Concentrations Of Traffic-related Air Pollutants Research Articles

Observational studies generate misleading results about the health effects of air pollution: Evidence from chronic air pollution and COVID-19 outcomes.

Several observational studies from locations around the globe have documented a positive correlation between air pollution and the severity of COVID-19 disease. Observational studies cannot identify the causal link between air quality and the severity of COVID-19 outcomes, and these studies face three key identification challenges: 1) air pollution is not randomly distributed across geographies; 2) air-quality monitoring networks are sparse spatially; and 3) defensive behaviors to mediate exposure to air pollution and COVID-19 are not equally available to all, leading to large measurement error bias when using rate-based COVID-19 outcome measures (e.g., incidence rate or mortality rate). Using a quasi-experimental design, we explore whether traffic-related air pollutants cause people with COVID-19 to suffer more extreme health outcomes in New York City (NYC). When we address the previously overlooked challenges to identification, we do not detect causal impacts of increased chronic concentrations of traffic-related air pollutants on COVID-19 death or hospitalization counts in NYC census tracts.

Concentration-dependent alterations in the human plasma proteome following controlled exposure to diesel exhaust

Traffic-related air pollution (TRAP) exposure is associated with systemic health effects, which can be studied using blood-based markers. Although we have previously shown that high TRAP concentrations alter the plasma proteome, the concentration-response relationship between blood proteins and TRAP is unexplored in controlled human exposure studies. We aimed to identify concentration-dependent plasma markers of diesel exhaust (DE), a model of TRAP. Fifteen healthy non-smokers were enrolled into a double-blinded, crossover study where they were exposed to filtered air (FA) and DE at 20, 50 and 150 μg/m3 PM2.5 for 4h, separated by ≥ 4-week washouts. We collected blood at 24h post-exposure and used label-free mass spectrometry to quantify proteins in plasma. Proteins exhibiting a concentration-response, as determined by linear mixed effects models (LMEMs), were assessed for pathway enrichment using WebGestalt. Top candidates, identified by sparse partial least squares discriminant analysis and LMEMs, were confirmed using enzyme-linked immunoassays. Thereafter, we assessed correlations between proteins that showed a DE concentration-response and acute inflammatory endpoints, forced expiratory volume in 1 s (FEV1) and methacholine provocation concentration causing a 20% drop in FEV1 (PC20). DE exposure was associated with concentration-dependent alterations in 45 proteins, which were enriched in complement pathways. Of the 9 proteins selected for confirmatory immunoassays, based on complementary bioinformatic approaches to narrow targets and availability of high-quality assays, complement factor I (CFI) exhibited a significant concentration-dependent decrease (−0.02 μg/mL per μg/m3 of PM2.5, p = 0.04). Comparing to FA at discrete concentrations, CFI trended downward at 50 (−2.14 ± 1.18, p = 0.08) and significantly decreased at 150 μg/m3 PM2.5 (−2.93 ± 1.18, p = 0.02). CFI levels were correlated with FEV1, PC20 and nasal interleukin (IL)-6 and IL-1β. This study details concentration-dependent alterations in the plasma proteome following DE exposure at concentrations relevant to occupational and community settings. CFI shows a robust concentration-response and association with established measures of airway function and inflammation.

Prenatal and postnatal exposure to NO2 and rapid infant weight gain - A population-based cohort study.

Childhood overweight and obesity is a global public health problem. Rapid infant weight gain is predictive of childhood overweight. Studies found that exposure to ambient air pollution is associated with childhood overweight, and have linked prenatal exposure to air pollution with rapid infant weight gain. To examine the association between prenatal and postnatal ambient NO2 exposure, a traffic-related marker, with rapid weight gain in infants. We carried out a population-based historical cohort study using data from the Israeli national network of maternal and child health clinics. The study included 474,136 infants born at term with birthweight ≥2500 g in 2011-2019 in central Israel. Weekly averages of NO2 concentration throughout pregnancy (prenatal) and the first 4 weeks of life (postnatal) were assessed using an optimized dispersion model and were linked to geocoded home addresses. We modelled weight gain velocity throughout infancy using the SuperImposition by Translation and Rotation (SITAR) method, a mixed-effects nonlinear model specialized for modelling growth curves, and defined rapid weight gain as the highest velocity tertile. Distributed-lag models were used to assess critical periods of risk and to measure relative risks for rapid weight gain. Adjustments were made for socioeconomic status, population group, subdistrict, month and year of birth, and the alternate exposure period - prenatal or postnatal. The cumulative adjusted relative risk for rapid weight gain of NO2 exposure was 1.02 (95% confidence intereval [CI] 1.00, 1.04) for exposure throughout pregnancy and 1.02 (95% CI 1.01, 1.04) for exposure during the first four postnatal weeks per NO2 interquartile range increase (7.3 ppb). An examination of weekly associations revealed that the critical period of risk for the prenatal exposure was from mid-pregnancy to birth. Prenatal and postnatal exposures to higher concentrations of traffic-related air pollution are each independently associated with rapid infant weight gain, a risk factor for childhood overweight and obesity.

Traffic-related air pollution and risk of lung, breast and urinary tract cancer in Halifax, Nova Scotia.

We assessed the association of traffic-related air pollution (TRAP) with the incidence of lung, breast and urinary tract cancer in Halifax, Nova Scotia. Our case-control study included 2315 cancers and 8501 age-sex matched controls. Land-use regression was used to estimated TRAP concentrations. Logistic regression was used to assess cancer risk in relation to TRAP, adjusting for community social and material deprivation. There was no association between the risk of lung, breast or urinary tract cancer in relation to TRAP. Lung cancer risk was significantly increased in the most deprived communities, whereas breast cancer risk was highest in the least deprived communities. In a city characterized by low levels of ambient air pollution, there was no evidence of a linear increased lung, breast or urinary tract cancer risk in relation to TRAP.

Characterizing in-cabin air quality and vehicular air filtering performance for passenger cars in China

The rapidly growing vehicle population has become a crucial contributor to severe air-pollution and public health issues. In urban areas, vehicles have become one of the important sources of air pollutants such as nitrogen oxides and fine particulate matter (PM2.5). In particular, the on-road concentrations of traffic-related air pollutants (TRAPs) are typically many times higher than normal ambient concentrations, potentially leading to high in-vehicle exposure levels to TRAPs. Limited studies have focused on the variability in in-vehicle concentrations of TRAPs and linked the pollution level to both out-cabin conditions and the in-cabin filtration performance during real-world travels. Therefore, this study measured on-roadway, in-cabin concentrations of PM2.5 and carbon dioxide (CO2) by using well-calibrated low-cost sensors during various conditions. Our results indicate that, although in-cabin PM2.5 concentrations are correlated to out-cabin PM2.5 concentration levels, the control efficiency would be affected by the ventilation mode and the adoption of vehicular filtration device. The PM2.5 reduction efficiencies could achieve 45% and 77% for in-use and new filters made by vehicle manufacturers respectively, with the average CO2 concentration remained at a safe level (<800 ppm) under the in-vehicle outside air ventilation. The application of a high-efficiency cabin air (HECA) filter can further enhance the PM2.5 filtration efficiency up to 85–96%, indicating the significance of advanced cabin air filtration technology for improving in-cabin air quality and reducing health risk of Chinese drivers.

A randomized crossover trial of portable in-home air purifiers for highway PM and cardiovascular risk: HAFTRAP study update

Background and aim: We have shown previously that cardiovascular biomarkers are associated with traffic-related air pollution (TRAP) near highways and that reducing particulate exposure improves blood pressure (BP) in controlled settings. Our aim here is to assess the efficacy of portable in-home high-efficiency particle arrestance (HEPA) air purifiers to reduce indoor concentrations of TRAP and therefore reduce BP and systemic inflammation in a real world, lived-in setting. Methods: We are conducting a randomized crossover trial of air purifiers in homes &amp;#x3c;200m from a major highway. Participants receive real or sham filtration for one month each separated by a one-month wash out period. We collect peripheral and central BP, as well as blood samples for inflammatory biomarker analysis before and after each one-month period. We also conduct air monitoring and satisfaction interviews with a subset of homes and participants. Results: A sample of 57 participants has been enrolled with recruitment ongoing. Thirty-three percent live within 100m of the highway. The average age of participants is 44 years (range: 30-78 years), 68% are female, and 37% are racial/ethnic minorities. The mean (SD) baseline peripheral and central systolic BP are 123 (14) mmHg and 113 (13) mmHg, respectively. Indoor and outdoor PNC measurements indicate that median concentrations were 40-60% lower during HEPA than SHAM and during HEPA use indoor concentrations were 60-70% lower than outdoors. Data on electricity use and quantitative and qualitative feedback suggest air purifiers were on the medium setting most of the time. Conclusions: Approximately one-third of the way to our recruitment goal we have good acceptance and compliance with the intervention, quality data and indications that the air purifiers are reducing TRAP as intended. An interim analysis of health outcomes should be possible in a year.

Traffic-related air pollution and genome-wide DNA methylation: A randomized, crossover trial

BackgroundTraffic-related air pollution (TRAP) has been associated with changes in gene-specific DNA methylation. However, few studies have investigated impact of TRAP exposure on genome-wide DNA methylation in circulating blood of human. ObjectiveTo explore the association between TRAP exposure and genome-wide DNA methylation. MethodsWe conducted a randomized, crossover exposure trial among 35 healthy adults in Shanghai, China. All subjects were randomly allocated to a traffic-free park or a main road for consecutive 4 h, respectively. Blood genome-wide DNA methylation after each exposure session was measured by the Infinium Methylation EPIC BeadChip (850K). The differentially methylated CpGs loci associated with TRAP exposure were identified using linear mixed-effect model. ResultsThe average concentrations of traffic-related air pollutants including black carbon, ultrafine particles, carbon dioxide, and nitrogen dioxide were 2–3 times higher in the road compared to those in the park. Methylation levels of 68 CpG loci were significantly changed (false discovery rate < 0.05) following TRAP exposure, among which 49 were hypermethylated and 19 were hypomethylated. The annotated genes based on the differential CpGs loci were related to pathways in cardiovascular signaling, cytokine signaling, immune response, nervous system signaling, and metabolism. ConclusionsWe found that TRAP exposure was associated with DNA methylation in dozens of genes concerning cardiometabolic health. This trial for the first-time profiled genome-wide methylation changes induced by TRAP exposure using the 850K assay, providing epigenetic insights in understanding the cardiometabolic effects of TRAP exposure.

Characterization of winter air pollutant gradients near a major highway

Traffic-related air pollutants (TRAP) including nitric oxide (NO), nitrogen oxide (NOx), carbon monoxide (CO), ultrafine particles (UFP), black carbon (BC), and fine particulate matter (PM2.5) were simultaneously measured at near-road sites located at 10 m (NR10) and 150 m (NR150) from the same side of a busy highway to provide insights into the influence of winter time meteorology on exposure to TRAP near major roads. The spatial variabilities of TRAP were examined for ambient temperatures ranging from −11 °C to +19 °C under downwind, upwind, and stagnant air conditions. The downwind TRAP concentrations at NR10 were higher than the upwind concentrations by a factor of 1.4 for CO to 13 for NO. Despite steep downwind reductions of 38 % to 75 % within 150 m, the downwind concentrations at NR150 were still well above upwind concentrations. Near-road concentrations of NOx and UFP increased as ambient temperatures decreased due to elevated emissions of NOx and UFP from vehicles under colder temperatures. Traffic-related PM2.5 sources were identified using hourly PM2.5 chemical components including organic/inorganic aerosol and trace metals at both sites. The downwind concentrations of primary PM2.5 species related to tailpipe and non-tailpipe emissions at NR10 were substantially higher than the upwind concentrations by a factor of 4 and 32, respectively. Traffic-related PM2.5 sources accounted for almost half of total PM2.5 mass under downwind conditions, leading to a rapid change of PM2.5 chemical composition. Under stagnant air conditions, the concentrations of most TRAP and related PM2.5 including tailpipe emissions, secondary nitrate, and organic aerosol were comparable to, or even greater than, the downwind concentrations under windy conditions, especially at NR150. This study demonstrates that stagnant air conditions further widen the traffic-influenced area and people living near major roadways may experience increased risks from elevated exposure to traffic emissions during cold and stagnant winter conditions.

Characterization of Annual Average Traffic-Related Air Pollution Concentrations in the Greater Seattle Area from a Year-Long Mobile Monitoring Campaign.

Growing evidence links traffic-related air pollution (TRAP) to adverse health effects. We designed an innovative and extensive mobile monitoring campaign to characterize TRAP exposure levels for the Adult Changes in Thought (ACT) study, a Seattle-based cohort. The campaign measured particle number concentration (PNC) to capture ultrafine particles (UFP), black carbon (BC), nitrogen dioxide (NO2), fine particulate matter (PM2.5), and carbon dioxide (CO2) at 309 roadside sites within a large, 1200 land km2 (463 mi2) area representative of the cohort. We collected about 29 two-minute measurements at each site during all seasons, days of the week, and most times of the day over a 1-year period. Validation showed good agreement between our BC, NO2, and PM2.5 measurements and monitoring agency sites (R2 = 0.68-0.73). Universal kriging-partial least squares models of annual average pollutant concentrations had cross-validated mean square error-based R2 (and root mean square error) values of 0.77 (1177 pt/cm3) for PNC, 0.60 (102 ng/m3) for BC, 0.77 (1.3 ppb) for NO2, 0.70 (0.3 μg/m3) for PM2.5, and 0.51 (4.2 ppm) for CO2. Overall, we found that the design of this extensive campaign captured the spatial pollutant variations well and these were explained by sensible land use features, including those related to traffic.

Understanding the environmental factors related to the decrease in Pediatric Emergency Department referrals for acute asthma during the SARS-CoV-2 pandemic.

BackgroundLockdown measures during the SARS‐CoV‐2 pandemic determined radical changes to behavioral and social habits, that were reflected by a reduction in the transmission of respiratory pathogens and in anthropogenic atmospheric emissions.ObjectiveThis ecological study aims to provide a descriptive evaluation on how restrictive measures during the SARS‐CoV‐2 pandemic impacted Pediatric Emergency Department (PED) referrals for asthma exacerbations, and their potentially associated environmental triggers in Bologna, a densely populated urban area in Northern Italy.MethodsFiles of children evaluated for acute asthma during 2015 to 2020 at the PED of Sant'Orsola University Hospital of Bologna were retrospectively reviewed. Historical daily concentration records of particulate (PM2.5, PM10) and gaseous (NO2, C6H6) air pollutants, and pollen were concurrently evaluated, including specific PM chemical tracers for traffic‐related air pollution (TRAP).ResultsIn 2020, asthma‐related PED referrals decreased compared to referral rates of the previous 5 years (p < 0.01). This effect was particularly marked during the first lockdown period (March to May), when the drastic drop in PED referrals was associated with a reduction of high‐priority cases up to 85% and by 54%, on average. A concomitant reduction in the concentrations of traffic‐related air pollutants was observed in the range of 40%–60% (p < 0.01).ConclusionsThe lower rate of asthma exacerbations in childhood was in this study paralleled with reduced TRAP levels during the pandemic. Synergic interactions of the multiple consequences of lockdowns likely contributed to the reduced exacerbations, including decreased exposure to ambient pollutants and fewer respiratory infections, identified as the most important factor in the literature.

Impacts of noise barriers on near-viaduct air quality in a city: A case study in Xi'an

Viaducts built in cities all over the world can increase their traffic capacity. Yet whether specific dispersion and reduction strategies for traffic-related pollutants, such as ultrafine particles (UFP), fine particles (PM2.5), and black carbon (BC), are needed in urban residents' activity areas is uncertain. Here we investigated the distribution patterns of traffic-related pollutants near a viaduct having various infrastructures. Measurements were taken using mobile devices in three sampling sections alongside and extending away from the viaduct in Xi'an, China. Difference-in-differences analysis was used to explore the mitigation effect of noise barriers. The results showed that the pollutant distribution profiles behind both noise barriers and combination barriers (i.e., solid noise barrier plus tree vegetation) are characterized by a novel, unimodal mode whereby the UFP and PM2.5 concentrations first increased and then decreased. Lower traffic-related air pollutant concentrations were observed on the lee side of the noise barrier than at the non-barrier site section. Evidently, compared with a noise barrier alone, the mitigation effect upon UFP, PM2.5, and BC near a viaduct is greater when barrier types are combined, enabling concentration reductions of 5% (UFP), 21% (BC), and 50% (PM2.5). In addition, this study also observed lesser reductions of the three pollutants at greater wind speeds. However, conditions did occur when pollutant concentrations were higher behind a barrier than when no barrier was present, namely when the wind speed exceeded 0.8 m•s−1. Overall, our findings suggest beneficial effects of noise barriers and combination barriers for mitigating the air pollution near viaducts.

Traffic-related air pollution is associated with glucose dysregulation, blood pressure, and oxidative stress in children

BackgroundMetabolic syndrome increases the risk of cardiovascular disease in adults. Antecedents likely begin in childhood and whether childhood exposure to air pollution plays a contributory role is not well understood. ObjectivesTo assess whether children's exposure to air pollution is associated with markers of risk for metabolic syndrome and oxidative stress, a hypothesized mediator of air pollution-related health effects. MethodsWe studied 299 children (ages 6–8) living in the Fresno, CA area. At a study center visit, questionnaire and biomarker data were collected. Outcomes included hemoglobin A1c (HbA1c), urinary 8-isoprostane, systolic blood pressure (SBP), and BMI. Individual-level exposure estimates for a set of four pollutants that are constituents of traffic-related air pollution (TRAP) – the sum of 4-, 5-, and 6-ring polycyclic aromatic hydrocarbon compounds (PAH456), NO2, elemental carbon, and fine particulate matter (PM2.5) – were modeled at the primary residential location for 1-day lag, and 1-week, 1-month, 3-month, 6-month, and 1-year averages prior to each participant's visit date. Generalized additive models were used to estimate associations between each air pollutant exposure and outcome. ResultsThe study population was 53% male, 80% Latinx, 11% Black and largely low-income (6% were White and 3% were Asian/Pacific Islander). HbA1c percentage was associated with longer-term increases in TRAP; for example a 4.42 ng/m3 increase in 6-month average PAH456 was associated with a 0.07% increase (95% CI: 0.01, 0.14) and a 3.62 μg/m3 increase in 6-month average PM2.5 was associated with a 0.06% increase (95% CI: 0.01, 0.10). The influence of air pollutants on blood pressure was strongest at 3 months; for example, a 6.2 ppb increase in 3-month average NO2 was associated with a 9.4 mmHg increase in SBP (95% CI: 2.8, 15.9). TRAP concentrations were not significantly associated with anthropometric or adipokine measures. Short-term TRAP exposure averages were significantly associated with creatinine-adjusted urinary 8-isoprostane. DiscussionOur results suggest that both short- and longer-term estimated individual-level outdoor residential exposures to several traffic-related air pollutants, including ambient PAHs, are associated with biomarkers of risk for metabolic syndrome and oxidative stress in children.

Four Decades of United States Mobile Source Pollutants: Spatial-Temporal Trends Assessed by Ground-Based Monitors, Air Quality Models, and Satellites.

On-road emissions sources degrade air quality, and these sources have been highly regulated. Epidemiological and environmental justice studies often use road proximity as a proxy for traffic-related air pollution (TRAP) exposure, and other studies employ air quality models or satellite observations. To assess these metrics' abilities to reproduce observed near-road concentration gradients and changes over time, we apply a hierarchical linear regression to ground-based observations, long-term air quality model simulations using Community Multiscale Air Quality (CMAQ), and satellite products. Across 1980-2019, observed TRAP concentrations decreased, and road proximity was positively correlated with TRAP. For all pollutants, concentrations decreased fastest at locations with higher road proximity, resulting in "flatter" concentration fields in recent years. This flattening unfolded at a relatively constant rate for NOx, whereas the flattening of CO concentration fields has slowed. CMAQ largely captures observed spatial-temporal NO2 trends across 2002-2010 but overstates the relationships between CO and elemental carbon fine particulate matter (EC) road proximity. Satellite NOx measures overstate concentration reductions near roads. We show how this perspective provides evidence that California's on-road vehicle regulations led to substantial decreases in NO2, NOx, and EC in California, with other states that adopted California's light-duty automobile standards showing mixed benefits over states that did not adopt these standards.

Determinants of ultrafine particles, black carbon, nitrogen dioxide, and carbon monoxide concentrations inside vehicles in the Paris area: PUF-TAXI study.

This study presents real-time concentrations of traffic-related air pollutants during 499 trips conducted by 50 Parisian taxi drivers from PUF-TAXI project. Ultrafine particles (UFP), black carbon (BC), and nitrogen dioxide (NO2 )/carbon monoxide (CO) were measured inside vehicles by Diffusion Size Classifier Miniature® , microAeth® , and Gas-Pro® , respectively, for nine hours. Vehicle/trip data characteristics were collected by questionnaires and on ambient conditions by monitoring stations. The associations between pollutant levels and their potential determinants were analyzed using generalized estimating equation model. Determinants of in-vehicle pollutants levels were identified: (1) ambient factors (meteorology and ambient pollution)-affecting BC, NO2, and CO; (2) vehicle characteristics-affecting all pollutants; and (3) trip-related driving habits-affecting UFP, BC, and CO. We highlight that commuters can, therefore, avoid high in-vehicle air pollutant concentrations mainly by (1) closing windows and activating air-conditioning under air recirculation mode in congested traffic; (2) smooth driving; and (3) maintaining cabin air filters.

Using Big Data Techniques to Better Understand High-Resolution Cumulative Exposure Assessment of Traffic-Related Air Pollution

In this paper, we calculate exposure concentrations of traffic-related air pollutants for different travel modes in the urban environment. Using recent high-resolution mobile sensor measured air po...

Air pollution from traffic during pregnancy impairs newborn's cord blood immune cells: The NELA cohort

BackgroundHazards of traffic-related air pollution (TRAP) on the developing immune system are poorly understood. We sought to investigate the effects of prenatal exposure to TRAP on cord blood immune cell distributions; and to identify gestational windows of susceptibility. MethodsIn-depth immunophenotyping of cord blood leukocyte and lymphocyte subsets was performed by flow cytometry in 190 newborns embedded in the Nutrition in Early Life and Asthma (NELA) birth cohort (2015–2018). Long-term (whole pregnancy and trimesters) and short-term (15-days before delivery) residential exposures to traffic-related nitrogen dioxide (NO2), particulate matter (PM2.5 and PM10), and ozone (O3) were estimated using dispersion/chemical transport modelling. Associations between TRAP concentrations and cord blood immune cell counts were assessed using multivariate Poisson regression models. ResultsMean number of natural killer (NK) cells decreased 15% in relation to higher NO2 concentrations (≥36.4 μg/m3) during whole pregnancy (incidence relative risk (IRR), 0.85; 95% CI, 0.72, 0.99), with stronger associations in the first trimester. Higher PM2.5 concentrations (≥13.3 μg/m3) during whole pregnancy associated with a reduced mean number of cytotoxic T cells (IRR, 0.88; 95% CI, 0.78, 0.99). Newborns exposed to higher PM10 (≥23.6 μg/m3) and PM2.5 concentrations during the first and third trimester showed greater mean number of helper T type 1 (Th1) cells (P < 0.05). Decreased number of regulatory T (Treg) cells was associated with greater short-term NO2 (IRR, 0.90; 95% CI, 0.80, 1.01) and PM10 (IRR, 0.88; 95% CI, 0.77, 0.99) concentrations. ConclusionsPrenatal exposure to TRAP, particularly in early and late gestation, impairs fetal immune system development through disturbances in cord blood leukocyte and lymphocyte distributions.

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.

Predicting differential improvements in annual pollutant concentrations and exposures for regulatory policy assessment

Over the past decade, researchers and policy-makers have become increasingly interested in regulatory and policy interventions to reduce air pollution concentrations and improve human health. Studies have typically relied on relatively sparse environmental monitoring data that lack the spatial resolution to assess small-area improvements in air quality and health. Few studies have integrated multiple types of measures of an air pollutant into one single modeling framework that combines spatially- and temporally-rich monitoring data.In this paper, we investigated the differential effects of California emissions reduction plan on reducing air pollution between those living in the goods movement corridors (GMC) that are within 500 m of major highways that serve as truck routes to those farther away or adjacent to routes that prohibit trucks. A mixed effects Deletion/Substitution/Addition (D/S/A) machine learning algorithm was developed to model annual pollutant concentrations of nitrogen dioxide (NO2) by taking repeated measures into consideration and by integrating multiple types of NO2 measurements, including those through government regulatory and research-oriented saturation monitoring into a single modeling framework. Difference-in-difference analysis was conducted to identify whether those living in GMC demonstrated statistically larger reductions in air pollution exposure.The mixed effects D/S/A machine learning modeling result indicated that GMC had 2 ppb greater reductions in NO2 concentrations from pre- to post-policy period than far away areas. The difference-in-difference analysis demonstrated that the subjects living in GMC experienced statistically significant greater reductions in NO2 exposure than those living in the far away areas.This study contributes to scientific knowledge by providing empirical evidence that improvements in air quality via the emissions reductions plan policies impacted traffic-related air pollutant concentrations and associated exposures most among low-income Californians with chronic conditions living in GMC. The identified differences in pollutant reductions across different location domains may be applicable to other states or other countries if similar policies are enacted.

Health impact assessment by the implementation of Madrid City air-quality plan in 2020

ObjectivesAir pollutant concentrations in many urban areas are still above the legal and recommended limits that are set to protect the citizens’ health. Madrid is one of the cities where traffic causes high NO2 levels. In this context, Madrid City Council launched the Air Quality and Climate Change Plan for the city of Madrid (Plan A), a local strategy approved by the previous government in 2017. The aim of this study was to conduct a quantitative health impact assessment to evaluate the number of premature deaths that could potentially be prevented by the implementation of Plan A in Madrid in 2020, at both citywide and within-city level. The main purpose was to support decision-making processes in order to maximize the positive health impacts from the implementation of Plan A measures. MethodsThe Regional Statistical Office provided information on population and daily mortality in Madrid. For exposure assessment, we estimated PM2.5, NO2 and O3 concentration levels for Madrid city in 2012 (baseline air-quality scenario) and 2020 (projected air-quality scenario based on the implementation of Plan A), by means of an Eulerian chemical-transport model with a spatial resolution of 1 km × 1 km and 30 vertical levels. We used the concentration-response functions proposed by two relevant WHO projects to calculate the number of attributable annual deaths corresponding to all non-accidental causes (ICD-10: A00-R99) among all-ages and the adult population (>30 years old) for each district and for Madrid city overall. This health impact assessment was conducted dependant on health-data availability. ResultsIn 2020, the implementation of Plan A would imply a reduction in the Madrid citywide annual mean PM2.5 concentration of 0.6 μg/m3 and 4.0 μg/m3 for NO2. In contrast, an increase of 1 μg/m3 for O3 would be expected. The annual number of all-cause deaths from long-term exposure (95% CI) that could be postponed in the adult population by the expected air-pollutant concentration reduction was 88 (57–117) for PM2.5 and 519 (295–750) for NO2; short-term exposure accounted for 20 (7–32) for PM2.5 and 79 (47–111) for NO2 in the total population. According to the spatial distribution of air pollutants, the highest mortality change estimations were for the city centre – including Madrid Central and mainly within the M-30 ring road –, as compared to peripheral districts. The positive health impacts from the reductions in PM2.5 and NO2 far exceeded the adverse mortality effects expected from the increase in O3. ConclusionsEffective implementation of Plan A measures in Madrid city would bring about an appreciable decline in traffic-related air-pollutant concentrations and, in turn, would lead to significant health-related benefits.

Interaction between neighborhood walkability and traffic-related air pollution on hypertension and diabetes: The CANHEART cohort

BackgroundLiving in unwalkable neighborhoods has been associated with heightened risk for diabetes and hypertension. However, highly walkable environments may have higher concentrations of traffic-related air pollution, which may contribute to increased cardiovascular disease risk. We therefore aimed to assess how walkability and traffic-related air pollution jointly affect risk for hypertension and diabetes. MethodsWe used a cross-sectional, population-based sample of individuals aged 40–74 years residing in selected large urban centres in Ontario, Canada on January 1, 2008, assembled from administrative databases. Walkability and traffic-related air pollution (NO2) were assessed using validated tools and linked to individuals based on neighborhood of residence. Logistic regression was used to estimate adjusted associations between exposures and diagnoses of hypertension or diabetes accounting for potential confounders. ResultsOverall, 2,496,458 individuals were included in our analyses. Low walkability was associated with higher odds of hypertension (lowest vs. highest quintile OR = 1.34, 95% CI: 1.32, 1.37) and diabetes (lowest vs. highest quintile OR = 1.25, 95% CI: 1.22, 1.29), while NO2 exhibited similar trends (hypertension: OR = 1.09 per 10 p.p.b., 95% CI: 1.08, 1.10; diabetes: OR = 1.16, 95% CI: 1.14, 1.17). Significant interactions were identified between walkability and NO2 on risk for hypertension (p < 0.0001 and diabetes (p < 0.0001). At higher levels of pollution (40 p.p.b.), differences in the probability of hypertension (lowest vs. highest walkability quintile: 0.26 vs. 0.25) or diabetes (lowest vs. highest walkability quintile: 0.15 vs. 0.15) between highly walkable and unwalkable neighborhoods were diminished, compared to differences observed at lower levels of pollution (5 p.p.b.) (hypertension, lowest vs. highest walkability quintile: 0.21 vs. 0.13; diabetes, lowest vs. highest walkability quintile: 0.09 vs. 0.06). ConclusionsWalkability and traffic-related air pollution interact to jointly predict risk for hypertension and diabetes. Although walkable neighborhoods appear to have beneficial effects, they may accentuate the harmful effects of air pollution on cardiovascular risk factors.