Electrolytic Methanogenic−Methanotrophic Coupling for Tetrachloroethylene Bioremediation: Proof of Concept
Bibliographic record
Abstract
Coupling of methanogenic and methanotrophic catabolisms was performed in a single-stage technology equipped with a water electrolysis cell placed in the effluent recirculation loop. The electrolysis-generated hydrogen served as an electron donor for both bicarbonate reduction into CH4 and reductive dechlorination, while the O2 and CH4, supported the cometabolic oxidation of chlorinated intermediates left over by the tetrachloroethylene (PCE) transformation. The electrolytical methanogenic/methanotrophic coupled (eMaMoC) process was tested in a laboratory-scale setup at PCE loads ranging from 5 to 50 micromol/L(rx) x d (inlet concentrations from 4 to 11 mg/L), and at various hydraulic residence times (HRT). Degradation followed essentially a reductive dechlorination pathway from PCE to cis-1,2-dichloroethene (DCE), and an oxidative pathway from DCE to CO2. PCE reductive dechlorination to DCE was consistently over 98% while a maximum oxidative DCE mineralization of 89% was obtained at a load of 4.3 micromol PCE/ L(rx) x d and an HRT of 6 days. Controlling dissolved oxygen concentrations within a relatively low range (2-3 mg/L) seemed instrumental to sustain the overall degradation capacity. Degradation kinetics were further evaluated: the apparent half-saturation constant (K(s)) had to be set relatively high (29 microM) for the simulated data to best fit the experimental ones. In spite of such kinetic limitations, the eMaMoC system, while fueled by water electrolysis, was effective in building and sustaining a functional methanogenic/methanotrophic consortium capable of significant PCE mineralization in a single-stage process. Hence, degradation standards are within reach so long as the methanotrophic DCE-oxidizing potential, including substrate affinity, are optimized and HRT accordingly adjusted.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".