Synergistic and Trade-Off Influences of Combined PM 2.5 -O 3 Pollution in the Shenyang Metropolitan Area, China: A Comparative Land Use Regression Analysis

Fine particulate matter (PM 2.5 ) and ozone (O 3 ) are the main pollutants affecting the air quality in China, yet their common influencing factors and spatial patterns remain unclear. Focusing on the year 2020, this study adopted the least absolute shrinkage and selection operator algorithm to construct land use regression models with 34 environmental variables for the O 3 concentration at the air quality monitoring stations in the Shenyang Metropolitan Area. For comparison, PM 2.5 models had been developed in our previous work using the same approach. Model performance was satisfactory (cross-validated R 2 = 0.49–0.81 for O 3 ; 0.56–0.65 for PM 2.5 in our previous study), confirming the robustness of the approach. The results showed that: (1) Tree cover and grassland exerted synergistic, co-directional mitigation on both pollutants, whereas built-up areas and permanent water bodies were positively associated with their concentrations; (2) Longitude, elevation, and population, as well as atmospheric components such as nitrous dioxide column density and aerosol optical depth, displayed opposite effects on both pollutants, indicating trade-offs; (3) Spatially, PM 2.5 played the dominant role in shaping the pattern of combined pollution, with higher PM 2.5 levels than O 3 in nearly half of the area (46.97%), while O 3 -dominant regions were rare (4.27%) and mostly confined to localized zones. This study contributes to a deeper understanding of the synergies and trade-offs driving PM 2.5 and O 3 pollution as well as providing a scientific basis for formulating policies on integrated control measures against combined pollution.