Evidence of transboundary mercury and other pollutants in the Puyango-Tumbes River basin, Ecuador–Peru
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In Portovelo in southern Ecuador, 87 gold processing centers along the Puyango-Tumbes River produce an estimated 6 tonnes of gold per annum using a combination of mercury amalgamation and/or cyanidation and processing poly-metallic ores. We analysed total Hg, Hg isotopes, total arsenic, cadmium, copper, lead and zinc in water and sediment along the Puyango in 2012-2014. The highest total mercury (THg) concentrations in sediments were found within a 40 km stretch downriver from the processing plants, with levels varying between 0.78-30.8 mg kg-1 during the dry season and 1.80-70.7 mg kg-1 during the wet season, with most concentrations above the CCME (Canadian Council of Ministers of the Environment) Probable Effect Level (PEL) of 0.5 mg kg-1. Data from mercury isotopic analyses support the conclusion that mercury use during gold processing in Portovelo is the source of Hg pollution found downstream in the Tumbes Delta in Peru, 160 km away. The majority of the water and sediment samples collected from the Puyango-Tumbes River had elevated concentrations of, arsenic, cadmium, copper, lead and zinc exceeding the CCME thresholds for the Protection of Aquatic Life. At monitoring points immediately below the processing plants, total dissolved concentrations of these metals exceeded the thresholds by 156-3567 times in surface waters and by 19-740 times in sediment. The results illustrate a significant transboundary pollution problem involving Hg and other toxic metals, amplified by the fact that the Puyango-Tumbes River is the only available water source in the semi-arid region of northern Peru.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.007 |
| Scholarly communication | 0.000 | 0.002 |
| 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 it