Applied Sciences (Apr 2023)

Assessment of Photosynthetic Carbon Capture versus Carbon Footprint of an Industrial Microalgal Process

  • Arthur Oliver,
  • Cristobal Camarena-Bernard,
  • Jules Lagirarde,
  • Victor Pozzobon

DOI
https://doi.org/10.3390/app13085193
Journal volume & issue
Vol. 13, no. 8
p. 5193

Abstract

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It is often read that industrial microalgal biotechnology could contribute to carbon capture through photosynthesis. While technically accurate, this claim is rarely supported by sound figures nor put in regard to the carbon emissions associated with said processes. In this view, this work provides a quantitative assessment of the extent microalgal processes compensation for their carbon dioxide emissions. To do so, microalgae were cultivated under photolimited conditions. Their growth dynamic and photosynthetic apparatus status were monitored by daily cell density measurement and fluorescence assays. Ultimate analyses were used to determine microalgal carbon content. Simultaneously, the power consumption of the process was recorded, and the associated carbon dioxide emissions were computed using European electrical production carbon intensity. All in all, the recorded values confirmed microalgae growth under good physiological conditions and allowed computing the carbon capture rate, the energy storing rate, and the carbon dioxide emissions of the process. The process captured 0.72 ± 0.19 gCO2/day while emitting 182 gCO2/day, on average (over 15 days). The photoconversion efficiency was 4.34 ± 0.68%. Even if it were highly optimized (red/blue LED instead of white, for example), the process could only capture 1.02 ± 0.40% of its emissions. From these figures, the claim stating that a biotechnological microalgal production process could partly compensate for its emission seems rather bold. Authors should, therefore, emphasize other ecosystemic benefits of microalgal cultivation, such as phosphorous intake. Finally, we were also able to evaluate Chlorella vulgaris light and dark respiration (0.0377 ± 0.042 day−1 and 7.42 × 10−3 ± 3.33 × 10−3 day−1), which could help to assess carbon emission by biomass respiratory activity.

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