Environmental Water Quality Monitoring Research Articles

A facile fabricated electrochemical sensor based on dual-shell Sn4CoO9.3 microspheres for simultaneous detection of Pb2+ and Hg2+

The presence of heavy metal ions poses significant health hazards to humans, necessitating an urgent demand for a rapid and efficient detection method. Electrochemical sensing offers a promising approach that enables high sensitivity and selectivity in detecting heavy metal ions. In this study, a novel bimetallic oxide, Sn4CoO9.3, with dual shells and multiple pores was developed by a simple template-free method. The unique dual-shell structure and multiple pores greatly enhance its adsorption capacity for heavy metal ions, while the mesoporous pores facilitate electrolyte and ion diffusion. A sensor based on Sn4CoO9.3/CS-ERGO with the excellent electroactive properties and outstanding absorption capacity was fabricated for the simultaneous detection of different heavy metal ions (Pb2+ and Hg2+). By harnessing the benefits of Sn4CoO9.3 and graphene sheets, the sensors that were created exhibited exceptional sensitivity, stability, and minimal interference when detecting Pb2+ and Hg2+ in real samples. These results suggest promising prospects for utilizing the sensor in environmental water quality monitoring applications.

A Ratiometric Fluorescent Detection Platform Using G‐CDs@[Ru(bpy)3]2+ for the Specific Detection of Hypochlorite and Live Cell Imaging

AbstractHypochlorite (ClO−), an essential reactive oxygen species (ROS) in physiological processes, is identified to be closely connected with oxidative stress and related diseases. Meanwhile, ClO− is a commonly‐used disinfector for water treatment, and in public places, under acidic conditions, it's easily decomposed into hypertoxic chlorine gas. Since the strong oxidizing property of ClO−, many oxidizing agents may disturb the ClO− detection. Specific and accurate detection of ClO− with superior sensitivity is a challenge. In this work, a sensing platform for rapid, sensitive, and specific ClO− detection is constructed using green fluorescent carbon dots (G‐CDs), with a linear detection range of 0.5–11 µm and a detection limit of 0.233 µm. Moreover, introducing a red fluorescent tripyridinium ruthenium ([Ru(bpy)3]2+) as a reference, a ratiometric fluorescence nanoprobe G‐CDs@[Ru(bpy)3]2+ is prepared and shows favorable intracellular imaging of exogenous and endogenous ClO−. With G‐CDs@[Ru(bpy)3]2+‐based test paper microarrays and a color recognition APP, a smartphone‐based sensing system for point‐of‐care testing of ClO− is also fabricated. In summary, this work proposed a versatile and economical smartphone‐based sensing system that featured reliability and simplicity, and suggested its potential applications in environmental water quality monitoring and live cell imaging.

At-Home, Cell-Free Synthetic Biology Education Modules for Transcriptional Regulation and Environmental Water Quality Monitoring.

As the field of synthetic biology expands, the need to grow and train science, technology, engineering, and math (STEM) practitioners is essential. However, the lack of access to hands-on demonstrations has led to inequalities of opportunity and practice. In addition, there is a gap in providing content that enables students to make their own bioengineered systems. To address these challenges, we develop four shelf-stable cell-free biosensing educational modules that work by simply adding water and DNA to freeze-dried crude extracts of non-pathogenic Escherichia coli. We introduce activities and supporting curricula to teach the structure and function of the lac operon, dose-responsive behavior, considerations for biosensor outputs, and a "build-your-own" activity for monitoring environmental contaminants in water. We piloted these modules with K-12 teachers and 130 high-school students in their classrooms─and at home─without professional laboratory equipment. This work promises to catalyze access to interactive synthetic biology education opportunities.

Study of the Hydrosystem and Environmental Monitoring of Water Quality of the Ponds and Water Sources in the National Dendrological Park "Sofiyivka" of the NAS of Ukraine

Study of the Hydrosystem and Environmental Monitoring of Water Quality of the Ponds and Water Sources in the National Dendrological Park "Sofiyivka" of the NAS of Ukraine

Calibration-free pH long-time measurement method based on electrode potential drift dynamic compensation-applying self-adaptive dynamic optimization exponential smoothing method

The long-term in-situ accurate measurement of pH value is an urgent need for environmental water quality monitoring without calibration of pH electrodes. The nonlinearity and potential drift of pH electrode is the main problem which restricts long-term continuous monitoring. The characteristic rules including electrode potential, zero value, electrode slope coefficient, and electrode potential drift for pH electrode are analyzed in detail under the condition of long-term continuous use. The exponential smoothing potential drift prediction model with self-adaptive dynamic optimization smoothing order and smoothing coefficient is established. Combining electrode potential drift threshold judgment and Nernst equation, calibration-free dynamic calculation mathematical model of pH long-term monitoring is established. Indoor simulation and field test indicate that the measurement absolute error caused by electrode drift is within 0.01 pH and the specified measurement error for pH monitoring instrument is always within 0.1 pH. The proposed method is very suitable for the terminal of pH detector with the advantages of good portability for the MCU chip, small samples, high-precision and fast running speed. Furthermore, the life of pH electrode can be prolonged significantly. It is also proved that the proposed method has a good application prospect.

Analysis and Research on Quality Control Methods of Environmental Water Quality Monitoring

Analysis and Research on Quality Control Methods of Environmental Water Quality Monitoring

Rapid Determination of Mercury Ions in Environmental Water Based on an N-Rich Covalent Organic Framework Potential Sensor

In this article, an N-rich covalent organic framework (COFTFPB-TZT) was successfully synthesized using 4,4′,4′-(1,3,5-triazine-2,4,6-triyl) trianiline (TZT), and 4-[3,5-bis (4-formyl-phenyl) phenyl] benzaldehyde (TFPB). The as-prepared COFTFPB-TZT possesses irregular cotton wool patches with a large specific surface area. A novel selective electrode based on COFTFPB-TZT was used for the determination of Mercury ions. The abundance of N atoms in COFTFPB-TZT provides more coordination sites for Hg2+ adsorption, resulting in a change in the surface membrane potential of the electrode to selectively recognize Hg2+. Under optimal experimental conditions, the ion-selective electrode shows a good potential response to Hg2+, with a linear range of 1.0 × 10−9∼1.0 × 10−4, a Nernst response slope of 30.32 ± 0.2 mV/-PC at 25°C and a detection limit of 4.5 pM. At the same time, the mercury-ion electrode shows a fast response time of 10 s and good reproducibility and stability. The selectivity coefficients for Fe2+, Zn2+, As3+, Cr6+, Cu2+, Cr3+, Al3+, Pb2+, NH4+, Ag+, Ba2+, Mg2+, Na+, and K+ are found to be small, indicating no interference in the detection system. The proposed method can be successfully applied to the determination of Hg2+ in 3 typical environmental water samples, with a recovery rate of 98.6–101.8%. In comparison with the spectrophotometric method utilizing dithizone, the proposed method is simple and fast and holds great potential application prospects in environmental water quality monitoring and other fields.

Improved Spatial Outlier Detection Method within a River Network

A spatial outlier refers to the observation whose non-spatial attribute values are significantly different from those of its neighbors. Such observations can also be found in water quality data at monitoring stations within a river network. However, existing spatial outlier detection procedures based on distance measures such as the Euclidean distance between monitoring stations do not take into account the river network topology. In general, water quality levels in lower streams will be affected by the flow from the upper streams. Similarly, the water quality at some tributaries may have little influence on the other tributaries. Hence, a method for identifying spatial outliers in a river network, taking into account the effect of river flow connectivity on the determination of the neighbors of the monitoring stations, is proposed. While the robust Mahalalobis distance is used in both methods, the proposed method uses river distance instead of the Euclidean distance. The performance of the proposed method is shown to be superior using a synthetic river dataset through simulation. For illustration, we apply the proposed method on the water quality data from Sg. Klang Basin in 2016 provided by the Department of Environment, Malaysia. The finding provides a better identification of the water quality in some stations that significantly differ from their neighbouring stations. Such information is useful for the authorities in their planning of the environmental monitoring of water quality in the areas.

Rapid Detection of Three Common Bacteria Based on Fluorescence Spectroscopy.

As an important part of environmental water quality monitoring, efficient bacterial detection has attracted widespread attention. Among them, LIF (laser-induced fluorescence) technology has the characteristics of high efficiency and sensitivity for bacterial detection. To simplify the experimental process of bacterial detection, fluorescence emission spectra of E. coli (Escherichia coli) and its deactivated controls, K. pneumoniae (Klebsiella pneumoniae) and S. aureus (Staphylococcus aureus), were analyzed with fluorescence excitation by a 266 nm laser. By analyzing the results, it was found that the dominant fluorescence peaks of bacterial solutions at 335~350 nm were contributed by tryptophan, and the subfluorescence peaks at 515.9 nm were contributed by flavin; besides, K. pneumoniae and S. aureus had their own fluoresces characteristics, such as tyrosine contributing to sub-fluorescence peaks at 300 nm. The three species of bacteria can be differentiated with whole fluorescence spectrum by statistically analysis (p < 0.05), for various concentrations of aromatic amino acids and flavin in different bacteria. The experimental results also proved that the inactivation operation did not alter the spectral properties of E. coli. The indexes of fluorescence intensity and FIR (fluorescence intensity ratio, I335~350/I515.9) can be used to retrieve the bacteria concentration as well as for bacteria differentiation using the index of slopes. The detection limit of bacteria is less than ~105 cell/mL using laser induced fluorescence methods in the paper. The study demonstrated the rapid detection capability of the LIF bacterial detection system and its great potential for rapid quantitative analysis of bacteria. This may bring new insight into the detection of common bacteria in water in situ.

Statistical tools for water quality assessment and monitoring in river ecosystems – a scoping review and recommendations for data analysis

Abstract Robust scientific inference is crucial to ensure evidence-based decision making. Accordingly, the selection of appropriate statistical tools and experimental designs is integral to achieve accuracy from data analytical processes. Environmental monitoring of water quality has become increasingly common and widespread as a result of technological advances, leading to an abundance of datasets. We conducted a scoping review of the water quality literature and found that correlation and linear regression are by far the most used statistical tools. However, the accuracy of inferences drawn from ordinary least squares (OLS) techniques depends on a set of assumptions, most prominently: (a) independence among observations, (b) normally distributed errors, (c) equal variances of errors, and (d) balanced designs. Environmental data, however, are often faced with temporal and spatial dependencies, and unbalanced designs, thus making OLS techniques not suitable to provide valid statistical inferences. Generalized least squares (GLS), linear mixed-effect models (LMMs), and generalized linear mixed-effect models (GLMMs), as well as Bayesian data analyses, have been developed to better tackle these problems. Recent progress in the development of statistical software has made these approaches more accessible and user-friendly. We provide a high-level summary and practical guidance for those statistical techniques.

A GIS-MCDA-Based Suitability Analysis for Meeting Targets 6.3 and 6.5 of the Sustainable Development Goals

Among the Sustainable Development Goals (SDGs) established in the 2030 Agenda, goals 6.3, regarding clean water and improve of water quality, and 6.5, regarding integrated water resources management, highlight the need for the implementation of successful environmental water quality monitoring programs of transboundary river waterbodies. In the present study, the designation of high priority areas for water quality monitoring of Drin transboundary watershed is performed using a suitability model, a GIS-based multicriteria decision analysis (GIS-MCDA) approach that takes into consideration the most important conditioning factors that impose pressures on rivers. Based on the results, the methodological approach used manages to sufficiently delimit the areas with increased need for water quality monitoring in the Drin watershed, and the validation procedure produces a correlation coefficient of 0.454 (statistically significant at a 0.01 level). Limitations arise in the case of a lack of detailed information or inaccurate input data and due to the inconsistency among the input data and the different methodological approaches regarding the information collection of each country involved. These restrictions foreground the need for cooperation between the countries involved regarding the exchange of scientific knowledge and common legislation, so as to achieve integrated, effective, and sustainable management of water resources of the area.

Environmental monitoring of water quality in the interstate Ural river

This article analyzes the content of biological oxygen demand, chemical oxygen demand, heavy metals using the example of the content of copper and zinc and oil products in the Ural River, which is transboundary and runs along Bashkiria, Chelyabinsk and Orenburg regions, as well as in The Republic of Kazakhstan, West Kazakhstan and Atyrau regions. An excess is noted for all indicators. So the content of biological oxygen demand exceeds from 2 to 15 maximum permissible concentration, the content of chemical oxygen demand on the territory of the Russian territory exceeds about 2 maximum permissible concentration. The content of heavy metals copper and zinc ranges from 1.5 to 6.3 maximum permissible concentration, while the highest values are typical for the Kazakhstani territory, which is a consequence of the accumulation received from the Russian territory. The content of petroleum products exceeds for the most part up to 2 maximum permissible concentration and more, only in the territory of the village of Makhambet and the village of Bogdanovskoye is it lower than the maximum permissible concentration.

Simple chemical detection based on a surface-modified electroosmotic pump via interval immobilization.

Environmental water quality monitoring plays an important role in human health risk assessments for pharmaceuticals in water and pollutant source control. A new chemical detection method was developed to enhance molecular selectivity and portability by combining the molecularly imprinted technique and an electroosmotic pump (EOP), which requires only a small pump, batteries and stopwatch in principle. Selective chemical adsorption on the surface-modified EOP decreases the pumping performance of EOP due to a decrease in the surface electric charge. For proof of concept, the microfabricated EOPs with chemical surface treatment were used to investigate the effects of surface chemical change on pumping performance. The microfluidic EOP of a size of 20 mm × 20 mm × 1 mm was modified by an interval immobilization method using the template of 4-(tributylammonium-methyl)-benzyltributylammonium chloride (TBTA) and evaluated by measuring EOF. The pumping performance of the surface-modified EOP was decreased by the selective adsorption of TBTA to a two-point recognition site on the EOP surfaces. The relationships between the flow rate and the TBTA concentration were fitted to the Langmuir equation. The EOP can selectively detect the model substance even in a mixture solution with a different chemical compound. This molecular imprinted EOP does not require large and expensive instruments for driving the device and chemical detection, which can be applied to a portable analytical device for onsite analysis.

An evaluation of apparent color of seawater based on the in-situ and satellite-derived Forel-Ule color scale

Apparent color of seawater is a key variable that can be used to describe the optical properties of seawater and plays a crucial role in understanding surface marine ecosystems and processes. The apparent color of seawater traditionally determined from a hand-held Forel-Ule color comparator scale can now be derived from satellite ocean color end-product water leaving radiance or remote sensing reflectance. However, this retrieval algorithm has not been verified in China's offshore waters, which are some of the most turbid waters in the world. Thus, the precision of the satellite-derived Forel-Ule index (FUIsatellite) is unknown in this area. In this paper, FUIsatellite values is evaluated using in-situ FUI (FUIinsitu) observations obtained in the first large-scale systematic survey on the marine environment in China, and the results show that there is a generally good agreement (r = 0.75, N = 2390, p = 0.00, MAD = 2.61, MUPD = 35.02%) between them. Uncertainties of satellite derivation along the coast of the East China Sea (ECS) and the Beibu Gulf are identified. Moreover, the probability of uncertainties of FUIsatellite as a function of FUIinsitu can be well fitted by Gaussian function (r2 = 0.99). Our study also demonstrates that the radial basis function, which uses linear function as the basis function, is the optimal method on the spatial interpolation of FUIinsitu. The FUIsatellite is still in good agreement with the interpolated FUIinsitu field (r = 0.77, N = 265302, p = 0.00, MAD = 1.73, MUPD = 36.06%), which reveals that remote sensing techniques could be an integral tool for operational environmental monitoring of water quality in China's offshore waters.

Thermal Design of Microreactor Structural Elements for Water Quality Analyser

The research object is a Lab-chip device for environmental water quality monitoring. The main objective of the actual work is to determine a set of functional, geometric and technological parameters of Lab-chip microreactor to provide optimal temperature field conditions for predefined chemical reaction protocols. Since Lab-chip operates with a microdose of liquids or reagents and temperature processes in fluid flows are highly inertial, the problem of setting, maintaining and ensuring fast transient of certain temperature values in different areas of Lab-chip microchannels is nontrivial. The main focus was pointed on precise heating of defined Lab-chip areas (reaction chambers) and strict compliance with the non-stationary thermal regime, required for chemical reaction protocols. Modelling and simulation were done in COMSOL Multiphysics tool. As a result of the conducted research, there was obtained a set of parameters that provides the required thermal regime of reaction microchamber for the physicochemical determination of selected hazardous species in environmental water samples.

Making the Most of Ecological Data from the LTER Site: Manager’s Point of View

Climate change is affecting the ecosystems and the services they provide for human well-being. For a better understanding of the causes and effects of this change in the functioning of ecosystems, detailed information of environmental parameters needs to be considered. Researchers generate multiple databases in their academic disciplines but often this data collection is not openly available nor does it fulfill the FAIR principles of Findability, Accessibility, Interoperability, and Reusability (Wilkinson et al. 2016). In this regard, Long-Term Ecosystem Research (LTER) plays an important role as an open research infrastructure that helps to integrate in-situ data, remote sensing products and modelling efforts, related to biodiversity and geodiversity. Within LTER networks, the Dynamic Ecological Information Management System – Site and Dataset Registry (DEIMS-SDR), is used as the central site catalogue to provide information about facilities, ecosystems and environmental parameters in an openly available and standardized way (Wohner et al. 2019), organized by each location’s site. These LTER sites from all around the globe, receive a special protection status due to their ecological value, which through research and observation, enhances the protection and conservation of these areas. The LTER Ria de Aveiro site in Portugal (DEIMS.ID; LTER website), classified under the Natura 2000 network, is of paramount importance for the regional and national economy, agriculture, commercial fisheries, aquaculture, manufacturing, tourism, sports and recreational activities (e.g. Lillebø et al. 2019). Since the establishment of the LTER Ria de Aveiro site in 2011, its research has focused on the contribution to the effective implementation of the Water Framework Directive and European Union Biodiversity Strategy targets. Studies have been developed to target key policies within Natura 2000 areas, Action 5 including habitat mapping and assessment of ecosystems and their services, data collection of important fauna groups, and engagement of stakeholders and common frameworks for the conservation of biodiversity. Currently, the site is part of the Portuguese e-Infrastructure for Information and Research on Biodiversity (PORBIOTA), being aligned with the European Research Infrastructure Consortium (LifeWatch-ERIC). The LTER site team infrastructure includes laboratory facilities for field observation and environmental monitoring of water quality and environmental parameters that are used to feed models. A recently obtained Unmanned Aerial Vehicle (UAV), commonly known as drone, will contribute to ecological observations, generating data to provide biodiversity monitoring in space and time. As LTER site managers and data providers, we have to deal with how to make the transition from our metadata to FAIR ecological data. Our aim is to deal with the implementation of standardized data profiles in our own data. For instance, to upload data files to the central repositories (e.g. DEIMS-SDR), to store and publish our raw data (e.g. B2Share), to create online distribution links and digital object identifiers (DOIs), and to use a convenient vocabulary (e.g. Environmental Thesaurus) to be understandable by everyone (Pérez-Luque et al. 2019). This substantially will increase the potential of databases in the scientific community, and will contribute to a successful building of LTER.

Future water quality monitoring: improving the balance between exposure and toxicity assessments of real-world pollutant mixtures

Environmental water quality monitoring aims to provide the data required for safeguarding the environment against adverse biological effects from multiple chemical contamination arising from anthropogenic diffuse emissions and point sources. Here, we integrate the experience of the international EU-funded project SOLUTIONS to shift the focus of water monitoring from a few legacy chemicals to complex chemical mixtures, and to identify relevant drivers of toxic effects. Monitoring serves a range of purposes, from control of chemical and ecological status compliance to safeguarding specific water uses, such as drinking water abstraction. Various water sampling techniques, chemical target, suspect and non-target analyses as well as an array of in vitro, in vivo and in situ bioanalytical methods were advanced to improve monitoring of water contamination. Major improvements for broader applicability include tailored sampling techniques, screening and identification techniques for a broader and more diverse set of chemicals, higher detection sensitivity, standardized protocols for chemical, toxicological, and ecological assessments combined with systematic evidence evaluation techniques. No single method or combination of methods is able to meet all divergent monitoring purposes. Current monitoring approaches tend to emphasize either targeted exposure or effect detection. Here, we argue that, irrespective of the specific purpose, assessment of monitoring results would benefit substantially from obtaining and linking information on the occurrence of both chemicals and potentially adverse biological effects. In this paper, we specify the information required to: (1) identify relevant contaminants, (2) assess the impact of contamination in aquatic ecosystems, or (3) quantify cause–effect relationships between contaminants and adverse effects. Specific strategies to link chemical and bioanalytical information are outlined for each of these distinct goals. These strategies have been developed and explored using case studies in the Danube and Rhine river basins as well as for rivers of the Iberian Peninsula. Current water quality assessment suffers from biases resulting from differences in approaches and associated uncertainty analyses. While exposure approaches tend to ignore data gaps (i.e., missing contaminants), effect-based approaches penalize data gaps with increased uncertainty factors. This integrated work suggests systematic ways to deal with mixture exposures and combined effects in a more balanced way, and thus provides guidance for future tailored environmental monitoring.

Developing an environmental water quality monitoring program for Haraz River in Northern Iran.

Water quality management plans are an indispensable strategy for conservation and utilization of water resources in a sustainable manner. One common industrial use of water is aquaculture. The present study is an attempt to use statistical analyses in order to prepare an environmental water quality monitoring program for Haraz River, in Northern Iran. For this purpose, the analysis of a total number of 18 physicochemical parameters was performed at 15 stations during a 1-year sampling period. According to the results of the multivariate statistical methods, the optimal monitoring would be possible by only 3 stations and 12 parameters, including NH3, EC, BOD, TSS, DO, PO4, NO3, TDS, temperature, turbidity, coliform, and discharge. In other words, newly designed network, with a total number of 36 measurements (3 stations×12 parameters=36 parameters), could achieve exactly the same performance as the former network, designed based on 234 measurements (13 stations×18 parameters=234 parameters). Based on the results of cluster, principal component, and factor analyses, the stations were divided into three groups of high pollution (HP), medium pollution (MP), and low pollution (LP). By clustering the stations, it would be possible to track the water quality of Haraz River, only by one station at each cluster, which facilitates rapid assessment of the water quality in the river basin. Emphasizing on three main axes of monitoring program, including measurement parameters, sampling frequency, and spatial pattern of sampling points, the water quality monitoring program was optimized for the river basin based on natural conditions of the study area, monitoring objectives, and required financial resources (a total annual cost of about US $2625, excluding the overhead costs).

A Miniature Water Surface Jumping Robot

Many small insects such as water striders can leap from water surface. Inspired by their jumping capability, we present the design of a novel, miniature, water surface jumping robot in this paper. Jumping from water surface is more challenging than jumping from ground due to the liquid water surface. We address this problem by using carbon fiber strip to store energy, two wings to flap the water surface, a hollow body to initially support the robot, and an intermittent gear train to charge and release energy. With such a design, the final robot weighs around 12.5 g and has a maximum size of 10 cm. Experimental results show that the robot can jump up to 9.5 cm in height, which is close to the predicted results from a dynamic model developed by us to capture the hydrodynamic behaviors of the robot during the whole jumping process. The research presented in this paper offers a new design of tiny robots for mimicking the water-jumping capability of aquatic insects. The robot, if equipped with sensors, can be employed for aquatic environmental monitoring of water quality.

Assessment of the effects of Cu and Ag in oysters Crassostrea gigas (Thunberg, 1793) using a battery of cell and tissue level biomarkers

Oysters are considered sentinel organisms in environmental water quality monitoring programs in which cell and tissue level biomarkers are reliable tools. Copper (Cu) and silver (Ag) are present in relatively high concentrations in several estuaries, potentially affecting environmental and human health. Crassostrea gigas oysters were exposed during 28 days to a range of environmentally relevant concentrations of Cu and Ag alone or in mixture. Effects were studied through cell and tissue level biomarkers approach. Results indicated: changes in the Condition Index (CI), altered digestive gland epithelium and presence of histopathological alterations in the gonad and digestive gland of exposed oysters. A time-dependent increase in lipofuscin contents in exposed oysters and an increase in intralysosomal metal accumulation in digestive cells through the experiment were also recorded. The Integrative Biological Response (IBR) Index showed that even at low exposure levels, Ag and Cu can produce alterations on oysters' health status.