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Abstract Accurate estimation of greenhouse gas (GHG) emissions at the infrastructure scale remains essential to climate science and policy applications. Vehicle emissions often dominate GHG emissions in urban areas and are rapidly increasing globally. Climate Trace (CT), co-founded by former U.S. Vice President Al Gore, is a new AI-based effort to estimate roadway-scale GHG emissions. However, limited independent peer-reviewed assessment has been made of this dataset. Here, we compare CT on road CO 2 emissions in U.S. urban areas to atmospherically calibrated, multi-constraint estimates of on road CO 2 emissions from the Vulcan Project. Across 260 urban areas in 2021, we find a mean relative difference (MRD) of 70.4%. These large differences are driven by biases in CT’s machine learning model, fuel economy values, and fleet distribution values. We conclude that sub-national policy guidance or climate science applications using the on road CO 2 emissions estimates made by CT should be done so with caution.
Gurney et al. (Wed,) studied this question.