Abstract View
Impact of Climate Uncertainty on Projections of PM2.5 Pollution over the US
JAMES EAST, Erwan Monier, Fernando Garcia-Menendez, North Carolina State University
Abstract Number: 415
Working Group: Aerosols, Clouds and Climate
Abstract
Projections of climate change impacts on air quality show that climate and air quality are connected, beyond anthropogenic emissions, and that a warming climate can lead to a "climate penalty" on PM2.5 levels over the US. However, these projections are subject to considerable uncertainty derived from climate modeling. Despite significant advancements in understanding the role of major sources of uncertainty in climate change simulations (internal variability, greenhouse gas emissions scenario, and model response), these uncertainties have not been systematically analyzed for air quality impacts. Using a coupled climate-air quality modeling framework designed to account for these uncertainties, we simulate over 3900 years of atmospheric chemistry driven by climate projections at the beginning, middle, and end of the 21st century to assess the contribution of each source to total uncertainty in air quality projections. We show that uncertainty in PM2.5 projections due to internal variability increases slightly from beginning to end century, but is surpassed by scenario and climate model response uncertainty at mid-century. By end-century, scenario uncertainty dominates, followed by climate model response and internal variability. Uncertainty in internal variability, emissions scenario, and model response lead to US average uncertainties of 0.2, 0.5, and 0.6 ug/m3 for the PM2.5 air quality penalty at end century and reach 4.0 ug/m3 in polluted regions in the Midwest and Northeast. The climate penalty on PM2.5 increases with climate sensitivity and with less restrictive policy, reaching 2 ug/m3 under a no-policy and high climate sensitivity scenario. These results give clarity to the role of climate uncertainty in projections of PM2.5.