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.     

The Southeastern Aerosol Research and Characterization Study: Part II. Filter-based measurements of fine and coarse particulate matter mass and composition

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 (PM2.5) and coarse particulate matter (PM10-2.5) in the Southeastern United States. This work is an initial analysis of 5 years (1999-2003) of filter-based PM2.5 and PM10-2.5 data from SEARCH. We find that annual PM2.5 design values were consistently above the National Ambient Air Quality Standards (NAAQS) 15 microg/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 microg/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 PM2.5 underestimates mass by 3-7% as a result of these volatilization losses. Organic matter (OM) and sulfate account for approximately 60% of PM2.5 mass at SEARCH sites, whereas major metal oxides (MMO) and unidentified components ("other") account for > or = 80% of PM10-2.5 mass. Limited data suggest that much of the unidentified mass in PM10-2.5 may be OM. For paired comparisons of urban-rural sites, differences in PM2.5 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 PM2.5 and PM10-2.5 mass and major components demonstrate substantial declines at all of the SEARCH sites over the 1999-2003 period (10-20% in the case of PM2.5, dominated by 14-20% declines in sulfate and 11-26% declines in OM, and 14-25% in the case of PM10-2.5, 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.     

Historical trends in the mass and chemical species concentrations of coarse particulate matter in the Los Angeles Basin and relation to sources and air quality regulations

To assess the impact of past, current and proposed air quality regulations on coarse particulate matter (CPM), the concentrations of CPM mass and its chemical constituents were examined in the Los Angeles Basin from 1986 to 2009 using PM data acquired from peer-reviewed journals and regulatory agency database. PM10 mass levels decreased by approximately half from 1988 to 2009 at the three sampling sites examined- located in downtown Los Angeles, Long Beach and Riverside. Annual CPM mass concentrations were calculated from the difference between daily PM10 and PM2.5 from 1999 to 2009. High CPM episodes driven by high wind speed/stagnant condition caused year-to-year fluctuations in the 99th/98th percentile CPM levels. The reductions of average CPM levels were lower than those of PM10 in the same period, therefore the decrease of PM10 level was mainly driven by reductions in the emission levels of PM2.5 (or fine) particles, as demonstrated by the higher annual reduction of average PM2.5 (0.92 microg/m3) compared with CPM (0.39 microg/m3) from 1999 to 2009 in downtown Los Angeles despite their comparable concentrations. This is further confirmed by the significant decrease of Ni, Cr, V and EC in the coarse fraction after 1995. On the other hand, the levels of several inorganic ions (sulfate, chloride and to a lesser extent nitrate) remained comparable. From 1995 to 2008, levels of Cu, a tracer of brake wear, either remained similar or decreased at a smaller rate compared with elements of combustion origins. This differential reduction of CPM components suggests that past and current regulations may have been more effective in reducing fugitive dust (Al, Fe and Si) and combustion emissions (Ni, Cr, V, and EC) rather than CPM from vehicular abrasion (Cu) and inorganic ions (NO3(-), SO4(2-) and Cl(-)) in urban areas. Implications: Limited information is currently available to provide the scientific basis for understanding the sources and physical and chemical variations of CPM, and their relations to air quality regulations and adverse health effects. This study investigates the historical trends of CPM mass and its chemical components in the Los Angeles Basin to advance our understanding on the impact of past and current air quality regulations on the coarse fraction of PM. The results of this study will aid policy makers to design more targeted regulations to control CPM sources to ensure substantial protection of public health from CPM exposure. Supplemental Materials: Supplemental materials are available for this article. Go to the publisher's online edition of the Journal of the Air & Waste Management Association for (1) details of the sampling sites and (2) the daily concentrations of high CPM/PM10 episodes.     

Monitoring of PM10 and PM2.5 around primary particulate anthropogenic emission sources

Investigations on the monitoring of ambient air levels of atmospheric particulates were developed around a large source of primary anthropogenic particulate emissions: the industrial ceramic area in the province of Castelló (Eastern Spain). Although these primary particulate emissions have a coarse grain-size distribution, the atmospheric transport dominated by the breeze circulation accounts for a grain-size segregation, which results in ambient air particles occurring mainly in the 2.5–10 μm range. The chemical composition of the ceramic particulate emissions is very similar to the crustal end-member but the use of high Al, Ti and Fe as tracer elements as well as a peculiar grain-size distribution in the insoluble major phases allow us to identify the ceramic input in the bulk particulate matter. PM2.5 instead of PM10 monitoring may avoid the interference of crustal particles without a major reduction in the secondary anthropogenic load, with the exception of nitrate. However, a methodology based in PM2.5 measurement alone is not adequate for monitoring the impact of primary particulate emissions (such as ceramic emissions) on air quality, since the major ambient air particles derived from these emissions are mainly in the range of 2.5–10 μm. Consequently, in areas characterised by major secondary particulate emissions, PM2.5 monitoring should detect anthropogenic particulate pollutants without crustal particulate interference, whereas PM10 measurements should be used in areas with major primary anthropogenic particulate emissions.     

Dilution-based emissions sampling from stationary sources: Part 1--Compact sampler methodology and performance

This paper presents the design and performance of a compact dilution sampler (CDS) for characterizing fine particle emissions from stationary sources. The sampler is described, along with the methodology adopted for its use. Dilution sampling has a number of advantages, including source emissions that are measured under conditions simulating stack gas entry and mixing in the ambient atmosphere. This is particularly important for characterizing the semivolatile species in effluents as a part of particulate emissions. The CDS characteristics and performance are given, along with sampling methodology. The CDS was compared with a reference dilution sampler. The results indicate that the two designs are comparable for tests on gas-fired units and a diesel electrical generator. The performance data indicate that lower detection limits can be achieved relative to current regulatory methods for particulate emissions. Test data for the fine particulate matter (PM2.5) emissions are provided for comparison with U.S. Environment Protection Agency (EPA) Conditional Test Method 040 for filterable particulate matter (FPM) and the EPA Method 202 for condensable particulate matter. This comparison showed important differences between methods, depending on whether a comparison is done between in situ FPM determinations or the sum of such values with condensable PM from liquid filled impingers chilled in an ice bath. These differences are interpretable in the light of semivolatile material present in the stack effluent and, in some cases, differences in detection and quantification limits. Determination of emissions from combustors using liquid fuels can be readily achieved using 1-hr sampling with the CDS. Emissions from gasfired combustors are very low, requiring careful attention to sample volumes. Sampling volumes corresponding with 6-hr operation were used for the combined mass and broad chemical speciation. Particular attention to dilution sampler operation with clean dilution air also is essential for gas-fired sources.     

Characterization of the fugitive particulate emissions from construction mud/dirt carryout

Although the fugitive dust associated with construction mud/dirt carryout can represent a substantial portion of the particulate matter (PM) emissions inventory in nonattainment 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 < or =10 and 2.5 microm 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 reentrained mud/dirt carryout.     

Characterization of ambient fine particles in the northwestern area and Anchorage, Alaska

Ambient PM2.5 (particulate matter less than 2.5 microm in aerodynamic diameter) in the northwestern United States and Alaska is dominated by carbonaceous compounds associated with wood burning and transportation sources. PM2.5 source characterization studies analyzing recent PM2.5 speciation data have not been previously reported for these areas. In this study, ambient PM2.5 speciation samples collected at two monitoring sites located in the northwestern area, Olympic Peninsula, WA, and Portland, OR, and one monitoring site located in Anchorage, AK, were characterized through source apportionments. Gasoline vehicle, secondary sulfate, and wood smoke were the largest sources of PM2.5 collected at the Anchorage, Olympic, and Portland monitoring sites, respectively. Secondary sulfates showed an April peak at Anchorage and a November peak at Portland that are likely related to the increased photochemical reaction and long-range transport in Anchorage and meteorological stagnation in Portland. Secondary nitrate at the Olympic site showed a weak summer high peak that could be caused by seasonal tourism in the national park. Backward trajectories suggested that the elevated aged sea salt concentrations at the Portland monitoring site could be regional transport of sea salt that passed through other contaminated air sheds along the coast. Oil combustion emissions that might originate from ships and ferries were observed at the Olympic monitoring site.     

Measurement, analysis, and modeling of fine particulate matter in eastern North Carolina

An analysis of fine particulate data in eastern North Carolina was conducted to investigate the impact of the hog industry and its emissions of ammonia into the atmosphere. The fine particulate data are simulated using ISORROPIA, an equilibrium thermodynamic model that simulates the gas and aerosol equilibrium of inorganic atmospheric species. The observational data analyses show that the major constituents of fine particulate matter (PM2.5) are organic carbon, elemental carbon, sulfate, nitrate, and ammonium. The observed PM2.5 concentration is positively correlated with temperature but anticorrelated with wind speed. The correlation between PM2.5 and wind direction at some locations suggests an impact of ammonia emissions from hog facilities on PM2.5 formation. The modeled results are in good agreement with observations, with slightly better agreement at urban sites than at rural sites. The predicted total inorganic particulate matter (PM) concentrations are within 5% of the observed values under conditions with median initial total PM species concentrations, median relative humidity (RH), and median temperature. Ambient conditions with high PM precursor concentrations, low temperature, and high RH appear to favor the formation of secondary PM.     

Informative Report

Abstract

Chemical composition and particle size data for particulate emissions from stationary sources are required for environmental health effect assessments, air chemistry studies and for air quality modeling investigations such as source apportionment. The Information presented In this paper is directed to those individuals concerned with these environmental Investigations. In this study, particulate emissions from a group of non-ferrous smelters have been physically and chemically characterized. Emission samples were collected at the baghouse outlets from smelter furnaces and at smelter acid plant stacks at three locations; a zinc, a lead, and a copper smelter.

Mass emission rate determinations were made by EPA reference methods. Cascade impactors were used to collect in-stack samples for particle size distribution measurements. Particulate samples for chemical characterization were collected on membrane filters for analysis by X-ray fluorescence spectroscopy. Development of measurement techniques required to determine the elemental composition of the total mass and sized fractions of the emission are discussed. Results of the tests at the three smelters include total mass and elemental emission rates, particle size distribution, and the elemental composition of the total particulate mass and of sized fractions from both the smelter furnaces and acid plants. The results obtained at the copper smelter may not be representative of the emissions at the many copper smelters where reverbatory furnaces have been replaced.     

Source profiles of particulate matter emissions from a pilot-scale boiler burning North American coal blends.

Recent awareness of suspected adverse health effects from ambient particulate matter (PM) emission has prompted publication of new standards for fine PM with aerodynamic diameter less than 2.5 microm (PM2.5). However, scientific data on fine PM emissions from various point sources and their characteristics are very limited. Source apportionment methods are applied to identify contributions of individual regional sources to tropospheric particulate concentrations. The existing industrial database developed using traditional source measurement techniques provides total emission rates only, with no details on chemical nature or size characteristics of particulates. This database is inadequate, in current form, to address source-receptor relationships. A source dilution system was developed for sampling and characterization of total PM, PM2.5, and PM10 (i.e., PM with aerodynamic diameter less than 10 pm) from residual oil and coal combustion. This new system has automatic control capabilities for key parameters, such as relative humidity (RH), temperature, and sample dilution. During optimization of the prototype equipment, three North American coal blends were burned using a 0.7-megawatt thermal (MWt) pulverized coal-fired, pilot-scale boiler. Characteristic emission profiles, including PM2.5 and total PM soluble acids, and elemental and carbon concentrations for three coal blends are presented. Preliminary results indicate that volatile trace elements such as Pb, Zn, Ti, and Se are preferentially enriched in PM2.5. PM2.5 is also more concentrated in soluble sulfates relative to total PM. Coal fly ash collected at the outlet of the electrostatic precipitator (ESP) contains about 85-90% PM10 and 30-50% PM2.5. Particles contain the highest elemental concentrations of Si and Al while Ca, Fe, Na, Ba, and K also exist as major elements. Approximately 4-12% of the materials exists as soluble sulfates in fly ash generated by coal blends containing 0.2-0.8% sulfur by mass. Source profile data for an eastern U.S. coal show good agreement with those reported from a similar study done in the United States. Based on the inadequacies identified in the initial sampling equipment, a new, plume-simulating fine PM measurement system with modular components for field use is being developed for determining coal combustion PM source profiles from utility boiler stacks.     

Sensitivity of source apportionment of urban particulate matter to uncertainty in motor vehicle emissions profiles

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.     

Apportionment of ambient primary and secondary fine particulate matter at the Pittsburgh National Energy Laboratory particulate matter characterization site using positive matrix factorization and a potential source contributions function analysis

Fine particulate matter (PM2.5) concentrations associated with 202 24-hr samples collected at the National Energy Technology Laboratory (NETL) particulate matter (PM) characterization site in south Pittsburgh from October 1999 through September 2001 were used to apportion PM2.5 into primary and secondary contributions using Positive Matrix Factorization (PMF2). Input included the concentrations of PM2.5 mass determined with a Federal Reference Method (FRM) sampler, semi-volatile PM2.5 organic material, elemental carbon (EC), and trace element components of PM2.5. A total of 11 factors were identified. The results of potential source contributions function (PSCF) analysis using PMF2 factors and HYSPLIT-calculated back-trajectories were used to identify those factors associated with specific meteorological transport conditions. The 11 factors were identified as being associated with emissions from various specific regions and facilities including crustal material, gasoline combustion, diesel combustion, and three nearby sources high in trace metals. Three sources associated with transport from coal-fired power plants to the southeast, a combination of point sources to the northwest, and a steel mill and associated sources to the west were identified. In addition, two secondary-material-dominated sources were identified, one was associated with secondary products of local emissions and one was dominated by secondary ammonium sulfate transported to the NETL site from the west and southwest. Of these 11 factors, the four largest contributors to PM2.5 were the secondary transported material (dominated by ammonium sulfate) (47%), local secondary material (19%), diesel combustion emissions (10%), and gasoline combustion emissions (8%). The other seven factors accounted for the remaining 16% of the PM2.5 mass. The findings are consistent with the major source of PM2.5 in the Pittsburgh area being dominated by ammonium sulfate from distant transport and so decoupled from local activity emitting organic pollutants in the metropolitan area. In contrast, the major local secondary sources are dominated by organic material.     

The need for ammonia abatement with respect to secondary PM reductions in Europe

In Europe, secondary particulate matter (PM) comprises 50% or more of PM 2.5. To reduce PM concentrations requires lowering precursor emissions. Since the 1980s, SO(2) emissions have decreased by more than 60%, while particle concentrations have decreased less. NO(x) and NH(3) emissions have decreased slightly. The role of ammonia in particle formation is addressed here. It is shown that secondary PM concentrations can only be effectively reduced if ammonia emissions are decreased in much the same way as those of SO(2) and NO(x).     

Comparison of speciation sampler and PC-BOSS fine particulate matter organic material results obtained in Lindon, Utah, during winter 2001-2002

The Particle Concentrator-Brigham Young University Organic Sampling System (PC-BOSS) has been previously verified as being capable of measuring total fine particulate matter (PM2.5), including semi-volatile species. The present study was conducted to determine if the simple modification of a commercial speciation sampler with a charcoal denuder followed by a filter pack containing a quartz filter and a charcoal-impregnated glass (CIG) fiber filter would allow for the measurement of total PM2.5, including semi-volatile organic material. Data were collected using an R&P (Rupprecht and Pastasnik Co., Inc.) Partisol Model 2300 speciation sampler; an R&P Partisol speciation sampler modified with a BOSS denuder, followed by a filter pack with a quartz and a CIG filter; a Met One spiral aerosol speciation sampler (SASS); and the PC-BOSS from November 2001 to March 2002 at a U.S. Environmental Protection Agency (EPA) Science to Achieve Results (STAR) sampling site in Lindon, UT. Total PM2.5 mass, ammonium nitrate (both nonvolatile and semi-volatile), ammonium sulfate, organic carbon (both non-volatile and semi-volatile), and elemental carbon were determined on a 24-hr basis. Results obtained with the individual samplers were compared to determine the capability of the modified R&P speciation sampler for measuring total PM2.5, including semi-volatile components. Data obtained with the modified speciation sampler agreed with the PC-BOSS results. Data obtained with the two unmodified speciation samplers were low by an average of 26% because of the loss of semi-volatile organic material from the quartz filter during sample collection.     

Receptor modeling application framework for particle source apportionment

Receptor models infer contributions from particulate matter (PM) source types using multivariate measurements of particle chemical and physical properties. Receptor models complement source models that estimate concentrations from emissions inventories and transport meteorology. Enrichment factor, chemical mass balance, multiple linear regression, eigenvector. edge detection, neural network, aerosol evolution, and aerosol equilibrium models have all been used to solve particulate air quality problems, and more than 500 citations of their theory and application document these uses. While elements, ions, and carbons were often used to apportion TSP, PM10, and PM2.5 among many source types, many of these components have been reduced in source emissions such that more complex measurements of carbon fractions, specific organic compounds, single particle characteristics, and isotopic abundances now need to be measured in source and receptor samples. Compliance monitoring networks are not usually designed to obtain data for the observables, locations, and time periods that allow receptor models to be applied. Measurements from existing networks can be used to form conceptual models that allow the needed monitoring network to be optimized. The framework for using receptor models to solve air quality problems consists of: (1) formulating a conceptual model; (2) identifying potential sources; (3) characterizing source emissions; (4) obtaining and analyzing ambient PM samples for major components and source markers; (5) confirming source types with multivariate receptor models; (6) quantifying source contributions with the chemical mass balance; (7) estimating profile changes and the limiting precursor gases for secondary aerosols; and (8) reconciling receptor modeling results with source models, emissions inventories, and receptor data analyses.     

Particulate emissions from U.S. Department of Defense artillery backblast testing

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 approximately 9 g of PM2.5 and 49 g of PM2.5 per firing. The average measured emission rates for PM1o 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.     

Development of a PM2 5 Emissions Inventory for the South Coast Air Basin

ABSTRACT

With the promulgation of a national PM_2.5 ambient air quality standard, it is important that PM_2.5 emissions inventories be developed as a tool for understanding the magnitude of potential PM2.5 violations. Current PM₁₀ inventories include only emissions of primary particulate matter (1 ^ï PM), whereas, based on ambient measurements, both PM₁₀ and PM2.5 emissions inventories will need to include sources of both 1^ï PM and secondary particulate matter (2^ï PM). Furthermore, the U. S. Environmental Protection Agency’s (EPA) current edition of AP-42 includes size distribution data for 1o PM that overestimate the PM_2.5 fraction of fugitive dust sources by at least a factor of 2 based on recent studies.

This paper presents a PM_2.5 emissions inventory developed for the South Coast Air Basin (SCAB) that for the first time includes both 1^ï PM and 2^ï PM. The former is calculated by multiplying PM₁₀ emissions estimates by the PM_2.5/PM₁₀ ratios for different sources. The latter is calculated from estimated emission rates of gas-phase aerosol precursor and gas to aerosol conversion rates consistent with the measured chemical composition of ambient PM_2.5 concentrations observed in the SCAB. The major finding of this PM_2.5 emissions inventory is that the ^2ï aerosol component is more than twice the ^1ï aerosol component, which may result in widely different control strategies being required for fine PM and coarse PM.     

Fine particulate matter emissions inventories: comparisons of emissions estimates with observations from recent field programs

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.s 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.     

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.     

Emission strength validation using four-dimensional data assimilation: application to primary aerosol and precursors to ozone and secondary aerosol.

Three-dimensional air quality models (AQMs) represent the most powerful tool to follow the dynamics of air pollutants at urban and regional scales. Current AQMs can account for the complex interactions between gas-phase chemistry, aerosol growth, cloud and scavenging processes, and transport. However, errors in model applications still exist due in part to limitations in the models themselves and in part to uncertainties in model inputs. Four-dimensional data assimilation (FDDA) can be used as a top-down tool to validate several of the model inputs, including emissions inventories, based on ambient measurements. Previously, this FDDA technique was used to estimate adjustments in the strength and composition of emissions of gas-phase primary species and O3 precursors. In this paper, we present an extension to the FDDA technique to incorporate the analysis of particulate matter (PM) and its precursors. The FDDA approach consists of an iterative optimization procedure in which an AQM is coupled to an inverse model, and adjusting the emissions minimizes the difference between ambient measurements and model-derived concentrations. Here, the FDDA technique was applied to two episodes, with the modeling domain covering the eastern United States, to derive emission adjustments of domainwide sources of NO., volatile organic compounds (VOCs), CO, SO2, NH3, and fine organic aerosol emissions. Ambient measurements used include gas-phase inorganic and organic species and speciated fine PM. Results for the base-case inventories used here indicate that emissions of SO2 and CO appear to be estimated reasonably well (requiring minor revisions), while emissions of NOx, VOC, NH3, and organic PM with aerodynamic diameter less than 2.5 microm (PM2.5) require more significant revision.