The light-duty-vehicle fleet's evolution : anticipating PHEV adoption and greenhouse gas emissions across the U.S. fleet.

755017135PDFTech ReportSWUTC/11/161023-110727VehiclesVehicle operationsFleet managementGreenhouse gasesPollutionPolluting gasesExhaust gasesHybrid vehiclesElectric vehiclesHybrid automobilesElectric automobilesPlug-in hybrid vehiclesTexasSouthwest Region University Transportation Center (U.S.)Paul, BinnyKockleman, Kara M.Musti, SashankUniversity of Texas at Austin. Center for Transportation ResearchNTL-ENERGY AND ENVIRONMENT-Air QualityNTL-ENERGY AND ENVIRONMENT-Alternative FuelsNTL-ENERGY AND ENVIRONMENT-ENERGY AND ENVIRONMENTNTL-ENERGY AND ENVIRONMENT-Environment ImpactsNTL-PLANNING AND POLICY-PLANNING AND POLICYUS Transportation CollectionThe first part of this report relies on stated and revealed preference survey results across a sample of U.S. households to firstascertain vehicle acquisition, disposal, and use patterns, and then simulate these for a synthetic population over time. Resultsinclude predictions of future U.S. household-fleet composition, use, and greenhouse gas (GHG) emissions under nine differentscenarios, including variations in fuel and plug-in-electric-vehicle (PHEV) prices, new-vehicle feebate policies, and land-usedensitysettings. This work highlights the impacts of various directions consumers may head with such vehicles. For example,twenty-five-year simulations at gas prices at $7 per gallon resulted in the second highest market share predictions (16.30%) forPHEVs, HEVs, and Smart Cars (combined) \u2014 and the greatest GHG-emissions reductions. The strciter feebate policy (pivotpoint at 30 mpg and fee or rebate rate of $400 per mpg) \u2013 coupled with gasoline at $5 per gallon \u2013 resulted in the highestmarket share (16.37%) for PHEVs, HEVs, and Smart Cars, but not as much GHG emissions reduction as the $7 gas pricescenario. Excepting the low PHEV price and two feebate policy simulations, all other scenarios predicted a lower fleet VMT.While plug-in vehicles are now hitting the market, their adoption and widespread use will depend on thoughtful marketing,competitive pricing, government incentives, reliable driving-range reports, and adequate charging infrastructure.The second part of this report relies on data from the U.S. Consumer Expenditure Survey (CEX) to estimate the welfareimpacts of carbon taxes and household-level capping of emissions (with carbon-credit trading allowed). A translog utilityframework was calibrated and then used to anticipate household expenditures across nine consumer goods categories,including vehicle usage and vehicle expenses. An input-output model was used to estimate the impact of carbon pricing ongoods prices, and a vehicle choice model determined vehicle type preferences, along with each household\u2019s effective travelcosts. Behaviors were predicted under two carbon tax scenarios ($50 per ton and $100 per ton of CO2-equivalents) and fourcap-and-trade scenarios (10-ton and 15-ton cap per person per year with trading allowed at $50 per ton and $100 per toncarbon price). Carbon taxes were found to relatively regressive than a cap-and-trade setting (in terms of taxes paid per dollarof expenditure), but a tax-revenue redistribution can be used to offset this regressivity. In the absence of substitutionopportunities (within each of the nine expenditure categories), these results represent highly conservative (worst-case) results,but they illuminate the behavioral response trends while providing a rigorous framework for future work