Evaluation of the Pollution by PhACs in the Zala River (Spas vs. WWTPs)
Notice bibliographique
Résumé
The spatio-temporal distribution of concentration and assessed environmental risk levels of the 3 most frequent pharmaceutically active compounds (PhACs) -caffeine (naturally occurring central nervous system stimulant), carbamazepine (antiepileptic), and diclofenac (nonsteroidal anti-inflammatory drug) -in water matrices globally [1] were investigated in Zala River (Hungary) in related to the local popular spas, wastewater treatment plants (WWTPs), and other pollution sources.The investigated area is famous for its healing thermal water baths/spas (4.1 million attendance at the baths of Zala county in the studied year), but the adequacy of treatment of used water from baths, and wastewater is questionable.While approximately 11.5 million m 3 of municipal wastewater is discharged into the Zala River annually, and 2.2 million m 3 of used water from bathing sites.Measurements of PhACs have already been carried out in this area, according to that results 66 active substances out of 134 were detected [2].In this study, sampling took place at 8 different sites 4 different times within a year.According to our results, the concentration of diclofenac in river waters in the last decade proved to be high in international comparison [2-5] (up to 2530 ng/L), and this compound presented high environmental risk level in the most sampled cases.Concentration changes depending on time of only diclofenac showed correlation with indicators of spa tourism (based on number of medical treatments in baths in Zala county), but only at sampling points near certain popular thermal baths.It can be explained by the fact that the spas with thermal water in the study area have a beneficial effect on joint inflammations and rheumatic pains, just like diclofenac [6].In other words, the visitors coming for medical treatment in these spas are most likely users of diclofenac, and this increases the level of local use and thereby environmental load by this PhAC.According to our further results, in the main tourist month (August -based on number of guest nights at commercial locations in Zala county) elevated concentrations of the 3 PhACs were not detected which can be explained by the strong and lasting UV radiation.Furthermore, the microbial activity and composition of activated sludge in WWTPs depend on temperature, and these all influence the degradation of the PhACs [7][8].Summarized, our data suggest that the local WWTPs should be reviewed, additionally necessity of treatment of used thermal water also in term of certain PhACs should be considered for sustainability and protection of aquatic ecosystem.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 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 tête enseignante, 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 ».