Air pollution in urban-industrial areas is caused by simultaneous impact of many factors, including different types of emission sources. Ambient air quality in Krakow is a crucial problem regarding the regularly occurring exceedances of limit values of particulate matter and some of its chemical compounds. This paper presents quantification of urban, suburban and industrial background of dust substances concentrations that are present in the industrialized area, located in the vicinity of scattered household and road traffic emission sources. There were included the concentrations of such substances as: particulate matter (PM10), benzo(a)pyrene, arsenic, cadmium, lead and nickel. The impact of daytime and season of the year (especially heating and non-heating season) on variability of air pollutant concentrations was examined. In order to distinguish between local and inflow background of air pollutants the additional meteorological data concerning wind speed and direction was considered. The performed analyses included application of statistical methods, among others principal component analysis (PCA). Some of the results were visualized via R programming environment, providing tools for air pollution data processing (openair package). The backward trajectories modelling using HYSPLIT model, allowed the validation of wind direction analyses. The conducted research revealed the strong dependence of air pollution background type influencing the measurement results on instantaneous wind direction.
In cities with an extensive air quality monitoring (AQM) system, the results of pollutant concentration measurements obtained in this system can be used not only for current assessments of air pollution, but also for analyzes aimed at better identification of factors influencing the air quality and for tracking trends in changes taking place in this regard. This can be achieved with the use of statistical methods that allow for the assessment of the variability of measurement data observed at stations of various types and for the determination of possible interdependencies between these data. In this article, an analysis of this type was carried out for traffic, urban background and industrial AQM stations in Krakow (Southern Poland) operating in the years 2017–2018 with the use of, i.a., cluster analyzes, as well as dependent samples t-test and Wilcoxon signed-rank test, taking into account the concentrations of air pollutants such as fine particulate matter (PM10), nitrogen dioxide (NO2), benzene (C6H6) and sulfur dioxide (SO2). On the basis of the conducted analyzes, similarities and differences were shown between the data observed at individual types of stations, and the possibilities of using them to identify the causes of the observed changes and the effects of remedial actions to improve air quality undertaken recently and planned in the future were indicated. It was found that the air concentrations of some substances measured at these stations can be used to assess the emission abatement effects in road transport (NO2, PM10 or C6H6), residential heating (PM10 or SO2), and selective industrial plants (SO2, NO2 or C6H6).
The exceedance of air quality standards in urban agglomerations leads local communities to take actions that aim to improve aerosanitary conditions. For these actions to be efficient, it is essential to regularly collect accurate quantitative data that is able to characterize the degree of ambient air pollution. In order to achieve this objective, air quality monitoring systems are constantly being extended. In this paper, the usefulness of newly established air quality measuring stations in Krakow was examined. The assessment was carried out using statistical methods on the basis of the spatial and temporal variability of particulate matter (PM 10) air concentrations over the period of 2016-2017. In the analysis, meteorological data (wind directions) were applied. The main part of this assessment was a pairwise comparison of the PM 10 concentrations measured at particular stations. The differences between the average values and the Pearson correlation coefficient were considered. In order to verify the statistical significance of the obtained results, the t-Student test was conducted. The greatest absolute differences between the measured values occurred during the autumn-winter period (heating season). Notwithstanding the foregoing, a high variability was also observed among the traffic stations.
Abstract. The paper presents a comparison of air pollutant concentrations in three cities in South-Eastern Poland (Krakow, Tarnow and Rzeszow) using statistical analyses and backward trajectory modelling (the HYSPLIT model). The analyses were based on particulate matter (PM10), nitrogen dioxide (NO2) and sulphur dioxide (SO2) levels as well as meteorological data from year 2017. The performed analyses revealed, among others, that the PM10 and SO2 concentrations in the air depend on the season of the year, while the NO2 concentrations are seasonally independent, which is mainly associated with emissions from road transport. Air quality in the analysed cities depends on local meteorological conditions and the structure of emission sources, including the inflowing background. The most unfavourable situation regarding high concentrations of PM10 and NO2 occurs in Krakow. For all analysed urban background stations very similar low SO2 air concentrations are observed which proves the decreasing significance of emissions from coal combustion sources.
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