981 resultados para FINE PARTICULATE MATTER


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Objective. To investigate the short-term effects of exposure to particulate matter from biomass burning in the Amazon on the daily demand for outpatient care due to respiratory diseases in children and the elderly. Methods. Epidemiologic study with ecologic time series design. Daily consultation records were obtained from the 14 primary health care clinics in the municipality of Alta Floresta, state of Mato Grosso, in the southern region of the Brazilian Amazon, between January 2004 and December 2005. Information on the daily levels of fine particulate matter was made available by the Brazilian National Institute for Spatial Research. To control for confounding factors ( situations in which a non-causal association between exposure and disease is observed due to a third variable), variables related to time trends, seasonality, temperature, relative humidity, rainfall, and calendar effects ( such as occurrence of holidays and weekends) were included in the model. Poisson regression with generalized additive models was used. Results. A 10 mu g/m(3) increase in the level of exposure to particulate matter was associated with increases of 2.9% and 2.6% in outpatient consultations due to respiratory diseases in children on the 6th and 7th days following exposure. Significant associations were not observed for elderly individuals. Conclusions. The results suggest that the levels of particulate matter from biomass burning in the Amazon are associated with adverse effects on the respiratory health of children.

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Non-mechanised sugarcane harvesting preceded by burning exposes workers and the people of neighbouring towns to high concentrations of pollutants. This study was aimed to evaluate the respiratory symptoms, lung function and oxidative stress markers in sugarcane workers and the residents of Mendonca, an agricultural town in Brazil, during the non-harvesting and harvesting periods and to assess the population and individual exposures to fine particulate matter (PM2.5). Sugarcane workers and healthy volunteers were evaluated with two respiratory symptom questionnaires, spirometry, urinary 1-hydroxypyrene levels, and the measurement of antioxidant enzymes and plasma malonaldehyde during the non-harvesting and harvesting periods. The environmental assessment was determined from PM2.5 concentration. PM2.5 level increased from 8 mu g/m(3) during the non-harvesting period to 23.5 mu g/m(3) in the town and 61 mu g/m(3) on the plantations during the harvesting period. Wheezing, coughing, sneezing, and breathlessness increased significantly in both groups during the harvesting period, but more markedly in workers. A decrease in lung function and antioxidant enzyme activity was observed in both populations during harvesting; this decrease was greater among the sugarcane workers. The urinary 1-hydroxypyrene levels only increased in the sugarcane workers during the harvesting period. The malonaldehyde levels were elevated in both groups, with a higher increase observed in the workers. This research demonstrates the exposure of sugarcane workers and the inhabitants of a neighbouring town to high PM2.5 concentrations during the sugarcane harvest period. This exposure was higher among the sugarcane workers, as illustrated by both higher PM2.5 concentrations in the sugarcane fields and higher urinary 1-hydroxypyrene levels in the volunteers in this group. The higher incidence of respiratory symptoms, greater decrease in lung function and more marked elevation of oxidative stress markers among the sugarcane workers during the harvest confirms the greater effect magnitude in this population and a dose-dependent relationship between pollution and the observed effects. (C) 2012 Elsevier B.V. All rights reserved.

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We propose a method for diagnosing confounding bias under a model which links a spatially and temporally varying exposure and health outcome. We decompose the association into orthogonal components, corresponding to distinct spatial and temporal scales of variation. If the model fully controls for confounding, the exposure effect estimates should be equal at the different temporal and spatial scales. We show that the overall exposure effect estimate is a weighted average of the scale-specific exposure effect estimates. We use this approach to estimate the association between monthly averages of fine particles (PM2.5) over the preceding 12 months and monthly mortality rates in 113 U.S. counties from 2000-2002. We decompose the association between PM2.5 and mortality into two components: 1) the association between “national trends” in PM2.5 and mortality; and 2) the association between “local trends,” defined as county-specificdeviations from national trends. This second component provides evidence as to whether counties having steeper declines in PM2.5 also have steeper declines in mortality relative to their national trends. We find that the exposure effect estimates are different at these two spatio-temporalscales, which raises concerns about confounding bias. We believe that the association between trends in PM2.5 and mortality at the national scale is more likely to be confounded than is the association between trends in PM2.5 and mortality at the local scale. If the association at the national scale is set aside, there is little evidence of an association between 12-month exposure to PM2.5 and mortality.

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Prospective cohort studies have provided evidence on longer-term mortality risks of fine particulate matter (PM2.5), but due to their complexity and costs, only a few have been conducted. By linking monitoring data to the U.S. Medicare system by county of residence, we developed a retrospective cohort study, the Medicare Air Pollution Cohort Study (MCAPS), comprising over 20 million enrollees in the 250 largest counties during 2000-2002. We estimated log-linear regression models having as outcome the age-specific mortality rate for each county and as the main predictor, the average level for the study period 2000. Area-level covariates were used to adjust for socio-economic status and smoking. We reported results under several degrees of adjustment for spatial confounding and with stratification into by eastern, central and western counties. We estimated that a 10 µg/m3 increase in PM25 is associated with a 7.6% increase in mortality (95% CI: 4.4 to 10.8%). We found a stronger association in the eastern counties than nationally, with no evidence of an association in western counties. When adjusted for spatial confounding, the estimated log-relative risks drop by 50%. We demonstrated the feasibility of using Medicare data to establish cohorts for follow-up for effects of air pollution. Particulate matter (PM) air pollution is a global public health problem (1). In developing countries, levels of airborne particles still reach concentrations at which serious health consequences are well-documented; in developed countries, recent epidemiologic evidence shows continued adverse effects, even though particle levels have declined in the last two decades (2-6). Increased mortality associated with higher levels of PM air pollution has been of particular concern, giving an imperative for stronger protective regulations (7). Evidence on PM and health comes from studies of acute and chronic adverse effects (6). The London Fog of 1952 provides dramatic evidence of the unacceptable short-term risk of extremely high levels of PM air pollution (8-10); multi-site time-series studies of daily mortality show that far lower levels of particles are still associated with short-term risk (5)(11-13). Cohort studies provide complementary evidence on the longer-term risks of PM air pollution, indicating the extent to which exposure reduces life expectancy. The design of these studies involves follow-up of cohorts for mortality over periods of years to decades and an assessment of mortality risk in association with estimated long-term exposure to air pollution (2-4;14-17). Because of the complexity and costs of such studies, only a small number have been conducted. The most rigorously executed, including the Harvard Six Cities Study and the American Cancer Society’s (ACS) Cancer Prevention Study II, have provided generally consistent evidence for an association of long- term exposure to particulate matter air pollution with increased all-cause and cardio-respiratory mortality (2,4,14,15). Results from these studies have been used in risk assessments conducted for setting the U.S. National Ambient Air Quality Standard (NAAQS) for PM and for estimating the global burden of disease attributable to air pollution (18,19). Additional prospective cohort studies are necessary, however, to confirm associations between long-term exposure to PM and mortality, to broaden the populations studied, and to refine estimates by regions across which particle composition varies. Toward this end, we have used data from the U.S. Medicare system, which covers nearly all persons 65 years of age and older in the United States. We linked Medicare mortality data to (particulate matter less than 2.5 µm in aerodynamic diameter) air pollution monitoring data to create a new retrospective cohort study, the Medicare Air Pollution Cohort Study (MCAPS), consisting of 20 million persons from 250 counties and representing about 50% of the US population of elderly living in urban settings. In this paper, we report on the relationship between longer-term exposure to PM2.5 and mortality risk over the period 2000 to 2002 in the MCAPS.

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An investigation was undertaken to determine the chemical characterization of inhalable particulate matter in the Houston area, with special emphasis on source identification and apportionment of outdoor and indoor atmospheric aerosols using multivariate statistical analyses.^ Fine (<2.5 (mu)m) particle aerosol samples were collected by means of dichotomous samplers at two fixed site (Clear Lake and Sunnyside) ambient monitoring stations and one mobile monitoring van in the Houston area during June-October 1981 as part of the Houston Asthma Study. The mobile van allowed particulate sampling to take place both inside and outside of twelve homes.^ The samples collected for 12-h sampling on a 7 AM-7 PM and 7 PM-7 AM (CDT) schedule were analyzed for mass, trace elements, and two anions. Mass was determined gravimetrically. An energy-dispersive X-ray fluorescence (XRF) spectrometer was used for determination of elemental composition. Ion chromatography (IC) was used to determine sulfate and nitrate.^ Average chemical compositions of fine aerosol at each site were presented. Sulfate was found to be the largest single component in the fine fraction mass, comprising approximately 30% of the fine mass outdoors and 12% indoors, respectively.^ Principal components analysis (PCA) was applied to identify sources of aerosols and to assess the role of meteorological factors on the variation in particulate samples. The results suggested that meteorological parameters were not associated with sources of aerosol samples collected at these Houston sites.^ Source factor contributions to fine mass were calculated using a combination of PCA and stepwise multivariate regression analysis. It was found that much of the total fine mass was apparently contributed by sulfate-related aerosols. The average contributions to the fine mass coming from the sulfate-related aerosols were 56% of the Houston outdoor ambient fine particulate matter and 26% of the indoor fine particulate matter.^ Characterization of indoor aerosol in residential environments was compared with the results for outdoor aerosols. It was suggested that much of the indoor aerosol may be due to outdoor sources, but there may be important contributions from common indoor sources in the home environment such as smoking and gas cooking. ^

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Particulate matter research is essential because of the well known significant adverse effects of aerosol particles on human health and the environment. In particular, identification of the origin or sources of particulate matter emissions is of paramount importance in assisting efforts to control and reduce air pollution in the atmosphere. This thesis aims to: identify the sources of particulate matter; compare pollution conditions at urban, rural and roadside receptor sites; combine information about the sources with meteorological conditions at the sites to locate the emission sources; compare sources based on particle size or mass; and ultimately, provide the basis for control and reduction in particulate matter concentrations in the atmosphere. To achieve these objectives, data was obtained from assorted local and international receptor sites over long sampling periods. The samples were analysed using Ion Beam Analysis and Scanning Mobility Particle Sizer methods to measure the particle mass with chemical composition and the particle size distribution, respectively. Advanced data analysis techniques were employed to derive information from large, complex data sets. Multi-Criteria Decision Making (MCDM), a ranking method, drew on data variability to examine the overall trends, and provided the rank ordering of the sites and years that sampling was conducted. Coupled with the receptor model Positive Matrix Factorisation (PMF), the pollution emission sources were identified and meaningful information pertinent to the prioritisation of control and reduction strategies was obtained. This thesis is presented in the thesis by publication format. It includes four refereed papers which together demonstrate a novel combination of data analysis techniques that enabled particulate matter sources to be identified and sampling site/year ranked. The strength of this source identification process was corroborated when the analysis procedure was expanded to encompass multiple receptor sites. Initially applied to identify the contributing sources at roadside and suburban sites in Brisbane, the technique was subsequently applied to three receptor sites (roadside, urban and rural) located in Hong Kong. The comparable results from these international and national sites over several sampling periods indicated similarities in source contributions between receptor site-types, irrespective of global location and suggested the need to apply these methods to air pollution investigations worldwide. Furthermore, an investigation into particle size distribution data was conducted to deduce the sources of aerosol emissions based on particle size and elemental composition. Considering the adverse effects on human health caused by small-sized particles, knowledge of particle size distribution and their elemental composition provides a different perspective on the pollution problem. This thesis clearly illustrates that the application of an innovative combination of advanced data interpretation methods to identify particulate matter sources and rank sampling sites/years provides the basis for the prioritisation of future air pollution control measures. Moreover, this study contributes significantly to knowledge based on chemical composition of airborne particulate matter in Brisbane, Australia and on the identity and plausible locations of the contributing sources. Such novel source apportionment and ranking procedures are ultimately applicable to environmental investigations worldwide.

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Recent epidemiological studies have shown a consistent association of the mass concentration of urban air thoracic (PM10) and fine (PM2.5) particles with mortality and morbidity among cardiorespiratory patients. However, the chemical characteristics of different particulate size ranges and the biological mechanisms responsible for these adverse health effects are not well known. The principal aims of this thesis were to validate a high volume cascade impactor (HVCI) for the collection of particulate matter for physicochemical and toxicological studies, and to make an in-depth chemical and source characterisation of samples collected during different pollution situations. The particulate samples were collected with the HVCI, virtual impactors and a Berner low pressure impactor in six European cities: Helsinki, Duisburg, Prague, Amsterdam, Barcelona and Athens. The samples were analysed for particle mass, common ions, total and water-soluble elements as well as elemental and organic carbon. Laboratory calibration and field comparisons indicated that the HVCI can provide a unique large capacity, high efficiency sampling of size-segregated aerosol particles. The cutoff sizes of the recommended HVCI configuration were 2.4, 0.9 and 0.2 μm. The HVCI mass concentrations were in a good agreement with the reference methods, but the chemical composition of especially the fine particulate samples showed some differences. This implies that the chemical characterization of the exposure variable in toxicological studies needs to be done from the same HVCI samples as used in cell and animal studies. The data from parallel, low volume reference samplers provide valuable additional information for chemical mass closure and source assessment. The major components of PM2.5 in the virtual impactor samples were carbonaceous compounds, secondary inorganic ions and sea salt, whereas those of coarse particles (PM2.5-10) were soil-derived compounds, carbonaceous compounds, sea salt and nitrate. The major and minor components together accounted for 77-106% and 77-96% of the gravimetrically-measured masses of fine and coarse particles, respectively. Relatively large differences between sampling campaigns were observed in the organic carbon content of the PM2.5 samples as well as the mineral composition of the PM2.5-10 samples. A source assessment based on chemical tracers suggested clear differences in the dominant sources (e.g. traffic, residential heating with solid fuels, metal industry plants, regional or long-range transport) between the sampling campaigns. In summary, the field campaigns exhibited different profiles with regard to particulate sources, size distribution and chemical composition, thus, providing a highly useful setup for toxicological studies on the size-segregated HVCI samples.

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In this paper, source apportionment techniques are employed to identify and quantify the major particle pollution source classes affecting a monitoring site in metropolitan Boston, MA. A Principal Component Analysis (PCA) of paniculate elemental data allows the estimation of mass contributions for five fine mass panicle source classes (soil, motor vehicle, coal related, oil and salt aerosols), and six coarse panicle source classes (soil, motor vehicle, refuse incineration, residual oil, salt and sulfate aerosols). Also derived are the elemental characteristics of those source aerosols and their contributions to the total recorded elemental concentrations (i.e. an elemental mass balance). These are estimated by applying a new approach to apportioning mass among various PCA source components: the calculation of Absolute Principal Component Scores, and the subsequent regression of daily mass and elemental concentrations on these scores.

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Suspended particulate matter (SPM) measurements obtained along a cross-section in the central English Channel (Wight-Cotentin transect) indicate that the area may be differentiated into: (1) an English coastal zone, associated with the highest concentrations; (2) a French coastal zone, with intermediate concentrations; and (3) the offshore waters of the Channel, characterised by a very low suspended-sediment load. The SPM particle-size distribution was modal close to the English coast (main mode 10-12 mu m); the remainder of the area was characterised by flat SPM distributions. Examination of the diatom communities in the SPM suggest:; that material resuspended in the intertidal zone and the estuarine environments was advected towards the offshore waters of the English Channel. Considerable variations in SPM concentrations occurred during a tidal cycle: maximum concentrations were sometimes up to 3 times higher than the minimum concentrations, Empirical orthogonal function (EOF) analysis of the SPM concentration time series indicates that, although the bottom waters were more turbid than the surficial waters, this was not likely to be the result of in situ sediment resuspension. Instead, the observed variations appear to be controlled mainly by advective mechanisms. The limited resuspension was probably caused by: (1) the limited availability of fine-grained material within the bottom sediments, and (2) 'bed-armouring' processes which protect the finer-grained fractions of the seabed material from erosion and entrainment within the overlying flow during the less energetic stages of the tide.

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Hospitals are considered as a special and important type of indoor public place where air quality has significant impacts on potential health outcomes. Information on indoor air quality of these environments, concerning exposures to particulate matter (PM) and related toxicity, is limited though. This work aims to evaluate risks associated with inhalation exposure to ten toxic metals and chlorine (As, Ni, Cr, Cd, Pb, Mn, Se, Ba, Al, Si, and Cl) in coarse (PM2.5–10) and fine (PM2.5) particles in a Portuguese hospital in comparison with studies representative of other countries. Samples were collected during 1 month in one urban hospital; elemental PM characterization was determined by proton-induced X-ray emission. Noncarcinogenic and carcinogenic risks were assessed according to the methodology provided by the United States Environmental Protection Agency (USEPA; Region III Risk-Based Concentration Table) for three different age categories of hospital personnel (adults, >20, and <65 years) and patients (considering nine different age groups, i.e., children of 1–3 years to seniors of >65 years). The estimated noncarcinogenic risks due to occupational inhalation exposure to PM2.5-bound metals ranged from 5.88×10−6 for Se (adults, 55–64 years) to 9.35×10−1 for As (adults, 20–24 years) with total noncarcinogenic risks (sum of all metals) above the safe level for all three age categories. As and Cl (the latter due to its high abundances) were the most important contributors (approximately 90 %) to noncarcinogenic risks. For PM2.5–10, noncarcinogenic risks of all metals were acceptable to all age groups. Concerning carcinogenic risks, for Ni and Pb, they were negligible (<1×10−6) in both PM fractions for all age groups of hospital personnel; potential risks were observed for As and Cr with values in PM2.5 exceeding (up to 62 and 5 times, respectively) USEPA guideline across all age groups; for PM2.5–10, increased excess risks of As and Cr were observed particularly for long-term exposures (adults, 55–64 years). Total carcinogenic risks highly (up to 67 times) exceeded the recommended level for all age groups, thus clearly showing that occupational exposure to metals in fine particles pose significant risks. If the extensive working hours of hospital medical staff were considered, the respective noncarcinogenic and carcinogenic risks were increased, the latter for PM2.5 exceeding the USEPA cumulative guideline of 10−4. For adult patients, the estimated noncarcinogenic and carcinogenic risks were approximately three times higher than for personnel, with particular concerns observed for children and adolescents.

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In the metropolitan area of Sao Paulo, Brazil, ozone and particulate matter ( PM) are the air pollutants that pose the greatest threat to air quality, since the PM and the ozone precursors ( nitrogen oxides and volatile organic compounds) are the main source of air pollution from vehicular emissions. Vehicular emissions can be measured inside road tunnels, and those measurements can provide information about emission factors of in-use vehicles. Emission factors are used to estimate vehicular emissions and are described as the amount of species emitted per vehicle distance driven or per volume of fuel consumed. This study presents emission factor data for fine particles, coarse particles, inhalable particulate matter and black carbon, as well as size distribution data for inhalable particulate matter, as measured in March and May of 2004, respectively, in the Janio Quadros and Maria Maluf road tunnels, both located in Sao Paulo. The Janio Quadros tunnel carries mainly light-duty vehicles, whereas the Maria Maluf tunnel carries light-duty and heavy-duty vehicles. In the Janio Quadros tunnel, the estimated light-duty vehicle emission factors for the trace elements copper and bromine were 261 and 220 mu g km(-1), respectively, and 16, 197, 127 and 92 mg km(-1), respectively, for black carbon, inhalable particulate matter, coarse particles and fine particles. The mean contribution of heavy-duty vehicles to the emissions of black carbon, inhalable particulate matter, coarse particles and fine particles was, respectively 29, 4, 6 and 6 times higher than that of light-duty vehicles. The inhalable particulate matter emission factor for heavy-duty vehicles was 1.2 times higher than that found during dynamometer testing. In general, the particle emissions in Sao Paulo tunnels are higher than those found in other cities of the world.

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In the present study Tradescantia pallida micronucleus (Trad-MCN) bioassay was used to assess the genotoxicity of particulate matter with a mass median aerodynamic diameter less than 10 pm (PM(10)) in Tangara da Serra (MT), a Brazilian Amazon region that suffers the impact of biomass burning. The levels of PM (coarse and fine size fractions) and black carbon (BC) collected were also measured. Furthermore, the alkanes and polycyclic aromatic hydrocarbons (PAHs) were identified and quantified in the samples taken during the burning period by gas chromatography with flame ionization detection (GC-FID). The PM and BC results for both fractions indicate a strong correlation (p < 0.001). The analysis of alkanes indicates an anthropic influence. Retene was the most abundant PAH found, an indicator of biomass burning, and 12 other PAHs considered to be potentially mutagenic and/or carcinogenic were identified in this sample. The Trad-MCN bioassay showed a significant increase in micronucleus frequency during the period of most intense burning, possibly related to the mutagenic PAHs that were found in such extracts. This study demonstrated that Trad-MCN was sensitive and efficient in evaluating the genotoxicity of organic compounds from biomass burning. It further emphasizes the importance of performing chemical analysis, because changes in chemical composition generally have a negative effect on many living organisms. This bioassay (ex situ), using T. pallida with chemical analysis, is thus recommended for characterizing the genotoxicity of air pollution. Crown Copyright (C) 2011 Published by Elsevier Inc. All rights reserved.

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We present the first results of a study investigating the processes that control concentrations and sources of Pb and particulate matter in the atmosphere of Sao Paulo City Brazil Aerosols were collected with high temporal resolution (3 hours) during a four-day period in July 2005 The highest Pb concentrations measured coincided with large fireworks during celebration events and associated to high traffic occurrence Our high-resolution data highlights the impact that a singular transient event can have on air quality even in a megacity Under meteorological conditions non-conducive to pollutant dispersion Pb and particulate matter concentrations accumulated during the night leading to the highest concentrations in aerosols collected early in the morning of the following day The stable isotopes of Pb suggest that emissions from traffic remain an Important source of Pb in Sao Paulo City due to the large traffic fleet despite low Pb concentrations in fuels (C) 2010 Elsevier BV All rights reserved