Decomposition analysis applied to energy and emissions: A literature review

doi:10.1007/s42524-023-0270-4

Front. Eng

2023, Vol. 10

Issue (4) : 625-639 https://doi.org/10.1007/s42524-023-0270-4

REVIEW ARTICLE

Decomposition analysis applied to energy and emissions: A literature review

Hui WANG¹(

), Yafei YANG²

¹. School of Economics and Management, China University of Petroleum, Qingdao 266580, China; Institute for Energy Economics and Policy, China University of Petroleum, Qingdao 266580, China
². School of Economics and Management, China University of Petroleum, Qingdao 266580, China

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Abstract

Decomposition analysis has been widely used to assess the determinants of energy and CO₂ emissions in academic research and policy studies. Both the methodology and application of decomposition analysis have been largely improved in the past decades. After more than 50 years’ developments, decomposition studies have become increasingly sophisticated and diversified, and tend to converge internally and integrate with other analytical approaches externally. A good understanding of the literature and state of the art is critical to identify knowledge gaps and formulate future research agenda. To this end, this study presents a literature survey for decomposition analysis applied to energy and emission issues, with a focus on the period of 2016–2021. A review for three individual decomposition techniques is first conducted, followed by a synthesis of emerging trends and features for the decomposition analysis literature as a whole. The findings are expected to direct future research in decomposition analysis.

Keywords index decomposition analysis structural decomposition analysis production decomposition analysis energy CO₂ emissions

Corresponding Author(s): Hui WANG

Just Accepted Date: 23 October 2023 Online First Date: 16 November 2023 Issue Date: 07 December 2023

Cite this article:

Hui WANG,Yafei YANG. Decomposition analysis applied to energy and emissions: A literature review[J]. Front. Eng, 2023, 10(4): 625-639.

URL:

https://academic.hep.com.cn/fem/EN/10.1007/s42524-023-0270-4
https://academic.hep.com.cn/fem/EN/Y2023/V10/I4/625

Decomposition model		Determinants	Decomposition effects	Explanation
IDA	$E = ∑ i E i X i X i X X = ∑ i I i S i X$ $E T ? E 0 = Δ E i n t + Δ E str + Δ E act$	Energy intensity of sector i (I_i)	Energy intensity (?E_int)	Energy use technology changes
		Share of activity for sector i (S_i)	Activity structure (?E_str)	Shifts in composition of energy end-use activities
		Total activity (X)	Total activity (?E_act)	Changes in scale of overall energy end-use activities
SDA	$E = ∑ i j I i L i j Y j Y Y = ∑ i j I i L i j F S j Y$ $E T ? E 0 = Δ E i n t + Δ E pstr + Δ E fstr + Δ E tfd$	Energy intensity of sector i (I_i)	Energy intensity (?E_int)	Energy use technology changes
		Production structure (L_ij)	Production structure (?E_pstr)	Changes in production linkages between sectors/regions
		Share of final demand for sector j (FS_j)	Demand structure (?E_fstr)	Shifts in consumption pattern
		Total final demand (Y)	Total final demand (?E_tfd)	Changes in scale of final demand
PDA	$E = ∑ i E i / E i D i, E D i, E X i D i, E X i X X = ∑ i P E I i T E i S i X$ $E T ? E 0 = Δ E pei + Δ E tc + Δ E ec + Δ E str + Δ E out$	Potential energy intensity of sector i (PEI_i)	Potential energy intensity (?E_pei)	Non-energy technology changes
		Technical inefficiency of sector i (TE_i)	Technological change (?E_tc)	Energy technology innovation
		Technical inefficiency of sector i (TE_i)	Efficiency change (?E_ec)	Energy use efficiency changes
		Share of output for sector i (S_i)	Output structure (?E_str)	Shifts in composition of energy end-use activities
		Total output (X)	Total output (?E_out)	Changes in scale of overall energy end-use activities

Tab.1 Basic decomposition approaches

Fig.1 Distribution of papers among the top 10 journals for (a) IDA, (b) SDA, and (c) PDA (note: red/blue parts refer to the common/unique journals for the three branches of decomposition analysis).

Fig.2 Citation graph of top 50 decomposition studies (note: the size of circle reflects the magnitude of LCS (the value before author-year in labels); red circles indicate IDA studies, green circles indicate SDA studies, blue circles indicate PDA studies, and yellow circles indicate interdisciplinary studies).

Fig.3 Methodology and application features of IDA studies, 2016–2021: (a) Total number of IDA studies involving both energy/emissions and at economy-wide/sectoral level; (b) number of studies by single-level and multi-level analysis; (c) number of studies by aggregate indicator and decomposition form; (d) number of studies by decomposition methods.

Fig.4 Methodology and application features of SDA studies, 2016–2021: (a) Total number of SDA studies involving both energy/emissions and at economy-wide/sectoral level; (b) number of studies by one-stage and two-stage decomposition; (c) number of studies by aggregate indicator and decomposition form; (d) number of studies by decomposition methods.

Fig.5 Methodology and application features of PDA studies, 2006–2021: (a) Total number of PDA studies at economy-wide/sectoral level; (b) number of studies by emissions and energy; (c) number of studies by aggregate indicator and decomposition form; (d) number of studies by decomposition methods.

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