Forecast of steel demand and the availability of depreciated steel scrap in China

Yang, Xuan; Yue, Qiang

doi:10.1016/j.resconrec.2016.02.003

Cited by 82 publications

(34 citation statements)

References 47 publications

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“…Previous studies have estimated LQ scrap availability in China to reach ca. 400 Mtonnes by 2050 (Wang et al 2014;Xuan and Yue 2016). Our projections are within the same range, albeit somewhat lower at ca.…”

Section: Scrap Availability-results From Saamsupporting

confidence: 68%

“…Some of these studies focus on modeling specific countries or regions (Kuramochi (2015) for Japan; Serrenho et al (2016) for the UK; and Wang et al (2014Wang et al ( , 2015, Wubbeke andHeroth 2014, andXuan andYue 2016 for China), while others have a multiregion or global perspective (Morfeldt et al 2012;Oda et al 2013;Pauliuk et al 2013a, b;Yellishetty et al 2011). Other studies investigate current and potential recycling rates that can be achieved to close the production cycle (Graedel et al 2011a, b;Wang et al 2007).…”

Section: Introductionmentioning

confidence: 99%

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Weighing regional scrap availability in global pathways for steel production processes

et al. 2017

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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 postconsumer scrap. In 2050, almost 50% of postconsumer 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 energyefficient and less carbon-intensive emerging technologies.

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Section: Scrap Availability-results From Saamsupporting

confidence: 68%

Section: Introductionmentioning

confidence: 99%

Weighing regional scrap availability in global pathways for steel production processes

et al. 2017

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“…In addition, steel has been consumed in different products and applications over the years with different alloy contents, where the lifetimes of steel have not been product specific. Thereby, it has been difficult to obtain the lifetime of steel data on an annual basis [10][11][12][13][14][15][16][17][18][19][20][21][22][23][24][25][26][27].…”

Section: Introductionmentioning

confidence: 99%

“…In previous DMFMs, the input data are projected over the years based on discrete models [10][11][12][13][14][15][16][17][18][19][20][21][22][23][24][25][26]. In this study, the dynamic behavior between the parameters of the lifetimes of steel, recycling rate, and in-use steel stock per capita enables the possibility to distinguish the range of the variance of the model results on the steel scrap generation.…”

Section: Introductionmentioning

confidence: 99%

The Global Societal Steel Scrap Reserves and Amounts of Losses

et al. 2016

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Abstract:In this study a newly developed method called the Progressing and Backcasting models were used to evaluate the annual resource utilizations of steel scrap in Sweden and globally. The model results show that it is possible to assess the amounts of steel scrap available for steelmaking at a given point in time, based on statistical dynamic material flow models. By a better mapping of the available amounts of steel scrap reserves on a country basis, it is possible to ease the trade of scrap across country boarders. This in turn can optimize the supply of recyclable metals as a raw material used in the industry. The results for Swedish steel consumption show that export bans used to secure the domestic market of steel scrap do damage the internal market due to increased amounts of losses. This suggests that export bans should be lifted to optimize recycling in countries. The model results also show that the global losses of steel are higher than for an industrialized country such as Sweden. Furthermore, the results show that the Backcasting and Progressing models can be used to calculate robust forecasts on the long term availability of steel scrap assets. This information could be used for future structural plans of scrap consuming steelmaking mills and waste management facilities. Hence, it is possible to contribute to a sustainable industrial development and a circular economy.

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“…A abordagem mais comum é a análise econométrica que respeita a demanda de aço, ou ferro, em função do produto interno bruto (PIB) ou PIB per capita -avalia o PIB em função da população (XUAN;YUE, 2016).…”

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Previsão de demanda de minério de ferro da Empresa Vale S.A. no período de 2010 a 2015

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et al. 2016

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ResumoO presente trabalho tem como objetivo realizar a previsão de demanda do minério de ferro da empresa Vale S.A. no período de 2010 a 2015. Para tanto utilizou-se do método de regressão linear múltipla, realizado com auxílio do software IBM SPSS Statistics 23. Obtendo como resultado a equação da previsão de demanda do minério de ferro dadas as variáveis preditivas produção mundial de aço, preço do minério de ferro e movimentação portuária minério de ferro, sendo que apenas o coeficiente atribuído à variável preço do minério de ferro é não significativo ao nível de confiança de 95%. Essa previsão auxilia outras empresas do mesmo ramo a analisarem a previsão de demanda da empresa Vale S.A para assim adaptarem seu desempenho. Palavras-chave: previsão de demanda, minério de ferro, regressão linear múltipla. AbstractThis paper aims to conduct the demand forecasting for iron ore from Vale S.A. in the period of 2010 to 2015. For this purpose, it was used the multiple linear regression method, performed with the help of IBM SPSS Statistics 23 software. The results were found through the use of the equation of iron ore demand forecasting given the predictive variables such as world steel production, the price of iron ore and port iron ore handling, and only the coefficient assigned to the variable price of iron ore is not significant at the Grupo de Pesquisa em Avaliação da qualidade de vida e qualidade de vida no trabalho Ponta Grossa -PR -Brasil v. 01, n. 02, jul./dez. 2016, p. 46-59

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Forecast of steel demand and the availability of depreciated steel scrap in China

Cited by 82 publications

References 47 publications

Weighing regional scrap availability in global pathways for steel production processes

Weighing regional scrap availability in global pathways for steel production processes

The Global Societal Steel Scrap Reserves and Amounts of Losses

Previsão de demanda de minério de ferro da Empresa Vale S.A. no período de 2010 a 2015

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