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The paper describes a MAS (multi-agent system) simulation approach forcontrolling PM10 (Particulate Matter) crisis peaks. A dispersion model is usedwith an Artificial Neural Network (ANN) to predict the PM10 concentrationlevel. The dispersion and ANN models are integrated into a MAS system. PM10source controllers are modelled as software agents. The MAS is composed ofagents that cooperate with each other for reducing their emissions and controlthe air pollution peaks. Different control strategies are simulated andcompared using data from Annaba (North-East Algeria). The simulator helps tocompare and assess the efficiency of policies to control peaks in PM10.

Modelling PM10 Crisis Peaks Using Multi-Agent based Simulation: Application to Annaba City, North-East Algeria