List of abbreviations
AIST Association for Iron & SteelTechnology
BF
Blast furnace
BOF Basic oxygen furnace
CCContinuous casting
DRI Direct reduced iron
EAF Electric arc furnace

May 1, 2022

Estimated energy intensity in 2019:
Iron and steel sector (scrap-EAF route)
Systems Analysis Group
Research Institute of Innovative Technology for the Earth (RITE)
TEL: +81-774-75-2304 E-mail: sysinfo@rite.or.jp
Junichiro Oda
Graduate School of International Resource Sciences
Akita University
TEL: +81-18-889-3277 E-mail: oda@gipc.akita-u.ac.jp

1. Introduction

Background and purpose

Background In order to promote early and effective GHG emission reduction, it is necessary
to understand the energy intensity and the reduction potential of each region inthe world.
 By using the results of EAF steel presented this time in addition to the estimation
results of the energy intensity of the integrated steelworks already presented, it
will be possible to calculate the GHG reduction potential of the entire steel
industry.
 There is increasing mention of carbon neutrality, but before that it is important toshare such information widely.
Purpose The purpose is to provide comparable energy intensity estimates for the steel
sector in 2019 to contribute to the discussion of climate change mitigation.

2

1. Introduction

Analytical framework3 The energy intensity is measured by the energy consumption (GJ) per 1t of crude steel production.
 Electricity is converted at a rate of 1MWh = 3.6GJ / 0.333 = 10.8GJ for all regions.
 Assuming the case of manufacturing ordinary steel products using scrap (the processes in [ ] below
are the evaluation targets).
Scrap gathering, cutting, and compression processes → Transportation of materials to steelplants → [Preheating → EAF → Secondary refining → CC → heat treatment furnace → Hotrolling] → Finishing/final processing → Steel product shipment
 Energy intensity is estimated by combining the following methods.
A: Refer to the absolutevalue of energy intensity

B: Refer to relative change
in energy intensity compared
to 2015

1. Method based on Association for Iron and SteelTechnology (AIST) "2020 EAF Roundup"

Method A1

Method B1

2. Micro-data approach based on individual statistics
for each region

Method A2

Method B2

3. Macro-statistics approach based on IEA "WorldEnergy Balances"

Method A3

Method B3

4. Assumed energy intensity given the new capacity isapplied to the energy intensity for 2015

Method B4

1. Introduction

Consolidation of steel production methods

4

 Not only scrap but also DRI and pig iron are widely used as iron sources for EAF.
 Steel production methods are classified into 1) BF-BOF, 2) scrap-EAF, and 3) DRI-EAF.
 Scrap-EAF is deﬁned as a process in which 100% of the iron source is scrap, and thisanalysis focuses on Scrap-EAF.
Crude steel production categorized by route in 2019
BF-BOF
Total crude steel production → 87.8

100%

4%

7.2
21%

Ratio

75%

14.5 39.6
1%

30%

29%

Scrap-EAF

157 99.3 71.4
41%

24%

996

111 31.7

10%

10%

32%

37%

50%
25%

70%

70%

59%

76%

30%
0%

Note: EU (28) figures, including the UK, are shown for easy comparison with previous results

33.7 44.3 60.7 101 1875 Mt
16%

34%

66%
79%

DRI-EAF

90%
68%

44%

6%

21%

22%

71%

72%

31%

68%

22%

8%

94%
53%

54%
32%
6%

Ref： Estimation based on worldsteel “Steel Statistical Yearbook 2021 (Extended version)”2. Method A1, B1

AIST “2020 EAF Roundup”

5Ref: Excerpts from AIST's public version sample, etc.

 This AIST table is based on EAF data reported by AIST participating companies.
 Production capacity, iron source ratio, power intensity (kWh/t), natural gas intensity (Nm3/t),
etc. are listed for each EAF.
 However, there are some N/A terms marked with "-" in the table.

2. Method A1, B1

Coverage of AIST “2020 EAF Roundup”

CanadaU.S.
MexicoBrazilColombia
EcuadorPeru
Chile
Argentina
UruguayGermany
Italy
Australia
AIST total

6

Number of EAFs
listed in AIST

Coverage of AIST “2020EAF Roundup”

N/A term ratio

19131
17127323811113
218

100%
100%
75%
44%
100%
100%
46%
100%
100%
100%
10%
57%
100%
78%

10%
20%
25%
5%
15%
75%
30%
0%
31%
0%
0%
5%
0%
18%

2. Method A1, B1

Complementing data in AIST “2020 EAF Roundup”
Relationship between capacity andpower consumption intensity

Power consumption (kWh/billet ton)

Power consumption (kWh/billet ton)

N=154800

700
600
500
400
300
200
1000Relationship between scrap ratio andpower consumption intensity

N=154800

7700
600
500
400300200
10000500

1000

1500

Capacity (kt/y)

2000

2500

02550Scrap ratio (%)

75100

2. Method A1, B1Results based on AIST “2020 EAF Roundup”

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Estimated primary energy intensity of EAF(Corrected when 100% of iron source is scrap)

Primary energy intensity(GJ/billet ton)7654

 The energy consumption in the above figure covers only EAF.
 By adding 2.96 GJ/t to the upper end of the above figure, the boundary becomes consistent and canbe compared with other estimated values.
 2.96 GJ/t is an estimated value of energy consumption for secondary refining, continuous casting, heattreatment furnace, hot rolling equipment, etc.

3. Method A2, B2

Micro-data approach based on individual statistics
Europe Energy intensity of European countries was estimated with reference to Eurostat EnergyBalances (2022 edition) in the figure below.
 For example, the following estimates for Germany were obtained: A2: 8.4 GJ/t, B2: 8.6 GJ/t.

https://ec.europa.eu/eurostat/web/energy/data/energy-balances

Japan Japanese energy intensity was estimated based on “General Energy Statistics.”

94. Summary

Estimated results for 2019 (Japan = 100)

10

 The following final estimation results were calculated by weighted averaging the estimated values
obtained by methods A1 to B4.

Energy intensity estimation result of scrap EAF for 2019 (Japan = 100)
Primary energy intensity of scrap EAF(GJ/t crude steel) [Japan = 100]

120

110

100

100

101

103

103

104

China

U.S.

Germany

106

107

Spain, EU (28)PortugalItaly

104112113Russia

India

108

9080

Japan

Korea

TurkeyNote: EU (28) figures including the UK are shown for comparison with existing results.

4. Summary

Estimated results for 2005-2019

11Energy intensity estimation result of scrap EAF

Primary energy intensity of scrap EAF(GJ/t crude steel)

12

2005

2010

2015

2019

108

6

4U.S.

Germany

Italy

Spain, EU (28)Portugal

Japan

Korea

China

India

TurkeyRussiaWorldAverage

Note: EU (28) figures including the UK are shown for comparison with existing results.