Under worldwide environmental stress, zero-emission vehicles (ZEV) are rapidly coming to market. However, it is not clear how such vehicles reduce vehicular emissions at a spatially explicit level, which is crucial for developing specific policies. This study proposed a quantitative approach to estimate the effectiveness of ZEVs in reducing emissions to support investment decisions promoting the use of ZEVs. The approach uses existing statewide travel demand and mobile emission models in an integrated framework. Scenarios are designed to measure the emissions reduction effects of ZEVs at different spatial scales (statewide, county, and roadway) and characteristics (densely and sparsely populated counties) and with various levels of market penetration and driving range limits. Results show significant spatial differentiation of the impact of ZEV deployment from county to roadway levels. Offering greater spatial detail and new insights on decision-making processes, this study described an integrated tool for identifying effective strategies for ZEV implementation.
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References
1.
Emissions of Greenhouse Gases in the U.S. Energy Information Administration, U.S. Department of Energy, 2011.
2.
Greenhouse Gas Emissions from the U.S. Transportation Sector, 1990–2003. EPA, 2006.
3.
Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2011, EPA, 2013.
4.
Emissions of Air Pollutants for the World Energy Outlook 2012 Energy Scenarios. International Energy Agency, Paris, 2012.
5.
Vehicle Technologies Program Multi-Year Program Plan (2011–2015). U.S. Department of Energy, 2010.
HarrisonG., and ShepherdS.. An Interdisciplinary Study to Explore Impacts from Policies for the Introduction of Low Carbon Vehicles. Transportation Planning and Technology, Vol. 37, No. 1, 2014, pp. 98–117. https://doi.org/10.1080/03081060.2013.844904.
8.
Electric Vehicles in Metropolitan Washington. Metropolitan Washington Council of Government, Washington, D.C., 2012.
9.
EppsteinM. J., GroverD. K., MarshallJ. S., and RizzoD. M.. An Agent-Based Model to Study Market Penetration of Plug-in Hybrid Electric Vehicles. Energy Policy, Vol. 39, No. 6, 2011, pp. 3789–3802. https://doi.org/10.1016/j.enpol.2011.04.007.
10.
BeckerT. A., and SidhuI.. Electric Vehicles in the United States: A New Model with Forecasts to 2030. Center for Entrepreneurship and Technology, University of California, Berkeley, 2009.
11.
Multi-State ZEV Action Plan. ZEV Program Implementation Task Force, 2014. http://www.zevstates.us. Accessed July 31, 2015.
12.
Nationwide Greenhouse Gas Emissions, Vol. 1, Environmental Assessment of Plug-In Hybrid Electric Vehicles. Electric Power Research Institute and Natural Resources Defense Council, Washington, D.C., 2007.
13.
JaramilloP., SamarasC., WakeleyH., and MeisterlingK.. Greenhouse Gas Implications of Using Coal for Transportation: Life Cycle Assessment of Coal-to-Liquids, Plug-In Hybrids, and Hydrogen Pathways. Energy Policy, Vol. 37, No. 7, 2009, pp. 2689–2695. https://doi.org/10.1016/j.enpol.2009.03.001.
14.
KarplusV. J., PaltsevS., and ReillyJ. M.. Prospects for Plug-In Hybrid Electric Vehicles in the United States and Japan: A General Equilibrium Analysis. Transportation Research Part A: Policy and Practice, Vol. 44, No. 8, 2010, pp. 620–641. https://doi.org/10.1016/j.tra.2010.04.004.
15.
SmithW. J.Plug-In Hybrid Electric Vehicles—A Low-Carbon Solution for Ireland?Energy Policy, Vol. 38, No. 3, 2010, pp. 1485–1499. https://doi.org/10.1016/j.enpol.2009.11.031.
16.
SkerlosS. J., and WinebrakeJ. J.. Targeting Plug-In Hybrid Electric Vehicle Policies to Increase Social Benefits. Energy Policy, Vol. 38, No. 2, 2010, pp. 705–708. https://doi.org/10.1016/j.enpol.2009.11.014.
17.
HollandS. P., MansurE. T., MullerN. Z. and YatesA. J.Measuring the Spatial Heterogeneity in Environmental Externalities from Driving: A Comparison of Gasoline and Electric Vehicles. American Economic Association 2015 Conference. https://www.aeaweb.org/aea/2015conference/program/retrieve.php?pdfid=394. Accessed July 7, 2015.
18.
WelchT. F.Climate Action Plans—Fact or Fiction? Evidence from Maryland. PhD dissertation. University of Maryland, College Park, 2013. http://drum.lib.umd.edu/handle/1903/14270. Accessed July 31, 2015.
19.
LambersonP. J.The Diffusion of Hybrid Electric Vehicles. Center for the Study of Complex Systems, University of Michigan, Ann Arbor, 2009.
20.
McManusW., and SenterR.Jr. Market Models for Predicting PHEV Adoption and Diffusion. Transportation Research Institute, University of Michigan, Ann Arbor, 2010.
21.
MustiS., and KockelmanK. M.. Evolution of the Household Vehicle Fleet: Anticipating Fleet Composition, PHEV Adoption and GHG Emissions in Austin, Texas. Transportation Research Part A: Policy and Practice, Vol. 45, No. 8, 2011, pp. 707–720. https://doi.org/10.1016/j.tra.2011.04.011.
22.
HidrueM., ParsonsG. R., KemptonW., and GardnerM. P.. Willingness to Pay for Electric Vehicles and Their Attributes. Resource and Energy Economics, Vol. 33, No. 3, 2011, pp. 686–705. https://doi.org/10.1016/j.reseneeco.2011.02.002.
23.
SikesK., GrossT., LinZ., SullivanJ., ClearyT., and WardJ.Plug-In Hybrid Electric Vehicle Market Introduction Study: Final Report. Oak Ridge National Laboratory, Oak Ridge, Tenn., 2010.
24.
CuiX., LiuC., KimH. K., KaoS.-C., TuttleM. A., and BhaduriB. L.. A Multi Agent-Based Framework for Simulating Household PHEV Distribution and Electric Distribution Network Impact. Presented at 90th Annual Meeting of the Transportation Research Board, Washington, D.C., 2011.
25.
SullivanJ. L., SalmeenI. T., and SimonC. P.. PHEV Market Place Penetration: An Agent Based Simulation. Transportation Research Institute, University of Michigan, Ann Arbor, 2009.
26.
Al-AlawiB. M., and BradleyT. H.. Review of Hybrid, Plug-In Hybrid, and Electric Vehicle Market Modeling Studies. Renewable & Sustainable Energy Reviews, Vol. 21, 2013, pp. 190–203. https://doi.org/10.1016/j.rser.2012.12.048.
27.
BalducciP. J.Plug-in Hybrid Electric Vehicles Market Penetration Scenarios. Pacific Northwest National Laboratory, Richland, Wash., 2008. https://doi.org/10.2172/961683.
28.
HeckmannC. G., MichalekJ. J., MorrowW. R., and LiuY.. Sensitivity of Vehicle Market Share Predictions to Alternative Discrete Choice Model Specifications. ASME 13 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, Portland, Ore., Aug. 4–7, 2013. https://doi.org/10.1115/DETC2013-13372.
29.
ShinJ., HongJ., JeongG., and LeeJ.. Impact of Electric Vehicles on Existing Car Usage: A Mixed Multiple Discrete–Continuous Extreme Value Model Approach. Transportation Research Part D: Transport and Environment, Vol. 17, No. 2, 2012, pp. 138–144. https://doi.org/10.1016/j.trd.2011.10.004.
30.
Van VlietO., BrouwerA. S., KuramochiT., van den BroekM., and FaaijA.. Energy Use, Cost and CO2 Emissions of Electric Cars. Journal of Power Sources, Vol. 196, No. 4, 2011, pp. 2298–2310. https://doi.org/10.1016/j.jpowsour.2010.09.119.
31.
RichardsonD. B.Electric Vehicles and the Electric Grid: A Review of Modeling Approaches, Impacts, and Renewable Energy Integration. Renewable & Sustainable Energy Reviews, Vol. 19, 2013, pp. 247–254. https://doi.org/10.1016/j.rser.2012.11.042.
32.
AmirjamshidiG., MostafaT. S., MisraA., and RoordaM. J.. Integrated Model for Microsimulating Vehicle Emissions, Pollutant Dispersion and Population Exposure. Transportation Research Part D: Transport and Environment, Vol. 18, 2013, pp. 16–24. https://doi.org/10.1016/j.trd.2012.08.003.
33.
NamdeoA., MitchellG., and DixonR.. TEMMS: An Integrated Package for Modelling and Mapping Urban Traffic Emissions and Air Quality. Environmental Modelling & Software, No. 17, 2002, pp. 179–190.
34.
NejadkoorkiF., NicholsonK., LakeI., and DaviesT.. An Approach for Modelling CO2 Emissions from Road Traffic in Urban Areas. Science of the Total Environment, Vol. 406, No. 1–2, 2008, pp. 269–278. https://doi.org/10.1016/j.scitotenv.2008.07.055.
35.
AffumJ. K., BrownA. L., and ChanY. C.. Integrating Air Pollution Modelling with Scenario Testing in Road Transport Planning: The TRAEMS Approach. Science of the Total Environment, Vol. 312, No. 1–3, 2003, pp. 1–14. https://doi.org/10.1016/S0048-9697(03)00192-X.
36.
PotoglouD., and KanaroglouP. S.. Household Demand and Willingness to Pay for Clean Vehicles. Transportation Research Part D: Transport and Environment, Vol. 12, No. 4, 2007, pp. 264–274. https://doi.org/10.1016/j.trd.2007.03.001.
37.
GouliasK. G., BhatC. R., PendylaR. M., ChenY., PaletiR., KonduriK. C., HuangH. G., and HuH. H.. Simulator of Activities, Greenhouse Emissions, Networks, and Travel (SimAGENT) in Southern California. Proceedings of the 2011 IEEE Forum on Integrated and Sustainable Transportation Systems, Vienna, June 28–July 1, 2011, pp. 164–169.
38.
WeiH., WangX., YaoZ., and LiuJ.. Framework for Integrating Traffic-Source Emission Estimates into Sustainability Analysis. Proceedings of the 12th COTA International Conference of Transportation Professionals, Beijing, People’s Republic of China, Aug. 3–6, 2012. https://doi.org/10.1061/9780784412442.364.
39.
XieY., ChowdhuryM., BhavsarP., and ZhouY.. An Integrated Modeling Approach for Facilitating Emission Estimations of Alternative Fueled Vehicles. Transportation Research Part D: Transport and Environment, Vol. 17, No. 1, 2012, pp. 15–20. https://doi.org/10.1016/j.trd.2011.08.009.
40.
ChoJ., and HuW.. Network-Based Simulation of Air Pollution Emissions Associated with Truck Operations. Journal of the Transportation Research Forum, Vol. 52, No. 3, 2013, pp. 41–62.
41.
Maryland Statewide Transportation Model—Phase III. Report Prepared by National Center for Smart Growth Research and Education and Parsons Brinkerhoff for Maryland State Highway Administration, Baltimore, 2013.
42.
PearreN. S., KemptonW., GuenslerR. L., and ElangoV. V.. Electric Vehicles: How Much Range Is Required for a Day’s Driving?Transportation Research Part C: Emerging Technologies, Vol. 19, No. 6, 2011, pp. 1171–1184. https://doi.org/10.1016/j.trc.2010.12.010.
43.
WuQ., NielsenA. H., OstergaardJ., ChaS. T., MarraF., ChenY., and TraeholtC.. Driving Pattern Analysis for Electric Vehicle (EV) Grid Integration Study. Proceedings of the 2010 IEEE PES Innovative Smart Grid Technologies Conference Europe, Gothenburg, Sweden, Oct. 11–13, 2010, pp. 1–6.
44.
Electric Vehicle Infrastructure Council. Interim Report. Maryland Department of Transportation, Hanover, 2015.
45.
Long-Term Electric Report for Maryland. Maryland Department of Natural Resources, Annapolis, 2011.
46.
GermanT. M.Zero Emission Passenger Vehicles in the United States, Anticipating Future Automobile Industry Trends Based on Stakeholder Interview Analysis. Master’s thesis. Massachusetts Institute of Technology, Cambridge, 2012.
47.
GolobT. F., and GouldJ.. Projecting Use of Electric Vehicles from Household Vehicle Trials. Transportation Research Part B: Methodological, Vol. 32, No. 7, 1998, pp. 441–454. https://doi.org/10.1016/S0191-2615(98)00001-0.
48.
DainaN., PolakJ. W., and SivakumarA.. Patent and Latent Predictors of Electric Vehicle Charging Behavior. Transportation Research Record: Journal of the Transportation Research Board, No. 2502, 2015, pp. 116–123. https://dx.doi.org/10.3141/2502-14.
ZhouY., WangM., HaoH., JohnsonL., WangH., and HaoH.. Plug-In Electric Vehicle Market Penetration and Incentives: A Global Review. Mitigation and Adaptation Strategies for Global Change, Vol. 20, No. 5, 2015, pp. 777–795. https://doi.org/10.1007/s11027-014-9611-2.
54.
Drive Cycle Development, in Modifying Link-Level Emissions Modeling Procedures for Applications within the MOVES Framework. FHWA, U.S. Department of Transportation, 2014.
Feasibility and Benefit of Advanced Four-Step and Activity-Based Travel Demand Models for Maryland. Maryland State Highway Administration, Baltimore, 2011.
