Investigating the deposition behavior of different polystyrene nanoplastics onto mineral surfaces using QCM-D
Notice bibliographique
Résumé
Nanoplastic, as primary or secondary plastics, emerges as a contaminant across all environmental compartments. In terrestrial settings, the vadose zone is considered a plastic sink. Yet, leaching into deeper saturated subsurface areas and groundwater may occur via preferential flow paths, changing hydro-chemical conditions, or direct infiltration in low lying or recharge areas. Understanding transport and deposition behavior of nanoplastics in aquifer settings is crucial as it i) is expected to deviate from that of engineered nanoparticles (ENPs) due to its more complex physical and chemical properties, and ii) to be able to develop and inform numerical models to upscale nanoplastic contaminant transport when e.g., exploring groundwater resources. Quartz-crystal microbalance with dissipation monitoring (QCM-D) was used to investigate the deposition behavior of various model polystyrene nanoparticles onto two of the most abundant mineral species on Earth: quartz and kaolinite under various chemical settings.Three types of polystyrene of ~ 100 nm were used herein: A non-functionalized spherical polystyrene (PLAIN), a spherical carboxyl functionalized polystyrene (CARBO) and a hexagonal secondary polystyrene (GRIND) produced by mechanical grinding of larger polystyrene beads. Furthermore, divalent ion concentrations in terrestrial environments are inducing larger effects on nanoplastic processes than monovalent ions and therefore only the effect of increasing Ca2+ concentration in solution was tested. Moreover, natural organic matter (NOM) in terrestrial environments is usually degraded with depth, thus its presence in saturated groundwater can be negligible, yet to consider even low concentrations, we also tested the effect of technical grade humic acid as a model NOM. We found that deposition behavior differs between various particles and mineral surfaces as well as with Ca2+ concentration. For quartz surfaces, non-spherical particles showed the highest deposition rates, while with the increasing mineral complexity (kaolinite), this effect diminished, and other factors gained more importance. Kaolinite surfaces showed the highest deposition rates among all particle types. This suggests the involvement of surface charge driven processes, where positive Al-OH sites of the kaolinite more effectively attract negatively charged nanoplastics as compared to negatively charged quartz. Increasing the ionic strength increased the deposition behavior until a peak deposition observed at 15 mM Ca2+ due to a gradual charge decrease of particles and minerals. Beyond 15 mM, deposition decreases as a result of reduced particle stability, and consequently lowered convective-diffusive transport to the mineral surface. Surprisingly, highly carboxylated CARBO particles showed a large increase in deposition on kaolinite irrespective of Ca2+ concentration. This may be explained by the importance of Al-OH sites, which bind -COOH groups more effectively than Si-O sites. Adding 1mg/L humic acid at 15 mM Ca2+ reduced the deposition behavior significantly at both mineral surfaces. Our results highlight important processes between nanoplastics and mineral surfaces and thereby also important impacts in understanding nanoplastic transport in subsurface terrestrial environments. Charge driven processes dominate in simple mineral settings (quartz), while with increasing mineral complexity, chemical processes and specific ion binding interactions will dominate nanoplastic deposition and transport.
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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) | 0,000 | 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) | 0,001 | 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 ».