IHSS&IWA26 / BRNO / CZECHIA / 23–28 August 2026 BOOK OF ABSTRACTS 194 Poster Session / Soil Organic Matter, Caustobiolites, and Biochar Hall A clustering of each compound class. Strong quantitative correlations (R² > 0.69) were observed between EGA thermogram peak heights and stepwise Py-GC/MS compound abundances. Depth-resolved thermograms showed decreasing polysaccharide and nitrogenous signals and increasing aromatic and aliphatic signals with depth, consistent with progressive humification, corroborated by increasing humification degree and C/N ratio. A radar plot–based visualization using the four markerion groups revealed clear spatial and temporal compositional variations. A matrix addition experiment confirmed robustness against mineral content variability (CV ≤ 7.6%). Conclusion EGA-MS, combined with selected marker ions, provides a practical, solventfree, and high-throughput approach for the chemical characterization of Scottish peat [1]. The method captures major compositional trends related to humification, depth, and site-specific conditions, with quantitative reliability validated against stepwise Py-GC/ MS. It offers significant advantages in throughput and operational simplicity, making it well suited for environmental monitoring and industrial quality control in the Scotch whisky industry. References 1. X. Chu, N. Takeda, N. Fujitake, S. Yanaka, Y. Fuse, J. Chromatogr. A 1757 (2025) 466142. 2. B.M. Harrison, F.G. Priest, J. Agric. Food Chem. 57 (2009) 2385–2391. 3. N. Katsumi et al., Talanta 155 (2016) 28–37. Acknowledgement This work was supported by JSPS KAKENHI Grant Numbers 22H03723, 20H04307, and 17K00519.
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