A GIS-based atmospheric dispersion model for pollutants emitted by complex source areas

Area of Science:

• Environmental Science
• Atmospheric Science
• Computational Science

Background:

• Gaussian dispersion models are essential for simulating pollutant transport but often face computational limitations with complex source geometries.
• Existing models struggle with intricate source configurations, limiting their application in detailed environmental impact assessments.
• The need for efficient and user-friendly tools for atmospheric dispersion modeling is critical for regulatory compliance and environmental management.

Purpose of the Study:

• To introduce CAREA, a novel GIS-based Gaussian dispersion model engineered for complex source areas.
• To develop a model that overcomes the computational and geometrical limitations of existing Gaussian models.
• To provide a user-friendly tool for simulating pollutant concentrations and deposition fluxes within a GIS environment.

Main Methods:

• CAREA was developed using Python, incorporating a simplified formulation inspired by the AERMOD model.
• The model integrates seamlessly with GIS environments, allowing for the definition of thousands of complex sources and receptors.
• It computes ground-level pollutant concentrations and dry deposition fluxes, with full management of input, output, and model runs within GIS.

Main Results:

• CAREA successfully handles complex source geometries with numerous vertices and holes, processing thousands of receptors efficiently.
• Tests demonstrate satisfactory processing times, ease of use for defining sources/receptors, and straightforward output retrieval within GIS.
• Comparative analysis shows CAREA accurately replicates AERMOD simulations while significantly reducing computation time.

Conclusions:

• CAREA provides a robust and efficient solution for atmospheric dispersion modeling of complex source areas.
• Its GIS integration enhances usability and accessibility for environmental professionals.
• The model's speed and accuracy make it a valuable tool for air quality assessments and regulatory applications.