Decomposition analysis applied to energy and emissions: A literature review

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.

Graphical abstract

Keywords

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

References

[1] Ang, B W (2004). Decomposition analysis for policymaking in energy: Which is the preferred method?. Energy Policy, 32( 9): 1131–1139

[2] Ang, B W (2015). LMDI decomposition approach: A guide for implementation. Energy Policy, 86: 233–238

[3] Ang, B W Goh, T (2019). Index decomposition analysis for comparing emission scenarios: Applications and challenges. Energy Economics, 83: 74–87

[4] Ang, B W Su, B Wang, H (2016). A spatial-temporal decomposition approach to performance assessment in energy and emissions. Energy Economics, 60: 112–121

[5] Ang, B W Zhang, F Q (2000). A survey of index decomposition analysis in energy and environmental studies. Energy, 25( 12): 1149–1176

[6] Boyd, G A Hanson, D A Sterner, T (1988). Decomposition of changes in energy intensity: A comparison of the Divisia index and other methods. Energy Economics, 10( 4): 309–312

[7] Chang, N Han, C H (2022). Regional CO₂ emissions and cross-boundary mitigation potential in China. Economic Systems Research, 34( 3): 367–382

[8] Chen, J Xu, C Shahbaz, M Song, M (2021). Interaction determinants and projections of China’s energy consumption: 1997–2030. Applied Energy, 283: 116345

[9] Chen, L Duan, Q (2016). Decomposition analysis of factors driving CO₂ emissions in Chinese provinces based on production-theoretical decomposition analysis. Natural Hazards, 84( S1): 267–277

[10] Chen, X Liu, Y Mcelroy, M (2022). Transition towards carbon-neutral electrical systems for China: Challenges and perspectives. Frontiers of Engineering Management, 9( 3): 504–508

[11] Cheng, S Fan, W Chen, J Meng, F Liu, G Song, M Yang, Z (2020). The impact of fiscal decentralization on CO₂ emissions in China. Energy, 192: 116685

[12] de Boer, P Rodrigues, J F D (2020). Decomposition analysis: When to use which method?. Economic Systems Research, 32( 1): 1–28

[13] de Vries, G J Ferrarini, B (2017). What accounts for the growth of carbon dioxide emissions in advanced and emerging economies? The role of consumption, technology and global supply chain participation. Ecological Economics, 132: 213–223

[14] Dennehy, E R Ó, Gallachóir B P (2018). Ex-post decomposition analysis of passenger car energy demand and associated CO₂ emissions. Transportation Research Part D: Transport and Environment, 59: 400–416

[15] Dietzenbacher, E Kulionis, V Capurro, F (2020). Measuring the effects of energy transition: A structural decomposition analysis of the change in renewable energy use between 2000 and 2014. Applied Energy, 258: 114040

[16] Dietzenbacher, E Los, B (1998). Structural decomposition techniques: Sense and sensitivity. Economic Systems Research, 10( 4): 307–324

[17] Duarte, R Miranda-Buetas, S Sarasa, C (2021). Household consumption patterns and income inequality in EU countries: Scenario analysis for a fair transition towards low-carbon economies. Energy Economics, 104: 105614

[18] Duarte, R Serrano, A (2021). Environmental analysis of structural and technological change in a context of trade expansion: Lessons from the EU enlargement. Energy Policy, 150: 112142

[19] EmeleLGraichenJMendelevitchR (2022). Decomposition analysis of CO₂ emissions in the European cement sector: Identifying drivers of emission trends between 2005 and 2018. Berlin: German Environment Agency

[20] European CommissionJRC (2020). Regional Input-Output Data for Europe. Dataset. European Commission, Joint Research Centre (JRC) Data Catalogue

[21] Fan, Y Fang, C (2020). Insight into carbon emissions related to residential consumption in Tibetan Plateau: Case study of Qinghai. Sustainable Cities and Society, 61: 102310

[22] Fetanat, A Shafipour, G (2017). A hybrid method of LMDI, symmetrical components, and SFA to estimate the distribution of energy-saving potential with consideration of unbalanced components in decomposition analysis. Energy Efficiency, 10( 4): 1041–1059

[23] Fragkos, P Tasios, N Paroussos, L Capros, P Tsani, S (2017). Energy system impacts and policy implications of the European Intended Nationally Determined Contribution and low-carbon pathway to 2050. Energy Policy, 100: 216–226

[24] Goh, T Ang, B W (2018). Quantifying CO₂ emission reductions from renewables and nuclear energy: Some paradoxes. Energy Policy, 113: 651–662

[25] Goh, T Ang, B W (2021). Integrating combined heat and power in index decomposition analysis of the power sector. Energy Efficiency, 14( 7): 76

[26] Goh, T Ang, B W Xu, X Y (2018). Quantifying drivers of CO₂ emissions from electricity generation: Current practices and future extensions. Applied Energy, 231: 1191–1204

[27] Guevara, Z Domingos, T (2017). Three-level decoupling of energy use in Portugal 1995–2010. Energy Policy, 108: 134–142

[28] Guevara, Z Rodrigues, J F D (2016). Structural transitions and energy use: A decomposition analysis of Portugal 1995–2010. Economic Systems Research, 28( 2): 202–223

[29] Hang, Y Wang, F Su, B Wang, Y Zhang, W Wang, Q (2021). Multi-region multi-sector contributions to drivers of air pollution in China. Earth’s Future, 9( 6): e2021EF002012

[30] Harmsen, R Crijns-Graus, W (2021). Unhiding the role of CHP in power & heat sector decomposition analyses. Energy Policy, 152: 112208

[31] Hoekstra, R Michel, B Suh, S (2016). The emission cost of international sourcing: Using structural decomposition analysis to calculate the contribution of international sourcing to CO₂-emission growth. Economic Systems Research, 28( 2): 151–167

[32] Hoekstra, R van den Bergh, J C (2003). Comparing structural decomposition analysis and index. Energy Economics, 25( 1): 39–64

[33] Huang, Y H (2020). Examining impact factors of residential electricity consumption in Taiwan using index decomposition analysis based on end-use level data. Energy, 213: 119067

[34] IEA (2022). Energy Efficiency 2022. Paris: International Energy Agency (IEA)

[35] IPCC (2022). Climate Change 2022: Mitigation of Climate Change. Contribution of Working Group III to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC). Cambridge: Cambridge University Press

[36] Jiang, X Guan, D (2017). The global CO₂ emissions growth after international crisis and the role of international trade. Energy Policy, 109: 734–746

[37] Kaltenegger, O Löschel, A Pothen, F (2017). The effect of globalisation on energy footprints: Disentangling the links of global value chains. Energy Economics, 68: 148–168

[38] KeramidasKFosseFDiaz-VazquezASchadeBTchung-MingSWeitzelMVandyckTWojtowiczK (2021). Global Energy and Climate Outlook 2020: A New Normal Beyond COVID-19. European Commission, Joint Research Centre Science for Policy Report. Luxembourg: Publications Office of the European Union

[39] Kesicki, F (2013). Marginal abatement cost curves: Combining energy system modelling and decomposition analysis. Environmental Modeling and Assessment, 18( 1): 27–37

[40] Kobayakawa, T (2022). The carbon footprint of capital formation: An empirical analysis on its relationship with a country’s income growth. Journal of Industrial Ecology, 26( 2): 522–535

[41] Kone, A C Buke, T (2019). Factor analysis of projected carbon dioxide emissions according to the IPCC based sustainable emission scenario in Turkey. Renewable Energy, 133: 914–918

[42] Lan, J Malik, A Lenzen, M McBain, D Kanemoto, K (2016). A structural decomposition analysis of global energy footprints. Applied Energy, 163: 436–451

[43] Lenzen, M (2016). Structural analyses of energy use and carbon emissions: An overview. Economic Systems Research, 28( 2): 119–132

[44] Lenzen, M Kanemoto, K Moran, D Geschke, A (2012). Mapping the structure of the world economy. Environmental Science & Technology, 46( 15): 8374–8381

[45] Lenzen, M Moran, D Kanemoto, K Geschke, A (2013). Building Eora: A global multi-region input–output database at high country and sector resolution. Economic Systems Research, 25( 1): 20–49

[46] Li, J S Wei, W D Zhen, W Guo, Y Chen, B (2019). How green transition of energy system impacts China’s Mercury emissions. Earth’s Future, 7( 12): 1407–1416

[47] Li, J S Zhou, H W Meng, J Yang, Q Chen, B Zhang, Y Y (2018). Carbon emissions and their drivers for a typical urban economy from multiple perspectives: A case analysis for Beijing city. Applied Energy, 226: 1076–1086

[48] Liu, X Hang, Y Wang, Q Chiu, C R Zhou, D (2022). The role of energy consumption in global carbon intensity change: A meta-frontier-based production-theoretical decomposition analysis. Energy Economics, 109: 105968

[49] Liu, X Zhou, D Zhou, P Wang, Q (2017). What drives CO₂ emissions from China’s civil aviation? An exploration using a new generalized PDA method. Transportation Research Part A: Policy and Practice, 99: 30–45

[50] Luo, Y Zeng, W Wang, Y Li, D Hu, X Zhang, H (2021). A hybrid approach for examining the drivers of energy consumption in Shanghai. Renewable & Sustainable Energy Reviews, 151: 111571

[51] Ma, J Du, G Xie, B (2019). CO₂ emission changes of China’s power generation system: Input–output subsystem analysis. Energy Policy, 124: 1–12

[52] MariasinghamJ (2015). ADB multi-region input–output database: Sources and methods. Online Views

[53] Mathy, S Menanteau, P Criqui, P (2018). After the Paris Agreement: Measuring the global decarbonization wedges from national energy scenarios. Ecological Economics, 150: 273–289

[54] Mi, Z Meng, J Guan, D Shan, Y Song, M Wei, Y M Liu, Z Hubacek, K (2017). Chinese CO₂ emission flows have reversed since the global financial crisis. Nature Communications, 8( 1): 1712

[55] Mohlin, K Bi, A Brooks, S Camuzeaux, J Stoerk, T (2019). Turning the corner on US power sector CO₂ emissions: A 1990–2015 state level analysis. Environmental Research Letters, 14( 8): 084049

[56] Moran, D Giljum, S Kanemoto, K Godar, J (2020). From satellite to supply chain: New approaches connect earth observation to economic decisions. One Earth, 3( 1): 5–8

[57] Natural Resources CanadaOEE (2016). Energy Efficiency Trends in Canada 1990–2013. Natural Resources Canada’s Office of Energy Efficiency (OEE)

[58] Olanrewaju, O A Mbohwa, C (2017). Assessing potential reduction in greenhouse gas: An integrated approach. Journal of Cleaner Production, 141: 891–899

[59] Palmer, K Paul, A Keyes, A (2018). Changing baselines, shifting margins: How predicted impacts of pricing carbon in the electricity sector have evolved over time. Energy Economics, 73: 371–379

[60] Pasurka Jr, C A (2006). Decomposing electric power plant emissions within a joint production framework. Energy Economics, 28( 1): 26–43

[61] Qian, H Xu, S Cao, J Ren, F Wei, W Meng, J Wu, L (2021). Air pollution reduction and climate co-benefits in China’s industries. Nature Sustainability, 4( 5): 417–425

[62] Roinioti, A Koroneos, C (2017). The decomposition of CO₂ emissions from energy use in Greece before and during the economic crisis and their decoupling from economic growth. Renewable & Sustainable Energy Reviews, 76: 448–459

[63] RørmoseP (2010). Structural Decomposition Analysis Sense and Sensitivity. Statistics Denmark

[64] Shahiduzzaman, M Layton, A (2017). Decomposition analysis for assessing the United States 2025 emissions target: How big is the challenge?. Renewable & Sustainable Energy Reviews, 67: 372–383

[65] Shan, Y Guan, Y Hang, Y Zheng, H Li, Y Guan, D Li, J Zhou, Y Li, L Hubacek, K (2022). City-level emission peak and drivers in China. Science Bulletin, 67( 18): 1910–1920

[66] Shigetomi, Y Ohno, H Chapman, A Fujii, H Nansai, K Fukushima, Y (2019). Clarifying demographic impacts on embodied and materially retained carbon toward climate change mitigation. Environmental Science & Technology, 53( 24): 14123–14133

[67] Södersten, C J Wood, R Hertwich, E G (2018). Environmental impacts of capital formation. Journal of Industrial Ecology, 22( 1): 55–67

[68] Su, B Ang, B W (2012). Structural decomposition analysis applied to energy and emissions: Some methodological developments. Energy Economics, 34( 1): 177–188

[69] Su, B Ang, B W (2016). Multi-region comparisons of emission performance: The structural decomposition analysis approach. Ecological Indicators, 67: 78–87

[70] Su, B Ang, B W (2017). Multiplicative structural decomposition analysis of aggregate embodied energy and emission intensities. Energy Economics, 65: 137–147

[71] Su, B Ang, B W (2022). Improved granularity in input-output analysis of embodied energy and emissions: The use of monthly data. Energy Economics, 113: 106245

[72] Su, B Thomson, E (2016). China’s carbon emissions embodied in (normal and processing) exports and their driving forces, 2006–2012. Energy Economics, 59: 414–422

[73] Sueyoshi, T Li, A Liu, X (2019). Exploring sources of China’s CO₂ emission: Decomposition analysis under different technology changes. European Journal of Operational Research, 279( 3): 984–995

[74] Tan, R Lin, B (2018). What factors lead to the decline of energy intensity in China’s energy intensive industries?. Energy Economics, 71: 213–221

[75] Timmer, M P Dietzenbacher, E Los, B Stehrer, R de Vries, G J (2015). An illustrated user guide to the world input-output database: The case of global automotive production. Review of International Economics, 23( 3): 575–605

[76] Tukker, A de Koning, A Wood, R Hawkins, T Lutter, S Acosta, J Rueda Cantuche, J M R Bouwmeester, M Oosterhaven, J Drosdowski, T Kuenen, J (2013). EXIOPOL: Development and illustrative analyses of a detailed global MR EE SUT/IOT. Economic Systems Research, 25( 1): 50–70

[77] UNFCCC (2021). Technical analysis of the third biennial update report of Malaysia submitted on 31 December 2020. Technical Analysis Summary Report. United Nations Framework Convention on Climate Change (UNFCCC)

[78] US EIA (2022). US Energy-Related Carbon Dioxide Emissions, 2021. US Energy Information Administration (EIA)

[79] van den Berg, N J Hof, A F van der Wijst, K I Akenji, L Daioglou, V Edelenbosch, O Y van Sluisveld, M A E Timmer, V J van Vuuren, D P (2021). Decomposition analysis of per capita emissions: A tool for assessing consumption changes and technology changes within scenarios. Environmental Research Communications, 3( 1): 015004

[80] Wang, B Wang, Q Wei, Y M Li, Z P (2018a). Role of renewable energy in China’s energy security and climate change mitigation: An index decomposition analysis. Renewable & Sustainable Energy Reviews, 90: 187–194

[81] Wang, H Ang, B W Zhou, P (2018b). Decomposing aggregate CO₂ emission changes with heterogeneity: An extended production-theoretical approach. The Energy Journal, 39( 1): 59–79

[82] Wang, H Ang, B W Su, B (2017a). Assessing drivers of economy-wide energy use and emissions: IDA versus SDA. Energy Policy, 107: 585–599

[83] Wang, H Ang, B W Su, B (2017b). A multi-region structural decomposition analysis of global CO₂ emission intensity. Ecological Economics, 142: 163–176

[84] Wang, H Ang, B W Su, B (2017c). Multiplicative structural decomposition analysis of energy and emission intensities: Some methodological issues. Energy, 123: 47–63

[85] Wang, H Li, R Zhang, N Zhou, P Wang, Q (2020). Assessing the role of technology in global manufacturing energy intensity change: A production-theoretical decomposition analysis. Technological Forecasting and Social Change, 160: 120245

[86] Wang, H Pan, C Ang, B W Zhou, P (2021a). Does global value chain participation decouple Chinese development from CO₂ emissions? A structural decomposition analysis. Energy Journal, 42( 2): 183–204

[87] Wang, H Zhou, P (2018). Multi-country comparisons of CO₂ emission intensity: The production-theoretical decomposition analysis approach. Energy Economics, 74: 310–320

[88] Wang, H Zhou, P Xie, B C Zhang, N (2019a). Assessing drivers of CO₂ emissions in China’s electricity sector: A metafrontier production-theoretical decomposition analysis. European Journal of Operational Research, 275( 3): 1096–1107

[89] Wang, M Feng, C (2020). The impacts of technological gap and scale economy on the low-carbon development of China’s industries: An extended decomposition analysis. Technological Forecasting and Social Change, 157: 120050

[90] Wang, Q Wang, Y Hang, Y Zhou, P (2019b). An improved production-theoretical approach to decomposing carbon dioxide emissions. Journal of Environmental Management, 252: 109577

[91] Wang, Y Wang, Q Hang, Y Zhou, D (2021b). Decomposition of industrial pollution intensity change and reduction potential: A two-stage meta-frontier PDA method. Sustainable Production and Consumption, 28: 472–483

[92] Wang, Z Li, Y Cai, H Yang, Y Wang, B (2019c). Regional difference and drivers in China’s carbon emissions embodied in internal trade. Energy Economics, 83: 217–228

[93] Wei, L Li, C Wang, J Wang, X Wang, Z Cui, C Peng, S Liu, Y Yu, S Wang, L Shi, Z (2020). Rising middle and rich classes drove China’s carbon emissions. Resources, Conservation and Recycling, 159: 104839

[94] Wood, R Neuhoff, K Moran, D Simas, M Grubb, M Stadler, K (2020). The structure, drivers and policy implications of the European carbon footprint. Climate Policy, 20( sup1): S39–S57

[95] World Bank (2015). Sustainable Energy for All: Global Tracking Framework. Washington, DC: World Bank

[96] WrightP (2014). Drivers of industrial carbon dioxide emissions and energy use: A decomposition analysis. Report for the Committee on Climate Change

[97] Wu, F Ji, D J Zha, D L Zhou, D Q Zhou, P (2022). A nonparametric distance function approach with endogenous direction for estimating marginal abatement costs of CO₂ emissions. Journal of Management Science and Engineering, 7( 2): 330–345

[98] Wu, F Zhou, P Zhou, D Q (2020). Modeling carbon emission performance under a new joint production technology with energy input. Energy Economics, 92: 104963

[99] Xie, X Lin, B (2019). Understanding the energy intensity change in China’s food industry: A comprehensive decomposition method. Energy Policy, 129: 53–68

[100] Xu, X Y Ang, B W (2013). Index decomposition analysis applied to CO₂ emission studies. Ecological Economics, 93: 313–329

[101] Xu, X Y Ang, B W (2014). Multilevel index decomposition analysis: Approaches and application. Energy Economics, 44: 375–382

[102] Yang, Y Wang, H Löschel, A Zhou, P (2022). Energy transition toward carbon-neutrality in China: Pathways, implications and uncertainties. Frontiers of Engineering Management, 9( 3): 358–372

[103] Yeh, S Mishra, G S Fulton, L Kyle, P McCollum, D L Miller, J Cazzola, P Teter, J (2017). Detailed assessment of global transport-energy models’ structures and projections. Transportation Research Part D: Transport and Environment, 55: 294–309

[104] Yu, D Shi, S (2015). Researching the development of Atanassov intuitionistic fuzzy set: Using a citation network analysis. Applied Soft Computing, 32: 189–198

[105] Yue, X Deane, J P O’Gallachoir, B Rogan, F (2020). Identifying decarbonisation opportunities using marginal abatement cost curves and energy system scenario ensembles. Applied Energy, 276: 115456

[106] Zhang, D Wang, H Löschel, A Zhou, P (2021). The changing role of global value chains in CO₂ emission intensity in 2000–2014. Energy Economics, 93: 105053

[107] Zhang, H Lahr, M L Bi, J (2016). Challenges of green consumption in China: A household energy use perspective. Economic Systems Research, 28( 2): 183–201

[108] Zhang, L Ma, X Wang, Y Song, R Li, J Yuan, W Zhang, S (2020a). The increasing district heating energy consumption of the building sector in China: Decomposition and decoupling analysis. Journal of Cleaner Production, 271: 122696

[109] Zhang, X Zhao, X Jiang, Z Shao, S (2017). How to achieve the 2030 CO₂ emission-reduction targets for China’s industrial sector: Retrospective decomposition and prospective trajectories. Global Environmental Change, 44: 83–97

[110] Zhang, Z Guan, D Wang, R Meng, J Zheng, H Zhu, K Du, H (2020b). Embodied carbon emissions in the supply chains of multinational enterprises. Nature Climate Change, 10( 12): 1096–1101

[111] Zhao, X Zhang, X Shao, S (2016). Decoupling CO₂ emissions and industrial growth in China over 1993–2013: The role of investment. Energy Economics, 60: 275–292

[112] Zhao, Z Shi, X Zhao, L Zhang, J (2020). Extending production-theoretical decomposition analysis to environmentally sensitive growth: Case study of Belt and Road Initiative countries. Technological Forecasting and Social Change, 161: 120289

[113] ZhongS (2015). Structural decompositions of energy consumption, energy intensity, emissions and emission intensity: A sectoral perspective, empirical evidence from WIOD over 1995 to 2009. United Nations University – Maastricht Economic and Social Research Institute on Innovation and Technology Working Papers 2016–015

[114] Zhou, H Yang, Y Chen, Y Zhu, J (2018). Data envelopment analysis application in sustainability: The origins, development and future directions. European Journal of Operational Research, 264( 1): 1–16

[115] Zhou, P Ang, B W (2008). Decomposition of aggregate CO₂ emissions: A production-theoretical approach. Energy Economics, 30( 3): 1054–1067

[116] Zhou, P Gao, S Lv, Y Zhao, G (2022). Energy transition management towards a low-carbon world. Frontiers of Engineering Management, 9( 3): 499–503

[117] Zhou, X Kuosmanen, T (2020). What drives decarbonization of new passenger cars?. European Journal of Operational Research, 284( 3): 1043–1057

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