Spatiotemporal patterns of recent PM_2.5 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 PM_2.5 (fine particulate matter with an aerodynamic diameter ≤ 2.5 μm) throughout China, and specifically in nine typical urban agglomerations and one economic region, were statistically analyzed using high-resolution ground-based PM_2.5 observations from June 2014 to May 2018. The spatial variation of PM_2.5 was also explored via spatial autocorrelation analysis. High annual mean PM_2.5 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 PM_2.5 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 PM_2.5 concentrations meeting the CAAQS Grade I 24-h standard increased in five national-level urban agglomerations, and the average annual PM_2.5 decreased from 2015 to 2017 with a reduction rate of over 20%. The southern Beijing-Tianjin-Hebei agglomeration and surrounding areas revealed the highest PM_2.5 pollution in four seasons. Monthly mean PM_2.5 typically exhibited a characteristic "U" shape. Diurnal mean PM_2.5 concentrations were generally consistent with typical urban agglomerations, with maximum and minimum PM_2.5 values occurring at approximately 08:00-12:00 and 15:00-17:00, respectively, except for the Northern Slope of Tianshan Mountain urban agglomeration (NSTM-UA) (14:00 and 08:00, respectively). A positive spatial autocorrelation of PM_2.5 concentrations was observed in all urban agglomerations (except NSTM-UA); high-high agglomeration centers of PM_2.5 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 PM_2.5 concentrations among urban agglomerations and region-oriented air pollution control strategies are highly suggested.