Diffusion of energy efficient technologies and CO2

emission reductions in iron and steel sector

Junichiro Oda ⁎,Keigo Akimoto,Fuminori Sano,Toshimasa Tomoda

Systems Analysis Group,Research Institute of Innovative Technology for the Earth (RITE),

9–2Kizugawadai,Kizu-cho,Soraku-gun,Kyoto 619–0292,Japan

Received 15July 2006;received in revised form 21December 2006;accepted 6January 2007

Available online 22February 2007

Abstracts

This paper evaluates CO 2emission reduction potentials and the minimum cost of technological options in the iron and steel sector by regions across the world.Based on an intensive and in-depth survey of current steel producing facilities and energy efficient technologies,we modified a global energy systems model,which we call DNE21+;technologies in the steel sector are explicitly modeled as well as those in the energy supply sector.Two types of targets are studied;the top-down type (550ppmv stabilization)and the bottom-up type (energy efficiency targets in the steel sector).Their cost-effective technological responses are obtained,and the emissions reduction effects are evaluated for the bottom-up targets.©2007Elsevier B.V .All rights reserved.

JEL classification:P28;Q41;Q48;L61

Keywords:Global warming mitigation;Iron and steel sector;Energy systems model;Energy saving;Energy efficient technology

1.Introduction

The Kyoto Protocol came into effect on February 16,2005,and the international official discussion on the post-Kyoto regimes began in 2005.In addition to the frameworks under the UNFCCC for global warming mitigation,e.g.,the Kyoto Protocol and the post-Kyoto regimes,regional and action-oriented cooperation is also being explored for energy efficiency improvement and CO 2emission reductions.For example,Asia –Pacific Partnership of Clean Development and Climate (APP),which was established by Australia,China,India,Japan,Republic of Korea,and the United States in

January Energy Economics 29(2007)868–

888www.elsevier.com/locate/eneco

⁎Corresponding author.Tel.:+81774752304;fax:+81774752317.

E-mail address:jun-oda@rite.or.jp (J.Oda).

0140-9883/$-see front matter ©2007Elsevier B.V .All rights reserved.

doi:10.1016/j.eneco.2007.01.003

2006,aims to address increased energy needs and associated challenges,including air pollution,energy security,and climate change,by promoting the development,deployment,and transfer of cleaner and more efficient technologies.It has established eight public –private task forces including the iron and steel sector.Meanwhile,the China –EU partnership on climate change including cooperation for clean energy developments was established in September 2005.Although various types of frameworks for CO 2emission reductions have been developed,technological development,transfer,and diffusion are important for any framework.The G8Gleneagles Summit also adopted an action plan with respect to climate change that has a similar framework.

The demand for steel has rapidly increased in the countries that have been in a primary stage of rapid economic growth,e.g.,Japan in the 1960s.Currently,China has reached this stage,and India,along with their economic growth,is also expected to reach this stage in the near future.Global steel productions have maintained an upward trend for the last five years and have reached a value of 1058million tons of crude steel in 2004(IISI,2005).The steel sector is one of the most energy intensive end-use sectors and emits around 590Mt-C accounting for 5.2%of the global anthropogenic GHG emissions in 2004(OECD,2005).

Under these circumstances,the assessments of the technological options for CO 2emission reductions not only in the energy supply sectors but also in the energy intensive end-use sectors,particularly in the steel production sector,are important to show ways for achieving the Kyoto target,for providing useful information for constructing the post-Kyoto regimes,and also for action-oriented cooperation such as the APP and the G8action plan.As cost-effective CO 2emission reduction measures are inevitably different across regions,the assessments should pay attention to regional differences in energy systems,energy consumption growth,current status of energy consumption,technology in the end-use sector,etc.

We had developed a global energy systems model,which we called DNE21+,in order to evaluate the cost-effective technological options of the supply side,including carbon capture and storage (CCS)taking into consideration regional differences (Akimoto et al.,2004a ).The model disaggregates the entire world into 77regions,and covers a time range up to 2050.The model minimizes the cumulative discounted present value of the world energy systems costs and seeks the cost-effective trajectory of global energy systems.Although the DNE21+treated the energy supply systems in a bottom-up fashion,the model treated the end-use sectors in a top-down fashion using long-term price elasticities for four types of secondary energy carriers:solid fuel,liquid fuel,gaseous fuel,and electricity.Due to the above ways of modeling,the DNE21+was not able to evaluate the technological options of energy saving and CO 2emission reductions in the end-use sectors.However,the previous study with the DNE21+indicated that the energy savings in the end-use sectors play an important role particularly in the near future,while improvements and reconstructions of energy supply systems including the CCS are inevitable for the long-term stabilization of atmospheric CO 2concentration.Thus,it is of great importance to evaluate mitigation opportunities in the end-use sectors,and should be done so in consistence with the energy supply sectors because these sectors are interlinked and not independent of each other.

Some studies on the evaluations of technologies in the end-use sectors are available (e.g.,Kainuma et al.,2003;Gielen and Moriguchi,2002;Hidalgo et al.,2005).These evaluations are restricted in some points as described below.The AIM/Enduse model analyzes a number of energy efficient technologies of end-use sectors for some Asian countries.However,the model treats endogenously only the end-use sectors (Kainuma et al.,2003).Gielen and Moriguchi (2002)evaluated CO 2emission reduction potentials in the Japanese iron and steel industry up to 2040with a linear programming model.Hidalgo et al.(2005)evaluated the technological options in the iron and steel industry with a 869

J.Oda et al./Energy Economics 29(2007)868–888

In this paper we address the following issues:(1)the cost-effective technology mix by region for(A)the reference case(no-climate change policy),(B)the case of atmospheric CO2 concentration stabilization at550ppmv,and(C)the case of energy efficiency target in the steel sector.(2)the CO2emission reduction potentials for the cases(B)and(C).For the above purpose, we first conducted a survey of the energy efficiency,costs,and installation vintages of the facilities in the steel sector by region,and we assumed global and regional future steel production scenarios based on their historical trend data,etc.Based on the survey and assumed data,the DNE21+was modified so that the technological options in the steel sector as well as in the energy supply sectors can be treated endogenously.The evaluation time span is only up to2030because the perspective of technological changes over longer periods becomes less certain even in the iron and steel sector.

The analysis using the modified DNE21+has some advantages compared to other analyses described above.(1)This analysis results are consistent across global regions and between the energy supply sectors and end-use sectors.(2)The trajectory of technological changes shall be a practical one because the vintages and lifetimes of the facilities are taken into account and the technological replacement is allowed only at the expense of depreciated cost of the facility to be replaced.

The disadvantages are:(1)this study does not treat changes in industrial structure and industry relocation endogenously,because the regional scenarios of steel productions are provided exogenously.(2)This study neglects short-term fluctuations of fuel prices because of the mid-term analysis up to2030.(3)This study does not treat such drastic options as the carbon capture from BOF steelmaking process,because we do not expect their introduction of a significant amount before2030although their substantial use may be expected in the longer time span.

2.Energy efficiency and technological options in iron and steel sector

Basically two major process routes have been used for crude steel production in the last three decades.One route is to reduce iron ore to pig iron with coke in blast furnaces,and then convert it into crude steel in basic oxygen furnaces(BOF steelmaking process).The other route is to smelt scrap iron in an electric arc furnace(EAF steelmaking process).The first route needs the heat of iron ore reduction at least,i.e.,theoretically7.37GJ/ton of pig iron,and actual energy consumption in the processes from coke making to hot rolling can vary between20and50GJ/ton of BOF steel including electric power consumption(e.g.,Worrell et al.,1997).The second route actually consumes400to750kWh/ton of EAF steel(e.g.,Worrell et al.,1999).In addition to the above two major routes,a direct reduction ironmaking route is also commercially available.

Many technological options exist for net energy saving and/or net CO2emissions reduction: exhaust heat recovery,process gas recovery,and non-fossil fuel use.The energy saving effects of the technological options are not uniquely determined but dependent on the process parameters,facility capacity,etc.Take top-pressure recovery turbine(TRT),which is an energy saving technology originally developed in the former Soviet Union,for instance.TRT generates electricity using pressurized gases from the blast furnace.The theoretical electric output of the TRT L(kW)is estimated by the following equation(Kawasaki Steel Corporation/NEDO, 2000).

L¼

1

860

d g d Q d C p d T1d1−

P2

P1

k−1

k

()

ð1Þ

870J.Oda et al./Energy Economics29(2007)868–888

where ηis the efficiency of the gas turbine and generator;Q (Nm 3/h),the gas flow at the inlet of the turbine;C p (kcal/kg ·K),the specific heat of the gas;T 1(K),the temperature at the inlet of the turbine;P 1and P 2(kg/cm 2),the gas pressures at the inlet and outlet of the turbine,respectively;and k ,the adiabatic exponent of the gas (=∼1.36).The electricity generation per ton of pig iron of the TRT is non-linearly related to the pressure of the blast furnace as represented in Eq.(1),and the pressure depends on the volume of the blast furnace and the mode of high-pressure operation of the blast furnace.A typical modern TRT of the dry type generates 55kWh/ton of pig iron in the case of the high-pressure operation of the blast furnace (Japan Consulting Institute/NEDO,2001),whereas a TRT of the wet type generates less power,e.g.,30kWh/ton of pig iron (Worrell et al.,1999).

Coke dry quenching (CDQ)recovers the sensible heat of red-hot coke using inactive gas in a dry process.A typical modern CDQ generates 150kWh/ton of coke and brings several co-benefits such as minimizing water consumption and enhancing coke quality.The coke quality improvement enhances the productivity and reduces the coke ratio of the blast furnace (Japan Consulting Institute/NEDO,2001;Nippon Steel Corporation/NEDO,2002).

The coke ratio have been declining with the diffusion of pulverized coal injection (PCI).PCI improves the net energy efficiency.However,the effect depends on the energy efficiency of coke oven and characteristics of resources (e.g.,Worrell et al.,1999).An oxygen enrichment,over-pressure and temperature raise of the blast can also reduce the coke ratio (Daniëls,2002).Cold iron sources,i.e.,scrap and direct reduced iron (DRI),can be practically used up to 35%in basic oxygen furnaces (BOFs).

The recovery of by-product gases,i.e.,coke oven gas (COG),blast furnace gas (BFG),and oxygen furnace gas (LDG),and their sensible heat recovery are also the key factors for the net energy efficiency improvements of the BOF steelmaking process.The LDG is generated in a batch process,and therefore,high-level control systems are particularly required for the recovery and effective utilization of LDG and its sensible heat (Japan Consulting Institute/NEDO,2001).

In addition to currently available technologies described by Worrell et al.(1999)and Japan Consulting Institute/NEDO (2001),we surveyed future technologies;a next-generation coke oven technology such as SCOPE21(Super Coke Oven for Productivity and Environmental enhancement toward the 21st century)has been developed and is now being demonstrated in Japan.The purpose of SCOPE21is not only energy saving or cost reduction but also increasing the input ratio of noncaking coal from 20%to 50%(NEDO and Center for Coal Utilization,Japan,2004).From the long-term point of view,many technological options are proposed for expanding the potentials of CO 2emission reductions,e.g.,Corex,Finex,Cyclone Converter Furnace,DIOS,AISI,HISmelt,Fastmet,Fastmelt,Circofer,Circored,and CCS in the steel sector (Daniëls,2002;Rynikiewicz,2005).

3.The model

3.1.Framework of the global energy systems model DNE21+

The DNE21+model divides the world into 77regions;the countries of interest are treated as independent regions,and countries with large areas such as the US,Canada,Australia,China,India,Brazil,and Russia are further disaggregated into 3–8regions to consider the transportation costs of energy and CO 2in more detail.In order to evaluate the technological options including end-use sectors,the time span of the model analysis is limited only until 2030in this study,and the time interval is 5years.The total global cost of energy systems is minimized over the time period from 2000to 2030.

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3.2.Energy supply,CCS,and end-use sectors other than steel sectors

Eight types of primary energy sources are explicitly modeled:natural gas,oil,coal,biomass, hydro and geothermal,photovoltaics,wind,and nuclear.The prices of fossil fuel in this study are assumed based on an average wellhead price in the past ten years(1996–2005)and AEO projections(DOE/EIA,2006).

As technological options,various types of energy-conversion technologies are explicitly modeled in addition to electricity generation.The lifetimes of nuclear power and other facilities are assumed to be40and30years,respectively.These include oil refinery,natural gas liquefaction,coal gasification,water electrolysis,methanol synthesis,etc.The vintage of energy-conversion plants is taken into account.Five types of CCS technologies are also considered:1) injection into oil wells for EOR operation,2)storage in depleted natural gas wells,3)injection into coal beds for ECBM operation,4)storage in aquifers,and5)storage in oceans.Each type of fossil fueled power technology has three assumed levels of energy efficiencies and three corresponding levels of facilities costs and the technological progresses are assumed exogenously for these power generation technologies and CCS technology.

The end-use sector excluding the steel sector are disaggregated into four types of secondary energy carriers:1)solid fuel,2)liquid fuel,3)gaseous fuel,and4)electricity.The demands for these energy carriers are endogenously calculated in a top-down fashion using long-term price elasticities in other cases than the reference case.The demand for electricity is expressed by the load duration curves that are characterized by four types of time periods,and the relationship between the supply and demand of electricity is formulated for each of the four periods.The steel sector is fully integrated into the DNE21+model.This model explores the optimal point of the coal consumption and its cost to minimize the total costs of energy systems considering the interaction among coal consumptions in all the sectors.

See Fujii and Yamaji(1998),Yamaji et al.(2000),Akimoto et al.(2004a)and Akimoto et al. (2004b)for a detailed description of the energy supply and CCS technologies in the DNE21+and DNE21.

3.3.Iron and steel sector

The technological options for energy savings and CO2emission reductions in the steel sector were modeled based on the technological information as described in Section2.In addition,the following information was utilized for the modeling:the data on the status of the current facility in Asian countries and the former Soviet Union(Kawasaki Steel Corporation/NEDO,2000;Nippon Steel Corporation/NEDO,2002;Kawatetsu Techno-Research Corporation,2002;Nippon Steel Corporation/NEDO,1999),the installation share of energy efficient technologies of major steelmaking countries surveyed by Japan Iron and Steel Federation(2006),the status of the US iron and steel sector analyzed by Worrell et al.(1999),and the preceding modeling activities,e.g., Kainuma et al.(2003),Gielen and Moriguchi(2002),and Hidalgo et al.(2005).The outline of the model of the iron and steel sector is as follows:

1.Nine types of steelmaking routes having different levels of energy efficiency are modeled.

Those consist of four types of BOF steelmaking,three types of scrap-based EAF steelmaking and two types of DRI-based EAF steelmaking.

2.In the BOF steelmaking routes,retrofit measures of the facilities of CDQ,TRT,waste plastics

and tires recycling,and COG and LDG recovery are explicitly modeled.

3.The lifetime of all the facilities in the steel sector described above is assumed to be 40years.The model considers the historical installation of the facilities.

4.Scenarios of crude steel production by region are assumed exogenously.In addition,the maximum and minimum scrap-based EAF steel production scenarios are also assumed.These assumptions are kept fixed regardless of the simulation cases and described in detail in Section 3.

5.

Fig.1shows the concept of assumed energy flows in steelmaking processes.These nine steelmaking routes (four BOF steelmaking processes,three scrap-based EAF steelmaking processes and two DRI-based EAF steelmaking processes)encompass processes from

raw

Fig.2.Assumed energy use of low-efficiency BOF steelmaking (type

I).Fig.1.Modeling of energy use of the steel sector in DNE21+.

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materials input to coke oven and sintering furnace and from scrap input to EAF and BOF,to hot rolling;they do not include the processes of downstream,such as cold rolling,thin coating,special steel making,and ferroalloy making.

Figs.2–5show the assumed energy flows and the required and recovered energies of each type shown in Fig.1.Table 1shows the assumed facility costs of the technological options in the type I –VII.The cost data is assumed based on many studies by NEDO (e.g.,Japan Consulting Institute/NEDO,2001;Kawasaki Steel Corporation/NEDO,2000;Nippon Steel Corporation/NEDO,2002),and the assumptions of Worrell et al.(1999)and Kainuma et al.(2003)

.

Fig.4.Assumed energy use of high-efficiency BOF steelmaking (type III and

IV).

Fig.3.Assumed energy use of middle-efficiency BOF steelmaking (type II).

As shown in Fig.2,we assumed that the low-efficiency basic oxygen furnace (BOF)steelmaking route (type I)has a smaller scale capacity,partly including ingot making and some classical processes such as beehive coke oven and open hearth furnace (OHF).Type I is allowed to retrofit coke oven gas (COG)recovery in the model.

Fig.3shows the assumed middle-efficiency BOF steelmaking route (type II).Type II is a large-scale facility with modern steelmaking processes including pulverized coal injection (PCI)and continuous casting facilities.The assumed average coal injection ratio in the type II is 88kg/t-pig iron (2.3GJ/t-pig iron),which can bring a net energy saving of 1.0–1.4GJ/t-pig iron.The model allows some retrofit measures for COG recovery,basic oxygen furnace gas (LDG)recovery,effective utilization facility of COG and LDG,CDQ,and TRT to the type II.Table 1

Assumed capital costs for the steelmaking routes and retrofit facilities (type I –VII)

Facility costs (US 2000$/(t-crude steel/yr))

BF and BOF steelmaking process

Type I:low-eff.(BOF and open hearth furnace)

276.2+coke oven gas (COG)recovery [for type I]

+11.6Type II:middle-eff.

295.4+coke oven gas (COG)recovery [for type II]

+9.3+basic oxygen gas (LDG)recovery

+16.2+coke dry quenching (CDQ)

+16.1+top-pressure recovery turbine (TRT)

+13.6Type III:high-eff.

386.5+recycling facilities of waste plastics and tires

+1.54Type IV:high-eff.with next-generation coke oven

377.1Scrap-based EAF steelmaking process

Type V:low-eff.(EAF and induction furnace)

143.0Type VI:middle-eff.

174.0Type VII:high-eff.

183.7

Fig.5.Modeling of three types of EAF steelmaking (type V ,VI,and VII).

Fig.5shows the assumed energy flow of electric arc furnace(EAF)steel production.The low-efficiency electric steelmaking route(type V)consists of a small-scale EAF and induction furnace that is widely utilized in India.The middle-efficiency EAF steelmaking route(type VI)assumes an alternate current(AC)arc furnace that is widely used in the US,Europe,and Japan.The high-efficiency EAF steelmaking route(type VII)consists of a direct current(DC)arc furnace and many types of energy saving facilities such as scrap preheating and recuperative burner ladle preheating.

Table2shows the assumed capital costs and energy efficiencies of DRI-based EAF routes (type VIII and IX).The model treats the DRI-based EAF routes as a gas-based DRI technology, i.e.,Midrex,Hyl I and Hyl III,according to the current diffusion status(Midrex,2005).The data of costs and energy efficiencies are derived from Daniëls(2002)and the European ULCOS(Ultra Low CO2Steelmaking)Project(Rynikiewicz,2005).In addition to gas-based DRI,Corex and coal-based DRI technologies are also commercially available.This study dose not treat these technologies,since the production shares are not large at this moment(Midrex,2005;Daniëls, 2002).

The vintages of the nine types of steelmaking facilities were estimated based on the data as follow:(1)the long-term records of the historical BOF and EAF steel productions(IISI,2005; Japan Iron and Steel Federation,2004;Midrex,2005),(2)the data of the energy consumption per ton of crude steel production calculated using the statistics for crude steel productions(IISI,2005) and Extended Energy Balances(IEA,2005),(3)and historical installation data on blast furnaces of a scale larger than2000m3in volume(Japan Iron and Steel Federation,2004).The historical installation capacities of COG and LDG recovery and effective utilization facilities were estimated from the Extended Energy Balances(IEA,2002)and survey of Japan Iron and Steel Federation(2006).The vintages of the CDQ and TRT were estimated from the cumulative capacities of the installations of the CDQ and TRT of each steel company and steelwork (Kawatetsu Techno-Research Corporation,2002;Kawasaki Steel Corporation/NEDO,2000; Nippon Steel Corporation/NEDO,2002;Japan Iron and Steel Federation,2006).

Fig.6shows the estimated“installation share”of energy efficient facilities in the total capacity of BOF steel production in2000.The meaning of“installation share”in Fig.6is not a diffusion ratio based on the number of the facility,but the one based on the net energy saving effect of the Table2

Assumed capital costs and energy efficiency for the DRI-based EAF routes(type VIII and IX)

DRI-based EAF steelmaking process Natural gas consumption

(GJ/t-crude steel)Electricity consumption

(GJ/t-crude steel)

Facility costs(US2000$/

(t-crude steel/yr))

Type VIII:middle-eff.15.9705374.3 Type IX:high-eff.12.1695438.1

facility.The share of continuous casting is simply IISI's data (IISI,2005).In China,the iron and steel industry has been dramatically restructured since the mid-1990s,and high-efficiency integrated steelworks with the CDQ and TRT are constructed according to the official targets in the last several years (National Development and Reform Commission,2005).The latest diffusion ratios of these facilities will be larger than the data shown in Fig.6.

The energy efficiency of an actual steelwork can vary not only with regard to its tech-nological constitution but also with regard to the characteristics of iron ore and coal (ledge of ore),type and quality of steel products,operation control technology,failure rate of facilities,usage rate,and other uncountable factors,e.g.,air temperature (Nippon Steel Corporation/NEDO,1999).We assumed that these nine steelmaking technology types and their diffusion ratios can well represent the average energy efficiency of the region and are sufficient for our analysis objections.

3.4.Assumed final energy demand

The future scenario of final energy demands is derived from the IPCC SRES B2(Nakicenovic et al.,2000).We made some modification to the original scenario data for consistency with historical energy demands (IEA,2005),regional division,and assumed boundary of this model.The global final energy demand excluding the energy use of steel production in the reference case reaches 9.96Gtoe/year in 2030.

3.5.Steel production scenario

The above modeling requires an exogenous scenario of future crude steel production.For the top sixteen steel producing countries,we assumed a future scenario of apparent consumption of crude steel per capita taking into consideration the historical trends,the relationship with GDP per capita,and the theoretical scope that the steel consumption would increase steeply in the primary stage of economic growth and become stable or decline in a fully developed economic stage.Future population and GDP are derived from the B2Scenario of IPCC SRES (Nakicenovic et al.,2000;TGCIA,2002).Fig.7shows the assumed crude steel production scenario that

was Fig.6.Assumed diffusion ratio of energy efficient facilities by region in 2000.

estimated based on the population,the apparent consumption per capita scenario,and the assumed exogenous steel trade scenario.The crude steel production scenario for the non-major steel producing countries was estimated simply based on the relation with the historical GDP and future GDP scenario.The production share of these countries will be below 15%throughout the evaluation period.The assumed scenario of total crude steel production for India agrees fairly well with the outlook publicized by the Indian

government.

Fig.8.Assumed scenarios of world crude steel and EAF steel

productions.

Fig.7.Assumed scenario of crude steel production by region.

Fig.9.World power generation in the reference case and the case of550ppmv with trade.

transport limitations and social systems.This study assumed that the supply of scrap in China and India continues a steady growth and not a radical one.

It is noted that this study cannot explicitly analyze carbon leakage effects,since the exogenous scenario of total crude steel production is fixed by region.However,the interchange ability between ore-based steel and scrap-based EAF steel in the region is considered in the model.

4.Model simulation results

4.1.Simulation cases

No-climate policy case(A)and two policy cases top-down and bottom-up targets are studied. The top-down target scenario represents the stabilization at550ppmv with and without emissions trading(B1and B2,respectively).Assumed national targets of emission reductions for the stabilization case are rather complicated,reflecting the current international situations:the Annex I countries other than the US follow the Kyoto target until2010.The US follows its own target: per-GDP CO2emission reduction of18%.Thereafter all the Annex I countries reduce their emissions according to the proposal by UK that requires the Annex I countries to reduce about 60%of emissions relative to their1990levels by2050,while the non-Annex I countries have no obligation of emission reduction until2010but thereafter are restricted so that the global emissions may not surpass the emission path of the550ppmv stabilization.

There are two types of bottom-up targets.One is the energy efficiency target on both BOF and EAF steels(C1).The case(C1)requires all regions to improve the“energy efficiency”to the current“energy efficiency”level of Japan by2020.The“energy efficiency”means the total energy input to BOF and EAF steel producing divided by the total volume of BOF and EAF steel productions.The other one is the energy efficiency target on BOF steel only(C2).The case(C2)requires all regions to improve the energy efficiency of BOF steel to current energy efficiency of BOF steel of Japan by2020.

A discount rate of5%per year is adopted throughout the study.

Fig.10.CO2emission reductions for the world in the case of550ppmv with trade.4.2.Model results and discussions

Fig.9shows the world power generation up to the year2030in the reference case(A)and the case of550ppmv with trade(B1).The major cost-effective power source is coal in the reference case(A).In the550ppmv case(B1),the major cost-effective power source is still coal;however, other sources,e.g.,gas,wind and biomass,are increasing in the550ppmv case(B1).Fig.10shows the global cost-effective technological scenario to achieve550ppmv the emissions trade allowed (B1).While renewables,nuclear and fuel switching among fossil fuels make considerable amounts of contribution to the emission reduction,CCS and energy saving play much greater roles in the case(B1);their contribution is3.0Gt-C/yr and1.6Gt-C/y,respectively in2030.Large amounts of

Fig.11.World steelmaking capacity by steelmaking route.

carbon capture technologies are adopted particularly in coal fired power plants in the case (B1),and therefore,the CO 2intensity of electricity is considerably lower than that of the reference case

(A).The results shown in Fig.9inevitably depends on the assumed prices of fossil fuel.In this study,we also confirmed that the results of emission reductions in CCS depend on the prices.

Fig.11shows the world steelmaking capacity for the three cases.In the reference case (A),the share of the middle-efficiency BOF route (type II)is increasing.In the case of 550ppmv with trade (B1),

the

Fig.12.Capacity shares of nine route of steelmaking in

2020.

Fig.11(continued ).

Fig.13.World installation share in production capacity of energy efficiency facilities.

47Mt-C accounting for approximately 50%reduction in 2030.However,the reduction due to the CO 2intensity improvement should be attributed to the power generation sector's effort.

Fig.12shows the share of steel producing capacity by region in 2020.In China,the share of the middle-efficiency BOF (type II)is dominant in the reference case (A);however,the shares of high-efficiency BOF (type III)and next-generation coke oven steelmaking route (type IV)increase in the other cases (B1and C1).In EU and Japan,high-efficiency routes (type III,IV ,and VII)are dominant in all the cases.In the FSU,the share of the capacity in the case of 550ppmv without trade (B2)is similar to the reference case (A)due to the moderate constraint of emissions.(Hot air exists at present.)However,emissions trading affects this situation and more efficient steelmaking types are introduced in the case of 550ppmv with trade (B1).In the case of energy efficiency target on BOF and EAF steels (C1),the share of DRI-based EAF routes (type VIII and IX)also increases compared to that in the other cases (A,B1and B2)in the FSU.In this study,we also confirmed that the assumed fuel prices affect the results of gas-based DRI routes in the global steel sector.

Fig.13shows the global installation share of energy efficient facilities.The shares of the CDQ,TRT,and LDG recovery increase in the case of 550ppmv with trade (B1)and the case of energy efficiency target on BOF and EAF steels (C1),and reach approximately 90%of total BOF steel production capacity by 2030,while their shares are below 60%in the reference case (A).The next-generation coke oven increases in the case of 550ppmv with trade (B1)and reaches approximately 35%in 2030.In addition to the substitution of bundled technologies (Fig.11),COG and LDG recovery,CDQ and TRT decrease the energy input to the steel sector from the other sectors.

Fig.14shows the profiles of energy intensity for the target and CO 2emission reductions relative to the reference case (A)in the world steel sector.In the reference case (A),the energy intensity continuously improves to a 15%reduction in 2030from the current intensity.In the case of 550ppmv with trade (B1),the energy intensity additionally improves by 13%in 2030.

The

Fig.13(continued ).

improvement in the energy intensity in the case of 550ppmv without trade (B2)is smaller than that in the case (B1);this is because the potential for improvement in the energy efficiency in transitional economy regions and developing countries is larger than that in many developed countries in the steel sector.

The improvement rate of the energy intensity in the case of the energy efficiency target on BOF steel (C2)is lower than that in the case of energy efficiency target on BOF and EAF steels (C1).This is because the energy efficiency improvement of the BOF steelmaking in the reference case

(A)also continues throughout the evaluation period,and the adopted target on BOF steel (C2)is relatively moderate.The adopted energy efficiency target on BOF and EAF steels (C1)requires large energy saving particularly for countries having a low ratio of the EAF steel,such as China and the FSU (also see Fig.12

).Fig.14.Energy intensities improvement and CO 2emission reductions in world steel sector.

886J.Oda et al./Energy Economics29(2007)868–888

The lower panel shows the emissions reduction in the steel sector relative to the reference case. This figure shows the effectiveness of the energy efficiency targets in terms of emissions reduction.We observe relatively a large difference between the550ppmv cases(B1and B2)and the energy efficiency cases(C1and C2)as compared to the difference in energy efficiency between the two as shown in the upper panel.This is because the CO2intensities of electricity is lower in the550ppmv cases(B1and B2)than in the energy efficiency target cases(C1and C2). Although the bottom-up target is less cost-effective than the top-down target for the purpose of emissions reduction,the former target such as on the energy efficiency is action-oriented and seems to be more acceptable to many countries including developing countries.

5.Conclusions

This article surveyed energy efficient technologies and their installation capacities in the iron and steel sector for countries across the world.A global energy systems model of optimization type having a high regional resolution,DNE21+,was modified to treat the technological options in the steel sector based on the intensive surveys.The steelmaking processes are modeled into nine bundled routes(four types of BOF,three type of scrap-based EAF and two types of DRI-based EAF)in terms of energy efficiency,input material,etc.The model also includes retrofit measures such as COG and LDG recovery,waste plastics and tires recycling, CDQ and TRT.

Using the modified model,we explored the minimum cost technological measures for top-down and bottom-up targets as well as for no-climate policy case;550ppmv stabilization with and without emissions trading and the energy efficiency targets on BOF steel and on both BOF and EAF steels.The energy efficiency targets require all regions to achieve the current energy efficiency of Japan by2020.The analysis results shall be consistent across global regions and between the energy supply and end-use sectors because of the model structure.The trajectory of technological changes shall be practical one because the vintages and lifetimes of the facilities are taken into account and the technological replacement is allowed only at the expense of depreciated cost of the facility to be replaced.

Major analysis results are as follows.The technological changes in power generation for the case of550ppmv with trade are increase in gas,wind power,biomass and nuclear with coal still dominant.The energy saving is a great contributor to emission reductions up to2030,which implies the importance of the study on energy efficiency improvement in energy intensive sectors such as the iron and steel industry.

In the reference case,the energy efficiency of steel production improves by15%in2030 relative to the current efficiency.In the assumed550ppmv and energy efficiency target cases,the improvement is approximately25%in2030.The trajectories of transitions of nine types of steelmaking routes are obtained,and also the capacity shares of energy efficient facilities such as COG and LDG recovery,CDQ,TRT and next-generation coke oven; middle-efficiency BOF route(type II)is dominant over the evaluation time period with a slight increase in high-efficiency BOF route(type III)and type IV that utilizes a next-generation coke oven in the reference case,while type III,type IV and high-efficiency EAF route(type VII)show large increase in the case of550ppmv with trade.LDG recovery,TRT and CDQ shares are below60%in the world in the reference case and their shares reach about90%in the case of550ppmv with trade and in the case of energy efficiency target on BOF and EAF steels.The capacity shares of the nine steelmaking routes by region are also obtained.

In the 550ppmv cases,the decreased CO 2intensity of electricity generation contributes to the emission reduction in the steel sector.Including this effect,the CO 2emissions reductions in the world steel sector is approximately 80Mt-C/yr in 2030relative to the reference case.

The modified model,DNE21+enabled us to analyze the bottom-up target cases as well as the top-down cases,providing the minimum cost technological responses in the iron and steel sector for achieving the targets,and also the effects of emissions reduction for the bottom-up target cases.Interestingly enough,these two types of assumed targets brought about approximately the same amount of emissions reductions in the steel sector.This result roughly implies that if the current Japanese technologies of iron and steel sector are transferred to other countries,the expected emissions reduction will reach the amount that will be required in the iron and steel sector for the 550ppmv stabilization.

The iron and steel sector is one of the energy intensive sectors,and there are several other energy intensive sectors;cement,pulp and paper,etc.Expansion of the model capacity to enable the explicit treatment of technologies and the analysis of bottom-up targets of these sectors will be a future work,and it will make a great contribution to the detailed planning of action-oriented reduction frameworks such as APP and also the discussion and examination of post-Kyoto regimes.

Acknowledgements

The authors would like to thank Professor Yoshiki Ogawa (Toyo University),Mr.Toru Ono (Nippon Steel Corporation),and Professor Yoichi Kaya (Research Institute of Innovative Technology for the Earth (RITE)).This study was supported by New Energy and Industrial Technology Development Organization (NEDO),Japan.

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