Abstract

A new hydrogen-based hollow fiber membrane biofilm reactor (MBfR) with double membrane technique was developed in this work and systematic research was conducted. A mathematical model was built up to predict pH and Langelier Saturation Index (LSI) in the hydrogen-based autotrophic denitrification system with minimal error. The model tested with varied CO2 pressures identified that increasing CO2 pressure resulted in pH decrease and prevention from precipitation. Long-term performance of the new MBfR was also evaluated. When CO2 was delivered at 0.05 MPa, 99% nitrate was removed with a constant neutral pH in the reactor. In the long-term experiment, misdistributions of H2 and CO2 caused disparity of biomass communities on the H2 and CO2 modules, but functional bacteria existed on both modules; this suggested that despite of misdistribution, bubbleless H2 was still able to be transported by recirculation to the CO2 module and became available for the bacteria on the module.

Original languageEnglish (US)
Pages (from-to)154-160
Number of pages7
JournalChemical Engineering Journal
Volume290
DOIs
StatePublished - Apr 15 2016

Fingerprint

Biofilms
biofilm
Hydrogen
hydrogen
membrane
Membranes
Bacteria
bacterium
Denitrification
Nitrates
denitrification
Biomass
saturation
Mathematical models
nitrate
Fibers
biomass
development model
reactor
Experiments

Keywords

  • CO
  • MBfR
  • Model
  • pH control

ASJC Scopus subject areas

  • Chemical Engineering(all)
  • Chemistry(all)
  • Industrial and Manufacturing Engineering
  • Environmental Chemistry

Cite this

Direct delivery of CO2 into a hydrogen-based membrane biofilm reactor and model development. / Xia, Siqing; Xu, Xiaoyin; Zhou, Chen; Wang, Chenhui; Zhou, Lijie; Rittmann, Bruce.

In: Chemical Engineering Journal, Vol. 290, 15.04.2016, p. 154-160.

Research output: Contribution to journalArticle

Xia, Siqing ; Xu, Xiaoyin ; Zhou, Chen ; Wang, Chenhui ; Zhou, Lijie ; Rittmann, Bruce. / Direct delivery of CO2 into a hydrogen-based membrane biofilm reactor and model development. In: Chemical Engineering Journal. 2016 ; Vol. 290. pp. 154-160.
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