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1.
John G. Watson Judith C. Chow Douglas H. Lowenthal L.-W. Antony Chen Stephanie Shaw Eric S. Edgerton 《Journal of the Air & Waste Management Association (1995)》2013,63(9):1104-1118
Positive matrix factorization (PMF) and effective variance (EV) solutions to the chemical mass balance (CMB) were applied to PM2.5 (particulate matter with an aerodynamic diameter <2.5 μm) mass and chemically speciated measurements for samples taken from 2008 to 2010 at the Atlanta, Georgia, and Birmingham, Alabama, sites. Commonly measured PM2.5 mass, elemental, ionic, and thermal carbon fraction concentrations were supplemented with detailed nonpolar organic speciation by thermal desorption-gas chromatography/mass spectrometry (TD-GC/MS). Source contribution estimates were calculated for motor vehicle exhaust, biomass burning, cooking, coal-fired power plants, road dust, vegetative detritus, and secondary sulfates and nitrates for Atlanta. Similar sources were found for Birmingham, with the addition of an industrial source and the separation of biomass burning into open burning and residential wood combustion. EV-CMB results based on conventional species were qualitatively similar to those estimated by PMF-CMB. Secondary ammonium sulfate was the largest contributor, accounting for 27–38% of PM2.5, followed by biomass burning (21–24%) and motor vehicle exhaust (9–24%) at both sites, with 4–6% of PM2.5 attributed to coal-fired power plants by EV-CMB. Including organic compounds in the EV-CMB reduced the motor vehicle exhaust and biomass burning contributions at both sites, with a 13–23% deficit for PM2.5 mass. The PMF-CMB solution showed mixing of sources within the derived factors, both with and without the addition of speciated organics, as is often the case with complex source mixtures such as those at these urban-scale sites. The nonpolar TD-GC/MS compounds can be obtained from existing filter samples and are a useful complement to the elements, ions, and carbon fractions. However, they should be supplemented with other methods, such as TD-GC/MS on derivitized samples, to obtain a wider range of polar compounds such as sterols, sugars, and organic acids. The PMF and EV solutions to the CMB equations are complementary to, rather than replacements for, each other, as comparisons of their results reveal uncertainties that are not otherwise evident.Implications:?Organic markers can be measured on currently acquired PM2.5 filter samples by thermal methods. These markers can complement element, ion, and carbon fraction measurements from long-term speciation networks. Applying the positive matrix factorization and effective variance solutions for the chemical mass balance equations provides useful information on the accuracy of the source contribution estimates. Nonpolar compounds need to be complemented with polar compounds to better apportion cooking and secondary organic aerosol contributors. 相似文献
2.
Chen LW Watson JG Chow JC DuBois DW Herschberger L 《Journal of the Air & Waste Management Association (1995)》2011,61(11):1204-1217
Chemical mass balance (CMB) and trajectory receptor models were applied to speciated particulate matter with aerodynamic diameter < or =2.5 microm (PM2.5) measurements from Speciation Trends Network (STN; part of the Chemical Speciation Network [CSN]) and Interagency Monitoring of Protected Visual Environments (IMPROVE) monitoring network across the state of Minnesota as part of the Minnesota PM2.5 Source Apportionment Study (MPSAS). CMB equations were solved by the Unmix, positive matrix factorization (PMF), and effective variance (EV) methods, giving collective source contribution and uncertainty estimates. Geological source profiles developed from local dust materials were either incorporated into the EV-CMB model or used to verify factors derived from Unmix and PMF. Common sources include soil dust, calcium (Ca)-rich dust, diesel and gasoline vehicle exhausts, biomass burning, secondary sulfate, and secondary nitrate. Secondary sulfate and nitrate aerosols dominate PM2.5 mass (50-69%). Mobile sources outweigh area sources at urban sites, and vice versa at rural sites due to traffic emissions. Gasoline and diesel contributions can be separated using data from the STN, despite significant uncertainties. Major differences between MPSAS and earlier studies on similar environments appear to be the type and magnitude of stationary sources, but these sources are generally minor (<7%) in this and other studies. Ensemble back-trajectory analysis shows that the lower Midwestern states are the predominant source region for secondary ammoniated sulfate in Minnesota. It also suggests substantial contributions of biomass burning and soil dust from out-of-state on occasions, although a quantitative separation of local and regional contributions was not achieved in the current study. Supplemental materials are available for this article. Go to the publisher's online edition of the Journal of the Air & Waste Management Association for a summary of input data, Unmix and PMF factor profiles, and additional maps. 相似文献
3.
John Salop George F. Maier 《Journal of the Air & Waste Management Association (1995)》2013,63(6):641-642
ABSTRACT The Las Vegas Valley PM10 Study was conducted during 1995 to determine the contributions to PM10 aerosol from fugitive dust, motor vehicle exhaust, residential wood combustion, and secondary aerosol sources. Twenty-four-hr PM10 samples were collected at two neighborhood-scale sites every sixth day for 13 months. Five week-long intensive studies were conducted over a middle-scale sub-region at 29 locations that contained many construction projects emitting fugitive dust. The study found that the zone of influence around individual emitters was less than 1 km. Most of the sampling sites in residential and commercial areas yielded equivalent PM10 concentrations in the neighborhood region, even though they were more distant from each other than they were from the nearby construction sources. Based on chemical mass balance (CMB) receptor modeling, fugitive dust accounted for 80–90% of the PM10, and motor vehicle exhaust accounted for 3–9% of the PM10 in the Las Vegas Valley. 相似文献
4.
Eugene Kim Youjun Qin 《Journal of the Air & Waste Management Association (1995)》2013,63(8):1190-1199
Abstract Because the particulate organic carbon (OC) concentrations reported in U.S. Environment Protection Agency Speciation Trends Network (STN) data were not blank corrected, the OC blank concentrations were estimated using the intercept in particulate matter ≤2.5 µm in aerodynamic diameter (PM2.5) regression against OC concentrations. The estimated OC blank concentrations ranged from 1 to 2.4 μg/m3 showing higher values in urban areas for the 13 monitoring sites in the northeastern United States. In the STN data, several different samplers and analyzers are used, and various instruments show different method detection limit (MDL) values, as well as errors. A comprehensive set of error structures that would be used for numerous source apportionment studies of STN data was estimated by comparing a limited set of measured concentrations and their associated uncertainties. To examine the estimated error structures and investigate the appropriate MDL values, PM2.5 samples collected at a STN site in Burlington, VT, were analyzed through the application of the positive matrix factorization. A total of 323 samples that were collected between December 2000 and December 2003 and 49 species based on several variable selection criteria were used, and eight sources were successfully identi?ed in this study with the estimated error structures and min values among different MDL values from the ?ve instruments: secondary sulfate aerosol (41%), secondary nitrate aerosol (20%), airborne soil (15%), gasoline vehicle emissions (7%), diesel emissions (7%), aged sea salt (4%), copper smelting (3%), and ferrous smelting (2%). Time series plots of contributions from airborne soil indicate that the highly elevated impacts from this source were likely caused primarily by dust storms. 相似文献
5.
S. B. Twiss D. M. Teague J. W. Bozek M. V. Sink 《Journal of the Air & Waste Management Association (1995)》2013,63(2):75-83
Abstract The Mohave Valley region of southern Nevada/southwestern Arizona has experienced elevated particulate concentrations and is classified as a PM10 nonattainment area. Anthropogenic aerosol sources in the area include the Mohave Power Project (MPP), a 1,580-MW coal-fired power plant; motor vehicles; construction activities; and paved and unpaved road dust and disturbed desert soil. Aerosols may also be transported long distances from other areas, such as the Los Angeles Basin. Based on the infrequency of plume contact at sites in the valley (as determined by SO2 measurements), it was believed that the contribution of the MPP to primary PM10 was minimal and that fugitive dust was the primary source of ambient particulate matter. To evaluate the magnitude of source contributors, PM10 measurements were made using a medium-volume sampler along with ancillary meteorological and air quality measurements in the Mohave Valley at Bullhead City, Arizona, for a period of longer than one year (September 1988 through mid-October 1989). The aerosol filter samples were analyzed for mass, elements, ions, and carbon. Source apportionment using the Chemical Mass Balance (CMB) receptor model was performed. On average, geological dust was the major contributor to PM10 (79.5%), followed by primary motor vehicle sources (16.7%), secondary ammonium sulfate (3.5%), secondary ammonium nitrate (0.1%), and primary coal-fired power plant emissions (0.1%). 相似文献
6.
G. Argyropoulos Th. Grigoratos M. Voutsinas C. Samara 《Environmental science and pollution research international》2013,20(10):7214-7230
Ambient concentrations of PM10 and associated elemental and ionic species were measured over the cold and the warm months of 2010 at an urban and two rural sites located in the lignite-fired power generation area of Megalopolis in Peloponnese, southern Greece. The PM10 concentrations at the urban site (44.2?±?33.6 μg m?3) were significantly higher than those at the rural sites (23.7?±?20.4 and 22.7?±?26.9 μg m?3). Source apportionment of PM10 and associated components was accomplished by an advanced computational procedure, the robotic chemical mass balance model (RCMB), using chemical profiles for a variety of local fugitive dust sources (power plant fly ash, flue gas desulfurization wet ash, feeding lignite, infertile material from the opencast mines, paved and unpaved road dusts, soil), which were resuspended and sampled through a PM10 inlet onto filters and then chemically analyzed, as well as of other common sources such as vehicular traffic, residential oil combustion, biomass burning, uncontrolled waste burning, marine aerosol, and secondary aerosol formation. Geological dusts (road/soil dust) were found to be major PM10 contributors in both the cold and warm periods of the year, with average annual contribution of 32.6 % at the urban site vs. 22.0 and 29.0 % at the rural sites. Secondary aerosol also appeared to be a significant source, contributing 22.1 % at the urban site in comparison to 30.6 and 28.7 % at the rural sites. At all sites, the contribution of biomass burning was most significant in winter (28.2 % at the urban site vs. 14.6 and 24.6 % at the rural sites), whereas vehicular exhaust contribution appeared to be important mostly in the summer (21.9 % at the urban site vs. 11.5 and 10.5 % at the rural sites). The highest contribution of fly ash (33.2 %) was found at the rural site located to the north of the power plants during wintertime, when winds are favorable. In the warm period, the highest contribution of fly ash was found at the rural site located to the south of the power plants, although it was less important (7.2 %). Moderate contributions of fly ash were found at the urban site (5.4 and 2.7 % in the cold and the warm period, respectively). Finally, the mine field was identified as a minor PM10 source, occasionally contributing with lignite dust and/or deposited wet ash dust under dry summer conditions, with the summertime contributions ranging between 3.1 and 11.0 % among the three sites. The non-parametric bootstrapped potential source contribution function analysis was further applied to localize the regions of sources apportioned by the RCMB. For the majority of sources, source regions appeared as being located within short distances from the sampling sites (within the Peloponnesse Peninsula). More distant Greek areas of the NNE sector also appeared to be source regions for traffic emissions and secondary calcium sulfate dust. 相似文献
7.
U.S. National PM2.5 Chemical Speciation Monitoring Networks—CSN and IMPROVE: Description of networks
Paul A. Solomon Dennis Crumpler James B. Flanagan R.K.M. Jayanty Ed E. Rickman Charles E. McDade 《Journal of the Air & Waste Management Association (1995)》2014,64(12):1410-1438
The U.S. Environmental Protection Agency (EPA) initiated the national PM2.5 Chemical Speciation Monitoring Network (CSN) in 2000 to support evaluation of long-term trends and to better quantify the impact of sources on particulate matter (PM) concentrations in the size range below 2.5 μm aerodynamic diameter (PM2.5; fine particles). The network peaked at more than 260 sites in 2005. In response to the 1999 Regional Haze Rule and the need to better understand the regional transport of PM, EPA also augmented the long-existing Interagency Monitoring of Protected Visual Environments (IMPROVE) visibility monitoring network in 2000, adding nearly 100 additional IMPROVE sites in rural Class 1 Areas across the country. Both networks measure the major chemical components of PM2.5 using historically accepted filter-based methods. Components measured by both networks include major anions, carbonaceous material, and a series of trace elements. CSN also measures ammonium and other cations directly, whereas IMPROVE estimates ammonium assuming complete neutralization of the measured sulfate and nitrate. IMPROVE also measures chloride and nitrite. In general, the field and laboratory approaches used in the two networks are similar; however, there are numerous, often subtle differences in sampling and chemical analysis methods, shipping, and quality control practices. These could potentially affect merging the two data sets when used to understand better the impact of sources on PM concentrations and the regional nature and long-range transport of PM2.5. This paper describes, for the first time in the peer-reviewed literature, these networks as they have existed since 2000, outlines differences in field and laboratory approaches, provides a summary of the analytical parameters that address data uncertainty, and summarizes major network changes since the inception of CSN.
ImplicationsTwo long-term chemical speciation particle monitoring networks have operated simultaneously in the United States since 2001, when the EPA began regular operations of its PM2.5 Chemical Speciation Monitoring Network (IMPROVE began in 1988). These networks use similar field sampling and analytical methods, but there are numerous, often subtle differences in equipment and methodologies that can affect the results. This paper describes these networks since 2000 (inception of CSN) and their differences, and summarizes the analytical parameters that address data uncertainty, providing researchers and policymakers with background information they may need (e.g., for 2018 PM2.5 designation and State Implementation Plan process; McCarthy, 2013) to assess results from each network and decide how these data sets can be mutually employed for enhanced analyses. Changes in CSN and IMPROVE that have occurred over the years also are described. 相似文献
8.
《Atmospheric environment (Oxford, England : 1994)》1999,33(19):3251-3268
Aerosol samples for PM2.5 and PM10 (particulate matter with aerodynamic diameters less than 2.5 and 10 μm, respectively) were collected from 1993 to 1995 at five sites in Brisbane, a subtropical coastal city in Australia. This paper investigates the contributions of emission sources to PM2.5 and PM10 aerosol mass in Brisbane. Source apportionment results derived from the chemical mass balance (CMB), target transformation factor analysis (TTFA) and multiple linear regression (MLR) methods agree well with each other. The contributions from emission sources exhibit large variations in particle size with temporal and spatial differences. On average, the major contributors of PM10 aerosol mass in Brisbane include: soil/road side dusts (25% by mass), motor vehicle exhausts (13%, not including the secondary products), sea salt (12%), Ca-rich and Ti-rich compounds (11%, from cement works and mineral processing industries), biomass burning (7%), and elemental carbon and secondary products contribute to around 15% of the aerosol mass on average. The major sources of PM2.5 aerosols at the Griffith University (GU) site (a suburban site surrounded by forest area) are: elemental carbon (24% by mass), secondary organics (21%), biomass burning (15%) and secondary sulphate (14%). Most of the secondary products are related to motor vehicle exhausts, so, although motor vehicle exhausts contribute directly to only 6% of the PM2.5 aerosol mass, their total contribution (including their secondary products) could be substantial. This pattern of source contribution is similar to the results for Rozelle (Sydney) among the major Australian studies, and is less in contributions from industrial and motor vehicular exhausts than the other cities. An attempt was made to estimate the contribution of rural dust and road side dust. The results show that road side dusts could contribute more than half of the crustal matter. More than 80% of the contribution of vehicle exhausts arises from diesel-fuelled trucks/buses. Biomass burning, large contributions of crustal matter, and/or local contributing sources under calm weather conditions, are often the cause of the high PM10 episodes at the GU site in Brisbane. 相似文献
9.
Fujita EM Zielinska B Campbell DE Arnott WP Sagebiel JC Mazzoleni L Chow JC Gabele PA Crews W Snow R Clark NN Wayne WS Lawson DR 《Journal of the Air & Waste Management Association (1995)》2007,57(6):705-720
The U.S. Department of Energy Gasoline/Diesel PM Split Study examined the sources of uncertainties in using an organic compound-based chemical mass balance receptor model to quantify the contributions of spark-ignition (SI) and compression-ignition (CI) engine exhaust to ambient fine particulate matter (PM2.5). This paper presents the chemical composition profiles of SI and CI engine exhaust from the vehicle-testing portion of the study. Chemical analysis of source samples consisted of gravimetric mass, elements, ions, organic carbon (OC), and elemental carbon (EC) by the Interagency Monitoring of Protected Visual Environments (IMPROVE) and Speciation Trends Network (STN) thermal/optical methods, polycyclic aromatic hydrocarbons (PAHs), hopanes, steranes, alkanes, and polar organic compounds. More than half of the mass of carbonaceous particles emitted by heavy-duty diesel trucks was EC (IMPROVE) and emissions from SI vehicles contained predominantly OC. Although total carbon (TC) by the IMPROVE and STN protocols agreed well for all of the samples, the STN/IMPROVE ratios for EC from SI exhaust decreased with decreasing sample loading. SI vehicles, whether low or high emitters, emitted greater amounts of high-molecular-weight particulate PAHs (benzo[ghi]perylene, indeno[1,2,3-cd]pyrene, and coronene) than did CI vehicles. Diesel emissions contained higher abundances of two- to four-ring semivolatile PAHs. Diacids were emitted by CI vehicles but are also prevalent in secondary organic aerosols, so they cannot be considered unique tracers. Hopanes and steranes were present in lubricating oil with similar composition for both gasoline and diesel vehicles and were negligible in gasoline or diesel fuels. CI vehicles emitted greater total amounts of hopanes and steranes on a mass per mile basis, but abundances were comparable to SI exhaust normalized to TC emissions within measurement uncertainty. The combustion-produced high-molecular-weight PAHs were found in used gasoline motor oil but not in fresh oil and are negligible in used diesel engine oil. The contributions of lubrication oils to abundances of these PAHs in the exhaust were large in some cases and were variable with the age and consumption rate of the oil. These factors contributed to the observed variations in their abundances to total carbon or PM2.5 among the SI composition profiles. 相似文献
10.
Chi-Fan Chen Jeng-Jong Liang 《Environmental science and pollution research international》2013,20(5):2867-2881
This study integrated estimated oxidation ratio of sulfur (SOR) and oxidation ratio of nitrogen (NOR) with source-receptor modeling results to identify the effects of terrain and monsoons on ambient aerosols in an urban area (north basin) and a rural area (south basin) of the Taichung Basin. The estimated results indicate that the conversion of sulfur mainly occurs in fine particles (PM2.5), whereas the conversion of nitrogen occurs in approximately equal quantities of PM2.5 and coarse particles (PM2.5–10). The results show a direct relationship for PM2.5 between the modeling results with SOR and NOR. The high PM2.5 SOR, NOR, and secondary aerosol values all occurred in the upwind area during both monsoons; this shows that the photochemical reaction and the terrain effect on the pollutant transmission were significant in the basin. Additionally, the urban heat island effect on the urban area and the valley effect on the rural area were significant. The results show that secondary aerosol in PM2.5–10 contributed approximately 10 % during both monsoons, and the difference in the contribution from secondary aerosol between both areas was small. Vehicle exhaust emissions and wind-borne dust were two crucial PM2.5–10 contributors during both monsoons; their average contributions in both areas were higher than 34 and 32 %, respectively. 相似文献
11.
《Atmospheric environment (Oxford, England : 1994)》2001,35(23):4033-4039
The gravimetric and chemical composition of fugitive dust emitters of Mexico City were analyzed to determine the particulate matter source profiles. Samples of geological material, unpaved and paved roads, agricultural soil, dried lake, asphalt, cement plants, landfill, gravel, and tezontle soil, were collected directly from the ground using a broom and a dustpan. These were dried, sieved and taken through a laboratory resuspension chamber to emulate the natural wind-blown processes of bulk soils and also to provide a uniform deposit on Teflon membrane and quartz fiber filters for further gravimetric and chemical analyses of PM2.5 and PM10 size fractions. Chemical analyses of the filters included X-ray fluorescence for elemental composition, ion chromatography for water soluble anions, atomic absorption for water soluble metals, automated colorimetric analysis for ammonium and thermal/optical reflectance analysis for carbon species. The data show that most fugitive emitters are composed of 20–30% PM2.5, which is relatively less than the reported contribution by fossil fuels and biomass (40–60%). 相似文献
12.
ABSTRACT The chemical mass balance (CMB) model was applied to winter (November through January) 1991–1996 PM2.5 and PM10 data from the Sacramento 13th and T Streets site in order to identify the contributions from major source categories to peak 24-hr ambient PM2.5 and PM10 levels. The average monthly PM10 monitoring data for the nine-year period in Sacramento County indicate that elevated concentrations are typical in the winter months. Concentrations on days of highest PM10 are dominated by the PM2.5 fraction. One factor contributing to increased PM2.5 concentrations in the winter is meteorology (cool temperatures, low wind speeds, low inversion layers, and more humid conditions) that favors the formation of secondary nitrate and sulfate aerosols. Residential wood burning also elevates fine particulate concentrations in the Sacramento area. The results of the CMB analysis highlight three key points. First, the source apportionment results indicate that primary motor vehicle exhaust and wood smoke are significant sources of both PM2.5 and PM10 in winter. Second, nitrates, secondarily formed as a result of motor-vehicle and other sources of nitrogen oxide (NOx), are another principal cause of the high PM2.5 and PM10 levels during the winter months. Third, fugitive dust, whether it is resuspended soil and dust or agricultural tillage, is not the major contributor to peak winter PM2.5 and PM10 levels in the Sacramento area. 相似文献
13.
Eugene Kim Katarzyna Turkiewicz Sylvia A. Zulawnick Karen L. Magliano 《Atmospheric environment (Oxford, England : 1994)》2010,44(26):3095-3100
PM2.5 (particulate matter less than 2.5 μm in aerodynamic diameter) speciation data collected between 2003 and 2005 at two United State Environmental Protection Agency (US EPA) Speciation Trends Network monitoring sites in the South Coast area, California were analyzed to identify major PM2.5 sources as a part of the State Implementation Plan development. Eight and nine major PM2.5 sources were identified in LA and Rubidoux, respectively, through PMF2 analyses. Similar to a previous study analyzing earlier data (Kim and Hopke, 2007a), secondary particles contributed the most to the PM2.5 concentrations: 53% in LA and 59% in Rubidoux. The next highest contributors were diesel emissions (11%) in LA and Gasoline vehicle emissions (10%) in Rubidoux. Most of the source contributions were lower than those from the earlier study. However, the average source contributions from airborne soil, sea salt, and aged sea salt in LA and biomass smoke in Rubidoux increased.To validate the apportioned sources in this study, PMF2 results were compared with those obtained from EPA PMF (US EPA, 2005). Both models identified the same number of major sources and the resolved source profiles and contributions were similar at the two monitoring sites. The minor differences in the results caused by the differences in the least square algorithm and non-negativity constraints between two models did not affect the source identifications. 相似文献
14.
John S. Kinsey Kara J. Linna William C. Squier Gregory E. Muleski Chatten Cowherd Jr. 《Journal of the Air & Waste Management Association (1995)》2013,63(11):1394-1404
Abstract Although the fugitive dust associated with construction mud/dirt carryout can represent a substantial portion of the particulate matter (PM) emissions inventory in non-attainment areas, it has not been well characterized by direct sampling methods. In this paper, a research program is described that directly determined both PM10 and PM2.5 (particles ≤10 and 2.5 μm in classical aerodynamic diameter, respectively) emission factors for mud/dirt carryout from a major construction project located in metropolitan Kansas City, MO. The program also assessed the contribution of automotive emissions to the total PM2.5 burden and determined the baseline emissions from the test road. As part of the study, both time-integrated and continuous exposure-profiling methods were used to assess the PM emissions, including particle size and elemental composition. This research resulted in overall PM10 and PM2.5 emission factors of 6 and 0.2 g/vehicle, respectively. Although PM10 is within the range of prior U.S. Environmental Protection Agency (EPA) guidance, the PM2.5 emission factor is far lower than previous estimates published by EPA. In addition, based on both the particle size and chemical data obtained in the study, a major portion of the PM2.5 emissions appears to be attributable to automotive exhaust from light-duty, gasoline-powered vehicles and not to the fugitive dust associated with re-entrained mud/dirt carryout. 相似文献
15.
Source characterization of ambient fine particles at multiple sites in the Seattle area 总被引:2,自引:0,他引:2
To identify major PM2.5 (particulate matter ≤2.5 μm in aerodynamic diameter) sources with a particular emphasis on the ship engine emissions from a major port, integrated 24 h PM2.5 speciation data collected between 2000 and 2005 at five United State Environmental Protection Agency's Speciation Trends Network monitoring sites in Seattle, WA were analyzed. Seven to ten PM2.5 sources were identified through the application of positive matrix factorization (PMF). Secondary particles (12–26% for secondary nitrate; 17–20% for secondary sulfate) and gasoline vehicle emissions (13–31%) made the largest contributions to the PM2.5 mass concentrations at all of the monitoring sites except for the residential Lake Forest site, where wood smoke contributed the most PM2.5 mass (31%). Other identified sources include diesel vehicle emissions, airborne soil, residual oil combustion, sea salt, aged sea salt, metal processing, and cement kiln. Residual oil combustion sources identified at multiple monitoring sites point clearly to the Port of Seattle suggesting ship emissions as the source of oil combustion particles. In addition, the relationship between sulfate concentrations and the oil combustion emissions indicated contributions of ship emissions to the local sulfate concentrations. The analysis of spatial variability of PM2.5 sources shows that the spatial distributions of several PM2.5 sources were heterogeneous within a given air shed. 相似文献
16.
《Atmospheric environment (Oxford, England : 1994)》2007,41(3):567-575
In order to use the US Environmental Protection Agency's speciation trends networks (STN) data in source apportionment studies with positive matrix factorization (PMF), uncertainties for each of the measured data points are required. Since STN data were not accompanied by sample-species specific uncertainties (SSU) prior to July 2003, a comprehensive set of fractional uncertainties was estimated by Kim et al. [2005. Estimation of organic carbon blank values and error structures of the speciation trends network data for source apportionments. Journal of Air and Waste Management Association 55, 1190–1199]. The objective of this study is to compare the use of the estimated fractional uncertainties (EFU) for the source apportionment of PM2.5 (particulate matter less than 2.5 μm in aerodynamic diameter) measured at the STN monitoring sites with the results obtained using SSU. Thus, the source apportionment of STN PM2.5 data were performed and their contributions were estimated through the application of PMF for two selected STN sites, Elizabeth, NJ and Baltimore, MD with both SSU and EFU for the elements measured by X-ray fluorescence. The PMF resolved factor profiles and contributions using EFU were similar to those using SSU at both monitoring sites. The comparisons of normalized concentrations indicated that the STN SSU were not well estimated. This study supports the use of EFU for the STN samples to provide useful error structure for the source apportionment studies of the STN data. 相似文献
17.
A comprehensive air quality modeling project was carried out to simulate regional source contributions to secondary and total (=primary + secondary) airborne particle concentrations in California's Central Valley. A three-week stagnation episode lasting from December 15, 2000 to January 7, 2001, was chosen for study using the air quality and meteorological data collected during the California Regional PM10/PM2.5 Air Quality Study (CRPAQS). The UCD/CIT mechanistic air quality model was used with explicit decomposition of the gas phase reaction chemistry to track source contributions to secondary PM. Inert artificial tracers were used with an internal mixture representation to track source contributions to primary PM. Both primary and secondary source apportionment calculations were performed for 15 size fractions ranging from 0.01 to 10 μm particle diameters. Primary and secondary source contributions were resolved for fugitive dust, road dust, diesel engines, catalyst equipped gasoline engines, non-catalyst equipped gasoline engines, wood burning, food cooking, high sulfur fuel combustion, and other anthropogenic sources.Diesel engines were identified as the largest source of secondary nitrate in central California during the study episode, accounting for approximately 40% of the total PM2.5 nitrate. Catalyst equipped gasoline engines were also significant, contributing approximately 20% of the total secondary PM2.5 nitrate. Agricultural sources were the dominant source of secondary ammonium ion. Sharp gradients of PM concentrations were predicted around major urban areas. The relative source contributions to PM2.5 from each source category in urban areas differ from those in rural areas, due to the dominance of primary OC in urban locations and secondary nitrate in the rural areas. The source contributions to ultra-fine particle mass PM0.1 also show clear urban/rural differences. Wood smoke was found to be the major source of PM0.1 in urban areas while motor vehicle sources were the major contributor of PM0.1 in rural areas, reflecting the influence from two major highways that transect the Valley. 相似文献
18.
《Journal of the Air & Waste Management Association (1995)》2013,63(2):320-343
Abstract Emissions inventories of fine particulate matter (PM2.5) were compared with estimates of emissions based on data emerging from U.S. Environment Protection Agency Particulate Matter Supersites and other field programs. Six source categories for PM2.5 emissions were reviewed: on-road mobile sources, nonroad mobile sources, cooking, biomass combustion, fugitive dust, and stationary sources. Ammonia emissions from all of the source categories were also examined. Regional emissions inventories of PM in the exhaust from on-road and nonroad sources were generally consistent with ambient observations, though uncertainties in some emission factors were twice as large as the emission factors. In contrast, emissions inventories of road dust were up to an order of magnitude larger than ambient observations, and estimated brake wear and tire dust emissions were half as large as ambient observations in urban areas. Although comprehensive nationwide emissions inventories of PM2.5 from cooking sources and biomass burning are not yet available, observational data in urban areas suggest that cooking sources account for approximately 5–20% of total primary emissions (excluding dust), and biomass burning sources are highly dependent on region. Finally, relatively few observational data were available to assess the accuracy of emission estimates for stationary sources. Overall, the uncertainties in primary emissions for PM2.5 are substantial. Similar uncertainties exist for ammonia emissions. Because of these uncertainties, the design of PM2.5 control strategies should be based on inventories that have been refined by a combination of bottom-up and top-down methods. 相似文献
19.
Jane E. Clougherty E. Andres Houseman Jonathan I. Levy 《Atmospheric environment (Oxford, England : 1994)》2009,43(34):5545-5555
Recent studies have used land use regression (LUR) techniques to explain spatial variability in exposures to PM2.5 and traffic-related pollutants. Factor analysis has been used to determine source contributions to measured concentrations. Few studies have combined these methods, however, to construct and explain latent source effects. In this study, we derive latent source factors using confirmatory factor analysis constrained to non-negative loadings, and develop LUR models to predict the influence of outdoor sources on latent source factors using GIS-based measures of traffic and other local sources, central site monitoring data, and meteorology. We collected 3–4 day samples of nitrogen dioxide (NO2) and PM2.5 outside of 44 homes in summer and winter, from 2003 to 2005 in and around Boston, Massachusetts. Reflectance analysis, X-ray fluorescence spectroscopy (XRF), and high-resolution inductively-coupled plasma mass spectrometry (ICP-MS) were performed on particle filters to estimate elemental carbon (EC), trace element, and water-soluble metals concentrations. Within our constrained factor analysis, a five-factor model was optimal, balancing statistical robustness and physical interpretability. This model produced loadings indicating long-range transport, brake wear/traffic exhaust, diesel exhaust, fuel oil combustion, and resuspended road dust. LUR models largely corroborated factor interpretations through covariate significance. For example, ‘long-range transport’ was predicted by central site PM2.5 and season; ‘brake wear/traffic exhaust’ and ‘resuspended road dust’ by traffic and residential density; ‘diesel exhaust’ by percent diesel traffic on nearest major road; and ‘fuel oil combustion’ by population density. Results suggest that outdoor residential PM2.5 source contributions can be partially predicted using GIS-based terms, and that LUR techniques can support factor interpretation for source apportionment. Together, LUR and factor analysis facilitate source identification, assessment of spatial and temporal variability, and more refined source exposure assignment for evaluation of source contributions to health outcomes in epidemiological studies. 相似文献
20.
J. S. Evans P. L. Kinney J. L. Koehler D. W. Cooper 《Journal of the Air & Waste Management Association (1995)》2013,63(5):551-553
Abstract There is a dearth of information on dust emissions from sources that are unique to the U.S. Department of Defense testing and training activities. However, accurate emissions factors are needed for these sources so that military installations can prepare accurate particulate matter (PM) emission inventories. One such source, coarse and fine PM (PM10 and PM2.5) emissions from artillery backblast testing on improved gun positions, was characterized at the Yuma Proving Ground near Yuma, AZ, in October 2005. Fugitive emissions are created by the shockwave from artillery pieces, which ejects dust from the surface on which the artillery is resting. Other contributions of PM can be attributed to the combustion of the propellants. For a 155–mm howitzer firing a range of propellant charges or zones, amounts of emitted PM10 ranged from ~19 g of PM10 per firing event for a zone 1 charge to 92 g of PM10 per firing event for a zone 5. The corresponding rates for PM2.5 were ~9 g of PM2.5 and 49 g of PM2.5 per firing. The average measured emission rates for PM10 and PM2.5 appear to scale with the zone charge value. The measurements show that the estimated annual contributions of PM10 (52.2 t) and PM2.5 (28.5 t) from artillery backblast are insignificant in the context of the 2002 U.S. Environment Protection Agency (EPA) PM emission inventory. Using national–level activity data for artillery fire, the most conservative estimate is that backblast would contribute the equivalent of 5 x 10–4% and 1.6 x 10–3% of the annual total PM10 and PM2.5 fugitive dust contributions, respectively, based on 2002 EPA inventory data. 相似文献