Quantifying carbon emissions in cold chain transport: A real-world data-driven approach

Sustainable 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.