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    Effect of pH on the Performance of Sulfate and Thiosulfate-Fed Sulfate Reducing Inverse Fluidized Bed Reactors

    Source: Journal of Environmental Engineering:;2016:;Volume ( 142 ):;issue: 009
    Author:
    Suthee Janyasuthiwong
    ,
    Eldon R. Rene
    ,
    Giovanni Esposito
    ,
    Piet N. L. Lens
    DOI: 10.1061/(ASCE)EE.1943-7870.0001004
    Publisher: American Society of Civil Engineers
    Abstract: Sulfate-reducing bacteria (SRB)–based technologies have gained a lot of attention in the field of wastewater treatment, especially to treat metal-contaminated wastewaters. An inverse fluidized bed (IFB) bioreactor is a versatile bioreactor configuration that uses SRB technology for metal removal and recovery from wastewater. Apart from sulfate, which is commonly used as an electron acceptor, thiosulfate is another potential candidate for this process. In this study, the performance of two IFB bioreactors that were operated at pH 7.0 (R1) and 5.0 (R2) using sulfate and thiosulfate as the electron acceptors were evaluated. The electron donor used in this study was ethanol and the chemical oxygen demand (COD) to electron acceptor ratio (SO42− or S2O32−) was kept constant at 1.0. By using sulfate as the electron acceptor, the average COD removal efficiency was 75.0 and 58.0% at pH 7.0 and 5.0, respectively, while the sulfate removal efficiency was 74.4 and 50.4%, respectively. The average sulfide production was 246.3 and 150.7  mg/L at pH 7.0 and pH 5.0, respectively. Using thiosulfate as the electron acceptor, slightly higher sulfate reduction activities were achieved when compared to sulfate at pH 5.0. The maximum COD removal efficiency was 54.8% and 162.7  mg/L sulfide was produced. The COD and sulfate removal efficiencies as well as the total sulfide production profiles in the IFB reactor fed with sulfate were modeled using a three-layered artificial neural network (ANN). The results showed that the developed ANN model with a topology of 3-7-3 was able to give good predictions of the performance variables. Moreover, the sensitivity analysis from ANN showed that this process is mainly pH dependent.
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      Effect of pH on the Performance of Sulfate and Thiosulfate-Fed Sulfate Reducing Inverse Fluidized Bed Reactors

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    contributor authorSuthee Janyasuthiwong
    contributor authorEldon R. Rene
    contributor authorGiovanni Esposito
    contributor authorPiet N. L. Lens
    date accessioned2017-12-30T12:54:24Z
    date available2017-12-30T12:54:24Z
    date issued2016
    identifier other%28ASCE%29EE.1943-7870.0001004.pdf
    identifier urihttp://138.201.223.254:8080/yetl1/handle/yetl/4243218
    description abstractSulfate-reducing bacteria (SRB)–based technologies have gained a lot of attention in the field of wastewater treatment, especially to treat metal-contaminated wastewaters. An inverse fluidized bed (IFB) bioreactor is a versatile bioreactor configuration that uses SRB technology for metal removal and recovery from wastewater. Apart from sulfate, which is commonly used as an electron acceptor, thiosulfate is another potential candidate for this process. In this study, the performance of two IFB bioreactors that were operated at pH 7.0 (R1) and 5.0 (R2) using sulfate and thiosulfate as the electron acceptors were evaluated. The electron donor used in this study was ethanol and the chemical oxygen demand (COD) to electron acceptor ratio (SO42− or S2O32−) was kept constant at 1.0. By using sulfate as the electron acceptor, the average COD removal efficiency was 75.0 and 58.0% at pH 7.0 and 5.0, respectively, while the sulfate removal efficiency was 74.4 and 50.4%, respectively. The average sulfide production was 246.3 and 150.7  mg/L at pH 7.0 and pH 5.0, respectively. Using thiosulfate as the electron acceptor, slightly higher sulfate reduction activities were achieved when compared to sulfate at pH 5.0. The maximum COD removal efficiency was 54.8% and 162.7  mg/L sulfide was produced. The COD and sulfate removal efficiencies as well as the total sulfide production profiles in the IFB reactor fed with sulfate were modeled using a three-layered artificial neural network (ANN). The results showed that the developed ANN model with a topology of 3-7-3 was able to give good predictions of the performance variables. Moreover, the sensitivity analysis from ANN showed that this process is mainly pH dependent.
    publisherAmerican Society of Civil Engineers
    titleEffect of pH on the Performance of Sulfate and Thiosulfate-Fed Sulfate Reducing Inverse Fluidized Bed Reactors
    typeJournal Paper
    journal volume142
    journal issue9
    journal titleJournal of Environmental Engineering
    identifier doi10.1061/(ASCE)EE.1943-7870.0001004
    pageC4015012
    treeJournal of Environmental Engineering:;2016:;Volume ( 142 ):;issue: 009
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
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