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Anthropogenic activities were greatly restricted in many South Asian cities during the COVID-19 (Coronavirus disease-2019) pandemic creating an opportunity to observe source reduction of air pollutants. This study analyzed the change in columnar nitrogen dioxide (NO2) and particulate matter (PM2.5, aerodynamic diameter ≤2.5 µm) in five megacities of South Asian countries (Delhi, Dhaka, Kathmandu, Kolkata, and Lahore) from April 1 - May 31 over the previous three years (2018-2020). The Dutch-Finnish Ozone Monitoring Instrument (OMI) provided satellite-based daily tropospheric columnar NO2 values for this study. Ground-based hourly PM2.5 data were collected from the World's Air Pollution: Real-time Air Quality Index Project. The study observed a decrease of tropospheric columnar NO2 in selected cities in 2020 compared to 2018 and 2019 from April 1 - May 31. The mean daily reading of PM2.5 was 36.56% and 45.44% less in Delhi; 12.67% and 23.46% less in Dhaka; in Kathmandu 28.32% and 37.42% less; in Kolkata 41.02% less in 2020 than 2018 and 34.08% less in 2019 during April 1 - May 31. The PM2.5 was 44.26% less in 2020 than in 2019 during April 9 - May 31 in Lahore. The daily mean difference in concentration during April 1 - May 31, 2018-2020 was significantly lower at α=0.01 level for both pollutants. Introducing appropriate mitigation measures would provide safer environments and reduce future air pollution in South Asian cities
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Environment and Natural Resources Journal 2021; 19(X): xx-xx
Effect of COVID-19 Lockdown on Air Quality: Evidence from South
Asian Megacities
Ahmad Kamruzzaman Majumder1*, Abdullah Al Nayeem1, Mahmuda Islam1, William S Carter1,
Razib1, and SM Munjurul Hannan Khan2
1Center for Atmospheric Pollution Studies (CAPS), Department of Environmental Science, Stamford University Bangladesh,
Dhaka-1209, Bangladesh
2Additional Secretary at Government of the People's Republic of Bangladesh, Bangladesh
ARTICLE INFO
ABSTRACT
Received: 13 Oct 2020
Received in revised: 15 Dec 2020
Accepted: 28 Jan 2021
Published online: 3 Mar 2021
DOI: 10.32526/ennrj/19/2020230
Anthropogenic activities were greatly restricted in many South Asian cities
during the COVID-19 (Coronavirus disease-2019) pandemic creating an
opportunity to observe source reduction of air pollutants. This study analyzed
the change in columnar nitrogen dioxide (NO2) and particulate matter
(PM2.5, aerodynamic diameter ≤2.5 µm) in five megacities of South Asian
countries (Delhi, Dhaka, Kathmandu, Kolkata, and Lahore) from April 1 - May
31 over the previous three years (2018-2020). The Dutch-Finnish Ozone
Monitoring Instrument (OMI) provided satellite-based daily tropospheric
columnar NO2 values for this study. Ground-based hourly PM2.5 data were
collected from the World's Air Pollution: Real-time Air Quality Index Project.
The study observed a decrease of tropospheric columnar NO2 in selected cities
in 2020 compared to 2018 and 2019 from April 1 - May 31. The mean daily
reading of PM2.5 was 36.56% and 45.44% less in Delhi; 12.67% and 23.46%
less in Dhaka; in Kathmandu 28.32% and 37.42% less; in Kolkata 41.02% less
in 2020 than 2018 and 34.08% less in 2019 during April 1 - May 31. The PM2.5
was 44.26% less in 2020 than in 2019 during April 9 - May 31 in Lahore. The
daily mean difference in concentration during April 1 - May 31, 2018-2020 was
significantly lower at α=0.01 level for both pollutants. Introducing appropriate
mitigation measures would provide safer environments and reduce future air
pollution in South Asian cities.
Keywords:
Corona virus/ Lockdown/ South
Asian cities/ Tropospheric columnar
NO2/ PM2.5
* Corresponding author:
E-mail: dk@stamforduniversity.
edu.bd
1. INTRODUCTION
1.1 Coronavirus disease (COVID-19) pandemic
The world was reminded of environmental
determinism in December 2019 by a new strain of
Coronavirus (COVID-19). The virus appeared to have
originated in Wuhan, China (Chen et al., 2020). This
respiratory illness spread worldwide and led to a
global pandemic. COVID-19 pandemic has impacted
many aspects of human life and the global economy.
A reduction of pollution has occurred due to limited
social and economic activities despite the negative
impacts of COVID-19 in many aspects of daily life
(Dutheil et al., 2020). Most countries have tried to
contain the spread of the highly contagious virus with
massive COVID-19 screening tests, social distancing
public policies, travel restrictions, and lockdown. The
South Asian countries of Bangladesh, India, Nepal,
and Pakistan restricted movements from the mid of
March 2020 to mitigate the COVID-19 pandemic
(Shrestha et al., 2020; Mahato et al., 2020; Nayeem et
al., 2020).
The Bangladesh government reported the first
three known cases on March 8, 2020 (IEDCR, 2020).
To protect the population from this outbreak, the
government declared a countrywide lockdown from
March 23 to May 30, 2020 (Nayeem et al., 2020).
Heavy vehicles (long road trucks) and diesel buses
were restricted during the daytime in Dhaka during
these weeks.
India identified the first case of COVID-19 on
January 30, 2020; by July 7, 2020, India had the third-
highest number of confirmed cases after the United
States and Brazil (Kulkarni, 2020). The Indian
government imposed a nationwide lockdown on
Citation: Majumder AK, Nayeem AA, Islam M, Carter WS, Razib, Khan SMMH. Effect of COVID-19 lockdown on air quality: Evidence from
South Asian megacities. Environ. Nat. Resour. J. 2021;19(X):xx-xx.
Majumder AK et al. / Environment and Natural Resources Journal 2021; 19(X): xx-xx
March 24, 2020, for 21 days to control this outbreak
extending it to May 31, 2020. The government
restricted vehicle movements (except emergency
services) in Delhi and Kolkata to comply with the
social distancing policy.
Nepal reported the first COVID-19 positive
patient on January 23, 2020, when a 31-year-old
student returned to Kathmandu from Wuhan, China. In
response, the Nepal government suspended on-arrival
tourist visas for all countries from March 14 - April
30, 2020. After that, a countrywide lockdown came
into effect on March 24, 2020, which ended on July
21, 2020 (Pradhan, 2020). The government also closed
the land border entry points for third-country nationals
and canceled all mountain climbing expeditions,
including Mount Everest. Enforcement of these
restrictions was from March 14 - April 30, 2020
(Himalayan Times, 2020).
Pakistan reported the first confirmed case on
February 26, 2020. As a result, the Pakistan
government closed shopping malls, markets, parks,
and public gathering places. The government declared
a 14-day lockdown from March 24 - April 6, later
extended to April 30 (Sipra et al., 2020). The
government shut down all land borders and canceled
international and domestic flights.
With all these restraints in these four countries,
only emergency services such as medical, healthcare,
logistics, food supply chain, power sector, and
banking were allowed to be carried on in a limited
way. Therefore, less vehicle movement on the roads,
restricted construction, and industrial activities has led
to an emission reduction of various gases and
particulate matter in the atmosphere (Nadzir et al.,
2020).
1.2 Sources apportionment of air pollution over
different cities
A study carried out in Delhi during the winter
of 2013-2014, and the summer of 2014 identified the
source apportionment of PM2.5 as road dust (38%),
vehicular pollution (20%), domestic sources (12%),
industrial sources (11%), concrete batching (6%), and
13% from other sources (Nagar et al., 2017). Vehicular
emission (51.4%), followed by industrial sources
(24.5%) and road dust (21.1%) were identified as the
significant sources of air pollution in Kolkata (Haque
and Singh, 2017). In Dhaka, previous studies have
identified brick kilns located near the city,
uncontrolled open burning of trash, and vehicle
exhaust as significant sources of PM2.5 (Nayeem et al.,
2020). Primary sources of PM2.5 in Lahore are diesel
emission and two-stroke vehicles (36%), biomass
burning (15%), coal combustion (13%), and industrial
activities (Dutkiewicz et al., 2009; Raja et al., 2010;
Stone et al., 2010). Brick kilns (40%), motor vehicles
(37%) biomass/garbage burning (22%), and soil dust
(1%) have been identified as contributing sources in
the Kathmandu Valley (Kim et al., 2015).
1.3 COVID-19 and air pollution
One of the significant environmental problems
of developing countries is air pollution, mostly seen in
urban areas due to exhaust from vehicles, brick kilns,
industrial and construction activities, unsustainable
farming, open waste dumping, and combustion of
fossil fuels (Majumder et al., 2020; Nayeem et al.,
2019; Razib et al., 2020; Nadzir et al., 2020; Hossain
et al., 2019). These emissions are responsible for the
release of several gaseous compounds such as carbon
monoxide (CO), nitrogen dioxide (NO2), ozone (O3),
sulfur dioxide (SO2), and particulate matter (coarse
and fine particles) into the atmosphere. Among these
compounds, the concentrations of nitrogen dioxide
(NO2) and fine particulate matter (PM2.5) are
monitored continuously in urban areas since these
compounds have adverse impacts on human health
(Latif et al., 2012; Banan et al., 2012; Nadzir et al.,
2018). Increased levels of these pollutants may cause
acute and chronic diseases resulting in 5.5 million
unnecessary deaths annually (WHO, 2016).
Many satellite and ground-based air pollution
studies have addressed the impacts of COVID-19
pandemic. A study reported that three cities in central
China (Wuhan, Jingmen, and Enshi) had recorded
total reductions of air pollutants of PM2.5 by 30.1% and
of NO2 by 61.4% during the pandemic (Xu et al.,
2020). The average air quality index (AQI) for these
three cities decreased significantly compared to 2017-
2019. In another study, the Copernicus Atmosphere
Monitoring Service (CAMS) was used to observe the
concentration of particulate matter (PM2.5) in China
and found a 20-30% reduction throughout lockdown
compared to the previous three years of 2017, 2018,
and 2019 during the same months (Zambrano et al.,
2020). In one study over the peninsular Malaysia
region, the concentration of PM2.5 was found to be
reduced by 58.4% during the lockdown (Abdullah et
al., 2020). A study in Barcelona, Spain, using
Copernicus Tropospheric Monitoring Instrument,
reported a 51.0% reduction of tropospheric columnar
NO2 during the lockdown than the month before the
Majumder AK et al. / Environment and Natural Resources Journal 2021; 19(X): xx-xx
lockdown (Tobías et al., 2020). A sharp declining
trend of NO2 concentrations was also observed in
developed countries such as France, Germany, Italy,
and Spain (ESA, 2020).
According to the 2019 IQAir report,
Bangladesh (1st), Pakistan (2nd), India (5th), and Nepal
(8th) are some of the world’s most polluted countries
for PM2.5 exposure with high urban growth rates
(UNCTAD, 2020), Delhi topped the list of the world’s
most polluted capital cities followed by Dhaka (IQAir,
2019). Since India ranks as the second-most populous
country, Kolkata, a very crowded city just adjacent to
Bangladesh surrounded by numerous coal power
plants, is also worthy of being evaluated (Vadrevu et
al., 2020). While Islamabad, the capital city of
Pakistan, ranked 14th, PM2.5 exposure data is not
available. This study considered, a relative nearby
alternative Lahore (270 km), where a strict lockdown
was imposed and is a significant polluted city
according to the US Air Quality Index (Sipra et al.,
2020). In Nepal, Kathmandu has the 6th highest PM2.5
value of any capital being analyzed (IQAir, 2019). As
several studies found that atmospheric pollution is a
transboundary issue (Shehzad et al., 2020; Rana et al.,
2016), only the research on a regional scale can
identify issues. According to the Koppen climate
classification scheme, part of Delhi and Lahore are
considered Bsh (semi-arid), other parts of Delhi and
Kathmandu are in a Cwa (humid subtropical) climatic
zone, and Kolkata and Dhaka fall in a Aw (tropical
wet-and-dry) zone (Lohmann et al., 1993) and these
cities are also part of the regional wind system. This
study chose these five megacities of four neighboring
countries since they are cities in member countries of
the regional forum SAARC (South Asian Association
of Regional Cooperation). We have carried out this
study to observe the impacts of COVID-19 lockdown
on air quality in those five polluted megacities of
South Asia. The objective of this study was to analyze
the variations in satellite-derived tropospheric
columnar NO2 and ground-based PM2.5 concentration
in selected South Asian megacities: Delhi, Dhaka,
Kathmandu, Kolkata, and Lahore for the three years
(2018-2020) at the same period of April 1 - May 31.
2. METHODOLOGY
2.1 Tropospheric NO2 Vertical Column Densities
(VCDs)
The Dutch-Finnish Ozone Monitoring
Instrument (OMI), a UV-Visible wavelength
spectrometer on the polar-orbiting NASA Aura
satellite (https://so2.gsfc.nasa.gov/no2/no2_index.html),
provided daily tropospheric columnar NO2 values.
This OMI sensor measures direct and atmospheric
backscattered sunlight in the ultraviolet-visible (UV-
Vis) zone ranging from 270 to 500 nm (Levelt et al.,
2006). The normal spatial resolution is 24 × 13 km2 in
nadir and was zoomed into 13 × 13 km2 to monitor
urban scale pollution sources (Boersma et al., 2004).
In this study, level 2 data were collected as comma-
separated value (CSV) files to detect tropospheric
columnar NO2 in five megacities of South Asian
countries during the COVID-19 pandemic compared
to 2018 and 2019 during the same months (April-
May). The 1 × 1 degree grid boxes surrounding each
city was calculated to be: Delhi (76.709N 28.1139E
77.709N 29.1139E); Dhaka (89.9201N 23.308E
90.9201N 24.308E); Kathmandu (84.824N 27.2172E
85.824N 28.2172E); Kolkata (87.9001N 22.0667E
88.9001N 23.0667E), and Lahore (73.8436N
31.0497E 74.8436N 32.0497E). We retrieved average
spatial maps of tropospheric columnar NO2 in the
troposphere with 0.25° × 0.25° resolution from the
GIOVANNI online platform (GIOVANNI, 2020).
2.2 Ground level PM2.5
PM2.5 data were gathered from April 1 - May 31
over the last three years (2018-2020) from four
selected Southeast Asian cities: Dhaka, Kolkata,
Delhi, and Kathmandu. Data from April 9 - April 30,
2019, and May 9 - May 31, 2020 were used for
Lahore since other data was lacking (Figure 1). We
obtained hourly readings of PM2.5 from the publicly
available air quality data at World's Air Pollution:
Real-time Air Quality Index Project (Air Now, 2020).
Ground-based PM2.5 monitoring stations, located at
or near the US embassies and consulates of each
country, record data. Several researchers have used
this data source to determine compliance with air
quality standards, simulate model, forecast air quality,
study epidemiology, and assess health risk (Diao et al.,
2019; Bulto, 2020; Yousefian et al., 2020; Roy et al.,
2020). In the global village, using open-access air
quality data helps develop integrated actions to control
air pollution.
2.3 Data analysis
SPSSv20 and Microsoft Excelv10 were used for
data processing, analysis, and preparing tables and
graphs. Tukey’s post hoc multiple comparison test was
conducted to determine the significant level of changes
Majumder AK et al. / Environment and Natural Resources Journal 2021; 19(X): xx-xx
Figure 1. Geographical distribution of the selected cities in South Asian countries
in the selected years for both PM2.5 concentration and
tropospheric columnar NO2. ArcGIS 10.2.1 was used
to visualize the study area map.
3. RESULTS AND DISCUSSION
3.1 Tropospheric NO2 Vertical Column Densities
(VCDs) measured by OMI
The tropospheric columnar NO2 observed from
space through OMI denote emissions of nitrogen
oxides (NOx = NO + NO2) formed from fossil fuel
combustion in industries, biomass burning, fires, and
lightning. The wind direction and speed transport the
NO2 away from its sources. Many of these
anthropogenic pollution sources were inactive since
Bangladesh, India, Nepal, and Pakistan implemented
strict traffic restrictions and self-quarantine measures
to control the expansion of the COVID-19 pandemic
(Shrestha et al., 2020). Significant air pollution
changes in Delhi, Dhaka, Kathmandu, Kolkata, and
Lahore resulted. This study observed a decreasing
trend of tropospheric columnar NO2 compared to
previous years during the same months in these
selected cities of South Asia (Figure 2). Tropospheric
columnar NO2 values were much higher in 2018 in
Delhi, Dhaka, Kolkata, and Lahore. In Kathmandu, the
highest value observed was in 2019. Table 1 shows the
daily average of tropospheric columnar NO2 in the
selected cities from 2018-2020 during April and May.
Delhi observed a dramatic reduction in the daily
tropospheric columnar NO2 during the COVID-19
period of 48% and 45.6% compared to 2018 and
2019. In Dhaka, the daily average tropospheric
columnar NO2 was 4.36, 3.47, and 2.57 molecules/cm2
in 2018, 2019, and 2020, respectively. The
tropospheric columnar NO2 values in 2020 were
41.0% and 25.9% lower relative to 2018 and 2019
during the lockdown. The rate was reduced in Kolkata
by 24.7% and 17.6% in 2020 compared to the previous
two years.
In Lahore, the daily average tropospheric
columnar NO2 concentration was 36.0% and 25.0%
lower in 2020 during the COVID-19 period compared
to 2018 and 2019. In Kathmandu, the 2020
tropospheric columnar NO2 is 8.7% lower than in
2018 and 15.0% than in 2019. Other studies showed
that Delhi had a significant tropospheric columnar
NO2 reduction during the lockdown period (Vadrevu
et al., 2020; Shehzad et al., 2020). Kolkata, as a
coastal city, saw less reduction (Vadrevu et al., 2020).
Additionally, in Kolkata, most coal power plants were
not closed during the pandemic, which may have
contributed to less reduction (Vadrevu et al., 2020).
Majumder AK et al. / Environment and Natural Resources Journal 2021; 19(X): xx-xx
Figure 2. The whisker box plot shows the daily average of OMI derived tropospheric columnar NO2 (10 15 molecules/cm2). A horizontal
black line within the box marks the median; the lower boundary of the box indicates the 25th percentile, the upper boundary of the box
indicates the 75th percentile. The whisker represents the maximum (upper whisker) and minimum value (lower whisker). Points above the
whiskers indicate outliers.
Table 1. Daily Mean of Tropospheric Columnar NO2 (1015 molecules/cm2) with Relative Changes (%)
Location
Month
2018
2019
A
B
Delhi
April
4.73
4.96
-65.5
-73.3
May
5.32
4.94
-35.7
-26.0
Average
5.03
4.95
-48.0
-45.6
Dhaka
April
5.06
4.03
-47.2
-33.7
May
3.69
2.93
-34.8
-18.1
Average
4.36
3.47
-41.0
-25.9
Kathmandu
April
2.48
2.26
-11.3
-2.5
May
2.18
2.83
-6.1
-27.5
Average
2.33
2.55
-8.7
-15.0
Kolkata
April
3.36
3.16
-18.4
-13.4
May
3.15
2.78
-31.0
-21.9
Average
3.25
2.97
-24.7
-17.6
Lahore
April
4.49
4.03
-44.4
-38.1
May
6.36
5.22
-27.6
-11.9
Average
5.44
4.64
-36.0
-25.0
Note: A=2020 vs 2018; B=2020 vs 2019
The reduction in Kathmandu may have occurred
because of wildfires in the first half of April, open
garbage burning, and cross border pollution haze
(Nepal Times, 2020). Thermal inversions trap
pollutants during the winter season, making conditions
worse in this valley (Mahapatra et al., 2019).
Atmospheric NO2 concentration has decreased
in some developed countries during the COVID-19
outbreak. The readings from the Copernicus Sentinel-
5P satellite showed a significant decrease of
tropospheric columnar NO2 concentrations during
lockdown over Rome, Madrid, and Paris (Zambrano et
al., 2020). The most substantial reduction of NO2 was
estimated at 51% in Barcelona (Tobías et al., 2020).
Dhaka, Bangalore, Beijing, Bangkok, Delhi, and
Nanjing experienced lower tropospheric columnar
NO2. Several major trade centers such as New York,
London, Paris, Seoul, Sydney, and Tokyo experienced
reduced atmospheric NO2 levels (Roy et al., 2020,
Shrestha et al., 2020). The Tukey post hoc test, as
Majumder AK et al. / Environment and Natural Resources Journal 2021; 19(X): xx-xx
shown in Table 2, displays the significant changes in
the daily tropospheric columnar NO2 data in 2020. The
mean differences are significantly lower (at α=0.01
level) in 2020 compared to 2018 and 2019 for the same
period for all selected cities. Major cities of all
selected countries are shown in Figure 3 comparing
satellite measurements of background tropospheric
columnar NO2, supplied by OMI in 2018-2020.
Analyses show that the tropospheric columnar NO2
concentration reduced significantly during the
lockdown. Combustion processes such as diesel and
gasoline combustion from road traffic, manufacturing,
power generation, and shipping industry release urban
NO2 (Tobías et al., 2020); most of these sectors ceased
or reduced operations during the lockdown. In India,
the average concentrations of tropospheric columnar
NO2 decreased by 45.99% in industrial areas and
50.61% in traffic-dominated locations (Mahato et al.,
2020).
Table 2. Summary of Tukey’s post hoc multiple comparisons between tropospheric columnar NO2 and years
Location
(I) Year
(J) Year
Mean difference (I-J)
Std. Error
Delhi
2020
2018
-1.63a
0.09
2019
-1.55a
0.09
Dhaka
2020
2018
-1.83a
0.14
2019
-0.94a
0.14
Kathmandu
2020
2018
-0.21b
0.07
2019
-0.43a
0.07
Kolkata
2020
2018
-0.80a
0.06
2019
-0.52a
0.06
Lahore
2020
2018
-1.81a
0.18
2019
-1.07a
0.18
a The mean difference is significant at α=0.001
b The mean difference is significant at α=0.01
3.2 Concentration of PM2.5
Vehicle emissions, biomass burning, brick
kilns, and construction activities generate PM2.5,
defined as fine particulate matter less than 2.5
microns. Many of these emission sectors were shut
down worldwide during the COVID-19 induced
lockdown. The whisker box plots in Figure 4 shows
that Delhi, Dhaka, and Kathmandu had higher
pollution levels in 2019 compared to 2018, showing
the decreasing trend of PM2.5 during the lockdown in
five megacities of South Asia. During lockdown in
2020, the pollution level decreased noticeably in all
the selected cities compared to the previous two years.
Figure 3. Spatial distribution of tropospheric columnar NO2 in Delhi (76.709N, 28.1139E, 77.709 N, 29.1139E); Dhaka (89.9201N
23.308E 90.9201N 24.308E); Kathmandu (84.824N 27.2172E 85.824N 28.2172E); Kolkata (87.9001N 22.0667E 88.9001N 23.0667E)
and Lahore (73.8436N 31.0497E 74.8436N 32.0497E) from 2018-2020 (Average of April-May)
Majumder AK et al. / Environment and Natural Resources Journal 2021; 19(X): xx-xx
Figure 3. Spatial distribution of tropospheric columnar NO2 in Delhi (76.709N, 28.1139E, 77.709 N, 29.1139E); Dhaka (89.9201N
23.308E 90.9201N 24.308E); Kathmandu (84.824N 27.2172E 85.824N 28.2172E); Kolkata (87.9001N 22.0667E 88.9001N 23.0667E)
and Lahore (73.8436N 31.0497E 74.8436N 32.0497E) from 2018-2020 (Average of April-May) (cont.)
The daily mean of PM2.5 concentration in five
cities from 2018-2020 is in Table 3. Delhi’s air
contained 72.02, 83.74, and 45.69 µg/m3 of PM2.5 in
2018, 2019, and 2020 from April 1 - May 31. PM2.5
concentration decreased during the COVID-19 period
in 2020 in Delhi, reducing 36.6% compared to 2018
and 45.4% compared to 2019. Nagar et al. (2017)
found the PM2.5 levels in Delhi resulted from a regional
problem caused by contiguous urban agglomerations.
In Dhaka, the mean concentration was 56.91
µg/m3 in 2018, 64.93 µg/m3 in 2019, and 49.70 µg/m3
in 2020 from April 1 - May 31. The PM2.5
concentration reduced by 12.7% compared to 2018
and 23.5% compared to 2019 during the lockdown
in those months. Dhaka experienced less PM2.5
reduction than other cities because construction of the
Mass Rapid Transit (MRT) continued during COVID-
19 lockdown (Nayeem et al., 2020). Other factors may
have been meteorological characteristics (Mofijur et
al., 2020), higher population density, greater
dependence on fossil fuel for cooking, and reopening
of industry. Market and shopping malls were open,
allowing private vehicle movement inside the city
(Nayeem et al., 2020).
In Kolkata, the daily concentration of PM2.5 in
2020 decreased by 41.0% compared to 2018 and
34.1% relative to 2019. The PM2.5 in Kathmandu was
28.3% less in 2020 than in 2018 and 37.4% less than
in 2019. The Kathmandu valley geography causes
large diurnal variability in temperature and relative
humidity resulting in a corresponding gas-aerosol
phase partitioning of NH3, HNO3, and HCl and aerosol
solution affecting the pH (Islam et al., 2020).
In Lahore, only a comparison with the
concentration of 2019 was available. PM2.5 decreased
by 44.26% in 2020 compared to 2019, more than in
other cities. The PM2.5 reduction in Delhi and Kolkata
was more than in other cities during the lockdown. The
restriction in social contact, the closing of restaurants,
shops, and many commercial and administrative
centers, reduced these air pollutants.
Majumder AK et al. / Environment and Natural Resources Journal 2021; 19(X): xx-xx
Figure 4. The whisker box plot shows the daily average of ground-level PM2.5 (µg/m3) concentration. A horizontal black line marks the
median. The lower boundary of the box indicates the 25th percentile. The upper boundary of the box indicates the 75th percentile. The
whisker represents the maximum (upper whisker) and minimum value (lower whisker). Points above the whiskers indicate outliers.
Table 3. Daily mean of PM2.5 (µg/m3) with relative changes (%)
Location
Month
2018
2019
2020
A
B
Delhi
April
71.47
75.13
40.72
-43.03
-45.80
May
72.56
92.06
50.51
-30.39
-45.13
Average
72.02
83.74
45.69
-36.56
-45.44
Dhaka
April
70.71
70.82
52.24
-26.12
-26.24
May
43.55
59.04
46.52
-6.82
-21.21
Average
56.91
64.93
49.70
-12.67
-23.46
Kathmandu
April
58.84
50.46
47.08
-19.99
-6.70
May
40.13
62.34
24.02
-40.14
-61.47
Average
49.33
56.50
35.36
-28.32
-37.42
Kolkata
April
41.60
34.37
28.06
-32.55
-18.36
May
33.73
33.04
16.56
-50.90
-49.88
Average
37.66
33.69
22.21
-41.02
-34.08
Lahore
May
DNA
109.14
60.84
DNA
-44.26
Average
DNA
109.14
60.84
DNA
-44.26
Note: A=2020 vs 2018; B=2020 vs 2019; DNA=Data Not Available
Table 4 shows Tukey’s post hoc analysis to test
the significant changes in the daily average of PM2.5
data based on 2020 with an equal sample size. The
mean differences of daily PM2.5 concentration between
the year 2019 and 2020 during the lockdown period
were significantly lower (at α=0.01) during the same
time in Delhi, Dhaka, Kathmandu, and Kolkata. The
mean differences of daily PM2.5 concentration
between 2020 and 2018 were also significantly lower
in all those cities except Dhaka.
Figure 5 depicts the diurnal changes of PM2.5 in
selected cities from 2018-2020 at the same time of
April and May. The nighttime air pollution (8 pm-6
am) is higher than during the day in all cities except
Kolkata. Restriction of the heavy vehicle (long road
trucks) occurs only throughout the day in Delhi,
Dhaka, and Lahore year around (Nagar et al., 2017;
Nayeem et al., 2020; Rasheed et al., 2015; Gorai et al.,
2018). The primary cause of higher pollution levels at
night in these cities may be heavy vehicle traffic. Since
there is little restriction on heavy traffic in Kolkata,
PM2.5 is similar during the day and night (Bera et al.,
2020). The pollution levels increase at night in
Majumder AK et al. / Environment and Natural Resources Journal 2021; 19(X): xx-xx
Kathmandu because of the slopes and orientation of
the mountains (Mahapatra et al., 2019).
Table 5 shows the mean differences of diurnal
PM2.5 concentration between 2019 and 2020, and 2018
and 2020 were also significantly lower (at α=0.01)
according to Tukey’s post hoc comparison. During the
COVID-19 lockdown in these cities, nighttime entry
to the central city was open for these vehicles. The mean
differences were not significant at night (8 pm-6 am)
in Delhi, Dhaka, and Lahore, possibly because the
traffic conditions were similar to previous years. The
study found pollutant levels high at nighttime in the
Kathmandu valley because of the surrounding
mountains (Mahapatra et al., 2019).
Table 4. Summary of Tukey’s post hoc multiple comparisons between hourly PM2.5 and years
Location
(I) Year
(J) Year
Mean difference (I-J)
Std. Error
Delhi
2020
2018
-26.3a
4.9
2019
-38.1a
4.9
Dhaka
2020
2018
-7.2
4.6
2019
-15.2b
4.6
Kathmandu
2020
2018
-13.9b
3.9
2019
-21.2a
3.9
Kolkata
2020
2018
-15.4a
2.2
2019
-11.5a
2.2
a The mean difference is significant at α=0.001
b The mean difference is significant at α=0.01
Figure 5. Diurnal changes of PM2.5 in different cities from 2018-2020 at same time (April-May)
Table 5. Summary of Tukey’s post hoc multiple comparisons between diurnal PM2.5 and years
Location
(I) Year
(J) Year
Mean difference (I-J)
Std. Error
Delhi
Night (8 pm-6 am)
2020
2018
-11.42
4.47
2019
-4.51
4.47
Day (6 am-8 pm)
2020
2018
-35.11a
5.21
2019
-37.62a
5.21
Majumder AK et al. / Environment and Natural Resources Journal 2021; 19(X): xx-xx
Table 5. Summary of Tukey’s post hoc multiple comparisons between diurnal PM2.5 and years (cont.)
Location
(I) Year
(J) Year
Mean difference (I-J)
Std. Error
Dhaka
Night (8 pm-6 am)
2020
2018
-3.18
4.37
2019
-7.70
4.36
Day (6 am-8 pm)
2020
2018
-17.01b
5.20
2019
-14.56a
5.11
Kathmandu
Night (8 pm-6 am)
2020
2018
-9.70
3.70
2019
-6.25
3.72
Day (6 am-8 pm)
2020
2018
-17.88a
2.48
2019
-21.90a
2.49
Kolkata
Night (8 pm-6 am)
2020
2018
-15.39a
2.21
2019
-7.86a
2.17
Day (6 am-8 pm)
2020
2018
-6.74
3.39
2019
-7.36
3.28
a The mean difference is significant at α=0.001
b The mean difference is significant at α=0.01
Air pollution concentrations in the Kathmandu valley
increased gradually after sunset (Shrestha et al., 2002).
In Kolkata, the nighttime mean differences for both the
cases (2018-2020 and 2019-2020) were significantly
lower (at α=0.01). No restriction on vehicle movement
and the emission from the nearby coal power plant of
Kolkata might be the reasons for high pollution in the
daytime (Bera et al., 2020).
4. CONCLUSION
The present study found a significant reduction
of daily tropospheric columnar NO2 and PM2.5
concentrations in all the cities compared to previous
years during the same timeline.
The tropospheric columnar NO2 values were
reduced between 9% and 48% in the cities studied.
The daily mean PM2.5 values were reduced
between 13% and 46% in the cities studied.
The diurnal pattern of PM2.5 showed
significant improvement of between 15% and 38%
during the day in Delhi, Dhaka, and Kathmandu due
to traffic restrictions.
Abatement of tropospheric columnar NO2 and
PM2.5 occurred because of the restrictive actions
imposed to reduce the population's mobility and shut
down many commercial establishments and industries.
The temporary decrease in the concentrations of
pollutants is not a sustainable way to improve the
environment. The effect of the lockdown on air
pollution provided a unique opportunity to analyze the
effects of various emission sources and further assess
air quality policies. Traffic was significantly less
during the lockdown in each of the selected cities. Air
quality can be improved by increasing mass transit or
restricting vehicles in certain areas of each city. The
closing of companies resulted in emissions reduction
from manufacturing and industrial facilities.
Introducing more fuel-efficient transportation systems
and improved pollution strategies for industries would
improve air quality permanently. Improvement in
industrial emission standards could assist in these
cities reaching similar air quality during normal
operations. This study was not able to compare
overpass sensor data to tropospheric columnar NO2
sensor data. In addition, a single monitoring station of
PM2.5 cannot represent an entire city. This study
indicates the relative impact on tropospheric columnar
NO2 and PM2.5 resulting from the COVID-19
lockdown.
ACKNOWLEDGEMENTS
The authors acknowledge the AirNow for
providing the PM2.5 data that measured from its
measuring station on an hourly basis under the Real-
time Air Quality Index project. The authors also
gratefully acknowledge the members of the nitrogen
dioxide group of the NASA science team for providing
the daily tropospheric columnar NO2 of the selected
cities. The researchers did not receive any external
funds or grants for this study.
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