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Microframework for Modeling of High-Emitting Vehicles

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Microframework for Modeling of High-Emitting Vehicles
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  VT-M ICRO F RAMEWORK FOR M ODELING OF H IGH E MITTING V EHICLES   Kyoungho Ahn Virginia Tech Transportation Institute 3500 Transportation Research Plaza Blacksburg, VA 24061 kahn@vt.edu (540) 231-1573 Fax: (540) 231-1555 Hesham Rakha Civil and Environmental Engineering Virginia Tech Blacksburg, VA 24061 hrakha@vt.edu (540) 231-1505 Fax: (540)231-1555 Antonio Trani Civil and Environmental Engineering Virginia Tech Blacksburg, VA 24061 vuela@vt.edu (540) 231-4418 Total word count: 5,193 + 2,750 = 7,943  Ahn, Rakha, and Trani 2 A BSTRACT   High emitters represent a small fraction of the vehicle fleet, yet they are responsible for a large portion of the total mobile source emissions. This paper first develops drive-cycle-specific high-emitter cut-points for the identification of high-emitter vehicles. Subsequently, the paper develops a microscopic model for estimating high-emitter vehicle emissions using second-by-second emission data. The proposed model estimates vehicle emissions with a margin of error of 10 percent when compared to in-laboratory bag emission measurements. The model was incorporated within the INTEGRATION traffic assignment and simulation software for the environmental assessment of alternative traffic operational projects, including emerging Intelligent Transportation System initiatives.  Ahn, Rakha, and Trani 3 I NTRODUCTION   High-emitter or high-emitting vehicles (HEVs) are motor vehicles that produce higher emissions than the average-emitting vehicles under normal driving conditions. Studies have shown that a small fraction of HEVs contribute significantly to the total mobile source emissions (Wenzel and Ross 1998; Wolf et al. 1998). According to the literature, high emitters that account for 20 percent of the fleet are responsible for 50  percent of the total emissions. Other studies indicate that 5 percent of the vehicles emit 80 percent of the emissions (Wolf et al. 1998). These estimations differ as a result of differences in high-emitter vehicle classifications. Consequently, identifying HEVs and estimating their emissions accurately is critical for the  precise modeling of mobile source emissions. This paper develops a high-emitter identification procedure and a simple mathematical model to estimate the emissions from HEVs. The objectives of this paper are two-fold. First, the paper develops drive-cycle-specific criteria for identifying high-emitting vehicles. Specifically, multiplicative factors are derived for the newly developed US Environmental Protection Agency (EPA) drive cycles. Second, the paper develops microscopic HEV emission models that can be incorporated within traffic simulation software. The significance of the research is that it develops microscopic HEV emission models that are sensitive to the instantaneous vehicle speed and acceleration levels. Consequently, this model can be implemented within a microscopic traffic simulation environment to quantify the environmental impacts of Intelligent Transportation System (ITS) technologies, such as traffic signal coordination, incident management, and electronic payment systems. In addition, the cycle-specific HEV cut-points make it possible to classify HEV vehicles using different drive cycles as opposed to using a single drive cycle. For example, the low speed  New York (FNYC) cycle may be tested in very contaminated urban areas, while the Arterial Level of Service (LOS) A (ARTA) cycle can be utilized for suburban or rural areas. S TATE - OF -P RACTICE M ODELING OF H IGH E MITTERS   This section describes the current state-of-practice procedures for classifying HEVs and the current state-of-art models for modeling HEVs in the US. These models include the MOBILE6 and Comprehensive Modal Emission Model (CMEM). MOBILE6 is the most widely used macroscopic mobile source emission model while the CMEM model is one of the most recently developed power-based microscopic emission models. High Emitter Vehicle Classifications The Environmental Protection Agency (EPA) recommends the use of the Inspection and Maintenance (I/M)  program for the identification of HEVs. Specifically, within the I/M program, the vehicle is tested on a dynamometer over the IM240 drive cycle, which is designed to simulate a typical city trip. In screening HEVs, second-by-second instantaneous emission measurements are measured and summed up for the entire drive cycle. A distance emission rate is then computed by dividing by the length of the drive cycle. Trip emission rates that are two to three times higher than manufacturer certification standards for new vehicles are classified as HEVs. However, given that manufacturer emission rates are quoted for the Federal Test Procedure (FTP) city and highway cycles, which typically involve cold-start effects, the use of the IM240 cycle may not be consistent with manufacturer thresholds. The literature reveals little consensus on the required drive cycle for identification of HEVs. Specifically, a number of drive cycles have been utilized to classify HEVs, including the FTP test, the LA4 cycle (also known as UDDS and city cycle), the IM240 test, and the FTP Bag2 (Wolf et al., 1998). The FTP cycle consists of three parts: a cold-start segment, a hot-stabilized segment, and a hot-start segment. The first  part, which includes cold-start effects (known as Bag1), lasts for 505 seconds over a length of 5.74 km (3.59 miles). Before the test, the vehicle is stored for a minimum of 12 hours to simulate a 12-hour overnight soak  period. The second segment of the FTP cycle, which is termed Bag2, lasts 867 seconds over a length of 6.26 km (3.91 miles) under hot-stabilized engine conditions. Bag2 emissions are collected immediately after Bag1  Ahn, Rakha, and Trani 4 following a 10-minute soak period. Specifically, after a 10-minute soak time, the 505 seconds of the start segment (Bag1) is re-run and the total emissions measured is termed Bag3. Georgia Tech researchers utilize the FTP Bag2 emission rate to classify vehicles as high emitters (Wolf et al., 1998) because it does not include any cold-start effects and has minimum enrichment mode of operation. Alternatively, the EPA utilizes the LA4 emission rates instead of the FTP Bag2 to classify vehicles as HEVs (Brzezinski et al. 1999), while some EPA researchers use the FTP cycle for high-emitter classification (Brzezinski et al. 1999; Glover and Koupal 1999; Koupal and Glover 1999). The LA4 cycle includes Bag1 and Bag2 of the FTP test  but does not include any engine starts. Typically, the emission cut-points are considered to be two times the new-vehicle emission standard for HC and NO x  emissions and three times the standard for CO emissions. Specifically, the cut-points that are recommended in the literature are 0.5 g/km, 6.4 g/km, and 1.3 g/km, for HC, CO, and NO x  emissions, respectively. The selection of the appropriate drive cycle and cut-point is very important because the emission rates vary substantially across different drive cycles, especially if some drive cycles involve cold starts. MOBILE6 Model MOBILE5a and MOBILE6 models were developed by the EPA Office of Transportation and Air Quality (OTAQ). MOBILE6 is the latest of the MOBILE models and is substantially different from its predecessor MOBILE5a, and thus is described in further detail. Specifically, MOBILE6 was developed using recent vehicle-emission testing data collected by the EPA, California Air Resources Board (CARB), automobile manufacturers, as well as inspection and maintenance tests conducted in various states. A major characteristic of the MOBILE6 model is the addition of so-called off-cycle emissions, which involve aggressive driving with various facility-type modeling. MOBILE6 estimates emission factors based on different roadway types (e.g., highways, arterials, locals). Emission factors can be adjusted for different facility types and different average speeds based on vehicle testing over a series of facility cycles. Also, MOBILE6 estimates emission factors for the start portion and the running portion of the trip separately (National Research Council. (U.S.) 2000). Comprehensive Modal Emission Model The Comprehensive Modal Emissions Model (CMEM) is one of the most recently developed power demand-based emission models. CMEM was developed by researchers at the University of California, Riverside. The CMEM model estimates LDV and LDT emissions as a function of the vehicle's operating mode (Barth et al. 2000). The CMEM model includes four categories of high emitters, which were determined based on their emission characteristics. These high emitters include vehicles that operate lean or rich, have a misfire, and have catalyst related problems. The lean high emitter is a vehicle that operates with a chronically lean fuel-to-air ratio at moderate power. This type of vehicle typically shows low HC and CO emissions and high NO x  emissions. While the exact physical problem is unknown, an improper signal from the oxygen sensor or an improper functioning of the electronic engine control could be causes for such  behavior. The rich type of high emitter is a vehicle with a rich fuel-to-air ratio at moderate power demands. Under these conditions, the engine-out HC emissions remain normal; however, the CO emission index and catalyst pass fraction are high, resulting in high tailpipe CO emissions. One possible reason for this enrichment failure is a leaking exhaust line. The leaking exhaust line imports oxygen before the oxygen sensor causing the sensor calling for more fuel from the injectors. The misfire high emitters have high engine-out HC emissions, high engine-out CO and high CO catalyst pass fraction. These vehicles have incomplete combustion problems (misfire) and a poor catalyst performance, resulting in moderate to slightly high tailpipe CO, very high HC, and moderate to low NO x  emissions. The fourth type of high emitters emits high tailpipe emissions of HC, CO, and NO x . These vehicles have chronically (burned-out or a missing catalyst) or transiently (high catalyst pass fraction) poor catalyst performance (Barth et al. 2000).  Ahn, Rakha, and Trani 5 E MISSION D ATA D ESCRIPTION   This section describes the data that were utilized for the development of the high-emitter models that are  presented in the paper. The study utilized the emission data that were utilized for the development of the MOBILE6 model. The section describes the data collection procedures and the drive cycles that were utilized for vehicle testing. Data Collection Procedures Field data were collected on a chassis dynamometer in the spring of 1997 by the EPA at the Automotive Testing Laboratories, Inc. (ATL) in Ohio and at the EPA's National Vehicle and Fuels Emission Laboratory (NVREL) in Michigan. All the vehicles at ATL were drafted at Inspection and Maintenance lanes used by the State of Ohio and were tested under as-received condition (without repairs). A total of 62 vehicles in East Liberty, Ohio,and 39 vehicles in Ann Arbor, Michigan were recruited and tested. The sample of 101 vehicles included 3 heavy-duty trucks that were not utilized in this study because the data were insufficient, 34 light-duty trucks, and 64 light-duty cars. The vehicle model years ranged from 1986 through 1996. Of the 98 light-duty vehicle data, 87 vehicle samples were selected for this study because the remaining 11 vehicles did not include FTP emission data, which is essential when comparing various driving cycles. The sample of 87 vehicles included 24 light-duty trucks. Most of the 87 vehicles were fuel injection engines, with 3 carbureted passenger cars and 4 carbureted light-duty trucks. Also, among the 87 vehicles, 24 vehicles had manual transmissions, and the remaining 63 vehicles had automatic transmissions (Brzezinski et al. 1999). All vehicles were tested at FTP under ambient conditions using the standard vehicle certification test fuel. Vehicle emission tests were performed in random order to offset any possible order bias that could result in different ambient conditions for the tested cycles. The vehicle emissions of HC, CO, NO x , and CO 2  were measured instantaneously each second and were aggregated as composite "bags" (Brzezinski et al. 1999). Drive Cycle Characterization One of the requests of the Clean Air Act Amendments (CAAA) of 1990 was the addition of "real-world” driving cycles within emission modeling. Consequently, the EPA proposed the adjustment of emissions for different facility types and levels of congestion. Specifically, eleven facility-specific drive cycles were developed by Sierra Research that cover freeway, non-freeway, and area-wide driving cycles. These cycles were developed using chase-car and instrumented-vehicle data gathered in Baltimore, MD; Spokane, WA; and Los Angeles, CA. According to the EPA, these new cycles better represent actual fleet driving and include more aggressive "real-world driving" (Carlson and Austin 1997). In order to represent real-world driving conditions, the driving behavior in each driving cycle was developed using the observed speed-acceleration and specific power frequency distribution of the chase-car data. A range of roadway types and several congestion levels were tested. The congestion levels were grouped into a “level of service” (LOS), similar to the transportation congestion index, from “A” through “G.” Table 1 provides a brief description of the new cycles and additional emission test cycles used for emission testing. Each of the 87 vehicles was tested over 14 to 16 driving cycles. H IGH E MITTER C RITERIA FOR D RIVE C YCLES   This section derives drive-cycle-specific emission rates for the classification of high emitters. The objective of these derived high-emitter thresholds is to develop a consistent and systematic procedure for the identification of high emitters that is not drive-cycle specific.
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