A multi-distance dataset of city-level road freight transport and carbon emissions in 285 Chinese cities

High-resolution road freight and emissions data are essential for understanding subnational logistics activity, evaluating decarbonization pathways (especially for long-haul trucking), and supporting evidence-based transport and climate policy. However, publicly accessible datasets that provide consistent city-level road freight volumes—particularly those further resolved by transport distance and vehicle powertrain type—remain scarce in China. Here, we compile a multi-distance dataset for 285 prefecture-level cities that reports annual city-level road freight totals for 2013–2023 (in units of 10 Kt) and, for 2023, disaggregates freight activity into six distance groups (intra-city, 10–50, 50–100, 100–200, 200–400, 400+ km), together with distance-specific powertrain shares (electric vs fuel trucks) and corresponding distance- and powertrain-resolved carbon emissions (also in 10 Kt). The dataset is constructed through a transparent, reproducible, top-down workflow that integrates publicly available statistical records with high-resolution inter-city truck flow information from Baidu Maps, distance-specific payload assumptions, city-level electric freight vehicle penetration information, and standardized emission factors. Technical validation includes consistency checks against authoritative aggregates (e.g., provincial/national constraints) and diagnostic evaluations of the reconstruction models, supporting the reliability and internal coherence of the resulting city-by-distance-by-powertrain estimates. This dataset fills a critical data gap for urban and regional freight research by providing a publicly reusable, fine-grained basis for freight pattern analysis, emissions accounting, scenario assessment of electrification, and studies of spatial heterogeneity in road freight systems.