High operational cost due to membrane fouling propensity remains a major drawback for the widespread application of membrane bioreactor (MBR) technology. As a result, studies on membrane fouling mitigation through the application of integrated processes have been widely explored. In this work, the combined application of electrochemical processes and moving bed biofilm reactor (MBBR) technology within an MBR at laboratory scale was performed by applying an intermittent voltage of 3 V/cm to a reactor filled with 30% carriers. The treatment efficiency of the electro moving bed membrane bioreactor (eMB-MBR) technology in terms of ammonium nitrogen (NH₄-N) and orthophosphate (PO₄-P) removal significantly improved from 49.8% and 76.7% in the moving bed membrane bioreactor (MB-MBR) control system to 55% and 98.7% in the eMB-MBR, respectively. Additionally, concentrations of known fouling precursors and membrane fouling rate were noticeably lower in the eMB-MBR system as compared to the control system. Hence, this study successfully demonstrated an innovative and effective technology (i.e., eMB-MBR) to improve MBR performance in terms of both conventional contaminant removal and fouling mitigation.

Instrumental odour monitoring systems (IOMS) are intelligent electronic sensing tools for which the primary application is the generation of odour metrics that are indicators of odour as perceived by human observers. The quality of the odour sensor signal, the mathematical treatment of the acquired data, and the validation of the correlation of the odour metric are key topics to control in order to ensure a robust and reliable measurement. The research presents and discusses the use of different pattern recognition and feature extraction techniques in the elaboration and effectiveness of the odour classification monitoring model (OCMM). The effect of the rise, intermediate, and peak period from the original response curve, in collaboration with Linear Discriminant Analysis (LDA) and Artificial Neural Networks (ANN) as a pattern recognition algorithm, were investigated. Laboratory analyses were performed with real odour samples collected in a complex industrial plant, using an advanced smart IOMS. The results demonstrate the influence of the choice of method on the quality of the OCMM produced. The peak period in combination with the Artificial Neural Network (ANN) highlighted the best combination on the basis of high classification rates. The paper provides information to develop a solution to optimize the performance of IOMS.

The transition from considering e-waste as a liability to recognizing it as a valuable resource is pivotal for environmental sustainability. Electronic waste is growing at an alarming rate, and the extraction and recovery of precious metals offer an economically and ecologically sound solution. Furthermore, with the global shift towards electrification, renewable energy, and advanced technologies, the demand for rare earth elements continues to rise. Extracting these elements from e-waste, even through rudimentary methods, can address their scarcity and reduce our reliance on environmentally destructive mining practices. However, the unethical export of e-waste from developed to developing countries remains a critical issue. Furthermore, there is there is the health risks associated with improper dismantling practices in the informal sector. To eradicate this risk a scheme providing proper environmental practices by way of formalizing the informal sector. A cost to benefit analysis was made to study several set ups for a material recovery facility. The project outcomes include a greater awareness of the health risks of hazardous materials in ewaste and an appreciation of the proper waste handling practices. This study's findings underscore the urgency of enforcing international agreements like the Basel Convention, improving working conditions in the informal sector, and implementing safer recycling practices. Moreover, the study serves as a valuable blueprint for replication in other barangays or villages in the country with a vision to offering lessons on how to transform this global problem into an opportunity for sustainable resource management while protecting human health and the environment.

Tree leaf polyphenols, natural antioxidants, form complexes with iron minerals that enhance contaminant degradation via reductive processes.