Citation:

Destephano, P., S. Smith, Chris Nolte, AND Dan Loughlin. A method for identifying challenges to air quality management and developing robust management strategies. 19th Annual CMAS Conference, Chapel Hill, North Carolina, October 26 - 30, 2020.

Impact/Purpose:

More than 130 million people in the U.S. live in areas that do not attain one or more of the National Ambient Air Quality Standards. State environmental agencies face the challenge of determining how to achieve these standards and maintain good air quality into the future. The planning process can be complicated because of the many factors that affect future emissions, including population growth, economic transformation, climate change, technology change, adoption of climate and energy policies, and human choices and behaviors. The long-term planning process would benefit from tools that allow planners to more fully understand the challenges and opportunities associated with these factors. Such tools could also provide a "computational laboratory" for evaluating the impacts of potential air quality management strategies.

Description:

In the U.S., more than 130 million people live in areas that do not meet the National Ambient Air Quality Standards. State environmental agencies face the challenge of determining how to achieve these standards and maintain good air quality into the future while simultaneously working to meet greenhouse gas reduction targets and ensure reliable and affordable energy. Identifying strategies for meeting air, climate, and energy goals over the long term is difficult given the uncertainties inherent in the future. Predictive modeling generally extrapolates from current trends; however, as modelers look farther in the future, these trends are less certain. Challenges may arise from new and emerging sources of emissions or increasing demands for energy that are driven by population growth, economic transformation, and a changing climate. Consumer behaviors and attitudes can also result in challenges, particularly if trends of increasing house size, vehicle mass, and commute distances continue. In this project, we are using a human-earth systems model, GCAM-USA. We will be conducting a combinatorial analysis, examining combinations of different assumptions about population, economic transformation, climate impacts, consumer behavior, and technology change. These results of hundreds of GCAM-USA runs will then be examined, identifying which combinations of assumptions result in challenges to air, climate, and energy goals. In a second phase of the project, we will repeat the initial analysis with combinations of policies that have been identified by stakeholders at state agencies. These include a range of policies directed at transportation, renewable energy, and energy efficiency. Evaluating these policies across a large set of scenarios will provide insights regarding their relative efficacy over wide-ranging conditions. This information can help state agencies refine policies in the face of emerging trends and develop policies that are robust to an array of future scenarios. This presentation will detail the methodology outlined above, discuss lessons learned through stakeholder interactions, and provide preliminary results from model runs exploring a subset of the scenario dimensions.

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