Develop a guidebook for practitioners, fusing public and private light and heavy vehicle datasets for inventory, regional, and project level hot spot analysis
Summary Statement: Research is needed in fusing together public and private commodity flow and operational datasets describing the light and heavy truck shipments between supplies and buyers. The data fusion method is needed to enhance air quality modeling inputs resulting in a greater understanding of light and heavy duty truck emissions associated with freight movement. Research will lead to the development of a guidebook on methods to fuse identified public and private datasets for emissions modeling. The goal of the work is to leverage the enhanced emission modeling features within the current emission simulator tools (MOVES2014 and EMFAC2011). The MPO's regional emission and DOT's hotspot analyses rely on national defaults allocating truck and non-truck vehicles by travel speed into Vehicle Specific Power (VSP) bins due to lack of locally observed data. Vehicle Specific Power, the forces a vehicle must overcome when operating on the road, was adopted for emission modeling with the release of MOtor Vehicle Emission Simulator (MOVES) (EPA , MOVES2009, April, 2009) and has shown to be a useful metric for characterizing vehicle emissions. The MOVES model adopts a formula for VSP that includes speed, acceleration, the force of gravity due to positive road grade, tire rolling resistance, and aerodynamic drag normalizing the power by the vehicle mass. The benefit is the combining of several physical factors influential to vehicle fuel consumption and emissions. It then uses this VSP, along with vehicle type and vehicle age, to weight emission rates before they are applied to the activity data to generate emissions estimates. Currently the national default database of MOVES includes 40 different drive schedules mapped to specific vehicle and roadway types. The MOVES database is limited in terms of representing travel activity for specific transportation facilities (intersections, ramps), specific vehicle types (heavy duty diesel trucks (HDDVs)), and certain emission processes (cold start and idling emissions). To estimate emissions from HDDVs, MOVES relies on emissions data from different sources (Clark et al, 2007 ). The private and public sector collects several physical factors used in the VSP calculation. However, the collected datasets are in various aggregate and disaggregate formats, different spatial and temporal resolutions and based on different collection methods (survey, count, and estimate). The private and public datasets contain segments of the commodity flow and vehicle operations describing the supply chain connecting suppliers to buyers, but with no complete supply chain dataset to develop emission simulator inputs refining light and heavy truck mobile source emissions. Thus, improving the data collection efforts are critical as these are important components contributing to a majority of emissions especially at analyzing hot-spots. The work products will be a practitioner's guidebook on fusing identified commodity flow and vehicle operational data in characterizing light and heavy truck emissions. Key tasks will include: • Derive an overall work plan to fuse traffic activity data from public and private commodity flow and operational datasets • Complete a literature review of existing data fusion methods. • Identification of private and public sources of commodity flow and vehicle operation data. • Compile data from private and public sources related to commodity flow and vehicle operation data. o Identify gaps in data and provide potential methods to collect missing data. • Develop methods to fuse compiled data. • Develop methods to query fused data set extracting emission simulator inputs. • Develop and test emission simulator enhanced VSP inputs for both a regional and hot spot mobile source emission analysis. • Document and present findings. Final product should be a guidebook on how to advance the state of the emission simulator practice considering the physical features influential to light and heavy truck fuel consumption and emissions.
Both the public and private sector have developed data fusion methods linking independently developed administrative, surveyed, collected, and estimated data sets creating a more complete portrayal of the area under study. Regional and hot spot emissions analysis would be enhanced with the data fusion of the segmented private and public sector freight supply chain data. Commodity flow data are available in datasets such as the Freight Analysis Framework and the Commodity Flow Survey. Truck duty schedules and GPS-recorded truck delivery tours are available from private sources, and truck weights and speeds are available from DOT's Weight-In-Motion and loop detector stations recording vehicle class counts and speed. Emission simulator model input assumptions would be enhanced improving regional and hot spot emission analysis. Air quality and environmental planners through additional analysis of the fused database would gain greater knowledge of light and heavy truck emissions related to the movement of goods. The additional knowledge could lead to better sighting of emission monitoring equipment, properly targeting local light and heavy truck emissions hotspots, evaluation of control strategy policies leading to meaningful reductions and compliance with National Ambient Air Quality Standards (NAAQS). Improved data for light and heavy truck activity is needed in the near-term to support regional planning, and SIP and TIP development. SIP updates, in particular, motivate the need for this work in the next few years. SIPs establish mobile source emissions budgets used for regional plans and the TIP conformity determination. Once the SIP is prepared, it is a time-consuming process to amend, making it important for new SIP development work to use the best available information regarding light and heavy truck activity. More accurate data will help to ensure future regional transportation plans, and TIPs will more closely align with the emissions budgets established through the SIP approval process. Underestimating emissions budgets could result in transportation conformity failures and delays in federally funded transportation projects. (Note - during the January 2016 TRB Annual Research Conference, this project was identified by the TRB Regional Air Quality Subcommittee as one of the top priority research needs; the original research statement was prepared by Jenny Narvaez North Central Texas Council of Governments 616 Six Flags Drive Arlington, TX 76011 817-608-2342 firstname.lastname@example.org and Charles Baber Baltimore Metropolitan Council 1500 Whetstone Way, Suite 300 Baltimore, MD 21230 410-732-0500, x1056 email@example.com)
Douglas Eisinger on behalf of ADC-20 (TRB Air Quality Committee)
Sonoma Technology, Inc.
May 8, 2017
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