NYMTC Post-Processor Software Development

Accurate transportation emissions inventories are a key component to transportation planning, air quality modeling, and relevant policy making. Regional level inventories are essential to the conformity process required by the Clean Air Act, and they can help inform planners of the regional effects of changes to the transportation infrastructure. Regional inventories alone provide an incomplete picture, however. They lack the ability and temporal/spatial resolution to inform planners of local changes to emissions inventories and air quality impacts (e.g., hotspots). Furthermore, insufficient temporal and spatial resolution limits their capacity to provide useful input to air quality models, which can predict dispersion and chemical reactions of the emissions in the atmosphere. Providing highly spatially and temporally resolved gridded emissions inventories, while staying with well grounded assumptions and within computational limits, will be one of the greatest challenges of developing the next generation of post-processor software for the New York Metropolitan Transportation Council's (NYMTC's) Best Practice Model (BPM). Another significant challenge will be building in compatibility with the Motor Vehicle Emissions Simulator (MOVES), EPA's next generation emissions software. MOVES software computes emissions rates in fundamentally different ways, and has dramatically higher computational needs than its predecessor, MOBILE6.2. This proposed study consists of a phased approach involving fourteen integrated tasks for the development of NYMTC post-processor software--next generation grid-based transportation emissions inventory estimation using BPM and EPA's new MOVES model. The tasks include: (1) Administrative Structure; (2) Study Coordination; (3) Project Website; (4) Identification of Data Needs and Available Data Resources;  (5) Evaluation of Software Platform for Post-Processor; (6) Software Specification; (7) Data Integration and Assembly; (8) Software Development and Estimation; (9) Computational Efficiency Improvements; (10) Software Calibration and Adjustments; (11) Software Validation and Refinement; (12) Software Integration and Implementation; (13) Staff Training and Technical Support; and (14) Final Documentation. The study will be the first comprehensive post-processor development for NYMTC that incorporates the most up-to-date advancements in experimental and analytical tools for accurate estimation of transportation emissions inventory. The resulting models and tools will provide rich and reliable information to characterize transportation emissions, air quality impacts, and public health implications, facilitate demonstrations and evaluations of environmental benefits from regional transportation plans and transportation improvement programs, and provide enhanced factual information and scientific understanding of various transportation strategies that can be used for future policy making in NYS and for comparisons across the country. This study also represents the first attempt to explore and assess potential methodologies and algorithms to link the state-of-science activity-based travel demand models (NYMTC's BPM) and EPA's next generation transportation emissions model, MOVES. Result from this study will support NYMTC and NYS programs in air quality management, especially the transportation conformity and State Implementation Plans for nonattainment areas, and provides quantitative basis to assist NYMTC and the State in securing federal funding through Congestion Mitigation and Air Quality Improvement Program.

Language

  • English

Project

  • Status: Proposed
  • Funding: $385005.00
  • Contract Numbers:

    RF 55658-04-02

  • Sponsor Organizations:

    New York Metropolitan Transportation Council

    199 Water Street
    New York, NY  United States  10038
  • Project Managers:

    Amber, Wieslawa

  • Performing Organizations:

    Cornell University

    Ithaca, NY  United States  14853
  • Principal Investigators:

    Gehrke, Johannes

    Gao, Huaizhu

  • Start Date: 20091101
  • Expected Completion Date: 20171231
  • Actual Completion Date: 0
  • Source Data: RiP Project 24000

Subject/Index Terms

Filing Info

  • Accession Number: 01572643
  • Record Type: Research project
  • Source Agency: University Transportation Research Center
  • Contract Numbers: RF 55658-04-02
  • Files: UTC, RiP
  • Created Date: Aug 11 2015 1:00AM