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Forecasting air pollution potential: a synoptic climatological approach.

G M Scott¹, R D Diab

¹University of Natal, Durban, South Africa.

Journal of the Air & Waste Management Association (1995)

|April 6, 2001

Summary

A new air pollution potential (APP) forecast model warns industries of poor atmospheric dispersion. Negative surface pressure tendency signals episode start, while wind direction helps predict the end, improving SO2 alert accuracy.

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Area of Science:

Environmental Science
Climatology
Atmospheric Science

Background:

Industrialized areas face challenges with air quality management.
Forecasting air pollution potential (APP) is crucial for mitigating industrial emissions.
Durban, South Africa, requires effective tools for managing air quality in its industrial zones.

Purpose of the Study:

To develop and apply an air pollution potential (APP) forecast model for an industrialized region.
To provide industries with advance warnings of poor atmospheric dispersion events.
To enable industries to proactively reduce emissions during high-risk periods.

Main Methods:

Utilized a synoptic climatological approach for forecasting.
Developed a system of alerts (orange, red, all-clear) for industry communication.

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Identified key meteorological parameters for predicting APP episode onset and cessation.

Main Results:

Negative surface pressure tendency was the key indicator for the commencement of APP episodes.
Wind direction proved most effective in estimating the end of APP episodes.
The model demonstrated high success in identifying periods of elevated sulfur dioxide (SO2) concentrations.

Conclusions:

The developed APP forecast model is effective in identifying high pollution potential periods.
Further refinement is needed for accurately forecasting the end of APP episodes.
The model provides valuable support for industrial emission control strategies in Durban.