Research on the distribution and influencing factors of fine mode aerosol optical depth (AODf) in China

Abstract

Analyzing the distribution and causes of fine mode aerosol optical depth (AODf) is important for assessing the impact of air pollution on human health and sustainable development. Based on remote sensing data and station information, the study uses Theil Sen's method and the Mann-Kendall test to analyze the spatio-temporal distribution and trends of AODf. Meanwhile, the study used the Extreme Gradient Boosting (XGBoost) model and the Shapley Additive Explanations (SHAP) algorithm to analyze the spatial drivers of AODf and interactive effects. The results show a trend of an initial increase followed by a decline in AODf across China and in most city clusters, with AODf peaking around 2011. Areas with high AODf are mainly concentrated in the eastern and central regions. On a seasonal scale, the average AODf is highest in summer (0.25), followed by winter (0.23), autumn (0.21), and spring (0.19). The AODf, mainly in the eastern and central regions, showed rapid increases and decreases in the 2000–2013 and 2013–2020 periods, respectively. Secondly, the most important factor influencing AODf is sulfate (SO4), contributing 54.84%. This is followed by elevation (DEM) at 10.31%. The SO4, organic carbon (OC), and DEM to AODf are 20–54%, 10–44%, and 11–45% respectively at the city cluster level. Lastly, the response thresholds of AODf to the main factors show significant spatial heterogeneity. The thresholds for SO4 and OC to increase AODf are in the range of 5–16 μg/m3 and 1–10 μg/m3, respectively. The study is of great importance for a comprehensive understanding of the variation patterns of AODf and for the formulation of tailored air pollution control policies based on local conditions.