Enhanced performance and economic feasibility of sewage sludge digestion using a two-stage anaerobic digestion with a dynamic membrane and alkaline-thermal pretreatment.

This study suggests a high-rate sewage sludge anaerobic digestion (AD) process. An alkaline-thermal pretreatment and a dynamic membrane (DM) were used to enhance AD efficiency and economic feasibility in a two-stage system. The effect of pretreatment on volatile fatty acid (VFA) production in the acidogenic phase was investigated at various hydraulic retention times (HRT).

Explainable artificial intelligence for the interpretation of ensemble learning performance in algal bloom estimation.

Chlorophyll-a (Chl-a) concentrations, a key indicator of algal blooms, were estimated using the XGBoost machine learning model with 23 variables, including water quality and meteorological factors. The model performance was evaluated using three indices: root mean square error (RMSE), RMSE-observation standard deviation ratio (RSR), and Nash-Sutcliffe efficiency. Nine datasets were created by averaging 1 hour data to cover time frequencies ranging from 1 hour to 1 month.

Real-time chlorophyll-a forecasting using machine learning framework with dimension reduction and hyperspectral data.

Since water is an essential resource in various fields, it requires constant monitoring. Chlorophyll-a concentration is a crucial indicator of water quality and can be used to monitor water quality. In this study, we developed methods to forecast chlorophyll-a concentrations in real-time using hyperspectral data on IoT platform and various machine learning algorithms.

Recent advances in algal bloom detection and prediction technology using machine learning.

Harmful algal blooms (HAB) including red tides and cyanobacteria are a significant environmental issue that can have harmful effects on aquatic ecosystems and human health. Traditional methods of detecting and managing algal blooms have been limited by their reliance on manual observation and analysis, which can be time-consuming and costly. Recent advances in machine learning (ML) technology have shown promise in improving the accuracy and efficiency of algal bloom detection and prediction.

Anaerobic digestion of sewage sludge using anaerobic dynamic membrane bioreactor under various sludge composition and organic loading rates.

This study investigates the effects of sludge compositions and organic loading rates (OLRs) on stable biogas production during sludge digestion. Batch digestion experiments evaluate the effects of alkaline-thermal pretreatment and waste activated sludge (WAS) fractions on the biochemical methane potential (BMP) of sludge. A lab-scale anaerobic dynamic membrane bioreactor (AnDMBR) is fed with a mixture of primary sludge and pretreated WAS.

Predicting the impact of hydraulic retention time and biodegradability on the performance of sludge acidogenesis using an artificial neural network.

This study aimed to predict volatile fatty acids (VFAs) production from SDBS-pretreated waste-activated sludge (WAS). A lab-scale continuous experiment was conducted at varying hydraulic retention times (HRTs) of 7 d to 1 d. The highest VFA yield considering the WAS biodegradability was 86.

Machine learning in fermentative biohydrogen production: Advantages, challenges, and applications.

Hydrogen can be produced in an environmentally friendly manner through biological processes using a variety of organic waste and biomass as feedstock. However, the complexity of biological processes limits their predictability and reliability, which hinders the scale-up and dissemination. This article reviews contemporary research and perspectives on the application of machine learning in biohydrogen production technology.

Exploration of deep learning models for real-time monitoring of state and performance of anaerobic digestion with online sensors.

The immediate response to the state disturbances of anaerobic digestion is essential to prevent anaerobic digestion failure. However, frequent monitoring of the state and performance of anaerobic digestion is challenging. Thus, deep learning models were investigated to predict the state and performance variables from online sensor data.

Synthesis of fatty acid-based ammonium ionic liquids and their application for extraction of Co(II) and Ni(II) metals ions from aqueous solution.

Leaching of cobalt and nickel into diverse water streams has become an environmental hazard and is continuously impacting human health through the food chain. Solvent extraction is the most widely accepted for separating these metals, but traditional extractants employed in conjunction with molecular diluents often lack selectivity and caused major environmental hurdles. Therefore, the development of cost-effective, environmentally friendly technologies for recovering these heavy metals has been strongly encouraged in recent years.

Valorization of pretreated waste activated sludge to organic acids and biopolymer.

Polyhydroxybutyrate (PHB) is a natural polyester that may be made by utilizing volatile fatty acids (VFAs) as a substrate. VFA generated by continuous anaerobic fermentation of waste activated sludge (WAS) was fed into bioreactors for PHB synthesis in this work. Series of optimization tests were conducted to increase the biodegradability and hydrolysis of waste activated sludge.

The effects of ammonia acclimation on biogas recovery and the microbial population in continuous anaerobic digestion of swine manure.

This study investigated the ammonia toxicity and the acclimation of anaerobic microbiome in continuous anaerobic digestion of swine manure using unacclimated inoculum. When the total ammonia nitrogen concentration (TAN) reached 2.5 g N/L, the methane yield decreased from 254.

Interpretation of ensemble learning to predict water quality using explainable artificial intelligence.

Algal bloom is a significant issue when managing water quality in freshwater; specifically, predicting the concentration of algae is essential to maintaining the safety of the drinking water supply system. The chlorophyll-a (Chl-a) concentration is a commonly used indicator to obtain an estimation of algal concentration. In this study, an XGBoost ensemble machine learning (ML) model was developed from eighteen input variables to predict Chl-a concentration.

Sludge disintegration and anaerobic digestion enhancement by alkaline-thermal pretreatment: Economic evaluation and microbial population analysis.

Alkaline-thermal pretreatment was examined for waste activated sludge (WAS) disintegration and subsequent anaerobic digestion (AD). Pretreatment at 60 °C was estimated to provide better economic benefits than higher temperature conditions. The maximum methane yield of 215.

Biofilm formation as a method of improved treatment during anaerobic digestion of organic matter for biogas recovery.

The efficiency of anaerobic digestion could be increased by promoting microbial retention through biofilm development. The inclusion of certain types of biofilm carriers has differentiated existing AD biofilm reactors through their respective mode of biofilm growth. Bacteria and archaea engaged in methanogenesis during anaerobic processes potentially build biofilms by adhering or attaching to biofilm carriers.

Effect of low-thermal pretreatment on the methanogenic performance and microbiome population of continuous high-solid anaerobic digester treating dewatered sludge.

Undigested and dewatered sludge at 10% total solids was pretreated at 60 °C for 3 h and fed to a lab-scale horizontal anaerobic bioreactor for 130 days with solids retention time (SRTs) from 25 to 16 d. The low-thermal pretreatment enabled higher net energy production, improved sludge treatment efficiency, and enhanced digestion stability. The highest average biomethane yield and production rate were 138.

Enhanced anaerobic digestion of waste-activated sludge via bioaugmentation strategy-Phylogenetic investigation of communities by reconstruction of unobserved states (PICRUSt2) analysis through hydrolytic enzymes and possible linkage to system performance.

In this study, anaerobic digestion of waste-activated sludge was bioaugmented with hydrolytic bacteria, Bacteroidetes uniformis (Bacteroidetes, B) and Clostridium sp. (Firmicutes, F) at various dosages. Bioaugmentation resulted in enhanced methane conversion of waste-activated sludge.

Assessment of Chlorella sp. as a potential feedstock for biological methane production.

Microalgal biomass sequestrates CO and is regarded as a promising renewable feedstock for anaerobic digestion because of its adequate carbohydrate content and lignin-free structure. This study optimizes the dilute-acid pretreatment of Chlorella sp. and subsequent biomethane production using response surface methodology and central composite design with temperature, pretreatment time and solid-to-liquid ratio as variables.

Cavitational activity in heterogeneous systems containing fine particles.

Ultrasound has been increasingly used in various processes containing a variety of homogeneous and heterogeneous systems. For largescale applications, a high energy efficiency of the process is required. With this view, the calorimetric energy and cavitational activity measurements were carried out in heterogeneous systems consisting of both liquid and solid phases (fine particles) in a 28-kHz double-bath sonoreactor.

Silica-quaternary ammonium "Fixed-Quat" nanofilm coated fiberglass mesh for water disinfection and harmful algal blooms control.

Intensification of pollution loading worldwide has promoted an escalation of different types of disease-causing microorganisms, such as harmful algal blooms (HABs), instigating detrimental impacts on the quality of receiving surface waters. Formation of unwanted disinfection by-products (DBPs) resulting from conventional disinfection technologies reveals the need for the development of new sustainable alternatives. Quaternary Ammonium Compounds (QACs) are cationic surfactants widely known for their effective biocidal properties at the ppm level.

Variation of efficiencies and limits of ultrasonication for practical algal bloom control in fields.

Algal blooms are an increasing issue in managing water resources for drinking water production and recreational activities in many countries. Among various techniques, ultrasonication is known as a cost-effective method for control of harmful algal blooms (HABs) in relatively large area of water bodies. Most of engineering parameters for operating ultrasonication have been empirically determined based on laboratory scale tests, however, field or pilot tests in real environments are still rare.

Expression of CPNE7 during mouse dentinogenesis.

Interactions between the ectodermal and mesenchymal tissues are the basis of the central mechanism regulating tooth development. Based on this epithelial-mesenchymal interaction (EMI), we demonstrated that copine-7 (CPNE7) is secreted by preameloblasts and regulates the differentiation of mesenchymal cells of dental or non-dental origin into odontoblasts. However, the precise expression patterns of CPNE7 in the stages of tooth development have not yet been elucidated.

Modeling fine particle dynamics in gravel-bedded streams: Storage and re-suspension of fine particles.

Fine particles or sediments have various effects on water quality and aquatic ecosystems. Thus, understanding the dynamics of these fine particles between water body and stream bed is an important issue in sediment research. Previous studies and analysis of empirical data suggest that fine particles are stored in the sediment bed in the low flow regime, where flow rate is smaller than the critical flow rate that mobilizes the sediment bed.

Recent advances in ultrasonic treatment: Challenges and field applications for controlling harmful algal blooms (HABs).

Algal blooms are a naturally occurring phenomenon which can occur in both freshwater and saltwater. However, due to excess nutrient loading in water bodies (e.g.

Large-area fabrication of periodic sub-15 nm-width single-layer graphene nanorings.

A periodically aligned array of graphene nanorings (GRNRs) with a sub-15 nm linewidth at a pitch of 450 nm is fabricated with a large area, 9 cm(2) , through conventional nanoimprint lithography coupled with sophisticated metal deposition and plasma-etching processes. The existence of the single-layer GRNRs is verified by various techniques.