Effects of swine manure biochar on sorption equilibrium of cadmium and zinc in sandy soils
Bibliographic record
Abstract
Swine manure is an agricultural waste that can increase soil fertility. However, this residue has a high content of heavy metals, particularly zinc (Zn) and cadmium (Cd), that are not only toxic to plants and soil organisms but they also pose a great threat to human health due to the potential accumulation of these metals through the food chain. Transforming swine manure into biochar and adding it to soils can improve the soil’s capacity to retain heavy metals. The main objective of this research was to study the capacity of sandy soils mixed with different doses of swine manure biochar (SMB) to retain Cd and Zn as well as to evaluate the sorption equilibrium of these metals. Sorption essays were performed by adding solutions of Zn (ZnCl2) or Cd (CdCl2) at different concentrations (0, 2.5, 5, 10, 50 and 100 mg L-1) to soil samples mixed with different doses of SMB (0, 0.25, 0.75, 1.5, and 3.0 % (w/w)). The data were modelled using both Langmuir and Freundlich adsorption isotherm models to describe the adsorption processes. The data were best represented by the Langmuir model (R2>0.97), indicating a mono-layer sorption to the surface. Results showed that sorption capacity of Zn and Cd increased with the dose of SMB, improving metal retention. The Langmuir constant (KL) for soil without SMB for Cd and Zn were 0.01 L mg-1 and 0.05 L mg-1, respectively. With the highest dose of SMB, KL increased to 9.86 L mg-1 and 1.26 L mg-1 for Cd and Zn, respectively. Results suggest that SMB has the potential to mitigate Zn and Cd contamination of sandy soils.
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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 | 0.000 | 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 teacher head, 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".