能源消费CO2排放研究综述

doi:10.11820/dlkxjz.2015.02.004

摘要/Abstract

摘要：

气候变化已成为当前国际社会所关注的热点问题,而CO₂排放是影响全球变暖的主要因素。本文基于多学科视角,综合运用文献资料法、对比分析法,梳理了CO₂排放的估算方法、排放强度、排放绩效、排放影响因素和未来排放模拟方法的研究进展,分析了存在的主要问题,并展望了下一步的研究重点与方向。结果表明,CO₂排放研究发展迅速并且成果丰富,CO₂排放是不同因素众多变量之间相互作用、相互依赖的一个综合复杂的系统工程;多学科融合框架下地理与空间因素重视不足,研究尺度以全球化、国际化为主,多尺度研究逐步凸显并开始关注尺度效应,但省级、城市尺度的面板研究仍匮乏;面板数据逐步受到关注,动态分析对比评价仍待完善。未来研究在变量选取上应更加全面细化,尝试多尺度综合分析,逐步凸显城市碳排放研究,需更加关注理论结合本地化实践,运用系统的思维和方法掌握差异化趋势研究。

关键词: CO2排放, 估算方法, 排放强度, 排放绩效, 影响因素, 预测与模拟

Abstract:

Climate change has in recent years become an environmental issue globally. Through deepening research into and analysis of the phenomenon, most climate scientists now identify greenhouse gases, most notably CO₂ emissions, as constituting the main cause of global warming. Based on literature study and comparative analysis, this article discusses the progress of the research of CO₂ emissions from a multidisciplinary perspective and analyzes the calculation methods, intensity, performance, influencing factors, and forecasting methods of CO₂emissions. This article also discusses the remaining issues and future directions of the research on CO₂ emissions. Results indicate that the research of CO₂ emissions has gained fruitful achievements and has experienced rapid development in recent years. CO₂ emission is an integrated, complex, interdependent system engineering of numerous variables interplay between different factors. Under the framework of multidisciplinary integration, geographical and spatial factors have however received insufficient attention. Research scale has mainly focused on global and international levels, although recent studies have begun to highlight multi-scale research and pay attention to scale effect. Panel study of provincial and city scales is still scarce. Panel data are gradually receiving attention; however, dynamic analysis and comparative assessment still need improvement. Future research should focus on creating more detailed and comprehensive datasets, exploring multi-scale integrated research, and highlighting city scale analysis. Furthermore, future study should emphasize adapting theories to localized practices, employing systemic thinking and methods for differentiated trend research.

Key words: carbon emission calculation, carbon emission intensity, carbon emission performance, influencingfactors, forecasting and simulation

王少剑, 刘艳艳, 方创琳. 能源消费CO₂排放研究综述[J]. 地理科学进展, 2015, 34(2): 151-.

Shaojian WANG, Yanyan LIU, Chuanglin FANG. Review of energy-related CO₂ emission in response to climate change[J]. PROGRESS IN GEOGRAPHY, 2015, 34(2): 151-.

图/表 6

图1

表1

图2

表2

投入产出表基本形式"

		中间产品	最终需求	总产出
		$1, 2, … n$
中间投入	1 2 $?$ n	中间产品流量	最终产品	总产品
最初投入		最初投入
总产出		总产出
能源投入	1 2 $?$ m	各部门各类能源投入量	最终需求领域的各类能源投入量	能源投入总量
碳排放	1 2 $?$ k	各部门碳排放量	最终需求领域的各类碳排放量	碳排放总量

表2

表3

表4

CO2排放影响因素计算方法一览表"

名称	基本公式	描述及评价
IPAT模型	$I = Pop (P) × Aff ? (A) × Tec ? (T)$	I表示影响评价,Pop表示人口,Aff表示富裕度,Tec表示科技进步。IPAT模型格式简洁,最初被用于环境影响评价,后经逐步改进,广泛引用于测度CO₂排放影响因素分析中。
STIRPAT模型	$ln I it = a 0 + a 1 ln A it + a 2 (ln A it) 2 + a 3 (ln A it) 3 + a 4 ln P it + a 5 ln T it + ?$	STIRPAT模型是IPAT模型的扩展形式,由于IPAT模型的原始设定只含3个影响因素,有一定的局限性,后经改进引入新的变量,扩展了IPAT模型,同时还可以进一步验证CO₂(I)排放与经济发展(ln²A)的库茨涅茨（Kuznets）假设。
IDA指数分解模型	$I = Pop × GDP Pop × GD P IND GDP × ENE GD P IND × I ENE$	I表示CO₂排放,Pop表示人口,GDP表示国内生产总值,GDP_IND表示产业增加值,ENE表示能源消费,GDP/Pop表示人均GDP,GDP_IND/GDP表示产业份额,ENE/GDP_IND表示能源强度,I/ENE表示碳排放强度。该方法在能源经济学与环境经济学中广泛用于分解能源强度、能源消耗量、碳排放量的背后因素。
LMDI模型	$C = P × (Y / P) × (E / Y) × (C / E)$	C表示碳排放,P表示人口,Y/P表示人均GDP,E/Y表示能源消费强度,C/E表示能源结构强度。该模型原理和指数分解模型有相似之处,也是分解模型的一种。LMDI方法具有技术成熟、形式多样、计算方便、分解无残差等优点,已广泛应用于CO₂排放及其效应的分解。
AWD方法	$G t = C t Y t = C t E t E t Y t = I t ∑ j = 1 n C jt E jt E jt E t ? ? ? ? ? ? ? ? = I t ∑ j = 1 n e jt R jt$	G表示碳排放强度,C表示碳排放,Y表示GDP,E表示能源消费,I表示能源强度,t表示年份,j表示能源类型。该方法也是一种指数分解方法的一种,相比于Laspeyres指数分解和Marshall-Edgeworth指数分解,AWD方法可以更好的获得变量的参数值。
GFI方法	$D X j = ∏ V (S) V (S) / j 1 n × 1 n - 1 s ′ - 1 ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? = ∏ V (S) V (S) / j s ′ - 1! n - s ′! n!$	$D X j$ 表示碳排放强度, V表示总量指标,i表示总量指标的次级分类,n表示分量个数,S表示{1,2,3…,n}的一个子集,s^,为S的势。现在,关于碳排放因素测度常用方法有Laspeyres指数分解和Divisia 指数分解等。但当指数分解存在残差项时,碳排放变动的部分不能为以上模型所解释。而广义费雪指数(GFI)方法可克服以上缺陷,能更好的消除分解的残差项,得到的结果更加精确。
投入产出结构分解模型	$c = f (I - A) - 1 xY$	c为能源消费碳排放向量,f为部门直接碳排放行向量,I为强度矩阵,A为投入系数矩阵,Y为最终需求矩阵, $(I - A) - 1$ 列昂惕夫逆矩阵。投入产出结构分解分析模型是定量分析国民经济各部门之间相互依赖关系有力的工具,可考察国民经济运行中中间产品消费导致的碳排放水平;在投入产出分析框架上加入能源等环境因素,建立“经济—能源”投入产出结构分解模型。
Kaya等式	$GHG = GHG TOE × TOE GDP × GDP POP × POP ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? = f × e × g × p$	GHG表示温室气体排放,TOE表示能源消费量,GDP表示经济规模,POP表示人口规模,f表示能源结构强度,e表示能源消费强度,g表示人均GDP,p表示人口规模。Kaya恒等式最初由日本学者Kaya提出,是目前分析碳排放驱动因素的主流分析方法,在解释全球历史排放变化原因方面具有重要的作用,并具有数学形式简单、分解无残差、对碳排放变化推动因素解释力强等优点,但也存在局限性：只能解释流量变化,无法解释存量变化;驱动因素多为表象因素,对总量的实际影响难以确定等。
计量经济模型	$y it = α i + β 1 i x 1 i, t + β 2 i x 2 i, t + ? β Mi x Mi, t + e it$	y表示碳排放,x表示碳排放影响因素,α表示截距,β表示相应系数,i表示横截面个数,t表示时间,M表示碳排放影响因素个数。面板数据模型通常涵盖静态模型、动态模型、单位根和协整和因果关系分析,受限因变量、变系数模型和随机前沿模型。其与传统的时间序列和截面数据模型相比,优点为：可扩大信息量,增加估计和检验统计量的自由度;有助于提供动态分析的可靠性;有助于反映经济结构、经济制度的渐进性变化;有助于反映经济体的结构性特征。

表4

参考文献 113

1	邓吉祥, 刘晓, 王铮. 2014. 中国碳排放的区域差异及演变特征分析与因素分解[J]. 自然资源学报, 29(2): 189-200.
	[Deng J X, Liu X, Wang Z.2014. Characteristics analysis and factor decomposition based on the regional difference changes in China's CO2 emission[J]. Journal of Natural Resources, 29(2): 189-200.]
2	范英, 张晓兵, 朱磊. 2010. 基于多目标规划的中国二氧化碳减排的宏观经济成本估计[J]. 气候变化研究进展, 6(2): 130-135.
	[Fan Y, Zhang X B, Zhu L.2010. Estimating the macroeconomic cost of CO2 emission abatement in China based on multi-objective programming[J]. Advances in Climate Change Research, 6(2): 130-135.]
3	冯相昭, 邹骥. 2008. 中国CO2排放趋势的经济分析[J]. 中国人口·资源与环境, 18(3): 43-47.
	[Feng X Z, Zou J.2008. Economic analysis of CO2 emission trends in China[J]. China Population, Resources and Environment, 18(3): 43-47. ]
4	高鹏飞, 陈文颖, 何建坤. 2004. 中国的二氧化碳边际减排成本[J]. 清华大学学报: 自然科学版, 44(9): 1192-1195.
	[Gao P F, Chen W Y, He J K.2004. Marginal carbon abatement cost in China. Journal of Tsinghua University:(Science and Technology), 44(9): 1192-1195.]
5	高树婷, 张慧琴, 杨礼荣, 等. 1994. 我国温室气体排放量估测初探[J]. 环境科学研究, 7(6): 56-59.
	[Gao S T, Zhang H Q, Yang L R, et al.Forecast method and countermeasures for greenhouse gases in China[J]. Environmental Science Research, 7(6): 56-59.]
6	关海玲, 陈建成, 曹文. 2013. 碳排放与城市化关系的实证[J]. 中国人口·资源与环境, 23(4): 111-116.
	[Guan H L, Chen J C, Cao W.2013. Empirical study on the relationship between carbon emission and urbanization[J]. China Population, Resources and Environment, 23(4): 111-116.]
7	何介南, 康文星. 2008. 湖南省化石燃料和工业过程碳排放的估算[J]. 中南林业科技大学学报, 28(5): 52-58.
	[He J N, Kang W X.2008. Estimation of carbon emissions from fossil fuel and industrial production from 2000 to 2005 in Hunan Province[J]. Journal of Central South University of Forestry and Technology, 28(5): 52-58.]
8	霍金炜, 杨德刚, 唐宏. 2012. 新疆碳排放影响因素分析与政策建议[J]. 地理科学进展, 31(4): 435-441.
	[Huo J W, Yang D G, Tang H.2012. Empirical study and decomposition model analysis of carbon emissions in Xinjiang[J]. Progress in Geography, 31(4): 435-441.]
9	李广东, 方创琳. 2013. 中国区域经济增长差异研究进展与展望[J]. 地理科学进展, 32(7): 1102-1112.
	[Li G D, Fang C L.2013. A Review on divergence of regional economic growth in China[J]. Progress in Geography, 32(7): 1102-1112.
10	李健, 周慧. 2012. 中国碳排放强度与产业结构的关联分析[J]. 中国人口·资源与环境, 22(1): 7-14.
	[Li J, Zhou H.2012. Correlation analysis of carbon emission intensity and industrial structure in China[J]. China Population, Resources and Environment, 22(1): 7-14.]
11	李志鹏. 2011. 基于系统动力学的城市交通能源消耗与碳排放预测[D]. 天津:天津大学.
	[Li Z P.2011. The forecast of the energy consumption and carbon emission of urban traffic based on system dynamics-an empirical analysis on Tianjin[D]. Tianjin, China: Tianjin University]
12	刘广为, 赵涛. 2012. 中国碳排放强度影响因素的动态效应分析[J]. 资源科学, 34(11): 2106-2114.
	[Liu G W, Zhao T.2012. Influencing factors and dynamic effect analysis of China's carbon emission intensity[J]. Resources Science, 34(11): 2106-2114.]
13	刘明磊, 朱磊, 范英. 2011. 我国省级碳排放绩效评价及边际减排成本估计: 基于非参数距离的方法[J]. 中国软科学, (3): 106-114.
	[Liu M L, Zhu L, Fan Y, et al.2011. Evaluation of carbon emission performance and estimation of marginal CO2 abatement costs for provinces of China: a non-parametric distance function approach[J]. China Soft Science, (3): 106-114.]
14	刘亦文. 2013. 能源消费、碳排放与经济增长的可计算一般均衡分析[D]. 长沙:湖南大学.
	[Liu Y W.2013. The simulation research and policy choice of energy consumption, carbon emissions and economic growth: a dynamic CGE approach[D]. Changsha, China: Hunan University.]
15	刘竹, 耿涌, 薛冰, 等. 2011. 城市能源消费碳排放核算方法[J]. 资源科学, 33(7): 1325-1330.
	[Liu Z, Geng Y, Xue B, et al.2011. A calculation method of CO2 emission from urban energy consumption[J]. Resources Science, 33(7): 1325-1330.]
16	潘家华, 张丽峰. 2011. 我国碳生产率区域差异性研究[J]. 中国工业经济, (5): 47-57.
	[Pan J H, Zhang L F.2011. Research on the regional variation of carbon productivity in China[J]. China Industrial Economics, (5): 47-57.]
17	秦波, 刘志林. 2013. 城市形态与低碳城市[J]. 国际城市规划, 28(2): 1-3.
	[Qin B, Liu Z L.Urban form and low-carbon cities[J]. Urban Planning International, 28(2): 1-3]
18	石敏俊, 王妍, 张卓颖, 等. 2012. 中国各省区碳足迹与碳排放空间转移[J]. 地理学报, 67(10): 1327-1338.
	[Shi M J, Wang Y, Zhang Z Y, et al.2012. Regional carbon footprint and interregional transfer of carbon emissions in China[J]. Acta Geographica Sinica, 67(10): 1327-1338]
19	孙昌龙, 靳诺, 张小雷, 等. 2013. 城市化不同演化阶段对碳排放的影响差异[J]. 地理科学, 33(3): 266-272.
	[Sun C L, Jin N, Zhang X L, et al.2013. The impact of urbanization on the CO2 emission in the various development stages[J]. Scientia Ageographica Sinica. 33(3): 266-272.]
20	孙建卫, 陈志刚, 赵荣钦, 等. 2010. 基于投入产出分析的中国碳排放足迹研究[J]. 中国人口·资源与环境, 20(5): 28-34.
	[Sun J W, Chen Z G, Zhao R Q, et al.2010. Research on carbon emission footprint of China based on input-output model[J]. China Population, Resources and Environment, 20(5): 28-34.]
21	唐志鹏, 刘卫东, 刘红光, 等. 2009. 基于投入产出技术的中国部门生产链平均能耗[J]. 地理科学进展, 28(6): 919-925.
	[Tang Z P, Liu W D, Liu H G, et al.Research on China's average energy consumption of production chain based on input-output technique[J]. Progress in Geography, 28(6): 919-925.]
22	田立新, 张蓓蓓. 2011. 中国碳排放变动的因素分解分析[J]. 中国人口·资源与环境, 21(11): 1-7.
	[Tian L X, Zhang B B.2011. Factor decomposition analysis of carbon emissions change in China[J]. China Population, Resources and Environment, 21(11): 1-7.]
23	汪刚, 冯霄. 2006. 基于能量集成的CO2减排量的确定[J]. 化工进展, 25(12): 1467-1470.
	[Wang G, Feng X.2006. CO2 emission reduction through energy integration[J]. Chemical Industry and Engineering Progree, 25(12): 1467-1470.]
24	王雷. 2014. 基于投入产出模型的天津市碳排放预测研究[J]. 生态经济, 30(1): 51-56.
	[Wang L.2014. Prediction of carbon emissions in Tianjin based on the input-output model[J]. Ecological Economy, 30(1): 51-56.]
25	王群伟, 周鹏, 周德群. 2010. 我国二氧化碳排放绩效的动态变化、区域差异及影响因素[J]. 中国工业经济, 262: 45-54.
	[Wang Q W, Zhou P, Zhou D Q.2010. Research on dynamic carbon dioxide emissions performance, regional disparity and affecting factors in China[J]. China Industrial Economics, 262: 45-54.]
26	王伟林, 黄贤金. 2008. 区域碳排放强度变化的因素分解模型及实证分析: 以江苏省为例[J]. 生态经济, (12): 32-35.
	[Wang W L, Huang X J.Decompositions model of factors and substantiation analysis of area carbon dioxide emissions intensity change: taking Jiangsu Province as an example[J]. Ecological Economy, (12): 32-35.]
27	魏一鸣, 刘兰翠, 范英, 等. 2008. 中国能源报告2008: 碳排放研究[M]. 北京: 科学出版社.
	[Wei Y M, Liu L C, Fan Y, et al.2008. Energy report in china(2008): research on CO2 emissions [M]. Beijing, China: Science Press.]
28	武红, 谷树忠, 关兴良, 等. 2013. 中国化石能源消费碳排放与经济增长关系研究[J]. 自然资源学报, 28(3): 381-390.
	[Wu H, Gu S Z, Guan X L, et al.2013. Analysis on relationship between carbon emissions from fossil energy consumption and economic growth in China[J]. Journal of Natural Resources, 28(3): 381-390.]
29	徐国泉, 刘则渊, 姜照华. 2006. 中国碳排放的因素分解模型及实证分析: 1995-2004[J]. 中国人口·资源与环境, 16(6): 158-161.
	[Xu G Q, Liu Z Y, Jiang Z H.2006. Decomposition model and empirical study of carbon emission for China, 1995-2004[J]. China Population, Resources and Environment, 16(6): 158-161]
30	许士春, 习蓉, 何正霞. 2012. 中国能源消耗碳排放的影响因素分析及政策启示[J]. 资源科学, 34(1): 2-12.
	[Xu S C, Xi R, He Z X.2012. Influential factors and policy implications of carbon emissions for energy consumption in China[J]. Resources Science, 34(1): 2-12.]
31	袁路, 潘家华. 2013. Kaya恒等式的碳排放驱动因素分解及其政策含义的局限性[J]. 气候变化研究进展, 9(3): 2l0-215.
	[Yuan L, Pan J H.2013. Disaggregation of carbon emission drivers in Kaya identity and its limitations with regard to policy implications[J]. Advances in Climate Change Research, 9(3): 210-215.]
32	张征华, 彭迪云. 2013. 中国二氧化碳排放影响因素实证研究综述[J]. 生态经济, (6): 50-54.
	[Zhang Z H, Peng D Y.2013. Review on the empirical research on the impact factors of China's carbon dioxide emissions[J]. Ecological Economy, (6): 50-54.]
33	赵荣钦, 黄贤金, 彭补拙. 2012. 南京城市系统碳循环与碳平衡分析[J]. 地理学报, 67(6): 758-770.
34	[Zhao R Q, Huang X J, Peng B Z.2012. Research on carbon cycle and carbon balance of Nanjing urban system. Acta Geographica Sinica, 67(6): 758-770.
35	赵荣钦, 黄贤金, 钟太洋. 2010. 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, 65(9): 1048-1057.
	[Zhao R Q, Huang X J, Zhong T Y.2010. Research on carbon emission intensity and carbon footprint of different industrial spaces in China[J]. Acta Geographica Sinica, 65(9): 1048-1057.]
36	赵雲泰, 黄贤金, 钟太洋, 等. 2011. 1999-2007年中国能源消费碳排放强度空间演变特征[J]. 环境科学, 32(11): 3145-3152.
	[Zhao Y T, Huang X J, Zhong T X, et al.2011. Spatial pattern evolution of carbon emission intensity from energy consumption in China[J]. Environmental Science, 32(11): 3145-3152.]
37	郑长德, 刘帅. 2011. 基于空间计量经济学的碳排放与经济增长分析[J]. 中国人口·资源与环境, 21(5): 80-86.
	[Zheng C D, Liu S.2011. Empirical research of carbon emission and economic growth in China based on the spatial econometric analysis[J]. China Population, Resources and Environment, 21(5): 80-86.]
38	Al-mulali U.2012. Factors affecting CO2 emission in the Middle East: a panel data analysis[J]. Energy, 44(1): 564-569.
39	Ang B W.1999. Is the energy intensity a less useful indicator than the carbon factor in the study of climate change[J].Energy Policy, 27(15): 943-6.
40	Ang B W.2005. The LMDI approach to decomposition analysis: a practical guide. Energy Policy, 33(9): 867-871.
41	Ang B W, Liu F L, Chung H S.2004. A generalized fisher index approach to energy decomposition analysis[J]. Energy Economics, 26(5): 757-763.
42	Ang B W, Pandiyan G.1997. Decomposition of energy-related CO2 emissions in manufacturing[J]. Energy Economics, 19(3): 363-374.
43	Becker R A.2005. Air pollution abatement costs under the clean air act: evidence from the PACE survey[J]. Journal of Environmental Economics and Management, 50(1): 144-169.
44	Beinhocker E, Oppenheim J, Irons B, et al.2008. The carbon productivity challenge: curbing climate change and sustaining economic growth[M]. Washington, DC: McKinsey Global Institute.
45	Brown M A, Southworth F, Sarzynski A.2009. The geography of metropolitan carbon footprints[J]. Policy and Society, 27(4): 285-304.
46	Cai W J, Wang C, Wang K, et al.2007. Scenario analysis on CO2 emissions potential in China's electricity sector[J]. Energy Policy, 35(12): 6445-6456.
47	Cheng Y Q, Wang Z Y, Ye X Y, et al.2014. Spatiotemporal dynamics of carbon intensity from energy consumption in China[J]. Journal of Geographical Sciences, 24(4): 631-650.
48	Dietzenbacher E, Los B.1998. Structural decomposition techniques: sense and sensitivity[J]. Economic Systems Research, 10(4): 307-324.
49	Du L M, Wei C, Cai S H.2012. Economic development and carbon dioxide emissions in China: provincial panel data analysis[J]. China Economic Reviews, 23(2): 371-384
50	ERI. 2009. China's low carbon development pathways by 2050: Scenario analysis of energy demand and carbon emissions[M]. Beijing: China Science Press.
51	Fan Y, Liu L C, Wu G, et al.2007. Changes in carbon intensity in China: empirical findings from 1980-2003[J]. Ecological Economics, 62(3): 683-691.
52	Feng K S, Hubacek K, Guan D B.2009. Lifestyles, technology and CO2 emissions in China: a regional comparative analysis[J]. Ecological Economics, 69(1): 145-154.
53	Feng K, Siu Y L, Guan D B, et al.2012. Analyzing drivers of regional carbon dioxide emissions for China[J]. Journal of Industry Ecology, 16(4): 600-611.
54	Garbaccio F R, Ho S M, Jorgenson W D.1999. Controlling carbon emissions in China[J]. Environment and Development Economics, 4(4): 493-518.
55	Greening L A, Davis W B, Schipper L.1998. Decomposition of aggregate carbon intensity for the manufacturing sector: comparison of declining trends from 10 OECD countries for the period 1971-1991[J]. Energy Economics, 20(1): 43-65.
56	Hatzigeorgiou E, Polatidis H, Haralambopoulos D.2011. CO2 emissions, GDP and energy intensity: a multivariate cointegration and causality analysis for Greece, 1977-2007[J]. Applied Energy, 88(4): 1377-1385.
57	He K B, Huo H, Zhang Q, et al.2005. Oil consumption and CO2 emissions in China's road transport: current status, future trends, and policy implications[J]. Energy Policy, 33(12):1499-1507.
58	IEA. 2008. World energy outlook 2008[EB/OL]. 2008-05-01[2014-07-01]. .
59	Inmaculada M Z, Antonello M.2011. The impact of urbanization on CO2 emissions: evidence from developing countries[J]. Ecological Economics, 70(7): 1344-1353.
60	IPCC.2007. Summary for policymakers of climate change: the physical science basis[EB/OL]. 2007-06-30[2014-07-01]. https://www.ipcc.ch/pdf/assessment-report/ar4/wg1/ar4-wg1-spm.pdf.
61	Isaksson L H.2005. Abatement costs in response to the Swedish charge on nitrogen oxide emissions[J]. Journal of Environmental Economics and Management, 50(1): 102-120.
62	Islas J, Grande G.2008. Abatement costs of SO2 control options in the Mexican electric power sector[J]. Applied Energy, 85(2-3): 80-94.
63	Jayanthakumaran K, Verma R, Liu Y.2012. CO2 emissions, energy consumption, trade and income: a comparative analysis of China and India[J]. Energy Policy, 42: 450-460.
64	Jiang K J, Hu X L.2006. Energy demand and emissions in 2030 in China: scenarios and policy options[J]. Environmental Economics and Policy Studies, 7(3): 233-250.
65	Jobert T, Karanfil F, Tykhonenko A.2010. Convergence of per capita carbon dioxide emissions in the EU: legend or reality[J]. Energy Economics, 32(6): 1364-1373.
66	Kenny T, Gray N F.2009. Comparative performance of six carbon footprint models for use in Ireland[J]. Environmental Impact Assessment Review, 29(1): 1-6.
67	Klepper G, Peterson S.2006. Marginal abatement cost curves in general equilibrium: the influence of world energy prices[J]. Resource and Energy Economics, 28(1): 1-23.
68	Knapp T, Mookerjee R.1996. Population growth and global CO2 emissions[J]. Energy Policy, 24(1): 31-37.
69	Leontief W W.1951. The structure of american economy, 1919-1939: an empirical application of equilibrium analysis[M]. New York, NY: Oxford University Press.
70	Leontief W W.1986. Input-output economics[M]. New York, NY: Oxford University Press.
71	Li H, Mu H, Zhang M.2011. Analysis of China's energy consumption impact factors[J]. Procedia Environmental Sciences, 11: 824-830
72	Liang Q M, Fan Y, Wei Y M.2007. Multi-regional input-output model for regional energy requirements and CO2 emissions in China[J]. Energy Policy, 35(3): 1685-1700.
73	Liu L C, Fan Y, Wu G, et al.2007. Using LMDI method to analyze the change of China's industrial CO2 emissions from final fuel use: an empirical analysis[J]. Energy Policy, 35(11): 5892-5900.
74	Liu Z, Guan D B, Crawford-Brown D, et al.2013. Energy policy: a low-carbon road map for China[J]. Nature, 500: 143-145.
75	Mielnik O, Goldemberg J.1999. The evolution of the carbonization index in developing countries[J]. Energy Policy, 27(5): 307-308.
76	Miller R E, Blair P D.2009. Input-output analysis: foundations and extensions[M]. Cambridge, UK: Cambridge University Press.
77	Munoz P, Steininger K W.2010. Austria's CO2 responsibility and the carbon content of its international trade[J]. Ecological Economics, 69(10): 2003-2019.
78	Paul B S, Michael J L.2009. A cross-national study of the association between per capita carbon dioxide emissions and exports to the United States[J]. Social Science Research, 38(1): 239-250.
79	Phetkeo P, Shinji K.2010. Does urbanization lead to less energy use and lower CO2 emissions? a cross-country analysis[J]. Ecological Economics, 70(2): 434-444.
80	Piecyk M I, McKinnon A C.2010. Forecasting the carbon footprint of road freight transport in 2020[J]. International Journal of Production Economics, 128(1): 31-42.
81	Ramanathan R.2005. Combining indicators of energy consumption and CO2 emissions: a cross-country comparison[J]. International Journal of Global Energy Issues, 30(15): 2831-2841.
82	Rawski T G.2001. What is happening to China's GDP statistics[J]. China Economic Review, 12(4): 347-354.
83	Salvador E P, Joséluis P, Mariana C G.2008. Modeling population dynamics and economic growth as competing species: an application to CO2 global emissions[J]. Ecological Economics, 65(3): 602-615.
84	Shafik N, Bandyopadhyay S.1992. Economic growth and environmental quality: time series and cross-country evidence[R]. World Development Report.
85	Shui B, Harriss R C.2006. The role of CO2 embodiment in US-China trade[J]. Energy Policy, 34(18): 4063-4068.
86	Siddiqi T A.2000. The Asian financial crisis: is it good for the global environment[J]. Global Environmental Change, 10(1): 1-7.
87	Soloveitchik D, Ben-Aderet N, Grinman M, et al.2002. Multiobjective optimization and marginal pollution abatement cost in the electricity sector-an Israeli case study[J]. European Journal of Operational Research, 140(3): 571-583.
88	Stern N.2007. Stern Review: the economics of climate change[M]. Cambridge, UK: Cambridge University Press.
89	Stretesky P B, Lynch M J.2009. A cross-national study of the association between per capita carbon dioxide emissions and exports to the United States[J]. Social Science Research, 38(1): 239-250.
90	Sun J W.2005. The decrease of CO2 emission intensity is decarburization at national and global levels[J]. Energy Policy, 33(8): 975-978.
91	Wang C, Chen J N, Zou J.2005. Decomposition of energy-related CO2 emission in China: 1957-2000[J]. Energy, 30(1): 73-83.
92	Wang K, Wang C, Lu X D, et al.2007. Scenario analysis on CO2 emissions potential in China's iron and steel industry[J]. Energy Policy, 35(4): 2320-2335.
93	Wang P, Wu W S, Zhu B Z, et al.2013. Examining the impact factors of energy-related CO2 emissions using the STIRPAT model in Guangdong Province, China[J]. Applied Energy, 106: 65-71.
94	Wang Q W, Zhou P, Shen N, et al.2013. Measuring carbon dioxide emission performance in Chinese provinces: a parametric approach[J]. Renewable and Sustainable Energy Reviews, 21: 324-330.
95	Wang S J, Fang C L, Guan X L, et al.2014. Urbanisation, energy consumption, and carbon dioxide emissions in China: a panel data analysis of China's provinces[J]. Applied Energy, 136: 738-749.
96	Wang S J, Fang C L, Ma H T, et al.2014. Spatial differences and multi-mechanism of carbon footprint based on GWR model in provincial China[J]. Journal of Geographical Sciences, 24(4): 804-822.
97	Wang S J, Fang C L, Wang Y, et al.2015. Quantifying the relationship between urban development intensity and carbon dioxide emissions using a panel data analysis[J]. Ecological Indicators, 49: 121-131.
98	Wang Z H, Yin F C, Zhang Y X, et al.2012. An empirical research on the influencing factors of regional CO2 emissions: evidence from Beijing City, China[J]. Applied Energy, 100: 277-284.
99	World Bank. World Bank development data [EB/OL]. 2010-03-24[2014-07-01]. .
100	Wu L B, Kaneko S J, Matsuoka S J.2005. Driving forces behind the stagnancy of China's energy-related CO2 emissions from 1996 to 1999: the relative importance of structural change, intensity change and scale change[J]. Energy Policy, 33(3): 319-335.
101	Yao C R, Feng K S, Hubacek K.2014. Driving forces of CO2 emissions in the G20 countries: an index decomposition analysis from 1971 to 2010[J]. Ecological Informatics, in press.
102	York R, Rose EA, Dieta T.2003. STIRPAT, IPAT and ImPACT: analytic tools for unpacking the driving forces of environmental impacts[J]. Ecological Economics, 46(3): 351-365.
103	Zaim O, Taskin F.2000. Environmental efficiency in carbon dioxide emissions in the OECD: a non-parametric approach[J]. Journal of Environmental Management, 58(2): 95-107.
104	Zha D L, Zhou D Q.2007. The inequality about provincial energy efficiency and its related CO2 emission: decomposition based on kaya[J]. System Engineering, 25(11): 65-71.
105	Zha D L, Zhou D Q, Zhou P.2010. Driving forces of residential CO2 emissions in urban and rural China: an index decomposition analysis[J]. Energy Policy, 38(7): 3377-3383.
106	Zhang M, Mu H L, Ning Y D.2009. Accounting for energy-related CO2 emission in China, 1991-2006[J]. Energy Policy, 37(3): 1-7.
107	Zhang Y.2009. Structural decomposition analysis of sources of decarbonizing economic development in China: 1992-2006[J]. Ecological Economics, 68(8-9): 2399-2405
108	Zhang Z Q, Qu J S, Zeng J J.2008. Quantitative comparison and analysis on the assessment indicators of greenhouse gases emission[J]. Journal of Geographical Sciences, 18(4): 387-399.
109	Zhang Z X.2000. Decoupling China's carbon emissions increase from economic growth: an economic analysis and policy implications[J]. World Development, 28(4): 739-752.
110	Zhou P, Ang B W, Poh K L.2006. Slacks-based efficiency measures for modeling environmental performance[J]. Ecological Economics, 60(1): 111-118.
111	Zhou P, Ang B W, Poh K L.2008. Measuring environmental performance under different environmental DEA technologies[J]. Energy Economics, 30(1): 1-14.
112	Zhu H M, You W H, Zeng Z F.2012. Urbanization and CO2 emissions: a semi-parametric panel data analysis[J]. Economic Letters, 117(3): 848-850.
113	Zofio J L, Prieto A M.2001. Environmental efficiency and regulatory standards: the case of CO2 emissions from OECD industries[J]. Resource and Energy Economics, 23(1): 63-83.

文献类别	来源	说明
IPCC 报告指南	IPCC 网站	提供一般性的缺省因子
IPCC 排放因子数据库	IPCC 网站	提供一般性缺省因子和各国实践数据
国际能源署(IEA)	国家能源署网站	提供有用的缺省值或可用于对比检验
美国能源情报署(EIA)	美国能源情报署网站	提供有用的缺省值或可用于对比检验
EMEP/CORINAIR排放清单指导手册	欧洲环境机构网站（EEA）	提供有用的缺省值或可用于对比检验
国家发展和改革委员会能源研究所国家气候变化对策协调办公室（针对中国）	国家发展和改革委员会网站	提供中国一般性缺省因子
国内外著名期刊杂志	图书馆、期刊杂志、Web of Knowledge网站等	有针对性因子,但可得性和时效性较差
其他数据	大学等研究机构	需要检验数据的标准性和代表性

指标	定义	作者(年份)、国家
CO₂排放总量	CO₂排放总量	Wang et al (2005)、中国;Stern (2007)、全球
人均CO₂排放量	CO₂排放/人口数量	Stretesky et al (2009)、169个国家;Jobert et al (2010)、欧盟22个国家
碳指数	CO₂排放/能源消费	Mielnik (1999)、发展中国家
能源强度	能源消费/GDP	Ang (1999)、全球
CO₂排放强度	CO₂排放/GDP	Sun (2005)、全球;Greening et al, (1998)、OCED成员国;Fan et al (2007)、中国
CO₂生产率	GDP/CO₂排放	Beinhocker et al (2008)、全球;潘家华等(2011)、中国
工业累计人均CO₂排放量	工业CO₂排放量/人口数量	Zhang et al (2008)、中国

[1]	姜宛贝, 刘卫东, 刘志高, 韩梦瑶. 中国化石能源燃烧碳排放强度非均衡性及其演变的驱动力分析[J]. 地理科学进展, 2020, 39(9): 1425-1435.
[2]	付占辉, 梅林, 郑茹敏, 王彤彤. 东北地区城市女性就业水平空间分异机制[J]. 地理科学进展, 2020, 39(8): 1308-1318.
[3]	程晗蓓, 邹游, 林赛南, 李志刚. 居住迁移对居民健康的影响研究进展述评[J]. 地理科学进展, 2020, 39(7): 1210-1223.
[4]	丁建军, 王璋, 柳艳红, 余方薇. 中国连片特困区经济韧性测度及影响因素分析[J]. 地理科学进展, 2020, 39(6): 924-937.
[5]	胡小芳, 李小雅, 王天宇, 赵红敏, 杨铄, 邓磊, 李景旺. 民宿空间分布的集聚模式与影响因素研究——基于杭州、湖州、恩施的比较[J]. 地理科学进展, 2020, 39(10): 1698-1707.
[6]	杨奎,张宇,赵小风,文琦,钟太洋. 乡村土地利用结构效率时空特征及影响因素[J]. 地理科学进展, 2019, 38(9): 1393-1402.
[7]	陈秧分, 刘玉, 王国刚. 大都市乡村发展比较及其对乡村振兴战略的启示[J]. 地理科学进展, 2019, 38(9): 1403-1411.
[8]	戴旭俊, 刘爱利. 地方认同的内涵维度及影响因素研究进展[J]. 地理科学进展, 2019, 38(5): 662-674.
[9]	李雪铭, 刘贺, 田深圳, 宫一路. 东北三省城市人居活动网络结构及影响因素分析——基于百度贴吧分析[J]. 地理科学进展, 2019, 38(11): 1726-1734.
[10]	何萍, 崔梅艳, 李矜霄, 刘树华. 昆明市太阳辐射变化特征及影响因子分析[J]. 地理科学进展, 2019, 38(11): 1793-1801.
[11]	杨文越, 曹小曙. 多尺度交通出行碳排放影响因素研究进展[J]. 地理科学进展, 2019, 38(11): 1814-1828.
[12]	宋琼, 赵新正, 李同昇, 刘静玉. 多重城市网络空间结构及影响因素——基于有向多值关系视角[J]. 地理科学进展, 2018, 37(9): 1257-1267.
[13]	宋伟轩, 马雨竹, 陈艳如. 南京城区住宅售租价格时空分异与影响因素[J]. 地理科学进展, 2018, 37(9): 1268-1276.
[14]	王建顺, 林李月, 朱宇, 艾尼江·杰力力. 西部民族地区流动人口户籍迁移意愿及影响因素——以新疆为例[J]. 地理科学进展, 2018, 37(8): 1140-1149.
[15]	王圣云, 罗玉婷, 韩亚杰, 李晶. 中国人类福祉地区差距演变及其影响因素——基于人类发展指数(HDI)的分析[J]. 地理科学进展, 2018, 37(8): 1150-1158.

能源消费CO₂排放研究综述

Review of energy-related CO₂ emission in response to climate change

RichHTML

PDF (PC)

赞

可视化

摘要/Abstract

引用本文

使用本文

图/表 6

参考文献 113

相关文章 15

Metrics

本文评价

推荐阅读 0