Assessing drivers of economy-wide energy use and emissions: IDA versus SDA

Wang, H.; Ang, B.W.; Su, Bin

doi:10.1016/j.enpol.2017.05.034

Cited by 319 publications

(123 citation statements)

References 114 publications

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“…Energy efficiency decreased in the transport sector during this period, because of the lack of cohesion and coordination among the different modes of transport, such as the railways, aviation, highways, and waterways, and a modal shift from less energy consuming modes, such as the railways, to more energy consumption intensive modes, such as the highways and civil aviation [72]. During the period 2007-2010, China formulated a series of policies to promote emissions reduction, and stimulated the improvement of energy efficiency, and China's express railways developed rapidly, which improved the conveying efficiency and the energy efficiency in the transport during this period [73]. During the period 2010-2012, the low price of the fossil energy led to an increase in the rebound effect on energy consumption, resulting in an increase in the energy intensity of transport [74].…”

Section: Holistic Analysismentioning

confidence: 99%

Decomposition Analysis of the Factors that Influence Energy Related Air Pollutant Emission Changes in China Using the SDA Method

Zhang

et al. 2017

Sustainability

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Abstract:We decompose factors affecting China's energy-related air pollutant (NO x , PM 2.5 , and SO 2 ) emission changes into different effects using structural decomposition analysis (SDA). We find that, from 2005 to 2012, investment increased NO x , PM 2.5 , and SO 2 emissions by 14.04, 7.82 and 15.59 Mt respectively, and consumption increased these emissions by 11.09, 7.98, and 12.09 Mt respectively. Export and import slightly increased the emissions on the whole, but the rate of the increase has slowed down, possibly reflecting the shift in China's foreign trade structure. Energy intensity largely reduced NO x , PM 2.5 , and SO 2 emissions by 12.49, 14.33 and 23.06 Mt respectively, followed by emission efficiency that reduces these emissions by 4.57, 9.08, and 17.25 Mt respectively. Input-output efficiency slightly reduces the emissions. At sectoral and sub-sectoral levels, consumption is a great driving factor in agriculture and commerce, whereas investment is a great driving factor in transport, construction, and some industrial subsectors such as iron and steel, nonferrous metals, building materials, coking, and power and heating supply. Energy intensity increases emissions in transport, chemical products and manufacturing, but decreases emissions in all other sectors and subsectors. Some policies arising from our study results are discussed.

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Section: Holistic Analysismentioning

confidence: 99%

Decomposition Analysis of the Factors that Influence Energy Related Air Pollutant Emission Changes in China Using the SDA Method

Zhang

et al. 2017

Sustainability

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“…[49][50][51][52] There are typically two types of decomposition approaches: index decomposition analysis (IDA) and structural decomposition analysis (SDA). Wang et al 53 reviewed studies published in 2010-2015 and compared the two techniques from the methodological and application viewpoints. IDA method is built on the index number theory, and it only uses the department's aggregate data.…”

Section: Literaturementioning

confidence: 99%

China's provincial energy‐related carbon emissions‐economy nexus: A two‐stage framework based on decoupling analysis and panel vector autoregression

Pan

Liu

Tsai

et al. 2019

Energy Science & Engineering

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China is transforming the growth model and speeding up industrial structural improvement and upgrading now and in the coming years, which means the slowdown of economic growth and more serious environmental costs in economic and social development would be the “New Normal.” As the world's largest energy consumer and carbon‐emitting country, China's emissions reduction commitments are crucial to global greenhouse gas emissions mitigation, so there is a profusion of research focused on China's economy‐environment nexus. Among which, the dynamic relationship of carbon emission and economic growth and its evolution combined the national, regional, provincial data have not been discussed thoroughly. This paper analyses the elasticity of economic performance of carbon emissions based on 30 Chinese provincial data from 2000 to 2016; furthermore, a panel vector autoregressive model is constructed to discuss the interactions of variables within environmental economic system. It is concluded that China is experiencing a turning point from weak decoupling to strong decoupling in recent years, and its economic performance of carbon emissions has been gradually improved with larger disparities among provinces though. Regression result confirms the role of the energy mix on carbon emissions, and it also indicates that the impact of most factors influencing that have been discussed in previous studies may not be direct, prominent, and for long term.

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“…Decomposition analysis is widely applied in energy and environmental research fields to clarify the driving forces or determinants underlying these changes (Wang et al 2017). According to Hoekstra and van den Bergh (2003), two major techniques that can identify changes in decomposition indicators at the sector level are structural decomposition analysis (SDA) and index decomposition analysis (IDA).…”

Section: Choice Of Decomposition Analysis Modelmentioning

confidence: 99%

“…IDA was developed in energy and environmental research fields to understand the intensity change caused by technological development, such as that of emission intensity due to resource efficiency (Wang et al 2017). IDA has several estimation options, including the Laspeyres index and logarithmic mean Divisia index (LMDI) (Ang 2015).…”

Section: Choice Of Decomposition Analysis Modelmentioning

confidence: 99%

Decomposition of toxicity emission changes on the demand and supply sides: empirical study of the US industrial sector

Fujii

Okamoto

Kagawa

et al. 2017

Environ. Res. Lett.

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This study investigated the changes in the toxicity of chemical emissions from the US industrial sector over the 1998-2009 period. Specifically, we employed a multiregional input-output analysis framework and integrated a supply-side index decomposition analysis (IDA) with a demand-side structural decomposition analysis (SDA) to clarify the main drivers of changes in the toxicity of production-and consumption-based chemical emissions. The results showed that toxic emissions from the US industrial sector decreased by 83% over the studied period because of pollution abatement efforts adopted by US industries. A variety of pollution abatement efforts were used by different industries, and cleaner production in the mining sector and the use of alternative materials in the manufacture of transportation equipment represented the most important efforts.

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Assessing drivers of economy-wide energy use and emissions: IDA versus SDA

Cited by 319 publications

References 114 publications

Decomposition Analysis of the Factors that Influence Energy Related Air Pollutant Emission Changes in China Using the SDA Method

Decomposition Analysis of the Factors that Influence Energy Related Air Pollutant Emission Changes in China Using the SDA Method

China's provincial energy‐related carbon emissions‐economy nexus: A two‐stage framework based on decoupling analysis and panel vector autoregression

Decomposition of toxicity emission changes on the demand and supply sides: empirical study of the US industrial sector

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