Lake sediment grab sampling versus coring for environmental risk assessment of metal mining
Bibliographic record
Abstract
Current practices for baseline studies of sites to be developed for mining include surface grab sampling of sediments in aquatic receiving environments. In contrast, vertical sediment coring is a universal tool of paleolimnological research. This study evaluates the effectiveness of sediment grab sampling versus sediment coring for environmental risk assessment of metal mining. The former Aldermac mine (Cu, Zn, Au and Ag), 25 km west of Rouyn-Noranda in Abitibi, Quebec, operated from 1932-1943 and discharged acid mine drainage to the watershed downstream. The study site is representative of both a common mineral deposit and the legacy of historical mining practices. Contamination and adverse effects on aquatic habitats were demonstrated to the point where the government of Quebec led an environmental restoration of the Aldermac property (2008-11). Further mining development is foreseeable in the watershed. Surveys of sediment grab samples (2011-13) were done by Petite Ponar with a penetration depth of approximately 5-10 cm at 32 sites. Co-located sediment coring surveys were conducted using a 10-cm diameter gravity corer, modified with extension rods, to a sediment depth of 30-45 cm. Cores were sub-sampled at discrete depth intervals in two exercises: one survey with a larger regional distribution and thicker sediment slices (32 sites) and the other at 1-cm interval sections at 5 sites for detailed study. Grab sampling generated rapid results that permitted estimates of the current environmental reference state (baseline before new development), metal contaminant sources, and the spatial extent of metal contamination. Sediment coring produced estimates of naturally-occurring metal concentrations (pre-industrial background), the current baseline metal concentrations, metal contaminant sources, the duration of contamination, and its spatial extent. Although surveys of surface sediment grabs are faster and simpler and provide more sample material, they are imprecise snapshots without temporal scales. Sediment coring offers chronology of metal contaminant deposition, more precision, and potential for more targeted data (e.g., to fingerprint metal contaminant sources, assess diagenetic metal mobility, determine stability of metal-bearing phases). Cores can be taken in a reasonably rapid and simple manner, but less efficiently than grab sampling with less sample material for each core slice if sub-sampled at high resolution. Grab sampling offers a first approximation that may be sufficient for an initial environmental risk assessment. However, when further investigation is warranted, sediment coring can be optimized for efficiency and provide insight into accumulated metal contamination over time and an estimate of the range of metal levels in a naturally mineralized region (natural background).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".