Improvement in air quality and its impact on land surface temperature in major urban areas across India during the first lockdown of the pandemic

Abstract

The SARS CoV-2 (COVID-19) pandemic and the enforced lockdown have reduced the use of surface and air transportation. This study investigates the impact of the lockdown restrictions in India on atmospheric composition, using Sentinel-5Ps retrievals of tropospheric NO₂ concentration and ground-station measurements of NO₂ and PM_2.5 between March-May in 2019 and 2020. Detailed analysis of the changes to atmospheric composition are carried out over six major urban areas (i.e. Delhi, Mumbai, Kolkata, Chennai, Bangalore, and Hyderabad) by comparing Moderate Resolution Imaging Spectroradiometer (MODIS) Aerosol Optical Depth (AOD) and land surface temperature (LST) measurements in the lockdown year 2020 and pre-lockdown (2015-2019). Satellite-based data showed that NO₂ concentration reduced by 18% (Kolkata), 29% (Hyderabad), 32-34% (Chennai, Mumbai, and Bangalore), and 43% (Delhi). Surface-based concentrations of NO₂, PM_2.5, and AOD also substantially dropped by 32-74%, 10-42%, and 8-34%, respectively over these major cities during the lockdown period and co-located with the intensity of anthropogenic activity. Only a smaller fraction of the reduction of pollutants was associated with meteorological variability. A substantial negative anomaly was found for LST both in the day (-0.16 °C to -1 °C) and night (-0.63 °C to -2.1 °C) across select all cities, which was also consistent with air temperature measurements. The decreases in LST could be associated with a reduction in pollutants, greenhouse gases and water vapor content. Improvement in air quality with lower urban temperatures due to lockdown may be a temporary effect, but it provides a crucial connection among human activities, air pollution, aerosols, radiative flux, and temperature. The lockdown for a shorter-period showed a significant improvement in environmental quality and provides a strong evidence base for larger scale policy implementation to improve air quality.

Keywords: AOD; Atmospheric pollutants; LST; Net radiative flux; Water vapor.

Fig. 1

Present anomlay of mean tropospheric NO₂ concentration during effective lockdown period (i.e. 24th March–18th May) in 2020 across India and in six large cities.

Fig. 2

Box plots showing the percentage anomalies in NO₂ and PM_2.5 concentration measured from surface stations in six cities. The bars show the mean and the cross the median values derived from the average daily concentrations.

Fig. 3

Percentage change in ERA-5 meteorological variables in 2020 relative to the average over the period 2015–19 (i.e. March–May). (A) relative humidity, (B) wind speed at 1000 hPa pressure level, (C) boundary-layer height, and (D) precipitation. In B) the overlaid wind direction is that from 2020.

Fig. 4

Present standardized AOD anomaly during 24th March–18th May across India and over six cities against the demi-decadal mean over the same time period for the years 2015–19.

Fig. 5

Standardized (a) night-time MODIS LST and (b) day-time MODIS LST anomalies (°C) during 2020 (24th March–18th May) against the demi-decadal mean for the years 2015–19. The histogram showing distribution of positive and negative pixels.

Fig. 6

Standardized night-time LST anomalies (°C) during 2020 (24th March–18th May) over (a) Delhi, (b) Mumbai, (c) Kolkata, (d) Bangalore, (e) Chennai, and (f) Hyderabad city. A 20-km buffer has been applied from the city boundary.

Fig. 7

Standardized day-time LST anomalies (°C) during 2020 (24th March–18th May) over (a) Delhi, (b) Mumbai, (c) Kolkata, (d) Bangalore, (e) Chennai, and (f) Hyderabad city. A 20-km buffer has been applied from the city boundary.

Fig. 8

Ground-station standardized air temperature anomalies (Tmax and Tmin in °C) from daily average measurements in 2020 (24th March–18th May) over each city.

Fig. 9

Present standardized net radiative flux anomalies at top of the atmosphere (TOA) and surface (All-sky and clear-sky condition) during 2020 against the demi-decadal mean 2015–19 (i.e. April–May) for each city.