Kaanan Datt
Pronouns: he/him
Research Mentor(s): August Evrard
Research Mentor School/College/Department: Physics / LSA
Program: UROPF
Session: Session 2 (10:00am – 10:50am)
Authors: Kaanan Datt, August Evrard
Abstract
In the last century, the amount of fossil fuel emissions used by the world has greatly increased. It’s important to understand where and from what source these emissions originate to help find and target solutions, and to educate students. In this project, we aim to find a method using Python to map existing CO2 emission sources, and develop teaching materials for Physics 210 ‘Sustainable Energy Futures’. We use Python as the mapping software and use the maps we develop to design teaching modules. Currently, much software exists for mapping and organizing data but hasn’t been exactly for mapping this data. The method we are employing is first developing prototype maps using data on carbon emissions in 2021 from the Emissions Database for Global Atmospheric Research (EDGAR), condensing the programs with abstraction functions, and then developing learning modules in Python notebooks. We will apply these modules to the Physics 210 class in March 2023 as a 2-day lab, and judge the success of the modules based on feedback received. We hope to find this method of modeling easier to follow and understand, as well as easier for students to do their own self-exploration with the right tools. These results would suggest these Python notebook modules are a good teaching method for analyzing data, as well as an overall good model for the emission data. The scope is centered around creating useful modules for students in the class. This would give students a better understanding of carbon emission sources and help visualize the scope of emissions across the globe. The findings on the usefulness of Python as a teaching/exploration tool for modeling can be applied to research, and to benefit students and professors that use data modeling.
