Journal
ATMOSPHERIC CHEMISTRY AND PHYSICS
Volume 19, Issue 20, Pages 13367-13381Publisher
COPERNICUS GESELLSCHAFT MBH
DOI: 10.5194/acp-19-13367-2019
Keywords
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Funding
- EPA STAR [RD-83522801]
- NIH [P30-ES002109]
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Surface ozone (O-3) 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 O-3 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 O-3-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 O-3-temperature climate penalty, including PAN decomposition, soil NOx emissions, biogenic volatile organic compound (VOC) emissions, and dry deposition. We quantify the contribution of each mechanism to the overall correlation between O-3 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 O-3-temperature correlation in the United States. The effect is weaker in Europe, explaining 9% of the overall O-3-temperature relationship. The temperature dependence of biogenic emissions contributes 3% and 9% of the total O-3-temperature correlation in the United States and Europe on average, while temperature-dependent deposition (6% and 1 %) and soil NOx emissions (10% and 7 %) also contribute. Even considered collectively these mechanisms explain less than 46% of the modeled O-3-temperature correlation in the United States and 36% in Europe. We use commonality analysis to demonstrate that co-variance with other meteorological phenomena such as stagnancy and humidity can explain the bulk of the remainder of the O-3-temperature correlation. Thus, we demonstrate that the statistical correlation between O-3 and temperature alone may greatly overestimate the direct impacts of temperature on O-3, with implications for the interpretation of policy-relevant metrics such as climate penalty.
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