화학공학소재연구정보센터
홈 로그인 로그아웃 연락처 사이트맵
Journal of Industrial and Engineering Chemistry, Vol.110, 479-490, June, 2022
DOI10.1016/j.jiec.2022.03.020  Export Citation
Rate-based model for predicting and evaluating H2S absorption in the haloalkaliphilic biological desulfurization process
Zheng Chen1, 2, Gama Yang1, 2, Tingzhen Mu1, 3, †, Maohua Yang1, 3, Nadia A. Samak4, Sumit Peh1, 2, Yunpu Jia1, 2, Xuemi Hao1, 2, Xuhao Zhao1, 3, and Jianmin Xing1, 2, †
  • 1CAS Key Laboratory of Green Process and Engineering, State Key Laboratory of Biochemical Engineering, Institute of Process Engineering, Chinese Academy of Sciences (CAS), Beijing 100190, PR China
  • 2College of Chemical Engineering, University of Chinese Academy of Sciences, Beijing 100049, PR China
  • 3, China
  • 4Environmental Microbiology and Biotechnology, Aquatic Microbiology, University of Duisburg-Essen, 4141 Essen, Germany
E-mail:,
The highly efficient performance of H2S absorption is the crucial indicator for haloalkaliphilic biological desulfurization (HBDS) because it immediately concerns the H2S removal efficiency and pH change of alkaline solutions. Therefore, we investigated the effect of operating parameters on the H2S absorption’s performance under haloalkaline conditions. The gas–liquid ratio and packing height significantly improve H2S removal efficiency, from 80% to 90% and 66% to 99%, respectively. The absorption temperature had a trivial impact on the H2S removal efficiency, and the maximum value appeared at 45℃. Additionally, all operating parameters caused pH changes that varied in the acceptable range (0.1 to 0.5) during the absorption process. A rate-based model was successfully developed to predict the haloalkaliphilic H2S absorption process accurately. Moreover, this model could be implemented to effectively evaluate the HBDS system’s stability and provide reliable theoretical guidance for the industrial HBDS process to ensure good process stability.
Keywords:Haloalkaliphilic biological desulfurization;H2S absorption;Process stability;Rate-based model;Simulation;Optimization
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