Final Report Summary - POEM (Policy options to engage emerging Asian economies in a post-Kyoto regime)
Executive summary:
Mitigation efforts in China and India are necessary in order to meet ambitious global climate targets. In the POEM project, various aspects of carbon mitigation in India and China have been addressed. The main aim was to analyse how a 2-degree climate target could affect economic and energy systems development in China and India.
In an analysis of the scientific literature on how effort-sharing approaches affect emission allowances and abatement costs of China and India it was shown that reductions for both China and India differ greatly in time, across and within approaches and between concentration stabilisation targets. For China, allocated emission allowances in 2020 are substantially below baseline projections, while India's emission allowances show high increases compared to 2005 levels and, if emission trading is allowed, financial revenues from selling credits might compensate mitigation costs in most approaches.
In a modeling framework seven national (India and China) and global models (economy wide, computable general equilibrium - CGE, and energy system models) were soft-linked with harmonized baseline developments. Utilising the modelling framework, analyses were carried out based on a global greenhouse gas emission pathway aiming at a radiative forcing of 2.9 W/m2 in 2100, compatible with the 2-degree target, and with a policy regime based on convergence of per capita CO2 emissions with emissions trading.
Project Context and Objectives:
II.1 The Challenge
In order to restrict global warming to 2 oC, major greenhouse gas (GHG) emission reductions are needed by 2050. While most of the accumulated anthropogenic atmospheric carbon dioxide can be attributed to industrialized countries, the greater share of future emissions will come from the developing world, and India and China will contribute to a substantial part of this. Thus, participation by India and China in climate change abatement is essential. However, the countries are reluctant to enter into any binding commitment due to development objectives. Are there policy options being able to combine both the development and climate perspectives'
II.2 The Project Objectives
Any climate policy has spill-over effects across several societal sectors and, thus, carefully chosen national policies coupled with international cooperation may offset some of the possibly negative effects. The primary objective of the study was to develop a portfolio of policy options including both international and national policies as well as institutional frameworks for international cooperation for India and China in order to facilitate their engagement in post-2012 climate change abatement regime. By applying an integrated modeling framework, the project will explore possible multiple pathways which may exist for India and China to contribute into international climate initiatives while not compromising national development priorities.
II.3 The Methodology
The project built upon two hypothesis: that there are options for engagement of India and China in climate commitments combining climate and development objectives; and that an integrated modelling framework can assist in techno-economic assessments of such options.
The project modelling framework comprised a number of global and national models:
- the global climate model FAIR-connected to the global energy model TIMER,
- the global CGE model DART,
- a national macro-economic model for India and China, respectively,
- a national energy system model MARKAL for India and China, respectively.
Originally, applications of the global population and health model PHOENIX/integrated sustainability model GISMO were also planned for but they came to play a less prominent role in the project than anticipated.
II.4 Project structure
The research activities of the project, distributed over 36 months were divided into five work packages (WP):
- WP 1: Review of national socio-economic, energy and environment conditions and policies,
- WP 2: Identification/design of international climate policies in a post-Kyoto regime,
- WP 3: Modelling and policy analyses,
- WP 4: Design of national policies and institutional frameworks for international cooperation,
- WP 5: Dissemination.
Workpackages 1 to 4 were further divided into a number of tasks of different character.
Review of national socio-economic, energy and environment conditions and policies:
- Task 1.1: Review of macro-economic development and policies and setting related modelling parameters and indicators;
- Task 1.2: Review of energy and environment development and policies.
Identification/design of international climate policies in a post-Kyoto regime:
- Task 2.1: Review of the available international climate policies and framework;
- Task 2.2: Identifying/designing plausible post-2012 regimes and instruments for future commitments and participations of emerging economies.
Modelling and policy analyses:
- Task 3.1: Developing integrated modelling framework;
- Task 3.2: Policy and scenario analyses.
Design of national policies and institutional frameworks for international cooperation:
- Task 4.1: Identifying/designing macro-socio-economic, energy and environment related domestic policies;
- Task 4.2: Designing institutional frameworks for international cooperation.
Project Results:
The main results of the project will be described following the sequence of the work packages of the project. They were of rather different character. WP1 provided an overview and background on energy, economy, environment and policies in India and China. WP 2 analysed the literature on burden sharing regimes and their possible impact on India and China and, in particular, the different impacts on the two countries. In WP 3 a modeling framework utilising soft-linking of a number of economy and energy systems models was developed and applied for policy and scenario analysis. In WP4, possibilities and barriers of integrating international climate regimes with national policies were assessed.
III.1 Work package 1
The objectives of work package 1 were the
- Understanding of national macro-socio-economic, energy and environment development, policy issues and their interactions across different sectors; and
- Preparation of macro-economic and socio-economic parameters and indicators for modelling and policy simulations.
The work package had the following two tasks:
- Task 1.1: Review of macro-economic development and policies and setting related modelling parameters and indicators;
- Task 1.2: Review of energy and environment development and policies.
The work package report is divided into the following chapters:
- Ch 1: The role of Asian countries in climate debate
- Ch 2: Development and climate change linkages
- Ch 3: Development trends and drivers for China and India
- Ch4: Development indicators for China and India
- Ch 5: Energy and environment policies in China and India
- References
III.2 Work package 2
The objective of the work package was to:
- Identify and/or design plausible post-2012 regimes for future commitments for emerging economies and instruments for their participation to achieve targets
The work package was divided into two tasks:
- Task 2.1: Review of available international climate policies and framework,
- Task 2.2: Identifying/designing plausible post-2012 regimes and instruments for future commitments and participations of emerging economies.
Name Abbreviation Short description
Direct participation
Contraction and convergence C&C Emission targets based on a convergence of per capita emission levels of all Parties under a contraction of the global emission level.
Grandfathering GF Distribute permits in proportion to current emissions
Equal per capita allocation EqPC Distribute permits in proportion to population
CSE convergence CSE Per capita emission convergence (C&C) combined with basic sustainable emission rights, by Centre of Science and Environment
Historic responsibility* HR Distribute permits in proportion to the contribution of climate change over a certain period of time
Multicriteria MC Distribute permits based on a formula including several variables, such as population, GDP and others
Global compromise GC Allocation of the global emission allowances based on a population-weighted preference score voting for either emission (Grandfathering) or per capita allocation
Triptych TY National emission targets based on sectoral considerations
Horizontal equity Hor Distribute permits to equalise net welfare change as % of GDP
Vertical equity Vert Progressively distribute permits proportions inversely correlated with per capita GDP
Emission Intensity EI Emission reductions related to improvements in the emissions per unit of output, with a participation threshold
Carbon tax Tax All countries agree to a common, international GHG emission tax
Gradual participation
Multi-stage MS Countries participate at different stages and with stage-specific types of targets; countries transition between stages as a function of indicators such as income and emission level
Common but differentiated convergence CDC All countries' per capita emissions converge, but differentiated, as countries only start to converge when their per capita emissions are at a certain percentage above the global average
South-North Dialogue proposal S-N Countries participate in the system at different stages and with stage-specific types of targets
Ability to Pay AtP Emission reduction requirements based on per capita income levels, with a participation threshold
Income Distribution ID Distribute permits in proportion to the share of rich or poor people in a country, with a participation threshold
- The historical responsibility and emission intensity approaches are placed under full participation, but there are also some applications of this approach with a participation threshold that could be placed under gradual participation.
The work package 2 report concludes that:
The emission allowances for both China and India differ greatly between studies, hence, not only across regimes, but also within regimes. This can largely be explained by methodological issues such as model structure differences, assumptions on baseline developments and parameter assumptions within the regimes. Studies show especially a wide variation in baseline developments for China, leading to large uncertainties in the results.
For China, literature shows considerable differences between regimes on the short term, but literature on low stabilisation scenarios shows deep cuts in allowances on the long-term. Towards 2020 and 2030, studies to Multi-stage, CDC, Triptych and Historic Responsibility regimes show the highest emission allowances and lowest costs or economic impact. Studies to Grandfathering and C&C show large reductions in allowances for China. For 2050, however, studies to low stabilisation scenarios (IPCC cat. I) show that Chinese emission allowances reduce to 50-80% below 2005 levels, irrespective of the regime and that China becomes a buyer of emission rights by that time.
III.3 Work package 3
The overall objective of the work package was the development of an integrated modelling framework for policy and scenario analyses; and to carry of a number of policy and scenario analyses in order to quantify the impacts of national and international policies through the application of the modeling framework.
The work package was divided into two tasks, task 3.1. and task 3.2 where task 3.1 concerned the development of an integrated modelling framework while task 3.2 concerned the actual policy and scenario analyses applying the developed modelling framework.
The development of an integrated modelling framework was one of the core activities of the project, and the task with most manmonths related to it. The objective of the modelling framework was to enable quantifications of selected policy designs developed based on the work within primarily work package 2 but to some extent also work package 4.
In order to analyse the impacts of international climate policies at national socio-economic and sectoral levels, and cost-benefits of several policies, the project had to its disposal a number of different types of models at global and national scales:
- the global climate model FAIR-connected to the global energy model TIMER,
- the global CGE model DART,
- a national macro-economic model for India,
- a national macro-economic model for China,
- a national energy system model India-MARKAL
- a national energy system model China-MARKAL, and
- the global population and health model PHOENIX/integrated sustainability model GISMO, which eventually was not extensively utilized.
These models are described in detail in an appendix to the Workpackage 3 report and here just a summarizing description is provided.
The FAIR model, developed and maintained by PBL, calculates through its emissions allocation module the regional or countries' emission targets for different climate regimes for future commitments within the context of meeting long-term climate targets such as stabilising atmospheric GHG concentrations. It consists of: 1) a climate model for calculation of the climate impacts of global emission pathways; 2) an emission allocation model to calculate the emission allowances for countries and regions for more than ten regimes for the differentiation of future commitments; and 3) a costs model to calculate the abatement costs and abatements on the basis of the emission allowances, the use of the flexible Kyoto mechanisms such as international emissions trading and substitution of reductions between the different gases and sources following a least-cost approach.
The FAIR model was connected to the world energy model TIMER, which represents a consistent description of the world energy system. It allowed, in the context of the project, analysis of climate mitigation costs for China and India in a global context.
The Dynamic Applied Regional Trade (DART) model, developed and maintained by IfW, is a global applied general equilibrium model, with a coverage of several global regions including India and China. DART was developed especially for the analysis of international climate policies. The model, distinguishing various sectors, is sufficiently detailed to monitor the development of energy-related CO2 emissions.
Within the Global Integrated Sustainability Model (GISMO), PHOENIX, DART and TIMER are integrated and coupled to take into account feedbacks, and thereby insights in the interactions between the energy system, the economic system and the human system (including health issues), resulting in plausible and consistent scenarios.
A SAM (Social Accounting Matrix) based Computable General Equilibrium (CGE) model for India and China, respectively, is used to analyse the macro-economic and social impacts of energy and climate parameters due to climate abatement measures. A Social Accounting Matrix (SAM) can be defined as an organized matrix representation of all transactions and transfers between different production activities, factors of production and institutions (like households, corporate sector and government) within the economy and with respect to the rest of the world. A SAM is thus a comprehensive accounting framework within which the full circular flow of income from production to factor incomes, household income to household consumption and back to production is captured. Households are classified into different income classes and as urban and rural. SAM provides the database for many multi-sector models including the CGE models. Compared to DART the national SAM-based CGE models can provide better national and sectoral disaggregations. The China national CGE model is denoted CEEPA and the India national CGE model is denoted IEG-CGE.
MARKAL is a bottom-up technology-driven modelling framework based on a linear optimisation approach and thus a modelling framework useful for the understanding of complex interactions between energy and environment and the role of energy technologies for energy sector development. Inputs to MARKAL include energy demand by sectors/end-uses, energy resource availability, and energy technologies used for energy production, conversion and end-uses (represented by technical, economic and environmental characteristics). Model outputs include optimal energy technology choice, energy related emissions, energy system costs, marginal cost of energy supply, import/export strategies, and investment requirement for the energy sector. In the project, both MARKAL-China and MARKAL-India models were employed.
The above described models have not been run together in any structured way previously. It was one of the project objectives to investigate how a modelling framework like the one applied could contribute to improved knowledge creation. However, since the models utilised in the project are of very different kinds; global vs national; economic vs engineering; it was a delicate task to construct a modelling framework being able to contribute to improved decision support knowledge. In order to construct the modelling framework, harmonisation of the models to some extent was necessary. Further, the harmonisation process was designed in order for the project partners to improve their understanding of the other models during the harmonisation process. Thus, models were compared in a structured way using a template developed for these comparisons. This comparison was followed by decisions of harmonisation in a step-wise fashion; a new round of comparisons was carried out, followed by further harmonisation, and so further. Below, this process is described in some detail and in the WP 3 report further details are provided.
Comparison and harmonisation process:
- Comparison of global and national population and GDP figures to 2050, followed by harmonisation.
- Fossil fuel price comparison followed by harmonisation of international prices but not national (for national fossil fuel prices endogeneous supply curves were used).
- Comparison of marginal abatement cost (MAC) curves using block taxes. Large differences found in particular between engineering type models and computational general equilibrium (CGE) type models. This led to the introduction of new technology representation in the CGE models based on TIMER and MARKAL model data (back-stop technologies).
- Further, carbon abatement comparisons were carried out.
In addition to the harmonisation, model-linking schemes have been developed as presented in the WP3 report.
The respective owner of each model have been responsible for the model updating and, and Chalmers has been coordinating the activities and the process of model comparison, harmonisation and linking. All steps have been decided upon during the biannual project meetings.
In the original work plan, the possibility of establishing a hard link between two of the models is mentioned. This would have been an interesting exercise but since the major objective of the entire project is not model development as such but policy support and tools for policy support it was decided not to further develop the hard link, which would have been a time and resource consuming option but instead to use soft links throughout the project.
The modelling soft linking, can be described in the following steps:
Institute Netherlands Environmental Assessment Agency (PBL) Netherlands Environmental Assessment Agency (PBL) Kiel Institute for the World Economy (IfW) Beijing Institute of Technology (BIT) Tsinghua University (TU) Institute of Economic Growth (IEG) Indian Institute of Management (IIM-A)
Model class Climate policy model Recursive dynamic energy system model Recursive dynamic computable general equilibrium model (CGE) Recursive dynamic computable general equilibrium model (CGE) Energy system model with perfect foresight Recursive dynamic computable general equilibrium model (CGE) Energy system model with perfect foresight
Regional coverage Global
(26 regions) Global
(26 regions) Global
(13 regions) China China India India
Household groups NA 10 (urban and rural quintiles) 1representative agent per region 2 (urban and rural) 2 (urban and rural) 9 1
Sectors NA 5 sectors (industry, transport, residential, services and other) 12 24 5 sectors (agriculture, industry, commercial, residential and transport) and 32 sub-sectors 18 5 Sectors (agriculture, industry, commercial, residential and transport) 46 end-use sectors
Energy carriers NA Coal, oil, natural gas, modern biofuels, traditional biofuels, nuclear, solar, wind and hydro Coal, natural gas, oil, bio-energy, wind and hydro Coal, natural gas, oil, bio-energy, nuclear, wind and hydro Coal, natural gas, oil, bio-energy, nuclear, wind and hydro Coal, natural gas, oil, bio-energy, nuclear, wind/solar and hydro Coal, natural gas, oil, bio-energy, nuclear, solar, wind and hydro, hydrogen
Technology dynamics Based on marginal abatement cost curves from TIMER and other models Capital stocks, Penetration rate constraints, Learning by Doing Capital stocks, Learning by doing, Autonomous energy efficiency improvement Capital stocks, Autonomous energy efficiency improvement Capital stocks, penetration rate constraints Capital stocks, Energy efficiency improvement, Total factor productivity growth, Efficiency improvement in renewables Capital stocks, Penetration rate constraint, Energy Infrastructure
CCS NA Yes Yes No Yes Yes Yes
Substitutes to petroleum as transport fuel NA Electricity, modern biomass, hydrogen Not explicitly modeled Not explicitly modeled Yes No Electricity, modern biomass, hydrogen
- NA = not applicable
1. FAIR calculates the CO2-equivalent emissions pathway, a globally uniform carbon price and regional emission allowances based on the energy-related CO2 part of the pathway and an effort-sharing approach
2. DART determines the globally uniform carbon price based on the global energy-related CO2 pathway and the regional emission allowances from FAIR
3. The national CGE models use the emission allowance from FAIR and the carbon price from DART to determine changes to the energy system and total climate policy cost
4. The national MARKAL models use the emission allowances and carbon price from FAIR to determine changes to energy system and total climate policy cost
5. TIMER uses the emission allowances from FAIR to determine changes to energy system. Total climate policy cost is determined by FAIR.
Emission pathway
The analysis is based on a global greenhouse gas emission pathway that aims at a radiative forcing of 2.9 W/m2 in 2100 and with a policy regime based on convergence of per capita CO2 emissions with emissions trading.
Burden sharing approach
The so-called common-but-differentiated convergence (CDC) approach is a simple allocation scheme that takes into account 'common but differentiated responsibilities' (see the WP2 report and Ruijven et al 2012a and references therein). It assumes that per capita emission allowances of all countries converge over time. Different from the more well-known Contraction and convergence (C&C), in the CDC approach developing countries have to start their convergence trajectory only after reaching a certain threshold of per capita emissions.
Important parameters for the CDC approach are the long-term per capita emissions convergence level and the threshold that requires countries to enter the regime and start converging. Instead of a threshold, different country groupings are defined according to their current income levels, i.e. developed countries, Advanced Developing Countries (ADCs) and Other Developing Countries (ODCs), that take on different reduction objectives in terms of start year for convergence, convergence level and convergence year.
Main results of the scenario and policy analysis
Emissions
The global greenhouse gas emissions, including all Kyoto gasses, and the corresponding energy related CO2 emissions. Without any mitigation policies global greenhouse gas emissions and energy related CO2 emissions continue to increase towards 2050, with more than 50% and 80% compared to 2010 levels, respectively. The dotted lines represent the 2.9W/m2stabilization emissions pathway.
In DART and FAIR the transition from the baseline emissions to the 2.9 W/m2pathway is achieved via a carbon tax on emissions. These taxes are very similar up to 2045, beyond that the tax in DART rises further, as mitigation options in DART are limited after certain abatement levels, while FAIR allows for more radical technology changes that are especially available in the long run.
Energy system change and climate policy costs
Currently, the Chinese energy system is dominated by coal followed by oil. Other fuels such as natural gas and biomass play a less important role. The primary energy supply grows rapidly between 2010 and 2020 while at a slower speed between 2020 and 2050. Notable is that CEEPA shows a peak in primary energy supply by 2030 in the baseline, while the other models show continued growth. In all models, coal remains the most important fuel in the baseline scenario.
Direct and macro-economic costs of climate policy
The cost of climate policy is measured as abatement cost relative to baseline GDP levels in the energy system models (including FAIR) and as welfare changes (Hicks equivalent variation) relative to the baseline for the CGE models. The estimates for economic impacts between model classes are therefore not directly comparable. Furthermore, since the models include different technologies, sectors and energy sources it can be expected that abatement costs differ. Energy systems models focus on the competition between different technologies for meeting the demand for goods and services and derive cost estimates from detailed descriptions of the energy systems. In contrast, CGE models focus on the economy as a whole and include the interactions between the various sectors. They do not focus on direct costs, but on changes in economic production and consumption levels or welfare, which better captures the implications of overall structural changes and economy wide effects.
The economic impacts of the climate policy scenario for China and India.
While in all models (except CEEPA), costs are increasing over time there are large differences between the models. While the CGE models show moderate costs for a longer period, in the case of DART for the whole model period, costs increase to 2.5 or even 5% relative to GDP in the energy system models by 2040.
One explanation for the modest cost estimate in DART is that in DART the repercussions on the international fuel market are relatively large. The world (as a whole) consumes less fossil fuels in the climate policy scenario as compared to the baseline scenario, so that the (global) fossil fuel price declines. China, an importer of fossil fuels, can profit from this. The national models do not capture this effect.
Sensitivity analysis
In the sensitivity analysis it is tested if the model results are sensitive to alternative assumptions in GDP growth, the timing of emissions reductions, and to choices in the effort-sharing approach. We focus on the economic implications, since the qualitative nature of the energy results turn out to be relatively robust to changes in these assumptions.
The higher GDP growth assumptions imply that the models with a higher GDP growth scenario for China and India, while the rest of the world still follows the OECD baseline scenario. In this case China's economy is projected to grow on average about 6.2% per year between 2010 and 2050 compared to about 5% per year in our base case, while India's economy to grow on average about 7.9 % per year instead of about 6.8% per year. The altered growth assumption also leads to increases in CO2 emissions in the baseline.
In the climate policy case assumed throughout the main part of the analysis, countries implements their high Copenhagen Accord pledge for 2020, after which global emissions gradually decrease. Thus, resulting global 2020 emissions compared to 1990 are higher than in a cost-optimal pathway while the early action case represents a cost-optimal pathway. As a consequence while still aiming for the same 2.9 W/m2radiative forcing target in 2100, the mid- and long-term emissions levels (2025-2050) can be slightly higher.
As alternatives to the CDC base case, we consider two alternative regimes: a global uniform carbon tax approach and an alternative CDC approach. One of the most straightforward proposals is a globally uniform carbon tax, i.e. carbon tax is the same across all regions. Through the global equalization of marginal abatement costs this approach would ensure cost-effectiveness. However, a uniform carbon tax does not distinguish between developed and developing countries, hence leading to no compensation to developing countries.
In the alternative CDC case, further referred to as CDC with delayed participation, China and India start converging 5 years later than in the base case. To stay within the global emission pathway, developed countries have thus to reduce more and converge to 0.6 tCO2/cap - instead of 1.7 tCO2/cap in the base case. These results in a 90% emission reduction for developed countries in 2050 compared to 1990 while developing countries still converge to 1.7 tCO2/cap.
The results show that overall climate policy costs for China are more sensitive to the assumptions on the effort-sharing approaches than to assumptions for economic growth and the global emission pathway. Higher economic growth increases the cost of climate policy compared to the base case for all models, although considerably more for China-MARKAL and CEEPA than for FAIR and DART. Early action has a mixed impact on climate policy costs in the different models.
Finally, an effort-sharing approach with a uniform carbon taxes tends to be most detrimental for China in most models, except China-MARKAL. Also, the magnitude of the economic impact of a tax policy is very different across models. In the CDC with delayed participation, China does not adopt an emission cap in the context of the international climate negotiations until 2030 and for this reason costs are lower in all models compared to the base case. Besides DART, now also CEEPA shows a net benefit from such an effort-sharing approach.
Discussion and conclusion
Energy system change and cost estimations of climate regimes in the literature are often not directly comparable and differences in result are not always easy to explain (Van Ruijven et al., 2012a). The harmonization of the baseline and policy scenarios in this study improves the ability to understand the substantial differences in cost estimations across different model types and individual models. The analysis shows in particular that models with a similar structure (CGE vs. Energy system) lead to comparable results. Differences in model results can thus be explained in part by the general underlying assumptions of CGE versus energy system models.
CGE models are top-down models based on the economic structure and technologies of a reference year. Deviating from this equilibrium is possible through substituting energy inputs by additional capital inputs (technique effect) or by shifting demand to less carbon intensive sectors (composition effect), causing that a drop in energy intensity is important for abatement in these models. Both effects are driven by changes in relative prices. Furthermore, while substitution possibilities in the vicinity of the initial equilibrium are easy to achieve and therefore relatively cheap, deviating further from the initial situation is increasingly costly.
Only explicit modeling of alternative technologies makes it possible to change specific sectors more fundamentally. In our analysis, not all CGE models include low carbon technologies to the same extent and thus react differently to climate policy. We identify in particular a lack of technology alternatives for oil consuming sectors, most important the transport sector. Concerning cost estimates, CGE models take into account different kind of repercussions on other markets. Differences between the national CGE models and the global CGE model include modeling differences in representing repercussion on international fossil fuel markets and the impact of capital transfers on the exchange rate. For details see Weitzel et al (2012).
Generally, energy system models have more options for meeting energy demand than CGE models and more abatement takes place via carbon intensity reductions, i.e. through changes in the energy supply mix. Also, the inertia in the capital stock imply that small carbon taxes lead to little change in the short run in the energy system models. The timing of emission reductions is therefore more important for energy system models and leads compared to CGE models - to higher carbon taxes in the short run. For a more detailed discussion of this issue see Lucas et al. (in prep.). In the longer run, carbon taxes are lower than in the CGE models due to learning and explicit modeling of more abatement options a sharp increase would only be observable when the potential of relatively low cost abatement options is completely exhausted, which is not the case in our analysis. Concerning cost estimates energy system models are able to give only the direct cost of energy system changes.
For MARKAL models, the importance of energy efficiency improvements vis-vis carbon intensity improvements is about the same in relative terms for both countries. Also in TIMER, the carbon intensity improvement plays a major role but here the contribution is even more important in India than in China. For the reduction in carbon intensity, CCS stands out as the most important options across models. In addition, solar energy and small hydro are important in MARKAL-India, CCS is important in China MARKAL and modern biomass in TIMER.
In the main climate policy case assuming a least-cost implementation of international climate policy, CO2 emission levels for the different models in the year 2050 are in the range of -20% to +25% compared to 2005 emission levels in China and between +20 and +130% compared to 2005 emission levels in India. In 2010 China's CO2 emissions are almost three times higher than the Indian emissions, while in the baseline and policy scenarios in 2050 the CO2 emissions in China are about twice those in India. Demand for new capacity in India remains high towards 2050, while in China this demand levels off after 2030. As especially the energy-system models take account of the capital stock, this has a limiting effect on mitigation potential in China compared to India.
In our main policy case the costs of climate policy are larger for China than for India. In the energy system models the cumulative discounted costs as fraction of GDP are in the order of +0.4 to +1.8% for China and -0.7% to -1.7% for India, with positive numbers representing losses and negative numbers gains. In the CGE models, welfare losses range from +0.4% to -0.2% for China and from +1.1% to -4% for India. The main reason for these differences is that per capita emissions for China are already around the world average, while for India they are substantially lower. As the CDC approach implies a convergence of global per capita emissions, India is confronted with a lower reduction objective, and, as a result has a higher potential of selling reductions on the international carbon market generating revenues.
In general China is a seller on the short term, but becomes buyer on the long-term, while India is a seller over the whole 2010-2050 period. Only DART finds that China can benefit from international climate policy, mainly due to reduced costs of fossil fuels, although gains are small. For India, on the other hand, most models show an economic benefit of climate policies up to 2030/2040, mainly due to benefits from international emissions trading. For both India and China the models with a national focus tend to show more negative economic implications of climate policies than the global models. The reason for this is not trivial. For the CGE models, it can be explained in part by repercussions on international fuels market taken into account by the international DART model.
The sensitivity analyses reveal that both China and India benefit from delayed participation and both countries are more negatively affected by climate policies if a uniform carbon tax is assumed instead of a CDC approach. Although, China MARKAL is an exception here, showing that a uniform carbon tax approach results in the lowest costs. The reason behind this result is that in China MARKAL China is a net buyer of permits in the main CDC case. Finally, if higher economic growth rates for China and India are assumed, the model results point towards smaller benefits or larger costs (relative to GDP) of climate policies for both countries.
In conclusions, the results show that economic and energy implications for China and India vary across models. Decreased energy intensity is the most important abatement approach in the CGE models, while decreased carbon intensity is most important in the energy system models. Reliance on Coal without Carbon Capture and Storage (CCS) is significantly reduced in most models, while CCS is a central abatement technology in energy system models, as is renewable and nuclear energy. Concerning economic impacts China bears in general a higher cost than India, as China benefits less from emissions trading. Costs are also affected by changes in fossil fuel prices, currency depreciation from capital inflow from carbon trading and timing of emission reductions.
The multi-model analysis concludes that, compatible with the 2-degree target and global convergence of per-capita CO2 emissions, significant reductions are required in both China and India, implying huge changes in their energy systems.
There are large differences in the size of the energy system and the related CO2 emissions between China and India today, pertinent to the differences in economic activity. In the baseline scenario, the differences will decrease over time primarily due to higher economic growth in India. The current situation and the assumed future developments imply that there are differences as well as similarities in how India and China may be affected by climate policies on an aggregated national level.
In the main climate policy case Indian emissions are allowed to grow more than the Chinese emissions and still stay below their assigned amount, due to the per capita convergence rule and the higher population growth in India. Clear differences and similarities with respect to the actual consequences for the energy system of climate policy can be observed, not only among the two countries, but also among the two model types - CGE vs. energy system model. Energy efficiency improvements are important in the CGE models, while improvements in the carbon intensity, primarily through expansion of CCS and renewables, are more important for the energy system models. With respect to the carbon intensity improvements, CCS is more important in China, while renewables (including biomass) is more important in India.
The economic impacts of international climate policy either measured as direct mitigation costs in the energy system models or as welfare losses relative to baseline GDP in the CGE models - are generally larger in China than in India, while India can even gain. This is primarily the result of India benefiting more from international emissions trading. In general China is a seller on the short term, but becomes a buyer on the long-term, while India is a seller over the whole 2010-2050 period. Dependent on the model, costs are also affected by decreasing global fossil fuel prices, currency depreciation resulting from a net capital inflow from international carbon trading and timing of emission reductions. Furthermore, China and India benefit from delayed participation and both countries are more negatively affected by climate policies if a uniform carbon tax is assumed (no international emissions trading) instead of a CDC approach.
III.4 Work package 4
The main goal of WP 4 of the POEM project was to identify policies that enable participation of the emerging economies in the global carbon mitigation process and simultaneously achieve development and climate goals.
This WP has had two different tasks:
Task 4.1: Identifying/designing macro-socio-economic, energy and environment related domestic policies, and
Task 4.2: Designing institutional frameworks for international cooperation.
WP 4 built on the earlier POEM project work packages WP1 and WP2 and was also closely associated with WP3.
Following the review of macro-economic, energy and environment policies for the emerging economies that was carried out in WP1 and presented in the WP1 report, in this work package (WP4) different national policies (development, energy, environmental) in the emerging economies India and China were assessed from a climate perspective. Further, the alignment of national policies in the two countries was assessed in the perspective of international cooperation in a post-Kyoto regime.
In the project it was agreed that the basis of designing national policies and international co-operation framework would be based on the analysis of modeling results from WP3 for the 2 deg C global CO2 stabilization scenario.
Further, it was decided that the nature of international co-operation (institutional framework) would be assessed based on the agreed burden sharing regimes:
(i) uniform carbon tax with full participation, and
(ii) common but differentiated convergence.
A key focus of WP4 was policies having significant co-benefits vis-vis national development goals like energy security, energy access and air quality.
Some possible areas for exploring co-benefits in this context are:
i) Low Carbon Infrastructure,
ii) Water-Energy Nexus,
iii) Clean Energy,
iv) Energy Conservation,
v) Urban Planning and,
vi) Sustainable Agriculture.
The analysis of WP4 also stressed the immediate targets of 2020. As India and China have announced targets (emission intensities) for 2020 along with the policy road map to achieve those targets, it was useful to analyze domestic policies and international institutional cooperation keeping 2020 targets in mind. In a process building upon WP1, the WP4 report includes more detailed 5-year plan targets and its underlying relevance vis-vis the global climate targets and commitments.
There is some literature focusing on low carbon infrastructure and water-energy inter-linkages, but research work with regards to developing countries is scant. Quantifying the impacts of such a policy choice would help in making greater strides towards achieving global climate goals, particularly in the context of the 2 deg C stabilization target.
Primarily based on the model simulations carried out in WP3, Task 4.2 looked into the level of international cooperation needed to make India and China to comply with global climate combating efforts, without sacrificing the domestic priorities.
In the report, after a brief common introduction, India and China are treated in two different parts. Some key findings and conclusions are presented below, starting with India.
India
There has been a change in the structure of the Indian economy and in line with the nature of emerging economies; the share of service and industrial sector has been consistently growing over the past three decades with a corresponding decrease in the agriculture sector. Over the period, energy and environment policies in India have evolved; albeit slower compared to the challenges posed by rapidly growing economy. Environment policies have covered a wide-range of issues such as air and water pollution, waste management, and biodiversity conservation. However, the policies have traditionally been aimed at environmental protection and geared towards managing local issues.
The National Conservation Strategy and Policy Statement on Environment and Development, 1992, provided the basis for the integration of environmental considerations in the policies of various sectors. For example, the Policy Statement for Abatement of Pollution, 1992, stresses the prevention of pollution at the source based on the polluter pays' principle and The Forest Policy, 1988, highlights environmental protection through preservation and restoration of the ecological balance (a substantial increase of the forest cover in the country through afforestation programmes).
In 1991, liberalization of the economy triggered new policies such as focus on investment, deregulation and initiation of privatization. The energy sector was specifically targeted during the post-1991 period, with significant focus on expanding energy production opportunities (such as coal mining and oil exploration and production), use of alternative fuels (such as natural gas) and energy conversion capacities (such as power plants and oil refineries). Thus, energy policies in India started by laying emphasis on expanding energy production to match increasing demand. In the past decade, energy conservation and efficiency has received greater attention with the adoption of the Energy Conservation Act 2001 and Electricity Act 2003.
There are many supply-side oriented measures, in particular within the power sector, such as R&D in the area of ultra super critical boilers for coal-based thermal plants, use of integrated gasification combined-cycle (IGCC) technology to make coal-based power generation more efficient, the setting up of more combined cycle natural gas plants, promotion of nuclear energy through adoption of fast breeder and thorium based thermal reactor technology, adoption of high-voltage AC & DC transmission to reduce technical losses during transmission and distribution, setting up of small and large hydro power projects as a source of clean energy (apart from adaptation related benefits), promotion of renewable energy technologies such as biomass combustion and gasification based power generation, enhancement in the regulatory/tariff regimes to help mainstream renewable based sources in the national power system and promotion of renewable energy technologies for transportation (biofuels) and industrial fuels but also energy efficient technologies and appliances.
The Energy Conservation Act encompasses multitude of energy conservations measures and actions such as energy consumption standards for equipment and appliances; prohibited manufacture, sale, purchase and import of notified equipment and appliances not conforming to energy consumption standards; establishment and prescription of energy consumption norms and standards for designated consumers; and energy conservation building codes. Another major demand side measure is the Bachat Lamp Yojana (mass distribution of CFLsto help in reducing peak load demand and reduce electricity demand by 6 GW).
These measures have enabled the Indian energy landscape to shift to a more sustainable path, with the ultimate goal of off-setting demand additions on the supply side.
China
China has taken intensive actions to phase out old production capacity. The main aim of this is to contribute to improved energy efficiency but there are both climate and environmental benefits coupled to these measures. Small and old units have been phased out and substituted by larger, more modern technology; e.g. during 2005-2010 a total capacity of 72 GW of small thermal power units were closed, and the proportion of large-sized furnace in the iron and steel industry increased from 21% to 39%.
Other types of project whose objective is increased energy efficiency also have major positive climate implications. In order to implement the Outline of the Eleventh Five-year Plan for National Economic and Social Development and attain the mandatory goal of reducing energy consumption per unit of GDP by around 20%, the National Development and Reform Commission (NDRC) together with other departments, on the basis of the Mid- and Long-term Special Plan for Energy Conservation, formulated and issued in July 2006 the Opinion on Implementing 10 Key Projects of Energy Conservation in the Eleventh Five-year Plan Period. These ten key projects of energy conservation includes e.g. district combined heat and power generation; utilization of waste heat; petroleum conservation and substitution projects; introduction of electrical motors, energy conservation of buildings and 'green' lighting. The Implementation of the ten key projects has resulted in a total of 340 million TCEs saved.
The implementation of standards and labeling system for energy efficiency has improved the energy efficiency of terminal product, and up to date China has issued seven product lists subject to energy efficiency labeling management, covering 23 types of products in household electric appliance, industrial and lighting equipment etc.
The Chinese government attaches importance to the development of low-carbon energy, such as new and renewable energy, and has actively promoted a diversification of the Chinese energy mix e.g. through a number of financial, tax and price incentive policies in the area of renewable energy. Though the primary objective is rather energy security and diversification, the policies also have a strong climate impact.
From 2005 to 2010, the total installed capacity of hydropower plants was increased by 82 %, the total accumulative installed capacity of wind farms was increased by 30 times to 40 GW. The utilization level of solar resources was increased significantly and the total installed capacity of photovoltaic power generator sets was increased by 10 times and the total collector area of solar water heater was doubled. Biomass resources were developed, both as biomass power generation and production of transport biofuels. In addition to renewables, also the nuclear capacity has been expanding. From 2005 to 2010, the share of coal consumption was reduced from 71% to 68%, the share of natural gas consumption was increased from 2.6% to 4.4%, and the share of renewable and nuclear power increased from 6.8% to 8.6%.
The introduction of a carbon tax in China has been proposed by NDRC and the Ministry of Finance (MOF). One important aspect of the introduction of a carbon tax in China is the impact on GDP but also distribution effects are central. Therefore, the CEEPA model has been applied to simulate and compare different carbon tax schemes. The difference among the schemes lies in their different manners of levy, or different manners of revenue recycling.
The study concludes that, if no protections for households are considered, a carbon tax will reduce the living standard of both urban and rural households, and the negative impacts on rural households are greater than on urban households mainly because currently urban households obtain a much greater share in transfer payments.
Exemption of households from carbon tax has weak effects either on reducing the negative impacts on households, or on preventing the expansion of the urban-rural gap. Further, given the current social security system that obviously favors urban households, two measures can effectively reduce the extent of the urban-rural gap expansion caused by carbon taxation. These are a scheme using the carbon tax revenue to reduce the indirect tax and a scheme transferring the carbon tax revenues to households in proportion to their number. Given that the current social security system obviously favors urban households, the only scheme that can completely avoid the expansion of rural-urban gap is a scheme transferring carbon tax revenue to households in proportion to the population. But the long-term negative impacts on household living standard under this scheme are greater than with the no-protection scheme.
Given the current investment-driven economic growth pattern, the negative impacts on household income and welfare under each of the schemes will increase over time. In the long term, a scheme using the carbon tax revenue to reduce indirect tax has obviously smaller negative impacts on household living standard and economic growth than the other schemes. In addition, increasing the share that rural households obtain in government transfers helps to avoid the expansion of the urban-rural gap.
Based on this, some policy recommendations can be drawn. Given the current investment-driven economic growth pattern, it is necessary to introduce proper complementary measures for protecting economic growth and household life when designing a carbon tax scheme for China, and to use carbon tax revenues to reduce indirect tax is the best way to protect economic growth. Protections for households should also mainly rely on carbon tax revenue recycling.
A domestic carbon emission trading system is another possible important mitigation policy choice for China. The outline of the national twelfth five-year plan has addressed to establish an emissions trade market step by step and thus there is good reason to carry out studies on the possible impact of such a trade system in China. The CEEPA model was applied to assess the social-economic impacts of different allowance allocation methods for China.
Three ways to allocate primary permits have been assessed; allocation of the permits for free, not for free and a combination of free and not for free. Free allocation means that the primary permits are allocated for free to sectors or enterprises according to a given rule. Non-gratuitous allocation mainly includes auction and sale at fixed price. The mixed mechanism is a mix of auction and free allocation either simultaneously or time dependent.
Considering the macro-economy aspects of particular interest of the government when designing policies, this study identified gross national product (GDP), employment level (Lab), consumer price index (CPI), total consumption (Cons) and the government income (GovI) as the main objects to address when assessing the macro-economy impacts of different allocation approaches.
The result shows that all studied allocation approaches lead to negative social and economical impacts. The analysis shows that no one of the designed approaches can provide the best effects with regards to all addressed objectives, and that is there is no single optimal allocation approach.
Thus, a number of aspects should be considered in the design of the future allowance allocation approach when carrying out the emission trade system:
- From the perspective of comprehensiveness, the better choice is that permits are auctioned and the revenue is used to reduce the indirect taxes.
- If the protection of people's life in short term is of highest concern, permit auctioning combined with direct revenue transfer to household could be the core allocation mechanism, however it should not be the core allocation mechanism in the long term.
- If the function to raise the fiscal funds is emphasized, a mixed approach in which each sector can get a certain amount of free permit while the remaining needed permits are auctioned could be the core allocation mechanism, while it should not be the core allocation mechanism in long term.
III.5 Additional results
The project has generated a large amount of results of which many are yet to be analysed in detail. It has also led to a number of studies, which are based on the collaboration within the project and the project results but which have not been included in the main project reports. Abstracts, and to some extent conclusions from these four studies are presented below.
The POEM project has also already contributed to a number of other studies; e.g. v Ruijven et al 2011, Kainuma et al 2012, Krey et al 2012, v Ruijven et al 2012b; see the reference list.
1. Effects of international climate policy for India: Evidence from a national and global CGE model (published as Kiel Working Paper No. 1810, November 2012)
Matthias Weitzel, Joydeep Ghosh, Sonja Peterson, Basanta K. Pradhan
In order to reach the 2-degree target it is necessary to control CO2 emissions also in fast growing emerging economies such as India. The question is how the Indian economy would be affected by e.g. including the country into an international climate regime. Existing analyses with either a global model or a single country computable general equilibrium model miss important aspects such as distributional issues or international repercussions. By soft-linking models of these two classes, we provide a more detailed view on these issues. In particular, we analyze different options of transferring revenues from domestic carbon taxes and international transfers to different household types and how different assumptions on exchange rates affect transfer payments. We also show effects stemming from international price repercussions.
2. Energy system changes for China and India under different climate stabilization pathways
Paul Lucas, P.R. Shukla, Wenying Chen, Subash Dhar, Amir Bazaz, Bas J. van Ruijven, Michel M.G.J. den Elzen and Detlef P. van Vuuren
In order to limit global mean temperature increase to the UN climate goal of 2oC, deep reductions in greenhouse gas emissions are needed. We compare abatement costs and changes in the energy systems of China and India derived from three energy system models under two global emission pathways that are in line with a medium likelihood of meeting 2oC: a least-cost pathway and a pathway that postpones mitigation action by implementing the Copenhagen Accord pledges for 2020. Both pathways have similar cumulative CO2-eq emissions for 2010-2050. The analysis shows that postponing mitigation action increases cumulative mitigation costs for both China and India. Furthermore, postponing mitigation action increases the dependence on fossil fuels on the short-term, but decreases dependence on the longer term due to the deeper required emission cuts to compensate for the short-term emission growth. Differences between India and China relate to different periods of rapid economic change and capital stock turnover of power production capacity. China still has a significant share of conventional coal power plant in the mitigation scenarios in 2050 (possible combined with CCS), while Indian power production is almost CO2-neutral by 2050. It should be noted that climate policy also interferes with other energy-related issues that are important in both India and China. It may induce risks, such as increased indoor air pollution, but can also synergize with energy security and urban air pollution. These relations are important to take into account when designing national policies.
3. The impact of carbon taxes on growth, emissions and welfare in India: A CGE analysis
Basanta K Pradhan and Joydeep Ghosh
The main objective of this paper was to analyze the impact of two post-Kyoto climate policy regimes on GDP growth, CO2 emissions, and welfare in India. The first regime is a global carbon tax (CT) while the second regime is based on emission trading permits where the distribution of permits is based on the Common but Differentiated Convergence (CDC) approach. Both climate policy regimes are consistent with the objective of limiting the increase in average global temperature below 2°C over the long term. The results suggest that assumptions about the climate policy regime, model closure and values of substitution elasticities (between value added and energy) play an important role in determining the effects of climate policies.
4. Carbon taxes vs productivity shocks: A comparative analysis of the costs in a CGE framework for India
Basanta K Pradhan and Joydeep Ghosh
The main objective of this paper was to compare the costs of climate policy scenarios with those of probable climate change induced agricultural productivity shocks using a recursive dynamic CGE model in case of India. The social cost of carbon, in terms of agricultural productivity loss, is estimated to be about 17 and 14 percent of GDP, using zero and 3 percent discount rates, respectively. In comparison the costs of climate policy regimes are estimated at 3 and 2 percent, using similar discount rates, respectively. There is a strong case for the adoption of mitigation policies by India, along with other countries, to reduce the level of CO2 emissions in order to protect the agriculture sector from climate change induced productivity shocks. Besides, revenues generated from the implementation of climate policies could be a means to support the adoption of energy efficient technologies and augment capital formation in the economy.
III.6 Final remarks
The policy and modeling analysis was done in a top-down fashion, starting with a global burden-sharing agreement and the global models and then concluding with the impact at the national levels. A bottom-up approach, starting with national policies and objectives could have been chosen instead. These two general approaches were considered and the top-down approach was chosen because the analyzed scenarios were strongly supported by the Chinese and Indian project partners and are broadly in line with national Chinese and Indian proposals. The choice of the top-down approach was also the result of a decision to be consistent with the long-term 2-degree target. With a bottom-up approach we would not have had this guarantee. In some sense such global scenarios are also the natural starting point for using the newly developed modeling framework, which was at the heart of the POEM project. Yet, we see the importance of bottom-up approaches and this is strongly recommended for any future work. Such an approach could then also focus on issues like green financing and CDM and could possibly lead to a strong involvement of national policy makers in India and China at an early stage of the project.
Potential Impact:
The expected impact should, quoting the work programme of the topic ENV-2008.1.1.6.3 be 'to provide a portfolio of policy options for emerging economies to engage in climate change protection measures under a post-2012 regime. ' The project is not only presenting a portfolio of policy options under a post-2012 regime but also attempting to quantify these policy options possible impact on the economy and to some extent also on other societal sectors in terms of socio-economic development. The project is thus obviously highly policy relevant since the main outcome of the project is to contribute to support for policy makers.
The work has targeted India and China since these two countries are the emerging giants and any global climate agreement requires their participation. The work is thus country specific for these two countries and is addressing details on a sectoral level specific for these two countries.L
Major dissemination events
As planned, in each of the countries India and China one major national workshop has been organised by the country partners:
- POEM workshop in New Delhi, Thursday, September 6, 2012 India International Center (IIC), New Delhi.
- POEM workshop in Beijing, Tuesday, September 25, 2012, at the Hotel Nikko New Century Beijing, Haidian District, Beijing.
List of Websites:
http://www.chalmers.se/ee/poem-en.
Mitigation efforts in China and India are necessary in order to meet ambitious global climate targets. In the POEM project, various aspects of carbon mitigation in India and China have been addressed. The main aim was to analyse how a 2-degree climate target could affect economic and energy systems development in China and India.
In an analysis of the scientific literature on how effort-sharing approaches affect emission allowances and abatement costs of China and India it was shown that reductions for both China and India differ greatly in time, across and within approaches and between concentration stabilisation targets. For China, allocated emission allowances in 2020 are substantially below baseline projections, while India's emission allowances show high increases compared to 2005 levels and, if emission trading is allowed, financial revenues from selling credits might compensate mitigation costs in most approaches.
In a modeling framework seven national (India and China) and global models (economy wide, computable general equilibrium - CGE, and energy system models) were soft-linked with harmonized baseline developments. Utilising the modelling framework, analyses were carried out based on a global greenhouse gas emission pathway aiming at a radiative forcing of 2.9 W/m2 in 2100, compatible with the 2-degree target, and with a policy regime based on convergence of per capita CO2 emissions with emissions trading.
Project Context and Objectives:
II.1 The Challenge
In order to restrict global warming to 2 oC, major greenhouse gas (GHG) emission reductions are needed by 2050. While most of the accumulated anthropogenic atmospheric carbon dioxide can be attributed to industrialized countries, the greater share of future emissions will come from the developing world, and India and China will contribute to a substantial part of this. Thus, participation by India and China in climate change abatement is essential. However, the countries are reluctant to enter into any binding commitment due to development objectives. Are there policy options being able to combine both the development and climate perspectives'
II.2 The Project Objectives
Any climate policy has spill-over effects across several societal sectors and, thus, carefully chosen national policies coupled with international cooperation may offset some of the possibly negative effects. The primary objective of the study was to develop a portfolio of policy options including both international and national policies as well as institutional frameworks for international cooperation for India and China in order to facilitate their engagement in post-2012 climate change abatement regime. By applying an integrated modeling framework, the project will explore possible multiple pathways which may exist for India and China to contribute into international climate initiatives while not compromising national development priorities.
II.3 The Methodology
The project built upon two hypothesis: that there are options for engagement of India and China in climate commitments combining climate and development objectives; and that an integrated modelling framework can assist in techno-economic assessments of such options.
The project modelling framework comprised a number of global and national models:
- the global climate model FAIR-connected to the global energy model TIMER,
- the global CGE model DART,
- a national macro-economic model for India and China, respectively,
- a national energy system model MARKAL for India and China, respectively.
Originally, applications of the global population and health model PHOENIX/integrated sustainability model GISMO were also planned for but they came to play a less prominent role in the project than anticipated.
II.4 Project structure
The research activities of the project, distributed over 36 months were divided into five work packages (WP):
- WP 1: Review of national socio-economic, energy and environment conditions and policies,
- WP 2: Identification/design of international climate policies in a post-Kyoto regime,
- WP 3: Modelling and policy analyses,
- WP 4: Design of national policies and institutional frameworks for international cooperation,
- WP 5: Dissemination.
Workpackages 1 to 4 were further divided into a number of tasks of different character.
Review of national socio-economic, energy and environment conditions and policies:
- Task 1.1: Review of macro-economic development and policies and setting related modelling parameters and indicators;
- Task 1.2: Review of energy and environment development and policies.
Identification/design of international climate policies in a post-Kyoto regime:
- Task 2.1: Review of the available international climate policies and framework;
- Task 2.2: Identifying/designing plausible post-2012 regimes and instruments for future commitments and participations of emerging economies.
Modelling and policy analyses:
- Task 3.1: Developing integrated modelling framework;
- Task 3.2: Policy and scenario analyses.
Design of national policies and institutional frameworks for international cooperation:
- Task 4.1: Identifying/designing macro-socio-economic, energy and environment related domestic policies;
- Task 4.2: Designing institutional frameworks for international cooperation.
Project Results:
The main results of the project will be described following the sequence of the work packages of the project. They were of rather different character. WP1 provided an overview and background on energy, economy, environment and policies in India and China. WP 2 analysed the literature on burden sharing regimes and their possible impact on India and China and, in particular, the different impacts on the two countries. In WP 3 a modeling framework utilising soft-linking of a number of economy and energy systems models was developed and applied for policy and scenario analysis. In WP4, possibilities and barriers of integrating international climate regimes with national policies were assessed.
III.1 Work package 1
The objectives of work package 1 were the
- Understanding of national macro-socio-economic, energy and environment development, policy issues and their interactions across different sectors; and
- Preparation of macro-economic and socio-economic parameters and indicators for modelling and policy simulations.
The work package had the following two tasks:
- Task 1.1: Review of macro-economic development and policies and setting related modelling parameters and indicators;
- Task 1.2: Review of energy and environment development and policies.
The work package report is divided into the following chapters:
- Ch 1: The role of Asian countries in climate debate
- Ch 2: Development and climate change linkages
- Ch 3: Development trends and drivers for China and India
- Ch4: Development indicators for China and India
- Ch 5: Energy and environment policies in China and India
- References
III.2 Work package 2
The objective of the work package was to:
- Identify and/or design plausible post-2012 regimes for future commitments for emerging economies and instruments for their participation to achieve targets
The work package was divided into two tasks:
- Task 2.1: Review of available international climate policies and framework,
- Task 2.2: Identifying/designing plausible post-2012 regimes and instruments for future commitments and participations of emerging economies.
Name Abbreviation Short description
Direct participation
Contraction and convergence C&C Emission targets based on a convergence of per capita emission levels of all Parties under a contraction of the global emission level.
Grandfathering GF Distribute permits in proportion to current emissions
Equal per capita allocation EqPC Distribute permits in proportion to population
CSE convergence CSE Per capita emission convergence (C&C) combined with basic sustainable emission rights, by Centre of Science and Environment
Historic responsibility* HR Distribute permits in proportion to the contribution of climate change over a certain period of time
Multicriteria MC Distribute permits based on a formula including several variables, such as population, GDP and others
Global compromise GC Allocation of the global emission allowances based on a population-weighted preference score voting for either emission (Grandfathering) or per capita allocation
Triptych TY National emission targets based on sectoral considerations
Horizontal equity Hor Distribute permits to equalise net welfare change as % of GDP
Vertical equity Vert Progressively distribute permits proportions inversely correlated with per capita GDP
Emission Intensity EI Emission reductions related to improvements in the emissions per unit of output, with a participation threshold
Carbon tax Tax All countries agree to a common, international GHG emission tax
Gradual participation
Multi-stage MS Countries participate at different stages and with stage-specific types of targets; countries transition between stages as a function of indicators such as income and emission level
Common but differentiated convergence CDC All countries' per capita emissions converge, but differentiated, as countries only start to converge when their per capita emissions are at a certain percentage above the global average
South-North Dialogue proposal S-N Countries participate in the system at different stages and with stage-specific types of targets
Ability to Pay AtP Emission reduction requirements based on per capita income levels, with a participation threshold
Income Distribution ID Distribute permits in proportion to the share of rich or poor people in a country, with a participation threshold
- The historical responsibility and emission intensity approaches are placed under full participation, but there are also some applications of this approach with a participation threshold that could be placed under gradual participation.
The work package 2 report concludes that:
The emission allowances for both China and India differ greatly between studies, hence, not only across regimes, but also within regimes. This can largely be explained by methodological issues such as model structure differences, assumptions on baseline developments and parameter assumptions within the regimes. Studies show especially a wide variation in baseline developments for China, leading to large uncertainties in the results.
For China, literature shows considerable differences between regimes on the short term, but literature on low stabilisation scenarios shows deep cuts in allowances on the long-term. Towards 2020 and 2030, studies to Multi-stage, CDC, Triptych and Historic Responsibility regimes show the highest emission allowances and lowest costs or economic impact. Studies to Grandfathering and C&C show large reductions in allowances for China. For 2050, however, studies to low stabilisation scenarios (IPCC cat. I) show that Chinese emission allowances reduce to 50-80% below 2005 levels, irrespective of the regime and that China becomes a buyer of emission rights by that time.
III.3 Work package 3
The overall objective of the work package was the development of an integrated modelling framework for policy and scenario analyses; and to carry of a number of policy and scenario analyses in order to quantify the impacts of national and international policies through the application of the modeling framework.
The work package was divided into two tasks, task 3.1. and task 3.2 where task 3.1 concerned the development of an integrated modelling framework while task 3.2 concerned the actual policy and scenario analyses applying the developed modelling framework.
The development of an integrated modelling framework was one of the core activities of the project, and the task with most manmonths related to it. The objective of the modelling framework was to enable quantifications of selected policy designs developed based on the work within primarily work package 2 but to some extent also work package 4.
In order to analyse the impacts of international climate policies at national socio-economic and sectoral levels, and cost-benefits of several policies, the project had to its disposal a number of different types of models at global and national scales:
- the global climate model FAIR-connected to the global energy model TIMER,
- the global CGE model DART,
- a national macro-economic model for India,
- a national macro-economic model for China,
- a national energy system model India-MARKAL
- a national energy system model China-MARKAL, and
- the global population and health model PHOENIX/integrated sustainability model GISMO, which eventually was not extensively utilized.
These models are described in detail in an appendix to the Workpackage 3 report and here just a summarizing description is provided.
The FAIR model, developed and maintained by PBL, calculates through its emissions allocation module the regional or countries' emission targets for different climate regimes for future commitments within the context of meeting long-term climate targets such as stabilising atmospheric GHG concentrations. It consists of: 1) a climate model for calculation of the climate impacts of global emission pathways; 2) an emission allocation model to calculate the emission allowances for countries and regions for more than ten regimes for the differentiation of future commitments; and 3) a costs model to calculate the abatement costs and abatements on the basis of the emission allowances, the use of the flexible Kyoto mechanisms such as international emissions trading and substitution of reductions between the different gases and sources following a least-cost approach.
The FAIR model was connected to the world energy model TIMER, which represents a consistent description of the world energy system. It allowed, in the context of the project, analysis of climate mitigation costs for China and India in a global context.
The Dynamic Applied Regional Trade (DART) model, developed and maintained by IfW, is a global applied general equilibrium model, with a coverage of several global regions including India and China. DART was developed especially for the analysis of international climate policies. The model, distinguishing various sectors, is sufficiently detailed to monitor the development of energy-related CO2 emissions.
Within the Global Integrated Sustainability Model (GISMO), PHOENIX, DART and TIMER are integrated and coupled to take into account feedbacks, and thereby insights in the interactions between the energy system, the economic system and the human system (including health issues), resulting in plausible and consistent scenarios.
A SAM (Social Accounting Matrix) based Computable General Equilibrium (CGE) model for India and China, respectively, is used to analyse the macro-economic and social impacts of energy and climate parameters due to climate abatement measures. A Social Accounting Matrix (SAM) can be defined as an organized matrix representation of all transactions and transfers between different production activities, factors of production and institutions (like households, corporate sector and government) within the economy and with respect to the rest of the world. A SAM is thus a comprehensive accounting framework within which the full circular flow of income from production to factor incomes, household income to household consumption and back to production is captured. Households are classified into different income classes and as urban and rural. SAM provides the database for many multi-sector models including the CGE models. Compared to DART the national SAM-based CGE models can provide better national and sectoral disaggregations. The China national CGE model is denoted CEEPA and the India national CGE model is denoted IEG-CGE.
MARKAL is a bottom-up technology-driven modelling framework based on a linear optimisation approach and thus a modelling framework useful for the understanding of complex interactions between energy and environment and the role of energy technologies for energy sector development. Inputs to MARKAL include energy demand by sectors/end-uses, energy resource availability, and energy technologies used for energy production, conversion and end-uses (represented by technical, economic and environmental characteristics). Model outputs include optimal energy technology choice, energy related emissions, energy system costs, marginal cost of energy supply, import/export strategies, and investment requirement for the energy sector. In the project, both MARKAL-China and MARKAL-India models were employed.
The above described models have not been run together in any structured way previously. It was one of the project objectives to investigate how a modelling framework like the one applied could contribute to improved knowledge creation. However, since the models utilised in the project are of very different kinds; global vs national; economic vs engineering; it was a delicate task to construct a modelling framework being able to contribute to improved decision support knowledge. In order to construct the modelling framework, harmonisation of the models to some extent was necessary. Further, the harmonisation process was designed in order for the project partners to improve their understanding of the other models during the harmonisation process. Thus, models were compared in a structured way using a template developed for these comparisons. This comparison was followed by decisions of harmonisation in a step-wise fashion; a new round of comparisons was carried out, followed by further harmonisation, and so further. Below, this process is described in some detail and in the WP 3 report further details are provided.
Comparison and harmonisation process:
- Comparison of global and national population and GDP figures to 2050, followed by harmonisation.
- Fossil fuel price comparison followed by harmonisation of international prices but not national (for national fossil fuel prices endogeneous supply curves were used).
- Comparison of marginal abatement cost (MAC) curves using block taxes. Large differences found in particular between engineering type models and computational general equilibrium (CGE) type models. This led to the introduction of new technology representation in the CGE models based on TIMER and MARKAL model data (back-stop technologies).
- Further, carbon abatement comparisons were carried out.
In addition to the harmonisation, model-linking schemes have been developed as presented in the WP3 report.
The respective owner of each model have been responsible for the model updating and, and Chalmers has been coordinating the activities and the process of model comparison, harmonisation and linking. All steps have been decided upon during the biannual project meetings.
In the original work plan, the possibility of establishing a hard link between two of the models is mentioned. This would have been an interesting exercise but since the major objective of the entire project is not model development as such but policy support and tools for policy support it was decided not to further develop the hard link, which would have been a time and resource consuming option but instead to use soft links throughout the project.
The modelling soft linking, can be described in the following steps:
Institute Netherlands Environmental Assessment Agency (PBL) Netherlands Environmental Assessment Agency (PBL) Kiel Institute for the World Economy (IfW) Beijing Institute of Technology (BIT) Tsinghua University (TU) Institute of Economic Growth (IEG) Indian Institute of Management (IIM-A)
Model class Climate policy model Recursive dynamic energy system model Recursive dynamic computable general equilibrium model (CGE) Recursive dynamic computable general equilibrium model (CGE) Energy system model with perfect foresight Recursive dynamic computable general equilibrium model (CGE) Energy system model with perfect foresight
Regional coverage Global
(26 regions) Global
(26 regions) Global
(13 regions) China China India India
Household groups NA 10 (urban and rural quintiles) 1representative agent per region 2 (urban and rural) 2 (urban and rural) 9 1
Sectors NA 5 sectors (industry, transport, residential, services and other) 12 24 5 sectors (agriculture, industry, commercial, residential and transport) and 32 sub-sectors 18 5 Sectors (agriculture, industry, commercial, residential and transport) 46 end-use sectors
Energy carriers NA Coal, oil, natural gas, modern biofuels, traditional biofuels, nuclear, solar, wind and hydro Coal, natural gas, oil, bio-energy, wind and hydro Coal, natural gas, oil, bio-energy, nuclear, wind and hydro Coal, natural gas, oil, bio-energy, nuclear, wind and hydro Coal, natural gas, oil, bio-energy, nuclear, wind/solar and hydro Coal, natural gas, oil, bio-energy, nuclear, solar, wind and hydro, hydrogen
Technology dynamics Based on marginal abatement cost curves from TIMER and other models Capital stocks, Penetration rate constraints, Learning by Doing Capital stocks, Learning by doing, Autonomous energy efficiency improvement Capital stocks, Autonomous energy efficiency improvement Capital stocks, penetration rate constraints Capital stocks, Energy efficiency improvement, Total factor productivity growth, Efficiency improvement in renewables Capital stocks, Penetration rate constraint, Energy Infrastructure
CCS NA Yes Yes No Yes Yes Yes
Substitutes to petroleum as transport fuel NA Electricity, modern biomass, hydrogen Not explicitly modeled Not explicitly modeled Yes No Electricity, modern biomass, hydrogen
- NA = not applicable
1. FAIR calculates the CO2-equivalent emissions pathway, a globally uniform carbon price and regional emission allowances based on the energy-related CO2 part of the pathway and an effort-sharing approach
2. DART determines the globally uniform carbon price based on the global energy-related CO2 pathway and the regional emission allowances from FAIR
3. The national CGE models use the emission allowance from FAIR and the carbon price from DART to determine changes to the energy system and total climate policy cost
4. The national MARKAL models use the emission allowances and carbon price from FAIR to determine changes to energy system and total climate policy cost
5. TIMER uses the emission allowances from FAIR to determine changes to energy system. Total climate policy cost is determined by FAIR.
Emission pathway
The analysis is based on a global greenhouse gas emission pathway that aims at a radiative forcing of 2.9 W/m2 in 2100 and with a policy regime based on convergence of per capita CO2 emissions with emissions trading.
Burden sharing approach
The so-called common-but-differentiated convergence (CDC) approach is a simple allocation scheme that takes into account 'common but differentiated responsibilities' (see the WP2 report and Ruijven et al 2012a and references therein). It assumes that per capita emission allowances of all countries converge over time. Different from the more well-known Contraction and convergence (C&C), in the CDC approach developing countries have to start their convergence trajectory only after reaching a certain threshold of per capita emissions.
Important parameters for the CDC approach are the long-term per capita emissions convergence level and the threshold that requires countries to enter the regime and start converging. Instead of a threshold, different country groupings are defined according to their current income levels, i.e. developed countries, Advanced Developing Countries (ADCs) and Other Developing Countries (ODCs), that take on different reduction objectives in terms of start year for convergence, convergence level and convergence year.
Main results of the scenario and policy analysis
Emissions
The global greenhouse gas emissions, including all Kyoto gasses, and the corresponding energy related CO2 emissions. Without any mitigation policies global greenhouse gas emissions and energy related CO2 emissions continue to increase towards 2050, with more than 50% and 80% compared to 2010 levels, respectively. The dotted lines represent the 2.9W/m2stabilization emissions pathway.
In DART and FAIR the transition from the baseline emissions to the 2.9 W/m2pathway is achieved via a carbon tax on emissions. These taxes are very similar up to 2045, beyond that the tax in DART rises further, as mitigation options in DART are limited after certain abatement levels, while FAIR allows for more radical technology changes that are especially available in the long run.
Energy system change and climate policy costs
Currently, the Chinese energy system is dominated by coal followed by oil. Other fuels such as natural gas and biomass play a less important role. The primary energy supply grows rapidly between 2010 and 2020 while at a slower speed between 2020 and 2050. Notable is that CEEPA shows a peak in primary energy supply by 2030 in the baseline, while the other models show continued growth. In all models, coal remains the most important fuel in the baseline scenario.
Direct and macro-economic costs of climate policy
The cost of climate policy is measured as abatement cost relative to baseline GDP levels in the energy system models (including FAIR) and as welfare changes (Hicks equivalent variation) relative to the baseline for the CGE models. The estimates for economic impacts between model classes are therefore not directly comparable. Furthermore, since the models include different technologies, sectors and energy sources it can be expected that abatement costs differ. Energy systems models focus on the competition between different technologies for meeting the demand for goods and services and derive cost estimates from detailed descriptions of the energy systems. In contrast, CGE models focus on the economy as a whole and include the interactions between the various sectors. They do not focus on direct costs, but on changes in economic production and consumption levels or welfare, which better captures the implications of overall structural changes and economy wide effects.
The economic impacts of the climate policy scenario for China and India.
While in all models (except CEEPA), costs are increasing over time there are large differences between the models. While the CGE models show moderate costs for a longer period, in the case of DART for the whole model period, costs increase to 2.5 or even 5% relative to GDP in the energy system models by 2040.
One explanation for the modest cost estimate in DART is that in DART the repercussions on the international fuel market are relatively large. The world (as a whole) consumes less fossil fuels in the climate policy scenario as compared to the baseline scenario, so that the (global) fossil fuel price declines. China, an importer of fossil fuels, can profit from this. The national models do not capture this effect.
Sensitivity analysis
In the sensitivity analysis it is tested if the model results are sensitive to alternative assumptions in GDP growth, the timing of emissions reductions, and to choices in the effort-sharing approach. We focus on the economic implications, since the qualitative nature of the energy results turn out to be relatively robust to changes in these assumptions.
The higher GDP growth assumptions imply that the models with a higher GDP growth scenario for China and India, while the rest of the world still follows the OECD baseline scenario. In this case China's economy is projected to grow on average about 6.2% per year between 2010 and 2050 compared to about 5% per year in our base case, while India's economy to grow on average about 7.9 % per year instead of about 6.8% per year. The altered growth assumption also leads to increases in CO2 emissions in the baseline.
In the climate policy case assumed throughout the main part of the analysis, countries implements their high Copenhagen Accord pledge for 2020, after which global emissions gradually decrease. Thus, resulting global 2020 emissions compared to 1990 are higher than in a cost-optimal pathway while the early action case represents a cost-optimal pathway. As a consequence while still aiming for the same 2.9 W/m2radiative forcing target in 2100, the mid- and long-term emissions levels (2025-2050) can be slightly higher.
As alternatives to the CDC base case, we consider two alternative regimes: a global uniform carbon tax approach and an alternative CDC approach. One of the most straightforward proposals is a globally uniform carbon tax, i.e. carbon tax is the same across all regions. Through the global equalization of marginal abatement costs this approach would ensure cost-effectiveness. However, a uniform carbon tax does not distinguish between developed and developing countries, hence leading to no compensation to developing countries.
In the alternative CDC case, further referred to as CDC with delayed participation, China and India start converging 5 years later than in the base case. To stay within the global emission pathway, developed countries have thus to reduce more and converge to 0.6 tCO2/cap - instead of 1.7 tCO2/cap in the base case. These results in a 90% emission reduction for developed countries in 2050 compared to 1990 while developing countries still converge to 1.7 tCO2/cap.
The results show that overall climate policy costs for China are more sensitive to the assumptions on the effort-sharing approaches than to assumptions for economic growth and the global emission pathway. Higher economic growth increases the cost of climate policy compared to the base case for all models, although considerably more for China-MARKAL and CEEPA than for FAIR and DART. Early action has a mixed impact on climate policy costs in the different models.
Finally, an effort-sharing approach with a uniform carbon taxes tends to be most detrimental for China in most models, except China-MARKAL. Also, the magnitude of the economic impact of a tax policy is very different across models. In the CDC with delayed participation, China does not adopt an emission cap in the context of the international climate negotiations until 2030 and for this reason costs are lower in all models compared to the base case. Besides DART, now also CEEPA shows a net benefit from such an effort-sharing approach.
Discussion and conclusion
Energy system change and cost estimations of climate regimes in the literature are often not directly comparable and differences in result are not always easy to explain (Van Ruijven et al., 2012a). The harmonization of the baseline and policy scenarios in this study improves the ability to understand the substantial differences in cost estimations across different model types and individual models. The analysis shows in particular that models with a similar structure (CGE vs. Energy system) lead to comparable results. Differences in model results can thus be explained in part by the general underlying assumptions of CGE versus energy system models.
CGE models are top-down models based on the economic structure and technologies of a reference year. Deviating from this equilibrium is possible through substituting energy inputs by additional capital inputs (technique effect) or by shifting demand to less carbon intensive sectors (composition effect), causing that a drop in energy intensity is important for abatement in these models. Both effects are driven by changes in relative prices. Furthermore, while substitution possibilities in the vicinity of the initial equilibrium are easy to achieve and therefore relatively cheap, deviating further from the initial situation is increasingly costly.
Only explicit modeling of alternative technologies makes it possible to change specific sectors more fundamentally. In our analysis, not all CGE models include low carbon technologies to the same extent and thus react differently to climate policy. We identify in particular a lack of technology alternatives for oil consuming sectors, most important the transport sector. Concerning cost estimates, CGE models take into account different kind of repercussions on other markets. Differences between the national CGE models and the global CGE model include modeling differences in representing repercussion on international fossil fuel markets and the impact of capital transfers on the exchange rate. For details see Weitzel et al (2012).
Generally, energy system models have more options for meeting energy demand than CGE models and more abatement takes place via carbon intensity reductions, i.e. through changes in the energy supply mix. Also, the inertia in the capital stock imply that small carbon taxes lead to little change in the short run in the energy system models. The timing of emission reductions is therefore more important for energy system models and leads compared to CGE models - to higher carbon taxes in the short run. For a more detailed discussion of this issue see Lucas et al. (in prep.). In the longer run, carbon taxes are lower than in the CGE models due to learning and explicit modeling of more abatement options a sharp increase would only be observable when the potential of relatively low cost abatement options is completely exhausted, which is not the case in our analysis. Concerning cost estimates energy system models are able to give only the direct cost of energy system changes.
For MARKAL models, the importance of energy efficiency improvements vis-vis carbon intensity improvements is about the same in relative terms for both countries. Also in TIMER, the carbon intensity improvement plays a major role but here the contribution is even more important in India than in China. For the reduction in carbon intensity, CCS stands out as the most important options across models. In addition, solar energy and small hydro are important in MARKAL-India, CCS is important in China MARKAL and modern biomass in TIMER.
In the main climate policy case assuming a least-cost implementation of international climate policy, CO2 emission levels for the different models in the year 2050 are in the range of -20% to +25% compared to 2005 emission levels in China and between +20 and +130% compared to 2005 emission levels in India. In 2010 China's CO2 emissions are almost three times higher than the Indian emissions, while in the baseline and policy scenarios in 2050 the CO2 emissions in China are about twice those in India. Demand for new capacity in India remains high towards 2050, while in China this demand levels off after 2030. As especially the energy-system models take account of the capital stock, this has a limiting effect on mitigation potential in China compared to India.
In our main policy case the costs of climate policy are larger for China than for India. In the energy system models the cumulative discounted costs as fraction of GDP are in the order of +0.4 to +1.8% for China and -0.7% to -1.7% for India, with positive numbers representing losses and negative numbers gains. In the CGE models, welfare losses range from +0.4% to -0.2% for China and from +1.1% to -4% for India. The main reason for these differences is that per capita emissions for China are already around the world average, while for India they are substantially lower. As the CDC approach implies a convergence of global per capita emissions, India is confronted with a lower reduction objective, and, as a result has a higher potential of selling reductions on the international carbon market generating revenues.
In general China is a seller on the short term, but becomes buyer on the long-term, while India is a seller over the whole 2010-2050 period. Only DART finds that China can benefit from international climate policy, mainly due to reduced costs of fossil fuels, although gains are small. For India, on the other hand, most models show an economic benefit of climate policies up to 2030/2040, mainly due to benefits from international emissions trading. For both India and China the models with a national focus tend to show more negative economic implications of climate policies than the global models. The reason for this is not trivial. For the CGE models, it can be explained in part by repercussions on international fuels market taken into account by the international DART model.
The sensitivity analyses reveal that both China and India benefit from delayed participation and both countries are more negatively affected by climate policies if a uniform carbon tax is assumed instead of a CDC approach. Although, China MARKAL is an exception here, showing that a uniform carbon tax approach results in the lowest costs. The reason behind this result is that in China MARKAL China is a net buyer of permits in the main CDC case. Finally, if higher economic growth rates for China and India are assumed, the model results point towards smaller benefits or larger costs (relative to GDP) of climate policies for both countries.
In conclusions, the results show that economic and energy implications for China and India vary across models. Decreased energy intensity is the most important abatement approach in the CGE models, while decreased carbon intensity is most important in the energy system models. Reliance on Coal without Carbon Capture and Storage (CCS) is significantly reduced in most models, while CCS is a central abatement technology in energy system models, as is renewable and nuclear energy. Concerning economic impacts China bears in general a higher cost than India, as China benefits less from emissions trading. Costs are also affected by changes in fossil fuel prices, currency depreciation from capital inflow from carbon trading and timing of emission reductions.
The multi-model analysis concludes that, compatible with the 2-degree target and global convergence of per-capita CO2 emissions, significant reductions are required in both China and India, implying huge changes in their energy systems.
There are large differences in the size of the energy system and the related CO2 emissions between China and India today, pertinent to the differences in economic activity. In the baseline scenario, the differences will decrease over time primarily due to higher economic growth in India. The current situation and the assumed future developments imply that there are differences as well as similarities in how India and China may be affected by climate policies on an aggregated national level.
In the main climate policy case Indian emissions are allowed to grow more than the Chinese emissions and still stay below their assigned amount, due to the per capita convergence rule and the higher population growth in India. Clear differences and similarities with respect to the actual consequences for the energy system of climate policy can be observed, not only among the two countries, but also among the two model types - CGE vs. energy system model. Energy efficiency improvements are important in the CGE models, while improvements in the carbon intensity, primarily through expansion of CCS and renewables, are more important for the energy system models. With respect to the carbon intensity improvements, CCS is more important in China, while renewables (including biomass) is more important in India.
The economic impacts of international climate policy either measured as direct mitigation costs in the energy system models or as welfare losses relative to baseline GDP in the CGE models - are generally larger in China than in India, while India can even gain. This is primarily the result of India benefiting more from international emissions trading. In general China is a seller on the short term, but becomes a buyer on the long-term, while India is a seller over the whole 2010-2050 period. Dependent on the model, costs are also affected by decreasing global fossil fuel prices, currency depreciation resulting from a net capital inflow from international carbon trading and timing of emission reductions. Furthermore, China and India benefit from delayed participation and both countries are more negatively affected by climate policies if a uniform carbon tax is assumed (no international emissions trading) instead of a CDC approach.
III.4 Work package 4
The main goal of WP 4 of the POEM project was to identify policies that enable participation of the emerging economies in the global carbon mitigation process and simultaneously achieve development and climate goals.
This WP has had two different tasks:
Task 4.1: Identifying/designing macro-socio-economic, energy and environment related domestic policies, and
Task 4.2: Designing institutional frameworks for international cooperation.
WP 4 built on the earlier POEM project work packages WP1 and WP2 and was also closely associated with WP3.
Following the review of macro-economic, energy and environment policies for the emerging economies that was carried out in WP1 and presented in the WP1 report, in this work package (WP4) different national policies (development, energy, environmental) in the emerging economies India and China were assessed from a climate perspective. Further, the alignment of national policies in the two countries was assessed in the perspective of international cooperation in a post-Kyoto regime.
In the project it was agreed that the basis of designing national policies and international co-operation framework would be based on the analysis of modeling results from WP3 for the 2 deg C global CO2 stabilization scenario.
Further, it was decided that the nature of international co-operation (institutional framework) would be assessed based on the agreed burden sharing regimes:
(i) uniform carbon tax with full participation, and
(ii) common but differentiated convergence.
A key focus of WP4 was policies having significant co-benefits vis-vis national development goals like energy security, energy access and air quality.
Some possible areas for exploring co-benefits in this context are:
i) Low Carbon Infrastructure,
ii) Water-Energy Nexus,
iii) Clean Energy,
iv) Energy Conservation,
v) Urban Planning and,
vi) Sustainable Agriculture.
The analysis of WP4 also stressed the immediate targets of 2020. As India and China have announced targets (emission intensities) for 2020 along with the policy road map to achieve those targets, it was useful to analyze domestic policies and international institutional cooperation keeping 2020 targets in mind. In a process building upon WP1, the WP4 report includes more detailed 5-year plan targets and its underlying relevance vis-vis the global climate targets and commitments.
There is some literature focusing on low carbon infrastructure and water-energy inter-linkages, but research work with regards to developing countries is scant. Quantifying the impacts of such a policy choice would help in making greater strides towards achieving global climate goals, particularly in the context of the 2 deg C stabilization target.
Primarily based on the model simulations carried out in WP3, Task 4.2 looked into the level of international cooperation needed to make India and China to comply with global climate combating efforts, without sacrificing the domestic priorities.
In the report, after a brief common introduction, India and China are treated in two different parts. Some key findings and conclusions are presented below, starting with India.
India
There has been a change in the structure of the Indian economy and in line with the nature of emerging economies; the share of service and industrial sector has been consistently growing over the past three decades with a corresponding decrease in the agriculture sector. Over the period, energy and environment policies in India have evolved; albeit slower compared to the challenges posed by rapidly growing economy. Environment policies have covered a wide-range of issues such as air and water pollution, waste management, and biodiversity conservation. However, the policies have traditionally been aimed at environmental protection and geared towards managing local issues.
The National Conservation Strategy and Policy Statement on Environment and Development, 1992, provided the basis for the integration of environmental considerations in the policies of various sectors. For example, the Policy Statement for Abatement of Pollution, 1992, stresses the prevention of pollution at the source based on the polluter pays' principle and The Forest Policy, 1988, highlights environmental protection through preservation and restoration of the ecological balance (a substantial increase of the forest cover in the country through afforestation programmes).
In 1991, liberalization of the economy triggered new policies such as focus on investment, deregulation and initiation of privatization. The energy sector was specifically targeted during the post-1991 period, with significant focus on expanding energy production opportunities (such as coal mining and oil exploration and production), use of alternative fuels (such as natural gas) and energy conversion capacities (such as power plants and oil refineries). Thus, energy policies in India started by laying emphasis on expanding energy production to match increasing demand. In the past decade, energy conservation and efficiency has received greater attention with the adoption of the Energy Conservation Act 2001 and Electricity Act 2003.
There are many supply-side oriented measures, in particular within the power sector, such as R&D in the area of ultra super critical boilers for coal-based thermal plants, use of integrated gasification combined-cycle (IGCC) technology to make coal-based power generation more efficient, the setting up of more combined cycle natural gas plants, promotion of nuclear energy through adoption of fast breeder and thorium based thermal reactor technology, adoption of high-voltage AC & DC transmission to reduce technical losses during transmission and distribution, setting up of small and large hydro power projects as a source of clean energy (apart from adaptation related benefits), promotion of renewable energy technologies such as biomass combustion and gasification based power generation, enhancement in the regulatory/tariff regimes to help mainstream renewable based sources in the national power system and promotion of renewable energy technologies for transportation (biofuels) and industrial fuels but also energy efficient technologies and appliances.
The Energy Conservation Act encompasses multitude of energy conservations measures and actions such as energy consumption standards for equipment and appliances; prohibited manufacture, sale, purchase and import of notified equipment and appliances not conforming to energy consumption standards; establishment and prescription of energy consumption norms and standards for designated consumers; and energy conservation building codes. Another major demand side measure is the Bachat Lamp Yojana (mass distribution of CFLsto help in reducing peak load demand and reduce electricity demand by 6 GW).
These measures have enabled the Indian energy landscape to shift to a more sustainable path, with the ultimate goal of off-setting demand additions on the supply side.
China
China has taken intensive actions to phase out old production capacity. The main aim of this is to contribute to improved energy efficiency but there are both climate and environmental benefits coupled to these measures. Small and old units have been phased out and substituted by larger, more modern technology; e.g. during 2005-2010 a total capacity of 72 GW of small thermal power units were closed, and the proportion of large-sized furnace in the iron and steel industry increased from 21% to 39%.
Other types of project whose objective is increased energy efficiency also have major positive climate implications. In order to implement the Outline of the Eleventh Five-year Plan for National Economic and Social Development and attain the mandatory goal of reducing energy consumption per unit of GDP by around 20%, the National Development and Reform Commission (NDRC) together with other departments, on the basis of the Mid- and Long-term Special Plan for Energy Conservation, formulated and issued in July 2006 the Opinion on Implementing 10 Key Projects of Energy Conservation in the Eleventh Five-year Plan Period. These ten key projects of energy conservation includes e.g. district combined heat and power generation; utilization of waste heat; petroleum conservation and substitution projects; introduction of electrical motors, energy conservation of buildings and 'green' lighting. The Implementation of the ten key projects has resulted in a total of 340 million TCEs saved.
The implementation of standards and labeling system for energy efficiency has improved the energy efficiency of terminal product, and up to date China has issued seven product lists subject to energy efficiency labeling management, covering 23 types of products in household electric appliance, industrial and lighting equipment etc.
The Chinese government attaches importance to the development of low-carbon energy, such as new and renewable energy, and has actively promoted a diversification of the Chinese energy mix e.g. through a number of financial, tax and price incentive policies in the area of renewable energy. Though the primary objective is rather energy security and diversification, the policies also have a strong climate impact.
From 2005 to 2010, the total installed capacity of hydropower plants was increased by 82 %, the total accumulative installed capacity of wind farms was increased by 30 times to 40 GW. The utilization level of solar resources was increased significantly and the total installed capacity of photovoltaic power generator sets was increased by 10 times and the total collector area of solar water heater was doubled. Biomass resources were developed, both as biomass power generation and production of transport biofuels. In addition to renewables, also the nuclear capacity has been expanding. From 2005 to 2010, the share of coal consumption was reduced from 71% to 68%, the share of natural gas consumption was increased from 2.6% to 4.4%, and the share of renewable and nuclear power increased from 6.8% to 8.6%.
The introduction of a carbon tax in China has been proposed by NDRC and the Ministry of Finance (MOF). One important aspect of the introduction of a carbon tax in China is the impact on GDP but also distribution effects are central. Therefore, the CEEPA model has been applied to simulate and compare different carbon tax schemes. The difference among the schemes lies in their different manners of levy, or different manners of revenue recycling.
The study concludes that, if no protections for households are considered, a carbon tax will reduce the living standard of both urban and rural households, and the negative impacts on rural households are greater than on urban households mainly because currently urban households obtain a much greater share in transfer payments.
Exemption of households from carbon tax has weak effects either on reducing the negative impacts on households, or on preventing the expansion of the urban-rural gap. Further, given the current social security system that obviously favors urban households, two measures can effectively reduce the extent of the urban-rural gap expansion caused by carbon taxation. These are a scheme using the carbon tax revenue to reduce the indirect tax and a scheme transferring the carbon tax revenues to households in proportion to their number. Given that the current social security system obviously favors urban households, the only scheme that can completely avoid the expansion of rural-urban gap is a scheme transferring carbon tax revenue to households in proportion to the population. But the long-term negative impacts on household living standard under this scheme are greater than with the no-protection scheme.
Given the current investment-driven economic growth pattern, the negative impacts on household income and welfare under each of the schemes will increase over time. In the long term, a scheme using the carbon tax revenue to reduce indirect tax has obviously smaller negative impacts on household living standard and economic growth than the other schemes. In addition, increasing the share that rural households obtain in government transfers helps to avoid the expansion of the urban-rural gap.
Based on this, some policy recommendations can be drawn. Given the current investment-driven economic growth pattern, it is necessary to introduce proper complementary measures for protecting economic growth and household life when designing a carbon tax scheme for China, and to use carbon tax revenues to reduce indirect tax is the best way to protect economic growth. Protections for households should also mainly rely on carbon tax revenue recycling.
A domestic carbon emission trading system is another possible important mitigation policy choice for China. The outline of the national twelfth five-year plan has addressed to establish an emissions trade market step by step and thus there is good reason to carry out studies on the possible impact of such a trade system in China. The CEEPA model was applied to assess the social-economic impacts of different allowance allocation methods for China.
Three ways to allocate primary permits have been assessed; allocation of the permits for free, not for free and a combination of free and not for free. Free allocation means that the primary permits are allocated for free to sectors or enterprises according to a given rule. Non-gratuitous allocation mainly includes auction and sale at fixed price. The mixed mechanism is a mix of auction and free allocation either simultaneously or time dependent.
Considering the macro-economy aspects of particular interest of the government when designing policies, this study identified gross national product (GDP), employment level (Lab), consumer price index (CPI), total consumption (Cons) and the government income (GovI) as the main objects to address when assessing the macro-economy impacts of different allocation approaches.
The result shows that all studied allocation approaches lead to negative social and economical impacts. The analysis shows that no one of the designed approaches can provide the best effects with regards to all addressed objectives, and that is there is no single optimal allocation approach.
Thus, a number of aspects should be considered in the design of the future allowance allocation approach when carrying out the emission trade system:
- From the perspective of comprehensiveness, the better choice is that permits are auctioned and the revenue is used to reduce the indirect taxes.
- If the protection of people's life in short term is of highest concern, permit auctioning combined with direct revenue transfer to household could be the core allocation mechanism, however it should not be the core allocation mechanism in the long term.
- If the function to raise the fiscal funds is emphasized, a mixed approach in which each sector can get a certain amount of free permit while the remaining needed permits are auctioned could be the core allocation mechanism, while it should not be the core allocation mechanism in long term.
III.5 Additional results
The project has generated a large amount of results of which many are yet to be analysed in detail. It has also led to a number of studies, which are based on the collaboration within the project and the project results but which have not been included in the main project reports. Abstracts, and to some extent conclusions from these four studies are presented below.
The POEM project has also already contributed to a number of other studies; e.g. v Ruijven et al 2011, Kainuma et al 2012, Krey et al 2012, v Ruijven et al 2012b; see the reference list.
1. Effects of international climate policy for India: Evidence from a national and global CGE model (published as Kiel Working Paper No. 1810, November 2012)
Matthias Weitzel, Joydeep Ghosh, Sonja Peterson, Basanta K. Pradhan
In order to reach the 2-degree target it is necessary to control CO2 emissions also in fast growing emerging economies such as India. The question is how the Indian economy would be affected by e.g. including the country into an international climate regime. Existing analyses with either a global model or a single country computable general equilibrium model miss important aspects such as distributional issues or international repercussions. By soft-linking models of these two classes, we provide a more detailed view on these issues. In particular, we analyze different options of transferring revenues from domestic carbon taxes and international transfers to different household types and how different assumptions on exchange rates affect transfer payments. We also show effects stemming from international price repercussions.
2. Energy system changes for China and India under different climate stabilization pathways
Paul Lucas, P.R. Shukla, Wenying Chen, Subash Dhar, Amir Bazaz, Bas J. van Ruijven, Michel M.G.J. den Elzen and Detlef P. van Vuuren
In order to limit global mean temperature increase to the UN climate goal of 2oC, deep reductions in greenhouse gas emissions are needed. We compare abatement costs and changes in the energy systems of China and India derived from three energy system models under two global emission pathways that are in line with a medium likelihood of meeting 2oC: a least-cost pathway and a pathway that postpones mitigation action by implementing the Copenhagen Accord pledges for 2020. Both pathways have similar cumulative CO2-eq emissions for 2010-2050. The analysis shows that postponing mitigation action increases cumulative mitigation costs for both China and India. Furthermore, postponing mitigation action increases the dependence on fossil fuels on the short-term, but decreases dependence on the longer term due to the deeper required emission cuts to compensate for the short-term emission growth. Differences between India and China relate to different periods of rapid economic change and capital stock turnover of power production capacity. China still has a significant share of conventional coal power plant in the mitigation scenarios in 2050 (possible combined with CCS), while Indian power production is almost CO2-neutral by 2050. It should be noted that climate policy also interferes with other energy-related issues that are important in both India and China. It may induce risks, such as increased indoor air pollution, but can also synergize with energy security and urban air pollution. These relations are important to take into account when designing national policies.
3. The impact of carbon taxes on growth, emissions and welfare in India: A CGE analysis
Basanta K Pradhan and Joydeep Ghosh
The main objective of this paper was to analyze the impact of two post-Kyoto climate policy regimes on GDP growth, CO2 emissions, and welfare in India. The first regime is a global carbon tax (CT) while the second regime is based on emission trading permits where the distribution of permits is based on the Common but Differentiated Convergence (CDC) approach. Both climate policy regimes are consistent with the objective of limiting the increase in average global temperature below 2°C over the long term. The results suggest that assumptions about the climate policy regime, model closure and values of substitution elasticities (between value added and energy) play an important role in determining the effects of climate policies.
4. Carbon taxes vs productivity shocks: A comparative analysis of the costs in a CGE framework for India
Basanta K Pradhan and Joydeep Ghosh
The main objective of this paper was to compare the costs of climate policy scenarios with those of probable climate change induced agricultural productivity shocks using a recursive dynamic CGE model in case of India. The social cost of carbon, in terms of agricultural productivity loss, is estimated to be about 17 and 14 percent of GDP, using zero and 3 percent discount rates, respectively. In comparison the costs of climate policy regimes are estimated at 3 and 2 percent, using similar discount rates, respectively. There is a strong case for the adoption of mitigation policies by India, along with other countries, to reduce the level of CO2 emissions in order to protect the agriculture sector from climate change induced productivity shocks. Besides, revenues generated from the implementation of climate policies could be a means to support the adoption of energy efficient technologies and augment capital formation in the economy.
III.6 Final remarks
The policy and modeling analysis was done in a top-down fashion, starting with a global burden-sharing agreement and the global models and then concluding with the impact at the national levels. A bottom-up approach, starting with national policies and objectives could have been chosen instead. These two general approaches were considered and the top-down approach was chosen because the analyzed scenarios were strongly supported by the Chinese and Indian project partners and are broadly in line with national Chinese and Indian proposals. The choice of the top-down approach was also the result of a decision to be consistent with the long-term 2-degree target. With a bottom-up approach we would not have had this guarantee. In some sense such global scenarios are also the natural starting point for using the newly developed modeling framework, which was at the heart of the POEM project. Yet, we see the importance of bottom-up approaches and this is strongly recommended for any future work. Such an approach could then also focus on issues like green financing and CDM and could possibly lead to a strong involvement of national policy makers in India and China at an early stage of the project.
Potential Impact:
The expected impact should, quoting the work programme of the topic ENV-2008.1.1.6.3 be 'to provide a portfolio of policy options for emerging economies to engage in climate change protection measures under a post-2012 regime. ' The project is not only presenting a portfolio of policy options under a post-2012 regime but also attempting to quantify these policy options possible impact on the economy and to some extent also on other societal sectors in terms of socio-economic development. The project is thus obviously highly policy relevant since the main outcome of the project is to contribute to support for policy makers.
The work has targeted India and China since these two countries are the emerging giants and any global climate agreement requires their participation. The work is thus country specific for these two countries and is addressing details on a sectoral level specific for these two countries.L
Major dissemination events
As planned, in each of the countries India and China one major national workshop has been organised by the country partners:
- POEM workshop in New Delhi, Thursday, September 6, 2012 India International Center (IIC), New Delhi.
- POEM workshop in Beijing, Tuesday, September 25, 2012, at the Hotel Nikko New Century Beijing, Haidian District, Beijing.
List of Websites:
http://www.chalmers.se/ee/poem-en.