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. Author manuscript; available in PMC: 2020 Apr 1.
Published in final edited form as: Environ Int. 2019 Feb 1;125:97–106. doi: 10.1016/j.envint.2018.12.025

Fig. 6.

Fig. 6.

Spatial pattern of the odds of high Shared Multiplicative Exposure Measurement Error (SMME) in spatiotemporal NOx predictions for a random sample of 2500 predictions from the city of Long Beach, CA (a) unadjusted, (b) after spatial (c) and temporal adjustments. High SMME is defined with a cut-off based on the top 80th percentile of average covariance distribution in Long Beach at each unique location. Confounders of shared multiplicative exposure measurement error risk adjusted for in the model included population density, CALINE4 Non-freeway NOx, and Traffic Density on FCC2 Roads. Statistically significant geographic areas of increased or decreased risk of SMME are indicated using black contour lines.