Environmental impact of submerged anaerobic MBR (SAnMBR) technology used to treat urban wastewater at different temperatures

[EN] The objective of this study was to assess the environmental impact of a submerged anaerobic MBR (SAnMBR) system in the treatment of urban wastewater at different temperatures: ambient temperature (20 and 33 degrees C), and a controlled temperature (33 degrees C). To this end, an overall energy balance (OEB) and life cycle assessment (LCA), both based on real process data, were carried out. Four factors were considered in this study; (1) energy consumption during wastewater treatment; (2) energy recovered from biogas capture; (3) potential recovery of nutrients from the final effluent; and (4) sludge disposal. The OEB and LCA showed SAnMBR to be a promising technology for treating urban wastewater at ambient temperature (OEB = 0.19 kW h m(-3)). LCA results reinforce the importance of maximising the recovery of nutrients (environmental impact in eutrophication can be reduced up to 45%) and dissolved methane (positive environmental impact can be obtained) from SAnMBR effluent. (C) 2013 Elsevier Ltd. All rights reserved.This research work has been supported by the Spanish Ministry of Science and Innovation (MICINN, Project CTM2011-28595-CO2-01/02) jointly with the European Regional Development Fund (ERDF) which are gratefully acknowledged.Pretel, R.; Robles Martínez, Á.; Ruano García, MV.; Seco Torrecillas, A.; Ferrer, J. (2013). Environmental impact of submerged anaerobic MBR (SAnMBR) technology used to treat urban wastewater at different temperatures. Bioresource Technology. 149:532-540. https://doi.org/10.1016/j.biortech.2013.09.060S53254014

A plant-wide energy model for wastewater treatment plants: application to anaerobic membrane bioreactor technology

[EN] The aim of this study is to propose a detailed and comprehensive plant-wide model for assessing the energy demand of different wastewater treatment systems (beyond the traditional activated sludge) in both steady- and unsteady-state conditions. The proposed model makes it possible to calculate power and heat requirements (W and Q, respectively), and to recover both power and heat from methane and hydrogen capture. In order to account for the effect of biological processes on heat requirements, the model has been coupled to the extended version of the BNRM2 plant-wide mathematical model, which is implemented in DESSAS simulation software. Two case studies have been evaluated to assess the model's performance: (1) modelling the energy demand of two urban wastewater treatment plants based on conventional activated sludge and submerged anaerobic membrane bioreactor (AnMBR) technologies in steady-state conditions and (2) modelling the dynamics of reactor temperature and heat requirements in an AnMBR plant in unsteady-state conditions. The results indicate that the proposed model can be used to assess the energy performance of different wastewater treatment processes and would thus be useful, for example, WWTP design or upgrading or the development of new control strategies for energy savings.This research work has been supported by the Spanish Ministry of Science and Innovation [MICINN, Project CTM2011-28595-C02-01/02] jointly with the European Regional Development Fund (ERDF).Pretel-Jolis, R.; Robles Martínez, Á.; Ruano García, MV.; Seco, A.; Ferrer, J. (2016). A plant-wide energy model for wastewater treatment plants: application to anaerobic membrane bioreactor technology. Environmental Technology. 37(18):2298-2315. https://doi.org/10.1080/09593330.2016.1148903S229823153718Olsson, G., Carlsson, B., Comas, J., Copp, J., Gernaey, K. V., Ingildsen, P., … Åmand, L. (2014). Instrumentation, control and automation in wastewater – from London 1973 to Narbonne 2013. Water Science and Technology, 69(7), 1373-1385. doi:10.2166/wst.2014.057Nicolae, B., & George-Vlad, B. (2015). Life cycle analysis in refurbishment of the buildings as intervention practices in energy saving. Energy and Buildings, 86, 74-85. doi:10.1016/j.enbuild.2014.10.021Corominas, L., Foley, J., Guest, J. S., Hospido, A., Larsen, H. F., Morera, S., & Shaw, A. (2013). Life cycle assessment applied to wastewater treatment: State of the art. Water Research, 47(15), 5480-5492. doi:10.1016/j.watres.2013.06.049Bauer, A., Bösch, P., Friedl, A., & Amon, T. (2009). Analysis of methane potentials of steam-exploded wheat straw and estimation of energy yields of combined ethanol and methane production. Journal of Biotechnology, 142(1), 50-55. doi:10.1016/j.jbiotec.2009.01.017Venkatesh, G., & Elmi, R. A. (2013). Economic–environmental analysis of handling biogas from sewage sludge digesters in WWTPs (wastewater treatment plants) for energy recovery: Case study of Bekkelaget WWTP in Oslo (Norway). Energy, 58, 220-235. doi:10.1016/j.energy.2013.05.025EPA (Environmental Protection Agency). Combined Heat and Power Partnership. Agency of the United States federal government; 2015.Descoins, N., Deleris, S., Lestienne, R., Trouvé, E., & Maréchal, F. (2012). Energy efficiency in waste water treatments plants: Optimization of activated sludge process coupled with anaerobic digestion. Energy, 41(1), 153-164. doi:10.1016/j.energy.2011.03.078Gernaey, K. V., van Loosdrecht, M. C. ., Henze, M., Lind, M., & Jørgensen, S. B. (2004). Activated sludge wastewater treatment plant modelling and simulation: state of the art. Environmental Modelling & Software, 19(9), 763-783. doi:10.1016/j.envsoft.2003.03.005Ferrer, J., Seco, A., Serralta, J., Ribes, J., Manga, J., Asensi, E., … Llavador, F. (2008). DESASS: A software tool for designing, simulating and optimising WWTPs. Environmental Modelling & Software, 23(1), 19-26. doi:10.1016/j.envsoft.2007.04.005Bozkurt, H., Quaglia, A., Gernaey, K. V., & Sin, G. (2015). A mathematical programming framework for early stage design of wastewater treatment plants. Environmental Modelling & Software, 64, 164-176. doi:10.1016/j.envsoft.2014.11.023Jeppsson, U., Rosen, C., Alex, J., Copp, J., Gernaey, K. V., Pons, M.-N., & Vanrolleghem, P. A. (2006). Towards a benchmark simulation model for plant-wide control strategy performance evaluation of WWTPs. Water Science and Technology, 53(1), 287-295. doi:10.2166/wst.2006.031Gomez, J., de Gracia, M., Ayesa, E., & Garcia-Heras, J. L. (2007). Mathematical modelling of autothermal thermophilic aerobic digesters. Water Research, 41(5), 959-968. doi:10.1016/j.watres.2006.11.042Righi, S., Oliviero, L., Pedrini, M., Buscaroli, A., & Della Casa, C. (2013). Life Cycle Assessment of management systems for sewage sludge and food waste: centralized and decentralized approaches. Journal of Cleaner Production, 44, 8-17. doi:10.1016/j.jclepro.2012.12.004Lemos, D., Dias, A. C., Gabarrell, X., & Arroja, L. (2013). Environmental assessment of an urban water system. Journal of Cleaner Production, 54, 157-165. doi:10.1016/j.jclepro.2013.04.029Nowak, O., Enderle, P., & Varbanov, P. (2015). Ways to optimize the energy balance of municipal wastewater systems: lessons learned from Austrian applications. Journal of Cleaner Production, 88, 125-131. doi:10.1016/j.jclepro.2014.08.068Tous M, Ladislav B, Houdková L, Pavlas M, Stehlík P. Waste-to energy (W2E) software – a support tool for decision making process. Brno University of Technology, Institute of Process and Environmental Engineering, Chemical Engineering Transactions, Volume 18; 2009.Pijáková, I. (2015). Application of Dynamic Simulations for Assessment of Urban Wastewater Systems Operation. Chemical and Biochemical Engineering Quarterly Journal, 29(1), 55-62. doi:10.15255/cabeq.2014.2127McCarty, P. L., Bae, J., & Kim, J. (2011). Domestic Wastewater Treatment as a Net Energy Producer–Can This be Achieved? Environmental Science & Technology, 45(17), 7100-7106. doi:10.1021/es2014264Giménez, J. B., Robles, A., Carretero, L., Durán, F., Ruano, M. V., Gatti, M. N., … Seco, A. (2011). Experimental study of the anaerobic urban wastewater treatment in a submerged hollow-fibre membrane bioreactor at pilot scale. Bioresource Technology, 102(19), 8799-8806. doi:10.1016/j.biortech.2011.07.014Smith, A. L., Stadler, L. B., Cao, L., Love, N. G., Raskin, L., & Skerlos, S. J. (2014). Navigating Wastewater Energy Recovery Strategies: A Life Cycle Comparison of Anaerobic Membrane Bioreactor and Conventional Treatment Systems with Anaerobic Digestion. Environmental Science & Technology, 48(10), 5972-5981. doi:10.1021/es5006169Barat, R., Serralta, J., Ruano, M. V., Jiménez, E., Ribes, J., Seco, A., & Ferrer, J. (2013). Biological Nutrient Removal Model No. 2 (BNRM2): a general model for wastewater treatment plants. Water Science and Technology, 67(7), 1481-1489. doi:10.2166/wst.2013.004Durán F. Mathematical modelling of the anaerobic urban wastewater treatment including sulphate-reducing bacteria. Application to an anaerobic membrane bioreactor (Modelación matemática del tratamiento anaerobio de aguas residuales urbanas incluyendo las bacterias sulfatorreductoras, Aplicación a un biorreactor anaerobio de membranas), Ph.D. thesis, Dept. of Hydraulic Engineering and Environment, Universitat Politècnica de València, Spain; 2013.Pretel, R., Robles, A., Ruano, M. V., Seco, A., & Ferrer, J. (2013). Environmental impact of submerged anaerobic MBR (SAnMBR) technology used to treat urban wastewater at different temperatures. Bioresource Technology, 149, 532-540. doi:10.1016/j.biortech.2013.09.060Gillot, S., & Vanrolleghem, P. A. (2003). Equilibrium temperature in aerated basins—comparison of two prediction models. Water Research, 37(15), 3742-3748. doi:10.1016/s0043-1354(03)00263-xEPA. Catalog of Biomass Combined Heat and Power Catalog of Technologies; 2007 [cited 2015 May 5] Available from: http://www.epa.gov/chp/documents/biomass_chp_catalog.pdf.PSE Probiogas. Development of sustainable systems of biogas production and use in Spain. Funded by the Ministry of science and innovation. Spanish government, Madrid; 2010 [cited 2012 May 5] http://213.229.136.11/bases/ainia_probiogas.nsf/0/F9F832A77BF0CA25C125753F0058C4B2/$FILE/Cap2.pdf.Serralta, J., Ferrer, J., Borrás, L., & Seco, A. (2004). An extension of ASM2d including pH calculation. Water Research, 38(19), 4029-4038. doi:10.1016/j.watres.2004.07.009Chanona, J., Ribes, J., Seco, A., & Ferrer, J. (2006). Optimum design and operation of primary sludge fermentation schemes for volatile fatty acids production. Water Research, 40(1), 53-60. doi:10.1016/j.watres.2005.10.020Gatti MN. Characterization of wastewaters and calibration of the mathematical model BNRM1 for simulation of the biological removal process of organic matter and nutrients (Caracterización de las aguas residuales y calibración del modelo matemático BNRM1 para la simulación de los procesos de eliminación biológica de materia orgánica y nutrientes). Ph.D. thesis, Dept. of Hydraulic Engineering and Environment, Universitat de València, Spain; 2009.Ruano, M. V., Serralta, J., Ribes, J., Garcia-Usach, F., Bouzas, A., Barat, R., … Ferrer, J. (2012). Application of the general model ‘Biological Nutrient Removal Model No. 1’ to upgrade two full-scale WWTPs. Environmental Technology, 33(9), 1005-1012. doi:10.1080/09593330.2011.604877Ferrer, J., Pretel, R., Durán, F., Giménez, J. B., Robles, A., Ruano, M. V., … Seco, A. (2015). Design methodology for submerged anaerobic membrane bioreactors (AnMBR): A case study. Separation and Purification Technology, 141, 378-386. doi:10.1016/j.seppur.2014.12.018AEMET. State Meteorological Agency (Agencia Estatal de Meteorología). Register of hourly and daily average ambient temperature from 2010 to 2014 located in Valencia; 2015

Economic and environmental sustainability of submerged anaerobic MBR based (AnMBR-based) technology compared to aerobic-based technologies for moderate-/high-loaded urban wastewater treatment

[EN] The objective of this study was to assess the economic and environmental sustainability of submerged anaerobic membrane bioreactors (AnMBRs) in comparison with aerobic-based technologies for moderate-/high-loaded urban wastewater (UWW) treatment. To this aim, a combined approach of steady-state performance modelling, life cycle analysis (LCA) and life cycle costing (LCC) was used, in which AnMBR (coupled with an aerobic-based post-treatment) was compared to aerobic membrane bioreactor (AeMBR) and conventional activated sludge (CAS). AnMBR with CAS-based post-treatment for nutrient removal was identified as a sustainable option for moderate-/high-loaded UWW treatment: low energy consumption and reduced sludge production could be obtained at given operating conditions. In addition, significant reductions can be achieved in different aspects of environmental impact (global warming potential (GWP), abiotic depletion, acidification, etc.) and LCC over existing UWW treatment technologies.Pretel, R.; Robles Martínez, Á.; Ruano García, MV.; Seco Torrecillas, A.; Ferrer, J. (2016). Economic and environmental sustainability of submerged anaerobic MBR based (AnMBR-based) technology compared to aerobic-based technologies for moderate-/high-loaded urban wastewater treatment. Journal of Environmental Management. 166:45-54. https://doi.org/10.1016/j.jenvman.2015.10.004S455416

Filtration process cost in submerged anaerobic membrane bioreactors (AnMBRs) for urban wastewater treatment

[EN] The objective of this study was to evaluate the effect of the main factors affecting the cost of the filtration process in submerged anaerobic membrane bioreactors (AnMBRs) for urban wastewater (UWW) treatment. Experimental data for CAPEX/OPEX calculations was obtained in an AnMBR system featuring industrial-scale hollow-fiber (HF) membranes. Results showed that operating at J(20) slightly higher than the critical flux results in minimum CAPEX/OPEX. The minimum filtration process cost ranged from Euro0.03 to Euro0.12 per m(3), mainly depending on SGD(m) (from 0.05 to 0.3 m(3)m(-2)h(-1)) and MLSS (from 5 to 25 gL-1). The optimal SGD(m) resulted in approx. 0.1 m(3)m(-2)h(-1).This research work was possible thanks to projects CTM2011-28595-C02-01/02 (funded by the Spanish Ministry of Economy and Competitiveness jointly with the European Regional Development Fund) and FCC Aqualia INNPRONTA IISIS IPT-20111023 (partially funded by the Centre for Industrial Technological Development (CDTI), and supported by the Spanish Ministry of Economy and Competitiveness).Pretel-Jolis, R.; Robles Martínez, Á.; Ruano García, MV.; Seco Torrecillas, A.; Ferrer, J. (2016). Filtration process cost in submerged anaerobic membrane bioreactors (AnMBRs) for urban wastewater treatment. Separation Science and Technology. 51(3):517-524. https://doi.org/10.1080/01496395.2015.1094092S517524513Lin, H., Chen, J., Wang, F., Ding, L., & Hong, H. (2011). Feasibility evaluation of submerged anaerobic membrane bioreactor for municipal secondary wastewater treatment. Desalination, 280(1-3), 120-126. doi:10.1016/j.desal.2011.06.058Smith, A. L., Skerlos, S. J., & Raskin, L. (2013). Psychrophilic anaerobic membrane bioreactor treatment of domestic wastewater. Water Research, 47(4), 1655-1665. doi:10.1016/j.watres.2012.12.028Ferrer, J., Pretel, R., Durán, F., Giménez, J. B., Robles, A., Ruano, M. V., … Seco, A. (2015). Design methodology for submerged anaerobic membrane bioreactors (AnMBR): A case study. Separation and Purification Technology, 141, 378-386. doi:10.1016/j.seppur.2014.12.018Robles, A.; Ruano, M. V.; García-Usach, F; Ferrer, J. (2012) Sub-critical filtration conditions of commercial hollow-fiber membranes in a submerged anaerobic MBR (HF-SAnMBR) system: The effect of gas sparging intensity.Bioresource Technol. 114: 247–254.Martin Garcia, I., Mokosch, M., Soares, A., Pidou, M., & Jefferson, B. (2013). Impact on reactor configuration on the performance of anaerobic MBRs: Treatment of settled sewage in temperate climates. Water Research, 47(14), 4853-4860. doi:10.1016/j.watres.2013.05.008Lin, H., Peng, W., Zhang, M., Chen, J., Hong, H., & Zhang, Y. (2013). A review on anaerobic membrane bioreactors: Applications, membrane fouling and future perspectives. Desalination, 314, 169-188. doi:10.1016/j.desal.2013.01.019Giménez, J. B., Robles, A., Carretero, L., Durán, F., Ruano, M. V., Gatti, M. N., … Seco, A. (2011). Experimental study of the anaerobic urban wastewater treatment in a submerged hollow-fibre membrane bioreactor at pilot scale. Bioresource Technology, 102(19), 8799-8806. doi:10.1016/j.biortech.2011.07.014Robles, A., Ruano, M. V., Ribes, J., & Ferrer, J. (2013). Factors that affect the permeability of commercial hollow-fibre membranes in a submerged anaerobic MBR (HF-SAnMBR) system. Water Research, 47(3), 1277-1288. doi:10.1016/j.watres.2012.11.055Judd, S. (2008). The status of membrane bioreactor technology. Trends in Biotechnology, 26(2), 109-116. doi:10.1016/j.tibtech.2007.11.005Verrecht, B., Maere, T., Nopens, I., Brepols, C., & Judd, S. (2010). The cost of a large-scale hollow fibre MBR. Water Research, 44(18), 5274-5283. doi:10.1016/j.watres.2010.06.054Gil, J. A., Túa, L., Rueda, A., Montaño, B., Rodríguez, M., & Prats, D. (2010). Monitoring and analysis of the energy cost of an MBR. Desalination, 250(3), 997-1001. doi:10.1016/j.desal.2009.09.089Maere, T., Verrecht, B., Moerenhout, S., Judd, S., & Nopens, I. (2011). BSM-MBR: A benchmark simulation model to compare control and operational strategies for membrane bioreactors. Water Research, 45(6), 2181-2190. doi:10.1016/j.watres.2011.01.006Fenu, A., Roels, J., Wambecq, T., De Gussem, K., Thoeye, C., De Gueldre, G., & Van De Steene, B. (2010). Energy audit of a full scale MBR system. Desalination, 262(1-3), 121-128. doi:10.1016/j.desal.2010.05.057Zhang, K., Wei, P., Yao, M., Field, R. W., & Cui, Z. (2011). Effect of the bubbling regimes on the performance and energy cost of flat sheet MBRs. Desalination, 283, 221-226. doi:10.1016/j.desal.2011.04.02

Implementation of an Artificial Neural Network on the Test Barcelona Workstation As a Predictive Model for the Classification of Normal, Mild Cognitive Impairment and Alzheimer’s Disease Subjects Using the Neuronorma Battery

Objective: To develop and implement an online Artificial Neural Network (ANN) that provides the probability of a subject having mild cognitive impairment (MCI) or Alzheimer’s disease (AD). Method: Different ANNs were trained using a sample of 350 controls (CONT), 75 MCI and 93 AD subjects. The ANN structure chosen was the following: (1) an input layer of 33 cognitive variables from the Neuronorma battery plus two sociodemographic variables, age and education. This layer was reduced to a 15 features input vector using Multiple Discriminant Analysis method, (2) one hidden layer with 8 neurons, and (3) three output neurons corresponding to the 3 expected cognitive states. This ANN was defined in a previous study [28]. The ANN was implemented on the web site www.test-barcelona.com (Test Barcelona Workstation) [9]. Results: When comparing CONT, MCI and AD participants, the best ANN correctly classifies up to 94,87% of the study participants. Conclusions: The online implemented ANN, delivers the probabilities (%) of belonging to the CONT, MCI and AD groups of a subject assessed using the 35 characteristics (variables) of the Neuronorma profile. This tool is a good complement for the interpretation of cognitive profiles. This technology improves clinical decision making. Keywords: Artificial Neural Network, Probability, Alzheimer disease, Test Barcelona Workstation

Estudio citogenético de Heterakis spumosa Schaeider, 1866

Se ha realizado un estudio cito genético en Heterakis spumosa. El número cromosómico diploide es 2n = 10 en hembras y 2n = 9 en machos. El mecanismo del determinismo del sexo X0/XX.A cytogenetic study of Hetterakis spumosa has been made. Diploid chromosome number in female is 2n = 10 and 2n = 9' in males. The sex determining mechanism is XO/XX

Economic and environmental sustainability of an AnMBR treating urban wastewater and organic fraction of municipal solid waste

[EN] The objective of this study was to evaluate the economic and environmental sustainability of a sub- merged anaerobic membrane bioreactor (AnMBR) treating urban wastewater (UWW) and organic fraction of municipal solid waste (OFMSW) at ambient temperature in mild/hot climates. To this aim, power requirements, energy recovery from methane (biogas methane and methane dissolved in the effluent), consumption of reagents for membrane cleaning, and sludge handling (polyelectrolyte and energy consumption) and disposal (farmland, landfilling and incineration) were evaluated within different operating scenarios. Results showed that, for the operating conditions considered in this study, AnMBR technology is likely to be a net energy producer, resulting in considerable cost savings (up to V0.023 per m3 of treated water) when treating low-sulphate influent. Life cycle analysis (LCA) results revealed that operating at high sludge retention times (70 days) and treating enhances the overall environmental performance of AnMBR technology.This research work was supported by Generalitat Valenciana (project PROMETEO/2012/029), which is gratefully acknowledged. Besides, financial support from the Spanish Ministry of Education, Culture and Sport via a pre-doctoral FPU grant to the first author (AP-2010-2148) is gratefully acknowledged.Pretel-Jolis, R.; Moñino Amorós, P.; Robles Martínez, Á.; Ruano García, MV.; Seco Torrecillas, A.; Ferrer, J. (2016). Economic and environmental sustainability of an AnMBR treating urban wastewater and organic fraction of municipal solid waste. Journal of Environmental Management. 179:83-92. https://doi.org/10.1016/j.jenvman.2016.04.057S839217

Interplay between collective effects and nonstandard interactions of supernova neutrinos

We consider the effect of non-standard neutrino interactions (NSI, for short) on the propagation of neutrinos through the supernova (SN) envelope within a three-neutrino framework and taking into account the presence of a neutrino background. We find that for given NSI parameters, with strength generically denoted by εij, neutrino evolution exhibits a significant time dependence. For |εττ|≳ 10−3 the neutrino survival probability may become sensitive to the θ23 octant and the sign of εττ. In particular, if εττ≳10−2 an internal I-resonance may arise independently of the matter density. For typical values found in SN simulations this takes place in the same dense-neutrino region above the neutrinosphere where collective effects occur, in particular during the synchronization regime. This resonance may lead to an exchange of the neutrino fluxes entering the bipolar regime. The main consequences are (i) bipolar conversion taking place for normal neutrino mass hierarchy and (ii) a transformation of the flux of low-energy νe, instead of the usual spectral swap