Assessment of hydrological, geological, and biological parameters of a river basin impacted by old Hg mining in NW Spain
Bibliographic record
Abstract
Abstract Mercury (Hg) is a toxic metal that can cause adverse effects for the health of ecosystems. The Caudal River is one of the main rivers in the Asturias region (NW Spain), whose basin is highly anthropized, hosting several Hg mines, closed in the last century. Arsenic (As) is also found in the mineral paragenesis of the Hg deposits, posing a greater environmental risk. In the mining sites, remaining old facilities and tailings continue to release these elements into the environment. In this work, samples of fluvial sediments and water were taken, both in areas affected by anthropic activity and in pristine areas, in order to establish the background levels for the critical elements. The mineralogical study of the sediments, combined with EDS microanalysis, is useful to identify mineralogical traps such as Fe oxides or clays to retain the As. The As content in all sampled sediments is above the threshold effect levels (TEL), the possible effect range within which adverse effects occasionally occur, according to the Canadian Sediment Quality Guidelines for the Protection of Aquatic Life. This fact is related to a naturally high geochemical background in the basin, due to the existing mineral deposits. The PEL threshold (the probable effect range within which adverse effects frequently occur) is exceeded by more than an order of magnitude in the sediments downstream of the Hg mines. In these points, the As content in the water, exceeding 700 μg L−1 As, is also above the quality standard established in Spanish legislation. As a result, the Caudal River tributaries in the lower part of the basin do not reach a good ecological state, according to the Hydrological Planning Office, and in some cases their state is deficient, showing low richness and high dominance of macroinvertebrates. Although the concentrations decrease with distance from the source, these findings justify the low ecological quality of the affected watercourses.
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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 | 0.001 | 0.001 |
| 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) | 0.000 | 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".