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The aim of this research is to develop a multiparametric downscaling analysis for the detection of abandoned waste in the environment. This methodology, using a multi-technological approach, involves the adoption VHR satellite images, Unmanned Aircraft System (UAS) and Unmanned Ground Vehicles (UGV). The identified Warning Areas (WA) will be investigated through an in-situ analysis with air quality measurement devices based on advanced sensors mounted on drones. The creation of a Cadastre Accumulation of Abandoned Materials (CAMA) and the related APP will allow the administrations to monitor the phenomenon. Finally, the waste product analysis, retrieved by means of UAS dataset computation, allows to retrieve some interesting prospects regarding Waste to Energy framework. Here, preliminary results obtained by the on-going INTESA Project are presented.

Aerosols, as well as suspended particulate matter, impact atmospheric pollution, the climate, and human health, directly or indirectly. Particle size, chemical composition, and other aerosol characteristics are determinant factors for atmospheric pollution dynamics and more. In the last decade, low-cost devices have been widely used in instrumentation to measure aerosols. However, they present some issues, such as the problem of discriminating whether the aerosol is composed of liquid particles or solid. This issue could lead to errors in the estimation of mass concentration in monitoring environments where there is fog. In this study, we investigate the use of an optical particle counter (OPC) coupled to a quartz crystal microbalance with an integrated microheater (H-QCM) to enhance measurement performances. The H-QCM was used not only to measure the collected mass on its surface but also, by using the integrated microheater, it was able to heat the collected mass by performing heating cycles. In particular, we tested the developed system with aerosolized saline solutions of sodium chloride (NaCl), with three decreasing concentrations of salt and three electronic cigarette solutions (e-liquid), with different concentrations of propylene glycol and glycerin mixtures. The results showed that the OPC coherently counted the salt dilution effects, and the H-QCM output confirmed the presence of liquid and solid particles in the aerosols. In the case of e-liquid aerosols, the OPC counted the particles, and the HQCM output highlighted that in the aerosol, there were no solid particles but a liquid phase only. These findings contribute to the refinement of aerosol measurement methodologies by low-cost sensors, fostering a more comprehensive understanding.

An original approach has been proposed for designing a nanofibrous (NF) layer using UV-cured polyvinylpyrrolidone (PVP) as a matrix, incorporating mesoporous graphene carbon (MGC) nanopowder both inside and outside the fibers, creating a sandwich-like structure. This architecture is intended to selectively adsorb and detect acetic acid vapors, which are known to cause health issues in exposed workers. The nanocomposite MGC-PVP-NFs layer was fabricated through electrospinning deposition onto interdigitated microelectrodes (IDEs) and stabilized under UV-light irradiation. To enhance the adhesion of MGC onto the surface of the nanocomposite polymeric fibers, the layer was dipped in a suspension of polyethyleneimine (PEI) and MGC. The resulting structure demonstrated promising electrical and sensing properties, including rapid responses, high sensitivity, good linearity, reversibility, repeatability, and selectivity towards acetic acid vapors. Initial testing was conducted in a laboratory using a bench electrometer, followed by validation in a portable sensing device based on consumer electronic components (by ARDUINO ® ). This portable system was designed to provide a compact, cost-effective solution with high sensing capabilities. Under room temperature and ambient air conditions, both laboratory and portable tests exhibited favorable linear responses, with detection limits of 0.16 and 1 ppm, respectively.

Suspended particulate matter (PMx) is one of the most important environmental pollutants. Miniaturized sensors capable of measuring and analyzing PMx are crucial in environmental research fields. The quartz crystal microbalance (QCM) is one of the most well-known sensors that could be used to monitor PMx. In general, in environmental pollution science, PMx is divided into two main categories correlated to particle diameter (e.g., PM < 2.5 µm and PM < 10 µm). QCM-based systems are capable of measuring this range of particles, but there is an important issue that limits the application. In fact, if particles with different diameters are collected on QCM electrodes, the response will be a result of the total mass of particles; there are no simple methods to discriminate the mass of the two categories without the use of a filter or manipulation during sampling. The QCM response depends on particle dimensions, fundamental resonant frequency, the amplitude of oscillation, and system dissipation properties. In this paper, we study the effects of oscillation amplitude variations and fundamental frequency (10, 5, and 2.5 MHz) values on the response, when particle matter with different sizes (2 µm and 10 µm) is deposited on the electrodes. The results showed that the 10 MHz QCM was not capable of detecting the 10 µm particles, and its response was not influenced by oscillation amplitude. On the other hand, the 2.5 MHz QCM detected the diameters of both particles, but only if a low amplitude value was used.

Quartz crystal microbalances are widely used sensors with applications for the detection of very-low-mass deposition in many different fields, from contamination monitoring in the high vacuum of deep space missions to the monitoring of biological activity or pollution using specifically designed active substrates. These sensors are very stable over time; nevertheless, their sensitivity to the temperature is well known, and different implementations have been devised to correct it, e.g., through compensation with a dual crystal. This paper deals with the effects of temperature on QCM but separates the case of uniform crystal temperature from the case of in-plane temperature gradients considering a QCM based on quartz crystals with deposited film resistors used as both RTDs and heaters. This configuration allows both an accurate temperature measurement and efficient thermal control, allowing the achievement of crystals temperatures in the order of 400 °C higher than the environment with a low power dissipation of the order of 1 W. The film resistors deposited around the electrodes allow directly measuring the average crystal temperature and directly delivering power to the crystal for thermal control. The localized delivery of the heat nevertheless also determines uncommon temperature fields on the crystal, and thus, an analysis of both the effects of temperature on the new microbalance was performed. The temperature gradient has strong effects on the frequency; therefore, along with the temperature, the thermal gradients have tobe compensated. The calibration of the QCM thermometers and the assessment of the achievable measurement accuracy were performed, as well as the determination of the frequency-temperature relationship. The comparison between frequency changes in the case of uniform temperature and those observed while using crystal heaters proved that temperature gradients have a strong effect on the crystal frequency. To identify the temperature field on the crystal surface of a QCM crystal, the gold coating of the deposited films was removed to achieve an emissivity acceptable for thermal imaging with an IR camera. Moreover, image processing for emissivity correction was developed. In order to correlate the temperature gradient with the frequency variation, a test campaign was performed to measure the frequency changes derived from different power levels delivered to the crystal heaters. From this test campaign and thermal analysis, the effect of the thermal gradient was assessed.

Maintenance has a major impact on the financial plan of road managers. To ameliorate road conditions and reduce safety constraints, distress evaluation methods should be efficient and should avoid being time consuming. That is why road cadastral catalogs should be updated periodically, and interventions should be provided for specific management plans. This paper focuses on the setting of an Unmanned Ground Vehicle (UGV) for road pavement distress monitoring, and the Rover for bituminOus pAvement Distress Survey (ROADS) prototype is presented in this paper. ROADS has a multisensory platform fixed on it that is able to collect different parameters. Navigation and environment sensors support a two-image acquisition system which is composed of a high-resolution digital camera and a multispectral imaging sensor. The Pavement Condition Index (PCI) and the Image Distress Quantity (IDQ) are, respectively, calculated by field activities and image computation. The model used to calculate the I ROADS index from PCI had an accuracy of 74.2%. Such results show that the retrieval of PCI from image-based approach is achievable and values can be categorized as "Good"/"Preventive Maintenance", "Fair"/"Rehabilitation", "Poor"/"Reconstruction", which are ranges of the custom PCI ranting scale and represents a typical repair strategy.