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Record W2889313189 · doi:10.1021/acs.est.8b02027

Chemical Forms of Mercury in Pyrite: Implications for Predicting Mercury Releases in Acid Mine Drainage Settings

2018· article· en· W2889313189 on OpenAlexaff
Alain Manceau, Margarita Merkulova, Magdalena Murdzek, Valentina Batanova, Rafał Baran, Pieter Glatzel, Binoy K. Saikia, Doğan Paktunç, Liliana Lefticariu

Bibliographic record

VenueEnvironmental Science & Technology · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicMercury impact and mitigation studies
Canadian institutionsNatural Resources Canada
FundersAgence Nationale de la Recherche
KeywordsPyriteMercury (programming language)MarcasiteAcid mine drainageSulfurSulfide mineralsSulfideEnvironmental chemistryChemistryMineralogyGeologyCoalGeochemistrySphalerite

Abstract

fetched live from OpenAlex

Pyrite (cubic FeS2) is the most abundant metal sulfide in nature and also the main host mineral of toxic mercury (Hg). Release of mercury in acid mine drainage resulting from the oxidative dissolution of pyrite in coal and ore and rock resulting from mining, processing, waste management, reclamation, and large construction activities is an ongoing environmental challenge. The fate of mercury depends on its chemical forms at the point source, which in turn depends on how it occurs in pyrite. Here, we show that pyrite in coal, sedimentary rocks, and hydrothermal ore deposits can host varying structural forms of Hg which can be identified with high energy-resolution XANES (HR-XANES) spectroscopy. Nominally divalent Hg is incorporated at the Fe site in pyrite from coal and at a marcasite-type Fe site in pyrite from sedimentary rocks. Distinction of the two Hg bonding environments offers a mean to detect microscopic marcasite inclusions (orthorhombic FeS2) in bulk pyrite. In epigenetic pyrite from Carlin-type Au deposit, up to 55 ± 6 at. % of the total Hg occurs as metacinnabar nanoparticles (β-HgSNP), with the remainder being substitutional at the Fe site. Pyritic mercury from Idrija-type Hg deposit (α-HgS ore) is partly divalent and substitutional and partly reduced into elemental form (liquid). Divalent mercury ions, mercury sulfide nanoparticles, and elemental mercury released by the oxidation of pyrite in acid mine drainage settings would have different environmental pathways. Our results could find important applications for designing control strategies of mercury released to land and water in mine-impacted watersheds.

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 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 categoriesScience and technology studies
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 score0.095
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.005
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.009
GPT teacher head0.262
Teacher spread0.253 · 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 designBench or experimental
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

Citations59
Published2018
Admission routes1
Has abstractyes

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