Improved granularity in input-output analysis of embodied energy and emissions: The use of monthly data

• Published in: Energy economics 2022-09, Vol.113, p.106245, Article 106245
• Main Authors: Su, Bin, Ang, B.W.
• Format: Article
• Language: English
• Subjects: Aggregate embodied intensity; China; Embodied energy/emissions; Input-output analysis; Structural decomposition analysis; Temporal disaggregation
• ISSN: 0140-9883; 1873-6181
• DOI: 10.1016/j.eneco.2022.106245

Input-output (I-O) analysis has been widely used in national energy and energy-related emission studies. These studies are generally conducted using annual data. In a growing number of countries, significant variations in renewable energy supply and in final demands of goods and services are observed over time within a year. These temporal variations cannot be captured in I-O analysis using annual data. To investigate such temporal dynamics, we propose an I-O analysis framework that uses monthly data. Further to that, the drivers in embodiments and aggregate embodied intensity (AEI) indicators are studied via Structural Decomposition Analysis (SDA). Additive SDA and multiplicative SDA are applied to reveal the temporal dynamics associated with energy and emission embodiments and AEI indicators, respectively. An application study using China's 2018 datasets show the importance of temporal dynamics in studying its embodiments and AEI indicators, with drivers of their changes show significant variations over months. It is shown that increased data granularity reveals useful information which would otherwise undetected if annual data are employed. Implications of the findings on future research are discussed. •We propose a framework of temporal disaggregation in an extended I-O analysis.•Additive SDA is introduced to investigate the temporal dynamics in embodiments.•Multiplicative SDA is introduced to investigate the temporal dynamics in AEI indicators.•Empirical study of China shows the importance of temporal dynamics in energy and emission studies.