Data Driven Decision Support Tool for Assessing the Environmental Impact of Unmanned Aerial Vehicles in Last mile logistics

The increasing use of Unmanned Aerial Vehicles (UAVs) for last mile logistics (LML) has raised questions about their environmental impact. While there is growing interest in the operational efficiency of UAVs, the literature lacks comprehensive studies addressing their full life cycle impact. This paper presents the structure of a decision support tool for the environmental impact assessment of delivery UAVs. The tool classifies UAVs based on an analysis of key technical characteristics, providing a baseline UAV model for estimating a Bill of Materials (BoM). Using the baseline BoM, the tool performs a Life Cycle Assessment (LCA) covering material extraction, production, and end-of-life phases. Additionally, the tool can simulate delivery scenarios to estimate emissions during the use phase. This tool aims to evaluate the life cycle impact of different UAV models adopted for LML involving different tools for covering all processes in aa life cycle perspective. This paper outlines the structure of the tool, showing its potential to fill a critical gap in existing research by providing a holistic environmental assessment of UAV in LML. This approach can support decision-making processes for designing and managing more sustainable LML solutions based on UAVs.