IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v16y2022i1p459-d1021763.html
   My bibliography  Save this article

Energy Efficiency of Heavy-Duty Vehicles in Mexico

Author

Listed:
  • Oscar S. Serrano-Guevara

    (Energy and Climate Change Research Group, School of Engineering and Sciences, Tecnologico de Monterrey, Monterrey 64849, NL, Mexico)

  • José I. Huertas

    (Energy and Climate Change Research Group, School of Engineering and Sciences, Tecnologico de Monterrey, Monterrey 64849, NL, Mexico)

  • Luis F. Quirama

    (Sustainable Mobility Unit, United Nations Environment Program, Nairobi 30552, Kenya)

  • Antonio E. Mogro

    (Energy and Climate Change Research Group, School of Engineering and Sciences, Tecnologico de Monterrey, Monterrey 64849, NL, Mexico)

Abstract

The energy consumption of a large sample of vehicles (6955) operating during the last 3 years under everyday conditions across Mexico was monitored via OBD-based telematics systems. A life cycle statistical analysis of the obtained data showed that, on average, 54 t diesel vehicles used for long-distance freight transport consume 44.25 L/100 km and emit 1513 g CO 2 e/km. When these vehicles are powered by natural gas, the energy consumption and the emissions of greenhouse gases (GHG) are increased by 23% and reduced by 0.8%, respectively. Using manufacturers’ data, these values reduce energy consumption by 16% and GHG emissions by 52% when they are electric. Similar observations were made for other vehicles sizes used for transporting goods and people.

Suggested Citation

  • Oscar S. Serrano-Guevara & José I. Huertas & Luis F. Quirama & Antonio E. Mogro, 2022. "Energy Efficiency of Heavy-Duty Vehicles in Mexico," Energies, MDPI, vol. 16(1), pages 1-25, December.
    • Handle: RePEc:gam:jeners:v:16:y:2022:i:1:p:459-:d:1021763
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/16/1/459/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/16/1/459/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Huertas, José I. & Serrano-Guevara, Oscar & Díaz-Ramírez, Jenny & Prato, Daniel & Tabares, Lina, 2022. "Real vehicle fuel consumption in logistic corridors," Applied Energy, Elsevier, vol. 314(C).
    2. Malik, Leeza & Tiwari, Geetam, 2017. "Assessment of interstate freight vehicle characteristics and impact of future emission and fuel economy standards on their emissions in India," Energy Policy, Elsevier, vol. 108(C), pages 121-133.
    3. Zhang, Shaojun & Wu, Ye & Liu, Huan & Huang, Ruikun & Yang, Liuhanzi & Li, Zhenhua & Fu, Lixin & Hao, Jiming, 2014. "Real-world fuel consumption and CO2 emissions of urban public buses in Beijing," Applied Energy, Elsevier, vol. 113(C), pages 1645-1655.
    4. Aroua, Ayoub & Lhomme, Walter & Redondo-Iglesias, Eduardo & Verbelen, Florian, 2022. "Fuel saving potential of a long haul heavy duty vehicle equipped with an electrical variable transmission," Applied Energy, Elsevier, vol. 307(C).
    Full references (including those not matched with items on IDEAS)

    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. Sun, Lu & Liu, Wenjing & Li, Zhaoling & Cai, Bofeng & Fujii, Minoru & Luo, Xiao & Chen, Wei & Geng, Yong & Fujita, Tsuyoshi & Le, Yiping, 2021. "Spatial and structural characteristics of CO2 emissions in East Asian megacities and its indication for low-carbon city development," Applied Energy, Elsevier, vol. 284(C).
    2. Zhang, Shaojun & Wu, Ye & Un, Puikei & Fu, Lixin & Hao, Jiming, 2016. "Modeling real-world fuel consumption and carbon dioxide emissions with high resolution for light-duty passenger vehicles in a traffic populated city," Energy, Elsevier, vol. 113(C), pages 461-471.
    3. Tong, Zheming & Chen, Yujiao & Malkawi, Ali & Liu, Zhu & Freeman, Richard B., 2016. "Energy saving potential of natural ventilation in China: The impact of ambient air pollution," Applied Energy, Elsevier, vol. 179(C), pages 660-668.
    4. Yurii Gutarevych & Vasyl Mateichyk & Jonas Matijošius & Alfredas Rimkus & Igor Gritsuk & Oleksander Syrota & Yevheniy Shuba, 2020. "Improving Fuel Economy of Spark Ignition Engines Applying the Combined Method of Power Regulation," Energies, MDPI, vol. 13(5), pages 1-19, March.
    5. Liyan Feng & Jun Zhai & Lei Chen & Wuqiang Long & Jiangping Tian & Bin Tang, 2017. "Increasing the application of gas engines to decrease China’s GHG emissions," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 22(6), pages 839-861, August.
    6. Pu Lyu & Yongjie Lin & Yuanqing Wang, 2019. "The impacts of household features on commuting carbon emissions: a case study of Xi’an, China," Transportation, Springer, vol. 46(3), pages 841-857, June.
    7. Salvo, Orlando de & Vaz de Almeida, Flávio G., 2019. "Influence of technologies on energy efficiency results of official Brazilian tests of vehicle energy consumption," Applied Energy, Elsevier, vol. 241(C), pages 98-112.
    8. Ribau, João P. & Sousa, João M.C. & Silva, Carla M., 2015. "Reducing the carbon footprint of urban bus fleets using multi-objective optimization," Energy, Elsevier, vol. 93(P1), pages 1089-1104.
    9. Jose Alejandro Cano & Abraham Londoño-Pineda & Carolina Rodas, 2022. "Sustainable Logistics for E-Commerce: A Literature Review and Bibliometric Analysis," Sustainability, MDPI, vol. 14(19), pages 1-24, September.
    10. Liu, Liwei & Zong, Haijing & Zhao, Erdong & Chen, Chuxiang & Wang, Jianzhou, 2014. "Can China realize its carbon emission reduction goal in 2020: From the perspective of thermal power development," Applied Energy, Elsevier, vol. 124(C), pages 199-212.
    11. Aderiana Mutheu Mbandi & Jan R. Böhnke & Dietrich Schwela & Harry Vallack & Mike R. Ashmore & Lisa Emberson, 2019. "Estimating On-Road Vehicle Fuel Economy in Africa: A Case Study Based on an Urban Transport Survey in Nairobi, Kenya," Energies, MDPI, vol. 12(6), pages 1-28, March.
    12. Bo Hong & Hongqiao Qin & Runsheng Jiang & Min Xu & Jiaqi Niu, 2018. "How Outdoor Trees Affect Indoor Particulate Matter Dispersion: CFD Simulations in a Naturally Ventilated Auditorium," IJERPH, MDPI, vol. 15(12), pages 1-21, December.
    13. Nie, Qingyun & Zhang, Lihui & Tong, Zihao & Hubacek, Klaus, 2022. "Strategies for applying carbon trading to the new energy vehicle market in China: An improved evolutionary game analysis for the bus industry," Energy, Elsevier, vol. 259(C).
    14. Bigazzi, Alexander, 2019. "Comparison of marginal and average emission factors for passenger transportation modes," Applied Energy, Elsevier, vol. 242(C), pages 1460-1466.
    15. O'Shea, R. & Wall, D.M. & McDonagh, S. & Murphy, J.D., 2017. "The potential of power to gas to provide green gas utilising existing CO2 sources from industries, distilleries and wastewater treatment facilities," Renewable Energy, Elsevier, vol. 114(PB), pages 1090-1100.
    16. Akbar Ali & Nasir Ayub & Muhammad Shiraz & Niamat Ullah & Abdullah Gani & Muhammad Ahsan Qureshi, 2021. "Traffic Efficiency Models for Urban Traffic Management Using Mobile Crowd Sensing: A Survey," Sustainability, MDPI, vol. 13(23), pages 1-18, November.
    17. Yang, Yuan & Wang, Can & Liu, Wenling & Zhou, Peng, 2017. "Microsimulation of low carbon urban transport policies in Beijing," Energy Policy, Elsevier, vol. 107(C), pages 561-572.
    18. García, Antonio & Monsalve-Serrano, Javier & Martinez-Boggio, Santiago & Zhao, Wenbin & Qian, Yong, 2022. "Intelligent charge compression ignition combustion for range extender medium duty applications," Renewable Energy, Elsevier, vol. 187(C), pages 671-687.
    19. Rosero, Fredy & Fonseca, Natalia & López, José-María & Casanova, Jesús, 2021. "Effects of passenger load, road grade, and congestion level on real-world fuel consumption and emissions from compressed natural gas and diesel urban buses," Applied Energy, Elsevier, vol. 282(PB).
    20. Wen, Yifan & Wu, Ruoxi & Zhou, Zihang & Zhang, Shaojun & Yang, Shengge & Wallington, Timothy J. & Shen, Wei & Tan, Qinwen & Deng, Ye & Wu, Ye, 2022. "A data-driven method of traffic emissions mapping with land use random forest models," Applied Energy, Elsevier, vol. 305(C).

    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:gam:jeners:v:16:y:2022:i:1:p:459-:d:1021763. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.