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.     

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 PM(10) and PM(2.5) in Bangkok Metropolitan Region (BMR). Ambient PM(10) 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. PM(10) 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 PM(10) and PM(2.5) concentrations was distinct between dry and wet seasons. Major source of PM(10) at the traffic site indicated that automobile emissions and biomass burning-related sources contributed approximately 33% each. Automobiles contributed approximately 39 and 22% of PM(10) mass at two residential sites while biomass burning contributed about 36 and 28%. PM(10) 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.     

Source apportionment of fine carbonaceous particles by positive matrix factorization at Gosan background site in East Asia

Fine particle (aerodynamic diameter <2.5 microm) samples were collected during six intensive measurement periods from November 2001 to August 2003 at Gosan, Jeju Island, Korea, which is one of the representative background sites in East Asia. Chemical composition of these aerosol samples including major ion components, trace elements, organic and elemental carbon (OC and EC), and particulate polycyclic aromatic hydrocarbons (PAHs) were analyzed to study the impact of long-range transport of anthropogenic aerosol. Aerosol chemical composition data were then analyzed using the positive matrix factorization (PMF) technique in order to identify the possible sources and estimate their contribution to particulate matter mass. Fourteen sources were then resolved including soil dust, fresh sea salt, transformed natural source, ammonium sulfate, ammonium nitrate, secondary organic carbon, diesel vehicle, gasoline vehicle, fuel oil combustion, biomass burning, coal combustion, municipal incineration, metallurgical emission source, and volcanic emission. The PMF analysis results of source contributions showed that the natural sources including soil dust, fresh and aged sea salt, and volcanic emission contributed to about 20% of the measured PM(2.5) mass. Other primary anthropogenic sources such as diesel and gasoline vehicle, coal and fuel oil combustion, biomass burning, municipal incineration, metallurgical source contributed about 34% of PM(2.5) mass. Especially, the secondary aerosol mainly involved with sulfate, nitrate, ammonium, and organic carbon contributed to about 39% of the PM(2.5) mass.     

WATCH

Abstract

The characteristics of fine particulate pollution (PM₁₀ and PM_2.5) were measured at urban and suburban sites in Jinan during the 2008–2009 heating and non-heating seasons. The results showed that PM₁₀ and PM_2.5 pollution was quite serious, and PM mass concentration was higher during the heating season than the non-heating season. PM was the highest in the chemical factory and lowest in the development zone. The mass concentrations of PM₁₀ and PM_2.5 were linearly related, and the mass concentration ratio of PM_2.5/PM₁₀ was up to 0.59 in urban areas. PM pollution in Jinan was related to local meteorological factors: PM_2.5 mass concentration and humidity were positively correlated, and PM_2.5 mass concentration was negatively correlated with both click on the temperature and wind speed, although wind speed varied more.     

Contribution of (222)Rn-bearing water to indoor radon and indoor air quality assessment in hot spring hotels of Guangdong, China

This study investigates the contribution of radon (²²²Rn)-bearing water to indoor ²²²Rn in thermal baths. The ²²²Rn concentrations in air were monitored in the bathroom and the bedroom. Particulate matter (PM, both PM₁₀ and PM_2.5) and carbon dioxide (CO₂) were also monitored with portable analyzers. The bathrooms were supplied with hot spring water containing 66-260 kBq m⁻³ of ²²²Rn. The results show that the spray of hot spring water from the bath spouts is the dominant mechanism by which ²²²Rn is released into the air of the bathroom, and then it diffuses into the bedroom. Average ²²²Rn level was 110-410% higher in the bedrooms and 510-1200% higher in the bathrooms compared to the corresponding average levels when there was no use of hot spring water. The indoor ²²²Rn levels were influenced by the ²²²Rn concentrations in the hot spring water and the bathing times. The average ²²²Rn transfer coefficients from water to air were 6.2 × 10⁻⁴-4.1 × 10⁻³. The 24-h average levels of CO₂ and PM₁₀ in the hotel rooms were 89% and 22% higher than the present Indoor Air Quality (IAQ) standard of China. The main particle pollutant in the hotel rooms was PM_2.5. Radon and PM₁₀ levels in some hotel rooms were at much higher concentrations than guideline levels, and thus the potential health risks to tourists and especially to the hotel workers should be of great concern, and measures should be taken to lower inhalation exposure to these air pollutants.     

Spatial variation of PM elemental composition between and within 20 European study areas — Results of the ESCAPE project

An increasing number of epidemiological studies suggest that adverse health effects of air pollution may be related to particulate matter (PM) composition, particularly trace metals. However, we lack comprehensive data on the spatial distribution of these elements.We measured PM_2.5 and PM₁₀ in twenty study areas across Europe in three seasonal two-week periods over a year using Harvard impactors and standardized protocols. In each area, we selected street (ST), urban (UB) and regional background (RB) sites (totaling 20) to characterize local spatial variability. Elemental composition was determined by energy-dispersive X-ray fluorescence analysis of all PM_2.5 and PM₁₀ filters. We selected a priori eight (Cu, Fe, K, Ni, S, Si, V, Zn) well-detected elements of health interest, which also roughly represented different sources including traffic, industry, ports, and wood burning.PM elemental composition varied greatly across Europe, indicating different regional influences. Average street to urban background ratios ranged from 0.90 (V) to 1.60 (Cu) for PM_2.5 and from 0.93 (V) to 2.28 (Cu) for PM₁₀.Our selected PM elements were variably correlated with the main pollutants (PM_2.5, PM₁₀, PM_2.5 absorbance, NO₂ and NO_x) across Europe: in general, Cu and Fe in all size fractions were highly correlated (Pearson correlations above 0.75); Si and Zn in the coarse fractions were modestly correlated (between 0.5 and 0.75); and the remaining elements in the various size fractions had lower correlations (around 0.5 or below). This variability in correlation demonstrated the distinctly different spatial distributions of most of the elements. Variability of PM₁₀_Cu and Fe was mostly due to within-study area differences (67% and 64% of overall variance, respectively) versus between-study area and exceeded that of most other traffic-related pollutants, including NO₂ and soot, signaling the importance of non-tailpipe (e.g., brake wear) emissions in PM.     

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.     

Distribution of PBDEs in air particles from an electronic waste recycling site compared with Guangzhou and Hong Kong, South China

Air samples of total suspended particles (TSP, particles less than 30-60 microm), and particles with aerodynamic diameter smaller than 2.5 microm (PM(2.5)) were collected simultaneously at Guiyu (an electronic waste recycling site), three urban sites in Hong Kong and two urban sites in Guangzhou, South China from 16 August to 17 September 2004. Twenty-two PBDE congeners (BDE-3, -7, -15, -17, -28, -49, -71, -47, -66, -77, -100, -119, -99, -85, -126, -154, -153, -138, -156, -184, -183, -191) in TSP and PM(2.5) were measured. The results showed that the overall average concentrations of TSP and PM(2.5) collected at Guiyu were 124 and 62.1 microg m(-3), respectively. The monthly concentrations of the sum of 22 BDE congeners contained in TSP and PM(2.5) at Guiyu were 21.5 and 16.6 ng m(-3), with 74.5 and 84.3%, contributed by nine congeners (BDE-28, -47, -66, -100, -99, -154, -153, -183 and -191 respectively). This pattern was similar to Tsuen Wan site of Hong Kong. Two urban sites of Guangzhou had the same congener pattern, but were different from Yuen Long and Hok Tsui sites of Hong Kong. The results also showed that the amount of mono to penta brominated congeners, which are more toxic, accounted for 79.4-95.6% of Sigma(22)PBDEs from all sites. All congeners tested in Guiyu were up to 58-691 times higher than the other urban sites and more than 100 times higher than other studies reported elsewhere. The higher concentration in the air was due to heating or opening burning of electronic waste since PBDEs are formed when plastics containing brominated flame retardants are heated.     

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.     

Economic Valuation of Health Impact of PM10 Pollution in Beijing from 2001 to 2006

Abstract

In light of the practical need for research to inform policy in Beijing, this study evaluates the economic cost of the impact of PM₁₀ pollution in Beijing from 2001 to 2006, taking health as the main impact, and mortality as the main outcome. Based on the literature review, this study adopts relatively conservative parameters as the basis for calculating the health impacts. It concludes that nearly 30% of mortality among registered residents above age 30 in Beijing can be attributed to PM₁₀ pollution, and that the economic cost equals 0.8%–1.2% of the city’s GDP over the same period. This is lower than the results of previous studies, but still high enough to warrant a commitment to solve the city’s air pollution problem.     

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.     

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.     

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

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

A new approach to spatial source apportionment of haze pollution in large scale and its application in China

Long-lasting expansion of haze pollution in China has already presented a stern challenge to regional joint prevention and control. There is an urgent need to enlarge and reconstruct the coverage of joint prevention and control of air pollution in key area. Air quality models can identify and quantify the regional contribution of haze pollution and its key components with the help of numerical simulation, but it is difficult to be applied to larger spatial scale due to the complexity of model parameters. The time series analysis can recognize the existence of spatial interaction of haze pollution between cities, but it has not yet been used to further identify the spatial sources of haze pollution in large scale. Using econometric framework of time series analysis, this paper developed a new approach to perform spatial source apportionment. We applied this approach to calculate the contribution from spatial sources of haze pollution in China, using the monitoring data of particulate matter (PM_2.5) across 161 Chinese cities. This approach overcame the limitation of numerical simulation that the model complexity increases at excess with the expansion of sample range, and could effectively deal with severe large-scale haze episodes.     

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

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

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

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

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.     

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

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

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.     

Association between long-term exposure to air pollution and mortality in France: A 25-year follow-up study

IntroductionLong-term exposure to air pollution (AP) has been shown to have an impact on mortality in numerous countries, but since 2005 no data exists for France.ObjectivesWe analyzed the association between long-term exposure to air pollution and mortality at the individual level in a large French cohort followed from 1989 to 2013.MethodsThe study sample consisted of 20,327 adults working at the French national electricity and gas company EDF-GDF. Annual exposure to PM₁₀, PM_10–2.5, PM_2.5, NO₂, O₃, SO₂, and benzene was assessed for the place of residence of participants using a chemistry-transport model and taking residential history into account. Hazard ratios were estimated using a Cox proportional-hazards regression model, adjusted for selected individual and contextual risk factors. Hazard ratios were computed for an interquartile range (IQR) increase in air pollutant concentrations.ResultsThe cohort recorded 1967 non-accidental deaths. Long-term exposures to baseline PM_2.5, PM_10-25, NO₂ and benzene were associated with an increase in non-accidental mortality (Hazard Ratio, HR = 1.09; 95% CI: 0.99, 1.20 per 5.9 μg/m³, PM_10-25; HR = 1.09;95% CI: 1.04, 1.15 per 2.2 μg/m³, NO₂: HR = 1.14; 95% CI: 0.99, 1.31 per 19.3 μg/m³ and benzene: HR = 1.10; 95% CI: 1.00, 1.22 per 1.7 μg/m³).The strongest association was found for PM₁₀: HR = 1.14; 95% CI: 1.05, 1.25 per 7.8 μg/m³. PM₁₀, PM_10-25 and SO₂ were associated with non-accidental mortality when using time varying exposure. No significant associations were observed between air pollution and cardiovascular and respiratory mortality.ConclusionLong-term exposure to fine particles, nitrogen dioxide, sulfur dioxide and benzene is associated with an increased risk of non-accidental mortality in France. Our results strengthen existing evidence that outdoor air pollution is a significant environmental risk factor for mortality. Due to the limited sample size and the nature of our study (occupational), further investigations are needed in France with a larger representative population sample.