The Impact of COVID-19 Lockdown on Ambient Air Quality in Shanghai, 2022

Abstract

The COVID-19 lockdown contributes to the improvement of air quality. Most previous studies have attributed this to the reduction of human activity while ignoring the meteorological changes, this may lead to an overestimation or underestimation of the impact of COVID-19 lockdown measures on air pollution levels. To investigate this issue, we propose an XGBoost-based model to predict the concentrations of PM2.5 and PM10 during the COVID-19 lockdown period in 2022, Shanghai, and thus explore the limits of anthropogenic emission on air pollution levels by comprehensively employing the meteorological factors and the concentrations of other air pollutants. Results demonstrate that actual observations of PM2.5 and PM10 during the COVID-19 lockdown period were reduced by 60.81% and 43.12% compared with the predicted values (regarded as the period without the lockdown measures). In addition, by comparing with the time series prediction results without considering meteorological factors, the actual observations of PM2.5 and PM10 during the lockdown period were reduced by 50.20% and 19.06%, respectively, against the predicted values during the non-lockdown period. The analysis results indicate that ignoring meteorological factors will underestimate the positive impact of COVID-19 lockdown measures on air quality.

Impact of COVID-19 Restrictions Liberalization on Air Quality: A Case Study of Chongqing, Southwest China

“…These studies revealed varying degrees of decrease in PM 2.5 , PM 10 , NO 2 concentrations among different cities globally during periods of restrictive policies. For instance, observed PM 2.5 and PM 10 concentrations decreased by approximately 60.81% and 43.12%, respectively, compared to predicted values during the restriction period in Shanghai; whereas considering only anthropogenic factors without accounting for meteorological in uences resulted in decreases of around 50.20% for PM 2.5 and 19.06% for PM 10 (Zhang et al, 2023b). In Beijing, observed PM 2.5 , PM 10 , and NO 2 concentrations exhibited reductions of 39.4%, 50.1%, and 43.1%, respectively, during the restriction period.…”

“…These data were sourced from the historical records of the online air quality monitoring and analysis platform (www.aqistudy.cn/historydata/), including AQI, PM 2.5 , PM 10 , NO 2 , and O 3 . The daily AQI, which is a dimensionless relative value used to indicate the level of air pollution on a given day (Zhang et al, 2023b). For PM 2.5 , PM 10 , and NO 2 concentrations, average values from 24-hour monitoring data were employed; while for O 3 levels, daily 8-hour moving averages were used.…”