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  • 标题:Experimental and Theoretical Study for Hydrogen Biogas Production from Municipal Solid Waste
  • 本地全文:下载
  • 作者:Ali, A. H. ; Ali, A. H. ; Al-Mussawy, H. A.
  • 期刊名称:Pollution
  • 印刷版ISSN:2383-451X
  • 电子版ISSN:2383-4501
  • 出版年度:2019
  • 卷号:5
  • 期号:1
  • 页码:147-159
  • DOI:10.22059/poll.2018.262786.483
  • 语种:English
  • 出版社:University of Tehran
  • 摘要:This study carried out to investigate the production of hydrogen using the organic fraction of municipal solid waste OFMSW, where the anaerobic digester was depended as a method for disposing and treating OFMSW and producing bio-hydrogen. Bio-hydrogen production had been studied under different parameters including pH, solid content T.S%, temperature and mixing ratios between the thick sludge to OFMSW. The optimal conditions were found at pH, T.S%, temp and mix ratio of 7, 8%, 32oC, and 1:5, respectively where the hydrogen yield was (138.88 mL/gm vs). To found the most important parameters in this process, the ANN model had been applied. The effectiveness of temperature, total solid, mixing ratio and pH comes in the following sequence 100%, 75.8%, 71.9%, and 57.2% respectively, with R 2 of 95.7%. Multiple correlation model was used to formulate an equation linked between the hydrogen production and the parameters effected on. Gompertz model was applied to compare between theoretical and experimental outcomes, it also given a mathematical equation with high correlation coefficient R 2 of 99.95% where the theoretical bio-hydrogen was (141.76 mL/gm vs) under best conditions. The first order kinetic model was applied to evaluate the dynamics of the degradation process. The obtained negative value of (k = - 0.0886), indicates that, the solid waste biodegradation was fast and progresses in the right directio.
  • 关键词:Anaerobic digestion; Artificial neural network (ANN); Multiple correlation; Gompertz model
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