Atmospheric Particulate Emissions from Dry Abrasive Blasting Using Coal Slag

Abstract

Coal slag is one of the widely used abrasives in dry abrasive blasting. Atmospheric emissions from this process include particulate matter (PM) and heavy metals, such as chromium, lead, manganese, nickel. Quantities and characteristics of PM emissions depend on abrasive characteristics and process parameters. Emission factors are key inputs to estimate emissions. Experiments were conducted to study the effect of blast pressure, abrasive feed rate, and initial surface contamination on total PM (TPM) emission factors for coal slag. Rusted and painted mild steel surfaces were used as base plates. Blasting was carried out in an enclosed chamber, and PM was collected from an exhaust duct using U.S. Environment Protection Agency source sampling methods for stationary sources. Results showed that there is significant effect of blast pressure, feed rate, and surface contamination on TPM emissions. Mathematical equations were developed to estimate emission factors in terms of mass of emissions per unit mass of abrasive used, as well as mass of emissions per unit of surface area cleaned. These equations will help industries in estimating PM emissions based on blast pressure and abrasive feed rate. In addition, emissions can be reduced by choosing optimum operating conditions.     

Evaluation of total particulate matter emission factors for copper slag in dry abrasive blasting

Abrasive blasting was performed in enclosed conditions to evaluate the effect of blast pressure, feed rate and surface contamination on Total Particulate Matter (TPM) emission factors for copper slag. Stack sampling methods were used to collect uncontrolled TPM. Emission factors were calculated as grams of TPM emitted per pound of copper slag used (g/lb) and grams of TPM emitted per square foot of area cleaned (g/sq.ft). Emission factor models were developed to study variation of TPM emission factors with pressure, feed rate and surface contamination. These models can be used to reduce emissions by selecting optimum operating condition as well as to determine emission factors at any operating conditions, within the tested range, for copper slag.     

Application of a combined measurement and modeling method to quantify windblown dust emissions from the exposed playa at Mono Lake, California

Particulate matter < or =10 microm (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 x 10(-5) to 5.1 x 10(-5) for sand flux measured at 15 cm above the surface (q15). Hourly PM10 emissions, F, were calculated by applying seasonal K-factors to sand flux measurements (F = K(f) x q15). The maximum hourly PM10 emission rate from the study area was 76 g/m2 x hr (10-m wind speed = 23.5 m/sec). Maximum daily PM10 emissions were estimated at 450 g/m2 x day, and annual emissions at 1095 g/m2 x 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 microg/m3 (slope = 0.89, R2 = 0.77).     

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

There is a dearth of information on dust emissions from sources that are unique to the U.S. Department of Defense testing and training activities. However, accurate emissions factors are needed for these sources so that military installations can prepare accurate particulate matter (PM) emission inventories. One such source, coarse and fine PM (PM10 and PM2.5) emissions from artillery backblast testing on improved gun positions, was characterized at the Yuma Proving Ground near Yuma, AZ, in October 2005. Fugitive emissions are created by the shockwave from artillery pieces, which ejects dust from the surface on which the artillery is resting. Other contributions of PM can be attributed to the combustion of the propellants. For a 155-mm howitzer firing a range of propellant charges or zones, amounts of emitted PM10 ranged from -19 g of PM10 per firing event for a zone 1 charge to 92 g of PM10 per firing event for a zone 5. The corresponding rates for PM2.5 were approximately 9 g of PM2.5 and 49 g of PM2.5 per firing. The average measured emission rates for PM1o and PM2.5 appear to scale with the zone charge value. The measurements show that the estimated annual contributions of PM10 (52.2 t) and PM2.5 (28.5 t) from artillery backblast are insignificant in the context of the 2002 U.S. Environment Protection Agency (EPA) PM emission inventory. Using national-level activity data for artillery fire, the most conservative estimate is that backblast would contribute the equivalent of 5 x 10(-4) % and 1.6 x 10(-3)% of the annual total PM10 and PM2.5 fugitive dust contributions, respectively, based on 2002 EPA inventory data.     

Standardized emissions inventory methodology for open-pit mining areas

INTRODUCTION: There is still interest in a unified methodology to quantify the mass of particulate material emitted into the atmosphere by activities inherent to open-pit mining. For the case of total suspended particles (TSP), the current practice is to estimate such emissions by developing inventories based on the emission factors recommended by the USEPA for this purpose. However, there are disputes over the specific emission factors that must be used for each activity and the applicability of such factors to cases quite different to the ones under which they were obtained. There is also a need for particulate matter with an aerodynamic diameter less than 10?μm (PM(10)) emission inventories and for metrics to evaluate the emission control programs implemented by open-pit mines. STANDARDIZED EMISSION INVENTORY METHODOLOGY: To address these needs, work was carried out to establish a standardized TSP and PM(10) emission inventory methodology for open-pit mining areas. The proposed methodology was applied to seven of the eight mining companies operating in the northern part of Colombia, home to the one of the world's largest open-pit coal mining operations (～70?Mt/year). RESULTS: The results obtained show that transport on unpaved roads is the mining activity that generates most of the emissions and that the total emissions may be reduced up to 72% by spraying water on the unpaved roads. Performance metrics were defined for the emission control programs implemented by mining companies. It was found that coal open-pit mines are emitting 0.726 and 0.180?kg of TSP and PM(10), respectively, per ton of coal produced. It was also found that these mines are using on average 1.148?m(2) of land per ton of coal produced per year.     

深圳市在用柴油公交车排放研究

以公交车为例,利用OBS-2200和ELPI(electrical low pressure impactor)对深圳市重型柴油车(high-duty diesel vehicles,HDDVs)进行了3次在实际道路上的车载排放测试.根据测试数据计算了NOx和PM排放因子及百公里油耗,并分析了不同道路、不同工况对NOx...     

Mobile load simulators – A tool to distinguish between the emissions due to abrasion and resuspension of PM10 from road surfaces

Mechanically produced abrasion particles and resuspension processes are responsible for a significant part of the PM10 emissions of road traffic. However, specific differentiation between PM10 emissions due to abrasion and resuspension from road pavement is very difficult due to their similar elemental composition and highly correlated variation in time. In this work Mobile Load Simulators were used to estimate PM10 emission factors for pavement abrasion and resuspension on different pavement types for light and heavy duty vehicles.From the experiments it was derived that particle emissions due to abrasion from pavements in good condition are quite low in the range of only a few mg·km^?1 per vehicle if quantifiable at all. Considerable abrasion emissions, however, can occur from damaged pavements. Resuspension of deposited dust can cause high and extremely variable particle emissions depending strongly on the dirt load of the road surface. Porous pavements seem to retain deposited dust better than dense pavements, thus leading to lower emissions due to resuspension compared to pavements with a dense structure (e.g. asphalt concrete). Tyre wear seemed not to be a quantitatively significant source of PM10 emissions from road traffic.     

Revised estimates of construction activity and emissions: Effects on ozone and elemental carbon concentrations in southern California

Emissions from diesel-powered construction equipment are an important source of nitrogen oxides (NO_x) and particulate matter (PM). A new emission inventory for construction equipment emissions is developed based on surveys of diesel fuel use; the revised inventory is compared to current emission inventories. California's OFFROAD model estimates are 4.5 and 3.1 times greater, for NO_x and PM respectively, than the fuel-based estimates developed here. The most relevant uncertainties are the overall amount of construction activity/diesel fuel use, exhaust emission factors for PM and NO_x, and the spatial allocation of emissions to county level and finer spatial scales. Construction permit data were used in this study to estimate spatial distributions of emissions; the resulting distribution is well correlated with population growth. An air quality model was used to assess the impacts of revised emission estimates. Increases of up to 15 ppb in predicted peak ozone concentrations were found in southern California. Elemental carbon and fine particle mass concentrations were in better agreement with observations using revised emission estimates, whereas negative bias in predictions of ambient NO_x concentrations increased.     

Effectiveness of emission control technologies for auxiliary engines on ocean-going vessels

Large auxiliary engines operated on ocean-going vessels in transit and at berth impact the air quality of populated areas near ports. This paper presents new information on the comparison of emission ranges from three similar engines and the effectiveness of three control technologies: switching to cleaner burning fuels, operating in the low oxides of nitrogen (NOx) mode, and selective catalytic reduction (SCR). In-use measurements of gaseous (NOx, carbon monoxide [CO], carbon dioxide [CO2]) and fine particulate matter (PM2.5; total and speciated) emissions were made on three auxiliary engines on post-PanaMax class container vessels following the International Organization for Standardization-8178-1 protocol. The in-use NOx emissions for the MAN B&W 7L32/40 engine family vary from 15 to 21.1 g/kW-hr for heavy fuel oil and 8.9 to 19.6 g/kW-hr for marine distillate oil. Use of cleaner burning fuels resulted in NOx reductions ranging from 7 to 41% across different engines and a PM2.5 reduction of up to 83%. The NOx reductions are a consequence of fuel nitrogen content and engine operation; the PM2.5 reduction is attributed to the large reductions in the hydrated sulfate and organic carbon (OC) fractions. As expected, operating in the low-NOx mode reduced NOx emissions by approximately 32% and nearly doubled elemental carbon (EC) emissions. However, PM2.5 emission factors were nearly unchanged because the EC emission factor is only approximately 5% of the total PM2.5 mass. SCR reduced the NOx emission factor to less than 2.4 g/kW-hr, but it increased the PM2.5 emissions by a factor of 1.5-3.8. This increase was a direct consequence of the conversion of sulfur dioxide to sulfate emissions on the SCR catalyst. The EC and OC fractions of PM2.5 reduced across the SCR unit.     

Updating the conceptual model for fine particle mass emissions from combustion systems

Atmospheric transformations determine the contribution of emissions from combustion systems to fine particulate matter (PM) mass. For example, combustion systems emit vapors that condense onto existing particles or form new particles as the emissions are cooled and diluted. Upon entering the atmosphere, emissions are exposed to atmospheric oxidants and sunlight, which causes them to evolve chemically and physically, generating secondary PM. This review discusses these transformations, focusing on organic PM. Organic PM emissions are semi-volatile at atmospheric conditions and thus their partitioning varies continuously with changing temperature and concentration. Because organics contribute a large portion of the PM mass emitted by most combustion sources, these emissions cannot be represented using a traditional, static emission factor. Instead, knowledge of the volatility distribution of emissions is required to explicitly account for changes in gas-particle partitioning. This requires updating how PM emissions from combustion systems are measured and simulated from combustion systems. Secondary PM production often greatly exceeds the direct or primary PM emissions; therefore, secondary PM must be included in any assessment of the contribution of combustion systems to ambient PM concentrations. Low-volatility organic vapors emitted by combustion systems appear to be very important secondary PM precursors that are poorly accounted for in inventories and models. The review concludes by discussing the implications that the dynamic nature of these PM emissions have on source testing for emission inventory development and regulatory purposes. This discussion highlights important linkages between primary and secondary PM, which could lead to simplified certification test procedures while capturing the emission components that contribute most to atmospheric PM mass.     

Characterization of particulate matter and gaseous emissions of a C-130H aircraft

The gaseous and nonvolatile particulate matter (PM) emissions of two T56-A-15 turboprop engines of a C-130H aircraft stationed at the 123rd Airlift Wing in the Kentucky Air National Guard were characterized. The emissions campaign supports the Strategic Environmental Research and Development Program (SERDP) project WP-1401 to determine emissions factors from military aircraft. The purpose of the project is to develop a comprehensive emissions measurement program using both conventional and advanced techniques to determine emissions factors of pollutants, and to investigate the spatial and temporal evolutions of the exhaust plumes from fixed and rotating wing military aircraft. Standard practices for the measurement of gaseous emissions from aircraft have been well established; however, there is no certified methodology for the measurement of aircraft PM emissions. In this study, several conventional instruments were used to physically characterize and quantify the PM emissions from the two turboprop engines. Emissions samples were extracted from the engine exit plane and transported to the analytical instrumentation via heated lines. Multiple sampling probes were used to assess the spatial variation and obtain a representative average of the engine emissions. Particle concentrations, size distributions, and mass emissions were measured using commercially available aerosol instruments. Engine smoke numbers were determined using established Society of Automotive Engineers (SAE) practices, and gaseous species were quantified via a Fourier-transform infrared-based gas analyzer. The engines were tested at five power settings, from idle to take-off power, to cover a wide range of operating conditions. Average corrected particle numbers (PNs) of (6.4-14.3) x 10(7) particles per cm3 and PN emission indices (EI) from 3.5 x 10(15) to 10.0 x 10(15) particles per kg-fuel were observed. The highest PN EI were observed for the idle power conditions. The mean particle diameter varied between 50 nm at idle to 70 nm at maximum engine power. PM mass EI ranged from 1.6 to 3.5 g/kg-fuel for the conditions tested, which are in agreement with previous T56 engine measurements using other techniques. Additional PM data, smoke numbers, and gaseous emissions will be presented and discussed.     

Evaluation of particulate matter abatement strategies for almond harvest

Almond harvest accounts for substantial PM10 (particulate matter [PM] < or =10 microm in nominal aerodynamic diameter) emissions in California each harvest season. This paper evaluates the effects of using reduced-pass sweepers and lower harvester separation fan speeds (930 rpm) on lowering PM emissions from almond harvesting operations. In-canopy measurements of PM concentrations were collected along with PM concentration measurements at the orchard boundary; these were used in conjunction with on-site meteorological data and inverse dispersion modeling to back-calculate emission rates from the measured concentrations. The harvester discharge plume was measured as a function of visible plume opacity during conditioning operations. Reduced-pass sweeping showed the potential for reducing PM emissions, but results were confounded because of differences in orchard maturity and irrigation methods. Fuel consumption and sweeping time per unit area were reduced when comparing a reduced-pass sweeper to a conventional sweeper. Reducing the separation fan speed from 1080 to 930 rpm led to reductions in PM emissions. In general, foreign matter levels within harvested product were nominally affected by separation fan speed in the south (less mature) orchard; however, in samples conditioned using the lower fan speed from the north (more mature) orchard, these levels were unacceptable.     

Impact of biogenic emission uncertainties on the simulated response of ozone and fine particulate matter to anthropogenic emission reductions

The role of emissions of volatile organic compounds and nitric oxide from biogenic sources is becoming increasingly important in regulatory air quality modeling as levels of anthropogenic emissions continue to decrease and stricter health-based air quality standards are being adopted. However, considerable uncertainties still exist in the current estimation methodologies for biogenic emissions. The impact of these uncertainties on ozone and fine particulate matter (PM2.5) levels for the eastern United States was studied, focusing on biogenic emissions estimates from two commonly used biogenic emission models, the Model of Emissions of Gases and Aerosols from Nature (MEGAN) and the Biogenic Emissions Inventory System (BEIS). Photochemical grid modeling simulations were performed for two scenarios: one reflecting present day conditions and the other reflecting a hypothetical future year with reductions in emissions of anthropogenic oxides of nitrogen (NOx). For ozone, the use of MEGAN emissions resulted in a higher ozone response to hypothetical anthropogenic NOx emission reductions compared with BEIS. Applying the current U.S. Environmental Protection Agency guidance on regulatory air quality modeling in conjunction with typical maximum ozone concentrations, the differences in estimated future year ozone design values (DVF) stemming from differences in biogenic emissions estimates were on the order of 4 parts per billion (ppb), corresponding to approximately 5% of the daily maximum 8-hr ozone National Ambient Air Quality Standard (NAAQS) of 75 ppb. For PM2.5, the differences were 0.1-0.25 microg/m3 in the summer total organic mass component of DVFs, corresponding to approximately 1-2% of the value of the annual PM2.5 NAAQS of 15 microg/m3. Spatial variations in the ozone and PM2.5 differences also reveal that the impacts of different biogenic emission estimates on ozone and PM2.5 levels are dependent on ambient levels of anthropogenic emissions.     

Boiler briquette coal versus raw coal: Part I--Stack gas emissions

Stack gas emissions were characterized for a steam-generating boiler commonly used in China. The boiler was tested when fired with a newly formulated boiler briquette coal (BB-coal) and when fired with conventional raw coal (R-coal). The stack gas emissions were analyzed to determine emission rates and emission factors and to develop chemical source profiles. A dilution source sampling system was used to collect PM on both Teflon membrane filters and quartz fiber filters. The Teflon filters were analyzed gravimetrically for PM10 and PM2.5 mass concentrations and by X-ray fluorescence (XRF) for trace elements. The quartz fiber filters were analyzed for organic carbon (OC) and elemental carbon (EC) using a thermal/optical reflectance technique. Sulfur dioxide was measured using the standard wet chemistry method. Carbon monoxide was measured using an Orsat combustion analyzer. The emission rates of the R-coal combustion (in kg/hr), determined using the measured stack gas concentrations and the stack gas emission rates, were 0.74 for PM10, 0.38 for PM2.5, 20.7 for SO2, and 6.8 for CO, while those of the BB-coal combustion were 0.95 for PM10, 0.30 for PM2.5, 7.5 for SO2, and 5.3 for CO. The fuel-mass-based emission factors (in g/kg) of the R-coal, determined using the emission rates and the fuel burn rates, were 1.68 for PM10, 0.87 for PM2.5, 46.7 for SO2, and 15 for CO, while those of the BB-coal were 2.51 for PM10, 0.79 for PM2.5, 19.9 for SO2, and 14 for CO. The task-based emission factors (in g/ton steam generated) of the R-coal, determined using the fuel-mass-based emission factors and the coal/steam conversion factors, were 0.23 for PM10, 0.12 for PM2.5, 6.4 for SO2, and 2.0 for CO, while those of the BB-coal were 0.30 for PM10, 0.094 for PM2.5, 2.4 for SO2, and 1.7 for CO. PM10 and PM2.5 elemental compositions are also presented for both types of coal tested in the study.     

Scattering cross-section emission factors for visibility and radiative transfer applications: military vehicles traveling on unpaved roads

Emission factors for particulate matter (PM) are generally reported as mass emission factors (PM mass emitted per time or activity) as appropriate for air quality standards based on mass concentration. However, for visibility and radiative transfer applications, scattering, absorption, and extinction coefficients are the parameters of interest, with visibility standards based on extinction coefficients. These coefficients (dimension of inverse distance) equal cross-section concentrations, and, therefore, cross-section emission factors are appropriate. Scattering cross-section emission factors were determined for dust entrainment by nine vehicles, ranging from light passenger vehicles to heavy military vehicles, traveling on an unpaved road. Each vehicle made multiple passes at multiple speeds while scattering and absorption coefficients, wind velocity and dust plume profiles, and additional parameters were measured downwind of the road. Light absorption of the entrained PM was negligible, and the light extinction was primarily caused by scattering. The resulting scattering cross-section emission factors per vehicle kilometer traveled (vkt) range from 12.5 m2/vkt for a slow (16 km/ hr), light (1176 kg) vehicle to 3724 m2/vkt for a fast (64 km/hr), heavy (17,727 kg) vehicle and generally increase with vehicle speed and mass. The increase is approximately linear with speed, yielding emission factors per vkt and speed ranging from 4.2 m2/(vkt km/hr) to 53 m2/(vkt km/hr). These emission factors depend approximately linearly on vehicle mass within the groups of light (vehicle mass < or =3100 kg) and heavy (vehicle mass >8000 kg) vehicles yielding emission factors per vkt, speed, and mass of 0.0056 m2/(vkt km/hr kg) and 0.0024 m2/(vkt km/hr kg), respectively. Comparison of the scattering cross-section and PM mass emission factors yields average mass scattering efficiencies of 1.5 m2/g for the light vehicles and of 0.8 m2/g for the heavy vehicles indicating that the heavy vehicles entrain larger particles than the light vehicles.     

Development and preliminary evaluation of a particulate matter emission factor model for European motor vehicles

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 microns, 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, PM2.5, 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.     

Combustion sources of particles: 2. Emission factors and measurement methods

Emissions from the combustion of biomass and fossil fuels are a significant source of particulate matter (PM) in ambient outdoor and/or indoor air. It is important to quantify PM emissions from combustion sources for regulatory and control purposes in relation to air quality. In this paper, we review emission factors for several types of important combustion sources: road transport, industrial facilities, small household combustion devices, environmental tobacco smoke, and vegetation burning. We also review current methods for measuring particle physical characteristics (mass and number concentrations) and principles of methodologies for measuring emission factors. The emission factors can be measured on a fuel-mass basis and/or a task basis. Fuel-mass based emission factors (e.g., g/kg of fuel) can be readily used for the development of emission inventories when the amount of fuels consumed are known. Task-based emission factors (g/mile driven, g/MJ generated) are more appropriate when used to conduct comparisons of air pollution potentials of different combustion devices. Finally, we discuss major shortcomings and limitations of current methods for measuring particle emissions and present recommendations for development of future measurement techniques.     

Development of a microscale emission factor model for particulate matter for predicting real-time motor vehicle emissions

The U.S. Environmental Protection Agency's National Exposure Research Laboratory is pursuing a project to improve the methodology for modeling human exposure to motor vehicle emissions. The overall project goal is to develop improved methods for modeling the source through the air pathway to human exposure in significant exposure microenvironments. Current particulate matter (PM) emission models, particle emission factor model (used in the United States, except California) and motor vehicle emission factor model (used in California only), are suitable only for county-scale modeling and emission inventories. There is a need to develop a site-specific real-time emission factor model for PM emissions to support human exposure studies near roadways. A microscale emission factor model for predicting site-specific real-time motor vehicle PM (MicroFacPM) emissions for total suspended PM, PM less than 10 microm aerodynamic diameter, and PM less than 2.5 microm aerodynamic diameter has been developed. The algorithm used to calculate emission factors in MicroFacPM is disaggregated, and emission factors are calculated from a real-time fleet, rather than from a fleet-wide average estimated by a vehicle-miles-traveled weighting of the emission factors for different vehicle classes. MicroFacPM requires input information necessary to characterize the site-specific real-time fleet being modeled. Other variables required include average vehicle speed, time and day of the year, ambient temperature, and relative humidity.     

Sensitivity analysis and evaluation of MicroFacPM: a microscale motor vehicle emission factor model for particulate matter emissions

A microscale emission factor model (MicroFacPM) for predicting real-time site-specific motor vehicle particulate matter emissions was presented in the companion paper titled "Development of a Microscale Emission Factor Model for Particulate Matter (MicroFacPM) for Predicting Real-Time Motor Vehicle Emissions". The emission rates discussed are in mass per unit distance with the model providing estimates of fine particulate matter (PM2.5) and coarse particulate matter. This paper complements the companion paper by presenting a sensitivity analysis of the model to input variables and evaluation model outputs using data from limited field studies. The sensitivity analysis has shown that MicroFacPM emission estimates are very sensitive to vehicle fleet composition, speed, and the percentage of high-emitting vehicles. The vehicle fleet composition can affect fleet emission rates from 8 mg/mi to 1215 mg/mi; an increase of 5% in the smoking (high-emitting) current average U.S. light-duty vehicle fleet (compared with 0%) increased PM2.5 emission rates by -272% for 2000; and for the current U.S. fleet, PM2.5 emission rates are reduced by a factor of -0.64 for speeds >50 miles per hour (mph) relative to a speed of 10 mph. MicroFacPM can also be applied to examine the contribution of emission rates per vehicle class, model year, and sources of PM. The model evaluation is presented for the Tuscarora Mountain Tunnel, Pennsylvania Turnpike, PA, and some limited evaluations at two locations: Sepulveda Tunnel, Los Angeles, CA, and Van Nuys Tunnel, Van Nuys, CA. In general, the performance of MicroFacPM has shown very encouraging results.