I was part of a multi-investigator team that analyzed the risks for human health of antibiotic use in high-density hog farms. My students and I developed a Bayesian belief network model to predict the risks that humans will become infected with multi-drug-resistant Staphylococcus aureus as a result of intensive antibiotic use in hog farms. This research was funded by the National Science Foundation.
You can see a news story about the research project here.
For the past three years, my students and I have been analyzing publicly available data to document racial disparities in access to community water and sewer service in North Carolina. We have mapped locations where such disparities exist, analyzed water quality in selected communities lacking access to public water, and analyzed the health implications. Our research is funded by the Robert Wood Johnson Foundation and the IBM Junior Faculty Development Award.
Related stories:
UNC Study Explores Reasons for Disparities in Access to Municipal Water and Sewer Systems in N.C.
Public Health a Low Priority for Water and Sewer Extensions, Study Finds
With post-doctoral research Kelsey Pieper, my team built a Bayesian belief network model to predict risks to wastewater workers exposed to sewage from hospitals and other healthcare facilities treating patients infected by Ebola and other emerging pathogens. We analyzed the magnitude of these risks plus alternative approaches for improving worker protection. This work was funded by the Water-Environment Research Foundation.
With doctoral student Ted Mansfield and others, my team explored how alternative designs for cities affect public health through effects on air quality and opportunities for walking and cycling. Our goal was to identify urban design features that minimize adverse environmental and health impacts—representing a re-establishment of links between urban planners and environmental engineers that began with the sanitarian movement in the late nineteenth century.
This work has been funded by the BlueCross BlueShield Foundation of North Carolina and by the North Carolina Department of Transportation. You can read news about some of our research here.
Toxic waste sites where volatile chemicals have migrated into groundwater can contaminate the indoor air in overlying homes through a process known as vapor intrusion. With doctoral student Jill Johnston, I conducted a series of studies, including a field investigation, to develop improved methods to predict vapor intrusion risks. Jill, now Assistant Professor of Preventive Medicine, Keck School of Medicine, University of Southern California, is a leading expert on the vapor intrusion phenomenon.
You can find more information about the results of our work in several publications:
The migration of chlorinated volatile organic compounds from groundwater to indoor air—known as vapor intrusion—is an important exposure pathway at sites with contaminated groundwater. High-quality screening methods to prioritize homes for monitoring and remediation are needed, because measuring indoor air quality in privately owned buildings is often logistically and financially infeasible. We demonstrate an approach for improving the accuracy of the Johnson-Ettinger model (JEM), which the Environmental Protection Agency (EPA) recommends as a screening tool in assessing vapor intrusion risks. We use Bayesian statistical techniques to update key Johnson-Ettinger input parameters, and we compare the performance of the prior and updated models in predicting indoor air concentrations measured in 20 homes. Overall, the updated model reduces the root mean squared error in the predicted concentration by 66%, in comparison to the prior model. Further, in 18 of the 20 homes, the mean measured concentration is within the 90% confidence interval of the concentration predicted by the updated model. The resulting calibrated model accounts for model uncertainty and variability and decreases the false negatives rate; hence, it may offer an improved screening approach, compared to the current EPA deterministic approach. More »
The migration of volatile contaminants from groundwater and soil into indoor air is a potential health threat at thousands of contaminated sites across the country. This phenomenon, known as vapor intrusion, is characterized by spatial and temporal heterogeneity. This study examined short-term fluctuations in concentrations of tetrachloroethylene (PCE) in the indoor air of residential homes due to vapor intrusion in a community in San Antonio, Texas, that sits atop an extensive, shallow plume of contaminated groundwater. Using a community-based design, we removed potential indoor sources of PCE and then collected twelve 3-day passive indoor air samples in each of the 20 homes. Results demonstrated a one-order-of-magnitude variability in concentration across both space and time among the study homes, although all measured concentrations were below risk-based screening levels. We found that within any given home, indoor concentrations increase with the magnitude of the barometric pressure drop (P=0.048) and humidity (P<0.001), while concentrations decrease as wind speed increases (P<0.001) and also during winter (P=0.001). In a second analysis to examine sources of spatial variability, we found that indoor air PCE concentrations between homes increase with groundwater concentration (P=0.030) and a slab-on-grade (as compared with a crawl space) foundation (P=0.028), whereas concentrations decrease in homes without air conditioners (P=0.015). This study offers insights into the drivers of temporal and spatial variability in vapor intrusion that can inform decisions regarding monitoring and exposure assessment at affected sites. More »
This paper describes a probabilistic model, based on the Johnson-Ettinger algorithm, developed to characterize the current and historic exposure to tricholorethylene (TCE) and tetrachlorethylene (PCE) in indoor air from plumes of groundwater contamination emanating from the former Kelly Air Force Base in San Antonio, Texas. We estimate indoor air concentration, house by house, in 30 101 homes and compare the estimated concentrations with measured values in a small subset of homes. We also compare two versions of the Johnson-Ettinger model: one used by the Environmental Protection Agency (EPA) and another based on an alternative parametrization. The modeled mean predicted PCE concentration historically exceeded PCE screening levels (0.41 ug/m3) in 5.5% of houses, and the 95th percentile of the predicted concentration exceeded screening levels in 85.3% of houses. For TCE, the mean concentration exceeded the screening level (0.25 ug/m3) in 49% of homes, and the 95th percentile of the predicted concentration exceeded the screening level in 99% of homes. The EPA model predicts slightly lower indoor concentrations than the alternative parametrization. Comparison with measured samples suggests both models, with the inputs selected, underestimate indoor concentrations and that the 95th percentiles of the predicted concentrations are closer to measured concentrations than predicted mean values. More »
The migration of chlorinated volatile organic compounds from groundwater to indoor air—known as vapor intrusion—can be an important exposure pathway at hazardous waste sites. Because sampling indoor air at every potentially affected home is often logistically infeasible, screening tools are needed to help identify at-risk homes. Currently, the U.S. Environmental Protection Agency (EPA) uses a simple screening approach that employs a generic vapor "attenuation factor," the ratio of the indoor air pollutant concentration to the pollutant concentration in the soil gas directly above the groundwater table. At every potentially affected home above contaminated groundwater, the EPA assumes the vapor attenuation factor is less than 1/1000 – that is, that the indoor air concentration will not exceed 1/1000 times the soil–gas concentration immediately above groundwater. This paper reports on a screening-level model that improves on the EPA approach by considering environmental, contaminant, and household characteristics. The model is based on an analysis of the EPA’s vapor intrusion database, which contains almost 2,400 indoor air and corresponding subsurface concentration samples collected in 15 states. We use the site data to develop a multilevel regression model for predicting the vapor attenuation factor. We find that the attenuation factor varies significantly with soil type, depth to groundwater, season, household foundation type, and contaminant molecular weight. The resulting model decreases the rate of false negatives compared to EPA’s screening approach. More »
The migration of volatile contaminants into overlying buildings, known as vapor intrusion, is a health concern for people living above contaminated groundwater. As public health and environmental agencies develop protocols to evaluate vapor intrusion exposure, little attention has been paid to the experiences and opinions of communities likely to be affected by vapor intrusion. Using a community-driven research approach and qualitative interviews, we explored community perspectives on the vapor intrusion pathway and the perceived impact on community health and well-being among neighbors living atop a large, shallow-chlorinated solvent plume in San Antonio, TX. Most participants associated vapor intrusion with health risks, expressing concern about the unavoidable and uncontrollable nature of their exposure. Few were satisfied with the responsiveness of public officials. Above all, participants wanted more accurate, transparent information and additional independent scientific investigations. More »
I led a three-year project to quantify the number of annual deaths and illnesses attributable to pollutants in air, water, soil, and food in the United Arab Emirates. The results informed a strategic plan for investing in measures to decrease environmental impacts on public health in the UAE.
You can find a book about the project on Amazon.
