Characterisation of Air Pollution on Trinidad’s North-West Coast (San Fernando to Port-of-Spain)
Notice bibliographique
Résumé
Air pollution is a complex mixture of toxic gases and particulates that has been identified as the largest global environmental threat facing the world today, estimated to have caused 7-10 million deaths worldwide annually [1,2]. Trinidad is the most industrialised of the Caribbean islands, with a large energy and petrochemical economic base. In addition, it is affected by seasonal Sahara dust (PM2.5). This study characterizes the baseline levels of fine and respirable particulates (three PM size fractions), trace metals in PM, gaseous pollutants and meteorological parameters at four sites over the heavily populated west coast of Trinidad during March’ 15 - May ‘16. Stations represent rural, urban, mixed background and industrial land uses. Annual mean levels of PM2.5 and PM10 in ambient air exceeded the WHO guidelines for protection of public health at all four stations (n=522). PM2.5 and PM10 exceed the WHO (2006) safe limit guidelines (PM2.5 is 10 µg/m3, PM10 is 20 µg/m3) over 70% of the time sampled at urban and industrial sites. Factor analysis indicated the variables impacting PM distribution and type of PM (size fraction) were time of year and location of station (land use). The temporal pattern for PM at the industrial station was markedly different from the other three stations, being at a constant high level throughout the year. Trace metals (in PM10) found in exceedance of Canadian (Ontario) 2012 [3] standards were, beryllium, cadmium, chromium, iron, manganese and nickel. Cd and Ni were deemed to pose the highest risk to public health as they are genotoxic carcinogens found in the smallest PM fractions. Several gaseous pollutants of concern were CO, NH3, NO2, N2O, C6H6. Nitrogen dioxide and benzene were the most prolific, being the highest most frequently at the industrial and urban stations. NO2 exceedance averaged 89% (often 2-3 times the USEPA limit for the protection of public health), reflective of the large amount of industrial combustion gases in the ambient air in the Pt. Lisas area. Benzene was found to exceed public health limit values >90% of the time measured at the urban station (Port-of-Spain) and at >80% at the mixed background station (at San Fernando). Both gases are reflective of combustion and vehicle emissions derived pollutant sources. The pollutant data was used to calculate and validate an aggregated Air Pollution Index (R2= 0.91) that could be readily applied to ongoing monitoring data in four statistically validated classification tiers; Good, Normal, High, Very High. The industrial station has the highest frequency of ‘very high’ pollutant levels, as well as the highest frequency of ‘good’ air quality days. The urban station had highest frequency of ‘normal’ to ‘high’ rankings. The rural station, as expected, had much better overall air quality. The worst air quality occurred during June-July ’15 and December ’15 -January ’16 periods. Monitoring data for air quality provides the best option to drive data driven decision making and effective air pollution management. The baseline levels of air pollutants provide adequate justification for revision of the current local regulations to afford better public health protection from unnecessarily high levels of ambient air pollution.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| 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 | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 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 | 0,000 |
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 source (Gemma direct ou Codex distillé), 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 ».