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Elsevier, Algal Research, (6), p. 242-249, 2014

DOI: 10.1016/j.algal.2013.12.007

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The environmental photobioreactor (ePBR): An algal culturing platform for simulating dynamic natural environments

Journal article published in 2014 by Ben F. Lucker, Christopher C. Hall, Robert Zegarac ORCID, David M. Kramer
This paper was not found in any repository, but could be made available legally by the author.
This paper was not found in any repository, but could be made available legally by the author.

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Data provided by SHERPA/RoMEO

Abstract

Algae in natural or production setting experience fluctuating environmental conditions including changes in light, temperature, CO2 and nutrient availability, oxygen and mixing. In response, algae respond to environmental changes dynamically, adjusting light energy capture strategies, physiological processes and cell cycle control. It is thus the combination of environmental conditions and biological responses that determines the performance of the algae. In contrast, much algal research is performed under artificially static laboratory environments, where different constraints determine performance. Consequently, algal strains selected for mass production in the laboratory may fail to perform well or outcompete local algal strains under outdoor production conditions. To address these issues, we have developed a novel environmental photobioreactor (ePBR), designed to mimic lighting from natural pond environments while controlling key environmental parameters including temperature, pH and CO2 levels, mixing, and culture density. Natural lighting is simulated by illuminating from the top of a columnar culture vessel with a single high power white LED. This combination of lighting and geometry provides light intensities up to full sunlight at the culture surface, with light attenuation through the culture column similar to that observed in raceways or high rate algal ponds. Environmental parameters can be imposed in complex sequences with high time resolution via a user-programmable scripting language. Multiple ePBR units can be networked to perform parallel experiments, enabling semi-high throughput operations. In this report, we demonstrate the utility of this system by showing that fluctuating environmental conditions in ePBR significantly impact algal growth.