Evaluating vehicle re-entrained road dust and its potential to deposit to Lake Tahoe: a bottom-up inventory approach.

Identifying hotspot areas impacted by emissions of dust from roadways is an essential step for mitigation. This paper develops a detailed road dust PM10 emission inventory using a bottom-up approach and evaluates the potential for the dust to deposit to Lake Tahoe where it can affect water clarity. Previous studies of estimates of quantities of atmospheric deposition of fine sediment particles ("FSP", <16 µm in diameter) to the lake were questioned due to low confidence in the results and insufficient data. A bottom-up approach that integrates measured road dust emission factors, five years of meteorological data, a traffic demand model and GIS analysis was used to estimate the near field deposition of airborne particulate matter <16 µm, and assess the relationship between trip location and the potential magnitude of this source of atmospheric deposition to the lake. Approximately ~20 Mg year(-1) of PM10 and ~36 Mg year(-1) Total Suspended Particulate (TSP) from roadway emissions of dust are estimated to reach the lake. We estimate that the atmospheric dry deposition of particles to the lake attributable to vehicle travel on paved roads is approximately 0.6% of the Total Maximum Daily Loadings (TMDL) of FSP that the lake can receive and still meet water quality standards.

Particulate emission factors for mobile fossil fuel and biomass combustion sources.

PM emission factors (EFs) for gasoline- and diesel-fueled vehicles and biomass combustion were measured in several recent studies. In the Gas/Diesel Split Study (GD-Split), PM(2.5) EFs for heavy-duty diesel vehicles (HDDV) ranged from 0.2 to ~2 g/mile and increased with vehicle age. EFs for HDDV estimated with the U.S. EPA MOBILE 6.2 and California Air Resources Board (ARB) EMFAC2007 models correlated well with measured values. PM(2.5) EFs measured for gasoline vehicles were ~two orders of magnitude lower than those for HDDV and did not correlate with model estimates. In the Kansas City Study, PM(2.5) EFs for gasoline-powered vehicles (e.g., passenger cars and light trucks) were generally <0.03 g/mile and were higher in winter than summer. EMFAC2007 reported higher PM(2.5) EFs than MOBILE 6.2 during winter, but not during summer, and neither model captured the variability of the measured EFs. Total PM EFs for heavy-duty diesel military vehicles ranged from 0.18±0.03 and 1.20±0.12 g/kg fuel, corresponding to 0.3 and 2 g/mile, respectively. These values are comparable to those of on-road HDDV. EFs for biomass burning measured during the Fire Laboratory at Missoula Experiment (FLAME) were compared with EFs from the ARB Emission Estimation System (EES) model. The highest PM(2.5) EFs (76.8±37.5 g/kg) were measured for wet (>50% moisture content) Ponderosa Pine needles. EFs were generally <20 g/kg when moisture content was <20%. The EES model agreed with measured EFs for fuels with low moisture content but underestimated measured EFs for fuel with moisture content >40%. Average EFs for dry chamise, rice straw, and dry grass were within a factor of three of values adopted by ARB in California's San Joaquin Valley (SJV). Discrepancies between measured and modeled emission factors suggest that there may be important uncertainties in current PM(2.5) emission inventories.

Fugitive dust emissions from paved road travel in the Lake Tahoe basin.

The clarity of water in Lake Tahoe has declined substantially over the past 40 yr. Causes of the degradation include nitrogen and phosphorous fertilization of the lake waters and increasing amounts of inorganic fine sediment that can scatter light. Atmospheric deposition is a major source of fine sediment. A year-round monitoring study of road dust emissions around the lake was completed in 2007 using the Testing Re-entrained Aerosol Kinetic Emissions from Roads (TRAKER) system developed at the Desert Research Institute (DRI). Results of this study found that, compared with the summer season, road dust emissions increased by a factor of 5 in winter, on average, and about a factor of 10 when traction control material was applied to the roads after snow events. For winter and summer, road dust emission factors (grams coarse particulate matter [PM10] per vehicle kilometer traveled [g/vkt]) showed a decreasing trend with the travel speed of the road. The highest emission factors were observed on very low traffic volume roads on the west side of the lake. These roads were composed of either a 3/8-in. gravel material or had degraded asphalt. The principle factors influencing road dust emissions in the basin are season, vehicle speed (or road type), road condition, road grade, and proximity to other high-emitting roads. Combined with a traffic volume model, an analysis of the total emissions from the road sections surveyed indicated that urban areas (in particular South Lake Tahoe) had the highest emitting roads in the basin.

The In-Plume Emission Test Stand: an instrument platform for the real-time characterization of fuel-based combustion emissions.

The In-Plume Emission Test Stand (IPETS) characterizes gaseous and particulate matter (PM) emissions from combustion sources in real time. Carbon dioxide (CO2), carbon monoxide (CO), nitric oxide (NO), nitrogen dioxide (NO2), and other gases are quantified with a closed-path Fourier transform infrared spectrometer (FTIR). Particle concentrations, chemical composition, and other particle properties are characterized with an electrical low-pressure impactor (ELPI), a light-scattering particle detector, an optical particle counter, and filter samples amenable to different laboratory analysis. IPETS measurements of fuel-based emission factors for a diesel generator are compared with those from a Mobile Emissions Laboratory (MEL). IPETS emission factors ranged from 0.3 to 11.8, 0.2 to 3.7, and 22.2 to 32.8 g/kg fuel for CO, NO2, and NO, respectively. IPETS PM emission factors ranged from 0.4 to 1.4, 0.3 to 1.8, 0.3 to 2.2, and 1 to 3.4 g/kg fuel for filter, photoacoustic, nephelometer, and impactor measurements, respectively. Observed linear regression statistics for IPETS versus MEL concentrations were as follows: CO slope = 1.1, r2 = 0.99; NO slope = 1.1, r2 = 0.92; and NO2 slope = 0.8, r2 = 0.96. IPETS versus MEL PM regression statistics were: filter slope = 1.3, r2 = 0.80; ELPI slope = 1.7, r2 = 0.87; light-scattering slope = 2.7, r2 = 0.92; and photoacoustic slope = 2.1, r2 = 0.91. Lower temperatures in the dilution air (approximately 25 degrees C for IPETS vs. approximately 50 degrees C for MEL) may result in greater condensation of semi-volatile compounds on existing particles, thereby explaining the 30% difference for filters. The other PM measurement devices are highly correlated with the filter, but their factory-default PM calibration factors do not represent the size and optical properties of diesel exhaust. They must be normalized to a simultaneous filter measurement.

In-Plume Emission Test Stand 2: emission factors for 10- to 100-kW U.S. military generators.

Although emissions of air pollutants from some military tactical equipment are not subject to the emissions standards, local communities near military bases must conform to the National Ambient Air Quality Standards. Military diesel generators are widely used in training. A portable in-plume system was used to measure fuel-based emission factors (EFs) for particulate matter (PM), carbon monoxide (CO), nitrogen oxides (NOx), and hydrocarbons (HCs) for 30-, 60-, and 100-kW generators at five load levels and for cold starts. It was found that EFs depend on multiple parameters including engine size, engine load, unit age, and total running hours. The average CO EF of generators tested was 5% lower, and the average NOx EF was 63% lower than AP-42 estimates; average PM EF was 80% less than the AP-42 estimates. A 2002 model-year 60-kW engine produced 25% less PM than a 1995 engine of the same family with similar running hours. CO EFs decrease with increasing engine load, NOx EFs increase up to mid-loads and decrease slightly at high loads, PM EFs increase with loads for 30- and 60-kW engines. CO and PM have higher EFs and NOx has a lower EF during cold starts than during hot-stabilized operation. PM chemical source profiles were also examined.

A case study of real-world tailpipe emissions for school buses using a 20% biodiesel blend.

Numerous laboratory studies report carbon monoxide, hydrocarbon, and particulate matter emission reductions with a slight nitrogen oxides emission increase from engines operating with biodiesel and biodiesel blends as compared to using petroleum diesel. We conducted a field study on a fleet of school buses to evaluate the effects of biodiesel use on gaseous and particulate matter fuel-based emission factors under real-world conditions. The field experiment was carried out in two phases during winter 2004. In January (phase I), emissions from approximately 200 school buses operating on petroleum diesel were measured. Immediately after the end of the first phase measurement period, the buses were switched to a 20% biodiesel blend. Emission factors were measured again in March 2004 (phase II) and compared with the January emission factors. To measure gaseous emission factors we used a commercial gaseous remote sensor. Particulate matter emission factors were determined with a combination of the gaseous remote sensor, a Lidar (light detection and ranging), and transmissometer system developed at the Desert Research Institute of Reno, NV, U.S.A. Particulate matter emissions from school buses significantly increased (up to a factor of 1.8) after the switch from petroleum diesel to a 20% biodiesel blend. The fuel used during this campaign was provided by a local distributor and was independently analyzed at the end of the on-road experiment. The analysis found high concentrations of free glycerin and reduced flash points in the B 100 parent fuel. Both measures indicate improper separation and processing of the biodiesel product during production. The biodiesel fuels used in the school buses were not in compliance with the U.S.A. ASTM D6751 biodiesel standard that was finalized in December of 2001. The U.S.A. National Biodiesel Board has formed a voluntary National Biodiesel Accreditation Program for producers and marketers of biodiesel to ensure product quality and compliance with the ASTM standard. The results of our study underline the importance of the program since potential emission benefits from biodiesel may be reduced or even reversed without appropriate fuel quality control on real-world fuels.

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.

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 of a United States-Mexico Emissions Inventory for the Big Bend Regional Aerosol and Visibility Observational (BRAVO) Study.

The Big Bend Regional Aerosol and Visibility Observational (BRAVO) Study was commissioned to investigate the sources of haze at Big Bend National Park in southwest Texas. The modeling domain of the BRAVO Study includes most of the continental United States and Mexico. The BRAVO emissions inventory was constructed from the 1999 National Emission Inventory for the United States, modified to include finer-resolution data for Texas and 13 U.S. states in close proximity. The first regional-scale Mexican emissions inventory designed for air-quality modeling applications was developed for 10 northern Mexican states, the Tula Industrial Park in the state of Hidalgo, and the Popocatépetl volcano in the state of Puebla. Emissions data were compiled from numerous sources, including the U.S. Environmental Protection Agency (EPA), the Texas Natural Resources Conservation Commission (now Texas Commission on Environmental Quality), the Eastern Research Group, the Minerals Management Service, the Instituto Nacional de Ecología, and the Instituto Nacional de Estadistica Geografía y Informática. The inventory includes emissions for CO, nitrogen oxides, sulfur dioxide, volatile organic compounds (VOCs), ammonia, particulate matter (PM) < 10 microm in aerodynamic diameter, and PM < 2.5 microm in aerodynamic diameter. Wind-blown dust and biomass burning were not included in the inventory, although high concentrations of dust and organic PM attributed to biomass burning have been observed at Big Bend National Park. The SMOKE modeling system was used to generate gridded emissions fields for use with the Regional Modeling System for Aerosols and Deposition (REMSAD) and the Community Multiscale Air Quality model modified with the Model of Aerosol Dynamics, Reaction, Ionization and Dissolution (CMAQ-MADRID). The compilation of the inventory, supporting model input data, and issues encountered during the development of the inventory are documented. A comparison of the BRAVO emissions inventory for Mexico with other emerging Mexican emission inventories illustrates their uncertainty.

Spatial variability of unpaved road dust PM10 emission factors near El Paso, Texas.

The testing re-entrained aerosol kinetic emissions from roads technique is compared with distance-based emission factors (EFs; g/VKT) measured downwind of a dirt road by using towers instrumented with real-time meteorological and particle sensors at multiple heights. The emission potential (EP), defined as the EF divided by the vehicle speed (m/sec), and weight index permits the intercomparison of emissions from multiple roadways surveyed by the TRAKER vehicle. A survey of 72 km of unpaved roads on the Ft. Bliss Military Base near El Paso, Texas, indicated that 60% of all measured EPs fell between 6.7 (g/VKT)/(m/sec) and 9.6 (g/VKT)/(m/sec). The EP measured across the base was approximately 50% lower than those collected in the vicinity of the instrumented towers. This implies that EFs measured for other vehicles on the same test section should be reduced by 50% to more accurately represent EFs for the entire military base. Using geographic information system-based soil maps, the inferred EFs are related to differences in soil types over the survey area. Variations among five different soil types accounted for <10% of variation in EP. Individual measurements using the testing re-entrained aerosol kinetic emissions from roads technique did show larger spatial variations in EP; however, these were not effectively captured by the soil classifications, partly because of the comparatively coarse spatial classification used in the soil survey data.

Deposition and removal of fugitive dust in the arid southwestern United States: measurements and model results.

This work was motivated by the need to better reconcile emission factors for fugitive dust with the amount of geologic material found on ambient filter samples. The deposition of particulate matter with aerodynamic diameter less than or equal to 10 microm (PM10), generated by travel over an unpaved road, over the first 100 m of transport downwind of the road was examined at Ft. Bliss, near El Paso, TX. The field conditions, typical for warm days in the arid southwestern United States, represented sparsely vegetated terrain under neutral to unstable atmospheric conditions. Emission fluxes of PM10 dust were obtained from towers downwind of the unpaved road at 7, 50, and 100 m. The horizontal flux measurements at the 7 m and 100 m towers indicated that PM10 deposition to the vegetation and ground was too small to measure. The data indicated, with 95% confidence, that the loss of PM10 between the source of emission at the unpaved road, represented by the 7 m tower, and a point 100 m downwind was less than 9.5%. A Gaussian model was used to simulate the plume. Values of the vertical standard deviation sigma(z) and the deposition velocity Vd were similar to the U.S. Environmental Protection Agency (EPA) ISC3 model. For the field conditions, the model predicted that removal of PM10 unpaved road dust by deposition over the distance between the point of emission and 100 m downwind would be less than 5%. However, the model results also indicated that particles larger than 10 microm (aerodynamic diameter) would deposit more appreciably. The model was consistent with changes observed in size distributions between 7 m and 100 m downwind, which were measured with optical particle counters. The Gaussian model predictions were also compared with another study conducted over rough terrain and stable atmospheric conditions. Under such conditions, measured PM10 removal rates over 95 m of downwind transport were reported to be between 86% and 89%, whereas the Gaussian model predicted only a 30% removal. One explanation for the large discrepancy between measurements and model results was the possibility that under the conditions of the study, the dust plume was comparable in vertical extent to the roughness elements, thereby violating one of the model assumptions. Results of the field study reported here and the previous work over rough terrain bound the extent of particle deposition expected to occur under most unpaved road emission scenarios.

On-road vehicle particulate matter and gaseous emission distributions in Las Vegas, Nevada, compared with other areas.

During the spring and summer of 2000, 2001, and 2002, gaseous and particulate matter (PM) fuel-based emission factors for approximately 150,000 low-tailpipe, individual vehicles in the Las Vegas, NV, area were measured via on-road remote sensing. For the gaseous pollutants (carbon monoxide, hydrocarbons, and nitrogen oxide), a commercial vehicle emissions remote sensing system (VERSS) was used. The PM emissions were determined using a Lidar-based VERSS. Emission distributions and their shapes were analyzed and compared with previous studies. The large skewness of the distributions is evident for both gaseous pollutants and PM and has important implications for emission reduction policies, because the majority of emissions are attributed to a small fraction of vehicles. Results of this Las Vegas study and studies at other geographical locations were compared. The gaseous pollutants were found to be close to those measured by VERSS in other U.S. cities. The PM emission factors for spark ignition and diesel vehicles are in the range of previous tunnel and dynamometer studies.

Remote sensing of PM, NO, CO and HC emission factors for on-road gasoline and diesel engine vehicles in Las Vegas, NV.

A novel light detection and ranging-based remote sensing system was assembled and used to measure mass particulate matter (PM) emissions per unit of fuel burned from in-use on-road vehicles. A commercially available remote sensing system was concurrently used to measure emissions of carbon monoxide (CO), nitrogen oxide (NO) and hydrocarbons (HC). The two systems were used to measure 61,207 gasoline and 1180 diesel powered vehicle emissions in Las Vegas, NV from 4/4/2000 to 5/16/2002. Emission factors were related to vehicle age, weight class and fuel type by matching license IDs to the state registration data. Measurements of vehicle speed and acceleration permitted the analysis of emission factors by vehicle specific power (VSP). Average emission factors were calculated for light-duty (<3863 kg [8500 lbs]) gasoline vehicles (LDGV), light-duty diesel vehicles (LDDV), heavy-duty (>3863 kg [8500 lbs]) gasoline vehicles (HDGV) and heavy-duty diesel vehicles (HDDV). LDDV and HDDV emitted approximately 25 times more PM per mass of fuel than LDGV and HDGV. Sufficient numbers of LDGV were measured to relate VSP with CO, HC and NO emissions. No relationship was observed between PM emissions and VSP. PM emission factors from LDGV increased with vehicle age. Fuel-based emission factors measured by remote sensing were compared with MOBILE6 and PART5 emissions model factors. Good agreement was observed for HC emission factors for vehicles less than 20 years old. MOBILE6 CO emission factors were approximately 2 times greater than measured CO emission factors for vehicles less than 13 years old. Measured NO emission factors were approximately 50% greater than MOBILE6 factors for vehicles 7-15 years old but in good agreement for vehicles less than 7 years old. Measured PM emission factors showed a clear increase with vehicle age, however, PART5 uses only a single PM emission factor for LDGV less than 18 years old. The PM emission factors for the fleet of LDGV, HDGV, LDDV and HDDV were 0.06, 0.05, 1.6 and 1.5 g/kg, respectively.

Source profiles for industrial, mobile, and area sources in the Big Bend Regional Aerosol Visibility and Observational study.

Representative PM2.5 and PM10 source emissions were sampled in Texas during the Big Bend Regional Aerosol Visibility and Observa (BRAVO) study. Chemical source profiles for elements, ions, and carbon fractions of 145 samples are reported for paved and unpaved road dust, soil dust, motor vehicle exhaust, vegetative burning, four coal-fired power stations, an oil refinery catalytic cracker, two cement kilns, and residential meat cooking. Several samples were taken from each emitter and source type, and these were averaged by source type, and in source subgroups based on commonality of chemical composition. The standard deviation represents the variability of the chemical mass fractions. BRAVO profiles differed in some respects from profiles measured elsewhere. High calcium abundances in geological dust, high selenium abundances in coal-fired power stations, and high antimony abundances in oil refinery catalytic cracker emissions were found. Abundances of eight thermally evolved carbon fractions [Atmos. Environ. 28 (15) (1994) 2493] differ among combustion sources, and a Monte Carlo simulation demonstrates that these differences are sufficient to differentiate among several carbon-emitters.

On-road measurement of automotive particle emissions by ultraviolet lidar and transmissometer: instrument.

A novel vehicle emissions remote sensing system (VERSS) for the on-road measurement of fuel-based particulate matter (PM) emission factors is described. This system utilizes two complementary PM channels using an ultraviolet Lidar and transmissometer for the measurement of PM mass column content behind a passing vehicle. Ratioing the PM mass column content with the carbon mass column content, simultaneously measured with infrared absorption, yields the fuel-based PM mass emission factor. The transmissometer directly yields PM extinction coefficients without calibration, while the Lidar measurement of PM backscatter coefficients is calibrated through laboratory measurements of gases with well-known backscatter coefficients. The PM mass column content is calculated from these extinction and backscatter coefficients with the help of mass backscatter and extinction efficiencies obtained from theoretical calculations. This novel VERSS has been used extensively in a major air quality study, and example data are presented.

Application of the tracer-aerosol gradient interpretive technique to sulfur attribution for the big bend regional aerosol and visibility observational study.

A simple data analysis method called the Tracer-Aerosol Gradient Interpretive Technique (TAGIT) is used to attribute particulate S and SO2 at Big Bend National Park in Texas and nearby areas to local and regional sources. Particulate S at Big Bend is of concern because of its effects on atmospheric visibility. The analysis used particulate S, SO2, and perfluorocarbon tracer data from six 6-hr sampling sites in and near Big Bend National Park. The data were collected in support of the Big Bend Regional Aerosol and Visibility Observational (BRAVO) Study; the field portion was conducted from July through October 1999. Perfluorocarbon tracer was released continuously from a tower at Eagle Pass, TX, approximately 25 km northeast of two large coal-fired power plants (Carbon I and II) in Coahuila, Mexico, and approximately 270 km east-southeast of Big Bend National Park. The perfluorocarbon tracer did not properly represent the location of the emissions from the Carbon power plants for individual 6-hr sampling periods and attributed only 3% of the particulate S and 27% of the SO2 at the 6-hr sites in and near Big Bend to sources represented by the tracer. An alternative approach using SO2 to tag "local" sources such as the Carbon plants attributed 10% of the particulate S and 75% of the SO2 at the 6-hr sites to local sources. Based on these two approaches, most of the regional (65-86%) and a small fraction (19-31%) of the local SO2 was converted to particulate S. The analysis implies that substantial reductions in particulate S at Big Bend National Park cannot be achieved by only reducing emissions from the Carbon power plants; reduction of emissions from many sources over a regional area would be necessary.

Attribution of Particulate Sulfur in the Grand Canyon to Specific Point Sources Using Tracer-Aerosol Gradient Interpretive Technique (TAGIT).

Since aerosol particulate sulfur is generally a secondary airborne pollutant, most source attribution techniques require many assumptions about the transport and chemistry of sulfur dioxide (SO2) emissions. Uncertainties in our understanding of these processes impair our ability to generate reliable attribution information that is necessary for designing cost-effective pollution control policies. A new attribution technique using artificial tracer is presented in hopes of reducing the uncertainty of secondary aerosol source attribution. The Tracer-Aerosol Gradient Interpretive Technique (TAGIT) uses tracer data from a monitoring network to distinguish sites impacted by a source tagged with tracer from nonimpacted sites. Sites determined not to be influenced by the plume are considered to represent background particulate sulfur concentrations. The particulate sulfur attributable to the source at sites within the plume is calculated as the difference between observed and background particulate sulfur. TAGIT is applied to measurements made in the vicinity of the east and west ends of the Grand Canyon in order to attribute particulate sulfur to the sources within the Eastern Colorado River Valley (ECRV) and the Mohave Power Project (MPP), respectively. TAGIT results indicate that during the winter intensive field sampling experiment (January 15-February 13, 1992), an average of 59 + 12% of the particulate sulfur at Marble Canyon, AZ, was attributable to ECRV sources. Similarly, during the summer field sampling experiment (July 13-August 30, 1992), MPP is estimated to have contributed an average of 7 + 3% of the particulate sulfur at Meadview, AZ. Uncertainties associated with the assumptions of TAGIT are discussed and quantified. The attribution results suggest that SO2-to-sulfate conversion rates are highly variable from day to day in this region.