Hung-Jui LinPei-Ci ChenHsuan-Po LinI-YUN HSIEH2025-05-172025-05-172025-05https://www.scopus.com/record/display.uri?eid=2-s2.0-85218887709&origin=recordpagehttps://scholars.lib.ntu.edu.tw/handle/123456789/729404Sustainable urban development necessitates advanced low-carbon transportation strategies, particularly within the cold chain logistics sector, where transporting perishable goods significantly contributes to environmental emissions. This study addresses the gap in empirical research by deploying real-world data from 128 long-haul trips, provided by a logistics company, to develop a comprehensive bottom-up operational-level carbon emission model. Our model quantifies emissions through various operational phases—loading, unloading, and transport—capturing contributions from vehicle operation (driving and idling), refrigeration processes (including transmission, infiltration, and pre-cooling), and refrigerant leakage. It further assesses the impact of ambient temperature on emissions and examines the effectiveness of decarbonization strategies such as employing shore power for pre-cooling and adopting low-carbon refrigerants. Validated against actual fuel consumption with an impressive accuracy of −1.84%, our findings significantly advance green logistics practices, offering practical insights for a transition towards net-zero emissions and improving the sustainability of cold chain transportation systems.Carbon Emissions ModelingCold Chain LogisticsData-Driven Logistics StudyDecarbonization StrategiesRefrigerated Transportjournal article10.1016/j.trd.2025.104679