气候变化研究进展 ›› 2012, Vol. 8 ›› Issue (4): 278-284.

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基于聚类分析的碳强度目标分解研究

杨 源1, 蔡闻佳1, 王 灿1, 王思强1,2     

  1. 1 清华大学环境学院;
    2 国家能源局
  • 收稿日期:2011-10-31 修回日期:2012-04-17 出版日期:2012-07-30 发布日期:2012-07-30
  • 通讯作者: 蔡闻佳 E-mail:caiwj05@mails.tsinghua.edu.cn
  • 基金资助:

    国家科技支撑计划

Regional Allocation of CO2 Intensity Reduction Targets Based on Cluster Analysis

  • Received:2011-10-31 Revised:2012-04-17 Online:2012-07-30 Published:2012-07-30

摘要: 基于地区聚类分析得到了我国2020年碳强度目标分解方案。根据各地区在经济能力、排放水平和减排潜力上的相似程度,将我国30个省区分成6类。按照公平原则,经济最发达的第1、2类地区减排目标最高,分别为55%和65%,但是其减排潜力较小;按照效率原则,减排潜力较大的第3、5类地区减排目标最高,分别为48%和61%,但是其经济相对落后;综合分解方案显示减排潜力最大的第5类地区,以及属于工业与排放大省的第2、3类地区的减排目标最高,分别为54%、49%和49%。而在这3种分解方案下,经济能力、排放水平与减排潜力都较低的第4类与第6类地区减排指标最高不超过40%。经济能力与减排潜力在空间上存在一定程度的错位,导致仅通过碳强度目标的分解无法较好地兼顾公平与效率,还需要建立配套的市场机制和政策工具。

关键词: 碳强度目标分解, 聚类分析, 地区差异

Abstract: To meet China’s CO2 intensity target of 40%-45% reduction by 2020 from 2005 level, a regional allocation method based on cluster analysis was developed. The 30 provinces were classified into 6 groups based on economy, emission and reduction potential indicators. Under equity principle, the two most developed groups are assigned the highest reduction targets (55% and 65% respectively), however their reduction potential is limited. Under efficiency principle, the 2 groups with highest reduction potential take the highest targets (48% and 61% respectively), but their economy is relatively backward. When equity and efficiency are equally weighted, the 5th group with prominent reduction potential takes the highest target (54%), and the 2nd and 3rd groups with large industry scale take the second highest target (49%). Whereas under the 3 allocation schemes, the targets are not greater than 40% for the 4th and 6th group, which have relatively low economic ability, emission and reduction potential. Due to inconsistency between economic ability and reduction potential, corresponding market mechanism and policy instrument should be established to ensure equity and efficiency of regional target allocation.

Key words: CO2 intensity reduction target allocation, cluster analysis, regional difference

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