A database of monthly mean air temperature data collected in Ukraine has been created. The database contains records of 514 stations, which were working at one time or another during the period 1812-2014. Metadata have also been collected using the available descriptions of the stations' histories. Regular observations at a sufficiently large number of stations contained in the database began in the early 1880s. However, due to the disruptions that occurred during World Wars I and II and resulted in a lot of missing data, a reliable homogenized data set can be obtained only for the period 1946-2014. For this period, we have homogenized the data from 178 stations by means of the HOMER software. The total number of breaks that we have identified is 287. However, only approximately 31% of them can be explained by the station relocations or other reasons. The shift magnitudes in annual series do not exceed ±1 ∘ C with the small negative mean value. Therefore, on average, the inhomogeneities of the time series have an effect of increasing the past temperature slightly over the territory of Ukraine and, consequently, decrease the rate of the temperature rise. The trend analysis of the raw and homogenized time series confirms this conclusion. The homogenized data show a more realistic pattern of the spatial distribution of the temperature tendencies, in contrast to many artificial spots of higher or lower trend values in the raw data. After the homogenization, the areas with insignificant trends were considerably reduced.

Digital databases of monthly means of daily extreme, minimum (Tn) and maximum (Tx) air temperature collected in Ukraine were created. The databases contain temperature records of 371/340 (Tn/Tx) climatological stations which recorded data on the territory of Ukraine anytime during 1881-2015. The significant part of the data sets (~48/47%) was obtained after conducting a data rescue process, recovering historical paper records. Due to a great deal of missing data during World War I and II, homogenization was possible to perform only for 178 time series covering the period of 1946-2015. A homogenization procedure, conducted by means of the HOMER software, revealed 323 break points for minimum temperature (~1.8 breaks per station) and 310 for maximum temperature (~1.7 breaks per station). Approximately 37/33% (Tn/Tx) of the breaks can be explained by metadata. Shift amplitudes in Tn time series ranged between −1.18 and 1.71 C, while for maximum temperature the range was slightly less from −0.99 to 1.15 C. For both temperatures, mean values of shift amplitudes were near zero (−0.04/−0.05 C). To validate the homogenization results, several statistical procedures were performed to compare inhomogeneous and homogeneous time series. The conducted statistical calculations provide the proofs that inhomogeneity of the Ukrainian extreme air temperature data should be taken into account when analysing regional climate change and variability. K E Y W O R D S extreme (minimum/maximum) air temperature, homogenization of time series, HOMER software, Ukraine

The paper analyzes air quality changes in Ukraine during a wildfire event in April 2020 and a dust storm episode during the 16th of April 2020. The wildfire event contained two episodes of active fires and huge pollutants' emission: 4-14 April and 16-21 April, respectively. Using the Sentinel-5P data of CO and NO 2 column number density and ground-based measurements, there was estimated air quality deterioration. Advection of polluted air masses and analysis of affected territories were made in combination with a Web-based HYSPLIT model. Satellite data described air quality changes better than in-situ measurements. Data intercomparison showed better coincidence in regions that were not affected by wildfire emissions. The paper described the dust storm event based on absorbing aerosol index (AAI) data that occurred between two wildfire episodes.

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The procedure of anthropization extent modeling for landscapes and/or physic-geographic taxons was implemented for the specified megaregion. It includes Ukrainian physic-geographic zones of mixed and broad-leaved forests and forest-steppe. The spatial data bases (SDB) were organized for the implementation megaregion by appropriate geoinformation processing of up-to-date open digital spatial data sources. The implementation operating scale of anthropization extent for physic-geographic taxons was substantiated and created in accordance with the megaregional SDB. The scale embodies 55 operating land use and/or land cover (LULC) systems causing determinate anthropization extent. The last is presented by corresponding to mentioned systems anthropization categories and indexes. The operating scale was strictly implemented for the megaregion. The implementation included the anthropization extent modeling at the level of physic-geographic areas and districts. The interpretation of the obtained model results was carried out. The results display that the land use consequences are altogether unfavorable for the natural environment of the megaregion. Environmental Research, Engineering and Management 2018/74/2 68The model implementation achievements indicated the relevance and objectivity of proposed approaches to the landscape anthropization extent modeling. The approaches are applicable to schemes and projects of environmental management.