High-Resolution PM_2.5 and Ozone (O₃) Estimates and the Impacts on Human Health and Crop Yields Across Sichuan Basin During 2015–2021

Despite stringent national clean air policies, severe PM_2.5 and ozone (O₃) pollution persists in some parts of China, notably the Sichuan Basin—a key economic zone in the southwest. High-resolution assessment of the health and crop impacts of these pollutants remains limited in this region. In this study, we developed a multi-source data fusion framework based on a machine learning model to reconstruct daily PM_2.5 and O₃ concentrations at 1 km resolution during 2015–2021. The model integrates ground observations, meteorological data, chemical transport model outputs, and satellite retrievals. The model performed robustly, achieving R² values of 0.91 for PM_2.5 and 0.64 for O₃. PM_2.5 exhibited a decreasing tendency after 2017, while O₃ showed interannual variability, with peaks in 2016 and 2018. Spatially, PM_2.5 was more concentrated in urban centers, whereas O₃ showed higher levels in western Sichuan and a banded pattern in the east. Seasonal patterns were also evident: PM_2.5 increased in autumn and winter due to meteorological and emission factors, while O₃ peaked in spring and summer, driven by photochemistry and high temperatures. Topography and emissions further shaped these distributions, with mountains in the west trapping O₃ and urban clusters exacerbating PM_2.5. Based on the reconstructed dataset, we further explored the potential impacts of pollutant exposure on human health and crop yields. The results provide a high-resolution dataset for understanding pollutant variability.