Projecting state-level air pollutant emissions using an integrated assessment model: GCAM-USA

Wenjing Shi, Yang Ou, Steven J. Smith, Catherine M. Ledna, Christopher G. Nolte and Daniel H. Loughlin

Applied Energy, 2017, vol. 208, issue C, No S0306261917314125, 521 pages

Abstract: Integrated Assessment Models (IAMs) characterize the interactions among human and earth systems. IAMs typically have been applied to investigate future energy, land use, and emission pathways at global to continental scales. Recent directions in IAM development include enhanced technological detail, greater spatial and temporal resolution, and the inclusion of air pollutant emissions. These developments expand the potential applications of IAMs to include support for air quality management and for coordinated environmental, climate, and energy planning. Furthermore, these IAMs could help decision makers more fully understand tradeoffs and synergies among policy goals, identify important cross-sector interactions, and, via scenarios, consider uncertainties in factors such as population and economic growth, technology development, human behavior, and climate change. A version of the Global Change Assessment Model with U.S. state-level resolution (GCAM-USA) is presented that incorporates U.S.-specific emission factors, pollutant controls, and air quality and energy regulations. Resulting air pollutant emission outputs are compared to U.S. Environmental Protection Agency 2011 and projected inventories. A Quality Metric is used to quantify GCAM-USA performance for several pollutants at the sectoral and state levels. This information provides insights into the types of applications for which GCAM-USA is currently well suited and highlights where additional refinement may be warranted. While this analysis is specific to the U.S., the results indicate more generally the importance of enhanced spatial resolution and of considering national and sub-national regulatory constraints within IAMs.

Keywords: Integrated assessment model; Energy system; Emissions projection; Air pollutant; Air quality; Scenario (search for similar items in EconPapers)
Date: 2017
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DOI: 10.1016/j.apenergy.2017.09.122

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