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Optimizing regional allocation of CO2 emissions considering output under overall efficiency

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  • Zhang, Jingxiao
  • Jin, Weixing
  • Yang, Guo-liang
  • Li, Hui
  • Ke, Yongjian
  • Philbin, Simon Patrick

Abstract

Reduction of CO2 emissions is a strategic priority for the construction industry, however current schemes do not provide the level of performance that is required. There is also a lack of understanding of how to allocate CO2 emissions targets within regions. Therefore, this research study develops a three-stage empirical system to identify the CO2 emissions allocation scheme for the Chinese construction industry at the provincial level. The results indicate that (a) the construction industry's CO2 emissions need to be reduced by ca. 10% from the base level in 2017; (b) 86.7% of the provinces have a relatively large capacity for CO2 emissions reduction; (c) China's East region accounts for 44.0% of the total amount for CO2 emissions reduction; and (d) about one-third of the provinces face enormous pressure to reduce CO2 emissions by more than 10% on the base of 2017. This research study provides unique insights and guidance to support assessment of the regional allocation of CO2 emissions for the construction industry, which is a valuable reference for other countries and industries.

Suggested Citation

  • Zhang, Jingxiao & Jin, Weixing & Yang, Guo-liang & Li, Hui & Ke, Yongjian & Philbin, Simon Patrick, 2021. "Optimizing regional allocation of CO2 emissions considering output under overall efficiency," Socio-Economic Planning Sciences, Elsevier, vol. 77(C).
    • Handle: RePEc:eee:soceps:v:77:y:2021:i:c:s0038012121000045
    DOI: 10.1016/j.seps.2021.101012
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    as
    1. Kiani Mavi, Reza & Saen, Reza Farzipoor & Goh, Mark, 2019. "Joint analysis of eco-efficiency and eco-innovation with common weights in two-stage network DEA: A big data approach," Technological Forecasting and Social Change, Elsevier, vol. 144(C), pages 553-562.
    2. Tengfei Huo & Hong Ren & Weiguang Cai & Wei Feng & Miaohan Tang & Nan Zhou, 2018. "The total-factor energy productivity growth of China’s construction industry: evidence from the regional level," 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. 92(3), pages 1593-1616, July.
    3. 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.
    4. E G Gomes & M P E Lins, 2008. "Modelling undesirable outputs with zero sum gains data envelopment analysis models," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(5), pages 616-623, May.
    5. Wei, Quanling & Zhang, Jianzhong & Zhang, Xiangsun, 2000. "An inverse DEA model for inputs/outputs estimate," European Journal of Operational Research, Elsevier, vol. 121(1), pages 151-163, February.
    6. Emrouznejad, Ali & Yang, Guo-liang, 2016. "A framework for measuring global Malmquist–Luenberger productivity index with CO2 emissions on Chinese manufacturing industries," Energy, Elsevier, vol. 115(P1), pages 840-856.
    7. Nässén, Jonas & Holmberg, John & Wadeskog, Anders & Nyman, Madeleine, 2007. "Direct and indirect energy use and carbon emissions in the production phase of buildings: An input–output analysis," Energy, Elsevier, vol. 32(9), pages 1593-1602.
    8. Yuan Chen & Bingsheng Liu & Yinghua Shen & Xueqing Wang, 2018. "Spatial analysis of change trend and influencing factors of total factor productivity in China’s regional construction industry," Applied Economics, Taylor & Francis Journals, vol. 50(25), pages 2824-2843, May.
    9. Nordhaus, William D & Yang, Zili, 1996. "A Regional Dynamic General-Equilibrium Model of Alternative Climate-Change Strategies," American Economic Review, American Economic Association, vol. 86(4), pages 741-765, September.
    10. Zhou, P. & Wang, M., 2016. "Carbon dioxide emissions allocation: A review," Ecological Economics, Elsevier, vol. 125(C), pages 47-59.
    11. Gholam R. Amin & Ali Emrouznejad & Said Gattoufi, 2017. "Modelling generalized firms’ restructuring using inverse DEA," Journal of Productivity Analysis, Springer, vol. 48(1), pages 51-61, August.
    12. 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.
    13. Bao Zhu & Jing He & Shiting Zhai, 2019. "Does Financial Inclusion Create a Spatial Spillover Effect Between Regions? Evidence from China," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 55(5), pages 980-997, April.
    14. Lim, Dong-Joon, 2016. "Inverse DEA with frontier changes for new product target setting," European Journal of Operational Research, Elsevier, vol. 254(2), pages 510-516.
    15. Du, Mingxi & Wang, Xiaoge & Peng, Changhui & Shan, Yuli & Chen, Huai & Wang, Meng & Zhu, Qiuan, 2018. "Quantification and scenario analysis of CO2 emissions from the central heating supply system in China from 2006 to 2025," Applied Energy, Elsevier, vol. 225(C), pages 869-875.
    16. Zhang, Yue-Jun & Wang, Ao-Dong & Da, Ya-Bin, 2014. "Regional allocation of carbon emission quotas in China: Evidence from the Shapley value method," Energy Policy, Elsevier, vol. 74(C), pages 454-464.
    17. Yang, Guo-liang & Fukuyama, Hirofumi, 2018. "Measuring the Chinese regional production potential using a generalized capacity utilization indicator," Omega, Elsevier, vol. 76(C), pages 112-127.
    18. Zhang, Weijie & Zhang, Ning & Yu, Yanni, 2019. "Carbon mitigation effects and potential cost savings from carbon emissions trading in China's regional industry," Technological Forecasting and Social Change, Elsevier, vol. 141(C), pages 1-11.
    19. Ya Wang & Jiaofeng Pan & Ruimin Pei & Guoliang Yang & Bowen Yi, 2020. "A Framework for Assessing Green Capacity Utilization Considering CO 2 Emissions in China’s High-Tech Manufacturing Industry," Sustainability, MDPI, vol. 12(11), pages 1-25, May.
    20. Yue-Jun Zhang & Jun-Fang Hao, 2017. "Carbon emission quota allocation among China’s industrial sectors based on the equity and efficiency principles," Annals of Operations Research, Springer, vol. 255(1), pages 117-140, August.
    21. Xu, Jin-Hua & Fleiter, Tobias & Eichhammer, Wolfgang & Fan, Ying, 2012. "Energy consumption and CO2 emissions in China's cement industry: A perspective from LMDI decomposition analysis," Energy Policy, Elsevier, vol. 50(C), pages 821-832.
    22. Luzzati, T. & Gucciardi, G., 2015. "A non-simplistic approach to composite indicators and rankings: an illustration by comparing the sustainability of the EU Countries," Ecological Economics, Elsevier, vol. 113(C), pages 25-38.
    23. Emrouznejad, Ali & Yang, Guo-liang, 2016. "CO2 emissions reduction of Chinese light manufacturing industries: A novel RAM-based global Malmquist–Luenberger productivity index," Energy Policy, Elsevier, vol. 96(C), pages 397-410.
    24. Zhou, P. & Zhang, L. & Zhou, D.Q. & Xia, W.J., 2013. "Modeling economic performance of interprovincial CO2 emission reduction quota trading in China," Applied Energy, Elsevier, vol. 112(C), pages 1518-1528.
    25. Wang, Run & Liu, Wenjuan & Xiao, Lishan & Liu, Jian & Kao, William, 2011. "Path towards achieving of China's 2020 carbon emission reduction target--A discussion of low-carbon energy policies at province level," Energy Policy, Elsevier, vol. 39(5), pages 2740-2747, May.
    26. Fang, Kai & Zhang, Qifeng & Long, Yin & Yoshida, Yoshikuni & Sun, Lu & Zhang, Haoran & Dou, Yi & Li, Shuai, 2019. "How can China achieve its Intended Nationally Determined Contributions by 2030? A multi-criteria allocation of China’s carbon emission allowance," Applied Energy, Elsevier, vol. 241(C), pages 380-389.
    27. Wang, Yuanping & Ren, Hong & Dong, Liang & Park, Hung-Suck & Zhang, Yuepeng & Xu, Yanwei, 2019. "Smart solutions shape for sustainable low-carbon future: A review on smart cities and industrial parks in China," Technological Forecasting and Social Change, Elsevier, vol. 144(C), pages 103-117.
    28. Yan Li & Chunlu Liu, 2010. "Malmquist indices of total factor productivity changes in the Australian construction industry," Construction Management and Economics, Taylor & Francis Journals, vol. 28(9), pages 933-945.
    29. Wang, Juan & Hu, Mingming & Rodrigues, João F.D., 2018. "The evolution and driving forces of industrial aggregate energy intensity in China: An extended decomposition analysis," Applied Energy, Elsevier, vol. 228(C), pages 2195-2206.
    30. Filar, J.A. & Gaertner, P.S., 1997. "A regional allocation of world CO2 emission reductions," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 43(3), pages 269-275.
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