Geographical information systems supported green logistics solutions for urban food supply

Urban food systems are increasingly emphasized in climate policy and sustainability science, yet the transport aspect of food logistics remains underexplored. This PhD research addresses this gap by examining how green logistics, specifically sourcing localization and routing optimization, can decarbonize Urban Food Supply and Distribution Systems (UFSDS). The study focuses on Eskişehir, Türkiye, a mid-sized city, analyzing how spatially reconfigured supply chains and emissions-sensitive routes can reduce greenhouse gas (GHG) emissions from food transport. A scenario-based modeling framework integrates Geographic Information Systems (GIS), incorporating road network structure, urban slope, crop production, and wholesale market data. Emissions are estimated using the IPCC Tier 1 method across four localization levels (25–100%) and three routing strategies (shortest, fastest, greenest). A custom greenest-path algorithm is developed to reduce fuel consumption by minimizing both distance and slope. Inter-urban supply and intra-urban distribution are analyzed separately for high-resolution emission outputs. Results show that full localization reduces inter-urban emissions by 50.04%, while the greenest-path strategy lowers intra-urban emissions by an average of 7.45%, reaching 11.6% on slope-intensive routes. Combined, these measures save around 280 tons of CO₂e annually. Intra-urban distribution emerges as a major emission source, emphasizing the importance of last-mile optimization. The study contributes to urban food logistics decarbonization by integrating SFSCs, spatial planning, and GIS-based tools, offering policy insights on low-carbon transport, peri-urban production support, and carbon taxation.