AUTHOR=Kong Shaojie , Wang Teng , Li Fei , Yan Jingjing , Qu Zhiguang 

TITLE=Unraveling spatiotemporal patterns and multiple driving factors of surface ozone across China and its urban agglomerations management strategies

JOURNAL=Frontiers in Ecology and Evolution

VOLUME=Volume 11 - 2023

YEAR=2023

URL=https://www.frontiersin.org/journals/ecology-and-evolution/articles/10.3389/fevo.2023.1103503

DOI=10.3389/fevo.2023.1103503

ISSN=2296-701X

ABSTRACT=Since State Council launched the Action Plan for Air Pollution Prevention and Control in 2013, China make fair performance that national concentration of fine particulate matter (PM2.5) has continued to decline, while surface ozone (O3) pollution shows an obvious rise in recent years. To identity hot regions and develop targeted policy, the spatiotemporal O3 variation and its population-weighted exposure features were analyzed in 337 cities across China, using autocorrelation analysis and grid exposure calculation. In the identified hot urban agglomerations, the correlation analysis and geographic weighted regression model (GWR) were used to study related meteorological factors and socioeconomic driving factors. Consequently, O3 pollution and its human exposure have significant spatial aggregation characteristics showing regional management policy need. And Beijing-Tianjin-Hebei Urban Agglomeration (BTH-UA), Central Plains Urban Agglomeration (CP-UA), and Yangtze River Delta Urban Agglomeration (YRD-UA) were identified as hot regions due to where O3 concentration exceed 160 μg·m-3, exceedence rate more than 20% and relatively high population-weighted exposure risk. Correlation analysis in the hot regions indicated high surface temperature, low relative humidity, and low wind speed were positive to O3 increase. Further, GWR results revealed that O3 in majority cities were positively related with population density (PD), the per capita GDP (Per_GDP), industrial soot emissions (ISE), industrial SO2 emissions (ISO2), and average annual concentration of inhaled fine particulate matter (PM10), while negatively related with total land area of administrative region (Administration) and area of green land (Green). From the regional driving factor difference, the targeted UA management policy were provided.