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Carbon tax scenarios for China and India: exploring politically feasible mitigation goals

Abstract

China and India are two Asian giants and global players. They both have large populations and booming economies hungry for energy. China and India will therefore play a major role in shaping future global emissions of greenhouse gases. This paper assesses emissions reductions targets that can be realistically adopted by China and India in the following rounds of climate negotiations. The analysis is based on a business-as-usual (BaU) scenario and on four carbon tax scenarios until 2050, developed using the WITCH model. Results show that the lowest level of taxation (starting at 10$ per tonne of CO2 in 2020) would reduce emissions in 2050 by 25% in China and by 30% in India, with respect to the BaU, at little cost. The marginal abatement cost curves are, however, steep and a higher level of taxation brings little emissions reductions at high costs. In China, only the two highest tax levels reduce emissions in 2050 below the 2005 level. In India, emissions in 2050 are higher than in 2005 even with the highest tax. Therefore, the pledge of the G8 and the MEF of reducing global emissions by 50% in 2050—with high-income countries cutting them by 80% and low-income ones by 25–30%—appears extremely costly and therefore unrealistic. A more sensible international climate architecture would push for the introduction of a moderate control of emissions in China and India and would avoid overly ambitious targets.

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Notes

  1. 1.

    According to Wikipedia, the credit of coining the now popular term goes to Jairam Ramesh, an Indian politician.

  2. 2.

    Recently, the IAM community has gathered to discuss long-term energy and emissions scenarios for Asian economies in the Asia Modelling Exercise. However, a whole set of new scenarios will not be published until the end of 2011.

  3. 3.

    By combining the economy, energy, ecosystems and climate, IAMs allow the creation of scenarios on future GHG emissions and the study of transition pathways towards a low-carbon world. For a discussion of key characteristics and the use of IAMs see, among others, Dowlatabadi (1995), Ackerman et al. (2010) and Weyant (2010).

  4. 4.

    For a comparison of China and OECD economies see Carraro and Massetti (2011).

  5. 5.

    Using Purchasing Power Parities (PPP) instead of Market Exchange Rates (MER) to compare GDPs internationally would narrow the income gap between poor and rich countries.

  6. 6.

    For a detailed analysis of energy intensity trends in China and for a review of policies to increase energy efficiency see Levine and Aden (2008), Levine et al. (2009), Zhou et al. (2010).

  7. 7.

    Wood fuels are the cause of no net carbon emissions. When they are replaced with fossil fuels the carbon content of energy increases considerably.

  8. 8.

    Still 80% of cooking in rural India comes from fuelwood; in 2030, this share is expected to decline to about 55% (IEA 2008).

  9. 9.

    The emissions tax is obtained by solving the model imposing a global pattern of emissions that is consistent with the 2100 concentration target and allowing countries to trade emissions allowances internationally to equate marginal abatement costs. We then run the model imposing the carbon price as a tax, thus avoiding complex distribution issues. This concentration target is equivalent to a temperature increase of 2.5°C above the pre-industrial level with median probability in 2100, well above the stated objective of keeping temperature increase below 2°C.

  10. 10.

    WITCH is a perfect foresight model. The level of future taxation influences present decisions. Therefore, it is optimal to smooth the transition to a regime of emissions taxes in WITCH. This explains why emissions decline with respect to the BaU before 2020 in Figs. 7 and 8. Equivalently, the high level of taxes in 2050 affects investment decisions in earlier years.

  11. 11.

    The reference year for the emissions cuts is not clear. We use here 2005. An alternative would be 1990. Using the BaU as a reference would imply emissions levels not coherent with the 2°C target.

  12. 12.

    If the −80% target is valid for Annex I countries, Non-Annex I countries must reduce emissions by 22%. If the −80% target is valid only for G8 countries, Non Annex I countries must reduce emissions more.

Abbreviations

BaU:

business-as-usual

COP:

Conference of parties

EIA:

Energy information administration

EU27:

The 27 member countries of the European union

G8:

The group of eight

GDP:

Gross domestic product

GHG:

Greenhouse gas

IAM:

Integrated assessment model

IEA:

International energy agency

MACCs:

Marginal abatement cost curves

MEF:

Major economies forum

OECD:

Organization for economic cooperation and development

TPES:

Total primary energy supply

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Acknowledgments

This paper is part of the research work being carried out by the Sustainable Development Programme at the Fondazione Eni Enrico Mattei and by the Climate Impacts and Policy Division of the Euro-Mediterranean Centre on Climate Change. Financial support under the Climate Policy Outreach project, from the European Community’s Seventh Framework Programme (FP7/2007-2013) under grant agreement n° 244766 - PASHMINA (PAradigm SHifts Modelling and INnovative Approaches) and the EC2 Europe-China Clean Energy Centre is gratefully acknowledged. A previous version of this paper was published as FEEM Working Paper No. 24.2011 in March 2011, with the title ‘A Tale of Two Countries: Emissions Scenarios for China and India’.

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Massetti, E. Carbon tax scenarios for China and India: exploring politically feasible mitigation goals. Int Environ Agreements 11, 209 (2011). https://doi.org/10.1007/s10784-011-9157-7

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Keywords

  • Climate change mitigation
  • China
  • India
  • Energy efficiency
  • Energy and development