An Assessment of Uncertainty in Projections of Climate-Induced Changes to U.S. O3 Pollution

Abstract:

We have generated an ensemble simulation of 21st century climate change with over 3,000 years of modeled air quality to explore major sources of uncertainty in projections of climate-induced change to surface O₃ over the US. Using the Community Atmosphere Model with Chemistry (CAM-Chem) coupled to the MIT Integrated Global System Model (IGSM-CAM), we are able to evaluate and compare how the three main drivers of uncertainty in climate simulations, emissions scenario, model response and natural variability, propagate to estimates of O₃ concentrations. Our simulations of atmospheric chemistry in 2050 and 2100 under three different socioeconomic scenarios, suggest that the climate penalty on US O₃ pollution may be substantial (> 5 ppb) under a business-as-usual case. These projections also reveal that greenhouse gas mitigation policies can significantly lessen these impacts. However, large uncertainties in climate models beyond emissions scenario strongly propagate to simulated O₃ concentrations. Our results from hundreds of years of simulated air quality under multiple model initializations show that truly isolating the impact of anthropogenic-forced climate change requires multidecadal simulations (>15 years) and natural variability can largely mask climate-induced changes to surface O₃ projected prior to 2050, under greenhouse gas mitigation, or for specific regions of the US. Similarly the effect of climate model response, largely ignored in air quality impact assessments, is evaluated by applying different values of climate sensitivity (2.0 - 4.5˚C) within the ensemble. Here again, projected impacts of climate change on O₃ are shown to be largely dependent on the magnitude of model response beyond greenhouse gas emissions scenario. Finally, we discuss how uncertainty in air quality projections may further propagate to estimates of health and economic impacts, as well as the implications for cost-benefit climate policy analyses.