Probabilistic Material Flow Analysis Research Articles

Probabilistic material flow analysis of released nano titanium dioxide in Mexico

Engineered Nanomaterials (ENMs) or products containing ENMs, known as nano-enabled products are commercialized globally by a large number of companies. Concern about the potential risks and negative impacts of releasing ENMs into the environment is under investigation. For this reason, methodologies to estimate the probable mass concentrations of ENMs released in different regions of the world have been developed. As a first attempt to estimate the probable mass flows of nanosized titanium dioxide (nano-TiO2) released in Mexico, we developed a Probabilistic Material Flow Analysis (PMFA) for 2015.The model describes probabilistic mass flows of released nano-TiO2 during the life cycle of sunscreens, coatings, ceramic, and other nano-enabled products, including the flows through the solid waste and wastewater management systems, as well as the transfer of nano-TiO2 to three environmental compartments (atmosphere, topsoil, and surface water). The PMFA incorporates the uncertainty related to the input data. We observed that the most significant nano-TiO2 flows occur to the surface water, landfill, and soil compartments, targeted as the main “hot-spots”, where living organisms could be more exposed to this material. Further improvements in the model are needed due to some data gaps at some life cycle stages, for instance, solid waste management and reused wastewater manipulation for irrigation purposes. Finally, the model developed in this study can be adjusted to assess other ENM releases and can be beneficial for further investigation in fate modeling and environmental risk assessment.

Accounting for product recovery potential in building life cycle assessments: a disassembly network-based approach

PurposeExisting life cycle assessment (LCA) methods for buildings often overlook the benefits of product recovery potential, whether for future reuse or repurposing. This oversight arises from the limited scope of such methods, which often ignore the complex interdependencies between building products. The present paper, backed by its supplementary Python library, introduces a method that addresses this gap, emphasizing the influence of product interdependencies and future recovery potential on environmental impact.MethodsImplementing the proposed method requires adding a phase, the recovery potential assessment, to the four phases that constitute an LCA according to the ISO 14040/14044 guidelines. Given the disassembly sequence for each product, in the first step of the recovery potential assessment, a disassembly network (DN) is created that displays structural and accessibility dependencies. By calculating the average of the disassembly potential (DP) of each structural dependency (second step) associated with that product, we obtain the DP (0.1–1) at the product level in a third step. Because there is no empirical data available to support a specific relationship between product disassembly potential and recovery potential (RP) (0–1), we employ, in a fourth step, a flexible model specification to represent scenarios of how this relationship may look like. Ultimately, for each scenario, the resulting RP is used to enable a probabilistic material flow analysis with a binary outcome, whether to be recovered or not. The resulting product-level median material flows are then used to quantify the building’s environmental impact for a given impact category in the life cycle impact assessment (LCIA). The results are interpreted through an uncertainty, hotspot, and sensitivity analysis.Results and discussionOur results show that not considering the interdependencies between building products in building LCAs results in underestimating the embodied greenhouse gas (GHG) emissions by up to 28.29%. This discrepancy is primarily attributed to a failure to account for additional material flows stemming from secondary replacements owing to the interdependencies during the life cycle. When accounting for end-of-life recovery benefits, a zero-energy building (ZEB) design incorporating some DfD principles demonstrated up to 45.94% lower embodied GHG emissions than the ZEB design with low disassembly potential when assuming that recovered products will be reused.ConclusionsOur approach provides first-of-a-kind evidence that not accounting for recovery potential may significantly distort the results of an LCA for buildings. The method and its supporting code support the semi-automated calculation of the otherwise neglected potential environmental impact, thus helping to drive the transition towards a more sustainable built environment. The supporting code allows researchers to build on the proposed framework if more data on the relationship between DP and RP become available in the future. Finally, while applied to buildings in this paper, the proposed framework is adaptable to any complex product with limited modifications in the supporting code.

Mapping Plastic and Plastic Additive Cycles in Coastal Countries: A Norwegian Case Study.

The growing environmental consequences caused by plastic pollution highlight the need for a better understanding of plastic polymer cycles and their associated additives. We present a novel, comprehensive top-down method using inflow-driven dynamic probabilistic material flow analysis (DPMFA) to map the plastic cycle in coastal countries. For the first time, we covered the progressive leaching of microplastics to the environment during the use phase of products and modeled the presence of 232 plastic additives. We applied this methodology to Norway and proposed initial release pathways to different environmental compartments. 758 kt of plastics distributed among 13 different polymers was introduced to the Norwegian economy in 2020, 4.4 Mt was present in in-use stocks, and 632 kt was wasted, of which 15.2 kt (2.4%) was released to the environment with a similar share of macro- and microplastics and 4.8 kt ended up in the ocean. Our study shows tire wear rubber as a highly pollutive microplastic source, while most macroplastics originated from consumer packaging with LDPE, PP, and PET as dominant polymers. Additionally, 75 kt of plastic additives was potentially released to the environment alongside these polymers. We emphasize that upstream measures, such as consumption reduction and changes in product design, would result in the most positive impact for limiting plastic pollution.

Mapping Chinese plastic flows from 2001 to 2040 based on dynamic probabilistic material flow analysis and scenario projection

Plastic waste management, deeply intertwined with our economy, presents a global challenge. Plastic pollution pervades both aquatic and terrestrial ecosystems worldwide. In a vast country like China, establishing a comprehensive plastic flow regime that accounts for socioeconomic disparities between urban and rural areas is essential for effectively reducing s plastic waste. This study aims to map the life-cycle of China's plastic flows from 2001 to 2040, distinguishing between urban and rural sources, through integrating dynamic probabilistic material flow analysis with scenario analysis. The results indicate that from 2001 to 2020, cumulative plastic waste generation was 1001 ± 14.6 million tonnes (Mt), with a higher proportion originating from urban areas (706 ± 10.3 Mt) compared to rural areas (218 ± 3.2 Mt). The rate of increase in mismanaged plastic wastes (MPWs) in rural areas outpaced that in urban areas, peaking in 2016, five years after the peak in urban areas. Consequently, the cumulative total of rural MPWs, including littering (103.5 ± 2.0 Mt) and open dumping (74.8 ± 1.5 Mt), was higher than that in urban areas (littering: 83.0 ± 4.0 Mt; open dumping: 70.3 ± 1.4 Mt). The scenario analysis forecasts a reduction of 96.5 ± 0.4 % and an 83.0 ± 2.1 % in MPW generations in urban and rural areas by 2040, respectively, if all interventions are implemented. However, strategies like reuse&recycling and reduce&substitute are less effective in rural areas compared to urban areas. Therefore, we recommend establishing a collection system with both penalties and incentives to reduce rural MPWs.

The limitations of end-of-life copper recycling and its implications for the circular economy of metals

Increasing the recycling of metals reaching their end-of-life (EoL) is a vital circular economy approach to meet the growing demand for metals and reduce reliance on mining. To assess the potential of recycling strategies in fulfilling future metal demand and replacing primary production, we develop a novel dynamic probabilistic material flow analysis (MFA) model. Unlike previous MFA studies, our model explicitly explores the potential of recycling to reduce metal mining activities while considering uncertainties in future EoL collection and recycling rates. Focusing on copper, a critical mineral for low-carbon technologies, the model dynamically estimates the future copper stocks and flows under three different demand scenarios and probabilistic EoL collection and recycling assumptions. Our analysis reveals that the share of EoL secondary supply of overall copper demand, which currently stands at 23 %, will even under the scenario with the lowest future copper demand only be averaging 33.4 % over the next three decades. In addition, even under the most optimistic circumstances with lower than expected copper demand and very high collection and recycling rate growth, the annual share of EoL secondary supply of overall copper demand would only reach 49.6 % in 2050. Thus, primary copper extraction is expected to rise significantly until at least 2040 and under 87 % of all 30,000 modelled outcomes, primary production of copper in 2050 will still be above 2020 production levels. Consequently, we emphasise the need for alternative circular economy strategies beyond recycling, such as demand reduction and mitigating the harmful impacts of primary metal production.

Probabilistic material flow analysis of eight commodity plastics in China: Comparison between 2017 and 2020

As the largest manufacturing economy, China's strong trade connections to the rest of the world make it a major actor in global plastic flows. Knowledge regarding flows within, into, and out of China is therefore essential, particularly the effects of China's 2017 ban on imported plastic waste. We used probabilistic material flow analysis to model the life-cycles of 8 commodity polymers in China in 2017 and 2020. We considered 9 product sectors, 33 product categories, and 6 disposal options. China produced and imported a large amount of primary plastics while exporting numerous semi-finished and finished plastic products. The largest application of plastics is packaging, followed by textiles, with PP and PET having the largest consumption. Waste plastics were mainly incinerated and landfilled, and their recycling rates were high. This study provides separate analyses for each polymer, makes comparisons with Europe, and lays the foundation for plastic management in China.

A high-resolution dynamic probabilistic material flow analysis of seven plastic polymers; A case study of Norway

Plastic pollution has long been identified as one of the biggest challenges of the 21st century. To tackle this problem, governments are setting stringent recycling targets to keep plastics in a closed loop. Yet, knowledge of the stocks and flows of plastic has not been well integrated into policies. This study presents a dynamic probabilistic economy-wide material flow analysis (MFA) of seven plastic polymers (HDPE, LDPE, PP, PS, PVC, EPS, and PET) in Norway from 2000 to 2050. A total of 40 individual product categories aggregated into nine industrial sectors were examined. An estimated 620 ± 23 kt or 114 kg/capita of these seven plastic polymers was put on the Norwegian market in 2020. Packaging products contributed to the largest share of plastic put on the market (∼40%). The accumulated in-use stock in 2020 was about 3400 ± 56 kt with ∼60% remaining in buildings and construction sector. In 2020, about 460 ± 22 kt of plastic waste was generated in Norway, with half originating from packaging. Although ∼50% of all plastic waste is collected separately from the waste stream, only around 25% is sorted for recycling. Overall, ∼50% of plastic waste is incinerated, ∼15% exported, and ∼10% landfilled. Under a business-as-usual scenario, the plastic put on the market, in-use stock, and waste generation will increase by 65%, 140%, and 90%, respectively by 2050. The outcomes of this work can be used as a guideline for other countries to establish the stocks and flows of plastic polymers from various industrial sectors which is needed for the implementation of necessary regulatory actions and circular strategies. The systematic classification of products suitable for recycling or be made of recyclate will facilitate the safe and sustainable recycling of plastic waste into new products, cap production, lower consumption, and prevent waste generation.

Prospective Dynamic and Probabilistic Material Flow Analysis of Graphene-Based Materials in Europe from 2004 to 2030.

As industrial demand for graphene-based materials (GBMs) grows, more attention falls on potential environmental risks. The present article describes a first assessment of the environmental releases of GBMs using dynamic probabilistic material flow analysis. The model considered all current or expected uses of GBMs from 2004 to 2030, during which time there have already been significant changes in how the graphene mass produced is distributed to different product categories. Although the volume of GBM production is expected to grow exponentially in the coming years, outflow from the consumption of products containing GBMs shows only a slightly positive trend due to their long lifetimes and the large in-use stock of some applications (e.g., GBM composites used in wind turbine blades). From consumption and end-of-life phase GBM mass flows in 2030, estimates suggest that more than 50% will be incinerated and oxidized in waste plants, 16% will be landfilled, 12% will be exported out of Europe, and 1.4% of the annual production will flow to the environment. Predicted release concentrations for 2030 are 1.4 ng/L in surface water and 20 μg/kg in sludge-treated soil. This study’s results could be used for prospective environmental risk assessments and as input for environmental fate models.

Applying probabilistic material flow analysis for quality control and management of waste recycling in steelmaking

In modern steelmaking, multiple processes comprise a continuous manufacturing system, but not all phosphorus content data are connected or integrated into a holistic and systematic database. Disconnected data hinder the improvement of material management and resource efficiency in the industry. The objective of this study was to establish a method to evaluate material flows, reduce uncertainty, and perform quality control for waste recycling in the steelmaking industry. The results indicate that 10% of the phosphorus input is present in the final products, 30% accumulates in the slags, and more than 60% of the total mass remains in the processes. Comparing the material flow analysis results obtained using static and probabilistic approaches, the partition ratio of the phosphorus content in slags changes from 24.07% to 40.78%, but that in processes changes from 49.10% to 68.05%. This indicates that the variations in phosphorus content in slags and processes might affect the effectiveness of slag recycling and might increase the resource consumption required to maintain the quality of final products. The probability of forming substandard products in the baseline scenario is 0.43. Adopting a 50% removal rate, the probabilities of forming substandard products are reduced to 0.36 (waste removal scenario), 0.38 (slag reduction scenario), and 0.31 (raw material treatment scenario). The performance of raw material treatment and waste removal is more efficient for quality control. The method used in this study can be applied to evaluate the possible outcomes of waste recycling and reduce the probability of forming substandard products.

Predicting the global environmental distribution of plastic polymers

This study represents the first quantitative global prediction of the mass distribution of six widespread polymers, plus plastic fibers and rubber across four environmental compartments and 11 sub-compartments. The approach used probabilistic material flow analysis for 2015, with model input values and transfer coefficients between compartments taken from literature. We estimated that 3.2 ± 1.8 Mt/year of polyethylene, 1.3 ± 0.8 Mt/year of polypropylene, 0.5 ± 0.3 Mt/year of polystyrene, 0.3 ± 0.15 Mt/year of polyvinyl chloride, 1.6 ± 0.9 Mt/year of polyethylene terephthalate and 2.4 ± 1.2 Mt/year of plastic fibers enter the environment. Combining all plastic, including rubber, 4.9 ± 1.3, 4.8 ± 1.9 and 1.8 ± 1.2 Mt/year accumulated in the soil, ocean, and freshwater, respectively. Urban soils and ocean shorelines were predicted as hotspots for plastic accumulation, accounting for 33% and 25% of total plastic, respectively. The floor of freshwater systems and the ocean were predicted as hotspots for high density plastic such as polyethylene terephthalate, polyvinyl chloride and plastic fibers. Furthermore, 59% of environmental rubber was predicted to accumulate in soil. The findings of this study provide baseline data for quantifying plastic transport and accumulation, which can inform future ecotoxicity studies and risk assessments, as well as targeting efforts to mitigate plastic pollution.

A High-Resolution Dynamic Probabilistic Material Flow Analysis of Plastics; a Case Study of Norway

A High-Resolution Dynamic Probabilistic Material Flow Analysis of Plastics; a Case Study of Norway

Probabilistic material flow analysis and emissions modeling for five commodity plastics (PUR, ABS, PA, PC, and PMMA) as macroplastics and microplastics✰

Detailed knowledge about polymer flows through the anthroposphere and into the environment is information essential to the better management of plastics. Currently, only limited knowledge about specific polymer flows is available. This work aimed to model those flows for five polymers: polyurethane (PUR), acrylonitrile butadiene styrene (ABS), polyamide (PA), polycarbonate (PC) and polymethyl methacrylate (PMMA). Probabilistic material flow analysis (PMFA) was used to quantify flows from production in 45 product categories to their end-of-life in Europe and Switzerland. We then considered 40 release pathways for macro- and microplastic flows to assess polymer release into Switzerland's environment. PMFA results showed considerable variations between the polymers considered because their flows through the anthroposphere are determined by their different uses. Total macro- and microplastic emissions into Switzerland's environment in 2018 were estimated at masses of 208±76 t for PA, 179±98 t for PUR, 79±26 t for PC, 36±23 t for PMMA and 25±6 t for ABS. Relative to Switzerland's total production and imports, this amounted to total releases of 0.23% of PA, 0.07% of PUR, 0.16% of PC, 0.32% of PMMA and 0.14% of ABS. Contributions as released microplastics ranged from 18% of PMMA to 75% of ABS. These results showed that the amounts of the polymers considered released into the environment were much smaller than previously assumed in simpler release estimates, and they may be more realistic for countries with well-functioning waste treatment systems.

Country-Specific Environmental Risks of Fragrance Encapsulates Used in Laundry Care Products.

Fragrance encapsulates (FEs) are designed to deliver fragrance components, notably in laundry care products. They are made of thermoset polymeric shells surrounding the fragrance content. These materials enter the environment mainly during laundry washing, but little is known about their distribution in and impact on the environment. The aim of the present study was to estimate the environmental concentrations of FE shells in freshwater, sediment, and soil compartments for 34 selected countries and to compare them with ecotoxicological effects. Probabilistic material flow analysis was used to estimate worst‐case predicted environmental concentrations (PECs). The lowest freshwater PEC was predicted for Finland (0.00011 µg/L) and the highest for Belgium (0.13 µg/L). Accumulation of FE shells between 2010 and 2019 was considered for sediments and sludge‐treated soils. The PECs in sediments ranged from 3.0 µg/kg (Finland) to 3400 µg/kg (Belgium). For sludge‐treated soil, the concentration was estimated to be between 0 (Malta and Switzerland) and 3600 µg/kg (Vietnam). Ecotoxicological tests showed no effects for FE shells at any tested concentration (up to 2700 µg/L freshwater, 5400 µg/kg sediment, and 9100 µg/kg soil), thus not allowing derivation of a predicted‐no‐effect concentration (PNEC). Therefore, to characterize the environmental risks, the PEC values were compared with highest‐observed‐no‐effect concentrations (HONECs) derived from ecotoxicological tests. The PEC/HONEC ratios were 9.3 × 10–6, 0.13, and 0.04 for surface waters, sediments, and sludge‐treated soils, respectively, which are much below 1, suggesting no environmental risk. Because the PEC values constitute an upper boundary (no fate considered) and the HONEC values represent a lower boundary (actual PNEC values based on NOECs will be higher), the current risk estimation can be considered a precautionary worst‐case assessment. Environ Toxicol Chem 2022;41:905–916. © 2021 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Polymer-specific dynamic probabilistic material flow analysis of seven polymers in Europe from 1950 to 2016

Information on the flows of specific polymers through the anthroposphere forms the basis of any assessment of the environmental implications of plastic. This work presents a dynamic probabilistic material flow analysis of seven commodity thermoplastics: low-density polyethylene (LDPE), high-density polyethylene (HDPE), polypropylene (PP), polystyrene (PS), expanded polystyrene (EPS), polyvinylchloride (PVC), and polyethylene terephthalate (PET). The analysis examines nine product sectors and 35 product categories, including textiles, across Europe from 1950 to 2016. Total consumption of these seven polymers was 90.0 ± 4.8 kg/cap in 2016. The in-use stock that year was 47 kg/cap for LDPE, 81 kg/cap for HDPE, 81 kg/cap for PP, 21 kg/cap for PS, 56 kg/cap for EPS, 163 kg/cap for PVC, and 16 kg/cap for PET. For EPS and PVC, the fraction contained in the in-use stock is 51% and 39% of the total production. Landfill is the major compartment where LDPE, HDPE, PP, PS, and PET end up (48%–60%). Elimination—incineration and destruction in waste incineration plants—occurs for 15%–19% of LDPE, HDPE, PP, PS, and PET, and 10% of EPS and PVC. Current European recycling rates vary from 11% for PS to 33% for PET. The precise separation of different polymers into very detailed product categories will allow the formulation of future scenarios about interventions to improve the circularity of specific polymers and provide the basis to assess the polymer-specific releases to the environment.

Representation, Propagation, and Interpretation of Uncertain Knowledge in Dynamic Probabilistic Material Flow Models

The determination of the environmental concentration of a pollutant is a crucial step in the risk assessment of anthropogenic substances. Dynamic probabilistic material flow analysis (DPMFA) is a method to predict flows of substances to the environment that can be converted into environmental concentrations. In cases where direct quantitative measurements of concentrations are impossible, environmental stocks are predicted by reproducing the flow processes creating these stocks in a mathematical model. Incomplete parameter knowledge is represented in the form of stochastic distributions and propagated through the model using Monte Carlo simulation. This work discusses suitable means for the model design and the representation of system knowledge from several information sources of varying credibility as model parameter distributions, further evaluation of the simulation outcomes using sensitivity analyses, and the impacts of parameter uncertainty on the total uncertainty of the simulation output. Based on a model developed in a case study of carbon nanotubes in Switzerland, the modeling process, the representation and interpretation of the simulation results are described and approaches to sensitivity and uncertainty analyses are demonstrated. Finally, the overall approach is summarized and provided in the form of a set of modelling and evaluation rules for DPMFA studies.

Integrated dynamic probabilistic material flow analysis of engineered materials in all European countries

Uncertainties remain regarding the potential environmental risks of engineered nanomaterials, reflecting missing information on both the exposure and the hazard sides. Probabilistic material flow analysis (PMFA) is a useful exposure assessment tool that maps the flows of a substance through its lifecycle towards the environment, taking into account the uncertainties associated with the input data. In the last years, several refinements have been made to the original PMFA method, increasing its complexity with respect to systems dynamics, fate during recycling and reprocessing and forms of release. In this work, an integrated dynamic probabilistic material flow analysis (IDPMFA) was developed that combines all separate advancements of the method in one overarching software code. The new method was used to assess the forms in which nano-Ag, nano-TiO2 and nano-ZnO are released into air, soils and surface water. Each European country (EU28, Norway and Switzerland) was studied from the year 2000 to the year 2020. The present model includes new assessments of the forms in which nano-ZnO is released into the environment and of the flows out of reprocessing (last step of recycling) of nano-Ag, nano-TiO2 and nano-ZnO towards both technical and environmental compartments. The forms of ZnO released to different compartments vary greatly with different proportions between pristine, dissolved, matrix-embedded and transformed forms. The same applies for the forms of the other ENMs released after reprocessing, where different processes result in very different distributions between the various forms. The country-specific assessment showed that it is mainly the different solid waste treatment schemes that influence the distribution to final environmental sinks. Overall, the results of IDPMFA show the great importance of considering the full life cycle of nanoproducts including the different stages of recycling, the differences between countries, and the forms of the released materials. The results from the integrated model will provide useful input information for environmental fate models and for environmental risk assessments.

Size-Specific, Dynamic, Probabilistic Material Flow Analysis of Titanium Dioxide Releases into the Environment.

Most of the existing exposure models for engineered nanomaterials (ENMs) do not consider particle size, crystalline forms, and coating materials that all may influence the material's fate, transport, and toxicity. Our work aimed to incorporate particle size distributions into a material flow analysis (MFA) to develop a size-specific, dynamic, probabilistic MFA model (ss-DPMFA). Using titanium dioxide (TiO2) as a first case study, we aimed to determine the contribution of conventional TiO2 pigments to the total amount of nanoscale TiO2 released into the environment. Besides providing information on mass flows, the new model used particle size distributions and crystalline forms to describe the stocks and flows of TiO2. The most striking modeling result to emerge was that before TiO2 ENMs came onto the market as such in 2000, 22,400 tons of nanosized (<100 nm) TiO2 particles had already been released into the environment, originating from conventional TiO2 pigments. Even in 2016, 50% of the nanosized TiO2 particles released into wastewater came from the nanosized fraction of TiO2 particles in pigments. Quantitative data on the particle size distribution of TiO2 particles released into the environment can be used as input for environmental fate models. Our new ss-DPMFA model's additional insights about crystalline forms and coatings could pave the way for advanced size- and form-specific hazard and risk assessments for other nanomaterials in ecological systems.

Dynamic probabilistic material flow analysis of engineered nanomaterials in European waste treatment systems

Knowledge on the material flows of engineered nanomaterials (ENMs) is crucial for assessing their environmental risks. Waste management processes constitute important parts of material flow analyses as they affect large fractions of the ENMs. Accordingly, their detailed representation could substantially improve the models. Our goal was to consider the temporal variations of wastewater and solid waste management in the dynamic probabilistic material flow analysis of carbon nanotubes (CNTs), nano-Ag, -TiO2 and -ZnO in Europe from 2000 to 2020. New input parameters included wastewater and solid waste management rates for each year. The uncertainties associated with these data were assessed based on the type of consulted source, the geographical representativeness and temporal concordance. Results show modal values of 10–27% of ENMs going from sorting to reprocessing. Large shares of environmental releases of nano-Ag and nano-ZnO end in surface water (4.9 t and 1700 t respectively in 2020), while sludge-treated soil as environmental compartment is receiving most of nano-TiO2 (22,000 t in 2020) and CNTs (8.8 t in 2020). Discharges from wastewater management to the subsurface soil make this compartment the largest environmental sink of nano-Ag and nano-ZnO (30 t and 3860 t accumulated in 2020, respectively). Landfills represent significant stocks of ENMs, with 105 t, 2077 t, 69,000 t and 1042 t of nano-Ag, nano-ZnO, nano-TiO2 and CNTs. This model includes detailed descriptions of waste management and sources of ENMs released at the European scale. However, a better understanding of the behaviour, i.e. fate and potential transformations of ENMs in reprocessing systems, is needed to complete the full assessment.

Dynamic probabilistic material flow analysis of rubber release from tires into the environment

The presence of microplastics in the environment is currently receiving a lot of attention. Rubber particles from tire wear have been estimated in several mass emission inventories to be a major contributor to the total microplastic release. This work used dynamic probabilistic material flow analysis to quantify the flows of rubber particles from tires to roads and further onto soils and surface waters of Switzerland. The model considered the whole life-cycle of tires from import over the use phase to the end-of-life and the re-use of scrap tires. Uncertainties of model parameters and data variability were considered by using a probabilistic approach. Mass flows onto soils and through road drainage by both uncontrolled dispersal and engineered systems are considered. In addition, the release of rubber from artificial turfs was included. The accumulation of rubber particles in the environment was quantified over the time frame from 1988 to 2018. The results show that in 2018, 1.29 ± 0.45 kg/capita of rubber was emitted from tire wear (97%) and rubber granules (3%). Street cleaning and waste water treatment removed around 26% of this rubber mass before finally reaching the receiving environmental compartment, resulting in an effective input of 0.96 ± 0.35 kg/capita of rubber in 2018 into the natural environment. Most of this mass (74%) was deposited on roadside soils (up to 5 m distance from road), 22% flowed into surface waters and the remaining part (4%) was emitted to soils. The dynamic modeling showed an increase of the input into the environment by about 10% from 1990 to 2018. The ban of sewage sludge application on soils resulted in a marked decrease in the amount transferred to soils after the year 2000. In total, 219 ± 22 ktonnes of rubber particles have accumulated in the environment since 1988 in Switzerland.

Polymer-Specific Modeling of the Environmental Emissions of Seven Commodity Plastics As Macro- and Microplastics.

Plastic has been identified as an emerging contaminant in aquatic and terrestrial ecosystems. Uncertainties remain concerning the amounts present in the environment and the main responsible sources. In this study, the emissions of macro- and microplastics have been mapped for seven polymers in Switzerland. The modeling is based on a complete analysis of the flows from production and use to end-of-life using probabilistic material flow analysis. We estimate that 94 ± 34 g/capita/year of low-density polyethylene, 98 ± 50 g/cap/a of high-density polyethylene, 126 ± 43 g/cap/a of polypropylene, 24 ± 13 g/cap/a of polystyrene, 16 ± 12 g/cap/a of expanded polystyrene, 65 ± 36 g/cap/a of polyvinyl chloride, and 200 ± 120 g/cap/a of polyethylene terephthalate enter the Swiss environment. All polymers combined, 540 ± 140 and 73 ± 14 g/cap/a are emitted into soil as macroplastics and microplastics, respectively, and 13.3 ± 4.9 and 1.8 ± 1.1 g/cap/a are emitted into freshwater as macroplastics and microplastics, respectively. The leading emission pathway is littering for both terrestrial and aquatic environments. Construction, agriculture, and pre- and postconsumer processes cause important emissions of microplastics into soils, and postconsumer processes, textiles, and personal care products release most of the microplastics into waters. Because mass flows into soils are predicted to be 40 times larger than those into waters, more attention should be placed on this compartment. Our work also highlights the importance of referring to specific polymers instead of just "plastics".