Modeling Mobile-Source Emissions (2000) / Chapter Skim
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5 Alternative Mobile-Source Emissions Modeling Techniques
5 Alternative Mobile-Source Emissions Modeling Techniques
Pages 167-196
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From page 167... ...
This chapter briefly describes these alternative mobile- source emissions models, with a focus on defining key differences between MOBILE and the alternatives. Further, this chapter builds upon the transportation and emissions-model integration issues introduced in Chapter 2, defining how mobile-source emissions inventories can be generated at different levels of detail.
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· BURDEN calculates the emissions inventory (tons/ day) for a specified county, air basin, or the entire state.
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All these models rely upon regression analyses of data sets to get basic emissions rates and correction factors. There is some sharing of data between the two models, but generally the main data sets for exhaust emissions of light-duty vehicles (LDVs)
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However, the two models share the same overall approach and neither model provides any guidance for an innovative approach to the estimation of on-road mobile-source emissions. MOBILE-SOURCE EMISSIONS MODELING IN THE FEDERAL REPUBLIC OF GERMANY The Federal Republic of Germany has developed a set of mobile-source emissions models for a number of purposes (UBA/SAEFL 1999~.
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For example, many of the emissions factors used in TREMOD come directly from the Handbook. This set of emissions models is used for a number of purposes, including assisting in the development of standards of emissions protection; performing environmental assessment studies; road planning; and establishing permits for construction; .
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It is often used in conjunction with traffic-simulation models in which emissions are estimated for different roadway sections in a transportation network. The Handbook also provides key emissions factors for the other emissions models, CITAIR and TREMOD.
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The representative driving patterns derived as part of the driving-behavior component were then combined with the instantaneous emissions functions (i.e., lookup tables) representing the different vehicle types.
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FUEL-BASED EMISSIONS INVENTORIES The majority of regional emissions models in the United States, such as MOBILE and EMFAC, use travel-based models that combine gram-permile emissions factors with activity data in the form of VMT to estimate emissions. In contrast, fuel-based emissions inventories can also be calculated by normalizing emission factors to fuel consumption rather than VMT.
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From page 177... ...
In summary, the use of gram-per-gallon instead of gram-per-mile emissions factors is claimed to be a simpler method to calculate an emissions inventory, as long as sufficient remote-sensing and fuel-sales data is readily available. Many remote-sensing studies are taking place around the world and the use of remote-sensing in I/M programs are providing additional data.
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Models that can predict emissions based on these vehicle-operating modes are often referred to as modal emissions models. In general, several emissions modeling approaches have been introduced that attempt to include additional parameters beyond average speeds to better characterize emissions.
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is considered one time step at a time, an emissions value is obtained from the lookup table, and all emissions values are then summed together to obtain an emissions value for the entire cycle. There are several modal emissions models that are based on this lookup-table technique.
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Many vehicle types exist for which vehicle-operating history (i.e., the last several seconds of vehicle operation) can play a significant role in an instantaneous emissions value (e.g., the use of a timer to delay command enrichment, and oxygen storage in the catalytic converter)
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(1997) describes the development of an aggregate modal emissions modeling approach using sophisticated statistical techniques.
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Physical Instantaneous Emissions Mocdels Another approach to instantaneous emissions modeling is to use an analytical, physical modeling approach. In this type of approach, the entire emissions creation process is broken down into different components that correspond to physical phenomena associated with vehicle operation and emissions production (Barth et al.
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The physical modal emissions modeling approach has several attractive attributes: It inherently handles all of the factors in the vehicle-operating environment that affect emissions, such as vehicle technology, fuel type, operating modes, maintenance, accessory use, and road grade. Various components model the different processes in the vehicle related to emisslons.
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Thus, to obtain an accurate estimate of both the mean and distribution of emissions from a particular vehicle type, a very large number of vehicles would have to be characterized. INTEGRATION OF EMISSION MODELS WITH TRANSPORTATION MODELS To calculate an emissions inventory, it is necessary to have both a vehicle activity component and an emissions-factor component.
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In the framework shown in Figure 5-4, the MOBILE model fans into the macroscale level of emissions factor models. When creating an emissions inventory, regional transportation models predict total vehicle volume and average speed for all vehicles (in many cases broken out on a facility-specific basis)
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With the use of a modal emissions model, many more factors could be produced for a wide range of driving cycles for many different vehicle types. Thus, the SCF functions would have a much stronger foundation, as long as a reasonably accurate modal emissions model was used in deriving them.
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The easiest form of a modal emissions model to be applied here is the velocity-acceleration-indexed lookup table. In fact, the majority of microscale traffic-simulation models already have the built-in ability to predict emissions, given these emissions lookup tables.
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that uses an aggregate modal emissions model described earlier. The GIS framework allows for facility-level aggregations of microscale traffic-simulation, or disaggregation of traditional macroscale four-step travel-demand forecasting models to develop emissions-specific vehicle-activity data (Guensler et al.
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The modal emissions modeling component is the CMEM model described earlier. ITEM's transportation component is being developed on a hybrid macroscale and microscale approach.
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Each microscale traffic-simulation model is tightly coupled with the macroscale traffic-assignment model, which can dynamically reroute traffic as network capacities change. A travel-demand model drives the traffic-assignment, thus a regional emissions inventory can be produced by using statistical emissions rates (as a function of roadway facility and congestion level)
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transportation-controT measures, and their effect on motor-vehicle emissions. TRANSIMS has several key features: The identity of individual synthetic travelers is maintained throughout the entire simulation and analysis architecture, with activity times and locations computed for each individual.
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Evaporative emissions are also estimated. A total emissions inventory is produced and is used as input to various air-quality models (e.g., the MODELS-3 framework developed by EPA)
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If the vehicle has operated in the last hour, hotsoak start emissions are calculated based on the MOBILES formulation. For LDV emissions, the comprehensive modal emissions model (discussed in an earlier section)
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Various other vehicle emissions models have been or are being developed in other countries, at other regulatory agencies, and at different research organizations. These other modeling activities approach vehicle emissions estimation in a variety of ways.
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One of the key points of this chapter is that some models are more appropriate in terms of their spatial and temporal resolution than others for a given application. It is clear that MOBILE cannot satisfy many of the applications that it is currently used for; therefore, the committee recommends consideration of an emissions modeling toolkit that incorporates a variety of emissions models for different applications.
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