Development of an emission-driven box model to diagnose ozone formation sensitivity

Abstract

Surface ozone (O₃) pollution affects air quality, human health, and the ecosystem. Understanding the complex non-linear relationship between ozone formation and its precursors, nitrogen oxides (NO_x), and volatile organic compounds (VOCs) is critical for policymakers to mitigate the pollution. The Empirical Kinetic Modeling Approach (EKMA) based on classical observation-constrained zero-dimension box model provides the sensitivity of ozone production to precursor concentrations instead of emissions. This makes the box-model EKMA hard to apply in a real emission reduction scenario. Here, we developed an alternative box model approach driven by localized emissions, which are derived from the field-observed concentrations. This model approach reproduced the O₃ variations well by capturing the short-term changes of NO_x and AVOCs emissions among different phases of pollution control during the 31st World University Games in Chengdu in 2023. The EKMA analysis based on this model approach showed a different O₃ response to precursor reductions from the concentration-constrained approach, which overestimated the baseline of O₃ concentration. The result from the EKMA analysis demonstrated that the O₃ level was most sensitive to NO_x due to stringent control strategies during the event and rapidly rebounded to almost VOC-limited regime after the event. The effects of VOCs reduction on O₃ control examined by concentration-constrained model approach were less pronounced than those by emission-driven approach due to the lack of consideration of the emission-to-reaction process. Our findings suggest that the emission-driven box model is applicable for developing O₃ control strategy in the local scale.