Bacterial Aerosol in Ambient Air—A Review Study

Abstract

Bioaerosols, including airborne bacteria, are significant pollutants affecting both indoor and outdoor air quality, with implications for human health. Despite extensive research on indoor air quality, there is a notable lack of comprehensive data on ambient bacterial concentrations and their interactions with pollutants and meteorological factors. This review focuses on bacterial aerosols in the atmosphere, measured using the culture-based method, considered the “gold standard” for microorganism detection and identification. Studies reveal significant variability in bacterial concentrations across different environments and seasons, influenced by factors such as temperature, humidity, wind speed, solar radiation, and precipitation, underscoring the need for further research and monitoring to enhance health risk assessments and mitigation strategies. The presence of air pollutants such as particulate matter (PM) and ozone (O₃) further complicates these dynamics. The authors emphasize the need for more extensive research on outdoor bacterial aerosols and recommend that future studies prioritize detailed bioaerosol characterization to establish comprehensive exposure standards in ambient air, thereby improving public health protection and environmental management practices.

1. Introduction

Bioaerosols, comprising airborne biological particles, represent a significant category of pollutants. Both indoor and outdoor air quality directly impact human health [1,2,3]. Although individuals spend 80–90% of their time indoors [4,5,6], indoor air quality (IAQ) is significantly influenced by bioaerosols originating from the outdoor environment [7,8,9]. Consequently, comprehensive monitoring of ambient aerosol concentrations is crucial not only for environmental management but also for assessing the health impacts of microbiological air pollution (MAP).

Bioaerosols can infiltrate indoor spaces through natural ventilation routes, such as windows and doors, contributing to a range of health issues, including infectious, allergic, and toxic diseases, and even cancer [10,11,12,13]. The health impacts of bioaerosols are influenced not only by their biological characteristics and chemical composition but also by the volume inhaled and the specific regions within the respiratory tract where deposition occurs [14]. Since particle deposition in the respiratory system is closely linked to aerodynamic diameter, the health effects of bioaerosols are largely dependent on their physical properties, particularly size distribution [15,16,17].

Bioaerosols refer to airborne particles suspended in a gas that may contain (i) intact living or dead microorganisms (as single units, in homogeneous or heterogeneous groups, or attached to other particles); (ii) microbial spores (resistant reproductive structures produced by many fungi and some bacteria); (iii) fragments of microorganisms and larger organisms (e.g., body parts of arthropods, skin scales from mammals, pollen, and plant debris); and (iv) other particles from living or dead organisms (e.g., excreta from arthropods such as dust mites and cockroaches, allergens from microorganisms, plants, animals, and microbial toxins) [18].

Humans typically inhale air containing approximately 10⁶ airborne microorganisms per day [19,20]. Bioaerosols constitute 20–30% of the total atmospheric particulate matter larger than 0.2 μm [21,22], while other studies report that 5–10% of the total suspended particulate mass is composed of bioaerosols [23,24]. Among these, bacteria, fungal spores, and pollen are the most prevalent. Airborne bacteria are a major component of microbiological air pollution (MAP), representing over 80% of the total microbial load in the atmosphere [23]. Bacteria have been detected in various atmospheric layers, including the atmospheric boundary layer (up to 1.5 km altitude), the upper troposphere (up to 12 km altitude), and even the stratosphere at altitudes of 20 km and 41 km above sea level [25]. However, they are most abundant in the lower atmosphere, where atmospheric transport affects the distribution and spread of organisms and species. Bioaerosol transport is believed to be analogous to the transport of heat and moisture, influencing the rate of evolution, the formation of new species and microbial communities, and the adaptation to changing environments [11]. Current knowledge of the distribution of bacteria in the atmosphere remains limited, as most bioaerosol studies to date have focused on indoor air quality (IAQ) [26,27,28,29,30,31,32,33].

In this review, we focus on bacterial aerosols and their interactions with critical pollutants such as particulate matter (PM) and ozone (O₃), as well as their sensitivity to meteorological parameters such as temperature, relative humidity, wind speed, rainfall, and solar radiation. Understanding bacterial concentrations in the atmospheric boundary layer is essential for assessing potential health impacts related to air quality. Despite its importance, there is a notable shortage of comprehensive data on the correlation between ambient bacterial concentrations and other pollutants and meteorological factors, highlighting the urgent need for more extensive research on bacterial aerosols in outdoor environments.

We chose to collect data on culturable bacterial concentrations in CFU/m³ for several reasons. This unit of measurement enables quantitative analysis of viable bacterial concentrations in the air, offering standardization as CFU (colony-forming unit) is a widely accepted metric in microbiology. This facilitates consistent comparisons across studies and environmental contexts. Moreover, the culture-based method is simple, cost-effective, and suitable for both quantitative and qualitative analyses, particularly in low- and middle-income countries where understanding bioaerosol concentrations in CFU/m³ of inhaled air is critical for health impact assessments, as higher concentrations are associated with adverse health effects.

2. Sources of Bacterial Aerosol in Ambient Air

Bacteria enter the near-surface atmosphere through aerosolization from various surfaces exposed to air currents. Jones and Harrison [34] propose that bacteria from soil and plant surfaces are released into the air through the resuspension of particles, a concept supported by numerous studies. For example, research by Bertolini et al. [35], Shaffer and Lighthart [36], and Tong and Lighthart [37] has demonstrated a correlation between land cover types and bacterial concentrations in near-surface air.

Additionally, the composition of airborne bacterial communities is shaped by geographical factors such as landscape and land use. For instance, crop harvesting has been shown to significantly increase the number of airborne bacteria [20]. Identifying the sources of bacteria in outdoor environments presents challenges due to the diverse range of organisms and events that contribute to the release and transport of microorganisms.

Global research reveals significant variability in bacterial concentrations across different outdoor environments, with notable seasonal fluctuations [38,39,40]. The World Health Organization (WHO) recommends a maximum concentration of 300 CFU/m³ for airborne bacteria in environments occupied by immunocompromised individuals. In contrast, several countries have established higher thresholds: Finland (4500 CFU/m³), Germany, and the Netherlands (10,000 CFU/m³). The UK and Ireland have set specific exposure limits for green waste composting sites with “sensitive receptors” (i.e., locations where individuals are present for more than six hours at a time). The ambient environmental compliance parameter at 250 m downwind is set at 1000 (+30%) CFU/m³ for total bacteria, as outlined in the “Technical Guidance Note M9: Monitoring Methods for Ambient Air” by the UK Environment Agency [41]. Among the studies reviewed (Table S1), the lowest average concentrations of ambient bacteria (<100 CFU/m³) were reported in Mexico [42], during summer in Iran [43], and during winter in Poland [4,44] and France (Porquerolles Island) [45]. In contrast, the highest average concentrations (>1000 CFU/m³) were found in Vietnam [46], China [47,48], India [49], Pakistan [50], and Korea [40].

Geographic and climatic factors play a crucial role in shaping outdoor microbial concentrations. The dispersion of bioaerosols is primarily governed by hydrodynamic and kinetic mechanisms, while their persistence and fate are influenced by their chemical composition and the meteorological conditions they encounter [51].

Furthermore, bioaerosols can function as typical atmospheric aerosols, exerting a significant influence on the climate system by serving as cloud condensation nuclei (CCN) and ice nuclei, thereby participating in cloud formation and the cloud water cycle [11,22,52]. Due to their aerodynamic buoyancy, bioaerosols can be transported over vast distances [53], facilitating the dissemination of trace elements and pathogens far from their original sources [54].

3. Discussion

It is well recognized that bacteria present in outdoor air are influenced by various factors [55,56]. In an extensive review, Smets et al. [57] discussed factors such as sources, dispersal, deposition, survival, meteorological conditions, location, time, and atmospheric composition, highlighting their impacts on human health and the role of bacteria in regional and global climate feedback mechanisms. Our review focused on air pollutants and meteorological factors, as these parameters are relatively straightforward to measure. Following the methodology of Zhen et al. [8], who employed quantitative polymerase chain reaction (qPCR), we aim to test their hypothesis that meteorological factors have a greater influence on shaping airborne bacterial communities than air pollutants.

Although culture-independent methods have gained popularity [58,59,60], the high cost of PCR has led many researchers to continue using culture-based methods to identify bacteria. Figure 1 illustrates the bacterial measurement points obtained using single- or six-stage impactor culture-based methods, conducted alongside pollutant concentrations and/or meteorological parameters. As shown, no such research has been conducted yet in regions like Africa, where bioaerosols of natural origin play a significant role in public health, agriculture, and the near-surface atmosphere. In such regions, simple and inexpensive culture-based methods can be used for both quantitative and qualitative analyses of bioaerosols [61].

This review examines the correlation coefficients and p values that indicate the presence or absence of statistically significant relationships between total bacterial concentrations and environmental variables such as particulate matter (PM₁, PM_2.5, and PM₁₀) and ozone (O₃), as presented in

Table 1. Correlation coefficients or p values between total bacteria and selected air pollutants.

Independent Variable	Correlation		Total Bacteria	References
	R	p	CFU/m3
PM1, μg/m3
68–120	0.60	*	1963 ± 616	[49]
PM2.5, μg/m3
12.9 ± 8.4 78.8 ± 47.8	0.020 spring −0.261 winter	*	355 (80–1124) 65 (4–265)	[4]
93.24 ± 14.05	0.652	**	570 ± 313	[24]
40 ± 25 29 ± 19	dust days and non-dust days	>0.05	1–40 6–68	[40]
16.6–40.4		>0.05	35–116	[43]
108.5 ± 42.3 146.9 ± 93.4	0.139 autumn −0.491 winter	*	523.5 ± 301.1 581 ± 305.4	[47]
90 (11–230)	0.6	*	4595 ± 3410	[48]
95–150	0.55	*	1963 ± 616	[49]
31.3–214.7	0.808	**	497.7–1736.5	[62]
57.04–355.67	−0.300 FB −0.249 CB		129–5035 (FB + CB)	[63]
8–32	−0.0505		36.7–268.04	[64]
13.74–72.57 9.08–62.88 11.08–61.19	0.77 pre-COVID-19 0.60 during COVID-19 0.67 post-COVID-19		782 602 529	[65]
PM10, μg/m3
27.4 ± 21.5 90.5 ± 50.4	−0.067 spring −0.301 winter	*	355 (80–1124) 65 (4–265)	[4]
241 ± 165 58 ± 32	0.573 dust days non-dust days	* >0.05	1–40 6–68	[40]
144 (29–315)	0.6	*	4595 ± 3410	[48]
160–230	0.75	*	1963 ± 616	[49]
16–112	0.0883		36.7–268.04	[64]
16.33–87.65 14.36–83.13 17.80–70.37	0.89 pre-COVID-19 0.80 during COVID-19 0.81 post-COVID-19		782 602 529	[65]
26–230	0.40	*	14–2999	[66]
O3, μg/m3
9.8 ± 9.4 13.1 ± 9.8	0.016 autumn −0.795 winter	**	523.5 ± 301.1 581 ± 305.4	[47]
46 (5–160)	−0.6	**	4595 ± 3410	[48]
44.35–88.6	0.5252	*	36.7–268.04	[64]

* p < 0.05, ** p < 0.01, FB—fine bacteria, CB—coarse bacteria.

. Additionally, it explores meteorological parameters, including temperature, relative humidity, solar radiation, wind speed, and rainfall, illustrating the complexity of these interactions based on local and temporal conditions (

Table 2. Correlation coefficients or p values between total bacteria and environmental factors.

Independent Variable	Correlation		Total Bacteria	References
	R	p	CFU/m3
Temperature, °C
18.7 ± 4.7 −3.6 ± 4.4	−0.316 spring 0.675 winter	* *	355 (80–1124) 65 (4–265)	[4]
23.28 (16.0–38.7)	−0.618	**	570 ± 313	[24]
16.8–31.2 24.8–31.7	0.531 winter 0.293 spring	*	1–40 6–68	[42]
6.9–30.3		−0.04	35–116	[43]
15–20 29–25 >25 10–15 15–20	city city city island island	0.04 0.006	801 736 752 68 88	[45]
29.9–33.89	0.440		790.6–1514.8	[46]
11.4 ± 3.7 5 ± 3.3	−0.471 autumn 0.314 winter	*	523.5 ± 301.1 581 ± 305.4	[47]
5.6 (−8.1–23.9)	−0.3		4595 ± 3410	[48]
17.0–30.1	0.70	*	1963 ± 616	[49]
11.1–20.6	0.088		497.7–1736.5	[62]
26–33	−0.334 FB −0.285 CB	** *	129–5035 (FB + CB)	[63]
−2–9	0.5468	*	36.7–268.04	[64]
−9.8–12.03 −2.24–12.29 −0.79–14.87	−0.27 pre-COVID-19 0.28 during COVID-19 0.41 post-COVID-19		782 602 529	[65]
11.8–30.1	0.08		14–2999	[66]
26–40	−0.66 GPB −0.64 GNB		21–272 21–352	[67]
−2.5–26.4	−0.256 TB −0.203 MB		33–664 63–815	[68]
−8.7–26.7	0.716	*	101–3800	[69]
17.66–35.6	−0.073		111–536	[70]
Relative humidity, %
72.2 ± 15.7 77.4 ± 11.2	0.156 spring 0.351 winter	*	355 (80–1124) 65 (4–265)	[4]
45 (22–72)		>0.05	570 ± 313	[24]
10.7–40 14.3–43.4	0.150 winter 0.530 spring	*	1–40 6–68	[42]
12.7–58.2		>0.05	35–116	[43]
<50 >50 <50 >50	city city island island	0.529 0.291	868 609 57 53	[45]
58.04–76.3	−0.530		790.6–1514.8	[46]
66.6 ± 13.8 54.4 ± 8.9	0.041 autumn 0.121 winter		523.5 ± 301.1 581 ± 305.4	[47]
43.6 (12–89)	0.6	*	4595 ± 3410	[48]
36.5–74.6	0.64	*	1963 ± 616	[49]
63.57–84.43	0.500		497.7–1736.5	[62]
20.72–76.5	−0.233 FB −0.221 CB		129–5035 (FB + CB)	[63]
43–93	−0.7410	*	36.7–268.04	[64]
53.96–92.8 35.43–88.79 34.83–89.29	0.05 pre-COVID-19 −0.10 during COVID-19 −0.20 post-COVID-19		782 602 529	[65]
55.6–85	−0.416* TB −0.273 MB		33–664 63–815	[68]
8.5–59	−0.720	*	101–3800	[69]
46.7–60.7	−0.006		111–536	[70]
Solar radiation, W/m2
461.1 ± 246.5 145.4 ± 118.5	−0.329 spring −0.603 winter	* *	355 (80–1124) 65 (4–265)	[4]
1.5–12.3 UVindex		>0.05	35–116	[43]
358–596	0.49		1963 ± 616	[49]
2.9771–16.7346	−0.489		497.7–1736.5	[62]
230–840	0.673	*	101–3800	[69]
Wind speed, m/s
2.58 ± 1.44 4.00 ± 1.75	−0.040 spring −0.102 winter		355 (80–1124) 65 (4–265)	[4]
3.7 (0–6)		>0.05	570 ± 313	[24]
1.9–3.3		0.009	35–116	[43]
15–25 (knots) >25 (knots) <10 (knots) 10–15 (knots) 15–25 (knots) >25 (knots) <10 (knots)	city city city city island island island	<0.0001 <0.001	924 2069 469 868 38 135 36	[45]
1.24–2.42	0.06		1963 ± 616	[49]
0.6–3.11 0.53–3.34 0.42–3.34	−0.06 pre-COVID-19 0.05 during COVID-19 −0.07 post-COVID-19		782 602 529	[65]
	0.08		14–2999	[66]
2.3–5.4	−0.030 TB −0.017 MB		33–664 63–815	[68]
2.38–4.86	0.659	*	101–3800	[69]
Rainfall, mm
0–8.48	0.42	*	1963 ± 616	[49]
1.5–4.3	−0.385		101–3800	[69]

* p < 0.05, ** p < 0.01, GPB—Gram-positive bacteria, GNB—Gram-negative bacteria, TB—terrestrial bacteria, MB—marine bacteria, FB—fine bacteria, CB—coarse bacteria.

). A comprehensive table (Table S1) containing all relevant details and results from the selected studies is provided in the Supplementary Materials.

As shown in Table 1 and Table 2, researchers most frequently analyze correlations between bacterial aerosols and fine particles (PM_2.5), temperature, and humidity. The fewest studies involve submicron particles (PM₁) and rainfall. The data highlight the influence of location (terrestrial and marine) and season, particularly winter. However, we did not distinguish between haze and non-haze days, following the approach of Gao et al. [63], who analyzed bacterial concentrations under different air pollutant levels during the same month, as well as the same pollutant levels across different months, and found no significant differences between haze and non-haze days.

3.1. Interactions with Air Pollutants

3.1.1. Particulate Matter (PM₁, PM_2.5, and PM₁₀)

Particulate matter generally shows strong positive correlations with total bacterial concentrations (Figure 2). Across a wide range of suspended dust concentrations, from a few to over 300 μg/m³, both positive and negative correlations between bacterial aerosols and particulate matter have been observed. Only one study, conducted by Madhwal et al. [49], evaluated the relationship between bioaerosol concentrations and submicron particles. In this study, PM₁ (ranging from 68 to 120 µg/m³) exhibited a significant positive correlation (R = 0.60, p < 0.05).

PM_2.5 exhibits even stronger correlations with bacterial aerosols across multiple studies, with coefficients as high as 0.808 (p < 0.01) [62] and 0.652 (p < 0.01) [24]. The highest positive correlation was observed at higher PM_2.5 concentrations, ranging from 31.3 to 214.7 μg/m³, and bacterial aerosol concentrations ranged from 497.7 to 1736.5 CFU/m³. In comparison, measurements of PM₁, PM_2.5, and PM₁₀ conducted in India during the monsoon, post-monsoon, winter, and summer seasons [49] revealed the highest correlation coefficient with PM₁₀ at 0.75 (p < 0.05) for PM₁₀ concentrations ranging from 29 to 315 μg/m³ and very high bacterial concentrations (4595 ± 3410 CFU/m³). The lowest correlation was observed with PM_2.5 at 0.55 (p < 0.05), suggesting that the bioaerosol loading in fine particulate fractions is lower compared to larger fractions. Madhwal et al. [49] emphasized the elevated microbial contribution in larger-sized particles. Lighthart [71] and Raisi et al. [72] explained that larger particles tend to have higher bacterial concentrations due to their greater surface area and volume, which can harbor microbial cells. As particle size decreases (i.e., aerodynamic diameter becomes smaller), bacteria are more likely to remain suspended in the air as individual cells rather than attached to particles. Smaller particles can remain airborne longer and more easily, allowing microbes to be suspended as single cells.

Interestingly, PM_2.5 displays seasonal variations, with a positive but not statistically significant correlation in autumn (0.139) and a negative correlation in winter (R = −0.491, p < 0.05) [47]. The significant negative correlation during winter is consistent with findings from Brągoszewska et al. [4]. Hosseini et al. [43] noted that the increased concentration of PM_2.5 during winter, due to phenomena such as thermal inversion and fog, can elevate bioaerosol levels. However, their observations did not identify a statistically significant positive correlation between PM_2.5 and bioaerosol levels during this season. This suggests that, although higher PM_2.5 levels in winter may be associated with factors that could potentially influence bioaerosol concentrations, the data do not support a significant increase in bioaerosols. Góralska et al. [64] also did not find a statistically significant relationship between the total number of bacteria and the levels of PM_2.5 and PM₁₀. They suggested that this lack of correlation may be related to low air temperatures during sampling, which negatively affected the survival of microorganisms. In contrast, during spring (March 2018–2023), correlations slightly fluctuated, with values of 0.77 in the pre-COVID-19 period, 0.60 during COVID-19, and 0.67 post-COVID-19 [65].

Similar to fine particles, the correlations between coarse particles and bacterial aerosols vary across studies, reflecting different contexts, conditions, and potentially geographic or methodological differences. Generally, most studies indicate a positive correlation, meaning that as PM₁₀ levels increase, so do bacterial aerosol concentrations. This relationship is particularly strong and significant in studies by Madhwal et al. [49] and Yan et al. [48], and under specific conditions such as dust days [40]. Seasonal variations noted by Brągoszewska et al. [4] suggest that this relationship can reverse in winter, potentially due to different sources or behaviors of PM₁₀ and bacteria during colder months. Data from the pandemic period, as reported by Brągoszewska et al. [65], show that significant public changes also affect this relationship but maintain a strong positive correlation overall. Inconclusive relationships between PM and bacterial aerosols may support the thesis of Zhen et al. [8], which posits that meteorological factors have a greater influence on shaping airborne bacterial communities than air pollutants. Conversely, some studies reviewed indicate a negative correlation between PM and bacterial aerosols during the winter season, which might highlight the significant role of toxic substances in PM. Xie et al. [73] noted that inverse trends between bioaerosol concentration and PM are related to the air quality index. During low-haze conditions, the growth-promoting effect of sulfate and nitrate in suspended particles predominates, while the concentrations of toxic and hazardous chemicals adhering to these particles do not reach levels sufficient to exert a significant poisonous effect. However, as haze pollution intensifies, PM_2.5 concentrations increase, amplifying the toxic effects. Research by Sun et al. [74] demonstrated that bacterial community diversity in PM_2.5 was higher than in PM₁₀, but high PM concentrations had a certain inhibitory effect on the bacterial community richness of PM_2.5. This may be due to the larger specific surface area of PM_2.5, which facilitates the absorption of a greater quantity of chemical substances detrimental to microbial survival. Toxic and hazardous substances in PM, including crustal elements, heavy metals, and inorganic ions, play a particular role. For example, heavy metals released from airborne PM with redox potential act as catalysts in the generation of reactive oxygen species (ROS), especially hydroxyl radicals (HO^•) which damage cellular biological molecules [75,76]. Additionally, some inorganic ions cannot be neglected. SO₄²⁻ has a distinct ability to influence the existence and growth of microbes, thereby affecting their relative abundance [77]. Dong et al. [78] pointed out that secondary inorganic aerosols, including SO₄²⁻ and NO₃⁻, formed by aqueous or photochemical transformation from SO₂ and NO₂, are recognized as an important source of nutrients for microorganism growth. Ca²⁺ affects various bacterial cellular processes, including the cell cycle, cell division, competence, pathogenesis, motility, and chemotaxis [79]. Cl⁻ is involved in water disinfection processes and can cause bacterial stress and injury [80], while high concentrations of K⁺ and Na⁺ may disrupt bacterial structure and function, potentially leading to bacterial death [80]. Consequently, lower bioaerosol concentrations may be observed during periods of extreme pollution. Based on this premise, it can be hypothesized that the interplay between growth-promoting effects and toxic effects from chemical pollutants adhering to bioaerosols may influence bioaerosol concentration levels during winter. However, the effects of toxic chemical components in airborne particulate matter on microorganisms remain largely unexplored. Gao et al. [63] highlighted the significant role of the size distribution of viable bioaerosols. Their results showed that airborne bacteria of different particle sizes varied distinctly with PM_2.5 concentrations. Specifically, bacteria concentrations from stage I (diameter >7.0 μm) to stage IV (diameter 2.1–3.3 μm) had a negative correlation with PM_2.5, although this relationship was not statistically significant. However, bacteria concentrations at stage VI (diameter 0.65–1.1 μm) had a statistically significant (p < 0.01) negative correlation with PM_2.5, indicating that smaller bacterial aerosols decreased with increasing PM_2.5. Additionally, the negative correlation of the fine bacteria percentage contribution (FB%) and the corresponding positive correlation of coarse bacteria percentage contribution (CB%) with PM_2.5 suggest that a fraction of fine particle size bacterial aerosols decreased with increasing PM_2.5, while a fraction of bacterial aerosols with coarse particle sizes increased. This result may be attributed to the coagulation of fine particulates, which frequently occurs during haze days [81].

Further monitoring across broader spatial and temporal scales, covering the size distribution of bacterial particles, as well as additional toxicological data, is necessary to substantiate these hypotheses.

3.1.2. Ozone (O₃)

Ozone is an effective and practical antibacterial agent [82,83] used in buildings. However, the relationship between O₃ and bacterial aerosols exhibits both positive and negative correlations, with context and seasonal variations playing significant roles. Góralska et al. [64] found a moderate positive correlation (0.5252, p < 0.05), indicating that higher ozone levels ranging from 44.35 to 88.6 μg/m³ (Table S1) may be associated with an increase in bacterial aerosols under certain conditions. High concentrations of O₃ can be toxic to bioaerosols after reacting with atmospheric olefins to form so-called open-air factors [84,85]. Figure 3 presents statistically significant correlations between O₃ and bacterial aerosols. Estillore et al. [76] highlighted that the physical and biological properties of bioaerosols change significantly after exposure to ozone and water vapor. However, the exact mechanisms for these observed changes were not reported and require future investigation. The role of temperature is particularly evident in the range from −1.5 to 9 °C, which was significantly correlated with bacterial aerosols (0.5468, p < 0.05). In contrast, two other studies report significant negative correlations, particularly Yan et al. [48] (−0.6, p < 0.01) and Yang et al. [47] (−0.795, p < 0.01) during winter, indicating that higher ozone levels are associated with reduced bacterial aerosol concentrations. This suggests that ozone might have an inhibitory effect on airborne bacteria, possibly due to its oxidative properties. However, the O₃ concentrations in these studies were between 5 and 60 μg/m³ and between 4 and 41 μg/m³, which are lower than those reported by Góralska et al. [64]. Additionally, temperature ranges in these studies were −8.1 to 23.9 °C and −2.5 to 21.0 °C, respectively, and also showed a negative correlation with bacterial aerosols (Table 1).

3.2. Interactions with Meteorological Factors

3.2.1. Temperature

The results of multiple studies reveal intricate dynamics in the relationship between temperature and airborne bacterial concentrations (Table 1 and Figure 4a). The analysis demonstrates that temperature fluctuations significantly impact both fine bacteria (FB) and coarse bacteria (CB). The correlation coefficients for FB and CB are −0.334 (p < 0.01) and −0.285 (p < 0.05), respectively [63], indicating an inverse relationship, wherein higher temperatures are generally associated with lower concentrations of fine and coarse airborne bacteria.

Seasonal variations further modulate the relationship between temperature and airborne bacterial concentrations. In autumn, a significant negative correlation of −0.471 (p < 0.05) indicates that lower temperatures are associated with elevated bacterial levels [47]. Conversely, winter exhibits a positive correlation of 0.675 (p < 0.05) [65] and 0.531 (p < 0.05) [42] suggesting that bacterial levels may decrease despite lower temperatures. Similarly, Madhawal et al. [49] reported a positive correlation with temperature (R = 0.70, p < 0.05) in the humid subtropical climate of India. Their findings highlighted that minimum bacterial concentrations during winter were associated with low temperatures (17.0 ± 2.7 °C), while elevated concentrations in other seasons could be attributed to optimal temperatures for microbial growth (28.8 ± 6.7 °C). This increase may be influenced by factors such as reduced air circulation or specific environmental conditions. Lower temperatures have been linked to higher pathogenic bacterial levels, particularly under haze conditions [23,86]. However, Kowalski et al. [87] noted that in Poland’s moderate climate zone, a temperature threshold of 7.5 °C serves as a breakpoint, inhibiting an increase in bacterial aerosols. Additionally, cooler temperatures are thought to stabilize atmospheric layers, trapping air pollutants and microorganisms and preventing their dispersion [88].

During spring, a negative correlation of −0.316 (p < 0.05) [65] suggests that warmer temperatures correspond to lower bacterial concentrations. In Turkey, airborne bacterial levels peak during autumn [89]. Conversely, Bowers et al. [90] observed that in Colorado, the highest average bacterial aerosol concentrations occurred in spring. Data from Montreal further revealed minimal bacterial concentrations during summer and winter, with peak levels in spring and autumn [91].

3.2.2. Relative Humidity (RH)

RH plays a critical role in modulating bacterial concentrations, with correlations exhibiting considerable variability. In general, elevated RH fosters bacterial growth, as bacteria can absorb moisture from the environment to facilitate metabolic processes (Figure 4b). Furthermore, high RH can promote the aggregation of bacterial cells, potentially enhancing their survival [32]. A single raindrop can generate over 100 bioaerosol droplets with diameters smaller than 10 µm. Moreover, soil bacteria such as Pseudomonas syringae, Bacillus subtilis, and Corynebacterium glutamicum have been found to remain culturable for up to one hour following aerosolization [92]. Heavy rainfall has been associated with an increase in both airborne bacterial diversity and humidity, which promotes the activity and survival of airborne bacteria [8].

In contrast, very low relative humidity (RH) inhibits microbial activity, as dry conditions suppress the metabolic and physiological functions of microorganisms [93]. Additionally, Smets et al. [57] observed a negative correlation between RH and bacterial diversity, likely due to increased moisture facilitating particle deposition through the enlargement of particle sizes, while wet soil surfaces reduce the likelihood of aerosolization.

The relationship between RH and bacterial concentrations exhibits considerable variability across studies. Some research studies report positive correlations, ranging from 0.291 to 0.529 [45], suggesting that higher RH may be associated with increased bacterial concentrations. However, other studies have identified negative correlations, such as −0.720 (p < 0.05) [69], indicating that elevated RH could correspond with lower bacterial levels. For terrestrial bacteria, negative correlations have been observed, with values as low as −0.416 (p < 0.05) [68], highlighting the inverse relationship between RH and bacterial concentrations. Seasonal variations further affect these dynamics, with correlations between RH and bacterial levels being weakly positive, ranging from 0.351 (p < 0.05) in winter [4] to 0.53 (p < 0.05) in spring [42].

3.2.3. Solar Radiation

Solar radiation appears to have a variable effect on bacterial concentrations, although the available data on this relationship are limited (Table 1). Some studies indicate a negative correlation between solar radiation and airborne bacteria. For instance, a correlation coefficient of −0.489 (p < 0.05) suggests that higher levels of solar radiation may be associated with lower bacterial concentrations. However, this effect is not consistently observed across studies. One study reports a positive correlation of 0.673 (p < 0.05), implying that increased solar radiation could potentially lead to higher bacterial levels [69].

Seasonal variations also influence the impact of solar radiation on bacterial concentrations. Data from the spring indicate a negative correlation of −0.329 (p < 0.05), while winter shows a more pronounced negative correlation of −0.603 (p < 0.05) [4]. These findings suggest that solar radiation may exert a stronger influence during these seasons, though the exact nature of this effect remains unclear.

In a previous study conducted in southern Poland, we observed a significant reduction in bacterial aerosol concentrations on days with peak temperatures [94]. This decrease may be attributable to the combined effects of elevated temperatures and, more importantly, high levels of solar radiation. This result aligns with the existing literature, which suggests that increased temperatures and strong solar radiation can lead to lower levels of outdoor bacterial aerosols [95,96].

While some studies propose that solar radiation may affect airborne bacterial concentrations, the evidence remains limited and inconsistent. Further research is necessary to clarify the precise relationship between solar radiation and airborne bacteria, as well as to elucidate the underlying mechanisms governing this interaction.

3.2.4. Wind Speed

Wind speed has been positively associated with both the concentration and diversity of bacterial populations in various studies. It plays a crucial role in facilitating the generation of bioaerosols in soil and water environments [90]. The data presented in Table 1 illustrate the complex relationship between wind speed and airborne bacterial concentrations. Wind can influence bacterial levels by resuspending particles from surfaces such as soil and vegetation. Lighthart and Stetzenbach [91], along with Jones and Harrison [34], have documented how wind enhances atmospheric dilution, which can lead to a reduction in local bacterial concentrations. Strong winds, in particular, are known to contribute to this dilution effect, especially during pollution events [8].

Recent advances in backward air trajectory modeling have demonstrated that typical wind patterns significantly contribute to the long-distance dispersal of airborne bacterial communities. Research on dispersion patterns over the past two decades has shown that changes in air mass circulation directly influence microorganism dispersal, often occurring within relatively short time frames [97]. Despite these findings, the relationship between airborne bacterial community composition and seasonal variations driven by atmospheric processes remains poorly understood and underexplored in many global environments.

Studies underscore the variability in wind’s impact on bacterial concentrations. For instance, a correlation of 0.659 (p < 0.05) suggests that wind may sometimes contribute to increased bacterial levels through resuspension [17]. However, the effect of wind speed on bacterial concentrations is complex, often reflecting local environmental conditions and seasonal variations.

3.2.5. Rainfall

The varying correlation coefficients (−0.385, p > 0.05, and 0.42, p < 0.05) suggest that the relationship between rainfall and total bacterial concentrations may differ depending on the context or location of the study. The negative correlation observed in study [69] indicates that increased rainfall might lead to a washout or dilution effect, thereby reducing bacterial concentrations in the air. Conversely, the positive correlation reported in study [49] suggests that rainfall could enhance bacterial growth or release, thereby increasing their airborne concentrations, particularly during the monsoon season. The significant positive correlation (0.42) provides stronger evidence for the latter relationship within the context of that specific study. Similar conclusions during the monsoon season were drawn by Heo et al. [98], whose experimental results indicate that bioaerosol concentrations increase during rain events.

This phenomenon can be explained by several mechanisms. First, bioaerosols act as ice or cloud condensation nuclei, allowing raindrops to form around bacterial particles at high altitudes, which subsequently descend to the Earth’s surface during rain events, thereby increasing bioaerosol concentrations. Second, bioaerosols may be resuspended from the ground by the impact of raindrops. Rainfall produces numerous small vibrations on the surface, which can dislodge and aerosolize microorganisms with the assistance of wind. This resuspension effect, through the splashing of spores and microorganisms, can result in increased bioaerosol concentrations. Third, a reduction in solar radiation during rain events may also influence the concentrations of culturable bioaerosols. It is well established that rain clouds reduce solar radiation, and this decrease may enhance the survival rates of bioaerosols, as lower levels of solar radiation during rain events can create more favorable conditions for their persistence.

The question of why bacterial aerosol concentrations may either increase or decrease during rain events remains unresolved. The variability in available results highlights the complexity of environmental interactions with bacterial aerosols, emphasizing the importance of considering local conditions and study contexts when interpreting such data.

4. Future Directions (Control and Mitigation Strategies)

Several areas clearly warrant further research. This section provides an overview of key and promising avenues for future investigation, which can be broadly categorized into seven main fields: (1) enhanced predictive models and characterization; (2) improved measurement techniques and atmospheric dynamics; (3) ecosystem and climate interactions; (4) health implications and public health strategies; (5) biotechnological applications and air quality; (6) regulatory and policy considerations; and (7) interdisciplinary collaboration. Research within these fields could help address the significant knowledge gaps identified in this review, reduce uncertainties in key parameters and assumptions, and improve the modeling of bioaerosol impacts on climate, health, and ecosystems at local, regional, and global scales.

(1)

Enhanced predictive models and characterization

Significant progress has been made in developing predictive models for ambient bacteria and endotoxins, though further refinement is required. For example, Raisi [72] observed that bacterial concentrations were positively correlated with relative humidity and fungal concentrations, and negatively correlated with solar radiation. Similarly, Kallawicha et al. [32] identified temperature, relative humidity, and particulate matter as the primary predictors of ambient bacteria and endotoxins in their regression model, which aligns with the findings of our literature review. Other reviews [11,99] emphasize the need for future studies to include additional variables to better understand the relationships between bacterial exposure and adverse health outcomes, particularly during rainstorms. Despite advancements in molecular methods, current exposure limits for biological aerosols still primarily rely on traditional culturable and microscopic techniques due to their simplicity and cost-effectiveness. To address this gap, research should focus on the detailed characterization of bioaerosol components using advanced technologies such as next-generation sequencing (NGS) and fluorescence detection. This approach will facilitate the development of comprehensive guidelines for acceptable exposure standards, which are currently lacking but are essential for improving risk assessment and public health protection.

(2)

Improved measurement techniques and atmospheric dynamics

Future research must advance innovative measurement techniques to accurately identify, quantify, and characterize bioaerosols. For the past 30 years, cultivation-dependent techniques have been the standard methods for investigating microbial communities in the environment, including aerosols and atmospheric waters [99]. To ensure consistency and comparability across studies, it is necessary to develop and apply molecular or single-cell approaches as standardized sampling and analysis methods. Additionally, understanding the spatial and temporal dynamics of bioaerosols, from molecular to global scales, remains a critical area of study. Research should focus on the emission, transport, and transformation of bioaerosols, with particular attention to their interactions with clouds, precipitation, and other atmospheric processes. Integrating ground-based measurements using real-time samplers, such as fluorescence or mass spectrometric analyzers [100], with satellite data [101] will provide a more comprehensive understanding of bioparticle distribution. This approach is essential for validating or refining current hypotheses regarding the impacts of bioaerosols on climate and ecosystems.

(3)

Ecosystem and climate interactions

Research on bioaerosols should be expanded to include a diverse range of ecosystems, from tropical to polar and from continental to marine regions. This broadening is essential to enhance our understanding of the relationships between bioaerosol emissions, biodiversity, climate, and land use changes [68]. Such research has the potential to inform ecosystem models that investigate the coevolution of life and climate [11], as well as the dispersion of pathogens and allergens [61], which carry significant public health implications. By elucidating the interdependencies between bioaerosols and environmental factors, scientists can contribute to the development of more effective environmental management practices and climate adaptation strategies.

(4)

Health implications and public health strategies

The health effects of bioaerosol exposure represent a critical area for future research. Longitudinal studies that assess both chronic and acute exposure to bioaerosols are necessary, particularly in diverse populations varying by age, gender, and health status. Detailed exposure assessments, coupled with objective health measurements such as lung function tests and biochemical analyses, will provide a clearer understanding of the health risks associated with bioaerosols. Establishing comprehensive exposure standards is essential for enhancing risk assessments and safeguarding public health. Additionally, understanding the distribution, sources, and impacts of bacterial aerosols will be crucial for developing effective public health strategies and improving environmental management practices [41,49,102].

(5)

Biotechnological applications and air quality

The unique metabolic properties and resilience of airborne bacteria to environmental stressors offer promising opportunities for biotechnological applications [25,57]. Future research should investigate the potential uses of airborne bacteria in areas such as air quality improvement and weather pattern analysis. These applications could drive significant innovations benefiting both human health and the environment. Expanding microbiological research into atmospheric conditions will enhance our understanding of airborne bacteria and their potential applications.

(6)

Regulatory and policy considerations

As research on bioaerosols advances, it is crucial for regulatory authorities to have access to accurate and up-to-date information. This knowledge is vital for developing strategies to mitigate risks associated with bioaerosols and for establishing comprehensive databases to monitor microbial air pollution. Developing comprehensive guidelines for acceptable exposure standards to biological aerosols is essential. Future research should focus on creating these standards, which are currently lacking [103]. Establishing such standards is critical for improving risk assessment and safeguarding public health. Identifying and addressing key knowledge gaps will facilitate the creation of acceptable exposure limits, which are necessary for effective public health protection and environmental management.

(7)

Interdisciplinary collaboration

Addressing the broad and complex questions related to bioaerosols necessitates intensified collaboration across multiple disciplines. Fields such as atmospheric chemistry, climate science, biogeochemistry, ecology, and public health must work together to develop a more comprehensive understanding of bioaerosols and their impacts on both local and global scales. By fostering interdisciplinary exchange, researchers can devise more effective strategies for managing the impacts of bioaerosols on society, health, and ecosystems.

In conclusion, future research on bioaerosols should integrate advanced molecular methods with atmospheric transport models, conduct long-term studies across diverse ecosystems, and explore the health impacts of bioaerosol exposure. Addressing current knowledge gaps and developing comprehensive guidelines for acceptable exposure standards are essential for protecting public health and improving environmental management practices. Additionally, the potential biotechnological applications of airborne bacteria highlight the importance of continued research in this field. Through collaborative efforts, the scientific community can enhance its understanding of bioaerosols and their multifaceted roles in climate, health, and ecosystems, thereby leading to more effective strategies for managing their impact on society.