Common approaches to assess the evolution of CO2 emissions from road vehicles are usually based on (a) estimates of future fleet composition, where most approaches consider vehicles at a rather aggregated level, and (b) emission factors, which are either based on CO2 certification data or statistically-provided functional relationships obtained from real world test data, or a combination of the two. This approach has certain limitations in capturing the effect of new technologies on CO2 emission related policy initiatives. The present study proposes a new method for the detailed calculation of the European light duty vehicle fleet CO2 emissions, which could help to overcome such limitations, achieve better results when making CO2 emissions projections and better support future policies. Simulation at individual vehicle level is combined with fleet composition data, retrieved from the official European CO2 emissions monitoring database, and publicly available data regarding individual vehicle characteristics in order to calculate vehicle CO2 emissions and fuel consumption over different conditions and vehicle configurations. The methodology is applied to analyse and assess the impact of the introduction of the new certification procedure, the Worldwide Light duty vehicle Test Procedure (WLTP), on the European car fleet CO2 emissions. Results show an average WLTP to NEDC CO2 emissions ratio of approximately 1.2. The increases in CO2 emissions are higher for cars exhibiting lower NEDC emission values (additional 29 and 25 gCO2/km for vehicles emitting 100 and 119 gCO2/km, respectively). At higher emission levels (about 250 CO2 g/km) WLTP and NEDC present comparable results. Three possible scenarios for the translation of projected NEDC CO2 emissions to WLTP-based ones are quantified. ; JRC.C.4-Sustainable Transport


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    Titel :

    A simulation-based methodology for quantifying European passenger car fleet CO2 emissions


    Beteiligte:

    Erscheinungsdatum :

    2017-04-04



    Medientyp :

    Sonstige


    Format :

    Elektronische Ressource


    Sprache :

    Englisch


    Klassifikation :

    DDC:    629




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