4.7 Article

Optimization of Fenton process for removing TOC and color from swine wastewater using response surface method (RSM)

期刊

JOURNAL OF ENVIRONMENTAL MANAGEMENT
卷 279, 期 -, 页码 -

出版社

ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD
DOI: 10.1016/j.jenvman.2020.111625

关键词

TOC removal; Color removal; Advanced oxidation processes (AOPs); Response surface method (RSM); Fenton oxidation; Swine wastewater

资金

  1. National Research Foundation of Korea [NRF-2020R1A2C2012106]

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The Fenton oxidation process was successfully applied to biologically treated swine wastewater (BSWW) for the removal of TOC and color constituents. By optimizing operational variables using the response surface method (RSM), it was found that FeSO4 is more important for TOC removal, while H2O2 plays a significant role in color removal. The optimal conditions derived through process optimization led to 76.7% removal of TOC and 98% removal of color from the swine wastewater.
The Fenton oxidation process was applied to biologically treated swine wastewater (BSWW) for the removal of TOC and color constituents after coagulation with FeCl3. Optimizing of operational variables such as FeSO4 and H2O2 doses was achieved by the response surface method (RSM). Statistical analysis led to the conclusion that FeSO4 is the more important than H2O2 in the removal of TOC. However, H2O2 plays a more significant role than FeSO4 in color removal. The optimal conditions for effective removal of TOC and color from swine wastewater were derived by using process optimization. The experimental results show that overall removal of TOC and color is 76.7% and 98%, respectively, when optimal conditions of 800 mg/L (FeSO4) and 5207 mg/L (H2O2) at 120 min were used. Furthermore, the optimization model produces a desirability value of 0.980 that verifies the optimal conditions. Finally, it is observed that removal of undesirable compounds follows a pseudo-first order and pseudo-second order kinetics model with high R-2 values of 0.99 for both TOC and color removal, respectively. Statistical analysis and process optimization show that the employed model may determine conditions conducive to the effective removal of TOC and color from swine wastewater.

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