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Invited review article
Bioaerosols in the Earth system: Climate, health, and
ecosystem interactions
Janine Fröhlich-Nowoisky
a,
⁎,ChristopherJ.Kampf
a,b
, Bettina Weber
a
, J. Alex Huffman
c
, Christopher Pöhlker
a
,
Meinrat O. Andreae
a
, Naama Lang-Yona
a
, Susannah M. Burrows
d
,SachinS.Gunthe
e
, Wolfgang Elbert
a
,
Hang Su
a
, Peter Hoor
f
, Eckhard Thines
g
,ThorstenHoffmann
b
, Viviane R. Després
h
,UlrichPöschl
a,
⁎
a
Multiphase Chemistry and Biogeochemistry Departments, Max Planck Institute for Chemistry, Mainz, Germany
b
Institute of Inorganic and Analytical Chemistry, Johannes Gutenberg University, Mainz, Germany
c
Department of Chemistry and Biochemistry, University of Denver, Denver, CO, USA
d
Atmospheric Science and Global Change Division, Pacific Northwest National Laboratory, Richland, WA, USA
e
Department of Civil Engineering, IIT Madras, Chennai, India
f
Institute for Atmospheric Physics, Johannes Gutenberg University, Mainz, Germany
g
Institute ofMicrobiology and Wine Research, Johannes Gutenberg University, Mainz, Germany
h
Institute ofGeneral Botany, Johannes Gutenberg University, Mainz, Germany
abstractarticle info
Article history:
Received 23 February 2016
Received in revised form 14 July 2016
Accepted 19 July 2016
Available online 9 August 2016
Aerosols of biological origin play a vital role in the Earth system, particularly in the interactions between atmo-
sphere, biosphere, climate, and public health. Airborne bacteria, fungal spores, pollen, and other bioparticles
are essential for the reproduction and spread of organisms across various ecosystems, and they can cause or en-
hance human, animal, and plant diseases. Moreover, they can serve as nuclei for cloud droplets, ice crystals, and
precipitation, thus influencing the hydrological cycle and climate. The sources, abundance, composition, and
effects of biological aerosols and the atmospheric microbiome are, however, not yet well characterized and con-
stitute a large gap in the scientific understanding of the interaction and co-evolution of life and climate in the
Earth system. This review presents an overview of the state of bioaerosol research, highlights recent advances,
and outlinesfuture perspectivesin terms of bioaerosol identification,characterization, transport, and transforma-
tion processes, as well astheir interactions with climate,health, and ecosystems, focusing on the role bioaerosols
play in the Earth system.
© 2016 The Authors and Battelle Memorial Institute. Published by Elsevier B.V. This is an open access article
under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Keywords:
Bioaerosol
Biological ice nuclei
Allergens
Bacteria
Fungi
Contents
1. Introduction.............................................................. 347
2. Identificationandcharacterizationofbioaerosols ............................................. 349
2.1. Biologicalcharacterization .................................................... 349
2.2. Chemicalandphysicalcharacterization............................................... 349
3. Transportandtransformationofbioaerosols................................................ 353
3.1. Emissionandtransport...................................................... 354
3.2. Physical,chemical,andbiologicaltransformation.......................................... 355
3.3. Cloudinteractionsandbioprecipitationcycle............................................ 355
4. Bioaerosol-ecosysteminteractions .................................................... 358
4.1. Terrestrialecosystems ...................................................... 358
4.2. Aquaticecosystems ....................................................... 359
4.3. Pathogensandallergens ..................................................... 361
5. Futureperspectives........................................................... 364
Acknowledgements ............................................................. 365
References ................................................................. 365
Atmospheric Research 182 (2016) 346–376
⁎Corresponding authors.
E-mail addresses: j.frohlich@mpic.de (J. Fröhlich-Nowoisky), u.poschl@mpic.de (U. Pöschl).
http://dx.doi.org/10.1016/j.atmosres.2016.07.018
0169-809 5/© 2016 The Authors and Battelle Memorial Institute. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Contents lists available at ScienceDirect
Atmospheric Research
journal homepage: www.elsevier.com/locate/atmosres
1. Introduction
Primary biological aerosols (PBA), in short bioaerosols, are a subset
of atmospheric particles, which are directly released from the biosphere
into the atmosphere. They comprise living and dead organisms
(e.g., algae, archaea, bacteria), dispersal units (e.g., fungal spores and
plant pollen), and various fragments or excretions (e.g., plant debris
and brochosomes; Ariya and Amyot, 2004; Brown et al., 1964; Castillo
et al., 2012; Cox and Wathes, 1995; Després et al., 2012; Graham,
2003; Madelin, 1994; Matthias-Maser et al., 1995; Rogerson and
Detwiler, 1999; Tesson et al., 2016; Womack et al., 2010). As illustrated
in Fig. 1, PBA particle diameters range from nanometers up to about a
tenth of a millimeter. The upper limit of the aerosol particle size range
is determined by rapid sedimentation, i.e., larger particles are too
heavy to remain airborne for extended periods of time (Hinds, 1999;
Pöschl, 2005).
Historically, the first investigations of the occurrence and dispersion
of microorganisms and spores in the air can be traced back to the early
19th century (Ehrenberg, 1830;Pasteur, 1860a, 1860b). Since then, the
study of bioaerosol has come a long way, and air samples collected with
aircraft, balloons, and rockets have shown that PBA released from land
and ocean surfaces can be transported over long distances and up
to very high alt itudes, i.e., between continents and beyond the tropo-
sphere (Brown and Hovmøller, 2002; DeLeon-Rodriguez et al., 2013;
Elbert et al., 2007; Gregory, 1945; Griffin et al., 2001; Griffin, 2004;
Hallar et al., 2011; Hirst et al., 1967; Imshenetsky et al., 1978; Maki
et al., 2013; McCarthy, 2001; Pady et al., 1950; Polymenakou et al.,
2007; Pósfai et al., 2003; Proctor, 1934; Prospero et al., 2005;
Scheppegrell, 1924; Shivaji et al., 2006; Smith et al., 2013; Wainwright
et al., 2003).
Bioaerosols play a key role in the dispersal of reproductive units
from plants and microbes (pollen, spores, etc.), for which the atmo-
sphere enables transport over geographic barriers and long distances
(e.g., Brown and Hovmøller, 2002; Burrows et al., 2009a, 2009b;
Després et al., 2012; Womack et al., 2010). Bioaerosols are thus highly
relevant for the spread of organisms, allowing genetic exchange be-
tween habitats and geographic shifts of biomes. They are central ele-
ments in the development, evolution, and dynamics of ecosystems.
The dispersal of plant, animal, and human pathogens and allergens
has major implications for agriculture and public health (e.g., Adhikari
et al., 2006; Brodie et al., 2007; Brown and Hovmøller, 2002; Després
et al., 2012; Douwes, 2003; Fisher et al., 2012; Fröhlich-Nowoisky
et al., 2009; Gorny et al., 2002; Kellogg and Griffin,2006), and the poten-
tial impacts of airborne transmission of genetically modified organisms
are under discussion (e.g., Angevin et al., 2008; Folloni et al., 2012;
Kawashima and Hama, 2011). Moreover, bioaerosols can serve as nuclei
for cloud droplets, ice crystals, and precipitation, thus influencing the
hydrological cycle and climate. Especially in pristine air over vegetated
regions, bioaerosols are likely to be an essential regulating factor in
the formation of precipitation and vice versa (e.g., DeLeon-Rodriguez
et al., 2013; Huffman et al., 2013; Möhler et al., 2007; Morris et al.,
2014a; Pöschl et al.,2010; Prenni et al., 2013; Sands et al., 1982; Schnell
and Vali, 1972; Sesartic et al., 2013; Tobo et al., 2013; Vali et al., 1976).
Also in marine environments, particulate matter of biological origin
may contribute substantially to the abundance of ice nuclei (Alpert
et al., 2011a; Burrows et al., 2013a; Knopf et al., 2010; Lee et al., 2015;
Parker et al., 1985; Schnell and Vali, 1976; Schnell and Vali, 1975;
Schnell, 1975; Wilson et al., 2015).
An overview of bioaerosol cycling and effects in the Earth system is
given in Fig. 2. Some organisms actively emit PBA particles, such as
wet-discharged fungal spores, which are emitted with the help of os-
motic pressure or surface tension effects, while the passive emission
of other PBA particles, like thallus fragments and dry-discharged fungal
spores, is mostly wind-driven (Elbert et al., 2007). In the atmosphere,
PBA undergo internal and external mixing with other aerosols, includ-
ing biogenic secondary organic aerosol (SOA) formed upon oxidation
and gas-to-particle conversion of biogenic volatile organic compounds,
which can influence bioaerosol properties through SOA coatings on
PBA particles (Hallquist et al., 2009; Huffman et al., 2012; Pöhlker
et al., 2012b; Pöschl et al., 2010).
In the course of atmospheric transport, bioaerosols undergo further
chemical and physical transformation, stress, and biological aging
upon interaction with UV radiation, photo-oxidants, and various air
pollutants like acids, nitrogen oxides, aromatic compounds, and soot
(Estillore et al., 2016; Franze et al., 2005; Santarpia et al., 2012;
Shiraiwa et al., 2012b). Particle transformation and aging also occur
Fig. 1. Characteristic size ranges of atmosphericparticles and bioaerosols withexemplary illustrations: (A) protein, (B) virus, (C) bacteria, (D) fungal spore,and (E) pollen grain (adapted
from Pöschl and Shiraiwa, 2015). Image A is a model simulation of BetV1 (Kofler et al., 2012; Xu and Zhang, 2009) created with PDB protein workshop 3.9 (Moreland et al., 2005).
Images (B–E) are scanningelectron micrographs of representativeparticles from eachof the bioaerosol categories listed. Image B reprinted from Whonet al. (2012), copyright 2012 , with
permission from American Societyfor Microbiology. ImagesC and D reprinted fromWittmaack et al. (2005),copyright 2005,with permissionfrom Elsevier. ImageE reprinted fromValsan
et al. (2015), copyright 2015, with permission from Elsevier.
347J. Fröhlich-Nowoisky et al. / Atmospheric Research 182 (2016) 346–376
upon cloud processing, i.e., when cloud droplets or ice crystals form on
or scavenge bioaerosol particles. Most clouds re-evaporate and release
modified particles, but when they form precipitation that reaches the
Earth's surface, not only condensation and ice nuclei but also other aero-
sol particles are scavenged on the way to the surface and removed from
the atmosphere. This process of “wet deposition”is the major sink for
atmospheric aerosol particles. “Dry deposition”by sedimentation and
diffusion tends to be less important on global scales but is particularly
relevant with respect to local air quality and health effects (inhalation
and deposition in the respiratory tract). Depending on aerosol proper-
ties and meteorological conditions, the characteristic residence times
(lifetimes) of aerosol particles in the atmosphere range from hours to
weeks. After returning to the ground, viable bioparticles can continue
biological reproduction and metabolic activity that may generate fur-
ther emission of PBA particles and SOA precursors, thus closing a feed-
back loop and biogeochemical cycle of biologically-derived aerosols in
the Earth system (Andreae and Crutzen, 1997; Deguillaume et al.,
2008; Morris et al., 2014a; Pöhlker et al., 2012b; Pöschl, 2005; Pöschl
et al., 2010; Suni et al., 2015).
In most terrestrial environments, bioaerosols constitute a substantial
fraction of the atmospheric aerosol load (Tables 1a and 1b). With regard
to number and mass concentration in the coarse particle size range with
diameters larger than ∼1μm, bioaerosols typically account for around
30% in urban and rural air (Després et al., 2012; Huffman et al., 2013,
2010; Matthias-Maser and Jaenicke, 1995; Matthias-Maser et al., 2000a,
2000b; Monks et al., 2009; Schumacher et al., 2013; Sesartic et al., 2012)
andupto∼80% in pristine rainforest air (Graham, 2003; Huffman et al.,
2012; Martin et al., 2010; Pöhlker et al., 2012a; Pöschl et al., 2010). The
number and mass concentrations of PBA particles over vegetated regions
are typically in the order of ∼10
4
m
−3
and ∼1μgm
−3
, respectively
(Tables 1a and 1b; e.g., Bauer et al., 2002a, 2002b; Burrows et al., 2009a,
2009b; Després et al., 2012; Elbert et al., 2007; Heald and Spracklen,
2009; Huffman et al., 2013, 2012, 2010; Sesartic et al., 2012).
However, the actual identity, diversity, and abundance of different
types of bioaerosol particles as well as their temporal and spatial
variability are not well characterized. Recent studies suggest that the
average number fluxes of emission of bacteria and fungal spores over
continental regions are in the order of ∼10
2
m
−2
s
−1
(Burrows et al.,
2009a, 2009b; Crawford et al., 2014; Elbert et al., 2007; Heald and
Spracklen, 2009; Lighthart and Shaffer, 1994; Lindemann et al., 1982;
Sesartic and Dallafior, 2011), reflecting an intense and rapid exchange
of biological matter and genetic information between atmosphere and
biosphere. Estimates of globalbioaerosol mass emission rates, however,
vary widely (∼10–1000 Tg a
−1
;Tables 1a and 1b;Després et al., 2012),
and the regional and temporal variations in the atmospheric abundance
and fluxes ofemission and transport of different types of bioaerosol par-
ticles are poorly constrained (Bowers et al., 2012, 2010, 2009; Burrows
et al., 2009a, 2009b; Fröhlich-Nowoisky et al., 2012, 2009; Heald and
Spracklen, 2009; Jaenicke, 2005; Sesartic and Dallafior, 2011).
Overall, the role of bioaerosols in the atmosphere and their interac-
tion with terrestrial and marine ecosystems are not well described and
understood –neither for the present state of the Earth system and
climate, nor with regard to past evolution and future change. Indeed,
the properties and interactions of atmospheric aerosols, including
bioaerosols, are among the largest uncertainties in the current under-
standing and prediction of climate change (Solomon et al., 2007;
Stocker et al., 2013). This lack of knowledge is particularly severe with
regard to the assessment, prediction, and management of global envi-
ronmental change in the Anthropocene as established by Paul Crutzen
(Crutzen and Stoermer, 2000; Crutzen, 2002), i.e., in the present era of
steeply increasingand globally pervasive human influence on the diver-
sity, metabolic activity, and future development of life on planet Earth
Fig. 2. Bioaerosol cycling in the Earth system. After emission from the biosphere,
bioaerosol particles interact with other aerosol particles and trace gases in the
atmosphere and can be involved in the formation of clouds and precipitation. After dry
or wet deposition to the Earth's surface, viable bioparticles can contribute to biological
reproduction and further emission. This feedback can be particularly efficient when
coupled to the water cycle (bioprecipitation).
Adapted from Pöschl and Shiraiwa (2015) and Pöschl (2005).
Table 1a
Estimates of global emissions and characteristic number and mass concentrations in near-
surface air for different types of primary biological aerosol(PBA) particles.
Adapted from Després et al. (2012) and references therein.
Global emissions
[Tg a
−1
]
Number
concentration
[# m
−3
]
Mass
concentration
[μgm
−3
]
Bacteria 0.4–28 ~10
4
~0.1
Fungal spores 8–190 ~10
3
–10
4
~0.1–1
Fungal hyphal
fragments
~10
3
Pollen 47–84 ~10 (up to ~ 10
3
)~1
Plant debris ~0.1–1
Algae ~100 (up to ~ 10
3
)~10
−3
Fern spores ~10 (up to ~ 10
3
)~1
Viral particles ~10
4
~10
−3
Total PBA b10 (dominated by plant
debris and fungal spores)
to ~1000 (includes cellular
fragments)
Table 1b
Estimates of global emissions and mass burdens for differenttypes of atmosphericaerosol
components including organic carbon from primary biological aerosol (PBA) particles.
Adapted from Andreae and Rosenfeld (2008) and Monks et al. (2009).
Global emissions
[Tg a
−1
]
Mass burden
[Tg]
Carbonaceous aerosols
Primary organic (0–2μm) 95 1.2
Biogenic (PBA) 35 0.2
Biomass burning & fossil fuel 58 –
Black carbon (0–2μm) 10 0.1
Secondary organic 28 0.8
Biogenic 25 0.7
Anthropogenic 3.5 0.08
Sulfates 200 2.8
Nitrates 18 0.49
Sea salt 10,130 15
Desert/soil dust 1600 18 ± 5
Anthropogenic total 312 3.1
Biogenic total 117 2.1
348 J. Fröhlich-Nowoisky et al. / Atmospheric Research 182 (2016) 346–376
(Pöschl and Shiraiwa, 2015; Williams and Crutzen, 2013). For example,
it is not clear how the ongoing global and regional changes in land use,
climate, and biodiversity will affect the abundance and properties of at-
mospheric bioaerosols that may influence the spread of vegetation and
disease as well as the spatial and temporal patterns of precipitation,
which in turn may act as a positive or negative feedback on climate
(Morris et al., 2014a). These issues are closely linked to societally rele-
vant questions about how agriculture and other types of land use and
human activity may be developed to efficiently mitigate or adapt to
climate change. For example, these scenarios are more pertinent to
the developing countries, especially densely populated South Asia,
where information about bioaerosol properties and abundance is
extremely limited.
In the following sections, this article will summarize the state of the
science, highlight recent advances and outline future perspectives re-
garding bioaerosols and their role in the Earth system in terms of their
identification and characterization, transport and transformation pro-
cesses, as well as their interactions with climate, health, and terrestrial
and marine ecosystems.
2. Identification and characterization of bioaerosols
A wide range of methods have been developed and applied for
bioaerosol sampling and measurement: filter, impactor, impinger, and
cyclone samplers; cultivation and staining techniques; immunological
methods; light and electron microscopy; optical spectroscopy and
mass spectrometry as well as chemical tracer analyses (Baron and
Willeke, 2001; Buters et al., 2012; Carestia et al., 2015; Caruana, 2011;
Cox and Wathes, 1995; Crook and Sherwood-Higham, 1997; De Linares
et al., 2014; DeCosemo et al.,1992; Després et al., 2012; Georgakopoulos
et al., 2009; Ghosh et al., 2015; Griffin et al., 2001; Griffiths and
DeCosemo, 1994; Griffiths et al., 1997; Grinshpun and Clark, 2005;
Grinshpun et al., 2005; Henningson and Ahlberg, 1994; Laskin et al.,
2016; Levetin, 2004; Miyajima et al., 2014; Oteros et al., 2015; Valsan
et al., 2015; West et al., 2016; Wittmaack et al., 2005; Xu et al., 2011;
and references therein). Most of this work has been presented in the
review by Després et al. (2012); therefore we focus in this section on
recent advances in the following areas: Analysis of ribonucleic acids
(DNA/RNA); fluorescence detection, spectroscopy and microscopy;
X-ray microscopy and spectroscopy; and online and single-particle
mass spectrometry.
2.1. Biological characterization
Microbiology has experienced an especially strong transformation
over the last few decades. Most microorganisms cannot be grown read-
ily in pure culture, and earlier studies using traditional microbiological
cultivation techniques covered only small percentages of the species
present in the investigated samples and environments; e.g., ∼1% of bac-
teria, according to Lewis (2009),and∼17% of fungi, according to Bridge
and Spooner (2001). The entire spectrum of atmospheric microbial di-
versity, i.e., the atmospheric microbiome is now becoming accessible
through recent developments and applications of DNA- and RNA-
based methods (e.g., Boreson et al., 2004; Maron et al., 2005; Peccia
and Hernandez, 2006; Radosevich et al., 2002).
The identity of bioaerosols can be determined by DNA sequencing.
Many studies use the traditional Sanger sequencing approach, as this
provides sequences that are long enough to identify individual genera
or species by comparison with sequences available in online databases
like the National Center for Biotechnology Information (NCBI; Boreson
et al., 2004; Després et al., 2007; Fahlgren et al., 2011; Fierer et al.,
2008; Fröhlich-Nowoisky et al., 2009, 2012, 2014; Huffman et al.,
2013; Maron et al., 2005; Urbano et al., 2011).
The Sanger sequencing-based bioaerosol analysis is being slowly re-
placed by modern Next Generation Sequencing (NGS) technologies. In
the past, the length of the sequences has often been a limiting factor
for the identification to the species or genus level, as the reads were
much shorter than sequences obtained by Sanger sequencing. Next
Generation Sequencing technologies are continuously improving and
are currently able to provide sequences longer than 400 bp (Schmidt
et al., 2013; Sinclair et al., 2015). These technologies alsoallow the gen-
eration of millions of reads from air samples in order to analyze the ge-
nomics and transcriptomics (RNA analysis), and have been successfully
used in several recent bioaerosol related studies (e.g., Be et al., 2013;
Bertolini et al., 2013; Bowers et al., 2013, 2012, 2011, 2010, 2009; Cao
et al., 2014; DeLeon-Rodriguez et al., 2013; Franzetti et al., 2011;
Kraaijeveld et al., 2015; Seifried et al., 2015; Tringe et al., 2008; Womack
et al., 2015; Yooseph et al., 2013). In particular, metagenomic ap-
proaches enable comprehensive determination of the diversity and
metabolic potential of the organisms present in an aerosol sample.
Metagenomic techniques also allow the characterization of airborne
viral diversity and dynamics, as viruses are genetically highly variable
and do not possess conserved genes, which makes amplicon-based ap-
plications challenging (Prussin et al., 2014; Whon et al., 2012).
Fig. 3A shows an overview of the global atmospheric distribution
of fungal phyla derived from Sanger sequencing of air samples col-
lected at a wide range of geographic locations. The species richness
of Basidiomycota (BMC) vs. Ascomycota (AMC) exhibits distinct bio-
geographic patterns with higher BMC/AMC ratios in continental air
compared to marine air (Fröhlich-Nowoisky et al., 2012; Womack
et al., 2010). Fig. 3B shows the relative abundance of fungal phyla in
various soils and in tropical rainforest air, contrasting the total and met-
abolically active fungi determined by NGS sequencing of DNA and RNA
(Womack et al., 2015).
Although sequence data from NGS studies provide information of
the relative abundance of specific taxa, calculated as the fraction or
percentage of the sequences representing the taxa of interest to the
total amount of sequences, taxon-specific quantitative polymerase
chain reaction (PCR) is the most accurate reflection of absolute concen-
trations (Dannemiller et al., 2014; Georgakopoulos et al., 2009). Quanti-
tative PCR (qPCR) has been successfully applied to air samples to
quantify individual species, genera, or groups of fungi, bacteria, or
archaea (Casabianca et al., 2013; DeLeon-Rodriguez et al., 2013;
Fröhlich-Nowoisky et al., 2014; Lang-Yona et al., 2012, 2014; Lee et al.,
2010; Müller-Germann et al., 2015; Schweigkofler et al., 2004; Zeng
et al., 2004, 2006). A promising new method for bioaerosol quantifica-
tion is the droplet digital PCR (ddPCR) technique (Hindson et al.,
2011; Jones et al., 2014); it utilizes a water-oil emulsion system in
which the sample is fractionated into thousands of nanoliter droplets
to enable high-throughput digital PCR.
Preliminary estimates of total DNA concentrations of several nano-
gram per cubic meter in urban air suggest that the amount of DNA
inhaled by human adults may be as high as ~ 0.1–1μg per day, which
corresponds to ~10
14
–10
15
bp and would be equivalent to as much bio-
logical information as ~10
7
–10
8
bacterial genomes or ~10
4
–10
5
human
genomes (Després et al., 2007). Due to the variability of atmospheric
aerosol composition and experimental difficulties in the quantitative
extraction and measurement of the total DNA content of air filter sam-
ples, however, these preliminary estimates remain to be confirmed
and further specified for different environments and conditions.
2.2. Chemical and physical characterization
Recently, several new microscopy techniques have been developed
that bypass the resolution limit of optical microscopy (super-resolution
technologies) and allow the precise localization of intracellular com-
ponents (Best et al., 2013; Betzig et al., 2006; Cremer, 2012; Hell and
Kroug, 1995). Moreover, fluorescence imaging and spectroscopy
techniques have also made tremendous progress in recent years.
Wavelength-dependent fluorescence emission spectra, recorded as
a function of excitation wavelength, can be plotted as three-
dimensional landscapes, referred to as an excitation-emission matrix
349J. Fröhlich-Nowoisky et al. / Atmospheric Research 182 (2016) 346–376
(EEM). Such plots, accordingly, relay a broad collection of information
about the steady-state autofluorescence properties of a sample and can
be regarded as a unique, sample-specificfingerprint. Fig. 4Adisplaysa
conceptual overview EEM, illustrating the spectral zones of interest,
contour plots of three frequently investigated biological fluorophores
(tryptophan, nicotinamide adenine dinucleotide phosphate [NADPH],
and riboflavin), elastic scattering interferences, and operational
ranges of selected fluorescence-detecting bioaerosol instruments
(Pöhlker et al., 2012a). Fluorescence microscopy is well established
and often used to study bioaerosols by taking advantage of either
the autofluorescence of biological compounds or fluorescent stains
specifically binding to various biological molecules. Fig. 4BandC
shows fluorescence microscopy images of selected pollen species.
Flow cytometry is also often employed to enumerate and character-
ize bioaerosols collected into water and then tagged with fluorescent
stains (Chen and Li, 2005; Lange et al., 1997).
A number of instruments able to discriminate biological content in
real-time based on the emission of laser/light-induced fluorescence
(LIF) have been developed over the last two decades, originally for the
rapid detection of biowarfare threat agents (Cheng, 1999; Crouzy
Fig. 3. Biodiversity and biogeographyof airborne fungidetermined by DNA and RNAanalysis: (A) biogeography ofairborne fungi over landand oceans: geographical location and relative
proportions of differentfungal phyla at continental, coastal, and marine sampling locations determined by Sanger sequencing and(B) relative abundances of fungal phyla in various soils
and in tropical rainforest air, demonstratingdifferences in thecomposition of totaland metabolicallyactive airbornefungi determinedby NGS sequencingof DNA and RNA (Womack et al.,
2015).
(A) Adapted from Fröhlich-Nowoisky et al. (2012).
350 J. Fröhlich-Nowoisky et al. / Atmospheric Research 182 (2016) 346–376
et al., 2016; Ho, 2002; Huffman et al., 2016; Kaye et al., 2000; Manninen
et al., 2008; Pan et al., 2009; Pinnick et al., 1995; Sivaprakasam et al.,
2004). Recently, severalof these instruments have become commercial-
ly available and are among the most promising techniques for
bioaerosol analysis (e.g., Agranovski et al., 2003; Brosseau et al., 2000;
Hairston et al., 1997; Saari et al., 2014; Stanley et al., 2011). While
these instruments do not offer the molecular specificity or detailed im-
aging capabilities of microscopy, many of them are able to provide an
estimate of PBA properties in real-time, with high time and size resolu-
tion (Gabey et al., 2010; Healy et al., 2014; Huffman et al., 2010, 2012;
O'Connor et al., 2014; Perring et al., 2015; Pöhlker et al., 2012a, 2013;
Saari et al., 2015, 2016; Twohy et al., 2016; Ziemba et al., 2016).
Healy et al. (2014) compared measurements by two commercially
available real-time instruments for characterization of bioaerosols
using single particle fluorescence spectroscopy (wideband integrated
aerosol sensor, WIBS-4, and ultraviolet aerodynamic particle sizer, UV-
APS) with results from optical microscopy of Sporewatch single-stage
impactor samples. As shown in Figs. 5 and 6, the different WIBS
channels exhibited variable distributions, size-resolved diurnal concen-
trations, and correlations with fungal spore concentrations. The fluores-
cent particle number of the WIBS-4 channel FL3 and the UV-APS were
strongly correlated and the particle size distribution was dominated
by a 3 μmmode(Fig. 6). The diurnal plots show an increase in biological
or fluorescent number concentration during the night and early morn-
ing hours, with daily minima occurring in the mid-afternoon, corre-
sponding to the diurnal trend in relative humidity, which peaks at
similar hours. Additionally, as displayed in Fig. 7, long-term UV-APS
measurements at two climatically very different sampling sites, a boreal
forest in Finland and a semi-arid site in Colorado, showed similar sea-
sonal patterns with higher concentrations of fluorescent bioaerosols in
summer (Manninen et al., 2014; Schumacher et al., 2013). Perring
et al. (2015) used a WIBS-4 to detect fluorescent aerosol properties on
a blimp transect across the whole of the southern United States, show-
ing that number concentrations of fluorescent aerosol averaged up to
24% of the total aerosol number, with strong regional differences in
number and size.
The use of fluorescence alone for detection of airborne biological
particles is complicated by non-biological entities that exhibit fluores-
cence (e.g., certain SOA compounds, mineral dusts, and humic-like sub-
stances, HULIS) and by microorganisms that fluoresce too weakly to be
detected by these techniques (Bones et al., 2010; Gabey et al., 2013;
Huffman et al., 2010, 2012; Lee et al., 2013; Pinnick et al., 2004;
Pöhlker et al., 2012a; Toprak and Schnaiter, 2013). Nonetheless, these
limitations are minimized in pristine environments, where most of the
ambient measurements to date have been recorded, and to a first ap-
proximation fluorescent bioaerosol particles (FBAP) can be considered
as a lower limit for the abundance of biological particles (Huffman
et al., 2010). Thus, time-resolved FBAP measurements contribute to im-
proved parameterizations for daily, seasonal, and annual cycles to better
reflect PBA emissions and effects in atmospheric modeling. Based on
FBAP measurements at four locations in Europe, Hummel et al. (2015)
incorporated a new parameterization into a regional model. Fig. 8A
shows the FBAP emission fluxes (F
FBAP
) simulated with this model for
late August 2010, horizontally distributed over a model domain cover-
ing Europe. Averaged over the land areas of the domain, the mean
F
FBAP
is 1 × 10
3
m
−2
s
−1
. During July and October, the average fluxes
are to 1.4 × 10
3
and 0.4 × 10
3
m
−2
s
−1
, respectively. The horizontally
distributed near-surface (approximately 10 m above ground) FBAP/
fungal spore number concentration using F
FBAP
is shown in Fig. 8B.
Mass spectrometry (MS) is attractive for work in microbiology due
to its speed (Krásný et al., 2013). Aerosol mass spectrometry can deliver
single particle information to explore the spatial variability and dynam-
ics of bioaerosols (Bozzetti et al., 2016; Chen et al., 2009; Fergenson
et al., 2004; Kleefsman et al., 2007; Laskin et al., 2012; Pratt and
Prather, 2012; Schneider et al., 2011; Tobias et al., 2005; van
Wuijckhuijse et al., 2005). Another advantage of MS is that chemical
tracer molecules, which are not easily accessible by sequencing or fluo-
rescence labeling techniques, canbe quantified on a single-particle basis
Fig. 4. Fluorescence spectroscopyand microscopy: (A) conceptual EEM displaying: fluorescence dataarea (white), areas strongly influenced by Rayleighand Tyndall light scattering (grey
diagonal bars), areas without meaningful data (grey stripes); contour lines for the fluorophores tryptophan, NADPH, and riboflavin; operational range of selected bioaerosol detectors
represented by horizontal colored lines: UV-APS (ultraviolet aerodynamic particle sizer), WIBS (wideband integrated bioaerosol sensor), BIO IN (Bioaerosol single particle detector for
the Fast Ice Nucleus CHamber (FINCH)), AIM (aerosol interrogation module), DPFS (Dual-excitation-wavelength Particle Fluorescence Spectrometer), Fabiola (Fluorescence Applied to
BIOLogical Agents detection), and AFS (aerosol fluorescence sensor). Length of individual lines indicates measured emission band for a certain excitation wavelength shown as sharp
line for purpose of clarity. Single-wavelength detectors are represented by one line, dual-wavelength detectors by two lines (Pöhlker et al., 2012a). High-resolution microscopy images
of selected pollen species: (B) Pinus sylvestris, and (C) Betula fontinalis in bright field (left, scale bar = 30 μm.) and fluorescence mode (right). Fluorescence images shown as overlay of
three channels (Pöhlker et al., 2013).
351J. Fröhlich-Nowoisky et al. / Atmospheric Research 182 (2016) 346–376
(e.g., lipids, cellulose, or biogenic SOA components; Buiarelli et al., 2013;
Liang et al., 2013; Zhang et al., 2015). Recent developments in mass
analyzer techniques, which combine high resolution with high mass ac-
curacy (e.g., Orbitrap technology), are opening up new possibilities for
biomarker and proteomic analyses (Hernàndez et al., 2012; Liu et al.,
2016; Makarov and Scigelova, 2010; Pratt and Prather, 2012; Yates
et al., 2009). Vibrational spectroscopy (infrared and Raman scattering)
has also been utilized in a number of instances to characterize
bioaerosols (Ben-David and Ren, 2003; Huston et al., 2004; Rösch
et al., 2006; Thrush et al., 2012), and recently a Raman microscope for
real-time analysis of bioaerosols has become commercially available
(Ronningen et al., 2014).
Cell viability and vitality are other important aspects of bioaerosol
analysis (Urbano et al., 2011). Viability, transformation, and adaptation
are essential for the biological, ecological, and pathological roles of
bioaerosols. Evenbacterial ice nucleation hasbeen suggested to be high-
ly dependent on the status of cells, as proteins associated with intact
cells have been proposed to be more efficient ice nuclei than purified
proteins or proteins associated with disrupted cells (Möhler et al.,
2007; Morris et al., 2004). Thus, in addition to the taxonomic and chem-
ical identification of bioaerosols it is important to obtain information re-
garding their viability and metabolic activity to ascertain the role of
bioaerosols in atmospheric processes.
Cultivation methods have long been used to detect living microor-
ganisms. As pointed out above, only a small fraction of all species that
exist in nature can be grown in the laboratorywith the current culturing
techniques. Thus, culturing can be particularly useful for targeting indi-
vidual species or groups where culture conditions are known. In addi-
tion to culturing, bioluminescence-based techniques that detect the
presence of adenosine-5′-triphosphate (ATP), the primary source of
Fig. 5. Relationship of themean fluorescent coarseparticle concentration (N
F,C
) determinedby real-time instruments(WIBS-4 fluorescence channelsFL1, FL2, and FL3; UV-APS) andspore
concentrations fromSporewatch impactor sampleanalysis. Crossesrepresent 2 h measurement points, colored bysampling date. Blacklines representunweightedlinearfits (Healy et al.,
2014).
Fig. 6. Diurnal plots of spore number concentrations (a) and size-resolved numberconcentrations of fluorescent particles (upper half of panels b–e) and integrated fluorescent particle
number (N
F,c
,D
a
N1μm) as the black trace and relative humidity as the blue trace (lower half of panel b–e) (Healy et al., 2014).
352 J. Fröhlich-Nowoisky et al. / Atmospheric Research 182 (2016) 346–376
energy in a living cell, allow a rapid but not species-specific assessment
of the viable microorganisms in air and cloud water samples (Amato
et al., 2007b; Lin et al., 2013; Park et al., 2014, 2015; Stewart et al.,
1997; Stopa et al., 1999).
In summary, to gain a better understanding of the abundance,
sources, transport, and transformation of bioaerosols, it is crucial to
determine their chemical, genetic, and taxonomic composition as
well as their concentration, seasonal variation, vitality, regional di-
versity, and evolution. Sophisticated techniques in the field of instru -
mental trace analysis (e.g., mass spectrometry) and microbiology,
especially DNA sequencing technologies, need to be further developed
and applied. Molecular probes for strain- to phyla-specificclassification
of microorganisms are necessary to open up new possibilities for the
study of biological particles in the atmosphere. Metagenomic and
metatranscriptomic analysesmay prove especiallyuseful to open a win-
dow on health-related issues, as the identity and activity of pathogens
can be determined. The comprehensive characterization and identifica-
tion of airborne microbial communities will impact various disciplines,
including studies of microbial diversity and biogeography, public
health, and microbial roles in biogeochemical cycling and climate
processes.
3. Transport and transformation of bioaerosols
Since bioaerosols are released at the Earth's surface, they are typical-
ly most abundant in the lowest part of the atmosphere, the so-called
Fig. 7. Seasonal cycles of FBAP concentration measurements with the UV-APS at two climatically different sampling sites and key meteorological data (Schumacher et al., 2013).
Fig. 8. Regional scale simulations: (A) average simulated FBAP emission flux (F
FBAP
) in late August 2010 [m
−2
s
−1
] and (B) averaged horizontally distributed FBAP/fungal spore
concentration, emitted by F
FBAP
, in the lowest model layer, in late August 2010 [L
−1
]. Circles indicate the locations of the different FBAPmeasurement time series and the color within
the white circles represents the mean emission flux calculated from FBAP measurements at each location (Hummel et al., 2015).
353J. Fröhlich-Nowoisky et al. / Atmospheric Research 182 (2016) 346–376
planetary boundary layer (PBL). From a biological perspective it is par-
ticularly important to understand the transport processes in the PBL,
since these transport processes affect the spread and the distribution
of organisms and species, the speed of evolution, the formation of new
species and microbialcommunities, and the adaptation to changingen-
vironmental conditions (Fröhlich-Nowoisky et al., 2012; Morris et al.,
2014b; Womack et al., 2010). In atmospheric processes, bioaerosols
play a role in the formation of cloud droplets, ice crystals, and precipita-
tion, and may thus affect the hydrological cycle as well as atmospheric
chemistry and physics (Amato et al., 2007a; Deguillaume et al., 2008;
Diehl and Wurzler, 2010; Diehl et al., 2001; Hoose and Möhler, 2012;
Huffman et al., 2013; Möhler et al., 2007; Morris et al., 2014a; Pöschl
et al., 2010; Pratt et al., 2009; Prenni et al., 2009, 2013; Sesartic et al.,
2012; Tobo et al., 2013). However, current knowledge on the vertical
distribution of bioaerosols and the factors controlling their atmospheric
transport over large scales and above the PBL based on observations is
limited (Després et al., 2012).
3.1. Emission and transport
Global and regional models have been used to improve the scientific
understanding of bioaerosol emission, transport, and atmospheric im-
pact (Fig. 9;Ansari et al., 2015; Burrows et al., 2009a, 2009b, 2013b;
Heald and Spracklen, 2009; Hoose et al., 2010; Hummel et al., 2015;
Sesarticet al., 2012; Spracklen and Heald, 2014). These models are high-
ly dependent on the correct representation of the emissions and the
particle properties and modifications that might occur during transport,
as well as on the correct representation of thesmall-scale transport pro-
cesses themselves. Furthermore, these models do not address the bio-
logical consequences for the organisms concerning survival, vitality,
and metabolic activity. Emission estimates of PBA particles suffer from
large uncertainties (Elbert et al., 2007), which can range from 80 to
870% (Burrows et al., 2009a, 2009b). These uncertainties originate
from biological processes in the ecosystems, including seasonality, life
cycles, land cover changes, climatic dependencies, variation in microbial
populations, and species competition. In addition, alterations caused by
aging, chemical processing, and microphysics introduce additional chal-
lenges to estimating correctly global transport and effects of bioaerosols
in the atmosphere (Burrows et al., 2013b). The emission strengths of
bioaerosols and their interaction with atmospheric transport processes
thus need improved quantification.
Close to the ground, turbulent small-scale transport drives the distri-
bution of all particles emitted from the Earth's surface. The planetary
boundary layer is directly affected by emissions from the surface and
therefore also by the emission of bioaerosols. Depending on the geo-
graphic location and season, the thickness of the boundary layer un-
dergoes a diurnal cycle, typically spanning a few hundred meters
during nighttime, but extending up to 3 km during daytime. Diurnal
and seasonal cycles of solar radiation and temperature stimulate biolog-
ical activity, thereby constituting a strong link between biological activ-
ity, emissions, and atmospheric transport (Jones and Harrison, 2004;
Matthias-Maser et al., 1995; Toprak and Schnaiter, 2013). Small-scale
atmospheric processes, such as cloud processing in low-level clouds
and wet deposition, further affect the abundance of bioaerosols in the
atmosphere (Huffman et al., 2013). These atmospheric processes partly
limit the travel distances in the boundary layer and reduce the number
concentrations of non-biological as well as biological particles entering
the free troposphere above the boundary layer (Sesartic et al., 2012).
However, several processes like frontal uplift, convection, or turbulence
at the boundary layer top maylead to an uplift of these air masses across
the inversion capping the boundary layer into the free troposphere,
where biological particles can potentially travel large distances as part
of the tropospheric flow.
Direct measurements of bioaerosol abundance are mainly ground
based. Even observations at 50 m above ground level are very sparse
and only few measurements from aircraft (Andreeva et al., 2002;
DeLeon-Rodriguez et al., 2013; Fulton, 1966; Gruber et al., 1998;
Kourtev et al., 2011; Ziemba et al., 2016; Zweifel et al., 2012)orhighal-
titude stations are available (Crawford et al., 2016; Gabey et al., 2013;
Hallar et al., 2011; Matthias-Maser et al., 2000c). Consequently, global
and regional model estimates regarding possible effects of bioaerosols
on atmospheric processes also suffer from these uncertainties and
need to be better constrained by observations in the atmosphere. Nota-
bly, knowledge of bioaerosol emission quantities close to their sources
and of subsequent transformation processes is crucial for reliable esti-
mations of the effects of bioaerosols on the atmosphere.
Estimates of emissions based on measurements of particle concen-
tration also suffer from inherent uncertainties, as the removal rates of
Fig. 9. Modelresults for annual-mean near-surface concentrations of PBA:(A) fungi in fine mode aerosol [μgm
−3
], (B) fungiin coarse mode aerosol[μgm
−3
], and (C) number of bacteria
tracers [10
3
m
−3
](Burrows et al., 2009a, 2009b), (D) bacteria, fungal spores, and pollen [m
−3
](Hoose et al., 2010).
Images A and B reprinted from Heald and Spracklen (2009); copyright 2009, with permission of John Wiley and Sons, Inc.
354 J. Fröhlich-Nowoisky et al. / Atmospheric Research 182 (2016) 346–376
particles from the atmosphere are not known and emissions must be in-
ferred indirectly using models or assumptions about emissions. Mea-
surements of bioaerosol emission fluxes by more direct methods,
while less commonly performed, can provide valuable direct observa-
tional constraints. Possible methods for bioaerosol emission flux mea-
surements fall into two general classes, gradient methods and eddy
covariance-like methods. Gradient methods, such as the Bowen ratio
method assume that the transport of atmospheric trace constituents
in the boundary layer can be assumed to be analogous to the transport
of more readily measureable quantities, such as heat and moisture.
The Bowen ratio method and related gradient methods have been ap-
plied in many of theexisting studies including direct flux measurements
of bacteria and other bioaerosols (e.g., Crawford et al., 2014; Lighthart
and Shaffer, 1994). These methods require a large number of measure-
ments for statistical significance and suffer from inherent uncertainties
due to the assumptions used to interpret the gradients.
Eddy covariance and related methods involve calculating the corre-
lations between high-frequency time-series measurements of particu-
late or trace gas concentrations and the vertical wind speed. The eddy
covariance method is regarded as the “gold standard”for flux measure-
ments of trace gases and aerosol number fluxes (e.g., Gallagher et al.,
1997; Norris et al., 2008; Pryor et al., 2007). This method requires fast-
response instrumentation (typically 10 Hz or faster) and sufficiently
high concentrations for robust statistical analyses, which are difficult
to achieve for bioaerosols. In the absence of high-time-resolution mea-
surement capabilities, an adaptation of eddy covariance known as “re-
laxed eddy accumulation”(Businger and Oncley, 1990; Gaman et al.,
2004; Held et al., 2003, 2008), may be a more appropriate method for
the measurement of bioaerosol fluxes. Relaxed eddy accumulation is
based on conditional sampling of updrafts and downdrafts, and can be
used with analysis methods that have much slower response times.
3.2. Physical, chemical, and biological transformation
The atmosphere not only acts as a passive transport medium, but
also modifies the microphysical and chemical properties of living and
dead biological matter. Cellular responses are initiated in living matter,
whereas dead matter can be decomposed and become a source of cellu-
lar structures and smaller chemical compounds, which may influence
the physical, chemical, and biological properties of the aerosols.
Bioaerosol particles can undergo fragmentation in the atmosphere,
and bioparticle fragments can be suspended from the Earth's surface
into the air. Altering the size distribution and other properties of
bioaerosol particles (surface and bulk composition, hygroscopicity,
etc.) in turn can affect their ability to act as cloud condensation nuclei
(CCN) or ice nuclei (IN), thus influencing their atmospheric transport
and processing (Diehl et al., 2001; Morris et al., 2004; Schnell and Vali,
1972). Heterogeneous and multiphase chemical reactions can lead to
oxidation, nitration, oligomerization, and degradation of proteins and
other primary biological substances, modifying the molecular composi-
tion and biological activity of bioparticles. For example, reactions with
air pollutants (e.g., O
3
and NO
2
) have been shown to enhance the aller-
genic potential of airborne allergens, such as birch pollen, ragweed pol-
len, and Aspergillus spores (Franze et al., 2005; Gruijthuijsen et al., 2006;
Lang-Yona et al., 2016; Reinmuth-Selzle et al., 2014; Zhao et al., 2016).
Also, secondary organic and inorganic material can form a liquid or
solid coating on bioparticles influencing their chemical, physical, and bi-
ological properties.
Certain types of bioparticles were specifically shaped by evolution to
be transported by wind and use the atmosphere for their dispersal.
These comprise endo- or resting spores of bacteria, fungi, mosses and
ferns, pollen grains, and small plant seeds. These structures are gen-
erally found to have, on the one hand, thick cell walls sheltering
them effectively from environmental stresses and, on the other
hand, a minimal metabolism rate. These dispersal units are either ac-
tively emitted, such as wet-discharged fungal spores, or passively
emitted, such as dry-discharged fungal spores, small seeds, and most
pollen (Arditti and Ghani, 2000; Elbert et al., 2007; Jones and
Harrison, 2004; Marshall and Chalmers, 1997; Morris et al., 2014b;
Murren and Ellison, 1998). Besides such dedicated dispersal units,
many other organisms, such as algae, (cyano)bacteria, fungi, and virus-
es, can also become aerosolized and are transported passively through
the air. The vitality of these organisms is dependent on their adaptation
or ability to react actively to changing environmental conditions (resil-
ience). Moreover, also aggregation of cells, attachment to other aerosol
particles, or protective envelopes may influence viability of bioaerosols
(Amato et al., 2015; Morawska, 2006; Tong and Lighthart, 1998). How-
ever, although the atmosphere is intensively discussed as a possible
habitat, hardly any studies exist that reveal the metabolic activity of mi-
croorganisms during their residence time in the atmosphere. Up to
now, metabolic activity has been shown almost exclusively in specific
small-scale environments like cloud droplets (Amato et al., 2005,
2007a, 2007b; Dimmick et al., 1975; Vaïtilingom et al., 2013).
The stresses induced in microorganisms while airborne influence
their activity and vitality andthus their capability to colonizenew hab-
itats and to survive. Atmospheric stress can be considered an evolution-
ary force exposing airborne bioaerosols to selection pressure, thereby
affecting the dispersal and evolution of microorganisms. Among the
most significant stress factors are temperature, humidity, oxidative
stress, starvation, radiation, and osmotic stress. Furthermore, it is
believed that phylogenetic aspects of primary biological particles in
the atmosphere lead to a selection of species becoming airborne or
transported as living matter to high altitudes (Alfreider et al., 1996).
How airborne transport affects different microorganisms and their abil-
ity to settle and then proliferate again is currently not well understood.
3.3. Cloud interactions and bioprecipitation cycle
The role of biological particles in cloud formation, precipitation, eco-
system interactions, and possible feedback cycles is a topic of increasing
interest (Amato et al., 2015; Andreae and Rosenfeld, 2008; Ariya et al.,
2009; Ariya and Amyot, 2004; Després et al., 2012; Haga et al., 2013;
Hoose and Möhler, 2012; Huffman et al., 2013; Joly et al., 2014; Mason
et al., 2015; Michaud et al., 2014; Möhler et al., 2007; Morris et al.,
2014a;Pöschletal.,2010;Prattetal.,2009;Sandsetal.,1982;Stopelli
et al., 2015; and references therein). Forplant pollen and many microor-
ganisms aerial dispersal is part of their life cycle (Brown and Hovmøller,
2002). To maintain viability in the atmosphere, microorganisms have
adapted to the conditionsin the atmosphere and evolved survival strat-
egies for long-distance dispersal or dispersal at high altitudes (Griffin,
2004; Imshenetsky et al., 1978; Joly et al., 2015; Kellogg and Griffin,
2006; Morris et al., 2011; Prospero et al., 2005; Womack et al., 2010).
As alreadymentioned above, microorganisms and other bioaerosols
are removed from the atmosphere either by dry or wet deposition,
i.e., incorporationinto cloud droplets or ice crystals, possibly influencing
precipitation, the hydrological cycle, and climate (Fig. 2). Biological CCN
or IN may be present as living or deadcells, cell fragments, hyphae,pol-
len, spores, detached IN-active macromolecules, biogenic potassium-
salt particles, or associated with plant particles or soil organic matter
(e.g., Bauer et al., 2003; Conen et al., 2011; Després et al., 2012; Diehl
et al., 2001; Dingle, 1966; Franc and Demott, 1998; Fröhlich-Nowoisky
et al., 2015; Hill et al., 2016; Hiranuma et al., 2015; Huffman et al.,
2013; Kieft and Ahmadjian, 1989; Kieft, 1988; Maki and Willoughby,
1978; Möhler et al., 2007; O'Sullivan et al., 2016; Pöhlker et al., 2012b;
Pouleur et al., 1992; Pummer et al., 2012, 2015; Šantl-Temkiv et al.,
2015; Sattler et al., 2001; Schnell and Vali, 1976; Schnell and Vali,
1972; Tobo et al., 2014; Vali et al., 1976).
Cloud condensation nuclei can nucleate liquid cloud droplets. The
potential for a particle to act as CCN is ranked by the atmospheric
water vapor pressure required for it to nucleate and depends on both
its size and composition (Andreae and Rosenfeld, 2008; Farmer et al.,
2015). Some pollen, fungal spores, and bacteria can be activated as
355J. Fröhlich-Nowoisky et al. / Atmospheric Research 182 (2016) 346–376
CCN at relatively low supersaturation levels and are called giant CCN
due to their large size compared to other non-bioaerosol CCN-active
aerosols (e.g., Andreae and Rosenfeld, 2008; Bauer et al., 2003; Delort
et al., 2010; Franc and Demott, 1998; Hassett et al., 2015; Pope, 2010;
Sun and Ariya, 2006). For example, Bauer et al. (2003) isolated several
bacterial species from aerosol and cloud water samples that were acti-
vated as CCNat supersaturations between ~0.07 and 0.11%. In the atmo-
sphere, giant CCN represent a small fraction (0.001–0.01%) of particles
(Posselt and Lohmann, 2008). Nevertheless, they are of special interest,
because they will be activated first, grow readily and play a role in shap-
ing cloud cycles (Andreae and Rosenfeld, 2008). According to a global
modeling study, the incorporation of the giant CCN accelerates the hy-
drological cycle, so that clouds precipitate faster (but not more) and
less condensed water is accumulated in the atmosphere (Posselt and
Lohmann, 2008). Additionally, it has been shown that pollen grains
can rupture under humid conditions and release cytoplasmic material,
forming submicron particles that can act as CCN (Steiner et al., 2015;
Taylor et al., 2002, 2004).
Ice particles in the atmosphere can be formed via homogeneous or
heterogeneous ice nucleation. Homogeneous freezing of liquid water
droplets is a time-dependent stochastic process, which can be described
by the formation of an ice embryo with critical size, whose probability to
form ice increases with time (Pruppacher and Klett, 2010). In contrast,
heterogeneous freezing is triggered by foreign particles or macromole-
cules serving as IN (Hoose and Möhler, 2012; Pummer et al., 2015).
Bioaerosols had already been found in ice crystals in the late 1950s
(Ariya and Amyot, 2004; Schnell and Vali, 1976; Vali et al., 1976).
Fig. 10 shows that biological IN, such as bacteria, are much more
efficient IN for immersion freezing than mineral dust or soot, as they
can trigger ice formation at high subzero temperatures (Hoose and
Möhler, 2012). Thus, biological IN can be expected to be important for
clouds or cloud regions warmer than −15 °C (DeMott and Prenni,
2010; Morris et al., 2014a; Murray et al., 2012). Additionally, between
Fig. 10. Ice-nucleation-active site densities for Arizona test dust (ATD), kaolinite, natural
desert dusts, soot, and bioaerosols for immersion freezing, including deposition, and
condensation freezing experiments at or above water saturation. The lines are inserted
to guide the eye. The blue line refers to ATD, desert dusts, and clay minerals. The green
line refers to biological aerosols (Hoose and Möhler, 2012).
Fig. 11.Cumulative IN spectrabefore and after filtration for different fungalspecies and pollen:(A) Acremonium implicatum (now Sarocladium implicatum), Isaria farinosa,Mortierella alpina
(Pummer et al., 2015), (B) Fusarium avenaceum, and (C) pollen from Betula pendula (O'Sullivan et al., 2015).
356 J. Fröhlich-Nowoisky et al. / Atmospheric Research 182 (2016) 346–376
temperatures of −3°Cand−8 °C, ice multiplication by the Hallett-
Mossop process might occur, leading to higher concentrations of ice
crystals by rime splintering of ice particles (Hallett and Mossop, 1974).
The best studied IN-active microorganisms are bacteria, which have
been found in the boundary layer and in the upper troposphere
(Lindemann and Upper, 1985; Lindemann et al., 1982). Many strains
of the genera Pseudomonas,Pantoea,andXanthomonas are IN-active
and express isoforms of the same IN-active protein (Hill et al., 2014a).
The proteins are anchored in the outer membrane and can form large
aggregates triggering ice nucleation at up to −1.5 °C (Kozloff et al.,
1991; Lindow, 1989). As shown in Fig. 10, IN-active bacteria, such as
some Pseudomonas syringae strains, reach IN-active surface site densi-
ties of N10
10
m
−2
already at temperatures above −10 °C, whereas for
mineral dust, these values are typically reached only below −20 °C. Re-
cent investigation of the interaction of P. syringae with water molecules
demonstrated that the IN-active protein enhances ice nucleation by ar-
ranging water molecules into alternating stripes of higher and lower-
ordered molecules, and that latent heat is effectively removed from
the nucleation site (Pandey et al., 2016).
Ice nucleation activity has also been documented in pollen, algae,
fungi, lichen, insects, leaf litter, and plankton, as reviewed elsewhere
(Després et al., 2012; Moffett et al., 2015; Pummer et al., 2015; von
Blohn et al., 2005). For example, laboratory experiments examining
the IN activity of pollen in the immersion mode have shown that birch
pollen grains can induce freezing of droplets at temperatures as high
as −9°C(Diehl et al., 2002). Recently, IN activity has been discovered
in several moss and liverwort species (Moffett, 2015; Weber, 2015).
Moreover, Mortazavi et al. (2015) isolated an IN-active bacterium pos-
sibly belonging to the genus Bacillus (96% similarity) from fresh snow.
There is also a growing interest in the IN properties of fungal species,
and IN activity above −20 °C has been found in several fungal species,
such as Boletus zelleri (Haga et al., 2014), Endocronartium harknessii
(Haga et al., 2013), Hemileia vastatrix (Morris et al., 2013), Isaria farinosa
(Huffman et al., 2013), Mortierella alpina (Fröhlich-Nowoisky et al.,
2015), Puccinia spp. (Haga et al., 2013; Morris et al., 2013), Sarocladium
(formerly Acremonium)implicatum (Huffman et al., 2013), and Ustilago
nigra (Haga et al., 2014).
Particularly interesting is the observation of detached nanometer-
sized IN-active macromolecules (INM) that are active at high tempera-
tures in fungal species of different phyla and in pollen (Fig. 11;
Fröhlich-Nowoisky et al., 2015; O'Sullivan et al., 2015; Pouleur et al.,
1992; Pummer et al., 2012, 2015). Associated with soil dust particles,
these INM may impact cloud glaciation indirectly, indicating a higher
contribution and importance of biological, in particular fungal, IN than
previously assumed (Fröhlich-Nowoisky et al., 2015; O'Sullivan et al.,
2015; Pummer et al., 2015). For proteinaceous INM from Fusarium
avenaceum it was recently demonstrated that they can be adsorbed
onto kaolinite, a common soil clay mineral, conferring their IN activity
to the mineral particles (O'Sullivan et al., 2016). Augustin-Bauditz
et al. (2016) presented similar findings of illite-NX particles mixed
with birch pollen INM. Moreover, nanometer-sized particles of biologi-
cal and inorganic origin were found to be the most abundant particles in
snow samplesfrom different ecosystems (Rangel-Alvarado et al., 2015).
It is still an open question whether there are sufficient numbers of
CCN- and IN-active bioaerosols at cloud altitudes to affect cloud forma-
tion and evolution. However, in pristine air over vegetated regions or
under remote conditions, bioaerosols might represent a significant frac-
tion of CCN and IN and are likely to be an essential regulating factor in
the formation of clouds and precipitation (Andreae and Rosenfeld,
2008; Healy et al., 2014; Huffman et al., 2013; Pöhlker et al., 2012b;
Fig. 12. Aerosol properties during dry periods and rain events: (A, B) fluorescence microscope images of aerosol impactor samples, (C, D) size distributions of IN and of fluorescent
bioparticles, and (E, F) number concentrations of IN plotted against fluorescent bioparticles (Huffman et al., 2013).
357J. Fröhlich-Nowoisky et al. / Atmospheric Research 182 (2016) 346–376
Pöschl et al., 2010). Moreover, Creamean et al. (2013) found by direct
cloud and precipitation measurements that long-range transported
dust mixed with biological residues plays an important role in cloud
ice formation and precipitation processes over the western United
States. Wright et al. (2014) proposed that increasing relative humidity,
due to a cold-frontal passage, could trigger the release of biological IN,
which in turn may seed the frontal cloud band. Increasing concentra-
tions of bioaerosols and IN during and after rain events have been
found in a forest ecosystem (Fig. 12;Huffman et al., 2013; Prenni
et al., 2013; Tobo et al., 2013).
Fig. 12A and B shows microscopic images of aerosol impactor sam-
ples highlighting the contrast between irregularly shaped dust in a sam-
ple collected during dry weather and cellular structures in a sample
collected during a rain event. During dry weather conditions dominated
by dust, the concentrations of IN at −15 °C were between 0.01 and
0.02 L
−1
, and no correlation with FBAP concentration was found
(Fig. 12C and E). In contrast, during rain events, the size distribution of
IN exhibits a distinct peak in the range of 2–6μm that coincides with
the peak of the size distribution of FBAP (Fig. 12D). Furthermore, the
measured IN concentrations followed a close linear correlation with
FBAP concentration (Fig. 12F). The strong contrast between dry and
rainy periods suggests that the release of PBA during and after rain
may play an important role in the spread and reproduction of microor-
ganisms in certain environments, and it may also contribute to the at-
mospheric transmission of pathogenic and allergenic agents (Fig. 13A;
Huffman et al., 2013).
Additionally, long-term measurements of IN concentrations and
rainfall in Australia indicate strong links between microorganisms
and rainfall that persist over longer periods of time than previously
assumed (Bigg et al., 2015). Ice nucleation activity that promotes
the formation of precipitation would be a beneficial adaptation for
microorganisms to return to the land surface under favorable condi-
tions (Fig. 13;Morris et al., 2008; Sands et al., 1982). A feedback cycle
involving the release of plant-associated microorganisms that are
transported to cloud altitudes, followed by microbial rainfall induc-
tion resulting in increased plant and microbial growth, was already
proposed in 1982 (Sands et al., 1982). This bioprecipitation feedback
mechanism and related biotic processes involved in the hydrological
cycle may have played an important role in the coevolution of life
and climate as well as in the future development of the Earth system
inthecourseoftheAnthropocene(Christner et al., 2008; Huffman
et al., 2013; Morris et al., 2014a; Pöschl and Shiraiwa, 2015). A
more detailed discussion linking the bioprecipitation feedback
cycle with Earth history and biological species evolution is given in
Morris et al. (2014a).
Primary biological aerosols also contribute to the abundance of IN in
marine environments. Ice nucleation activity has been identified in sev-
eral marine bacteria and phytoplankton species (Alpert et al., 2011a,
2011b; Knopf et al., 2010; Parker et al., 1985; Schnell and Vali, 1975;
Schnell, 1975). As summarized in section 4.2, particulate matter of bio-
logical origin can be emitted via sea spray from marine sources. Organic
matter from the sea-surface microlayer has been shown to be a source
of atmospheric IN (Wilson et al., 2015), and laboratory simulations
using real wave breaking in a laboratory flume showed an increase
of sea spray IN emissions associated with phytoplankton blooms
(DeMott et al., 2015).
Different model simulations suggest regional differences in the im-
portance of marine biogenic IN (Burrows et al., 2013a; Wilson et al.,
2015). As illustrated in Fig. 14, marine biogenic IN are likely to play a
dominant role in the near-surface air in remote marine regions, such
as over the Southern Ocean. These regions are less influenced by long-
distance transport of continental dust and more affected by sea spray
generation due to strong winds.
Climate and land-use related changes in the atmospheric abundance
of bioaerosols and in consequence of biological CCN and IN could result
in previously unconsidered feedbacks that influence the hydrological
cycle and the Earth's energy balance (Andreae and Rosenfeld, 2008;
Burrows et al., 2013a).
Integration and synthesis of experimental studies, measurement
data, and model calculations of biopa rticle emission, transport, trans-
formation, and deposition will be essential to achieve full understand-
ing of the atmospheric lifecycle of bioaerosols and to find out if
bioprecipitation and related effects are important for the co-evolution
of climate and life on Earth.
4. Bioaerosol-ecosystem interactions
4.1. Terrestrial ecosystems
Terrestrial ecosystems are major sources of atmospheric bioaerosols.
Vascularplants and fungi are well known to produce and release pollen
and spores during reproduction, and fragments of plant and fungal tis-
sues can alsobe emitted into the atmosphere in the course of decay pro-
cesses (Després et al., 2012; Jaenicke, 2005; Matthias-Maser et al.,
2000b). Less well-known emission sources of bioaerosols are micro-
bial surface communities or cryptogamic covers consisting of
(cyano)bacteria, archaea, algae, fungi, lichens, and bryophytes in
varying proportions. As so-called cryptogamic ground covers they
occur on soil and rocks, forming biological soil and rock crusts as
Fig. 13. Bioprecipitation cycle. Terrestrial ecosystems are the major source of ice nucleation
active microorganisms; precipitation and humidity can enhance bioparticle emissions (rain
splash, active wet discharge, etc.); bioparticles serving as ice nuclei or giant cloud
condensation nuclei (IN/GCCN) can influence the evolution of clouds and precipitation,
which provide water for growth of vegetation and for multiplication of microorganisms (A,
B). Deposition of pathogenic and allergenicspecies can trigger human, animal and plant
diseases (A; Huffman et al., 2013). Ice nucleation activity of microorganisms is positively
selected in various ecosystems, on frost damaged plants and with precipitation itself.
(B) Adapted from Morris et al. (2014a); copyright 2013, with permission from John Wiley
and Sons, Inc.
358 J. Fröhlich-Nowoisky et al. / Atmospheric Research 182 (2016) 346–376
well as bryophyte and lichen carpets. Cryptogamic plant covers
spread over large portions of terrestrial plant surfaces, including
stems, branches, and leaves of treesand shrubs (Fig. 15). These crypto-
gamic covers have been estimated to cover about one third of the avail-
able and suitable ground surface area (i.e., ∼27.3 × 10
6
km
2
) and one
third of the suitable plant surface area (i.e., ∼57.3 × 10
6
km
2
; see Sup-
plementary Table S1 in Elbert et al., 2012). Thus, cryptogamic covers
have a total estimated projected surface area of ∼85 × 10
6
km
2
, being
larger than the surface area of Africa and the Americas combined, and
thereby contribute to the terrestrial bioaerosol formation. This also ex-
plains why microorganisms and bryophytes contribute large diversity
and number concentrations per unit surface area in various natural
and anthropogenically influenced environments (Hantsch et al., 2013;
Lindow and Brandl, 2003; Morris and Kinkel, 2002; Yadav et al., 2005).
Plant pollen, fungal spores, bacteria, algae, and cyanobacteria
have been identified in bioaerosol samples (e.g., Bauer et al.,
2002a; Bowers et al., 2013; Brown et al., 1964; DeLeon-Rodriguez
et al., 2013; Delort et al., 2010; Després et al., 2012; Favero-Longo
et al., 2014; Fröhlich-Nowoisky et al., 2009; Marshall and Chalmers,
1997; Sesartic and Dallafior, 2011; Smets et al., 2016), but their inter-
actions with different habitats have not been resolved. In addition, the
relative importance of vascular plants and cryptogamic covers has not
been investigated across different biomes and ecosystems. Plants and
fungi also release volatile organic compounds (Kesselmeier et al.,
1999; Wilske and Kesselmeier, 1999; Wilske et al., 2001)andhave
been proposed as a source of small (≤100 nm) potassium salt particles
that can act as nuclei for the condensation of low-volatility organic
vapors in rainforest air (Pöhlker et al., 2012b). Thus, both vascular
plants and cryptogamic organisms can influence the composition,
quantity, and chemical processing of bioaerosols. Apart from its role as
a source of bioaerosols, vegetation is also affected by the deposition of
bioaerosols from the atmosphere, influencing the dispersal, genetic
mixing, and evolution of plants and microorganisms.
Both bioaerosol formation and the effects of bioaerosols on vegeta-
tion are influenced by climate and habitat conditions. Land use change
is also known to affect the formation and dispersal of bioaerosols.
Once natural lands are converted to human use (e.g., agriculture and
construction), natural vegetation and cryptogamic covers are often
destroyed. As biological soil crusts are well known to stabilize the soil
surface, drastically reducing the erosive effects of wind (Belnap and
Gillette, 1998; Eldridge and Leys, 2003), their destruction, besides the
damage to vascular plant vegetation, causes increases in frequency
and strength of dust storms, as for example experienced in the western
United States during settlement in the 19th century (Neff et al., 2008).
But also recent dust storm events, as in China, are considered to be
largely caused by land use changes (Hill et al., 2014b). Soil dust particles
containing biogenic compounds, which are also expected to be emitted
during these events, have been described to be particularly potent dur-
ing ice nucleation processes (e.g., Schnell and Vali, 1972; O'Sullivan
et al., 2015). As the vitality of cryptogamic covers and organisms de-
pends strongly on the availability of water in their environment, they
are particularly susceptible to the bioprecipitation feedback mecha-
nisms outlined above (Sect. 3.3). Thus, bioaerosol emissions from cryp-
togamic covers may be strongly affected by global change and should be
further investigated and explicitly considered in regional and global
models of atmosphere, biosphere, and climate interactions.
4.2. Aquatic ecosystems
Compared to terrestrial ecosystems, much less is known about the
contribution of marine ecosystems as sources and sinks of bioaerosols,
although oceans cover N70% of the Earth's surface. On one hand,
bioaerosols over the oceans are influenced by terrestrial sources
and long-distance transport of microbes, e.g., plant and human patho-
gens (Brown and Hovmøller, 2002; Cho and Hwang, 2011; Sharoni
et al., 2015). On the other hand, the oceans themselves are sources of
bioaerosols (Aller et al., 2005; Amato et al., 2007b; DeLeon-Rodriguez
et al., 2013; Després et al., 2012; Fahlgren et al., 2015; Leck and
Bigg, 2005; Matthias-Maser et al., 1999; Pósfai et al., 2003). Bacterial
cell concentrations in marine and freshwater environments are around
10
6
mL
−1
, whereas virus particle concentrations are larger, at around
10
7
–10
10
mL
−1
(Cho and Hwang, 2011; Maranger and Bird, 1995;
O'Dowd et al., 2015). These microbes can become airborne by the erup-
tion of rising bubbles through the sea-surface microlayer as illustrated
in Fig. 16 (Aller et al., 2005; Blanchard, 1975; Blanchard et al., 1981;
Hultin et al., 2011; Veron, 2015; Wilson et al., 2015). Film and jet
drops are generated behind the breaking wave crest when bubbles
burst or when the bubble cavity collapses. Additionally, if the wind
speed is high enough, spume drops can be ejected from the breaking
wave crest (Veron, 2015). The bubble-bursting results in an enrichment
of microbes in the aerosol compared to subsurface water (Aller et al.,
2005; Wilson et al., 2015). Depending on the concentration of bacteria
Fig. 14. Global model simulations of marine biogenic IN: (A) simulated annual mean
relative contribution of marine biogenic IN to marine boundary layer IN concentrations
at −15 °C, given in percent (Burrows et al., 2013a), (B) simulated distribution of IN
(here displayed as ice nucleating particle (INP)) concentration active at −15 °C [m
−3
]
and surface-level marine aerosol organic mass concentration [μgm
−3
], and (C) modeled
distribution of marine biogenic IN concentrations active at −20 °C at 850 hPa
(corresponding to the altitude of high-latitude mixed-phase clouds).
Images B andC reprinted with permission from MacmillanPublishers Ltd.:Nature. Wilson
et al., 2015, copyright 2015.
359J. Fröhlich-Nowoisky et al. / Atmospheric Research 182 (2016) 346–376
in the surface water and the enrichment factor, the estimated global
emission of marine bacteria is between 2000 and 10,000 Gg a
−1
(Burrows et al., 2009b). This estimate is based on a small number of
measurements, as most measurements of airborne bacteria have fo-
cused on urban or rural locations. Furthermore, until recently, marine
bioaerosol studies often relied on traditional culture-dependent tech-
niques, thusdetecting only the viable and culturable fraction of bacteria.
The majority of the bacterial population remained undetected in these
studies, as the culturability of seawater bacteria is estimated to be be-
tween 0.001% and 0.1% (Amann et al., 1995). For a more detailed
discussion of the problem of culturability of airborne bacteria see
Burrows et al. (2009b). Recently, some studies used a combination of
culture-dependent and culture-independent methods such as cloning
and DGGE (denaturing gradient gel electrophoresis) and showed differ-
ent results for the same bacterial populations, with some overlapping
findings (Cho and Hwang, 2011; Fahlgren et al., 2010; Urbano et al.,
2011). As these methods most likely reflect only the most abundant
taxa due to the limited number of sequences obtained, 16S rRNA gene
pyrosequencing has been successfully used to study bacterial popula-
tions in marine bioaerosol samples, enabling a better coverage of the
Fig. 15. Cryptogamic covers(microbialsurface communities) growing on rock, plants, and soil: (A) cryptogamicrock cover: mosaic of lichens on granitic rock, CapePoint, South Africa,
(B) cryptogamic plant cover: epiphytic lichens (Teloschistes cap ensis), Cape Point, South Africa, and (C) biological soil crust dominated by the green-algal lichen Psora decipiens,
Soebatsfontein, South Africa. All scales = 5 cm.
Fig. 16. Aerosol generation and enrichment of surface organic material (green layer) at the air-sea interface by bubble bursting.
Reprintedwith permission from Macmillan Publishers Ltd.: Nature.Wilson et al. (2015), copyright 2015.
360 J. Fröhlich-Nowoisky et al. / Atmospheric Research 182 (2016) 346–376
whole marine bacterial community (DeLeon-Rodriguez et al., 2013;
Seifried et al., 2015). Moreover, quantitative PCR has been applied to
quantify selected health-relevant cyanobacteria and dinoflagellate spe-
cies in marine air samples (Casabianca et al., 2013; Lang-Yona et al.,
2014).
Other bioaerosol types like archaea, fungi, protozoa, and algae can
also be ejected from the oceans into the atmosphere (Després et al.,
2012; Elbert et al., 2007; Hamilton and Lenton, 1998; Mayol et al.,
2014). Measurements on South Atlantic Ocean aerosol showed that bi-
ological particlesaccount for 17% in number and 10% in volume concen-
tration (Matthias-Maser et al., 1999). For the North Atlantic Ocean, the
abundances of eukaryotic and prokaryotic microorganisms in the
boundary layer ranged between 6 × 10
4
and 1.6 × 10
7
m
−2
ocean
surface,indicating a dynamic sea-air exchange with millions of microor-
ganisms leaving andenteringthe ocean per square meter everyday and
10% of microorganisms still airborne four days later (Mayol et al., 2014).
In addition, other non-cellular particles, such as waste products or exu-
dates of marine organisms, make up a large portion of microbially-
derived matter in marine waters and affect the composition of marine
atmospheric aerosol (Bigg and Leck, 2008; Burrows et al., 2013a,
2014; Wang et al., 2015). The global marine emissions of submicron pri-
mary organic aerosol particles by sea spray have been estimated to be
10 ± 5 Tg a
−1
(Gantt and Meskhidze, 2013). Consequently, improving
observations and understanding of the size-resolved organic fraction
of sea spray emissions has been identified as high priority research
topic (Meskhidze et al., 2013). These emissions can influence the num-
ber of cloud condensation nuclei available to marine clouds, which can
affect their properties and brightness (Karydis et al., 2012; Moore
et al., 2013). The resultant effects on clouds may be large enough to be
observable by satellites, allowing top-down observational constraints
on their magnitude. Recently, McCoy et al. (2015) analyzed seasonal
and spatial patterns in the satellite-observed cloud droplet number con-
centration over the Southern Ocean (35–55°S latitude), where the
ocean is the dominant source of particulate matter, and inferred an an-
nual zonal mean radiative forcing of up to 1–2Wm
−2
attributable to
the influence of marine organic sea spray aerosol on cloud droplet num-
ber and, consequently, on cloud brightness.
Fungal spores and cell emissionsfrom the oceans have been estimat-
ed to be around 10 Mg a
−1
, six orders of magnitude smaller than land
surface emissions (Elbert et al., 2007). Observed differences in fungal
species richness in marine and continental air clearly demonstrate the
presence of biogeographic patterns, and indicate that regional differ-
ences may be important for the effects of microorganisms on climate
and public health (Fröhlich-Nowoisky et al., 2012). These findings also
suggest that airflow patterns and the global atmospheric circulation
are important for the evolution of microbial ecology and for the under-
standingof global changes in biodiversity. There is a need for more mea-
surements of total concentration, fluxes, and ice-nucleating properties
of all types of bioaerosols in the marine atmosphere to understand the
importance of bioaerosols for the maintenance of biodiversity, climate,
andhealthonaglobalscale(Burrows et al., 2009b; Mason et al., 2015;
Pöschl, 2005). Moreover, deposited PBA particles in marine sediments,
as well as in lake sediments and ice cores, can provide information
about climatic changes of the past (Combourieu-Nebout et al., 2013;
Kattel andSirocko, 2011;Liu et al., 1998; Mueller et al., 2010;Schmiedl
et al., 2010). For instance, pollen grains are well preserved in the sedi-
ment layers. They can be extracted from sediments and identified
based on morphology, which allows a reconstruction of past vegetation
patterns. Changes over time in the diversity and abundance of different
types of pollen grainscan indicate changes in vegetation that may be re-
lated to climate change or human influence. However, it is necessary to
understand the source area of pollen, i.e., the influence of long-distance
transported pollen, and the factors that influence the preservation,
transport, and deposition of pollen grains in an aquatic environment
in order to accurately interpret the pollen record (Barreto et al., 2012;
Davis and Brubaker, 1973; Davis, 1968, 2000; Klemm et al., 2015;
Matthias and Giesecke, 2014; Pittam et al., 2006). As reviewed by
Davis (2000), different models have been developed to predict the
size of the relevant source areas, how the ratio of regional to local pollen
changes with lake size, or how landscape patterns will be reflected in
pollen records. These models can help to choose lakes of appropriate
size and to calculate the size of the expected source area. In addition,
also biomarkers and DNA analysis can be used to investigate the rele-
vance of different organisms in the past (Domaizon et al., 2013; Kyle
et al., 2015; Okano et al., 2007; Romero-Sarmiento et al., 2011).
4.3. Pathogens and allergens
Bioaerosols can have infectious, allergenic, or toxic effects on liv-
ing organisms, impacting health and agriculture on local, regional,
and global scales. Many plant, animal, and human pathogens are
dispersed through the air; some can travel over long distances
spreading diseases across and even between continents (Brown
and Hovmøller, 2002; Fisher et al., 2012). Several plant pathogens,
including those causing rust, downy mildew, and powdery mildew
diseases are responsible for significant economic losses in agriculture
worldwide (Aylor and Taylor, 1982; Brown and Hovmøller, 2002;
Burt, 1995; García-Blázquez et al., 2008; Lucas et al., 1992; Milgroom
et al., 1996). For example, coffee leaf rust caused by the fungus Hemileia
vastatrix is the most destructive disease of coffee in the world (Lucas
et al., 1992). Urediniospores from infected and fallen coffee leaves are
easily spread by wind or rain. Fig. 17 shows the symptoms of coffee
leaf rust that include the appearance of orange-yellow powdery spots
and early defoliation (Carvalho et al., 2011; Lucas et al., 1992).
Various major infectious diseases of humans and animals, like
anthrax, foot-and-mouth disease, tuberculosis, Legionnaire's disease,
influenza, and measles could be spread by airborne bacteria or viruses
(Arzt et al., 2011; Langer et al., 2012; Riley, 1974; Shafazand
et al., 1999). The inhalation of pathogenic viable airborne fungi,
like Aspergillus,Cryptococcus,andPneumocystis spp., into the lungs can
cause invasive infections associated with mortality rates of up to 95%
in infectedpopulations, especially in individuals with impaired immune
function (Brown et al., 2012; Lin et al., 2001; Yu et al., 2010). In partic-
ular, the spread of airborne pathogens within hospitals represents a
permanent health challenge in infection control (Hoffman et al., 1999;
Schaal, 1991). The transmission of pathogens and other bioaerosols
between humans has long been a topic of research as humans harbor
diverse microbes (including pathogens) in and on their bodies. Par-
ticularly in indoor environments, the presence and activities of
humans can influence bioaerosol concentration. The emission of par-
ticles by breathing, sneezing, coughing, talking, and movement, as
well as from resuspension of dust due to human activity, has been
the focus of numerous indoor bioaerosol studies (e.g., Adams et al.,
2015; Bhangar et al., 2014, 2015; Castillo et al., 2012; Hospodsky et al.,
2012; Meadow et al., 2014, 2015; Morawska, 2006; Nazaroff, 2015;
Noble, 1975; Qian et al., 2012, 2014; You, 2013). As discussed by
Bhangar et al. (2015), many studies have not differentiated between
direct emissions from the human body and resuspension of dust from
surfaces during human activity, thus providing only overall emission
rates. Chamber experiments offer a more controlled environment to
study direct human emission rates under varying conditions (Adams
et al., 2015; Bhangar et al., 2015; Hospodsky et al., 2012; Meadow
et al., 2015; Nazaroff, 2015; You, 2013). Recently, Bhangar et al.
(2015) found by measuring FBAPin a chamber study that approximate-
ly 10
6
human-associated particles are emitted into the surrounding air
per human and hour under seated conditions (Bhangar et al., 2015).
Other recent findings indicate that the microbial clouds released by
humans are personalized and can be traced back to particular individ-
uals (Meadow et al., 2015).
Different modeling strategies have been used to simulate the spread
of human, animal, and plant pathogens, focusing on risk assessment and
disease forecasting (Aylor, 2003; Davis, 1987; Isard et al., 2005; Van
361J. Fröhlich-Nowoisky et al. / Atmospheric Research 182 (2016) 346–376
Leuken et al., 2016; Yao et al., 1997). As suggested by Van Leuken et al.
(2016), risk assessment models simulating the dispersal of pathogens
need to be further improved by implementing well-quantified emission
and inactivation rates as well as dose–response functions to better esti-
mate infection probabilities.
Moreover, the inhalation and deposition of bioaerosols in various
regions of the respiratory system can cause allergic or toxic responses
in humans and animals. The deposition of inhaled particles in the respi-
ratory tract depends on particle properties, airway morphology, and
breathing characteristics (Hofmann, 2011; Hussain et al., 2011).
Fig. 18 shows thesize-dependent particledeposition in different regions
of the respiratory tract. Particles larger than 0.5 μm are deposited by
sedimentation and impaction mainly in the head airways. Particles
smaller than 0.5 μm can reach the lower airways by diffusion. A more
detailed description of particle deposition in the respiratory tract and
lung deposition modeling can be found in related reviews and refer-
ences therein (Hofmann, 2011; Hussain et al., 2011; Nazaroff, 2015).
Allergenic and toxic bioaerosols need not to be viable, as also dead
cells or cell fragments may provoke the same adverse health effects. Ex-
amples for biological toxins found in air particulate matter are cell wall
components of bacteria (endotoxins) or secondary metabolites pro-
duced by bacteria (exotoxins) or fungi (mycotoxins).
Exposure to mycotoxins after inhalation of mycotoxin-containing
particles, such as fungal spores, is particularly relevant in farm environ-
ments or water-damaged buildings (Hintikka and Nikulin, 1998; Mayer
et al., 2007; Nielsen, 2003; Robbins et al., 2000). Mycotoxins are a struc-
turally diverse group of mostly low-molecular-weight compounds that
have no apparent function in the fungal metabolism, but can have a va-
riety of acute and chronic health effects in humans and animals, as re-
cently reviewed by Ashiq et al. (2014);Edite Bezerra da Rocha et al.
(2014),andMarroquín-Cardona et al. (2014).
Bacterial endotoxins are lipopolysaccharides (LPS), which are com-
ponents of the outer cell membrane of gram-negative bacteria that
can be released during cell lysis. They are of particular interest as they
can induce strong inflammatory responses and symptoms like fever,
headache, coughing, and respiratory distress (Degobbi et al., 2011;
Douwes, 2003; Heederik and von Mutius, 2012; Longhin et al., 2013;
Ortiz-Martínez et al., 2015; Rylander, 2002; Soukup and Becker, 2001;
Vernooy et al., 2002). Elevated levels of endotoxins in air particulate
matter were found in indoor air (Gehring et al., 2002; Gereda et al.,
2000), in agriculture and related industries (Rylander, 2002; Spaan
et al., 2006), as part of PM10 (Cheng et al., 2012; Heinrich et al., 2003;
Morgenstern et al., 2005; Mueller-Annelling et al., 2004; Nilsson et al.,
2011; Traversi et al., 2011; Wheeler et al., 2011), connected to microbial
biomass (Woo et al., 2013), and to cyanobacteria and chlorophyll-a con-
centration (Lang-Yona et al., 2014).
In addition to LPS or endotoxin, bacteria can alsoproduce toxic sec-
ondary metabolites. These exotoxins are secreted by some bacterial
pathogens, such as some strains of Corynebacterium diphtheria (diph-
theria toxin) (Hadfield et al., 2000) and Bordetella pertussis (pertussis
toxin) (Mattoo and Cherry, 2005; Warfel et al., 2012), which can be
transmitted through the air. Moreover, of particular concern are toxins
produced by cyanobacteria. Cyanobacteria are widespread and abun-
dant organisms in terrestrial, as well as aquatic environments, which
produce neurotoxins, cytotoxins, dermatotoxins, and different types of
hepatotoxins (Codd et al., 1997, 1999; Cox et al., 2005; Kaasalainen
et al., 2012; Oberholster et al., 2004; Wiegand and Pflugmacher,
2005). Whereas neurotoxins inhibit neurotransmission by a variety of
mechanisms, frequently causing death of the exposed organisms,
hepatotoxins, comprising the cyclic peptide groups of microcystins
and nodularins as well as the cyclic guanidine alkaloid cylindrospermin,
are hepatotoxic, causing severe and sometimes toxic health effects in
domestic and wild animals as well as in humans (Codd et al., 1997,
1999). Both neurotoxins and hepatotoxins are produced by someaquat-
ic genera, as e.g. Anabaena,Oscillatoria,Microcystis,andAphanizomenon,
and hepatotoxins are also produced by a variety of terrestrial lichens
with cyanobacterial photobionts (Kaasalainen et al., 2012). Exposure
to cyanotoxins has been described to occur via skin contact, inhalation,
ingestion, and haemodialysis (Backer et al., 2010; Benson et al., 2005;
Codd et al., 1999; Wood and Dietrich, 2011).
One neurotoxin produced by cyanobacteria, β-methylamino-L-ala-
nine (BMAA), is suspected to contribute to human neurodegenerative
Fig. 17. Symptoms of coffee leaf rust Hemileia vastatrix: (A) defoliation,(B) leaf symptoms (bar = 0.5 cm), and (C) detail of suprastomatal uredinial pustules coalescing over lower leaf
surface (bar = 0.5 cm).
Adapted from Carvalho et al. (2011).
362 J. Fröhlich-Nowoisky et al. / Atmospheric Research 182 (2016) 346–376
diseases,as the same substance has been identified in the brain and ce-
rebrospinal fluid of amyotrophic lateral sclerosis (ALS) and Alzheimer's
disease victims (Cervantes Cianca et al., 2012; Field et al., 2013; Metcalf
and Codd, 2009) and has been shown to cause neuronal changes in an-
imal experiments (Karlsson et al., 2012; Okle et al., 2013; Zhou et al.,
2010). The neurotoxin BMAA is produced by free-living and symbiotic
cyanobacteria, diatoms, and dinoflagellates in marine, freshwater, and
terrestrial environments (Cervantes Cianca et al., 2012; Cox et al.,
2005; Jiang and Ilag, 2014; Jiang et al., 2014a, 2014b; Lage et al.,
2014). Uptake of BMAA has been suggested to happen via consumption
of contaminated food and exposure to water harboring cyanobacterial
blooms, as well as via aerosolization, which may happen in cooling
towers (Stommel et al., 2013).
Important sources of aeroallergens are wind-dispersed pollen from
trees, grasses, and weeds, fungal spores and hyphae, animal dander,
and house-dust mite excretions (Buters et al., 2015; D'Amato
et al., 2007; Esch et al., 2001; Green et al., 2003, 2005,2006, 2011;
Grinn-Gofrońand Rapiejko, 2009; Horner et al., 1995; Jochner
et al., 2015; Shiraiwa et al., 2012a; Twaroch et al., 2015; Vara
et al., 2016). Allergies and associated respiratory diseases represent a
Fig. 18. Deposition of inhaled particles: (A) human respiratory tract and (B) predicted total and regional particle deposition in relation to particle size, based on the International
Commission on Radiological Protection (ICRP) deposition model for nasal breathing and light exercise and deposition mechanisms. HA: head airways; TB: tracheobronchial region;
ALV: alveolar region.
(A) Reprinted from The Lancet 383, Guarnieri and Balmes (2014), copyright 2014, with permission from Elsevier.
363J. Fröhlich-Nowoisky et al. / Atmospheric Research 182 (2016) 346–376
serious health challenge of increasing importance in many countries
(D'Amato et al., 2007; Ring et al., 2001). Pollen allergies affect up to
40% of the population in industrialized countries and have become a
global problem (D'Amato et al., 2007; Shiraiwa et al., 2012a). Further-
more, up to 30% of atopic individuals are sensitized to one or more fun-
gal allergens (Esch et al., 2001).
A common type of allergy is mediated by the production of specific
IgE antibodies against otherwise harmless proteins, then called aller-
gens (Traidl-Hoffmann et al., 2009). Proteins account for up to 5% of
urban air particulate matter, and interactions of these proteins with
ozone, nitrogen dioxide, sulfur dioxide, and air particulate matter can
lead to modified proteins with modified allergenic potential (Franze
et al., 2005; Gruijthuijsen et al., 2006; Knox et al., 1997; Lang-Yona
et al., 2016; Shiraiwa et al., 2012a). Many studies have demonstrated
an increase in sensitization and allergic symptoms and correlations
with high levels of anthropogenic air pollution, but the underlying
mechanisms remain unclear (D'Amato, 2000; D'Amato et al., 2001,
2007, 2013; Gehring et al., 2010; Morgenstern et al., 2008).
The prevalence and severity ofallergic diseasesand asthma are likely
to increase further through anthropogenic air pollution and climate
change related factors. Effects of climate change on the physiology and
distribution of plants and fungi have been shown in several studies
(Cecchi et al., 2010; Reid and Gamble, 2009). For instance, increasing
temperature and CO
2
concentration can affect fungal fruiting patterns
and sporulation (Gange et al., 2007; Klironomos et al., 1997; Wolf
et al., 2010), pollen production and pollination periods in plants
(Zhang et al., 2014a, 2014b; Ziska and Caufield, 2000), the allergen con-
tent of spores and pollen (Lang-Yona et al., 2013; Singer et al., 2005),
and the distribution patterns of aeroallergens (Cecchi et al., 2010; Reid
and Gamble, 2009).
Moreover, both changes in climate and an intensification of land use
have been shown to cause an increase in dust storm frequency and in-
tensity (McLeman et al., 2014; Stanelle et al., 2014; Stocker et al.,
2013), and dust particles are known to carry biological and organic com-
ponents with pathogenic and allergenic properties (Chen et al., 2010;
Esmaeil et al., 2014; Goudie, 2014; Griffin, 2007; Hallar et al., 2011;
Kellogg and Griffin, 2006; Leski et al., 2011; Ortiz-Martínez et al.,
2015; Schlesinger et al., 2006) but possible synergistic effects of differ-
ent dust constituents on human health, the propagation of pathogenic-
ity along thedust event, and sources of health relevant PBA are still not
well characterized.
Anthropogenic air pollution, thunderstorms, and humidity have
been shown to influence allergen release from pollen and spores
(Behrendt and Becker, 2001; Behrendt et al., 1997; Buters et al., 2015;
Cecchi et al., 2010; Grote et al., 2001; Motta et al., 2006; Ouyang et al.,
2016; Schäppi et al., 1997). During a thunderstorm, pollen and spores
may break by osmotic shock and release allergens into the atmosphere
leading to asthma outbreaks known as thunderstorm asthma (Behrendt
and Becker, 2001; Cecchi et al., 2010; Laskin et al., 2016; Taylor and
Jonsson,2004; Taylor et al., 2002). Thunderstorms also favor an incr ease
of fungal spore counts, further contributing to asthma epidemics
(Behrendt and Becker, 2001; Cecchi et al., 2010; D'Amato et al., 2007).
Furthermore, under humid conditions pollen grains release proin-
flammatory substances (Bacsi et al., 2006; Behrendt and Becker,
2001; Miguel et al., 2006). The release of these substances was
found to be higher for pollen collected near roads with heavy traffic
(Behrendt and Becker, 2001). Free allergens and related compounds
can bind to fine particulate matter, such as diesel exhaust particles,
leading to the generation of allergen-containing aerosols in the
submicrometer range that can be transported deep into the airways
(Knox et al., 1997; Namork et al., 2006; Ormstad, 2000). Additionally,
traffic-related pollutants can also modify the immune system response
to the allergen itself. Diesel exhaust particles can modify allergen pre-
sentation, whereas gaseous pollutants like O
3
,SO
2
,andNO
2
can en-
hance immune system response by enhanced antibody production
and late inflammation (Saxon and Diaz-Sanchez, 2005). The impact of
air pollutants and environmental factors on PBA allergenicity still
needs to be better characterized. Especially, further investigation is
required in order to better understand the complex interactions of
modified allergens within the human body.
5. Future perspectives
Fig. 19 shows an overview of important and promising areas of fu-
ture research, which can be coarsely divided into the three main fields:
(1) bioparticle identification and characterization; (2) atmospheric
transport and transformation; and (3) ecosystem interactions of
bioaerosols. Studies within these fields could help to close or narrow
the large gaps of knowledge outlined in this review and toconstrain un-
certain parameters and assumptions, which will allow to improve
modeling of the effects of bioaerosols on climate, health, and ecosys-
tems on local, regional, and global scales.
(1) For comprehensive taxonomic and chemical identification,
characterization, and quantification of bioaerosol particles, their
viability and metabolic state, the wide range of advanced and in-
novative online and offline measurement methods outlined in
Sect. 2 should be applied and further developed (NGS sequenc-
ing, fluorescence detection, etc.). An important aspect is the cou-
pling of detailed biological analyses and information with the
real-time data of modern physical and chemical techniques, in-
cluding genomic, proteomic, and metabolomic approaches. The
development and application of standardized sampling andanal-
ysis techniques appears necessary to achieve consistency be-
tween different measurements and datasets.
(2) To understand the spatial and temporal dynamicsof atmospheric
bioaerosols, the pathways of emission, transport, and transfor-
mation in the atmosphere need to be analyzed from molecular
to global scales. Major challenges include the quantitative char-
acterization of exchange between surface, planetary boundary
layer, and free troposphere. For this purpose, ground based
measurements have to be combined with tall tower and aircraft
measurements as well with satellite remote sensing to obtain
information on the vertical and horizontal distribution of
bioparticles. Particularly interesting are the distribution patterns
of IN-active microorganisms and detached nanometer-sized IN-
active particle fragments and macromolecules (also called
“nano-INP”or “INM”), and their interactions with clouds and
precipitation. These have to be elucidated on microscopic as
well as regional and global scales to validate or discard the
bioprecipitation feedback hypothesis and its relevance for
the Earth system (Sect. 3.3). Other important aspects are the
effects of physical, chemical, and biological transformation,
aging, and stress upon exposure to atmospheric oxidants, ra-
diation, and changes of temperature, pressure, and humidity
(osmotic shock) on the emission, vitality, and viability of air-
borne bioparticles. These effects need to be quantified in
chamber and field studies under relevant conditions to fully
understand the impact of atmospheric transport on the adapta-
tion and resilience of aerially disseminated organisms (wind-
pollinated plants, sporulating microbes) and their influence on
the functioning of ecosystems.
(3) Representative measurements and climatologies of bioaerosols
in and above ecosystems along the climatic gradients from
tropical to polar and continental to marine regions are re-
quired to unravel the interdependence of biodiversity and
biogeography in the air and at the Earth surface, as well as
the impact of environmental conditions, climate, and land
use change on bioaerosol emission and deposition, related
biogeochemical cycles, and public health. Key aspects are the
roles of cryptogamic covers on ground and plant surfaces, nitro-
gen cycling microbes, and bioprecipitation feedbacks in the co-
364 J. Fröhlich-Nowoisky et al. / Atmospheric Research 182 (2016) 346–376
evolution of life and climate, as well as the spread and effects of
pathogens and allergens interacting with air pollutants. To ad-
dress these issues, the results of comprehensive observations
and bioaerosol monitoring in today's atmosphere (e.g., by NGS
sequencing, fluorescence detection, and chemical analysis)
should be compared and combined with climate archive analy-
ses (e.g., pollen, spores, biomarkers, and DNA in lake and ocean
sediments) and implemented in ecosystem and Earth system
models. Ecosystem and Earth system model descriptions and pa-
rameterizations of all bioaerosol properties and processes
outlined above are relevant for our understanding of the origins
and spread of life on Earthand for the modeling of ecosystem in-
teractions in Earth's history and future climate.
To tackle the wide range of open questions outlined above, it
will be necessary to further intensify collaboration and interdisciplinary
exchange across the fields of chemistry, Earth, and life science, in partic-
ular between the scientific communities of atmospheric chemistry and
physics, climate and aerosol science, biogeochemistry and ecology, air
quality and public health, forestry and agriculture, and geo- and
bioinformatics.
Acknowledgements
The authors gratefully acknowledge stimulating scientific exchange
and discussions with numerous members of the scientificcommunity,
in particular with the colleagues involved in the referenced studies, on
which this review and perspective article is building, and with members
of the Mainz Bioaerosol Laboratory (MBAL). J.F.-N., U.P., and C.J.K ac-
knowledge support from the Deutsche Forschungsgemeinschaft (DFG
FR3641/1-2, FOR 1525 INUIT and KA 4008/1-1, respectively) and B.W.
and S.S.G. acknowledge support from the Max Planck Society (Nobel
Laureate Fellowship and MPG Partner Group, respectively). N.L.-Y.
acknowledges support from the Max Planck Society and from the Weiz-
mann Institute of Science - National Postdoctoral Award Program for
Advancing Women in Science. J.A.H. acknowledges internal support
from the University of Denver. S.M.B. acknowledges support fromthe
U.S. Department of Energy, Officeof Science Biological and Environmen-
tal Research Program.
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