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Publikasjoner

NIBIOs ansatte publiserer flere hundre vitenskapelige artikler og forskningsrapporter hvert år. Her finner du referanser og lenker til publikasjoner og andre forsknings- og formidlingsaktiviteter. Samlingen oppdateres løpende med både nytt og historisk materiale. For mer informasjon om NIBIOs publikasjoner, besøk NIBIOs bibliotek.

2023

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Sammendrag

Pyrolysis is a valid thermos-chemical process of energy production that produces biochar from potentially harmful biomasses. This study aims to investigate the pyrolytic conversion of olive mill solid residues (OMSR) into biochar, with the aim of characterizing this product towards applications for soil improvement and soil C sequestration. Production parameters of OMSR-biochar (OB) and physico-chemical characteristics were analyzed and compared with published data to assess the potential of OB to serve as a soil amendment and soil C sequestration method. The slow pyrolysis of OMSR at 450° leads to a good proportion between produced products (fuels liquid and gas, and solid), and generates about the 35% of OB. In turn, this product reveals the absence of phytotoxicity, the presence of exchangeable surface cations, structure, particle size distribution and external surface groups suitable for agricultural uses, and high C content with a potential long lasting in soil. The physico-chemical characteristics of OB reported here suggest that OB could be used for improving soils and increasing C sequestration in a sustainable way.

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Sammendrag

Numerical models are crucial to understand and/or predict past and future soil organic carbon dynamics. For those models aiming at prediction, validation is a critical step to gain confidence in projections. With a comprehensive review of ~250 models, we assess how models are validated depending on their objectives and features, discuss how validation of predictive models can be improved. We find a critical lack of independent validation using observed time series. Conducting such validations should be a priority to improve the model reliability. Approximately 60% of the models we analysed are not designed for predictions, but rather for conceptual understanding of soil processes. These models provide important insights by identifying key processes and alternative formalisms that can be relevant for predictive models. We argue that combining independent validation based on observed time series and improved information flow between predictive and conceptual models will increase reliability in predictions.