A circular economy (CE) aims to decouple economic growth from resource consumption by cycling products and materials back into production, either by returning materials to generate new products, or by releasing benign substances to the environment through degradation.
Circularity can be embedded into products during the design phase, but such a transformation would require fundamental shifts in the way resources are extracted, products are designed, and businesses and consumers are engaged for reuse and recycling, along with a concurrent deployment of supporting energy, mobility, and end-of-life management infrastructure. Such a transformation would not only achieve environmental goals, but could also contribute to social and economic development.
While circular economy is advancing in Europe and Asia, CE is greatly lacking in the US. Moreover, current efforts in this domain are typically placed within disciplinary silos, leading to an incomplete understanding of system dynamics.
Achieving circularity will require transformative research that deeply integrates across engineering, architecture, logistics and operations, data science, chemistry and chemical engineering, and biology fields, to name a few.
Convergent circular economy research requires transdisciplinary teams to study not only their engineering designs, economic models, and the culture, but will also emphasize the connections between those components. We have assembled a team of chemical, environmental, and civil engineers, anthropologists, economists, and political scientists to engage in convergent research around CE. Our main areas of investigation are highlighted below.
This work is funded by the National Science Foundation:
Collaborative Research: Growing Convergence Research: Convergence Around the Circular Economy (Grant No. 1934824)
Closing resource loops
Closing resource loops involves either creating products and components that can be easily and safely absorbed by the biosphere, or creating items that while they cannot be released to the ecosystem, can be easily recycled to high-value uses. As such, closing loops involves (a) Design for a biological cycle, (b) Design for a technological cycle, (c) Design for disassembly and reassembly.
We address closing resource loops and design for disassembly by addressing the technical and scientific challenge of how we formulate, produce, and use material resources to reduce consumption and its environmental impact while also creating new ways to cycle these resources back into use at end-of-life, while considering the environmental impacts. Plastic products are a key case study, with an emphasis on molecularly-designed products for disassembly, and reuse, while also considering associated economic, business, and environmental drivers and barriers, via the new general equilibrium behavioral-economic model that incorporates insights from psychology and anthropology and consider non-optimizing, highly socialized behavior. We address the societal challenge of global plastic waste.
We are specifically focusing our technical challenge on thermosets: co-PI Eric Beckman is working to create an inherently recyclable thermoset composite system. Thermosets can be polymers, plastics, and/or resins hardened by curing. Thermosets produce intractable products that cannot be reprocessed, nor can the individual components be separated for reuse. Thus, this significant market ends up as waste. Thermosets span many household products such as polyurethane (e.g., shoe soles and foams) and melamine resins (e.g., hard surfaces), to industrial products that include windmill blades or aerospace designs. In the built environment, thermosets are often found in insulation systems, adhesives, coatings and paints, and fiber composites. We aim to investigate this product from the molecule to the product to the sector (see figure below).
While we are focusing on plastic reformulations, many of these same ideas can be applied across products and sectors, including other products in the construction sector.
While it might be assumed that circular designs are more sustainable than their throw-away analogs, this is not necessarily true. There is a need to adopt life cycle environmental analysis to products that are designed to move in loops. However, even with established standards, LCA application to emerging circular systems faces key uncertainties, including challenges of modeling multiple life cycles, changing product functionality, and integrating disparate data sources associated with new materials, products, and systems. Solving these challenges requires methodological innovations in LCA to account for rapidly evolving product systems under data uncertainty. We are leading research to further develop and apply a Dynamic LCA (DLCA) framework that specifically applies to evaluating CE solutions. A specific case will be to connect interacting models of buildings and the construction sector ) and the polymer-based materials that are used in construction.
We are using LCA to guide the design process with iterative feedback loops (design-evaluate-redesign-re-evaluate) that will inform sustainable and circular economy decision-making to preclude future realization of unintended consequences of CE designs.
Slowing resource loops
Design for slowing resource loops includes design for longer-life and product life extension. In design for longer life, one aims to create more robust products with longer viable service lives, while also creating designs to which consumers become emotionally attached. Product life extension can be achieved through several strategies: (a) Design for ease of maintenance and repair, (b) Design for upgradability and adaptability, (c) Design for standardization and compatibility, and (d) Design for dis- and re-assembly (see figure below).
We address slowing resource loops through design for standardization and enabling a new business model to support extending product value. We argue that we cannot create a circular economy without a clear system for asset and material tracking. One promising solution to asset and materials tracking is blockchain.
Blockchain offers an approach that can greatly facilitate retention of value within the circular economy. It is an encrypted peer-to-peer network that promises enhanced trust, security, and reduced transaction costs. Each block contains a set of data and is represented by a unique cryptographic hash (a digital fingerprint). The header for each data block stores the hash for the previous block, thus creating a “chain” of encrypted data.
There are significant opportunities in employing circular economy and blockchain in the building and construction sector. One could track the materials in the buildings, the quality of the materials, and then potential materials available during deconstruction, with buildings serving as ‘material banks.’ We are exploring how to integrate CE in existing building technologies and platforms, such as Radio-Frequency Identification (RFID) and Building Information Models (BIM). We propose the development of the Blockchain Enabled Asset Tracking System (BEATS), in which circular economy goals are realized through superposition of the database onto life cycle stages (see figure above). We plan to illustrate how BEATS can be operationalized, with building-level data from UPitt and Mascaro Contruction.
Fostering circular economy convergence research
By deeply integrating diverse disciplines, research converges upon solutions to complex challenges facing society today. Convergence can be difficult to achieve, given current cultural and institutional roadblocks that have created the silos of disciplinary structures. Complexity Leadership Theory (CLT) provides a framework to re-conceptualize knowledge-producing organizations whose desired outcomes are learning, adaptability, and innovation. Instead of focusing on individual behaviors, CLT focuses on the interactive dynamics of the collective.
Guided by the CLT framework and led by our co-PI Gemma Jiang, we are implementing complexity-sensitive developmental evaluation (DE) methodologies. We are exploring emergent behaviors in complex, dynamic social networks to initiate and sustain convergent research; evaluate the influence of social networks on attitudes of individual members; capture the complexities of a multifaceted experience, and provide a useful case for transdisciplinary research communities. We anticipate that our research network will evolve to a more robust state; our ability to monitor this progress will enable effective intervention to strengthen nascent initial connections.
The DE plan includes social network analysis. This method provides network visualization and metrics to aid in diagnostics of the overall network structure of the community and each individual. An increasingly robust network is evidence for convergence. Social network analysis examines relationship patterns among interacting and interdependent agents. . Social network analysis with ORA returns network visualizations, as well as network- and agent-level metrics (see figure below). These results can be used for performing diagnostics and devising evidence-based intervention.
By examining network structures as a whole, we can understand how well information and ideas are flowing through the organization and make changes. If we identify disconnection between major disciplinary groups, we can design strategies to connect them. Agent-level network measures provide insights on each individual’s level of integration into the network. In addition, we are evaluating the effects of network dynamics on desired outcomes, such as research progress. We expect to see the network structures among our team to become more robust. The evolution of network structures will provide convincing evidence for convergence in our approaches. We also expect individuals already at strategic positions to become more capable of taking advantage of their network positions, and individuals in peripheral positions to become more integrated as we apply networked interventions.
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