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Prospective on energy related carbon emissions peak integrating optimized intelligent algorithm with dry process technique application for China's cement industry

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  • Li, Wei
  • Gao, Shubin

Abstract

Global climate change is a significant environmental problem. A major trigger of climate change is the excess carbon emissions. Based on 44 scenarios in the second generation of new dry cement technology systems, this paper establishes IPSO-BP model to forecast the carbon emissions peak of China‘s cement industry for 2016–2050 years. The results indicate that China's cement industry only implements capacity reduction plans and the second generation of new dry cement technology systems, so that carbon emissions can reach the peak before 2030. It is up to 19 years ahead of the carbon emissions peak of the basic scenario and the carbon emissions peak is reduced by 38 Mt. Moreover, this paper analyzes the technical combination of the earliest carbon emissions and the lowest carbon emissions. As for the earliest carbon emissions technical combination, China's cement industry carbon emissions will peak at 789.95 Mt in 2021. According to the lowest carbon emissions technical combination, China's cement industry carbon emissions will peak at 742.37 Mt in 2025. Accordingly, the conclusions will be helpful for making carbon emissions reduction policies for China's cement industry.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:energy:v:165:y:2018:i:pb:p:33-54
    DOI: 10.1016/j.energy.2018.09.152
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    as
    1. Wen, Zongguo & Chen, Min & Meng, Fanxin, 2015. "Evaluation of energy saving potential in China's cement industry using the Asian-Pacific Integrated Model and the technology promotion policy analysis," Energy Policy, Elsevier, vol. 77(C), pages 227-237.
    2. Cai, Wenjia & Wang, Can & Chen, Jining & Wang, Ke & Zhang, Ying & Lu, Xuedu, 2008. "Comparison of CO2 emission scenarios and mitigation opportunities in China's five sectors in 2020," Energy Policy, Elsevier, vol. 36(3), pages 1181-1194, March.
    3. Jinying Li & Jianfeng Shi & Jinchao Li, 2016. "Exploring Reduction Potential of Carbon Intensity Based on Back Propagation Neural Network and Scenario Analysis: A Case of Beijing, China," Energies, MDPI, vol. 9(8), pages 1-17, August.
    4. Wee, Jung-Ho, 2010. "Contribution of fuel cell systems to CO2 emission reduction in their application fields," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(2), pages 735-744, February.
    5. Li, Nan & Ma, Ding & Chen, Wenying, 2017. "Quantifying the impacts of decarbonisation in China’s cement sector: A perspective from an integrated assessment approach," Applied Energy, Elsevier, vol. 185(P2), pages 1840-1848.
    6. Branger, Frédéric & Quirion, Philippe, 2015. "Reaping the carbon rent: Abatement and overallocation profits in the European cement industry, insights from an LMDI decomposition analysis," Energy Economics, Elsevier, vol. 47(C), pages 189-205.
    7. Xu, Bin & Lin, Boqiang, 2016. "Assessing CO2 emissions in China’s iron and steel industry: A dynamic vector autoregression model," Applied Energy, Elsevier, vol. 161(C), pages 375-386.
    8. Li, Wei & Lu, Can & Ding, Yi & Zhang, Yan-Wu, 2017. "The impacts of policy mix for resolving overcapacity in heavy chemical industry and operating national carbon emission trading market in China," Applied Energy, Elsevier, vol. 204(C), pages 509-524.
    9. Lin, Boqiang & Zhang, Zihan, 2016. "Carbon emissions in China׳s cement industry: A sector and policy analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 58(C), pages 1387-1394.
    10. Kumar, Subhash & Madlener, Reinhard, 2016. "CO2 emission reduction potential assessment using renewable energy in India," Energy, Elsevier, vol. 97(C), pages 273-282.
    11. Boqiang Lin & Zihan Zhang & Fei Ge, 2017. "Energy Conservation in China’s Cement Industry," Sustainability, MDPI, vol. 9(4), pages 1-17, April.
    12. Burhan, Muhammad & Chua, Kian Jon Ernest & Ng, Kim Choon, 2016. "Sunlight to hydrogen conversion: Design optimization and energy management of concentrated photovoltaic (CPV-Hydrogen) system using micro genetic algorithm," Energy, Elsevier, vol. 99(C), pages 115-128.
    13. Li, Wei & Jia, Zhijie & Zhang, Hongzhi, 2017. "The impact of electric vehicles and CCS in the context of emission trading scheme in China: A CGE-based analysis," Energy, Elsevier, vol. 119(C), pages 800-816.
    14. Lin, Boqiang & Ouyang, Xiaoling, 2014. "Analysis of energy-related CO2 (carbon dioxide) emissions and reduction potential in the Chinese non-metallic mineral products industry," Energy, Elsevier, vol. 68(C), pages 688-697.
    15. Xu, Jin-Hua & Fleiter, Tobias & Fan, Ying & Eichhammer, Wolfgang, 2014. "CO2 emissions reduction potential in China’s cement industry compared to IEA’s Cement Technology Roadmap up to 2050," Applied Energy, Elsevier, vol. 130(C), pages 592-602.
    16. Cai, Bofeng & Wang, Jinnan & He, Jie & Geng, Yong, 2016. "Evaluating CO2 emission performance in China’s cement industry: An enterprise perspective," Applied Energy, Elsevier, vol. 166(C), pages 191-200.
    17. Harris, Paul G. & Chow, Alice S.Y. & Symons, Jonathan, 2012. "Greenhouse gas emissions from cities and regions: International implications revealed by Hong Kong," Energy Policy, Elsevier, vol. 44(C), pages 416-424.
    18. Uzlu, Ergun & Kankal, Murat & Akpınar, Adem & Dede, Tayfun, 2014. "Estimates of energy consumption in Turkey using neural networks with the teaching–learning-based optimization algorithm," Energy, Elsevier, vol. 75(C), pages 295-303.
    19. Shen, Weiguo & Liu, Yi & Yan, Bilan & Wang, Jing & He, Pengtao & Zhou, Congcong & Huo, Xujia & Zhang, Wuzong & Xu, Gelong & Ding, Qingjun, 2017. "Cement industry of China: Driving force, environment impact and sustainable development," Renewable and Sustainable Energy Reviews, Elsevier, vol. 75(C), pages 618-628.
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