Mass Transfer Limitation during Slow Anaerobic Biodegradation of 2-Methylnaphthalene
Bibliographic record
Abstract
Abstract While they are theoretically conceptualized to restrict biodegradation of organic contaminants, bioavailability limitations are challenging to observe directly. Here we explore the onset of mass transfer limitations during slow biodegradation of the polycyclic aromatic hydrocarbon 2-methylnaphthalene (2-MN) by the anaerobic, sulfate-reducing strain NaphS2. Carbon and hydrogen compound specific isotope fractionation was pronounced at high aqueous 2-MN concentrations (60 μM) (εcarbon = −2.1 ± 0.1‰/εhydrogen = −40 ± 7‰) in the absence of an oil phase but became significantly smaller (εcarbon = −0.9 ± 0.3‰/εhydrogen = −6 ± 3‰) or nondetectable when low aqueous concentrations (4 μM versus 0.5 μM) were in equilibrium with 80 or 10 mM 2-MN in hexadecane, respectively. This masking of isotope fractionation directly evidenced mass transfer limitations at (sub)micromolar substrate concentrations. Remarkably, oil–water mass transfer coefficients were 60–90 times greater in biotic experiments than in the absence of bacteria (korg-aq2-MN = 0.01 ± 0.003 cm h–1). The ability of isotope fractionation to identify mass transfer limitations may help study how microorganisms adapt and navigate at the brink of bioavailability at low concentrations. For field surveys our results imply that, at trace concentrations, the absence of isotope fractionation does not necessarily indicate the absence of biodegradation.
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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 | 0.000 | 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) | 0.002 | 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".