## 1 Introduction  
In an era when human life significantly depends on the electricity supply, uninterrupted power system operation is a daily challenge. The power system components are located mostly above the ground and are therefore exposed to various weather and climate conditions that can affect them both positively and negatively. To ensure optimal energy transfer, transmission system operators in the power system control operational service use different tools, one of them being contingency analysis. The inputs for the contingency analysis algorithm can include various types of information about the power system, as well as terrestrial and remote sensing meteorological data and other relevant information. An example of such an indirect influence of weather and climate on the power network is forest fires. The behavior of the forest fire significantly depends on the weather conditions and the state of the ground, and its consequences are well known. It is less known that smoke and ash may damage overhead lines, decrease their transmission capacity, etc. Smoke and ash, together with pollen, dust, sea salt, and other atmospheric pollutants, are known as aerosols. Aerosols that may damage the power network have various atmospheric sources, dimensions, and behaviors. Forest fires' challenges and disastrous consequences are well known. Unfortunately, there are still many gaps in the protection against them. One of them is a lack of meteorological measurements, especially on the microscale, and information about the state of the landscape. It may be fulfilled using satellite data, e.g., Sentinel missions [1]. Also, there is a lack of weather and air-quality data in the aerosol contamination monitoring. The Croatian air-quality network is located mainly in the industrial zones [2]. The disruption in the power system operation could appear because of high levels of aerosol that may be released outside of industrial zones. The experience from the transmission system operator (TSO) is that aerosol originating from forest fires, sea salt, dust released during grain harvesting, etc., may cause significant problems, which was a motivation for exploring the possibilities of using Sentinel 5p data in aerosol contamination monitoring. Satellite data can be used in various ways to protect the power network against forest fires and aerosol contamination. The literature provides many examples of Sentinel 2 data applications in monitoring urban and rural landscapes by calculating various indices [3; 4; 5; 6; 7]. Landscape monitoring may include vegetation growth monitoring [8], burnt area detection [9], and fire severity classification [10]. A group of authors continuously researched the Sentinel 3 Fire Radiative Power (FRP) product's performance in active fire detection and fire radiative power retrieval in various parts of the world. A comparison of Sentinel 3 FRP products with similar data sources showed that FRP performances are at a high level [11; 12; 13]. Air temperature and land surface temperature are strongly connected to forest fire behavior [14]. The land surface temperature is possible to obtain by using the Sentinel 3 Land Surface Temperature (LST) product [15]. Its performances showed an accuracy of 1.8 K and a precision of 1.2 K [16]. These performances indicate the possibilities of the Sentinel 3 LST data application in forest fire-spreading prediction and monitoring. Including information about the land surface temperature together with information about vegetation moisture in fire-spreading prediction can produce results similar to or better than those obtained using only the Canadian Fire Weather Index (FWI) [17]. The other factor that can significantly influence forest fire ignition and spreading is soil moisture. In the literature, it is shown that the soil and/or vegetation moisture can be calculated through the evening and morning [18] or some other time interval [19], LST difference, as well as the difference between LST and air temperature [20].