Dongzi Zhu

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 Californias 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

Abstract 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.

In-Plume Emission Test Stand 2: Emission Factors for 10- to 100-kW U.S. Military Generators

Abstract 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.

Effect of Soil Type and Momentum on Unpaved Road Particulate Matter Emissions from Wheeled and Tracked Vehicles

Excluding windblown dust, unpaved road dust PM 10 emissions in the US EPAs 2002 National Emission Inventory account for more than half of all PM 10 emissions in the arid states of the western U.S. (i.e., CA, AZ, NV, NM, and TX). Despite the large size of the source, substantial uncertainty is associated with both the vehicle activity (i.e., number of kilometers traveled at a particular speed) and the emission factors (i.e., grams of PM 10 per kilometer traveled). In this study, emission factors were measured using the flux tower method for both tracked and wheeled military vehicles at three military bases in the Western U.S. Test vehicle weights ranged from 2400 kg to 60,000 kg. Results from both previously published and unpublished field studies are combined to link emission factors to three related variables: soil type, vehicle momentum, and tred type (i.e., tire or track). Current emission factor models in US EPAs AP-42 Emission Factor Compendium do not factor both speed and weight into unpaved road emission factor calculations. Tracked vehicle emission factors from Ft. Carson, CO, and Ft. Bliss, TX were related to vehicle momentum (speed * mass) with ratios ranging from 0.004–0.006 (g-PM vkt− 1)/(kg m s− 1). For similar vehicle momentum, wheeled vehicles emitted approximately 2 to 4 times more PM 10 than tracked vehicles. At Yakima, WA, tracked vehicle PM 10 emission factors were substantially higher (0.38 (g-PM vkt− 1)/(kg m s− 1)) due to the unique volcanic ash soil characteristics (48% silt). Results from PI-SWERL, a portable wind tunnel surrogate, are presented to assess its utility to predict unpaved road dust emissions without the deployment of flux tower systems. PI-SWERL showed only a factor of 6 variation between sites in comparison with the 60-fold variation as measured by the flux towers.

The In-Plume Emission Test Stand: An Instrument Platform for the Real-Time Characterization of Fuel-Based Combustion Emissions

Abstract 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 (~25 °C for IPETS vs. ~50 °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.

Detection of Gasoline Vehicles with Gross PM Emissions

Light duty gasoline vehicles (LDGV) are estimated to contribute 40% of the total on-road mobile source tailpipe emissions of particulate matter (PM) in California. While considerable efforts have been made to reduce toxic diesel PM emissions going into the future, less emphasis has been placed on PM from LDGVs. The goals of this work were to characterize a small fleet of visibly smoking and high PM emitting LDGVs, to explore the potential PM-reduction benefits of Smog Check and of repairs, and to examine remote sensing devices (RSD) as a potential method for identifying high PM emitters in the in-use fleet. For this study, we recruited a fleet of eight vehicles covering a spectrum of PM emission levels. PM and criteria pollutant emissions were quantified on a dynamometer and CVS dilution tunnel system over the Unified Cycle using standard methods and real time PM instruments. The vehicles were then tested using RSD equipment over a test track, tested with a standard Smog Check, and tested with a screening device during the Smog Check. The PM emission rates of the visibly smoking vehicles range from 60 to 1718 mg/mi over the UC cycle. The light or invisible smokers had PM emissions ranging from 7 to 25 mg/mi. The smoking vehicles showed particle number rates on the order of 10