45 research outputs found

    Modeling light and temperature influence on ammonium removal by Scenedesmus sp. under outdoor conditions

    Full text link
    [EN] The ammonium removal rate of the microalga Scenedesmus sp. was studied under outdoor conditions. Microalgae were grown in a 500 L flat-plate photobioreactor and fed with the effluent of a submerged anaerobic membrane bioreactor. Temperature ranged between 9.5 WC and 32.5 WC and maximum light intensity was 1,860 μmol·m2·s1. A maximum specific ammonium removal rate of 3.71 mg NH4 þ-N·g TSS1·h1 was measured (at 22.6 WC and with a light intensity of 1,734 μmol·m2·s1). A mathematical model considering the influence of ammonium concentration, light and temperature was validated. The model successfully reproduced the observed values of ammonium removal rate obtained and it is thus presented as a useful tool for plant operation.This research work has been supported by the Spanish Ministry of Education, Culture and Sports (CTM2011-28595-C02-01/02) jointly with the European Regional Development Fund (ERDF) and Generalitat Valenciana (ACOMP2013/203), which are gratefully acknowledged. This research was also supported by the Spanish Ministry of Education, Culture and Sport via a pre-doctoral FPU fellowship to the first author (AP2009-4903). The authors also gratefully acknowledge the support from the water management entities of the Generalitat Valenciana (EPSAR).Ruiz Martinez, A.; Serralta Sevilla, J.; Seco Torrecillas, A.; Ferrer, J. (2016). Modeling light and temperature influence on ammonium removal by Scenedesmus sp. under outdoor conditions. Water Science & Technology. 74(8):1964-1970. https://doi.org/10.2166/wst.2016.383S19641970748Åkerström, A. M., Mortensen, L. M., Rusten, B., & Gislerød, H. R. (2014). Biomass production and nutrient removal by Chlorella sp. as affected by sludge liquor concentration. Journal of Environmental Management, 144, 118-124. doi:10.1016/j.jenvman.2014.05.015Bernard, O., & Rémond, B. (2012). Validation of a simple model accounting for light and temperature effect on microalgal growth. Bioresource Technology, 123, 520-527. doi:10.1016/j.biortech.2012.07.022Brennan, L., & Owende, P. (2010). Biofuels from microalgae—A review of technologies for production, processing, and extractions of biofuels and co-products. Renewable and Sustainable Energy Reviews, 14(2), 557-577. doi:10.1016/j.rser.2009.10.009Broekhuizen, N., Park, J. B. K., McBride, G. B., & Craggs, R. J. (2012). Modification, calibration and verification of the IWA River Water Quality Model to simulate a pilot-scale high rate algal pond. Water Research, 46(9), 2911-2926. doi:10.1016/j.watres.2012.03.011Giménez, 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.2011.07.014Kurano, N., & Miyachi, S. (2005). Selection of microalgal growth model for describing specific growth rate-light response using extended information criterion. Journal of Bioscience and Bioengineering, 100(4), 403-408. doi:10.1263/jbb.100.403McGinn, P. J., Dickinson, K. E., Park, K. C., Whitney, C. G., MacQuarrie, S. P., Black, F. J., … O’Leary, S. J. B. (2012). Assessment of the bioenergy and bioremediation potentials of the microalga Scenedesmus sp. AMDD cultivated in municipal wastewater effluent in batch and continuous mode. Algal Research, 1(2), 155-165. doi:10.1016/j.algal.2012.05.001Reynolds, C. S. (2006). The Ecology of Phytoplankton. doi:10.1017/cbo9780511542145Rouzic, B. L., & Bertru, G. (1997). Phytoplankton community growth in enrichment bioassays: Possible role of the nutrient intracellular pools. Acta Oecologica, 18(2), 121-133. doi:10.1016/s1146-609x(97)80069-0Ruiz-Martinez, A., Serralta, J., Pachés, M., Seco, A., & Ferrer, J. (2014). Mixed microalgae culture for ammonium removal in the absence of phosphorus: Effect of phosphorus supplementation and process modeling. Process Biochemistry, 49(12), 2249-2257. doi:10.1016/j.procbio.2014.09.002Ruiz-Martínez, A., Serralta, J., Romero, I., Seco, A., & Ferrer, J. (2015). Effect of intracellular P content on phosphate removal in Scenedesmus sp. Experimental study and kinetic expression. Bioresource Technology, 175, 325-332. doi:10.1016/j.biortech.2014.10.081Ruiz-Martínez, A., Serralta, J., Seco, A., & Ferrer, J. (2015). Effect of temperature on ammonium removal in Scenedesmus sp. Bioresource Technology, 191, 346-349. doi:10.1016/j.biortech.2015.05.070Singh, G., & Thomas, P. B. (2012). Nutrient removal from membrane bioreactor permeate using microalgae and in a microalgae membrane photoreactor. Bioresource Technology, 117, 80-85. doi:10.1016/j.biortech.2012.03.125Wang, B., & Lan, C. Q. (2011). Biomass production and nitrogen and phosphorus removal by the green alga Neochloris oleoabundans in simulated wastewater and secondary municipal wastewater effluent. Bioresource Technology, 102(10), 5639-5644. doi:10.1016/j.biortech.2011.02.054Wang, L., Min, M., Li, Y., Chen, P., Chen, Y., Liu, Y., … Ruan, R. (2009). Cultivation of Green Algae Chlorella sp. in Different Wastewaters from Municipal Wastewater Treatment Plant. Applied Biochemistry and Biotechnology, 162(4), 1174-1186. doi:10.1007/s12010-009-8866-7Wu, Y.-H., Li, X., Yu, Y., Hu, H.-Y., Zhang, T.-Y., & Li, F.-M. (2013). An integrated microalgal growth model and its application to optimize the biomass production of Scenedesmus sp. LX1 in open pond under the nutrient level of domestic secondary effluent. Bioresource Technology, 144, 445-451. doi:10.1016/j.biortech.2013.06.065Wu, Y.-H., Hu, H.-Y., Yu, Y., Zhang, T.-Y., Zhu, S.-F., Zhuang, L.-L., … Lu, Y. (2014). Microalgal species for sustainable biomass/lipid production using wastewater as resource: A review. Renewable and Sustainable Energy Reviews, 33, 675-688. doi:10.1016/j.rser.2014.02.026Xin, L., Hong-ying, H., & Yu-ping, Z. (2011). Growth and lipid accumulation properties of a freshwater microalga Scenedesmus sp. under different cultivation temperature. Bioresource Technology, 102(3), 3098-3102. doi:10.1016/j.biortech.2010.10.05

    PLS-based soft-sensor to predict ammonium concentration evolution in hollow fibre membrane contactors for nitrogen recovery

    Full text link
    [EN] Hollow fibre membrane contactors (HFMC) have emerged as a promising technology for nitrogen-recovery that can be implemented in wastewater treatment plants (WWTPs) to promote circular economy. In this process, a hydrophobic membrane allows the transference of free-ammonia across the hollow fibres. During its operation, the ammonium concentration decreases, and real-time measurements would be of great value for process monitoring, optimization and control. Ammonium probes exist, but they are expensive and present noticeably maintenance costs. In this work, results from eight N-recovery experiments performed at different pH values using real supernatant of a full-scale anaerobic digester were analysed in terms of the time-evolution profiles of pH and total ammonium nitrogen (TAN). The pH revealed to carry relevant information related to the TAN concentration, as it decreased in the feed solution due to free ammonia stripping. The pH is an inexpensive-to measure process variable that can be routinely acquired in any WWTP. Therefore, a data-driven soft-sensor has been developed. It uses the pH, its derivative, and the pH increments after each reagent dosing as input signals, to estimate the TAN concentration via PLS. An extended PLS-model incorporating interaction terms, quadratic and cubic forms of the three input variables improved the TAN concentration estimation. The developed soft-sensor was able to accurately reproduce the evolution of TAN concentration (in the range 0-1000 mgNH(4)(+)-N/L with R-2 > 0.97 and RMSE < 40 mg/L) during the HFMC process operation, thus making it possible to monitor the process as well as enabling future development of different control and optimization strategies.This research was financially supported by the Spanish Ministry of Economy and Competitiveness (MINECO projects CTM2014-54980-C2-1/2-R and CTM2017-86751-C2-1/2-R) with the European Regional Development Fund (ERDF) as well as the Universitat Polite`cnica de Vale`ncia via a pre-doctoral FPI fellowship to Guillermo Noriega.Aguado García, D.; Noriega-Hevia, G.; Ferrer, J.; Seco, A.; Serralta Sevilla, J. (2022). PLS-based soft-sensor to predict ammonium concentration evolution in hollow fibre membrane contactors for nitrogen recovery. Journal of Water Process Engineering. 47:1-7. https://doi.org/10.1016/j.jwpe.2022.102735174

    Effect of intracellular P content on phosphate removal in Scenedesmus sp. Experimental study and kinetic expression

    Full text link
    The present work determines the effect of phosphorus content on phosphate uptake rate in a mixed culture of Chlorophyceae in which the genus Scenedesmus dominates. Phosphate uptake rate was determined in eighteen laboratory batch experiments, with samples taken from a progressively more P-starved culture in which a minimum P content of 0.11% (w/w) was achieved. The results obtained showed that the higher the internal biomass P content, the lower the phosphate removal rate. The highest specific phosphate removal rate was 6.5 mgPO4 P gTSS -1 h -1 . Microalgae with a P content around 1% (w/w) attained 10% of this highest removal rate, whereas those with a P content of 0.6% (w/w) presented 50% of the maximum removal rate. Different kinetic expressions were used to reproduce the experimental data. Best simulation results for the phosphate uptake process were obtained combining Steele equation and Hill function to represent the effect of light and intracellular phosphorus content, respectively.This research work has been supported by the Spanish Ministry of Economy and Competitiveness (MINECO, CTM2011-28595-C02-01/02) jointly with the European Regional Development Fund (ERDF) which are gratefully acknowledged.Ruiz Martínez, A.; Serralta Sevilla, J.; Romero Gil, I.; Seco Torrecillas, A.; Ferrer, J. (2015). Effect of intracellular P content on phosphate removal in Scenedesmus sp. Experimental study and kinetic expression. Bioresource Technology. 175:325-332. https://doi.org/10.1016/j.biortech.2014.10.08132533217

    Life cycle assessment of AnMBR technology for urban wastewater treatment: A case study based on a demo-scale AnMBR system

    Get PDF
    This study aims at assessing the environmental performance of a projected full-scale anaerobic membrane bioreactor (AnMBR) treating urban wastewater (UWW) at ambient temperature. To this aim, data from an AnMBR demonstration plant equipped with commercially available equipment, including industrial hollow fiber and degassing membranes, was used for projecting a full-scale facility. The use of real operation data allows to obtain robust results that contribute to improve the knowledge of the environmental performance of this technology, pointing out its strengths and the challenges that still need to be addressed. Life cycle assessment (LCA) was applied by means of Ecoinvent data base and ReCiPe2016 methodology considering 1 kg of removed COD as functional unit. Additionally, sensitivity and uncertainty analysis were conducted. Energy balance showed AnMBR performing as energy producer (net energy surplus up to - 0.688 kWh⋅kg CODrem - 1 ) and carbon sink (emissions credit up to 0.223 kgCO2eq⋅kgCODrem - 1). Results also showed energy recovery, heavy metals in sludge, dissolved methane in the effluent, and effluent nutrient content as the most important aspects affecting LCA outcome. Construction phase affected some impact categories significantly (e.g., 51-71% in mineral resource scarcity, 18-27% in fossil resource scarcity, 21-28% in water consumption), therefore its exclusion should be carefully evaluated. CHP efficiency, dissolved methane recovery, filtration productivity, membrane scouring, reactor mixing, HRT and SRT appeared most influencing parameters. Finally, actions leading to increase the recovery and valorization of dissolved methane and/or of nutrients through, for instance, fertigation, improve the environmental performance of AnMBR for UWW treatment

    Coupling AnMBR, Primary Settling and Anaerobic Digestion to Improve Carbon Fate when Treating Sulfate-Rich Wastewater

    Full text link
    [EN] The present work involved an assessment of the technical feasibility of coupling AnMBR, primary settling and anaerobic digestion to treat sulfate-rich wastewater at ambient temperature. The innovative approach used focused on reducing the carbon footprint of wastewater treatment while maximizing the energy recovered from influent organic matter. In this process, primary settling reduces the COD/SO4-S ratio in the influent of the AnMBR system and completely removes organic matter by sulfate-reducing bacteria (SRB), while increasing the COD/SO4-S ratio in the sidestream anaerobic digester (AD), enhancing energy recovery and biogas quality. This approach has the significant advantage of only producing methane in the AD, so that the AnMBR produces a high-quality, methane-free effluent with no environmental impact from fugitive methane emissions. The performance of this treatment scheme was assessed by operating a demonstration-scale AnMBR plant fed by primary settled municipal wastewater at the hydraulic retention times of 25, 12 and 8.5 h. The results showed that the COD and BOD removed by SRB enabled setting the discharge limits at 25 and 12 h and lowered the carbon footprint to levels below those of an AnMBR plant fed by raw municipal wastewater, mainly by eliminating fugitive methane emissions.The authors would like to acknowledge the Ministry of Science and Innovation for supporting the project "RECREATE" (PID2020-114315RB-C22) and "BIONUTEN" (CTM2014-54980-C2-R)where this research is framed and the Ministry of Universities for the financial research fellowship of the first author (BES-2015-073403).Mateo, O.; Sanchis-Perucho, P.; Giménez, JB.; Robles, Á.; Martí, N.; Serralta Sevilla, J.; Seco, A. (2023). Coupling AnMBR, Primary Settling and Anaerobic Digestion to Improve Carbon Fate when Treating Sulfate-Rich Wastewater. Water. 15(20):1-18. https://doi.org/10.3390/w15203574118152

    Effect of pH and HNO2 concentration on the activity of ammonia-oxidizing bacteria in a partial nitritation reactor

    Full text link
    Ammonia-oxidizing bacteria (AOB) are very sensitive to environmental conditions and wastewater treatment plant operational parameters. One of the most important factors affecting their activity is pH. Its effect is associated with: NH3/NH4 þ and HNO2/NO2 chemical equilibriums and biological reaction rates. The aim of this study was to quantify and model the effect of pH and free nitrous acid (FNA) concentration on the activity of AOB present in a lab-scale partial nitritation reactor. For this purpose, two sets of batch experiments were carried out using biomass from this reactor. Fluorescent in situ hybridization analysis showed that Nitrosomona eutropha and Nitrosomona europaea species were dominant in the partial nitritation reactor (>94%). The experimental results showed that FNA inhibits the AOB activity. This inhibition was properly modelled by the noncompetitive inhibition function and the half inhibition constant value was determined as 1.32 mg HNO2-N L 1. The optimal pH for these AOB was found to be in the range 7.4 7.8. The pH inhibitory effect was stronger at high pH values than at low pH values. Therefore, an asymmetric inhibition function was proposed to represent the pH effect on these bacteria. A combination of two sigmoidal functions was able to reproduce the experimental results obtained.Claros Bedoya, JA.; Jiménez Douglas, E.; Aguado García, D.; Ferrer, J.; Seco Torrecillas, A.; Serralta Sevilla, J. (2013). Effect of pH and HNO2 concentration on the activity of ammonia-oxidizing bacteria in a partial nitritation reactor. Water Science and Technology. 67(11):2587-2594. doi:10.2166/wst.2013.132S25872594671

    Plant-wide modelling in wastewater treatment: showcasing experiences using the Biological Nutrient Removal Model

    Full text link
    [EN] Plant-wide modelling can be considered an appropriate approach to represent the current complexity in water resource recovery facilities, reproducing all known phenomena in the different process units. Nonetheless, novel processes and new treatment schemes are still being developed and need to be fully incorporated in these models. This work presents a short chronological overview of some of the most relevant plant-wide models for wastewater treatment, as well as the authors' experience in plant-wide modelling using the general model BNRM (Biological Nutrient Removal Model), illustrating the key role of general models (also known as supermodels) in the field of wastewater treatment, both for engineering and research.Seco, A.; Ruano, MV.; Ruiz-Martínez, A.; Robles Martínez, Á.; Barat, R.; Serralta Sevilla, J.; Ferrer, J. (2020). Plant-wide modelling in wastewater treatment: showcasing experiences using the Biological Nutrient Removal Model. Water Science & Technology. 81(8):1700-1714. https://doi.org/10.2166/wst.2020.056S17001714818Barat, R., Montoya, T., Seco, A., & Ferrer, J. (2011). Modelling biological and chemically induced precipitation of calcium phosphate in enhanced biological phosphorus removal systems. Water Research, 45(12), 3744-3752. doi:10.1016/j.watres.2011.04.028Barat, 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.2013.004Batstone, D. J., Hülsen, T., Mehta, C. M., & Keller, J. (2015). Platforms for energy and nutrient recovery from domestic wastewater: A review. Chemosphere, 140, 2-11. doi:10.1016/j.chemosphere.2014.10.021Borrás F. L. 2008 Técnicas microbiológicas aplicadas a la identificación y cuantificación de organismos presentes en sistemas EBPR (Microbiological Techniques Applied to Identification and Quantification of Organisms Present in EBPR Systems). PhD Thesis, Universitat Politècnica de València, Valencia, Spain.Claros, J., Jiménez, E., Aguado, D., Ferrer, J., Seco, A., & Serralta, J. (2013). Effect of pH and HNO2 concentration on the activity of ammonia-oxidizing bacteria in a partial nitritation reactor. Water Science and Technology, 67(11), 2587-2594. doi:10.2166/wst.2013.132Copp, J. B., Jeppsson, U., & Rosen, C. (2003). TOWARDS AN ASM1 – ADM1 STATE VARIABLE INTERFACE FOR PLANT-WIDE WASTEWATER TREATMENT MODELING. Proceedings of the Water Environment Federation, 2003(7), 498-510. doi:10.2175/193864703784641207Dorofeev, A. G., Nikolaev, Y. A., Kozlov, M. N., Kevbrina, M. V., Agarev, A. M., Kallistova, A. Y., & Pimenov, N. V. (2017). Modeling of anammox process with the biowin software suite. Applied Biochemistry and Microbiology, 53(1), 78-84. doi:10.1134/s0003683817010100Drewnowski, J., Zaborowska, E., & Hernandez De Vega, C. (2018). Computer Simulation in Predicting Biochemical Processes and Energy Balance at WWTPs. E3S Web of Conferences, 30, 03007. doi:10.1051/e3sconf/20183003007Durán F. 2013 Modelación matemática del tratamiento anaerobio de aguas residuales urbanas incluyendo las bacterias sulfatorreductoras. Aplicación a un biorreactor anaerobio de membranas (Mathematical Model of Urban Wastewater Anaerobic Treatment Including Sulphate Reducing Bacteria. Application to an Anaerobic Membrane Bioreactor). PhD Thesis, Universitat Politècnica de València, Valencia, Spain.Ekama, G. A. (2009). Using bioprocess stoichiometry to build a plant-wide mass balance based steady-state WWTP model. Water Research, 43(8), 2101-2120. doi:10.1016/j.watres.2009.01.036EPA 2006 User's manual version 4.03 2006. Available from: https://www.epa.gov/ceam/minteqa2-equilibrium-speciation-model (accessed July 2019).Fernández-Arévalo, T., Lizarralde, I., Fdz-Polanco, F., Pérez-Elvira, S. I., Garrido, J. M., Puig, S., … Ayesa, E. (2017). Quantitative assessment of energy and resource recovery in wastewater treatment plants based on plant-wide simulations. Water Research, 118, 272-288. doi:10.1016/j.watres.2017.04.001Ferrer, 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.2007.04.005Ferrer J., Seco A., Ruano M. V., Ribes J., Serralta J., Gómez T., Robles A. 2011 LoDif BioControl® Control Software, Intellectual Property. Main Institution: Universitat de València; Universitat Politècnica de València.Flores-Alsina, X., Corominas, L., Snip, L., & Vanrolleghem, P. A. (2011). Including greenhouse gas emissions during benchmarking of wastewater treatment plant control strategies. Water Research, 45(16), 4700-4710. doi:10.1016/j.watres.2011.04.040Flores-Alsina, X., Arnell, M., Amerlinck, Y., Corominas, L., Gernaey, K. V., Guo, L., … Jeppsson, U. (2014). Balancing effluent quality, economic cost and greenhouse gas emissions during the evaluation of (plant-wide) control/operational strategies in WWTPs. Science of The Total Environment, 466-467, 616-624. doi:10.1016/j.scitotenv.2013.07.046Flores-Alsina, X., Kazadi Mbamba, C., Solon, K., Vrecko, D., Tait, S., Batstone, D. J., … Gernaey, K. V. (2015). A plant-wide aqueous phase chemistry module describing pH variations and ion speciation/pairing in wastewater treatment process models. Water Research, 85, 255-265. doi:10.1016/j.watres.2015.07.014Ge, Z. (2017). Review on data-driven modeling and monitoring for plant-wide industrial processes. Chemometrics and Intelligent Laboratory Systems, 171, 16-25. doi:10.1016/j.chemolab.2017.09.021Grau, P., de Gracia, M., Vanrolleghem, P. A., & Ayesa, E. (2007). A new plant-wide modelling methodology for WWTPs. Water Research, 41(19), 4357-4372. doi:10.1016/j.watres.2007.06.019Grau, P., Copp, J., Vanrolleghem, P. A., Takács, I., & Ayesa, E. (2009). A comparative analysis of different approaches for integrated WWTP modelling. Water Science and Technology, 59(1), 141-147. doi:10.2166/wst.2009.589Henze M., Gujer W., Mino T., van Loosdrecht M. C. M. 2000 Activated Sludge Models ASM1, ASM2, ASM2d and ASM3. IWA Scientific and Technical Report No.9. IWA Publishing, London, UK.Jeppsson, U., & Pons, M.-N. (2004). The COST benchmark simulation model—current state and future perspective. Control Engineering Practice, 12(3), 299-304. doi:10.1016/j.conengprac.2003.07.001Jeppsson, 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.2006.031Ji, X., Liu, Y., Zhang, J., Huang, D., Zhou, P., & Zheng, Z. (2018). Development of model simulation based on BioWin and dynamic analyses on advanced nitrate nitrogen removal in deep bed denitrification filter. Bioprocess and Biosystems Engineering, 42(2), 199-212. doi:10.1007/s00449-018-2025-xJiménez, E., Giménez, J. B., Ruano, M. V., Ferrer, J., & Serralta, J. (2011). Effect of pH and nitrite concentration on nitrite oxidation rate. Bioresource Technology, 102(19), 8741-8747. doi:10.1016/j.biortech.2011.07.092Jiménez, E., Giménez, J. B., Seco, A., Ferrer, J., & Serralta, J. (2012). Effect of pH, substrate and free nitrous acid concentrations on ammonium oxidation rate. Bioresource Technology, 124, 478-484. doi:10.1016/j.biortech.2012.07.079Kazadi Mbamba, C., Flores-Alsina, X., John Batstone, D., & Tait, S. (2016). Validation of a plant-wide phosphorus modelling approach with minerals precipitation in a full-scale WWTP. Water Research, 100, 169-183. doi:10.1016/j.watres.2016.05.003Kazadi Mbamba, C., Lindblom, E., Flores-Alsina, X., Tait, S., Anderson, S., Saagi, R., … Jeppsson, U. (2019). Plant-wide model-based analysis of iron dosage strategies for chemical phosphorus removal in wastewater treatment systems. Water Research, 155, 12-25. doi:10.1016/j.watres.2019.01.048Liu, Y., Peng, L., Ngo, H. H., Guo, W., Wang, D., Pan, Y., … Ni, B.-J. (2016). Evaluation of Nitrous Oxide Emission from Sulfide- and Sulfur-Based Autotrophic Denitrification Processes. Environmental Science & Technology, 50(17), 9407-9415. doi:10.1021/acs.est.6b02202Lizarralde, I., Fernández-Arévalo, T., Brouckaert, C., Vanrolleghem, P., Ikumi, D. S., Ekama, G. A., … Grau, P. (2015). A new general methodology for incorporating physico-chemical transformations into multi-phase wastewater treatment process models. Water Research, 74, 239-256. doi:10.1016/j.watres.2015.01.031Lizarralde, I., Fernández-Arévalo, T., Manas, A., Ayesa, E., & Grau, P. (2019). Model-based opti mization of phosphorus management strategies in Sur WWTP, Madrid. Water Research, 153, 39-52. doi:10.1016/j.watres.2018.12.056Maere, 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.2011.01.006Mannina, G., Ekama, G., Caniani, D., Cosenza, A., Esposito, G., Gori, R., … Olsson, G. (2016). Greenhouse gases from wastewater treatment — A review of modelling tools. Science of The Total Environment, 551-552, 254-270. doi:10.1016/j.scitotenv.2016.01.163Martí, N., Barat, R., Seco, A., Pastor, L., & Bouzas, A. (2017). Sludge management modeling to enhance P-recovery as struvite in wastewater treatment plants. Journal of Environmental Management, 196, 340-346. doi:10.1016/j.jenvman.2016.12.074Moretti, P., Choubert, J.-M., Canler, J.-P., Buffière, P., Pétrimaux, O., & Lessard, P. (2017). Dynamic modeling of nitrogen removal for a three-stage integrated fixed-film activated sludge process treating municipal wastewater. Bioprocess and Biosystems Engineering, 41(2), 237-247. doi:10.1007/s00449-017-1862-3Nagy, J., Kaljunen, J., & Toth, A. J. (2019). Nitrogen recovery from wastewater and human urine with hydrophobic gas separation membrane: experiments and modelling. Chemical Papers, 73(8), 1903-1915. doi:10.1007/s11696-019-00740-xNewhart, K. B., Holloway, R. W., Hering, A. S., & Cath, T. Y. (2019). Data-driven performance analyses of wastewater treatment plants: A review. Water Research, 157, 498-513. doi:10.1016/j.watres.2019.03.030Nopens, I., Batstone, D. J., Copp, J. B., Jeppsson, U., Volcke, E., Alex, J., & Vanrolleghem, P. A. (2009). An ASM/ADM model interface for dynamic plant-wide simulation. Water Research, 43(7), 1913-1923. doi:10.1016/j.watres.2009.01.012Nopens, I., Benedetti, L., Jeppsson, U., Pons, M.-N., Alex, J., Copp, J. B., … Vanrolleghem, P. A. (2010). Benchmark Simulation Model No 2: finalisation of plant layout and default control strategy. Water Science and Technology, 62(9), 1967-1974. doi:10.2166/wst.2010.044Ontiveros, G. A., & Campanella, E. A. (2013). Environmental performance of biological nutrient removal processes from a life cycle perspective. Bioresource Technology, 150, 506-512. doi:10.1016/j.biortech.2013.08.059Penya-Roja, J. M., Seco, A., Ferrer, J., & Serralta, J. (2002). Calibration and Validation of Activated Sludge Model No.2d for Spanish Municipal Wastewater. Environmental Technology, 23(8), 849-862. doi:10.1080/09593332308618360Pretel, R., Robles, A., Ruano, M. V., 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. doi:10.1080/09593330.2016.1148903Pretel, R., Robles, A., Ruano, M. V., Seco, A., & Ferrer, J. (2016). Economic and environmental sustainability of submerged anaerobic MBR-based (AnMBR-based) technology as compared to aerobic-based technologies for moderate-/high-loaded urban wastewater treatment. Journal of Environmental Management, 166, 45-54. doi:10.1016/j.jenvman.2015.10.004Rehman, U., Audenaert, W., Amerlinck, Y., Maere, T., Arnaldos, M., & Nopens, I. (2017). How well-mixed is well mixed? Hydrodynamic-biokinetic model integration in an aerated tank of a full-scale water resource recovery facility. Water Science and Technology, 76(8), 1950-1965. doi:10.2166/wst.2017.330Rieger L., Gillot S., Langergraber G., Ohtsuki T., Shaw A., Takacs I., Winkler S. 2012 Guidelines for Using Activated Sludge Models Scientific and Technical report No. 21. EWA Task Group on Good Modelling Practice. IWA Publishing Volume 11.Robles, A., Ruano, M. V., Ribes, J., Seco, A., & Ferrer, J. (2014). Model-based automatic tuning of a filtration control system for submerged anaerobic membrane bioreactors (AnMBR). Journal of Membrane Science, 465, 14-26. doi:10.1016/j.memsci.2014.04.012Robles, A., Capson-Tojo, G., Ruano, M. V., Seco, A., & Ferrer, J. (2018). Real-time optimization of the key filtration parameters in an AnMBR: Urban wastewater mono-digestion vs. co-digestion with domestic food waste. Waste Management, 80, 299-309. doi:10.1016/j.wasman.2018.09.031Ruano, 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:10.1080/09593330.2011.604877Seco, A., Ribes, J., Serralta, J., & Ferrer, J. (2004). Biological nutrient removal model No.1 (BNRM1). Water Science and Technology, 50(6), 69-70. doi:10.2166/wst.2004.0361Serralta, 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.2004.07.009Shoener, B. D., Schramm, S. M., Béline, F., Bernard, O., Martínez, C., Plósz, B. G., … Guest, J. S. (2019). Microalgae and cyanobacteria modeling in water resource recovery facilities: A critical review. Water Research X, 2, 100024. doi:10.1016/j.wroa.2018.100024Solon, K., Flores-Alsina, X., Kazadi Mbamba, C., Ikumi, D., Volcke, E. I. P., Vaneeckhaute, C., … Jeppsson, U. (2017). Plant-wide modelling of phosphorus transformations in wastewater treatment systems: Impacts of control and operational strategies. Water Research, 113, 97-110. doi:10.1016/j.watres.2017.02.007Solon, K., Jia, M., & Volcke, E. I. P. (2019). Process schemes for future energy-positive water resource recovery facilities. Water Science and Technology, 79(9), 1808-1820. doi:10.2166/wst.2019.183Vanrolleghem, P. A., Rosen, C., Zaher, U., Copp, J., Benedetti, L., Ayesa, E., & Jeppsson, U. (2005). Continuity-based interfacing of models for wastewater systems described by Petersen matrices. Water Science and Technology, 52(1-2), 493-500. doi:10.2166/wst.2005.055

    Biological Nutrient Removal Model Nº 2 (BNRM2): A general model for Wastewater Treatment Plants

    Full text link
    This paper presents the plant-wide model Biological Nutrient Removal Model No. 2 (BNRM2). Since nitrite was not considered in the BNRM1, and this previous model also failed to accurately simulate the anaerobic digestion because precipitation processes were not considered, an extension of BNRM1 has been developed. This extension comprises all the components and processes required to simulate nitrogen removal via nitrite and the formation of the solids most likely to precipitate in anaerobic digesters. The solids considered in BNRM2 are: struvite, amorphous calcium phosphate, hidroxyapatite, newberite, vivianite, strengite, variscite, and calcium carbonate. With regard to nitrogen removal via nitrite, apart from nitrite oxidizing bacteria two groups of ammonium oxidizing organisms (AOO) have been considered since different sets of kinetic parameters have been reported for the AOO present in activated sludge systems and SHARON (Single reactor system for High activity Ammonium Removal Over Nitrite) reactors. Due to the new processes considered, BNRM2 allows an accurate prediction of wastewater treatment plant performance in wider environmental and operating conditions.This research work has been supported by the Spanish Research Foundation (CICYT Projects, PPQ2002-04043-C02, CTM2005-06919-C03-/TECNO) and Entidad Publica de Saneamiento de Aguas Residuales de la Comunidad Valenciana, which are gratefully acknowledged. This paper was presented at WWTmod2012 and the fruitful discussions are kindly acknowledged.Barat Baviera, R.; Serralta Sevilla, J.; Ruano García, MV.; Jiménez Douglas, E.; Ribes Bertomeu, J.; Seco Torrecillas, 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. https://doi.org/10.2166/wst.2013.004S1481148967

    Anaerobic membrane bioreactors (AnMBR) treating urban wastewater in mild climates

    Get PDF
    Feasibility of an AnMBR demonstration plant treating urban wastewater (UWW) at temperatures around 25-30 ºC was assessed during a 350-day experimental period. The plant was fitted with industrial-scale hollow-fiber membranes and fed with the effluent from the pre-treatment of a full-scale municipal WWTP. Biodegradability of the UWW reached values up to 87%, although a portion of the biodegradable COD was consumed by sulfate reducing organisms. Effluent COD remained below effluent discharge limits, achieving COD removals above 90%. System operation resulted in a reduction of sludge production of 36-58% compared to theoretical aerobic sludge productions. The membranes were operated at gross transmembrane fluxes above 20 LMH maintaining low membrane fouling propensities for more than 250 days without chemical cleaning requirements. Thus, the system resulted in net positive energy productions and GHG emissions around zero. The results obtained confirm the feasibility of UWW treatment in AnMBR under mild and warm climates

    Tratamientos biológicos de aguas residuales

    Full text link
    El presente libro tiene como objetivo general conocer los fundamentos y la aplicación de las tecnologías disponibles para el tratamiento bilógico de las aguas residuales. Este libro pretende dotar a estudiantes, profesionales o investigadores de los conocimientos y habilidades necesarias para el pre-diseño de diferentes sistemas de tratamiento bilógico de las aguas residuales y de los fangos producidos en el proceso. Para ello, se profundiza en el estudio de los procesos biológicos, cuyo uso generalizado en la depuración de aguas residuales urbanas y gran número de industriales, por una parte, y su gran complejidad, por otra, justifica la importancia de un estudio detallado de los mismos. Asimismo, se tratan aspectos fundamentales referentes a la microbiología de los procesos, la cinética y la estequiometría de las reacciones bioquímicas, tipos de procesos, esquemas de proceso, aplicabilidad, etc. Además, se aborda la problemática de la producción de fangos, así como el diseño de los distintos métodos de tratamiento existentes.Ferrer Polo, J.; Seco Torrecillas, A.; Robles Martínez, Á.; Asensi Dasí, EJ.; Serralta Sevilla, J. (2022). Tratamientos biológicos de aguas residuales. Editorial Universitat Politècnica de València. http://hdl.handle.net/10251/181422EDITORIA
    corecore