Development and Preliminary Evaluation of a Particulate Matter Emission Factor Model for European Motor Vehicles

ABSTRACT

Although modeling of gaseous emissions from motor vehicles is now quite advanced, prediction of particulate emissions is still at an unsophisticated stage. Emission factors for gasoline vehicles are not reliably available, since gasoline vehicles are not included in the European Union (EU) emission test procedure. Regarding diesel vehicles, emission factors are available for different driving cycles but give little information about change of emissions with speed or engine load. We have developed size-specific speed-dependent emission factors for gasoline and diesel vehicles. Other vehicle-generated emission factors are also considered and the empirical equation for re-entrained road dust is modified to include humidity effects. A methodology is proposed to calculate modal (accelerating, cruising, or idling) emission factors. The emission factors cover particle size ranges up to 10 um, either from published data or from user-defined size distributions.

A particulate matter emission factor model (PMFAC), which incorporates virtually all the available information on particulate emissions for European motor vehicles, has been developed. PMFAC calculates the emission factors for five particle size ranges [i.e., total suspended particulates (TSP), PM₁₀, PM₅, PM₂₅, and PM₁] from both vehicle exhaust and nonexhaust emissions, such as tire wear, brake wear, and re-entrained road dust. The model can be used for an unlimited number of roads and lanes, and to calculate emission factors near an intersection in user-defined elements of the lane. PMFAC can be used for a variety of fleet structures. Hot emission factors at the user-defined speed can be calculated for individual vehicles, along with relative cold-to-hot emission factors. The model accounts for the proportions of distance driven with cold engines as a function of ambient temperature and road type (i.e., urban, rural, or motorway).

A preliminary evaluation of PMFAC with an available dispersion model to predict the airborne concentration in the urban environment is presented. The trial was on the A6 trunk road where it passes through Loughborough, a medium-size town in the English East Midlands. This evaluation for TSP and PM₁₀ was carried out for a range of traffic fleet compositions, speeds, and meteorological conditions. Given the limited basis of the evaluation, encouraging agreement was shown between predicted and measured concentrations.     

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.     

Fugitive Dust Emission Source Profiles and Assessment of Selected Control Strategies for Particulate Matter at Gravel Processing Sites in Taiwan

Abstract

Particles emitted from gravel processing sites are one contributor to worsening air quality in Taiwan. Major pollution sources at gravel processing sites include gravel and sand piles, unpaved roads, material crushers, and bare ground. This study analyzed fugitive dust emission characteristics at each pollution source using several types of particle samplers, including total suspended particulates (TSP), suspended particulate (PM₁₀), fine suspended particulate (PM_2.5), particulate sizer, and dust-fall collectors. Furthermore, silt content and moisture in the gravel were measured to develop particulate emission factors. The results showed that TSP (<100 µm) concentrations at the boundary of gravel sites ranged from 280 to 1290 µg/m³, which clearly exceeds the Taiwan hourly air quality standard of 500 µg/m³. Moreover, PM₁₀ concentrations, ranging from 135 to 550 µg/m³, were also above the daily air quality standard of 125 µg/m³ and approximately 1.2 and 1.5 times the PM_2.5 concentrations, ranging from 105 to 470 µg/m³. The size distribution analysis reveals that mass mean diameter and geometric standard deviation ranged from 3.2 to 5.7 µm and from 2.82 to 5.51, respectively. In this study, spraying surfactant was the most effective control strategy to abate windblown dust from unpaved roads, having a control efficiency of approximately 93%, which is significantly higher than using paved road strategies with a control efficiency of approximately 45%. For paved roads, wet suppression provided the best dust control efficiencies ranging from 50 to 83%. Re-vegetation of disturbed ground had dust control efficiencies ranging from 48 to 64%.     

Application of Infrared Spectroscopy to Exhaust Gas Analysis

Abstract

The Mohave Valley region of southern Nevada/southwestern Arizona has experienced elevated particulate concentrations and is classified as a PM₁₀ nonattainment area. Anthropogenic aerosol sources in the area include the Mohave Power Project (MPP), a 1,580-MW coal-fired power plant; motor vehicles; construction activities; and paved and unpaved road dust and disturbed desert soil. Aerosols may also be transported long distances from other areas, such as the Los Angeles Basin. Based on the infrequency of plume contact at sites in the valley (as determined by SO₂ measurements), it was believed that the contribution of the MPP to primary PM₁₀ was minimal and that fugitive dust was the primary source of ambient particulate matter.

To evaluate the magnitude of source contributors, PM₁₀ measurements were made using a medium-volume sampler along with ancillary meteorological and air quality measurements in the Mohave Valley at Bullhead City, Arizona, for a period of longer than one year (September 1988 through mid-October 1989). The aerosol filter samples were analyzed for mass, elements, ions, and carbon. Source apportionment using the Chemical Mass Balance (CMB) receptor model was performed. On average, geological dust was the major contributor to PM10 (79.5%), followed by primary motor vehicle sources (16.7%), secondary ammonium sulfate (3.5%), secondary ammonium nitrate (0.1%), and primary coal-fired power plant emissions (0.1%).     

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.     

Spatial Differences in Outdoor PM10 Mass and Aerosol Composition in Mexico City

Abstract

Twenty-five MiniVol samplers were operated throughout the Mexico City metropolitan region from February 22 through March 22, 1997, to evaluate the variability of PM₁₀ concentrations and composition. The highest PM₁₀ concentrations were found in neighborhoods with unpaved or dirty roads, and elements related to crustal material were the main cause of differences from nearby (<200 m) monitors that were not adjacent to the roadbed. SO₄ ^2?concentrations were homogeneous across the city. SO₄ ^2?measured at the city boundaries was about two-thirds of the concentrations measured within the urbanized area, indicating that most SO₄ ^2? is of regional origin. Elemental carbon (EC) and organic carbon (OC) concentrations were highly variable, with higher concentrations in areas that had high diesel traffic and older vehicles. Spatial correlations among PM₁₀ concentrations were high, even though absolute concentrations were variable, indicating a common effect of meteorology on the concentration or dispersion of local emissions.     

Application of a Combined Measurement and Modeling Method to Quantify Windblown Dust Emissions from the Exposed Playa at Mono Lake,California

ABSTRACT

Particulate matter ≤10 μm (PM₁₀) emissions due to wind erosion can vary dramatically with changing surface conditions. Crust formation, mechanical disturbance, soil texture, moisture, and chemical content of the soil can affect the amount of dust emitted during a wind event. A refined method of quantifying windblown dust emissions was applied at Mono Lake, CA, to account for changing surface conditions. This method used a combination of real-time sand flux monitoring, ambient PM₁₀ monitoring, and dispersion modeling to estimate dust emissions and their downwind impact. The method identified periods with high emissions and periods when the surface was stable (no sand flux), even though winds may have been high. A network of 25 Cox sand catchers (CSCs) was used to measure the mass of saltating particles to estimate sand flux rates across a 2-km² area. Two electronic sensors (Sensits) were used to time-resolve the CSC sand mass to estimate hourly sand flux rates, and a perimeter tapered element oscillating microbalance (TEOM) monitor measured hourly PM₁₀ concentrations. Hourly sand flux rates were related by dispersion modeling to hourly PM₁₀ concentrations to back-calculate the ratio of vertical PM₁₀ flux to horizontal sand flux (K-factors). Geometric mean K-factor values (K _f) were found to change seasonally, ranging from 1.3 × 10^?5 to 5.1 × 10^?5 for sand flux measured at 15 cm above the surface (q ₁₅). Hourly PM₁₀ emissions, F, were calculated by applying seasonal K-factors to sand flux measurements (F?=?K _f ×?q ₁₅). The maximum hourly PM10 emission rate from the study area was 76 g/m²·hr (10-m wind speed?=?23.5 m/sec). Maximum daily PM₁₀ emissions were estimated at 450 g/m²·day, and annual emissions at 1095 g/m²·yr. Hourly PM₁₀ emissions were used by the U.S. Environmental Protection Agency (EPA) guideline AERMOD dispersion model to estimate downwind ambient impacts. Model predictions compared well with monitor concentrations, with hourly PM₁₀ ranging from 16 to over 60,000 μg/m³ (slope?=?0.89, R ²?=?0.77).

IMPLICATIONS Under a U.S. Environmental Protection Agency (EPA)-approved plan, the method described in this paper has been used since 2000 at Owens Lake, CA, to identify and successfully mitigate dust from over 100 km² of the dry lakebed. It continues to be used to monitor dust control compliance at Owens Lake. Scaled-down versions of the Owens Lake network can be implemented in other areas in a manner similar to the Mono Lake study. Once K-factors are established, low-cost CSC samplers (about $35 U.S.) may be used for periodic monitoring (e.g., daily, weekly, or monthly) to estimate PM₁₀ emissions or to evaluate dust control compliance.     

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

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.     

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.     

Road Dust Resuspension in the Vicinity of Limestone Quarries in Jordan

Abstract

Many areas in Jordan suffer from elevated levels of coarse particulate matter (PM₁₀). One potentially significant source of the observed PM is the resuspension of road dust in the vicinity of limestone quarries. To obtain data to assess the impact from this source, PM₁₀ road dust resus-pension factors near Abusiiah, a town to the north east of Amman surrounded by many quarries and brick factories, were measured. Measurements included PM₁₀ mass, particle size distributions, wind speed, and wind direction.The results showed that PM₁₀ concentrations could be as high as 600 µg/m³, and most of the airborne PM is in the coarse fraction. Loading trucks play a major role in resus-pending road dust, with an observed PM₁₀ emission rate of >6000 mg/km.     

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.     

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.     

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.     

Emission of respirable dust from stone quarrying,potential health effects,and its management

Mining of minerals exerts adverse pressure on different compartments of environment directly or indirectly. Air is the worst affected environmental matrix, and it can carry the harmful effect of pollutants generated from mining activity even to distant places. The present study was undertaken to estimate the emission of particulate matter (PM_2.5 and PM₁₀) from different activities undertaken in stone quarrying in Mahendragarh, Haryana. The results obtained from the present study indicated that drilling, blasting, crushing, and transport of mined material are chiefly responsible for the generation of dust. Whereas drilling, blasting, and loading were responsible for emission of higher fraction of PM₁₀, crushing and re-suspension of roadside dust from movement of vehicles resulted in generation of relatively higher fraction of finer dust (PM_2.5). Modelling the transport of dust over the Hybrid Single-Particle Lagrangian Integrated Trajectory model revealed that the emitted particle may move up to the distance of about 40 km within 4 h of emission under average meteorological conditions. Fourier transform infrared (FTIR) spectroscopy analysis of dust confirmed the presence of calcite and gypsum, thus confirming the source as mining. The study concluded that generation of PM_2.5-sized particles may impose serious respiratory health effects over the workers engaged in mining, crushing, and transportation of sandstone. Apart from it, population residing downwind of the mining area is particularly vulnerable to the pulmonary effects due to inhalation of dust.

     

Source Apportionment of Ambient Total Suspended Particulates and Coarse Particulate Matter in Urban Areas of Jiaozuo,China

Abstract

Approximately 750 total suspended particulates (TSPs) and coarse particulate matter (PM₁₀) filter samples from six urban sites and a background site and >210 source samples were collected in Jiaozuo City during January 2002 to April 2003. They were analyzed for mass and abundances of 25 chemical components. Seven contributive sources were identified, and their contributions to ambient TSP/PM₁₀ levels at the seven sites in three seasons (spring, summer, and winter days) and a “whole” year were estimated by a chemical mass balance (CMB) receptor model. The spatial TSP average was high in spring and winter days at a level of approximately 530 ～g/m³ and low in summer days at 456 ～g/m³; however, the spatial PM₁₀ average exhibited little variation at a level of approximately 325 ～g/m³, and PM_10-to-TSP ratios ranged from 0.58 to 0.81, which suggested heavy particulate matter pollution existing in the urban areas. Apportionment results indicated that geological material was the largest contributor to ambient TSP/PM₁₀ concentrations, followed by dust emissions from construction activities, coal combustion, secondary aerosols, vehicle movement, and other industrial sources. In addition, paved road dust and re-entrained dust were also apportioned to the seven source types and found soil, coal combustion, and construction dust to be the major contributors.     

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.     

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.     

The measurement of roadway PM10 emission rates using atmospheric tracer ratio techniques

In this work, stationary and mobile point source tracer release techniques have been used to determine PM₁₀ emission rates from four-lane commercial/residential paved roads under sanded and unsanded conditions, and from unpaved roads relative to site-specific vehicular and ambient parameters. Measured street (4 + lanes; ? 10,000 vehicles per day) emission factors for unsanded and sanded roads were 40 and 20% lower, respectively, than the EPA approved reference value. The sanded road emission factor was approximately 40% higher than that for the unsanded road. These results indicate a consistent relationship between PM₁₀ and relative humidity under unsanded conditions. There is some evidence to suggest that street sweeping has a measurable effect on PM,, emission reduction during periods of low relative humidity (i.e. ? 30%). Within the constraints imposed by the variable experimental conditions, the emission factors determined for unpaved roads agreed reasonably well with the unpaved road empirical formula. Limited correlations were observed with ambient meteorological parameters. The capability of the “upwind-dowiawind” concentration modeling method to predict accurate emission was tested using a Gaussian dispersion model (SIMFLUX). Predictions agreed well with the experimentally determined emission factors.     

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