City-wide measurement of outdoor PM2.5 and black carbon to support evidence-based environmental policy in Dhaka, Bangladesh
Notice bibliographique
Résumé
Existing literature reported high concentrations of ambient particulates, specifically during the dry months, severely affecting street and construction site workers, elderly, and school-aged children in Dhaka city, Bangladesh. The available air quality data from only three continuous air monitoring stations is inadequate for any evidence-based study regarding public health outcomes. Significant knowledge gaps exist due to air monitoring networks being limited to low-cost optical sensors, key suburban areas, slum areas, and industrial areas remaining uncovered and little information about sources contributing to air pollution. Therefore, this ongoing air monitoring study aimed to conduct a city-wide measurement campaign of fine particulate matter (PM2.5) and black carbon (BC), investigate source contributors to air pollution using source apportionment analysis, and produce spatiotemporal land use regression (LUR) models to estimate PM2.5 and BC concentrations across the city. The study team has recently conducted two seasonal (two months each) air monitoring campaigns from systematically designed eight fixed sites and sixty-one rotating sites considering the major land use classes across the city domain. Sites covered different land use types such as commercial, residential, industrial, suburban, major roads, green space, and brick kilns. The significant challenges during the air monitoring campaign included high road traffic from religious congress, political protests, and waterlogging from sudden intense rainfall. Weather conditions such as high heat and heavy rain affected the functioning and performance of equipment. Besides, exposure of the field team to dengue outbreaks, particularly during the wet season, had to be dealt with. Preliminary results showed that the unadjusted concentration of PM2.5 from the Zefan sensors was substantially higher (often exceeded the WHO 24-hour standard) in the dry season compared to the wet season across the different monitoring sites. Concentrations were also higher during nighttime compared to daytime in both seasons, and this difference was much more pronounced in the dry season. The fixed site in a significant industrial area, Shyampur, showed the highest concentrations compared to the other sites during both seasons, with a dry season average of approximately 290 ug/m3 and a wet season average of about 175 ug/m3. The real-time PM2.5 data will be further validated with filter-based gravimetric measurements for quality assurance. Filters are currently being analyzed for mass, black carbon, and chemical composition in a geochemistry laboratory. Incorporating source apportionment analysis and land use-based regression models of the datasets will support source identification. This will help to improve air pollution mitigation policies and implementation plans for reducing pollution while targeting its sources. The ultimate findings of this research will be conducive to assessing public health outcomes by incorporating socio-economic, demographic, and health data with the air quality data from this study, which is much needed in formulating an improved public health policy.
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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 | 0,003 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 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 | 0,001 | 0,004 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 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 ».