COVID-19 slowdown induced improvement in air quality in India: rapid assessment using Sentinel-5P TROPOMI data

Abstract

The COVID-19 lock/slow down affected humanity and livelihood, while it showed some positive effects on the environment with improvement in air quality indicators. Though many studies published after COVID-19 first phase lockdown observed reduction in pollutants over India, no studies yet compared the air quality indicators over the two lock/slow down windows during 2020–2021. This study reports results of rapid assessment of seven air quality indicators such as Nitrogen dioxide (NO₂), Sulphur dioxide (SO₂), Formaldehyde (HCHO), Methane (CH₄), Carbon monoxide (CO), Aerosol (Ultraviolet Aerosol Index, UVAI), and Ozone (O₃) for the past three years on monthly time scale using TROPOMI (Tropospheric Monitoring Instrument) data on GEE (Google Earth Engine) platform over India, with focus on the Gangetic plain, an air pollution hotspot. Significant reduction in NO₂, SO₂, HCHO and Absorbing Aerosol Index (AAI) was observed during March–May 2020 as compared to the same period in 2019, while the levels of NO₂, SO₂, HCHO and CO increased significantly in 2021 compared to March–May 2020. This suggests that COVID-19 lock/slow down in 2020 played a significant role in improving air quality indicators, while the relaxation in 2021 has led to detoriation, compared to 2020. The pyrogenic (forest fire and slash and burn agriculture) and agricultural (wet crop) sources were identified to contaminate the expression of slow/lock down effects on air quality indicators such as HCHO, CO and CH₄ over India.

Keywords:

• Sentinel-5P
• Google Earth Engine
• Indian Gangetic plain
• agro-climatic regions

Acknowledgements

MDB thanks authorities of Centre for Oceans, Rivers, Atmosphere and Land Sciences (CORAL), and Indian Institute of Technology, Kharagpur for supporting the investigation. SM thanks MeitY, Government of India, New Delhi for supporting fellowship in form of a Research project. All other Authors thank Ministry of Education, Government of India, New Delhi for providing fellowship for M.Tech study. All Authors thank the authorities of Sentinel-5P and GEE for providing data and platform for this analysis. The IARI and CPCB are thankfully acknowledged for providing ACR boundary map and air quality data. The Authors express their sincere thanks to the two anonymous reviewers who have provided very useful comments to the earlier version of the manuscript.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

These data were derived from the following resources available in the public domain: [https://developers.google.com/earth-engine/datasets/catalog/sentinel-5p].