Integrated agent-based transport simulation and air pollution modelling in urban areas - the example of Munich
Notice bibliographique
Résumé
Against the background of high air pollution levels in urban areas, which are often related to high traffic demand and lead to adverse effects on human health and the environment, there is a demand to develop transport policies to reduce air pollution in a sustainable way.This thesis focuses on the modelling of air pollutant concentration and, thereby, addresses three fields of research: transport modelling, air pollutant emission and atmospheric dispersion modelling.In each of these fields nowadays, specific methods and tools are increasingly developed to provide new valuable insights.However, owing to their complexity these approaches often cannot be integrated in order to analyse the impact of different transport policies on air pollution.Even though less detailed methods and tools are also available and suitable for decision making processes, they do not provide all the information necessary to understand the cause-and-effect chain.This thesis addresses this gap by presenting a new approach, an integrated air pollution model, which simulates the complete cause-and-effect chain from changes in transport behaviour and vehicle technology to the impact on air quality.The developed approach links agent-based transport modelling with vehicle specific emission factors based on traffic situations.As a result, it is possible to include driving dynamics, in terms of traffic situations, and vehicle attributes to calculate air pollutant emissions through the use of HBEFA emission factors.In this thesis, an emission calculation tool is first developed and integrated within the environment of the multiagent transport simulation, MATSim.It could be shown that simulated link travel times follow measured travel times and simulated emissions correlate with sophisticated emission simulations using measured driving cycles.Additionally, this methodology is projected on the real-world scenario of the Munich metropolitan area in Germany, through a large-scale simulation with MATSim.The emission level is linked to the agent causing it, as well as to where the emission level was caused forming the basis for following the cause-and-effect-chain.By mapping emissions back to their source, i.e. the road section, a disaggregated spatial analysis of air pollutant emissions is possible.Finally, the complete integrated approach from traffic activity to air pollution modelling is developed, validated and applied to the inner city area of Munich.A street canyon approach with respect to atmospheric dispersion modelling is applied and integrated with MATSim and the emission calculation tool.The integrated approach is able to simulate air pollutant concentrations for every street canyon and on an even more disaggregated level for several points distributed within the street canyon.Furthermore, locations with high air pollutant concentration levels, so-called hotspots, and the impact on this level due to changes in travel behaviour and vehicle technology can be determined.With the developed approach, transport policies can be evaluated.In the case of rising car user costs, for example, through the introduction of higher fuel taxes, traffic demand and the emission level decrease to different extents.This can be shown on an aggregated and spatially disaggregated level.Car user price elasticity of commuters differ from the one of inner-urban travel demand.The introduction of a speed limit in the inner city of Munich shows an overall decrease in car trips, a slight increase in car distance travelled by commuters and reduced air pollutant concentrations within a selected street canyon.The integrated air pollution modelling approach allows for the evaluation of a variety of further transport policies providing aggregated impacts of changes in transport behaviour and vehicle technology on traffic demand and the emission level as well as, with respect to a spatially disaggregated level, on air pollutant emissions and concentrations.As a result, it provides a basis for future research work in the modelling of agent-based transport and environmental effects as well as the application of this approach to other cities.
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 | 0,002 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,002 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| 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 ».