The role of urban green space landscape patterns in the synergistic prevention of PM2.5 and ozone pollution: A case study in Shenyang city, China

Abstract

Urban green space (UGS) landscape patterns can alter the spatial and temporal distributions of PM_2.5 and O₃ concentrations by affecting the source‒sink functions of pollutants. However, the role of UGS landscape patterns in the synergistic prevention of O₃ and PM_2.5 pollution has not been adequately studied, especially at the different scales. This study describes the temporal changes in PM_2.5 and O₃ concentrations in Shenyang city via long-term monitoring data from 2015 to 2020. Ridge regression and PCA were used to explore the relationships among the PM_2.5, O₃, and UGS landscape patterns across the four seasons at six scales. The results show that the PM_2.5 concentration significantly decreased as the UGS area increased (r = −0.57, p < 0.05), but the O₃ concentrations showed a nonsignificant increasing trend (r = 0.22, p = 0.51). Landscape patch index and aggregation index significantly negatively affected the PM_2.5 and O₃ concentrations in summer. In contrast, the patch density had a significantly positive effect. Our results suggest that increasing patch homogeneity and aggregation, increasing the proportion of largest patch, and reducing patch fragmentation in the UGS landscapes at 1500–2000 m scales are more favorable for the synergistic prevention of O₃ and PM_2.5 pollution. These findings provide important insights that can help urban planners mitigate air pollution.