This paper presents new laboratory measurements of the mass absorption efficiency (MAE) between 375 and 850 nm for mineral dust of different origin in two size classes: PM 10.6 (mass fraction of particles of aerodynamic diameter lower than 10.6 µm) and PM 2.5 (mass fraction of particles of aerodynamic diameter lower than 2.5 µm). Experiments have been performed in the CESAM simulation chamber using generated mineral dust from natural parent soils, and optical and gravimetric analyses. Results show that the MAE values are lower for the PM 10.6 mass fraction (range 37–135 × 10 −3 m 2 g −1 at 375 nm) than for the PM 2.5 (range 95–711 × 10 −3 m 2 g −1 at 375 nm), and decrease with increasing wavelength as λ -AAE , where Angstrom Absorption Exponent (AAE) averages between 3.3–3.5, regardless of size. The size-independence of AAE suggests that, for a given size distribution, the possible variation of dust composition with size would not affect significantly the spectral behavior of shortwave absorption. Because of its high atmospheric concentration, light-absorption by mineral dust can be competitive to black and brown carbon even during atmospheric transport over heavy polluted regions, when dust concentrations are significantly lower than at emission. The AAE values of mineral dust are higher than for black carbon (~ 1), but in the same range as light-absorbing organic (brown) carbon. As a result, depending on the environment, there can be some ambiguity in apportioning the AAOD based on spectral dependence, which is relevant to the development of remote sensing of light-absorption aerosols from space, and their assimilation in climate models. We suggest that the sample-to-sample variability in our dataset of MAE values is related to regional differences of the mineralogical composition of the parent soils. Particularly in the PM 2.5 fraction, we found a strong linear correlation between the dust light-absorption properties and elemental iron rather than the iron oxide fraction, which could ease the application and the validation of climate models that now start to include the representation of the dust composition, as well as for remote sensing of dust absorption in the UV-VIS spectral region.