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In characterizing the emissions from mobile sources, it is essential that the vehicle be exercised in a way that reasonably represents typical in-use behavior. A heavy-heavy duty diesel truck (HHDDT) test schedule was developed from speed-time data gathered during two Air Resources Board-sponsored truck activity programs. The data were divided into four modes, termed Idle, Creep, Transient and Cruise Modes, in order of increasing speed. For the last three modes, speed-time schedules were created that represented all the data in that mode. Statistical parameters such as average speed, stops per unit distance, kinetic energy, maximum speed and acceleration and deceleration values were considered in arriving at these schedules. The schedules were evaluated using two Class 8 over-the-road tractors on a chassis dynamometer. Emissions were measured using a full-scale dilution tunnel, filtration for particulate matter (PM), and research grade analyzers for the gases.

Today's computer-based vehicle operation simulators use engine speed, engine torque, and lookup tables to predict emissions during a driving simulation [1]. This approach is used primarily for light and medium-duty vehicles, with large discrepancies inherently due to the lack of transient engine emissions data and inaccurate emissions prediction methods [2]. West Virginia University (WVU) has developed an artificial neural network (ANN) based emissions model for incorporation into the ADvanced VehIcle SimulatOR (ADVISOR) software package developed by the National Renewable Energy Laboratory (NREL). Transient engine dynamometer tests were conducted to obtain training data for the ANN. The ANN was trained to predict carbon dioxide (CO2) and oxides of nitrogen (NOx) emissions based on engine speed, torque, and their representative first and second derivatives over various time ranges.

The 1998 Consent Decrees between the settling heavy-duty diesel engine manufacturers and the United States Government require the engine manufacturer to perform in-use emissions testing to evaluate their engine designs and emissions when the vehicle is placed into service. This additional requirement will oblige the manufacturer to account for real-world conditions when designing engines and engine control algorithms and include driving conditions, ambient conditions, and fuel properties in addition to the engine certification test procedures. Engine operation and ambient conditions can be designed into the engine control algorithm. However, there will most likely be no on-board determination of fuel properties or composition in the near future. Therefore, the engine manufacturer will need to account for varying fuel properties when developing the engine control algorithm for when in-use testing is performed.

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.

Hybrid diesel electric buses offer the advantage of superior fuel economy through use of regenerative braking and lowered transient emissions by reducing the need of the engine to follow load as closely as in a conventional bus. With the support of the Department of Energy (DOE), five Lockheed Martin-Orion hybrid diesel-electric buses were operated on the West Virginia University Transportable Laboratory in Brooklyn, New York. The buses were exercised through a new cycle, termed the Manhattan cycle, that was representative of today's bus use as well as the accepted Central Business District Cycle and New York Bus Cycle. Emissions data were corrected for the state of charge of the batteries. The emissions can be expressed in units of grams/mile, grams/axle hp-hr and grams/gallon fuel. The role of improved fuel economy in reducing oxides of nitrogen relative to conventional automatic buses is evident in the data.