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Biogas production through anaerobic digestion (AD) is one of the complex non-linear biological processes, wherein understanding its dynamics plays a crucial role towards process control and optimization. In this work, a machine learning based biogas predictive model was developed for high solid systems using algorithms, including SVM, ET, DT, GPR, and KNN and two different datasets (Dataset-1:10, Dataset-2:5 inputs). Support Vector Machine had the highest accuracy (R 2 ) of all the algorithms at 91 % (Dataset-1) and 87 % (Dataset-2), respectively. The statistical analysis showed that there was no significant difference (p = 0.377) across the datasets, wherein with less inputs, accurate results could be predicted. In case of biogas yield, the critical factors which affect the model predictions include loading rate and retention time. The developed high solid machine learning model shows the possibility of integrating Artificial Intelligence to optimize and control AD process, thus contributing to a generic model for enhancing the overall performance of the biogas plant., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Karthik Rajendran reports financial support was provided by SRM University AP - Amaravati. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Due to resource scarcity, current industrial systems are switching from waste treatment, such as wastewater treatment and biomass, to resource recovery (RR). Biofuels, manure, pesticides, organic acids, and other bioproducts with a great market value can be produced from wastewater and activated sludge (AS). This will not only help in the transition from a linear economy to a circular economy, but also contribute to sustainable development. However, the cost of recovering resources from wastewater and AS to produce value-added products is quite high as compared to conventional treatment methods. In addition, most antioxidant technologies remain at the laboratory scale that have not yet reached the level at industrial scale. In order to promote the innovation of resource recovery technology, the various methods of treating wastewater and AS to produce biofuels, nutrients and energy are reviewed, including biochemistry, thermochemistry and chemical stabilization. The limitations of wastewater and AS treatment methods are prospected from biochemical characteristics, economic and environmental factors. The biofuels derived from third generation feedstocks, such as wastewater are more sustainable. Microalgal biomass are being used to produce biodiesel, bioethanol, biohydrogen, biogas, biooils, bioplastics, biofertilizers, biochar and biopesticides. New technologies and policies can promote a circular economy based on biological materials., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

In this study, a mild two-stage hydrothermal pretreatment was employed to optimally valorize industrial hemp (Cannabis sativa sp.) fibrous waste into sugars for Poly(3-hydroxybuyrate) (PHB) production using recombinant Escherichia coli LSBJ. Biomass was pretreated using hot water at 160, 180, and 200 °C for 5 and 10 min (15% solids), followed by disk refining. The sugar yields during enzymatic hydrolysis were found to improve with increasing temperature and the yields for hot water-disk refining pretreatment (HWDM) were higher compared to only hot water pretreatment at all conditions. The maximum glucose (56 g/L) and cellulose conversion (92%) were achieved for HWDM at 200 °C for 10 min. The hydrolysate obtained was fermented at a sugar concentration of 20 g/L. The PHB inclusion and concentration of 48% and 1.8 g/L, respectively, were similar to those from pure sugars. A pH-controlled fermentation resulted in a near bi-fold increase in PHB yield (3.46 g/L)., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Environmental contamination is considered a major issue with the growing urbanization and industrialization. In this context, the scientific society is engaged in searching for a sustainable, safe, and eco-friendly solution. Sustainable materials such as biochar play an important role in environmental contamination. It has some specific properties such as micropores which increase the surface area to bind the pollutants. This review endeavors to analyze the potential of fruit wastes especially tropical fruit tree residues as potential candidates for producing highly efficient biochar materials. The review discusses various aspects of biochar production viz. pyrolysis, torrefaction, hydrothermal carbonization, and gasification. In addition, it discusses biochar use as an adsorbent, wastewater treatment, catalyst, energy storage, carbon sequestration and animal feed. The review put forward a critical discussion about key aspects of applying biochar to the environment., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Increases in population and urbanization leads to generation of a large amount of food waste (FW) and its effective waste management is a major concern. But putrescible nature and high moisture content is a major limiting factor for cost effective FW valorization. Bioconversion of FW for the production of value added products is an eco-friendly and economically viable strategy for addressing these issues. Targeting on production of multiple products will solve these issues to greater extent. This article provides an overview of bioconversion of FW to different value added products., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

This review provides an update on the state-of-the art technologies for the valorization of solid waste and its mechanism to generate various bio-products. The organic content of these wastes can be easily utilized by the microbes and produce value-added compounds. Microbial fermentation techniques can be utilized for developing waste biorefinery processes. The utilization of lignocellulosic and plastics wastes for the generation of carbon sources for microbial utilization after pre-processing steps will make the process a multi-product biorefinery. The C1 and C2 gases generated from different industries could also be utilized by various microbes, and this will help to control global warming. The review seeks to expand expertise about the potential application through several perspectives, factors influencing remediation, issues, and prospects., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Time series-based modeling provides a fundamental understanding of process fluctuations in an anaerobic digestion process. However, such models are scarce in literature. In this work, a dynamic model was developed based on modified Hill's model using MATLAB, which can predict biomethane production with time series. This model can predict the biomethane production for both batch and continuous process, across substrates and at diverse conditions such as total solids, loading rate, and days of operation. The deviation between literature and the developed model was less than ± 7.6%, which shows the accuracy and robustness of this model. Moreover, statistical analysis showed there was no significant difference between literature and simulation, verifying the null hypothesis. Finding a steady and optimized loading rate was necessary to an industrial perspective, which usually requires extensive experimental data. With the developed model, a stable and optimal methane yield generating loading rate could be identified at minimal input., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

This study explores the effect of high-solids loading for a fed batch enzymatic hydrolysis and fermentation. The solids loading considered was 19%, 30% and 45% using wheat straw and corn stover as a feedstock. Based on the experimental results, techno-economic analysis and life cycle assessments were performed. The experimental results showed that 205±25.8g/L glucose could be obtained from corn stover at 45% solids loading after 96h which when fermented yielded 115.9±6.37g/L ethanol after 60h of fermentation. Techno-economic analysis showed that corn stover at 45% loading yielded the highest ROI at 8% with a payback period less than 12years. Similarly, the global warming potential was lowest for corn stover at 45% loading at -37.8gCO 2 eq./MJ ethanol produced., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

Anaerobic digestion (AD) has been in use for many decades. To date, it has been primarily aimed at treating organic wastes, mainly manures and wastewater sludge, and industrial wastewaters. However, with the current advancements, a more open mind is required to look beyond these somewhat restricted original applications of AD. Biorefineries are such concepts, where multiple products including chemicals, fuels, polymers etc. are produced from organic feedstocks. The anaerobic biorefinery concept is now gaining increased attention, utilizing AD as the final disposal step. This review aims at evaluating the potential significance of anaerobic biorefineries, including types of feedstocks, uses for the produced energy, as well as sustainable applications of the generated residual digestate. A comprehensive analysis of various types of anaerobic biorefineries has been developed, including both large-scale and household level applications. Finally, future directives are highlighted showing how anaerobic biorefinery concept could impact the bioeconomy in the near future., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

The methane potential of forest residues was compared after applying organic solvent, i.e., acetic acid, ethanol, and methanol pretreatments using batch anaerobic digestion (AD). The pretreatments were performed at 190 °C with 50% (V/V) organic solvent for 60 min. The accumulated methane yields after 40 days of AD from pretreated forest residues were between 0.23 and 0.34 m(3) CH4/kg VS, which shows a significant improvement compared to 0.05 m(3) CH4/kg VS, from untreated forest residues. These improvements count up to 50% increase in the methane yields from the pretreated substrates based on expected theoretical yield from carbohydrates. Among the organic solvents, pretreatments with acetic acid and ethanol led to highest methane yields, i.e., over 0.30 m(3) CH4/kg VS. However, techno-economical evaluation showed, pretreatment with methanol was more viable financially. The capital investments of the plant operating 20,000 tons of forest residues varied between 56 and 60 million USD, which could be recovered in less than 8 years of operation., (Copyright © 2014 Elsevier Ltd. All rights reserved.)

A novel process simulation model (PSM) was developed for biogas production in anaerobic digesters using Aspen Plus®. The PSM is a library model of anaerobic digestion, which predicts the biogas production from any substrate at any given process condition. A total of 46 reactions were used in the model, which include inhibitions, rate-kinetics, pH, ammonia, volume, loading rate, and retention time. The hydrolysis reactions were based on the extent of the reaction, while the acidogenic, acetogenic, and methanogenic reactions were based on the kinetics. The PSM was validated against a variety of lab and industrial data on anaerobic digestion. The P-value after statistical analysis was found to be 0.701, which showed that there was no significant difference between discrete validations and processing conditions. The sensitivity analysis for a ±10% change in composition of substrate and extent of reaction results in 5.285% higher value than the experimental value. The model is available at http://hdl.handle.net/2320/12358 (Rajendran et al., 2013b)., (Copyright © 2014 Elsevier Ltd. All rights reserved.)