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The GLIMPSE Project: A decision support tool for air quality management
Citation:
Loughlin, Dan, Chris Nolte, C. Lenox, T. Wu, A. Kreider, S. Wong, S. Babaee, P. Destephano, F. Jia, S. Simm, S. Smith, Y. Ou, AND M. Weber. The GLIMPSE Project: A decision support tool for air quality management. 19th Annual CMAS Conference, Chapel Hill, North Carolina, October 26 - 30, 2020.
Impact/Purpose:
State environmental decision makers may be tasked with developing long-term plans, such as for achieving air quality and climate goals. EPA's Office of Research and Development is developing a system for helping support such planning. This system, the GCAM Long-term Interactive Multi-Pollutant Scenario Evaluator (GLIMPSE), allows decision makers and analysts to understand future emission trends for various scenarios and test various management strategies in a virtual environment. GLIMPSE will even allow users to define emission reduction goals, and the system will then identify cost-effective strategies for achieving those goals. The model used within GLIMPSE is the Global Change Analysis Model (GCAM). In this presentation, we will describe GLIMPSE development, applications, and plans for the future.
Description:
The U.S. EPA is developing a decision support tool for air quality management called GLIMPSE, an acronym for GCAM Long-term Interactive Multi-Pollutant Scenario Evaluator. GLIMPSE is built upon the Global Change Analysis Model (GCAM), an open source human-earth system model whose development is led by Pacific Northwest National Laboratory. GCAM includes representations of the energy, water, agriculture, land use, and climate systems, simulating their co-evolution through 2100. The model has a relatively high level of technological detail within the energy system, including the electric sector, industry, buildings, and onroad and nonroad transportation. Technologies compete against each other for market share based on their relative costs and other factors. Emissions associated with the resulting technological pathway are reported. GLIMPSE works with GCAM and with a variant of GCAM with state-level resolution (GCAM-USA). GCAM-USA includes representations of major national environmental and energy policies, including the Cross-State Air Pollution Rule, the Corporate Average Fuel Economy standards, New Source Performance Standards for air pollutants, and the Tier 3 engine and fuel emission standards. It also includes many state and regional policies, including the Regional Greenhouse Gas Initiative and Zero Emission Vehicle targets. From an air quality planning perspective, GLIMPSE has a number of potential uses. For example, GLIMPSE can estimate emissions for specific scenarios. For example, one could examine future air pollutant and greenhouse gas (GHG) emissions under baseline assumptions as well as alternative assumptions about population growth, economic growth, technology change, and climate change. With its state-level resolution and coverage of both air pollutants and greenhouse gas emissions, GLIMPSE also provides states with a tool for helping develop and evaluate policy options. For example, if states have identified specific policy measures, such as specifying energy efficiency and renewable energy targets, GLIMPSE can be used to quantify the resulting impacts on emissions. GLIMPSE also supports an optimization capability. Emission reduction targets can be specified by the user, then GLIMPSE automates the selection of control measures for meeting those targets at low cost. In this presentation, we will discuss the capabilities, computational and user requirements, applications to date, and plans for making GLIMPSE available with training in 2021.
