Effective and accurate modeling of air quality in complex terrain constitutes one of the main challenges for the community of modelers. One of the basic problems is the selection of input data of adequate quality in combination with a uniform configuration of the modeling systems. Simultaneously, the primary aim is to obtain predictions of satisfying accuracy. In the article the results of the evaluation for the CALMET/CALPUFF modeling system in near-field and complex terrain were presented. Research was conducted based on three experimental databases for the dispersion model evaluation, i.e. Martin's Creek (SO2), Lovett (SO2) and Tracy Power Plant (SF6). Each experiment concerned an area characterized by different topography, meteorological conditions, emission source features and the location of tracer substance monitors (SO2, SF6). The aim of the study was to determine the optimal settings for the CALMET/CALPUFF models with regard to the digital elevation model dataset (GTOPO30, SRTM3, NED), grid resolution (ranging from 100 to 4000 m) and the terrain adjustment methods available in the CALPUFF model (MCTADJ = 0, 1, 2 and 3). The results of the CALMET/CALPUFF accuracy evaluation showed, that the use of the digital elevation model (DEM) with a horizontal accuracy of approximately 90 m and a vertical accuracy of 15 m (SRTM3) is sufficient. Application of more accurate data (NED) resulted in comparable model evaluation outcomes. Using both dense and coarse grids resulted in FB and/or FBRHC higher than 0.6. Omitting the terrain adjustment method in the CALPUFF model results in the twofold underestimation of the measurements. The best results of the CALMET/CALPUFF accuracy evaluation for each experiment (|FB| < 0.30, FAC = 1.0, NAD ≤ 0.15, VG < 1.12, IOA > 0.5) were achieved for the grid resolution of 400 m with the use of a partial plume path adjustment method (MCTADJ = 3).

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.

The paper discusses the role of wind speed and mixing-layer height in shaping the levels of pollutant concentrations in the air of Krakow (Southern Poland). The hourly averaged measurements of concentrations of selected air pollutants and wind speed values from the period of 2014-2015, recorded at two of the air quality monitoring stations within Krakow (both industrial and urban background) were used for this purpose. Temporal variability of mixing-layer height in the area of the monitoring stations was determined using numerical modelling with the CALMET model and the measurements derived from, i.a., two upper air stations. It was found that wind speed and mixing-layer height are in at least moderate agreement with the concentration values for some pollutants. For PM10, PM2.5, NO2, NOx, CO and C6H6 correlation coefficient is of negative value, which indicates that the low wind speed and low mixing-layer height may be the dominant reason for elevated concentrations of these substances in the air, especially in the winter months. Moderate but positive correlation was found between O3 concentrations and analysed meteorological parameters, proving that the availability of appropriate precursors and their inflow from the neighbouring areas have an important role in the formation of tropospheric ozone. On the other hand, in case of SO2, a weak both positive and negative correlation coefficient was obtained, depending on the period and location of the station concerned

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.

The AERMET/AERMOD (American Meteorological Society (AMS)/EPA Regulatory Model) dispersion modeling system constitutes a tool recommended by the United States Environmental Protection Agency (U.S. EPA) both for flat and complex terrain in a local scale with a distance of 50 km. This model requires several input data for pollutant prediction. As part of the research, the effectiveness evaluation of the AERMOD model was conducted based on two of the model evaluation databases (Martin’s Creek and Lovett) depending on different available DEM sources. The analysis involved comparison of different modeling results obtained with the application of different DEM datasets, i.e. NED (National Elevation Dataset), ASTER (Aster Global Digital Elevation Model), SRTM (Shuttle Radar Topography Mission) and USDEM (US GeoData Digital Elevation Models). Achieved outcomes indicated, that the use of different elevation datasets did not influence the evaluation results of the AERMOD model in a local scale and complex terrain significantly. Regardless of the field experiment and DEM dataset, for each case the values of FB and FB_RHC fell within the range of ± 0.33. The highest values of the model performance measures reached 0.89 – 0.91 for IOA and 0.78 – 0.81 for COE in the case using the NED dataset. Slightly worse model performance was observed for the SRTM data with IOA equal to 0.82 – 0.91 and COE reaching 0.64 – 0.83.