An Evaluative Screening Level Model of the Fate of Organic Chemicals in Sludge-Amended Soils Including Organic Matter Degradation
Bibliographic record
Abstract
The Biosolids-Amended Soil: Level IV (BASL4) evaluative screening level model of the fate of organic chemicals introduced to a two-layer soil in association with contaminated biosolids amendments is described. The model is intended for use in assessing the likely month-to-month and year-to-year fate and possible build-up of chemicals in sludge-amended soils in which there can be relatively rapid degradation of the organic matter (OM) present in the applied sludge. To accomplish this goal, processes of chemical degradation, inter-layer transport, volatilization, leaching, diffusion, sorbed phase transport due to bioturbation, and degradation of both fast and slow degrading OM present in the soil and amendment are quantified. Chemical can be introduced as pure compound or in biosolids; it may be applied to the surface layer of the soil or injected into a deeper layer of soil, and it may be ploughed into the surface and deeper layer. BASL4 was applied illustratively to three dissimilar chemicals: DDT, benzene, and phenol for a 12-month simulation period. Several simulations of DDT fate in different amended and unamended soil scenarios demonstrate the capabilities of the model. Degradation of OM is shown to significantly affect partitioning between solids, pore water, and pore air and hence the fate of the chemicals. A preliminary evaluation of the model is described by simulating three field and laboratory studies and the results are regarded as being in reasonable accord with observations. A sensitivity analysis is included with the objective of determining the relative importance of the various parameters describing chemical and soil properties. The model is a useful tool for evaluating the potential for soil contamination under conditions of OM degradation, for identifying the need for soil monitoring studies, and as a basis for estimating concentrations in soil-dwelling organisms.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".