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CO2 intensity decomposition analysis in the Netherlands' manufacturing industry: an application of monetary and physical indicators

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  • Ali Faridzad

    (Allameh Tabataba‘i University)

  • Mahta Ghafarian Ghadim

    (Allameh Tabataba‘i University)

Abstract

Carbon dioxide intensity as a metric to assess the carbon emission variation can be studied from different aspects based on the activity indicators. Carbon intensity is often estimated in the manufacturing sector by applying the Carbon to GDP ratio (CGR) with the monetary activity indicators; however, the physical activity indicators' availability and considering them into the Index Decomposition Analysis (IDA) have led to different results. The Composite Carbon Intensity (CCI) and physical Activity Revaluation (AR) intensity are two of the carbon intensities resulting from the physical approaches. More accurate results would be obtained by applying more physical activity indicators through an appropriate method since problems that arise from using aggregated monetary indicators in computation have been removed. This study compared the carbon intensity results from three aspects in the Netherlands manufacturing sectors in 2005–2015. The empirical results indicated that the CGR as the monetary activity indicator revealed a decrease in carbon emissions while moving toward CCI and AR intensity by incorporating the physical activity indicators into decomposition signified an increase in CO2 emissions.

Suggested Citation

  • Ali Faridzad & Mahta Ghafarian Ghadim, 2023. "CO2 intensity decomposition analysis in the Netherlands' manufacturing industry: an application of monetary and physical indicators," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(8), pages 8799-8817, August.
    • Handle: RePEc:spr:endesu:v:25:y:2023:i:8:d:10.1007_s10668-022-02423-2
    DOI: 10.1007/s10668-022-02423-2
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    as
    1. Ang, B. W., 2004. "Decomposition analysis for policymaking in energy:: which is the preferred method?," Energy Policy, Elsevier, vol. 32(9), pages 1131-1139, June.
    2. Choi, Ki-Hong & Oh, Wankeun, 2014. "Extended Divisia index decomposition of changes in energy intensity: A case of Korean manufacturing industry," Energy Policy, Elsevier, vol. 65(C), pages 275-283.
    3. Wang, Wenwen & Li, Man & Zhang, Ming, 2017. "Study on the changes of the decoupling indicator between energy-related CO2 emission and GDP in China," Energy, Elsevier, vol. 128(C), pages 11-18.
    4. Fernández González, P. & Landajo, M. & Presno, M.J., 2014. "Tracking European Union CO2 emissions through LMDI (logarithmic-mean Divisia index) decomposition. The activity revaluation approach," Energy, Elsevier, vol. 73(C), pages 741-750.
    5. Farla, Jacco & Cuelenaere11, Rob & Blok, Kornelis, 1998. "Energy efficiency and structural change in the Netherlands, 1980-1990," Energy Economics, Elsevier, vol. 20(1), pages 1-28, February.
    6. Ang, B.W., 2015. "LMDI decomposition approach: A guide for implementation," Energy Policy, Elsevier, vol. 86(C), pages 233-238.
    7. Norman, Jonathan B., 2017. "Measuring improvements in industrial energy efficiency: A decomposition analysis applied to the UK," Energy, Elsevier, vol. 137(C), pages 1144-1151.
    8. Farla, Jacco C.M & Blok, Kornelis, 2000. "The use of physical indicators for the monitoring of energy intensity developments in the Netherlands, 1980–1995," Energy, Elsevier, vol. 25(7), pages 609-638.
    9. Akerboom, Sanne & Botzen, Wouter & Buijze, Anoeska & Michels, Ank & van Rijswick, Marleen, 2020. "Meeting goals of sustainability policy: CO2 emission reduction, cost-effectiveness and societal acceptance. An analysis of the proposal to phase-out coal in the Netherlands," Energy Policy, Elsevier, vol. 138(C).
    10. Jeong, Kyonghwa & Kim, Suyi, 2013. "LMDI decomposition analysis of greenhouse gas emissions in the Korean manufacturing sector," Energy Policy, Elsevier, vol. 62(C), pages 1245-1253.
    11. Cahill, Caiman J. & Ó Gallachóir, Brian P., 2012. "Combining physical and economic output data to analyse energy and CO2 emissions trends in industry," Energy Policy, Elsevier, vol. 49(C), pages 422-429.
    12. Ang, B.W. & Goh, Tian, 2019. "Index decomposition analysis for comparing emission scenarios: Applications and challenges," Energy Economics, Elsevier, vol. 83(C), pages 74-87.
    13. Ang, B.W. & Goh, Tian, 2018. "Bridging the gap between energy-to-GDP ratio and composite energy intensity index," Energy Policy, Elsevier, vol. 119(C), pages 105-112.
    14. Ang, B.W. & Xu, X.Y., 2013. "Tracking industrial energy efficiency trends using index decomposition analysis," Energy Economics, Elsevier, vol. 40(C), pages 1014-1021.
    15. Worrell, Ernst & Price, Lynn & Martin, Nathan & Farla, Jacco & Schaeffer, Roberto, 1997. "Energy intensity in the iron and steel industry: a comparison of physical and economic indicators," Energy Policy, Elsevier, vol. 25(7-9), pages 727-744.
    16. Wang, H. & Ang, B.W. & Su, Bin, 2017. "Assessing drivers of economy-wide energy use and emissions: IDA versus SDA," Energy Policy, Elsevier, vol. 107(C), pages 585-599.
    17. Deng, Guangyao & Xu, Yan, 2017. "Accounting and structure decomposition analysis of embodied carbon trade: A global perspective," Energy, Elsevier, vol. 137(C), pages 140-151.
    18. Cansino, José M. & Román, Rocío & Ordóñez, Manuel, 2016. "Main drivers of changes in CO2 emissions in the Spanish economy: A structural decomposition analysis," Energy Policy, Elsevier, vol. 89(C), pages 150-159.
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    More about this item

    Keywords

    Activity revaluation approach; Carbon to GDP ratio (CGR); Composite Carbon Intensity (CCI); Logarithmic Mean Divisia Index (LMDI); Manufacturing; Physical activity data;
    All these keywords.

    JEL classification:

    • C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation
    • L62 - Industrial Organization - - Industry Studies: Manufacturing - - - Automobiles; Other Transportation Equipment; Related Parts and Equipment
    • L63 - Industrial Organization - - Industry Studies: Manufacturing - - - Microelectronics; Computers; Communications Equipment
    • L64 - Industrial Organization - - Industry Studies: Manufacturing - - - Other Machinery; Business Equipment; Armaments
    • L65 - Industrial Organization - - Industry Studies: Manufacturing - - - Chemicals; Rubber; Drugs; Biotechnology; Plastics
    • L66 - Industrial Organization - - Industry Studies: Manufacturing - - - Food; Beverages; Cosmetics; Tobacco
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy
    • Q50 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - General

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