Comprehensive evaluation of China’s renewable energy plan and climate
commitment by 2020 with dynamic Input-output model
University of Tsukuba
University of Tsukuba
University of Tsukuba
University of Tsukuba

Shanshan WANG
Feng XU
Takeshi MIZUNOYA
Yoshiro HIGANO

1. Introduction
Predominantly based on coal, China’s electricity sector is the world’s single largest source of GHG
emissions (IEA, 2009). GHG emission reduction in electricity sector is the key to mitigation in China.
Chinese government has recognized the problem and made great efforts to develop renewable energy
power generation. Early in 2007, National Development and Reform Committee established “China’sMedium- and Long-term plan for renewable energy” drafting ambitious targets for renewablegeneration (NDRC, 2007).
Input-output model is a suitable tool for analyzing GHG emission on a macroeconomic scale. Thereare two main directions of input-output model utilization in GHG emission issues. First is GHG
emission accounting of a given year. Davis and Caldeira (2010), Peters (2008) and Wiedmann (2009)
calculated production-based or consumption-based national emission based on the input-output theory.
Second is outlook research of GHG emission by constructing an input-output model. But it is still in
initial stage. Wei et al.(2006) and Liang et al. (2007) used input-output model and multi-regional
input-output model to analyze the CO2 emissions in China. However, the key parameters such as
population, urban rate and technology improvement are exogenous in a linear algebra equation system,without analyzing the indepth relationship among energy, economy and GHG emission. Therefore, ourstudy is an innovation to construct a dynamic input-output model in an integrated
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energy-economy-GHG perspective.
The paper is organized as follows. Section 2 introduces the model. The simulation results areanalyzed in section 3. Finally section 4 provides the conclusion.
2. Overview of the model
The dynamic simulation model is consisted of an objective function and a series of subjectivefunctions, including commodity flow balance module, value flow balance module, electricity balance
module and macroeconomic module. The objective function of this model is to minimize total GHG
emission from 2007 to 2020, subjected to all modules. The commodity flow balance module describes
the total demand of usual industry’s commodity. The value flow balance module illustrates the total
input needed to develop an industry. The electricity balance module states the demand and supply ofelectricity in the society. The macroeconomic module presents the income and expenditure ofhousehold and government, and the balance between saving and investment. We set four cases toevaluate the technical feasibility and social acceptance of China’s renewable energy development plan.
The 42 sectors in “2007 input-output table of China” are converted into 16 sectors, categorized into
usual industry, thermal power industry and hydropower industry. Besides, we introduce threerenewable power sectors. Therefore, there are 19 sectors in this model (see Table 1), including 6industries. They are usual industry (No.1-14), thermal power industry (No.15), hydropower industry(No.16), wind power industry (No.17), solar power industry (No.18) and biomass power industry(No.19) separately. Output of each sector follows a linear production function related with capitalstock through a fixed coefficient.
Table 1 Sector definition in the model

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No.

Specific sectors

No.

Specific sectors

1Agriculture

11

Production of Water

2

Mining

12Construction

3

Light industry

13

Transport and postal services

4

Petroleum and Coking

14

Other service

5

Chemical Industry

15

Thermal power

6

Nonmetal Mineral Products

16

Hydropower

7

Smelting of Metals

17Wind power

8

Metal Products

18

Solar power

9

Other manufacture

19

Biomass power

10

Production of Gas

3. Simulation results
3.1 Objective function
In this study, we assumed the different development rate of China’s renewable target in 2020 fromcase 1 to case 4. Comparing the results of simulation (Fig. 1), the development of renewable energy iseffective to reduce GHG emission. The accumulative emission from 2007 to 2020 in case 4 is 8,327
million ton CO2e less than that of case 1. In 2020, GHG emission is 11,994 million ton CO2e in case 4,
1,061 million ton CO2e less than that of case 1. Therefore, renewable energy plays an important role in
China’s GHG mitigation. If China’s renewable energy development plan is fully accomplished,
thermal power sector is still the largest emitting sector in all years though the share of thermal power
sector’s emission in total GHG emission is decreased from 41% in 2007 to 37% in 2020, as shown inFig. 2.
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Fig.1 Trend of GHG emission in all cases

Fig.2 GHG emission by each sector

3.2 GHG intensity outlook to 2020
GHG intensity is an important indicator in China’s climate commitment. China promised to reduce its
GHG intensity by 40-45% for 2020 relative to its 2005 levels. The official value of GHG intensity ineach year is not issued. Dai (2011) gave the value of GHG intensity in 2005, 0.282 kg CO 2e/yuan.
Based on this data, we can get the specific value of the targets above. The target in 2020 is in the rangeof 0.155 to 0.169 kg CO2e/yuan.
The trend of GHG intensity is shown in Fig. 3, and it is decreasing from 2007 to 2020 in all cases.
There are two reasons. First, it is the advantage of introducing renewable energy. Second, theoptimization of industrial structure in the output contributes a lot.

Fig.3 Trend of GHG intensity in all cases

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Table 2 GHG intensity in cases
Case 1Case 2

Case 3Case 4

0.198

0.194

0.189

0.185

GHG intensity in 2020 (kg CO2e/yuan)

0.180

0.177

0.171

0.166

Intensity Reduction rate from 2005 (%)

36%

37%

39%

41%

Average GHG intensityfrom 2007to 2020 (kg CO2e/yuan)

In regarding to China’s climate commitment, GHG intensity in 2020 will fall by 36% relative to 2005
in case 1, and will be reduced further by 5% if China’s renewable energy target can be achieved incase 4 (Table 2). It implies that China’s climate commitment can be realized by accomplishing therenewable energy plan successfully.
4Conclusions

With a dynamic time-recursive input-output model, the study analyzes the effects of developing
renewable energy power generation in China. The following conclusions are obtained by this study.
First, though GHG emission will be increased to 11,994 million ton CO2e, it is technically feasible toaccomplish China’s renewable energy plan in 2020 while keeps 8% annual growth rate of GDP.
Second, China’s climate commitment can be realized by accomplishing the renewable energy plan
successfully and its renewable energy plan in 2020 will contribute about 5% to GHG intensityreduction. Third, implementation of the renewable energy plan will affect China’s electricity demandand supply, and change the industrial structure gradually. The development of industry has
transformed from energy-intensive industries to less energy-consuming industries. In terms ofelectricity demand and supply, the total electricity demand will increase to 6228 TWh in 2020, and thegeneration of renewable energy is 1557 TWh, 25.01% of total electricity supply.
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