Traffic-related Ultrafine Particles Research Articles

Traffic-related ultrafine particles impair mitochondrial functions in human olfactory mucosa cells – Implications for Alzheimer's disease

Constituents of air pollution, the ultrafine particles (UFP) with a diameter of ≤0.1 μm, are considerably related to traffic emissions. Several studies link air pollution to Alzheimer's disease (AD), yet the exact relationship between the two remains poorly understood. Mitochondria are known targets of environmental toxicants, and their dysfunction is associated with neurodegenerative diseases. The olfactory mucosa (OM), located at the rooftop of the nasal cavity, is directly exposed to the environment and in contact with the brain. Mounting evidence suggests that the UFPs can impact the brain directly through the olfactory tract. By using primary human OM cultures established from nasal biopsies of cognitively healthy controls and individuals diagnosed with AD, we aimed to decipher the effects of traffic-related UFPs on mitochondria. The UFP samples were collected from the exhausts of a modern heavy-duty diesel engine (HDE) without aftertreatment systems, run with renewable diesel (A0) and petroleum diesel (A20), and from an engine of a 2019 model diesel passenger car (DI-E6d) equipped with state-of-the-art aftertreatment devices and run with renewable diesel (Euro6). OM cells were exposed to three different UFPs for 24-h and 72-h, after which cellular processes were assessed on the functional and transcriptomic levels. Our results show that UFPs impair mitochondrial functions in primary human OM cells by hampering oxidative phosphorylation (OXPHOS) and redox balance, and the responses of AD cells differ from cognitively healthy controls. RNA-Seq and IPA® revealed inhibition of OXPHOS and mitochondrial dysfunction in response to UFPs A0 and A20. Functional validation confirmed that A0 and A20 impair cellular respiration, decrease ATP levels, and disturb redox balance by altering NAD and glutathione metabolism, leading to increased ROS and oxidative stress. RNA-Seq and functional assessment revealed the presence of AD-related alterations in human OM cells and that different fuels and engine technologies elicit differential effects.

The Exposure Peaks of Traffic-Related Ultrafine Particles Associated with Inflammatory Biomarkers and Blood Lipid Profiles.

In this article, we explored the effects of ultrafine particle (UFP) peak exposure on inflammatory biomarkers and blood lipids using two novel metrics-the intensity of peaks and the frequency of peaks. We used data previously collected by the Community Assessment of Freeway Exposure and Health project from participants in the Greater Boston Area. The UFP exposure data were time-activity-adjusted hourly average concentration, estimated using land use regression models based on mobile-monitored ambient concentrations. The outcome data included C-reactive protein, interleukin-6 (IL-6), tumor necrosis factor-alpha receptor 2 (TNF-RII), low-density lipoprotein (LDL), high-density lipoprotein (HDL), triglycerides and total cholesterol. For each health indicator, multivariate regression models were used to assess their associations with UFP peaks (N = 364-411). After adjusting for age, sex, body mass index, smoking status and education level, an increase in UFP peak exposure was significantly (p < 0.05) associated with an increase in TNF-RII and a decrease in HDL and triglycerides. Increases in UFP peaks were also significantly associated with increased IL-6 and decreased total cholesterol, while the same associations were not significant when annual average exposure was used. Our work suggests that analysis using peak exposure metrics could reveal more details about the effect of environmental exposures than the annual average metric.

Acceptability of air purifiers to reduce traffic-related particulate exposure near a highway

Background and aim: Traffic-related ultrafine particle pollution near highways has been associated with adverse health. Reducing exposure by use of portable air purifiers in homes is one way to try to reduce this risk. However, acceptability of having air purifiers in homes is not well studied. Methods: We collected data via questionnaires (N=43 surveys at the end of the first month of the intervention), interviews (N=19) and HOBO monitors on air purifiers (N=14) from participants in our randomized crossover trial of air purifiers in homes near a major highway. Results: From survey questions, only 17% and 12% were bothered by noise of the air purifier in the living room and bedroom, respectively. Most survey respondents, 75% and 68%, again for living room and bedroom, reported they set the air purifier to medium air flow. In qualitative interviews, Seventy-four percent (74%) reported that they did not move their air purifiers, but 63% changed the fan speed, many to reduce noise or air flow. Only 21% said that they ever turned it off. Space, noise, airflow and energy consumption were the main concerns from interviews, while cleaner air, improved symptoms and white noise were positives. Data on electricity use indicates &amp;#x3e;95% compliance of use on a consistent setting (majority choose medium) during our intervention. We have had few participants drop out after their first home data collection visit, with 36 completing the entire intervention, 20 still actively in the intervention and only one lost to follow-up. Conclusions: Evidence from surveys, interviews and HOBO monitors suggests that a small minority of participants were bothered by noise, space issues or air movement from the air purifiers and that they are largely accepted and used by residents near a highway, albeit on settings below maximal air flow.

A new exposure metric for the cumulative effect of short-term exposure peaks of traffic-related ultrafine particles.

The adverse health outcomes of traffic-related ultrafine particles (UFPs) disproportionally impact near-highway neighborhoods. Current studies focus on either short-term health outcomes associated with short-term UFP exposures averaged over days or weeks, or long-term outcomes associated with long-term (yearly or longer) average UFP exposures. We hypothesized that frequent and repeated exposure to short-term UFP peaks that last for just hours could overwhelm or alter physiological defensive responses, resulting in long-term health issues. Herein, we propose a new exposure metric for measuring the cumulative effect of these peak exposures. We used UFP exposure data estimated by the Community Assessment of Freeway Exposure and Health (CAFEH) project, which recruited 704 participants from three pairs of near-highway/urban background neighborhoods in the Greater Boston Area between 2009 and 2012. CAFEH developed land use regression (LUR) models to estimate hourly averages of ambient UFP levels within the study areas based on mobile-monitored UFP data, and applied time-activity adjustment (TAA) to calculate adjusted final hourly estimates. Our alternative metric assigns cumulative peak exposure, which is determined as either the intensity (a high percentile of an individual's adjusted hourly UFP estimates) or the frequency (the number of hours with adjusted UFP estimates greater than a high percentile of all adjusted hourly UFP estimates of all participants in the study area) of UFP peaks. After TAA was applied, for most of the time, our cumulative peak exposure metrics were not strongly correlated with the annual average. However, the level of correlation varied greatly from neighborhood to neighborhood (Spearman's R ranges from 0.39 to 0.97). There was variation in UFP peak exposure that was not explained by the annual average, suggesting that our proposed peak metric distinct from annual average exposure metric.

Coagulation patterns and the impacts on traffic-related ultrafine particle dispersion in road tunnels employing dynamic mesh algorithms.

.In this study, we continue to analyze the diffusion mechanism of ultrafine particles and the particle coagulation phenomenon with a size range of 26-287 nm exhausted from vehicles during the process of passing through a 100-m-long tunnel using the realizable k-ε model and dynamic grid technique. A three-dimensional model consisting of a 100-m highway tunnel and four side-by-side gasoline vehicles (L × W × H = 4.5 m × 1.8 m × 1.5 m) was established in the STAR-CCM+ computational fluid dynamics software. The gasoline vehicles traveled simultaneously under different situations of three driving speeds of 60 km h-1, 40 km h-1, and 20 km h-1 during the simulation. Through data analysis and research, it was found that the coagulation process of particles is very complicated, especially at low speeds. When the vehicle speed is 20 km h-1, the variation in particle concentration at the vehicle wake near the tailpipe (at the vertical plane located 0.1 m behind the exhaust pipe) causes a large error if the coagulation action is not considered. The relative error of the average particle concentration at 0.5 s of the vertical section 0.1 m away from the exhaust pipe is as high as 193.51%. The relative error in the entire tunnel is only 2.82%, which is less than 5%. Thus, it is recommended that particle coagulation should be considered when analyzing particle dispersion in the near-wake region behind the vehicle and the breathing areas, especially when the vehicle travels slowly inside the tunnel. However, when evaluating the particle concentration and exposure levels for the entire tunnel, coagulation can be ignored without significant errors, especially at a high vehicle speeds. This study clarified the importance of coagulation in different areas and its influence on the diffusion of particulate matter. This is conducive to further analysis of the diffusion characteristics of particulate matter and can appreciably reduce the pollution degree in a tunnel by changing the coagulation efficiency of particulate matter in the future.

An Evaluation of an Environmental Health Infographic in Community Settings.

Background: Infographics are an effective way of communicating complex information due to their reliance on concise language and clear, uncluttered visuals. Research indicates that traffic-related ultrafine particles (UFPs) in air pollutions adversely affect human health, including respiratory and cardiovascular diseases. In this study, we work with community-based adult literacy programs to develop an infographic about UFPs in air pollution with the goal of community-driven problem solving related to traffic-related UFPs within affected neighborhoods. Objective: In this paper, we discuss the development and evaluation of an infographic about the dangers of UFPs from traffic pollution, and actions that readers in affected communities can take to protect their health. We used the infographic format to conceptualize UFP pollution and its health effects visually for community members many of whom are new immigrants and do not speak English as their first language. Methods: We conducted 1 focus group and 4 interviews over Zoom, and collected 74 anonymous surveys among Boston Chinatown and Somerville, MA residents. Community partner organizations assisted us in recruiting participants by sending a recruitment flyer to their email contacts and identifying specific people who were interested in participating. Key Results: Data from the surveys, focus group, and interviews yielded 8 themes that guided the revision of the infographic. The majority of the participants responded positively to the infographic: 95.9% (n = 71) of respondents reported that the purpose of the infographic was clear, that the infographic contained a clear message, and that the infographic uses images to explain important points. Conclusions: Our experience developing and evaluating an infographic about near highway pollution in environmental justice communities suggests that infographics can be a viable communication tool in this context. Further research with infographics of a similar nature but in diverse communities is needed to strengthen our conclusion.

A New Exposure Metric for the Cumulative Effect of Short-term Peaks of Exposure to Traffic-related Ultrafine Particles

Introduction Traffic-related ultrafine particles (UFPs) can cause adverse health outcomes through inflammatory reactions. Current epidemiology studies focus on either short-term health outcomes associated with UFP levels averaged over days or weeks, or long-term outcomes associated with a long-term (annual or longer) average exposure to UFP. We hypothesize that frequent and repeated exposure to short-term UFP peaks that last for just one or a few hours could overwhelm human’s biological defenses, which may result in long-term health effects. We propose a new exposure metric for measuring the cumulative effect of the peaks. Method Our study uses data collected by the Community Assessment of Freeway Exposure and Health (CAFEH) project, which recruited 704 participants from six “near-highway” or “urban background” neighborhoods in the Greater Boston Area between 2009 and 2012. The CAFEH project developed land use regression models to estimate hourly averages of ambient UFP level throughout the study areas, and applied time-activity adjustment to calculate the adjusted hourly estimate. Our alternative metric is the cumulative peak exposure, determined by the intensity (the 99th percentile of an individual’s adjusted hourly UFP estimates) and the frequency (the number of hours with the UFP level higher than the 99th percentile of all adjusted hourly UFP estimates of all participants) of UFP peaks. Results The cumulative peak exposure does not always correlate well with the annual average, especially in certain near-highway neighborhoods. (Pearson’s R between the intensity of UFP peaks and the annual average of hourly UFP estimates ranges from 0.33 to 0.98.) Thus, it appears that there is still sufficient variation within the residents’ UFP peak exposure after holding their annual average constant, which suggests they are distinct measurements. Conclusion Measuring the cumulative effect of peak exposures may provide a new exposure assessment metric that could be tested for association with long-term health outcomes.

An estimate of the exposure-response relationship between traffic-related ultrafine particles and systolic blood pressure

Exposure to traffic-related air pollution (TRAP) is associated with adverse health outcomes, including hypertension and elevated blood pressure; however, the nature of the exposure-response functions for these associations is not well established. In a previous three-exposure, three-period crossover trial we showed that using portable HEPA filters to reduce indoor infiltration of TRAP was significantly effective in preventing short-term average increases in systolic blood pressure (SBP). We measured particle number concentrations (PNC), black carbon (BC) concentrations, and room temperatures continuously during the trial, and we measured participant blood pressures every 10 minutes. We then examined the relationship between SBP and PNC. A total of 1321 SBPs arising from 76 participants were analyzed. The average age of the participants was 60 years, 79% were female, 77% were Asian, and 17% were White. None had serious health conditions. The average SBP was 120.0 mmHg and the average particle number concentration (PNC) was 13,000 particles/cm3, ranging from 860 to 99,000 particles/cm3. A linear mixed model was used to fit a curvilinear relationship between SBP and PNC. The model included BC concentrations and room temperatures as covariates, as well as a random intercept to account for the interdependence of multiple SBPs recorded from each participant. The resulting adjusted model, yielding statistically significant regression coefficients (p &lt; 0.001), can be written as: SBP = 117.54 + 1.22 (PNC/5000) - 0.059 (PNC/5000)2, which implies that SBP increases by 1.22 mmHg for every 5000 particles/cm3 increase in PNC but tapers off at higher levels of PNC. For example, at 5000 particles/cm3 the average SBP is expected to be 118.7 mmHg, but it increases to 121.0 mmHg at 15,000 particles/cm3 and to 124.5 mmHg at 30,000 particles/cm3. The results of the present study suggest an exposure-response function for SBP and PNC.

Impacts of the COVID-19 responses on traffic-related air pollution in a Northwestern US city

This study evaluates the COVID-19 impacts on traffic-related air pollution, including ultrafine particles (UFPs), PM2.5, black carbon (BC), NO, NO2, NOx, and CO in a Northwestern US city. Hourly traffic, air pollutants, and meteorological data on/near a major freeway in the downtown of Seattle, Washington, were collected for five weeks before and ten weeks after the Washington Stay Home Order (SHO) was enacted, respectively (February 17–May 31, 2020). The pollutants between pre- and post-SHO periods were compared, and their differences were statistically tested. Besides, first-order multivariate autoregressive (MAR(1)) models were developed to reveal the impacts specific to the change of traffic due to the COVID-19 responses while controlling for meteorological conditions. Results indicate that compared with those in the post-SHO period, the median traffic volume and road occupancy decreased by 37% and 52%, respectively. As for pollutants, the median BC and PM2.5 levels significantly decreased by 25% and 33%, relatively, while NO, NO2, NOx, and CO decreased by 33%, 29%, 30%, and 17%, respectively. In contrast, neither size-resolved UFPs nor total UFPs showed significant changes between the two periods, although larger particles (≥115.5 nm) decreased by 4–29%. Additionally, significant differences were found in meteorological conditions between the two periods. Based on the MAR(1) models, controlling for meteorological conditions, the COVID-19 responses were associated with significant decreases in median levels of traffic-related pollutants including 11.5–154.0 nm particles (ranging from −3% [95% confidence interval (CI): −1%, −4%] to −12% [95% CI: −10%, −14%]), total UFPs (−7% [95% CI: −5%, −8%]), BC (−6% [95% CI: −5%, −7%]), PM2.5 (−2% [95% CI: −1%, −3%]), NO, NO2, NOx (ranging from −3% [95% CI: −2%, −4%] to −10% [95% CI: −18%, −12%]), and CO (−4% [95% CI, −3%, −5%]). These findings illustrate that the conclusion of the COVID-19 impacts on urban traffic-related air pollutant levels could be completely different in scenarios whether meteorology was adjusted for or not. Fully adjusting for meteorology, this study shows that the COVID-19 responses were associated with much more reductions in traffic-related UFPs than PM2.5 in the Seattle region, in contrast to the reverse trend from the direct empirical data comparison.

An instantaneous spatiotemporal model for predicting traffic-related ultrafine particle concentration through mobile noise measurements

People living near roadways are exposed to high concentrations of ultrafine particles (UFP, diameter < 100 nm). This can result in adverse health effects such as respiratory illness and cardiovascular diseases. However, accurately characterizing the UFP number concentration requires expensive sets of instruments. The development of an UFP surrogate with cheap and convenient measures is needed. In this study, we used a mobile measurement platform with a Fast Mobility Particle Sizer (FMPS) and sound level meter to investigate the spatiotemporal relations of noise and UFP and identify the hotspots of UFP. UFP concentration levels were significantly influenced by temporal and spatial variations (p < 0.001). We proposed a Generalized Additive Models to predict UFP number concentration in the study area. The model uses noise and meteorological covariates to predict the UFP number concentrations at an industrial site in Taichung, Taiwan. During the one year sampling campaign from fall 2013 to summer 2014, mobile measurements were performed at least one week for each season, both on weekdays and weekends. The proposed model can explain 80% of deviance and has coefficient of determination (R2) of 0.77. Moreover, the developed UFP model was able to adequately predict UFP concentrations, and can provide people with a convenient way to determine UFP levels. Finally, the results from this study could help facilitate the future development of noise mobile measurement.

Comparisons of traffic-related ultrafine particle number concentrations measured in two urban areas by central, residential, and mobile monitoring

Traffic-related ultrafine particles (UFP; <100 nanometers diameter) are ubiquitous in urban air. While studies have shown that UFP are toxic, epidemiological evidence of health effects, which is needed to inform risk assessment at the population scale, is limited due to challenges of accurately estimating UFP exposures. Epidemiologic studies often use empirical models to estimate UFP exposures; however, the monitoring strategies upon which the models are based have varied between studies. Our study compares particle number concentrations (PNC; a proxy for UFP) measured by three different monitoring approaches (central-site, short-term residential-site, and mobile on-road monitoring) in two study areas in metropolitan Boston (MA, USA). Our objectives were to quantify ambient PNC differences between the three monitoring platforms, compare the temporal patterns and the spatial heterogeneity of PNC between the monitoring platforms, and identify factors that affect correlations across the platforms. We collected >12,000 hours of measurements at the central sites, 1,000 hours of measurements at each of 20 residential sites in the two study areas, and >120 hours of mobile measurements over the course of ~1 year in each study area. Our results show differences between the monitoring strategies: mean one-minute PNC on-roads were higher (64,000 and 32,000 particles/cm3 in Boston and Chelsea, respectively) compared to central-site measurements (23,000 and 19,000 particles/cm3) and both were higher than at residences (14,000 and 15,000 particles/cm3). Temporal correlations and spatial heterogeneity also differed between the platforms. Temporal correlations were generally highest between central and residential sites, and lowest between central-site and on-road measurements. We observed the greatest spatial heterogeneity across monitoring platforms during the morning rush hours (06:00-09:00) and the lowest during the overnight hours (18:00-06:00). Longer averaging times (days and hours vs. minutes) increased temporal correlations (Pearson correlations were 0.69 and 0.60 vs. 0.39 in Boston; 0.71 and 0.61 vs. 0.45 in Chelsea) and reduced spatial heterogeneity (coefficients of divergence were 0.24 and 0.29 vs. 0.33 in Boston; 0.20 and 0.27 vs. 0.31 in Chelsea). Our results suggest that combining stationary and mobile monitoring may lead to improved characterization of UFP in urban areas and thereby lead to improved exposure assignment for epidemiology studies.

Assessing the Suitability of Multiple Dispersion and Land Use Regression Models for Urban Traffic-Related Ultrafine Particles.

Comparative evaluations are needed to assess the suitability of near-road air pollution models for traffic-related ultrafine particle number concentration (PNC). Our goal was to evaluate the ability of dispersion (CALINE4, AERMOD, R-LINE, and QUIC) and regression models to predict PNC in a residential neighborhood (Somerville) and an urban center (Chinatown) near highways in and near Boston, Massachusetts. PNC was measured in each area, and models were compared to each other and measurements for hot (>18 °C) and cold (<10 °C) hours with wind directions parallel to and perpendicular downwind from highways. In Somerville, correlation and error statistics were typically acceptable, and all models predicted concentration gradients extending ∼100 m from the highway. In contrast, in Chinatown, PNC trends differed among models, and predictions were poorly correlated with measurements likely due to effects of street canyons and nonhighway particle sources. Our results demonstrate the importance of selecting PNC models that align with study area characteristics (e.g., dominant sources and building geometry). We applied widely available models to typical urban study areas; therefore, our results should be generalizable to models of hourly averaged PNC in similar urban areas.

Developing an evidence based zoning ordinance to reduce exposure to traffic-related ultrafine particles

Introduction: As a result of increasing evidence that traffic-related ultrafine particles (UFP) present a health risk there is a need to develop protective measures. In the absence of regulations, community-level responses are particularly important. Methods: We drew on the broader literature as well as findings from our own research to develop a zoning ordinance for the City of Somerville, MA, USA. Previous work included near-highway land use regression (LUR) modeling, individualized exposure assessment and demonstration of associations with blood biomarkers of inflammation for residents of Somerville. Additionally, we conducted indoor and outdoor monitoring for near highway housing to test efficacy of current HVAC filtration at reducing UFP levels. Results: Our proposed rule would apply to new residential developments and significantly rehabilitated housing near major roadways. Based on the LUR models, housing would be included if it was &lt;100 feet (30 m) from roads with &gt;10,000 vehicle trips/day (v/d). The buffer distance would increase an additional 100 feet for every 10,000 additional v/d to a maximum buffer of 500 feet (150 m) for roadways of &gt;50,000 v/d. UFP levels within housing inside the buffer would be required to be 80% lower than outdoor levels based on predicted health risk and feasibility. There would also be credits for use of physical barriers, distance buffers and protective placement of air intake vents. A detailed air monitoring protocol was developed to measure compliance. Our ordinance is currently under consideration for inclusion in the zoning code for the city. Conclusions: Our ordinance, which was developed cooperatively with the city government, shows the viability of local regulations that protect against exposure to traffic-related UFP. There is a need for research to test whether measures of this sort effectively reduce exposure and are also associated with health benefits.

Long-term Exposure to Ambient Air Pollution and Incidence of Brain Cancer: The Danish Nurse Cohort

Introduction: Experimental studies suggest that traffic-related ultrafine particles can cross blood-brain barrier leading to neurotoxicity and development of brain tumors in animals, but epidemiological evidence in humans is sparse. We examine association between long-term exposure to air pollution and incidence of brain cancer, for the first time with particulate matter with diameter &lt; 2.5 (PM2.5). Methods: For 28,731 nurses (age ≥ 44 years) from the Danish Nurse Cohort, recruited in 1993 or 1999, we obtained data on brain cancer incidence until 2013 from Danish Cancer Register, and estimated levels of PM2.5, particulate matter with diameter &lt;10 µm (PM10), nitrogen oxides (NOx) and nitrogen dioxide (NO2) at residence since 1990 using a dispersion model. We examined association between 3-year running mean of pollutants and brain tumor incidence using a time-varying Cox regression, separately for total brain cancer, and for subtypes by location (brain or meninges) and malignancy (malignant or benign). Results: Of 25,143 cancer-free nurses at recruitment 121 developed brain tumor during 15.7 years of follow-up. We found weak positive association between total brain cancer and PM2.5 (Hazard Ratio: 1.06; 95% Confidence Interval: 0.80-1.40) per interquartile range (IQR, 3.37 µg/m3) and NO2 (1.09; 0.91-1.29) per 7.5 µg/m3 and none with NOx or PM10. Associations with PM2.5 and NO2 were stronger for tumor located in meninges than in brain, and for benign than for malignant tumors. Finally, associations of total brain cancer with PM2.5 were modified by body mass index and were statistically significantly enhanced in obese women (2.03; 1.35-3.05). Conclusion: We found weak evidence of association between long-term exposure to PM2.5 and development of brain cancer in women older than 44 years. Findings of relevance of air pollution for meninges and benign tumors, as well that obese women may be most susceptible, requires further investigation.

Effect of time-activity adjustment on exposure assessment for traffic-related ultrafine particles

Exposures to ultrafine particles (<100 nm, estimated as particle number concentration, PNC) differ from ambient concentrations because of the spatial and temporal variability of both PNC and people. Our goal was to evaluate the influence of time-activity adjustment on exposure assignment and associations with blood biomarkers for a near-highway population. A regression model based on mobile monitoring and spatial and temporal variables was used to generate hourly ambient residential PNC for a full year for a subset of participants (n=140) in the Community Assessment of Freeway Exposure and Health study. We modified the ambient estimates for each hour using personal estimates of hourly time spent in five micro-environments (inside home, outside home, at work, commuting, other) as well as particle infiltration. Time-activity adjusted (TAA)-PNC values differed from residential ambient annual average (RAA)-PNC, with lower exposures predicted for participants who spent more time away from home. Employment status and distance to highway had a differential effect on TAA-PNC. We found associations of RAA-PNC with high sensitivity C-reactive protein and Interleukin-6, although exposure-response functions were non-monotonic. TAA-PNC associations had larger effect estimates and linear exposure-response functions. Our findings suggest that time-activity adjustment improves exposure assessment for air pollutants that vary greatly in space and time.

Comparison of Regression Models of Traffic-Related Ultrafine Particles in Three Near-Highway Neighborhoods in the Metropolitan Boston Area

Comparison of Regression Models of Traffic-Related Ultrafine Particles in Three Near-Highway Neighborhoods in the Metropolitan Boston Area

Association between personal exposures to traffic related ultrafine particles and biomarkers of cardiovascular health

Background: Ultrafine particles (<100 nm, UFP) are elevated near highways and major roadways and could influence cardiovascular health, but personal exposures may differ significantly from ambient ...

Mobile monitoring of traffic-related ultrafine particles in near-highway neighborhoods in Boston, Massachusetts (USA)

Background: Intensive mobile monitoring data are needed for development of models for exposure assessment of ultrafine particles (UFP) and other traffic-related air pollutants in near-highway urban...

Regression Models of traffic-related ultrafine particles in Near-Highway Neighborhoods

Regression Models of traffic-related ultrafine particles in Near-Highway Neighborhoods

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

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.