Lisa K. Baxter

Land use regression modeling of intra-urban residential variability in multiple traffic-related air pollutants

BackgroundThere is a growing body of literature linking GIS-based measures of traffic density to asthma and other respiratory outcomes. However, no consensus exists on which traffic indicators best capture variability in different pollutants or within different settings. As part of a study on childhood asthma etiology, we examined variability in outdoor concentrations of multiple traffic-related air pollutants within urban communities, using a range of GIS-based predictors and land use regression techniques.MethodsWe measured fine particulate matter (PM2.5), nitrogen dioxide (NO2), and elemental carbon (EC) outside 44 homes representing a range of traffic densities and neighborhoods across Boston, Massachusetts and nearby communities. Multiple three to four-day average samples were collected at each home during winters and summers from 2003 to 2005. Traffic indicators were derived using Massachusetts Highway Department data and direct traffic counts. Multivariate regression analyses were performed separately for each pollutant, using traffic indicators, land use, meteorology, site characteristics, and central site concentrations.ResultsPM2.5 was strongly associated with the central site monitor (R2 = 0.68). Additional variability was explained by total roadway length within 100 m of the home, smoking or grilling near the monitor, and block-group population density (R2 = 0.76). EC showed greater spatial variability, especially during winter months, and was predicted by roadway length within 200 m of the home. The influence of traffic was greater under low wind speed conditions, and concentrations were lower during summer (R2 = 0.52). NO2 showed significant spatial variability, predicted by population density and roadway length within 50 m of the home, modified by site characteristics (obstruction), and with higher concentrations during summer (R2 = 0.56).ConclusionEach pollutant examined displayed somewhat different spatial patterns within urban neighborhoods, and were differently related to local traffic and meteorology. Our results indicate a need for multi-pollutant exposure modeling to disentangle causal agents in epidemiological studies, and further investigation of site-specific and meteorological modification of the traffic-concentration relationship in urban neighborhoods.

Uncertainty and variability in health-related damages from coal-fired power plants in the United States.

The health-related damages associated with emissions from coal-fired power plants can vary greatly across facilities as a function of plant, site, and population characteristics, but the degree of variability and the contributing factors have not been formally evaluated. In this study, we modeled the monetized damages associated with 407 coal-fired power plants in the United States, focusing on premature mortality from fine particulate matter (PM(2.5)). We applied a reduced-form chemistry-transport model accounting for primary PM(2.5) emissions and the influence of sulfur dioxide (SO(2)) and nitrogen oxide (NO(x)) emissions on secondary particulate formation. Outputs were linked with a concentration-response function for PM(2.5)-related mortality that incorporated nonlinearities and model uncertainty. We valued mortality with a value of statistical life approach, characterizing and propagating uncertainties in all model elements. At the median of the plant-specific uncertainty distributions, damages across plants ranged from

Predictors of concentrations of nitrogen dioxide, fine particulate matter, and particle constituents inside of lower socioeconomic status urban homes

30,000 to

Air pollution exposure prediction approaches used in air pollution epidemiology studies.

500,000 per ton of PM(2.5),

Exposure prediction approaches used in air pollution epidemiology studies: key findings and future recommendations.

6,000 to

Variability in the fraction of ambient fine particulate matter found indoors and observed heterogeneity in health effect estimates.

50,000 per ton of SO(2),

Influence of human activity patterns, particle composition, and residential air exchange rates on modeled distributions of PM 2.5 exposure compared with central-site monitoring data

500 to

Feasibility of assessing public health impacts of air pollution reduction programs on a local scale: New Haven case study.

15,000 per ton of NO(x), and

Development and evaluation of alternative approaches for exposure assessment of multiple air pollutants in Atlanta, Georgia

0.02 to

Spatiotemporally resolved air exchange rate as a modifier of acute air pollution-related morbidity in Atlanta

1.57 per kilowatt-hour of electricity generated. Variability in damages per ton of emissions was almost entirely explained by population exposure per unit emissions (intake fraction), which itself was related to atmospheric conditions and the population size at various distances from the power plant. Variability in damages per kilowatt-hour was highly correlated with SO(2) emissions, related to fuel and control technology characteristics, but was also correlated with atmospheric conditions and population size at various distances. Our findings emphasize that control strategies that consider variability in damages across facilities would yield more efficient outcomes.