Over the last few decades, the systematic approach of knowledge transfer from biological concept generators to technical applications has received increasing attention, particularly because marketable bio-derived developments are often described as sustainable. The objective of this paper is to rationalize and refine the discussion about bio-derived developments also with respect to sustainability by taking descriptive, normative and emotional aspects into consideration. In the framework of supervised learning, a dataset of 70 biology-derived and technology-derived developments characterised by 9 different attributes together with their respective values and assigned to one of 17 classes was created. On the basis of the dataset a decision tree was generated which can be used as a straightforward classification tool to identify biology-derived and technology-derived developments. The validation of the applied learning procedure achieved an average accuracy of 90.0%. Additional extraordinary qualities of technical applications are generally discussed by means of selected biology-derived and technology-derived examples with reference to normative (contribution to sustainability) and emotional aspects (aesthetics and symbolic character). In the context of a case study from the building sector, all aspects are critically discussed.

This paper describes a methodological approach for a sustainability assessment of development cooperation projects. Between the scientific disciplines there is no agreement on the term of "sustainability". Whereas the definition of sustainability within the context of development cooperation frequently highlights the long-term success of an intervention, the United Nations herald the inclusion of social, economic and environmental aspects. This paper proposes to bridge this gap by providing an analytical framework that uses nine impact category groups based on thematic priorities of sustainable development derived from the Sustainable Development Goals. Additionally, the long-term effectiveness of a project is taken into consideration. These impact category groups comprise the analytical framework, which is investigated by the Life Cycle Assessment and an indicator-based analysis. These data are obtained through empirical social research and the LCA inventory. The underlying concept is based on life cycle thinking. Taking up a multi-cycle model this study establishes two life cycles: first, the project management life cycle; and, second, the life cycle of a project's innovation. The innovation's life cycle is identified to have the greatest impact on the target region and the local people and is consequently of primary interest. This methodological approach enables an ex-post sustainability assessment of a built innovation of a development cooperation project and is tested on a case study on Improved Cooking Stoves in Bangladesh.

Various municipal solid waste management (MSWM) innovations have emerged in developing countries in face of the challenges posed by increasing waste generation and poor MSWM practice. We present a methodology to assess the potential sustainability impact of MSWM innovations in a holistic manner. The Life Cycle Sustainability Analysis (LCSA) framework and the United Nations (UN) sustainable development goals (SDGs) facilitated the methodology development. The result of applying the methodology to the case of waste bank (WB) in Bandung City shows that WB potentially generates the greatest sustainability impact in the resource recovery phase and the smallest impact in the collection and final disposal phase. All negative impacts could arise in the economic dimension. Surprisingly, WB as a national strategy to achieve 3Rs would not effectively solve Bandung City’s landfill problem. Almost all SDGs would benefit from the WB program under the assumed conditions. This methodology will facilitate the decision-making in MSWM by (1) comparing available innovations to find the optimal solution, (2) identifying the hot spots and taking measures to combat the negative impacts, (3) providing the basis for monitoring the implementation process and the ex-post performance assessment.