Characterizing VOC Emissions and Retention in Recovered Water during Solar Drying of Wastewater Sludge under Variable Conditions
Notice bibliographique
Résumé
Photochemical processes are a significant source of secondary organic aerosols (SOAs), many of which are watersoluble and remain in the condensed phase [1], [2], [3].Water recovery from wastewater sludge is feasible, as previously discussed in this congress ("Greenhouse Gas Emissions and Water Recovery in Solar Drying of Wastewater Sludge: Insights from LIFE-DRY4GASr").However, the characterization of VOC emissions during solar drying of wastewater sludge (WWS) under varying light intensities has not been explored.This study provides the first identification of VOCs emitted into the air and retained in water during laboratory-scale solar drying of WWS.A laboratory-scale solar dryer with controllable heat sources was designed for this purpose.Experiments were conducted using two independent heat sources: artificial solar light and heated plates.Light intensities of 625 W, 400 W and 200 W corresponded to dryer temperatures of 50 C, 45 C and 35 C, respectively, while heated plates were set to 60 C, 50 C, 40 C, yielding internal dryer temperatures of 45 C, 37.8 C, and 28 C.To simulate the dryness levels achieved in the LIFE-DRY4GAS prototype [4], each experiment continued until the WWS weight decreased from 100 to 15 %.VOC emissions during drying were measured in both the air and the recovered water.Airflow was directed sequentially through the sludge, water recovery system, and air emissions sampling setup.Hydrophobic VOCs were collected using two Tenax sorbent tubes in series.Recovered water was stored at varying pH levels to evaluate its influence on VOC retention.In one set of experiments, samples were preserved at their original pH (8-10) or acidified to pH 2. In another setup, the impingers were acidified with HSO before condensation to maintain a pH of 2 throughout condensation.Recovered water was analysed by ion chromatography for F -, CH3OO -, HCOO -, ClO2 -, NO2 -, NO3 -, PO4 3-, SO4 2-, and C2O4 2-.VOCs in water were further analysed using headspace solid-phase micro extraction (HS-SPME), while VOCs retained in Tenax tubes were identified using a thermal desorption system coupled to gas chromatography-mass spectrometry (TDS-GC-MS).The results revealed that VOC emissions were higher when temperature increases were driven by artificial solar light compared to heated plates.The dominant chemical families included alkanes, non-oxygenated terpenes, and aromatic hydrocarbons.Recovered water showed acetate concentrations around 300 ppm, while other analytes remained below 1 ppm, consistent with results from the LIFE-DRY4GAS prototype.VOC analysis of recovered water indicated two predominant chemical families: carboxylic acids and aromatic hydrocarbons.Carboxylic acids were more concentrated at acidic pH, whereas aromatic hydrocarbons dominated at the original pH (8-9).Acidification of water after recovery increased the concentration of carboxylic acids, while pre-acidification of impingersresulted in greater VOC diversity, particularly esters.Aromatic compounds in water were primarily toluene and phenols, whereas the carboxylic acids identified included butanoic acid, propanoic acid, and pentatonic acid.These findings demonstrate the interplay between temperature, light intensity, and pH in determining VOC emissions and their retention in recovered water, providing valuable insights for optimizing sustainable WWS drying processes.
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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 | 0,000 | 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 ».