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The need for a cleaner and less expensive alternative energy source to conventional petroleum fuels for powering the transportation sector has gained increasing attention during the past decade. Special attention has been directed towards natural gas (NG) which has proven to be a viable option due to its clean-burning properties, reduced cost and abundant availability, and therefore, lead to a steady increase in the worldwide vehicle population operated with NG. The heavy-duty vehicle sector has seen the introduction of natural gas first in larger, locally operated fleets, such as transit buses or refuse-haulers. However, with increasing expansion of the NG distribution network more drayage and long-haul fleets are beginning to adopt natural gas as a fuel.

Stringent emission regulations have forced drastic technological improvements in diesel after treatment systems, particularly in reducing Particulate Matter (PM) emissions. Those improvements generally regard the use of Diesel Oxidation Catalyst (DOC), Diesel Particulate Filter (DPF) and lately also the use of Selective Catalyst Reduction (SCR) systems along with improved engine control strategies for reduction of NOx emissions from these engines. Studies that have led to these technological advancements were made in controlled laboratory environment and are not representative of real world emissions from these engines or vehicles. In addition, formation and evolution of PM from these engines are extremely sensitive to overall changes in the dilution process.

Diesel Particulate Filters (DPFs) are well assessed exhaust aftertreatment devices currently equipping almost every modern diesel engine to comply with the most stringent emission standards. However, an accurate estimation of soot content (loading) is critical to managing the regeneration of DPFs in order to attain optimal behavior of the whole engine-after-treatment assembly, and minimize fuel consumption. Real-time models can be used to address challenges posed by advanced control systems, such as the integration of the DPF with the engine or other critical aftertreatment components or to develop model-based OBD sensors. One of the major hurdles in such applications is the accurate estimation of engine Particulate Matter (PM) emissions as a function of time. Such data would be required as input data for any kind of accurate models. The most accurate way consists of employing soot sensors to gather the real transient soot emissions signal, which will serve as an input to the model.

In order to comply with stringent 2010 US-Environmental Protection Agency (EPA) on-road, Heavy-Duty Diesel (HDD) emissions regulations, the Selective Catalytic Reduction (SCR) aftertreatment system has been judged by a multitude of engine manufacturers as the primary technology for mitigating emissions of oxides of nitrogen (NOx). As virtually stand-alone aftertreatment systems, SCR technology further represents a very flexible and efficient solution for retrofitting legacy diesel engines as the most straightforward means of cost-effective compliance attainment. However, the addition of a reducing agent injection system as well as the inherent operation limitations of the SCR system due to required catalyst bed temperatures introduce new, unique problems, most notably that of ammonia (NH₃) slip.

Diesel particulate filters (DPFs) are recognized as the most efficient technology for particulate matter (PM) reduction, with filtration efficiencies in excess of 90%. Design guidelines for DPFs typically are: high removal efficiency, low pressure drop, high durability and capacity to resist high temperature excursions during regeneration events. The collected mass inside the trap needs to be periodically oxidized to regenerate the DPF. Thus, an in-depth understanding of filtration and regeneration mechanisms, together with the ability of predicting actual DPF conditions, could play a key role in optimizing the duration and number of regeneration events in case of active DPFs. Thus, the correct estimation of soot loading during operation is imperative for effectively controlling the whole engine-DPF assembly and simultaneously avoidingany system failure due to a malfunctioning DPF. A viable way to solve this problem is to use DPF models.

Fuel economy and regulated emissions were measured from eight forty-foot transit buses operated on petroleum diesel and a “B20” blend of 80% diesel fuel and 20% biodiesel by volume. Use of biodiesel is attractive to displace petroleum fuel and reduce an operation's carbon footprint. Usually it is assumed that biodiesel will also reduce particulate matter (PM) emissions relative to those of petroleum diesel. Model years of the vehicles evaluated were newer 2007-08 Gillig low-floor buses, 2005 Gillig Phantom buses, and a 2002 Gillig Phantom bus. Engine technology represented three different emissions standards, and included buses with OEM diesel particulate filters. Each bus was evaluated using two transient speed-time schedules, the Orange County Transit Authority (OCTA) driving schedule which represents moderate speed urban/suburban operation and the Urban Dynamometer Driving Schedule (UDDS) which represents a mix of suburban and higher speed on-highway operation.

Biodiesel may be derived from either plant or animal sources, and is usually employed as a compression ignition fuel in a blend with petroleum diesel (PD). Emissions differences between vehicles operated on biodiesel blends and on diesel have been published previously, but data do not cover the latest engine technologies. Prior studies have shown that biodiesel offers advantages in reducing particulate matter, with either no advantage or a slight disadvantage for oxides of nitrogen emissions. This paper describes a recent study on the emissions impact of two biodiesel blends B20A, made from 20% animal fat (tallow) biodiesel and 80% PD, and B20B, obtained from 20% soybean biodiesel and 80% PD. These blends used the same PD fuel for blending and were contrasted with the same PD fuel as a reference. The research was conducted on a 2007 medium heavy-duty diesel truck (MHDDT), with an engine equipped with Exhaust Gas Recirculation (EGR) and a Diesel Particulate Filter (DPF).

The temporary deactivation of the selective catalytic reduction (SCR) device due to malfunction requires the engine control to engage multiple engine-out calibrations. Further, it is expected that emitted particles will be different in composition, size and morphology when an engine, which meets the 2010 particulate matter (PM) gravimetric limits, is programmed with multiple maps. This study investigated the correlation between SCR-out/engine-out PM emissions from an 11-liter Volvo engine. Measurement of PM concentrations and size distributions were conducted under steady state and transient cycles. Ion Chromatograph analysis on gravimetric filters at the SCR-out has revealed the presence of sulfates. Two different PM size-distributions were generated over a single engine test mode in the accumulation mode region with the aid of a design of experiment (DOE) tool. The SCR-out PM size distributions were found to correlate with the two engine-out distributions.

Transit agencies across the United States operate bus fleets primarily powered by diesel, natural gas, and hybrid drive systems. Passenger loading affects the power demanded from the engine, which in turn affects distance-specific emissions and fuel consumption. Analysis shows that the nature of bus activity, taking into account the idle time, tire rolling resistance, wind drag, and acceleration energy, influences the way in which passenger load impacts emissions. Emissions performance and fuel consumption from diesel and natural gas powered buses were characterized by the West Virginia University (WVU) Transportable Emissions Testing Laboratory. A comparison matrix for all three bus technologies included three common driving cycles (the Braunschweig Cycle, the OCTA Cycle, and the ADEME-RATP Paris Cycle). Each bus was tested at three different passenger loading conditions (empty weight, half weight, and full weight).

Heavy-Duty Diesel (HDD) engines' particulate matter (PM) emissions are most often measured quantitatively by weighing filters that collect diluted exhaust samples pre- and post-test. PM sampling systems that dilute exhaust gas and collect PM samples have different effects on measured PM data. Those effects usually contribute to inter-laboratory variance. The U.S. Environmental Protection Agency (EPA)'s 2007 PM emission measurement regulations for the test of HDD engines should reduce variability, but must also cope with PM mass that is an order of magnitude lower than legacy engine testing. To support the design of a 2007 US standard HDD PM emission sampling system, a parametric study based on a systematic Simulink® model was performed. This model acted as an auxiliary design tool when setting up a new 2007 HDD PM emission sampling system in a heavy-duty test cell at West Virginia University (WVU). It was also designed to provide assistance in post-test data processing.

Heavy duty diesel vehicle (HDDV) emissions are known to affect air quality, but few studies have quantified the real-world contribution to the inventory. The objective of this study was to provide data that may enable ambient emissions investigators to m,odel the air quality more accurately. The 25 vehicles reported in this paper are from the first phase of a program to determine representative regulated emissions from Heavy Heavy-Duty Diesel Trucks (HHDDT) operating in Southern California. Emissions data were gathered using a chassis dynamometer, full flow dilution tunnel, and research grade analyzers. The subject program employed two truck test weights and four new test modes (one was idle operation), in addition to the Urban Dynamometer Driving Schedule (UDDS), and the AC50/80 cycle. The reason for such a broad test cycle scope was to determine thoroughly how HHDDT emissions are influenced by operating cycle to improve accuracy of models.

The Federal Test Procedure (FTP) for heavy-duty engines requires the use of a full-flow tunnel based constant volume sampler (CVS). These are costly to build and maintain, and require a large workspace. A small portable micro-dilution system that could be used on-board, for measuring emissions of in-use, heavy-duty vehicles would be an inexpensive alternative. This paper presents the rationale behind the design of such a portable particulate matter measuring system. The presented micro-dilution tunnel operates on the same principle as a full-flow tunnel, however given the reduced size dilution ratios can be more easily controlled with the micro dilution system. The design targets dilution ratios of at least four to one, in accordance with the ISO 8178 requirements. The unique features of the micro-dilution system are the use of only a single pump and a porous sintered stainless steel tube for mixing dilution air and raw exhaust sample.

The Federal Test Procedure (FTP) for heavy-duty engines requires the use of a full-flow tunnel based constant volume sampler (CVS) which is costly to build and maintain, and requires a large workspace. A portable micro-dilution system that could be used for measuring on-board, in use emissions from heavy duty vehicles would be an inexpensive alternative compared to a full-flow CVS tunnel, as well as requiring significantly less workspace. This paper evaluates such a portable particulate matter measuring system. This micro-dilution tunnel operates on the same principle as a full-flow tunnel, however dilution ratios can be more easily controlled with the micro dilution system. The dilution ratios for the micro-dilution system were maintained at least four to one, as per ISO 8178 requirements, by measuring the mass flow rates of the dilution air and dilute exhaust.

The Tapered Element Oscillating Microbalance (TEOM) measures captured particle mass continuously on a small filter held on an oscillating element. In addition to traditional filter-based particulate matter (PM) measurement, a TEOM was used to characterize PM from the dilute exhaust of trucks examined in two phases (Phase 1.5 and Phase 2) of the Coordinating Research Council (CRC) Heavy-Duty Vehicle Emissions Inventory Project E-55/E-59. Test schedules employed were the Heavy Heavy-Duty Diesel Truck (HHDDT) test schedule that consists of four modes (Idle, Creep, Transient and Cruise), the HHDDT Short (HHDDT_S) which represents high-speed freeway operation, and the Heavy-Duty Urban Dynamometer Driving Schedule (UDDS). TEOM results were on average 6% lower than those from traditional particulate filter weighing. Data (in units of g/cycle) were examined by plotting cycle-averaged TEOM mass against filter mass. Regression (R2) values for these plots were from 0.88 to 0.99.

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.

The California Air Resources Board (ARB) developed a Medium Heavy-Duty Truck (MHDT) schedule by selecting and joining microtrips from real-world MHDT. The MHDT consisted of three modes; namely, a Lower Speed Transient, a Higher Speed Transient, and a Cruise mode. The maximum speeds of these modes were 28.9, 58.2 and 66.0 mph, respectively. Each mode represented statistically selected truck behavior patterns in California. The MHDT is intended to be applied to emissions characterization of trucks (14,001 to 33,000lb gross vehicle weight) exercised on a chassis dynamometer. This paper presents the creation of the MHDT and an examination of repeatability of emissions data from MHDT driven through this schedule. Two trucks were procured to acquire data using the MHDT schedule. The first, a GMC truck with an 8.2-liter Isuzu engine and a standard transmission, was tested at laden weight (90% GVW, 17,550lb) and at unladen weight (50% GVW, 9,750lb).

Diesel particulate matter emissions, because they do not disperse as readily gaseous emissions, have a very localized effect and eventually settle to the ground not far from where they were emitted. One subset of heavy-duty diesel vehicles that warrant further attention for controlling particulate emissions matter is sanitation trucks. Cummins Inc. and West Virginia University investigated particulate emissions reduction technologies for New York City Department of Sanitation refuse trucks under the EPA Consent Decree program. Regulated emissions were measured on four retrofitted sanitation trucks with and without the DPF installed. Cummins engines powered all of the retrofitted trucks. The Engelhard DPX reduced PM emissions by 97% and 84% on the New York Garbage Truck Cycle (NYGTC) and Orange County Refuse Truck Cycle (OCRTC) respectively. The Johnson-Matthey CRT system reduced PM emissions by 81% and 87% over the NYGTC and OCRTC respectively.

In an effort to develop engine/vehicle test methods that will reflect real-world emission characteristics, West Virginia University (WVU) designed and conducted a study on a Class-8 tractor with an electronically controlled diesel engine that was mounted on a chassis dynamometer in the Old Dominion University Langley full-scale wind tunnel. With wind speeds set at 88 km/hr in the tunnel, and the tractor operating at 88 km/hr on the chassis dynamometer, a Scanning Mobility Particle Sizer (SMPS) was employed for measuring PM size distributions and concentrations. The SMPS was housed in a container that was attached to a three-axis gantry in the wind tunnel. Background PM size-distributions were measured with another SMPS unit that was located upstream of the truck plume. Ambient temperatures were recorded at each of the sampling locations. The truck was also operated through transient tests with vehicle speeds varying from 65 to 88 km/hr, with a wind speed of 76 km/hr.

Concern over health effects associated with diesel exhaust and debate over the influence of high number counts of particles in diesel exhaust prompted research to develop a methodology for diesel particulate matter (PM) characterization. As part of this program, a tractor truck with an electronically managed diesel engine and a dynamometer were installed in the Old Dominion University (ODU) Langley full-scale wind tunnel. This arrangement permitted repeat measurements of diesel exhaust under realistic and reproducible conditions and permitted examination of the steady exhaust plume at multiple points. Background particle size distribution was characterized using a Scanning Mobility Particle Sizer (SMPS). In addition, a remote sampling system consisting of a SMPS, PM filter arrangement, and carbon dioxide (CO2) analyzer, was attached to a roving gantry allowing for exhaust plume sampling in a three dimensional grid. Raw exhaust CO2 levels and truck performance data were also measured.

A study was performed in the spring of 2001 to chemically characterize exhaust emissions from trucks and buses fueled by various test fuels and operated with and without diesel particle filters. This study was part of a multi-year technology validation program designed to evaluate the emissions impact of ultra-low sulfur diesel fuels and passive diesel particle filters (DPF) in several different heavy-duty vehicle fleets operating in Southern California. The overall study of exhaust chemical composition included organic compounds, inorganic ions, individual elements, and particulate matter in various size-cuts. Detailed descriptions of the overall technology validation program and chemical speciation methodology have been provided in previous SAE publications (2002-01-0432 and 2002-01-0433).