<p>Surface-wave analysis can be performed according to a multitude of approaches. In fact, both the determination of the dispersive properties and data inversion can be accomplished according to several possible techniques, which should be chosen on a case-by-case basis, depending on the goals and site characteristics. The <i>Miniature Array Analysis of Microtremors</i> (MAAM) is an interesting methodology aimed at extracting the dispersive properties of the vertical (Z) component of Rayleigh waves from passive data recorded according to a circular-symmetry array. Compared to other techniques, MAAM can investigate larger wavelengths and provide phase velocities in a wider frequency range (a triangular array with a radius of a couple of meters can provide the dispersion curve in the 2–20&#xa0;Hz frequency range, approximatively). Despite its remarkable potential, MAAM can be affected by industrial noise that alters the natural microtremor field. The comparative analysis of the Z-component dispersion retrieved via <i>Extended Spatial AutoCorrelation</i> (ESAC) and MAAM is initially conducted to validate the adopted procedures and verify the paradigms to adopt to identify the frequency range properly investigated. Following this, analysing a second time-lapse dataset, the effects of industrial components on both the dispersion curve obtained via MAAM and the Horizontal-to-Vertical Spectral Ratio (HVSR) are investigated. The experimental evidences show that non-monochromatic industrial components can have a malicious effect on both MAAM and HVSR. In this context, analysing the coherence functions of the multi-component data recorded by a 3-component geophone, together with the spectral ratio and noise-to-signal ratio obtained during MAAM processing, is crucial for assessing the possible presence of industrial components that may affect the observables ultimately used in the joint inversion.</p>