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The paper presents the possibilities of selected functions from openair package for R programming environment in urban air pollution assessment. Examples of data analysis were based on the measurements from continuous air quality monitoring stations in Krakow (Poland). In order to present additional functionality of this software, modeling results of back trajectories and air pollution dispersion were used. Functions and visualization methods included in openair package make scrutiny of large data sets easier and less time consuming. They allow for analysis of measurement data with the determination of general relationships between parameters, additional complex spatial analyses for back trajectories, and validation of air pollution dispersion models. Openair package is, therefore, a valuable and functional tool that can be successfully used as a support in the air quality management system.

Abstract. Scientific research studies conducted in various parts of the world confirm that PM10 concentrations in urban air depend to a great extent on the resuspension processes of the dust deposited on the road surface. The paper presents the results of the study related to the determination of the re-entrained PM10 emissions from four selected streets of Krakow (Southern Poland) together with the assessment of its impact on air quality. Examined streets are characterised by different traffic intensity (from 500 to over 20 000 vehicles per day) and individual vehicle structure. Dust material sampling and estimation of the PM10 emission were conducted according to the U.S. EPA methodology (AP 42 Fifth Edition). Two variants of sample collection were applied: from the road surface including the area at the curb (4 streets) and from the road surface alone (1 street). The estimates of resuspended road dust emission as well as the reference values derived from the U.S. EPA guidelines were used to assess the impact of this emission on the PM10 levels in the air at the location of one of the analysed streets. This assessment was conducted using the CALINE4 mathematical model. The study showed that the PM10 emissions from the re-entrained road dust can be responsible for up to 25 % in the winter and 50 % in the summer of the total PM10 concentrations in the air near the roads.

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.

Advanced dispersion models, taking into account information on the relief and land cover, as well as temporal and spatial variability of meteorological conditions, are beginning to play an increasingly important role in the assessment of the impact on the air quality. There are numerous spatial databases which can be used in this type of a calculation process, however, there is no answer to the question of how the use of appropriate data set of terrain characteristics affects the results of the distribution of air pollutant concentrations at the surface of the ground. This paper presents two different sets of spatial data of the relief and land cover. Then, their impact on the results of modeling the propagation of pollutants in the ambient air was characterized, using the meteorological processor CALMET and the dispersion model CALPUFF. The obtained results of concentrations in the adopted calculation area were compared on the basis of statistical indicators used to assess pollution dispersion models contained in the statistical package BOOT Statistical Model Evaluation Software Package Version 2.0. The obtained results of calculations of the maximum 1-hour concentrations, the maximum 24-hour mean concentrations and annual mean concentrations for the prepared computational grids with a resolution of 1×1 km were analyzed.

Assessment of the impact on air quality for combustion sources should be carried out using advanced modelling systems with chemical transformation modules taken into account, especially for the facilities characterized by significant emission of gaseous air pollutants (including SO2). This approach increases the reliability of the obtained evaluation results by modelling the formation of secondary inorganic aerosol (SIA) in the air which can substantially contribute to PM10. This paper assesses in this regard selected chemical transformation modules (MESOPUFF, RIVAD/ARM3, ISORROPIA/RIVAD) available in the CALPUFF model (v. 6.42) and its application in the atmospheric dispersion modelling of air emissions from a coal-fired large combustion plant (LCP) not equipped with a flue gas desulphurization (FGD) system. It has been proven that consideration an additional mechanism of secondary sulfate aerosol formation in aqueous phase in the ISORROPIA/RIVAD module (AQUA option) causes a significant increase in the annual average concentration of PM10 in the air compared to the other considered options, along with the calculation variant which excludes chemical transformation mechanisms. Type of the selected chemical transformation module has no significant effect on the results of modelled NO, NO2 and NOx concentrations in the air. However, it can lead to different SO2 results, especially for annual averaged, and in some points, for the hourly averaged concentrations.

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One of the elements of strategy aimed at minimizing the impact of road transport on air quality is the introduction of its reorganization resulting in decreased pollutant emissions to the air. The aim of the study was to determine the optimal strategy of corrective actions in terms of the air pollutant emissions from road transport. The study presents the assessment results of the emission reduction degree of selected pollutants (PM10, PM2.5, and NOx) as well as the impact evaluation of this reduction on their concentrations in the air for adopted scenarios of the road management changes for one of the street canyons in Krakow (Southern Poland). Three scenarios under consideration of the city authorities were assessed: narrowing the cross-section of the street by eliminating one lane in both directions, limiting the maximum speed from 70 km/h to 50 km/h, and allowing only passenger and light commercial vehicles on the streets that meet the Euro 4 standard or higher. The best effects were obtained for the variant assuming banning of vehicles failing to meet the specified Euro standard. It would result in a decrease of the yearly averaged PM10 and PM2.5 concentrations by about 8–9% and for NOx by almost 30%.