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Estimating Climate Impact on Population-Weighted Airborne Particulate Matter Concentrations in California during Extreme Events
Abdullah Mahmud (1) Mark Hixson (1) Zhan Zhao (1) Shu-Hua Chen (1) Michael J. Kleeman (1)
(1) University of California, Davis
Abstract Number: 523
Last modified: May 13, 2010
Preference: Platform Presentation
Working Group: Urban Aerosols
Abstract
The climate change effect on population-weighted concentrations of particulate matter (PM) was studied using the Parallel Climate Model (PCM), the Weather Research and Forecasting (WRF) model and the UCD/CIT 3-D photochemical air quality model. A “business as usual” climate emissions scenario was dynamically downscaled for the entire state of California between the years 2000-06 and 2047-53. Air quality simulations were carried out for 1008 days in each of the present-day and future climate conditions using emissions at 2000 level. Population-weighted 24-hr average concentrations of PM$_(0.1), PM$_(2.5), and PM$_(10) total mass, components species, trace metal and primary source contributions during extreme events were calculated for California and three air basins: the Sacramento Valley air basin (SV), the San Joaquin Valley air basin (SJV) and the South Coast Air Basin (SoCAB).
Extreme PM concentrations were examined by calculating the average concentration on the 10 most heavily polluted days during present and future climate conditions (99th percentile concentrations). Extreme PM2.5 total mass was predicted to be ~20 micro-gram m$^(-3) higher in the future compared to the present-day in the SJV and SV. Predicted extreme population-weighted PM$_(2.5) and PM$_(10) concentrations for total mass and almost all components and primary source contributions increased in the future vs. present climate in the SV and SJV. Statewide extreme population-weighted PM$_(2.5) primary diesel concentrations were higher in the future due to the effects of climate change, while PM$_(2.5) primary shipping concentrations decreased. These trends reflect the increased strength of future stagnation episodes which trap pollutants close to the locations where they were emitted.
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