Search

Treatment and reuse of some produced waters is made difficult due to their hypersalinity, high concentrations of myriad other dissolved and suspended components, specialized technology requirements (modularity, portability, and short residence times), and lack of existing information on their processing. In this work, produced water containing ∼100,000 mg/L total dissolved solids from the Permian Basin was coagulated with aluminum chlorohydrate (ACH) and flocculated with an anionic high molecular weight organic polymer prior to dissolved air flotation (DAF) and sedimentation to reduce turbidity to4 NTU and iron0.8 mg/L (95% removal in both cases) with a total coagulation-flocculation-sedimentation/flotation residence time of only 5 min. Two advantages of DAF over sedimentation were noted: (i) DAF required only half the dosage of the pre-hydrolyzed ACH coagulant to remove ∼90% of turbidity and iron even without the organic polymeric flocculant and (ii) DAF even operated successfully without ACH coagulation (i.e., using only the organic polymeric flocculant) evidencing its lower chemical dosing needs. Further, DAF attained all water quality and operational goals at a recycle ratio of only 12% demonstrating that it outperformed sedimentation to generate clean brine at relatively reduced excess energies necessary for air saturation. Higher DAF recycle ratios reduced turbidity and iron removal possibly due to floc breakage. Colloids were effectively destabilized by double layer compression (due to high water salinity), charge neutralization (via adsorption of Al

Uncertainty is inherent in experimentation, modeling, and analysis. Variations and errors in parameter estimates or physical processes are unavoidable and can affect the reliability of model predictions. Therefore understanding the role of uncertainty is embedded in the process of modeling and approximating the real world. In this manuscript we consider uncertainty propagation in a theoretical model of water/wastewater treatment. In dead-end microfiltration contaminated water is fed through a membrane that filters out colloids, bacteria, and protozoa. However, these particles foul the membrane reducing the filter productivity, which is alleviated by periodically reversing the flow, i.e. backwashing. We investigate how uncertainty in sensitive parameter estimates propagates to the estimates of the optimal amount of volume of water that is filtered in a fixed time period and the associated backwashing timing and duration. We find that the model provides conservative estimates for the total volume since the uncertainty is not propagated symmetrically with respect to over and underestimating specific measurable quantities. The uncertainty in the timing is more symmetric implying that there is essentially an equal amount of uncertainty for increasing or decreasing the frequency and duration of backwashing. We identified biofilm production as propagating the most uncertainty in the volume estimate. The fouling rate has the most effect on the timing estimates. Additionally we explored the affect of asymmetric parameter distributions and find that, for most parameters, asymmetry does not lead to increased asymmetry in predicted optimal regimes, implying that uncertainty in the skewness is likely not an issue.

One promising water management strategy during hydraulic fracturing is treatment and reuse of flowback/produced water. In particular, the saline flowback water contains many of the chemicals employed for fracking, which need to be removed before possible reuse as “frac water.” This manuscript targets turbidity along with one of the additives; borate-based cross-linkers used to adjust the rheological characteristics of the frac-fluid. Alum and ferric chloride were evaluated as coagulants for clarification and boron removal from saline flowback water obtained from a well in the Eagle Ford shale. Extremely high dosages (> 9000 mg/L or 333 mM Al and 160 mM Fe) corresponding to Al/B and Fe/B mass ratios of ∼70 and molar ratios of ∼28 and 13 respectively were necessary to remove ∼80% boron. Hence, coagulation does not appear to be feasible for boron removal from high-strength waste streams. X-ray photoelectron spectroscopy revealed B O bonding on surfaces of freshly precipitated Al(OH)3(am) and Fe(OH)3(am) suggesting boron uptake was predominantly via ligand exchange. Attenuated total reflection-Fourier transform infrared spectroscopy provided direct evidence of inner-sphere boron complexation with surface hydroxyl groups on both amorphous aluminum and iron hydroxides. Only trigonal boron was detected on aluminum flocs since possible presence of tetrahedral boron was masked by severe Al O interferences. Both trigonal and tetrahedral conformation of boron complexes were identified on Fe(OH)3 surfaces.

One of the central problems in membrane implementation is that foulants deposit on surfaces of microfilters employed for water and wastewater treatment and reuse, reducing their productivity. In an effort to remove as much of the deposited materials as possible and maintain the flux, the direction of flow across these membranes is regularly and frequently reversed. However, backwashing only removes the loosely or reversibly bound materials necessitating the entire system to be taken off-line for chemical cleaning when fouling increases beyond a threshold value. We recently presented a mathematically rigorous methodology to determine timing and duration of backwashes so as to delay membrane chemical cleaning and reduce associated operational complexity and costs. By considering an optimal control formulation, using the flow direction as the control variable, the optimal timing and maximum volume of water that can be microfiltered in a given time period were predicted during dead-end filtration of bacterial suspensions. The value of these predictions depend on our ability to accurately and precisely estimate input parameters such as the clean membrane resistance, influent water quality estimates, and biofilm and exo-polymeric substance formation rates and effects. These estimates are inherently uncertain leading to uncertainty in the predictions, which can be rigorously quantified using Sobol indices. These provide a global method for assessing the sensitivity of model predictions (e.g. optimal timing and volume filtered) with respect to variations in the inputs.

Bench-scale nanofiltration (NF) experiments were performed with two commercially available membranes having different ion rejection characteristics to assess dominant fouling mechanisms during inland brackish surface water desalination and the role of rejection on flux decline. The Foss Reservoir in the state of Oklahoma, USA was used as a representative natural brackish surface water source in these experiments. Both nanofilters rejected divalent cations to a very high extent (Mg>94% and Ca>92%) but exhibited substantially different rejections of monovalent cations (e.g. Na removals of 60% and 97%). A model solution formulated to have a similar ionic composition as the natural water but with no added natural organic matter (NOM) was also employed to isolate mineral scaling effects. The low monovalent ion rejecting membrane was predominantly fouled by NOM with only limited contributions from calcium carbonate scaling. In contrast, electron microscopy along with infrared and X-ray photoelectron spectroscopy revealed that both NOM and gypsum were major foulants for the membrane that highly rejected both mono- and divalent ions. The exacerbated flux decline for the more salt-rejecting nanofilter was attributed to the synergistic effects of NOM and gypsum on fouling coupled with the formation of a very compact organic foulant layer due to greater extent of Ca-NOM interactions and the higher ionic strength of the concentration polarization layer. These results demonstrate that the relative contributions of NOM and mineral scaling to flux decline during brackish surface water NF depends on membrane ion rejection characteristics. Hence, optimal membrane selection needs to balance total dissolved solids concentration of the product water with the need to minimize fouling.

Microfiltration and ultrafiltration are methods of removing colloidal impurities from water and wastewater. One of the major issues when dealing with the practical implementation of membranes is the reduction of water productivity as the foulants accumulate on the membrane surface or within the pores. Membrane regeneration by periodic backwashing is an effective method of reducing fouling; however, to date the timing and duration of the backwashing for effective fouling control is largely only empirically determined. In this manuscript, we present an optimal control formulation to determine the timing and duration for membrane regeneration by backwashing. In this formulation, we use the direction of the flow as the control variable and make predictions regarding the optimal protocol. We explicitly include irreversible attachment due to bacterial deposition and biofilm formation on the membrane and demonstrate that irreversible attachment of bacteria has important ramifications for the effective timing of hydraulic backwashes as well as the efficiency in producing clean water. In particular, we find that irreversible attachment and additional fouling due to exo-polymeric substance (EPS) production and biofilm formation decreases the maximum filtration volume. Additionally, as the effectiveness of membrane regeneration declines, the timing of the cycling is also altered. In general, including the role of EPS in biofouling substantially changes predictions of backwashing timing and implies important considerations for practical predictions.

Reusing produced water for hydraulic fracturing simultaneously satisfies challenges of fresh water sourcing and the installation/operation of an extensive disposal well infrastructure. Herein, we systematically and rigorously investigate produced water treatment for reuse during hydraulic fracturing. Highly saline and turbid produced water from the Permian Basin was treated by adding chlorine as an oxidant, FeCl3 as the primary coagulant, and an anionic polymer to induce high rate sedimentation to generate “clean brine” by removing suspended solids and iron over a range of environmentally relevant temperatures. Mobile phone video capture, optical microscopy, and digital image/video analysis were employed to characterize floc morphology and measure its size and settling velocity. Conformational changes of the polymeric coagulant between 4 and 44 °C were inferred from viscosity and dynamic light scattering measurements providing clues to its performance characteristics. Floc settling velocities measured over the entire range of polymer dosages and temperatures were empirically modelled incorporating their fractal nature, average size, and the viscosity of the produced water using only a single fitting parameter. Juxtaposing the anionic polymer with the hydrolyzing metal-ion coagulant effectively destabilized the suspension and caused floc growth through a combination of enmeshment, adsorption and charge neutralization and inter-particle bridging as evidenced by Fourier transform infrared spectroscopy and thermogravimetric analysis. Very high turbidity (≥98%) and total iron (≥97%) removals were accomplished even with very short flocculation and sedimentation times of only 6 minutes each suggesting the feasibility of this approach to reuse produced water for hydraulic fracturing.

The primary objective of this research is to accurately estimate light-duty vehicles' (LDVs') emissions of PM2.5 and PM10 over the course of a year within the property line of an inner-city school located adjacent to a heavily-trafficked interstate highway by measuring platinum group elements (PGEs – Rh, Pd, and Pt) along with 49 other major and trace elements. Amongst PGEs, ambient Pd concentrations were the highest, averaging 11 pg/m3 in PM10 and 4.0 pg/m3 in PM2.5 followed by Pt (3.5 pg/m3 in PM10 and 1.4 pg/m3 in PM2.5), and Rh (1.6 pg/m3 in PM10 and 0.52 pg/m3 in PM2.5). Simultaneous three-component variations in Rh, Pd, and Pt in both PM size classes at this surface site closely matched the composition of (i) a mixed random lot of recycled autocatalysts obtained from numerous LDVs and (ii) PM inside a proximal underwater tunnel open only to light-duty vehicles. Additionally, quantitative estimates of LDV contributions to ambient PM calculated by chemical mass balance modeling (CMB) were strongly correlated with PGE abundances. Therefore, PGEs predominantly originated from gasoline-driven motor vehicles validating them as unique LDV tracers. Further, CMB estimated that vehicles contributed 37% on average (12–67%) to PM10 and 49% on average (25–73%) to PM2.5. Evidence is also presented for a subset of other trace metals; i.e. Cu, As, Mo, Cd, and Sb to also be relatively strong LDV tracers. Results highlight the importance of measuring PGEs in addition to numerous other elements in PM to accurately apportion aerosols emanating from LDVs, which will better isolate public health and environmental impacts associated with the transportation sector.

The rejection coefficient of nonspherical particles from ultrafiltration and microfiltration membranes has been examined from both theoretical and experimental perspectives. Modeling efforts focused on incorporating the convective hindrance factor for a capsule shaped particle in a cylindrical pore into predictions of the rejection coefficient. First, the convective hindrance factor was approximated using previously reported results for the hydrodynamic resistances experienced by a sphere in a pore. Second, computational fluid dynamics calculations predicted the convective hindrance factor for a capsule in a cylindrical pore. Results from both approaches indicate that including hydrodynamic interactions in predictions of the rejection coefficient has a greater effect for smaller particles and particles with smaller aspect ratio (i.e., close to spherical shape). Rejections of several rod-shaped Gram negative bacteria with aspect ratio from 2 to 5 by clean track-etched membranes were in general agreement with theoretical predictions. © 2013 American Institute of Chemical Engineers AIChE J, 59: 3863–3873, 2013

Results from a laboratory-scale study evaluating virus control by a hybrid iron electrocoagulation – microfiltration process revealed only 1.0–1.5 log MS2 bacteriophage reduction even at relatively high iron dosages (∼13 mg/L as Fe) for natural surface water containing moderate natural organic matter (NOM) concentrations (4.5 mg/L dissolved organic carbon, DOC). In contrast, much greater reductions were measured (6.5-log at pH 6.4 and 4-log at pH 7.5) at similar iron dosages for synthetic water that was devoid of NOM. Quantitative agreement with Faraday’s law with 2-electron transfer and speciation with phenanthroline demonstrated electrochemical generation of soluble ferrous iron. Near quantitative extraction of viruses by dissolving flocs formed in synthetic water provided direct evidence of their removal by sorption and enmeshment onto iron hydroxide flocs. In contrast, only approximately 1% of the viruses were associated with the flocs formed in natural water consistent with the measured poor removals. 1–2 logs of virus inactivation were also observed in the electrochemical cell for synthetic water (no NOM) but not for surface water (4.5 mg/L DOC). Sweep flocculation was the dominant destabilization mechanism since the ζ potential did not reach zero even when 6-log virus reductions were achieved. Charge neutralization only played a secondary role since ζ potential → 0 with increasing iron electrocoagulant dosage. Importantly, virus removal from synthetic water decreased when Suwanee River Humic Acid was added. Therefore, NOM present in natural waters appears to reduce the effectiveness of iron electrocoagulation pretreatment to microfiltration for virus control by complexing ferrous ions. This inhibits (i) Fe 2+ oxidation, precipitation, and virus destabilization and (ii) virus inactivation through reactive oxygen species intermediates or by direct interactions with Fe 2+ ions.

Water quality results related to disinfection by products (DBPs) from a bench-scale study designed to evaluate surface water nanofiltration (NF) for the City of Houston are analyzed to provide insights into mechanisms of DBP formation and control. One contribution of this manuscript is that we report on DBP speciation following NF of Lake Houston water containing very low concentrations of the bromide ion ( 254 ), dissolved organic carbon (DOC), and chlorine consumption were found to be excellent surrogates for aqueous DBP concentrations even in chlorinated nanofiltered waters. Mole fractions of mono-, di-, and trihalogenated HAA species were invariant with respect to changes in Br − /DOC molar ratio suggesting that the brominated HAAs are formed through the same mechanisms as the chlorinated ones in NF permeate waters. Additionally, bromine incorporation into both THMs and HAAs increased with increasing Br/DOC ratio suggesting that the brominated THM and HAA species form first consuming the reactive precursor sites and in the process restricting formation of the chlorinated species. Bromide utilization was observed to decrease with Br − /DOC molar ratio demonstrating that nanofilter permeate waters were substantially limited with respect to NOM and DBP precursors.

Fine particulate matter levels at four air sampling stations in the Houston, TX area are apportioned to quantify the impact of emissions from a local refinery during a reported emission event. Through quantification of lanthanum and lanthanides using a recently developed analytical technique, the impacts of emissions from fluidized-bed catalytic cracking (FCC) units are quantitatively tracked across the Houston region. The results show a significant (33-106-fold) increase in contributions of FCC emissions to PM2.5 compared with background levels associated with routine operation. This impact from industrial emissions to ambient air quality occurs simultaneously with a larger, regional haze episode that lead to elevated PM2.5 concentrations throughout the entire region. By focusing on detailed chemical analysis of unique maker metals (lanthanum and lanthanides), the impact of emissions from the FCC unit was tracked from the local refinery that reported the emission event to a site approximately 50 km downwind, illustrating the strength of the analytical method to isolate an important source during a regional haze episode not related to the emission event. While this source apportionment technique could separate contributions from FCC emissions, improved time-resolved sampling is proposed to more precisely quantify the impacts of transient emission events on ambient PM2.5.

Electrocoagulation (EC) is the intentional corrosion of sacrificial anodes (typically aluminum or iron) by passing electricity to release metal-ion coagulant species and destabilize a wide range of suspended, dissolved, and macromolecular contaminants. It can be integrated ahead of microfiltration (MF) to effectively control turbidity, microorganisms, and disinfection by-products (DBPs) and simultaneously maintain a high MF specific flux. This manuscript summarizes the current knowledge on MF pretreatment by aluminum EC particularly focusing on mechanisms of (i) electrocoagulant dosing, (ii) (bio)colloid destabilization, (iii) fouling reductions, and (iv) enhanced removal of viruses, natural organic matter (NOM), and DBP precursors. Electrolysis efficiently removes hydrophobic NOM, viruses, and siliceous foulants. Aluminum effectively electrocoagulates viruses by physically encapsulating them in flocs, neutralizing their surface charge and reducing electrostatic repulsion, and increasing hydrophobic interactions between any sorbed NOM and free viruses. New results included herein demonstrate that EC achieves DBP control by removing NOM, reducing chlorine-reactivity of remaining NOM, and inducing a slight shift toward more brominated trihalomethanes and haloacetic acids. EC reduces MF fouling by forming large flocs that tend to deposit on the membrane surface, i.e. decrease pore penetration and forming more permeable cakes and by reducing foulant mass in case of significant floc-flotation.

Phenomenological coefficients arising from the application of irreversible thermodynamics to the passage of water and dilute solutions of alcohols, sugars, NaCI and NaClO 4 across two commercially available nanofiltration membranes are physically interpreted using the frictional model proposed by Spiegler, Kedem and Katchalsky. The effects of temperature in the range 5-41°C and NaCI concentration in the range 1-50 meq l -1 were also quantified. Pure water permeability, solute reflection coefficient and solute diffusive permeability are linked to solute-water, solute-membrane and water-membrane frictional interactions within the nanofilters' polymeric network. Changes in intra-membrane frictional coefficients with feed water temperature and concentration are related to variations in nanofilter morphological and charge characteristics. As may be expected, water-membrane friction coefficients were several orders of magnitude smaller than solute-membrane friction coefficients demonstrating that the semi-permeable nanofilters hindered solute passage to a substantially greater degree than water. Analogous to viscosity, all frictional coefficients decreased with temperature. Greater steric hindrances faced by larger solutes to passage across nanofilters are manifested as increasing activation energies of solute-membrane interactions and solute-water interactions. Hydrodynamic theories of hindered transport are shown to closely follow trends in frictional coefficients with increasing solute size. Antagonistic effects of changes in electrostatic and steric interactions with temperature reduced activation energies of electrolyte-membrane frictional interactions.

Robust artificial neural network (ANN) models for membrane fouling induced by polydispersed feed suspensions during crossflow microfiltration were derived and validated. ANNs performed highly accurate simulations of time-variant specific fluxes for several feed suspensions under a wide range of hydrodynamic parameters. Hence, ANNs incorporate the integral effects of complex colloidal transport and deposition mechanisms as well as changes in cake morphology and resistance with hydrodynamics better than mathematically complicated mechanistic models. An important contribution of this research is that it is demonstrated that ANNs need not be used simply as black boxes and cause-effect information can be quantitatively extracted from network connection weights to assist in model development and experimental design. Such an analysis revealed that the initial permeate flux is the most important operational variable influencing membrane fouling. However, in contrast to crossflow filtration of monodispersed suspensions, the shear rate was found to only weakly influence specific flux.

A robust artificial neural network (ANN) model requiring minimal training, closely predicted membrane fouling during nanofiltration (NF) of ground and surface water. Neural networks accurately simulated the total resistance to water permeation across NF membranes during bench-scale experiments with flat membrane sheets, tests with single spiral-wound elements, as well as pilot- and full-scale tests with multiple spiral-wound elements arranged in two stages. ANN inputs included physically meaningful and independent variables including flow rates and feed water quality parameters (pH, UV254, and total dissolved solids (TDS)) that are commonly monitored during water treatment thereby facilitating their implementation. Therefore, under the experimental conditions investigated, colloidal fouling and biofouling appeared to be negligible because accurate ANN predictions were possible without using feed water turbidity and bacteria concentrations as inputs. One emphasis during this work was to minimize the data employed for ANN training while simultaneously performing simulations in purely predictive mode for entire cycles (experiments). Cumulatively, using only 10% of experimental data for ANN training allowed prediction of 93% of them with

A semiempirical differential model based on homogenous solution and diffusion is developed to analyze contaminant removal during municipal water nanofiltration at high feed water recoveries. An intrinsic transport parameter derived using this model from bench-top experiments employing flat membrane sheets is used to predict contaminant rejection in large-scale experiments using single and multiple spiral-wound modules conducted under the Information Collection Rule. Because solute back-transport dominated permeate flux, concentration polarization was negligible during these nanofiltration experiments. Permeation coefficients were found to increase monotonically with increasing solute aqueous diffusivity. Pseudostochastic simulations were performed in a purely predictive manner using the Monte Carlo methodology to theoretically calculate permeate concentrations in large-scale facilities using probability density functions for permeation coefficients (obtained from bench-top experiments) and observed feed w...

Leaching of trace elements including heavy metals, nonmetals, and radionuclides from surface impoundments of tailings generated during uranium mining and milling often leads to groundwater contamination. This paper reports results from coagulation and membrane filtration experiments designed to evaluate the capabilities of these processes to remove molybdenum, selenium, uranium, radium, thorium, and other mono- and divalent ions from contaminated groundwater in a shallow unconfined aquifer influenced by uranium tailings. A 10 mg Fe³\u+/L dose at pH 4 and 10 was found to be very effective for removing radium and thorium that were associated with particles in the raw water. Molybdenum and uranium removals by coagulation are consistent with surface complexation and electrostatic interactions between major coagulant and contaminant complexes in solution. Poor selenium removal suggests that selenate [Se(VI)] was the dominant species in the surficial groundwater. Permeation coefficients (intrinsic transport parameters) for dissolved ions and complexes across three new generation thin-film composite nanofiltration and reverse osmosis membranes evaluated obeyed Gaussian distributions with ionic charge having a mean value of zero. Thus, dissolved solute rejection from brackish multicomponent solutions appears to be only a function of the magnitude of ionic charge and not its sign (positive or negative). Solute permeation coefficients decreased in a power-law fashion with magnitude of ionic charge and not its sign (positive or negative). Solute permeation coefficients decreased in a power-law fashion with increasing product of molecular weight and absolute ion charge suggesting that both properties determine their removal by nanofiltration and reverse osmosis membranes. Because nanofiltration and reverse osmosis were found to be highly effective for removing a variety of ionic solutes they can be employed in pump and treat operations for groundwater purification prior to reinjection.

Results from Information Collection Rule nanofiltration studies representing various source waters and membranes are analyzed to gain insights into the effects of source water location, season, and membrane type (composition). In the range of experimental conditions investigated, membrane type appears to have a stronger influence on contaminant removal when compared to source water location and seasonal variations. Therefore, the extent of site-specific demonstration studies currently required by state primacy agencies prior to regulatory approval of each nanofiltration installation might be limited to issues other than permeate water quality subsequent to conducting just one pilot study with the membrane under consideration. Intrinsic membrane transport coefficients for all organic water-quality parameters evaluated were highly correlated with each other, demonstrating that the solution and diffusion characteristics of natural organic matter (measured as dissolved organic carbon and/or ultraviolet absorb...

Results from a potable water microfiltration (MF) pilot study employing untreated surface water are reported. The effects of filtrate flux and recovery on direct flow, outside-inside, hollow fiber MF fouling rates, and backwash effectiveness are presented. Constant flux experiments suggested the existence of a critical recovery below which MF fouling rates were low and effectiveness of backwashes was high and relatively independent of the recovery. However, in the range of experimental conditions investigated, fouling rates increased dramatically and backwash effectiveness decreased steeply when this critical recovery was exceeded regardless of the flux. In general, for a fixed recovery, specific flux profiles analyzed on the basis of volume filtered per unit membrane area were insensitive to filtrate flux. Fouling was accelerated by operating membranes at constant flux rather than at constant pressure, in part, because of membrane compaction and cake compression. Changing the mode of filtration between constant flux and constant pressure is shown to have no effect on MF filtrate water quality. For any given capacity, membrane area requirements are decreased, and power requirements are increased when membranes are operated at constant flux rather than at constant pressure.

Despite greater NF fouling rates, life cycle costs for membrane facilities appear to be reduced when membranes are operated at higher permeate fluxes and feedwater recoveries.

A mechanistic model was derived for direct flow microfiltration (MF), one which lends more insight into the factors that control MF performance compared to a statistical curve-fitting procedure that is often used to estimate chemical cleaning intervals at pilot-scale. This theoretical approach to MF fouling was based on fundamental feed water, membrane, and cake characteristics and was shown to predict well pilot-scale experimental specific flux profiles when backwash effectiveness is used as a fitting parameter. Long-term experimental specific flux profiles obtained during the constant flux filtration of natural colloidal materials are reported under conditions typical of water treatment applications. Cakes formed during the filtration of untreated surface waters were found to be highly resistant and compressible. Longer chemical cleaning intervals (and higher values of the backwash effectiveness parameter)were obtained during the constant flux filtration of natural colloidal materials by a decrease in flux, feed water turbidity, and/or backwash interval.

The disturbances in uniform creeping flow in the presence of an isolated porous floc are investigated theoretically. Using the Carman-Kozeny equation, the floc permeability is related to its fractal dimension, D . Fluid streamlines, drag coefficient and the fluid collection efficiency of porous aggregates are expressed in terms of D . As D increases, for a fixed packing factor and ratio of primary particle radius to floc radius, the permeability is found to decrease and the fluid mechanics resembles more closely that of an isolated impermeable sphere. As a simplification, it is suggested that a rectilinear model for flow up to an impervious sphere may be a reasonable approximation for aggregate-aggregate and particle-aggregate interactions if D ≲ 2 . Curvilinear models for flow up to an impervious sphere may be accurate approximations for interactions involving aggregates with higher fractal dimensions D ≳ 2.3 .

Artificial neural network (ANN) models were developed to predict disinfection by-product (DBP) formation during municipal drinking water treatment using the Information Collection Rule Treatment Studies database complied by the United States Environmental Protection Agency. The formation of trihalomethanes (THMs), haloacetic acids (HAAs), and total organic halide (TOX) upon chlorination of untreated water, and after conventional treatment, granular activated carbon treatment, and nanofiltration were quantified using ANNs. Highly accurate predictions of DBP concentrations were possible using physically meaningful water quality parameters as ANN inputs including dissolved organic carbon (DOC) concentration, ultraviolet absorbance at 254nm and one cm path length (UV(254)), bromide ion concentration (Br(-)), chlorine dose, chlorination pH, contact time, and reaction temperature. This highlights the ability of ANNs to closely capture the highly complex and non-linear relationships underlying DBP formation. Accurate simulations suggest the potential use of ANNs for process control and optimization, comparison of treatment alternatives for DBP control prior to piloting, and even to reduce the number of experiments to evaluate water quality variations when operating conditions are changed. Changes in THM and HAA speciation and bromine substitution patterns following treatment are also discussed.

Particle transport in crossflow membrane filters is the result of complex interactions originating from module hydrodynamics, suspension chemistry and external forces. Experimental and theoretical investigations of particle transport in dilute suspensions were conducted in a laboratory model membrane filter to understand fundamental aspects of macrocolloidal transport. Particle residence time distributions (RTDs) were obtained experimentally under varying hydrodynamic conditions in the filter by making pulse inputs. Under conditions of laminar flow, particle transport can be divided into two regimes: convection dominated and diffusion dominated. Convective transport is described quantitatively by theories of particle mechanics as evidenced by correlations presented regarding the first passage time as well as the peak response. Diffusive transport is demonstrated by multiple peaks in the RTDs under existing experimental conditions. Understanding these transport processes can lead to a more rational design, selection and operation of membrane systems and pre-treatment options.

Particle transport and deposition studies in laminar cross-flow membrane filtration are reported. Particle residence time distributions (RTDs) in experimental conditions typical of ultra- and microfiltration are compared with theoretical predictions incorporating the effects of hydrodynamic, Coulombic, electrodynamic, and external gravity forces. Numerical simulations show that, for a given flow field, mechanisms controlling lateral migration in the far-field region in membrane afters depend primarily on inertial, gravity, and permeation drag forces. The theory accurately predicts first passage times and multimodal RTDs under conditions of high membrane permeability and fast axial flows.

Extracellular polymeric substances (EPS) secreted by suspended cultures of microorganisms from an activated sludge plant in the presence of glucose were characterized in detail using colorimetry, X-ray photoelectron spectroscopy (XPS) and Fourier transform infrared (FTIR) spectroscopy. EPS produced by the multi-species community were similar to literature reports of pure cultures in terms of functionalities with respect to C and O but differed subtly in terms of N and P. Hence, it appears that EPS produced by different microorganisms maybe homologous in major chemical constituents but may differ in minor components such as lipids and phosphodiesters. The role of specific EPS constituents on microbial aggregation was also determined. The weak tendency of microorganisms to bioflocculate during the exponential growth phase was attributed to electrostatic repulsion when EPS concentration was low and acidic in nature (higher fraction of uronic acids to total EPS) as well as reduced polymer bridging. However, during the stationary phase, polymeric interactions overwhelmed electrostatic interactions (lower fraction of uronic acids to total EPS) resulting in improved bioflocculation. More specifically, microorganisms appeared to aggregate in the presence of protein secondary structures including aggregated strands, beta-sheets, alpha- and 3-turn helical structures. Bioflocculation was also favored by increasing O-acetylated carbohydrates and overall C-(O,N) and O=C-OH+O=C-OR functionalities.

A simple, closed-form analytical expression based on the homogenous solution diffusion model is derived for contaminant removal during nanofiltration (NF) of ground and surface water. Solute permeation and back-diffusion coefficients were used as fitting parameters to model rejection characteristics of four thin-film composite NF membranes under conditions typical of drinking water NF. Nonlinear fits of the model to experimental data suggests that the United States Environmental Protection Agency's (USEPA)'s Information Collection Rule protocol for bench-scale studies could be improved to obtain greater precision of the mass transfer coefficients. The model was found to fit rejection data for several water treatment contaminants including total organic carbon, precursors to total organic halide, four trihalomethanes and nine haloacetic acids containing chlorine and bromine, calcium and total hardness, alkalinity and conductivity. The simplified approach to mass transfer calculations from multisolute systems suggests that feed water recovery has a stronger influence on contaminant rejection than permeate flux. Evidence for coupled transport of divalent inorganic ions is also presented. Even though the model developed does not account for ion coupling and cannot be applied in a purely predictive mode, it can assist in the better design and interpretation of data obtained from site-specific pilot-scale water treatment NF studies conducted in support of plant design.