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Papers
61,005 resultsShowing papers similar to Towards Adaptive Water Quality Indexing: Integrating Fuzzy Logic for Improved Contaminant Detection and Treatment Planning
ClearEnvironmental health risk assessment of urban water sources based on fuzzy set theory
A fuzzy set theory-based environmental health risk assessment framework was developed and applied to urban water sources, improving risk credibility by handling uncertainty and multiple pollution indicators simultaneously. The approach offers a more nuanced tool for water resource protection decision-making.
Emerging Contaminants in Water: Detection, Treatment, and Regulation
This review covers emerging contaminants in water — including microplastics, pharmaceuticals, and industrial chemicals — discussing detection methods, treatment technologies, and regulatory frameworks. The authors highlight major gaps in current water quality standards and the need for updated regulations to address these newer pollutants.
Novel Quantitative Evaluation of Biotreatment Suitability of Wastewater
This study developed a new framework for evaluating how suitable wastewater is for biological treatment, going beyond standard water quality indicators. Better assessment tools could improve wastewater treatment efficiency and reduce pollutant discharges, including microplastics.
Assessment of Sustainable Wastewater Treatment Technologies Using Interval-valued Intuitionistic Fuzzy Distance Measure-based Mairca Method
Researchers developed a decision-making framework for evaluating sustainable wastewater treatment technologies using fuzzy set theory and multi-criteria analysis. The method accounts for uncertainty in expert assessments while comparing technologies across economic, environmental, and social criteria. The study provides a systematic approach for selecting wastewater treatment solutions that can address emerging contaminants including microplastics.
Integrated Approaches to Water Quality Assessment and Treatment: A Comprehensive Review
This comprehensive review integrates physical, chemical, and biological water quality parameters, examines major pollution sources including emerging contaminants like microplastics, and surveys advances in real-time IoT-enabled monitoring and integrated treatment approaches.
Understanding emerging contaminants in water and wastewater: A comprehensive review on detection, impacts, and solutions
This review covers emerging contaminants in water including pharmaceuticals, PFAS, microplastics, and nanomaterials that escape conventional water treatment and persist in the environment. It evaluates advanced detection techniques and newer treatment methods such as membrane filtration, advanced oxidation, and bioremediation to address these pollutants that pose ongoing risks to public health.
Identification of biomarkers in wastewater-based epidemiology: Main approaches and analytical methods
This review covers biomarker identification in wastewater-based epidemiology, examining how emerging contaminants including microplastics and pharmaceuticals in wastewater can serve as population-level indicators of disease, health behaviors, and chemical exposures in cities.
Standardized Fuzzy Comprehensive Evaluation Biological Index Method for Ecosystem Health Evaluation in Large Waters of Aquaculture Type
Researchers developed a standardized fuzzy comprehensive evaluation biological index method for assessing ecosystem health in large aquaculture-type water bodies, providing a more nuanced tool for monitoring river and lake ecosystem conditions under increasing human environmental pressure.
Water Quality Modelling, Monitoring, and Mitigation
This special issue review examines advances in water quality modelling, monitoring, and mitigation approaches, noting that while models and indices have become central tools for water resource management, site-specific limitations and high uncertainty in predictions remain key challenges for reliably assessing freshwater body health.
A Comprehensive Method for Water Environment Assessment considering Trends of Water Quality
Researchers developed a comprehensive water quality assessment method that accounts for both current pollution levels and trends over time, applying it to rivers feeding a major Chinese reservoir. Water quality assessment frameworks are increasingly being adapted to include microplastic contamination as a standard monitoring parameter.
Application of Index Models for Assessing Freshwater Microplastics Pollution
Researchers applied pollution and health risk index models to microplastic data from freshwater environments, demonstrating that standardized indices can help compare contamination levels across studies with different units and methodologies.
Recent Developments in Emerging Contaminants Determination and Treatment Technologies
This review covers recent advances in detecting and treating emerging contaminants in water, including microplastics, pharmaceuticals, and endocrine disruptors, summarizing the most promising analytical and treatment technologies.
Smart Water, Smart Models: Algorithmic Assessment of Water Quality under Evolving Chemical and Industrial Stressors
This review examines how machine learning approaches — including deep neural networks, hybrid physics-data models, and reinforcement learning — can be applied to detect and predict emerging chemical pollutants such as microplastics and recycling byproducts in water quality monitoring systems.
Emerging Pollutants in Aquatic Environment: Critical Risk Assessment and Treatment Options
This review provided a critical risk assessment and treatment approaches for emerging pollutants in aquatic environments, including pharmaceuticals, microplastics, and personal care products, evaluating removal efficiency across treatment technologies.
AI-based wastewater treatment for a circular economy and sustainable management of PFAS, heavy metals, microplastics, and antibiotics
This review examined how artificial intelligence can be integrated into wastewater treatment systems to improve removal of emerging contaminants including PFAS, heavy metals, microplastics, and antibiotics. The authors conclude that AI-driven optimization offers significant potential for a circular economy approach to water treatment.
Efficient Data-Driven Machine Learning Models for Water Quality Prediction
This study tested machine learning methods for predicting water quality based on physical, chemical, and biological measurements. While focused on water safety testing rather than microplastics specifically, the automated classification tools developed here could help water treatment facilities quickly identify contaminated water. Better monitoring technology is important because current methods for detecting microplastics in water are slow and expensive.
Aquatic ecosystem indices, linking ecosystem health to human health risks
Researchers reviewed indicators used to assess aquatic ecosystem health and found that most existing tools don't adequately capture the risks that degraded water ecosystems pose to human health and well-being. They propose a new set of combined indicators — covering chemical contaminants, pathogens, and biological markers — to better link ecosystem health monitoring to human health outcomes.
Understanding hazardous concentrations of microplastics in fresh water using non-traditional toxicity data
Researchers developed hazard concentration thresholds for microplastics in freshwater using non-traditional toxicity data, accounting for environmentally relevant sizes, shapes, and polymer types to provide more realistic governance standards.
Emerging Contaminants in Water: An Overview of Causes, Metrics, and Treatment Methods
This review defined emerging contaminants in water — including pharmaceuticals, microplastics, and endocrine disruptors — and surveyed the metrics used to assess them along with treatment technologies capable of their removal. It highlighted the gap between detection capabilities and treatment effectiveness for many contaminants.
Which\nMicropollutants in Water Environments Deserve\nMore Attention Globally?
This review analyzed which organic micropollutants in water environments deserve the most global attention based on their toxicity, occurrence frequency, and persistence. Microplastics are among the contaminants considered, alongside pharmaceuticals, pesticides, and industrial chemicals that routinely escape conventional water treatment and accumulate in aquatic ecosystems.
Which\nMicropollutants in Water Environments Deserve\nMore Attention Globally?
This review analyzed which organic micropollutants in water environments deserve the most global attention based on their toxicity, occurrence frequency, and persistence. Microplastics are among the contaminants considered, alongside pharmaceuticals, pesticides, and industrial chemicals that routinely escape conventional water treatment and accumulate in aquatic ecosystems.
A Fuzzy Ballast Water Risk Assessment Model in Maritime Transport
Researchers developed a fuzzy logic-based risk assessment model for evaluating the environmental hazards of ballast water discharge from maritime transport, including the spread of invasive species and pollutants. The model addresses the complex uncertainties that traditional assessment methods often fail to capture. The study suggests this approach can help port authorities and shipping companies better manage ballast water risks to marine ecosystems.
Green Analytical Chemistry Strategies for Urban Wastewater Monitoring of Emerging Contaminants: a Machine Learning and Multi-technique Strategy
This study developed a green analytical chemistry strategy combining machine learning and multiple spectroscopic techniques to monitor emerging contaminants including microplastics, pharmaceuticals, and endocrine-disrupting chemicals in urban wastewater from Nigerian cities. The approach reduced toxic reagent use while improving detection accuracy for a wide range of contaminants.
Transforming Pollution into Purity: Ensuring Water Quality for Human Health and Environmental Sustainability
This review examines global threats to water quality from contaminants including microplastics, heavy metals, pharmaceuticals, and agrochemicals, and their consequences for human health and ecosystems. The authors advocate for a comprehensive strategy combining source protection, advanced treatment technologies like constructed wetlands and advanced oxidation, and robust governance to ensure safe water access.