关中地区城市碳排放核算与碳排放分类调控策略研究
发布时间：2018-09-10 21:31
【摘要】：减少CO2排放,有效应对全球气候变化已引起越来越多国家的关注。随着中国“西部大开发战略”的进一步实施,关中地区各城市经济进入新的增长阶段,区域城市综合能源消耗和工业分行业能源活动带来的碳排放量呈现上升趋势,给生态环境带来一定挑战。因此,本文对关中地区城市碳排放核算及其分类调控进行研究,以期为促进“高碳经济”向“低碳经济”、“高碳行业”向“低碳行业”转变提供参考,同时为小尺度地区公平分配碳减排责任和关中各城市经济的持续发展提供依据。 根据2000-2011年关中各城市综合能源消耗数据和行业部门能源消耗数据,采用IPCC能源清单法、灰色关联模型、投入产出模型、基尼系数、集中指数、响应力系数、感应力系数以及LMDI结构分解模型对关中各城市及其部门直接和间接碳排放进行区域和行业部门核算及影响机制分析,并有针对性地提出分类调控策略。主要结论包括： (1)2000-2011年关中地区城市西安、咸阳、渭南、宝鸡的碳排放量均呈现出增长的趋势,同期碳排放强度均呈现下降趋势。 (2)2011年关中地区城市碳排放量与碳排放强度存在区域差异。四个城市碳排放量的区域格局特征为：西安咸阳渭南宝鸡,四个城市碳排放强度的区域格局特征为：宝鸡渭南咸阳西安。 关中地区各城市碳排放量与影响因素之间的关联程度有一定相似之处。表现为：经济因素人口因素能源结构技术水平。经济发展对碳排放的推动作用最大,人均GDP的增加是碳排放量增加的主要因素,技术水平提高可以一定程度上提高能源利用效率,降低碳排放量。 (3)从区域角度的行业部门碳排放量来看,四个城市的直接碳排放量和间接碳排放以及完全碳排放量均呈现出区域差异。直接碳排放为：西安咸阳渭南宝鸡；这主要受工业经济发展的影响；间接碳排放为：渭南咸阳宝鸡西安,这主要是受区域经济联系与出口产品的影响；完全碳排放为：渭南咸阳宝鸡西安,这主要是因为整体经济发展和工业中间投入引起的碳排放差异。 (4)从行业部门内部碳排放量来看,2011年西安和咸阳行业直接碳排放和间接碳排放存在部门差异。集中指数和基尼系数显示两市的行业碳排放集中程度较高,碳排放部门间分配不均衡,高碳行业与低碳行业差距较大。响应力系数和感应力系数较高的部门对整个国民经济发展的推动作用较大,国民经济及其他部门对这些部门的拉动作用也较大,间接碳排放较高。 (5)LMDI因素分解模型显示行业间接碳排放受不同影响因素影响程度不同,并且在部门间存在影响差异。规模效应对间接碳排放影响最大,其次是强度效应,最后是结构效应。规模效应是间接碳排放增加的主要因素,强度效应是间接碳排放增加的抑制性因素,结构效应对间接碳排放的影响有正有负,三个因素在部门之间又表现出一定的差异性,电力、热力的生产和供应业对间接碳排放影响最大。 根据城市碳排放情况针对性的提出碳排放的分类调控策略。主要针对城市综合能源消耗碳排放和部门直接消耗碳排放以及中间投入过程中间接消耗碳排放,从区域角度、部门角度和综合建议方面进行分类调控。在区域中,对城市综合能源消耗碳排放进行产业结构和能源结构优化及不同区域减排对策来降低城市碳排放量,对城市间接消耗碳排放进行城市出口消费结构优化,加强区域产业联系方面进行减排。在部门中,对部门直接消耗碳排放和中间投入过程中间接消耗碳排放进行工业部门优化及中间投入过程优化。在综合调控中,对不同主体提出一些减排建议。
[Abstract]:More and more countries have paid close attention to reducing CO2 emissions and effectively coping with global climate change. With the further implementation of China's "West Development Strategy", the economy of cities in Guanzhong region has entered a new growth stage. The carbon emissions from regional urban comprehensive energy consumption and industrial energy activities have shown an upward trend, bringing about livelihood. Therefore, this paper studies the urban carbon emission accounting and its classification regulation in Guanzhong area, in order to provide reference for promoting the transformation from "high-carbon economy" to "low-carbon economy" and "high-carbon industry" to "low-carbon industry". At the same time, it also provides a fair distribution of carbon emission reduction responsibilities in small-scale areas and the economy of Guanzhong cities. Provide basis for sustainable development.
According to the comprehensive energy consumption data and the energy consumption data of various industries in Guanzhong from 2000 to 2011, the IPCC Energy Inventory method, grey relational model, input-output model, Gini coefficient, concentration index, response coefficient, induction coefficient and LMDI structural decomposition model were used to analyze the direct and indirect carbon emissions of the cities and their departments in Guanzhong. The main conclusions are as follows:
(1) From 2000 to 2011, the carbon emissions of Xi'an, Xianyang, Weinan and Baoji in Guanzhong region showed an increasing trend, while the intensity of carbon emissions showed a downward trend.
(2) There are regional differences between urban carbon emissions and intensity of carbon emissions in central Shaanxi in 2011. The regional patterns of carbon emissions in four cities are as follows: Xi'an Xianyang Weinan Baoji, and the regional patterns of carbon emissions intensity in four cities are as follows: Baoji Weinan Xianyang Xi'an.
There are some similarities in the correlation between carbon emissions and influencing factors among cities in Guanzhong area, which are shown as follows: economic factors, population factors, energy structure and technological level. Energy efficiency and reduce carbon emissions.
(3) From the regional point of view, the direct and indirect carbon emissions and total carbon emissions of the four cities show regional differences. The direct carbon emissions are: Xi'an Xianyang Weinan Baoji; this is mainly affected by industrial economic development; the indirect carbon emissions are: Wei'nan Xianyang Baoji Xi'an, which is the main one. The total carbon emissions are: Weinan Xianyang Baoji Xi'an, which is mainly due to the differences of carbon emissions caused by the overall economic development and industrial intermediate input.
(4) From the perspective of carbon emissions within the industry sector, there are sectoral differences in direct and indirect carbon emissions between Xi'an and Xianyang in 2011. Concentration index and Gini coefficient show that the two cities have a high degree of concentration of carbon emissions, unbalanced distribution of carbon emissions between sectors, and a large gap between high-carbon industry and low-carbon industry. The departments with higher coefficients of force play a greater role in promoting the development of the whole national economy, the national economy and other departments play a greater role in promoting these sectors, and the indirect carbon emissions are higher.
(5) Factor decomposition model of LMDI shows that indirect carbon emissions are affected by different factors, and there are differences among different sectors. Scale effect has the greatest impact on indirect carbon emissions, followed by intensity effect, and finally structure effect. Increased inhibitory factors, structural effects on indirect carbon emissions have positive and negative effects, and the three factors show some differences among sectors. Electricity, thermal production and supply industries have the greatest impact on indirect carbon emissions.
According to the situation of urban carbon emissions, this paper puts forward the classified control strategy of carbon emissions, mainly aiming at the carbon emissions of urban comprehensive energy consumption, direct sectoral consumption and indirect consumption of carbon emissions in the process of intermediate input. To reduce urban carbon emissions, we should optimize the industrial structure and energy structure of source-consuming carbon emissions, and take measures to reduce carbon emissions in different regions. We should optimize the structure of urban indirect consumption of carbon emissions in urban export and consumption, and strengthen regional industrial links to reduce emissions. Carbon consumption emissions are optimized by industrial sector and intermediate input process. In the comprehensive regulation and control, some suggestions are put forward for different subjects.
【学位授予单位】：陕西师范大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：X321
本文编号：2235669
[Abstract]:More and more countries have paid close attention to reducing CO2 emissions and effectively coping with global climate change. With the further implementation of China's "West Development Strategy", the economy of cities in Guanzhong region has entered a new growth stage. The carbon emissions from regional urban comprehensive energy consumption and industrial energy activities have shown an upward trend, bringing about livelihood. Therefore, this paper studies the urban carbon emission accounting and its classification regulation in Guanzhong area, in order to provide reference for promoting the transformation from "high-carbon economy" to "low-carbon economy" and "high-carbon industry" to "low-carbon industry". At the same time, it also provides a fair distribution of carbon emission reduction responsibilities in small-scale areas and the economy of Guanzhong cities. Provide basis for sustainable development.
According to the comprehensive energy consumption data and the energy consumption data of various industries in Guanzhong from 2000 to 2011, the IPCC Energy Inventory method, grey relational model, input-output model, Gini coefficient, concentration index, response coefficient, induction coefficient and LMDI structural decomposition model were used to analyze the direct and indirect carbon emissions of the cities and their departments in Guanzhong. The main conclusions are as follows:
(1) From 2000 to 2011, the carbon emissions of Xi'an, Xianyang, Weinan and Baoji in Guanzhong region showed an increasing trend, while the intensity of carbon emissions showed a downward trend.
(2) There are regional differences between urban carbon emissions and intensity of carbon emissions in central Shaanxi in 2011. The regional patterns of carbon emissions in four cities are as follows: Xi'an Xianyang Weinan Baoji, and the regional patterns of carbon emissions intensity in four cities are as follows: Baoji Weinan Xianyang Xi'an.
There are some similarities in the correlation between carbon emissions and influencing factors among cities in Guanzhong area, which are shown as follows: economic factors, population factors, energy structure and technological level. Energy efficiency and reduce carbon emissions.
(3) From the regional point of view, the direct and indirect carbon emissions and total carbon emissions of the four cities show regional differences. The direct carbon emissions are: Xi'an Xianyang Weinan Baoji; this is mainly affected by industrial economic development; the indirect carbon emissions are: Wei'nan Xianyang Baoji Xi'an, which is the main one. The total carbon emissions are: Weinan Xianyang Baoji Xi'an, which is mainly due to the differences of carbon emissions caused by the overall economic development and industrial intermediate input.
(4) From the perspective of carbon emissions within the industry sector, there are sectoral differences in direct and indirect carbon emissions between Xi'an and Xianyang in 2011. Concentration index and Gini coefficient show that the two cities have a high degree of concentration of carbon emissions, unbalanced distribution of carbon emissions between sectors, and a large gap between high-carbon industry and low-carbon industry. The departments with higher coefficients of force play a greater role in promoting the development of the whole national economy, the national economy and other departments play a greater role in promoting these sectors, and the indirect carbon emissions are higher.
(5) Factor decomposition model of LMDI shows that indirect carbon emissions are affected by different factors, and there are differences among different sectors. Scale effect has the greatest impact on indirect carbon emissions, followed by intensity effect, and finally structure effect. Increased inhibitory factors, structural effects on indirect carbon emissions have positive and negative effects, and the three factors show some differences among sectors. Electricity, thermal production and supply industries have the greatest impact on indirect carbon emissions.
According to the situation of urban carbon emissions, this paper puts forward the classified control strategy of carbon emissions, mainly aiming at the carbon emissions of urban comprehensive energy consumption, direct sectoral consumption and indirect consumption of carbon emissions in the process of intermediate input. To reduce urban carbon emissions, we should optimize the industrial structure and energy structure of source-consuming carbon emissions, and take measures to reduce carbon emissions in different regions. We should optimize the structure of urban indirect consumption of carbon emissions in urban export and consumption, and strengthen regional industrial links to reduce emissions. Carbon consumption emissions are optimized by industrial sector and intermediate input process. In the comprehensive regulation and control, some suggestions are put forward for different subjects.
【学位授予单位】：陕西师范大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：X321
【参考文献】
相关期刊论文 前10条
1 邵帅;杨莉莉;曹建华;;工业能源消费碳排放影响因素研究——基于STIRPAT模型的上海分行业动态面板数据实证分析[J];财经研究;2010年11期
2 欧阳强;李奇;;湖南省碳排放影响因素的灰色关联分析与预测[J];长沙理工大学学报(社会科学版);2012年01期
3 雷厉;仲云云;袁晓玲;;中国区域碳排放的因素分解模型及实证分析[J];当代经济科学;2011年05期
4 赵冠伟;杨木壮;陈健飞;;1990-2007年中国能源足迹时空差异分析[J];地理与地理信息科学;2011年02期
5 姜磊;季民河;;基于STIRPAT模型的中国能源压力分析——基于空间计量经济学模型的视角[J];地理科学;2011年09期
6 燕华;郭运功;林逢春;;基于STIRPAT模型分析CO_2控制下上海城市发展模式[J];地理学报;2010年08期
7 赵荣钦;黄贤金;钟太洋;;中国不同产业空间的碳排放强度与碳足迹分析[J];地理学报;2010年09期
8 张雷;;中国一次能源消费的碳排放区域格局变化[J];地理研究;2006年01期
9 刘红光;刘卫东;范晓梅;;贸易对中国产业能源活动碳排放的影响[J];地理研究;2011年04期
10 吴宗杰;唐合龙;;我国区域碳减排的实证分析及应对策略研究[J];东岳论丛;2011年06期
，本文编号：2235669
本文链接：https://www.wllwen.com/jingjilunwen/quyujingjilunwen/2235669.html
