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Strategy to enhance the semicontinuous anaerobic digestion of food waste via exogenous additives: experimental and machine learning approaches

The anaerobic digestion (AD) of food waste (FW) was easy to acidify and accumulate ammonia nitrogen. Adding exogenous materials to the AD system can enhance its conversion efficiency by alleviating acidification and ammonia nitrogen inhibition. This work investigated the effects of the addition freq...

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Autores principales: Ding, Chuan, Zhang, Yi, Li, Xindu, Liu, Qiang, Li, Yeqing, Lu, Yanjuan, Feng, Lu, Pan, Junting, Zhou, Hongjun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Royal Society of Chemistry 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10695191/
http://dx.doi.org/10.1039/d3ra05811e
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author Ding, Chuan
Zhang, Yi
Li, Xindu
Liu, Qiang
Li, Yeqing
Lu, Yanjuan
Feng, Lu
Pan, Junting
Zhou, Hongjun
author_facet Ding, Chuan
Zhang, Yi
Li, Xindu
Liu, Qiang
Li, Yeqing
Lu, Yanjuan
Feng, Lu
Pan, Junting
Zhou, Hongjun
author_sort Ding, Chuan
collection PubMed
description The anaerobic digestion (AD) of food waste (FW) was easy to acidify and accumulate ammonia nitrogen. Adding exogenous materials to the AD system can enhance its conversion efficiency by alleviating acidification and ammonia nitrogen inhibition. This work investigated the effects of the addition frequency and additive amount on the AD of FW with increasing organic loading rate (OLR). When the OLR was 3.0 g VS per L per day and the concentration of the additives was 0.5 g per L per day, the stable methane yield reached 263 ± 22 mL per g VS, which was higher than that of the group without the additives (189 mL per g VS). Methanosaetaceae was the dominant archaea, with a maximum abundance of 93.25%. Through machine learning analysis, it was found that the optimal daily methane yield could be achieved. When the OLR was within the range of 0–3.0 g VS per L per day, the pH was within the range of 7.6–8.0, and the additive concentration was more than 0.5 g per L per day. This study proposed a novel additive and determined its usage strategy for regulating the AD of FW through experimental and simulation approaches.
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spelling pubmed-106951912023-12-05 Strategy to enhance the semicontinuous anaerobic digestion of food waste via exogenous additives: experimental and machine learning approaches Ding, Chuan Zhang, Yi Li, Xindu Liu, Qiang Li, Yeqing Lu, Yanjuan Feng, Lu Pan, Junting Zhou, Hongjun RSC Adv Chemistry The anaerobic digestion (AD) of food waste (FW) was easy to acidify and accumulate ammonia nitrogen. Adding exogenous materials to the AD system can enhance its conversion efficiency by alleviating acidification and ammonia nitrogen inhibition. This work investigated the effects of the addition frequency and additive amount on the AD of FW with increasing organic loading rate (OLR). When the OLR was 3.0 g VS per L per day and the concentration of the additives was 0.5 g per L per day, the stable methane yield reached 263 ± 22 mL per g VS, which was higher than that of the group without the additives (189 mL per g VS). Methanosaetaceae was the dominant archaea, with a maximum abundance of 93.25%. Through machine learning analysis, it was found that the optimal daily methane yield could be achieved. When the OLR was within the range of 0–3.0 g VS per L per day, the pH was within the range of 7.6–8.0, and the additive concentration was more than 0.5 g per L per day. This study proposed a novel additive and determined its usage strategy for regulating the AD of FW through experimental and simulation approaches. The Royal Society of Chemistry 2023-12-04 /pmc/articles/PMC10695191/ http://dx.doi.org/10.1039/d3ra05811e Text en This journal is © The Royal Society of Chemistry https://creativecommons.org/licenses/by-nc/3.0/
spellingShingle Chemistry
Ding, Chuan
Zhang, Yi
Li, Xindu
Liu, Qiang
Li, Yeqing
Lu, Yanjuan
Feng, Lu
Pan, Junting
Zhou, Hongjun
Strategy to enhance the semicontinuous anaerobic digestion of food waste via exogenous additives: experimental and machine learning approaches
title Strategy to enhance the semicontinuous anaerobic digestion of food waste via exogenous additives: experimental and machine learning approaches
title_full Strategy to enhance the semicontinuous anaerobic digestion of food waste via exogenous additives: experimental and machine learning approaches
title_fullStr Strategy to enhance the semicontinuous anaerobic digestion of food waste via exogenous additives: experimental and machine learning approaches
title_full_unstemmed Strategy to enhance the semicontinuous anaerobic digestion of food waste via exogenous additives: experimental and machine learning approaches
title_short Strategy to enhance the semicontinuous anaerobic digestion of food waste via exogenous additives: experimental and machine learning approaches
title_sort strategy to enhance the semicontinuous anaerobic digestion of food waste via exogenous additives: experimental and machine learning approaches
topic Chemistry
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10695191/
http://dx.doi.org/10.1039/d3ra05811e
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