Assessing exposure to chlorinated solvents from the subsurface to indoor air pathway.

详细信息   

• 作者：Johnston ; Jill E.
• 学历：Ph.D.
• 年：2013
• 导师：MacDonald-Gibson, Jacqueline A.,eadvisorAndrews, Richardecommittee memberPleil, Joachimecommittee memberSerre, Marcecommittee memberWing, Stevenecommittee member
• 毕业院校：The University of North Carolina
• Department：Environmental Sciences & Engineering
• ISBN：9781303356605
• CBH：3593245
• Country：USA
• 语种：English
• FileSize：5822911
• Pages：156

文摘

The migration of chlorinated volatile organic compounds from groundwater to indoor air&ndash；known as vapor intrusion&ndash；is an important exposure pathway at sites with contaminated groundwater. However, monitoring indoor air quality in the hundreds or thousands of at-risk homes at each site is logistically and financially infeasible. Screening methods are needed to prioritize homes for monitoring and remediation. Current screening approaches do not adequately account for the substantial spatial and temporal variability in vapor intrusion risk, in part because the causes of this variability are not well understood. This work explores variability in vapor intrusion risk in a case-study community and then develops two different modeling approaches for screening at-risk homes. We employed a community-based approach to collect indoor air samples and analyze vapor intrusion risk in 20 homes at a case-study site. Results demonstrate that indoor concentrations of tetrachloroethylene from vapor intrusion vary by an order of magnitude across space and time. We show that key factors affecting this variability include barometric pressure drop, humidity, wind speed, and season. Using data collected from 370 homes in the National Database on Vapor Intrusion, we developed a multilevel regression model to predict vapor intrusion risks in unmonitored homes. The resulting predictions decrease the rate of false negatives compared with the U.S. Environmental Protection Agencys EPA) current screening approach, which assumes that indoor air concentration will not exceed 1/1,000 times the soil gas concentration just above the groundwater. Finally, we demonstrate a second approach for improving the accuracy of screening by using Bayesian statistical techniques to integrate observational data into a mechanistic model describing the physical and chemical processes driving vapor intrusion. The resulting calibrated model also decreases the rate of false negatives in screening homes for vapor intrusion risks when compared with the current EPA approach. The results suggest current policy may underestimate vapor intrusion exposures, and we demonstrate two approaches to improve exposure assessment. Future research should evaluate the potential for community-centered and real-time monitoring devices, the integration of localized and cumulative risk information into the framework, and assessment of the risks and benefits of a precautionary approach to mitigation.