There have been significant improvements in recent years in transportation and emissions modeling to allow better evaluations of transportation operational effects and associated vehicle emissions. In particular, instantaneous or modal emissions models have been developed for a variety of light-duty vehicles. To date, most of the effort has focused primarily on developing these models for light-duty vehicles with less effort devoted to heavy-duty diesel (HDD) vehicles. Although HDD vehicles currently make up only a fraction of the total vehicle population, they are major contributors to the emissions inventory. A description is provided of an HDD truck model that is part of a larger comprehensive modal emissions modeling (CMEM) program developed at the University of California (UC), Riverside. Several HDD truck submodels have been developed in the CMEM framework, each corresponding to a distinctive vehicletechnology category. The developed models use a parameterized physical approach in which the entire emission process is broken down into different components that correspond to physical phenomena associated with vehicle operation and emission production. A variety of trucks were extensively tested under a wide range of operating conditions at UC Riverside's Mobile Emissions Research Laboratory. The collected data were then used to calibrate the HDD models. Particular care was taken to investigate and implement the effects of varying grade and the use of variable fuel injection strategies. Results show good estimates for fuel use and the regulated emission species including nitrogen oxides, one of the key targets for HDD vehicles.

On-road heavy-duty diesel vehicles are a major contributor of oxides of nitrogen (NO) emissions. In the US, many heavy-duty diesel vehicles employ selective catalytic reduction (SCR) technology to meet the 2010 emission standard for NO. Typically, SCR needs to be at least 200°C before a significant level of NO reduction is achieved. However, this SCR temperature requirement may not be met under some real-world operating conditions, such as during cold starts, long idling, or low speed/low engine load driving activities. The frequency of vehicle operation with low SCR temperature varies partly by the vehicle's vocational use. In this study, detailed vehicle and engine activity data were collected from 90 heavy-duty vehicles involved in a range of vocations, including line haul, drayage, construction, agricultural, food distribution, beverage distribution, refuse, public work, and utility repair. The data were used to create real-world SCR temperature and engine load profiles and identify the fraction of vehicle operating time that SCR may not be as effective for NO control. It is found that the vehicles participated in this study operate with SCR temperature lower than 200°C for 11-70% of the time depending on their vocation type. This implies that real-world NO control efficiency could deviate from the control efficiency observed during engine certification.

Real-world nitrogen oxides (NO x ) emissions were estimated using on-board sensor readings from 72 heavy-duty diesel vehicles (HDDVs) equipped with a Selective Catalytic Reduction (SCR) system in California. The results showed that there were large differences between in-use and certification NO x emissions, with 12 HDDVs emitting more than three times the standard during hot-running and idling operations in the real world. The overall NO x conversion efficiencies of the SCR system on many vehicles were well below the 90% threshold that is expected for an efficient SCR system, even when the SCR system was above the optimum operating temperature threshold of 250°C. This could potentially be associated with SCR catalyst deterioration on some engines. The Not-to-Exceed (NTE) requirements currently used by the heavy-duty in-use compliance program were evaluated using on-board NO x sensor data. Valid NTE events covered only 4.2−16.4% of the engine operation and 6.6−34.6% of the estimated NO x emissions. This work shows that low cost on-board NO x sensors are a convenient tool to monitor in-use NO x emissions in real-time, evaluate the SCR system performance, and identify vehicle operating modes with high NO x emissions. This information can inform certification and compliance programs to ensure low in-use NO x emissions.

NH3 emissions from motor vehicles have been the subject of a number of recent studies due to their potential impact on ambient particulate matter (PM). Highly time-resolved NH3 emissions can be measured and correlated with specific driving events utilizing a tunable diode laser (TDL). It is possible to incorporate NH3 emissions with this new information into models that can be used to predict emissions inventories from vehicles. The newer generation of modal models are based on modal events, with the data collected at second-by-second time resolution, unlike the bag-based emission inventory models such as EMFAC and MOBILE. The development of an NH3 modal model is described in this paper. This represents one of the first attempts to incorporate vehicle NH3 emissions into a comprehensive emissions model. This model was used in conjunction with on-road driving profiles to estimate the emissions of SULEV, ULEV, and LEV vehicles to be 9.4 +/- 4.1, 21.8 +/- 5.2, and 34.9 +/- 6.0 mg/mi, respectively. We also implement this new NH3 model to predict and evaluate the NH3 emission inventory in the South Coast air basin (SoCAB).

Research Program. This paper describes the initial phase of a longterm project with national implications for the improvement of transportation and air quality. The overall objective of the research is to develop and verify a comprehensive modal emissions model that accurately reflects the impacts of a vehicle's operating mode. The model is comprehensive in the sense that it will be able to predict emissions for a wide variety of light-duty vehicles (LDVs, i.e., cars and trucks) in various states of condition (e.g., properly functioning, deteriorated, malfunctioning). Other efforts and further background on modal emission modeling have been described elsewhere (1) and elsewhere in this Record by An et al.A specific modal emissions testing protocol has been developed that reflects both real-world driving and specific modal events associated with different levels of emissions. This testing protocol (described later in this paper) is being applied to more than 300 vehicles to provide the foundation for the modal emissions model. As a preliminary step, the test cycle has been applied to an initial fleet of 30 vehicles, where at least 1 vehicle falls into each of the 28 defined vehicle/technology categories. The preliminary analysis of the initial test fleet is described. VEHICLE/TECHNOLOGY CATEGORIZATIONThe conventional emission inventory models are based on bag emissions data (FTP) collected from certification tests of new cars, surveillance programs, and inspection/maintenance programs. These large sets of emissions data provide the basis for the conventional emission inventory models and are indexed primarily by model year. For LDVs, groupings are based on a few different vehicle classes and technology groups.In developing a modal emission model, we cannot base the model on these bag data and must collect second-by-second emissions data from a sample of vehicles to build a model that predicts emissions for the national fleet. The choice of vehicles for this sample is therefore crucial, since only a small sample (300+ vehicles) will be the basis for the model.The determination of the vehicle/technology categories in the modal model is a critical task, not only for vehicle recruitment and testing but also for the development of the model. Because the eventual output of the model is emissions, the vehicle/technology categories and the sampling proportions of the major vehicle/technology groups (normal versus high emitter, and carbureted versus fuel injected versus Tier 1) have been chosen based on each major category's contribution to total emissions, as opposed to a group's actual population in the national fleet. Recent results from both remote sensing and surveillance studies have indicated that a small population of vehicles contribute a substantial fraction of the total emissions The initial phase of a long-term project with national implications for the improvement of transportation and air quality is described. The overall objective of the research is to develop and verify a computer model that accurately esti...