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Options and Instruments for a Deep Cut in CO2 Emissions: Carbon Dioxide Capture or Renewables, Taxes or Subsidies?

Reyer Gerlagh and Bob van der Zwaan

Year: 2006
Volume: Volume 27
Number: Number 3
DOI: 10.5547/ISSN0195-6574-EJ-Vol27-No3-3
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Abstract:
This paper compares both the main physical options and the principal policy instruments to realize a deep cut in carbon dioxide emissions necessary to control global climate change. A top-down energy-economy model is used that has three emission reduction options: energy savings, a transition towards less carbon-intensive or non-carbon energy resources, and the use of carbon dioxide capture and storage technology. Five policy instruments - carbon taxes, fossil fuel taxes, non-carbon (renewable) energy subsidies, a portfolio standard for the carbon intensity of energy production, and a portfolio standard for the use of non-carbon (renewable) energy resources - are compared in terms of costs, efficiency and their impact on the composition of the energy supply system. One of our main conclusions is that a carbon intensity portfolio standard, involving the recycling of carbon taxes to support renewables deployment, is the most cost-efficient way to address the problem of global climate change. A comprehensive introduction of the capture and storage of carbon dioxide would contribute to reducing the costs of climate change control, but would not obviate the large-scale need for renewables.



Inter-temporal R&D and capital investment portfolios for the electricity industry’s low carbon future

Nidhi R. Santen, Mort D. Webster, David Popp, and Ignacio Pérez-Arriaga

Year: 2017
Volume: Volume 38
Number: Number 6
DOI: https://doi.org/10.5547/01956574.38.6.nsan
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Abstract:
A pressing question facing policy makers today in developing a long-term strategy to manage carbon emissions from the electric power sector is how to appropriately balance investment in R&D for driving innovation in emerging low-and zero-carbon technologies with investment in commercially available technologies for meeting existing energy needs. Likewise, policy makers need to determine how to allocate limited funding across multiple technologies. Unfortunately, existing modeling tools to study these questions lack a realistic representation of electric power system operations, the innovation process, or both. In this paper, we present a new modeling framework for long-term R&D and electricity generation capacity planning that combines an economic representation of endogenous non-linear technical change with a detailed representation of the power system. The model captures the complementary nature of technologies in the power sector; physical integration constraints of the system; and the opportunity to build new knowledge capital as a non-linear function of R&D and accumulated knowledge, reflective of the diminishing marginal returns to research inherent in the energy innovation process. Through a series of numerical experiments and sensitivity analyses - with and without carbon policy - we show how using frameworks that do not incorporate these features can over-or under-estimate the value of different emerging technologies, and potentially misrepresent the cost-effectiveness of R&D opportunities.





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