Traffic-related Air Pollution Research Articles

Impact of exposure to urban air pollution on grey squirrel (Sciurus carolinensis) lung health

The increased rate of global urbanisation has recently exacerbated the significant public health problem of traffic related air pollution. Despite the known significant impact on human health, little is known about the effects of air pollution on wildlife health. The lung is the primary target organ for the effects of exposure to air pollution, leading to lung inflammation, altering the lung epigenome, culminating in respiratory disease. In this study, we aimed to assess lung health and DNA methylation profiles in Eastern grey squirrel (Sciurus carolinensis) populations living across an urban-rural air pollution gradient. Squirrel lung health was assessed in four populations situated across the most polluted inner-city boroughs to the less polluted edges of Greater London. We also assessed lung DNA methylation across three London sites and a further two rural sites in Sussex and North Wales. Lung and tracheal diseases were present in 28% and 13% of the squirrels respectively. Specifically, focal inflammation (13%), focal macrophages with vacuolated cytoplasm (3%) and endogenous lipid pneumonia (3%). There was no significant difference in prevalence of lung, tracheal diseases, anthracosis (carbon presence) or lung DNA methylation levels between urban sites and urban and rural sites respectively or NO2 levels. BALT (Bronchus-Associated Lymphoid Tissue) was significantly smaller in the site with highest NO2 and contained the highest carbon loading compared to sites with lower NO2, however differences in carbon loading in between sites were not significant. High pollution site individuals also had significantly higher numbers of alveolar macrophages which suggests that grey squirrels are exposed to and respond to traffic-related air pollution and further research is needed to understand the impact of traffic-related air pollutants on wildlife health.

Environmental characteristics and disparities in adult asthma in north central Texas urban counties

ObjectivesDisparities in asthma prevalence present a persistent challenge to public health. The complex nature of the issue requires studies through a wide range of lenses. To date, little research has examined associations between asthma and multiple social and environmental factors simultaneously. This study aims to fill the gap with a focus on the impacts of multiple environmental characteristics and social determinants of health on asthma. Study designThis study uses secondary analysis with data from a variety of sources to analyze the effects of environmental and social factors on adult asthma occurrence in North Central Texas. MethodHospital records and demographic and environmental data for four urban counties in North Central Texas (Collin, Dallas, Denton, and Tarrant) come from the Dallas/Fort Worth Hospital Council Foundation, the US census, the North Central Texas Council of Governments, and the Railroad Commission of Texas. The data were integrated using ArcGIS. A hotspot analysis was performed to inspect the spatial patterns of hospital visits for asthma exacerbations in 2014. The impacts of multiple environmental characteristics and social determinants of health were modeled using negative binomial regression. ResultsThe results revealed spatial clusters of adult asthma prevalence and disparities by race, class, and education. The occurrence of asthma exacerbations was positively associated with exposure to traffic-related air pollution, energy-related drilling activities, and older housing stock and negatively linked to green space. ConclusionsAssociations between built environmental characteristics and asthma prevalence have implications for urban planners, healthcare professionals, and policy makers. Empirical evidence for the role of social determinants of health supports continuing efforts in policies and practices to improve education and reduce socio-economic inequities.

Association between Outdoor Air Pollution and Fatal Acute Myocardial Infarction in Lithuania between 2006 and 2015: A Time Series Design.

Air pollution has a significant effect on human health and there is a broad body of evidence showing that exposure to air pollution is associated with an increased risk of adverse health effects. The main objective of this study was to assess the association of traffic-related air pollutants with fatal AMI during the ten-year period. The study was conducted in Kaunas city, where the WHO MONICA register included a total of 2273 adult cases of fatal AMI cases during the 10-year study period. We focused on the period between 2006 and 2015. The associations between exposure to traffic-related air pollution and the risk of fatal AMI were evaluated by using a multivariate Poisson regression model, RR presented per an increase in IQR. It was found that the risk of fatal AMI was significantly higher in all subjects (RR 1.06; 95% CI 1.00-1.12) and women (RR 1.12; 95% CI 1.02-1.22) when the concentration of PM10 in the ambient air was increased 5-11 days before the onset of AMI, adjusting for NO2 concentration. The effect was stronger during spring in all subjects (RR 1.12; 95% CI 1.03-1.22), in men (RR 1.13; 95% CI 1.01-1.26), in younger-aged (RR 1.15; 95% CI 1.03-1.28), and in winter in women (RR 1.24; 95% CI 1.03-1.50). Our findings show that ambient air pollution increases the risk of fatal AMI, and this pertains to PM10 specifically.

The effect of exposure to traffic related air pollutants in pregnancy on birth anthropometry: a cohort study in a heavily polluted low-middle income country

BackgroundAmbient air pollution has been recognized as one of the most important environmental health threats. Exposure in early life may affect pregnancy outcomes and the health of the offspring. The main objective of our study was to assess the association between prenatal exposure to traffic related air pollutants during pregnancy on birth weight and length. Second, to evaluate the association between prenatal exposure to traffic related air pollutants and the risk of low birth weight (LBW).MethodsThree hundred forty mother-infant pairs were included in this prospective cohort study performed in Jakarta, March 2016–September 2020. Exposure to outdoor PM2.5, soot, NOx, and NO2 was assessed by land use regression (LUR) models at individual level. Multiple linear regression models were built to evaluate the association between air pollutants with birth weight (BW) and birth length (BL). Logistic regression was used to assess the risk of low birth weight (LBW) associated with all air pollutants.ResultsThe average PM2.5 concentration was almost eight times higher than the current WHO guideline and the NO2 level was three times higher. Soot and NOx were significantly associated with reduced birth length. Birth length was reduced by − 3.83 mm (95% CI -6.91; − 0.75) for every IQR (0.74 × 10− 5 per m) increase of soot, and reduced by − 2.82 mm (95% CI -5.33;-0.30) for every IQR (4.68 μg/m3) increase of NOx. Outdoor air pollutants were not significantly associated with reduced birth weight nor the risk of LBW.ConclusionExposure to soot and NOx during pregnancy was associated with reduced birth length. Associations between exposure to all air pollutants with birth weight and the risk of LBW were less convincing.

Urban policy interventions to reduce traffic-related emissions and air pollution: A systematic evidence map

BackgroundUrban areas are hot spots for human exposure to air pollution, which originates in large part from traffic. As the urban population continues to grow, a greater number of people risk exposure to traffic-related air pollution (TRAP) and its adverse, costly health effects. In many cities, there is a need and scope for air quality improvements through targeted policy interventions, which continue to grow including rapidly changing technologies. ObjectiveThis systematic evidence map (SEM) examines and characterizes peer-reviewed evidence on urban-level policy interventions aimed at reducing traffic emissions and/or TRAP from on-road mobile sources, thus potentially reducing human exposures and adverse health effects and producing various co-benefits. MethodsThis SEM follows a previously peer-reviewed and published protocol with minor deviations, explicitly outlined here. Articles indexed in Public Affairs Index, TRID, Medline and Embase were searched, limited to English, published between January 1, 2000, and June 1, 2020. Covidence was used to screen articles based on previously developed eligibility criteria. Data for included articles was extracted and manually documented into an Excel database. Data visualizations were created in Tableau. ResultsWe identified 7528 unique articles from database searches and included 376 unique articles in the final SEM. There were 58 unique policy interventions, and a total of 1,139 unique policy scenarios, comprising these interventions and different combinations thereof. The policy interventions fell under 6 overarching policy categories: 1) pricing, 2) land use, 3) infrastructure, 4) behavioral, 5) technology, and 6) management, standards, and services, with the latter being the most studied. For geographic location, 463 policy scenarios were studied in Europe, followed by 355 in Asia, 206 in North America, 57 in South America, 10 in Africa, and 7 in Australia. Alternative fuel technology was the most frequently studied intervention (271 times), followed by vehicle emission regulation (134 times). The least frequently studied interventions were vehicle ownership taxes, and studded tire regulations, studied once each. A mere 3 % of studies addressed all elements of the full-chain—traffic emissions, TRAP, exposures, and health. The evidence recorded for each unique policy scenario is hosted in an open-access, query-able Excel database, and a complementary interactive visualization tool. We showcase how users can find more about the effectiveness of the 1,139 included policy scenarios in reducing, increasing, having mixed or no effect on traffic emissions and/or TRAP. ConclusionThis is the first peer-reviewed SEM to compile international evidence on urban-level policy interventions to reduce traffic emissions and/or TRAP in the context of human exposure and health effects. We also documented reported enablers, barriers, and co-benefits. The open-access Excel database and interactive visualization tool can be valuable resources for practitioners, policymakers, and researchers. Future updates to this work are recommended. Protocol RegistrationSanchez, K.A., Foster, M., Nieuwenhuijsen, M.J., May, A.D., Ramani, T., Zietsman, J. and Khreis, H., 2020. Urban policy interventions to reduce traffic emissions and traffic-related air pollution: Protocol for a systematic evidence map. Environment international, 142, p.105826.

Traffic-Related Air Pollution and Breast Cancer Risk: A Systematic Review and Meta-Analysis of Observational Studies.

Current evidence of an association of breast cancer (BC) risk with air pollution exposure, in particular from traffic exhaust, remains inconclusive, and the exposure assessment methodologies are heterogeneous. This study aimed to conduct a systematic review and meta-analysis on the association between traffic-related air pollution (TRAP) and BC incidence (PROSPERO CRD42021286774). We systematically reviewed observational studies assessing exposure to TRAP and BC risk published until June 2022, available on Medline/PubMed and Web of Science databases. Studies using models for assessing exposure to traffic-related air pollutants or using exposure proxies (including traffic density, distance to road, etc.) were eligible for inclusion. A random-effects meta-analysis of studies investigating the association between NO2/NOx exposure and BC risk was conducted. Overall, 21 studies meeting the inclusion criteria were included (seven case-control, one nested case-control, 13 cohort studies); 13 studies (five case-control, eight cohort) provided data for inclusion in the meta-analyses. Individual studies provided little evidence of an association between TRAP and BC risk; exposure assessment methods and time periods of traffic emissions were different. The meta-estimate on NO2 exposure indicated a positive association (pooled relative risk per 10 µg/m3 of NO2: 1.015; 95% confidence interval, CI: 1.003; 1.028). No association between NOx exposure and BC was found (three studies). Although there was limited evidence of an association for TRAP estimated with proxies, the meta-analysis showed a significant association between NO2 exposure, a common TRAP pollutant marker, and BC risk, yet with a small effect size. Our findings provide additional support for air pollution carcinogenicity.

On-board measurements using two successive vehicles to assess in-cabin concentrations of on-road pollutants

Gaseous and particulate pollutants are produced in large quantities from road vehicles. These traffic-related air pollutants can infiltrate the car-cabins exposing drivers and passengers to toxic substances with serious adverse health effects. The infiltration process depends on many parameters, those from outside of the vehicle (e.g. traffic intensity, meteorology, road type) and those depending on the vehicle itself such as the ventilation and/or the vehicle speed/age. In the present study, we undertook on-road measurements to assess the impact of ventilation and vehicles spacing (proximity effect) on in-cabin to on-road (I/O) concentration ratios of nitrogen oxides (NOx) and ultrafine particles (UFP). The novelty of the present work is that two successive vehicles have been used to circumvent the influence of the emissions of the upstream vehicle on the downstream test vehicle. We show that the distance to the upstream vehicle influences significantly the (I/O) ratios. Overall, the results show that car cabin is less polluted when the ventilation is set to recirculation mode and keeping a distance to the upstream car corresponding to twice its height in non-idle conditions.

Abstract TP187: The Mortality Cost Of Air Pollution And Carbon Dioxide Related To Mobile Stroke Unit Operation

Background: Mobile stroke units (MSU) have reduced time to thrombolysis, improved outcomes in ischemic stroke, but their sustainability and external costs have not been thoroughly evaluated. Fossil fuel combustion produces carbon dioxide (CO 2 ) and air pollution, which contribute to global climate crisis and excess mortality. Aim: To estimate the mortality cost of MSU due to increment of CO 2 and air pollution from fuel burned by MSU. Methods: Fuel cost of annual operation of MSU, obtained through correspondence, was used to obtain annual volume of gasoline burned by MSU. Estimate of excess global mortality between 2020 and 2100 from CO 2 -related climate change per increment of CO 2 was obtain from literature on the Mortality Cost of Carbon. Assuming the annual city-wide fuel consumption by road vehicles (publicly available) is directly proportional to excess mortality attributable to local traffic-related fine particulate matter (PM 2.5 ) air pollution (obtained from the literature), I estimated the increment of excess mortality related to air pollution produced by MSU operations. Results: Annual operation of one MSU burned 14.552 EUR of fuel, or 10.3 ton of gasoline, producing 24.7 ton of CO 2 . Such an increment of CO 2 in 2020 is expected to cause 0.0056 excess deaths (95% CI -0.0042, 0.0168) globally between 2020 and 2100 by contribution to climate crisis. In Berlin, mobile sources burn about 1.250.000 tons of liquid fossil fuel annually; and ~744 of annual deaths are attributable to traffic-related air pollution [2.17% (95% CI 1.55%, 2.79%) of total mortality]. Assuming the emission factor of MSU is the same as the local vehicle average, MSU-related air pollution leads to 0.0061 excess deaths (95% CI: 0.0044, 0.0079) per MSU-year. Conclusion: Fossil fuel combustion related to MSU operation is estimated to cause 0.0117 excess annual deaths (95% CI 0.0002, 0.0247) due to contribution to local air pollution and global climate crisis.

Long-term exposure to ambient air pollution and cognitive function in older US adults: The Multi-Ethnic Study of Atherosclerosis.

Cognitive assessment, including the Cognitive Abilities Screening Instrument (CASI), Digit Symbol Coding (DSC), and Digit Span (DS), was completed in 4392 older participants in the United States during 2010-2012. Residence-specific air pollution exposures (i.e., oxides of nitrogen [NO2/NOx], PM2.5 and its components: elemental carbon [EC], organic carbon [OC], sulfur [S], and silicon [Si]) were estimated by geo-statistical models. Linear and logistic regression models were used to estimate the associations between each air pollutants metric and cognitive function. An interquartile range (IQR) increase in EC (0.8 μg/m3) and Si (23.1 ng/m3) was associated with -1.27 (95% confidence interval [CI]: -0.09, -2.45) and -0.88 (95% CI: -0.21, -1.54) lower CASI scores in global cognitive function. For each IQR increase in Si, the odds of low cognitive function (LCF) across domains was 1.29 times higher (95% CI: 1.04, 1.60). For other tests, NO X was associated with slower processing speed (DSC: -2.01, 95% CI: -3.50, -0.52) and worse working memory (total DS: -0.4, 95% CI: -0.78, -0.01). No associations were found for PM2.5 and two PM2.5 components (OC and S) with any cognitive function outcomes. Higher exposure to traffic-related air pollutants including both tailpipe (EC and NO x ) and non-tailpipe (Si) species were associated with lower cognitive function in older adults.

Relationship between traffic-related air pollution and inflammation biomarkers using structural equation modeling

BackgroundEvidence suggests that exposure to traffic-related air pollution (TRAP) and social stressors can increase inflammation. Given that there are many different markers of TRAP exposure, socio-economic status (SES), and inflammation, analytical approaches can leverage multiple markers to better elucidate associations. In this study, we applied structural equation modeling (SEM) to assess the association between a TRAP construct and a SES construct with an inflammation construct. MethodsThis analysis was conducted as part of the Community Assessment of Freeway Exposure and Health (CAFEH; N = 408) study. Air pollution was characterized using a spatiotemporal model of particle number concentration (PNC) combined with individual participant time-activity adjustment (TAA). TAA-PNC and proximity to highways were considered for a construct of TRAP exposure. Participant demographics on education and income for an SES construct were assessed via questionnaires. Blood samples were analyzed for high sensitivity C-reactive protein (hsCRP), interleukin-6 (IL-6), and tumor necrosis factor-α receptor II (TNFRII), which were considered for the construct for inflammation. We conducted SEM and compared our findings with those obtained using generalized linear models (GLM). ResultsUsing GLM, TAA-PNC was associated with multiple inflammation biomarkers. An IQR (10,000 particles/cm3) increase of TAA-PNC was associated with a 14 % increase in hsCRP in the GLM. Using SEM, the association between the TRAP construct and the inflammation construct was twice as large as the associations with any individual inflammation biomarker. SES had an inverse association with inflammation in all models. Using SEM to estimate the indirect effects of SES on inflammation through the TRAP construct strengthened confidence in the association of TRAP with inflammation. ConclusionOur TRAP construct resulted in stronger associations with a combined construct for inflammation than with individual biomarkers, reinforcing the value of statistical approaches that combine multiple, related exposures or outcomes. Our findings are consistent with inflammatory risk from TRAP exposure.

Traffic-Related Air Pollution and Ground-Level Ozone Associated Global DNA Hypomethylation and Bulky DNA Adduct Formation.

Studies have indicated that air pollution, including surface-level ozone (O3), can significantly influence the risk of chronic diseases. To better understand the carcinogenic mechanisms of air pollutants and identify predictive disease biomarkers, we examined the association between traffic-related pollutants with DNA methylation alterations and bulky DNA adducts, two biomarkers of carcinogen exposure and cancer risk, in the peripheral blood of 140 volunteers-95 traffic police officers, and 45 unexposed subjects. The DNA methylation and adduct measurements were performed by bisulfite-PCR and pyrosequencing and 32P-postlabeling assay. Airborne levels of benzo(a)pyrene [B(a)P], carbon monoxide, and tropospheric O3 were determined by personal exposure biomonitoring or by fixed monitoring stations. Overall, air pollution exposure was associated with a significant reduction (1.41 units) in global DNA methylation (95% C.I. -2.65-0.04, p = 0.026). The decrement in ALU repetitive elements was greatest in the policemen working downtown (95% C.I. -3.23--0.49, p = 0.008). The DNA adducts were found to be significantly increased (0.45 units) in the municipal officers with respect to unexposed subjects (95% C.I. 0.02-0.88, p = 0.039), mainly in those who were controlling traffic in downtown areas (95% C.I. 0.39-1.29, p < 0.001). Regression models indicated an increment of ALU methylation at higher B(a)P concentrations (95% C.I. 0.03-0.60, p = 0.032). Moreover, statistical models showed a decrement in ALU methylation and an increment of DNA damage only above the cut-off value of 30 µg/m3 O3. A significant increment of 0.73 units of IL-6 gene methylation was also found in smokers with respect to non-smokers. Our results highlighted the role of air pollution on epigenetic alterations and genotoxic effects, especially above the target value of 30 µg/m3 surface-level O3, supporting the necessity for developing public health strategies aimed to reduce traffic-related air pollution molecular alterations.

Cross-sectional associations of different types of nature exposure with psychotropic, antihypertensive and asthma medication

BackgroundExposure to natural environments is thought to be beneficial for human health, but the evidence is inconsistent.ObjectiveTo examine whether exposure to green and blue spaces in urban environments is associated...

Brief diesel exhaust exposure acutely impairs functional brain connectivity in humans: a randomized controlled crossover study

BackgroundWhile it is known that exposure to traffic-related air pollution causes an enormous global toll on human health, neurobiological underpinnings therein remain elusive. The study addresses this gap in knowledge.MethodsWe performed the first controlled human exposure study using functional MRI with an efficient order-randomized double-blind crossover study of diesel exhaust (DE) and control (filtered air; FA) in 25 healthy adults (14 males, 11 females; 19–49 years old; no withdrawals). Analyses were carried out using a mixed effects model in FLAME. Z (Gaussianised T/F) statistic images were thresholded non-parametrically using clusters determined by Z > 2.3 and a (corrected) cluster significance threshold of p = 0.05.ResultsAll 25 adults went through the exposures and functional MRI imaging were collected. Exposure to DE yielded a decrease in functional connectivity compared to exposure to FA, shown through the comparison of DE and FA in post-exposure measurement of functional connectivity.ConclusionWe observed short-term pollution-attributable decrements in default mode network functional connectivity. Decrements in brain connectivity causes many detrimental effects to the human body so this finding should guide policy change in air pollution exposure regulation.Trial registrationUniversity of British Columbia Clinical Research Ethics Board (# H12-03025), Vancouver Coastal Health Ethics Board (# V12-03025), and Health Canada’s Research Ethics Board (# 2012-0040).

Long-term exposure to traffic-related air pollution and temperature increases gynecological cancers

BackgroundCervical, endometrial, and ovarian cancers are three major gynecological cancers (GCs) leading to heavy disease burden and high mortality among women worldwide, which are associated with environmental exposure. However, the role of air pollution and temperature on GCs remains unclear. ObjectiveTo assess the combined effects of short-term, medium-term, and long-term exposure to ambient air pollution and temperature indicators on GCs in women. MethodsA case-control study was conducted in XiangYa Hospital from 2010 to 2018 at Changsha, China. A standard questionnaire was designed to collect the health status and personal factors of 305 cases with GCs including cervical, endometrial, and ovarian cancers and 399 healthy women as control group. Personal exposure to ambient air pollution (PM10, SO2, and NO2), temperature, and diurnal temperature variation (DTV) during past one year, past five years, and past ten years was calculated by inverse distance weighted (IDW) method based on each subject's home address. Multiple logistic regression model was used to analyse the relationship of GCs with outdoor air pollution and temperature indicators. ResultsExposure to NO2 during past five years and past ten years was significantly associated with GCs, with adjusted ORs (95% CI) of 1.40 (1.02–1.91) and 1.41 (1.03–1.93). Furthermore, an increase in temperature during past ten years was related with GCs, with OR (95% CI) = 1.95 (1.16–3.25). We strikingly found that high temperature increased the effect of long-term exposure to PM10 and NO2 during past ten years on GCs, while low DTV elevated GCs risk of air pollution exposure. Sensitivity analysis suggests that some specific subjects were more susceptible to the effect of air pollution and temperature indicators on GCs. ConclusionRelatively long-term exposure to traffic-related air pollution (NO2) and increased temperature played important roles in the development of women's GCs. There may be interactions between air pollution and temperature indicators on GCs.

Modeling expected air quality impacts of Oregon's proposed expanded clean fuels program

The public health burden of traffic-related air pollution falls most heavily on the population living closest to major transportation corridors, which leads to exposure disparities between different socio-economic groups across the United States. The state of Oregon has adopted climate policies to reduce transportation fuel carbon intensity (CI). These climate policies have the potential co-benefit of reducing air pollution exposure disparities for different socio-economic groups. Here we analyze the emissions and air quality outcomes of three future year (2035) scenarios for transportation fuels in Oregon: (i) a Business as usual (BAU) scenario, (ii) a Clean Fuels Program (CFP) scenario that represents adoption and successful achievement of a proposed 25% reduction in carbon intensity in 2035; and (iii) a maximum ambition scenario (CFP MAX) that builds on the CFP scenario to achieve a 37% CI reduction by adopting low carbon fuels more aggressively, especially for heavy duty vehicles. Transportation emissions under all scenarios were estimated using the MOVES model for every county in Oregon. Detailed emissions with 4 km spatial resolution were then developed for each scenario by scaling the National Emissions Inventory (NEI) for the year 2017 based on the emissions derived from the MOVES analysis. Air quality in 2035 was simulated using the UCD/CIT chemical transport model that enables a detailed analysis of PM2.5 and PM0.1 components and sources. Exposure fields were analyzed using the BenMAP model to predict public health outcomes. Environmental justice analysis was conducted by race/ethnicity categories and income categories obtained from the American Community Survey (ACS). Results suggest that adoption of low-carbon transportation fuels will improve air quality in Oregon, yielding public health benefits equivalent to approximately $80M/yr. Adoption of low carbon transportation fuels will also reduce disparities in exposure to transportation-related air pollution between residents in different race/ethnicity categories by ∼14% in Portland and ∼20% in Salem. Adoption of low-carbon fuels reduces PM2.5 mass disparity by 10% in Salem, but does not have a significant effect in Portland, because on-road mobile sources contribute to less than 3% of the total PM2.5 mass disparity in this city. The analysis reveals that the spatial distribution of each race/ethnicity group in each city is the primary factor that determines the impact of low carbon fuel adoption on exposure disparity.

Relationships of Residential Distance to Major Traffic Roads with Dementia Incidence and Brain Structure Measures: Mediation Role of Air Pollution.

Background: Uncertainty exists regarding the operating pathways between near-roadway exposure and dementia incidence. We intend to examine relationships between proximity to major roadways with dementia incidence and brain MRI structure measures, and potential mediation roles of air and noise pollution. Methods: The cohort study was based on the UK Biobank. Baseline survey was conducted from 2006 to 2010, with linkage to electronic health records conducted for follow-up. Residential distance to major roadways was ascertained residential address postcode. A land use regression model was applied for estimating traffic-related air pollution at residence. Dementia incidence was ascertained using national administrative databases. Brain MRI measures were derived as image-derived phenotypes, including total brain, white matter, gray matter, and peripheral cortical gray matter. Results: We included 460,901 participants [mean (SD) age: 57.1 (8.1) years; men: 45.7%]. Compared with individuals living >1,000 m from major traffic roads, living ≤1,000 m was associated with a 13% to 14% higher dementia risk, accounting for 10% of dementia cases. Observed association between residential distance and dementia was substantially mediated by traffic-related air pollution, mainly nitrogen dioxide (proportion mediated: 63.6%; 95% CI, 27.0 to 89.2%) and PM2.5 (60.9%, 26.8 to 87.0%). The shorter residential distance was associated with smaller volumes of brain structures, which was also mediated by traffic-related air pollutants. No significant mediation role was observed of noise pollution. Conclusions: The shorter residential distance to major roads was associated with elevated dementia incidence and smaller brain structure volumes, which was mainly mediated by traffic-related air pollution.

Exposure to outdoor residential noise during pregnancy, embryonic size, fetal growth, and birth outcomes

IntroductionPrevious literature suggested that noise exposure during pregnancy was not associated with adverse birth outcomes. However, no studies evaluated the association between noise exposure and embryonic and fetal growth, or mutually assessed other urban environmental exposures such as traffic-related air pollution or natural spaces. MethodsWe included 7947 pregnant women from the Generation R Study, the Netherlands. We estimated total (road traffic, aircraft, railway, and industry), road traffic, and railway noise at the participants' home addresses during pregnancy using environmental noise maps. We estimated traffic-related air pollution using land-use regression models, greenness within a 300 m buffer using the normalized difference vegetation index, and distance to blue spaces using topographical maps at the home addresses. Embryonic size (crown-rump length) and fetal growth parameters (head circumference, femur length, and estimated fetal weight) were measured by ultrasound at several gestational ages. Information on neonatal anthropometrics at birth (head circumference, length, and weight) and adverse birth outcomes (preterm birth, low birth weight, and small for gestational age) were retrieved from medical records. ResultsHigher total noise exposure during pregnancy was associated with larger crown-rump length (0.07 SDS [95%CI 0.00 to 0.14]). No association was found with fetal growth parameters, neonatal anthropometrics, and adverse birth outcomes. Similar results were observed for road traffic noise exposure, while railway noise exposure was not associated with any of the outcomes. Traffic-related air pollution was not associated with crown-rump length. Total noise exposure mediated 15% of the association between exposure to greenness and smaller crown-rump length. No association was observed between distance to blue spaces and total noise exposure. ConclusionExposure to outdoor residential noise during pregnancy was associated with larger embryonic size. Moreover, a reduction of total noise exposure during pregnancy partially mediated the association between exposure to greenness and smaller embryonic size. Additional research is warranted to confirm and further understand these novel findings.

Prenatal exposure to tailpipe and non-tailpipe tracers of particulate matter pollution and autism spectrum disorders

BackgroundTraffic-related air pollution exposure is associated with increased risk of autism spectrum disorder (ASD). It is unknown whether carbonaceous material from vehicular tailpipe emissions or redox-active non-tailpipe metals, eg. from tire and brake wear, are responsible. We assessed ASD associations with fine particulate matter (PM2.5) tracers of tailpipe (elemental carbon [EC] and organic carbon [OC]) and non-tailpipe (copper [Cu]; iron [Fe] and manganese [Mn]) sources during pregnancy in a large cohort. MethodsThis retrospective cohort study included 318,750 children born in Kaiser Permanente Southern California (KPSC) hospitals during 2001–2014, followed until age 5. ASD cases were identified by ICD codes. Monthly estimates of PM2.5 and PM2.5 constituents EC, OC, Cu, Fe, and Mn with 4 km spatial resolution were obtained from a source-oriented chemical transport model. These exposures and NO2 were assigned to each maternal address during pregnancy, and associations with ASD were assessed using Cox regression models adjusted for covariates. PM constituent effect estimates were adjusted for PM2.5 and NO2 to assess independent effects. To distinguish ASD risk associated with non-tailpipe from tailpipe sources, the associations with Cu, Fe, and Mn were adjusted for EC and OC, and vice versa. ResultsThere were 4559 children diagnosed with ASD. In single-pollutant models, increased ASD risk was associated with gestational exposures to tracers of both tailpipe and non-tailpipe emissions. The ASD hazard ratios (HRs) per inter-quartile increment of exposure) for EC, OC, Cu, Fe, and Mn were 1.11 (95% CI: 1.06–1.16), 1.09 (95% CI: 1.04–1.15), 1.09 (95% CI: 1.04–1.13), 1.14 (95% CI: 1.09–1.20), and 1.17 (95% CI: 1.12–1.22), respectively. Estimated effects of Cu, Fe, and Mn (reflecting non-tailpipe sources) were largely unchanged in two-pollutant models adjusting for PM2.5, NO2, EC or OC. In contrast, ASD associations with EC and OC were markedly attenuated by adjustment for non-tailpipe sources. ConclusionResults suggest that non-tailpipe emissions may contribute to ASD. Implications are that reducing tailpipe emissions, especially from vehicles with internal combustion engines, may not eliminate ASD associations with traffic-related air pollution.

Determining the Concentration Level of Air Pollutants Related to Road Traffic in Kano Metropolis

The problem of road traffic-related air pollutants is universal. Traffic air pollution usually occurs on roads and mainly at intersections which significantly affects the air quality of such areas. The research aims to provide empirical evidence on the relationship between road transport air pollutants and temperature conditions on climate modification in the study area, which might perfect environmental sustainability. The study was best designed on field Experimentation to assess the spatiotemporal emission levels and analyses the implications of road Vehicular traffic-related air pollutants Concentration (such as, Carbon monoxide, Nitrogen dioxide, Sulphur dioxide, Hydrogen Sulphide and Methane gas) on Kano weather conditions (precisely Temperature) in 15 selected sample sites or locations, the measurements of pollutants Concentration, temperature level were carried out using the instruments called a Crowcorn gas detector, field thermometer were used together with the help of 5 research assistants. presents the periodic concentration levels of CH4 (methane) in relation to road traffic in different time periods: afternoon, evening, and morning, categorized into three concentration levels: high, medium, and low. The table provides various statistical measures to describe the distribution of methane concentrations within each category. High Concentrations in the afternoon reveal an average mean methane concentration is 0.20. The coefficient of variability, which measures the dispersion of the data points around the mean, is 46.06%. The skewness of 1.19 implies a moderately positively skewed distribution. The kurtosis of 1.38 indicates a distribution with a peak slightly higher than a normal distribution and a moderate presence of outliers. These findings could inform air quality management and monitoring efforts in Kano Metropolis. If temperature is consistently correlated with higher CO and CH4 levels, authorities may need to consider seasonal variations and temperature-related interventions when addressing air quality issues.

Selected Indicators of Al-Najaf Road Network: Public Transportation Noise and Pollution

It is urgently necessary to improve the state of transportation and related infrastructure, especially given that the most important indicators of urban development gauge a city's progress. One of the most influential of these indicators is what is known as "smart transport, " which refers to transportation that utilizes modern communication and information technology technologies to address various challenges in various transportation sectors. The holy city of Najaf smart transportation strategy seeks to reduce dangerous levels of traffic-related noise and air pollution while enhancing various aspects of mobility and traffic flow indicators. This study aims to evaluate the performance of the existing traffic network and public transport in Najaf City and its interference with noise and air pollution at selected points for data gathering by using field measurements using cameras, noise meters, and pollution measurement devices. The study states that the public transport sector in Al-Najaf city is significantly poor as private cars are dominant by about 65% of traffic mix with values of pollution and noise above the standards. One of the most effective solutions to traffic problems is the implementation of intelligent transportation systems. Part of these strategies is establishing a tram network and raising road classes’ strategies by proposing some geometric design editing, U-turns reducing, and raised ramps additions.