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Effect of N/S ratio on anoxic thiosulfate oxidation in a fluidized bed reactor: Experimental and artificial neural network model analysis

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Effect of N/S ratio on anoxic thiosulfate oxidation in a fluidized bed reactor : Experimental and artificial neural network model analysis. / Khanongnuch, Ramita; Di Capua, Francesco; Lakaniemi, Aino-Maija; Rene, Eldon R.; Lens, Piet N.L.

julkaisussa: Process Biochemistry, Vuosikerta 68, 2018, s. 171-181.

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Khanongnuch, Ramita ; Di Capua, Francesco ; Lakaniemi, Aino-Maija ; Rene, Eldon R. ; Lens, Piet N.L. / Effect of N/S ratio on anoxic thiosulfate oxidation in a fluidized bed reactor : Experimental and artificial neural network model analysis. Julkaisussa: Process Biochemistry. 2018 ; Vuosikerta 68. Sivut 171-181.

Bibtex - Lataa

@article{e3eb8d48dc684cd1a7ddc8f07ae54079,
title = "Effect of N/S ratio on anoxic thiosulfate oxidation in a fluidized bed reactor: Experimental and artificial neural network model analysis",
abstract = "Anoxic thiosulfate (S2O3 2−) oxidation using autotrophic denitrification by a mixed culture of nitrate reducing, sulfur oxidizing bacteria (NR-SOB) was studied in a fluidized bed reactor (FBR). The long-term performance of the FBR was evaluated for 306 days at three nitrogen-to-sulfur (N/S) molar ratios (0.5, 0.3 and 0.1) and a hydraulic retention time (HRT) of 5 h. S2O3 2− removal efficiencies >99{\%} were obtained at a N/S ratio of 0.5 and a S2O3 2− and nitrate (NO3 −) loading rate of 820 (±84) mg S-S2O3 2− L−1 d−1 and 173 (±10) mg N-NO3 − L−1 d−1, respectively. The S2O3 2− removal efficiency decreased to 76{\%} and 26{\%} at N/S ratios of 0.3 and 0.1, respectively, and recovered to 80{\%} within 3 days after increasing the N/S ratio from 0.1 back to 0.5. The highest observed half-saturation (Ks) and inhibition (KI) constants of the biofilm-grown NR-SOB obtained from batch cultivations were 172 and 800 mg S-S2O3 2− L−1, respectively. Thiobacilus denitrificans was the dominant microorganism in the FBR. Artificial neural network modeling successfully predicted S2O3 2− and NO3 − removal efficiencies and SO4 2− production in the FBR. Additionally, results from the sensitivity analysis showed that the effluent pH was the most influential parameter affecting the S2O3 2− removal efficiency.",
keywords = "Anoxic thiosulfate oxidation, Artificial neutral network, Kinetic constants, Nitrate reducing-sulfur oxidizing bacteria, Thiobacilus denitrificans",
author = "Ramita Khanongnuch and {Di Capua}, Francesco and Aino-Maija Lakaniemi and Rene, {Eldon R.} and Lens, {Piet N.L.}",
year = "2018",
doi = "10.1016/j.procbio.2018.02.018",
language = "English",
volume = "68",
pages = "171--181",
journal = "Process Biochemistry",
issn = "1359-5113",
publisher = "Elsevier",

}

RIS (suitable for import to EndNote) - Lataa

TY - JOUR

T1 - Effect of N/S ratio on anoxic thiosulfate oxidation in a fluidized bed reactor

T2 - Experimental and artificial neural network model analysis

AU - Khanongnuch, Ramita

AU - Di Capua, Francesco

AU - Lakaniemi, Aino-Maija

AU - Rene, Eldon R.

AU - Lens, Piet N.L.

PY - 2018

Y1 - 2018

N2 - Anoxic thiosulfate (S2O3 2−) oxidation using autotrophic denitrification by a mixed culture of nitrate reducing, sulfur oxidizing bacteria (NR-SOB) was studied in a fluidized bed reactor (FBR). The long-term performance of the FBR was evaluated for 306 days at three nitrogen-to-sulfur (N/S) molar ratios (0.5, 0.3 and 0.1) and a hydraulic retention time (HRT) of 5 h. S2O3 2− removal efficiencies >99% were obtained at a N/S ratio of 0.5 and a S2O3 2− and nitrate (NO3 −) loading rate of 820 (±84) mg S-S2O3 2− L−1 d−1 and 173 (±10) mg N-NO3 − L−1 d−1, respectively. The S2O3 2− removal efficiency decreased to 76% and 26% at N/S ratios of 0.3 and 0.1, respectively, and recovered to 80% within 3 days after increasing the N/S ratio from 0.1 back to 0.5. The highest observed half-saturation (Ks) and inhibition (KI) constants of the biofilm-grown NR-SOB obtained from batch cultivations were 172 and 800 mg S-S2O3 2− L−1, respectively. Thiobacilus denitrificans was the dominant microorganism in the FBR. Artificial neural network modeling successfully predicted S2O3 2− and NO3 − removal efficiencies and SO4 2− production in the FBR. Additionally, results from the sensitivity analysis showed that the effluent pH was the most influential parameter affecting the S2O3 2− removal efficiency.

AB - Anoxic thiosulfate (S2O3 2−) oxidation using autotrophic denitrification by a mixed culture of nitrate reducing, sulfur oxidizing bacteria (NR-SOB) was studied in a fluidized bed reactor (FBR). The long-term performance of the FBR was evaluated for 306 days at three nitrogen-to-sulfur (N/S) molar ratios (0.5, 0.3 and 0.1) and a hydraulic retention time (HRT) of 5 h. S2O3 2− removal efficiencies >99% were obtained at a N/S ratio of 0.5 and a S2O3 2− and nitrate (NO3 −) loading rate of 820 (±84) mg S-S2O3 2− L−1 d−1 and 173 (±10) mg N-NO3 − L−1 d−1, respectively. The S2O3 2− removal efficiency decreased to 76% and 26% at N/S ratios of 0.3 and 0.1, respectively, and recovered to 80% within 3 days after increasing the N/S ratio from 0.1 back to 0.5. The highest observed half-saturation (Ks) and inhibition (KI) constants of the biofilm-grown NR-SOB obtained from batch cultivations were 172 and 800 mg S-S2O3 2− L−1, respectively. Thiobacilus denitrificans was the dominant microorganism in the FBR. Artificial neural network modeling successfully predicted S2O3 2− and NO3 − removal efficiencies and SO4 2− production in the FBR. Additionally, results from the sensitivity analysis showed that the effluent pH was the most influential parameter affecting the S2O3 2− removal efficiency.

KW - Anoxic thiosulfate oxidation

KW - Artificial neutral network

KW - Kinetic constants

KW - Nitrate reducing-sulfur oxidizing bacteria

KW - Thiobacilus denitrificans

U2 - 10.1016/j.procbio.2018.02.018

DO - 10.1016/j.procbio.2018.02.018

M3 - Article

VL - 68

SP - 171

EP - 181

JO - Process Biochemistry

JF - Process Biochemistry

SN - 1359-5113

ER -