IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i15p9624-d880670.html
   My bibliography  Save this article

Towards Sustainable Development: A Study of Cross-Regional Collaborative Carbon Emission Reduction in China

Author

Listed:
  • Xiumei Sun

    (Business School, Shandong University of Technology, Zibo 255000, China)

  • Haotian Zhang

    (Business School, Shandong University of Technology, Zibo 255000, China)

  • Xueyang Wang

    (Business School, Shandong University of Technology, Zibo 255000, China)

  • Zhongkui Qiao

    (YanTai Gold College, Yantai 265401, China)

  • Jinsong Li

    (Business School, Shandong University of Technology, Zibo 255000, China)

Abstract

Exploring a scientific and reasonable cross-regional carbon emission reduction path in China is essential to achieving sustainable development and the carbon neutrality target. This study constructs a simulation model of China’s cross-regional carbon emission reduction ( CER ) system and adopts a multi-agent approach to simulate cross-regional CER scenarios to predict the pathway. The conclusions are as follows: (1) under the national unified CER policy scenarios, carbon emissions are on a continuous growth trend with fast economic growth not matching emission reduction efforts in Scenario I. Scenario II has a lower economic scale, and carbon emissions peak in 2029. Scenario III has smooth economy and reaches the carbon emission peak in 2026. The economy of Scenario IV grows fast, carbon emissions grow slowly, and the peak does not appear in 2030. (2) In three scenarios with provinces as the main agent for CER , if provinces sacrifice the economy to strengthen CER , the peak of carbon emissions will appear in 2020. While the economy of non-synergistic and synergistic CER scenarios in each province is growing steadily, the peak in two modes is reached in 2026 and 2032. The peak is reached four years earlier in 2026 in the synergistic model and 2032 in the non-synergistic model, and the economic growth of some energy-intensive provinces slows down. (3) The synergistic low-carbon model is best for balancing economic development and carbon emission control. Policy recommendations are presented based on the above findings for China’s CER and sustainable development.

Suggested Citation

  • Xiumei Sun & Haotian Zhang & Xueyang Wang & Zhongkui Qiao & Jinsong Li, 2022. "Towards Sustainable Development: A Study of Cross-Regional Collaborative Carbon Emission Reduction in China," Sustainability, MDPI, vol. 14(15), pages 1-21, August.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:15:p:9624-:d:880670
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/15/9624/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/14/15/9624/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Yao, Shiyue & Yu, Xueying & Yan, Sen & Wen, Shiyan, 2021. "Heterogeneous emission trading schemes and green innovation," Energy Policy, Elsevier, vol. 155(C).
    2. Mahmood, Ahmad & Zahoor, Ahmed & Xiyue, Yang & Nazim, Hussain & Sinha, Avik, 2021. "Financial development and environmental degradation: Do human capital and institutional quality make a difference?," MPRA Paper 110039, University Library of Munich, Germany, revised 2021.
    3. Xiaohui Yu & Sai Ma & Kang Cheng & Grigorios L. Kyriakopoulos, 2020. "An Evaluation System for Sustainable Urban Space Development Based in Green Urbanism Principles—A Case Study Based on the Qin-Ba Mountain Area in China," Sustainability, MDPI, vol. 12(14), pages 1-22, July.
    4. Shahbaz, Muhammad & Li, Jiaman & Dong, Xiucheng & Dong, Kangyin, 2022. "How financial inclusion affects the collaborative reduction of pollutant and carbon emissions: The case of China," Energy Economics, Elsevier, vol. 107(C).
    5. Xu, Haitao & Pan, Xiongfeng & Guo, Shucen & Lu, Yuduo, 2021. "Forecasting Chinese CO2 emission using a non-linear multi-agent intertemporal optimization model and scenario analysis," Energy, Elsevier, vol. 228(C).
    6. Yu, Song-min & Fan, Ying & Zhu, Lei & Eichhammer, Wolfgang, 2020. "Modeling the emission trading scheme from an agent-based perspective: System dynamics emerging from firms’ coordination among abatement options," European Journal of Operational Research, Elsevier, vol. 286(3), pages 1113-1128.
    7. Xiaohang Ren & Cheng Cheng & Zhen Wang & Cheng Yan, 2021. "Spillover and dynamic effects of energy transition and economic growth on carbon dioxide emissions for the European Union: A dynamic spatial panel model," Sustainable Development, John Wiley & Sons, Ltd., vol. 29(1), pages 228-242, January.
    8. Tang, Ling & Wu, Jiaqian & Yu, Lean & Bao, Qin, 2015. "Carbon emissions trading scheme exploration in China: A multi-agent-based model," Energy Policy, Elsevier, vol. 81(C), pages 152-169.
    9. Xiaofei Han & Jianling Jiao & Lancui Liu & Lanlan Li, 2017. "China’s energy demand and carbon dioxide emissions: do carbon emission reduction paths matter?," 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. 86(3), pages 1333-1345, April.
    10. Zhang, Yue-Jun & Peng, Yu-Lu & Ma, Chao-Qun & Shen, Bo, 2017. "Can environmental innovation facilitate carbon emissions reduction? Evidence from China," Energy Policy, Elsevier, vol. 100(C), pages 18-28.
    11. Jia, Zhijie & Lin, Boqiang, 2020. "Rethinking the choice of carbon tax and carbon trading in China," Technological Forecasting and Social Change, Elsevier, vol. 159(C).
    12. Huang, Junbing & Chen, Xiang & Cai, Xiaochen & Zou, Hong, 2021. "Assessing the impact of energy-saving R&D on China’s energy consumption: Evidence from dynamic spatial panel model," Energy, Elsevier, vol. 218(C).
    13. Zakeri, Atefe & Dehghanian, Farzad & Fahimnia, Behnam & Sarkis, Joseph, 2015. "Carbon pricing versus emissions trading: A supply chain planning perspective," International Journal of Production Economics, Elsevier, vol. 164(C), pages 197-205.
    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. Tang, Ling & Wang, Haohan & Li, Ling & Yang, Kaitong & Mi, Zhifu, 2020. "Quantitative models in emission trading system research: A literature review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 132(C).
    2. Xiaoqi Li & Dingfei Guo & Chao Feng, 2022. "The Carbon Emissions Trading Policy of China: Does It Really Promote the Enterprises’ Green Technology Innovations?," IJERPH, MDPI, vol. 19(21), pages 1-15, November.
    3. Li, Jiaman & Dong, Xiucheng & Dong, Kangyin, 2022. "How much does financial inclusion contribute to renewable energy growth? Ways to realize green finance in China," Renewable Energy, Elsevier, vol. 198(C), pages 760-771.
    4. Maxwell Chukwudi Udeagha & Nicholas Ngepah, 2022. "Dynamic ARDL Simulations Effects of Fiscal Decentralization, Green Technological Innovation, Trade Openness, and Institutional Quality on Environmental Sustainability: Evidence from South Africa," Sustainability, MDPI, vol. 14(16), pages 1-35, August.
    5. Yan, Kai & Zhang, Wei & Shen, Dehua, 2020. "Stylized facts of the carbon emission market in China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 555(C).
    6. Wei, Yigang & Liang, Xin & Xu, Liang & Kou, Gang & Chevallier, Julien, 2023. "Trading, storage, or penalty? Uncovering firms' decision-making behavior in the Shanghai emissions trading scheme: Insights from agent-based modeling," Energy Economics, Elsevier, vol. 117(C).
    7. Afshan, Sahar & Ozturk, Ilhan & Yaqoob, Tanzeela, 2022. "Facilitating renewable energy transition, ecological innovations and stringent environmental policies to improve ecological sustainability: Evidence from MM-QR method," Renewable Energy, Elsevier, vol. 196(C), pages 151-160.
    8. Yue‐Jun Zhang & Wei Shi & Lin Jiang, 2020. "Does China's carbon emissions trading policy improve the technology innovation of relevant enterprises?," Business Strategy and the Environment, Wiley Blackwell, vol. 29(3), pages 872-885, March.
    9. Yu, Xianyu & Hu, Yuezhi & Zhou, Dequn & Wang, Qunwei & Sang, Xiuzhi & Huang, Kai, 2023. "Carbon emission reduction analysis for cloud computing industry: Can carbon emissions trading and technology innovation help?," Energy Economics, Elsevier, vol. 125(C).
    10. Zhang, Yue-Jun & Wang, Wei, 2021. "How does China's carbon emissions trading (CET) policy affect the investment of CET-covered enterprises?," Energy Economics, Elsevier, vol. 98(C).
    11. Wang, Bo & Zhao, Jun & Dong, Kangyin & Jiang, Qingzhe, 2022. "High-quality energy development in China: Comprehensive assessment and its impact on CO2 emissions," Energy Economics, Elsevier, vol. 110(C).
    12. Foramitti, Joël & Savin, Ivan & van den Bergh, Jeroen C.J.M., 2021. "Emission tax vs. permit trading under bounded rationality and dynamic markets," Energy Policy, Elsevier, vol. 148(PB).
    13. Ma, Guangcheng & Qin, Jiahong & Zhang, Yumeng, 2023. "Does the carbon emissions trading system reduce carbon emissions by promoting two-way FDI in developing countries? Evidence from Chinese listed companies and cities," Energy Economics, Elsevier, vol. 120(C).
    14. Lin, Boqiang & Wesseh, Presley K., 2020. "On the economics of carbon pricing: Insights from econometric modeling with industry-level data," Energy Economics, Elsevier, vol. 86(C).
    15. Wu, Jie & Fan, Ying & Timilsina, Govinda & Xia, Yan, 2022. "Exploiting Complementarity of Carbon Pricing Instruments for Low-Carbon Development in the People’s Republic of China," ADBI Working Papers 1329, Asian Development Bank Institute.
    16. Shuang Liang & Xinyue Lin & Xiaoxue Liu & Haoran Pan, 2022. "The Pathway to China’s Carbon Neutrality Based on an Endogenous Technology CGE Model," IJERPH, MDPI, vol. 19(10), pages 1-22, May.
    17. Limin Su & Yongchao Cao & Wenjuan Zhang, 2023. "Low-Carbon Supply Chain Operation Decisions and Coordination Strategies Considering the Consumers’ Preferences," Sustainability, MDPI, vol. 15(14), pages 1-20, July.
    18. Qiuyue Xia & Lu Li & Jie Dong & Bin Zhang, 2021. "Reduction Effect and Mechanism Analysis of Carbon Trading Policy on Carbon Emissions from Land Use," Sustainability, MDPI, vol. 13(17), pages 1-22, August.
    19. Hongpeng Guo & Zhihao Lv & Junyi Hua & Hongxu Yuan & Qingyu Yu, 2021. "Design of Combined Auction Model for Emission Rights of International Forestry Carbon Sequestration and Other Pollutants Based on SMRA," Sustainability, MDPI, vol. 13(20), pages 1-18, October.
    20. Liu, Yu & Tan, Xiu-Jie & Yu, Yang & Qi, Shao-Zhou, 2017. "Assessment of impacts of Hubei Pilot emission trading schemes in China – A CGE-analysis using TermCO2 model," Applied Energy, Elsevier, vol. 189(C), pages 762-769.

    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:15:p:9624-:d:880670. 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.