The main objective of the presented study was to verify the potential of the Sentinel-5 Precursor (S-5P) Tropospheric NO₂ Column Number Density (NO₂ TVCD) to support air pollution monitoring in Poland. The secondary objective of this project was to establish a relationship between air pollution and meteorological conditions. The ERA-5 data together with the NO₂ TVCD product and auxiliary data were further assimilated into an artificial intelligence model in order to estimate surface NO₂ concentrations. The results revealed that the random forest method was the most accurate method for estimating the surface NO₂. The random forest model demonstrated MAE values of 3.4 μg/m³ (MAPE~37%) and 3.2 μg/m³ (MAPE~31%) for the hourly and weekly estimates, respectively. It was observed that the proposed model could be used for at least 120 days per year due to the cloud-free conditions. Further, it was found that the S-5P NO₂ TVCD was the most important variable, which explained more than 50% of the predictions. Other important variables were the nightlights, solar radiation flux, road density, population, and planetary boundary layer height. The predictions obtained with the proposed model were better fitted to the actual surface NO₂ concentrations than the CAMS median ensemble estimations (~15% better accuracy).

The COVID-19 pandemic has affected many aspects of human well-being including air quality. The present study aims at quantifying this effect by means of ground-level concentrations of NO₂, PM_2.5, as well as aerosol optical depth (AOD) measurements and tropospheric NO₂ column number density (NO₂ TVCD), during the imposed governmental restrictions in spring 2020. The analyses were performed for both urban and non-built-up areas across the whole of Poland accompanied by Warsaw (urban site) and Strzyzow (a background site). The results revealed that mean PM_2.5 concentrations in spring 2020 for urban and non-built-up areas across Poland and for Warsaw were 20%, 23%, 15% lower than the 10-year average, respectively. Analogous mean NO₂ concentrations were lower by 20%, 18%, 30% and NO₂ TVCD revealed 9%, 4%, 9% reductions in 2020 as compared to 2019. Regarding mean AOD, retrieved from MERRA-2 reanalysis, it was found that for the whole of Poland during spring 2020 the reduction in AOD as compared to the 10-year average was 15%. The contribution of the lockdown within total air pollution reduction is not easily assessable due to anomalous weather conditions in 2020 which resulted in advection of clean air masses identified from MERRA-2 reanalysis and Strzyzow observatory.

The CO ₂ flux on Biebrza Wetlands in Poland is analysed by ground measurements and satellite data. The main goal of this study was to determine the Net Ecosystem Exchange (NEE) for sedges, reeds and grasses using meteorological, soil and vegetation parameters and satellite indicators. The calculations are based on chamber measurements scattered over the main habitats and meteorological registrations, and compared to the 2015–2022 eddy covariance (EC) measurements. The NEE model, to get its distribution throughout the day, was elaborated using modelled gross primary production GPP and modelled respiration RESP. The model of ecosystem respiration was developed applying air temperature, soil temperature, soil moisture and NDVI. The satellite vegetation index NDVI, surface and air difference temperature (T _S -T _A ), and NDII proved to be good predictors for the daily mean GPP. The data from the EC tower was used to compare the results from modelled NEE and CO ₂ flux.

The main goal of this study was the determination of carbon flux model for the area of the Biebrza Wetlands, to evaluate their potential as carbon sinks, based on meteorological, soil and vegetation parameters. Based on ground data and satellite data (images from the Sentinel -1, -2, -3 and MODIS) acquired in 2017–2019, a statistical model was used that combines the carbon dioxide stream, latent heat and soil moisture. The flux of carbon dioxide and latent heat were recorded using the eddy covariance tower, which allows for very high sensitivity measurements at a frequency of 20 Hz. Soil moisture was measured at various points in the Biebrza National Park at a depth of 5 cm with a time resolution of 15 minutes. Later, the field parameters were replaced with their satellite equivalents (e.g. soil moisture - [1]), which made it possible to obtain carbon dioxide flux values for any point within the park. The assessment of carbon fluxes is performed at 1-km spatial scale. Carbon measurements done by the chamber method were used to verify the model. All data were extracted using a R programming language script. Further analyses were carried out in R and Statistica program, the satellite image processing was performed using a ERDAS and program R.