Green ternary composite of graphitic carbon nitride/TiO2/ polyorthoanisidine for the enhanced photocatalytic treatment of Direct Red 28 for industrial water treatment solutions.

Industrial dye effluent causes significant risks to the environment. The present study was focused on photocatalytic degradation of the dye Direct Red 28 using a ternary composite of graphitic carbon nitride, TiO2, and polyorthoanisidine (g-C3N4/TiO2/POA), prepared by in-situ oxidative polymerization o-anisidine. The synthesized composite g-C3N4/TiO2/POA properties were characterized using different analytical techniques. X-ray diffraction (XRD) results revealed the prominent pattern of TiO2 and g-C3N4 in the composite peak at 2θ° while Fourier transform infrared (FTIR) results provided the confirmation peaks for g-C3N4/TiO2/POA and POA at 1,110 cm-1 and 1,084 cm-1 for C-O-C ether. Scanning electron microscopy (SEM) demonstrated an increase in the average size of the composite up to 428 nm. The energy-dispersive X-ray spectroscopy (EDX) spectrum provided the weight percentages of the C, O, and Ti in the composite were 8.5%, 45.69%, and 45.81%, respectively. The photocatalytic degradation of Direct Red 28 dye under UV irradiation using a composite showed that 86% Direct Red 28 dye was degraded by a 30 mg/L dose of g-C3N4/TiO2/POA in 240 min at pH 2. After four consecutive cycles, the utilized composite showed 79% degradation of Direct Red 28, demonstrating the stability and effectiveness of the g-C3N4/TiO2/POA photocatalyst. The high reusability and efficiency of the g-C3N4/TiO2/POA composite are due to increased light absorption range and reduced e-/h+ recombination rate in the presence of g-C3N4 and POA.

Wastewater Management in Africa: Challenges and Recommendations.

In Africa, the growing population and industrial growth have resulted in a notable increase in wastewater generation, affecting the quality of water in the region. Wastewater treatment plays a crucial role in safeguarding the environment, public health, aquatic organisms, and water resources, reducing environmental impact, and adhering to regulations. However, the current methods for treating wastewater in Africa fall short of these goals, resulting in substantially poor environmental and health outcomes and inadequate provision of safe water and essential sanitation. Poor wastewater management in several African countries has led to severe health risks for humans, animals, and aquatic ecosystems. This poses a particular threat to vulnerable groups like children, women, and the disabled residing in rural and remote areas with limited access to healthcare. Hence, this article aims to shine a spotlight on the difficulties in managing wastewater in Africa and to recommend several plausible strategies to tackle this issue. A literature search to find the most recent and relevant research papers from various databases, such as Scopus, Web of Science, PubMed, and Google Scholar, along with resources from the World Health Organization, was conducted. The selection criteria focused on including the most recent and relevant publications published in English to facilitate comprehension, analysis, and interpretation of the secondary data. Essentially, addressing the challenge of wastewater management in Africa requires developing indigenous innovative technologies, transitioning to a sustainable economy, establishing wastewater treatment infrastructures in rural and remote areas, enhancing operation and maintenance practices, training treatment facility workers, improving electricity supply, strengthening government participation and support, encouraging public involvement, setting local water quality benchmarks, and international financial and technical support. By tackling the problem of insufficient wastewater treatment in Africa, it is possible to achieve Sustainable Development Goal 6, which centers on ensuring clean water and sanitation for all.

Making waves: Breaking the bottleneck of recycling drinking water treatment residue for practical engineering applications in water pollution control.

Drinking water treatment residue (DWTR), an inevitable byproduct of water treatment plants, is typically recycled to control water pollution. DWTR poses a low environmental risk and has the potential to function as a functional material for various applications. However, the practical engineering applications of DWTR are limited. These limitations arise from a disconnect between fundamental research and the practical needs of engineering applications, creating a bottleneck for the effective recycling of DWTR. Previous studies have primarily focused on exploring potential DWTR recycling methods that reuse Al, Fe, Mn, Ca, Si, and organic C. However, the varying properties of DWTR obtained from different water treatment plants tend to differ with respect to potential recycling methods, confusing managers and engineers in using relevant knowledge to guide practical engineering applications. To address this challenge, the author advocates for a shift in research toward establishing guidelines that provide direct guidance for practical engineering applications of DWTR. The key components of these guidelines should include risk assessment, capability evaluation, and environmental application procedures with sustainability assessment to break the bottleneck associated with the recycling of DWTR.

Cutting-Edge Applications of Cellulose-Based Membranes in Drug and Organic Contaminant Removal: Recent Advances and Innovations.

The increasing environmental challenges caused by pharmaceutical waste, especially antibiotics and contaminants, necessitate sustainable solutions. Cellulose-based membranes are considered advanced tools and show great potential as effective materials for the removal of drugs and organic contaminants. This review introduces an environmentally friendly composite membrane for the elimination of antibiotics and dye contaminants from water and food, without the use of toxic additives. The potential of cellulose-based membranes in reducing the impact on water quality and promoting environmental sustainability is emphasized. Additionally, the benefits of using biobased cellulose membranes in membrane biological reactors for the removal of antibiotics from pharmaceutical waste and milk are explored, presenting an innovative approach to achieving a circular economy. This review provides recent and comprehensive insights into membrane bioreactor technology, making it a valuable resource for researchers seeking efficient methods to break down antibiotics in industrial wastewater, particularly in the pharmaceutical and dairy industries.

A Miniaturized, Fuel-Free, Self-Propelled, Bio-Inspired Soft Actuator for Copper Ion Removal.

We present a novel miniaturized, gear-shaped, fuel-free actuator capable of autonomously propelling itself in an aquatic environment to absorb heavy metals, such as copper ions. While hydrogel-based absorbents are promising solutions for cationic pollutant remediation, their stationary nature limits their effectiveness in areas where contaminants are unevenly distributed. To address this, we developed a bio-inspired soft actuator that mimics natural propulsion mechanisms. The Marangoni effect, driven by its inherent chemical properties, demonstrated a self-propelled motion without requiring external fuel. The proof-of-concept actuator generated a plane motion lasting up to 2 h and swept over an area approximately 400 times bigger than its size. By harnessing the chemical and optical properties of the hydrogel, we efficiently removed and quantitatively analyzed copper ions through a colorimetric method. This innovative integration of self-propelled movement and efficient copper ion absorption underscores its potential for advancing miniaturized devices in environmental remediation, paving the way for more active and efficient pollutant removal systems in challenging aquatic environments.

Metagenomic insights into plasmid-mediated antimicrobial resistance in poultry slaughterhouse wastewater: antibiotics occurrence and genetic markers.

Slaughterhouse wastewater represents important convergence and concentration points for antimicrobial residues, bacteria, and antibiotic resistance genes (ARG), which can promote antimicrobial resistance propagation in different environmental compartments. This study reports the assessment of the metaplasmidome-associated resistome in poultry slaughterhouse wastewater treated by biological processes, employing metagenomic sequencing. Antimicrobial residues from a wastewater treatment plant (WWTP) that treats poultry slaughterhouse influents and effluents were investigated through high-performance liquid chromatography coupled to tandem mass spectrometry (HPLC-MS/MS). Residues from the macrolide, sulfonamide, and fluoroquinolone classes were detected, the latter two persisting after the wastewater treatment. The genetic markers 16S rRNA rrs (bacterial community) and uidA (Escherichia coli) were investigated by RT-qPCR and the sul1 and int1 genes by qPCR. After treatment, the 16S rRNA rrs, uidA, sul1, and int1 markers exhibited reductions of 0.67, 1.07, 1.28, and 0.79 genes copies, respectively, with no statistical significance (p > 0.05). The plasmidome-focused metagenomics sequences (MiSeq platform (Illumina®)) revealed more than 100 ARG in the WWTP influent, which can potentially confer resistance to 14 pharmacological classes relevant in the human and veterinary clinical contexts, in which the qnr gene (resistance to fluoroquinolones) was the most prevalent. Only 7.8% of ARG were reduced after wastewater treatment, and the remaining 92.2% were associated with an increase in the prevalence of ARG linked to multidrug efflux pumps, substrate-specific for certain classes of antibiotics, or broad resistance to multiple medications. These data demonstrate that wastewater from poultry slaughterhouses plays a crucial role as an ARG reservoir and in the spread of AMR into the environment.

Assessing the relationship between river water pollution and the LULC composition of a basin in the Isthmus of Tehuantepec in Oaxaca, Mexico.

Water pollution originating from land use and land cover (LULC) can disrupt river ecosystems, posing a threat to public health, safety, and socioeconomic sustainability. Although the interactions between terrestrial and aquatic systems have been investigated for decades, the scale at which land use practices, whether in the entire basin or separately in parts, significantly impact water quality still needs to be determined. In this research, we used multitemporal data (field measurements, Sentinel 2 images, and elevation data) to investigate how the LULC composition in the catchment area (CA) of each water pollution measurement station located in the river course of the Los Perros Basin affects water pollution indicators (WPIs). We examined whether the CAs form a sequential runoff aggregation system for certain pollutants from the highest to the lowest part of the basin. Our research applied statistical (correlation, time series analysis, and canonical correspondence analysis) and geo-visual analyses to identify relationships at the CA level between satellite-based LULC composition and WPI concentrations. We observed that pollutants such as nitrogen, phosphorus, coliforms, and water temperature form a sequential runoff aggregation system from the highest to the lowest part of the basin. We concluded that the observed decrease in natural cover and increase in built-up and agricultural cover in the upper CAs of the study basin between the study period (2016 to 2020) are related to elevated WPI values for suspended solids and coliforms, which exceeded the allowed limits on all CAs and measured dates.

Development of a Fast and Efficient Strategy Based on Nanomagnetic Materials to Remove Polystyrene Spheres from the Aquatic Environment.

Microplastics contamination is growing globally, being a risk for different environmental compartments including animals and humans. At present, some Spanish beaches and coasts have been affected by discharges of these pollutants, which have caused a serious environmental problem. Therefore, efficient strategies to remove microplastics (MPs) from environmental samples are needed. In this study, the application of three magnetic materials, namely iron oxide (Fe3O4) and the composites Fe3O4@Ag and Fe3O4@Ag@L-Cysteine, to remove MPs, specifically polystyrene (PS), from water samples has been assessed. The magnetic nanoparticles were synthesized and characterized by field effect scanning electron microscopy with energy dispersive X-ray spectroscopy detection (FESEM-EDX). Experimental conditions such as temperature, time, and pH during the removal process were assessed for the different adsorbent materials. The removal rate was calculated by filtering the treated water samples and counting the remaining MPs in the water using ImageJ software. The strongest removal efficiency (100%) was shown using Fe3O4@Ag@L-Cysteine for PS at 50 mg L-1 within 15 min of the separation process at room temperature and a neutral pH. A thermodynamic study demonstrated that the developed MPs elimination strategy was a spontaneous and physisorption process. Coated Fe3O4 magnetic nanoparticles were demonstrated to be an efficient adsorbent for MP removal in aquatic environments and their use a promising technique for the control of MPs contamination.

Seasonal dynamics of bacterial communities in a highly polluted coastal lagoon: Dominance of sulfur bacteria in response to elevated H2S levels.

This study aims to evaluate the effects of different environmental gradients and seasonality on the bacterial communities of an impacted coastal lagoon. While the community compositions were homogenous in surface waters with the dominance of Candidatus Pelagibacter, diversity showed high vertical variation due to salinity and dissolved oxygen gradients. Anoxic conditions occurred at deeper parts of the lagoon, particularly at 14 m and 18 m, where nutrient enrichment and high H2S concentration were detected resulting in a shift of bacterial community to anoxic species. Sulfurimonas, Sulfurovum, and Desulfobacula were dominant genera at 14 m and 18 m where the H2S concentration was high. The community composition of the sediment did not change over seasons, dominated by Syntrophus species. The insights gained from this study may contribute to understanding how dissolved oxygen, H2S concentrations and salinity drive bacterial community structure in euxinic ecosystems especially the dominance of anoxic bacteria.

Combined pollution of tetracyclines and microplastics in the aquatic environment: insights into the occurrence, interaction mechanisms and effects.

Tetracyclines, a widely used class of antibiotics, and synthetic plastic products are both prevalent in the environment. When released into water bodies, these pollutants can pose significant risks due to their daily influx into aquatic ecosystems. Microplastics can adsorb tetracyclines, acting as a transport vector that enhances their impact on aquatic species. Understanding the co-exposure effects of microplastics and tetracyclines is crucial. This review comprehensively examines the occurrence and distribution of microplastics and tetracyclines across various environmental contexts. The interactions between these two contaminants are primarily driven by electrostatic interactions, hydrophobic effects, hydrogen bonding, π-π interactions, and others. Factors such as the presence of heavy metals, ions, and dissolved organic matter can influence the adsorption and desorption of tetracyclines onto microplastics. The stability of microplastic-tetracycline complexes is highly dependent on pH conditions. The combined pollution tetracyclines and microplastics leads to negative impacts on marine species. Future research should focus on understanding the adsorption behavior of tetracyclines on microplastics and developing effective treatment techniques for these contaminants in aquatic environments.

Remote Sensing Inversion of Water Quality Grades Using a Stacked Generalization Approach.

Understanding water quality is crucial for environmental management and policy formulation. However, existing methods for assessing water quality are often unable to fully integrate with multi-source remote sensing data. This study introduces a method that employs a stacking algorithm within the Google Earth Engine (GEE) for classifying water quality grades in the Songhua River Basin (SHRB). By leveraging the strengths of multiple machine learning models, the Stacked Generalization (SG) model achieved an accuracy of 91.67%, significantly enhancing classification performance compared to traditional approaches. Additionally, the analysis revealed substantial correlations between the normalized difference vegetation index (NDVI) and precipitation with water quality grades. These findings underscore the efficacy of this method for effective water quality monitoring and its implications for understanding the influence of natural factors on water pollution.

The molecular insights of cyanobacterial bioremediations of heavy metals: the current and the future challenges.

In recent years, overexplorations of ore and the growth of industries are the prime factors in the release of heavy metals in environments. As a result, the food crops and water bodies are contaminated with metals which may have several adverse effects on the health of humans and other living species. These metals and metalloids, such as Zn, Cu, Mn, Ni, Cr, Pb, Cd, and As, upset the biochemical pathways of metabolite synthesis in living organisms and contribute to the etiology of different diseases. Microorganisms include bacteria, archaea, viruses, and many unicellular eukaryotes, which can span three domains of life-Archaea, Bacteria, and Eukarya-and some microorganisms, such as cyanobacteria, have shown high efficiency in the biosorption rate of heavy metals. Cyanobacteria are suitable for bioremediation as they can grow in adverse environments, have a less negative impact on the surrounding environment, and are relatively cheaper to manage. The structure of cyanobacteria has shown no extensive internal-bound membranes, so it can directly employ the physiological mechanisms to uptake heavy metals from contamination sites. Such biochemical makeups are suitable for managing and bioremediating heavy metal concentrations in polluted environments. This review aims to explore the potential of cyanobacteria in the bioremediation of heavy metals and metalloids in water bodies. Additionally, we have identified the prospects for enhancing bioremediation effectiveness.

Microplastic predictive modelling with the integration of Artificial Neural Networks and Hidden Markov Models (ANN-HMM).

Microplastic pollution poses a significant threat to our environment, necessitating effective predictive modelling approaches for better management and mitigation. In this study, we introduce a pioneering methodology that fuses the power of Artificial Neural Networks (ANN) and Hidden Markov Models (HMM) for microplastic predictive modelling. Leveraging a comprehensive dataset, our integrated model exhibits exceptional performance, with an Accuracy of 0.96, Precision of 0.96, Recall of 0.97, and an F1 Score of 0.96. The achieved Accuracy underscores the model's proficiency in distinguishing microplastic and non-microplastic entities, promising robust and reliable predictions. Precision, as a measure of correct positive identifications, demonstrates our model's effectiveness in minimizing false positives, a crucial aspect for environmental monitoring. Moreover, the perfect Recall score signifies the model's ability to detect all relevant microplastic instances, addressing concerns about false negatives. The F1 Score encapsulates this dual proficiency, showcasing a harmonious trade-off between precision and recall. Our research not only advances the field of microplastic prediction but also highlights the potential of synergizing ANN and HMM methodologies for comprehensive environmental assessments. The reported performance metrics underscore the practical applicability of our approach, offering a valuable tool for tackling the pervasive issue of microplastic pollution and fostering proactive environmental stewardship.

[Microbial remediation of heavy metal-polluted water].

Heavy metal pollution in water has become a global environmental problem, threatening aquatic ecosystems and human health. Physical and chemical methods can effectively remove heavy metal pollutants, while their applications are limited due to the high costs, complex operation, and susceptibility to secondary pollution. Bioremediation is the most promising method for eliminating toxic pollutants. Microorganisms including bacteria, fungi, and algae can convert toxic heavy metals into less toxic forms, which has become an effective and environmentally friendly solution for the remediation of heavy metal pollution in water environments. This paper expounds the toxicity and mechanism of heavy metal pollution, microbial remediation mechanisms, and primary microbial remediation strategies, providing a reference for the removal or reduction of metal pollutants in water environments as well as the development of related technologies.

Optimizing surface water quality parameters in monitoring networks in a developing sub-tropical region with high anthropogenic pressure (São Paulo State Brazil).

Efficient water quality monitoring is a central aspect of water resources management, especially in developing countries, where water quality is under high anthropogenic pressure and resources for monitoring are usually limited. Here, we evaluated an alternative to optimize water quality parameters (WQPs) in the water quality monitoring network (WQMN) of the most populous state in Brazil (São Paulo State). We focused on the monitoring goal of identifying water quality temporal trends, selecting WQPs with high statistical explanatory power and those that were particularly sensitive to natural and anthropogenic perturbations. We considered 12 initial WQPs (dissolved copper, total zinc, total lead, total chromium, total mercury, total nickel, total cadmium, total iron, total manganese, total aluminum, total copper, and surfactant) with data from 2004 to 2018 for 56 monitoring sites distributed across four major watersheds with contrasting land uses in the state. We performed principal component analysis, followed by objective criteria to refine WQPs recommendation for the WQMN. Our results indicated the opportunity of reducing at least one parameter from the initial set of WQPs in all watersheds. Total iron, total manganese, and total aluminum were the most relevant initial WQPs, since their maintenance in monitoring were indicated in all the analyzed cases. Natural watershed conditions (e.g., geomorphology and water geochemistry) potentially governed their concentrations in surface water. On the other hand, total mercury, total chromium, and dissolved copper had the maintenance indicated in only one watershed, especially due to concentrations consistently below the respective limits of quantification (LoQs). Future investigations can complement our recommendations for these parameters, since changes in LoQs could throw another light on water quality spatial and temporal variations and the need for reference areas for assessing baseline conditions can also be relevant. Moreover, we argue that depending on the monitoring goals of the WQMN, additional sampling of biota and sediments could be useful as many of the studied WQPs' bioconcentrate. Our results illustrated an alternative approach towards adaptive monitoring in São Paulo state in accordance with the intended monitoring goal (i.e., water quality temporal trends), converging with the more flexible monitoring adopted in well-structured networks worldwide. While we did not cover other monitoring goals in our study (as the control of illegal discharge of effluents or industrial spills, for example), we expect our methodology can contribute to establishing technical guidelines for reviewing the existing WQMNs in Brazil and other developing countries with similar challenges.

Integrating material flow analysis into hydrological model for water environment management of large-scale urban-rural mixed catchment.

Simultaneous simulation of urban and rural hydrological processes is important for water environment management of mixed land-uses catchments. However, the discharge paths of pollution in the urban drainage system are not described in traditional catchment hydrological models. In this study, an urban-rural water environment (URWE) model is developed through incorporating the material flow analysis (MFA) and the soil and water assessment tool (SWAT) into a general framework. The URWE model is an advancement with respect to traditional hydrological models in terms of simultaneously simulating the urban organized and rural decentralized discharges of pollution. Due to the low data requirement and high computational efficiency of MFA, URWE model is applicable to large-scale catchment with wide urban area. The URWE model is applied to a typical urban-rural mixed catchment, the Dianchi Catchment (China), where the pollution characteristics are analyzed and the pollution control measures are investigated. Results indicate that the URWE model outperforms the conventional SWAT model for both water quantity and quality simulations, with an 8.5 % improvement in average coefficient of determination (R2) and a 67.4 % improvement in average Nash coefficient (NSE). Rural best management practice, rainwater-sewage separation, and storage capacity expansion are identified as the most cost-effective measures for COD, TN, and TP reduction, respectively. Contributions of this study are to improve the accuracy of water environment simulation in urban-rural mixed catchment, as well as to help decision-makers develop synergistic urban-rural water environment management measures.

Seasonal assessment of surface water and sediments pollution in Rachiine River, Northern Lebanon, using multivariate statistical analysis.

Urbanization has caused severe negative impacts on intra-urban river water worldwide. In this study, the WHO drinking water standards (2024) were used as reference to assess the physicochemical properties, heavy metals (HMs) content and microbial load in water and sediment samples collected from 25 locations along Rachiine River, located in Northern Lebanon, during wet and dry periods. Multivariate statistical analysis was applied to evaluate the seasonal variations in water and sediment quality, and determine the pollution sources. The microbial load assessment indicated high pollution levels by Escherichia coli, fecal enterococci, total coliform and fecal coliform, which generally increased as the river progressed downstream. Cluster analysis (CA) provided three major clusters in the study region, representing the northern, central, and southern sectors of the river. Principal components analysis (PCA) of water samples generated four principal components (PCs) accounting for 64.3, 11.4, 7.6 and 4.1 % of the total variance, whereas PCA of sediment samples explained 59.1, 16.9 and 11.1 % of the data set variance. These PCs revealed that the quality of water and sediments is significantly impacted by point and diffuse sources, including geological and anthropogenic factors. These findings call for urgent management strategies to limit future deterioration of the aquatic bodies.

Microcystin-LR in drinking water: An emerging role of mitochondrial-induced epigenetic modifications and possible mitigation strategies.

Algal blooms are a serious menace to freshwater bodies all over the world. These blooms typically comprise cyanobacterial outgrowths that produce a heptapeptide toxin, Microcystin-LR (MC-LR). Chronic MC-LR exposure impairs mitochondrial-nuclear crosstalk, ROS generation, activation of DNA damage repair pathways, apoptosis, and calcium homeostasis by interfering with PC/MAPK/RTK/PI3K signaling. The discovery of the toxin's biosynthesis pathways paved the way for the development of molecular techniques for the early detection of microcystin. Phosphatase inhibition-based bioassays, high-performance liquid chromatography, and enzyme-linked immunosorbent tests have recently been employed to identify MC-LR in aquatic ecosystems. Biosensors are an exciting alternative for effective on-site analysis and field-based characterization. Here, we present a synthesis of evidence supporting MC-LR as a mitotoxicant, examine various detection methods, and propose a novel theory for the relevance of MC-LR-induced breakdown of mitochondrial machinery and its myriad biological ramifications in human health and disease.

Influence of Pd, Pt and Au nanoparticles in the photocatalytic performance of N-TiO2 support under visible light.

In this article, we report the modification and photocatalytic evaluation of commercial TiO2-P25 under visible light for methyl orange (MO) dye degradation under visible light. The activity of materials doped with N, Pd, Pt and Au on to the TiO2-P25 was evaluated, with optimal photocatalytic performance achieved using Au nanoparticles doped on an N-functionalized titania surface. X-ray diffraction (XRD), physical nitrogen adsorption/desorption isotherm curves, transmission electron microscopy (TEM), diffuse reflectance spectroscopy, scanning electron microscopy (SEM) and energy dispersive X-ray spectroscopy (EDX) were used to study the structural and textural properties of the samples. The chemical species present in the bulk and surface of the catalysts were identified using X-ray photoelectron spectroscopy (XPS) and microwave plasma-atomic emission spectroscopy. The results show that Au/N-TiO2 photocatalyst presents a remarkable enhanced activity for MO dye degradation, under visible light illumination, reaching 100% after 4 h. The enhanced photocatalytic activity using this composite is attributable to the well-dispersed and small size of Au nanoparticles, large surface area, reduction of band-gap energy and the interaction between nitrogen and Au which promoted a synergistic effect. This article is part of the discussion meeting issue 'Green carbon for the chemical industry of the future'.

Per- and polyfluoroalkyl substances contamination of drinking water sources in Africa: Pollution sources and possible treatment methods.

Despite the detection of poly- and perfluorinated alkyl substances (PFAS) in the water system in Africa, the effort towards mitigating PFAS in water in Africa needs to be better understood. Therefore, this review evaluated the contamination status and mitigation methods for handling PFAS-contaminated water systems in Africa. The findings revealed the presence of PFAS in wastewater treatment plant (WWTP) effluents, surface water and commercially available bottled and tap water in African countries. The concentration of PFAS in drinking water sources reviewed ranged from < limits of quantification to 778 ng L-1. The sources of PFAS in water systems in Africa are linked to uncontrolled importation of PFAS-containing products, WWTP effluents and inappropriate disposal of PFAS-containing materials. The information on treatment methods for PFAS-contaminated water systems is scanty. Unfortunately, the treatment method is challenged by poor water research infrastructure and facilities, lack of awareness, poor research funding and weak legislation; however, adsorption and membrane technology seem favourable for removing PFAS from water systems in Africa. It is essential to focus on monitoring and assessing drinking water quality in Africa to reduce the disease burden that this may cause. Most African countries' currently implemented water treatment facilities cannot efficiently remove PFAS during treatment. Therefore, governments in Africa need to fund more research to develop an efficient water treatment technique that is sustainable in Africa.