Published May 2016 | Version v1
Journal article

Emissions reduction scenarios in the Argentinean Energy Sector

  • 1. Fundación Bariloche, Energy Program, Bariloche (Argentina)
  • 2. Energy research Centre of the Netherlands, Policy Studies, Amsterdam (Netherlands)
  • 3. Pacific Northwest National Laboratories, Joint Global Change Research Institute, College Park MD (United States)

Description

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. - Highlights: • A scenario that incorporates mitigation measures considered most feasible by relevant Argentinean stakeholders generates a CO2e emissions reduction of 16% compared to BAU. • This scenario has a total additional cumulative cost of $22.8 Billion (2005 USD) along the period 2010–2050 • A high CO2 price scenario in LEAP generates a CO2e emissions reduction of 11.3% compared to the baseline • A high CO2 price scenario in TIAM-ECN and GCAM generates reductions in CO2e emissions of 37% and 94% respectively. The main reason for this difference between models includes varying assumptions about technology cost and availability, CO2 storage capacity, and the ability to import bioenergy. • Under climate policy, natural gas remains an important part of the energy mix, and although models agree that aggregate and proportional fossil fuel use declines, predictions vary as to the extent coal, nuclear and renewable energy play a role moving forward.

Availability note (English)

Available from http://dx.doi.org/10.1016/j.eneco.2015.03.021

Additional details

Identifiers

DOI
10.1016/j.eneco.2015.03.021;
PII
S0140-9883(15)00113-9;

Publishing Information

Journal Title
Energy Economics
Journal Volume
56
Journal Page Range
p. 552-563
ISSN
0140-9883
CODEN
EECODR

Optional Information

Copyright
Copyright (c) 2016 Elsevier Science B.V., Amsterdam, The Netherlands, All rights reserved.