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Record W2027187166 · doi:10.1144/1467-7873/05-099

The role of smelter emissions and element remobilization in the sediment chemistry of 99 lakes around the Horne smelter, Quebec

2006· article· en· W2027187166 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueGeochemistry Exploration Environment Analysis · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicHeavy metals in environment
Canadian institutionsUniversity of OttawaGeological Survey of CanadaUniversity of Victoria
Fundersnot available
KeywordsSmeltingSedimentEnvironmental chemistryEnvironmental scienceChemistryMetallurgyGeologyMaterials scienceGeomorphology

Abstract

fetched live from OpenAlex

Ninety-nine lakes were sampled at varying distances up to 75 km from the Horne smelter at Rouyn-Noranda, Quebec, to study the influence of the smelter versus other factors on metal concentrations in lake sediments. Most of these lakes lie within the Abitibi Greenstone Belt, a zone of extensive base metal and gold mineralization and the focus of a mining and smelting economy for almost a century. Lake sediment cores, c . 25 cm long, were collected and sampled at the top (0–2 cm) and the bottom (18–20 cm) to capture sediment that was deposited after the smelter was in operation (‘post-industrial’) and well before the mining and smelting activity was started (‘pre-industrial’). Additionally, nine cores were sampled in 1 cm increments to depths of up to 50 cm to study temporal patterns and potential element remobilization in detail. The cores were analysed for an extensive suite of elements. This paper focuses on those elements that are emitted by the smelter for which there are records of emissions through time, namely As, Cd, Cu, Pb and Zn. A spatial statistical approach – a logistic model of metal content versus distance from the smelter – was used investigate the relationship of sediment chemistry with smelter emissions and other possible influences. Using Cu as a representative proxy for the other emitted metals, this analysis demonstrates that elements are enriched in lake sediments by a factor of about three times around the smelter, that the impact of the smelter is detectable in lakes to a distance of at least 50 km, and that there is no obvious association between sediment Cu concentration and bedrock geology, land-use, lake pH, or lake morphometry (lake area/lake catchment area). The nine lakes studied in detail show enrichment towards the sediment–water interface (SWI) and relatively steady concentrations below depths of c . 10 cm. However, depth profiles do not match changes in the magnitude of smelter emissions through time, nor do they match changes in emission chemistry (element ratios) through time. Element ratios do generally move towards the chemistry of the emissions, suggesting smelter influence, but do not do so predictably. For example, (i) trends in the Cu/Pb ratio continue to the very bottom of cores into material deposited hundreds of years before industrialization, and (ii) proximity to the smelter does not lead to greater similarity between sediment and emission chemistry. These results suggest that significant element remobilization is occurring and that it differs from lake to lake and from element to element. We conclude that lakes within 50 km of the smelter have elevated metal concentrations in their near-surface sediments due to stack emissions but, due to element cycling and mobility, it is difficult to quantitatively determine the magnitude of metal increase attributable to the smelter. We also suggest that due to upward remobilization, the duration of industrial metal enrichments in surface sediments (the residence time) may be increased, thereby making surface enrichments more persistent than would be predicted by the sedimentation rate.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.127
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.006
GPT teacher head0.205
Teacher spread0.199 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it