Japanese Steel Industry - Engineering approach, rather than economic - PowerPoint PPT Presentation

The 5th IAEE Asian Conference, Perth, Australia Feb 14-17, 2016 Carbon Intensity and its Determinants in Japanese Steel Industry - Engineering approach, rather than economic approach - Junichiro Oda*, Keigo Akimoto, Takashi Homma Systems analysis group Research Institute of Innovative Technology for the Earth (RITE) Kyoto, Japan *Contact us: jun-oda@rite.or.jp

Contents 2 1. Introduction 2. Analysis results: quick view 3. Methodology, and results 4. Summary

1.1 Overview of steelmaking process in Japan 3  Carbon intensity, e.g., 196 MtCO 2 / 113 Mt crude steel = 1.743 (tCO 2 /t crude steel)  Hot metal ratio, e.g., 83 Mt pig iron / 113 Mt crude steel = 0.74 Upstream Downstream Ref) RITE Oxygen Coke oven Coal Hot meal (Pig iron) Basic oxygen furnace (BOF) Sintering Iron ore, etc Blast furnace furnace (BF) Liquid steel Steel scrap Electric arc furnace (EAF) Rolling mill Heating furnace Crude steel Continuous casting Steel products

Appendix: Energy and climate policies of Japanese industry 4  Regulations  RD&D financial and technical supports  The Energy conservation Act  Taxes  Voluntary Actions (VAs)  Energy taxes  [From 1997 to 2012 ]  Duties on imported energy  Carbon taxes Voluntary Action Plan on the Environment  [From 2012]  Tax credits Commitment to a Low Carbon  Investment in RD&D Society  Investment in energy saving facilities  Green energy, e.g., PV, wind

1.2 Carbon intensity of Japanese steel industry (1/2) 5  The Japanese steel industry has been reporting their carbon intensity under  [From 1997 to 2012 ] “ Voluntary Action (VA) Plan on the Environment ”, and Higher intensity  [From 2012 ] “ Commitment to a Low Carbon Society (Lower efficiency) 2.0 Reported carbon intensity in Japan Carbon intensity (tCO 2 /t crude steel) 1.743 Next slide 1.5  These VAs are “negotiated agreements” rather than “VAs”  The coverage of VAs is around 98% 1.0  FY2016 time schedule is fixed: 2016 2015 Mar Jun Dec Apr FY2015 0.5 Data Third party commissions Ref) RITE estimates based on the Japan Iron and gathering about FY2015 carbon intensity Lower intensity Steel Federation report (Higher efficiency) 0.0 FY00 FY02 FY04 FY06 FY08 FY10 FY12 FY14

1.2 Carbon intensity of Japanese steel industry (2/2) 6  Carbon intensity (tCO 2 /t crude steel) was improving until the 2008 financial crisis  After that, apparently, there was no clear time trend of carbon intensity Higher intensity (Lower efficiency) 1.85 Reported carbon intensity in Japan Carbon intensity (tCO 2 /t crude steel) 1.80 1.75 1.743 The 2011 East  Including EAFs Japan Earthquake  Fixed emission 1.70 factor for grid Ref) RITE estimates based The 2008 electricity, i.e., on the Japan Iron and Lower intensity financial crisis 0.42 kgCO 2 /kWh Steel Federation report (Higher efficiency) 1.65 FY00 FY02 FY04 FY06 FY08 FY10 FY12 FY14

1.3 Objectives 7  To answer these two questions: Question 1 What is the determinant of carbon intensity (tCO 2 /t crude steel)?  Short-term (yearly) fluctuation of carbon intensity  Long-term (FY2000-FY2014) trend of carbon intensity Question 2 Can we observe a long-term trend of carbon intensity improvement? Did VAs (negotiated agreements) have an effect on carbon intensity improvement?

2.1 Analysis results: FY2007 vs FY2008 8 1.763 ⊿ x 1 (capacity factor): +0.063 Reported carbon [CF 104.8  91.2 (FY2005=100)] intensity +0.072 +4.3% point ⊿ x 2 (upstream): +0.030 [Hot metal ratio 0.723  0.744] 1.691 ⊿ x 2 (downstream): -0.004 ⊿ x3 (time trend variable): -0.005 FY2007 FY2008 ⊿ Residual error: -0.012  The effect of the 2008 financial crisis (effect of CF decrease) was significant

2.2 Analysis results: FY2000 vs FY2014 9  The time trend variable implies diffusion of energy saving from FY2000 to FY2014 1.846 Reported carbon intensity ⊿ x 1 (capacity factor): +0.010 -0.085 [CF 93.9  91.7 (FY2005=100)] -4.6% point ⊿ x 2 (upstream): +0.013 [Hot metal ratio 0.755  0.764] 1.761 ⊿ x 2 (downstream): -0.019, [Effect of steel product mix] FY2000 FY2014 ⊿ x3 (time trend variable): -0.071 ⊿ Residual error: -0.018

3.1 Methodology 10  Parametric regression Effects on carbon intensity = β 1 × ( x 1,t – x 1,2005 ) x 1. Capacity factor index Unknown parameters solved by ordinary least Effects on carbon x 2. Production process index squares (OLS) regression intensity are  Upstream: Hot metal ratio exogenously given  Downstream: Steel product mix Effects on carbon intensity = β 2 × ( t – 2005) x 3. Time trend variable  Improvement factor: Diffusion of energy saving tech. (?)  Worsening factor: Aging facilities (?)

3.2 Capacity factor 11 Capacity factor index ( x 1 ) Production process index ( x 2 ): Upstream, Downstream Capacity factor index 110 Capacity factor index (FY2005 = 100) 105 99 101 100 103 100 Weight 96 94 32%-33% 93 91 91 92 90 62%-65% 91 89 89 Blast furnaces (BFs) 3%-5% Electric arc furnaces (EAFs) 82 80 Industrial Production Index Weighted average Note) We referred to monthly 70 capacity factors (reported by METI) and convert 00 02 04 06 08 10 12 14 them into annual data FY

3.3 Upstream production process 12 Capacity factor index ( x 1 ) Production process index ( x 2 ): Upstream, Downstream Relationship between hot metal ratio Hot metal ratio Iron ore dominant and upstream index 0.78 1.80 0.774 FY01 y = 1.42x + 0.70 Hot metal ratio (t pig iron/t crude steel) Upstream index (FY2005=1.743) 0.764 FY12 FY14 0.764 1.78 0.76 0.754 FY00 FY11 0.752 FY09 FY13 0.755 2.5 FY10 1.76 Upstream index 2.12 0.746 0.751 0.744 FY08 FY03 0.748 FY02 FY05 0.74 0.743 FY05 0.70 0.736 1.74 FY08 0.0 0.734 0.723 0 1 Hot metal ratio FY07 0.721 1.72 FY06 0.72 0.72 0.74 0.76 0.78 2000 02 04 06 08 10 12 14 Hot metal ratio (t pig iron/t crude steel) FY Iron ore dominant Note) We referred to METI statistics Scrap dominant

3.4 Downstream production process (1/2) 13 Capacity factor index ( x 1 ) Production process index ( x 2 ): Upstream, Downstream “Steel product share” × “intensity” Export price from Japan Examples of steel products 400 367 Seamless pipe Stainless steel sheet Export price (nominal US$/t steel) 323 273 300 237 Stainless steel 177 200 except seamless pipe Ref) http://sumitomothailand.co.th/ 82 100 69 59 Wide flange & H beams Steel bar 44 26 Steel bar 0 00 02 04 06 08 10 12 14 FY Note) RITE estimates based on Trade Statistics of Japan

3.4 Downstream production process (2/2) 14 Capacity factor index ( x 1 ) Production process index ( x 2 ): Upstream, Downstream Special steel (14) 100% 3.2% 3.0% 3.2% 3.0% 2.9% 2.8% 3.2% 3.2% 2.7% 2.8% 2.8% 3.3% 3.4% 3.5% 3.5% 3.0% 3.5% 4.4% 26-29,31. Other special steel 4.2% 4.4% 4.6% 5.2% 4.2% 4.3% 4.6% 5.4% 5.5% 4.4% 5.2% 5.1% 5.8% 5.6% 90% 6.7% 6.4% 6.9% 7.2% 7.9% 7.4% 7.6% 7.9% 7.9% 8.2% 8.2% 8.3% 8.5% 2.6% 30. High-tensile steel 2.9% 2.7% 2.9% 3.0% 2.4% 2.7% 2.7% 2.6% 2.5% 2.5% 2.5% 2.7% 2.6% 2.6% 6.2% 6.1% 80% 4.5% 5.5% 5.5% 5.6% 24,25. Structural steel 5.7% 5.5% 5.6% 4.9% 4.9% 5.7% 4.8% 4.6% 4.7% 70% 21-23. Tool steel 16.8% 16.1% 16.8% 17.3% 17.0% 17.1% 17.0% 17.0% 16.4% 16.7% Share of final steel products (%) 16.7% 16.1% 16.1% 15.6% 15.1% 20. Stainless 60% 8.9% 9.4% 10.0% 8.3% 8.6% 9.2% 8.7% 8.5% 9.6% 8.5% 9.5% 8.8% 9.3% 18,19. Special pipe 10.1% 9.0% 50% 13.2% 13.8% 16,17. Ordinary pipe 14.7% 13.3% 13.5% 11.8% 12.6% 13.6% 12.7% 16.2% 15.7% 15.5% 17.7% 17.9% 18.8% 40% 12-14',15. Coated sheet, coil 8.7% 9.6% 9.0% 10.2% 11.0% 12.0% 11.4% 12.2% 14.5% 13.1% 30% 10,11. Cold rolled sheet , coil 12.9% 13.0% 11.8% 11.0% 11.2% 20% 9,9'. Hot rolled coil 29.6% 29.2% 26.7% 25.4% 24.2% 24.5% 25.0% 23.9% 23.3% 21.6% 19.2% 20.5% 21.0% 21.9% 21.2% 7,7',8. Hot rolled plate, sheet 10% 1-6. Long products 0% Ordinary steel (20) FY00 FY02 FY04 FY06 FY08 FY10 FY12 FY14  We aggregated steel products (about 45 steel products by METI stat. and about 620 steel products by Trade Stat.) into 34 categories

3.5 Results from FY2000 to FY2014 15 Reported carbon intensity Estimates: 1.743+ ⊿ x1+ ⊿ x2+ ⊿ x3 106.1 Capacity factor index: x1 Production process index: x2 1.85 Time trend variable: x3 Relative carbon intensity (FY05=100) Carbon intensity (tCO 2 /t crude steel) 103.3 1.80 ⊿ x 1 100.4 ⊿ x 2 1.75 100 ⊿ x 3 97.5 1.70 Coefficient of capacity factor index ( x 1): Time trend variable ( x 3): -0.005 tCO 2 /t/y [t-stat: -8.7] -0.26% per 1% point [t-stat: -13.6] This is equivalent to a 0.3%/y of improvement rate. 94.7 1.65 FY00 FY02 FY04 FY06 FY08 FY10 FY12 FY14  The estimates well explain the reported carbon intensity trajectory  Determinant of annual fluctuation: capacity factor  Determinant of long-term trend: time trend variable