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How to peak carbon emissions of provincial construction industry? Scenario analysis of Jiangsu Province

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  • Li, Dezhi
  • Huang, Guanying
  • Zhu, Shiyao
  • Chen, Long
  • Wang, Jiangbo

Abstract

China has become the world's largest carbon emitter, and its commitment to peak carbon emissions by 2030 is important for global development. The construction industry is one of China's biggest carbon emitters, and its peak has a direct impact on China's carbon commitment. Due to the regional heterogeneity of different provinces, the carbon emission of construction industry (CECI) at provincial level is of unique significance. To accurately predict the peak of provincial CECI, a prediction model was established by system dynamics, including direct CECI, indirect CECI and operational CECI. Taking Jiangsu province as an example, the single and multiple scenario settings with increasing R&D investment, promoting energy-saving buildings and implementing carbon trading from 2016 to 2030 was carried out, indicating that: 1) Without any carbon emission reduction measures, the CECI would maintain an annual growth rate of 5.58% to reach 530.61 million tons by 2030, and the indirect and operational CECI account for the majority of total with an average annual growth rate of 8.02% and 2.79% respectively. 2) All three measures had good carbon reduction effects, which would reduce the total CECI by 26.46% 21.68% and 10.68% respectively by 2030, but only when implemented simultaneously can CECI peak before 2030, 308.77 million tons at 2029. In the end, three policy implications was put forward. The framework presented in this paper provided a basis for the prediction of peak CECI in a province or state, which can help policy makers plan a more reasonable low-carbon development roadmap.

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  • 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).
    • Handle: RePEc:eee:rensus:v:144:y:2021:i:c:s1364032121002458
    DOI: 10.1016/j.rser.2021.110953
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    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. Chang, Chia-Lin & Mai, Te-Ke & McAleer, Michael, 2019. "Establishing national carbon emission prices for China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 106(C), pages 1-16.
    3. Tol, Richard S.J., 2019. "A social cost of carbon for (almost) every country," Energy Economics, Elsevier, vol. 83(C), pages 555-566.
    4. Lu, Mengxue & Lai, Joseph, 2020. "Review on carbon emissions of commercial buildings," Renewable and Sustainable Energy Reviews, Elsevier, vol. 119(C).
    5. Wang, Ke & Yang, Kexin & Wei, Yi-Ming & Zhang, Chi, 2018. "Shadow prices of direct and overall carbon emissions in China’s construction industry: A parametric directional distance function-based sensitive estimation," Structural Change and Economic Dynamics, Elsevier, vol. 47(C), pages 180-193.
    6. Cheng, Yung-Hsiang & Chang, Yu-Hern & Lu, I.J., 2015. "Urban transportation energy and carbon dioxide emission reduction strategies," Applied Energy, Elsevier, vol. 157(C), pages 953-973.
    7. Xingang Zhao & Yuzhuo Zhang & Ji Liang & Yanbin Li & Rongda Jia & Ling Wang, 2018. "The Sustainable Development of the Economic-Energy-Environment (3E) System under the Carbon Trading (CT) Mechanism: A Chinese Case," Sustainability, MDPI, vol. 10(1), pages 1-21, January.
    8. Kayaçetin, N.C. & Tanyer, A.M., 2020. "Embodied carbon assessment of residential housing at urban scale," Renewable and Sustainable Energy Reviews, Elsevier, vol. 117(C).
    9. Tang, Baojun & Li, Ru & Yu, Biying & An, Runying & Wei, Yi-Ming, 2018. "How to peak carbon emissions in China's power sector: A regional perspective," Energy Policy, Elsevier, vol. 120(C), pages 365-381.
    10. Ke Wang & Kexin Yang & Yi-Ming Wei & Chi Zhang, 2018. "Shadow prices of direct and overall carbon emissions in China¡¯s construction industry: a parametric directional distance function-based sensitive estimation," CEEP-BIT Working Papers 120, Center for Energy and Environmental Policy Research (CEEP), Beijing Institute of Technology.
    11. Karlsson, Ida & Rootzén, Johan & Johnsson, Filip, 2020. "Reaching net-zero carbon emissions in construction supply chains – Analysis of a Swedish road construction project," Renewable and Sustainable Energy Reviews, Elsevier, vol. 120(C).
    12. Li, Wei & Gao, Shubin, 2018. "Prospective on energy related carbon emissions peak integrating optimized intelligent algorithm with dry process technique application for China's cement industry," Energy, Elsevier, vol. 165(PB), pages 33-54.
    13. Huang, Lizhen & Krigsvoll, Guri & Johansen, Fred & Liu, Yongping & Zhang, Xiaoling, 2018. "Carbon emission of global construction sector," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P2), pages 1906-1916.
    14. Lei Wen & Lu Bai & Ernv Zhang & Jianfeng Weng, 2016. "A system dynamics model for industrial carbon emissions in Baoding," Mathematical and Computer Modelling of Dynamical Systems, Taylor & Francis Journals, vol. 22(6), pages 555-568, November.
    15. Jindamas Sutthichaimethee & Kuskana Kubaha, 2018. "Forecasting Energy-Related Carbon Dioxide Emissions in Thailand’s Construction Sector by Enriching the LS-ARIMAXi-ECM Model," Sustainability, MDPI, vol. 10(10), pages 1-19, October.
    16. Shengxian Ge & Xianyu Yu & Dequn Zhou & Xiuzhi Sang, 2019. "The Integrated Effect of Carbon Emissions Trading and Pollution Rights Trading for Power Enterprises—A Case Study of Chongqing," Sustainability, MDPI, vol. 11(11), pages 1-17, June.
    17. Zeng, Bo & Duan, Huiming & Bai, Yun & Meng, Wei, 2018. "Forecasting the output of shale gas in China using an unbiased grey model and weakening buffer operator," Energy, Elsevier, vol. 151(C), pages 238-249.
    18. 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).
    19. Wu, Lifeng & Liu, Sifeng & Liu, Dinglin & Fang, Zhigeng & Xu, Haiyan, 2015. "Modelling and forecasting CO2 emissions in the BRICS (Brazil, Russia, India, China, and South Africa) countries using a novel multi-variable grey model," Energy, Elsevier, vol. 79(C), pages 489-495.
    20. Zhao, Zhitong & Chong, Katie & Jiang, Jingyang & Wilson, Karen & Zhang, Xiaochen & Wang, Feng, 2018. "Low-carbon roadmap of chemical production: A case study of ethylene in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 97(C), pages 580-591.
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