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Article
Environmental Sciences
Divyesh Rameshbhai Vaghela et al.
Summary: The removal of Pb2+ from wheat straw-derived biochar produced at 600 & DEG;C was studied. The study found that the wheat straw biochar had a larger surface area, pore volume, and pore diameter. The optimal conditions for removing Pb2+ were determined through experimentation.
INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH
(2023)
Article
Engineering, Environmental
Hyuck Kwon et al.
Summary: The application of Internet of Things (IoT) technology in the operation of the sequencing batch reactor (SBR) process resulted in increased nitrogen removal and better handling of inflow fluctuations. By reducing the time required for settling and discharging (TRSD) through an automatic mechanical decanter, monitoring the sludge blanket layer and suspended solid (SS) concentration, the average TRSD was decreased by 27-59% compared to conventional SBR processes. Implementing a step-feed mode with nitrogen ion monitoring improved total nitrogen (T-N) removal to 92-93%, compared to 82-88% in single-feed mode.
Review
Computer Science, Artificial Intelligence
Majid Bahramian et al.
Summary: Increasing energy efficiency in wastewater treatment plants is crucial and exploiting data science and modelling, as well as deploying sensors and artificial intelligence, can help achieve this goal. Artificial Neural Networks (ANN) is the most popular standalone model for WWTP modelling, followed by Decision Trees (DT), Fuzzy Logic (FL), Genetic algorithm (GA), and Support Vector Machine (SVM). Hybrid models, especially the Machine Learning (ML)-metaheuristic, demonstrate better performance than standalone models. Industrial deployment is still lacking, and future research should focus on enhancing collaboration between interested parties for more effective implementation.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Environmental Sciences
Chengxi Li et al.
Summary: Hormesis has been a topic of concern in the environmental and toxicological communities. Previous studies have focused on the hormesis induced by stressors in terms of their biotoxicity, but little research has been done on hormesis in the context of biological wastewater treatment processes. In this study, the removal of NH4+-N and Cu2+ by S. polyrrhiza was investigated under long-term exposure to environmentally relevant concentrations of Cu2+ in swine wastewater. The results showed that long-term exposure to Cu2+ enhanced the removal of NH4+-N by S. polyrrhiza, and previous exposure to low doses of Cu2+ significantly improved the removal efficiency in a second exposure.
SCIENCE OF THE TOTAL ENVIRONMENT
(2023)
Article
Engineering, Environmental
KiJeon Nam et al.
Summary: This study developed a digital multi-solution for optimal operation of wastewater treatment plants (WWTPs) based on multi-agent reinforcement learning. The digital multi-solution accurately determined operational setpoints under varying influent conditions, outperforming manual operating systems and improving energy efficiency and effluent quality.
JOURNAL OF WATER PROCESS ENGINEERING
(2023)
Article
Chemistry, Applied
Andy G. Kumi et al.
Summary: This study investigates the treatment of petrochemical industrial wastewater using modified biochar for the adsorption of toluene and xylene. The results show that the modified biochar has a high removal efficiency for both pollutants. Economic feasibility estimation suggests a relatively short payback period for the biochar application. The study has important implications for water ecosystem restoration, biochar modification in industrial applications, and climate change mitigation.
ADSORPTION SCIENCE & TECHNOLOGY
(2022)
Article
Chemistry, Applied
Areej Alhothali et al.
Summary: This study evaluated the effectiveness of different methods for simulating and optimizing the adsorptive removal of COD and TOC in produced water using tea waste biochar. The results showed that the ANFIS model outperformed other methods in predicting adsorption data. By utilizing various optimization approaches, maximum removal rates of COD and TOC were achieved.
ADSORPTION SCIENCE & TECHNOLOGY
(2022)
Article
Chemistry, Applied
Mohamed K. Mostafa et al.
Summary: This study developed a quadratic regression model and artificial neural network (ANN) for predicting the removal of biochemical oxygen demand (BOD) under different adsorption conditions. The use of nanozero-valent iron encapsulated into cellulose acetate as an adsorbent showed high efficiency in BOD reduction. Both the ANN and quadratic regression models achieved accurate predictions of BOD removal. These computational-based methods can enhance the performance of wastewater treatment under various adsorption conditions.
ADSORPTION SCIENCE & TECHNOLOGY
(2022)
Review
Chemistry, Applied
Hilda Elizabeth Reynel-Avila et al.
Summary: This article reviews the application of artificial neural networks in adsorption modeling, focusing on the prediction of kinetics, isotherms, and breakthrough curves. However, most of the existing studies have only considered adsorption systems with a single pollutant, and have not delved into the analysis of multicomponent adsorption systems. The review highlights the significant potential of artificial neural networks in modeling multicomponent adsorption systems and provides some recommendations for their reliable application and implementation, which is crucial for improving the process engineering in water treatment and purification.
ADSORPTION SCIENCE & TECHNOLOGY
(2022)
Article
Green & Sustainable Science & Technology
Love O. David et al.
Summary: This study evaluates the application of Fourth Industrial Revolution (4IR) technologies on the water, energy, and food (WEF) nexus and finds that most technologies have not been integrated, except for the Internet of Things and Big Data analytics. The study highlights the importance of data collection, accuracy, and analysis for the security of the WEF nexus.
JOURNAL OF CLEANER PRODUCTION
(2022)
Article
Chemistry, Applied
Gabriel Dan Suditu et al.
Summary: This study highlights the benefits of optimizing the decolorization of bromocresol green through adsorption on active carbon. The optimum working conditions were determined using a combination of modeling, optimization strategies, and artificial intelligence techniques, leading to a maximum efficiency of over 99%.
ADSORPTION SCIENCE & TECHNOLOGY
(2022)
Article
Environmental Sciences
Vicent Hernandez-Chover et al.
Summary: Digitalization is revolutionizing the water sector by generating large amounts of data and improving the efficiency of infrastructure processes. It enables integration with other sectors and facilitates the practical application of circular economy principles.
Proceedings Paper
Automation & Control Systems
Hana Efendic et al.
Summary: Given the global rise of pandemics, preventing infectious diseases has become a crucial concern. Wastewater provides optimal conditions for the proliferation of pathogens, making biosensors crucial in monitoring and improving population health. This review study examines 13 specific scientific papers published between 2015 and 2021, highlighting the ability to connect medical areas with sewage using simple tools and an online approach.
Article
Chemistry, Applied
Virendra Kumar Yadav et al.
Summary: In this study, a novel method for synthesizing Ca-based zeolite from incense stick ash waste through alkali-treatment was reported for the first time. Characterization of the synthesized zeolites using various instruments confirmed their microstructure, crystalline nature, and aggregation properties. Computational simulations were utilized to evaluate structural, electronic, and density of states' characteristics of the zeolite structures. The research demonstrated the potential of transforming incense stick ash waste into value-added mineral for wastewater treatment.
ADSORPTION SCIENCE & TECHNOLOGY
(2021)
Article
Environmental Sciences
Leo Heijnen et al.
Summary: Wastewater surveillance using RT-ddPCR for specific detection of the N501Y mutation in SARS-CoV-2 variants has proven to be an effective tool in monitoring the trends and spread of COVID-19 variants in the community, supporting public health decision-making for control measures.
SCIENCE OF THE TOTAL ENVIRONMENT
(2021)
