Spatial Data Analysis

Coal Ash Contamination and Cancer Rates: A Spatial Analysis of North Carolina

Master’s Student Project - Public Policy 275

This student research project investigated potential correlations between coal ash disposal site contamination and cancer rates across North Carolina.

Report Summary

Using newly released data from EarthJustice on coal ash disposal sites, I combined multiple geospatial techniques:

  • Created raster datasets through upsampling of county-level cancer data

  • Applied inverse-distance weighting to model contamination exposure

  • Conducted moving window regression analysis to identify statistically significant correlations

  • Generated visualization overlays to identify high-priority areas for further investigation

Technical skills demonstrated:

  • Spatial data analysis using Python

  • Statistical analysis (regression, p-value calculation)

  • Data visualization and mapping

  • Processing of publicly available datasets

  • Interpretation of environmental contamination data