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System dynamics prediction and development path optimization of regional carbon emissions: A case study of Tianjin

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  • Li, Guohao
  • Chen, Xue
  • You, Xue-yi

Abstract

The prediction of regional carbon emissions and the optimization of development paths are particularly important. Regional heterogeneity leads to different links between carbon emissions and population, economy, industry, energy, environment, and other factors. However, most of the previous studies carried out the accounting, factor decomposition, prediction, and decision-making of regional carbon emissions alone, which failed to form the sustainable assessment of regional carbon emissions. Therefore, the carbon emissions coefficient, Logarithmic Mean Divisia Index, system dynamics model and Interlink Decision Making Index were selected in this study to establish the regional carbon emissions systems framework. In this study, a mega-city such as Tianjin was taken as an example, the comprehensive assessment and prediction of regional carbon emissions system was carried out. The results show the change in energy intensity had the strongest mitigation effect, reducing carbon emissions by 106.17 million tons in total, and the per capita GDP effect had the strongest promotion effect, with a cumulative contribution of 265.19 million tons of carbon emissions. Among all 13 scenarios in Tianjin, Scenario-12 is identified as the optimal development path and provides policy suggestions. The results of this study not only verify the effectiveness and necessity of the framework, but also provide guidance tools for regional carbon emissions development. The results of this study validate the effectiveness and necessity of the framework to provide guidance for the regional carbon emissions development path. The results of the case also provide help for the optimization of Tianjin's carbon emissions development path.

Suggested Citation

  • Li, Guohao & Chen, Xue & You, Xue-yi, 2023. "System dynamics prediction and development path optimization of regional carbon emissions: A case study of Tianjin," Renewable and Sustainable Energy Reviews, Elsevier, vol. 184(C).
    • Handle: RePEc:eee:rensus:v:184:y:2023:i:c:s1364032123004367
    DOI: 10.1016/j.rser.2023.113579
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    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. Dinga, Christian Doh & Wen, Zongguo, 2022. "China's green deal: Can China's cement industry achieve carbon neutral emissions by 2060?," Renewable and Sustainable Energy Reviews, Elsevier, vol. 155(C).
    3. Robert G. King & Ross Levine, 1993. "Finance and Growth: Schumpeter Might Be Right," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 108(3), pages 717-737.
    4. Zhifu Mi & Jing Meng & Dabo Guan & Yuli Shan & Malin Song & Yi-Ming Wei & Zhu Liu & Klaus Hubacek, 2017. "Chinese CO2 emission flows have reversed since the global financial crisis," Nature Communications, Nature, vol. 8(1), pages 1-10, December.
    5. Kohli, Ulrich, 2004. "Real GDP, real domestic income, and terms-of-trade changes," Journal of International Economics, Elsevier, vol. 62(1), pages 83-106, January.
    6. Wang, Zhaojing & Jiang, Qingzhe & Dong, Kangyin & Mubarik, Muhammad Shujaat & Dong, Xiucheng, 2020. "Decomposition of the US CO2 emissions and its mitigation potential: An aggregate and sectoral analysis," Energy Policy, Elsevier, vol. 147(C).
    7. Feng, Y.Y. & Chen, S.Q. & Zhang, L.X., 2013. "System dynamics modeling for urban energy consumption and CO2 emissions: A case study of Beijing, China," Ecological Modelling, Elsevier, vol. 252(C), pages 44-52.
    8. Ang, B. W., 2005. "The LMDI approach to decomposition analysis: a practical guide," Energy Policy, Elsevier, vol. 33(7), pages 867-871, May.
    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. Li, Dezhi & Huang, Guanying & Zhu, Shiyao & Chen, Long & Wang, Jiangbo, 2021. "How to peak carbon emissions of provincial construction industry? Scenario analysis of Jiangsu Province," Renewable and Sustainable Energy Reviews, Elsevier, vol. 144(C).
    11. Xu, Guangyue & Schwarz, Peter & Yang, Hualiu, 2020. "Adjusting energy consumption structure to achieve China's CO2 emissions peak," Renewable and Sustainable Energy Reviews, Elsevier, vol. 122(C).
    12. Stephen Crooks & Ariana E. Sutton-Grier & Tiffany G. Troxler & Nathaniel Herold & Blanca Bernal & Lisa Schile-Beers & Tom Wirth, 2018. "Coastal wetland management as a contribution to the US National Greenhouse Gas Inventory," Nature Climate Change, Nature, vol. 8(12), pages 1109-1112, December.
    13. Ruijing Zheng & Yu Cheng & Haimeng Liu & Wei Chen & Xiaodong Chen & Yaping Wang, 2022. "The Spatiotemporal Distribution and Drivers of Urban Carbon Emission Efficiency: The Role of Technological Innovation," IJERPH, MDPI, vol. 19(15), pages 1-22, July.
    14. Shi, Huiting & Chai, Jian & Lu, Quanying & Zheng, Jiali & Wang, Shouyang, 2022. "The impact of China's low-carbon transition on economy, society and energy in 2030 based on CO2 emissions drivers," Energy, Elsevier, vol. 239(PD).
    15. Khanali, Majid & Ghasemi-Mobtaker, Hassan & Varmazyar, Hossein & Mohammadkashi, Naghmeh & Chau, Kwok-wing & Nabavi-Pelesaraei, Ashkan, 2022. "Applying novel eco-exergoenvironmental toxicity index to select the best irrigation system of sunflower production," Energy, Elsevier, vol. 250(C).
    16. Decai Tang & Tingyu Ma & Zhijiang Li & Jiexin Tang & Brandon J. Bethel, 2016. "Trend Prediction and Decomposed Driving Factors of Carbon Emissions in Jiangsu Province during 2015–2020," Sustainability, MDPI, vol. 8(10), pages 1-15, October.
    17. Sen, Parag & Roy, Mousumi & Pal, Parimal, 2016. "Application of ARIMA for forecasting energy consumption and GHG emission: A case study of an Indian pig iron manufacturing organization," Energy, Elsevier, vol. 116(P1), pages 1031-1038.
    18. Meng, Ming & Niu, Dongxiao, 2011. "Modeling CO2 emissions from fossil fuel combustion using the logistic equation," Energy, Elsevier, vol. 36(5), pages 3355-3359.
    19. Dong, Feng & Li, Xiaohui & Long, Ruyin & Liu, Xiaoyan, 2013. "Regional carbon emission performance in China according to a stochastic frontier model," Renewable and Sustainable Energy Reviews, Elsevier, vol. 28(C), pages 525-530.
    20. Pohekar, S. D. & Ramachandran, M., 2004. "Application of multi-criteria decision making to sustainable energy planning--A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 8(4), pages 365-381, August.
    21. Koo, Choongwan & Hong, Taehoon & Kim, Jimin & Kim, Hyunjoong, 2015. "An integrated multi-objective optimization model for establishing the low-carbon scenario 2020 to achieve the national carbon emissions reduction target for residential buildings," Renewable and Sustainable Energy Reviews, Elsevier, vol. 49(C), pages 410-425.
    22. Ye, Bin & Jiang, JingJing & Li, Changsheng & Miao, Lixin & Tang, Jie, 2017. "Quantification and driving force analysis of provincial-level carbon emissions in China," Applied Energy, Elsevier, vol. 198(C), pages 223-238.
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