Biografi

Forskningsarbeidene mine tar primært sikte på å styrke anaerob fordøyelsesbasert sirkulær økonomi, rollen til anaerob fordøyelsesprosess på økologisk landbruk, dens effekt på resirkulering og flytting av næringsstoffene, og innvirkning på jords fruktbarhet og klimagassutslipp. For tiden har jeg interesser i å utvikle innovative bioteknologier for å konvertere organiske rester, til bioenergi, organiske syrer, protein, biometanering og syngassfermentering.

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Monophenols form humic acids (HA) through polycondensation reaction in the anaerobic digestion (AD) process, which will inhibit AD process. Currently, metal ions are the option for in-situ relieving HA inhibition during AD, but excess metal ions are harmful to microorganisms. In this study, carbon quantum dots (CQDs, a non-metallic materials) were proposed to relieve HA inhibition in-situ. We investigated the effect of HA on AD acidification and methanation stage, and synthesized CQDs using sodium citrate (s-CQDs) and p-phenylenediamine (p-CQDs) as precursors to relieve the HA inhibition in-situ. Results showed that s-CQDs (3.0 g/L) significantly increased the cumulative CH4 yield from AD of ethanol with 1.0 g/L HA (1.9 times higher than that without s-CQDs). Microbiological analysis indicated the most dominant methanogen was Methanosarcinaceae, with richness of 89.7%. Compared to the HA inhibition system, the relative abundance of Methanosarcinaceae increased by 87.5%. The analysis of interaction mechanism between CQDs and HA indicated that s-CQDs has an in-situ binding effect to HA by reacting with -OH, Cdouble bondC, and -COOH. This study provided a novel means for in-situ relieving HA inhibition, and illustrated the interaction mechanism between CQDs and HA, which will guide the application in production of bioenergy.

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Anaerobic digestion (AD) can be used as a stand-alone process or integrated as part of a larger biorefining process to produce biofuels, biochemicals and fertiliser, and has the potential to play a central role in the emerging circular bioeconomy (CBE). Agricultural residues, such as animal slurry, straw, and grass silage, represent an important resource and have a huge potential to boost biogas and methane yields. Under the CBE concept, there is a need to assess the long-term impact and investigate the potential accumulation of specific unwanted substances. Thus, a comprehensive literature review to summarise the benefits and environmental impacts of using agricultural residues for AD is needed. This review analyses the benefits and potential adverse effects related to developing biogas-centred CBE. The identified potential risks/challenges for developing biogas CBE include GHG emission, nutrient management, pollutants, etc. In general, the environmental risks are highly dependent on the input feedstocks and resulting digestate. Integrated treatment processes should be developed as these could both minimise risks and improve the economic perspective.

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Manure management is a significant source of methane (CH4) and ammonia (NH3), and there is an urgent need for strategies to reduce these emissions. More frequent export of manure for outside storage can lower gaseous emissions from housing facilities, but the longer residence time may then increase emissions during outside storage. This study examined CH4 and NH3 emissions from liquid pig manure (pig slurry) removed from the in-house slurry collection pits at three different frequencies, i.e., three times per week (T2.3), once per week (T7), or once after 40 days (T40, reference). The slurry from treatments T2.3 and T7 was transferred for outside storage weekly over four weeks, and slurry from treatment T40 once after 40 days, in connection with summer and winter production cycles with growing-finishing pigs. The slurry was stored in pilot-scale storage tanks with solid cover and continuous ventilation. Compared to T40, the treatments T2.3 and T7 increased CH4 emissions during outside storage, but in-house emissions were reduced even more, and the net effects on total CH4 emissions from manure management (housing unit and outside storage) were reductions of 18–41% in summer and 53–83% in winter. The frequent slurry export for outside storage led to more NH3 emissions, except for the treatment T2.3, which has slurry funnel inserts beneath the slatted floor. Measurements of in-vitro CH4 production rates suggested that shorter residence time for slurry in pig houses delayed the development of active methanogenic populations, and that this contributed to the reduction of CH4 emissions.

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In the anaerobic digestion (AD) process, the effects of humic acid (HA) derived from different feedstocks on AD are influenced by the variations in their structural composition and oxygen-containing functional groups. Thus, clarifying the structural differences of HA obtained from different feedstocks is crucial for understanding their impact on AD. In this study, the structure of five humic acids (HAs) derived from liquid digestate, food waste, silage corn straw, lignite and commercial HA, and their effects on AD were investigated. The study found that HA from food waste had more carboxyl groups, while straw-derived HA had more phenolic hydroxyl groups. Both types of HA had higher aromaticity and humification degree and showed significant inhibition effect on AD. HA from food waste had an average methanogenic inhibition rate of 43.5 % with 1 g/L HA added. In addition, commercial HA and HA derived from lignite had similar functional group types and aromaticity, with an average methanogenic inhibition rate of about 20 %. The study revealed that HAs with more carboxyl groups exhibited greater effectiveness in inhibiting AD, thereby confirming the influence of HA structures derived from different feedstocks on AD. In conclusion, this study provides valuable insights into the mechanism of HA effect on AD and offers guidance for future research focused on enhancing AD efficiency.

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The treatment of organic waste (OW) by anaerobic digestion (AD) conforms to the concept of sustainable development. But AD is facing the issue of low conversion rate. In this work, the photo-AD system using visible light (LED lamp) as the source was constructed and the performances and mechanism of N-doped carbon quantum dots (NCQD) were explored in the system for the first time. The results showed that 0.5 g/L NCQD promoted a 23.1 % increase in cumulative CH4 yield in the photo-AD system. Microbial analysis results showed that in photo-AD with NCQD, the dominant strain was Methanosarciniales, with an abundance of 69.0 %. Microbial activity and structural integrity tests showed that the microorganisms were not damaged by free radicals. In addition, NCQD increased the redox peak intensity of the CV curve and increased photocurrent intensity of photo-AD. Furthermore, it promoted an increase of 18.2 % (0.26 ± 0.03 μmol/mL) in ATP concentration. The photoelectrochemical analysis and quantitative analysis of functional genes results indicated that NCQD mainly promoted methanogenesis by providing photoelectrons. This promotion mechanism increased the copynumber (61,652.8 g−1) of EchA in photo-AD, rather than Vht and Hdr related to cytochrome. This work provided new strategies for the enhancement of AD and clarified potential mechanisms.

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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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Biowaste is becoming a significant category in the global energy mix to mitigate the negative impacts of burning fossil fuels. The aim of this review paper was to investigate the potential, conversion mechanisms, benefits, and policy gaps related to the utilization of solid biowaste resources as renewable, clean, and affordable energy sources. Thus, a systematic review approach was employed to undertake a comprehensive analysis of the studies that dealt with solid biowaste resources for energy recovery. This review paper was conducted from November 2022 to June 2023. The relevant literature was searched using databases from scholarly journal publishers, online search engines, and websites. A total of 82 studies were determined to be eligible from 659 records. Ethiopia has a huge potential for biowaste resources, with an annual generation potential of 18,446.4 MJ per year. The multifaceted advantages associated with biowaste-to-energy conversion such as clean energy production, waste management, forest conservation, greenhouse gas emission reduction, and maintaining soil fertility using the digestate left after anaerobic digestion were mentioned. This review highlights various conversion technologies for converting solid biowastes into valuable forms of energy, such as thermochemical, biochemical, and physico-mechanical techniques. It also investigated the value-added products of the Solid Biowastes-to-Energy (SBWtoE) process, including bio-oil, syngas, bioethanol, biodiesel, biomethane, bio-briquettes, and pellets, with applications ranging from transportation to power generation. Furthermore, this review addresses the multifaceted challenges associated with implementing a circular economy, emphasizing the need to overcome policy, technological, financial, and institutional barriers. These efforts are crucial for harnessing the growing biowaste resources in Ethiopia, ultimately promoting sustainable and cost-effective energy production while advancing the nation's environmental objectives.

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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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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.

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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.

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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.

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利用可再生能源发电获得单细胞蛋白质,即“电转蛋白质(Power-to-Protein,PtP)”,是生产单细胞蛋白质的 绿色可持续途径. 厌氧消化(anaerobic digestion,AD)可提供“电转蛋白质”过程中所需要的碳源以及部分氮源、微 量元素等,通过厌氧消化与“电转蛋白质”技术相结合构建了一种可持续的蛋白质生产工艺,“厌氧消化-电转蛋白质 (anaerobic digestion-Power-to-Protein,ADPtP)”. 本文介绍现有利用AD出料培养微生物获得单细胞蛋白质的工艺, 分析引入PtP技术后的工艺效率与能耗,重点介绍ADPtP工艺的基础模式、过程中资源整合与利用. 在电化学法还原模 式中将沼气升级后培养甲烷氧化细菌操作简便易行且环境效益高,而以Wood-Ljungdahl碳转化途径设计的ADPtP工艺 在安全性方面占优势. ADPtP工艺中,降低爆炸风险和提高转化效率是亟须解决的关键问题. 另外,工艺中资源整合方 式为电化学沼气升级、电化学消化液提氨、电解水产氢. 未来,我国沼气产量与潜在储备量以及可再生能源发电量将为 ADPtP提供发展基础,同时具有良好的政策环境和巨大的潜在蛋白质市场需求,因此该工艺在我国作为新型绿色蛋白质 生产工艺而施行具有良好基础与应用前景. (图1 表2 参64)

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Proper treatment of polyvinyl chloride (PVC) waste is challenge as it is not easily degraded and incineration can lead to environmental issue as it will produce toxic chemicals. In this study, a hydrothermal carbonization approach was applied to treat PVC waste. The influence of exogenous additives on dechlorination efficiency of PVC were evaluated. The results showed that, with exogenous additive, substitution, elimination, dehydration and aromatization reaction were enhanced during hydrothermal carbonization. The maximum dechlorination efficiency of 97.50% was achieved with the mass ratio of 1.4% between rice straw and PVC resin at hydrothermal carbonization temperature 240℃ for 120min. The calorific value of hydrothermal charcoal was relatively higher (39.57MJ/kg ± 0.40MJ/kg), indicating a good combustion process. This study presented a novel and sustainable approach, which could convert PVC-waste as a form of solid fuel.

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Anaerobic digestion of animal slurry to produce biogas is the dominated treatment approach and a storage period is normally applied prior to digestion. Pre-storage, however, contributes to CH4 emissions and results in loss of biogas potential. Manure management was found to be an efficient approach to reduce not only the on-site CH4 emission but may also have extended influence on CH4 emission/losses for storage and subsequent biogas process, while the connection remains unclear. The objective of this study was therefore to evaluate the impact of slurry management (e.g. removal frequency) on CH4 emission (both on-site and storage process prior to biogas) and biogas yield. An experimental pig house for growing-finishing pigs (30–110 kg) and the relevant CH4 emission was monitored for one year. In addition, the specific CH4 activity (SMA) test was conducted and used as an alternative indicator to reflect the impact. Results showed that the manure management affected both on-site and subsequent methane emission; with increased manure removal frequencies, the methane emission became less dependent on variation of temperatures and the specific methanogenesis activity was significantly lower. The highest SMA (100 mL CH4 gVS-1), for instance, was observed from the slurries with limited emptied times, which was 10 times of that from the slurries being emptied three times a week. These findings could enlighten the development of environmentally friendly strategies for animal slurry management and biogas production.

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Due to the diversity of microbiota and the high complexity of their interactions that mediate biogas production, a detailed understanding of the microbiota is essential for the overall stability and performance of the anaerobic digestion (AD) process. This study evaluated the microbial taxonomy, metabolism, function, and genetic differences in 14 full-scale biogas reactors and laboratory reactors operating under various conditions in China. This is the first known study of the microbial ecology of AD at food waste (FW) at a regional scale based on multi-omics (16S rRNA gene amplicon sequencing, metagenomics, and proteomics). Temperature significantly affected the bacterial and archaeal community structure (R2 = 0.996, P = 0.001; R2 = 0.846, P < 0.002) and total inorganic carbon(TIC) slightly changed the microbial structure (R2 = 0.532, P = 0.005; R2 = 0.349, P = 0.016). The Wood-Ljungdahl coupled with hydrogenotrophic methanogenic pathways were dominant in the thermophilic reactors, where the acs, metF, cooA, mer, mch and ftr genes were 10.1-, 2.8-, 16.2-, 1.74-, 4.15-, 1.04-folds of the mesophilic reactors (P < 0.01). However, acetoclastic and methylotrophic methanogenesis was the primary pathway in the mesophilic reactors, where the ackA, pta, cdh and mta genes were 2.2-, 3.2-, 14.3-, 1.88-folds of the thermophilic group (P < 0.01). Finally, the Wilcoxon rank-sum test was applied to explain the cause of the temperature affecting AD microbial activities. The findings have deepened the understanding of the effect of temperature on AD microbial ecosystems and are expected to guide the construction and management of full-scale FW biogas plants.

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The parameters from full-scale biogas plants are highly nonlinear and imbalanced, resulting in low prediction accuracy when using traditional machine learning algorithms. In this study, a hybrid extreme learning machine (ELM) model was proposed to improve prediction accuracy by solving imbalanced data. The results showed that the best ELM model had a good prediction for validation data (R2 = 0.972), and the model was developed into the software (prediction error of 2.15 %). Furthermore, two parameters within a certain range (feed volume (FV) = 23–45 m3 and total volatile fatty acids of anaerobic digestion (TVFAAD) = 1750–3000 mg/L) were identified as the most important characteristics that positively affected biogas production. This study combines machine learning with data-balancing techniques and optimization algorithms to achieve accurate predictions of plant biogas production at various loads.

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The amount of lignocellulose biomass and sludge is enormous, so it is of great significance to find a treatment combining the two substances. Co-hydrothermal carbonization (Co-HTC) has emerged as an efficient approach to dispose sludge. However, the improvement of sludge upgrading and combustion performance remains an important challenge during the Co-HTC of sludge. In this work, the Co-HTC of sludge and Fenton's reagent at different mixing ratios was proposed to achieve sludge reduction. Moreover, the addition of two kinds of biomass improved the adsorption capacity and combustion performance of hydrochars. When sludge and sawdust were the Co-HTC at the mass ratio of 1:3, the liquid phase Pb concentration decreased notably to 18.06%. Furthermore, the adsorption capacity of hydrochars was further improved by modification, which was in accordance with pseudo-second-order kinetics. Particularly, the hydrochars derived from the Co-HTC had higher heating value (HHV) and could be used as a clean fuel. This study proposed a new technical route of combining the HTC with Fenton's reagent and lignocellulose biomass, which could be served as a cleaner and eco-friendly treatment of sludge.

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This study evaluated the effects of bio-based carbon materials on methane production by anaerobic digestion. The results showed that biochar and hydrochar can promote cumulative methane yield by 15% to 29%. However, there was no statistical significance (p > 0.05) between hydrochar and biochar produced at different temperature on methane production. 16S rRNA gene sequencing and bioinformatics analysis showed that biochar and hydrochar enriched microorganism that might participate in direct interspecies electron transfer (DIET) such as Pseudomonadaceae, Bacillaceae, and Clostridiaceae. The the surface properties of the modified biochar were characterized with BET, Raman, FTIR and XPS. Bio-based carbon materials with uniform dispersion provided a stable environment for the DIET of microorganisms and electrons are transferred through aromatic functional groups on the surface of materials. This study reveals bio-based carbon materials surface properties on methane production in anaerobic digestion and provides a new approach to recycling spent coffee grounds.

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Syngas from pyrolysis/gasification process is a mixture of CO, CO2 and H2, which could be converted to CH4, so called syngas biomethanation. Its development is obstructed due to the low productivity and CO inhibition. The aim of this study was to demonstrate the feasibility of using syngas as the only carbon source containing high CO concentration (40%) for biomethanation. Lab-scale thermophilic bioreactor inoculated with anaerobic sludge was operated continuously for over 900 h and the shift of microbial structure were investigated. Results showed that thermophilic condition was suitable for syngas biomethanation and the microbes could adapt to high CO concentration. Higher processing capacity of 12.6 m3/m3/d was found and volumetric methane yield of 2.97 m3/m3/d was observed. These findings could strengthen the theoretical basis of syngas biomethanation and support its industrialization in the future.

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With the development of the world economy and society, the living standards of residents have been improved, along with a large amount of food waste and carbon dioxide (CO2) emissions. In the face of global warming and energy shortages, food waste can be used as high-value bio-energy raw materials which is also an effective way to reduce CO2 emissions. Therefore, this paper proposes a novel anaerobic digestion and CO2 emissions efficiency analysis based on a Slacks-Based Measure integrating Data Envelopment Analysis (SBM-DEA) model to evaluate and optimize the process structure of anaerobic treatment of food waste. The total feed volume and the discharge volume of liquid digestate are taken as inputs, and the total methane (CH4) production volume is taken as the desirable output and CO2 emissions are regarded as the undesirable output to build the biogas production and CO2 emissions evaluation model during the anaerobic digestion process. Finally, the proposed method is used in the actual anaerobic digestion process. The results show that the overall efficiency values in January, April, May, and June in 2020 are higher than those in other months. At the same time, due to the optimal allocation of slack variables of inputs and undesirable outputs, the efficiency values of other inefficient anaerobic digestion days can be improved.