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Record W3160001808 · doi:10.5194/egusphere-egu21-1381

Geochemical perspectives from the past: understanding the natural enrichment of Cd in pre-industrial and pre-anthropogenic aerosols using polar ice and peat cores from remote locations

2021· article· en· W3160001808 on OpenAlexaffabout
Fiorella Barraza, James Zheng, Michael Krachler, Chad W. Cuss, Andrii Oleksandrenko, Iain Grant‐Weaver, William Shotyk

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnvironmental Science
TopicHeavy metals in environment
Canadian institutionsUniversity of OttawaGeological Survey of CanadaUniversity of Alberta
Fundersnot available
KeywordsPeatOmbrotrophicBogEnvironmental chemistryCadmiumSmeltingAerosolEnvironmental scienceChemistryGeographyArchaeology

Abstract

fetched live from OpenAlex

Cadmium (Cd) is a potentially toxic chalcophile element with profound health consequences when organisms are exposed to elevated concentrations. Cadmium is emitted to the atmosphere through various industrial processes (metallurgical smelting, coal combustion), but it is also derived from natural sources (volcanic emissions, wind-borne soil particles). In contemporary air samples collected within urban areas across the globe, Cd enrichment factors (EF) relative to the Upper Continental Crust (UCC) are often up to 100, and are typically interpreted as reflecting inputs exclusively from anthropogenic activities. This presentation reports on the range of Cd EF values in aerosol archives from various locations representing up to 15,500 years of atmospheric Cd deposition, including: (i) Polar ice collected at Devon Island (Nunavut, Canada), and; (ii) Peat from ombrotrophic bogs collected at Etang de la Gruère (Jura Mountains, Switzerland), Birch Mountain (BMW) and Caribou Mountain Wildlands (CMW) (Alberta, Canada), and Drizzle Bog (DB) (British Columbia, Canada). The ice samples were melted and acidified, and the peat samples digested, with double sub-boiled concentrated nitric acid, analyzed using SF-ICP-MS and ICP-QMS, respectively. All analyses were undertaken in metal-free, ultraclean laboratories. Age-dating of ice was obtained using electrical conductivity and oxygen isotopes, and the peat samples with conventional 14C AMS and 210Pb. Cadmium concentrations were normalized to the conservative lithophile reference elements (Sc, Ti, and Th) to calculate the EF. Regardless of the reference element and the compilation selected for the UCC, the EF in old and ancient samples was often very high: up to 4000 in ice and up to 400 in peat bogs. These profound enrichments of Cd and dramatic variation pre-dating anthropogenic activities suggest that either natural emissions of Cd were not constant, or that non-crustal sources of Cd have been underestimated. In the ice cores, the period with the lowest and most constant Cd concentrations was found between 2,500 and 4,500 years BP (0.92 ± 0.13 pg g-1), with an average EFSc of 107. Samples from the early and middle Holocene (4,500 to 12,000 years BP) contained higher concentrations of Cd (2.43±0.50 pg g-1), with an average EFSc of 255. In the Swiss bog, the Cd EFTh ranged from 9 to 800, and was more stable in the period between 9,000 to 11,000 years BP (14±5). In the pre-industrial layers of peat bogs from remote locations in Canada, the EFTh values averaged 30 (DB), 54 (BMW) and 167 (CMW). These variations in Cd enrichment levels likely reflect differences in contributions from natural sources: volcanic activity, deposition of fine airborne soil particles, and natural forest fires. The biological uptake and recycling of Cd observed in some terrestrial plants and corresponding enrichment in humus may also play a role, but these potential contributions have received limited attention. The very high EF found in contemporary aerosols, recent peat layers and modern snow samples should be interpreted with caution pending improved understanding of the sources of natural aerosol Cd enrichments, and associated processes.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.027
Threshold uncertainty score0.054

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
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 head0.038
GPT teacher head0.275
Teacher spread0.236 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2021
Admission routes2
Has abstractyes

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