Abstract
Despite a growing literature on the impacts of the COVID-19 pandemic, scant evidence currently exists on its impacts on air quality. We offer an early assessment with cross-national evidence on the causal impacts of COVID-19 on air pollution. We assemble a rich database consisting of daily, sub-national level data of air quality for 164 countries before and after the COVID-19 lockdowns and we analyze it using a Regression Discontinuity Design approach. We find the global concentration of NO(2) and PM(2.5) to decrease by 5 percent and 4 percent, respectively, using data-driven optimal bandwidth selection. These results are consistent across measures of air quality and data sources and robust to various model specifications and placebo tests. We also find that mobility restrictions following the lockdowns are a possible explanation for improved air quality.