Trace Metals in Groundwater and Vadose Zone Calcite: In Situ Containment and Stabilization of Stronthium-90 and Other Divalent Metals and Radionuclides at Arid Western DOE Sites: Final Report for Award Number DE-FG07-02ER63486 to the University of Idaho (RW Smith) Environmental Management Science Program Project Number 87016
Bibliographic record
Abstract
Radionuclide and metal contaminants are present in the vadose zone and groundwater throughout the U.S. Department of Energy (DOE) energy research and weapons complex. In situ containment and stabilization of these contaminants represents a cost-effective treatment strategy that minimizes workers’ exposure to hazardous substances, does not require removal or transport of contaminants, and generally does not generate a secondary waste stream. We have investigated an in situ bioremediation approach that immobilizes radionuclides or contaminant metals (e.g., strontium-90) by their microbially facilitated co-precipitation with calcium carbonate in groundwater and vadose zone systems. Calcite, a common mineral in many aquifers and vadose zones in the arid west, can incorporate divalent metals such as strontium, cadmium, lead, and cobalt into its crystal structure by the formation of a solid solution. Collaborative research undertaken by the Idaho National Laboratory (INL), University of Idaho, and University of Toronto as part of this Environmental Management Science Program project has focused on in situ microbially-catalyzed urea hydrolysis, which results in an increase in pH, carbonate alkalinity, ammonium, calcite precipitation, and co-precipitation of divalent cations. In calcite-saturated aquifers, microbially facilitated co-precipitation with calcium carbonate represents a potential long-term contaminant sequestration mechanism. Key results of the project include: **Demonstrating the linkage between urea hydrolysis and calcite precipitation in field and laboratory experiments **Observing strontium incorporation into calcite precipitate by urea hydrolyzers with higher distribution coefficient than in abiotic **Developing and applying molecular methods for characterizing microbial urease activity in groundwater including a quantitative PCR method for enumerating ureolytic bacteria **Applying the suite of developed molecular methods to assess the feasibility of the proposed bioremediation technique at a contaminated site located within the 100-N area of the Hanford, Washington site **Assessing the role of nitrification on the persistence of precipitated calcite by modifying primers for identification of the amoA gene region of various ammonia oxidizing bacteria (AOB) for characterizing AOB in the field
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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) | 0.001 | 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".