Lockdown effects of the COVID-19 on the spatio-temporal distribution of air pollution in Beijing, China. (February 2023)

• Record Type: Journal Article
• Authors: Wu, Min; Hu, Xisheng; Wang, Zhanyong; Zeng, Xiaoying
• Is Part Of: Ecological indicators. Volume 146(2023)
• Publication Date: 2023-02
• Subjects: Transportation -- Continuous wavelet transform -- PM2.5 -- NO2; Environmental monitoring -- Periodicals; Environmental management -- Periodicals; Environmental impact analysis -- Periodicals; Environmental risk assessment -- Periodicals; Sustainable development -- Periodicals; 333.71405
• DOI: 10.1016/j.ecolind.2023.109862
• Languages: English
• ISSNs: 1470-160X

Abstract

Highlights: Spatiotemporal variations in air pollutants and their lockdown effects were explored. The diurnal variation of NO2 concentration was mainly related to the rush hours of traffic volume. PM2.5, SO2 and NO2 had four primary periods, while O3 only had two primary periods. NO2 and SO2 decreased considerably during lockdown, whereas PM2.5 and O3 increased dramatically. The contribution rates of transportation and industrial activities to the NO2, O3, air pollutants were estimated. Abstract: To prevent the spread of COVID-19, China enacted a series of strict policies, which reduced anthropogenic activities to a near standstill. This provided a precious window to explore its effects on the spatio-temporal distribution of air pollution in Beijing, China. In this study, continuous wavelet transforms and spatial interpolation methods were used to explore the spatiotemporal variations in air pollutants and their lockdown effects. The results indicate that except O3, the annual average concentration of NO2, PM2.5 and SO2 showed a decreasing trend during 2016 and 2019; NO2, PM2.5 and SO2 show a trend of "low in summer and high in winter"; the diurnal variation of NO2 concentration was mainly related to the rush hours of traffic volume, with the first peak at the morning peak (7:00), and then accumulating gradually to second peak (22:00). The continuous wavelet analysis shows that PM2.5, SO2 and NO2 had four primary periods, while O3 only had two primary periods. The high NO2 concentration areas were mainly in Dongcheng, Xicheng, Chaoyang and Fengtai, while the low concentration areas were located in the northern areas, such as Miyun and Huairou; the PM2.5 concentration decreased from south to north; this characteristic presented more obviously in winter. Compared to the pre-lockdown, NO2 and SO2 decreased considerably during lockdown, whereas PM2.5 and O3 increased dramatically. The contribution rates of transportation activities to the NO2, O3, PM2.5 and SO2 were estimated be 9.4 % ∼ 17.2 %, −76.4 % ∼ −42.9 %, −39.5 % ∼ –22.8 % and 5.7 % ∼ 43.7 %, respectively; the contribution rates of industrial activities were 19.9 % ∼ 26.7 %, 7.8 % ∼ 30.9 %, 1.6 % ∼ 36.2 % and −10.5 % ∼ 15.9 %, respectively. Considering meteorological factors, we inferred that pauses in anthropogenic activities indeed help improving air pollution, but it is difficult to offset the impact of extreme weather. These findings can enhance our understanding on the sources of air pollution, and can therefore provide insights on urban air pollution mitigation.