Simulation of algae growth in a bench‐scale bubble column reactor

Wu, Xinghuo; Merchuk, José C.

doi:10.1002/bit.10350

Cited by 82 publications

(51 citation statements)

References 26 publications

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“…For the growth of Porphyridium sp., the parameters used in the equations are estimated by Wu and Merchuk (2002) and are shown in Table I.…”

Section: Three-state Photosynthesis Rate Modelmentioning

confidence: 99%

“…Me is a maintenance constant accounting for cellular damage due to adverse environments, e.g., high shear stress. Wu and Merchuk (2002) defined Me as:…”

Section: Three-state Photosynthesis Rate Modelmentioning

confidence: 99%

“…Unfortunately, such Lagrangian information of cells' movement has not been available until recently (Luo et al, 2003) due to the need for advanced hydrodynamic measurement techniques. As a result, Wu and Merchuk (2002) used a trajectories predicted by a multi-circulation cells model (Joshi and Sharma, 1979) where such circulation cells are physically unrealistic (Degaleesan, 1997;Luo et al, 2003).…”

Section: Introductionmentioning

confidence: 99%

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Analyzing and modeling of photobioreactors by combining first principles of physiology and hydrodynamics

Luo

Al‐Dahhan

2004

Biotech & Bioengineering

116

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Mixing in photobioreactors is known to enhance biomass productivity considerably, and flow dynamics play a significant role in the reactor's performance, as they determine the mixing and the cells' movement. In this work we focus on analyzing the effects of mixing and flow dynamics on the photobioreactor performance. Based on hydrodynamic findings from the CARPT(Computer Automated Radioactive Particle Tracking) technique, a possible mechanism for the interaction between the mixing and the physiology of photosynthesis is presented, and the effects of flow dynamics on light availability and light intensity fluctuation are discussed and quantitatively characterized. Furthermore, a dynamic modeling approach is developed for photobioreactor performance evaluation, which integrates first principles of photosynthesis, hydrodynamics, and irradiance distribution within the reactor. The results demonstrate the reliability and the possible applicability of this approach to commercially interesting microalgae/cyanobacteria culture systems.

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“…For the growth of Porphyridium sp., the parameters used in the equations are estimated by Wu and Merchuk (2002) and are shown in Table I.…”

Section: Three-state Photosynthesis Rate Modelmentioning

confidence: 99%

“…Me is a maintenance constant accounting for cellular damage due to adverse environments, e.g., high shear stress. Wu and Merchuk (2002) defined Me as:…”

Section: Three-state Photosynthesis Rate Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Analyzing and modeling of photobioreactors by combining first principles of physiology and hydrodynamics

Luo

Al‐Dahhan

2004

Biotech & Bioengineering

116

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“…Photoinhibition is a reduction in an alga's capacity for photosynthesis caused by exposure to strong light. Photoinhibition is not necessarily caused by intense light, but rather absorption of too much light energy compared with the photosynthetic capacity (Acien Fernandez et al, 1998;Yun and Park, 2001;Wu and Merchuk, 2002;Barbosa, 2003 …”

Section: Algae Specificationmentioning

confidence: 99%

Temperature Influence and Heat Management Requirements of Microalgae Cultivation in Photobioreactors

Mehlitz

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Temperature Influence and Heat Management Requirements of Microalgae Cultivation inPhotobioreactors. Thomas Hagen MehlitzMicroalgae are considered one of the most promising feedstocks for biofuel production for the future. The most efficient way to produce vast amounts of algal biomass is the use of closed tubular photobioreactors (PBR). The heat requirement for a given system is a major concern since the best algae growth rates are obtained between 25-30 °C, depending on the specific strain. A procedure to determine temperature influence on algal growth rates was developed for a lab-scale PBR system using the species Chlorella. A maximum growth rate of 1.44 doublings per day at 29 °C (optimal temperature) was determined. In addition, a dynamic mathematical model was developed to simulate heating and cooling energy requirements of tubular PBRs for any desired location. Operating the model with hourly weather data as input, heating and cooling loads can be calculated early in the planning stage of a project. Furthermore, the model makes it possible to compare the operation inside a greenhouse to the outdoor operations, and consequently provides fundamental information for an economic feasibility study.The best configuration for a specific location can be evaluated easily. The model was exemplary tested for a hypothetical 100,000 l photobioreactor located in San Luis Obispo, California, U.S.A. Average algae productivity rates of 23% and 67% for outdoor and indoor PBR operations, respectively, were obtained. Actual energy loads (heating and cooling) needed to maintain the PBR at optimal temperature were determined and v compared. Sensitivity analyses had been performed for abrupt temperature and solar radiation steps, PBR row distances, ground reflectivities, and ventilation rates of the greenhouse. An optimal row distance of 0.75 m was determined for the specific PBR.The least amount of energy was needed for a ground reflectivity of 20%. The ventilation rate had no major influence on the productivity rate of the system. Results demonstrated the importance of a simulation model as well as the economic impact of a sophisticated heat management system. Energy savings due to an optimized heat management system will eventually increase proficiency of the systems, which will support a new sustainable industry and future developmental potential.

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“…The parameters related to the original 3-state model (α, β, γ, δ, kp, Rs) are based on those reported by Wu and Merchuk (2001) as a reference point and are modified where indicated [1] Wu and Merchuk (2002) [2] García-Camacho et al (2012) [3] Gross et al (1991) The rate of deactivation is slightly higher than reported by Wu and Merchuk (0.146 s -1 ) since it is modified by P/Pmax and thus represents an upper limit. The parameters relating to carbon assimilation efficiency are based on a study of higher plants (Gross et al 1991), since no data for algae is available.…”

Section: Parameter Estimation and Justificationmentioning

confidence: 99%

Photosynthesis of microalgae in outdoor mass cultures and modelling its effects on biomass productivity for fuels, feeds and chemicals

Yarnold¹

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Practical applications of microalgae include uses as feedstocks for sustainable fuels, feeds, nutraceuticals, and chemicals; for the treatment of wastewater and industrial flue gas; and for use as recombinant protein expression systems. Improvements in biomass yields are required for commercially viable and sustainable algal technologies, particularly for low value commodities such as biofuels.Although several algae exhibit higher growth rates than terrestrial crops, with theoretical upper limits of 8-10% photon conversion efficiency (PCE), solar-illuminated outdoor microalgal production systems typically have a PCE far below this and even below those achieved under laboratory conditions. The most intractable limiting factor is poor light distribution through the mass culture, where photoinhibitory light at the surface and dark zones deeper in the culture reduce photosynthetic productivity. Moreover, microalgae have evolved a suite of photoacclimation and photoregulation mechanisms to cope with rapid (seconds to minutes) light fluxes in natural environments, yet these processes remain poorly understood in well-mixed photobioreactors.The aim of this thesis study was to combine an experimental and theoretical approach to: 1) investigate and understand the photosynthetic response of algae under mass culture conditions; 2) develop a mathematical model which could accurately predict light-tobiomass productivities under a broad range of design scenarios for outdoor production systems; and 3) identify key biological and design parameters to maximise biomass yields.In the first part of the study, a light-to-biomass model was developed that could be easily applied to rapidly assess biomass yields of different algal strains under a range of design scenarios. This model predicts temporal and spatial irradiance at the reactor surface and through the mass culture with inputs of local solar radiation data, local coordinates, system properties and the optical properties of the culture. Local growth rates are then coupled to local light intensities within the reactor based on a static Haldane growth model derived from empirical growth-irradiance curves. Growth rates are integrated over space and time to compute areal and volumetric productivities.Validation of the model was attempted by conducting batch harvest experiments in a laboratory scale photobioreactor matrix which simulated diurnal light cycles representative of three 'typical' days of solar radiation in Brisbane. The strains used were ii Chlamydomonas reinhardtii and its truncated light-harvesting antenna mutant, tla1, reported to possess improved optical properties. Initially, the model did not satisfactorily predict growth under batch cultivation for the three different incident light conditions, overestimating productivity under low light days and overestimating on high light days.Subsequent adjustment of the model to include photoacclimative changes in the optical properties of the cell and a re-fit of the growth parameter values provided a more accurate m...

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Simulation of algae growth in a bench‐scale bubble column reactor

Cited by 82 publications

References 26 publications

Analyzing and modeling of photobioreactors by combining first principles of physiology and hydrodynamics

Analyzing and modeling of photobioreactors by combining first principles of physiology and hydrodynamics

Temperature Influence and Heat Management Requirements of Microalgae Cultivation in Photobioreactors

Photosynthesis of microalgae in outdoor mass cultures and modelling its effects on biomass productivity for fuels, feeds and chemicals

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