Ambit-Based Activity Model for Evaluating Green House Gas Emission Reduction Policies

摘要

This study presents an Ambit-Based Activity Model (A-BAM) for evaluating Green House Gas (GHG) emission reduction policies that are being considered for implementation in transportation sector in the wake of more stringent emission reduction targets envisaged in a post-Kyoto international climate treaty. This study demonstrates how A-BAM can be used to estimate the 'effectiveness' of reducing GHG emissions from multiple policy interventions from year to year in a given geographical area. The A-BAM model builds upon the fact that any change in the current state of transportation systems through policy interventions will inevitably cause a change in the transportation activities of agents. So, for quantifying GHG emission reduction policy effectiveness, A-BAM requires that the transportation activities of randomly sampled agents for the evaluation area be systematically tracked and analyzed. At the core of the A-BAM is the concept of agents ambit that represents movement through space around an agents home place in all directions over a period of time. Analytical notions of trip-weighted and time-weighted centroids are formally derived to calculate the ambit of agents. Although GPS devices are empirically better to track agents ambit, this study, due to cost limitations, uses memory-based, travel-diary kind of a survey instrument to operationalize the spatial parameters of A-BAM. Survey data from 74 volunteers in California is deployed to track their ambit and carbon footprints. It is found that trip-weighted centroids are generally smaller than time-weighted centroids; and as the magnitude of the trip- and time-weighted centroids increases, the carbon footprint grows non-linearly.