IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v7y2015i7p9140-9159d52590.html
   My bibliography  Save this article

Spatial Distribution of Energy Consumption and Carbon Emission of Regional Logistics

Author

Listed:
  • Fan Xiao

    (School of Information Engineering Institute, Shanghai Maritime University, Shanghai 200135, China
    Logistics Research Center, Shanghai Maritime University, Shanghai 200135, China)

  • Zhi-Hua Hu

    (Logistics Research Center, Shanghai Maritime University, Shanghai 200135, China)

  • Ke-Xin Wang

    (School of Economics and Management, Shanghai Maritime University, Shanghai 200135, China)

  • Pei-Hua Fu

    (School of Computer Science and Information Engineering, Zhejiang Gongshang University, Hangzhou 310018, China)

Abstract

Facing serious energy-related constraints and environmental stress, the development of the green logistics industry is restricted by degrees of logistics energy utilization and carbon emissions. Considering different logistics spatial distributions, this paper uses the degree of regional logistics energy utilization and the spatial distribution of carbon emissions as two indicators of green logistics to investigate the regional differences and changes in spatiotemporal logistics energy efficiency. We firstly measure the regional logistics in terms of energy consumption and carbon emission, then further measure the logistics by energy intensity and carbon intensity. Based on these four indicators, the relations between spatiotemporal logistics and regional logistics development are analyzed. Through studying the spatial and temporal evolution trends of the above indicators, we found that a certain convergence exists. Finally, based on the analysis, the suggestions for energy saving and emission reduction are proposed according to regional conditions. The results benefit to narrow the efficiency gap between regions and achieve the goal of improving logistics energy efficiency.

Suggested Citation

  • Fan Xiao & Zhi-Hua Hu & Ke-Xin Wang & Pei-Hua Fu, 2015. "Spatial Distribution of Energy Consumption and Carbon Emission of Regional Logistics," Sustainability, MDPI, vol. 7(7), pages 1-20, July.
    • Handle: RePEc:gam:jsusta:v:7:y:2015:i:7:p:9140-9159:d:52590
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/7/7/9140/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/7/7/9140/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Caraiani, Chirața & Lungu, Camelia I. & Dascălu, Cornelia, 2015. "Energy consumption and GDP causality: A three-step analysis for emerging European countries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 44(C), pages 198-210.
    2. Li, Zheng & Pan, Lingying & Fu, Feng & Liu, Pei & Ma, Linwei & Amorelli, Angelo, 2014. "China's regional disparities in energy consumption: An input–output analysis," Energy, Elsevier, vol. 78(C), pages 426-438.
    3. Rivera, Liliana & Sheffi, Yossi & Welsch, Roy, 2014. "Logistics agglomeration in the US," Transportation Research Part A: Policy and Practice, Elsevier, vol. 59(C), pages 222-238.
    4. Fahimnia, Behnam & Sarkis, Joseph & Eshragh, Ali, 2015. "A tradeoff model for green supply chain planning:A leanness-versus-greenness analysis," Omega, Elsevier, vol. 54(C), pages 173-190.
    5. Zhang, Ning & Wei, Xiao, 2015. "Dynamic total factor carbon emissions performance changes in the Chinese transportation industry," Applied Energy, Elsevier, vol. 146(C), pages 409-420.
    6. Jiang, Lei & Folmer, Henk & Ji, Minhe, 2014. "The drivers of energy intensity in China: A spatial panel data approach," China Economic Review, Elsevier, vol. 31(C), pages 351-360.
    7. Hu, Jin-Li & Wang, Shih-Chuan, 2006. "Total-factor energy efficiency of regions in China," Energy Policy, Elsevier, vol. 34(17), pages 3206-3217, November.
    8. Bilgen, S., 2014. "Structure and environmental impact of global energy consumption," Renewable and Sustainable Energy Reviews, Elsevier, vol. 38(C), pages 890-902.
    9. Sheu, Jiuh-Biing & Chou, Yi-Hwa & Hu, Chun-Chia, 2005. "An integrated logistics operational model for green-supply chain management," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 41(4), pages 287-313, July.
    10. Lin, Boqiang & Wang, Xiaolei, 2014. "Exploring energy efficiency in China׳s iron and steel industry: A stochastic frontier approach," Energy Policy, Elsevier, vol. 72(C), pages 87-96.
    11. van den Heuvel, Frank P. & de Langen, Peter W. & van Donselaar, Karel H. & Fransoo, Jan C., 2013. "Regional logistics land allocation policies: Stimulating spatial concentration of logistics firms," Transport Policy, Elsevier, vol. 30(C), pages 275-282.
    12. Wang, Zhaohua & Lu, Milin, 2014. "An empirical study of direct rebound effect for road freight transport in China," Applied Energy, Elsevier, vol. 133(C), pages 274-281.
    13. Duan, Hong-Bo & Zhu, Lei & Fan, Ying, 2014. "Optimal carbon taxes in carbon-constrained China: A logistic-induced energy economic hybrid model," Energy, Elsevier, vol. 69(C), pages 345-356.
    14. Hooi Lean, Hooi & Huang, Wei & Hong, Junjie, 2014. "Logistics and economic development: Experience from China," Transport Policy, Elsevier, vol. 32(C), pages 96-104.
    15. Lai, Kee-hung & Wong, Christina W.Y. & Cheng, T.C.E., 2012. "Ecological modernisation of Chinese export manufacturing via green logistics management and its regional implications," Technological Forecasting and Social Change, Elsevier, vol. 79(4), pages 766-770.
    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. Hao Zhang & Xin Sun & Kailong Dong & Lianghui Sui & Min Wang & Qiong Hong, 2022. "Green Innovation in Regional Logistics: Level Evaluation and Spatial Analysis," IJERPH, MDPI, vol. 20(1), pages 1-20, December.
    2. Meiling He & Jiaren Shen & Xiaohui Wu & Jianqiang Luo, 2018. "Logistics Space: A Literature Review from the Sustainability Perspective," Sustainability, MDPI, vol. 10(8), pages 1-24, August.
    3. Lijun Liu & Zhixin Long & Chuangchuang Kou & Haozeng Guo & Xinyu Li, 2023. "Evaluation of the Environmental Cost of Integrated Inbound Logistics: A Case Study of a Gigafactory of a Chinese Logistics Firm," Sustainability, MDPI, vol. 15(15), pages 1-20, July.
    4. Xueping Tao & Ping Wang & Bangzhu Zhu, 2016. "Measuring the Interprovincial CO 2 Emissions Considering Electric Power Dispatching in China: From Production and Consumption Perspectives," Sustainability, MDPI, vol. 8(6), pages 1-12, May.
    5. Zhang, Cheng & Zhou, Xinxin & Zhou, Bo & Zhao, Ziwei, 2022. "Impacts of a mega sporting event on local carbon emissions: A case of the 2014 Nanjing Youth Olympics," China Economic Review, Elsevier, vol. 73(C).
    6. Tamás Bányai, 2018. "Real-Time Decision Making in First Mile and Last Mile Logistics: How Smart Scheduling Affects Energy Efficiency of Hyperconnected Supply Chain Solutions," Energies, MDPI, vol. 11(7), pages 1-25, July.
    7. Caiquan Bai & Yuehua Mao & Yuan Gong & Chen Feng, 2019. "Club Convergence and Factors of Per Capita Transportation Carbon Emissions in China," Sustainability, MDPI, vol. 11(2), pages 1-13, January.
    8. Guo-Ling Jia & Rong-Guo Ma & Zhi-Hua Hu, 2019. "Urban Transit Network Properties Evaluation and Optimization Based on Complex Network Theory," Sustainability, MDPI, vol. 11(7), pages 1-16, April.
    9. Gao, Jingzhe & Xiao, Zhongdong & Cao, Binbin & Chai, Qiangfei, 2018. "Green supply chain planning considering consumer’s transportation process," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 109(C), pages 311-330.
    10. Xiaopeng Guo & Jiaxing Shi & Dongfang Ren & Jing Ren & Qilin Liu, 2017. "Correlations between air pollutant emission, logistic services, GDP, and urban population growth from vector autoregressive modeling: a case study of Beijing," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 87(2), pages 885-897, June.
    11. Miroslav Stefanov, 2018. "Features of Compressed Natural Gas Physical Distribution: A Bulgarian Case Study," Logistics, MDPI, vol. 2(3), pages 1-21, September.
    12. Cejun Cao & Congdong Li & Qin Yang & Fanshun Zhang, 2017. "Multi-Objective Optimization Model of Emergency Organization Allocation for Sustainable Disaster Supply Chain," Sustainability, MDPI, vol. 9(11), pages 1-22, November.
    13. Li, Wei & Sun, Wen & Li, Guomin & Cui, Pengfei & Wu, Wen & Jin, Baihui, 2017. "Temporal and spatial heterogeneity of carbon intensity in China's construction industry," Resources, Conservation & Recycling, Elsevier, vol. 126(C), pages 162-173.
    14. Sören Lauenstein & Christoph Schank, 2022. "Design of a Sustainable Last Mile in Urban Logistics—A Systematic Literature Review," Sustainability, MDPI, vol. 14(9), pages 1-14, May.
    15. Lei Yang & Yiji Cai & Jiahui Hong & Yongqiang Shi & Zhiyong Zhang, 2016. "Urban Distribution Mode Selection under Low Carbon Economy—A Case Study of Guangzhou City," Sustainability, MDPI, vol. 8(7), pages 1-22, July.

    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. Yan, Huijie, 2015. "Provincial energy intensity in China: The role of urbanization," Energy Policy, Elsevier, vol. 86(C), pages 635-650.
    2. Zhang, Yue-Jun & Liu, Zhao & Zhou, Si-Ming & Qin, Chang-Xiong & Zhang, Huan, 2018. "The impact of China's Central Rise Policy on carbon emissions at the stage of operation in road sector," Economic Modelling, Elsevier, vol. 71(C), pages 159-173.
    3. Zebin Zheng & Wenjun Xiao & Ziye Cheng, 2023. "China’s Green Total Factor Energy Efficiency Assessment Based on Coordinated Reduction in Pollution and Carbon Emission: From the 11th to the 13th Five-Year Plan," Sustainability, MDPI, vol. 15(9), pages 1-20, April.
    4. Zhang, Yue-Jun & Sun, Ya-Fang & Huang, Junling, 2018. "Energy efficiency, carbon emission performance, and technology gaps: Evidence from CDM project investment," Energy Policy, Elsevier, vol. 115(C), pages 119-130.
    5. Du, Minzhe & Wang, Bing & Zhang, Ning, 2018. "National research funding and energy efficiency: Evidence from the National Science Foundation of China," Energy Policy, Elsevier, vol. 120(C), pages 335-346.
    6. Zhong, Zhangqi & Jiang, Lei & Zhou, Peng, 2018. "Transnational transfer of carbon emissions embodied in trade: Characteristics and determinants from a spatial perspective," Energy, Elsevier, vol. 147(C), pages 858-875.
    7. Ding, Li-Li & Lei, Liang & Zhao, Xin & Calin, Adrian Cantemir, 2020. "Modelling energy and carbon emission performance: A constrained performance index measure," Energy, Elsevier, vol. 197(C).
    8. Li, Ke & Lin, Boqiang, 2015. "Measuring green productivity growth of Chinese industrial sectors during 1998–2011," China Economic Review, Elsevier, vol. 36(C), pages 279-295.
    9. Cheng, Zhonghua & Li, Lianshui & Liu, Jun & Zhang, Huiming, 2018. "Total-factor carbon emission efficiency of China's provincial industrial sector and its dynamic evolution," Renewable and Sustainable Energy Reviews, Elsevier, vol. 94(C), pages 330-339.
    10. Sun, Qi & Xu, Lin & Yin, Hua, 2016. "Energy pricing reform and energy efficiency in China: Evidence from the automobile market," Resource and Energy Economics, Elsevier, vol. 44(C), pages 39-51.
    11. Lin, Boqiang & Zhu, Runqing, 2022. "How does market-oriented reform influence the rebound effect of China’s mining industry?," Economic Analysis and Policy, Elsevier, vol. 74(C), pages 34-44.
    12. Zhang, Yue-Jun & Jiang, Lin & Shi, Wei, 2020. "Exploring the growth-adjusted energy-emission efficiency of transportation industry in China," Energy Economics, Elsevier, vol. 90(C).
    13. Ouyang, Xiaoling & Chen, Jiaqi & Du, Kerui, 2021. "Energy efficiency performance of the industrial sector: From the perspective of technological gap in different regions in China," Energy, Elsevier, vol. 214(C).
    14. Xiaobo Shen & Boqiang Lin, 2017. "Total Factor Energy Efficiency of China’s Industrial Sector: A Stochastic Frontier Analysis," Sustainability, MDPI, vol. 9(4), pages 1-17, April.
    15. Holl, Adelheid & Mariotti, Ilaria, 2018. "Highways and firm performance in the logistics industry," Journal of Transport Geography, Elsevier, vol. 72(C), pages 139-150.
    16. Ying Li & Yung-Ho Chiu & Liang Chun Lu, 2018. "Regional Energy, CO 2 , and Economic and Air Quality Index Performances in China: A Meta-Frontier Approach," Energies, MDPI, vol. 11(8), pages 1-20, August.
    17. Li, Jianglong & Lin, Boqiang, 2017. "Ecological total-factor energy efficiency of China's heavy and light industries: Which performs better?," Renewable and Sustainable Energy Reviews, Elsevier, vol. 72(C), pages 83-94.
    18. Yan, Zheming & Ouyang, Xiaoling & Du, Kerui, 2019. "Economy-wide estimates of energy rebound effect: Evidence from China's provinces," Energy Economics, Elsevier, vol. 83(C), pages 389-401.
    19. Jaehn, Florian & Meissner, Finn, 2022. "The rebound effect in transportation," Omega, Elsevier, vol. 108(C).
    20. Lin, Boqiang & Du, Kerui, 2014. "Measuring energy efficiency under heterogeneous technologies using a latent class stochastic frontier approach: An application to Chinese energy economy," Energy, Elsevier, vol. 76(C), pages 884-890.

    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:jsusta:v:7:y:2015:i:7:p:9140-9159:d:52590. 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.