The Experts below are selected from a list of 78081 Experts worldwide ranked by ideXlab platform
S. Mahdi Hosseinian - One of the best experts on this subject based on the ideXlab platform.
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Data needed for assessing water footprint of Steel Production.
Data in brief, 2020Co-Authors: Reza Nezamoleslami, S. Mahdi HosseinianAbstract:Abstract The data presented in this paper offer the information needed for assessing the water footprint of Steel Production. The data provided here are related to the research paper, “An Improved Water Footprint Model of Steel Production Concerning Virtual Water of Personnel: The Case of Iran” [1]. The data were collected form analysing a case study and reviewing the relevant literature. The case study data were collected from a large Steel plant in Iran. All information received from this plant is related to 2017. The primary data were collected by interviewing the head of the research and development of the plant. All relevant formal documents of the plant and information on its web site were also reviewed. For data related to the water footprint of energy and raw materials, used for Steel Production, the relevant studies were reviewed.
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An improved water footprint model of Steel Production concerning virtual water of personnel: The case of Iran.
Journal of environmental management, 2020Co-Authors: Reza Nezamoleslami, S. Mahdi HosseinianAbstract:Abstract The water footprint concept has been widely applied to the agriculture sector; however, little attention has been given to industrial products. In this paper, the concept of water footprint is applied to a large Steel plant located in a semi-arid basin in the central part of Iran. The limitations of existing research, including the lack of any advanced approach for assessing the virtual water of personnel's food, working in the plant, and the lack of providing independent data sources, are addressed. An improved water footprint model of Steel Production is proposed based on the water footprint network methodology and the life cycle assessment framework. Ideas from food ecological footprint are applied to measure the water footprint of personnel's foods. The case of Iran demonstrates that the water footprint of Steel Production is considerably large compared with other industrial products. The results highlight the relevance of Production line technology, energy efficiency measures, and human management on reducing the water footprint of Steel products. The paper adds to a growing body of literature on environmentally friendly Steel Production.
J. Katzberg - One of the best experts on this subject based on the ideXlab platform.
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Steel Production schedule generation
International Journal of Production Research, 1997Co-Authors: I. Assaf, M. Chen, J. KatzbergAbstract:In this paper, an iron and Steel Production scheduling problem is studied. An algorithm based on an implicit enumeration procedure is developed to solve the problem. Due to the large number of practical constraints, the real-world scheduling problem can be e fficiently solved by the enumeration based algorithm within acceptable computation time. The method is applied to generate Steel Production schedules for a Steel Production company in Canada. The computer generated schedules are compared with the manually generated and currently used schedules in the company. Computational results show large potential savings from the optimal schedules over the manually generated schedules.
Reza Nezamoleslami - One of the best experts on this subject based on the ideXlab platform.
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Data needed for assessing water footprint of Steel Production.
Data in brief, 2020Co-Authors: Reza Nezamoleslami, S. Mahdi HosseinianAbstract:Abstract The data presented in this paper offer the information needed for assessing the water footprint of Steel Production. The data provided here are related to the research paper, “An Improved Water Footprint Model of Steel Production Concerning Virtual Water of Personnel: The Case of Iran” [1]. The data were collected form analysing a case study and reviewing the relevant literature. The case study data were collected from a large Steel plant in Iran. All information received from this plant is related to 2017. The primary data were collected by interviewing the head of the research and development of the plant. All relevant formal documents of the plant and information on its web site were also reviewed. For data related to the water footprint of energy and raw materials, used for Steel Production, the relevant studies were reviewed.
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An improved water footprint model of Steel Production concerning virtual water of personnel: The case of Iran.
Journal of environmental management, 2020Co-Authors: Reza Nezamoleslami, S. Mahdi HosseinianAbstract:Abstract The water footprint concept has been widely applied to the agriculture sector; however, little attention has been given to industrial products. In this paper, the concept of water footprint is applied to a large Steel plant located in a semi-arid basin in the central part of Iran. The limitations of existing research, including the lack of any advanced approach for assessing the virtual water of personnel's food, working in the plant, and the lack of providing independent data sources, are addressed. An improved water footprint model of Steel Production is proposed based on the water footprint network methodology and the life cycle assessment framework. Ideas from food ecological footprint are applied to measure the water footprint of personnel's foods. The case of Iran demonstrates that the water footprint of Steel Production is considerably large compared with other industrial products. The results highlight the relevance of Production line technology, energy efficiency measures, and human management on reducing the water footprint of Steel products. The paper adds to a growing body of literature on environmentally friendly Steel Production.
Ali Hasanbeigi - One of the best experts on this subject based on the ideXlab platform.
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Comparison of carbon dioxide emissions intensity of Steel Production in China, Germany, Mexico, and the United States
Resources Conservation and Recycling, 2016Co-Authors: Ali Hasanbeigi, Marlene Arens, Jose Carlos Rojas Cardenas, Lynn Price, Ryan TrioloAbstract:Abstract Production of iron and Steel is an energy-intensive manufacturing process. The goal of this study was to develop a methodology for accurately and more fairly comparing the energy-related carbon dioxide (CO2) emissions intensity of Steel Production in different countries and to demonstrate the application of this methodology in an analysis of the Steel industry in China, Germany, Mexico, and the U.S. Our methodology addresses the industry’s boundary definition, conversion factors, and industry structure. The results of our analysis show that, for the entire iron and Steel Production process, the base-case (2010) CO2 emissions intensity was 2148 kg CO2/tonne crude Steel in China, 1708 kg CO2/tonne crude Steel in Germany, 1080 kg CO2/tonne crude Steel in Mexico, and 1736 kg CO2/tonne crude Steel in the U.S. One of the main reasons that Mexico has the lowest CO2 emissions intensity is Mexico’s large share of Steel Production using electric arc furnaces (EAFs) (69.4%). EAF Steel Production has lower CO2 emissions intensity than Production using blast furnaces/basic oxygen furnaces. China, by contrast, has the smallest share of EAF Production among the four countries—9.8% in the base-case year 2010. In one scenario, we applied the Chinese share of EAF Production to the other three case-study countries; the result was an increase in CO2 emissions intensity of Steel Production of 19% (2036 kg CO2/tonne crude Steel) in Germany, 92% (2074 kgCO2/tonne crude Steel) in Mexico, and 56% (2703 kg CO2/tonne crude Steel) in the U.S. compared to these countries’ base-case analyses. In another scenario, we applied the Chinese national average grid electricity CO2 emissions factor from 2010, which is the highest emissions factor among the four countries, to the other three countries. In that scenario, the CO2 emissions intensity of Steel Production increased by 5% in Germany, 11% in Mexico, and 10% in the U.S.
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a comparison of iron and Steel Production energy use and energy intensity in china and the u s
Journal of Cleaner Production, 2014Co-Authors: Ali Hasanbeigi, Lynn Price, Nathaniel Aden, Zhang Chunxia, Li Xiuping, Shangguan FangqinAbstract:E RNEST O RLANDO L AWRENCE B ERKELEY N ATIONAL L ABORATORY A Comparison of Iron and Steel Production Energy Use and Energy Intensity in China and the U.S. Ali Hasanbeigi, Lynn Price, Nathaniel Aden China Energy Group, Energy Analysis Department Environmental Energy Technologies Division Lawrence Berkeley National Laboratory Zhang Chunxia, Li Xiuping, Shangguan Fangqin State Key Laboratory of Advanced Steel Processes and Products, China Iron & Steel Research Institute June 2011 This work was supported by the China Sustainable Energy Program of the Energy Foundation through the U.S. Department of Energy under Contract No. DE-AC02-05CH11231.
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A Comparison of Iron and Steel Production Energy Use and Energy Intensity in China and the U.S.
2011Co-Authors: Ali Hasanbeigi, Lynn Price, Nathaniel Aden, Zhang Chunxia, Li Xiuping, Shangguan FangqinAbstract:Production of iron and Steel is an energy-intensive manufacturing process. In 2006, the iron and Steel industry accounted for 13.6% and 1.4% of primary energy consumption in China and the U.S., respectively (U.S. DOE/EIA, 2010a; Zhang et al., 2010). The energy efficiency of Steel Production has a direct impact on overall energy consumption and related carbon dioxide (CO2) emissions. The goal of this study is to develop a methodology for making an accurate comparison of the energy intensity (energy use per unit of Steel produced) of Steel Production. The methodology is applied to the Steel industry in China and the U.S. The methodology addresses issues related to boundary definitions, conversion factors, and indicators in order to develop a common framework for comparing Steel industry energy use. This study uses a bottom-up, physical-based method to compare the energy intensity of China and U.S. crude Steel Production in 2006. This year was chosen in order to maximize the availability of comparable Steel-sector data. However, data published in China and the U.S. are not always consistent in terms of analytical scope, conversion factors, and information on adoption of energy-saving technologies. This study is primarily based on published annual data from the China Iron & Steel Association and National Bureau of Statistics in China and the Energy Information Agency in the U.S. This report found that the energy intensity of Steel Production is lower in the United States than China primarily due to structural differences in the Steel industry in these two countries. In order to understand the differences in energy intensity of Steel Production in both countries, this report identified key determinants of sector energy use in both countries. Five determinants analyzed in this report include: share of electric arc furnaces in total Steel Production, sector penetration of energy-efficiency technologies, scale of Production equipment, fuel shares in the iron and Steel industry, and final Steel product mix in both countries. The share of lower energy intensity electric arc furnace Production in each country was a key determinant of total Steel sector energy efficiency. Overall Steel sector structure, in terms of average plant vintage and Production capacity, is also an important variable though data were not available to quantify this in a scenario. The methodology developed in this report, along with the accompanying quantitative and qualitative analyses, provides a foundation for comparative international assessment of Steel sector energy intensity
Semida Silveira - One of the best experts on this subject based on the ideXlab platform.
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Weighing regional scrap availability in global pathways for Steel Production processes
Energy Efficiency, 2017Co-Authors: Maria Xylia, Semida Silveira, J. Duerinck, F. Meinke-hubenyAbstract:This study analyses the impact of the rising availability of Steel scrap on the future Steel Production up to the year 2100 and implications for Steel Production capacity planning. Steel Production processes are energy, resource, and emission intensive, but there are significant variations due to different Production routes, product mixes, and processes. This analysis is based on the development of Steel demand, using the Steel Optimization Model, which provides a region-detailed representation of technologies, energy and material flows, and trade activities. It is linked to the Scrap Availability Assessment Model which estimates the theoretical Steel scrap availability. Aggregated crude Steel Production is estimated to evolve into an almost balanced split by 2050 between the primary Production route using iron ore in the blast oven furnace and the secondary route using mostly Steel scrap in the electric arc furnace. By 2060, the share of secondary Steel Production will exceed the share of primary Steel Production globally. The results also estimate a global increase in scrap use from 611 Mtonnes in 2015 to 1500 Mtonnes in 2050, with the highest growth being for post-consumer scrap. In 2050, almost 50% of post-consumer scrap is expected to be traded, with the main exporter being China and major importing regions being Africa, India, and other developing Asian countries. The results provide valuable insights on scrap availability and capacity development at the regional level for producers contemplating new investments. Regional availability, quality, and trade patterns of scrap will influence Production route choices, possibly in favor of secondary routes. Also, policy instruments such as carbon taxation may affect investment choices and favor more energy-efficient and less carbon-intensive emerging technologies.
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Worldwide resource eficient Steel Production
2016Co-Authors: Maria Xylia, Semida Silveira, J. Duerinck, F. Meinke-hubenyAbstract:Steel Production processes are energy and emission intensive, but there are variations due to different choices of Production routes, product mixes and processes. This study analyses future Steel Production globally, with focus on the rising availability of Steel scrap, and implications for Steel Production capacity planning. We evaluate the development of Steel demand, using the Steel Optimization Model, which provides a regiondetailed representation of technologies, energy and material flows and trade activities. We link it to the Scrap Availability Assessment Model, which estimates the theoretical Steel scrap availability. The modelling horizon stretches until 2100, with 2050 serving as a benchmark for the analysis. The scenarios require a range of inputs to estimate regional pathways for Steel demand including demographic development and economic growth, and these affect scrap availability. The results show that aggregated crude Steel Production will evolve into an almost balanced split between the primary Production route using iron ore and secondary Production from Steel scrap by 2050 and the share of EAF will exceed by 2060 the Production in BOF globally. The results also show a global increase in scrap use from 611 Mtonnes in 2015 to 1.5 Gtonnes in 2050, with highest growth being for post-consumer scrap. In 2050, almost 50 % of post-consumer scrap is expected to be traded, with the main exporter being China and major importing regions being Africa, India and other developing Asian countries. Surprisingly, the increase in scrap use does not depend much on the introduction of a global carbon price until 2050. The results are important for producers contemplating new investments, since regional availability, quality and trade patterns of scrap will influence Production route choices, possibly in favor of secondary routes. Also policy instruments such as carbon taxation may affect investment choices, and favor more energy eficient and less carbon-intensive emerging technologies.
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The impact of climate targets on future Steel Production – an analysis based on a global energy system model
Journal of Cleaner Production, 2015Co-Authors: Johannes Morfeldt, Wouter Nijs, Semida SilveiraAbstract:This paper addresses how a global climate target may influence iron and Steel Production technology deployment and scrap use. A global energy system model, ETSAP-TIAM, was used and a Scrap Availability Assessment Model (SAAM) was developed to analyse the relation between Steel demand, recycling and the availability of scrap and their implications for Steel Production technology choices. Steel Production using recycled materials has a continuous growth and is likely to be a major route for Steel Production in the long run. However, as the global average of in-use Steel stock increases up to the current average stock of the industrialised economies, global Steel demand keeps growing and stagnates only after 2050. Due to high Steel demand levels and scarcity of scrap, more than 50% of the Steel Production in 2050 will still have to come from virgin materials. Hydrogen-based Steel Production could become a major technology option for Production from virgin materials, particularly in a scenario where Carbon Capture and Storage (CCS) is not available. Imposing a binding climate target will shift the crude Steel price to approximately 500 USD per tonne in the year 2050, provided that CCS is available. However, the increased prices are induced by CO2 prices rather than inflated Production costs. It is concluded that a global climate target is not likely to influence the use of scrap, whereas it shall have an impact on the price of scrap. Finally, the results indicate that energy efficiency improvements of current processes will only be sufficient to meet the climate target in combination with CCS. New innovative techniques with lower climate impact will be vital for mitigating climate change.
