Developing LPS downscale model and apply to Chinese iron andsteel industry
Zhaoling Li1, Tatsuya Hanaoka1
1 Center for Social and Environmental Systems research, National Institute for Environmental Studies, Tsukuba 305-8506, Japan
ISIplant_2018database<all other values>
6 - 300
301 - 500
501 - 700
701 - 900
901 - 1200
1201 - 1700
1701 - 2200
2201 - 2700
2701 - 3400
3401 - 4100

1. Introduction

2. Research area

This research aims to establish a Down Scale Model to provide a decision tool for iron and steel (IS) plant
planning at the national level. Given to the trend of rapid growth in iron and steel industry (ISI) in Southeast Asia
countries and the possible downward trend in developed countries and China, there are two aspects should beconsidered in the model, which are the viability of optimal location for new iron and steel plant and the appropriate
algorithm to shut up outdated facilities. The model is built up by: Analyzing the correlations among LPS location and evaluation factors, including transportation, naturalcondition, economy, policy and environmental criteria, based on historical data; Designing an evaluating algorithm of allocating LPS and verifying the possibility by adapt a case study; Allocating the air pollutants emissions on industrial level.

China’s crude steel output experienced a rapid growth in last two
decades, and lots of IS plants has been constructed. So, it is atypical case for analyzing the correlation between plant allocationand the criteria. On the other hand, China is eliminating theoutdated equipment and plants to fix the problems in ISI, such as
overcapacity and outdated technologies. Moreover, the crude steel
demand is predicted to decrease after entering the late urbanization
stage. Both of these two aspects could give a good reference forFig.1 Iron and steel plant in China based on Jams Kingbuilding up the Down Scale Model (Fig. 1).
2018 database

Enduse modelServicedemand model
Emission pass way

1) Distance to railway/highway;2) Surface water reserves;
3) Land cover;4) Distance to raw materials;
5) GDP and POP
6) Policy

1) Transportation;2) Slop;3) Land cover type;4) Grid occupancy;
5) Water resource;
Constraint criteria

LPS
data

New DSL
model

5401 - 6300
6301 - 7700
7701 - 9000
9001 - 10300
10301 - 14000
14001 - 20000
20001 - 30000
30001 - 150000

Evaluation criterial

New plant allocation

HealthimpactSorting principle

Distance to railway/highway

the closer, the better

Surface water reserves

the more, the better

Distance to raw materials

the closer, the better

GDP and POP

S1: the higher, the betterS2: the lower, the better∑

10,11,40,130,190,200 (1)10,11,40,130,190,200(2)

10,11,40,130,190,200(3)∑10,130,190,/: area of each land cover type (l) within one grid (g);: area of grid;
R: ratio of each land use type and the total area within one grid;
Sn: ranking of each land use type and give serial number based on the ratio;: ranking of each grid based on the sum of serial number of total area and eachland cover type, lower is better, and give each grid a serial number accordingly;

(4)
⁄

（5）

S2

S1

Laborloss

Fig. 3 Appropriate locations for new iron and steel plant

For the grid ranking based on land cover type, there are four principles that need to be considered. ① gridoccupancy, ②cropland and ③grassland areas: the higher, the better; ④urban area: the lower, the better.

Small-scale enterprise

Estimate the industrial emission concentration
until 2050

Old facilities

Atmosphericmodel

Small scale capacity

Induction furnace andOHF Martin

Plant levelEmission map(1) New plant allocation
Databases showed in Tab. A-1 are attached in 30km×30km grid cells map, each cell representing an alternative
location for a IS plant. Constraints criteria is to exclude the infeasible sites. Selection parameter is decided based on
the condition of existing plants and the result is shown in Fig. 3.
Selection criteria is using for ranking the priority of each appropriate sites (remaining grids in Fig. 3) according tospatial multi-criteria decision making. Sorting principles of some selection criteria are showed in Tab. 1.
Tab. 1 Sorting principles of some selection criteria

Selection criteria

Close outdated facility

Ecologic
al loss

4701 - 5400

4. Algorithm construction

3. Research framework

Economic loss

4101 - 4700

S1

Cs: carbon emission
LPS: Large point source

Fig. 2 Research framework
S2

5. Case study

LegendTab. 2 Future demand of crude steel in China in SSP2 scenario
2015
2020
2025
2030
2035
2040

2045

2050
844404

Demand in SSP2 (kt)8202659817261066304

10740901032735

975297912056

Import amount (kt)

13178

13178

13178

13178

13178

13178

13178

13178

Domestic production (kt)8070879685481053126

10609121019557

962119898878831226

Current capacity (kt)9731651054130

1064925

1021358964580897952833404

Increasing demand (kt)

27769

79960

6782

-45368-59239-65702-66726

Ferrous scrap stock (kt)261814368022435130486812

517658528702525033

EAF capacity demand (kt)170262239331282972316582

33664234382434143861520000-22072.84

17250.87-36859.49 -96595.31-78279-72233-64103

88.63

89.73

88.743

88.34

87.22

Number of new plant
BOF capacity (“-” means BTE)
Operating ratio (OR) (%)

89.57

89.36

11 1
14 11
3
11 - 1130 29
11 - 1142 41
11 - 1148 47
11 - 1151 50
11 - 1155 54
11 - 1161 60
11 - 1167 66
11 - 1169 68
11 - 1172 71
11 - 1174 7311 - 1176 75
11 - 1196 95
12 - 1216 15
12 - 1221 20
12 - 1231 30
12 - 1233 32
12 - 1250 49
12 - 1265 64
12 - 1295 94
13 - 1303 02
13 - 1328 27
19 - 1904 03
20 - 20
26 25
20 - 2038 37
20 - 2040 39
20 - 2057 56
20 - 2070 69
20 - 2077 76
21 - 21
21 20
21 - 2154 53
22 - 2213 12
22 - 2225 24
22 - 2231 30
23 - 23
11 1023 - 23
13 12
23 - 23
17 16
23 - 2340 39
23 - 2345 44
23 - 2357 56
23 - 2359 58
23 - 2380 79
24 - 24
22 2124 - 2457 56
24 - 2467 66-251
2

Crude steel demand based on SSP2 scenario will peak in 2030 and then decrease (Tab. 2). In this case, we should
consider both new plants construction and facility shut down in China until 2050. Moreover, electric arc furnace(EAF) has better effect on promoting energy conservation and clean production than basic oxygen furnace (BOF).
Thus, production structure upgrading should be considered during the industrial optimization. Average capacity ofiron and steel plant built after 2000 is 5397.65 kt. This result will be used to decide the number of new plant.

R_Final_highFig. 4 Final ranking of each grid based on six criteria proposed in this research. S1: higher
GDP/POP, the better; S2: lower GDP/POP, the better(2) Close facility
Currently, over capacity is one of the most important problem in China with only about 70% of operating ratio, far
below the average level in developed countries. Domestic steel demand may decrease after the late of urbanization in
China. Therefore, it is necessary to figure out an algorithm to remove the redundant capacity. The final target is toachieve 80% operating ratio in 2020.

Fig. 5 Framework about how to close the existing facilities~2020: close outdated facilities + new plants +BTE

2026~2030: New plants + BTE

After reaching the 80% OR in 2020. The remaining capacity is a little bit
lower than the demand. Therefore, 6 new plans should be built up. At thesame time, due to the quick increase of recyclable scrap, part of BOF needto transfer to EAF (Fig.7).

2 new plant will be built for the slight increasing demand. Scrap is still
remaining rapid growth. So, some BOF still need to be converted to EAF(Fig.9).

2025

2020

2030

Total
Fig. 6 Location of new plants from 2020 to 2030

2036~2040: Close old facilities + BTE
Crude steel demand will decrease. Whereas, scrap is still remaining rapid
growth. So, some BOF still need to be both closed and converted to EAF(Fig.7).

Fig. 9 Plants location/capacity and the CO2 emissions in 2040

Fig. 8 Plants location/capacity and the CO2 emissions in 2030

Fig. 7 Plants location/capacity and the CO2 emissions in 2020

Comparison between original data and result

2046~2050: Close old facilities
Both crude steel demand and recyclable scrap are decreasing. So,
outdated BOF and EAF need to be (Fig.13).

Fig. 14 Differences of plants location/capacity and the CO2 emissions
between JK database and estimation results in 2050

Fig. 10 Plants location/capacity and the CO2 emissions in 2045

The aim of this research is to design, apply and evaluate an integrate framework for responding to dynamic development changes of the ironand steel industry, and then construct an emission map at the plant level. For this aim, a GIS-based multi-criteria decision analysis procedure
has been developed and then applied to China. Finally, we found that:
1) The evaluating algorithms for both selecting the most appropriate sites for the new plant and eliminating the outdated facilities are able tohandle the multi-criteria for multiple objectives that need to be considered when constructing a new iron and steel plant and closing oldfurnaces;
2) Industrial upgrading also performs well by transforming BOF to relatively environmental friendly EAF route. The recyclable scrap isestimated and can be just completely consumed.
3) Large amount of capacity in Beijing-Tianjin-Hebei region are closed, while most capacity in Shanghai are remained, which indicating a
different level of facility and production in these two old steel bases.
4) The center of crude steel production will move to western China and southern China. At the same time, emission will also transfer tothose two regions, which needs to arouse our attention.
Hypothesis:
1. crude steel imported form other countries in 2015 must be imported unless there is a technological breakthrough;2. Construction time of new plant is not considered in this research;

CSDt /80%: 80% OR,maximum capacity freedom

MIS: maximum
capacity increase

6. Conclusion

CSDt / 70%:
70% OR

GJS: gap between
JS and CSDt

CSDt = CAJt / 100%:
100% ORCAJT: capacity
in JK database
CSDt: SSP2’

3. Scrap generated in 2015 can be total reused by current EAF facilities;
4. BOF is the first choice to be closed, EAF will not be reduced after during 2020-2045;

201520202025

2030

Estimation method of recyclable scrap:
Ofs (t) = 0.08

0.06 Ocru t

0.32Ocru t

15

0.6Ocru t50