Sr isotope analysis of water samples at the Radiogenic Isotope Laboratory of the Istituto Nazionale di Geofisica e Vulcanologia, Sezione di Napoli - Osservatorio Vesuviano (INGV-OV)
Notice bibliographique
Résumé
Since 2000, a Thermal Ionisation Mass Spectrometer (Thermo ScientificTM Triton TI® Mass Spectrometer) and a clean laboratory are operating at the Istituto Nazionale di Geofisica e Vulcanologia (INGV), Sezione di Napoli, Osservatorio Vesuviano (OV) to measure strontium (Sr) and neodymium (Nd) isotope compositions of volcanic products for scientific purposes. In 2014 particular attention has been dedicated to set up the analytical procedure for extracting Sr and Nd and measuring their isotope compositions from groundwater and mineral water, due to its growing interest on environmental topics. Strontium is considered a trace element and Sr2+ preferentially substitutes for Ca2+ in most rock types since it geochemically behaves like calcium. Groundwater is enriched in Sr during water-rock interaction processes occurring within the saturated and/or unsaturated zones. Conversely, Sr is removed from water as a result of mineral precipitation and ion exchange reactions. The most common removal process is the coprecipitation of Sr2+ ions with calcium carbonate. However, this latter process does not fractionate Sr2+ [Faure and Powell, 1972]. Therefore, the Sr isotopic composition of groundwater records an integrated signal of water-rock interaction along flow path and dissolution/precipitation events, and can be used as a dynamic tracer to constrain subsurface flow in volcanic, non volcanic and geothermal areas. Water is a natural resource, which is renewed by different processes. The aforementioned geochemical processes and reactions with dissolving/precipitating minerals have a profound effect on water quality. Since the 1990s, Sr isotopes have been extensively used as a natural tracer of groundwater flow [Peterman and Stuckless, 1992; Bullen et al., 1996; Johnson and De Paolo, 1994; McNutt et al., 1990; McNutt, 2000; Frost et al., 2002; Gosselin et al., 2004; Klaus et al., 2007] because groundwater progressively acquires the 87Sr /86Sr isotopic ratio from the rocks with which it has interacted [Prasanna et al. 2009]. Furthermore, variable Sr isotope ratios and concentrations characterize different groundwater sources and are tracers of groundwater mixing [eg. Carucci et al., 2012]. In this work we present the first results obtained by analyzing the Sr isotope composition of two mineral waters, selected groundwater samples from Mt. Etna and a certified water sample from North America (National Research Council Canada - NRC, Certified Reference Materials - CRM TM-25.4). On the contrary, the Nd isotope ratios of such water samples have been not measured due to the low Nd content of the investigated samples. A statistically representative data set on certified international standards (NIST SRM 987, La Jolla and JNdi-1) was used to evaluate the quality of the analytical data produced at the INGVOV Radiogenic Isotope Laboratory since 2014. This methodological approach will allow us to isotopically characterize different water systems with the aim to trace back the water-rock interaction and mixing processes in different environments. This analytical procedure could be exported to other geological contests and applied to other types of waters (e.g. surface and thermal water).
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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) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,001 |
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 ».