Japan Steel and Iron Industry - GTAP

ENVIRONMENTAL STRATEGY DESIGN FOR THE JAPANESE IRON

AND STEEL INDUSTRY

-A global perspective-

D.J. Gielen Y. Moriguchi

- DRAFT 21/6/2001 -

CONTENT GLOSSARY 5

1 INTRODUCTION 7

1.1 General industry structure 8

1.2 Environmental problems in the life cycle of iron and steel 10

1.3 Problem and research questions 22

2 JAPANESE GHG EMISSION REDUCTION STRATEGIES 23

2.1 Increase the energy efficiency 23

2.2 Substitute coal by other fuels 28

2.3 Increase the recycling rate 30

2.4 Increase the efficiency of materials use 33

2.5 Initiate JI and CDM projects 33

2.6 Overview 35

3 MODELLING ISSUES 36

3.1 System Boundaries 39

3.2 Emission Accounting 40

3.3 Energy and material flow modelling 42

3.4 Process Characterization 42

3.5 Regional detail 43

3.6 Demand projections 45

3.7 Market distortions 47

3.8 International trade modelling 49

3.9 Scrap management modelling 50

3.10 Software and model operation 51

3.11 Scenario definition and policy simulation 51

4 MODEL RESULTS 53

4.1 Model validation 53

4.2 Global GHG policies 57

4.3 Japanese and European stand-alone policies 65

5 SENSITIVITY ANALYSIS 71

5.1 Interest rate 71

5.2 Higher price elasticity 72

5.3 Lower gas price 73

5.4 Technology mix: including smelting reduction 73

5.5 Technology mix: no CO2 removal 73

5.6 Technology mix: no CO2 free electricity 74

5.7 Market mechanism: monopolies 75

5.8 Introduction of import tariffs 76

5.9 Overview of sensitivities 77

6 CONCLUSIONS 78

6.1 GHG emission reduction potentials 78

6.2 The impact of GHG emission taxation on the iron and steel industry 80

6.3 Consequences for R&D 81

7 REFERENCES 82

ANNEXES ANNEX 1 Overview of energy carriers and materials in the STEAP model ANNEX 2 Overview of processes in the STEAP model ANNEX 3 Transportation costs and trade tariffs ANNEX 4 Investment costs, labour costs, energy and resource costs

relative to Japan ANNEX 5 Assumptions for demand forecast ANNEX 6 Waste collection costs ANNEX 7 Global energy consumption and energy efficiency in the iron

and steel industry ANNEX 8 Energy efficiency in the Japanese iron and steel industry

The Iron and Steel Industry

Gielen and Moriguchi, 2001


GLOSSARY AMEI Autonomous Materials Efficiency Improvement BC Base Case BF Blast Furnace BOF Basic Oxygen Furnace CaCO3 CalciumCarbonate CDM Clean Development Mechanism CH4 Methane CIS Community of Independent States CO2 Carbon dioxide DRC DRI Direct Reduced Iron EAF Electric Arc Furnace GATT General Agreement on Trade and Tariffs GHG Greenhouse gas GJ GigaJoule GWP Global Warming Potential HFC HydroFluoroCarbon HHV Higher Heating Value IISI International Iron and Steel Institute IPCC Intergovernmental Panel on Climate Change JI Joint Implementation LCA Life Cycle Analysis LHV Lower Heating Value MFA Material Flow Analysis MSW Municipal Solid Waste NAFTA North American Free Trade Association NIES National Institute of Environmental Studies N2O Nitrous Oxide OHF Open Hearth Furnace PCI Powder Coal Injection PFC PerFluoroCarbon PVC PolyVinylChloride RDF Refuse Derived Fuel SF6 SulphurHexaFluoride STEAP Steel Environmental Assessment Program UNFCCC United Nations Framework Convention on Climate Change WTO World Trade Organization



1 Introduction This study is part if a two-year research programme at the National Institute of Environmental Studies in Tsukuba during the period 2000-2002, focusing on environmental energy and materials policies1. In an earlier study, Japanese petrochemicals have been analysed (Gielen and Moriguchi 2001). This study focuses on the Japanese iron and steel industry. Global steel exports increased from 22.6 to 38.1% of the total steel production during the period 1975-1997 (IISI 2001). It is likely that trade will increase further in future years. As a consequence a study concerning the future of the Japanese steel industry must have a global perspective. The study is based on a techno-economic life cycle perspective. The environmental impact depends on production volume and the environmental impact per unit of production (the environmental efficiency). The production volume depends on demand trends and the competitiveness of the Japanese industry and government policies that determine the market structure. The environmental efficiency depends on the sector structure and the technology that is applied. Only a limited number of key factors are considered explicitly in this study:

• Demand trends; • The emergence of new technology; • Emerging environmental policies; • Future natural resource availability and resource prices; • Trade liberalisation and changing market structure.

The reason for the selection of these factors will be elaborated briefly. Other factors such as legislation, labour policies etc. may also be of significance, but are not considered in this study in order to keep a clear focus. A ‘ceteris paribus’ condition applies to all factors that are not considered in more detail. Technology is a key driving force in steel making. Research in the iron and steel industry focuses on more simple and small-scale primary steel production2 routes. A number of technological breakthroughs in steel production have been forecast during the last two decades (Zervas 1996) but so far none of them has 1 The stay of Dolf Gielen at NIES is enabled by a fellowship of the Science and Technology Agency. This fellowship is gratefully acknowledged. 2 Primary steel production refers to the production of steel from primary (natural) resources, c.q. iron ore. Steel production from scrap is called secondary production.



captured a significant market share. However this may change in the future. Changing technology can have a significant impact on the environment, to the good or to the worse. The iron and steel industry used to be an important source of air pollution and waste. However the steel industry has improved its environmental performance significantly during the last 50 years, see e.g. (Philipp and Theobald 1993). The emission of carbon dioxide (CO2) is probably the most important remaining environmental problem (see below). Regarding the sustainability of natural resource consumption, coal and iron ore are abundant resources. However the availability of steel scrap and comparatively clean energy resources such as natural gas and renewables can pose an important competitive advantage in the future. The availability of these resources is region specific. Traditionally the iron and steel industry is considered a key sector from a national security point of view. Moreover the sector employs many people. This has resulted in large-scale government intervention favouring the steel industry, such as subsidies and import barriers. This intervention is apparent in many countries, see e.g. (International Trade Administration, 2000). Because the strategic relevance of the steel industry has decreased in time, government intervention is decreasing and the market structure is changing towards a globally free market. This trend will affect the future industry location choice. The impact of changing market conditions will be considered in more detail in this study. In this chapter the general industry characteristics will be discussed in more detail. Next in chapter 2, CO2 emission reduction strategies for the Japanese iron and steel industry are detailed. In chapter 3, the STEAP model is discussed in detail. This model serves as a comprehensive framework for the analysis of the interact ion of factors mentioned above. In chapter 4, the results from the model are discussed. The sensitivity of the results for key variables is elaborated in chapter 5. This is followed by the conclusions in chapter 6. 1.1 General industry structure The steel industry produces steel products. Currently two main process routes exist for crude steel production: the blast furnace (BF) – Basic Oxygen Furnace (BOF) route and the Electric Arc Furnace (EAF). The first route is based on the use of coal and iron ore. The second route is based on the use of scrap and electricity. Global steel production amounted to 786 Mt3 crude steel (705 Mt

3 In order to make this quantity more tangible the annual global steel production amounts to a single block of 1 km2 approximately 100 metres high. In comparison to steel, the global plastics production amounts to 150 Mt per year and the global production of wood products amounts to 750 Mt oven dry matter.



finished steel products) in 1999 (IISI 2001). 59.8% of the production is based on BF-BOF technology, 33.4% is based on EAF technology. The remainder (6.8%) is based on other, outdated, technologies. The use of EAF is limited by scrap availability. The fraction EAF is increasing in time because the scrap quantity is increasing more quickly than the total steel production volume. In this study, cast iron production is included with the iron and steel industry because the production of cast iron requires iron or scrap feedstock material. Cast iron production data are scare, estimates suggest it amounts approximately to 70Mt per year (Farla and Blok 2001). Global steel production is concentrated in industrialised countries. North East Asia (Japan, South Korea, and Taiwan), The European Union (EU-15) and North America (NAFTA) together account for 53% of the global steel production. While steel production has been stagnating or even declining in Japan, Western Europe and the United States during the last decades, it has been increasing rapidly in developing countries. Especially the Chinese steel production is growing by more than 10% per year. China is nowadays the largest steel producing country in the world (124 Mt/yr in 1999), followed by the USA and Japan (IISI 2001). Rapid changes are taking place on a company level. Especially the scale of primary steel producing companies is increasing rapidly. Nippon Steel was in the 70’s the first company with a production capacity in excess of 20 Mt per year. Other companies such as Posco, Arbed, Krupp-Thyssen, Corus and Bao steel are following suit, based on mergers or capacity expansions. Especially in the last 10 years, a new class of large-scale steel producers is emerging. Amongst others this trend is driven by economies of scale. One modern blast furnace produces approximately 3.5 Mt iron per year, one modern production site contains between 2 and 7 blast furnaces. Each company has several production sites, resulting in a production capacity in excess of 20 Mt. In Japan there are five primary steel producers (Nippon steel, NKK, Kawasaki steel, Kobe steel and Sumitomo, see annex 8). The announced merger of NKK and Sumitomo will result in another steel company with a production capacity in excess of 20 Mt per year. In contrast to primary steel production, EAF based secondary steel production has a much smaller scale, usually less than 0.5 Mt annual capacity. This smaller size of operations is caused by less pronounced economies of scale. However this industry is subject to economies of scale too, resulting in a tendency toward larger scale operations. For example the Nucor EAF steel plant in Berkeley (USA, SC) has recently been expanded to 3 Mt per year (Fonner 2001). However the scale of an average EAF steel production site is less than one tenth of the scale of a blast furnace production site. Regional scrap availability is the major bottleneck for further capacity increase.



1.2 Environmental problems in the life cycle of iron and steel Only the Japanese situation will be discussed in more detail. The situation abroad, especially in developing countries, may be different. Despite the huge quantities of resources that are consumed, resource scarcity is less of a problem. Both coal and iron ore resources will last for several hundred years. Regarding coal one must add that the scarcity of high quality coking coal resources may increase more rapidly. However new steel production processes have been developed that can use low quality steam coal (see chapter 2 and 3). The SO2 and NOx emissions from the iron and steel industry are of secondary importance. Because of the reducing environment in the blast furnace, this process is no source of NOx. The bulk of the sulphur from the coal ends up in the slag. Coke ovens used to be a source of important organic pollution. However modern coke ovens with closed water systems are no major emission source anymore. Japanese industrial dioxin emissions are dealt with by METI, the Ministry of Economy, Trade and Industry. An agreement has been reached that emissions in the steel industry will be reduced. The emissions in steel sintering will be reduced from 101.3 g-TEQ (2,3,7,8- tetrachlorodibenzo-p-dioxin equivalents) in 1999 to 93.2 g-TEQ in 2002. The emissions from EAFs will be reduced from 141.5 g-TEQ in 1999 to 130.3 g-TEQ in 2002 (METI 2000). These figures can be compared to a total Japanese dioxin emission of 3981 g-TEQ in 1998. The emissions from the steel industry represent approximately 6% of the total Japanese dioxin emissions. This fraction may increase because emissions from waste incinerators, the main dioxin source, will be reduced significantly. Steel scrap is an important resource and is recycled completely. Primary steelmaking results in blast furnace slag and steel slag. Both residues can be used in the building and construction industry, and pose no major environmental problem. Dust discharged from EAFs contains 20-30% zinc. EAF steel producers generate about 15 kg of dust for every ton of steel they produce. In Japan the annual volume of EAF dust amount to 0.5 Mt per year. Zinc is recovered from only 65% of the dust because of the high cost of zinc removal (1997 figures) (Furukawa 1997). The remaining 35% ends up in landfills (about 45 kt of zinc is landfilled). However Kawasaki steel has developed a new smelting reduction process that can reduce processing cost by 40%, and recover 99% of the zinc metal. Greenhouse gas (GHG) emission reduction is a key issue for environmental policies in the first half of the 21st century. CO2 is the most important greenhouse gas, representing 70-75% of the total annual GHG emission. The countries of the European Union, the United States and Japan agreed at the UNFCCC (United



Nations Framework Convention on Climate Change) conference in Kyoto in December 1997 to reduce their emissions by 8, 7, and 6% in the period 2008-2012, respectively, compared to their emissions for a reference year4. The US government has announced it is reconsidering its participation in the Kyoto agreements. In case the US does not participate the protocol becomes in practice irrelevant. However the GHG issue does not disappear and even further emission reductions are likely on the long run. The bulk of the CO2 emissions (80%) is related to the use of fossil energy carriers. As a consequence energy intensive materials such as steel can be affected significantly by GHG emission reduction policies. The Kyoto agreement covers six categories of greenhouse gases: carbon dioxide (CO2), methane (CH4), nitrous oxide (N2O), perfluorocarbons (PFCs), hydrofluorocarbons (HFCs) and sulphurhexafluoride (SF6). These emissions are aggregated on the basis of their global warming potential (GWP) for a time horizon of 100 years. Approximately 4% of the global CO2 emissions can be attributed to the production of iron and steel (Yoshiki-Gravelsins et al. 1993). The iron and steel industry is the single most important industrial source of CO2 emissions. The emissions of non-CO2 greenhouse gases by this industry (e.g. methane or nitrous oxide) are negligible and will not be discussed in more detail5. The bulk of the CO2 emissions in the iron and steel industry is related to the use of fossil fuels (especially coal). The fossil fuel consumption depends to a large extent on the crude steel production technology. Similar to the situation in most other major steel producing countries, the Japanese iron and steel industry is based on two production routes. The Blast Furnace (BF) is used to reduce iron ore into liquid iron, which is subsequently converted into steel in a Basic Oxygen Furnace (BOF). Electric Arc Furnaces (EAFs) are used to produce steel from scrap. In 1999 69.5% of the Japanese was produced in BOFs, 30.5% in EAFs. Scrap based EAF steel production requires considerably less energy than the BF/BOF route, mainly because the chemical energy for the ore reduction can be

4 The reference year is 1990 for CO2, CH4 and N2O, 1995 for HFCs, PFCs and SF6 5 CH4 emissions due to deep coal mining can contribute 5-15 kg CO2 equivalents per GJ coal, but will not be discussed in more detail. In case these emissions are allocated to the final coal consumers, the emissions for steel increase by 5-15%. However technologies are available to capture the methane and use it for energy purposes. Moreover these emissions do not occur in case of surface mining.



saved6. The preparation of coke, ore pellets or sinter for the BF requires also considerable amounts of energy. Table 1.1 provides an overview of energy consumption for different processes in the iron and steel industry. The second column (IISI 1982) relates to the reference plant from a study by the International Iron and Steel Institute IISI that incorporates many energy efficient technical facilities and operating practices, which have been proven commercially viable and which have been widely implemented in the early 1980s. The second and third weighting scheme related to reference plants in the mid-1990s. The ‘EcoTech’ reference process that was defined by IISI includes all financially viable and proven energy-saving technologies and therefore represents state of the art steel making. The ‘All Tech’ reference process includes all proven energy saving technologies regardless of profitability and therefore represents a more severe standard for energy efficiency. All units are expressed per ton of cured steel. The figures indicate a decline from 15.58 to 13.96 GJ per ton average finished steel product in case all cost-effective technologies are applied (a 10% decline in 13 years), and a potential reduction to 12.84 GJ in case all technologies are applied that are not yet cost-effective. The blast furnace is the main energy consuming operation, but energy consumption in finishing is important, too. A tendency exists toward more advanced steel products (from hot rolled to cold rolled and galvanized) that increases the energy consumption per ton of product. However the functionality of this steel is higher (less steel required per unit of product), which results in considerable energy savings. A life cycle assessment if required for proper assessment of such energy saving options (Gielen 1999).

6 The minimum energy requirement for reducing Hematite (Fe2O3, the main iron ore type) at room temperature is 7400 MJ/t iron. The minimum amount to carbon that is needed for the chemical reduction is 320 kg if CO is formed and would be 160 kg if CO2 were formed (Birat et al. 1999)



Table 1.1: Representative process energy consumption, expressed in primary energy equivalents (Farla and Blok 2001)(efficiency of electricity production = 37% (1982) and 39% (1995), respectively, for purchased electricity). Excludes coke oven. IISI

1982

IISIEco-Tech

1995

IISIAll-Tech

1995Sinter 1.54 1.12Pellets 1.26 1.26Pig Iron 14.43 12.33 12.23BOF steel7 0.17 -0.16 -0.16EAF steel, scrap based7

5.66 5.40 4.41

Hot rolled products

2.97 2.16 1.82

Cold rolled products8

6.33 4.08 3.35

Tinmill products9 6.46 5.61Galvanized products10

6.10 4.93

Total weighted average11

15.58 13.96 12.84

Table 1.2 shows an analysis of the energy consumption in the Japanese iron and steel industry. Note that the original statistical data are in higher heating values (HHV). All energy data and emission coefficients in this paper have been expressed in lower heating values in order to allow comparison with international energy data that are expressed in lower heating values. The CO2 emission from fossil fuel consumption can be calculated from the energy consumption data and the CO2 emission coefficients per unit of energy, see table 1.3. In Japan, national electricity production ranges from nuclear or hydropower plants with zero CO2

emissions to coal fired power plants with 0.25 t CO2 per GJ electricity. On average, electricity is produced with a specific CO2 emission of approximately 0.096 t CO2 per GJ electricity (based on IEA 1999).

7 Includes continuous casting 8 Cold rolling + hot rolling 9 Cold rolling + tinmill 10 Cold rolling + galvanizing. Assumption 50% hot-dip galvanizing and 50% electro-galvanizing 11 See IISI (1998) for the production shares in the basket





Table 1.2: Energy balance of the Japanese iron and steel industry, 1999 (MITI 2000)

[PJLHV/yr] Sintering Pelletising BF Ferroalloys BOF EAF Forging Casting Rolling &

pipe

Power generation

boiler & cogeneration

Other iron& steel

sectorsCoke

manufacturingOther

sectors Total Kerosene 0.00 0.00 0.00 0.06 0.01 1.98 0.93 0.50 3.17 0.53 1.53 0.00 0.67 9.39 Gas oils 0.00 0.00 0.00 0.02 0.05 0.00 0.01 0.00

0.52 0.00 0.45 0.00 0.22 1.28 Fuel oils 0.14 0.08 0.12 2.66 0.35 2.07 2.87 0.73 29.48 20.64 3.69 0.00 1.37 64.20 Hydrocarbon oil

0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 4.23 0.00 4.23

LPG 0.03 0.00 0.83 0.04 2.74 0.15 0.40 0.21 8.05 3.51 3.62 0.00 1.77 21.34 Petroleum coke 0.00 0.00 17.40 0.17 0.00 0.20 0.00 0.00 0.00 0.00 0.00 15.35 0.01 33.14 Coking coal 0.00 0.00 75.32 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1092.85 0.00 1168.18 Other coal 28.90 1.81 203.91 12.92 13.81 0.03 0.00 0.00 0.00 69.88 0.03 0.00 0.00 331.29 Coal coke 110.98 1.16 858.87 9.88 3.46 3.88 0.00 0.00 0.00 0.00 6.90 -750.58 0.34 244.89 Tar 0.09 0.00 2.36 0.00 0.00 0.00 0.00 0.00 0.00 0.69 0.10 -23.78 0.01 -20.53 Coke oven gas 2.40 0.86 24.81 0.07 5.75 0.49 0.55 0.04 65.75 29.55 5.88 -162.57 1.23 -25.19 Blast furnace gas 0.17 0.00 -279.28 0.00 0.03 0.00 0.01 0.00 2.97 97.42 1.33 47.01 0.06 -130.30 Converter gas 0.23 0.00 9.60 0.05 -69.90 0.02 0.07 0.00 11.58 19.02 0.31 1.95 0.72 -26.35 Electric furnaces gas 0.00 0.00 0.00 0.05 0.00 -0.81 0.00 0.00 0.00 0.00 0.00 0.00 0.34 -0.42 LNG 0.03 0.00 0.11 0.00 0.04 0.50 0.51 0.00 14.44 2.05 2.41 0.03 0.01 20.13 Town gas 0.03 0.00 0.15 0.00 0.30 0.67 0.84 0.24 15.64 5.77 6.06 0.03 2.20 31.93 Oxygen 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Electric power 11.70 1.04 6.77 9.39 13.28 49.22 1.89 1.38 64.91 -66.17 45.71 3.94 9.42 152.49 Steam 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Total 154.70 4.94 920.98 35.32 -30.08 58.41 8.09 3.10 216.51 182.88 78.01 228.46 18.37 1879.69



The use of fossil fuels is not the only source of CO2. CO2 is also emitted during iron production because of the decarbonisation of limestone (CaCO3). Birat et al. (1999) indicate a total of 0.135 t CO2 per ton primary crude steel for limestone dissociation. The Japanese iron and steel industry consumed 12.34 Mt limestone, 4.30 Mt quicklime, 0.34 Mt baked dolomite and 1.17 Mt dolomite in 1999 (MITI 2000). Assuming that these carbonaceous components are completely dissociated. The emission amount to 0.44 t CO2 per ton limestone and dolomite, and 0.75 t CO2 per ton quicklime and baked dolomite (Gielen 1997). This is a source of 9.4 Mt CO2 (0.144 t CO2 per ton primary crude steel, close to the literature figure). The iron and steel industry produces significant amounts of energy by-products: coke oven gas, blast furnace gas and BOF-gas. If these gaseous energy carriers are sold, their carbon content can either be allocated to the user of the gas (generally a power producer) or to the steel industry. In the current practice the carbon content of residual gas deliveries to electricity producers is allocated to the electricity producers, not to the steel industry. However the CO2 emission coefficient for blast furnace gas is relatively low (see table 1.3). If all the carbon monoxide in this gas would be counted as energy carrier, its CO2 emission coefficient would increase to 0.2 t CO2/GJ (twice as high). This approach would decrease statistical emissions in the iron and steel industry. However the iron and steel industry as a whole is a net buyer of electricity and the only party that can influence blast furnace gas production, blast furnace gas use allocation to the iron and steel industry will pose such an incentive. The difference (0 allocation to iron & steel vs. 0.2 t CO2/GJ) amounts to 25 Mt CO2. Coke production and cast iron production can be considered part of the iron and steel industry, but two independent coke producers and iron casting companies are not accounted for in the Japanese the iron and steel industry CO2 emissions. The coke ovens of Mitsubishi and Mitsui represent 12% of the Japanese coking capacity (Japan Institute of Energy, 2000). Also blast furnace slag is produced as a by-product. This slag can be used as a cement substitute. As a consequence the emissions in cement production are reduced. Blast furnace slag production amounts approximately to 250 kg per ton of iron. It consists of dissociated limestone and coal ash. Given a blast furnace pig iron production of 73.9 Mt, blast furnace slag production amounts to 18.5 Mt. Production of Portland cement results in 0.8 ton CO2 per ton cement. Assuming substitution on a mass par basis, the savings amount to 14.8 Mt CO2. Finally Japan is a net exporter of steel scrap (about 4 Mt/yr) and steel products (net export about 20 Mt/yr). These emissions could be allocated to the importers of these commodities. In total these credits may amount to 40-50 Mt CO2 (assuming high quality primary steel is exported).



Given these system boundary problems, the CO2 emission in the Japanese iron and steel industry ranges from 115 Mt (no inorganic emissions, no emissions from electricity production, trade correction) to 210 Mt (inorganic emissions, coal based emissions in electricity production, carbon content of gas by-products allocated to iron and steel), see table 1.4. Because the steel industry uses coal as its main energy source, its relevance is higher from a CO2 point of view than from an energy point of view. Table 1.3: Energy content and specific CO2 emissions for energy carriers (Environment Agency 1992, NTK 1993, IPCC 1997, IEE 2000, IEA 2000) Energy carrier Unit HHV

Japan[GJ/unit]

LHV12 Japan

[GJ/unit] [kg CO2/GJ LHV]Coal products Coking coal [t] 31.7 30.2 0.094 Steam coal, briquet [t] 27.1 25.8 0.098 Cokes [t] 30.0 29.8 0.111 Blast furnace gas [1000

m3]3.0 3.0 0.098

Coke oven gas [1000 m3]

19.7 17.8 0.059

Converter gas/EAF gas

[1000 m3]

9.4 9.4

Tar [t] 44.0 0.076Oil products Kerosene [t] 45.9 42.8 0.073 Gas oil [t] 45.5 42.6 0.074 Fuel oil [t] 43.4-45.0 41.3-42.3 0.076 Hydrocarbon oil [t] 45.0 42.5 0.076 LPG [t] 50.0 45.0 0.067 Petroleum coke [t] 36.1 35.2 0.094Gas LNG [t] 54.7 49.4 0.057 Town gas [1000

m3]41.7 37.7 0.057

Electricity (external)

0.096

12 LHV Lower Heating Value can be calculated from HHV higher heating value (for As Received figures) based on the formula: LHV = HHV – 0.212H-0.0245M-0.0008O, where M is % moisture, H is % Hydrogen and O is % Oxygen. Typically M = 10%, H=4%, O =5% (25% Volatile Matter CH2). For typical bituminous coal the difference between LHV and HHV amounts to 1.09 GJ/t (World Coal Institute, 2000)





Table 1.4: CO2 emissions in the Japanese iron and steel industry, 1999

[Mt CO2/yr] Sintering Pelletising BFFerro alloys BOF EAF Forging Casting

Rolling & pipe

Power generation

boiler & cogeneration

Other iron& steel sectors

Coke manufacturi

ngOther

sectors TotalKerosene 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.0 0.2 0.0 0.1 0.0 0.0 0.7Gas oils 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1Fuel oils 0.0 0.0 0.0 0.2 0.0 0.2 0.2 0.1 2.2 1.6 0.3 0.0 0.1 4.9Hydrocarbon oil

0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.3 0.0 0.3

LPG 0.0

0.0 0.1 0.0 0.2 0.0 0.0 0.0 0.5 0.2 0.2 0.0 0.1 1.4Petroleum coke 0.0 0.0 1.6 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.4 0.0 3.1Coking coal 0.0 0.0 7.1 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 102.7 0.0 109.8Other coal 2.8 0.2 20.0 1.3 1.4 0.0 0.0 0.0 0.0 6.8 0.0 0.0 0.0 32.5Coal coke 12.3 0.1 95.3 1.1 0.4 0.4 0.0 0.0 0.0 0.0 0.8 -83.3 0.0 27.2Tar 0.0 0.0 0.2 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.0 -1.8 0.0 -1.6Coke oven gas 0.1 0.1 1.5 0.0 0.3 0.0 0.0 0.0 3.9 1.7 0.3 -9.6 0.1 -1.5Blast furnace gas 0.0 0.0 -27.4 0.0 0.0 0.0 0.0 0.0 0.3 9.5 0.1 4.6 0.0 -12.8Converter gas 0.0 0.0 0.9 0.0 -6.6 0.0 0.0 0.0 1.1 1.8 0.0 0.2 0.1 -2.5Electric furnaces gas

0.0 0.0 0.0 0.0 0.0 -0.1 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

LNG 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.8 0.1 0.1 0.0 0.0 1.1Town gas 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.9 0.3 0.3 0.0 0.1 1.8Oxygen 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0Electric power 1.1 0.1 0.7 0.9 1.3 4.7 0.2 0.1 6.2 -6.4 4.4 0.4 0.9 14.6Inorganic CO2 6.5 0.0 0.1 0.0 2.7 0.1 0.0 0.0 0.0 0.0 0.0 0.0 0.0 9.4Total 23.0 0.5 100.0 3.5 -0.3 5.6 0.6 0.3 16.3 15.9 6.8 15.0 1.5 188.7


The steel industry represents between 9% and 16% of the total Japanese emission, depending on the allocation scheme. This contribution is well above the global average of 4%. The difference is related to the strong Japanese export position for steel and steel products. This affects the emissions two-fold: production is much higher than consumption, and scrap availability is limited, resulting in a low penetration of EAF steel production. For example in the USA, EAF represents 46.2% of the total crude steel production, in Western Europe (EU-15) 38.1%, in Japan only 30.5% (1999 figures). 1.3 Problem and research questions Many studies have analysed new steel production technologies and emission reduction options within the basic metals industry (e.g. (Eketrop 1989, Elliott 1991, Gruebler 1993, Daniels and Moll 1997, Birat et al. 1999). In this study, the emission reduction is analysed within the framework of the changing (inter-) national energy and materials system configuration. This includes the whole environmental life cycle ‘from cradle to grave’. Not only metals production, but also metals consumption is considered in the optimisation. The effects of materials substitution, changing consumer preferences, changing energy prices, and changing environmental policies are integrated into the analysis. The approach that is applied in this study combines a number of topics into an integrated analysis:

• System dynamics are considered, such as the standing capital equipment stock from previous years, the changing scrap availability, and changing energy prices;

• Changing technology characteristics is considered; • The interaction of emission abatement options in the materials life cycle is

considered; • Changing international market conditions are considered.

Similar studies based on the MARKAL model have been done for the Netherlands (Gielen and Dril 1997a), for Western Europe (Gielen and Dril 1997b, Gielen and Dril 1999) and for South Korea (Hong, unpublished data). In this study the global perspective including changes in international trade represents the main new element. The following questions will be studied:

- What is the emission reduction potential in the World and in Japan? - What are the consequences of GHG policies for the location choice of the

iron and steel industry? - Which policy strategies can reduce emissions in Japan significantly while

maintaining international competitiveness? - What actions are required by industry, government and the scientific

community in order to achieve a meaningful emission reduction?


2 Japanese GHG emission reduction strategies A number of technical options exist to reduce CO2 emissions in the Japanese iron and steel industry (Gielen 1999):

• Increase the energy efficiency; • Substitute coal by other fuels; • Increase the recycling rate; • CO2 removal and disposal in the sea; • Increase the efficiency of materials use; • Initiate JI (Joint implementation) and CDM (Clean Development

Mechanism) projects. These strategies will be discussed individually. 2.1 Increase the energy efficiency The energy efficiency of the Japanese steel producers is high, see e.g. (Ishikawa et al. 1994, Worrell et al. 1999, Farla and Blok 2001). This high efficiency can be explained by the comparatively high energy prices in Japan and the relative recent industry start-up (in comparison to European and US producers). A number of options exist to increase the energy efficiency:

• Increase the coal injection rate in blast furnaces (as a substitute for coke); • Increase the efficiency of energy recovery from blast furnace gas; • Introduce thin slab casting and near net shape casting; • Introduce direct smelting technologies, avoiding coking and possibly also

avoiding ore preparation. Increased coal injection Japan consumed 10.4 Mt pulverised coal for blast furnace injection in 1999 (World coal institute 2000). This figure can be compared to a total coking coal consumption of 61.9 Mt in the same year. The current Japanese coal injection rate ranges from 67 to 207 kg/t pig iron (see Annex 8). Assuming a maximum of 200 kg/t, coke substitution on a thermal par basis and energy use for coke production of 8 GJ/t (based on Daniels and Moll 1997), the potential for CO2 emission reduction amounts to 3.8 Mt per year in case all blast furnaces apply 200 kg coal injection. This is a conservative estimate. In case coke consumption can be reduced to 200 kg/t pig iron (coal injection rate 300 kg/t) (Edström and Scheele 1993), the potential increases to 8.9 Mt CO2 per year. In the Japanese case, the coke ovens have not yet reached the end of their technical life span. This situation is different from the European case. This

23


difference explains the lower coal injection rates in Japan. Rebuilding coke ovens is costly, a major consideration in Europe to maximize coal injection. However the only driving force in Japan is the lower price of steam coal (for coal injection) in comparison to coking coal. However nowadays it is possible to use steam coal for cokes production. As a consequence the financial incentives for coal injection are reduced (personal communication N. Takamatsu, Nippon Steel). Full oxygen blast furnaces may allow even further reductions of the coke rate to 174 kg/t pig iron. Superheating of the hot blast using a plasma arc may reduce coke rates to approximately 105 kg/t pig iron (Daniels and Moll 1997). The coal injection increases accordingly. However the additional energy use for oxygen production and preheating will offset the CO2 benefits of coal injection. As a consequence, these options have not been analysed in more detail. Increase the efficiency of energy recovery The quantity of blast-furnace gas amounts to 4.9 GJ/t of pig iron (Daniels and Moll 1997). The quality of this gas is low. The energy content is about 4 MJ/m3, vs. 35 MJ/m3 for natural gas (Gielen and Dril 1997). This poses a problem for the efficient use of this gas. The quality was too low for use in electricity production using conventional gas turbines. As a consequence it used to be mixed with natural gas or it was used in special gas engines with comparatively low efficiencies of 25-30%. In recent years, new gas turbines have been developed that are able to use low quality gas such as blast furnace gas. Such gas turbines are for example used by Baoshan, the largest Chinese steel producer (personal communication energy manager Baoshan). These turbines have been developed in cooperation with ABB, and the total electric efficiency of the gas turbine is reportedly 40%. Assuming that such turbines are not yet applied by Japanese steel makers and assuming that the gain in energy efficiency is 10% and the reference electricity production has an CO2 intensity of 0.094 kg/GJel, the potential for emission reduction amounts to 3.2 Mt CO2. Introduce thin slab casting and near net shape casting Steel is traditionally cast into slabs and billets of 15-20 cm thickness that are cooled down to room temperature and reheated before they are rolled into hot rolled sheet of 0.5-3 cm thickness. More advanced is the direct connection between the steel caster and the hot rolling mill, saving part of the reheating energy. This technology is nowadays widely applied. However rolling and reheating require still considerable amounts of energy (see table 1.1). The more the size of the cast steel resembles the final product, the less energy is required for finishing. Nowadays Japanese producers apply direct rolling to 12-80 mm thickness (“thin slab casting”). Casting products with a reduced thickness (1-10 mm) will reduce the energy requirements for steel rolling even further (“Near Net Shape casting”). Such technologies are currently being developed, but important technical problems remain regarding the steel quality. Purity and surface quality are the main issues for thin sheet casting, especially for low alloy, low carbon steel qualities (C<0.1%) (Wolf 1996). Nippon Steel recently built a commercial

24


strip casting plant in Hikari (for alloyed steel; 60 t capacity; 770-1330 mm width). In case the quality problems for low alloy, low carbon steel are solved reheating, hot rolling and cold rolling can be avoided for car body materials etc. and average savings may amount to 1 GJ/t. In case this figure can be applied to half of all steel products, savings amount to 4.5 Mt CO2. Smelting reduction and direct reduction Corex is a proven technology for producing pig iron from pellets and coal. The use of coal instead of coke results in an energy saving of 3 GJ coal/t steel. However the net energy balance depends on the efficiency of by-product use (steam and off-gas). In case of high efficiency of by-product use, the energy balance is better than BF. In case of low efficiency, the balance is worse. The energy balance of Corex is shown in table 2.1 (Corex C-1000). 2.25 Mt Corex pig iron capacity is currently in operation worldwide (VAI 2001). This is equivalent to 5% of the global pig iron production capacity. Corex C-3000 (an advanced process design compared to C-1000) requires a coal input of 28.0 GJ/t pig iron and produces 13.3 GJ/t gas by-product (note the difference with the C-1000 energy data in table 2.1). Moreover the process consumes 0.74 ton of oxygen per ton of pig iron (VAI 2001). Table 2.1: Energy and mass balance for Corex C-1000 (Pühringer et al. 1991) Input [GJ/t iron] Output [GJ/t iron]Coal 950 kg 29.0 Hot metal 1000 kg 9.9Ore 1500 kg Slag 300 kg 0.4Oxygen 714 kg Gas 10.9Lime 110 kg Steam 6.4 Losses 1.4Total 29.0 29.0 Lumps of iron ore, pellets and sinter are reduced in a reduction shaft that is fed with reducing gases from the smelting vessel. In the process, a mixture of FeO and Fe2O3 is generated. The coal is added to the smelting vessel, where the iron is completely reduced. The iron quality is similar to the iron quality from blast furnaces. Oxygen is used for the gasification, together with air in order to keep the off-gas temperatures below 1750°C in order to prevent excessive wear of equipment. The process can use bituminous coal in pieces of 0-50 mm. Off-gases are pure and can be used for power generation. The main advantage compared to the blast furnace is that coke production can be avoided and a lower coal quality can be used13. An interesting combination is Corex and direct reduction based on Corex off-gases. Such a plant is in operation in Saldanha bay in South Africa since 13 One must add that Japanese steelmakers have made considerable progress in using steamcoal as a substitute for coking coal in blast furnaces and coking ovens. As a consequence the advantage of Corex is decreasing (personal communication N. Takamatsu, Nippon steel)

25


December 1998 (VAI 2001b). The Corex plant produces 650 kt pig iron per year, the DR plant produces 800 kt DRI (Direct Reduced Iron, iron ore reduced to iron in its solid state). This indicates the high volume of energy by-products of Corex and other smelting reduction processes, especially if low coal grades are used (Edström and Scheele, 1993). The average energy use (Corex + DRI) amounts to 10.3 GJ/t metal (compared to 17 GJ/t for the blast furnace, including coking and ore preparation). In combination with pelletisation and electricity use for EAF the energy use amounts to 1.2 t/t steel (Birat et al. 1999). Full-scale introduction in Japan would result in an emission reduction of 50 Mt CO2. Since August 1999 POSCO is operating a pilot plant for their Finex technology in Pohan (Mistry 1999, VAI 2001), an advanced Corex plant that is developed in co-operation with VAI. Iron ore fines are used instead of pellets. In case this development is successful, both coke production and ore preparation can be avoided, resulting is significant environmental benefits and economic benefits. Given the fact that the energy supply situation in South Korea is very similar to the situation in Japan, such technology could also be interesting for Japanese steel makers. In general smelting reduction processes can be split into a coal gasification step and an ore reduction step that uses the coal gas. The ideal concept of a direct-smelting reduction process to convert fine ore and coal to liquid iron has not been realized yet. The smelting reduction concepts differ in the technological approach. Original plans were even to replace the steelmaking step, but this idea proved to be infeasible up till now. A number of alternative direct smelting processes have been announced. This includes the Japanese DIOS process, the Australian HI-smelt process, the American Iron and Steel Institute (AISI) process and the the cyclone converter furnace (CCF) originally developed by Hoogovens (currently a part or Corus steel). Only the last one will be discussed in more detail as an example14. The CCF concept may have an advantage compared to Corex because the concept is based on the use of iron ore fines and coal. The two-stage process consists of pre-reduction and pre-melting of iron ore in a melting cyclone, followed by final reduction in a converter type vessel containing a liquid iron bath. Both stages of the process are combined in a single reactor. Both process stages have been proven on a bench-scale. The integrated process is currently considered for upscaling to a pilot plant scale (0.5-1 Mt per year). It remains to prove if the process can be developed successfully, given the obstacles that have been encountered during the development of other smelting reduction processes.

14 Forecasting the viability of such new technology is difficult. If it works, it is obviously a significant competitive advantage. However the technological feasibility of the process is not clear. Information is often misleading because of important commercial interests.

26


In the CCF process, ore and oxygen are injected tangentially into the melting cyclone. The melting cyclone is mounted on top of a converter type vessel. The pre-reduced molten ore is collected on the wall of the cyclone and flows into the bath. The final reduction of the ore and gasification of granular coke take place in the iron bath. About 25% post-combustion with 80% heat recovery is required in order to cover the heat requirement in this stage of the process. The pre-reduction degree of the iron (in the cyclone) is 25%. The gases arising from the smelter are further combusted in the melting cyclone in order to generate melting and pre-reduction heat. The final combustion rate of the off-gases is 75%. The energy balance for the CCF process is shown in table 2.2 (based on 25% post combustion, 80% heat recovery above the iron bath, hot metal with 4% carbon at 1500°C, a slag basicity of 1.1 and an exit gas temperature of 1800°C, excluding oxygen production). The process generates significant amounts of energy by-products. Recent preliminary calculations indicate that the actual energy consumption may prove to be somewhat lower, with a higher ratio of gas to steam by-product. Table 2.2: Energy and mass balance of the CCF process (Gielen and Dril 1997) Input [GJ/t iron] Output [GJ/t iron]Coal 640 kg 20.1 Hot metal 1000 kg 9.9Ore 1500 kg Slag 270 kg 0.4Oxygen 730 kg Gas 1214 Nm 4.0Lime 110 kg Steam 4.3 Losses 1.4Total 20.1 20.1 Apart from these complex shaft furnace processes, a number of rotary kilns for coal based direct reduction are operational. This includes the Finmet process (operational in Venezuela) and the DRC rotary kiln technology (operational in Australia)(VAI 2001). Fluid bed technology can also be applied, the so-called Circofer process (Daniels and Moll, 1997). This listing is not exhaustive, at least 10-15 alternatives have been developed. These technologies produce solid iron briquettes, which can be shipped and fed to electric arc furnaces. This process seems no iron production alternative for Japanese producers, because the lack of indigenous coal or iron ore resources makes an iron export strategy very unlikely. However import of iron briquettes may be an interesting option for the future in case national emissions must be reduced. From a global perspective such a switch does not result in a significant emission reduction. However a market niche may exist in case DRI and iron briquettes can be used to dilute polluting scrap elements. Given the uncertainties regarding technology development, only proven technologies are considered in this study: Corex and the combined Corex/DRI process.

27


2.2 Substitute coal by other fuels A number of energy alternatives exist for coal:

• Natural gas; • Charcoal; • Waste plastics; • Hydrogen; • Electricity.

The CO2 content of the latter two energy carriers is zero. However the emissions in their production may be considerable, depending on the primary energy carrier that is applied. Nuclear energy based electricity would be the only large-scale option that would be available in the next two decades. Public opposition may pose an obstacle for such an emission reduction strategy. Natural gas Natural gas can be used for the production of DRI, which can be processed in EAFs. Gas based DRI production is an established technology. Global DRI production amounted in 1999 to 38.6 Mt (7% of the total global iron production). Gas based DRI production covers 92% of total DRI production, the other 8% is coal based. Two processes are dominant: MIDREX and HYLIII. Midrex covered 63% of the global production capacity in 1999 (Fritz, 1999). The energy consumption is approximately 9.5 (MIDREX)-10 (HYL II) GJ/t (Zervas et al. 1996). Given emissions of 0.056 t CO2/GJ gas, the DRI/EAF combination would result in 0.7 t CO2/t crude steel, a 65% reduction compared to the conventional BF-BOF route. The saving potential for 70 Mt primary steel amounts to 91 Mt CO2. DRI is a solid commodity that can be bought on the world market. Its production is especially attractive on remote gas field locations with access to iron ore resources. However the DRI price in case of Japanese imports is generally higher than the price of BF iron (approximately 110 US$/t CIF (Ritt 2000)). Charcoal Charcoal is produced from wood. Global charcoal production amounted in 1999 to 22.6 Mt (FAO 2001). The energy content is approximately 27 GJ/t, the total global production is equivalent to 610 PJ. This represents only 30% of the total energy consumption in the Japanese iron and steel industry. However part of the Brazilian iron production is based on the use of charcoal. Approximately 1.3% of the global iron production (approx. 7 Mt) is based on the use of charcoal (Gielen and Dril 1997). In fact, iron production in Europe was initially based on charcoal before coal was introduced as a substitute because the forests were disappearing. The future global biomass availability may allow large-scale charcoal introduction, in case large-scale high yield biomass plantations are established. Estimates of biomass availability in 2050 range from 0 to 400 EJ (compared to a current global primary energy consumption of approximately 400 EJ, and 20 EJ energy use in the Iron and Steel industry) (Fischer and

28


Schrattenholzer in press)). Charcoal lacks the mechanical stability of coke, but it is possible to substitute blast furnace coal injection by charcoal injection (Gielen and Dril 1997). The production of charcoal takes usually place in small-scale operations. Traditional charcoal burning is a very polluting activity. New, modern shaft kilns have been developed in e.g. Germany. The emissions are much lower, but the production costs of this charcoal are significantly higher (Feber and Gielen 2000). Assuming that a maximum of 200 kg coal per ton of iron can be substituted, the emission reduction potential amounts to 35 Mt CO2. Waste plastics Plastic waste can be injected into blast furnaces as a substitute for coke and coal. The technology has been developed and applied in Germany (Gielen and Yagita 2001). Mixed plastic waste injection into blast furnaces is currently practiced on a pilot plant scale in Japan by NKK at its Keihin works. Before plastic waste is added, the chlorine content must be reduced in cases where PVC (PolyVinylChloride) containing waste types are used. The molten plastic can then be injected into the blast furnace. Coal and coke are replaced on a thermal par basis (NKK 2000). Waste plastics can also be added to the coke oven. This option is preferred by Nippon Steel (Nippon Steel 2000). The technology is not yet applied in other countries. First the waste is sorted manually, followed by separation of PVC based on differences in density. The resulting plastic waste is processed into an RDF type pellet (Refuse Derived Fuel). This pellet is used as feedstock for the cokes oven. The cokes oven product mix consists of 40 % cokes oven gas, 20% cokes and 40% oil. The energy efficiency of a coke oven is approximately 82%, if the gas use for firing is accounted for (Daniels and Moll 1997). The main driving force for this alternative to blast furnace injection is the production of high value liquids and gaseous energy carriers, increased flexibility (in combination with the blast furnace injection), and less stringent control requirements regarding the chlorine content of the waste fraction. Moreover the powdering of the plastic can be avoided (personal communication N. Takamatsu, Nippon Steel). The CO2 reduction effect depends on the allocation of CO2 emissions from plastic waste to the steel industry or to the waste producers. Plastic waste contains approximately 0.073 t CO2/GJ (vs. 0.1 t CO2/GJ coal, see table 1.3). The CO2 reduction ranges from 0.027 to 0.1 t CO2/GJ, depending on the allocation scheme. The difference is almost a factor 4, which indicates that this allocation may affect the choice significantly. The option is limited by plastic waste availability. A maximum of 5 Mt seems feasible. Assuming an energy content of 30 GJ/t the emission reduction amounts to 4 Mt CO2. In case the carbon content of waste plastic is not allocated to the steel producers but to the

29


waste generators, the net emission reduction amounts to 15 Mt CO2 (Gielen and Yagita 2001). 2.3 Increase the recycling rate The CO2 emission from EAF steel production based on 100% scrap is approximately 0.7 kg/t crude steel vs. 2.2 t/t crude steel for blast furnaces (see section 1.2). As a consequence a switch from BF to EAF steel will result in a CO2 emission reduction: more steel recycling can reduce CO2 emissions. Obviously this option is limited by steel scrap availability. The Japanese apparent domestic scrap supply amounted to 44 Mt in 1998 (IISI 2001). Japan is a net scrap exporter. Net exports amounted to 3.6 Mt in 1998. According to STEAP model calculations (see Chapter 4), scrap availability would amount to 50 Mt. This suggests that there is some room for increased scrap recovery. Achieving 100% recovery is unlikely given the very high costs. It is assumed that 2 Mt additional recovery is the maximum feasible. A combination of 2 Mt additional scrap recovery and a stop of the scrap export would result in 5.6 Mt additional scrap, which could be converted into steel. The emission reduction would amount to 10 Mt CO2, in case primary steel is substituted. Scrap imports are not considered in this assessment because it would imply more primary steel production elsewhere. Steel scrap quality is an important issue, because it determines to some extent the quality of the secondary steel. DRI and iron produced from iron ore contain small amounts of trace elements and unspecified residual elements. Certain scrap types contain high quantities of tramp elements. An overview of tramp elements in scrap and steel tramp element standards is shown in table 2.3.

30


Table 2.3: Typical tramp elements in scrap and quality limits for selected carbon steels (UNECE 1992) Steel grade Total Cu+Sn+Ni+Cr+Mo [%] Maximum content Tinplate for draw and iron cans 0.12 Extra deep drawing quality steel 0.14 Drawing quality and enamelling steels 0.16 Commercial quality sheet 0.22 Fine wire grades 0.25 Special bar quality 0.35 Merchant bar quality 0.50 Characteristic content DRI 0.02 Pig iron 0.06 (American scrap standards) Scrap: no. 1 factory bundles 0.13 Scrap: bushelling 0.20 Scrap: shredded cars 0.51 Scrap: no. 2 heavy melting (mixed scrap)

0.73

Table 2.3 shows that especially car scrap and no. 2 heavy melting scrap cannot be used for all mentioned steel qualities. Current practice is to mix some scrap into the primary steel production. This process results in a dilution of trace elements and a gradual increase of these elements in the whole steel product stock. This may be a cost-effective solution for steel companies, it remains to see if this strategy pays off on the long term. In the same time period the trace elements build up in the steel stock, the steel quality requirements increase because of increased steel purity requirements, e.g. for transportation applications. On the longer run, dilution can pose serious problems for high quality recycling. New upgrading processes may be necessary or scrap must be landfilled. With regard to galvanized steel scrap (zinc coated steel sheet), this scrap quality can be recycled in electric arc furnaces while recycling in basic oxygen furnaces is only possible after costly zinc removal. The zinc is recovered in the filter dust of the EAF which can be recycled in the zinc industry. Because the fraction of zinc coated steel is increasing rapidly, this is an important advantage for EAF steel producers. Another important problem regarding scrap recycling is copper contamination. Copper originates from electric motors and from copper wiring. Especially for shredder waste, copper poses a problem. Shredder waste contains currently 0.8% copper. This results in 1.25% copper in the liquid steel if this scrap is processed in EAF furnaces. This high content limits the application of this scrap type. A maximum dismantling scheme can reduce the copper content to 0.5% in the liquid steel. Mechanic processing through shredding and subsequent

31


magnetic separation reduces the copper content to that of standard scrap grades (Ender et al., 1994). Scrap can be upgraded by separation and treatment systems. Balers, shears and shredders are used to upgrade waste products to steel scrap that can serve as input for EAF or BOF steel making. Operating costs are 6000, 5000 and 9000 Y/t, respectively. A description of these technologies can be found in (Nijkerk, 1994). For some scrap types, detinning is used to generate a more suitable scrap quality. CO2 removal and disposal in the sea CO2 can be removed from off-gases and stored. Different storage options have been proposed:

• Oil and gas producing reservoirs; • Depleted oil and gas reservoirs; • Coal seams; • Deep saline aquifers; • The deep ocean.

Given the lack of fossil fuel resources, deep saline aquifers and the deep ocean would be the options for Japan (note: this situation is very different from the European and North American situation, where such land based reservoirs exist). The total cost of capture and transportation of CO2 to a deep ocean site 500 km offshore is estimated to be 3000 – 4000 Y/t CO2 (IEA 1999). The energy requirements amount to 1.8 GJ primary energy per t CO2 for capture (mainly low temperature steam, which may be recovered from other steel production processes) and 0.4 GJ/t for compression (Gielen 1999). Additionally the sea transportation adds 0.1 GJ per t. The transportation technology would be similar to existing LPG tankers. The body of scientific knowledge is limited. In 2001, a project starts to inject 50 to 100 t CO2 off the coast of Hawaii in order to study this option in more detail (Monastersky, 1999). The quantity of CO2 from one steel plant is in the range of 5-10 Mt, approximately 100,000 times more. It is obvious that much more research is required. Currently deep ocean disposal of CO2 is illegal (IEA 1999). It remains to see if this ban will be lifted on the long term, given strong social opposition and uncertainty regarding environmental impacts. For this reason CO2 storage in sea is not considered a viable alternative for the Japanese steel industry for the next two decades. Injection in deeps saline aquifers below land is an alternative. However the geology of Japan is characterised by a complex geology, high volcanic activity and seismic activity. Especially the main areas with blast furnaces (the Eastern part of Tokyo bay, Nagoya, Kobe) are geologically instable. As a consequence

32


the actual retention of the CO2 below ground must be studied in more detail before this option is applied on a large scale. 2.4 Increase the efficiency of materials use One of the explaining factors regarding the slow growth of final steel demand is the rapid improvement of materials efficiency. Examples are found in many fields of application. For example the weight of cast iron engine blacks for passenger cars can be reduced by 30% through improved design (Röhrig and Deike 1997). New designs for the body-in-white of passenger cars can result in a 35% weight reduction (IISI 1994). In the case of building materials (I-beams) or for machinery, similar efficiency potentials exist (Gielen 1999). In Japan the National Institute for Metals is studying the development of high tensile strength, ultra-high fatigue strength steels and high temperature and corrosion resistant steels (Furukawa, 1998). However the assessment of these potentials requires detailed engineering knowledge and design studies on the product level. For example high temperature resistant steel will allow an increase of steam temperature in boilers of coal fired power plants. This will result in an increased electric efficiency of approximately 1%, enabling a Japanese emission reduction of 2 Mt CO2 (20% coal fired power plants, IEE 2000). Such potentials can only be assessed from a life cycle perspective, beyond the scope of this study. The potential reward is substantial, both in CO2 terms and in monetary terms. 2.5 Initiate JI and CDM projects Foreign steel production is considerably less energy efficient than Japanese steel production. This is illustrated by the Chinese energy efficiency figures in table 2.3. Annex 7 provides a comprehensive overview of efficiencies of global steel industries on a national level. It shows that the efficiencies in China, India and the Ukraine are low, while the production in these countries is significant. The specific coal consumption per unit of primary steel is 50% to 100% higher than the coal consumption in Japan. In case the energy efficiency in these countries would be raised to Japanese levels this would reduce emissions significantly. Given the proximity to China and the importance of Chinese steel production on the global level, only co-operation with China has been considered in more detail. Baosteel in Shanghai is the largest Chinese steel producer with efficiencies approaching the Japanese levels (see table 2.4). If all other Chinese steel producers would be upgraded to the same energy efficiency level this would result in an emission reduction of 55 Mt CO2 per year. However the energy efficiency of Chinese steel producers is increasing rapidly as Open Hearth furnaces are phased out and the hot connection between blast furnaces and BOFs is established. Data for Chinese steel plants indicate in case these two improvements are implemented the energy consumption drops by about 10 GJ/t steel (from 30 to 20 GJ/t) (Chen et al. unpublished data). Moreover the small-scale steel producers below 5 Mt per year may not be competitive on the long term and may be replaced anyway. If such considerations are taken into account

33


in the establishment of baseline emissions, the efficiency potential is reduced significantly. Table 2.4: Energy efficiency of Chinese steel producers, 1997 (Wu 2000) Company Production

[Mt]Energy use

[t coal eq/t steel]Baosteel 15.1 0.737Anshan 8.3 1.282Capital 8.0 0.972Wuhan 6.1 1.044Maanshan 3.0 1.342Panzhihua 2.9 1.211Benxi 2.6 1.529Handan 2.5 0.855Taiyuan 2.4 1.233Tangshan 2.4 1.117China 108.9 1.392 The establishment of GHG emission reduction projects abroad could include projects outside the iron and steel industry. Planting trees for carbon storage would represent such an option. Initially CO2 is stored in living trees and soil. Ultimately the trees could be used for production of charcoal for injection in blast furnaces. However the land areas involved are very substantial. For an annual reduction of 10 Mt CO2, assuming a (high) yield of 20 t biomass/ha.yr (odm) and 1.8 t CO2/t biomass, requires an area of 275,000 hectares (about 50 km length and width). Another approach may be the purchase of emission reduction permits in the international market. These permits may be available at a price below 1000 yen/t CO2. However on the long term the price of such permits is probably significantly higher, in case international GHG emission reduction is aimed for. Given the recent announcement of the US government that they do not want to participate in the Kyoto protocol, the future of JI and CDM is uncertain, too. Given this uncertainty it is recommended to focus on technological improvements within Japan and use foreign emission reduction as a backstop strategy.

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2.6 Overview Table 2.5 provides an overview of emission reduction potentials and emission reduction costs. The potentials have been estimated for 2010 and for 2020. The assessment is based on current production levels, competition between options is not considered. Because of competition (either coal injection in BF or DRI/EAF steel production), addition of emission reduction potentials results in an overestimation. The figures represent a technical potential, socio-economic barriers are not considered. Table 2.5: Overview of emission reduction options. Figures in brackets indicate 2020 potentials Category Option Potential 2010

(potential 2020) [Mt CO2/yr]

Costs15

[Y/t CO2] Energy efficiency

Coal injection 8.9 (8.9) 0

Near net shape casting

1.0 (4.5) -10,000-0

Energy recovery

3.2 (3.2) ?

Smelting reduction

10 (50) 0

Fuel switch DRI/Natural gas

20 (70) 1000-2000

Charcoal 10 (35) 2000-5000 Waste plastics 15 (15) 0 CO2 storage Oceanic 0 (>100) 2000-5000 Deep aquifers 2000-5000 Materials efficiency

5 (20) -10,000-10,000

JI/CDM China 55 (0) 0-2000 Tree

plantations 2 (10) 0-2000

15 Costs are expressed relative to a business-as-usual situation

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3 Modelling issues In order to study the complex interactions between technological change, trade patterns and CO2 emission reduction a model has been developed, called STEAP (Steel Environmental strategy Assessment Program). A life cycle approach has been used in this study. The basic model code is similar to the one for other materials that have been discussed in detail in previous publications (MARKAL-MATTER, Cheap and Reap models, Gielen 1999, Gielen and Yagita 2001, Gielen and Moriguchi in press). This model has been developed from an industrial ecology perspective. The iron and steel economy is considered to be a system consisting of processes that are linked via flows of energy and materials and monetary flows. These flows can change due to government, industry and consumer decisions. The algorithm reflects the mechanism of an ideal market. A number of new elements have been added compared to previous models in order to account for the specific characteristics of the steel industry:

• The model scope has been extended from a purely national scope to a regionalized global scope with materials trade between the regions, in line with the Freak model for global petrochemicals (Gielen and Yagita in press);

• The life span of capital equipment can be specified individually per process type;

• The model can be run with the assumption of perfect market or with regional monopolies, with or without international competitors.

The model is written in the GAMS modelling language (General Algebraic Modelling System, Brooke et al. 1992). The model is based on a so-called 'perfect foresight' approach; all future developments are taken into account in current investment decisions. The optimisation is done from a national cost perspective, excluding subsidies and taxes. The STEAP model structure in comparison to life cycle analysis (LCA) and material flow analysis (MFA) is shown in figure 3.1. The figure has two dimensions: the life cycle stage (horizontal) and time (vertical). MFA focuses on the material flows in a certain area in one year. LCA focuses on the flows throughout the life cycle of one product. The STEAP model encompasses the material flows in the life cycle of all products in an area for a period of 75 years (1965-2040). STEAP is limited to iron and steel (but could in principle be extended to other materials as well). As a consequence the current model version is not suited to study to study materials competition, see (Gielen 1999). An overview of energy carriers and materials in this model is provided in annex 1 of this report

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PROD

PROD

USE

WASTEPROD

USE

WASTE

WASTE

USE

LCA

MFA

CHEAP

TIME

LIFE CYCLE STAGE

T

T+1

T+2

Figure 3.1: CHEAP model structure vs. LCA and MFA The STEAP model covers the full life cycle of all steel products (see figure 2). This enables a proper comparison of options such as industrial energy efficiency improvements and fuel switches vs. increased recycling. The relation between current materials consumption and future scrap release is considered in the model. The life cycle of iron and steel is modelled from ‘cradle to grave’. Both heat and electricity production (and the related CO2 effects) are included in the model. It is an aggregated national model without regional detail. The main model features are listed in table 3.1.

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IRON ORE

FINISHED STEEL

FINISHING

ORE PREPARATION

EAF

CONSUMPTION

BLAST FURNACE

SINTER/PELLETS

IRON

SCRAP

CRUDE STEEL

DISPOSAL

FINISHED STEEL

FINISHING

BOF

CRUDE STEEL

Figure 3.2: Life cycle model structure in STEAP

The model is dynamic. This includes the following features:

• The waste quantities are calculated from materials consumption in previous years;

• Capital equipment vintage is accounted for; • Future availability of new technology is accounted for; • Changing prices of scarce natural resources (fossil fuels, biomass,

disposal sites etc.) are accounted for.

38


Table 3.1: Summary of STEAP model characteristics Driving force Materials service demand Coverage Full life cycle Spatial boundary Global (11 regions) Time period 1965-2040, 5 year periods Coverage All iron & steel products Objective function Consumer/producer surplus Energy & heat production Endogenous Valuation waste treatment revenues (electricity, recycled materials etc.)

Endogenous

Strategies considered Fuel/feedstock switch, energy efficiency, demand reductions, recycling, energy recovery, CO2 storage

Number of energy and material flows 44 Number of processes 75

Processes are characterized by a limited number of variables. The number of variables in the model exceeds the number of relations (equations) among the variables. One so-called objective function is defined which is minimized or maximized (in this case, the loss of consumer/producer surplus is minimized). The special feature of linear programming models (such as STEAP) is the proportional relations between inputs and outputs of processes (and also costs), an obvious abstraction from reality (e.g. the energy efficiency of an industrial plant and the cost per unit of production capacity depend to some extent on its size). This limitation does not apply to non-linear programming models. However, in practice, the use of non-linear programming is severely limited by the speed of current computers and data availability. 3.1 System Boundaries The model covers the time period 1965-2040, divided into five-year periods. There are three reasons why such a broad time span has been considered. The first reason is that computer models often produce results for the first and last time periods that are affected by this system boundary (e.g. because investments are not depreciated properly). The results for the initial periods and the last periods are not accurate. Especially in the steel life cycle with long life capital equipment and long life products, a long term perspective is essential. The second reason is to allow some model validation, based on the comparison of modelling results and the actual economic data for the last three decades. The third reason is proper accounting of waste release (from steel consumption in earlier periods). Regarding spatial boundaries, the model covers the life cycle of steel from the iron ore mining to the waste scrap-handling stage. The model is global. The materials that are considered in the model are listed in annex 1. For each material, at least one production process has been modelled. In some cases, a number of alternative production options have been considered, selected on the basis of the GHG emission reduction potential (see chapter 2).

39


3.2 Emission Accounting GHG emissions are calculated according to the IPCC (Intergovernmental Panel on Climate Change) emission accounting guidelines (IPCC 1997). The emission accounting takes place at the moment the fuels that enter the system (buying of fuels). Credits are given for net exports of fuels from the system. Energy outputs of the system have been credited on the basis of the CO2 equivalent carbon content of the energy carriers. The use of blast furnace gas is completely allocated to the steel life cycle. Credits are given in case natural gas is substituted by blast furnace gas of coke oven gas outside of the iron and steel sector. These credits are equal to the CO2 emissions of natural gas combustion. No CO2 emissions are accounted for in biomass use (the quantity of carbon stored in the growing biomass is equal to the quantity of carbon released when the biomass is combusted). Carbon storage in iron and steel is neglected. Emissions for limestone calcinations are also accounted for. Regarding CO2 emissions from electricity and steam production, it is assumed that the industry produces its own energy. Seven types of power plants are considered:

• BF gas engines • Natural gas fired power plant (full electric mode) • Wood gasifier IGCC (integrated gasifier combined cycle) • Coal fired steam cycle • Coal fired IGCC (integrated gasifier combined cycle) • Nuclear power plant • Hydro power plant

Availability of these power plant types depends on regional natural resources (hydro) and social acceptance (nuclear). Because the iron and steel industry represents only a small part of the total electricity demand, allocation of one specific type of electricity source to the iron and steel industry is questionable. However this approach was chosen in order to account for a decreasing CO2 intensity of electricity in case of CO2 taxes. Model calculations indicate that electricity production will become virtually CO2-free at comparatively low CO2 tax levels, see e.g. (Gielen 1999). In case these fuels are not sufficient to cover the demand for heat and electricity, natural gas can be used for heat generation (either via combined heat and power generation or stand-alone electricity production, depending on the energy demand structure). Because of insufficient regional detail the model is not suited to study district heating or heat cascading. As a consequence the model underestimates the energy efficiency potentials.

40


Because of the sheer volumes and the transportation distances, transportation of resources, materials, and waste in the steel cycle is also a considerable source of GHG emissions. Total marine bunkers (for ocean-going vessels) amounted to 452 Mt CO2 in 1998 (World Coal Institute, 2001). An overview of world seaborne trade of main commodities is provided in table 3.2. Approximately 35% of the trade in coal is accounted for by coking coal. Assuming an energy consumption of 0.2 MJ/t.km, the total CO2 emission amounts to 327 Mt. This is slightly lower than the actual total emission. The gap can be explained by bunkering for passenger transportation, fishing etc.. The trade of iron ore and coking coal contributes approximately 45 Mt CO2. Trade of finished steel products must be added to this figure. The quantity is approximately 300 Mt (IISI 2001). Assuming an average transportation distance of 10,000 km, this adds another 45 Mt. It is estimated that 25 Mt of scrap is traded intercontinentally, based on (IISI 2001). Assuming an average transportation distance of 10,000 km this adds 4 Mt CO2. In total trade contributes 120 Mt CO2 emissions, compared to 2000 Mt emissions in production. Seaborne transportation adds 6% to the total emissions in the steel life cycle. This quantity is not negligible, especially if the 100% increase of trade in finished steel products during the last 10 years is considered. As a consequence the emissions during seaborne transportation have been included in the model, but they have not been taxed because they occur outside the national emission framework. Table 3.2: World seaborne trade of main bulk commodities, 1999 (Fearnleys, 1999) Tonnage

[Mt]Tonne-km[109 t.km]

Fraction [%]

CO2[Mt/yr]

Iron ore 410 2220 10.3 33Coal 480 2430 11.3 36Grain 210 1170 5.4 18Bauxite/alumina 53 295 1.4 4Phosphate rock 31 135 0.6 2Crude oil 1480 7500 34.9 112Oil products 410 2010 9.4 30Others 2140 6150 28.6 92Total 5100 21480 100.0 327 Trade among the regions has been modelled for all types of solid products (ore, DRI, scrap, steel products. Liquid iron and liquid steel cannot be traded). Trade has been split into two categories: bulk commodities (ore, DRI, scrap) and steel products. Bulk commodities can be traded at lower cost because no packaging is required and larger bulk carriers can be used. The assumptions regarding transportation cost and transportation distances are summarized in Annex 3.

41


Inland transportation (shipping, rail and road transportation) has been neglected in this study because of the scale of the model does not allow analysis of transportation on such a detailed level. It is estimated that transportation of iron and steel adds another 250 Mt CO2, based on an assumption of 2000 km throughout the life cycle (the total for steel, steel product and scrap transportation) and 2 MJ/t.km. This represents approximately 15% of the emissions in steel production. 3.3 Energy and material flow modelling The model flow variables have been divided into four categories (see Annex 1):

• Energy carriers; • Resources; • Materials; • Waste.

All energy carriers are expressed in energy units (GJ) and all resource, materials and waste flows are expressed in mass flows (tons). Within the category energy carriers, two types are discerned. One type is endogenous to the system (BF gas, coke oven gas and electricity), the other energy carriers can be exchanged with across the system boundary (at given price levels). For materials and for waste, a mass balance principle applies: the production is equal to the consumption. Nine types of finished iron and steel products are modelled:

• Cast iron; • Concrete reinforcement bars; • Hot rolled sheet; • Steel wire; • Alloyed steel; • Heavy plate; • Cold rolled coil; • Cold rolled coil, annealed and tempered; • Galvanized sheet.

3.4 Process Characterization Each process is characterized by its physical inputs and outputs of energy (in GJ per unit of activity) and its physical inputs and outputs of materials (in metric tons per unit of activity). These process characteristics are the same for all time periods. The model input data for processes are characterised in Table 3.3. The model input data consist of physical data (energy and materials balance) and financial data. Moreover maximum capacity constraints can be added. A detailed listing of input parameters is provided in Annex 2-6.

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Table 3.3: Example of model input data for a process, i.c. EAF steel production INPUT ELECTRICITY [GJ/t] 1.4STEELSCRAP [t] 1.05OUTPUT LIQUID STEEL [t] 1.0 INVESTMENT [Y/t.yr] 50,000VARIABLE COST [Y/t] 2,000 UPPER BOUND CAPACITY [Mt/yr] Year and region specificLIFE [years] 20 Costs have been divided into investment costs, fixed costs and variable costs. The investment costs and the fixed costs are proportional to the installed capacity. Investment costs occur in the time period that the process comes on line. Fixed costs arise for all years the process is operational (the full life span). Annual fixed costs have been set at 4% of the investment costs. Variable costs are proportional to the inputs of energy and materials. All costs have been expressed in costs of the base year, based on a 8% discount rate that reflects industrial profitability criteria. The life of all processes can be defined exogenously (in periods of 5 years). The data for the processes have been derived from a Western European database (Daniels and Moll 1997, MATTER2000). Data have been adjusted to reflect regional differences and new processes have been added in order to reflect production technologies in other regions (e.g. iron ingot casting, open hearth furnaces, and beehive coke ovens). 3.5 Regional detail Because this study focuses on Japan, the region around Japan has been modelled in detail, while other world regions have been modelled on the continent level. This has resulted in a model with 11 regions:

• Japan; • China; • South Korea; • Oceania (Australia and New Zealand); • The community of independent states CIS (the former USSR); • North America (Canada, USA and Mexico); • Middle East (Iran, Irak, Saudi Arabia, Kuwait, Oman, UAE, Yemen, Egypt,

Lybia, Algeria); • Europe (EU15 + Norway, Iceland, Switzerland, Czech republic, Slovakia,

Poland, Romania, former Yugoslavia, Turkey, Bulgaria); • Other Latin America; • Other Asia; • Other Africa.

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The Middle East has been modelled separately because of the gas reserves and the CO2 storage potential in depleted oil and gas fields. Japan, China and South Korea are the main players in the North East Asian steel market. Their production amounted to 94.2, 123.7 and 41 Mt, respectively, in 1999. Their joint production (259 Mt) represents 33% of the global steel production. The investment costs differ per region, the labour costs differ per region, resource availability differs, regional market size differs and the technology availability differs. The regional diversity of investment costs, labour costs, energy costs and resource costs has been expressed relative to the costs in Japan. The assumptions are summarized in Annex 4. Figure 3.3 shows the model structure for steel production. Three coal-based technologies are considered for production of liquid iron: the blast furnace, Corex and a combined Corex/DRI production process. Four types of coke ovens have been considered (Moll and Daniels 1997, Jiang et al. 1998, Buss et al. 1999):

- Recovery type, wet quenching; - Recovery type, dry quenching; - Non-recovery type; - Small-scale beehive oven.

Increased coal injection is considered as autonomous development for blast furnaces. Charcoal and waste plastic are considered as substitutes for (limited amounts of) coal in iron making. Three steel making routes are considered: OHF (Open Hearth Furnace, which is disappearing), BOF (the Basic Oxygen Furnace) and EAF (the Electric Arc Furnace). DRI (Direct Reduced Iron, a solid iron product based on iron and natural gas) can substitute scrap in EAF steel making. Two steel qualities are considered: high quality (e.g. sheet < 3 mm, coated sheet, wire and tubes) and conventional (e.g. heavy plate, bars, castings). This reflects the fact that impurities can limit the steel application. Scrap based EAF steel can only be used for the conventional quality. It is assumed that the high quality can only be produced from iron ore.

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COKING

SCRAPIRON ORECOKING COAL

COREX

PELLETISING

SINTER PELLETS

SINTERING

REHEAT

BLAST FURNACE

DRI PROD.

COKE

EAF

ROLLING

BOF

CASTING

LIQUID IRON

STEAM COAL

PIG IRON

NATURAL GAS

EAF

OFF-GASPLASTICS

DRI

HQ LIQ. STEEL

OHF

CONT. CASTINGNNS CASTING

FINISHED STEEL PRODUCTS

LIQ. STEEL

INGOT CASTING

REHEATING

CONT. CASTING

STEEL INGOTS

ROLLING

OFF-GAS

CHARCOAL

PCI

PLASMAFUEL OIL

Figure 3.3: STEAP model structure for steel supply. See glossary for acronyms. 3.6 Demand projections Demand has been forecast as a function of GDP, income elasticities, and autonomous efficiency gains. The assumptions are summarised in Annex 3. The demand vector in STEAP has been split into national demand and (net) exports. National demand has been divided into 8 demand categories (packaging, building materials etc., based on (Crompton 2000)). Each product category is characterized by a fixed mix of plastics and by a fixed product life. The steel mix in each sector has been calibrated with the actual consumption data. Future demand is estimated as a function of GDP, an income elasticity of 0.5 (1% GDP growth results in 0.5% physical demand growth, based on (Mannearts 2000)), and an autonomous materials efficiency improvement (AMEI) of 0.5% per year. The latter variable reflects technological progress based on product re-design, improved materials quality, etc.. Also price elasticities of demand have been considered. This elasticity reflects the fact that the demand decreases in case prices rise. This decline is caused by a number of mechanisms (Gielen 1999): a substitution of product services, re-design of products with less materials, materials substitution, re-use of products and increased product life. Figure 3.4 illustrates the optimisation procedure for one material (Loulou and Lavigne 1996).

45


D

S’

SSP’SP

P

QEQEQ’

Figure 3.4: Supply and demand equilibrium Figure 3.4 shows a supply curve (S) and a demand curve (D) for the base case (without GHG tax). Both curves are simulated with step-wise functions in order to be able to use a linear programming algorithm, which has major advantages from a computing point of view. The horizontal axis Q represents the quantity, the vertical axis P represents the price. The demand decreases if the price increases. Equilibrium between supply and demand is reached in point EQ (in model terms, the area to the left between the supply curve and the demand curve is maximised). The price that is set in this market is the shadow price SP. Supply curves are derived from the database of supply options in the model. Each supply option is characterised by costs, physical inputs and outputs and emissions. The potential contribution of each option is limited by the availability of the physical inputs and by the bounds on each supply option (e.g. a limited biomass availability because of the limited availability of land). Supply options are selected on the basis of cost minimisation, thus simulating the supply curve. In case a CO2 tax is introduced, the supply curve moves in an upward direction because all emissions in the supply chain are penalised and transferred in the production chain through increasing energy and materials prices (S changes to S’). Demand decreases because of increasing prices and a new equilibrium price and equilibrium quantity are achieved (EQ’). Three variables are used to model the elastic demand function: the demand elasticity, the maximum decrease of the demand, and the number of demand steps. The demand function is defined as (Loulou and Lavigne 1996):

46


Qip/Qib = (Pip/Pib)ei where: Qip = demand for product (demand category) i after introduction of GHG tax Qib = demand for product i in the base case Pip = price of product i after introduction of the GHG tax Pib = price of product i in the base case e = price elasticity of demand This function is split into a fixed number of steps, characterised by a set fraction of demand and a cost level. These “demand reduction options” compete with options for emission reduction in materials production and waste management. The costs of these demand reductions are equivalent to the loss of consumer surplus (the decrease of the area below the demand curve D, see figure 3.4). The minimum and maximum demand is 50% lower respectively 25% higher than the default demand in the base case. This section of the curve is split into 30 steps (each step represents 2.5% of the BC demand). The demand elasticity has been set at –0.2 (a 1% price increase results in a 0.2% demand reduction) (Mannaerts 2000). 3.7 Market distortions During the last two years the US government has been claiming that in other countries, especially Japan use non-competitive practices (Tilton 1998, International Trade Administration 2000). Amongst others, they claim with regard to Japan that:

• Japanese steel prices are 60% above world market prices; • Despite the high prices, imports into Japan are insignificant; • The market shares of the five primary steel producers have been constant

over a period of more than two decades; • A secret agreement of European and Japanese producers exists not to

trade in each others markets, resulting in increasing sales in the US market;

• The Japanese steel producers control the trading companies, thus preventing any imports;

• The Japanese steel producers get METI involved in production planning, so the Japanese Free Trade Commission cannot intervene (one ministry cannot act in the competence field of another ministry).

It is not clear whether all these allegations are true. The bilateral trade restrictions that were raised by the US have been rejected by WTO (WTO 2001). However the amounted evidence suggests that the ideal market mechanism may not reflect the real world adequately. This is especially valid for historical years. For this reason an alternative market mechanism has been analysed, the regional monopoly. Probably the real world is in between a monopoly and the ideal market.

47


Market distortions have been modelled via: • Upper limits for trade; • Upper limits for regional production activity; • Import tariffs; • Additional trade costs reflecting market barriers such as regulations and

transaction costs; • Monopoly algorithm (in a separate model run).

Trade modelling is discussed in more detail in the next section. The monopoly is discussed in this section. In the ideal market simulation, the loss of consumer/producer surplus (the area between the supply curve and the demand curve in figure 3.4) is minimized. In the monopoly simulation, the profit of the monopolist is maximized. This situation is illustrated in figure 3.5. In the ideal market, the equilibrium is given by (Q1,P1). In the monopoly, the equilibrium is (Q2,P2). This new equilibrium is characterised by the condition of maximised profits (Francois 1998): (P2 – MC)/P2 = 1/e e = - dQ/dP X P/Q e is the market elasticity of demand (the first order derivative of the demand curve). MC is the marginal cost level (the cross-section of the vertical line from P2Q2 and the supply curve). P2 can be calculated as a function of the base case price and quantity: P2 = P1 x (Q2/Q1)1/e

Q2 = Q1 x (1 – N x 0.025)

48


P

QQ2(MON)

P2

DEMAND

SUPPLY

Q1(IM)

MC

P1

Figure 3.5: Supply-demand equilibrium in an ideal market (IM) and in a monopoly (MON). P = price, Q = quantity, MC = marginal costs 3.8 International trade modelling This model is based on the assumption that imports are prefect substitutes for national iron and steel products. However such international trade is constrained by trade barriers. Trade barriers can be split into natural trade barriers (transportation cost) and government policies. Governments regulate imports through a combination of tariff and non-tariff measures (Worldbank 2000). The most common form of tariff is an ad valorem duty (a percentage of the trade value in monetary units), but tariffs may also be levied on a specific, or per unit basis. Non-tariff barriers may take many forms. Some common ones are licensing schemes, quotas, prohibitions, export restraint agreements. Moreover a wide range of domestic policies and regulations may act as non-tariff barriers. It is difficult to prove the existence of non-tariff barriers, but studies suggest that they

49


are common practice for steel (International Trade Administration, 2000). It is even more difficult to quantify non-tariff barriers and to include them in the model. A ban on imports has been considered. Other non-tariff barriers have been expressed in monetary terms (annex 3). The data basis for these values is non-existent. The estimates are based on information regarding interregional trade (ECE 1987, International Trade Administration 2000, IISI 2001). In case trade does not occur, despite model calculations indicate trade, significant non-tariff barriers have been added. It is assumed that these barriers will disappear in the next decade because of the increasing influence of GATT. Two types of trade barriers have been considered in the model:

• Transportation costs; • Import tariffs.

Import tariffs have been estimated on the basis of the mean tariff for primary products16 (Worldbank 2000). In case the model region covers a number of countries, the tariffs for the largest country (in terms of steel markets) have been used (e.g. Brazil for Latin America, India for Other Asia). The product prices have been taken from a STEAP BC model run (excluding tariffs). The resulting tax has been set as a fixed value. Also a correction has been applied for the decreasing import tariffs in time. The assumptions are listed in Annex 3. 3.9 Scrap management modelling Not all steel ends up as scrap. Part of it is oxidized during use. Another part is ‘lost’, for example for foundations, during mining, drilling, sea pipelines etc.. However data regarding these losses are not available. In this study it has been assumed that these losses range from 10% (transportation equipment, machinery, buildings) to 30% (packaging). Scrap has been split into four types:

• Bulk scrap (transportation equipment, machinery, scrap in building and construction waste);

• Diluted steel scrap (either distance >500 km, very low population (scrap) density or more than 25% other materials included);

• Steel scrap in municipal solid waste (beverage cans, tins, part of electric appliances);

• Collected and prepared scrap, ready for re-use. The first three scrap types can be upgraded for recycling. The upgrading costs depend on the scrap quality. For example galvanised and painted sheet “diluted steel scrap ”requires significant pre-treatment before it can be used in EAFs. The collection costs and the upgrading costs depend also on the distance, the

16 Covering SITC revision 2 sections 0-4 plus division 68 (non-ferrous metals)

50


population density and the scrap quality. These have been varied across regions (see annex 5). Different collection costs have been assumed, ranging from 2000 to 4000 Y/t (based on global scrap prices). The costs for pre-treatment range from approximately 2000 Y/t for bulk scrap collection and preparation in industrialised countries to 8000 Y/t for scrap recovery from MSW in CIS. The opportunity cost of scrap depend also on the alternative waste treatment (i.c. disposal). Assumed disposal costs in 2015 range from 1.800 Y/t (Oceania, Middle East, CIS) to 18,000 Y/t (Japan, Korea, Europe). Note that all these costs are assumptions, based on fragmentary knowledge from earlier modelling studies for Europe and other regions. 3.10 Software and model operation The STEAP model consists of the following elements

• An Excel spreadsheet with model input parameters • A model code with equations • A program which builds a matrix from the input data and the model code

(GAMS) • A matrix solver (e.g. CPLEX, OSL or CONOPT) • A model code for the report writing

The model consists of 175,000 rows and columns. The model solves in 30 minutes, using a PC with a Pentium III processor. This model run time is short enough to allow extensive sensitivity analysis and scenario analysis. 3.11 Scenario definition and policy simulation The assumptions regarding economic growth, income elasticity of steel demand and autonomous efficiency gains are shown in annex 5. Given the high uncertainty which is inherent to the forecasting method and given the relative insensitivity of steel demand to growth figures in comparison to other materials), only one socio-economic scenario is considered. This approach reduces the volume of output data significantly and it allows a policy analysis and discussion of results in greater detail. At a later stage more scenarios can be developed for strategy development. A base case (BC) has been analysed that represents a ‘business-as-usual’ scenario without any additional policies. Five CO2 tax levels have been analysed, ranging from 1,250 Y/t CO2 (CO2tax12) to 20,000 Y/t CO2 (CO2tax200), see figure 3.6. A global tax has been analysed (the same tax in all countries) and a tax in Japan and Europe, and no tax in other regions (indicated by the code JE).

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igure 3.6: CO2 tax levels analysed

0250050007500

1000012500150001750020000

2000 2005 2010 2015 2020 2025 2030[YEAR]

[Y/t CO2] CO2tax200CO2tax100CO2tax50CO2tax25CO2tax12

F

52


4 Model results The discussion of model results is split into four sections

• Model validation – how close are the results for the past and the actual data;

• Results in case of a global tax; • Results in case of a Japanese/European tax; • Comparison of the results with other studies.

4.1 Model validation Each model should be tested for its ability to simulate the reality. However it is per definition impossible to predict the future. At the very best, a model may provide some insights regarding mechanisms that would have been overlooked if simple extrapolation was applied. Many scientists demand that a model should at least be validated for the past. Unfortunately even this validation has only limited value. The reason is that we know now what we did not know in the past. For example the oil prices have fluctuated greatly, and very few people have forecast these fluctuations accurately at that time. The same holds true for technological development. A model simulation of the past with this added knowledge provides little information regarding the forecasting quality for the future. Comparison with other forecasting studies proves little relief: the studies are not independent. The forecasting community is small, often the same data sources are used etc.. As a consequence the results of any long-term technology forecast should be discounted heavily. “The illusion of knowing what’s going to happen is worse than not knowing” (Utterback, quoted by Sherden, 1998). Data regarding coal inputs into the iron and steel industry are available from statistics (table 4.1). The model coal consumption for 1980-1995 is within 10% of the actual consumption, which is sufficiently close given the uncertainties in statistical data. Some data sources suggest that part of the coal use in countries such as China is accounted for by heating of company employee residences etc., a demand category that is not considered in this model. As a consequence the data are even closer. However for the year 2000 the gap widens to 14%. This gap can be explained by an overestimation of steel recycling (see below). This is an indication that product life may be underestimated or recovery rates are overestimated.

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Table 4.1: Coal consumption for steel production, comparison of model output and actual data (World Coal Institute 2000b, IEA2000). Figures in brackets indicate the additional coal use for electricity production. Assumption 27 GJ/t coal (Steap model figures are in energy units). Actual

Coal for I&S [Mt/yr]

STEAP Coal for I&S

[Mt/yr]

STEAP Coal for electricity

[Mt/yr] 1980 622 650 84 1990 628 676 81 1995 573 635 94 2000 608 527 115 Actual interregional trade in the period 1970-1985 is considerably lower than the model results (ECE1987). This gap may be explained by non-price trade barriers. The implicit assumption in the model is that these barriers are gone after 2000. If this is not the case, the model is not a good representation of the real world situation. However in such a case any CO2 policy becomes feasible and the analysis of trade effects becomes irrelevant. Table 4.2: Global trade in iron and steel (ECE 1987). Excludes intra-regional trade. Actual trade

[Mt/yr]STEAP model

[Mt/yr]1970 62.5 2351975 83.2 2581980 99.8 2661982 99.1 273

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Table 4.3 shows the actual EAF steel production in comparison to the model estimates. The model results for 1985-1995 are within 10% of the actual values. However EAF steel recycling in 2000 is overestimated by 15%. In model terms this can be explained by large quantities of steel scrap from the building sector that are released after a product life of 35 years. Buildings from 1965 (the first year within the model time horizon) are scrapped in 2000. Because the building sector is a major steel market, this results in a significant increase of steel scrap quantities. A more sophisticated model regarding product life may generate more realistic results. Table 4.3: EAF steel production (Fritz 1999). Actual

[Mt/yr]STEAP model

[Mt/yr]1980 1651985 185 1951990 215 2181995 245 2192000 300 349 Table 4.4 shows the actual crude steel production and the production according to the model. One must add that the model steel production data do not account for losses in steel casting. These losses are probably accounted for in the statistics and account for 2-5% of production. The results show that the model overestimates production. In 2000, the overestimation amounts to 7%. Table 4.4: Global crude steel production (IISI 2001). Actual production

[Mt/yr]

STEAP model

[Mt/yr]

STEAP Cast iron

[Mt/yr] 1970 595 672 31 1975 644 712 37 1980 714 748 43 1985 719 774 49 1990 770 828 57 1995 756 857 62 2000 828 890 68 Table 4.5 compares the actual finished steel production and the model results. The model overestimates final steel production by 10%.

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Table 4.5: Global finished steel production (IISI 2001). Actual production

[Mt/yr]

STEAP model

[Mt/yr]

STEAP Cast iron

[Mt/yr] 1970 445 479 31 1975 520 529 37 1980 555 573 43 1985 585 624 49 1990 630 688 57 1995 648 719 62 2000 757 68 Prices of finished products and model shadow prices are compared in table 4.6. The results indicate that the shadow prices are very close to the real world prices. However one must add that the shadow prices change significantly in time. Table 4.6: Actual prices of finished steel products (World Bank 2001) vs. model shadow prices (100 Y = 1 US$) Product Japanese export price

fob17 1999-2000[Y/t]

STEAP model BC2000[Y/t]

Cold rolled coil 32,000-38,500 31,000Hot rolled coil/sheet 23,000-29,500 24,700Rebar 23,400-25,000 23,400Wire rod 29,000-31,000 25,900 In conclusion, the model reflects the results for the past with 10% accuracy. As a consequence the model is not suited for the analysis if small scale system distortions, but may provide new insights regarding the impact of significant distortions (e.g. the impact of a 10% coal price increase can not be analysed properly, but a doubling of coal prices can be analysed).

17 fob free on board

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4.2 Global GHG policies Global steel production for increasing GHG taxes is shown in figure 4.1. Steel production continues growing during the next three decades, but the growth levels off. In 2030, production amounts to 818 Mt. This represents a growth of 14% from 2000 levels. The impact of the CO2 tax on the consumption is comparatively small. The maximum decline in the (hypothetical) 20,000 Y/t tax case amounts to 63 Mt (-6.5% of the total production).

igure 4.1: Global steel production 1965-2030 (final products)

igure 4.2 shows the CO2 emissions. The emissions for the period 1965-1965

g EAF f

of

0

200

400

600

800

1000

1200

1965

1975

1985

1995

2005

2015

2025

[Mt/y

r]

BC

CO2tax12

CO2tax25

CO2tax50

CO2tax100

CO2tax200

F Fare almost stable at a level of 2000 Mt, despite a significant increase of production (that is compensated by energy efficiency gains and increasinsteel production). BC emissions decline during the period 2000-2025 to a level o1525 Mt. The gap between the increasing production and the declining emissions can be explained by increasing energy efficiency, increasing scrap availability and fuel switches (including switches in electricity production). The introductiona global CO2 tax has a significant impact on the emissions. They decline by up to 560 Mt in 2015 (-34%) and they decline by up to 1170 Mt (-75%) in 2030.

57


0

500

1000

1500

2000

2500

1965

1975

1985

1995

2005

2015

2025

[Mt C

O2/

yr] BC

CO2tax12

CO2tax25

CO2tax50

CO2tax100

CO2tax200

Figure 4.2: Global CO2 emissions in the steel life cycle, 1965-2030 The changes in foreign trade are shown in figure 4.3. In BC the figures indicate a gradual increase. The model results suggest strong growth of interregional trade in the period 2000-2030 (+250%). A global CO2 tax has no significant effect on trade. However this does not imply that the trade patterns remain unchanged (see the results for Japan below).

0100200300400500600700800900

1000

1965

1980

1995

2010

2025

[Mt/y

r]

BC

CO2tax12

CO2tax25

CO2tax50

CO2tax100

CO2tax200

Figure 4.3: Interregional trade in iron and steel products, 1965-2030 The distribution of production in BC is shown in figure 4.4. The results suggest a gradual decline of steel production in the US, and a gradual increase in Europe and especially China.

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0

100

200

300

400

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OASIALAMERICAMEASTCISNAMERICAEUROPEOCEANIAKOREACHINAJAPAN


Figure 4.4: Distribution of production, 1965-2030, BC Comparison of figure 4.4 and figure 4.5 shows the impact of a CO2 tax on global steel production. The impact is very limited. Production increases in Europe and the US from 2025 onward. Production declines in China. The impact on other regions (including Japan) is rather limited. This result suggests that a global CO2 reduction policy would not affect the competitive position of countries, an important conclusion that opens the way to meaningful emission reductions. Off course the key assumption in this analysis is the establishment of a global tax. In case the tax is only levied in a limited number of countries, the results may look quite different (see below).

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Figure 4.5: Distribution of production 1965-2030, CO2tax50

59


Figure 4.6 shows the global primary energy use, which is almost constant during the period 1965-1995. The 20EJ energy demand can be compared to a total global energy consumption of approximately 400 EJ (5%). However beyond 1995 energy consumption declines by 25%, in line with CO2 emission reduction. The demand for steam coal keeps growing (for electricity production for EAF steel production), while the demand for coking coal in 2030 is reduced to a third of the demand in 1995.

-5000

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[PJ/

yr]

NUCLEAR

HYDROTARFUEL OILSTEAMGASCOKING COALSTEAM COAL

Figure 4.6: Primary global energy use, BC The changing primary energy use due to CO2 taxes is shown in figure 4.7. Total primary energy use declines only marginally. However a significant switch occurs in the fuel mix. Hydro energy, nuclear energy and wood are introduced at the expense of coal. This fuel switch occurs in electricity production.

60


-20000

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BC

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yr]

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STECOA

MIDREX/DRICOREXBFBF old

Figure 4.7: Primary energy use, 2020 Figure 4.8 shows the strong decline in iron production from 600 Mt in 1995 to 400 Mt in 2030. Gas based DRI production disappears after 1995. The combined Corex/DRI steel production is introduced from 2025 onward. This pattern is barely affected by a CO2 tax.

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Figure 4.8: Iron production, BC Figure 4.9 shows the steel production mix. The Open Hearth Furnace disappears gradually. Scrap based EAF steel production shows the strongest growth, but

61


BOF steel production continues growing, too. Note the overestimation of EAF steel production in 1965: the model is not valid in this initial period. The steep increase of EAF steel production in 2000 is caused by the assumed 35-year life span for steel products in the building and construction sector.

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Figure 4.9: Steel production mix 1965-2030, BC Table 4.7 shows the model shadow prices for iron and steel products in 2020. Note that the price for iron is significantly lower than the current market price. The price for a number of EAF products becomes negative, indicating that increased production would not cost money but gain money. The reason is the steel scrap quality that prevents any additional recycling. Instead steel scrap is disposed. The costs for disposal can be saved in case of recycling, causing the negative shadow price. Note the significant price increases caused by CO2 taxes. However because a prices rise in all regions, the effects on competition are rather limited.

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Table 4.7: Changing shadow prices, Japan, 2020 BC CO2tax12 CO2tax25 CO2tax50 CO2tax200 MMFI 2,993 5,741 9,282 12,216 16,336 17,492

2,122 3,777 7,201 9,060 12,170 12,555 MMFIBF 2,628 5,357

CO2tax100

MMFIING 8,877 11,771 15,912 17,045

MMFDRI 9,870 15,815 18,275 21,937 30,386 32,012 MMFLSH 4,698 7,549 10,844 13,894 18,415 19,374 MMFLSL -804 -359 -506 -581 -1,121 -1,152 MMFCSING 7,121 10,542 13,432 17,502 18,588 MMFCSTH 4,503 7,629 11,111 13,935 18,692 19,245 MMFCSTL -79 420 291 209 -462 -516 MMFCI 73,241 75,617 76,818 77,822 79,502 80,148 MMFREB 1,908 2,358 2,245 2,269 1,627 1,547 MMFHRS 14,716 15,462 15,129 17,326 21,418 21,424 MMFWIR 10,687 11,684 11,042 11,859 14,850 14,800 MMFALL 30,322 31,307 30,941 34,320 42,092 41,353 MMFHEP 17,518 21,122 24,930 30,375 37,195 37,942 MMFHRC 12,867 16,081 19,290 23,918 30,968 32,640 MMFCRC 17,924 21,369 24,635 29,511 36,924 38,665 MMFCRCAT 22,341 26,020 29,428 34,834 43,386 45,305 MMFGSH 27,602 31,341 34,584 40,848 51,194 53,310 MMFSIN 2,044 2,398 2,739 3,050 3,509 3,794

BFEAF

4,266

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Figure 4.10: Scrap treatment, BC

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-250-200-150-100-50

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t/yr]

OAFRICA


Figure 4.11: Scrap shipments, BC

64


4.3 Japanese and European stand-alone policies In case only Japan and Europe implement the tax of 1250-5000 Y/t, the emission reduction is less significant than in case of a global tax: a reduction of 93 Mt in 2015 (-5.6%) and a reduction of 114 Mt (-7.5%) in 2030. Global emissions actually increase in case higher taxes are implemented. This effect can be attributed to relocation of production to countries with lower energy efficiency, and increased emissions for transportation.

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CO2tax12JE

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CO2tax100JE

CO2tax200JE

Figure 4.12: Global CO2 emissions in the steel life cycle, 1965-2030, in case Japan and Europe introduce a tax A tax limited to Japan and Europe results in an increase of trade volumes by 50-150 Mt.

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CO2tax25JE

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CO2tax200JE

Figure 4.13: Trade in steel in case of a Japanese/European tax

65


Figure 4.14 shows the production per region in case only Japan and Europe introduce a tax of 5000 EUR/t. Production in Japan declines by 35-50%, production in Europe declines by 35%. Production increases in all other regions by 10-20%.

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Figure 4.14: Distribution of production 1965-2030, CO2tax50JE Table 4.8 shows the carbon leakage effects. Carbon leakage is defined as: CL = Emission increase outside the tax region/ Emission reduction inside the tax region The carbon leakage in the period 2010 to 2030 amounts to 54-75%. This is a clear indication that such a policy would make little sense: all emission reductions in Japan and Europe are balanced by increasing emissions in other regions. Such a tax policy makes only sense in case the industry is protected (e.g. by taxing imports).

66


Table 4.8: Carbon leakage effects in case Japan and Europe introduce a 5000 Y/t tax

Japan/EuropeGlobal tax

[Mt CO2/yr]

Japan/EuropeJE tax

[Mt CO2/yr]

GlobalJE tax

[Mt CO2/yr]

LeakageJE tax

[%]2000 23.3 38.0 16.6 382005 23.3 34.8 22.2 362010 101.4 180.7 82.5 542015 119.4 253.0 93.2 632020 147.3 340.8 113.2 672025 102.5 324.3 80.8 752030 112.9 339.6 114.0 66

Figure 4.15 shows the carbon leakage as a function of the tax level. The leakage increases in time, and it increases for increasing tax levels. Even for a comparatively low tax level of 1250 Y/t CO2, the leakage in 2020 amounts to 35%. The most significant increase of carbon leakage occurs in the range from BC to 5,000 Y/t. For higher tax levels, the increase is small. The results show in no case a leakage in excess of 100%. This result is in contrast with industry claims that leakage would exceed 100% because of relocation of industry to countries with lower energy efficiencies. The model results suggest that developing countries improve their energy efficiency during the next two decades significantly, thus limiting leakage.

igure 4.15: Carbon leakage as a function of the tax level

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age

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F

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Japanese results Figure 4.15 shows the historical steel production and the model results for different policy cases. Historical demand is slightly underestimated in the model. However figures for 1995 match with the actual production data. The decline for future production is in line with other studies, e.g. (Crompton 2000). In case of a global tax, production is not affected. In case of a Japanese/European tax, production is halved in 2020.

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BC

CO2tax50

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Figure 4.15: Japanese crude steel production 1965-2030 Figure 4.16 shows the CO2 emissions. The emissions in 1995 according to the model amount to 232 Mt CO2. This includes 14 Mt CO2 in electricity production. According to statistics, emissions in 1998 amounted to 160 Mt CO2 (including electricity production)(IEE 2000). It is not clear how the emissions from blast furnace gas are accounted for in this statistic. Coal consumption for iron and steel industry and for coke production amounted to 66.1 Mt in 1998. The model indicates a coal consumption of 77 Mt for 1995 and 60 Mt for 2000, in line with the statistics. BC emissions decline from 230 Mt in 1995 to 150 Mt in 2030. in case of a global tax, an emission reduction of 50 Mt is achieved. In case of a tax in Japan and Europe, emissions decline by 120 Mt in 2030. However the bulk of this additional emission reduction can be attributed to a reduction of primary steel output that is compensated by increased imports.

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Figure 4.16: CO2 emissions in the steel life cycle, Japan, 1965-2030 European results European steel production is shown in Figure 4.17. The model production data for 1990 and 1995 are within 5% of the actual production. The model indicates a 5-10% decline of production in case a global tax is implemented, and a 40% decline of production in case of a Japanese/European tax.

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Figure 4.17: European steel production, 1965-2030 Figure 4.18 shows the CO2 emissions in different policy cases. BC emissions decline from 500 Mt to less than 300 Mt in 2030. In case of a global tax, emissions decline by 10-100 Mt. In case of a Japanese/European tax emissions decline by 300-400 Mt (up to 90% emission reduction).

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Figure 4.18: CO2 emissions 1965-2030

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5 Sensitivity analysis The model contains approximately half a million non-zeros. Fortunately a limited number of variables determine to a large extent the model output. The most important variables have been selected for sensitivity analysis. Table 5.1 provides an overview of the sensitivity model runs. Variables for sensitivity analysis have been selected based on experiences from previous modelling exercises (see e.g. Gielen et al. 1996, Gielen and Moriguchi 2001), and they have been selected in order to assess the special features of the models (in case of the market mechanism and trade barriers). Table 5.1: Overview of sensitivity model runs Standard runs Sensitivity analysis 1 Interest rate 8% 3% 2 Price elasticity -0.2 -0.5 3 Gas price Gas 550 Y/GJ

(2020) Gas 400 Y/GJ (2020)

4 Technology mix

No CCF CCF

5 Technology mix

CO2 removal No CO2 removal

6 Technology mix

CO2-free electricity No CO2-free electricity

7 Market mechanism

Ideal market Regional monopoly

8 Trade barriers No regulatory barriers/tariffs

+2,500 Y/t

The discussion of results is limited to the key environmental issues in this study. Other variables may also be affected, but are not discussed in more detail. 5.1 Interest rate Figure 5.1 shows the impact of the interest rate on GHG emissions. The real interest rate (excluding inflation) has been decreased for 8% (an industry perspective) to 3% (a government perspective). In case of a tax of 2,500 Y/t Co2, emissions are initially lower in case of a lower interest rate, but emissions from 2020 onward are identical for the 8% interest rate and the 3% interest case. The initial gap can be explained by differences in electricity production (it is more attractive to build capital intensive hydropower plants or nuclear plants instead of coal fired power plants in case of low interest rates. However these plants are introduced in the 8% interest case at the 2,500 Y/t tax level, too.

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REF 8%

3%

Figure 5.1: CO2 emissions in case of 3% interest rate, tax 2,500 Y/t CO2 5.2 Higher price elasticity In the reference calculations the demand elasticity was set at –0.2, based on (Mannaerts, 2000). In the authors engineering experience, such a low elasticity is surprising. Ample engineering data exist that materials savings of 25-50% are technically feasible for limited additional cost. As a consequence a sensitivity analysis has been done with an elasticity of –0.5. The results are shown in figure 5.1. For a tax of 10,000 Y/t, the reference calculation (E=-0.2) shows a demand reduction of 60 Mt in 2020 (-6%), while the higher elasticity (E = -0.5) results in a demand reduction of 150 Mt (-16%). The impact on CO2 emissions is of a similar order of magnitude: the emission reduction declines by 65 Mt in 2020 (-6%). These results indicate that the elasticity is a key parameter, and more research regarding long-term future elasticities is strongly recommended.

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Figure 5.1: Iron and steel demand for different elasticities

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5.3 Lower gas price The impact of the gas price has been analyzed in a sensitivity analysis at the 2,500 Y/t tax level where the gas price has been lowered to a level of 400 Y/t in Japan (and lower elsewhere, see annex 4), compared to 550 Y/t in the reference calculation. The results showed no difference compared to the reference calculations. This suggests that the results are fairly robust with regard to the gas price. 5.4 Technology mix: including smelting reduction CCF technology represents an example of smelting reduction technologies that use coal and ore input (instead for pellets and coke for the blast furnace) in order to produce liquid iron. CCF has been simulated by changing the input for Corex from pellets to iron ore. In the BC, CCF iron production amounts to 25-30 Mt in 2025. The results for the 10,000 Y/t case show an increased CCF iron production (approx. 40 Mt from 2020 onward). CO2 emissions amount to 1030 Mt in 2020 (compared to 500 Mt in the reference calculations) emissions from 2025 onward are approximately 50 Mt higher than in the reference calculations. Still, the blast furnace remains the dominant iron production technology. 5.5 Technology mix: no CO2 removal CO2 removal contributes significantly to the total emission reduction. However the future of this strategy is by no means certain. For example local residents may object to disposal. Another problem is the long-term effect of CO2 storage. Some authors claim the CO2 may escape in case of cap rock leakages, resulting in a zero storage effect over a period of decades. As a consequence the case has been considered without CO2 storage (for a tax of 10,000 Y/t). Only a high tax level has been analyzed because this option is comparatively costly and the option is not applied in the reference calculations at lower tax levels. The resulting CO2 emissions are shown in figure 5.2. CO2 emissions after 2015 are approximately 600 Mt higher (emission reduction declines from 1100 Mt to 500 Mt). Figure 5.3 shows the iron production. Comparison with figure 4.8 (BC) shows no significant differences (more CCF in 2020).

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Figure 5.2: CO2 removal with and without CO2 removal

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Figure 5.3: Iron production, tax 10,000 Y/t, no CO2 removal 5.6 Technology mix: no CO2 free electricity Figure 5.4 shows the CO2 emissions in case of a 10,000 Y/t tax and no CO2-free electricity (and no biomass for charcoal injection). The CO2 emissions after 2015 are approximately 600 Mt higher. This shows the importance of electricity for the emissions throughout the iron and steel life cycle.

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Figure 5.4: CO2 emissions without CO2-free electricity, tax 10,000 Y/t 5.7 Market mechanism: monopolies Increasing scale of steel companies is an ongoing trend. This will affect the market structure, which will change from a market with many suppliers to a market of a few suppliers. One extreme has been analyzed in this study: regional monopolies (one supplier per region). This supplier has to compete with steel producers from other regions. It is assumed that these trends towards increased scale occur in the OECD countries, in China and in the CIS region. Producers in other developing regions (Latin America, Africa, Other Asia and the Middle East) remain of a smaller scale, resulting in competition. Because the regions compete amongst each other, the resulting market type could also be characterized as a global oligopoly. A natural limit is set to the profit maximization of the regional monopolist, given by the market entrance price levels for foreign producers. Two cases have been analyzed: a base case and a case of a 5,000 Y/t tax.

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Figure 5.5: Steel production in case of a regional monopoly

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Figure 5.6: CO2 emissions in case of a regional monopoly 5.8 Introduction of import tariffs One way to overcome the problem of carbon leakage is to erect trade barriers. Import tariffs are an example of effective barriers. Such barriers may even comply with the GATT agreement in case the environmental incentives are clear (e.g. on the basis of studies such as this one). The impact of trade barriers on carbon leakage is shown in table 5.2. A negative leakage indicates that emissions decrease globally while the decrease within the region, too. One must keep in mind that the reference for these calculations is the base case without import tariffs. In case trade tariffs would be introduced in the base case, emissions may decrease, too, for example because production is relocated from developing countries (cheap labor, low energy efficiency) to industrialized countries (expensive labor, high energy efficiency). The break-even point (0 carbon leakage) is reached at an import tariff between 2,500 and 5,000 Y/t. Table 5.2: Carbon leakage for increasing import tariffs in Japan and Europe, tax 2,500 Y/t CO2

Tariff No tariff 2,500 Y/t 5,000 Y/t 10,000 Y/t 20,000 Y/t2010 83 69 58 65 682015 59 10 -13 -17 -202020 84 7 -11 0 -122025 128 -48 -113 -110 -107

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5.9 Overview of sensitivities Table 5.3: Overview of sensitivity model runs, in comparison to reference calculations Policy regime Change of iron and

steel production 2020 [Mt/yr]

Change of CO2 emissions 2020 [Mt/yr]

1 Interest rate 2,500 Y/t 0 0 2 Price elasticity 10,000 Y/t -90 -65 3 Gas price 2,500 Y/t 0 0 4 Technology

mix CCF 10,000 Y/t +20 Mt CCF +500

5 Technology mix CO2 removal

10,000 Y/t -10 +600

6 Technology mix CO2 free electricity

10,000 Y/t -30 +500

7 Market mechanism regional monopoly

BC/5,000 Y/t -195/-165 -310/-300

8 Import tariff 2,500-5,000 Y/t

2,500 Y/t 0 -50

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6 Conclusions During the last decades the environmental performance of the iron and steel industry has been improved significantly. The emission of CO2 is one of the remaining environmental challenges for this industry sector. Globally 6-7% of the GHG emissions are caused by iron and steel production (approximately 2000 Mt CO2 per year). The emissions are decreasing autonomously because of a steel demand that grows at a rate below the demand for other energy services, a gradual change in the sector structure from primary to secondary steel, and an increasing energy efficiency in primary steel production that is driven by technological progress. Emissions decline autonomously to a level of 1500 Mt in 2025 (-25% compared to 1995 levels), despite finished iron and steel output increases by 25% in the same period. As a consequence the autonomous decoupling amounts to a factor 1.67. 6.1 GHG emission reduction potentials The Japanese iron and steel industry may be affected significantly by CO2

policies because its relevance from a national GHG perspective. The Japanese steel industry emits 13% of the total national GHG emissions (approximately 160 Mt per year). This fraction is 2-3 times higher that the global contribution of the iron and steel industry. However in recent years emissions have been declining because of declining primary steel production. The energy efficiency of Japanese steel producers is among the highest in the world. However this does not mean that the technical potential for CO2 emission reduction is exhausted. A number of options exist to reduce the emissions even further. An overview is provided in table 6.1.

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Table 6.1: Overview of emission reduction options for the iron and steel industry. Figures in brackets indicate the potential for 2020 Category Option Potential 2010

(potential 2020) [Mt CO2/yr]

Cost18 [Y/t CO2]

Energy efficiency

Coal injection 8.9 (8.9) 0

Near net shape casting

1.0 (4.5) -10,000-0

Energy recovery

3.2 (3.2) ?

Smelting reduction

10 (50) 0

Fuel switch DRI/Natural gas

20 (70) 1000-2000

Charcoal 10 (35) 2000-5000 Waste plastics 15 (15) 0 CO2 storage Oceanic 0 (>100) 2000-5000 Deep aquifers 2000-5000 Materials efficiency

5 (20) -10,000-10,000

JI/CDM China 55 (0) 0-2000 Tree

plantations 2 (10) 0-2000

Some of these options are characterised by zero or even negative cost. As a consequence they could be implemented without major negative impacts on the industry competitiveness, in fact they may even enhance the industrial competitiveness. However in a number of cases the technology is not yet fully developed, which may pose a barrier for rapid introduction. Options in this category include increase powder coal injection rates, enhanced energy recovery from blast furnace gas, smelting reduction technology, near net shape casting and waste plastic injection in blast furnaces. R&D should focus on the development of such technologies. In a number of other cases, significant costs arise. This is especially true in the case of CO2 storage. Introduction of such technology will affect the competitiveness of the national industry negatively, unless similar policies are introduced in other countries. This is also the case for the import of DRI and the use of charcoal or electricity for iron production. The potentials in table 6.1 cannot be added straightforward because options compete and interact. For example if EAF steel recycling replaces BF-BOF steel

18 Costs are expressed relative to a business-as-usual situation

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making, emission reductions in BF-BOF steel making become infeasible. As a consequence integrated assessment is required for proper analysis. On a global scale, the energy efficiency differs significantly. Outdated steel production practices in developing countries are characterised by coal consumption rates that are 50%-100% higher than Japanese coal consumption rates. In case all global steel producers would be brought to the highest possible energy efficiency standard, CO2 emissions would be reduced by approximately 500 Mt per year. Because many of these emission reductions are cost-effective and the emission reduction potentials are significant on a global scale, the iron and steel industry should consider options within the sector instead of buying emission reduction permits of unclear origin. 6.2 The impact of GHG emission taxation on the iron and steel industry The STEAP model has been developed in order to study the economic impact of a CO2 tax on the global steel industry. Model calculations suggest an ongoing shift from primary steel to scrap based steel production. This shift is driven by increasing scrap qualities and declining demand growth. New iron and steel production technologies do not gain a dominant position. This can be explained by the technology lock-in, caused by the long life span and high sunk cost of primary steel making plants. In case of global emission taxation, the impact on the selection of production locations is limited. Because the steel demand is comparatively inelastic to price changes, the production remains almost at the same level. In such a situation a 50% emission reduction is possible. In case Japan and Europe would implement a tax and other regions would not follow suit, the impact on Japan would be limited. However the impact on Europe would be a very substantial reduction of production. The emissions within both regions decline substantially but the emissions increase in other regions. The carbon leakage (the increase of foreign emissions divided by the emission reduction in Japan and Europe) amounts to 50-80%. Given the economic impacts, such a policy does not seem attractive unless measures are introduced in order to prevent carbon leakage. However GATT may prevent the introduction of such measures. A significant potential exists for improved materials efficiency. This potential is generally neglected in energy efficiency and CO2 reduction studies. Improved steel qualities can be of similar importance for CO2 emission reduction as increased energy efficiency. Assuming a moderate global efficiency potential of 10%, the emission reduction potential amounts to 150 Mt CO2 per year. It remains to see if this potential will be used to its full extent in the next decades.

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6.3 Consequences for R&D The results indicate a number of areas where more research is warranted:

- The combined Corex/DRI production process; - Increased materials efficiency; - CO2 removal and storage; - Near net shape casting; - CDM based CO2 emission reduction in steel industries in China, India, and

the former USSR - Removal of impurities from steel scrap in order to enable high grade

recycling.

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Feber, M.A.P., Gielen, D.J. 2000: Biomass for greenhouse gas emission reduction. Task 7: Energy Technology characterisation. Netherlands Energy Research Foundation. Fischer, G., Schrattenholzer, L. (in press): Global energy potentials through 2050. Biomass and bioenergy, 2000. Fonner, F. 2001: Nucor steel – Berkeley expands flat rolled capacity. AISI Steel Technology March, pp. 20-25. Francois, J.F. 1998: Scale economies and imperfect competition in the GTAP model. GTAP technical paper no. 14. Via internet: http://www.agecon.purdue.edu/gtap/ Fritz, D. 1999: Latest EAF statistics from IISI. AISE steel technology magazine November 1999. Via Internet: http://www.aise.org/magazine/99nov65_67.htm Furokawa, T. 1997: Recovering zinc and iron from EAF dust at Chiba works. Via Internet: http://www.newsteel.com/features/NS9706F4.HTM Furokawa, T. 1998: Japan’s search for “ultra steel”. Via Internet: http://www.newsteel.com/features/Ns9803f5.htm Gielen, D.J., Dril, A.W.N. van 1997a: The Basic Metal Industry and Its Energy Use. Prospects for the Dutch Energy Intensive Industry. ECN—C-97-019. Petten, March 1997. Via Internet: http://www.ecn.nl/unit_bs/etsap/markal/matter/ Gielen, D.J., Dril, A.W.A. van 1997b: Long Term Energy and Materials Strategies for Reduction of CO2 Emissions. A case study for the iron and steel industry. In: M. Olszewsky (ed.): ACEEE summer study proceedings, ACEEE, Washington DC. Gielen 1999: Materialising dematerialisation. Integrated energy and materials system optimization for GHG emission reduction. PhD thesis Delft University of Technology, the Netherlands. ISBN90-5155-008-1. Gielen,D.J., Dril, A.W.N. van 1999: CO2 reduction strategies in the Basic Metals Industry: A Systems Approach. In: B. Mishra (ed.): 1999 EPD Congress proceedings, San Diego, USA, February 28-March 4, 1999. The Minerals, Metals and Materials Society, Washington DC, USA. D.J. Gielen and H. Yagita 2001. Assessment of CO2 emission reduction strategies for the Japanese petrochemical industry. Journal of Industrial Ecology 4, issue 3, in press. Gielen, D.J., Yagita, H. in press: The long term impact of GHG reduction policies on global trade. A case study for the petrochemical industry. European Journal of Operational Research. Gielen, D.J. and Moriguchi, Y. 2001: The interaction of environmental policies. A case study for Japan. National Institute for Environmental Studies, Tsukuba, Japan. Gielen, D.J. and Moriguchi, Y. in press: Modelling of materials policies. Submitted to Environmental Modelling & Assessment. Grübler, A. 1993: Emission reduction at the global level. Energy 18 (5), 539-581 International Energy Agency 1996: World energy outlook. IEA/OECD, Paris, 1996. IEA 1999: Ocean storage of CO2. IEA greenhouse gas R&D programme.

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ISBN 1 898373 25 6. Via Internet: http://www.ieagreen.org.uk/ocean.htm IEA 1999: Energy balances of OECD countries. 1996-1997. IEA/OECD, Paris. UNFCCC 2001: UNFCCC greenhouse gases inventory database. Via Internet: http://www.unfccc.de IEA 2000: Coal information 2000. IEA/OECD, Paris. IEE 2000: Handbook of Energy & Economic Statistics in Japan. The Energy Conservation Center, Tokyo. IISI 1994: Competition between steel and aluminium for passenger cars. Brussels, Belgium. IISI 1998: Energy use in the iron and steel industry. International Iron and Steel Institute, Brussels, Belgium. IISI 2001: Steel statistics. Via internet: http://www.worldsteel.org/ International Trade Administration 2000: Global steel trade. Structural problems and future solutions. US Department of Commerce. Via Internet: http://www.ita.doc.gov/media/steelreport726.htm Ishikawa, M., Fujii, Y., Tonooka, Y. 1994: Carbon dioxide reduction potential of steel industry in Japan. In: Yamamoto R. et.al. (eds): Advanced Materials ’93. Trans. Mat. Res. Soc. Jpn., Volume 18A, pp. 369-372. Elsevier, Amsterdam. Jiang, K., Hu, X., Matsuoka, Y., Morita, T. 1998: Energy technology and CO2 emission scenarios in China. Environmental economics and policy studies vol. 1 no. 2, pp. 141-160. Jennings, N.S. 1997: Steel in the new millennium: Nine case studies. Working paper SAP 2.62/WP.112. International Labour Organization, Geneva. Loulou R., Lavigne, D. 1996: MARKAL model with Elastic Demands: Application to Greenhouse Gas Emission Control. In: C. Carraro, A. Haurie (eds.): Operations research and environmental management, pp. 201-220. Kluwer Scientific Publishers, Dordrecht, the Netherlands. Mannaerts, H. 2000: STREAM: Substance throughput related to economic activity model. A partial equilibrium model for material flows in the economy. CPB research memorandum no. 165, the Hague. ISBN 90 5833 042 7 MATTER 2000: MATTER4.2 model database. Via internet: http://www.ecn.nl/unit_bs/etsap/markal/matter/ METI 2000: White paper concerning quantitative aims for reducing industrial dioxin emissions. Via Internet: http://www.meti.go.jp/english/report/data/gDioxin01e.html Mistry S. 1999: Capacity expansion curb by Posco to help arrest decline in steel prices. Via Internet: http://www.expressindia.com/fe/daily/19990726/fec26022.html MITI 2000: Yearbook of iron and steel statistics 1999. Research and Statistics Department Minister’s Secretariat. Ministry of International Trade and Industry, Tokyo. Monastersky R. 1999: Good-bye to a greenhouse gas. Dumping carbon dioxide underground or in the oceans could slow global warming. Science News online June 19. Via Internet: http://www.sciencenews.org/sn_arc99/6_19_99/bob1.htm Nijkerk A. (1994) Handbook of recycling technologies. In Dutch. Novem/NOH no. 9451, Utrecht.

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Annex 1: Overview of energy carriers and materials in the STEAP model EN energy carriers STECOA Steam coal COKCOA Coking coal COK Coke COALINJ Energy injection in blast furnace GAS Natural gas BFGAS Blast furnace gas COGAS Coke oven gas COREXGAS Corex gas ELE Electricity STE Steam FUO Fuel oil WOD Wood TAR Tar ENEND(EN) endogenous energy carriers (produced and consumed within the system) COK COALINJ BFGAS COGAS COREXGAS ELE

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M materials MMFI Liquid iron for use in steel plants MMFIING Iron ingots MMFIBF Liquid iron from blast furnace MMFDRI Direct reduced iron MMFLSH Liquid steel high quality MMFLSL Liquid steel low quality MMFCSING Cast steel ingots MMFCSTH Cast steel liquid high quality MMFCSTL Cast steel liquid low quality MMFCI Cast iron MMFREB Rebars MMFHRS Hot rolled sheet MMFWIR Wire rod MMFALL Alloy steel MMFHEP Heavy plate MMFHRC Hot rolled coil MMFCRC Cold rolled coil MMFCRCAT Cold rolled coil, annealed and tempered MMFGSH Galvanised sheet MMFSIN Sinter MMFPEL Pellets OXY Oxygen CO2REM CO2 removed W waste materials WMF Prepared steel scrap WMFBULK Steel scrap, pure WMFDIL Steel scrap, diluted with other materials (e.g. shredder scrap) WMFMSW Steel scrap in municipal solid waste R natural resources MMFORE Iron ore MMFLIM Limestone MMFALLOY Alloying elements AIR Air DISP Disposal space BFS Blast furnace slag

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Annex 2: Overview of processes in the STEAP model E01 Electricity production from BF gas E02 Electricity production from natural gas E03 Wood gasifier E04 Electricity production from coal conventional E05 Electricity production from coal advanced E06 Nuclear electricity E07 Hydro electricity E08 Oil fired power plants GA1 Steam production IIO Oxygen production IS2 Sinter plant IS3 Pelletising plant IS4 Blast furnace IS5 Basic oxygen furnace IS6 Continuous casting high quality steel IS61 Near net shape casting high quality steel IS7 Hot strip mill IS8 Plate mill IS9 Wire rod mill ISA Heavy section mill ISB Rebar mill ISC Cold rolling mill ISD Hot dip galvanising ISE Annealing and tempering ISF Electrogalvanising ISG Electric arc furnace scrap fed ISH Electric arc furnace DRI fed ISI Continuous casting low quality steel ISI1 Near net shape casting low quality steel ISJ Steel ingot casting ISK Steel ingot reheating ISL Pig iron casting ISM Pig iron reheating ISN Open hearth furnace ISO Hot connection ISP Blast furnace small scale 1 Mt IT1 Cupola cast iron production IT2 EAF alloy steel production including finishing IU1 Corex IU2 DRI production gas based IU3 DRI production corex gas based IV1 Coke oven recovery wet quenching IV2 Coke oven recovery dry quenching IV3 Coke oven non recovery

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IV4 Coke beehive oven IV5 Charcoal traditional IV6 Charcoal advanced XA1 Dummy coke oven gas to regular gas XA2 Dummy iron to steel scrap XA3 Dummy high quality steel to low quality steel XA4 Dummy scrap disposal XA5 Dummy BF gas to gas XA6 Dummy ele surplus use XA7 Dummy corex gas to BF gas XA8 Dummy coal injection XA9 Dummy coke use instead of coal injection XA10 Dummy oil injection XA11 Dummy plastic waste injection XA12 Dummy plasma injection XA13 BF gas CO2 removal XA14 Coke oven gas CO2 removal XA15 Corex gas CO2 removal XA16 Gas based DRI CO2 removal XA17 Dummy DRI to scrap XA18 Dummy steel scrap and DRI mixing for upgrading XA19 Dummy historical losses XB1 Bulk scrap collection and separation shredders etc XB2 Diluted bulk scrap large distance and mixed with other materials XB3 Scrap in municipal solid waste collection and magnetic separation XB4 Diluted scrap disposal XB5 Scrap in municipal solid waste disposal ZA1 CO2 storage deep sea ZA2 CO2 storage deep saline aquifers ZA3 CO2 storage depleted oil and gas fields

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Annex 3: Transportation cost and trade tariffs Transportation costs are split into transportation costs for finished steel products and bulk commodity transportation costs. The costs for packaging and the handling costs are considerably higher for finished steel products. Moreover the size of shipments is generally smaller. As a consequence total transportation costs are much higher. Table A3.1: Assumptions regarding sea borne transportation costs for finished steel products, CIF, in Yen of 2000 (Gielen and Dril 1997) JAPAN CHINA KOREA OCEANIA EUROPE NAMERICA CIS MEAST LAMERICA OASIA JAPAN CHINA 2000 KOREA 1500 1500 OCEANIA 3000 3000 3000 EUROPE 10000 10000 10000 8000 NAMERICA 3000 3000 3000 4000 3000 CIS 12000 6000 10000 12000 3000 6000 MEAST 4000 4000 4000 4000 2000 6000 2000 LAMERICA 10000 10000 10000 10000 4000 2000 4000 4000 OASIA 3000 3000 3000 3000 6000 10000 6000 6000 6000 OAFRICA 6000 6000 6000 6000 5000 8000 5000 5000 5000 5000 Table A3.2 shows examples of bulk commodity transportation costs. Vessel size and route are important variables (the route determines if a return load exists, which halves costs). Table A3.2: Transportation costs 1999 (1 US$ = 110 Y) (IEA 2000) [Y/t] Iron ore 150 kt Tubarao/Rotterdam (Capesize)

350-725

Iron ore 140 kt W. Australia/Beilun (Capesize)

300-630

Grain 50 kt US Gulf/Japan (Panamax)

1375-2550

Grain 50 kt US Gulf/MEAST (Panamax)

900-1500

The waterfront charges (port authority, ancillary, terminal) and taxes and royalties must be added to the commodity transportation costs in table A3.2. In the case of coal they range from 5 U$/t to 10 US$/t (550-1100 Y/t) (IEA, 2000). They are probably similar for other commodities. Apart from the seaborne transportation costs, in land-transportation can be costly. For example US steel producers in Pittsburg (IEA, 2000) or German steel makers in the Ruhr area face significant additional costs (Gielen and Dril 1997). Rail transportation costs (including loading/unloading) amount to 1000 Y/1000 km. Given the global character of the model such detailed cost data cannot be used. Bulk transportation cost estimates are listed in table 4.3.

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Table A3.3: Assumptions regarding bulk transportation costs JAPAN CHINA KOREA OCEANIAEUROPE NAMERICACIS MEAST LAMERICA OASIA OAFRICAJAPAN

CHINA 500

KOREA 500 500

OCEANIA 750 750 750

EUROPE 2000 2000 2000 2000

NAMERICA 2000 2000 2000 2000 750

CIS 2000 1500 1500 3000 1500 3000

MEAST 1500 1500 1500 1500 1500 2000 2000

LAMERICA 1250 1250 1250 1250 1000 1000 1500 1250

OASIA 750 750 750 750 1000 1250 1500 500 1250

OAFRICA 1000 1000 1000 1000 1000 1000 1250 750 750 5000

Table A3.4: Relative seaborne transportation costs in time (2000=1) 1965 31970 1.51975 1.41980 1.31985 1.21990 1.11995 12000 12005 0.952010 0.932015 0.92020 0.892025 0.882030 0.872035 0.862040 0.85 Table A3.5: Non-tariff barriers [Y/t] 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015JAPAN 20000 20000 20000 15000 15000 15000 10000 5000 2500 2500 0CHINA 5000 5000 5000 5000 5000 5000 5000 5000 2500 2500 0KOREA 2000 2000 2000 2000 2000 2000 2000 2000 1000 1000 0OCEANIA 0 0 0 0 0 0 0 0 0 0 0EUROPE 2000 2000 2000 2000 2000 2000 2000 2000 1000 1000 0NAMERICA 2000 2000 2000 2000 2000 2000 2000 2000 1000 1000 0CIS 5000 5000 5000 5000 5000 5000 5000 5000 2500 2500 0MEAST 0 0 0 0 0 0 0 0 0 0 0LAMERICA 5000 5000 5000 5000 5000 5000 5000 5000 2500 2500 0OASIA 20000 20000 20000 20000 15000 10000 10000 10000 5000 5000 0OAFRICA 0 0 0 0 0 0 0 0 0 0 0 Trade tariffs have been estimated on the basis of average trade tariffs for primary industrial commodities. In fact trade tariffs vary per steel product and per country within a region.

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Table A3.6: Trade tariffs, 2000 (World Bank 2000) JAPAN CHINA KOREA OCEANIA EUROPE NAMERICA CIS MEAST LAMERICA OASIA OAFRICA MMFI 1250 2500 1750 125 1250 750 1250 1500 1250 3125 1250 MMFIING 1250 2500 1750 125 1250 750 1250 1500 1250 3125 1250 MMFIBF 1250 2500 1750 125 1250 750 1250 1500 1250 3125 1250 MMFDRI 1500 3000 2100 150 1500 900 1500 1800 1500 3750 1500 MMFLSH 1500 3000 2100 150 1500 900 1500 1800 1500 3750 1500 MMFLSL 1500 3000 2100 150 1500 900 1500 1800 1500 3750 1500 MMFCSING 1700 3400 2380 170 1700 1020 1700 2040 1700 4250 1700 MMFCSTH 1700 3400 2380 170 1700 1020 1700 2040 1700 4250 1700 MMFCSTL 1700 3400 2380 170 1700 1020 1700 2040 1700 4250 1700 MMFCI 10000 20000 14000 1000 10000 6000 1000

0 12000 10000 25000 10000

MMFREB 2000 4000 2800 200 2000 1200 2000 2400 2000 5000 2000 MMFHRS 2500 5000 3500 250 2500 1500 2500 3000 2500 6250 2500 MMFWIR 2300 4600 3220 230 2300 1380 2300 2760 2300 5750 2300 MMFALL 20000 40000 28000 2000 20000 12000 2000

0 24000 20000 50000 20000

MMFHEP 2500 5000 3500 250 2500 1500 2500 3000 2500 6250 2500 MMFHRC 2200 4400 3080 220 2200 1320 2200 2640 2200 5500 2200 MMFCRC 3000 6000 4200 300 3000 1800 3000 3600 3000 7500 3000 MMFCRCAT 3000 6000 4200 300 3000 1800 3000 3600 3000 7500 3000 MMFGSH 3200 6400 4480 320 3200 1920 3200 3840 3200 8000 3200 MMFSIN 200 400 280 20 200 120 200 240 200 500 200 MMFPEL 100 200 140 10 100 60 100 120 100 250 100

Table A3.4: Trade tariff trends 1965-2040 1965 4 1970 3 1975 2.5 1980 1.5 1985 1.5 1990 1.5 1995 1.5 2000 1 2005 1 2010 0.8 2015 0.7 2020 0.6 2025 0.5 2030 0.5 2035 0.5 2040 0.5

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ANNEX 4: Investment costs, labour costs, energy and resource costs relative to Japan Table A4.1: Relative energy costs (Japan = 1) JAPAN CHINA KOREA OCEANIA EUROPE NAMERICA CIS MEAST LAMERICA OASIA OAFRICA COA 1 0.5 1 0.5 1 0.75 0.5 1 0.75 1 0.5 GAS 1 0.75 1 0.5 0.7 0.8 0.5 0.3 0.75 0.75 1 FUO 1 0.8 1 1 0.9 0.9 0.7 0.5 0.75 1 1 CHAR 1 0.7 1 1 0.9 1 0.7 1 0.5 0.75 0.5 TAR 1 0.8 1 0.7 0.9 0.9 0.7 0.8 0.75 1 1 Table A4.2: Coking coal prices for industry (IEA, 2000) (1 US$ = 110 Y; 28 GJ/t). In the case of Japan, prices for the iron and steel industry are approximately 5% below the industrial average price. 1980 1985 1990 1995 2000Japan [US$/t] 65.90 59.52 61.12 54.91 48.86OECD Europe [US$/t] 75.65 58.00 61.18 59.60 39.36USA [US$/t] 61.20 59.10 52.01 51.52 50.67Japan [Y/GJ] 258 234 240 216 192OECD Europe [Y/GJ] 297 228 240 234 155USA [Y/GJ] 240 232 204 202 199 Table A4.3: Relative resource costs (Japan = 1) JAPAN CHINA KOREA OCEANIA EUROPE NAMERICA CIS MEAST LAMERICA OASIA OAFRICA MMFORE 1 1 1 0.5 1 1 1 1 0.5 1 0.75 MMFLIM 1 0.5 1 0.5 0.5 0.5 1 1 0.5 0.5 0.5 MMFALLOY 1 1 1 1 1 1 0.75 1 1 1 1 DISP 1 0.2 1 0.1 1 0.3 0.1 0.1 0.1 0.2 0.2 AIR 1 1 1 1 1 1 1 1 1 1 1 BFS 1 1 1 0.5 1 1 1 1 1 1 1 Table A4.4: Relative investment costs (Japan = 1) Japan 1 China 1 Korea 1 Oceania 1.25 Europe 1 Namerica 0.8 CIS 1.25 MEAST 1.5 Lamerica 1.5 Oasia 1.25 Oafrica 1.25

94


Table A4.5: Relative labour costs (Japan = 1) Japan 1 China 1 Korea 1 Oceania 1.25 Europe 0.9 Namerica 1.75 CIS 1 MEAST 1 Lamerica 1 Oasia 0.75 Oafrica 0.75

95


Table A4.6: Labour productivity analysis (IISI 2001, Jennings 1997)

Workforce (1000) 1974 1990 1995 1996 1997 1998 1999Production [%]

BF [%]

EAF %]

Labour productivity[t/cap.yr]

Austria 44 21 13 13 12 12 12 5.2 90.7 9.3 420Belgium 69 26 24 23 21 20 20 10.9 82.2 17.8 493Finland 10 10 7 7 7 8 7 4.0 77.6 22.4 502France 158 46 39 39 38 38 38 20.2 62.4 37.6 432Germany (1) 232 125 93 86 82 80 78 42.1 70.8 29.2 462Italy 96 56 42 39 37 39 39 24.9 42.2 57.8 456Luxembourg 23 9 6 5 5 4 4 2.6 - 100.0 310Netherlands 25 17 13 12 12 12 12 6.1 97.9 2.1 514Spain 89 36 25 24 23 23 22 14.9 28.1 71.9 434Sweden 51 26 15 14 14 14 13 5.1 64.0 36.0 324United Kingdom 194 51 38 37 36 34 31 16.3 77.6 22.4 474European Union (total) 998 434 321 306 293 290 280 155.2 61.9 38.1 449Canada 77 53 54 53 53 55 57 16.2 58.5 41.5 227United States 521 204 171 167 163 160 153 97.3 53.8 46.2 488Japan 459 305 252 240 230 221 208 94.2 69.5 30.5 384South Korea n/a 67 67 66 65 64 64 41.0 58.4 41.6 508Australia 42 30 22 21 20 20 24 8.2 84.5 15.5 314Developing countries Brazil 118 115 78 79 74 63 59 25.0 78.1 21.9 378Russia 600 51.5 58.9 12.8 80South Africa 100 112 76 71 70 61 55 7.3 62.1 36.6 108India 50-100China 3 000 123.7 66.3 15.8 38

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Table A4.7: Indexes of hourly compensation costs for production workers in manufacturing, 29 countries or areas and selected economic groups, 1991-1999 (Index, U.S. = 100)(US Department of Labor, 2000) Country or area 1991 1992 1993 1994 1995 1996 1997 1998 1999 North America United States 100 100 100 100 100 100 100 100 100 Canada 111 107 100 94 94 94 90 84 81 Mexico 12 13 15 15 9 9 10 10 11 Asia and Oceania

Australia 87 81 76 84 89 95 91 80 83 Hong Kong 23 24 26 27 28 29 30 29 28 Israel 56 56 53 54 61 64 66 64 62 Japan 94 102 116 127 139 119 107 98 109 Korea 30 32 34 38 42 46 29 35 New Zealand 53 48 48 52 58 61 59 48 48 Singapore 28 31 32 37 43 47 45 42 37 Sri Lanka 3 2 3 3 3 3 3 3 -

Taiwan 28 32 32 33 35 34 32 28 29 Europe Austria 116 126 122 128 147 140 120 119 114 Belgium 127 137 130 137 155 147 125 124 119 Denmark 118 126 116 120 140 136 121 122 120 Finland 136 124 101 113 140 132 117 116 110 France 100 109 102 105 116 113 98 98 94 Germany, Former West

145 158 153 158 184 176 152 147 140

Germany, Unified - - 148 153 178 171 147 143 136 Greece 45 47 44 46 53 54 50 48 - Ireland 76 82 72 74 79 79 74 72 71 Italy 118 120 96 94 94 100 96 92 86 Luxembourg 110 119 114 121 136 127 104 100 - Netherlands 116 125 121 123 140 131 115 113 109 Norway 139 143 122 124 142 142 130 126 125 Portugal 27 32 27 27 31 32 29 29 - Spain 79 84 70 68 75 76 67 65 63 Sweden 142 153 107 110 125 138 122 118 112 Switzerland 139 144 137 148 170 160 132 131 123 United Kingdom 88 89 75 76 80 80 85 88 86 Trade-weighted measures 3

All 28 foreign econ.

86 89 87 89 95 91 84 79 79

OECD 4 93 96 94 96 103 98 90 85 86 less Mexico, Korea 5

107 111 108 110 118 112 103 98 98

Europe 115 122 111 114 128 125 112 110 106 European Union 114 121 110 112 126 123 111 109 105 Asian NIEs 28 30 31 34 37 39 37 31 32

43

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Annex 5: Assumptions for demand forecast Table A5.1: GDP growth rate [%/yr] 2000-

2005 2005-2010

2010-2015

2030-2035

2035-2040

2015-2020

2020-2025

2025-2030

JAPAN 2 2 1.5 1.5 1 1 1 1 5 3 2 3 2 1 1 1 1 1

OCEANIA 4 4 3 3 2 2 1 1 EUROPE 2 2 2 2 2 1 1 1 NAMERICA 2 2 2 2 1 1 1 1 CIS 5 5 5 5 4 4 3 3 MEAST 2 2 1 1 1 1 1 LAMERICA 3 3 3 3 3 3 2 2 OASIA 2 2 2 2 2 2 2 2 OAFRICA 2 2 2 2 2

CHINA 6 4 2 2 2 KOREA 4

2

2 2 2 Table A5.2: Income elasticities 2000-

2005 2005-2010

2010-2015

2015-2020

2020-2025

2025-2030

2030-2035

2035-2040

PACK 1.5 1.5 1.5 1.5 1.5 1.5 1.5 1.5 TRANS 1.5 1.5 1.5 1 1

1

1 1 1 MACH 1 1 1 1 1 1 1 1 CONSTR 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 FABMETPR 1 1 1 1 1 1 1 1 ELMACH 1 1 1 1 1 1 1 1 OTHMAN 1 1 1 1 1 1 1 LOSS 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 Table A5.3: Autonomous efficiency gains [%/yr] PACK 0.5 TRANS 1 MACH 0.2 CONSTR 1 FABMETPR 0.2 ELMACH 0.5 OTHMAN 0.5 LOSS 0

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Annex 6: Waste collection cost Table A6.1: Waste generation per product category WMFBULK WMFDIL WMFMSWPACK 0 0 0.7TRANS 0.9 0 0MACH 0.45 0.45 0CONSTR 0.7 0.1 0FABMETPR 0.3 0.3 0.3ELMACH 0.3 0.3 0.3OTHMAN 0.2 0.3 0.3LOSS 1 0 0 Table A6.2: Waste collection and upgrading costs XB1 XB2 XB3 Japan 500 1000 1000China 500 2000 1000Korea 500 2000 1000Oceania 1000 2000 2000Europe 500 1000 1000Namerica 500 2000 1000CIS 500 2000 2000MEAST 500 2000 2000Lamerica 1000 2000 2000Oasia 1000 2000 2000Oafrica 1000 2000 2000

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Annex 7: Global energy consumption and energy efficiency in the iron and steel industry Table A7.1: Coal consumption in the iron and steel industry, based on (IISI 2001, IEA 2000)

Iron

productionCoking coal

consumptionCoke

consumption PCISCC iron

productionCoke

productionCoal for

coking Coking effGER iron

prod [Mt/yr] [Mt/yr] [Mt/yr] [Mt/yr] [t C/t iron] [Mt/yr] [Mt/yr] [t coke/t coal] [t coal/t iron] 1999 1999 1999 1999 1999 1999 1999 1999 1999 (1) (2) (3) (4) (5) (6) (7) (8) (9)Austria 3.9 2.0 2.2 0.30 0.64 1.6 2.2 0.73 0.85Belgium-Luxembourg 8.4 3.9 3.8 1.53 0.63 3.1 3.9 0.79 0.75Finland 3.0 1.3 1.4 0.40 0.61 0.9 1.3 0.69 0.81France 13.9 7.6 6.2 2.39 0.62 5.4 7.1 0.76 0.76Germany 27.9 11.0 12.6 2.28 0.53 8.6 13.0 0.66 0.77Italy 10.6 6.8 5.2 1.00 0.58 5.0 6.8 0.74 0.76Netherlands 5.3 4.4 2.1 0.92 0.57 2.3 2.7 0.85 0.64Portugal 0.4 - 0.3 - 0.77 0.4 0.0 Spain 4.1 3.4 2.1 0.67 0.67 2.3 3.8 0.61 1.00Sweden 3.2 1.7 1.5 0.29 0.56 1.1 1.7 0.65 0.81United Kingdom 12.1 9.0 6.3 0.49 0.56 5.9 8.2 0.72 0.76European Union (15) 92.9 Bulgaria 1.1 0.9 - 0.60 0.80Czech Republic 4.0 4.6 2.6 - 0.65 3.3 5.3 0.62 1.05Hungary 1.3 1.2 0.8

0.67

1.7

23.1

- 0.61 0.9 1.3 0.69 0.89Poland 5.2 16.1 5.6 - 1.07 8.5 12.7 1.60Romania 3.0 3.4 - 0.60 1.60Slovakia 3.0 0.30 0.60 0.67Turkey 5.2 4.6 3.3 - 0.64 2.8 4.4 0.64 1.04Others 0.3Other Europe Kazakhstan 3.5 3.9 0.60 1.12Russia 40.0 51.8 0.60 1.29Ukraine 21.9 40.4 1.84Other ex- USSR - Former USSR 65.4 Canada 8.9 4.7 3.3 0.26 0.40 3.3 4.4 0.75 0.52Mexico 4.8 1.6 3.0 0.62 2.2 2.7 0.81 0.77United States 46.4 26.5 20.2 4.50 0.53 18.2 27.1 0.67 0.74NAFTA 60.0 Argentina 2.0 0.5 - 0.25Brazil 24.5 12.7 - 0.52Chile 1.0 -Venezuela - - Other LA 0.5 -Central and South America 28.1Egypt 1.3 1.9 - 1.46South Africa 6.1 3.3 - 0.54Other Africa 0.6Africa 8.0Iran 2.1 1.5 - 0.71China 125.4 132.6 - 0.56 1.06India 20.1 53.9 - 2.68Japan 74.5 62.2 36.2 8.76 0.60South Korea 13.7

253.6

38.0 58.1 0.65 0.9223.3 18.4 13.7 2.55 0.70 18.3 0.75 0.90

Taiwan 8.9 8.0 - 0.90Other Asia 1.3 10.0 - 7.69Asia Australia 7.0 9.0 4.1 - 0.58 4.4 6.8 0.65 1.21New Zealand 0.6World 541.0 526.5 26.65 1.02

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Iron production data are available from IISI statistics (IISI 2001) and global coal consumption data for the iron and steel industry are available from IEA statistics (IEA 2000). They are shown in table A7.1. PCI refers to Powder Coal Injection into blast furnaces. SCC refers to the Specific Coal Consumption per ton of iron, the total of coke consumption and PCI divided by the iron production (a measure for the energy efficiency of the blast furnace) (in table 2 columns [(3+4)/1]). GER refers to the Gross Energy Requirement, the coal consumption per ton of iron, including coking, ore preparation and PCI (a measure for the energy efficiency of the whole iron production process, in table 2 columns [(3/8+4)/1]). A correction has been applied for international coke trade. No correction has been applied for the sales of energy by-products such as blast furnace gas, coke oven gas and steam. Also no correction has been applied for the use of non-coal derived energy carriers (which results in an underestimation of the GER value). In case coke oven efficiency data were not available, the ratio of coal consumption and iron production has been applied as a proxy. This approach results in an overestimation of the GER value in case significant quantities of coal are used for rolling, and it neglects coke trade (which may be a source of either underestimation or overestimation, depending on the net trade flows). The SCC data for all countries are rather close. Remarkable anomalities are Poland (too high) and Canada (too low). The high value for Portugal can be attributed to rounding and is not significant. If these three countries are omitted, the range for all others is 0.53-0.70 t C/t iron. This small range suggests this is a meaningful figure, and efficiency potentials are limited. The GER values show a much wider range from 0.25 (Argentina) to 2.68 (India). This range is too wide to be meaningful, given similar production technology throughout the world. However a closer look at national production practices reveals the sources of this wide range. The low values for Latin American countries (Argentina, Brazil) can be explained by the use of charcoal from wood instead of coke. The low value for South Africa can be explained by the use of Corex technology for iron production, a new process that uses steam coal instead of coking coal (see below). The low value for Canada can be explained by the injection of other fuels into the blast furnace. The low value for the Netherlands can be explained by high pellet use rates (50%) and errors in the energy statistics (Farla and Blok 2001). The high values for Japan and Korea (both countries with an energy efficient iron and steel industry) can be explained by high electricity prices (making maximised electricity generation attractive, using the blast furnace and coke oven as a kind of coal gasifier).

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Annex 8: Energy efficiency in the Japanese iron and steel industry Annex 8.1: Japanese blast furnaces, 1999

Company Site Pig iron production

Coke production

Coke purchase

Coke consumption

Other fuels PCI Total fuel Iron prod

Coke cons PCI

Savings by PCI increase to 200 kg/t

[t/yr] [t/yr] [t/yr] [kg/t] [kg/t] [kg/t] [kg/t] [Mt/yr] [PJ HHV/yr] [PJ HHV/yr] [PJ/yr]Nippon steel Yahata 3,531,591 1,371,031 0 348 0 152 500 3.53 36.9 17.0 4.18 Nagoya 5,938,613 2,341,528 0 363 0 133

35200 101

387

4,182,3401,161,692

807.4

496 5.94 64.7 25.0 7.93 Kimitsu 8,451,112 3,876,517 0 371 0 140 511 8.45 94.1 37.5 10.82 Ooita 7,160,608 2,924,330 120,759 0 130 482 7.16 75.7 29.5 9.74 Muroran 1,710,683 945,186 367 0 132 499 1.71 18.8 7.2 2.30NKK Keihin 3,151,987 1,811,418 454 0 555 3.15 43.0 10.1 5.02 Fukuyama 9,720,726 4,116,664 256,510 0 157 544 9.72 112.9 48.4 11.12Kawasaki steel Chiba 4,071,054 2,184,941 0 476 0 67 543 4.07 58.2 8.6 7.59 Mizushima 8,223,143 0 416 0 104 520 8.22 102.7 27.1 12.89Sumitomo Kokura 0 464,849 371 0 128 499 1.16 12.9 4.7 1.60 Wakayama 3,136,214 1,550,756 0 413 0 130 543 3.14 38.9 12.9 4.27

Kashima 6,182,937 3,031,519 7,428 409 5 83 497 6.18 75.9 16.3 10.73Kobe steel Kobe 1,317,250 0 521,960 333 0 176 509 1.32 13.2 7.3 1.31 Kakogawa 6,014,670 2,440,880 69,280 329 0 207 536 6.01 59.4 39.5 69.77 291.1 89.50 8.86

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Tale A8.2: Japanese coking oven characteristics, 1999 Site Oven Work rate Cycle time Load Chambers

Energy use HHV

Energy use LHV Production

[hrs] [t/chamber] [-] [kcal/kg] [GJ/t] [Mt/yr]Nippon steel Yahata 4 117.5 16.5 13.7 90 499 2.01 0.77 5 114.8 17.1 29.1 110 504 2.03 1.88 Nagoya 1 100.4 19 19.32 75 538 2.17 0.67 2 106.9

25.97

4

26.13 2.29

17.5111

92

104.6

569

2.33121 120 2.20

30.4

Sakaide

18.8 18.97 110 547 2.20 1.04 3 100.3 26 90 499 2.01 0.79 4 101.2 19.3 25.96 100 528 2.13 1.19 Ooita 1 124.3 16 26.8 78 599 2.41 1.42 2 123.4 16 26.8 78 599 2.41 1.41 3 121.3 16.3 26.8 82 592 2.38 1.43 121.5 16.3 26.8 82 575 2.32 1.43Hokkai seitetsu Muroran 5 109.8 17 19.48 91 630 2.54 1.00 6 123 13 28.13 42 592 2.38 0.98Shinnintetsu Kagaku Kimitsu 1 116.2 17.6 90 568 1.36 2 116.6 17.5 26.13 95 569 2.29 1.45 3 116.3 26.11 100 550 2.21 1.52 4 17.5 30.55 92 509 2.05 1.56 5 102.5 17.5 28.94 92 564 2.27 1.37NKK Keihin 1 111.5 18.3 36.9 124 594 2.39 2.44 2 102.1 19.8 36.7 74 594 2.39 1.23 Fukuyama 3 123 16.8 27.7 104 597 2.40 1.85 4 126.7 16.5 27.8 175 620 2.50 3.27 5 128.1 16.3 28.3 165 571 2.30 3.21Kawasaki steel Chiba 5 95.9 20.8 26.2 530 2.13 0.97 6 107.9 18.5 30.56 102 504 2.03 1.59 7 127.8 16.6 30.33 66 529 2.13 1.35 Mizushima 1 103.5 18.1 26.95 78 508 2.05 1.05 2 18.3 26.99 86 508 2.05 1.16 3 123.3 16.8 29.74 86 498 2.01 1.64 4 123.1 16.6 29.77 86 496 2.00 1.66 5 123.9 16.3 29.74 86 500 2.01 1.70 6 125 16.3 29.48 43 501 2.02 0.85Sumitomo Wakayama 4 92.1 23.2 21 76 604 2.43 0.56 5 92.1 23 21 92 2.29 0.68 6 94.5 22.5 26.4 106 559 2.25 1.03 Kashima 1AB 96.8 19.3 35.64 72 582 2.34 1.13

1CD 96.8 18.5 35.64 82 576 2.32 1.34 2AB 100 18.8 35.64 92 554 2.23 1.53 2CD 100 19 35.64 87 578 1.43Kansainetsukagaku Kagokawa 1,2 17.5 30.3 591 2.38 3,4 121.1 17.3 128 581 2.34 2.39Nakayamaseikou Funamachi 2A 155.6 13.3 15.135 34 591 2.38 0.53 2B 150.2 13.1 15.135 32 581 2.34 0.49Mitsubishi kagaku 1 128 15.3 25.9 100 653 2.63 1.90 2 124 16.4 32.3 223 647 2.60 4.77 3 124 16.4 32.3 223 647 2.60 4.77Mitsuikouzan Kitakyushu 1 89.8 21.5 29.932 46 566 2.28 0.50 2 115.2 17.3 31.195 108 594 2.39 1.97 72.5

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Japan Steel and Iron Industry - GTAP

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