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Fine particulate matter with aerodynamic diameters ≤2.5 µ m (PM 2.5) has adverse effects on human health and the atmospheric environment. The estimation of surface PM 2.5 concentrations has made intensive use of satellite-derived aerosol products. However, it has been a great challenge to obtain high-quality and high-resolution PM 2.5 data from both ground and satellite observations, which is essential to monitor air pollution over small-scale areas such as metropolitan regions. Here, the space–time extremely randomized trees (STET) model was enhanced by integrating updated spatiotemporal information and additional auxiliary data to improve the spatial resolution and overall accuracy of PM 2.5 estimates across China. To this end, the newly released Moderate Resolution Imaging Spectroradiometer Multi-Angle Implementation of Atmospheric Correction AOD product, along with meteorological, topographical and land-use data and pollution emissions, was input to the STET model, and daily 1 km PM 2.5 maps for 2018 covering mainland China were produced. The STET model performed well, with a high out-of-sample (out-of-station) cross-validation coefficient of determination (R2) of 0.89 (0.88), a low root-mean-square error of 10.33 (10.93) µ g m -3 , a small mean absolute error of 6.69 (7.15) µ g m -3 and a small mean relative error of 21.28 % (23.69 %). In particular, the model captured well the PM 2.5 concentrations at both regional and individual site scales. The North China Plain, the Sichuan Basin and Xinjiang Province always featured high PM 2.5 pollution levels, especially in winter. The STET model outperformed most models presented in previous related studies, with a strong predictive power (e.g., monthly R2=0.80), which can be used to estimate historical PM 2.5 records. More importantly, this study provides a new approach for obtaining high-resolution and high-quality PM 2.5 dataset across mainland China (i.e., ChinaHighPM 2.5), important for air pollution studies focused on urban areas. [ABSTRACT FROM AUTHOR]

Biomass burning (BB) seriously affect air pollution, human health and global climate. A severe pollution episode (PE) caused by BB was investigated in the southern Sichuan Basin (SSB), one of the most polluted areas in China. Hourly variations in criteria air pollutants (PM 2.5 , PM 10 , SO 2 , NO 2 , CO, and O 3), chemical components, and sources of PM 2.5 before, during, and after the severe regional air PE were characterized at three sites, namely Neijiang (NJ), Zigong (ZG), and Yibin (YB). The results showed that combination of intensive pollution from BB, stable meteorological conditions, and the basin topography caused this severe regional PE in the SSB. The average daily concentrations of PM 2.5 during the PE were 1.8–6 times those measured during the periods before and after the PE, and 4.0–7.4 times that of World Health Organization air quality guidelines in the SSB. The highest PM levels occurred in ZG, where the peak values of PM 2.5 and PM 10 reached 536 μg m−3 and 578 μg m−3 at night, respectively. PM 10 , NO 2 , and CO also increased dramatically at night in the SSB. O 3 formation was affected by BB, showing lower levels at night but higher levels in the day during the PE than before and after the PE, whereas SO 2 levels were not affected. Sulfate–nitrate–ammonium in PM 2.5 was the main chemical compositions before the PE, whereas organic matter (OM) and K+ became characteristics compositions during and after the PE. Higher OC/EC and K excess /EC ratios were observed during the PE and K excess /EC ratio was a better indicator of BB in the SSB than OC/EC ratio. The results of a positive matrix factorization model indicated that BB was the most significant contributor to PM 2.5 during the PE, accounting for 58% in NJ, 65% in ZG, and 56% in YB. Backward trajectory analysis confirmed that the SSB is susceptible to pollutants from Chongqing and other surrounding cities, especially in ZG and NJ, due to the unique topography of the basin. Our findings suggest that BB in the basin topography can cause severe regional air pollution events at night, thus supporting the critical need for BB control in the basin to improve regional air quality. Image 1 • The evolution of region air pollution event caused by biomass burning was observed. • PM 2.5 , PM 10 , NO 2 , and CO increased dramatically during the pollution episode. • O 3 formation was influenced by biomass burning. • Chemical components and sources variations of PM 2.5 were investigated. • The southern Sichuan Basin was susceptible to air masses from Chongqing. [ABSTRACT FROM AUTHOR]