Total exposure and significant source apportionment: The relationships among emission sources, concentration, exposure, and health effects of particulate matter

This dissertation seeks to improve the information base for air pollution control programs by enhancing understanding of the relationships among emission, concentration, exposure, dose and health effects for particulate air pollution. In this dissertation, there are three particulate matter (PM) studies organized according to the same underlying concept---improved exposure assessment is a keystone to achieving more efficient air pollution control.; The first PM study was conducted in Bangkok, Thailand, to investigate the relationship between indoor and outdoor PM. Results show that day-to-day fluctuations of the indoor PM correlated well with changes in ambient PM. This implies that ambient monitors are able to capture the daily variations of indoor levels or even personal exposure and may help explain the robust association between ambient PM levels and adverse health effects found in many epidemiological studies. Absolute personal exposure, however, may be underestimated or overestimated by ambient monitors, depending on indoor characteristics.; The second study is an epidemiological analysis applying a new method, Factor Analysis and Poisson Regression (FA/PR), to explore the relationship between ambient PM and daily mortality in New Jersey. Exposure metrics used in this study were source-related PM chemical speciation obtained by FA. Statistically significant associations were found between mortality and several PM sources, including oil burning, industrial sources, sulfate, and motor vehicles. The use of FA/PR to integrate multiple chemical species as PM exposure metrics was found to be more useful than the traditional approach using PM mass alone. This study showed that exposure to various chemical species plays a role in PM-induced health effects, and risks posed are not same for various PM sources.; The third study presents the Total Exposure and Significant Source Apportionment (TESSA) methodology, integrating total exposure assessment and receptor modeling. TESSA prioritizes sources for control based on the contributions to human exposure. TESSA was applied in Los Angeles as a case study to demonstrate the discrepancy of major sources for control by ambient air management and exposure management. Results show that indoor sources (such as cooking and smoking) that are not listed in the emission inventory and that do not strongly affect ambient concentrations are important exposure sources. Control costs of smoking and ambient sources were compared to illustrate the importance of integrating exposure effectiveness or dose effectiveness in decision-making processes.; Policy implications of the findings in these studies are discussed in Chapter Five. Future research is recommended based on the lessons learned from the dissertation work.