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Accueil Tous les numéros Volume 108 / Numéro 5-6 (2020) Matériaux & Techniques, 108 5-6 (2020) 510 Références
Numéro
Matériaux & Techniques
Volume 108, Numéro 5-6, 2020
Materials and Society: transitions in society, materials and energy
Numéro d'article 510
Nombre de pages 12
Section Environnement - recyclage / Environment - recycling
DOI https://doi.org/10.1051/mattech/2021006
Publié en ligne 26 avril 2021
  1. World Steel Association, Water management in the steel industry, position paper, World Steel Association 2015, ISBN 978-2-930069-81-4 [Google Scholar]
  2. Y. Gu, J. Xu, A.A. Keller, et al., Calculation of water footprint of the iron and steel industry: a case study in Eastern China, J. Clean. Prod. 92, 274–281 (2015) [Google Scholar]
  3. S.R. Kalvani, A.H. Sharaai, L.A. Manaf, A.H. Hamidian, Review On Water Footprint Method In Different Sectors, Int. J. Adv. Sci. Technol. 29, 1778–1785 (2020) [Google Scholar]
  4. G.F. Porzio, E. Alcamisi, I. Matino, V. Colla, An integrated approach for industrial water systems optimal design, in: Technical Proceedings of the 2014 NSTI Nanotechnology Conference and Expo, NSTI-Nanotech 2014, Vol. 3, 2014, pp. 529–532 [Google Scholar]
  5. S. Roudier, L.D. Sancho, R. Remus, M. Aguadomonsonet, Best Available Techniques (BAT) reference document for iron and steel production. Industrial Emissions Directive 2010/75/EU: Integrated Pollution Prevention and Control, Institute for Prospective and Technological Studies, Joint Research Centre, European Commission, 2013 [Google Scholar]
  6. T.A. Branca, B. Fornai, V. Colla, M.M. Murri, E. Streppa, A.J. Schröder, The challenge of digitalization in the steel sector, Metals 10, 2 (2020) [Google Scholar]
  7. J. Wang, S. Li, G. Xiong, D. Cang, Application of digital technologies about water network in steel industry, Resour. Conserv. Recycl. 55(8), 755–759 (2011) [Google Scholar]
  8. C. Deng, W. Jiang, W. Zhou, X. Feng, New superstructure-based optimization of property-based industrial water system, J. Clean. Prod. 189, 878–886 (2018) [Google Scholar]
  9. I. Matino, E. Alcamisi, G.F. Porzio, V. Colla, Application of Unconventional Techniques for Evaluation and Monitoring of Physico-Chemical Properties of Water Streams, Int. J. Simul. Syst. Sci. Technol. 16, 1 (2015) [Google Scholar]
  10. E. Alcamisi, I. Matino, M. Vannocci, V. Colla, Simplified Ionic Representation of Industrial Water Streams, in: 8th European Modeling Symposium on Mathematical Modeling and Computer simulation EMS2014, Pisa, Italy, pp. 286–290, (2014) [Google Scholar]
  11. I.A. Katsoyuannis, P. Gkotsis, M. Castellana, F. Cartechini, A.I. Zouboulis, Production of demineralized water for use in thermal power stations by advanced treatment of secondary wastewater effluent, J. Environ. Manag. 190, 132–139 (2017) [Google Scholar]
  12. B. Das, B. Chakrabarty, P. Barkakati, Preparation and Characterization of novel Ceramic Membranes for Micro-Filtration Applications, Ceram. Int. 43, 13 (2016) [Google Scholar]
  13. W. Liu, N. Canfield, Development of thin porous metal sheet as micro-filtration membrane and inorganic membrane support, J. Membr. Sci. 409(10), 113–126 (2012) [Google Scholar]
  14. C. Dong, G. He, H. Li, Y. Han, Y. Deng, Antifouling enhancement of poly(vinylidene fluoride) microfiltration membrane by adding Mg(OH)2 nanoparticles, J. Membr. Sci. 387-388, 40–47 (2012) [Google Scholar]
  15. J. Liu, J. Tian, Z. Wang, D. Zhao, F. Jia, B. Dong, Mechanism analysis of powdered activated carbon controlling microfiltration membrane fouling in surface water treatment, Coll. Surf. A: Phydicochem. Eng. Aspects 517, 45–51 (2017) [Google Scholar]
  16. J. Liu, B. Dong, B. Cao, D. Zhao, Z. Wang, Microfiltration process for surface water treatment: irreversible fouling identification and chemical cleaning, RSC Adv. 6, 115 (2016) [Google Scholar]
  17. V. Colla, I. Matino, T.A. Branca, B. Fornai, L. Romaniello, F. Rosito, Efficient Use of Water Resources in the Steel Industry, Water 9(11), 874 (2017) [Google Scholar]
  18. I. Matino, V. Colla, L. Romaniello, F. Rosito, L. Portulano, Simulation techniques for an efficient use of resources: An overview for the steelmaking field, in: World Congress on Sustainable Technologies (WCST), IEEE, 2015, pp. 48–54 [Google Scholar]
  19. I. Matino, B. Fornai, V. Colla, L. Romaniello, F. Rosito, Water Process Integration: Assessment of an Ultrafiltration and Reverse Osmosis Based Treatment to Regenerate Coke-Making Area Wastewater, in: Proceedings of European Steel Technology and Application Days (ESTAD 2017), 2017 [Google Scholar]
  20. V. Colla, T.A. Branca, F. Rosito, C. Lucca, B.P. Vivas, V.M. Delmiro, Sustainable reverse osmosis application for wastewater treatment in the steel industry, J. Clean. Prod. 130, 103–115 (2016) [Google Scholar]
  21. I. Matino, V. Colla, F. Cirilli, et al., Environmental impact evaluation for effective resource management in EAF steelmaking, Metall. Ital. 10, 48–58 (2017) [Google Scholar]
  22. Eurofer, Susteel – Sustainability for steel construction products mark – Definition of the KPI system, (2012) [Google Scholar]
  23. J.M. Fernández, F.R. Pérez, M.G. Huerta, A.S. Vizán, Methodology for the selection of key performance indicators for sustainable steel production through an intelligent control system use, Project Manag. Eng. Res. 89–102 (2014) [Google Scholar]
  24. V. Colla, I. Matino, F. Cirilli, et al., Improving energy and resource efficiency of electric steelmaking through simulation tools and process data analyses, Materiaux & Techniques 104, 6–7 (2016) [Google Scholar]
  25. V. Colla, I. Matino, S. Dettori, et al., Assessing the efficiency of the off-gas network management in integrated steelworks, Materiaux & Techniques 107, 1 (2019) [Google Scholar]
  26. I. Matino, V. Colla, V. Colucci, P. Lamia, S. Baragiola, C. Di Cecca, Improving sustainability of electric steelworks through process simulations, Chem. Eng. Trans. 52, 763–768 (2016) [Google Scholar]
  27. E. Alcamisi, I. Matino, V. Colla, A. Maddaloni, L. Romaniello, F. Rosito, Process Integration Solutions for Water Networks in Integrated Steel Making Plants, Chem. Eng. Trans. 45, 37–42 (2015) [Google Scholar]
  28. J.J. Klemeš, P.S. Varbanov, S.R.W. Alwi, Z.A. Manan, Sustainable Process Integration and Intensification: Saving Energy, Water and Resources, Walter de Gruyter GmbH & Co KG, 2018 [Google Scholar]
  29. R.M. Smith, Chemical Process: Design and Integration, John Wiley & Sons, Ltd., Chichester, West Sussex, United Kingdom, 2005 [Google Scholar]
  30. UNEP’s Finance Industry Initiatives, Industry as a Partner for Sustainable Development. Finance and Insurance, Geneva, Switzerland, 2002 [Google Scholar]
  31. R. Wolters, M. Hubrich, M. Kozariszczuk, P. Mund, J. Kamp, M. Wessling, Treatment of Cooling and Process Water in the Steel Industry, Chem.-Ingenieur-Tech. 91(10), 1445–1453 (2019) [Google Scholar]
  32. Y.P. Luzin, V. Kazyuta, N. Mozharenko, A. Zen’kovich, Removal of cyanides from blast-furnace gas and wastewater, Steel Transl. 42(7), 606–610 (2012) [Google Scholar]
  33. I. Matino, V. Colla, Modelling of an Ozonation Process for Cyanide Removal from Blast Furnace Gas-Washing Water and Analyses of Process Behaviour in Different Scenarios, Chem. Eng. Trans. 61, 1447–1452 (2017) [Google Scholar]
  34. I. Matino, V. Colla, T.A. Branca, Extension of pilot tests of cyanide elimination by ozone from blast furnace gas washing water through Aspen Plus® based model, Front. Chem. Sci. Eng. 12, 718–730 (2018) [Google Scholar]
  35. V. Colla, F. Cirilli, B. Kleimt, et al., Monitoring the environmental and energy impacts of electric arc furnace steelmaking, Matériaux & Techniques 104, 102 (2016) [CrossRef] [EDP Sciences] [Google Scholar]

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