Transport and fate of estrogens from swine manure in a biochar amended sandy soil in a freeze-thaw environment
Bibliographic record
Abstract
Under growing concerns of their possible adverse effects on ecosystems, natural steroidal sex hormones, originating from liquid swine manure, have been detected at trace concentrations in a number of natural environments. Various studies have highlighted biochar’s potential in adsorbing such hormones, given its structural and physiochemical properties. The remaining hormone adsorption capacity of a 1% slow pyrolysis biochar topsoil amendment was tested after one year of its application to a sandy soil, housed in outdoor lysimeters irrigated with simulated rainfall. The fate and transport of estrogens, over a 46-day period following the incorporation of liquid swine manure (4 g N/L @ 16 L/m2) into the topsoil, was monitored in biochar-amended and non-amended lysimeters. While in the first year of biochar application, a significant spatial-temporal stratification of steroidal sex hormones had been observed in the biochar-amended soil (vs. non-amended soil), in the second year biochar absorbed hormones to a considerably lesser degree. Concurring with the findings of laboratory batch adsorption experiments on fresh and used biochar, the present study showed that 1% slow pyrolysis biochar`s capacity to absorb sex hormones (estrogens) released from liquid swine manure in sandy soil decreases during second year. This is presumably the freezing and thawing weather conditions of experimental site that resulted in biochar surface degradation leading to the release of soluble organic carbon, thereby facilitating a heightened mobility of hormones and their resultant leaching to lower depths in the soil profile.
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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) | 0.000 | 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".