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Improving the Methodology for Determining the Biomass/Coal Co-Combustion Ratio: Predictive Modeling of the 14 C Activity of Pure Biomass

Author

Listed:
  • Yinchen Wang

    (State Key Laboratory of Clean Energy Utilization, Zhejiang University, Hangzhou 310027, China)

  • Zhongyang Luo

    (State Key Laboratory of Clean Energy Utilization, Zhejiang University, Hangzhou 310027, China)

  • Chunjiang Yu

    (State Key Laboratory of Clean Energy Utilization, Zhejiang University, Hangzhou 310027, China)

  • Sheng Wang

    (State Key Laboratory of Clean Energy Utilization, Zhejiang University, Hangzhou 310027, China)

  • Xiaohuan Wang

    (State Key Laboratory of Clean Energy Utilization, Zhejiang University, Hangzhou 310027, China)

  • Peiliang Zhu

    (State Key Laboratory of Clean Energy Utilization, Zhejiang University, Hangzhou 310027, China)

Abstract

Sampling and 14 C detection of biomass are now essential steps to ensure the accuracy of the 14 C method, but they require additional time and economic investment. When there are multiple types of biomass fuels, it is not possible to guarantee the uniformity of sampling. The 14 C activity of biomass fuels exhibits variability, and this value significantly impacts the precision of the 14 C method. Therefore, this study aims to investigate the influencing factors of 14 C activity in biomass fuels. It also provides predicted values of 14 C activity for different types of biomass fuels for each year from 2020 to 2030. Additionally, this study discusses the potential blending ratio measurement errors that may arise due to the uncertainties of the predicted values. The reduction in the 14 C activity of biomass fuels can occur due to the utilization of fossil fuels, human activities, and the photosynthesis mode of C3 plants. This study presents a prediction method for determining the reduction factor. The other component of the prediction methodology involves determining the original 14 C activity of biomass fuels. The 14 C activity of the annual biomass is equal to the 14 CO 2 activity (the 14 C activity of CO 2 ) of the surrounding environment, and it experiences a decline of 0.355 pMC/year. The 14 C activity has ranges of five types of perennial biomass fuels, including wood chips and branches, bark, leaves, wasted furniture, and abandoned building wood, for the time period between 2020 and 2030, are 97.34~102.84, 96.35~106.27, 96.35~102.64, 111.00~118.60, and 111.32~129.47 pMC, respectively. Based on these, this study introduces a new formula for calculating blending ratios, which enhances the current methodology. The calculation errors of blending ratios caused by the uncertainties of the predicted values are generally negligible, with the exception of wasted furniture and construction wood. The annual decrease in the blending ratio calculation error, caused by the uncertainty associated with the predicted value, can be observed. This study aims to reduce the implementation time and economic cost of the 14 C method while ensuring the accuracy of biomass blending ratio detection.

Suggested Citation

  • Yinchen Wang & Zhongyang Luo & Chunjiang Yu & Sheng Wang & Xiaohuan Wang & Peiliang Zhu, 2024. "Improving the Methodology for Determining the Biomass/Coal Co-Combustion Ratio: Predictive Modeling of the 14 C Activity of Pure Biomass," Energies, MDPI, vol. 17(4), pages 1-23, February.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:4:p:942-:d:1340579
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    References listed on IDEAS

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    1. Yao Li & Liulin Yang & Tianlu Luo, 2023. "Energy System Low-Carbon Transition under Dual-Carbon Goals: The Case of Guangxi, China Using the EnergyPLAN Tool," Energies, MDPI, vol. 16(8), pages 1-16, April.
    2. Karol Król & Dorota Nowak-Woźny & Wojciech Moroń, 2023. "Study of Ash Sintering Temperature and Ash Deposition Behavior during Co-Firing of Polish Bituminous Coal with Barley Straw Using Non-Standard Tests," Energies, MDPI, vol. 16(11), pages 1-15, May.
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