Semi-continuous anaerobic digestion of mixed wastewater sludge with biochar addition

Anaerobic sludge digestion enhancement with bioelectrochemical and electrically conductive materials augmentation: A state of the art review

Excess biological sludge processing and disposal have a significant impact on the energy balance and economics of wastewater treatment operations, and on receiving environments. Anaerobic digestion is probably the most widespread in-plant sludge processing method globally, since it stabilizes and converts biosolids organic matter into biogas, allowing partial recovery of their embedded chemical energy. A considerable number of studies concerning applicable techniques to improve biogas production, both in quantity and quality, include pre-treatment strategies to promote biosolids disintegration aimed at the release and solubilization of intracellular energy compounds, inorganic/biological amendments aimed at improving process performance, and sludge thermal pre-treatment. As for in-process amendments, iron, micro and macro-nutrients, ashes from waste incineration and nanoparticles addition have been studied for the improvement of enzymatic reactions. Recently, use of electrically conductive materials has been credited with the possibility to accelerate and stabilize the conversion of organic substrates to methane. The possibility of increasing both biogas generation and its relative biomethane content by interfacing anaerobic digestion with bioelectrochemical systems was also postulated. This review addresses the research gap surrounding the integration of anaerobic digestion with novel technologies, particularly bioelectrochemical systems, to enhance biogas production and methane enrichment. While existing studies focus on pre-treatment and in-process amendments, the feasibility, mechanisms, and benefits of such integration remain underexplored. By critically evaluating the current state of the art, this review identifies the potential of bioelectrochemical integration to improve energy recovery and process stability, while highlighting key challenges and research needs for advancing these technologies toward practical implementation.

Eco-friendly remedies for soil contamination: manufacturing and analysis of nanobiochar using sugarcane bagasse and olive mill waste

Soil degradation poses a significant challenge to Egypt's agriculture, making resource optimization essential. Nanobiochar presents a promising solution for pollutant removal; however, its low yields may hinder commercialization. This study investigates the production of biochar from sugarcane bagasse and olive mill waste, focusing on its composition, morphology, and effectiveness in soil immobilization. Advanced techniques like SEM, TEM, and FTIR were used to characterize the nanobiochar, highlighting its potential as a sustainable solution to soil contamination. The study revealed that ZnCl2 treatment significantly lowers pH, while KOH modification raises it. Surface morphology analysis showed that SCB biochar exhibited a highly porous structure, while OMW biochar had less porous edges and irregular oval-shaped pores. The effects of biochar activation on the availability of heavy metals like Ni, Pb, and Mo (in mg.Kg-1) were also examined. Ni concentrations decreased from 1.27 mg.Kg-1 in untreated biochar (NA) to 0.78 mg.Kg-1 in KOH-treated biochar (KA) and 0.67 mg.Kg-1 in ZnCl2-treated biochar (ZnA). Pb levels dropped from 7.7 mg.Kg-1 in NA to 5.2 mg.Kg-1 in KA and slightly to 4.74 mg.Kg-1 in ZnA. Mo showed a similar trend, with the highest concentration in NA at 1.21 mg.Kg-1, followed by 0.88 mg.Kg-1 in KA and 0.75 mg.Kg-1 in ZnA. Overall, OMW nanobiochar demonstrated a greener, more sustainable solution to soil contamination compared to SCB nanobiochar.

Sustainable valorisation of sewage sludge via carbon dioxide-assisted pyrolysis

The escalating volume of sewage sludge (SS) generated poses challenges in disposal, given its potential harm to the environment and human health. This study explored sustainable solutions for SS management with a focus on energy recovery. Employing CO2-assisted pyrolysis, we converted SS into flammable gases (H2 and CO; syngas). Single-stage pyrolysis of SS in a CO2 conditions demonstrated that CO2 enhances flammable gas production (especially CO) through gas phase reactions (GPRs) with volatile matter (VM) at temperatures ≥520 °C. Specifically, the CO2 partially oxidized the VM released from SS and concurrently underwent reduction into CO. To enhance the syngas production at temperatures ≤520 °C, multi-stage pyrolysis setup with additional heat energy and a Ni/Al2O3 catalyst were utilized. These configurations significantly increased flammable gas production, particularly CO, at temperatures ≤520 °C. Indeed, the flammable gas yield in the catalytic pyrolysis of SS increased from 200.3 mmol under N2 conditions to 219.2 mmol under CO2 conditions, representing a 4.4-fold increase compared to single-stage pyrolysis under CO2 conditions (50.0 mmol). By integrating a water-gas-shift reaction, the flammable gases produced from CO2-assisted catalytic pyrolysis were expected to have the potential to generate revenue of US$4.04 billion. These findings highlight the effectiveness of employing CO2 in SS pyrolysis as a sustainable and effective approach for treating and valorising SS into valuable energy resources.

Machine learning for high solid anaerobic digestion: Performance prediction and optimization

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 (R2) 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.

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 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.

Impacts of lignite and biochar addition on anaerobic digestion of and fertilizer production from dairy manure

Anaerobic digestion (AD) is one of the most popular technologies to convert organic residues into renewable energy. The use of additives has been shown to increase the process stability and degradation efficiency during AD. However, little attention has been paid to the associated fertilizer production. Thus, this study aims to simultaneously investigate the impact of biochar and lignite on AD and fertilizer production of dairy manure in semi-continuous experiments. Results show that compared to the biogas production rate (BPR) of the reference (394.01 ± 0.39 lN/(kgVS∙d), lignite can increase BPR by 4.98 %, whereas no impact on BPR was detected due to biochar addition. This indicates that higher O/C and H/C ratios attributed to lignite are a dominant factor influencing BPR, while high specific surface is not beneficial. Nitrogen yield in the solid phase was increased by 19.47 % (lignite) and 14.65 % (biochar), significantly promoting the utilization of digestate as solid nitrogen fertilizer.