| Title: | Modelling the removal of volatile pollutants under transient conditions in a two-stage bioreactor using artificial neural networks |
| Author(s): | Lopez ME; Rene ER; Boger Z; Veiga MC; Kennes C; |
| Address: | "Chemical Engineering Laboratory, Faculty of Sciences, University of La Coruna, Rua da Fraga, 10, E-15008 La Coruna, Spain. Chemical Engineering Laboratory, Faculty of Sciences, University of La Coruna, Rua da Fraga, 10, E-15008 La Coruna, Spain; Department of Environmental Engineering and Water Technology, UNESCO-IHE, P.O. Box 3015, 2601 DA Delft, The Netherlands. OPTIMAL-Industrial Neural Systems, 54 Rambal St., Be'er Sheva, 84243 Israel. Chemical Engineering Laboratory, Faculty of Sciences, University of La Coruna, Rua da Fraga, 10, E-15008 La Coruna, Spain. Electronic address: Kennes@udc.es" |
| DOI: | 10.1016/j.jhazmat.2016.03.018 |
| ISSN/ISBN: | 1873-3336 (Electronic) 0304-3894 (Linking) |
| Abstract: | "A two-stage biological waste gas treatment system consisting of a first stage biotrickling filter (BTF) and second stage biofilter (BF) was tested for the removal of a gas-phase methanol (M), hydrogen sulphide (HS) and alpha-pinene (P) mixture. The bioreactors were tested with two types of shock loads, i.e., long-term (66h) low to medium concentration loads, and short-term (12h) low to high concentration loads. M and HS were removed in the BTF, reaching maximum elimination capacities (EC(max)) of 684 and 33 gm(-3)h(-1), respectively. P was removed better in the second stage BF with an EC(max) of 130 gm(-3)h(-1). The performance was modelled using two multi-layer perceptrons (MLPs) that employed the error backpropagation with momentum algorithm, in order to predict the removal efficiencies (RE, %) of methanol (RE(M)), hydrogen sulphide (RE(HS)) and alpha-pinene (RE(P)), respectively. It was observed that, a MLP with the topology 3-4-2 was able to predict RE(M) and RE(HS) in the BTF, while a topology of 3-3-1 was able to approximate RE(P) in the BF. The results show that artificial neural network (ANN) based models can effectively be used to model the transient-state performance of bioprocesses treating gas-phase pollutants" |
| Keywords: | "Air Pollutants/*isolation & purification Algorithms Bicyclic Monoterpenes Biodegradation, Environmental *Bioreactors Computer Simulation Hydrogen Sulfide/isolation & purification Methanol/isolation & purification Monoterpenes/isolation & purification *Neu;" |
| Notes: | "MedlineLopez, M Estefania Rene, Eldon R Boger, Zvi Veiga, Maria C Kennes, Christian eng Netherlands 2016/03/30 J Hazard Mater. 2017 Feb 15; 324(Pt A):100-109. doi: 10.1016/j.jhazmat.2016.03.018. Epub 2016 Mar 8" |
