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Material Flow Analysis with Multiple Material Characteristics to Assess the Potential for Flat Steel Prompt Scrap Prevention and Diversion without Remelting

  • Iain P. Flint
    Iain P. Flint
    Department of Engineering, University of Cambridge, Trumpington Street, Cambridge CB2 1PZ, United Kingdom
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  • André Cabrera Serrenho
    André Cabrera Serrenho
    Department of Engineering, University of Cambridge, Trumpington Street, Cambridge CB2 1PZ, United Kingdom
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  • Richard C. Lupton
    Richard C. Lupton
    Department of Engineering, University of Cambridge, Trumpington Street, Cambridge CB2 1PZ, United Kingdom
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  • , and 
  • Julian M. Allwood*
    Julian M. Allwood
    Department of Engineering, University of Cambridge, Trumpington Street, Cambridge CB2 1PZ, United Kingdom
    *E-mail: [email protected]. Phone: +44 1223 748 271.
    More by Julian M. Allwood
    Orcidhttp://orcid.org/0000-0003-0931-3831
Cite this: Environ. Sci. Technol. 2020, 54, 4, 2459–2466
Publication Date (Web):January 21, 2020
https://doi.org/10.1021/acs.est.9b03955

Copyright © 2022 American Chemical Society. This publication is licensed under CC-BY.

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Abstract

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Thirty-two percent of the liquid metal used to make flat steel products in Europe does not end up in a final product. Sixty percent of this material is instead scrapped during manufacturing and the remainder during fabrication of finished steel products. Although this scrap is collected and recycled, remelting this scrap requires approximately 2 MWh/t, but some of this material could instead be diverted for use in other applications without remelting. However, this diversion depends not just on the mass of scrapped steel but also on its material characteristics. To enhance our understanding of the potential for such scrap diversion, this paper presents a novel material flow analysis of flat steel produced in Europe in 2013. This analysis considers the flow of steel characterized not only by mass but, for the first time, also by grade, thickness, and coating. The results show that thin-gauge galvanized drawing steel is the most commonly demanded steel grade across the industry, and most scrap of this grade is generated by the automotive industry. There are thus potential opportunities for preventing and diverting scrap of this grade. We discuss the role of the geometric compatibility of parts and propose tessellating blanks for various car manufacturers in the same coil of steel to increase the utilization rates of steel.

Introduction

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With wide ranges of available strength, formability, weldability, toughness, and hardness, there is a grade of steel suitable for most engineering applications. By combining this variety with abundant ores and a relatively cheap cost of production, steel has become ubiquitous across the globe. 1.63 billion tonnes of steel were produced in 2016, (1) more than any other material apart from cement. (2) This ubiquity has its price: According to Allwood et al., (3) steel accounts for 6% of global CO2 emissions, giving it the largest footprint of any material in use today. With the combined pressures of emission targets, overcapacity of blast furnaces, and cheaper production in developing economies, it is pertinent to ask: is this a good time to change the way we use steel?
Improvements in energy efficiency over the last 50 years have already substantially decreased CO2 emissions from the steel industry to half of what they were per tonne in the 1960s. (4) However, over that same period, demand for steel has quadrupled, leading to a net doubling in emissions, a trend that is likely to continue as global economies develop. As an alternative, Allwood et al., (5) Milford et al., (6) and Pauliuk and Müller, (7) among others, have shown that pursuing material efficiency strategies can substantially reduce the carbon footprint of the steel industry. However, not all steel is created equal. The World Steel Association estimates that there are approximately 3500 grades in use today, each tailored for particular applications. Evaluation of material efficiency strategies such as process scrap diversion across different manufacturing sectors requires an understanding of the physical dimensions, mechanical properties, and corrosion protection required by each sector. For this reason, more than just measuring the mass flow of steel for each application, additional resolution of the grade, thickness, and coating of steel products would provide new insights into the most efficient uses of all steel products.
Material flow analysis (MFA) applies conservation of mass within a well-defined system boundary to determine the flow of material between the elements of that system. (8) Over the past two decades, MFA has been used to calculate the trade flow of materials between nations, (9) estimate material stocks, (10) and project trends of steel scrap supply. (11) MFA studies can be classified as top-down if they rely upon nationally collected statistics to form their data set, or bottom-up if the data is gathered by the inventory of the stocks within a system.
Top-down studies determine the flow in each time interval, from which stocks can be deduced. Previous top-down studies have calculated the flow of energy required during steelmaking, (12) mapped global production and consumption of steel, (13) and estimated the future demand for steel and the availability of scrap. These studies have been applied to inform decisions, including the requirement for new blast furnace or electric arc furnace capacity. (7,11,14,15)
Conversely, bottom-up studies involve the determination of stocks within a system boundary, from which the flow could in theory be determined. This would require knowledge of stock levels over consecutive time intervals, but in practice this has not yet been attempted. Bottom-up studies have calculated stocks of iron at the municipal, (16) state, (17) and national (18) levels through the direct inventory of iron-containing goods, as well as at state and national levels using correlations with proxy measures such as nighttime light intensity (19−21) and GDP/capita. (22)
A review of 50 MFA studies calculating stocks and flow of steel in the Supporting Information reveals that methods to date provide compelling insights into both the aggregate flow of steel at the global and national scale, as well as determination of steel stocks at a remarkably fine level of spatial resolution. However, two major gaps were identified in this literature: steel flow has only been disaggregated for few types of steel, and, where this detail is provided, higher-resolution steel flow has only been assessed for a small set of manufacturing industries.
In most assessments, steel is treated as a single material type, whereas, because of the range of available grades, coatings, and thicknesses, it is in reality a class of many different material types. A few studies have considered various steel grades. For example, Nakajima et al. (23) used input–output methods to assess the flow of three alloying elements of steel in Japan. More recently, Ohno et al. (24) have assessed the flow of steel in vehicles, with detail on the alloying elements present in steel to minimize their losses in steel recycling. However, for all previous studies, manufacturing with steel has only been disaggregated for a small set of industry sectors, most of them only for the automotive industry. But yield losses vary considerably across manufacturing processes and grades of steel, and therefore the availability of prompt scrap varies substantially for different grades of steel. Lack of detail on the quantities of prompt scrap by grade has been preventing the identification of opportunities for scrap diversion as feedstock across different industries, and further opportunities for reducing the generation of the prompt scrap. However, a higher-resolution MFA, capable of tracking not only flow of steel by grade, but also other material characteristics, such as thickness and coating, in addition to mass, coupled with a detailed assessment of manufacturing processes across industries, could enable the identification of novel opportunities to reduce steel production and to prevent unnecessary recycling and consequent energy use and emissions.
In this paper, for the first time, an MFA is constructed from commercial, statistical, and interview data, disaggregated by both material characteristics and the manufacturing process for Europe. This assessment enables the identification of potential opportunities for scrap diversion of flat steel across European industries, and it provides new insights into the novel opportunities to combine similar grades of steel in the same coils by tessellation across products.

Methods

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The following sections outline how adapting conventional MFA to allow for material characteristics can open the path to assessing the real potential for scrap diversion across manufacturing sectors. Then, the creation of a data set detailed around material characteristics and production stages in both steelmaking and manufacturing is described, created from three main data sources.

Allowing for Material Characteristics

Conventional MFA considers flow described by four dimensions:
1.

Source: where the flow originates

2.

Target: where the flow is sent

3.

Time: when the flow occurred

4.

Measure: the quantity and units of the flow

However, a fifth dimension can be introduced to differentiate between multiple material types in the same study:
5.

Material: the composition of the flow

The material dimension could simply differentiate between a few different metals, or be as complex as tracking the elemental composition, microstructure, and geometry of flow of steel through a system. In the framework devised by Lupton and Allwood, (25) the material dimension for each flow, along with the source, target, and time dimensions, can be assigned an ID that describes the characteristics of that material within a “Dimension Table”. These four IDs when paired with a measure then form a flow within the “Fact Table”, with all the tables together constituting the MFA database.
For conservation of mass across all materials, MFA requires the satisfaction of two equalities, which can therefore be adapted to include material characteristics as
(1)
(2)
where fi,p,m,t and fp,i,m,t are the quantities of material characteristic m flowing to and from process p from and to process i, respectively, during time t, cp,m,t and dp,m,t are the quantities of the material created and destroyed, respectively, in p during t, and Sp,m,t is the total stock in p at time t.

Data Required for a Disaggregated Steel MFA

To produce an MFA with disaggregation in material and manufacturing processes, three types of data were collected. First, a large European steelmaker provided shipment data for 2013 that describes the physical dimensions, mechanical properties, and surface quality of each order sold along with its mass. Second, top-down data from Eurofer, the European Steel Trade Association, describing the flow of each product category of steel into each industry sector was used to scale the commercial data to represent all European flat steel. Third, models for the production of each type of intermediate steel product and each manufacturing sector were developed based on data gathered from industry interviews and site visits. These models, which we will call process maps, determine the sequence of processes required to produce each coil of steel and to convert each coil into the final goods or scrap. Figure 1 shows examples of these process maps for (a) the production of a unit of galvanized steel and (b) the conversion of a unit of steel by the light vehicles sector.

Figure 1

Figure 1. Example process maps for (a) a backward-allocated order of hot-dip galvanized steel and (b) a forward-allocated order to the light vehicles sector.

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The following sections provide an overview of how the data was gathered and processed to produce the data set, and associated analyses are shown in the Results section. Full details of how this MFA was constructed and the Supporting Information associated with each of the following sections are available in the Supporting Information.

Shipment Data

The shipment database acquired for this study comprises all orders of flat steel delivered by one European steelmaking company for the year 2013. Each order is associated with many pieces of information, including the physical characteristics of the steel sold, such as its grade and thickness, as well as the mill of origin, the end user, and other commercially relevant data. To describe each order as a flow in eqs 1 and 2, five classes of information were extracted from the database:

  • Source: Where the flow originates, determined by the product category of each order; one of seven types of intermediate steel products (see Table 2) was chosen, since this allows estimation of what steelmaking processes must have occurred to produce this order.

  • Target: The destinations of steel orders from the commercial data set were consolidated into 22 industry sectors within the broad classifications of transport, construction, machinery, and goods. Some orders were shipped via distributors, providing stock holding and coil processing services. Two interviews and three site visits to steel stockists and service centers were conducted to estimate the proportion of each sector served by distributors. It was assumed that orders sent directly to an end user and those sent via distribution would lead to the same levels of scrap.

  • Material: The physical dimensions of width and thickness, the grade and grade family of steel, and the types and thicknesses of metallic or organic coatings were used to classify the material.

  • Time: This study used data from 2013 only.

  • Measure: The mass of each order in tonnes was used as the measure of flow, written as fi,j,m,t, where i, j, m, and t represent the source, the target, the material, and the timeframe of the flow, respectively.

EU Flat Steel Production

The shipment database describes the flat steel produced in Europe in 2013 by one European steelmaking company. Although data for only one company was used, their production volumes and the market share of this company were sought to gain insight into European flat steel flow. Therefore, this data was scaled up to European levels using specific ratios of the steel company’s output to that of the EU, for each end user and product category. Table 1 shows the mass of EU-produced steel for each of the seven product categories consumed by each of the eight manufacturing sectors. This table was produced by combining a linear interpolation of similar tables for 2010 and 2015 from Eurofer with other publicly reported data. (26) The flow extracted from the commercial database was categorized into one of these 56 product–sector pairs to allow scaling, with the total mass summing correctly to 88.4 Mt, the total output of the European flat steel industry in 2013.
Table 1. Estimates of Shipments of Flat Steel Products to Different Industry Sectors in Europe in 2013a
steel product categoryconstructionmechanical engineeringautomotiveelectricalother transporttubesmetal goodsother sectors
hot rolled65504910513058048099004060760
plate3530326022020124017001150230
cold rolled20502270369017902509703800360
hot-dip galvanized5170123099506402207802060390
electrocoated280901990170902034070
organic coated3080210240340300250140
tin plate01010000161010
a

All numbers in kt.

Modeling Steelmaking and Manufacturing Sectors

The flow upstream and downstream of each order of steel were determined by process maps. Each flow in the scaled database was assigned an upstream process map based on its product category and a downstream process map based on its target location and material composition. The upstream maps describe the series of steelmaking processes from creating liquid metal through to rolling and coating. The downstream maps describe the series of manufacturing processes from blanking and stamping through to the final assembly required to produce final goods. The upstream and downstream maps together depict the full production history of that order from iron ore and scrap inputs to the output of goods and the new process scrap, allowing calculations of material efficiency at the process level and up to the whole system level.
The steel industry process maps were developed from those of Llewellyn and Hudd. (27) Each process leads to yield losses (scrap), which were determined from values in the literature (13,28) and consultation with technicians during visits to an integrated steel mill in Belgium. The production outputs and associated losses for each process map are displayed in Table 2.
Table 2. Production Output and Steelmaking Losses Associated with Each Flat Steel Product in Europe in 2013a
 output
product categorylossescoils out
hot-rolled nonpicked1.07.0
hot-rolled picked3.926.6
cold rolled2.113.5
hot-dip galvanized3.018.8
electrogalvanized0.52.9
organic coated0.63.9
tin coated0.53.4
plate1.510.8
total13.087.0
a

All values in Mt.

Thirty-four interviews, 12 of which included site visits, were conducted to develop the downstream manufacturing process maps. For some sectors, distinct production pathways were identified for a material of different thicknesses, and thus some sectors are represented by multiple process maps. Table 3 summarizes this research and lists the demand, output, and scrap rate of each sector. The full details of these are provided in the Supporting Information.
Table 3. Twenty-Two Manufacturing Sectors Considered in this Study with the Number of Interviews and Site Visits Used to Determine the Process Map for Each Sectora
sectorsubsectorinterviews and site visitsdemand (kt)output (kt)scrap (kt)scrap rate (%)
transportcomponents12630168095036
 heavy vehicles1119076043036
 light vehicles316 5009400710043
 rail12502005020
 shipbuilding173056017023
constructioncivil engineering32120189023011
 exterior210 20096904905
 interior25600465095017
machineryagricultural149903790119024
 domestic appliances139302870106027
 electrical266404190246037
 other machinery140202810121030
 yellow goods12170154053029
goodspackaging35570499058010
 profiles115401450906
 containers122102120904
 drums and barrels14070358049012
 racking2313029701605
 tubes2898086203604
 boilers27206309013
 pressure vessels16405608013
 radiators1590560304
a

The calculated demand for steel in each sector, as well as the output of final goods and the scrap, is listed in thousands of tonnes (kt), as well as the scrap rate for each sector.

Results

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The procedure described in the previous section was followed to produce an MFA data set of flat steel production and manufacturing in the EU for the year 2013. This data set has been visualized as a Sankey diagram in Figure 2 with no differentiation of steel characteristics and with all steelmaking processes shown in detail, while manufacturing processes are aggregated at the sector level. Figure 2 demonstrates that the method employed in this study achieved the same level of detail as previous top-down studies for a single year, like the one produced by Cullen et al., (13) albeit at the European rather than global scale.

Figure 2

Figure 2. Sankey diagram visualization of the European steel flow for 2013. All values are in million tonnes of iron.

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Figure 2 shows that, in 2013, a total input of 116.6 Mt of iron contained in ore, process scrap, and home scrap was converted into 67.9 Mt of final products, an overall material efficiency of 58.3%. Process scrap (19.1 Mt) was produced in manufacturing. Production of light vehicles created the most losses, with a yield of only 57%. Out of a total material demand of 16.5 and 7.1 Mt of scrap was produced in this sector, most of which is galvanized and of relatively high value compared with other flat steel.
Figure 3 shows alternate views of the data set with the flow separated into bundles defined by one material category. The left side of each diagram shows inputs of steel to each manufacturing sector group, while the right side shows the products of each manufacturing sector and the scrap generated in processing. Figure 3a–d shows the flow divided by intermediate steel product category, thickness, grade family, and coating, respectively, while Figure 3e,f shows the data set with uncoated flow filtered out colored by material and manufacturing sector, respectively. From Figure 3b,c, it is clear that steel with a thickness below 2 mm or made of a drawing grade is required by all four manufacturing sectors, suggesting that there may be potential for substituting materials across different industries. Further details are provided in Section 4 of the Supporting Information file.

Figure 3

Figure 3. EU steel flow for 2013, divided by material characteristics. Each view shows inputs of steel to manufacturing from steelmaking and outputs of end-use goods, as well as scrap from each of the four main manufacturing sectors: transport, construction, machinery, and goods. The views are differentiated by (a) product category, (b) thickness, (c) grade, and (d) coating. Diagrams (e) and (f) show the steel flow, excluding all uncoated material, colored by coating (e) and by manufacturing sector (f).

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Figure 4a is in the same format as Figure 3, filtered for drawing-grade, thin-gauge galvanized steel, with the characteristics shown in Figure 3b–f in demand across multiple sectors. Figure 4b shows the demand for this material in each manufacturing sector, as well as the scrap produced. The highest demand and the greatest scrap output of any sector for this material type are in the light vehicles sector, which creates more scrap than the total demand of most other sectors.

Figure 4

Figure 4. (a) European flow of galvanized drawing steel with a thickness of 1–2 mm. (b) Demand for galvanized drawing steel with a thickness of 1–2 mm, and scrap generated by the industry sector.

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Discussion

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The results show that thin-gauge galvanized drawing steel is the most common steel grade demanded across the European manufacturing sectors and is thus the easiest grade of flat steel scrap that could be prevented or diverted as feedstock to other manufacturing industries. The European automotive industry produces 190 kt of this grade per year (Figure 4), as a result of 43% yield losses in their manufacturing processes. Various interventions can improve material utilization rates in this sector, but even if only current best practices were implemented by all manufacturers (29) this would create savings of 32–42 M€ and 125–171 kt CO2 in the EU every year, at €570–730 (30) and 2.2–3.0 t CO2 per tonne of flat steel. (1)
The results show that 37% of manufacturing scrap is generated by light vehicle manufacturers, even though this sector accounts for just 19% of the demand. Approximately 30% of this scrap comes from blanking, where both the scrap and parts leaving the blanking dies remain flat, and thus hold higher chances of having geometries compatible with other uses. Although there are opportunities for improving material utilization in the automotive industry, (29) part of its high yield losses arises from the production of each component from a different coil of steel. Since automotive manufacturers are simultaneously the greatest producers and users of 1–2 mm hot-dip galvanized drawing grade, there may be opportunities to reuse this scrap within this sector. However, this is unlikely to take place, unless the steel industry tessellates blanks for various automotive manufacturers from the same coil.
The potential improvements of tessellating components could be enhanced by relaxing the specifications for steel grade for individual components across the industry, which would allow for more components to be obtained from the same coil and by matching component geometries. (31) Further opportunities may exist across industries if other sectors using identical materials were able to communicate their part geometry to the steelmaker alongside the requirements of the vehicle manufacturer. Steelmakers could thus provide blanks rather than coils of steel, avoiding fabrication scrap downstream of the supply chain. In doing so, the same service to consumers could be provided with less metal production. This would reduce supply-side costs without reducing the demand-side value, saving both emissions and resources in the process.
The results shown in the previous section reveal a potential opportunity for diversion of thin-gauge galvanized drawing steel, by assessing the compatibility of mass and material grade across the EU flat steel supply chain. The opportunities for scrap reuse depend not only on grade compatibility but also on geometry and size. An assessment of automotive sheet metal components by Horton et al. (32) shows that the excess material from blanking in the automotive industry does not result in small fragments. Since this is one of the most abundant sources of flat steel scrap, blanking scrap can thus be used in other applications. However, real opportunities for scrap diversion would also require detailed information on the geometry of scrap parts produced. Although this information is not currently available, the methodology demonstrated in this analysis could be used to estimate this opportunity by adding eventual data on geometry as a material dimension in the model described in eqs 1 and 2.
Steel scrap generated by all manufacturers is collected by scrap merchants and sold for remelting and recycling. Although steel recycling produces up to three times less emissions than primary steel production, this is still a very energy-intensive process, requiring an average of 2 MWh/t of recycled steel. (33) However, the method demonstrated in this article enables the identification of opportunities to divert fabrication scrap for use as feedstock by other manufacturers, potentially avoiding unnecessary recycling. This is possible by the identification of material grades with the highest potential for scrap diversion because they are widely used across various industries. Moreover, this identification can provide important insights into the material grade choice, since relaxing grade tolerances across many applications could increase the uses of the most common grades, thus enhancing the opportunities for scrap diversion. For example, as shown in Figure 4, galvanized drawing steel with a thickness of 1–2 mm is the most common grade of steel across most European manufacturing sectors, and therefore relaxing the thickness tolerances within this grade would create potential diversion opportunities.
Manufacturing practices evolve as a result of changes in demand and progress in engineering and manufacturing technology. Consequently, the demand for material grades in each sector is equally likely to evolve, and thus the opportunities for scrap diversion depend on the dynamics of the demand for different grades and quantities of steel products over time. The method described in this paper could be applied to update potential opportunities according to the dynamics of the steel demand at each time. This method could also be applied to other material industries where significant differences in material characteristics could be exploited and large companies in possession of reliable commercial data could provide a similar starting database to the one used in this study. This might be of particular interest to aluminum suppliers.
Rigorous data on the national flow of steel, scrap arisings, and on the allocation of grades of steel to manufacturers is difficult to obtain, since there are no official statistics reporting them, and there is a lack of national studies quantifying this flow. The analysis presented here is thus subject to uncertainty. A shipment database of a big European steelmaking company was used to represent European flow, and the material flow analysis required several assumptions described in detail in the Supporting Information file. Despite these limitations, the data used in this paper is the best available data for the entire European flow of flat steel and it is sufficient to determine the scale of flow, since the market share of the company considered for this assessment is big enough to be representative of the European market, and the assumptions used here resulted from several interviews conducted across various European countries.

Supporting Information

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The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acs.est.9b03955.

  • Full literature review; extended discussion of the methodology employed in this study; data gathered and generated to create the MFA flow data set; EU flat steel production; modelling steelmaking and manufacturing sectors (PDF)

Terms & Conditions

Most electronic Supporting Information files are available without a subscription to ACS Web Editions. Such files may be downloaded by article for research use (if there is a public use license linked to the relevant article, that license may permit other uses). Permission may be obtained from ACS for other uses through requests via the RightsLink permission system: http://pubs.acs.org/page/copyright/permissions.html.

Author Information

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  • Corresponding Author
  • Authors
    • Iain P. Flint - Department of Engineering, University of Cambridge, Trumpington Street, Cambridge CB2 1PZ, United Kingdom
    • André Cabrera Serrenho - Department of Engineering, University of Cambridge, Trumpington Street, Cambridge CB2 1PZ, United Kingdom
    • Richard C. Lupton - Department of Engineering, University of Cambridge, Trumpington Street, Cambridge CB2 1PZ, United Kingdom
  • Notes
    The authors declare no competing financial interest.

Acknowledgments

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The authors would like to acknowledge the help of all the companies that provided data and facilitated site visits. The authors were supported by ArcelorMittal and a grant provided by the UK Engineering and Physical Sciences Research Council (EPSRC grant reference EP/N02351X/1).

References

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    Steel prodn. accounts for 25% of industrial carbon emissions. Long-term forecasts of steel demand and scrap supply are needed to develop strategies for how the steel industry could respond to industrialization and urbanization in the developing world while simultaneously reducing its environmental impact, and in particular, its carbon footprint. We developed a dynamic stock model to est. future final demand for steel and the available scrap for 10 world regions. Based on evidence from developed countries, we assumed that per capita in-use stocks will sat. eventually. We detd. the response of the entire steel cycle to stock satn., in particular the future split between primary and secondary steel prodn.During the 21st century, steel demand may peak in the developed world, China, the Middle East, Latin America, and India. As China completes its industrialization, global primary steel prodn. may peak between 2020 and 2030 and decline thereafter. We developed a capacity model to show how extensive trade of finished steel could prolong the lifetime of the Chinese steelmaking assets. Secondary steel prodn. will more than double by 2050, and it may surpass primary prodn. between 2050 and 2060: the late 21st century can become the steel scrap age.
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    Metallurgical iron cycles are characterized for four anthropogenic life stages: prodn., fabrication and manufg., use, and waste management and recycling. This anal. is conducted for year 2000 and at three spatial levels: 68 countries and territories, nine world regions, and the planet. Findings include the following: (1) contemporary iron cycles are basically open and substantially dependent on environmental sources and sinks; (2) Asia leads the world regions in iron prodn. and use; Oceania, Latin America and the Caribbean, Africa, and the Commonwealth of Independent States present a highly prodn.-biased iron cycle; (3) purchased scrap contributes a quarter of the global iron and steel prodn.; (4) iron exiting use is three times less than that entering use; (5) about 45% of global iron entering use is devoted to construction, 24% is devoted to transport equipment, and 20% goes to industrial machinery; (6) with respect to international trade of iron ore, iron and steel products, and scrap, 54 out of the 68 countries are net iron importers, while only 14 are net exporters; (7) global iron discharges in tailings, slag, and landfill approx. one-third of the iron mined. Overall, these results provide a foundation for studies of iron-related resource policy, industrial development, and waste and environmental management.
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    A dynamic material flow model was used to analyze patterns of iron stocks in use for 6 industrialized countries. The contemporary iron stock in the remaining countries was estd. assuming they follow a similar pattern of iron stock/economic activity. Iron stocks reached a plateau of ∼8-12 tons per capita in the US, France, and UK, but not yet in Japan, Canada, and Australia. The global av. iron stock was detd. to be 2.7 tons per capita. An increase to a level of 10 tons over the next decades would about deplete currently identified reserves. A subsequent satn. would open a long-term potential to dramatically shift resource use from primary to secondary sources. The obsd. satn. pattern implies 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 not sufficiently addressed in the climate change debate.
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    Environmental Science & Technology (2013), 47 (7), 3448-3454CODEN: ESTHAG; ISSN:0013-936X. (American Chemical Society)
    Steel prodn. accounts for 25% of industrial carbon emissions. Long-term forecasts of steel demand and scrap supply are needed to develop strategies for how the steel industry could respond to industrialization and urbanization in the developing world while simultaneously reducing its environmental impact, and in particular, its carbon footprint. We developed a dynamic stock model to est. future final demand for steel and the available scrap for 10 world regions. Based on evidence from developed countries, we assumed that per capita in-use stocks will sat. eventually. We detd. the response of the entire steel cycle to stock satn., in particular the future split between primary and secondary steel prodn.During the 21st century, steel demand may peak in the developed world, China, the Middle East, Latin America, and India. As China completes its industrialization, global primary steel prodn. may peak between 2020 and 2030 and decline thereafter. We developed a capacity model to show how extensive trade of finished steel could prolong the lifetime of the Chinese steelmaking assets. Secondary steel prodn. will more than double by 2050, and it may surpass primary prodn. between 2050 and 2060: the late 21st century can become the steel scrap age.
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    Global demand for steel has risen to 1.4 billion tonnes/y and is set to at least double by 2050. The steel industry generates nearly 10% of energy-related CO2 emissions worldwide. Meeting 2050 climate change targets would require a 75% redn. in CO2 emissions for every tonne of steel produced; finding credible solns. is a challenge. The starting point to understand the environmental impacts of steel prodn. is to accurately map the global steel supply chain and identify the largest steel flows where actions can be directed to deliver the largest impact. This work presents a map of global steel which, for the first time, traces steel flow from steelmaking, through casting, forming, and rolling, to final goods fabrication. This diagram reveals the relative scale of steel flow and shows where efforts to improve energy and material efficiency should focus.
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    Steel is the most widely used material in the world and numerous studies analyzing the material flow of steel have been conducted for Japan, Asia and the world. While top-down and bottom-up approaches have been employed in material flow anal. and steel stock accounting, the applicability of these approaches is largely dependent on data availability. To overcome this problem of limited data, we proposed a method for estg. steel stock based on satellite images. Previous studies have shown that satellite images of nighttime lights are closely correlated with human activities, such as electricity consumption, CO2 emissions, and GDP, etc., which are also linked to the amt. of steel stock. Therefore, in this study, images of nighttime lights were used in conjunction with land cover data to est. the building and civil construction steel stock in Japan and other Asian countries. We initially performed the anal. for each prefecture of Japan and then applied the combined result to Japan, China, South Korea and Taiwan. Building steel stock was highly correlated with urban nighttime lights, while the steel stock used for civil construction structures was more closely correlated with total nighttime lights.
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    Human activity has become a significant geomorphic force in modern times, resulting in unprecedented movements of material around Earth. An essential constituent of this material movement, the major industrial metals aluminum, copper, iron, and zinc in the human-built environment are mapped globally at 1-km nominal resoln. for the year 2000 and compared with the locations of present-day in-ground resources. While the maps of in-ground resources generated essentially combine available databases, the mapping methodol. of in-use stocks relies on the linear regression between gross domestic product and both in-use stock ests. and the Nighttime Lights of the World dataset. As the first global maps of in-use metal stocks, they reveal that a full 25% of the world's Fe, Al, Cu, and Zn in-use deposits are concd. in three bands: (i) the Eastern seaboard from Washington, D.C. to Boston in the United States, (ii) England, Benelux into Germany and Northern Italy, and (iii) South Korea and Japan. This pattern is consistent across all metals investigated. In contrast, the global maps of primary metal resources reveal these deposits are more evenly distributed between the developed and developing worlds, with the distribution pattern differing depending on the metal. This anal. highlights the magnitude at which in-ground metal resources have been translocated to in-use stocks, largely from highly concd. but globally dispersed in-ground deposits to more diffuse in-use stocks located primarily in developed urban regions.
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    A review. Steel is not elemental iron but rather a group of iron-based alloys contg. many elements, esp. chromium, nickel, and molybdenum. Steel recycling is expected to promote efficient resource use. However, open-loop recycling of steel could result in quality loss of nickel and molybdenum and/or material loss of chromium. Knowledge about alloying element substance flow is needed to avoid such losses. Material flow analyses (MFAs) indicate the importance of steel recycling to recovery of alloying elements. Flows of nickel, chromium, and molybdenum are interconnected, but MFAs have paid little attention to the interconnected flow of materials/substances in supply chains. This study combined a waste input-output material flow model and phys. unit input-output anal. to perform a simultaneous MFA for nickel, chromium, and molybdenum in the Japanese economy in 2000. Results indicated the importance of recovery of these elements in recycling policies for end-of-life (EoL) vehicles and constructions. Improvement in EoL sorting technologies and implementation of designs for recycling/disassembly at the manufg. phase are needed. Possible solns. include development of sorting processes for steel scrap and introduction of easier methods for identifying the compn. of secondary resources. Recovery of steel scrap with a high alloy content will reduce primary inputs of alloying elements and contribute to more efficient resource use.
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    Environmental Science & Technology (2017), 51 (22), 13086-13094CODEN: ESTHAG; ISSN:0013-936X. (American Chemical Society)
    Importance of end-of-life vehicles (ELVs) as an urban mine is expected to grow, as more people in developing countries are experiencing increased stds. 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 elec.-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 (Mn, Cr, Ni, and Mo), which may replace 10% of the virgin sources in elec. arc furnace-based crude alloy steel prodn.
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  • Abstract

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    Figure 1

    Figure 1. Example process maps for (a) a backward-allocated order of hot-dip galvanized steel and (b) a forward-allocated order to the light vehicles sector.

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    Figure 2. Sankey diagram visualization of the European steel flow for 2013. All values are in million tonnes of iron.

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    Figure 3

    Figure 3. EU steel flow for 2013, divided by material characteristics. Each view shows inputs of steel to manufacturing from steelmaking and outputs of end-use goods, as well as scrap from each of the four main manufacturing sectors: transport, construction, machinery, and goods. The views are differentiated by (a) product category, (b) thickness, (c) grade, and (d) coating. Diagrams (e) and (f) show the steel flow, excluding all uncoated material, colored by coating (e) and by manufacturing sector (f).

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    Figure 4

    Figure 4. (a) European flow of galvanized drawing steel with a thickness of 1–2 mm. (b) Demand for galvanized drawing steel with a thickness of 1–2 mm, and scrap generated by the industry sector.

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