Comparison of different model solutions to simulate membrane fouling in the ultrafiltration of a secondary effluent from a municipal wastewater treatment plant

The quality of the secondary treatment effluent (STE) from a municipal wastewater treatment plant (MWWTP) is not good enough for some applications such as agriculture. Membrane ultrafiltration (UF) has been proven to be a reliable tertiary treatment to achieve the needed water quality. The productivity of the UF processes depends on the membrane fouling. The aim of this work is to prepare a model wastewater that could mimic the fouling trend of a STE wastewater from a MWWTP. Several model wastewaters consisting of different proteins and carbohydrates were used in the UF experiments. UF was also performed with a STE. The membrane used in the UF tests was a UFCM5 from Norit X-flow® hydrophilic polyethersulfone/polyvinylpyrrolidone blend hollow-fiber UF membrane of 200 KDa molecular weight cut-off with a fiber diameter of 1.5 mm. Membrane configuration was inside-out. UF tests with model wastewater and STE wastewater were compared. The results showed that the best model wastewater, which represents the fouling trend of STE wastewater is the model wastewater whose composition is 15 mg/l of bovine serum albumin and 5.5 mg/l of dextran.The authors of this work wish to gratefully acknowledge the financial support from the Generalitat Valenciana through the program "Ayudas para la realizacion de proyectos I+D para grupos de investigacion emergentes GV/2013."Tora Grau, M.; Soler Cabezas, JL.; Vincent Vela, MC.; Mendoza Roca, JA.; Martínez Francisco, FJ. (2014). Comparison of different model solutions to simulate membrane fouling in the ultrafiltration of a secondary effluent from a municipal wastewater treatment plant. Desalination and Water Treatment. 1-7. https://doi.org/10.1080/19443994.2014.939865S17Delgado, S., Dı́az, F., Vera, L., Dı́az, R., & Elmaleh, S. (2004). Modelling hollow-fibre ultrafiltration of biologically treated wastewater with and without gas sparging. Journal of Membrane Science, 228(1), 55-63. doi:10.1016/j.memsci.2003.09.011Qin, J.-J., Oo, M. H., Lee, H., & Kolkman, R. (2004). Dead-end ultrafiltration for pretreatment of RO in reclamation of municipal wastewater effluent. Journal of Membrane Science, 243(1-2), 107-113. doi:10.1016/j.memsci.2004.06.010Konieczny, K. (1998). Disinfection of surface and ground waters with polymeric ultrafiltration membranes. Desalination, 119(1-3), 251-258. doi:10.1016/s0011-9164(98)00166-0Madaeni, S. S., Fane, A. G., & Grohmann, G. S. (1995). Virus removal from water and wastewater using membranes. Journal of Membrane Science, 102, 65-75. doi:10.1016/0376-7388(94)00252-tArnal Arnal, J. M., Sancho Fernández, M., Martín Verdú, G., & Lora García, J. (2001). Design of a membrane facility for water potabilization and its application to Third World countries. Desalination, 137(1-3), 63-69. doi:10.1016/s0011-9164(01)00205-3Arévalo, J., Garralón, G., Plaza, F., Moreno, B., Pérez, J., & Gómez, M. Á. (2009). Wastewater reuse after treatment by tertiary ultrafiltration and a membrane bioreactor (MBR): a comparative study. Desalination, 243(1-3), 32-41. doi:10.1016/j.desal.2008.04.013Katsoufidou, K., Yiantsios, S. G., & Karabelas, A. J. (2008). An experimental study of UF membrane fouling by humic acid and sodium alginate solutions: the effect of backwashing on flux recovery. Desalination, 220(1-3), 214-227. doi:10.1016/j.desal.2007.02.038Muthukumaran, S., Nguyen, D. A., & Baskaran, K. (2011). Performance evaluation of different ultrafiltration membranes for the reclamation and reuse of secondary effluent. Desalination, 279(1-3), 383-389. doi:10.1016/j.desal.2011.06.040Henderson, R. K., Subhi, N., Antony, A., Khan, S. J., Murphy, K. R., Leslie, G. L., … Le-Clech, P. (2011). Evaluation of effluent organic matter fouling in ultrafiltration treatment using advanced organic characterisation techniques. Journal of Membrane Science, 382(1-2), 50-59. doi:10.1016/j.memsci.2011.07.041Fan, L., Nguyen, T., Roddick, F. A., & Harris, J. L. (2008). Low-pressure membrane filtration of secondary effluent in water reuse: Pre-treatment for fouling reduction. Journal of Membrane Science, 320(1-2), 135-142. doi:10.1016/j.memsci.2008.03.058Xiao, D., Li, W., Chou, S., Wang, R., & Tang, C. Y. (2012). A modeling investigation on optimizing the design of forward osmosis hollow fiber modules. Journal of Membrane Science, 392-393, 76-87. doi:10.1016/j.memsci.2011.12.006Kaya, Y., Barlas, H., & Arayici, S. (2011). Evaluation of fouling mechanisms in the nanofiltration of solutions with high anionic and nonionic surfactant contents using a resistance-in-series model. Journal of Membrane Science, 367(1-2), 45-54. doi:10.1016/j.memsci.2010.10.037Yu, C.-H., Fang, L.-C., Lateef, S. K., Wu, C.-H., & Lin, C.-F. (2010). Enzymatic treatment for controlling irreversible membrane fouling in cross-flow humic acid-fed ultrafiltration. Journal of Hazardous Materials, 177(1-3), 1153-1158. doi:10.1016/j.jhazmat.2010.01.022Gao, W., Liang, H., Ma, J., Han, M., Chen, Z., Han, Z., & Li, G. (2011). Membrane fouling control in ultrafiltration technology for drinking water production: A review. Desalination, 272(1-3), 1-8. doi:10.1016/j.desal.2011.01.051Amin Saad, M. (2004). Early discovery of RO membrane fouling and real-time monitoring of plant performance for optimizing cost of water. Desalination, 165, 183-191. doi:10.1016/j.desal.2004.06.021Jayalakshmi, A., Rajesh, S., & Mohan, D. (2012). Fouling propensity and separation efficiency of epoxidated polyethersulfone incorporated cellulose acetate ultrafiltration membrane in the retention of proteins. Applied Surface Science, 258(24), 9770-9781. doi:10.1016/j.apsusc.2012.06.028Qu, F., Liang, H., Wang, Z., Wang, H., Yu, H., & Li, G. (2012). Ultrafiltration membrane fouling by extracellular organic matters (EOM) of Microcystis aeruginosa in stationary phase: Influences of interfacial characteristics of foulants and fouling mechanisms. Water Research, 46(5), 1490-1500. doi:10.1016/j.watres.2011.11.051Wang, C., Li, Q., Tang, H., Yan, D., Zhou, W., Xing, J., & Wan, Y. (2012). Membrane fouling mechanism in ultrafiltration of succinic acid fermentation broth. Bioresource Technology, 116, 366-371. doi:10.1016/j.biortech.2012.03.099Nataraj, S., Schomäcker, R., Kraume, M., Mishra, I. M., & Drews, A. (2008). Analyses of polysaccharide fouling mechanisms during crossflow membrane filtration. Journal of Membrane Science, 308(1-2), 152-161. doi:10.1016/j.memsci.2007.09.060Zator, M., Ferrando, M., López, F., & Güell, C. (2007). Membrane fouling characterization by confocal microscopy during filtration of BSA/dextran mixtures. Journal of Membrane Science, 301(1-2), 57-66. doi:10.1016/j.memsci.2007.05.038Xiao, K., Wang, X., Huang, X., Waite, T. D., & Wen, X. (2009). Analysis of polysaccharide, protein and humic acid retention by microfiltration membranes using Thomas’ dynamic adsorption model. Journal of Membrane Science, 342(1-2), 22-34. doi:10.1016/j.memsci.2009.06.016Nigam, M. O., Bansal, B., & Chen, X. D. (2008). Fouling and cleaning of whey protein concentrate fouled ultrafiltration membranes. Desalination, 218(1-3), 313-322. doi:10.1016/j.desal.2007.02.027MOUROUZIDISMOUROUZIS, S., & KARABELAS, A. (2006). Whey protein fouling of microfiltration ceramic membranes—Pressure effects. Journal of Membrane Science, 282(1-2), 124-132. doi:10.1016/j.memsci.2006.05.012Carić, M. Đ., Milanović, S. D., Krstić, D. M., & Tekić, M. N. (2000). Fouling of inorganic membranes by adsorption of whey proteins. Journal of Membrane Science, 165(1), 83-88. doi:10.1016/s0376-7388(99)00221-5Tasselli, F., Cassano, A., & Drioli, E. (2007). Ultrafiltration of kiwifruit juice using modified poly(ether ether ketone) hollow fibre membranes. Separation and Purification Technology, 57(1), 94-102. doi:10.1016/j.seppur.2007.03.007Hao, Y., Moriya, A., Maruyama, T., Ohmukai, Y., & Matsuyama, H. (2011). Effect of metal ions on humic acid fouling of hollow fiber ultrafiltration membrane. Journal of Membrane Science, 376(1-2), 247-253. doi:10.1016/j.memsci.2011.04.035Marcos, B., Moresoli, C., Skorepova, J., & Vaughan, B. (2009). CFD modeling of a transient hollow fiber ultrafiltration system for protein concentration. Journal of Membrane Science, 337(1-2), 136-144. doi:10.1016/j.memsci.2009.03.036Chung, T.-S., Qin, J.-J., & Gu, J. (2000). Effect of shear rate within the spinneret on morphology, separation performance and mechanical properties of ultrafiltration polyethersulfone hollow fiber membranes. Chemical Engineering Science, 55(6), 1077-1091. doi:10.1016/s0009-2509(99)00371-1Nguyen, T.-A., Yoshikawa, S., Karasu, K., & Ookawara, S. (2012). A simple combination model for filtrate flux in cross-flow ultrafiltration of protein suspension. Journal of Membrane Science, 403-404, 84-93. doi:10.1016/j.memsci.2012.02.026Domínguez Chabaliná, L., Rodríguez Pastor, M., & Rico, D. P. (2013). Characterization of soluble and bound EPS obtained from 2 submerged membrane bioreactors by 3D-EEM and HPSEC. Talanta, 115, 706-712. doi:10.1016/j.talanta.2013.05.062Viebke, C. (2000). Determination of molecular mass distribution of κ-carrageenan and xanthan using asymmetrical flow field-flow fractionation. Food Hydrocolloids, 14(3), 265-270. doi:10.1016/s0268-005x(99)00066-1Kelly, S. T., & Zydney, A. L. (1995). Mechanisms for BSA fouling during microfiltration. Journal of Membrane Science, 107(1-2), 115-127. doi:10.1016/0376-7388(95)00108-oHwang, K.-J., & Sz, P.-Y. (2011). Membrane fouling mechanism and concentration effect in cross-flow microfiltration of BSA/dextran mixtures. Chemical Engineering Journal, 166(2), 669-677. doi:10.1016/j.cej.2010.11.04

Study of the influence of operational conditions and hollow-fiber diameter on the ultrafiltration performance of a secondary treatment effluent

Secondary treatment effluents from municipal wastewater treatment plants (MWWTP) must achieve high water quality standards for their reuse in agriculture. To achieve these standards, ultrafiltration (UF) process, which is economically feasible, is carried out. However, UF has a drawback, membrane fouling, which causes operating difficulties and an increment of the operating cost. In order to minimize this phenomenon, it is important to determine the best operational conditions. Wastewater samples provided by MWWTP have a lot of variability in their composition due to factors such as temperature, efficiency of the secondary treatment, etc. Besides, the soluble microbial products of the secondary effluent are dependent on the type of the biological treatment implemented and its operating conditions. A model wastewater feed solution was prepared consisting of 15 mg/L of bovine serum albumin and 5.5 mg/L of dextran. In this research, UF tests were performed with the optimal simulated wastewater using two membranes UFCM5 Norit X-flow® hollow-fiber: one of them with a fiber diameter of 1.5 mm and the other one with a fiber diameter of 0.8 mm. The operational conditions, which influence membrane fouling, were varied in the range of 62 100 kPa for transmembrane pressure (TMP) and in the range of 0.8 1.2 m/s for cross-flow velocity (CFV). The best operational conditions were selected in terms of higher permeate flux. The highest permeate flux was obtained for the membrane of 0.8 mm and the lower energy consumption was achieved at a CFV of 1.2 m/s and a TMP of 62 kPa.Torà Grau, M.; Soler Cabezas, JL.; Vincent Vela, MC.; Mendoza Roca, JA.; Martínez Francisco, FJ. (2015). Study of the influence of operational conditions and hollow-fiber diameter on the ultrafiltration performance of a secondary treatment effluent. Desalination and Water Treatment. 1-7. doi:10.1080/19443994.2015.1118887S1

Ultrafiltration fouling trend simulation of a municipal wastewater treatment plant effluent with model wastewater

Secondary treatment effluents from Municipal Wastewater Treatment Plants require tertiary treatments to be reused in agriculture. Among tertiary treatment technologies, ultrafiltration has been proven to be a reliable reclamation process. Nevertheless this technique has an important disadvantage: membrane fouling. This phenomenon causes decline in permeate flux with time and increases the operational costs. Due to the fact that secondary effluents from Municipal Wastewater Treatment Plants contain a large amount of different compounds and that there is certain variability in their composition, the use of a simplified model wastewater consisting of only few compounds may help to simulate better the ultrafiltration fouling trend. The main secondary treatment effluent components responsible for fouling membrane during ultrafiltration tests are extracellular polymeric substances. These substances are mainly composed of proteins and polysaccharides, thus they are commonly used to prepare model wastewaters. This work consisted in two parts. Firstly, a model wastewater was selected among different model solutions mimicking secondary treatment effluent. Secondly, ultrafiltration behaviour of the selected model solution was compared with the behaviour of the secondary effluent in the ultrafiltration tests at different cross-flow velocities and transmembrane pressures. The membrane used in the ultrafiltration tests was UFCM5 Norit X-flow® hollow-fiber. To prepare model wastewaters, three parameters (proteins and carbohydrates concentrations and chemical oxygen demand) were considered. The model wastewater that represented the best the fouling trend of the secondary treatment effluent had a composition of 15 mg/l of bovine serum albumin and 5.5 mg/l of dextranThe authors wish to gratefully acknowledge the financial support of the Generalitat Valenciana through the project "Ayudas para la realizacion de proyectos I+D para grupos de investigacion emergentes GV/2013."Tora Grau, M.; Soler Cabezas, JL.; Vincent Vela, MC.; Mendoza Roca, JA.; Martínez Francisco, FJ. (2015). Ultrafiltration fouling trend simulation of a municipal wastewater treatment plant effluent with model wastewater. Desalination and Water Treatment. 1-9. doi:10.1080/19443994.2014.999714S19Qin, J.-J., Oo, M. H., Lee, H., & Kolkman, R. (2004). Dead-end ultrafiltration for pretreatment of RO in reclamation of municipal wastewater effluent. Journal of Membrane Science, 243(1-2), 107-113. doi:10.1016/j.memsci.2004.06.010Arévalo, J., Garralón, G., Plaza, F., Moreno, B., Pérez, J., & Gómez, M. Á. (2009). Wastewater reuse after treatment by tertiary ultrafiltration and a membrane bioreactor (MBR): a comparative study. Desalination, 243(1-3), 32-41. doi:10.1016/j.desal.2008.04.013Katsoufidou, K., Yiantsios, S. G., & Karabelas, A. J. (2008). An experimental study of UF membrane fouling by humic acid and sodium alginate solutions: the effect of backwashing on flux recovery. Desalination, 220(1-3), 214-227. doi:10.1016/j.desal.2007.02.038Muthukumaran, S., Nguyen, D. A., & Baskaran, K. (2011). Performance evaluation of different ultrafiltration membranes for the reclamation and reuse of secondary effluent. Desalination, 279(1-3), 383-389. doi:10.1016/j.desal.2011.06.040Henderson, R. K., Subhi, N., Antony, A., Khan, S. J., Murphy, K. R., Leslie, G. L., … Le-Clech, P. (2011). Evaluation of effluent organic matter fouling in ultrafiltration treatment using advanced organic characterisation techniques. Journal of Membrane Science, 382(1-2), 50-59. doi:10.1016/j.memsci.2011.07.041Muthukumaran, S., Jegatheesan, J. V., & Baskaran, K. (2013). Comparison of fouling mechanisms in low-pressure membrane (MF/UF) filtration of secondary effluent. Desalination and Water Treatment, 52(4-6), 650-662. doi:10.1080/19443994.2013.826324Yu, C.-H., Fang, L.-C., Lateef, S. K., Wu, C.-H., & Lin, C.-F. (2010). Enzymatic treatment for controlling irreversible membrane fouling in cross-flow humic acid-fed ultrafiltration. Journal of Hazardous Materials, 177(1-3), 1153-1158. doi:10.1016/j.jhazmat.2010.01.022Gao, W., Liang, H., Ma, J., Han, M., Chen, Z., Han, Z., & Li, G. (2011). Membrane fouling control in ultrafiltration technology for drinking water production: A review. Desalination, 272(1-3), 1-8. doi:10.1016/j.desal.2011.01.051Kaya, Y., Barlas, H., & Arayici, S. (2011). Evaluation of fouling mechanisms in the nanofiltration of solutions with high anionic and nonionic surfactant contents using a resistance-in-series model. Journal of Membrane Science, 367(1-2), 45-54. doi:10.1016/j.memsci.2010.10.037Delgado, S., Dı́az, F., Vera, L., Dı́az, R., & Elmaleh, S. (2004). Modelling hollow-fibre ultrafiltration of biologically treated wastewater with and without gas sparging. Journal of Membrane Science, 228(1), 55-63. doi:10.1016/j.memsci.2003.09.011Fan, L., Nguyen, T., Roddick, F. A., & Harris, J. L. (2008). Low-pressure membrane filtration of secondary effluent in water reuse: Pre-treatment for fouling reduction. Journal of Membrane Science, 320(1-2), 135-142. doi:10.1016/j.memsci.2008.03.058Xiao, D., Li, W., Chou, S., Wang, R., & Tang, C. Y. (2012). A modeling investigation on optimizing the design of forward osmosis hollow fiber modules. Journal of Membrane Science, 392-393, 76-87. doi:10.1016/j.memsci.2011.12.006Zator, M., Ferrando, M., López, F., & Güell, C. (2007). Membrane fouling characterization by confocal microscopy during filtration of BSA/dextran mixtures. Journal of Membrane Science, 301(1-2), 57-66. doi:10.1016/j.memsci.2007.05.038Nataraj, S., Schomäcker, R., Kraume, M., Mishra, I. M., & Drews, A. (2008). Analyses of polysaccharide fouling mechanisms during crossflow membrane filtration. Journal of Membrane Science, 308(1-2), 152-161. doi:10.1016/j.memsci.2007.09.060Nguyen, S. T., & Roddick, F. A. (2011). Chemical cleaning of ultrafiltration membrane fouled by an activated sludge effluent. Desalination and Water Treatment, 34(1-3), 94-99. doi:10.5004/dwt.2011.2790Xiao, K., Wang, X., Huang, X., Waite, T. D., & Wen, X. (2009). Analysis of polysaccharide, protein and humic acid retention by microfiltration membranes using Thomas’ dynamic adsorption model. Journal of Membrane Science, 342(1-2), 22-34. doi:10.1016/j.memsci.2009.06.016Hwang, K.-J., & Chiang, Y.-C. (2014). Comparisons of membrane fouling and separation efficiency in protein/polysaccharide cross-flow microfiltration using membranes with different morphologies. Separation and Purification Technology, 125, 74-82. doi:10.1016/j.seppur.2014.01.041Yamamura, H., Okimoto, K., Kimura, K., & Watanabe, Y. (2014). Hydrophilic fraction of natural organic matter causing irreversible fouling of microfiltration and ultrafiltration membranes. Water Research, 54, 123-136. doi:10.1016/j.watres.2014.01.024Nigam, M. O., Bansal, B., & Chen, X. D. (2008). Fouling and cleaning of whey protein concentrate fouled ultrafiltration membranes. Desalination, 218(1-3), 313-322. doi:10.1016/j.desal.2007.02.027MOUROUZIDISMOUROUZIS, S., & KARABELAS, A. (2006). Whey protein fouling of microfiltration ceramic membranes—Pressure effects. Journal of Membrane Science, 282(1-2), 124-132. doi:10.1016/j.memsci.2006.05.012Carić, M. Đ., Milanović, S. D., Krstić, D. M., & Tekić, M. N. (2000). Fouling of inorganic membranes by adsorption of whey proteins. Journal of Membrane Science, 165(1), 83-88. doi:10.1016/s0376-7388(99)00221-5Tasselli, F., Cassano, A., & Drioli, E. (2007). Ultrafiltration of kiwifruit juice using modified poly(ether ether ketone) hollow fibre membranes. Separation and Purification Technology, 57(1), 94-102. doi:10.1016/j.seppur.2007.03.007Vincent-Vela, M.-C., Álvarez-Blanco, S., Lora-García, J., & Bergantiños-Rodríguez, E. (2009). Estimation of the gel layer concentration in ultrafiltration: Comparison of different methods. Desalination and Water Treatment, 3(1-3), 157-161. doi:10.5004/dwt.2009.454Valiño, V., San Román, M. F., Ibáñez, R., Benito, J. M., Escudero, I., & Ortiz, I. (2014). Accurate determination of key surface properties that determine the efficient separation of bovine milk BSA and LF proteins. Separation and Purification Technology, 135, 145-157. doi:10.1016/j.seppur.2014.07.051Luck, P. J., Vardhanabhuti, B., Yong, Y. H., Laundon, T., Barbano, D. M., & Foegeding, E. A. (2013). Comparison of functional properties of 34% and 80% whey protein and milk serum protein concentrates. Journal of Dairy Science, 96(9), 5522-5531. doi:10.3168/jds.2013-6617Marcos, B., Moresoli, C., Skorepova, J., & Vaughan, B. (2009). CFD modeling of a transient hollow fiber ultrafiltration system for protein concentration. Journal of Membrane Science, 337(1-2), 136-144. doi:10.1016/j.memsci.2009.03.036Chung, T.-S., Qin, J.-J., & Gu, J. (2000). Effect of shear rate within the spinneret on morphology, separation performance and mechanical properties of ultrafiltration polyethersulfone hollow fiber membranes. Chemical Engineering Science, 55(6), 1077-1091. doi:10.1016/s0009-2509(99)00371-1Salahi, A., Mohammadi, T., Rahmat Pour, A., & Rekabdar, F. (2009). Oily wastewater treatment using ultrafiltration. Desalination and Water Treatment, 6(1-3), 289-298. doi:10.5004/dwt.2009.480Janssen, A. N., van Agtmaal, J., van den Broek, W. B. P., de Koning, J., Menkveld, H. W. H., Schrotter, J.-C., … van der Graaf, J. H. J. M. (2008). Monitoring of SUR to control and enhance the performance of dead-end ultrafiltration installations treating wwtp effluent. Desalination, 231(1-3), 99-107. doi:10.1016/j.desal.2007.10.024Torà-Grau, M., Soler-Cabezas, J. L., Vincent-Vela, M. C., Mendoza-Roca, J. A., & Martínez-Francisco, F. J. (2014). Comparison of different model solutions to simulate membrane fouling in the ultrafiltration of a secondary effluent from a municipal wastewater treatment plant. Desalination and Water Treatment, 1-7. doi:10.1080/19443994.2014.93986

Ultrafiltration of municipal wastewater: study on fouling models and fouling mechanisms

Ultrafiltration (UF) with hollow fiber membranes is a proven membrane technique that can achieve high water quality standards as a tertiary treatment in municipal wastewater treatment plants. However, UF has a major drawback, membrane fouling, which causes losses of productivity and increases operation costs. Thus, the aim of this work is to model membrane fouling in the UF of a secondary treatment effluent. The tests were carried out with a model wastewater solution that consisted of bovine serum albumin and dextran. Three different transmembrane pressures and three different crossflow velocities were tested. Several fouling models available in the literature, and new models proposed, were fitted to permeate flux decline experimental data. The models studied by other authors and considered in this study were: Hermia s models (complete, intermediate, standard pore blocking and gel layer) and Belfort s model. The new models proposed in this work were: modified Belfort s model, quadratic exponential model, logarithmic inversed model, double exponential model and tangent inversed model. The fitting accuracy of the models was determined in terms of the R-squared and standard deviation. The results showed that the model that had the higher fitting accuracy was the logarithmic inversed model. Among the Hermia s models, the model that had the higher fitting accuracy was the intermediate pore blocking model. Therefore, the predominant fouling mechanism was determined and it was the intermediate pore blocking modelThe authors wish to gratefully acknowledge the financial support of the Generalitat Valenciana through the project "Ayudas para la realizacion de proyectos I+D para grupos de investigacion emergentes GV/2013".Soler Cabezas, JL.; Tora Grau, M.; Vincent Vela, MC.; Mendoza Roca, JA.; Martínez Francisco, FJ. (2014). Ultrafiltration of municipal wastewater: study on fouling models and fouling mechanisms. Desalination and Water Treatment. 1-11. doi:10.1080/19443994.2014.969320S111Gadani, V., Irwin, R., & Mandra, V. (1996). Ultrafiltration as a tertiary treatment: Joint research program on membranes. Desalination, 106(1-3), 47-53. doi:10.1016/s0011-9164(96)00091-4Illueca-Muñoz, J., Mendoza-Roca, J. A., Iborra-Clar, A., Bes-Piá, A., Fajardo-Montañana, V., Martínez-Francisco, F. J., & Bernácer-Bonora, I. (2008). Study of different alternatives of tertiary treatments for wastewater reclamation to optimize the water quality for irrigation reuse. Desalination, 222(1-3), 222-229. doi:10.1016/j.desal.2007.01.157Muthukumaran, S., Jegatheesan, J. V., & Baskaran, K. (2013). Comparison of fouling mechanisms in low-pressure membrane (MF/UF) filtration of secondary effluent. Desalination and Water Treatment, 52(4-6), 650-662. doi:10.1080/19443994.2013.826324Delgado, S., Dı́az, F., Vera, L., Dı́az, R., & Elmaleh, S. (2004). Modelling hollow-fibre ultrafiltration of biologically treated wastewater with and without gas sparging. Journal of Membrane Science, 228(1), 55-63. doi:10.1016/j.memsci.2003.09.011Qin, J.-J., Oo, M. H., Lee, H., & Kolkman, R. (2004). Dead-end ultrafiltration for pretreatment of RO in reclamation of municipal wastewater effluent. Journal of Membrane Science, 243(1-2), 107-113. doi:10.1016/j.memsci.2004.06.010Konieczny, K. (1998). Disinfection of surface and ground waters with polymeric ultrafiltration membranes. Desalination, 119(1-3), 251-258. doi:10.1016/s0011-9164(98)00166-0Madaeni, S. S., Fane, A. G., & Grohmann, G. S. (1995). Virus removal from water and wastewater using membranes. Journal of Membrane Science, 102, 65-75. doi:10.1016/0376-7388(94)00252-tArnal Arnal, J. M., Sancho Fernández, M., Martín Verdú, G., & Lora García, J. (2001). Design of a membrane facility for water potabilization and its application to Third World countries. Desalination, 137(1-3), 63-69. doi:10.1016/s0011-9164(01)00205-3Arévalo, J., Garralón, G., Plaza, F., Moreno, B., Pérez, J., & Gómez, M. Á. (2009). Wastewater reuse after treatment by tertiary ultrafiltration and a membrane bioreactor (MBR): a comparative study. Desalination, 243(1-3), 32-41. doi:10.1016/j.desal.2008.04.013Katsoufidou, K., Yiantsios, S. G., & Karabelas, A. J. (2008). An experimental study of UF membrane fouling by humic acid and sodium alginate solutions: the effect of backwashing on flux recovery. Desalination, 220(1-3), 214-227. doi:10.1016/j.desal.2007.02.038Muthukumaran, S., Nguyen, D. A., & Baskaran, K. (2011). Performance evaluation of different ultrafiltration membranes for the reclamation and reuse of secondary effluent. Desalination, 279(1-3), 383-389. doi:10.1016/j.desal.2011.06.040Henderson, R. K., Subhi, N., Antony, A., Khan, S. J., Murphy, K. 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Objective Evaluation of Multiple Sclerosis Lesion Segmentation using a Data Management and Processing Infrastructure

We present a study of multiple sclerosis segmentation algorithms conducted at the international MICCAI 2016 challenge. This challenge was operated using a new open-science computing infrastructure. This allowed for the automatic and independent evaluation of a large range of algorithms in a fair and completely automatic manner. This computing infrastructure was used to evaluate thirteen methods of MS lesions segmentation, exploring a broad range of state-of-theart algorithms, against a high-quality database of 53 MS cases coming from four centers following a common definition of the acquisition protocol. Each case was annotated manually by an unprecedented number of seven different experts. Results of the challenge highlighted that automatic algorithms, including the recent machine learning methods (random forests, deep learning, …), are still trailing human expertise on both detection and delineation criteria. In addition, we demonstrate that computing a statistically robust consensus of the algorithms performs closer to human expertise on one score (segmentation) although still trailing on detection scores

Naturalized alien flora of the world: species diversity, taxonomic and phylogenetic patterns, geographic distribution and global hotspots of plant invasion

Using the recently built Global Naturalized Alien Flora (GloNAF) database, containing data on the distribution of naturalized alien plants in 483 mainland and 361 island regions of the world, we describe patterns in diversity and geographic distribution of naturalized and invasive plant species, taxonomic, phylogenetic and life-history structure of the global naturalized flora as well as levels of naturalization and their determinants. The mainland regions with the highest numbers of naturalized aliens are some Australian states (with New South Wales being the richest on this continent) and several North American regions (of which California with 1753 naturalized plant species represents the world's richest region in terms of naturalized alien vascular plants). England, Japan, New Zealand and the Hawaiian archipelago harbour most naturalized plants among islands or island groups. These regions also form the main hotspots of the regional levels of naturalization, measured as the percentage of naturalized aliens in the total flora of the region. Such hotspots of relative naturalized species richness appear on both the western and eastern coasts of North America, in north-western Europe, South Africa, south-eastern Australia, New Zealand, and India. High levels of island invasions by naturalized plants are concentrated in the Pacific, but also occur on individual islands across all oceans. The numbers of naturalized species are closely correlated with those of native species, with a stronger correlation and steeper increase for islands than mainland regions, indicating a greater vulnerability of islands to invasion by species that become successfully naturalized. South Africa, India, California, Cuba, Florida, Queensland and Japan have the highest numbers of invasive species. Regions in temperate and tropical zonobiomes harbour in total 9036 and 6774 naturalized species, respectively, followed by 3280 species naturalized in the Mediterranean zonobiome, 3057 in the subtropical zonobiome and 321 in the Arctic. The New World is richer in naturalized alien plants, with 9905 species compared to 7923 recorded in the Old World. While isolation is the key factor driving the level of naturalization on islands, zonobiomes differing in climatic regimes, and socioeconomy represented by per capita GDP, are central for mainland regions. The 11 most widely distributed species each occur in regions covering about one third of the globe or more in terms of the number of regions where they are naturalized and at least 35% of the Earth's land surface in terms of those regions' areas, with the most widely distributed species Sonchus oleraceus occuring in 48% of the regions that cover 42% of the world area. Other widely distributed species are Ricinus communis, Oxalis corniculata, Portulaca oleracea, Eleusine indica, Chenopodium album, Capsella bursa-pastoris, Stellaria media, Bidens pilosa, Datura stramonium and Echinochloa crus-galli. Using the occurrence as invasive rather than only naturalized yields a different ranking, with Lantana camara (120 regions out of 349 for which data on invasive status are known), Calotropis procera (118), Eichhornia crassipes (113), Sonchus oleraceus (108) and Leucaena leucocephala (103) on top. As to the life-history spectra, islands harbour more naturalized woody species (34.4%) than mainland regions (29.5%), and fewer annual herbs (18.7% compared to 22.3%). Ranking families by their absolute numbers of naturalized species reveals that Compositae (1343 species), Poaceae (1267) and Leguminosae (1189) contribute most to the global naturalized alien flora. Some families are disproportionally represented by naturalized aliens on islands (Arecaceae, Araceae, Acanthaceae, Amaryllidaceae, Asparagaceae, Convolvulaceae, Rubiaceae, Malvaceae), and much fewer so on mainland (e.g. Brassicaceae, Caryophyllaceae, Boraginaceae). Relating the numbers of naturalized species in a family to its total global richness shows that some of the large species-rich families are over-represented among naturalized aliens (e.g. Poaceae, Leguminosae, Rosaceae, Amaranthaceae, Pinaceae), some under-represented (e.g. Euphorbiaceae, Rubiaceae), whereas the one richest in naturalized species, Compositae, reaches a value expected from its global species richness. Significant phylogenetic signal indicates that families with an increased potential of their species to naturalize are not distributed randomly on the evolutionary tree. Solanum (112 species), Euphorbia (108) and Carex (106) are the genera richest in terms of naturalized species; over-represented on islands are Cotoneaster, Juncus, Eucalyptus, Salix, Hypericum, Geranium and Persicaria, while those relatively richer in naturalized species on the mainland are Atriplex, Opuntia, Oenothera, Artemisia, Vicia, Galium and Rosa. The data presented in this paper also point to where information is lacking and set priorities for future data collection. The GloNAF database has potential for designing concerted action to fill such data gaps, and provide a basis for allocating resources most efficiently towards better understanding and management of plant invasions worldwide

The comparative responsiveness of Hospital Universitario Princesa Index and other composite indices for assessing rheumatoid arthritis activity

Objective To evaluate the responsiveness in terms of correlation of the Hospital Universitario La Princesa Index (HUPI) comparatively to the traditional composite indices used to assess disease activity in rheumatoid arthritis (RA), and to compare the performance of HUPI-based response criteria with that of the EULAR response criteria. Methods Secondary data analysis from the following studies: ACT-RAY (clinical trial), PROAR (early RA cohort) and EMECAR (pre-biologic era long term RA cohort). Responsiveness was evaluated by: 1) comparing change from baseline (Delta) of HUPI with Delta in other scores by calculating correlation coefficients; 2) calculating standardised effect sizes. The accuracy of response by HUPI and by EULAR criteria was analyzed using linear regressions in which the dependent variable was change in global assessment by physician (Delta GDA-Phy). Results Delta HUPI correlation with change in all other indices ranged from 0.387 to 0.791); HUPI's standardized effect size was larger than those from the other indices in each database used. In ACT-RAY, depending on visit, between 65 and 80% of patients were equally classified by HUPI and EULAR response criteria. However, HUPI criteria were slightly more stringent, with higher percentage of patients classified as non-responder, especially at early visits. HUPI response criteria showed a slightly higher accuracy than EULAR response criteria when using Delta GDA-Phy as gold standard. Conclusion HUPI shows good responsiveness in terms of correlation in each studied scenario (clinical trial, early RA cohort, and established RA cohort). Response criteria by HUPI seem more stringent than EULAR''s

Deep-sequencing reveals broad subtype-specific HCV resistance mutations associated with treatment failure

A percentage of hepatitis C virus (HCV)-infected patients fail direct acting antiviral (DAA)-based treatment regimens, often because of drug resistance-associated substitutions (RAS). The aim of this study was to characterize the resistance profile of a large cohort of patients failing DAA-based treatments, and investigate the relationship between HCV subtype and failure, as an aid to optimizing management of these patients. A new, standardized HCV-RAS testing protocol based on deep sequencing was designed and applied to 220 previously subtyped samples from patients failing DAA treatment, collected in 39 Spanish hospitals. The majority had received DAA-based interferon (IFN) a-free regimens; 79% had failed sofosbuvir-containing therapy. Genomic regions encoding the nonstructural protein (NS) 3, NS5A, and NS5B (DAA target regions) were analyzed using subtype-specific primers. Viral subtype distribution was as follows: genotype (G) 1, 62.7%; G3a, 21.4%; G4d, 12.3%; G2, 1.8%; and mixed infections 1.8%. Overall, 88.6% of patients carried at least 1 RAS, and 19% carried RAS at frequencies below 20% in the mutant spectrum. There were no differences in RAS selection between treatments with and without ribavirin. Regardless of the treatment received, each HCV subtype showed specific types of RAS. Of note, no RAS were detected in the target proteins of 18.6% of patients failing treatment, and 30.4% of patients had RAS in proteins that were not targets of the inhibitors they received. HCV patients failing DAA therapy showed a high diversity of RAS. Ribavirin use did not influence the type or number of RAS at failure. The subtype-specific pattern of RAS emergence underscores the importance of accurate HCV subtyping. The frequency of “extra-target” RAS suggests the need for RAS screening in all three DAA target regions

7th Drug hypersensitivity meeting: part two

No abstract availabl