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This study developed tree-based ensemble machine learning models to predict forward osmosis (FO) permeate flux using extreme gradient boosting (XGBoost) and light-gradient boosting machine (LGBM) methods. The models were trained by approximately 700 data points from the FO experimental data. The results showed that LGBM and XGBoost could predict the FO permeate flux with very high accuracy (>0.95 of R2) in the test set. Feature analysis using Shapley additive explanations values was performed to identify the influences of input variables on the model output and the correlation between the input variables. The results revealed that water permeability and pressure difference have the most significant variables on the FO permeate flux. The correlation between the operating conditions and water permeability cannot be neglected. In this study, we clarified the applicability of ensemble machine learning models for FO systems and suggested directions for future data collection. [ABSTRACT FROM AUTHOR]

Seawater reverse osmosis (SWRO) has played a key role in alleviating water stress worldwide. However, its intensive energy consumption, which is highly dependent on fossil fuels, needs to be reduced to mitigate the CO2 emissions resulting from SWRO. Many technologies, including pressure-retarded osmosis (PRO), have been applied in an attempt to reduce the energy consumption of SWRO. In this study, potential trends in CO2 emissions from SWRO processes in Korea are considered based on SWRO operational data collected from a range of sources and relating to societal scenarios of the future. These societal scenarios are based on current population trends in Korea and the proportion of renewable energy currently utilized in Korea. Next, using a dimensionless performance index for the SWRO-PRO hybrid process, the study presents the potential efficacy of PRO in reducing the magnitude of CO2 emissions from SWRO processes in Korea. The analysis shows that CO2 may be reduced by 10%-40%. The results of the study suggest a promising role for PRO as a suppressor of CO2 emissions. It is anticipated that the study will facilitate further in-depth studies into the use of PRO. [ABSTRACT FROM AUTHOR]

It is essential that water resource management plans require explicit links across different spatial scales in a single watershed. This study aimed to identify existing gaps between sub-basin and watershed management strategies using a watershed simulation model soil and water assessment tool (SWAT). The SWAT was calibrated and validated at the upper and middle regions of the Yeongsan River in Korea using past weather inputs from 2012 to 2014. The simulation outputs from 2014 used as a reference were compared to those with future weather scenarios in 2032 produced from a regional climate model (RCM) such as RCM 2.6, 4.5, 6.0, and 8.5. We found that the calibration and validation results agreed well with the observed data, yielding Nash--Sutcliffe efficiency values more than 0.72 for daily streamflow as well as for monthly sediment and total phosphorus (TP) loads at the final watershed outlet. However, all projected weather data led to a significant difference in streamflow only at the sub-basin level, while all three variables at the watershed level varied significantly from scenario to scenario. These imply that water resource management plans determined at the watershed scale may not be suitable for those at the sub-basin scale, calling for a more refined search that harmonizes both management decisions. [ABSTRACT FROM AUTHOR]

Statistical analyses are often subject to misinterpretation due to poor data quality which is inaccurate, incomplete, or unavailable. This study describes how incomplete data diminishes the screening accuracy of water pollution hotspots using a self-organizing map (SOM), a popular algorithm in reducing the dimension of complex data in a nonlinear fashion. A full data set consisting of 12 water quality and quantity parameters monitored monthly over 3 years at the Yeongsan River in Korea was provided to SOM as a reference input. For purposes of comparison, SOM was further allowed to accept three incomplete data sets in terms of variable availability as well as data loss for single and multiple parameters and different pollution levels. We found that data loss of either single or multiple parameters exceeding 15% of the entire data set led to significant changes in spatial and temporal patterns of the original data. However, the variables intentionally unavailable in the given data set affected the screening performance of water pollution hotspots in SOM, to a less obvious extent, as long as the percentage of missing data fell below 10%. The same applied to data loss with three pollution levels, from high through moderate to low concentrations of one important variable. Therefore, we recommend the use of multiple approaches that couple dimensionality reduction algorithms with reasonable imputation methods for the data set with a high percentage (e.g. above 15%) of missing values. [ABSTRACT FROM AUTHOR]

In this study, we conducted a numerical simulation to evaluate stability in the seawater reverse osmosis (SWRO) process against seasonal variations of feed water. The impact of element configuration on SWRO operation was analyzed using a process model consisting of the solution--diffusion model. Seawater quality and temperature data collected from the intake of the Fujairah desalination plant (United Arab Emirates) were used to identify optimum internally staged design (ISD) configurations. Monitoring data were also used to simulate changes in SWRO performance. The process performance of the ISD configurations as compared to conventional design configurations in terms of specific energy consumption, permeate total dissolved solids concentration and recovery ratio. The results showed that SWRO processes with four ISD configurations met the performance requirements over 12 months despite the fluctuations in seawater quality and temperature. The prediction results of the ISD configurations showed stable operation during the 12 month simulation period. These configurations had a significant advantage with respect to membrane maintenance. This study's findings could be used to optimize the element configuration of the SWRO process by predicting the process performance while accounting for seasonal variations of seawater quality and temperature. [ABSTRACT FROM AUTHOR]

Eutrophication is caused by the discharge of excess nutrients from various point and nonpoint sources. In particular, nonpoint sources of nutrients are difficult to identify because of diffuse sources and the effects of climate change. The objective of this study is to investigate the change in nutrient loading from land areas under climate change. In this study, the soil and water assessment tool (SWAT) model was applied to predict the sediment, total nitrogen (TN), and total phosphorus (TP) loads in the Yeongsan River Basin using geographical information (i.e., digital elevation map, land use, and soil type), observed data (i.e., meteorological data, streamflow, and water quality). Future climatic variables were obtained from a general circulation model, which was simulated using four representative concentration pathway (RCP) scenarios such as RCP 2.6, 4.5, 6.0, and 8.5. The results showed that flow rate, sediment load, TN load, and TP load were changed in terms of climate change under the different RCP scenarios. Impacts of climate change on a basin may be an important factor in eutrophication management in the Yeongsan River. The SWAT model provided an accurate prediction of the current nutrient pollutant loads and facilitated the reliable prediction of future nutrient pollutant loads under climate change. [ABSTRACT FROM AUTHOR]

A Kalman filter (KF) algorithm is a recursive data processing algorithm typically recommended for estimating unmeasured state variables in chemical engineering processes. We studied the performance of a KF algorithm in a range of noise levels as well as indirectly observed data from the process model. For this study, two versions of the KF algorithm widely adopted for a nonlinear system, the extended Kalman filter and the unscented Kalman filter, were applied to 1-year time series data monitored during the operation of the Fujairah seawater reverse osmosis desalination plant. We found that variables indicating the state of fouling, membrane resistance, and solute permeability agreed well with those estimated by the two KF algorithms, specifically in terms of noise reduction and peak detection. When the two KF algorithms were exposed to various noise levels, they showed a corresponding increase in the error rates (for unmeasured state variables) according to the noise levels varying from 10% to 50%, regardless of the algorithms used. The two KF algorithms provided a good prediction performance only for the permeate flow rate rather than for the permeate concentration, out of the two types of measured data. However, the individual KF algorithms still showed different performances in computing estimated and predicted data in the reverse osmosis process. This result calls for further research on the determination of the best KF algorithms for either estimation or prediction of directly and indirectly measured state variables in various chemical processes. [ABSTRACT FROM AUTHOR]

Hollow fiber is one of the most widely used membrane types in the field of membrane-based water treatment, as hollow fiber membranes contain self-supporting structures and are easy to scale up due to their high productivity-per-unit volume. In the commercialization of hollow fiber membranes, module configuration is a key issue that is closely related to system performance. Especially for membrane distillation process, proper design of hollow fiber membrane module is necessary considering mass and heat transport. In an effort to enhance such performance, the inner-workings of the transport phenomena inside these membrane modules are investigated via various numerical approaches. A review of membrane module configurations allows for an examination of recent advances, applications, and numerical approaches related to hollow fiber modules; this is accomplished by a consideration of the characteristics of membrane distillation processes. Based on an analysis of previous research studies, and in an attempt to contribute to improved performance, potential challenges and applications of novel hollow fiber membrane modules are suggested. [ABSTRACT FROM AUTHOR]

In this study, 98%-100% of cross-linked polyamide (PA) membranes were synthesized by interfacial polymerization between trimesoyl chloride (TMC) and m-phenylenediamine (MPD), using molecular dynamics (MD) simulations. Previous studies have not been able to synthesize such highly crosslinked membranes, due to a lack of monomer diffusion near the unreacted sites inside the complex three-dimensional PA matrix. This barrier was removed by raising the temperature of the reaction mixture to 1,000 K for 0.02 ns, which increases the monomer diffusion inside the PA matrix for cross-linking. In this study, an automatic, fully generalized, and self-contained Python module was developed to synthesize PA membranes using MD simulations, employing a new algorithm that mimics the physicochemical synthesis of the membranes. Initial amounts of 100, 200, 300, and 400 TMC molecules with varying ratios (TMC:MPD) of 1:0.5, 1:1, 1:1.5, 1:2, 1:2.5, and 1:3 were used. The reaction progress was investigated based on the number of amide bonds formed, which showed an exponentially decreasing trend. The effect of the TMC to MPD ratio on membrane size and degree of cross-linking (DOCL) revealed that a 1:2 (TMC:MPD) ratio was optimal for maximum membrane growth, with approximately 90% TMC consumption and 90% cross-links. The observed DOCL in the membranes synthesized with TMC:MPD < 1:2 was around 99%, and in a few cases 100% cross-linked membranes were obtained. The cross-sectional examination of membranes showed two distinct pore sizes of approximately 5.32 Å ± 0.66 and less than 5.17 Å ± 0.74, for the membranes synthesized with TMC:MPD = 1:1 and <1:1, respectively. These results will be achieved with the ability to synthesize membranes of various DOCLs, by simply changing the ratio between the monomers. The module is available free of charge, and any efficacious suggestions for the improvement of this module will be fully acknowledged. [ABSTRACT FROM AUTHOR]

Membrane fouling significantly affects membrane performance, but cleaning and replacement schedules are often set at regular time intervals, regardless of the extent of deterioration in performance. The aim of this study is to develop an improved prediction model for membrane fouling in the seawater reverse osmosis (SWRO) process using a hybrid machine learning approach. A Kalman filter (KF) was combined with either an artificial neural network (ANN) or a support vector machine (SVM)--a family of machine learning models--in series. The performance of these integrated models was evaluated with training and testing data sets compiled from the Fujairah SWRO plant over a period of 18 months. Our findings showed that the SVM alone provided, on average, slightly better prediction of membrane resistance (an indirect indicator of membrane fouling) than a single ANN during training and testing sets. However, hybrid machine learning methods consistently outperformed any single model, with the combination of the KF and SVM exhibiting better performance than that of the KF and ANN, except for one special case in which the accuracy of a single SVM already exceeded 0.8 for both Nash-Sutcliffe model efficiency and R². Taken together, our results demonstrated that the hybrid machine learning approach not only enhanced the prediction ability of membrane resistance in classical fouling and machine learning models, but could also be used to adjust cleaning and replacement schedules correctly in response to progressive deterioration in membrane performance during operation. [ABSTRACT FROM AUTHOR]

Watershed-scale water quality models are often used for interpreting changes in complex environmental systems. Precipitation is a primary control affecting the output of watershed-scale water quality model, and higher resolution of precipitation data is highly desirable. The objective of this study was to investigate whether the radar rainfall estimates can improve the accuracy of stream flow, TSS load, and TP load simulations with the soil and water assessment tool for high- and low-flow conditions. Yeongsan River watershed (YRW) was selected for this study. This watershed, located south-west of Korean Peninsula, has an area of about 2,938 km², and is divided into 25 sub-watersheds. The simulations were conducted under different rainfall datasets: (1) rainfall observations from nine ground rain gauges (GR), (2) 25 corrected radar rainfall estimates (RR), and (3) a combination of nine ground rain gauges and 16 corrected radar rainfall estimates that represent the 16 ungauged sub-watersheds in YRW (GARR). Simulation results under different the rainfall datasets were compared using the Nash–Sutcliffe efficiency coefficient and percentage bias. The prediction of both high and low stream flows using GARR was better than using GR and RR data. The model performance for predicting TSS load was significantly better under GARR data than under GR and RR data. In case of TP, the model performances using RR and GARR data were significantly better than that using GR data. Overall, combining gauge rainfall and corrected radar rainfall led to an improvement in the prediction accuracy for the watershed-scale water quality model. [ABSTRACT FROM AUTHOR]

Land use and cover is one of the important factors that influence water flow within a watershed. Alteration of land use through time affects hydrological processes as well as the water budget in the watershed. In analyzing these processes that occur within basins and watershed, Soil and Water Assessment Tool (SWAT) is considered an indispensable tool. In this study, scenario analysis was done through the SWAT model by simulating stream discharge in a sub-basin in Yeongsan River Basin for the years 1990 (scenario 1) and 2000 (scenario 2). Input data in two scenarios were all the same except for the land use data. Land use data shows a decrease in forest and agricultural land area and increase in urban area from year 1990 to 2000. Developed models were evaluated to have acceptable performance since statistical parameters Nash-Sutcliffe efficiency (NSE) and ratio of mean squared error to the standard deviation of the measured data (RSR) in the validation for both scenarios are within the satisfactory rating limits. Water budget analysis showed an increase in annual average surface runoff and decrease in annual average evapotranspiration and lateral flow which is attributed decrease in forest and agricultural area and increase in urban area. [ABSTRACT FROM AUTHOR]

Accurate assessment of piping systems’ risk to damage reduces annual operation and maintenance costs. Recently, extreme climate events (e.g. cold snaps or heavy snow) due to global climate change have increased pipe system failure. The objective of this study is to establish a framework for developing screening models of pipe failure events, due to water network systems freezing using two statistical approaches. More specifically, logistic regression was used to estimate the probability of failure at a household level, whereas the customized model developed to predict the frequency of community-wide failure events. The data recorded at least one failure event in Korea from 2008 to 2015, which was provided to the logistic regression model. The customized model, however, only used the data set compiled from three areas of concern with the highest frequency of the failures. Results showed that the logistic model showed the best performance out of the 11 constructed models, in terms of R and the variance inflation factor (of lower than two). The logistic model incorporated three variables: the minimum temperature on the day of failure, the natural logarithm of the total water usage in the previous month and the mean minimum temperature over the previous 10 days. The selected model had an overall prediction accuracy of 66.4%. When the customized model at the community level was examined the three models not only yielded moderate R² values ranging from 0.53 to 0.66, but also helped identify water network systems at risk of failures. Overall, this study demonstrated that the proposed methodology can be used to highlight areas of concern at different geographic scales, along with refining existing statistical models with new variables updated in real time. [ABSTRACT FROM AUTHOR]

While the size of single low impact development (LID) unit determines the performance in attenuating water quantity and quality from storm runoff, the performance of multiple LID units is sensitive to both their size and arrangement order. This study describes a methodology to obtain the best performance for multiple LID units under varying by time-to-peak of storm with the same intensity and duration using storm water management model (SWMM), a popular model for rainfall-runoff and water quality simulation. The hypothetical temporal distributions were designated by Huff curves, which provided characterizing storm mass curves, along with the relationship of intensity-duration-frequency to determine storm intensity for 1-h in 2-year return period. Three types of LID units (rain barrel, infiltration trench, and vegetative swale) were selected to develop aggregate LID scenarios using the SWMM. The results indicated that, when compared with other field experiments, the SWMM successfully estimated change in flow discharge and suspended solid (SS) loss reflecting different storm patterns at the final outlet of and urbanized sub-catchment as well as the effects of LID practices. The performances of aggregate LID scenarios including lag time of peak runoff, peak runoff reduction, volume reduction, and SS loss reduction were sensitive to arrangement order and time-of-storm peak-to-storm duration. Scenario 5, which had the order of vegetative swale, rain barrel, and infiltration trench, showed the most effective serial arrangement, as it exhibited the more consistent results across the storm patters. This study thus provides insights into the effective design of aggregate LID scenarios considering different storm characteristics. [ABSTRACT FROM AUTHOR]

Successful data analysis is an essential component of any environmental monitoring programs. This study introduces an effective data analysis method to identify water pollution hotspots as well as to drop redundant monitoring parameters and samples using a self-organizing map (SOM), which has a strong specialty in pattern extraction from complex monitoring data. A full data set consisted of nine parameters that were obtained on a monthly basis from 83 sites in various tributary streams along the Yeongsan River, Korea, from May 2011 to December 2015. The given data set was further partitioned into a number of subsets to examine their effect on variable importance and temporal pattern analysis. We found that water pollution hotspots were more clearly addressed in load-based SOM analysis than in concentration-based SOM analysis due to strong correlation between variables resulted from variability reduction by combining two variables into a single one for load analysis. In addition, the variables chemical oxygen demand and electrical conductivity and the parameters discharge and total nitrogen were found to participate most and least actively in describing spatial and temporal variation of the observed variables, respectively. About 35% of the sampling locations showed high similarity among the monthly data extending from November in the previous year to February in the following year. We believe that the proposed methodology can be useful in revising the upcoming water monitoring study by clarifying several issues related to monitoring parameters and frequency in the existing program. [ABSTRACT FROM AUTHOR]

This paper describes the effects of weir construction on water quality in the Yeongsan (YS) River. In general, weirs affect aquatic environments of rivers and streams by interrupting natural water flow. To identify changes in water quality before and after weir construction, analysis of variance and autocorrelation tests were conducted on data from four monitoring stations. Seasonal variations in suspended solids (SS), biochemical oxygen demand (BOD5), chemical oxygen demand (COD), total nitrogen (TN), total phosphorus (TP), and pH were analyzed using data from six years of monitoring. No significant changes in mean BOD5 or COD followed the construction of weirs. However, mean TN and TP were changed significantly during and after construction. Moreover, SS and pH changed significantly during construction, and TN and TP concentrations were slightly improved after weir construction. However, continuous monitoring and analysis of water quality changes in each weir are required to prevent environmental disasters such as algal blooms. [ABSTRACT FROM AUTHOR]

The fouling behavior of seawater reverse osmosis membranes has yet to be definitively investigated due to the complexity of seawater compositions. In this study, a time-series image analysis (TSIA) was performed to investigate the fouling mechanism using scanning electron microscopy (SEM) and atomic force microscopy (AFM). The fouling experiments were conducted with synthetic seawater (SS) and SS mixed with humic acid substances (SHA). The effect of operational time was investigated for 2, 4, 6, 8, 12, and 20 h. According to the TSIA results, different fouling characteristics between SS and SHA experiments were observed. In the SS case, the fouling mechanism is the interaction between inorganic particles and the membrane surface as well as interaction between inorganic particles and the deposited foulants. Then, increased accumulation of deposited foulants was observed with respect to the operational time. However, in the presence of humic acid, the fouling mechanism was significantly influenced by the adsorption of humic acid onto the membrane surface at the initial stage (first 2 h). This organic layer traps inorganic particles and organic substances, and accelerates the fouling formation on the membrane surface, thereby leading to a greater flux decline compared to the SS experiment. [ABSTRACT FROM AUTHOR]

The development and exploitation of sustainable and environment-friendly energy resources are required in order to resolve global energy shortages. Recently, salinity gradient power (SGP) has been considered a feasible candidate, with high potential to become a substitute for the current use of fossil fuels due to benefits such as less periodicity, abundance and no emission of carbon dioxide. In this paper, one SGP, pressure-retarded osmosis (PRO) system, was reviewed in terms of its mechanism, limitations and available applications. In the PRO system, water permeates through a semipermeable membrane from the feed solution to the draw solution, and energy is generated by depressurizing the permeated flow through a hydro turbine. Models for understanding its mechanism and for improving of its performance were reviewed. In addition, applications of sea water reverse osmosis (SWRO), wastewater treatment (WWT) and PRO hybrid process were introduced in order to develop new water-energy nexus processes. In particular, it is thought that the SWRO--PRO hybrid process and SWRO--PRO--WWT hybrid process can contribute to reducing the total energy consumption in SWRO plants as well as to applying the SGP energy to other engineering fields. [ABSTRACT FROM AUTHOR]

Membrane filtration is lately becoming a popular process for the pre-treatment of seawater in reverse osmosis (SWRO) desalination. The common practiced method of controlling membrane fouling and reducing the treatment costs usually involves a short coagulation step prior to the membrane filtration. In this work, a study of the feasibility of a coagulation free microfiltration (MF) as pre-treatment for SWRO desalination from a technical, economical and environmental point of view was performed. The experimental part included filtration of seawater from the Yellow Sea in Korea both with and without granular activated carbon (GAC) pre-treatment using a laboratory scale MF plant and different constant fluxes in outside-in dead-end mode. The results show that a coagulant and GAC free, stand-alone microfiltration using low fluxes and intense chemical cleanings is technically possible. When compared to a state of the art coagulation-MF, such a process could be economically and environmentally favourable when accounting for the lower energy demand and the relinquishment of the sludge treatment system. [ABSTRACT FROM AUTHOR]

A lab-scale vortex separator, based on a swirling motion to remove settleable particles, was used to remove suspended solids in urban stormwater runoff. However, the treatment is limited to the removal of large settleable particles. The synthesized stormwater runoff was made with tap water and the addition of road sediment. The vortex separator has internal components designed to enhance vortex separation by minimizing the turbulence, increasing the efficiency, and preventing captured pollutants from washout. As the flow continues to spiral down around the inlet baffle, a low energy vortex motion directs settleable particles into the protected sediment storage zone. Advanced vortex separation provided an extendable and stabilized flow path while protecting the captured pollutants for a wide range of flow rates. The range of the inflow rate was 30-115 l/m, and the size of the influent particles varied from 75 to 200 µm. Overall removal effi ciencies of 51.8% for SS, 26.6% for COD, 70.5% for TP, and 35.6% for TN were achieved. The efficiency of particle removal for a high inflow rate was better than for a low inflow rate under the same condition of infl uent particles. The particle removal efficiency of the inlet baffle improved by about 5-10% compared to without an inlet baffle. [ABSTRACT FROM AUTHOR]

To manage and control the nonpoint source (NPS) pollution and to improve the water quality of impaired streams, rivers and lakes, practices including constructed wetlands, permeable pavement, swales and others are being attempted in the world. Before applying these techniques, an analysis of stormwater runoff characteristics should be understood due to the complexity in estimating system design factors for best management practices (BMPs). This study investigates the stormwater discharge from an agricultural area in Korea. Based on this investigation, pollutant and fl ow coeffi cient of variation (PFCoV) values were developed in an attempt to explain the stormwater runoff in the agricultural area. Four fi eld studies categorized by rainfall type were then employed to assess the PFCoV values. The results show that the physical meaning of PFCoV values indicates the variation of NPS pollutants during a storm event. As such, this simple and meaningful result can be applied to a wide range of stormwater management designs or water quality controls in agricultural areas. [ABSTRACT FROM AUTHOR]

A four-year monitoring study was conducted to determine the diffuse pollutant unit loads for the six representative transportation landuses (i.e., highway, parking lot, bridge, service area and toll gate) in urban areas in Korea. Pollutant event mean concentrations (EMCs) were calculated from 123 storm events at eleven sites and the average annual rainfall and runoff coefficients were determined to estimate the unit loads using the National Institute of Environmental Research (NIER) method. Apparent differences in the unit load values existed among landuses as explained by the high variability of EMCs for different rainfall events. The study has found that runoff from bridges and highways contained the highest loadings of TSS and COD while service areas are the primary sources of nutrients and metals. The results of this study could be used by the Ministry of Environment (MOE) to separate the unit loads of transportation landuses from the urban area category in the current unit load system. The values obtained are also useful for planning and simulation purposes especially in the total maximum daily load (TMDL) programs and diffuse pollution abatement measures. [ABSTRACT FROM AUTHOR]

Different numerical schemes for the fate and transport models of fecal indicator bacteria (FIB) were used to predict the concentration of FIB in a creek, which were then compared to a steady state model (QUAL2E). Escherichia coli (EC) and enterococci bacteria (ENT) were selected as representative FIB to compare the model performance under different flow and weather conditions in the Gwangju Creek in Korea. The results revealed that model accuracy of the forward time centered space (FTCS) scheme is the highest compared to the upstream, Dufort-Frankel, Crank-Nicolson methods and steady state model (QUAL2E) under dry weather conditions. In wet weather conditions, however, the upstream scheme shows the best performance among the five models. The upstream scheme thus represented a potential method for predicting the fate and transport of FIB originating from nonpoint sources during the rainy season. This study demonstrates that prediction results could vary in response to different numerical schemes and that the amount of discrepancy between the observed and predicted results can be quite signifi cant. We expect that this study could be applied to the water quality forecasting system as a real time management in near future. [ABSTRACT FROM AUTHOR]

Forward osmosis (FO) is a membrane-based desalination technique using an osmotic pressure gradient as a driving force. FO enables lower energy consumption to produce water than reverse osmosis (RO) because it does not require high transmembrane pressure. However, FO needs to be combined with other processes such as RO or evaporation because the draw salts in the FO products should be removed. This paper focused on theoretical investigation of combined systems with FO and RO for seawater desalination. A theoretical model to predict the performance of the combined systems was developed based on the solution-diffusion model and the modified film theory. The effect of internal concentration polarization on FO efficiency was also considered in the model. A pilot-scale system of FO and RO was assumed for model calculations. Results showed that the combinations of FO with seawater reverse osmosis (SWRO) have potential for desalination with high recovery (up to 80%). It was also found that FO may be incorporated with brackish reverse osmosis (BWRO) to produce high quality of water with higher flux and recovery than conventional RO-based desalination systems. [ABSTRACT FROM AUTHOR]

Reverse osmosis (RO) membranes have high rejection for most of solutes in seawater except for boron. Therefore, boron rejection should be considered in the design and operation of the RO process for seawater desalination. In this paper, we investigated boron rejection and its relation to salt rejection using an irreversible thermodynamic model. Permeability constants for commercially-available RO membranes were obtained using theoretical model and the simulation data from membrane performance test program provided by membrane manufacturers. The effect of pH and concentration of the feed water on the boron rejection was also theoretically investigated under various operating conditions. The model calculations revealed that the rejection of boron follows a different mechanism from those of other ionic solutes and could not be readily correlated with ion rejections. To overcome the limit of mechanistic models, we explored an alternative approach for predicting boron permeability from membrane properties and ion permeability. It appears that this alternative approach can aid to achieve a better understanding of boron rejection by seawater RO membranes. [ABSTRACT FROM AUTHOR]

Scale formation of soluble salts is one of the major factors limiting the performance of reverse osmosis (RO) membranes for desalination. However, it is difficult to predict membrane fouling due to scale formation in a complicated feed water containing dissolved organics such as humic substances. This study aims at prediction of the complicated fouling phenomenon by scale formation in the presence of dissolved organic matters. Experimental studies with model solutions were conducted in a small batch filtration device. Humic acid and calcium sulfate were used as model dissolved organic matters and scale-forming salts. A genetic programming technique was applied to predict the effect of dissolved organic matters on scale formation. [ABSTRACT FROM AUTHOR]

A seawater reverse osmosis (SWRO) desalination process has become an alternative technology to solve water shortage problem in the world. Although SWRO is an advanced and useful technology for humanity, there is still unsettled cost effective issue. Therefore, the estimation of operation and maintenance (O&M) costs should be significantly considered before a new construction of SWRO desalination plant. The objective of this feasibility study is to estimate total annual profits (TAP) according to O&M for a new construction of SWRO desalination plant at 9 candidate sites along the shoreline in Korea. The cost estimation model was developed and validated with Fujairah SWRO plant operation data in 2005. As a result, TAPs for the 9 candidate sites were estimated and compared with that of Fujairah SWRO plant. The result reflects that the cost estimation model in this study is able to propose a reasonable range of TAP for a new construction project of SWRO desalination plant in Korea. [ABSTRACT FROM AUTHOR]

To date, over 80 papers on transport modeling and natural organic matter (NOM) relating to sea-water reverse osmosis (SWRO), have been reviewed. As a result of such focus, NOM, one of the main foulants related to reverse osmosis (RO) membranes, has been shown to possess intrinsic chemical complexities and ambiguities, necessitating further investigation. Consequently, since such NOM fouling and transport mechanisms associated with SWRO are not fully understood, a summation of previous studies has been included in the paper in question to systematize information, not only as to RO membrane transport modeling, but NOM fouling characteristics, as well. Accordingly, RO transport models in the review are classified into three categories: diffusion-based, pore, and irreversible thermodynamic models. In addition, specific features, unique assumptions, and applications for each model are examined. The paper consists of the following components towards meaningful understanding of NOM fouling model development during SWRO: 1) SWRO fundamentals as to membranes, 2) NOM fundamentals as to seawater, 3) RO transport modeling theories, 4) conclusion, and 5) future directions of NOM fouling model development. [ABSTRACT FROM AUTHOR]

In the present study, the feasibility of a tri-hybrid desalination system for the production of electricity, energy for heating and cooling and water was studied. The tri-hybrid desalination system is a combination of a cogeneration and a desalination system. The system is composed of a generator driven by a gas engine, a gas boiler, a turbo-refrigerator, an absorption refrigerator for cogeneration, and an RO and an MED for the desalination system. The excess heat was calculated based on the electrical, heating and cooling load data and assumed that would be used for the production of water. The quantitative analysis of the product water and the energy consumption rate was compared on a month-by-month basis, and the feasibility of the tri-hybrid desalination system is explained. [ABSTRACT FROM AUTHOR]

The successful operation of a seawater reverse osmosis desalination plant depends greatly on the performance of the pretreatment step. The start-up of a pretreatment filtration process usually begins with a dynamic part called ripening, during which the filter media increases its adsorption ability and improves the removal of foulants from the seawater. In that period (typically lasting 30-60 min, depending on the system's conditions) the effluent often does not meet the quality requirements of the RO membranes and must often be disposed of. An observation and analysis of the ripening phenomena was performed using lab scale acrylic filter columns containing granular activated carbon. The seawater originated from the Yellow Sea in Korea and an inline coagulation was performed prior to filtration using an optimal dose of FeCl3 based on a jar test. The turbidity, total suspended solids concentration and dissolved organic carbon were measured before and after filtration with the goal of assessing the filtration performance. The filter media, which was cleaned and dried before filtration showed distinct ripening characteristics. The measurements were then used for parameter identification of a typical filtration model. Based on the fitted model one can predict the optimal filter depth that would reduce the waste stream production of the plant. [ABSTRACT FROM AUTHOR]

The model of salt transport through the membrane in multi-component system was developed with the irreversible thermodynamics theory considering the effect of the interaction between the salt ions. With the proposed transport model, the model for spiral-wound module was built based on the mass conservation law and concentration polarization derived by film theory. Through the parameter estimation, the frictional coefficients related to permeability of water and each ion was determined and then phenomenological analysis was conducted. The simulation results show that the salt rejection is increasing as the applied pressure and feed flow rate increasing. Also, the predictions by present model are in good agreement with the experimental data in the literature. [ABSTRACT FROM AUTHOR]

Desalination offers one of the reasonable alternatives as a solution to water scarcity. Among the desalination technologies, seawater reverse osmosis (SWRO) process becomes increasingly attractive for freshwater supply with comparatively low energy consumption and cost-effective operation. In this study, a benchmark of operating Fujairah SWRO desalination plant in the United Arab Emirates is applied to assess the relative performance of a new and large plant construction in other sites. A process model was developed to simulate the performance of SWRO desalination process and to estimate its operating cost. The developed model was validated using one-year SWRO operation data obtained from Fujairah SWRO desalination plant. Temperature and salinity data were collected from World Ocean Atlas 2005, and then applied to the model to estimate the operating cost under the site-specific conditions of 9 different countries. The results of this study present that the performance of the SWRO desalination process was significantly influenced by feed water concentration (i.e., mainly salinity) and temperature, and that the total operating cost is significantly dependent of the local electricity costs. As a conclusion, World Ocean Atlas data and the benchmark provide a method of comparing the performance of various SWRO desalination systems among different countries. Furthermore the methodology is applicable to simulate the process model with site-specific water quality data and to estimate the operating cost before a new construction of SWRO desalination plant at a target area elsewhere. [ABSTRACT FROM AUTHOR]

Recovery and salt rejection rate, which are directly related to the membrane properties and operating conditions (i.e., feed flow rate, pressure, temperature, and TDS concentration), are two main indicators for evaluating the performance of a reverse osmosis (RO) membrane process. A simple and rapid test with minimum data is inevitably requested to diagnose membrane performance at a certain operating conditions, because experiments at all operating conditions are inefficient and consumable work in the view of cost as well as man-hour. In this study, permeate flow rate and TDS concentration of three kinds of commercial RO membranes were carefully examined under various operating conditions [i.e., feed pressure (45-65 kgf/cm2) and temperature (5-30°C)]. Based on the experimental data, membrane resistance models including temperature and pressure correction factors were developed for the rapid diagnosis of SWRO membrane performances. As a result, the models developed in this study have good agreements between observed and simulated data. Based on the procedure in this study, the performance of any type of RO membranes can be rapidly examined by simple model parameter inputs. Furthermore, the developed diagnosis tool for performance test of SWRO membranes can be practically applied to build database of membrane performance for designing the SWRO process with minimum data as well as to reduce the cost and effort for data acquisition. [ABSTRACT FROM AUTHOR]

Seawater reverse osmosis (SWRO) desalination is considered one of the most promising technologies for supplying freshwater to the regions suffering from water scarcity. Although a considerable amount of research has been conducted in attempts to improve SWRO desalination technology, reducing the cost of producing freshwater is still required. In Korea, this effort is already been being carried out by the Seawater Engineering & Architecture of High Efficiency Reverse Osmosis (SeaHERO) project. Core Technology 2 (CT2), one of the most important sub-projects out of four CTs under SeaHERO, pursues two main goals: optimization of processes for low energy consumption/ high efficiency and localization of core parts/equipments of the SWRO plant. Four unit technologies (UTs) are then incorporated into CT2 and each UT has its own technical target; UT1 focuses on the development of SWRO desalination system integration and optimization technology in terms of energy saving; UT2 and 3 work to develop high performance RO membranes and 16-inch modules with polyamide-type materials and novel (i.e., non-polyamide) materials, respectively; UT4 works to develop a high-pressure/massive-capacity pump and hydrostatic energy recovery device for a high efficiency SWRO plant. Accordingly, the integration of the four UTs of CT2 in the SeaHERO project is expected to contribute to reducing the cost and energy consumption in producing freshwater from seawater using the SWRO process. [ABSTRACT FROM AUTHOR]

In this study, unlike the previous researches, the pretreatment equipment composed of a 40-μm disk filter and a hollow fiber ultra-filtration (UF) membrane was constructed. The performances of the pretreatment facilities were analyzed on the basis of 5-week-long continuous experiments using sea water. The results confirmed that the newly constructed pretreatment equipment could be used for the pretreatment of sea water reverse osmosis as evidenced by silt density index15 values below two for a long period and measured turbidities of about 0.4 NTU. The membrane fouling could be removed by using chemical enhanced backwash. Trans-membrane pressure and the permeability could be returned to the initial conditions. It reveals that UF membrane performances of the pretreatment were dependent on the sea water conditions and operating conditions. [ABSTRACT FROM AUTHOR]

Nonpoint source (NPS) pollution is widely recognized as a major source affecting the water quality deterioration in rivers, lakes, and marine environments. Many studies about the relations between NPS pollutants and solid matters from drainage area have been carried out in the area of stormwater management. This study collected stormwater and soil samples from a drainage area in Korea; the particle size distributions (PSDs) were then analyzed during four storm events. The results indicate that the PSDs of fine and medium silt in the stormwater are related to the soil component of the drainage area. In addition, solid matter was strongly related to NPS pollutant discharges such as total nitrogen and total phosphorus during stormwater runoff. Therefore, to design an NPS management facility, the PSD from the drainage area should be considered. It is expected that this study can be applied to the designs of settling ponds used to remove particles from stormwater runoff. [ABSTRACT FROM AUTHOR]

Advanced total phosphorus (TP) removal is required to regulate the TP concentrations to less than 0.2 mg/L, as specified by the South Korean policies for the prevention of aquatic eutrophication. In order to meet the standards from 2012, the treatment efficiency of conventional treatment plants should be improved. This study addresses this need by developing a novel TP removal methodology that uses a static mixer for coagulation and a redesigned sedimentation tank incorporated with a guiding baffle. Experiments were carried out during summer, autumn, and winter. Results show that: (1) the phosphorus removal efficiency was relatively higher in summer than in autumn and winter, (2) the inline static mixer increased the efficiency of soluble phosphorus removal to above 95%, and (3) optimal angle determination for the guiding baffle was essential to achieve a stable hydraulic behavior and a low shear rate at the bottom of the sedimentation tank and thus to improve the sedimentation rate. In addition, the application of combined sewer overflows sludge led to stable and high phosphorus removal efficiency (> 90%). These results indicate that the newly designed TP removal plant could serve as a prototype for an advanced treatment of phosphorus in wastewaters. [ABSTRACT FROM AUTHOR]

Nonpoint source pollutions discharged with stormwater runoff during rainfall events degrade public waterbodies. Because combined sewer overflows (CSOs) especially affect public waterbodies, necessary measures must be taken for CSOs. Therefore, this study treated CSOs using the ultra-rapid coagulation (URC) process. More than 50% of the study site was comprised of an industrial area, followed by forest, farmland and residential areas at 21.3, 2.6, and 23.5%, respectively. The 30,000 ton capacity URC process was used to treat CSOs generated from the catchment. Monitoring was conducted over 8 rainfall events, and the samples were analyzed for pollutant parameters such as total suspended solids (TSS), biochemical oxygen demand (BOD), chemical oxygen demand (CODcr), total nitrogen (TN), total phosphorus (TP), and heavy metals. At the beginning of the rainfall, the first flash effect was observed, but was not observed 20 min later. The concentration of TSS and BOD increased as the rainfall intensity became stronger in the middle stage of the rainfall. The treatment efficiency of the pollutants by the URC process was analyzed as TSS 94.4%, BOD 70.8%, CODcr 77.6%, TN 36.1%, and TP 83.5%. These treatment efficiencies were higher than those of other nonpoint pollution control facilities. Meanwhile, the removed particle size ranged from 0.1 to 10 µm or from 80 to 300µm. [ABSTRACT FROM AUTHOR]