關中地區(qū)城市碳排放核算與碳排放分類調控策略研究
發(fā)布時間：2018-09-10 21:31
【摘要】：減少CO2排放,有效應對全球氣候變化已引起越來越多國家的關注。隨著中國“西部大開發(fā)戰(zhàn)略”的進一步實施,關中地區(qū)各城市經濟進入新的增長階段,區(qū)域城市綜合能源消耗和工業(yè)分行業(yè)能源活動帶來的碳排放量呈現(xiàn)上升趨勢,給生態(tài)環(huán)境帶來一定挑戰(zhàn)。因此,本文對關中地區(qū)城市碳排放核算及其分類調控進行研究,以期為促進“高碳經濟”向“低碳經濟”、“高碳行業(yè)”向“低碳行業(yè)”轉變提供參考,同時為小尺度地區(qū)公平分配碳減排責任和關中各城市經濟的持續(xù)發(fā)展提供依據(jù)。 根據(jù)2000-2011年關中各城市綜合能源消耗數(shù)據(jù)和行業(yè)部門能源消耗數(shù)據(jù),采用IPCC能源清單法、灰色關聯(lián)模型、投入產出模型、基尼系數(shù)、集中指數(shù)、響應力系數(shù)、感應力系數(shù)以及LMDI結構分解模型對關中各城市及其部門直接和間接碳排放進行區(qū)域和行業(yè)部門核算及影響機制分析,并有針對性地提出分類調控策略。主要結論包括： (1)2000-2011年關中地區(qū)城市西安、咸陽、渭南、寶雞的碳排放量均呈現(xiàn)出增長的趨勢,同期碳排放強度均呈現(xiàn)下降趨勢。 (2)2011年關中地區(qū)城市碳排放量與碳排放強度存在區(qū)域差異。四個城市碳排放量的區(qū)域格局特征為：西安咸陽渭南寶雞,四個城市碳排放強度的區(qū)域格局特征為：寶雞渭南咸陽西安。 關中地區(qū)各城市碳排放量與影響因素之間的關聯(lián)程度有一定相似之處。表現(xiàn)為：經濟因素人口因素能源結構技術水平。經濟發(fā)展對碳排放的推動作用最大,人均GDP的增加是碳排放量增加的主要因素,技術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)從區(qū)域角度的行業(yè)部門碳排放量來看,四個城市的直接碳排放量和間接碳排放以及完全碳排放量均呈現(xiàn)出區(qū)域差異。直接碳排放為：西安咸陽渭南寶雞；這主要受工業(yè)經濟發(fā)展的影響；間接碳排放為：渭南咸陽寶雞西安,這主要是受區(qū)域經濟聯(lián)系與出口產品的影響；完全碳排放為：渭南咸陽寶雞西安,這主要是因為整體經濟發(fā)展和工業(yè)中間投入引起的碳排放差異。 (4)從行業(yè)部門內部碳排放量來看,2011年西安和咸陽行業(yè)直接碳排放和間接碳排放存在部門差異。集中指數(shù)和基尼系數(shù)顯示兩市的行業(yè)碳排放集中程度較高,碳排放部門間分配不均衡,高碳行業(yè)與低碳行業(yè)差距較大。響應力系數(shù)和感應力系數(shù)較高的部門對整個國民經濟發(fā)展的推動作用較大,國民經濟及其他部門對這些部門的拉動作用也較大,間接碳排放較高。 (5)LMDI因素分解模型顯示行業(yè)間接碳排放受不同影響因素影響程度不同,并且在部門間存在影響差異。規(guī)模效應對間接碳排放影響最大,其次是強度效應,最后是結構效應。規(guī)模效應是間接碳排放增加的主要因素,強度效應是間接碳排放增加的抑制性因素,結構效應對間接碳排放的影響有正有負,三個因素在部門之間又表現(xiàn)出一定的差異性,電力、熱力的生產和供應業(yè)對間接碳排放影響最大。 根據(jù)城市碳排放情況針對性的提出碳排放的分類調控策略。主要針對城市綜合能源消耗碳排放和部門直接消耗碳排放以及中間投入過程中間接消耗碳排放,從區(qū)域角度、部門角度和綜合建議方面進行分類調控。在區(qū)域中,對城市綜合能源消耗碳排放進行產業(yè)結構和能源結構優(yōu)化及不同區(qū)域減排對策來降低城市碳排放量,對城市間接消耗碳排放進行城市出口消費結構優(yōu)化,加強區(qū)域產業(yè)聯(lián)系方面進行減排。在部門中,對部門直接消耗碳排放和中間投入過程中間接消耗碳排放進行工業(yè)部門優(yōu)化及中間投入過程優(yōu)化。在綜合調控中,對不同主體提出一些減排建議。
[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.
【學位授予單位】：陜西師范大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：X321
本文編號：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.
【學位授予單位】：陜西師范大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：X321
【參考文獻】
相關期刊論文 前10條
1 邵帥;楊莉莉;曹建華;;工業(yè)能源消費碳排放影響因素研究——基于STIRPAT模型的上海分行業(yè)動態(tài)面板數(shù)據(jù)實證分析[J];財經研究;2010年11期
2 歐陽強;李奇;;湖南省碳排放影響因素的灰色關聯(lián)分析與預測[J];長沙理工大學學報(社會科學版);2012年01期
3 雷厲;仲云云;袁曉玲;;中國區(qū)域碳排放的因素分解模型及實證分析[J];當代經濟科學;2011年05期
4 趙冠偉;楊木壯;陳健飛;;1990-2007年中國能源足跡時空差異分析[J];地理與地理信息科學;2011年02期
5 姜磊;季民河;;基于STIRPAT模型的中國能源壓力分析——基于空間計量經濟學模型的視角[J];地理科學;2011年09期
6 燕華;郭運功;林逢春;;基于STIRPAT模型分析CO_2控制下上海城市發(fā)展模式[J];地理學報;2010年08期
7 趙榮欽;黃賢金;鐘太洋;;中國不同產業(yè)空間的碳排放強度與碳足跡分析[J];地理學報;2010年09期
8 張雷;;中國一次能源消費的碳排放區(qū)域格局變化[J];地理研究;2006年01期
9 劉紅光;劉衛(wèi)東;范曉梅;;貿易對中國產業(yè)能源活動碳排放的影響[J];地理研究;2011年04期
10 吳宗杰;唐合龍;;我國區(qū)域碳減排的實證分析及應對策略研究[J];東岳論叢;2011年06期
，本文編號：2235669
本文鏈接：http://sikaile.net/jingjilunwen/quyujingjilunwen/2235669.html
最近更新
教材專著
