A simulation study to evaluate economic and environmental effects of different unloading infrastructure in an urban retail street

This work explores the impact of resources provided for unloading operations and freight vehicle parking in an urban retail street. We present a novel discrete-event simulation approach to analyze how unloading infrastructure and available staff influence lead times as well as local and global emissions to air. Results show that emissions to air and lead times of freight delivery vehicles can be drastically reduced when appropriate infrastructure and resources are provided. Changing the type of unloading areas can reduce NOX emissions by up to 95 %, while lead times can be reduced by 78 % if staff helps with unloading. Some configurations are more suitable to lower emissions to air while others are more effective in reducing lead times. Consequently, decision makers can use this model to explore how adjustments in infrastructure and available resources impact emissions and delivery vehicle lead times. Furthermore, it can act as a basis tool to analyze policies and laws to facilitate sustainable retail street operations in the future.