Product reuse advances circular economy by reducing material demand. However, environmental assessments often assume reused products fully replace new ones, or they overlook market changes and shortened lifespans driven by resale and repurchase opportunities. This study presents an empirically based analysis of the second-hand smartphone market and its cumulative effects on manufacturing demand and carbon emissions. Integrating consumer survey data and product lifetime estimates in a stock-and-flow model, we find that in the United States, each second-hand transaction currently extends smartphone use time by 40%, displaces 0.40 new devices, and that circular consumption results in a 34% lower annual carbon footprint. With 25% of consumers purchasing used phones, production demand and carbon emissions are lowered by 15% and 14%, respectively. Yet, shortened use times offset nearly half the potential gains. If reuse became the norm, manufacturing demand could decline by one-third, revealing both the promise and the limits of reuse.

Understanding the detailed material composition of the various industrial and consumer products is essential for implementing efficient recycling practices and policies, conducting material flow analyses, and facilitating a transition toward a circular economy. However, existing data sources are limited in their product and material coverage. Currently, no source or methodology allows such data to be obtained in a relatively uniform, updated, and accessible manner across a diverse range of products. This work presents an approach that allows estimating the material composition of thousands of products using available life cycle inventory (LCI) databases. Methodologically, this is implemented by splitting the physical flows that describe supply chains in LCI databases into “incorporated” and “not incorporated” fractions using an incorporation parameter. Building primarily on existing matrix-based life cycle assessment calculations, this approach can be used to calculate the material content of products. A generally applicable mathematical model, as well as a ready-to-use software, is presented for future practitioners. To demonstrate the robustness of the proposed method, a case study involving three metals and plastic in three consumer goods has been conducted based on the ecoinvent database. Our method delivered accurate material content estimates (i.e., weight fractions of materials in products) with an average relative error of 26% and an absolute error of 1.1% (between our estimates and existing values).

Data on the total product lifetimes, which is much needed in the fields of sustainability and circularity assessment, is currently sparse and challenging to measure. To meet such data and methodological needs, the first information system of its kind has been developed as part of this research. While an online portal collects and stores consumer reports on use and disposal patterns for various electronics owned and used, the harvested survey data was automatically fed into a novel stochastic model that allowed estimating the total lifetimes and durability of the different products considering the impacts of second-hand use. This was done without reliance on auxiliary market statistics and costly facility-based analysis while preserving a satisfactory degree of accuracy. Additionally, the structure of the collected data allows for measuring the effects of the different circular practices (repair, reuse, recycling, etc.) on product longevity which is of specific interest to researchers and policymakers.

Car-sharing platforms provide access to a shared rather than a private fleet of automobiles distributed in the region. Participation in such services induces changes in mobility behaviour as well as vehicle ownership patterns that could have positive environmental impacts. This study contributes to the understanding of the total mobility-related greenhouse gas emissions reduction related to business-to-consumer car-sharing participation. A comprehensive model which takes into account distances travelled annually by the major urban transport modes as well as their life-cycle emissions factors is proposed, and the before-and-after analysis is conducted for an average car-sharing member in three geographical cases (Netherlands, San Francisco, Calgary). In addition to non-operational emissions for all the transport modes involved, this approach considers the rebound effects associated with the modal shift effect (substituting driving distances with alternative modes) and the lifetime shift effect for the shared automobiles, phenomena which have been barely analysed in the previous studies. As a result, in contrast to the previous impact assessments in the field, a significantly more modest reduction of the annual total mobility-related life-cycle greenhouse gas emissions caused by car-sharing participation has been estimated, 3–18% for three geographical case studies investigated (versus up to 67% estimated previously). This suggests the significance of the newly considered effects and provides with the practical implications for improved assessments in the future.