Browsing by Subject "particulate matter"

It is well known that particulate matter (PM) has strong associations with various negative health endpoints. However, the precise mechanisms linking PM to these negative impacts are complex and not fully understood. The U.S. Environmental Protection Agency currently regulates PM on a mass concentration basis (μg of PM per m3 of air), which does not account for the differential toxicity of different particle species. More research is needed to improve understanding on how toxicity changes with different PM sources, and to answer: which environments have PM compositions that are particularly dangerous? The primary objective of this work is to characterize understudied aspects of particulate matter generated in environments that are relevant to human exposure (i.e., environments where people spend a large portion of their time). The exposure-relevant sites examined in this work investigate PM2.5 (particulate matter with diameters <2.5 microns) collected from inside cars during daily commutes in Atlanta, from urban India where roadside and residential trash burning is ubiquitously practiced, and from residential sites in rural and urban Guatemala. As mentioned, though the associations between negative health impacts and PM concentrations are striking, the toxicity pathways are not well understood. One proposed pathway of acute toxicity is related to an inhaled particle’s ability to generate reactive oxygen species (ROS) and exert oxidative stress on the lungs. In recent years, various assays have been developed to assess the ROS-generating capacity of particulate matter. Two of the most established assays used in air pollution research are the DTT (dithiotreitol) assay and the lung macrophage assay. These assays were used to make the first-ever measurements of oxidative potential of PM2.5 collected from in-vehicle commutes (in Atlanta) and from in-situ trash burning events (in Bangalore, India). In-vehicle results from ~2-hour morning commutes (n = 50) indicate that on-road DTT activity (median [IQR] = 0.68 [0.75] nmol min-1 m-3) is ~2 times higher than DTT activity measured from 23-hour roadside samples. Results highlight how gas-phase compounds make important contributions to DTT activity and that short-term exposures are associated with distinct changes in oxidative potential. This was echoed by results from trash-burning samples (n = 24), which suggest that ~1 minute of direct exposure to emissions from trash burning was equivalent in DTT activity to breathing in an entire day of ambient air in Bangalore. Though ambient samples (n = 6) show notable DTT activity (median [IQR] = 0.76 [0.03] nmol min-1 m-3), trash burning DTT activity was extremely high, averaging >1,000 nmol min-1 m-3. However, when considering DTT and macrophage results on a per-mass basis, ambient PM2.5 appears to be ~2 – 100 times more redox active than fresh trash-burning emissions, suggesting that many compounds found in fresh trash-burning emissions are not redox active; this may also indicate how atmospheric processing and aging can result in increased PM redox activity. Results highlight the importance of assessing PM with additional toxicity pathways since ROS activity alone is not sufficient to describe the many ways in which PM may impact health. Overall, results indicate that near trash-burning sources, exposure to redox-active PM can be extremely high. A follow-up project was launched in response to observing widely varying emissions from trash burning, which results from Bangalore show were vastly different even when comparing trash piles of similar size, composition, and burning conditions. This follow-up project was educational in nature as it was a collaborative effort between students at Duke University and the India Institute of Technology. To generate emissions in a more comparable way, we controlled for pile size, composition, and environmental variables (e.g., wind speed) that may affect burning conditions, and then we iteratively burned compiled mixtures of trash in a small-scale combustor. Burn piles (n = 28) were compiled to represent trash compositions observed and collected from six sites in Ahmedabad, India, where average pile composition was observed to be ~60% plastic by volume; plastic-only piles were also burned in the combustor. Plastic bottles were observed to generate the highest concentrations of PM2.5 and black carbon emissions, while plastic films emitted very low pollutant concentrations with PM2.5 close to background levels. Using low-cost sensors and thermocouples attached to the incinerator body proved to be an affordable way to make semi-quantitative assessments of controlled burns. We also demonstrate how low-cost sensors attached to a commercial UAV (unmanned aerial vehicle) could be useful for safely collecting pollutant data over a smoky municipal dumpsite. Trash burning is clearly a source of highly variable and spatially sporadic emissions. This follow-up project is valuable as it makes small but important steps toward finding affordable ways to measure and mitigate emissions. Lastly, a final project was pursued to assess air pollution and microbial concentrations from residential sites in Guatemala, including in a community where PM2.5 levels indoors were observed to be exceedingly high due to traditional cookstove use. Though many studies have measured PM in similar settings, existing research has not investigated microbial concentrations in the air at these settings (as the majority of existing research has focused on sites in high-income countries). Airborne viruses and bacteria were enumerated from filter samples using a staining microscopy technique. Air samples (n = 40) were collected at different times of day indoors and outdoors to provide insight on whether household or ambient sources dominate bioaerosol contributions. Results suggest that bioaerosols from indoor sources dominate in the mornings, while outdoor sources contribute more to bioaerosol concentrations in the afternoon. Links were observed between PM2.5 and microbial concentrations (Spearman’s rho, rs = 0.5; p < 0.001) but this correlation becomes insignificant when looking specifically at sites where cooking occurred; non-cooking sites continue to show significant correlation. Though the majority of viruses and bacteria are not pathogenic, recent research has indicated that even nonpathogenic and inactivated microbes may influence the oxidative potential of PM. Identifying important microbial sources in these high-PM environments is also necessary to create effect controls (for example, results show lowest microbial concentrations at two sampling environments that were well-sealed and where an air filter was present). In general, this work characterizes various aspects of PM2.5 in environments that many people encounter daily. Unless commutes can be shortened and traffic emissions reduced, or trash can be managed in ways other than burning, these will continue to be important factors in daily PM2.5 exposure.

In the first chapter of this dissertation, I outline a hedonic equilibrium model that explicitly controls for moving costs and forward-looking behavior. Hedonic equilibrium models allow researchers to recover willingness to pay for spatially delineated amenities by using the notion that individuals "vote with their feet." However, the hedonic literature and, more recently, the estimable Tiebout sorting model literature, has largely ignored both the costs associated with migration (financial and psychological), as well as the forward-looking behavior that individuals exercise in making location decisions. Each of these omissions could lead to biased estimates of willingness to pay. Building upon dynamic migration models from the labor literature, I estimate a fully dynamic model of individual migration at the national level. By employing a two-step estimation routine, I avoid the computational burden associated with the full recursive solution and can then include a richly-specified, realistic state space. With this model, I am able to perform non-market valuation exercises and learn about the spatial determinants of labor market outcomes in a dynamic setting. Including dynamics has a significant positive impact on the estimates of willingness to pay for air quality. In addition, I find that location-specific amenity values can explain important trends in observed migration patterns in the United States.

The second chapter of this dissertation describes a model which estimates willingness to pay for air quality using property value hedonics techniques. Since Rosen's seminal 1974 paper, property value hedonics has become commonplace in the non-market valuation of environmental amenities, despite a number of well-known methodological problems. In particular, recovery of the marginal willingness to pay function suffers from important endogeneity biases that are difficult to correct with instrumental variables procedures [Epple (1987)]. Bajari and Benkard (2005) propose a "preference inversion" procedure for recovering heterogeneous measures of marginal willingness to pay that avoids these problems. However, using cross-sectional data, their approach imposes unrealistic constraints on the elasticity of marginal willingness to pay. Following Bajari and Benkard's suggestion, I show how data describing repeat purchase decisions by individual home buyers can be used to relax these constraints. Using data on ozone pollution in the Bay Area of California, I find that endogeneity bias and flexibility in the shape of the marginal willingness to pay function are both important.

Finally, in the third chapter of this dissertation, I combine the insights of the Bajari-Benkard inversion approach employed in second chapter with more standard estimation techniques (i.e., Rosen (1974)) to arrive at a new hedonic methodology that allows for flexible and heterogeneous preferences while avoiding the endogeneity problems that plague the traditional Rosen two-stage model. Implementing this estimator using the Bay Area ozone data, I again find evidence of considerable heterogeneity and of endogeneity bias. In particular, I find that a one unit deterioration in air quality (measured in days in which ozone levels exceed the state standards) raises marginal willingness to pay by $145.18 per year. The canonical two-stage Rosen model finds, counter-intuitively, that this same change would reduce marginal willingness to pay by $94.24.