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

Abstract

<p>Anoxic thiosulfate (S<sub>2</sub>O<sub>3</sub> <sup>2−</sup>) 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. S<sub>2</sub>O<sub>3</sub> <sup>2−</sup> removal efficiencies >99% were obtained at a N/S ratio of 0.5 and a S<sub>2</sub>O<sub>3</sub> <sup>2−</sup> and nitrate (NO<sub>3</sub> <sup>−</sup>) loading rate of 820 (±84) mg S-S<sub>2</sub>O<sub>3</sub> <sup>2−</sup> L<sup>−1</sup> d<sup>−1</sup> and 173 (±10) mg N-NO<sub>3</sub> <sup>−</sup> L<sup>−1</sup> d<sup>−1</sup>, respectively. The S<sub>2</sub>O<sub>3</sub> <sup>2−</sup> 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 (K<sub>s</sub>) and inhibition (K<sub>I</sub>) constants of the biofilm-grown NR-SOB obtained from batch cultivations were 172 and 800 mg S-S<sub>2</sub>O<sub>3</sub> <sup>2−</sup> L<sup>−1</sup>, respectively. Thiobacilus denitrificans was the dominant microorganism in the FBR. Artificial neural network modeling successfully predicted S<sub>2</sub>O<sub>3</sub> <sup>2−</sup> and NO<sub>3</sub> <sup>−</sup> removal efficiencies and SO<sub>4</sub> <sup>2−</sup> production in the FBR. Additionally, results from the sensitivity analysis showed that the effluent pH was the most influential parameter affecting the S<sub>2</sub>O<sub>3</sub> <sup>2−</sup> removal efficiency.</p>