Traffic and air pollution pose significant challenges to environmental sustainability in the South Coast Air Basin, particularly in urban areas like Riverside, California, where major highways contribute to high levels of background air pollution. This study investigates the impact of traffic-related air pollutants, specifically NO2 and PM2.5, in Riverside's Innovation Corridor, a six-mile roadway serving key urban centers and logistics activities. Utilizing a low-cost, measurement-based approach over a one year period, the researchers employed gradient-boosted regression trees to model pollutant concentrations based on traffic and meteorological conditions. Preliminary findings indicate that background PM2.5 and relative humidity are crucial drivers for local PM2.5 levels, while NO2 concentrations are influenced by daily traffic patterns. The study confirms that NO2, a primary pollutant, is closely linked to daily activity, whereas PM2.5 is influenced by regional trends and local meteorology. These insights suggest that pollution reduction strategies should focus on NO2 emissions while also considering the complex dynamics of PM2.5. The study highlights the need for further investigation into the sources of NO2 and the effectiveness of proposed traffic interventions in improving local air quality. Future analyses will aim to evaluate the impact of modifications in traffic patterns on pollutant levels along the corridor.
