Prof. Wu Libo

Executive Director , Center for Energy Economics and Strategy Studies

Fudan University, Shanghai，China

Email： wulibo@fudan.edu.cn

0.0

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1.0

1.5

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能源消费 弹性系数 电力消费 弹性系数

0

5

10

15

20

25

30

工业增加值同比增速 轻工业增加值同比增速

重工业增加值同比增速

Realistic Constraints：

The increase in China's energy intensity is mainly caused

by industrial structure change, which is quasi-rigid, and very

difficult to reverse in short term:

• Rigid demand caused by rapid urbanization process

• The process of international industrial specialization

transfers “heavy” industries into China through FDI

• The lagging behind of service industry intensifies the

imbalance of industrial structure

• The divergence of the structure of employment and

economic development will restrict the upgrading of the

industrial structure transformation

0

0.2

0.4

0.6

0.8

1

第一产业比重 第二产业比重

第三产业比重 第一产业就业比例

第二产业就业比例 第三产业就业比例 Energy consumption

elasticity coefficient

Electricity consumption

elasticity coefficient

The first industry proportion

The third industry proportion

The second industry

employment proportion

The second industry proportion

The first industry employment proportion

The third industry employment proportion

Growth of Value-Added

(Overall Industry)

Growth of Value-Added

(Heavy Industry)

Growth of Value-Added

(Light Industry)

• From 1990 to 2009, China’s total energy production

grew by 158.5%, energy consumption grew by

206.2%. The supply gap accounted for 12.4% of

total production in 2009 (322.61 mill. tce).

• From 2000 to 2009, the portion of energy

consumption by energy-intensive industries grew

from 77% to 81%, and accounted for 40% of total

energy consumption.

Historical Trend of the Share of Energy

Consumption by Energy-intensive Industries

Textile industry

Oil processing industry

Chemical fiber industry

Black metal industry

Electric power, gas and water

Paper and paper products

Chemical products industry

Nonmetallic mineral products industry

Non-ferrous metal industry

Share of Energy Consumption by Energy-intensive

Industries, 2000

Textile industry

Chemical fiber industry

Nonmetallic mineral products industry

Non-ferrous metal industry

Oil processing industry

Black metal industry Chemical products industry

Electric power, gas and water

Paper and paper products

Raw coal Heat Electricity Coke Natural gas Crude oil

Textile industry

Chemical fiber industry

Nonmetallic mineral products industry

Non-ferrous metal industry

Oil processing industry

Black metal industry Chemical products industry

Electric power, gas and water

Paper and paper products

Raw coal Heat Electricity Coke Natural gas Crude oil

Share of Energy Consumption by Energy-intensive

Industries, 2005

Proportion of China’s energy-intensive industry in GDP

Trend of Energy Intensity

in China’s Largest Energy-intensive Industries, 2000-2009 From 2000 to 2009,

• The added value of China’s energy-

intensive industries grew by 570% to

5.5 trillion Yuan in 2009.

• Energy intensity of largest energy

consuming industries continued to

decline.

• Share of energy-intensive industries

in total GDP grew form 23% to 40%,

while consumed 80% of total energy

consumption.

Textile industry

Oil processing industry

Chemical fiber industry

Ferrous metal industry

Electric power, gas and water

Paper and paper products

Chemical products industry

Nonmetallic mineral product industry

Non-ferrous metal industry

Energy Consumption Share Added Value in GDP

TIMES model aims to supply energy services at minimum global cost (more

accurately at minimum loss of surplus) by region. It is foresight and could be

effectively applied into long-term energy policy making and new energy technology

planning.

1 1 2 2Min n nc x c x c x

11 1 12 2 1 1

21 1 22 2 2 2

1 1 2 2

1 1 2 2

n n

n n

i i in n i

m m mn n m

a x a x a x b

a x a x a x b

a x a x a x b

a x a x a x b

Objective

function ：

constraints：

•Investment and operation cost

•Cost and quantity of inputs

•Discount rate and interest rate

•End use energy demand

•Resources of input

•GHG emission

•Efficiency of technology transform

•Other constraints on the

technology input and output share.

The linear programming model scheme

Four steps for modeling：

1. RES Designing

2. Technology parameter valuation

3. End use energy demand forecast

4. Policy scenario comparison

TIMES (Integrated MARKAL-EFOM System) is an integrated model combined with

the two models MARKEAL and EFOM. It is an advanced economic model used for energy

system optimization.

TIMES and MARKAL are widely applied in the energy economics study as members of

bottom-up model family. They are developed by ETSAP of IEA. They are both reference

energy system (RES) based model, including energy, environment and economic study.

Energy service demand curve Related factors: GDP \Outputs\Population

Elasticity: Related factors, own prices

Primary energy and raw materials supply curve (Energy reserves; resources; Annual average development

potential; trading factors)

Policy scenario Emission Constraints; Carbon tax; Trade mechanism

Technology allocation, Tendency subsidies

Tech-Econ parameters Transform tech（process）(fuel, materials, energy service,

carbon emission)

Demand

Supply

Policy

Tech & Econ

Base Scenario

Alternative

scenario

Main path

Dual path

Tech investment cost;

Tech implementation level;

Import and export of energy

and materials;

Extraction level of primary

energy and materials;

Flow in and flow out of tech;

Emission of tech, sector and

total system;

Trend analysis of GHG

change

Shadow price of the

commodities of RES(energy,

demand, emission and raw

materials)

Tech cost balance(Added

investment to make one tech

competitive)

Input

Output

The simplified RES of China-TIMES

We used 18 energy

commodities and 88 energy

technology to build up our

China-TIMES, including 7

energy input tech, 5

processing and transforming

tech, 23 power generating

tech, 32 basic industry tech

and 21 energy saving tech.

Coal extr.

Oil extr.

Gas extr.

Oil imp.

Gas imp.

LNG imp.

Gsl. refine

Diesl refine

Fuel oil refine

Coking

LNG gasify

Super-critical

SSC Units

IGCC

NGCC

Large Scale Hydro Power

Small Scale Hydro Power

On-shore wind power

Off-shore wind power

PV

Solar Thermal

Nuclear II

Nuclear III

Steel Ind. Coal Tech

Steel Ind. Coke Tech

Steel Ind. NG Tech

Steel Ind. Crude Tech

Steel Ind. Gasl. Tech

Steel Ind. Desl. Tech

Steel Ind. Fuel oil Tech

Steel Ind. Elec. Tech

Steel Ind. Energy

Conservation Tech.

Cement Ind. Coal Tech

Cement Ind. Energy

Conservation Tech.

Chem. Ind. Coal Tech

Chem. Ind. Energy

Conservation Tech.

Non-fer. Ind. Coal Tech

Non-fer. Ind. Energy

Conservation Tech.

Co

ke

Fu

el O

il

Die

se

l

Ga

so

lin

e

Ele

c.

LN

G.

NG

Pe

tr.

Co

al Ura

niu

m

Ur. extr.

1

3

4

5

6

7

Energy input technology

Energy process and transform tech

2

Unit 2010 2015 2020 2025 2030

Domestic price

of coal

yuan/ton 450.00 473.46 541.63 557.02 568.88

Domestic price

of oil

yuan/ton 3,000.00 4,140.66 4,777.50 5,135.81 5,494.13

Domestic price

of natural gas

yuan/m³ 2.80 1.60 1.94 2.20 2.49

Import price of

oil

dollar/barrel 97.19 86.67 100.00 107.50 115.00

Import price of

natural gas

dollar/Btu 8.25 7.29 8.87 10.04 11.36

Import price of

LNG

dollar/Btu 12.64 11.91 13.75 14.83 15.87

Domestic and Importing energy price Resource：IEA（2009）

Note：All prices are deflated，

The assumed inflation rate is 2.3%。

Mainly divided into：Domestic

independent energy and imported

energy. Importing price comes from

IEA《WEO2009》.We assume the

domestic price tracks the

international price. But the domestic

coal price gets a 20% discount.

Process the primary energy into

secondary energy. The transforming

efficiency refers to NBS《China

Statistic yearbook 2010》

Tech name Efficie

ncy

Transform

Efficiency

O&M cost

（million yuan /PJ）

Life

（year）

Emission

factor

（1000ton/

PJ） Gaso. refine 0.9 0.9663 1.2 40 4.118

Des. refine 0.9 0.9663 1.2 40 4.118

Fuel oil ref. 0.9 0.9663 1.2 40 4.118

Coking 0.9 0.9738 1.2 30 25.24

LNG Gasify 0.9 0.9800 1.2 40 -

Main parameters of processing and transforming Resource： NBS，Kannan (2009)

1

3

4

5

6

7

Power generating

tech

Industry Tech

2

Mainly include thermal, water, wind, solar and nuclear power. Besides,

we make CCS applied into thermal power unit.

IEA thermal power learning curve

IEA, ETP2010

0

2,000

4,000

6,000

8,000

10,000

12,000

14,000

2010 2015 2020 2025 2030

超临界和超超临界发电

超超临界发电（CCS装置）

IGCC

IGCC（CCS装置）

NGCC

NGCC（CCS装置）

(元/千瓦)Tech name Efficiency

O&M cost

mill. yuan /PJ

Life

year

Emission factor

（1000ton/PJ） Supercritical & ultra supercritical

power generation 0.57 2.0 20 91.68

IGCC 0.90 3.3 35 91.68

NGCC 0.90 5.6 30 52.95

Water power 0.39 - 40 -

Wind power 0.24 - 25 -

Solar power 0.23 - 25 -

2nd generation of nuclear power 0.76 0.5 40 -

3rd generation of nuclear power 0.85 7.7 50 -

Main parameters of power generating Resource: China electric power enterprise federation , Kannan 2009

Tech name Efficiency Investment cost

（million yuan/PJ）

Fixed cost

(million yuan/PJ）

Pellet rotary kiln 0.8633 34.4585 3.4458

Metallurgy lime thermal kiln 0.7350 30.5620 3.0562

Thermal refractory kiln 0.7700 30.5255 3.0525

NDRC《The "eleventh five-year

plan" ten major energy conservation

projects implementation planning》21 key conservation technologies

Key industry technical parameters

SC & SSC

SC & CCS

1

3

4

5

6

7

Demand forecast

2

Assume the compound

growth rate of 2011-

15,2016-20,2021-25 and

2026-30 decrease by 20%,

50%, 70% and 90% of the

2005-09 level. Then we get

the energy demand forecast

of four sectors in 2010-30.

0

5,000

10,000

15,000

20,000

25,000

30,000

35,000

2010 2015 2020 2025 2030

钢铁业

建材业

化工业

有色金属业

(PJ)

Meanwhile, we forecast the DGP of

2010-30.Supposing the develop speed

will slow down as it moves forward,

the total GDP of China will reach

121.5 hundred billion yuan in 2030. 0

200,000

400,000

600,000

800,000

1,000,000

1,200,000

1,400,000

2010 2015 2020 2025 2030

2%

3%

4%

5%

6%

7%

8%

9%

国内生产总值(左轴) 国内生产总值年均复合增长率(右轴)

(亿元) Forecast of GDP

Energy demand forecast of four sectors

Steel

Cement

Chem.

Non-fer.

GDP (left, 10^8 Yuan) Growth rate (right)

Scenario

1

3

4

5

6

7

2

2010 2015 2020 2025 2030

GDP（100 million yuan） 397983 584767.6 782550.95 998755.35 1215138.6

GDP annual compound growth rate 8% 6% 5% 4%

CO2 emission(kt) 6094826.4 6109322.8 6981080.2 7408758.9 7593224.4

Emission per unit of GDP 15.314288 10.447437 8.9209273 7.4179916 6.2488545

Low carbon scenario

Target of emission per unit of GDP 9.9542873 7.6571441 6.1257153 5.3600009

CO2 Constraints 5820944.7 5992105.4 6118090.9 6513143.9

Strong low carbon scenario

Target of emission per unit of GDP 9.9542873 7.6571441

CO2 Constraints 5820944.7 5992105.4 5992105.4 5992105.4

Parameter settings of low carbon scenario

BASE

LC1

LC2

Base scenario：no emission constraint

Low carbon scenario

The emission per unit GDP in 2015 will decrease by 35% of 2010;

The emission per unit GDP in 2020 will decrease by 50% of 2010;

The emission per unit GDP in 2025 will decrease by 60% of 2010;

The emission per unit GDP in 2030 will decrease by 65% of 2010.

Strong low carbon scenario

The emission per unit GDP in 2015 will decrease by 35% of 2010；

The emission per unit GDP in 2020 will decrease by 50% of 2010；

Volume control will be taken after 2020.The total volume of CO2

emission in 2025 and 2030 will keep the level of 2020.

43.60

22.83

10.06 10.06 9.93

31.33

42.08

49.02 49.01 49.01

8.36

12.7415.30 15.30 15.30

9.6811.59

13.07 13.10 13.18

1.473.13 4.36 4.36 4.40

5.55 7.63 8.18 8.18 8.19

0%

20%

40%

60%

80%

100%

2010 2015 2020 2025 2030

能源加工部门

有色金属业

化工业

建材业

钢铁业

电力部门

0

1,000,000

2,000,000

3,000,000

4,000,000

5,000,000

6,000,000

7,000,000

8,000,000

2010 2015 2020 2025 2030

0

5

10

15

20

基准情景-排放(左轴) 低碳情景-排放(左轴)

强化低碳情景-排放(左轴) 基准情景-单位GDP排放(右轴)

低碳情景-单位GDP排放(右轴) 强化低碳情景-单位GDP排放(右轴)

(千吨) (千吨/亿元)

The total CO2 emission decreases

plunged since the government make

some constraints.

Meanwhile，the decrease of the

emission per unit GDP also slows down

as time moves on.

From the structure of the source of emissions ，the sector structure gets an obvious change

after the government make some constraints, among which the power sector gets the best result.

43.60

21.75 18.79 17.34 19.25

31.33

43.97 45.03 45.43 44.32

8.36

12.91 14.63 16.04 15.65

9.6811.12 10.83 10.40 10.24

1.472.98 3.74 4.18 4.07

5.55 7.27 6.99 6.62 6.46

0%

20%

40%

60%

80%

100%

2010 2015 2020 2025 2030

能源加工部门

有色金属业

化工业

建材业

钢铁业

电力部门

43.60

22.83

9.23 9.04 12.39

31.33

42.08

48.91 48.06 46.23

8.36

13.0915.91 16.44 15.81

9.6811.69

13.45 13.40 12.97

1.472.68 4.36 5.04 4.88

5.55 7.63 8.14 8.01 7.71

0%

20%

40%

60%

80%

100%

2010 2015 2020 2025 2030

能源加工部门

有色金属业

化工业

建材业

钢铁业

电力部门

Base scenario CO2 emission structure Low carbon scenario CO2

emission structure

Strong low carbon scenario

CO2 emission structure

1

3

4

5

6

7

2

Optimal

results CO2

Emission

CO2 emission and emission per unit GDP

Emission-Baseline Emission-Low Carbon II

Emission-Low Carbon

Intensity-Baseline

Intensity-Low Carbon Intensity-Low Carbon II

Ptr. Chem.

Non-Ferr.

Chem.

Cement

Steel

Power

1

3

4

5

6

7

2

Optimal

results Energy consumption

in power sector

Being affected by the emission constraints，the

energy demand structures are very different among three

scenarios. More new energies and new technologies will

be used as there are stronger emission constraints.

0

5,000

10,000

15,000

20,000

2010 2015 2020 2025 2030

核能

风能

太阳能

水力

天然气

煤炭

(PJ)

In base scenario，although the share of renewable

power increases steadily, coal always keeps the dominant

place.

In low carbon scenario，the energy consumption

structure changes a lot. The share of coal power plunged

quickly between 2010 and 2020 while natural gas and water

power increases rapidly.

After 2020, wind power and CCS grow up fast. The whole

power sector will become “clean” till 2030 with the rest few

CO2 from natural gas and coal. The total generated power will

be 23,733.25PJ(66 thousand kWh) in 2030, 22.3% higher than

in the base scenario。

0

5,000

10,000

15,000

20,000

25,000

2010 2015 2020 2025 2030

核能

风能

太阳能

水力

天然气CCS

天然气

煤炭CCS

煤炭

(PJ)

Energy Consumption Structure in Base Scenario

In strong low carbon scenario，the energy consumption

structure is similar to the low carbon scenario，with the

renewable energy developing potentially. At the same time，the

total power volume gets bigger. The coal power is strictly

controlled with CCS developed.

0

5,000

10,000

15,000

20,000

25,000

30,000

2010 2015 2020 2025 2030

核能

风能

太阳能

水力

天然气CCS

天然气

煤炭CCS

煤炭

(PJ)

Energy Consumption Structure in LC1 Scenario

Energy Consumption Structure in LC2 Scenario

Nuclear

Wind

Solar.

Hydro

NG

Coal

Nuclear

Wind

Solar. Hydro

NG + CCS

Coal

NG

Coal+ CCS

Nuclear

Wind

Solar. Hydro

NG + CCS

Coal

NG

Coal+ CCS

1

3

4

5

6

7

2

Simulated Results

Prediction for main industrial sectors – Steel Industry

0.00%

10.00%

20.00%

30.00%

40.00%

50.00%

60.00%

70.00%

2010 2015 2020 2025 2030

传统煤炭技术

煤炭节能技术

焦煤

电力

0.00%

10.00%

20.00%

30.00%

40.00%

50.00%

60.00%

70.00%

2010 2015 2020 2025 2030

传统煤炭技术

煤炭节能技术

焦煤

电力

0.00%

10.00%

20.00%

30.00%

40.00%

50.00%

60.00%

70.00%

2010 2015 2020 2025 2030

传统煤炭技术

焦煤

电力

Under the Base Scenario, coal-related energy saving

technology seems to grow fastest in proportion, as it is

the optimal choice for steel company to reduce their

costs. Meanwhile, the proportion of steel energy using

technology, represented by the generative heating

furnace of steel rolling technology, will raise to 34%,

which domains this field.

Under the Low Carbon 1 Scenario, with restricted

carbon emissions, the coal-related technology is

suppressed, while the steel sector will turn to cleaner

sources like electricity. However, in the following ten

years, coal energy saving technologies will be fairly

developed when the emission reduction pressure hasn't

been so stressful. Under the Low Carbon 2

Scenario, where the carbon

emissions are strictly

restricted, the coal-related

technologies basically will

have no further development,

even the traditional coal techs

will fade away as time passes

by. On the contrary, electric

technology develops

prosperously. It will exceed

the coking coal and become

the main energy source for

the steel production.

Coking coal is the

biggest part of the

energy technologies

used in the steel sector.

However, with time

passing by and the

structural changes

taking places in this

sector, the proportion of

coking coal will

continuously decrease.

Meanwhile, coal energy

saving techs and electric

techs becomes more

and more important.

BASE

LC1

LC2

Traditional coal

Coal-related

Energy Saving

Coking coal

Electric

Traditional coal

Coal-related

Energy Saving

Coking coal

Electric

Traditional coal

Coking coal

Electric

0.00%

10.00%

20.00%

30.00%

40.00%

50.00%

60.00%

2010 2015 2020 2025 2030

传统煤炭技术

煤炭节能技术

焦煤

原油

电力

1

3

4

5

6

7

2

BASE

LC1

LC2

0.00%

10.00%

20.00%

30.00%

40.00%

50.00%

60.00%

2010 2015 2020 2025 2030

传统煤炭技术

焦煤

原油

电力

天然气

0.00%

10.00%

20.00%

30.00%

40.00%

50.00%

60.00%

70.00%

2010 2015 2020 2025 2030

焦煤

原油

电力

天然气

Simulated Results

Prediction for main industrial sectors – Chemical Industry

Under the Base Scenario, coal-related energy saving

technology becomes the most promising technology in

the next 10-15 years. But, with the development

bottleneck approaching, its proportion may decrease,

while electric technology becomes the most important

energy-saving technology.

Under the Low Carbon 1 Scenario, coal-related

energy saving technology is not chosen by the model.

Natural gas related technology suddenly rises,

becoming the most important energy saving technology,

followed by the electric technology which increases

steadily in proportion.

Under the Low Carbon 2

Scenario, any coal-related

technology is not chosen. The

clean energy technologies

such as electric and natural

gas will domain the chemical

industry from the beginning to

end.

The chemical industry is

currently using coal-

related technologies as

its main applied

technologies. While the

proportion of electric and

natural gas techs remain

relatively stable.

Traditional coal

Coal-related

Energy Saving

Coking coal

Crude Oil

Electric

Traditional coal

Coking coal

Crude Oil

Electric

Natural Gas

Coking coal

Crude Oil

Electric

Natural Gas

1

3

4

5

6

7

2

BASE

LC1

LC2

0.00%

20.00%

40.00%

60.00%

80.00%

100.00%

2010 2015 2020 2025 2030

传统煤炭技术

煤炭节能技术

电力

0.00%

20.00%

40.00%

60.00%

80.00%

100.00%

2010 2015 2020 2025 2030

传统煤炭技术

煤炭节能技术

电力

0.00%

20.00%

40.00%

60.00%

80.00%

100.00%

120.00%

2010 2015 2020 2025 2030

传统煤炭技术

煤炭节能技术

电力

Simulated Results

Prediction for main industrial sectors – Building Materials

Under the Base Scenario, coal-related energy saving

technology, represented by the Energy-saving wall

material production kiln, is considered as the optimal

choice from the beginning to end. The proportion of

traditional coal technology continues to decrease.

Under the Low Carbon 1 Scenario, coal-related

energy saving technology is still the dominant

technology, but the development of electric technology

is strengthened.

Under the Low Carbon 2

Scenario, the situation is

reversed from the two

scenarios shown above.

Electric technology which is

the most clean one becomes

the dominant choice, while

there’s only limited space for

the development of coal-

related technology.

The building material

industry is now mainly

based on coal-related

technologies. Similar

with the steel sector, the

development of different

technologies in the

industry is directly

depend on the extent of

restrictions on carbon

emissions.

Traditional coal

Coal-related

Energy Saving

Electric

Traditional coal

Coal-related

Energy Saving

Electric

Traditional coal

Coal-related

Energy Saving

Electric

0.00%

20.00%

40.00%

60.00%

80.00%

2010 2015 2020 2025 2030

传统煤炭技术

煤炭节能技术

焦煤

电力

1

3

4

5

6

7

2

BASE

LC1

LC2

0.00%

20.00%

40.00%

60.00%

80.00%

100.00%

2010 2015 2020 2025 2030

传统煤炭技术

煤炭节能技术

焦煤

电力

0.00%

20.00%

40.00%

60.00%

80.00%

100.00%

2010 2015 2020 2025 2030

传统煤炭技术

煤炭节能技术

焦煤

电力

Simulated Results

Prediction for main industrial sectors – Nonferrous Metals

Under the Base Scenario, electric technology gets the

biggest part, but tends to decrease. The coal-related

energy saving technology, represented by the utilization

of the waste heat, will develop fast, reaching a

proportion of 50% in the applied technologies up to 2025.

Under the Low Carbon 1 Scenario, the situation is

somewhat very similar to the base scenario. The coal-

related energy saving and electric technology are still

the optimal choices in the model. And, the former one

appears to be more competitive at the earlier stage.

Under the Low Carbon 2

Scenario, electric technology

still have advantage over the

others, since it is cleaner.

While coal-related energy

saving technology will

develop faster as it has

relatively lower costs.

The nonferrous metal

industry is

significantly

distinctive from the

previous ones. Electric

technology always has

the largest share

among all the

technologies.

Traditional coal

Coal-related

Energy Saving

Coking Coal

Electric

Traditional coal

Coal-related

Energy Saving

Coking Coal

Electric

Traditional coal

Coal-related

Energy Saving

Coking Coal

Electric

Unit:% 2015 2020 2025 2030

Power Generation 0 58 57 46

Steel Industry 9 7 13 13

Building Materials 3 7 15 15

Chemical Industry (0) (7) (6) (6)

Nonferrous Metals 14 0 0 (0)

Energy Production 0 0 0 0

Unit:% 2015 2020 2025 2030

Power Generation 0 54 53 59

Steel Industry 9 7 13 13

Building Materials 6 10 23 23

Chemical Industry 1 (4) (2) (2)

Nonferrous Metals 0 0 16 15

Energy Production 0 (0) 0 0

These tables show the CO2 emission reduction in the 6 main

energy sectors under the scenarios of LC1 and LC2 compared to

the base scenario from 2015 to 2030.

CO2 Emission Reduction Results by Sectors in LC1

The power generation sector

appears to be the biggest

emission reduction source.

Now matter in which scenario, its

CO2 emission as part of the whole

energy system will decrease

dramatically. Under the base

scenario, the reason is that the

costs of new energy power

generation will decrease fast,

resulting in using more clean

energy in the power generation

sector. While under the LC1 and

LC2 scenarios, the reason is that

the marginal reduction costs in this

sector is lower than that of the

others.

CO2 Emission Reduction Results by Sectors in LC2

Under the Low Carbon Scenarios, the steel industry and the building industry

are the first ones to start emission reduction among the four energy-intensive

industries. And they have relatively low marginal emission reduction costs.

The key to advance the emission reduction efforts in the power generation

industry lies in the proper utilization of new energy technologies. The research,

demonstration and spread of the new energy technologies have significant

importance. Furthermore, with the requirements of carbon restriction rising, CCS

technology will overcome the obstacles of high costs, resulting in the improvements of

generation capacity.

By comparing the integrated using costs of different energy saving

technologies, we’ve found four technologies that have advantages over the

others, whose development should be given priority in the near future. They are

regenerative heating furnace of steel rolling technology in the steel sector, energy-

saving wall material production kiln in the building materials industry, synthetic

ammonia technology for energy conservation in the chemical industry, and the

utilization of the waste heat in the nonferrous metals industry.

To encourage the whole energy system to improve productivity and optimize

resource allocation, the adjustment of production and structural changes in the

traditional industries should be made. Only by upgrading the manufacturing

technologies and using more energy-saving technologies, can the whole energy

system achieve the optimum operation.

Conclusions and Analysis

A：Develop B：Apply C：Grow D：Mature E：Alternative technology F：Drop out

Time

Market volume

Technology life cycle

theory

• In R&D phase

• Low risk in the future

• In R&D phase

• High future uncertainty

•Mature; • High learning

/transformation cost

Medium term policy module

Short term Policy module

Long term policy module

Technology attribute

Policy3: Provide tax preferential policies (accelerated depreciation) to promote technical transformation

Core policy： Set technology standard and

force promotion

Policy2: Provide special subsidies and support R&D, purchasing and application of new technology

Policy6: Establish energy saving, carbon emissions trading system; create market

Policy4: Offer credit preferential policy, such as discount loans, etc .

Policy5: Energy contract management mechanism with nations to provide credit guarantee

Policy1: Build detailed benchmark management system based on key craft and technology

Applicable technology: •Electric power equipment reform technology •High efficient continuous casting, thin slab continuous technology •Lower production rate and reduce device coke coked technology •Ethylene online burning technology •Automation, efficiency, textile industry technology

•……

Policy3: Perfect intellectual property rights system; strengthen protection for enterprise R&D achievements

Core policy: Nation lead;

R&D demonstrate; Government special fund

Policy2: Provide green label; improve certification system for energy efficiency label and energy-saving product

Policy6:Provide green loans for enterprise R&D projects

Policy4: Strengthen international technology exchanges and cooperation; introduce foreign advanced technology

Policy5: Establish technical innovation platform; strengthen mutual support between technical R&D, innovation and diffusion

Policy1: Government first purchase and subscription policy for enterprise demonstration projects

Applicable technology: •Coal-fired power plant optimized operation and condition monitoring technology •Refill coked inhibitors, low energy separation technology •Ionic membrane caustic soda technology and oxygen cathode technology •High yield pulping technology and strong bleach technology •……

Policy3:Provide platform for technology industrialization through Esco and energy conservation service system,

Core policy: Use financial

instrument ,spread risk by

market

Policy2: Asset securitization; disperse investment risk

Policy6: Participate in international carbon market (CDM market); establish and perfect domestic emissions trading spot and futures market

Policy4: Encourage large enterprises to strengthen supply chain finance; support small and medium-sized enterprise

Policy5: Combination of production, study and research

Policy1:Financing preferential policies, such as green credit, low interest rate loan

Applicable technology: •Hydrogenation high heat flow optimization technology •High iron, low silicon, low fuel consumption, high reductive degree sintering technology •Large-scale nonferrous metal open mining and underground mine stope technology •Large-scale, integrated, automotive synthetic ammonia producing technology •Oilgas field development dynamic tracking technology •……

Thank you very much

for your attention!