The Near-Road Exposures and Effects of Urban Air Pollutants Study (NEXUS) investigated the impact of exposure to traffic-related air pollution on the respiratory health of asthmatic children in Detroit, Michigan. Since indoor mold exposure may also contribute to asthma, floor dust samples were collected in participants homes (n=112) to assess mold contamination using the Environmental Relative Moldiness Index (ERMI). The repeatability of the ERMI over time, as well as ERMI differences between rooms and dust collection methods, was evaluated for insights into the application of the ERMI metric. ERMI values for the standard settled floor dust samples had a mean ± standard deviation of 14.5±7.9, indicating high levels of mold contamination. ERMI values for samples collected from the same home 1 to 7 months apart (n=52) were consistent and without systematic bias. ERMI values for separate bedroom and living room samples were highly correlated (r=0.69, n=66). Vacuum bag dust ERMI values were lower than for floor dust but correlated (r=0.58, n=28). These results support the use of the ERMI to evaluate residential mold exposure as a confounder in air pollution health effects studies.

Air pollution health studies often use outdoor concentrations as exposure surrogates. Failure to account for variability of residential infiltration of outdoor pollutants can induce exposure errors and lead to bias and incorrect confidence intervals in health effect estimates. The residential air exchange rate (AER), which is the rate of exchange of indoor air with outdoor air, is an important determinant for house-to-house (spatial) and temporal variations of air pollution infiltration. Our goal was to evaluate and apply mechanistic models to predict AERs for 213 homes in the Near-Road Exposures and Effects of Urban Air Pollutants Study (NEXUS), a cohort study of traffic-related air pollution exposures and respiratory effects in asthmatic children living near major roads in Detroit, Michigan. We used a previously developed model (LBL), which predicts AER from meteorology and questionnaire data on building characteristics related to air leakage, and an extended version of this model (LBLX) that includes natural ventilation from open windows. As a critical and novel aspect of our AER modeling approach, we performed a cross validation, which included both parameter estimation (i.e., model calibration) and model evaluation, based on daily AER measurements from a subset of 24 study homes on five consecutive days during two seasons. The measured AER varied between 0.09 and 3.48 h−1 with a median of 0.64 h−1. For the individual model-predicted and measured AER, the median absolute difference was 29% (0.19 h‑1) for both the LBL and LBLX models. The LBL and LBLX models predicted 59% and 61% of the variance in the AER, respectively. Daily AER predictions for all 213 homes during the three year study (2010–2012) showed considerable house-to-house variations from building leakage differences, and temporal variations from outdoor temperature and wind speed fluctuations. Using this novel approach, NEXUS will be one of the first epidemiology studies to apply calibrated and home-specific AER models, and to include the spatial and temporal variations of AER for over 200 individual homes across multiple years into an exposure assessment in support of improving risk estimates.

A major challenge in traffic-related air pollution exposure studies is the lack of information regarding pollutant exposure characterization. Air quality modeling can provide spatially and temporally varying exposure estimates for examining relationships between traffic-related air pollutants and adverse health outcomes. A hybrid air quality modeling approach was used to estimate exposure to traffic-related air pollutants in support of the Near-Road Exposures and Effects of Urban Air Pollutants Study (NEXUS) conducted in Detroit (Michigan, USA). Model-based exposure metrics, associated with local variations of emissions and meteorology, were estimated using a combination of the American Meteorological Society/Environmental Protection Agency Regulatory Model (AERMOD) and Research LINE-source dispersion model for near-surface releases (RLINE) dispersion models, local emission source information from the National Emissions Inventory, detailed road network locations and traffic activity, and meteorological data from the Detroit City Airport. The regional background contribution was estimated using a combination of the Community Multi-scale Air Quality (CMAQ) and the Space-Time Ordinary Kriging (STOK) models. To capture the near-road pollutant gradients, refined "mini-grids" of model receptors were placed around participant homes. Exposure metrics for CO, NOx, PM2.5 and its components (elemental and organic carbon) were predicted at each home location for multiple time periods including daily and rush hours. The exposure metrics were evaluated for their ability to characterize the spatial and temporal variations of multiple ambient air pollutants compared to measurements across the study area.

BACKGROUND: The Near-Road Exposures and Effects of Urban Air Pollutants Study (NEXUS) is investigating the relationship between near-roadway exposures to air pollutants and respiratory responses in asthmatic children living near major roads in Detroit, Michigan. The study uses an integrated measurement and modeling approach to assess the children's exposure to near-road air pollution. To estimate tiers of exposure metrics, we developed an exposure model for individuals (EMI). One tier of EMI is the air exchange rate (AER) for homes, where people spend most of their time. The AER, which is the airflow into and out of a building, is a key determinant for infiltration of outdoor air pollutants. AIMS: Our goal was to calibrate, evaluate, and apply a mechanistic AER model to predict hourly AER for all homes during NEXUS. METHODS: We developed a mechanistic AER model to predict residential AER from building characteristics related to air leakage, indoor-outdoor temperature differences, wind speed, and open windows. Cross validation was used to estimate model parameters and evaluate model uncertainty based on a subset of homes (N=25) with daily questionnaires and daily AER measured on five consecutive days during two seasons (Fall 2010, Spring 2011).The model was then applied to predict hourly AER for all homes (N=150) over the study duration (September 2010 to December 2012). RESULTS: Predicted AER at the individual level matched measured AER with a median absolute difference was 34% (0.18 h-1) and 26% (0.18 h-1) for the fall and spring seasons, respectively. CONCLUSIONS: We demonstrated the feasibility of using a mechanistic model to predict residential AER in a health study. These hourly AER predictions will enable the development of refined tiers of exposure metrics (e.g., residential indoor pollutant concentrations) that account for the diurnal variation of traffic-related pollutants.

BACKGROUND:Nearly 3 billion people worldwide rely on solid fuel combustion to meet basic household energy needs. The resulting exposure to air pollution causes an estimated 4.5% of the global burden of disease. Large variability and a lack of resources for research and development have resulted in highly uncertain exposure estimates. OBJECTIVE:We sought to identify research priorities for exposure assessment that will more accurately and precisely define exposure-response relationships of household air pollution necessary to inform future cleaner-burning cookstove dissemination programs. DATA SOURCES:As part of an international workshop in May 2011, an expert group characterized the state of the science and developed recommendations for exposure assessment of household air pollution. SYNTHESIS:The following priority research areas were identified to explain variability and reduce uncertainty of household air pollution exposure measurements: improved characterization of spatial and temporal variability for studies examining both short- and long-term health effects; development and validation of measurement technology and approaches to conduct complex exposure assessments in resource-limited settings with a large range of pollutant concentrations; and development and validation of biomarkers for estimating dose. Addressing these priority research areas, which will inherently require an increased allocation of resources for cookstove research, will lead to better characterization of exposure-response relationships. CONCLUSIONS:Although the type and extent of exposure assessment will necessarily depend on the goal and design of the cookstove study, without improved understanding of exposure-response relationships, the level of air pollution reduction necessary to meet the health targets of cookstove interventions will remain uncertain.

Exposure models for air pollutants often adjust for effects of the physical environment (e.g., season, urban vs. rural populations) in order to improve exposure and risk predictions. Yet attempts are seldom made to attribute variability in observed outdoor air measurements to specific environmental variables. This research presents a statistical strategy to identify and explain the spatial and temporal components of air pollutant measurement variance using regional predictors and large-scale (with impacts over multiple kilometers of distance) emission source effects. The emission sources considered in this investigation include major highways and industries, and were chosen based on their proximity to monitoring areas designated in the Detroit Exposure and Aerosol Research Study (DEARS). Linear mixed effects models were used to investigate 24-h averaged outdoor residential air measurements of several pollutants, including PM2.5 mass, PM components (elemental carbon, organic carbon, metals, elements), nitrogen dioxide, and volatile organic compounds (VOCs). Three hierarchal statistical models were utilized to calculate and examine variance component estimates for each analyte before and after adjustment for fixed effects, which included sampling season, day of the week, air concentrations at an ambient (centralized) monitoring site, and the frequency of time a receptor was downwind of specific large-emissions sources. Results indicate that temporal variability accounted for the majority of total measurement variance (90% on average). Adjustments for ambient concentration and sampling season significantly reduced temporal variance estimates for most VOCs and for about half of the PM components (generally with reductions of 24–97%). Major exceptions to this trend were found with metals (Fe, Mn, and Zn), ethyltoluene, and p-dichlorobenzene, where only 4–30% of the temporal variance was explained after the same adjustments. Additional reductions in temporal variance (up to 37%) were observed after adjusting for the large-emission sources and day of the week effects, with the strongest effects observed for PM components, including select metals. Thus, for the Detroit airshed, VOCs appear to have been largely affected by regional factors, whereas PM components were explained by both regional factors and localized large-emissions sources. Examination of the radial directions associated with suspected emission sources generally supported a priori expectations of source–analyte associations (e.g., NO2 increases from areas of high vehicle traffic). Overall, this investigation presents a statistical multi-pollutant analysis strategy that is useful for simultaneously (1) estimating spatial and temporal variance components of outdoor air pollutant measurements, (2) estimating the effects of regional variables on pollutant levels, and (3) identifying likely emissions sources that may affect outdoor air levels of individual or co-occurring pollutants.

The Near-Road Exposures and Effects of Urban Air Pollutants Study (NEXUS) was designed to examine the relationship between near-roadway exposures to air pollutants and respiratory outcomes in a cohort of asthmatic children who live close to major roadways in Detroit, Michigan USA. From September 2010 to December 2012 a total of 139 children with asthma, ages 6–14, were enrolled in the study on the basis of the proximity of their home to major roadways that carried different amounts of diesel traffic. The goal of the study was to investigate the effects of traffic-associated exposures on adverse respiratory outcomes, biomolecular markers of inflammatory and oxidative stress, and how these exposures affect the frequency and severity of respiratory viral infections in a cohort of children with asthma. An integrated measurement and modeling approach was used to quantitatively estimate the contribution of traffic sources to near-roadway air pollution and evaluate predictive models for assessing the impact of near-roadway pollution on children's exposures. Two intensive field campaigns were conducted in Fall 2010 and Spring 2011 to measure a suite of air pollutants including PM2.5 mass and composition, oxides of nitrogen (NO and NO2), carbon monoxide, and black carbon indoors and outdoors of 25 participants' homes, at two area schools, and along a spatial transect adjacent to I-96, a major highway in Detroit. These data were used to evaluate and refine models to estimate air quality and exposures for each child on a daily basis for the health analyses. The study design and methods are described, and selected measurement results from the Fall 2010 field intensive are presented to illustrate the design and successful implementation of the study. These data provide evidence of roadway impacts and exposure variability between study participants that will be further explored for associations with the health measures.

Nonparametric Trajectory Analysis (NTA), a receptor-oriented model, was used to assess the impact of local sources of air pollution at monitoring sites located adjacent to highway I-15 in Las Vegas, NV. Measurements of black carbon, carbon monoxide, nitrogen oxides, and sulfur dioxide concentrations were collected from December 2008 to December 2009. The purpose of the study was to determine the impact of the highway at three downwind monitoring stations using an upwind station to measure background concentrations. NTA was used to precisely determine the contribution of the highway to the average concentrations measured at the monitoring stations accounting for the spatially heterogeneous contributions of other local urban sources. NTA uses short time average concentrations, 5 min in this case, and constructed local back-trajectories from similarly short time average wind speed and direction to locate and quantify contributions from local source regions. Averaged over an entire year, the decrease of concentrations with distance from the highway was found to be consistent with previous studies. For this study, the NTA model is shown to be a reliable approach to quantify the impact of the highway on local air quality in an urban area with other local sources.

Roadside noise barriers are common features along major highways in urban regions and are anticipated to have important effects on near-road air pollution through altering the dispersion of traffic emissions and resulting downstream concentrations. A 3-dimensional computational fluid dynamics (CFD) 6-lane road model has been developed to simulate roadside barrier effects on near-road air quality and evaluate the influence of key variables, such as barrier height and wind direction. The CFD model matches an existing wind tunnel road model and comparison with the wind tunnel data guided the selection of the optimal turbulence model (Realizeable k–ɛ turbulence model with a Schmidt number of 1.0). Under winds perpendicular to the road, CFD model simulations show that roadside barriers reduce the concentration of an inert gaseous tracer (χ), relative to a no-barrier situation, vertically up to approximately half the barrier height and at all horizontal distances from the road. At 20m (3.3H, where H=6m) from the road, barriers of heights ranging from 0.5H to 3.0H reduce the maximum concentrations by 15–61% relative to a no-barrier case, with the location of the maximum shifted to occur near the top of the barrier. The near-road reduction comes at a penalty for on-road air pollutant concentrations: on-road pollution is projected to increase by a factor of 1.1–2.3 corresponding to barriers ranging from 0.5H to 3.0H. When the noise barrier is downwind of the road, a stagnant zone is formed behind the barrier and minor road emissions (e.g., 5% of the highway emissions strength) in this zone, such as a moderately traveled service road, have a magnified effect on concentrations immediately behind the barrier. Wind direction and barrier termination also play a critical role, with a spill-over of accumulated emissions upwind of the barrier strongly increasing near-road concentrations at one end of the barrier. These results imply that roadside barriers may mitigate near-road air pollution, although local meteorology, the barrier structure, and the degree of lee-side emission sources are critical factors determining the outcome.

The U.S. EPA periodically evaluates ambient concentrations, human exposures, and health risks for 180 hazardous air pollutants plus diesel particulate matter using modeled estimates from the National-Scale Air Toxics Assessment (NATA). NATA publishes estimates at the spatial resolution of U.S. Census tracts, which are subdivisions of a county. These local scale, model-predicted estimates from NATA are used extensively in community-based assessments; however, evaluation of NATA’s ambient concentrations and human exposure estimates against measurement data has been limited to date. This paper compares modeled annual average benzene results from the 2002 NATA with measured results from the 2004 to 2007 Detroit Exposure and Aerosol Research Study (DEARS) as a case study of the quality of NATA results. NATA model estimates support community-scale characterization and assessment. Benzene is particularly important as it was estimated by the 2002 NATA as the largest single air toxic pollutant in terms of cancer risk in the U.S. We found that the average ambient concentrations of benzene predicted by NATA were within 5 percent, on average, of the 24-h integrated average ambient concentrations measured in DEARS. The NATA human exposure estimates, which include only outdoor sources for benzene, were, on average, approximately half the measured breathing zone concentrations from DEARS. Our analyses support that the factors driving higher DEARS personal benzene concentrations relative to the NATA predicted exposure values are likely due, at least in part, to indoor sources. This work points to further community-scale modeling research to improve characterizations and assessments of human exposures.

Environmental temperatures are inversely related to BP; however, the effects of short-term temperature changes within a 24-hourperiod and measured with high accuracy at the personal level have not been described. Fifty-one nonsmoking patients living in the Detroit area had up to 5 consecutive days of 24-hour personal-level environmental temperature ( PET) monitoring along with daily cardiovascular measurements, including BP, performed mostly between 5 PM and 7 PM during summer and / or winter periods. The associations between hour-long mean PET levels during the previous 24 hours with the outcomes were assessed by linear mixed models. Accounting for demographics, environmental factors, and monitoring compliance, systolic and diastolic BP were positively associated with several hour-long PET measurements ending from 10 to 15 hours beforehand. During this time, corresponding mostly to a period starting from between 1AM and 3 AM to ending between 7 AM and 9 AM, an increase of 1 degrees C was associated with a 0.81 mm Hg to 1.44 mm Hg and 0.59 mm Hg to 0.83 mm Hg elevation in systolic and diastolic BP, respectively. Modestly warmer, commonly encountered PET levels posed a clinically meaningful effect ( eg, a 6.95 mm Hg systolic pressure increase per interquartile range (4.8 degrees C) elevation at lag hour 10). Community-level outdoor ambient temperatures were not related to BP. The authors provide the first evidence that personal exposure to warmer nighttime and early-morning environmental temperatures might lead to an increase in BP during the ensuing day. J Clin Hypertens ( Greenwich). 2011; 13: 881-888. (C) 2011 Wiley Periodicals, Inc.

Background: Ambient fine particulate matter < 2.5 μm (PM2.5) levels are associated with alterations in arterial hemodynamics and vascular function one or more days later. However, the characteristics of the same-day rapid exposure-response relationships within hours of exposures remain unclear. Objectives and Methods: We aimed to explore the effects of personal PM2.5 exposures within the preceding 24 hours on blood pressure (BP), heart rate (HR), brachial artery diameter (BAD), endothelial function (flow-mediated dilatation (FMD)) and nitroglycerin-mediated dilatation (NMD). Fifty-one non-smoking general population subjects living in Wayne County Michigan, who were participating in the Detroit Exposure and Aerosol Research Study conducted by the Environmental Protection Agency, had up to 5 consecutive days of 24-hour personal PM2.5 monitoring and daily cardiovascular (CV) measurements performed in their households during summer and/or winter periods. The associations between integrated hour-long total per...

Near-road air quality is an issue of emerging concern, with field studies consistently showing elevated air pollutant concentrations adjacent to major roads, usually decreasing to background levels within several hundred meters. Roadside barriers, both vegetative and structural, are expected to alter the dispersion patterns of trafficrelated emissions and the resulting ambient air pollutant concentrations. In order to understand the influence of roadside barriers on near-road air quality, an idealized computational fluid dynamics (CFD) model of a roadway was developed and simulated using FLUENT. The CFD turbulence model selection and surface roughness parameters were based on comparison with previous wind tunnel experiments. The model includes a sixlane highway and a single-lane access road parallel to the highway which are separated by a solid noise wall. The noise wall is finite in length, allowing the impact of barrier edges to be observed. Downwind normalized air pollutant concentrations (Chi) and turbulent kinetic energy (TKE) are compared for barrier versus no-barrier road segments. The presence of a roadside barrier was observed to significantly impact the horizontal and vertical profiles of Chi and TKE under neutral stability conditions. In addition, the evaluation of barrier-impacted emissions dispersion under oblique wind directions is discussed.

Background Higher ambient fine particulate matter (PM2.5) levels can be associated with increased blood pressure and vascular dysfunction. Objectives To determine the differential effects on blood pressure and vascular function of daily changes in community ambient- versus personal-level PM2.5 measurements. Methods Cardiovascular outcomes included vascular tone and function and blood pressure measured in 65 non-smoking subjects. PM2.5 exposure metrics included 24 h integrated personal- (by vest monitors) and community-based ambient levels measured for up to 5 consecutive days (357 observations). Associations between community- and personal-level PM2.5 exposures with alterations in cardiovascular outcomes were assessed by linear mixed models. Results Mean daily personal and community measures of PM2.5 were 21.9±24.8 and 15.4±7.5 μg/m3, respectively. Community PM2.5 levels were not associated with cardiovascular outcomes. However, a 10 μg/m3 increase in total personal-level PM2.5 exposure (TPE) was associated with systolic blood pressure elevation (+1.41 mm Hg; lag day 1, p<0.001) and trends towards vasoconstriction in subsets of individuals (0.08 mm; lag day 2 among subjects with low secondhand smoke exposure, p=0.07). TPE and secondhand smoke were associated with elevated systolic blood pressure on lag day 1. Flow-mediated dilatation was not associated with any exposure. Conclusions Exposure to higher personal-level PM2.5 during routine daily activity measured with low-bias and minimally-confounded personal monitors was associated with modest increases in systolic blood pressure and trends towards arterial vasoconstriction. Comparable elevations in community PM2.5 levels were not related to these outcomes, suggesting that specific components within personal and background ambient PM2.5 may elicit differing cardiovascular responses.

BACKGROUND: Levels of fine particulate matter [<= 2.5 mu m in aerodynamic diameter (PM2.5)] are associated with alterations in arterial hemodynamics and vascular function. However, the characteristics of the same-day exposure-response relationships remain unclear.OBJECTIVES: We aimed to explore the effects of personal PM2.5 exposures within the preceding 24 hr on blood pressure (BP), heart rate (HR), brachial artery diameter (BAD), endothelial function [flow-mediated dilatation (FMD)], and nitroglycerin-mediated dilatation (NMD).METHODS: Fifty-one nonsmoking subjects had up to 5 consecutive days of 24-hr personal PM2.5 monitoring and daily cardiovascular (CV) measurements during summer and/or winter periods. The associations between integrated hour-long total personal PM2.5 exposure (TPE) levels (continuous nephelometry among compliant subjects with low secondhand tobacco smoke exposures; n = 30) with the CV outcomes were assessed over a 24-hr period by linear mixed models.RESULTS: We observed the strongest associations (and smallest estimation errors) between HR and TPE recorded 1-10 hr before CV measurements. The associations were not pronounced for the other time lags (11-24 hr). The associations between TPE and FMD or BAD did not show as clear a temporal pattern. However, we found some suggestion of a negative association with FMD and a positive association with BAD related to TPE just before measurement (0-2 hr).CONCLUSIONS: Brief elevations in ambient TPE levels encountered during routine daily activity were associated with small increases in HR and trends toward conduit arterial vasodilatation and endothelial dysfunction within a few hours of exposure. These responses could reflect acute PM2.5-induced autonomic imbalance and may factor in the associated rapid increase in CV risk among susceptible individuals.