Testing Silica-Encapsulated DNA Molecules with Iron Nanocore as a Groundwater Tracer in Fractured Silurian Dolostone Bedrock
Notice bibliographique
Résumé
DNA-based tracers have recently been used as groundwater tracers, primarily in granular aquifer media. Given the possibility of simultaneously applying and distinguishing multiple tracers with distinct DNA labels, they offer unique opportunities for tracing distinct pathways between injection and arrival points. They are synthesised by adsorbing DNA molecules on a silica or magnetite nanocore and encapsulated with a silica layer to protect the molecule against extreme temperatures, pH, and microbial attack. These nanotracers can be exponentially amplified, pushing the detection sensitivity down to one molecule, thus helping to mitigate the narrower detection range associated with conventional solutes. However, when co-injected, both tracers are expected to follow the same preferential flow paths in a connected fracture network but with distinct travel times. While solute tracers are attenuated by diffusion into the matrix enhanced by sorption, the nanotracer mobility is dominated by advective transport enhanced by size exclusion. Considering the uncertainty in the nanotracer mobility, especially in bedrock aquifers, pairing these tracers provides complementary insight into the nature and variability of the fracture pathways and rates.In this study, we co-injected a novel DNA-based nanotracer with magnetite nanocore (acronym: SiDNAMag) and Uranine in a Silurian dolostone aquifer under controlled natural gradient flow conditions to characterise fracture connectivity, groundwater velocities and diffusion process influences. The experiment was conducted at a toluene-contaminated site in Guelph, Canada, where depth-discrete multilevel systems (MLSs) were installed for 3D monitoring, improving insights on spatial variability in tracer transport. The tracer solution was injected at 0.5 L/min over a 1.6 m vertical interval, isolated with straddle packers in an upgradient well 10.5 m from the modestly pumped (0.11 L/min) extraction well and monitored from 15 MLSs comprising 82 ports. Using temporal moment analysis, we compared the transport of SiDNAMag to Uranine and observed the preferential flow geometries through the fractured dolostone aquifer. SiDNAMag showed an earlier breakthrough (2.25 h) compared to Uranine (6.25 h) at the extraction well with higher average velocity. 2.5% of Uranine mass was recovered, while SiDNAMag recovery was unquantifiable due to intermittent detection in the extraction well. SiDNAMag was predominantly detected at depths below the injection interval compared to Uranine, suggesting an influence of density on particle mobility. Preferential pathways also exist in the zone above the injection interval, evidenced by early detection of Uranine in the shallow ports of MLSs between the injection and extraction wells.These findings enhance our understanding of fracture connectivity and the delineation of dominant flow pathways in the dolostone aquifer. They also provide insights into the variability of discrete fracture pathways within the 3D field domain, supporting the generation of fracture networks that accurately represent field conditions. Using HydroGeosphere, a discrete fracture matrix (DFM) numerical flow and transport model, these networks can be used to evaluate remediation strategies effectively. Although this study reveals SiDNAMag as a promising tool for groundwater tracing in fractured dolostone aquifers, a critical aspect of understanding its transport behaviour lies in examining the effects of groundwater chemistry and aquifer mineralogy on SiDNAMag.
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 | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 ».