A Method for Predicting Chloride Concentrations in Leachate at Natural Attenuation Landfills in the Precambrian Shield Regions of Ontario, Canada
Bibliographic record
Abstract
Abstract Natural attenuation landfill sites continue to be the preferred method of domestic waste disposal in the Precambrian Shield regions of Ontario due to economic factors. The main challenge in siting these landfills is ensuring that there will be no adverse impact on off‐site water resources. Impact risk assessments are generally based on estimated volumes and strengths of chloride in the leachate. While volumes can be estimated using simple water balances, peak chloride concentration predictions are based on judgment and are quite variable. Since design chloride strengths dictate the size of the required attenuation zone, overestimating concentrations will typically make it impossible to find a suitable site, while underestimating concentrations increases the potential for adverse off‐site impacts occurring. Hydrogeological data from active and closed landfills in the Precambrian Shield region were collected to help develop a reliable method of predicting peak chloride concentrations in leachate. This study focused on 21 sites located on relatively permeable sandy soils since landfills underlain by low permeability clayey soils retain leachate similar to lined facilities. Linear regression analyses were conducted to determine if source chloride concentrations at the “sand” sites are significantly influenced by waste thickness, fill area, waste volume, waste deposition rate, hydraulic conductivity, upgradient flow length, depth to the water table, and moisture surplus. A strong relationship (R = 0.957) was found to exist between source chloride concentrations and waste volume. This empirical volume versus chloride regression equation can be used as the basis for establishing design chloride concentrations at new natural attenuation landfills developed over sandy soils in the Precambrian Shield regions of Ontario. An alternative risk assessment approach is required for sites developed over clay soils.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".