IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v10y2017i3p367-d93128.html
   My bibliography  Save this article

Spatial Heterogeneity of Energy-Related CO 2 Emission Growth Rates around the World and Their Determinants during 1990–2014

Author

Listed:
  • Yebing Fang

    (Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
    University of Chinese Academy of Sciences, Beijing 100049, China
    College of Territorial Resources and Tourism, Anhui Normal University, Wuhu 241003, China)

  • Limao Wang

    (Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
    University of Chinese Academy of Sciences, Beijing 100049, China)

  • Zhoupeng Ren

    (Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
    University of Chinese Academy of Sciences, Beijing 100049, China)

  • Yan Yang

    (The CAE Center for Strategic Studies, Chinese Academy of Engineering, Beijing 100088, China
    Department of Chemical Engineering, Tsinghua University, Beijing 100084, China)

  • Chufu Mou

    (Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
    University of Chinese Academy of Sciences, Beijing 100049, China)

  • Qiushi Qu

    (Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
    University of Chinese Academy of Sciences, Beijing 100049, China)

Abstract

Understanding the spatial heterogeneity and driving force identification of energy-related CO 2 emissions (ECEs) can help build consensus for mitigating CO 2 emissions and designing appropriate policies. However, previous studies on ECEs that focus on both the global-regional scale and the interaction of factors have been seldom conducted. In this paper, ECE data from 143 countries from 1990 to 2014 were selected to analyze regional differences in ECE growth rates by using the coefficient of variation. Then a geographical detector was used to analyze the key determinant factors on ECE growth rates around the world and in eight types of regions. The results show that: (1) the ECE growth rate in the Organization for Economic Cooperation and Development (OECD) region is low and tended to decrease, while in the non-OECD region it is high and tended to increase; (2) the coefficient of variation and detection factor of ECE growth rates at a regional scale are higher than those at a global scale; (3) in terms of the key determinant factors, population growth rate, growth rate of per capita GDP, and energy intensity growth rate are the three key determinant factors of ECE growth rates in the OECD region and most of the non-OECD regions such as non-OECD European and Eurasian (NO-EE), Asia (NO-AS), non-OECD Americas (NO-AM). The key determinant factors in the African (NO-AF) region are population growth rates and natural gas carbon intensity growth rates. The key determinant factors of the Middle East (NO-ME) are population growth rate, coal carbon intensity growth rate and per capita GDP growth rate; (4) the determinant power of the detection factor, the population growth rate at the global scale and regional scale is the strongest, showing a significant spatial consistency. The determinant power of per capita GDP growth rate and energy intensity growth rate in the OECD region, respectively, rank second and third, also showing a spatial consistency. However, the carbon intensity growth rates of the three fossil fuels contribute little to the growth rate of ECEs, and their spatial coherence is weak; (5) from the perspective of the interaction of detection factors, six detection factors showed bilinear or non-linear enhancement at a global and a regional scale, and the determinant power of the interaction of factors was significantly enhanced; and (6) from the perspective of ecological detection, the growth rate of carbon intensity and the growth rate of natural gas carbon intensity at the global scale and NO-ME region are significantly stronger than other factors, with a significant difference in the spatial distribution of its incidence. Therefore, the OECD region should continue to reduce the growth of energy intensity, and develop alternative energy resources in the future, while those that are plagued by carbon emissions in non-OECD regions should pay more attention to the positive influence of lower population growth rates on reducing the growth rate of energy-related CO 2 emissions. Reducing energy intensity growth rates and reducing, fossil energy consumption carbon intensity.

Suggested Citation

  • Yebing Fang & Limao Wang & Zhoupeng Ren & Yan Yang & Chufu Mou & Qiushi Qu, 2017. "Spatial Heterogeneity of Energy-Related CO 2 Emission Growth Rates around the World and Their Determinants during 1990–2014," Energies, MDPI, vol. 10(3), pages 1-17, March.
    • Handle: RePEc:gam:jeners:v:10:y:2017:i:3:p:367-:d:93128
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/10/3/367/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/10/3/367/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Bowen Xiao & Dongxiao Niu & Xiaodan Guo, 2016. "The Driving Forces of Changes in CO 2 Emissions in China: A Structural Decomposition Analysis," Energies, MDPI, vol. 9(4), pages 1-17, March.
    2. Lima, Fátima & Nunes, Manuel Lopes & Cunha, Jorge & Lucena, André F.P., 2016. "A cross-country assessment of energy-related CO2 emissions: An extended Kaya Index Decomposition Approach," Energy, Elsevier, vol. 115(P2), pages 1361-1374.
    3. Ang, B.W. & Su, Bin, 2016. "Carbon emission intensity in electricity production: A global analysis," Energy Policy, Elsevier, vol. 94(C), pages 56-63.
    4. Qi, Tianyu & Weng, Yuyan & Zhang, Xiliang & He, Jiankun, 2016. "An analysis of the driving factors of energy-related CO2 emission reduction in China from 2005 to 2013," Energy Economics, Elsevier, vol. 60(C), pages 15-22.
    5. Arvin, Mak B. & Pradhan, Rudra P. & Norman, Neville R., 2015. "Transportation intensity, urbanization, economic growth, and CO2 emissions in the G-20 countries," Utilities Policy, Elsevier, vol. 35(C), pages 50-66.
    6. Ang, B. W., 2005. "The LMDI approach to decomposition analysis: a practical guide," Energy Policy, Elsevier, vol. 33(7), pages 867-871, May.
    7. Zhang, Wei & Li, Ke & Zhou, Dequn & Zhang, Wenrui & Gao, Hui, 2016. "Decomposition of intensity of energy-related CO2 emission in Chinese provinces using the LMDI method," Energy Policy, Elsevier, vol. 92(C), pages 369-381.
    8. Kamphol Promjiraprawat & Bundit Limmeechokchai, 2012. "Assessment of Thailand’s Energy Policies and CO 2 Emissions: Analyses of Energy Efficiency Measures and Renewable Power Generation," Energies, MDPI, vol. 5(8), pages 1-20, August.
    9. Wang, Yafei & Zhao, Hongyan & Li, Liying & Liu, Zhu & Liang, Sai, 2013. "Carbon dioxide emission drivers for a typical metropolis using input–output structural decomposition analysis," Energy Policy, Elsevier, vol. 58(C), pages 312-318.
    10. Ramanathan, Ramakrishnan, 2005. "An analysis of energy consumption and carbon dioxide emissions in countries of the Middle East and North Africa," Energy, Elsevier, vol. 30(15), pages 2831-2842.
    11. Ang, B.W. & Goh, Tian, 2016. "Carbon intensity of electricity in ASEAN: Drivers, performance and outlook," Energy Policy, Elsevier, vol. 98(C), pages 170-179.
    12. Andreoni, Valeria & Galmarini, Stefano, 2016. "Drivers in CO2 emissions variation: A decomposition analysis for 33 world countries," Energy, Elsevier, vol. 103(C), pages 27-37.
    13. Xiangzheng Deng & Jianzhi Han & Fang Yin, 2012. "Net Energy, CO 2 Emission and Land-Based Cost-Benefit Analyses of Jatropha Biodiesel: A Case Study of the Panzhihua Region of Sichuan Province in China," Energies, MDPI, vol. 5(7), pages 1-15, June.
    14. Brizga, Janis & Feng, Kuishuang & Hubacek, Klaus, 2013. "Drivers of CO2 emissions in the former Soviet Union: A country level IPAT analysis from 1990 to 2010," Energy, Elsevier, vol. 59(C), pages 743-753.
    15. Feng, Kuishuang & Hubacek, Klaus & Guan, Dabo, 2009. "Lifestyles, technology and CO2 emissions in China: A regional comparative analysis," Ecological Economics, Elsevier, vol. 69(1), pages 145-154, November.
    16. Cansino, José M. & Román, Rocío & Ordóñez, Manuel, 2016. "Main drivers of changes in CO2 emissions in the Spanish economy: A structural decomposition analysis," Energy Policy, Elsevier, vol. 89(C), pages 150-159.
    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. Zhenkai Yang & Mei-Chih Wang & Tsangyao Chang & Wing-Keung Wong & Fangjhy Li, 2022. "Which Factors Determine CO 2 Emissions in China? Trade Openness, Financial Development, Coal Consumption, Economic Growth or Urbanization: Quantile Granger Causality Test," Energies, MDPI, vol. 15(7), pages 1-18, March.
    2. Sidong Zhao & Weiwei Li & Kaixu Zhao & Ping Zhang, 2021. "Change Characteristics and Multilevel Influencing Factors of Real Estate Inventory—Case Studies from 35 Key Cities in China," Land, MDPI, vol. 10(9), pages 1-29, September.

    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. Román-Collado, Rocío & Cansino, José M. & Botia, Camilo, 2018. "How far is Colombia from decoupling? Two-level decomposition analysis of energy consumption changes," Energy, Elsevier, vol. 148(C), pages 687-700.
    2. Cansino, José M. & Sánchez-Braza, Antonio & Rodríguez-Arévalo, María L., 2018. "How can Chile move away from a high carbon economy?," Energy Economics, Elsevier, vol. 69(C), pages 350-366.
    3. Fei Wang & Changjian Wang & Jing Chen & Zeng Li & Ling Li, 2020. "Examining the determinants of energy-related carbon emissions in Central Asia: country-level LMDI and EKC analysis during different phases," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 22(8), pages 7743-7769, December.
    4. Linwei Ma & Chinhao Chong & Xi Zhang & Pei Liu & Weiqi Li & Zheng Li & Weidou Ni, 2018. "LMDI Decomposition of Energy-Related CO 2 Emissions Based on Energy and CO 2 Allocation Sankey Diagrams: The Method and an Application to China," Sustainability, MDPI, vol. 10(2), pages 1-37, January.
    5. Li, Hao & Zhao, Yuhuan & Qiao, Xiaoyong & Liu, Ya & Cao, Ye & Li, Yue & Wang, Song & Zhang, Zhonghua & Zhang, Yongfeng & Weng, Jianfeng, 2017. "Identifying the driving forces of national and regional CO2 emissions in China: Based on temporal and spatial decomposition analysis models," Energy Economics, Elsevier, vol. 68(C), pages 522-538.
    6. Mine Isik & P. Ozge Kaplan, 2020. "Understanding Technology, Fuel, Market and Policy Drivers for New York State’s Power Sector Transformation," Sustainability, MDPI, vol. 13(1), pages 1-23, December.
    7. Wang, Miao & Feng, Chao, 2017. "Decomposition of energy-related CO2 emissions in China: An empirical analysis based on provincial panel data of three sectors," Applied Energy, Elsevier, vol. 190(C), pages 772-787.
    8. Zheng, Jiali & Mi, Zhifu & Coffman, D'Maris & Milcheva, Stanimira & Shan, Yuli & Guan, Dabo & Wang, Shouyang, 2019. "Regional development and carbon emissions in China," Energy Economics, Elsevier, vol. 81(C), pages 25-36.
    9. Yang, Xue & Su, Bin, 2019. "Impacts of international export on global and regional carbon intensity," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    10. Shigetomi, Yosuke & Matsumoto, Ken'ichi & Ogawa, Yuki & Shiraki, Hiroto & Yamamoto, Yuki & Ochi, Yuki & Ehara, Tomoki, 2018. "Driving forces underlying sub-national carbon dioxide emissions within the household sector and implications for the Paris Agreement targets in Japan," Applied Energy, Elsevier, vol. 228(C), pages 2321-2332.
    11. Jia, Hongxiang & Li, Tianjiao & Wang, Anjian & Liu, Guwang & Guo, Xiaoqian, 2021. "Decoupling analysis of economic growth and mineral resources consumption in China from 1992 to 2017: A comparison between tonnage and exergy perspective," Resources Policy, Elsevier, vol. 74(C).
    12. Wang, Miao & Feng, Chao, 2018. "Decomposing the change in energy consumption in China's nonferrous metal industry: An empirical analysis based on the LMDI method," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 2652-2663.
    13. Henriques, Sofia Teives & Borowiecki, Karol J., 2017. "The drivers of long-run CO2 emissions in Europe, North America and Japan since 1800," Energy Policy, Elsevier, vol. 101(C), pages 537-549.
    14. Wang, Junfeng & He, Shutong & Qiu, Ye & Liu, Nan & Li, Yongjian & Dong, Zhanfeng, 2018. "Investigating driving forces of aggregate carbon intensity of electricity generation in China," Energy Policy, Elsevier, vol. 113(C), pages 249-257.
    15. Lu, Guanyu & Sugino, Makoto & Arimura, Toshi H. & Horie, Tetsuya, 2022. "Success and failure of the voluntary action plan: Disaggregated sector decomposition analysis of energy-related CO2 emissions in Japan," Energy Policy, Elsevier, vol. 163(C).
    16. Perry Sadorsky, 2020. "Energy Related CO 2 Emissions before and after the Financial Crisis," Sustainability, MDPI, vol. 12(9), pages 1-22, May.
    17. Jaruwan Chontanawat & Paitoon Wiboonchutikula & Atinat Buddhivanich, 2020. "Decomposition Analysis of the Carbon Emissions of the Manufacturing and Industrial Sector in Thailand," Energies, MDPI, vol. 13(4), pages 1-23, February.
    18. Wen, Hong-xing & Chen, Zhe & Yang, Qian & Liu, Jin-yi & Nie, Pu-yan, 2022. "Driving forces and mitigating strategies of CO2 emissions in China: A decomposition analysis based on 38 industrial sub-sectors," Energy, Elsevier, vol. 245(C).
    19. Zbigniew Golas, 2021. "Energy-Related Greenhouse Gas Emissions in Poland from 2000 to 2018: An LMDI Decomposition Analysis Perspective," European Research Studies Journal, European Research Studies Journal, vol. 0(2), pages 1243-1257.
    20. Juan David Rivera-Niquepa & Daniela Rojas-Lozano & Paulo M. De Oliveira-De Jesus & Jose M. Yusta, 2022. "Decomposition Analysis of the Aggregate Carbon Intensity (ACI) of the Power Sector in Colombia—A Multi-Temporal Analysis," Sustainability, MDPI, vol. 14(20), pages 1-18, October.

    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:10:y:2017:i:3:p:367-:d:93128. 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.