Occurrence and risk assessment of typical PPCPs and biodegradation pathway of ribavirin in wastewater treatment plants
Bibliographic record
Abstract
A large number of pharmaceuticals and personal care products (PPCPs) persist in wastewater, and the consumption of PPCPs for COVID-19 control and prevention has sharply increased during the pandemic. This study investigated the occurrence, removal efficiency, and risk assessment of six typical PPCPs commonly used in China in two wastewater treatment plants (WWTPs). Ribavirin (RBV) is an effective pharmaceutical for severely ill patients with COVID-19, and the possible biodegradation pathway of RBV by activated sludge was discovered. The experimental results showed that PPCPs were detected in two WWTPs with a detection rate of 100% and concentrations ranging between 612 and 2323 ng L−1. The detection frequency and concentrations of RBV were substantially higher, with a maximum concentration of 314 ng L−1. Relatively high pollution loads were found for the following PPCPs from influent: ibuprofen > ranitidine hydrochloride > RBV > ampicillin sodium > clozapine > sulfamethoxazole. The removal efficiency of PPCPs was closely related to adsorption and biodegradation in activated sludge, and the moving bed biofilm reactor (MBBR) had a higher removal capacity than the anoxic-anaerobic-anoxic-oxic (AAAO) process. The removal efficiencies of sulfamethoxazole, ampicillin sodium, ibuprofen, and clozapine ranged from 92.21% to 97.86% in MBBR process and were relatively low, from 61.82% to 97.62% in AAAO process, and the removal of RBV and ranitidine hydrochloride were lower than 42.96% in both MBBR and AAAO processes. The discrepancy in removal efficiency is caused by temperature, hydrophilicity, and hydrophobicity of the compound, and acidity and alkalinity. The transformation products of RBV in activated sludge were detected and identified, and the biodegradation process of RBV could be speculated as follows: first breaks into TCONH2 and an oxygen-containing five-membered heterocyclic ring under the nucleosidase reaction, and then TCONH2 is finally formed into TCOOH through amide hydrolysis. Aquatic ecological risks based on risk quotient (RQ) assessment showed that PPCPs had high and medium risks in the influent, and the RQ values were all reduced after MBBR and AAAO treatment. Ranitidine hydrochloride and clozapine still showed high and medium risks in the effluent, respectively, and thus presented potential risks to the aquatic ecosystem.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".