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A Factor Decomposition on China's Carbon Emission from 1997 to 2012 Based on IPAT-LMDI Model

机译:基于IPAT-LMDI模型的1997-2012年中国碳排放因子分解

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摘要

We probe into the key factors that possess significant effects on China's CO2 emissions during 1997-2012 on the basis of IPAT-LMDI model. Carbon dioxide emissions are specifically decomposed into CO2 emission intensity, energy structure, energy intensity, industrial structure, economic output, and population scale effects. Results indicate that the paramount driving factors that resulted in the growth of CO2 emissions are economic output, population scale, and energy structure. In contrast, energy intensity and industrial structure generally play an outstanding role in reducing emissions. This paper constructs a new weight assessment system by introducing "contribution value-significant factor-effect coefficient" to replace "contribution value-contribution rate" in the previous literature. According to the most significant positive effect and the most negative effect from the conclusion, we point out the effective policies that can not only accelerate the target of "China's carbon emissions per unit of GDP could be cut down by 40-45% by 2020, from 2005 levels," but also have crucial significance on the low-carbon economic development strategy of China.
机译:基于IPAT-LMDI模型,我们探讨了1997-2012年间对中国CO2排放产生重大影响的关键因素。二氧化碳的排放具体分解为二氧化碳排放强度,能源结构,能源强度,产业结构,经济产出和人口规模效应。结果表明,导致二氧化碳排放量增长的最主要驱动因素是经济产出,人口规模和能源结构。相比之下,能源强度和产业结构通常在减少排放方面发挥突出作用。本文通过引入“贡献值-显着因子-效应系数”代替以前文献中的“贡献值-贡献率”,构建了一个新的权重评估系统。根据结论中最显着的积极影响和最消极的影响,我们指出了有效的政策,这些政策不仅可以加速实现“到2020年中国单位GDP的碳排放可以减少40-45%,从2005年的水平开始”,对于中国的低碳经济发展战略也具有至关重要的意义。

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  • 来源
    《Mathematical Problems in Engineering》 |2015年第9期|943758.1-943758.14|共14页
  • 作者单位

    North China Elect Power Univ, Dept Econ Management, Baoding 071003, Peoples R China.;

    North China Elect Power Univ, Dept Econ Management, Baoding 071003, Peoples R China.;

    North China Elect Power Univ, Dept Econ Management, Baoding 071003, Peoples R China.;

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