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The reduction of energy consumption in the reverse osmosis (RO) process is critical. The forward osmosis (FO)-RO hybrid process can be suggested to reduce RO energy consumption. In this study, a numerical FO-RO process model was developed to analyze the FO-RO hybrid process. The performance of the FO-RO hybrid process was compared with the stand-alone RO process. In addition, the impacts of the control parameters for operation, and the intrinsic membrane parameters, were analyzed using sensitivity analysis. In conclusion, the FO-RO hybrid process involves less RO energy consumption than the stand-alone RO process. The FO draw flow velocity and the RO applied pressure were derived as the major factors for controlling the FO-RO process. In addition, the control parameters for operation were found to be more important than the intrinsic membrane parameters in the minimization of RO energy consumption. Subsequently, the FO elements installed in front of the RO process should be configured with a parallel connection, in order to minimize RO energy consumption. The results in this study could be used to develop guidelines for the optimal design of the FO-RO hybrid process.

Despite many kinds of research on pressure-retarded osmosis (PRO), feasibility studies for PRO are still insufficient. To provide a better understanding of PRO-hybridized processes, an energy efficiency analysis should reflect the hybridization features of three processes, including PRO, seawater reverse osmosis (SWRO), and membrane distillation (MD). To this end, a new dimensionless (i.e., unitless or scale-free) performance index is proposed to facilitate a fair comparison of energy efficiency between SWRO-PRO and SWRO-MD-PRO. The new performance index physically implies a ratio of the total energy recovered by PRO to the total energy consumed by SWRO and MD. The performances of hybridized processes were estimated with the new index and compared to each other after running several simulations. The simulation results showed that SWRO-MD-PRO generally has a higher energy efficiency than SWRO-PRO if an inexpensive heat source, such as waste heat, is used. However, the energy efficiencies of both PRO-hybridized processes were different according to the simulation conditions. Therefore, it can be concluded that energy optimization for PRO-hybridized processes should be conducted differently than for SWRO. The results from this study are expected to play a key role in providing a new roadmap for PRO-hybridized process research.

Climate change is a primary driver that alters water pollution hotspots in watersheds, which complicates the use of Best management practices (BMPs) for diffuse pollution mitigation strategies. The objective of this study is to evaluate future changes in BMPs on total phosphorus (TP) loads to the river system, depending on climate change. Current weather data were collected from 2000 to 2010 and future weather data from 2040 to 2050 were obtained from regional climate model simulations based on Representative Concentration Pathways (RCP) 2.6, 4.5, and 8.5 scenarios. This study describes various BMP implementation plans at affordable cost that are adapted to different weather conditions, current (for 2000–2010) and future climate scenarios (for 2040–2050). The Soil and Water Assessment Tool (SWAT), i.e., one of the deterministic models for watershed management, was used to estimate total phosphorus (TP) removal efficiency of various types of BMP at two crop fields (rice paddy and soybean fields) in the Yeongsan River (YR) watershed of Korea. The Non-dominated Sorting Genetic Algorithm II (NSGA-II), i.e., one of the artificial intelligence (AI) models for decision support framework, was applied to obtain allow for trade-off analysis between two conflict objectives, the maximum TP load reduction against implementation costs. The SWAT simulation results showed that the model performance based on the Nash-Sutcliffe efficiency and percent bias was acceptable for simulating three parameters; daily flow discharge, monthly sediment loads, and TP loads in the river. As a result, monthly sediment loads and TP loads increase remarkably under all future climate change scenarios except for July, when a comparable amount of precipitation is recorded during the present and future conditions. New implementation of BMPs, therefore, will be required for future climate change scenarios to achieve 50% TP load reduction in the given watershed condition. Interestingly, parallel terraces which showed good efficiency in reducing TP loads at both fields under the current weather condition cannot be effective any more under the worst-case weather scenario in the future climate. In such a case, detention ponds can be proposed as BMP alternative to parallel terraces. Overall, this study not only demonstrates that watershed management plans using BMPs should be adjusted according to climate change scenarios, but also that the hybrid use of SWAT model and AI can help in refining existing and future BMPs at affordable cost.

Despite a growing awareness of the problems associated with cyanobacterial blooms in rivers, and particularly in regulated rivers, the drivers of bloom formation and abundance in rivers are not well understood. We developed a Bayesian hierarchical model to assess the relative importance of predictors of summer cyanobacteria abundance, and to test whether the relative importance of each predictor varies by site, using monitoring data from 16 sites in the four major rivers of South Korea. The results suggested that temperature and residence time, but not nutrient levels, are important predictors of summer cyanobacteria abundance in rivers. Although the two predictors were of similar significance across the sites, the residence time was marginally better in accounting for the variation in cyanobacteria abundance. The model with spatial hierarchy demonstrated that temperature played a consistently significant role at all sites, and showed no effect from site-specific factors. In contrast, the importance of residence time varied significantly from site to site. This variation was shown to depend on the trophic state, indicated by the chlorophyll-a and total phosphorus levels. Our results also suggested that the magnitude of weir inflow is a key factor determining the cyanobacteria abundance under baseline conditions.

In this study, Internally Staged Design (ISD) was numerically optimized in order to demonstrate the long-term performance of full-scale seawater reverse osmosis (SWRO) membrane systems in the presence of colloidal foulants. To this end, a numerical model based on a finite difference method was developed and optimized with various feed water qualities, such as fouling potential and total dissolved solids (TDS). As a result, the optimized ISD exhibited greater water flux and higher energy efficiency in long-term operation (90 days) compared to conventional designs, where single-type membrane elements were employed over a pressure vessel while achieving potable TDS concentration in permeate (

The presence of flow control devices and/or obstacles in the fluid flow such as baffles and spacers complicates the solid-fluid mixing pattern, which remains difficult to describe by classical analytical solutions. In this study, the removal of fine particles in a tertiary sedimentation tank mounting an adjustable baffle was investigated using the computational fluid dynamics code-COMSOL. The solid-fluid motion was solved by consecutively applying the equations of the continuity and momentum using the finite element method. The experiment was conducted by the sedimentation tank with the adjustable baffle inclined at 30° in a pilot scale plant. It's used as the reference data set for numerical simulations that were run on a 2-dimensional domain by modifying the configuration settings of angles for an adjustable baffle (i.e., 30°, 45°, and 60°) and without one. Results showed that the simulation results matched well with the experimental data for an adjustable baffle at 30° (NSE=0.97). The sedimentation tank with the adjustable baffle at different angles had a lower overflow rate (in the area of flow rebound) and mixing intensity (in the area of flow curve) than without one, eventually leading to enhanced particle removal efficiency. This tendency became more pronounced as the particle motion stabilized over time. The sedimentation tank mounting the adjustable baffle at 30° provided the best settling efficiency among the four different flow patterns. However, the conventional index that represents the mixing properties did not correctly address their relative efficiency for fine particle removal. Therefore, a numerical simulation tailored to a given geometry should be conducted to fully elucidate the fluid dynamics in the sedimentation tank with complex devices or obstacles.

Since the early 2000s, pressure retarded osmosis (PRO) has been continuously investigated, based on its potential to harvest energy from a salinity gradient. However, recent negative reports on its fundamental feasibility and the closure of the largest industrial implementation have slowed its momentum, with regard to its commercialization. In this respect, this review provides insights into the current status of PRO technologies in membrane fabrication, module design, process optimization, and industrial movements for the commercialization of PRO. Notably, despite dramatic advancements in lab-scale PRO membrane performance, recent modeling studies have revealed advanced membrane properties have only a minor impact on PRO performance. In contrast, developing PRO module designs are deemed to have paramount importance, due to the drastically low module performance compared to lab-scale membrane performance, and high potential of design modification to resolve inefficient PRO module structures. Various simulation methods for optimizing PRO processes using the classic mass transfer model, thermodynamics, and machine learning optimizations are comparatively analyzed. Integrations of seawater reverse osmosis and PRO and other hybrid processes with PRO are discussed in terms of recent pilot-scale implementations and modeling results. Finally, small and large industrial movements and projects for PRO commercialization are analyzed in detail, based on their quantitative outcomes.

Bacteria are a primary contaminant in natural surface water. The instream concentration of fecal coliform, a potential indicator of pathogens, is influenced by meteorological conditions and land-use characteristics. However, the relationships between these conditions and fecal coliforms are not fully understood. Furthermore, the sources of large variability in fecal coliform counts, e.g., temporal or spatial sources, remain unexplained, especially at large scales. This study proposes the use of Bayesian overdispersed Poisson models, whereby the combined effects of temperature, rainfall, and land-use characteristics on fecal coliform concentration are quantified with predictive uncertainty, and the sources of variability in fecal coliform concentration are assessed. The models were developed using 8-year weekly observations of fecal coliforms obtained from the Wachusett Reservoir watershed in Massachusetts, USA. The results highlight the importance of interactions among meteorological and land-use characteristics in controlling the instream fecal coliform concentration; the increase in fecal coliform concentration with temperature increase was more drastic when rainfall occurred. Also, the responses of fecal coliforms to temperature increases were more pronounced in forest-dominated than in urban-dominated areas. In contrast, the fecal coliform concentration increased more rapidly with rainfall increases in urban-dominated than in forest-dominated areas. The models also demonstrate that among the sources of variability, the monthly component made the most significant contribution to the variability in fecal coliform concentrations. Our results suggest that seasonally dependent processes, including surface runoff, are critical factors that regulate fecal coliform concentration in streams.

© 2016 Elsevier B.V. In this study, colloidal fouling behavior in pressure retarded osmosis (PRO) was systematically investigated in terms of the effects of draw solution concentration, applied hydraulic pressure at the draw side, feed solution pH, and particle size. Commercially-available cellulose triacetate (CTA) membranes were fouled with feed solution containing silica colloidal particles. Two different silica particles with mean diameter of 27 and 152 nm were used as model foulants. Our findings demonstrated that the colloidal fouling in PRO was dominantly affected by the cake layer buildup at the membrane surface. Fouling was further exacerbated by diffused salts from the draw side because retained salts within the cake layer elevated the salt concentration on the membrane surface, and consequently reduced the driving force of PRO. Substantial flux decline with the smaller particles was attributed to the high cake layer resistance due to the formation of the void-less cake layer. In addition, our approaches to mitigate the colloidal fouling revealed that the hydraulic cleaning by increasing the cross-flow rates was not effective to eliminate the compact cake layer. However, adjusting the feed solution pH showed the high potential to relieve the colloidal fouling resulting from the more stabilization of particles at low solution pH.

Fecal coliforms are indicators of pathogens and thereby, understanding of their fate and transport in surface waters is important to protect drinking water sources and public health. We compiled fecal coliform observations from four different sites in the USA and Korea and found a seasonal variability with a significant connection to temperature levels. In all observations, fecal coliform concentrations were relatively higher in summer and lower during the winter season. This could be explained by the seasonal dominance of growth or die-off of bacteria in soil and in-stream. Existing hydrologic models, however, have limitations in simulating the seasonal variability of fecal coliform. Soil and in-stream bacterial modules of the Soil and Water Assessment Tool (SWAT) model are oversimplified in that they exclude simulations of alternating bacterial growth. This study develops a new bacteria subroutine for the SWAT in an attempt to improve its prediction accuracy. We introduced critical temperatures as a parameter to simulate the onset of bacterial growth/die-off and to reproduce the seasonal variability of bacteria. The module developed in this study will improve modeling for environmental management schemes.

A performance analysis of a tri-combined process that consists of reverse osmosis (RO), membrane distillation (MD), and pressure-retarded osmosis (PRO) was conducted by using numerical approaches in order to evaluate its feasibility. In the hybrid process, the RO brine is partially used as the MD feed solution, and the concentrated MD brine is then mixed with the rest of the RO brine to be considered as the PRO draw solution. Here, the brine division ratio, incoming flow rate of RO, dimensions of the MD and PRO processes, and the supply cost of the MD heat source were considered as influential parameters. Previously validated process models were employed and the specific energy consumption (SEC) was calculated to examine the performance of the RO–MD–PRO hybrid process. The simulation results confirmed that the RO–MD–PRO hybrid process could outperform stand-alone RO in terms of reducing the SEC and the environmental footprint by dilution of the RO brine in locations where free or low-cost thermal energy can be exploited. Despite the need for further investigations and pilot-tests to determine its commercial practicability, this study provides insights into future directions for water and energy nexus processes for energy efficient desalination.

The pressure retarded osmosis (PRO) process has been considered as an alternative and renewable technology to generate electricity from mixing two solutions of different salinities. However, improving the osmotic performance of semi-permeable membrane is still a major challenge in the PRO system. Therefore, thin-film nanocomposite (TFN) membrane was synthesized by using carbon nanotubes (CNT)-embedded-polyethersulfone (PES) supporting layer and polyamide active layer in this study. The prepared membranes were further employed in the PRO process to harvest energy from saline water. The water flux increase of the TFN membrane was promoted by CNT-induced porosity and the hydrophilicity of the support layer as well as by the chemical etching of the active layer. The water flux and maximum power density of the developed TFN membrane was found to be 87% (averaged from 2 bar to 10 bar) and 110% greater than for bare thin-film composite (TFC) membranes, respectively. Furthermore, the TFN membrane preparation could easily be scaled up using conventional fabrication methods with less than 2% additional material cost. Therefore, this finding could contribute to the commercialization of sustainable energy generation by utilizing the tremendous potential of fresh- and salt-water mixing.

Summary To control algal blooms, the stressor–response relationships between water quality metrics, environmental variables, and algal growth need to be better understood and modeled. Machine-learning methods have been suggested as means to express the stressor–response relationships that are found when applying mechanistic water quality models. The objective of this work was to evaluate the efficiency of regression trees in the development of a stressor–response model for chlorophyll-a (Chl-a) concentrations, using the results from site-specific mechanistic water quality modeling. The 2-dimensional hydrodynamic and water quality model (CE-QUAL-W2) model was applied to simulate water quality using four-year observational data and additional scenarios of air temperature increases for the Yeongsan Reservoir in South Korea. Regression tree modeling was applied to the results of these simulations. Given the well-expressed seasonality in the simulated Chl-a dynamics, separate regression trees were developed for months from May to September. The regression trees provided a reasonably accurate representation of the stressor–response dependence generated by the CE-QUAL-W2 model. Different stressors were then selected as split variables for different months, and, in most cases, splits by the same stressor variable yielded the same correlation sign between the variable and the Chl-a concentration. Compared to physical variables, nutrient content appeared to better predict Chl-a responses. The highest Chl-a temperature sensitivities were found for May and June. Regression tree splits based on ammonium concentration resulted in a consistent trend of greater sensitivity in the groups of samples with higher ammonium concentrations. Regression tree models provided a transparent visual representation of the stressor–response relationships for Chl-a and its sensitivity. Overall, the representation of relationships using classification and regression tools can be considered a useful approach to assess the state of aquatic ecosystems and effectively determine significant stressor variables.

When stormwater runoff flows into a constructed wetland, the water level changes inside, and the volume of the wetland changes accordingly. In this study, the relationship between pollutant removal and water depth flowrate changes was analyzed with velocity phase analysis, using the concepts of horizontal velocity and vertical velocity. A constructed wetland located in an agricultural area was used for the velocity phase analysis. Analysis results revealed that all four ponds and Phases I and III accounted for over 90% of the pollutant load. In particular, Phase III, where vertical and horizontal velocities were reduced, was responsible for approximately twice the load on average. The reason for the highest load in Phase III was due to the inflow of contaminants into the constructed wetland through the first flush effect occurred at the time when the flow rate decreased due to the difference in runoff strength. Therefore, it is necessary to maximize Phases I and III in the velocity phase when designing multi-stage wetlands to make the flow of water more natural. Furthermore, considering pollutant load levels, a design review is needed to expand the size of downstream wetlands, so that they can optimize water quality management functions.

The presence of the spacer and biofilm can accompany the high complexity of the mass and momentum transport in an osmotic backwash (OBW) process of reverse osmosis (RO) membranes. For more reliable simulations, it would be essential to consider such highly complex transport phenomena across the membranes and through membrane flow channels. Therefore, we simulated the effects of spacer designs, hydrodynamic, and membrane properties on OBW in the scenario of biofouling on RO membrane surfaces. To this end, the OBW process was numerically modeled in two-dimensional spacer-filled crossflow channels based on the finite element method. Subsequently, the concentration and velocity fields inside of the membrane, biofilm, and flow channels were analyzed. Results showed that the submerged spacer could enhance the water and salt mass transfer in the membrane channel, to a greater extent than the cavity and zigzag spacers, which can ultimately enhance the OBW efficiency for a foulant removal. Additionally, the OBW performance is chiefly impacted by the structure parameter of the porous support layer. Also, the existence of biofilm in the feed channel can render the feed concentration and membrane water permeability more sensitive to the OBW process than the non-fouled channel.

Of growing amount of food waste, the integrated food waste and waste water treatment was regarded as one of the efficient modeling method. However, the load of food waste to the conventional waste treatment process might lead to the high concentration of total nitrogen (T-N) impact on the effluent water quality. The objective of this study is to establish two machine learning models-artificial neural networks (ANNs) and support vector machines (SVMs), in order to predict 1-day interval T-N concentration of effluent from a wastewater treatment plant in Ulsan, Korea. Daily water quality data and meteorological data were used and the performance of both models was evaluated in terms of the coefficient of determination (R2), Nash-Sutcliff efficiency (NSE), relative efficiency criteria (drel). Additionally, Latin-Hypercube one-factor-at-a-time (LH-OAT) and a pattern search algorithm were applied to sensitivity analysis and model parameter optimization, respectively. Results showed that both models could be effectively applied to the 1-day interval prediction of T-N concentration of effluent. SVM model showed a higher prediction accuracy in the training stage and similar result in the validation stage. However, the sensitivity analysis demonstrated that the ANN model was a superior model for 1-day interval T-N concentration prediction in terms of the cause-and-effect relationship between T-N concentration and modeling input values to integrated food waste and waste water treatment. This study suggested the efficient and robust nonlinear time-series modeling method for an early prediction of the water quality of integrated food waste and waste water treatment process.

Chlorophyll-a (Chl-a) is a direct indicator used to evaluate the ecological state of a waterbody, such as algal blooms that degrade the water quality in lakes, reservoirs and estuaries. In this study, artificial neural network (ANN) and support vector machine (SVM) were used to predict Chl-a concentration for the early warning in the Juam Reservoir and Yeongsan Reservoir, which are located in an upstream region (freshwater reservoir) and downstream region (estuarine reservoir), respectively. Weekly water quality data and meteorological data for a 7-year period were used to train and validate both the ANN and SVM models. The Latin-hypercube one-factor-at-a-time (LH-OAT) method and a pattern search algorithm were applied to perform sensitivity analyses for the input variables and to optimize the parameters of the two models, respectively. Results revealed that the two models well-reproduced the temporal variation of Chl-a based on the weekly input variables. In particular, the SVM model showed better performance than the ANN model, displaying a higher prediction accuracy in the validation step. The Williams-Kloot test and sensitivity analysis demonstrated that the SVM model was superior for predicting Chl-a in terms of prediction accuracy and description of the cause-and-effect relationship between Chl-a concentration and environmental variables in both the Juam Reservoir and Yeongsan Reservoir. Furthermore, a 7-day interval was determined as an efficient early warning interval in the two reservoirs. As such, this study suggested an effective early-warning prediction method for Chl-a concentration and improved the eutrophication management scheme for reservoirs.

Blocking the natural bi-directional flow in an estuarine system using an artificial dyke has commonly caused serious water quality problems. In the southwestern part of South Korea, a parallel triple-reservoir system was constructed by blocking the mouth of three different rivers (Yeongsan, Okcheon, and Kumja), which were then interconnected using two open channels. This system has experienced a deterioration in water quality due to pollutants accumulated from the upper watershed, and has continually discharged pollutant loads to the outer ocean. Therefore, the objective of this study is to establish an effective dam operation plan for reducing nutrient loads released from the integrated reservoir. In this study, the CE-QUAL-W2 model, which is a 2-dimentional hydrodynamic and water quality model, was applied to predict the pollutant load released from each reservoir in response to different flow scenarios for the interconnecting channel. The model was calibrated using two novel methods: a sensitivity analysis to determine meaningful model parameters, and a pattern search to optimize the parameters. From the scenario analysis using flow control, it was determined that the total nitrogen (TN) and total phosphorus (TP) loadings could be reduced by 27.2% and 6.6%, respectively, under the optimal channel flow scenario by regulating the chlorophyll-a concentration in the reservoir. The results confirm that effective dam operation could contribute to a decrease in pollutant loads in the receiving seawater body. As such, this study suggests operational strategies for a multi-reservoir system that can be used to reduce the nutrient load being discharged from reservoirs.

A hybrid forward osmosis (FO)/crystallization/reverse osmosis (RO) process for seawater desalination was proposed, and the theoretical analysis of the process was conducted. When the FO unit is considered as the main desalination unit, the crystallization and RO units can be regarded as a draw solute recovery process. First, in the FO process, fresh water is extracted from seawater and permeates into draw solution. This diluted draw solution is cooled down in the crystallization process and the draw solute is precipitated up to the saturation at low temperature. As a result, the feed stream of the RO process has lower concentration, and consequently, total energy consumption is expected to be reduced. In order to apply the proposed process in practice, the selection of suitable draw solute should be carefully determined. In the present work, five substances were suggested as draw solutes in the proposed system: ammonium oxalate, ammonium aluminum sulfate, sodium periodate, sodium phosphate and sodium sulfate. Based on properties of the substances, total energy consumption was analyzed for each draw solute. The total energy was calculated by the sum of cooling energy in crystallization process and pumping energy in RO process. Through the hybridization of these three unit processes, the energy requirement for fresh water production can be reduced to 2.15 kW h/m3. Thus, it is concluded that the proposed process can be highly competitive.

We conducted a scenario study on a promising RO–PRO hybrid system to alleviate water and energy demands. We utilized a previously validated reverse osmosis (RO) process model and modified a model of a pressure-retarded osmosis (PRO) process to properly consider the spatial distribution of concentration and velocity based on a mass balance principle. Using the models, we compared four different RO–PRO hybrid configurations based on the water and energy return rate (WERR). Subsequently, the comparison of the water production rate and energy production rate confirmed the results that RO plays a dominant role to determine the WERR value. Hybrid systems that use seawater as a feed water for RO are more energy price sensitive. That is, a decrease in the RO plant size considerably diminishes the WERR values; however, the PRO plant size plays a minor role to determine the WERR value. Research and available literature on RO–PRO hybrid processes are in a relatively early stage; this study is a preliminary step to evaluate further advances in hybrid systems that can eventually alleviate water and energy demands.

A thorough investigation of membranes as well as their transport and material properties is a key to understanding the governing principles and unresolved issues of membrane processes. Through molecular dynamics (MD) simulations, static and dynamic properties of membrane separation systems may be investigated on a molecular level. By reviewing over 70 articles, this paper aims to highlight the usefulness of applying molecular dynamics in membranes (MDM) in order to broaden our knowledge of membrane-based water treatment processes. Here, the theoretical foundations of classical MD are described together with the results that are obtainable from MDM simulations. By compiling results from published works, we emphasize the ability of MD to determine membrane transport and material properties from simulations. The authors conclude by suggesting the further use of MDM for prospective research areas pertaining to membrane-based water treatment processes.

A numerical model for predicting the flux decline due to colloidal fouling was developed for a forward osmosis (FO) membrane system. We derived the kinetic equation of the cake layer growth based on a first-order reaction and control volume approach. Based on the model simulation, it was found that the deposited particles on a membrane surface are proportional to the feed concentration and the permeate flux. Moreover, the simulation result reveals that the cake-enhanced osmotic pressure (CEOP) is a key factor diminishing the permeate flux for large colloidal foulants. For small colloidal foulants, the hydraulic resistance of the cake layer is dominant in flux decline at the beginning of the fouling and CEOP increasingly become significant as fouling progresses. The effects of the reverse draw solute permeation on the flux decline were also simulated. Interestingly, the increased reverse draw solute permeation obtained by increasing the solute permeability showed little effect on the flux decline. Contrarily, variation of the diffusivity significantly influenced the flux decline. Consequently, the numerical model developed in this paper suggests that the selection of draw solute for an FO membrane process should be carefully regarded, along with the fouling mechanism.

Understanding the mass transfer in membrane separation processes plays a crucial role in improving the process performance. In this study, we numerically scrutinized the impacts of spacers—a structure enhancing the mass transfer in the vicinity of the membrane—on the concentration polarization (CP) in a forward osmosis (FO) process. To quantitatively measure the extent of CP, we introduce a concentration polarization index (CPI), which is proportional to the degree of CP and inversely proportional to the permeate flux. Based on the CPI, we simulated the impact of spacers on FO performance at various concentration conditions and found that the FO spacers generally reduce the extent of the CP; subsequently, this shows that FO spacers are important factors for the advancement of FO technology. In FO processes it was found that the boundary layer compression is more efficient for diminishing the CP than the boundary layer disruption, whereas the disruption mechanism was more successful in alleviating the CP in reverse osmosis (RO) processes. This contradiction was subsequently attributed to the intrinsic characteristics of the boundary layer disruption, which inevitably caused a dead zone near the spacer attachment and thereby boosted the CP in the FO process. Moreover, it was observed that spacers in feed channels increase the CP even when the concentration of the feed solution is zero, unless the membrane completely rejects salt, because any solute penetrating through the active layer of the membrane by a reverse diffusion mechanism accumulates near the spacer attachment. Hence, it is crucial to minimize the adverse impacts of FO spacers to maximize the beneficial effects of spacers to decrease the CP and improve the performance of FO processes.

A fouling model for the seawater reverse osmosis (SWRO) process is required to propose an appropriate strategy for membrane maintenance (i.e., membrane cleaning and replacement). In this study, a fouling model that considered the concentration polarization was properly developed to simulate the long-term performance of the SWRO process based on models from the literature. The model was practically applied to one-year operation data obtained from the Fujairah SWRO desalination plant with parameter estimation, and good agreement between the measured data and simulated results was obtained for both the rejection and recovery rates. Compared to an integrated model consisting of two models from the literature, the fouling model proposed in this study showed reliable performance for membrane fouling such as the increase in the permeate TDS concentration according to operating time. In addition, simulations for membrane maintenance were conducted based on the variation in membrane resistance, which reflects the fouling state of the membrane. These revealed that the rearrangement of membranes is not significantly effective without cleaning the fouled membrane. Instead, a partial replacement of membranes can be an effective maintenance scheme to increase the recovery rate. Accordingly, the results of the study presented here can be used to save operation and maintenance (O&M) costs in SWRO plants through the optimized management of fouled membranes.

The forward osmosis process is considered a promising desalination method due to its low energy requirement compared to other methods. In this study, modelling and simulations for a plate-and-frame and a modified spiral-wound module are carried out for the FO process. The mathematical models consist of mass balance, a permeate flux model, and concentration polarization equations. The plate-and-frame model is formulated with consideration of flow directions, and the modified spiral-wound model is formulated with consideration of its geometric characteristics. These two sets of model equations are numerically and iteratively integrated since they are implicit and highly non-linear. The simulation for both modules was conducted by varying 4 types of operating conditions: volumetric flow rate of the feed and the draw solution, the concentration of the draw solution, flow direction, and the membrane orientation. The results for various conditions are also compared. In future research, the developed model could be applied for designing FO modules and finding optimal operating conditions.

Performance of forward osmosis (FO) process is significantly affected by factors such as membrane properties, concentration polarization (CP), and fouling. In this study, FO performance of a plate and frame type membrane is investigated via a numerical simulation based on mass conservation theorem. To evaluate the FO membrane performance, permeate flux and recovery rate are simulated according to membrane orientation, flow direction of feed and draw solutions, flow rate, and solute resistivity (K). In the case of membrane orientation, all-inside case, in which the draw solution faces the active layer, displays a relatively higher performance than all-outside and all-up cases. Notably, the membrane performance is highly affected by K indicating the extent of the internal CP. During the simulation approach, the spatial variation of the concentration profile was observed on a 2-dimensional membrane area; it was expected to cause a high diffusion load on a particular area of membrane, due to the relatively higher flux at that location. Moreover, it can result in unexpected fouling in a specific area on a membrane. Accordingly, the findings in this study suggest that the numerical simulation can be applied to optimize both physical properties and operation conditions, thereby ensuring cost-effective operation of FO processes.

Mo–N/Cu films were deposited on silicon and steel substrates by inductively coupled plasma sputtering using Mo–Cu alloy targets having different Cu concentrations. The structure and mechanical properties of the Mo–N/Cu films were investigated. The (200)-oriented γ-Mo2N–Cu films were obtained at a nitrogen flow rate higher than 1.5 sccm, whereas metallic films were deposited at a nitrogen flow rate lower than 1 sccm. Cu contents in the films increased from 3 at.% to 8 at.% with corresponding increase in Cu concentrations in the target from 5 at.% to 20 at.%. Hardness of the films varied between 19 and 35 GPa as the Cu concentration and nitrogen flow rate were changed. HRTEM and XPS analyses showed that Mo–N/Cu films consisted of γ-Mo2N grains lower than 10 nm in size and a copper amorphous phase. The minimum value of coefficient of friction (CoF) of the films was 0.17 when the film tested by alumina ball.

The membrane structure parameter (S) is an intrinsic membrane parameter used to determine the degree of internal concentration polarization (ICP) in the porous support structure of forward osmosis (FO) membranes, and is crucial in evaluations of FO membrane performance. Although S values only depend on membrane properties, and should be close to a constant value, experiments to determine the S values produce various values, which vary with respect to the concentrations of the feed and draw solutions. In this study, we develop a numerical model based on the finite element method (FEM) to determine a constant membrane structure parameter. In contrast to other FO models, the developed model successfully simulates the performance of FO processes, and maintains a consistent S value. Here, the most influential factor causing inconsistent S values is found to be the assumption that the ratio of concentrations is approximately identical to the ratio of osmotic pressures, as is frequently used in FO modeling due to lack of availability of concentration profiles at the active layer–support layer interface. However, use of a constant diffusion coefficient had little influence on either the simulation result or the S value consistency.

Summary Escherichia coli release from streambed sediments may substantially affect microbial water quality. Models of E. coli release and transport commonly use a single set of parameters for the whole stream or reservoir, yet little is known about the magnitude and sources of the variability of parameters of the streambed bacteria release. The objectives of this work were: (a) to obtain and compare parameters of streambed E. coli resuspension in three stream reaches with distinctly different bottom sediment textures, and (b) to see whether the modeling of streambed E. coli resuspension with reach-specific parameters could provide substantially better accuracy than modeling with a single set of parameters. Sediment particle size distributions and the streambed E. coli concentrations were measured along a first-order creek in the USDA-ARS OPE3 experimental watershed in Maryland. Afterwards, 80 m3 of water were released into the creek at a rate of 60 L per second in four equal allotments separated by 1–3 min intervals. Flow rates and E. coli concentrations were monitored with automated samplers at the ends of the three reaches with a total length of 630 m. A high concentration of streambed E. coli (“hotspot”) resuspended within the first reach caused a pulse of high E. coli concentrations that propagated along the creek without substantial attenuation; inputs of sediment-borne E. coli from the next two reaches were relatively small. The E. coli transport model included one-dimensional Saint–Venant and advective–dispersive equations. The calibrated roughness coefficient values were comparable for the three reaches, whereas the critical stress and the entrainment rate differed among reaches by a half order and an order of magnitude, respectively. Overall, better accuracy was observed when the model contained reach-specific parameters. Additional research is needed to understand which and how sediment properties affect parameters of streambed E. coli release into the water column.

The spread of antibiotics resistance among bacteria is a threat to human health. Since South Korea uses approximately 1.5 times more antibiotics than do other OECD countries, this is likely to impact the numbers and types of antibiotic-resistant bacteria found in the environment. In this study we examined feces from domesticated animals and humans for the diversity and abundance of antibiotic-resistant Escherichia coli. Abundant antibiotic-resistant E. coli were isolated from all the tested animals and humans and were examined by horizontal, fluorophore-enhanced, rep-PCR (HFERP) DNA fingerprint analysis. A total of 793 unique, non-clonal, E. coli isolates were obtained from the 513 human and animal hosts examined. Antibiotic resistance analysis, done using 14 antibiotics, indicated that 72.3% of the isolates (573 of 793) were found resistant to more than one antibiotic. The E. coli isolated from swine were resistant to the greatest number of antibiotics. Tetracycline resistant E. coli were routinely isolated from all animal hosts (36 to 77% per host), except for dairy cattle (9.3%). Twenty nine E. coli isolates from all hosts, except for duck, were resistant to more than 10 antibiotics. Gene transfer and southern hybridization studies revealed that resistance to 13 of the antibiotics was self-transmissible, and likely mediated by plasmids and integrons. Since genetically diverse and numerically abundant antibiotic-resistant E. coli were consistently recovered from chicken, swine and other domesticated animals in South Korea, our results suggest that the use of sub-therapeutic levels of antibiotics for disease prophylaxis and growth promotion should be curtailed.

This study reveals land-use factors that explain stream water quality during wet and dry weather conditions in a large river basin using two different linear models-multiple linear regression (MLR) models and constrained least squares (CLS) models. Six land-use types and three topographical parameters (size, slope, and permeability) of the watershed were incorporated into the models as explanatory variables. The suggested models were then demonstrated using a digitized elevation map in conjunction with the land-use and the measured concentration data for Escherichia coli (EC), Enterococci bacteria (ENT), and six heavy metal species collected monthly during 2007-2008 at 50 monitoring sites in the Yeongsan Watershed, Korea. The results showed that the MLR models can be a powerful tool for predicting the average concentrations of pollutants in stream water (the Nash-Sutcliffe (NS) model efficiency coefficients ranged from 0.67 to 0.95). On the other hand, the CLS models, with moderately good prediction performance (the NS coefficients ranged 0.28-0.85), were more suitable for quantifying contributions of respective land-uses to the stream water quality. The CLS models suggested that industrial and urban land-uses are major contributors to the stream concentrations of EC and ENT, whereas agricultural, industrial, and mining areas were significant sources of many heavy metal species. In addition, the slope, size, and permeability of the watershed were found to be important factors determining the extent of the contribution from each land-use type to the stream water quality. The models proposed in this paper can be considered useful tools for developing land cover guidelines and for prioritizing locations for implementing management practices to maintain stream water quality standard in a large river basin.

Gwangju Creek (GJC) in Korea, which drains a highly urbanized watershed, has suffered from substantial fecal contamination, thereby limiting the beneficial use of the water in addition to threatening public health. In this study, to quantitatively estimate the sinks and sources of fecal indicator bacteria (FIB) in GJC under varying meteorological conditions, two FIB (i.e., Escherichia coli and enterococci bacteria) were monitored hourly for 24 h periods during both wet and dry weather conditions at four sites along GJC, and the collected data was subsequently used to develop a spatiotemporal FIB prediction model. The monitoring data revealed that storm washoff and irradiational die-off by sunlight are the two key processes controlling FIB populations in wet and dry weather, respectively. FIB populations significantly increased during precipitation, with greater concentrations occurring at higher rainfall intensity. During dry weather, FIB populations decreased in the presence of sunlight in daytime but quickly recovered at nighttime due to continuous point-source inputs. In this way, the contributions of the key processes (i.e., irradiational die-off by sunlight, settling, storm washoff, and resuspension) to the FIB levels in GJC under different meteorological conditions were quantitatively estimated using the developed model. The modeling results showed that the die-off by sunlight is the major sink of FIB during the daytime in dry weather with a minor contribution from the settling process. During wet weather, storm washoff and resuspension are equally important processes that are responsible for the substantial increase of FIB populations.

This study focused on the analysis of As levels in human hair samples collected from six villages in the Kandal Province of Cambodia. Of interest were the influence of, and interactions among, certain factors affecting As intake into the human body: As concentrations in groundwater, period of groundwater consumption, age and gender. The results revealed As levels in human hair ranging from 0.06 to 30 μg g −1 with median and arithmetic mean values of 0.61 and 3.20 μg g −1 ( n = 68), respectively. Furthermore, a linear relationship was found between As concentrations in human hair and in the local groundwater. Arsenic (III) is the dominant species in Kandal groundwater, constituting in most cases at least 60% of the total As. Arsenic concentration ranged from 5 to 1543 μg L −1 , with the median value 348 μg L −1 and arithmetic mean 454 μg L −1 . In large rural, poor areas holding most of Kandal’s 1.1 million people, up to 2 in 1000 people are believed to be at risk of cancer through the As-enriched water they drink. A toxicity risk assessment provides a hazard quotient (HQ) equaling 5.12, also a clear indication of non-carcinogenic exposure risk. On the authors’ visit to Kampong Kong commune, Kandal Province, cases of arsenicosis were diagnosed in patients as a result of drinking As-enriched groundwater.

In the recent past, machine learning (ML) techniques such as artificial neural networks (ANN) or genetic algorithm (GA) have been increasingly used to model membrane fouling and performance. In the present study, we select genetic programming (GP) for modeling and prediction of the membrane fouling rate in a pilot-scale drinking water production system. The model used input parameters for operating conditions (flow rate and filtration time) and feed water quality (turbidity, temperature, algae pH). GP was applied to discover the mathematical function for the pattern of the membrane fouling rate. The GP model allows predicting satisfactorily the filtration performances of the pilot plant obtained for different water quality and changing operating conditions. A valuable benefit of GP modeling was that the models did not require underlying descriptions of the physical processes. GP has displayed the potential to evaluate membrane performance as a feed-forward simulator toward an “intelligent” membrane system.

Forward osmosis (FO) is an osmotic process that uses a semi-permeable membrane to effect separation of water from dissolved solutes by an osmotic pressure gradient. Unlike reverse osmosis (RO), FO does not require high pressure for separation, allowing low energy consumption to produce water. However, the internal concentration polarization in FO is an important factor affecting the performance of FO processes. This paper was intended to investigate the characteristics of FO and RO processes. A simple film theory model was applied to consider concentration polarization in FO and RO processes. This model allows the estimation of internal and external concentration polarization effects in FO process. A laboratory-scale FO device was used to find the model parameters for further calculations. The calculated flux was compared with experimental flux under a variety of operating conditions. It was found that the combination of FO and RO may result in a higher flux than FO-only process under some operating conditions. Further research will be required to investigate the effect of membrane materials on energy efficiency of FO and RO hybrid system.

This paper presents a novel methodology to determine an optimized control method for feed water temperature in a seawater reverse osmosis (SWRO) desalination process using genetic programming (GP) which is an evolutionary algorithm used to fi nd functional forms through training data. Two functional models were determined by GP with operation data collected over four years from Fujairah SWRO plant. The models showed high accuracy (>99.0%) in terms of the average error rate between the observed and the predicted values. The fi rst model involved the permeate water fl ow rate with a functional temperature correction factor (TCF), water transfer coeffi cient, and net driving pressure (NDP) and the second is the salt passage ratio with a functional TCF, salt transfer coeffi cient, and total dissolved solids (TDS) in the feed. To determine the optimized control of the feed water temperature, a new control methodology with the two functional models was proposed and applied to a simulation of the feed water temperature, which showed better performance in terms of the permeate fl ow rate. Applying the optimized control of feed water temperatures to a plant under identical operational conditions, it was found that the permeate fl ow rate could be increased by approximately 900 m 3 /day under a steady condition of 600 ppm in permeate TDS.

Seawater reverse osmosis (SWRO) desalination is rising as an alternative solution for the water shortage problem which is more severe than before. In this study, a package of process models was developed and tested by four-year SWRO plant operation data obtained from Fujairah in UAE, as a tool not only for simulating the performance of SWRO desalination process but for estimating the total profits of the plant operation. The simulation results based on the developed process models were reasonably satisfied to predict the SWRO desalination plant performance in terms of permeate water concentration and flow rate. And the results of cost estimation show a possibility that the models can successfully predict total annual profits (TAP) within the order of magnitude of USD/year, according to operating date, feed water concentration, and permeate water condition. Consequently, the developed package model is applicable to support design criteria and efficient operation of SWRO desalination plant as references.

An artificial neural network (ANN) was developed to predict the performance of a seawater reverse osmosis (SWRO) desalination plant, and was then applied to the simulation of feed water temperature. The model consists of five input parameters (i.e., feed temperature, feed total dissolved solids (TDS), trans-membrane pressure (TMP), feed flow rate, and time) and two output parameters (i.e., permeate TDS and flow rate). Then, the one-year operation data (n = 200) from the Fujairah SWRO plant was divided into three data sets (i.e., training, validation, and test data set) to develop the ANN model. The trained ANN model was subsequently found to produce good agreement between the observed and simulated data (TDS: R2 = 0.96; flow rate: R2 = 0.75) in the test data set. The results of this study show that the variation of the feed water temperature and TMP was found to significantly affect both the permeate TDS and flow rate. From subsequent simulations with various temperature controls, it is further suggested that the permeate TDS can be reduced using a linear increase control (from 27.5 to 29.5°C) for the feed temperature in an SWRO hybrid system with multi-stage flash (MSF) distillation, such as the Fujairah plant.

This study proposes a new operation methodology for energy saving in the Fujairah seawater reverse osmosis (SWRO) plant, as the optimum feed pressure is determined at the controlled operating temperature. To this end, two functional models were developed by genetic programming (GP) using two-year operational data. The data revealed that the required feed pressure for the plant operation was potentially overestimated. Based on the developed models, simulation of a three-step sequential control was carried out to reduce and optimize the required feed pressure. The simulation results first indicate that the temperature control significantly reduces the required feed pressure at a reasonably high temperature. Second, as the permeate water flow rate (PFR) is determined by the optimized feed pressure instead of the permeate pressure actually used to maintain a steady PFR in Fujairah, the required feed pressure could be substantially reduced. As a result, the proposed methodology can potentially reduce the required feed pressure, by approximately 10 bar, under the identical performance of both PFR and permeate water total dissolved solids (TDS). This study implies that the optimization of operation and management of MSF-hybridized SWRO processes can considerably improve the efficiency of the desalination process in terms of energy and, eventually, cost saving.

Fouling is one of the most serious problems in seawater desalination using reverse osmosis (SWRO) which is important to lower the production cost of desalinated water. For efficient operation of the SWRO plant, accurate models are crucial to decide the optimal operating condition and cleaning operation. The model for RO membrane system has been studied by many researchers and its usefulness has been increased as its accuracy has been improved. However, the prediction of fouling is difficult due to its extremely complicated mechanism of growth involving various foulants. In this study, the development of the fouling is predicted by monitoring the membrane resistance across the membrane and the friction coefficient through spiral-wound membrane from the operation data. Using nonlinear recursive least-squares (NRLS) method, the two properties are identified from the operating data based on the one-dimensional model of the SWRO system. By this method, the degree of fouling can be inferred from the two properties and potential cleaning time can be predicted. It can also assess the effectiveness of membrane cleaning. Using the actual data of an existing plant, the trends of resistance and friction coefficient could be monitored and the effect of cleaning pattern of the real plant can be evaluated by recursive parameter estimation online.

Statistical regression models involve linear equations, which often lead to significant prediction errors due to poor statistical stability and accuracy. This concern arises from multicollinearity in the models, which may drastically affect model performance in terms of a trade-off scenario for effective water resource management logistics. In this paper, we propose a new methodology for improving the statistical stability and accuracy of regression models, and then show how to cope with pitfalls in the models and determine optimal parameters with a decreased number of predictive variables. Here, a comparison of the predictive performance was made using four types of multiple linear regression (MLR) and principal component regression (PCR) models in the prediction of chlorophyll-a (chl-a) concentration in the Yeongsan (YS) Reservoir, Korea, an estuarine reservoir that historically suffers from high levels of nutrient input. During a 3-year water quality monitoring period, results showed that PCRs could be a compact solution for improving the accuracy of the models, as in each case MLR could not accurately produce reliable predictions due to a persistent collinearity problem. Furthermore, based on R2 (goodness of fit) and F-overall number (confidence of regression), and the number of explanatory variables (R-F-N) curve, it was revealed that PCR-F(7) was the best model among the four regression models in predicting chl-a, having the fewest explanatory variables (seven) and the lowest uncertainty. Seven PCs were identified as significant variables, related to eight water quality parameters: pH, 5-day biochemical oxygen demand, total coliform, fecal indicator bacteria, chemical oxygen demand, ammonia–nitrogen, total nitrogen, and dissolved oxygen. Overall, the results not only demonstrated that the models employed successfully simulated chl-a in a reservoir in both the test and validation periods, but also suggested that the optimal parameters should cautiously be considered in the design of regression models.

Over 100 papers were reviewed to elucidate factors influencing large-scale seawater desalination plants with reverse osmosis networks (SWRO). This paper consists of subjects such as SWRO systems investigation, system models of pretreatment and RO networks, systems optimization to minimize the total cost of SWRO plant design, and the future direction of SWRO technology. In order to design a large-scale seawater desalination plant, a systematic understanding of SWRO processes should be followed. After investigating all the processes, including site-specific features, seawater intakes, pretreatment systems, RO networks, energy recovery systems, post-treatment systems, brine disposal, and the environmental impact of SWRO desalination, system models are discussed for predicting the performance of each system. Based on the minimal principle of total cost required for a full-scale SWRO plant, optimized results are discussed. Studies needed for developing future SWRO technologies are suggested.

The Center for Seawater Desalination Plant (CSDP), which was established in December 2006, launched its R&D project [seawater engineering and architecture of high efficiency reverse osmosis (SEAHERO)] in the middle of 2007 and aimed to get world top-level seawater reverse osmosis (SWRO) plant technologies. SEAHERO will accomplish its technical objectives with a fund of US $165 million for 5 years. One of the most important technical targets of SEAHERO is the scale-up of the SWRO system for economies-of-scale. Through a rigorous technical review of the scale-up strategies, CSDP selected two key strategies for the scale-up. One is the scale-up of RO unit trains by assembling RO modules and the other is the scale-up of RO module size. An SWRO plant test-bed of 10 MIGD (≈45,000 m3/d) in capacity will consist of two different RO unit trains of 6 MIGD (≈27,000 m3/d) and 4 MIGD (≈18,000 m3/d). The 6 MIGD train targets the largest RO unit train in the world. The 4 MIGD train will adapt RO modules 16" in diameter, which are twice as large as modules in current RO markets. The two different RO trains divide the risk of the new technology to increase the probability of success. With the two scale-up strategies, SEAHERO is expected to achieve the leading SWRO plant technology in the world.

Scale formation of soluble salts is one of the major factors limiting the performance of reverse osmosis (RO) membranes for desalination. In this study, a dynamic model based on the crystallization theory was developed to analyze the effect of CaSO4 scale formation on RO desalination process. Taking into consideration two mechanisms in scale formation including surface and bulk crystallization, the performance of RO filtration was predicted as a function of crossflow velocity, transmembrane pressure, permeate recovery, and operation mode. The model results indicated that RO fouling due to surface crystallization is important in batch filtration whereas both surface and bulk crystallization is important in crossflow filtration. This is because concentration polarization is directly related to surface crystallization. RO fouling due to bulk crystallization appeared to increase with increasing crossflow velocity and permeate recovery. The effects of background organic matters and antiscalant on scale formation were quantified using the model. The effect of operating parameters on RO fouling and concentration polarization was explored based on the model analysis.

As a means of optimizing desalination processes, site-specificity in the determination of seawater quality conditions is a crucial point for improving the overall energy efficiency of a seawater reverse osmosis (SWRO) process. To this end, field studies were carried out at 16 sampling sites along the shoreline in South Korea to investigate the site-specific features of seawater quality. Also, two mathematical models were developed for the simulation of SWRO processes dependent on seawater quality in macroscopic and microscopic contexts, respectively. As a result, the microscopic dynamic model revealed that concentration polarization in the vicinity of the membrane surface and permeate concentration are affected by the feed seawater concentration and pressure. Then, the application of Fujairah SWRO plant operation data to the macroscopic simulation of a non-isobaric SWRO process model resulted in significant energy savings in terms of operational pressure savings, reducing 0.3 bar from the annual average value in the first pass operational pressure. These findings suggest that a cost-effective SWRO operation can be feasible using non-isobaric pressure controls by considering site-specific feed seawater concentrations. Results of the study presented here can be applied to improving the energy efficiency in SWRO plants through the optimization of pressurized systems.

The effect of inductively coupled plasma (ICP) treatment on the surface activation of the polycarbonate (PC) substrate was studied. At high working pressure and ICP power the wetting angle could be decreased as low as 5°. The wetting angle was decreased effectively when the impinging ions had proper energy ∼ 8 eV. Excess ion energy interfered with reducing the wetting angle. The polar functional group (C O) significantly affected the change of surface energy. Compared with the deposited Al2O3 film on the PC substrate treated at a low wetting angle, that on the PC substrate treated at a high wetting angle adhered very well.

Well-crystallized tin oxide films were successfully synthesized without additional heating by inductively coupled plasma assisted chemical vapor deposition (ICP-CVD). The degree of crystallization was affected by the ICP power and hydrogen flow rate. The substrate temperature was increased only up to 423–453 K by plasma heating, which suggests that the formation of the SnO 2 crystals was not caused by plasma heating, but by enhanced reactivity of precursors in high density plasma. The micro-hardness of deposited tin oxide films ranged from 5.5 to 11 GPa at different hydrogen flow rates.

Surface-flow wetlands constructed with Acorus and Typha plants, connected to a wastewater treatment plant, were investigated with respect to organics (dissolved organic matter), anions (nitrate, sulfate, and phosphate), metals (Cu, Ni, Zn, Fe, and Mn), and metalloids (As). The results of the research indicated: (1) effluent organic matter (EfOM), based on dissolved organic carbon (DOC), was not efficiently removed by the wetlands. However, the hydrophobic, transphilic, and hydrophilic EfOM fractions varied throughout the wetlands, as identified by XAD-8/4 resins. (2) Nitrate, as compared to sulfate and phosphate, was efficiently removed, especially in the Typha wetland pond that had long retention time, under anoxic condition. (3) Most of the heavy metals were ineffectively removed via the wetland ponds. However, the iron concentration increased in the Typha wetland pond, which was probably due to its reduction under anoxic condition.

The coagulation and sedimentation of particles is central to many environmental and industrial processes. Kinetic descriptions of this process can be divided into two approaches. Population balance equation (PBE) theory accounts for mass transfer between particle size classes by coagulation and loss of particle mass by sedimentation. Its practical application is limited by the fact that the rate constants, or kernels, for coagulation between all combinations of cluster sizes are unknown, and only a few solutions are available for simplified forms of the coagulation kernel. A second approach involves the use of simple rate expressions for the loss of particle mass with time, where the order of the reaction is determined by the mathematical properties of the coagulation kernel and the sedimentation term. Two different theories (similarity theory, ST, and the quasi-steady-state hypothesis, QSSH) give conflicting estimates for the order of the reaction. In this paper, we derive a PBE solution for the choice of a constant kernel and a particle removal rate that increases linearly with cluster volume. The kinetics of mass removal predicted by this solution are then compared directly to generalized forms of ST and QSSH which we also derive. We find that the PBE solution does not rigorously conform to either ST or QSSH, although the predictions of ST may be close enough for practical applications. This paper presents the first rigorous comparison of PBE, ST, and QSSH descriptions of particle coagulation and sedimentation. Copyright 2001 Academic Press.

s / Developmental Biology 331 (2009) 517–529 occurred. Overexpression of TBX22 caused a striking decrease in proliferation but did not change the level of apoptosis. Furthermore we identified two targets of TBX22 that could be mediating the phenotype, DLX5 and MSX2. We have therefore demonstrated novel functions for TBX22, a gene that causes some forms of human orofacial clefting. This work was funded by CIHR grants to JMR. doi:10.1016/j.ydbio.2009.05.521 Program/Abstract # 494 A point mutation in Arid1a reveals an essential role for this SWI/SNF subunit in extraembryonic blood vessel and trophoblast development Ronald L. Chandler, Jennifer Brennen, Terry Magnuson Department of Genetics, University of North Carolina, Chapel Hill, NC, USA Arid1a is a signature subunit of the mammalian SWI/SNF ATP- dependent chromatin remodeling complex. We performed an ENU mutagenesis screen for Arid1a coding mutations and generated mice carrying a valine-to-glycine point mutation in the ARID DNA binding domain of Arid1a. Although mutant protein is expressed near wild- type levels and capable of interacting with its catalytic subunit, Brg1, it appears to display reduced DNA binding capacities in vitro. Homozygous mutant embryos undergo development arrest by E10.5 and exhibit defects in the trophoblast placenta and extraembryonic vasculature, including a compacted labyrinth layer and reduced vascular branching. These data suggest the ARID domain of Arid1a is essential for development. doi:10.1016/j.ydbio.2009.05.522 Program/Abstract # 495 The role of Friend of GATA in primitive red blood cell development Mizuho S. Mimoto, Jan L. Christian Department of Cell and Developmental Biology, Oregon Health and Science University, Portland, OR, USA The transcription factor GATA-1 and its cofactor Friend of GATA (FOG) are required to promote embryonic red blood cell (RBC) development in mice. In contrast, the current model in Xenopus, based on overexpression studies, predicts that FOG inhibits RBC development by recruiting the transcriptional co-repressor C- terminal Binding Protein (CtBP). To resolve these seemingly contra- dictory findings, we have used morpholinos to perform a loss-of- function study in frogs. We find that in Xenopus, as in mice, FOG is in fact required for RBC development. Specifically, targeted injection of FOG morpholinos into the ventral blood-forming mesoderm of 8-cell Xenopus embryos results in a dose-dependent loss of globin expression at the tailbud stage. In addition, we find that over- expression of both wildtype FOG and mutant FOG isoforms that either lack known repressor binding domains, or harbor mutations at key GATA-interaction residues, also result in loss of blood. Together, these studies suggest that FOG is required for RBC development and that loss of blood seen with FOG overexpression is likely due to a dominant-interfering effect by which excess FOG sequesters other co-factors required for RBC development away from endogenous target promoters. Specific domains of FOG required for RBC development in vivo have not yet been elucidated. We are currently asking whether various FOG mutant constructs can rescue RBC formation in FOG morphants. This will allow us to determine which functional domains of FOG are required for normal erythropoiesis, and may suggest novel binding partners that are important for FOG's role during RBC development. doi:10.1016/j.ydbio.2009.05.523 Program/Abstract # 496 Stacked expression of Hand2 and Dlx mediates signaling from Edn1 to produce discrete pharyngeal arch patterning domains Jared Coffin Talbot, Charles B. Kimmel Institute of Neuroscience, University of Oregon, Eugene, OR, USA Recent studies have suggested that Endothelin1 (Edn1) acts in a dose dependent fashion to pattern skeleton from the first two pharyngeal arches into dorsal, intermediate, and ventral domains via its targets hand2 and Dlx. We hypothesized that hand2 expression defines the ventral domain, in part by repressing intermediate domain genes. We further hypothesized that Dlx genes pattern the intermediate domain. Third, we propose that the combined patter- ning from hand2 and Dlx delineates ventral/intermediate domains from dorsal. Here we demonstrate that hand2 is expressed next to edn1, and the expression of all Dlx genes extends dorsal to hand2. We provide evidence that dlx3b, dlx4b, and dlx5a are redundantly required for intermediate domain patterning. Furthermore we show that by 36 hpf, dlx3b, dlx4a, and dlx4b are specifically expressed in intermediate arch mesenchyme. Previous work demonstrated that hand2 is required for ventral cartilage formation. We confirmed this with two alleles of hand2. We further show that in hand2 mutants, dlx3b, dlx4a, and dlx4b expression expands into the ventral domain at 36hpf. Finally, when Dlx-MO is injected into hand2 mutants, both ventral and intermediate defects are seen, and the ventral-most structures may acquire dorsal shape. Collectively our work suggests that the stacked expression of hand2 and Dlx mediates signaling from Edn1 to generate ventral and intermediate domains with distinct identities separate from dorsal. (Supported by NIH grants DE13834 and DTG GM007257). doi:10.1016/j.ydbio.2009.05.524 Program/Abstract # 497 A follistatin-BMP7 feedback circuit controls taste papillae development and patterning in mouse tongue Piper L. Hollenbeck a,d , Crestina Beites a , Joon Kim a , Robin Lovell-Badge e , Scott Christley c,d , Qing Nie c,d , Arthur Lander b,d , Anne Calof a,b,d a Department of Anat. and Neuro., UC Irvine, Irvine, CA, USA b Department of Dev. and Cell Bio., UC Irvine, Irvine, CA, USA c Department of Math., UC Irvine, Irvine, CA, USA d Center for Complex Biological Systems, UC Irvine, Irvine, CA, USA e Department of Dev. Genetics, NIMR-MRC, London, UK Interactions between epithelium and mesenchyme are thought to drive development and patterning of taste papillae, but the identities of the mesenchymal signals are unknown. Using mouse genetics, we show that Fst, which is expressed in tongue mesenchyme during development, controls these processes in both anterior (normally gustatory) and posterior (normally non-gustatory) lingual epithelium. In anterior Fst −/− tongue there are increased numbers of Sox2+ taste progenitors, with fungiform papillae of abnormal size and spacing. In posterior Fst −/− tongue, ectopic Sox2+ epithelial domains develop and non-gustatory filiform papillae are absent. Increased Bmp7 expression is evident in regions of ectopic Sox2+ progenitors, and