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Driving Factor Analysis of Carbon Emissions in China's Power Sector for Low-Carbon Economy

机译:中国电力行业低碳经济中碳排放的驱动因素分析

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摘要

The largest percentage of China's total coal consumption is used for coal-fired power generation, which has resulted in the power sector becoming China's largest carbon emissions emitter. Most of the previous studies concerning the driving factors of carbon emissions changes lacked considerations of different socioeconomic factors. This study examines the impacts of eight factors from different aspects on carbon emissions within power sector from 1981 to 2013 by using the extended Stochastic Impacts by Regression on Population, Affluence and Technology (STIRPAT) model; in addition, the regression coefficients are effectively determined by a partial least squares regression (PLS) method. The empirical results show that (1) the degree of influence of various factors from strong to weak is urbanization level (UL) > technology level (T-1) > population (P) > GDP per capita (A) > line loss (T-2) > power generation structure (T-3) > energy intensity (T-4) > industry structure (IS); (2) economic activity is no longer the most important contributing factor; the strong correlation between electricity consumption and economic growth is weakening; and (3) the coal consumption rate of power generation had the most obvious inhibitory effect, indicating that technological progress is still a vital means of achieving emissions reductions.
机译:在中国煤炭消费总量中,最大的百分比用于燃煤发电,这导致电力部门成为中国最大的碳排放排放国。先前有关碳排放变化驱动因素的大多数研究都缺乏对不同社会经济因素的考虑。本研究通过使用扩展的回归对人口,富裕度和技术的随机影响(STIRPAT)模型,研究了1981年至2013年不同方面的八个因素对电力行业碳排放的影响;此外,回归系数可以通过偏最小二乘回归(PLS)方法有效地确定。实证结果表明:(1)各种因素从强到弱的影响程度是城市化水平(UL)>技术水平(T-1)>人口(P)>人均GDP(A)>线损(T) -2)>发电结构(T-3)>能源强度(T-4)>产业结构(IS); (2)经济活动不再是最重要的贡献因素;电力消费与经济增长之间的密切关系正在减弱; (3)发电煤耗率的抑制作用最明显,表明技术进步仍然是实现减排的重要手段。

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  • 来源
    《Mathematical Problems in Engineering》 |2017年第2017期|4954217.1-4954217.10|共10页
  • 作者

    Yan Dan; Lei Yalin; Li Li;

  • 作者单位

    China Univ Geosci, Sch Humanities & Econ Management, Beijing 100083, Peoples R China|Minist Land & Resources, Key Lab Carrying Capac Assessment Resource & Envi, Beijing 100083, Peoples R China;

    China Univ Geosci, Sch Humanities & Econ Management, Beijing 100083, Peoples R China|Minist Land & Resources, Key Lab Carrying Capac Assessment Resource & Envi, Beijing 100083, Peoples R China;

    China Univ Geosci, Sch Humanities & Econ Management, Beijing 100083, Peoples R China|Minist Land & Resources, Key Lab Carrying Capac Assessment Resource & Envi, Beijing 100083, Peoples R China;

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