Hydrolysis kinetics for solubilizing waste activated sludge at low temperature thermal treatment derived from multivariate non-linear model

Improving methane production from waste-activated sludge by coupling thermal hydrolysis with potassium ferrate pretreatment

Thermal hydrolysis (TH) is effective in improving the solubilization of waste-activated sludge, but opportunities for enhancement remain, particularly in increasing organic matter conversion and reducing the generation of refractory substances. This study proposed a novel pretreatment method combining TH and potassium ferrate (PF) and evaluated its performance in improving sludge methane production. The results indicated that the combined pretreatment increased the methane yield from 118 ± 2 mL/g VS to 215 ± 7 mL/g VS, an increase of 82.2 % compared to the control. Combined pretreatment promoted the exposure of functional groups in the extracellular polymeric substances (EPS) and altered protein secondary structure composition, thereby disrupting EPS. PF improved the biodegradability of TH-treated sludge by degrading humic acids and Maillard reaction products. In addition, Fe(III) produced by PF induces dissimilar iron reduction, which enhances microbial electron transfer activity and facilitates subsequent hydrolysis and acidification processes. Combined pretreatment increased the abundance of hydrolyzing and acidifying bacteria, but reduced hydrogenotrophic methanogens. This article reveals that PF improves the biodegradability of TH-treated sludge and provides new ideas for advanced TH technologies for sludge resource recovery.

Improved Short-Chain Fatty Acids Production and Protein Degradation During the Anaerobic Fermentation of Waste-Activated Sludge via Alumina Slag-Modified Biochar

As the by-product in the biological sewage treatment, waste-activated sludge (WAS) always suffers from the difficulty of disposal. Anaerobic fermentation to achieve valuable carbon sources is a feasible way for resource utilization of WAS, whereas the process is always restricted by its biochemical efficiency. Hence, the WAS was used as the feedstock in this study. Alumina slag-modified biochar (Al@BioC) respectively from pine wood (PW) or fresh vinegar residue (FVR) was employed to stimulate the process of short-chain fatty acids (SCFAs) production during the anaerobic treatment of WAS. The results indicate that the addition of Al@BioC could facilitate the distinct increase in SCFAs yield (42.66 g/L) by 14.09% and acetate yield (33.30 g/L) by 18.77%, respectively, when compared with that in regular fermentation without Al@BioC addition. Furthermore, protein degradation was also improved. With the Al@BioCPW added, the maximum concentration of soluble protein reached 867.68 mg/L and was 24.39% higher than the initial level, while the enhancement in the group with Al@BioCFVR and without biochar addition was 12.49% and 7.44%, respectively. According to the results of 16S rDNA sequencing, the relative abundance of acid-producing bacteria (Bacteroidota and Firmicutes) was enriched, enhancing the pathways of protein metabolisms and the ability to resist the harsh environment, respectively. Moreover, Proteiniphilum under Bacteroidota and Fastidiosipila under Firmicutes were the main microorganisms to metabolize protein. The above results might provide a novel material for harvesting the SCFAs production, which is conducive to harmless disposal and carbon resource recovery.

Biotransformation of Pb and As from sewage sludge and food waste by black soldier fly larvae: Migration mechanism of bacterial community and metalloregulatory protein scales

The accumulation and transformation of lead (Pb) and arsenic (As) during the digestion of sewage sludge (SS) by black soldier fly larvae (BSFL) remain unclear. In this study, we used 16 s rRNA and metagenomic sequencing techniques to investigate the correlation between the microbial community, metalloregulatory proteins (MRPs), and Pb and As migration and transformation. During the 15-day test period, BSFL were able to absorb 34-48 % of Pb and 32-45 % of As into their body. Changes in bacterial community abundance, upregulation of MRPs, and redundancy analysis (RDA) results confirmed that ZntA, EfeO, CadC, ArsR, ArsB, ArsD, and ArsA play major roles in the adsorption and stabilization of Pb and As, which is mainly due to the high contribution rates of Lactobacillus (48-59 %) and Enterococcus (21-23 %). Owing to the redox reaction, the regulation of the MRPs, and the change in pH, the Pb and As in the BSFL residue were mainly the residual fraction (F4). The RDA results showed that Lactobacillus and L.koreensis could significantly (P < 0.01) reduce the reducible fraction (F2) and F4 of Pb, whereas Firmicutes and L.fermentum can significantly (P < 0.05) promote the transformation of As to F4, thus realizing the passivation Pb and As. This study contributes to the understanding of Pb and As in SS adsorbed by BSFL and provides important insights into the factors that arise during the BSFL-mediated migration of Pb and As.

Kinetic model derived from machine learning for accurate prediction of microalgal hydrogen production via conversion from low thermally pre-treated palm kernel expeller waste

The depletion of fossil fuel sources and increase in energy demands have increased the need for a sustainable alternative energy source. The ability to produce hydrogen from microalgae is generating a lot of attention in both academia and industry. Due to complex production procedures, the commercial production of microalgal biohydrogen is not yet practical. Developing the most optimum microalgal hydrogen production process is also very laborious and expensive as proven from the experimental measurement. Therefore, this research project intended to analyse the random time series dataset collected during microalgal hydrogen productions while using various low thermally pre-treated palm kernel expeller (PKE) waste via machine learning (ML) approach. The analysis of collected dataset allowed the derivation of an enhanced kinetic model based on the Gompertz model amidst the dark fermentative hydrogen production that integrated thermal pre-treatment duration as a function within the model. The optimum microalgal hydrogen production attained with the enhanced kinetic model was 387.1 mL/g microalgae after 6 days with 1 h thermally pre-treated PKE waste at 90 °C. The enhanced model also had better accuracy (R2 = 0.9556) and net energy ratio (NER) value (0.71) than previous studies. Finally, the NER could be further improved to 0.91 when the microalgal culture was reused, heralding the potential application of ML in optimizing the microalgal hydrogen production process.