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

Sampling and C-14 detection of biomass are now essential steps to ensure the accuracy of the C-14 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 C-14 activity of biomass fuels exhibits variability, and this value significantly impacts the precision of the C-14 method. Therefore, this study aims to investigate the influencing factors of C-14 activity in biomass fuels. It also provides predicted values of C-14 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 C-14 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 C-14 activity of biomass fuels. The C-14 activity of the annual biomass is equal to the (CO2)-C-14 activity (the C-14 activity of CO2) of the surrounding environment, and it experiences a decline of 0.355 pMC/year. The C-14 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 similar to 102.84, 96.35 similar to 106.27, 96.35 similar to 102.64, 111.00 similar to 118.60, and 111.32 similar to 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 C-14 method while ensuring the accuracy of biomass blending ratio detection.