Abstract. The ever-increasing automotive travel demand is a major source of urban carbon emissions. Therefore, it could be an effective way for local governments to achieve carbon peak by optimizing facility distribution and transport management strategies, that results in lower automotive demand. This study adopts a two-stage approach to evaluate the carbon emission performance of a representative Chinese megacity, i.e. Suzhou. The first stage is to predict the carbon peak through multi-scenario sensitivity analysis with respect to three essential factors for the whole city. The second stage is to estimate the link-based carbon emissions with given traffic flow and vehicle operating mode indicators during the peak hour, so as to locate urban areas and/or facilities with higher emission intensity. Then a correlation analysis is further conducted to explore the possible connections between the built environment factors and transport-related carbon emissions.

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