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author:

Lin, Ping Ping (Lin, Ping Ping.) [1] | Li, Deng Feng (Li, Deng Feng.) [2] | Jiang, Bin Qian (Jiang, Bin Qian.) [3] | Wei, An Peng (Wei, An Peng.) [4] | Yu, Gao Feng (Yu, Gao Feng.) [5]

Indexed by:

SSCI EI Scopus SCIE

Abstract:

To assess the potential of China's industrial restructuring on energy conservation and greenhouse gas (GHG) emission reduction in 2020, this study proposes an input-output multi-choice goal programming model and method. In this model, the goals include the maximization of gross domestic product (GDP), minimization of energy consumption and GHG emission. They are subjected to the input-output balance, economy development, energy supply, and industry diversity. And four scenarios with different decision preferences are taken into accounted in the solutions of the industrial structure optimization model. The results demonstrate that industrial restructuring has potential in energy saving and emission reducing. First, after optimization, energy consumption intensity and GHG emission intensity can drop by 13.88246% and 5.33767% over 2012, and GDP can grow up at annual growth rate 6.6% from 2013-2020. Second, promoting the development of the low energy-intensive and low GHG emission intensive sectors is an effective method for energy conservation and emission reduction. Three, compared to energy intensity reduction, GHG emission intensity reduction is less effective for four scenarios. Four, there are several difficulties to achieve the amounts and intensity control targets of energy conservation and GHG emission reduction simultaneously. It is suggested that China had better strive to promote progress of technologies of energy conservation and GHG emission reduction while adjusting the industrial structure. (C) 2019 The Authors. Published by Atlantis Press SARL.

Keyword:

Big data analysis Energy conservation Greenhouse gas emission reduction Industrial restructuring Input-output model

Community:

  • [ 1 ] [Lin, Ping Ping]Fuzhou Univ, Sch Econ & Management, 2 Xueyuan Rd, Fuzhou 350108, Peoples R China
  • [ 2 ] [Jiang, Bin Qian]Fuzhou Univ, Sch Econ & Management, 2 Xueyuan Rd, Fuzhou 350108, Peoples R China
  • [ 3 ] [Wei, An Peng]Fuzhou Univ, Sch Econ & Management, 2 Xueyuan Rd, Fuzhou 350108, Peoples R China
  • [ 4 ] [Yu, Gao Feng]Fuzhou Univ, Sch Econ & Management, 2 Xueyuan Rd, Fuzhou 350108, Peoples R China
  • [ 5 ] [Li, Deng Feng]Univ Elect Sci & Technol China, Sch Management & Econ, 2006 Xiyuan Ave, Chengdu 611731, Sichuan, Peoples R China

Reprint 's Address:

  • [Li, Deng Feng]Univ Elect Sci & Technol China, Sch Management & Econ, 2006 Xiyuan Ave, Chengdu 611731, Sichuan, Peoples R China

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Source :

INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE SYSTEMS

ISSN: 1875-6891

Year: 2019

Issue: 2

Volume: 12

Page: 1311-1322

1 . 8 3 8

JCR@2019

2 . 5 0 0

JCR@2023

ESI Discipline: COMPUTER SCIENCE;

ESI HC Threshold:162

JCR Journal Grade:3

CAS Journal Grade:4

Cited Count:

WoS CC Cited Count: 10

SCOPUS Cited Count: 13

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 2

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