Assessment of Guangdong Carbon Emission Trading With AIM/CGE Model
Wang Peng1 Dai Han-cheng2

Zhao Dai-qing1 Toshihiko Masui2Ren Song-yan1

1. Guangzhou Institute of Energy Conversion, Chinese Academy of Sciences, China, Guangzhou
2. National Institute for Environmental Studies, Japan, Tsukuba

Summary: As one of the most developed and one of the largest energy consumption areas inChina, Guangdong has been chosen by the Chinese government as the setting for trials on low
carbon transition. In recent years, Guangdong has achieved the highest GDP among all theprovinces of China, and contributed more than 11% to the total GDP of the country. It also
accounts for about 8% of total energy consumption, and coal still dominates as the primaryenergy supply. For example, Guangdong consumed 19.6 million tons of coal equivalents in 2007,
and coal accounted for 49.1% of this consumption. To address climate change and realize low
carbon development, Guangdong has committed to reduce CO2 emission intensity per unit ofGDP in 2015 by 19.5% compared with 2010 level and decided to implement carbon emission
trading system. In the first stage, the power, cement, oil refinery and iron and steel sector
which caused about 58% of the total CO2 emissions in Guangdong are allowed to implement
carbon trading.
In order to evaluate the economic impact of Guangdong carbon emission trading system(ETS), this study uses the two-region provincial CGE model developed by NIES to simulate theimplementation of carbon trading policy under the constraint of carbon intensity reduction target.
For comparing the abatement contribution of different countermeasures in completing the target,
five scenarios are constructed. To evaluate the effects of ETS policy, a reference scenario (BaUscenario), which has no policy intervention, is developed first. After the BaU scenario, this study
designed four kinds of policy scenarios. Two scenarios are setting intensity decrease rate targetand sector cap (SAV and SAVET scenario as the 33% reduction target from 2010-2020), anothertwo scenarios are set as absolute sector cap target which means more rigid target (LCE andLCET scenario as the 40% reduction target from 2010-2020). SAV and LCE scenario are notusing carbon trade for the four sectors.
From the simulation results, we can see that the change of the key index data. When setting
the reduction target for the four policy scenarios, it will bring the carbon abatement cost for all
sectors. And this carbon price will increase the cost and decrease the demand of some sectors,
which will cause the GDP loss. Compared SAV with LCE scenario, we can see that the bigger
reduction target, the bigger loss in GDP. Compared LCE with LCET, the carbon price of four
sectors reduce and the GDP loss decrease. It shows that the carbon trade can reduce the total
abatement cost. But for the SAV and SAVET scenario, the GDP loss difference is not big. From
the abatement cost of other sector, we can see that as the other sector will not allow to trade, thecarbon price of other sector is big. This situation can still reduce the GDP loss. So if we want toconsider the effect of ETS, we should allow more sectors implement carbon trade.