Microalgae and cyanobacteria modeling in water resource recovery facilities

A critical review

Brian D. Shoener, Stephanie M. Schramm, Fabrice Béline, Olivier Bernard, Carlos Martínez, Benedek G. Plósz, Spencer Snowling, Jean Philippe Steyer, Borja Valverde-Pérez, Dorottya Wágner, Jeremy S. Guest*

*Corresponding author for this work

Research output: Contribution to journalReviewResearchpeer-review

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Abstract

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.

Original languageEnglish
Article number100024
JournalWater Research X
Volume2
Number of pages18
ISSN0043-1354
DOIs
Publication statusPublished - 1 Feb 2019

Keywords

  • Growth
  • Lipid storage
  • Nutrient uptake
  • Starch storage
  • Wastewater treatment plant (WWTP)

Cite this

Shoener, 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]. https://doi.org/10.1016/j.wroa.2018.100024
Shoener, Brian D. ; Schramm, Stephanie M. ; Béline, Fabrice ; Bernard, Olivier ; Martínez, Carlos ; Plósz, Benedek G. ; Snowling, Spencer ; Steyer, Jean Philippe ; Valverde-Pérez, Borja ; Wágner, Dorottya ; Guest, Jeremy S. / Microalgae and cyanobacteria modeling in water resource recovery facilities : A critical review. In: Water Research X. 2019 ; Vol. 2.
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abstract = "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.",
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Shoener, BD, Schramm, SM, Béline, F, Bernard, O, Martínez, C, Plósz, BG, Snowling, S, Steyer, JP, Valverde-Pérez, B, Wágner, D & Guest, JS 2019, 'Microalgae and cyanobacteria modeling in water resource recovery facilities: A critical review', Water Research X, vol. 2, 100024. https://doi.org/10.1016/j.wroa.2018.100024

Microalgae and cyanobacteria modeling in water resource recovery facilities : A critical review. / Shoener, Brian D.; Schramm, Stephanie M.; Béline, Fabrice; Bernard, Olivier; Martínez, Carlos; Plósz, Benedek G.; Snowling, Spencer; Steyer, Jean Philippe; Valverde-Pérez, Borja; Wágner, Dorottya; Guest, Jeremy S.

In: Water Research X, Vol. 2, 100024, 01.02.2019.

Research output: Contribution to journalReviewResearchpeer-review

TY - JOUR

T1 - Microalgae and cyanobacteria modeling in water resource recovery facilities

T2 - A critical review

AU - Shoener, Brian D.

AU - Schramm, Stephanie M.

AU - Béline, Fabrice

AU - Bernard, Olivier

AU - Martínez, Carlos

AU - Plósz, Benedek G.

AU - Snowling, Spencer

AU - Steyer, Jean Philippe

AU - Valverde-Pérez, Borja

AU - Wágner, Dorottya

AU - Guest, Jeremy S.

PY - 2019/2/1

Y1 - 2019/2/1

N2 - 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.

AB - 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.

KW - Growth

KW - Lipid storage

KW - Nutrient uptake

KW - Starch storage

KW - Wastewater treatment plant (WWTP)

U2 - 10.1016/j.wroa.2018.100024

DO - 10.1016/j.wroa.2018.100024

M3 - Review

VL - 2

JO - Water Research

JF - Water Research

SN - 0043-1354

M1 - 100024

ER -

Shoener BD, Schramm SM, Béline F, Bernard O, Martínez C, Plósz BG et al. Microalgae and cyanobacteria modeling in water resource recovery facilities: A critical review. Water Research X. 2019 Feb 1;2. 100024. https://doi.org/10.1016/j.wroa.2018.100024