Evaluates transformation products in wastewater, suggesting a need for risk assessments in treatments.
In this study, an integrated in silico risk assessment strategy combining suspect screening, (Q)SAR modeling, and multicriteria decision-making (MCDM) was applied to prioritize predicted high-risk TPs formed during the solar photo-Fenton (SPF) process operated under different pH conditions. Six pharmaceuticals widely used during the pandemic, namely azithromycin (AZT), hydroxychloroquine (HCQ), nitazoxanide (NTZ), dipyrone (DIP), paracetamol (PCT), and dexamethasone acetate (ADEX) were subjected to SPF in deionized water and real hospital WW, at pH 2.8 and at near-neutral pH (5.0), using single and multiple additions of iron. Higher removal efficiencies of the parent compounds and the highest number of TPs were achieved at pH 2.8. From 136 TPs of purpose-built database constructed, a total of 36 TPs were observed, including a previously unreported TP of AZT. Under all SPF conditions, most of the TPs persisted until the end of the treatment. (Q)SAR predictions performed for the parent compounds and TPs were integrated with an entropy-weighted VIKOR approach. The ranking revealed that TPs derived mainly from HCQ and NTZ presented the highest predicted overall risks, while TPs related to PCT were consistently ranked as low priority. Of the 36 tentatively identified TPs, 39% had a higher predicted risk than their pharmaceutical originals, based on the overall ranking. The results highlight the importance of incorporating TP risk evaluation into the appraisal of AOPs.
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Frois et al. (2026) studied this question.
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