globalchange  > 气候变化事实与影响
CSCD记录号: CSCD:6090449
论文题名:
中国工业碳排放达峰的情景预测与减排潜力评估
其他题名: Scene prediction of carbon emission peak and emission reduction potential estimation in Chinese industry
作者: 王勇; 毕莹; 王恩东
刊名: 中国人口·资源与环境
ISSN: 1002-2104
出版年: 2017
卷: 27, 期:10, 页码:47-51
语种: 中文
中文关键词: 工业 ; 碳排放达峰 ; STIRPAT模型 ; 情景分析 ; 减排潜力
英文关键词: industry ; carbon emission peak ; STIRPAT Model ; scene analysis ; emission reduction potential
WOS学科分类: ENVIRONMENTAL SCIENCES
WOS研究方向: Environmental Sciences & Ecology
中文摘要: 实现2030年碳排放达峰不仅是中国为应对全球气候变化向国际社会做出的郑重承诺,也是中国未来经济结构转型与可持续发展的必然选择。基于中国实现2030年碳排放达到峰值的宏观目标为背景,本文以中国碳排放的主要行业工业为研究对象,首先运用拓展的STIRPAT模型对工业及其9个细分行业的碳排放达峰进行了情景预测,然后基于公平和效率的双重视角对工业细分行业的减排潜力进行评估。研究表明:①仅有低碳情景和抑制排放情景2可以实现中国碳排放2030年达峰,低碳情景是实现中国工业碳排放达峰的最佳发展模式,达峰时间最早( 2030年),峰值最低( 140.43亿t) 。激进排放情景则是最差的发展模式,达峰时间最晚( 2036年),峰值也最高( 150.09亿t) 。②工业内部各细分行业碳排放的最优达峰情景差别较大。建材和纺织制造业能够实现提前达峰,可以在这类行业率先实施达峰管理措施,使其带动其他行业陆续达峰。③最具减排潜力的行业是石油制造业,其次是电力行业,这些减排潜力较大的行业应该成为国家节能减排的重点对象。④基于工业各细分行业在减排公平性和效率性上的差异将工业9个细分行业分为四类。其中,石油、钢铁制造业和电力行业属于高效高公平行业;化工、建材制造业属于低效高公平行业;采掘业属于高效不公平行业;纺织、轻工和机电制造业属于低效不公平行业。中国应针对不同类型的行业制定出相应的减排战略,将减排重点放在各行业最具潜力的方面。最后,文章对实现中国工业碳排放达峰管理提出了几点政策建议。
英文摘要: Achieving the peak carbon emissions in 2030 is not only a solemn commitment that China made to the international community for coping with global climate change,but also an inevitable choice for China's future economic restructuring and sustainable development. Based on China's macroeconomic goal of achieving peak carbon emissions in 2030, this paper takes Chinese industry, which is China's major division of carbon emissions, as the research object. First, it uses the extended STIRPAT Model to make the scene prediction for the carbon emission peak of Chinese industry and its nine sectors. And then based on the dual perspective of equity and efficiency, it evaluates the potential for emission reduction of each industrial sectors. The results show that: ①Only the low-carbon scenario and the 2th emission-reduction-scenario could achieve the 2030 peak carbon emissions in China, and the low-carbon scenario is the best development mode for Chinese industry,because its peak time is the earliest ( by 2030) and the peak is the lowest ( 140.43 billion t). However, the radical-emission scenario is the worst development mode, as the peak time in this model is the latest ( by 2036) and the peak is also the highest ( 150.09 billion t). ②The optimal peak scenario of carbon emissions in each industrial sectors is quite different. The building materials manufacturing industry and the textile manufacturing industry can reach the peak in advance, so it is better to take the lead in such sub-industries to implement the peak management measures to enable other industries to reach the peak one after another. ③The most potential emission reduction industry is oil manufacturing, followed by the power industry. These two industries that have greater emission reduction potential should be the focus of the national energy-saving emission reduction. ④Based on the differences in equity and efficiency, the nine industrial sectors are divided into four categories. Among them, the petroleum industry, the iron and steel industry, and the electric power industry belong to thehigh-efficiency & high-equity'type; the chemical industry and the building materials manufacturing industry belong to thelow-efficiency & high-equity'type; the mining industry belongs to thehigh-efficiency & low-equity'type; the textile industry, the light industry,and the machinery manufacturing industry belong to thelow-efficiency & low-equity'type. So Chinese government should develop appropriate emission reduction strategies for different types of industries,making sure that the emphasis on emission reduction has focused on its most potential areas. Finally, this paper puts forward some policy recommendations to achieve the peak management of China's industrial carbon emissions.
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/153551
Appears in Collections:气候变化事实与影响

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作者单位: 东北财经大学统计学院, 大连, 辽宁 116025, 中国

Recommended Citation:
王勇,毕莹,王恩东. 中国工业碳排放达峰的情景预测与减排潜力评估[J]. 中国人口·资源与环境,2017-01-01,27(10):47-51
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