Spatiotemporal patterns of recent PM2.5 concentrations over typical urban agglomerations in China

China experiences severe particulate matter pollution associated with rapid economic growth and accelerated urbanization. In this study, concentrations of PM2.5 (fine particulate matter with an aerodynamic diameter <= 2.5 mu m) throughout China, and specifically in nine typical urban agglomerations and one economic region, were statistically analyzed using high-resolution ground-based PM2.5 observations from June 2014 to May 2018. The spatial variation of PM2.5 was also explored via spatial autocorrelation analysis. High annual mean PM2.5 concentrations were predominantly concentrated in the Beijing-Tianjin-Hebei, Central Plain, Northern Slope of Tianshan Mountain, and Cheng-Yu urban agglomerations, as well as the Huaihai Economic Region. The proportion of air quality nationwide monitoring sites where annual average PM2.5 concentrations exceeded the Chinese Ambient Air Quality Standards (CAAQS) Grade II annual standard were 82.8%, 77.1%, and 70.8% in 2015, 2016, and 2017, respectively. Moreover, the frequency of PM2.5 concentrations meeting the CAAQS Grade I 24-h standard increased in five national-level urban agglomerations, and the average annual PM2.5 decreased from2015 to 2017 with a reduction rate of over 20%. The southern Beijing-Tianjin-Hebei agglomeration and surrounding areas revealed the highest PM2.5 pollution in four seasons. Monthly mean PM2.5 typically exhibited a characteristic U shape. Diurnal mean PM2.5 concentrations were generally consistent with typical urban agglomerations, with maximum and minimum PM2.5 values occurring at approximately 08: 00-12: 00 and 15: 00-17: 00, respectively, except for the Northern Slope of Tianshan Mountain urban agglomeration (NSTMUA) (14: 00 and 08: 00, respectively). A positive spatial autocorrelation of PM2.5 concentrations was observed in all urban agglomerations (except NSTM-UA); high-high agglomeration centers of PM2.5 pollution were located far inland with a circular distribution, and low-low agglomeration centers formed at the periphery of the high-high agglomeration region. This study is key for understanding the difference in PM2.5 concentrations among urban agglomerations and region-oriented air pollution control strategies are highly suggested. (c) 2018 Elsevier B. V. All rights reserved.