Using the Community Multiscale Air Quality (CMAQ) model to estimate public health impacts of PM2.5 from individual power plants

We estimated PM_2.5-related public health impacts/ton emitted of primary PM_2.5, SO₂, and NO_x for a set of power plants in the Mid-Atlantic and Lower Great Lakes regions of the United States, selected to include varying emission profiles and broad geographic representation. We then developed a regression model explaining variability in impacts per ton emitted using the population distributions around each plant. We linked outputs from the Community Multiscale Air Quality (CMAQ) model v 4.7.1 with census data and concentration–response functions for PM_2.5-related mortality, and monetized health estimates using the value-of-statistical-life. The median impacts for the final set of plants were $130,000/ton for primary PM_2.5 (range: $22,000–230,000), $28,000/ton for SO₂ (range: $19,000–33,000), and $16,000/ton for NOx (range: $7100–26,000). Impacts of NO_x were a median of 34% (range: 20%–75%) from ammonium nitrate and 66% (range: 25%–79%) from ammonium sulfate. The latter pathway is likely from NO_x enhancing atmospheric oxidative capacity and amplifying sulfate formation, and is often excluded. Our regression models explained most of the variation in impact/ton estimates using basic population covariates, and can aid in estimating impacts averted from interventions such as pollution controls, alternative energy installations, or demand-side management.     

Projecting future air pollution-related mortality under a changing climate: progress,uncertainties and research needs

BackgroundClimate change may affect mortality associated with air pollutants, especially for fine particulate matter (PM_2.5) and ozone (O₃). Projection studies of such kind involve complicated modelling approaches with uncertainties.ObjectivesWe conducted a systematic review of researches and methods for projecting future PM_2.5-/O₃-related mortality to identify the uncertainties and optimal approaches for handling uncertainty.MethodsA literature search was conducted in October 2013, using the electronic databases: PubMed, Scopus, ScienceDirect, ProQuest, and Web of Science. The search was limited to peer-reviewed journal articles published in English from January 1980 to September 2013.DiscussionFifteen studies fulfilled the inclusion criteria. Most studies reported that an increase of climate change-induced PM_2.5 and O₃ may result in an increase in mortality. However, little research has been conducted in developing countries with high emissions and dense populations. Additionally, health effects induced by PM_2.5 may dominate compared to those caused by O₃, but projection studies of PM_2.5-related mortality are fewer than those of O₃-related mortality.There is a considerable variation in approaches of scenario-based projection researches, which makes it difficult to compare results. Multiple scenarios, models and downscaling methods have been used to reduce uncertainties. However, few studies have discussed what the main source of uncertainties is and which uncertainty could be most effectively reduced.ConclusionsProjecting air pollution-related mortality requires a systematic consideration of assumptions and uncertainties, which will significantly aid policymakers in efforts to manage potential impacts of PM_2.5 and O₃ on mortality in the context of climate change.     

Modelling future impacts of air pollution using the multi-scale UK Integrated Assessment Model (UKIAM)

Integrated assessment modelling has evolved to support policy development in relation to air pollutants and greenhouse gases by providing integrated simulation tools able to produce quick and realistic representations of emission scenarios and their environmental impacts without the need to re-run complex atmospheric dispersion models. The UK Integrated Assessment Model (UKIAM) has been developed to investigate strategies for reducing UK emissions by bringing together information on projected UK emissions of SO₂, NO_x, NH₃, PM₁₀ and PM_2.5, atmospheric dispersion, criteria for protection of ecosystems, urban air quality and human health, and data on potential abatement measures to reduce emissions, which may subsequently be linked to associated analyses of costs and benefits. We describe the multi-scale model structure ranging from continental to roadside, UK emission sources, atmospheric dispersion of emissions, implementation of abatement measures, integration with European-scale modelling, and environmental impacts. The model generates outputs from a national perspective which are used to evaluate alternative strategies in relation to emissions, deposition patterns, air quality metrics and ecosystem critical load exceedance. We present a selection of scenarios in relation to the 2020 Business-As-Usual projections and identify potential further reductions beyond those currently being planned.     

Effect of the shape of the exposure-response function on estimated hospital costs in a study on non-elective pneumonia hospitalizations related to particulate matter

ObjectiveWe used log-linear and log-log exposure-response (E-R) functions to model the association between PM_2.5 exposure and non-elective hospitalizations for pneumonia, and estimated the attributable hospital costs by using the effect estimates obtained from both functions.MethodsWe used hospital discharge data on 3519 non-elective pneumonia admissions from UZ Brussels between 2007 and 2012 and we combined a case-crossover design with distributed lag models. The annual averted pneumonia hospitalization costs for a reduction in PM_2.5 exposure from the mean (21.4 μg/m³) to the WHO guideline for annual mean PM_2.5 (10 μg/m³) were estimated and extrapolated for Belgium.ResultsNon-elective hospitalizations for pneumonia were significantly associated with PM_2.5 exposure in both models. Using a log-linear E-R function, the estimated risk reduction for pneumonia hospitalization associated with a decrease in mean PM_2.5 exposure to 10 μg/m³ was 4.9%. The corresponding estimate for the log-log model was 10.7%. These estimates translate to an annual pneumonia hospital cost saving in Belgium of €15.5 million and almost €34 million for the log-linear and log-log E-R function, respectively.DiscussionAlthough further research is required to assess the shape of the association between PM_2.5 exposure and pneumonia hospitalizations, we demonstrated that estimates for health effects and associated costs heavily depend on the assumed E-R function. These results are important for policy making, as supra-linear E-R associations imply that significant health benefits may still be obtained from additional pollution control measures in areas where PM levels have already been reduced.     

Future climate and adverse health effects caused by fine particulate matter air pollution: case study for Poland

Ground level air pollution, especially fine particulate matter (PM_2.5), has been associated with a number of adverse health effects. The dispersion of PM_2.5 through the atmosphere depends on several mutually connected anthropogenic, geophysical and meteorological parameters, all of which are affected by climate change. This study examines how projected climate change would affect population exposure to PM_2.5 air pollution in Poland. Population exposure to PM_2.5 in Poland was estimated for three decades: the 1990s, 2040s and 2090s. Future climate conditions were projected by Regional Climate Model RegCM (Beta), forced by the general atmospheric circulation model ECHAM5. The dispersion of PM_2.5 was simulated with chemical transport model CAMx version 4.40. Population exposure estimates of PM_2.5 were 18.3, 17.2 and 17.1 μg/m³ for the 1990s, 2040s and 2090s, respectively. PM_2.5 air pollution was estimated to cause approximately 39,800 premature deaths in the population of Poland in the year 2000. Our results indicate that in Poland, climate change may reduce the levels of exposure to anthropogenic particulate air pollution in future decades and that this reduction will reduce adverse health effects caused by the air pollution.     

A framework to spatially cluster air pollution monitoring sites in US based on the PM2.5 composition

BackgroundHeterogeneity in the response to PM_2.5 is hypothesized to be related to differences in particle composition across monitoring sites which reflect differences in source types as well as climatic and topographic conditions impacting different geographic locations. Identifying spatial patterns in particle composition is a multivariate problem that requires novel methodologies.ObjectivesUse cluster analysis methods to identify spatial patterns in PM_2.5 composition. Verify that the resulting clusters are distinct and informative.Methods109 monitoring sites with 75% reported speciation data during the period 2003–2008 were selected. These sites were categorized based on their average PM_2.5 composition over the study period using k-means cluster analysis. The obtained clusters were validated and characterized based on their physico-chemical characteristics, geographic locations, emissions profiles, population density and proximity to major emission sources.ResultsOverall 31 clusters were identified. These include 21 clusters with 2 or more sites which were further grouped into 4 main types using hierarchical clustering. The resulting groupings are chemically meaningful and represent broad differences in emissions. The remaining clusters, encompassing single sites, were characterized based on their particle composition and geographic location.ConclusionsThe framework presented here provides a novel tool which can be used to identify and further classify sites based on their PM_2.5 composition. The solution presented is fairly robust and yielded groupings that were meaningful in the context of air-pollution research.     

Exposure to long-term air pollution and road traffic noise in relation to cholesterol: A cross-sectional study

BackgroundExposure to traffic noise and air pollution have both been associated with cardiovascular disease, though the mechanisms behind are not yet clear.ObjectivesWe aimed to investigate whether the two exposures were associated with levels of cholesterol in a cross-sectional design.MethodsIn 1993–1997, 39,863 participants aged 50–64 year and living in the Greater Copenhagen area were enrolled in a population-based cohort study. For each participant, non-fasting total cholesterol was determined in whole blood samples on the day of enrolment. Residential addresses 5-years preceding enrolment were identified in a national register and road traffic noise (L_den) were modeled for all addresses. For air pollution, nitrogen dioxide (NO₂) was modeled at all addresses using a dispersion model and PM_2.5 was modeled at all enrolment addresses using a land-use regression model. Analyses were done using linear regression with adjustment for potential confounders as well as mutual adjustment for the three exposures.ResultsBaseline residential exposure to the interquartile range of road traffic noise, NO₂ and PM_2.5 was associated with a 0.58 mg/dl (95% confidence interval: − 0.09; 1.25), a 0.68 mg/dl (0.22; 1.16) and a 0.78 mg/dl (0.22; 1.34) higher level of total cholesterol in single pollutant models, respectively. In two pollutant models with adjustment for noise in air pollution models and vice versa, the association between air pollution and cholesterol remained for both air pollution variables (NO₂: 0.72 (0.11; 1.34); PM_2.5: 0.70 (0.12; 1.28) mg/dl), whereas there was no association for noise (− 0.08 mg/dl). In three-pollutant models (NO₂, PM_2.5 and road traffic noise), estimates for NO₂ and PM_2.5 were slightly diminished (NO₂: 0.58 (− 0.05; 1.22); PM_2.5: 0.57 (− 0.02; 1.17) mg/dl).ConclusionsAir pollution and possibly also road traffic noise may be associated with slightly higher levels of cholesterol, though associations for the two exposures were difficult to separate.     

Smoke-haze pollution: a review of the 1997 episode in Southeast Asia

In the second half of 1997, large areas in Southeast Asia were severely affected by a smoke-haze pollution episode caused by the emissions of an estimated 45,600 km² of vegetation that burnt on the Indonesian islands Kalimantan and Sumatra. To document the impacts of these fires on air quality, data for total suspended particulate matter (TSP) and for particulate matter below or equal to 10 microns in diameter (PM₁₀) from selected sites in Indonesia, Malaysia and Singapore are analysed in this paper. These data are supplemented by meteorological data, satellite images and a summary of related research. TSP was above 2,000 μg m^–3 for several days in Indonesian locations close to the most extensive fire activity. In Malaysia and Singapore, ambient particle concentrations increased to several times their average September levels. Characteristically for emissions from vegetation burning, the additional atmospheric particle loading during the smoke-haze episode was predominantly due to an increase of the fraction below or equal to 2.5 microns in diameter (PM_2.5). Due to the dominance of respirable particles (PM_2.5) in the smoke-haze, air quality reporting based on TSP or PM₁₀ may be inadequate to assess the health risk. Upgrading of PM_2.5 monitoring facilities is therefore needed. Reducing the probability of similar smoke-haze events in future would require appropriate fire use and smoke management strategies. Electronic Publication     

DNA hypomethylation and its mediation in the effects of fine particulate air pollution on cardiovascular biomarkers: A randomized crossover trial

BackgroundShort-term exposure to fine particulate matter (PM_2.5) air pollution has been associated with altered DNA methylation in observational studies, but it remains unclear whether this change mediates the effects on cardiovascular biomarkers.ObjectiveTo examine the impact of ambient PM_2.5 on gene-specific DNA methylation and its potential mediation in the acute effects of PM_2.5 on cardiovascular biomarkers.MethodsWe designed a randomized, double-blind crossover trial using true or sham air purifiers for 48 h among 35 healthy college students in Shanghai, China, in 2014. We measured blood global methylation estimated in long interspersed nucleotide element-1 (LINE‑1) and Alu repetitive elements, methylation in ten specific genes, and ten cardiovascular biomarkers. We used linear mixed-effect models to examine the associations between PM_2.5 and methylation. We also performed causal mediation analyses to evaluate the potential mediation of methylation in the associations between PM_2.5 and biomarkers.ResultsAir purification increased DNA methylation in repetitive elements and all candidate genes. An IQR increase (64 μg/m³) in PM_2.5 was significantly associated with reduction of methylation in LINE-1 (1.44%), one pro-inflammatory gene (CD40LG, 9.13%), two pro-coagulant genes (F3, 15.20%; SERPINE1, 3.69%), and two pro-vasoconstriction genes (ACE, 4.64%; EDN1, 9.74%). There was a significant mediated effect (17.82%, P = 0.03) of PM_2.5 on sCD40L protein through CD40LG hypomethylation. Hypomethylation in other candidate genes generally showed positive but non-significant mediation.ConclusionsThis intervention study provided robust human evidence that ambient PM_2.5 could induce rapid decreases in DNA methylation and consequently partly mediate its effects on cardiovascular biomarkers.     

Exposure to coarse particulate matter during gestation and birth weight in the U.S.

Few studies have explored the relationship between coarse particles (PM_10-2.5) and adverse birth outcomes. We examined associations between gestational exposure of PM_10-2.5 and birth weight. U.S. birth certificates data (1999–2007) were acquired for 8,017,865 births. Gestational and trimester exposures of PM_10-2.5 were estimated using co-located PM₁₀ and PM_2.5 monitors ≤ 35 km from the population-weighted centroid of mothers' residential counties. A linear regression model was applied, adjusted by potential confounders. As sensitivity analyses, we explored alternative PM_10-2.5 estimations, adjustment for PM_2.5, and stratification by regions. Gestational exposure to PM_10-2.5 was associated with 6.6 g (95% Confidence Interval: 5.9, 7.2) lower birth weight per interquartile range increase (7.8 μg/m³) in PM_10-2.5 exposures. All three trimesters showed associations. Under different exposure methods for PM_10-2.5, associations remained consistent but with different magnitudes. Results were robust after adjusting for PM_2.5, and regional analyses showed associations in all four regions with larger estimates in the South. Our results suggest that PM_10-2.5 is associated with birth weight in addition to PM_2.5. Regional heterogeneity may reflect differences in population, measurement error, region-specific emission pattern, or different chemical composition within PM_10-2.5. Most countries do not set health-based standards for PM_10-2.5, but our findings indicate potentially important health effects of PM_10-2.5.     

Modeling the effects of emission controls in the Netherlands

A photochemical air quality simulation model was applied to an area covering a large portion of The Netherlands and nearby source areas in Belgium and Germany. Simulations of an O₃ episode typical of those that occur during summer months yielded good agreement between predicted and observed O₃ levels. The level of performance for NO₂ and NO was somewhat less than that for O₃. The model was used to study the influence of mobile and stationary sources within the region, as well as the inflow of pollutants from outside the region on predicted O₃, NO₂, and NO levels within the modeling region. Pollutants transported into the region appear to have a significant influence on O₃ levels. The influence of stationary source emissions on O₃ and NO₂ levels is greater than that of mobile source emissions. The model has been a valuable tool in evaluating the possible influence of different source categories and control regulations on pollutant concentration levels.     

Traffic-related air pollution and hyperactivity/inattention,dyslexia and dyscalculia in adolescents of the German GINIplus and LISAplus birth cohorts

BackgroundFew studies have examined the link between air pollution exposure and behavioural problems and learning disorders during late childhood and adolescence.ObjectivesTo determine whether traffic-related air pollution exposure is associated with hyperactivity/inattention, dyslexia and dyscalculia up to age 15 years using the German GINIplus and LISAplus birth cohorts (recruitment 1995–1999).MethodsHyperactivity/inattention was assessed using the German parent-completed (10 years) and self-completed (15 years) Strengths and Difficulties Questionnaire. Responses were categorized into normal versus borderline/abnormal. Parent-reported dyslexia and dyscalculia (yes/no) at age 10 and 15 years were defined using parent-completed questionnaires. Individual-level annual average estimates of nitrogen dioxide (NO₂), particulate matter (PM)₁₀ mass, PM_2.5 mass and PM_2.5 absorbance concentrations were assigned to each participant's birth, 10 year and 15 year home address. Longitudinal associations between the air pollutants and the neurodevelopmental outcomes were assessed using generalized estimation equations, separately for both study areas, and combined in a random-effects meta-analysis. Odds ratios and 95% confidence intervals are given per interquartile range increase in pollutant concentration.ResultsThe prevalence of abnormal/borderline hyperactivity/inattention scores and parental-reported dyslexia and dyscalculia at 15 years of age was 12.9%, 10.5% and 3.4%, respectively, in the combined population (N = 4745). In the meta- analysis, hyperactivity/inattention was associated with PM_2.5 mass estimated to the 10 and 15 year addresses (1.12 [1.01, 1.23] and 1.11 [1.01, 1.22]) and PM_2.5 absorbance estimated to the 10 and 15 year addresses (1.14 [1.05, 1.25] and 1.13 [1.04, 1.23], respectively).ConclusionsWe report associations suggesting a potential link between air pollution exposure and hyperactivity/inattention scores, although these findings require replication.     

A statistical model to evaluate the effectiveness of PM2.5 emissions control during the Beijing 2008 Olympic Games

A statistical model was developed using satellite remote sensing data and meteorological parameters to evaluate the effectiveness of air pollution control measures during the 2008 Beijing Olympic Games. Custom satellite retrievals under hazy conditions were included in the modeling dataset to represent the air pollution levels more accurately. This model explained 70% of the PM_2.5 variability during the modeling period from June to October 2008. Using this tool, we estimate that the aggressive emission reduction measures alone effectively lowered PM_2.5 levels by 20–24 μg/m³ or 27–33% on average during the Games period, which is substantially greater than those reported previously. Since parameters required to develop this model are readily available in most cities of the world, it can be quickly applied after other major events to evaluate air pollution control policy.     

Traffic-related air pollution and health co-benefits of alternative transport in Adelaide,South Australia

BackgroundMotor vehicle emissions contribute nearly a quarter of the world's energy-related greenhouse gases and cause non-negligible air pollution, primarily in urban areas. Changing people's travel behaviour towards alternative transport is an efficient approach to mitigate harmful environmental impacts caused by a large number of vehicles. Such a strategy also provides an opportunity to gain health co-benefits of improved air quality and enhanced physical activities. This study aimed at quantifying co-benefit effects of alternative transport use in Adelaide, South Australia.MethodWe made projections for a business-as-usual scenario for 2030 with alternative transport scenarios. Separate models including air pollution models and comparative risk assessment health models were developed to link alternative transport scenarios with possible environmental and health benefits.ResultsIn the study region with an estimated population of 1.4 million in 2030, by shifting 40% of vehicle kilometres travelled (VKT) by passenger vehicles to alternative transport, annual average urban PM_2.5 would decline by approximately 0.4 μg/m³ compared to business-as-usual, resulting in net health benefits of an estimated 13 deaths/year prevented and 118 disability-adjusted life years (DALYs) prevented per year due to improved air quality. Further health benefits would be obtained from improved physical fitness through active transport (508 deaths/year prevented, 6569 DALYs/year prevented), and changes in traffic injuries (21 deaths and, 960 DALYs prevented).ConclusionAlthough uncertainties remain, our findings suggest that significant environmental and health benefits are possible if alternative transport replaces even a relatively small portion of car trips. The results may provide assistance to various government organisations and relevant service providers and promote collaboration in policy-making, city planning and infrastructure establishment.     

Combustion particles emitted during church services: Implications for human respiratory health

Burning candles and incense generate particulate matter (PM) that produces poor indoor air quality and may cause human pulmonary problems. This study physically characterised combustion particles collected in a church during services. In addition, the emissions from five types of candles and two types of incense were investigated using a combustion chamber. The plasmid scission assay was used to determine the oxidative capacities of these church particles. The corresponding risk factor (CRf) was derived from the emission factor (Ef) and the oxidative DNA damage, and used to evaluate the relative respiratory exposure risks. Real-time PM measurements in the church during candle–incense burning services showed that the levels (91.6 μg/m³ for PM₁₀; 38.9 μg/m³ for PM_2.5) exceeded the European Union (EU) air quality guidelines. The combustion chamber testing, using the same environmental conditions, showed that the incense Ef for both PM₁₀ (490.6–587.9 mg/g) and PM_2.5 (290.1–417.2 mg/g) exceeded that of candles; particularly the PM_2.5 emissions. These CRf results suggested that the exposure to significant amounts of incense PM could result in a higher risk of oxidative DNA adducts (27.4–32.8 times) than tobacco PM. The generation and subsequent inhalation of PM during church activities may therefore pose significant risks in terms of respiratory health effects.     

Levels and major sources of PM2.5 and PM10 in Bangkok Metropolitan Region

This research was the first long-term attempt to concurrently measure and identify major sources of both PM₁₀ and PM_2.5 in Bangkok Metropolitan Region (BMR). Ambient PM₁₀ and PM_2.5 were evaluated at four monitoring stations and analyzed for elemental compositions, water-soluble ions, and total carbon during February 2002–January 2003. Fifteen chemical elements, four water-soluble ions, and total carbon were analyzed to assist major source identification by a receptor model approach, known as chemical mass balance. PM₁₀ and PM_2.5 were significantly different (p < 0.05) at all sites and 24 h averages were high at traffic location while two separated residential sites were similar. Seasonal difference of PM₁₀ and PM_2.5 concentrations was distinct between dry and wet seasons. Major source of PM₁₀ at the traffic site indicated that automobile emissions and biomass burning-related sources contributed approximately 33% each. Automobiles contributed approximately 39 and 22% of PM₁₀ mass at two residential sites while biomass burning contributed about 36 and 28%. PM₁₀ from re-suspended soil and cooking sources accounted for 10 to 15% at a residential site. Major sources of PM_2.5 at traffic site were automobile and biomass burning, contributing approximately 32 and 26%, respectively. Biomass burning was the major source of PM_2.5 mass concentrations at residential sites. Meat cooking also accounted for 31% of PM_2.5 mass at a low impact site. Automobile, biomass burning, and road dust were less significant, contributed 10, 6, and 5%, respectively. Major sources identification at some location had difficulty to achieve performance criteria due to limited source profiles. Improved in characterize other sources profiles will help local authority to better air quality.     

Personal exposure to fine particulate matter and blood pressure: A role of angiotensin converting enzyme and its DNA methylation

BackgroundThe underlying intermediate mechanisms about the association between fine particulate matter (PM_2.5) air pollution and blood pressure (BP) were unclear. Few epidemiological studies have explored the potential mediation effects of angiotensin-converting enzyme (ACE) and its DNA methylation.MethodsWe designed a longitudinal panel study with 4 follow-ups among 36 healthy college students in Shanghai, China from December 17, 2014 to July 11, 2015. We measured personal real-time exposure to PM_2.5, serum ACE level, and blood methylation of ACE gene and the repetitive elements. We applied linear mixed-effects models to examine the effects of PM_2.5 on ACE protein, DNA methylation and BP markers. Furthermore, we conducted mediation analyses to evaluate the potential pathways.ResultsAn interquartile range increase (26.78 μg/m³) in 24-h average exposure to PM_2.5 was significantly associated with 1.12 decreases in ACE average methylation (%5mC), 13.27% increase in ACE protein, and increments of 1.13 mmHg in systolic BP, 0.66 mmHg in diastolic BP and 0.82 mmHg in mean arterial pressure. ACE hypomethylation mediated 11.78% (P = 0.03) of the elevated ACE protein by PM_2.5. Increased ACE protein accounted for 3.90 ~ 13.44% (P = 0.35 ~ 0.68) of the elevated BP by PM_2.5. Repetitive-element methylation was also decreased but did not significantly mediate the association between PM_2.5 and BP.ConclusionsThis investigation provided strong evidence that short-term exposure to PM_2.5 was significantly associated with BP, ACE protein and ACE methylation. Our findings highlighted a possible involvement of ACE and ACE methylation in the effects of PM_2.5 on elevating BP.     

Racial isolation and exposure to airborne particulate matter and ozone in understudied US populations: Environmental justice applications of downscaled numerical model output

BackgroundResearchers and policymakers are increasingly focused on combined exposures to social and environmental stressors, especially given how often these stressors tend to co-locate. Such exposures are equally relevant in urban and rural areas and may accrue disproportionately to particular communities or specific subpopulations.ObjectivesTo estimate relationships between racial isolation (RI), a measure of the extent to which minority racial/ethnic group members are exposed to only one another, and long-term particulate matter with an aerodynamic diameter of < 2.5 μ (PM_2.5) and ozone (O₃) levels in urban and nonurban areas of the eastern two-thirds of the US.MethodsLong-term (5 year average) census tract-level PM_2.5 and O₃ concentrations were calculated using output from a downscaler model (2002–2006). The downscaler uses a linear regression with additive and multiplicative bias coefficients to relate ambient monitoring data with gridded output from the Community Multi-scale Air Quality (CMAQ) model. A local, spatial measure of RI was calculated at the tract level, and tracts were classified by urbanicity, RI, and geographic region. We examined differences in estimated pollutant exposures by RI, urbanicity, and demographic subgroup (e.g., race/ethnicity, education, socioeconomic status, age), and used linear models to estimate associations between RI and air pollution levels in urban, suburban, and rural tracts.ResultsHigh RI tracts (≥ 80th percentile) had higher average PM_2.5 levels in each category of urbanicity compared to low RI tracts (< 20th percentile), with the exception of the rural West. Patterns in O₃ levels by urbanicity and RI differed by region. Linear models indicated that PM_2.5 concentrations were significantly and positively associated with RI. The largest association between PM_2.5 and RI was observed in the rural Midwest, where a one quintile increase in RI was associated with a 0.90 μg/m³ (95% confidence interval: 0.83, 0.99 μg/m³) increase in PM_2.5 concentration. Associations between O₃ and RI in the Northeast, Midwest and West were positive and highest in suburban and rural tracts, even after controlling for potential confounders such as percentage in poverty.ConclusionRI is associated with higher 5 year estimated PM_2.5 concentrations in urban, suburban, and rural census tracts, adding to evidence that segregation is broadly associated with disparate air pollution exposures. Disproportionate burdens to adverse exposures such as air pollution may be a pathway to racial/ethnic disparities in health.     

Associations among plasma metabolite levels and short-term exposure to PM2.5 and ozone in a cardiac catheterization cohort

RationaleExposure to ambient particulate matter (PM) and ozone has been associated with cardiovascular disease (CVD). However, the mechanisms linking PM and ozone exposure to CVD remain poorly understood.ObjectiveThis study explored associations between short-term exposures to PM with a diameter < 2.5 μm (PM_2.5) and ozone with plasma metabolite concentrations.Methods and resultsWe used cross-sectional data from a cardiac catheterization cohort at Duke University, North Carolina (NC), USA, accumulated between 2001 and 2007. Amino acids, acylcarnitines, ketones and total non-esterified fatty acid plasma concentrations were determined in fasting samples. Daily concentrations of PM_2.5 and ozone were obtained from a Bayesian space-time hierarchical model, matched to each patient's residential address. Ten metabolites were selected for the analysis based on quality criteria and cluster analysis. Associations between metabolites and PM_2.5 or ozone were analyzed using linear regression models adjusting for long-term trend and seasonality, calendar effects, meteorological parameters, and participant characteristics.We found delayed associations between PM_2.5 or ozone and changes in metabolite levels of the glycine-ornithine-arginine metabolic axis and incomplete fatty acid oxidation associated with mitochondrial dysfunction. The strongest association was seen for an increase of 8.1 μg/m³ in PM_2.5 with a lag of one day and decreased mean glycine concentrations (− 2.5% [95% confidence interval: − 3.8%; − 1.2%]).ConclusionsShort-term exposures to ambient PM_2.5 and ozone is associated with changes in plasma concentrations of metabolites in a cohort of cardiac catheterization patients. Our findings might help to understand the link between air pollution and cardiovascular disease.     

The mortality effect of ship-related fine particulate matter in the Sydney greater metropolitan region of NSW,Australia

This study investigates the mortality effect of primary and secondary PM_2.5 related to ship exhaust in the Sydney greater metropolitan region of Australia. A detailed inventory of ship exhaust emissions was used to model a) the 2010/11 concentration of ship-related PM_2.5 across the region, and b) the reduction in PM_2.5 concentration that would occur if ships used distillate fuel with a 0.1% sulfur content at berth or within 300 km of Sydney. The annual loss of life attributable to 2010/11 levels of ship-related PM_2.5 and the improvement in survival associated with use of low-sulfur fuel were estimated from the modelled concentrations.In 2010/11, approximately 1.9% of the region-wide annual average population weighted-mean concentration of all natural and human-made PM_2.5 was attributable to ship exhaust, and up to 9.4% at suburbs close to ports. An estimated 220 years of life were lost by people who died in 2010/11 as a result of ship exhaust-related exposure (95% CI_β: 140–290, where CI_β is the uncertainty in the concentration-response coefficient only). Use of 0.1% sulfur fuel at berth would reduce the population weighted-mean concentration of PM_2.5 related to ship exhaust by 25% and result in a gain of 390 life-years over a twenty year period (95% CI_β: 260–520). Use of 0.1% sulfur fuel within 300 km of Sydney would reduce the concentration by 56% and result in a gain of 920 life-years over twenty years (95% CI_β: 600–1200).Ship exhaust is an important source of human exposure to PM_2.5 in the Sydney greater metropolitan region. This assessment supports intervention to reduce ship emissions in the GMR. Local strategies to limit the sulfur content of fuel would reduce exposure and will become increasingly beneficial as the shipping industry expands. A requirement for use of 0.1% sulfur fuel by ships within 300 km of Sydney would provide more than twice the mortality benefit of a requirement for ships to use 0.1% sulfur fuel at berth.