The road transport sector significantly contributes to urban air pollution globally. City-scale inventories, relying on regional (macroscale) traffic emission models, attempt to grasp the spatial and temporal road transport emissions distribution. However, understanding high pollution levels in specific urban microenvironments requires more detailed information. Efforts have been made to integrate traffic details into emissions models at the microscale with a focus on high-resolution air quality solutions for polluted urban areas. The increased data demands and longer processing times of microscale tools, makes it crucial to reconcile this detail with a comprehensive city-scale view for effective policy actions. This study provides insights to understand how relevant microscale variables vary when they are aggregated over time. Objectives include testing the integration of microscale features into macroscale emission assessments and evaluating how microscale data align with coarser scales for inclusion in a parameterization. Utilizing one Hz microscale data for speed, road grade, and estimated Vehicle Specific Power for light-duty gasoline vehicles, the study evaluates macroscale approaches’ capability to capture microscale high values. Results indicate a decay in accuracy for all factors with increasing time aggregation. While speed preserves the highest accuracy, falling below 90% only after 1200 s (20 min) or more of aggregation, accuracies of over 80% are achieved for all factors with a notable inflection point at 300 s (5 min) average. This study emphasizes the importance of balancing accuracy and computational efficiency when parameterizing microscale applications based on macroscale information.


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    Title :

    Road Transport Emission Parameterization for Microscale Applications Based on Macroscale Measurable Traffic Information


    Additional title:

    Lect.Notes Mobility



    Conference:

    Transport Research Arena Conference ; 2024 ; Dublin, Ireland April 15, 2024 - April 18, 2024



    Publication date :

    2025-07-19


    Size :

    6 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English





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