Comparative Analysis of Small WEEE Pre-treatment Options: An Economic and Environmental Assessment

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Small WEEE (sWEEE) have recently received increased attention by legislators that have recognised the improvement of this deficiency as an integral part of mitigating associated greenhouse-gas emissions and transforming the EU's economy towards carbon neutrality. Different sWEEE pre-treatment methods are currently in use, which pose a range of economic and ecological impacts. This study examines the economic properties and potential impacts on climate change of the different sWEEE pre-treatment options that currently exist in Germany for eight devices representative of sWEEE. A consequential bin-to-cradle life cycle assessment (cLCA) and an extended Life Cycle Costing (LCC) were conducted to identify the most beneficial pre-treatment option for each device regarding economic feasibility and greenhouse-gas emissions. The results indicate improvement potential in both aspects, particularly for the reduction of greenhouse-gas emissions, by pre-treating the device classes differently from the current status quo. Furthermore, discrepancies between most profitable and least greenhouse-gas-intensive pre-treatment option were found. Electronic Waste E-Waste WEEE cLCA LCC Figures Figure 1 Figure 2 Figure 3 Introduction With a constantly increasing amount of waste electrical and electronic equipment (WEEE) and the scarcity of certain resources required for electrical and electronic equipment (EEE) production, the management of WEEE is becoming a growing concern. According to the Global E-waste Monitor (Baldé, et al., 2017), an estimated 53.6 million tons of e-waste were generated worldwide in the year 2019. WEEE often contains critical elements, such as rare earth metals or precious metals, which are in some cases concentrated at higher levels than in traditional mines, and thus poses significant Urban Mining potentials – in particular for the European Union (EU), which is scarce of natural deposits for many elements needed for a high-tech economy (European Comission, 2023). To address this xissue, the EU has introduced the Circular Economy Action Plan (European Comission, 2020) that includes a list of critical elements necessary for electronic device production. Moreover, e-waste management offers potential economic benefits. Recycling e-waste can create jobs and generate revenue, while also reducing the environmental impact of the waste (Baldé, et al., 2017). Understanding the various End-of-Life (EoL) treatment pathways for WEEE and their characteristics is crucial to ensure an effective management of this waste stream. This requires the identification of the potential environmental and economic implications of each approach – not just in general, but for different types of WEEE devices. In this study, the pre-treatment of eight small WEEE (sWEEE) devices according to three different treatment methods currently employed in Germany will be modelled with regards to economic feasibility and their potential impacts regarding climate change. The reviewed pre-treatment options for sWEEE are manual dismantling, mechanical processing, and direct smelting (Table 1). Subsection: State of the art While the recovery rates of the actual treatment processes for the main fractions in sWEEE, in particular many precious and semi-precious metal fractions (Cu, Au, Ag, Pd, Pt), are already very high at around 95 %, the overall recycling efficiency for sWEEE is still lacking. Works such as (Hagelüken & Goldmann, 2022) have shown that amongst the three EoL phases 1. collection, 2. pre-treatment, 3. end-treatment for WEEE, the first two steps have the lowest material recovery rates. For elementary gold, the total recycling rate only reaches 67 % which can mostly be attributed to the low efficiency in pre-treatment (Hagelüken & Goldmann, 2022). The precious and semi-precious metals make up for a significant economic share which makes them a key factor for WEEE recycling enterprises (Bigum, et al., 2012). They are thus in the focus of the modelling in this study, whereas other fractions, no matter their mass relevance have comparatively little economic impact and are thus modelled in a simplified way. In general, the goal of the pre-treatment is 1) the liberation and 2) the concentration of valuable fractions as well as 3) the removal of pollutants (Batinic, et al., 2017). The sWEEE pre-treatment procedures currently widely established are manual dismantling (A), mechanical liberation (B) and direct smelting with preceding pollutant removal (C). Their characteristics are briefly presented in Table 1. Table 1: Three Different sWEEE Pre-treatment Procedures Applied in Germany (PCB: Printed Circuit Board) Pre-treatment method Process description Characterstics of devices A: Manual Dismantling Device is dismantled by hand, which allows for separation of high-value components (and others) without heavy losses Low component complexity, easily dismantable B: Mechanical processing Device is shredded or physically stressed until it breaks open. The resulting fractions are sorted (fractions: ferrous metals, PCB's and semi-precious metals, light metals, plastics etc.) Low economic potential (usually very low-grade or small PCB) C: Direct smelter feeding Device is wholly fed into a secondary Cu-smelter. Precious and semi-precious metals are recovered, less noble metals are lost in slag, organic materials are consumed thermally. If necessary, pollutants need to be removed from device (e. g. batteries) High-grade components (e. g. PCB), high component complexity Materials and Methods The latest version of the German law on electric and electronic devices (Elektro- und Elektronikgesetz – ElektroG) released in 2022 requires EEE retailers of a certain size to take back and dispose of any WEEE that is smaller than 25 cm in length, and all collected WEEE to be sorted and treated in accordance with environmental standards (Deutscher Bundestag, 2015). It is therefore expected that an increased waste stream of the affected EEE products will occur in the coming years. Hence, WEEE devices which are smaller than 25 cm (in the following referred to as small WEEE or sWEEE) are in the focus of this research. Eight device types from the sWEEE category that are largely representative of sWEEE were chosen for modelling: smartphone, router, remote control, MP3 player, USB stick, DVD player, digital camera and tablet computer. In order to explore the improvement potential of economic flows and greenhouse-gas emissions of the sWEEE pre-treatment status quo in Germany and to determine this improvement margin, all three presented options are modelled for each device and compared to the current status quo. To properly reflect the losses of (semi-)precious metals of device components that occur in options A and B but not in C (due to lack of comminution), the copper smelter process was modelled as well, though it is not part of the pre-treatment stage. This was done to ensure comparability between all three options. The system boundaries of three sWEEE pre-treatment pathways are illustrated respectively in Figure 1. A consequential bin-to-cradle Life Cycle Assessment (LCA) and an extended Life Cycle Costing (LCC) were carried out. LCA's are standardised in the ISO 14040 and 14044, according to which they mus contain the four phases 1. Goal and Scope Definition, 2. Life Cycle Inventory (LCI), 3. Life Cycle Impact Assessment (LCIA) and 4. Interpretation (DIN Deutsches Institut für Normung e. V., 2009). The Goal and Scope Definition and Life Cycle Inventory phases are briefly explained in this chapter. Inventory lists can be found in the Supplementary Material (Tables 1-4). The LCA only focuses on the impact category climate change . The LCA’s function is the pre-treatment of sWEEE in Germany. SWEEE is to be understood as a placeholder for any of the eight chosen device types. The functional unit is defined as the pre-treatment of 1 kg of sWEEE in Germany. The reference flows are thus 1 kg of waste smartphones, 1 kg of waste routers, etc. The temporal scope ranges from 2017 to 2022 which is the timespan from which the modelled processes stem. The geographical scope is Germany. The LCC is not only considering costs and expenses but also revenue. Its results are in the following referred to as monetary value , the unit is Euros. The LCC results are calculated similarly to the LCA results in that each material flow is assigned a Global Warming Potential (GWP) and monetary value property, which is then summed up for each process. While Costs are expressed as negative monetary value, the revenue is modelled positively. Positive overall monetary values thus indicate that a process is economically feasible. The multi-property process modelling approach, which was developed by Fraunhofer IWKS and initially introduced in \cite{klemenz2021mppm}, is used to build the process chains of the pre-treatment options. For more details, see Supplementary Material Figure 1. While the inputs were determined by expert consultation and literature research, the outputs are not only process- but also device-specific. Thus, the material fractions of a device were transformed into the outputs with the help of process-specific transfer coefficients (Supplementary Material Table 5). Material fractions that are not cleanly liberated and separated cannot be found in their respective output fraction and are lost and seen as waste. The coefficients are arranged in a matrix format, while the original device composition is required as a vector. The resulting output fractions can then be calculated as another vector by multiplying the device composition with the process-specific transfer coefficient matrix. To minimise inaccuracies caused by imprecise modelling of the copper smelting route, only the differences between two treatment systems for the same device are evaluated, because the metallurgical process was modelled similarly for all pre-treatment options. The data was collected by screening literature, conducting experiments and interviewing experts. For example, the output fractions of the processes were determined by combining a bill of materials with process-specific transfer coefficient matrices, which were taken from literature and expert interviews. The background database used for GWP calculations was ecoinvent v3.8 consequential, the reference time horizon of which is 2021. The data for the composition of devices was taken from (Babbit, et al., 2020).Precious metal recovery rates are based on (Schops, et al., 2010). Results The pre-treatment according to the status quo, and the optimal pre-treatment based on the result of the modelling are demonstrated in Table 2. The values for GWP are stated in kg CO 2 -eq. per kg device (minimisation desired), while monetary value is expressed as Euro per kg of device (maximisation desired). For both parameters, the difference to the status quo pre-treatment is listed. A difference of zero indicates that the optimal process is already employed. The best pre-treatment path may vary for GWP and monetary value. Which one is utilized depends on the prioritisation of the parameters. Table 2: Status Quo Pre-treatment and Optimal Pre-treatment According to the Modelling Regarding Both GWP and Monetary Value in Comparison With the Respective Improvement Potential (A: Manual Dismantling, B: Mechanical Processing; C: Depollution and Smelting). 1: CITATION San19 \l 1031 (Sander, et al., 2019) , 2: CITATION Hag06 \l 1031 (Hagelüken, 2006) , 3: CITATION Bun18 \l 1031 (Bund/Länder-Arbeitsgemeinschaft Abfall (LAGA), 2018) , 4: CITATION Gri22 \l 1031 (Grieger, 2022) Device Status quo pre-treatment ∆GWP ∆Monetary value Treatment path Savings potential per kg [kg CO2-eq.] Treatment path Affitional generated value per kg [€] DVD Player B 1 A -0.86 A 1.07 Digital camera C 2 A -2.49 C 0 Tablet computer C 3 A -3.22 A 0.28 USB stick B 1 C -3.78 B 0 MP3 player C 3 A -9.90 C 0 Remote control B 4 C -4.13 B 0 Router B 4 C -6.11 A 3.53 Smartphone C 3 A -3.22 C 0 Regarding monetary value, the conventional treatment of mechanical liberation is preferable for 2 of the 8 investigated device types. The remaining device classes are split evenly between manual dismantling and direct smelting with 3 of the 8 classes each. Digital camera, USB stick, MP3 player, remote control and smartphone devices are currently already pre-treated in the optimal way. The treatment of DVD player, tablet computer and router devices can be improved by manually dismantling them, however this improvement margin is rather small. The potential can be ascribed to the low dismantling time of these devices relative to their content of valuable components. Regarding the impact category climate change, the best pre-treatment path is mostly the manual dismantling. Only for USB stick, remote control and router devices, the direct smelter feeding option is to be preferred. This can be explained by the low losses of (semi-)precious metals during pre-treatment in both pathways compared to the Mechanical Processing. The option with the lowest emission intensity is not yet employed for any of the devices. The total potentially avoidable greenhouse-gas emissions for the considered devices on a national scale are displayed in Table 3. A contribution analysis was done for processes within their respective product system. The analysis is shown exemplary for the GWP and monetary value of the pre-treatment path A (Manual Dismantling) for all eight devices. Figure 2 graphically shows the analysis results for the Smartphone. The results of the process contribution analysis show a high significance of the copper smelter process regarding both GWP and monetary value for every pre-treatment option. For some devices an increased importance of the manual dismantling step was identified regarding monetary value. The comminution and sorting process in pathway A showed very little environmental and monetary impact in comparison with the other process steps. The smelting process also dominates the impacts for GWP and monetary value in the pathways B and C. To further investigate this, a flow contribution analysis was conducted exemplarily for the smartphone. The flow contribution analysis for smartphone devices showed that the recovered gold alone, which substitutes the production of primary gold, accounts for 92 % of generated monetary value and 89 % of GWP savings. As shown in Figure 2 the revenue of this process outweighs the operating and investment costs by far, suggesting that the semi-precious metal recovery, especially gold recovery, is of high priority for both economic and environmental parameters. The findings are in general accordance with literature (Bigum, et al., 2012). When investigating the contributions to the manual dismantling process for smartphones, it was found that the manual labour costs are responsible for over 99 % of the total costs of this process. Thus, analogously to the recovery of gold in the metallurgy process, this flow has a strong effect on the entire process chain. Table 3: Improvement Potential of the eight Devices on a National Scale (Germany); a: Estimate Device Amount [t/a] Potential GWP change [kt CO2-eq./a] Additional monetary value [mil. €/a] DVD player 7800 -6.74 8.34 Digital camera 1819 -4.53 0 Tablet computer 4161 -13.40 1.17 USB stick 120 -0.46 0 MP3 player 427 -4.23 0 Remote control 3352 -13.85 0 Router 100 a -0.61 0.35 Smartphone 3257 -10.49 0 Sum -54.30 9.86 Considering the amount of EEE devices entering circulation annually in Germany[], for the eight investigated devices a greenhouse gas savings potential of roughly 54300 t CO 2 -eq. p. a. compared to the status quo was determined. Analogously, by choosing the optimal pre-treatment path according to the model, additional added value of about 9.9 mio. € p. a. could be generated (see Table 3). When interpreting the results and comparing the investigated devices, it must be considered that the LCA’s functional unit is 1 kg of a device and not 1 device. Device weight ranges from 8 g (USB stick) to 3.7 kg (DVD player). This leads to some oddities in the results, for example the manual dismantling step of a USB stick, which is only slightly uneconomical but results in a large cost deficit when scaled up to 1 kg. Discussion In regard to monetary value, the direct smelting path is preferable for compact, high-tech devices such as the digital camera, MP3 player and smartphone, all of which have high precious metal contents but are time-intensive in manual dismantling. The mechanical treatment route can be suitable when devices contain little amounts of precious metals or PCB in general and their main value lies in the non-precious metals/bulk metals. Although this route has the lowest material recovery rates for the precious metals it can be quite economical due to averted labour expenditures, especially for "low-tech" devices like remote controls. The higher the precious metal content in a device, the higher are the absolute losses when passing through a process step with a low transfer coefficient for precious metals. This leads comparatively to exceptionally good results of the copper smelting route for devices with higher precious metal contents. A qualitative representation of the most beneficial pre-treatment paths in dependence of the dismantling time and the precious metal content of devices is shown in Figure 3. Based on the results and illustrated by Figure 3, the trend of preferred pre-treatment shows a similar pattern for GWP and monetary value considering the direct smelting path. Mechanical pre-treatment is not shown in Figure 3 a) as it was not preferred regarding greenhouse-gas emissions for any device in this study. Regarding monetary value, reducing the dismantling time and complexity of several devices shifts the optimal pre-treatment from direct smelting to manual dismantling, thus promoting the more advantageous route in terms of global warming potential. If the best pre-treatment option by GWP shall actually be implemented by pre-treatment facility operators, the two diagrams would have to match exactly. They would need to be incentivised through corresponding policies when their recovery is currently not profitable according to the state of the art. It can thus be considered that market interventions are necessary to get pre-treatment of sWEEE, which is in reality mainly chosen based on economic feasibility, to align with environmental and possibly strategic ambitions. Figure 3 also shows that reducing the dismantling time and complexity of multiple devices shifts the optimal pre-treatment from direct smelting to manual dismantling, thus promoting the more advantageous route in terms of global warming potential. A decreasing precious metal content, which can currently be observed (Zhang, et al., 2017), would diminish potential revenue and thus make mechanical pre-processing more preferrable (shift to the left on the graph). Manual dismantling facilitates high recovery rates for every fraction of interest. Applying economic incentives to the recovery of desired elements is currently in many cases necessary to enable their recycling. From the perspective of total material recovery and critical material recovery, pre-treatment options which result in the fewest losses are desirable, which does not always have to align with the most economical or even most ecological options. Developments such as the ever-decreasing precious metal content in EEE (Zhang, et al., 2017) and uncertain price fluctuations in the primary production of relevant metals make future predictions about the economic drivers difficult. Other than policy changes and economical incentives, labour expenditures could be reduced by making complex, high-grade devices easier to properly dismantle. The so-called ecodesign and design for circularity can already be observed in current niche technology developments (e. g. (Reuter, et al., 2018)) and can be enhanced by current legislation changes such as the EU's right to repair . The fact that mechanical pre-treatment was not found as ecologically optimal for any of the eight devices highlights the importance of high precious metal recovery rates for ecological considerations, in this case the impact category climate change. However, in practice, one major reason which makes a more distinguished pre-treatment inconvenient is the difficult separation of devices from the main WEEE stream that enters the treatment facilities. This is mostly done manually and works better for larger devices. A clear comparison of the different pre-treatment options as it was done in this work is thus best supported by adequate sorting possibilities that allow for improved sorting. A sorting or classification of devices prior to entering the actual pre-treatment could thus aid in achieving the best possible outcome. This could be done in automated sorting machines via image recognition or by reading stored device metadata from a machine-readable product passport which would not just facilitate optimal pre-treatment by correct sorting but also cut on labour costs necessary to screen the WEEE devices. This study highlighted that albeit material liberation is generally desirable, economically feasible pre-treatment without heavy losses can currently not be realised for many, especially smaller, high-grade devices due to their complexity and associated labour costs. Emerging process technology in the field of automated sWEEE liberation without such losses thus seem promising and should be assessed. The electro-hydraulic fragmentation, for instance, is a technology which is designed to break apart strongly-jointed composite materials by emerging them in water and causing shock waves through electrical impulses which stress their material interfaces. (Öhl, et al., 2018) As the system boundaries do not only include pre-treatment steps but also the copper smelting process, it is not advised to directly compare the results of this work to those of other studies, which only cover pre-treatment. Furthermore, due to the method of consequential LCA investigating system changes, only the differences between the recommended pathways and the Status Quo should be used and not the absolute results for both GWP and monetary value. Limitations of this work include a limited number of selected devices that does not represent all devices which are considered sWEEE. Furthermore, the only ecological impact category investigated is climate change , and no statement about other potential environmental consequences can be made. Additionally, the method of modelling is currently static (coefficient matrix) and relies on generic data which does not take into account real-life aberrations like synergy effects. Conclusion This study showed that the pre-treatment of sWEEE in Germany can potentially be improved regarding both greenhouse gas emissions and monetary value. The adaptation of the presented optimised pre-treatment options - possibly in combination with prior separation of devices into classes - poses potential for increased economic and ecological benefits. The precious metal content of sWEEE, which is often proportional to the PCB size and grade, as well as the labour expenditures of manual processes, are the main economic drivers in the pre-treatment process chain. It was shown that these aspects can hinder ecological pre-treatment in favor of profitability. It is necessary that the expected increasing amounts of sWEEE are recycled as best as possible to mitigate greenhouse gas emissions and to prevent losses of critical materials in the EU. Currently economic pre-treatment options for some devices like mechanical comminution and sorting are often not preferable in terms of emitted greenhouse-gases and total material recovery. The implementation of instruments that couple ecological and strategic concerns to the economic feasibility should thus be considered. Developments in the design and production stage of EEE that improve component accessibility or information transfer could help to mitigate the gap between economic and ecological considerations in sWEEE pre-treatment. Declarations Conflict of Interest: The Authors declare no conflict of interest. Author Contribution P. S.: Investigation, data curation, methodology, software, resources, writing - original draft, visualization, formal analysisC. L.: Data curation, methodology, writing, review and editing, supervisionM. V.: validation, writing, review and editingT. M.: validation, review, methodology, project administrationE. I.: supervision Data Availability Data is provided within the manuscript and supplementary information files. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6279511","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":440751354,"identity":"adcc2774-e0b6-424f-ab2b-16bec12bce53","order_by":0,"name":"Philipp Stephani","email":"","orcid":"","institution":"Fraunhofer Research Institution Materials Recycling and Resource Strategies","correspondingAuthor":false,"prefix":"","firstName":"Philipp","middleName":"","lastName":"Stephani","suffix":""},{"id":440751355,"identity":"e03f2009-722a-498b-8403-56a26c013bea","order_by":1,"name":"Chanchan Li","email":"data:image/png;base64,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","orcid":"","institution":"Fraunhofer Research Institution Materials Recycling and Resource Strategies","correspondingAuthor":true,"prefix":"","firstName":"Chanchan","middleName":"","lastName":"Li","suffix":""},{"id":440751357,"identity":"dfcbb0c8-2575-4b47-bf08-45b5bd440b57","order_by":2,"name":"Theresa Mack","email":"","orcid":"","institution":"Fraunhofer Research Institution Materials Recycling and Resource Strategies","correspondingAuthor":false,"prefix":"","firstName":"Theresa","middleName":"","lastName":"Mack","suffix":""},{"id":440751358,"identity":"b40ee91c-de61-4ecc-8b8e-ffc390173f48","order_by":3,"name":"Malte Vogelgesang","email":"","orcid":"","institution":"Fraunhofer Research Institution Materials Recycling and Resource Strategies","correspondingAuthor":false,"prefix":"","firstName":"Malte","middleName":"","lastName":"Vogelgesang","suffix":""},{"id":440751359,"identity":"1f0410fa-93ea-4bc2-b608-48b0669c3a69","order_by":4,"name":"Emanuel Ionescu","email":"","orcid":"","institution":"Fraunhofer Research Institution Materials Recycling and Resource Strategies","correspondingAuthor":false,"prefix":"","firstName":"Emanuel","middleName":"","lastName":"Ionescu","suffix":""}],"badges":[],"createdAt":"2025-03-21 17:23:17","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6279511/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6279511/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":80901435,"identity":"1d4d3a7d-94a7-4f63-af1c-80686dc34138","added_by":"auto","created_at":"2025-04-18 13:34:52","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":159858,"visible":true,"origin":"","legend":"\u003cp\u003eSystem Boundaries of three sWEEE End-Of-Life Proceduces. Blue Rectangles Represent Processes, Green Ovals Represent Value Flows, Orange Ovals Represent Waste Flows. sWEEE: small Waste Electrical and Electronic Equipment\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6279511/v1/59e893484e88d5b4c3f0c0da.jpeg"},{"id":80901431,"identity":"6f9fe93b-0903-46a5-afb5-5c07dd22f850","added_by":"auto","created_at":"2025-04-18 13:34:52","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":28671,"visible":true,"origin":"","legend":"\u003cp\u003eProcess Contribution Analysis for GWP (left) and Monetary Value (right) of Pre-treatment by Manual Dismantling (Path A) Of A Smartphone\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-6279511/v1/a08e408a0b43a30e0dbc12d5.png"},{"id":80901438,"identity":"d3bd51fe-2ba3-424d-9a55-95357a49fd1d","added_by":"auto","created_at":"2025-04-18 13:34:52","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":106746,"visible":true,"origin":"","legend":"\u003cp\u003eQualitative Illustration of Most Beneficial Pre-treatment Option Regarding Gwp (Left) and Monetary Value (Right) Depending on Precious Metal Content and Dismantling Time of the Eight Investigated Devices (Green: Manual Dismantling, Blue: Mechanical Pro\u003c/p\u003e","description":"","filename":"floatimage4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6279511/v1/91f3904d3a2202adcdf6eb29.jpeg"},{"id":94042425,"identity":"cf8072c8-bdd1-42a3-a30e-9198749cdbf9","added_by":"auto","created_at":"2025-10-21 19:01:29","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":798583,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6279511/v1/9d17a365-f73f-4c6e-9cb6-5c58f716f1a5.pdf"},{"id":80901440,"identity":"e64c0f8a-8eeb-4af3-993c-abb01c9305a9","added_by":"auto","created_at":"2025-04-18 13:34:52","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":467352,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryMaterial.docx","url":"https://assets-eu.researchsquare.com/files/rs-6279511/v1/9c537eb3868cf79749a21382.docx"},{"id":80901433,"identity":"ae94e413-8e13-4a95-ab9b-fff3fbf324ff","added_by":"auto","created_at":"2025-04-18 13:34:52","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":237877,"visible":true,"origin":"","legend":"","description":"","filename":"GraphicalAbstract.docx","url":"https://assets-eu.researchsquare.com/files/rs-6279511/v1/1aba912f7deecf1b7568a0e2.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Comparative Analysis of Small WEEE Pre-treatment Options: An Economic and Environmental Assessment","fulltext":[{"header":"Introduction","content":"\u003cp\u003eWith a constantly increasing amount of waste electrical and electronic equipment (WEEE) and the scarcity of certain resources required for electrical and electronic equipment (EEE) production, the management of WEEE is becoming a growing concern. According to the Global E-waste Monitor (Bald\u0026eacute;, et al., 2017), an estimated 53.6 million tons of e-waste were generated worldwide in the year 2019.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWEEE often contains critical elements, such as rare earth metals or precious metals, which are in some cases concentrated at higher levels than in traditional mines, and thus poses significant Urban Mining potentials \u0026ndash; in particular for the European Union (EU), which is scarce of natural deposits for many elements needed for a high-tech economy (European Comission, 2023). To address this xissue, the EU has introduced the Circular Economy Action Plan (European Comission, 2020) that includes a list of critical elements necessary for electronic device production. Moreover, e-waste management offers potential economic benefits. Recycling e-waste can create jobs and generate revenue, while also reducing the environmental impact of the waste (Bald\u0026eacute;, et al., 2017).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eUnderstanding the various End-of-Life (EoL) treatment pathways for WEEE and their characteristics is crucial to ensure an effective management of this waste stream. This requires the identification of the potential environmental and economic implications of each approach \u0026ndash; not just in general, but for different types of WEEE devices. In this study, the pre-treatment of eight small WEEE (sWEEE) devices according to three different treatment methods currently employed in Germany will be modelled with regards to economic feasibility and their potential impacts regarding climate change. The reviewed pre-treatment options for sWEEE are manual dismantling, mechanical processing, and direct smelting (Table 1).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSubsection: State of the art\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWhile the recovery rates of the actual treatment processes for the main fractions in sWEEE, in particular many precious and semi-precious metal fractions (Cu, Au, Ag, Pd, Pt), are already very high at around 95 %, the overall recycling efficiency for sWEEE is still lacking. Works such as (Hagel\u0026uuml;ken \u0026amp; Goldmann, 2022) have shown that amongst the three EoL phases 1. collection, 2. pre-treatment, 3. end-treatment for WEEE, the first two steps have the lowest material recovery rates. For elementary gold, the total recycling rate only reaches 67 % which can mostly be attributed to the low efficiency in pre-treatment (Hagel\u0026uuml;ken \u0026amp; Goldmann, 2022). The precious and semi-precious metals make up for a significant economic share which makes them a key factor for WEEE recycling enterprises (Bigum, et al., 2012). They are thus in the focus of the modelling in this study, whereas other fractions, no matter their mass relevance have comparatively little economic impact and are thus modelled in a simplified way.\u003c/p\u003e\n\u003cp\u003eIn general, the goal of the pre-treatment is 1) the liberation and 2) the concentration of valuable fractions as well as 3) the removal of pollutants (Batinic, et al., 2017). The sWEEE pre-treatment procedures currently widely established are manual dismantling (A), mechanical liberation (B) and direct smelting with preceding pollutant removal (C). Their characteristics are briefly presented in Table 1.\u003c/p\u003e\n\u003cp\u003eTable 1: Three Different sWEEE Pre-treatment Procedures Applied in Germany (PCB: Printed Circuit Board)\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePre-treatment method\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 331px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eProcess description\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCharacterstics of devices\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eA: Manual Dismantling\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 331px;\"\u003e\n \u003cp\u003eDevice is dismantled by hand, which allows for separation of high-value components (and others) without heavy losses\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003eLow component complexity, easily dismantable\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eB: Mechanical processing\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 331px;\"\u003e\n \u003cp\u003eDevice is shredded or physically stressed until it breaks open. The resulting fractions are sorted \u0026nbsp;(fractions: ferrous metals, PCB\u0026apos;s and semi-precious metals, light metals, plastics etc.)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003eLow economic potential (usually very low-grade or small PCB)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eC: Direct smelter feeding\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 331px;\"\u003e\n \u003cp\u003eDevice is wholly fed into a secondary Cu-smelter. Precious and semi-precious metals are recovered, less noble metals are lost in slag, organic materials are consumed thermally. If necessary, pollutants need to be removed from device (e. g. batteries)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003eHigh-grade components (e. g. \u0026nbsp;PCB), high component complexity\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003eThe latest version of the German law on electric and electronic devices (Elektro- und Elektronikgesetz \u0026ndash; ElektroG) released in 2022 requires EEE retailers of a certain size to take back and dispose of any WEEE that is smaller than 25 cm in length, and all collected WEEE to be sorted and treated in accordance with environmental standards (Deutscher Bundestag, 2015). It is therefore expected that an increased waste stream of the affected EEE products will occur in the coming years. Hence, WEEE devices which are smaller than 25 cm (in the following referred to as small WEEE or sWEEE) are in the focus of this research.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eEight device types from the sWEEE category that are largely representative of sWEEE were chosen for modelling: smartphone, router, remote control, MP3 player, USB stick, DVD player, digital camera and tablet computer.\u003c/p\u003e\n\u003cp\u003eIn order to explore the improvement potential of economic flows and greenhouse-gas emissions of the sWEEE pre-treatment status quo in Germany and to determine this improvement margin, all three presented options are modelled for each device and compared to the current status quo. To properly reflect the losses of (semi-)precious metals of device components that occur in options A and B but not in C (due to lack of comminution), the copper smelter process was modelled as well, though it is not part of the pre-treatment stage. This was done to ensure comparability between all three options. The system boundaries of three sWEEE pre-treatment pathways are illustrated respectively in Figure 1.\u003c/p\u003e\n\u003cp\u003eA consequential bin-to-cradle Life Cycle Assessment (LCA) and an extended Life Cycle Costing (LCC) were carried out. LCA\u0026apos;s are standardised in the ISO 14040 and 14044, according to which they mus contain the four phases 1. Goal and Scope Definition, 2. Life Cycle Inventory (LCI), 3. Life Cycle Impact Assessment (LCIA) and 4. Interpretation (DIN Deutsches Institut f\u0026uuml;r Normung e. V., 2009). The Goal and Scope Definition and Life Cycle Inventory phases are briefly explained in this chapter. Inventory lists can be found in the Supplementary Material (Tables 1-4).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe LCA only focuses on the impact category \u003cem\u003eclimate change\u003c/em\u003e. The LCA\u0026rsquo;s function is the pre-treatment of sWEEE in Germany. \u003cem\u003eSWEEE\u003c/em\u003e is to be understood as a placeholder for any of the eight chosen device types.\u003c/p\u003e\n\u003cp\u003eThe functional unit is defined as the pre-treatment of 1 kg of sWEEE in Germany. The reference flows are thus 1 kg of waste smartphones, 1 kg of waste routers, etc. The temporal scope ranges from 2017 to 2022 which is the timespan from which the modelled processes stem. The geographical scope is Germany.\u003c/p\u003e\n\u003cp\u003eThe LCC is not only considering costs and expenses but also revenue. Its results are in the following referred to as \u003cem\u003emonetary value\u003c/em\u003e, the unit is Euros. The LCC results are calculated similarly to the LCA results in that each material flow is assigned a Global Warming Potential (GWP) and monetary value property, which is then summed up for each process. While Costs are expressed as negative monetary value, the revenue is modelled positively. Positive overall monetary values thus indicate that a process is economically feasible.\u003c/p\u003e\n\u003cp\u003eThe multi-property process modelling approach, which was developed by Fraunhofer IWKS and initially introduced in \\cite{klemenz2021mppm}, is used to build the process chains of the pre-treatment options. For more details, see Supplementary Material Figure 1.\u003c/p\u003e\n\u003cp\u003eWhile the inputs were determined by expert consultation and literature research, the outputs are not only process- but also device-specific. Thus, the material fractions of a device were transformed into the outputs with the help of process-specific transfer coefficients (Supplementary Material Table 5). Material fractions that are not cleanly liberated and separated cannot be found in their respective output fraction and are lost and seen as waste.\u003c/p\u003e\n\u003cp\u003eThe coefficients are arranged in a matrix format, while the original device composition is required as a vector. The resulting output fractions can then be calculated as another vector by multiplying the device composition with the process-specific transfer coefficient matrix.\u003c/p\u003e\n\u003cp\u003eTo minimise inaccuracies caused by imprecise modelling of the copper smelting route, only the differences between two treatment systems for the same device are evaluated, because the metallurgical process was modelled similarly for all pre-treatment options.\u003c/p\u003e\n\u003cp\u003eThe data was collected by screening literature, conducting experiments and interviewing experts. For example, the output fractions of the processes were determined by combining a bill of materials with process-specific transfer coefficient matrices, which were taken from literature and expert interviews. The background database used for GWP calculations was ecoinvent v3.8 consequential, the reference time horizon of which is 2021.\u003c/p\u003e\n\u003cp\u003eThe data for the composition of devices was taken from (Babbit, et al., 2020).Precious metal recovery rates are based on (Schops, et al., 2010).\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eThe pre-treatment according to the status quo, and the optimal pre-treatment based on the result of the modelling are demonstrated in Table 2. The values for GWP are stated in kg CO\u003csub\u003e2\u003c/sub\u003e-eq. per kg device (minimisation desired), while monetary value is expressed as Euro per kg of device (maximisation desired).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFor both parameters, the difference to the status quo pre-treatment is listed. A difference of zero indicates that the optimal process is already employed. The best pre-treatment path may vary for GWP and monetary value. Which one is utilized depends on the prioritisation of the parameters.\u003c/p\u003e\n\u003cp\u003eTable 2: Status Quo Pre-treatment and Optimal Pre-treatment According to the Modelling Regarding Both GWP and Monetary Value in Comparison With the Respective Improvement Potential (A: Manual Dismantling, B: Mechanical Processing; C: Depollution and Smelting). 1:\n \u003c!--[if supportFields]\u003e\u003cspan style='mso-element: field-begin'\u003e\u003c/span\u003e\u003cspan lang=DE style='mso-ansi-language:DE'\u003e\u0026nbsp;CITATION San19 \\l 1031 \u003c/span\u003e\u003cspan style='mso-element:field-separator'\u003e\u003c/span\u003e\u003c![endif]--\u003e\u003cspan lang=\"DE\"\u003e(Sander, et al., 2019)\u003c/span\u003e\n \u003c!--[if supportFields]\u003e\u003cspan style='mso-element:field-end'\u003e\u003c/span\u003e\u003c![endif]--\u003e, 2:\n \u003c!--[if supportFields]\u003e\u003cspan style='mso-element:field-begin'\u003e\u003c/span\u003e\u003cspan lang=DE style='mso-ansi-language:DE'\u003e\u0026nbsp;CITATION Hag06 \\l 1031 \u003c/span\u003e\u003cspan style='mso-element:field-separator'\u003e\u003c/span\u003e\u003c![endif]--\u003e\u003cspan lang=\"DE\"\u003e(Hagel\u0026uuml;ken, 2006)\u003c/span\u003e\n \u003c!--[if supportFields]\u003e\u003cspan style='mso-element:field-end'\u003e\u003c/span\u003e\u003c![endif]--\u003e, 3:\n \u003c!--[if supportFields]\u003e\u003cspan style='mso-element:field-begin'\u003e\u003c/span\u003e\u003cspan lang=DE style='mso-ansi-language:DE'\u003e\u0026nbsp;CITATION Bun18 \\l 1031 \u003c/span\u003e\u003cspan style='mso-element:field-separator'\u003e\u003c/span\u003e\u003c![endif]--\u003e\u003cspan lang=\"DE\"\u003e(Bund/L\u0026auml;nder-Arbeitsgemeinschaft Abfall (LAGA), 2018)\u003c/span\u003e\n \u003c!--[if supportFields]\u003e\u003cspan style='mso-element: field-end'\u003e\u003c/span\u003e\u003c![endif]--\u003e, 4:\n \u003c!--[if supportFields]\u003e\u003cspan style='mso-element:field-begin'\u003e\u003c/span\u003e\u003cspan lang=DE style='mso-ansi-language: DE'\u003e\u0026nbsp;CITATION Gri22 \\l 1031 \u003c/span\u003e\u003cspan style='mso-element:field-separator'\u003e\u003c/span\u003e\u003c![endif]--\u003e\u003cspan lang=\"DE\"\u003e(Grieger, 2022)\u003c/span\u003e\n \u003c!--[if supportFields]\u003e\u003cspan style='mso-element:field-end'\u003e\u003c/span\u003e\u003c![endif]--\u003e\n\u003c/p\u003e\n\u003ctable\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eDevice\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eStatus quo pre-treatment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e∆GWP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e∆Monetary value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eTreatment path\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eSavings potential per kg [kg CO2-eq.]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eTreatment path\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eAffitional generated value per kg [\u0026euro;]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eDVD Player\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eB\u003csub\u003e1\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-0.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.07\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eDigital camera\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eC\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-2.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eTablet computer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eC\u003csub\u003e3\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-3.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.28\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eUSB stick\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eB\u003csub\u003e1\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-3.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eMP3 player\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eC\u003csub\u003e3\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-9.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eRemote control\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eB\u003csub\u003e4\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-4.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eRouter\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eB\u003csub\u003e4\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-6.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3.53\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSmartphone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eC\u003csub\u003e3\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-3.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eRegarding monetary value, the conventional treatment of mechanical liberation is preferable for 2 of the 8 investigated device types. The remaining device classes are split evenly between manual dismantling and direct smelting with 3 of the 8 classes each.\u003c/p\u003e\n\u003cp\u003eDigital camera, USB stick, MP3 player, remote control and smartphone devices are currently already pre-treated in the optimal way. The treatment of DVD player, tablet computer and router devices can be improved by manually dismantling them, however this improvement margin is rather small. The potential can be ascribed to the low dismantling time of these devices relative to their content of valuable components.\u003c/p\u003e\n\u003cp\u003eRegarding the impact category climate change, the best pre-treatment path is mostly the manual dismantling. Only for USB stick, remote control and router devices, the direct smelter feeding option is to be preferred. This can be explained by the low losses of (semi-)precious metals during pre-treatment in both pathways compared to the Mechanical Processing. The option with the lowest emission intensity is not yet employed for any of the devices. The total potentially avoidable greenhouse-gas emissions for the considered devices on a national scale are displayed in Table 3. A contribution analysis was done for processes within their respective product system. The analysis is shown exemplary for the GWP and monetary value of the pre-treatment path A (Manual Dismantling) for all eight devices. Figure 2 graphically shows the analysis results for the Smartphone.\u003c/p\u003e\n\u003cp\u003eThe results of the process contribution analysis show a high significance of the copper smelter process regarding both GWP and monetary value for every pre-treatment option. For some devices an increased importance of the manual dismantling step was identified regarding monetary value. The comminution and sorting process in pathway A showed very little environmental and monetary impact in comparison with the other process steps. The smelting process also dominates the impacts for GWP and monetary value in the pathways B and C.\u003c/p\u003e\n\u003cp\u003eTo further investigate this, a flow contribution analysis was conducted exemplarily for the smartphone. The flow contribution analysis for smartphone devices showed that the recovered gold alone, which substitutes the production of primary gold, accounts for 92 % of generated monetary value and 89 % of GWP savings. As shown in Figure 2 the revenue of this process outweighs the operating and investment costs by far, suggesting that the semi-precious metal recovery, especially gold recovery, is of high priority for both economic and environmental parameters. The findings are in general accordance with literature (Bigum, et al., 2012).\u003c/p\u003e\n\u003cp\u003eWhen investigating the contributions to the manual dismantling process for smartphones, it was found that the manual labour costs are responsible for over 99 % of the total costs of this process. Thus, analogously to the recovery of gold in the metallurgy process, this flow has a strong effect on the entire process chain.\u003c/p\u003e\n\u003cp\u003eTable 3: Improvement Potential of the eight Devices on a National Scale (Germany); a: Estimate\u003c/p\u003e\n\u003ctable\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eDevice\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eAmount\u0026nbsp;\u003cbr\u003e\u0026nbsp;[t/a]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003ePotential GWP change [kt CO2-eq./a]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eAdditional monetary value [mil. \u0026euro;/a]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eDVD player\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7800\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-6.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e8.34\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eDigital camera\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1819\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-4.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eTablet computer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4161\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-13.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.17\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eUSB stick\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e120\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-0.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eMP3 player\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e427\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-4.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eRemote control\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3352\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-13.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eRouter\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e100\u003csub\u003ea\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-0.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.35\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSmartphone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3257\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-10.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-54.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e9.86\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eConsidering the amount of EEE devices entering circulation annually in Germany[], for the eight investigated devices a greenhouse gas savings potential of roughly 54300 t CO\u003csub\u003e2\u003c/sub\u003e-eq. p. a. compared to the status quo was determined. Analogously, by choosing the optimal pre-treatment path according to the model, additional added value of about 9.9 mio. \u0026euro; p. a. could be generated (see Table 3).\u003c/p\u003e\n\u003cp\u003eWhen interpreting the results and comparing the investigated devices, it must be considered that the LCA\u0026rsquo;s functional unit is 1 kg of a device and not 1 device. Device weight ranges from 8 g (USB stick) to 3.7 kg (DVD player). This leads to some oddities in the results, for example the manual dismantling step of a USB stick, which is only slightly uneconomical but results in a large cost deficit when scaled up to 1 kg.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn regard to monetary value, the direct smelting path is preferable for compact, high-tech devices such as the digital camera, MP3 player and smartphone, all of which have high precious metal contents but are time-intensive in manual dismantling. The mechanical treatment route can be suitable when devices contain little amounts of precious metals or PCB in general and their main value lies in the non-precious metals/bulk metals. Although this route has the lowest material recovery rates for the precious metals it can be quite economical due to averted labour expenditures, especially for \u0026quot;low-tech\u0026quot; devices like remote controls.\u003c/p\u003e\n\u003cp\u003eThe higher the precious metal content in a device, the higher are the absolute losses when passing through a process step with a low transfer coefficient for precious metals. This leads comparatively to exceptionally good results of the copper smelting route for devices with higher precious metal contents. A qualitative representation of the most beneficial pre-treatment paths in dependence of the dismantling time and the precious metal content of devices is shown in Figure 3.\u003c/p\u003e\n\u003cp\u003eBased on the results and illustrated by Figure 3, the trend of preferred pre-treatment shows a similar pattern for GWP and monetary value considering the direct smelting path. Mechanical pre-treatment is not shown in Figure 3 a) as it was not preferred regarding greenhouse-gas emissions for any device in this study. Regarding monetary value, reducing the dismantling time and complexity of several devices shifts the optimal pre-treatment from direct smelting to manual dismantling, thus promoting the more advantageous route in terms of global warming potential.\u003c/p\u003e\n\u003cp\u003eIf the best pre-treatment option by GWP shall actually be implemented by pre-treatment facility operators, the two diagrams would have to match exactly. They would need to be incentivised through corresponding policies when their recovery is currently not profitable according to the state of the art. It can thus be considered that market interventions are necessary to get pre-treatment of sWEEE, which is in reality mainly chosen based on economic feasibility, to align with environmental and possibly strategic ambitions.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFigure 3 also shows that reducing the dismantling time and complexity of multiple devices shifts the optimal pre-treatment from direct smelting to manual dismantling, thus promoting the more advantageous route in terms of global warming potential. A decreasing precious metal content, which can currently be observed (Zhang, et al., 2017), would diminish potential revenue and thus make mechanical pre-processing more preferrable (shift to the left on the graph).\u003c/p\u003e\n\u003cp\u003eManual dismantling facilitates high recovery rates for every fraction of interest. Applying economic incentives to the recovery of desired elements is currently in many cases necessary to enable their recycling. From the perspective of total material recovery and critical material recovery, pre-treatment options which result in the fewest losses are desirable, which does not always have to align with the most economical or even most ecological options.\u003c/p\u003e\n\u003cp\u003eDevelopments such as the ever-decreasing precious metal content in EEE (Zhang, et al., 2017) and uncertain price fluctuations in the primary production of relevant metals make future predictions about the economic drivers difficult. Other than policy changes and economical incentives, labour expenditures could be reduced by making complex, high-grade devices easier to properly dismantle. The so-called \u003cem\u003eecodesign\u003c/em\u003e and \u003cem\u003edesign for circularity\u003c/em\u003e can already be observed in current niche technology developments (e. g. (Reuter, et al., 2018)) and can be enhanced by current legislation changes such as the EU\u0026apos;s \u003cem\u003eright to repair\u003c/em\u003e.\u003c/p\u003e\n\u003cp\u003eThe fact that mechanical pre-treatment was not found as ecologically optimal for any of the eight devices highlights the importance of high precious metal recovery rates for ecological considerations, in this case the impact category climate change.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eHowever, in practice, one major reason which makes a more distinguished pre-treatment inconvenient is the difficult separation of devices from the main WEEE stream that enters the treatment facilities. This is mostly done manually and works better for larger devices. A clear comparison of the different pre-treatment options as it was done in this work is thus best supported by adequate sorting possibilities that allow for improved sorting.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eA sorting or classification of devices prior to entering the actual pre-treatment could thus aid in achieving the best possible outcome. This could be done in automated sorting machines via image recognition or by reading stored device metadata from a machine-readable product passport which would not just facilitate optimal pre-treatment by correct sorting but also cut on labour costs necessary to screen the WEEE devices.\u003c/p\u003e\n\u003cp\u003eThis study highlighted that albeit material liberation is generally desirable, economically feasible pre-treatment without heavy losses can currently not be realised for many, especially smaller, high-grade devices due to their complexity and associated labour costs. \u0026nbsp;Emerging process technology in the field of automated sWEEE liberation without such losses thus seem promising and should be assessed. The electro-hydraulic fragmentation, for instance, is a technology which is designed to break apart strongly-jointed composite materials by emerging them in water and causing shock waves through electrical impulses which stress their material interfaces. (\u0026Ouml;hl, et al., 2018)\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAs the system boundaries do not only include pre-treatment steps but also the copper smelting process, it is not advised to directly compare the results of this work to those of other studies, which only cover pre-treatment. Furthermore, due to the method of consequential LCA investigating system changes, only the differences between the recommended pathways and the Status Quo should be used and not the absolute results for both GWP and monetary value.\u003c/p\u003e\n\u003cp\u003eLimitations of this work include a limited number of selected devices that does not represent all devices which are considered sWEEE. Furthermore, the only ecological impact category investigated is \u003cem\u003eclimate change\u003c/em\u003e, and no statement about other potential environmental consequences can be made. Additionally, the method of modelling is currently static (coefficient matrix) and relies on generic data which does not take into account real-life aberrations like synergy effects.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study showed that the pre-treatment of sWEEE in Germany can potentially be improved regarding both greenhouse gas emissions and monetary value. The adaptation of the presented optimised pre-treatment options - possibly in combination with prior separation of devices into classes - poses potential for increased economic and ecological benefits.\u003c/p\u003e\n\u003cp\u003eThe precious metal content of sWEEE, which is often proportional to the PCB size and grade, as well as the labour expenditures of manual processes, are the main economic drivers in the pre-treatment process chain. It was shown that these aspects can hinder ecological pre-treatment in favor of profitability.\u003c/p\u003e\n\u003cp\u003eIt is necessary that the expected increasing amounts of sWEEE are recycled as best as possible to mitigate greenhouse gas emissions and to prevent losses of critical materials in the EU. Currently economic pre-treatment options for some devices like mechanical comminution and sorting are often not preferable in terms of emitted greenhouse-gases and total material recovery. The implementation of instruments that couple ecological and strategic concerns to the economic feasibility should thus be considered. Developments in the design and production stage of EEE that improve component accessibility or information transfer could help to mitigate the gap between economic and ecological considerations in sWEEE pre-treatment.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eConflict of Interest:\u003c/h2\u003e\n\u003cp\u003eThe Authors declare no conflict of interest.\u003c/p\u003e\n\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\n\u003cp\u003eP. S.: Investigation, data curation, methodology, software, resources, writing - original draft, visualization, formal analysisC. L.: Data curation, methodology, writing, review and editing, supervisionM. V.: validation, writing, review and editingT. M.: validation, review, methodology, project administrationE. I.: supervision\u003c/p\u003e\n\u003ch2\u003eData Availability\u003c/h2\u003e\n\u003cp\u003eData is provided within the manuscript and supplementary information files.\u003c/p\u003e\n\u003ch2\u003eSupplementary Material:\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eSupplementary Material for this work can be found in an external word file (\u0026ldquo;Supplementary Material short.docx\u0026rdquo;)\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eBabbit, C. W. et al., 2020. Disassembly-based bill of materials data for consumer electronic products. \u003cem\u003eScientific data,\u0026nbsp;\u003c/em\u003eVolume 7, p. 251.\u003c/li\u003e\n \u003cli\u003eBald\u0026eacute;, C. 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Supply and demand of some critical metals and present status of their recycling in WEEE. \u003cem\u003eWaste Management,\u0026nbsp;\u003c/em\u003eVolume 65, pp. 113-127.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Electronic Waste, E-Waste, WEEE, cLCA, LCC","lastPublishedDoi":"10.21203/rs.3.rs-6279511/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6279511/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eCollection and pre-treatment of Waste Electrical and Electronic Equipment (WEEE) are the two biggest limiting factors of enabling a high WEEE recovery rate. Small WEEE (sWEEE) have recently received increased attention by legislators that have recognised the improvement of this deficiency as an integral part of mitigating associated greenhouse-gas emissions and transforming the EU's economy towards carbon neutrality. Different sWEEE pre-treatment methods are currently in use, which pose a range of economic and ecological impacts. This study examines the economic properties and potential impacts on climate change of the different sWEEE pre-treatment options that currently exist in Germany for eight devices representative of sWEEE. A consequential bin-to-cradle life cycle assessment (cLCA) and an extended Life Cycle Costing (LCC) were conducted to identify the most beneficial pre-treatment option for each device regarding economic feasibility and greenhouse-gas emissions. The results indicate improvement potential in both aspects, particularly for the reduction of greenhouse-gas emissions, by pre-treating the device classes differently from the current status quo. Furthermore, discrepancies between most profitable and least greenhouse-gas-intensive pre-treatment option were found.\u003c/p\u003e","manuscriptTitle":"Comparative Analysis of Small WEEE Pre-treatment Options: An Economic and Environmental Assessment","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-18 13:34:48","doi":"10.21203/rs.3.rs-6279511/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"78764b5d-4059-40cb-b4e7-16f967f4d2e5","owner":[],"postedDate":"April 18th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-01-27T04:39:07+00:00","versionOfRecord":[],"versionCreatedAt":"2025-04-18 13:34:48","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6279511","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6279511","identity":"rs-6279511","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}