Decomposing the influencing factors of industrial carbon emissions in Shanghai using the LMDI method

被引：278

作者：

Zhao, Min ^{[1
]}

Tan, Lirong ^{[1
]}

Zhang, Weiguo ^{[2
]}

Ji, Minhe ^{[1
]}

Liu, Yuan ^{[1
]}

Yu, Lizhong ^{[1
]}

机构：

[1] E China Normal Univ, Coll Resource & Environm Sci, Shanghai 200062, Peoples R China

[2] E China Normal Univ, State Key Lab Estuarine & Coastal Res, Shanghai 200062, Peoples R China

来源：

ENERGY | 2010年 / 35卷 / 06期

基金：

中国国家自然科学基金;

关键词：

Industrial carbon emissions; Energy consumption; LMDI; Shanghai; CO2; EMISSIONS; INDEX; COUNTRIES; ENERGY;

D O I：

10.1016/j.energy.2010.02.049

中图分类号：

O414.1 [热力学];

学科分类号：

摘要：

Knowledge of influencing factors of industrial carbon emissions (ICE) is crucial to the efforts of reducing anthropogenic greenhouse gas emissions. In this paper, main factors responsible for the ICE in Shanghai between 1996 and 2007 were identified and quantitatively analyzed using the Log-Mean Divisia Index method. It was found that the industrial output was the main driving force of ICE. The decline in energy intensity and the adjustment of energy and industrial structure are major determinants for reduction of ICE, with the former alone accounting for 90% of the reduction. To better investigate the relative contribution of different industrial sectors and their changes over time, we divided the study period into two equal time intervals and analyzed some high-carbon emission sectors. The results suggested that the intensity of energy use should be reduced further, for it was far higher than the world average. Adjustment of industrial structure by developing low-carbon emission industries is more crucial than energy mix. (C) 2010 Elsevier Ltd. All rights reserved.

引用

页码：2505 / 2510

页数：6

共 18 条

[1] The LMDI approach to decomposition analysis: a practical guide [J].

Ang, BW .

ENERGY POLICY, 2005, 33 (07) :867-871

[2] Decomposition analysis for policymaking in energy: which is the preferred method? [J].

Ang, BW .

ENERGY POLICY, 2004, 32 (09) :1131-1139

[3] A survey of index decomposition analysis in energy and environmental studies [J].

Ang, BW ;

Zhang, FQ .

ENERGY, 2000, 25 (12) :1149-1176

[4]

[Anonymous], SUMM POL SYNTH REP I

[5] Carbon dioxide emissions in the US economy - A structural decomposition analysis [J].

Casler, SD ;

Rose, A .

ENVIRONMENTAL & RESOURCE ECONOMICS, 1998, 11 (3-4) :349-363

[6] Decomposition of aggregate carbon intensity for the manufacturing sector: comparison of declining trends from 10 OECD countries for the period 1971-1991 [J].

Greening, LA ;

Davis, WB ;

Schipper, L .

ENERGY ECONOMICS, 1998, 20 (01) :43-65

[7] CO2 emissions in Greece for 1990-2002:: A decomposition analysis and comparison of results using the Arithmetic Mean Divisia Index and Logarithmic Mean Divisia Index techniques [J].

Hatzigeorgiou, Emmanouil ;

Polatidis, Heracles ;

Haralambopoulos, Dias .

ENERGY, 2008, 33 (03) :492-499

[8] Comparing structural and index decomposition analysis [J].

Hoekstra, R ;

van der Bergh, JJCJM .

ENERGY ECONOMICS, 2003, 25 (01) :39-64

[9]

IPCC, 2006, GUIDELINES NATL GREE, DOI DOI https://doi.org/10.1186/1477-7525-4-79

[10] Analysis of CO2 emissions in APEC countries:: A time-series and a cross-sectional decomposition using the log mean Divisia method [J].

Lee, Kihoon ;

Oh, Wankeun .

ENERGY POLICY, 2006, 34 (17) :2779-2787

← 1 2 →