This study aims to use chemodynamics to engage the interplay between societal actions and environmental response. The project will build upon data from thermogravimetric and isotopic analysis capturing macroscopic soil chemodynamics in response to suburbanization in the Dallas-Fort Worth Metroplex (DFW). The DFW is one of the fastest growing metro areas in the US. Our early data suggests that a minimum of 30-yrs is the required period of lawn care before key chemodynamic indicators of soil health/resilience, such as R50 and isotope 13C (quantity and quality, is needed for lawns to return to their pre-suburbanization environmental status.

The objective is to examine implications at the microphysical and molecular-level via: Assessing how differences in the molecular composition of soil organic matter from a suburban lawn changes over time.

We propose a GIS project analyzing waste disposal accessibility by comparing recycling quality between low-income and high-income neighborhoods. Using spatial analysis and field data, we will compare the amount of waste generated to the income of Los Angeles counties, and document any trends. The findings will provide insights into potential disparities in waste management services and inform policy recommendations for improving recycling programs in underserved communities.

The purpose of this project is to determine if California's raging wildfires are having a detrimental effect on the state’s tree populations/health. Two main components of this project would be, a model of California's tree density/canopy cover in 1990, and a model of California’s tree density/canopy cover in 2020. The goal of this project is to determine if an increase in wildfires is a key factor in the decrease of California tree density, and if so, make recommendations for further research on how to protect trees from this natural disaster.

The Coll de Montllobar cliffs in the Pyrenees Mountains contain plant fossils known as root models, which show signs of oxidation and reduction along a depositional dip, indicating varying environmental conditions Since plant roots do not grow below standing water levels, these fossilized roots and their distribution can serve as markers for past water table positions. This study examines whether root density decreases toward the bottom of the channels, indicating that roots stopped growing once they reached below the water table. If the roots disappear at a certain depth, it suggests that the bar was saturated at that level, stopping root growth. By analyzing the presence and absence of these roots, we aim to determine if they mark a clear boundary indicating historical water table levels. Our findings contribute to understanding past depositional environments and hydrological conditions in this region

The Barnett Shale formation in the Fort Worth Basin has been a substantial producer of oil and gas energy resources. The Barnett Shale serves as an ideal testing ground for innovative approaches to subsurface analysis, offering both abundant production history and a wealth of existing data. This study integrates innovative thermal analysis techniques with AI-driven workflows to rapidly process and interpret large volumes of geochemical data. We aim to identify and evaluate geochemical variability and the distribution, content, and quality of geogenic carbon with depth across key stratigraphic intervals. Expanding subsurface applications of AI and machine learning enhances the scalability of resource assessments and underscores the broader potential of these emerging analytical tools in energy exploration.