Assessment of background particulate matter concentrations in small cities and rural locations—Prince George, Canada
Notice bibliographique
Résumé
UNLABELLED: This study investigates the development and application of a simple method to calculate annual and seasonal PM2.5 and PM10 background concentrations in small cities and rural areas. The Low Pollution Sectors and Conditions (LPSC) method is based on existing measured long-term data sets and is designed for locations where particulate matter (PM) monitors are only influenced by local anthropogenic emission sources from particular wind sectors. The LPSC method combines the analysis of measured hourly meteorological data, PM concentrations, and geographical emission source distributions. PM background levels emerge from measured data for specific wind conditions, where air parcel trajectories measured at a monitoring station are assumed to have passed over geographic sectors with negligible local emissions. Seasonal and annual background levels were estimated for two monitoring stations in Prince George, Canada, and the method was also applied to four other small cities (Burns Lake, Houston, Quesnel, Smithers) in northern British Columbia. The analysis showed reasonable background concentrations for both monitoring stations in Prince George, whereas annual PM10 background concentrations at two of the other locations and PM2.5 background concentrations at one other location were implausibly high. For those locations where the LPSC method was successful, annual background levels ranged between 1.8 +/- 0.1 microg/m3 and 2.5 +/- 0.1 microg/m3 for PM2.5 and between 6.3 +/- 0.3 microg/m3 and 8.5 +/- 0.3 microg/m3 for PM10. Precipitation effects and patterns of seasonal variability in the estimated background concentrations were detectable for all locations where the method was successful. Overall the method was dependent on the configuration of local geography and sources with respect to the monitoring location, and may fail at some locations and under some conditions. Where applicable, the LPSC method can provide a fast and cost-efficient way to estimate background PM concentrations for small cities in sparsely populated regions like northern British Columbia. IMPLICATIONS: In rural areas like northern British Columbia, particulate matter (PM) monitoring stations are usually located close to emission sources and residential areas in order to assess the PM impact on human health. Thus there is a lack of accurate PM background concentration data that represent PM ambient concentrations in the absence of local emissions. The background calculation method developed in this study uses observed meteorological data as well as local source emission locations and provides annual, seasonal and precipitation-related PM background concentrations that are comparable to literature values for four out of six monitoring stations.
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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 | 0,001 | 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 ».