Particulates generated from combustion of polymers (plastics)

This is an experimental study on the characterization of particulate (soot) emissions from burning polymers. Emissions of polystyrene (PS), polyethylene (PE), polypropylene (PP), polymethyl methacrylate (PMMA), and polyvinyl chloride (PVC) plastics were studied. Combustion took place in a laboratory-scale, electrically heated, drop-tube furnace at temperatures of 1300 and 1500 K, in air. The nominal bulk (global) equivalence ratio, phi, was varied in the range of 0.5-1.5, and the gas residence time in the nearly isothermal radiation zone of the furnace was approximately 1 sec. The particulate emissions were size-classified at the exit of the furnace, using a multi-stage inertial particle impactor. Results showed that both the yields and the size distributions of the emitted soot were remarkably different for the five plastics burned. Soot yields increased with an increasing bulk equivalence ratio. Combustion of PS yielded the highest amounts of soot (most highly agglomerated), several times more than the rest of the polymers. More soot was emitted from PS at 1500 than at 1300 K. Substantial amounts of soot agglomerates were larger than 9 microns. At 1500 and 1300 K, 35 and 29% of the soot mass, respectively, was PM2 (2 microns or smaller). Emissions from PE and PP were remarkably similar to each other. These polymers produced very low emissions at phi < or = 0.5, but emissions increased drastically with phi, and most of the soot was very fine (70-97% of the mass was PM2, depending on phi). Emissions from the combustion of PMMA were comparatively low and were the least influenced by the bulk phi, and 79-95% of the emissions were PM2. Combustion of PVC yielded the lowest amounts of soot; moreover, only 13-34% of the mass was PM2. On a comparative basis, at 1500 K, the following ranges of particulate yields were PM2: 19-75 mg/g of PS, 8-36 mg/g of PE, 1.5-47 mg/g of PP, 11-20 mg/g of PMMA, and 2-8 mg/g of PVC, depending on phi. These comparative results demonstrate that PS produces the highest amounts of fine particulates, followed by PP, PE, and PMMA, and then PVC. Burning these materials with excess oxygen drastically reduces the particulate emissions of PE and PP, substantially reduces those of PS, and mildly reduces those of PMMA and PVC.     

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.     

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.     

Soil water and particle size distribution influence laboratory-generated PM10

Management of soils to reduce the amount of PM₁₀ emitted during agricultural tillage operations is important for attainment of air quality standards in California's San Joaquin Valley (SJV). The purpose of this study was to improve and expand upon earlier work of predicting tillage-generated dust emissions based on soil properties. We focus on gravimetric soil water content (GWC) and soil texture. A mechanical laboratory dust generator was used to test 23 soils collected for this study. Averaged results showed PM₁₀ concentrations (mg m^?3) increased logarithmically as GWC decreased below soil water potentials of ?1500 kPa. Soils with clay contents less than about 10% by weight began to emit PM₁₀ at GWCs 1.5–4 times their GWC at ?1500 kPa. Soils with clay contents greater than about 10% began to emit PM₁₀ at GWC values closer to ?1500 kPa. We found no correlation between maximum PM₁₀ concentrations, measured at low GWC values, and the %sand, %silt, or %clay in a soil. However, there was a significant correlation between the %silt to %clay ratio and PM₁₀ concentrations. This not only suggests the dependence of dust emission magnitudes on the supply of particles of PM₁₀ size, but also the importance of clay in stabilizing aggregates and maintaining higher amounts of capillary water at lower water potentials. Based on modeled results of pooled data, PM₁₀ concentrations increased linearly (slope = 564) for every unit increase in the %silt to %clay ratio. However, when soils were separated into groups based on clay content, the slopes for PM₁₀ concentrations vs. %silt to %clay ratio were texture dependent. The slope for soils with <10% clay (slope = 727) was 3.3 times greater than for soils with >20% clay (slope = 221). Improved PM₁₀ emission prediction based on soil properties should improve management decisions aimed at reducing tillage-generated PM₁₀.     

Control of Fine Particulate (PM2.5) Emissions from Restaurant Operations

ABSTRACT

This paper describes efforts to reduce particulate matter (PM) emissions from restaurant operations, including application of an existing control method to a new equipment type. Commercial charbroiling in the South Coast Air Basin results in emissions of approximately 10 tons/day of fine particulate matter ₍PM_2.5) and 1.3 tons/day of volatile organic compounds (VOCs). Over a seven-year period, the South Coast Air Quality Management District worked with industry to develop test methods for measuring emissions from various cooking operations, evaluate control technologies, and develop a rule to reduce these emissions.

Of the two basic types of charbroilers—chain-driven and underfired—underfired produce four times the emissions when equivalent amounts of product are cooked. Cost-effective control technology is currently available only for chain-driven charbroilers. The application of flameless catalytic oxidizers to chain-driven charbroilers was found to effectively reduce emissions by at least 83% and is cost-effective. The catalysts have been used worldwide at restaurants for several years. Research efforts are underway to identify control options for underfired charbroilers.

Implementation of Rule 1138, Control of Emissions from Restaurant Operations, adopted November 14, 1997, will result in reductions of 0.5 tons/day of PM_2.5 and 0.2 tons/day of VOCs. Future rules will result in reductions from underfired charbroilers and possibly other restaurant equipment when cost-effective solutions are available.     

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.     

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     

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.     

Size and Composition Distributions of Particulate Matter Emissions: Part 1—Light-Duty Gasoline Vehicles

Abstract

Size-resolved particulate matter (PM) emitted from light-duty gasoline vehicles (LDGVs) was characterized using filter-based samplers, cascade impactors, and scanning mobility particle size measurements in the summer 2002. Thirty LDGVs, with different engine and emissions control technologies (model years 1965–2003; odometer readings 1264–207,104 mi), were tested on a chassis dynamometer using the federal test procedure (FTP), the unified cycle (UC), and the correction cycle (CC). LDGV PM emissions were strongly correlated with vehicle age and emissions control technology. The oldest models had average ultrafine PM_0.1 (0.056- to 0.1-μm aerodynamic diameter) and fine PM_1.8 (≤1.8-μm aerodynamic diame ter) emission rates of 9.6 mg/km and 213 mg/km, respectively. The newest vehicles had PM_0.1 and PM_1.8 emis sions of 51 μg/km and 371 μg/km, respectively. Light duty trucks and sport utility vehicles had PM_0.1 and PM_1.8 emissions nearly double the corresponding emission rates from passenger cars. Higher PM emissions were associated with cold starts and hard accelerations. The FTP driving cycle produced the lowest emissions, followed by the UC and the CC. PM mass distributions peaked between 0.1-and 0.18-μm particle diameter for all vehicles except those emitting visible smoke, which peaked between 0.18 and 0.32 μm. The majority of the PM was composed of carbonaceous material, with only trace amounts of water-soluble ions. Elemental carbon (EC) and organic matter (OM) had similar size distributions, but the EC/OM ratio in LDGV exhaust particles was a strong function of the adopted emissions control technology and of vehicle maintenance. Exhaust from LDGV classes with lower PM emissions generally had higher EC/OM ratios. LDGVs adopting newer technologies were characterized by the highest EC/OM ratios, whereas OM dominated PM emissions from older vehicles. Driving cycles with cold starts and hard accelerations produced higher EC/OM ratios in ultrafine particles.     

Identification of sources of atmospheric PM at the Pittsburgh Supersite—Part III: Source characterization

Single-particle mass spectrometry data collected during the Pittsburgh Supersite experiment was used to isolate an episode on 27 October 2001 when the measurement site was primarily influenced by emissions from coal combustion sources. Results showed that (a) 60–80% of the particles detected during this event belonged to the Na/Si/K/Ca/Fe/Ga/Pb particle class associated with coal combustion emissions, (b) observation of this class was an isolated event occurring only during the hours of 06:00–14:00 EST, and (c) the detection of these particles was highly correlated with shifts in wind direction. Coincident SMPS, TEOM PM_2.5, SO₂, NO_x, and O₃ measurements were in excellent agreement with the single-particle results in terms of both identifying and characterizing this event. The three most likely point sources of these particles were isolated and Gaussian plume dispersion models were used in reverse to predict their particle number, particle mass, and gas phase emissions. Calculated mass emission rates were in general agreement with the US EPA National Emissions Inventory (NEI) database emissions estimates and the Title V PM₁₀ limit. The largest of the three sources emits about 2.4×10¹⁷ fine and ultrafine particles per second.     

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.     

Near-road air pollutant concentrations of CO and PM2.5: A comparison of MOBILE6.2/CALINE4 and generalized additive models

The contribution of vehicular traffic to air pollutant concentrations is often difficult to establish. This paper utilizes both time-series and simulation models to estimate vehicle contributions to pollutant levels near roadways. The time-series model used generalized additive models (GAMs) and fitted pollutant observations to traffic counts and meteorological variables. A one year period (2004) was analyzed on a seasonal basis using hourly measurements of carbon monoxide (CO) and particulate matter less than 2.5 μm in diameter (PM_2.5) monitored near a major highway in Detroit, Michigan, along with hourly traffic counts and local meteorological data. Traffic counts showed statistically significant and approximately linear relationships with CO concentrations in fall, and piecewise linear relationships in spring, summer and winter. The same period was simulated using emission and dispersion models (Motor Vehicle Emissions Factor Model/MOBILE6.2; California Line Source Dispersion Model/CALINE4). CO emissions derived from the GAM were similar, on average, to those estimated by MOBILE6.2. The same analyses for PM_2.5 showed that GAM emission estimates were much higher (by 4–5 times) than the dispersion model results, and that the traffic-PM_2.5 relationship varied seasonally. This analysis suggests that the simulation model performed reasonably well for CO, but it significantly underestimated PM_2.5 concentrations, a likely result of underestimating PM_2.5 emission factors. Comparisons between statistical and simulation models can help identify model deficiencies and improve estimates of vehicle emissions and near-road air quality.     

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.     

Testing Re-entrained Aerosol Kinetic Emissions from Roads : a new approach to infer silt loading on roadways

PM₁₀ and PM_2.5 emissions from roadways are currently estimated using the silt loading on the road surface as a surrogate for the emissions potential of road dust. While the United States Environmental Protection Agency prescribes this method in AP-42, there is considerable cost associated with silt loading measurements; it is feasible to sample only a small portion of a roadway network. A new approach for measuring the concentration of suspendable PM₁₀ above road surfaces has been developed to obtain a more spatially representative estimate of a road's potential to emit dust. The Testing Re-entrained Aerosols Kinetic Emissions from Roads (TRAKER) system uses real-time aerosol sensors mounted on a vehicle to measure the concentration of dust suspended from the road while the vehicle is in motion. When coupled with a Global Positioning System (GPS) instrument, TRAKER can be used to efficiently survey the changes in suspendable particles due to varying road conditions over a large spatial domain.In a recent study on paved roads in Las Vegas, the TRAKER system was compared with collocated silt loading measurements. The TRAKER system was also used to survey the relative amounts of suspendable road dust on approximately 300 miles of paved roads. The system provides a unique perspective on road dust sources and their spatial distribution.Results of this study indicated that the difference of the PM₁₀ concentrations measured behind the tire and on the hood is exponentially related to vehicle speed. This was an interesting finding because current AP-42 road dust emissions estimation methods do not include vehicle speed as a factor in the emissions calculations. The experiment also demonstrated that the distribution of suspendable material on roadways is highly variable and that a large number of samples are needed to represent road dust emissions potential on an urban scale for a variety of road and activity conditions.     

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.     

Particulate Emission Rates for Unpaved Shoulders along a Paved Road

ABSTRACT

This paper reports the first empirical estimate of particle emissions from unpaved shoulders along paved roads.¹ Its objectives are to develop and demonstrate an emission rate measurement methodology that can be applied in different areas; identify the mechanisms that suspend dust from unpaved shoulders and the observables related to this suspension process; and quantify PM₁₀ mass emissions in the form of an emission rate. To achieve these objectives, fast-response observations from nephelometers and a sonic anemometer were used to characterize shortlived dust plumes generated by passing vehicles. In addition, detailed soil surface measurements determined the mechanical properties of the shoulder surfaces.

Large traffic-induced turbulence events that led to significant dust entrainment were almost exclusively caused by “large” vehicles such as trucks, semis, and vehicles pulling trailers, all traveling 50-65 mph. PM₁₀ emission rates for these large, fast-traveling vehicles were determined to be 8 ± 4 grams per vehicle kilometer traveled under dry conditions. Emissions due to smaller vehicles such as cars, vans, and sport utility vehicles were negligible for normal on-road driving. These results indicate that the majority of PM₁₀ emissions from unpaved shoulders is caused by relatively few vehicles.     

Inventory of aerosol and sulphur dioxide emissions from India: I—Fossil fuel combustion

A comprehensive, spatially resolved (0.25°×0.25°) fossil fuel consumption database and emissions inventory was constructed, for India, for the first time. Emissions of sulphur dioxide and aerosol chemical constituents were estimated for 1996–1997 and extrapolated to the Indian Ocean Experiment (INDOEX) study period (1998–1999). District level consumption of coal/lignite, petroleum and natural gas in power plants, industrial, transportation and domestic sectors was 9411 PJ, with major contributions from coal (54%) followed by diesel (18%). Emission factors for various pollutants were derived using India specific fuel characteristics and information on combustion/air pollution control technologies for the power and industrial sectors. Domestic and transportation emission factors, appropriate for Indian source characteristics, were compiled from literature. SO₂ emissions from fossil fuel combustion for 1996–1997 were 4.0 Tg SO₂ yr⁻¹, with 756 large point sources (e.g. utilities, iron and steel, fertilisers, cement, refineries and petrochemicals and non-ferrous metals), accounting for 62%. PM_2.5 emitted was 0.5 and 2.0 Tg yr⁻¹ for the 100% and the 50% control scenario, respectively, applied to coal burning in the power and industrial sectors. Coal combustion was the major source of PM_2.5 (92%) primarily consisting of fly ash, accounting for 98% of the “inorganic fraction” emissions (difference between PM_2.5 and black carbon+organic matter) of 1.6 Tg yr⁻¹. Black carbon emissions were estimated at 0.1 Tg yr⁻¹, with 58% from diesel transport, and organic matter emissions at 0.3 Tg yr⁻¹, with 48% from brick-kilns. Fossil fuel consumption and emissions peaked at the large point industrial sources and 22 cities, with elevated area fluxes in northern and western India. The spatial resolution of this inventory makes it suitable for regional-scale aerosol-climate studies. These results are compared to previous studies and differences discussed. Measurements of emission factors for Indian sources are needed to further refine these estimates.     

Modeling an air pollution episode in northwestern United States: Identifying the effect of nitrogen oxide and volatile organic compound emission changes on air pollutants formation using direct sensitivity analysis

Air quality impacts of volatile organic compound (VOC) and nitrogen oxide (NO_x) emissions from major sources over the northwestern United States are simulated. The comprehensive nested modeling system comprises three models: Community Multiscale Air Quality (CMAQ), Weather Research and Forecasting (WRF), and Sparse Matrix Operator Kernel Emissions (SMOKE). In addition, the decoupled direct method in three dimensions (DDM-3D) is used to determine the sensitivities of pollutant concentrations to changes in precursor emissions during a severe smog episode in July of 2006. The average simulated 8-hr daily maximum O₃ concentration is 48.9 ppb, with 1-hr O₃ maxima up to 106 ppb (40 km southeast of Seattle). The average simulated PM_2.5 (particulate matter with an aerodynamic diameter <2.5 μm) concentration at the measurement sites is 9.06 μg m^?3, which is in good agreement with the observed concentration (8.06 μg m^?3). In urban areas (i.e., Seattle, Vancouver, etc.), the model predicts that, on average, a reduction of NO_x emissions is simulated to lead to an increase in average 8-hr daily maximum O₃ concentrations, and will be most prominent in Seattle (where the greatest sensitivity is??0.2 ppb per % change of mobile sources). On the other hand, decreasing NO_x emissions is simulated to decrease the 8-hr maximum O₃ concentrations in remote and forested areas. Decreased NO_x emissions are simulated to slightly increase PM_2.5 in major urban areas. In urban areas, a decrease in VOC emissions will result in a decrease of 8-hr maximum O₃ concentrations. The impact of decreased VOC emissions from biogenic, mobile, nonroad, and area sources on average 8-hr daily maximum O₃ concentrations is up to 0.05 ppb decrease per % of emission change, each. Decreased emissions of VOCs decrease average PM_2.5 concentrations in the entire modeling domain. In major cities, PM_2.5 concentrations are more sensitive to emissions of VOCs from biogenic sources than other sources of VOCs. These results can be used to interpret the effectiveness of VOC or NO_x controls over pollutant concentrations, especially for localities that may exceed National Ambient Air Quality Standards (NAAQS).

Implications: The effect of NO_x and VOC controls on ozone and PM_2.5 concentrations in the northwestern United States is examined using the decoupled direct method in three dimensions (DDM-3D) in a state-of-the-art three-dimensional chemical transport model (CMAQ). NO_x controls are predicted to increase PM_2.5 and ozone in major urban areas and decrease ozone in more remote and forested areas. VOC reductions are helpful in reducing ozone and PM_2.5 concentrations in urban areas. Biogenic VOC sources have the largest impact on O₃ and PM_2.5 concentrations.     

Source apportionment of PM2.5 at two Seattle chemical speciation sites

ABSTRACT

Positive Matrix Factorization analysis of PM_2.5 chemical speciation data collected from 2015–2017 at Washington State Department of Ecology’s urban NCore (Beacon Hill) and near-road (10th and Weller) sites found similar PM_2.5 sources at both sites. Identified factors were associated with gasoline exhaust, diesel exhaust, aged and fresh sea salt, crustal, nitrate-rich, sulfur-rich, unidentified urban, zinc-rich, residual fuel oil, and wood smoke. Factors associated with vehicle emissions were the highest contributing sources at both sites. Gasoline exhaust emissions comprised 26% and 21% of identified sources at Beacon Hill and 10th and Weller, respectively. Diesel exhaust emissions comprised 29% of identified sources at 10th and Weller but only 3% of identified sources at Beacon Hill. Correlation of the diesel exhaust factor with measured concentrations of black carbon and nitrogen oxides at 10th and Weller suggests a method to predict PM_2.5 from diesel exhaust without a full chemical speciation analysis. While most PM_2.5 sources exhibit minimal change over time, primary PM_2.5 from gasoline emissions is increasing on average 0.18 µg m^?3 per year in Seattle.     

Spatial patterns of mobile source particulate matter emissions-to-exposure relationships across the United States

Assessing the public health benefits from air pollution control measures is assisted by understanding the relationship between mobile source emissions and subsequent fine particulate matter (PM_2.5) exposure. Since this relationship varies by location, we characterized its magnitude and geographic distribution using the intake fraction (iF) concept. We considered emissions of primary PM_2.5 as well as particle precursors SO₂ and NO_x from each of 3080 counties in the US. We modeled the relationship between these emissions and total US population exposure to PM_2.5, making use of a source–receptor matrix developed for health risk assessment. For primary PM_2.5, we found a median iF of 1.2 per million, with a range of 0.12–25. Half of the total exposure was reached by a median distance of 150 km from the county where mobile source emissions originated, though this spatial extent varied across counties from within the county borders to 1800 km away. For secondary ammonium sulfate from SO₂ emissions, the median iF was 0.41 per million (range: 0.050–10), versus 0.068 per million for secondary ammonium nitrate from NO_x emissions (range: 0.00092–1.3). The median distance to half of the total exposure was greater for secondary PM_2.5 (450 km for sulfate, 390 km for nitrate). Regression analyses using exhaustive population predictors explained much of the variation in primary PM_2.5 iF (R²=0.83) as well as secondary sulfate and nitrate iF (R²=0.74 and 0.60), with greater near-source contribution for primary than for secondary PM_2.5. We conclude that long-range dispersion models with coarse geographic resolution are appropriate for risk assessments of secondary PM_2.5 or primary PM_2.5 emitted from mobile sources in rural areas, but that more resolved dispersion models are warranted for primary PM_2.5 in urban areas due to the substantial contribution of near-source populations.