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Annual steel production in China and share of China steel production in world production between 1995 and 2010 (Mtonnes) (WSA 2011) 

Annual steel production in China and share of China steel production in world production between 1995 and 2010 (Mtonnes) (WSA 2011) 

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We perform a scenario analysis of three strategies for long-term energy savings and carbon dioxide (CO2) emission reductions in iron and steel production in China, using a linear optimization modeling framework industry sector energy efficiency modeling (ISEEM). The modeling includes annual projections for one base scenario representing business-as...

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... becoming the world's largest steel producer in 1996, China experienced rapid growth in annual steel production that reached 626.7 Mtonnes in 2010, an equivalent of 44 % of the world annual steel production shown in Fig. 1. Steel is manufactured mainly by two different types of production processes in China: (1) basic oxygen furnaces (BOFs) and (2) electric arc furnaces (EAFs). BOF production processes make steel from raw materials such as iron ore and coking coal. Coke is produced by heating coking coal in the absence of oxygen at high temperatures in ...
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... indicates that a carbon pricing strategy can be more effective in reducing energy use in the medium-term, while all three strategies result in similar annual energy use reduction in 2050. Figure 10 shows the breakdown of energy sources used in China's iron and steel sector under the BAU and three alternative scenarios. Corresponding to the increasing shares of EAF production, shares of electricity usage in annual energy consumption increase significantly through the planning horizon in all scenarios. ...
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... generation turns out to be economically attractive for the optimization process, as a cheap electricity supply alternative. Figure 11 also shows that corresponding to higher shares of EAF production in the PS scenario, the onsite electricity generation share is higher than that of the BAU scenario, particularly in the long run (e.g., onsite electricity share is 42 and 47 % in both BAU and PS scenarios in 2050). On the other hand, total electricity usage in the CP scenario is similar to that of the BAU scenario, while onsite electricity share diminishes as grid electricity is adopted and offsite coke usage is maximized. ...
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... offsite coke and grid electricity corresponded to lower carbon emission factors. Figure 11 exhibits the increasing trends in the shares of electricity usage for all scenarios overtime. Higher shares of electricity usage are projected in the PS and ER scenarios. ...
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... in the long-term (e.g., 2050), all three scenarios approach to a similar level, reducing the energy intensity from 9.4 GJ/tonne steel in the BAU scenario to approx- imately 8.0 GJ/tonne steel in 2050. Figure 12 shows the decreasing trends in carbon emission intensity for all scenarios that are affected by production switches, technological choices, and the accompanying supply mixes. In the BAU scenario, the emission intensity decreases from 2.3 ton CO 2 /tonne steel in 2010 to 1.3 ton CO 2 /tonne steel in 2050. ...
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... to the BAU scenario, all three scenarios exhibit Table 3 Coking coal usage in the BAU and alternative scenarios (PJ) Coking coal usage (PJ) 2010 2015 2020 2025 2030 2035 2040 2045 2050 BAU 3,173 3,699 4,592 3,893 3,722 3,298 1,992 2, BAU business-as-usual, PS production share, ER emission reduction, CP carbon emission pricing BAU business-as-usual, PS production share, ER emission reduction, CP carbon emission pricing reduction in emission intensity, with the carbon-pricing scenario corresponding to the lowest intensity (e.g., 0.8 ton CO 2 /tonne steel in 2050). Figure 13 shows emission reductions relative to the BAU scenario. The CP scenario exhibits the highest relative emission reduction: 20 % in 2025 and 41 % in 2050. ...
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... contrast, optimization process for modeling the ER scenario results in higher penetration of energy efficiency measures and low emission fuels. Figure 13 shows that CO 2 emissions are reduced by 9 % in year 2015 and 26 % in year 2035 in most effective scenario-the CP scenario, when compared to 2010 CO 2 emission intensity level. China's industry ministry recently made a statement for the firms in the sectors including iron and steel to reduce their 2010 CO 2 emission intensity (i.e., CO 2 produced per unit of output) by 18 % by 2015 ( Haas and Carr 2013). ...
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... the investments in emission reduction may lead to higher system production costs. Figure 14 shows the total system costs for the BAU and alternative scenarios and the associated increases in average unit steel production cost. While implementing the carbon emission pricing strategy in CP scenario is more effective in reducing emission intensity than the other strategies (Fig. 13), this scenario calls for higher annual total system costs for emission reduction (Fig. 14). ...
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... reduction may lead to higher system production costs. Figure 14 shows the total system costs for the BAU and alternative scenarios and the associated increases in average unit steel production cost. While implementing the carbon emission pricing strategy in CP scenario is more effective in reducing emission intensity than the other strategies (Fig. 13), this scenario calls for higher annual total system costs for emission reduction (Fig. 14). Table 5 shows that the increase in unit production cost of emission reduction in the PS scenario is smallest among all three scenarios throughout the planning horizon, while CP scenario exhibits the highest increase in unit production cost of ...
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... costs for the BAU and alternative scenarios and the associated increases in average unit steel production cost. While implementing the carbon emission pricing strategy in CP scenario is more effective in reducing emission intensity than the other strategies (Fig. 13), this scenario calls for higher annual total system costs for emission reduction (Fig. 14). Table 5 shows that the increase in unit production cost of emission reduction in the PS scenario is smallest among all three scenarios throughout the planning horizon, while CP scenario exhibits the highest increase in unit production cost of emission reduction. Under the assumptions used for the modeling, the production switching ...

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... Internationally, China's IS sector still accounts for about a quarter of global industrial emissions (IEA, 2016). Nationally, the IS industry is currently the third largest source of CO 2 emissions (Karali et al., 2016;Wang and Lin, 2016) and is responsible for more than 10% of the total national emissions (Xu and Lin, 2017;. Although the Report on Energy Saving and Low-carbon Development of China's IS Industry 2019 shows that the IS industry has made significant progress in energy and emissions reduction (i.e., in 2018, the average comprehensive energy use per ton of steel production was 555 kgs standard coal of China's key steel enterprises, fulfilling the energy reduction targets in the 13th Five-Year Plan (2016-2020) ahead of schedule), and the energy efficiency of China's IS industry has improved over time (CMIPRI, 2019), there is still a gap between China's energy intensity of the IS industry and the world average (He et al., 2020a). ...
Article
By comprehensively evaluating the potential effectiveness of environmental regulations and technical innovation in facilitating emission reductions, this study highlights the complexity of the relationships — short- and long-term as well as dynamic responses — between carbon dioxide (CO2) emissions, energy efficiency, economic performance, environmental regulation and technological innovation using the vector error correction model (VECM) by incorporating exogenous policy factors based on China IS industrial data during the period 1995–2017. Empirical analysis indicates: (a) the existence of the Environmental Kuznets Curve (EKC) Hypothesis is established given an inverted U-shaped curve of CO2 emissions along with the increase of industrial output value; (b) weak Porter Hypothesis (pH) stands in the short term as innovation can be spurred by environmental regulation, whereas strong pH is supported in both the short and long term when energy efficiency and emission reduction can be achieved under strict regulations;(c) Jevons’ Paradox is confirmed since the emissions increment brought by the massive increase in demand is greater than the emission reduction volume brought by energy efficiency improvement and; (d) Environmental regulation exerts a critical role in emission reduction, especially for the policies with market-based and common-and-control functions implemented since 2006. Corresponding policy implications to facilitate low-carbon transition of the ISI are proposed.
... For example, China's iron and steel sector as identified in Zhang et al. (2014) shows a lower final energy use in base-year 2010, of 16 EJ, compared to Hasanbeigi et al. (2013b) (from China's Statistics Bureau-CSB (NBS 2017)) and ERI (Dai et al., 2013), which is around 17 EJ. The processes of steel production and its specific energy consumption differ between various studies Karali et al., 2016;Ma et al., 2016;, and conflict with statistics for 2010 (ERI and CSB). The studies Zhang et al., 2017) are based on the same energy consumption per unit product (17.72 GJ/t-steel) to explore future energy efficiency improvement. ...
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Industry is the largest electricity consuming sector in the world. China consumes about 25% of global electricity demand, and 69% of this is used in industries. The high electricity demand in industry is responsible for 45% of CO2, 25% of SO2, 34% of NOx and 14% of PM emissions in China. This study aims to fill the knowledge gap on the potential for electricity savings in China’s industries, thereby providing important implications for the potential of reducing emissions in electricity-intensive industrial subsectors in general. Available studies are reviewed and compared to identify electricity-saving potentials. The findings show that China’s industrial energy system is shifting to higher electricity and relatively lower fossil fuel use due to accelerated end-use electrification. China’s industry can reduce electricity use by 7–24% in 2040, compared to baseline levels, and generate emission reductions of 192–1118 Mt-CO2, 385–2241 kt-SO2, 406–2362 kt-NOx and 92–534 kt-PM2.5. The iron & steel subsector has the largest contribution to the industrial electricity savings, followed by non-ferrous metals, chemicals, cement and pulp & paper. Policies that combine environmental targets, demand-side efficiency and supply-side retrofits in the power sector should be adopted. Given the different performance of policies in terms of energy savings and emission reduction, sector- and region-specific policies would be preferred.
... Regression model (Ciacci et al., 2020;Dhar et al., 2020;Dong et al., 2019;Edelenbosch et al., 2017;Elshkaki et al., 2020Elshkaki et al., , 2018Elshkaki et al., , 2017A. 2016;Kesicki and Yanagisawa, 2014;Kuipers et al., 2018;Schipper et al., 2018;Van der Voet et al., 2019;Xuan and Yue, 2016) Specific growth rate model (de Koning et al., 2018;Graus et al., 2011;Hoogwijk et al., 2010;Karali et al., 2016;Kermeli et al., 2015Kermeli et al., , 2014Legarth, 1996;Li and Zhu, 2014;Morfeldt et al., 2015;Northey et al., 2014;Wang et al., 2014;Yellishetty et al., 2010) Logistic consumption model (Akashi et al., 2014(Akashi et al., , 2011Allwood et al., 2010;Gauffin et al., 2017;Giurco and Petrie, 2007;Oda et al., 2013Oda et al., , 2007Van Ruijven et al., 2016;Zeltner et al., 1999;Zeng et al., 2018) Intensity of use model (Halada et al., 2008;Hidalgo et al., 2005;Kapur, 2006Kapur, , 2005Tokimatsu et al., 2017;Vuuren et al., 1999;Watari et al., 2018;Zhou et al., 2013) Computable general equilibrium model (Gielen and Moriguchi, 2002;Hatfield-Dodds et al., 2017;Schandl et al., 2020Schandl et al., , 2016 Constant consumption model (Valero et al., 2018;Yokoi et al., 2018) Linear consumption model (Legarth, 1996;Zeltner et al., 1999) Stock saturation model (Daigo et al., 2014;Hatayama et al., 2012Hatayama et al., , 2010Milford et al., 2013;Morfeldt et al., 2015;Pauliuk et al., 2013aPauliuk et al., , 2012Song et al., 2020;Xylia et al., 2018;Yokoi et al., 2018;Yoshimura and Matsuno, 2018;Yu et al., 2020;Zhang et al., 2015a) Individual stock models for metal-containing technologies (Chen et al., 2014;de Koning et al., 2018;Dong et al., 2019;Gerst, 2009;Schipper et al., 2018;Valero et al., 2018;Watari et al., 2018;Zhang et al., 2015b) ...
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Sustainable metal supply requires well-coordinated strategy and policy packages based on a sound scientific understanding of anticipated long-term demand, supply, and associated environmental implications. Such information , however, is highly fragmented among various case studies. Accordingly, this extensive review explores the projected long-term status of six major metals-iron, aluminum, copper, zinc, lead, and nickel-with around 200 data points for global demand through 2030, 2050 and 2100. Our findings showed that global demand for these major metals is likely to increase continuously over the 21st century, increasing approximately 2-6-fold depending on the metal. Although the extraction and processing required to meet this increase in demand must be environmentally sustainable, the existing extraction and processing scenarios have few explicit linkages to the Earth's carrying capacity. We further found that strategy choices are heavily biased towards end-of-life phase analyses, specifically that of end-of-life recycling. Consequently, a full range of opportunities across entire life cycles is being overlooked, including advances in product design, manufacturing and in-use phases. Importantly, despite the emergence of numerous scenarios, few provide science-based targets for major metal flows, stock, circularity, and efficiency. These knowledge gaps need to be addressed urgently in order to ensure that future research directly supports science-based decision and policy making.
... Reheating furnace is used to reheat materials for thermomechanical processing at various academic laboratories, pilot plants and large scale industry. Therefore, reheating furnaces must be designed and operated to achieve maximum thermal efficiency along with desired production rate, acceptable product quality, environment friendly output and so forth Arink and Hassan, 2017;Charles and Cang, 2010;Hosseini et al., 2019;Karali et al., 2016;Palacios et al., 2019). In a large scale steel industry, reheating furnace is one of the most intensive energy consumer (Demin et al., 2018a,b;Enes et al., 2014;Ghanbari et al., 2012;Neumann et al., 2018;Han et al., 2007). ...
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Steel is the inevitable material for the infrastructure and has the strategic importance for the growth of the country. Iron and steel making industry is one of the most energy-intensive industries, with 5% of the worlds total energy consumption. Therefore, it is required to develop suitable and efficient energy management during various processing in steel plants. Both academic and industrial research is going on worldwide to increase the energy efficiency for reducing the energy cost imparted due to application of reheating furnaces in various metallurgical process. Reheating furnaces are widely used in the Iron and Steel Industry to reheat the semi-finished products like slabs or billets to the rolling temperature at 1250 °C. Reheating furnace is one of the major energy consuming equipment for rolling mills. It is also important to optimize the fuel consumption in this reheating process to avoid any overheating of the steel material which may result in the poor quality of the final product. The aim of this investigation is to conduct an analysis to explore possibilities for the improvement in the energy efficiency of an operating natural gas fired reheating furnace. Some important efficiency improvement measurements were conducted and the fuel efficiency improved by 21% along with the productivity increased by 11%. As a result of these investigations, some energy saving opportunities were ascertained. These measures culminate in the overall projected fiscal savings of INR 264 million/year. Our study not only provides efficient solutions to steel industry for proper energy utilization, but also offers ways for the self-innovation of other academic and laboratory scale research activity.
... [ [67][68][69] Petrochemical sector CO 2 emissions in China's petrochemical sector will keep growing for a relatively longer period, and they may reach a peak between 2030 and 2040. [10,27] [70] ...
... Further accounting for the enhanced technical level and declined carbon intensity in production, CO 2 emissions of China's iron and steel sector could approach a stable level and then begin to decline before 2020 [64][65][66]. To promote a deep reduction of CO 2 emissions and reach an early emission peak, this sector would mainly depend on removing excessive capacities and enhancing production and energy efficiencies in the short run, while relying more heavily on the upgrade of industrial structure, reuse of steel scrap, CO 2 recycling and utilisation technologies, and low-carbon financial incentives over the long run [67][68][69]. Additionally, the petrochemical sector is also a substantial emitter of CO 2 in China. ...
... The improvement of energy efficiency and the phase-out of excess production capacity can notably abate CO 2 emissions in the short term, while the application of alternative materials/fuels and CCS technologies as well as the promotion of waste heat recovery will become essential to pursue more ambitious emission reductions and they will play increasingly important roles over the middle and long terms [60][61][62]. Regarding the iron and steel sector, emission abatement efforts should focus on promoting currently available energy efficient technologies and removing excess capacities in the near future, while implementing production process adjustment, industrial upgrade, steel scrap reuse, and the construction of modern large-scale plants over the long term [67][68][69]. With respect to the petrochemical sector, the improvement of energy efficiency and production technique will primarily determine CO 2 emission reductions in the near term, while for long-term emission reductions the increasing demand for petrochemical products must be regulated and the structure of sectoral energy consumption should be decarbonised consistently. ...
... As an illustration, a combination of the scenario analysis and a system dynamic model was applied to forecasting CO 2 emissions in China by 2020 (Xiao et al., 2016). Scenario analysis also has been applied to scrutinize the long-term solutions for reducing energy utilization and CO 2 emissions of the steel industry in China (Karali et al., 2016). Another study has adopted the methodology in a combination with a linear programming model to prioritize alternative solutions to the problem of global warming (Tokimatsu et al., 2017). ...
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Iran has become one of the most CO 2 emitting countries during the last decades. The country ranks after Japan and Germany in terms of CO 2 emissions. However, from an economic viewpoint, the gross domestic product (GDP) of Iran is lower than the summation of Berlin and Tokyo GDP. Moreover, a large proportion of Iran's revenue comes from the crude oil export; therefore, this level of CO 2 emission cannot be economically driven and is as a result of high energy intensity in this country. This is while the government also has not a clear program in this regard. The Sixth Five-year Development Plan of Iran, in addition, sets a number of ambitious targets mostly regarding the energy intensity, GDP growth, and renewable energies, but does not mention to CO 2 emission issue. Therefore, prospects for an early settlement of the dispute are seemingly dim. Our aim is to predict Iran's CO 2 emissions in 2030 under assumptions of two scenarios, i.e. business as usual (BAU) and the Sixth Development Plan (SDP), using multiple linear regression (MLR) and multiple polynomial regression (MPR) analysis. Findings suggest that Iran most likely will not meet its commitment to the Paris Agreement under the BAU's assumptions; however, full implementation of the ambitiously shaped SDP could have met the target by end 2018.
... After introducing more low-carbon technologies (LT scenario), the potential of CO 2 emission reduction would be intensified, along with cumulative [9] (actual EAF production share). b The changes in the structure of production in 2030 refer to the current world's EAF ratio [40] (future EAF production share). In 2030, as the proportion of EAF increases from 23.16% in the BAU to 30.11% in the PS scenario, CO 2 emissions will decrease by 0.54% and 1.45% in 2020 and 2030, respectively, in the PS compared with the BAU scenario. ...
... For instance, Xiao et al. (2016) forecast the CO 2 intensity in China during 2020 using scenario analysis and a system dynamics model. Karali et al. (2016) analyzed the long-term strategies employed in China to reduce energy use and CO 2 emissions in the steel production process based on scenario analysis and linear optimization modeling. Tokimatsu et al. (2017) investigated the possibility of achieving the target of a global average temperature drop of 2°C by using scenario analysis and a linear programming optimization method. ...
... In terms of the CO 2 emissions and CO 2 intensity forecast in China, previous studies focused on industries such as the textile industry (Lin and Moubarak 2014), iron and steel industry (Karali et al. 2016), civil aviation industry (Zhou et al. 2016), power sector (Hu et al. 2017), building sector (Yang et al. 2017), and industrial sector , and specific regions were also considered, e.g., Beijing city (Feng and Zhang 2012), Jiangsu province (Yue et al. 2013), and Shandong province (Ren et al. 2015). Some studies forecast the total CO 2 emissions and CO 2 intensity in China. ...
Article
Full-text available
Due to the increasingly severe situation regarding adaptation to climate change, global attention has focused on whether China can fulfill its commitment to the Paris Agreement as the largest producer of carbon dioxide (CO2) emissions. In this study, the CO2 emissions and CO2 intensities in China during 2030 were forecast using three scenarios, seven indicators, and a back-propagation neural network. Under the business as usual (BAU), strategic planning (SP), and low carbon (LC) scenarios, the predicted CO2 emissions in China during 2030 are 13,908.00, 11,837.60, and 9102.50 million tonnes, respectively, and the predicted CO2 intensities are 1.8652, 1.7405, and 1.5382 when considering carbon capture, utilization, and storage (CCUS). Furthermore, China cannot fulfill its commitment under the BAU scenario, whereas China will fulfill its commitment on schedule under the SP scenario. Under the LC scenario, China will fulfill its commitment ahead of schedule to reduce the CO2 intensity by 60% in 2025, and it will even reduce the CO2 intensity by 65% in 2030. In addition, if the amounts of CCUS are not considered for measuring the CO2 intensity, China can still fulfill its commitment under the LC scenario, whereas it cannot fulfill its commitment by 2030 under the SP scenario. This study evaluated the fulfillment of China’s commitment in the Paris Agreement, demonstrated that CCUS plays an important role in reducing the CO2 intensity, and provided policy suggestions for the Chinese government regarding the reductions of the CO2 intensity.
... As the largest GHG emitter (Friedlingstein et al., 2014), China committed to lowering the carbon intensity of its economy by 60% to 65% from the 2005 level by 2030 (Karali et al., 2014). To meet this commitment, China needs to develop a multitude of GHG emissions reduction strategies. ...
... Studies have determined China's iron and steel sector emissions using a variety of approaches (Karali et al., 2014;Li et al., 2016;Chen et al., 2014;Hasanbeigi et al., 2013), but these studies either did not model the upstream emissions for iron production and processing, as the objective of the work was to determine the size of the sectorial emissions or to explore mitigation possibilities. Li et al. did include upstream ore mining and processing but aggregated the results for coal and iron ore production (Li et al., 2002;Iosif et al., 2008). ...
Article
Total iron ore demand in China grew to 1.1 billion tonnes in 2013 as a result of ongoing urbanization and massive infrastructure development. Iron ore and steel production are major sources for greenhouse gas (GHG) emissions. Since China has committed to lowering carbon intensity to meet climate change mitigation goals, detailed studies of the energy use and GHG emissions associated with iron ore mining and processing can aid in quantifying the impact and effectiveness of emissions reduction strategies. In this study, a life-cycle model for mining and processing of Chinese iron ores is developed and used to estimate GHG emissions. Results show that the mean life-cycle GHG emissions for Chinese iron ore production are 270 kg CO2e/tonne, with a 90% confidence interval ranging from 210 to 380 kg CO2e/tonne. The two largest contributors to overall GHG emissions are agglomeration (60%) and ore processing (23%). Iron content (ore grade) varies from 15% to 60% and is the largest contributor (40%) to the uncertainty of the results. Iron ore demand growth and the depletion of rich ore deposits will result in increased exploitation of lower grade ores with the concomitant increase in energy consumption and GHG emissions.
... Although a carbon tax market quota allocation has been launched, China has not implemented a carbon tax policy [5,13,27]. In this study, we assume a CO 2 price of 100 yuan/tonne CO 2 for our analysis of EST cost effectiveness [27]. ...
Article
To investigate the potential of energy saving and emissions mitigation during 2015–2050 in China's iron and steel industry (CISI), a comprehensive assessment approach was developed and applied on the basis of the dynamic Material Flow Analysis (MFA) model and the energy consumption and carbon dioxide (CO2) emission model. Four scenarios including the business-as-usual (BAU) scenario, the structure adjustment (STA) scenario, the energy-efficiency improvement (EEI) scenario, and the strengthened policy (STP) scenario have been set to describe future energy saving and carbon mitigation strategies in relation to the development of the iron and steel industry. The modeling results show that China's steel demand will gradually decrease from 789.35 Mt in 2013 to 440.38 Mt in 2043 and will stabilize at around 450 Mt, and the scrap resources are sufficient to support the promotion of the production structure under all four scenarios. The results also indicate that energy consumption and CO2 emissions will gradually decline under the synergistic effect of technology promotion and structure adjustment during the period. In the short term, they will depend more on technology improvement; in the long term, particularly after 2040, promotion of the production structure adjustment will be the main force. The selected 35 energy saving technologies (ESTs) contribute to 3.01 GJ/t and 398.22 kg CO2/t crude steel when the discount rate of 15% is applied.