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- 10.1016/j.resconrec.2023.106916
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Abstract
Resources, Conservation & Recycling 192 (2023) 106916 Contents lists available at ScienceDirect Resources, Conservation & Recycling journal homepage: www.elsevier.com/locate/resconrec Full length article How much can chemical recycling contribute to plastic waste recycling in Europe? An assessment using material flow analysis modeling a, b, * b b c c Irdanto Saputra Lase , Davide Tonini , Dario Caro , Paola F. Albizzati , Jorge Cristobal , a d e d f Martijn Roosen , Marvin Kusenberg , Kim Ragaert , Kevin M. Van Geem , Jo Dewulf , a, * Steven De Meester Laboratory for Circular Process Engineering (LCPE), Department of Green Chemistry and Technology, Faculty of Bioscience Engineering, Ghent University, Graaf Karel de Goedlaan 5, B-8500 Kortrijk, Belgium Joint Research Centre of the European Commission, Calle Inca Garcilaso, 41092 Seville, Spain Joint Research Centre of the European Commission, via Enrico Fermi 2749, 21027 Ispra (VA), Italy Laboratory for Chemical Technology (LCT), Department of Materials, Textiles, and Chemical Engineering, Faculty of Engineering and Architecture, Ghent University, Technologiepark 130, B-9052 Zwijnaarde, Belgium Circular Plastics, Department of Circular Chemical Engineering (CCE), Faculty of Science and Engineering, Maastricht University, Urmonderbaan 22, 6162 Geleen, The Netherlands Sustainable Systems Engineering (STEN), Department of Green Chemistry and Technology, Faculty of Bioscience Engineering, Ghent University, Coupure Links 653, 9000 Ghent, Belgium ARTICLE INFO ABSTRACT Keywords: Plastic recycling rate in Europe is low, urging developments in recycling technology and strategies to increase Material flow analysis circularity. Mechanical recycling (MR) has been the reference recycling technology for years, but in the near Chemical recycling future chemical recycling (CR) options are expected to contribute to improve plastic circularity. This study uses a Plastic waste material flow analysis (MFA) at European level to provide quantitative estimates of the contribution of CR Circularity indicator technologies to plastic recycling. Ten most used polymer types from five sectors are selected. A status quo 2018 Recycled content scenario is modelled and compared to five potential future scenarios (in 2030) of plastic waste treatment, including one that only looks at improved waste collection, sorting, and MR technologies and four exploring developments of CR options. The so-called ‘missing plastics’, i.e., plastic waste generated but currently not accounted for in statistics, is considered in one of the future scenarios. The MFA results are compared by calculating four circularity indicators namely end-of-life recycling rate (EoL-RR), plastic-to-plastic rate, plastic- to-chemicals rate, and plastic-to-fuels rate. The results indicate that in the most optimistic scenario the EoL-RR in 2030 is 73–80% (sum of plastic-to-plastic and plastic-to-chemical rates, excluding plastic-to-fuel rate), in which 41–46% is plastic-to-plastic from MR, 15–38% is plastic-to-plastic from CR and 19–35% is plastic-to-chemicals. The highest achievable plastic-to-plastic rate is estimated to be 61% (46% from MR and 15% from CR). In all future scenarios, the plastic-to-fuel rate is estimated to be 3–6%. The MFA results are also used to estimate potential recycled content availability in 2030, which suggest that closed-loop recycling and processing the ‘missing plastics’ will be necessary to achieve the targets. 1. Introduction automotive sectors. In the same year, 353 Mt of plastic waste were generated, of which only 6% was effectively recycled globally while the Plastic is a bulk term for a wide range of polymers that is widely used remaining mass was mostly incinerated or landfilled (OECD, 2022). in various applications due to their light weight, durability, affordability Some studies also emphasize the leakage of macro- and micro-plastics and broad application range (Lebreton and Andrady, 2019; Hsu et al., into the environment (Ryberg et al., 2019; Peano et al., 2020; 2021). In 2019, global plastic use amounted to 460 million tonnes (Mt), Boucher et al., 2020). Moreover, the demand for plastic, and the sub- of which more than 60% was used in the packaging, construction, and sequent plastic waste generation, is expected to increase considerably in * Corresponding authors. E-mail addresses: [email protected] (I.S. Lase), [email protected] (S. De Meester). https://doi.org/10.1016/j.resconrec.2023.106916 Received 21 November 2022; Received in revised form 26 January 2023; Accepted 6 February 2023 Available online 26 February 2023 0921-3449/© 2023 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). I.S. Lase et al. Resources, Conservation & Recycling 192 (2023) 106916 the coming years (Material Economics, 2022; Geyer et al., 2017; Balde unused space for packaging), and fostering new delivery business et al., 2017). Thus, there is an urgent need to tackle plastic waste models (e.g., through promoting reuse) (OECD, 2022; SYSTEMIQ, 2022; problems amongst others by increasing the circularity of the plastic Feber et al., 2020). On the other hand, the EoL treatment-oriented solu- value chain. tions focus on improving the existing waste management infrastructure According to Plastics Europe (2020), Europe generated 29.1 Mt of and practices such as promoting separate collection, sorting per polymer plastic waste in 2019. Of the generated plastic waste in 2019, it is group, and advancing recycling technologies (Ellen MacArthur Foun- estimated that 19.6 Mt (i.e., 67%) was landfilled or incinerated and only dation, 2016; PRI, 2019). 9.4 Mt (i.e., 33%) was sent to recycling facilities (Plastics Europe, 2020). Related to EoL solutions, today, mechanical recycling (MR) is still the Further, it is estimated that out of the plastic waste sent to recycling in most commercially used technique to recycle plastic (over 9.0 Mt pro- 2019, only 4 Mt were effectively recycled, hence resulting in recycling cessing capacity), while chemical recycling (CR) and solvent-based rates of approx. 15–33%, depending on the calculation methods (Plas- recycling (SBR) is treating only less than 0.2 Mt of plastic waste in tics Europe, 2020; Agora Industry, 2022). The 33% plastic recycling rate Europe (Plastics Europe, 2019a). However, MR faces several challenges is calculated based on the quantity of plastic waste entering recycling in treating plastic waste, such as thermal-mechanical degradation, the facilities over the reported plastic waste generation (Plastics Europe, presence of legacy additives and chemicals, and inadequate technical 2020). The 15% plastic recycling rate is calculated based on the quantity properties of the final regranulates to meet the market demands of recycled plastic production (after regranulation) over the total esti- (Ragaert et al., 2017; Simon and Martin, 2019; Eriksen et al., 2020). mated plastic waste generated (i.e., reported plastic waste quantity plus Also, potential degradation might occur by multiple rounds of recycling the ‘missing plastic’) (Agora Industry, 2022). According to Material (Demori et al., 2015; P´ erez et al., 2010; Schyns and Shaver, 2021; Arena Economics (2022), the reported amount of plastic waste in Europe (i.e., and Ardolino, 2022). Several improvements can be implemented to 29.1 Mt) is deemed to be underestimated as substantial amounts are tackle these MR challenges such as the implementation of advanced seemingly not accounted for (so-called ‘missing plastic’) in the statistical (pre-)treatment processes (e.g., deinking and deodorization), advanced databases, e.g., municipal waste statistics. Studies from Agora Industry washing (e.g., hot washing with detergents) and improved extrusion (e. (2022) and SYSTEMIQ (2022) estimate that 7–15 Mt of plastic waste are g., double melt filtration) (Lase et al., 2022; Kol et al., 2021; Roosen ‘missing’ because of either underestimation of plastic in mixed et al., 2021; Demets et al., 2020). Nevertheless, even after elaborated (municipal) waste, underestimation of lifetime of plastic applications, or sorting process, some plastic waste streams remain unsuitable for MR unidentified/undocumented flows (e.g., unauthorised waste treatment due to the heterogeneous composition (e.g., mixed of rubbers, thermo- or exports of waste). sets, and thermoplastics), substantial level of hazardous substances (e.g., Reinforcing the efforts to improve the plastic circularity in Europe, legacy chemicals from flame retardants), or multi-material structures (e. the European Commission (EC) has enacted several regulations, along g., fiber-reinforced composites or metalized packaging) (Cardamone with (voluntarily) pledges made by stakeholders in the plastic value et al., 2022; Arena and Ardolino, 2022). chain (e.g., by cars and electronic products manufacturers). For On the other hand, several studies predict that CR technologies (i.e., example, 55% of plastic packaging waste should be recycled by 2030 as pyrolysis, gasification, depolymerization) and SBR technologies (i.e., stated in the Packaging and Packaging Waste Directive (PPWD) (Euro- dissolution-precipitation, deinking, delamination) will play a big role in pean Commission, 2018a). Cars and electronic manufacturers also the future plastic waste treatment in Europe (Simon and Martin, 2019; pledge to use 25–30% of recycled plastic in their new products by 2030 Hann and Connock, 2020; Crippa et al., 2019; Manˇ zuch et al., 2021). (Maury et al., 2022; Sandoval, 2018; Volvo, 2018). The Landfill Direc- These technologies are claimed to have a higher tolerance in dealing tive also limits municipal waste to be landfilled in 2035 by 10% (Eu- with contaminated and complex waste streams, i.e., waste streams that ropean Commission, 2018b). The complete list of relevant laws and are not recycled yet due to the limitation of current state-of-the-art MR pledges is available in Table S1. The regulations and pledges also aim to (SYSTEMIQ, 2022; Cardamone et al., 2022; Arena and Ardolino, 2022; enhance the uptake of recycled plastic in new products (i.e., recycled Vollmer et al., 2020; Solis and Silveira, 2020). Several plans to build CR content), which would increase the demand and potentially the price of plants have been announced such as gasification plant in Spain (treating recycled plastics (Maury et al., 2022; European Commission, 2022a). non-recyclable mixed solid waste with 400,000 tonne/year capacity), However several studies indicate that either the targets are not yet pyrolysis plant in Spain and Belgium (treating mixed polyolefin and accomplished or significant improvements are still needed to achieve polystyrene with up to 65,000 tonne/year capacity), and chemical the targets. Lase et al. (2021) suggest that the recycled content targets in depolymerization plant in the United Kingdom, France, Belgium, and the electronic sector will be difficult to achieve in Belgium and the Spain (treating polyurethane; 2000 tonne/year capacity and poly- Netherlands due to inefficiencies in collection, sorting and recycling styrene; 15,000 tonne/year capacity) (Indaver, 2022; INEOS Styr- chains. Studies from Maury et al. (2022), Cardamone et al. (2022), and olution, 2021; AIMPLAS, 2022). In this sense, CR and SBR technologies Williams et al. (2020) suggest that plastic from end-of-life vehicles and are perceived as complementary to treat plastic waste streams that (ELVs) are treated with less attention to polymer recovery and the ‘reuse otherwise would have been landfilled or incinerated (Arena and Ardo- and recycling’ target from ELV (i.e., 85%) stated in the End-of-Life Ve- lino, 2022; Manzuch et al., 2021). From a life cycle perspective, hicles Directive (ELVD) is mainly achieved by recycling aluminum and diverting plastic waste streams from landfill, incineration, and export metals from ELVs, leaving a substantial amount of plastic to be landfilled outside Europe (e.g., to African and Asian countries; Huisman et al., or incinerated. Similarly, a significant amount of plastics packaging 2012; Jacobs et al., 2018) leads to environmental benefits by simulta- waste is not separately collected, correctly sorted or recycled, while neously avoiding such sub-optimal management practices and produc- substantial improvements are needed to meet the 55% recycling target ing new secondary materials to replace production of virgin ones. by 2030 stated in the PPWD (Picuno et al., 2021; Antonopoulos et al., Several studies indeed indicate better environmental performance of CR 2021; Lopez-Aguilar et al., 2022; Van Eygen et al., 2018). It is thus clear plastic waste compared to landfill and incineration (Arena and Ardo- that the circular economy for plastic needs an urgent boost. lino, 2022; Vollmer et al., 2020; Demetrious and Crossin, 2019; Civ- The ways to improve plastic circularity and recycling rates in Europe ancik-Uslu et al., 2021; Schwarz et al., 2021; Eschenbacher et al., 2022). are two-fold: implementation of plastic production and use-oriented so- However, while some studies have preliminarily investigated the envi- lutions, and end-of-life (EoL) treatment-oriented solutions. Production and ronmental benefits (Arena and Ardolino, 2022; Vollmer et al., 2020; use-oriented solutions typically focus on improving products’ design for Civancik-Uslu et al., 2021; Jeswani et al., 2021) and technical feasibility easier EoL treatment (i.e., design-for-recycling principles), reducing (Kusenberg et al., 2022a, 2022b; Larrain et al., 2020; Genuino et al., material complexity (e.g., by changing from multi- to mono-material), 2022) of some CR and SBR technologies, research on the performance reducing plastic use in a product (e.g., reduce packaging weight or and on the role and deployment of these technologies at industrial scale 2 I.S. Lase et al. Resources, Conservation & Recycling 192 (2023) 106916 in the future Europe plastic waste management system is still scarce. and 2019b). Moreover, CR options such as pyrolysis and gasification produce not The MFA of the selected polymers is modelled by following four only monomers but also other base chemical products (i.e., benzene, steps, following the methodology from previous studies (Antonopoulos toluene, xylene, wax, etc.) and fuels (i.e., hydrocarbons as synthesis gas et al., 2021; Eriksen et al., 2020; Kawecki et al., 2018). Firstly, the or oil) (Kusenberg et al., 2022c, 2022d). Nevertheless, such variety of required inputs data for MFA model are gathered: (i) a process diagram outputs, while certainly contributing to plastic circularity, poses legal of the current (and future) plastic waste management systems in EU challenges as fuel- and energy-like outputs are not considered under 27+3, (ii) the respective transfer coefficients (TCs, in%) of each process, ‘recycling’ in the Waste Framework Directive (WFD) (European Com- and (iii) the quantities of the selected polymers (in kilo tonnes, kt). The mission 2018a, 2008). TCs describe the partitioning of mass input(s) to output(s) for each In the context of the urgent need to increase the circularity of plas- process in the system. The MFA model quantifies the mass balance (in tics, and to achieve (voluntary) targets or pledges, CR and SBR could kt) throughout the defined system that is obtained by multiplying the play a pivotal role. However there is little quantitative evidence (and mass input quantity with the TCs of each process in the system. Sec- data available) on how big this contribution might be. Hence, study ondly, status quo scenario and five potential future scenarios are devel- investigates the current and future flows of ten most used plastic waste oped, representing the flow of the selected polymers in 2018 and throughout the plastic waste management systems (of five different potential flows in 2030, respectively. In order to model the mass flows in sectors) in Europe. A material flow analysis (MFA) model based on mass 2030, projections of waste quantities, improvements of the TCs, and balance principles is developed and used. Six scenarios are developed recycling pathways (MR, CR, and/or SBR options) are implemented. and discussed: i) status quo scenario in 2018 (S0, as benchmark) and ii) Thirdly, the MFA results from the six different scenarios are assessed and five potential future scenarios in 2030 (S1 – S5), including improving compared by calculating four selected circularity indicators. Lastly, for only collection, sorting, and MR as well as a combination of improved each output (material flows and circularity indicators), the parametrical MR, CR, and SBR of plastic waste. One of the future scenarios also in- input uncertainties are propagated into output uncertainties. The un- vestigates the contribution of processing the so-called ‘missing plastics’ certainty propagation with Monte Carlo simulation is performed and the according to Material Economics (2022); Agora Industry (2022) and standard deviation of the mass flow is calculated. The standard devia- SYSTEMIQ (2022). The selection of suitable CR and SBR options in this tion is calculated assuming a Triangular Distribution (TD) of the dataset study is determined by considering the capability of the CR and SBR and the values are selected based on the relevant literature of plastic options to treat plastic waste streams, including the type and composi- waste management in EU 27+3. tion of the streams as recently reported by the stakeholders to the EC. For each scenario, a set of circularity indicators of plastic waste 2.2. Defining the scope of recycling technologies treatment are calculated based on MFA, namely: EoL recycling rates (EOL-RR), plastic-to-plastic (P2P), plastic-to-chemicals (P2C) and plastic- After plastic waste is collected and sorted, MR, CR and SBR routes to-fuels (P2F) rates in order to assess the potential improvements when can be chosen. MR refers to mechanical reprocessing by means of CR and SBR options are implemented at large scale. This study thus shredding, washing, drying, and extrusion of polymers without breaking includes the amounts of materials produced such as polymers (i.e., down the polymer chains. CR refers to a reprocessing technologies that recycled plastics from MR, CR, and SBR), base chemicals (e.g., wax, break down the polymer chains and converts them into high added- benzene, toluene, xylene from CR), and fuels (e.g., synthesis gas from value materials, such as oligomers, monomers, base chemicals, and CR). Lastly, the potential of recycled content availability in 2030 from hydrocarbons (solid, liquid, or gas) (Arena and Ardolino, 2022; Hann different scenarios is quantified and discussed, which is based on the ˇ and Connock, 2020; Crippa et al., 2019; Manzuch et al., 2021). How- share of recycled plastic production (per sector) over plastic demand ever, CR is an umbrella term that has been used to cover a broader set of (per sector) in 2030. technologies (Hann and Connock, 2020; Manˇ zuch et al., 2021), such as thermal depolymerization (i.e., pyrolysis coupled with steam cracking or gasification coupled with Fischer-Tropsch Synthesis) and chemical 2. Materials and methods depolymerization (i.e., glycolysis, methanolysis, etc.). SBR (also known as ‘physical’ or ‘material’ recycling) refers to material reprocessing by 2.1. General modeling approach means of dissolving the polymer (or additives and pigments), in which the impurities is removed while the polymer is recovered through This study focuses on the ten most used polymers in the European Union (EU) 27+3 (Norway, Switzerland, and the United Kingdom) filtration or extraction phase (Crippa et al., 2019). A more detailed (Plastics Europe, 2019) with high data availability in all life cycle stages explanation of each technology at process level can be found in the from production to the EoL treatment (Eriksen et al., 2020; Kawecki Supporting Information (SI)–Section 2. et al., 2018) and considered as priority products within the plastic in- dustry (Watkins et al., 2020). The ten polymers considered in scope 2.3. Material flow analysis model development within this study are Linear Low Density Polyethylene (LLDPE), High Density Polyethylene (HDPE), Polypropylene (PP), Poly(ethylene Tere- 2.3.1. Description of system boundaries and scenarios phthalate) (PET), Polystyrene (PS), Expanded Polystyrene (EPS), Poly This study focuses on Europe as EU27+3 as most of the datasets used (vinyl Chloride) (PVC), Acrylonitrile Butadiene Styrene (ABS), Poly- in this study cover this region (Eriksen et al., 2020; Plastics Europe, urethane (PUR), and Polyamide (PA). These polymers are applied in 2019b; Kawecki et al., 2018; Watkins et al., 2020; Hestin et al., 2017). different sectors with their specific use and EoL fate. The five sectors The diagram of the system boundaries can be found in Fig. 1. The included in this study are: packaging, building and construction, auto- boundary comprises collection, sorting, and recycling, including the motive, electronic, and agriculture sector. Overall the selected polymers future potential plastic recycling using CR technologies in 2030. Fig. 1 and sectors in this study cover 60% of the total reported plastic waste in illustrates the waste management systems for plastic waste in the 2018 in EU 27+3 (Plastics Europe, 2019a,2019b). The other 40% of EU27+3 per sector. Detailed information on the waste management polymers that are not considered in this study (which is subjected for systems per sector can be found in the SI–Section 3. There are three future research) include waste from household goods, textiles, and potential destinations of the plastic waste treatment: i) secondary ma- others (e.g., medical) (estimated to be 15–25%, based on Plastics terials to be used in the economy again, ii) waste streams that are sent Europe, 2019a) and some polymer types (e.g., Polycarbonate or Poly for residual treatment (i.e., incineration or landfilling), and iii) waste (methyl methacrylate), etc.) in packaging, electronic and automotive export and/or informal waste treatments (Fig. 1). As for the waste that is sectors (up to 35% of ‘other polymers’, based on Plastics Europe, 2019a informally treated, the whereabouts of these flows are difficult to track. 3 I.S. Lase et al. Resources, Conservation & Recycling 192 (2023) 106916 Fig. 1. Conceptual diagram of the end-of-life treatment of the selected plastic waste from different sectors considered in this study. The thickness of the arrows does not repre- sent mass/quantity. Abbreviations: ABS (Acrylonitrile Butadiene Styrene), APW (agriculture plastic waste), ASR (automotive shredder residue), CDW (construction and demolition waste), CFA (cooling and freezing appliance), EEE (electronic and electrical equipment), ELV (end-of-life vehicle), EPS (Expanded Polystyrene), HDPE (High Den- sity Polyethylene), LLDPE (Linear Low Density Poly- ethylene), LHA (large household appliance), PA (Polyamide), PET (Polyethylene Terephthalate), PP (Polypropylene), PS (Polystyrene), PTTs (Pots, trays, and tubes), PUR (Polyurethane), PVC (Polyvinyl Chloride), SHA (small household appliance), TCs (transfer co- efficients), WEEE (waste electronic and electrical equip- ment), WEEP (waste electronic and electrical plastic). However, several studies suggest potential destination of these flows waste management systems, following the trends of increased collection such as unreported recycling within EU 27+3, illegal export outside EU rates and improved sorting and MR technologies (Maury et al., 2022; 27+3 (can be partially recycled), or leakage to the environment. Lase et al., 2021; Antonopoulos et al., 2021). S1 assumes that only MR (Ryberg et al., 2019; Peano et al., 2020; Boucher et al., 2020; Lase et al., will be deployed to treat plastic waste. S2 serves as ‘explorative’ pro- 2021). Note that in this study the legal waste export from EU 27+3 to jections, in which CR and SBR are assumed to outcompete MR (tech- other countries is merged together with ‘informal waste treatments’ due nologically and quantity wise) to deal with plastic waste. In S2, all sorted to limited data available to estimate exact fate of these flows, which has plastic waste, including the rejects from sorting and MR (i.e., 90–100% been pointed out by previous studies (Material Economics, 2022; Agora of mass, SYSTEMIQ, 2022) and mixed waste streams (i.e., 50–80% of Industry, 2022; SYSTEMIQ, 2022; Lase et al., 2021). Plastic packaging mass, SYSTEMIQ, 2022) are assumed to be processed via CR. S3 in- waste export (including non-household waste) usually occurs after a vestigates the CR and SBR options as an alternative technology to MR certain degree of separate collection (and sometimes partial sorting), i. option. In S3, it is assumed that CR and SBR options would take a small e., 25% of the sorted bales are sent to countries outside EU27+3, as share of plastic waste stream that is already mechanically recycled (i.e., suggested by Antonopoulos et al. (2021). The plastic waste treatment of 1–20% mass), including rejects (i.e., 90–100% mass, SYSTEMIQ, 2022) the exported waste at their final destinations (e.g., to Southeast Asia or and mixed waste streams (i.e., 50–80% mass, SYSTEMIQ, 2022). S3 African countries) is poorly reported, however it is a combination of assumes that MR still outcompetes CR and SBR (technologically and recycling parts of it, with illegal dumping, unsanitary landfill, or open quantity wise) in processing sorted plastic waste. Also, it is assumed in burning of residues (Tran, 2018; Wang, 2014; Liang et al., 2021; Petrlik S3 that CR and SBR will only process low quantities of sorted plastic in et al., 2019; Chen et al., 2021; Lasaridi et al., 2018; Lase et al., 2021). 2030 because they encounter several operational (and technical) issues In this study, six scenarios are modelled (Table 1): one scenario as to scale up the technologies at industrial scale (Jehano et al., 2022; benchmark (i.e. the status quo in 2018) (S0), and five potential future Coates and Getzler, 2020; Tukker et al., 1999). Manzuch et al. (2021) scenarios in 2030 (S1–S5). The future scenarios take into account the and Kusenberg et al. (2022e) also indicates that significant improve- feedstock type, composition, technology readiness level, and few im- ments are needed to upgrade pyrolysis oil as well as feedstock quantity provements within the waste management systems (e.g., PP flex pack- (and quality) for industrial steam crackers. Improvements are also still aging waste could be separated from the mixed films streams; Lase et al., needed to scale up and optimize SBR technique (Jehano et al., 2022; 2022). Table 1 also summarizes the supporting argumentations and Coates and Getzler, 2020; Tukker et al., 1999). Hence, S3 can also be assumptions of the five potential future scenarios in 2030, including perceived as ‘sub-optimal’ CR and SBR implementation, while MR is still information on the feedstock to CR and SBR options and their output(s). chosen to be the main recycling technology. Furthermore, S4 in- Moreover, it is assumed that the rate of waste export in 2030 will be vestigates CR as complementary technology to MR for waste streams significantly lower compared to the status quo scenario in 2018 because that otherwise would be landfilled or incinerated. In S4, CR is assumed of two reasons. First, the implementation of CR and SBR is expected to to process mixed polyolefin (PO) packaging (rigid and flexible) bales, allow more heterogenous waste streams to be reprocessed inside mixed plastic packaging bales, 50–80% rejects, and 90–100% mixed EU27+3 and second, stricter regulations of transboundary waste ship- waste streams. Notice that in the development of this scenario we strive ment (e.g., as mandated by UNEP Basel Convention; Lasaridi et al., to learn from, and to the extent possible align with, precedent studies 2018). It is important to note that indeed other scenarios might enroll in that investigated the potential role of CR and SBR in the future in EU future work too, based on new developments and insights. 27+3 (in S4, notably SYSTEMIQ, 2022; Arena and Ardolino, 2022; S1 illustrates the improvements of current state-of-the-art plastic Hann and Connock, 2020; Manˇ zuch et al., 2021). Finally, S5 is identical 4 I.S. Lase et al. Resources, Conservation & Recycling 192 (2023) 106916 Table 1 Overview of the developed scenarios for the MFA of plastic waste in European Union 27+Norway, Switzerland, and the United Kingdom. ABS (Acrylonitrile Butadiene Styrene), APW (agriculture plastic waste), CDW (construction and demolition waste), CR (Chemical recycling), ELV (end-of-life vehicle), MR (Mechanical recycling). PE (Polyethylene), PA (Polyamide), PET (Polyethylene Terephthalate), PP (Polypropylene), PS (Polystyrene), PUR (Polyurethane), PVC (Polyvinyl Chloride), SBR (solvent-based recycling), TCs (transfer coefficients), TD (Triangular distribution), WEEP (waste electronic and electrical plastic). Scenarios Supporting argumentation Description Input(s) for CR and SBR Output(s) from CR and SBR S0: Status quo in 2018 Benchmark (reference) scenario Flows of plastic waste in 2018 Not applicable Not applicable S1: Plastic waste treatment via MR in Improvement in waste collection rate, Improved TCs of waste collection Not applicable Not applicable 2030 sorting, and MR in 2030 towards rate, sorting, and MR yield in breakthrough of (currently) known 2030 towards. The rejects (from best practices in 2022 based on sorting and MR) and mixed waste previous studies (Maury et al., 2022; streams are sent to residual Lase et al., 2021; Antonopoulos et al., treatment 2021). S2: Plastic waste treatment via CR and ‘Explorative’ projections of plastic All sorted plastic are sent to CR or Dissolution-precipitation: Chemical SBR in 2030 waste management in which CR and SBR, including 50–80% rejects Sorted PVC and PS from depolymerization and SBR options technologically from sorting and MR (assuming CDW dissolution- outcompetes MR option TD) and 90–100% mixed waste Chemical depolymerization: precipitation: ○ ○ streams (assuming TD) in 2030 Sorted PET bales (packaging Polymer (and flakes sector) for dissolution- Manually dismantled and precipitation) post-sorted PA and PUR from Pyrolysis with Steam ELVs Cracking: Pyrolysis with Steam Cracking: Polymer ○ Sorted PE film, PP film, PE ○ Base chemicals (e.g., rigid, PP rigid, mixed PO wax, benzene, (film and rigid), and mixed toluene, xylene, etc.) plastic film bales (packaging Fuels (i.e., synthesis sector) gas) Manually dismantled and Gasification with sorted PP from ELVs Fischer-Tropsch Sorted PP, PS and ABS from Synthesis: WEEP Polymer ○ Sorted PE and PP from CDW ○ Base chemicals (e.g., and APW tar, benzene, Gasification with Fischer- toluene, xylene, etc.) Tropsch Synthesis: Fuels (i.e., synthesis Rejects from sorting and MR oil) Mixed waste streams S3: Plastic waste treatment via MR and ‘Sub-optimal’ CR and SBR Improved TCs of collection, Dissolution-precipitation: Chemical CR in 2030, in which MR option still implementation, while MR is still sorting, and MR yield in 2030, ○ Sorted PVC and PS from depolymerization and technologically outcompetes CR and chosen as the main recycling option. while CR or SBR treats 1–20% CDW dissolution- SBR options Sub-optimal implementation is caused mass (assuming TD) of sorted Chemical depolymerization: precipitation: ○ ○ by operational (and technical) issues to plastic waste from different Sorted PET bales (packaging Polymer (and flakes scale up CR and SBR technologies to sectors that is already sent to MR sector) for dissolution- industrial scale (Jehano et al., 2022; (in S1). Plastic waste in reject Manually dismantled and precipitation) Coates and Getzler, 2020; Tukker (50–80%, assuming TD) and sorted PA and PUR from Pyrolysis with Steam et al., 1999) and the need to optimize mixed waste streams (90–100%, ELVs Cracking: CR and SBR technologies (Manˇ zuch assuming TD) are also sent to CR Pyrolysis with Steam Cracking: Polymer et al., 2021; Kusenberg et al., 2022e). in 2030 ○ Sorted PE film, PP film, PE ○ Base chemicals (e.g., rigid, PP rigid, mixed PO wax, benzene, (film and rigid), and mixed toluene, xylene, etc.) plastic film bales (packaging Fuels (i.e., synthesis sector) gas) ○ Manually dismantled and Gasification with sorted PP from ELVs Fischer-Tropsch ○ Sorted PP, PS and ABS from Synthesis: WEEP Polymer ○ ○ Sorted PE and PP from CDW Base chemicals (e.g., and APW tar, benzene, Gasification with Fischer- toluene, xylene, etc.) Tropsch synthesis: ○ Fuels (i.e., synthesis Rejects from sorting and MR oil) ○ Mixed waste streams S4: Plastic waste treatment via MR and CR as complementary technology to Improved TCs of collection, Relevant to S4 and S5: Relevant to S4 and S5: CR in 2030, in which CR options MR for waste streams that otherwise sorting, and MR yield in 2030, Chemical depolymerization: Chemical serve as complementary technology would be landfilled or incinerated such while CR treats mixed PO bales, depolymerization: to treat waste streams that otherwise as mixed PO packaging (rigid and mixed plastic bales, mixed waste Sorted PA from ELVs would be landfilled or incinerated flexible) bales, mixed plastic packaging (90–100%, assuming TD) and the Pyrolysis: ○ Polymer bales, rejects, and mixed waste reject streams from sorting and Pyrolysis with Steam streams. (SYSTEMIQ, 2022; Arena and MR (50–80%, assuming TD) in ○ Mixed Plastic bales and Cracking: Ardolino, 2022; Hann and Connock, 2030 Mixed Polyolefin (MPO) ˇ ○ 2020; Manzuch et al., 2021). bales Polymer Gasification: Base chemicals (e.g., wax, benzene, Rejects from sorting and MR toluene, xylene, etc.) (continued on next page) 5 I.S. Lase et al. Resources, Conservation & Recycling 192 (2023) 106916 Table 1 (continued ) Scenarios Supporting argumentation Description Input(s) for CR and SBR Output(s) from CR and SBR ○ ○ Mixed waste streams Fuels (i.e., synthesis gas) Gasification with Fischer-Tropsch Syn- thesis: Polymer Base chemicals (e.g., tar, benzene, toluene, xylene, etc.) ○ Fuels (i.e., synthesis oil) S5: Plastic waste treatment via MR and Identical to S4, with extra mass CR in 2030, in which CR options from accounting the ‘missing serve as complementary technology plastic’ (Plastics Europe, 2020; to treat waste streams that otherwise Plastics Europe, 2019b) landfill or incinerated, including the ‘missing plastic’ in 2030 to S4 but accounts for the extra plastic mass (in kt) derived from the next section). ‘missing plastic’, and explores the impact of processing ‘missing plastic’ The improvement of sorting and MR yields in 2030 are projected by on the overall performance of plastic waste treatment in EU 27+3. When assuming that the best practices of plastic waste sorting and recycling the quantities of ‘missing plastic’ are normalized to the total plastic will be reached by 2035 (Antonopoulos et al., 2021). The assumption demand in Europe in 2019 and 2020 (Plastics Europe, 2020, 2019b), illustrates the optimization and widespread implementation of best they account for 15–30% of the total plastic demand. A more detailed available technologies in sorting and recycling different polymers across description of the explorative future scenarios and improvements per different sectors by 2035. The whole dataset in Table S2–S6 is used to sector is reported in the SI–Section 3. calculate the uncertainty of the flows in 2030. Through this approach, the annual growth of sorting and recycling yields are calculated for 2.3.2. Transfer coefficients different polymers across different sectors. More detailed information on For the purpose of calculating the uncertainty of the outputs, the TCs the projections of collection rate, sorting, and recycling yields can be are assumed to have a Triangular Distribution (TD) to cover the diversity found in Figure S10–S22. of the information from several studies. The full list of TCs for the listed scenarios in 2018 and 2030, together with the corresponding TD, can be 2.3.2.2. Transfer coefficients of chemical and solvent-based recycling. found in Table S2–S6. Essentially, the study of Watkins et al. (2020) is Pyrolysis, coupled with Distillation, Hydrotreatment, and Steam Cracker: used as the primary data points to model the flows of plastic in 2018. The first steps of the (after the plastic waste is separately collected and Additionally, a few studies are selected to be the key literature studies to sorted) are shredding, cold washing (to remove contaminants like compare or complement the TCs presented and used by Watkins et al. organic and inorganic residue; Lase et al., 2022) and extrusion (using (2020). Table S2–S6 provides information on the key literature that extrusive dehalogenation technique to remove substances like PVC and provide the TCs for the MFA modeling in the year 2018. Moreover, the flame retardants; Kusenberg et al., 2022e). Afterwards, the plastic approach to estimate TCs for the MFA model in 2030 as well as the TCs wastes are fed into the cracking and condensation reactor to produce for CR and SBR are elaborated in the next sections. pyrolysis oil that is distilled into naphtha and wax. The naphtha is fed into the steam crackers (with pyrolysis oil upgrading such as hydro- 2.3.2.1. Improved transfer coefficients in 2030 for collection, sorting, and treatment) to produce monomers, which are used as a feedstock to mechanical recycling. To model the flows of plastic in 2030, it is assumed recreate polymers again, and base chemicals. The TCs of the shredding, that the collection rate, sorting, and MR yield will improve. For collec- washing, and extrusion of MPO and Mixed Plastic bales are adopted tion, improvements of the collection rates are extrapolated (and pro- from Lase et al. (2022) and Civancik-Uslu et al. (2021). The TCs from the jected in 2030) using linear regression based on the past reported cracking and condensation until (re)polymerization are obtained from collection rate from several sources (Hestin et al., 2017; Global E-Waste literature (Civanvik-Uslu, 2021; Kusenberg et al., 2022a; Kusenberg Statistics Partnership, 2022; Eurostat, 2021; 2022a, 2022b). From the et al., 2022b; Larrain et al., 2020; Jeswani et al., 2021; Genuino et al., linear regression calculations, the annual growth of the collection rates 2022; Ghalomi et al., 2021; Zayoud et al., 2022; Kusenberg et al., from 2018 to 2030 are obtained. For the packaging sector, the projection 2022e). is based on Hestin et al. (2017) in 2012–2014. The annual growth of Gasification , coupled with Fischer-Tropsch Synthesis: the processing of collection rate is estimated to be 4.0%. For the automotive sector, the mixed waste and reject streams (from sorting and MR) via gasification collection rate is calculated as the share (or ratio) of the reported ELV starts with shredding the plastic waste into flakes followed by feeding recycling over ELV waste generated from Eurostat (2021) in 2010 – them into gasification reactors to create mainly syngas with a small 2019. The annual growth of ELV collection rate is estimated to be 1.4%. fraction of tar and char. The syngas is processed through Fischer- Similarly, the collection rate of waste electronic and electrical equip- Tropsch Synthesis (FTS) to create monomers (incl. other base chem- ment (WEEE) is calculated as the share (or ratio) of the reported WEEE icals) that are used as feedstock for repolymerization processing. The generation (Global E-Waste Statistics Partnership, 2022) over the TCs for converting plastic waste into syngas are obtained from literature collected WEEE (Eurostat 2022b) in 2015 – 2019, with the annual (Mastellone, 2019; Lopez et al., 2018; Brems et al., 2015; Mastellone and growth of collection rate equal to 1.4%. For the building & construction Zaccariello, 2013; Arena, 2012). Lastly, the TCs for FTS and (re)poly- and agriculture sector, it is assumed that the improvements of the merization are estimated from Zhao et al. (2021), Lee et al. (2008), and collection rates are similar to the annual growth of the respective waste Jeswani et al. (2021). generation, i.e., annual growth of 0.8% for construction and demolition Chemical depolymerization (i.e., glycolysis, methanolysis, aminolysis, waste (CDW) and 1.0% for agriculture plastic waste (APW) (more in the etc.) is mainly implemented on sorted PET, PA, and PUR. The process 6 I.S. Lase et al. Resources, Conservation & Recycling 192 (2023) 106916 starts with shredding and washing followed by depolymerization. The Table 2 Summary of circularity indicators of plastic waste treatment, their correspond- TCs for shredding and washing are estimated from Larrain et al. (2020) ing definitions and formulas applied in this study, which are also elaborated in and Lase et al. (2022), while the TCs for depolymerization are obtained previous studies (UNEP, 2011; Perio et al., 2018; Broeren et al., 2022; Arena and from Kol et al. (2021), Vollmer et al. (2020), Schwarz et al. (2021), Shen Ardolino, 2022). et al. (2010), and Nikje et al. (2011). Circularity Definition Equation Solvent-based recycling (e.g., dissolution-precipitation) is employed to indicators dissolve the polymer waste using a solvent, followed by the removal of μ + μ additives through filtration or phase extraction to recover the dissolved End-of-life The total mass of plastic polymer base chemicals EoL RR = (in recycling waste that is converted polymer and the solvent (Crippa et al., 2019). The TCs for solvent-based reported waste rates (EoL- into secondary S0–S4) (Eq. 1) purification are estimated from literature (Schwarz et al., 2021; Naviroj RR) materials (polymers μ + μ polymer base chemicals et al., 2019). More detailed information on the TCs for CR and SBR EoL RR = and base chemicals) μ + μ reported waste missing plastic considered and used in this study can be found in Table S7–S11. over total plastic waste (in S5) (Eq. 2) generation (i.e., reported plastic waste 2.3.3. Waste categories and quantities (in S0–S4) plus the ‘missing plastic’ (in S5) 2.3.3.1. Waste quantity in 2018. Table SI12 shows the waste categories under the definition of ‘ recycling’ from the and quantities (in kilo tonne, kt) used in this study, including some European Commission examples of the relevant products of the respective category. The esti- (2018a, 2008), mation of waste quantities in 2018 is mainly based on Watkins et al. excluding plastic (2020). Within the packaging group, the share of mono- and multi-layer waste-to-energy (e.g., flexible packaging is estimated to be 80% and 20%, respectively (Lase hydrocarbons) polymer Plastic-to- The total of plastic et al., 2022). The share of bottles and pots, trays and tubes (PTTs) for PP P2P = (in S0–S4) (Eq. 3) plastic rate waste that is converted reported waste rigid, HDPE, and PET is estimated from Hestin et al. (2017). The (P2P) into new polymer over polymer P2P = (in S5) quantities of EPS foam are estimated from Hestin et al. (80), i.e., 33% of the total plastic waste μ + μ reported waste missing plastic the total PS in the packaging sector. In the automotive sector, the generation (Eq. 4) base chemicals quantities of PA is estimated to be 12% of the total polymer used (Maury Plastic-to- The total of plastic P2C = (in S0–S4) (Eq. 5) chemicals waste that is converted reported waste et al., 2022; European Commission, 2020). Lastly, the quantities of PP base chemicals rate (P2C) into base chemicals P2C = (in S5) and ABS used in the electronic sector are estimated from Lase et al., μ + μ over the total plastic reported waste missing plastic (2021) and European Commission (2020). (Eq. 6) waste generation fuel Plastic-to- The total of plastic P2F = (in S0 – S4) (Eq. 7) fuels rate waste that is converted reported waste 2.3.3.2. Estimation of waste quantity in 2030 based on historical data (P2F) into fuels for energy use fuel P2F = (in S5) extrapolation. The quantities of the selected polymers in 2030 are μ + μ over the total plastic reported waste missing plastic extrapolated using linear regression based on the historical waste gen- waste generation (Eq. 8) eration found in statistical databases (Eurostat, 2021, 2022a, 2022b, The definition of ‘recycling’ as stated in European Commission (2018a, 2022c), e.g., from 2010 to 2018 in packaging sector based on data 2008) reports are ‘any recovery operation by which waste materials are reprocessed availability for EU27+3 found in Eurostat (2022a), more in into products, materials or substances whether for the original or other purposes. It Figure S23–S27. Later, the information on the annual growth per sector includes the reprocessing of organic material but does not include energy recovery and is extracted and applied to estimate the quantities of waste in 2030 (see the reprocessing into materials that are to be used as fuels or for backfilling opera- Table SI12). For the packaging, automotive, and electronic sector, the tions’. Hence, it (mainly) includes plastic waste recycling back into plastic from projections are based on the historical packaging waste, ELV, and WEEE mechanical recycling in 2018. When chemical recycling is implemented in 2030, generation based on Eurostat (2021, 2022a, 2022b). Regarding the ‘recycling’ can include plastic waste recycling back into plastic or other mate- projections of waste quantities for building & construction and agri- rials for other purposes (e.g., base chemicals from pyrolysis for petrochemical industry such as cosmetics, fertilizers, pharmaceutical, etc.), excluding fuel or culture sectors, historical waste quantity data by NACE activity (NACE energy use. F: Construction and NACE A: Agriculture, forestry, and fishing, respec- tively) are extracted from Eurostat (2022c). Overall the annual growth (μ ) that is converted into polymers (μ ), base chemicals rates for packaging, ELV, WEEE, CDW, and APW are 1.4–1.8%, waste generation polymer 1.3–1.6%, 1.1–1.2%, 0.8–0.9%, and 1.0–1.1%, respectively. Detailed (μ ), and fuels (μ ), respectively (Broeren et al., 2022; Arena base chemicals fuel results of the projections and annual growth can be found in Supple- and Ardolino, 2022). On the denominator, in S0–S5, only the reported mentary Materials, section 8. plastic waste (μ ) is considered and in S5 the reported plastic reported waste waste plus ‘missing plastic’ (μ + μ ) is considered (see reported waste missing plastic Fig. 2). In all developed scenarios, the assumed legal waste export for 2.4. Circularity indicators recycling is not counted in the EoL-RR and P2P rate calculations. The summary of the four circularity indicators can be found in Table 2 (Eqs. 1–8). In Fig. 2, a conceptual diagram of life cycle of plastic 2.5. Uncertainty analysis is presented to show the calculation point of each indicator. The end-of- life recycling rate (EoL-RR) (measured in%) is calculated as the ratio The uncertainty analysis is calculated because of the diversity of the between the total mass (in kt) of polymer and base chemicals (μ + polymer modeling inputs that are taken from relevant literature related to the μ ) that is produced from the plastic waste treatments over the waste management practices in EU 27+3 (Table S2–S6). The uncertainty base chemicals waste generated (μ ) (in kt) (UNEP, 2011; Perio et al., 2018). analysis is calculated assuming TD of the input parameters (i.e., the waste generation On the numerator, only polymer and base chemicals are considered as TCs). As suggested by Bisinella et al. (2016), the uncertainty is calcu- recycled products to conform to the definition of ‘recycling’ by the WFD lated by systematically propagating the output uncertainties (i.e., mass (European Commission 2018a, 2008), which excludes materials (such as of plastic flows and circularity indicators). For this, the Monte Carlo fuel) for energy usage. The plastic-to-plastic rate (P2P), plastic-to-chem- analysis with 1000 iterations is used to randomly sample a value within icals rate (P2C), and plastic-to-fuels rate (P2F) (measured in%) are each uncertainty distribution and calculate the standard deviation, described as the share of total mass (in kt) of plastic waste generated which is shown relative to the likely value in%. For example, if the MFA 7 I.S. Lase et al. Resources, Conservation & Recycling 192 (2023) 106916 Fig. 2. Conceptual diagram of life cycle of plastic (adapted from Plastics Europe) (Plastics Europe, 2019a, 2019b) to show the calculation points for each circularity indicator and recycled content availability. The thickness of the flows does not represent mass/quantity. Abbreviation: EoL-RR (End-of-life recycling rate), P2C (plastic-to-chemicals), P2F (plastic-to-fuel), P2P (plastic-to-plastic). result shows 4090 kt of polymer production with the uncertainty of 3. Results ±353 kt, the result is presented as 4090 kt±9% (i.e., 353 kt / 4090 kt × 100%). For the circularity indicators, if the EoL-RR is estimated to be 3.1. Material flow analysis: status quo (in 2018) and future scenarios (in 24% with ±2% uncertainty, it means that the likely values (i.e., 24%) 2030) can be deviated to 22% (min.) and 26% (max.). This approach is consistently applied throughout the MFA modeling in this study. The MFA results of the ten polymers over the different sectors are shown in Figs. 3A–F for S0 – S5, respectively. Per sector, the Sankey diagrams can be found in Figures S29-S53, and the mass balances can be 2.6. Estimation of the recycled content availability in 2030 found in Table S15. In the status quo scenario (S0), it is estimated that 3273 ± 9% kt of From the MFA model results, the potential use of recycled plastic in polymer (i.e., recycled plastic) is produced from plastic recycling sys- different markets and applications is investigated. However, it is chal- tems in 2018, while 12,287 ± 3% kt plastic waste are sent for residual lenging to project future market uptake of recycled plastic production treatment and 1805 ± 5% kt are sent to waste export and/or informal because of i) different quality of recycled plastic, ii) a breadth of tech- treatment (e.g., illegal export or unauthorised recycling by brokers or nical requirements of various applications, and ii) market saturation of scraps dealers) (Fig. 3A). According to the figures from Plastics Europe some applications (Demets et al., 2020; Huysveld et al., 2022; Tonini (Plastics Europe, 2019a, 2019b), it is estimated that 37% and 63% of the et al., 2022). In this study, two assumptions are considered to quantify waste sent for residual treatment is landfilled and incinerated, the potential recycled plastic (in kt) and recycled content (in%) avail- respectively. ability in 2030. First, projecting the share of market uptake of recycled The results obtained for S1, assuming best practices of waste plastics in 2018 reported by Watkins et al. (2020) and European Com- collection, sorting, and MR are widely applied in the whole EU 27+3, mission (2020) (details in Table S13). Second, assuming 100% show that the recycled plastic production is expected to increase to closed-loop recycling, i.e., no mass exchange between the sectors. The 10,277 ± 5% kt (Fig. 3B), which is approx. 3.0 times higher than what is closed-loop recycling itself is defined as the use of recycled materials for estimated for S0. Still, a considerable amount of plastic waste is sent to the same market applications as that of its previous life cycle (UNEP, residual treatment (i.e., 10,253 ± 5% kt) and a small share is still sent to 2011), e.g., recycled plastics from packaging waste is used in the same waste export and/or informal treatment (402 ± 10% kt). From the re- sector. This is perceived as ‘explorative’ projection, in a sense that it sults obtained for S2, which is the scenario in which CR and SBR have does not take into account for example quality aspects yet (e.g., tech- become dominant (i.e., CR and SBR technologically outcompetes MR), it nical properties, processability, color, etc.) because of the difficulty to can be observed that 7903 ± 6% kt of recycled plastic are produced predict future market uptake (incl. potential market share of the inten- together with 7247 ± 6% kt of base chemicals and 1189 ± 4% kt of fuel ded applications) and the quality of recycling (Huysveld et al., 2022; (Fig. 3C). The recycled plastic production in S2 (i.e., 7903 ± 6%) is Tonini et al., 2022; Hestin et al., 2017) at the time of writing the approx. 2.5 times higher than in S0. However, the recycled plastic manuscript. Thus, it should be seen as a maximum uptake under optimal production in S2 is slightly lower than in S1 (i.e., a reduction of approx. conditions and it is likely that the actual uptake will be lower. 23% of recycled plastic produced compared to S1), yet considerable The recycled content (in%) is quantified as the share of the uptake of amounts of base chemicals and fuels are produced in S2 as opposed to recycled plastic over the projected plastic demand per sector in 2030 S1. Important to note is that these numbers are based on the Transfer (Eq. (9)). For this purpose, the plastic demand in 2030 is projected using Coefficients (TCs) retrieved from current data sources (see Table S7- linear regression from Plastics Europe (data from 2014 to 2020) (Plas- S11), and, while potential improvements in the technology might still tics Europe, 2019a, 2019b) and is elaborated in Figure S28. It is occur, it is nevertheless difficult to quantify technological learnings important to note that the amount of plastic flowing from use phase to without an established history (as assumed for MR, sorting or collection EoL phase (μ ) in 2030 is not the same as the plastic demand rates). waste generation in 2030 (μ ) because some plastic will remain in ‘stock’ In Fig. 3D and 3E, the MFA results display that 12,262 ± 6% kt and plastic demand 12,740 ± 6% of recycled plastic are estimated to be produced from S3 (μ ) depending on their lifespan distribution (Fig. 2), as described by stocks (the scenario in which little competition between CR, SBR, and MR Lase et al., (2021). occurs) and S4 (the scenario in which CR serves as complementary Uptake of μ (per sector, in 2030) polymer technologies to MR), respectively. This shows that the implementation Recycled content availability = μ (per sector, in 2030) Plastic Demand of MR, CR and SBR in treating plastic waste delivers a higher quantity of recycled plastic compared to S1 (which considers only improved MR) × 100% and S2 (which considers only CR and SBR). In particular, the MFA results (9) for S4 estimate that CR produces 3110 ± 6% kt recycled plastic. This 8 I.S. Lase et al. Resources, Conservation & Recycling 192 (2023) 106916 Fig. 3. Material flow analysis of the selected polymers throughout the waste management systems in EU 27+3 in 2018 and 2030 of S0 (3A), S1 (3B), S2 (3C), S3 (3D), S4 (3E) and S5 (3F). Values are in rounded in kilo tonne, including the calculated standard deviation (in%). Different colors represent different polymer types, while the gray color refers to waste export and/or informal waste treatment (e.g., illegal export or unauthorised recycling brokers/scraps dealers), mixed waste, reject (from sorting, washing, extrusion), and residual streams. The dark green, light green, and dark brown colors represent (mixed) polymer, base chemicals, and fuel productions from chemical recycling, respectively. finding aligns with SYSTEMIQ (2022) and Caro et al., (2022) that esti- scenarios is estimated to be 683 ± 4% kt and 628 ± 4% kt, respectively. mate around 3100 and 3400 kt P2P production from CR and SBR, For S5 (the scenario in which extra mass from the ‘missing plastic’ is respectively. On the other hand, in S3 and S4, the amount of base treated via CR and MR), the recycled plastic, base chemicals, and fuel chemicals production from plastic waste treatment is estimated to be production from plastic waste is estimated to be 18,536 ± 6% kt, 5556 4272 ± 6% kt and 3951 ± 6% kt (i.e., a reduction of 41% and 45% ± 6% kt, and 881 ± 4% kt, respectively (Fig. 3F). The inclusion of the compared to S2, respectively), while the fuel production from the same ‘missing plastic’ in future plastic waste recycling treatment, combined 9 I.S. Lase et al. Resources, Conservation & Recycling 192 (2023) 106916 Fig. 3. (continued). with complementarity between MR and CR, increases the total recycled 3.2. Circularity of plastic value chain: to what extent can chemical plastic production by 5.5 times relative to S0. This would allow reaching recycling contribute to improve plastic recycling in EU? the recycled content target (Section 3.3). Table 3 summarizes the results obtained for the circularity indicators 10 I.S. Lase et al. Resources, Conservation & Recycling 192 (2023) 106916 Fig. 3. (continued). 11 I.S. Lase et al. Resources, Conservation & Recycling 192 (2023) 106916 Table 3 the smallest improvement in P2P rate (compared to the S0 status quo, Summary of the circularity indicators for all scenarios in 2018 (S0) and 2030 18% ± 2% P2P rate) is observed for S2 (i.e., 38% ± 2%) where all the (S1–S5). Values are rounded, including the standard deviation (in%). Acronyms: sorted plastic waste, including the rejects (from sorting and MR) and CR (chemical recycling), EoL-RR (end-of-life recycling rate), MR (mechanical mixed waste streams, are sent to CR options. The result obtained for S2 recycling), P2C (plastic-to-chemical), P2F (plastic-to-fuel), P2P (plastic-to- (CR and SBR become more dominant than MR) is lower than what is plastic), SBR (solvent-based recycling). obtained for S1 (i.e., 49% ± 3%) where all sorted plastic waste is treated Overall S0 S1 S2 S3 S4 S5 via MR (and CR and SBR are assumed zero). circularity indicators 3.3. Recycled content availability in 2030 P2P 18% ± 49% ± 38% ± 58% ± 61% ± 61% ± 2% 3% 2% 3% 3% 3% P2P from MR 18% ± 49% ± – 41% ± 46% ± 46% ± Figs. 4 and 5 summarize the potential recycled plastic (i.e., only P2P 2% 3% 3% 3% 3% from MR, CR, and SBR) and recycled content (RC) availabilities in 2030 P2P from CR and – – 38% ± 17% ± 15% ± 15% ± per sector. Fig. 4 shows the results assuming that the share of recycled SBR 2% 1% 1% 1% plastic uptake between sectors in 2018 is maintained in 2030 (i.e., P2C – – 35% ± 20% ± 19% ± 19% ± 2% 1% 1% 1% closed-loop and open-loop recycling occur). For example, recycled P2F – – 6% ± 3% ± 3% ± 3% ± plastic from plastic waste in packaging sector can be used for applica- 0% 0% 0% 0% tions in packaging and other sectors too. In contrast, Fig. 5 shows the EoL-RR 18% ± 49% ± 73% ± 78% ± 80% ± 80% ± results assuming 100% closed-loop recycling (i.e., the recycled plastic is 2% 3% 3% 3% 3% 3% used in the same sector where the waste is originated). For example in The ‘overall’ data points quantify the sum of mass quantities (in kt) from all Fig. 4A, it is estimated that the packaging sector will demand 22,057 kt sectors and aggregated calculations for the circularity indicators. of plastic (blue bar) in 2030 and it is estimated that 2817 kt of recycled EoL-RR considers only P2P and P2C because P2F recycling does not conform plastic (green bar, in S1) will be produced, result in 13% RC availability to the definition of ‘recycling’ in WFD (European Commission, 2018a, 2008). (red dot, S1 in Fig. 4A). In Fig. 5A, assuming 100% closed-loop recycling based on best practices in MR, it is estimated that 8528 kt of recycled (EoL-RR, P2P, P2C, and P2F rates) for scenarios S0 – S5. The EoL-RR of plastic could be produced in S1 and will thus result in a potential RC plastic waste in S0 is 18% ± 2% in which the only contributor is P2P availability of 39% in packaging sector. In Fig. 4, the ‘others’ sector refer from MR. Significant improvements in the EoL-RR can be observed in all to household goods, furniture, textiles, sports equipment, etc. future scenarios (S1 – S5). The overall EoL-RR in S1 (i.e., 49% ± 3%) is From Fig. 4 it can be observed for all future scenarios (S1–S5) a approx. 2.7 times higher than in S0 (i.e., 18% ± 2%). For the S2, the considerable amount of recycled plastic is diverted into ’others’ sector EoL-RR (i.e., 73% ± 3%) is approx. 4 times higher than in S0 and it is (3670–7141 kt) and make the RC availability for ‘others’ sector the approx. 1.5 times higher than in S1. In S2, 38% ± 2% and 35% ± 2% of highest among other sectors (from 39% in S2 to 77% in S5). The building the overall EoL-RR come from P2P and P2C from CR and SBR (only P2P), and construction sector comes second as the biggest recycled plastic respectively. However the P2P rate in S2 (38% ± 2%) is slightly lower receiver (from 1986 kt in S2 to 5229 kt in S5), followed by the packaging than the P2P rate in S1 (49% ± 3%) (Table 3). sector (from 1318 kt in S2 to 3960 kt in S5). These result to RC avail- The results of circularity indicators for S3 and S4 estimate that the ability ranges from 17% in S2 to 46% in S5 for building and construction overall EoL-RR increases by approx. 4.5 times higher relative to S0 sector, while the RC availability in packaging sector ranges from 6% in (Table 3). When comparing to S1, the EoL-RR of S3 and S4 (i.e., 78–80% S2 to 18% in S5. The recycled plastic availabilities in the automotive ± 3%) is 1.6 times higher, while when comparing to S2, the EoL-RR of S3 (from 656 kt in S2 to 857 kt in S5), electronic (from 170 kt in S2 to 415 kt and S4 is 1.1 times higher. It is estimated that the EoL-RR in S3 and S4 in S5), and agriculture sectors (from 107 kt in S2 to 936 kt in S5) are comes from P2P from MR (41–46% ± 3%), P2P from CR and SBR considerably lower than the packaging, construction and ‘others’ sector. (15–17% ± 1%), and P2C from CR (19–20% ± 1%). When the ‘missing These result in a considerably lower RC availability in automotive sector plastic’ is included in S5, the EoL-RR is identical to S4 however S5 (6–15%) and electronic sector (3–11%). Again, note that all these results produces more recycled plastics, base chemicals, and fuels as elaborated assume that the share of recycled plastic uptake between sectors in 2018 in the previous section (Section 3.1). It is important to note that in this will be maintained in 2030. study the EoL-RR is calculated as the share of total recycled plastic (and When 100% closed-loop recycling is assumed (Fig. 5), the packaging base chemicals) over waste generated (incl. ‘missing plastic’ in S5) sector is expected to receive the highest amount of recycled plastics (i.e., hence resulting the same EoL-RR in S4 and S5, but with different 7698–11,430 kt), as expected, followed by the building and construction quantities involved. Furthermore, in all scenarios where CR options are sector (i.e., 619–2107 kt) since most of the recycled plastics are pro- implemented, the P2F rate is relatively low ranging from 3% (S3–S5) to duced from these sectors (see Table SI15). The highest increase of RC 6% (S2). availability can be observed in the packaging and electronic sectors (i.e., In Table S16 the plastic circularity per sector can be found. In status 3.5 times higher than assumed 2018 market uptake) and the lowest quo scenario (S0) the highest EoL-RR is achieved by agriculture sector increase in the automotive sector (i.e., 1.5 times higher than assumed (44% ± 5%), followed by building and construction (30% ± 2%), 2018 market uptake). As results, the RC availability increases to 35–52% packaging (17% ± 2%), electronic (17% ± 2%), and automotive sectors in packaging sector and 5–38% in electronic sector. Still, in the auto- (10% ± 1%), which is comparable with Maury et al., (2022) study. In all motive sector the RC availability increases to 5–26% (Fig. 5). Instead, as future scenarios (S1–S5), the EoL-RR will increase. In the most positive expected, the potential RC availability in the construction sector is 2.5 future scenarios (S4 and S5) the highest EoL-RR is achieved by building lower than if current trends are maintained (open- and closed-loop, and construction and agriculture sectors (84% ± 5%), followed by Fig. 4), which reduces the RC availability to 5–19%. packaging sector (81% ± 3%), automotive (72% ± 4%), and electronic sectors (60% ± 3%). CR and SBR implementation contribute in 4. Discussion increased EoL-RR in future scenarios by adding around 15–18% ± 2% of P2C and 8–25% ± 2% of P2P from CR and SBR, while P2P from MR 4.1. Interpretation and contextualization of the results in relation to other contributes 29–56% ± 3% (Table S16). Relative to S0, improved MR, CR studies and SBR implementation can increase the EoL-RR by roughly 2–5 times. When focusing only on the P2P rate, the highest improvements can The MFA results of the status quo scenario (S0, 3273 ± 9% kt) ob- be observed in S4 and S5 (61% ± 3%). Moreover, the results suggest that tained in this study is comparable to the findings of Watkins et al., 12 I.S. Lase et al. Resources, Conservation & Recycling 192 (2023) 106916 Fig. 4. Projected plastic demand (blue bar, in kt), recycled plastics production from mechanical recycling (green bar, in kt) and chemical recycling (orange bar, in kt), and recycled content (the dots, in%) assuming recycled plastic market uptake in 2018 based on Watkins et al., (2020) and European Commission (2020). The red dot represents the potential recycled content achieved via mechanical recycling. The black dot represent potential recycled content achieved via chemical recycling or the sum of mechanical recycling and chemical recycling. 13 I.S. Lase et al. Resources, Conservation & Recycling 192 (2023) 106916 Fig. 5. Projected plastic demand (blue bar, in kt), recycled plastics production from mechanical recycling (green bar, in kt) and chemical recycling (orange bar, in kt), and recycled content (the dots, in%) assuming 100% closed-loop recycling. The red dot represents the potential recycled content achieved via mechanical recycling. The black dot represent potential recycled content achieved via chemical recycling or the sum of mechanical recycling and chemical recycling. 14 I.S. Lase et al. Resources, Conservation & Recycling 192 (2023) 106916 (2020) (i.e., 3854 kt of recycled plastic in 2018). Plastics Europe (2020) targets, since the production of fuels (i.e., recycling products to be used instead estimated a higher amount of recycled plastic, i.e., around 4900 as energy sources such as hydrocarbons) is not considered as ‘recycling’ kt in 2018, likely due to the higher number of polymer types considered. under the Waste Framework Directive (WFD) (European Commission, In S0 (status quo scenario), the total amount of waste export and/or 2018a, 2008). In this context, this study strives to differentiate between informal waste treatments (1805 ± 5% kt) is comparable to Plastics multiple outputs from CR (i.e., polymer, base chemicals, and fuel) in the Europe (2020) and Eurostat (2022d) data, which indicate a total export endeavor to better illustrate the potential contributions of CR technol- of 1900 kt and 1593 kt in 2018, respectively. Several studies have shown ogies to plastic circularity and recycling rates. Moreover, it is important that plastic waste can be legally or illegally exported to countries like to highlight that in all future scenarios in which CR options for plastic Turkey, Malaysia, Vietnam, Ghana, Nigeria, Argentina, etc. (Tran, 2018; waste treatment are considered, the base chemicals production refers to Wang, 2014; Liang et al., 2021; Petrlik et al., 2019; Chen et al., 2021). producing valuable materials (e.g., wax, benzene, toluene, xylene, Note that in this study the exported waste is neither counted as recycling methane, propane, etc.) as suggested by previous studies (Civancik-Uslu (i.e., not contributing to the EoL-RR) nor considered in the calculation of et al., 2021; Kusenberg et al., 2022a; Kusenberg et al., 2022b; Kusen- recycled content availability in EU27+3. The exact fate of the currently berg et al., 2022c; Ghalomi et al., 2021; Zayoud et al., 2022), which shipped waste, evolution of export quantities, and final geographical might be used as feedstock in the petrochemical industries. Moreover, and technical destination should be subjected to future research. the fuel is mainly hydrocarbons (gas and oil), which can also be used as Looking at each future scenario in 2030 (S1–S5), including when the energy input for CR processes (Civancik-Uslu et al., 2021; Larrain et al., CR and SBR are implemented, it can be observed that the recycled plastic 2020). produced from only CR and SBR implementation (S2; 7903±6% kt) is By observing the circularity indicators in all future scenarios considerably lower than the other developed scenarios in this study (i.e., (S1–S5), it can be noticed the most positive scenario with EoL-RR of 80% S1, S3, S4, S5). This also means that the highest recycled plastic pro- ± 3% is achieved when MR and CR are implemented simultaneously and duction possible can be achieved only when MR, CR and SBR are complementarily, as opposed to only improving MR (S1, EoL-RR 49% ± implemented simultaneously, as can be observed in the other investi- 3%) or CR and SBR (S2, EoL-RR 73% ± 3%). The highest EoL-RR (80% gated future scenarios in 2030. ± 3%) is indeed achieved in S4 and S5. In these two scenarios, the EoL- Focusing on the circularity indicators, it can be observed that RR reaches 80% ± 3% because of the contribution of improved MR modeling results of EoL-RR in 2018 (18% ± 2%) is lower than the one (46% ± 3%) and complementary CR (34% ± 1%), where, out of the reported by Plastics Europe (2019a, 2019b) (i.e., 33%) but higher than total obtained, 15% ± 1% is related to the P2P rate and 19% ± 1% to the the one reported by Material Economics (2022) and Agora Industry P2C rate. These findings illustrate the importance of balancing the (2022), which is 15%. Important aspects to consider when comparing plastic waste streams into MR and CR options to reach the highest these numbers are i) recycling rate measurement points (as numerator in circularity potential possible, i.e. the two technologies need to be the EoL-RR formula) and ii) total considered EoL plastic waste (as de- complementary and not competitive. It should also keep in mind that, in nominator in the EoL-RR formula). The reported EoL-RR from Plastics future scenarios, CR might be able to increase its P2P ratio (at the cost of Europe (2019a, 2019b) (i.e., 33% EoL-RR) calculates the share of sorted P2C and P2F), for example by applying other pyrolysis conditions such plastic waste that is sent to recycling facilities (9.6 Mt as the numerator) as by adding catalysts, hydrocracking, etc. (Kusenberg et al., 2022e; over the reported waste quantities (29.1 Mt as the denominator), which Kusenberg et al., 2022a). A study from Eschenbacher et al. (2022) increases the EoL-RR. The reported EoL-RR by Plastics Europe (2019a, suggests that the yield of olefins (i.e., C2–C4) from a mixed polyolefin 2019b) further excludes the ‘missing plastic’ (i.e., 8–15 Mt) and, to a waste can increase up to ~75% by introducing catalysts. Thus, for large extent, the losses from recycling, which inclusion will decrease example, if the yield of naphtha can improve, the P2P rate can increase further the EoL-RR. On the other hand, EoL-RR calculation by Material by up to ~65% (given the same yield from naphtha to monomers in the Economics (2022) and Agora Industry (2022) (i.e., 15% EoL-RR) steam crackers). consider the net recycled plastic production (6.7 Mt, after extrusion By examining circularity indicators per sector, it can be observed and losses from recycling) as the numerator and reported plastic waste that CR implementation contributes to reach recycling targets. In the generated plus the ‘missing plastic’ as the denominator (i.e., estimated packaging sector, the recycling targets stated by PPWD (i.e., 55% by to be 45 Mt). In this study the EoL-RR is calculated based on the share of 2030, European Commission, 2018) cannot be achieved only by total recycled plastic production (plus base chemicals when CR is improving the current waste management treatments (i.e., collection, implemented) over the total plastic waste generation (incl. the ‘missing sorting, and MR) as the estimated EoL-RR in S1 is 49% ± 3%. The CR plastic’ in S5) (see Table 2). and SBR options will contribute to reach the recycling targets set by PPWD, as the EoL-RR is expected to increase to 73% ± 4%, 80% ± 3%, 81% ± 3%, and 81% ± 3% in S2, S3, S4, S5, respectively. The P2P and 4.2. Potential contribution of chemical recycling to plastic recycling rates P2C from CR and SBR is estimated to add 15–38% ± 2% and 20–35% ± 2% to the EoL-RR in packaging sector (i.e., 73–81% ± 3%) in S2–S5, Mass balance approach, as shown in this study, has been proposed to measure the contribution of CR and SBR (Broeren et al., 2022). For CR respectively. The contribution of CR and SBR options to increase the EoL-RR can also be noticed in the other sectors, e.g., significant im- technologies, for example pyrolysis, the mass balance approach means accounting for the full process from breaking down the polymer chains provements in the EoL-RR in the automotive sector are expected (from 38% ± 3% in S1 to 72% ± 4% in S4 and S5, Table SI16). Furthermore, into its basic building blocks (e.g., pyrolysis oil), purification steps (e.g., distillation and hydrotreatment), feeding into cracking process (e.g., the findings from this study (in Table S16) can also be used as the basis to formulate recycling targets for plastic waste in the sector with no steam crackers) to produce base chemicals (incl. olefins), and (re)poly- targets yet (e.g., in agriculture or construction sector). merization (Tabrizi et al., 2021). Moreover, the mass balance approach In a similar way, the results can be used to perform plausibility- can also be used as a tool by policy makers to monitor the yield of CR and checks on stakeholders’ pledges. For example, it can be observed that SBR technologies and to formulate ambitious but realistic recycling targets (e.g., EoL-RR targets for plastic). the recycled plastic produced from only CR and SBR of plastic (S2; 7903 ± 6% kt) is not enough to meet the pledges made by CPA to reach 10,000 As CR options yield multiple products (i.e., monomers, chemicals, and hydrocarbon), it is important to clearly identify the potential kt in 2030 (European Commission, 2022a). It is evident that such goal can only be achieved with an important contribution by MR, CR and SBR quantities of each output to further distinguish recycled plastic pro- duction (i.e., plastic-to-plastic recycling) from the other outputs (e.g., (as in scenario S3, S4, and S5) plastic-to-fuel). This is also relevant to appropriately report the plastic recycling rate in Europe to monitoring the attainment of recycling 15 I.S. Lase et al. Resources, Conservation & Recycling 192 (2023) 106916 4.3. Plausibility-checks on achievable recycled content targets more robust investigation should be carried out by taking into consid- eration not only the waste streams’ characteristics but also the quality of Mass balance approach has been proposed to monitor and determine the secondary products to better understand their potential market ap- recycled content of a product (Broeren et al., 2022; Tabrizi et al., 2021). plications. Evaluation of quality includes legal aspects to use recycled For consumers, the mass balance approach means that brands and plastics in certain application (e.g., as food contact material), technical product manufacturers should ensure full transparency of the claimed characteristics of recycled plastic to meet market specification (e.g., recycled content (e.g., share of recycled plastic) of the total weight of a processability of recycled plastics), and consider potential market up- product. Policy makers can use mass balance approach can be used to take (i.e., to avoid market saturation that will reduce the uptake of measure recycled content targets via, for example, transparent moni- recycled plastic) (Huysveld et al., 2022; Tonini et al., 2022). A study toring and certification systems (Tabrizi et al., 2021). Moreover, the from De Tandt et al. (2021) illustrates the importance to consider leg- presented MFA model (using mass balance principles) can support pol- islative requirements for the use of mechanical recycled plastic espe- icy makers to formulate ambitious but realistic recycled content targets cially as food contact material. Studies from Demets et al. (2020) also (for plastic-based items) by taking into account the quantities of recy- show the complexity in defining quality of recycling that, to some cled plastic produced annually. This MFA model can also be used to extent, determines the uptake of recycled plastic produced. identify the bottlenecks towards meeting the targets. Moreover, it is difficult to predict the market uptake of recycled Looking at the RC availability per sector, it can be observed that a plastic in the future as well as to realize RC targets. Nonetheless, the significant amount of recycled plastic (i.e., 3670–7141 kt) might be used finding from this study can be used as basis to formulate realistically in the ‘others’ sector (i.e., household goods, textile, etc.) as open-loop achievable targets or pledges regarding RC in new products in the near recycling in 2030. In other words, if the current market uptake as of future, specifically by considering the current and potential future flows 2018 is maintained in 2030, the pledges or targets on RC in some sectors of recycled plastic. Lastly, the quantification of recycled content avail- such as automotive and electronic will not be achieved. For example, ability only shows the potential at sector level. However, some pledges 25–30% RC target in electronic sector (Sandoval, 2018; Lase et al., are very specific to application or product level such as recycled content 2021) will not be met as only 11% of RC would be available at the most in electronic products (e.g., RC in coffee machines or vacuum cleaners). positive scenario (i.e., CR is implemented and ‘missing plastic’ is In this case, the findings can be perceived as indications or proxy to- accounted for, S5 in Fig. 4D). Similarly, the RC targets in automotive wards the average recycled content availability in the respective sector sector (i.e., 20–25% in new passenger cars; Maury et al., 2022, Volvo, and a more detailed research should be carried out to assess the feasi- 2018) is not achieved as only 15% RC will be available in the most bility of recycled content targets at application or product level. Ulti- positive scenario (S5 in Fig. 4C). For electronic and automotive sectors, mately, this study is limited to the selected ten polymers and six the RC targets can only be achieved by the inclusion of CR options, scenarios, which can be further extended in the future (based on new processing the ‘missing plastic’, and closed-loop recycling (S5 in Fig. 5C technological development and insights) alongside the quantification of and 5D). the environmental and economic impact of the future plastic recycling The findings on RC availability can be used to formulate targets for scenario. The MFA model can be used as basis for analysis of the sus- the each sector, e.g., packaging. It can be observed that around 35–52% tainability performance of different alternative scenarios towards of RC will be available for packaging sector in 2030, assuming closed- meeting the circular economy targets (i.e., by coupling MFA with social- loop recycling (i.e., S1–S5 in Fig. 3A). This finding aligns with 30% economic-environment impact assessment). More importantly, future RC targets for PET beverage bottles stated by the Single Use Plastic research should aims to provide information on the sustainability as- Directive (European Commission, 2019) as well as study from Bashir- pects (e.g., social, economic, and environmental impacts) concerning gonbadi et al. (2022) that shows PP films can be made of 32 wt% CR. To date, several studies have indicated that the environmental recycled PP. Therefore, the findings of this research can also be used as performance of CR is better than landfill and incineration (Vollmer et al., basis to set RC targets for broader plastic packaging types such as flex - 2020; Schwarz et al., 2021), but not outcompeting mechanical recycling. ible packaging, HDPE bottles, etc. Yet, depending on the substitution rate of virgin plastic (i.e., the quality aspects), CR can perform better than mechanical recycling (i.e., 1:1 substitution rate of virgin plastic) (Huysveld et al., 2022). Thus, there is 4.4. Limitations of the study and future perspectives a need to further deal with quality aspects in such sustainability studies, for example also to take into account the other products from CR such as This study focuses on the projected plastic flows and treatments in waxes or aromatics. 2030 compared to the status quo in 2018. The projected plastic flows assumes that waste quantities will increase in 2030 based on a historical regression (more in the SI–Section 8). Using this approach, the impli- 5. Conclusion cations of production and use-oriented solutions such as waste reduc- tion, re-use or refill strategies (e.g., as stated in the proposal of Current end-of-life recycling rate from 2018 data in Europe, based on Packaging and Packaging Waste Regulations; European Commission, mechanical recycling, is about 18% calculated from the amount of 2022b) are yet to be evaluated in further research. Moreover, to achieve recycled plastic production over the reported plastic waste generation. highest RC availability, one should take into account not only the mass The growth of plastic waste generation until 2030 is projected using flows (as shown in this study) but also the recycled plastic’s qualities historical data, while widespread implementation of production and suitable for certain applications. Addressing the quality of recycled use-oriented solutions such as waste reduction, re-use, re-fill, etc. are not plastic would improve the potential market applications recycled plas- yet considered in this study. In future, several scenarios can be deployed tic. For example, there is a possibility that a considerable amount of to improve the recycling rate. In first instance, stretching the possibil- mechanically-recycled plastic have to be exported outside EU 27+3 ities of current commercially used mechanical recycling technologies because the market that can deal with certain mechanical recycling can lead to an overall end-of-life recycling rate up to 49% in 2030. Re- qualities gets saturated (Grant et al., 2020), which would mean that sults of this study show that the implementation of chemical and certain quantities of recycled plastic produced in S1, S3, S4, and S5 solvent-based recycling technologies bring positive impacts towards the (Figs. 3, 4, and 5) might not be used in the EU 27+3. According to the end-of-life-recycling rate as plastic-to-plastic and plastic-to-chemicals current perception, potential market applications that can use recycled recycling (from chemical recycling) will increase the rate up to 80%. plastic might be less of a concern for chemically-recycled plastic because In this most positive scenario (and potentially the most realistic one), of a higher quality (Manzuch et al., 2021; Huysveld et al., 2022). chemical recycling becomes complementary (and not competitive) to To further improve the capabilities of the developed MFA model, a improved mechanical recycling. In this scenario, plastic-to-plastic rate 16 I.S. 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