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     

Characterizing the PM2.5-related health benefits of emission reductions for 17 industrial,area and mobile emission sectors across the U.S.

BackgroundAir pollution benefits assessments tend to be time and resource intensive. Reduced-form approaches offer computational efficiency, but may introduce uncertainty. Some reduced-form approaches apply simplified air quality models, which may not capture the complex non-linear chemistry governing the formation of certain pollutants such as PM_2.5. Other approaches apply the results of sophisticated photochemical modeling, but characterize only a small number of source types in a limited geographic area.MethodsWe apply CAMx source apportionment photochemical modeling, coupled with a PC-based human health benefits software program, to develop a suite of PM_2.5 benefit per ton estimates. These per-ton estimates relate emission changes to health impacts and monetized benefits for 17 sectors across the continental U.S., including Electricity Generating Units (EGU), mobile, area and industrial point sources.ResultsThe benefit per ton of reducing directly emitted PM_2.5 is about an order of magnitude larger than reducing emissions of PM_2.5 precursor emissions. On a per-ton basis, the value of reducing directly emitted PM_2.5 and PM_2.5 precursors in 2005 ranges between approximately $1300 (2010$) for reducing a ton of NO_x from Ocean-Going Vessels to about $450,000 (2010$) for reducing a ton of directly emitted PM_2.5 from Iron and Steel facilities. The benefit per ton estimates for 2016 are generally higher than the 2005 estimates. The values estimated here are generally comparable with those generated using photochemical modeling, but larger than those calculated using simplified air quality models.ConclusionsOur approach characterizes well the per-ton benefits of reducing emissions from a broad array of 17 industrial point, EGU and mobile sectors, while our use of photochemical air quality modeling gives us greater confidence that we have accounted for the non-linear chemistry governing PM_2.5 formation. The resulting benefit per-ton estimates thus represent a compromise between approaches that may simplify the treatment of PM_2.5 air quality formation and those techniques that are based in photochemical modeling but account for only a small number of emission sources.     

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.     

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.     

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.     

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.     

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.     

Long-term trend and spatial pattern of PM2.5 induced premature mortality in China

With rapid economic growth, China has witnessed increasingly frequent and severe haze and smog episodes over the past decade, posing serious health impacts to the Chinese population, especially those in densely populated city clusters. Quantification of the spatial and temporal variation of health impacts attributable to ambient fine particulate matter (PM_2.5) has important implications for China's policies on air pollution control. In this study, we evaluated the spatial distribution of premature deaths in China between 2000 and 2010 attributable to ambient PM_2.5 in accord with the Global Burden of Disease based on a high resolution population density map of China, satellite retrieved PM_2.5 concentrations, and provincial health data. Our results suggest that China's anthropogenic ambient PM_2.5 led to 1,255,400 premature deaths in 2010, 42% higher than the level in 2000. Besides increased PM_2.5 concentration, rapid urbanization has attracted large population migration into the more developed eastern coastal urban areas, intensifying the overall health impact. In addition, our analysis implies that health burdens were exacerbated in some developing inner provinces with high population density (e.g. Henan, Anhui, Sichuan) because of the relocation of more polluting and resource-intensive industries into these regions. In order to avoid such national level environmental inequities, China's regulations on PM_2.5 should not be loosened in inner provinces. Furthermore policies should create incentive mechanisms that can promote transfer of advanced production and emissions control technologies from the coastal regions to the interior regions.     

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

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

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.     

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.     

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.     

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.     

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.     

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.     

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

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

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.     

Exposure to emissions from municipal solid waste incinerators and miscarriages: A multisite study of the MONITER Project

BackgroundMiscarriages are an important indicator of reproductive health but only few studies have analyzed their association with exposure to emissions from municipal solid waste incinerators.This study analyzed the occurrence of miscarriages in women aged 15–49 years residing near seven incinerators of the Emilia-Romagna Region (Northern Italy) in the period 2002–2006.MethodsWe considered all pregnancies occurring in women residing during the first trimester of pregnancy within a 4 km radius of each incinerator. Addresses were geocoded and exposures were characterized by a dispersion model (ADMS Urban model) producing pollution maps for incinerators based on PM₁₀ stack measurements and for other pollution sources based on NO_x ground measurements. Information on pregnancies and their outcomes was obtained from the Hospital Discharge Database. Simplified True Abortion Risks (STAR) × 100 estimated pregnancies were calculated. We ran logistic regressions adjusting for maternal characteristics, exposure to other sources of pollution, and sites, considering the whole population and stratifying by miscarriage history.ResultsThe study analyzed 11,875 pregnancies with 1375 miscarriages. After adjusting for confounders, an increase of PM₁₀ due to incinerator emissions was associated with an increased risk of miscarriage (test for trend, p = 0.042). The odds ratio for the highest quartile of exposed versus not exposed women was 1.29, 95% CI 0.97–1.72. The effect was present only for women without previous miscarriages (highest quartile of exposed versus not exposed women 1.44, 95% CI 1.06–1.96; test for trend, p = 0.009).ConclusionExposure to incinerator emissions is associated with an increased risk of miscarriage. This result should be interpreted with those of a previous study on reproductive health conducted in the same area that observed an association between incinerator exposure and preterm births.     

Saharan dust,particulate matter and cause-specific mortality: A case–crossover study in Barcelona (Spain)

BackgroundStudies measuring health effects of Saharan dust based on large particulate matter (PM) fraction groups may be masking some effects. Long distant transport reduces the amount of heavier and larger particles in the Saharan air masses increasing the relative contribution of smaller particles that may be more innocuous. This study investigates the association between different PM fractions and daily mortality during Saharan and non-Saharan days in Barcelona, Spain.MethodsWe collected daily PM₁, PM_2.5–1 and PM_10–2.5 fractions, and cause-specific mortality (cardiovascular, respiratory and cerebrovascular) between March 2003 and December 2007. Changes of effects between Saharan and non-Saharan dust days were assessed using a time-stratified case–crossover design.ResultsDuring non-Saharan dust days we found statistically significant (p < 0.05) effects of PM_10–2.5 for cardiovascular (odds ratio for increase of an interquartile range, OR = 1.033, 95% confidence interval: 1.006–1.060) and respiratory mortality (OR = 1.044, 95% CI: 1.001–1.089). During Saharan dust days strongest cardiovascular effects were found for the same fraction (OR = 1.085, 95% CI: 1.017–1.158) with an indication of effect modification (p = 0.111). Effects of PM_2.5–1 during Saharan dust days were about the double than in non-dust days for cardiovascular and respiratory mortality, but these differences were not statistically significant.ConclusionOur results using independent fractions of PMs provide further evidence that the effects of short-term exposure to PM during Saharan dust days are associated with both cardiovascular and respiratory mortality. A better understanding of which of the different PM size fractions brought by Saharan dust is more likely to accelerate adverse effects may help better understand mechanisms of toxicity.     

Seasonal distribution and modeling of diesel particulate matter in the Southeast US

The fine and ultra fine size of diesel particulate mater (DPM) are of great health concern and significantly contribute to the overall cancer risk. In addition, diesel particles may contribute a warming effect on the planet's climate. The composition of these particles is composed principally of elemental carbon (EC) with adsorbed organic compounds, sulfate, nitrate, ammonia, metals, and other trace elements. The purpose of this study was to depict the seasonality and modeling of particulate matter in the Southeastern US produced by the diesel fueled sources (DFSs). The modeling results came from four one-month cases including March, June, September, and December to represent different seasons in 2003 by linking Models-3/CMAQ and SMOKE. The 1999 National Emissions Inventory Version 3 (NEI99) was used in this analysis for point, area, and non-road sources, whereas the National Mobile Inventory Model (NMIM) was used to create the on-road emissions. Three urban areas, Atlanta, Birmingham, and Nashville were selected to analyze the DPM emissions and concentrations. Even though the model performance was not very strong, it could be considered satisfactory to conduct seasonal distribution analysis for DPM. Important hourly DPM seasonality was observed in each city, of which higher values occurred at the morning traffic rush hours. The EC contributions of primary DPM were similar for all three sites (~ 74%). The results showed that there is no significant daily seasonality of DPM contribution to PM_2.5 for any of these three cities in 2003. The annual DPM contribution to total PM_2.5 for Atlanta, Nashville, and Birmingham were 3.7%, 2.5%, and 2.2%, respectively.