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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

Rapporten omhandler muligheter for bruk av organiske restfraksjoner i Lierne kommune. Produsentene av restfraksjoner i Lierne har i dag etablerte rutiner og avtaler for å håndtere avfallet sitt, og restfraksjonen blir håndtert på en hensiktsmessig måte. Bedriftene har begrenset kapasitet og anleggsressurser for å videreforedle restressursene. Det ligger likevel gode muligheter i sambehandling av avfall fra flere næringsaktører. Gjerne i sambehandling med husdyrgjødsel og matavfall i biogassanlegg.

Sammendrag

De siste årene har det kommet en rekke bionedbrytbare plastvarianter, også i Norge. Men hvor nedbrytbar er egentlig denne plasten under norske forhold med relativt lave temperaturer? Brytes den fullstendig ned, eller omdannes den til makro- eller mikroplast i stedet? Gjennom prosjektet DGRADE – Nedbrytning av bionedbrytbar plast i jord og avfallsstrømmer har forskere forsøkt å finne svar på disse spørsmålene. De kan nå slå fast at plasten brytes ned, men kun hvis forholdene ligger til rette for det. Hvis ikke forholdene er gode nok, kan også nedbrytbare plastprodukter bidra til plastforsøpling

Sammendrag

Ny forskning viser at nedbrytbar plast brytes ned under norske forhold, men kun dersom den havner der den skal. Det vil si i industriell kompost eller i et jordmiljø der forholdene ligger til rette for at mikroorganismene kan bryte den ned.

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Sammendrag

Industrial-scale garage dry fermentation systems are extremely nonlinear, and traditional machine learning algorithms have low prediction accuracy. Therefore, this study presents a novel intelligent system that employs two automated machine learning (AutoML) algorithms (AutoGluon and H2O) for biogas performance prediction and Shapley additive explanation (SHAP) for interpretable analysis, along with multiobjective particle swarm optimization (MOPSO) for early warning guidance of industrial-scale garage dry fermentation. The stacked ensemble models generated by AutoGluon have the highest prediction accuracy for digester and percolate tank biogas performances. Based on the interpretable analysis, the optimal parameter combinations for the digester and percolate tank were determined in order to maximize biogas production and CH4 content. The optimal conditions for the digester involve maintaining a temperature range of 35–38 °C, implementing a daily spray time of approximately 10 min and a pressure of 1000 Pa, and utilizing a feedstock with high total solids content. Additionally, the percolate tank should be maintained at a temperature range of 35–38 °C, with a liquid level of 1500 mm, a pH range of 8.0–8.1, and a total inorganic carbon concentration greater than 13.8 g/L. The software developed based on the intelligent system was successfully validated in production for prediction and early warning, and MOPSO-recommended guidance was provided. In conclusion, the novel intelligent system described in this study could accurately predict biogas performance in industrial-scale garage dry fermentation and guide operating condition optimization, paving the way for the next generation of intelligent industrial systems.

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Sammendrag

The anaerobic digestion of organic materials produces biogas; however, optimizing methane (CH4) content within biogas plants by capturing carbon dioxide (CO2) is one of the challenges for sustainable biomethane production. CH4 is separated from biogas, which is called biogas upgrading for biomethane production. In this regard, in-situ CO2 capture and utilization could be an alternative approach that can be achieved using conductive particles, where the conductive particles support the direct intraspecific electron transfer (DIET) to promote CH4 production. In this investigation, a carbon nanotube (CNT) was grown over conductive activated carbon (AC). Then an iron (Fe) nanoparticle was anchored (AC/CNT/Fe), which ultimately supported microbes to build the biofilm matrix, thereby enhancing the DIET for CH4 formation. The biogas production and CH4 content increased by 17.57 % and 15.91 %, respectively, when AC/CNT/Fe was utilized. Additionally, 18S rRNA gene sequencing reveals that Methanosarcinaceae and Methanobacteriaceae families were the most dominant microbes in the reactor when conductive particles (AC/CNT/Fe) were applied. The proposed study supports the stable operation of biogas plants to utilize CO2 for CH4 production by using surface-modified material.