Anthropogenic Climate Change Analysis
Using data to prove humans are changing the climate.
A data analysis project examining the statistical relationship between CO2 emissions, urbanization rates, and global temperature increases using multiple public datasets.
Problem
Climate change is often discussed qualitatively. The goal of this project was to quantitatively demonstrate the correlation between human activity and rising global temperatures using real-world data.
Approach
Using Python, I pulled and cleaned datasets from public sources including NASA and NOAA, then applied statistical analysis and visualization to surface meaningful trends.
- Cleaned and merged multiple public climate datasets in Python
- Applied regression analysis to measure correlation between CO2 and temperature
- Visualized urbanization trends alongside temperature anomalies
- Documented findings with reproducible Jupyter notebooks
Outcome
The analysis clearly demonstrated a statistically significant correlation between human CO2 emissions, urbanization, and global temperature increases — providing a data-backed foundation for climate policy discussion.