Exploring common factors influencing PM2.5 and O3 concentrations in the Pearl River Delta: Tradeoffs and synergies

Particulate matter with an aerodynamic equivalent dimeter less than 2.5 μm (PM₂.₅) and ozone (O₃) are major air pollutants, with coupled and complex relationships. The control of both PM₂.₅ and O₃ pollution requires the identification of their common influencing factors, which has rarely been attempted. In this study, land use regression (LUR) models based on the least absolute shrinkage and selection operator were developed to estimate PM₂.₅ and O₃ concentrations in China's Pearl River Delta region during 2019. The common factors in the tradeoffs between the two air pollutants and their synergistic effects were analyzed. The model inputs included spatial coordinates, remote sensing observations, meteorological conditions, population density, road density, land cover, and landscape metrics. The LUR models performed well, capturing 54–89% and 42–83% of the variations in annual and seasonal PM₂.₅ and O₃ concentrations, respectively, as shown by the 10-fold cross validation. The overlap of variables between the PM₂.₅ and O₃ models indicated that longitude, aerosol optical depth, O₃ column number density, tropospheric NO₂ column number density, relative humidity, sunshine duration, population density, the percentage cover of forest, grass, impervious surfaces, and bare land, and perimeter-area fractal dimension had opposing effects on PM₂.₅ and O₃. The tropospheric formaldehyde column number density, wind speed, road density, and area-weighted mean fractal dimension index had complementary effects on PM₂.₅ and O₃ concentrations. This study has improved our understanding of the tradeoff and synergistic factors involved in PM₂.₅ and O₃ pollution, and the results can be used to develop joint control policies for both pollutants.