Particulate Matter Prediction and Source Attribution for U.S. Air Quality Management in a Changing World

Donald J. Wuebbles, University of Illinois at Urbana-Champaign

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Xin-Zhong Liang, Donald J. Wuebbles, Robert Rauber, Chao Sun, David New, Hao He, Swarnali Sanyal, Vitaly Kholodovsky, Jun Zhang

In this project, we are studying how projected global changes in climate and emissions could affect the U.S. air quality, focusing on fine particulate matter and ozone, including effects on their future trends and quantifying key source attribution. We are using state-of-the-science dynamic prediction system that couples global climate-chemical transport model with regional climate-air quality models over North America, to determine individual and combined impacts of global climate and emissions changes on U.S. air quality, including uncertainty evaluation, from the present to 2050 under multiple climate and emission scenarios. We are using the allocation to do the long-term global climate chemistry runs using the Community Earth System Model CESM1.2.2 with fully coupled chemistry using CAM5-chem at 0.9° x 1.25° horizontal resolution. Regional modeling system includes coupled CWRF and CMAQ models to downscale the regional climate and simulate the U.S. air quality at present-day period and future 2050s (RCP4.5 and RCP8.5) scenarios. The results from the global and regional model simulations for the past are evaluated with observational data to evaluate the capabilities of the model simulation and impacts of emissions change, climate change, and long-range transport on future U.S. air pollution will be investigated.