TY - JOUR
T1 - Quantifying inertinite carbon in biochar
AU - Sanei, Hamed
AU - Wojtaszek-Kalaitzidi, Małgorzata
AU - Schovsbo, Niels Hemmingsen
AU - Stenshøj, Rasmus
AU - Zhou, Zhiheng
AU - Schmidt, Hans Peter
AU - Hagemann, Nikolas
AU - Chiaramonti, David
AU - Kiaitsis, Tryfonas
AU - Rudra, Arka
AU - Lehner, Anna J.
AU - Brown, Robert W.
AU - Gill, Sophie
AU - Dorr, Erica
AU - Kalaitzidis, Stavros
AU - Goodarzi, Fariborz
AU - Petersen, Henrik Ingermann
N1 - Publisher Copyright:
© 2025
PY - 2025/11/5
Y1 - 2025/11/5
N2 - The carbon dioxide removal (CDR) potential of biochar is determined by the long-term stability of its biogenic carbon, derived from atmospheric CO₂ fixed by photosynthesis and stabilized in solid form. This stability (carbon permanence) is commonly assessed using decay models to evaluate resistance to re-emission as greenhouse gases. However, these models are limited, as they focus primarily on short-term degradation of labile carbon fractions and are not suited to project the behavior of the highly recalcitrant component of biochar over extended timescales. Inertinite represents highly aromatized and condensed carbon structures that are geochemically stable over millennia. This paper builds upon the Inertinite Benchmarking (IBRo2) methodology, directly quantifying the stable carbon fraction in biochar rather than relying on modeling. The method combines thermochemical analysis and incident-light microscopy to measure the reactive (labile) component and solid carbonized macerals, respectively. Random reflectance analysis (Ro) provides a representative distribution of carbonization states, with Ro values >2.0 % defining the inertinite fraction after discounting reactive organic carbon. The Ro distribution is processed using kernel density estimation (KDE) and numerical integration to classify inertinite carbon with precision and statistical robustness. As CDR crediting can be linked to measured inertinite content, statistical validity is essential. A Monte Carlo simulation model evaluates uncertainties from sampling frequency and production variability. Results show that increased sampling reduces uncertainty and lowers the conservative safety margin needed for potential errors. This framework supports a justified safety margin applied to reported inertinite carbon and corresponding CDR values, enabling conservative and robust crediting. By combining direct quantification of inertinite carbon with probabilistic modeling of uncertainty, the IBRo2 method offers a transparent and rigorous framework for assessing biochar permanence, aligned with emerging international certification and national inventory methodologies.
AB - The carbon dioxide removal (CDR) potential of biochar is determined by the long-term stability of its biogenic carbon, derived from atmospheric CO₂ fixed by photosynthesis and stabilized in solid form. This stability (carbon permanence) is commonly assessed using decay models to evaluate resistance to re-emission as greenhouse gases. However, these models are limited, as they focus primarily on short-term degradation of labile carbon fractions and are not suited to project the behavior of the highly recalcitrant component of biochar over extended timescales. Inertinite represents highly aromatized and condensed carbon structures that are geochemically stable over millennia. This paper builds upon the Inertinite Benchmarking (IBRo2) methodology, directly quantifying the stable carbon fraction in biochar rather than relying on modeling. The method combines thermochemical analysis and incident-light microscopy to measure the reactive (labile) component and solid carbonized macerals, respectively. Random reflectance analysis (Ro) provides a representative distribution of carbonization states, with Ro values >2.0 % defining the inertinite fraction after discounting reactive organic carbon. The Ro distribution is processed using kernel density estimation (KDE) and numerical integration to classify inertinite carbon with precision and statistical robustness. As CDR crediting can be linked to measured inertinite content, statistical validity is essential. A Monte Carlo simulation model evaluates uncertainties from sampling frequency and production variability. Results show that increased sampling reduces uncertainty and lowers the conservative safety margin needed for potential errors. This framework supports a justified safety margin applied to reported inertinite carbon and corresponding CDR values, enabling conservative and robust crediting. By combining direct quantification of inertinite carbon with probabilistic modeling of uncertainty, the IBRo2 method offers a transparent and rigorous framework for assessing biochar permanence, aligned with emerging international certification and national inventory methodologies.
KW - Biochar permanence
KW - Carbon dioxide removal (CDR)
KW - Inertinite benchmarking
KW - Random reflectance (R)
KW - Sampling frequency
UR - https://www.scopus.com/pages/publications/105018173356
U2 - 10.1016/j.coal.2025.104886
DO - 10.1016/j.coal.2025.104886
M3 - Article
AN - SCOPUS:105018173356
SN - 0166-5162
VL - 310
JO - International Journal of Coal Geology
JF - International Journal of Coal Geology
M1 - 104886
ER -