Chemical and isotopic evidence for accelerated bacterial sulphate reduction in acid mining lakes after addition of organic carbon: laboratory batch experiments
Bibliographic record
Abstract
Acid mine drainage is a widespread environmental problem in Lusatia in the eastern part of Germany, where extensive brown coal and lignite mining was carried out during the last century. As a result of oxidation of pyrite in strip mine dumps of this region, numerous mine drainage lakes have pH values <3 and are characterized by high concentrations of dissolved sulphate and ferrous iron. Using chemical and isotopic techniques, we tested in laboratory bottle experiments the extent to which the addition of degradable organic carbon to acid lake water and sediments could stimulate bacterial (dissimilatory) sulphate reduction. The overall goal was to evaluate whether bacterial sulphate reduction, and subsequent formation of sedimentary sulphide minerals, could generate enough alkalinity to potentially neutralize the acid lakes in Lusatia. Pyruvate, glucose, succinic acid, lactate, ethanol, acetate, and various industrial by-products were added in various concentrations to original lake water and sediments in glass bottles and incubated between 4 and 12 weeks in darkness. The extent of bacterial sulphate reduction was determined by analyzing the concentrations and the isotopic compositions of sulphate in the water column, and the contents and δ34S values of various sedimentary sulphur compounds at the beginning and the end of the experiments. Bacterial sulphate reduction was significantly enhanced after addition of pure substances (lactate, pyruvate, acetate, and ethanol) resulting in elevated pH values (4.5 to 6.0) in the bottle water at the end of the experiments. Cheap industrial by-products (whey, molasses, Pfezi-granules, and Carbokalk) as organic carbon source were also shown to be effective in enhancing bacterial sulphate reduction, thereby increasing the pH value of the bottle water. In general, the addition of selected organic carbon compounds enhanced sufficiently bacterial sulphate reduction and the formation of sedimentary sulphur minerals, generating enough alkalinity for raising the pH of the bottle water to near-neutral values. Further research in enclosures and under field conditions is needed to determine whether this technique constitutes a feasible remediation strategy for the acid lakes in Lusatia.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".