This paper presents a new sampling head design and the method used to evaluate it. The elemental composition of aerosols collected by two different sampling devices in a semi-arid region of Tunisia is compared by means of compositional perturbation vectors and biplots. This set of underused mathematical tools belongs to a family of statistics created specifically to deal with compositional data. The two sampling devices operate at a flow rate in the range of 1 m(3) h(-1), with a cut-off diameter of 10 mu m. The first device is a low-cost laboratory-made system, where the largest particles are removed by gravitational settling in a vertical tube. This new system will be compared to the second device, a brand-new standard commercial PM10 sampling head, where size segregation is achieved by particle impaction on a metal surface. A total of 44 elements (including rare earth elements, REEs, together with Al, As, Ba, Be, Ca, Cd, Co, Cr, Cu, Fe, K, Li, Mg, Mn, Mo, Na, Ni, P, Pb, Rb, S, Sc, Se, Sr, Ti, Tl, U, V, Zn, and Zr) were analysed in 16 paired samples, collected during a 2-week field campaign in Tunisian dry lands, close to source areas, with high levels of large particles. The contrasting meteorological conditions encountered during the field campaign allowed a broad range of aerosol compositions to be collected, with very different aerosol mass concentrations. The compositional data analysis (CoDA) tools show that no compositional differences were observed between samples collected simultaneously by the two devices. The mass concentration of the particles collected was estimated through chemical analysis. Results for the two sampling devices were very similar to those obtained from an online aerosol weighing system, FLOM (tapered element oscillating microbalance), installed next to them. These results suggest that the commercial PM10 impactor head can therefore be replaced by the decanter, without any measurable bias, for the determination of chemical composition and for further assessment of PM10 concentrations in source regions.