In desalination plants, disinfection is necessary to control biofouling, one of the main problems in the long-term performance of reverse osmosis membranes. The addition of both chlorine and the dechlorination reagents affects oxidation and reduction potential (ORP). The present investigation evaluates the evolution with time between bisulfite dose and ORP values, to assess the impact of chlorine dioxide, chlorite, chlorate and dissolved metals in the redox potential. Results showed that using chlorine dioxide as an oxidant (1 mg/L), it was needed at least 45.8 mg/L of bisulfite to reduce ORP values below 300 mV. In the presence of chlorite ion (0.65 mg/L) and adding 100 mu g/L of different dissolved metals, the redox potential values did not increase higher than 300 mV except for cobalt (Co2+); at 3 mg/L of chlorite, it was needed at least 46.9 mg/L of bisulfite to reduce the ORP below 300 mV. The influence of bisulfite without chlorination species in brackish water, but with dissolved metals showed redox values always below 300 mV, except for 15 mg/L of bisulfite with 250 and 500 mu g/L of dissolved Co2+. Overall, the presence of chlorine dioxide, chlorite and dissolved metals, particularly Co2+, has a strong influence on the behavior of the redox potential after the addition of bisulfite.

Hexavalent chromium (Cr6+) is of particular environmental concern due to its toxicity and mobility and removing it from industrial wastewater is a challenging task. The present investigation deals with the removal of Cr6+ (similar to 150 ppb) of tunneling wastewater, which has a very basic pH (11-12). For this purpose, batch experiments with wastewater samples were conducted to determine whether sub-ppb concentrations of dissolved Cr6+ could be achieved by chemical (using ferrous sulfate) or electrochemical reduction (iron electrodes). Cr6+ is chemically reduced to less soluble Cr3+ species by Fe2+. The influence of pH, temperature, suspended solids, concentration of ferrous sulfate, current density and reaction time were evaluated in the removal of Cr6+. Further, predictive equations were developed within the studied ranges. The results showed that ferrous sulfate is a good reducing agent of Cr6+ at very basic conditions and at short reaction times. Optimal conditions were at pH = 12 degrees C and 22 degrees C, with the presence of suspended solids and at molar ratios 15: 1 (Fe2+/Cr6+); 97.8% of Cr6+ was removed under these conditions. On the other hand, electrocoagulation was better at reducing Cr6+ at lower pH; 99.3% of Cr6+ was removed at pH = 8, 0.5 mA cm(-2), and 8 min of reaction time. At very basic conditions, the removal of Cr6+ could be achieved by means of higher current density values. Overall, the removal of Cr6+ with ferrous sulfate was more efficient at higher pH and at reaction times lower than 5 min, while electrocoagulation showed enhanced removal at neutral pH and at longer reaction times.

Hybrid forward osmosis (FO) processes such as forward osmosis with membrane bioreactors (FO-MBR), electrodialysis (FO-ED), nanofiltration (FO-NF) or reverse osmosis (FO-RO) present promising technologies for wastewater reuse in agriculture as they meet high effluent quality requirements, especially regarding boron and/or salt content. An FO-NF demonstration plant for this application was built and operated treating 3m(3) h(-1) of real wastewater with a salinity of 3-5 mS cm(-1) and 1.5 mg L-1 of boron in continuous mode for 480 days. Three draw solutions (DS) were evaluated in different periods of experimentation. Sodium polyacrylate led to reversible fouling on the FO and NF membranes and the permeate was not suitable for irrigation. Magnesium sulphate, used as DS in a second phase, generated severe irreversible fouling on NF membranes and therefore it was discarded. Finally, magnesium chloride showed the best performance, with FO-NF membranes presenting a stable permeability and low membrane fouling during long-term operation. The FO-NF permeate showed high quality for irrigation, achieving a conductivity value of 1 mS cm(-1), a boron concentration below 0.4 mg L-1 and an average SAR of 1.98 (mequ L-1)(0.5). DS replacement costs were reduced by working with high rejection NF membranes. However, energy consumption costs associated with the NF step make the global process more energy intensive than conventional technology.

Dissolved air flotation (DAF) technologies are commonly used in water and wastewater treatment.In particular, flotation of suspended solids to pre-treat high salinity water such as seawater is now becoming more widespread, even though conductivity effects on microbubble formation and behaviour are not yet well known.Thus, a series of experiments were conducted with artificial sea water and distilled water to study the effects of conductivity on size and flow patterns of the air bubbles inside a pilotscale DAF tank.The experimental set-up included a high-speed CCD camera to capture the generated microbubbles.Posterior image processing determined the bubble diameters.Also, fluorescein was used as a fluorescent tracer to follow flow paths.The viability of using fluorescein was first assessed at laboratory scale.The intensity of the dye was determined through molecular fluorescence as a function of the concentration using a high conductivity matrix.Furthermore, a stability study of the intensity along time was performed in order to ensure reliability of the experimental measurements.The results showed that bubble size decreased and dead areas increased when seawater was used instead of distilled water.

The aim of this work was the study of degradation of a commercial polyamide membrane by two commonly employed oxidants for disinfection in seawater desalination, hypochlorite, and chlorine dioxide. A conventional reverse osmosis (RO) membrane is a thin film composite membrane composed of three different layers, a polyester support web, a microporous polysulfone interlayer, and a thin cross-linked polyamide barrier layer on the top surface, which is the active layer of the RO membrane. The degree of membrane degradation in seawater was evaluated in terms of decline in membrane performance calculated from permeability and salt rejection. In order to establish a relationship between the hydraulic properties and spectroscopic data, infrared and X-ray photoemission techniques (ATR-FTIR and XPS) were employed. The obtained results were compared with the Fujiwara test which is usually performed in membrane autopsies to check the degradation of polyamides with halogens. The chemical degradation of the surface active layer was analyzed using infrared spectroscopy (ATR-FTIR) by monitoring the changes in the characteristic infrared bands of the polyamide. It is possible to calculate the transmittance bands ratio between peak at 1540 cm(-1) (due to amide II) and peak at 1585 cm(-1) (due to the polysulfone layer) in order to get the comparison of the degraded membranes with a virgin membrane. The amide II band was selected to evaluate the degradation process, because it is the first band that reduces its transmittance value when the degradation process begins. Once the ratio is obtained for the degraded membrane and considering the value obtained from the virgin membrane as the reference point, a new index is calculated named as degradation index. The higher the parameter is, the greater the chemical attacks the polyamide layer. X-ray spectroscopy (XPS) measures the elemental composition and the chemical state of the elements that exist in the surface of a solid. Evaluation of the binding energy is possible to determine if the halogens are attached to the polyamide structure. It was concluded in this work that both spectroscopic techniques ATR-FTIR and XPS could detect the membrane degradation process earlier than Fujiwara test.

DNA can adopt structures in solution apart from the we] I-known Watson-Crick double helix, ranging from disordered single strands to high-order structures such as triplexes or quadruplexes. Moreover, different topologies can be adopted depending on the polarity of the DNA strands. The elucidation of the structure and topology adopted by a DNA sequence is Usually carried out by means of spectroscopic techniques. such as circular dichroism.In this work, the ability of several chemometric methods to efficiently classify DNA structures from circular dichroism data is tested. With this objective in mind, a dataset including 50 experimental spectra corresponding to different DNA structures (random coil, duplex, hairpin, reversed and normal triplex, parallel and antiparallel G-quadruplex, and i-motif) has been analyzed by means of unsupervised hierarchical clustering analysis, principal component analysis and partial least squares discriminant analysis. The results have shown than those methods allow efficiently the classification of DNA structures from circular dichroism spectra. Moreover, these classification methods also provided the most characteristic wavelengths used in the classification procedures. (C) 2009 Elsevier B.V. All rights reserved.

Protein classification and characterization often rely on the information contained in the protein secondary structure. Protein class assignment is usually based on X-ray diffraction measurements, which need the protein in a crystallized form, or on NAIR spectra, to obtain the structure of a protein in solution. Simple spectroscopic techniques, such as circular dichroism (CD) and infrared (IR) spectroscopies, are also known to be related to protein secondary structure, but they have seldom been used for protein classification. To see the potential of CD, IR, and combined CD/IR measurements for protein classification, unsupervised pattern recognition methods, Principal Component Analysis (PCA) and cluster analysis, are proposed first to check for natural grouping tendencies of proteins according to their measured spectra. Partial Least Squares Discriminant Analysis (PLS-DA), a supervised pattern recognition method, is used afterwards to test the possibility to model explicitly each protein class and to test these models in class assignment of unknown proteins. Determination of the protein secondary structure, understood as the prediction of the abundance of the different secondary structure motifs in the biomolecule, was carried out with the local regression method interval Partial Least Squares (iPLS). CD, IR, and CD/IR measurements were correlated to the fraction of the motif to be predicted, determined from X-ray measurements. iPLS builds models extracting the spectral information most correlated to a specific secondary motif and avoids the use of irrelevant spectral regions. Spectral intervals chosen by iPLS models provide structural information which can be used to confirm previous biochemical assignments or identify new motif-related spectral features. The predictive ability of the models built with the selected spectral regions has a quality similar to previous classical approaches.

Mass spectrometry has recently become one of the major analytical tools to study biomolecular structure and function. Ionization techniques, such as electrospray ionization (ESI), desorb biomolecules from solution to the gas phase keeping practically intact their natural structure. ESI applied to a protein solution produces a mixture of multiply charged ions, the ion charge distribution of which depends on the oligomeric form (mass) and on the protein surface exposed (amount of accommodated charges) of the related protein conformation. ESI-MS provides an efficient way to monitor protein processes; however, the ionic contributions of the different protein conformations involved usually overlap, and the use of chemometric tools is necessary to unravel the information related to the pure conformations that the biomolecule adopts along the process. Multivariate curve resolution-alternating least squares applied to MS-monitored protein processes provides the concentration profiles associated with the different protein conformations occurring during the process and the related pure mass spectra. The concentration profiles, in this context, the ionic contributions, describe the process mechanism and the structural information derived from the pure mass spectra characterizes the involved conformations. Mass spectra can be expressed schematically through percentages of base peak intensity. This chemical transformation compresses significantly the raw spectra and allows for an easier application of natural MS-related constraints, such as the presence of only one maximum, i.e., the base peak of a particular conformation, into the resolution of the pure signals. The combination of mass spectrometry and multivariate curve resolution methods is used to elucidate the mechanism of the pH-induced conformation changes of the bovine beta-lactoglobulin. As a final step, MS data are fused with circular dichroism data and are simultaneously analyzed to ensure and confirm that all the previously detected MS conformations really exist in solution and are an artifact of neither the ionization process nor their chemometric resolution.

The infrared amide bands are sensitive to the conformation of the polypeptide backbone of proteins. Since the backbone of proteins folds in complex spatial arrangements, the amide bands of these proteins result from the superimposition of vibration modes corresponding to the different types of structural motifs (α helices, β sheets, etc.). Initially, band deconvolution techniques were applied to determine the secondary structure of proteins, i.e., the abundance of each structural motif in the polypeptide chain was directly related to the area of the suitable deconvolved vibration modes under the amide I band (1700–1600cm−1). Recently, several multivariate regression methods have been used to predict the secondary structure of proteins as an alternative to the previous methods. They are based on establishing a relationship between a matrix of infrared protein spectra and another that includes their secondary structure, expressed as the fractions of the different structural motifs, determined from X-ray analysis. In this study, we investigated the use of the local regression method interval partial least-squares (iPLS) to seek improvements to the full-spectrum PLS and other regression methods. The local character of iPLS avoids the use of spectral regions that can introduce noise or that can be irrelevant for prediction and focuses on finding specific spectral ranges related to each secondary structure motif in all the proteins. This study has been applied to a representative protein data set with infrared spectra covering a large wavenumber range, including amides I–III bands (1700–1200cm−1). iPLS has revealed new structural mode assignments related to less explored amide bands and has offered a satisfactory predictive ability using a small amount of selected specific spectral information.

The combination of near- and midinfrared spectroscopies (NIR and MIR) is proposed to monitor temperature-dependent transitions of proteins. These techniques offer a high discriminating power to distinguish among protein structural conformations but, in temperature-dependent processes, present the drawback associated with the intense and evolving absorption of the deuterium oxide, used as a solvent in the protein solutions. Multivariate curve resolution-alternating least squares (MCR-ALS) is chosen as the data analysis technique able to unravel the contributions of the pure protein and deuterium oxide species from the mixed raw experimental measurements. To do so, MCR-ALS works by analyzing simultaneously experiments from MIR and NIR on pure deuterium oxide solutions and protein solutions in D2O. This strategy has proven to be effective for modeling the protein process in the presence of D2O and, therefore, for avoiding the inclusion of artifacts in the data stemming from inadequate baseline corrections. The use of MIR and NIR and MCR-ALS has been tested in the study of the temperature-dependent evolution of beta-lactoglobulin. Only the combined use of these two infrared techniques has allowed for the distinction of the three pure conformations involved in the process in the working thermal range: native, R-type state, and molten globule.

The information related to the local rank plays a key role in the resolution of dynamic multicomponent systems. Methods based on Principal Component Analysis, such as Evolving Factor Analysis (EFA), are perfectly designed to obtain this information as long as the processes under study are described by full rank two-way data sets, i.e., single matrices where all process contributions are linearly independent and can be mathematically distinguished from each other. Two-way rank-deficient systems do not fulfil the requirements needed by classical local rank analysis methods. On one hand, the structure of the single data matrix as such does not allow for the distinction of all the real process contributions: on the other hand, the condition of full rank can only be achieved by matrix augmentation and, then, a three-way data set is obtained.The aim of this work is the design of a local rank exploratory method adapted to work with full rank three-way data sets obtained by matrix augmentation of rank-deficient systems. The method will be tested on several real examples, where the rank-deficiency derives from the presence of coexisting evolving systems. Chemometric aspects, such as the way to obtain local rank information and to build initial estimates, and chemical aspects, such as the use of the method to gather knowledge about unknown interferent systems or about main contributions affected by strong evolving backgrounds, will be commented from the results obtained. (C) 2003 Elsevier B.V. All rights reserved.

Thermally induced protein unfolding/folding processes have been studied on alpha-lactalbumin and alpha-apolactalbumin. Experiments monitored by fluorescence and circular dichroism spectroscopic techniques on alpha-apolactalbumin showed the formation of an intermediate species, whereas in the case of alpha-lactalbumin, this intermediate species was not detected. The presence and resolution of this intermediate species, its spectrum, and the evolution of all conformations during protein unfolding/folding processes were estimated using the multivariate curve resolution-alternating least-squares method. Elucidation of the nature and contribution of the different secondary structure motifs in each of the resolved protein conformations, including the intermediate, was also carried out. Multivariate resolution has shown to be an excellent tool for the complete characterization of all protein conformations involved in folding processes, including intermediate species that cannot be isolated by physical or chemical means. Indeed, it is in the determination and modeling of these intermediates that this chemometric approach outperforms in power and reliability previous methodologies based on simpler measurements and data treatments and fills the void linked to the elucidation and interpretation of complex mechanisms in protein folding processes.

Multivariate curve resolution-alternating least squares (MCR-ALS) is proposed as a three-way analysis method to deal with multispectroscopic monitoring of protein folding. MCR-ALS provides the concentration profiles associated with the different protein conformations occurring during the process and their related spectra. The concentration profiles describe the folding mechanism and the spectra provide the structural information of the conformations involved. Analysis either of the protein folding process monitored with different techniques (i.e. a row-wise augmented data matrix) or of several experiments done in different conditions using the same technique (i.e. a column-wise augmented matrix) or both possibilities at the same time (i.e. a row- and column-wise augmented matrix), can be performed. Thermal unfolding and refolding of α-lactalbumin, monitored using far- and near-UV circular dichroism, fluorescence and UV spectrometry, is shown as example. Information related to changes in the tertiary and the secondary structure of the protein, to the presence of intermediates along the protein folding process and to the reversibility of the thermal process can be obtained.

Molecular modeling studies performed on the two cyclooxygenase isozymes (COXs) suggest that active site hydration is crucial for understanding inhibitor selectivity. In this work, models have been constructed considering some implicit water molecules, placed in the position suggested by GRID, that participate in the dynamic hydrogen-bonding network at the polar active site entrance together with protein residues 355, 524, 120, and 513. The selectivity observed for ketoprofen (1) and the structural analogues 2 and 3 may be rationalized in terms of such implicit hydration.