Impact of Organic Carbon on Manganese Release, Colloid Formation, and Aggregation in Surface and Groundwater
Bibliographic record
Abstract
The interaction of manganese (Mn) oxides with natural organic matter (NOM) can mobilize Mn, impacting groundwater quality. However, the formation of Mn colloids, critical determinants of Mn transport and aggregation, is often overlooked. To investigate Mn behavior and colloid formation upon C amendment, humic acid was reacted with Mn oxide suspensions at different C:Mn molar ratios (C:Mn = 0-15) over 200 h. The addition of organic carbon promoted the formation of highly stabilized and mixed-valence Mn colloids through reductive dissolution and complexation, with "aqueous" Mn (<450 nm, C:Mn = 15) release increasing by 56.3% from 0 to 200 h and colloidal Mn increasing by up to 31.9% (3-450 nm, C:Mn = 15, t = 200 h) compared to without carbon addition. Analysis of Mn oxidation state revealed that C-Mn colloids contained Mn in multiple oxidation states, and the percentage of Mn(II,III) relative to total Mn increased with increasing C concentrations. In surface water, the hydrodynamic diameter of both Mn and C-Mn colloids remained stable. In groundwater, C-Mn colloids (C:Mn = 3) remained stable (150 nm) over 30 days, while Mn colloids aggregated into larger particles. Analysis of natural surface and groundwaters identified a substantial fraction of Mn (up to 19.2 and 27.2%, respectively) existing in colloidal phases. These findings shed light on the intricate cycling of Mn among particulate, colloidal, and dissolved phases, which governs Mn fate and transport in the environment.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".