Selective and Continuous Oil Removal from Oil-Water Mixtures Using a Superhydrophobic and Superoleophilic Stainless Steel Mesh Tube.

The development of continuous oil-water separation processes has applications in the treatment of industrial oily wastewater and effective management of oil spills. In this research, the performance of a superhydrophobic-superoleophilic (SHSO) membrane in oil-water separation is investigated through dynamic tests. We investigate the effects of the total flow rate and oil concentration on the separation efficiency using an as-fabricated SHSO mesh tube. To construct the SHSO membrane, a tubular stainless steel mesh is dip-coated into a solution, containing a long-chain alkyl silane (Dynasylan F8261) and functionalized silica nanoparticles (AEROSIL R812). The as-prepared SHSO mesh tube illustrates a water contact angle of 164° and an oil contact angle of zero for hexane. A maximum oil separation efficiency (SE) of 97% is obtained when the inlet oil-water mixture has the lowest flow rate (5 mL/min) with an oil concentration of 10 vol %, while the minimum oil SE (86%) is achieved for the scenario with the highest total flow rate (e.g., 15 mL/min) and the highest oil concentration (e.g., 50 vol %). The water SE of about 100% in the tests indicates that the water separation is not affected by the total flow rate and oil concentration, due to the superhydrophobic state of the fabricated mesh. The clear color of water and oil output streams also reveals the high SE of both phases in dynamic tests. The outlet oil flux increases from 314 to 790 (L/m2·h) by increasing the oil permeate flow rate from 0.5 to 7.5 (mL/min). The linear behavior of the cumulative amounts of collected oil and water with time demonstrates the high separation performance of a single SHSO mesh, implying no pore blocking during dynamic tests. The significant oil SE (97%) of the fabricated SHSO membrane with robust chemical stability shows its promising potential for industrial-scale oil-water separation applications.

Towards real-time detection of wastewater in surface waters using fluorescence spectroscopy.

The presence of municipal wastewater at the intake of a major drinking water treatment facility located on Lake Ontario was examined using fluorescence data collected during a period of continuous monitoring. In addition, controlled mixing of lake water and wastewater sampled from a local treatment facility were conducted using a bench-scale fluorescence system to quantify observed changes in natural organic matter. Multivariate linear regression was applied to components derived from parallel factors analysis. The resulting mean absolute error for predicted wastewater level was 0.22% (V/V, wastewater/lake water), indicating that wastewater detection at below 1.0% (V/V) was possible. Analyses of sucralose, a wastewater indicator, were conducted for treated wastewater as well as surface water collected at two intake locations on Lake Ontario. Results suggested minimal wastewater contribution at the drinking water intake. A wastewater detection model using a moving baseline was developed and applied to continuous fluorescence data collected at one of the drinking water intakes, which agreed well with sucralose results. Furthermore, the simulated addition of 1.0% (V/V) of wastewater/wastewater was detectable in 89% of samples analyzed, demonstrating the utility of fluorescence-based wastewater monitoring.

Rapid and direct spectrophotometric method for kinetics studies and routine assay of peroxidase based on aniline diazo substrates.

Peroxidases are ubiquitous enzymes that play an important role in living organisms. Current spectrophotometrically based peroxidase assay methods are based on the production of chromophoric substances at the end of the enzymatic reaction. The ambiguity regarding the formation and identity of the final chromophoric product and its possible reactions with other molecules have raised concerns about the accuracy of these methods. This can be of serious concern in inhibition studies. A novel spectrophotometric assay for peroxidase, based on direct measurement of a soluble aniline diazo substrate, is introduced. In addition to the routine assays, this method can be used in comprehensive kinetics studies. 4-[(4-Sulfophenyl)azo]aniline (λmax = 390 nm, ɛ = 32 880 M(-1) cm(-1) at pH 4.5 to 9) was introduced for routine assay of peroxidase. This compound is commercially available and is indexed as a food dye. Using this method, a detection limit of 0.05 nmol mL(-1) was achieved for peroxidase.

Development of a soft-sensor based on multi-wavelength fluorescence spectroscopy and a dynamic metabolic model for monitoring mammalian cell cultures.

A soft-sensor based on an Extended Kalman Filter (EKF) that combines data obtained using a fluorescence-based soft-sensor with a dynamic mechanistic model, was investigated as a tool for continuous monitoring of a Chinese hamster ovary (CHO) cell cultivation process. A standalone fluorescence based soft-sensor, which uses a combination of an empirical multivariate statistical model and measured spectra, was designed for predicting key culture variables including viable and dead cells, recombinant protein, glucose, and ammonia concentrations. The standalone fluorescence sensor was then combined with a dynamic mechanistic model within an EKF framework, for improving the prediction accuracy and generating predictions in-between sampling instances. The dynamic model used for the EKF framework was based on a structured metabolic flux analysis and mass balances. In order to calibrate the fluorescence-based empirical model and the dynamic mechanistic model, cells were grown in batch mode with different initial glucose and glutamine concentrations. To mitigate the uncertainty associated with the model structure and parameters, non-stationary disturbances were accounted for in the EKF by parameter-adaptation. It was demonstrated that the implementation of the EKF along with the dynamic model could improve the accuracy of the fluorescence-based predictions at the sampling instances. Additionally, it was shown that the major advantage of the EKF-based soft-sensor, compared to the standalone fluorescence-based counterpart, was its capability to track the temporal evolution of key process variables between measurement instances obtained by the fluorescence-based soft-sensor. This is crucial for designing control strategies of CHO cell cultures with the aim of guaranteeing product quality.

Fluorescence-based soft sensor for at situ monitoring of Chinese hamster ovary cell cultures.

Multi-wavelength fluorescence spectroscopy was investigated as a potential tool for use in monitoring key process variables that include: viable and dead cells, recombinant protein, glucose, and ammonia concentrations for Chinese hamster ovary (CHO) cells during cultivation.For the purpose of calibrating the fluorescence-based empirical model, cells were grown in batch mode with different initial glucose and glutamine concentrations.Spectrofluorometer settings were optimized to ensure reproducibility and accuracy of the acquired spectra. With the purpose of gaining qualitative insight into the evolution of the spectra, the trajectories of individual fluorophore peaks were studied during the cultivation process. Spectral changes related to biomass and secreted proteins were investigated by comparing the spectra at various stages during the downstream processing. A partial least square regression (PLSR) was used to formulate empirical models that related the input data set, i.e., the fluorescence excitation-emission matrix, to the actual state of the system including viable cell and dead cells and recombinant protein, glucose, and ammonia concentrations. The models exhibited accurate prediction ability for the process variables of interest.

Comparison of the catabolic activity and catabolic profiles of rhizospheric, gravel-associated and interstitial microbial communities in treatment wetlands.

Microbial communities play a critical role in degrading organic contaminants in treatment wetlands; however, an understanding of the different roles played by rhizospheric, gravel-associated and interstitial microbial communities is deficient due to a lack of data directly comparing these microbial communities. Community level physiological profiling (CLPP) was used to compare the catabolic capabilities of rhizospheric, gravel-associated and interstitial microbial communities in vertical-flow planted and unplanted wetland mesocosms. Wetland mesocosms were decommissioned to gather microbial community samples associated with the roots and gravel bed media taken from the top (10 cm depth), middle (30 cm depth) and bottom (60 cm depth). The catabolic capabilities of the rhizospheric microbial communities were seen to be much greater than those of the gravel-associated communities. A decrease in catabolic capability was seen with increasing depth, suggesting that communities near the surface play a larger role in the degradation of carbon-based compounds. A general difference in catabolic profiles based on plant presence/absence was observed for the interstitial water and all gravel-associated samples at all depths, suggesting that the presence of roots within part of the mesocosm not only has a localized effect on the attached microbial population, but also on gravel-associated microbial communities throughout the mesocosms.

Direct spectrophotometric assay of laccase using diazo derivatives of guaiacol.

Laccase (EC 1.10.3.2) is a widespread cuproenzyme able to oxidize various types of phenols and similar aromatic compounds through a one-electron transfer mechanism. The enzyme has already found its way into the market as a biocatalyst. Because of its ability to be paired by electron mediators, the expectation for employing laccases in versatile processes is very high. There are a few spectrophotometric methods for assaying the laccase activity; however, all of them are based on the formation of product(s) resulting from the enzymatic and inevitable succeeding chemical reactions. Use of diazo derivatives of guaiacol (DdG) was developed as a new spectrophotometric method based on substrate depletion allowing direct assessment of enzyme activity has been introduced. This method allows accurate comprehensive kinetic studies of laccases and provides reliable information about the quality of docking of different substrates or one substrate to the active sites of different laccases. Using this method, the kinetic parameters of various DdG carrying different electron donating and withdrawing substituents were used to assay laccase from Neurospora crassa. 2-Methoxy-4-[(4-phenyl)azo]-phenol (K(m) = 93.5 µM and V = 1.98 µM/min) was identified as an appropriate substrate for the accurate and routine spectrophotometric based assay of laccases.

Investigation of the effects of oxidative stress-inducing factors on culturing and productivity of Bordetella pertussis.

The stress response of Bordetella pertussis during fermentation was assessed by means of fluorescence-based techniques. During the manufacturing of vaccines, B. pertussis is subjected to stress during adaptation to a new environment and operating conditions in the bioreactor, which can have harmful consequences on growth and protein yield. In this study, stress was imposed by varying the percentage of dissolved oxygen (DO) and inoculum size, and by adding rotenone and hydrogen peroxide. In this study, fluorescence spectroscopy is used as a tool for measuring oxidative stress. High levels of DO during fed-batch operation had no detrimental effect on growth, but the specific productivity of pertactin (PRN) decreased. Cultures that were started with an inoculum size that was 10 times smaller than the control resulted in significantly less PRN as compared to controls where reduction was more significant in flasks as compared to bioreactors. A comparison of filtered to heat-sterilized media revealed that filtered media offered a protective effect against H2 O2 . Heat sterilization of the media might result in the destruction of components that offer protection against oxidative stress. Nonetheless, filter sterilization on its own would be insufficient for large-scale manufacturing. It should be emphasized that the effects of these stressors while investigating for other microorganisms have not been studied for B. pertussis.

Functional properties of navy bean (Phaseolus vulgaris) protein concentrates obtained by pneumatic tribo-electrostatic separation.

A sustainable, chemical-free dry tribo-electrostatic separation approach was employed to fractionate navy bean flour. The resulting protein-enriched fractions had 36-38% protein on a moisture free basis, accounting for 43% of the total available protein. SDS-PAGE analysis of the dry-enriched protein fractions showed a similar protein profile to that of the original navy bean flour. The functional properties of these fractions were examined and compared with the commercial soybean protein concentrate as well as navy bean protein isolate obtained by a conventional wet fractionation process. These electrostatically separated protein fractions exhibited superior solubility at their intrinsic pH as well as superior emulsion stability (ES), foam expansion (FE) and foam volume stability (FVS) compared to the wet-fractionated navy bean protein isolate that was almost depleted of albumins, exhibiting poor solubility and foaming properties. These results suggest electrostatic separation as a promising route to deliver functional protein concentrates as novel food formulation ingredients.

Fluorescence-based soft-sensor for monitoring beta-lactoglobulin and alpha-lactalbumin solubility during thermal aggregation.

A soft-sensor for monitoring solubility of native-like alpha-lactalbumin (alpha-LA) and beta-lactoglobulin (beta-LG) and their aggregation behavior following heat treatment of mixtures under different treatment conditions was developed using fluorescence spectroscopy data regressed with a multivariate Partial Least Squares (PLS) regression algorithm. PLS regression was used to correlate the concentrations of alpha-LA and beta-LG to the fluorescence spectra obtained for their mixtures. Data for the calibration and validation of the soft sensor was derived from fluorescence spectra. The process of thermal induced aggregation of beta-LG and alpha-LA protein in mixtures, which involves the disappearance of native-like proteins, was studied under various treatment conditions including different temperatures, pH, total initial protein concentration and proportions of alpha-LA and beta-LG. It was demonstrated that the multivariate regression models used could effectively deconvolute multi-wavelength fluorescence spectra collected under a variety of process conditions and provide a fairly accurate quantification of respective native-like proteins despite the significant overlapping between their emission profiles. It was also demonstrated that a PLS model can be used as a black-box prediction tool for estimating protein aggregation when combined with simple mass balances.

Assessment of changes in the microbial community of constructed wetland mesocosms in response to acid mine drainage exposure.

Changes in the bacterial community in the interstitial water of 5 different constructed wetland mesocosms were studied over a 22-day period following exposure to simulated acid mine drainage (AMD). The community-level physiological profile (CLPP) of each mesocosm was assessed using substrate utilization patterns gathered via BIOLOG ECO plates. Principal component analysis (PCA) of the BIOLOG ECO plate data proved feasible and useful in characterizing the interstitial bacterial community in the constructed wetland mesocosms based on mesocosm characteristics such as fixed biological regime development and plant presence, and was also used to successfully track changes in the interstitial bacterial community in response to AMD exposure. Clustering analysis of the BIOLOG ECO plate data was used to characterize the interstitial bacterial community and to validate the mesocosm groupings observed through PCA ordination. The calculation of substrate-based diversity indices from the BIOLOG ECO plate data was used to assess the robustness and the degree of change shown by the metabolic fingerprint of the interstitial bacterial community within the mesocosms. The interstitial bacterial community in the constructed mesocosms was shown to be significantly affected after exposure to AMD. Exposure to AMD caused similar bacterial species to detach from the fixed biotic regime of the mesocosms. It was also shown that mesocosms planted with Phragmites australis did not experience as great an ecological shift in the microbial ecology of the interstitial water after exposure to AMD as did the unplanted mesocosms. The substrate-based diversity indices for the planted mesocosms were also found to be more stable, after exposure to AMD, than those for the unplanted mesocosms. It is possible that the interaction between the plant root system and the substrate biological regime, collectively called the rhizosphere, may create a more ecologically robust and stable treatment system.

Recent developments in biodegradation of industrial pollutants by white rot fungi and their enzyme system.

Increasing discharge and improper management of liquid and solid industrial wastes have created a great concern among industrialists and the scientific community over their economic treatment and safe disposal. White rot fungi (WRF) are versatile and robust organisms having enormous potential for oxidative bioremediation of a variety of toxic chemical pollutants due to high tolerance to toxic substances in the environment. WRF are capable of mineralizing a wide variety of toxic xenobiotics due to non-specific nature of their extracellular lignin mineralizing enzymes (LMEs). In recent years, a lot of work has been done on the development and optimization of bioremediation processes using WRF, with emphasis on the study of their enzyme systems involved in biodegradation of industrial pollutants. Many new strains have been identified and their LMEs isolated, purified and characterized. In this review, we have tried to cover the latest developments on enzyme systems of WRF, their low molecular mass mediators and their potential use for bioremediation of industrial pollutants.

Detachment of solids and nitrifiers in integrated, fixed-film activated sludge systems.

Despite the importance of detachment to biofilm processes, detachment phenomena are not well understood. In this study, researchers investigated biofilm detachment from free-floating biofilm carriers that were established in an integrated, fixed-film activated sludge (IFAS) installation in Mississauga, Ontario. A method for assessing detachment from biofilm carrier systems was devised, evaluated, and refined during this study. In the absence of substrate, superficial air velocity significantly affected the 24-hour detachment rates of total suspended solids from the carriers. Short-term growth conditions did not appear to significantly affect the rate of detachment of solids and nitrifiers. The measured solids-detachment rates were found to be described by a second order function of biofilm attached growth total solids with a detachment coefficient of 0.006 +/- 0.0008 (g/m x d)(-1).

Oxygen uptake rate tests to evaluate integrated fixed film activated sludge processes.

A modified oxygen uptake rate (OUR) test for characterizing the performance of integrated fixed-film activated sludge (IFAS) processes was developed while monitoring the startup of a full-scale demonstration facility. Data on total biofilm solids, in-basin nitrification rates, and batch nitrification rates were compared to the OUR test. The data was used to investigate dynamic changes in the physical and microbiological parameters during and after plant startup. Nitrification of the carriers was observed to follow different trends than the biofilm total solids during process startup. The process reached high nitrification rates within weeks, whereas the biofilm total solids required more than 50 days to attain a quasi-steady-state. This study illustrated that parameters in addition to biofilm total solids are required to assess activity in nitrifying IFAS processes and oxygen uptake rates can be a useful tool in this regard.

Neural networks for dimensionality reduction of fluorescence spectra and prediction of drinking water disinfection by-products.

The use of fluorescence data coupled with neural networks for improved predictability of drinking water disinfection by-products (DBPs) was investigated. Novel application of autoencoders to process high-dimensional fluorescence data was related to common dimensionality reduction techniques of parallel factors analysis (PARAFAC) and principal component analysis (PCA). The proposed method was assessed based on component interpretability as well as for prediction of organic matter reactivity to formation of DBPs. Optimal prediction accuracies on a validation dataset were observed with an autoencoder-neural network approach or by utilizing the full spectrum without pre-processing. Latent representation by an autoencoder appeared to mitigate overfitting when compared to other methods. Although DBP prediction error was minimized by other pre-processing techniques, PARAFAC yielded interpretable components which resemble fluorescence expected from individual organic fluorophores. Through analysis of the network weights, fluorescence regions associated with DBP formation can be identified, representing a potential method to distinguish reactivity between fluorophore groupings. However, distinct results due to the applied dimensionality reduction approaches were observed, dictating a need for considering the role of data pre-processing in the interpretability of the results. In comparison to common organic measures currently used for DBP formation prediction, fluorescence was shown to improve prediction accuracies, with improvements to DBP prediction best realized when appropriate pre-processing and regression techniques were applied. The results of this study show promise for the potential application of neural networks to best utilize fluorescence EEM data for prediction of organic matter reactivity.

New insight into the allosteric effect of L-tyrosine on mushroom tyrosinase during L-dopa production.

Kinetics studies of L-tyrosine (LTy) ortho-hydroxylation by mushroom tyrosinase (MT) confirmed that MT was severely, but not completely, inhibited at higher concentrations of LTy. Despite the availability of the crystal structure reports, no allosteric site has been identified on MT. To examine the assumption that a non-specific binding site works as a regulatory site, docking simulations were run for the second molecule of L-tyrosine (LTy2) on the complexes of the first L-tyrosine molecule (LTy1) with the heavy chain (H) of MT (LTy1/HMT) and its dimer with the light chain (Ty1/LHMT). In both, LTy2 occupied a non-specific binding site (MTPc). MD simulations revealed LTy2/HMT/LTy1 and LTy2/LHMT/LTy1 were stable. Binding free-energy analysis supported the formation of LTy2/HMT/LTy1 and LTy2/LHMT/LTy1 at higher concentrations of LTy and disclosed the importance of ΔEelec and ΔGpolar during binding of LTy2 to MTPc. Upon LTy2 binding to MTPc, the Cu-Cu distance remained unchanged while the spatial position of LTy1 in the active site (MTPa) changed so that it would not be able to participate in ortho-hydroxylation. This study suggests a tuning role for L chain during binding of the ligands to MTPa and MTPc. Given these results, a plausible mechanism was proposed for the MT substrate inhibition.

Data transformations in the analysis of community-level substrate utilization data from microplates.

BIOLOG EcoPlates provide one method for determination of functional diversity indices and community-level physiological profiling of microbial populations based on carbon substrate utilization. In this study, the effect of data transformation on BIOLOG EcoPlate data derived from wetland mesocosms and biofiltration systems was examined. Homoscedasticity, normality, and the number of linear correlations between variables were quantified and evaluated for data that had been transformed using either Taylor or logarithmic transforms. Subsequent multivariate analysis was implemented using the untransformed, Taylor transformed and logarithmic transformed data sets. The effect of data transformation and its effect on principle component analysis are presented. The transforms are shown to help increase homogeneity of variance, increase normality of the data, and increase the number of significant linear correlations for the data. Separate principle component analyses and ordinations of the data showed the transforms to be well suited to this type of data and in particular illustrate the ability of the logarithmic transform to reduce the influence of high leverage or outlying observations on the overall analysis and its robustness in terms of treating data from different ecological systems. Although BIOLOG EcoPlates were used in this study to illustrate the use of transformations on multivariate data, the techniques described may be employed on similar microplate data. In addition, if homoscedasticity, normality and the number of linear correlations within a data set are not evaluated and the possibility of transforming the data, using the Taylor, logarithmic or another transform, is not considered, erroneous analysis and misleading conclusions may be attained when performing multivariate analysis on microplate data.

Enhanced aqueous solubilization of tetrachloroethylene by a rhamnolipid biosurfactant.

A rhamnolipid biosurfactant produced by Pseudomonas aeruginosa ATCC 9027 was isolated, purified and characterized in terms of its ability to mobilize and solubilize tetrachloroethylene (PCE) for potential use in surfactant-enhanced aquifer remediation (SEAR) applications. Using a drop volume method, the PCE-biosurfactant steady-state interfacial tension was determined and found to be ca. 10 mN/m which is not low enough to cause significant PCE nonaqueous phase liquid (NAPL) mobilization. It was observed that the biosurfactant partitioned significantly into PCE at aqueous concentrations higher than the critical micelle concentration (CMC). After accounting for rhamnolipid partitioning into the PCE phase, a weight solubilization ratio (WSR) of 1.2 g(PCE)/g(rhamnolipid) was determined and through this mechanism the biosurfactant significantly improved the apparent aqueous solubility of PCE.

Tracers for investigating pathogen fate and removal mechanisms in mesocosms.

The purpose of the present investigation has been to develop a tracer suite that has application in in-situ assessment and optimization of physical and biological removal and elimination mechanisms of pathogens within laboratory scale biological treatment systems. The tracer suite includes three pathogen indicators, namely, a conserved non-viable particle (fluorescently labelled microspheres, FLM), a non-conserved non-viable particle (fluorescently labelled bioparticles, FLB), and a non-conserved viable particle (Nalidixic acid resistant E. coli, NAREC). The tracer triplet principles were developed with practical experiments on planted, and unplanted subsurface flow wetland mesocosms treating a synthetic domestic wastewater. The tracers monitor for physical removal mechanisms (FLM), elimination activity (FLB), and removal thresholds (NAREC). FLM enumeration was simplified by calibration of particle concentration with respect to acetone-extractable fluorescence. Similarly, FLB elimination was assessed by bulk fluorescence using two characteristic excitation-emission wavelength pairs: 494/519 and 220/319 nm. NAREC results indicated that first order removal kinetics may only proceed down to limiting threshold concentrations.

Investigation of fluorescence methods for rapid detection of municipal wastewater impact on drinking water sources.

Fluorescence spectroscopy as a means to detect low levels of treated wastewater impact on two source waters was investigated using effluents from five wastewater facilities. To identify how best to interpret the fluorescence excitation-emission matrices (EEMs) for detecting the presence of wastewater, several feature selection and classification methods were compared. An expert supervised regional integration approach was used based on previously identified features which distinguish biologically processed organic matter including protein-like fluorescence and the ratio of protein to humic-like fluorescence. Use of nicotinamide adenine dinucleotide-like (NADH) fluorescence was found to result in higher linear correlations for low levels of wastewater presence. Parallel factors analysis (PARAFAC) was also applied to contrast an unsupervised multiway approach to identify underlying fluorescing components. A humic-like component attributed to reduced semiquinone-like structures was found to best correlate with wastewater presence. These fluorescent features were used to classify, by volume, low (0.1-0.5%), medium (1-2%), and high (5-15%) levels by applying support vector machines (SVMs) and logistic regression. The ability of SVMs to utilize high-dimensional input data without prior feature selection was demonstrated through their performance when considering full unprocessed EEMs (66.7% accuracy). The observed high classification accuracies are encouraging when considering implementation of fluorescence spectroscopy as a water quality monitoring tool. Furthermore, the use of SVMs for classification of fluorescence data presents itself as a promising novel approach by directly utilizing the high-dimensional EEMs.