The mechanisms and meteorological drivers of the summertime ozone–temperature relationship

Surface ozone (inline-formulaO₃) pollution levels are strongly correlated with daytime surface temperatures, especially in highly polluted regions. This correlation is nonlinear and occurs through a variety of temperature-dependent mechanisms related to inline-formulaO₃ precursor emissions, lifetimes, and reaction rates, making the reproduction of temperature sensitivities – and the projection of associated human health risks – a complex problem. Here we explore the summertime inline-formulaO₃–temperature relationship in the United States and Europe using the chemical transport model GEOS-Chem. We remove the temperature dependence of several mechanisms most frequently cited as causes of the inline-formulaO₃–temperature “climate penalty”, including PAN decomposition, soil inline-formulaNO_x emissions, biogenic volatile organic compound (VOC) emissions, and dry deposition. We quantify the contribution of each mechanism to the overall correlation between inline-formulaO₃ and temperature both individually and collectively. Through this analysis we find that the thermal decomposition of PAN can explain, on average, 20 % of the overall inline-formulaO₃–temperature correlation in the United States. The effect is weaker in Europe, explaining 9 % of the overall inline-formulaO₃–temperature relationship. The temperature dependence of biogenic emissions contributes 3 % and 9 % of the total inline-formulaO₃–temperature correlation in the United States and Europe on average, while temperature-dependent deposition (6 % and 1 %) and soil inline-formulaNO_x emissions (10 % and 7 %) also contribute. Even considered collectively these mechanisms explain less than 46 % of the modeled inline-formulaO₃–temperature correlation in the United States and 36 % in Europe. We use commonality analysis to demonstrate that covariance with other meteorological phenomena such as stagnancy and humidity can explain the bulk of the remainder of the inline-formulaO₃–temperature correlation. Thus, we demonstrate that the statistical correlation between inline-formulaO₃ and temperature alone may greatly overestimate the direct impacts of temperature on inline-formulaO₃, with implications for the interpretation of policy-relevant metrics such as climate penalty.