Determination of the factors that influence increments in CO2 emissions in Jiangsu, China using the SDA method

被引:83
|
作者
Xu, Shi-Chun [1 ]
Zhang, Le [1 ]
Liu, Yuan-Tao [1 ]
Zhang, Wen-Wen [1 ]
He, Zheng-Xia [2 ]
Long, Ru-Yin [1 ]
Chen, Hong [1 ]
机构
[1] China Univ Min & Technol, Sch Management, Xuzhou 221116, Peoples R China
[2] Jiangsu Normal Univ, Commercial Sch, Xuzhou 221116, Peoples R China
基金
中国国家自然科学基金;
关键词
Jiangsu; CO2; emissions; Energy consumption; SDA method; STRUCTURAL DECOMPOSITION ANALYSIS; CARBON-DIOXIDE EMISSIONS; GREENHOUSE-GAS EMISSIONS; INPUT-OUTPUT; ENERGY-CONSUMPTION; ECONOMIC-GROWTH; DRIVING FORCES; INTENSITY; DRIVERS; INDUSTRY;
D O I
10.1016/j.jclepro.2016.10.161
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Using the structural decomposition analysis (SDA) method, we decomposed the factors affecting the increments in CO2 emissions in China's Jiangsu Province. A comparative analysis of these factors at the holistic, sectoral, and sub-sectoral levels revealed that the effects related to the province's economic growth; in particular, the transfers-out and investment effects greatly increased Jiangsu's CO2 emissions. Overall, the import and export effects increased the emissions, reflecting the deteriorating foreign trade structure from the perspective of the emissions reduction. The energy intensity reduced Jiangsu's CO2 emissions greatly, whereas the energy structure had only a slight effect, which shows the high energy efficiency and inappropriate energy structure. The technology effect had a relatively slight reducing impact on the CO2 emissions compared with the other effects, so the input and output efficiency in Jiangsu had not yet been significantly improved. On the whole, the transfers-out, investment, and export effects increased the CO2 emissions in all sectors and subsectors, whereas the other effects on the increments in Jiangsu's CO2 emissions in the sectors and industrial subsectors differed greatly. Some policy implications arising from our study results are discussed. (C) 2016 Elsevier Ltd. All rights reserved.
引用
收藏
页码:3061 / 3074
页数:14
相关论文
共 50 条
  • [1] Inequality characteristics and influencing factors of CO2 emissions per capita in Jiangsu Province, China
    Li J.
    Huang X.
    Chuai X.
    Yang H.
    Chen H.
    Li Y.
    Wu C.
    Environmental Science and Pollution Research, 2024, 31 (19) : 28564 - 28577
  • [2] Marginal abatement costs of industrial CO2 emissions and their influence factors in China
    Wang, Feng
    Wang, Ruiqi
    Nan, Xue
    SUSTAINABLE PRODUCTION AND CONSUMPTION, 2022, 30 : 930 - 945
  • [3] The influence factors of interprovincial power transmission on China's CO2 emissions
    Li, Wenchao
    Xu, Lingyu
    Jin, Yi
    SCIENCE PROGRESS, 2022, 105 (04)
  • [4] Analyzing the driving effect of influence factors on CO2 emissions using the STIRPAT model in Tianjin of China
    Zhao, Tao
    Gou, Xue
    RESOURCES AND SUSTAINABLE DEVELOPMENT, PTS 1-4, 2013, 734-737 : 1896 - 1900
  • [5] Driving factors of aggregate CO2 emissions in China
    Wang, Qunwei
    Chiu, Ching-Ren
    Chiu, Yung-Ho
    INTERNATIONAL CONFERENCE ON APPLIED ENERGY, ICAE2014, 2014, 61 : 1327 - 1330
  • [6] Using STIRPAT Model to Analyze Impact Factors on CO2 Emissions of China
    Wang, Jianjun
    Li, Li
    INTERNATIONAL JOINT CONFERENCE ON APPLIED MATHEMATICS, STATISTICS AND PUBLIC ADMINISTRATION (AMSPA 2014), 2014, : 1 - 5
  • [7] Forecast and analysis of China's industrial CO2 emissions from 2020 to 2060 based on the IO-SDA method
    Wang, Huo-Gen
    Wang, Yu-Ting
    Xiao, Li-Xiang
    Zhongguo Huanjing Kexue/China Environmental Science, 2024, 44 (03): : 1743 - 1755
  • [8] Using LMDI method to analyze transport sector CO2 emissions in China
    Wang, W. W.
    Zhang, M.
    Zhou, M.
    ENERGY, 2011, 36 (10) : 5909 - 5915
  • [9] CO2 emissions in China’s power industry by using the LMDI method
    Xin Zou
    Jiaxuan Li
    Qian Zhang
    Environmental Science and Pollution Research, 2023, 30 : 31332 - 31347
  • [10] CO2 emissions in China's power industry by using the LMDI method
    Zou, Xin
    Li, Jiaxuan
    Zhang, Qian
    ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH, 2023, 30 (11) : 31332 - 31347