Dynamic Material Flow Model Research Articles

Evaluating the Use of Global Sensitivity Analysis in Dynamic MFA

SummaryDynamic material flow analysis (MFA) provides information about material usage over time and consequent changes in material stocks and flows. In order to understand the effect of limited data quality and model assumptions on MFA results, the use of sensitivity analysis methods in dynamic MFA studies has been on the increase. So far, sensitivity analysis in dynamic MFA has been conducted by means of a one‐at‐a‐time method, which tests parameter perturbations individually and observes the outcomes on output. In contrast to that, variance‐based global sensitivity analysis decomposes the variance of the model output into fractions caused by the uncertainty or variability of input parameters. The present study investigates interaction and time‐delay effects of uncertain parameters on the output of an archetypal input‐driven dynamic material flow model using variance‐based global sensitivity analysis. The results show that determining the main (first‐order) effects of parameter variations is often sufficient in dynamic MFA because substantial effects attributed to the simultaneous variation of several parameters (higher‐order effects) do not appear for classical setups of dynamic material flow models. For models with time‐varying parameters, time‐delay effects of parameter variation on model outputs need to be considered, potentially boosting the computational cost of global sensitivity analysis. Finally, the implications of exploring the sensitivities of model outputs with respect to parameter variations in the archetypical model are used to derive model‐ and goal‐specific recommendations on choosing appropriate sensitivity analysis methods in dynamic MFA.

Time-varying losses in material flows of steel using dynamic material flow models

A method for annual evaluation of recycling rates in material flows was established to enable a consistent analysis of resource utilizations. The algorithm to calculate the time-varying losses was derived based on a sound statistical approach that would be viable for both historical data and future predictions. This method eliminates the need for adjustable parameters and is solely based on input data of the material consumption and scrap collection. This article describes the model methodology and the calculation procedures to classify the societal scrap reserve from the amounts of losses, based on statistics. These statistical models contribute to establish a standardized method to obtain consistent results. Based on the method the lifetime of steel data was for the first time calculated on an annual basis for the steel usage as well as for the end of life scrap amount. This was done for the Swedish steel consumption and the global steel consumption between 1900 and 2013 as well as for future predictions between 2013 and 2060. The lifetime of steel was calculated to be higher in an industrialized country such as Sweden compared to the global average value. More specifically, the service lifetimes of EOL steel in Sweden and in the World were calculated to be 35 and 28 years in 2012, respectively. This novel approach of using system specific data on the lifetime of steel on an annual basis enables a possibility to evaluate recycling trends and potentials to increase the recycling rate.

Material Cycles and Chemicals: Dynamic Material Flow Analysis of Contaminants in Paper Recycling.

This study provides a systematic approach for assessment of contaminants in materials for recycling. Paper recycling is used as an illustrative example. Three selected chemicals, bisphenol A (BPA), diethylhexyl phthalate (DEHP) and mineral oil hydrocarbons (MOHs), are evaluated within the paper cycle. The approach combines static material flow analysis (MFA) with dynamic material and substance flow modeling. The results indicate that phasing out of chemicals is the most effective measure for reducing chemical contamination. However, this scenario was also associated with a considerable lag phase (between approximately one and three decades) before the presence of chemicals in paper products could be considered insignificant. While improved decontamination may appear to be an effective way of minimizing chemicals in products, this may also result in lower production yields. Optimized waste material source-segregation and collection was the least effective strategy for reducing chemical contamination, if the overall recycling rates should be maintained at the current level (approximately 70% for Europe). The study provides a consistent approach for evaluating contaminant levels in material cycles. The results clearly indicate that mass-based recycling targets are not sufficient to ensure high quality material recycling.

The Global Societal Steel Scrap Reserves and Amounts of Losses

In this study a newly developed method called the Progressing and Backcasting models were used to evaluate the annual resource utilizations of steel scrap in Sweden and globally. The model results show that it is possible to assess the amounts of steel scrap available for steelmaking at a given point in time, based on statistical dynamic material flow models. By a better mapping of the available amounts of steel scrap reserves on a country basis, it is possible to ease the trade of scrap across country boarders. This in turn can optimize the supply of recyclable metals as a raw material used in the industry. The results for Swedish steel consumption show that export bans used to secure the domestic market of steel scrap do damage the internal market due to increased amounts of losses. This suggests that export bans should be lifted to optimize recycling in countries. The model results also show that the global losses of steel are higher than for an industrialized country such as Sweden. Furthermore, the results show that the Backcasting and Progressing models can be used to calculate robust forecasts on the long term availability of steel scrap assets. This information could be used for future structural plans of scrap consuming steelmaking mills and waste management facilities. Hence, it is possible to contribute to a sustainable industrial development and a circular economy.

Dynamic Probabilistic Modeling of Environmental Emissions of Engineered Nanomaterials.

The need for an environmental risk assessment for engineered nanomaterials (ENM) necessitates the knowledge about their environmental concentrations. Despite significant advances in analytical methods, it is still not possible to measure the concentrations of ENM in natural systems. Material flow and environmental fate models have been used to provide predicted environmental concentrations. However, almost all current models are static and consider neither the rapid development of ENM production nor the fact that many ENM are entering an in-use stock and are released with a lag phase. Here we use dynamic probabilistic material flow modeling to predict the flows of four ENM (nano-TiO2, nano-ZnO, nano-Ag and CNT) to the environment and to quantify their amounts in (temporary) sinks such as the in-use stock and ("final") environmental sinks such as soil and sediment. Caused by the increase in production, the concentrations of all ENM in all compartments are increasing. Nano-TiO2 had far higher concentrations than the other three ENM. Sediment showed in our worst-case scenario concentrations ranging from 6.7 μg/kg (CNT) to about 40 000 μg/kg (nano-TiO2). In most cases the concentrations in waste incineration residues are at the "mg/kg" level. The flows to the environment that we provide will constitute the most accurate and reliable input of masses for environmental fate models which are using process-based descriptions of the fate and behavior of ENM in natural systems and rely on accurate mass input parameters.

A dynamic probabilistic material flow modeling method

Material flow modeling constitutes an important approach to predicting and understanding the flows of materials through the anthroposphere into the environment. The new “Dynamic Probabilistic Material Flow Analysis (DPMFA)” method, combining dynamic material flow modeling with probabilistic modeling, is presented in this paper. Material transfers that lead to particular environmental stocks are represented as systems of mass-balanced flows. The time-dynamic behavior of the system is calculated by adding up the flows over several consecutive periods, considering changes in the inflow to the system and intermediate delays in local stocks. Incomplete parameter knowledge is represented and propagated using Bayesian modeling. The method is implemented as a simulation framework in Python to support experts from different domains in the development of their application models. After the introduction of the method and its implementation, a case study is presented in which the framework is applied to predict the environmental concentrations of carbon nanotubes in Switzerland.

Future Raw Material Supply: Opportunities and Limits of Aluminium Recycling in Austria

In order to promote sustainable production by using secondary raw material from existing material stocks, complementary to primary raw material, information about the future availability of secondary resources constitutes a prerequisite. In this study, a dynamic material flow model of historic aluminium (Al) flows in Austria is combined with forecasts on future Al consumption to estimate the development of old scrap generation and in-use stocks until 2050. In-use stocks are estimated to increase by 60 % to 515 kg/cap. by 2050 assuming a scenario of moderate economic growth. Old scrap generation in 2050 would thereby more than double (up to 30 kg/cap.) in comparison to the 2010 amounts. Despite this substantial increase in old scrap generation, industrial self-supply from old scrap will probably not exceed 20 %, and final consumption self-supply of Al will not exceed 40 % given present conditions. Opportunities and limits of increasing self-supply through higher collection rates and lower scrap export levels are investigated in this study as the European Raw Material Initiative considers enhanced recycling to be a key measure to ensure future resource supply. Based on these analyses, a self-sustaining Al supply from post-consumer Al is not expected if current trends of Al usage continue. Therefore, comprehensive resource policy should be based on a profound understanding of the availability of primary and secondary resources potentials and their dynamics.

Dynamic material flow modeling: an effort to calibrate and validate aluminum stocks and flows in Austria.

A calibrated and validated dynamic material flow model of Austrian aluminum (Al) stocks and flows between 1964 and 2012 was developed. Calibration and extensive plausibility testing was performed to illustrate how the quality of dynamic material flow analysis can be improved on the basis of the consideration of independent bottom-up estimates. According to the model, total Austrian in-use Al stocks reached a level of 360 kg/capita in 2012, with buildings (45%) and transport applications (32%) being the major in-use stocks. Old scrap generation (including export of end-of-life vehicles) amounted to 12.5 kg/capita in 2012, still being on the increase, while Al final demand has remained rather constant at around 25 kg/capita in the past few years. The application of global sensitivity analysis showed that only small parts of the total variance of old scrap generation could be explained by the variation of single parameters, emphasizing the need for comprehensive sensitivity analysis tools accounting for interaction between parameters and time-delay effects in dynamic material flow models. Overall, it was possible to generate a detailed understanding of the evolution of Al stocks and flows in Austria, including plausibility evaluations of the results. Such models constitute a reliable basis for evaluating future recycling potentials, in particular with respect to application-specific qualities of current and future national Al scrap generation and utilization.

Dysprosium, the balance problem, and wind power technology

Wind power technology is one of the cleanest electricity generation technologies that are expected to have a substantial share in the future electricity mix. Nonetheless, the expected increase in the market share of wind technology has led to an increasing concern of the availability, production capacity and geographical concentration of the metals required for the technology, especially the rear earth elements (REE) neodymium (Nd) and the far less abundant dysprosium (Dy), and the impacts associated with their production. Moreover, Nd and Dy are coproduced with other rare earth metals mainly from iron, titanium, zirconium, and thorium deposits. Consequently, an increase in the demand for Nd and Dy in wind power technology and in their traditional applications may lead to an increase in the production of the host metals and other companion REE, with possible implications on their supply and demand. In this regard, we have used a dynamic material flow and stock model to study the impacts of the increasing demand for Nd and Dy on the supply and demand of the host metals and other companion REE. In one scenario, when the supply of Dy is covered by all current and expected producing deposits, the increase in the demand for Dy leads to an oversupply of 255 Gg of total REE and an oversupply of the coproduced REE Nd, La, Ce and Y. In the second and third scenarios, however, when the supply of Dy is covered by critical REE rich deposits or Dy rich deposits, the increase in Dy demand results in an oversupply of Ce and Y only, while the demand for Nd and La exceeds their supply. In the case of an oversupply of REEs, the environmental impacts associated with the REEs production should be allocated to Dy and consequently to the technologies that utilize the metal. The results also show that very large quantities of thorium will be co-produced as a result of the demand for Dy. The thorium would need to be carefully disposed of, or significant thorium applications would need to be found.

Greening China's Wastewater Treatment Infrastructure in the Face of Rapid Development: Analysis Based on Material Stock and Flow through 2050

SummaryWastewater treatment infrastructure (WWTI) construction in China has entered an accelerated stage of development in recent years as a result of rapid economic growth, urbanization, and the demand for improving water quality. As a result, a large amount of resources and materials will be allocated for the WWTI, and it is particularly important to find ways to reduce resource consumption effectively so that social dematerialization and sustainable development can be achieved. In this study, we employed the dynamic material flow model to estimate the material flows and stocks of WWTIs and the associated carbon dioxide (CO2) emissions through 2050, considering effects of a rise in water consumption, a longer lifetime, and an increased material recycling rate. Our results indicate that material consumption in WWTIs will increase rapidly through 2025 to meet the needs of the increased volume of discharged wastewater as well as to overcome the shortage of existing wastewater treatment plants. In contrast with the moderate effects of rise in water consumption, prolonging the lifetime will greatly reduce material consumption in WWTI construction during the period 2030–2050, and approximately 60% of the total material input will be saved in the medium‐lifetime scenario, compared with the short‐lifetime scenario. Material output and CO2 emissions associated with WWTIs will be reduced by 87% and 37%, respectively, in the medium‐lifetime scenario, compared with the short‐lifetime scenario, under high‐water‐consumption growth. Our results highlight the great importance of pipeline construction and cement consumption in resource consumption associated with WWTI construction in China. Moreover, this study also examined the potential ways to reduce material consumption in WWTI construction in the context of the demand chain, the design, construction, operation and management, and demolition.

Dynamic analysis of the global metals flows and stocks in electricity generation technologies

The demand for energy and consequently the emissions from energy generation have been increasing in recent years at rapid rates, leading to an urgent need for cleaner technologies. Cleaner technologies, however, require scarce resources. This paper analyzes the future development of electricity generation technologies and the metals required for their components, using a multi level dynamic material flow model. The model includes ten electricity generation technologies and the most important factors determining the dynamics of their metals requirement. The analysis is carried out from 1980 through 2050, using two scenarios, termed Market First and Policy First, combined with specific scenarios for the technologies. The results show that no resource problems occur in production capacity or in the availability of resources for wind power technologies in either scenario. In contrast, each photovoltaic solar technology has a constraining metal supply in the Policy First scenario: silver for silicon based technologies, tellurium for cadmium telluride technology, indium for copper indium gallium diselenide, and germanium for amorphous silicon. The model results show that the most critical photovoltaic solar metal in terms of resource availability and production capacity is tellurium. The demand for the base metals aluminium, copper, chromium, nickel, lead, and iron needed for electricity generation technologies can be met in the two scenarios.

Centennial Evolution of Aluminum In-Use Stocks on Our Aluminized Planet

A dynamic material flow model was developed to simulate the evolution of global aluminum stocks in geological reserve and anthropogenic reservoir from 1900 to 2010 on a country level. The contemporary global aluminum stock in use (0.6 Gt or 90 kg/capita) has reached about 10% of that in known bauxite reserves and represents an embodied energy amount that is equivalent to three-quarters of the present global annual electricity consumption. The largest proportions of in-use stock are located in the U.S. (28%), China (15%), Japan (7%), and Germany (6%) and in sectors of building and construction (40%) and transportation (27%). Industrialized countries have shown similar patterns of aluminum in-use stock growth: once the per-capita stocks have reached a threshold level of 50 kg, they kept a near linear annual growth of 5-10 kg/capita; no clear signs of saturation can yet be observed. The present aluminum in-use stocks vary widely across countries: approximately 100-600 kg/capita in industrialized countries and below 100 kg/capita in developing countries. The growing global aluminum in-use stock has significant implications on future aluminum demand and provides important recycling opportunities that will be critical for greenhouse gas emissions mitigation in the aluminum industry in the coming decades.

Towards a dynamic assessment of raw materials criticality: Linking agent-based demand — With material flow supply modelling approaches

Emerging technologies such as information and communication-, photovoltaic- or battery technologies are expected to increase significantly the demand for scarce metals in the near future. The recently developed methods to evaluate the criticality of mineral raw materials typically provide a ‘snapshot’ of the criticality of a certain material at one point in time by using static indicators both for supply risk and for the impacts of supply restrictions. While allowing for insights into the mechanisms behind the criticality of raw materials, these methods cannot account for dynamic changes in products and/or activities over time. In this paper we propose a conceptual framework intended to overcome these limitations by including the dynamic interactions between different possible demand and supply configurations. The framework integrates an agent-based behaviour model, where demand emerges from individual agent decisions and interaction, into a dynamic material flow model, representing the materials' stocks and flows. Within the framework, the environmental implications of substitution decisions are evaluated by applying life-cycle assessment methodology. The approach makes a first step towards a dynamic criticality assessment and will enhance the understanding of industrial substitution decisions and environmental implications related to critical metals. We discuss the potential and limitation of such an approach in contrast to state-of-the-art methods and how it might lead to criticality assessments tailored to the specific circumstances of single industrial sectors or individual companies.

Future recycling flows of tellurium from cadmium telluride photovoltaic waste

According to the European Photovoltaic Industry Association, photovoltaic energy has the potential to contribute up to 13% to the global electricity supply by 2040. A part of this electricity production will come from thin-film photovoltaic technologies. From various thin-film technologies available on the market today, low-cost cadmium telluride photovoltaics (CdTe-PV) can be considered the market leader with a market share of 5% at annual production. There are however two major concerns about this technology: first, the potential negative environmental impacts of cadmium contamination from CdTe-PV; and second, the possible shortage of the metal tellurium in the future. Because of these concerns, the recycling of production scrap and end-of-life PV modules is essential. In this paper we estimate how much tellurium will be recovered from PV scrap to substitute for primary tellurium. In order to estimate global tellurium flows until 2040, we have created a dynamic material flow model for the life-cycle of CdTe-PV modules. Three scenarios, which describe different market developments and technology trajectories, show how material efficiency measures – higher material utilization in production, decrease of material content in PV modules, and recycling of production scrap and end-of-life modules – will affect demand, waste flows, and recycling flows of semiconductor grade tellurium. The results depict that efficiency measures at process and cell level will reduce the specific tellurium demand per watt peak such that total tellurium demand starts to decline after 2020 despite further market growth. Thus, the CdTe-PV industry has the potential to fully rely on tellurium from recycled end-of-life modules by 2038. However, in order to achieve this goal, material efficiency must be substantially improved and efficient collection and recycling systems have to be built up.

The Role of Automobiles for the Future of Aluminum Recycling

To reach required product qualities with lowest costs, aluminum postconsumer scrap is currently recycled using strategies of downgrading and dilution, due to difficulties in refining. These strategies depend on a continuous and fast growth of the bottom reservoir of the aluminum downgrading cascade, which is formed by secondary castings, mainly used in automotive applications. A dynamic material flow model for the global vehicle system was developed to assess the likelihood, timing, and extent of a potential scrap surplus. The results demonstrate that a continuation of the above-mentioned strategies will lead to a nonrecyclable scrap surplus by around 2018 ± 5 if no additional measures are taken. The surplus could grow to reach a level of 0.4-2 kg/cap/yr in 2050, corresponding to a loss of energy saving potential of 43-240 TWh/yr electricity. Various intervention options for avoiding scrap surplus are discussed. Effective strategies need to include an immediate and rapid penetration of dramatically improved scrap sorting technologies for end-of-life vehicles and other aluminum applications.

Unearthing Potentials for Decarbonizing the U.S. Aluminum Cycle

Global aluminum demand is anticipated to triple by 2050, by which time global greenhouse gas (GHG) emissions are advised to be cut 50-85% to avoid catastrophic climate impacts. To explore mitigation strategies systematically, a dynamic material flow model was developed to simulate the stocks and flows of the U.S. aluminum cycle and analyze the corresponding GHG emissions. Theoretical and realistic reduction potentials were identified and quantified. The total GHG emissions for the U.S. aluminum cycle in 2006 amount to 38 Mt CO(2)-equivalence. However, the U.S. has increasingly relied on imports of aluminum embodied in various products. The in-use stock is still growing fast in most product categories, which limits current scrap availability for recycling and emissions saving. Nevertheless, there is still large emission mitigation potential through recycling. The potentials from "100% old scrap collection" and "low emission energy" were each calculated to be higher than all process technology potential. Total emissions will decrease dramatically and mitigation priorities will change significantly under a stock saturation situation as much more old scrap becomes available for recycling. The nature of in-use stock development over the coming decades will be decisive for the aluminum industry to reach deeper emission cuts.

Patterns of Iron Use in Societal Evolution

A dynamic material flow model was used to analyze the patterns of iron stocks in use for six industrialized countries. The contemporary iron stock in the remaining countries was estimated assuming that they follow a similar pattern of iron stock per economic activity. Iron stocks have reached a plateau of about 8-12 tons per capita in the United States, France, and the United Kingdom, but not yet in Japan, Canada, and Australia. The global average iron stock was determined to be 2.7 tons per capita. An increase to a level of 10 tons over the next decades would deplete about the currently identified reserves. A subsequent saturation would open a long-term potential to dramatically shift resource use from primary to secondary sources. The observed saturation pattern implies that developing countries with rapidly growing stocks have a lower potential for recycling domestic scrap and hence for greenhouse gas emissions saving than industrialized countries, a fact that has not been addressed sufficiently in the climate change debate.

Copper flows in buildings, infrastructure and mobiles: a dynamic model and its application to Switzerland

During the last century, the consumption of materials for human needs increased by several orders of magnitude, even for non-renewable materials such as metals. Some data on annual consumption (input) and recycling/waste (output) can often be found in the federal statistics, but a clear picture of the main flows is missing. A dynamic material flow model is developed for the example of copper in Switzerland in order to simulate the relevant copper flows and stocks over the last 150 years. The model is calibrated using data from statistical and published sources as well as from interviews and measurements. A simulation of the current state (2000) is compared with data from other studies. The results show that Swiss consumption and losses are both high, at a level of about 8 and 2 kg/(cap year), respectively, or about three times higher than the world average. The model gives an understanding of the flows and stocks and their interdependencies as a function of time. This is crucial for materials whose consumption dynamics are characterised by long lifetimes and hence for relating the current output to the input of the whole past. The model allows a comprehensive discussion of possible measures to reduce resource use and losses to the environment. While increasing the recycling reduces losses to landfill, only copper substitution can reduce the different losses to the environment, although with a time delay of the order of a lifetime.

Aluminum Stock and Flows in U.S. Passenger Vehicles and Implications for Energy Use

SummaryIn this article, a methodology to model the annual stock and flows of aluminum in a key end‐use sector in the United States—passenger vehicles—from 1975–2035 is described. This dynamic material flow model has enabled analysis of the corresponding energy embodied in automotive aluminum as well as the cumulative aluminum production energy demand. The former was found to be significant at 2.6 × 109 gigajoules (GJ) in year 2008 under baseline assumptions. From 2008–2035, the cumulative energy required to produce aluminum to be used in vehicles is estimated at 7.8 × 109 GJ. Although the automotive aluminum stock is expected to increase by 1.8 times by 2035, the corresponding energy embodied is not expected to grow as rapidly due to efficiency improvements in aluminum processing over time. The model's robustness was tested by checking the sensitivity of the results to variations in key input assumptions, including future vehicle sales, lifetimes, and scrap recovery. Sensitivity of energy embodied in automotive aluminum to changes in aluminum production efficiency and aluminum applications within the vehicle were also explored. Using more recycled aluminum or improving the energy efficiency of aluminum production at a faster rate can lower production energy demands. However, aggressive and sustained changes are needed beginning today to achieve meaningful reductions. This may potentially be countered by increased use of stamped aluminum in vehicles.

Material flow and economic analysis as a suitable tool for system analysis under the constraints of poor data availability and quality in emerging economies

Waste from electrical and electronic equipment or e-waste is increasingly processed in transitional or developing countries. The waste originates from both national consumption and waste imports. In these countries the e-waste processing and recycling is managed almost entirely by informal recycling businesses. Due to the application of inappropriate techniques, this sector bares high risks of environmental and occupational hazards and also looses valuable materials. Formal recycling industries have to compete with the informal businesses and simultaneously comply with environmental and occupational regulations. The presented model applies a dynamic stock-driven material flow model and an economic evaluation of gold and copper flows to the Indian personal computer (PC) recycling sector. The metal concentration per PC and value of these metals mainly determine the profits for recyclers. The study introduced threshold values for formal and informal gold and copper recycling according to their recycling cost per PC. At present level of metal concentration per PC and metal prices the formal sector will not become active. Two scenarios, one with double metal prices and a second with reduced threshold values for formal recycling, have been calculated. Also under theses scenarios the formal recycling sector will not overtake a majority of the recycling. The model proves that a stock-driven dynamic material flow model can be combined with an economic evaluation of material flows. The analysis included a calculation of error propagation and a sensitivity analysis.