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The development of accurate emission inventories at an urban scale is of utmost importance for cities in light of climate change commitments and the need to identify the emission reduction potential of various strategies. Emission inventories for on-road transportation are sensitive to the network models used to generate traffic activity data. For large networks (cities or regions), average-speed models have been relied upon extensively in research and practice, primarily due to their computational attractiveness. Nevertheless, these models are myopic to traffic states and driving cycles and therefore lack in accuracy. The aim of this study is to improve the quality of regional on-road emission inventories without resorting to computationally-intensive traffic microsimulation of an entire region. For this purpose, macroscopic, mesoscopic, and microscopic emission models are applied and compared, using average speed …