Air Pollution, Health and Economic Impacts of Global Change Policy and Future Technologies: An Integrated Model Analysis
The MIT Integrated Global Systems Model (IGSM), coupled with MIT/NCAR version of the Community Atmospheric Model version 3 (CAM3) of NCAR’s Community Climate System Model version (CCSM), will be used to assess the local air pollution impacts of 1) emerging vehicle technologies such as plug-in hybrid electric vehicles and biofuels and 2) air pollution and climate policies, separately and in combination. We will assess the impacts of technologies and policy choices on human health and the economic benefits and costs of these policies and technologies.
Urban areas will be simulated with a reduced-form (polynomial-fit) metamodel, based on the CAMx model, enabling computationally-efficient assessment of impacts for a broad range of U.S. cities and policy and technology developments. The metamodel will be validated using a detailed case study of the Northeast U.S. using the full CAMx model. Impacts to human health and the economy will be assessed using the MIT Emissions Prediction and Policy Analysis (EPPA) model and its extensions to deal with health effects from O3 and PM. These impacts will then feed back into the economy, affecting emissions, thus allowing a fully-consistent characterization of air pollution impacts under global change scenarios.
Outcomes of this research will include:
- Developing modeling capability to facilitate better understanding of the interplay between human activities, air pollution and regulatory requirements, climate policy, human health, and large-scale economic factors at local to global scales in approximately 2050.
- Providing insights to the air quality community about strategies for air quality regulation and climate change, and quantify potential human health benefits.
- Providing insights to the air quality community about the potential for societal changes, especially collective choices about personal vehicle technologies and fuels, to impact air quality, and identify potential unintended consequences of these large-scale changes.
Sponsor Award Number: RD-83427901
Source Category: Federal Research Grant
Principal Investigators: Noelle Selin and Mort Webster