# Adaptive Path Planning for UAV-Based Pollution Sampling
## 1 Introduction
Their maneuverability positions them as viable alternatives to balloons and airships. Additionally, HALE UAVs can act as measurement platforms or substitutes for satellites, commonly referred to as High-Altitude Pseudo-Satellites (HAPSs) [13]. A review by the EU on black carbon (BC) [14] highlights the essential contribution of observations from aircraft and ships in investigating episodes of pollutant transport regarding long distances. At an altitude of 20 km, the atmospheric density is no more than 10% of that at sea level, resulting in minimal dynamic pressure required to sustain lift. This limitation is offset by the need for high velocities [13]. Achieving high altitudes is particularly challenging for aircraft with limited battery capacity. However, once this altitude is reached, it provides access to an almost unlimited source of solar energy. This potential has inspired numerous research teams to pursue the development of such aircraft since Sunrise, the first solar-powered flight, in 1974 [13]. This capability is especially critical for addressing global challenges such as monitoring pollutants like BC, which play a significant role in atmospheric dynamics and climate change. Forest fires and contrails generated by air movements in the tropopause are primary contributors to the transport of BC [15]. BC is described by [PERSON] et al. as \"a component of submicrometer aerosol particles\" that influences the regional radiation balance by absorbing solar radiation (direct effect), reducing the albedo of snow and ice surfaces after deposition, and altering cloud distribution and radiative properties [16]. However, as highlighted in [14], intensive field campaigns for BC observations incur significant costs. Thus, the development of energy-efficient, largely autonomous, and cost-effective scientific platforms becomes essential for studying the sources, sinks, and transport mechanisms of BC. These platforms also play a vital role in advancing our understanding of the impact of natural and anthropogenic aerosol transport on clouds and their properties [15]. The research presented in this paper is closely tied to the primary objective of the international LEADER project-\"Long-endurance UAV for collecting air quality data with high spatial and temporal resolutions\". The project, realized under the \"Applied Research\" program within the Norwegian Financial Mechanisms 2014-2021, aims to develop a HALE UAV as a flying research platform for atmospheric measurements, such as aerosol sampling [15], smog profiling, and BC measurements. The LEADER project focuses on creating a UAV that is capable of long-term flights to collect air quality data over large areas, addressing the need for detailed atmospheric monitoring. The LEADER project is conducted by an international consortium comprising the following partners: SUT--Silesian University of Technology (Poland), UW--University of Warsaw (Poland), NORCE--NORUT (Norway), and ELAB--SkyTech eLab LLC (Poland). The previous research conducted as part of the LEADER project focused on enhancing the energy autonomy, aerodynamic efficiency, and design methodologies of Unmanned Aerial Vehicles (UAVs) through Model-Based Design (MBD). Methods such as optimizing UAV structural shapes using parametric geometry models enable reductions in aerodynamic drag and structural weight [17]. Additionally, solar-powered systems enable extended flight durations, supported by advanced simulation models [18; 19]. The integration of MBD into the design process facilitates rapid evaluation and optimization of load-bearing structures, as demonstrated in HALE-class UAVs [20]. These studies drive innovative UAV solutions, particularly for long-endurance missions. For pollution measurements at higher altitudes, the HALE UAV developed under the LEADER project must sustain extended flight times, addressing the significant challenges posed by limited energy resources and stricter kinematic constraints compared to platforms like multirotors.