Agata Jaroń

Civilisational progress contributes to an increase in the number of vehicles on the road, thereby intensifying air pollutant emissions and accelerating the degradation of the natural environment. Effective protection of urban areas against air pollution enhances safeguarding against numerous allergies and diseases resulting from unplanned and unintended absorption of harmful pollutants into the human body. Sustainable urban planning requires the collaboration of multiple scientific disciplines. In this context, measurement becomes crucial, as it reveals the spatial scale of the problem and identifies existing disparities. This study uses an integrated approach of standard measurement methods and statistical and geostatistical data analysis, identifying PM₁ fractions that are not included in EU air quality monitoring. The hypothesis explores how surface-based results correspond to point-based results from national air quality monitoring. The presented implications demonstrate similarities and differences between the studied measurement methods and the spatial distributions of PM₁₀, PM_2.5, and PM₁ dust.

Profiling pollutant distributions contributes to a deeper understanding of the diffusion of traffic air pollution, with road transport being a significant source of air pollution. The available literature presents numerous methods for analyzing air pollution distributions resulting from vehicular transport. However, these studies primarily focus on simulated conditions rather than real-world field measurements. This study examines real-world field measurements of air pollution near a highway in Poland using an unmanned aerial vehicle (UAV) platform across different seasons. The UAV platform was equipped with a semiconductor laser sensor for measuring air pollutants such as SO2, CO2, NxOy, O3 and PM10, PM 2.5 and PM1. Although there are many works on profiling pollutants, this is the first such attempt to visualize pollutants in Poland, along with comparing the indications to the National Air Pollution Monitoring. By applying Spearman’s correlation coefficient, the study assesses the correlation of pollutant concentrations within the vertical profile from a street canyon and conducts pollution mapping. Observations indicate that in spring, summer, and autumn, pollutant concentrations decrease with altitude. However, in winter, a “pollution cloud” was detected at an altitude of 20–30 m, while concentrations above this threshold declined. The findings provide valuable insights for developing recommendations to protect public health. In the future, they may be used to properly manage urban infrastructure in order to protect the population from the negative effects of air pollution.

The aim of this study was to analyze long-term trends and spatial variability of PM10 concentrations in Poland during the period 2019–2024, based on data from the European Air Quality Monitoring System (EAQ). The analysis covered nine locations representing three types of areas: large agglomerations (Warsaw, Kraków, Katowice), medium-sized cities (Wrocław, Poznań), and spa towns (Ciechocinek, Lądek-Zdrój, Świnoujście). An integrated statistical approach was applied, including Welch’s ANOVA, Linear Mixed Models (LMM), Generalized Additive Models (GAM), and Quantile Regression (FDR–BH). Mean PM10 concentrations in the analyzed period ranged from 17.43 µg/m³ in Świnoujście to 31.16 µg/m³ in Kraków, with 30.17 µg/m³ in Katowice and 27.90 µg/m³ in Warsaw. The largest differences between locations were observed during smog episodes —the 90th percentile values reached 56.61 µg/m³ in Kraków, 49.99 µg/m³ in Katowice, and 29.19 µg/m³ in Świnoujście. In most locations, a downward trend in PM10 levels was recorded over time; however, regional differences persist. The GAMs confirmed strong seasonality (winter maximum, summer minimum), while quantile regression indicated that the highest risk of smog episodes occurs in southern Poland. The novelty of this study lies in the integration of three complementary modeling approaches (LMM, GAM, and Quantile Regression) in the analysis of the spatio-temporal variability of PM10, as well as in the innovative comparison-unique in the literature-of agglomerations, medium-sized cities, and spa towns in Poland based on a uniform, reference EAQ dataset. This approach made it possible to reveal persistent environmental disparities of significant relevance to the national anti-smog policy and enables a more realistic assessment of environmental risk within the European research context.

Road transport is a significant source of pollution, accounting for up to 25% in the EU. Traffic pollution resulting from the movement of vehicles harms human health. Therefore, it is important to understand the process of spreading harmful substances from the source of their formation. This article presents an original method for measuring pollution in the roadside area for a key road in the Silesian Voivodeship. The focus was on determining the mathematical dependencies related to the diffusion of pollutants from the selected road section. The determined correlations may contribute to the implementation of traffic route projects, which can reduce air pollution. A key innovation of this study is the use of an unmanned aerial vehicle equipped with air quality sensors to perform spatial pollution measurements near a highway. This method enables a high-resolution, three-dimensional assessment of pollutant dispersion, which is then compared to conventional point-based data from the Chief Inspectorate of Environmental Protection (GIOŚ). This novel approach not only improves measurement coverage but also provides new insights for air quality modeling and environmental planning.

Achieving climate neutrality has become an environmental goal for all European Union (EU) Member States. Thanks to numerous projects and subsidies, EU countries are able to achieve the goal of decarbonizing energy sources. The aim of the presented study is to assess the validity of Member States’ actions to reduce CO₂ emissions based on data provided by Eurostat. The presented study combines, using regression, data on financial outlays dictated by environmental protection, the share of renewable energy, and total CO₂ emissions in individual Member States. This study has shown that, despite differences in the use of energy sources, Member States are able to achieve economic growth in symbiosis with the environment.

Environmental protection is a pivotal element of sustainable development, both essential and indispensable in the construction of smart, green cities. Road transport contributes significantly to atmospheric pollution, accounting for as much as 25% of annual emissions within the European Union (EU). To combat the adverse effects of road transport, the EU has set targets to reduce greenhouse gas emissions from both passenger and commercial vehicles. Consequently, sustainable air pollution management has become a focal point for numerous researchers. This study continues the investigation into the distribution of air pollutants along a specific highway segment in Poland. The article addresses two primary research questions: first, the temporal and spatial variations in air pollution adjacent to a major highway in Poland, and second, whether emission levels exhibit significant annual differences and if there is a correlation between pollutant concentrations and the distance from the roadway. The findings offer valuable data on one of the principal substances polluting the air along EU transportation routes. Moreover, the analysis provides recommendations for future road infrastructure renovation projects and strategies to protect the public from harmful traffic-related pollutants, thereby supporting the development of green cities in accordance with sustainable development principles.

Sustainable development and the creation of smart, green cities requires cooperation in many scientific fields, including those related to ecology, mobility, or sustainable management, among others. Environmental protection is a particularly important element here. Atmospheric pollution, due to air movements, spreads over very large areas; therefore, air quality monitoring is crucial to ensure protection from harmful substances. One of the most severe sources of air pollution, accounting for as much as approximately 25% of total annual emissions within the EU, is road transport. Therefore, the European Union has set an ambitious target to reduce total emissions to 55% for cars and 50% for vans by 2030. In recent years, unmanned aerial vehicles (UAVs) have become increasingly popular in many scientific fields, including environmental protection and photogrammetry. The use of UAVs to identify harmful pollutants allows them to gain an advantage over conventional detection methods, due to the possibility of remote (therefore safe for humans), faster, and area-based measurements. Given the ever-expanding scale of the use of this technology, this paper presents the possibilities of using UAVs to identify and visualize (map) pollution. The examples presented in the foreign literature, as well as our own research, in imaging the altitude distribution of air pollutants; gaseous pollutants: C₆H₆, HCHO, SO₂; and particulate matter: PM₁, PM_2.5, PM₁₀ demonstrate the validity of such measures. This research was carried out in the area of one of Poland’s key A4 highways. The maps obtained allow for an area-wise and altitude-wise presentation of one of the significant air pollutants in the EU. In addition, they can be a valuable source of information for the implementation of future projects and the improvement of road infrastructure, thus contributing to the reduction of air pollution and the creation of so-called “green cities”.

The study analyzed the impact of the COVID-19 pandemic on the carbon dioxide emissions from electricity generation. Additionally, monthly seasonality was taken into account. It was assumed (research hypothesis) that both the COVID-19 pandemic (expressed in individual waves of infection cases) and the month have a significant impact on CO₂ emissions. Analysis of variance (ANOVA) and non-parametric Kruskal–Wallis tests were used to evaluate the significance of the influence of individual explanatory variables on the CO₂ emission. The identification of the studied series (CO₂ emission) was first made by means of a linear regression model with binary variables and then by the ARMAX model. The analysis shows that in the consecutive months and periods of the COVID-19 pandemic, CO₂ emissions differ significantly. The highest increase in emissions was recorded for the second wave of the pandemic, as well as in January and February. This is due to the overlapping of both the increase in infections (favoring stays at home) and the winter season. It can be concluded that working plants, schools and factories had the same demand for electricity, but sources of increased consumption were people staying at home and in hospitals as a result of deteriorated health, isolation or quarantine.

Cel pracy: Celem pracy była ocena zmian stężeń wybranych jonów w wodach zbiorniku zaporowego Słupsko oraz określenie jego roli jako „osadnika wstępnego” dla zbiornika Pławniowice. Materiał i metody: Określenia czynników wywołujących te zmiany dokonano na podstawie pomiaru...