Elucidation of reaction pathways and multi-response optimization of 2,4-dichlorophenoxyacetic acid degradation in a
Abdollah Dargahi1, Zahra Danandeh2, S Ahmad Mokhtari2
1Department of Environmental Health Engineering, Khalkhal University of Medical Sciences Khalkhal Iran.
Abstract:
The persistence of chlorophenoxy herbicides in aquatic environments poses significant environmental and public health concerns due to their resistance to conventional treatment processes. In this study, the degradation of 2,4-dichlorophenoxyacetic acid (2,4-D) was systematically investigated using a hybrid UV/persulfate/ozone (UV/PS/O3) advanced oxidation process integrating statistical optimization with mechanistic pathway elucidation. A Box-Behnken response surface methodology (RSM) was applied to evaluate the effects of initial pH, 2,4-D concentration, persulfate dosage, reaction time, and ozone flow rate on degradation efficiency. The developed quadratic model demonstrated excellent predictive performance (R 2 = 0.9919, p < 0.0001) with a non-significant lack-of-fit, confirming the robustness of the optimization framework. Among the investigated variables, reaction time exerted the strongest influence on degradation efficiency, followed by initial pollutant concentration and pH. Under the optimized conditions (pH 5, 20 mg L-1 2,4-D, 35 mg L-1 persulfate, 30 min reaction time, and 2 L min-1 ozone flow rate), the process achieved 99.5% removal of 2,4-D and 70-90% total organic carbon reduction, indicating substantial mineralization. The calculated synergy index (1.38) confirmed that the integrated system outperformed the additive effects of the individual oxidation processes through the simultaneous generation of sulfate radicals (SO4˙-) and hydroxyl radicals (˙OH). LC-QTOF-MS analysis identified key aromatic and aliphatic intermediates, enabling the proposal of a degradation pathway involving ether bond cleavage, dechlorination, hydroxylation, aromatic ring opening, and final mineralization. The findings demonstrate that coupling RSM-based optimization with mechanistic analysis provides an effective framework for designing hybrid sulfate radical-based advanced oxidation systems for the treatment of refractory herbicides in contaminated water matrices.
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