Urban heat island (UHI) is one of the most distinctive characteristics of urban climate. The objective of the presented study was to apply a statistical modelling of the nocturnal atmospheric UHI based on the relationship between observed air temperature from ground stations and remotely-sensed temperature of the urban surface. The goal of the approach was to limit input data for the developed modelling method in order to assure transferability of the methodology to different cities. Time series of surface temperature and NDVI were obtained from the MODIS instrument for a 10 year period (2008-2017). The air temperature was collected from the in-situ observational network of 21 stations. The study was conducted for different locations with gradual changes in urbanization in order to assess the impact of urbanization on the relationship between simultaneous air and surface UHI. The urbanization was described by commonly available land cover metrics. Results showed that the proposed approach provided satisfactory AUHI modelling results for the locations with the least degree of urbanization. The best results were obtained with a simple linear regression model with the iterative procedure to minimize the mean absolute gross error (MAGE). The lowest MAGE for modelled UHI was 1.18°C with 69% of the variance explained. The strongest linear relationship between simultaneous SUHI and AUHI was noted for those station pairs which their surroundings have the highest differences in urbanization, and the highest UHI intensities observed. The strength of the SUHI/AUHI linear relationship decreases gradually with the increasing urbanization of the stations' surroundings.

For many years, the Polish air quality modelling system was decentralized, which significantly hampered the appropriate development of methodologies, evaluations, and comparisons of modelling results. The major contributor to air pollution in Poland is the residential combustion sector. This paper demonstrates a novel methodology for residential emission estimation utilized for national air quality modelling and assessment. Our data were compared with EMEP and CAMS inventories, and despite some inequalities in country totals, spatial patterns were similar. We discuss the shortcomings of the presented method and draw conclusions for future improvements.

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.

Assessment of the concentrations of dust pollution resulting from both measurements at reference stations and those determined using mathematical modelling requires accurate identification of the sources of emission. Although the concentration of dust results from several complex transport processes, as well as chemical and microphysical transformations of aerosols, sources of emissions may have a significant impact on the local level of pollution. This pilot study aimed to use measurements of the concentrations of dust (with the specification of the PM10 and PM2.5 fractions) made over a heap/excavation and its surroundings using an airship equipped with equipment for testing the optical and microphysical properties of atmospheric aerosols, and a ground station located at the facility. On the basis of the measurements, the function of the source of emissions of dust was estimated. According to our study, the yearly emission of dust varies between 42,470 and 886,289 kg for PM10, and between 42,470 and 803,893 for PM2.5 (minimum and maximum values). A model of local air quality was also used, which allowed us to verify the parameterization of emissions of dust pollutants for the PM10 and PM2.5 fractions from heaps and excavations based on the modelling results.