Towards Sustainable Cruise Ships – Accompanying Socio-Ecological Assessment of Innovative Ship Cabins

Abstract

As a major contributor to climate change, the shipping industry is supposed to cut its CO2-emissions by 50% by 2050, according to an agreement of the International Maritime Organization (IMO). In comparison to approaches, that mainly focus on weight or propulsion efficiency to achieve this goal, in our current BMWi funded project of EcoCab, we, together with the MEYER WERFT GmbH & Co. KG, aim at developing a decentralized energy supply in the form of photovoltaic and battery technologies and more sustainable materials in cruise ship cabins. The latter have, with a total amount of up to 3,500 cabins per ship, a significant impact on the electricity usage on board and the material composition of the ship itself. The extent to which such innovative ship cabins actually contribute to reducing CO2-emissions and other environmental impacts compared with conventional ship cabins is investigated as part of our study within a development accompanying Life Cycle Assessment (LCA). Due to its specific role as being the passengers’ private space onboard, though, a manifold of additional aspects (eg. legal, technical, social) has to be considered in cabin design, making solely environmental based decisions concerning materials or the energy supply neither possible nor useful. Therefore, a novel methodological approach was set up, using qualitative expert interviews with stakeholders of the cruise ship sector, to identify those additional matters, that impact decision making and the LCA itself. Our contribution to the conference will therefore include insights on the methodological considerations of using qualitative expert interviews within an iterative LCA process, focussing on the approach as well as its chances and obstacles. Moreover, we show the results and experiences of our specific case study on cruise ship cabins. These findings can contribute to the assessment methodologies for technologies under development and to the use of LCA data within a decision-making process.