Exploring the Potential and Challenges of Electrochemical Processes for Sustainable Waste Water Remediation and Treatment
Journal Title: Acadlore Transactions on Geosciences - Year 2023, Vol 2, Issue 2
Abstract
Emerging as an efficient, cost-effective, and environmentally sound approach, electrochemical treatment methods hold significant promise for sustainable remediation and wastewater treatment. This review elucidates recent progress in electrochemical techniques used for site decontamination and wastewater management. It elucidates the fundamental electrochemical processes, detailing the principles of electrocoagulation, electroflocculation, electrochemical membranes, electrochemical oxidation (EO), and advanced oxidation processes (AOPs). The broad applicability of these methods for contaminant removal, inclusive of heavy metals, organic pollutants, complex organic compounds, and suspended particulate matter, is underscored. Notwithstanding, the adoption of these techniques encounters notable challenges. These involve the heterogeneity of soil conditions, the presence of intricate contaminant mixtures, and the risk of electrode fouling and degradation. Suggestions for overcoming such challenges include refining the comprehension of electrochemical treatment processes in field-scale applications, investigating innovative electrode materials, and developing advanced modeling and simulation tools. This review offers a robust overview of electrochemical treatment strategies for sustainable wastewater management and can guide researchers, engineers, and policymakers towards the successful adoption and implementation of these techniques to meet environmental challenges and foster sustainable water management.
Authors and Affiliations
Olusola D. Ogundele, David A. Oyegoke, Temitope E. Anaun
Keywords
Related Articles
- EP ID EP732836
- DOI 10.56578/atg020203
- Views 65
- Downloads 0
Forecasting Rainfall in Selected Cities of Southwest Nigeria: A Comparative Study of Random Forest and Long Short-Term Memory Models
Rainfall is crucial for agricultural practices, and climate change has significantly altered rainfall patterns. Understanding the dynamic nature of rainfall in the context of climate change through Machine Learning (ML)...
Seasonal Variations in PM2.5 Carbon Components: A Case Study
This study conducted a comprehensive analysis of the carbon components in $\mathrm{PM}_{2.5}$ particulate matter in Linfen City for the year 2020. Utilizing the thermal-optical transmittance (TOT) method, the mass concen...
Tendencies in Land Use and Land Cover in Serbia Towards Sustainable Development in 1990-2018
The overuse of natural resources by humanity in recent decades has resulted in noticeable changes environment quality. Global environmental research is particularly interested in the topics of land use change and land co...
Progressive Failure Characteristics and Failure Symptoms of Straight-Walled Arched Sandstone Tunnels
In order to investigate the development process of crack formation in shallow-buried sandstone tunnel, biaxial compression tests were conducted on a similar model of the real straight-walled arched sandstone tunnel. The...
Comparing Artificial Neural Networks with Multiple Linear Regression for Forecasting Heavy Metal Content
This paper adopts two modeling tools, namely, multiple linear regression (MLR) and artificial neural networks (ANNs), to predict the concentrations of heavy metals (zinc, boron, and manganese) in surface waters of the Ou...