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The objective of this project, which is supported by the U.S. Department of Energy (DOE) through the National Renewable Energy Laboratory (NREL), is to provide a comprehensive comparison of heavy-duty trucks operating on alternative fuels and diesel fuel. Data collection from up to eight sites is planned. This paper summarizes the design of the project and early results from the first two sites. Data collection is planned for operations, maintenance, truck system descriptions, emissions, duty cycle, safety incidents, and capital costs and operating costs associated with the use of alternative fuels in trucking.

The historical lack of continuous data for PM emissions from heavy-duty diesel engines hampers advanced inventory approaches and hampers second-by-second engine control optimization. Continuos PM data can be obtained using a Tapered Element Oscillating Microbalance (TEOM), but moisture correction of data is needed to remove unwanted transient components of the mass. Reasonable correlation can be found between TEOM data integrated over the cycle and conventional PM filter data. Considerable scatter was evident when continuous TEOM data were plotted against instantaneous power, but by dispersing the power in time a clearer relationship was evident. Continuous TEOM data showed the same gross trends as PM filter mass distributed over a cycle in proportion to instantaneous CO, but it was evident that this CO proportioning technique is at best approximate. Binning of PM mass rate as a function of vehicle speed and acceleration were also evaluated for inventory purposes.

Selective Catalytic Reduction (SCR), using urea injection, is being examined as a method for substantial reduction of oxides of nitrogen (NOx) for diesel engines, but the urea injection rates must be controlled to match the NOx production which may need to be predicted during open loop control. Unfortunately NOx is usually measured in the laboratory using a full-scale dilution tunnel and chemiluminescent analyzer, which cause delay and diffusion (in time) of the true manifold NOx concentration. Similarly, delay and diffusion of measurements of all emissions cause the task of creating instantaneous emissions models for vehicle simulations more difficult. Data were obtained to relate injections of carbon dioxide (CO2) into a tunnel with analyzer measurements. The analyzer response was found to match a gamma distribution of the input pulse, so that the analyzer output could be modeled from the tunnel CO2 input.

Gaseous and particulate emissions from heavy-duty vehicles are affected by fuel types, vehicle/engine parameters, driving characteristics, and environmental conditions. Transient chassis tests were conducted on twenty-six heavy-duty vehicles fueled with methanol, compressed natural gas (CNG), #1 diesel, and #2 diesel, using West Virginia University (WVU) Transportable Heavy-Duty Vehicle Emissions Testing Laboratory. The vehicles were operated on the central business district (CBD) testing cycle, and regulated emissions of carbon monoxide (CO), total hydrocarbon (HC), nitrogen oxides (NOx), and particulate matter (PM) were measured. Comparisons of regulated emissions results revealed that the vehicles powered on methanol and CNG produced much lower particulate emissions than the conventionally fueled vehicles.

The West Virginia University (WVU) Transportable Heavy-Duty Vehicle Emissions Testing Laboratory was employed to conduct chassis dynamometer tests in the field to measure the exhaust emissions from heavy-duty buses and trucks. This laboratory began operation in the field in January, 1992. During the period January, 1992 through June, 1993, over 150 city buses, trucks, and tractors operated by 18 different authorities in 11 states were tested by the facility. The tested vehicles were powered by 14 different types of engines fueled with natural gas (CNG or LNG), methanol, ethanol, liquified petroleum gas (LPG), #2 diesel, and low sulfur diesel (#1 diesel or Jet A). Some of the tested vehicles were equipped with exhaust after-treatment systems. In this paper, a total of 12 CNG-fueled and #2 diesel-fueled transit buses equipped with Cummins L-10 engines, were chosen for investigation.

Results of a research effort directed towards identifying and measuring the genotoxic properties of respirable particulate matter involved in mining exposures, especially those which may synergistically affect genotoxic hazard, are presented. Particulate matter emissions from a direct injection diesel engine have been sampled and assayed to determine the genotoxic potential as a function of engine operating conditions. Diesel exhaust from a Caterpillar 3304 diesel engine, representative of the ones found in underground mines, rated 100 hp at 2200 rpm is diluted in a multi-tube mini-dilution tunnel and the particulate matter is collected on 70 mm fluorocarbon coated glass fiber filters as well as on 8″ x 10″ hi-volume filters. A six mode steady state duty cycle was used to relate engine operating conditions to the genotoxic potential.

Techniques have been developed to sample and speciate dilute heavy duty diesel exhaust to determine the specific reactivities and the ozone forming potential. While the Auto/Oil Air Quality Improvement Research Program (AQIRP) has conducted a comprehensive investigation to develop data on potential improvements in vehicle emissions and air quality from reformulated gasoline and various other alternative fuels. However, the development of sampling protocols and speciation of heavy duty diesel exhaust is still in its infancy [1, 2, 3, 4, 5 and 6]. This paper focuses on the first phase of the heavy duty diesel speciation program, that involves the development of a unique set of sampling protocols for the gas phase, semi-volatile and particulate matter from the exhaust of engines operating on different types of diesel fuel. Effects of sampling trains, sampling temperatures, semi-volatile adsorbents and driving cycles are being investigated.

When heavy-duty truck emissions rates are expressed in distance-specific units (such as g/mile), average speed and the degree of transient behavior of the vehicle activity can affect the emissions rate. Previous one-dimensional studies have shown some correlation of distance-specific emissions rates between cycles. This paper reviews emissions data sets from the 5-mode CARB Heavy Heavy-Duty Diesel Truck (HHDDT) Schedule, the Heavy Duty Urban Dynamometer Driving Schedule (UDDS) and an inspection and maintenance cycle, known as the AC5080. A heavy-duty chassis dynamometer was used for emissions characterization along with a full-scale dilution tunnel. The vehicle test weights were simulated at 56,000 lbs. Two-dimensional correlations were used to predict the emissions rate on one mode or cycle from the rates of two other modes or cycles.