Track: A
Date: 31.08.2018
Time: 3:00 – 4:00pm
Room: Brandenburg Gate
Session 13: Innovative Approaches to Assess Sustainability from a Life Cycle Perspective (2)
Presenter: Raul Carlsson, Swerea SWECAST AB
By considering the sustainability challenges and opportunities of cast metal industry, potentially disruptive technological innovations have been initiated the cast metal industry. Three major dimensions have been considered while formulating and developing the innovations: Firstly, the sustainability potential of the innovations, considering a life cycle perspective and opportunities for a circular economy. Secondly, the industrial commercial potential and clear sectorial ownership of the innovation. Thirdly, the significance of establishing an innovation eco-system and a true win-win value network. The cases exemplified are sensors integrated in cast metal, and the digital tagging of cast metal components. Both cases are closely related to industrial needs, and there are strong industrial research collaboration and development efforts to bring these sustainability solutions to market. Among the many sustainability potentials can be particularly mentioned the decoupling of value and material mass.
Carlsson, R., Elmquist, L., Johansson, C., Cast metal with intelligence – from passive to intelligent cast components, Conference: VIII ECCOMAS Thematic Conference on Smart Structures and Materials SMART 2017, Madrid, Spain, June 2017
Carlson, R., Digitally tagged cast metal facilitates circular business relationships, Circular Materials Conference 2018, Gothenburg, Sweden, March 2018
Presenter: Andreas Fritsch, Karlsruhe Institute of Technology
Co-Authors: Mario Nolte, Stefanie Betz
As an established approach, Life Cycle Assessment allows to collect, document and analyze information about potential sustainability impacts of a product system. This information can be used for decision making in support of a sustainable development of an organization. Currently, there exists a huge variety of different approaches to collect and manage such information: different LCA Tools and databases containing impact data, but also variants and extensions to LCA, like the integration of social aspects. In this context, we propose a novel approach to leverage the advantages of conceptual modeling for LCA. In computer science, conceptual modeling is used to reduce complexity in designing and analyzing complex systems. Therefore, we see the potential of using conceptual modeling to structure the domain of LCA and to facilitate the collection and representation of information about a product system. Visual representations of such models can foster an easier way of understanding, by allowing different kinds of navigation and aggregation to make information more comprehensible for involved actors (ref 1). It is also possible, to integrate such models with different perspectives of an organization (e.g. its goals or processes) by different stakeholders, which is something several authors have demanded in the discourse of sustainable development (ref 2).
We present the advantages resulting from the use of conceptual modeling and enterprise modeling for the Life Cycle Assessment of Product Systems based on our current research that deals with the use of conceptual modeling in the areas of social (ref 3) and ecological (ref 4) Life Cycle Assessment.
In particular, we discuss how current developments in conceptual modeling (ref 5) might improve the reuse of existing information in different contexts while collecting specific context dependent information. This innovative approach can help to build specialized LCA-tools that are geared towards the requirements of specific domains (e.g. chemical or automotive industry) or even single enterprises. Still, the flexible architecture ensures economics-of-scale, rigor and coherency when building these tools.
1: Thalheim, B. (2012). The science and art of conceptual modelling. In Transactions on Large-Scale Data-and Knowledge-Centered Systems VI (pp. 76-105). Springer, Berlin, Heidelberg.
2: Giddings, B., Hopwood, B., & O’brien, G. (2002). Environment, economy and society: fitting them together into sustainable development. Sustainable development, 10(4), 187-196.
3: Betz, S., Fritsch, A., & Oberweis, A. (2017) TracyML-A Modeling Language for Social Impacts of Product Life Cycles. Proceedings of the ER Forum 2017, Valencia, Spain.
4: Nolte, M., & Kaczmarek-Heß, M. (2017, November). Product Life-Cycle Assessment in the Realm of Enterprise Modeling. In IFIP Working Conference on The Practice of Enterprise Modeling (pp. 187-202). Springer, Cham.
5: Frank, U. (2014). Mehrebenen-Modellierung. Wirtschaftsinformatik, 56(6), 347-367.
Presenter: Alice Micolier, University of Bordeaux
Co-Authors: Franck Taillandier, Guido Sonnemann, Frédéric Bos
aConstruction sector is recognized as a major hotspot of resource use and environmental impacts and strong efforts are made to encourage the design of environmentally-friendly buildings. However, low energy buildings have particularly confined indoors in which pollution have major impacts. Learning how to design buildings with good indoor air quality (IAQ) is one of the tomorrow’s challenge. In this context, the aim of this study is to develop a decision-making tool to guide design choices of buildings providing good IAQ while ensuring energetic and environmental performances.
Life-cycle assessment (LCA) is a relevant methodology to account for impacts from indoor air while avoiding potential burden shifting from the life cycle of energy or materials used. Nevertheless, the current use of LCA still faces scientific obstacles such as: (a) inclusion of the dynamical effects of indoor pollution on human health and (b) consideration of occupants’ behavior. This question is particularly relevant when dealing with IAQ as the human factor is worth accounting for at the (i) inventory step (occupants generate pollution by their activities) and (ii) the impact assessment step (they undergo pollution through their presence).
Agent-based models (ABM) are computational models for complex systems simulation with a bottom-up approach. Behavioral models incorporated in ABM are well suited to finely model human cognition. Coupling ABM with LCA has a high potential to supplement LCA in its methodological weaknesses (a) and (b).
Inventory data related to the occupants’ behavior (energy consumption, pollutant emission) are collected from Li-BIM (Live in BIM), an agent-based model simulating occupants’ behavior in residential building from the numerical representation of the building (BIM). Building components (wall, windows…) and their parameters (geometry, material…) are directly extracted from the standardized exchange format (IFC) to be implemented as agents. Li-BIM is based on an evolved occupational cognitive and social framework. By taking into account inter-individual behavioral variation and rebound effect, Li-BIM contribute toward a more robust modeling of the use phase and increase the accuracy of associated results.
What’s more, Be-BIM (Breath in BIM) is currently being implemented to capture the dynamic and localized fate of pollutants and occupants exposure. Therefore, Be-BIM will assess the human toxicity due to IAQ in a dynamic and spatially differentiated way at the scale of the building.
This tool will be capable to compare the LCA of different building scenarios with a focus on IAQ sensitive to users’ behavior and the related dynamic of air emissions.