Artificial sweeteners in wastewater treatment plants: A systematic review of global occurrence, distribution, removal, and degradation pathways
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The widespread use of artificial sweeteners in foods, drinks, and pharmaceuticals has led to rising concentrations in wastewater, with specific sweeteners raising concerns due to demonstrated toxicological risks to ecosystems and humans. To date, a comprehensive summary of the occurrence, distribution, and removal status of artificial sweeteners in wastewater treatment plants (WWTP) is lacking, making it difficult to evaluate the associated risks and environmental impacts. We conducted a systematic review of scientific literature and grey literature with rigorous screening covering 24 countries and 6 continents. Globally, sucralose, acesulfame, saccharin, and cyclamate are prevalent artificial sweeteners in WWTP, with concentrations of 0.6-303.0 µg/L in influent and 0.1-81.2 µg/L in effluent. Sucralose showed obvious increasing concentrations over time in wastewater in the United States and Canada, with an increase of 5.6-5.7 µg/L·y in influent and 4.7-5.5 µg/L·y in effluent. Summer wastewater usually contains 11.1-33.3 % higher concentrations of artificial sweeteners than other seasons. Saccharin and cyclamate are the most easily removable sweeteners (>90.0 % removal) in WWTP, followed by acesulfame (25.0-70.1 %) and sucralose (-10.0-10.0 %). Wastewater treatment processes with longer HRT and more diverse microbial communities showed better performance in sucralose removal, while processes with aerobic conditions showed better performance in acesulfame and saccharin removal than anaerobic processes. Increasing trends for persistent sucralose and acesulfame removal have been observed globally, suggesting potential microbial evolution/adaptation. This review contributes to a comprehensive understanding of the spatiotemporal distribution and ever-evolving biodegradation of artificial sweeteners in WWTP, providing future perspectives and potential policy requirements.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 it