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Knowledge extraction and acute forecasting are among the most challenging issues concerning the use of computational intelligence (CI) methods in real world applications. Both aspects are essential in cases where decision making is required, especially in domains directly related to the quality of life, like the quality of the atmospheric environment. In the present paper we emphasize on short term Air Quality (AQ) forecasting as a key constituent of every AQ management system, and we apply various CI methods and tools for assessing PMio concentration values. We report our experimental strategy and preliminary results that reveal interesting interrelations between AQ and various city operations, while performing satisfactory in predicting concentration values.