
==== Front
Heliyon
Heliyon
Heliyon
2405-8440
Elsevier

S2405-8440(24)12881-2
10.1016/j.heliyon.2024.e36850
e36850
Research Article
Contribution to the study of possible transport of PM10 aerosols in the eastern part of the Czech Republic
Volná Vladimíra vladimira.volna@chmi.cz
⁎
Blažek Zdeněk
Czech Hydrometeorological Institute, Air Quality Department, K Myslivně 3/2182, Poruba, 708 00, Ostrava, Czech Republic
⁎ Corresponding author. vladimira.volna@chmi.cz
24 8 2024
15 9 2024
24 8 2024
10 17 e368505 3 2024
15 8 2024
22 8 2024
© 2024 The Authors. Published by Elsevier Ltd.
2024

https://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
The article deals with the assessment of air pollution in the eastern regions of the Czech Republic: Moravia and Silesia, where the limits for the protection of human health for PM and benzo[a]pyrene are significantly exceeded, especially in the north-eastern area. The extent to which this heavily polluted part of Moravia and Silesia affects the central, southern and south-eastern parts of Moravia, i.e. south-eastern part of the Czech Republic, has often been discussed but not proven. The assessment demonstrated the influence and extent of pollutant transport by determining the prevailing daily wind direction. The prevailing NE wind direction results in worse dispersion conditions and higher PM10 concentrations throughout the study area. Conversely, the SW wind direction is a carrier of better dispersion conditions with lower PM10 concentrations in the area. The effect of transport of PM10 pollution in the daily type from the NE direction can be observed at those sites located in the NE of the area of interest from the border with Poland to the Prerov site. In the case of more southerly sites, the methodology used does not allow to determine whether and to what extent they are affected by pollution transport from the northeastern part of Moravia or from neighbouring Poland. This methodology is particularly useful when only 24-h pollutant concentrations are available (not at more detailed, e.g. 1-hour intervals). The internal methodology of the Czech Hydrometeorological Institutefor calculating back trajectories of wind from ground stations is particularly applicable for detecting the origin of short-term episodes with high pollutant concentrations.

Keywords

Air pollution transport
Back trajectories
Daily wind type
Prevailing wind direction
==== Body
pmc1 Introduction

The aerosol fraction PM10 is a problematic pollutant with a wide range of effects on human health (mainly on the respiratory and cardiovascular systems of the human body) [[1], [2], [3], [4]]. The hazards of this pollutant lie not only in its quantity, in high concentrations, but also in the morphology of the particles and their qualitative composition. Suspended particles are capable of forming bonds which can, of course, lead to the transfer of a number of other elements, such as heavy metals and polycyclic aromatic hydrocarbons, to the human body. The effects on the human body of some of these transported substances (e.g. benzo[a]pyrene and heavy metals) have been clinically demonstrated to be adverse, particularly in terms of carcinogenesis [[1], [2], [3], [4]].

The Ostrava-Karvina agglomeration, located in the centre of the Ostrava basin in the north-eastern part of the Czech Republic, is one of the most polluted areas in Europe [[5], [6], [7], [8]]. In addition to its own sources of air pollution, the air quality in the Ostrava-Karvina agglomeration is significantly influenced by sources from the neighbouring Upper Silesia agglomeration in Poland. The area consistently exceeds the applicable outdoor air quality standards [[9], [10], [11], [12]] for aerosol PM10 and benzo[a]pyrene are consistently exceeded [[13], [14], [15], [16]]. Previous work has focused on the assessment of air quality and pollutant transport between the Czech Republic and Poland in the north-eastern part of the Czech Republic and the southern part of Poland [17]. Poland has been shown to have a greater negative impact on air quality in the north-eastern part of the Czech Republic [[18], [19], [20], [21]]. The first such study was carried out within the Air Silesia project [22].

However, the question remains to what extent the territory of the Czech Republic (Eastern Moravia region) is affected by pollution from Poland or from the north-eastern part of the Czech Republic. It was not clear to what extent, if at all, the transport of pollutants from the polluted region in the north-east of the Czech Republic contributes to the air quality in central and southern Moravia. The aim is to assess the extent of interactions between air pollution levels in the whole area of interest. For this purpose, we have used the method of calculating daily wind direction types (for the assessment of daily/24-h PM10 concentrations) and the method of calculating back trajectories (for the assessment of short-term/1-h PM10 concentrations). For both methods, we also determined the suitability of their use.

If we do not také into account the long-range transport of pollutants in the upper layers of the atmosphere, the assumed corridor for the possible transfer of pollutants is the axis in the SW and NE direction given by the orography of the terrain in the area of interest, in particular the location of the Moravian Gate. The Moravian Gate is an elongated depression separating the geomorphological units of the Podbeskydska Hills area (Carpathians) and the Nizky Jesenik (Eastern Sudetes) in the area of interest. It is one of the most important natural links between the Baltic and Danube regions [23]. The stations for the assessment were chosen to follow the axis of the Moravian Gate and to be roughly parallel to the border line between the Czech Republic and Slovakia (Fig. 1).Fig. 1 Location of Air Quality stations included in the evaluation. The inset map in the top left corner indicates the position of the study area within Europe.

Fig. 1

2 Materials and methods

The article uses the results of measurements of daily average concentrations (24-h averages) of PM10 and hourly measurements of wind direction and speed at selected stations of the National Air Quality Monitoring Network [24,25], which is operated by the Czech Hydrometeorological Institute for the period from April 1, 2016 to March 31, 2023. For selected stations with PM10 measurements, where wind measurements were not available, wind direction and speed measurements from the nearest meteorological station of the CHMI were used. Data from stations of the National Air Quality Monitoring Network are stored in the Air Quality Information System database (www.chmi.cz/files/portal/docs/uoco/web_generator/locality/pollution_locality/index_CZ.html), data from meteorological stations are stored in the National Climatological Database CLIDATA (www.chmi.cz/files/portal/docs/poboc/OS/stanice/ShowStations_CZ.html). The list of stations used is given in Table 1, their location is shown in Fig. 1.Table 1 Sites of measurement included in the evaluation (sorted by location – from north to south).

Table 1Used air quality stations	Used meteorological stations	Altitude (m a.s.l.)	Distance between stations (km)	
Vernovice	–	203	–	
Karvina	Karvina	238/224	1,6	
Rychvald	–	241	–	
Studenka	–	231	–	
Belotin	Belotin	306	<0,1	
Prerov	Prerov	210	1,5	
Prostejov	Prostejov	218/217	2,2	
Tesnovice	Kromeriz	280/233	4,3	
Vyskov	Ivanovice na Hane	260/243	8,5	
Brno-Turany	Brno-Turany	241	<0,1	
Kucharovice	Kucharovice	334	<0,1	
Mikulov-Sedlec	–	245	–	

All assessments were made separately for cold seasons (October–March) and warm seasons (April–September). Thus, a total of 7 cold periods (2016/17–2022/23; 1275 days in total) and 7 warm periods (2016–2022; 1281 days in total) were evaluated.

To investigate the dependence of daily mean PM10 concentrations on wind direction, so-called daily wind direction types were used [21]. The methodology for determining daily wind direction types is mainly used in cases where only 24-h concentrations of the given pollutant are available. According to this methodology, each day is assigned to one of the daily wind direction types listed in Table 2.Table 2 The daily type of wind direction.

Table 2Daily type of wind direction	Description	
X	X = N, NE, E, SE, S, SW, W, NW	During a given 24-h period, the prevailing wind direction was from this octant.	
XY	XY = N + NE, NE + E, E + SE, SE + S, S + SW, SW + W, W + NW, NW + N	During a given 24-h period, the prevailing wind direction was almost uniformly from both of these adjacent octants.	
CALM	During a given 24-h period, calm winds prevailed.	
cbd/var	The daily type of wind direction cannot be determined (day with variable wind direction, or with significant change in wind direction during a given 24-h period).	
NIL	Not determined. For a given 24-h period, the number of 1-h wind direction data is less than 18.	

The basic daily type of wind direction X are days on which the wind direction prevails in one of the eight octants of X (the axis of each octant is one of the 8 basic wind directions) (see Table. 3, Table. 3ba,b). For individual groups of days with a given daily type of wind direction according to Tables 2 and in further processing were calculated the frequency of days (wind rose), the mean daily concentration, its confidence interval (calculated using the CONFIDENCE.T function in MS Excel at the 95 % confidence level), and the frequency of days exceeding the daily limit of 50 μg m−3 were calculated for each evaluated site. In addition, the sum of all concentrations measured on days with a given day type was estimated, expressed as a percentage of the sum of all concentrations from all days of the relevant set (weighted concentration increase). Due to the occurrence of days with the daily type of wind direction XY, the evaluation of frequencies and concentration means for eight basic directions, further denoted as N*, NE*, E*, SE*, S*, SW*, W* and NW*, was performed as follows: the frequencies of all days with type X and half of the frequencies of days with neighbouring types XY were included in the given direction X* (e. g. frequency n for NE* = n/NE+½n/(N + NE)+½n/(NE + N)); the mean concentration for days with type X* was calculated as the mean of the concentrations of all days with adjacent types XY and twice the concentrations of days with type X.Table. 3 aRelative frequencies of daily types of wind direction in cold periods 2016/2017–2022/2023.

Table. 3	N*	NE*	E*	SE*	S*	SW*	W*	NW*	Calm + cbd/var	
Vernovice	30.5	7.9	8.7	0.7	3.4	44.0	2.6	11.3	17.9	
Karvina	30.8	9.4	2.9	2.7	3.5	40.3	3.7	9.3	24.4	
Rychvald	90.0	5.6	4.9	1.9	6.3	45.3	1.7	7.2	18.1	
Studenka	11.6	14.5	0.1	0.1	1.6	58.0	4.5	0.6	9.0	
Belotin	7.5	18.2	0.5	0.2	6.6	47.1	7.0	0.8	12.1	
Prerov	3.1	10.4	5.9	2.4	26.2	5.4	4.5	12.5	29.7	
Prostejov	11.1	1.7	1.8	5.9	23.7	7.7	5.8	15.1	27.1	
Kromeriz	8.8	5.8	0.8	12.0	16.5	12.0	6.9	8.3	28.8	
Ivanovice na Hane	9.5	15.0	1.9	0.2	9.7	17.3	21.1	2.4	22.8	
Brno-Turany	4.5	10.5	6.0	14.0	5.8	6.6	9.8	13.7	29.1	
Kucharovice	10.8	2.6	5.8	18.1	3.8	0.8	13.4	22.5	22.3	
Mikulov-Sedlec	15.2	2.9	5.6	12.1	5.3	8.7	23.1	6.8	20.1	

Table. 3b Relative frequencies of daily types of wind direction in warm periods 2017–2022.

Table. 3b	N*	NE*	E*	SE*	S*	SW*	W*	NW*	Calm + cbd/var	
Vernovice	6.1	9.8	11.3	0.4	3.1	18.0	2.5	23.5	25.2	
Karvina	7.2	12.0	3.7	1.9	1.6	18.5	4.1	15.5	35.4	
Rychvald	21.8	7.9	8.2	0.9	7.9	21.4	0.7	8.8	22.4	
Studenka	17.3	22.1	2.8	0.3	2.8	30.5	5.5	1.1	17.7	
Belotin	10.5	29.1	1.7	0.4	6.8	17.4	7.7	1.3	25.0	
Prerov	3.4	13.7	10.2	3.2	15.7	1.8	1.8	17.9	32.2	
Prostejov	14.2	3.7	2.8	5.1	14.1	3.6	3.6	21.0	32.0	
Kromeriz	7.2	9.5	1.5	8.7	11.7	3.9	5.1	13.6	38.7	
Ivanovice na Hane	13.2	21.4	4.2	0.7	9.9	10.0	5.6	2.4	32.6	
Brno-Turany	8.0	11.0	6.6	5.8	3.6	3.5	6.2	17.0	38.3	
Kucharovice	16.4	1.8	2.2	12.4	3.1	0.6	7.9	24.9	30.8	
Mikulov-Sedlec	15.0	2.5	3.5	7.8	4.1	8.8	24.5	7.1	26.8	

The Moravian Gate, which separates the industrial agglomeration of Ostrava-Karvina from Central and Southern Moravia, runs approximately in the direction from NE to SW. Therefore, in addition to the evaluation of PM10 concentrations for the above mentioned daily types X*, the characteristics of PM10 concentrations for the days when the wind direction at the given location was from the so-called extended quadrant (eq) NE or SW (eqNE = N + NE, NE, NE + E; eqSW = S + SW, SW, SW + W) were evaluated together.

Characteristics of PM10 concentrations for eight daily wind direction types (types N* to NW*) and for daily types from the extended quadrant eqNE and eqSW were calculated for all stations from the concentrations measured for the entire cold and warm periods evaluated. In addition, for daily wind direction types from the extended quadrant eqNE, PM10 concentration characteristics were also calculated for subsets of days preceding days with a given daily wind direction type (day 0) and for sets of days with the first and second day of the situation with the same daily wind direction type (day 1, day 2). Mean concentrations and their confidence intervals were calculated for each station and each period for all the above subsets where at least seven mean daily concentrations were available.

The assessment also used back trajectories calculated using the internal methodology of the Czech Hydrometeorological Institute [26]. This is based on the interpolation of wind direction and wind speed at 10-min or 1-h intervals. The calculation uses data from the National Climatological Database CLIDATA [[27], [28], [29]], which includes data from meteorological stations in the Czech Republic and border areas of neighbouring countries. It is therefore able to use all verified and stored wind direction and wind speed data in the database for the Czech Republic at once. This back-trajectory method has the advantage over the HYSPLIT back-trajectory method [30] that it is representative for a height of 10 m above ground. Wind direction and wind speed data from ground based meteorological stations with a standard measurement height of 10 m above ground were used. The application is mainly used to identify the causes of episodes with high pollutant concentrations and to identify pollution sources in areas of interest.

3 Results and discussion

The chapter includes an assessment of daily PM10 concentrations and background information to describe the transport of pollution as a function of wind direction at ground station measurement heights.

3.1 Daily types of wind direction at each station

The relative frequency of days with a daily wind direction type calm on average over all stations is 3.3 % in cold periods and only 0.9 % in warm periods (the frequency of days with calm is greater than 5 % in cold periods only at 3 stations). The relative frequency of days with daily wind direction type cbd/var (cannot be determined/variable) ranges from 9.0 % (Studenka) to 29.7 % (Prerov) in cold periods and from 17.7 % (Studenka) to 38.7 % (Kromeriz) in warm periods (at the same stations as in the case of cold periods). Table. 3, Table. 3ba,b below (and in Fig. S1 in the Supplementary Materials) shows the relative abundances of the eight daily wind direction types and together the relative abundances of the calm + cbd/var types. For the stations located northeast of Prerov, the SW* daily wind direction types are most abundant in cold periods, with frequency greater than 40 %. The daily calm + cbd/var types are most frequent at five stations in cold periods and at all stations except Studenka and Belotin in warm periods.

The assessment of daily PM concentrations in relation to daily flow types was first used in the project "Air quality information system in the Polish-Czech border region of Silesia and Moravia-Silesia” [22]. The main objective of this project was to assess the transboundary transport of pollutants between the Czech Republic and Poland and to quantify the amount of transported pollution. The use of daily wind types and extended quadrants was appropriately used in the evaluation within this project [17]. The stations from the north-eastern part of the Czech Republic included in the project are the same as those used in the evaluation of this work. The predominant relative frequency of wind direction in the cold seasons corresponds to the SW direction, while in the summer seasons it is calm and variable daily type.

Fig. 2, Fig. 3 show the frequencies of the extended quadrant eqNE and extended quadrant eqSW types at each station during the cold and warm seasons. A comparison of the relative frequencies of the extended quadrant eqNE and eqSW types shows that while the frequencies of eqNE are lower in the cold season at practically all stations (except Kucharovice and Mikulov-Sedlec) than in the warm season, the frequencies of eqSW types are significantly higher in the cold season, especially at stations in the north-eastern part of the study area.Fig. 2 Relative frequencies of daily wind direction types, cold season 2016/17–2022/23.

Fig. 2

Fig. 3 Relative frequencies of daily wind direction types, warm season 2017–2022.

Fig. 3

To complement the information on daily wind types, arithmetic averages of mean daily wind speeds at all assessed stations during cold and warm periods are given in Table S1 in the Supplementary Material. Values are given for all days, for days with wind direction eqSW or eq NE and for days with daily wind type calm + cbd/var. These arithmetic means range from 0.7 to 4.3 m s−1 in cold periods and from 0.8 to 3.6 m s−1 in warm periods. For all days and days with wind direction from eqNE, the wind speed is higher at all stations in cold periods. For days with daily wind type eqSW this is true not only at the Prerov and Brno-Turany stations. For days with daily wind type calm + cbd/var, the average wind speed is higher in cold periods only at the stations Vernovice, Rychvald, Studenka and Mikulov-Sedlec.

3.2 Air pollution PM10

The comparison of PM10 concentrations with the applicable limits is shown in Tables S2 and S3 in Supplementary Materials. The annual limit of 40 μg m−3 for PM10 was exceeded in 2017–2018 at the Vernovice station among the stations assessed. The permitted number of 35 days with an exceedance of the daily PM10 concentration limit of 50 μg m−3 was exceeded at the Vernovice, Karvina and Rychvald stations for most of the assessed period, whereas it was not exceeded at all at the stations south of Prerov and Prostejov. The characteristics of PM10 concentration in individual years show a relatively significant decrease in the level of air pollution during the whole assessment period. The mean annual concentrations for the last two years 2021 and 2022 at individual stations are only 70–86 % of the mean concentrations for the first two years 2017–2018. The number of days with daily concentrations above than 50 μg m−3 in 2021–2022 is only 13–60 % of the number in 2017–2018.

Table S4 in the Supplementary Materials shows the basic statistical characteristics of air pollution levels of PM10 concentrations for cold and warm seasons. The mean PM10 concentrations at all stations in the cold seasons were on average about 11 μg m−3 higher than their mean in the warm seasons. The lowest mean concentrations in the cold seasons were reached at the station Kuchařovice, on the contrary, the highest at the station Věřnovice. At individual stations the seasonal mean concentrations in cold periods range from 116 % (Kucharovice) to 191 % (Vernovice) of the seasonal mean concentrations in warm periods. In warm periods, the daily mean concentrations exceed the limit value of 50 μg m−3 only occasionally at most of the stations investigated. In total, 14.7 days with exceedance of the 50 μg m−3 limit value were recorded on average at all stations assessed during a warm period, of which 12.2 days were recorded at Vernovice, Karvina and Rychvald. The main results, the comparison of PM10 concentrations and the seasonal differences are in agreement with the previous work focused on the area of interest of this paper [31,32].

3.3 Dependence of PM10 concentrations on daily wind direction types

Tables S5 and S6 in the Supplementary Materials show the PM10 air pollution levels at each station depending on the eight daily wind types during cold and warm seasons. The tables show the basic statistical characteristics of the mean daily PM10 concentrations depending on the daily wind type. In the cold periods (Table S5 in the Supplementary Materials), when it was possible to evaluate the mean concentration for the daily type of wind calm (N > 6) at a given station, the mean would be the highest. Furthermore, for all stations (except Prerov), the mean PM10 concentration for the daily type of wind direction cbd/var is higher than the total mean concentration at the station regardless of wind direction.

The mean PM10 concentrations at the evaluated stations range from 9 μg m−3 (Kucharovice, W*) to 89 μg m−3 (Rychvald, calm) for each daily wind direction type. The smallest differences between the mean PM10 concentrations for the types N* to NW* are at the station Mikulov-Sedlec (from 13 μg m−3 for W* to 32 μg m−3 for NE*), the largest at the station Rychvald (from 20 μg m−3 for W* to 84 μg m−3 for SE*). The maximum PM10 concentration contributions of each assessed daily wind direction type to the total air pollution level at a given station range from 22 % (Mikulov-Sedlec, N*) to 51 % (Studenka, SW*). The smallest differences between these percentages are for the daily wind direction types N* to NW* at the Brno-Turany station (from 4 % for N* to 15 % for NE*), and the largest at the station Studenka (from 0 % for E*, SE* and NW* to 51 % for SW*).

In warm periods (Table S6 in the Supplementary Materials), it is also true for all stations (except for Belotin) that the mean PM10 concentration for the daily wind direction type cbd/var is higher than the total mean concentration at the station regardless of wind direction. For the daily wind direction type calm, this mean is the highest only at the Karvina station (but N < 7 at half of the evaluated stations). The mean concentrations at the evaluated stations for the individual daily wind direction types range from 11 μg m−3 (Vyskov, NW*) to 34 μg m−3 (Karvina, calm).

The smallest differences between mean PM10 concentrations for types N* to NW* are at the Prerov station (from 15 μg m−3 for NW* to 21 μg m−3 for E*), and the largest at the Studenka station (from 11 μg m−3 for NW* to 26 μg m−3 for E*). The maximum contribution of PM10 concentration of each assessed daily wind direction type to the total air pollution level at a given station ranges from 22 % (Rychvald, cbd/var) to 48 % (Brno-Turany, cbd/var). The smallest differences between these percentages are for the N* to NW* types at the Tesnovice station (from 2 % for E* to 12 % for S*), and the largest at the Belotin station (from 0.5 % for SE* to 33 % for NE*). As the daily mean PM10 concentration of 50 μg m−3 is exceeded only sporadically in the warm season (Table S4 in Supplementary Materials), the seasonal mean number of days with daily mean PM10 concentrations >25 μg m−3 is shown in Table S6 (in the Supplementary Materials).

Table 4 shows the differences between the contribution of PM10 to air pollution at the assessed stations on days with the indicated daily wind direction type and the relative frequency of this type. Differences greater than +3 and less than −3%, respectively, are highlighted. Positive differences indicate wind directions that contribute more to air pollution levels at a given location than the corresponding frequency of these directions. In cold periods, the largest positive differences are >7 % on calm + cbd/var days at Karvina and Prerov stations and on NE* days at Studenka and Belotin. The largest negative differences < -7% are for wind direction SW* at stations Vernovice, Karvina and Rychvald and for wind direction W* at Mikulov-Sedlec. In the warm season the estimated differences are much smaller and the most significant values are −5% at the stations Kucharovice with wind direction NW* and Mikulov-Sedlec with wind direction W*. The differences in the contributions of PM10 concentrations between cold and warm seasons are mainly due to differences in the representation of pollution sources, either in the different areas of the total area of interest or to differences in their activity during the year. Industrial sources, located mainly in the north-eastern part of Moravia (and neighbouring Poland), contribute to air pollution levels almost evenly throughout the year. In the north-eastern part of the study area (and neighbouring Poland) the highest density of individual solid fuel heating is historically linked to coal mining. The contribution of PM10 concentrations in this area increases mainly during the cold part of the year (heating season) and decreases towards the south. Similarly, differences in the contribution of PM10 concentrations in the northeastern part of Moravia have already been evaluated in the Air Silesia project [17,18,22] and other treatments [21,31,32].Table 4 Differences between the percentage proportion to air pollution from a given wind direction and the frequency of that direction (cold periods 2016/2017–2022/2023, warm period (2017–2022).

Table 4	N*	NE*	E*	SE*	S*	SW*	W*	NW*	Calm + cbd/var	N*	NE*	E*	SE*	S*	SW*	W*	NW*	Calm + cbd/var	
	Cold Period (I–III, X–XII)	Warm Period (IV–IX)	
Vernovice	0	4	6	0	−1	−14	0	−1	5	0	1	2	0	1	−2	0	−3	2	
Karvina	0	4	2	0	−1	−14	0	0	9	0	2	0	0	0	−3	0	−2	1	
Rychvald	2	2	3	2	−1	−13	−1	−1	6	0	2	2	0	0	−3	0	−1	1	
Studenka	−1	8	0	0	−1	−7	−1	0	1	−2	4	1	0	0	−3	−1	0	0	
Belotin	−2	8	0	0	−2	−4	−1	0	1	−2	4	0	0	0	−1	−1	0	−1	
Prerov	−1	3	2	−1	−4	−1	−1	−4	8	−1	1	2	0	1	0	0	−3	0	
Prostejov	0	0	2	0	0	−1	−3	−5	7	−1	1	0	1	3	0	−1	−4	2	
Tesnovice	3	4	0	−2	0	−5	−3	−2	5	0	2	0	1	0	−1	−1	−2	1	
Vyskov	−4	3	1	0	0	0	−3	−1	3	−3	0	1	0	3	0	−1	−1	1	
Brno-Turany	−1	4	3	1	0	−2	−4	−4	2	−1	1	1	1	0	−1	−2	−4	3	
Kucharovice	2	1	2	5	0	0	−7	−6	4	−1	0	0	4	0	0	−2	−5	3	
Mikulov-Sedlec	7	2	1	1	1	−3	−9	−2	2	1	0	1	2	0	−1	−5	−1	3	

An evaluation of the PM10 air pollution level at each station depending on the daily types of wind direction from the extended quadrants eqNE and eqSW (Chapter 2) during cold and warm seasons is shown in Fig. 4, Fig. 5, Fig. 6, Fig. 7. In cold periods (Fig. 4, Fig. 5), the difference between the relative contribution of PM10 to air pollution at a given station on days with wind direction from the extended quadrant NE and the frequency of these days is positive (from 1 to 8 %) at all stations. On days with wind direction from the extended quadrant SW it is negative (from −15 to −1%, except for the stations Vyskov and Kucharovice, where the difference is zero).Fig. 4 p.m.10 air pollution during cold periods on days with daily type of wind direction from the extended quadrant NE, 2016/2017–2022/2023.

Fig. 4

Fig. 5 p.m.10 air polution during cold periods on days with daily type of wind direction from the extended quadrant SW, 2016/2017–2022/2023.

Fig. 5

Fig. 6 p.m.10 air pollution during warm periods on days with daily type of wind direction from the extended quadrant NE, 2017–2022.

Fig. 6

Fig. 7 p.m.10 air pollution during warm periods on days with daily type of wind direction from the extended quadrant SW, 2017–2022.

Fig. 7

In warm periods (Fig. 6, Fig. 7), the figures show similar conclusions, but the assessed differencesare smaller. The differences between the relative contribution of PM10 to air pollution at a given station on days with a given type of wind direction and the frequency of these days reach values ranging from 0 to 5 % at each station for eqNE and from −3 to 0 % for eqSW. In cold periods, on days with wind direction from eqNE, the difference between the mean PM10 concentration at stations located in the north-earth Vernovice, Karvina and Rychvald and the mean PM10 concentration at stations located in the south-west Brno-Turany, Kucharovice and Mikulov-Sedlec is 28 μg m−3. On days with wind direction from the extended quadrant SW, this difference is only 13 μg m−3. In warm periods, these values are also lower (10 μg m−3 on days with wind direction from the extended quadrant NE and 7 μg m−3 on days with wind direction from the quadrant SW).

According to the title and focus of this article, for daily wind direction types from the extended quadrant eqNE, the dependence of PM10 concentrations during this daily wind direction type was additionally investigated. For the selected stations (the condition was that there were two other stations at least 25 km to the northeast of the selected station), the mean daily PM10 concentration and its confidence interval were always calculated for the files of all days before the first day of the duration of the given day type (day 0). Furthermore, from all the first and second days of the continuous duration of the given situation, in cases where this type of wind direction was also present at the other two stations located to the northeast of the evaluated station on the specified days. The results obtained are shown in Fig. 8, Fig. 9 (Figs. S2 and S3 in the Supplementary Materials).Fig. 8 Mean PM10 concentrations on days with wind direction from eqNE in cold periods 2016/2017–2022/2023 as a function of the duration of this situation.

Fig. 8

Fig. 9 Mean PM10 concentrations on days with wind direction from eqNE in warm periods 2017–2022 as a function of the duration of this situation.

Fig. 9

In cold and warm seasons, the mean concentrations at all stations for days 0–2 are always larger than the seasonal mean concentration (except for the concentration for day 0 in Belotin in the cold season and for Studenka, Belotin and Prerov in the warm season). Positive differences to PM10 concentrations on day 0 greater than 2 μg m−3 are for days 1 and 2 in the cold season in Studenka, Belotin and Prerov, in Kucharovice for day 1 (day 2 was not evaluated due to the small number of days). Concentrations on day 2 are already decreasing compared to day 1 in Studenka and Belotin, in Prerov they are still increasing. PM10 concentrations on day 1 and 2 continue to decrease at the Brno-Turany station. Significant increases in mean PM10 concentrations were observed in the warm season at the stations Studenka and Belotin on days 1 and 2; while concentrations were already decreasing on day 2 at Studenka, they continued to increase at Belotin. The largest increase in PM10 concentrations was observed at Prerov on day 2.

An evaluation of the average daily wind speeds in these situations shows that in 95 % of the cases the wind path on the first day is longer than about 50 km. If the situation with the same type of wind direction lasts for 2 days, in 95 % of the cases the wind trajectory on days 1 and 2 is longer than about 120 km. The Prerov station is about 90 km away from the Ostrava-Karvina agglomeration, the Brno-Turany station is 150 km away and the Kucharovice station is 200 km away.

Previous assessments of pollution transport in the Czech Republic, the prevailing wind direction and the interactions between different parts of the area of interest have always focused in detail on the most polluted part of the area - the north-eastern part [[17], [18], [19], [20], [21], [22]] and the central part [29]. The southern part of the area of interest (including the stations Mikulov-Sedlec, Kucharovice, Brno-Turany, Vyskov) has been more neglected in this respect. The reason for this was the better air quality in this area [5,33] and thus less interest of the state administration authorities in studying the region and taking targeted measures to reduce air pollution.

However, there is a need to better identify the sources of pollution, the long-range transport of pollution, the formation of secondary pollutants and, last but not least, the forthcoming tightening of limit values for air pollutants in order to protect human health [34]. The present assessment of the dependence of PM10 concentrations on wind direction should serve as a basis for further elaboration. A number of detailed measurements of air pollutants have been carried out throughout the study area (some are still ongoing). The results of the CHMI measurements will then be evaluated and presented using the PMF (Positive Matrix Factorization) model [35] to understand the transport of pollutants in this part of Central Europe, both within the Czech Republic and with respect to transport between the Czech Republic and neighbouring countries (Poland, Slovakia and Austria). These extensive measurements and processing are and will be part of the Air Quality Research Assessment and Monitoring Integrated System project [36].

3.4 Back trajectories

For the cases of days with maximum daily concentrations (Table S4 in the Supplementary Materials), back wind trajectories were calculated for each station (Fig. 10, Fig. 11, Fig. 12 and S4–S12 in the Supplementary Materials). The trajectories are calculated at 1-h intervals for a 24-h period on a given day. Maximum daily concentrations for the whole study period were found at the stations in January and February 2017. On the days when maximum daily PM10 concentrations were recorded, the prevailing wind direction at all monitored stations was from the north-east. The wind rose only indicates the wind direction at a given location, the back trajectories describe the wind trajectory to the site from distant locations too. There are cases where the prevailing wind direction (hourly data) at a given station is from the SW, but when the calculated back trajectories are plotted, it is clear that the wind trajectory has changed over the last few hours and the wind movement over the 24-h interval was from the opposite direction (e.g. Fig. 11 or Fig. S8 in the Supplementary Materials).Fig. 10 Back trajectories of wind for the day with maximum daily PM10 concentration, Rychvald, January 9, 2017.

Fig. 10

Fig. 11 Back trajectories of wind for the day with maximum daily PM10 concentration, Prostejov, February 14, 2017.

Fig. 11

Fig. 12 Back trajectories of wind for the day with maximum daily PM10 concentration, Kucharovice, February 13, 2017.

Fig. 12

This paper focuses primarily on the assessment of 24-h PM concentrations using daily wind types. Back trajectories have only been used to supplement information on episodes with maximum daily concentrations. Always for one episode with the highest PM10 concentrations for each station. In CHMI practice, back trajectories from ground weather station data are mainly used to evaluate episodes with high short-term concentrations and to identify their possible causes. From a long-term point of view (e.g. the degree of influence of a certain pollution on a given location), the back trajectories are analysed in an interval of 10 min or 1 h using cluster analysis [37,38]. The length of the trajectories and their route represent the wind speed and the stability or variability of the wind direction. The backtrajectory application is connected to the National Climatological Database CLIDATA, which contains data on wind direction and speed (standard in 10 m) from station measurements from the whole Czech Republic and the border areas of neighbouring countries [28,29]. Thus, only wind direction and wind speed data are input to the backtrajectory application, in contrast to e.g. Ref. [39], where other variables (solar radiation and constants determined by the Pasquill stability distribution) are added to the input. The input application also does not work with the orography of the terrain. The authors are aware of some uncertainties in the results, but these uncertainties are partly compensated by the input of all wind direction and wind speed data from the whole Czech Republic. For long-range transport of pollutants, it is more appropriate to use other available modelling resources, e.g. HYSPLIT [40]. The advantage of using back trajectories is the ability to determine the wind direction towards the location of interest. Wind roses and concentration roses are representative of the measurement location and may not always show the correct direction of influence of the pollution source.

4 Conclusion

The paper presents an example of an assessment of PM10 transport that is representative of ground-based air pollution measurements at 2 m and wind direction and speed measurements at 10 m above ground. Different models and methodological approaches would be required to assess long-range transport at higher levels of the atmosphere. Daily wind direction types and the methodology for calculating back trajectories of wind from ground-based meteorological measurements were appropriately applied in the processing. The daily wind type methodology is suitable for identifying the location of pollution sources when only 24-h concentrations of a given pollutant are available. However, they are not able to capture short-term differences in wind flow, nor cases where the wind is yawing away from the station compared to the back trajectories. The method of evaluating back trajectories using CHMI's internal methodology is more suitable for identifying episodes of short term high concentrations. However, back trajectories are also a useful addition (information gathering) when assessing daily concentrations of pollutants. They provide more detailed information on the direction, speed, veering or stability of the wind, even at locations further away from the station. For the needs of processing longer time periods and prevailing wind direction, it is possible to further use cluster analysis.

The prevailing NE wind direction results in worse dispersion conditions and higher PM10 concentrations throughout the area of interest. Conversely, the SW wind direction is a carrier of better dispersion conditions with lower PM10 concentrations in the area. The effect of transport of PM10 pollution in the daily type from the NE direction can be observed at those sites located in the NE of the area of interest from the border with Poland to the Prerov site. In the case of more southerly locations, it is not longer possible to clearly assess whether and to what extent they are affected by pollution transport from the north-eastern part of Moravia or from neighbouring Poland.

Data availability

The data for the analysis were provided by the Czech Hydrometeorological Institute (www.chmi.cz). The assessment is based on measurements at the sites run by the Czech Hydrometeorological Institute.

CRediT authorship contribution statement

Vladimíra Volná: Writing – original draft, Visualization, Methodology, Formal analysis, Conceptualization. Zdeněk Blažek: Writing – original draft, Supervision, Methodology, Investigation, Conceptualization.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Appendix A Supplementary data

The following is the Supplementary data to this article:Multimedia component 1

Multimedia component 1

Appendix A Supplementary data to this article can be found online at https://doi.org/10.1016/j.heliyon.2024.e36850.
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