Evaluating Spatial Outliers And Integrating Temporal Data In Air Pollution Models For The Detroit-Windsor Airshed

The heterogeneous nature of urban air complicates human exposure estimates and creates a need for accurate, highly detailed spatiotemporal air contaminant models. The study expands on previous investigations by the Geospatial Determinants of Health Outcomes Consortium that examined relationships between air pollutant distributions and asthma exacerbations. Two approaches, the removal of spatial data outliers and the integration of spatial and temporal data, were used to refine air quality models in the Detroit and Windsor international airshed. The evaluation of associations between the resulting air quality models and asthma exacerbations in Detroit and Windsor revealed weaker correlations with spatial outliers removed but improved correlations with the addition of temporal data. Recommendations for future work include increasing the spatial and temporal resolution of the asthma datasets and incorporating Windsor NAPS data through temporal scaling to help confirm the findings of the Detroit temporal scaling