This study examines the trade-offs between energy consumption and food loss during the expansion of the cold chain from the perspective of carbon emissions. A nonlinear optimization framework is constructed to determine the optimal scale of the cold chain under the constant final demand and to analyze the potentials in GHG emission reduction for developed and developing countries using system dynamics. Meat, milk and aquatic products in China and US are selected as case studies. Results reveal that the expansion of the cold chain contributes to the reduction of total carbon emissions that 51.93%/29.34%, 3.16%/14.01%, and 84.17%/79.75% of current level of carbon emissions can be reduced from meat, milk and aquatic products in China/US, respectively, if the full coverage of cold chain could be acquired at the current level of final food demand. Meanwhile, the efficiency of the “trade-offs” varies from food categories to countries, that averagely each increased unit (in CO2e) of electricity will avoid 3.34/5.94, 1.06/1.43 and 19.85/16.14 unit (in CO2e) of food loss for meat, milk and aquatic products, respectively. Diet structure, power generation structure and carbon footprints of food products and electricity are all contributing to the differences of the trade-offs between the increased energy consumption and the avoided food loss by cold chain.
CSS Publication Number:
Journal of Cleaner Production
December 1, 2019
Hu, Guangwen, Xianzhong Mu, Ming Xu, and Shelie Miller. (2019) “Potentials of GHG Emission Reductions from Cold from Cold Chain Systems: Case studies of China and the United States.” Journal of Cleaner Production 239: 1-11.