2016 International Conference on New Energy and Future Energy System | |
Economic-energy-industrial-environmental optimization (EEIEO) model for identification of optimal strategies - a case study of Beijing-Tianjin-Hebei region, China | |
Chen, C.^1,2,3 ; Long, H.L.^1 ; Wan, J.^3 ; Jia, J.L.^3 ; Li, X.^3 ; Chu, C.J.^3 | |
Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing | |
100101, China^1 | |
University of Science and Technology Beijing, Donlinks School of Economics and Management, Beijing | |
100083, China^2 | |
China Academy for Environmental Planning, Beijing | |
100012, China^3 | |
关键词: Beijing-tianjin-hebei regions; Economic development; Energy and environment; Environment management; Environmental sector; Industrial restructuring; Optimization framework; Tertiary industries; | |
Others : https://iopscience.iop.org/article/10.1088/1755-1315/40/1/012005/pdf DOI : 10.1088/1755-1315/40/1/012005 |
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来源: IOP | |
【 摘 要 】
An economic-energy-industrial-environmental optimization (EEIEO) model is proposed for identification of optimal economic, industry, energy and environment strategies. The EEIEO model is applied to a real case of Beijing-Tianjin-Hebei (BTH) region, which is the important economic growth pole of northern China. The EEIEO model could fully consider the interaction between industrial, energy, urbanization and environment sector, and generate the optimized economic development, industrial restructuring, energy consumption and environment management schemes. This is first attempt to introduce economic, energy, industrial, urbanization and environmental sectors into an optimization framework, while sustainable energy and environment development pathways are explored through EEIEO model. The results suggest that: (i) the GDP of BTH region would increase about 73.80% over the planning horizon; (ii) the contribution of tertiary industry for BTH region's economic development would gradually increase from 54.00% in 2015 to 65.00% in 2030; (iii) the consumption of coal would decrease by 36%, and the natural gas would obviously increase by 97.70% over the planning horizon; and (iv) the SO2, smoke and dust emissions and CO2would reduce by 30.20%, 35.30% and 4.50% from 2015 to 2030, respectively.
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