4.2 Article

Variability of PM2.5 and O3 concentrations and their driving forces over Chinese megacities during 2018-2020

Journal

JOURNAL OF ENVIRONMENTAL SCIENCES
Volume 124, Issue -, Pages 1-10

Publisher

SCIENCE PRESS
DOI: 10.1016/j.jes.2021.10.014

Keywords

Air pollution; PM2.5 and O-3 trends; Meteorology; COVID-19 lockdown

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This study characterized the temporal trends of PM2.5 and O-3 concentrations in four Chinese cities and quantified the contributions of meteorological factors and gas precursors using generalized additive models (GAMS). The analysis showed that PM2.5 variability is largely influenced by precursor gases, while O-3 variability is mainly affected by meteorological conditions. The impact of the COVID-19 lockdown on PM2.5 and O-3 concentrations was also evaluated, with a significant decrease in PM2.5 but an increasing trend in O-3 during the lockdown period.
Recently, air pollution especially fine particulate matters (PM2.5) and ozone (O-3) has become a severe issue in China. In this study, we first characterized the temporal trends of PM2.5 and O-3 for Beijing, Guangzhou, Shanghai, and Wuhan respectively during 2018-2020. The annual mean PM2.5 has decreased by 7.82%-33.92%, while O-3 concentration showed insignificant variations by -6.77%-4.65% during 2018-2020. The generalized additive models (GAMS) were implemented to quantify the contribution of individual meteorological factors and their gas precursors on PM2.5 and O-3. On a short-term perspective, GAMS modeling shows that the daily variability of PM2.5 concentration is largely related to the variation of precursor gases (R = 0.67-0.90), while meteorological conditions mainly affect the daily variability of O-3 concentration (R = 0.65-0.80) during 2018-2020. The impact of COVID-19 lockdown on PM2.5 and O-3 concentrations were also quantified by using GAMS. During the 2020 lockdown, PM2.5 decreased significantly for these megacities, yet the ozone concentration showed an increasing trend compared to 2019. The GAMS analysis indicated that the contribution of precursor gases to PM2.5 and O-3 changes is 3-8 times higher than that of meteorological factors. In general, GAMS modeling on air quality is helpful to the understanding and control of PM2.5 and O-3 pollution in China. (C) 2022 The Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences. Published by Elsevier B.V.

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