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.     

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

BackgroundEpidemiological 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.ObjectivesTo 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.MethodsIn 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 < 10 μm (PM₁₀) and < 2.5 μm (PM_2.5) 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.ResultsA 5 ng/m³ increase in PM_2.5 copper and a 500 ng/m³ 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 10 ng/m³ increase in PM_2.5 zinc was associated with a 1.2% [0.1; 2.4%] increase in fibrinogen; confidence intervals widened when additionally adjusting for PM_2.5.ConclusionsLong-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.     

Seasonal variation in outdoor,indoor, and personal air pollution exposures of women using wood stoves in the Tibetan Plateau: Baseline assessment for an energy intervention study

Cooking and heating with coal and biomass is the main source of household air pollution in China and a leading contributor to disease burden. As part of a baseline assessment for a household energy intervention program, we enrolled 205 adult women cooking with biomass fuels in Sichuan, China and measured their 48-h personal exposure to fine particulate matter (PM_2.5) and carbon monoxide (CO) in winter and summer. We also measured the indoor 48-h PM_2.5 concentrations in their homes and conducted outdoor PM_2.5 measurements during 101 (74) days in summer (winter). Indoor concentrations of CO and nitrogen oxides (NO, NO₂) were measured over 48-h in a subset of ~ 80 homes. Women's geometric mean 48-h exposure to PM_2.5 was 80 μg/m³ (95% CI: 74, 87) in summer and twice as high in winter (169 μg/m³ (95% CI: 150, 190), with similar seasonal trends for indoor PM_2.5 concentrations (winter: 252 μg/m³; 95% CI: 215, 295; summer: 101 μg/m³; 95% CI: 91, 112). We found a moderately strong relationship between indoor PM_2.5 and CO (r = 0.60, 95% CI: 0.46, 0.72), and a weak correlation between personal PM_2.5 and CO (r = 0.41, 95% CI: − 0.02, 0.71). NO₂/NO ratios were higher in summer (range: 0.01 to 0.68) than in winter (range: 0 to 0.11), suggesting outdoor formation of NO₂ via reaction of NO with ozone is a more important source of NO₂ than biomass combustion indoors. The predictors of women's personal exposure to PM_2.5 differed by season. In winter, our results show that primary heating with a low-polluting fuel (i.e., electric stove or wood-charcoal) and more frequent kitchen ventilation could reduce personal PM_2.5 exposures. In summer, primary use of a gaseous fuel or electricity for cooking and reducing exposure to outdoor PM_2.5 would likely have the greatest impacts on personal PM_2.5 exposure.     

The contributions to long-term health-relevant particulate matter at the UK EMEP supersites between 2010 and 2013: Quantifying the mitigation challenge

Human health burdens associated with long-term exposure to particulate matter (PM) are substantial. The metrics currently recommended by the World Health Organization for quantification of long-term health-relevant PM are the annual average PM₁₀ and PM_2.5 mass concentrations, with no low concentration threshold. However, within an annual average, there is substantial variation in the composition of PM associated with different sources. To inform effective mitigation strategies, therefore, it is necessary to quantify the conditions that contribute to annual average PM₁₀ and PM_2.5 (rather than just short-term episodic concentrations). PM₁₀, PM_2.5, and speciated water-soluble inorganic, carbonaceous, heavy metal and polycyclic aromatic hydrocarbon components are concurrently measured at the two UK European Monitoring and Evaluation Programme (EMEP) ‘supersites’ at Harwell (SE England) and Auchencorth Moss (SE Scotland). In this work, statistical analyses of these measurements are integrated with air-mass back trajectory data to characterise the ‘chemical climate’ associated with the long-term health-relevant PM metrics at these sites. Specifically, the contributions from different PM concentrations, months, components and geographic regions are detailed. The analyses at these sites provide policy-relevant conclusions on mitigation of (i) long-term health-relevant PM in the spatial domain for which these sites are representative, and (ii) the contribution of regional background PM to long-term health-relevant PM.At Harwell the mean (± 1 sd) 2010–2013 annual average concentrations were PM₁₀ = 16.4 ± 1.4 μg m^− 3 and PM_2.5 = 11.9 ± 1.1 μg m^− 3 and at Auchencorth PM₁₀ = 7.4 ± 0.4 μg m^− 3 and PM_2.5 = 4.1 ± 0.2 μg m^− 3. The chemical climate state at each site showed that frequent, moderate hourly PM₁₀ and PM_2.5 concentrations (defined as approximately 5–15 μg m^− 3 for PM₁₀ and PM_2.5 at Harwell and 5–10 μg m^− 3 for PM₁₀ at Auchencorth) determined the magnitude of annual average PM₁₀ and PM_2.5 to a greater extent than the relatively infrequent high, episodic PM₁₀ and PM_2.5 concentrations. These moderate PM₁₀ and PM_2.5 concentrations were derived across the range of chemical components, seasons and air-mass pathways, in contrast to the highest PM concentrations which tended to associate with specific conditions. For example, the largest contribution to moderate PM₁₀ and PM_2.5 concentrations – the secondary inorganic aerosol components, specifically NO₃⁻ – were accumulated during the arrival of trajectories traversing the spectrum of marine, UK, and continental Europe areas. Mitigation of the long-term health-relevant PM impact in the regions characterised by these two sites requires multilateral action, across species (and hence source sectors), both nationally and internationally; there is no dominant determinant of the long-term PM metrics to target.     

Status and characteristics of ambient PM2.5 pollution in global megacities

Ambient PM_2.5 pollution is a substantial threat to public health in global megacities. This paper reviews the PM_2.5 pollution of 45 global megacities in 2013, based on mass concentration from official monitoring networks and composition data reported in the literature. The results showed that the five most polluted megacities were Delhi, Cairo, Xi'an, Tianjin and Chengdu, all of which had an annual average concentration of PM_2.5 greater than 89 μg/m³. The five cleanest megacities were Miami, Toronto, New York, Madrid and Philadelphia, the annual averages of which were less than 10 μg/m³. Spatial distribution indicated that the highly polluted megacities are concentrated in east-central China and the Indo-Gangetic Plain. Organic matter and SNA (sum of sulfate, nitrate and ammonium) contributed 30% and 36%, respectively, of the average PM_2.5 mass for all megacities. Notable seasonal variation of PM_2.5 polluted days was observed, especially for the polluted megacities of China and India, resulting in frequent heavy pollution episodes occurring during more polluted seasons such as winter. Marked differences in PM_2.5 pollution between developing and developed megacities require more effort on local emissions reduction as well as global cooperation to address the PM_2.5 pollution of those megacities mainly in Asia.     

Characteristics of PM10, PM2.5, CO2 and CO monitored in interiors and platforms of subway train in Seoul, Korea

This study was performed to investigate the concentration of PM₁₀ and PM_2.5 inside trains and platforms on subway lines 1, 2, 4 and 5 in Seoul, KOREA. PM₁₀, PM_2.5, carbon dioxide (CO₂) and carbon monoxide (CO) were monitored using real-time monitoring instruments in the afternoons (between 13:00 and 16:00). The concentrations of PM₁₀ and PM_2.5 inside trains were significantly higher than those measured on platforms and in ambient air reported by the Korea Ministry of Environment (Korea MOE). This study found that PM₁₀ levels inside subway lines 1, 2 and 4 exceeded the Korea indoor air quality (Korea IAQ) standard of 150 μg/m³. The average percentage that exceeded the PM₁₀ standard was 83.3% on line 1, 37.9% on line 2 and 63.1% on line 4, respectively. PM_2.5 concentration ranged from 77.7 μg/m³ to 158.2 μg/m³, which were found to be much higher than the ambient air PM_2.5 standard promulgated by United States Environmental Protection Agency (US-EPA) (24 h arithmetic mean: 65 μg/m³). The reason for interior PM₁₀ and PM_2.5 being higher than those on platforms is due to subway trains in Korea not having mechanical ventilation systems to supply fresh air inside the train. This assumption was supported by the CO₂ concentration results monitored in tube of subway that ranged from 1153 ppm to 3377 ppm. The percentage of PM_2.5 in PM₁₀ was 86.2% on platforms, 81.7% inside trains, 80.2% underground and 90.2% at ground track. These results indicated that fine particles (PM_2.5) accounted for most of PM₁₀ and polluted subway air. GLM statistical analysis indicated that two factors related to monitoring locations (underground and ground or inside trains and on platforms) significantly influence PM₁₀ (p < 0.001, R² = 0.230) and PM_2.5 concentrations (p < 0.001, R² = 0.172). Correlation analysis indicated that PM₁₀, PM_2.5, CO₂ and CO were significantly correlated at p < 0.01 although correlation coefficients were different. The highest coefficient was 0.884 for the relationship between PM₁₀ and PM_2.5.     

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.     

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.     

Annual and diurnal variations of gaseous and particulate pollutants in 31 provincial capital cities based on in situ air quality monitoring data from China National Environmental Monitoring Center

Long-term air quality data with high temporal and spatial resolutions are needed to understand some important processes affecting the air quality and corresponding environmental and health effects. The annual and diurnal variations of each criteria pollutant including PM_2.5 and PM₁₀ (particulate matter with aerodynamic diameter less than 2.5 μm and 10 μm, respectively), CO (carbon monoxide), NO₂ (nitrogen dioxide), SO₂ (sulfur dioxide) and O₃ (ozone) in 31 provincial capital cities between April 2014 and March 2015 were investigated by cluster analysis to evaluate current air pollution situations in China, and the cities were classified as severely, moderately, and slightly polluted cities according to the variations. The concentrations of air pollutants in winter months were significantly higher than those in other months with the exception of O₃, and the cities with the highest CO and SO₂ concentrations were located in northern China. The annual variation of PM_2.5 concentrations in northern cities was bimodal with comparable peaks in October 2014 and January 2015, while that in southern China was unobvious with slightly high PM_2.5 concentrations in winter months. The concentrations of particulate matter and trace gases from primary emissions (SO₂ and CO) and NO₂ were low in the afternoon (~ 16:00), while diurnal variation of O₃ concentrations was opposite to that of other pollutants with the highest values in the afternoon. The most polluted cities were mainly located in North China Plain, while slightly polluted cities mostly focus on southern China and the cities with high altitude such as Lasa. This study provides a basis for the formulation of future urban air pollution control measures in China.     

Cause-specific premature death from ambient PM2.5 exposure in India: Estimate adjusted for baseline mortality

In India, more than a billion population is at risk of exposure to ambient fine particulate matter (PM_2.5) concentration exceeding World Health Organization air quality guideline, posing a serious threat to health. Cause-specific premature death from ambient PM_2.5 exposure is poorly known for India. Here we develop a non-linear power law (NLP) function to estimate the relative risk associated with ambient PM_2.5 exposure using satellite-based PM_2.5 concentration (2001 − 2010) that is bias-corrected against coincident direct measurements. We show that estimate of annual premature death in India is lower by 14.7% (19.2%) using NLP (integrated exposure risk function, IER) for assumption of uniform baseline mortality across India (as considered in the global burden of disease study) relative to the estimate obtained by adjusting for state-specific baseline mortality using GDP as a proxy. 486,100 (811,000) annual premature death in India is estimated using NLP (IER) risk functions after baseline mortality adjustment. 54.5% of premature death estimated using NLP risk function is attributed to chronic obstructive pulmonary disease (COPD), 24.0% to ischemic heart disease (IHD), 18.5% to stroke and the remaining 3.0% to lung cancer (LC). 44,900 (5900–173,300) less premature death is expected annually, if India achieves its present annual air quality target of 40 μg m^− 3. Our results identify the worst affected districts in terms of ambient PM_2.5 exposure and resulting annual premature death and call for initiation of long-term measures through a systematic framework of pollution and health data archive.     

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.     

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.     

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.     

Chronic disease prevalence in women and air pollution — A 30-year longitudinal cohort study

BackgroundAir pollution, such as fine particulate matter (PM_2.5), can increase risk of adverse health events among people with heart disease, diabetes, asthma and chronic obstructive pulmonary disease (COPD) by aggravating these conditions. Identifying the influence of PM_2.5 on prevalence of these conditions may help target interventions to reduce disease morbidity among high-risk populations.ObjectivesThe objective of this study is to measure the association of exposure of PM_2.5 with prevalence risk of various chronic diseases among a longitudinal cohort of women.MethodsWomen from Ontario who enrolled in the Canadian National Breast Screening Study (CNBSS) from 1980 to 1985 (n = 29,549) were linked to provincial health administrative data from April 1, 1992 to March 31, 2013 to determine the prevalence of major chronic disease and conditions (heart disease, diabetes, asthma, COPD, acute myocardial infarction, angina, stroke and cancers). Exposure to PM_2.5 was measured using satellite data collected from January 1, 1998 to December 31, 2006 and assigned to resident postal-code at time of entry into study. Poisson regression models were used to describe the relationship between exposure to ambient PM_2.5 and chronic disease prevalence. Prevalence rate ratios (PRs) were estimated while adjusting for potential confounders: baseline age, smoking, BMI, marital status, education and occupation. Separate models were run for each chronic disease and condition.ResultsCongestive heart failure (PR = 1.31, 95% CI: 1.13, 1.51), diabetes (PR = 1.28, 95% CI: 1.16, 1.41), ischemic heart disease (PR = 1.22, 95% CI: 1.14, 1.30), and stroke (PR = 1.21, 95% CI: 1.09, 1.35) showed over a 20% increase in PRs per 10 μg/m³ increase in PM_2.5 after adjusting for risk factors. Risks were elevated in smokers and those with BMI greater than 30.ConclusionsThis study estimated significant elevated prevalent rate ratios per unit increase in PM_2.5 in nine of the ten chronic diseases studied.     

Associations between ultrafine and fine particles and mortality in five central European cities — Results from the UFIREG study

BackgroundEvidence on health effects of ultrafine particles (UFP) is still limited as they are usually not monitored routinely. The few epidemiological studies on UFP and (cause-specific) mortality so far have reported inconsistent results.ObjectivesThe main objective of the UFIREG project was to investigate the short-term associations between UFP and fine particulate matter (PM) < 2.5 μm (PM_2.5) and daily (cause-specific) mortality in five European Cities. We also examined the effects of PM < 10 μm (PM₁₀) and coarse particles (PM_2.5–10).MethodsUFP (20–100 nm), PM and meteorological data were measured in Dresden and Augsburg (Germany), Prague (Czech Republic), Ljubljana (Slovenia) and Chernivtsi (Ukraine). Daily counts of natural and cardio-respiratory mortality were collected for all five cities. Depending on data availability, the following study periods were chosen: Augsburg and Dresden 2011–2012, Ljubljana and Prague 2012–2013, Chernivtsi 2013–March 2014. The associations between air pollutants and health outcomes were assessed using confounder-adjusted Poisson regression models examining single (lag 0–lag 5) and cumulative lags (lag 0–1, lag 2–5, and lag 0–5). City-specific estimates were pooled using meta-analyses methods.ResultsResults indicated a delayed and prolonged association between UFP and respiratory mortality (9.9% [95%-confidence interval: − 6.3%; 28.8%] increase in association with a 6-day average increase of 2750 particles/cm³ (average interquartile range across all cities)). Cardiovascular mortality increased by 3.0% [− 2.7%; 9.1%] and 4.1% [0.4%; 8.0%] in association with a 12.4 μg/m³ and 4.7 μg/m³ increase in the PM_2.5- and PM_2.5–10-averages of lag 2–5.ConclusionsWe observed positive but not statistically significant associations between prolonged exposures to UFP and respiratory mortality, which were independent of particle mass exposures. Further multi-centre studies are needed investigating several years to produce more precise estimates on health effects of UFP.     

Short-term dynamics of indoor and outdoor endotoxin exposure: Case of Santiago,Chile, 2012

Indoor and outdoor endotoxin in PM_2.5 was measured for the very first time in Santiago, Chile, in spring 2012. Average endotoxin concentrations were 0.099 and 0.094 [EU/m³] for indoor (N = 44) and outdoor (N = 41) samples, respectively; the indoor–outdoor correlation (log-transformed concentrations) was low: R = − 0.06, 95% CI: (− 0.35 to 0.24), likely owing to outdoor spatial variability.A linear regression model explained 68% of variability in outdoor endotoxins, using as predictors elemental carbon (a proxy of traffic emissions), chlorine (a tracer of marine air masses reaching the city) and relative humidity (a modulator of surface emissions of dust, vegetation and garbage debris). In this study, for the first time a potential source contribution function (PSCF) was applied to outdoor endotoxin measurements. Wind trajectory analysis identified upwind agricultural sources as contributors to the short-term, outdoor endotoxin variability. Our results confirm an association between combustion particles from traffic and outdoor endotoxin concentrations.For indoor endotoxins, a predictive model was developed but it only explained 44% of endotoxin variability; the significant predictors were tracers of indoor PM_2.5 dust (Si, Ca), number of external windows and number of hours with internal doors open. Results suggest that short-term indoor endotoxin variability may be driven by household dust/garbage production and handling. This would explain the modest predictive performance of published models that use answers to household surveys as predictors. One feasible alternative is to increase the sampling period so that household features would arise as significant predictors of long-term airborne endotoxin levels.     

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.     

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.     

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.     

Exposure to fine particle matter,nitrogen dioxide and benzene during pregnancy and cognitive and psychomotor developments in children at 15 months of age

BackgroundPrenatal exposure to air pollutants has recently been identified as a potential risk factor for neuropsychological impairment.ObjectivesTo assess whether prenatal exposure to fine particulate matter (PM_2.5), nitrogen dioxide (NO₂) and benzene were associated with impaired development in infants during their second year of life.MethodsRegression analyses, based on 438 mother–child pairs, were performed to estimate the association between mother exposure to air pollutants during pregnancy and neurodevelopment of the child. The average exposure to PM_2.5, NO₂ and benzene over the whole pregnancy was calculated for each woman. During the second year of life, infant neuropsychological development was assessed using the Bayley Scales of Infant Development. Regression analyses were performed to estimate the association between exposure and outcomes, accounting for potential confounders.ResultsWe estimated that a 1 μg/m³ increase during pregnancy in the average levels of PM_2.5 was associated with a − 1.14 point decrease in motor score (90% CI: − 1.75; − 0.53) and that a 1 μg/m³ increase of NO₂ exposure was associated with a − 0.29 point decrease in mental score (90% CI: − 0.47; − 0.11). Benzene did not show any significant association with development. Considering women living closer (≤ 100 m) to metal processing activities, we found that motor scores decreased by − 3.20 (90% CI: − 5.18; − 1.21) for PM_2.5 and − 0.51 (− 0.89; − 0.13) for NO₂, while mental score decreased by − 2.71 (90% CI: − 4.69; − 0.74) for PM_2.5, and − 0.41 (9% CI: − 0.76; − 0.06) for NO₂.ConclusionsOur findings suggest that prenatal residential exposure to PM_2.5 and NO₂ adversely affects infant motor and cognitive developments. This negative effect could be higher in the proximity of metal processing plants.