Influence of Input‐Scrap Quality on the Environmental Impact of Secondary Steel Production
Abstract
Summary: In electric arc furnaces (EAFs), different grades of steel scrap are combined to produce the targeted carbon steel quality. The goal of this study is to assess the influence of scrap quality on the recycling process and on the final product by investigating the effect of the scrap mix composition, and other inputs, for example, preheating energy, on the electricity demand of the melting process. A large industrial data set (empirical data set of ∼20,000 individual heats recorded during 2.5 years at a Swiss EAF site) is analyzed using linear regression. The influence of scrap grades on electricity demand are found to correlate strongly with their respective quality; specific electricity demand is up to 45% higher for low‐quality scrap than for high‐quality scrap. Given that chemical compositions of scrap grades are highly variable and often unknown, average concentrations are determined using linear regression with scrap input as the predictors and the amounts of the investigated elements in liquid steel as the dependent variable. The lowest quality (highest copper and tin concentrations) and the highest electricity demand in the EAF are found for scrap recovered from bottom ashes of municipal solid waste incineration. Although even with low‐quality scrap input steel recycling is environmentally superior to primary steel production, the optimization potential in terms of energy efficiency and resource recovery, for example, through pretreatment, seems to be substantial.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Haupt et al estimated that 'sweetening' low quality steel scrap requires about 1.4 times more energy than high quality steel scrap.
“Haupt et al [107] estimated that 'sweetening' low quality steel scrap requires about 1.4 times more energy than high quality steel scrap.”
From Material efficiency strategies to reducing greenhouse gas emissions associated with buildings, vehicles, and electronics—a review (2019) · cites this paper as [107]
Cites
Model Evaluation Guidelines for Systematic Quantification of Accuracy in Watershed Simulations
Moriasi, D. N., Arnold, J. G., Liew, M. W. V., Bingner, R. L., Harmel, R. D., & Veith, T. L. (2007) · Transactions of the ASABE · doi:10.13031/2013.23153 · Cited by 13,446 · see citing works
Kuhn, M., & Johnson, K. (2013) · doi:10.1007/978-1-4614-6849-3 · Cited by 6,788 · see citing works
Status of Automatic Calibration for Hydrologic Models: Comparison with Multilevel Expert Calibration
Gupta, H. V., Sorooshian, S., & Yapo, P. O. (1999) · Journal of Hydrologic Engineering · doi:10.1061/(asce)1084-0699(1999)4:2(135 · Cited by 2,266 · see citing works
Web Based Knowledge Infrastructures for the Sciences: An Adaptive Document
Hars, A. (2000) · Communications of the Association for Information Systems · doi:10.17705/1cais.00401 · Cited by 1,142 · see citing works
Reck, B. K., & Graedel, T. E. (2012) · Science · doi:10.1126/science.1217501 · Cited by 854 · see citing works
Life Cycle Assessment of Metals: A Scientific Synthesis
Nuss, P., & Eckelman, M. J. (2014) · PLoS ONE · doi:10.1371/journal.pone.0101298 · Cited by 777 · see citing works
mgcv:Mixed GAM Computation Vehicle with GCV/AIC/REML smoothness estimation
Wood, S. N. (2012) · Cited by 570 · see citing works
Metal recycling: opportunities, limits, infrastructure
Peuter, M., Hudson, C. W., Hagelüken, C., Heiskanen, K., Meskers, C. E. M., van Schaik, A., & Acker, K. V. (2012) · Cited by 224 · see citing works
Patterns of Iron Use in Societal Evolution
Müller, D. B., Wang, T., & Duval, B. D. (2010) · Environmental Science & Technology · doi:10.1021/es102273t · Cited by 198 · see citing works
Process Knowledge, System Dynamics, and Metal Ecology
Verhoef, E., Dijkema, G. P. J., & Reuter, M. A. (2004) · Journal of Industrial Ecology · doi:10.1162/1088198041269382 · Cited by 140 · see citing works
The role of automobiles for the future of aluminum recycling
Modaresi, R., & Müller, D. B. (2012) · Environmental Science & Technology · doi:10.1021/es300648w · Cited by 138 · see citing works
Gaustad, G. G., Olivetti, E., & Kirchain, R. (2010) · Journal of Industrial Ecology · doi:10.1111/j.1530-9290.2010.00229.x · Cited by 136 · see citing works
Thermodynamic Analysis for the Controllability of Elements in the Recycling Process of Metals
Nakajima, K., Takeda, O., Miki, T., Matsubae, K., & Nagasaka, T. (2011) · Environmental Science & Technology · doi:10.1021/es104231n · Cited by 121 · see citing works
Environmental consequences of recycling aluminum old scrap in a global market
Sevigné‐Itoiz, E., Gasol, C. M., Rieradevall, J., & Gabarrell, X. (2014) · Resources Conservation and Recycling · doi:10.1016/j.resconrec.2014.05.002 · Cited by 118 · see citing works
Unintentional Flow of Alloying Elements in Steel during Recycling of End‐of‐Life Vehicles
Ohno, H., Matsubae, K., Nakajima, K., Nakamura, S., & Nagasaka, T. (2014) · Journal of Industrial Ecology · doi:10.1111/jiec.12095 · Cited by 103 · see citing works
Nakamura, S., Kondo, Y., Matsubae, K., Nakajima, K., Tasaki, T., & Nagasaka, T. (2012) · Environmental Science & Technology · doi:10.1021/es3013529 · Cited by 95 · see citing works
A Survey of Mathematical Programming Applications in Integrated Steel Plants
Dutta, G., & Fourer, R. (2001) · Manufacturing & Service Operations Management · doi:10.1287/msom.3.4.387.9972 · Cited by 88 · see citing works
Worrell, E., Blinde, P., Neelis, M. L., et al. (2010) · doi:10.2172/1026806 · Cited by 79 · see citing works
A Linear Programming Model of Integrated Iron and Steel Production
Fabian, T. (1958) · Management Science · doi:10.1287/mnsc.4.4.415 · Cited by 64 · see citing works
Sustainable resource use requires “clean cycles” and safe “final sinks”
Kral, U., Kellner, K., & Brunner, P. H. (2012) · The Science of The Total Environment · doi:10.1016/j.scitotenv.2012.08.094 · Cited by 64 · see citing works
Hiraki, T., Takeda, O., Nakajima, K., et al. (2011) · Science and Technology of Advanced Materials · doi:10.1088/1468-6996/12/3/035003 · Cited by 50 · see citing works
A case study on raw material blending for the recycling of ferrous wastes in a blast furnace
Fröhling, M., & Rentz, O. (2009) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2009.08.002 · Cited by 42 · see citing works
A Material Flow‐based Approach to Enhance Resource Efficiency in Production and Recycling Networks
Fröhling, M., Schwaderer, F., Bartusch, H., et al. (2012) · Journal of Industrial Ecology · doi:10.1111/j.1530-9290.2012.00502.x · Cited by 41 · see citing works
Modeling of steelmaking processes
Price, D. J. (2010) · Ironmaking & Steelmaking Processes Products and Applications · doi:10.1179/030192310x12628786049198 · Cited by 39 · see citing works
Estimation of the Change in Quality of Domestic Steel Production Affected by Steel Scrap Exports
Igarashi, Y., Daigo, I., Matsuno, Y., & Adachi, Y. (2007) · ISIJ International · doi:10.2355/isijinternational.47.753 · Cited by 39 · see citing works
Thermodynamic metrics for measuring the “sustainability” of design for recycling
Reuter, M. A., & van Schaik, A. (2008) · JOM · doi:10.1007/s11837-008-0106-z · Cited by 36 · see citing works
Nachhaltige Metallwirtschaft Hamburg : Grundlagen und Vorgehensweise
Brahmer-Lohss, M., von Gleich, A., Gottschick, M., et al. (2000) · Cited by 1 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Hertwich, E. G., Ali, S., Ciacci, L., Fishman, T., Heeren, N., Masanet, E., Asghari, F. N., Olivetti, E., Pauliuk, S., Tu, Q., et al. (2019) · Environmental Research Letters · doi:10.1088/1748-9326/ab0fe3 · Cited by 477 · see citing works
Metal Dissipation and Inefficient Recycling Intensify Climate Forcing
Ciacci, L., Harper, E. M., Nassar, N. T., Reck, B. K., & Graedel, T. E. (2016) · Environmental Science & Technology · doi:10.1021/acs.est.6b02714 · Cited by 78 · see citing works
- Authors
- Haupt, M., Vadenbo, C., Zeltner, C., & Hellweg, S.
- Affiliations
- ETH Zurich (CH)
- Venue
- Journal of Industrial Ecology
- Published
- 2016-05-19
- Volume
- 21
- Issue
- 2
- Pages
- 391-401
- ISSN
- 1088-1980 (ISSN-L)
- 1530-9290
- OpenAlex
- W2400588323
- Cited by
- 83
- References
- 27
- Citations by year
- 2026: 12 · 2025: 8 · 2024: 10 · 2023: 6 · 2022: 8 · 2021: 6 · 2020: 10 · 2019: 12 · 2018: 5 · 2017: 3 · 2016: 3
- FWCI
- 6.81
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Industrial Ecology (publishedVersion)
- Funders
- Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung
- Eidgenössische Technische Hochschule Zürich
- Topics
- Physical Sciences › Engineering › Mechanical Engineering › Iron and Steelmaking Processes
- Physical Sciences › Engineering › Mechanical Engineering › Metallurgical Processes and Thermodynamics
- Physical Sciences › Environmental Science › Waste Management and Disposal › Recycling and Waste Management Techniques
- Keywords
- electric arc furnace, electricity demand, municipal solid waste incineration bottom ash, steel recycling, energy efficiency, environmental impact of steel production
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
