Expanding the Application of Sentinel-2 Chlorophyll Monitoring across United States Lakes.

Eutrophication of inland lakes poses various societal and ecological threats, making water quality monitoring crucial. Satellites provide a comprehensive and cost-effective supplement to traditional in situ sampling. The Sentinel-2 MultiSpectral Instrument (S2 MSI) offers unique spectral bands positioned to quantify chlorophyll a, a water-quality and trophic-state indicator, along with fine spatial resolution, enabling the monitoring of small waterbodies. In this study, two algorithms-the Maximum Chlorophyll Index (MCI) and the Normalized Difference Chlorophyll Index (NDCI)-were applied to S2 MSI data. They were calibrated and validated using in situ chlorophyll a measurements for 103 lakes across the contiguous U.S. Both algorithms were tested using top-of-atmosphere reflectances (ρ t), Rayleigh-corrected reflectances (ρ s), and remote sensing reflectances (R rs ). MCI slightly outperformed NDCI across all reflectance products. MCI using ρ t showed the best overall performance, with a mean absolute error factor of 2.08 and a mean bias factor of 1.15. Conversion of derived chlorophyll a to trophic state improved the potential for management applications, with 82% accuracy using a binary classification. We report algorithm-to-chlorophyll-a conversions that show potential for application across the U.S., demonstrating that S2 can serve as a monitoring tool for inland lakes across broad spatial scales.

Evaluation of low-cost sensors to integrate in a water quality monitor for real-time measurements.

Low-cost sensors integrated with the Internet of Things can enable real-time environmental monitoring networks and provide valuable water quality information to the public. However, the accuracy and precision of the values measured by the sensors are critical for widespread adoption. In this study, 19 different low-cost sensors, commonly found in the literature, from four different manufacturers are tested for measuring five water quality parameters: pH, dissolved oxygen, oxidation-reduction potential, turbidity, and temperature. The low-cost sensors are evaluated for each parameter by calculating the error and precision compared to a typical multiparameter probe assumed as a reference. The comparison was performed in a controlled environment with simultaneous measurements of real water samples. The relative error ranged from - 0.33 to 33.77%, and most of them were ≤ 5%. The pH and temperature were the ones with the most accurate results. In conclusion, low-cost sensors are a complementary alternative to quickly detect changes in water quality parameters. Further studies are necessary to establish a guideline for the operation and maintenance of low-cost sensors.

Centralized or Onsite Testing? Examining the Costs of Water Quality Monitoring in Rural Africa.

Rural water systems in Africa have room to improve water quality monitoring. However, the most cost-effective approach for microbial water testing remains uncertain. This study compared the cost per E. coli test (membrane filtration) of four approaches representing different levels of centralization: (i) one centralized laboratory serving all water systems, (ii) a mobile laboratory serving all systems, (iii) multiple semi-centralized laboratories serving clusters of systems, and (iv) decentralized analysis at each system. We employed Monte Carlo analyses to model the costs of these approaches in three real-world contexts in Ghana and Uganda and in hypothetical simulations capturing various conditions across rural Africa. Centralized testing was the lowest cost in two real-world settings and the widest variety of simulations, especially those with water systems close to a central laboratory (<36 km). Semi-centralized testing was the lowest cost in one real-world setting and in simulations with clustered water systems and intermediate sampling frequencies (1-2 monthly samples per system). The mobile lab was the lowest cost in the fewest simulations, requiring few systems and infrequent sampling. Decentralized testing was cost-effective for remote systems and frequent sampling, but only if sampling did not require a dedicated vehicle. Alternative low-cost testing methods could make decentralized testing more competitive.

Breaking barriers in passive sampling: The potential of PTFE membranes in the monitoring of hydrophilic micropollutants.

Passive samplers are key tools to sample hydrophilic micropollutants in water. Two main approaches address the influence of hydrodynamics: (1) determining site-specific sampling rate (RS) by characterizing kw, the mass transfer coefficient of the water-boundary layer (WBL), and (2) reducing WBL impact using a diffusive material to control the uptake. The first requires calibration data and the second has only been achieved using fragile diffusive material. This study assesses the transfer of hydrophilic contaminants through polytetrafluoroethylene (PTFE; 30 µm thick), a new membrane material with lower sorption than commonly used polyethersulfone (PES). Combined for the first time in a Chemcatcher-like configuration, we calibrated the modified samplers for 44 micropollutants to provide RS - kw relationships for in-situ RS determination (approach 1). Micropollutants accumulated over 2000 times more on the sorbent than on PTFE. PTFE-based RS (0.027 to 0.300 L day-1) were 2.5 higher than previously reported with PES. Membrane property measurements (porosity, tortuosity) indicated that accumulation is primarily controlled by the membrane. Extrapolation indicated that using thicker PTFE membranes (≥ 100 µm) would shift uptake control entirely to the membrane in river conditions (approach 2). This finding could enable RS prediction based on contaminants properties, thus representing a significant advancement in passive sampling.

Automated identification of toxigenic cyanobacterial genera for water quality control purposes.

Cyanobacteria are the dominating microorganisms in aquatic environments, posing significant risks to public health due to toxin production in drinking water reservoirs. Traditional water quality assessments for abundance of the toxigenic genera in water samples are both time-consuming and error-prone, highlighting the urgent need for a fast and accurate automated approach. This study addresses this gap by introducing a novel public dataset, TCB-DS (Toxigenic Cyanobacteria Dataset), comprising 2593 microscopic images of 10 toxigenic cyanobacterial genera and subsequently, an automated system to identify these genera which can be divided into two parts. Initially, a feature extractor Convolutional Neural Network (CNN) model was employed, with MobileNet emerging as the optimal choice after comparing it with various other popular architectures such as MobileNetV2, VGG, etc. Secondly, to perform classification algorithms on the extracted features of the first section, multiple approaches were tested and the experimental results indicate that a Fully Connected Neural Network (FCNN) had the optimal performance with weighted accuracy and f1-score of 94.79% and 94.91%, respectively. The highest macro accuracy and f1-score were 90.17% and 87.64% which were acquired using MobileNetV2 as the feature extractor and FCNN as the classifier. These results demonstrate that the proposed approach can be employed as an automated screening tool for identifying toxigenic Cyanobacteria with practical implications for water quality control replacing the traditional estimation given by the lab operator following microscopic observations. The dataset and code of this paper are publicly available at https://github.com/iman2693/CTCB.

Optimizing sampling location for water quality degradation monitoring in distribution systems: Assessing global representativeness and potential health risk.

Selecting the optimal monitoring points in a water distribution network is challenging due to the complex spatiotemporal variability of water quality degradation. The lack of a standardized methodology for monitoring point selection forces operators to rely on general recommendations, historical data and professional experience, which can mask water quality problems and increase the risk to consumers. This study proposes a new methodology to optimize the selection of monitoring points in distribution networks. The method considers the spatiotemporal degradation of water quality, the definition of representative zones and two selection criteria: global representativeness and potential health risk. Representative zones were determined for each node of the network based on hydraulic paths and their water quality spatial variability. Part of the distribution network in Quebec City, Canada was used as the case study, in which four water quality parameters were investigated: free chlorine residual (FRC), heterotrophic plate counts (HPC), trihalomethanes (THMs) and haloacetic acids (HAAs). Seasonal variabilities (summer and winter) were also analyzed. The results obtained for the two criteria and for both seasons were compared, and methodological and practical recommendations were established for dynamic monitoring programs that respond to the needs of operators.

Application of in vitro bioassays to monitor pharmaceuticals in water: A synthesis of chronological analysis, mode of action, and practical insights.

Pharmaceutical compounds in wastewater have emerged as a significant concern for the aquatic environment. The use of in vitro bioassays represents a sustainable and cost-effective approach for assessing the potential toxicological risks of these biologically active compounds in wastewater and aligns with ethical considerations in research. It facilitates high-throughput analysis, captures mixture effects, integrates impacts of both known and unknown chemicals, and reduces reliance on animal testing. The core aim of the current review was to explore the practical application of in vitro bioassays in evaluating the environmental impacts of pharmaceuticals in wastewater. This comprehensive review strives to achieve several key objectives. First, it provides a summary categorisation of pharmaceuticals based on their mode of action, providing a structured framework for understanding their ecological significance. Second, a chronological analysis of pharmaceutical research aims to document their prevalence and trends over time, shedding light on evolving environmental challenges. Third, the review critically analyses existing bioassay applications in wastewater, while also examining bioassay coverage of representative compounds within major pharmaceutical classes. Finally, it explores the potential for developing innovative bioassays tailored for water quality monitoring of pharmaceuticals, paving the way for more robust environmental monitoring and risk assessment. Overall, adopting effect-based methods for pharmaceutical monitoring in water holds significant promise. It encompasses a broad spectrum of biological impacts, promotes standardized protocols, and supports a bioassay test battery approach indicative of different endpoints, thereby enhancing the effectiveness of environmental risk assessment.

Beyond the Drinking Water Directive: The use of reporter gene assays as an added tool for effect-based monitoring of polycyclic aromatic hydrocarbons and polychlorinated biphenyls in drinking water sources.

Polycyclic aromatic hydrocarbons (PAHs) and polychlorinated biphenyls (PCBs) are legacy organic micropollutants (OMPs) that are sporadically detected in drinking water (DW) sources. The European Drinking Water Directive requires EU member states to monitor 5 PAHs in DW and its sources. The Dutch national regulations require 6 additional PAHs to be monitored and 7 polychlorinated biphenyls (PCBs). These indicator compounds act as representatives for large compound classes. PCBs alone comprise 209 congeners, it is evident that conventional chemical target analysis (GC-tQ-MS) alone is not sufficient to monitor these entire compound classes. This study investigated the application of reporter gene assays as effect-based methods (EBMs) to monitor PAHs and PCBs in DW sources. Herein, it was assessed what added value the bioassays can bring compared to the current approach of chemical target analysis for PCBs and PAHs. Regulated and non-regulated PAHs and PCBs were tested in four bioassays to determine the relative potency factors (RPFs) for these compounds. Non-regulated congeners were found to be active in the PAH-CALUX and anti-AR CALUX. An assessment of surface water (SW) spiked with standard mixtures containing PAHs and PCBs confirmed the predictable behavior of the PAH-CALUX. Moreover, the bioassay was able to detect AhR-mediated activity caused by non-regulated PAHs and PCBs, whereas this would have been missed by conventional chemical target analysis. Last, a field study was conducted in Dutch DW sources at six sampling moments. The PAH-CALUX detected AhR-mediated activity at all sampling moments and an ecological effect-based trigger (EBT) value was exceeded on multiple accounts. Combined application of GC-tQ-MS and the PAH-CALUX ensures compliancy with monitoring legislation and provides additional insights into potential hazards to humans and the environment.

Distribution of toxigenic cyanobacteria in Alpine lakes and rivers as revealed by molecular screening.

The increasing frequency of cyanobacteria blooms in waterbodies caused by ecosystem eutrophication could endanger human health. This risk can be mitigated by effective monitoring incorporating molecular methods. To date, most molecular studies on toxigenic cyanobacteria have been limited to microcystins (MCs), disregarding other cyanotoxins, to freshwater planktic habitats while ignoring benthic habitats, and to limited geographic areas (usually one or a few specific waterbodies). In this study, we used PCR-based methods including PCR product sequencing and chemical-analytical methods (LC-MS/MS) to screen many plankton (n = 123) and biofilm samples (n = 113) originating from 29 Alpine lakes and 18 rivers for their cyanotoxin production potential. Both mcyE (indicating MC synthesis) and anaC (indicating anatoxin (ATX) synthesis) gene fragments were able to qualitatively predict MC or ATX occurrence. The abundance of mcyE gene fragments was significantly related to MC concentrations in plankton samples (R2 = 0.61). mcyE gene fragments indicative of MC synthesis were most abundant in planktic samples (65 %) and were assigned to the genera Planktothrix and Microcystis. However, mcyE rarely occurred in biofilms of lakes and rivers, i.e., 4 % and 5 %, respectively, and were assigned to Microcystis, Planktothrix, and Nostoc. In contrast, anaC gene fragments occurred frequently in planktic samples (14 % assigned to Tychonema, Phormidium (Microcoleus), and Oscillatoria), but also in biofilms of lakes (49 %) and rivers (18 %) and were assigned to the genera Phormidium, Oscillatoria, and Nostocales. The cyrJ gene fragment indicating cylindrospermopsin synthesis occurred only once in plankton (assigned to Dolichospermum), while saxitoxin synthesis potential was not detected. For plankton samples, monomictic and less eutrophic conditions were positively related to mcyE/MC occurrence frequency, while oligomictic conditions were related to anaC/ATX frequency. The anaC/ATX frequency in biofilm was related to the lake habitats generally showing higher biodiversity as revealed from metabarcoding in a parallel study.

A regulatory framework for bottled water quality monitoring: A case of Emfuleni local municipality.

Background: The quality of drinking water has recently become of utmost concern to consumers worldwide, especially in areas where Water Service Authorities (WSAs) failed to provide safe water. To combat this challenge, government entities regulate water to ensure that safe water is provided. The Emfuleni Local Municipality (ELM) has experienced cases of water contamination by human excretion, whereby communities were affected. As a result, there was a sharp increase in bottled water (BW) use, which however gave rise to unregulated and counterfeit versions of popular brands. This situation poses threats to public health. Aim: This study sought to determine the regulation of drinking water and to assess whether environmental health practitioners (EHPs) monitor the quality of water sources (BW and tap water) in ELM as outlined by the National Environmental Health Norms and Standards (NEHNS). Settings: The study was conducted in the Emfuleni Local Municipality in South Africa. Methods: A quantitative cross-sectional study design was employed in this research. Fifteen online questionnaires using a Google Forms survey were distributed amongst all EHPs servicing ELM. Secondary data that included the Integrated Development Plan (IDP) and Service Delivery Budget Implentation Plan (SDBIP) for the 2017-2020 financial years were also evaluated, specifically for water quality monitoring (tap and bottled water). The dataset was analysed using the Statistical Package for the Social Sciences (SPSS) version 29. Results: Due to complexity in the legislation and NEHNS in relation to Municipal Health Services (MHS), bottled water was not sampled at all. A number of EHPs were also not conversant with the regulations governing BW. Moreover, NEHNS consider bottled water as food, which does not fall under the MHS. Conclusion: There should be clarity in the legislation to ensure that bottled water monitoring is intensified to protect public health within the WSAs. Contribution: The findings of this study could assist policy-makers to make informed decisions on water quality monitoring, as well as clarify legislative issues on bottled water.

Evaluation of the water quality monitoring network layout based on driving-pressure-state-response framework and entropy weight TOPSIS model: A case study of Liao River, China.

The establishment of river water quality monitoring network is crucial for watershed protection. However, the evaluation process of monitoring network layout involves significant subjectivity and has not yet to form a complete indicator system. This study constructed an indicator system based on the DPSR (Driving-Pressure-State-Response) framework in the Liao River Basin, China. SWAT model and ArcGIS were used to quantify the indicators. And the entropy weight-TOPSIS method was employed to rank monitoring points. The results showed that pressure and state indicators had a greater impact on the network layout, with the indicator for proportion of land use in residential areas carrying the largest weight of 0.136. It suggested that the risk of river pollution remained high, and the governance strategies needed to be improved. Priority monitoring points were mainly located in the east and middle of the basin, consistent with the distribution of human activities such as urban areas and farmland. In addition, the redundancy of points should be avoided, and evaluation results should be adjusted based on the actual situation. The study provided an evaluation method for the layout of monitoring points.

Quantification and risk assessment of polar organic contaminants in two chalk streams in Hampshire, UK using the Chemcatcher passive sampler.

Freshwater systems are facing a number of pressures due to the inputs of polar organic contaminants from a range of sources including agriculture, domestic and industry. The River Itchen and River Test are two sensitive chalk streams in Southern England that are experiencing a decline in invertebrate communities. We used Chemcatcher passive samplers to measure time-weighted average concentrations (14 days) of polar pollutants at nine sites on the River Itchen and eight sites on the River Test over a 12-month period. Sampler extracts were analysed using a targeted LC/MS method. In total, 121 plant protection products and pharmaceutical and personal care products were quantified (range of log Kow from - 1.5 to 7). Concentrations (sub ng L-1 to >500 ng L-1) in both rivers showed spatial and temporal variations. A greater number of compounds and higher concentrations were found in the River Test. The chemical profile was dominated by inputs from wastewater treatment plants and legacy plant protection products. On the River Itchen, high concentrations (∼100 ng L-1) of caffeine were observed directly downstream of a fish farm. Using the NORMAN database, the predicted no effect concentration (PNEC) freshwater values were exceeded by only five contaminants (2-hydroxy-terbuthylazine, alprazolam, azithromycin, diclofenac and imidacloprid). In addition, venlafaxine was detected above its EU Watch List concentration. These exceedances were mainly downstream of direct inputs from treatment plants. These compounds are known to have ecotoxicological effects on a range of aquatic biota including macroinvertebrates. Of concern is the ubiquitous presence of the ectoparasiticide imidacloprid, highlighting the need to control its use. The impact of the cocktail of pollutants found in this study on the long-term effects on chalk stream ecosystems remains unknown and needs further investigation.

How suitable is freshwater sponge Ephydatia fluviatilis (Linnaeus, 1759) for time-integrated biomonitoring of microbial water quality?

Faecal pollution of water by bacteria has a negative effect on water quality and can pose a potential health hazard. Conventional surveillance of microbial water quality relies on the analysis of low-frequency spot samples and is thus likely to miss episodic or periodic pollution. This study aimed to investigate the potential of filter-feeding sponges for time-integrated biomonitoring of microbial water quality. Laboratory trials tested the effects of different ratios of bacterial abundance and the sequence of exposure on bacterial retention by the freshwater sponge Ephydatia fluviatilis (Linnaeus, 1759) to establish its potential to indicate bacterial exposure. Gemmule grown sponges were simultaneously exposed to Escherichia coli and Enterococcus faecalis but at different ratios (Trial 1) or individually exposed to each bacterial species but in different sequential order (Trial 2). The E. coli and E. faecalis retained in each sponge was quantified by culture on selective agars. Data analysis was conducted using the Kruskal-Wallis test and/or the Mann-Whitney U test to compare between the numbers of bacteria retained in each treatment. Additionally, the Wilcoxon matched-paired signed-rank test was used for comparison of the different bacterial abundances retained within each individual sponge. Sponges from all trials retained E. coli and E. faecalis in small numbers relative to the exposure (<0.05 % Trial 1 and <0.07 % Trial 2) but exhibited higher retention of E. coli. Higher abundance of either bacterial species resulted in significantly lower (P<0.005) retention of the same species within sponges (Trial 1). An initial exposure to E. coli resulted in significantly higher (P=0.040) retention of both bacterial species than when sponges were exposed to E. faecalis first (Trial 2).Bacterial retention by sponges was neither quantitatively representative of bacterial abundance in the ambient water nor the sequence of exposure. This implies either selective filtration or an attempt by sponges to prevent infection. However, freshwater sponges may still be useful in biomonitoring as qualitative time-integrated samplers of faecal indicator bacteria as they detect different bacteria present in the water even if their quantities cannot be estimated.

Improved accuracy in IoT-Based water quality monitoring for aquaculture tanks using low-cost sensors: Asian seabass fish farming.

Traditional approaches to monitoring water quality in aquaculture tanks present numerous limitations, including the inability to provide real-time data, which can lead to improper feeding practices, reduced productivity, and potential environmental risks. To address these challenges, this study aimed to create an accurate water quality monitoring system for Asian seabass fish farming in aquaculture tanks. This was achieved by enhancing the accuracy of low-cost sensors using simple linear regression and validating the IoT system data with YSI Professional Pro. The system's development and validation were conducted over three months, employing professional devices for accuracy assessment. The accuracy of low-cost sensors was significantly improved through simple linear regression. The results demonstrated impressive accuracy levels ranging from 76% to 97%. The relative error values which range from 0.27% to 4% demonstrate a smaller range compared to the values obtained from the YSI probe during the validation process, signifying the enhanced accuracy and reliability of the IoT sensor by using simple linear regression. The system's enhanced accuracy facilitates convenient and reliable real-time water quality monitoring for aquafarmers. Real-time data visualization was achieved through a microcontroller, Thingspeak, Virtuino application, and ESP 8266 Wi-Fi module, providing comprehensive insights into water quality conditions. Overall, this adaptable tool holds promise for accurate water quality management in diverse aquatic farming practices, ultimately leading to improved yields and sustainability.

A High-Frequency and Real-Time Ground Remote Sensing System for Obtaining Water Quality Based on a Micro Hyper-Spectrometer.

The safeguarding of scarce water resources is critically dependent on continuous water quality monitoring. Traditional methods like satellite imagery and automated underwater observation have limitations in cost-efficiency and frequency. Addressing these challenges, a ground-based remote sensing system for the high-frequency, real-time monitoring of water parameters has been developed. This system is encased in a durable stainless-steel shell, suited for outdoor environments, and features a compact hyperspectral instrument with a 4 nm spectral resolution covering a 350-950 nm wavelength range. In addition, it also integrates solar power, Wi-Fi, and microcomputers, enabling the autonomous long-term monitoring of water quality. Positioned on a rotating platform near the shore, this setup allows the spectrometer to quickly capture the reflective spectrum of water within 3 s. To assess its effectiveness, an empirical method correlated the reflective spectrum with the actual chlorophyll a(Chla) concentration. Machine learning algorithms were also used to analyze the spectrum's relationship with key water quality indicators like total phosphorus (TP), total nitrogen (TN), and chemical oxygen demand (COD). Results indicate that the band ratio algorithm accurately determines Chla concentration (R-squared = 0.95; RMSD = 0.06 mg/L). For TP, TN, and COD, support vector machine (SVM) and linear models were highly effective, yielding R-squared values of 0.93, 0.92, and 0.88, respectively. This innovative hyperspectral water quality monitoring system is both practical and reliable, offering a new solution for effective water quality assessment.

Small and Micro-Water Quality Monitoring Based on the Integration of a Full-Space Real 3D Model and IoT.

In order to address the challenges of small and micro-water pollution in parks and the low level of 3D visualization of water quality monitoring systems, this research paper proposes a novel wireless remote water quality monitoring system that combines the Internet of Things (IoT) and a 3D model of reality. To begin with, the construction of a comprehensive 3D model relies on various technologies, including unmanned aerial vehicle (UAV) tilt photography, 3D laser scanning, unmanned ship measurement, and close-range photogrammetry. These techniques are utilized to capture the park's geographical terrain, natural resources, and ecological environment, which are then integrated into the three-dimensional model. Secondly, GNSS positioning, multi-source water quality sensors, NB-IoT wireless communication, and video surveillance are combined with IoT technologies to enable wireless remote real-time monitoring of small and micro-water bodies. Finally, a high-precision underwater, indoor, and outdoor full-space real-scene three-dimensional visual water quality monitoring system integrated with IoT is constructed. The integrated system significantly reduces water pollution in small and micro-water bodies and optimizes the water quality monitoring system.

A nonsymmetrical salamo-like fluorescence chemical sensor for selective identification of Cu2+ and B4O72- ions and practical applications.

An innovative salamo-like fluorescent chemical sensor H2L, has been prepared that can be utilized to selectively detect Cu2+ and B4O72- ions. Cu2+ ions can bind to oxime state nitrogen and phenol state oxygen atoms in the chemosensor H2L, triggering the LMCT effect leading to fluorescence enhancement. The crystal structure of the copper(II) complex, named as [Cu(L)], has been achieved via X-ray crystallography, and the sensing mechanism has been confirmed by further theoretical calculations with DFT. Besides, the sensor H2L recognizes B4O72- ions causing an ICT effect resulting in bright blue fluorescence. Moreover, the sensor has relatively high selectivity and sensitivity for Cu2+ and B4O72- ions, and the detection limits are 1.02 × 10-7 and 2.06 × 10-7 M, respectively. In addition, the good biocompatibility and excellent water solubility of the sensor H2L make it very advantageous in practical applications, using H2L powder for fingerprint visualization, using H2L to identify the phenomenon of B4O72- ions emitting bright blue fluorescence, making it an ink that can print encrypted messages on A4 paper, in addition to this, based on H2L, the real water sample was tested for Cu2+ ion recognition, and finally the test strip experiment was carried out.

Simple microfluidic devices for in situ detection of water contamination: a state-of-art review.

Water security is an important global issue that is pivotal in the pursuit of sustainable resources for future generations. It is a multifaceted concept that combines water availability with the quality of the water's chemical, biological, and physical characteristics to ensure its suitability and safety. Water quality is a focal aspect of water security. Quality index data are determined and provided via laboratory testing using expensive instrumentation with high maintenance costs and expertise. Due to increased practices in this sector that can compromise water quality, innovative technologies such as microfluidics are necessary to accelerate the timeline of test procedures. Microfluidic technology demonstrates sophisticated functionality in various applications due to the chip's miniaturization system that can control the movement of fluids in tiny amounts and be used for onsite testing when integrated with smart applications. This review aims to highlight the basics of microfluidic technology starting from the component system to the properties of the chip's fabricated materials. The published research on developing microfluidic sensor devices for monitoring chemical and biological contaminants in water is summarized to understand the obstacles and challenges and explore future opportunities for advancement in water quality monitoring.

Evaluation of groundwater quality by adopting a multivariate statistical approach and indexing of water quality in Sagar Island, West Bengal, India.

In the vicinity of the coast, predominantly groundwater is the sole reliable resource for potable purposes as the surface water sources are highly saline and unfit for human consumption. However, the groundwater in Sagar Island is highly vulnerable to saltwater intrusion. The majority of drinking water comes from government-owned hand pump-equipped tube wells. But during the summer season, many of these tube wells yield significantly less water. Hence, in the current scenario, water quality assessment has become important to the quantity available. Total of 31 samples of deep tube wells (groundwater) are collected at variegated locations during pre-monsoon season throughout Sagar, and then, the physical and chemical quality parameters of these water samples are analysed. Furthermore, a multivariate statistical technique is executed with the aid of the SPSS program. The hydro-chemical parameters that are taken into account for the quality analysis are pH, salinity, electrical conductivity (EC), total dissolved solids (TDS), total hardness, aluminium, arsenic, bi-carbonate, cadmium, iron, chloride, copper, chromium, cobalt, lead, magnesium, manganese, nickel, potassium, sulphate, zinc, and sodium. Then, the analysed data evaluates the water quality index (WQI). Five components are identified through the principal component analysis (PCA) technique, and 82.642% total variance is found. The outcomes of the quality assessment study illustrate that about 54.84% of collected samples come in the "excellent" water quality class when calculated by the "weighted arithmetic WQI method," and 90.32% of collected groundwater samples come in the "good" water quality class when computed using the "modified weighted arithmetic WQI method." This study helps for the interpretation of WQI to assess groundwater quality.

Internet of Things and citizen science as alternative water quality monitoring approaches and the importance of effective water quality communication.

The increasing demand for water and worsening climate change place significant pressure on this vital resource, making its preservation a global priority. Water quality monitoring programs are essential for effectively managing this resource. Current programs rely on traditional monitoring approaches, leading to limitations such as low spatiotemporal resolution and high operational costs. Despite the adoption of novel monitoring approaches that enable better data resolution, the public's comprehension of water quality matters remains low, primarily due to communication process deficiencies. This study explores the advantages and challenges of using Internet of Things (IoT) and citizen science as alternative monitoring approaches, emphasizing the need for enhancing public communication of water quality data. Through a systematic review of studies implemented on-field, we identify and propose strategies to address five key challenges that IoT and citizen science monitoring approaches must overcome to mature into robust sources of water quality information. Additionally, we highlight three fundamental problems affecting the water quality communication process and outline strategies to convey this topic effectively to the public.