ArticleScientific reports2021
Counterfactual time series analysis of short-term change in air pollution following the COVID-19 state of emergency in the United States.
Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- The long-term impact of Spain's 2010 Anti-Smoking Law: A counterfactual and prospective time-series analysis.AIMS public health · 2026Article
- Effect of Air Pollution Reductions on Mortality During the COVID-19 Lockdowns in Early 2020.Research report (Health Effects Institute) · 2025Article
- Alleviation of PM2.5-associated Risk of Daily Influenza Hospitalization by COVID-19 Lockdown Measures: A Time-series Study in Northeastern Thailand.Journal of preventive medicine and public health = Yebang Uihakhoe chi · 2024Article
- A decreased impact of air pollution on hospital pneumonia visits during COVID-19 outbreak in northeastern Thailand.Journal of thoracic disease · 2024Article
- Assessing the impact of COVID-19 pandemic on maternal healthcare usage: evidence from routine health data in Kenya and Ethiopia.BMJ public health · 2023Article
- Exposure to the early COVID-19 pandemic and early, moderate and overall preterm births in the United States: A conception cohort approach.Paediatric and perinatal epidemiology · 2023Article
- Artificial intelligence for improving Nitrogen Dioxide forecasting of Abu Dhabi environment agency ground-based stations.Journal of big data · 2023Article
- Quantifying diurnal changes in NOHygiene and environmental health advances · 2022Article
- Emissions of nitrogen dioxide in the northeast U.S. during the 2020 COVID-19 lockdown.Journal of environmental management · 2022Article
- A spatiotemporal analysis of NOEnvironmetrics · 2022Article
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Authors and funding
7 authors.
Funding
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 (NO
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