Microalgae and cyanobacteria modeling in water resource recovery facilities: A critical review
2019
Shoener, Brian D. | Schramm, Stephanie M. | Béline, Fabrice | Bernard, Olivier | Martínez, Carlos | Plosz, Benedek G. | Snowling, Spencer | Steyer, Jean-Philippe | Valverde-Pérez, Borja | Wagner, Dorottya | Guest, Jeremy S. | Civil and Environmental Engineering [Illinois] (CEE) ; University of Illinois at Urbana-Champaign [Urbana] (UIUC) ; University of Illinois System-University of Illinois System | Optimisation des procédés en Agriculture, Agroalimentaire et Environnement (UR OPAALE) ; Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA) | Biological control of artificial ecosystems (BIOCORE) ; Centre Inria d'Université Côte d'Azur ; Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de la Recherche Agronomique (INRA)-Laboratoire d'océanographie de Villefranche (LOV) ; Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut de la Mer de Villefranche (IMEV) ; Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut de la Mer de Villefranche (IMEV) ; Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS) | Department of Chemical Engineering [Bath] ; University of Bath [Bath] | Hydromantis Environmental Software Solutions, Inc. | Laboratoire de Biotechnologie de l'Environnement [Narbonne] (LBE) ; Institut National de la Recherche Agronomique (INRA)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro) | DTU Environment, Department of Environmental Engineering ; Danmarks Tekniske Universitet = Technical University of Denmark (DTU) | Department of Chemistry and Bioscience [Aalborg] ; Aalborg University [Aalborg] (AAU) | This work supported by the National Science Foundation Graduate Research Fellowship Program (GRFP) for B.S. and S.S., and the Paul L. Busch Award from the Water Environment & Reuse Foundation (now the Water Research Foundation) for J.G. The CONICYT doctoral grant supported C.M. The IPL Algae in Silico project supported C.M. and O.B. The Phycover Research Project (ANR-14-CE04-0011) funded by the French National Research Agency (ANR) and the French clusters Trimatec, Mer Bretagne Atlantique, and Mer Méditerranée supported O.B. and J.-P.S. | ANR-14-CE04-0011,Phycover,Durabilité des productions microalgales par recyclage du phosphore et de l'azote des eaux résiduaires : vers la station d'épuration du futur(2014)
[Notes_IRSTEA]Article number 100024 [Departement_IRSTEA]Ecotechnologies [TR1_IRSTEA]TED [ADD1_IRSTEA]Valoriser les effluents et déchets organiques
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Mostrar más [+] Menos [-]Inglés. Microalgal and cyanobacterial resource recovery systems could significantly advance nutrient recovery from wastewater by achieving effluent nitrogen (N) and phosphorus (P) levels below the current limit of technology. The successful implementation of phytoplankton, however, requires the formulation of process models that balance fidelity and simplicity to accurately simulate dynamic performance in response to environmental conditions. This work synthesizes the range of model structures that have been leveraged for algae and cyanobacteria modeling and core model features that are required to enable reliable process modeling in the context of water resource recovery facilities. Results from an extensive literature review of over 300 published phytoplankton models are presented, with particular attention to similarities with and differences from existing strategies to model chemotrophic wastewater treatment processes (e.g., via the Activated Sludge Models, ASMs). Building on published process models, the core requirements of a model structure for algal and cyanobacterial processes are presented, including detailed recommendations for the prediction of growth (under phototrophic, heterotrophic, and mixotrophic conditions), nutrient uptake, carbon uptake and storage, and respiration. © 2018 The Authors
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