With the increased interest in the interactions of land use and transportation and their related impacts on global warming, there is now a warranted need for improved and quicker techniques for simulating mobile source based, regional and sub-regional greenhouse gas emissions. The Bay Area Simplified Simulation of Travel, Energy and Greenhouse Gases (BASTEGG) is a GIS-based tool for calculating automobile availability, vehicle usage, fuel consumption, and greenhouse gas emissions, by each household within the San Francisco Bay Area at the neighborhood level. There are three component models in the BASSTEGG, simulating auto ownership levels, vehicle usage levels, and carbon dioxide emissions. Socio-economic and relative transit-to-highway accessibility data at the travel analysis zone level is used to predict the distribution of households by vehicle availability level. Cross-classification models of vehicle miles of travel per household (VMT/HH) are applied based on urban density levels, workers in household levels, income levels, and vehicle availability levels. Lastly, emissions per mile models, based on California Air Resources Board's EMFAC models for various forecast years, are used to convert VMT per household into on-road, mobile source greenhouse gas emissions per household. The BASSTEGG model is intended to be used in land use alternatives scenario testing at the regional level, and by city planners interested in the VMT and greenhouse gases produced by residents of their communities.


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    Title :

    BASSTEGG (Bay Area Simplified Simulation of Travel, Energy, and Greenhouse Gases): Sketch Planning Charrette/GIS Models for Predicting Household Vehicle Miles of Travel (VMT) and Greenhouse Gas (CO2) Emissions


    Contributors:

    Conference:

    Transportation, Land Use, Planning, and Air Quality 2009 ; 2009 ; Denver, Colorado, United States



    Publication date :

    2009-07-23




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English