【摘要】：全球變暖已成為當前人類面臨的嚴重環(huán)境問題。目前國際社會已經(jīng)普遍認為人類活動產(chǎn)生的溫室氣體特別是C02是導致全球變暖的主要原因。隨著經(jīng)濟社會的發(fā)展、城市化進程的加快以及人民生活水平的提高,居民家庭生活碳排放量不斷增加。相關(guān)研究表明,居民家庭和個人消費行為的改變,有助于減少碳排放,促使碳排放結(jié)構(gòu)更加合理,家庭生活領(lǐng)域有巨大的減排潛力。分析碳排放影響因素,通過限制某個或某些因素,可以有效減少碳排放。本文利用國家統(tǒng)計數(shù)據(jù),評估了1995-2012年西北地區(qū)(陜西、甘肅、青海、寧夏、新疆)家庭碳排放的基本狀況,基于STIRPAT模型的擴展模型,結(jié)合嶺回歸擬合,對西北地區(qū)家庭碳排放的影響因素進行了實證研究。本文主要做了以下幾個方面的工作：(1)評估1995-2012年西北地區(qū)家庭生活碳排放的基本狀況。從家庭碳排放總量、人均家庭碳排放量、直接間接碳排放量、家庭碳排放結(jié)構(gòu)等角度入手對西北地區(qū)整體及五省之間的生活碳排放進行了分析。結(jié)果顯示：西北地區(qū)家庭碳排放總量在1995-2012年間增加了2.82倍,人均家庭碳排放量增加了2.36倍；西北五省之間家庭碳排放總量的差距始終較大,但人均家庭碳排放的差距卻逐漸減��；間接碳排放在排放總量中所占比重持續(xù)上升,人均間接碳排放已遠高于人均直接碳排放；家庭碳排放重點從煤炭排放轉(zhuǎn)移為電力和食品排放。(2)基于STIRPAT模型的擴展模型,對1995-2012年西北地區(qū)家庭碳排放的影響因素進行了實證研究。結(jié)果表明,1995-2012年西北地區(qū)家庭碳排放的各影響因素按其影響程度從大到小依次為：人均GDP(20.26%)、家庭碳排放強度(17.38%)、人均消費支出(11.51%)、城鎮(zhèn)化率(10.75%)、家庭規(guī)模(-10.18%)、勞動年齡人口比重(9.61%)、大專以上文化程度人口比重(9.43%)、人口總量(5.36%)。其中,家庭規(guī)模對家庭碳排放的影響是負向的。(3)基于STIRPAT模型的擴展模型,對1995-2012年陜西、甘肅、青海、寧夏、新疆各省家庭碳排放的影響因素進行了分析。結(jié)果發(fā)現(xiàn),人均GDP(20.62%)、家庭碳排放強度(17.35%)、人均消費支出(12.23%)是影響陜西家庭碳排放的主要因素；人均GDP(18.22%)、家庭規(guī)模(-15.13%)、家庭碳排放強度(14.9%)是影響甘肅家庭碳排放的主要因素；家庭碳排放強度(18.47%)、城鎮(zhèn)化率(14.86%)、人均消費支出(12.83%)是影響青海家庭碳排放的主要因素；人均GDP(17.06%)、人均消費支出(12.92%)、勞動年齡人口比重(12.55%)是影響寧夏家庭碳排放的主要因素；家庭碳排放強度(28.25%)、人均GDP(16.63%)、人均消費支出(14.37%)是影響新疆家庭碳排放的主要因素。
[Abstract]:Global warming has become a serious environmental problem faced by human beings. At present, the international community has generally believed that greenhouse gases, especially CO2, are the main causes of global warming. With the development of economy and society, the acceleration of urbanization and the improvement of people's living standards, the carbon emissions from household life are increasing. Relevant studies have shown that the change of household and personal consumption behavior is helpful to reduce carbon emissions, promote a more reasonable structure of carbon emissions, and has great potential to reduce emissions in the field of household life. By analyzing the influencing factors of carbon emissions, carbon emissions can be effectively reduced by limiting one or some factors. Based on the national statistical data, this paper evaluates the basic situation of household carbon emissions in Northwest China from 1995 to 2012 (Shaanxi, Gansu, Qinghai, Ningxia, Xinjiang). Based on the extended model of STIRPAT model, combined with ridge regression fitting, This paper makes an empirical study on the influencing factors of household carbon emissions in Northwest China. The main work of this paper is as follows: (1) to evaluate the basic situation of carbon emissions from household life in Northwest China from 1995 to 2012. From the point of view of total household carbon emissions, per capita household carbon emissions, direct and indirect carbon emissions, household carbon emission structure and so on, this paper analyzes the domestic carbon emissions in Northwest China as a whole and among the five provinces. The results show that the total household carbon emissions in Northwest China increased by 2.82 times in 1995 / 2012, and the per capita household carbon emissions increased by 2.36 times. The gap of total household carbon emissions between the five provinces of Northwest China is always large, but the gap of per capita household carbon emissions is gradually decreasing. The proportion of indirect carbon emissions in the total emissions continues to rise, and the per capita indirect carbon emissions are much higher than the per capita direct carbon emissions. The focus of household carbon emissions from coal emissions to electricity and food emissions. (2) based on the extended model of STIRPAT model, this paper makes an empirical study on the influencing factors of household carbon emissions in Northwest China from 1995 to 2012. The results showed that the influencing factors of household carbon emissions in Northwest China from 1995 to 2012 were as follows: per capita GDP (20.26%), household carbon emission intensity (17.38%), per capita consumption expenditure (11.51%). Urbanization rate (10.75%), family size (- 10.18%), proportion of working-age population (9.61%), proportion of population with higher educational level (9.43%), total population (5.36%). Among them, the influence of household size on household carbon emissions is negative. (3) based on the extended model of STIRPAT model, the influencing factors of household carbon emissions in Shaanxi, Gansu, Qinghai, Ningxia and Xinjiang provinces from 1995 to 2012 are analyzed. The results showed that per capita GDP (20.62%), household carbon emission intensity (17.35%) and per capita consumption expenditure (12.23%) were the main factors affecting household carbon emissions in Shaanxi. Per capita GDP (18.22%), household size (- 15.13%) and household carbon emission intensity (14.9%) were the main factors affecting household carbon emissions in Gansu Province. The intensity of household carbon emissions (18.47%), urbanization rate (14.86%) and per capita consumption expenditure (12.83%) are the main factors affecting household carbon emissions in Qinghai. Per capita GDP (17.06%), per capita consumption expenditure (12.92%) and proportion of working-age population (12.55%) were the main factors affecting household carbon emissions in Ningxia. Household carbon emission intensity (28.25%), per capita GDP (16.63%) and per capita consumption expenditure (14.37%) are the main factors affecting household carbon emissions in Xinjiang.
【學位授予單位】：蘭州大學
【學位級別】：碩士
【學位授予年份】：2015
【分類號】：X321

【參考文獻】

相關(guān)期刊論文 前8條

1 朱勤;彭希哲;陸志明;于娟;;1980—2007年中國居民生活用能碳排放測算與分析[J];安全與環(huán)境學報;2010年02期

2 張志強;曾靜靜;曲建升;;世界主要國家碳排放強度歷史變化趨勢及相關(guān)關(guān)系研究[J];地球科學進展;2011年08期

3 曲建升;張志強;曾靜靜;李燕;王勤花;邱巨龍;劉莉娜;董利蘋;唐霞;;西北地區(qū)居民生活碳排放結(jié)構(gòu)及其影響因素[J];科學通報;2013年03期

4 黃宜;趙光洲;王艷偉;;基于STIRPAT模型的能源消費碳排放影響因素研究——以云南省為例[J];價值工程;2013年32期

5 鳳振華;鄒樂樂;魏一鳴;;中國居民生活與CO_2排放關(guān)系研究[J];中國能源;2010年03期

6 陳佳瑛;彭希哲;朱勤;;家庭模式對碳排放影響的宏觀實證分析[J];中國人口科學;2009年05期

7 李科;;我國城鄉(xiāng)居民生活能源消費碳排放的影響因素分析[J];消費經(jīng)濟;2013年02期

8 李治;李培;郭菊娥;曾先峰;;城市家庭碳排放影響因素與跨城市差異分析[J];中國人口.資源與環(huán)境;2013年10期

，

本文編號：2485855