19th AIM International Workshop– Tsukuba, Japan, December 13-14, 2013

Assessment of Guangdong Carbon Emission
Trading with AIM/CGE ModelWang Peng1 Dai Han-cheng2 Zhao Dai-qing1 Toshihiko Masui2 Ren Song-yan1
1.Guangzhou Institute of Energy Conversion, Chinese Academy of Sciences, China,Guangzhou
2. National Institute for Environmental Studies, Tsukuba-City, Japan

Introduction

Future scenario• Guangdong contributes over 11% of China’s GDP and consumes 8%(19.6 million tons of coal equivalents) of China’s energy in 2007.
• Guangdong has committed to reduce its carbon intensity per unitof GDP by 19.5% in 2015 from 2010 level and decided toimplement carbon emission trading system across industry sectors.
• At the first stage, four sectors are selected for emission trading,including power, cement, oil refinery ,iron and steel sectors which
contribute to 58% of total CO2 emissions in Guangdong.

• All the datasets are converted to the base year of 2007.
• The projections on population and GDP are based on the 12th five-year
economic development plan and research assumptions.

Table.1 Key assumptions
2010
Population (thousand)
GDP (billion Yuan)

Methods

0.5%
7.8%97302
3994

Table.2 Scenario setting
Carbon constraintScenario• This study uses the dynamic provincial CGE model developed by
NIES to assess carbon trading policy under the constraint ofcarbon intensity reduction target towards 2020.
• This model is a two-region recursive dynamic CGE model andselects 2007 as the base year and include 33 sectors.
• Five scenarios are constructed considering two dimensions (Table2): scenario SAV has weaker target whereas LCE has more
stringent target (Fig. 1). In addition, scenarios SAVET and LCET
allow emission trading.

2015-2020

CMIntensity target
2010-20

Sector emission cap
2015-20

Emissiontrade1BaU

×××2

SAV-33%×3

SAVET-33%

Power sector : 1% annualincrease,otherthreesectors: 2% annual increase

4LCE-40%

Fixed to 2015 level×5LCET-40%√√

Results
Impacts of intensity target• The more stringent the target is, the more GDP
loss there would be (Fig.3).
Impacts of emission trading• Without emission trading, carbon price of oil
refinery and iron & steel sectors would berelatively high and that of power sector would
be low (Fig 2).
• With carbon trade the sector abatement costsof cement, oil refinery and iron & steel sectors
would decrease (Fig 2).
• Power sector is the seller due to renewableenergy development, whereas other threesectors are buyer (Fig. 4).

Conclusion

Fig.1: CO2 emission pathway of Guangdong

Fig.3: GDP loss of four policy scenarios• This study evaluates the economic impacts of Guangdong’s carbon emission trading
system.
• Implementing carbon trade could reduce the abatement costs of cement, oil refinery, iron and steel sectors, and the costs of other sectors will increase.
• More stringent cap will cause more GDP loss, so it is important to consider how to set
the sector cap for industry which will not harm the industry too much.

Fig.2: carbon abatement cost

Fig.4: emission trading (positive meansseller while negative means buyer)

References :[1].National Bureau of Statistics of China, National Energy
Administration of China. China energy statistics yearbook 2008.
Beijing, China Statistics Press; 2009 [in Chinese].
[2].H. Dai et al. Assessment of China’s Climate commitment andnon-fossil energy plan towards 2020 using hybrid AIM/CGE model.
Energy policy 39(2011)2875-2887.
[3]. Fujimori (2012) AIM/CGE model manual. Internal report. AIM,NIES.