Fig 1.
Spatial map of 2016 annual PM2.5 model concentrations for (a) CMAQ 12 km x 12 km grid resolution for a subdomain in central North Carolina (b) CMAQ + R-LINE Hybrid, and (d) RAMP Hybrid at census block centroids. Each map includes measurements represented as circles. The gray lines represent the major roads. The gradient bar in figures a, b, and d represents concentration levels in μg/m3. Also shown is one of the RAMP curves (c) used to correct biases from the Hybrid model. The grey dots represent paired observed and modeled daily PM2.5 concentrations for all of 2016 consisting of the 50 closest AQS measurement stations to the centroid of the CMAQ grid cell G(p). The dashed vertical lines represent the 10 equally divided bins used to stratify all the paired data where each bin includes one decile of all the paired points. The solid black line is the one-to-one line between model and observed. The red dots in each bin identify the average of paired observed values within each decile bin. The red dots are linearly interpolated to obtain λ1(p) corresponding to the hybrid modeled data
with G(p).
Fig 2.
Spatial map of 2016 annual PM2.5 and NO2 model concentrations for CMAQ, CMAQ R-LINE Hybrid, and RAMP Hybrid at census block centroids at Boston, Massachusetts and Chicago, Illinois.
The gradient bar represents concentration levels in μg/m3 that range from the smallest 10th percentile of the 3 three models to the highest 90th percentile of the three models for the corresponding domain.
Table 1.
Model performance statistics for annual PM2.5 and NO2 for 2016 of CMAQ, Hybrid, and RAMP hybrid evaluated at AQS Sites across the continental United States.
[PM2.5 (μg/m3): MO = 7.64, SDO = 2.06; NO2 (ppb): MO = 8.38, SDO = 5.73]. The best performing model metric has been highlighted when possible.
Fig 3.
Premature mortality difference between RAMP Hybrid and CMAQ attributable to PM2.5 (left) and NO2 (right) aggregated by county. The Top Panel Show spatial differences across the continental United States. In the Bottom Panel, the blue bars represent the top 20 counties where RAMP Hybrid shows less premature mortality than CMAQ. The red bars represent the top 20 counties where RAMP Hybrid shows more premature mortality than CMAQ. The lines in each bar correspond to the 95% confidence intervals.
Fig 4.
Net difference in premature mortality for PM2.5 and NO2 between models with varying resolution vs distance from primary road.
Net premature mortality was aggregated at every 25 m from a primary road. The blue line represents the population aggregated at every 25 m from a primary road and the red line corresponds to the cumulative sum of the population.
Table 2.
Distribution of exposure inequity ratio estimated at county level, census tract level, and census block group level for PM2.5 and NO2.
Fig 5.
Exposure inequity ratio (EIR) at Madera County, CA.
Top panel shows Exposure Inequity Ratio (EIR) at Madera County, CA (highlighted) and surrounding counties for PM2.5 and NO2 at County (left), Census Tract (middle), and Census Block Group level (right). Bottom panel shows RAMP Hybrid concentration as circles for PM2.5 (left) and NO2 (right) at census block centroids where the size of the census block centroid is proportional to population, as well as the percent of Minority population (middle) at census block centroids where size of census block is proportional to percent Minority at Madera County, CA.
Fig 6.
Population-Weighted Exposure using RAMP (top) for PM2.5 (left) and NO2 (right) and Exposure Inequity ratio (bottom) aggregated at 10m from major roads across the continental U.S. In the bottom two frames, EIRs has been blurred at distances greater than 2 km from the road to convey that there is high noise in the EIR results.