Road traffic is among the main sources of atmospheric pollution in cities. Maps of pollutants are based on geostatistical models using a digital model of the city along with traffic parameters allowing for ongoing analyses and prediction of the condition of the environment. The aim of the work was to determine the size of areas at risk of carbon monoxide pollution derived from road traffic along with determining the number of inhabitants exposed to excessive CO levels using geostatistical modeling on the example of the city of Bydgoszcz, a city in the northern part of Poland. The COPERT STREET LEVEL program was used to calculate CO emissions. Next, based on geostatistical modelling, a prediction map of CO pollution (kg/year) was generated, along with determining the level of CO concentration (mg/m³/year). The studies accounted for the variability of road sources as well as the spatial structure of the terrain. The results are presented for the city as well as divided into individual housing estates. The level of total carbon monoxide concentration for the city was 5.18 mg/m³/year, indicating good air quality. Detailed calculation analyses showed that the level of air pollution with CO varies in the individual housing estates, ranging from 0.08 to 35.70 mg/m³/year. Out of the 51 studied residential estates, the limit value was exceeded in 10, with 45% of the population at risk of poor air quality. The obtained results indicate that only detailed monitoring of the level of pollution can provide us with reliable information on air quality. The results also show in what way geostatistical tools can be used to map the spatial variability of air pollution in a city. The obtained spatial details can be used to improve estimated concentration based on interpolation between direct observation and prediction models.

Road transport is one among the sources of air pollution in a city, which results in lowering the comfort of life and increases the occurrence of respiratory diseases. The level of pollutants emitted in the city is variable, and it depends on the type and nature of the source and the manner of land development. For this reason, the purpose of the article is an attempt at a spatial (inner) diversification of a city in terms of air quality, using a study of perception and semantic differentials (SD). The research, which covered the period from June to November 2021, was performed in Kielce—the Polish Smart City—among local experts, people well acquainted with the city and knowledgeable about air quality and the impact of pollution on human health. The results allowed the demarcation of areas with the best and the worst parameters in terms of air quality within the city. Verification of the survey was carried out using the ADMS-Roads (Atmospheric Dispersion Modeling System) software for modeling pollution levels and GIS software, using data on road traffic. The verification allowed checking whether the respondents participating in the research accurately evaluated the city space. The modeling proved that within the two selected areas, the pollution level is similar, and it does not exceed the permitted values. This might indicate that in society there is still low awareness of air quality, particularly in terms of knowing the sources of pollutants and their impact on human health, and perception of areas with the best and the worst air quality was the result of an analysis of the manner of land development and its morphology.

Noise as a form of environmental pollution negatively affects the attractiveness of residential areas. Its adverse effect is particularly noticeable in the vicinity of roads with high traffic volume. Along with the dynamic development of roads, the problem of the impact of traffic noise on the prices of residential real estate is now common. The purpose of this article was to determine the impact of road traffic noise from a busy route on residential property prices using strategic noise map (SNM) resources as a source of information on real estate. Housing estate was identified in the area of the Polish city of Bydgoszcz. Assuming that the prices of real estate reflect its characteristics, the article attempts to verify the following hypothesis: for residential premises located at Kujawska St., noise is a feature that reduces their price. SNM resources, statistical analyses and econometric modelling were used in the research. The studies show that housing prices vary with acoustic zones, but differences in prices in the areas surveyed are not statistically significant. In addition, the undertaken research has shown that SNM resources can be a source of information on real estate, especially in the context of environmental factors.

In navigation practice, there are various navigational architecture and integration strategies of measuring instruments that affect the choice of the Kalman filtering algorithm. The analysis of different methods of Kalman filtration and associated smoothers applied in object tracing was made on the grounds of simulation tests of algorithms designed and presented in this paper. EKF (Extended Kalman Filter) filter based on approximation with (jacobians) partial derivations and derivative-free filters like UKF (Unscented Kalman Filter) and CDKF (Central Difference Kalman Filter) were implemented in comparison. For each method of filtration, appropriate smoothers EKS (Extended Kalman Smoother), UKS (Unscented Kalman Smoother) and CDKS (Central Difference Kalman Smoother) were presented as well. Algorithms performance is discussed on the theoretical base and simulation results of two cases are presented.

Urban traffic causes air pollution in the city, contributing to respiratory diseases. For this reason, the article aimed to identify places in the street network where nitrogen oxide (NOX) pollution exceeds the permissible value, i.e., 30 µg/m3, by Directive 2008/50/EC of the European Parliament. The research was conducted during the COVID-19 pandemic during the period of the most significant restrictions in 2020, with most restrictions lifted in 2021. The article presents a method for identifying points with concentrations of air pollutants exceeding the standards in the example of a large Polish city. The research results allowed for precisely identifying places in the city’s street network with the worst air quality parameters. Hence, the article aimed to identify areas with the worst air quality parameters in terms of NOX emissions, which will enable actions that may reduce the pollutants examined. The research used the ADMS atmospheric dispersion modeling program, a road traffic database obtained from the Sydney Cooperative Adaptive Traffic System, and Geographic Information System programs. The number of identified points with NOX pollution exceeding the permissible EU standard in 2020 (during the Covid-19 pandemic) was in the range of 30.00–79.42 µg/m3 was 771, while after the pandemic it ranged from 30.06 to 97, 91 µg/m3 428. The proposed method for precise point identification of NOX pollutants caused by road traffic is a universal tool for detecting and analyzing pollutants in urban agglomerations.