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Environmental issues are becoming one of the main topics of concern forsociety, and the quality of air is closely linked to people's lives. Previousstudies have examined the effects of abrupt interventions on changes in airpollution. For example, researchers used an interrupted time series design toquantify the impact of the 1990 Dublin coal ban; and a regression discontinuityto determine the arbitrary spatial impact of the Huaihe River policy in China.An important feature of each of these studies is that they investigated abruptand localized changes over relatively short time spans (the Dublin coal ban)and spatial scales (the Huaihe policy). Due to the abrupt nature of theseinterventions, defining a hypothetical experiment in these studies isstraightforward. In response to the novel coronavirus outbreak, Chinaimplemented 'the largest quarantine in human history' in Wuhan on January 23,2020. Similar measures were implemented in other Chinese cities. Since then,the movement of people and associated production and consumption activitieshave been significantly reduced. This provides us with an unprecedentedopportunity to estimate the changes in air pollution brought about by thissudden "silent" move. We speculate that the initiative will lead to asignificant reduction in regional air pollution. Thus, we performedcounterfactual time series analysis on Wuhan air quality data from 2017-2022based on three models, SARIMA, LSTM and XGBOOST, and compared the excellence ofdifferent models. Finally, we conclude that 'silent' measures willsignificantly reduce air pollution. Using this conclusion to furtherinvestigate the extent of air pollution reduction will help the country tobetter designate environmental policies.

Counterfactual time series analysis for the air pollution during the outbreak of COVID-19 in Wuhan