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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.

The study was aimed at assessing in-use emissions of a USEPA 2010 emissions-compliant heavy-duty diesel vehicle powered by a model year (MY) 2011 engine using West Virginia University's Transportable Emissions Measurement System (TEMS). The TEMS houses full-scale CVS dilution tunnel and laboratory-grade emissions measurement systems, which are compliant with the Code of Federal Regulation (CFR), Title 40, Part 1065 [1] emissions measurement specifications. One of the specific objectives of the study, and the key topic of this paper, is the quantification of greenhouse gas (GHG) emissions (CO2, N2O and CH4) along with ammonia (NH3) and regulated emissions during real-world operation of a long-haul heavy-duty vehicle, equipped with a diesel particulate filter (DPF) and urea based selective catalytic reduction (SCR) aftertreatment system for PM and NOx reduction, respectively.

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.

This paper discusses the design and qualification of a High Temperature Sampling System (HTSS), capable of stripping the volatile fraction from a sample flow stream in order to provide for quantification of total, solid and volatile particulate matter (PM) on a near real-time basis. The sampling system, which incorporates a heated diesel oxidation catalyst, is designed for temperatures up to 450°C. The design accounts for molecular diffusion of volatile compounds, solid particles diffusion and reaction kinetics inside one channel of the oxidation catalyst. An overall solid particle loss study in the sampling was performed, and numerical results were compared with experimental data gathered at the West Virginia University Engine and Emissions Research Laboratory (EERL) and West Virginia University's Transportable Heavy-Duty Vehicle Emissions Testing Laboratory (THDVETL).

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.