CEE ENV/WR Seminar: Cheng-Pin Kuo
Title: "Evaluating Spatial Heterogeneity of PM2.5 Exposure Risks and Disease Burdens at Diverse Urbanization Levels"
The adverse health impacts of exposure to ambient PM2.5 (fine inhalable particle matters) pollution have been studied for several years. The risk of PM2.5 exposure is related to PM2.5 toxicity, human/environment interactions, and individual factors, but few studies systematically linked the exposure risk with land-use characteristics and directly calculated the burdens of the diseases. In our research, the hospital emergency visit data in Tainan City, Taiwan, were fused with land-use data and air quality data, and the PM2.5 risks and disease burdens among different urbanization levels were retrieved. The uncertainty of disease burdens by using different risk values and PM2.5 concentration data sources was also analyzed, and the bias emphasized the representativeness of employed parameters.
Cheng-Pin Ku is a fourth-year PhD student in the Department of Civil and Environmental Engineering at UT. Kuo received his Bachelor of Science and Master of Science in the College of Public Health from National Taiwan University, Taiwan, in 2011 and 2013 respectively. The focus of Kuo’s research works includes air quality modeling, machine learning, and exposure assessment. He also developed a hybrid framework with multiple machine learning techniques to build a model for planning better lockdowns during the COVID-19 pandemic. His publications had been presented in several international conferences including AGU, A&WMA, and CMAS, and accepted to publish in SCI journals (6 articles) since 2018. His doctoral research will focus on the fusion of machine learning techniques and air quality models, and their application on the burden of the diseases estimations and public health policies.
Thursday, October 7 at 2:50pm
John D. Tickle Engineering Building, 402
851 Neyland Dr, Knoxville, TN 37996