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Insights into key properties of biochar with a fast adsorption rate and high adsorption capacity are urgent to design biochar as an adsorbent in pollution emergency treatment. Machine learning (ML) incorporating classical theoretical adsorption models was applied to build prediction models for adsorption kinetics rate (i.e., K) and maximum adsorption capacity (i.e., Q m ) of emerging contaminants (ECs) on biochar. Results demonstrated that the prediction performance of adaptive boosting algorithm significantly improved after data preprocessing (i.e., log-transformation) in the small unbalanced datasets with R 2 of 0.865 and 0.874 for K and Q m , respectively. The surface chemistry, primarily led by ash content of biochar significantly influenced the K, while surface porous structure of biochar showed a dominant role in predicting Q m . An interactive platform was deployed for relevant scientists to predict K and Q m of new biochar for ECs. The research provided practical references for future engineered biochar design for ECs removal., 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 © 2024 Elsevier Ltd. All rights reserved.)

The sustainable disposal of high-moisture municipal sludge (MS) has received increasing attention. Thermochemical conversion technologies can be used to recycle MS into liquid/gas bio-fuel and value-added solid products. In this review, we compared energy recovery potential of common thermochemical technologies (i.e., incineration, pyrolysis, hydrothermal conversion) for MS disposal via statistical methods, which indicated that hydrothermal conversion had a great potential in achieving energy recovery from MS. The application of machine learning (ML) in MS recycling was discussed to decipher complex relationships among MS components, process parameters and physicochemical reactions. Comprehensive ML models should be developed considering successive reaction processes of thermochemical conversion in future studies. Furthermore, challenges and prospects were proposed to improve effectiveness of ML for energizing thermochemical conversion of MS regarding data collection and preprocessing, model optimization and interpretability. This review sheds light on mechanism exploration of MS thermochemical recycling by ML, and provide practical guidance for MS recycling., 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.)

This study investigated the potential of micro-nano bubble (MNB) ozonation pretreatment to eliminate oxytetracycline (OTC) from wastewater and improve subsequent anaerobic digestion (AD) performance. The findings revealed that MNB ozonation achieved efficient OTC oxidation (>99 % in 60 min), and significantly enhanced methane production by 51 % compared to conventional ozonation (under 30 min of pretreatment). Additionally, MNB ozonation resulted in a decrease in the soluble chemical oxygen demand and reduced volatile fatty acid accumulation compared to conventional ozonation. Furthermore, the study sheds light on the profound impact of OTC and its oxidation by-products on the sludge microbiome. Exposure to OTC and its oxidation by-products resulted in alterations in extracellular polymeric substances composition and led to significant shifts in microbial community structure. This study highlights the promise of MNB ozonation as an effective approach for pharmaceutical pollutant removal and the optimization of AD performance in wastewater treatment, with implications for improved environmental sustainability., 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 the context of advocating carbon neutrality, there are new requirements for sustainable management of municipal sludge (MS). Hydrothermal carbonization (HTC) is a promising technology to deal with high-moisture MS considering its low energy consumption (without drying pretreatment) and value-added products (i.e., hydrochar). This study applied machine learning (ML) methods to conduct a holistic assessment with higher heating value (HHV) of hydrochar, carbon recovery (CR), and energy recovery (ER) as model targets, yielding accurate prediction models with R 2 of 0.983, 0.844 and 0.858, respectively. Furthermore, MS properties showed positive (e.g., carbon content, HHV) and negative (e.g., ash content, O/C, and N/C) influences on the hydrochar HHV. By comparison, HTC parameters play a critical role for CR (51.7%) and ER (52.5%) prediction. The primary sludge was an optimal HTC feedstock while anaerobic digestion sludge had the lowest potential. This study provided a comprehensive reference for sustainable MS treatment and industrial application., 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 © 2022 Elsevier Ltd. All rights reserved.)

The activated sludge process (ASP) is widely used for wastewater treatment, and the aeration efficiency is crucial to the operation of wastewater treatment plants. Recently, microbubble (MB)- and nanobubble (NB)-aeration has attracted much attention as there is growing evidence that it holds a great promise for upgrading the process efficiency of current ASP under conventional macro-bubble-aeration. However, a comprehensive review to elucidate the potential application of MB- and NB-aeration in ASP is still lacking. Therefore, this review will provide a systematic introduction to MB- and NB-aeration (including the unique properties and generation methods of MBs and NBs), and gain mechanistic insights on how MB- and NB-aeration improve gas-liquid mass transfer. The recent advances in MB- and NB-aeration applications to ASP and the resultant effects are also highlighted and discussed in-depth. The review concludes with a brief consideration of future research interests., 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 © 2022 Elsevier Ltd. All rights reserved.)

This study investigated the temporal dynamics of digestion efficiency and community stability in digesters fed with waste activated sludge (WAS), straw (STR-AD), food waste (FW-AD) and mixture of straw-and-food waste (STR-FW-AD). Results showed that carbon removals of recalcitrant substrates (i.e., 48.2 ± 3.9% in WAS-AD and 57.8 ± 4.9% in STR-AD) were lower than that of labile substrates (i.e., 70.7 ± 4.0% in FW-AD). Nonetheless, carbon removal of recalcitrant substrates was largely improved through co-digestion (70.3 ± 3.2% in STR-FW-AD). In contrast to monopoly communities (e.g., the highly enriched Paludibacter) fed with the labile substrates, recalcitrant substrates supported highly diverse communities. Accordingly, the medians of negative/positive cohesions of communities in WAS-AD, STR-AD, STR-FW-AD and FW-AD decreased from 0.86 to 0.63, suggesting their decreasing community stability. Microbial source tracking analyses showed the major contribution of the STR-AD community to the co-digestion community. This study provided unprecedented mechanistic insight into stability improvement of substrate co-digestion on the methanogenic digestion microbiome., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

In this study, temporal impacts of thermal, alkaline/acid and thermal-alkaline sludge pre-treatments on digestion performance and microbiome were investigated and compared in methanogenic sludge digesters. Results showed that thermal and alkaline/acid pre-treatments were efficient in releasing intracellular and EPS organic matter, respectively. The thermal-alkaline pre-treatment showed synergistic impacts of both thermal and alkaline/acid pre-treatments by releasing the major portion of sludge organic matter from solid- to liquid-phase, which result in 60-65% organic carbon removal in subsequent sludge digestion and further optimizing digestion temperature had negligible improvement. The 16S rRNA gene-based analyses suggested that organic matter released from sludge pre-treatments is a major deterministic parameter in shaping sludge microbiome. Pre-treatment specific lineages were identified in different sludge digesters, whereas several taxa were identified as common functionally active populations in sludge digestion. This study provided mechanistic insights into impacts of pre-treatments on digestion performance and microbiome in methanogenic sludge digesters., 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 © 2020 Elsevier Ltd. All rights reserved.)