Social and Earth System Feedbacks: Air Quality and Climate
As states and countries commit to large-scale climate policies, it is important to consider the convergence of the impact of these climate policies on air quality, as well as the impact of air quality and climate on these policies. Using a combination of chemical transport models, mathematical tools, and social impact assessment tools, I research the intersection of the social and earth sciences in regards to climate and air quality. I aim for all of my work to be translated into tools or solutions that can aid in policy-making and solutions for the joint issue of climate and air quality, with a particular focus on how we can incorporate environmental justice and holistic sustainable development goals into our policy approaches.
Spatial Variability in Social Feedbacks on the Earth System: This work merges energy grid models, often found in the social and energy research space, with chemical transport models, used in the earth sciences, to understand the impact of energy policy on air quality and climate. I’ve assisted in the development of US-EGO, an EGU specific energy grid optimization tool that allows for construction of policy scenarios in the United States, and subsequent chemical transport modelling of the emission changes and their impact on air quality. This framework is an improvement on the typical format of linear regressions that are used to assess changes after they occur, and allows us to think about future energy policy and its impacts at a local scale. My current work investigates the impact that nuclear power plant shut-downs would have on air quality and climate in the United States.
Intersection between Social and Earth System Responses to Coal Power Plants across Space and Time Making use of a number of mathematical tools, I simplify our ability to understand the earth system responses to Black Carbon, CO$_2$, and Mercury. This work creates a methodology that can be used to assess the impact of a given emission source on local, regional, and global areas over varying lifetimes of the source of emissions. This method allows us to think about the intersection temporal variation in the earth and social systems, where the lifetime of an emission source, the lifetime of its pollutants, and the timeline of the pollutant’s impacts are all varying and important to consider. Additionally this method allows us to simply assess the important components in spatial variability on emissions and their impacts. I apply this methodology to look at databases of coal powerplants globally, and assess the importance of their emissions, location, source of funding, amongst other sustainable development issues such as proximity to protected lands.
Spatial and Temporal Variability of Ozone Responses to Large and Small Scale Emissions Changes Similar to my work with Black Carbon, C$_2$, and Mercury, I use Green’s functions to create a methodology that can allow us to look at ozone formation across different background conditions, seasons, and other spatially relevant features. As ozone is a non-linear pollutant that depends on background VOC and NO$_x$ concentrations, I use a series of pulse emission model runs from GEOS-Chem to assess the most important spatial and temporal factors to consider in a mathematical function that represents ozone formation from a given pollution source. The aim of this work is to provide a simple method that can allow for impact assessments of individual pollution sources on ozone across multiple timescales and spatial scales, without having to run complicated Chemical Transport Models.