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Comparative analysis of carbon dioxide emission factors for energy industries in European Union countries

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  • Konstantinaviciute, Inga
  • Bobinaite, Viktorija

Abstract

Strategies for mitigating climate change require accurate estimates of the greenhouse gas (GHG) emissions. Estimates of the amounts of carbon dioxide (CO2) and other GHGs emitted into the atmosphere are crucial for planning and analyzing mitigation efforts. Emissions factors are the fundamental tool in developing national emissions inventories. The quality of GHG inventories has been a long-standing issue among the scientific community and its importance has more recently risen on the policy agenda because national inventories are now the basis of legally-binding commitments. According to the IPCC Good Practice Guidance comparison with the recommended IPCC default values may be informative in establishing the comparability of the country-specificity of the emission factors used. Such comparison may help to identify data outlier where uncertainty ranges do not overlap. The main objective of this article is to assess comparability of CO2 emissions factors between EU countries for energy industries and to evaluate whether the reporting of emissions from energy industries is good enough to monitor progress towards the emission reduction targets set under international agreements according to the quality criteria of transparency, consistency, comparability, completeness and accuracy. Performed analysis of CO2 emission factors showed that almost all EU countries seeking to reduce uncertainty apply country-specific CO2 emission factors for major sources of emissions from energy industries. Application of country-specific emission factors ensures greater accuracy and lower uncertainty of GHG inventory. Comparative analysis showed that country-specific CO2 emission factors applied in EU countries for the main fuels combusted in the energy industries have been established in a comparable way taking into account uncertainty ranges defined in the IPCC Guidelines. Seeking to ensure more accurate estimates of CO2 emissions it is important further improve knowledge on emission factors at individual plant level that allow estimating GHG emissions with lower uncertainty applying higher level tier methods.

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  • Konstantinaviciute, Inga & Bobinaite, Viktorija, 2015. "Comparative analysis of carbon dioxide emission factors for energy industries in European Union countries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 51(C), pages 603-612.
    • Handle: RePEc:eee:rensus:v:51:y:2015:i:c:p:603-612
    DOI: 10.1016/j.rser.2015.06.058
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    References listed on IDEAS

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    1. Gregg Marland & Khrystyna Hamal & Matthias Jonas, 2009. "How Uncertain Are Estimates of CO2 Emissions?," Journal of Industrial Ecology, Yale University, vol. 13(1), pages 4-7, February.
    2. Nina Uvarova & Vladimir Kuzovkin & Sergey Paramonov & Michael Gytarsky, 2014. "The improvement of greenhouse gas inventory as a tool for reduction emission uncertainties for operations with oil in the Russian Federation," Climatic Change, Springer, vol. 124(3), pages 535-544, June.
    3. Myroslava Lesiv & Andriy Bun & Matthias Jonas, 2014. "Analysis of change in relative uncertainty in GHG emissions from stationary sources for the EU 15," Climatic Change, Springer, vol. 124(3), pages 505-518, June.
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    3. Wang, Yihan & Wen, Zongguo & Yao, Jianguo & Doh Dinga, Christian, 2020. "Multi-objective optimization of synergic energy conservation and CO2 emission reduction in China's iron and steel industry under uncertainty," Renewable and Sustainable Energy Reviews, Elsevier, vol. 134(C).
    4. Chen, Jiandong & Cheng, Shulei & Song, Malin & Wu, Yinyin, 2016. "A carbon emissions reduction index: Integrating the volume and allocation of regional emissions," Applied Energy, Elsevier, vol. 184(C), pages 1154-1164.
    5. Su, Meirong & Pauleit, Stephan & Yin, Xuemei & Zheng, Ying & Chen, Shaoqing & Xu, Chao, 2016. "Greenhouse gas emission accounting for EU member states from 1991 to 2012," Applied Energy, Elsevier, vol. 184(C), pages 759-768.
    6. Feng, Zhiying & Tang, Wenhu & Niu, Zhewen & Wu, Qinghua, 2018. "Bi-level allocation of carbon emission permits based on clustering analysis and weighted voting: A case study in China," Applied Energy, Elsevier, vol. 228(C), pages 1122-1135.
    7. Ozturk, Fatma & Keles, Melek & Evrendilek, Fatih, 2016. "Quantifying rates and drivers of change in long-term sector- and country-specific trends of carbon dioxide-equivalent greenhouse gas emissions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 65(C), pages 823-831.

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