Optimal Recycling of Steel Scrap and Alloying ... - ACS Publications

Policy Analysis Cite This: Environ. Sci. Technol. XXXX, XXX, XXX-XXX

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Optimal Recycling of Steel Scrap and Alloying Elements: InputOutput based Linear Programming Method with Its Application to End-of-Life Vehicles in Japan Hajime Ohno,*,† Kazuyo Matsubae,‡ Kenichi Nakajima,§ Yasushi Kondo,∥ Shinichiro Nakamura,∥ Yasuhiro Fukushima,† and Tetsuya Nagasaka⊥ †

Department of Chemical Engineering, Graduate School of Engineering, Tohoku University, 6-6-07 Aramaki Aza Aoba, Aoba-ku, Sendai, Miyagi 980-8579, Japan ‡ Department of Environmental Study for Advanced Society, Graduate School of Environmental Studies, Tohoku University, 468-1 Aramaki Aza Aoba, Aoba-ku, Sendai Miyagi 980-0845, Japan § Center for Material Cycles and Waste Management, National Institute for Environmental Studies, 16-2 Onogawa, Tsukuba, Ibaraki 305-8506, Japan ∥ Faculty of Political Science and Economics, Waseda University, 1-6-1 Nishi-waseda, Shinjuku-ku, Tokyo 169-8050, Japan ⊥ Department of Metallurgy, Graduate School of Engineering, Tohoku University, 6-6-02 Aramaki Aza Aoba, Aoba-ku, Sendai, Miyagi 980-8579, Japan S Supporting Information *

ABSTRACT: Importance of end-of-life vehicles (ELVs) as an urban mine is expected to grow, as more people in developing countries are experiencing increased standards of living, while the automobiles are increasingly made using high-quality materials to meet stricter environmental and safety requirements. While most materials in ELVs, particularly steel, have been recycled at high rates, quality issues have not been adequately addressed due to the complex use of automobile materials, leading to considerable losses of valuable alloying elements. This study highlights the maximal potential of quality-oriented recycling of ELV steel, by exploring the utilization methods of scrap, sorted by parts, to produce electric-arc-furnace-based crude alloy steel with minimal losses of alloying elements. Using linear programming on the case of Japanese economy in 2005, we found that adoption of parts-based scrap sorting could result in the recovery of around 94−98% of the alloying elements occurring in parts scrap (manganese, chromium, nickel, and molybdenum), which may replace 10% of the virgin sources in electric arc furnace-based crude alloy steel production. (i.e., alloyed) combined forms.7 Not only alloyed metals, but also mechanically combined metals become practically inseparable during the remelting stage in the recycling process, unless they are separated in advance.5,9 Consequently, closedloop recycling of metals maintaining required quality tends to be infeasible. Currently open-loop recycling is the mainstream recycling strategy.10,11 In open-loop metal recycling the way in which scrap is sorted and allocated to the production of secondary materials determine recycling ratio of the metal.2,6,12,13 The importance of considering subprimary metal contents in scrap allocation to

1. INTRODUCTION Urban mining is a key concept for the sustainable use of metals.1 However, the recovery and/or recycling of metals from end-of-life (EoL) products (i.e., urban mines) has become increasingly complicated due to the complex structure and composition of recent functional products.2 Potential issues such as unintentional alloying, contamination, and dissipation may occur, induced by this complication in some metals with high recycling ratios3 as those metals are typically not used independently, but are combined and/or alloyed.4−6 The efficient recovery of metals from EoL products requires analyzing how metals are contained in EoL products and determining the appropriate recycling methods for them.2,7 Closed-loop recycling would be an ideal way of recycling metals sustainably.8 However, it is seldom applied, because metals are mostly utilized in mechanically and/or physically © XXXX American Chemical Society

Received: August 31, 2017 Revised: October 20, 2017 Accepted: October 24, 2017

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DOI: 10.1021/acs.est.7b04477 Environ. Sci. Technol. XXXX, XXX, XXX−XXX

Policy Analysis

Environmental Science & Technology

2. MATERIALS AND METHODS 2.1. Contributions of Linear Programing to Waste Recycling. In waste recycling, various types of waste are treated as secondary resources. Additionally, various technologies are available for waste recovery and use. Consequently, there are many possible combinations of waste, recovery, and recycling technologies. For sustainable resource management, it is important to choose an optimal combination of the available alternatives that maximizes recycling benefits and minimizes losses. LP has been used as a practical approach to identify a system that minimizes the environmental impacts of various production and recycling systems, such as plastic materials production,30 energy supply,31 oil refining,32 and solid waste recycling.33 Those studies use linearized process inventories for formulation of a linear program. In addition, LP has also been applied with input-output table to various areas in industrial ecology.34−38 Kondo and Nakamura developed the waste inputoutput-LP model (WIO-LP),39 which can be used to optimize the selection of waste treatment and recycling technology, along with goods and service-production technologies, under the objective of environmental load minimization based on the IO model extended for waste (WIO).40 Lin applied WIO-LP to wastewater treatment to optimize technological choices for minimizing environmental loads.41 Studies based on LP are also available for ELV recycling.42,43 However, there are few LPbased studies focusing on the quality of scrap recycling in terms of AEs. An exception is Løvik et al., who applied LP to optimize ELV-derived aluminum scrap recycling to reduce scrap surplus, considering AE concentrations in sorted aluminum scrap.13 Løvik et al.’s approach is similar to the present study in its consideration of quality aspects. However, using the IO approach in this study enables the evaluation of the influence of optimized recycling on the whole national economy, whereas Løvik et al.’s study only focused on aluminum used in the automobile industry. Gaustad et al.15 identified three scrap allocation models: pooled scrap allocation, pseudoclosed-loop scrap allocation, and market-based scrap allocation. In the pooled scrap allocation, scrap is collected and allocated without any distinction for either origin or usage. In the pseudoclosedloop allocation, scrap derived from an EoL product is directly allocated to produce the same product again. In reality, however, scrap is purchased by secondary material producers first, and secondary material producers then decide the usage of scrap for secondary material production (i.e., market-based allocation).15 Since mass-produced metals, such as aluminum and steel, are widely utilized in various industries, market-based allocation can simulate the behavior of secondary producers that have several options regarding scrap use and secondary material production to meet the demand from various industries. This study follows the market-based allocation approach by applying the IO database, developed for the WIOMFA (hereafter, called WIO-MFA table),6,12,22 based on the Japanese IO table for 200544 as a reference to AE demand in EAF steelmaking and demand for EAF steel materials. 2.2. Linear Program. The equality constraints of our optimization problem are classified into three groups. The first group represents the supply demand balance regarding goods and services. The equality takes the form x = Ax + y,45 the standard supply demand balance equation in input-output analysis. The second group represents the supply demand balance regarding scrap. The third group of constraints refers to

secondary material productions was emphasized in studies regarding aluminum scrap recycling, since the reduction of impurity accumulations in recycled aluminum is an important subject.13−16 On the other hand, studies focusing on subprimary metal contents in steel recycling are rare, except for those concerned with contamination by copper,4,17 presumably because of the small share of steel materials containing alloying elements (AEs) compared with massproduced carbon steel.18,19 The recent increase in automobile production20 and its increasing use of alloy steel21 made sustainable management of both primary (iron) and subprimary (AEs) metals in scrap,6,12,22,23 important. In fact, Daigo et al.24 found that the dissipation of AEs into carbon steel is causing a gradual increase in the concentration of AEs (regarded as contaminants) in steel scrap,25 emphasizing the need for quality in recycling steel for sustainable use. In our previous studies,6,12,22 the masses of the AEs contained in automobiles are estimated by waste input-output material flow analysis (WIO-MFA)26,27 with confirmations of consistency with chemically analyzed composition28 and discussions on the uncertainty included in the results.12 Furthermore, the potential benefits of scrap sorting before shredding and melting are estimated by a scenario-based approach comparing the AE contents in ELV-derived steel scrap (ES) sorted by parts (hereafter, called “parts scrap” to distinguish it from ES in generic terms) with industrial standards of steel grades.6,12,22 In addition, the fate of AEs embodied in each of products over multiple life cycles of products are tracked by MaTrace-alloy model by giving scrap allocation scenarios to alternative refining processes exogenously.29 However, the exploration of allocation scenarios may have been insufficient in scope and in variations. To discuss how effective practical scenarios of interests are, and to systematically synthesize near-ideal allocation scenarios, maximal potential benefits needs to be addressed.22 In this paper, we reveal the optimal allocation of parts scrap to the production of EAF steel, and evaluate potential benefits of parts scrap utilization as a secondary source of AEs on the reduction of the embodied greenhouse gas (GHG) emissions and costs. Building upon previous works, we use input-output based linear programing (LP) to identify an optimal way of using secondary AE sources, that is, parts scraps having specific AE compositions. The secondary and virgin AE sources are used together to produce electric-arc-furnace (EAF) steels that are subject to different AE requirements. Two alternative objective functions are considered: (1) minimizing greenhouse gas (GHG) emissions embodied in virgin AE sources, and (2) minimizing the cost of purchasing virgin AE sources in EAF steelmaking. In addition to the allocation of secondary AE sources, the uses of virgin AE sources were also optimized based on the objective functions. Constraints for the linear program are given by the economy-wide supply demand balance obtained from the IO database developed for simultaneous AE flow analysis with WIO-MFA.6,12 This enables us to understand the influences of optimized parts scrap utilization on both steelmaking-related and other sectors. In addition, we explore strategies for reducing the embodied GHG emissions to be consistent with the cost reduction by studying the differences between the results from the two objective functions. Finally, we discuss the technological and political implications of our work. B


Policy Analysis


result of WIO-MFA22 with the AEs demands for EAF steelmaking indicated in the WIO-MFA table,6 rather than against industrial standards. Since Løvik et al. pointed out the presence of several industrial standards for alloys, defining the representative allowable ranges of AE concentration is difficult, limiting the usefulness of the allocation model approach.13 Addressing this challenge, we choose to employ the WIO-MFA table as a reference of AE demands in EAF steelmaking, instead of various industrial standards. The database comprises the weighted average of AE inputs in the production of each grade of EAF steel, considering both industrial standards and their share in the production of each steel grade.6,12 Accordingly, the supply and demand information for AEs in the WIO-MFA table is well represented, reflecting the practical conditions of EAF steelmaking. For simplicity, this study avoids the issues of contamination by nonferrous elements, other than AEs, by assuming that parts scrap is completely separated and sorted from the mechanically combined (i.e., nonalloyed) nonferrous elements, which are relatively easily separated by ELV treatments such as magnetic and/or eddy current separation.46 As in our previous study, we estimate the AE composition of an ELV generated in 2005 with the WIO-MFA table of that year, and thus neglect any change in the composition that could have taken place over the life of the ELV.22 These are strong assumptions that disregard any possible variability in material composition and the AE contents of automobiles over time. Given the limited data availability, however, we find it a reasonable approach to be adopted for obtaining a benchmark. Furthermore, we ignored the varieties of AE contents in the parts originated from the different models of automobiles by referring to the national average composition of automobiles obtained by WIO-MFA instead. In other words, our model simulates the situation that there are heaps of ES sorted by parts regardless of the original model of automobiles. This assumption is much closer to the real situation of practical ELV recycling rather than identifying and sorting the scrap based on models or types of automobiles.47 As virgin AE sources, ferroalloys (e.g., ferromanganese, silicomanganese, ferrochromium, ferronickel, and ferromolybdenum), metallic AEs (e.g., metallic manganese and metallic nickel), and other sources (e.g., molybdenum briquettes) were considered. For the grade of steel to be produced by EAF, we define carbon steel and the 19 grades of alloy steel separately. Alloy steel in this study represents a steel that requires contents of AEs and/or special treatments to obtain some desired properties (i.e., “specialty steel” in Japanese categorization21). Accordingly, carbon steel is steel that is not categorized as alloy steel in this study. For detailed definitions on steel grades, see SI. The embodied GHG emissions and price intensity of each virgin AE source, were separately set for domestically produced virgin AE sources and imported ones, based on several references.44,48−50 The intensity for embodied GHG emissions was referenced from the LCI database IDEA ver 1.040 for domestically produced virgin AE sources, and from Ecoinvent49 for imported virgin AE sources. Regarding the virgin AE sources’ purchase costs, the unit price of each virgin AE source was obtained from an appendix of the 2005 Japanese IO table44 and Japanese trade statistics50 for domestic and imported virgin AE sources, respectively. For the numerical values regarding the sets and constants, see SI. We conducted a sensitivity analysis with regard to the influence of variations of data on the results by using the dual

the composition of metals that are specific to alloy steels and is determined based on technical conditions, whereas the first and second groups of constraints refer to market balance conditions. We consider non-negativity constraints on variables and two alternative objective functions to minimize: GHG emission and production cost. The production recipes, that is, the combinations of raw material inputs, for producing various types of alloy steel are the design variables in this linear program. In general, there are two methods to implement this optimization of production recipes in input-output analysis. One is to introduce additional columns and variables, which represent alternative production technologies to produce alloy steel; this results in the input coefficient matrix A having more columns than rows.35,36 This method is suitable when “extreme” production recipes are known and any feasible recipe can be expressed as a weighted average, or convex combination, of extreme alternatives. However, this is not the case in our study. The other method that we employed is to treat input coefficients as variables. Our problem can be modeled using a linear program, coping with the nonlinearity introduced by this method along the lines of Kondo and Nakamura.39 It should be noted that the third set of group constraints, showing the mass balance of each sector regarding metal elements, plays the role of keeping variable input coefficients valid in the sense that requirements for the elemental composition of produced alloy steel are fulfilled. Because parts scrap contains AEs, it can be a secondary AE source and replace some fractions of AEs derived from virgin AE sources. The model would enable us to quantify the extent of this substitution under the objectives. We introduced additional inequality constraints to our linear program to rule out meaningless solutions. See Supporting Information (SI) for further details. 2.3. Data. In this study, the WIO-MFA table, developed based on the Japanese IO Table for 2005 in our previous studies,6,22 provides the data required to formulate constraints for the optimization of parts scrap use. The WIO-MFA table is an extended IO table for flow analysis in the level of AEs by disaggregating both raw material sectors (e.g., Ferroalloys) and crude-steel production sector in the original IO table based on production reports obtained by Japanese main steelmakers, industrial standards and their share among the production of each steel grade.6 For example, the Ferroalloys sector, which had been aggregated into only one sector for all metal species in the original IO table, was disaggregated into nine sectors such as Ferromanganese, Ferrochromium and so on corresponding to each metal species.6 Crude-steel production sector was disaggregated into 58 sectors on the basis of two production methods (i.e., basic oxygen furnace [BOF] and EAF) and 29 steel grades.6 The WIO-MFA26,27 was conducted based on the table, and enabled us to obtain material compositions and AE contents in approximately 400 kinds of products.6,22 The obtained composition and AE contents of automobile can be regarded as national average confirmed to be in the same range with a detailed chemical analysis.28 Besides, AE contents in parts scrap were estimated based on the result of WIO-MFA for automobiles by considering current ELV treatments such as dismantling of engine and/or reusable parts, pressing, and shredding.6,22 For more details on the development of WIOMFA table and the results of the analysis, see our previous works.6,22 To optimize parts scrap use, in terms of its AE content, we compare the AE content in parts scrap estimated based on the C


Policy Analysis


Figure 1. Optimized flows of scrap mass (upper half) and alloying elements (bottom half) under two objective functions (left half and right half) with satisfying demands for alloying elements in EAF steel production in Japan in 2005. The left-hand side and right-hand side of each Sankey diagram respectively depict separated parts scrap to be used for steel production by EAF, and alloy steel grades chosen to be produced by using parts scrap from 19 grades as well as carbon steel. Steel grades not appearing in the figure were unable to use parts scrap in the production due to certain discordances between contents and requirements of alloying elements in steel grades and parts scrap, respectively.

objective functions, parts scrap was almost entirely consumed in alloy steel production, with only a small fraction ending up in carbon steel. This implies that most AEs were efficiently utilized as a secondary source of AE in EAF steelmaking: approximately 10 200 t (t) of manganese, 19 900 t of chromium, 5500 t of nickel, and 570 t of molybdenum were utilized as AE sources, respectively. These masses correspond to 94%, 99%, 98%, and 98% of manganese, chromium, nickel, and molybdenum occurring in parts scrap, respectively. In total, 97% of AEs in parts scrap can be effectively utilized as AE sources in EAF steelmaking. According to our previous study, 93% of ES was remelted without sorting in EAF steelmaking to produce carbon steel in Japan in 2005,6 implying that 93% of AEs contained in ES dissipated into carbon steel and steelmaking slag. Furthermore, the ratio of AE recovery from parts scrap was estimated as 78% by a scenario-based approach.22 Our results thus demonstrate significant benefits of sorting ES into parts scrap and appropriately utilizing them on the recovery of AEs contained in ES. 3.2. Benefits of Parts Scrap Utilization. Benefits were quantified by referring to the base state of Japan in 2005 as described in the WIO-MFA table (hereafter, referred to as BS). Figure 2 shows that the optimal use of parts scrap can reduce the input of AEs from virgin sources by 10% of BS for both the objective functions. Figure 2 also shows that the extent of

properties of the LP. The results from the sensitivity analysis are explained in the SI.

3. RESULTS AND DISCUSSION 3.1. Optimized Scrap Usage. Figure 1 shows the optimized flows of scrap mass and alloying element under the two objective functions. It turned out that of the 19 grades of alloy steel, only 9 grades were assigned for parts scrap usage with carbon steel. The requirements for AEs in the other 10 grades do not match with the AE content of any parts scrap. For these 10 grades of alloy steel, parts scrap cannot be used without the dilutive input of iron, or intended removal by oxidation. For example, Cr stainless steel (i.e., ferritic stainless steel) was not assigned as a parts scrap application, because this alloy steel does not require nickel input, but requires significant amounts of chromium, some manganese, and molybdenum. This demand pattern for AEs in Cr stainless steel production did not allow for the input of any parts scrap, as all parts scrap contains traces of nickel. The scrap flows toward carbon steel imply the loss of AEs into carbon steel as the nonfunctional inclusion. On a scrap mass basis, automobile body parts dominated the flows, as they have the largest mass among the parts scraps,22 whereas on an AE mass basis, exhaust parts dominated the flows of chromium, nickel, and molybdenum. Under both the D


Policy Analysis


virgin sources consumed in EAF steelmaking at BS. Compared with the results obtained under cost minimization, this reduction is 1.5 times larger. Regarding the total purchase cost of virgin sources, 31.6 billion Japanese yen (JPY) (ca. 287 million USD at 1 USD = 110 JPY) could be optimally reduced, which corresponds to 15.2% of the value of virgin sources consumed in EAF steelmaking at BS. For both GHG emission and costs, the magnitudes of reduction achieved under the optimization exceeded those of our previous research, which shows 318 to 609 kt-CO2eq and 13 billion JPY for the reduction of GHG emission and costs, respectively without employing any optimization algorithms, 22 showing the usefulness of applying optimization to parts scrap utilization for the maximization of benefits. 3.3. Choice of Virgin Sources of AEs. Figure 3 compares the amounts of consumption of virgin AE sources in 2005 with those obtained under each of the objective functions. For chromium, the two objectives resulted in the same results with regard to the choice of virgin chromium sources. Of its four virgin AE sources, optimization resulted in the entire elimination of domestic and imported “Other Cr sources” and “FeCr,” whereas for “FeCr (Imp)” the reduction was kept at a modest level. For the other AEs, the results differed depending on the choice of the objective function. For manganese, “Metallic Mn (Imp)” was reduced under cost minimization, while “SiMn” was reduced under GHG emission minimization. For nickel, domestic/imported “other Ni sources” were reduced under cost minimization, whereas “FeNi (Imp)” and “Metallic Ni” were reduced under GHG

Figure 2. Reduction achievements obtained by optimal parts scrap utilization by referring to base state in Japan in 2005 (BS). Reduction achievements in GHG and cost are different depending on the objective functions, whereas almost the same mass of AEs derived from virgin sources are reduced.

reduction in GHG emissions and the purchase cost of virgin AE sources differ depending on the objective function. Regarding GHG minimization, 749 kt-CO2eq could be reduced, which corresponds to 28.3% of the GHG emissions embodied in

Figure 3. Consumption of virgin AE sources in EAF steelmaking observed in base state in Japan in 2005 (BS) and obtained by the optimization under each of the objective functions. Details for virgin AE sources indicated by simplified labels in the graph are shown in the SI. E


Policy Analysis


Figure 4. Frontiers maximizing the benefit of parts scrap utilization (a) and the breakdown of the frontier by AEs (b). Points A to E represent the points where the frontier is bent and correspond to the ranges of certain weights between two objective functions. For example, Point C represents the reduction ratios for the cost reduction and the GHG reduction at the weight (0.98, 0.02) to (0.87, 0.13). Sums of reduction ratios of points in (b) are consistent with the ratios in (a). For example, the sum of GHG reduction ratios of Point B for four AEs and iron comes to about 24% of the same sum for Point B in (a).

emission minimization. For molybdenum, domestic/imported “FeMo” was reduced under both objective functions, but with a slight quantitative difference. Under cost minimization, the demand for AE virgin sources with higher prices would be reduced, whereas under GHG minimization those with larger embodied GHG emission intensities would be reduced. Consequently, if a high-price virgin AE source happened to have low GHG emission intensity, a trade-off relationship would emerge between the solutions of the objective functions (see SI for more details on the results for individual virgin AE sources). 3.4. Multiobjective Optimization. The trade-off relationship can be visualized as a frontier as shown in Figure 4 by conducting a multiobjective optimization. This procedure enables us to find weights balancing both the reductions of GHG emissions and of purchase costs for virgin AE sources. The result of this multiobjective optimization can support decision making regarding parts scrap utilization. See the SI for methodological details of our multiobjective optimization. In Figure 4 (a), every point on the frontier represents the maximum benefits of both objective functions. The points, A, B, C, D, and E on the frontier correspond to the benefits for both objective functions at a certain weight ratio between the minimization of costs and GHG emissions. Points A and E represent the benefits when we consider either only costs minimization or embodied GHG minimization, respectively. A slight consideration for embodied GHG reduction has a large impact on the benefits. Point A corresponds to the maximum reduction in costs. Point C indicates, however, that if the extent of cost reduction was kept at a slightly higher level, 14.4% instead of 15.2%, a reduction in embodied GHG of 27.6% could be achieved, which is very close to its maximum reduction. This implies the possibility of a slight sacrifice in cost reduction resulting in a significant reduction in GHG emissions. Figure 4(b) decomposes the points on the frontier by elements. By observing correspondences of the points between Figure 4(a) and (b), we can understand which AEs contributed to the shift of the points. The shift from Points A to B was made by the change in choice in the virgin manganese sources; Points B to C, and Points C to D were caused by virgin nickel sources; and Points D to E were due to virgin molybdenum sources. Besides these changes, chromium and iron contributed to the benefits of both reductions with constant choices at any

weights. By combining with Figure 3, Point C, which would be the best balance between the objectives, can be achieved by choosing “SiMn” for manganese, and “FeNi (Imp)” and “Metallic Ni” for nickel instead of virgin AE sources chosen under the objective function minimizing the costs (for detailed methodology and results, see SI). 3.5. Implications and Future Directions. This study demonstrated that appropriate utilization of parts scrap as secondary AE sources reduced both GHG emissions and the costs of virgin AE sources. The proposed ES recycling strategy sorting ES into just eight kinds of parts scrap and utilizing them appropriately in EAF steelmaking could make parts scrap an indispensable source of urban mining. It implies that more precise sorting of ES by grades of steel will bring better benefits on AE saving in ES recycling. In current ES recycling, however, ES is usually regarded as an “iron source,” with its AE content mostly neglected,6 even in Japan and EU, which have established automobile recycling laws under 3R (Reduce, Reuse, and Recycling) policies51 and ELV directive, 52 respectively.53 The laws only regulate the mass-based recycling rate of materials from ELVs,54 and do not control the use of ES in EAF steelmaking. While discussions on the concept and definition of the Circular Economy is still ongoing,55,56 importance of the quality of recycling and subsequent preservation of materials are pointed out as one of its essential components.57 This study provides a theoretical benchmark for implementation of this important strategy for steel material used in automotive sector. Toward the development of a quality Circular Economy, amendment of current policies is required to engage the industries utilizing the recycled materials as well as the recyclers and producers of the products subject to recycling. The current policies only regulate activities of ELV recyclers in terms of ES.53 A higher level of engagement of EAF steelmakers would be an important target of the amended policies. For the purpose of exploiting the maximal benefits of AE contentoriented ES recycling in grade level, ELV recyclers are expected to play larger roles than EAF steelmakers. Investment requirements for ELV recyclers, such as the installation of additional processes and/or equipment, are likely to discourage them from committing to detailed disassembling and sorting of ES, unless compensated for by the proper pricing of ES instead of the current pricing one on the shapes of scrap alone,22 and/ F


Policy Analysis

Environmental Science & Technology ORCID

or economic incentives supported by policies to encourage EAF steelmaker to purchase and utilize ES. In addition to ELV recyclers, developers of scrap sorting technologies accurately detecting elements and sorting steel scrap according to AE contents are also important players in the system for the exploitation of potential benefits. Recently, technologies that rapidly determine AE composition in steel material by applying X-ray58,59 or laser60,61 have been developed. The development of automatic separation equipment and/or process applying these technologies is expected to be the next step. Financial support for the technology developers is another important role of policies. Development of better sorting technologies allow ELV recyclers to sort ES precisely according to AE content and provide useful secondary sources of iron and AEs for EAF steelmakers. Not only for ELV recycling but for all kinds of waste, policies covering all the stakeholders in waste treatment systems are necessary toward the development of a quality Circular Economy. Since these benefits were estimated based on the prices of virgin AE sources, prices for each type of parts scrap may also be decided based on the AE content in each scrap. Under cost minimization, the optimum pattern of the use of parts scrap would vary with the prices of virgin AE sources. AE valueoriented optimization and AE content-oriented ES price estimation will be a future direction for this study. This study considered two objective functions. Given the availability of relevant inventory data, a larger set of objective functions can be considered. This would help us identify more practical information relevant for a wide range of stakeholders. Another important direction for future research would be to extend its scopeJapan, for this studyon a global scale. Japan has both EAF steelmakers and ELV recyclers as stakeholders, but other countries and regions may not. Since ELVs are generated worldwide,62,63 this difference in the existence of stakeholders could be included in the discussion on global scrap price decisions. International price decisions on ES, based on AE content, will affect the attitudes of countries regarding ELV treatment and activate the trade for ES as a useful urban mine of AE. In facing a rapidly motorizing world, an efficient recycling system for ELV will be required not only at the stakeholder level in a region, but also at a global level.64 Furthermore, we can apply this model to every type of steel scrap. Along with ES, quality-oriented recycling of massgenerated construction steel scrap, industrial machinery, and other types of steel scrap can be evaluated by determining their representative AE compositions. Implementing steel scrap recycling on a larger scale, we can develop an efficient steel and AE urban mining society.

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Hajime Ohno: 0000-0002-8826-3854 Shinichiro Nakamura: 0000-0002-7735-024X Yasuhiro Fukushima: 0000-0002-1525-7242 Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS This research was supported by the Japan Society for the Promotion of Science (JSPS) (KAKENHI 23686131, 26281059, 15K12265, and Grant-in-Aid for JSPS Research Fellow 258801), the Iron and Steel Institute of Japan (a research group for recycling automobiles from the perspective of the material industry), and the Research Institute of Science and Technology for Society of the Japan Science and Technology Agency (JST-RISTEX).

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(1) United Nations Environment Programme (UNEP). Metal recycling: Opportunities, limits, infrastructure2013. (2) Reck, B. K.; Graedel, T. E. Challenges in metal recycling. Science 2012, 337 (6095), 690−5. (3) Graedel, T. E.; Allwood, J.; Birat, J.-P.; Buchert, M.; Hagelüken, C.; Reck, B. K.; Sibley, S. F.; Sonnemann, G. What do we know about metal recycling rates? J. Ind. Ecol. 2011, 15 (3), 355−366. (4) Nakamura, S.; Kondo, Y.; Matsubae, K.; Nakajima, K.; Tasaki, T.; Nagasaka, T. Quality- and dilution losses in the recycling of ferrous materials from end-of-life passenger cars: Input-output analysis under explicit consideration of scrap quality. Environ. Sci. Technol. 2012, 46 (17), 9266−73. (5) Nakajima, K.; Takeda, O.; Miki, T.; Matsubae, K.; Nagasaka, T. Thermodynamic analysis for the controllability of elements in the recycling process of metals. Environ. Sci. Technol. 2011, 45 (11), 4929− 36. (6) Ohno, H.; Matsubae, K.; Nakajima, K.; Nakamura, S.; Nagasaka, T. Unintentional flow of alloying elements in steel during recycling of end-of-life vehicles. J. Ind. Ecol. 2014, 18 (2), 242−253. (7) Ohno, H.; Nuss, P.; Chen, W. Q.; Graedel, T. E. Deriving the metal and alloy networks of modern technology. Environ. Sci. Technol. 2016, 50 (7), 4082−90. (8) Gleich, A. v.; Ayres, R. U.; Gössling-Reisemann, S. Sustainable metals management: Securing our future-steps towards a closed loop economy; Springer: Dordrecht, 2006; p xvi, 607 p. (9) Hiraki, T.; Takeda, O.; Nakajima, K.; Matsubae, K.; Nakamura, S.; Nagasaka, T. Thermodynamic criteria for the removal of impurities from end-of-life magnesium alloys by evaporation and flux treatment. Sci. Technol. Adv. Mater. 2011, 12 (3), 035003. (10) Nakamura, S.; Kondo, Y.; Kagawa, S.; Matsubae, K.; Nakajima, K.; Nagasaka, T. MaTrace: Tracing the fate of materials over time and across products in open-loop recycling. Environ. Sci. Technol. 2014, 48 (13), 7207−14. (11) Pauliuk, S.; Kondo, Y.; Nakamura, S.; Nakajima, K. Regional distribution and losses of end-of-life steel throughout multiple product life cycles-insights from the global multiregional MaTrace model. Resour. Conserv. Recycl. 2017, 116, 84−93. (12) Nakajima, K.; Ohno, H.; Kondo, Y.; Matsubae, K.; Takeda, O.; Miki, T.; Nakamura, S.; Nagasaka, T. Simultaneous material flow analysis of nickel, chromium, and molybdenum used in alloy steel by means of input-output analysis. Environ. Sci. Technol. 2013, 47 (9), 4653−60. (13) Lovik, A. N.; Modaresi, R.; Muller, D. B. Long-term strategies for increased recycling of automotive aluminum and its alloying elements. Environ. Sci. Technol. 2014, 48 (8), 4257−65. (14) Yamada, H.; Hatayama, H.; Daigo, I.; Matsuno, Y.; Adachi, Y. Optimization method for metal recycling system and its application to aluminum recycling flow in Japan. Nippon Kinzoku Gakkaishi 2006, 70 (12), 995−1001.

ASSOCIATED CONTENT

* Supporting Information S

The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.est.7b04477. The detailed methodology for the derivation of the linear program, multiobjective optimization, the background data for the program, and detailed results on the choice of virgin AE sources as well as multiobjective optimization, and sensitivity analysis (PDF)

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*Phone +81-22-795-5869; e-mail: [email protected]. G


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