Publications
NIBIOs employees contribute to several hundred scientific articles and research reports every year. You can browse or search in our collection which contains references and links to these publications as well as other research and dissemination activities. The collection is continously updated with new and historical material.
2023
Authors
Chuan Ding Yi Zhang Xindu Li Qiang Liu Yeqing Li Yanjuan Lu Lu Feng Junting Pan Hongjun ZhouAbstract
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.
Abstract
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.
Abstract
No abstract has been registered
Authors
Yi Zhang Yijing Feng Zhonghao Ren Runguo Zuo Tianhui Zhang Yeqing Li Yajing Wang Zhiyang Liu Ziyan Sun Yongming Han Lu Feng Mortaza Aghbashlo Meisam Tabatabaei Junting PanAbstract
The ideal conditions for anaerobic digestion experiments with biochar addition are challenging to thoroughly study due to different experimental purposes. Therefore, three tree-based machine learning models were developed to depict the intricate connection between biochar properties and anaerobic digestion. For the methane yield and maximum methane production rate, the gradient boosting decision tree produced R2 values of 0.84 and 0.69, respectively. According to feature analysis, digestion time and particle size had a substantial impact on the methane yield and production rate, respectively. When particle sizes were in the range of 0.3–0.5 mm and the specific surface area was approximately 290 m2/g, corresponding to a range of O content (>31%) and biochar addition (>20 g/L), the maximum promotion of methane yield and maximum methane production rate were attained. Therefore, this study presents new insights into the effects of biochar on anaerobic digestion through tree-based machine learning.
Authors
Yi Zhang Zhangmu Jing Yijing Feng Shuo Chen Yeqing Li Yongming Han Lu Feng Junting Pan Mahmoud Mazarji Hongjun Zhou Xiaonan Wang Chunming XuAbstract
Exploring key factors has important guidance for understanding complex anaerobic digestion (AD) systems. This study proposed a multi-layer automated machine learning framework to understand the complex interactions in AD systems and explore key factors at the environmental factor, microorganisms and system levels. The first layer of the framework identified hydraulic residence time (HRT) as the most important environmental factor, with an optimal range of 33–45 d. In the second layer of the framework, Methanocelleus (optimal relative abundance (ORA) = 3.0%) and Candidatus_Caldatribacterium (ORA = 1.7%) were found to be the key archaea and bacteria, respectively. Furthermore, the prediction of key microorganisms based on environmental factors and remaining microbial data showed the essential roles of Methanothermobacter and Acetomicrobium. The third layer for finding the optimal combination of data variables for predicting biogas production demonstrated that combined Archaea genera and environmental factors should be achieved for the most accurate prediction (root mean square error (RMSE) = 84.21). GBM had the best model performance and prediction accuracy among all the built-in models. Based on the optimal GBM model, the analysis at the system level showed that HRT was the most important variable. However the most important microorganism, Methanocelleus, within the appropriate survival range is also essential to achieve optimal biogas production. This research explores key parameters at various levels through automated machine learning techniques, which are expected to provide guidance in understanding the complex architecture of industrial and laboratory AD systems.
Abstract
This report shows results from an experiment where it was investigated whether a powder of freeze-dried microalgae (Phaeodactylum tricornutum) had a biostimulating effect on the growth and content of nutrients and antioxidants in basil (Ocimum basilicum). The effect of the microalgae powder was tested as a supplement to either mineral fertilizer or a commercial organic fertilizer. We found no significant effect on the yield of applied microalgae powder, but there was a tendency for a higher yield with added microalgae powder for the treatment with organic fertiliser. This may be due to additional nitrogen supply with the microalgae powder. With mineral fertiliser, there was the opposite tendency, highest yield without microalgae powder. The only statistically significant effect of the microalgae powder was an increase in the concentration of boron for the treatment with organic fertiliser. This was probably an effect of a significant additional supply of boron with the microalgae biomass. There was a tendency for an increased concentration of copper with the addition of microalgae powder with both mineral and organic fertiliser, although the additional copper supply with the microalgae powder was small. With organic fertiliser, there was also a tendency towards increased phosphorus and potassium concentrations with the addition of microalgae powder. This could be a biostimulating effect as the additional phosphorus and potassium supply with the microalgae powder was small, but as mentioned, the effect was not statistically significant. We found no significant differences between the treatments for total antioxidant content.
Authors
Claire CoutrisAbstract
No abstract has been registered
Abstract
Tire wear particles (TWP) are a major source of microplastics that are mainly transported by stormwater from roads to the environment. Their risk has not yet been sufficiently evaluated, mainly because of the lack of suitable analytical methods for identifying and measuring their environmental concentrations. Moreover, TWP are persistent in the environment while their generation is increasing, which calls for action to limit their environmental spread. Conversely, stormwater management solutions are becoming a growing fixture in the road environment for their multipurpose role in controlling peak runoff and reducing pollution. However, knowledge of the effect of stormwater management solutions in removing TWP is limited. The overall goal of this Ph.D. study was to introduce a suitable analytical method for detecting and quantifying TWP in the environment and measuring the actual concentrations of TWP in sediments of stormwater management solutions associated with roads. Three study sites and laboratory experiments were used as data sources for the studies included in this thesis (Papers I–IV). Simultaneous thermal analysis (STA) and Fourier transform infrared spectroscopy (FTIR) were used to analyze the samples, and parallel factor analysis (PARAFAC) was used for data analysis. Analysis of variance (ANOVA) and t-tests were used for statistical analysis.
Authors
Claire CoutrisAbstract
No abstract has been registered
Authors
Márk Rékási Péter Ragályi Déniel Benjámin Sándor Anita Szabó Pierre-Adrien Rivier Csilla Farkas Orsolya Szécsy Nikolett UzingerAbstract
Vermicomposts and composts prepared from sewage sludge digestate and additives (spent mushroom compost, straw, biochar) after 43 days pre-composting followed by 90 days vermicomposting with Eisenia fetida or by compost maturing were investigated regarding the potentially toxic element (PTE) As, Co, Cr, Cu, Mo, Ni, Pb and Zn contents. The average increment in the total PTE concentration for the entire process was ten times higher (104 %) compared to the increment solely in the composting or vermicomposting (9.3 and 9.5 %, respectively) after pretreatment. Compared to the untreated digestate the As and Co concentrations in the final mixtures were 26 and 51 % higher, respectively while for the other PTEs 26 ± 9 % average decrease was observed. Total PTE content was the same in composts and vermicomposts. Average PTE bioavailability (water soluble/total concentration) was statistically the same in vermicomposts (2.5) and composts (2.7), but lower in mixtures with biochar (2.5) than without it (2.8).