Microplastic-induced alterations in water flow and solute transport dynamics in soil
Bibliographic record
Abstract
The growing use of plastic-based practices in agriculture has led to a significant accumulation of plastic waste in soil. Microplastics (MPs) increasingly threaten soil health and fertility by disrupting its physical and chemical environment, and impairing essential ecological functions. We conducted laboratory column measurements combined with microfluidic experiments to assess the effects of MPs on water flow and solute transport in soil, key processes for sustaining soil water and nutrient availability and thus crop growth and yield. Changes in hydraulic conductivity and solute breakthrough curves in sandy soils were investigated in the presence of varying concentrations of polyethylene (PE) and polyvinylchloride (PVC) microplastics. Alterations in pore structure and clogging of pore throats by MPs, as further evidenced through confocal and fluorescence microscopy of synthesized porous media, led to 39% and 74% reductions in hydraulic conductivity of sand samples containing 5% PVC and 5% PE, respectively. Solute transport experiments using a brine tracer revealed broader breakthrough curves in the presence of MPs. Overall, the enhancement of pore-scale flow heterogeneity driven by the development of preferential flow paths and the formation of low-permeability zones increased hydrodynamic dispersion and resulted in both early breakthrough and delayed transport of the tracer within the soil column.
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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".