Abstract

Public transport buses are heavy-duty vehicles that travel through the city from morning till night, which emits a large number of greenhouse gases. Understanding and estimating the characteristics of carbon emissions for transit buses are critical in achieving a low-carbon transportation system. In this study, the changes in carbon dioxide (CO2) emissions generated from new-energy buses as well as traditional diesel buses at bus stations, intersections, and road segments are compared using statistical analysis approaches; then the factors significantly affecting the emission rates are identified based on correlation analysis and feature selection methods. Finally, a gradient boosted regression tree (GBRT) model is proposed to conduct estimations for CO2 emission rates of buses. The results indicate that different sensitivities to various influencing factors exist in the carbon dioxide emissions of different types of buses. In addition, the VT-Micro regression method and Random forest technique were utilized to compare with the developed GBRT model. According to the comparison results, the estimation errors of GBRT fluctuate in a smaller range, suggesting that the GBRT model outperforms traditional approaches in emission estimation of carbon dioxide. Also, the deep understanding of the emission characteristics for both new-energy buses and conventional diesel buses helps to plan and dispatch buses with different fuel types according to local traffic conditions.

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