IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v58y2013icp168-177.html
   My bibliography  Save this article

Highly-resolved modeling of personal transportation energy consumption in the United States

Author

Listed:
  • Muratori, Matteo
  • Moran, Michael J.
  • Serra, Emmanuele
  • Rizzoni, Giorgio

Abstract

This paper centers on the estimation of the total primary energy consumption for personal transportation in the United States, to include gasoline and/or electricity consumption, depending on vehicle type. The bottom-up sector-based estimation method introduced here contributes to a computational tool under development at The Ohio State University for assisting decision making in energy policy, pricing, and investment.

Suggested Citation

  • Muratori, Matteo & Moran, Michael J. & Serra, Emmanuele & Rizzoni, Giorgio, 2013. "Highly-resolved modeling of personal transportation energy consumption in the United States," Energy, Elsevier, vol. 58(C), pages 168-177.
    • Handle: RePEc:eee:energy:v:58:y:2013:i:c:p:168-177
    DOI: 10.1016/j.energy.2013.02.055
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544213001692
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2013.02.055?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Perrels, Adriaan & Weber, Christoph, 2000. "Modelling Impacts of Lifestyle on Energy Demand and Related Emissions," Discussion Papers 228, VATT Institute for Economic Research.
    2. Bin, Shui & Dowlatabadi, Hadi, 2005. "Corrigendum to "Consumer lifestyles approach to US energy use and the related CO2 emissions": [Energy Policy 33 (2005) 197-208]," Energy Policy, Elsevier, vol. 33(10), pages 1362-1363, July.
    3. Bin, Shui & Dowlatabadi, Hadi, 2005. "Consumer lifestyle approach to US energy use and the related CO2 emissions," Energy Policy, Elsevier, vol. 33(2), pages 197-208, January.
    4. Weber, Christoph & Perrels, Adriaan, 2000. "Modelling lifestyle effects on energy demand and related emissions," Energy Policy, Elsevier, vol. 28(8), pages 549-566, July.
    5. Shiau, Ching-Shin Norman & Samaras, Constantine & Hauffe, Richard & Michalek, Jeremy J., 2009. "Impact of battery weight and charging patterns on the economic and environmental benefits of plug-in hybrid vehicles," Energy Policy, Elsevier, vol. 37(7), pages 2653-2663, July.
    6. Muratori, Matteo & Roberts, Matthew C. & Sioshansi, Ramteen & Marano, Vincenzo & Rizzoni, Giorgio, 2013. "A highly resolved modeling technique to simulate residential power demand," Applied Energy, Elsevier, vol. 107(C), pages 465-473.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Tianduo Peng & Sheng Zhou & Zhiyi Yuan & Xunmin Ou, 2017. "Life Cycle Greenhouse Gas Analysis of Multiple Vehicle Fuel Pathways in China," Sustainability, MDPI, vol. 9(12), pages 1-24, November.
    2. Saket, Mohammad Javad & Maleki, Abbas & Hezaveh, Erfan Doroudgar & Karimi, Mohammad Sadegh, 2019. "Institutional analysis on impediments over fuel consumption reduction at Iran's transportation niches," Energy Policy, Elsevier, vol. 129(C), pages 861-867.
    3. Selima Sultana & Nastaran Pourebrahim & Hyojin Kim, 2018. "Household Energy Expenditures in North Carolina: A Geographically Weighted Regression Approach," Sustainability, MDPI, vol. 10(5), pages 1-22, May.
    4. O. V. Mazurova & E. V. Gal’perova, 2023. "Energy Consumption in Russia: Current State and Forecast," Studies on Russian Economic Development, Springer, vol. 34(1), pages 105-114, February.
    5. Dindarloo, Saeid R. & Siami-Irdemoosa, Elnaz, 2016. "Determinants of fuel consumption in mining trucks," Energy, Elsevier, vol. 112(C), pages 232-240.
    6. Sahraei, Mohammad Ali & Duman, Hakan & Çodur, Muhammed Yasin & Eyduran, Ecevit, 2021. "Prediction of transportation energy demand: Multivariate Adaptive Regression Splines," Energy, Elsevier, vol. 224(C).
    7. Arslan, Okan & Karasan, Oya Ekin, 2013. "Cost and emission impacts of virtual power plant formation in plug-in hybrid electric vehicle penetrated networks," Energy, Elsevier, vol. 60(C), pages 116-124.
    8. Lin, Haiyang & Fu, Kun & Wang, Yu & Sun, Qie & Li, Hailong & Hu, Yukun & Sun, Bo & Wennersten, Ronald, 2019. "Characteristics of electric vehicle charging demand at multiple types of location - Application of an agent-based trip chain model," Energy, Elsevier, vol. 188(C).
    9. Tang, Yanyan & Zhang, Qi & Mclellan, Benjamin & Li, Hailong, 2018. "Study on the impacts of sharing business models on economic performance of distributed PV-Battery systems," Energy, Elsevier, vol. 161(C), pages 544-558.
    10. Soto, Esteban A. & Bosman, Lisa B. & Wollega, Ebisa & Leon-Salas, Walter D., 2022. "Comparison of net-metering with peer-to-peer models using the grid and electric vehicles for the electricity exchange," Applied Energy, Elsevier, vol. 310(C).
    11. Fiori, Chiara & Ahn, Kyoungho & Rakha, Hesham A., 2016. "Power-based electric vehicle energy consumption model: Model development and validation," Applied Energy, Elsevier, vol. 168(C), pages 257-268.
    12. Orsi, Francesco & Muratori, Matteo & Rocco, Matteo & Colombo, Emanuela & Rizzoni, Giorgio, 2016. "A multi-dimensional well-to-wheels analysis of passenger vehicles in different regions: Primary energy consumption, CO2 emissions, and economic cost," Applied Energy, Elsevier, vol. 169(C), pages 197-209.
    13. Akansha Jain & Masoud Karimi-Ghartemani, 2022. "Mitigating Adverse Impacts of Increased Electric Vehicle Charging on Distribution Transformers," Energies, MDPI, vol. 15(23), pages 1-26, November.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Nieves, J.A. & Aristizábal, A.J. & Dyner, I. & Báez, O. & Ospina, D.H., 2019. "Energy demand and greenhouse gas emissions analysis in Colombia: A LEAP model application," Energy, Elsevier, vol. 169(C), pages 380-397.
    2. Sardianou, Eleni, 2007. "Estimating energy conservation patterns of Greek households," Energy Policy, Elsevier, vol. 35(7), pages 3778-3791, July.
    3. Ryu Koide & Michael Lettenmeier & Satoshi Kojima & Viivi Toivio & Aryanie Amellina & Lewis Akenji, 2019. "Carbon Footprints and Consumer Lifestyles: An Analysis of Lifestyle Factors and Gap Analysis by Consumer Segment in Japan," Sustainability, MDPI, vol. 11(21), pages 1-25, October.
    4. Kok, Rixt & Benders, Rene M.J. & Moll, Henri C., 2006. "Measuring the environmental load of household consumption using some methods based on input-output energy analysis: A comparison of methods and a discussion of results," Energy Policy, Elsevier, vol. 34(17), pages 2744-2761, November.
    5. Bai, Yin & Liu, Yong, 2013. "An exploration of residents’ low-carbon awareness and behavior in Tianjin, China," Energy Policy, Elsevier, vol. 61(C), pages 1261-1270.
    6. Golley, Jane & Meng, Xin, 2012. "Income inequality and carbon dioxide emissions: The case of Chinese urban households," Energy Economics, Elsevier, vol. 34(6), pages 1864-1872.
    7. Tilov, Ivan & Farsi, Mehdi & Volland, Benjamin, 2019. "Interactions in Swiss households’ energy demand: A holistic approach," Energy Policy, Elsevier, vol. 128(C), pages 136-149.
    8. Yong Liu & Jin Liu & Yunpeng Su, 2021. "Low-Carbon Awareness and Behaviors: Effects of Exposure to Climate Change Impact Photographs," SAGE Open, , vol. 11(3), pages 21582440211, July.
    9. Stephan Schwarzinger & David Neil Bird & Tomas Moe Skjølsvold, 2019. "Identifying Consumer Lifestyles through Their Energy Impacts: Transforming Social Science Data into Policy-Relevant Group-Level Knowledge," Sustainability, MDPI, vol. 11(21), pages 1-22, November.
    10. Wiedenhofer, Dominik & Lenzen, Manfred & Steinberger, Julia K., 2013. "Energy requirements of consumption: Urban form, climatic and socio-economic factors, rebounds and their policy implications," Energy Policy, Elsevier, vol. 63(C), pages 696-707.
    11. Benders, Rene M.J. & Kok, Rixt & Moll, Henri C. & Wiersma, Gerwin & Noorman, Klaas Jan, 2006. "New approaches for household energy conservation--In search of personal household energy budgets and energy reduction options," Energy Policy, Elsevier, vol. 34(18), pages 3612-3622, December.
    12. Yujiro Hirano & Tomohiko Ihara & Masayuki Hara & Keita Honjo, 2020. "Estimation of Direct and Indirect Household CO 2 Emissions in 49 Japanese Cities with Consideration of Regional Conditions," Sustainability, MDPI, vol. 12(11), pages 1-17, June.
    13. Zhang, Junjie & Yu, Biying & Wei, Yi-Ming, 2018. "Heterogeneous impacts of households on carbon dioxide emissions in Chinese provinces," Applied Energy, Elsevier, vol. 229(C), pages 236-252.
    14. Schmidt, Stephan & Weigt, Hannes, 2013. "A Review on Energy Consumption from a Socio-Economic Perspective: Reduction through Energy Efficiency and Beyond," Working papers 2013/15, Faculty of Business and Economics - University of Basel.
    15. Rui Huang & Shaohui Zhang & Changxin Liu, 2018. "Comparing Urban and Rural Household CO 2 Emissions—Case from China’s Four Megacities: Beijing, Tianjin, Shanghai, and Chongqing," Energies, MDPI, vol. 11(5), pages 1-17, May.
    16. Li, Jun & Zhang, Dayong & Su, Bin, 2019. "The Impact of Social Awareness and Lifestyles on Household Carbon Emissions in China," Ecological Economics, Elsevier, vol. 160(C), pages 145-155.
    17. Yuan, Baolong & Ren, Shenggang & Chen, Xiaohong, 2015. "The effects of urbanization, consumption ratio and consumption structure on residential indirect CO2 emissions in China: A regional comparative analysis," Applied Energy, Elsevier, vol. 140(C), pages 94-106.
    18. Fan, Jin & Li, Jun & Wu, Yanrui & Wang, Shanyong & Zhao, Dingtao, 2016. "The effects of allowance price on energy demand under a personal carbon trading scheme," Applied Energy, Elsevier, vol. 170(C), pages 242-249.
    19. Yu, Biying & Zhang, Junyi & Fujiwara, Akimasa, 2011. "Representing in-home and out-of-home energy consumption behavior in Beijing," Energy Policy, Elsevier, vol. 39(7), pages 4168-4177, July.
    20. Moises Neil V. Seriño & Stephan Klasen, 2015. "Estimation and Determinants of the Philippines' Household Carbon Footprint," The Developing Economies, Institute of Developing Economies, vol. 53(1), pages 44-62, March.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:energy:v:58:y:2013:i:c:p:168-177. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.