The generally adopted worldwide target is to keep the increase in the global mean temperature lower than 2 °C by 2100, which is comparable with that of the preindustrial era. It is feasible for China to realize an emission pathway that is consistent with this target; however, we need to understand the roadmap to do so. In this paper, the results of a modeling study by the Integrated Policy Assessment Model for China (IPAC) concerning the investment required to realize the 2 °C scenario by examining the penetration of low-carbon technologies including energy supply and energy efficiency improvement in end-use sectors is presented. It is found that the investment required in the energy supply sector to realize the 2 °C scenario could reach CN¥1.2 trillion by 2020, CN¥1.0 trillion by 2030, and CN¥1.4 trillion by 2050. The investment needed for energy saving could reach CN¥1.6 trillion by 2020, CN¥1.8 trillion by 2030, and CN¥1.5 trillion by 2050, which represents the additional investment as compared with the use of old technologies. If the investment required both in the energy supply sector and in energy saving in end-use sectors is considered, the total investment is estimated to be CN¥2.8 trillion by 2020, CN¥2.8 trillion by 2030, and CN¥2.9 trillion by 2050. These investments account for 2.5% of Chinas total GDP in 2020, 1.3% in 2030, and 0.6% by 2050, which represents quite a small investment percentage to realize the goal of low-carbon development.


Climate change ; Mitigation ; 2 °C target ; Investment ; China ; Modeling

1. Introduction

Responding to climate change has become a mainstream global policy concern. The goal of achieving a global 2 °C temperature target by 2100 was confirmed during the international negotiation process in recent years. For China, it is essential that CO2 emissions be reduced to support the global climate change target.

In the research of the IPAC model team (Jiang et al., 2013 ), it is possible for China to realize the 2 °C emission pathway if the policies options could be implemented. The policy options in the studies were also assessed to be made and implemented based on the policy framework in China. However there is strong need to understand the size of investment, which is commonly considered to be huge for the 2 °C emission pathway, and will be a big barrier.

China still heavily relies on fossil fuel energy, especially on coal use. Share of coal in total primary energy is 66% in 2014 (NBSC, 2015a  ;  NBSC, 2015b ). There is need to be a rapid transition on energy system under the 2 °C emission pathway for China. Among several key policy options, the use of low-carbon technologies to reduce emissions is one of the most important pathways. However, for this to happen, there must be an investment in low-carbon technologies in order for them to become widely established.

Investment for future low-carbon development is a key issue in future pathway to match the future climate targets. There are already some researches to present the related finding. IEA (2015) concludes that the global demand on newly increased investment is around US$65 trillion from now to 2040 for the 2 °C scenario. Global modeling teams also calculated the investment need for the target of 2 °C (Chaturvedi et al., 2014  ;  IPCC, 2014 ). In China there are also some researches to estimate the investment demand for low-carbon development (Wang and Zhao, 2014 ; Li, 2011  ;  UNDP, 2010 ). These international analysis did not provide technology details for the calculation on investment, and the researches from China did not look at the 2 °C target, and more short term focused. To understand the investment requirements, a quantitative modeling tool is used in this study to analyze the technology investment demands under different scenarios.

2. Methodology

2.1. Methodology framework

For future CO2 emission reduction, changes in energy supply sector and energy efficiency improvement in end-use sector including transport, building and industry are the most important area. This study will mainly focus on the investment need for technology penetration in future in energy supply sector and energy efficiency in end-use sectors.

The investment need for energy supply sector will be presented as total fixed cost need, that is the investment for technologies. Other investment such as investment on land, investment on other environment protection, etc. are not covered. For energy efficiency investment, it is the additional investment to compare the technologies in baseline scenario and the technologies in the 2 °C scenario. For this purpose, in the baseline scenario, benchmark technologies as comparison for higher energy efficiency technologies are identified. Then the investment need is calculated by comparing the difference between fixed cost for both bench mark technologies and higher efficiency technologies. In transport sector, investment for subway is given without any baseline comparison, total investment for subway by investment per kilometer is given.

The definition of power saving investment is the investment in power saving technology minus the investment in baseline technology, which is equal to the extra investment. Concerning transportation, it is difficult to compare it with baseline technology, with respect to investments in subways, railway locomotives, vessels, and aircrafts. Under these circumstances, investments in these technologies are included in the total investment.

The target year is 2050. This is a milestone year for global greenhouse gas (GHG) emission reduction to realize the long-term climate change target. The investment need is also given up to 2050.

2.2. Model framework

In 1992, the Integrated Policy Assessment Model for China (IPAC) model group of Chinas Energy Research Institute began building models. After more than twenty years of research and development, the current IPAC has become a comprehensive policy evaluation model that uses a variety of model approaches (http://www.ipac-model.org ). The IPAC model has been widely applied to policy evaluations of energy and climate change in China, e.g., the national 10th Five-Year, 11th Five-Year, and 12th Five-Year Plans. The IPAC-AIM/technology model is a major component of the IPAC model, whose aim is to give a detailed description of the energy services and related equipment of both the status quo and future development and to simulate the energy consumption process. It includes the computable general equilibrium model, the dynamic economic model, the partial equilibrium model, the minimum cost optimization model based on linear programming techniques that are described in detail, and industry simulation models (Jiang et al., 1998 ; Jiang et al., 2000 ; Jiang et al., 2006  ;  Jiang et al., 2008 .

The IPAC-AIM/technology model covers more than 700 kinds of technologies in 55 sectors, of which more than 150 important technologies were selected in the low-carbon and energy-saving fields for this analysis. To consider these main technologies, we also included their associated learning curves, i.e. future investment costs, as a basis on which to calculate the investment requirements. In the IPAC-AIM/technology model, the technological parameters include the amount of per unit output, the energy consumption in sub-species, other non-energy inputs, fixed technology investments, and technological pollutant emissions factors. Fixed technology investments are given year by year, including both the technology learning curve and the description of future technology costs.

The IPAC-AIM/technology model employs the minimum cost analysis method, in which a variety of minimum cost technologies can be chosen to examine their energy service performances. This model uses linear programming to analyze some of the complex processes of energy use, and the analysis is conducted with respect to process systems rather than any single technique. In the model analysis, when setting various parameters, different criteria and methods can be used, which can expand the scope of the analysis. For example, various investments during technology operation add up to the total technology operating costs, and these investments can, under different circumstances, cover investments in energy, raw materials, labor, and so on. As such, the analysis of the technology costs can reflect those of the actual situation.

2.3. Scenarios

In the IPAC modeling studies, to comprehensively reflect the future emissions of GHGs in China, various emission scenarios were designed based on several main factors related to future emissions, drawn from a previous study of scenarios for 2050 that was carried out by the IPAC modeling team (Jiang et al., 2008  ;  Jiang et al., 2013 ). In this study, two scenarios are chosen for the investment analysis.

First, a business-as-usual (BAU) scenario was examined in which no extra climate change countermeasures are adopted and all development models are possible. The main driving factor in this scenario is economic development. Based on the conclusions of the previous scenario analysis research (Jiang et al., 2008  ;  Jiang et al., 2013 ), it basically reflects Chinas economic development path for the next 50 years, which can be reviewed and commented upon today. The population development model follows the national population plan, in which the population of China will reach a peak of 1.47 billion during 2040–2050. Since 2010 is used as the baseline year, policies issued before 2010 are included in the scenario.

The second scenario is the 2 °C scenario, which mainly analyzes whether the emissions in China can support the 2 °C warming limit of the pre-industrialization era (generally considered to be 1850–2100). The method used here is to firstly analyze Chinas emission space under the 2 °C target. Then, the IPAC-AIM/technology model is used to analyze Chinas scenario for this space and focused on the possibilities. The main measures include further enhancing energy conservation, enhanced renewable energy sources, and nuclear power development as well as the further use of carbon capture and storage (CCS).

In this research, the different scenarios are also compared in the discussion of investment and cost. Key parameters for these scenario such as macro-economic development, democracy, industry products output, technology parameters could be found in Jiang et al., 2008  ;  Jiang et al., 2013 .

3. Key factor in future energy and GHG emissions in China

The 2 °C target proposed by the G8 summit in Italy in 2009 was written into the Copenhagen Accord, but another indicator—cutting the 2050 global GHG emissions by half from those of 1990—was not included in the Accord.

Among the emission pathways determined by current global model groups for the different warming goals (UNEP, 2015 ), the green emission range, in which the possibility of achieving the target of 2 °C temperature rise is more than 66%, is considered the least likely way to achieve the desired emission target. In the IPCC Fifth Assessment Report, the most likely way to realize the 2 °C warming target scenario offered by the model group was to achieve a global emission peak by 2020–2025. The sooner the global emission peak is achieved, the greater the pressure will be imposed on China. So, to analyze Chinas emission scenario, a scenario in which the global emission pathway will achieve the emission peak later was selected. Based on this consideration and analysis, the Chinese emission scenario is the most favorable for China in realizing the global warming target.

Low-carbon development is not always costly. In this analysis, there are two factors. First, because the energy demand resulting from energy saving in a low-carbon scenario is significantly less than that in the baseline scenario, judging the scale of the energy industry sector, the investment in low-carbon scenario is less than that in the baseline scenario. Second, the technology cost in the low-carbon scenario is higher than that in the baseline scenario, which requires an increasing investment in the energy industry sector. Considering these two factors together, investment in the energy industry sector in the low-carbon scenario is slightly less than that in the baseline scenario.

A countrys energy consumption is another indicator for determining that countrys required investment. National energy consumption expenditure refers to the amount of end-use energy multiplied by energy prices. On one hand, due to energy saving, final energy demand declines in the low-carbon scenario, so expenditure decreases, but due to the increase in energy and carbon taxes, energy prices rise, which leads to increase in cost. Overall, the energy cost in the low-carbon scenario is below that of the baseline scenario. If energy and carbon taxes are not considered, energy prices in the low-carbon scenario decline compared with those in the baseline scenario.

To achieve a target of a global 2 °C temperature increase by 2100, the CO2 emissions across the world related to energy activities must drop by 60% by 2050, which is consistent with a 50% decrease in GHG emissions. Considering the difficulty of decreasing GHG emissions by non-energy activities, the main contribution of this decrease is the GHGs discharged due to energy activities. Based on the previous research (Jiang et al., 2013 ), from 2005 to 2050, the accumulative CO2 emission in the baseline scenario is 480 Gt. Under the scenario for achieving the 2 °C target, China must control the accumulative emission volume to within 300 Gt, which will account for 38% of the worlds emissions.

4. Computation of required investment

Investment in energy supply sector will increase in both BAU scenario and the 2 °C scenario because of the future increasing demand for energy. In BAU scenario (Fig. 1 ), due to the slowing down of heavy industry after 2015, the investment energy demand increase will also slow down, and then the newly increase energy infrastructure will be smaller compared with previous years.

Fig. 1

Fig. 1.

Energy supply sector investment in the baseline scenario and 2 °C scenario (unit: CN¥ billion in 2010).

Compared with BAU scenario, investment need in the 2 °C scenario (Fig. 1 ) increase significantly by 2020 and after. The major driving force is to invest on renewable energy development such as wind and solar power, together with grid development to support renewable energy. In 2020, the investment demand in 2 °C scenario is 51% higher than the BAU scenario, and 20%, 66%, 14% higher in 2030, 2040 and 2050 respectively.

For investment in energy efficiency, there is not big difference between the BAU scenario and the 2 °C scenario. In the BAU scenario (Table 1 ), energy efficiency improvement is emphasized, there is not big potential for further improvement in the 2 °C scenario (Table 2 ). In 2020, investment for energy efficiency in the 2 °C scenario goes up to CN¥ 1.56 trillion, and then increase to CN¥1.84 trillion in 2030.

Table 1. Energy saving investment in the baseline scenario (unit: CN¥ billion in 2010).
Sector 2010 2020 2030 2040 2050
Manufacturing 342.6 192.8 220.7 227.8 247.9
Transportation 100.1 494.5 434.4 372.0 236.0
Building 445.3 391.9 497.6 365.8 625.9
Total 888.0 1079.2 1152.7 965.6 1109.8

Table 2. Energy saving investment in the 2 °C scenario (unit: CN¥ billion in 2010).
Sector 2010 2020 2030 2040 2050
Manufacturing 342.6 215.2 190.6 221.6 227.8
Transportation 296.5 731.5 980.7 888.6 821.4
Building 445.3 618.3 669.6 514.9 447.0
Total 1084.4 1565.0 1840.9 1625.1 1496.2

Investment in transport is given in Table 3 . The investment on subway is given as targeted amount based on the total length of subway system in China, by figuring out the demand of subway with different size of cities. By 2030 altogether there will be 17,000 km subway in China in the 2 °C scenario. With the technology progress for higher efficiency vehicles, aircraft, vessel etc., there cost increase is not significant compared with traditional technologies.

Table 3. Transportation investment in the 2 °C scenario (unit: CN¥ billion in 2010).
Sector 2010 2020 2030
Subway 130.0 1500.0 2900.0
Energy saving vehicles 96.0 174.0 425.0
Energy saving locomotives 7.2 8.4 8.4
Energy saving vessels 4.3 4.3 3.5
Energy saving aircrafts 135.0 135.0 125.0

Investment in power generation sector in detail is given in Table 4 . Renewable energy including wind, solar and hydro dominates the newly increased investment. With the assumption of cost reduction in future for renewable energy and nuclear power, the investment for the low carbon power is not huge.

Table 4. Energy supply sector investment in the 2 °C scenario (unit: CN¥ billion in 2010).
Year Coal fired power Oil fired power Gas fired power Hydro-power Nuclear power Wind power Solar power Biomass Power Total
2010 300.6 3.1 8.6 153.0 25.9 51.6 9.0 4.5 556.3
2020 93.5 4.0 27.4 232.3 88.3 168.3 198.8 22.8 835.4
2030 31.2 2.6 16.1 127.2 86.4 162.1 206.3 8.0 640.0

Table 5 lists the detailed investments and emissions per sector, and Table 6  ;  Table 7 detail the capacity of generation per technology. These tables could tell more detailed calculation from the model. It reflects the technology progress with learning curve effects in different sectors. Investment in renewable energy is the major part for the investment needs.

Table 5. Investment/power saving investment in the 2 °C scenario.
Sector Investment breakdowns per sector (CN¥ billion in 2010) Emissions (Mt CO2 )
2020 2050 2020 2050
Electric power Traditional resources 124.9 26.4 4034.0 3663.o
Renewable resources 389.8 669.1
Nuclear power 88.3 128.6
CCS 15.9 104.5 114.1 1781.4
Grid 396.8 442.6
Petroleum 98.8 91.3
Coal 53.7 0.4
Agriculture 32.7 46.6 95.4 112.8
Manufacturing Steel 85.6 33.6 1069.6 452.9
Glass 8.3 9.9 31.0 17.9
Non-ferrous 5.0 2.5 219.4 107.4
Chemical 26.1 21.8 497.0 311.8
Boiler 21.62 28.1
Electric motor 49.6 118.0
Transportation Energy saving vehicle 174.0 466.6
Subway 698.7 408.0
Others 147.7 114.7
Building New building 204.4 184.8
Old building renovation 361.1 169.3

Table 6. Power generation by technology in the 2 °C scenario (unit: TW h).
Year Small coal Large coal unit Super critical U.S.-critical IGCCa -20% IGCC-fuel cell PFBCb
2010 319 1565 894 287 0 0 128
2020 116 1625 1122 638 213 0 155
2025 37 1312 1162 750 337 0 150
2030 0 831 1143 793 554 38 104
2040 0 276 645 524 483 60 26
2050 0 0 366 392 457 78 13

a. Integrated gasification combine cycle.

b. Pressurized fluidized bed combustion.

Table 7. Generation capacity per technology in the 2 °C scenario (unit: TW h).
Year Natural gas NGCC Oil Solar PV Solar thermal Biomass direct Biomass IGCC Wind on shore Wind off shore Nuclear Hydro
2010 78 5 58 1.2 0.0 20.7 0.0 66.0 0.2 140.7 575.2
2020 349 122 72 130.4 0.0 130.4 0.0 502.1 5.1 760.8 1304.3
2025 404 208 64 225.7 0.0 145.1 0.0 718.4 7.3 1088.4 1451.2
2030 415 353 61 323.2 17.0 165.7 0.0 882.8 76.8 1483.0 1483.0
2040 356 652 50 735.1 72.7 189.5 0.0 1292.5 303.2 2613.0 1695.4
2050 185 1133 44 1006.8 124.4 208.7 0.0 1481.6 605.2 3240.0 1647.5

As fossil fuel fired power generation, Integrated Gasification Combined Cycle (IGCC) should be launched at early time as a clean technology of both CO2 emissions and local air pollution. IGCC is not yet on the way to be supported by policies right now. CCS also need to be promoted from today, in order to follow the roadmap for CO2 emission reduction by CCS. The policies need to be designed to support CCS to be developed today while its CO2 emission reduction will be in future. This is time mismatch which need the policy support. With the 2 °C emission pathway, CCS will getting to be very crucial in long term, especially in the negative emission world.

Investment on renewable energy will increase in future, to reach the high penetration by 2050. A good news is the investment for renewable energy already go more than CN¥600 billion in 2015, which is higher than the data shows in Table 5 . The key question is whether the investment will keep for long time. Based on EUs data, EU only put investment on renewable energy to be more than US$100 billion for 2–3 years, and then decrease sharply (REN21, 2016 ). If China will make the transition in power generation to be low carbon, large amount of investment on renewable energy is essential. The cost of wind and solar, and other modern renewable energy will drop in future.

5. Conclusions

Despite the difficulty in determining the investment required to realize Chinas CO2 emission target, due to the various definitions and methodologies used to quantify it, the required investment based on the required technology investment has been considered. Based predictions of the investment needed in the energy industry on the specific technologies required in the low-carbon scenario with respect to the associated fixed assets. For other end-use energy sectors, the investment required based on the additional cost for more highly energy efficient technologies was calculated, as compared with reference technologies.

Based on the IPAC modeling analysis, the investment required for the energy sector in the 2 °C scenario could reach CN¥1.2 trillion by 2020, CN¥1 trillion by 2030, and CN¥1.4 trillion by 2050.

Investment requirements for energy saving could be CN¥1.6 trillion by 2020, CN¥1.8 trillion by 2030, and CN¥1.5 trillion by 2050, which represent the additional investment as compared with using old technologies.

The investments in the energy sector and in energy saving was put together, the requirement would be CN¥2.8 trillion by 2020, CN¥2.8 trillion by 2030, and CN¥2.9 trillion by 2050. These investments account for 2.5% of Chinas total GDP by 2020, 1.3% by 2030, and 0.6% by 2050. As such, they represent quite a small percentage to meet national investment goals for low-carbon development.


This study was supported by National Science and Technology Program (2012CB955801 ), Basic Research and National Objectives& National Basic Research Program of China (2014CB441300 ), and National Social Science Foundation (15ZDA055 ).


  1. Chaturvedi et al., 2014 V. Chaturvedi, L. Clarke, J. James Edmonds, et al.; Capital investment requirements for greenhouse gas emissions mitigation in power generation on near term to century time scales and global to regional spatial scales; Energy Econ., 46 (2014), pp. 267–278
  2. IEA, 2015 IEA (International Energy Agency); World Energy Outlook 2015; IEA Publication, Paris (2015)
  3. IPCC, 2014 IPCC; Climate Change: Mitigation of Climate Change; Cambridge University Press, Cambridge and New York (2014)
  4. Jiang et al., 2006 K. Jiang, X. Hu, S. Zhu; Multi-gas mitigation analysis by IPAC, volume multi-greenhouse gas mitigation and climate policy; Energy J., 27 (Special Issue 3) (2006), pp. 425–440
  5. Jiang et al., 1998 K. Jiang, X. Hu, Y. Matsuoka, et al.; Energy technology changes and CO2 emission scenarios in China  ; Environ. Econ. Policy Stud., 1 (1998), pp. 141–160
  6. Jiang et al., 2000 K. Jiang, T. Masui, T. Morita, et al.; Long-term GHG emission scenarios of Asia-Pacific and the world; Technol. Forecast. Soc. Change, 61 (2–3) (2000), pp. 207–229
  7. Jiang et al., 2008 K.-J. Jiang, X.-L. Hu, X. Zhuang, et al.; Chinas energy demand and emission scenarios by 2050; Adv. Clim. Change Res. Rev., 4 (5) (2008), pp. 296–302
  8. Jiang et al., 2013 K.-J. Jiang, X. Zhuang, R. Miao, et al.; Chinas role in attaining the global 2 target; Clim. Policy, 13 (S01) (2013), pp. S55–S69 http://dx.doi.org/10.1080/14693062.2012.746070
  9. Li, 2011 M. Li; Calculation of fund needs for low carbon transition in China; J. Huazhong Univ. Sci. Technol. Soc. Sci. Ed., 25 (3) (2011), pp. 98–103
  10. NBSC, 2015a NBSC (National Bureau of Statistics of China); China Statistic Year Book; China Statistic Press, Beijing (2015) (in Chinese)
  11. NBSC, 2015b NBSC (National Bureau of Statistics of China); China Energy Statistic Year Book 2015; China Statistic Press, Beijing (2015) (in Chinese)
  12. REN21 Renewables, 2016 REN21 Renewables; Global Status Report; REN21 Report, Paris (2016) http://www.ren21.net/status-of-renewables/global-status-report/
  13. UNDP, 2010 UNDP (The United Nations Environment Programme); China Human Development Report; UNDP Publication (2010)
  14. UNEP, 2015 UNEP; Emission Gaps 2015; UNEP Publication (2015)
  15. Wang and Zhao, 2014 L.-J. Wang, Y. Zhao; Analysis of economic losses and capital needs in China to achieve low carbon development; Ecol. Econ., 30 (3) (2014)
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