Sustainable Solutions and AI-Driven Approaches for Water and Wastewater Treatment

Water and wastewater treatment has become an increasingly critical field in addressing the dual pressures of population growth and climate stress on finite water resources. Traditional treatment approaches, though effective, are often energy-intensive and environmentally taxing. In recent years, research has advanced rapidly toward more sustainable, efficient, and intelligent systems through the integration of electrochemical processes, artificial intelligence (AI), and sensor-based technologies. Electrochemical oxidation, photocatalysis, advanced membrane design, and coupled biological–electrochemical systems are among the emerging tools transforming treatment efficacy and scalability. Yet, challenges remain in upscaling laboratory innovations, ensuring system durability under real conditions, integrating predictive models into full-scale plants, and translating complex data analytics into effective environmental strategies.The thematic scope encompasses innovative eco-friendly technologies and processes, electrochemical methods, AI-driven monitoring and optimization, smart sensors, and modelling approaches. The Research Topic welcomes contributions spanning fundamental scientific investigations, process modelling and simulation, applied engineering developments, and real-world case studies. Collectively, this collection seeks to accelerate industrial adoption, inform evidence-based policy and regulatory strategies, and contribute to improved environmental and public health outcomes through eco-friendly and intelligent water and wastewater treatment solutions.This Research Topic aims to promote multidisciplinary approaches for the development, optimization, and implementation of sustainable and intelligent treatment systems. It seeks to unite researchers and practitioners working across electrochemistry, environmental engineering, materials science, and data analytics to explore how innovative sensing, modelling, and control mechanisms can revolutionize water and wastewater infrastructures. By fostering collaboration between academia, industry, and policymakers, the Research Topic will provide evidence-based insights to guide the transition toward greener, digitally enhanced, and more resilient water management technologies worldwide.To gather further insights into sustainable, AI-driven, and electrochemical water and wastewater treatment strategies, we welcome articles addressing, but not limited to, the following themes:· Electrochemical and photoelectrochemical processes for water and wastewater purification· AI-enabled process optimization, machine learning, and predictive maintenance· Smart sensors, real-time monitoring, and Internet of Things (IoT) integration· Green materials and catalysts for energy-efficient treatment and resource recovery· Modelling, simulation, and digital twins for sustainable plant operation· Life-cycle assessment, techno-economic evaluation, and sustainability metrics· Policy development, industrial demonstrations, and collaborative frameworks for intelligent water managementAccepted article types include Original Research, Reviews, Mini Reviews, and Perspectives. Topic editors: Khalid Hashim, Patryk Kot, Magomed Muradov, Rafid Alkhaddar Source: https://www.frontiersin.org/research-topics/78993/sustainable-solutions-and-ai-driven-approaches-for-water-and-wastewater-treatment