Air pollution from anthropogenic aerosols poses severe health and environmental risks, yet isolating local urban contributions from regional backgrounds in arid regions remains challenging due to dominant natural dust sources. This study introduces and evaluates an urban-rural aerosol contrast metric (Delta AAI) derived from TROPOMI Absorbing Aerosol Index observations across 429 Iranian cities to quantify local anthropogenic enhancement and identify its determinants. Delta AAI was calculated as the difference between mean AAI within urban boundaries and surrounding rural reference zones, subjected to buffer sensitivity analysis and bootstrap uncertainty quantification, and compared against annual ground-based PM2.(5) concentrations. Generalized additive models (GAMs) examined non-linear relationships between Delta AAI and predictors including urban extent, development intensity, vegetation cover, and aridity. Results show that 78% of cities exhibit positive Delta AAI (mean = 0.32 +/- 0.35), with estimates robust to buffer radius (r >= 0.93) and sampling uncertainty (mean bootstrap SE = 0.041). Delta AAI correlated significantly with PM2.(5) (R-2 = 0.38, p < 0.001), indicating a moderate, single-year consistency with surface pollution. The GAM explained 53.3% of deviance, identifying urban extent as the dominant predictor with enhancement saturating beyond similar to 30 km(2), while vegetation cover consistently associated with reduced contrast. The findings suggest that Delta AAI provides a useful indicator of local anthropogenic enhancement in dust-dominated environments and highlight that urban scale and vegetation are primary, non-linear controls on aerosol enhancement, providing a methodological basis for targeted air quality monitoring in data-sparse regions.