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. 2024 Oct 30;31(54):63145–63160. doi: 10.1007/s11356-024-35470-5

Comparative analysis of airborne fungal spore distribution in urban and rural environments of Slovakia

Matúš Žilka 1, Michal Hrabovský 1, Jozef Dušička 1, Eva Zahradníková 1, Dominika Gahurová 1, Jana Ščevková 1,✉
PMCID: PMC11599331  PMID: 39477828

Abstract

Monitoring airborne fungal spores is crucial for public health and plant production since they belong to important aeroallergens and phytopathogens. Due to different land use, their concentration can differ significantly between urban and rural areas. We monitored their spectrum and quantity on two geographically close sites with a different degree of urbanisation: Bratislava City and Kaplna Village in Slovakia, located 38 km apart. We recorded the spectrum of airborne fungal spores over a year and confirmed the microscopic results by amplicon-based metagenomic analysis. The main spore season of the most frequent genera lasted over a week longer in Kaplna, but its intensity was approximately two-fold higher in Bratislava. This can be possibly connected to the microclimatic conditions of the urban area (especially wind speed and heat island effect) and the lesser use of fungicides. Cladosporium was the dominant genus on both sites, influencing the intensity most significantly. Through statistical analysis of the influence of meteorological parameters on airborne fungal spore levels, we identified a significant relationship with temperature, while the impact of other parameters varied depending on the spore type and release mechanism. Our results show the differences in airborne fungal spore levels between urban and rural areas and highlight the necessity for more monitoring stations in various environments.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11356-024-35470-5.

Keywords: Airborne fungi, Hirst-type sampler, Seasonal spore integral, Cyclone sampler, Amplicon-based metagenomic analysis, Meteorological parameters

Introduction

Fungi, with more than 150 thousand formally described species (Phukhamsakda et al. 2022) thrive in different environments (Grossart et al. 2019; Debeljak and Baltar 2023). Their successful spread to almost every terrestrial ecosystem has been largely due to airborne spore dispersal (Dijksterhuis 2019). In general, fungal spores constitute about 5% of the PM10 mass, though this percentage can rise to as much as 35% in tropical rainforest regions (Elbert et al. 2007; Fröhlich-Nowoisky et al. 2009; Huffman et al. 2012). Most fungal spores are dispersed near the source (Sesartic and Dallafior 2011) but some could be transported over long distances (Sadyś et al. 2014; Grewling et al. 2022).

Despite the undoubtedly positive role of fungi in ecosystems due to their ability to decompose organic matter, several fungi with airborne spores belong to important phytopathogens and aeroallergens, negatively affecting agricultural sustainability and public health. On plants, such as potatoes (Solanum tuberosum L.), common grapes (Vitis vinifera L.), or various deciduous trees, fungal spores can initiate a variety of diseases such as powdery mildew, rust, and blight, which compromise plant health and productivity (e.g. Dai et al. 2007; Leiminger and Hausladen 2012; Solairaj et al. 2022; Scott et al. 2022). These diseases can lead to substantial agricultural losses by reducing crop yields, increasing the need for chemical fungicides, and diminishing the overall quality of produce. Fungal spores are also common allergens that can trigger respiratory allergic diseases, such as rhinitis, asthma, and alveolitis, in susceptible individuals (Denning et al. 2006; Crameri et al. 2014; D'Amato et al. 2023). More than 80 genera of fungi are associated with allergic sensitisation (Pashley and Wardlaw 2021), with 120 fungal allergen molecules listed in the WHO/IUIS allergen database (http://allergen.org/index.php), predominantly from the two major fungal groups: Ascomycota and Basidiomycota. Ten percent of the global population is sensitive to allergenic fungal spores (Khachatourians 2019).

The species spectrum and concentration of fungal spores in the air depend on several factors, such as meteorological conditions, geographic location, the availability of proper substrates for mycelial growth, and anthropogenic activities (Grinn-Gofroń and Bosiacka 2015; Sztandera-Tymoczek and Szuster-Ciesielska 2023). Among meteorological factors, air temperature, relative humidity, precipitation, and wind speed are the most significant (Grinn-Gofroń et al. 2018). The level of urbanisation influences many of these factors (Kasprzyk and Worek 2006; Oliveira et al. 2010; Liu et al. 2019; Haas et al. 2023), especially substrate availability and anthropogenic activities, but also wind speed and temperature due to the urban heat island effect and associated turbulent air currents (Wang et al. 2019).

Despite extensive research on the temporal distribution of airborne fungal spores in urban environments (Herrero et al. 2006; Klaric and Pepeljnjak 2006; Almaguer et al. 2014; Pyrri and Kapsanaki-Gotsi 2015; Sadyś et al. 2016a, b; Dey et al. 2019; Antón et al. 2019; Núñez et al. 2019; Grinn-Gofroń et al. 2020; Anees-Hill et al. 2022), it is still unknown whether and to what extent their spectrum and concentration differ in geographically close urban and rural environments. Moreover, in most cases, the identification of fungal spores was solely based on their morphological characteristics, which is a less accurate method compared to molecular approaches (Simović et al. 2023). To fill this gap, we aimed to assess the biodiversity and abundance of airborne fungal spores based on their morphology and confirm the results by next-generation sequencing (NGS). The spores were sampled in two areas with different levels of urbanisation: an urban area of Bratislava City and a rural area of Kaplna Village, both located in the Podunajská nížina Lowland, an agriculturally important area of Slovakia. Additionally, the effects of meteorological factors on abundantly represented fungal spore types in the air of both sites were assessed.

Materials and methods

Study area

Airborne bioparticles were sampled from February to November 2022 at two sites differing in urbanisation level and land use. Bratislava (BA), a city in southwestern Slovakia (48° 08′ N, 17° 06′ E, 126–514 m a. s. l.), represented an urban location, and Kaplna (KP), a village 38 km northeast of BA (48° 17′ N, 17° 27′ E, 146 m a. s. l.), represented a rural location (Fig. 1). BA, with 476,922 inhabitants and an area of 367.7 km2, exhibits diverse land use. While an extensive part of the city is covered with buildings and anthropogenic structures, urban greenery constitutes approximately 40% of the city area. This greenery primarily consists of Carpathian oak-hornbeam forests, Danube riparian vegetation, and vineyards (Belčáková et al. 2022). The north part of the city extends into the Malé Karpaty Mts. with Devín gate in their northwestern part, affecting air circulation in BA. The southern and eastern parts of the city lie in the Podunajská nížina Lowland, predominantly featuring cultivated arable land. KP is a small rural village, with 944 inhabitants and an area of 5.5 km2, situated at the western end of the Podunajská nížina Lowland (~ 150 m a.s.l.). The village area features mainly family houses surrounded by garden vegetation, while the surrounding area is predominantly agricultural, with rapeseed, wheat, and corn as the main crops.

Fig. 1.

Fig. 1

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Location of study sites and sampling stations of Bratislava and Kaplna

Both study sites are located in Central Europe, where the climate is temperate continental, featuring warm summers and cold winters. In BA, the average annual air temperature is 11.2 °C. July is the warmest month, averaging 21.8 °C, while January is the coldest, with an average temperature of 0.3 °C. The annual total precipitation averages 765 mm, with August being the rainiest month at 87 mm and April the driest at 45 mm (data from 2002 to 2021, collected by the Meteorological Observatory BA–Mlynská dolina located approximately 0.5 km northwest of the monitoring station). The average annual air temperature in KP is 10.6 °C, with July being the warmest month at 21.4 °C and January the coldest at − 0.7 °C. The average annual total precipitation is 579 mm, with August being the rainiest month (68 mm) and April the driest (31 mm) (data from 2002 to 2021, collected at the Meteorological Observatory Jaslovské Bohunice, 26 km southeast of the monitoring station).

In 2022, meteorological conditions varied significantly between the study areas. The average daily air temperature was 11.9 °C in BA and 11.4 °C in KP. BA also experienced substantially higher annual precipitation of 830 mm compared to 455 mm in KP.

Sample collection and evaluation

Airborne bioparticles were collected at each site using a Hirst-type sampler and a multi-vial cyclone sampler (Burkard Manufacturing Co., Ltd.), which are suitable for microscopic and genetic analyses. The samplers were positioned on building rooftops without obstructions to airflow: 18 m above ground level in BA (N 48.14973, E 17.07375) and 3 m above ground level in KP (N 48.29548, E 17.45022). The lower sampling height in KP was due to the logistical limitations. The operation period of the Hirst-type and cyclone samplers was from 1 February to 31 October 2022. Samples collected by Hirst-type samplers were used for light microscopy to evaluate daily fungal spore diversity and abundance. In this sampler, airborne particles are suctioned through a 2 × 14 mm slit at an airflow rate of 10 L/min and adhere to a strip of adhesive tape moving at 2 mm/h. The tape was changed weekly at the same time, precisely cut into segments representing each sampling day, and mounted on microscopic slides using a mixture of gelatin, glycerin, phenol, and distilled water. The samples were stained with fuchsin to enhance pollen and spore differentiation. Fungal spores were identified using reference atlases (Grant Smith 2000; Lacey and West 2006; Li et al. 2023) and counted under a light microscope (Motic B1-252SP) at × 400 magnification. Each slide was examined along 12 vertical transects (Galán et al. 2021). Daily concentrations were reported as spores per cubic metre of air (spores/m3).

The main spore season (MSS) and its characteristics, including season start, end, duration, seasonal spore integral (SSIn), peak value, peak date, and the number of high days (HD), were defined for taxa with annual total spore concentration (annual spore integral (ASIn)) exceeding 2000 spores*day/m3 at both stations (19 taxa). We used the 90% method (Nilsson and Persson 1981) to define the MSS. SSIn was defined as the sum of daily spore concentrations over the MSS. A high day (HD) was defined as a day when the spore concentration exceeded a daily average of 3000 spores/m3 for Cladosporium and 100 spores/m3 for other spore taxa. These threshold values are known to trigger clinical fungal spore allergy symptoms (Gravesen 1979; Rapiejko et al. 2007; Sadyś et al. 2016a, b).

Samples collected by multi-vial cyclone samplers were analysed for fungal presence and diversity using amplicon-based metagenomic analysis (hereinafter referred to as metagenomic analysis). The multi-vial sampler operates at an airflow rate of 16.5 L/min, separating particles in a mini cyclone and depositing them into 1.5-mL test tubes, each representing a full day of exposure. The test tubes were stored at − 20 °C until the DNA isolation. Twelve samples (six for each station) were selected for metagenomic analysis. To ensure a high yield of eDNA, we picked the dates with the highest fungal spore diversity and quantity based on the microscopic analysis. These samples were collected on the following dates: BA: 19 June, 16 July, 15 August, 19 August, 14 September, and 18 October and KP: 27 June, 27 July, 12 August, 19 August, 28 September, and 2 October. DNA extraction, Illumina library construction of the amplified internal transcribed spacer region 2 (ITS2) from fungal species present in the aerobiological samples, and a metagenomic study characterising the community using these amplified regions were performed by Microsynth AG (Balgach, Switzerland). ITS2 was amplified with locus-specific primers ITS3 and ITS4 (White et al. 1990) as part of the Nextera barcoded PCR libraries, which were then sequenced on an Illumina MiSeq platform. The paired-end reads that passed Illumina’s chastity filter were de-multiplexed and trimmed of Illumina adapter residuals, and their quality was checked using FastQC software version 0.11.8. The ITS2 primers were trimmed from the sequencing reads using Cutadapt v3.2. The trimmed reads were merged, and fungal ITS2 subregions were extracted with ITSx v1.1.3 and its accompanying database. The obtained Amplicon sequence variants (ASV) sequences also called zero-radius Operational taxonomic units (zOTU) were compared to reference sequences from the UNITE (v7.2) database. Taxa were predicted, and their confidences were calculated using the SINTAX algorithm implemented in USEARCH. The metagenome was visualised using Krona charts, and alpha diversity calculations and rarefaction analysis were performed with the R software packages phyloseq v1.30.0 and vegan v2.5–7.

Data evaluation

The spore calendars for BA and KP were created using the method described by Spieksma (1991). Mean daily spore concentrations for 10-day periods were categorised into six exponential classes (EC, spore concentrations for Cladosporium are in parentheses): (a) 1–10 (1–300), (b) 11–50 (301–1,500), (c) 51–100 (1501–3000), (d) 101–500 (3001–5000), (e) 501–1000 (5001–10,000), and (f) ˃ 1000 (˃ 10,001). The spore calendar only includes the spore types with ASIn reaching 250 + spores/m3, listed in chronological order based on the intensity of the MSS.

We categorised the spores based on the period of the year when their average 10-day spore concentrations exceeded the threshold value EC “d”. Seasonal spores are characterised by exceeding the threshold value continuously for over a month and can be categorised as summer, summer-autumn, and autumn spores. When the average 10-day spore concentrations exceed the threshold value as early as spring and these above-threshold levels persist until autumn, we can refer to them as all-year-round spores.

The statistical differences in ASIn between BA and KP spore concentrations were evaluated using a paired samples Wilcoxon test with the wilcox.test() function.

Non-parametric Spearman’s correlation analysis was employed to assess the relationship between the 19 most abundant taxa and selected meteorological variables: daily average mean air temperature (°C), relative humidity (%), wind speed (m/s), sunshine duration (h), and total daily precipitation (mm). The data analyses were conducted using Statistica 12.

Results

Diversity of fungal spores in the air of the study areas

Based on microscopic analysis, we recorded 67 fungal spore groups, with 64 present in BA and 59 in KP (Table 1). The taxa confirmed by metagenomic analysis were placed in these groups, together with other potential taxa identified based on their morphology and distribution (Table S1). Except for the Myxomycetes of the Protozoa and Peronospora of the Chromista kingdom, all identified spores belong to the Ascomycota or Basidiomycota phylum of the Fungi kingdom, with Ascomycota being the dominant group (Table 1). The most frequently occurring group (> 90% days per year) on both sites were Alternaria, Arthrinium, Cladosporium, Coprinus type, Epicoccum, and Leptosphaeria type. The less frequently occurring groups (< 10% days per year) were Camarosporium, Camptophora, Chalastospora, Oncopodiella, Saccobolus, Tetraploa, and Tilletia in BA and Corynespora, Exosporiella type, Oncopodiella, Panaeolina, Sporidesmium, and Tilletia in KP (Table 1).

Table 1.

Annual Spore Integrals (ASIn), percentage contribution and frequency of all fungal spore types found in the atmosphere of Bratislava and Kaplna in 2022

Spore type TG Bratislava Kaplna
ASIn (spore*day/m3) % Frequency (% of days) ASIn (spore*day/m3) % Frequency (% of days)
Agaricus type A 170,831 7.21 68.4 25,243 2.27 69.6
Agrocybe B 9489 0.4 85.4 6843 0.61 89.9
Alternaria A 33,766 1.43 96.9 46,019 4.13 96.4
Amphisphaeria A 1835 0.08 56.5 1365 0.12 52.9
Arthrinium A 2641 0.11 90.1 13,194 1.19 94.6
Ascobolus A 68  < 0.01 17 28  < 0.01 12
Ascochyta A 5342 0.23 34.7 2846 0.26 70.7
Aspergillus/Penicillium A 2141 0.09 37.1 6827 0.61 63.8
Asterosporium A – – – 25  < 0.01 10.1
Bipolaris A 264 0.01 49 84 0.01 12.7
Botrytis A 1764 0.07 50.3 1051 0.09 59.8
Bovista B 716 0.03 34.7 23,855 2.14 63
Caloplaca A 1610 0.07 31 362 0.03 25
Camarosporum A 47  < 0.01 6.8 – – –
Camptophora A 4  < 0.01 1 – – –
Cercospora A 968 0.04 26.9 595 0.05 33.3
Cerebella A 537 0.02 22.4 452 0.04 27.5
Cladosporium A 1,649,583 69.65 100 726,757 65.25 100
Coprinus B 7367 0.31 85 5317 0.48 80.8
Coprinus type B 172,948 7.3 98 124,548 11.18 96
Corynespora A – – – 6  < 0.01 1.4
Cucurbitaria A 1152 0.05 37.8 – – –
Curvularia A 71  < 0.01 18.4 299 0.03 24.3
Diatripaceae A 3839 0.16 32.7 1920 0.17 21.4
Drechslera A 120 0.01 22.4 213 0.02 44.2
Epicoccum A 14,863 0.63 95.9 11,453 1.03 97.5
Exosporiella type A 309 0.01 35.7 28  < 0.01 3.6
Exosporium A 10,482 0.44 66.3 1523 0.14 71.4
Fomes B 8714 0.37 28.6 – – –
Fusarium A 3864 0.16 16.7 3543 0.32 60.9
Fusicladium A 351 0.02 60.5 135 0.01 39.9
Ganoderma B 29,157 1.23 68.7 22,072 1.98 79.3
Helicospores A 119 0.01 21.8 742 0.07 42.4
Chaetomium A 796 0.03 74.8 1005 0.09 75.4
Chalastospora A 20  < 0.01 2.7 – – –
Leptosphaeria type A 108,775 4.59 99.3 22,642 2.03 94.6
Massaria A 47  < 0.01 13.6 223 0.02 43.5
Melanospora A 143 0.01 36.1 341 0.03 57.2
Myxomycetes P 29,574 1.25 79.9 25,141 2.26 96.4
Neohendersonia A 52  < 0.01 16.3 144 0.01 41.7
Nigrospora A 1326 0.06 92.2 721 0.07 84.4
Oidium type A 53,575 2.26 68 12,263 1.1 81.2
Oncopodiella A 24  < 0.01 8.2 2  < 0.01 1.1
Panaeolina B 175 0.01 21.4 1  < 0.01 0.7
Panaeolus B 611 0.03 48.6 453 0.04 48.9
Periconia A 3041 0.13 94.2 2366 0.21 86.6
Peronospora Ch 722 0.03 67.7 1071 0.1 75.4
Pithomyces A 2889 0.12 73.8 1596 0.14 71.7
Pleospora A 4069 0.17 95.9 4074 0.37 82.6
Polythrincium A 312 0.01 45.6 128 0.01 34.8
Puccinia B 147 0.01 12.9 930 0.08 77.5
Saccobolus A 7  < 0.01 2 – – –
Sordaria A 154 0.01 38.8 291 0.03 56.5
Spegazzinia A 73  < 0.01 19 27  < 0.01 10.1
Splanchonema A 176 0.01 34.4 – – –
Sporidesmium A 194 0.01 44.6 28  < 0.01 8
Sporormiella A 75  < 0.01 22.4 78 0.01 15.6
Stemphylium A 2726 0.12 62.6 1937 0.17 79.7
Teliospores B – – – 30  < 0.01 12.3
Tetraploa A 1  < 0.01 0.3 7  < 0.01 25.7
Tilletia B 4  < 0.01 1.4 149 0.01 3.6
Torula A 2639 0.11 85.4 3226 0.29 92.4
Uredinospores B 2104 0.09 43.5 498 0.05 53.3
Urocystis B 170 0.01 25.5 129 0.01 24.6
Ustilago B 6774 0.29 65.6 1582 0.14 29
Venturia A 304 0.01 21.4 – – –
Xylariaceae A 11,706 0.49 90.5 5436 0.49 77.5
Total 2,368,367 100 1,113,862 100
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TG taxonomic group, A Ascomycota, B Basidiomycota, P Protozoa, Ch Chromista

The mean daily number of identified spore groups was 28 for BA and 31 for KP. The diversity rose during the spring (March–May), peaked in the summer (June–August), and decreased in autumn (September–November) (Fig. 2). The highest diversity of fungal spores in both areas was recorded in July, with an average number of spore groups of 36 for BA and 37 for KP, and the lowest in February (14 spore types) for BA and in March (15 spore types) for KP.

Fig. 2.

Fig. 2

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Number of fungal spore groups in the air of Bratislava (BA) and Kaplna (KP) in 2022

The results of the metagenomic analysis focused on fungal taxonomic profiling of samples revealed in a total of 96 OTU (operational taxonomic unit) sequences belonging to the phyla Ascomycota and Basidiomycota (Table S2). Ascomycota accounted on average for 84% of fungal DNA in BA and 73% in KP. Of the 10 classes identified, Dothideomycetes and Tremellomycetes were the most abundant. Twenty-three taxa were classified to the order level, with Capnodiales and Pleosporales as the most numerous, and 36 were assigned to the family level and 42 to the genus level. The most abundant genera were Mycosphaerella, Cladosporium, Alternaria, and Ascochyta. Of the 40 identified species, Mycosphaerella tassiana was present in samples most frequently.

The metagenomic analysis confirmed the presence of 22 genera which also were detected by microscopic analysis and could be placed in 17 spore groups (Table S1). Forty-eight percent of genera were unique to the metagenomic analysis, and 66% of spore groups were unique to microscopic analysis (Fig. 3).

Fig. 3.

Fig. 3

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Venn diagram representing the total number of unique and common fungal genera in the airborne samples collected from Bratislava and Kaplna in 2022 based on metagenomic (NGS) and microscopic (MIC) analysis

The number of genera in each sample from the metagenomic analysis ranged from 21 to 30 for BA and between 17 and 27 for KP. Microscopic analysis of samples from the same dates revealed similar diversity between sites, differing by a maximum of 5 genera (Fig. 4).

Fig. 4.

Fig. 4

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Daily numbers of spore groups recorded by microscopic (MIC) and metagenomic (NGS) analysis during 6 days (VI—19 June, VII—16 July, VIII (1)—15 August, VIII (2)—19 August, IX—14 September, X—18 October) in Bratislava (BA) and 6 days (VI—27 June, VII—27 July, VIII (1)—12 August, VIII (2)—19 August, IX—28 September, X—2 October) in Kaplna (KP) in 2022

Quantity and abundance of fungal spores in the air of the study areas

Based on the results of microscopic analysis, the sum of ASIn for all analysed taxa reached a value of 2,368,367 spore*day/m3 in BA and 1,113,864 spore*day/m3 in KP (Table 1). Except for winter and early spring months, high concentrations of spores were consistently present in the air, especially in July (21.6% of the total annual spore concentration) for BA and June (20.9%) for KP (Fig. 5). Summer months (June–August) accounted for more than 50% of the ASIn on both sites. Differences in total monthly spore concentration between the two sites were most pronounced in July when over three times more spores were recorded in BA (509,937 spores/m3) compared to KP (134,880 spores/m3).

Fig. 5.

Fig. 5

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Monthly variation in airborne fungal spore concentration (expressed in percentages) in Bratislava (BA) and Kaplna (KP) in 2022

The most abundant genera, which accounted for more than 90% of the sum of ASIn, were Cladosporium, Coprinus type, Agaricus type, Leptosphaeria type, Oidium type, Alternaria, Myxomycetes, and Ganoderma on both sites. Among the top 10 most abundant taxa were also Bovista and Arthrinium in KP and Epicoccum and Xylariaceae in BA (Table 1). The dominant genus on both sites was Cladosporium, contributing 69.6% to the sum of ASIn in BA and 65.2% in KP, followed by Coprinus type (BA 7.3%, KP 11.2%). The ratio between genera was similar in study sites, although all the most abundant genera, except for Alternaria, had higher concentrations in BA, frequently by two or more-fold (Table 1).

MSS-related characteristics

The MSS-related characteristics were calculated for the 19 taxa whose ASIn exceeded 2000 spore*day/m3 on both sites (Table 2). According to the Wilcoxon test, there was a statistically significant difference in ASIn between BA and KP (V = 1644.5, p = 0.0016). Regarding timing, MSS for the majority of fungal spore groups started earlier in KP than in BA and ended at approximately the same time in both areas, from mid-August to mid-November. However, the MSS of the most abundant genus Cladosporium started 32 days earlier in BA. The first genus to sporulate in both regions was Periconia (3 March in BA and 19 March in KP), and the last spore group was the Agaricus type (16 September in BA and 8 August in KP). Out of the total evaluated taxa, 11 reached peak value earlier in KP than in BA. In terms of duration, the MSS of most spore groups lasted longer in KP, with the MSS of 11 taxa more than 5 days longer. The duration of MSS ranged from 46 days (Agaricus type) in BA to 236 days (Pleospora) in KP. The intensity of MSS, expressed by SSIn values, peak value, and number of HD, was higher in BA. The average SSIn value (117,480 spore*day/m3) and peak value (3845 spores/m3) were 133% and 44% higher in BA than in KP, respectively. In BA, 14 taxa achieved a higher SSIn value, and 10 taxa achieved a higher peak value compared to KP. The highest number of HD in BA was recorded for the spore groups Cladosporium (151 days), Coprinus type (150 days), and Leptosphaeria type (144 days), while in KP, it was for Coprinus type (122 days), Alternaria (120 days), and Ganoderma (84 days). The average daily concentration of all 19 spore groups was also higher in BA than in KP except for Alternaria, Aspergillus/Penicillium, Arthrinium, Fusarium, and Torula (Fig. S1). The daily concentration of Agaricus type, Ascochyta, Cladosporium, Leptosphaeria type, Myxomycetes, and Oidium was most notably higher in BA.

Table 2.

The MSS characteristics of abundantly represented fungal taxa in the air of Bratislava (BA) and Kaplna (KP) in 2022

Taxa Season start (DOY) Season end (DOY) Season length (days) SSIn (spore*day/m3) Peak value (spore/m3) Peak day (DOY) High daysa (number)
BA KP BA KP BA KP BA KP BA KP BA KP BA KP
Agaricus type 259 219 304 292 46 73 154,457 22,851 14,517 2494 289 281 46 36
Agrocybe 163 159 321 318 159 159 8545 6162 410 273 277 306 28 16
Alternaria 170 166 299 297 130 131 30,394 41,414 820 1668 239 261 90 120
Arthrynium 74 119 295 289 222 170 2386 11,863 48 1885 222 161 0 19
Ascochyta 133 117 307 303 175 186 4796 2526 565 115 137 258 14 1
Aspergillus/Penicillium 126 86 295 262 170 176 1888 6119 146 279 217 97 3 0
Cladosporium 96 128 323 303 228 175 1,632,471 653,380 41,841 32,541 187 178 151 77
Coprinus 162 131 318 322 157 191 6586 4790 342 336 279 305 17 13
Coprinus type 144 130 311 308 168 178 155,746 111,616 5985 5336 279 247 150 122
Epicoccum 166 166 307 308 142 142 13,363 10,333 516 456 306 261 46 32
Fusarium 159 116 262 312 104 196 3452 3194 357 162 240 68 13 6
Ganoderma 169 164 295 300 127 136 26,194 19,862 549 433 224 257 102 84
Leptosphaeria type 134 116 307 303 174 187 9810 20,339 3,984 826 183 212 144 73
Myxomycetes 236 130 312 315 77 185 26,221 22,711 1,652 2488 286 290 50 53
Oidium type 164 113 226 230 63 117 48,264 11,023 6110 709 184 131 41 30
Periconia 62 77 293 307 232 230 2712 2133 74 60 281 142 0 0
Pleospora 91 90 326 298 236 208 3643 3697 118 467 329 270 2 8
Torula 74 83 289 290 216 207 2377 2901 60 79 170 132 0 0
Xylariaceae 167 160 308 312 142 152 10,533 4871 464 160 259 259 34 7
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SSIn seasonal spore integral, DOY day of the year from 1 January

aSpore concentration ˃ 3000 spores/m3 for Cladosporium and ˃ 100 spores/m3 for all taxa except Cladosporium

Spore calendars

The fungal spore calendars for BA and KP are shown in Figs. 6 and 7, respectively. For both BA and KP, Cladosporium, Coprinus type, and Leptosphaeria type were identified as all-year-round spores. The Oidium type is among the significant summer spores in BA, with concentrations continuously exceeding threshold levels from early June to late August. Alternaria and Ganoderma are classified as summer-autumn spores, with their concentrations continuously exceeding threshold levels from June except for Ganoderma in KP (July) and lasting until the autumn months. Among the significant autumn spores with continuous above-threshold levels between September and November are the Agaricus type and Myxomycetes in both locations and Bovista in KP. Short-term occurrences of above-threshold levels were also recorded for the spore groups Epicoccum, Agrocybe, and Coprinus in both locations; Xylariaceae, Exosporium, Ustilago, Ascochyta, Diatripaceae, and Fomes in BA; and Aspergillus/Penicillium, Arthrinium, and Oidium type in KP. In BA, spore concentrations reaching exponential class “f” were recorded for Coprinus type, Leptosphaeria type, Agaricus type, Oidium type (above 1000 spores/m3), and for Cladosporium (above 10,000 spores/m3). In KP, only the Coprinus type reached this value (from the end of August to mid-October). During the sporulation season of Cladosporium, we recorded two periods where the concentration exceeded 5000 spores/m3 (exponential class “e”) per day.

Fig. 6.

Fig. 6

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Fungal spore calendar for Bratislava, year 2022. Exponential classes (spores/m3): a 1–10 (1–300), b 11–50 (301–1500), c 51–100 (1501–3000), d 101–500 (3001–5000), e 501–1000 (5001–10,000), f ˃ 1000 (˃ 10,001). Spore concentrations for Cladosporium are in parentheses. Asp/Pen—Aspergillus/Penicillium; Leptosph. type—Leptosphaeria type

Fig. 7.

Fig. 7

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Fungal spore calendar for Kaplna, year 2022. Exponential classes (spores/m3): a 1–10 (1–300), b 11–50 (301–1500), c 51–100 (1501–3000), d 101–500 (3001–5000), e 501–1000 (5001–10,000), f ˃ 1000 (˃ 10,001). Spore concentrations for Cladosporium are in parentheses. Asp/Pen—Aspergillus/Penicillium; Leptosph. type—Leptosphaeria type

Relationship between airborne spore concentrations and meteorological parameters

For the 19 abundantly represented taxa at both sites, Spearman ‘s correlation analysis identified relative humidity, temperature, and sunshine as the most significant meteorological parameters (Table 3). Relative humidity had both positive and negative effects on fungal spores; however, positive correlations were more frequent and stronger. Strong negative correlations were only observed for Torula on both sites and Ganoderma and Arthrinium in BA. The correlation with temperature was positive for most analysed taxa except for Agaricus type, Agrocybe, and Coprinus in KP. Alternaria, Cladosporium, Ganoderma, and Torula had the strongest correlations with temperature on both sites (p < 0.001). Correlations with sunshine were similar to those with temperature but weaker. Regarding precipitation, we observed a significant positive relationship with only four spore groups (Leptosphaeria type and Pleospora at both sites and Ascochyta and Diatripaceae in BA). Wind speed was the weakest factor affecting airborne fungal spore concentrations, showing a negative correlation with Coprinus type on both sites and with Ganoderma and Xylariaceae in BA. A positive influence of the wind speed was only recorded for Diatrypaceae in KP.

Table 3.

Spearman’s correlation coefficients between airborne fungal spore concentrations and meteorological variables recorded in Bratislava (BA) and Kaplna (KP) in 2022. Significant trends are in bold

Spore group Temperature (°C) Sunshine (h) Relative humidity (%) Wind speed (m/s) Precipitation (mm)
BA KP BA KP BA KP BA KP BA KP
Agaricus type  − 0.056  − 0.224*  − 0.136  − 0.247* 0.294** 0.308**  − 0.141  − 0.133  − 0.104  − 0.077
Agrocybe  − 0.191  − 0.242*  − 0.238*  − 0.268** 0.437*** 0.486***  − 0.183  − 0.128  − 0.124  − 0.038
Alternaria 0.501*** 0.433*** 0.185 0.095  − 0.008  − 0.072  − 0.093 0.102  − 0.113  − 0.055
Arthrinium 0.443*** 0.164 0.297** 0.134  − 0.271**  − 0.069  − 0.061 0.117  − 0.097 0.039
Ascochyta  − 0.024 0.021  − 0.095  − 0.169 0.124 0.233* 0.041 0.067 0.511*** 0.184
Aspergillus/Penicillium 0.212* 0.036 0.017 0.022  − 0.088  − 0.134  − 0.077  − 0.058  − 0.045 0.029
Cladosporium 0.615*** 0.519*** 0.291** 0.233* 0.046  − 0.032  − 0.173 0.019  − 0.004 0.078
Coprinus  − 0.123  − 0.308**  − 0.234*  − 0.288** 0.405*** 0.468***  − 0.121  − 0.161  − 0.093  − 0.085
Coprinus type 0.159 0.074  − 0.014  − 0.134 0.342*** 0.306**  − 0.249*  − 0.215*  − 0.095  − 0.006
Diatrypaceae 0.107  − 0.153  − 0.268**  − 0.212* 0.282** 0.267**  − 0.08 0.278** 0.456*** 0.193
Epicoccum 0.291** 0.154 0.019  − 0.117 0.228* 0.215*  − 0.119 0.017  − 0.112  − 0.06
Ganoderma 0.591*** 0.405*** 0.316** 0.12  − 0.447***  − 0.066  − 0.233*  − 0.125  − 0.166  − 0.024
Leptosphaeria type 0.365*** 0.211*  − 0.055  − 0.183 0.317** 0.276**  − 0.187 0.067 0.342*** 0.411***
Myxomycetes  − 0.116  − 0.021  − 0.187  − 0.014 0.283** 0.11  − 0.035  − 0.115  − 0.114  − 0.064
Oidium type 0.337*** 0.264** 0.259** 0.222*  − 0.089  − 0.207*  − 0.155  − 0.193  − 0.045  − 0.016
Periconia 0.314** 0.112 0.308** 0.145  − 0.255*  − 0.093  − 0.045 0.065  − 0.057  − 0.038
Pleospora 0.199*  − 0.033  − 0.207*  − 0.297** 0.333*** 0.284**  − 0.101 0.043 0.509*** 0.467***
Torula 0.426*** 0.368*** 0.308** 0.222*  − 0.304**  − 0.269**  − 0.091  − 0.061  − 0.154  − 0.045
Xylariaceae 0.271**  − 0.014  − 0.033  − 0.153 0.171 0.242*  − 0.244* 0.056 0.042 0.071
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*p < 0.05, **p < 0.01, ***p < 0.001

Discussion

Fungal spore diversity

Hirst-type spore sampling in BA and KP and subsequential assessment by light microscopy revealed 67 different spore groups, with 56 represented on both study sites. Due to the wide range of fungal spores detected, the results can be applied in several sectors such as healthcare, agriculture, or forestry. Such a broad-scale analysis of the fungal spore spectrum is important since most studies are often focused only on individual taxa, rarely including 30 or more of them (Herrero et al. 2006; Pyrri and Kapsanaki-Gotsi 2015; Bednarz and Pawłowska 2016; Grinn-Gofroń et al. 2020). Fungal spore diversity varies throughout the year, reaching its peak in summer when the meteorological conditions are optimal for plant and mycelium growth (Anees-Hill et al. 2022). Ascomycota and Basidiomycota were the dominant spore groups, consistent with other studies focusing on spore morphology in this climate region (Kasprzyk and Worek 2006; Bednarz and Pawłowska 2016).

Applying the metagenomic method, our research revealed 96 OTUs in the Ascomycota and Basidiomycota phylum. The average number of taxa did not vary significantly between sites, similar to the light microscopy results. Fungal diversity in the air is considerably more uniform than in soil or water (Wagner et al. 2022). Significant changes in the diversity of fungal spores in the air are observable at distances greater than 100 km (Abrego et al. 2018), whereas our sites were only 30 km apart. At the same time, the number of taxa generally decreases with increasing urbanisation (Abrego et al. 2020). However, our results showed a slight increase in diversity at urban sites, as revealed by microscopic and metagenomic analyses. This could be attributed to the varying land use and, consequently, the substrate diversity in BA, as well as the placement of the sampler at a higher elevation, allowing it to collect spores from a broader area. In contrast to other studies (Pashley et al. 2012; Yamamoto et al. 2012; Niu et al. 2021; Apangu et al. 2022b), we observed higher fungal diversity when using morphological analysis compared to metagenomic methods. Nevertheless, accurate species classification can still be useful for targeted human health protection and the disease prevention of cultural plants.

Using a metagenomic method, we identified 42 genera, in contrast to the 318 genera and 558 genera identified in atmospheric samples from Tianjin, China (Niu et al. 2021), and New Haven, USA (Yamamoto et al. 2012), respectively. Fröhlich-Nowoisky et al. (2009) demonstrated that 70% of the detected species were found in only one sample, suggesting increased diversity with the number of samples examined. Therefore, we assume that increasing the number of samples could lead to the identification of more genera by metagenomic analysis; however, our goal was only to confirm the taxa identified by morphological analysis. Moreover, the method used for collecting and evaluating samples can significantly influence the outcomes of genetic analyses. Insufficient amounts of readable DNA in samples may contribute to the lower number of identified genera. The prevalence of Cladosporium and Alternaria was confirmed by both microscopic and metagenomic analysis, in agreement with previous studies (Yamamoto et al. 2012; Núñez et al. 2019; Niu et al. 2021; Simović et al. 2023).

Fungal spore quantity

Significant variations were observed in the total concentrations of airborne fungal spores, with markedly higher levels detected in urban areas. This is notable, as spore concentrations are typically higher in rural areas due to a greater abundance of plant biomass (Kasprzyk and Worek 2006; Oliveira et al. 2009). The reduced spore concentration in KP may be attributed to fungicide application in neighbouring monocultures and gardens (Oliver and Hewitt 2014). Conversely, such treatments are not employed in the BA area due to the presence of multiple nature reserves and water sources. The harvest of crops can also temporarily increase the spore levels in KP, but this effect is short-lasting due to the harvest being usually done in a single day and does not influence the yearly differences significantly.

The different sampling heights could also affect the quantity and diversity of fungal spores in some way, although not significantly. Other studies (Khattab and Levetin 2008; Damialis et al. 2017; Charalampopoulos et al. 2022) point out the differences in spore concentration between samples collected at ground and rooftop level, with a far more abundant presence of spores on ground level. If this effect were significant, we would expect more spores captured in the KP samples placed at the lower height, but the opposite was true. Therefore we can assume that this effect is not significant in the height of at least 3 m above ground level.

Similarly to other studies (Sadyś et al. 2016a, b; Grinn-Gofroń et al. 2020; Simović et al. 2023), the prevalence of Cladosporium was most notable, accounting for 70% and 65% of the total fungal spore concentration in BA and KP, respectively. From the dominant fungal spore groups, only Alternaria fit the pattern of higher spore levels in rural environments, with a higher ASIn in KP than in BA. Since Alternaria club-shaped spores are the least aerodynamic of this group and originate mostly from local sources (Apangu et al. 2022a), we can assume that the differences are caused by airborne spore transport. In this, BA has a relatively unique position caused by topography increasing the wind speed (Polčák and Šťastný 2011), which can explain the discrepancy with results from other cities. Long-distance transport of airborne bioparticles can bring spores from more distant sources than in KP, where local sources prevail in the bioaerosol composition.

A part of the difference between BA and KP can also be attributed to better conditions for aerosolisation and dispersion of fungal spores in BA. Factors such as increased traffic and movement facilitate the dispersal and resuspension of spores (Muafa et al. 2024), aided by the prevalence of concrete surfaces, which are less adhesive than soil, and differences in microclimatic conditions. In rural areas, the air circulation has a daily periodicity with sedimentation of spores during nighttime due to cooling and increased humidity. In urban environments, the heat island effect (Memon et al. 2008; Wouters et al. 2017) causes the near-surface layer of the troposphere to remain dynamic even during the evening and nighttime hours, preventing spore sedimentation (Jones and Harrison 2004). Our results showing the greatest differences in spore concentrations during summer months hint at this influence of the heat island effect as a possible cause. To mitigate urban heat islands, it is good practice to plant public greenery (Werbin et al. 2020) and retain water in parks, green roofs, and other green spaces within the city (Irfeey et al. 2023). This approach would also help increase the areas to which fungal spores could adhere and reduce their resuspension. However, it is important to select the right plants with regard to their allergenic or invasive potential (Domina et al. 2024). Proper storage and disposal of bio-waste, reduced traffic in the city, and planned denser development would also contribute to lower airborne spore concentrations.

MSS-related characteristics and spore calendars

Spore calendars, conveying the characteristics of the MSS, are valuable tools for easily tracking the temporal variation in airborne spore concentration throughout the year, making them useful in fields such as medicine, agriculture, forestry, and viticulture. The timing, especially the beginning of the MSS, is most important in agriculture and forestry, while the intensity of the MSS, especially the number of HD, is important in allergology. However, there are only a few examples of spore calendars covering the entire fungal spectrum in the air, and these are primarily from urban environments (Gioulekas et al. 2004; Bednarz and Pawłowska 2016; Antón et al. 2019; Dey et al. 2019; Ščevková and Kováč 2019; Symon et al. 2023).

An earlier start of MSS for most fungal spore groups was observed in KP, with a notable exception of Cladosporium. An earlier start of the MSS in a rural environment can be expected due to the closeness of local sources of spores (Ruas et al. 2022). From this point of view, it is important to record the timing of MSS in agricultural areas, since a warning issued by a monitoring station in an urban area, even a close one, could be late for effective treatment of crops.

From an allergological point of view, spore calendars are a useful tool for the effective prevalence and treatment of allergies caused by fungal spores (Katotomichelakis et al. 2016; Weryszko-Chmielewska et al. 2018; Anees-Hill et al. 2022). From the identified spores, six can be found in the WHO/IUIS allergen database (http://allergen.org/index.php): Alternaria, Aspergillus, Cladosporium, Epicoccum, Fusarium, and Leptosphaeria type. Despite the shorter duration of MSS in BA, it had a higher intensity in all of its parameters (SSIn, peak value, and number of HD), which agrees with the higher prevalence of fungal allergies in urban environments (Schröder et al. 2015; Kwong et al. 2023). This can have the same possible causes as the higher quantity of fungal spores in BA (see the “Fungal spore quantity” section).

Influence of meteorological parameters

Our study identified temperature, sunshine, and relative humidity as the most influential meteorological factors affecting spore concentration. These parameters, along with wind speed and precipitation, have also been highlighted as significant in other studies (Ianovici 2016; Grinn-Gofroń et al. 2018; Anees-Hill et al. 2022). However, the relationship between meteorological conditions and various types of fungal spores is highly complex, with some parameters having opposite effects on different genera.

The influence of temperature on spore concentration is generally positive (Almaguer et al. 2014; Grinn-Gofroń and Bosiacka 2015; Sadyś et al. 2015, 2016a, b; Akgül et al. 2016; Grinn-Gofroń et al. 2018; Olsen et al. 2020), as more plant biomass is produced, serving as a substrate for fungal growth (Rodriguez and Redman 1997), and the fungal mycelium also grows faster (Gange et al. 2007) and produces more spores (up to a certain temperature threshold) (Damialis et al. 2015).

The factors influencing the release of spores differ most noticeably across the different spore types. The dividing of spores into groups of dry-released spores, including Cladosporium, Alternaria, Epicoccum, Drechslera, and Ganoderma (Troutt and Levetin 2001; Ianovici 2016; Grinn-Gofroń et al. 2018), and wet-released spores, such as Coprinus, Leptosphaeria, Fusarium, Oidium, or Botrytis (Elbert et al. 2007; Antón et al. 2019), has been established in several studies. In “dry-air” spores, the simultaneous influence of increased temperature, wind speed, and low humidity creates favourable conditions for spore detachment and air dispersal (Ianovici 2016). The increase in temperature and sunshine during the day also accelerates the biomass production of plant hosts, which consequently increases the spore production of their fungal pathogens. In our results, this influence is most clearly seen in Arthinium, Ganoderma, Oidium type, Periconia, and Torula.

On the contrary, “wet-air” spore release is stimulated by increased humidity, closely linked to precipitation (Grinn-Gofroń and Bosiacka 2015). The increased humidity enables these fungi to grow their fruiting bodies faster and also accelerates sporulation, while rainfall contributes to the easier release of their spores into the air (Talley et al. 2002). These spores are usually colourless and are negatively influenced by UV radiation from sunlight (Klaric and Pepeljnjak 2006). Our results showed a positive correlation with humidity or precipitation and a negative correlation with sunshine, particularly pronounced in Agrocybe, Coprinus, Diatrypaceae, and Pleospora.

Conclusions

We conducted a study comparing fungal spore spectra and quantities in two nearby areas with varying degrees of urbanisation. Metagenomics allowed us to validate our findings obtained by light microscopy, revealing the degree of correctness of taxon identification and numbers at the two sites. We were also able to determine fungi to the species level, which would not have been possible by light microscopy alone. Furthermore, our knowledge of species diversity was enriched by the addition of new taxa whose presence had not previously been detected at the sites. However, several taxa were not detected by metagenomics, probably due to the small number of collections and the insufficient amount of material in samples. A significantly higher quantity of spores and intensity of the MSS was recorded in the urban area, while the duration of the MSS was longer in the rural area. These findings were predominantly influenced by the genus Cladosporium, which constituted a substantial portion of airborne fungal bioparticles in both locations. Meteorological analysis revealed temperature as a key factor positively impacting fungal spore levels, while the effects of other meteorological variables depended on spore release mechanisms. The characteristics of the MSS provide crucial insights for allergology and agricultural practices. However, continued monitoring over multiple years is essential to refine predictions. Our results highlight notable spatial variations in fungal spore levels and MSS characteristics even within geographically proximate areas underscoring the need for additional monitoring stations in economically important regions where airborne fungal spore data is crucial.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (DOCX 253 KB) (253.1KB, docx)

Acknowledgements

The authors acknowledge the Division of Meteorology and Climatology (Faculty of Mathematics, Physics, and Informatics of Comenius University in Bratislava) for providing the meteorological data used in this paper.

Author contribution

Matúš Žilka: data curation, formal analysis, conceptualisation, visualisation, and writing—original draft. Michal Hrabovský: data curation, formal analysis, and writing—review and editing. Jozef Dušička: data curation, formal analysis, and writing—review and editing. Eva Zahradníková: investigation, visualisation, and writing—review and editing. Dominika Gahurová: investigation, visualisation, and writing—review and editing. Jana Ščevková:methodology, supervision, validation, data curation, conceptualisation, and writing—original draft.

Funding

Open access funding provided by The Ministry of Education, Science, Research and Sport of the Slovak Republic in cooperation with Centre for Scientific and Technical Information of the Slovak Republic. This study was supported by Grant Agency VEGA (Bratislava), Grant No. 1/0180/22.

Data availability

The raw sequence reads from the amplicon-based metagenomic analysis of 12 samples mentioned in this article, along with 2 outlier samples (omitted from the analysis due to low quality), have been deposited in NCBI’s Sequence Read Archive (SRA) under BioProject accession number PRJNA1163380 (https://www.ncbi.nlm.nih.gov/bioproject/PRJNA1163380).

Declarations

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Footnotes

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

References

  1. Abrego N, Norros V, Halme P, Somervuo P, Ali-Kovero H, Ovaskainen O (2018) Give me a sample of air and I will tell which species are found from your region: molecular identification of fungi from airborne spore samples. Mol Ecol Resour 18:511–524. 10.1111/1755-0998.12755 [DOI] [PubMed] [Google Scholar]
  2. Abrego N, Crosier B, Somervuo P, Ivanova N, Abrahamyan A, Abdi A, Hämäläinen K, Junninen K, Maunula M, Purhonen P, Ovaskainen O (2020) Fungal communities decline with urbanization—more in air than in soil. ISME J 14:2806–2815. 10.1038/s41396-020-0732-1 [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Akgül H, Yılmazkaya D, Akata I, Tosunoğlu A, Bıçakçı A (2016) Determination of airborne fungal spores of Gaziantep (SE Turkey). Aerobiologia 32:441–452. 10.1007/s10453-015-9417-z [Google Scholar]
  4. Almaguer M, Aira MJ, Rodríguez-Rajo FJ, Rojas TI (2014) Temporal dynamics of airborne fungi in Havana (Cuba) during dry and rainy seasons: influence of meteorological parameters. Int J Biometeorol 58:1459–1470. 10.1007/s00484-013-0748-6 [DOI] [PubMed] [Google Scholar]
  5. Anees-Hill S, Douglas P, Pashley CH, Hansell A, Marczylo EL (2022) A systematic review of outdoor airborne fungal spore seasonality across Europe and the implications for health. Sci Total Environ 818:151716. 10.1016/j.scitotenv.2021.151716 [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Antón SF, Cruz DR, Sánchez JS, Reyes ES (2019) Analysis of the airborne fungal spores present in the atmosphere of Salamanca (MW Spain): a preliminary survey. Aerobiologia 3:447–462. 10.1007/s10453-019-09569-z [Google Scholar]
  7. Apangu GP, Adams-Groom B, Satchwell J, Pashley CH, Werner M, Kryza M, Szymanowski M, Malkiewicz M, Bruffaerts N, Hoebeke L, Grinn-Gofroń A, Grewling Ł, Roldan NG, Oliver G, Sindt Ch, Kloster M, Skjøth CA (2022a) Sentinel-2 satellite and HYSPLIT model suggest that local cereal harvesting substantially contribute to peak Alternaria spore concentrations. Agric Forest Meteorol 326:109156. 10.1016/j.agrformet.2022.109156 [Google Scholar]
  8. Apangu GP, Frisk CA, Petch GM, Muggia PA, Hanson M, Skjøth CA (2022b) Environmental DNA reveals diversity and abundance of Alternaria species in neighbouring heterogeneous landscapes in Worcester, UK. Aerobiologia 38:457–481. 10.1007/s10453-022-09760-9 [DOI] [PMC free article] [PubMed] [Google Scholar]
  9. Bednarz A, Pawłowska S (2016) A fungal spore calendar for the atmosphere of Szczecin. Poland Acta Agrobot 69:1669. 10.5586/aa.1669 [Google Scholar]
  10. Belčáková I, Slámová M, Demovičová Z (2022) Importance of urban green areas in the context of current and future global changes: lessons learned from a case study in Bratislava (Slovakia). Sustainability 14:14740. 10.3390/su142214740 [Google Scholar]
  11. Charalampopoulos A, Damialis A, Vokou D (2022) Spatiotemporal assessment of aeromycoflora under differing urban green space, sampling height, and meteorological regimes: the atmospheric fungiscape of Thessaloniki, Greece. Int J Biometeorol 66:895–909. 10.1007/s00484-022-02247-9 [DOI] [PubMed] [Google Scholar]
  12. Crameri R, Garbani M, Rhyner C, Huitema C (2014) Fungi: the neglected allergenic sources. Allergy 69:176–185. 10.1111/all.12325 [DOI] [PubMed] [Google Scholar]
  13. Dai YC, Cui BK, Yuan HS, Li BD (2007) Pathogenic wood-decaying fungi in China. For Pathol 37:105–120. 10.1111/j.1439-0329.2007.00485.x [Google Scholar]
  14. D’Amato G, Murrieta-Aguttes M, D’Amato M, Ansotegui IJ (2023) Pollen respiratory allergy: is it really seasonal? World Allergy Organ J 16:100799. 10.1016/j.waojou.2023.100799 [DOI] [PMC free article] [PubMed] [Google Scholar]
  15. Damialis A, Kaimakamis E, Konoglou M, Akritidis I, Traidl-Hoffmann C, Gioulekas D (2017) Estimating the abundance of airborne pollen and fungal spores at variable elevations using an aircraft: how high can they fly? Sci Rep 7:44535. 10.1038/srep44535 [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Damialis A, Mohammad AB, Halley JM, Gange AC (2015) Fungi in a changing world: growth rates will be elevated, but spore production may decrease in future climates. Int J Biometeorol 59:1157–1167. 10.1007/s00484-014-0927-0 [DOI] [PubMed] [Google Scholar]
  17. Debeljak P, Baltar F (2023) Fungal diversity and community composition across ecosystems. J Fungi 9:510. 10.3390/jof9050510 [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. Denning DW, O’Driscoll BR, Hogaboam CM, Bowyer P, Niven RM (2006) The link between fungi and severe asthma: a summary of the evidence. Eur Respir J 27:615–626. 10.1183/09031936.06.00074705 [DOI] [PubMed] [Google Scholar]
  19. Dey D, Ghosal K, Bhattacharya SG (2019) Aerial fungal spectrum of Kolkata, India, along with their allergenic impact on the public health: a quantitative and qualitative evaluation. Aerobiologia 35:15–25. 10.1007/s10453-018-9534-6 [Google Scholar]
  20. Dijksterhuis J (2019) Fungal spores: highly variable and stress-resistant vehicles for distribution and spoilage. Food Microbiol 81:2–11. 10.1016/j.fm.2018.11.006 [DOI] [PubMed] [Google Scholar]
  21. Domina G, Di Gristina E, Barone G (2024) Main poisonous and allergenic plant species in Sicilian gardens and parks: applications and recommendations for use. Plants 13:1031. 10.3390/plants13071031 [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Elbert W, Taylor PE, Andreae MO, Pöschl U (2007) Contribution of fungi to primary biogenic aerosols in the atmosphere: wet and dry discharged spores, carbohydrates, and inorganic ions. Atmos Chem Phys 7:4569–4588. 10.5194/acp-7-4569-2007 [Google Scholar]
  23. Fröhlich-Nowoisky J, Pickersgill DA, Després VR, Pöschl U (2009) High diversity of fungi in air particulate matter. PNAS 106:12814–12819. 10.1073/pnas.0811003106 [DOI] [PMC free article] [PubMed] [Google Scholar]
  24. Galán C, Smith M, Damialis A, Frenguelli G, Gehrig R, Grinn-Gofroń A, Kasprzyk I, Magyar D, Oteros J, Šaulienė I, Thibaudon M, Sikoparija B (2021) Airborne fungal spore monitoring: between analyst proficiency testing. Aerobiologia 37:351–361. 10.1007/s10453-021-09698-4 [Google Scholar]
  25. Gange AC, Gange EG, Sparks TH, Boddy L (2007) Rapid and recent changes in fungal fruiting patterns. Science 316:71. 10.1126/science.1137489 [DOI] [PubMed] [Google Scholar]
  26. Gioulekas D, Damialis A, Papakosta D, Spieksma F, Giouleka P, Patakas D (2004) Allergenic fungi spore records (15 years) and sensitization in patients with respiratory allergy in Thessaloniki-Greece. J Investig Allergol Clin Immunol 14:225–231 [PubMed] [Google Scholar]
  27. Grant Smith E (2000) Sampling and identifying allergenic pollens and moulds. Blewstone Press, San Antonio, TX [Google Scholar]
  28. Gravesen G (1979) Fungi as a cause of allergic disease. Allergy 34:134–154. 10.1111/j.1398-9995.1979.tb01562.x [DOI] [PubMed] [Google Scholar]
  29. Grewling Ł, Magyar D, Chłopek K, Grinn-Gofron A, Gwiazdowska J, Siddiquee A et al (2022) Bioaerosols on the atmospheric super highway: an example of long distance transport of Alternaria spores from the Pannonian Plain to Poland. Sci Total Environ 819:153148. 10.1016/j.scitotenv.2022.153148 [DOI] [PubMed] [Google Scholar]
  30. Grinn-Gofroń A, Bosiacka B (2015) Effects of meteorological factors on the composition of selected fungal spores in the air. Aerobiologia 31:63–72 [DOI] [PMC free article] [PubMed] [Google Scholar]
  31. Grinn-Gofroń A, Bosiacka B, Bednarz A, Wolski T (2018) A comparative study of hourly and daily relationships between selected meteorological parameters and airborne fungal spore composition. Aerobiologia 34:45–54. 10.1007/s10453-017-94933 [DOI] [PMC free article] [PubMed] [Google Scholar]
  32. Grinn-Gofroń A, Çeter T, Pinar NM, Bosiacka B, Çeter S, Keçeli T, Myśliwy M, Şahin AA, Bogawski P (2020) Airborne fungal spore load and season timing in the Central and Eastern Black Sea region of Turkey explained by climate conditions and land use. Agr Forest Meteorol 295:108191. 10.1016/j.agrformet.2020.108191 [Google Scholar]
  33. Grossart H-P, Van den Wyngaert S, Kagami M, Wurzbacher C, Cunliffe M, Rojas-Jimenez K (2019) Fungi in aquatic ecosystems. Nat Rev Microbiol 17:339–354. 10.1038/s41579-019-0175-8 [DOI] [PubMed] [Google Scholar]
  34. Haas D, Ilieva M, Fritz T, Galler H, Habib J, Kriso A, Kropsch M, Ofner-Kopeinig P, Reinthaler FF, Strasser A, Zentner E, Schalli M (2023) Background concentrations of airborne, culturable fungi and dust particles in urban, rural and mountain regions. Sci Total Environ 892:164700. 10.1016/j.scitotenv.2023.164700 [DOI] [PubMed] [Google Scholar]
  35. Herrero AD, Ruiz SS, Bustillo MG, Morales PC (2006) Study of airborne fungal spores in Madrid, Spain. Aerobiologia 22:133–140. 10.1007/s10453-006-9025-z [Google Scholar]
  36. Huffman JA, Sinha B, Garland RM, Snee-Pollmann A, Gunthe SS, Artaxo P, Martin ST, Andreae MO, Pöschl U (2012) Size distributions and temporal variations of biological aerosol particles in the Amazon rainforest characterized by microscopy and real-time UV-APS fluorescence techniques during AMAZE-08. Atmos Chem Phys 12:11997–12019. 10.5194/acp-12-11997-2012 [Google Scholar]
  37. Ianovici N (2016) Atmospheric concentrations of selected allergenic fungal spores in relation to some meteorological factors, in Timişoara (Romania). Aerobiologia 1:139–156. 10.1007/s10453-016-9427-5 [Google Scholar]
  38. Irfeey AMM, Chau H-W, Sumaiya MMF, Wai CY, Muttil N, Jamei E (2023) Sustainable mitigation strategies for urban heat island effects in urban areas. Sustainability 15:10767. 10.3390/su151410767 [Google Scholar]
  39. Jones AM, Harrison RM (2004) The effects of meteorological factors on atmospheric bioaerosol concentrations: a review. Sci Total Environ 326:151–180. 10.1016/j.scitotenv.2003.11.021 [DOI] [PubMed] [Google Scholar]
  40. Kasprzyk I, Worek M (2006) Airborne fungal spores in urban and rural environments in Poland. Aerobiologia 22:169–176. 10.1007/s10453-006-9029-8 [Google Scholar]
  41. Katotomichelakis M, Nikolaidis C, Makris M, Proimos E, Aggelides X, Constantinidis TC, Papadakis CE, Danielides V (2016) Alternaria and Cladosporium calendar of Western Thrace: relationship with allergic rhinitis symptoms. Laryngoscope 126:E51-56. 10.1002/lary.25594 [DOI] [PubMed] [Google Scholar]
  42. Khachatourians GG (2019) Insecticides, microbial. reference module in life sciences. Elsevier. 10.1016/B978-0-12-809633-8.13066-3
  43. Khattab A, Levetin E (2008) Effect of sampling height on the concentration of airborne fungal spores. Ann Allergy Asthma Immunol 101:529–534. 10.1016/S1081-1206(10)60293-1 [DOI] [PubMed] [Google Scholar]
  44. Klaric MS, Pepeljnjak S (2006) A year-round aeromycological study in Zagreb area, Croatia. Ann Agric Environ Med 13:55–64 [PubMed] [Google Scholar]
  45. Kwong K, Robinson M, Sullivan A, Letovsky S, Liu AH, Valcour A (2023) Fungal allergen sensitization: prevalence, risk factors, and geographic variation in the United States. J Allergy Clin Immunol 152:1658–1668. 10.1016/j.jaci.2023.09.010 [DOI] [PubMed] [Google Scholar]
  46. Lacey ME, West JS (2006) The air spora. The manual for catching and identifying airborne biological particles. Springer, Dordrecht [Google Scholar]
  47. Leiminger JH, Hausladen H (2012) Early blight control in potato using disease-orientated threshold values. Plant Dis 96:124–130. 10.1094/PDIS-05-11-0431 [DOI] [PubMed] [Google Scholar]
  48. Li D-W, Magyar D, Kendrick B (2023) Color atlas of fungal spores: a laboratory identification guide. American Conference of Governmental Industrial Hygienists (ACGIH), 852
  49. Liu H, Hu Z, Zhou M, Hu J, Yao X, Zhang H, Li Z, Lou L, Xi C, Qian H, Li C, Xu X, Zheng P, Hu B (2019) The distribution variance of airborne microorganisms in urban and rural environments. Environ Pollut 247:898–906. 10.1016/j.envpol.2019.01.090 [DOI] [PubMed] [Google Scholar]
  50. Memon R, Leung D, Chunho L (2008) A review on the generation, determination and mitigation of urban heat island. J Environ Sci 20:120–128. 10.1016/S1001-0742(08)60019-4 [DOI] [PubMed] [Google Scholar]
  51. Muafa MHM, Quach ZM, Al-Shaarani AAQA, Nafis MMH, Pecoraro L (2024) The influence of car traffic on airborne fungal diversity in Tianjin, China (in press). 10.6084/m9.figshare.25019113.v1 [DOI] [PMC free article] [PubMed]
  52. Nilsson S, Persson S (1981) Tree pollen spectra in the Stockholm region (Sweden), 1973–1980. Grana 20:179–182. 10.1080/00173138109427661 [Google Scholar]
  53. Niu M, Hu W, Cheng B, Wu L, Ren L, Deng J, Shen F, Fu P (2021) Influence of rainfall on fungal aerobiota in the urban atmosphere over Tianjin, China: a case study. Atmos Environ X 12:100137. 10.1016/j.aeaoa.2021.100137 [Google Scholar]
  54. Núñez A, Amo De Paz G, Rastrojo A, Ferencova Z, Gutiérrez-Bustillo AM, Alcamí A, Moreno DA (2019) Temporal patterns of variability for prokaryotic and eukaryotic diversity in the urban air of Madrid (Spain). Atmos Environ 217:116972. 10.1016/j.atmosenv.2019.116972 [Google Scholar]
  55. Oliveira M, Ribeiro H, Delgado JL, Abreu I (2009) Seasonal and intradiurnal variation of allergenic fungal spores in urban and rural areas of the North of Portugal. Aerobiologia 25:85–98. 10.1007/s10453-009-9112-z [Google Scholar]
  56. Oliveira M, Delgado L, Ribeiro H, Abreu I (2010) Fungal spores from Pleosporales in the atmosphere of urban and rural locations in Portugal. J Environ Monit 12:1187–1194. 10.1039/B913705J [DOI] [PubMed] [Google Scholar]
  57. Oliver RP, Hewitt HG (2014) Fungicides in crop protection. CAB International, Oxfordshire, Boston [Google Scholar]
  58. Olsen Y, Skjøth C, Hertel O, Rasmussen K, Sigsgaard T, Gosewinkel U (2020) Airborne Cladosporium and Alternaria spore concentrations through 26 years in Copenhagen, Denmark. Aerobiologia 36:141–157. 10.1007/s10453-019-09618-7 [Google Scholar]
  59. Pashley CH, Wardlaw AJ (2021) Allergic fungal airways disease (AFAD): an under-recognised asthma endotype. Mycopathologia 186:609–622. 10.1007/s11046-021-00562-0 [DOI] [PMC free article] [PubMed] [Google Scholar]
  60. Pashley CH, Fairs A, Free RC, Wardlaw AJ (2012) DNA analysis of outdoor air reveals a high degree of fungal diversity, temporal variability, and genera not seen by spore morphology. Fungal Biol 116:214–224. 10.1016/j.funbio.2011.11.004 [DOI] [PubMed] [Google Scholar]
  61. Phukhamsakda C, Nilsson RH, Bhunjun CS, de Farias ARG, Sun Y-R, Wijesinghe SN et al (2022) The numbers of fungi: contributions from traditional taxonomic studies and challenges of metabarcoding. Fungal Divers 114:327–386. 10.1007/s13225-022-00502-3 [Google Scholar]
  62. Polčák N, Šťastný P (2011) Topography influence on wind condition of Bratislava. In: Středová H, Rožnovský J, Litschmann T (eds) Mikroklíma a mezoklíma krajinných struktur a antropogenních prostředí. Sborník abstraktů z mezinárodní konference. Český hydrometeorologický ústav, Praha, 52 (in Slovak)
  63. Pyrri I, Kapsanaki-Gotsi E (2015) Evaluation of the fungal aerosol in Athens, Greece, based on spore analysis. Aerobiologia 31:179–190. 10.1007/s10453-014-9355-1 [Google Scholar]
  64. Rapiejko P, Stankiewicz W, Szczygielski K, Jurkiewicz D (2007) Progowe stężenie pyłku roślin niezbędnedo wywołania objawów alergicznych./Threshold pollen count necessary to evoke allergic symptoms. Otolaryngol Pol LXI 4:591–594 (in Polish) [DOI] [PubMed] [Google Scholar]
  65. Rodriguez RJ, Redman RS (1997) Fungal life-styles and ecosystem dynamics: biological aspects of plant pathogens, plant endophytes and saprophytes. In: Andrews JH, Tommerup IC, Callow JA (eds) Advances in botanical research. Academic Press 24: 169–193. 10.1016/S0065-2296(08)60073-7
  66. Ruas RB, Costa LMS, Bered F (2022) Urbanization driving changes in plant species and communities – a global view. Glob Ecol Conserv 38:e02243. 10.1016/j.gecco.2022.e02243 [Google Scholar]
  67. Sadyś M, Skjøth CA, Kennedy R (2014) Back-trajectories show export of airborne fungal spores (Ganoderma sp.) from forests to agricultural and urban areas in England. Atmos Environ 84:88–99. 10.1016/j.atmosenv.2013.11.015 [Google Scholar]
  68. Sadyś M, Strzelczak A, Grinn-Gofroń A, Kennedy R (2015) Application of redundancy analysis for aerobiological data. Int J Biometeorol 59:25–36. 10.1007/s00484-014-0818-4 [DOI] [PubMed] [Google Scholar]
  69. Sadyś M, Adams-Groom B, Herbert RJ, Kennedy R (2016a) Comparisons of fungal spore distributions using air sampling at Worcester, England (2006–2010). Aerobiologia 32:619–634. 10.1007/s10453-016-9436-4 [Google Scholar]
  70. Sadyś M, Skjøth CA, Kennedy R (2016b) Forecasting methodologies for Ganoderma spore concentration using combined statistical approaches and model evaluations. Int J Biometeorol 60:489–498. 10.1007/s00484-015-1045-3 [DOI] [PubMed] [Google Scholar]
  71. Ščevková J, Kováč J (2019) First fungal spore calendar for the atmosphere of Bratislava, Slovakia. Aerobiologia 35:343–356. 10.1007/s10453-019-09564-4 [Google Scholar]
  72. Schröder PC, Li J, Wong GW, Schaub B (2015) The rural–urban enigma of allergy: what can we learn from studies around the world? Pediatr Allergy Immunol 26:95–102. 10.1111/pai.12341 [DOI] [PubMed] [Google Scholar]
  73. Scott ES, Dambergs RG, Stummer BE, Petrovic T (2022) 13 - Fungal contaminants in the vineyard and wine quality and safety. In: Reynolds AG (ed) Managing wine quality (2nd Edition) (pp 587–623). Woodhead Publishing. 10.1016/B978-0-08-102067-8.00006-3
  74. Sesartic A, Dallafior TN (2011) Global fungal spore emissions, review and synthesis of literature data. Biogeosciences 8:1181–1192. 10.5194/bg-8-1181-2011 [Google Scholar]
  75. Simović I, Matavulj P, Šikoparija B (2023) Manual and automatic quantification of airborne fungal spores during the wheat harvest period. Aerobiologia 39:227–239. 10.1007/s10453-023-09788-5 [Google Scholar]
  76. Solairaj D, Legrand NNG, Yang Q, Liu J, Zhang H (2022) Microclimatic parameters affect Cladosporium rot development and berry quality in table grapes. Hortic Plant J 8:171–183. 10.1016/j.hpj.2021.07.002 [Google Scholar]
  77. Spieksma FTM (1991) Regional European pollen calendars. In: D’Amato G, Spieksma FTM, Bonini S (eds) Allergenic pollen and pollinosis in Europe. Blackwell Scientific Publications, Oxford, pp 49–65 [Google Scholar]
  78. Symon FA, Anees-Hill S, Satchwell J, Fairs A, Edwards R, Wardlaw AJ, Wardlaw J, Cuthbertson L, Hansell A, Pashley CH (2023) A fungal spore calendar for England: analysis of 13 years of daily concentrations at Leicester. UK (preprint). 10.1101/2023.12.15.571848 [Google Scholar]
  79. Sztandera-Tymoczek M, Szuster-Ciesielska A (2023) Fungal aeroallergens – the impact of climate change. J Fungi 9:544. 10.3390/jof9050544 [DOI] [PMC free article] [PubMed] [Google Scholar]
  80. Talley SM, Coley PD, Kursar TA (2002) The effects of weather on fungal abundance and richness among 25 communities in the Intermountain West. BMC Ecol 2:7. 10.1186/1472-6785-2-7 [DOI] [PMC free article] [PubMed] [Google Scholar]
  81. Troutt C, Levetin E (2001) Correlation of spring spore concentrations and meteorological conditions in Tulsa, Oklahoma. Int J Biometeorol 45:64–74. 10.1007/s004840100087 [DOI] [PubMed] [Google Scholar]
  82. Wagner R, Montoya L, Gao C, Head J, Remais J, Taylor J (2022) The air mycobiome is decoupled from the soil mycobiome in the California San Joaquin Valley. Mol Ecol 31:4962–4978. 10.1111/mec.16640 [DOI] [PMC free article] [PubMed] [Google Scholar]
  83. Wang Q, Wang Y, Fan Y, Hang J, Li Y (2019) Urban heat island circulations of an idealized circular city as affected by background wind speed. Build Environ 148:433–447. 10.1016/j.buildenv.2018.11.024 [Google Scholar]
  84. Werbin ZR, Heidari L, Buckley S, Brochu P, Butler LJ, Connolly C, Bloemendaal LH, McCabe TD, Miller TK, Hutyra LR (2020) A tree-planting decision support tool for urban heat mitigation. PLoS ONE 15:e0224959. 10.1371/journal.pone.0224959 [DOI] [PMC free article] [PubMed] [Google Scholar]
  85. Weryszko-Chmielewska E, Kasprzyk I, Nowak M, Sulborska A, Kaczmarek J, Szymanska A, Haratym W, Jedryczka M (2018) Health hazards related to conidia of Cladosporium—biological air pollutants in Poland, central Europe. J Environ Sci 65:271–281. 10.1016/j.jes.2017.02.018 [DOI] [PubMed] [Google Scholar]
  86. White TJ, Bruns TD, Lee SB, Taylor JW (1990) Amplification and direct sequencing of fungal ribosomal RNA genes for phylogenetics. In: Innis MA, Gelfand DH, Sninsky JJ, White TJ (eds) PCR protocols: a guide to methods and applications. Academic Press, New York, 315–322. 10.1016/B978-0-12-372180-8.50042-1
  87. Wouters H, De Ridder K, Poelmans L, Willems P, Brouwers J, Hosseinzadehtalaei P, Tabari H, Broucke SV, van Lipzig NPM, Demuzere M (2017) Heat stress increase under climate change twice as large in cities as in rural areas: a study for a densely populated midlatitude maritime region. Geophys Res Lett 44:8997–9007. 10.1002/2017GL074889 [Google Scholar]
  88. Yamamoto N, Bibby K, Qian J, Hospodsky D, Rismani-Yazdi H, Nazaroff WW, Peccia J (2012) Particle-size distributions and seasonal diversity of allergenic and pathogenic fungi in outdoor air. ISME J 6:1801–1811. 10.1038/ismej.2012.30 [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplementary file1 (DOCX 253 KB) (253.1KB, docx)

Data Availability Statement

The raw sequence reads from the amplicon-based metagenomic analysis of 12 samples mentioned in this article, along with 2 outlier samples (omitted from the analysis due to low quality), have been deposited in NCBI’s Sequence Read Archive (SRA) under BioProject accession number PRJNA1163380 (https://www.ncbi.nlm.nih.gov/bioproject/PRJNA1163380).

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