Christina H. Fuller

Indoor and outdoor measurements of particle number concentration in near-highway homes.

Exposure to high levels of traffic-generated particles may pose risks to human health; however, limited measurement has been conducted at homes near highways. The purpose of this study was to characterize differences between indoor and outdoor particle number concentration (PNC) in homes near to and distant from a highway and to identify factors that may affect infiltration. We monitored indoor and outdoor PNC (6–3000 nm) for 1–3 weeks at 18 homes located <1500 m from Interstate-93 (I-93) in Somerville, MA (USA). Median hourly indoor and outdoor PNC pooled over all homes were 5.2 × 103 and 5.9 × 103 particles/cm3, respectively; the median ratio of indoor-to-outdoor PNC was 0.95 (5th/95th percentile: 0.42/1.75). Homes <100 m from I-93 (n=4) had higher indoor and outdoor PNC compared with homes >1000 m away (n=3). In regression models, a 10% increase in outdoor PNC was associated with an approximately equal (10.8%) increase in indoor PNC. Wind speed and direction, temperature, time of day and weekday were also associated with indoor PNC. Average mean indoor PNC was lower for homes with air conditioners compared with homes without air conditioning. These results may have significance for estimating indoor, personal exposures to traffic-related air pollution.

A community participatory study of cardiovascular health and exposure to near-highway air pollution: study design and methods

Abstract Current literature is insufficient to make causal inferences or establish dose-response relationships for traffic-related ultrafine particles (UFPs) and cardiovascular (CV) health. The Community Assessment of Freeway Exposure and Health (CAFEH) is a cross-sectional study of the relationship between UFP and biomarkers of CV risk. CAFEH uses a community-based participatory research framework that partners university researchers with community groups and residents. Our central hypothesis is that chronic exposure to UFP is associated with changes in biomarkers. The study enrolled more than 700 residents from three near-highway neighborhoods in the Boston metropolitan area in Massachusetts, USA. All participants completed an in-home questionnaire and a subset (440+) completed an additional supplemental questionnaire and provided biomarkers. Air pollution monitoring was conducted by a mobile laboratory equipped with fast-response instruments, at fixed sites, and inside the homes of selected study participants. We seek to develop improved estimates of UFP exposure by combining spatiotemporal models of ambient UFP with data on participant time-activity and housing characteristics. Exposure estimates will then be compared with biomarker levels to ascertain associations. This article describes our study design and methods and presents preliminary findings from east Somerville, one of the three study communities.

Positional error and time-activity patterns in near-highway proximity studies: an exposure misclassification analysis

BackgroundThe growing interest in research on the health effects of near-highway air pollutants requires an assessment of potential sources of error in exposure assignment techniques that rely on residential proximity to roadways.MethodsWe compared the amount of positional error in the geocoding process for three different data sources (parcels, TIGER and StreetMap USA) to a “gold standard” residential geocoding process that used ortho-photos, large multi-building parcel layouts or large multi-unit building floor plans. The potential effect of positional error for each geocoding method was assessed as part of a proximity to highway epidemiological study in the Boston area, using all participants with complete address information (N = 703). Hourly time-activity data for the most recent workday/weekday and non-workday/weekend were collected to examine time spent in five different micro-environments (inside of home, outside of home, school/work, travel on highway, and other). Analysis included examination of whether time-activity patterns were differentially distributed either by proximity to highway or across demographic groups.ResultsMedian positional error was significantly higher in street network geocoding (StreetMap USA = 23 m; TIGER = 22 m) than parcel geocoding (8 m). When restricted to multi-building parcels and large multi-unit building parcels, all three geocoding methods had substantial positional error (parcels = 24 m; StreetMap USA = 28 m; TIGER = 37 m). Street network geocoding also differentially introduced greater amounts of positional error in the proximity to highway study in the 0–50 m proximity category. Time spent inside home on workdays/weekdays differed significantly by demographic variables (age, employment status, educational attainment, income and race). Time-activity patterns were also significantly different when stratified by proximity to highway, with those participants residing in the 0–50 m proximity category reporting significantly more time in the school/work micro-environment on workdays/weekdays than all other distance groups.ConclusionsThese findings indicate the potential for both differential and non-differential exposure misclassification due to geocoding error and time-activity patterns in studies of highway proximity. We also propose a multi-stage manual correction process to minimize positional error. Additional research is needed in other populations and geographic settings.

Response of biomarkers of inflammation and coagulation to short-term changes in central site, local, and predicted particle number concentrations

PURPOSE Previous studies have reported acute (hours-28 days) associations between ambient ultrafine particles (UFP; diameter <0.1) and biomarkers of cardiovascular health using central site data. We evaluated particle number concentration (a proxy measure for UFP) measured at a central site, a local near-highway site and predicted residential concentrations with response of biomarkers of inflammation and coagulation in a near-highway population. METHODS Participants provided two blood samples for analysis of interleukin-6 (IL-6), high-sensitivity C-reactive protein (hs-CRP), tumor necrosis factor-α receptor II, and fibrinogen. Mixed effect models were used to evaluate the association between PNC levels on the same day, prior 2 days, and moving averages of 3 to 28 days. RESULTS Estimated effects on biomarkers of a 5000 unit increase in central site PNC generally increased with longer averaging times for IL-6, hs-CRP, and fibrinogen. Effect estimates were highest for a 28-day moving average, with 91% (95% confidence interval [CI]: 9, 230) higher IL-6 levels, 74% (95% CI: -7, 220) higher hs-CRP levels, and 59% (95% CI: -13, 130) higher fibrinogen levels. We observed no clear trend between near-highway or predicted residential PNC and any of the biomarkers. CONCLUSIONS Only central site PNC increased blood markers of inflammation while near-highway and predicted residential values did not. We cannot fully explain this result, although differing PNC composition is a possibility. Future studies would assist in understanding these findings.

An Integrated Socio-Environmental Model of Health and Well-Being: a Conceptual Framework Exploring the Joint Contribution of Environmental and Social Exposures to Health and Disease Over the Life Span

Purpose of the reviewEnvironmental and social determinants of health often co-occur, particularly among socially disadvantaged populations, yet because they are usually studied separately, their joint effects on health are likely underestimated. Building on converging bodies of literature, we delineate a conceptual framework to address these issues.Recent findingsPrevious models provided a foundation for study in this area, and generated research pointing to additional important issues. These include a stronger focus on biobehavioral pathways, both positive and adverse health outcomes, and intergenerational effects. To accommodate the expanded set of issues, we put forward the Integrated Socio-Environmental Model of Health and Well-Being (ISEM), which examines how social and environmental factors combine and potentially interact, via multi-factorial pathways, to affect health and well-being over the life span. We then provide applied examples including the study of how food environments affect dietary behavior.SummaryThe ISEM provides a comprehensive, theoretically informed framework to guide future research on the joint contribution of social and environmental factors to health and well-being across the life span.

Phenology of a Vegetation Barrier and Resulting Impacts on Near-Highway Particle Number and Black Carbon Concentrations on a School Campus

Traffic-related air pollution is a persistent concern especially in urban areas where populations live in close proximity to roadways. Innovative solutions are needed to minimize human exposure and the installation of vegetative barriers shows potential as a method to reduce near-road concentrations. This study investigates the impact of an existing stand of deciduous and evergreen trees on near-road total particle number (PNC) and black carbon (BC) concentrations across three seasons. Measurements were taken during spring, fall and winter on the campus of a middle school in the Atlanta (GA, USA) area at distances of 10 m and 50 m from a major interstate highway. We identified consistent decreases in BC concentrations, but not for PNC, with increased distance from the highway. In multivariable models, hour of day, downwind conditions, distance to highway, temperature and relative humidity significantly predicted pollutant concentrations. The magnitude of effect of these variables differed by season, however, we were not able to show a definitive impact of the vegetative barrier on near-road concentrations. More detailed studies are necessary to further examine the specific configurations and scenarios that may produce pollutant and exposure reductions.

Socio-demographic Differences in Toxic Release Inventory Siting and Emissions in Metro Atlanta

Prior research has found that low socioeconomic status (SES) populations and minorities in some areas reside in communities with disproportionate exposure to hazardous chemicals. The objectives of this study were to evaluate the relevance of socio-demographic characteristics on the presence of Toxic Release Inventory (TRI) facilities, air releases, and prevalence and resolution of air quality complaints in the 20-county Atlanta Metropolitan Statistical Area (MSA). We found that there were 4.7% more minority residents in census tracts where TRI facilities were located. The odds ratio (OR) for the presence of a TRI facility was 0.89 (p < 0.01) for each 1% increase of females with a college degree and 2.4 (p < 0.01) for households with an income of

Mapping the Hidden Hazards: Community-Led Spatial Data Collection of Street-Level Environmental Stressors in a Degraded, Urban Watershed

22,000–

Short-and medium-term associations of particle number concentration with cardiovascular markers in a Puerto Rican cohort

55,000. The estimated reduction in the amount of chemicals emitted per release associated with population of females with a college degree was 18.53 pounds (p < 0.01). Complaints took longer to resolve in census tracts with higher Hispanic populations (OR = 1.031, 95% CI: 1.010–1.054). Overall, results indicate that SES and race/ethnicity are related to TRI facility siting, releases, and complaints in the Atlanta area. These findings have not been documented previously and suggest that lower SES and non-White communities may be disproportionately exposed.

Passive methods for improving air quality in the built environment: A review of porous and solid barriers

We utilized a participatory mapping approach to collect point locations, photographs, and descriptive data about select built environment stressors identified and prioritized by community residents living in the Proctor Creek Watershed, a degraded, urban watershed in Northwest Atlanta, Georgia. Residents (watershed researchers) used an indicator identification framework to select three watershed stressors that influence urban livability: standing water, illegal dumping on land and in surface water, and faulty stormwater infrastructure. Through a community–university partnership and using Geographic Information Systems and digital mapping tools, watershed researchers and university students designed a mobile application (app) that enabled them to collect data associated with these stressors to create a spatial narrative, informed by local community knowledge, that offers visual documentation and representation of community conditions that negatively influence the environment, health, and quality of life in urban areas. By elevating the local knowledge and lived experience of community residents and codeveloping a relevant data collection tool, community residents generated fine-grained, street-level, actionable data. This process helped to fill gaps in publicly available datasets about environmental hazards in their watershed and helped residents initiate solution-oriented dialogue with government officials to address problem areas. We demonstrate that community-based knowledge can contribute to and extend scientific inquiry, as well as help communities to advance environmental justice and leverage opportunities for remediation and policy change.