Quantifying Carbon Emissions in Cold Chain Transport: A Real-World Data-Driven Approach

Abstract

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 transition, 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.

@article{lin2025quantifying,
  title={Quantifying Carbon Emissions in Cold Chain Transport: A Real-World Data-Driven Approach},
  author={Lin, Hung-Jui and Chen, Pei-Ci and Lin, Hsuan-Po and Hsieh, I-Yun Lisa},
  journal={Transportation Research Part D: Transport and Environment},
  volume={142},
  pages={104679},
  year={2025},
  month=may,
  doi={10.1016/j.trd.2025.104679}
}