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Long-term lifetime trends of large appliances since the introduction in Norwegian households
Abstract
Longer lifetimes of consumer products are promoted as an element of sustainable consumption, yet there is a widespread notion that lifetimes are currently in decline, often attributed to planned obsolescence or throwaway mentality. However, empirical evidence is inconclusive and often subject to high uncertainties. Here, we explore long-term trends in the lifetimes of large household appliances using dynamic material flow analysis (dMFA). We investigate the sales and ownership of these products since their introduction in Norwegian households and use this co-evolution to estimate the lifetimes. By combining two model types with uncertainty analysis, we show that a significant lifetime decrease was likely experienced only by washing machines (-45%) and ovens (-39%) around the 1990s-2000s. This finding challenges the narratives about planned obsolescence despite their prevalence decreasing consumer incentives for longer product use and repair. We suggest multiple technical, economic, and social factors that could be responsible for the decrease, e.g., a reduction in relative prices of appliances or changes in habits surrounding laundry and kitchen use. Our results suggest that factors affecting product lifetimes are not uniform but context-dependent, which has implications for lifetime extension policy. The presented method could help monitor the long-term effectiveness of such policy.
... Let us consider a case study in which we demonstrate how the lifetime modeling framework can be applied to the system of dishwashers in Norwegian households. Studying the stocks and flows of large household appliances like dishwashers is relevant due to their energy consumption in the use phase (Ardente & Talens Peiró, 2015) and their content of metals and electronics (Magalini et al., 2017 from the purchase by the first user until the end-of-use by the last user, has been shown to be stable at around 15 years (Krych & Pettersen, 2024). ...
... We model flows and stocks of domestic dishwashers in Norway from 1950 to 2050. The baseline lifetime is assumed to follow the Weibull distribution with the shape parameter k = 1.65 and the scale parameter = 16.7 based on the findings from previous studies (Krych & Pettersen, 2024;Wang et al., 2013), resulting in a mean lifetime of approximately 14.9 years. For the historical years, we created an inflow-driven model based on data collected from national statistics on sales, production, and trade (Elektronikkbransjen, 2023;Statistics Norway, 1959-1960b, 1959-1960a, 1961-1967, 1961-1987, 2023a. ...
... The number of dwellings was calculated using drivers such as population (Statistics Norway, 2023b, 2023c), number of people per dwelling (Statistics Norway, 1895, 1904, 1913, 1952, and number of recreational cabins per person (Aasmundstad, 1981;Statistics Norway, 1976, 2023b, 2023c, 2024a, 2024b. Recreational cabins with a high technical standard (including electricity access and likely also dishwashers) became common only recently (Aall et al., 2011), and we considered this factor using the same method as Krych and Pettersen (2024). ...
Product life extension is often portrayed as one of the pillars of the circular economy since longer lifetimes slow down material turnover rates and thus decrease resource use and associated emissions. Strategies for product longevity can involve addressing the product “nature” (inherent product durability) or “nurture” (external factors). Yet, in most dynamic material flow analysis (dMFA) studies, lifetime is an intrinsic property of the cohort assigned “at birth,” so “nurture” strategies such as repair or reuse cannot be explicitly considered. Here, we introduce a Python‐based tool for comprehensive modeling of lifetime changes in dMFA, including three dimensions of lifetime: age, period (time), and cohort. The tool employs the hazard function, which directly links the outflow to the preceding year's stock, allowing for differentiating the influence of product nature and nurture on lifetimes. The tool supports dynamic stock and flow calculations and is compatible with ODYM, a commonly used dMFA framework. We apply the tool to a case study on dishwashers in Norway to illustrate nature‐ and nurture‐focused lifetime extension strategies. The framework enables linking product lifespans with events such as economic crises and pandemics. It can serve to model life extension scenarios in dMFA that (i) extend the lifetime not only of the new products entering use but also of the products already in use, thus achieving faster effects; and (ii) expand the group of potential stakeholders beyond producers and designers to, for example, consumers, repairers, and resellers. This article met the requirements for a gold‐gold JIE data openness badge described at http://jie.click/badges.
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