Atmospheric particulate emissions from dry abrasive blasting using coal slag

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).     

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.     

Characterization of Particulate Matter and Gaseous Emissions of a C-130H Aircraft

Abstract

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) × 10⁷ particles per cm³ and PN emission indices (EI) from 3.5 × 10¹⁵ to 10.0 × 10¹⁵ 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.     

Sources of Atmospheric Carbonaceous Particulate Matter in Pittsburgh,Pennsylvania

Abstract

The organic carbon (OC)/elemental carbon (EC) tracer method is applied to the Pittsburgh, PA, area to estimate the contribution of secondary organic aerosol (SOA) to the monthly average concentration of organic particu-late matter (PM) during 1995. An emissions inventory is constructed for the primary emissions of OC and EC in the area of interest. The ratio of primary emissions of OC to those of EC ranges between 2.4 in the winter months and 1.0 in the summer months. A mass balance model and ambient measurements were used to assess the accuracy of the emissions inventory. It is estimated to be accurate to within 50%. The results from this analysis show a strong monthly dependence on SOA contribution to the total organic PM concentration, varying from near zero during winter months to 50% or more of the total OC concentration in the summer.     

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...     

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.     

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.     

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.     

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.     

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.     

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.     

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.     

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.     

Sampling and Analysis of Volatile Organic Compounds Evolved During Thermal Processing of Acrylonitrile Butadiene Styrene Composite Resins

Abstract

The evaluation of emissions of volatile organic compounds (VOCs) during processing of resins is of interest to resin manufacturers and resin processors. An accurate estimate of the VOCs emitted from resin processing has been difficult due to the wide variation in processing facilities. This study was designed to estimate the emissions in terms of mass of emitted VOC per mass of resin processed.

A collection and analysis method was developed and validated for the determination of VOCs present in the emissions of thermally processed acrylonitrile butadiene styrene (ABS) resins. Four composite resins were blended from automotive, general molding, pipe, and refrigeration grade ABS resins obtained from the manufacturers. Emission samples were collected in evacuated 6-L Summa canisters and then analyzed using gas chromatography/flame ionization detection/mass selective detection (GC/FID/MSD). Levels were determined for nine target analytes detected in canister samples, and for total VOCs detected by an inline GC/FID. The emissions evolved from the extrusion of each composite resin were expressed in terms of mass of VOCs per mass of processed resin. Styrene was the principal volatile emission from all the composite resins. VOCs analyzed from the pipe resin sample contained the highest level of styrene at 402 μg/g. An additional collection and detection method was used to determine the presence of aerosols in the emissions. This method involved collecting particulates on glass fiber filters, extracting them with solvents, and analyzing them using gas chromatography/mass spectrometry (GC/MS). No significant levels of any of the target analytes were detected on the filters.     

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.     

Field Measurements of Particulate Matter Emissions,Carbon Monoxide,and Exhaust Opacity from Heavy-Duty Diesel Vehicles

ABSTRACT

Diesel particulate matter (PM) is a significant contributor to ambient air PM₁₀ and PM_2.5 particulate levels. In addition, recent literature argues that submicron diesel PM is a pulmonary health hazard. There is difficulty in attributing PM emissions to specific operating modes of a diesel engine, although it is acknowledged that PM production rises dramatically with load and that high PM emissions occur during rapid load increases on turbocharged engines. Snap-acceleration tests generally identify PM associated with rapid transient operating conditions, but not with high load. To quantify the origin of PM during transient engine operation, continuous opacity measurements have been made using a Wager 650CP full flow exhaust opacity meter. Opacity measurements were taken while the vehicles were operated over transient driving cycles on a chassis dynamometer using the West Virginia University (WVU) Transportable Heavy Duty Vehicle Emissions Testing Laboratories. Data were gathered from Detroit Diesel, Cummins, Caterpillar, and Navistar heavy-duty (HD) diesel engines. Driving cycles used were the Central Business District (CBD) cycle, the WVU 5-Peak Truck cycle, the WVU 5-Mile route, and the New York City Bus (NYCB) cycle. Continuous opacity measurements, integrated over the entire driving cycle, were compared to total integrated PM mass. In addition, the truck was subjected to repeat snap-acceleration tests, and PM was collected for a composite of these snap-acceleration tests. Additional data were obtained from a fleet of 1996 New Flyer buses in Flint, MI, equipped with electronically controlled Detroit Diesel Series 50 engines. Again, continuous opacity, regulated gaseous emissions, and PM were measured. The relationship between continuous carbon monoxide (CO) emissions and continuous opacity was noted. In identifying the level of PM emissions in transient diesel engine operation, it is suggested that CO emissions may prove to be a useful indicator and may be used to apportion total PM on a continuous basis over a transient cycle. The projected continuous PM data will prove valuable in future mobile source inventory prediction.     

The Formation of Mg3Ca(S04)4 during the Sulfation Reaction of Dolomite

Abstract

Inspection and maintenance programs for motor vehicles in the United States increasingly use loaded mode mass emissions testing (IM240). A method was developed to predict mass emission rates and mass emission changes, particularly from repair benefits, using a low-cost, portable four-gas non-dispersive infrared (NDIR) vehicle exhaust gas analyzer. A single vehicle was tested several times with the analyzer while on the dynamometer and undergoing successive repairs. Excellent correlations for CO and HC were observed. Five vehicles were measured using an on-road driving loop before and after emissions-related repairs, while another three vehicles were tested with no repairs performed. The on-road concentration data used to guide the repair process were converted to grams per gallon; when divided by estimated miles per gallon, this gave grams per mile emissions for comparison to IM240. Correlation coefficients (r²) of 0.87 for CO and 0.76 for HC were achieved for the 13 tests. The linear correlations between IM240 and emissions measured by this method would allow repair facilities to perform a relatively inexpensive test for diagnostic purposes and to estimate repair effectiveness without the need for a dynamometer.