Pesticide decontamination using UV/ferrous-activated persulfate with the aid neuro-fuzzy modeling: A case study of Malathion

• Published in: Food research international Vol. 137; p. 109557
• Main Authors: Vasseghian, Yasser, Moradi, Masoud, Pirsaheb, Meghdad, Khataee, Alireza, Rahimi, Shoeib, Badi, Mojtaba Yegane, Mousavi Khaneghah, Amin
• Format: Journal Article
• Language: English
• Published: Canada Elsevier Ltd 01.11.2020
• Subjects: Advanced oxidation process; Decontamination; Hydroxyl Radical; Malathion; Malathion degradation; Neuro-fuzzy model; Persulfate; Pesticides; Neuro-fuzzy model; Malathion degradation; Persulfate; Advanced oxidation process
• ISSN: 0963-9969; 1873-7145
• DOI: 10.1016/j.foodres.2020.109557

[Display omitted] •Decontamintion of Malathion by PS, UV, PS/Fe2+, PS/UV, and PS/Fe2+/UV processes was investigated.•The effects of different inorganic ions (Cl−, NO3−, HCO3−and H2PO4−) were evaluated.•The sulfate radicals had more contribution to Malathion degradation.•ANFIS is capable of modeling and optimizing the degradation process. In the current study, the Malathion decontamination by the aid of the UV/ferrous-activated persulfate (PS) was investigated and the effects of pH, persulfate (PS) concentration, ferrous concentration, Malathion concentration, and different inorganic ions were evaluated. Also, the Adaptive Neuro-Fuzzy Inference System (ANFIS) was applied to model Malathion degradation data. The maximum degradation efficiency was associated with pH = 3, PS concentration of 1.2 mM, the ferrous concentration of 0.6 mM, Malathion concentration of 20 mg/L for 60 min. The degradation efficiency was decreased in the presence of Cl− (23%), NO3− (13.5%), HCO3− (35.4%) and H2PO4− (48.7%) ions. Results revealed that persulfate radical (52%) plays a more important role in Malathion degradation while compared with hydroxyl radical (15%). The low root mean square error (RMSE = 6.451), mean absolute error (MAE = 3.8306), absolute-average-deviation (AAD = 0.1005) and high coefficient of determination (R2 = 0.972) correlated with the proposed ANFIS models confirmed the model accuracy. Besides, the process optimization was conducted by using ANFIS to predict the best operating circumstances, which resulted in the maximum Malathion degradation (95.54%).