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Uncertainty Analysis for the CH 4 Emission Factor of Thermal Power Plant by Monte Carlo Simulation

Author

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  • Changsang Cho

    (Climate Chang Research Center, Sejong University, Seoul 05006, Korea)

  • Seongmin Kang

    (Climate Chang Research Center, Sejong University, Seoul 05006, Korea)

  • Minwook Kim

    (Department of Environment & Energy, Sejong University, Seoul 05006, Korea)

  • Yoonjung Hong

    (Climate Chang Research Center, Sejong University, Seoul 05006, Korea)

  • Eui-chan Jeon

    (Department of Environment & Energy, Sejong University, Seoul 05006, Korea)

Abstract

Thermal power plants are a large source of greenhouse gas emissions among energy industry facilities. Emission factors for methane and nitrous oxide depend on combustion technologies and operating conditions and vary significantly with individual thermal power plants. Due to this variability, use of average emission factors for these gases will introduce relatively large uncertainties. This study determined the CH 4 emission factors of thermal power plants currently in operation in Korea by conducting field investigations according to fuel type and type of combustion technique. Through use of the Monte Carlo simulation, the uncertainty range for the CH 4 emission factor was determined. The estimation showed, at the 95% confidence level, that the uncertainty range for CH 4 emission factor from a tangential firing boiler using bituminous coal was −46.6% to +145.2%. The range for the opposed wall-firing boiler was −25.3% to +70.9%. The range for the tangential firing boiler using fuel oil was −39.0% to 93.5%, that from the opposed wall-firing boiler was −47.7% to +201.1%, and that from the internal combustion engine boiler was −38.7% to +106.1%. Finally, the uncertainty range for the CH 4 emission factor from the combined cycle boiler using LNG was −90% to +326%.

Suggested Citation

  • Changsang Cho & Seongmin Kang & Minwook Kim & Yoonjung Hong & Eui-chan Jeon, 2018. "Uncertainty Analysis for the CH 4 Emission Factor of Thermal Power Plant by Monte Carlo Simulation," Sustainability, MDPI, vol. 10(10), pages 1-14, September.
  • Handle: RePEc:gam:jsusta:v:10:y:2018:i:10:p:3448-:d:172369
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    Citations

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    Cited by:

    1. Nima Pirhadi & Xiaowei Tang & Qing Yang & Fei Kang, 2018. "A New Equation to Evaluate Liquefaction Triggering Using the Response Surface Method and Parametric Sensitivity Analysis," Sustainability, MDPI, vol. 11(1), pages 1-24, December.
    2. Shuo Sun & Linwei Ma & Zheng Li, 2022. "A Source-Level Estimation and Uncertainty Analysis of Methane Emission in China’s Oil and Natural Gas Sector," Energies, MDPI, vol. 15(10), pages 1-18, May.

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