In
this study, the degradation of Dicamba methyl ester
(DME) was
investigated using a low-cost chlorine/ferrous process. The degradation
yield was determined by examining the influence of several factors,
such as NaClO concentration, dicamba concentration, FeSO4 catalyst mass, and initial solution pH, over a 15 min period. To
determine the optimal conditions for DME degradation, an artificial
neural network (ANN) model with 4-5-1 architecture was developed.
The particle swarm optimization (PSO) algorithm was then utilized
in conjunction with the ANN model to identify the optimal factor levels
predicted yield of 88%. The following optimal conditions were identified:
[NaClO] = 422.3 μM, [Dicamba] = 4.4 mg/L, [FeSO4]
= 9.5 mg/L, and a pH of 2.56. GC/MS analysis was conducted to identify
the byproducts that were generated during DME degradation. Benzene,
1,2,4-trichloro-3-methoxy DME-BP (m/z 210) was the only identified byproduct that contained chlorine in
its structure. A proposed reaction pathway for the DME degradation
was suggested based on the obtained mass spectra. In the final stage
of the study, total organic carbon (TOC) removal was analyzed using
a Fenton-like process under optimized conditions for a duration of
195 min. To confirm the effectiveness of DME and its byproduct degradation,
toxicity assessments were performed using the Chlorella
vulgaris microalgae as a model organism. The results
indicated a low toxicity of 20% when the DME mineralization reached
62.52%. These findings provide strong evidence that support the effectiveness
of the proposed low-cost system for DME removal.