As the global community faces unprecedented climate change challenges, the transition towards a sustainable society has become an urgent priority. The complexity of this transition is characterised by the interplay of developing and implementing green manufacturing processes, integrated energy systems, and circular resource flows, and the inherent dynamics associated with geopolitical uncertainties, energy price fluctuations, and global instability. Although new technological advancements and more sustainable models are on the rise, a significant knowledge gap remains in comprehending the intricate dependencies and impacts of various uncertainties on complex industrial and energy systems. Dependency means that one component, sub-system, or variable relies on another for its operation or effectiveness. A change in one element will directly affect the other, causing changes in its status or actions. Because the components are interconnected in this way, they are not independent of each other. This knowledge gap is particularly noticeable in the lack of a comprehensive understanding of the interactions between the energy system and uncertainties. This became significantly more apparent during events such as the COVID-19 pandemic and the sub-sequent Russian invasion of Ukraine.  

The aim of this thesis is threefold: 1) to explore identified outcomes and values in industrial symbiosis collaborations within the context of the circular economy; 2) to assess electricity dynamics under the influence of uncertainty, focusing on the Swedish industrial sectors; and 3) to present a frame-work for evaluating integrated and circular systems and the potential influencing uncertainty mechanisms.  

The motivation for this research comes from the limited understanding of the dynamics in future sustainable industrial systems and how intended out-comes may be affected by various unexpected events or shocks. The increasing complexity and interconnectedness, including global links, call for a broader perspective that encompasses more than just technical aspects, acknowledging a broader set of interconnections between system components. Therefore, it is important to consider not only the interactions be-tween the components of the system but also their connections to the global environment.  

This thesis aims to fill this gap by exploring the aspects of outcomes and values in circular solutions and uncertainty’s influence on the electricity system. 

The results reveal that circular solutions in industry aim for resource efficiency, focusing mainly on short-term economic values through optimising material use, energy utilisation, water use, and waste exchanges. The results also reveal that research in circular approaches emphasises energy and environmental aspects, particularly CO2 reduction, where values are derived through market-based valuation. The shorter time horizons in the research literature signal a focus on immediate gains, with values based on non-market valuation underrepresented. In this context, non-market valuation refers to the assignment of monetary values to goods and services that are not usually traded in conventional markets. Examples include environmental as-sets such as clean air and water, as well as social and cultural assets.  The results also underscore that uncertainty significantly influences electricity utilisation across various Swedish industrial sectors and power sources. However, depending on the type of uncertainty measure, such as global or domestic uncertainty, the impact of uncertainty affects different industrial sectors in distinct ways, and the results also unveil industry-specific dependency structures.  This analysis shows the importance of understanding how industrial electricity utilisation interacts with various sectors and power sources, as well as the role of uncertainty. This understanding is especially vital considering its potential impact on interconnected resource flows and integrated energy systems. The findings also present a preliminary foundation for developing a framework capable of evaluating integrated and circular systems, encompassing aspects such as institutional units, symbiosis categories, outcome classification, connectivity, and time aspects, all while considering the influence of uncertainty.