PM2.5 emissions from aluminum smelters: coefficients and environmental impact

From 2004 to 2009, aiming to better understand implications for its smelters, Rio Tinto Alcan conducted a detailed study of PM2.5 and PM10 (particulate matter [PM] < or = 2.5 and 10 microm 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 PM2.5 and condensable particulate matter (CPM) at the roof vents of potrooms. This work aims to determine the PM2.5 emission coefficients of 17, 55, and 417 g x 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 PM2.5 emitters (85% of all smelter emissions) and that 71% of all smelter PM2.5 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 PM2.5 emissions for a representative smelter in an urban area.     

Characterization of the Fugitive Particulate Emissions from Construction Mud/Dirt Carryout

Abstract

Although the fugitive dust associated with construction mud/dirt carryout can represent a substantial portion of the particulate matter (PM) emissions inventory in non-attainment areas, it has not been well characterized by direct sampling methods. In this paper, a research program is described that directly determined both PM₁₀ and PM_2.5 (particles ≤10 and 2.5 μm in classical aerodynamic diameter, respectively) emission factors for mud/dirt carryout from a major construction project located in metropolitan Kansas City, MO. The program also assessed the contribution of automotive emissions to the total PM_2.5 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 PM_2.5 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 PM_2.5 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 PM_2.5 emissions appears to be attributable to automotive exhaust from light-duty, gasoline-powered vehicles and not to the fugitive dust associated with re-entrained mud/dirt carryout.     

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.     

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.     

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.     

PM Emissions Emanating from Limited-Access Highways

ABSTRACT

Motor vehicle contributions to primary particulate matter (PM) emissions include exhaust, tire wear, brake and clutch wear, and resuspended road dust. Relatively few field studies have been conducted to quantify fleetaverage exhaust emissions for actual on-road conditions. Therefore, direct measurements of motor vehicle-related PM emissions are warranted. In this study, PM₁₀ and PM_2.5 mass concentrations were measured near two major highways in the St. Louis area over the period from February–April 1997. Samplers were deployed both upwind and downwind of the roadways to capture the transport and dispersion of PM with distance from the roadway. The observed microscale concentration fields were compared to estimates using the PART5 emission factor model together with the CALINE4 highway dispersion model. Traffic- induced PM mass concentrations observed downwind of the roadway were always less than PART5/CALINE4 predictions; average percent differences for observed traffic-induced mass concentrations compared to predicted values were ?34% for PM_2.5 and -70% for PM₁₀. In most cases, the observed PM concentration decay with increasing distance from the roadway was steeper than predicted by dispersion modeling. Motor vehicle-induced emission factors were reconstructed by fitting CALINE4 to the observed concentration data with the emission factor as the sole adjustable parameter. Reconstructed fleet-average motor vehicle emission factors for the urban interstate highway were 0.03–0.04 g/VMT for both PM_2.5 and PM₁₀, while the fleet-average emission factors for the rural interstate highway were 0.2 and 0.3 g/VMT for PM_2.5 and PM₁₀, respectively.     

The Relationship between Cross-Sectional and Time Series Studies

Abstract

There is a dearth of information on dust emissions from sources that are unique to the U.S. Department of Defense testing and training activities. However, accurate emissions factors are needed for these sources so that military installations can prepare accurate particulate matter (PM) emission inventories. One such source, coarse and fine PM (PM₁₀ and PM_2.5) 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 PM_2.5 were ～9 g of PM_2.5 and 49 g of PM_2.5 per firing. The average measured emission rates for PM₁₀ and PM_2.5 appear to scale with the zone charge value. The measurements show that the estimated annual contributions of PM₁₀ (52.2 t) and PM_2.5 (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 PM_2.5 fugitive dust contributions, respectively, based on 2002 EPA inventory data.     

Compilation and application of a primary PM2.5 emissions inventory with high sectoral resolution in Japan

To elucidate the macro-structure of the PM_2.5 emissions generated by Japan's economic activities, this paper presents an emission inventory of primary particles of PM_2.5 with high sectoral resolution based on the Japanese Input–Output Tables, comprising some 400 sectors. These primary PM_2.5 emissions were estimated by multiplying the estimated energy consumption associated with each fuel type by a PM₁₀ emission factor incorporating the technological level of dust collection in each sector and the mass ratio of PM_2.5 to PM₁₀. Non-energy emissions from agricultural open burning were also determined. Total PM_2.5 emissions in 2000 were 252 kt, 49% of which were due to mobile emission sources. Changes in total PM_2.5 emissions between 1990 and 2000 were also calculated. This showed that a substantial increase in energy sector emissions due to rising coal consumption was offset by a sharp decline in emissions from road vehicles and shipping vessels, resulting in an overall decrease in total emissions. In addition, the emissions induced by economic demand in each sector were quantified by means of input–output analysis, which revealed that demand for construction, foods and communications and services constituted the principal causes of real domestic emissions. An assessment of sectoral contributions to PM_2.5 emissions that takes into account the effects of human exposure, expressed as external costs, suggests that the contribution of transportation is greater than indicated on the grounds of direct emissions alone.     

Trends in primary particulate matter emissions from Canadian agriculture

Particulate matter (PM) has long been recognized as an air pollutant due to its adverse health and environmental impacts. As emission of PM from agricultural operations is an emerging air quality issue, the Agricultural Particulate Matter Emissions Indicator (APMEI) has been developed to estimate the primary PM contribution to the atmosphere from agricultural operations on Census years and to assess the impact of practices adopted to mitigate these emissions at the soil landscape polygon scale as part of the agri-environmental indicator report series produced by Agriculture and Agri-Food Canada. In the APMEI, PM emissions from animal feeding operations, wind erosion, land preparation, crop harvest, fertilizer and chemical application, grain handling, and pollen were calculated and compared for the Census years of 1981–2006. In this study, we present the results for PM₁₀ and PM_2.5, which exclude chemical application and pollen sources as they only contribute to total suspended particles. In 2006, PM emissions from agricultural operations were estimated to be 652.6 kt for PM₁₀ and 158.1 kt for PM_2.5. PM emissions from wind erosion and land preparation account for most of PM emissions from agricultural operations in Canada, contributing 82% of PM₁₀ and 76% of PM_2.5 in 2006. Results from the APMEI show a strong reduction in PM emissions from agricultural operations between 1981 and 2006, with a decrease of 40% (442.8 kt) for PM₁₀ and 47% (137.7 kt) for PM_2.5. This emission reduction is mainly attributed to the adoption of conservation tillage and no-till practices and the reduction in the area of summerfallow land.

Implications: Increasing sustainability in agriculture often means adapting management practices to have a beneficial impact on the environment while maintaining or increasing production and economic benefits. We developed an inventory of primary PM emissions from agriculture in Canada to better quantify the apportionment, spatial distribution, and trends for Census years 1981–2006. We found major reductions of 40% in PM₁₀ and 47% in PM_2.5 emissions over the 25-yr period as a co-benefit of increasing carbon sequestration in agricultural soils. Indeed, farmers adopted conservation tillage/no-till practices, increased usage of cover crops, and reduced summerfallow, in order to increase soil organic matter and reduce carbon dioxide emissions, which also reduced primary PM emissions, although the agricultural production increased over the period.     

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.     

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.     

Emission Factors for High-Emitting Vehicles Based on On-Road Measurements of Individual Vehicle Exhaust with a Mobile Measurement Platform

ABSTRACT

Fuel-based emission factors for 143 light-duty gasoline vehicles (LDGVs) and 93 heavy-duty diesel trucks (HDDTs) were measured in Wilmington, CA using a zero-emission mobile measurement platform (MMP). The frequency distributions of emission factors of carbon monoxide (CO), nitrogen oxides (NO_x), and particle mass with aerodynamic diameter below 2.5 μm (PM_2.5) varied widely, whereas the average of the individual vehicle emission factors were comparable to those reported in previous tunnel and remote sensing studies as well as the predictions by Emission Factors (EMFAC) 2007 mobile source emission model for Los Angeles County. Variation in emissions due to different driving modes (idle, low- and high-speed acceleration, low- and high-speed cruise) was found to be relatively small in comparison to intervehicle variability and did not appear to interfere with the identification of high emitters, defined as the vehicles whose emissions were more than 5 times the fleet-average values. Using this definition, approximately 5% of the LDGVs and HDDTs measured were high emitters. Among the 143 LDGVs, the average emission factors of NO_x, black carbon (BC), PM_2.5, and ultrafine particle (UFP) would be reduced by 34%, 39%, 44%, and 31%, respectively, by removing the highest 5% of emitting vehicles, whereas CO emission factor would be reduced by 50%. The emission distributions of the 93 HDDTs measured were even more skewed: approximately half of the NO_x and CO fleet-average emission factors and more than 60% of PM_2.5, UFP, and BC fleet-average emission factors would be reduced by eliminating the highest-emitting 5% HDDTs. Furthermore, high emissions of BC, PM_2.5, and NO_x tended to cluster among the same vehicles.

IMPLICATIONS This study presents the characterization of on-road vehicle emissions in Wilmington, CA, by sampling individual vehicle plumes. Approximately 5% of the vehicles were high emitters, whose emissions were more than 5 times the fleet-average values. These high emitters were responsible for 30% and more than 50% of the average emission factors of LDGVs and HDDVs, respectively. It is likely that as the overall fleet becomes cleaner due to more stringent regulations, a small fraction of the fleet may contribute a growing and disproportionate share of the overall emissions. Therefore, long-term changes in on-road emissions need to be monitored.     

Authors’ Reply

ABSTRACT

Exposures of occupants in school buses to on-road vehicle emissions, including emissions from the bus itself, can be substantially greater than those in outdoor settings. A dual tracer method was developed and applied to two school buses in Seattle in 2005 to quantify in-cabin fine particulate matter (PM_2.5) concentrations attributable to the buses' diesel engine tailpipe (DPM_tp) and crankcase vent (PM_ck) emissions. The new method avoids the problem of differentiating bus emissions from chemically identical emissions of other vehicles by using a fuel-based organometallic iridium tracer for engine exhaust and by adding deuterated hexatriacontane to engine oil. Source testing results showed consistent PM:tracer ratios for the primary tracer for each type of emissions. Comparisons of the PM:tracer ratios indicated that there was a small amount of unburned lubricating oil emitted from the tailpipe; however, virtually no diesel fuel combustion products were found in the crankcase emissions. For the limited testing conducted here, although PM_ck emission rates (averages of 0.028 and 0.099 g/km for the two buses) were lower than those from the tailpipe (0.18 and 0.14 g/km), in-cabin PM_ck concentrations averaging 6.8 μg/m³ were higher than DPM_tp (0.91 μg/m³ average). In-cabin DPM_tp and PM_ck concentrations were significantly higher with bus windows closed (1.4 and 12 μg/m³, respectively) as compared with open (0.44 and 1.3 μg/m³, respectively). For comparison, average closed- and open-window in-cabin total PM_2.5 concentrations were 26 and 12 μg/m³, respectively. Despite the relatively short in-cabin sampling times, very high sensitivities were achieved, with detection limits of 0.002 μg/m³ for DPM_tp and 0.05 μg/m³ for PM_ck.

IMPLICATIONS PM_2.5 measurements in two Seattle school buses showed average concentrations of 26 and 12 μg/m³ with windows closed and open, respectively. Virtually all PM_2.5 was car bonaceous. Tracer measurements showed that bus self-pollution contributed approximately 50% of total PM_2.5 concentrations with windows closed and 15% with windows open, with over three-quarters of these contributions attributed to crankcase emissions. Maintaining ventilation in buses clearly reduces total PM_2.5 exposures and that from the buses' own emissions. The dual tracer method now offers researchers a new technique for explicit identification of single source contributions in settings with multiple sources of carbonaceous emissions.     

Characterization of PM2.5 fugitive metal in the workplaces and the surrounding environment of a secondary aluminum smelter

Fugitive metal in PM_2.5 at the blast furnace (S₁), reverberatory furnace (S₂), and surrounding environment (S₀) of a secondary aluminum smelter (a secondary ALS) was studied. PM_2.5 mass concentration at the blast furnace exceeded that at the reverberatory furnace and this was especially apparent during operation, giving an early indication that the blast furnace is more important as a pollutant source. Further, PM_2.5 mass concentration levels and patterns at S₀ indicated that emissions from the blast furnace and reverberatory furnace were the major source of the observed fine particle pollution in the surrounding environment. Si and K were the main components and hence pollutants by mass in the PM_2.5 at S₁, S₂ and S₀ during both operation and non-operation. Hg was not detected in the PM_2.5 aerosol during smelter operation but was present at all three sampling locations during non-operation. This is due to the falling blast furnace and reverberatory furnace temperatures during non-operation which cause Hg vapor formed during operation to condense to form detectable Hg particles, and hence Hg contributes to the pollutant load during non-operation. Average S₁/S₀ and S₂/S₀ mass concentration ratios of 40.32 and 18.53, respectively, for all measured metals during operation and 7.83 and 5.73 for all measured metals during non-operation indicate that metal particulate pollution at the workplaces of secondary ALSs, particularly at the blast furnace during operation, is a serious issue. S₁/S₀ mass concentration ratios were higher still for Pb (62.22), Ti (113.40) and Ba (248.64), while the S₂/S₀ mass concentration ratio for Mo was 138.20. Principal component analyses produced a PC1 that explained 32.36–48.16% of the total variance during operation of the smelter and 47.86–69.Ten percent during non-operation. Their strong component loadings were mainly related to the fugitive PM_2.5 mass. Compared to atmospheric metal concentrations reported for other regions of the world, the toxic metals that have relatively higher concentrations in the secondary ALS emissions are Cr, Cd, Cu, As, Pb, Se, Al and Zn, especially during smelter operation. Concentrations of these toxic heavy metals are approximately 2–4 orders of magnitude higher than those reported for various industrial regions and metropolises with heavy traffic across the world.     

Uncertainty in health risks due to anthropogenic primary fine particulate matter from different source types in Finland

The emission-exposure and exposure-response (toxicity) relationships are different for different emission source categories of anthropogenic primary fine particulate matter (PM_2.5). These variations have a potentially crucial importance in the integrated assessment, when determining cost-effective abatement strategies. We studied the importance of these variations by conducting a sensitivity analysis for an integrated assessment model. The model was developed to estimate the adverse health effects to the Finnish population attributable to primary PM_2.5 emissions from the whole of Europe. The primary PM_2.5 emissions in the whole of Europe and in more detail in Finland were evaluated using the inventory of the European Monitoring and Evaluation Programme (EMEP) and the Finnish Regional Emission Scenario model (FRES), respectively. The emission-exposure relationships for different primary PM_2.5 emission source categories in Finland have been previously evaluated and these values incorporated as intake fractions into the integrated assessment model. The primary PM_2.5 exposure-response functions and toxicity differences for the pollution originating from different source categories were estimated in an expert elicitation study performed by six European experts on air pollution health effects. The primary PM_2.5 emissions from Finnish and other European sources were estimated for the population of Finland in 2000 to be responsible for 209 (mean, 95% confidence interval 6–739) and 357 (mean, 95% CI 8–1482) premature deaths, respectively. The inclusion of emission-exposure and toxicity variation into the model increased the predicted relative importance of traffic related primary PM_2.5 emissions and correspondingly, decreased the predicted relative importance of other emission source categories. We conclude that the variations of emission-exposure relationship and toxicity between various source categories had significant impacts for the assessment on premature deaths caused by primary PM_2.5.     

A highly resolved temporal and spatial air pollutant emission inventory for the Pearl River Delta region, China and its uncertainty assessment

A highly resolved temporal and spatial Pearl River Delta (PRD) regional emission inventory for the year 2006 was developed with the use of best available domestic emission factors and activity data. The inventory covers major emission sources in the region and a bottom–up approach was adopted to compile the inventory for those sources where possible. The results show that the estimates for SO₂, NO_x, CO, PM₁₀, PM_2.5 and VOC emissions in the PRD region for the year 2006 are 711.4 kt, 891.9 kt, 3840.6 kt, 418.4 kt, 204.6 kt, and 1180.1 kt, respectively. About 91.4% of SO₂ emissions were from power plant and industrial sources, and 87.2% of NO_x emissions were from power plant and mobile sources. The industrial, mobile and power plant sources are major contributors to PM₁₀ and PM_2.5 emissions, accounting for 97.7% of the total PM₁₀ and 97.2% of PM_2.5 emissions, respectively. Mobile, biogenic and VOC product-related sources are responsible for 90.5% of the total VOC emissions. The emissions are spatially allocated onto grid cells with a resolution of 3 km × 3 km, showing that anthropogenic air pollutant emissions are mainly distributed over PRD central-southern city cluster areas. The preliminary temporal profiles were established for the power plant, industrial and on-road mobile sources. There is relatively low uncertainty in SO₂ emission estimates with a range of −16% to +21% from power plant sources, medium to high uncertainty for the NO_x emissions, and high uncertainties in the VOC, PM_2.5, PM₁₀ and CO emissions.     

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.     

Projected changes in particulate matter concentrations in the South Coast Air Basin due to basin-wide reductions in nitrogen oxides,volatile organic compounds,and ammonia emissions

An ozone abatement strategy for the South Coast Air Basin (SoCAB) has been proposed by the South Coast Air Quality Management District (SCAQMD) and the California Air Resources Board (ARB). The proposed emissions reduction strategy is focused on the reduction of nitrogen oxide (NO_x) emissions by the year 2030. Two high PM_2.5 concentration episodes with high ammonium nitrate compositions occurring during September and November 2008 were simulated with the Community Multi-scale Air Quality model (CMAQ). All simulations were made with same meteorological files provided by the SCAQMD to allow them to be more directly compared with their previous modeling studies. Although there was an overall under-prediction bias, the CMAQ simulations were within an overall normalized mean error of 50%; a range that is considered acceptable performance for PM modeling. A range of simulations of these episodes were made to evaluate sensitivity to NO_x and ammonia emissions inputs for the future year 2030. It was found that the current ozone control strategy will reduce daily average PM_2.5 concentrations. However, the targeted NO_x reductions for ozone were not found to be optimal for reducing PM_2.5 concentrations. Ammonia emission reductions reduced PM_2.5 and this might be considered as part of a PM_2.5 control strategy.

Implications: The SCAQMD and the ARB have proposed an ozone abatement strategy for the SoCAB that focuses on NO_x emission reductions. Their strategy will affect both ozone and PM_2.5. Two episodes that occurred during September and November 2008 with high PM_2.5 concentrations and high ammonium nitrate composition were selected for simulation with different levels of nitrogen oxide and ammonia emissions for the future year 2030. It was found that the ozone control strategy will reduce maximum daily average PM_2.5 concentrations but its effect on PM_2.5 concentrations is not optimal.     

Coarse Particulate Matter Apportionment around a Steel Smelter Plant

Abstract

The results from a study carried out in the urban area of Genoa, Italy, where a large steel smelter recently shut down are presented. We had the opportunity to sample particulate matter (PM) before and after plant closure and, therefore, to measure the changes in concentration and composition of PM₁₀ (atmospheric PM with aerodynamic diameter <10 µm). Elemental concentrations of Na to Pb were obtained through energy dispersive X-ray fluorescence (ED-XRF), and the contributions of specific sources of PM₁₀ were calculated by positive matrix factorization (PMF). The PM₁₀ average concentration turned out to be surprisingly similar before and after closing of the smelter. Nevertheless, the comparison among data collected in the two periods (plant operating and closed), even with the limited information provided by ED-XRF, allowed us to single out two sources of PM related to the smelter activities, to extract their emission profile, and to quantify the impact of the plant on PM₁₀ levels.     

Estimation and validation of PM2.5/PM10 exhaust and non-exhaust emission factors for practical street pollution modelling

In order to carry out efficient traffic and air quality management, validated models and PM emission estimates are needed. This paper compares current available emission factor estimates for PM₁₀ and PM_2.5 from emission databases and different emission models, and validates these against eight high quality street pollution measurements in Denmark, Sweden, Germany, Finland and Austria.The data sets show large variation of the PM concentration and emission factors with season and with location. Consistently at all roads the PM₁₀ and PM_2.5 emission factors are lower in the summer month than the rest of the year. For example, PM₁₀ emission factors are in average 5–45% lower during the month 6–10 compared to the annual average.The range of observed total emission factors (including non-exhaust emissions) for the different sites during summer conditions are 80–130 mg km⁻¹ for PM₁₀, 30–60 mg km⁻¹ for PM_2.5 and 20–50 mg km⁻¹ for the exhaust emissions.We present two different strategies regarding modelling of PM emissions: (1) For Nordic conditions with strong seasonal variations due to studded tyres and the use of sand/salt as anti-skid treatment a time varying emission model is needed. An empirical model accounting for these Nordic conditions was previously developed in Sweden. (2) For other roads with a less pronounced seasonal variation (e.g. in Denmark, Germany, Austria) methods using a constant emission factor maybe appropriate. Two models are presented here.Further, we apply the different emission models to data sets outside the original countries. For example, we apply the “Swedish” model for two streets without studded tyre usage and the “German” model for Nordic data sets. The “Swedish” empirical model performs best for streets with studded tyre use, but was not able to improve the correlation versus measurements in comparison to using constant emission factors for the Danish side. The “German” method performed well for the streets without clear seasonal variation and reproduces the summer conditions for streets with pronounced seasonal variation. However, the seasonal variation of PM emission factors can be important even for countries not using studded tyres, e.g. in areas with cold weather and snow events using sand and de-icing materials. Here a constant emission factor probably will under-estimate the 90-percentiles and therefore a time varying emission model need to be used or developed for such areas.All emission factor models consistently indicate that a large part (about 50–85% depending on the location) of the total PM₁₀ emissions originates from non-exhaust emissions. This implies that reduction measures for the exhaust part of the vehicle emissions will only have a limited effect on ambient PM₁₀ levels.