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.
ABSTRACT
Modeling efforts to understand the financial implications of microalgal biofuels often assume a static basis for microalgae biomass composition and cost, which has constrained cultivation and downstream conversion process design and limited in-depth understanding of their interdependencies. For this work, a dynamic biological cultivation model was integrated with thermo-chemical/biological unit process models for downstream biorefineries to increase modeling fidelity, to provide mechanistic links among unit operations, and to quantify minimum product selling prices of biofuels via techno-economic analysis. Variability in design, cultivation, and conversion parameters were characterized through Monte Carlo simulation, and sensitivity analyses were conducted to identify key cost and fuel yield drivers. Cultivating biomass to achieve the minimum biomass selling price or to achieve maximum lipid content were shown to lead to suboptimal fuel production costs. Depending on biomass composition, both hydrothermal liquefaction and a biochemical fractionation process (combined algal processing) were shown to have advantageous minimum product selling prices, which supports continued investment in multiple conversion pathways. Ultimately, this work demonstrates a clear need to leverage integrated modeling platforms to advance microalgae biofuel systems as a whole, and specific recommendations are made for the prioritization of research and development pathways to achieve economical biofuel production from microalgae.
