Indoor air quality in subterranean train stations is a concern in many places around the globe. However, because of the specificity of each case, numerous parameters of the problem remain unknown, such as the braking disc particle emission rate, the ventilation rate of the station or the complete particle size distribution of the emitted particles. In this study the problem of modelling PM10 concentration evolution is hence addressed with a particle-mass conservation model which parameters are fitted using a genetic algorithm. The parameters of the model allow to reproduce the dynamics and amplitude of the measured data and comply with realistic bounds in terms of emissions, deposition and ventilation rate.
conservation model, identification, PM10, underground air quality
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