Characterizing temporal trends in populations exposed to aircraft noise around U.S. airports: 1995-2015.

BACKGROUND: Aircraft noise is a key concern for communities surrounding airports, with increasing evidence for health effects and inequitable distributions of exposure. However, there have been limited national-scale assessments of aircraft noise exposure over time and across noise metrics, limiting evaluation of population exposure patterns. OBJECTIVE: We evaluated national-scale temporal trends in aviation noise exposure by airport characteristics and across racial/ethnic populations in the U.S. METHODS: Noise contours were modeled for 90 U.S. airports in 5-year intervals between 1995 and 2015 using the Federal Aviation Administration's Aviation Environmental Design Tool. We utilized linear fixed effects models to estimate changes in noise exposure areas for day-night average sound levels (DNL) of 45, 65, and a nighttime equivalent sound level (Lnight) of 45 A-weighted decibels (dB[A]). We used group-based trajectory modeling to identify distinct groups of airports sharing underlying characteristics. We overlaid noise contours and Census tract data from the U.S. Census Bureau and American Community Surveys for 2000 to 2015 to estimate exposure changes overall and by race/ethnicity. RESULTS: National-scale analyses showed non-monotonic trends in mean exposed areas that peaked in 2000, followed by a 37% decrease from 2005 to 2010 and a subsequent increase in 2015. We identified four distinct trajectory groups of airports sharing latent characteristics related to size and activity patterns. Those populations identifying as minority (e.g., Hispanic/Latino, Black/African American, Asian) experienced higher proportions of exposure relative to their subgroup populations compared to non-Hispanic or White populations across all years, indicating ethnic and racial disparities in airport noise exposure that persist over time. SIGNIFICANCE: Overall, these data identified differential exposure trends across airports and subpopulations, helping to identify vulnerable communities for aviation noise in the U.S. IMPACT STATEMENT: We conducted a descriptive analysis of temporal trends in aviation noise exposure in the U.S. at a national level. Using data from 90 U.S. airports over a span of two decades, we characterized the noise exposure trends overall and by airport characteristics, while estimating the numbers of exposed by population demographics to help identify the impact on vulnerable communities who may bear the burden of aircraft noise exposure.

Assessing the impact of aircraft arrival on ambient ultrafine particle number concentrations in near-airport communities in Boston, Massachusetts.

Aircraft emissions contribute to overall ambient air pollution, including ultrafine particle (UFP) concentrations. However, accurately ascertaining aviation contributions to UFP is challenging due to high spatiotemporal variability along with intermittent aviation emissions. The objective of this study was to evaluate the impact of arrival aircraft on particle number concentration (PNC), a proxy for UFP, across six study sites 3-17 km from a major arrival aircraft flight path into Boston Logan International Airport by utilizing real-time aircraft activity and meteorological data. Ambient PNC at all monitoring sites was similar at the median but had greater variation at the 95th and 99th percentiles with more than two-fold increases in PNC observed at sites closer to the airport. PNC was elevated during the hours with high aircraft activity with sites closest to the airport exhibiting stronger signals when downwind from the airport. Regression models indicated that the number of arrival aircraft per hour was associated with measured PNC at all six sites, with a maximum contribution of 50% of total PNC at a monitor 3 km from the airport during hours with arrival activity on the flight path of interest (26% across all hours). Our findings suggest strong but intermittent contributions from arrival aircraft to ambient PNC in communities near airports.

An exploratory analysis of sociodemographic characteristics with ultrafine particle concentrations in Boston, MA.

Little is known of the relationship between exposure to the smallest particles of air pollution and socio-demographic characteristics. This paper explores linkages between ultrafine particle (UFP) concentrations and indicators of both race/ethnicity and socioeconomic status in Boston, Massachusetts, USA. We used estimates of UFP based on a highly-resolved land-use regression model of concentrations. In multivariate linear regression models census block groups with high proportions of Asians were associated with higher levels of UFP in comparison to block groups with majority White or other minority groups. Lower UFP concentrations were associated with higher homeownership (indicating higher SES) and with higher female head of household (indicating lower socioeconomic status). One explanation for the results include the proximity of specific groups to traffic corridors that are the main sources of UFP in Boston. Additional studies, especially at higher geographic resolution, are needed in Boston and other major cities to better characterize UFP concentrations by sociodemographic factors.

Sociodemographic Patterns of Exposure to Civil Aircraft Noise in the United States.

BACKGROUND: Communities with lower socioeconomic status and higher prevalence of racial/ethnic minority populations are often more exposed to environmental pollutants. Although studies have shown associations between aircraft noise and property values and various health outcomes, little is known about how aircraft noise exposures are sociodemographically patterned. OBJECTIVE: Our aim was to describe characteristics of populations exposed to aviation noise by race/ethnicity, education, and income in the United States. METHODS: Aircraft noise contours characterized as day-night average sound level (DNL) were developed for 90 U.S. airports in 2010 for DNL ≥45 dB(A) in 1-dB(A) increments. We compared characteristics of exposed U.S. Census block groups at three thresholds (≥45, ≥55, and ≥65 dB(A)), assigned on the basis of the block group land area being ≥50% within the threshold, vs. unexposed block groups near study airports. Comparisons were made across block group race/ethnicity, education, and income categories within the study areas (n=4,031-74,253). We performed both multinomial and other various multivariable regression approaches, including models controlling for airport and models with random intercepts specifying within-airport effects and adjusting for airport-level means. RESULTS: Aggregated across multiple airports, block groups with a higher Hispanic population had higher odds of being exposed to aircraft noise. For example, the multinomial analysis showed that a 10-percentage point increase in a block group's Hispanic population was associated with an increased odds ratio of 39% (95% CI: 25%, 54%) of being exposed to ≥65 dB(A) compared with block groups exposed to <45 dB(A). Block groups with higher proportions of residents with only a high school education had higher odds of being exposed to aircraft noise. Results were robust across multiple regression approaches; however, there was substantial heterogeneity across airports. DISCUSSION: These results suggest that across U.S. airports, there is indication of sociodemographic disparities in noise exposures. https://doi.org/10.1289/EHP9307.

Prenatal Ambient Ultrafine Particle Exposure and Childhood Asthma in the Northeastern United States.

Rationale: Ambient ultrafine particles (UFPs; with an aerodynamic diameter < 0.1 µm) may exert greater toxicity than other pollution components because of their enhanced oxidative capacity and ability to translocate systemically. Studies examining associations between prenatal UFP exposure and childhood asthma remain sparse. Objectives: We used daily UFP exposure estimates to identify windows of susceptibility of prenatal UFP exposure related to asthma in children, accounting for sex-specific effects. Methods: Analyses included 376 mother-child dyads followed since pregnancy. Daily UFP exposure during pregnancy was estimated by using a spatiotemporally resolved particle number concentration prediction model. Bayesian distributed lag interaction models were used to identify windows of susceptibility for UFP exposure and examine whether effect estimates varied by sex. Incident asthma was determined at the first report of asthma (3.6 ± 3.2 yr). Covariates included maternal age, education, race, and obesity; child sex; nitrogen dioxide (NO2) and temperature averaged over gestation; and postnatal UFP exposure. Measurements and Main Results: Women were 37.8% Black and 43.9% Hispanic, with 52.9% reporting having an education at the high school level or lower; 18.4% of children developed asthma. The cumulative odds ratio (95% confidence interval) for incident asthma per doubling of the UFP exposure concentration across pregnancy was 4.28 (1.41-15.7), impacting males and females similarly. Bayesian distributed lag interaction models indicated sex differences in the windows of susceptibility, with the highest risk of asthma seen in females exposed to higher UFP concentrations during late pregnancy. Conclusions: Prenatal UFP exposure was associated with asthma development in children, independent of correlated ambient NO2 and temperature. Findings will benefit future research and policy-makers who are considering appropriate regulations to reduce the adverse effects of UFPs on child respiratory health.

Reductions in traffic-related black carbon and ultrafine particle number concentrations in an urban neighborhood during the COVID-19 pandemic.

We investigated changes in traffic-related air pollutant concentrations in an urban area during the COVID-19 pandemic. The study was conducted in a mixed commercial-residential neighborhood in Somerville (MA, USA), where traffic is the dominant source of air pollution. Measurements were made between March 27 and May 14, 2020, coinciding with a dramatic reduction in traffic (71% drop in car and 46% drop in truck traffic) due to business shutdowns and a statewide stay-at-home advisory. Indicators of fresh vehicular emissions (ultrafine particle number concentration [PNC] and black carbon [BC]) were measured with a mobile monitoring platform on an interstate highway and major and minor roadways. Our results show that depending on road class, median PNC and BC contributions from traffic were 60-68% and 22-46% lower, respectively, during the lockdown compared to pre-pandemic conditions, and corresponding reductions in total on-road concentrations were 45-69% and 22-56%, respectively. A higher BC: PNC concentration ratio was observed during the lockdown period likely indicative of the higher fraction of diesel vehicles in the fleet during the lockdown. Overall, the scale of reductions in ultrafine particle and BC concentrations was commensurate with the reductions in traffic. This natural experiment allowed us to quantify the direct impacts of reductions in traffic emissions on neighborhood-scale air quality, which are not captured by the regional regulatory-monitoring network. These results underscore the importance of measurements of appropriate proxies for traffic emissions at relevant spatial scales. Our results are useful for exposure analysis as well as city and regional planners evaluating mitigation strategies for traffic-related air pollution.

Ultrafine Particle Number Concentration Model for Estimating Retrospective and Prospective Long-Term Ambient Exposures in Urban Neighborhoods.

Short-term exposure to ultrafine particles (UFP; <100 nm in diameter), which are present at high concentrations near busy roadways, is associated with markers of cardiovascular and respiratory disease risk. To date, few long-term studies (months to years) have been conducted due to the challenges of long-term exposure assignment. To address this, we modified hybrid land-use regression models of particle number concentrations (PNCs; a proxy for UFP) for two study areas in Boston (MA) by replacing the measured PNC term with an hourly model and adjusting for overprediction. The hourly PNC models used covariates for meteorology, traffic, and sulfur dioxide concentrations (a marker of secondary particle formation). We compared model performance against long-term PNC data collected continuously from 9 years before and up to 3 years after the model-development period. Model predictions captured the major temporal variations in the data and model performance remained relatively stable retrospectively and prospectively. The Pearson correlation of modeled versus measured hourly log-transformed PNC at a long-term monitoring site for 9 years prior was 0.74. Our results demonstrate that highly resolved spatial-temporal PNC models are capable of estimating ambient concentrations retrospectively and prospectively with generally good accuracy, giving us confidence in using these models in epidemiological studies.

Applying Data Analytics to Address Social Determinants of Health in Practice.

As public health and health care increase focus toward addressing social determinants of health (SDH), the growth of data and analytics affords new, impactful tools for data-informed community health improvement. Best practices should be established for responsible use, meaningful interpretation, and actionable implementation of SDH data for community health improvement.

Combining Measurements from Mobile Monitoring and a Reference Site To Develop Models of Ambient Ultrafine Particle Number Concentration at Residences.

Significant spatial and temporal variation in ultrafine particle (UFP; <100 nm in diameter) concentrations creates challenges in developing predictive models for epidemiological investigations. We compared the performance of land-use regression models built by combining mobile and stationary measurements (hybrid model) with a regression model built using mobile measurements only (mobile model) in Chelsea and Boston, MA (USA). In each study area, particle number concentration (PNC; a proxy for UFP) was measured at a stationary reference site and with a mobile laboratory driven along a fixed route during an ∼1-year monitoring period. In comparing PNC measured at 20 residences and PNC estimates from hybrid and mobile models, the hybrid model showed higher Pearson correlations of natural log-transformed PNC ( r = 0.73 vs 0.51 in Chelsea; r = 0.74 vs 0.47 in Boston) and lower root-mean-square error in Chelsea (0.61 vs 0.72) but no benefit in Boston (0.72 vs 0.71). All models overpredicted log-transformed PNC by 3-6% at residences, yet the hybrid model reduced the standard deviation of the residuals by 15% in Chelsea and 31% in Boston with better tracking of overnight decreases in PNC. Overall, the hybrid model considerably outperformed the mobile model and could offer reduced exposure error for UFP epidemiology.

Longitudinal associations of long-term exposure to ultrafine particles with blood pressure and systemic inflammation in Puerto Rican adults.

BACKGROUND: Few longitudinal studies have examined the association between ultrafine particulate matter (UFP, particles < 0.1 µm aerodynamic diameter) exposure and cardiovascular disease (CVD) risk factors. We used data from 791 adults participating in the longitudinal Boston Puerto Rican Health Study (Massachusetts, USA) between 2004 and 2015 to assess whether UFP exposure was associated with blood pressure and high sensitivity C-reactive protein (hsCRP, a biomarker of systemic inflammation). METHODS: Residential annual average UFP exposure (measured as particle number concentration, PNC) was assigned using a model accounting for spatial and temporal trends. We also adjusted PNC values for participants' inhalation rate to obtain the particle inhalation rate (PIR) as a secondary exposure measure. Multilevel linear models with a random intercept for each participant were used to examine the association of UFP with blood pressure and hsCRP. RESULTS: Overall, in adjusted models, an inter-quartile range increase in PNC was associated with increased hsCRP (ß = 6.8; 95% CI = - 0.3, 14.0%) but not with increased systolic blood pressure (ß = 0.96; 95% CI = - 0.33, 2.25 mmHg), pulse pressure (ß = 0.70; 95% CI = - 0.27, 1.67 mmHg), or diastolic blood pressure (ß = 0.55; 95% CI = - 0.20, 1.30 mmHg). There were generally stronger positive associations among women and never smokers. Among men, there were inverse associations of PNC with systolic blood pressure and pulse pressure. In contrast to the primary findings, an inter-quartile range increase in the PIR was positively associated with systolic blood pressure (ß = 1.03; 95% CI = 0.00, 2.06 mmHg) and diastolic blood pressure (ß = 1.01; 95% CI = 0.36, 1.66 mmHg), but not with pulse pressure or hsCRP. CONCLUSIONS: We observed that exposure to PNC was associated with increases in measures of CVD risk markers, especially among certain sub-populations. The exploratory PIR exposure metric should be further developed.

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.

Lessons from in-home air filtration intervention trials to reduce urban ultrafine particle number concentrations.

BACKGROUND: Exposure to airborne ultrafine particle (UFP; <100 nm in aerodynamic diameter) is an emerging public health problem. Nevertheless, the benefit of using high efficiency particulate arrestance (HEPA) filtration to reduce UFP concentrations in homes is not yet clear. METHODS: We conducted a randomized crossover study of HEPA filtration without a washout period in 23 homes of low-income Puerto Ricans in Boston and Chelsea, MA (USA). Most participants were female, older adults who were overweight or obese. Particle number concentrations (PNC, a proxy for UFP) were measured indoors and outdoors at each home continuously for six weeks. Homes received both HEPA filtration and sham filtration for three weeks each in random order. RESULTS: Median PNC under HEPA filtration was 50-85% lower compared to sham filtration in most homes, but we found no benefit in terms of reduced inflammation; associations between hsCRP, IL-6, or TNFRII in blood samples and indoor PNC were inverse and not statistically significant. CONCLUSIONS: Limitations to our study design likely contributed to our findings. Limitations included carry-over effects, a population that may have been relatively unresponsive to UFP, reduction in PNC even during sham filtration that limited differences between HEPA and sham filtration, window opening by participants, and lack of fine-grained (room-specific) participant time-activity information. Our approach was similar to other recent HEPA intervention studies of particulate matter exposure and cardiovascular risk, suggesting that there is a need for better study designs.

A Randomized Cross-over Air Filtration Intervention Trial for Reducing Cardiovascular Health Risks in Residents of Public Housing near a Highway.

Exposure to traffic-generated ultrafine particles (UFP; particles <100 nm) is likely a risk factor for cardiovascular disease. We conducted a trial of high-efficiency particulate arrestance (HEPA) filtration in public housing near a highway. Twenty residents in 19 apartments living <200 m from the highway participated in a randomized, double-blind crossover trial. A HEPA filter unit and a particle counter (measuring particle number concentration (PNC), a proxy for UFP) were installed in living rooms. Participants were exposed to filtered air for 21 days and unfiltered air for 21 days. Blood samples were collected and blood pressure measured at days 0, 21 and 42 after a 12-hour fasting period. Plasma was analyzed for high sensitivity C-reactive protein (hsCRP), interleukin-6 (IL-6), tumor necrosis factor alpha-receptor II (TNF-RII) and fibrinogen. PNC reductions ranging from 21% to 68% were recorded in 15 of the apartments. We observed no significant differences in blood pressure or three of the four biomarkers (hsCRP, fibrinogen, and TNF-RII) measured in participants after 21-day exposure to HEPA-filtered air compared to measurements after 21-day exposure to sham-filtered air. In contrast, IL-6 concentrations were significantly higher following HEPA filtration (0.668 pg/mL; CI = 0.465-0.959) compared to sham filtration. Likewise, PNC adjusted for time activity were associated with increasing IL-6 in 14- and 21-day moving averages, and PNC was associated with decreasing blood pressure in Lags 0, 1 and 2, and in a 3-day moving average. These negative associations were unexpected and could be due to a combination of factors including exposure misclassification, unsuccessful randomization (i.e., IL-6 and use of anti-inflammatory medicines), or uncontrolled confounding. Studies with greater reduction in UFP levels and larger sample sizes are needed. There also needs to be more complete assessment of resident time activity and of outdoor vs. indoor source contributions to UFP exposure. HEPA filtration remains a promising, but not fully realized intervention.

Institutional facilitators and barriers to local public health preparedness planning for vulnerable and at-risk populations.

OBJECTIVE: Numerous institutional facilitators and barriers to preparedness planning exist at the local level for vulnerable and at-risk populations. Findings of this evaluation study contribute to ongoing practice-based efforts to improve response services and address public health preparedness planning and training as they relate to vulnerable and at-risk populations. METHODS: From January 2012 through June 2013, we conducted a multilevel, mixed-methods evaluation study of the North Carolina Preparedness and Emergency Response Research Center's Vulnerable & At-Risk Populations Resource Guide, an online tool to aid local health departments' (LHDs') preparedness planning efforts. We examined planning practices across multiple local, regional, and state jurisdictions utilizing user data, follow-up surveys, and secondary data. To identify potential incongruities in planning, we compared respondents' reported populations of interest with corresponding census data to determine whether or not there were differences in planning priorities. RESULTS: We used data collected from evaluation surveys to identify key institutional facilitators and barriers associated with planning for at-risk populations, including challenges to conducting assessments and lack of resources. Results identified both barriers within institutional culture and disconnects between planning priorities and evidence-based identification of vulnerable and at-risk populations, including variation in the planning process, partnerships, and perceptions. CONCLUSIONS: Our results highlight the important role of LHDs in preparedness planning and the potential implications associated with organizational and bureaucratic impediments to planning implementation. A more in-depth understanding of the relationships among public institutions and the levels of preparedness that contribute to the conditions and processes that generate vulnerability is needed.

Assessing functional needs sheltering in Pike County, Kentucky: using a community assessment for public health emergency response.

OBJECTIVE: During 2009-2011, Pike County, Kentucky, experienced a series of severe weather events that resulted in property damage, insufficient potable water, and need for temporary shelters. A Community Assessment for Public Health Emergency Response (CASPER) survey was implemented for future planning. CASPER assesses household health status, preparedness level, and anticipated demand for shelters. METHODS: We used a 2-stage cluster sampling design to randomly select 210 representative households for in-person interviews. We estimated the proportion of households with children aged 2 years or younger; adults aged 65 years or older; and residents with chronic health conditions, visual impairments, physical limitations, and supplemental oxygen requirements. RESULTS: Of all households surveyed, 8% included children aged 2 years or younger, and 27% included adults aged 65 years or older. The most common chronic health conditions were heart disease (51%), diabetes (28%), lung disease (23%), and asthma (21%). Visual impairments were reported in 29% of households, physical limitations in 24%, and supplemental oxygen use in 12%. CONCLUSIONS: Pike County residents should be encouraged to maintain an adequate supply of medications and copies of their prescriptions. Emergency response plans should include transportation for persons with physical limitations; and shelter plans should include sufficient medically trained staff and adequate supplies of infant formula, pharmaceuticals, and supplemental oxygen. (Disaster Med Public Health Preparedness. 2013;7:597-602).