Arsenic species in weathering mine tailings and biogenic solids at the Lava Cap Mine Superfund Site, Nevada City, CA
Notice bibliographique
Résumé
BACKGROUND: A realistic estimation of the health risk of human exposure to solid-phase arsenic (As) derived from historic mining operations is a major challenge to redevelopment of California's famed "Mother Lode" region. Arsenic, a known carcinogen, occurs in multiple solid forms that vary in bioaccessibility. X-ray absorption fine-structure spectroscopy (XAFS) was used to identify and quantify the forms of As in mine wastes and biogenic solids at the Lava Cap Mine Superfund (LCMS) site, a historic "Mother Lode" gold mine. Principal component analysis (PCA) was used to assess variance within water chemistry, solids chemistry, and XAFS spectral datasets. Linear combination, least-squares fits constrained in part by PCA results were then used to quantify arsenic speciation in XAFS spectra of tailings and biogenic solids. RESULTS: The highest dissolved arsenic concentrations were found in Lost Lake porewater and in a groundwater-fed pond in the tailings deposition area. Iron, dissolved oxygen, alkalinity, specific conductivity, and As were the major variables in the water chemistry PCA. Arsenic was, on average, 14 times more concentrated in biologically-produced iron (hydr)oxide than in mine tailings. Phosphorous, manganese, calcium, aluminum, and As were the major variables in the solids chemistry PCA. Linear combination fits to XAFS spectra indicate that arsenopyrite (FeAsS), the dominant form of As in ore material, remains abundant (average: 65%) in minimally-weathered ore samples and water-saturated tailings at the bottom of Lost Lake. However, tailings that underwent drying and wetting cycles contain an average of only 30% arsenopyrite. The predominant products of arsenopyrite weathering were identified by XAFS to be As-bearing Fe (hydr)oxide and arseniosiderite (Ca2Fe(AsO4)3O3•3H2O). Existence of the former species is not in question, but the presence of the latter species was not confirmed by additional measurements, so its identification is less certain. The linear combination, least-squares fits totals of several samples deviate by more than ± 20% from 100%, suggesting that additional phases may be present that were not identified or evaluated in this study. CONCLUSIONS: Sub- to anoxic conditions minimize dissolution of arsenopyrite at the LCMS site, but may accelerate the dissolution of As-bearing secondary iron phases such as Fe3+-oxyhydroxides and arseniosiderite, if sufficient organic matter is present to spur anaerobic microbial activity. Oxidizing, dry conditions favor the stabilization of secondary phases, while promoting oxidative breakdown of the primary sulfides. The stability of both primary and secondary As phases is likely to be at a minimum under cyclic wet-dry conditions. Biogenic iron (hydr)oxide flocs can sequester significant amounts of arsenic; this property may be useful for treatment of perpetual sources of As such as mine adit water, but the fate of As associated with natural accumulations of floc material needs to be assessed.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».