Efficient degradation of diclofenac by digestate-derived biochar catalyzed peroxymonosulfate oxidation: Performance, machine learning prediction, and mechanism

Diclofenac (DCF), a widely used drug, is frequently found in natural waters, and its removal has caused extensive concern. Sulfate radical-based advanced oxidation processes are efficient for the degradation of organic pollutants, but the self-decomposition of persulfates is always sluggish and restricted. Herein, self-N doped biochar derived from food waste digestate (FWDB) was evaluated as the activator of peroxylmonosulfate (PMS) in terms of DCF degradation. The effects of several key operating variables were examined, and the results indicated that similar to 93% of DCF with an initial concentration of 20 mg/L was removed at FWDB dosage of 0.3 g/L and PMS concentration of 1.0 mM. Thereafter, the machine learning method was explored to simulate and predict the DCF removal process. The reactive oxygen species participated in the reaction was identified as O-1(2), and the reaction sites on FWDB were determined as graphitized carbon, C = O structure, doped-N, and defective edges. Moreover, based on the identification of intermediates and products, the possible DCF destruction pathways were proposed as hydroxylation, cleavage of N-C bond, and decarboxylation. This study provided an economical and convenient heterogeneous PMS activator for remediation of organic wastewater and confirmed the feasibility of optimizing the contaminant degradation process via data mining.