COVID lockdowns significantly affect statewide atmospheric fine aerosols in India after excluding long-term pollution patterns and time-lag effect

Abstract

Atmospheric fine particulate matter (PM2.5 , near-surface concentrations when size is ≤ 2.5 μm) affects global climate and human health. India alone accounts for a quarter of the global PM2.5-related health burden. Studies in India, mostly in urban areas, have reported significant declines in PM2.5 concentrations because of COVID-19 lockdown. These studies did not consider the long-term PM2.5 patterns and time-lag effect (inter yearly variations in PM2.5 concentrations carried forward from one period to another due to interannual shifts in meteorological conditions). Since the studies focused primarily on urban areas, not covering rural/remote areas where pollution may rise during lockdown, it is still unclear what impact lockdown had on statewide pollution levels in (AODf India. Here, we examine whether significant changes in fine-mode aerosol optical depth : columnar PM2.5 ) occurred statewide across India because of lockdown after excluding the confounding variables. We found a substantial decrease in AODf in a few (28%) states/territories. The declines were significant (ANCOVA; α = 0.05) in some Northeastern states/territories: Sikkim (29%), Arunachal Pradesh (24%), Nagaland (5%), Mizoram (4%) and Uttarakhand (3%). However, in most states/territories, AODf increased significantly because of lockdown. The lockdown-associated hardship caused more people to rely on polluting cooking fuels, thereby increasing residential emissions, particularly in rural areas. At city-level, we found significant reductions in near-surface PM2.5 concentrations due to lockdown. These declines were comparable or greater than previously reported. Also, there were significant reductions in AODf (PM2.5 concentrations) at state (city) levels resulting from previous environmental intervention measures. If not accounted, previous environmental intervention measures can significantly bias lockdown effect estimates in India.