# Real-Time Contrail Monitoring and Mitigation Using CubeSat Constellations  
[PERSON]  
1 Nottingham Geospatial Institute, University of Nottingham, Nottingham NG7 2 RD, UK;  
1 [EMAIL_ADDRESS] (L.C.); [EMAIL_ADDRESS] (C.C.)  
[PERSON]  
1 Nottingham Geospatial Institute, University of Nottingham, Nottingham NG7 2 RD, UK;  
1 [EMAIL_ADDRESS] (L.C.); [EMAIL_ADDRESS] (C.C.)  
[PERSON]  
1 Nottingham Geospatial Institute, University of Nottingham, Nottingham NG7 2 RD, UK;  
1 [EMAIL_ADDRESS] (L.C.); [EMAIL_ADDRESS] (C.C.)  
[PERSON]  
2 Nottingham NG7 2 RD, UK;  
the lower part of the wake, while crystal growth dominates in the upper part. Over a few minutes, the wake disperses, merging the contrail into the ambient air [6].  
The environmental impact of contrails is particularly concerning over high-traffic air routes, such as the North Atlantic Corridor, where the frequency and persistence of contrails are highest. In these regions, the cumulative effect of contrail-induced cloudiness can have a significant impact on regional and global climate patterns [7]. Despite their importance, contrails have not been given the same level of attention as CO\({}_{2}\) emissions in climate policy discussions, leaving a critical gap in our understanding and management of aviation's full environmental footprint [8; 9; 10].  
This research addresses the urgent need to better understand and mitigate the environmental impact of contrails. The primary objective is to explore the potential of CubeSats, miniaturized, low-cost satellites, for real-time monitoring of atmospheric conditions that lead to contrail formation. By deploying constellations of CubeSats with monitoring payloads, it is possible to collect high-resolution data on temperature, humidity, and other relevant atmospheric variables in key flight corridors [11; 12]. These data can then be integrated into machine learning algorithms [13; 14] to develop predictive models that inform real-time flight management decisions, enabling pilots to adjust flight paths to avoid conditions conducive to contrail formation.  
The significance of this research extends beyond its immediate application to contrail mitigation. It represents a broader shift towards integrating real-time environmental data into aviation operations, aligning the industry with global sustainability goals. Specifically, this research supports the United Nations Sustainable Development Goal 13 (Climate Action), which calls for urgent action to combat climate change and its impacts [15].  
This paper is structured to provide a detailed exploration of the challenges and opportunities associated with contrail monitoring and mitigation. It begins with an in-depth examination of the physical and atmospheric mechanisms behind contrail formation, including a discussion of the Schmidt-Appleman criterion and the role of various atmospheric variables. The environmental impact of contrails is then analyzed, with a focus on their contribution to global warming and the broader implications for climate change.  
Following this, the paper introduces CubeSat technology as a solution for real-time contrail monitoring. The capabilities of CubeSats, including their sensor payloads, data transmission systems, and potential for integration with machine learning algorithms, are discussed in detail. The paper then explores the concept of a distributed CubeSat system, examining the technical, logistical, and regulatory challenges of deploying such a system globally.  
Finally, the paper outlines a future roadmap for implementing CubeSat-based contrail monitoring, including phased deployment strategies, integration with flight management systems, and the potential for international collaboration. The long-term vision for this technology is also discussed, emphasizing its potential to transform the aviation industry and contribute to global climate goals.