The potential for carbon abatement in Taiwan’s steel industry and an analysis of carbon abatement trends

Renewable and Sustainable Energy Reviews (xxxx) xxxx–xxxx

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The potential for carbon abatement in Taiwan’s steel industry and an analysis of carbon abatement trends Chung-Chun Hsu1, Shang-Lien Lo

⁎,1

Graduate Institute of Environmental Engineering, National Taiwan University, 71, Chou-Shan Road, Taipei 106, Taiwan, ROC

A R T I C L E I N F O

A BS T RAC T

Keywords: Steel industry Abatement potential Abatement cost

This study applies a bottom-up approach to computation tree logic (CTL) by using mathematical relationships. According to a base scenario and a carbon abatement scenario, this study estimates the carbon abatement potential and costs in Taiwan's steel industry by drawing a carbon abatement cost curve for the years 2015, 2020, 2025, and 2030. In terms of short-term carbon abatement trends, the “existing carbon abatement technology that is undergoing steady growth and development” and the “currently popular carbon abatement technology that is facing transformational challenges” could be implemented immediately and should be the focus areas for research and development. In terms of long-term carbon abatement trends, if the steel industry in Taiwan were to implement the carbon abatement measures listed in this study, the amount of cost savings produced by energy conservations would be sufficient for covering the capital expenditure required for carbon reduction equipment. The carbon abatement cost curve in this study allows us to identify the carbon abatement measures that should be prioritized for the short, medium, and long terms, which would facilitate our development of a portfolio of carbon abatement measures, and provide a basis for the strategic analysis of carbon abatement technologies to the steel industry.

1. Introduction According to statistics produced by the World Steel Association, the five largest global steel producers in 2014 were China (822.7 Mt), Japan (110.7 Mt), the United States (88.2 Mt), India (87.3 Mt), and Russia (71.5 Mt). In 2014, the steel production figures in these countries, increased by approximately 0.09–7.38% from the figures in 2013 (WSA, 2015). A previous study analyzed the collected data on the domestic steel industry (China's iron and steel industry [CISI]), including energy consumption and steel production levels and other related information, by using the Logarithmic Mean Divisia Index (LMDI), and found that the correlation between the changes in CO2 emissions and those in steel production had very positive results (SUN Wen-qiang, 2011). Steel production is energy intensive and a high carbon producer. According to the World Resources Institute (WRI), the global steel industry emitted 1320 Mt of CO2 in 2011, which accounted for 5% of global CO2 emissions and 16% of global CO2 emissions from the industry. Many studies have analyzed CO2 abatement measures within the iron and steel industry (e.g [1–3,7,8,9,10,13,15]). McKinsey & Company (2011) predicted that if stronger emissions reduction mea-

⁎

1

sures were not to be implemented, the large increase of production combined with only a slight decrease in energy intensity would raise the global steel industry's carbon emissions to 4.3 GtCO2e by 2030, which would demonstrate a 48% increase from 2010. Promtida and Pichaya [11] pointed out that the different types of energy consumed affect the amount of CO2 emissions due to the variety of carbon content values that is in each fuel type. The obvious reduction of CO2 emissions from the energy consumption effect is mainly because of the utilization of advanced energy conservation technologies and the resulting improvement of energy efficiency (SUN Wen-qiang, 2011). Worrell et al. [13] analyzed the efficiency of the U.S. steel industry's energy-saving technologies and CO2 emissions reduction, which include energy use and CO2 emissions in its purpose steel process, special energy-saving technologies that measure efficiency (48), the analysis of energy use and CO2 emissions reduction potential, and the energy use and CO2 emissions in 1994 as the basis of the U.S. steel industry. The energy-saving supply curve method was used to calculate the energy efficiency in these energy cost-saving measures. In iron and steel production, energy costs, including heat and electricity, usually represent 20–40% of the total production costs Worldsteel, 2008 [14]. Oda et al. [4] evaluated the CO2 emissions

Corresponding author. E-mail address: [email protected] (S.-L. Lo). Mailing address: Graduate Institute of Environmental Engineering, National Taiwan University, 71, Chou-Shan Rd., Taipei 106, Taiwan, R.O.C.

http://dx.doi.org/10.1016/j.rser.2016.12.046 Received 13 March 2015; Received in revised form 24 November 2016; Accepted 6 December 2016 1364-0321/ © 2016 Elsevier Ltd. All rights reserved.

Please cite this article as: Hsu, C.-C., Renewable and Sustainable Energy Reviews (2016), http://dx.doi.org/10.1016/j.rser.2016.12.046

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C.-C. Hsu, S.-L. Lo

financial crisis. In 2010, Taiwan constructed a new BOF steel plant, and increased its BOF steel production by 1.7 million Mt, which was second only to the increase of 2.5 million Mt between 1996 and 1997. In 2011, BOF steel production in Taiwan only recovered to 10.3 million Mt, with a significant decline in capacity utilization. However, in 2013, Taiwan's production values set a new record at 12.58 million Mt. EAF steel production values increased from 6.65 million Mt in 1997 to 7.07 million Mt in 1998, which demonstrated a growth rate of 6.3%. However, following the 1999 financial crisis, the EAF production of crude steel fell back to 6.11 million, which demonstrated a sharp drop of 14%. Production subsequently recovered to 6.8 million Mt in 2000 and 2001, and broke the 10 million Mt barrier in 2007, which set a new record for EAF steel production levels while matching BOF production levels. However, EAF production fell to 7.66 million Mt in 2009, before recovering to 9.7 million in 2013. In terms of the growth trajectory of crude steel in Taiwan through the changes in crude steel production and apparent consumption over the past twenty years, with the significant expansion of BOF and EAF production capacities, Taiwan's crude steel output broke the 10 million Mt barrier in 1991, the 20 million Mt barrier in 2006, and reached 20.9 million Mt in 2007, which set a new record for crude steel production in Taiwan. Taiwan's crude steel production in 2013 was 22.28 million Mt, which was the twelfth highest in the world. Fig. 2 shows an analysis of the crude steel supply and demand in Taiwan. From 2000–2001, an abrupt decrease in exports occurred not only in Taiwan but also in several countries, mainly due to a decrease in the global steel demand and the comparative low prices of steel products from other regions, especially China (WSA, 2008). Taiwan's steel industry peaked in 2004, with both imports and exports reaching record levels. In 2007, as global steel prices reached record highs and the production of crude steel in Taiwan increased, imports fell to 5.09 million Mt, which was the lowest since 1992. Taiwan's crude steel production in 2013 was 22.28 million Mt, with imports of 3.49 million Mt and exports of 680,000 Mt. The self-sufficiency rate of crude steel reached 86%, with an export ratio of only 3%.

reduction potential and the minimum costs of technological options in the iron and steel sector in regions across the world. Oda et al. [5] also conducted an analysis of the diffusion of carbon capture and storage (CCS) and energy efficient technologies in the power and iron and steel sectors. The improvement of energy efficiency could vary from common best practices to retrofitting measures that use commercially available technologies. Some technologies, however, are applicable only for new plants. To achieve further reductions, capital costs for retrofitting would be necessary. In many cases, the annual operating costs could also be reduced due to savings in fuel and electricity Promtida and Pichaya [11]. Wang et al. [6] conducted a scenario analysis of the CO2 emissions reduction potential in the iron and steel industry in China by using the Long-range Energy Alternatives Planning (LEAP) model, based on the data from different regions and their iron- and steel-making plants. Hidalgo et al. [3] presented the potential effects of a CO2 emissions market by taking into account the compliance costs, the country's trading position, the evolution of technology, and the energy mixes based on an iron and steel industry global model. Based on the examples above, this study develops a cost curve model for the carbon abatement in Taiwan's steel industry. The study examines the common carbon abatement measures in Taiwan's steel industry, and compares the carbon abatement potential of these measures. The cost effectiveness of each carbon abatement measure is analyzed, which enables us to develop a carbon abatement strategy for Taiwan's steel industry that is based on economic cost considerations.

2. Material and methods 2.1. Activity trends of the Iron and Steel Industry in Taiwan

aapparent consu m mption

3000 2500 2000 1500 1000 500 0 Year

Production

Imports

Exports

2500

2000 1500 1000 500 0

1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

BOF

In BOF steel production, we can identify three system boundaries: coking and sintering, BOF steelmaking, and rolling. In terms of the energy consumption for each process, the largest share is the blast furnace that accounts for 55.64% of the total. The proportions of energy consumption for the other processes are 14.73% for rolling, 10.99% for coking, 9.74% for sintering, 5.06% for utilities, 2.04% for steelmaking, and 1.8% for others. Most of the energy consumed during BOF steel production is for smelting and maintaining the necessarily high temperatures. Thus, the types of fuels used and their ratios are as steel production exports and imports (10 4 Mt)

EAF

2.2. Manufacturing process features and energy flow

1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 00 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

crude steel production and consumption (104 Mt)

Steel is an internationally traded commodity, which means that the steel market in Taiwan is frequently affected by changes in global supply and demand. Fig. 1 shows that the steel market in Taiwan maintained a continued growth following the slowdown in 2001. With an export boom in the downstream steel industry, the annual apparent consumption of crude steel maintained a level of about 25 million Mt a year. However, the financial crisis resulted in a decline in the apparent consumption of crude steel to 19.3 million Mt in 2009. Electric arc furnace (EAF) has accounted for 49% of Taiwan's crude steel production over the past twenty years, while integrated steel manufacturing/ basic oxygen furnace (BOF) steelmaking has accounted for 51% of the total production values. BOF steel production reached record levels in 2004, with a total production of 10.94 million Mt, and maintained annual production levels of at least 10 million Mt until 2009, when production values fell to 8.15 million Mt in the wake of the

Year

Fig. 1. Taiwan's crude steel production and consumption (Ten Thousand Mt).

Fig. 2. Taiwan steel production exports and imports (Ten Thousand Mt).

2

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production and internal recycling of energy (to be deducted) external inputs of energy (required)

direct energy(coal) COG

coke

sinter

COG

electricity (production + purchase)

COG

BF

BFG

LDG indirect energy (purchased electricity)

electricity

BOF

COG

power plant

coal

(production + purchase)

Rolling

electricity (production + purchase)

direct energy(natural gas)

Fig. 3. Features and the energy use of the BOF steel production process in Taiwan.

is approximately 2.0 tCO2e/t Steel, while the carbon emissions intensity for EAF steel production is approximately 0.5 tCO2e/t Steel. BOF and EAF CO2 emissions account for 20% of the industrial emissions in Taiwan, and 10% of the total national CO2 emissions. Table 1 shows the CO2 emissions and emissions density estimates of the different energy sources in Taiwan's steel industry in 2010. The CO2 emissions for coal was 2.32 million Mt, while it was 0.28 million Mt for natural gas, 1.12 million Mt for fuel oil, and 9.12 million Mt for electricity use. The CO2 emissions density for coal was 0.37 tCO2e/ MWh, while it was 0.2 tCO2e/MWh for natural gas, 0.26 tCO2e/MWh for fuel oil, and 0.612 tCO2e/MWh for electricity use.

follows: bunker coal (3.79%), blast furnace coal (14.30%), furnace coal (74.45%), electricity (6.17%), low-sulfur oil (0.78%), NG diesel and gasoline (0.49%), and others (0.02%). It is evident that most of the energy consumption comes from coal. Fig. 3 shows the features and the energy use of the BOF steel production process. For coking and sintering, coal is the direct energy input, including pulverized coal injection (PCI), bunker coal, and furnace coal. Coking produces coke oven gas, which is used for sintering, BOF steelmaking, and rolling. The blast furnace gas and convertor gas produced by the BOF allow BOF steel plants to generate their own electricity, which fulfills the entire electricity requirements of the plant when combined with the electricity purchased from external sources. Rolling is divided into cold rolling and hot rolling. Cold rolling is used to meet higher quality requirements, and generally uses more natural gas or hydrogen as energy sources. For EAF steel production, we can identify two system boundaries: EAF steelmaking and processing. Fig. 4 shows the features and the energy use of the EAF steel production process. In EAF steel production, while natural gas and fuel oil are used for preheating purposes, they are not directly used in the furnace. The main sources of energy are coke and electricity, which are purchased externally. In the rolling process, the type of fuel that has the highest use is heavy oil.

2.4. Description of the system boundaries and data sources System boundaries for BOF and EAF are set for each individual process that is based on approximately twenty operators. The BOF process features three system boundaries: coking and sintering, BOF steel making, and rolling processing. In contrast, the EAF process features two system boundaries: EAF steelmaking and rolling. Based on the principles of mass balance, the external energy inputs and the self-generated and recycled energy are used together to calculate the carbon balance. For carbon abatement measures in the Taiwanese steel industry, this study uses data collection and interviews with experts to divide carbon abatement technologies into three major categories, according to the current development of carbon abatement technologies in Taiwan. These categories are “existing carbon abatement technology

2.3. Estimates of the CO2 emissions and emissions density of external energy sources The carbon emissions intensity for BOF steel production in Taiwan direct energy(NGˣfuel oil)

external inputs of energy (required)

preheat Scrap molten steel

Barrel indirect energy (purchased electricity)

indirect energy (purchased electricity)

EAF

direct energy(coke)

Rolling

direct energy(heavy oil)

Fig. 4. Features and the energy use of the EAF steel production process in Taiwan.

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Table 1 Estimates of the CO2 Emissions and Emissions Density of External Energy Sources in Taiwan's Steel Industry in 2010. Classification

Fuel used

Volume used (Mt)

CO2 emission factor (tCO2 / Mt)

CO2 emissions (Mt)

Total (Mt)

CO2 emissions density (tCO2e /MWh)

Solid fuel

Coke Anthracite

690,000 75,200

3.043 2.922

2,099,670 219,734.4

2,319,404.4

0.37

Gaseous fuel

Natural gas (selfproduced) Imported liquid natural gas

10,500

2.677

278,408

278,408

0.20

Diesel Fuel oil

6,466 350,172

3.130 3.153

20,238.6 1,104,092.3 9,118,004.4

1,124,330.9

0.26

9,118,004.4

0.612

Liquid fuel

93,500

Power

that is undergoing steady growth and development,” “new technology that is not yet mature but has the potential to deliver carbon abatement,” and “currently popular carbon abatement technology that is facing transformational challenges.”

emissions and emissions intensity(Murphy, 2011). The calculation for the CO2 emissions relational expression in the base scenario is constructed with the use of Eqs. (2)–(5).

CO2 (MtCO2 e)= EMI1 + EMI2 + EMI3

(2)

2.5. Model building and basic assumptions

EMI1 (MtCO2 e) = INT1 × V1

(3)

This study establishes two types of scenario: the base scenario and a carbon abatement scenario. The base scenario shows the future longterm trend in greenhouse gas emissions under the assumption that the current policy direction is maintained and no additional carbon abatement action is taken. The carbon abatement scenario includes the results of carbon abatement actions aside from the normal changes in economic activity, production technology, energy intensity, and the CO2 emission factor. This study surveys the carbon abatement potential of the carbon abatement technologies in the steel industry. The study is focused on the potential of technology rather than that of structural changes in the industry or that of changes in consumer behavior. The emissions for both the base and the carbon abatement scenarios are based on a logic tree that is produced from the Kaya equation, as shown in Eq. (1). To create the parameters for the relationship expressions in the logic tree, it is necessary to gather credible data, so that the final estimates of carbon abatement potential and costs are consistent with the actual situation in Taiwan's steel industry. The parameter data in this study are primarily obtained from expert interviews. The growth prediction references from the Taiwan Steel and Iron Industries Association and competent government authorities, the recently released government statistics on the industry, the international data, and the research published by relevant institutions in Taiwan and overseas are also used to corroborate the accuracy of the data obtained from the interviews. Both the base and the carbon abatement scenarios use 2010 as the base year, and estimate the carbon abatement potential and costs for the years 2015, 2020, 2025, and 2030.

EMI2 (MtCO2 e) = BOF + EAF

(4)

EMI3 (MtCO2 e) = INT2 × V2

(5)

C = (C1/ E ) (E / Y ) Y + (C2 / Y ) Y

where EMI1 is the CO2e emissions of coke and sinter production (MtCO2e), EMI2 is the CO2e emissions of steel production (MtCO2e), EMI3 is the CO2e emissions of steel after treatment (MtCO2e), INT1 is the CO2e intensity of coke and sinter (tCO2e/Mt Steel), INT2 is the CO2e intensity of steel after treatment (tCO2e/Mt Steel), BOF is the CO2e emissions of blast oxygen furnace production (MtCO2e), EAF is the CO2e emissions of EAF production (MtCO2e), V1 is the volume of BOF steel production (Mt Steel), and V2 is the volume of steel after treatment at the mills (Mt Steel). The respective ratios of the uses of natural gas, fuel oil, and coal, other fuels in the convertor manufacturing process for BOF steelmaking, the plant steel production process for EAF steelmaking, and the rolling manufacturing process are different, which causes variations in the CO2 intensity of the emissions from each steelmaking process. As shown in Fig. 5, this study uses a computation tree logic for BOF and EAF in Eq. (4) and INT2 in Eq. (5) to apply the relational expression in the logic tree to estimate the CO2 emissions for each steelmaking process. 3.2. Carbon abatement scenario assumptions and calculations When calculating the potential of individual carbon abatement technologies, we do not take into account costs or limitations such as socioeconomic or environmental impact assessments. Carbon abatement measures in the Taiwanese steel industry are classified into the following categories:

(1)

where C is the emissions of greenhouse gas, C1 is the emissions from fuel combustion, C2 is the emissions of the process, E is the energy consumption, such as coal and fossil fuel, and Y represents economic activity, product yield, or demand for energy services, such as crude steel yield. E/Y represents the energy required per unit of economic activity, such as the average energy required for producing a unit of crude steel. C2/Y represents non-fuel-based combustion emissions per unit economic activity.

1. “Existing carbon abatement technology that is undergoing steady growth and development,” which includes the improvement of coke and sinter (waste heat recovery), the improvement of rolling (hot charging), direct casting, coke dry quenching, and coke substitution; 2. “New technology that is not yet mature but has the potential to deliver carbon abatement,” which includes the improvement of EAF (energy efficiency), top gas recycling, smelt reduction, and CCS; 3. “Currently popular carbon abatement technology that is facing transformational challenges,” which includes the improvement of BOF (blast furnace top-pressure recovery turbine) and cogeneration.

3. Theory/calculation 3.1. Base scenario assumptions and calculations

The aforementioned three types of measures make classifications based on popularity and maturity. Although carbon abatement mea-

This study uses a bottom-up method to construct and estimate the 4

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Emissions, BOF production MtCO2e

Steel production volume, BOF Mt Steel CO2e intensity. BOF tCO2e/Mt Steel

CO2 intensity, Gas tCO2e/MWh

Process emissions intensity tCO2e/Mt steel Direct emissions intensity tCO2e/Mt steel Indirect emissions intensity tCO2e/Mt steel

Direct energy intensity, BOF MWh/Mt steel

Emissions, EAF production MtCO2e

CO2e intensity, EAF tCO2e/Mt Steel

Direct emissions intensity tCO2e/Mt steel

Indirect emissions intensity tCO2e/Mt steel

Direct emissions intensity tCO2e/Mt Steel CO2e intensity, after steel treatment tCO2e/Mt Steel

Indirect emissions intensity tCO2e/Mt Steel

CO2 intensity, Coal tCO2e/MWh

CO2e intensity, BOF tCO2e/MWh Indirect energy intensity, BOF MWh/Mt steel CO2e intensity, electricity tCO2e/MWh

Steel production volume, EAF Mt Steel

CO2 intensity, Oil tCO2e/MWh

Direct energy intensity, EAF MWh/Mt steel

Share, Gas Percent Share, Oil Percent Share, Coal Percent CO2 intensity, Gas tCO2e/MWh CO2 intensity, Oil tCO2e/MWh

CO2e intensity, EAF tCO2e/MWh

CO2 intensity, Coal tCO2e/MWh

Indirect energy intensity, EAF MWh/Mt steel

Share, Gas Percent

CO2e intensity, electricity tCO2e/MWh

Direct energy intensity, after steel treatment MWh/Mt steel CO2e intensity, after steel treatment tCO2e/MWh

Share, Oil Percent Share, Coal Percent CO2 intensity, Gas tCO2e/MWh CO2 intensity, Oil tCO2e/MWh CO2 intensity, Coal tCO2e/MWh

Indirect energy intensity, after steel treatment MWh/Mt steel

Share, Gas Percent

CO2e intensity, electricity tCO2e/MWh

Share, Coal Percent

Share, Oil Percent

Fig. 5. Computation tree logic for base scenario.

PCT1(%) = PCT2(abat) −PCT3(BAU)

sures are classified differently, the application of these measures is similar. Therefore, the computation logic for carbon abatement measures in the carbon abatement scenario can also be divided into three types. The first type of relational expression is shown in Eqs. (6)–(8). Carbon abatement measures that belong to this type of relational expression include cogeneration, direct casting, smelt reduction, coke substitution, coke dry quenching, and top gas recycling.

(10)

AV1(Mt CO2 e) = INT3 × V3

(6)

INT3 (Mt CO2 e /Mt Steel) = INT4 × INT5

(7)

where AV2 is the CO2e abatement volume (Mt CO2e), EMI4 is all of the energy technologies-related steel emissions (Mt CO2e), PCT1 is the incremental share of annual energy efficiency (%), PCT2(abat) is the share of annual energy efficiency in the abatement scenario (%), and PCT3(BAU) is the share of annual energy efficiency in business as usual (%). The third type of relational expression is shown in Eqs. (11)–(16). Carbon abatement measures that belong to this type of relational expression include CCS.

V3 (Mt Steel) = V4(abat) − V5(BAU)

(8)

AV3 (Mt CO2 e)= AV4 + AV5 + AV6

(11)

AV4 (Mt CO2 e) = INT6 × V6

(12)

AV5 (Mt CO2 e) = INT7 × V7 × PCT4

(13)

AV6 (Mt CO2 e) = INT8 × ELEC × S

(14)

INT6 (Mt CO2 e /Mt Steel) = INT9 × PCT5

(15)

V6 (Mt Steel) = V8 × PCT6

(16)

where AV1 is the CO2e abatement volume (Mt CO2e), INT3 is the carbon intensity reduction (Mt CO2e/Mt Steel), INT4 is the carbon intensity (tCO2e/MWh), INT5 is the energy intensity reduction (MWh/t Steel), V3 is the incremental steel production volume (Mt Steel), V4(abat) is the steel production volume in the abatement scenario (Mt Steel), and V5(BAU) is the steel production volume in business as usual (Mt Steel). The second type of relational expression is shown in Eqs. (9) and (10). Carbon abatement measures that belong to this type of relational expression include the improvement of coke and sinter (waste heat recovery), the improvement of BOF (blast furnace top-pressure recovery turbine), the improvement of EAF (energy efficiency), and the improvement of rolling (hot charging).

AV2 (Mt CO2 e) = EMI 4 × PCT1

where AV3 is the CO2e abatement volume (Mt CO2e), AV4 is the direct abatement (Mt CO2e), AV5 is the abatement process (Mt CO2e), AV6 is the indirect abatement (Mt CO2e), INT6 is the carbon intensity reduction from CCS (Mt CO2e/Mt Steel), V6 is the incremental steel production volume (Mt Steel), INT7 is the carbon intensity process emissions (Mt CO2e/Mt Steel), V7 is the incremental steel production volume (Mt Steel), PCT4 is the capture rate of CCS (%), INT8 is the

(9) 5

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45 40

38.28

39.11

34.92

35.13

CO2 emissions (MtCO2e)

35.81

35

28%

30 25

27.84

33.79 31.57

32.79

31.09

30.89

- 10% - 33%

31.77

27.23

26.06

20 15

BAU

10

existing advanced abatement lever future advanced abatement lever

5 0

2005

2010

2015

2020

2025

2030

Fig. 6. Estimated carbon abatement potential in Taiwan's steel industry, 2005–2030.

to avoid an excessive savings rate that may result from a low time preference rate. The long-term consumption growth rate refers to the long-term steady state rate of consumption growth. This is an objective parameter, which is approximately 2%, based on the experience of developed countries. The elasticity of the consumption of economic welfare is the level of discount on income growth. A higher elasticity of consumption indicates that we are less likely to agree on allowing the poorer generations to subsidize the richer generations and the richer generations to have a greater income discount. The value of 1.5 for consumption elasticity is based on the recommended value produced by the economist, Partha Dasgupta [12].

carbon intensity electricity (Mt CO2e/MWh), ELEC is specifically the CCS electricity requirement (MWh/t CO2e), S is the total sequestration (Mt CO2e), INT9 is the carbon intensity of BF/BOF production that is available for CCS capture (Mt CO2e/Mt Steel), PCT5 is the capture rate of CCS (%), V8 is the steel production volume for CCS (Mt steel), and PCT6 is the implementation share of CCS (%). The above relational expressions show the carbon abatement potential in the carbon abatement scenario. Next, we will discuss the carbon abatement cost assumptions in this scenario. When discussing carbon abatement costs, we first identify the three different scenarios of equipment costs. The first scenario is a one-time purchase of carbon reduction equipment, without any repeat purchases; as the full costs are paid in the first year, amortization is not necessary. The second scenario is the distribution of the purchase of carbon reduction equipment over multiple years as steel production increases. The third scenario is a one-time purchase or purchases made over multiple years, with amortization over the multiple years. The carbon abatement measures surveyed in this study are closer to those of the third type. The relational expression for carbon abatement costs is shown in Eqs. (17) and (18).

COST(USD/t CO2 e) = TCOST/V9

(17)

TCOST(USD) = Opex + Capex

(18)

K(%) = TR (%) + GR (%) × W( f )

where TR% is the time preference rate, GR% is the long-term consumption growth rate, and W (f) is the elasticity of the consumption of economic welfare. 4. Results In the base scenario in which no additional carbon abatement measures would be taken, there would be space for 28% carbon abatement by 2030, compared to the percentage by 2005. If the carbon abatement measures listed in this study were to be implemented, the reduction in carbon emissions compared to that of the base scenario would be as follows: 2.70 MtCO2e (reduction of 8%) in 2015; 4.92 MtCO2e (reduction of 14%) in 2020; 6.51 MtCO2e (reduction of 17%) in 2025; and 13.05 MtCO2e (33% reduction) in 2030, as shown in Fig. 6. In the carbon abatement scenario, emissions by 2030 would be 33% lower than the emissions in the base scenario, and lower than the emissions in 2005. However, as Taiwan's steel industry has already implemented some preliminary carbon abatement measures, including the “currently popular carbon abatement technology that is facing transformational challenges” and the “existing carbon abatement technology that is undergoing steady growth and development,” carbon emissions would be reduced by about 10% from those in the baseline scenario. There would also be space for 20% carbon abatement by 2030, compared to the percentage by 2005. Based on the three relational equations for the computation logic of carbon abatement presented in Section 3.2, the first relational equation for cogeneration, explains how carbon abatement measures can be applied to computation logic relational equations by configuring independent technical criterion. Subsequently, we should consider whether cogeneration is “newly established” or “existing” to determine abatement quantity. These considerations affect cogeneration utilization. The equation is illustrated in Figs. 7 and 8. Moreover, we should consider the effects that “newly established” and “existing” cogeneration have on “new steel yield” to determine abatement cost. These considerations affect Opex and Capex calculations, which consequently influence total abatement cost (Figs. 9 and 10). For the other carbon

where COST is the abatement cost (USD/t CO2e), TCOST is the total cost (USD), V9 is the abatement volume (t CO2e), Opex is the operating costs (USD), and Capex is the capital expenditures for carbon reduction equipment (USD). Among these, Capex must include the periodic payment for the amortization schedule over the life of the equipment, which is approximately thirty years. The final value of the annuity (FVA) is the total maturity value of the annuity of each period, as shown in Eq. (19).

FVAn = PMT ×

n

∑t =1 (1

+ K %)n −1

(20)

(19)

where FVAn is the final value of the annuity, PMT is the periodic payment schedule over a period of time, K is the social discount rate (%), and n is the lifespan of the carbon reduction equipment (year). The social discount rate (K%) in this study's hypothesis is 4%, which is calculated from the time preference rate, the long-term consumption growth rate, and the elasticity of the consumption of economic welfare, as shown in the relational expression of Eq. (20). The time preference rate is the relative economic welfare that is obtained by the present and future generations regardless of whether both generations enjoy the same wealth and income. If the time preference rate is zero, from the perspective of the present generation, the economic welfare obtained by each generation will be equal. This implies that the savings rate for the present and each future generation must be 100%. In this study, the time preference rate is assumed as 1% 6

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Carbon intensity indirect energy BF/BOF tCO2e/MWh

Carbon intensity reduction indirect BF/BOF Mt CO2e/Mt Steel

Energy intensity reduction indirect energy BF/BOF MWh/t Steel

Abatement volume Mt CO2e Incremental share of cogeneration new build Percent

Incremental steel production volume with BF/BOF cogeneration new build Mt Steel

Steel production volume with BF/BOF from new plants Mt Steel

Share of cogeneration new build in abatement case (AC) Percent Share of cogeneration new build in BAU Percent

Fig. 7. Cogeneration – New build, volume.

5. Discussion

abatement measures, the same logic for cogeneration can be applied to establish the equation for and calculate “abatement potential” and “abatement cost.” Calculation results for carbon abatement measures, abatement potential, and abatement cost were cross-referenced. The carbon abatement potential and unit costs of each carbon abatement measure are shown and listed in the order of unit cost; this produces the carbon abatement cost curve. The carbon abatement cost curves are shown in Figs. 11–14. Individual carbon abatement measures have both positive and negative costs, with the improvement of BOF (blast furnace top-pressure recovery turbine) and the improvement of rolling (hot charging) as the cheapest measures, and CCS and smelt reduction as the most expensive. Between 2011 and 2030, the steel industry in Taiwan would require an annual capital expenditure cash flow of US$ 379,000,000 in order to implement the carbon abatement measures listed in this study. At the same time, because many of the carbon abatement measures would be energy saving, an average of US$ 390,000,000 in operating expenses could be saved annually, which would be sufficient for covering the capital expenditures on carbon reduction equipment; there would even be a surplus of approximately US $11 million that could be put to other uses.

Carbon intensity reduction indirect BF/BOF Mt CO2e/Mt Steel

Abatement volume Mt CO2e Incremental steel production volume with BF/BOF cogeneration retrofit Mt Stee

When all of the carbon abatement measures with costs of less than 115 USD/tCO2e for the years 2015, 2020, 2025, and 2030 have been implemented, according to the cash flow, the social discount rate, and the lifespan of carbon reduction equipment, we can calculate the average amortized cost of carbon abatement, as follows: −68.94 USD/tCO2e in 2015; −64.27 USD/tCO2e in 2020; −68.08 USD/tCO2e in 2025; −2.82 USD/tCO2e in 2030. These results show that most of the carbon abatement measures that could be implemented in Taiwan's steel industry would have carbon abatement potential and be costeffective. As technology would continue to advance well into the beginning of 2020, the carbon abatement measures available would be significantly greater than those of 2015. The significant increase in average carbon abatement costs in 2030 would be the result of the use of the more costly CCS technology. All primary fuel-based carbon reduction technologies face a similar problem concerning primary fuel costs and social discount rates (SDRs): the effect of energy consumption and carbon emissions on future generations. With a focus on this issue, this study examines the sensitivity of the carbon reduction cost curve of fuel prices relative to SDRs in order to verify the impact of different fuel price levels and

Carbon intensity indirect energy BF/BOF t CO2e/MWh Energy intensity reduction indirect energy BF/BOF MWh/t Steel Steel production volume with BF/BOF cogeneration retrofit in abatement scenario Mt Steel

Steel production volume with BF/BOF cogeneration retrofit in BAU Mt Steel

Fig. 8. Cogeneration – Retrofit, volume.

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Share of cogeneration retrofit in abatement scenario Percent Steel production volume available for retrofit Mt Steel Share of cogeneration retrofit in BAU scenario Percent Steel production volume available for retrofit Mt Steel

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Opex difference new build MUSD

Cumulative annualized Capex new build per year MUSD

Abatement volume, new build Mt CO2e

Specific energy cost savings MUSD/Mt Steel

Incremental steel production volume with BF/BOF cogeneration new build Mt Steel

Total Cost – new build MUSD Abatement Cost USD/t CO2e

Opex cost difference with cogeneration new build MUSD/Mt Steel

Net specific Opex difference new build MUSD/Mt Steel

Annualized Capex new build per year MUSD

Cumulative

Capex new build per year MUSD

PMT

Fig. 9. Cogeneration – New build, cost.

175.3 (US$/ton) to 111.7, and the natural gas prices from 14.5 (US $/mmbtu) to 11.62. The costs of carbon reduction measures will then rise as a result. Therefore, the costs associated with carbon reduction measures, which include the improvement of rolling (hot charging), direct casting, improvement of coke and sinter (waste heat recovery), top gas recycling, and coke substitution, against activities that involve the use of fuel will increase significantly. In contrast, carbon reduction measures against activities that do not involve the use of fuel will not change the costs of carbon reduction. In analyzing the sensitivity of the SDR to carbon reduction costs, the study raises the SDR from 4–8%; an 8% SDR can be interpreted as a private discount rate. A private discount rate is meant to reflect the shorter payback period required by market investors when they are faced with the potential investment risks associated with new carbon reduction technologies. That is, market investors may require an additional risk premium, such as higher returns on an investment. Therefore, setting the private discount rate higher is meant to add a little bit of that cost-risk factor associated with new carbon reduction technologies to the model constructed in the study. The setting of the private discount rate at 8% is based on the need to adjust the time preference rate upwards to 2%, as suggested by many economists,

SDRs on carbon reduction costs. Based on the energy price estimates established by the International Energy Agency for various carbon reduction scenarios, this study explores the changes in carbon reduction costs due to energy price fluctuations for the various carbon reduction measures taken under the baseline and the 450 scenarios. A baseline scenario represents a situation in which existing policies and measures are to be implemented by various countries without any changes to these policies or the addition of other new policies. Under the development of such a scenario, the existing world carbon emission standards would increase the global temperature by more than 6 °C. A 450 scenario, on the other hand, represents a situation in which each country must maintain its atmospheric carbon dioxide concentration levels to within 450 ppm in order to reduce the possibility of an above 2 °C increase in global warming temperature to within 50%, which would be set as the target during policy formulation. In this study, each carbon reduction measure has the likelihood of providing an incentive for reducing carbon because of the energy-saving effect of rising fuel prices. If fuel prices in the 450 scenario drop, then, according to the International Energy Agency's World Energy Outlook estimates, the 2030 crude prices will drop from 131.1 (US$/barrel) to 97.29, the coal prices from

Net specific Opex difference retrofit MUSD/Mt Steel

Opex difference Retrofit MUSD

Abatement volume cogeneration – Retrofit Mt CO2e

Specific energy cost savings MUSD/Mt Steel

Incremental steel production volume with BF/BOF cogeneration retrofit Mt Steel

Total Cost – Retrofit MUSD Abatement Cost USD/t CO2e.

Opex cost difference with cogeneration retrofit MUSD/Mt Steel

Cumulative annualized Capex retrofit per year MUSD

Annualized Capex retrofit per year MUSD

Cumulative Fig. 10. Cogeneration – Retrofit, cost.

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Capex retrofit per year MUSD

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40 20 0 -20 -40

0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2.0 2.1 2.2 2.3 2.4 2.5 2.6 2.7 Abatement potential MtCO2e per year

-60

top gas recycling

coke substitution

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-100

-120 -140 -160 -180

cogeneration direct casting improvement of EAF(energy efficiency) improvement of BOF(blast furnace top-pressure recovery turbine) improvement of rolling(hot charging) negative cost

abatement cost 0~115 (USD/tCO2e)

Fig. 11. Carbon abatement cost curve in 2015.

trends, carbon abatement measures that should be given priority for immediate implementation include the improvement of BOF (blast furnace top-pressure recovery turbine), the improvement of EAF (energy efficiency), the improvement of rolling (hot charging), the improvement of coke and sinter (waste heat recovery), cogeneration, coke dry quenching (CDQ), coke substitution, and direct casting. Items that can now be developed for future follow-up carbon abatement programs include the “new technology that is not yet mature but has the potential to deliver carbon reduction,” such as top gas recycling, smelt reduction, and CCS. The proposed approach is advantageous in that it determines carbon abatement potential and the cost of relevant carbon abatement techniques based on expert opinions. It also highlights associations between carbon abatement potential, abatement cost, and abatement techniques. Such an approach also enables decision makers to configure and utilize carbon abatement measures to achieve a targeted total carbon abatement goal and maximize carbon abatement effectiveness. This is difficult to achieve using conventional model-based cost curve models, such as top-down computational general equilibrium models.

while simultaneously raising the intermediate value of consumption elasticity to 3, which is within the range recommended by economist Partha Dasgupta. The upwards adjustment of the SDR from 4–8% only result in the improvements of BOF (blast furnace top-pressure recovery turbine), coke and sinter (waste heat recovery), and coke substitution. The costs of carbon reduction from these measures do not significantly increase or change. However, the costs of other carbon reduction measures do increase significantly. One can speculate that changes in carbon reduction from the impact of the SDR would be small if the associated fixed equipment costs were also small. Implementation priority for carbon abatement measures can be examined through the “three horizons for implementation,” as shown in Fig. 15. The “three horizons for implementation” are based on the carbon abatement costs and the difficulty of implementation for each of the carbon abatement options, with implementation divided into three types: “do it now, no regrets,” “start slow, then accelerate,” and “develop now, capture over time.” Carbon abatement options that belong to the first two types include the “existing carbon reduction technology that is undergoing steady growth and development” and the “currently popular carbon reduction technology that is facing transformational challenges.” In terms of short-term carbon reduction

smelt reduction 120 100 80

Abatement cost (USD/tCO2e)

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40 20 0 -20

0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 2.2 2.4 2.6 2.8 3.0 3.2 3.4 3.6 3.8 4.0 4.2 4.4 Abatement potential MtCO2e per year coke dry quenching(CDQ)

-40 -60 -80

-100 -120 -140 -160

top gas recycling improvement of coke and sinter(waste heat recovery) cogeneration

direct casting improvement of EAF(energy efficiency) improvement of BOF(blast furnace top-pressure recovery turbine) improvement of rolling(hot charging) negative cost

abatement cost 0~115 (USD/tCO2e)

Fig. 12. Carbon abatement cost curve in 2020.

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smelt reduction

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Abatement cost (USD/tCO2e)

60 coke dry quenching(CDQ)

40 20 0 -20

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-60 -80 top gas recycling

-100

coke substitution

improvement of coke and sinter(waste heat recovery) cogeneration

-120 -140

direct casting

-160

improvement of EAF(energy efficiency) improvement of rolling(hot charging) improvement of BOF(blast furnace top-pressure recovery turbine) abatement cost 0~115 (USD/tCO2e)

negative cost

Fig. 13. Carbon abatement cost curve in 2025.

considered. However, the carbon abatement measures with negative costs could cause electricity savings or energy savings, which would lead to a reduction in electricity or energy costs. Over the cost recovery period, the cost savings would be greater than the capital expenditures of implementing the carbon abatement measures. Therefore, the carbon abatement measures that have negative costs should be regarded as a priority for implementation or research and development. If the potential of reducing carbon in a carbon reduction measure with negative carbon reduction costs can be realized, the demand for carbon reduction must at least be created artificially, starting with the formation of a carbon reduction policy. For example, "carbon tax" and "carbon trading" are artificial means of creating demand for carbon reduction that would help to realize the potential of carbon reduction technologies. Assuming that a government-imposed carbon tax is set in accordance to the excise tax on the highest historical EU ETS price of 43.36 USD/tCO2e, with the carbon tax for a baseline scenario set as zero, the potential of the measures of carbon reduction technologies with per unit carbon reduction costs below $43.36/tCO2e could then be realized. However, the study also finds that even if the given potential of a carbon reduction measure could be fully realized, there would still

6. Conclusions The carbon abatement potential and costs discussed in this study are based on a bottom-up expert assessment. This approach gathers a wide range of expert opinions on individual carbon abatement measures, which are then used to determine the energy saving rate, penetration rate, fixed investment, lifespan, and operating expenses of each measure. We estimate the carbon abatement potential and unit costs of each carbon abatement measure for the years 2015, 2020, 2025, and 2030, and list them in the order of unit cost. Each measure's carbon abatement potential and costs, as well as the overall carbon abatement potential, are shown in the form of a carbon abatement cost curve. The carbon abatement cost curve represents the supply potential of carbon abatement measures, rather than the demand for carbon abatement measures in the steel industry. Therefore, even the carbon abatement measures with negative costs would not necessarily be realized. The main reason is that when compared to the carbon abatement measures with positive costs, those with negative costs may not necessarily provide the same quality of service. In addition, the risk involved in the future development of technology must also be

CCS-retrofit

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cogeneration direct casting improvement of EAF(energy efficiency) improvement of rolling(hot charging) improvement of BOF(blast furnace top-pressure recovery turbine) negative cost

abatement cost 0~115 (USD/tCO2e)

Fig. 14. Carbon abatement cost curve in 2030.

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Fig. 15. Three horizons for implementation.

(USD/tCO2e) higher than the average in the baseline scenario. In terms of social discount, for the iron and steel industry with an 8% SDR, the 2030 average cost of all carbon reduction measures is 17.19 (USD/ tCO2e), which is 20.01 (USD/tCO2e) higher than the average carbon reduction cost of those with a SDR below 4%. This leads to a slight improvement of carbon reduction potential of about 0.25 (MtCO2e). The carbon reduction cost curve in this study allows us to identify the carbon reduction measures that should be prioritized for the short, medium, and long terms, and helps us to develop a portfolio of carbon reduction measures. These measures include programs for immediate implementation, programs with higher costs, and programs that may be important in the long term but would require the overcoming of obstacles before implementation. In addition, in response to the trend towards carbon trading mechanisms, the results of this study would enable the steel industry to evaluate its carbon credits effectively and provide a basis for the policy analysis on carbon reduction technologies. The results of this study would further enable the proper configuration of carbon abatement measures to produce a strategy that would provide a greater space for carbon abatement.

be gaps in carbon reduction. One reason for this is that a carbon tax or cap may not only incentivize an industry to adopt new carbon reduction technologies, thus helping to realize the potential of these technologies, but also cause that industry to reduce energy consumption by changing its behavior through the adjustment of its economic activities. The measures in this study are modeled based on their technological potential, which discounts the behavioral aspect of carbon reduction. Nonetheless, it is very difficult to use the technological aspect of the carbon reduction cost curve modeling to evaluate the overall carbon reduction effect derived from such a behavioral aspect as the carbon tax or cap. This is because, when calculating the total carbon reduction capability from both the technological and behavioral aspects, it is impossible to add the potential of carbon reduction, which is calculated from the technological aspect of the carbon reduction cost curve, directly to the effect of carbon reduction from the carbon tax derived from other studies, since doing so would result in double counting. If 300 USD/tCO2e or lower would be considered as a tolerable carbon abatement unit cost in 2030, carbon abatement measures that cost less than 300 USD could be applied. Therefore, compared to those in the base scenario, additional carbon abatement volumes in 2030 would reach 13.05 MtCO2e, with an average unit cost of −2.82 USD/ tCO2e. This indicates that if the steel industry were to invest in each of the carbon abatement measures with negative costs, the cost savings would sufficiently cover the higher costs of the “new technology that is not yet mature but has the potential to deliver carbon reduction,” and leave a surplus of 2.82 USD/tCO2e. Under the influence of the international price of carbon and the assumption of the 450 scenario, in which the International Energy Agency (IEA) estimates that carbon dioxide concentrations in the atmosphere should be maintained at less than 450 ppm, the international price of carbon dioxide would be $90 per Mt. With the use of the international price of carbon under this scenario as the baseline, the emerging carbon abatement measure of smelt reduction could be included as a priority of the carbon abatement program. In 2030, carbon abatement measures in Taiwan's steel industry with a cost of less than $90 per Mt would provide a carbon abatement potential of 7.29 MtCO2e. In the “Discussion” section, we presented the effects of energy price variance and social discount variance on the costs of carbon abatement policies. These were then incorporated into a sensitivity analysis to predict future changes in carbon abatement cost in the steel industry under various scenarios. Such results help decision-makers allocate carbon abatement measures and formulate contingencies. In terms of energy price, if the 2030 energy price is assumed to be that of the 450 scenario, in which the average cost of all carbon reduction measures in the steel industry is 8.95 (USD/tCO2e), the energy price will be 11.77

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