants, particularly higher
PM2.5 levels, may weakens the immunity and thus raises the risk of COVID-19
infection. Detailed study in this regard is needed.
However, as per present study, the levels of NO2 and Ozone throughout
the India are found within the National Ambient Air Quality Standards,
notified as per the Central Pollution Control Board Notification in the Gazette
of India, dated 18th November, 2009 (
PM10 std. 24 hourly = 100 microgram per meter cube, PM2.5 std. 24 hourly = 60
microgram per meter cube, NO2 std. 24 hourly = 80 microgram per meter cube and
Ozone std. 1 hourly = 180 microgram per meter cube).
Though, levels of PM10 and PM2.5 have significantly declined
during Lockdown period as compared to Normal days. However, levels of PM10 and
PM2.5 in some States/ UTs at few locations are found above the Standards.
Though, presently, we have observed clean air due to the lockdown in
India but this respite is for short term period. After the restrictions are lifted and human
activities start, there will be a sudden rise in air pollution. But, the lockdown during
COVID-19 has shown ways to tackle air pollution issues, only what’s
needed is political will, societal interventions and strict enforcement.
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