MIPAS is a satellite-borne limb emission sounder. The algorithm used to infer atmospheric composition from its measurements exploits the assumption that the atmosphere is horizontally homogeneous. This assumption can cause significant errors. We use synthetic observations to quantify these errors. Furthermore we show that the inclusion of any kind of horizontal variability model improves all the retrieval targets and that the two-dimensional approach implies the smallest errors.