Chair of Ecological Systems Design

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Circular Economy, Resources Management & Industrial Ecology

Proper management of natural resources is essential to avoid resource scarcity and environmental impacts. The aspiration to close traditionally linear energy and material flows within the economy, analogous to the flows in biological ecosystems, lies at the center of a scientific field known as industrial ecology. Identifying opportunities to reduce environmental impact and create more efficient uses of resources through the closing of material cycles is one of the main objectives. This goes hand in hand with the concept of a Circular Economy.

In collaboration with industry and authorities we are conducting various projects in the broader fields of circular economy, industrial ecology and resource management. Our projects on primary resources focus on tracing international supply chains and quantifying environmental impacts (e.g. of mineral resources or biomass). In some projects, we combine the methodological tools of Material Flow Anaylsis (MFA), Life Cycle Assessment (LCA), scenario analysis and mathematical optimization to environmentally optimize systems such as (national) waste or resource management systems or regional building energy demand and supply. Recently, we started to use Data Mining techniques to model consumption of households.

The extraction of resources from the natural world is responsible for a large share of greenhouse gas emissions, biodiversity loss, and waster-stress. Hence, to reduce these environmental impacts, these resources need to be better managed. In our research, we cover topics from improved mining management to the enabling of a circular economy. Research areas in this context include the environmental assessment of materials recovery and valorization of voluminous residues in industrial materials. We also seek sustainable metal/ mineral production strategies, which provide the backbone for the low-carbon transition.
The concept of a circular economy strives to phase out waste and maximize the cycling of resources. However, it is not always clear whether becoming more circular also helps in mitigating environmental impacts. In our research, we focus on the development of sound and holistic environmental assessment methods, to evaluate and enable the transformation towards a sustainable, and potentially circular, economy. We apply these methods, for example, on plastics, household furniture, textile clothing, waste recycling, sustainable mining, whether in Switzerland or beyond to identify ways for increased circularity and reduced environmental impacts.

Current Research Projects

Finished Research Projects

Optimization refers to an act, process, or methodology of making something as fully perfect, functional or effective as possible (Download Merriam Webster). This represents a novel area of interest of the ESD group and implies a step beyond what is commonly covered in a scenario-based Life Cycle Assessment (LCA). Our main motivation for exploring the opportunities to combine LCA with optimization techniques is that it offers a way to systematically determine the environmentally-optimal solution or the maximum improvement potential out of a very large set of feasible system or process configurations. It also enables us to consider resource availability and other system- or process-specific constraints to better reflect the decision making context. Departing from the previous and ongoing work in modelling of energy technologies, industrial processes and waste management systems, our aim is to be develop methodologies for optimization of energy and material flows on a regional or national system level.

Current Research Projects

Finished Research Projects

Data-mining and machine-learning methods can be useful to exploit extensive and complex data for understanding and improving the environmental performance of products, technologies and society as a whole. In our research we have applied machine learning to predict household-specific consumption profiles and related impact. Recently, we developed this model further to predict consumption rebound effects. Rebound effects may e.g. occur when environmental policies lead to a cost reduction and, as a consequence, more money is available to households for additional consumption, offsetting (part of) the intended environmental gains. Moreover, with data mining, machine learning techniques and by interlinking various existing models we generated a spatial model platform that predicts a realistic consumption behavior for each household in Switzerland. Current efforts are targeted towards using machine learning and regression analysis to predict the material composition of buildings. Finally, we are currently updating a tool to predict chemical inventories, based on an existing neural-networks based tool that we had co-developed to predict the energy demand of chemical production as a function of the functional structure of chemicals.  

Current Research Projects

Finished Research Projects

 

New technologies’ impacts are difficult to assess because little is known on their future environmental performance. However, a prospective assessment of new technologies is of tremendous importance in order to avoid long-term and extensive environmental effects and to identify proactive strategies to prevent adverse impacts before they occur. In our research, we address the hot spots of such technologies and implement methods for prospective assessments like scenario analysis into LCA. We also combine scenario analysis with material flow analysis and life cycle assessment to develop strategies for sustainable resource management and waste management. Finally, we quantify the effect of technology learning and scaling on the trajectory of  environmental impacts of new technologies, to enable a fair comparison between mature and new technologies.  

In our teaching activities, we dedicated one master-level class to this topic (Prospective Environmental Assessment).

Current Research Projects

Finished Research Projects

Global supply chains have become increasingly connected worldwide. For example, many materials, food, and fuels are extracted and processed in another country than ultimately consumed. Hence, the environmental impacts of commodities produced in one country are linked to the consumption somewhere else on the globe. Due to imports, high-income regions, in particular, have increasingly shifted their consumption-based environmental impacts, called footprint, to regions with less stringent environmental policies, high water stress, and greater biodiversity loss. For example, two-thirds of the Swiss carbon footprint is caused abroad nowadays. Thus, improved supply chain management is crucial for sustainable consumption. In our research, we combine enhanced multi-regional input-output analysis (a top-down approach in LCA) with regionalized impact assessment methods to map global supply chains and their environmental impacts. This allows us to bridge the information gap from the local scale of resource extraction to the international scale of processing, manufacturing, and final consumption while addressing the key environmental issues listed by the United Nations agenda. Our goal is to explore more sustainable supply chains measures to provide decision support for industry and policy and promote supply chain management.

Current Research Projects

Finished Projects

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