Dynamic modelling of Rhodopseudomonas palustris biohydrogen production: Perturbation analysis and photobioreactor upscaling

Bovinille Anye Cho, Brandon Sean Ross, Jan-Pierre du Toit, Robert William McClelland Pott, Ehecatl Antonio del Río Chanona‬‬‬‬, Dongda Zhang

Research output: Contribution to journalArticlepeer-review

Abstract

Developing kinetic models to simulate Rhodopseudomonas palustris biohydrogen production within different configurations of photobioreactors (PBRs) poses a significant challenge. In this study, two types of PBRs: schott bottle-based and vertical tubular-based, were investigated, and three original contributions are presented. Firstly, a mechanistic model was constructed to simulate effects of light intensity, light attenuation and temperature on biomass growth and biohydrogen synthesis, previously not unified for photosynthetic bacteria. Secondly, perturbation analysis was exploited to identify critical parameters influencing the accuracy of the model. Thirdly, two parameters: effective light coefficient and biohydrogen enhancement coefficient, both linked to the PBR's transport phenomena were proposed for process scale-up prediction. By comparing against experimental data, the model's accuracy was confirmed to be high. Moreover, the enhancement of biohydrogen production rate by improved culture mixing and gas removal was also described mechanistically. This provides important advances for future efficient design of PBRs and process online optimisation.

Original languageEnglish
Pages (from-to)36696-36708
Number of pages13
JournalInternational Journal of Hydrogen Energy
Volume46
Issue number74
Early online date15 Sept 2021
DOIs
Publication statusPublished - 26 Oct 2021

Keywords

  • Biohydrogen production
  • Kinetic modelling
  • Photobioreactor
  • Purple non-sulfur bacteria
  • Upscaling

Fingerprint

Dive into the research topics of 'Dynamic modelling of Rhodopseudomonas palustris biohydrogen production: Perturbation analysis and photobioreactor upscaling'. Together they form a unique fingerprint.

Cite this