Policies that encourage reduced travel, such as traveling shorter distances, and increased use of more efficient transportation modes, such as public transportation and high-occupancy private automobiles, are often considered one of several possible tools aimed at improving the sustainability of transportation. This study develops a statistical model that provides an important step towards quantifying the possible benefits that could be derived from such policies in terms of potential reductions in greenhouse gas (GHG) emissions. In general, passenger transportation related energy consumption and GHG emissions per capita in urbanized areas are expected to be dependent on the supply and demand characteristics of the multiple modes of passenger travel in these areas. Naturally, an overall reduction in travel leads to lower GHG emissions. Moreover, due to the efficient nature of public transportation and the greater flexibility this mode offers in using different sources of energy, it is expected that, in general, an increase in the use of transit services could lead to a reduction in GHG emissions. Similarly, higher private vehicle occupancy is expected to mitigate the negative impacts of the single-occupancy vehicle mode, again in the form of reduced GHG emissions. Furthermore, population density has the potential to contribute to reduced travel and the adoption of policies and services that encourage more efficient modes. In addition to understanding the explanatory effects of transportation mode choice, the supply of transportation services, and population density, it is equally important to take into account the direct or indirect effects of government policies aimed at reducing GHG emissions


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    Titel :

    Impact of Public Transit Market Share and Other Transportation Variables on GHG Emissions: Developing Statistical Models for Aggregate Predictions


    Beteiligte:
    R. G. Mishalani (Autor:in) / P. Goel (Autor:in)

    Erscheinungsdatum :

    2015


    Format / Umfang :

    8 pages


    Medientyp :

    Report


    Format :

    Keine Angabe


    Sprache :

    Englisch