Abstract Description: Objectives Our team aims to test the relationship between 1940 air quality and dementia onset in the 1990s-2000s, but this work is limited by a lack of air quality data, including emissions information and historical measurements for evaluation, prior to 1970 in the United States. Here, we devised and implemented advanced methodologies to quantify the air quality in 1940 and compared our estimates to present-day where we could validate our methods using air quality monitors. We developed several county-level source-specific exposure metrics across the contiguous United States in 1940 and 2010. We quantified exposure to traffic-related air pollution (TRAP), oil/gas wells, power plants, and fine particulate matter (PM2.5). For TRAP, we incorporated information on statewide gasoline sales and county-level population to estimate gasoline consumed. Using oil/gas well locations, we employed Inverse Distance Weighting (IDW). For fossil fuel power plant locations, we employed IDW. We quantified PM2.5 concentrations using climate model output from the Coupled Model Intercomparison Project Phase 6 (CMIP6). We evaluated these source-specific exposure estimates against observed 2010 annual concentrations from EPA Air Quality System monitors, using Pearson correlation coefficients and mean differences as evaluation metrics. The initial evaluation revealed that CMIP6-based simulations correlated moderately with observed PM2.5 concentrations (Pearson: 0.40). In contrast, automobile emissions showed a weak correlation with PM2.5 (Pearson: 0.04), but a stronger one with NOx (Pearson: 0.41). Well activity presented stronger correlations with VOCs (Pearson: 0.34). The IDW approach to power plant emissions indicated a fair correlation with PM2.5 (Pearson: 0.29) and a higher correlation with sulfate (Pearson: 0.33). Positive correlations suggest expected relationships between the sources of interest and observed air pollutant concentrations. The somewhat lower than expected correlations, however, suggest some refinement to the exposure methods may be necessary. In addition, there may be utility in comparing the concentrations at finer spatial scale than county level.
Keywords: Air modeling, Health assessment, Source-Specific Exposure
