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Energy intensity and greenhouse gases footprint of metallurgical processes: A

continuous steelmaking case study

Mansoor Barati

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Barati, M., 2010. Energy intensity and greenhouse gases footprint of metallurgical processes: A continuous steelmaking case study. Energy, 35(9), pp.3731-3737. DOI: 10.1016/j.energy.2010.05.022

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Energy Intensity and Greenhouse Gases Footprint of Metallurgical Processes: A

Continuous Steelmaking Case Study

Mansoor Barati *

Department of Materials Science and Engineering, University of Toronto, WB140, 184

College St. , Toronto, Ontario, Canada, M5S 3E4

Abstract

The demand on primary energy resources of three steelmaking technologies has been evaluated

using an integrated energy analysis approach that takes into account the energy equivalent of major

materials and supplies used in the process, as well as the inefficiency of electricity generation. Two new

parameters, Material CO2 Footprint (MCF) and Process CO2 Footprint (PCF), are defined to provide

unified measures for carbon footprint of the treated materials, and the process respectively. Using these

measures, a comparative study of the three processes has been performed. It is demonstrated that a novel

steelmaking that operates continuously leads to substantial reduction in the overall energy demand, when

compared with the conventional batch processes. CO2 reduction associated with the improvement of the

energy efficiency is presented for several scenarios of power generation.

1. Introduction

Over three decades ago in the wake of 1970’s energy crisis, Kellogg [1] emphasized the

significance of an integrated energy analysis approach for comparing the metal extraction and refining

processes. He suggested that only a comprehensive measure such as Process Fuel Equivalent (PFE), that

takes into account all forms of energy consumed by the process including the inefficiencies in their

generation, as well as the energy associated with processing of all reagents, supplies, and fluxes should

be used to assess and rank competing processes. By definition, PFE represents the total energy consumed

by a given process per unit mass or volume of the product (e.g. kJ/kg) and is calculated as following:

𝑃𝐹𝐸 = 𝐹 + 𝐸 + 𝑆 − 𝐵 (1)

where F is the sum of all fuels used directly by the process; E represents the fuel equivalent of the

electric energy used; S sums the total energy (i.e. fuel and fuel equivalent) consumed to produce the

* Corresponding author: Tel.: +1(416)978–5637 , Fax: +1(416)978–4155

Email address: mansoor.barati@utoronto.ca

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major supplies such as oxygen, lime, fluxes, reagents, etc; and B sums the gross energy value of the by–

products of the process, such as steam, fuel gas, etc.

A second parameter introduced as Material Fuel Equivalent (MFE), and defined in Eq. (2) was

used to measure the total of all energy resources consumed to produce the material from its ultimately

raw form in the nature. In this equation, R is the fuel equivalent of the main raw material fed to the

process in kJ/kg.

𝑀𝐹𝐸 = 𝑃𝐹𝐸 + 𝑅 (2)

As demonstrated in a case study on melting of copper [2], the approach sets a straightforward,

yet reliable measure for comparing energy efficiency of technologies of a similar function. The

advantage of the method is that calculations are very simple, while providing a comprehensive measure

of the process energy intensity. On the other hand, the analysis requires MFE values for essentially any

processed material such as reagents, chemicals, gases, feedstock, etc that is used in the process. Such

information is difficult to obtain due to significant variations from one operation to another, also

inadequate record-keeping of the consumptions. As practiced by Kellogg [1], the most reliable approach

to collect the data is from the average figures of the relevant industry.

In the present work, similar measures will be used to compare the total energy intake of a novel

steelmaking technology with the conventional processes. Also, new parameters for quantifying the

overall greenhouse gas emission of a process are introduced. Both energy intensity and greenhouse gas

footprint are evaluated for the three technologies of interest.

2. Electric Furnace Based Steelmaking and CRISP Technology

Steel manufacturing has been the pioneer industry in energy efficiency, reducing its energy

intensity 55 percent from 1970 to 2000 [3]. Several breakthrough technologies such as preparation of

Blast Furnace (BF) burden, introduction of Basic Oxygen Furnace (BOF) steelmaking, and further

recycling of scrap steel have contributed significantly to this improvement. Among various approaches to

increase energy efficiency of metallurgical processes, there has been an increasing trend in replacing the

conventional batch operations with continuous processes, such as continuous casting [4]. Continuous

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steelmaking however, has yet to be realized despite the known technical and economic advantages for

such process. Several attempts for continuous steelmaking from hot metal or scrap ([5]–[13]) have not

resulted to date in developing a commercial technology, due to technical problems such as short

refractory life, complicated process control, energy efficiency, and low production rate.

While the previous investigations on continuous steelmaking had focused on refining of hot

metal or melting of recycled scrap, a novel steelmaking technology is developed based on Direct

Reduced Iron (DRI) feedstock [14–15]. DRI is a high quality source of iron for Electric Arc Furnace

(EAF) steelmaking that is dominantly produced by reducing iron oxide using a mixture of CO and H2

gases. The DRI together with scrap and fluxes is melted and refined to finished or semi–finished steel in

an EAF. In this method of steelmaking (DR–EAF), DRI is produced continuously, but charged

intermittently to EAF, since the EAF is a batch operation. The new steelmaking process, known as

CRISP (Continuous Reduced Iron Steelmaking Process), overcomes the mismatch problem, by

introducing a stationary, six–in–line electrode EAF that can receive, melt and refine DRI on a continuous

basis. The process relies on an extended refractory life that enables uninterrupted operation of the furnace

for periods in excess of one year. The design and process characteristics of the CRISP have demonstrated

metallurgical [16], [17] and economic advantages [18] against the existing DRI–based steelmaking

technologies.

The latest Direct Reduction (DR) technologies offer a variety of product options including

discharging hot DRI (HDRI) to the EAF directly, to reduce the electrical energy consumption of EAF

about 20 – 30% [19–21], by saving the inherent thermal energy of HDRI. Of the current DR–EAF plants,

only a few enjoy the benefits of HDRI charge, while the majority use cold DRI (CDRI) as the feed,

primarily because of technological limitations at the time they were built. While the advantages of HDRI

feeding are apparent and have been elaborated on previously, a comparison on energy consumption of a

batch EAF and the continuous EAF, i.e. CRISP, has not been made up to now. This is an essential

requirement for development and implementation of a new technology, as the issues of energy

requirement and environmental impact are becoming increasingly important. On the other hand, a simple

energy balance does not yield an adequate measure for comparing energy intensity of various processes,

since the forms of the energies that are utilized (i.e. electrical, chemical), as well as the type and amount

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of fluxes and supplies consumed in each process are different. The current study was undertaken to

perform a comprehensive evaluation on the energy consumption and CO2 footprint of the CRISP

steelmaking, and compare it with the conventional CDRI–EAF (Cold DRI charged EAF) and the rather

recent HDRI–EAF (Hot DRI charged EAF) processes. The methodology of analysis is discussed in the

following section.

3. Analysis Methodology

However, owing to the more diversified energy sources of today (such a larger share of nuclear,

hydropower, and renewable energies) compared to the 70’s “fuel” based energy, the term fuel equivalent

may not be adequately inclusive. Therefore, two new measures are introduced as PEE (process energy

equivalent) and MEE (material energy equivalent), although their calculation is very similar to the PFE

and MFE, respectively.

Similar to the energy terms, the CO2 impact of a process, as well as the total CO2 produced per

unit of the product are defined respectively as PCF (process CO2 footprint) and MCF (material CO2

footprint) as following.

𝑃𝐶𝐹 = 𝐷𝐶 + 𝐸𝐶 + 𝑀𝐶 − 𝑆𝐶 (3)

𝑀𝐶𝐹 = 𝑃𝐶𝐹 + 𝐶𝐶 (4)

where 𝐷𝐶 is the direct CO2 emission by the process, due to the reactions emitting CO2 such as

combustion of fossil fuels and calcinations of carbonates. 𝐸𝐶 presents the CO2 produced as a result of

electricity required for the process. 𝑀𝐶 is the CO2 generated for processing the materials, reagents and

supplies, and 𝑆𝐶 accounts for the amount of CO2 that may be permanently removed from the atmosphere

by the process, such as CO2 sequestration. 𝐶𝐶 in Eq. (4) is the equivalent CO2 of the material, i.e. the

amount of CO2 generated to convert the materials from its natural form into the feed of the process. The

unit for all the parameters are in kg CO2 per unit of the product.

It should be noted that the definitions may be extended to measure the overall global warming

potential of a process or a material, by including the equivalent of other emissions in the calculations.

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4. Energy Intensity of the Steelmaking Processes

The basic parameters of three steelmaking scenarios using DRI as the primary feedstock are

provided in Table 1. As seen, the major differences between process parameters of CRISP and the

conventional EAFs are in (a) source of oxygen to the furnace, (b) injected carbon, (c) off-gas CO/CO2

ratio, and (d) slag composition. The data for the energy analysis were derived from literature [17, 22–35]

as well as calculation of parameters such as heat loss. The following process description explains the

reason of the differences between the process parameters.

The process conditions of CRISP are unlike the conventional EAFs from several aspects. First,

the furnace is significantly larger, while the power input is generally lower [25], indicating that the

melting and refining reactions in this furnace take place under less intense conditions. Therefore, metal–

slag interactions are closer to the equilibrium [17], and the final product carbon is achieved with lower

FeO in the slag. Second, the longer residence time of the steel inside the furnace allows control of the

bath carbon by adding iron oxide rather than gaseous oxygen. Although the reduction of iron oxide in the

slag is accompanied by higher electrical energy consumption, the increase is offset by lower slag FeO

(higher yield), no gaseous oxygen requirement, and less slag volume (reduced energy loss). Third, the

off–gas produced in the CRISP furnace is rich in CO as a result of virtually oxygen-free atmosphere

above the slag, together with reduced air infiltration as a result of a fixed furnace roof. Fourth, slag

foaming, is induced by the reaction between carbon of DRI and FeO from both slag and DRI, hence no

carbon injection is required. It is apparent that the CRISP is highly dependent on electrical energy with

minimum use of chemical energy sources such as coal or natural gas, where in the conventional EAFs,

the energy is supplied through a mix of fuels and electricity. An inclusive and comprehensive energy

analysis is then critical to evaluate the total energy consumption of each process.

1. Materials and Energy Balance

The materials balance on each process was performed to obtain the rates of the unknown streams

such as slag, off-gas, fluxes and iron-bearing feed. A combined materials and energy balance model was

set up, that solves the balance equations, while minimizing the slag weight. The results of the

calculations are provided in Table 2. As seen, the amounts of slag and off-gas in the CRISP operation are

much lower than those in the conventional EAFs. The reduced gas volume in CRISP is primarily a result

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of removing oxygen and natural gas from the system. On the other hand, lower basicity and FeO content

of the slag contribute to the smaller slag amount.

The results of the energy balance are summarized in Figure 1 as Sankey diagrams, showing the

distribution and the total energy for each process. The energy values presented in this figure represent the

energy at the use point. In other word, inefficiencies in production of electricity or energy equivalent of

oxygen lime, etc are not considered here, as they will be presented later. As shown, the total energy

demand of CRISP process is about 10% lower than both hot and cold charged conventional EAFs. This is

chiefly due to the lower off–gas and slag rates as well as the reduced energy loss. The larger heat loss

(per tonne of product) in the EAFs is a result of larger area to volume ratio, more extent of water cooling

requirement (due to smaller spacing between electrodes and wall), as well as the significant losses when

the furnace roof is removed. It is clear from Figure 1 that the total energy demand of the conventional

EAFs is essentially constant regardless of the temperature of the charged DRI. However, charging 90%

of DRI as hot DRI at the temperature of 600 °C, at the specific ratio of 90% DRI – 10% scrap results in a

saving of about 17% in the electrical energy consumption (from 524 to 435 kWh/tonne steel). The

advantage of charging HDRI however may be fully realized using CRISP, where hot DRI is charged

continuously to the EAF.

The energy sources to all three furnaces are in three forms; (a) electrical, (b) chemical, such as

coal, natural gas, and carbon in DRI and electrode, and (c) thermal energy associated with hot charge. It

is evident that the ratio of chemical to electrical energy in EAFs is about two times that of CRISP. The

difference is however offset by the lower total energy demand of CRISP so that the electrical energy

consumption in CRISP is about 505 kWh/tonne steel.

The effect of the reactions in the energy balance was considered it terms of two groups of

reactions; those that involve fuel or fuel–type reactants (such as carbon in the DRI), and the reactions

inherent to each process such as oxidation/reduction of iron (oxide) and formation of slag. The

contribution to energy of the former reactions appears as the energy associated with the particular fuel,

such as coal. For the second group, the effects of all the reactions are combined together as the net supply

(input) or consumption (output) energies. A comparison of energy distribution diagram indicates that the

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net effect of the second type of the reactions for CRIPS is consuming about 10% of the total energy,

while in the conventional EAFs the reactions produce around 2.3% of the total energy. This is a

reflection of the different nature of the reactions in the respective processes, where in CRISP, the iron

oxide is reduced to iron (an endothermic reaction), while it the EAFs, some iron is oxidized and reports

to slag as FeO (exothermic reaction).

The energy distributions presented in Figure 1, are results of the conventional method to the

energy analysis, by isolating the system (furnace), without assigning an energy value to supplies such as

oxygen and lime. This is certainly a very useful approach for day-to-day assessment and optimization of

a process, estimating the processing costs, and operational purposes. It also clearly shows the energy flow

and the potential saving opportunities in a process. However, as discussed earlier, it fails to provide a

comprehensive measure for comparing several processes that consume different mixes of energies and

various types of energy–demanding supplies and materials. The following section describes the use of

PEE and MEE for providing such a measure.

2. Energy Intensity of the Integrated DRI–based Steelmaking Processes

Calculation of the amount of energy resources consumed to produce steel by the three processes

of interest requires the knowledge of the amount and the MEE of each item used in the process. It is

practically impossible to obtain unambiguous MEE values for various supplies and energy forms, as

those are highly dependent on the type of the processing methods, geographical area, and efficiencies of

the processing routes. Nevertheless, by compiling a set of data collected from References [26–36] and

critical assessment of each, as well as estimations by the author, values representing typical North

American operations were obtained. Table 3 present the MEE and MCF values for the commonly used

supplies of EAF. The energy equivalent of electricity was taken as 11,063 kJ/kWh, to take into account a

conversion efficiency of 32.54% [35]. The MEE for HDRI and CDRI were calculated based on the

process parameters of Midrex direct reduction process [36]. For the off–gas MEE, it was estimated that a

minimum 40% of the total chemical and thermal energy of the CRISP off–gas can be effectively utilized.

Continuous operation of CRISP facilitates the recovery of this energy, using a waste heat boiler. The off–

gas energy is not recovered in the common EAF operations thus a zero value was assigned for the two

EAF scenarios.

Page 8 of 20

To calculate the MEE and MCF values for scrap, the recycling rate of steel was considered as

50% [33]. Therefore, the energy intensity of scrap was assumed to be the average of total energy

consumed to make finished steel from recycled scrap and iron ore.

Table 4 presents a summary of the PEE and MEE calculations for the three processes. By

including the energy value of the supplies and taking into account the inefficacy of electivity generation,

the overall energy demand of each steelmaking process, PEE, is obtained. It is seen that the PEE of the

HDRI–CRIP process stands at 6,001 MJ/tonne, about 18 and 14% lower than the conventional EAFs,

charged with HDRI and CDRI, respectively. When PFE is added to energy equivalent of the main feeds,

DRI and scrap, the MEE of steel from each process is obtained. The MEE represents the total energy

value of the steel product. In other words, it measures the sum of all energy resources put into the crude

materials in their natural form, to produce one ton of steel. As evident, the HDRI-CRISP approach

reduces the demand on energy resources about 8 and 3.5% compared to HDRI-EAF and CDRI-EAF.

The concept of MEE may be best visualized by a Sankey diagram as illustrated in Figure 2.

Unlike Figure 1, the energy values presented here represent the total amount of energy consumed to

convert the materials from their most natural form to the processes state. For example, it is seen that the

about 21 GJ of primary energy (from earth resourced) is consumed to produce one tonne of steel through

the HDRI-CRISP approach. The figure depicts the accumulation of energy in the product, as well as the

source of each energy item, as the product evolves from the raw materials. For example, it is clear that

about 49% of the total energy consumption is due to conversion of iron oxide pellets to DRI, while the

share of electrical energy consumed in CRISP is 26.5%. This type of diagram clearly shows the most

energy intensive components of a process.

5. CO2 Impact of the Steelmaking Processes

The greenhouse gas impact of each process is turning into a deciding factor for its adoption

within the industry. The CO2 intensity of steel is lower than the other structural metals such as aluminum

[37]. On the other hand, the contribution of steel industry to the CO2 emission is rather significant,

because of its production in large quantities, exceeding 1.3 billion tonnes per year.

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CO2 intensities of the three processes under study were calculated using Equations (3) and (4).

Similar to the energy analysis approach, the CO2 directly produced from each steelmaking process, and

the total CO2 as a result of producing steel in the integrated ironmaking-steelmaking process were

evaluated. It should be noted that the figures presented in this analysis take into account the CO2–

equivalent of other greenhouse gases (GHG), and may be regarded as an inclusive measure for the global

warming potential of the process.

The information related to MCF for each item was obtained as following. The type and amount

of fuels, materials and supplies, used in the processing steps of each item were obtained from various

references. The data were combined with the CO2 emission coefficient for the items, to yield the MCF

(Table 3). The CO2 emission caused by electricity generation is highly sensitive to the energy source

ranging from 0.009 kg/ kWh for wind power, to 1.05 kg/kWh for coal-fired power generators [38].

According to materials balance calculations, the CO2 rate in the HDRI–CRISP, HDRI–EAF, and

CDR–EAF facilities are 59, 105, and 106 kg CO2/tonne steel, respectively. The significantly lower CO2

rate in the CRISP process is primarily a result of eliminating the coal injection practice.

The results of the PCF analysis on integrated ironmaking–steelmaking processes are presented in

Figure 3. Also, for the sake of comparison, the PCF for the more common BF–BOF steelmaking route is

provided. The calculations made for the three DRI–based technologies are based on CO2 rate of 0.6 kg

CO2–e/kWh that is close to the rate of GHG emission for electricity generation in the U.S. and Germany

[23]. Figure 3 shows that the DRI–based technologies are more environmentally friendly, having 25–

30% smaller CO2 footprint than the dominant BF-BOF steelmaking. Reliance of BF on coke as the major

fuel gives rise to the high rate of CO2 for this process. Between the three processes using DRI, CRISP–

based integrated steelmaking is the least GHG emitting process, presenting a 10% reduction in CO2

against the conventional CDRI–EAF.

A sensitivity analysis was performed to evaluate the effect of the method of electricity

generation on the MCF. Figure 4 shows the variations in the CO2 footprint per tonne of liquid steel, as a

function of CO2 rate for electrical energy. Also indicated in Figure 4 are the positions of the most

common sources of energy used in electricity generation. Clearly, the source of primary energy in the

Page 10 of 20

power plant has substantial impact on the MCF. For example, a shift from coal–based electricity to

hydropower can reduce the emissions by 50 %.

6. Conclusions

Two new parameters for measuring the carbon footprint of a process and that of treated materials

were established. The parameters bring together both the direct CO2 emission and the indirect CO2

released during the processing of material as a result of energy use. Similarly, measures were used to

provide a unified energy figure for each process, by taking into account the direct energy use together

with the energy value of the materials used. The method was employed to compare the energy utilization

and CO2 emissions of a novel steelmaking technology with conventional processes. The new process,

CRISP, close links existing DRI making units with a stationary electric arc furnace that unlike the

common EAFs operations, is continuous. Energy–materials balance was performed to obtain energy

distribution for each process. Also, for a logical comparison of energy intensity of the three processes –

using various mixes of energy forms and consuming different materials – a comprehensive measure of

energy consumption was employed. The CO2 footprint of each process and its sensitivity to the primary

energy for electricity generation was examined. The following important conclusions can be drawn from

the study.

1. A comparison of true energy consumption and carbon footprint of several processes that use

various sources of energy and materials is possible through comprehensive measures such as PEE

and PCF.

2. The net energy consumed in CRISP steelmaking is about 10% lower than the current DRI–based

steelmaking technologies. When the energy value of supplies and off-gas credit are considered, the

CRISP energy saving is 14–18%.

3. Hot charging of DRI lowers the consumption of electrical energy about 20 – 30%. However, the

total energy balance remains unchanged.

Page 11 of 20

4. The integrated HDRI–CRISP steelmaking reduces the energy intensity of steel by about 8 and 3.5

% compared to the conventional EAFs charged with hot and cold DRI, respectively. The energy

value of molten steel for the former process is about 20.9 GJ/tonne.

5. Greenhouse gas emissions of the DRI–based steelmaking is 25–30% lower than that the common

BF–BOF technology. Of the three processes using DRI, CRISP has the lowest CO2 emission,

around 10% lower than the conventional EAFs.

6. The CO2 impact of the DRI–based steelmaking is highly sensitive to the CO2 rate of electricity

generation, providing the potential to cut the GHGs by 50%, using renewable energies such as

hydropower.

7. Acknowledgements

The author wishes to thank Hatch and Ontario Centres of Excellence for partially funding the

study. Insightful comments by Frank Wheeler and the permission by Hatch to use process data of CRISP

are greatly appreciated.

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Production processes. Journal of Cleaner Production 2007; 15(8–9): 838–848.

[38]. Gagnon L, Bélangery C, Uchimaya Y. Life–Cycle Assessment of Electricity Generation

Options: The Status of Research In Year 2001. Energy Policy 2002; 30(14): 1267–1278.

Page 14 of 20

Appendix: Detailed Calculation of MEE, PEE, MCF, and PCF for Manufacture of Lime

a) Mining and beneficiation of limestone

According to data extracted from [27], the following are obtained for average energy consumption and

CO2 emissions.

Energy consumption (per tonne of limestone):

Electricity = 2.995 kWh

Fuels = 27.9 MJ

The use of primary energy sources to generate electricity based on conversion of 11.063 MJ/kWh is:

2.995 × 11.063 MJ/kWh = 33.1 MJ/tonne

Therefore, total consumption of primary energies for extraction and processing of limestone is 61.0

MJ/tonne

CO2 Release:

Based on the mix of fuels, the CO2 generated as a result of using fuels is 2.03 kg /tonne, while CO2

generated because of electricity generation (at the rate of 0.6 kg/kWh) is: 2.995×0.6 = 1.80 kg/tonne.

Total CO2 footprint of limestone extraction and beneficiation is thus: 1.80+2.03 = 3.83 kg/tonne

limestone.

The MEE and MCF of limestone are thus 61.0 kJ/kg and 0.038 kg/kg, respectively.

b) Calcination of limestone to produce lime

According to data extracted from [27, 30, 34] and complied, the following are obtained

Item Consumption

(per tonne lime)

MEE

(Energy Value)

MCF Energy Use

(MJ/tonne)

CO2

Generation

(kg/tonne)

Electricity 69.1 kWh 11.063 MJ/kWh 0.6 kg/kWh 765 41.5

NG 73.5 Nm3 38.18 MJ/Nm3 1.89 kg/Nm3 2804 138.8

Heavy Fuel Oil 0.006 m3 42500 MJ/m3 3090 kg/m3 263 19.1

Middle Distillates 0.001 m3 38680 MJ/m3 2830 kg/m3 39 2.8

Propane 0.00006 m3 25310 MJ/tonne 1500 kg/m3 1 0.1

Pet Coke 0.045 tonne 38650 MJ/tonne 3500 kg/tonne 1724 156.1

Coal 0.055 tonne 26280 MJ/tonne 2480 kg/tonne 1443 136.1

Coke 0.006 tonne 28830 MJ/tonne 2480 kg/tonne 178 15.3

Total 7217 510

The analysis shows that total consumption of primary energies (PEE) for limestone calcinations is 7217

kJ/kg lime. On the other hand, CO2 emission due to use of this energy is 0.51 kg/kg lime. During the

process, another 0.746 kg of CO2 is released per each kg of lime (limestone composition being 95%

carbonates, 5% gangue), making the total CO2 release 1.256 kg CO2/kg lime.

Accordingly, The PEE and PCF of limestone calcinations process 72717 kJ/kg lime and 1.26 kg/kg lime,

respectively.

c) Total Energy Requirement and CO2 Release for Production of Lime:

Based on Lime/Limestone conversion of ~ 0.504 (95% carbonates, 5% gangue in the limestone), the

overall energy intensity (MEE) and CO2 footprint (MCF) for production of one tonne of lime are then

calculates as:

MEE = 7217 + 61/0.504 = 7338 MJ/tonne = 7338 kJ/kg lime

MCF = 1255.9 + 3.8/0.504 = 1263 MJ/tonne = 1.26 kg CO2/kg lime

Page 15 of 20

Figure Captions

Figure 1 – Energy distribution in the three steelmaking scenarios.

Figure 2 – Energy flow in the HDRI–CRISP steelmaking

Figure 3 – PCF for various steelmaking routes

Figure 4 – Effect of CO2 intensity of electrical energy on the steelmaking GHG emission

Table Captions

Table 1. Typical operating parameters of three DRI–based steelmaking approaches

Table 2. The materials balance (all units per tonne liquid steel)

Table 3. MEE and MCF for the materials and supplies used in EAF

Table 4. Total energy intensity of DRI–based steelmaking processes (MJ/tonne)

Page 16 of 20

Figure 1 – Energy distribution in the three steelmaking scenarios.

Figure 2 – Energy flow in the HDRI–CRISP steelmaking

(a) HDRI-CRISP

2690 MJ/t LS 3036 MJ/t LS

(b) HDRI-EAF

3043 MJ/t LS

(c) CDRI-EAF

Electricity

67.6%

Steel

50.8% 45.1%

Steel

45.0%

Steel

51.6%

Electricity

62.0%

Electricity

DRI (Chemical)17.5%

DRI (Thermal)12.8%

Electrode carbon2.1%

Losses & cooling10.2%

Reactions11.1%

Slag12.4%

Off-gas15.5%

16.4% DRI (Chemical)16.4% DRI (Chemical)DRI (Thermal)10.8%

2.3% Electrode carbon 2.3% Electrode carbon

10.1% Coal

7.0%Natural gas

2.3% Reactions

Coal10.1%

Natural gas7.0%

Reactions2.3%

Losses & cooling21.0% Losses & cooling20.9%

Slag15.9% Slag15.8%

Off-gas18.1% Off-gas18.3%

Iron ore

Ext

ract

ion

&

ben

efic

atio

n

Pel

leti

zin

g &

in

du

rati

on

HDRI production

Scrap

48.9%

Burnt dolomite production

Electrode

Refractory

Pelletizing & induration

Iron ore extraction & benefication

CRISP steelmaking

Off-gas credit

Steel

HDRI

Pellet

Lime production

8.9

% 0.8

%

1.0

%

0.4

%

0.1

%

0.4

% 26

.5%

9.0%4.0%61.9%

0.8%

99.2%

0.1%0.3%

Total Energy = 21.08 GJ/tonne liquid steel

HDRI-CRISP

Page 17 of 20

Figure 3 – PCF for various steelmaking routes

Figure 4 – Effect of CO 2 intensity of electrical energy on the steelmaking GHG emission

1310

14091452

1922

800

1000

1200

1400

1600

1800

2000

HDRI-CRISP HDRI-EAF CDRI-EAF BF-BOF

kg C

O2

/ To

nn

e L

iqu

id S

teel

Process

800

1000

1200

1400

1600

1800

2000

0 0.2 0.4 0.6 0.8 1 1.2 1.4

kg C

O2

-e/

Ton

ne

Liq

uid

Ste

el

CO2 Intensity of Electricity Generation (kg CO2-e/kWh)

CRISPH-EAFC-EAF

Hydro-power

NaturalGas

Coal

Page 18 of 20

Table 1. Typical operating parameters of three DRI–based steelmaking approaches

Parameter Unit HDRI–

CRISP

HDRI–EAF CDRI–EAF

Electrode consumption kg/ t. Ls 1.7 1.7 2.1

Refractory

consumption

kg/ t. Ls 1.8 3.6 3.6

Carbon injection kg/ t. Ls 0 9 9

Oxygen source – Iron Oxide O2 O2

Natural gas Nm3/t. Ls 0 6 6

DRI/Scrap ratio – 9 9 9

Off–gas CO/CO2 – 9 1 1

Hot DRI Temp °C 600 600 25

Off–gas Temp °C 1625 1625 1625

Steel Temp °C 1630 1630 1630

Slag Temp °C 1650 1650 1650

% Hot DRI 100 90 0

% Cold DRI 0 10 100

Slag parameters

FeO wt% 22 30 30

MgO wt% 12 8 8

Basicity (V ratio) – 1.75 2.5 2.5

Table 2. The materials balance (all units per tonne liquid steel)

Parameter Unit HDRI–

CRISP

HDRI–EAF CDRI–EAF

Input

Page 19 of 20

Cold DRI kg 0.0 101.2 1012.1

Hot DRI kg 959.8 910.9 0.0

Scrap kg 106.6 112.5 112.5

Iron ore pellets kg 46.4 0.0 0.0

Lime kg 28.0 65.2 65.2

Burnt dolomite kg 24.3 19.6 19.6

Oxygen Nm3 0.0 44.0 44.5

Output

Steel kg 1000.0 1000.0 1000.0

Slag kg 128.9 192.5 192.5

Off–gas Nm3 30.1 68.9 69.6

Table 3. MEE and MCF for the materials and supplies used in EAF

3. MEE

(kJ/kg)

MCF

(kg CO2–e/kg)

Iron Ore Conc. 729 0.05

Iron Ore Pellets 1,961 0.17

Cold DRI 13,315 0.69

Hot DRI 13,584 0.71

Coal 29,255 2.49

Steel scrap 17,544 1.75

Burnt dolomite 7,278 1.38

Lime 7,338 1.26

Electrode 46,738 4.13

Page 20 of 20

Refractory 14,556 1.90

Oxygen 3,875 0.21

Natural Gas 53,485 2.43

Table 4. Total energy intensity of DRI–based steelmaking processes (MJ/tonne)

HDRI–CRISP HDRI–EAF CDRI–EAF

Electrical 5,589 4,812 5,798

Fuels – 492 492

MEE of Supplies 579 996 1,018

MEE of By–products 167 – –

PEE (of the Steelmaking

process)

6,001 6,301 7,309

MEE of DRI and Scrap 14,909 15,694 15,450

MEE of liquid steel 20,910 21,995 22,759