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Open-top chambers (OTC) are experimental facilities that have been widely used to expose plants to an atmosphere with high concentration of CO2 for a long period. In carbon dioxide enriched environment vegetal species tend to intensify the photosynthesis process and consequently they acquire biomass more quickly. Currently there is a trend to use CO2 injection to speed up the production of vegetal species. In addition, the growing concern with the global warming stimulated experiments with OTC to evaluate the effects of high CO2 concentration on plants. The project of an efficient control system for those chambers depends upon a model that represents the dynamics of the process. This work describes a way to model the CO2 concentration inside an OTC by means of experimental data. The parameters of different auto regressive models (ARX and ARMAX) were estimated to fit the observed data. The models that presented the best performance were analyzed on the frequency domain with the intention of validating the most appropriate model for control purposes. The identification resulted in a first order output error (ARMAX) model that presented a fit of 69.64% to reproduce the validation data. This model showed to be reliable up to 0.35 rad/s.