UV/PMS and UV/PDS processes for efficient formaldehyde removal: Mechanistic insights, machine learning prediction, and eco-efficiency optimization
Journal of Environmental Chemical Engineering, cilt.14, sa.5, 2026 (SCI-Expanded, Scopus)
- Yayın Türü: Makale / Tam Makale
- Cilt numarası: 14 Sayı: 5
- Basım Tarihi: 2026
- Doi Numarası: 10.1016/j.jece.2026.124010
- Dergi Adı: Journal of Environmental Chemical Engineering
- Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Chemical Abstracts Core, Compendex, INSPEC
- Anahtar Kelimeler: Formaldehyde degradation, Machine learning, Sulfate radicals, UV/PDS, UV/PMS
- Ondokuz Mayıs Üniversitesi Adresli: Evet
Özet
Formaldehyde (HCHO) is a toxic organic pollutant commonly found in industrial wastewater, requiring efficient and sustainable treatment strategies. In this study, UV/PMS and UV/PDS systems were investigated for formaldehyde degradation. Key operational parameters, including oxidant dose, reaction time, initial concentration, and pH, were systematically evaluated. Both systems achieved near-complete removal under mild conditions (pH 6, 25°C), with UV/PDS exhibiting faster kinetics and reaching 99.73% removal within 5 min. Kinetic analysis revealed pseudo-second-order behavior, suggesting that the degradation process depends on the interaction between formaldehyde molecules and reactive radical species. Radical quenching experiments suggested a substantial contribution of sulfate radical-mediated oxidation to formaldehyde degradation, while hydroxyl radicals played a secondary role in UV/PMS and a limited role in UV/PDSA machine learning framework accurately predicted formaldehyde removal efficiency, with Gradient Boosting yielding the best performance (CV-R² = 0.854). SHAP analysis identified oxidant dose and reaction time as the key controlling variables. Eco-efficiency assessment identified an optimal operating window at 1.5–2.0 mM oxidant dose, where high formaldehyde removal was achieved with relatively low oxidant consumption. Under comparable operating conditions, the UV/PDS system exhibited a more favorable sustainability profile than the UV/PMS system, reflecting its ability to achieve near-complete degradation at lower oxidant demand and shorter reaction times. Overall, the integrated experimental, mechanistic, and predictive modeling framework provides quantitative guidance for the optimization and sustainable design of UV-activated persulfate treatment systems.