Accounting Material Rebound in LCA of Emerging Technology: A case study of Quantum Dot-enabled Display Devices

Recently, researchers of industrial ecology and life cycle assessment (LCA) have begun adapting the concept of rebound effect from the context of energy use to other environmental metrics.Accounting for environmental rebound... [ view full abstract ]

Recently, researchers of industrial ecology and life cycle assessment (LCA) have begun adapting the concept of rebound effect from the context of energy use to other environmental metrics.Accounting for environmental rebound is essential for estimating environmental impacts, as it helps to avoid overestimation of environmental benefits of emerging technologies and products.This work proposes an iterative probabilistic rebound-LCA framework that not only estimates conventional rebound due to changes in consumer behavior, but also considers the rebound resulting from substitution of materials and manufacturing processes. Such analysis of environmental rebound at both production and consumption stages allows the comparison of competing technologies and material variants that contribute different efficiency improvements to the final product. Rebound effect is computed in terms of existing lines of products incorporated with technological improvements that provide efficiency gains. The proposed framework for assessing rebound of emerging products is compatible with a comparative anticipatory LCA framework. To demonstrate the utility of this framework, we compute rebound-adjusted environmental impacts for quantum dot (QD)-enabled technology for next generation displays that are energy efficient and provide a large color gamut.To account for production-side rebound, or the increase in demand for a product due to increased efficiency provided by emerging technologies, we leverage the advances made in data storage and management for modeling the scale of demand for a consumer product by different demographic segments. Retailers like Amazon and Wal-mart use clustering techniques to determine their marketing mix (commonly referred to as 4Ps: product, price, place, promotion)for different segments. This information is integrated with diffusion theory to capture socio-economics dynamics and other factors (like economies of scale, imitation, etc.) that contribute to market penetration of an innovation in order to estimate its rate of adoption. For computing the consumption-side rebound, we model the patterns of use of an emerging technology and identify factors that influence consumer decisions based on insights from data collected through surveys and focus groups. These methods offer an understanding of whether and how the introduction of emerging technologies affects consumer behavior in different market segments. Production and consumption-side rebound effects adjust environmental impacts associated with different product lines such as smartphones and TVs by accounting for rebound associated with different QD type used (cadmium and indium QDs) and the mode of incorporating the QDs in displays (on-edge and on-surface).  From this analysis we note that rebound for a given emerging technology and different pathways for its production varies depending on the product it is incorporated in. We observe a greater rebound associated with consumer behavior for QD-enabled display technology in smart phones than in televisions, since phones with energy-efficient displays result in longer battery lives for consumers, which means more use. Moreover, products with greater consumption rebound (i.e.smartphones) also tend to demonstrate greater difference in production rebound of competing technologies (CdQDs over InQDs). This information not only allows manufacturers to understand the implications of their design decisions but also enables targeted product-specific policies.