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Contrails and aircraft-induced cirrus clouds are reputed being the largest components of aviation-induced global warming, even greater than carbon dioxide (CO2) exhaust emissions by aircraft. This article presents a contrail model algorithm specifically developed to be integrated within a multi-objective flight trajectory optimization software framework. The purpose of the algorithm is to supply to the optimizer a measure of the estimated radiative forcing from the contrails generated by the aircraft while flying a specific trajectory. In order to determine the precise measure, a comprehensive model is employed exploiting the Schmidt-Appleman criterion and ice-supersaturation regions. Additional parameters such as the solar zenith angle, contrail lifetime and spread are also considered.

This paper presents the conceptual design of a new low-cost measurement system for the determination of pollutant concentrations associated with aircraft operations. The proposed system employs Light Detection and Ranging (LIDAR) and passive electro-optics equipment installed in two non-collocated components. The source component consists of a tuneable small-size and low-cost/weight LIDAR emitter, which can be installed either on airborne or ground-based autonomous vehicles, or in fixed surface installations. The sensor component includes a target surface calibrated for reflectance and passive electro-optics equipment calibrated for radiance, both installed on an adjustable support. The proposed bistatic system determines the column-averaged molecular and aerosol pollutant concentrations along the LIDAR beam by measuring the cumulative absorption and scattering phenomena along the optical slant range.

A unified approach to cooperative and non-cooperative Detect-and-Avoid (DAA) is a key enabler for Remotely Piloted Aircraft System (RPAS) to safely and routinely access all classes of airspace. In this paper state-of-the-art cooperative and non-cooperative DAA sensor/system technologies for manned aircraft and RPAS are reviewed and the associated multi-sensor data fusion techniques are discussed. A DAA system architecture is presented based on Boolean Decision Logics (BDL) for selecting non-cooperative and cooperative sensors/systems including both passive and active Forward Looking Sensors (FLS), Traffic Collision Avoidance System (TCAS) and Automatic Dependent Surveillance - Broadcast (ADS-B). After elaborating the DAA system processes, the key mathematical models associated with both non-cooperative and cooperative DAA functions are presented.

As part of the current initiatives aimed at enhancing safety, efficiency and environmental sustainability of aviation, a significant improvement in the efficiency of aircraft operations is currently pursued. Innovative Communication, Navigation, Surveillance and Air Traffic Management (CNS/ATM) technologies and operational concepts are being developed to achieve the ambitious goals for efficiency and environmental sustainability set by national and international aviation organizations. These technological and operational innovations will be ultimately enabled by the introduction of novel CNS/ATM and Avionics (CNS+A) systems, featuring higher levels of automation. A core feature of such systems consists in the real-time multi-objective optimization of flight trajectories, incorporating all the operational, economic and environmental aspects of the aircraft mission.