Spatiotemporal distribution of oxidative potential in PM_2.5 and its key components across six Chinese cities

Increasing evidence has supported that oxidative potential (OP) serves as a crucial indicator of health risk of exposure to PM_2.5 over mass concentration. However, there is a lack of comparative studies across multiple cities, particularly on a fine temporal scale. In this study, we aim to investigate daily variation of ambient PM_2.5 OP through simultaneous samplings in six Chinese cities for one year. Results showed that more than 60 % of the sampling days exhibited non-zero ranking difference between volume-normalized oxidative potential (OPv) and mass concentration among the six cities. Key components contributing to OPv inculde Mn, NO₃^-, and K⁺, followed by Ca²⁺, Al, SO₄^2-, Cl^-, Fe, and NH₄⁺. Based on these chemical components, we developed a stepwise multivariable linear regression model (R²: 0.71) for OPv prediction. The performance of the model is comparable to both species- and sources-based ones in the literature. These findings suggest that a relatively lower daily-averaged mass concentration of PM_2.5 does not necessarily indicate a lower oxidative risk. Future studies and policy developments on health benefits should also consider OPv rather than mass concentration alone. Priority could be given to sources/species that contribute significantly to oxidative potential of ambient PM_2.5. SYNOPSIS: This study highlights inclusion of oxidative potential as a complementary metric for air pollution assessment and control.