Multi-way modeling of hydro-chemical data of an alluvial river system--a case study

A large data set pertaining to water quality of an alluvial river was analyzed using multi-way data analysis methods with a view to extract the hidden information, spatial and temporal variation trends in the river water quality. Four-way data (8 monitoring sites × 22 water quality variables × 10 monitoring years × 12 sampling months) analysis was performed using PARAFAC and Tucker3 models. A two component PARAFAC model, although explained 35.1% of the data variance, could not fit to the data set. Tucker3 model of optimum complexity (2,3,1,3) explaining 39.7% of the data variance, allowed interpretation of the data information in four modes. The model explained spatial and temporal variation trends in terms of water quality variables during the study period and revealed that sampling sites in mid-stretch of the river were dominated mainly by the variables of anthropogenic origin. The results delineated the mid stretch of the river as critical from pollution point of view and also identified summer months as having high influence on river water quality in this stretch. The information regarding spatial and temporal variations in water quality generated by the four-way modeling of data would be useful in developing long-term water resources management strategies in the river basin.     

A comparison of partial order technique with three methods of multi-criteria analysis for ranking of chemical substances

An alternative to the often cumbersome and time-consuming risk assessments of chemical substances could be more reliable and advanced priority setting methods. An elaboration of the simple scoring methods is provided by Hasse Diagram Technique (HDT) and/or Multi-Criteria Analysis (MCA). The present study provides an in depth evaluation of HDT relative to three MCA techniques. The new and main methodological step in the comparison is the use of probability concepts based on mathematical tools such as linear extensions of partially ordered sets and Monte Carlo simulations. A data set consisting of 12 High Production Volume Chemicals (HPVCs) is used for illustration. It is a paradigm in this investigation to claim that the need of external input (often subjective weightings of criteria) should be minimized and that the transparency should be maximized in any multicriteria prioritisation. The study illustrates that the Hasse diagram technique (HDT) needs least external input, is most transparent and is least subjective. However, HDT has some weaknesses if there are criteria which exclude each other. Then weighting is needed. Multi-Criteria Analysis (i.e. Utility Function approach, PROMETHEE and concordance analysis) can deal with such mutual exclusions because their formalisms to quantify preferences allow participation e.g. weighting of criteria. Consequently MCA include more subjectivity and loose transparency. The recommendation which arises from this study is that the first step in decision making is to run HDT and as the second step possibly is to run one of the MCA algorithms.     

A zebrafish scale assay to monitor dioxin-like activity in surface water samples

New regulations on water quality require a close control of the possible biological activities known or unexpected pollutants may bring about. We present here a protocol based on the direct exposure of zebrafish to river water and the analysis of expression of specific genes in their scales to determine the presence of compounds with dioxin-like biological activity. The method does not require the killing of animals and allows detection of the biological activity after a single day of exposure. When tested, the method with real samples from the Llobregat River, clear temporal and spatial variations were observed, demonstrating its suitability for monitoring natural variations in water quality linked to specific discharges. High biological activities were unrelated to the currently checked water quality parameters (macropollutants, turbidity, TOC, etc.), but they did correlate with the presence of micropollutants (estrogens, detergents, etc.) related to domestic and/or industrial runoffs. The scale assay therefore provides a new tool to evaluate water quality changes that cannot be easily derived from the existing standard analytical procedures. It ranks among the very few described protocols able to detect biological effects from natural water samples, without a pre-concentration step, and after only 24 h of exposure.     

Estimating sampling and analysis uncertainties to assess the fitness for purpose of a water quality monitoring network

In order to verify that the protocols used for water quality monitoring of surface waters within the Long-term Environmental Research Monitoring and Testing System (OPE), located in the north-eastern part of France in relation with a geological disposal for radioactive waste project, are fit for purpose, a validation study was conducted following the methodology described in the Eurachem/citac and Nordtest guidance documents on uncertainty arising from sampling. As one of the objectives of the OPE water monitoring programme was to investigate the spatial and temporal variability of water quality, quality requirements were set to having a measurement variance, including sampling and analytical contributions, less than 20 % of the total variance to minimise the impact of measurement over the observed environmental variability. The replicate method was then selected in order to estimate the measurement uncertainty, including the sampling contribution, as well as the spatial and temporal variability of water quality of surface waters. To minimise costs, a single-split level was selected. Analytical uncertainties were assessed from inter-laboratory data and/or internal quality control data from the last 2–5 years. Finally, ANOVA was applied to the data sets after elimination of outliers. Results showed that for pH, electrical conductivity, turbidity and nitrate, the sampling uncertainty was negligible, whereas for other parameters such as dissolved oxygen, total suspend solids, total organic carbon, nitrite and phosphate, the sampling contribution to the measurement uncertainty was largely significant. For all parameters except calcium, the sampling and analytical protocols were considered fit for purpose.     

Modelling spatial and temporal variations in the water quality of an artificial water reservoir in the semiarid midwest of Argentina

Temporal and spatial patterns of water quality of an important artificial water reservoir located in the semiarid Midwest of Argentina were investigated using chemometric techniques. Surface water samples were collected at 38 points of the water reservoir during eleven sampling campaigns between October 1998 and June 2000, covering the warm wet season and the cold dry season, and analyzed for dissolved oxygen (DO), conductivity, pH, ammonium, nitrate, nitrite, total dissolved solids (TDS), alkalinity, hardness, bicarbonate, chloride, sulfate, calcium, magnesium, fluoride, sodium, potassium, iron, aluminum, silica, phosphate, sulfide, arsenic, chromium, lead, cadmium, chemical oxygen demand (COD), biochemical oxygen demand (BOD), viable aerobic bacteria (VAB) and total coliform bacteria (TC). Concentrations of lead, ammonium, nitrite and coliforms were higher than the maximum allowable limits for drinking water in a large proportion of the water samples. To obtain a general representation of the spatial and temporal trends of the water quality parameters at the reservoir, the three-dimensional dataset (sampling sites×parameters×sampling campaigns) has been analyzed by matrix augmentation principal component analysis (MA-PCA) and N-way principal component analysis (N-PCA) using Tucker3 and PARAFAC (Parallel Factor Analysis) models. MA-PCA produced a component accounting for the general behavior of parameters associated with organic pollution. The Tucker3 models were not appropriate for modelling the water quality dataset. The two-factor PARAFAC model provided the best picture to understand the spatial and temporal variation of the water quality parameters of the reservoir. The first PARAFAC factor contains useful information regarding the relation of organic pollution with seasonality, whereas the second factor also encloses information concerning lead pollution. The most polluted areas in the reservoir and the polluting sources were identified by plotting PARAFAC loadings as a function of the UTM (Universal Transverse Mercator) coordinates.     

Support vector machines in water quality management

Support vector classification (SVC) and regression (SVR) models were constructed and applied to the surface water quality data to optimize the monitoring program. The data set comprised of 1500 water samples representing 10 different sites monitored for 15 years. The objectives of the study were to classify the sampling sites (spatial) and months (temporal) to group the similar ones in terms of water quality with a view to reduce their number; and to develop a suitable SVR model for predicting the biochemical oxygen demand (BOD) of water using a set of variables. The spatial and temporal SVC models rendered grouping of 10 monitoring sites and 12 sampling months into the clusters of 3 each with misclassification rates of 12.39% and 17.61% in training, 17.70% and 26.38% in validation, and 14.86% and 31.41% in test sets, respectively. The SVR model predicted water BOD values in training, validation, and test sets with reasonably high correlation (0.952, 0.909, and 0.907) with the measured values, and low root mean squared errors of 1.53, 1.44, and 1.32, respectively. The values of the performance criteria parameters suggested for the adequacy of the constructed models and their good predictive capabilities. The SVC model achieved a data reduction of 92.5% for redesigning the future monitoring program and the SVR model provided a tool for the prediction of the water BOD using set of a few measurable variables. The performance of the nonlinear models (SVM, KDA, KPLS) was comparable and these performed relatively better than the corresponding linear methods (DA, PLS) of classification and regression modeling.     

Multivariate classification and modeling in surface water pollution estimation

The present study deals with the application of self-organizing maps (SOM) and multiway principal-components analysis to classify, model, and interpret a large monitoring data set for surface water quality. The chemometric methods applied made it possible to reveal specific quality patterns of the chemical and biological parameters used to monitor the water quality (relation between water temperature, turbidity, hardness, colibacteria), seasonal impacts during the long period of observation and the relative independence on the spatial location of the sampling sites (water supply sources for the City of Trieste). Figure The schematic procedure for surface water pollution estimation supported by neural network-based classification and multivariate factor analysis     

Basic principles of Hasse diagram technique in chemistry

Principles of partial order applied to ranking are explained. The Hasse diagram technique (HDT) is the application of partial order theory based on a data matrix. In this paper, HDT is introduced in a stepwise procedure, and some elementary theorems are exemplified. The focus is to show how the multivariate character of a data matrix is realized by HDT and in which cases one should apply other mathematical or statistical methods. Many simple examples illustrate the basic theoretical ideas. Finally, it is shown that HDT is a useful alternative for the evaluation of antifouling agents, which was originally performed by amoeba diagrams.     

Assessment of pollution level in a Himalayan Lake,Kashmir, using geomatics approach

Pollution indices aggregate concentrations of several water quality parameters into a single quantity to indicate the general status of pollution in a region. In this study, a variant of the previous water quality index was used to evaluate the pollution status in the Wular Lake, Kashmir, which is a Ramsar site and wetland of international importance. The index termed as water quality status index (WQSI) is considered as a simple pollution indicator to support management actions in the Wular Lake, Kashmir. WQSI is a valuable and unique rating to depict the overall water quality status and pollution level of the waterbody in a spatial context and is also capable of dealing with those water quality parameters which do not have well-developed standard values. In this study, the water quality of the Wular Lake was investigated in June 2013 for 21 sample locations. The index used in this work is composed of 13 measurable physico-chemical parameters – pH, dissolved oxygen, chemical oxygen demand, biological oxygen demand, alkalinity, hardness, chloride, total dissolved solids, ammonia, iron, nitrite, nitrate and fluoride. The generation of WQSI is based on weighted overlay technique, in which interpolated raster maps were generated for all the 13 water quality parameters and weights are assigned to each and every parameter using analytic hierarchy process technique, considering their status as benefit or cost criteria. Based on the value of WQSI, the whole lake was divided into five zones, comprising least polluted zone (23%), moderately polluted zone (20%), high polluted zone (30%), very high polluted zone (22%) and extremely polluted zone (5%). From this study, it has been found that 60 km² (77%) of total lake area constitutes the moderate to extremely polluted zone and only 18 km² (23%) of the total lake area constitutes the least polluted zone, which is in the north-west region of the lake. The study reveals that the world-famous Wular Lake is undergoing the eutrophication process and as a result of which the lake is losing its water holding capacity to deal with the disastrous flood problem in Kashmir region.     

Printing chemical gradients

We describe a method to exploit the mass-transfer limitations of microcontact printing for the fabrication of surfaces with well-defined, arbitrarily shaped composition variations. An analysis of the transport processes reveals that the printing of hexadecanethiol (HDT) from poly(dimethylsiloxane) is purely diffusion-controlled. Stamps with geometries that enhance surface-normal diffusion paths therefore allow not only the contours, but also the local density of self-assembled monolayers to be controlled. We use stamps with variable thickness and uniform ink concentration to print HDT density gradients on gold, depleting the stamps during the process. In the second step, a perfluorinated thiol fills the vacancies in the partial monolayer to form a two-component gradient that we analyze by means of X-ray photoelectron spectroscopy and spectroscopic ellipsometry. Linear and radial gradients are shown here as examples for a wide range of geometries that can be fabricated with high precision using the method.     

Thermal properties,induction period,interfacial energy and nucleation parameters of solution grown benzophenone

The kinetic parameters (reaction order, n, activation energy, E, pre-exponential factor, A, constant rate, k) for the dehydration step due to elimination of osmotic water and hydrogen-bounded water with the carboxylic groups, and for the anhydrifying step owing to the dehydration of two neighboring (-COOH) groups, were determined under non-isothermal conditions for some carboxylic resins with acrylic-divinylbenzene (DVB) matrix. The kinetic parameters were evaluated by means of isoconversional methods from (TG/DTG) thermal analysis data. The results show a dependence of the apparent kinetic parameters on the cross-linking degree, granulation, gel/macroporous matrix nature, exchange capacity and heating rate.     

Investigation of the therapeutic effect of Hedan tablets on high-fat diet-induced obesity in rats by GC–MS technology and 16S ribosomal RNA gene sequencing

Obesity is a persistent metabolic condition resulting from the excessive accumulation or abnormal distribution of body fat. This study aimed to establish an experimental rat model of obesity. The efficacy of treating obesity with Hedan tablets (HDT) was assessed by monitoring changes in weight, blood lipid levels, analyzing inflammatory factors, evaluating organ indices, and observing liver tissue pathology. Furthermore, we utilized 16S ribosomal RNA gene sequencing technology to explore changes in intestinal flora. In addition, GC–MS was used to measure fecal short-chain fatty acid (SCFA) content. The onset of obesity led to a significant decrease in the relative abundance of beneficial bacteria. Conversely, the administration of HDT demonstrated a substantial ability to increase the relative abundance of beneficial bacteria. Obesity resulted in a noteworthy reduction in total SCFAs, a trend significantly reversed in the HDT group. Through correlation analysis, it was determined that HDT mitigated the inflammatory response and improved blood lipid levels by augmenting the abundance of Lactobacillus, Limosilactobacillus, Ruminococcus, and Enterococcus. These particular intestinal flora were identified as regulators of SCFA metabolism, thereby ameliorating metabolic abnormalities associated with obesity. Moreover, HDT intervention elevated the overall fecal concentration of SCFAs, thereby improving metabolic disorders induced by obesity. The anti-obesity effects of HDT are likely attributable to their capacity to influence the composition of intestinal flora and boost SCFA levels in the intestine.     

Exploring groundwater hydrochemistry of alluvial aquifers using multi-way modeling

A three-way data set pertaining to hydrochemistry of the groundwater of north Indo-Gangetic alluvial plains was analyzed using three-way component analysis method with the purpose of extracting the information on spatial and temporal variation trends in groundwater composition. Three-way data modeling was performed using PARAFAC and Tucker3 models. The models were tested for their stability and goodness of optimal fit using core consistency diagnostic and split-half analysis. Although, a two-component PARAFAC model, explaining 50.47% of data variance, yielded 100% core consistency, it failed to qualify the validation test. Tucker3 model (3, 3, 1) captured 55.18% of the data variance and yielded simple diagonal core with three significant elements, explaining 100% of the core variability. Interpretation of the information obtained through Tucker3 model revealed that the groundwater quality in Khar watershed is mainly dominated by water hardness and related variables, whereas, water composition of the dug wells is dominated by alkalinity and carbonate/bicarbonates. Moreover, shallow groundwater sources in the region are contaminated with nitrate derived from fertilizers application in the region. The shallow aquifers are relatively more contaminated during the post-monsoon season.     

Atomic and ionic fluorescence dip spectroscopy as a tool for flame and plasma diagnostics

When two pulsed dye lasers are tuned in spatial and temporal coincidence to two connected atomic transitions in a flame or plasma, the resonance fluorescence monitored from the first excited level decreases due to the depletion of the population of that level induced by the second laser excitation step. The monitoring of such a decrease (fluorescence dip) can be shown from simple theoretical considerations to be useful for diagnostic studies and for the evaluation of some fundamental parameters of the atomic transition involved in the second-excitation step. Both steady state and transient behaviour are discussed. The information content of the fluorescence dip is similar to that of the saturated fluorescence signal. However, several distinct advantages are offered by the new technique especially when the level reached by the second excitation step is close to the ionization limit of the atom.     

Determination of the design space of the HPLC analysis of water‐soluble vitamins

Analysis of water‐soluble vitamins has been tremendously approached through the last decades. A multitude of HPLC methods have been reported with a variety of advantages/shortcomings, yet, the design space of HPLC analysis of these vitamins was not defined in any of these reports. As per the food and drug administration (FDA), implementing the quality by design approach for the analysis of commercially available mixtures is hypothesized to enhance the pharmaceutical industry via facilitating the process of analytical method development and approval. This work illustrates a multifactorial optimization of three measured plus seven calculated influential HPLC parameters on the analysis of a mixture containing seven common water‐soluble vitamins (B₁, B₂, B₆, B_12, C, PABA, and PP). These three measured parameters are gradient time, temperature, and ternary eluent composition (B1/B2) and the seven calculated parameters are flow rate, column length, column internal diameter, dwell volume, extracolumn volume, %B (start), and %B (end). The design is based on 12 experiments in which, examining of the multifactorial effects of these 3 + 7 parameters on the critical resolution and selectivity, was carried out by systematical variation of all these parameters simultaneously. The 12 basic runs were based on two different gradient time each at two different temperatures, repeated at three different ternary eluent compositions (methanol or acetonitrile or a mixture of both). Multidimensional robust regions of high critical R_s were defined and graphically verified. The optimum method was selected based on the best resolution separation in the shortest run time for a synthetic mixture, followed by application on two pharmaceutical preparations available in the market. The predicted retention times of all peaks were found to be in good match with the virtual ones. In conclusion, the presented report offers an accurate determination of the design space for critical resolution in the analysis of water‐soluble vitamins by HPLC, which would help the regulatory authorities to judge the validity of presented analytical methods for approval.     

Ultra-trace nutritional and toxicological elements in Rome and Florence drinking waters determined by Instrumental Neutron Activation Analysis

In order to ascertain water quality for human consumption, the evaluation of trace and ultra-trace elements in drinking waters of two Italian cities, Rome and Florence, is investigated together with the potabilization processes involved and the relative human exposure to the contaminants. Through a multi-elemental detection with no chemical treatment using Instrumental Neutron Activation Analysis and Proton-Induced X-ray Emission the concentration of 40 elements is determined. Basically, the concentrations of the investigated parameters in drinking waters were within the permissible limits of the World Health Organization drinking water quality guidelines and the Water Pollution Control legislation of Italian authorities. The Rome drinking water shows a chemical water composition quite similar to uncontaminated natural water: potentially toxic elements (e.g., Cr, Hg, Ni, and Sb) are present at very low concentrations whereas the levels of nutritionally essential elements are adequate and low levels of I and Se cannot be considered a cause of deficiency diseases. A multivariate statistical approach was used to identify both the origins and correlations among elements and the six different apportionments contributing to the water supply in Rome. For the drinking waters distributed in Florence, the element levels show a sufficiently good situation, except for Al (range 103–267 μg/L) that is present at reasonable concentrations for almost the entire population due to the hard potabilization procedure involving aluminum salts. The values of Metal Index (MI), that helps to quickly evaluate the overall quality of drinking waters, show a good drinking water quality in Rome (Fe is the only element to be considered critical) whereas in Florence the situation is influenced by Al levels. No relevant differences are found among Rome and Florence water composition and other Italian and world potable waters.This study can be considered a useful reference for studies aimed to highlighting toxicological, nutritional and environmental disease patterns.     

Size-controlled electrochemical growth of PbS nanostructures into electrochemically patterned self-assembled monolayers

1-Hexadecanethiol self-assembled monolayers (HDT SAMs) on Au(111) were used as a molecular resist to fabricate nanosized patterns by electrochemical reductive partial desorption for subsequent electrodeposition of PbS from the same solution simultaneously. The influences of potential steps of variable pulse width and amplitude on the size and the number of patterns were investigated. The kinetics of pattern formation by reductive desorption appears to be instantaneous according to chronoamperometric and morphological investigations. PbS structures were deposited electrochemically into the patterns on HDT SAMs by a combined electrochemical technique, based on the codeposition from the same saturated PbS solution at the underpotential deposition of Pb and S. Scanning tunneling microscopy measurements showed that all of the PbS deposits were disk shaped and uniformly distributed on Au(111) surfaces. Preliminary results indicated that the diameter and the density of PbS deposits can be controlled by controlling the pulse width and amplitude of potential applied at the reductive removal stage of HDT SAMs and the deposition time during the electrochemical deposition step.     

Chemometric analysis of the water purification process data

The aim of this work was to show usefulness of chemometric analysis in processing of the data describing production of drinking water in the Silesian region of Poland. Water samples have been collected within the period of 1 year and the quality of water was characterized by a number of physical, chemical and microbiological parameters. Principal component analysis (PCA) and STATIS (Structuration des Tableaux A Trois Indices de la Statistique) were employed to obtain the knowledge about the complete water treatment process. PCA makes it possible to uncover seasonal changes influencing the water treatment process. In particular, it was found out that the salt content, hardness and conductivity of water tend to obtain higher levels in winter rather than in summer, and the relatively lower acidity is also to be expected in winter. The sensory quality of water is considerably improved over the consecutive purification steps. Complementary information about the individual technological units of the process is gained with the STATIS approach. The obtained results show that the water produced by the two independent filtering branches of the water plant is of similar quality and the prescribed quality characteristics of drinking water are fulfilled.     

Applications of flow injection analysis in a power plant determination of pH,ammonia and hydrazine in an AVT-conditioned water steam cycle

The quality of information concerning management of systems and subsystems of industrial processes is greatly affected by the analytical techniques uses. Flow-injection methods are described for monitoring pH (in the range 4.5–95), ammonia (0.25–2 mg l^?1 N) and hydrazine (50?300 μg l^?1 N) in a water/steam cycle, based on the use of potentiometric sensors. The procedures are discussed in terms of both applicability to very dilute solutions (with simple management of the sytem) and measurability. The parameters considered were precision, analysis frequency and application range. The application range and analysis frequency were good for hydrazine but only the application range was good fro pH and ammonia. Data evaluation by means of a “measurability” model gave acceptable results for ammonia and hydrazine, but not for pH measurements. The frequency of analysis is the main factor affecting the quality of the results.