Abstract

Shallow ponds with rapidly photosynthesising cyanobacteria or eukaryotic algae are used for growing biotechnology feedstock and have been proposed for biofuel production but a credible model to predict the productivity of a column of phytoplankton in such ponds is lacking. Oxygen electrodes and Pulse Amplitude Modulation (PAM) fluorometer technology were used to measure gross photosynthesis (P G) vs. irradiance (E) curves (P G vs. E curves) in Chlorella (chlorophyta), Dunaliella salina (chlorophyta) and Phaeodactylum (bacillariophyta). P G vs. E curves were fitted to the waiting-in-line function [P G = (P Gmax × E/Eopt) × exp(1 - E/Eopt)]. Attenuation of incident light with depth could then be used to model P G vs. E curves to describe P G vs. depth in pond cultures of uniformly distributed planktonic algae. Respiratory data (by O2-electrode) allowed net photosynthesis (P N) of algal ponds to be modelled with depth. Photoinhibition of photosynthesis at the pond surface reduced P N of the water column. Calculated optimum depths for the algal ponds were: Phaeodactylum, 63 mm; Dunaliella, 71 mm and Chlorella, 87 mm. Irradiance at this depth is ≈ 5 to 10 μmol m-2 s-1 photosynthetic photon flux density (PPFD). This knowledge can then be used to optimise the pond depth. The total net P N [μmol(O2) m-2 s-1] were: Chlorella, ≈ 12.6 ± 0.76; Dunaliella, ≈ 6.5 ± 0.41; Phaeodactylum ≈ 6.1 ± 0.35. Snell's and Fresnel's laws were used to correct irradiance for reflection and refraction and thus estimate the time course of P N over the course of a day taking into account respiration during the day and at night. The optimum P N of a pond adjusted to be of optimal depth (0.1-0.5 m) should be approximately constant because increasing the cell density will proportionally reduce the optimum depth of the pond and vice versa. Net photosynthesis for an optimised pond located at the tropic of Cancer would be [in t(C) ha-1 y-1]: Chlorella, ≈ 14.1 ± 0.66; Dunaliella, ≈ 5.48 ± 0.39; Phaeodactylum, ≈ 6.58 ± 0.42 but such calculations do not take weather, such as cloud cover, and temperature, into account.

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