Fine particulate air pollution and its components in association with cause-specific emergency admissions

Associations of short-term exposure to traffic-related air pollution with cardiovascular and respiratory hospital admissions in London, UK

OBJECTIVES

There is evidence of adverse associations between short-term exposure to traffic-related pollution and health, but little is known about the relative contribution of the various sources and particulate constituents.

METHODS

For each day for 2011-2012 in London, UK over 100 air pollutant metrics were assembled using monitors, modelling and chemical analyses. We selected a priori metrics indicative of traffic sources: general traffic, petrol exhaust, diesel exhaust and non-exhaust (mineral dust, brake and tyre wear). Using Poisson regression models, controlling for time-varying confounders, we derived effect estimates for cardiovascular and respiratory hospital admissions at prespecified lags and evaluated the sensitivity of estimates to multipollutant modelling and effect modification by season.

RESULTS

For single day exposure, we found consistent associations between adult (15-64 years) cardiovascular and paediatric (0-14 years) respiratory admissions with elemental and black carbon (EC/BC), ranging from 0.56% to 1.65% increase per IQR change, and to a lesser degree with carbon monoxide (CO) and aluminium (Al). The average of past 7 days EC/BC exposure was associated with elderly (65+ years) cardiovascular admissions. Indicated associations were higher during the warm period of the year. Although effect estimates were sensitive to the adjustment for other pollutants they remained consistent in direction, indicating independence of associations from different sources, especially between diesel and petrol engines, as well as mineral dust.

CONCLUSIONS

Our results suggest that exhaust related pollutants are associated with increased numbers of adult cardiovascular and paediatric respiratory hospitalisations. More extensive monitoring in urban centres is required to further elucidate the associations.

PM2.5 and survival among older adults: effect modification by particulate composition

BACKGROUND

Fine particulate (PM2.5) air pollution has been consistently linked to survival, but reported effect estimates are geographically heterogeneous. Exposure to different types of particle mixtures may explain some of this variation.

METHODS

We used k-means cluster analyses to identify cities with similar pollution profiles, (ie, PM2.5 composition) across the United States. We examined the impact of PM2.5 on survival, and its variation across clusters of cities with similar PM2.5 composition, among Medicare enrollees in 81 US cities (2000-2010). We used time-varying annual PM2.5 averages, measured at ambient central monitoring sites, as the exposure of interest. We ran by-city Cox models, adjusting for individual data on previous cardiopulmonary-related hospitalizations and stratifying by follow-up time, age, gender, and race. This eliminates confounding by factors varying across cities and long-term trends, focusing on year-to-year variations of air pollution around its city-specific mean and trend. We then pooled the city-specific effects using a random effects meta-regression. In this second stage, we also assessed effect modification by cluster membership and estimated cluster-specific PM2.5 effects.

RESULTS

We followed more than 19 million subjects and observed more than 6 million deaths. We found a harmful impact of annual PM2.5 concentrations on survival (hazard ratio = 1.11 [95% confidence interval = 1.01, 1.23] per 10 μg/m). This effect was modified by particulate composition, with higher effects observed in clusters containing high concentrations of nickel, vanadium, and sulfate. For instance, our highest effect estimate was observed in cities with harbors in the Northwest, characterized by high nickel, vanadium, and elemental carbon concentrations (1.9 [1.1, 3.3]). We observed null or negative associations in clusters with high oceanic and crustal particles.

CONCLUSIONS

To the best of our knowledge, this is the first study to examine the association between PM2.5 composition and survival. Our findings indicate that long-term exposure to fuel oil combustion and power plant emissions have the highest impact on survival.

A New Method to Jointly Estimate the Mortality Risk of Long-Term Exposure to Fine Particulate Matter and its Components

Most studies on the association between exposure to fine particulate matter (PM2.5) and mortality have considered only total concentration of PM2.5 or individual components of PM2.5, and not the combined effects of concentration and particulate composition. We sought to develop a method to estimate the risk of death from long-term exposure to PM2.5 and the distribution of its components, namely: sulphate, nitrate, ammonium, organic mass, black carbon, and mineral dust. We decomposed PM2.5 exposure into the sum of total concentration and the proportion of each component. We estimated the risk of death due to exposure using a cohort of ~2.4 million Canadians who were followed for vital status over 16 years. Modelling the concentration of PM2.5 with the distribution of the proportions of components together was a superior predictor for mortality than either total PM2.5 concentration alone, or all component concentrations modelled together. Our new approach has the advantage of characterizing the toxicity of the atmosphere in its entirety. This is required to fully understand the health benefits associated with strategies to improve air quality that may result in complex changes not only in PM2.5 concentration, but also in the distribution of particle components.

Association between indoor air pollutant exposure and blood pressure and heart rate in subjects according to body mass index

This study investigates the effects of high body mass index (BMI) of subjects on individual who exhibited high cardiovascular disease indexes with blood pressure (BP) and heart rate (HR) when exposed to high levels of indoor air pollutants. We collected 115 office workers, and measured their systolic blood pressure (SBP), diastolic blood pressure (DBP) and HR at the end of the workday. The subjects were divided into three groups according to BMI: 18-24 (normal weight), 24-27 (overweight) and >27 (obese). This study also measured the levels of carbon dioxide (CO2), total volatile organic compounds (TVOC), particulate matter with an aerodynamic diameter less than 2.5μm (PM2.5), as well as the bacteria and fungi in the subjects' work-places. The pollutant effects were divided by median. Two-way analysis of variance (ANOVA) was used to analyze the health effects of indoor air pollution exposure according to BMI. Our study showed that higher levels of SBP, DBP and HR occurred in subjects who were overweight or obese as compared to those with normal weight. Moreover, there was higher level of SBP in subjects who were overweight or obese when they were exposed to higher levels of TVOC and fungi (p<0.05). We also found higher value for DBP and HR with increasing BMI to be associated with exposure to higher TVOC levels. This study suggests that individuals with higher BMI have higher cardiovascular disease risk when they are exposed to poor indoor air quality (IAQ), and specifically in terms of TVOC.

The impact of PM2.5 on the human respiratory system

Recently, many researchers paid more attentions to the association between air pollution and respiratory system disease. In the past few years, levels of smog have increased throughout China resulting in the deterioration of air quality, raising worldwide concerns. PM2.5 (particles less than 2.5 micrometers in diameter) can penetrate deeply into the lung, irritate and corrode the alveolar wall, and consequently impair lung function. Hence it is important to investigate the impact of PM2.5 on the respiratory system and then to help China combat the current air pollution problems. In this review, we will discuss PM2.5 damage on human respiratory system from epidemiological, experimental and mechanism studies. At last, we recommend to the population to limit exposure to air pollution and call to the authorities to create an index of pollution related to health.

Assessing public health burden associated with exposure to ambient black carbon in the United States

Black carbon (BC) is a significant component of fine particulate matter (PM2.5) air pollution, which has been linked to a series of adverse health effects, in particular premature mortality. Recent scientific research indicates that BC also plays an important role in climate change. Therefore, controlling black carbon emissions provides an opportunity for a double dividend. This study quantifies the national burden of mortality and morbidity attributable to exposure to ambient BC in the United States (US). We use GEOS-Chem, a global 3-D model of atmospheric composition to estimate the 2010 annual average BC levels at 0.5×0.667° resolution, and then re-grid to 12-km grid resolution across the continental US. Using PM2.5 mortality risk coefficient drawn from the American Cancer Society cohort study, the numbers of deaths due to BC exposure were estimated for each 12-km grid, and then aggregated to the county, state and national level. Given evidence that BC particles may pose a greater risk on human health than other components of PM2.5, we also conducted sensitivity analysis using BC-specific risk coefficients drawn from recent literature. We estimated approximately 14,000 deaths to result from the 2010 BC levels, and hundreds of thousands of illness cases, ranging from hospitalizations and emergency department visits to minor respiratory symptoms. Sensitivity analysis indicates that the total BC-related mortality could be even significantly larger than the above mortality estimate. Our findings indicate that controlling BC emissions would have substantial benefits for public health in the US.

Use of the Adaptive LASSO Method to Identify PM2.5 Components Associated with Blood Pressure in Elderly Men: The Veterans Affairs Normative Aging Study

BACKGROUND

PM2.5 (particulate matter ≤ 2.5 μm) has been associated with adverse cardiovascular outcomes, but it is unclear whether specific PM2.5 components, particularly metals, may be responsible for cardiovascular effects.

OBJECTIVES

We aimed to determine which PM2.5 components are associated with blood pressure in a longitudinal cohort.

METHODS

We fit linear mixed-effects models with the adaptive LASSO penalty to longitudinal data from 718 elderly men in the Veterans Affairs Normative Aging Study, 1999-2010. We controlled for PM2.5 mass, age, body mass index, use of antihypertensive medication (ACE inhibitors, non-ophthalmic beta blockers, calcium channel blockers, diuretics, and angiotensin receptor antagonists), smoking status, alcohol intake, years of education, temperature, and season as fixed effects in the models, and additionally applied the adaptive LASSO method to select PM2.5 components associated with blood pressure. Final models were identified by the Bayesian Information Criterion (BIC).

RESULTS

For systolic blood pressure (SBP), nickel (Ni) and sodium (Na) were selected by the adaptive LASSO, whereas only Ni was selected for diastolic blood pressure (DBP). An interquartile range increase (2.5 ng/m3) in 7-day moving-average Ni was associated with 2.48-mmHg (95% CI: 1.45, 3.50 mmHg) increase in SBP and 2.22-mmHg (95% CI: 1.69, 2.75 mmHg) increase in DBP, respectively. Associations were comparable when the analysis was restricted to study visits with PM2.5 below the 75th percentile of the distribution (12 μg/m3).

CONCLUSIONS

Our study suggested that exposure to ambient Ni was associated with increased blood pressure independent of PM2.5 mass in our study population of elderly men. Further research is needed to confirm our findings, assess generalizability to other populations, and identify potential mechanisms for Ni effects.

CITATION

Dai L, Koutrakis P, Coull BA, Sparrow D, Vokonas PS, Schwartz JD. 2016. Use of the adaptive LASSO method to identify PM2.5 components associated with blood pressure in elderly men: the Veterans Affairs Normative Aging Study. Environ Health Perspect 124:120-125; http://dx.doi.org/10.1289/ehp.1409021.

Fine particulate matter components and mortality in Greater Houston: Did the risk reduce from 2000 to 2011?

Fine particulate matter (less than 2.5μm in aerodynamic diameter; PM2.5) pollution poses a major environmental threat in Greater Houston due to rapid economic growth and the numerous PM2.5 sources including ports, vehicles, and the largest petrochemical industry in the United States (U.S.). Our objectives were to estimate the short-term associations between the PM2.5 components and mortality during 2000-2011, and evaluate whether these associations have changed over time. A total of 333,317 deaths were included in our assessment, with an average of 76 deaths per day. We selected 17 PM2.5 components from the U.S. Environmental Protection Agency's Chemical Speciation Network, and then applied Poisson regression models to assess the associations between the PM2.5 components and mortality. Additionally, we repeated our analysis for two consecutive periods: 2000-2005 and 2006-2011. Interquartile range increases in ammonium (0.881μg/m(3)), nitrate (0.487μg/m(3)), sulfate (2.245μg/m(3)), and vanadium (0.004μg/m(3)) were associated with an increased risk in mortality of 0.69% (95% confidence interval (CI): 0.26, 1.12%), 0.38% (95% CI: 0.11, 0.66%), 0.61% (95% CI: 0.15, 1.06%), and 0.58% (95% CI: 0.12, 1.04%), respectively. Seasonal analysis suggested that the associations were strongest during the winter months. The association between PM2.5 mass and mortality decreased during 2000-2011, however, the PM2.5 components showed no notable changes in mortality risk over time. Our study indicates that the short-term associations between PM2.5 and mortality differ across the PM2.5 components and suggests that future air pollution control measures should not only focus on mass but also pollutant sources.

A model-based approach for imputing censored data in source apportionment studies

Sources of particulate matter (PM) air pollution are generally inferred from PM chemical constituent concentrations using source apportionment models. Concentrations of PM constituents are often censored below minimum detection limits (MDL) and most source apportionment models cannot handle these censored data. Frequently, censored data are first substituted by a constant proportion of the MDL or are removed to create a truncated dataset before sources are estimated. When estimating the complete data distribution, these commonly applied methods to adjust censored data perform poorly compared with model-based imputation methods. Model-based imputation has not been used in source apportionment and may lead to better source estimation. However if the censored chemical constituents are not important for estimating sources, censoring adjustment methods may have little impact on source estimation. We focus on two source apportionment models applied in the literature and provide a comprehensive assessment of how censoring adjustment methods, including model-based imputation, impact source estimation. A review of censoring adjustment methods critically informs how censored data should be handled in these source apportionment models. In a simulation study, we demonstrated that model-based multiple imputation frequently leads to better source estimation compared with commonly used censoring adjustment methods. We estimated sources of PM in New York City and found estimated source distributions differed by censoring adjustment method. In this study, we provide guidance for adjusting censored PM constituent data in common source apportionment models, which is necessary for estimation of PM sources and their subsequent health effects.

Air Pollution and Ischemic Stroke Among Young Adults

BACKGROUND AND PURPOSE

Studies have demonstrated consistent associations between cardiovascular illness and particulate matter (PM) <10 and <2.5 μm in diameter, but stroke received less attention. We hypothesized that air pollution, an inflammation progenitor, can be associated with stroke incidence in young patients in whom the usual risk factors for stroke are less prevalent. We aimed to evaluate the association between stroke incidence and exposure to PM <10 and <2.5 μm, in a desert area characterized by a wide range of PM.

METHODS

We included all members of the largest health maintenance organization in Israel, who were admitted to a local hospital with stroke between 2005 and 2012. Exposure assessment was based on a hybrid model incorporating daily satellite remote sensing data at 1-km spatial resolution. We performed case-crossover analysis, stratified by personal characteristics and distance from main roads.

RESULTS

We identified 4837 stroke cases (89.4% ischemic stroke). Interquartile range of PM <10 and <2.5 μm was 36.3 to 54.7 and 16.7 to 23.3 μg/m(3), respectively. The subjects' average age was 70 years; 53.4% were males. Associations between ischemic stroke and increases of interquartile range average concentrations of particulate matter <10 or <2.5 μm at the day of the event were observed among subjects <55 years (odds ratio [95% confidence interval], 1.11 [1.02-1.20] and 1.10 [1.00-1.21]). Stronger associations were observed in subjects living within 75 m from a main road (1.22 [1.03-1.43] and 1.26 [1.04-1.51]).

CONCLUSIONS

We observed higher risk for ischemic stroke associated with PM among young adults. This finding can be explained by the inflammatory mechanism, linking air pollution and stroke.

Effect of daily temperature range on respiratory health in Argentina and its modification by impaired socio-economic conditions and PM10 exposures

Epidemiological investigations regarding temperature influence on human health have focused on mortality rather than morbidity. In addition, most information comes from developed countries despite the increasing evidence that climate change will have devastating impacts on disadvantaged populations living in developing countries. In the present study, we assessed the impact of daily temperature range on upper and lower respiratory infections in Cordoba, Argentina, and explored the effect modification of socio-economic factors and influence of airborne particles We found that temperature range is a strong risk factor for admissions due to both upper and lower respiratory infections, particularly in elderly individuals, and that these effects are more pronounced in sub-populations with low education level or in poor living conditions. These results indicate that socio-economic factors are strong modifiers of the association between temperature variability and respiratory morbidity, thus they should be considered in risk assessments.

Ambient Coarse Particulate Matter and Hospital Admissions in the Medicare Cohort Air Pollution Study, 1999-2010

BACKGROUND

In recent years a number of studies have examined the short-term association between coarse particulate matter (PM(10-2.5)) and mortality and morbidity outcomes. These studies, however, have produced inconsistent conclusions.

OBJECTIVES

We estimated both the national- and regional-level associations between PM(10-2.5) and emergency hospitalizations for both cardiovascular and respiratory disease among Medicare enrollees ≥ 65 years of age during the 12-year period 1999 through 2010.

METHODS

Using air pollution data obtained from the U.S. Environmental Protection Agency air quality monitoring network and daily emergency hospitalizations for 110 large urban U.S. counties assembled from the Medicare Cohort Air Pollution Study (MCAPS), we estimated the association between short-term exposure to PM(10-2.5) and hospitalizations using a two-stage Bayesian hierarchical model and Poisson log-linear regression models.

RESULTS

A 10-μg/m3 increase in PM(10-2.5) was associated with a significant increase in same-day cardiovascular hospitalizations [0.69%; 95% posterior interval (PI): 0.45, 0.92]. After adjusting for PM2.5, this association remained significant (0.63%; 95% PI: 0.38, 0.88). A 10-μg/m3 increase in PM(10-2.5) was not associated with a significant increase in respiratory-related hospitalizations.

CONCLUSIONS

We found statistically significant evidence that daily variation in PM(10-2.5) is associated with emergency hospitalizations for cardiovascular diseases among Medicare enrollees ≥ 65 years of age. This association was robust to adjustment for concentrations of PM2.5.

CITATION

Powell H, Krall JR, Wang Y, Bell ML, Peng RD. 2015. Ambient coarse particulate matter and hospital admissions in the Medicare Cohort Air Pollution Study, 1999-2010. Environ Health Perspect 123:1152-1158; http://dx.doi.org/10.1289/ehp.1408720.

Coarse Particulate Air Pollution Associated with Increased Risk of Hospital Admissions for Respiratory Diseases in a Tropical City, Kaohsiung, Taiwan

This study was undertaken to determine whether there was an association between coarse particles (PM₂.₅-₁₀) levels and frequency of hospital admissions for respiratory diseases (RD) in Kaohsiung, Taiwan. Hospital admissions for RD including chronic obstructive pulmonary disease (COPD), asthma, and pneumonia, and ambient air pollution data levels for Kaohsiung were obtained for the period from 2006 to 2010. The relative risk of hospital admissions for RD was estimated using a case-crossover approach, controlling for weather variables, day of the week, seasonality, and long-term time trends. For the single pollutant model (without adjustment for other pollutants), increased rate of admissions for RD were significantly associated with higher coarse PM levels only on cool days (<25 °C), with a 10 µg/m³ elevation in PM₂.₅-₁₀ concentrations associated with a 3% (95% CI = 1%-5%) rise in COPD admissions, 4% (95% CI = 1%-7%) increase in asthma admissions, and 3% (95% CI = 2%-4%) rise in pneumonia admissions. No significant associations were found between coarse particle levels and the number of hospital admissions for RD on warm days. In the two-pollutant models, PM₂.₅-₁₀ levels remained significantly correlated with higher rate of RD admissions even controlling for sulfur dioxide, nitrogen dioxide, carbon monoxide, or ozone on cool days. This study provides evidence that higher levels of PM₂.₅-₁₀ enhance the risk of hospital admissions for RD on cool days.

Association of Roadway Proximity with Fasting Plasma Glucose and Metabolic Risk Factors for Cardiovascular Disease in a Cross-Sectional Study of Cardiac Catheterization Patients

BACKGROUND

The relationship between traffic-related air pollution (TRAP) and risk factors for cardiovascular disease needs to be better understood in order to address the adverse impact of air pollution on human health.

OBJECTIVE

We examined associations between roadway proximity and traffic exposure zones, as markers of TRAP exposure, and metabolic biomarkers for cardiovascular disease risk in a cohort of patients undergoing cardiac catheterization.

METHODS

We performed a cross-sectional study of 2,124 individuals residing in North Carolina (USA). Roadway proximity was assessed via distance to primary and secondary roadways, and we used residence in traffic exposure zones (TEZs) as a proxy for TRAP. Two categories of metabolic outcomes were studied: measures associated with glucose control, and measures associated with lipid metabolism. Statistical models were adjusted for race, sex, smoking, body mass index, and socioeconomic status (SES).

RESULTS

An interquartile-range (990 m) decrease in distance to roadways was associated with higher fasting plasma glucose (β = 2.17 mg/dL; 95% CI: -0.24, 4.59), and the association appeared to be limited to women (β = 5.16 mg/dL; 95% CI: 1.48, 8.84 compared with β = 0.14 mg/dL; 95% CI: -3.04, 3.33 in men). Residence in TEZ 5 (high-speed traffic) and TEZ 6 (stop-and-go traffic), the two traffic zones assumed to have the highest levels of TRAP, was positively associated with high-density lipoprotein cholesterol (HDL-C; β = 8.36; 95% CI: -0.15, 16.9 and β = 5.98; 95% CI: -3.96, 15.9, for TEZ 5 and 6, respectively).

CONCLUSION

Proxy measures of TRAP exposure were associated with intermediate metabolic traits associated with cardiovascular disease, including fasting plasma glucose and possibly HDL-C.

Zinc compound air releases from Toxics Release Inventory facilities and cardiovascular disease mortality rates

BACKGROUND

Inhaled zinc has been found in association with cardiopulmonary toxicity. However, limited human epidemiologic studies are available. This study analyzed the association between covariate-adjusted cardiovascular (CVD) mortality rates and zinc compound air releases in the United States.

METHODS

We conducted an ecological analysis on the association between zinc compound air releases for 1991-2000 using the Toxics Release Inventory database and average age-adjusted CVD mortality for 2006-2010, adjusting for race/ethnicity composition and several health and socioeconomic factors. Models were estimated for males and females and for metropolitan and nonmetropolitan counties.

RESULTS

Zinc compound air releases were positively associated with increased adjusted CVD mortality rates in all four models (β=0.0085, p<0.0001 for males in nonmetropolitan counties; β=0.0093, p<0.0001 for males in metropolitan counties; β=0.0145, p<0.0001 for females in nonmetropolitan counties; and β=0.0098, p<0.0001 for females in metropolitan counties). Results were largely robust to various sensitivity analyses.

CONCLUSION

This study provides epidemiological evidence for possible CVD health impacts of inhaled zinc in the United States. Although the strongest effect was found for females in nonmetropolitan counties, the associations were consistent in nonmetropolitan or metropolitan counties for both genders.

Size distribution of total and water-soluble fractions of particle-bound elements-assessment of possible risks via inhalation

The size distribution of total and water-soluble elemental concentrations in six particle sizes <0.49, 0.49-0.97, 0.97-1.5, 1.5-3.0, 3.0-7.2, and 7.2-30 μm was investigated in Thessaloniki area, N. Greece, at two sites representing urban-traffic and urban-background character during the cold and warm period. The elements As, Cd, Cr, Cu, Pb, Ni, Zn, Ru, and Ir exhibited their highest mass portion in the fine particle mode (0.97-1.5 μm), whereas Al, Ba, Ca, Fe, and Mn occurred predominately in the coarse particle mode (3.0-7.2 μm). The water-soluble elemental fractions exhibited significant spatiotemporal variations and particle size dependence. Possible non-carcinogenic and carcinogenic risks associated with inhalation of particle-bound elements based on total and water-soluble concentrations were in acceptable levels. However, the cumulative risk for all potential particle-bound constituents has to be considered.

Air Pollution and Emergency Department Visits for Hypertension in Edmonton and Calgary, Canada: A Case-Crossover Study

BACKGROUND

Ambient air pollutant exposures have been associated with a wide variety of cardiovascular events; however, few studies have evaluated their impact upon acute emergency department (ED) visits for hypertension.

METHODS

The purpose of this study was to examine the associations between ED visits for hypertension and ambient air pollution concentrations among 6,532 patients during the period of January 2010 to December 2011 in Edmonton and Calgary, Alberta, Canada. The associations were evaluated using a case-crossover design.

RESULTS

Odds ratios and their 95% confidence interval have been calculated for 1 unit increase in their interquartile range for lags (the time between air pollutant measurement and exposure-response) 0-8 days. During the cold season, statistically significant positive results were observed for SO2 among lag days 4-6 and 8 for females and lag days 5 and 6 for males. Moreover, statistically significant positive results were observed for NO2 on lag day 7 for females and for PM2.5 on lag days 5 and 7, for females and lag day 6 for males. During the warm season, statistically significant positive results were observed for O3 on lag days 3 and 4 and for SO2 on lag days 2 and 8 for females.

CONCLUSIONS

These findings support the hypothesis that recent exposures to ambient levels of several air pollutants can be capable of elevating blood pressure to a clinically significant extent such that it leads to ED visits for hypertension.

Long-term effects of elemental composition of particulate matter on inflammatory blood markers in European cohorts

BACKGROUND

Epidemiological studies have associated long-term exposure to ambient particulate matter with increased mortality from cardiovascular and respiratory disorders. Systemic inflammation is a plausible biological mechanism behind this association. However, it is unclear how the chemical composition of PM affects inflammatory responses.

OBJECTIVES

To investigate the association between long-term exposure to elemental components of PM and the inflammatory blood markers high-sensitivity C-reactive protein (hsCRP) and fibrinogen as part of the European ESCAPE and TRANSPHORM multi-center projects.

METHODS

In total, 21,558 hsCRP measurements and 17,428 fibrinogen measurements from cross-sections of five and four cohort studies were available, respectively. Residential long-term concentrations of particulate matter <10μm (PM10) and <2.5μm (PM2.5) in diameter and selected elemental components (copper, iron, potassium, nickel, sulfur, silicon, vanadium, zinc) were estimated based on land-use regression models. Associations between components and inflammatory markers were estimated using linear regression models for each cohort separately. Cohort-specific results were combined using random effects meta-analysis. As a sensitivity analysis the models were additionally adjusted for PM mass.

RESULTS

A 5ng/m(3) increase in PM2.5 copper and a 500ng/m(3) increase in PM10 iron were associated with a 6.3% [0.7; 12.3%] and 3.6% [0.3; 7.1%] increase in hsCRP, respectively. These associations between components and fibrinogen were slightly weaker. A 10ng/m(3) increase in PM2.5 zinc was associated with a 1.2% [0.1; 2.4%] increase in fibrinogen; confidence intervals widened when additionally adjusting for PM2.5.

CONCLUSIONS

Long-term exposure to transition metals within ambient particulate matter, originating from traffic and industry, may be related to chronic systemic inflammation providing a link to long-term health effects of particulate matter.

Ozone, Fine Particulate Matter, and Chronic Lower Respiratory Disease Mortality in the United States

RATIONALE

Short-term effects of air pollution exposure on respiratory disease mortality are well established. However, few studies have examined the effects of long-term exposure, and among those that have, results are inconsistent.

OBJECTIVES

To evaluate long-term association between ambient ozone, fine particulate matter (PM2.5, particles with an aerodynamic diameter of 2.5 μm or less), and chronic lower respiratory disease (CLRD) mortality in the contiguous United States.

METHODS

We fit Bayesian hierarchical spatial Poisson models, adjusting for five county-level covariates (percentage of adults aged ≥65 years, poverty, lifetime smoking, obesity, and temperature), with random effects at state and county levels to account for spatial heterogeneity and spatial dependence.

MEASUREMENTS AND MAIN RESULTS

We derived county-level average daily concentration levels for ambient ozone and PM2.5 for 2001-2008 from the U.S. Environmental Protection Agency's down-scaled estimates and obtained 2007-2008 CLRD deaths from the National Center for Health Statistics. Exposure to ambient ozone was associated with an increased rate of CLRD deaths, with a rate ratio of 1.05 (95% credible interval, 1.01-1.09) per 5-ppb increase in ozone; the association between ambient PM2.5 and CLRD mortality was positive but statistically insignificant (rate ratio, 1.07; 95% credible interval, 0.99-1.14).

CONCLUSIONS

This study links air pollution exposure data with CLRD mortality for all 3,109 contiguous U.S. counties. Ambient ozone may be associated with an increased rate of death from CLRD in the contiguous United States. Although we adjusted for selected county-level covariates and unobserved influences through Bayesian hierarchical spatial modeling, the possibility of ecologic bias remains.

Cytotoxic and inflammatory potential of size-fractionated particulate matter collected repeatedly within a small urban area

Background

Exposure to coarse, fine, and ultrafine particles is associated with adverse population health impacts. We investigated whether size-fractionated particles collected repeatedly in the vicinity of industrial (steel mills and associated coking operations, wastewater treatment), high traffic, and residential areas display systematic differences in biological potency.

Methods

Particulate matter (PM_<0.1, PM_0.1–0.5, PM_0.5–2.5, PM_2.5–10, PM_>10) samples collected at sites within Windsor, Ontario, were screened for biological potency in human A549 lung epithelial and murine J774A.1 macrophage-like cells using cytotoxicity bioassays (cellular ATP, resazurin reduction, lactate dehydrogenase (LDH) release), cytokine production, and transcript profiles. Potency was determined from the slope of each dose-effect relationship.

Results

Cytotoxic potency varied across size fractions and within a fraction across sites and sampling periods, suggesting that particle composition, in addition to size and mass, affected particle toxicity. While ATP and LDH profiles showed some similarity, resazurin reduction (a measure of metabolic activity) exhibited a unique pattern of response, indicating that the cytotoxicity assays were sensitive to distinct particle characteristics. Chemical speciation varied in relation to prevailing winds, consistent with enrichment of source emissions (e.g. higher metal and polycyclic aromatic hydrocarbon content downwind of the industrial site). Notwithstanding this variability, site-dependent differences in particle toxicity were evident, including greater potency of coarse fractions at the industrial site and of ultrafine particles at the traffic site (Site × Size interactions, p < 0.05). Regression of potency against particle constituents revealed correlations between resazurin reduction, induction of metal-responsive genes, and metal content, which were particularly strong for the coarse fraction, and between cytokine release and endotoxin, suggesting that these factors were important drivers of biological effects that explain, at least in part, the contrasting potencies of particles compared on an equivalent mass basis.

Conclusions

The data show that 1) particle potency and composition can exhibit significant temporal variation in relation to source contributions; 2) sources may differentially impact the potency of specific size fractions; and 3) particle constituents, notably metals and endotoxin, may elicit distinct biological responses. Together, the data are consistent with the notion that sources and composition, in addition to size and mass concentration, are relevant to particle toxicity.

Electronic supplementary material

The online version of this article (doi:10.1186/s12989-015-0099-z) contains supplementary material, which is available to authorized users.

Chemical characterization of atmospheric particles and source apportionment in the vicinity of a steelmaking industry

The objective of this work was to provide a chemical characterization of atmospheric particles collected in the vicinity of a steelmaking industry and to identify the sources that affect PM10 levels. A total of 94 PM samples were collected in two sampling campaigns that occurred in February and June/July of 2011. PM2.5 and PM2.5-10 were analyzed for a total of 22 elements by Instrumental Neutron Activation Analysis and Particle Induced X-ray Emission. The concentrations of water soluble ions in PM10 were measured by Ion Chromatography and Indophenol-Blue Spectrophotometry. Positive Matrix Factorization receptor model was used to identify sources of particulate matter and to determine their mass contribution to PM10. Seven main groups of sources were identified: marine aerosol identified by Na and Cl (22%), steelmaking and sinter plant represented by As, Cr, Cu, Fe, Ni, Mn, Pb, Sb and Zn (11%), sinter plant stack identified by NH4(+), K and Pb (12%), an unidentified Br source (1.8%), secondary aerosol from coke making and blast furnace (19%), fugitive emissions from the handling of raw material, sinter plant and vehicles dust resuspension identified by Al, Ca, La, Si, Ti and V (14%) and sinter plant and blast furnace associated essentially with Fe and Mn (21%).

Spatial modeling of PM2.5 concentrations with a multifactoral radial basis function neural network

Accurate measurements of PM2.5 concentration over time and space are especially critical for reducing adverse health outcomes. However, sparsely stationary monitoring sites considerably hinder the ability to effectively characterize observed concentrations. Utilizing data on meteorological and land-related factors, this study introduces a radial basis function (RBF) neural network method for estimating PM2.5 concentrations based on sparse observed inputs. The state of Texas in the USA was selected as the study area. Performance of the RBF models was evaluated by statistic indices including mean square error, mean absolute error, mean relative deviation, and the correlation coefficient. Results show that the annual PM2.5 concentrations estimated by the RBF models with meteorological factors and/or land-related factors were markedly closer to the observed concentrations. RBF models with combined meteorological and land-related factors achieved best performance relative to ones with either type of these factors only. It can be concluded that meteorological factors and land-related factors are useful for articulating the variation of PM2.5 concentration in a given study area. With these covariate factors, the RBF neural network can effectively estimate PM2.5 concentrations with acceptable accuracy under the condition of sparse monitoring stations. The improved accuracy of air concentration estimation would greatly benefit epidemiological and environmental studies in characterizing local air pollution and in helping reduce population exposures for areas with limited availability of air quality data.

Associations of mortality with long-term exposures to fine and ultrafine particles, species and sources: results from the California Teachers Study Cohort

BACKGROUND

Although several cohort studies report associations between chronic exposure to fine particles (PM2.5) and mortality, few have studied the effects of chronic exposure to ultrafine (UF) particles. In addition, few studies have estimated the effects of the constituents of either PM2.5 or UF particles.

METHODS

We used a statewide cohort of > 100,000 women from the California Teachers Study who were followed from 2001 through 2007. Exposure data at the residential level were provided by a chemical transport model that computed pollutant concentrations from > 900 sources in California. Besides particle mass, monthly concentrations of 11 species and 8 sources or primary particles were generated at 4-km grids. We used a Cox proportional hazards model to estimate the association between the pollutants and all-cause, cardiovascular, ischemic heart disease (IHD), and respiratory mortality.

RESULTS

We observed statistically significant (p < 0.05) associations of IHD with PM2.5 mass, nitrate, elemental carbon (EC), copper (Cu), and secondary organics and the sources gas- and diesel-fueled vehicles, meat cooking, and high-sulfur fuel combustion. The hazard ratio estimate of 1.19 (95% CI: 1.08, 1.31) for IHD in association with a 10-μg/m3 increase in PM2.5 is consistent with findings from the American Cancer Society cohort. We also observed significant positive associations between IHD and several UF components including EC, Cu, metals, and mobile sources.

CONCLUSIONS

Using an emissions-based model with a 4-km spatial scale, we observed significant positive associations between IHD mortality and both fine and ultrafine particle species and sources. Our results suggest that the exposure model effectively measured local exposures and facilitated the examination of the relative toxicity of particle species.

Associations between long-term exposure to chemical constituents of fine particulate matter (PM2.5) and mortality in Medicare enrollees in the eastern United States

BACKGROUND

Several epidemiological studies have reported that long-term exposure to fine particulate matter (PM2.5) is associated with higher mortality. Evidence regarding contributions of PM2.5 constituents is inconclusive.

OBJECTIVES

We assembled a data set of 12.5 million Medicare enrollees (≥ 65 years of age) to determine which PM2.5 constituents are a) associated with mortality controlling for previous-year PM2.5 total mass (main effect); and b) elevated in locations exhibiting stronger associations between previous-year PM2.5 and mortality (effect modification).

METHODS

For 518 PM2.5 monitoring locations (eastern United States, 2000-2006), we calculated monthly mortality rates, monthly long-term (previous 1-year average) PM2.5, and 7-year averages (2000-2006) of major PM2.5 constituents [elemental carbon (EC), organic carbon matter (OCM), sulfate (SO42-), silicon (Si), nitrate (NO3-), and sodium (Na)] and community-level variables. We applied a Bayesian hierarchical model to estimate location-specific mortality rates associated with previous-year PM2.5 (model level 1) and identify constituents that contributed to the spatial variability of mortality, and constituents that modified associations between previous-year PM2.5 and mortality (model level 2), controlling for community-level confounders.

RESULTS

One-standard deviation (SD) increases in 7-year average EC, Si, and NO3- concentrations were associated with 1.3% [95% posterior interval (PI): 0.3, 2.2], 1.4% (95% PI: 0.6, 2.4), and 1.2% (95% PI: 0.4, 2.1) increases in monthly mortality, controlling for previous-year PM2.5. Associations between previous-year PM2.5 and mortality were stronger in combination with 1-SD increases in SO42- and Na.

CONCLUSIONS

Long-term exposures to PM2.5 and several constituents were associated with mortality in the elderly population of the eastern United States. Moreover, some constituents increased the association between long-term exposure to PM2.5 and mortality. These results provide new evidence that chemical composition can partly explain the differential toxicity of PM2.5.

Effects of airborne fine particles (PM2.5 ) on deep vein thrombosis admissions in the northeastern United States

BACKGROUND

Literature relating air pollution exposure to deep vein thrombosis (DVT) and pulmonary embolism (PE), despite biological plausibility, is sparse. No comprehensive study examining associations between both short- and long-term exposure to particulate matter (PM)2.5 and DVT or PE has been published. Using a novel PM2.5 prediction model, we study whether long- and short-term PM2.5 exposure is associated with DVT and PE admissions among elderly across the northeastern United States.

METHODS

We estimated daily exposure of PM2.5 in each ZIP code. We investigated the long- and short-term effects of PM2.5 on DVT and PE hospital admissions. There were 453,413 DVT and 151,829 PE admissions in the study. For short-term exposure, we performed a case crossover analysis matching month and year and defined the hazard period as lag 01 (exposure of day of admission and previous day). For the long-term association, we used a Poisson regression.

RESULTS

A 10-μg m(-3) increase in short-term exposure was associated with a 0.63% increase in DVT admissions (95% confidence interval [CI] = 0.03% to 1.25%) and a 6.98% (95% CI = 5.65% to 8.33%) increase in long-term exposure admissions. For PE, the associated risks were 0.38% (95% CI = -0.68% to 1.25%) and 2.67% (95% CI = 5.65% to 8.33%). These results persisted when analyses were restricted to location-periods meeting the current Environmental Protection Agency annual standard of 12 μg m(-3) .

CONCLUSIONS

Our findings showed that PM2.5 exposure was associated with DVT and PE hospital admissions and that current standards are not protective of this result.

Fine particulate matter components and emergency department visits for cardiovascular and respiratory diseases in the St. Louis, Missouri-Illinois, metropolitan area

BACKGROUND

Given that fine particulate matter (≤ 2.5 μm; PM2.5) is a mixture of multiple components, it has been of high interest to identify its specific health-relevant physical and/or chemical features.

OBJECTIVES

We conducted a time-series study of PM2.5 and cardiorespiratory emergency department (ED) visits in the St. Louis, Missouri-Illinois metropolitan area, using 2 years of daily PM2.5 and PM2.5 component measurements (including ions, carbon, particle-phase organic compounds, and elements) made at the St. Louis-Midwest Supersite, a monitoring site of the U.S. Environmental Protection Agency Supersites ambient air monitoring research program.

METHODS

Using Poisson generalized linear models, we assessed short-term associations between daily cardiorespiratory ED visit counts and daily levels of 24 selected pollutants. Associations were estimated for interquartile range changes in each pollutant. To allow comparison of relationships among multiple pollutants and outcomes with potentially different lag structures, we used 3-day unconstrained distributed lag models controlling for time trends and meteorology.

RESULTS

Considering results of our primary models, as well as sensitivity analyses and models assessing co-pollutant confounding, we observed robust associations of cardiovascular disease visits with 17α(H),21β(H)-hopane and congestive heart failure visits with elemental carbon. We also observed a robust association of respiratory disease visits with ozone. For asthma/wheeze, associations were strongest with ozone and nitrogen dioxide; observed associations of asthma/wheeze with PM2.5 and its components were attenuated in two-pollutant models with these gases. Differential measurement error due to differential patterns of spatiotemporal variability may have influenced patterns of observed associations across pollutants.

CONCLUSIONS

Our findings add to the growing field examining the health effects of PM2.5 components. Combustion-related components of the pollutant mix showed particularly strong associations with cardiorespiratory ED visit outcomes.

Association between Fine Particulate Air Pollution and Daily Clinic Visits for Migraine in a Subtropical City: Taipei, Taiwan

This study was undertaken to determine whether there was an association between fine particle (PM_2.5) levels and daily clinic visits for migraine in Taipei, Taiwan. Daily clinic visits for migraine and ambient air pollution data for Taipei were obtained for the period from 2006–2011. The odds ratio of clinic visits was estimated using a case-crossover approach, controlling for weather variables, day of the week, seasonality, and long-term time trends. Generally, no significant associations between PM_2.5 levels and migraine visits were observed on cool days. On warm days, however, for the single pollutant model (without adjustment for other pollutants), increased clinic visits for migraine were significantly associated with PM_2.5 levels, with an interquartile range (IQR) rise associated with a 13% (95% CI = 8%–19%) elevation in number of migraine visits. In bi-pollutant model, PM_2.5 remained significant after the inclusion of sulfur dioxide (SO₂) or ozone (O₃) on warm days. This study provides evidence that higher levels of PM_2.5 increase the risk of clinic visits for migraine in Taipei, Taiwan.

Ensemble-based source apportionment of fine particulate matter and emergency department visits for pediatric asthma

Epidemiologic studies utilizing source apportionment (SA) of fine particulate matter have shown that particles from certain sources might be more detrimental to health than others; however, it is difficult to quantify the uncertainty associated with a given SA approach. In the present study, we examined associations between source contributions of fine particulate matter and emergency department visits for pediatric asthma in Atlanta, Georgia (2002-2010) using a novel ensemble-based SA technique. Six daily source contributions from 4 SA approaches were combined into an ensemble source contribution. To better account for exposure uncertainty, 10 source profiles were sampled from their posterior distributions, resulting in 10 time series with daily SA concentrations. For each of these time series, Poisson generalized linear models with varying lag structures were used to estimate the health associations for the 6 sources. The rate ratios for the source-specific health associations from the 10 imputed source contribution time series were combined, resulting in health associations with inflated confidence intervals to better account for exposure uncertainty. Adverse associations with pediatric asthma were observed for 8-day exposure to particles generated from diesel-fueled vehicles (rate ratio = 1.06, 95% confidence interval: 1.01, 1.10) and gasoline-fueled vehicles (rate ratio = 1.10, 95% confidence interval: 1.04, 1.17).

Association between atmospheric pollutants and hospital admissions in Lisbon

Ambient air pollution is recognised as one of the potential environmental risk factors causing health hazards to the exposed population, demonstrated in numerous previous studies. Several longitudinal, ecological and epidemiological studies have shown associations between outdoor levels of outdoor atmospheric pollutants and adverse health effects, especially associated with respiratory and cardiovascular hospital admissions. The aim of this work is to assess the influence of atmospheric pollutants over the hospital admissions in Lisbon, by Ordinary Least Squares Linear Regression. The pollutants (CO, NO, NO2, SO2, O3, PM10 and PM2.5) were obtained from 13 monitoring stations of the Portuguese Environmental Agency, which provide hourly observations. Hospital admission data were collected from the Central Administration of the Health System and were compiled by age: <15, 15-64, >64 years old. The study period was 2006-2008. Results showed significant positive associations between the following: (1) the pollutants CO, NO, NO2, SO2, PM10 and PM2.5 and circulatory diseases for ages between 15 and 64 years (0.5% hospital admissions (HA) increase with 10 μg m(-3) NO increase) and above 64 years (1.0% stroke admission increase with 10 μg m(-3) NO2 increase); (2) the pollutants CO, NO, NO2, SO2, PM10 and PM2.5 and respiratory diseases for ages below 15 years (up to 1.9% HA increase with 10 μg m(-3) pollutant increase); and (3) the pollutants NO, NO2 and SO2 and respiratory diseases for ages above 64 years (1.3% HA increase with 10 μg m(-3) CO increase).

Particulate matter 2.5 induces autophagy via inhibition of the phosphatidylinositol 3-kinase/Akt/mammalian target of rapamycin kinase signaling pathway in human bronchial epithelial cells

Particulate matter 2.5 (PM2.5) is a significant risk factor for asthma. A recent study revealed that autophagy was associated with asthma pathogenesis. However, the specific mechanisms underlying PM2.5-induced autophagy in asthma have remained elusive. In the present study, PM2.5-induced autophagy was evaluated in Beas-2B human bronchial epithelial cells and the potential molecular mechanisms were investigated. Using electron microscopy, immunofluorescence staining and immunoblot studies, it was confirmed that PM2.5 induced autophagy in Beas-2B cells as a result of PM2.5-mediated inhibition of the phosphatidylinositol 3-kinase (PI3K)/Akt/mammalian target of rapamycin (mTOR) pathway in Beas-2B cells. LY294002, a PI3K inhibitor, reduced the accumulation of microtubule-associated protein 1 light chain 3 II and attenuated the effect of PM2.5. Phosphorylated (p-)p38, p-extracellular signal-regulated kinase and p-c-Jun N-terminal kinase were dephosphorylated following exposure to PM2.5. The roles of p53, reactive oxygen species scavenger tetramethylthiourea and autophagy inhibitor 3-methyladenine in PM2.5-induced autophagy in Beas-2B cells were also investigated. The results suggested that the PI3K/Akt/mTOR signaling pathway may be a key contributor to PM2.5-induced autophagy in Beas-2B cells. The results of the present study therefore provided an a insight into potential future clinical applications targeting these signaling pathways, for the prevention and/or treatment of PM2.5-induced lung diseases.

Short term exposure to air pollution and stroke: systematic review and meta-analysis

OBJECTIVE

To review the evidence for the short term association between air pollution and stroke.

DESIGN

Systematic review and meta-analysis of observational studies

DATA SOURCES

Medline, Embase, Global Health, Cumulative Index to Nursing and Allied Health Literature (CINAHL), and Web of Science searched to January 2014 with no language restrictions.

ELIGIBILITY CRITERIA

Studies investigating the short term associations (up to lag of seven days) between daily increases in gaseous pollutants (carbon monoxide, sulphur dioxide, nitrogen dioxide, ozone) and particulate matter (<2.5 µm or <10 µm diameter (PM2.5 and PM10)), and admission to hospital for stroke or mortality.

MAIN OUTCOME MEASURES

Admission to hospital and mortality from stroke.

RESULTS

From 2748 articles, 238 were reviewed in depth with 103 satisfying our inclusion criteria and 94 contributing to our meta-estimates. This provided a total of 6.2 million events across 28 countries. Admission to hospital for stroke or mortality from stroke was associated with an increase in concentrations of carbon monoxide (relative risk 1.015 per 1 ppm, 95% confidence interval 1.004 to 1.026), sulphur dioxide (1.019 per 10 ppb, 1.011 to 1.027), and nitrogen dioxide (1.014 per 10 ppb, 1.009 to 1.019). Increases in PM2.5 and PM10 concentration were also associated with admission and mortality (1.011 per 10 μg/m(3) (1.011 to 1.012) and 1.003 per 10 µg/m(3) (1.002 to 1.004), respectively). The weakest association was seen with ozone (1.001 per 10 ppb, 1.000 to 1.002). Strongest associations were observed on the day of exposure with more persistent effects observed for PM(2·5).

CONCLUSION

Gaseous and particulate air pollutants have a marked and close temporal association with admissions to hospital for stroke or mortality from stroke. Public and environmental health policies to reduce air pollution could reduce the burden of stroke.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO-CRD42014009225.

A field application of a personal sensor for ultrafine particle exposure in children

BACKGROUND

Ultrafine particles (UFPs) have been associated with adverse health outcomes in children, but studies are often limited by surrogate estimates of exposure. Accurately characterizing children's personal exposure to UFP is difficult due to the high spatiotemporal variability of UFP and children's time-activity patterns.

OBJECTIVE

The objectives of this study were to conduct a field test of a personal sensor for UFP (PUFP) by measuring UFP exposure among children and assess the sensor's capabilities and limitations.

METHODS

Children wore the sensor at school, during transit periods between school and home, and in their home for 2-4h on 2 consecutive days and provided feedback regarding their experience with the sensor. The PUFP sensor recorded UFP number concentration at one second intervals and recorded GPS location allowing for comparisons of UFP exposure at homes, schools, and during transit. A mixed-effects linear model was used to compare the effect of microenvironment on personal UFP measurements.

RESULTS

The overall total median personal exposure to UFP was 12,900 particles/cm(3) (p/cm(3)). Median UFP exposure at homes, schools and during transit was 17,800, 11,900, and 13,600 p/cm(3), respectively. Results of the mixed-effects model found that riding in a car and walking were significantly associated with 1.36 (95% CI 1.33-1.39) and 2.51 (95% CI 2.44-2.57) times higher UFP concentrations compared to the home.

CONCLUSIONS

The PUFP sensor can measure near real-time exposure to UFP with high spatiotemporal resolution. Children's exposure to UFP varies by location, with increased exposure during transit to and from school.

Physiological and perceived health effects from daily changes in air pollution and weather among persons with heart failure: a panel study

We carried out this daily diary panel study in Montreal, Quebec, to determine whether oxygen saturation, pulse rate, blood pressure, self-rated health, and shortness of breath at night were associated with concentrations of indoor carbon monoxide (CO), and indoor and outdoor fine particles (PM2.5), temperature, and relative humidity. Over a 2-month consecutive period between 2008 and 2010, we measured daily indoor and outdoor levels of the air pollutants and weather variables and 55 subjects measured their daily health and other variables. To estimate the associations between the health outcomes and the environmental exposures, we used a mixed effects regression model using an autoregressive model of order-one and we adjusted for month and day and personal variables. The general pattern of associations can be summarized as follows: oxygen saturation was reduced for increases in indoor- and outdoor-PM2.5 and temperature. Pulse rate increased on the concurrent day for increases in indoor CO and PM2.5. Diastolic blood pressure increased with increasing indoor and outdoor PM2.5 and relative humidity. Systolic blood pressure increased with indoor PM2.5 and decreased with increasing indoor and outdoor temperature. Self-rated health diminished with increases in outdoor PM2.5 and indoor and outdoor temperature. Self-reported shortness of breath at night increased with increasing indoor and outdoor temperatures. Health in heart failure is affected in the short term by personal and environmental conditions that are manifest in intermediate physiological parameters.

Temporal-spatial variations of the physicochemical characteristics of air pollution Particulate Matter (PM2.5-0.3) and toxicological effects in human bronchial epithelial cells (BEAS-2B)

While the evidence for the health adverse effects of air pollution Particulate Matter (PM) has been growing, there is still uncertainty as to which constituents within PM are most harmful. Hence, to contribute to fulfill this gap of knowledge, some physicochemical characteristics and toxicological endpoints (i.e. cytotoxicity, oxidative damage, cytokine secretion) of PM2.5-0.3 samples produced during two different seasons (i.e. spring/summer or autumn/winter) in three different surroundings (i.e. rural, urban, or industrial) were studied, thereby expecting to differentiate their respective adverse effects in human bronchial epithelial cells (BEAS-2B). Physicochemical characteristics were closely related to respective origins and seasons of the six PM2.5-0.3 samples, highlighting the respective contributions of industrial and heavy motor vehicle traffic sources. Space- and season-dependent differences in cytotoxicity of the six PM2.5-0.3 samples could only be supported by considering both the physicochemical properties and the variance in air PM concentrations. Whatever spaces and seasons, dose- and even time-dependent increases in oxidative damage and cytokine secretion were reported in PM2.5-0.3-exposed BEAS-2B cells. However, the relationship between the chemical composition of each of the six PM2.5-0.3 samples and their oxidative or inflammatory potentials seemed to be very complex. These results supported the role of inorganic, ionic and organic components as exogenous source of Reactive Oxygen Species and, thereafter, cytokine secretion. Nevertheless, one of the most striking observation was that some inorganic, ionic and organic chemical components were preferentially associated with early oxidative events whereas others in the later oxidative damage and/or cytokine secretion. Taken together, these results indicated that PM mass concentration alone might not be able to explain the health outcomes, because PM is chemically nonspecific, and supported growing evidence that PM-size, composition and emission source, together with sampling season, interact in a complex manner to produce PM2.5-0.3-induced human adverse health effects.

Short-term effects of particulate matter constituents on daily hospitalizations and mortality in five South-European cities: results from the MED-PARTICLES project

BACKGROUND

Few recent studies examined acute effects on health of individual chemical species in the particulate matter (PM) mixture, and most of them have been conducted in North America. Studies in Southern Europe are scarce. The aim of this study is to examine the relationship between particulate matter constituents and daily hospital admissions and mortality in five cities in Southern Europe.

METHODS

The study included five cities in Southern Europe, three cities in Spain: Barcelona (2003-2010), Madrid (2007-2008) and Huelva (2003-2010); and two cities in Italy: Rome (2005-2007) and Bologna (2011-2013). A case-crossover design was used to link cardiovascular and respiratory hospital admissions and total, cardiovascular and respiratory mortality with a pre-defined list of 16 PM10 and PM2.5 constituents. Lags 0 to 2 were examined. City-specific results were combined by random-effects meta-analysis.

RESULTS

Most of the elements studied, namely EC, SO4(2-), SiO2, Ca, Fe, Zn, Cu, Ti, Mn, V and Ni, showed increased percent changes in cardiovascular and/or respiratory hospitalizations, mainly at lags 0 and 1. The percent increase by one interquartile range (IQR) change ranged from 0.69% to 3.29%. After adjustment for total PM levels, only associations for Mn, Zn and Ni remained significant. For mortality, although positive associations were identified (Fe and Ti for total mortality; EC and Mg for cardiovascular mortality; and NO3(-) for respiratory mortality) the patterns were less clear.

CONCLUSIONS

The associations found in this study reflect that several PM constituents, originating from different sources, may drive previously reported results between PM and hospital admissions in the Mediterranean area.

Air pollution in pristina, influence on cardiovascular hospital morbidity

Introduction:

Numerous studies observed health effects of particulate air pollution. Ambient air quality is particularly bad in Pristina. The principal sources of contaminants are sulfur dioxide (SO2), nitrogen oxides NO and NO2 (NOx), ozone (O3), lead (Pb), carbon dioxide (CO2), particulate matter (PM or dust).

Objective:

to investigate effects of concentrations of pollutants in ambient air on hospital admissions for cardiovascular disease in UCCK- Pristina.

Methods:

Retrospective ecological study. During the three year analytical research predict the potential benefit of decreasing for concentration of PM _2.5, PM ₁₀ were measured in two station in Pristina. The study population consisted of all hospitalization patient in intern clinic for 2010,2011 and 2012 year. Air pollution measurements will be used by KHMI data for the year of 2010, 2011 and 2012 for the municipality of

Pristina in the measurements point in:

KHMI-MESP which is equipped with automatic analyzer- Air Compact Monitoring System (Version 2.2) recordum MESSTECHNIK GmbH. Statistical data processing will be done with SPSS 17.0 statistical package.

Results:

Based on the results obtained during the study period concentrated PM are higher level than standards value. The results showed that the number of hospital admissions for cardiovascular disease are positively correlated with concentration pollutants. Results show clear seasonal variation in the effects of PM on hospital admissions in Kosovo. The study period was short but the mean daily admissions for cardiovascular illnesses were quite large.

Conclusion:

The main source for air pollution was coal-burned power plant and traffic (old vehicles) in Kosovo.

Short-term effects of fine particulate air pollution on hospital admissions for cardiovascular diseases: a case-crossover study in a tropical city

This study was undertaken to determine whether there was an association between fine particles (PM2.5) levels and hospital admissions for cardiovascular diseases (CVD) in Kaohsiung, Taiwan. Hospital admissions for CVD (including ischemic heart disease [IHD], stroke, congestive heart failure [CHF], and arrhythmias) and ambient air pollution data for Kaohsiung were obtained for the period from 2006-2010. The relative risk of hospital admissions for CVD was estimated using a case-crossover approach, controlling for weather variables, day of the week, seasonality, and long-term time trends. For the single-pollutant model (without adjustment for other pollutants), elevated number of admissions for CVD were significantly associated with higher PM2.5 levels only on cool days (<25°C), with an interquartile range rise associated with a 47% (95% CI = 39-56%), 48% (95% CI = 40-56%), 47% (95% CI = 34-61%), and 51% (95% CI = 34-70%) increase in IHD, stroke, CHF, and arrhythmias admissions, respectively. No significant associations between PM2.5 and hospital admissions for CVD were observed on warm days. In the two-pollutant models, PM2.5 levels remained significant even controlling for sulfur dioxide, nitrogen dioxide, carbon monoxide, or ozone on cool days. This study provides evidence that higher levels of PM2.5 enhance the risk of hospital admissions for CVD in Kaohsiung, Taiwan.

A systematic review of the physical health impacts from non-occupational exposure to wildfire smoke

BACKGROUND

Climate change is likely to increase the threat of wildfires, and little is known about how wildfires affect health in exposed communities. A better understanding of the impacts of the resulting air pollution has important public health implications for the present day and the future.

METHOD

We performed a systematic search to identify peer-reviewed scientific studies published since 1986 regarding impacts of wildfire smoke on health in exposed communities. We reviewed and synthesized the state of science of this issue including methods to estimate exposure, and identified limitations in current research.

RESULTS

We identified 61 epidemiological studies linking wildfire and human health in communities. The U.S. and Australia were the most frequently studied countries (18 studies on the U.S., 15 on Australia). Geographic scales ranged from a single small city (population about 55,000) to the entire globe. Most studies focused on areas close to fire events. Exposure was most commonly assessed with stationary air pollutant monitors (35 of 61 studies). Other methods included using satellite remote sensing and measurements from air samples collected during fires. Most studies compared risk of health outcomes between 1) periods with no fire events and periods during or after fire events, or 2) regions affected by wildfire smoke and unaffected regions. Daily pollution levels during or after wildfire in most studies exceeded U.S. EPA regulations. Levels of PM10, the most frequently studied pollutant, were 1.2 to 10 times higher due to wildfire smoke compared to non-fire periods and/or locations. Respiratory disease was the most frequently studied health condition, and had the most consistent results. Over 90% of these 45 studies reported that wildfire smoke was significantly associated with risk of respiratory morbidity.

CONCLUSION

Exposure measurement is a key challenge in current literature on wildfire and human health. A limitation is the difficulty of estimating pollution specific to wildfires. New methods are needed to separate air pollution levels of wildfires from those from ambient sources, such as transportation. The majority of studies found that wildfire smoke was associated with increased risk of respiratory and cardiovascular diseases. Children, the elderly and those with underlying chronic diseases appear to be susceptible. More studies on mortality and cardiovascular morbidity are needed. Further exploration with new methods could help ascertain the public health impacts of wildfires under climate change and guide mitigation policies.

Fine particulate air pollution and outpatient department visits for headache in Taipei, Taiwan

This study was undertaken to determine whether there was an association between fine particle matter (PM(2.5)) levels and daily outpatient department visits (OPD) for headaches in Taipei, Taiwan. Daily OPD visits for headaches and ambient air pollution data for Taipei were obtained for the period 2006-2011. The relative risk of visits for OPD headaches was estimated using a case-crossover approach, controlling for weather variables, day of the week, seasonality, and long-term time trends. For the single-pollutant model (without adjustment for other pollutants), increased OPD visits for headaches were significantly associated with levels of PM(2.5) both on warm days (>23°C) and cool days (<23°C), with an interquartile range rise associated with a 12% (95% CI = 10-14%) and 3% (95% CI = 1-5%) elevation in OPD visits for headaches, respectively. In the two-pollutant models, PM(2.5) remained significant after inclusion of sulfur dioxide (SO₂) or ozone (O₃) on both warm and cool days. This study provides evidence that higher levels of PM(2.5) increase the risk of OPD visits for headaches in Taipei, Taiwan.

Rat lung response to PM2.5 exposure under different cold stresses

Ambient particulate matters and temperature were reported to have additive effects over the respiratory disease hospital admissions and deaths. The purpose of this study is to discuss the interactive pulmonary toxicities of cold stress and fine particulate matter (PM2.5) exposure by estimating inflammation and oxidative stress responses. 48 Wistar male rats, matched by weight and age, were randomly assigned to six groups, which were treated with cold stress alone (0 °C, 10 °C, and 20 °C (Normal control)) and cold stresses plus PM2.5 exposures respectively. Cold stress alone groups were intratracheal instillation of 0.25 mL normal saline, while cold stress plus PM2.5 exposure groups were intratracheal instillation of 8 mg/0.25 mL PM2.5. These procedures were carried out for three times with an interval of 48 hours for each treatment. All rats were sacrificed after 48 hours of the third treatment. The bronchoalveolar lavage fluid (BALF) was collected for analyzing inflammatory cells and cytokines, and lung homogenate MDA was determined for oxidative stress estimation. Results showed higher level of total cell and neutrophil in the BALF of PM2.5 exposed groups (p < 0.05). Negative relationships between cold stress intensity and the level of tumor necrosis factor alpha (TNF-a), C-reactive protein (CRP) interleukin-6 (IL-6) and interleukin-8 (IL-8) in BALF were indicated in PM2.5 exposure groups. Exposure to cold stress alone caused significant increase of inflammatory cytokines and methane dicarboxylic aldehyde (MDA) and decline of superoxide dismutase (SOD) and glutathione peroxidase (GSH-Px) activity only in 0 °C exposure group (p < 0.05). The two-way ANOVA found significant interactive effects between PM2.5 exposure and cold stress in the level of neutrophil, IL-6 and IL-8 and SOD activity (p < 0.05). These data demonstrated that inflammation and oxidative stress involved in the additive effect of PM2.5 exposure and cold stress on pulmonary toxicity, providing explanation for epidemiological studies on the health effect of ambient PM2.5 and cold stress.

The public health benefits of reducing fine particulate matter through conversion to cleaner heating fuels in New York City

In recent years, both New York State and City issued regulations to reduce emissions from burning heating oil. To assess the benefits of these programs in New York City, where the density of emissions and vulnerable populations vary greatly, we simulated the air quality benefits of scenarios reflecting no action, partial, and complete phase-out of high-sulfur heating fuels using the Community MultiScale Air Quality (CMAQ) model conducted at a high spatial resolution (1 km). We evaluated the premature mortality and morbidity benefits of the scenarios within 42 city neighborhoods and computed benefits by neighborhood poverty status. The complete phase-out scenario reduces annual average fine particulate matter (PM2.5) by an estimated 0.71 μg/m(3) city-wide (average of 1 km estimates, 10-90th percentile: 0.1-1.6 μg/m(3)), avoiding an estimated 290 premature deaths, 180 hospital admissions for respiratory and cardiovascular disease, and 550 emergency department visits for asthma each year. The largest improvements were seen in areas of highest building and population density and the majority of benefits have occurred through the partial phase out of high-sulfur heating fuel already achieved. While emissions reductions were greatest in low-poverty neighborhoods, health benefits are estimated to be greatest in high-poverty neighborhoods due to higher baseline morbidity and mortality rates.

A Bayesian Multivariate Receptor Model for Estimating Source Contributions to Particulate Matter Pollution using National Databases

Time series studies have suggested that air pollution can negatively impact health. These studies have typically focused on the total mass of fine particulate matter air pollution or the individual chemical constituents that contribute to it, and not source-specific contributions to air pollution. Source-specific contribution estimates are useful from a regulatory standpoint by allowing regulators to focus limited resources on reducing emissions from sources that are major contributors to air pollution and are also desired when estimating source-specific health effects. However, researchers often lack direct observations of the emissions at the source level. We propose a Bayesian multivariate receptor model to infer information about source contributions from ambient air pollution measurements. The proposed model incorporates information from national databases containing data on both the composition of source emissions and the amount of emissions from known sources of air pollution. The proposed model is used to perform source apportionment analyses for two distinct locations in the United States (Boston, Massachusetts and Phoenix, Arizona). Our results mirror previous source apportionment analyses that did not utilize the information from national databases and provide additional information about uncertainty that is relevant to the estimation of health effects.

Tree and forest effects on air quality and human health in the United States

Trees remove air pollution by the interception of particulate matter on plant surfaces and the absorption of gaseous pollutants through the leaf stomata. However, the magnitude and value of the effects of trees and forests on air quality and human health across the United States remains unknown. Computer simulations with local environmental data reveal that trees and forests in the conterminous United States removed 17.4 million tonnes (t) of air pollution in 2010 (range: 9.0-23.2 million t), with human health effects valued at 6.8 billion U.S. dollars (range: $1.5-13.0 billion). This pollution removal equated to an average air quality improvement of less than one percent. Most of the pollution removal occurred in rural areas, while most of the health impacts and values were within urban areas. Health impacts included the avoidance of more than 850 incidences of human mortality and 670,000 incidences of acute respiratory symptoms.

Health effects of multi-pollutant profiles

BACKGROUND

The association between exposure to particle mass and mortality is well established; however, there are still uncertainties as to whether certain chemical components are more harmful than others. Moreover, understanding the health effects associated with exposure to pollutant mixtures may lead to new regulatory strategies.

OBJECTIVES

Recently we have introduced a new approach that uses cluster analysis to identify distinct air pollutant mixtures by classifying days into groups based on their pollutant concentration profiles. In Boston during the years 1999-2009, we examined whether the effect of PM2.5 on total mortality differed by distinct pollution mixtures.

METHODS

We applied a time series analysis to examine the association of PM2.5 with daily deaths. Subsequently, we included an interaction term between PM2.5 and the pollution mixture clusters.

RESULTS

We found a 1.1% increase (95% CI: 0.0, 2.2) and 2.3% increase (95% CI: 0.9-3.7) in total mortality for a 10 μg/m(3) increase in the same day and the two-day average of PM2.5 respectively. The association is larger in a cluster characterized by high concentrations of the elements related to primary traffic pollution and oil combustion emissions with a 3.7% increase (95% CI: 0.4, 7.1) in total mortality, per 10 μg/m(3) increase in the same day average of PM2.5.

CONCLUSIONS

Our study shows a higher association of PM2.5 on total mortality during days with a strong contribution of traffic emissions, and fuel oil combustion. Our proposed method to create multi-pollutant profiles is robust, and provides a promising tool to identify multi-pollutant mixtures which can be linked to the health effects.

The Association between Airborne PM2.5 Chemical Constituents and Birth Weight-Implication of Buffer Exposure Assignment

Several papers reported associations between airborne fine particulate matter (PM_2.5) and birth weight, though findings are inconsistent across studies. Conflicting results might be due to (1) different PM_2.5 chemical structure across locations, and (2) various exposure assignment methods across studies even among the studies that use ambient monitors to assess exposure. We investigated associations between birth weight and PM_2.5 chemical constituents, considering issues arising from choice of buffer size (i.e. distance between residence and pollution monitor). We estimated the association between each pollutant and term birth weight applying buffers of 5 to 30km in Connecticut (2000-2006), in the New England region of the U.S. We also investigated the implication of the choice of buffer size in relation to population characteristics, such as socioeconomic status. Results indicate that some PM_2.5 chemical constituents, such as nitrate, are associated with lower birth weight and appear more harmful than other constituents. However, associations vary with buffer size and the implications of different buffer sizes may differ by pollutant. A homogeneous pollutant level within a certain distance is a common assumption in many environmental epidemiology studies, but the validity of this assumption may vary by pollutant. Furthermore, we found that areas close to monitors reflect more minority and lower socio-economic populations, which implies that different exposure approaches may result in different types of study populations. Our findings demonstrate that choosing an exposure method involves key tradeoffs of the impacts of exposure misclassification, sample size, and population characteristics.

The Association between Airborne PM2.5 Chemical Constituents and Birth Weight-Implication of Buffer Exposure Assignment

Several papers reported associations between airborne fine particulate matter (PM_2.5) and birth weight, though findings are inconsistent across studies. Conflicting results might be due to (1) different PM_2.5 chemical structure across locations, and (2) various exposure assignment methods across studies even among the studies that use ambient monitors to assess exposure. We investigated associations between birth weight and PM_2.5 chemical constituents, considering issues arising from choice of buffer size (i.e. distance between residence and pollution monitor). We estimated the association between each pollutant and term birth weight applying buffers of 5 to 30km in Connecticut (2000-2006), in the New England region of the U.S. We also investigated the implication of the choice of buffer size in relation to population characteristics, such as socioeconomic status. Results indicate that some PM_2.5 chemical constituents, such as nitrate, are associated with lower birth weight and appear more harmful than other constituents. However, associations vary with buffer size and the implications of different buffer sizes may differ by pollutant. A homogeneous pollutant level within a certain distance is a common assumption in many environmental epidemiology studies, but the validity of this assumption may vary by pollutant. Furthermore, we found that areas close to monitors reflect more minority and lower socio-economic populations, which implies that different exposure approaches may result in different types of study populations. Our findings demonstrate that choosing an exposure method involves key tradeoffs of the impacts of exposure misclassification, sample size, and population characteristics.

Nuclear magnetic resonance spectroscopy for determining the functional content of organic aerosols: a review

The knowledge deficit of organic aerosol (OA) composition has been identified as the most important factor limiting our understanding of the atmospheric fate and implications of aerosol. The efforts to chemically characterize OA include the increasing utilization of nuclear magnetic resonance spectroscopy (NMR). Since 1998, the functional composition of different types, sizes and fractions of OA has been studied with one-dimensional, two-dimensional and solid state proton and carbon-13 NMR. This led to the use of functional group ratios to reconcile the most important sources of OA, including secondary organic aerosol and initial source apportionment using positive matrix factorization. Future research efforts may be directed towards the optimization of experimental parameters, detailed NMR experiments and analysis by pattern recognition methods to identify the chemical components, determination of the NMR fingerprints of OA sources and solid state NMR to study the content of OA as a whole.

Associations of fine particulate matter species with mortality in the United States: a multicity time-series analysis

BACKGROUND

Epidemiological studies have examined the association between PM2.5 and mortality, but uncertainty remains about the seasonal variations in PM2.5-related effects and the relative importance of species.

OBJECTIVES

We estimated the effects of PM2.5 species on mortality and how infiltration rates may modify the association.

METHODS

Using city-season specific Poisson regression, we estimated PM2.5 effects on approximately 4.5 million deaths for all causes, cardiovascular disease (CVD), myocardial infarction (MI), stroke, and respiratory diseases in 75 U.S. cities for 2000-2006. We added interaction terms between PM2.5 and monthly average species-to-PM2.5 proportions of individual species to determine the relative toxicity of each species. We combined results across cities using multivariate meta-regression, and controlled for infiltration.

RESULTS

We estimated a 1.18% (95% CI: 0.93, 1.44%) increase in all-cause mortality, a 1.03% (95% CI: 0.65, 1.41%) increase in CVD, a 1.22% (95% CI: 0.62, 1.82%) increase in MI, a 1.76% (95% CI: 1.01, 2.52%) increase in stroke, and a 1.71% (95% CI: 1.06, 2.35%) increase in respiratory deaths in association with a 10-μg/m3 increase in 2-day averaged PM2.5 concentration. The associations were largest in the spring. Silicon, calcium, and sulfur were associated with more all-cause mortality, whereas sulfur was related to more respiratory deaths. County-level smoking and alcohol were associated with larger estimated PM2.5 effects.

CONCLUSIONS

Our study showed an increased risk of mortality associated with PM2.5, which varied with seasons and species. The results suggest that mass alone might not be sufficient to evaluate the health effects of particles.

Spatial and temporal variation in fine particulate matter mass and chemical composition: the Middle East Consortium for Aerosol Research Study

Ambient fine particulate matter (PM_2.5) samples were collected from January to December 2007 to investigate the sources and chemical speciation in Palestine, Jordan, and Israel. The 24-h PM_2.5 samples were collected on 6-day intervals at eleven urban and rural sites simultaneously. Major chemical components including metals, ions, and organic and elemental carbon were analyzed. The mass concentrations of PM_2.5 across the 11 sites varied from 20.6 to 40.3 μg/m³, with an average of 28.7 μg/m³. Seasonal variation of PM_2.5 concentrations was substantial, with higher average concentrations (37.3 μg/m³) in the summer (April–June) months compared to winter (October–December) months (26.0 μg/m³) due mainly to high contributions of sulfate and crustal components. PM_2.5 concentrations in the spring were greatly impacted by regional dust storms. Carbonaceous mass was the most abundant component, contributing 40% to the total PM_2.5 mass averaged across the eleven sites. Crustal components averaged 19.1% of the PM_2.5 mass and sulfate, ammonium, and nitrate accounted for 16.2%, 6.4%, and 3.7%, respectively, of the total PM_2.5 mass. The results of this study demonstrate the need to better protect the health and welfare of the residents on both sides of the Jordan River in the Middle East.