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Various pretreatment methods, such as thermal, alkaline and acid, were applied on grass lawn (GL) waste and the effect of each pretreatment method on the Biochemical Methane Potential was evaluated for two options, namely using the whole slurry resulting from pretreatment or the separate solid and liquid fractions obtained. In addition, the effect of each pretreatment on carbohydrate solubilization and lignocellulossic content fractionation (to cellulose, hemicellulose, lignin) was also evaluated. The experimental results showed that the methane yield was enhanced with alkaline pretreatment and, the higher the NaOH concentration (20 g/100 gTotal Solids (TS)), the higher was the methane yield observed (427.07 L CH4/kg Volatile Solids (VS), which was almost 25.7% higher than the BMP of the untreated GL). Comparing the BMP obtained under the two options, i.e., that of the whole pretreatment slurry with the sum of the BMPs of both fractions, it was found that direct anaerobic digestion without separation of the pretreated biomass was favored, in almost all cases. A preliminary energy balance and economic assessment indicated that the process could be sustainable, leading to a positive net heat energy only when using a more concentrated pretreated slurry (i.e., 20% organic loading), or when applying NaOH pretreatment at a lower chemical loading.

Anaerobic digestion of organic waste into methane and carbon dioxide (biogas) is carried out by complex microbial communities. Here, we use full-length 16S rRNA gene sequencing of 285 full-scale anaerobic digesters (ADs) to expand our knowledge about diversity and function of the bacteria and archaea in ADs worldwide. The sequences are processed into full-length 16S rRNA amplicon sequence variants (FL-ASVs) and are used to expand the MiDAS 4 database for bacteria and archaea in wastewater treatment systems, creating MiDAS 5. The expansion of the MiDAS database increases the coverage for bacteria and archaea in ADs worldwide, leading to improved genus- and species-level classification. Using MiDAS 5, we carry out an amplicon-based, global-scale microbial community profiling of the sampled ADs using three common sets of primers targeting different regions of the 16S rRNA gene in bacteria and/or archaea. We reveal how environmental conditions and biogeography shape the AD microbiota. We also identify core and conditionally rare or abundant taxa, encompassing 692 genera and 1013 species. These represent 84–99% and 18–61% of the accumulated read abundance, respectively, across samples depending on the amplicon primers used. Finally, we examine the global diversity of functional groups with known importance for the anaerobic digestion process.

Four multiple air–cathode microbial fuel cells (MFCs) were developed under the scope of using extracts from fermentable household food waste (FORBI) for the production of bioelectricity. The operation of the MFCs was assessed in batch mode, considering each cell individually. Τhe chemical oxygen demand (COD) efficiency was relatively high in all cases (>85% for all batch cycles) while the electricity yield was 20 mJ/gCOD/L of extract solution. The four units were then electrically connected as a stack, both in series and in parallel, and were operated continuously. Approximately 62% COD consumption was obtained in continuous stack operation operated in series and 67% when operated in parallel. The electricity yield of the stack was 2.6 mJ/gCOD/L of extract solution when operated continuously in series and 0.7 mJ/gCOD/L when operated continuously in parallel.

The present study investigated the effect of thermo-chemical pretreatment on the enhancement of enzymatic digestibility of olive mill stones (OMS), as well as its possible valorisation via bioconversion of the generated free sugars to alcohols. Specifically, the influence of parameters such as reaction time, temperature, type and concentration of dilute acids and/or bases, was assessed during the thermo-chemical pretreatment. The hydrolysates and the solids remaining after pretreatment, as well as the whole pretreated slurries, were further evaluated as potential substrates for the simultaneous production of ethanol and xylitol via fermentation with the yeast Pachysolen tannophilus . The digestibility and overall saccharification of OMS were considerably enhanced in all cases, with the maximum enzymatic digestibility observed for dilute sodium hydroxide (almost 4-fold) which also yielded the highest total saccharification yield (91% of the total OMS carbohydrates). Ethanol and xylitol yields from the untreated OMS were 28 g/kg OMS and 25 g/kg OMS, respectively, and were both significantly enhanced by pretreatment. The highest ethanol yield was 79 g/kg OMS and was achieved by the alkali pretreatment and separate fermentation of hydrolysates and solids, whereas the highest xylitol yield was 49 g/kg OMS and was obtained by pretreatment with sulphuric acid and separate fermentation of hydrolysates and solids.

Bioelectrochemical systems have been the focus of extensive research due to their unique advantages of converting the chemical energy stored in waste to electricity. To acquire a better understanding and optimize these systems, modelling has been employed. A 2D microbial fuel cell (MFC) model was developed using the finite element software Comsol Multiphysics® (version 5.2), simulating a two-chamber MFC operating in batch mode. By solving mass and charge balance equations along with Monod–Butler–Volmer kinetics, the operation of the MFC was simulated. The model accurately describes voltage output and substrate consumption in the MFC. The computational results were compared with experimental data, thus validating the model. The voltage output and substrate consumption originating from the model were in agreement with the experimental data for two different cases (100 Ω, 1000 Ω external resistances). A polarization curve was extracted from the model by shifting the external resistance gradually, calculating a similar maximum power (47 mW/m2) to the observed experimental one (49 mW/m2). The validated model was used to predict the MFC response to varying initial substrate concentrations (0.125–4 g COD/L) and electrolyte conductivity (0.04–100 S/m) in order to determine the optimum operating conditions.

This study evaluated polyhydroxyalkanoates (PHAs) production from a medium corresponding to the condensate derived from food waste drying, using a mixed microbial culture in a 15 L Sequencing Batch Reactor (SBR). The reactor operation comprised two distinct periods to investigate the impact of varying organic loading rates on biomass performance and polymer accumulation. In Period 1, when the soluble Chemical Oxygen Demand (sCOD) was 6.8 ± 1.4 g/L, efficient nitrogen limitation promoted complete urea consumption and stable biomass growth, yielding higher intracellular PHA accumulation (11.74 ± 6.01%). The microbial community exhibited a balanced copolymer production (HB:HV ratio of approximately 54:46). Conversely, Period 2, characterized by higher organic loads (sCOD 12.1 ± 2.9 g/L), displayed incomplete urea utilization, reduced biomass viability, and significantly lower PHA accumulation (5.26 ± 2.53%). A second set of experiments aiming at the assessment of the impact of operation mode (with and without inclusion of a settling phase) demonstrated that removal of settling leads to a stable long-term steady-state operation with enriched PHA-accumulating bacteria and increased polymer storage capacity.

The growing environmental concerns associated with petroleum-based plastics require the development of sustainable, biodegradable alternatives. Polyhydroxyalkanoates (PHAs), a family of biodegradable bioplastics, offer a promising potential as eco-friendly substitutes due to their renewable origin and favorable degradation properties. This research investigates the use of synthetic condensate, mimicking the liquid fraction from drying and shredding of household food waste, as a viable substrate for PHA production using mixed microbial cultures. Two draw-fill reactors (DFRs) were operated under different feed organic concentrations (2.0 ± 0.5 and 3.8 ± 0.6 g COD/L), maintaining a consistent carbon-to-nitrogen ratio to selectively enrich microorganisms capable of accumulating PHAs through alternating nutrient availability and deficiency. Both reactors achieved efficient organic pollutant removal (>95% soluble COD removal), stable biomass growth, and optimal pH levels. Notably, the reactor with the higher organic load (DFR-2) demonstrated a modest increase in PHA accumulation (19.05 ± 7.18%) compared to the lower-loaded reactor (DFR-1; 15.19 ± 6.00%), alongside significantly enhanced biomass productivity. Polymer characterization revealed the formation of poly(3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBV), influenced by the substrate composition. Microbial community analysis showed an adaptive shift towards Proteobacteria dominance, signifying successful enrichment of effective PHA producers.

The effect of different pretreatment approaches based on alkali (NaOH)/hydrogen peroxide (H2O2) on willow sawdust (WS) biomass, in terms of delignification efficiency, structural changes of lignocellulose and subsequent fermentation toward ethanol, was investigated. Bioethanol production was carried out using the conventional yeast Saccharomyces cerevisiae, as well as three non-conventional yeasts strains, i.e., Pichia stipitis, Pachysolen tannophilus, Wickerhamomyces anomalus X19, separately and in co-cultures. The experimental results showed that a two-stage pretreatment approach (NaOH (0.5% w/v) for 24 h and H2O2 (0.5% v/v) for 24 h) led to higher delignification (38.3 ± 0.1%) and saccharification efficiency (31.7 ± 0.3%) and higher ethanol concentration and yield. Monocultures of S. cerevisiae or W. anomalus X19 and co-cultures with P. stipitis exhibited ethanol yields in the range of 11.67 ± 0.21 to 13.81 ± 0.20 g/100 g total solids (TS). When WS was subjected to H2O2 (0.5% v/v) alone for 24 h, the lowest ethanol yields were observed for all yeast strains, due to the minor impact of this treatment on the main chemical and structural WS characteristics. In order to decide which is the best pretreatment approach, a detailed techno-economical assessment is needed, which will take into account the ethanol yields and the minimum processing cost.

This work proposes an integrated process flowsheet for the recovery of pure crystalline Si and Ag from end of life (EoL) Si photovoltaic (PV) panels consisting of a primary thermal treatment, followed by downstream hydrometallurgical processes. The proposed flowsheet resulted from extensive experimental work and comprises the following unit operations: Shredding the PV modules to − 4 mm, after the removal and recovery of aluminum frames, junction boxes and copper cables. Delamination of the Si cells from the front soda-lime protective glass, through a thermal treatment at 550 °C for 15 min, in excess of air, in order to disintegrate the encapsulating organic material (ethylene vinyl acetate (EVA)) and the polyvinyl fluoride (PVF) polymer backsheet (Tedlar®). Separation of the detached Si flakes from the front glass and the “ash residue” and classification via mechanical screening by a perforated trommel rotary screen equipped with square wire mesh sieves. Further grinding of the recovered Si flakes by ball milling to − 90 μm, in order to increase the specific surface area, prior to the downstream hydrometallurgical process. Quantitative leaching of Ag and Al from the Si flakes in one stage by HNO 3 at ambient temperature. Alternatively, acid leaching in two stages can be applied: initially by H 2 SO 4 for Al quantitative extraction and subsequently by HNO 3 for Ag quantitative extraction at ambient temperature. In order to remove the anti-reflection coating, etching of the leached Si flakes by 2.5 M NaOH has been proven efficient and crystalline silicon of high purity was recovered. Separation and precipitation of Ag as AgCl or alternatively, Ag electrowinning from nitrate solutions and Al precipitation via solution neutralization. Graphical Abstract

Households are the major contributor to food waste generation in the European Union according to the recently published data from Eurostat. Promoting food systems sustainability and aspiring to achieve the United Nations SDG 12.3 requires a better insight to the underlying drivers of the household food waste occurrence. The present study presents the combination of a well-established method of acquiring information, the questionnaire surveys, with a state-of-the-art technology for data imputation and interpretation using machine learning (ML). The Food Loss and Waste Prevention Unit (FLWPU) of the municipality of Halandri employed two surveys within the framework of the European funded projects Food Connections and FOODRUS. The first questionnaire was designed for rapid completion, to maximize response rates and minimize respondent burden, ensuring the collection of a consistent core dataset. A total of 154 replies were collected. The second questionnaire, associated with FOODRUS, was more detailed, enabling the participants to provide more in-depth information on their household food waste (HHFW) practices. In total, 43 responses were collected. ML algorithms were applied for data enhancement and data clustering. Specifically, ML and statistical techniques are applied for data imputations. An XGBoost algorithm was trained so as to capture complex relationships between variables. Behavioral intentions and effective strategies for reducing food waste at the community level are identified from the responses of both questionnaires, while a clustering of respondents in five groups emerged by using k-means, thus providing valuable insight into targeted HHFW prevention action plans.