Journal
SCIENCE OF THE TOTAL ENVIRONMENT
Volume 862, Issue -, Pages -Publisher
ELSEVIER
DOI: 10.1016/j.scitotenv.2022.160802
Keywords
Sequence batch reactor; Box -Behnken design; Partial nitri fication; Response surface methodology; salinity; wastewater treatment
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In this study, the operation parameters of partial nitrification (PN) treating saline wastewater were optimized using the Box-Behnken design and response surface methodology (BBD-RSM). A control strategy based on carbon/nitrogen ratio (C/N), alkalinity/ammonia ratio (K/A), and salinity was used to achieve high and stable PN. The optimized process showed improved ammonia removal efficiency (ARE) and nitrite accumulation rate (NAR) compared to the nonoptimized process. The developed regression model accurately predicted the PN performance under optimal conditions.
In this study, the operation parameters of a partial nitrification process (PN) treating saline wastewater were optimized using the Box-Behnken design via the response surface methodology (BBD-RSM). A novel strategy based on the con-trol of the carbon/nitrogen ratio (C/N), alkalinity/ammonia ratio (K/A), and salinity in three stages was used to achieve PN in a sequence batch reactor. The results demonstrated that a high and stable PN was completed after 50 d with an ammonia removal efficiency (ARE) of 98.37 % and nitrite accumulation rate (NAR) of 85.93 %. Next, BBD-RSM was applied, where ARE and NAR were the responses. The highest responses from the confirmation exper-iment were 99.9 % +/- 0.04 and 95.25 % +/- 0.32 when the optimum C/N, K/A, and salinity were identified as 0.84, 2, and 5.5 (g/L), respectively. The results were higher than those for the nonoptimized reactor. The developed regression model adequately forecasts the PN performance under optimal conditions. Therefore, this study provides a promising strategy for controlling the PN process and shows how the BBD-RSM model can improve the PN performance.
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