IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i7p4052-d782323.html
   My bibliography  Save this article

Dynamic Evolution and Regional Disparity in Carbon Emission Intensity in China

Author

Listed:
  • Meng Yang

    (School of Economics and Management, Beijing Jiaotong University, No. 3 Shangyuancun, Haidian District, Beijing 100044, China)

  • Yisheng Liu

    (School of Economics and Management, Beijing Jiaotong University, No. 3 Shangyuancun, Haidian District, Beijing 100044, China)

  • Jinzhao Tian

    (School of Economics and Management, Beijing Jiaotong University, No. 3 Shangyuancun, Haidian District, Beijing 100044, China)

  • Feiyu Cheng

    (School of Economics and Management, Beijing Jiaotong University, No. 3 Shangyuancun, Haidian District, Beijing 100044, China)

  • Pengbo Song

    (School of Economics and Management, Beijing Jiaotong University, No. 3 Shangyuancun, Haidian District, Beijing 100044, China)

Abstract

China’s carbon reductions are of great significance to the realization of global temperature control targets. Carbon emission intensity (CEI) represents the degree of coordination between emissions and economic development to some extent. Nevertheless, there is a paucity of research on its spatial–temporal evolution and regional differences. To fill the gap, this study exploits the Theil index to shed light on the characteristics of its spatial–temporal distribution and regional disparities in China during the period of 2000–2019, and constructs a multi-regional spatial index decomposition model to analyze the differences in its drivers. The results indicate that the decreasing CEI during the period of 2000–2019 shows a distinctive imbalance in spatial–temporal distribution. The gap between north and south is greater than that between east and west. The expansion of the Theil index based on CEI reveals a widening tendency of the mismatch between emissions and economic development among provinces. CEI disparity is mainly due to growing intraregional differences. For most provinces, the energy intensity effect is the essential driver of spatial differences regarding CEI, with the energy structure and the industrial structure effects gradually changing from promoting to inhibiting effects. The carbon emission factor effect has no significant fluctuation, but regional differences are distinct.

Suggested Citation

  • Meng Yang & Yisheng Liu & Jinzhao Tian & Feiyu Cheng & Pengbo Song, 2022. "Dynamic Evolution and Regional Disparity in Carbon Emission Intensity in China," Sustainability, MDPI, vol. 14(7), pages 1-15, March.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:7:p:4052-:d:782323
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/7/4052/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/14/7/4052/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Fang, Kai & Tang, Yiqi & Zhang, Qifeng & Song, Junnian & Wen, Qi & Sun, Huaping & Ji, Chenyang & Xu, Anqi, 2019. "Will China peak its energy-related carbon emissions by 2030? Lessons from 30 Chinese provinces," Applied Energy, Elsevier, vol. 255(C).
    2. Bianco, Vincenzo & Cascetta, Furio & Marino, Alfonso & Nardini, Sergio, 2019. "Understanding energy consumption and carbon emissions in Europe: A focus on inequality issues," Energy, Elsevier, vol. 170(C), pages 120-130.
    3. Liu, Xianmei & Peng, Rui & Zhong, Chao & Wang, Mingyue & Guo, Pibin, 2021. "What drives the temporal and spatial differences of CO2 emissions in the transport sector? Empirical evidence from municipalities in China," Energy Policy, Elsevier, vol. 159(C).
    4. Su, Bin & Ang, B.W., 2017. "Multiplicative structural decomposition analysis of aggregate embodied energy and emission intensities," Energy Economics, Elsevier, vol. 65(C), pages 137-147.
    5. Liu, Nan & Ma, Zujun & Kang, Jidong & Su, Bin, 2019. "A multi-region multi-sector decomposition and attribution analysis of aggregate carbon intensity in China from 2000 to 2015," Energy Policy, Elsevier, vol. 129(C), pages 410-421.
    6. Wang, H. & Ang, B.W. & Su, Bin, 2017. "A Multi-region Structural Decomposition Analysis of Global CO2 Emission Intensity," Ecological Economics, Elsevier, vol. 142(C), pages 163-176.
    7. Ang, B.W. & Xu, X.Y. & Su, Bin, 2015. "Multi-country comparisons of energy performance: The index decomposition analysis approach," Energy Economics, Elsevier, vol. 47(C), pages 68-76.
    8. Chen, Jiandong & Xu, Chong & Cui, Lianbiao & Huang, Shuo & Song, Malin, 2019. "Driving factors of CO2 emissions and inequality characteristics in China: A combined decomposition approach," Energy Economics, Elsevier, vol. 78(C), pages 589-597.
    9. Pan, Xiongfeng & Guo, Shucen & Xu, Haitao & Tian, Mengyuan & Pan, Xianyou & Chu, Junhui, 2022. "China's carbon intensity factor decomposition and carbon emission decoupling analysis," Energy, Elsevier, vol. 239(PC).
    10. Wang, Zhaohua & Zhang, Bin & Liu, Tongfan, 2016. "Empirical analysis on the factors influencing national and regional carbon intensity in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 55(C), pages 34-42.
    11. Yang, Lin & Yang, Yuantao & Zhang, Xian & Tang, Kai, 2018. "Whether China's industrial sectors make efforts to reduce CO2 emissions from production? - A decomposed decoupling analysis," Energy, Elsevier, vol. 160(C), pages 796-809.
    12. Xiao, Hao & Sun, Ke-Juan & Bi, Hui-Min & Xue, Jin-Jun, 2019. "Changes in carbon intensity globally and in countries: Attribution and decomposition analysis," Applied Energy, Elsevier, vol. 235(C), pages 1492-1504.
    13. 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.
    14. Wang, Shaojian & Wang, Jieyu & Fang, Chuanglin & Feng, Kuishuang, 2019. "Inequalities in carbon intensity in China: A multi-scalar and multi-mechanism analysis," Applied Energy, Elsevier, vol. 254(C).
    15. Qiu, Shuo & Lei, Tian & Wu, Jiangtao & Bi, Shengshan, 2021. "Energy demand and supply planning of China through 2060," Energy, Elsevier, vol. 234(C).
    16. Liu, Jiaguo & Li, Sujuan & Ji, Qiang, 2021. "Regional differences and driving factors analysis of carbon emission intensity from transport sector in China," Energy, Elsevier, vol. 224(C).
    17. Grunewald, Nicole & Jakob, Michael & Mouratiadou, Ioanna, 2014. "Decomposing inequality in CO2 emissions: The role of primary energy carriers and economic sectors," Ecological Economics, Elsevier, vol. 100(C), pages 183-194.
    18. Wang, H. & Zhou, P., 2018. "Assessing Global CO2 Emission Inequality From Consumption Perspective: An Index Decomposition Analysis," Ecological Economics, Elsevier, vol. 154(C), pages 257-271.
    19. Yang, Chuxiao & Hao, Yu & Irfan, Muhammad, 2021. "Energy consumption structural adjustment and carbon neutrality in the post-COVID-19 era," Structural Change and Economic Dynamics, Elsevier, vol. 59(C), pages 442-453.
    20. Wu, Feng & Huang, Ningyu & Zhang, Qian & Qiao, Zhi & Zhan, Ni-ni, 2020. "Multi-province comparison and typology of China’s CO2 emission: A spatial–temporal decomposition approach," Energy, Elsevier, vol. 190(C).
    21. Mussini, Mauro & Grossi, Luigi, 2015. "Decomposing changes in CO2 emission inequality over time: The roles of re-ranking and changes in per capita CO2 emission disparities," Energy Economics, Elsevier, vol. 49(C), pages 274-281.
    22. Wang, H. & Ang, B.W. & Su, Bin, 2017. "Assessing drivers of economy-wide energy use and emissions: IDA versus SDA," Energy Policy, Elsevier, vol. 107(C), pages 585-599.
    23. Fang, Kai & Li, Chenglin & Tang, Yiqi & He, Jianjian & Song, Junnian, 2022. "China’s pathways to peak carbon emissions: New insights from various industrial sectors," Applied Energy, Elsevier, vol. 306(PA).
    24. Yang, Yi & Yuan, Zhuqing & Yang, Shengnan, 2022. "Difference in the drivers of industrial carbon emission costs determines the diverse policies in middle-income regions: A case of northwestern China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 155(C).
    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. Hui Wen & Yi Li & Zirong Li & Xiaoxue Cai & Fengxia Wang, 2022. "Spatial Differentiation of Carbon Budgets and Carbon Balance Zoning in China Based on the Land Use Perspective," Sustainability, MDPI, vol. 14(20), pages 1-20, October.
    2. Jia Wei & Wei Shi & Jingrou Ran & Jing Pu & Jiyang Li & Kai Wang, 2023. "Exploring the Driving Factors and Their Spatial Effects on Carbon Emissions in the Building Sector," Energies, MDPI, vol. 16(7), pages 1-21, March.
    3. Mirosława Szewczyk & Anna Szeliga-Duchnowska, 2022. "Make Hay While the Sun Shines: Beneficiaries of Renewable Energy Promotion," Energies, MDPI, vol. 15(9), pages 1-15, May.
    4. Qing Yang & Nianping Li, 2022. "Subjective and Objective Evaluation of Shading on Thermal, Visual, and Acoustic Properties of Indoor Environments," Sustainability, MDPI, vol. 14(18), pages 1-17, 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. Yang, Xue & Su, Bin, 2019. "Impacts of international export on global and regional carbon intensity," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    2. Xiaolei Liu & Heng Chen & Cheng Peng & Mingqiu Li, 2022. "Assessing the Drivers of Carbon Intensity Change in China: A Dynamic Spatial–Temporal Production-Theoretical Decomposition Analysis Approach," Sustainability, MDPI, vol. 14(19), pages 1-18, September.
    3. Li, Aijun & Zhou, Dinglin & Chen, Guoshi & Liu, Yuhao & Long, Yan, 2020. "Multi-region comparisons of energy-related CO2 emissions and production water use during energy development in northwestern China," Renewable Energy, Elsevier, vol. 153(C), pages 940-961.
    4. Yan, Junna & Su, Bin, 2020. "Spatial differences in energy performance among four municipalities of China: From both the aggregate and final demand perspectives," Energy, Elsevier, vol. 204(C).
    5. Zhang, Chi & Su, Bin & Zhou, Kaile & Sun, Yuan, 2020. "A multi-dimensional analysis on microeconomic factors of China's industrial energy intensity (2000–2017)," Energy Policy, Elsevier, vol. 147(C).
    6. Zhu, Bangzhu & Su, Bin & Li, Yingzhu & Ng, Tsan Sheng, 2020. "Embodied energy and intensity in China’s (normal and processing) exports and their driving forces, 2005-2015," Energy Economics, Elsevier, vol. 91(C).
    7. Liu, Yisheng & Yang, Meng & Cheng, Feiyu & Tian, Jinzhao & Du, Zhuoqun & Song, Pengbo, 2022. "Analysis of regional differences and decomposition of carbon emissions in China based on generalized divisia index method," Energy, Elsevier, vol. 256(C).
    8. Wang, Zhenguo & Su, Bin & Xie, Rui & Long, Haiyu, 2020. "China’s aggregate embodied CO2 emission intensity from 2007 to 2012: A multi-region multiplicative structural decomposition analysis," Energy Economics, Elsevier, vol. 85(C).
    9. Wang, Hui & Li, Rupeng & Zhang, Ning & Zhou, Peng & Wang, Qiang, 2020. "Assessing the role of technology in global manufacturing energy intensity change: A production-theoretical decomposition analysis," Technological Forecasting and Social Change, Elsevier, vol. 160(C).
    10. Duan, Yuwan & Yan, Bingqian, 2021. "Has processing trade made China's exports cleaner? A regional level analysis," Energy Economics, Elsevier, vol. 96(C).
    11. Su, Bin & Ang, B.W. & Li, Yingzhu, 2019. "Structural path and decomposition analysis of aggregate embodied energy and emission intensities," Energy Economics, Elsevier, vol. 83(C), pages 345-360.
    12. Bingquan Liu & Yue Wang & Xuran Chang & Boyang Nie & Lingqi Meng & Yongqing Li, 2022. "Does Land Urbanization Affect the Catch-Up Effect of Carbon Emissions Reduction in China’s Logistics?," Land, MDPI, vol. 11(9), pages 1-18, September.
    13. Wang, H. & Zhou, P., 2018. "Assessing Global CO2 Emission Inequality From Consumption Perspective: An Index Decomposition Analysis," Ecological Economics, Elsevier, vol. 154(C), pages 257-271.
    14. Chen, Huadun & Du, Qianxi & Huo, Tengfei & Liu, Peiran & Cai, Weiguang & Liu, Bingsheng, 2023. "Spatiotemporal patterns and driving mechanism of carbon emissions in China's urban residential building sector," Energy, Elsevier, vol. 263(PE).
    15. Wanbei Jiang & Weidong Liu, 2020. "Provincial-Level CO 2 Emissions Intensity Inequality in China: Regional Source and Explanatory Factors of Interregional and Intraregional Inequalities," Sustainability, MDPI, vol. 12(6), pages 1-16, March.
    16. Tian, Kailan & Dietzenbacher, Erik & Yan, Bingqian & Duan, Yuwan, 2020. "Upgrading or downgrading: China's regional carbon emission intensity evolution and its determinants," Energy Economics, Elsevier, vol. 91(C).
    17. Su, Bin & Ang, B.W., 2020. "Demand contributors and driving factors of Singapore’s aggregate carbon intensities," Energy Policy, Elsevier, vol. 146(C).
    18. Zhu, Bangzhu & Su, Bin & Li, Yingzhu, 2018. "Input-output and structural decomposition analysis of India’s carbon emissions and intensity, 2007/08 – 2013/14," Applied Energy, Elsevier, vol. 230(C), pages 1545-1556.
    19. Li, Rongrong & Han, Xinyu & Wang, Qiang, 2023. "Do technical differences lead to a widening gap in China's regional carbon emissions efficiency? Evidence from a combination of LMDI and PDA approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 182(C).
    20. Fan, Wei & Li, Li & Wang, Feiran & Li, Ding, 2020. "Driving factors of CO2 emission inequality in China: The role of government expenditure," China Economic Review, Elsevier, vol. 64(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:jsusta:v:14:y:2022:i:7:p:4052-:d:782323. 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.