The Poland-AOD aerosol research network was established in 2011 to improve aerosol–climate interaction knowledge and provide a real-time and historical, comprehensive, and quantitative database for the aerosol optical properties distribution over Poland. The network consists of research institutions and private owners operating 10 measurement stations and an organization responsible for aerosol model transport simulations. Poland-AOD collaboration provides observations of spectral aerosol optical depth (AOD), Ångstrom Exponent (AE), incoming shortwave (SW) and longwave (LW) radiation fluxes, vertical profiles of aerosol optical properties and surface aerosol scattering and absorption coefficient, as well as microphysical particle properties. Based on the radiative transfer model (RTM), the aerosol radiative forcing (ARF) and the heating rate are simulated. In addition, results from GEM-AQ and WRF-Chem models (e.g., aerosol mass mixing ratio and optical properties for several particle chemical components), and HYSPLIT back-trajectories are used to interpret the results of observation and to describe the 3D aerosol optical properties distribution. Results of Poland-AOD research indicate progressive improvement of air quality and at mospheric turbidity during the last decade. The AOD was reduced by about 0.02/10 yr (at 550 nm), which corresponds to positive trends in ARF. The estimated clear-sky ARF trend is 0.34 W/m²/10 yr and 0.68 W/m²/10 yr, respectively, at TOA and at Earth’s surface. Therefore, reduction in aerosol load observed in Poland can significantly contribute to climate warming.

One of the most important minor species in the atmosphere is nitrogen dioxide (NO₂). The primary objective of the presented research was to propose a method to adjust emission inventories (emission fluxes) using tropospheric NO₂ columns observed by OMI and SCIAMACHY instruments. Modified emission fluxes were used in a chemical weather model GEM-AQ. The GEM-AQ model results were compared with the monthly averaged satellite-derived column amount of NO₂ over Europe for the 2008–2010 observing period. It was shown that the observed and modelled spatial distribution of high values of the NO₂ column is highly correlated with the distribution of major anthropogenic sources in the modelling domain. The presented findings highlight the importance of the anthropogenic sources in the overall budget of NO₂ in the polluted troposphere. Regions for which modelling results showed underestimation or overestimation compared with observations were constant for the whole analysis period. Thus, the NO₂ column observations could be used for correcting emission estimates. The proposed emission correction method is based on the differences in modelled and satellite-derived NO₂ columns. Modelling was done for 2011 using the original and adjusted emission inventories and compared with observed NO₂ columns. The analysis was extended to compare modelling results with surface NO₂ observations from selected air quality stations in Poland. A significant improvement in modelling results was obtained over regions with large overestimations in the control run for which the original emission fluxes were used.

The TROPOMI instrument aboard Sentinel-5P is a relatively new, high-resolution source of information about atmosphere composition. One of the primary atmospheric trace gases that we can observe is nitrogen dioxide. Thanks to TROPOMI capabilities (high resolution and short revisit time), one can describe regional and seasonal $N{O}_2$ concentration patterns. Thus far, such patterns have been analysed by either ground measurements (which have been limited to specific locations and only to the near-surface troposphere layer) or numerical models. This paper compares the TROPOMI and GEM-AQ derived vertical column densities (VCD) over Poland, focusing on large point sources. Although well established in atmospheric science, the GEM-AQ simulations are always based on emission data, which in the case of the energy sector were reported by stack operators. In addition, we checked how cloudy conditions influence TROPOMI results. Finally, we tried to link the $N{O}_2$ column number densities with surface concentration using boundary layer height as an additional explanatory variable. Our results showed a general underestimation of $N{O}_2$ tropospheric column number density by the GEM-AQ model (compared to the TROPOMI). However, for the locations of the most significant point sources, we noticed a systematic overestimation by the GEM-AQ model (excluding spring and summer months when TROPOMI presents larger $N{O}_2$ VCDs than GEM-AQ). For the winter months, we have found TROPOMI $N{O}_2$ VCD results highly dependent on the choice of qa_value threshold.

The health impact of air quality has recently become an emerging issue. Many regions, especially densely populated regions, have deteriorating air quality. The primary source of pollution in Poland is the municipal sector. Air pollutants have a negative impact on human health, contribute to premature deaths, and are the cause of various diseases. Over recent years, Europe’s air quality has largely improved due to several measures to reduce pollutant emissions. The following paper presents the impact of annual average PM2.5 and NO₂ concentrations on premature deaths in Poland in 2019. Exposure to PM2.5 caused more than 19 000 premature deaths, and exposure to NO₂ contributed to around 6000 premature deaths in 2019. Taking 2019 as a baseline, the impact of the envisaged implementation of the national Clean Air Programme on the number of premature deaths is analysed. Implementing the mitigation measures focused on replacing inefficient stoves and boilers in individual households would significantly improve air quality, mainly particulate matter. Reducing PM2.5 concentrations would reduce premature deaths by around 3000 cases, while for NO_2, the number of premature deaths would not change much.

A coupled stratospheric chemistry–meteorology model was developed by combining the Canadian operational weather prediction model Global Environmental Multiscale (GEM) with a comprehensive stratospheric photochemistry model from the Belgian Assimilation System for Chemical ObsErvations (BASCOE). The coupled model was called GEM-BACH for GEM-Belgian Atmospheric CHemistry. The coupling was made across a chemical interface that preserves time-splitting while being modular, allowing GEM to run with or without chemistry. An evaluation of the coupling was performed by comparing the coupled model, refreshed by meteorological analyses every 6 h, against the standard offline chemical transport model (CTM) approach. Results show that the dynamical meteorological consistency between meteorological analysis times far outweighs the error created by the jump resulting from the meteorological analysis increments at regular time intervals, irrespective of whether a 3D-Var or 4D-Var meteorological analysis is used. Arguments in favor of using the same horizontal resolution for chemistry, meteorology, and meteorological and chemical analysis increments are also presented. GEM-BACH forecasts refreshed by meteorological analyses every 6 h were compared against independent measurements of temperature, long-lived species, ozone and water vapor. The comparison showed a relatively good agreement throughout the stratosphere except for an upper-level warm temperature bias and an ozone deficit of nearly 15%. In particular, the coupled model simulation during an ozone hole event gives better ozone concentrations than a 4D-Var chemical assimilation at a lower resolution.

This study presents the potential impacts of climate change in 49 Polish cities by analyzing seven climate indicators. The analysis was carried out for the following three horizons: the current climate conditions (an average period spanning 2006 to 2015), near-future conditions (an average period spanning 2026 to 2035), and future conditions (an average period spanning 2046 to 2055). Climate indices were computed with bias-corrected EURO-CORDEX model ensembles from two Representative Concentration Pathway scenarios, RCP4.5 and RCP8.5. The systematic error was reduced using the quantile mapping method with a non-parametric approach of robust empirical quantiles (RQUANT). Data were used as references in the period of current climate conditions, and those required for bias correction consisted of historical ground-based observations provided by the Institute of Meteorology and Water Management. The analysis encompassed various key climate indices, including the annual average temperature, the count of hot days, cold days, and frost days, the cumulative annual precipitation, the frequency of days with precipitation, and instances of extreme precipitation (defined as the days with precipitation exceeding 10 mm/day). These findings reveal a noteworthy rise in the average annual temperature of approximately 1 °C and an uptick in the number of hot days by 3.7 days. Conversely, a decline in the number of cold days by approximately 19 days and frost days by 8 days was observed. Additionally, there was an augmentation in the annual precipitation sum, reaching up to 80 mm in RCP 8.5, accompanied by an increase in the number of days with precipitation (up by 3.3 days) and days with extreme precipitation (up by 2 days).