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谭显春,赖海萍,顾佰和,涂唐奇,李辉.主体功能区视角下的碳排放核算——以广东省为例.生态学报,2018,(17).http://dx.doi.org/10.5846/stxb201710311950  
主体功能区视角下的碳排放核算——以广东省为例
Carbon emissions accounting from the perspective of main functional areas -- a case study of Guangdong Province
投稿时间:2017-10-31  修订日期:2018-04-04
DOI: 10.5846/stxb201710311950
关键词碳排放核算  主体功能区  广东省  县域
Key WordsCarbon emission accounting  Principle function area  Guangdong  County
基金项目国家自然科学基金面上项目(71573249); 中国科学院科技战略咨询研究院重大咨询项目(Y02015003); 中国清洁发展机制基金赠款项目(2014091); 中国科学院科技战略咨询研究院院长青年基金(Y7X1091Q01);国家自然科学基金项目(71741014)
作者单位E-mail
谭显春 中国科学院科技战略咨询研究院 txc@casipm.ac.cn 
赖海萍 中国科学院科技战略咨询研究院 laiwindsky@163.com 
顾佰和 中国科学院科技战略咨询研究院 gubaihes@163.com 
涂唐奇 中国科学院科技战略咨询研究院  
李辉 中国科学院科技战略咨询研究院  
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摘要:
区域碳排放核算是当前全球气候变化与碳排放研究的核心内容之一。中国于2010年出台《全国主体功能区规划》,主体功能区是以区域开发程度、资源环境基础和未来开发潜力为依据,县域为基本单位的区域规划方案,这为区域碳排放核算和配额分配提供了全新的视角。鉴于县域的能源数据不够完善,本文基于经济、人口、省级能耗量等数据构建了适用于主体功能区划分的碳排放核算方法,并确保各主体功能区的碳排放总量和分部门碳排放总量都与该省的总碳排放量或分部门的一一对应相等。文章以中国广东省为案例,对其四类主体功能区在2005—2015年间的碳排放情况进行核算分析。研究发现:四类主体功能区的碳排放总量与经济总量呈现高度正相关性;四类地区中碳排放量从大到小依次为优化、重点、农产品、生态开发区。碳排放强度最大的为生态开发区,其次是重点开发区,农产品开发区和优化开发区。重点开发区和优化开发区的碳排放占全省比值达86%,都应作为未来节能减排措施的最主要的作用对象,需加快产业结构升级,扩大新能源技术的应用。农产品开发区和生态开发区应加快发展循环农业,有机低碳农业生态环境友好型产业。
Abstract:
Regional carbon emission accounting is one of the core concepts of current global climate change and carbon emission research. The development of regional coordination has always been the focus of attention, and the importance of both the ecological environment and policy fairness is the central study for all kinds of land use planning. In 2010, China published the national functional zoning plan, which is based on regional development, resource environment foundations, and future development potential. According to the plan, the county is the basic unit of the regional carbon emission planning programs, which provides a new perspective for regional carbon accounting and quota allocation. Because the energy data for counties was not sufficient, this study has developed a new carbon emission accounting method based on the economic, population, and provincial energy consumption data, which is suitable for the division of main functional areas. We used the carbon intensity of three industries and per capita carbon emission as the main indicators to calculate the emissions. This method ensure two conditions: the total amount of carbon emissions of main functional areas should be equal to the carbon emissions of the province, and the carbon emissions of main functional areas in four sectors should be equal to the carbon emissions of the province in the corresponding sector. By taking Guangdong Province as a case example, this paper accounted for and analyzed the carbon emission of the four main functional areas of Guangdong Province from 2005–2015.The analysis reveals that the total carbon emission of the four main functional areas is highly positively correlated with their total economic output, but the GDP growth rate will be slightly higher than the carbon emissions growth rate on the whole. There is a link between "economic growth–energy consumption–carbon emissions" in the research results. The largest carbon emissions in the four regions was the optimizing development zone, which accounted for 64.84% of all emissions in 2015. The second largest emissions was caused by the key development zone, which account for 21.04%. The largest carbon emission intensity was the ecological development zone, at about 1.89 t/10,000 yuan. The second highest carbon emission intensity was found to be in the key development zone, and next was the agricultural development zone. The optimizing development zone has the lowest carbon intensity because of its advanced economic development. The optimizing development and key development zones should serve as the main targets for future energy conservation and emission reduction measures. The optimizing development zone should speed up the application of new energy technology and accelerate industrial upgrading. The agricultural development and ecological development zones should develop more environmentally friendly industries, such as organic food, low-carbon agriculture, and ecological tourism.
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