Atmospheric particulate matter (PM) is a primary pollutant affecting urban air quality, posing increasing threats to public health and ecological environments. While urban green spaces and meteorological conditions individually influence PM pollution, the mechanisms by which meteorological indicators mediate the relationship between green space patterns and PM concentrations remain unclear. We used daily PM concentration data in the Zhengzhou Metropolitan Area (ZMA) in 2021, combined with high-resolution satellite imagery and climate monitoring data. By employing Generalized Linear Models (GLMs) and Partial Least Squares Structural Equation Modeling (PLS-SEM), we investigated the effects of green spaces and meteorological conditions on PM, highlighting the significant mediating role of key meteorological indicators in the process by which green spaces mitigate PM pollution. Results indicated that PM