Impact of Stormwater Runoff on the Water Quality of Lakes in a Metropolitan Region in India
Notice bibliographique
Résumé
Pollutants originate in stormwater runoff from natural and anthropogenic activities in the urban watershed.In metropolitan areas, runoff is a significant contributor to non-point source pollution [1].Emerging contaminants are synthetic substances not commonly monitored in developing countries and have become an environmental concern due to their potential adverse effects on human health and ecosystems [2].This research aims to characterize the runoff in the Powai region of Mumbai, India and identify the potential sources of pollutants entering the Powai lake.The focus of the current work is on heavy metals and emerging contaminants.Runoff samples were collected from five different outfall locations in the region (SL1, SL2, SL3, SL4, and SL5) for ten storm events between the 2022 and 2023 monsoon seasons.The analysis of runoff samples revealed elevated concentrations of aluminum, lead, iron, nickel, manganese and chromium.In addition, trace levels of copper and zinc were detected for both the monsoon season.Vehicular sources were identified as probable sources of iron, lead, nickel, and aluminum.Construction activity and leaching from building materials were identified as likely sources of chromium.Phthalates, pesticides, personal care products and pharmaceuticals were the four classes of emerging contaminants detected in the runoff across the five locations.The following phthalate compounds, typically originating from microplastics: Di(2-ethylhexyl) phthalate (DEHP), Decyl hexyl phthalate, Diisooctyl phthalate, Octyl decyl phthalate, Bis(3,5,5trimethylhexyl) phthalate, Bis(2-ethylhexyl) isophthalate, Bis(2-ethylhexyl) phthalate, Dibutyl phthalate, Diethyl phthalate, Dimethyl phthalate and Dioctyl phthalate (DOP) were the most abundant phthalate esters.The study estimates PVC pipes, vinyl flooring, medical devices, and consumer-use plastics as the potential sources of phthalates.Diuron and Isoxaben, commonly used as herbicides, were prevalent across the sampling locations.The outfall locations SL1 and SL4, which convey runoff from varied catchments, indicated the presence of carbendazim, a fungicide that can migrate from urban green spaces.Zearalenone, a mycotoxin produced by certain fungi of the Fusarium genus, was detected for the 2022 monsoon seasons.Diflufenican, a commonly used herbicide for weed control in lawns, gardens, paints, and roof coatings, was also detected.Pharmaceutical and Personal care products (PPCPs) such as ethyl paraben, galaxolidone, enalapril, norgestrel, caffeine, metformin, and valsartan were detected and quantified.Research is underway to identify the probable sources of these PPCPs and elaborate on their fate and transport.Preliminary findings indicate that the mixing of untreated sewage and the presence of healthcare facilities in the region could be contributing to the detected PPCPs.The depleted levels of dissolved oxygen and higher fecal coliform counts observed at the outfall locations (SL1 and SL3) further confirm the hypothesis of sewage mixture with runoff.The findings of this study could be used as a reference to assess the impact of runoff on the degrading water quality of Powai Lake.
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 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 | 0,000 | 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 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 ».