India continues to experience substantial economic growth, with increased travel demand for both passengers and goods. As a result, roadway congestion is increasing in many cities and putting significant pressure on India's transportation infrastructure. One key concern is air pollution related to the increased transportation activity. To understand the transportation impacts on air quality, it is necessary to develop and apply appropriate modeling tools to the area of concern. Recently, a new on-road mobile source emissions model designed for use in developing countries has been developed: the international vehicle emissions (IVE) model. The IVE model was developed jointly by researchers at the International Sustainable Systems Research Center and the University of California at Riverside. This paper describes a research program that applied the IVE modeling approach to the city of Pune, India. As part of the approach, an extensive vehicle activity–fleet composition study took place in Pune; it consisted of videotaping and measuring traffic patterns, tracking representative vehicles with Global Positioning System data loggers, monitoring start–stop patterns in instrumented vehicles, and conducting surveys in the field. In this paper, the methodology and results of the study are described in detail, followed by mobile-source emissions predictions based on the calibrated IVE model. This overall effort was designed to support estimates of the air pollution impacts of on-road transportation in Pune that can now be used extensively in the development of air quality and transportation management plans for the region. It is also hoped that the collected data can be extrapolated to other Indian cities to support further environmental improvement efforts.


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    Title :

    Vehicle Activity Patterns and Emissions in Pune, India


    Additional title:

    Transportation Research Record


    Contributors:


    Publication date :

    2007-01-01




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



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