Solid asset creation from a liquid liability : Is the Evaplant technology appropriate for BC and Alberta mine applications?
Bibliographic record
Abstract
Effective management of impacted mine water can be a challenge in active mining, and in-situ volume reduction may positively impact long-term liability. The Evaplant technology is a patented zero-discharge developed by Ramo system to manage leachates, effluents, and impacted mine waters using hybrid willow (Salix sp.) evapotranspiration. Development began in 2008; operations in 2018. Evaplant manages effluents at three landfills and one mine site in Quebec. Treatment of mine water will begin in spring 2024. Ramo is a company focused on the use of willow in afforestation and the management of environmental challenges through a circular economy approach. Willows have been successfully used to achieve reclamation, improvement of marginal land, and treatment of impacted waters originating from mines, landfills and wastewater treatment systems. The willow approach leads to a circular economy wherein the willows may then be regularly harvested and used for purposes as a biomass feedstock. Mine water volume reduction with Evaplant uses in situ evapotranspiration. Zero-discharge means that no liquid escapes the system. Applied to a tailings pond, tailings are stabilized, preventing windborne migration of fine particulate matter. Soil forms over time and can be accelerated with harvest and deposition of the woody mulch. Willows grow in response to optimal irrigation, capturing carbon through tree growth in below- and aboveground biomass. Biomass is harvested regularly and used as organic matter mulch in the mine reclamation process. Water transitions from liability to a woody biomass asset. Organic matter is a precious commodity leading almost universally to improved reclamation outcomes. Impacted mine water in BC generally consists of metals and trace elements, copper, molybdenum, and selenium being noteworthy. Evaplant removes water with resultant elemental mass balances proportionately distributed throughout tailings, soil, or in dilute biomass, remaining in-situ, or bound in organic matter. Evaplant requires a larger land base than engineered water treatment but is cost effective by comparison. Mining case studies from Northern Quebec will be contrasted with modelled water scenarios for the Southern Interior and the Cariboo to demonstrate the transition from liability to asset. The model considers factors that the Evaplant process evaluates through feasibility, including initial water quality, cost of treatment, climate, and soil types, which may limit the amount of water that may be managed per unit area. Modelling local situations will contextualize the decision between treating impacted mine water as an asset, versus a liability.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".