Study of atmospheric dispersion of particulate matter using a meteorological model, a photochemical model and an emissions model in Asuncion, Paraguay

Abstract

This work utilizes an integrated air quality modeling framework combining the Community Multiscale Air Quality (CMAQ) model, the Weather Research and Forecasting (WRF) model, and the Sparse Matrix Operator Kernel Emissions (SMOKE) model to examine fine particulate matter (PM2.5) dispersion in Asuncion, Paraguay. The study focuses on simulating PM2.5 concentrations and validating these against observations from Asunción's air quality monitoring network to elucidate the impact of urban emissions and meteorological conditions on particulate dispersion. It highlights the significant influence of weather patterns and vehicular emissions on particulate levels. Integrating CMAQ with WRF and SMOKE models for this purpose is a novel approach, offering detailed insights into the factor s driving air quality in this Capital City. Findings from this research reveal pronounced variabilities in PM2.5 concentrations, driven by seasonal meteorological changes and urban activities. This emphasizes the need for accurate emissions inventories and ground-stations in real-time in air quality prediction. The application of the CMAQ-WRF-SMOKE modeling system represents a significant contribution to atmospheric science, showcasing the potential of integrated modeling approaches in understanding and managing urban air quality. This contribution underscores the broader implications of our findings, suggesting a scalable and adaptable framework for air quality assessment and intervention in cities worldwide.