Long-term SO2 dispersion modeling over a coastal region

Area of Science:

• Environmental science
• Atmospheric chemistry
• Air quality management

Background:

• Air dispersion modeling over coastal regions presents significant challenges for conventional models like ISC2 and HYSPLIT.
• Accurate prediction of ground-level concentrations in coastal zones requires advanced modeling techniques.

Purpose of the Study:

• To evaluate the efficacy of existing mathematical models for predicting plume dispersion in coastal environments.
• To assess the impact of sulfur dioxide (SO2) emissions from a petroleum refinery on adjacent communities.

Main Methods:

• Comparative analysis of air dispersion models, including CALPUFF, ISC2, and HYSPLIT.
• Evaluation of model performance using available input data for coastal dispersion scenarios.
• Assessment of predicted SO2 concentrations against regulatory standards.

Main Results:

• CALPUFF demonstrated superior reliability in predicting plume dispersion compared to other models evaluated.
• The operational intensity and data requirements of CALPUFF pose challenges, particularly in regions with limited data availability.
• Predicted annual average SO2 concentrations in nearby communities were found to be within established regulatory limits.

Conclusions:

• CALPUFF is a more reliable tool for coastal air dispersion modeling, despite its data-intensive nature.
• Data accessibility remains a critical factor for the effective implementation of advanced models like CALPUFF globally.
• Sulfur dioxide emissions from the studied petroleum refinery do not pose an exceedance risk to local air quality regulations.