Modeling Fine Particulate Matter and Quantifying Source Contributions in Central America

July 07, 2026

Ana Elizabeth Lasso de la Vega Guerra

Committee: Jeffrey Pierce (Advisor); Jeffrey Collett; Ellison Carter (Civil and Environmental Engineering)

Abstract

Fine particulate matter (PM2.5) poses a significant public health burden across Central America, yet the region remains critically undermonitored and largely absent from source-resolved air quality assessments. Ground-based monitoring networks are sparse, and satellite-based retrievals are limited by persistent cloud cover and high humidity, reducing the reliability of either observational approach. Here we present the PM2.5 characterization and source attribution for Central America, spanning Mexico City to Medellín, Colombia, using nested GEOS-Chem chemical transport model simulations at 0.5° × 0.625° resolution and a satellite-informed PM2.5 product. The model reproduces the spatial distribution of primary PM2.5 hotspots but tends to overestimate concentrations at source regions while underestimating background levels. Comparison against SPARTAN filter-based measurements in Mexico City reveals simulation overestimation of nitrate and underprediction of organic matter and black carbon, suggesting biases in the residential combustion sector of the emissions inventory. Sulfate and organic matter dominate the PM2.5 composition with low seasonal variability, while dust drive a pronounced summer seasonal signal. Zero-out sensitivity simulations identify residential combustion, biomass burning, waste management, and energy production as the consistent primary drivers of PM2.5 across the region. Population exposure estimates indicate that 35.6% and 92.6% of the regional population are exposed to long-term PM2.5 exceeding 10 µg/m³ and 5 µg/m³, respectively, rising to 71.7% and 99.9% based on satellite-informed concentrations. Residential combustion contributes the highest population-weighted mean PM2.5, followed by energy, biomass burning, and industry. These results provide a quantitative, policy-relevant foundation for regional air quality management analysis across a historically understudied part of the world.