Urban Air Quality Prediction

The objective of this project was to use regression modeling to compare urban air quality in Los Angeles and New York City. The objective was to develop an accurate prediction model of daily PM2.5 concentrations for these cities. Additionally, this study seeks to identify key environmental drivers influencing PM2.5 levels, including meteorological variables, pollutant interactions, and engineered features. Understanding these drivers not only improves predictive accuracy but also provides interpretable insights that can inform urban planning, emission control strategies, and public health interventions.