Source characterization of ambient fine particles at multiple sites in the Seattle area

To identify major PM_2.5 (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 PM_2.5 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 PM_2.5 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 PM_2.5 mass concentrations at all of the monitoring sites except for the residential Lake Forest site, where wood smoke contributed the most PM_2.5 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 PM_2.5 sources shows that the spatial distributions of several PM_2.5 sources were heterogeneous within a given air shed.     

Chemical mass balance source apportionment for combined PM2.5 measurements from U.S. non-urban and urban long-term networks

The Minnesota Particulate Matter 2.5 (PM_2.5) Source Apportionment Study was undertaken to explore the utility of PM_2.5 mass, element, ion, and carbon measurements from long-term speciation networks for pollution source attribution. Ambient monitoring data at eight sites across the state were retrieved from the archives of the Interagency Monitoring of Protected Visual Environments (IMPROVE) and the Speciation Trends Network (STN; part of the Chemical Speciation Network [CSN]) and analyzed by an Effective Variance – Chemical Mass Balance (EV-CMB) receptor model with region-specific geological source profiles developed in this study. PM_2.5 was apportioned into contributions of fugitive soil dust, calcium-rich dust, taconite (low grade iron ore) dust, road salt, motor vehicle exhaust, biomass burning, coal-fired utility, and secondary aerosol. Secondary sulfate and nitrate contributed strongly (49–71% of PM_2.5) across all sites and was dominant (≥60%) at IMPROVE sites. Vehicle exhausts accounted for 20–70% of the primary PM_2.5 contribution, largely exceeding the proportion in the primary PM_2.5 emission inventory. The diesel exhaust contribution was separable from the gasoline engine exhaust contribution at the STN sites. Higher detection limits for several marker elements in the STN resulted in non-detectable coal-fired boiler contributions which were detected in the IMPROVE data. Despite the different measured variables, analytical methods, and detection limits, EV-CMB results from a nearby IMPROVE-STN non-urban/urban sites showed similar contributions from regional sources – including fugitive dust and secondary aerosol. Seasonal variations of source contributions were examined and extreme PM_2.5 episodes were explained by both local and regional pollution events.     

Sources of fine particles in the South Coast area,California

PM_2.5 (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 PM_2.5 sources as a part of the State Implementation Plan development. Eight and nine major PM_2.5 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 PM_2.5 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.     

The stable carbon isotope composition of PM2.5 and PM10 in Mexico City Metropolitan Area air

The sources and distribution of carbon in ambient suspended particles (PM_2.5 and PM₁₀) of Mexico City Metropolitan Area (MCMA) air were traced using stable carbon isotopes (¹³C/¹²C). Tested potential sources included rural and agricultural soils, gasoline and diesel, liquefied-petroleum gas, volcanic ash, and street dust. The complete combustion of LP gas, diesel and gasoline yielded the lightest δ¹³C values (?27 to ?29‰ vs. PDB), while street dust (PM₁₀) represented the isotopically heaviest endmember (?17‰). The δ¹³C values of rural soils from four geographically separated sites were similar (?20.7 ± 1.5‰). δ¹³C values of particles and soot from diesel and gasoline vehicle emissions and agricultural soils varied between ?23 and ?26‰. Ambient PM samples collected in November of 2000, and March and December of 2001 at three representative receptor sites of industrial, commercial and residential activities had a δ¹³C value centered around ?25.1‰ in both fractions, resulting from common carbon sources. The predominant carbon sources to MCMA atmospheric particles were hydrocarbon combustion (diesel and/or gasoline) and particles of geological origin. The significantly depleted δ¹³C values from the industrial site reflect the input of diesel combustion by mobile and point source emissions. Based on stable carbon isotope mass balance, the carbon contribution of geological sources at the commercial and residential sites was approximately 73% for the PM₁₀ fraction and 54% for PM_2.5. Although not measured in this study, biomass-burning emissions from nearby forests are an important carbon source characterized by isotopically lighter values (?29‰), and can become a significant contributor (67%) of particulate carbon to MCMA air under the prevalence of southwesterly winds. Alternative sources of these ¹³C-depleted particles, such as cooking fires and municipal waste incineration, need to be assessed. Results show that stable carbon isotope measurements are useful for distinguishing between some carbon sources in suspended particles to MCMA air, and that wind direction has an impact on the distribution of carbon sources in this basin.     

Apportionment of Ambient Primary and Secondary Fine Particulate Matter during a 2001 Summer Intensive Study at the CMU Supersite and NETL Pittsburgh Site

Abstract

Gaseous and particulate pollutant concentrations associated with five samples per day collected during a July 2001 summer intensive study at the Pittsburgh Carnegie Mellon University (CMU) Supersite were used to apportion fine particulate matter (PM_2.5) into primary and secondary contributions using PMF2. Input to the PMF2 analysis included the concentrations of PM_2.5 nonvolatile and semivolatile organic material, elemental carbon (EC), ammonium sulfate, trace element components, gas-phase organic material, and NO_x, NO₂, and O₃ concentrations. A total of 10 factors were identified. These factors are associated with emissions from various sources and facilities including crustal material, gasoline combustion, diesel combustion, and three nearby sources high in trace metals. In addition, four secondary sources were identified, three of which were associated with secondary products of local emissions and were dominated by organic material and one of which was dominated by secondary ammonium sulfate transported to the CMU site from the west and southwest. The three largest contributors to PM_2.5 were sec ondary transported material (dominated by ammonium sulfate) from the west and southwest (49%), secondary material formed during midday photochemical processes (24%), and gasoline combustion emissions (11%). The other seven sources accounted for the remaining 16% of the PM_2.5. Results obtained at the CMU site were comparable to results previously reported at the National Energy Technology Laboratory (NETL), located approximately 18 km south of downtown Pittsburgh. The major contributor at both sites was material transported from the west and southwest. Some difference in nearby sources could be attributed to meteorology as evaluated by HYSPLIT model back-trajectory calculations. These findings are consistent with the majority of the secondary ammonium sulfate in the Pittsburgh area being the result of contributions from distant transport, and thus decoupled from local activity involving organic pollutants in the metropolitan area. In contrast, the major local secondary sources were dominated by organic material.     

On-road measurement of fine particle and nitrogen oxide emissions from light- and heavy-duty motor vehicles

An updated assessment of fine particle emissions from light- and heavy-duty vehicles is needed due to recent changes to the composition of gasoline and diesel fuel, more stringent emission standards applying to new vehicles sold in the 1990s, and the adoption of a new ambient air quality standard for fine particulate matter (PM_2.5) in the United States. This paper reports the measurement of emissions from vehicles in a northern California roadway tunnel during summer 1997. Separate measurements were made of uphill traffic in two tunnel bores: one bore carried both light-duty vehicles and heavy-duty diesel trucks, and the second bore was reserved for light-duty vehicles. Ninety-eight percent of the light-duty vehicles were gasoline-powered. In the tunnel, heavy-duty diesel trucks emitted 24, 37, and 21 times more fine particle, black carbon, and sulfate mass per unit mass of fuel burned than light-duty vehicles. Heavy-duty diesel trucks also emitted 15–20 times the number of particles per unit mass of fuel burned compared to light-duty vehicles. Fine particle emissions from both vehicle classes were composed mostly of carbon; diesel-derived particulate matter contained more black carbon (51±11% of PM_2.5 mass) than did light-duty fine particle emissions (33±4%). Sulfate comprised only 2% of total fine particle emissions for both vehicle classes. Sulfate emissions measured in this study for heavy-duty diesel trucks are significantly lower than values reported in earlier studies conducted before the introduction of low-sulfur diesel fuel. This study suggests that heavy-duty diesel vehicles in California are responsible for nearly half of oxides of nitrogen emissions and greater than three-quarters of exhaust fine particle emissions from on-road motor vehicles.     

Particulate matter speciation profiles for light-duty gasoline vehicles in the United States

Representative profiles for particulate matter particles less than or equal to 2.5 µm (PM_2.5) are developed from the Kansas City Light-Duty Vehicle Emissions Study for use in the U.S. Environmental Protection Agency (EPA) vehicle emission model, the Motor Vehicle Emission Simulator (MOVES), and for inclusion in the EPA SPECIATE database for speciation profiles. The profiles are compatible with the inputs of current photochemical air quality models, including the Community Multiscale Air Quality Aerosol Module Version 6 (AE6). The composition of light-duty gasoline PM_2.5 emissions differs significantly between cold start and hot stabilized running emissions, and between older and newer vehicles, reflecting both impacts of aging/deterioration and changes in vehicle technology. Fleet-average PM_2.5 profiles are estimated for cold start and hot stabilized running emission processes. Fleet-average profiles are calculated to include emissions from deteriorated high-emitting vehicles that are expected to continue to contribute disproportionately to the fleet-wide PM_2.5 emissions into the future. The profiles are calculated using a weighted average of the PM_2.5 composition according to the contribution of PM_2.5 emissions from each class of vehicles in the on-road gasoline fleet in the Kansas City Metropolitan Statistical Area. The paper introduces methods to exclude insignificant measurements, correct for organic carbon positive artifact, and control for contamination from the testing infrastructure in developing speciation profiles. The uncertainty of the PM_2.5 species fraction in each profile is quantified using sampling survey analysis methods. The primary use of the profiles is to develop PM_2.5 emissions inventories for the United States, but the profiles may also be used in source apportionment, atmospheric modeling, and exposure assessment, and as a basis for light-duty gasoline emission profiles for countries with limited data.

Implications: PM_2.5 speciation profiles were developed from a large sample of light-duty gasoline vehicles tested in the Kansas City area. Separate PM_2.5 profiles represent cold start and hot stabilized running emission processes to distinguish important differences in chemical composition. Statistical analysis was used to construct profiles that represent PM_2.5 emissions from the U.S. vehicle fleet based on vehicles tested from the 2005 calendar year Kansas City metropolitan area. The profiles have been incorporated into the EPA MOVES emissions model, as well as the EPA SPECIATE database, to improve emission inventories and provide the PM_2.5 chemical characterization needed by CMAQv5.0 for atmospheric chemistry modeling.     

A Fuel-Based Assessment of Off-Road Diesel Engine Emissions

ABSTRACT

The use of diesel engines in off-road applications is a significant source of nitrogen oxides (NO_x) and particulate matter (PM₁₀). Such off-road applications include railroad locomotives, marine vessels, and equipment used for agriculture, construction, logging, and mining. Emissions from these sources are only beginning to be controlled. Due to the large number of these engines and their wide range of applications, total activity and emissions from these sources are uncertain. A method for estimating the emissions from off-road diesel engines based on the quantity of diesel fuel consumed is presented. Emission factors are normalized by fuel consumption, and total activity is estimated by the total fuel consumed.

Total exhaust emissions from off-road diesel equipment (excluding locomotives and marine vessels) in the United States during 1996 have been estimated to be 1.2 × 10⁹ kg NO_x and 1.2 x 10⁸ kg PM₁₀. Emissions estimates published by the U.S. Environmental Protection Agency are 2.3 times higher for both NO_x and exhaust PM₁₀ emissions than estimates based directly on fuel consumption. These emissions estimates disagree mainly due to differences in activity estimates, rather than to differences in the emission factors. All current emission inventories for off-road engines are uncertain because of the limited in-use emissions testing that has been performed on these engines. Regional- and state-level breakdowns in diesel fuel consumption by off-road mobile sources are also presented. Taken together with on-road measurements of diesel engine emissions, results of this study suggest that in 1996, off-road diesel equipment (including     

The Southeastern Aerosol Research and Characterization Study: Part II. Filter-Based Measurements of Fine and Coarse Particulate Matter Mass and Composition

Abstract

The Southeastern Aerosol Research and Characterization Study (SEARCH) was implemented in 1998–1999 to provide data and analyses for the investigation of the sources, chemical speciation, and long-term trends of fine particulate matter (PM_2.5) and coarse particulate matter (PM_10–2.5) in the Southeastern United States. This work is an initial analysis of 5 years (1999–2003) of filter-based PM_2.5 and PM_10–2.5 data from SEARCH. We find that annual PM_2.5 design values were consistently above the National Ambient Air Quality Standards (NAAQS) 15 µg/m³ annual standard only at monitoring sites in the two largest urban areas (Atlanta, GA, and North Birmingham, AL). Other sites in the network had annual design values below the standard, and no site had daily design values above the NAAQS 65 µg/m³ daily standard. Using a particle composition monitor designed specifically for SEARCH, we found that volatilization losses of nitrate, ammonium, and organic carbon must be accounted for to accurately characterize atmospheric particulate matter. In particular, the federal reference method for PM_2.5 underestimates mass by 3–7% as a result of these volatilization losses. Organic matter (OM) and sulfate account for ≥60% of PM_2.5 mass at SEARCH sites, whereas major metal oxides (MMO) and unidentified components (“other”) account for ≥80% of PM_10–2.5 mass. Limited data suggest that much of the unidentified mass in PM_10–2.5 may be OM. For paired comparisons of urban-rural sites, differences in PM_2.5 mass are explained, in large part, by higher OM and black carbon at the urban site. For PM₁₀, higher urban concentrations are explained by higher MMO and “other.” Annual means for PM_2.5 and PM_10–2.5 mass and major components demonstrate substantial declines at all of the SEARCH sites over the 1999–2003 period (10–20% in the case of PM_2.5, dominated by 14–20% declines in sulfate and 11–26% declines in OM, and 14–25% in the case of PM_10–2.5, dominated by 17–30% declines in MMO and 14–31% declines in “ other”). Although declining national emissions of sulfur dioxide and anthropogenic carbon may account for a portion of the observed declines, additional investigation will be necessary to establish a quantitative assessment, especially regarding trends in local and regional emissions, primary carbon emissions, and meteorology.     

Effect of SME biodiesel blends on PM2.5 emission from a heavy-duty engine

To explore the effect of biodiesel and sulfur content on PM_2.5 emissions, engine dynamometer tests were performed on a Euro II engine to compare the PM_2.5 emissions from four fuels: two petroleum diesel fuels with sulfur contents of 50 and 100 ppm respectively, and two B20 fuels in which soy methyl ester (SME) biodiesel was added to each of the above mentioned petroleum diesel fuels (v/v: 80%/20% for petroleum diesel and SME respectively). Gaseous pollutants and PM_2.5 emissions were sampled with an AVL AMA4000 and Model 130 High-Flow Impactor (MSP Corp). Measurements were made of the PM_2.5 mass, organic carbon (OC), elemental carbon (EC) and the water-soluble ion distribution. The results showed that PM_2.5 emissions decreased with lower sulfur content or blending with SME biodiesel, and the decrease would be more by applying both two methods together. Particles of approximately 0.13 μm contributed 48–83% of PM_2.5 emissions. The impact of sulfur content on this percentage was different for low and high engine speed. The majority of PM_2.5 was comprised of OC and EC, and the carbon emission rate had the same trend as PM_2.5. Since the EC abatement of B20 was larger than OC, the OC/EC ratio of B20 was always larger than that of petroleum diesel. For petroleum diesel, the OC/EC increased with sulfur content, which was not the case for B20. The SO₄^2? had highest emission rate in the water-soluble ions of PM.     

Calibration and Certification of Audit Devices for Transmissometers

Abstract

Speciated fine particulate matter (PM_2.5) 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 PM_2.5 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 (North–brook, Indianapolis, and Bondville), steel/manufacturing with iron (Northbrook), industrial zinc (North–brook, 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 PM_2.5 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 PM_2.5 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.     

Sensitivity of Source Apportionment of Urban Particulate Matter to Uncertainty in Motor Vehicle Emissions Profiles

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 (PM_2.5) 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.     

Total versus urban: Well-to-wheels assessment of criteria pollutant emissions from various vehicle/fuel systems

The potential impact on the environment of alternative vehicle/fuel systems needs to be evaluated, especially with respect to human health effects resulting from air pollution. We used the Greenhouse gases, Regulated Emissions, and Energy use in Transportation (GREET) model to examine the well-to-wheels (WTW) emissions of five criteria pollutants (VOCs, NO_x, PM₁₀, PM_2.5, and CO) for nine vehicle/fuel systems: (1) conventional gasoline vehicles; (2) conventional diesel vehicles; (3) ethanol (E85) flexible-fuel vehicles (FFVs) fueled with corn-based ethanol; (4) E85 FFVs fueled with switchgrass-based ethanol; (5) gasoline hybrid vehicles (HEVs); (6) diesel HEVs; (7) electric vehicles (EVs) charged using the average U.S. generation mix; (8) EVs charged using the California generation mix; and (9) hydrogen fuel cell vehicles (FCVs). Pollutant emissions were separated into total and urban emissions to differentiate the locations of emissions, and emissions were presented by sources. The results show that WTW emissions of the vehicle/fuel systems differ significantly, in terms of not only the amounts but also with respect to locations and sources, both of which are important in evaluating alternative vehicle/fuel systems. E85 FFVs increase total emissions but reduce urban emissions by up to 30% because the majority of emissions are released from farming equipment, fertilizer manufacture, and ethanol plants, all of which are located in rural areas. HEVs reduce both total and urban emissions because of the improved fuel economy and lower emissions. While EVs significantly reduce total emissions of VOCs and CO by more than 90%, they increase total emissions of PM₁₀ and PM_2.5 by 35–325%. However, EVs can reduce urban PM emissions by more than 40%. FCVs reduce VOCs, CO, and NO_x emissions, but they increase both total and urban PM emissions because of the high process emissions that occur during hydrogen production. This study emphasizes the importance of specifying a thorough life-cycle emissions inventory that can account for both the locations and sources of the emissions to assist in achieving a fair comparison of alternative vehicle/fuel options in terms of their environmental impacts.     

Determination of sources of fine particles in different ambient atmospheres in South Korea using a chemical mass balance model

Abstract

To determine the sources of particulate matter less than 2.5?μm (PM_2.5 in different ambient atmospheres (urban, roadside, industrial, and rural sites), the chemical components of PM_2.5 such as ions (Cl^-, NO₃^-, SO₄^2-, NH₄⁺, Na⁺, K⁺, Ca²⁺, and Mg²⁺), carbonaceous species, and elements (Al, As, Ba, Cd, Cu, Fe, Mn, Ni, Pb, Se, V, and Zn) were measured. The average mass concentrations of PM_2.5 at the urban, roadside, industrial, and rural sites were 31.5?±?14.8, 31.6?±?22.3, 31.4?±?16.0, and 25.8?±?12.4?μg/m³, respectively. Except for secondary ammonium sulfate and ammonium nitrate, the model results showed that the traffic source (i.e., the sum of gasoline and diesel vehicle sources) was the most dominant source of PM_2.5 (17.1%) followed by biomass burning (13.8%) at the urban site. The major primary sources of PM_2.5 were consistent with the site characteristics (diesel vehicle source at the roadside site, coal-fired plants at the industrial site, and biomass burning at the rural site). Seasonal data from the urban site suggested that ammonium sulfate and ammonium nitrate were the most dominant sources of PM_2.5 during all seasons. Further, the contribution of road dust source to PM_2.5 increased during spring and fall seasons. We conclude that the determination of the major PM_2.5 sources is useful for establishing efficient control strategies for PM_2.5 in different regions and seasons.     

PM2.5 characterization for time series studies: Organic molecular marker speciation methods and observations from daily measurements in Denver

Particulate matter less than 2.5 microns in diameter (PM_2.5) has been shown to have a wide range of adverse health effects and consequently is regulated in accordance with the US-EPA's National Ambient Air Quality Standards. PM_2.5 originates from multiple primary sources and is also formed through secondary processes in the atmosphere. It is plausible that some sources form PM_2.5 that is more toxic than PM_2.5 from other sources. Identifying the responsible sources could provide insight into the biological mechanisms causing the observed health effects and provide a more efficient approach to regulation. This is the goal of the Denver Aerosol Sources and Health (DASH) study, a multi-year PM_2.5 source apportionment and health study.The first step in apportioning the PM_2.5 to different sources is to determine the chemical make-up of the PM_2.5. This paper presents the methodology used during the DASH study for organic speciation of PM_2.5. Specifically, methods are covered for solvent extraction of non-polar and semi-polar organic molecular markers using gas chromatography–mass spectrometry (GC–MS). Vast reductions in detection limits were obtained through the use of a programmable temperature vaporization (PTV) inlet along with other method improvements. Results are presented for the first 1.5 years of the DASH study revealing seasonal and source-related patterns in the molecular markers and their long-term correlation structure. Preliminary analysis suggests that point sources are not a significant contributor to the organic molecular markers measured at our receptor site. Several motor vehicle emission markers help identify a gasoline/diesel split in the ambient data. Findings show both similarities and differences when compared with other cities where similar measurements and assessments have been made.     

Particulate Emissions from Construction Activities

Abstract

Although it has long been recognized that road and building construction activity constitutes an important source of particulate matter (PM) emissions throughout the United States, until recently only limited research has been directed to its characterization. This paper presents the results of PM₁₀ and PM_2.5 (particles ≤10 μm and ≤2.5 μm in aerodynamic diameter, respectively) emission factor development from the onsite testing of component operations at actual construction sites during the period 1998 –2001. Much of the testing effort was directed at earthmoving operations with scrapers, because earthmoving is the most important contributor of PM emissions across the construction industry. Other sources tested were truck loading and dumping of crushed rock and mud and dirt carryout from construction site access points onto adjacent public paved roads. Also tested were the effects of watering for control of scraper travel routes and the use of paved and graveled aprons at construction site access points for reducing mud and dirt carryout. The PM₁₀ emissions from earthmoving were found to be up to an order of magnitude greater than predicted by AP-42 emission factors drawn from other industries. As expected, the observed PM_2.5:PM₁₀ emission factor ratios reflected the relative importance of the vehicle exhaust and the resuspended dust components of each type of construction activity. An unexpected finding was that PM_2.5 emissions from mud and dirt carryout were much less than anticipated. Finally, the control efficiency of watering of scraper travel routes was found to closely follow a bilinear moisture model.     

PM2.5 Emissions from Aluminum Smelters: Coefficients and Environmental Impact

ABSTRACT

From 2004 to 2009, aiming to better understand implications for its smelters, Rio Tinto Alcan conducted a detailed study of PM_2.5 and PM₁₀ (particulate matter [PM] ≤ 2.5 and 10 μm in aerodynamic diameter, respectively) in its facilities. This involved a two-level study: part 1, emission quantification; and part 2, assessment of aluminum smelter contribution to the surrounding environment. In the first part, U.S. Environmental Protection Agency Other Test Method (OTM) OTM27 and OTM28 are assessed as relevant and efficient methods for measuring fine particle emissions from aluminum smelter stacks. Rio Tinto Alcan has also developed a safe and robust method called CYCLEX to measure PM_2.5 and condensable particulate matter (CPM) at the roof vents of potrooms. This work aims to determine the PM_2.5 emission coefficients of 17, 55, and 417 g·t^?1 of aluminum produced (including CPM) in anode baking furnace exhaust (fume treatment center), at potroom scrubber stacks (gas treatment centers), and at potroom roof vents, respectively. Results indicate that roof vents are the primary PM_2.5 emitters (85% of all smelter emissions) and that 71% of all smelter PM_2.5 comes from CPM. In the second part, preliminary inorganic speciation studies are conducted by scanning electron microscopy–energy-dispersive X-ray analysis and by isotopic ratios to track smelter emissions to their surrounding environment. This paper releases the first speciation results for an aluminum smelter, and the preliminary isotopic ratio study indicates a 3% impact in terms of PM_2.5 emissions for a representative smelter in an urban area.

IMPLICATIONS Aluminum smelters tend to continuously improve their competitiveness by incrementally increasing production. In this context, assessing the effect of major contaminants is overriding, and ambient air modeling is often the preferred way to do so. Fine particles fit this category, and the primary aluminum industry needs to accurately know their emission factors to obtain representative modeling. Moreover, not all aluminum smelters have a method to measure PM_2.5 at roof vents, the primary emission outlets. Therefore, this paper describes the first-rate PM_2.5 measurement methods for aluminum smelter roof vents without down-comers. It also provides insight for environmental managers for tracking PM_2.5 emissions in plant surroundings.     

Emissions profile from new and in-use handheld, 2-stroke engines

The objective of this study was to characterize exhaust emissions from a series of handheld, 2-stroke small engines. A total of 23 new and used engines from model years 1981–2003 were studied; these engines spanned three phases of emission control (pre-control, phase-1, phase-2). Measured emissions included carbon monoxide (CO), carbon dioxide (CO₂), nitrogen oxides (NO_x), hydrocarbons (HC), fine particulate matter (PM_2.5), and sulfur dioxide (SO₂). Emissions reductions in CO (78%) and HC (52%) were significant between pre-control and phase-2 engines. These reductions can be attributed to improvements in engine design, reduced scavenging losses, and implementation of catalytic exhaust control. Total hydrocarbon emissions were strongly correlated with fuel consumption rates, indicating varying degrees of scavenging losses during the intake/exhaust stroke. The use of a reformulated gasoline containing 10% ethanol resulted in a 15% decrease in HC and a 29% decrease in CO emissions, on average. Increasing oil content of 2-stroke engine fuels results in a substantial increase of PM_2.5 emissions as well as smaller increases in HC and CO emissions. Results from this study enhance existing emission inventories and appear to validate predicted improvements to ambient air quality through implementation of new phase-2 handheld emission standards.     

PM2.5 source apportionment with organic markers in the Southeastern Aerosol Research and Characterization (SEARCH) study

Positive matrix factorization (PMF) and effective variance (EV) solutions to the chemical mass balance (CMB) were applied to PM_2.5 (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 PM_2.5 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 PM_2.5, followed by biomass burning (21–24%) and motor vehicle exhaust (9–24%) at both sites, with 4–6% of PM_2.5 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 PM_2.5 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 PM_2.5 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.     

Fine Particulate Matter Emissions Inventories: Comparisons of Emissions Estimates with Observations from Recent Field Programs

Abstract

Emissions inventories of fine particulate matter (PM_2.5) 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 PM_2.5 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 PM_2.5 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 PM_2.5 are substantial. Similar uncertainties exist for ammonia emissions. Because of these uncertainties, the design of PM_2.5 control strategies should be based on inventories that have been refined by a combination of bottom-up and top-down methods.