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This repository contains data and code for counterfactual time series analysis of air pollutant concentrations in the United States.

License: MIT License

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air-pollution time-series-analysis covid-19-usa counterfactual-analysis sarima-models bootstrap

usa-covid-air-pollution-sarima-analysis's Introduction

Short-term change in air pollution following the COVID-19 state of emergency: A national analysis for the United States

This repository contains the code used for analysis in our work on the short term air pollution changes in the USA. The preprint can be found here.

Broadly speaking, the code uses bootstrapped seasonal autoregressive time series models to make counterfactual predictions for pollutant concentrations based on historical data. These predictions are compared to the the actual pollutant concentrations to estimate the corresponding change during the pandemic.

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