Hyperspectral imaging approach for the identification of construction and demolition waste from earthquake sites

Earthquakes create significant volumes of rubbles and waste, strongly impacting the environment and posing serious health risks. In the last decade, earthquake occurred in several Italian areas, in particular the last sequence (Amatrice – Norcia, 2016-2017), still clearly visible in terms of destruction in the epicentral area, produced about 3 million tons of waste, mainly composed of Construction and Demolition Waste (CDW). Post-earthquake building waste is composed of heterogeneous materials, making difficult their separation and recovery as secondary raw materials. CDW recycling and reuse is of fundamental importance because it reduces the increase of landfilling, avoiding non-renewable raw materials exploitation and favoring circular economy. In this work, a sensor-based approach to classify different typologies of tile samples coming from buildings damaged by the Amatrice earthquake is proposed and investigated. Attention was focused on tiles, one of the most recycled masonry aggregates (RMA). This study presents a methodology based on a combination of two analytical techniques, HyperSpectral Imaging (HSI), working in the Short-Wave InfraRed (SWIR) range (1000-2500 nm), and micro-X-ray Fluorescence (micro-XRF), in order to discriminate different tile compositions and to detect the presence of cement mortar on the surface of the samples. The obtained results represent an important starting point to develop and introduce innovative strategies finalized to design, implement and set up automatic recognition and classification procedures of inert CDW fractions.