Unveiling the adsorption mechanisms and key influencing factors of cyclic acetals on powdered activated carbon
Bibliographic record
Abstract
Cyclic acetals (CAs), such as 2-ethyl-5,5-dimethyl-1,3-dioxane (2-EDD) and 2-ethyl-4-methyl-1,3-dioxolane (2-EMD), are emerging odourants in drinking water, raising significant concerns due to their extremely low odour thresholds, high stability, and potential health risks. This study investigated 2-EDD and 2-EMD adsorption performance on six powdered activated carbons (PACs). The adsorption isotherms fitted well with Freundlich (R2 = 0.907∼0.996) and Temkin models (R2 = 0.874–0.997). The adsorption efficiency of 2-EDD (the Freundlich constant KF = 0.0847–0.802) was higher than 2-EMD (KF = 0.0435–0.239), because of its greater molecular mass and higher hydrophobicity. All PACs reached equilibrium in about 120 minutes, and the adsorption kinetics fitted better with the pseudo-second-order model (R2 = 0.920∼0.997), indicating that chemical adsorption significantly contributed to CAs’ adsorption. The adsorption rates for 2-EDD (k2 = 0.123-1.235) were lower compared to 2-EMD (k2 = 0.245–4.770). Results from correlation analysis revealed that average pore size, pore volume, and mesoporous fraction were the key PAC properties in controlling CAs’ adsorption. Diffusion-chemisorption model, Weber and Morris intraparticle diffusion kinetic model, and Boyd kinetic model were employed to elucidate the adsorption mechanism. The results indicated that the two CAs were interacted mainly through chemical adsorption, with film diffusion serving as the step controlling the rate. PACs exhibited effective performance under neutral to slightly alkaline conditions, as well as in source water and tap water. Meanwhile, 20 mg·L−1 PAC could reduce CAs’ concentration from 40 ng·L−1 to 5 ng·L−1. This study provides a benchmark for selecting effective carbon to address odour issues caused by CAs.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".