Department of Earth and Atmospheric Sciences, National Institute of Technology Rourkela, Rourkela 769008, Odisha, India.
Leipzig Institute for Meteorology (LIM), Leipzig University, Stephanstrasse 3, 04103 Leipzig, Germany.
Environ Pollut. 2021 Feb 15;271:116354. doi: 10.1016/j.envpol.2020.116354. Epub 2020 Dec 22.
The present study investigates the air pollution pattern over India during the COVID-19 lockdown period (24 March-31 May 2020), pre-lockdown (1-23 March 2020) and the same periods from 2019 using Moderate Resolution Imaging Spectroradiometer (MODIS) Terra aerosol optical depth (AOD) with level 2 (10 km × 10 km) and level 3 (1° × 1° gridded) collection 6.1 Dark Target Deep Blue (DT-DB) aerosol product the Tropospheric Monitoring Instrument (TROPOMI) NO and SO data with a spatial resolution of 7 km × 3.5 km. We also use long-term average (2000-2017) of AOD for March-May to identify existing hotspot regions and to compare the variations observed in 2019 and 2020. The aim of the present work is to identify the pollution hotspot regions in India that existed during the lockdown and understanding the future projection scenarios reported by previous studies in light of the present findings. We have incorporated Menn-Kendall trend analysis to understand the AOD trends over India and percentage change in AOD, NO and SO to identify air pollution pattern changes during the lockdown. The results indicate higher air pollution levels over eastern India over the coal-fired power plants clusters. By considering the earlier projected studies, our results suggest that eastern India will have higher levels of air pollution, making it a new hotspot region for air pollution with highest magnitudes.
本研究调查了 COVID-19 封锁期间（2020 年 3 月 24 日至 5 月 31 日）、封锁前（2020 年 3 月 1 日至 23 日）和 2019 年同期印度的空气污染模式，使用了中分辨率成像光谱仪（MODIS）Terra 气溶胶光学深度（AOD），具有 2 级（10km×10km）和 3 级（1°×1°网格化）收集 6.1 暗目标深蓝天（DT-DB）气溶胶产品，对流层监测仪（TROPOMI）NO 和 SO 数据具有 7km×3.5km 的空间分辨率。我们还使用 AOD 的长期平均值（2000-2017 年），用于识别 3 月至 5 月的现有热点地区，并比较 2019 年和 2020 年观察到的变化。本工作的目的是识别印度在封锁期间存在的污染热点地区，并根据本研究结果了解先前研究报告的未来预测情景。我们已经将 Menn-Kendall 趋势分析纳入其中，以了解印度上空 AOD 的趋势以及 AOD、NO 和 SO 的百分比变化，以识别封锁期间的空气污染模式变化。结果表明，印度东部煤炭发电厂集群上空的空气污染水平较高。考虑到先前预测的研究，我们的结果表明，印度东部将有更高水平的空气污染，使其成为空气污染的新热点地区，空气污染程度最高。
