Methods to Estimate Carbon Dioxide Emissions Reduction and Low-Stress Bicycle Accessibility for School-Related Trips: a Montreal Case Study
Notice bibliographique
Résumé
Despite the important benefits, urban cycling still faces multiple barriers, mainly the lack of bicycle infrastructure, road safety, and adverse weather conditions. Cycling can be a relevant mode for short daily trips, such as school-related trips for children and teenagers. However, in part due to such barriers, the percentage of bicycle school trips is still very low in Canadian cities, including the City of Montreal. The thesis has a two-fold objective: 1) to estimate the potential CO2 savings of bicycle school trips, and 2) to evaluate the bicycleinfrastructure needs to improve the accessibility around schools using the Level of Traffic Stress method.For the first objective, a link-level emission model is calibrated for the City of Montreal using real-world CO2 measurements. Then, Montreal origin-destination data is analyzed to identify the school trips that could be transferred from private vehicles to bicycle trips. Afterward, the calibrated link-level emission model is applied to those transferable trips to estimate the CO2 emissions savings. For the second objective, we assess the biking low-stress accessibility to schools in Montreal. To achieve this, we applied the Level of Traffic Stress(LTS) methodology and developed an accessibility index for each school. This metric is then used to evaluate and prioritize potential biking network infrastructure improvements. Additionally, low-detour criteria or multi-modal trips are investigated to estimate their impact on school accessibility.This research shows that a realistic CO2 emission factor for an average Quebec light-duty vehicle is 285 gCO2/km, 42% more than the value of 200 gCO2/km observed in the literature. In the region of Montreal, it was found that 15% of the school-related car trips could be replaced by cycling trips given their proximity to schools (less than 4.5 kilometers). This represents 4.7 million kilometers traveled or 1335 tons of CO2 that could be avoided yearly for the region of Montreal. However, based on the Level of Traffic Stress analysis of the current bicycle network of Montreal, 94% of the schools have an accessibility below 10% and 49% have a null accessibility, which likely deters or prevents many children to cycle to school. A scenario of local improvements within 200 meters of the schools is evaluated, and the percentage of schools having a null accessibility decreases to 23%. The findings of this research can help city planners to identify the CO2 savings from bicycle use and advocate for its widespread use, and to evaluate the current accessibility around schools and select network improvement projects that increase children’s access to schools by bicycle the most
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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 | 0,001 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,002 | 0,003 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 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 ».