Counterfactual time series analysis of short-term change in air pollution following the COVID-19 state of emergency in the United States.

ABSTRACT: Lockdown measures implemented in response to the COVID-19 pandemic produced sudden behavioral changes. We implement counterfactual time series analysis based on seasonal autoregressive integrated moving average models (SARIMA), to examine the extent of air pollution reduction attained following state-level emergency declarations. We also investigate whether these reductions occurred everywhere in the US, and the local factors (geography, population density, and sources of emission) that drove them. Following state-level emergency declarations, we found evidence of a statistically significant decrease in nitrogen dioxide (NO₂) levels in 34 of the 36 states and in fine particulate matter (PM_2.5) levels in 16 of the 48 states that were investigated. The lockdown produced

SUBMITTER: Dey T 

PROVIDER: S-EPMC8651777 | biostudies-literature | 2021 Dec

REPOSITORIES: biostudies-literature