Abstract Diesel trucks are the primary source of PM2.5 and NOX. However, current methods for estimating real-world truck emissions rely on uniform emission factors, disregarding essential factors that could vary by the trip purpose, such as load status, empty-load rate, driving behavior, etc. Thus, this study decomposes the relationship between trip and emissions through the trip chain perspective by analyzing massive trajectory data. It introduces a method to calculate on-road truck emissions considering different trip purposes and the shift in load states between purposes. Results indicate that the real-world emissions from heavy-duty diesel trucks vary significantly by trip purpose, with the highest variations in the emission factors for NOX and PM2.5 exceeding 21.06% and 14.24%, respectively. Comparison with previous studies demonstrates the high accuracy and reliability of our proposed method for estimating truck emissions when accounting for different trip purposes.


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    Titel :

    Variation of truck emission by trip purposes: Cases by real-world trajectory data


    Beteiligte:
    Yao, Zhu (Autor:in) / Gan, Mi (Autor:in) / Qian, Qiujun (Autor:in) / Qiao, Yu (Autor:in) / Wei, Lifei (Autor:in)


    Erscheinungsdatum :

    2023-08-16




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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