Guangdong ETS - Impact Assessment and

policy recommendations

ZHAO Daiqing · WANG Peng · DAI Hancheng Energy Strategy Research Center

Guangzhou Institute of Energy Conversion, CAS

20th AIM International Workshop – Tsukuba, Japan, January 23-24, 2015

Main Contents

Macroeconomic Impact Analysis of GD ETS 2

1

Introduction of Guangdong ETS – the market building processes

新西兰ETS

广东ETS

泰国ETS

深圳ETS

重庆ETS

上海ETS

天津ETS 北京ETS

湖北ETS

南韩ETS

日本东京ETS

日本全国范围ETS 中国全国范围ETS

哈萨克斯坦ETS

欧盟 EU ETS

瑞士ETS

俄罗斯ETS

乌克兰ETS

土耳其ETS

巴西ETS

智利ETS

墨西哥ETS

美国加州ETS

加拿大不列颠哥伦比亚省 (WCI)

加拿大魁北克省(WCI)

加拿大安大略省(WCI) 美国区域温室气体减排计划

（RGGI)

加拿大马尼托巴ETS (链接WCI)

operating designing

澳大利亚ETS

Carbon Trading Mechanism has Become an Important Tool for

Governments to Reduce Carbon Emission

Chinese Government Carbon Trading Pilot

Deployment and Process

Shenzhen Beijing Shanghai Guangdong Tianjin Hubei Chongqing

2013.6.18 11.26 11.26 12.19 12.26 2014.4.2 6.19

In October 29, 2011, the national development and Reform Commission issued a document

<notice about carrying out the carbon emissions trading pilot work>, which approved seven

cities as pilots regions to carry out the carbon emissions trading system, including: Beijing,

Tianjin, Shanghai, Chongqing, Hubei, Guangdong, Shenzhen.

Seven China’s

pilot ETS launch

The step of National carbon market

Nov, 12,APEC，publish the Sino-US

joint statement on climate change ，announce the action after 2020.

US promise to reduce 25% before2025

China promise to peak at 2030 and non

fossil to 20%.

NDRC：National ETS market is considered as the key reform, it will

be launched from 13th Five-Year-Plan (2016-2020 )

Basic Economic and Social Development Situation

GD

Value Share in China

Population (Million persons) 94.49 7.2%

Energy (PJ) and emissions (Million ton)

Coal 2670.1 5.0%

Petrol oil 1980.2 14.9%

Gas 178.2 6.5%

Electricity (TWh) 3394.1 10.4%

CO2 414.7 7.02%

Economic indicators (billion USD)

GDP 405.3 11.6%

Per capita GDP 4289 1.61

Textile 72.2 12.3%

Paper and pulp 18.9 16.2%

Metal products 47.3 20.1%

Machinery 175.4 13.4%

Electronic equipment 207.2 37.8%

Guangdong in 2007

Growing energy consumption

with declining energy intensity

With continued economic growth

and urbanization, Guangdong’s

energy consumption will growth

year by year. Total energy

consumption of some high energy-

consuming industries will growth

rapidly.

However, energy intensity will

decline year by year with the

optimization of industrial structure

and implementing of energy-saving

measures.

The energy saving development situation of GD

– comparing internationally

Energy Structure in 2012 - comparing with other countries

GD

Energy Intensity – comparing with other countries

GD’s energy intensity is lower than the average level of China, and there is still a gap between world.

China

0.00

0.50

1.00

1.50

2.00

2.50

0%

200%

400%

600%

800%

199

5

199

6

199

7

199

8

199

9

200

0

200

1

200

2

200

3

200

4

200

5

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6

200

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200

8

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9

201

0

201

1

201

2

Gd

pg

row

th 和碳排放趋势

(1

99

5年

=1

00

%)

年份

碳排放强度

/(t

CO

2e/万

元)

GDP发展趋势 碳排放趋势

As the first major economic province，Guangdong’s GDP and carbon emissions showed an upward trend, and the

speed of GDP grow faster than that of carbon emission, emission intensity is decreasing year by year. Guangdong’s

carbon emission intensity had dropped from 2.32 in 1995 to 1.19 tCO2e/10,000 yuan in 2012, with average annual

decline of 4%. The result of carbon emission driving force factor decomposition showed that the main driving factor of

carbon emission increment is from economic output. With the sustained economic growth of Guangdong, carbon

emissions will rise further, but the speed will slow down gradually.

Driving Factors and Trend of Guangdong Carbon Emission

Carbon emission trend GDP growth

Carbon emission driving power

Energy intensity

Industry emission ratio

Industry structure

Residential emission ratio

Residential energy

consumption structure

Urbanization degree

Population

Industry energy structure

Wealth level

Economic output

Factors

Reduction target during the 11th five year plan

Reduction target during the12th five year plan

National Guangdong National Guangdong

Target of energy consumption per unit GDP decrease

20% 16% 16% 18%

Target of carbon emission reduction per unit GDP

19.1% - 17% 19.5%

The proportion of new and renewable energy in primary energy consumption

10% 11.4%

Forest coverage percentage 20% 21.66%

The Goal of Energy-saving and Emission Reduction During the 12th Five Year Plan

<planning of energy-saving and carbon emission reduction for the 12th five years>

Form the mechanism of reversal pressure to promote the transformation of economic development mode, establish

an effective incentive and control mechanism to reduce the GHGs emission and enhance energy using efficient.

Marketing mechanism will be an sound tool.

Design and operation of Guangdong carbon emissions trading mechanism

• Local regulations

"Guangdong Province carbon emissions trading pilot work plan“ (September 2012)

Decree 197th , announced the "Guangdong Province trial carbon emissions management measur

es“(January 2014)

• CAP

Guangdong’s total quotas of the cap was about 388 million ton-CO2 in 2013

• Coverage

Four energy intensive sectors: cement, electric power, steel and petrochemical have bee

n incorporated into ETS, the average annual emission of four industries accounted for more than

50% of the total carbon emissions of Guangdong.

• Allocation

Baseline method was employed by electric power and cement industries, the rest of the industry

uses the historical method

Main Contents

Macroeconomic Impact Analysis of GD ETS 2

1

Introduction of Guangdong ETS – the market building processes

• DEA model

• Factor Index analysis

• Two-region dynamic

CGE model

• Carbon cost

• Cost-benefit-ratio

• Allowance allocation

• Enterprise emissions

• Economy development

carbon

market

liquidity

Industry

Competitive

Execution

efficiency of

ETS

Macro

economic

impact

二、 Evaluation Methods of ETS

• This work was published in:

– Wang, P., H.-c. Dai, S.-y. Ren, D.-q. Zhao and T. Masui (2015). "Achieving Copenhagen target thro

ugh carbon emission trading: Economic impacts assessment in Guangdong Province of China." Ene

rgy 79(0): 212-227

• CGE model based on new classical economics general equilibrium theory

• Dynamic-recursive model, including two region of Guangdong and the rest of China and 33

sectors (7 energy sector).

三、 Macro economic impact analysis: model structure

Scenario Emission

trading

Emission constraint

Base None No carbon cap.

LCE None Carbon intensity reduces by 40% over 2010-20;

Annual growth rate of carbon between 2013-15:

Power sector 0.5% Oil refinery 0.8%, cement

0.5%, iron and steel 0.5%; 2016-20: Power

0.1%, other three sectors 0.2%.

LCET Yes

Carbon emissions and intensity change

15

From 2007 to 2020 in the Base scenario: CO2 emissions will increase by more than 2

times, and its share in China will increase from 7.0% to 7.4%.

Carbon caps are imposed on the four sectors in the LCE scenarios, the carbon intensity

will decrease 50% from 2005 to 2020, more than the Copenhagen commitment (40-45%)

0

100

200

300

400

500

600

700

800

900

2007 2009 2011 2013 2015 2017 2019

Mil

tio

n

BASE

LCE

LCET

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

2

2007 2009 2011 2013 2015 2017 2019

ton

-CO

2/1

00

0 U

SD

BASE

LCE

LCET

CO2 Carbon intensity

Carbon abatement cost

0

50

100

150

200

2015 2016 2017 2018 2019 2020

20

07

USD

/to

n-C

O2

PowerRefineryCementIron&SteelTrade price

Carbon shadow prices of sectors in 2020 are: 180USD (iron and steel), 152 USD

(refinery) and 26 USD (cement) and 18 USD (power) per ton-CO2

The level of the mitigation cost is determined by many factors. One of the most important

one is reduction rate from BASE level.

Emission trade: carbon price and trade volume

17

-20.0

-15.0

-10.0

-5.0

0.0

5.0

10.0

15.0

20.0

2013 2014 2015 2016 2017 2018 2019 2020

Mill

ion

to

n

Power

Refinery

Cement

Iron&Steel

Seller

Buyer

As the carbon abatement cost is different, emissions trading takes place among sectors

In 2020, the traded volume is 27 Mt and the equilibrium trading price is 37 USD/ton CO2,

resulting in the scale of the carbon market being 1.02 billion USD.

Impacts on GDP

18

• The aggregated GDP loss in 2020 is 1.38% in LCE scenario, but reduced to 1.15%

in LCET.

• The policy makers need to think seriously on how to reduce the GDP loss by more

appropriate design of climate policy based on market based instruments.

-1.5%

-1.0%

-0.5%

0.0%

2007 2009 2011 2013 2015 2017 2019

GD

P lo

ss

LCE

LCET

826

-43

3,881

2,299

34,597

2,650

-6,307

-3,166

-887

10,767

-16,944

31,469

-2,211

-12,889

1,409

-9,914

1,871

0-20,000 40,000

OtherManu

Electricity

Electronic

Transport

Construction

Service

Textile

Machinery

Cement

Metal products

Iron&steel

Food

Agriculture

Oil refinery

Paper

Mining

Chemicals

SAVET vs SAV (person) LCET vs LCE (person)

847

0

-5,575

-20,000

8,500

2,242

-2,557

3,185

-11,712

1,219

-1,170

-13,851

46,103

-13,336

2,692

2,886

41,854

-17,553

1,840

60,000

The quantity of employment in all sector change with and without ETS

ETS increase 45614

Employment increase： Agriculture、Food、textile、 Cement、Iron、Electronic ,service Total increase 37,000-45,000 jobs

Analysis results: ETS on the employment

ETS

adminstration

Province

city

Enterprise

report

control

The third party

verify

Carbon

assest

software

trader

Trade

account

finance

media

association

News

Research

Estimate：ETS on the service

Jobs： ~20,000 person

1. In 2020, the carbon price of power sector is the lowest, followed by cement

sector, whereas that of refinery and iron and steel sectors is higher.

2. During 2015-2020，controlling emissions will cause GDP loss 0.8%-1.4%. ETS

will reduce GDP loss ETS policy is economically efficient.

3. Enlarge the sector coverage of ETS will reduce the GDP loss and decrease the

carbon price.

4. Through CGE model simulation, ETS would bring 40,000 jobs compared with

carbon constraint policy. It’s important to pay attention to the jobless of

construction, mechanics and paper sectors.

Conclusions

Future work on modeling

Further simulate the carbon auction revenue return

back style

Develop the Enduse model to link with CGE to discuss

peak of Guangdong

Using model to research of air pollutant emission

control of Guangdong

Thank you very much !