976 resultados para FINE PARTICULATE MATTER SOURCES


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This paper reports the application of multicriteria decision making techniques, PROMETHEE and GAIA, and receptor models, PCA/APCS and PMF, to data from an air monitoring site located on the campus of Queensland University of Technology in Brisbane, Australia and operated by Queensland Environmental Protection Agency (QEPA). The data consisted of the concentrations of 21 chemical species and meteorological data collected between 1995 and 2003. PROMETHEE/GAIA separated the samples into those collected when leaded and unleaded petrol were used to power vehicles in the region. The number and source profiles of the factors obtained from PCA/APCS and PMF analyses were compared. There are noticeable differences in the outcomes possibly because of the non-negative constraints imposed on the PMF analysis. While PCA/APCS identified 6 sources, PMF reduced the data to 9 factors. Each factor had distinctive compositions that suggested that motor vehicle emissions, controlled burning of forests, secondary sulphate, sea salt and road dust/soil were the most important sources of fine particulate matter at the site. The most plausible locations of the sources were identified by combining the results obtained from the receptor models with meteorological data. The study demonstrated the potential benefits of combining results from multi-criteria decision making analysis with those from receptor models in order to gain insights into information that could enhance the development of air pollution control measures.

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We performed 124 measurements of particulate matter (PM(2.5)) in 95 hospitality venues such as restaurants, bars, cafés, and a disco, which had differing smoking regulations. We evaluated the impact of spatial separation between smoking and non-smoking areas on mean PM(2.5) concentration, taking relevant characteristics of the venue, such as the type of ventilation or the presence of additional PM(2.5) sources, into account. We differentiated five smoking environments: (i) completely smoke-free location, (ii) non-smoking room spatially separated from a smoking room, (iii) non-smoking area with a smoking area located in the same room, (iv) smoking area with a non-smoking area located in the same room, and (v) smoking location which could be either a room where smoking was allowed that was spatially separated from non-smoking room or a hospitality venue without smoking restriction. In these five groups, the geometric mean PM(2.5) levels were (i) 20.4, (ii) 43.9, (iii) 71.9, (iv) 110.4, and (v) 110.3 microg/m(3), respectively. This study showed that even if non-smoking and smoking areas were spatially separated into two rooms, geometric mean PM(2.5) levels in non-smoking rooms were considerably higher than in completely smoke-free hospitality venues. PRACTICAL IMPLICATIONS: PM(2.5) levels are considerably increased in the non-smoking area if smoking is allowed anywhere in the same location. Even locating the smoking area in another room resulted in a more than doubling of the PM(2.5) levels in the non-smoking room compared with venues where smoking was not allowed at all. In practice, spatial separation of rooms where smoking is allowed does not prevent exposure to environmental tobacco smoke in nearby non-smoking areas.

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Recent research highlights the promise of remotely-sensed aerosol optical depth (AOD) as a proxy for ground-level PM2.5. Particular interest lies in the information on spatial heterogeneity potentially provided by AOD, with important application to estimating and monitoring pollution exposure for public health purposes. Given the temporal and spatio-temporal correlations reported between AOD and PM2.5 , it is tempting to interpret the spatial patterns in AOD as reflecting patterns in PM2.5 . Here we find only limited spatial associations of AOD from three satellite retrievals with PM2.5 over the eastern U.S. at the daily and yearly levels in 2004. We then use statistical modeling to show that the patterns in monthly average AOD poorly reflect patterns in PM2.5 because of systematic, spatially-correlated error in AOD as a proxy for PM2.5 . Furthermore, when we include AOD as a predictor of monthly PM2.5 in a statistical prediction model, AOD provides little additional information to improve predictions of PM2.5 when included in a model that already accounts for land use, emission sources, meteorology and regional variability. These results suggest caution in using spatial variation in AOD to stand in for spatial variation in ground-level PM2.5 in epidemiological analyses and indicate that when PM2.5 monitoring is available, careful statistical modeling outperforms the use of AOD.

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A detailed characterization of air quality in the megacity of Paris (France) during two 1-month intensive campaigns and from additional 1-year observations revealed that about 70% of the urban background fine particulate matter (PM) is transported on average into the megacity from upwind regions. This dominant influence of regional sources was confirmed by in situ measurements during short intensive and longer-term campaigns, aerosol optical depth (AOD) measurements from ENVISAT, and modeling results from PMCAMx and CHIMERE chemistry transport models. While advection of sulfate is well documented for other megacities, there was surprisingly high contribution from long-range transport for both nitrate and organic aerosol. The origin of organic PM was investigated by comprehensive analysis of aerosol mass spectrometer (AMS), radiocarbon and tracer measurements during two intensive campaigns. Primary fossil fuel combustion emissions constituted less than 20%in winter and 40%in summer of carbonaceous fine PM, unexpectedly small for a megacity. Cooking activities and, during winter, residential wood burning are the major primary organic PM sources. This analysis suggests that the major part of secondary organic aerosol is of modern origin, i.e., from biogenic precursors and from wood burning. Black carbon concentrations are on the lower end of values encountered in megacities worldwide, but still represent an issue for air quality. These comparatively low air pollution levels are due to a combination of low emissions per inhabitant, flat terrain, and a meteorology that is in general not conducive to local pollution build-up. This revised picture of a megacity only being partially responsible for its own average and peak PM levels has important implications for air pollution regulation policies.

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Airborne particulate matter (PM) is of environmental concern not only in urban but also rural areas that are easily inhalable and have been considered responsible, together with gaseous pollutants, for possible health effects. The objectives of this research study is to generate an extensive data set for ambient PM collected at Belle Glade and Delray Beach that ultimately was used together with published source profiles to predict the contributions of major sources to the overall airborne particle burden in Belle Glade and Delray Beach. ^ The size segregated particle sampling was conducted for one entire year. The samples collected during the months of January and May were further subjected to chemical analysis for organic compounds by Gas Chromatography-Mass Spectrometry. Additional, PM10 sampling was conducted simultaneously with size segregated particle sampling during January and May to analyze for trace elements using Instrumental Neutron Activation Analysis technique. Elements and organic marker compounds were used in Chemical Mass Balance modeling to determine the major source contribution to the ambient fine particle matter burden. ^ Size segregated particle distribution results show bimodal in both sampling sites. Sugarcane pre-harvest burning in the rural site elevated PM10 concentration by about 30% during the sugarcane harvest season compared to sugarcane growing season. Sea salt particles and Saharan dust particles accounted for the external sources. ^ The results of trace element analysis show that Al, Ca, Cs, Eu, Lu, Nd, Sc, Sm, Th, and Yb are more abundant at the rural sampling site. The trace elements Ba, Br, Ce, Cl, Cr, Fe, Gd, Hf, Na, Sb, Ta, V, and W show high abundance at the urban site due to anthropogenic activities except for Na and Cl, which are from sea salt spray. On the other hand, size segregated trace organic compounds measurements show that organic compounds mainly from combustion process were accumulated in PM0.95. ^ In conclusion, major particle sources were determined by the CMB8.2 software as follows: road dust, sugarcane leaf burning, diesel-powered and gasoline powered vehicle exhaust, leaf surface abrasion particles, and a very small fraction of meat cooking. ^

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Coarse (PM10-2.5) and fine (PM2.5) particulate matter in the atmosphere adversely affect human health and influence climate. While PM2.5 is relatively well studied, less is known about the sources and fate of PM10-2.5. The Colorado Coarse Rural-Urban Sources and Health (CCRUSH) study measured PM10-2.5 and PM2.5 mass concentrations, as well as the fraction of semi-volatile material (SVM) in each size regime (SVM2.5, SVM10-2.5), for three years in Denver and comparatively rural Greeley, Colorado. Agricultural operations east of Greeley appear to have contributed to the peak PM10-2.5 concentrations there, but concentrations were generally lower in Greeley than in Denver. Traffic-influenced sites in Denver had PM10-2.5 concentrations that averaged from 14.6 to 19.7 µg/m**3 and mean PM10-2.5/PM10 ratios of 0.56 to 0.70, higher than at residential sites in Denver or Greeley. PM10-2.5 concentrations were more temporally variable than PM2.5 concentrations. Concentrations of the two pollutants were not correlated. Spatial correlations of daily averaged PM10-2.5 concentrations ranged from 0.59 to 0.62 for pairs of sites in Denver and from 0.47 to 0.70 between Denver and Greeley. Compared to PM10-2.5, concentrations of PM2.5 were more correlated across sites within Denver and less correlated between Denver and Greeley. PM10-2.5 concentrations were highest during the summer and early fall, while PM2.5 and SVM2.5 concentrations peaked in winter during periodic multi-day inversions. SVM10-2.5 concentrations were low at all sites. Diurnal peaks in PM10-2.5 and PM2.5 concentrations corresponded to morning and afternoon peaks of traffic activity, and were enhanced by boundary layer dynamics. SVM2.5 concentrations peaked around noon on both weekdays and weekends. PM10-2.5 concentrations at sites located near highways generally increased with wind speeds above about 3 m/s. Little wind speed dependence was observed for the residential sites in Denver and Greeley.

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The aim of the present work is to study the occupants' exposure to fine particulate concentrations in ten nightclubs (NCs) in Athens, Greece. Measurements of PM1 and PM 2.5 were made in the outdoor and indoor environment of each NC. The average indoorPM1 andPM 2.5 concentrations were found to be 181.77 μgm−3 and 454.08 μg m−3 respectively, while the corresponding outdoor values were 11.04 μg m−3 and 32.19 μg m−3. Ventilation and resuspension rates were estimated through consecutive numerical experiments with an indoor air quality model and were found to be remarkably lower than the minimum values recommended by national standards. The relative effects of the ventilation and smoking on the occupants' exposures were examined using multiple regression techniques. Itwas found that given the low ventilation rates, the effect of smoking as well as the occupancy is of the highest importance. Numerical evaluations showed that if the ventilation rates were at the minimum values set by national standards, then the indoor exposures would be reduced at the 70% of the present exposure values.

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Clinical evidence has identified the pulmonary circulation as an important target of air pollution. It was previously demonstrated that in vitro exposure to fine particulate matter (aerodynamic diameter <= 2.5 mu m, PM2.5) induces endothelial dysfunction in isolated pulmonary arteries. We aimed to investigate the effects of in vivo exposure to urban concentrated PM2.5 on rat pulmonary artery reactivity and the mechanisms involved. For this, adult Wistar rats were exposed to 2 weeks of concentrated Sao Paulo city air PM2.5 at an accumulated daily dose of approximately 600 mu g/m(3). Pulmonary arteries isolated from PM2.5-exposed animals exhibited impaired endothelium-dependent relaxation to acetylcholine without significant changes in nitric oxide donor response compared to control rats. PM2.5 caused vascular oxidative stress and enhanced protein expression of Cu/Zn- and Mn-superoxide dismutase in the pulmonary artery. Protein expression of endothelial nitric oxide synthase (eNOS) was reduced, while tumor necrosis factor (TNF)-alpha was enhanced by PM2.5 inhalation in pulmonary artery. There was a significant positive correlation between eNOS expression and maximal relaxation response (E-max) to acetylcholine. A negative correlation was found between vascular TNF-alpha expression and E-max to acetylcholine. Plasma cytokine levels, blood cells count and coagulation parameters were similar between control and PM2.5-exposed rats. The present findings showed that in vivo daily exposure to concentrated urban PM2.5 could decrease endothelium-dependent relaxation and eNOS expression on pulmonary arteries associated with local high TNF-alpha level but not systemic pro-inflammatory factors. Taken together, the present results elucidate the mechanisms underlying the trigger of cardiopulmonary diseases induced by urban ambient levels of PM2.5. (C) 2012 Elsevier Ireland Ltd. All rights reserved.

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This study represents a secondary analysis of the merging of emergency room visits and daily ozone and PM2.5. Although the adverse health effects of ozone and fine particulate matter have been documented in the literature, evidence regarding the health risks of these two pollutants in Harris County, Texas, is limited. Harris County (Houston) has sufficiently unique characteristics that analysis of these relationships in this setting and with the ozone and industry issues in Houston is informative. The objective of this study was to investigate the association between the joint exposure to ozone and fine particulate matter, and emergency room diagnoses of chronic obstructive pulmonary disease and cardiovascular disease in Harris County, Texas, from 2004 to 2009, with zero and one day lags. ^ The study variables were daily emergency room visits for Harris County, Texas, from 2004 to 2009, temperature, relative humidity, east wind component, north wind component, ozone, and fine particulate matter. Information about each patient's age, race, and gender was also included. The two dichotomous outcomes were emergency room visits diagnoses for chronic obstructive pulmonary disease and cardiovascular disease. Estimates of ozone and PM2.5 were interpolated using kriging, in which estimates of the two pollutants were predicted from monitoring data for every case residence zip code for every day of the six years, over 3 million estimates (one of each pollutant for each case in the database). ^ Logistic regressions were conducted to estimate odds ratios of the two outcomes. Three analyses were conducted: one for all records, another for visits during the four months of April and September of 2005 and 2009, and a third one for visits from zip codes that are close to PM2.5 monitoring stations (east area of Harris County). The last two analyses were designed to investigate special temporal and spatial characteristics of the associations. ^ The dataset included all ER visits surveyed by Safety Net from 2004 to 2009, exceeding 3 million visits for all causes. There were 95,765 COPD and 96,596 CVD cases during this six year period. A 1-μg/m3 increase in PM2.5 on the same day was associated with a 1.0% increase in the odds of chronic obstructive pulmonary disease emergency room diagnoses, a 0.4% increase in the odds of cardiovascular disease emergency room diagnoses, and a 0.2% increase in the odds of cardiovascular disease emergency room diagnoses on the following day. A 1-ppb increase in ozone was associated with a 0.1% increase in the odds of chronic obstructive pulmonary disease emergency room diagnoses on the same day. These four percentages add up to 1.7% of ER visits. That is, over the period of six years, one unit increase for both ozone and PM2.5 (joint increase), resulted in about 55,286 (3,252,102 * 0.017) extra ER visits for CVD or COPD, or 9,214 extra ER visits per year. ^ After adjustment for age, race, gender, day of the week, temperature, relative humidity, east wind component, north wind component, and wind speed, there were statistically significant associations between emergency room chronic obstructive pulmonary disease diagnosis in Harris County, Texas, with joint exposure to ozone and fine particulate matter for the same day; and between emergency room cardiovascular disease diagnosis and exposure to PM2.5 of the same day and the previous day. ^ Despite the small association between the two air pollutants and the health outcomes, this study points to important findings. Namely, the need to identify reasons for the increase of CVD and COPD ER visits over the course of the project, the statistical association between humidity (or whatever other variables for which it may serve as a surrogate) and CVD and COPD cases, and the confirmatory finding that males and blacks have higher odds for the two outcomes, as consistent with other studies. ^ An important finding of this research suggests that the number and distribution of PM2.5 monitors in Harris County - although not evenly spaced geographically—are adequate to detect significant association between exposure and the two outcomes. In addition, this study points to other potential factors that contribute to the rising incidence rates of CVD and COPD ER visits in Harris County such as population increases, patient history, life style, and other pollutants. Finally, results of validation, using a subset of the data demonstrate the robustness of the models.^

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We present results from the international field campaign DAURE (Detn. of the sources of atm. Aerosols in Urban and Rural Environments in the Western Mediterranean), with the objective of apportioning the sources of fine carbonaceous aerosols. Submicron fine particulate matter (PM1) samples were collected during Feb.-March 2009 and July 2009 at an urban background site in Barcelona (BCN) and at a forested regional background site in Montseny (MSY). We present radiocarbon (14C) anal. for elemental and org. carbon (EC and OC) and source apportionment for these data. We combine the results with those from component anal. of aerosol mass spectrometer (AMS) measurements, and compare to levoglucosan-based ests. of biomass burning OC, source apportionment of filter data with inorg. compn. + EC + OC, submicron bulk potassium (K) concns., and gaseous acetonitrile concns. At BCN, 87 % and 91 % of the EC on av., in winter and summer, resp., had a fossil origin, whereas at MSY these fractions were 66 % and 79 %. The contribution of fossil sources to org. carbon (OC) at BCN was 40 % and 48 %, in winter and summer, resp., and 31 % and 25 % at MSY. The combination of results obtained using the 14C technique, AMS data, and the correlations between fossil OC and fossil EC imply that the fossil OC at Barcelona is ∼47 % primary whereas at MSY the fossil OC is mainly secondary (∼85 %). Day-to-day variation in total carbonaceous aerosol loading and the relative contributions of different sources predominantly depended on the meteorol. transport conditions. The estd. biogenic secondary OC at MSY only increased by ∼40 % compared to the order-of-magnitude increase obsd. for biogenic volatile org. compds. (VOCs) between winter and summer, which highlights the uncertainties in the estn. of that component. Biomass burning contributions estd. using the 14C technique ranged from similar to slightly higher than when estd. using other techniques, and the different estns. were highly or moderately correlated. Differences can be explained by the contribution of secondary org. matter (not included in the primary biomass burning source ests.), and/or by an over-estn. of the biomass burning OC contribution by the 14C technique if the estd. biomass burning EC/OC ratio used for the calcns. is too high for this region. Acetonitrile concns. correlate well with the biomass burning EC detd. by 14C. K is a noisy tracer for biomass burning. [on SciFinder(R)]

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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.