基于DEA模型中國各省工業(yè)能源效率與節(jié)能減排分析
本文關(guān)鍵詞: 工業(yè)部門 能源效率 節(jié)能減排 DEA模型 Malmquist指數(shù) 出處:《天津大學(xué)》2014年碩士論文 論文類型:學(xué)位論文
【摘要】:工業(yè)化的推進極大促進了我國經(jīng)濟、社會的發(fā)展。在2010年,中國超越日本成為世界第二大經(jīng)濟體。然而,在巨大的發(fā)展成就背后,經(jīng)濟發(fā)展與資源供給、生態(tài)環(huán)境之間的矛盾正日益嚴重。中國已成為世界上最大的二氧化碳排放與能源消費國家。面對日益嚴峻的碳減排壓力,中國政府已經(jīng)認識到目前的發(fā)展方式難以維持經(jīng)濟的穩(wěn)定增長。工業(yè)部門是我國最大的能源消耗終端部門,同時也是最大的碳排放部門。在2007-2009年間,工業(yè)部門的能源消耗一直占到能源消耗總量的70%左右。因此,控制工業(yè)部門的能源消耗以及二氧化碳排放則是我國目前提高能源效率以及節(jié)能減排工作的關(guān)鍵所在。本文以中國30個省市的工業(yè)部門為研究對象,構(gòu)建一非徑向DEA模型衡量各地區(qū)2004至2011年間的工業(yè)能源效率狀況。在研究過程中,從靜態(tài)能源效率與動態(tài)能源效率兩個角度進行了相關(guān)分析。在了解各地區(qū)樣本期間的能源效率狀況后,又從能源結(jié)構(gòu)調(diào)整的角度,探究決策制定單元的能源節(jié)約與二氧化碳減排的潛力。研究結(jié)果表明:在2004至2011年間,全國的工業(yè)能源效率水平不高。并且工業(yè)部門的能源效率存在明顯的區(qū)域差異性。無論是從評價結(jié)果有效的地區(qū)數(shù)、還是樣本期間的效率平均值,東部地區(qū)的能源效率狀況都明顯好于中、西部地區(qū)。這與我國目前的工業(yè)發(fā)展現(xiàn)狀也是一致的。在運用Malmquist指數(shù)方法對各地區(qū)動態(tài)能源效率進行研究過程中,在樣本期間內(nèi),中國工業(yè)部門的能源效率持續(xù)保持上升的趨勢,工業(yè)部門的能源效率都發(fā)生著積極的變化。就具體增速而言,中部地區(qū)的能源效率改善的程度最高。在研究能源結(jié)構(gòu)調(diào)整對于降低能源消耗減少二氧化碳排放的作用時,發(fā)現(xiàn):降低煤炭資源在總能源消耗中的比例可以有效減少各類能源消耗以及降低二氧化碳的排放量。但是,能源結(jié)構(gòu)調(diào)整是一長期的過程,為了使能源結(jié)構(gòu)調(diào)整達到更好的效果,需要同時提高各類能源的運輸能力。
[Abstract]:In 2010, China overtook Japan to become the second largest economy in the world. However, behind the tremendous development achievements, economic development and resource supply. The contradiction between ecological environment is becoming more and more serious. China has become the largest carbon dioxide emission and energy consumption country in the world. The Chinese government has recognized that the current development approach is difficult to sustain steady economic growth. The industrial sector is the country's largest energy consumption terminal sector and also the largest carbon emission sector. In 2007-2009, Energy consumption in the industrial sector has always accounted for about 70% of the total energy consumption. Controlling the energy consumption and carbon dioxide emission in the industrial sector is the key to improving energy efficiency and energy saving and emission reduction in China. This paper takes the industrial sector of 30 provinces and cities in China as the research object. A non-radial DEA model was constructed to measure the industrial energy efficiency in various regions from 2004 to 2011. This paper analyzes the correlation between static energy efficiency and dynamic energy efficiency. After understanding the energy efficiency of each region during the sample period, it also analyzes the energy structure from the perspective of energy structure adjustment. Explore the potential for energy conservation and carbon dioxide emissions reduction in decision making units. The results show that between 2004 and 2011, The level of industrial energy efficiency in China is not high, and there are obvious regional differences in energy efficiency in the industrial sector. Whether from the number of regions where the evaluation results are valid, or from the average efficiency of the sample period, The energy efficiency in the eastern region is obviously better than that in the central and western regions. This is consistent with the present industrial development situation in China. In the course of studying the dynamic energy efficiency in each region by using the Malmquist index method, during the sample period, The energy efficiency of China's industrial sector continues to maintain an upward trend, and there are positive changes in the energy efficiency of the industrial sector. The central region has seen the greatest improvement in energy efficiency. In studying the role of energy restructuring in reducing energy consumption and reducing carbon dioxide emissions, It is found that reducing the proportion of coal resources in total energy consumption can effectively reduce all kinds of energy consumption and reduce carbon dioxide emissions. However, energy restructuring is a long-term process. In order to achieve better effect of energy structure adjustment, it is necessary to improve the transportation capacity of all kinds of energy at the same time.
【學(xué)位授予單位】:天津大學(xué)
【學(xué)位級別】:碩士
【學(xué)位授予年份】:2014
【分類號】:X322;F424
【參考文獻】
相關(guān)期刊論文 前8條
1 劉曉月;;我國霧霾天氣現(xiàn)狀與綜合治理分析[J];科技風(fēng);2014年13期
2 黃德春;董宇怡;張長征;劉炳勝;;基于三階段DEA模型中國區(qū)域能源效率研究(英文)[J];Journal of Resources and Ecology;2014年02期
3 趙露;方鵬騫;;我國省域衛(wèi)生資源利用效率的Malmquist跨期分析[J];中國衛(wèi)生經(jīng)濟;2013年02期
4 魏新強;張寶生;;反向思維的定權(quán)重DEA中國能源效率分析[J];技術(shù)經(jīng)濟與管理研究;2013年01期
5 黃森;蒲勇健;;基于三階段Malmquist模型的我國服務(wù)業(yè)效率研究[J];山西財經(jīng)大學(xué)學(xué)報;2011年07期
6 林伯強;姚昕;劉希穎;;節(jié)能和碳排放約束下的中國能源結(jié)構(gòu)戰(zhàn)略調(diào)整[J];中國社會科學(xué);2010年01期
7 李世祥;成金華;;中國能源效率評價及其影響因素分析[J];統(tǒng)計研究;2008年10期
8 王慶一;中國的能源效率及國際比較(上)[J];節(jié)能與環(huán)保;2003年08期
,本文編號:1497714
本文鏈接:http://sikaile.net/jingjilunwen/gongyejingjilunwen/1497714.html