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- Müller, Esther, et al.
(författare)
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Modeling Metal Stocks and Flows : A Review of Dynamic Material Flow Analysis Methods
- 2014
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Ingår i: Environmental Science and Technology. - : American Chemical Society (ACS). - 0013-936X .- 1520-5851. ; 48:4, s. 2102-2113
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Forskningsöversikt (refereegranskat)abstract
- Dynamic material flow analysis (MFA) is a frequently used method to assess past, present, and future stocks and flows of metals in the anthroposphere. Over the past fifteen years, dynamic MFA has contributed to increased knowledge about the quantities, qualities, and locations of metal-containing goods. This article presents a literature review of the methodologies applied in 60 dynamic MFAs of metals. The review is based on a standardized model description format, the ODD (overview, design concepts, details) protocol. We focus on giving a. comprehensive overview of modeling approaches and structure them according to essential aspects, such as their treatment of material dissipation, spatial dimension of flows, or data uncertainty. The reviewed literature features similar basic modeling principles but very diverse extrapolation methods. Basic principles include the calculation of outflows of the in-use stock based on inflow or stock data and a lifetime distribution function. For extrapolating stocks and flows, authors apply constant, linear, exponential, and logistic models or approaches based on socioeconomic variables, such as regression models or the intensity-of-use hypothesis. The consideration and treatment of further aspects, such as dissipation, spatial distribution, and data uncertainty, vary significantly and highly depends on the objectives of each study.
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- Thiebaud, Esther, et al.
(författare)
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Use, Storage, and Disposal of Electronic Equipment in Switzerland
- 2017
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Ingår i: Environmental Science and Technology. - : American Chemical Society (ACS). - 0013-936X .- 1520-5851. ; 51:8, s. 4494-4502
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Tidskriftsartikel (refereegranskat)abstract
- Electronic devices contain important resources, including precious and critical raw materials. For an efficient management of these resources, it is important to know where the devices are located, how long they are used and when and how they are disposed of. In this article, we explore the past and current quantities of electronic devices in the in-use stock and storage stock in Switzerland and quantify the flows between the use, storage and disposal phase with dynamic material flow analysis (MFA). Devices included are mobile phones, desktop and laptop computers, monitors, cathode ray tube and flat panel display televisions, DVD players, and headphones. The system for the dynamic MFA was developed as a cascade model dividing the use phase in first, second and further use, with each of these steps consisting of an in use stock and a storage stock for devices. Using a customized software tool, we apply Monte Carlo simulation to systematically consider data uncertainty. The results highlight the importance of the storage stock, which accounts for 25% (in terms of mass) or 40% (in terms of pieces) of the total stock of electronic devices in 2014. Reuse and storage significantly influence the total lifetime of devices and lead to wide and positively skewed lifetime distributions.
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- Thiebaud (Mueller), Esther, et al.
(författare)
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Service Lifetime, Storage Time, and Disposal Pathways of Electronic Equipment A Swiss Case Study
- 2018
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Ingår i: Journal of Industrial Ecology. - : Wiley. - 1088-1980 .- 1530-9290. ; 22:1, s. 196-208
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Tidskriftsartikel (refereegranskat)abstract
- Product lifetime is an essential aspect of dynamic material flow analyses and has been modeled using lifetime distribution functions, mostly average lifetimes. Existing data regarding the lifetime of electronic equipment (EE) are based on diverging definitions of lifetime as well as different temporal and regional scopes. After its active use, EE is often not disposed of immediately, but remains in storage for some time. Specific data on the share of EE that is stored and the time they remain in storage are scarce. This article investigates the service lifetime, storage time, and disposal pathways of ten electronic device types, based on data from an online survey complemented by structured interviews. We distinguish between new and secondhand devices and compute histograms, averages, and medians of the different lifetimes and their change over time. The average service lifetime varies from 3.3 years for mobile phones to 10.8 years for large loudspeakers, the average storage time from 0.8 years for flat panel display televisions to 3.6 years for large loudspeakers. Most service lifetime histograms are positively skewed and show substantial differences among device types. The storage time histograms, being more similar to one another, indicate that the storage behavior is similar for most device types. The data on disposal pathways show that a large proportion of devices are stored and reused before they reach the collection scheme.
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