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Uncertainty of the Electricity Emission Factor Incorporating the Uncertainty of the Fuel Emission Factors

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  • Kun Mo LEE

    (Department of Environmental and Safety Engineering, Ajou University, 206 Worldcup-ro, Yeongtong-gu, Suwon-si 16499, Korea)

  • Min Hyeok LEE

    (Global Manufacturing Center, SHE Group, Samsung Electro-Mechanics, 150, Maeyeong-ro, Yeongtong-gu, Suwon-si 16674, Gyeonggi-do, Korea)

Abstract

Greenhouse gas (GHG) emission from electricity generation has been recognized as one of the most significant contributors to global warming. The GHG emission factor of electricity (hereafter, electricity emission factor) can be expressed as a function of three different (average, minimum, and maximum) fuel emission factors, monthly fuel consumption, and monthly net power generation. Choosing the average fuel emission factor over the minimum and maximum fuel emission factors is the cause of uncertainty in the electricity emission factor, and thus GHG emissions of the power generation. The uncertainties of GHG emissions are higher than those of the electricity emission factor, indicating that the uncertainty of GHG emission propagates in the GHG emission computation model. The bootstrapped data were generated by applying the bootstrap method to the original data set which consists of a 60-monthly average, and minimum and maximum electricity emission factors. The bootstrapped data were used for computing the mean, confidence interval (CI), and percentage uncertainty (U) of the electricity emission factor. The CI, mean, and U were [0.431, 0.443] kg CO 2 -eq/kWh, 0.437 kg CO 2 -eq/kwh, and 2.56%, respectively.

Suggested Citation

  • Kun Mo LEE & Min Hyeok LEE, 2021. "Uncertainty of the Electricity Emission Factor Incorporating the Uncertainty of the Fuel Emission Factors," Energies, MDPI, vol. 14(18), pages 1-14, September.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:18:p:5697-:d:632871
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    References listed on IDEAS

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    Cited by:

    1. Michel Noussan & Matteo Jarre, 2021. "Assessing Commuting Energy and Emissions Savings through Remote Working and Carpooling: Lessons from an Italian Region," Energies, MDPI, vol. 14(21), pages 1-19, November.

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