A case study of integrated modelling of traffic, vehicular emissions, and air pollutant concentrations for Huron Church Road, Windsor
Notice bibliographique
Résumé
The objectives of this research are to examine spatial and temporal variations in traffic-related NO 2 and benzene concentrations and to investigate the sensitivity of estimated vehicular emissions and ambient concentrations on input parameters. The case study was conducted for Huron Church Road (9.5 km) in Windsor, Ontario. Observed vehicle counts and emission factors from Mobile6.2 were used to estimate vehicular emissions. Ambient concentrations were estimated using the AERMOD dispersion model. Results showed that traffic on Huron Church Road significantly contributes to near-road air quality. The simulated annual mean NO 2 concentration of 2008 was 27 μg/m3 at 40 m from the road, which was higher than the background concentration of 21 μg/m3. Concentrations sharply decreased with distance from the road. At 600 m from the road, the simulated annual concentration was 9% of the concentrations at a distance of 40 m from the road (=2.4 μg/m3, less than background concentration). Similar patterns were observed for benzene. Ambient concentrations were higher during the nighttime than the daytime due to poor mixing. Traffic counts and wind speed explained 40% of variations in the both observed and simulated NO 2 concentrations. The relationship between the truck/car counts and NO 2 /benzene concentration ratios was linear. The model-measurement comparison showed that Mobile6.2 and AERMOD reasonably reproduced the hour-of-day variations and spatial fall-off pattern of NO 2 concentrations. However, AERMOD underestimated concentrations during the daytime potentially due to over-mixing. Sensitivity analysis of the Mobile6.2 showed that the emission factors were most sensitive to the choice of Vehicle Mile Traveled compositions (Ontario versus US), followed by the choice of vehicle age distribution (Ontario versus US), and the average speed of vehicles. In AERMOD simulations, the hour-of-day variation in emission should be considered. Stop-and-go movements increased the total NOx emission over the 9.5 km road by 24% compared to the case of cruise speed of 50km/h during the morning peak hour. Two correction (multiplication) factors were devised to adjust uniform emissions by Mobile6.2 near signalized intersections: an upstream correction factor of 3.2 to account for idling and acceleration emissions, and a downstream correction factor of 1.6 to account for acceleration emissions.
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 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) | 0,001 | 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) | 0,000 | 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 ».