2022 Ph.D., Population, Health and Place, University of Southern California, Spatial Sciences Institute
2001 M.A., Geography, University of Southern California, Department of Geography
2001 Graduate Certificate in Geographic Information Science and Technology, University of Southern California, Department of Geography
1994 B.S., Urban and Environmental Science, Peking University
Dr. Yan Xu's dissertation was on "Personal PM2.5 Exposure during Pregnancy in an Environmental Health Disparities Population." In her dissertation, she focused on exposure to particulate matter air pollution with an aerodynamic diameter less than 2.5 μm (PM2.5), particularly during the 3rd trimester of pregnancy, being associated with adverse impacts on maternal and fetal health.
Pregnant women are mobile and locations they spend time in contribute to their personal PM2.5 exposures, while their total exposures are the mixtures of multiple sources and affected by multiple factors. Environmental health disparities groups including racial and ethnic minorities, marginalized, and lower income populations are disproportionally burdened by elevated PM2.5 exposure and may be more susceptible to its adverse health effects.
In her dissertation she used 48-hr integrated, personal PM2.5 measurements and concurrent GPS records collected from 213 low-income, predominately Hispanic women in their 3rd trimester living in Los Angeles, CA, to investigate the impacts of activity spaces on personal PM2.5 exposures (Chapter 2), derive the main sources contributing to personal PM2.5 mass (Chapter 3), and determine the influence of microenvironmental exposures estimated with a stochastic exposure model and total personal exposures (Chapter 4).
This research found indoor sources dominated personal PM2.5 exposures, where combined indoor source contributions (i.e., secondhand smoking, crustal) were more than triple those of outdoor sources (i.e., traffic, aged and fresh sea salt, and fuel oil). In addition, environmental exposures encountered within the activity spaces that participants frequented contributed significantly to personal PM2.5 exposure, with greater exposure to parks and greenness linked with lower personal exposures. Finally, the simulated personal exposures better approximated the distribution of personal measurements with the addition of more refined indoor source terms. However, total predicted PM2.5 exposure was highly correlated with outdoor PM2.5 which is contrary to the patterns observed with measurements.
Overall, the findings of this dissertation shed light on the complexity of sources and determinants of personal PM2.5 exposures during pregnancy in an environmental health disparities population, as well as the need for refined exposure assessment methods to capture the true variability in exposure and aid in the design of relevant interventions to reduce exposures.
During her time in the Population, Health and Place Ph.D. program, Yan served as a research assistant with the USC MADRES Center, working on five NIH and EPA projects.
Prior to joining the PHP program, she worked as a research associate in the Geosoft Lab in the Institute of Remote Sensing & GIS Research at Peking University and as a senior transportation planner and GIS analyst with the Los Angeles County Metropolitan Transportation Authority.
Her publications include:
- Gao Y, Liu J, Xu Y, Mu L, Liu Y. A Spatiotemporal Constraint Non-Negative Matrix Factorization Model to Discover Intra-Urban Mobility Patterns from Taxi Trips. Sustainability. 2019; 11(15):4214. https://doi.org/10.3390/su11154214
- Gao Y, Jiang D, Xu Y. Optimize taxi driving strategies based on reinforcement learning. International Journal of Geographical Information Science. 2018; 32:8, 1677-1696, DOI: 10.1080/13658816.2018.1458984.