UC San Diego

Improved understanding of the physical impacts to the climate caused by anthropogenic emissions has led to an increased focus on the role of policy on limiting mitigating the cause and the impacts of climate change. The emissions trajectory that society takes will play a major role in determining a wide variety of climate impacts from health to economic growth. This dissertation explores how idealized modeling can be used to inform the potential outcomes of the policies meant to mitigate the negative impacts of climate change and optimize the benefits of emission reduction. Chapter 1 explores the potential trade-offs between increased temperatures and reduced health impacts of considering aerosol emissions in international climate policy. Using an idealized model, it is possible to demonstrate that both health and temperature benefits can result from considering either health or temperature separately. Chapter 2 interrogates whether climate policy in the United States can be used to reduce existing racial inequities in air pollution exposure. The modeling shows that prioritizing by exclusively income or cost in national policy would result in worsening inequities, but that prioritizing by race explicitly has the opposite effect. Using a set of more realistic air quality simulations with randomized emission reduction, it appears that the transportation has a unique potential for air quality equity improvements. Lastly, Chapter 3 focuses on statistical models that use natural variation in annual weather to predict how climate will influence human outcomes. Using an idealized outcome variable and real data of global gross domestic product, it is possible to demonstrate that imperfect measurement networks and the mean shift in climate both work to underestimate future climate impacts.