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Key Factors Influencing the Achievement of Climate Neutrality Targets in the Manufacturing Industry: LMDI Decomposition Analysis

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  • Kristiāna Dolge

    (Institute of Energy Systems and Environment, Faculty of Electrical and Environmental Engineering, Riga Technical University, LV-1048 Riga, Latvia)

  • Dagnija Blumberga

    (Institute of Energy Systems and Environment, Faculty of Electrical and Environmental Engineering, Riga Technical University, LV-1048 Riga, Latvia)

Abstract

The manufacturing industry is often caught in the sustainability dilemma between economic growth targets and climate action plans. In this study, a Log-Mean Divisia Index (LMDI) decomposition analysis is applied to investigate how the amount of industrial energy-related CO 2 emissions in Latvia has changed in the period from 1995 to 2019. The change in aggregate energy-related CO 2 emissions in manufacturing industries is measured by five different factors: the industrial activity effect, structural change effect, energy intensity effect, fuel mix effect, and emission intensity effect. The decomposition analysis results showed that while there has been significant improvement in energy efficiency and decarbonization measures in industry, in recent years, the impact of the improvements has been largely offset by increased industrial activity in energy-intensive sectors such as wood processing and non-metallic mineral production. The results show that energy efficiency measures in industry contribute most to reducing carbon emissions. In the future, additional policies are needed to accelerate the deployment of clean energy and energy efficiency technologies.

Suggested Citation

  • Kristiāna Dolge & Dagnija Blumberga, 2021. "Key Factors Influencing the Achievement of Climate Neutrality Targets in the Manufacturing Industry: LMDI Decomposition Analysis," Energies, MDPI, vol. 14(23), pages 1-23, November.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:23:p:8006-:d:691992
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    References listed on IDEAS

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    Cited by:

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    2. Adeel Luqman & Qingyu Zhang & Shalini Talwar & Meena Bhatia & Amandeep Dhir, 2024. "Artificial intelligence and corporate carbon neutrality: A qualitative exploration," Business Strategy and the Environment, Wiley Blackwell, vol. 33(5), pages 3986-4003, July.
    3. Dolge, Kristiāna & Barisa, Aiga & Kirsanovs, Vladimirs & Blumberga, Dagnija, 2023. "The status quo of the EU transport sector: Cross-country indicator-based comparison and policy evaluation," Applied Energy, Elsevier, vol. 334(C).
    4. Di Peng & Haibin Liu, 2022. "Measurement and Driving Factors of Carbon Emissions from Coal Consumption in China Based on the Kaya-LMDI Model," Energies, MDPI, vol. 16(1), pages 1-19, December.
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    6. Daiva Makutėnienė & Dalia Perkumienė & Valdemaras Makutėnas, 2022. "Logarithmic Mean Divisia Index Decomposition Based on Kaya Identity of GHG Emissions from Agricultural Sector in Baltic States," Energies, MDPI, vol. 15(3), pages 1-26, February.

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