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Record W3134606421

Distribution of mercury species and mercury isotope ratios in soils and river suspended matter of a mercury mining area

2018· article· en· W3134606421 on OpenAlexaff
Carluvy Baptista‐Salazar, Holger Hintelmann, Harald Biester

Bibliographic record

VenueEGU General Assembly Conference Abstracts · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicMercury impact and mitigation studies
Canadian institutionsTrent University
Fundersnot available
KeywordsCinnabarMercury (programming language)Soil waterEnvironmental chemistryOrganic matterTributarySedimentChemistryIsotopeStable isotope ratioEnvironmental scienceMineralogyGeologyHydrology (agriculture)Soil science
DOInot available

Abstract

fetched live from OpenAlex

Mercury (Hg) released by mining activities can be dispersed in the environment, where it is subject to species transformations. Hg isotope ratios have been used to track sources in Hg contaminated areas, although it is unclear to what extent variations in δ-values are attributed to distinct Hg species. Hg was mined as Hg sulphide (cinnabar) in Idrija, Slovenia for centuries. Sediments are loaded with mining-residues (cinnabar and calcine), whereas contaminated soils mainly contain Hg bound to natural organic matter (NOM-Hg) related to atmospheric Hg deposition. Hg released from soils and sediments is transported as suspended matter (SM) in the Idrijca river to the Gulf of Trieste (GT), Italy. We determine Hg isotope ratios in river SM, sediments and soils from the Idrijca-catchment to decipher the Hg isotope ratio variability related to Hg species distribution in different grain-size fractions. δ202Hg values of SM collected from tributaries corresponded to those found in soils ranging from −2.58 to 0.19‰ and from −2.27 to −0.88‰, respectively. Speciation measurements reveal that fine fractions (0.45–20 μm) are dominated by NOM-Hg, while larger fractions contain more cinnabar. More negative δ202Hg values were related to higher proportions of NOM-Hg, which are predominant in soils and SM. Rain events increase SM-loads in the river, mainly due to resuspension of coarse grain-size fractions of bottom sediments bearing larger proportions of cinnabar, which leads to more positive δ202Hg values. The large magnitude of variation in δ202Hg and the smaller magnitude of variation in Δ199Hg (−0.37 to 0.09‰) are likely related to fractionation during ore roasting. Soil samples with high NOM-Hg content show more negative δ202Hg values and larger variation of Δ199Hg. More negative δ202Hg values in GT sediments were rather linked to distant sedimentation of soil derived NOM-Hg than to sedimentation of autochthonous marine material. Heterogeneity in the Idrija ore and ore processing likely produce large variations in the Hg isotopic composition of cinnabar and released metallic Hg, which complicate the differentiation of Hg sources. Combining Hg isotope measurements with solid phase Hg speciation reveals that Hg isotope ratios rather indicate different Hg species and are not necessarily symptomatic for Hg pollution sources.

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How this classification was reachedexpand

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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.477
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.031
GPT teacher head0.261
Teacher spread0.231 · 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 teacher head, not a consensus.

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".

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Citations0
Published2018
Admission routes1
Has abstractyes

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