Prediction of ozone concentration in atmosphere using statistical method

A statistical method for short-term prediction is investigated to predict t he ozone concentration in Seoul, Korea. Parameter estimation method and an artificial neural network (ANN) method were used to achieve real-time short -term prediction. Ozone concentrations often exceed air quality standards i n cities around the world, and thus reliable prediction methods of ozone le vels are needed. In this work, 16 hours and 16-21 hours prediction was perf ormed. To verify the effectiveness of the prediction methods proposed in th is work, the prediction results of ozone concentration were compared to the actual data. It appears that the methods proposed are a reasonable means o f developing real-time short-term prediction for an ozone warning system.