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Abstract
China has pledged to meet a series of political targets on energy and environmental performance, including a target of a 15% non-fossil fuel share in total energy use by 2020. Achieving this target requires expansion of non-fossil energy and restraining energy use, which has implications for achieving the 40–45% carbon intensity reduction target. The present study outlines quantitative formulas to measure the nexus between the dynamics of GDP, energy, and carbon intensity. Considering a ‘likely’ scenario of the non-fossil fuel expansion envisioned by the Chinese government and a GDP growth rate of 8% per annum, the key to accomplishing both targets is to restrain energy consumption to attain an energy elasticity to GDP of approximately 0.53. Both targets can be achieved simultaneously with the existing non-fossil expansion plan and are within the ‘normal’ range of GDP growth seen in China over the long term. This is, however, less than the value realized over the last 10 years. To comply with the non-fossil fuel target, the potentially slower expansion of nuclear power capacity must be compensated for by other non-fossil options. Otherwise, there must be a greater attempt to decouple energy demand and economic growth in order to realize a smaller energy elasticity to GDP.
Policy relevance
China has pledged to achieve a 15% non-fossil fuel share and reduce its carbon intensity by 40–45% by 2020. The key to accomplishing both targets is to restrain energy consumption and promote the development of non-fossil fuels. The achievement of these two targets by 2020 is analysed between share of non-fossil fuel, CO2 intensity of energy and GDP, and energy elasticity in relation to GDP. This analysis can inform the governmental energy and climate policy on the scale and pace of non-fossil fuel development, and the prerequisite regarding the energy elasticity to GDP to achieve the targets. The impacts of slower expansion of nuclear power capacity on the target achievement and implied elasticity of energy to GDP are also provided, which is close to the policy choice and actions of government on energy saving and emissions reduction.
1. Introduction
Climate change triggered by anthropogenic GHG emissions is a global problem of unprecedented scale (IPCC, 2007). China and other developing countries involved in the Bali Road Map in 2007 agreed to take appropriate mitigation actions at the national level. This commitment demonstrates that – independent of any climate regime that will be implemented in the next few years – China's mitigation action will be placed on its own national agenda (Wang, Wang, & Chen, 2009). Furthermore, the Durban Platform comprises a protocol signed by countries willing to negotiate a new climate treaty by 2015, with a legally binding commitment involving all of the parties expected to come into force in 2020. Domestically, China has nearly accomplished its national goal of reducing energy use per unit of GDP (i.e. the energy intensity target) by 20%, as outlined in the 11th Five Year Plan (FYP) (2006–2010).1 To limit emissions, and support efficiency and renewable energy, the Chinese government has set binding targets to increase the non-fossil fuel share of primary energy to 15% by 2020 and to reduce the carbon intensity by 40–45%, both compared with 2005 levels. Interim targets have also been set for the 12th FYP (2011–2015) to bridge the gap between the 2020 target and current levels (GoC, 2011).
The carbon intensity target, and its significance and implications, have been widely discussed (e.g. Wang, Liu, Xiao, Liu, & Kao, 2011; Yi, Zou, Guo, Wang, & Wei, 2011; Zhang, 2010) because it is part of the Copenhagen pledges. However, the role of the non-fossil fuel energy target and its implications have not yet been analysed.
To fill this knowledge gap and contribute to the existing literature, this article focuses on the non-fossil fuel target and explores its implications by 2020. Achieving the target is a function of two determinants: the utilization volume of renewable (mainly hydro, wind, solar, and biomass) and nuclear sources in the energy mix, and the total primary energy consumption. Hence, China can either increase the rate of development of renewable and nuclear energy resources or limit total primary energy demand due to economic growth (decoupling economic growth and primary energy demand is crucial for this). The main purpose of this study is to assess the relationship and compatibility of the non-fossil fuel and carbon intensity targets. The analysis starts from a hypothetical ‘most likely’ scenario regarding the status of non-fossil fuels, which is derived from the proposed plans of China's government for the deployment of nuclear and renewable energy by 2020. By varying future GDP growth, the energy elasticity to GDP required for the achievement of the non-fossil fuel target is estimated. Similarly, the energy elasticity to GDP and the GDP growth ratio required to achieve the carbon intensity target is also estimated. Finally, the role of a slowdown in nuclear power expansion as well as the measures required to maintain China's progress towards achieving both targets are discussed.
For the questions addressed in this study, the analytical framework is sufficient to derive meaningful policy conclusions. This study does not apply the energy–economy modelling that has been used to analyse various economy, energy, and emissions pathways for China, as undertaken by e.g. Stern and Jotzo (2010) and Dai, Masui, Matsuoka, and Fujimori (2011). In many ways, China is still not a mature free-market economy; in particular, it has a non-liberalized price system in the energy sector. The resulting inflexibility of supply and demand is difficult to represent in most economic models that use price/cost as the core variables of change. In the current analysis, it is assumed that non-fossil fuel capacity is a controllable and adjustable factor that can potentially provide a ‘handle’ (a means) towards achieving the non-fossil and carbon intensity targets. In Section 2, an overview is provided of the economic, energy, and emissions developments in China over the past 30 years. In Section 3, an interpretation is given of the quantitative nexus between energy, economic, and emissions indicators, and how they relate to the targets. In Section 4, a ‘most likely’ scenario is described for renewable and nuclear resource utilization based on national expansion plans, while Section 5 contains a discussion of the implications of this scenario for energy and emission dynamics, and the interrelationship between the two targets. It is concluded in Section 6 that the non-fossil fuel and carbon intensity targets can be achieved simultaneously using existing non-fossil expansion plans and require energy elasticity to GDP and GDP growth within the ‘normal’ seen in China over the past years. To comply with the non-fossil fuel target, the potentially slower expansion of nuclear power capacity must be compensated for by other non-fossil options. Otherwise, there must be a greater attempt to decouple energy demand and economic growth in order to realize a smaller energy elasticity to GDP.
2. Historical trends in economic, energy, and emissions development (1980–2010)
2.1. Overview
Over the past 30 years, China has experienced rapid economic development, with an average annual GDP growth rate of 10.1%. Primary energy consumption achieved an annual growth rate of 5.8% (NBS, 2012), which corresponds to an energy elasticity to GDP of approximately 0.58. Figure 1 shows the patterns of GDP, primary energy consumption, energy-related CO2 emissions, and the share of non-fossil fuel use from 1980 to 2010. Table 1 summarizes the historical economic, energy, and emission attributes for each FYP (i.e. at five-year intervals).
TABLE 1 Indicators of economic, energy, and CO2 emission from the 6th to 11th FYP
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08 March 2013![]({"type":"image","src":"/na101/home/literatum/publisher/tandf/journals/content/tcpo20/2013/tcpo20.v013.i03/14693062.2013.768929/20130308/images/medium/tcpo_a_768929_o_f0001g.jpg"})
Figure 1 GDP, primary energy, energy-related CO2 emissions and the share of non-fossil fuel
Sources: Energy-related CO2 emissions from IEA (2011a). The latest available data are from 2009; other data from NBS (2012).
Economic growth and energy consumption in China have been characterized by periodic variation. For example, since the 8th FYP (1991–1995), the economy has passed through a complete economic cycle, with above-average growth rates, which then weakened and were finally reestablished. Correspondingly, energy consumption from 1998 to 1999 declined. After 2000, energy consumption grew more rapidly than GDP, with rapid increases in the rate of industrialization and the use of coal, and an energy elasticity higher than 1. This trend began to change in 2006, when the effects of implementing intensive energy conservation and environmental protection measures were seen (see the reviews of Price et al., 2011).
Carbon dioxide emissions are highly correlated with energy use, because coal dominates energy consumption and the share of coal in the energy mix changes very little over time.
2.2. Structural change within the fossil fuel sector
Historically, structural change within the fossil fuel mix has been minor and slow. From 1980 to 2010, the share of coal in the fossil fuel mix lay in a narrow range of 73–80%, and the shares for oil and gas were 17–24% and 2–5%, respectively. Therefore, the change in the aggregated emission factor (measured in tCO2e/TJ) of fossil fuels has been insignificant.
Figure 2 presents the aggregated emissions factor of fossil fuels in China with an Intergovernmental Panel on Climate Change (IPCC) default factor of 87.3, 71.1, and 54.3 tCO2e/TJ for coal, oil, and gas, respectively. Over the entire period, the aggregated emissions factor for fossil fuels increased and then declined, which reflects the change in share of coal in the fossil energy mix. The emissions factor in 2010 was almost the same as in 1980.
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08 March 2013Figure 2 Aggregated emissions factor of coal, oil, and gas use in primary energy
Source: NBS (2012).
![]({"type":"image","src":"/na101/home/literatum/publisher/tandf/journals/content/tcpo20/2013/tcpo20.v013.i03/14693062.2013.768929/20130308/images/medium/tcpo_a_768929_o_f0002g.jpg"})
Figure 2 Aggregated emissions factor of coal, oil, and gas use in primary energy
Source: NBS (2012).
Although projections for the future should not be based solely on the past (Webster, 2002), one can imagine the difficulties China will face during its energy transition from a coal-dominated system.
2.3. Share of non-fossil fuels
Generally, non-fossil fuels comprise non-commercial biomass, solar heating, biogas, geothermal, and so on. However, statistics for the non-commercial utilization of non-fossil fuels in China are currently incomplete. More importantly, the potentially increased use of such fuels is disregarded by national energy statistics on primary energy use, which only account for the use of coal, oil, gas, hydro, nuclear, and other types of non-fossil power generation (NBS, 2012).
It is unclear whether the non-fossil fuel target plan will include primary energy sources supplying non-electric energy or not. Furthermore, the electricity sector is regarded as the only sector that can integrate large amounts of non-fossil energy over the next decade (Kahrl, Williams, Ding, & Hu, 2011). Therefore, only commercial power-related energy utilization is considered here. The substitution method was adopted to convert non-fossil primary electricity (kWh) into primary energy (tonnes or grams of coal equivalent, TCE or gce). In other words, electricity use is treated in primary energy terms as if it were produced in a conventional fossil fuel thermal power plant (Macknick, 2009). Conventionally, this approach is consistent with China's energy statistics on primary energy.
Within this accounting framework, there has been moderate growth in the share of non-fossil fuels in China's total primary energy mix, mainly due to the growth of hydropower after 1980. An electricity deficiency began in 2003 and lasted for almost three years. During this period, the construction and operation of large-scale fossil fuel-based power plants (predominantly coal-fired) depressed the share of non-fossil fuels, which declined from 7.3% in 2002 to 6.7% in 2006. Later, this trend was reversed with a gradual increase in the share of non-fossil fuel, reaching 8.4% in 2010. The acceleration in wind power development played an important role in this change, combined with the contribution of the steady growth in hydropower.
3. Interpretations of the nexus of energy, economic, and emission indicators
The future pathway of carbon emissions will be determined by the dynamics of GDP, the primary energy intensity of GDP, and the carbon intensity of primary energy, a relationship that is captured well by the Kaya identity (see Kaya, 1990) and its variations (e.g. Steckel, Jakob, Marschinski, & Luderer, 2011). Non-fossil fuel development will influence carbon intensity, the starting point of the analysis.
Logically, achieving the non-fossil fuel target will depend on the scale of non-fossil power capacity, as well as the dynamics of total primary energy use. Given a certain level of renewable and nuclear power expansion, this binding target indicates a ‘limited’ growth of energy use (i.e. the ‘quota’ in Section 5), and further implies a change in carbon and energy intensities with a certain level of GDP growth. The identities below quantitatively represent the interactions between these indicators. To obtain a better interpretation, the energy elasticity to GDP was extracted from the formula, rather than only from the growth rates of the variables in the Kaya identity.
3.1. Carbon intensity of energy and share of non-fossil fuel
Energy can be categorized into fossil and non-fossil fuels with different emissions factors. The change of aggregated emissions per unit of energy, i.e. the carbon intensity of energy, can be calculated as follows: 
If I fc is further disaggregated into coal, oil, and gas, the above equation can be expressed as 
The decline in CO2 emissions intensity (carbon intensity), which stems from the substitution of oil and natural gas for coal, is driven by many factors and is difficult to project. Section 2.2 describes how structural change has been negligible over past decades. So, ignoring the effects of internal structural change within the fossil fuel mix (so that the structural change that results from the replacement of coal by oil and gas can better aid the reduction in carbon intensity) gives (t+1) ≈ (t). Therefore, the decline in the rate of energy carbon intensity can be simplified as follows: 
That is, changes in the carbon intensity target are determined by the change in the share of fossil fuel in the total energy mix (or, equivalently, the change in the share of non-fossil fuel). This treatment provides the lower bound of improvement for the carbon intensity of energy if the share of coal does not increase.2
3.2. Growth of CO2 emission and energy consumption
Total CO2 emissions Q equals primary energy consumption E multiplied by I ec. For the emissions in year t+1, we have 
3.3. Energy intensity of GDP and energy elasticity to GDP
Energy intensity of GDP is defined as the primary energy divided by GDP, and the energy elasticity to GDP is the quotient of their growth rate. Following the work of Jiankun and Zhang (2004), the relationship between these two factors can be derived as (where the growth rate of GDP is not zero): 
Here, γ ge is the annual growth rate of the energy intensity of GDP, β GDP is the annual growth rate of GDP and ξ E-GDP is the energy elasticity of GDP.
3.4. Carbon intensity of GDP, carbon intensity of energy and the energy intensity of GDP
The carbon intensity of GDP is the energy intensity of GDP multiplied by the carbon intensity of energy. It can also be derived following Jiankun and Zhang (2004) using Equations 3 and 4: 
On the right-hand side of Equation 5, the first term represents the contribution of energy intensity changes that stem from efficiency improvements in energy production and utilization, and from GDP structural changes (e.g. shifts from energy-intensive industries to tertiary industries). The second term, γ ec/(1+β GDP), represents the effects of changes in the energy mix. (See Section 5 for a discussion of structural change within the fossil fuel mix, and from fossil to non-fossil fuels.)
4. Likely scenario of non-fossil fuel by 2020
The Chinese government has released a series of plans for renewable and nuclear energy resource utilization by 2020, including the ‘Medium- and long-term renewable energy development plan’ (August 2007), ‘The medium- to long-term (2005–2020) nuclear power development plan’ (October, 2007), and others. The national government still has the power to assess and approve all types of power generation projects. Thus, government planning measures will continue to play a crucial role in determining the investment scale and pace of deploying non-fossil sources in the short to medium term. Of course, if the political, socioeconomic, and technological conditions change over time, the planning will need to be updated continuously in order to remain ‘reasonable’ and plausible (e.g. to fit with people's subjective judgements and expectations).
4.1. Wind power grows far beyond expectation
In 2010, China's installed wind-power capacity exceeded 31 GW, a result of continuous double growth for the six years following 2004. This growth greatly exceeded the previous target set by the 11th FYP of Renewable Energy Development. This is partly due to a phenomenon called ‘49.5 MW wind farms’, which references the fact that many wind-power projects in China were built with a capacity slightly below 50 MW. Projects below this threshold can receive full approval by provincial authorities, and can thus avoid central government regulations. The central government has now reclaimed approval authority for wind-power projects of all sizes. Nevertheless, this has allowed China to continuously surpass its 2020 target and, consequently, its wind-power capacity target has been raised to 150 GW (http://www.newenergy.org.cn/html/0105/5121032470.html).
4.2. Faster cost decline of solar photovoltaic generation
Solar power development in China is promising because of the promotion of concession bidding mechanisms, with bidding prices therefore declining faster than expected. In 2011, the government issued the benchmark feed-in tariff for solar photovoltaic (PV) at CN¥1/kWh for newly built projects. Many solar PV power facilities are planned in a number of regions, particularly in northwest China. By 2020, solar power capacity could exceed 20 GW (http://www.cs.com.cn/xwzx/05/201004/t20100408_2388321.htm), compared to approximately 2 GW at the end of 2011 (CEC, 2012).
4.3. Changes in nuclear power development
The government originally called for a nuclear power operating capacity of 40 GW by 2020, with 18 GW under construction in the initial plan. Expectations subsequently increased to embrace the accelerated growth of this resource. The new target required that nuclear energy comprise approximately 5% of the primary energy mix, which corresponds to approximately 80 GW (http://energy.people.com.cn/GB/11070511.html). In 2010, China had 30 GW of nuclear power under construction, which appeared to indicate that a nuclear renaissance was on the horizon. However, the nuclear crisis at the nuclear power station in Fukushima, Japan, as a result of the earthquake in March 2011, slowed global nuclear development. The approval process for new nuclear power plants in China was halted temporarily in 2011 and has just re-started, with higher standards and a slower development schedule (AP, 2012); this has added some uncertainty regarding the future role of nuclear. (See Section 5.5 for an analysis of the impacts of slowed nuclear development on the non-fossil fuel utilization target.)
4.4. Hydropower
The utilization rate of hydropower in China is approximately 40% of the total technically exploitable capability (a figure of 542 GW is cited in China's hydro resources survey of Huang & Yan, 2009). There is still great potential compared to European countries (which use an average of 50% of their exploitable capacities), including advanced countries such as Sweden and France (which use over 70%) (WEC, 2007). While adhering to the prerequisite of social and environmental suitability, 13 large-scale hydropower bases have been planned in central and southwestern regions of China, which have abundant hydro resources. According to the National Energy Administration (NEA), the total capacity for hydropower is expected to be 350 GW by 2020 (http://news.sohu.com/20100323/n271016774.shtml).
4.5. Biomass generation
Biomass derived from waste, agricultural and forest residue, and biogas can be used to generate electricity. However, the development of biomass generation in China has encountered various setbacks due to technological, economic, and policy challenges. More specifically, feedstock source supplies in most plants are not stable, and the collection of raw material is extremely costly. The government benchmark feed-in tariff at CN¥0.75/kWh (NDRC, 2010) is insufficient to ensure net revenue for the project owners. The capacity target for biomass was extracted from the original official plan, and is set at 30 GW by 2020.
The updates of the official targets mentioned above form a likely policy-based scenario for China's non-fossil fuel electric power development by 2020 (see Table 2).
TABLE 2 ‘Likely’ scenario of non-fossil fuel power generation development by 2020
5. Implications of the non-fossil fuel target on energy and emissions dynamics
5.1. Carbon intensity of energy due to the changes in fossil fuel mix and fossil to non-fossil evolution
Changing the mix of utilized fossil fuels, as well as expanding non-fossil fuels, can reduce the carbon intensity of energy. In China, there are reasons to resist the substitution of oil and gas for coal. On the one hand, coal is broadly recognized as an energy resource that is secure, competitive, invulnerable, and predictable in price (Kavouridis & Koukouzas, 2009). China is well-endowed with this resource for the near- to medium-term future. On the other hand, the increasing pressure on the local and global environment has made ‘dirty coal’ an unwelcome option, globally as well as in China. Domestically and internationally, it can be argued that China should alleviate its dependency on coal and/or promote the cleaner utilization of coal, while scaling up carbon capture and storage (CCS) technologies to lower CO2 emissions (see Jaccard & Tu, 2011). By contrast, an expansion in the use of petroleum products is expected due to the thriving growth in transport demand, and the wider utilization of natural gas is also promising in household, power plant, and industrial sectors.
The share of coal should decline for the sake of climate protection, given it is not likely that CCS will be available on an industrial scale in China in the next decade. However, the degree of this decline will be determined by the particular technical, economic, social, and institutional changes that occur, and the decline is therefore subject to significant uncertainty. A detailed discussion on these matters is outside the scope of this article.
Table 3 draws on the literature and summarizes the modelling output, the resulting change in the aggregated emissions factor of fossil fuels, and the carbon intensity of primary energy by 2020 compared to 2005, by combining the effects of non-fossil fuel expansion and internal structural changes within fossil fuels, according to Equations 1 and 2.
TABLE 3 Change of carbon intensity of energy in 2020 due to fossil fuel mix change and non-fossil fuel expansion
In all the scenarios, the overall carbon intensity decline was less than 12.2%. This was calculated using Equation 1, which combines the effects of the structural changes from fossil fuels to non-fossil fuels and the structural changes within the fossil fuel mix. Independently, using Equation 2, the achieved non-fossil fuel target (15% from a level of about 6.8% in 2005) can contribute to an 8.8% decrease in the carbon intensity of energy. The impact of internal structural changes within the fossil fuel sector is not on a par with the impact of substituting fossil fuels with non-fossil fuels. There are two reasons for this: first, the difference in emissions factor is greater between non-fossil fuels and fossil fuels; second, the evolution of the fossil fuel share in the primary energy mix is comparatively smaller over the10 years from 2010–2020.
5.2. Non-fossil fuel and carbon intensity targets
Figure 3 depicts the relationship between the non-fossil fuel and carbon intensity targets, derived using Equations 4 and 5. The dashed line with a decreasing slope shows the combinations of GDP growth rates and elasticity of primary energy demand to GDP for which the planned expansion of non-fossil fuels is sufficient to achieve the 15% non-fossil fuel target. Combinations below (above) the line lead to over-achievement (under-achievement) of the target. If it is assumed that the 15% non-fossil fuel target is achieved, the positively sloped boundary curve (solid line) implies that different combinations of GDP growth and energy elasticity will impact the over- or under-achievement of the carbon intensity target (with a 45% carbon intensity reduction target, the effects of structural change in fossil fuels are included).
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08 March 2013Figure 3 Boundary curve for the accomplishment of the carbon intensity target assuming non-fossil fuel target achieved
Note: The solid line separates the area where the carbon intensity target is achieved or not. For the combination of GDP growth and energy elasticity above this line, the carbon intensity target is under-achieved; it will be over-achieved in the area below the line. The dashed line is drawn based on the assumption that the 15% target is achieved, given the likely non-fossil fuel scenarios mentioned in Section 4 (therefore, the line corresponds to a fixed level of primary energy use, i.e. 4.4 billion TCE). The point (8%, 0.53) corresponds to the scenario shown in Section 4.
![]({"type":"image","src":"/na101/home/literatum/publisher/tandf/journals/content/tcpo20/2013/tcpo20.v013.i03/14693062.2013.768929/20130308/images/medium/tcpo_a_768929_o_f0003g.jpg"})
Figure 3 Boundary curve for the accomplishment of the carbon intensity target assuming non-fossil fuel target achieved
Note: The solid line separates the area where the carbon intensity target is achieved or not. For the combination of GDP growth and energy elasticity above this line, the carbon intensity target is under-achieved; it will be over-achieved in the area below the line. The dashed line is drawn based on the assumption that the 15% target is achieved, given the likely non-fossil fuel scenarios mentioned in Section 4 (therefore, the line corresponds to a fixed level of primary energy use, i.e. 4.4 billion TCE). The point (8%, 0.53) corresponds to the scenario shown in Section 4.
The intersection point, approximately 0.55 for energy elasticity and 7–8% for GDP growth rate, is necessary to simultaneously achieve the non-fossil fuel and carbon intensity targets. At this point, the targets of non-fossil and carbon intensity are fully consistent, which corresponds to the likely scenario, i.e. the level at which there is a controllable investment scale in non-fossil fuel sources.
Both the GDP growth rate and the elasticity of energy to GDP are highly aggregated factors and will be determined by many factors in the economic and energy system, but an 8% GDP growth rate is more or less in the range expected by the Chinese government. It is not impossible to keep energy elasticity at about 0.55, which is roughly in the range of longer-term past experience. This is, however, less than the value achieved over the last 10 years (Table 1). These two factors required for the targets to be achieved are in the ‘normal’ range of GDP growth and energy elasticity observed in China. From this perspective, the non-fossil fuel and carbon intensity targets are consistent and achievable.
In order to draw additional policy-relevant conclusions, this relationship is now examined assuming a specific GDP growth scenario (8% from 2005 to 2020).
5.3. Energy consumption
In 2010, primary energy consumption was 3.25 billion TCE (NBS, 2012). Table 2 shows that the equivalent primary energy content of primary electricity will be 662 million TCE in 2020, assuming a coal consumption rate of 300 gce/kWh, which was used to convert electricity (kWh) to primary energy (measured in coal-equivalent value).3 Under such a likely scenario, the total energy consumption will have a ‘quota’ of 4.4 billion TCE, approximately a 3.1% annual growth from 2010 to 2020, in order to ensure that the share of non-fossil meets the 15% target.
If, during the same period, economic growth were to be sustained at 8% annually from 2005 to 2020 (or at 6.5% from 2010 to 2020), which is roughly consistent with current official planning, the energy elasticity to GDP should be kept below the level of 0.53 from 2005 to 2020 (see Table 4 and Figure 3).
TABLE 4 Energy and emission pattern for the non-fossil fuel target achieved and GDP scenario
Low energy elasticity implies the decoupling of economic development and energy consumption, which can be facilitated by structural change in the economy and energy efficiency improvements. In line with the GDP and non-fossil fuel scenario, the decline of energy intensity is 41.4% in 2020 from 2005 (3.5% yearly), which is equivalent to a 28% decline from 2010. The 12th FYP sets the energy intensity reduction target at 16% (GOC, 2011). An energy intensity target above 14% from 2016 to 2020, ceteris paribus, implies that the non-fossil fuel target will be achieved.
5.4. Emissions
If only the effects of non-fossil fuel expansion in the energy mix (Equation 2) are considered, the above GDP and non-fossil scenario will reduce the carbon intensity of GDP by 46.4% from 2005 to 2020 (4.1% annually) (Equation 5).
The potential evolution from coal to oil and gas could further reduce the carbon intensity of GDP. This, together with the effect from expansion of non-fossil fuels, could lead to a decline of carbon intensity to energy by as much as 12.2%. In this scenario, the carbon intensity of GDP would decline at a rate of 4.3% from 2005 to 2020, which is equivalent to a decline of 48.3% by 2020, slightly larger than the 40–45% target.
However, even if a 48.3% decline were to be achieved, CO2 emissions from energy use will continue to grow by 3.4% yearly until 2020. By 2020, this absolute number will increase to nearly 8.4 Gt from 5.1 Gt in 2005.4 If the 2 °C target is thought of as the carbon budget for the whole world, i.e. 30.9 Gt before 2020 (IEA, 2011b), China's emissions share will be 27% of this in 2020, compared to 18.8% in 2005. This increase in China's share of emissions threatens its international image, commodity-exporting environment, and sustainable development, and should be managed carefully.
5.5. Impacts of uncertainty regarding nuclear power
The use of nuclear power is increasingly slowing down in China, in order to strengthen safety norms and re-visit the Chinese government's original plans. If the government does not approve any new projects by 2020, the operating units of nuclear power will total 47 GW (current capacity – approved and in construction – was 37 GW at the end of 2010).5 If the non-fossil fuel target is still to be achieved, it will be necessary to further restrain total energy consumption or expand the development of other non-fossil fuels.
If operation is maintained without interruption, the load factor of nuclear power is approximately two times that of hydro, three or four times that of wind, and four or five times that of solar PV. To replace nuclear power, it is essential to make larger-scale investments in renewable energy. However, due to the emerging problems in the development of wind and solar power, it is not easy to accelerate this schedule and the Chinese government has even proposed slowing down the development process (http://english.gov.cn/2012-03/05/content_2083405.htm).
With only 47 GW of nuclear power at its disposal, and in the scenario where there is no compensation from other non-fossil fuels, China will need to lower its energy intensity (to 0.68 TCE/104 CN¥) and energy elasticity (to 0.30) in order to comply with the non-fossil fuel target. This is reflected in Figure 3, where the dashed line moves towards the origin with lower non-fossil fuel use (also, proportionally, total energy use). Total energy consumption must be reduced to 3.95 billion TCE (i.e. 10% less than the case with nuclear power), which will result in a greater carbon intensity decline of 55%. In this scenario, the carbon intensity target (40–45%) will be over-achieved if GDP growth can be sustained.
6. Conclusions
A series of energy and environmental performance targets – particularly the 15% non-fossil fuel target – has encouraged and rationalized large-scale investment in renewable and nuclear energy, which has the potential to form a significant part of China's energy and power systems. The implications of the non-fossil fuel target for the carbon intensity, energy consumption, and emissions pathway of China have been measured and analysed.
A scenario for non-fossil fuel expansion was evaluated by introducing and applying an analytical framework to check the consistency of the non-fossil fuel and carbon intensity targets. Although the method, admittedly, is simplified, not being based on a full energy system model, it allows a structured evaluation of targets and discussion of the crucial factors and their implications for the achievement of both targets. Four important conclusions can be drawn.
First, decoupling energy and GDP growth is of paramount importance to achieve the non-fossil fuel and carbon intensity targets. The ‘likely’ scenario used in the analysis provided a ‘quota’ of 4.4 billion TCE for primary energy use by 2020, with an energy elasticity to GDP of approximately 0.53 assuming a GDP growth rate of 8% per annum. Higher energy consumption and/or lower GDP growth will present a huge challenge to achieving the non-fossil fuel target and even the relatively less demanding carbon intensity target. With an 8% GDP growth rate (2005–2020), a 14% further decline in energy intensity (2016–2020) over the determined 16% reduction target (2011–2015) will guarantee this decoupling is consistent with the non-fossil fuel target, as well as a slight over-achievement for the carbon intensity target.
Second, the non-fossil fuel target and the 40–45% carbon intensity target can be achieved simultaneously when GDP growth and energy elasticity are in the ‘normal’ range, i.e. in the range of longer-term past experience. The required level of energy elasticity to GDP, however, needs to be less than the value realized over the last 10 years and reach a level that was only realized before China's recent period of rapid industrialization.
Third, to comply with the non-fossil fuel target, the slower expansion of nuclear power capacity must be compensated by other non-fossil options. Otherwise, if options are considered that only involve reducing the total primary energy consumption by 10% (according to the scenario), with nuclear power capacity shrinking from 80 GW to 47 GW), then it should be reduced. Therefore, it is necessary to decouple economic growth and energy demand in the coming decade to a stronger level (about 0.3).
Finally, a structural shift in the fossil-fuel energy mix, away from coal and towards oil and gas, would lead to lower emissions, which would thus support the achievement of the carbon intensity target. It has been a crucial assumption of the analysis that the share of coal will not increase (although there is, of course, no guarantee that this will be so). Specific and direct policies that disfavour coal should be promoted in China to turn this assumption into a reality, especially considering that CCS is not a short-term option. Otherwise, the effort to alleviate emissions growth by reducing energy intensity and expanding renewable and nuclear power will be counteracted by an increasing carbon intensity due to fossil fuels.
| No. of FYP | 6 | 7 | 8 | 9 | 10 | 11 |
|---|---|---|---|---|---|---|
| Year range of FYP | 1981–1985 | 1986–1990 | 1991–1995 | 1996–2000 | 2001–2005 | 2006–2010 |
| Average annual growth rate of GDP | 10.7% | 7.9% | 12.3% | 8.6% | 9.6% | 11.2% |
| Average annual growth rate of total primary energy use | 4.9% | 5.2% | 5.9% | 1.1% | 10.2% | 6.6% |
| Average elasticity of energy consumption to GDP | 0.46 | 0.66 | 0.48 | 0.13 | 1.06 | 0.58 |
| Energy intensity of GDP in the final year of each FYP (TCE/104 CN¥2005) | 2.61 | 2.30 | 1.71 | 1.19 | 1.29 | 1.04 |
| CO2 intensity to GDP in the final year of each FYPa (tCO2/104 CN¥2005) | 5.83 | 5.18 | 3.92 | 2.64 | 2.77 | – |
| Share of non-fossil fuel in the final year of each FYP | 4.9% | 5.1% | 6.1% | 6.4% | 6.8% | 8.4% |
| Sources: aIEA (2011a); otherwise NBS (2012). | ||||||
| Hydro | Nuclear | Wind | Solar | Biomass | |
|---|---|---|---|---|---|
| 2010 (GW) | 213 | 10 | 31 | ∼0.3 | 7 |
| 2020 (GW) | 350 | 80 | 150 | 20 | 30 |
| Annual operating hours (hours) | 3500 | 7000 | 2000 | 1500 | 3000 |
| Electricity generation (TWh) | 1225 | 560 | 300 | 30 | 90 |
| Equivalent primary energy volume (104 TCE) | 36,750 | 16,800 | 9000 | 900 | 2700 |
| Total primary energy content of non-fossil fuel (104 TCE) | 66,150 | ||||
| Corresponding total primary energy ‘quota’ consistent with achievement of 15% target (104 TCE) | 441,000 | ||||
| Sources: The historical statistical date is from CEC (2012); annual operating hours (load factor) are estimated by the authors based on a typical power generating project operation in China (1 TCE = 29.308 GJ). | |||||
| Scenario name | Share of coal, oil, and gas in fossil fuel use (%) | Aggregated emissions factor of fossil fuel (tCO2e/TJ) | Change of carbon intensity of total energy compared to 2005 (%) | ||
|---|---|---|---|---|---|
| Coal | Oil | Gas | |||
| Current policy scenarioa | 71.8 | 19.9 | 8.3 | 81.3 | 10.6 |
| 450 ppm scenarioa | 68.8 | 21.3 | 9.8 | 80.6 | 11.4 |
| Referenceb | 68.6 | 25.1 | 6.2 | 81.2 | 10.7 |
| Low carbonb | 64.8 | 24.9 | 10.3 | 79.9 | 12.2 |
| CM45c* | 66.5 | 26.9 | 6.6 | 80.8 | 11.2 |
| CM55c* | 62.2 | 30.7 | 7.2 | 80.0 | 12.1 |
| Referenced | 68.0 | 22.4 | 9.6 | 80.5 | 11.5 |
| Sources: a IEA (2011b); bJiang and Hu (2009); cDai et al. (2011); dChen (2005). | |||||
| Notes: *CM40 and CM45 denote that carbon intensity will be reduced by 40% and 45%, respectively; Figures calculated using Equation 1. | |||||
| 2006–2010 | 2011–2020 | 2006–2020 | |
|---|---|---|---|
| Average annual growth rate of GDP | 11.2% | 6.5% | 8.0% |
| Growth rate of total energy consumption | 6.6% | 3.1% | 4.3% |
| Average elasticity of energy consumption to GDP | 0.58 | 0.48 | 0.53 |
| Rate of decline of annual energy intensity of GDP | 4.1% | 3.2% | 3.5% |
| Rate of decline of CO2 intensity of GDP | – | – | 4.3% |
| Energy-related emissions in the final year of each period (Gt CO2) | – | 8.4 | 8.4 |
| Sources: Historical statistics and economic and energy data are from NBS (2012); emissions data from IEA (2011a). | |||
Acknowledgements
The International Climate Protection Fellowship of the Humboldt Foundation, Germany, supported this work, and we thank Dr Elmar Kriegler and Dorothe Ilskens in particular. We would like to thank the three anonymous referees for their constructive remarks and knowledge, which improved the article significantly. However, the authors alone remain fully responsible for this article's content.
Notes
According to the latest economic and energy statistics, the decline of energy intensity of GDP in the years from 2006 to 2010 was 2.74%, 5.04%, 5.20%, 3.56%, and 4.00%, respectively, which sum to a cumulative reduction of approximately 19% in five years.
It should be noted that from 2003, coal use was renascent and its share in the primary energy mix increased to 74.9% in 2008 (NBS, 2012). This trend was reversed from 2009 with a high-running coal price, the early phase-out of small power units, and the acceleration of renewable energy.
The conversion efficiency of 300 gce/kWh roughly corresponds to the coal consumption per unit of electricity generated of advanced 600 MW supercritical coal-fired power units in China, equivalent to a heating conversion efficiency of approximately 41%. During the past decade, many units of this level have been built in China's power sector, and this technology may come to dominate coal-fired generation units within two decades. So, it is no surprise that the gross coal consumption rate, i.e. the conversion efficiency from primary electricity to equivalent primary energy, could be 300 gce/kWh by 2020 (NEA, 2012). Hence, this conversion rate was used in the calculations for the primary electricity to energy contents.
CO2 emissions data from IEA (2011a, 2011b) shows that, in 2009, emissions from energy use were already 6.8 billion tonnes, which implies a 7.8% annual growth rate from 2005 to 2009. Thus, the CO2 growth rate should be well below an average of 3.7 from 2005 to 2020.
See http://www.gdcct.gov.cn/agritech/kjrd/201104/t20110414_472405.html for details.
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