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1.
We present estimates of the vehicular contribution to ambient organic carbon (OC) and fine particle mass (PM) in Pittsburgh, PA using the chemical mass balance (CMB) model and a large dataset of ambient molecular marker concentrations. Source profiles for CMB analysis are selected using a method of comparing the ambient ratios of marker species with published profiles for gasoline and diesel vehicle emissions. The ambient wintertime data cluster on a hopanes/EC ratio–ratio plot, and therefore can be explained by a large number of different source profile combinations. In contrast, the widely varying summer ambient ratios can be explained by a more limited number of source profile combinations. We present results for a number of different CMB scenarios, all of which perform well on the different statistical tests used to establish the quality of a CMB solution. The results illustrate how CMB estimates depend critically on the marker-to-OC and marker-to-PM ratios of the source profiles. The vehicular contribution in the winter is bounded between 13% and 20% of the ambient OC (274±56–416±72 ng-C m−3). However, variability in the diesel profiles creates uncertainty in the gasoline–diesel split. On an OC basis, one set of scenarios suggests gasoline dominance, while a second set indicates a more even split. On a PM basis, all solutions indicate a diesel-dominated split. The summer CMB solutions do not present a consistent picture given the seasonal shift and wide variation in the ambient hopanes-to-EC ratios relative to the source profiles. If one set of source profiles is applied to the entire dataset, gasoline vehicles dominate vehicular OC in the winter but diesel dominates in the summer. The seasonal pattern in the ambient hopanes-to-EC ratios may be caused by photochemical decay of hopanes in the summer or by seasonal changes in vehicle emission profiles.  相似文献   

2.
This paper presents chemical mass balance (CMB) analysis of organic molecular marker data to investigate the sources of organic aerosol and PM2.5 mass in Pittsburgh, Pennsylvania. The model accounts for emissions from eight primary source classes, including major anthropogenic sources such as motor vehicles, cooking, and biomass combustion as well as some primary biogenic emissions (leaf abrasion products). We consider uncertainty associated with selection of source profiles, selection of fitting species, sampling artifacts, photochemical aging, and unknown sources. In the context of the overall organic carbon (OC) mass balance, the contributions of diesel, wood-smoke, vegetative detritus, road dust, and coke-oven emissions are all small and well constrained; however, estimates for the contributions of gasoline-vehicle and cooking emissions can vary by an order of magnitude. A best-estimate solution is presented that represents the vast majority of our CMB results; it indicates that primary OC only contributes 27±8% and 50±14% (average±standard deviation of daily estimates) of the ambient OC in the summer and winter, respectively. Approximately two-thirds of the primary OC is transported into Pittsburgh as part of the regional air mass. The ambient OC that is not apportioned by the CMB model is well correlated with secondary organic aerosol (SOA) estimates based on the EC-tracer method and ambient concentrations of organic species associated with SOA. Therefore, SOA appears to be the major component of OC, not only in summer, but potentially in all seasons. Primary OC dominates the OC mass balance on a small number of nonsummer days with high OC concentrations; these events are associated with specific meteorological conditions such as local inversions. Primary particulate emissions only contribute a small fraction of the ambient fine-particle mass, especially in the summer.  相似文献   

3.
Mobile sources are significant contributors to ambient PM2.5, accounting for 50% or more of the total observed levels in some locations. One of the important methods for resolving the mobile source contribution is through chemical mass balance (CMB) receptor modeling. CMB requires chemically speciated source profiles with known uncertainty to ensure accurate source contribution estimates. Mobile source PM profiles are available from various sources and are generally in the form of weight fraction by chemical species. The weight fraction format is commonly used, since it is required for input into the CMB receptor model. This paper examines the similarities and differences in mobile source PM2.5 profiles that contain data for elements, ions, elemental carbon (EC) and organic carbon (OC), and in some cases speciated organics (e.g., polycyclic aromatic hydrocarbons [PAHs]), drawn from four different sources. Notable characteristics of the mass fraction data include variability (relative contributions of elements and ions) among supposedly similar sources and a wide range of average EC:OC ratios (0.60 +/- 0.53 to 1.42 +/- 2.99) for light-duty gasoline vehicles (LDGVs), indicating significant EC emissions from LDGVs in some cases. For diesel vehicles, average EC:OC ratios range from 1.09 +/- 2.66 to 3.54 +/- 3.07. That different populations of the same class of emitters can show considerable variability suggests caution should be exercised when selecting and using profiles in source apportionment studies.  相似文献   

4.
In an effort to better quantify wintertime particulate matter (PM) and the contribution of wood smoke to air pollution events in Fresno, CA, a field campaign was conducted in winter 2003-2004. Coarse and fine daily PM samples were collected at five locations in Fresno, including residential, urban, and industrial areas. Measurements of collected samples included gravimetric mass determination, organic and elemental carbon analysis, and trace organic compound analysis by gas chromatograph mass spectrometry (GC/MS). The wood smoke tracer levoglucosan was also measured in aqueous aerosol extracts using high-performance anion exchange chromatography coupled with pulsed amperometric detection. Sample preparation and analysis by this technique is much simpler and less expensive than derivatized levoglucosan analysis by GC/MS, permitting analysis of daily PM samples from all five of the measurement locations. Analyses revealed low spatial variability and similar temporal patterns of PM2.5 mass, organic carbon (OC), and levoglucosan. Daily mass concentrations appear to have been strongly influenced by meteorological conditions, including precipitation, wind, and fog events. Fine PM (PM2.5) concentrations are uncommonly low during the study period, reflecting frequent precipitation events. During the first portion of the study, levoglucosan had a strong relationship to the concentrations of PM2.5 and OC. In the later portion of the study, there was a significant reduction in levoglucosan relative to PM2.5 and OC. This may indicate a change in particle removal processes, perhaps because of fog events, which were more common in the latter period. Combined, the emissions from wood smoke, meat cooking, and motor vehicles appear to contribute approximately 65-80% to measured OC, with wood smoke, on average, accounting for approximately 41% of OC and approximately 18% of PM2.5 mass. Two residential sites exhibit somewhat higher contributions of wood smoke to OC than other locations.  相似文献   

5.
Chemical tracer methods for determining contributions to primary organic aerosol (POA) are fairly well established, whereas similar techniques for secondary organic aerosol (SOA), inherently complicated by time-dependent atmospheric processes, are only beginning to be studied. Laboratory chamber experiments provide insights into the precursors of SOA, but field data must be used to test the approaches. This study investigates primary and secondary sources of organic carbon (OC) and determines their mass contribution to particulate matter 2.5 microm or less in aerodynamic diameter (PM2.5) in Southeastern Aerosol Research and Characterization (SEARCH) network samples. Filter samples were taken during 20 24-hr periods between May and August 2005 at SEARCH sites in Atlanta, GA (JST); Birmingham, AL (BHM); Centerville, AL (CTR); and Pensacola, FL (PNS) and analyzed for organic tracers by gas chromatography-mass spectrometry. Contribution to primary OC was made using a chemical mass balance method and to secondary OC using a mass fraction method. Aerosol masses were reconstructed from the contributions of POA, SOA, elemental carbon, inorganic ions (sulfate [SO4(2-)], nitrate [NO3-], ammonium [NH4+]), metals, and metal oxides and compared with the measured PM2.5. From the analysis, OC contributions from seven primary sources and four secondary sources were determined. The major primary sources of carbon were from wood combustion, diesel and gasoline exhaust, and meat cooking; major secondary sources were from isoprene and monoterpenes with minor contributions from toluene and beta-caryophyllene SOA. Mass concentrations at the four sites were determined using source-specific organic mass (OM)-to-OC ratios and gave values in the range of 12-42 microg m(-3). Reconstructed masses at three of the sites (JST, CTR, PNS) ranged from 87 to 91% of the measured PM2.5 mass. The reconstructed mass at the BHM site exceeded the measured mass by approximately 25%. The difference between the reconstructed and measured PM2.5 mass for nonindustrial areas is consistent with not including aerosol liquid water or other sources of organic aerosol.  相似文献   

6.
Ambient particulates of PM2.5 were sampled at three sites in Kaohsiung, Taiwan, during February and March 1999. In addition, resuspended PM2.5 collected from traffic tunnels, paved roads, fly ash of a municipal solid waste (MSW) incinerator, and seawater was obtained. All the samples were analyzed for twenty constituents, including water-soluble ions, organic carbon (OC), elemental carbon (EC), and metallic elements. In conjunction with local source profiles and the source profiles in the model library SPECIATE EPA, the receptor model based on chemical mass balance (CMB) was then applied to determine the source contributions to ambient PM2.5. The mean concentration of ambient PM2.5 was 42.69-53.68 micrograms/m3 for the sampling period. The abundant species in ambient PM2.5 in the mass fraction for three sites were OC (12.7-14.2%), SO4(2-) (12.8-15.1%), NO3- (8.1-10.3%), NH4+ (6.7-7.5%), and EC (5.3-8.5%). Results of CMB modeling show that major pollution sources for ambient PM2.5 are traffic exhaust (18-54%), secondary aerosols (30-41% from SO4(2-) and NO3-), and outdoor burning of agriculture wastes (13-17%).  相似文献   

7.
The concentrations of trace metals and polycyclic aromatic hydrocarbons (PAHs) adsorbed to total suspended particulate (TSP) and finer fractions of airborne particulate matter (PM) were determined from a site in the centre of Athens (Greece), which is characterized by heavy local traffic and is densely populated, during the winter and summer periods in 2003-2004. Also, we collected and analyzed samples of diesel and gasoline exhaust particles from local vehicles (buses, taxis and private cars) and from chimney exhaust of residential central heating appliances. A seasonal effect was observed for the size distribution of aerosol mass, with a shift to larger fine fractions in winter. The most commonly detected trace metals in the TSP and PM fractions were Fe, Pb, Zn, Cu, Cr, V, Ni and Cd and their concentrations were similar to levels observed in heavily polluted urban areas from local traffic and other anthropogenic emissions. Analysis of 16 PAHs bound to PM showed that they are mostly traffic related. In general, the fine particulate PAHs concentrations were higher than coarse particles. The most common PAHs in PM(10.2) and PM(2.1) were pyrene, phenanthrene, acenapthylene and fluoranthene, which are associated with diesel and gasoline exhaust particles. The results of this study underlined the importance of local emission sources, especially vehicular traffic, central heating and other local anthropogenic emissions. Compared with other big cities, Athens has much higher levels of airborne particles, especially of the finer fractions PM(10) and PM(2.5), correlated with traffic-related air pollution.  相似文献   

8.
Speciated fine particulate matter (PM2.5) data collected as part of the Speciation Trends Network at four sites in the Midwest (Detroit, MI; Cincinnati, OH; Indianapolis, IN; and Northbrook, IL) and as part of the Interagency Monitoring of Protected Visual Environments program at the rural Bondville, IL, site were analyzed to understand sources contributing to organic carbon (OC) and PM2.5 mass. Positive matrix factorization (PMF) was applied to available data collected from January 2002 through March 2005, and seven to nine factors were identified at each site. Common factors at all of the sites included mobile (gasoline)/secondary organic aerosols with high OC, diesel with a high elemental carbon/OC ratio (only at the urban sites), secondary sulfate, secondary nitrate, soil, and biomass burning. Identified industrial factors included copper smelting (Northbrook, Indianapolis, and Bondville), steel/manufacturing with iron (Northbrook), industrial zinc (Northbrook, Cincinnati, Indianapolis, and Detroit), metal plating with chromium and nickel (Detroit, Indianapolis, and Bondville), mixed industrial with copper and iron (Cincinnati), and limestone with calcium and iron (Bondville). PMF results, on average, accounted for 96% of the measured PM2.5 mass at each site; residuals were consistently within tolerance (+/-3), and goodness-of-fit (Q) was acceptable. Potential source contribution function analysis helped identify regional and local impacts of the identified source types. Secondary sulfate and soil factors showed regional characteristics at each site, whereas industrial sources typically appeared to be locally influenced. These regional factors contributed approximately one third of the total PM2.5 mass, on average, whereas local mobile and industrial sources contributed to the remaining mass. Mobile sources were a major contributor (55-76% at the urban sites) to OC mass, generally with at least twice as much mass from nondiesel sources as from diesel. Regional OC associated with secondary sulfate and soil was generally low.  相似文献   

9.
Hourly indoor and outdoor fine particulate matter (PM2.5), organic and elemental carbon (OC and EC, respectively), particle number (PN), ozone (O3), carbon monoxide (CO), and nitrogen oxide (NOx) concentrations were measured at two different retirement communities in the Los Angeles, CA, area as part of the Cardiovascular Health and Air Pollution Study. Site A (group 1 [G1]) was operated from July 6 to August 20, 2005 (phase 1 [P1]) and from October 19 to December 10, 2005 (P2), whereas site B (group 2 [G2]) was operated from August 24 to October 15, 2005 (P1), and from January 4 to February 18, 2006 (P2). Overall, the magnitude of indoor and outdoor measurements was similar, probably because of the major influence of outdoor sources on indoor particle and gas levels. However, G2 showed a substantial increase in indoor OC, PN, and PM2.5 between 6:00 and 9:00 a.m., probably from cooking. The contributions of primary and secondary OC (SOA) to measured outdoor OC were estimated from collected OC and EC concentrations using EC as a tracer of primary combustion-generated OC (i.e., "EC tracer method"). The study average outdoor SOA accounted for 40% of outdoor particulate OC (40-45% in the summer and 32-40% in the winter). Air exchange rates (hr(-1)) and infiltration factors (Finf; dimensionless) at each site were also determined. Estimated Finf and measured particle concentrations were then used in a single compartment mass balance model to assess the contributions of indoor and/or outdoor sources to measured indoor OC, EC, PM2.5, and PN. The average percentage contributions of indoor SOA of outdoor origin to measured indoor OC were approximately 35% (during G1P1 and G1P2) and approximately 45% (for G2P1 and G2P2). On average, 36% (G2P1) to 44% (G1P1) of measured indoor OC was composed of outdoor-generated primary OC.  相似文献   

10.
Abstract

In an effort to better quantify wintertime particulate matter (PM) and the contribution of wood smoke to air pollution events in Fresno, CA, a field campaign was conducted in winter 2003–2004. Coarse and fine daily PM samples were collected at five locations in Fresno, including residential, urban, and industrial areas. Measurements of collected samples included gravimetric mass determination, organic and elemental carbon analysis, and trace organic compound analysis by gas chromatograph mass spectrometry (GC/MS). The wood smoke tracer levoglucosan was also measured in aqueous aerosol extracts using high-performance anion exchange chromatography coupled with pulsed amperometric detection. Sample preparation and analysis by this technique is much simpler and less expensive than derivatized levoglucosan analysis by GC/MS, permitting analysis of daily PM samples from all five of the measurement locations. Analyses revealed low spatial variability and similar temporal patterns of PM2.5 mass, organic carbon (OC), and levoglucosan. Daily mass concentrations appear to have been strongly influenced by meteorological conditions, including precipitation, wind, and fog events. Fine PM (PM2.5) concentrations are uncommonly low during the study period, reflecting frequent precipitation events. During the first portion of the study, levoglucosan had a strong relationship to the concentrations of PM2.5 and OC. In the later portion of the study, there was a significant reduction in levoglucosan relative to PM2.5 and OC. This may indicate a change in particle removal processes, perhaps because of fog events, which were more common in the latter period. Combined, the emissions from wood smoke, meat cooking, and motor vehicles appear to contribute ~65–80% to measured OC, with wood smoke, on average, accounting for ~41% of OC and ~18% of PM2.5 mass. Two residential sites exhibit somewhat higher contributions of wood smoke to OC than other locations.  相似文献   

11.
A nested version of the source-oriented externally mixed UCD/CIT model was developed to study the source contributions to airborne particulate matter (PM) during a two-week long air quality episode during the Texas 2000 Air Quality Study (TexAQS 2000). Contributions to primary PM and secondary ammonium sulfate in the Houston–Galveston Bay (HGB) and Beaumont–Port Arthur (BPA) areas were determined.The predicted 24-h elemental carbon (EC), organic compounds (OC), sulfate, ammonium ion and primary PM2.5 mass are in good agreement with filter-based observations. Predicted concentrations of hourly sulfate, ammonium ion, and primary OC from diesel and gasoline engines and biomass burning organic aerosol (BBOA) at La Porte, Texas agree well with measurements from an Aerodyne Aerosol Mass Spectrometer (AMS).The UCD/CIT model predicts that EC is mainly from diesel engines and majority of the primary OC is from internal combustion engines and industrial sources. Open burning contributes large fractions of EC, OC and primary PM2.5 mass. Road dust, internal combustion engines and industries are the major sources of primary PM2.5. Wildfire dominates the contributions to all primary PM components in areas near the fires. The predicted source contributions to primary PM are in general agreement with results from a chemical mass balance (CMB) model. Discrepancy between the two models suggests that further investigations on the industrial PM emissions are necessary.Secondary ammonium sulfate accounts for the majority of the secondary inorganic PM. Over 80% of the secondary sulfate in the 4 km domain is produced in upwind areas. Coal combustion is the largest source of sulfate. Ammonium ion is mainly from agriculture sources and contributions from gasoline vehicles are significant in urban areas.  相似文献   

12.
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   

13.
The Positive Matrix Factorization (PMF) receptor model version 1.1 was used with data from the fine particulate matter (PM2.5) Chemical Speciation Trends Network (STN) to estimate source contributions to ambient PM2.5 in a highly industrialized urban setting in the southeastern United States. Model results consistently resolved 10 factors that are interpreted as two secondary, five industrial, one motor vehicle, one road dust, and one biomass burning sources. The STN dataset is generally not corrected for field blank levels, which are significant in the case of organic carbon (OC). Estimation of primary OC using the elemental carbon (EC) tracer method applied on a seasonal basis significantly improved the model's performance. Uniform increase of input data uncertainty and exclusion of a few outlier samples (associated with high potassium) further improved the model results. However, it was found that most PMF factors did not cleanly represent single source types and instead are "contaminated" by other sources, a situation that might be improved by controlling rotational ambiguity within the model. Secondary particulate matter formed by atmospheric processes, such as sulfate and secondary OC, contribute the majority of ambient PM2.5 and exhibit strong seasonality (37 +/- 10% winter vs. 55 +/- 16% summer average). Motor vehicle emissions constitute the biggest primary PM2.5 mass contribution with almost 25 +/- 2% long-term average and winter maximum of 29 +/- 11%. PM2.5 contributions from the five identified industrial sources vary little with season and average 14 +/- 1.3%. In summary, this study demonstrates the utility of the EC tracer method to effectively blank-correct the OC concentrations in the STN dataset. In addition, examination of the effect of input uncertainty estimates on model results indicates that the estimated uncertainties currently being provided with the STN data may be somewhat lower than the levels needed for optimum modeling results.  相似文献   

14.
To investigate the chemical characteristics of fine particles in the Sihwa area, Korea, atmospheric aerosol samples were collected using a dichotomous PM10 sampler and two URG PM2.5 cyclone samplers during five intensive sampling periods between February 1998 and February 1999. The Inductively Coupled Plasma (ICP)-Atomic Emission Spectrometry (AES)/ICP-Mass Spectrometry (MS), ion chromatograph (IC), and thermal manganese dioxide oxidation (TMO) methods were used to analyze the trace elements, ionic species, and carbonaceous species, respectively. Backward trajectory analysis, factor analysis, and a chemical mass balance (CMB) model were used to estimate quantitatively source contributions to PM2.5 particles collected in the Sihwa area. The results of PM2.5 source apportionment using the CMB7 receptor model showed that (NH4)2SO4 was, on average, the major contributor to PM2.5 particles, followed by nontraffic organic carbon (OC) emission, NH4NO3, agricultural waste burning, motor vehicle emission, road dust, waste incineration, marine aerosol, and others. Here, the nontraffic OC sources include primary anthropogenic OC emitted from the industrial complex zone, secondary OC, and organic species from distant sources. The source impact of waste incineration emission became significant when the dominant wind directions were from southwest and west sectors during the sampling periods. It was found that PM2.5 particles in the Sihwa area were influenced mainly by both anthropogenic local sources and long-range transport and transformation of air pollutants.  相似文献   

15.
Sources of carbonaceous aerosols collected from three sites of Chattanooga, TN (CH), Muscle Shoals, AL (MS), and Look Rock, TN (LR) in the Tennessee Valley Region (TVR) were apportioned using both organic tracer-based chemical mass balance (CMB) modeling and radiocarbon (14C) measurement and the results were compared. Eight sources were resolved by CMB, among which wood combustion (averaging 0.92 μg m−3) was the largest contributor to primary organic carbon (OC) concentrations, followed by gasoline exhaust (0.35 μg m−3), and diesel exhaust (0.18 μg m−3). The identified primary sources accounted for 43%, 71%, and 14% of measured OC at CH, MS, and LR, respectively. Contributions from the eight primary sources resolved by CMB could explain 107±10% of ambient elemental carbon (EC) concentrations, with diesel exhaust (66±32%) and wood combustion (37±33%) as the most important contributors. The fossil fractions in total carbon determined by 14C measurements were in reasonably good agreement with that in primary (OC+EC) carbon apportioned by CMB in the MS winter samples. The comparison between the 14C and CMB results revealed that contemporary sources dominated other OC in the TVR, especially in summertime (84% contemporary).  相似文献   

16.
ABSTRACT

Mobile sources are significant contributors to ambient PM2 5, accounting for 50% or more of the total observed levels in some locations. One of the important methods for resolving the mobile source contribution is through chemical mass balance (CMB) receptor modeling. CMB requires chemically speciated source profiles with known uncertainty to ensure accurate source contribution estimates. Mobile source PM profiles are available from various sources and are generally in the form of weight fraction by chemical species. The weight fraction format is commonly used, since it is required for input into the CMB receptor model. This paper examines the similarities and differences in mobile source PM2.5 profiles that contain data for elements, ions, elemental carbon (EC) and organic carbon (OC), and in some cases speciated organics (e.g., polycyclic aromatic hydrocarbons [PAHs]), drawn from four different sources.

Notable characteristics of the mass fraction data include variability (relative contributions of elements and ions) among supposedly similar sources and a wide range of average EC:OC ratios (0.60 ± 0.53 to 1.42 ± 2.99) for light-duty gasoline vehicles (LDGVs), indicating significant EC emissions from LDGVs in some cases. For diesel vehicles, average EC:OC ratios range from 1.09 ± 2.66 to 3.54 ± 3.07. That different populations of the same class of emitters can show considerable variability suggests caution should be exercised when selecting and using profiles in source apportionment studies.  相似文献   

17.
A sensitivity analysis was conducted to characterize sources of uncertainty in results of a molecular marker source apportionment model of ambient particulate matter using mobile source emissions profiles obtained as part of the Gasoline/Diesel PM Split Study. A chemical mass balance (CMB) model was used to determine source contributions to samples of fine particulate matter (PM2.5) collected over 3 weeks at two sites in the Los Angeles area in July 2001. The ambient samples were composited for organic compound analysis by the day of the week to investigate weekly trends in source contributions. The sensitivity analysis specifically examined the impact of the uncertainty in mobile source emissions profiles on the CMB model results. The key parameter impacting model sensitivity was the source profile for gasoline smoker vehicles. High-emitting gasoline smoker vehicles with visible plumes were seen to be a significant source of PM in the area, but use of different measured profiles for smoker vehicles in the model gave very different results for apportionment of gasoline, diesel, and smoker vehicle tailpipe emissions. In addition, the contributions of gasoline and diesel emissions to total ambient PM varied as a function of the site and the day of the week.  相似文献   

18.
This paper presents results from positive matrix factorization (PMF) of organic molecular marker data to investigate the sources of organic carbon (OC) in Pittsburgh, Pennsylvania. PMF analysis of 21 different combinations of input species found essentially the same seven factors with distinctive source-class-specific groupings of molecular markers. To link factors with source classes we directly compare PMF factor profiles with actual source profiles. Six of the PMF factors appear related to primary emissions from sources such as motor vehicles, biomass combustion, and food cooking. Each primary factor contributed between 5% and 10% of the annual-average OC with the exception of the cooking related factor which contributed 20% of the OC. However, the contribution of the cooking factor was sensitive to the specific combinations of input species. PMF could not differentiate between gasoline and diesel emissions, but the aggregate contribution of primary emissions from these two source classes is estimated to be less than 10% of the annual-average OC. One factor appears related to secondary organic aerosol based on its substantial contribution to biogenic oxidation products. This secondary factor contributed more than 50% of the summertime average OC. Reasonable agreement was observed between the PMF results and those of a previously published chemical mass balance (CMB) analysis of the same molecular marker dataset. Individual PMF factors are correlated with specific CMB sources, but systematic biases exist between the two estimates. These biases were generally within the uncertainty of the two estimates, but there is also evidence that PMF is not cleanly differentiating between source classes.  相似文献   

19.
Abstract

A sensitivity analysis was conducted to characterize sources of uncertainty in results of a molecular marker source apportionment model of ambient particulate matter using mobile source emissions profiles obtained as part of the Gasoline/Diesel PM Split Study. A chemical mass balance (CMB) model was used to determine source contributions to samples of fine particulate matter (PM2.5) collected over 3 weeks at two sites in the Los Angeles area in July 2001. The ambient samples were composited for organic compound analysis by the day of the week to investigate weekly trends in source contributions. The sensitivity analysis specifically examined the impact of the uncertainty in mobile source emissions profiles on the CMB model results. The key parameter impacting model sensitivity was the source profile for gasoline smoker vehicles. High-emitting gasoline smoker vehicles with visible plumes were seen to be a significant source of PM in the area, but use of different measured profiles for smoker vehicles in the model gave very different results for apportionment of gasoline, diesel, and smoker vehicle tailpipe emissions. In addition, the contributions of gasoline and diesel emissions to total ambient PM varied as a function of the site and the day of the week.  相似文献   

20.
Diluted exhaust from selected military aircraft ground-support equipment (AGE) was analyzed for particulate mass, elemental carbon (EC) and organic carbon (OC), SO4(2-), and size distributions. The experiments occurred at idle and load conditions and utilized a chassis dynamometer. The selected AGE vehicles operated on gasoline, diesel, and JP-8. These military vehicles exhibited concentrations, size distributions, and emission factors in the same range as those reported for nonmilitary vehicles. The diesel and JP-8 emission rates for PM ranged from 0.092 to 1.1 g/kg fuel. The EC contributed less and the OC contributed more to the particulate mass than reported in recent studies of vehicle emissions. Overall, the particle size distribution varied significantly with engine condition, with the number of accumulation mode particles and the count median diameter (CMD) increasing as engine load increased. The SO4(2-) analyses showed that the distribution of SO4(2-) mass mirrored the distribution of particle mass.  相似文献   

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