Coupling pyrolysis with mid-infrared spectroscopy for the characterization of soil organic matter

Soil organic matter (SOM) is known to play an important role in the global carbon cycle due to its ability to sequester atmospheric carbon dioxide (CO2) and maintenance of soil physical, chemical, and biological properties. Due to the growing need to enhance the understanding of SOM composition and dynamics as influenced by natural and anthropogenic factors, in addition to the limited ability to exist analytical techniques to provide in-depth knowledge into the constituents of SOM, a lot of research is currently focused on the development of new techniques to address the aforementioned concerns. In this study, a novel analytical technique, pyrolysis coupled with mid-infrared spectroscopy (Py-MIRS) was developed and applied to study SOM bulk chemistry in soils by measuring certain mid-infrared organic functional groups. Secondly, the developed Py-MIRS technique was applied to soil samples from different long term experiments to investigate the effects of agricultural management practices and land uses by monitoring the different functional groups. Lastly, the implications of methodological considerations of diffuse reflectance Fourier transform mid-infrared spectroscopy (DRIFTS) on specific mid-infrared functional groups and quality indices were investigated on soils from a number of long-term field experiments. Py-MIRS was developed by testing critical experimental conditions like pyrolysis temperature, heating rate, and time using a range of reference standard compounds varying in chemical and structural composition and bulk soils. As a next step in the methodological development, the suitability of the newly developed Py-MIRS was further evaluated by testing the effect of long-term management and land use on the molecular composition of SOM in bulk soils taken from long-term field experiments in Ultuna, Sweden, and Lusignan, France. The newly developed Py-MIRS technique and the evaluation of the effect of drying temperatures on peak areas obtained with DRIFTS demonstrate progress in the use of pyrolytic and spectroscopic techniques in the domain of SOM characterization. Py-MIRS revealed its potential as a rapid, reproducible, and effective technique to yield information on SOM molecular composition with minimal constraints due to mineral interferences and secondary thermal reactions. Py-MIRS also provided some insights into sustainable practices that improve SOM quality. However, the technique requires further development and testing on different clay mineralogies and land uses.Die organische Bodensubstanz (OBS) spielt aufgrund der Möglichkeit atmosphärisches CO2 zu speichern, sowie ihrem Beitrag zum Erhalt der physikalischen, chemischen und biologischen Bodeneigenschaften, eine wichtige Rolle im globalen Kohlenstoffkreislauf. Es besteht ein wachsender Bedarf die Zusammensetzung und Dynamiken von OBS zu verstehen, insbesondere wie diese durch natürliche und anthropogene Faktoren beeinflusst werden. Zudem sind die derzeit vorhandenen Analysetechniken zur Bestimmung der Zusammensetzung von OBS in ihrer Eignung begrenzt. Die Entwicklung neuer Techniken zur Untersuchung der OBS Zusammensetzung ist daher ein wichtiges Anliegen der Wissenschaft. In der vorliegenden Arbeit wurde eine neue Analysetechnik, Pyrolyse gekoppelt mit Spektroskopie im mittleren Infrarot-Bereich (Py-MIRS), entwickelt und angewandt, mit dem Ziel die molekulare Zusammensetzung von OBS in Böden, durch die Messung bestimmter funktionaler organischer Verbindungen, zu bestimmen. In einem zweiten Schritt wurde die entwickelte Py-MIRS Technik zur Messung von Bodenproben verschiedener Langzeitversuche angewandt. Hierbei wurde der Effekt unterschiedlicher landwirtschaftlicher Praktiken und Landnutzungen, durch Monitoring funktionaler organischer Verbindungen, untersucht. Zuletzt wurden die Implikationen methodologischer Abschätzungen von Diffus-Reflexions-Infrarot-Fourier-Transformations-Spektroskopie (DRIFTS) auf bestimmte funktionale organische Verbindungen und Qualitätsindexe auf Böden einer Reihe von Langzeitfeldversuchen erforscht. Die entwickelte Py-MIRS Technik sowie die Erforschung des Effekts der Trockentemperatur auf DRIFTS Peakflächen markieren einen bedeutenden Fortschritt in der Nutzung pyrolytischer und spektraler Techniken im Bereich der OBS Klassifizierung. Py-MIRS zeigte Potential als schnelle, reproduzierbare und effektive Technik um Informationen über die molekulare Zusammensetzung von OBS, mit minimalen Einschränkungen aufgrund von Mineralinterferenz und sekundären thermischen Reaktionen, zu gewinnen. Zudem bot Py-MIRS Einblicke in nachhaltige Praktiken zur Verbesserung der OBS Qualität. Weitere Tests und eine Weiterentwicklung der Technik sind jedoch für Böden anderer Tonmineralogie sowie für andere Landnutzungen nötig

DRIFTS band areas as measured pool size proxy to reduce parameter uncertainty in soil organic matter models

Soil organic matter (SOM) turnover models predict changes in SOM due to management and environmental factors. Their initialization remains challenging as partitioning of SOM into different hypothetical pools is intrinsically linked to model assumptions. Diffuse reflectance mid-infrared Fourier transform spectroscopy (DRIFTS) provides information on SOM quality and could yield a measurable pool-partitioning proxy for SOM. This study tested DRIFTS-derived SOM pool partitioning using the Daisy model. The DRIFTS stability index (DSI) of bulk soil samples was defined as the ratio of the area below the aliphatic absorption band (2930 cm(-1)) to the area below the aromatic- carboxylate absorption band (1620 cm(-1)). For pool partitioning, the DSI (2930 cm(-1) / 1620 cm(-1)) was set equal to the ratio of fast-cycling / slow-cycling SOM. Performance was tested by simulating long-term bare fallow plots from the Bad Lauchstadt extreme farmyard manure experiment in Germany (Chernozem, 25 years), the Ultuna continuous soil organic matter field experiment in Sweden (Cambisol, 50 years), and 7 year duration bare fallow plots from the Kraichgau and Swabian Jura regions in southwest Germany (Luvisols). All experiments were at sites that were agricultural fields for centuries before fallow establishment, so classical theory would suggest that a steady state can be assumed for initializing SOM pools. Hence, steady-state and rameter sets that differed in turnover rates and humification efficiency. Initialization using the DSI significantly reduced Daisy model error for total soil organic carbon and microbial carbon in cases where assuming a steady state had poor model performance. This was irrespective of the parameter set, but faster turnover performed better for all sites except for Bad Lauchstadt. These results suggest that soils, although under long-term agricultural use, were not necessarily at a steady state. In a next step, Bayesian-calibration-inferred best-fitting turnover rates for Daisy using the DSI were evaluated for each individual site or for all sites combined. Two approaches significantly reduced parameter uncertainty and equifinality in Bayesian calibrations: (1) adding physicochemical meaning with the DSI (for humification efficiency and slow SOM turnover) and (2) combining all sites (for all parameters). Individual-site-derived turnover rates were strongly site specific. The Bayesian calibration combining all sites suggested a potential for rapid SOM loss with 95 % credibility intervals for the slow SOM pools' halflife being 278 to 1095 years (highest probability density at 426 years). The credibility intervals of this study were consistent with several recently published Bayesian calibrations of similar two-pool SOM models, i.e., with turnover rates being faster than earlier model calibrations suggested; hence they likely underestimated potential SOM losses