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GLIMPSE: Decision support for long-term air quality planning
Citation:
Loughlin, Dan, Chris Nolte, C. Lenox, T. Wu, W. Shi, Y. Ou, S. Babaee, AND S. Smith. GLIMPSE: Decision support for long-term air quality planning. 2018 Joint International Conference on ABaCAS and CMAS-Asia-Pacific, Being, CHINA, May 21 - 23, 2018.
Impact/Purpose:
The GLIMPSE decision support tool helps air quality managers identify air pollutant emissions for various scenarios of the future through mid-century. Thus, GLIMPSE allows the managers to identify, test and compare candidate management strategies. While GLIMPSE has been tailored to the U.S., it could also potentially be modified for application in China. Its features are particularly of use to the Chinese audience given China's air quality challenges.
Description:
The United States Environmental Protection Agency is developing the GLIMPSE decision support system for air quality management. GLIMPSE (GCAM-based Long-term Interactive Multi-Pollutant Scenario Evaluator) allows air quality managers to: (i) evaluate the emissions impacts of various assumptions about population growth and migration, economic growth and transformation, technology change and adoption, and environmental and energy policies, and (ii) automate the identification of cost-effective control strategies for meeting single- or multi-pollutant emission reduction goals. These strategies can include control technologies, renewable energy, energy efficiency, and conservation measures. The computational engine for GLIMPSE is the Global Change Assessment Model with US state-level resolution, or GCAM-USA. In this presentation, an overview of GLIMPSE and GCAM-USA will be provided. The potential linkage of GLIMPSE to the Air Benefit and Cost Assessment System (ABaCAS) also will be described. Two illustrative applications will be presented. In one example, the air pollutant emission implications of two population growth scenarios are explored. The results suggest that emissions would increase under higher population growth. However, this increase would differ by pollutant species, sector, and state. Existing regulations would drive some of these differences, with pollutant caps proving effective in avoiding emission increases. In the second example, the air quality implications of the Regional Greenhouse Gas Initiate (RGGI) are evaluated. The results indicate that RGGI would yield air pollutant emission reduction that could lead to billions of dollars of future health benefits to the region.