Characterization and source apportionment of PM2.5 in the Southeastern United States

Monte Carlo method;Spatio-temporal correlation;Regional impacts of PM2.5 emission sources;Prescribed burning

Lee, Sangil ; Civil and Environmental Engineering

University:Georgia Institute of Technology

Department:Civil and Environmental Engineering

关键词: Monte Carlo method;    Spatio-temporal correlation;    Regional impacts of PM2.5 emission sources;    Prescribed burning;   

Others  :  https://smartech.gatech.edu/bitstream/1853/14060/1/lee_sangil_200612_phd.pdf

美国|英语

来源: SMARTech Repository

【 摘 要 】

Fine particulate matter (PM2.5) affects the environment in a variety of ways, including of human health, visibility impairment, acid deposition, and climate change. As of March, 2006, 47 counties are designated as non-attainment areas in terms of PM2.5 in the southeastern United States. State agencies with PM2.5 non-attainment counties must develop plans that demonstrate how they will achieve attainment status. State agencies also have to address emission sources of visibility impairment and develop strategies to improve visibility. It is essential to understand PM2.5 composition and sources in order to develop effective control strategies to reduce PM2.5. In this thesis, actual prescribed burning emissions were characterized for better estimation of their impacts on air quality. Chemical mass balance (CMB) modeling, a receptor-oriented source apportionment technique, was applied to understand regional characteristics of PM2.5 source impacts in the Southeast. Uncertainty issues in the CMB source apportionment results due to both poor spatial representativeness and measurement errors was addressed for better understanding and estimation of the uncertainties. Possible future research is recommended based on the findings in this thesis.