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Estimating Environmental Co-benefits of U.S. GHG Reduction Pathways Using the GCAM-USA Integrated Assessment Model
Citation:
Ou, Y., W. Shi, Dan Loughlin, Chris Nolte, S. Smith, C. Ledna, AND J. West. Estimating Environmental Co-benefits of U.S. GHG Reduction Pathways Using the GCAM-USA Integrated Assessment Model. 2016 CMAS Conference, Chapel Hill, NC, October 24 - 26, 2016.
Impact/Purpose:
This poster will describe ongoing research being done at ORD using the GCAM-USA Integrated Assessment Model to estimate environmental co-benefits of alternate greenhouse gas emission reduction pathways for the U.S. The purpose of the meeting is scientific communication and exchange.
Description:
Previous studies have shown that mitigating climate change through curbing greenhouse gas (GHG) emissions can bring about substantial environmental co-benefits, such as for air quality and reductions in energy-related water demand. A variety of pathways are available for reducing GHG emissions, however, including a transition to low-carbon fuels, carbon capture technologies, renewable energy, and energy efficiency and conservation. These pathways can have very different environmental co-benefits. The cost and reliability of energy may also differ. Development of a sustainable climate mitigation strategy thus benefits from simultaneous consideration of climate change, environmental, and energy objectives. Integrated Assessment Models (IAMs) have the potential to support coordinated climate, environmental, and energy decision making. Here we illustrate how the Global Change Assessment Model-USA (GCAM-USA) – an IAM with state-level resolution for the U.S. – can be applied to explore the environmental co-benefits of alternative GHG reduction pathways. We compare an idealized mitigation pathway that focuses on nuclear energy and carbon capture with another that focuses on renewable energy to 2050. Environmental metrics such as emissions of multiple air pollutants and energy-related water demands are evaluated for various GHG mitigation targets. The resulting pollutant projections could be used for more detailed emission and air quality modeling through SMOKE and CMAQ.
