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Emissions reduction scenarios in the Argentinean Energy Sector

Author

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  • Di Sbroiavacca, Nicolás
  • Nadal, Gustavo
  • Lallana, Francisco
  • Falzon, James
  • Calvin, Katherine

Abstract

In this paper the LEAP, TIAM-ECN, and GCAM models were applied to evaluate the impact of a variety of climate change control policies (including carbon pricing and emission constraints relative to a base year) on primary energy consumption, final energy consumption, electricity sector development, and CO2 emission savings of the energy sector in Argentina over the 2010–2050 period. The LEAP model results indicate that if Argentina fully implements the most feasible mitigation measures currently under consideration by official bodies and key academic institutions on energy supply and demand, such as the ProBiomass program, a cumulative incremental economic cost of 22.8 billion US$(2005) to 2050 is expected, resulting in a 16% reduction in GHG emissions compared to a business-as-usual scenario. These measures also bring economic co-benefits, such as a reduction of energy imports improving the balance of trade. A Low CO2 price scenario in LEAP results in the replacement of coal by nuclear and wind energy in electricity expansion. A High CO2 price leverages additional investments in hydropower. By way of cross-model comparison with the TIAM-ECN and GCAM global integrated assessment models, significant variation in projected emissions reductions in the carbon price scenarios was observed, which illustrates the inherent uncertainties associated with such long-term projections. These models predict approximately 37% and 94% reductions under the High CO2 price scenario, respectively. By comparison, the LEAP model, using an approach based on the assessment of a limited set of mitigation options, predicts an 11.3% reduction. The main reasons for this difference include varying assumptions about technology cost and availability, CO2 storage capacity, and the ability to import bioenergy. An emission cap scenario (2050 emissions 20% lower than 2010 emissions) is feasible by including such measures as CCS and Bio CCS, but at a significant cost. In terms of technology pathways, the models agree that fossil fuels, in particular natural gas, will remain an important part of the electricity mix in the core baseline scenario. According to the models there is agreement that the introduction of a carbon price will lead to a decline in absolute and relative shares of aggregate fossil fuel generation. However, predictions vary as to the extent to which coal, nuclear and renewable energy play a role.

Suggested Citation

  • Di Sbroiavacca, Nicolás & Nadal, Gustavo & Lallana, Francisco & Falzon, James & Calvin, Katherine, 2016. "Emissions reduction scenarios in the Argentinean Energy Sector," Energy Economics, Elsevier, vol. 56(C), pages 552-563.
  • Handle: RePEc:eee:eneeco:v:56:y:2016:i:c:p:552-563
    DOI: 10.1016/j.eneco.2015.03.021
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    1. Clarke, Leon & McFarland, James & Octaviano, Claudia & van Ruijven, Bas & Beach, Robert & Daenzer, Kathryn & Herreras Martínez, Sara & Lucena, André F.P. & Kitous, Alban & Labriet, Maryse & Loboguerre, 2016. "Long-term abatement potential and current policy trajectories in Latin American countries," Energy Economics, Elsevier, vol. 56(C), pages 513-525.
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    11. Jhonathan Fernandes Torres Souza & Sergio Almeida Pacca, 2019. "How far can low-carbon energy scenarios reach based on proven technologies?," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 24(5), pages 687-705, June.
    12. Postic, Sebastien & Selosse, Sandrine & Maïzi, Nadia, 2017. "Energy contribution to Latin American INDCs: Analyzing sub-regional trends with a TIMES model," Energy Policy, Elsevier, vol. 101(C), pages 170-184.
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    More about this item

    Keywords

    Argentina; Energy sector; Mitigation measures; CO2 control policies;
    All these keywords.

    JEL classification:

    • Q47 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy Forecasting
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • Q58 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environmental Economics: Government Policy
    • O21 - Economic Development, Innovation, Technological Change, and Growth - - Development Planning and Policy - - - Planning Models; Planning Policy
    • O5 - Economic Development, Innovation, Technological Change, and Growth - - Economywide Country Studies

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