Micro X-ray fluorescence imaging coupled with chemometrics to detect and classify asbestos fibers in demolition waste

Abstract

Asbestos was largely used in the past by several countries all over the world. From 1900 to 1990 asbestos-containing materials (ACMs) were produced in large amounts and mainly utilized to produce insulation, flame retardant materials, as well as to improve the mechanical and the chemical characteristics of construction materials. Its extensive use has therefore led to the presence of fibers in existing buildings and within the construction and demolition waste. A fast, reliable and accurate recognition of ACMs represents an important target to be reached. In this paper the use of micro X-ray fluorescence (micro-XRF) technique coupled with a statistical multivariate approach was applied and discussed with reference to ACMs characterization. Different elemental maps of the ACMs were preliminary acquired in order to evaluate distribution and composition of asbestos fibers, then samples energy spectra where collected and processed using chemometric methods to perform an automatic classification of the different typologies of asbestos fibers. Spectral data were analyzed using PLS-Toolbox™ (Eigenvector Research, Inc.) running into Matlab® (The Mathworks, Inc.) environment. An automatic classification model was then built and applied. Results showed that asbestos fibers were correctly identified and classified according to their chemical composition. The proposed approach, based on micro-XRF analysis combined with an automatic classification of the elemental maps, is not only effective and non-destructive, it is fast, and it does not require the presence of a trained operator. The application of the developed methodology can help to correctly characterize and manage demolition waste where ACMs are present.