Decadal Delays in Groundwater Recovery from Nitrate Contamination Caused by Low O<sub>2</sub> Reduction Rates
Bibliographic record
Abstract
Abstract Nitrate (NO ) is one of the main pollutants in agriculturally impacted groundwater systems. The availability and reactivity of electron donors control the prevalent redox conditions in aquifers and past nitrate contamination of groundwater can be ameliorated if denitrification occurs. Using aqueous geochemistry data and the stable isotope composition of dissolved nitrate ( δ 15 N and δ 18 O), we found that nitrate concentrations above the World Health Organization drinking water guideline were caused predominantly by manure and to a lesser extent by synthetic fertilizer applications and that denitrification was not a significant nitrate removal process in an aquifer in southern Germany underlying agricultural land with intensive hog farming. We also applied environmental isotopes ( δ 2 H and δ 18 O, 3 H/ 3 He, and 14 C) linked with a lumped parameter approach to determine apparent mean transit times (MTT) of groundwater that ranged from <5 years to >100 years. Furthermore, we determined low reduction rates of dissolved oxygen (O 2 ) of 0.015 1/year for first‐order kinetics. By extrapolating the O 2 reduction rates beyond the apparent MTT ranges of sampled groundwater, denitrification lag times (time prior to commencement of denitrification) of approximately 114 years were determined. This suggests that it will take many decades to significantly reduce nitrate concentrations in the porous aquifer via denitrification, even if future nitrate inputs were significantly reduced.
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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 | 0.001 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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; both teacher heads agree on what is shown here.
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".