Historically understanding the spatial distributions of particle surface area concentrations over China estimated...

A non-parametric ensemble model was proposed to estimate the long-term (2015-2019) particle surface area concentrations (S_A) over China for the first time on basis of a vilification dataset of measured particle number size distribution. This ensemble model showed excellent cross-validation R² value (CV R² = 0.83) as well as a relatively low root-mean-square error (RMSE = 195.0 μm²/cm³). No matter in which year, considerable spatial heterogeneity of S_A was found over China with higher S_A in Beijing-Tianjin-Hebei (BTH), Yangtze River Delta (YRD), and Middle Lower Reaches of Yangtze River (MLYR). From 2015 to 2019, S_A significantly decreased in representative city clusters. The reduction rates were 140.1 μm²·cm^-3·a^-1 in BTH, 110.7 μm²·cm^-3·a^-1 in Pearl River Delta (PRD), 105.2 μm²·cm^-3·a^-1 in YRD, and 92.4 μm²·cm^-3·a^-1 in Sichuan Basin (SCB), respectively. Even though such quick reduction, high S_A (ranged from ~800 μm²/cm³ to ~1750 μm²/cm³) during the heavy pollution period (PM_2.5 > 75 μg/m³) still existed in the above-mentioned city clusters and may provide rich reaction vessels for multiphase chemistry. A dichotomy of enhanced annual 4th maximum daily 8-h average O₃ concentrations (4MDA8 O₃) and decreased S_A during summertime was found in Shanghai, a representative city of YRD. In Chengdu (SCB), increased 4MDA8 O₃ concentration was associated with a synchronous increase of S_A from 2017 to 2019. Differently, 4MDA8 O₃ concentrations enhanced in Beijing (BTH) and Guangzhou (PRD), while not significant for S_A before 2018. This work will greatly deepen our understanding of the historical variation and spatial distributions of S_A over China.