Revisiting the impact of temperature on ground-level ozone: A causal inference approach

It has been widely acknowledged that high temperatures and heatwaves promote ozone concentration, worsening the ambient air quality. However, temperature can impact ozone via multiple pathways, and quantifying each path is challenging due to environmental confounders. In this study, we frame the problem as a treatment-outcome issue and utilize a machine learning-aided causal inference technique to disentangle the impact of temperature on ozone formation. Our approach reveals that failing to account for the covariations of solar radiation and other meteorological factors leads to an overestimation of the O₃-temperature response. Through process evaluation, we find that temperature influences local ozone formation mainly by accelerating chemical reactions and enhancing precursor production and changing boundary layer heights. The O₃ response to temperature via enhancing soil NO_x and changing relative humidity and wind field is however observable. A better appreciation of O₃-temperature response is critical for improving air quality regulation in the warming future.