Introducing a Regression Model for Environmental Assessment in Aircraft Production

Abstract

Life Cycle Assessment (LCA) has become essential for comprehensive environmental analysis, particularly as air transport continues to grow and the demand to mitigate its environmental impact intensifies. A core challenge in conducting LCA studies lies in the extensive input data required—especially during the Life Cycle Inventory (LCI) phase, which serves as the backbone of the entire assessment. The LCI’s dataintensive nature often makes the process time-consuming and resource-demanding. This paper presents a high-level LCA methodology aimed at enabling faster assessments with reduced data requirements, focusing on identifying the key parameters that most significantly influence environmental outcomes. The proposed approach begins with a cradle-to-gate LCA, with the focus on the production phase of baseline aircraft. It includes regional models (ATR42, ATR72, and E190-E2), narrow-body types (A220, A320neo, and A321neo), and wide-body aircraft (B787, A330, and B777). This requires the creation of extensive LCIs, including manufacturing processes and aircraft materials and components. Regression models are then built using the results of the LCA impact categories, which include climate change and resource use, as the dependent variables. Aircraft parameters (e.g., aircraft or engine weight) are then used as the independent variables. Three regression approaches are evaluated: linear, quadratic, and cubic. This approach enables efficient and reliable LCA calculations and is aimed at LCA practitioners and stakeholders in academia and industry. It introduces a set of equations to quickly assess environmental impacts of aircraft based on in-depth LCA calculations. Such LCA results may be used to prioritise action and support informed Design for Environment (DfE)