NEW TECHNIQUES IN REAL-TIME 3D AIR QUALITY MONITORING: CO, NOX, O3, CO2 AND PM MEASUREMENTS WITH DRONES AND REMOTE AIRBORNE SENSORS

The airborne remote sensing has great potential in the environmental monitoring and during last years our research group has developed several scientific applied researches, discovering new methods and new technologies to perform an advanced real-time 3D air quality monitoring and today we have gained a specific know-how also to support government bodies in environmental actions and law enforcement. Airborne remote sensing has a much longer history then satellite-based Earth observation, which has led to the development of a wide variety of vehicles that can carry different sensors, ranging from tethered balloons to Unmanned Aerial Vehicles (UAVs) / Drones but, in this paper, we introduce the airborne systems only to assess their utility in the context of a full 3D data acquisition (e.g. vertical profiles). We specifically show a new system that combines a small drone multi-rotor with a specific payload that includes CO, NOX, O3, CO2 and PM sensors. During last year we test first prototypes of our new system in several missions and here we show the results of this experimental phase. First positive results of this experimentation have encouraged the signature of a memorandum of understanding between University of Naples Parthenope and several Government (e.g. Italian Coast Guard) and private bodies. We base our evaluation on a number of objective assessment criteria that include technical, economical and logistic aspects related to the system, as well as various considerations for mission requirements response, such as required acquisition time/period or specific criticalities of the examined scenario (urban, suburban, industrial etc.). In this paper we also illustrate how different mission scenarios can lead to a range of “observable consequences” that call for suitably adapted remote sensing tools, and how our new techniques can lead to improved real-time monitoring capability. We conclude with a table that summarizes the relevant characteristics of the main remote sensing data type and our solutions with respect to their suitability for different missions types, which can serve as guidance for Government decision makers.