The impact of on-site wastewater effluent on rural karstified aquifers
Notice bibliographique
Résumé
<p>Karst aquifers are exceptionally vulnerable to pollution and may be impacted by multiple contamination sources. In rural and suburban areas, human wastewater effluent from on-site domestic wastewater treatment systems (DWTSs) and agricultural sources are the most significant threats to groundwater quality. It has been estimated that around 2.8 billion people worldwide rely on DWTSs for treating domestic wastewater. As karst groundwater is a major source of drinking water for at least one-quarter of the world’s population it makes protection and management of karst aquifers extremely important. These aquifer systems are highly complex and challenging to understand, especially with regards to the fate and transport of contaminants through such systems. Thus, significant knowledge gaps exist with respect to linking contaminants with the origins of pollution and quantifying different pollution impacts on groundwater quality in karst environments.</p><p>In this paper, a novel approach for investigation of the impact of contaminants from DWTS effluent on rural karstified aquifers using a range of source-specific tracers is proposed, as it is extremely difficult to distinguish between agricultural and DWTS effluent pollution using only traditional water quality parameters or any single environmental marker. Domestic wastewater is primarily discharged from toilets, washing machines, showers and dishwashers, but even after on-site wastewater treatment processes a large number of different contaminants, including source-specific ones, can still reach the groundwater and wider environment. One example are microplastic particles which are found with other solid materials in the wastewater effluent principally due to household washing and cleaning processes. Investigations of microplastic occurrences in groundwater systems are very rare but several karst springs in the west of Ireland have been sampled during this study for quantification and identification of microplastic particles using Fourier-transform infrared spectroscopy (FTIR). Many of these particles were successfully linked to human wastewater on the basis of their physical and chemical properties and/or adsorbed/absorbed pollutants. The overall numbers of microplastics and numbers of household-derived microplastic particles were linked to other well-known indicators of human contamination such as fluorescent whitening compounds (FWCs) and specific anion ratio signatures (Cl:Br). Our results show a significant correlation between microplastics and detected FWC signals at different karst springs over time, which suggests the majority of found microplastic particles to be from DWTS effluent. Notably, certain limitations were found and furthermore understood in terms of the capability of Cl:Br ratio method in determining human wastewater impacts on karst groundwater. Additionally, we have found that faecal sterol and stanol concentrations, as source-specific faecal markers, and their ratios can very successfully differentiate and quantify DWTS effluent pollution and agricultural faecal contamination at karst springs due to rapid and extensive transport of these contaminants particularly through the karst conduit networks. </p>
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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) | 0,002 | 0,002 |
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; les deux têtes enseignantes s’accordent sur ce qui est montré ici.
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