SERIES B
CHEMICAL
AND PHYSICAL
METEOROLOGY
PUBLISHED BY THE INTERNATIONAL METEOROLOGICAL INSTITUTE IN STOCKHOLM
Primary biological aerosol particles in the atmosphere:
a review
By V I VI A N E R . DE S P R É S 1 * , J . A L E X H U F FM A N 2 , S U S A N N A H M. B U R R O W S 3 ,
C O R I N N A H O O S E 4 , A L E K S A N D R S. S A FA T O V 5 , GA L I N A B U R Y A K 5 ,
J A N I N E F R Ö H L I C H - N O W O I S K Y 3 , WO L F GA N G E L BE R T 3 , M E I N R A T O . A N D R E A E 3 ,
U L R I C H P Ö S CH L 3 a n d R U P R E C H T JA E N I C K E 6 *, 1Institute of General Botany, Johannes
Gutenberg University, Mainz, Germany; 2Department of Chemistry and Biochemistry, University of Denver,
Denver, CO, USA; 3Max Planck Institute for Chemistry, Mainz, Germany; 4Institute for Meteorology and
Climate Research, Karlsruhe Institute of Technology, Karlsruhe, Germany; 5Department of Biophysics and
Ecological Researches, State Research Center for Virology and Biotechnology, Vector, Koltsovo, Novosibirsk
Region, Russia; 6Institute for Physics of the Atmosphere, Johannes Gutenberg University, Mainz, Germany
(Manuscript received 19 July 2011; in final form 18 October 2011)
ABSTRACT
Atmospheric aerosol particles of biological origin are a very diverse group of biological materials and structures,
including microorganisms, dispersal units, fragments and excretions of biological organisms. In recent years, the
impact of biological aerosol particles on atmospheric processes has been studied with increasing intensity, and a
wealth of new information and insights has been gained. This review outlines the current knowledge on major
categories of primary biological aerosol particles (PBAP): bacteria and archaea, fungal spores and fragments,
pollen, viruses, algae and cyanobacteria, biological crusts and lichens and others like plant or animal fragments
and detritus. We give an overview of sampling methods and physical, chemical and biological techniques for
PBAP analysis (cultivation, microscopy, DNA/RNA analysis, chemical tracers, optical and mass spectrometry,
etc.). Moreover, we address and summarise the current understanding and open questions concerning the
influence of PBAP on the atmosphere and climate, i.e. their optical properties and their ability to act as ice nuclei
(IN) or cloud condensation nuclei (CCN). We suggest that the following research activities should be pursued in
future studies of atmospheric biological aerosol particles: (1) develop efficient and reliable analytical techniques
for the identification and quantification of PBAP; (2) apply advanced and standardised techniques to determine
the abundance and diversity of PBAP and their seasonal variation at regional and global scales (atmospheric
biogeography); (3) determine the emission rates, optical properties, IN and CCN activity of PBAP in field
measurements and laboratory experiments; (4) use field and laboratory data to constrain numerical models of
atmospheric transport, transformation and climate effects of PBAP.
Keywords: primary biological atmospheric aerosol, climate, cloud condensation nuclei, biology, atmospheric ice
nuclei
Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
1.1. History . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
1.2. Definition and sources of primary biological aerosol particles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
*Corresponding authors.
email: despres@uni-mainz.de; jaenicke@uni-mainz.de
Tellus B 2012. # 2012 V. R. Després et al. This is an Open Access article distributed under the terms of the Creative Commons Attribution-Noncommercial 3.0
Unported License (http://creativecommons.org/licenses/by-nc/3.0/), permitting all non-commercial use, distribution, and reproduction in any medium, provided
the original work is properly cited.
Citation: Tellus B 2012, 64, 015598, DOI: 10.3402/tellusb.v64i0.15598
1
(page number not for citation purpose)
2
V. R. DESPRÉS ET AL.
2. Characteristic types of primary biological aerosol particles . . . . . . . . . .
2.1. Bacteria and archaea . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2.1.1. Urban airborne bacteria . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2.1.2. Rural airborne bacteria . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2.1.3. Airborne bacteria at marine and coastal sites . . . . . . . . . . . . .
2.1.4. High altitude airborne bacteria . . . . . . . . . . . . . . . . . . . . . . .
2.1.5. Bacteria emission fluxes . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2.1.6. Archaea . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2.2. Fungal spores and fragments . . . . . . . . . . . . . . . . . . . . . . . . . .
2.3. Pollen . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2.4. Viruses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2.5. Algae and cyanobacteria . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2.6. Biological crusts and lichens . . . . . . . . . . . . . . . . . . . . . . . . . . .
2.7. Others . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2.8. Characteristic concentrations and emission estimates. . . . . . . . . .
3. Techniques for PBAP collection and analysis. . . . . . . . . . . . . . . . . . . .
3.1. PBAP sampling methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.2. Traditional analysis methods . . . . . . . . . . . . . . . . . . . . . . . . . .
3.2.1. Cultivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.2.2. Light microscopy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.2.3. Fluorescence microscopy. . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.3. Modern analysis methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.3.1. Molecular techniques . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.3.2. Optical methods. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.3.3. Non-optical methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
4. Atmospheric relevance. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
4.1. Atmospheric transport of biological particles . . . . . . . . . . . . . . .
4.2. PBAP as cloud condensation nuclei. . . . . . . . . . . . . . . . . . . . . .
4.3. PBAP as ice nuclei. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
4.3.1. Laboratory studies of ice nucleation active biological particles .
4.3.2. Observation of biological ice nuclei in the atmosphere. . . . . . .
4.3.3. Modeling of biological ice nuclei . . . . . . . . . . . . . . . . . . . . . .
4.4. Optical properties . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
5. Conclusions and outlook . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
1. Introduction
1.1. History
The occurrence and relevance of airborne biological
particles have been addressed since the beginnings of
scientific investigations into atmospheric aerosols (Ehrenberg, 1847; Pasteur, 1861; Carnelly et al., 1887; De Bary,
1887). For example, by the late nineteenth century, Miquel
(1883) had already shown that airborne spore concentrations in France followed a seasonal cycle and were
dependent on wind direction. He also showed that human
mortality in Paris followed the bacteria concentration in
the air. Since then, aerobiology (i.e. the study of airborne
biological particles) has become well established as a
multidisciplinary field of scientific research that interacts
with a host of physical, biological and medical science
disciplines (e.g. Gregory, 1973). The impact of aerobiology is especially notable in such diverse basic and
applied sciences such as allergology, bioclimatology,
palynology, biological pollution, biological warfare and
terrorism, mycology, biodiversity studies, ecology, plant
pathology, microbiology, indoor air quality, biological
weathering, industrial aerobiology and cultural heritage.
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The potential relevance of biological particles for atmospheric processes has also been recognised for many years
(e.g. Dingle, 1966; Schnell and Vali, 1972; Jaenicke and
Matthias, 1988; Matthias-Maser and Jaenicke, 1995;
Andreae and Crutzen, 1997; Jaenicke, 2005; Pöschl,
2005). Figure 1 outlines major processes in the cycling of
primary biological aerosol particles (PBAP)1 between
atmosphere and biosphere. After emission from the biosphere, PBAP undergo various physical and chemical aging
processes in the atmosphere (coagulation, surface coating,
reaction with photo-oxidants, etc.). Depending on their
surface properties, PBAP can serve as nuclei for water
droplets or ice crystals, leading to the formation of clouds
and precipitation. Removal from the atmosphere proceeds
via dry deposition (diffusion/sedimentation) or wet deposition with precipitation (nucleation/scavenging). After deposition, PBAP can interact with terrestrial or aquatic
ecosystems and trigger biological activities leading to
further PBAP emissions (growth and reproduction). However, biological particles in general have received less
1
A list of abbreviations can be found in the appendix.
PRIMARY BIOLOGICAL AEROSOL PARTICLES IN THE ATMOSPHERE
Fig. 1. Cycling and effects of primary biological aerosol particles
in the atmosphere and biosphere (adapted from Pöschl, 2005).
attention in atmospheric science than other types of aerosol
particles such as sulfate, sea salt, mineral dust or volcanic
ash (e.g. Junge, 1963; Hammond, 1971; Friedlander, 2000).
This is primarily because the atmospheric impact of
biological aerosols has been poorly understood, and
because atmospherically relevant measurements have been
costly and difficult to interpret. Also, global average
number concentrations of biological particles have often
been assumed to be insignificant compared to non-biological material and have thus not typically been considered
for widespread measurements or included in global climate
models. The Third Assessment Report (TAR) of the
Intergovernmental Panel on Climate Change (IPCC) in
2001, for example, listed the global source strength of
primary biological aerosol particles to be only 56 Tg/yr, in
contrast to 3340 Tg/yr for sea salt and 2150 Tg/yr for
mineral dust listed in the same report (Penner et al., 2001).
Furthermore, the Fourth Assessment Report of the IPCC
in 2007 stated that these estimates had not been refined,
and primary biological particles were not mentioned in the
contribution of Working Group I (Physical Science Basis)
to the overall report (IPCC 2007b). PBAP concentrations
have been estimated by other researchers (e.g. MatthiasMaser and Jaenicke, 1995) as comprising a much higher
percentage of total atmospheric aerosol volume, however,
and so important discrepancies exist.
Interest in biological aerosol has been growing significantly in recent decades. This is highlighted by the fact that
an Institute for Scientific Information (ISI) search for the
term ‘biological aerosol’ (including quotation marks) results
in less than a total of five publications until 1987, approximately one citation per year between 1987 and 1998, and then
steadily increasing numbers with an average of 9 citations
per year between 1998 and 2011. Recently, several investigations have suggested that biological particles can have a
substantial influence on clouds and precipitation and thus
may influence the hydrological cycle and climate at least on
regional scales (e.g. Andreae and Rosenfeld, 2008; Prenni
3
et al., 2009; Pöschl et al., 2010). Various fields of medical
research are also concerned with biological aerosols. Biological particles have been linked to many different adverse
health effects spanning from infectious diseases to acute toxic
effects, allergies, asthma and even cancer (Peccia et al.,
2011). The negative effects that bioaerosols can play on the
human respiratory system are particularly well documented
(Verhoeff and Burge, 1997; Burge and Rogers, 2000; Douwes
et al., 2003; Lee et al., 2005). Although medical research
dealing with biological aerosols is indeed critical, this review
article does not discuss medical applications of biological
aerosols directly, providing instead a synthesis and overview
of recent studies dealing with the observation and relevance
of primary biological aerosol particles in an atmospheric
context.
1.2. Definition and sources of primary biological
aerosol particles
Aerosols are generally defined as colloidal systems of liquid
or solid particles suspended in a gas (Hinds, 1999; Baron and
Willeke, 2001; Fuzzi et al., 2006). Particle diameters are
typically in the range of 1 nm to around 100 mm, where
the lower limit is given by the size of small molecular clusters
and the upper limit by high settling velocities comparable to
the magnitude of atmospheric updraft velocities (1 m s 1,
Hinds, 1999; Seinfeld and Pandis, 2006). Primary atmospheric aerosol particles are emitted directly into the atmosphere from a source material, whereas secondary particles
are formed in the atmosphere by condensation of gaseous
precursors (Pöschl, 2005; Fuzzi et al., 2006).
The term ‘primary biological aerosol particles’ is defined
to describe solid airborne particles derived from biological
organisms, including microorganisms and fragments of
biological materials such as plant debris and animal dander
(IGAP, 1992)2. The definition for PBAP used within the text,
as outlined in Table 1, can thus include all sorts of intact or
fragmented biological cells, dispersal units or tissues.
The term primary biological aerosol is more or less
equivalent to the ‘soft’ term ‘bioaerosol’ (Reponen et al.,
1995; Hinds, 1999). In contrast to the more rigorously
defined ‘biological aerosol’, however, the term ‘bioaerosol’
is not very clearly defined and is frequently used with
different meanings. In some cases, the term bioaerosol is
used in a rather narrow sense, excluding biological secretion such as plant wax particles, for example (Gelencér,
2004). In other cases, it is used in a very broad sense, e.g.
including any particle with biological activity/toxicity
2
Originally defined by Griffith, W. D.; Jaenicke, R.; Levin, Z.;
Matthias-Maser, S; Rantio-Lehtimaki, A.; Schnell, R. C.; and
Sinha, M. P.
4
V. R. DESPRÉS ET AL.
Table 1. Characteristic types of primary biological aerosol
particles (PBAP)
Particle types
Biological organisms or
dispersal units (dead or alive,
isolated or aggregated)
Solid fragments or excretions
of biological organisms or
dispersal units
Examples
Bacteria, fungi, protozoa, algae,
spores, pollen, lichen, archaea,
viruses, etc.
Detritus, microbial fragments,
plant debris/leaf litter, animal
tissue and excrements,
brochosomes, etc.
(Hirst, 1995), which would theoretically also comprise
droplets of toxic chemicals such as sulphuric or nitric
acid. Moreover, the term primary biological aerosol
enables clear and easy distinction from biogenic secondary
organic aerosols that are formed by atmospheric oxidation
and gas-to-particle conversion of volatile organic compounds released from biological organisms (Hallquist
et al., 2009; Jimenez et al., 2009). Therefore, we use the
term biological aerosol within this review for the types of
particles outlined in Table 1.
The size of PBAP can range from several nanometers
(e.g. viruses, cell fragments) to a few hundred micrometres
in aerodynamic diameter (e.g. pollen, plant debris; Cox and
Wathes, 1995; Hinds, 1999; Jaenicke, 2005; Pöschl, 2005).
Larger particles of biological material can also be lifted
into the air, but due to high settling velocities they are
rapidly deposited rather than being suspended over long
times. Thus, they are usually not considered to be atmospheric aerosol particles, which is also the case for selfpropelled organisms.
The biosphere, or the system in which all living things
interact, dominates the Earth’s surface, influencing the
composition of land, water and air. Thus, PBAP can be
released, both actively and passively, from every region of the
globe. Key PBAP-producing systems include the following.
Plants release PBAP in the course of decay processes (see
Section 2.7) as well as for reproduction, including pollen
from higher plants and spores from ferns and mosses (see
Section 2.3).
Microorganisms inhabit most plant, soil and rock
surfaces (see Sections 2.1, 2.2, 2.5, 2.6). These microorganisms can be very numerous, contributing huge number
concentrations per unit surface area (104 108 cells cm 2)
in various natural environments (Morris and Kinkel, 2002;
Lindow and Brandl, 2003; Yadav et al., 2004). Furthermore, the global leaf surface area is estimated to be roughly
four times the terrestrial ground surface area ( 6.4 108
km2 vs. 1.5 108 km2) that provides a correspondingly
large surface area for PBAP emission (Whittaker and
Likens, 1973).
Primary biological aerosol particles originating from
animals and humans include debris from skin or hair as
well as, for example, excrements, brochosomes and eggs
dispersed into the atmosphere by insects (see Section 2.7).
In areas of human activity, such as cities or agricultural
managed areas, the numbers and composition of microorganisms such as bacteria or fungi are often increased
and altered with respect to rural areas (see Sections 2.1.1,
2.2).
The cryosphere (e.g. Greenland, Antarctica, glaciers) is
formed largely from precipitation, and this may be
triggered by PBAP in some situations (Sands et al., 1982;
Christner et al., 2008b; Pöschl et al., 2010). Bacteria have
been discovered in ice cores from Antarctica at depths up
to 3519 m (Raymond et al., 2008), giving possible evidence
to the idea that these organisms have been introduced
through precipitation. Thus, surface snow under windblown conditions could be a powerful source for PBAP via
resuspension (Pomeroy and Jones, 1996).
Roughly, 70% of the globe is covered by oceans. They
are full of living and decaying organisms, such as bacteria,
archaea, fungi and algae, that are ejected from the ocean
surface by bubble-bursting mechanisms, similar to the way
other particles (e.g. sea salt) are emitted from such surfaces (Blanchard, 1983; O’Dowd et al., 2004).
In summary, the earth’s biosphere provides many diverse
and important sources of PBAP. We begin this review by
discussing seven major categories of atmospherically relevant biological particles in detail. This is followed by a
survey of available methods for PBAP detection and
analysis, and overviews of the general atmospheric relevance of PBAP and their optical properties.
2. Characteristic types of primary biological
aerosol particles
2.1. Bacteria and archaea
Due to their small size, bacteria have a relatively long
atmospheric residence time (on the order of several days or
more) compared to larger particles and can be transported
over long distances (up to thousands of kilometres).
Measurements show that mean concentrations in ambient
air can be greater than 1 104 cells m 3 over land (Bauer
et al., 2002a), whereas concentrations over the sea may be
lower by a factor of 100 1000 (Prospero et al., 2005;
Griffin et al., 2006). Airborne bacteria may be suspended
as individual cells but are more likely to be attached to
other particles, such as soil or leaf fragments, or found
as agglomerates of many bacterial cells (Bovallius et al.,
1978; Lighthart, 1997). For this reason, whereas individual
bacteria are typically on the order of 1 mm or less in size,
the median aerodynamic diameter of particles containing
PRIMARY BIOLOGICAL AEROSOL PARTICLES IN THE ATMOSPHERE
5
culturable bacteria at several continental sites has been
reported to be 4 mm, whereas at coastal sites it is 2 mm
(Shaffer and Lighthart, 1997; Tong and Lighthart, 1999;
Wang et al., 2007).
The analysis of the diversity, composition and abundance of bacteria in air has experienced a recent growth in
interest within the aerosol community (Morris et al., 2011).
Understanding of the presence or properties of airborne
bacteria is important because bacteria can influence atmospheric processes, function as human, plant and animal
pathogens and be distributed over large physical scales
from their natural or anthropogenic sources. In addition,
the prediction of behavioural changes in bacterial colonisation of remote environments may be linked to climatic or
anthropogenic changes that influence the atmosphere and
thus could be a useful marker of changes in biodiversity.
Although in recent years, research on bacteria in the
atmosphere has been constantly expanding, it remains
difficult to establish a clear picture of the actual abundance
and composition of bacteria in the air (Mancinelli and
Shulls, 1978; Grinshpun and Clark, 2005; Maki et al.,
2010). The presence of bacteria in air is strongly dependent
on many factors such as seasonality, meteorological
factors, anthropogenic influence, variability of bacterial
sources and many other complicated variables. More
importantly, the analysis of airborne bacteria still suffers
from a lack of standardisation in air sampling and sample
processing methods (Kuske, 2006; Peccia and Hernandez,
2006; Womack et al., 2010). Thus, differences in airborne
concentration estimates, as well as in composition and
abundance, could either be caused by biological variations
or by differences in sampling or analysis strategies.
Furthermore, many airborne bacteria studies were not
designed to study a broad range of species but only to
detect specific, and often pathogenic, species. Thus, current
understanding of airborne bacteria concentrations and
properties is undoubtedly influenced by such studies, and
the literature should be understood with this in mind.
One area of expanding research is work towards the use
of specific bacterial species for ‘source tracking’, conceptually similar to other atmospheric tracer methods. For
example, the relative contribution of bacteria from various
source environments can be determined, thus allowing
measurements at an individual measurement site to predict
the history of the air arriving at that location. Bowers et al.
(2010) made a contribution in this direction by identifying
groups of bacteria in atmospheric samples, which are
typically found primarily in the soil or on leaf-surface
environments.
has focused mostly on the comparison of bacterial concentration and not on diversity estimates. Historically,
bacteria have typically been divided into Gram-positive
and Gram-negative bacteria depending on their behaviour
when their cell walls are treated by Gram staining.
Culturing methods in general find more Gram-positive
bacteria (e.g. Mancinelli and Shulls, 1978; Atlas and
Bartha, 1997; Atlas and Bartha, 1997; Fuzzi et al., 1997;
Kellogg and Griffin, 2006; Amato et al., 2007b; Fang et al.,
2007; Fahlgren et al., 2010), whereas culture-independent
techniques primarily find Gram-negative bacteria (e.g.
Radosevich et al., 2002; Maron et al., 2005; Brodie et al.,
2007; Després et al., 2007; Fierer et al., 2008; Fahlgren
et al., 2010). Independent of the choice of detection
method, several general trends can be observed from
ambient measurements. A small number of existing studies
suggest that both in urban and in natural areas, airborne
bacterial communities are highly diverse, and variations in
their species diversity are more complex than had previously been supposed (Bovallius et al., 1978; Jones and
Cookson, 1983; Chihara and Someya, 1989). Bacterial
diversity in rural areas is generally higher than at urban
sites (Després et al., 2007). Still, the concentration of
bacteria seems often to be higher in urban than in rural
environments (Bovallius et al., 1978; Chihara and Someya,
1989; di Giorgio et al., 1996; Shaffer and Lighthart, 1997;
Fang et al., 2007; Fahlgren et al., 2010), even when the
samples are taken in the same geographic region. However,
opposite trends have also been found: For example, Rosas
et al. (1993) described that bacterial concentrations in rural
environments are higher than in urban sites. There is also
evidence that the bacterial concentrations in the urban
environment are influenced by human activities (Bovallius
et al., 1978; Fang et al., 2007). Different cities do vary in
their bacterial composition and abundance (Brodie et al.,
2007); thus, there can be no single, typical description of
urban bacterial composition.
A detailed description of the composition of bacteria
found in urban air is restricted to only a few studies, as
most culture-based studies classify cultured bacteria only as
Gram positive or Gram negative, or as cocci or rods but do
not provide taxonomic identification. Other studies dealing
with the analysis of urban airborne bacteria give only the
number of colony forming units (CFU) or other concentration estimates and do not try to identify the bacteria at
all. Still, the general trend from available reports is that
bacteria found in the air often belong to groups that are
also common soil bacteria: on the taxonomic level of phyla,
the Firmicutes (Table 2),3 Proteobacteria, Actinobacteria
2.1.1. Urban airborne bacteria. The analysis and comparison of bacteria between urban and other environments
3
Table 2 provides an overview of all taxonomic terms used in the
review
6
Table 2.
Kingdom
Taxonomic information on biological particles in air mentioned in the review
Superphylum
Bacteria
Bacteria
Bacteria
Bacteria
Phylum
Firmicutes
Proteobacteria
Class
Order
Family
Bacilli
Bacillales
Bacillaceae
Alphaproteobacteria
Sphingomonadales Sphingomonadaceae
Betaproteobacteria
Gammaproteobacteria Pseudomonadales Pseudomonadaceae
Bacteria
Bacteria
Bacteria
Bacteria
Bacteria
Bacteria
Moraxellaceae
Enterobacteriales
Enterobacteriaceae
Bacteria
Bacteria
Bacteria
Bacteria
Bacteria
Bacteria
Bacteria
Bacteria
Bacillus subtilis
Sphingomonas echinoides
Pseudomonas
Pseudomonas syringae
(which is also the main
component of Snomax)
Pseudomonas fluorescens
Pseudomonas viridiflava
Pseudomonas antarctica
Acinetobacter
Psychrobacter
Pantoea
Xanthomonadaceae
Flavobacteriales
Chroococcales
Nostocales
Oscillatoriales
Oscillatoriales
Oscillatoriales
Flavobacteriaceae
Escherichia
Xanthomonas
Luteimonas
Stenotrophomonas
Pantoea agglomerans
(formally called
Enterobacter
agglomeransor Erwinia
herbicola)
Pectobacterium
carotovorum (formally
called Erwinia carotovora)
Escherichia coli
Deltaproteobacteria
Epsilonproteobacteria
Chlamydiae/
Verrucomicrobia
group
Bacteroidetes/
Chlorophobi
group
Verrucomicrobia
Bacteroidetes
Bacteroidia
Flavobacteria
Bacteria
Bacteria
Bacteria
Bacteria
Bacteria
Bacillus
Sphingomonas
Pectobacterium
Xanthomonadales
Species
Cyanobacteria
Cyanobacteria
Cyanobacteria
Cyanobacteria
Cyanobacteria
Nostocaceae
Phormidiaceae
Flavobacterium
Chroococcus
Nostoc
Lyngbya
Phormidium
Schizothrix
Chroococcus limenticus
Nostoc Muscorum
Lyngbya lagerheinii
Phormidium fragile
Schizothrix purpurascens
V. R. DESPRÉS ET AL.
Bacteria
Genus
Table 2 (Continued )
Kingdom
Bacteria
Superphylum
Fibrobacteres/
Acidobacteria
group
Phylum
Class
Order
Family
Genus
Species
Acidobacteria
Planctomycetes
Chlorophlexi
Actinobacteria
Actinobacteria
Actinomycetales
Microbacteriaceae
Micrococcaceae
Pseudonocardiaceae
Streptomycetaceae
Microbacterium
Arthrobacter
Arthrobacter agilis
Saccharomonospora Saccharomonospora viridis
Streptomyces
Streptomyces albus
Fungi
Fungi
Basidiomycota
Ascomycota
Dothideomycetes
Capnodiales
Davidiellaceae
Cladosporium
Eurotiomycetes
Eurotiales
Trichocomaceae
Penicillium
Fungi
Fungi
Fungi
Fungi
Fungi
Fungi
Fungi
Fungi
Fungi
Fungi
Fungi
Fungi
Fungi
Fungi
Fungi
Fungi
Fungi
Fungi
Aspergillus
Leotiomycetes
Sordariomycetes
Fungi
ZygomycotaSubphylum:
Mucoromycotina
Zygomycetes
Plantae
Plantae
Chlorophyta
Pinophyta
Angiospermae
Chlorophyceae
Pinopsida
Erysiphales
Hypocreales
Erysiphaceae
Nectriaceae
Paecilomyces
Blumeria
Fusarium
Microascales
Microascaseae
Microascus
Mucorales
Mucoraceae
Rhizopus
Pinales
Asparagales
Pinaceae
Amaryllidaceae
Pinus (pine)
Narcissus
Cladosporium
cladosporioides
Cladosporium herbarum
Penicillium
brevicompactum
Penicillium chrysogenum
Penicillium digitatum
Penicillium frequentes
Penicillium melinii
Penicillium minioluteum
Penicillium notatum
Aspergillus flavus
Aspergillus fumigates
Aspergillus versicolor
Paecilomyces variotii
Fusarium avanaceum
Fusarium acuminatum
Fusarium oxysporum
Fusarium tricinctum
Microascus brevicaulis
(synonym: Scopulariopsis
brevicaulis)
Rhizopus stolonifera
PRIMARY BIOLOGICAL AEROSOL PARTICLES IN THE ATMOSPHERE
Bacteria
Bacteria
Bacteria
Bacteria
Bacteria
Bacteria
7
8
Table 2 (Continued )
Kingdom
Superphylum
Phylum
Class
Order
Family
Genus
Species
Asterales
Asteraceae
Ambrosia
Plantae
Caryophyllales
Ericales
Amaranthaceae
Theaceae
Amaranthus
Camellia
Plantae
Fagales
Betulaceae
Betula (birch)
Plantae
Plantae
Plantae
Plantae
Lamiales
Malpighiales
Fagaceae
Lamiaceae
Salicaceae
Alnus (alder)
Quercus (oak)
Salvia (sage)
Populus (poplar)
Plantae
Poales
Poaceae (true grasses)
Salix (willow)
Agrostis
Agrostis gigantea (red top
grass)
Poa pratensis (Kentucky
bluegrass)
Porphyridium aerugineum
Plantae
Rhodophyta
Porphyridiophyceae
Porphyridiales
Poaceae (true grasses), Poa
subfamily: Pooideae
Porphyridiaceae
Porphyridium
Camellia sinensis (Chinese
tea)
Betula occidentalis
(water birch)
Populus nigra ‘italica’
(Lombardy poplar)
Protista
Protista /
Protozoa
Chromalveolata
Chromalveolata
Dinoflagellata
Dinophyceae
Peridiniales
Peridiniaceae
Cachonina
Seaweed
Cachonina Niei
Heterokontophyta
Heterokontophyta
Chrysophyceae
Xanthophyceae
Chromulinales
Chromulinaceae
Ochromonas
Ochromonus danica
Archaea
Crenarchaeota
V. R. DESPRÉS ET AL.
Plantae
Ambrosia artemisiifolia
(common ragweed)
PRIMARY BIOLOGICAL AEROSOL PARTICLES IN THE ATMOSPHERE
are often present, and on the level of superphyla the
Cytophaga-Flavo-Bacteroidetes group is often being the
most commonly observed. Additionally, in some studies
bacteria from the phyla of Verrucomicrobia, Cyanobacteria,
Acidobacteria, Planctomycetes and Chloroflexi have been
detected. Within the airborne bacteria whose classes belong
to Proteobacteria, Gamma- and Betaproteobacteria have
been regularly identified, but Alpha-, Delta- and
Epsilonproteobacteria have also been observed. Although
Bacilli have been found often and in high numbers,
drawing conclusions from these observations about their
relative abundance is difficult due to high short-term
variability and biases from the different detection methods.
Concentrations of bacteria in cities exhibit especially
high spatial variation because they are released from strong
point sources, in contrast to the more spatially homogeneous release from, for example, an agricultural field.
Areas with heavy vehicular traffic or sewage pollution have
much higher concentrations of airborne bacteria, with a
weaker or non-existent seasonal cycle, as compared to
concentrations in more naturally influenced areas such as
urban parks, forests or coastal sites (e.g. Miquel, 1883;
Shaffer and Lighthart, 1997; Harrison et al., 2005; Fang
et al., 2007).
The concentrations and composition of bacteria undergo
daily, weekly and seasonal changes. It has often been found
that numbers are greatest in summer and autumn (Bovallius et al., 1978; Jones and Cookson, 1983; di Giorgio
et al., 1996; Tong and Lighthart, 1999; Fang et al., 2007;
Kaarkainen et al., 2008), although exceptions exist; Fahlgren et al. (2010) found that bacteria counts at a coastal site
were highest in winter, which they attributed to a strong
winter marine sea spray source. Over a period of 1 d,
bacteria have usually been observed to exhibit a peak
airborne concentration in the morning and evening (Lighthart and Shaffer, 1995; Shaffer and Lighthart, 1997; Fang
et al., 2007). It has been suggested by Maron et al. (2006)
that bacterial communities in cities show temporal variability, in which the daily and weekly variability is mainly
influenced by anthropogenic sources, whereas seasonal
variations are triggered by climate and atmospheric
changes.
2.1.2. Rural airborne bacteria. Among the Gram-positive
bacteria observed in rural air, Firmicutes and
Actinobacteria are the prevalent groups, whereas
Proteobacteria are the most prevalent Gram-negative
bacteria (e.g. Lighthart, 1997; Maron et al., 2005; Després
et al., 2007; Fang et al., 2007). Rural and urban sampling
sites usually differ with regard to bacterial genetic diversity.
Studies based on cultivation often find higher counts of
CFUs at urban sites compared to rural sites in the same
9
geographic regions (Bovallius et al., 1978; Jones and
Cookson, 1983; Chihara and Someya, 1989; di Giorgio
et al., 1996; Fang et al., 2007; Fahlgren et al., 2010). In
contrast, some studies based on cultivation or deoxyribonucleic acid (DNA) analysis have detected higher diversity
at rural than at urban sites (Rosas et al., 1993; Després
et al., 2007). Some studies have shown strong correlations
between bacteria concentrations at rural sites and meteorological conditions. For example, Lighthart et al. (2009)
found that six meteorological factors could account for
96% of the variance in culturable atmospheric bacteria
concentrations measured in rural Oregon. Harrison et al.
(2005) measured boundary layer concentrations of total
atmospheric bacteria at sites in England and found that
they increased exponentially as a function of 24-h mean
temperature and, except at the coastal site, decreased
logarithmically with increasing wind speed, probably due
to atmospheric dilution.
Shaffer and Lighthart (1997) found that mean concentrations of culturable bacteria differed between four
distinct land-use types chosen for study: urban, forest,
rural and coastal. However, Bowers et al. (2010) obtained
an apparently contradictory result, finding concentrations
to be 105 106 m 3 of air in each of three distinct land-use
types (agricultural fields, suburban areas and forests). The
difference could be related to the specific sites chosen, or
could be methodological; whereas Shaffer and Lighthart
(1997) used cultivation to enumerate bacteria, Bowers et al.
(2010) used fluorescent microscopy to count DNA-containing particles in the size range 0.5 10 mm in diameter.
Despite the lack of difference in total bacteria numbers
between the sites, Bowers et al. (2010) found that concentrations of high-temperature ice nuclei, as determined by a
droplet freezing assay, were on average two and eight times
higher in the samples from agricultural areas than from the
other two land-use types, which might indicate an agricultural, perhaps biological, source of ice nuclei, but the
nature of the ice nuclei was not determined.
2.1.3. Airborne bacteria at marine and coastal sites.
Although it has often been shown that airborne bacteria
are dominated by bacterial groups that are prevalent in the
soil, airborne bacteria, especially at marine and coastal
sites, can also originate from marine sources. Bacteria are
transmitted from water to the air by the bubble-bursting
mechanism (e.g. Blanchard et al., 1981; Blanchard and
Syzdek, 1982). Both, laboratory and field studies, have
demonstrated that the concentration of bacteria in bubble
bursting or sea spray aerosol greatly exceeds the concentration in the water from which the aerosol is produced
(Blanchard and Syzdek, 1978; Blanchard et al., 1981;
Blanchard and Syzdek, 1982; Blanchard, 1989; Marks
10
V. R. DESPRÉS ET AL.
et al., 2001; Aller et al., 2005). The mean atmospheric
residence time of bacteria emitted from the oceans is
expected to be shorter than for bacteria emitted from
land surface due to their quicker removal by precipitation
(Burrows et al., 2009b). In comparison with bacterial
concentrations in urban and rural environments, CFU
counts seem to be in general lower at coastal sites than at
inland sites (Bovallius et al., 1978; Shaffer and Lighthart,
1997). Variation in bacterial concentrations over the course
of a day can often be explained by considering onshore
breezes that generally bring air with fewer bacteria than
inland air (Lighthart, 1997).
Most of the studies dealing with the identification of
airborne bacteria at marine and coastal sites have been
conducted using culture-dependent techniques. However,
it has also been shown in culture-independent analyses
that bacteria at coastal and marine sites primarily stem
from the phyla of the Proteobacteria, Firmicutes and
Bacteroidetes. Within the Firmicutes, Bacillus seems to
be prevalent (Shaffer and Lighthart, 1997), whereas within
Proteobacteria mainly Alpha-, Beta- and Gammaproteobacteria were detected (Fahlgren et al., 2010; Urbano et al.,
2011).
Although in general it has been reported that the
concentration of bacteria is highest in summer and autumn,
while lowest in winter (Vlodavets and Mats, 1958; Pady
and Gregory, 1963; Borodulin et al., 2005), local exceptions can be found to this pattern. In a study analysing the
airborne bacterial community at a sampling site near the
Baltic Sea with mainly marine influenced air, Fahlgren
et al., (2010) detected higher CFU values during the winter
compared with the summer. Because marine bacteria are
ejected into the air along with sea spray aerosol particles,
the source of marine bacteria to the atmosphere increases
when winds become more powerful, generating more waves
and surf, and thus sea spray. As a result, it is likely that
marine bacteria are transferred to the atmosphere far more
effectively by stronger winter winds (Nilsson et al., 2001;
Nilsson et al., 2007; Fahlgren et al., 2010).
Examination of single particles collected in the air above
biologically active ocean areas (Arctic and Southern) shows
that bacteria are present, but their numbers are dwarfed by
the large number of particles consisting of biogenic organic
aggregates and colloids (Leck and Bigg, 2005a, 2005b;
Bigg, 2007; Bigg and Leck, 2008).
Methodological issues may have confounded previous
measurements of bacteria concentrations in marine air
using culture methods. The culturability of bacteria in
seawater is estimated to be between 0.001 and 0.1%,
compared to 0.25% for freshwater and 0.3% for soil
(Colwell, 2000). However, Fahlgren et al. (2010) presented
evidence that a majority of live airborne marine bacteria
collected on the Swedish coast may be culturable on Zobell
agar plates, which are based on Baltic seawater. Also,
marine bacteria are smaller than land bacteria, with
biovolumes often in the range 0.036 0.073 mm3 (Lee and
Fuhrman, 1987), corresponding to equivalent spherical
diameters of 0.20 0.26 mm. Consistent with the smaller
size of marine bacteria, the count median diameter of
particles associated with culturable bacteria has been found
to be smaller at coastal sites about 2 mm compared to
about 4 mm at continental sites (Shaffer and Lighthart,
1997; Tong and Lighthart, 2000; Wang et al., 2007).
2.1.4. High altitude airborne bacteria. The presence of
bacteria at high altitudes in the atmosphere had already
been detected as early as 1861 (Pasteur, 1861). Metabolically active microbes have been detected in air as high
as 2070 km in elevation (Imshenetsky et al., 1978;
Griffin, 2004; Wainwright et al., 2004a; Bowers et al.,
2009; Womack et al., 2010). Bacteria have been shown to
survive long distance transport and also to be able to live
and reproduce in airborne particles (Dimmick et al., 1979).
Because bacteria metabolise within cloud droplets, some
authors have proposed an impact on the chemistry of cloud
droplets and air (Amato et al., 2005, 2007a, 2007c;
Deguillaume et al., 2008; Vaitilingom et al., 2010). Vaitilingom et al. (2010) showed that biodegradation is more
likely to contribute to cloud chemistry at night than during
the day because it must compete with photochemistry
during the day. Bacteria collected in cloud water samples
have been shown to metabolise and reproduce when those
samples are incubated in the laboratory, even at supercooled conditions (Sattler et al., 2001; Amato et al., 2007a;
Amato et al., 2007c). Sattler et al. (2001) found that
generation times varied between 3.6 and 19.5 d, comparable to those of phytoplankton in the ocean. The mean
atmospheric residence time of a bacterial cell can be up to
about 1 week (Burrows et al., 2009b), but the cell will spend
only a small fraction of this time inside of a cloud droplet.
Lelieveld and Heintzenberg (1992) estimated that on
average, tropospheric air spends about 56% of its time
in clouds. It is, thus, unlikely that there is a significant
primary production of bacteria within cloud droplets.
In addition to the effect of low temperature at high
altitudes, it has been discussed repeatedly that air in general
is a hostile environment for microorganisms, as they are
exposed to UV light, have only small amounts of water
available are subject to changing oxygen partial pressure,
etc. (e.g. Womack et al., 2010 and references therein).
Bacteria found at high altitudes probably either originate
from high altitude habitats such as alpine sites, or they were
transported to high altitudes with air currents. Rapid
upwards transport of bacteria can be the result of storm
activity over land and seas, volcanic activity, impact events
PRIMARY BIOLOGICAL AEROSOL PARTICLES IN THE ATMOSPHERE
and human activity such as weapons testing, aviation and
spacecraft launches (Hall and Bruch, 1965; Bucker and
Horneck, 1969; Simkin and Siebert, 1994; Kring, 2000;
Griffin et al., 2002; Griffin, 2004). One evolutionary
strategy for bacteria to survive in such hostile environments
is the use of pigments to protect cells from harmful UV
radiation. Thus, some studies on the diversity of bacteria in
high altitude concentrate on pigmented bacteria (GonzálezToril et al., 2009).
The number of aerosol particles and PBAP decreases at
high altitudes in general, and several studies could show
that the diversity of airborne high-alpine bacteria is also
reduced in comparison to urban and rural sites (Després
et al., 2007; Bowers et al., 2009). These studies as well as
others find primarily bacteria belonging to Proteo- and
Actinobacteria as well as Bacteroidetes (González-Toril
et al., 2009). Within the Proteobacteria, Gamma- and
Betaproteobacteria are the prevalent classes detected. The
presence of Bacillus species has also been reported from
high altitude sites (Griffin, 2004; Maki et al., 2010).
Between the different environmental types, bacteria phyla
mainly differ in their relative proportions. Additional
differences probably exist also on the species and family
level.
2.1.5. Bacteria emission fluxes. Only a few studies have
attempted to directly measure the surface-atmosphere flux
(net rate of emission and deposition) of bacteria. Flux
measurements can be made using micrometeorological
methods that rely on measuring the vertical gradient of
bacteria concentrations in conjunction with gradients of air
11
velocity, temperature or other parameters. These methods
require fast and very short measurements for statistical
significance and can be difficult to design, carry out and
interpret. Existing estimates of the flux of culturable
bacteria to the atmosphere range from 4.7 CFU m 2 s 1
for a high desert chaparral in Oregon, USA (Lighthart and
Shaffer, 1994) to as much as 543 CFU m 2 s 1 for
undisturbed croplands (Lindemann et al., 1982) and much
stronger emissions for surfaces disturbed by human behaviour. For example, during harvesting of crops, emissions
may be as high as 109 CFU m 2 s 1 (Lighthart, 1984).
A first global model study estimates that average emissions
from land of 250 m 2 s 1 (range: 140380 m 2 s 1)
would be required to reproduce observed mean concentrations of bacteria in the air (Burrows et al., 2009b; Fig. 2),
note that this estimate refers to total as opposed to
culturable bacteria. Major obstacles to successful flux
measurements include low number concentrations of airborne bacteria and the lack of automated methods for
measuring concentrations because concentration measurements must be made continuously and at high time
resolution.
2.1.6. Archaea. All known life on earth can be categorised into one of three broad categories: archaea,
bacteria and eukarya. As with bacteria, the DNA of
archaea is not contained within a cell nucleus (prokaryotes). Little is known about archaea in the atmosphere.
They had long been thought to occur only in very
restricted, extreme environments, but by now they have
been found in a wide variety of habitats (Schleper et al.,
Fig. 2.
Column density of bacterial tracer (106 m 2), simulated from estimated emissions for a set of ten ecosystems estimates (Burrows
et al., 2009b).
12
V. R. DESPRÉS ET AL.
2005). They are one of the most diverse and widespread
forms of life on Earth and as major players in the
biogeochemical cycles of nitrogen and carbon they are
involved in the production of methane, the assimilation of
amino acids and the oxidation of ammonium (Schleper
et al., 2005). Archaea in the atmosphere have thus far been
difficult to detect and characterise. Many studies have
reported the detection of archaea from samples collected
from air above compost piles and biosolids (e.g. Baertsch
et al., 2007; Moletta et al., 2007; Thummes et al., 2007),
but these are specialised environments rich in biological
material. Three aerosol studies (Després et al., 2007; Fierer
et al., 2008; Bowers et al., 2009) utilised polymerase chain
reaction (PCR) primers capable of amplifying archaeal
DNA, but were unable to amplify and detect genetic
material from archaea. This may be due to limitations of
the applied PCR primers and amplification conditions as
described in Section 3.3.1.3. Radosevich et al. (2002) is the
only published report to successfully detect DNA sequences of three crenarchaeal clones from ambient air
but no further information is provided.
2.2. Fungal spores and fragments
Fungal spores and fragments are understood to be one of
the most common classes of airborne PBAP in a number of
environments (Womiloju et al., 2003; Elbert et al., 2007;
Bauer et al., 2008b; Crawford et al., 2009). Fungi are
comprised of vegetative mycelia that consist of a large
number of branched hyphae and grow in virtually every
ecosystem on Earth and are also capable of efficient
aerosolisation (Adhikari et al., 2009). Spores are often
released by active processes such as osmotic pressure
‘cannons’ and surface-tension catapults (e.g. Buller’s
Drop; Ingold, 1971; Lacey, 1996; Ingold, 1999; Pringle
et al., 2005). Spores can be released as a part of the sexual
and/or asexual morph (stage) of the lifecycle of a fungus,
and many species are able to produce spores from both
stages. Fungi that actively release spores during the sexual
morph, or telemorph, can typically produce one of three
different kinds of spores: ascospores are released from an
ascus (a long tube that typically holds eight spores),
basidiospores from a basidium (small pedestal on fruiting
bodies) or teliospores. The asexual stage, anamorph, of
some fungi produce conidia, also known as conidiospores,
that are produced by hyphal portions called conidiophores.
Many studies thus refer to spores as a singular class,
referring to both sexual and asexual morphs together.
Spores are also often subdivided for practical reasons into
hyaline (colorless) and dematiaceous (colored) spores (e.g.
Pady and Gregory, 1963; Adams et al., 1968). Spores most
commonly observed to dominate ambient concentrations
of airborne fungal material have been from the species:
Cladosporium, Alternaria, Penicillium, Aspergillus, as well
as Epicoccum and a variety of yeasts, smuts and rusts (plant
pathogens) and other basidiomycetes (e.g. Madelin, 1994).
Detailed reviews on fungal spores in the atmosphere are
available elsewhere (e.g. Madelin, 1994; Elbert et al., 2007)
and as an example Fig. 3 presents an example of fungal
spore micrographs with and without coating by secondary
organic aerosol. Some plants such as ferns and mosses also
disperse spores that are typically larger and less numerous
than fungal spores (Graham et al., 2003; Elbert et al.,
2007).
In recent PBAP analyses, molecular genetic methods
have been used that analyse the genetic substance, DNA, of
biological material. As discussed by Després et al. (2007),
fungal DNA detected in aerosol filter samples is most likely
to originate from spores that are known to resist environmental stress and survive atmospheric transport (Madelin,
1994; Griffin, 2004; Griffin and Kellogg, 2004). But, fungal
DNA may also be derived from other fungal material such
as hyphae and tissue fragments. Although it is generally
assumed that spores comprise the majority of airborne
Fig. 3. Fungal spores with and without coating by secondary organic aerosol (dark gray envelope in left panel). Electron micrographs of
aerosol filter samples from pristine tropical rainforest air in the Amazon (Pöschl et al., 2010), (Reproduced with permission from AAAS).
PRIMARY BIOLOGICAL AEROSOL PARTICLES IN THE ATMOSPHERE
fungal material, this remains largely unsubstantiated and
has important implications for interpretation of both,
laboratory or field measurements. Hyphal fragments have
been observed in ambient air in a number of studies (Gorny
et al., 2002; Green et al., 2006). Sinha and Kramer (1971)
suggested that airborne hyphae are most commonly
unbranched conidiophores that can be 1100 mm in length
but that are more commonly 540 mm. Pady and Gregory
(1963) summarise the observed concentrations to be within
the range 100 103 m 3 and observed that a large fraction
of ambient hyphae were viable and able to germinate
resulting in fungal colony growth. As most fungal species in
the biosphere are still unknown, the detection and characterisation of fungi in atmospheric aerosol samples by
DNA analysis can help to elucidate the global spread and
diversity of fungi. As a by-product of the active emission
process, fungal spores can be coated with specific sugar
(e.g. arabitol, mannitol) and sterol (e.g. ergosterol) compounds that have thus been utilised as chemical tracers for
ambient fungal spore concentrations (Lau et al., 2006;
13
Bauer et al., 2007). Spores can also be coated with
hydrophobin compounds that may affect both, their icenucleating ability (Iannone et al., 2011) and the immune
response they cause after human inhalation (Aimanianda
et al., 2009).
Depending on biological species, age and ambient
conditions, the diameter of fungal spores can vary (1
50 mm); most frequently it is in the range of 210 mm
(Elbert et al., 2007; Wang et al., 2008; Fröhlich-Nowoisky
et al., 2009; Huffman et al., 2010). Furthermore, fungal
spores are often observed to aggregate into long chains of
spores that greatly affect their aerodynamic diameter and
have implications for both, atmospheric lifetime and
deposition into human tissues (Lacey, 1991; Reponen
et al., 2001).
The number and mass concentrations of fungal spores are
typically observed to be 104 m 3 and 1 mg m 3,
respectively, in continental boundary layer air (Tables 3
and 4). They account for up to 10% of organic carbon
(OC) and 5% of PM10 at urban and suburban locations
Table 3. Global emission estimates for different types of PBAP and size ranges of air particulate matter (PMx, x upper limit of particle
diameter; TSP total suspended particulates)
Global emissions (Tg yr 1)
Bacteria
0.74 (0.41.8)
0.7
2.58
28.1
Fungal spores
Pollen
Total PBAP
Size range
Diameter: 1 mm (PM1)
Diameter: 1 mm (PM1)
Diameter: 1.17 mm
Lognormally distributed with geometric
mean number diameter: 2 mm, standard
deviation 1.37
8
Diameter: 4 mm (PM4)
28
Two size modes: fine ( B2.5 mm) and coarse
(2.510 mm) (PM10)
31
Diameter: 5 mm (PM5)
50
Diameter: 5 mm (PM5)
186
Lognormally distributed with geometric
mean number diameter: 3 mm, standard
deviation 1.37
47
Diameter: 30 mm (PM30)
84
Lognormally distributed with geometric
mean number diameter: 30 mm, standard
deviation 1.37
B10 (dominated by plant debris and
Diameter: 4 mm for fungal spores; diameter
fungal spores),
not specified for plant debris (TSP)
56 (090)
Diameter B2.5 mm (PM2.5)
78 (includes only bacteria, fungal spores Diameters as above (PM30)
and pollen)
186
Split equally into the two coarse size
fractions: 2.55 and 510 mm (PM10)
296 (includes only bacteria, fungal
Diameters as above
spores and pollen)
1000 (includes cellular fragments)
TSP
References
Burrows et al. (2009b)
Hoose et al. (2010a)
A. Sesartic, personal
communication
Jacobson and Streets (2009)
Sesartic and Dallafior (2011)
Heald and Spracklen, (2009)
Hoose et al. (2010a)
Elbert et al. (2007)
Jacobson and Streets (2009)
Hoose et al. (2010a)
Jacobson and Streets (2009)
Winiwarter et al. (2009)
Penner (1995)
Hoose et al. (2010a)
Mahowald et al. (2008)
Jacobson and Streets, (2009)
Jaenicke (2005)
14
Table 4.
V. R. DESPRÉS ET AL.
Characteristic magnitudes of the number and mass concentrations of PBAP in air over vegetated regions
Number
concentration
[m 3 air]
Bacteria
Plant debris (free cellulose)
Viral particles
Fungal spores
Fungal hyphal fragments
Pollen
Algae
Fern spores
10
4
104
103 104
103
10 (up to 103)
100 (up to 103)
10 (up to 103)
Mass concentration
[mg m 3]
Size range
0.1
0.11
10 3
0.11
PM10
PM10
1
10 3
1
TSP
(Bauer et al., 2002a, 2000b, 2008a). In pristine tropical
rainforest air, fungal spores account for up to 45% of
coarse particulate matter. Thus, the properties and effects of
fungal spores may be particularly important in tropical
regions where both, physico-chemical processes in the
atmosphere and biological activity at the Earth’s surface
are particularly intense (Graham et al., 2003; Gilbert, 2005;
Elbert et al., 2007; Pöschl et al., 2010; Zhang et al., 2010),
but chemical tracers typical of fungal spores have also been
reported in aerosols from semi-arid and arid sites (Graham
et al., 2004).
Most airborne fungi belong to the divisions of Ascomycota
and Basidiomycota (Fröhlich-Nowoisky et al., 2009). Most
Ascomycota and Basidiomycota actively eject their spores
with liquid jets or droplets (osmotic pressure and surface
tension effects), whereas others rely on dry spore detachment
by wind or other external forces. Dry-discharged spore
concentrations tend to be enhanced during warm,
dry weather conditions, whereas actively wet discharged
spores tend to be enhanced during humid conditions such as
those at night and in the early morning hours (Graham et al.,
2003; Elbert et al., 2007). Emission and dispersal of fungal
spores can thus be selectively correlated with various
meteorological parameters and usually have specific behaviours, depending on the species involved (Fitt et al., 1989;
Pasanen et al., 1991; Calderon et al., 1995; Katial et al.,
1997; Sabariego et al., 2000; Troutt and Levetin, 2001;
Burch and Leventin, 2002; Jones and Harrison, 2004;
Grinn-Gofron and Mika, 2008; Oliviera et al., 2009).
From spore counts and molecular tracers, Elbert et al.
(2007) derived a global emission rate of 50 Tg a 1 for
fungal spores, corresponding to average mass and number
emission fluxes of 23 ng m 2 s 1 and 200 m 2 s 1,
respectively, over land. These values are in fair agreement
with the global average model estimates of Heald and
Spracklen (2009): 28 Tg a 1 or 6 ng m 2 s 1 over
land, and 189 Tg a 1 calculated by Jacobson and Streets
(2009) for the year 2000. For Europe, Winiwater et al.
(2009) derived a value of 0.6 ng m 2 s 1, and recently
TSP
TSP
References
Bauer et al. (2002a); Burrows et al. (2009a)
Sánchez-Ochoa et al. (2007)
This work, Sect. 2.4
Elbert et al. (2007); Fröhlich-Nowoisky et al. (2009)
Pady and Gregory (1963)
Sofiev et al. (2006); Fröhlich-Nowoisky et al. (2009)
Reisser (2002)
Mücke and Lemmen (2008)
Sesartic and Dallafior (2011) estimated average mass and
number flux values of 17 ng m 2 s 1 and 513 m 2 s 1
over land. Overall, the studies indicate that the global
average emission rates of fungal spores are uncertain by
about one order of magnitude, which appears comparable
to many aerosol sources and less than for other types of
PBAP (Table 3). More field data are required to constrain
better the actual emission flux of fungal spores on regional
and global scales.
Studies based on DNA obtained directly from atmospheric aerosol samples offer new possibilities to identify
the origin of fungal matter, independent of viability,
cultivability and fragmentation (e.g. Boreson et al., 2004;
Peccia and Hernandez, 2006; Fierer et al., 2008; Bowers
et al., 2009; Fröhlich-Nowoisky et al., 2009). DNAbased techniques can amplify target regions of the DNA
extracted directly from atmospheric aerosol samples.
Amplification of the internal transcribed spacer (ITS)
regions between the 18S and 28S ribosomal ribonucleic
acid (rRNA) genes provides good target regions to identify
fungi to genus and often to species level (O’Brien et al.,
2005; Fröhlich-Nowoisky et al., 2009). DNA sequencing of
this region has proven to be an efficient tool for the
detection of rare and hard-to-cultivate fungi (e.g. Blumeria
graminis) as well as highly abundant and easy-to-cultivate
fungi (e.g. Cladosporium sp.) in aerosol samples (FröhlichNowoisky et al., 2009) and other habitats (e.g. Hunt et al.,
2004; O’Brien et al., 2005).
With regard to species richness, Fröhlich-Nowoisky et al.
(2009) detected 64% Basidiomycota and 34% Ascomycota
in a semi-urban environment in central Europe, whereas
Bowers et al. (2009) found only 4% Basidiomycota but 82
92% Ascomycota at a mountain site in North America. On
the class level within the Ascomycota, Dothideomycetes and
Eurotiomycetes seem to be the prevalent groups (Bowers
et al., 2009; Fröhlich-Nowoisky et al., 2009). These findings may be influenced not only by regional differences but
also by measurement issues, and the actual biogeographic
distribution of airborne fungal species is a subject of
PRIMARY BIOLOGICAL AEROSOL PARTICLES IN THE ATMOSPHERE
ongoing studies (Womack et al., 2010; Fröhlich-Nowoisky
et al., 2011). As in bacteria, seasonal variation exists and
differs between sampling sites also for fungi. During hot
summer seasons, a decrease in the airborne microflora was
reported for some fungi (Mullius et al., 1984; FilipelloMarchision et al., 1992; Fröhlich-Nowoisky et al., 2011).
The detection and apparent frequency of occurrence of
different species can be affected by technical factors such as
extraction efficiency of genomic DNA, varying rRNA gene
copy number in the species, primer matching and performance, amplification efficiency of the target region, and
cloning success. To our knowledge, from the few studies
that have reported DNA analyses of fungi in atmospheric
aerosol samples, some had neither found the expected high
abundance of, e.g. Cladosporium sp. nor a high species
richness (in particular Basidiomycota), which may well be
due to limitations of the applied PCR primers (e.g. Després
et al., 2007; Fierer et al., 2008; Bowers et al., 2009),
although over 1500 fungal DNA sequences from 5 urban
air samples were measured by Fierer et al. (2008) and
several dozens of filter samples of urban, rural and highalpine air were analysed by Després et al. (2007). Thus,
careful selection and combination of multiple PCR primer
pairs and other materials for the extraction and amplification of DNA obtained from aerosol samples are key
elements for achieving high coverage of species richness
(300 species), as discussed in Fröhlich-Nowoisky et al.
(2009). The high number of fungal species that were
detected only once indicates that a higher number of
samples and clones would have to be investigated for a
complete coverage of species diversity (Fröhlich-Nowoisky
et al., 2009). In any case, the detected and reported
numbers and frequencies of occurrence of species, families
and classes can only be taken as a lower limit for the actual
diversity and frequencies of occurrence.
2.3. Pollen
Among PBAP types, pollen grains can be among the largest
in physical size and represent the reproductive units of
plants that contain the male gamete. Pollen grains vary in
size between 10 and 100 mm, have various shapes and have
a hard shell that protects the sperm cells during the
transportation processes. Pollen grains occur as biological
aerosols not only as complete units but also as fragmented
pieces. Pollen can rupture when the humidity is high, and
these fragments have been shown to be in the range from
30 nm to 5 mm (Taylor et al., 2002, 2004; Miguel et al.,
2006). Pollen of anemophilous plants use wind as their
dispersal vector and have a typical diameter of 1758 mm
(Stanley and Linskins, 1974; Kuparinen, 2006; Nathan
et al., 2008; Pope, 2010). They are usually dispersed in large
amounts and over wide ranges because of their floating
15
ability (Straka, 1975). The pollen is often ejected in clumps
that stick to their neighbouring vegetation and are blown
away after drying (Jones and Harrison, 2004).
The ability of pollen to disperse into the atmosphere
depends on several parameters. On the one hand, dispersal
depends on resuspension as described in detail by Jones
and Harrison (2004). On the other hand, pollen dispersal
depends on meteorological factors. For example, bonding
of pollen to surfaces is affected by temperature and
moisture and thus by temperature and humidity of the air
(Jones and Harrison, 2004). It has also been shown that
pollen counts in, for example, the cypress family show
significant positive correlations with daily minimum, mean
and maximum temperatures and negative correlations with
precipitation (Lo and Levetin, 2007). After temperature
and humidity, wind and rain are typically the most
important parameters for pollen dispersal, and it has
been shown that pollen emission is reduced in the presence
of rain or when the wind speed was low (Ogden et al.,
1969). In general, the pollen concentration decreases with
height, and for birch it could be shown that at 2000 m
just 40% of the ground concentration were present
(Rempe, 1937). This general phenomenon can be modified
by inversion layers (Linskens and Jorge, 1986). The
horizontal distance over which pollen can be carried with
the wind can depend on prevailing temperatures, and it has
been suggested that an increase in air temperature may
induce atmospheric instability and thus promote pollen
dispersal (Kuparinen et al., 2009). However, pollen has
been observed to be lifted into the upper layers of the
atmosphere by convection (Monin and Obukhov, 1954;
Tackenberg, 2003; Taylor and Jonsson, 2004; Wright et al.,
2008), and this ability makes pollen grains possibly relevant
as ice nuclei in many environments.
The residence time of pollen in the atmosphere depends
on their settling velocities that depend on morphology
(shape), density and size of the pollen and vary widely
among pollen types (Digiovanni et al., 1995; Diehl et al.,
2001). The time pollen stay aloft in the atmosphere also
influences the horizontal distance they can travel. Long
distance dispersal (LDD) is not only interesting from the
atmospheric point of view but also shapes many fundamental processes in plant ecology and evolution (Ellstrand,
1992; Kawecki and Ebert, 2004; Neilson et al., 2005;
Nathan et al., 2008), e.g. the ability of plants to spread
into new areas (IPCC 2007a). Dust is well known to
frequently travel long distances, even across oceans (Kellogg and Griffin, 2006; Ben-Ami et al., 2010). Biological
particles can also be transported over similar distances and
have been observed to accompany dust plumes thousands
of miles from their assumed sources (Shinn et al., 2000;
Kellogg and Griffin, 2006; Polymenakou et al., 2008;
Hallar et al., 2011). The LDD of wind-dispersed pollen is
16
V. R. DESPRÉS ET AL.
typically promoted by turbulent vertical fluctuations in
wind and by coherency in vertical eddy motion that uplifts
seeds well above the vegetation canopy (Nathan et al.,
2002; Tackenberg, 2003; Soons et al., 2004). For a wide
range of plant types, a positive relationship has been
observed between mean air temperature and the frequency
of LDD by wind in a boreal forest. Thus, an increase in
local air temperature increases pollen dispersal distances
(Kuparinen et al., 2009).
Another characteristic of pollen is their seasonality, as
the presence of pollen in the atmosphere follows a clear
seasonal cycle in response to the flowering seasons of the
plant sources (Tormo et al., 2010). On a local scale, the
pollination season for each plant is predictable and only
shifts slightly as a function of meteorological parameters.
The amount of pollen disposed by individual plants can
vary greatly from 1 yr to another. Pollination during a
given season always has a date, at which the pollen begins
to disperse but at lower numbers, followed by the main
pollination season when most of the pollen is dispersed,
and conclude by a date when the plant stops its pollenproducing phase. However, usage of this nomenclature
varies greatly within the literature and can be confusing
(Jato et al., 2006). In addition, sedimented pollen might be
resuspended again from dry surfaces. Pollen grains occasionally show a diurnal cycle with concentrations rising
12 h after dawn, peaking a few hours later and decreasing
through the afternoon (Jones and Harrison, 2004). The
phenomenon of diurnal variability is also common among
other biological aerosol types such as bacteria and fungal
spores (Jones and Harrison, 2004; Huffman et al., 2010).
Pollen grains are large PBA particles that typically lead
to short atmospheric residence times. However, they can be
up-drafted to high altitudes and have large residence times,
and thus pollen can reach concentrations comparable to ice
nuclei in some circumstances (Scheppegrell, 1924; Pruppacher and Klett, 1997; Diehl et al., 2001). Detailed information on the behaviour of pollen in ice nucleation is given in
section 4.2.
Global changes, such as increasing atmospheric CO2
concentrations, increasing temperature, changes in the
amount, distribution, and intensity of precipitation events,
increases in the intensity and frequency of certain extreme
weather events, changes in land use, and urbanisation, will
likely have an impact on the production, distribution and
dispersion of pollen (IPCC 2007b; Reid and Gamble,
2009). Climatic changes may lead to shifted or even
elongated pollinations seasons. As pollen is known to
cause allergies in humans, these shifts may also lead to
changes in human exposure and changes in the prevalence
and severity of symptoms in individuals with allergic
diseases (Reid and Gamble, 2009). Alterations in the timing
of aeroallergen production in response to weather variables
have been clearly demonstrated for certain tree species, but
less for grass, weed and mould (Katial et al., 1997;
Emberlin et al., 2002; Clot, 2003).
Because pollen allergies can cause such medical problems, various pollen-monitoring programmes, networks
and databases have been developed recently to provide
data on pollen observation, share methods, encourage
collaborations and thus create foundation for intensive
pollen research. Examples include the Pollen Monitoring
Program in Europe (Giesecke et al., 2010) and the Pollen
Biology Research Coordination Network in the United
States. The Global Pollen Database combines pollen
information from Africa, the Americas and northern Asia
made available by regional networks such as the Indo
Pacific Database, the Latin America Pollen Database and
the North American Pollen Database. These international
collaborations are helping to advance knowledge of global
pollen distribution.
In addition to climate-related changes in the atmospheric
abundance of pollen and fungal spores, the allergenic
potential of PBAP can also be enhanced by interactions
with air pollutants (Taylor et al., 2002; Franze et al., 2003;
Taylor and Jonsson, 2004; Franze et al., 2005; Pöschl,
2005; Reid and Gamble, 2009). For example, the reaction
with ozone and nitrogen oxides leads to the formation of
reactive oxygen intermediates and nitrated proteins that
can influence the interaction of PBAP with the immune
system and trigger or exacerbate allergic diseases
(Gruijthuijsen et al., 2006; Shiraiwa et al., 2011; Zhang
et al., 2011).
2.4. Viruses
Viruses are among the smallest of common PBAP classes,
with physical diameter as low as 20 nm (Dongsheng, 2006).
However, viruses are not commonly airborne as individuals
and are more likely attached to other suspended particles
(e.g. Yang et al., 2011).
Many diseases present in humans, animals, birds, fish,
insects and plants are caused by viruses found in aerosols
(one of possible routes of infection transmission), confirmed by numerous laboratory studies (Akers, 1969;
Akers, 1973; Verreault et al., 2008). However, publications
revealing the presence of viruses as PBAP are not
numerous (Gloster et al., 1982; Christensen et al., 1990;
Grant et al., 1994; Chen et al., 2008b). This perceived lack
of research might be connected to the fact that before the
development of molecular biological methods (e.g. PCR) to
detect genetic material of microorganisms (Alvarez et al.,
1995; Peccia and Hernandez, 2006), only viable viruses
could be found in air samples. There are no universal test
systems for virus detection such as nutrient media for
bacteria or fungi. Instead, sensitive cell cultures, embryo-
PRIMARY BIOLOGICAL AEROSOL PARTICLES IN THE ATMOSPHERE
nated chicken eggs or susceptible laboratory animals are
required (Zhdanov and Gaudamovich, 1982a; Zhdanov
and Gaudamovich, 1982b), and specific test systems allow
only the detection of viruses replicating in them. No other
viable viruses, which can also be present in aerosol samples,
will be detected.
Another possible reason for the scarcity of publications
containing information on viable viruses in atmospheric
aerosol is inactivation of viruses in the atmosphere under
the influence of different environmental factors (changes
in temperature, relative humidity, solar radiation, etc.).
Unlike bacteria, fungi and algae, viruses have no repair
systems, and therefore, their inactivation rates are usually
higher than those of living microorganisms.
According to Posada et al. (2010), the inactivation rate
of viruses in an aerosol can be described by:
C=C0 ¼ ekt
Here C is the concentration of viable viruses at the time t,
C0 is the initial concentration of viable viruses and k is the
rate coefficient of inactivation. Even for the most stable
viruses, k is typically of the order of 0.01 min 1,
corresponding to an effective half-life of about one hour
(Donaldson, 1973; McDevitt et al., 2008). For most other
viruses, the inactivation rate in aerosol is considerably
higher (Harper, 1961; Miller et al., 1963; de Jong, 1965;
Miller and Artenstein, 1967; Songer, 1967; Akers, 1969;
Benbough, 1971; Barlow, 1972; Donaldson, 1972; Akers,
1973; Donaldson and Ferris, 1974). Viruses are almost
completely inactivated in aerosols in the span of 1 d under
such conditions.
Experimental data on the survival of viruses show that,
on the whole, the inactivation rate becomes higher for all
viruses with increasing temperature (Zhdanov and Gaudamovich, 1982a; Zhdanov and Gaudamovich, 1982b; Weber
and Stilianakis, 2008). Also, the number of surviving viral
particles in aerosol decreases with increased radiation dose
that the virus aerosol is exposed to (Jensen, 1964; Zhdanov
and Gaudamovich, 1982a; Zhdanov and Gaudamovich,
1982b; Sagripanti and Lytle, 2007; McDevitt et al., 2008).
Relative humidity influences the survival of viruses in
aerosol differently. For example, the survival rate of
influenza virus in aerosol is highest at high relative
humidity, whereas that of foot-and-mouth disease virus is
highest at intermediate relative humidity (5060%) (Akers,
1969; Donaldson, 1972; Schaffer et al., 1976; Weber and
Stilianakis, 2008).
The use of molecular biological methods for detecting
genetic material of viruses also involves certain difficulties.
As genetic material of different viruses is presented by very
different variants: DNA or RNA (ribonucleic acid) molecules, single-stranded genomes (with or strand), frag-
17
mented genomes, etc. (Zhdanov and Gaudamovich,
1982a), no universal PCR primer for detection of all viruses
has been developed so far. Consequently, such methods
determine only the presence of expected viruses in samples.
For example, Chen et al. (2008c) presented the results of
search for different subtypes of influenza-A virus in the
atmosphere of Taiwan. Other viruses in atmospheric air
samples were not even sought.
Virus-containing aerosols are formed in spray from
water surfaces (Baylor et al., 1977a; Baylor et al., 1977b;
Baylor and Baylor, 1980), from aerosolised virus-destroyed
tissues of plants, insects, animals and birds; they are also
shed by sick animals, birds and humans (Zhdanov and
Gaudamovich, 1982b; Jones and Harrison, 2004). One
should also note the intentional use of aerosols of insect
viruses for plant protection (Morris, 1980; Maiorov et al.,
1985; Jinn et al., 2009). The transfer of virus-containing
aerosols in the atmosphere has been described for local
scales, e.g. near sludge wastewater treatment plants and
stock farms (Strauch and Ballarini, 1994; Carducci et al.,
1995; Sigari et al., 2006; Langley and Morrow, 2010) as
well as for regional scales, e.g. transfer of foot-and-mouth
disease virus across the English Channel (Gloster et al.,
1982) and transfer of avian influenza virus from continental
China to Taiwan (Chen et al., 2008b). The hypothesis of
transcontinental transfer of influenza A virus aerosol was
demonstrated by Hammond et al. (1989). Consequently,
virus-containing aerosols can spread worldwide.
Relatively few studies have attempted to comprehensively estimate the concentration of different viruses in
ambient air and evaluate their source strength. One
example of such a study was reported by Safatov et al.
(2010) who collected 30 samples of atmospheric air (10
15 m3 each) onto fibrous filters during different seasons in
Southwestern Siberia. Samples were analysed using the
PCR method for the presence of viruses known to cause
respiratory diseases, although no virus genetic material was
found. It should be noted, however, that Southwestern
Siberia is not endemic to airborne viral infections largely
because it is located far from sources of viruses such as
influenza (Chen et al., 2008c) and habitats of migrant birds
transmitting influenza viruses (Liu et al., 2005). Electron
microscopy during the same study detected bacteria, fungal
spores and plant fragments (Safatov et al., 2010), but viruslike particles are impossible to confidently detect without
genetic methods such as PCR, as discussed above.
As noted by Chen et al. (2008b), the total concentration
of different subtypes of influenza A viruses can reach
800 m 3 copies of genetic material of these viruses in the
ambient atmosphere of Taiwan and up to 3 ×104 m 3 in
outdoor pet markets in Taiwan. It should be noted that
Taiwan, like the whole of South-East Asia, is an endemic
area for this virus, which explains the higher influenza virus
18
V. R. DESPRÉS ET AL.
concentrations in this region. For other viruses originating
from local sources, such as excreta of infected animals and
humans, sewage treatment plants, use in agriculture, etc.
(Fannin et al., 1985; Carducci et al., 1995; Sigari et al.,
2006), the total numbers of viruses in aerosol are not large,
and their contribution to the total mass of aerosol is
negligible. As for more powerful sources, such as soil,
vegetation and water surfaces, data on virus aerosol in the
air in natural conditions are available only for the latter
(Baylor et al., 1977a, 1977b; Baylor and Baylor, 1980).
Virus-like particles can also be present in the atmosphere
and water, such as those described by Leck and Bigg
(2005a) using electron microscopy. The concentration of
virus-containing particles in the air is low, however (less
than 100 cm 3 total concentration of aerosol particles
with diameter larger than 90 nm in marine atmosphere;
data from Bigg et al. (1995)), and by these methods it is
impossible to distinguish viruses from particles on which
they are bounded.
Virus aerosols collected from the exhaled air of infected
animals have been the subject of various research studies.
For example, for pigs infected with classical swine fever
virus, the concentration of viral particles may reach
104 m 3 of air (Weesendorp et al., 2008). Other infections
of animals and birds (such as foot-and-mouth disease,
Newcastle disease, etc.) are characterised by virus aerosol
exhalation of the same order of magnitude (Downie et al.,
1965; Donaldson et al., 1983; Donaldson and Alexandersen, 2002; Li et al., 2009). Taking into account that the
number of infected animals is typically not large, the total
number of exhaled viruses in aerosol is similarly small.
To evaluate the total mass of viruses in 1 m3 of the
atmosphere, let us consider an upper limit to the ambient
concentration of viral particles to be 3 ×104 m 3. Assuming
a per virus mass of 2 ×10 17 kg, one of the heaviest known
viruses (vaccina virus, Zhdanov and Gaudamovich, 1982b)
yields an estimated virus mass concentration of
6 ×10 4 mg m 3. This estimate is approximately four orders
of magnitude smaller than the total concentration of
biogenic substance in the atmosphere (Jaenicke, 2005;
Table 4) and thus, even if the concentration of viruses in
the atmosphere was underestimated by an order of
magnitude, the average mass concentration of viruses in
atmospheric air would be very small compared to other
biogenic aerosol mass.
2.5. Algae and cyanobacteria
The occurrence of algae in fresh and sea water is well
known. However, algae living outside of the aqueous
environment rarely attract attention. These algae are
termed terrestrial, aeroterrestrial, aerophytic or subaerial,
are able to reside on almost all substrates, natural or
artificial and can become airborne, constituting the aero(phyto) plankton. Chlorophycean and xanthophycean
species are common worldwide (Printz, 1921; Laundon,
1985; Dubovik, 2002; Reisser, 2002; Sharma et al., 2007;
Neustupa and Skaloud, 2010) and exist free living as well as
lichenised (Bubrick et al., 1984). Due to the size of the
algae and their spores, many smaller than 10 mm in
diameter (Printz, 1921; Dubovik, 2002; Burchardt and
Dankowska, 2003; Neustupa and Skaloud, 2010), they
can be easily dispersed in the atmosphere. In a recent
review article, the mechanisms involved in the aerosolisation of algae were presented, and Sharma et al. (2007)
stated that ‘airborne algae are the least-studied organisms
in both aerobiological and phycological studies’. This
seems to be valid for aerosol studies, too. Quantitative
measurements of algae in ambient air are very rare and it
was reported (Reisser, 2002) that algal cells are present at a
concentration of 300500 cells m 3 of air on a dry and
sunny summer day (Table 4).
Cyanobacteria belong taxonomically to bacteria,
although they have long been considered as algae, as
they have the ability to obtain their energy through
photosynthesis. Due to their colour, they have been called
blue-green algae, but they still belong as they lack a cell
nucleus to the bacteria domain. As cyanobacteria can be
found in almost every environment, have habitats across
all latitudes, are widespread in oceans and freshwater,
terrestrial ecosystems and bare rock and soils as well as in
extreme habitats such as hot springs, they have been
considered to be one of the most successful groups of
microorganisms. They fulfil vital ecological functions in
the world’s oceans as important contributors to global
carbon and nitrogen budgets (Stewart and Falconer,
2008). Cyanobacteria can not only occur as planktonic
cells but also create biofilms in marine, freshwater and
terrestrial environments. A few are involved in symbiosis
with lichen, plants and other organisms and provide
energy for their host. Although well studied in the marine
environment, not much is known about their presence in
the atmospheric environment.
Airborne cyanobacteria were found in Varanasi City,
India, where they were more abundant than green algae
and diatoms; Phormidium fragile as well as Nostoc
muscorum were recorded throughout the 2 yr of sampling
(Sharma and Rai, 2008). Similar observations were
made in Cairo, Egypt. The species Chroococcus limenticus, Lyngbya lagerheimii and Schizothrix purpurascens
appeared in all seasons (El-Gamal, 2008). Genitsari et al.
(2011) recently published an overview of taxa of airborne algae and cyanobacteria found in aerobiological
studies.
PRIMARY BIOLOGICAL AEROSOL PARTICLES IN THE ATMOSPHERE
2.6. Biological crusts and lichens
Arid and semi-arid regions of the globe exhibit biological
crusts (also called rock varnish, cryptobiotic, microbiotic
or biological soil crust) consisting of bacteria, fungi, algae,
lichens and bryophytes in variable proportions
(Belnap et al., 2003). Rock varnishes are natural, thin
(5 mm l mm), brown, black or grey (lead colour) coatings
on rock surfaces (Krumbein and Jens, 1981). They consist
largely of iron and manganese oxides with some quartz,
clays and carbonates admixed. They may contain considerable amounts of organic material that sometimes may be
responsible for the gel-like or lacquer-like appearance. The
grey or black films may sometimes consist predominantly
of dry cyanobacteria. Rocks outside of deserts often are
also covered by a varnish (Douglas, 1987). Although these
rock crusts are not suspended into the air by active
mechanisms, they can be eroded from their host surface
and broken into fragments producing small dust particles
(Grini et al., 2002; Büdel et al., 2004). Parts of biological
soil crusts can also be ablated from desert surfaces, and all
these particles may contribute to the content of organic
material in dust transported over long distances during
storms (Grini et al., 2002; Büdel et al., 2004; Prospero
et al., 2005; Hua et al., 2007).
As lichens are a symbiotic form of life between a wide
range of fungi, algae or cyanobacteria (Hawksworth et al.,
1995; Nash III, 1996) and distribute separately or together
via the air, they also can, in certain circumstances,
constitute a subgroup of PBAP. As biological aerosols,
they may play a role in ice nuclei activity as well as in health
effects. Lichen, for example, can cause human allergenic
reactions (Richardson, 1975; Fahselt, 1994; Ingolfsdottir,
2002).
Although lichens are regarded as an individual taxonomic group lichen taxonomy is based on the taxonomy
of the fungal partner, the mycobiont (Tehler, 1996) they
also must be considered separately from their host because
lichens are different in behaviour and life form from their
isolated partners (Nash III, 1996; Tehler, 1996). Nearly
20% of all known fungi species are lichenised (Lutzoni
et al., 2001) and more than 98% of the lichenised fungi
belong to Ascomycota and a few to Basidiomycota (Hawksworth et al., 1995; Tehler, 1996). Most of the lichenised
fungi form symbioses with Chlorophyta, whereas only
about 10% lichenise with cyanobacteria and 3% with
both (Tschermal-Woess, 1988; Lewis and McCourt, 2004).
In general, lichens can be found in three major life forms
that all can contribute to biological aerosol particles: a
crust-like biofilm (crustose), a leaf-like (foliose) and a
branched tree-like biofilm (fruticose) as described in
Hawksworth et al. (1995) and Büdel and Scheidegger
(1996). Especially for PBAP formation, the presence of
19
lichens in extreme habitats is interesting. They can deal
with extreme light, dryness or temperature that are less
favourable for higher plants. They are also tolerant to
extreme desiccation and UV light exposure due to their
cortical pigments (Nybakken et al., 2004; Gauslaa, 2005;
Vráblı́kova et al., 2006). Their ability to prevent the
formation or to scavenge free radicals also increases their
chance of surviving during their transport in air. Lichens
face considerable problems in colonising new sites and
maintaining existing populations. Mycobionts can distribute separately via Asco- or Basidiospores, or asexual by
singular lichen structures, that contain both, mycobiont
and phycobiont, such as insidia (protuberances from the
thallus of corticated algae and medullary tissue), soredia
(several algal cells encased by a hyphae) or hormocrusts
(fragments if filamentous cyanophyte Nostoc spp with
hypha penetrating the thallus fragments (Marshall, 1996;
Oksanen, 2006)).
Although lichen species have been detected in the atmosphere, estimates of lichens biomass and consequently
estimates of the number of lichen-derived aerosol particles
are difficult. Lichen species are adapted to almost every
temperate to extreme environment on Earth, such as arctic
tundra, hot deserts, rocky coasts, or toxic slag heaps, but
the spread of lichen population within each environment
type is different. They are abundant on plant leaves or
branches in rain forests or temperate woodlands, as well as
on bare rock including walls, and on exposed soil surfaces.
Henderson-Begg et al. (2009) suggested that canopy lichen
biomass in temperate forest is similar to leaf biomass.
Lichen detection directly in air has been pursued by
Marshall (1996) in an aerobiological monitoring programme, where he found lichen soredia to be the most
abundant airborne propagule with a size range of 30100
mm on Signy Island in Maritime Antarctica.
Lichens are not only adapted to survive hot and dry
environmental conditions but are also often frost tolerant
(Kershaw, 1985). In ice nucleation studies pursued by Kieft
(1988), nearly all lichens tested showed ice nucleation
activity at temperatures above 8 8C or even above
5 8C (see also Table 6). In theory, the IN could be the
bacterium or the fungal partner, but the failure to culture
IN bacteria from lichen and also the high density of IN in
active lichen carrying only few numbers of bacteria
suggests a non-bacterial source of lichen IN. Studies by
Kieft and Ahmadjian (1989) show that in their tests, always
the mycobiont was responsible for IN activity. IN activity
in lichen might enhance the uptake of atmospheric
moisture by enhancing the condensation or causing deposition of ice from water vapour. Lichen-associated IN might
even contribute to atmospheric IN (Kieft, 1988).
20
V. R. DESPRÉS ET AL.
2.7. Others
Apart from the PBAP defined above, there exist a variety
of other primary aerosol particles from the biosphere. Plant
fragments, in particular, are one of the largest mass
fractions of atmospheric PBAP and comprise a wide
spectrum of decaying matter. However, drawing a consistent definition between PBAP and other organic matter can
be difficult because plant materials can eventually be
broken down into humic-like substances (HULIS, Fuzzi
et al., 2006; Graber and Rudich, 2006) by oxidative
modification and degradation of biopolymers, and are
therefore, important components of soil. Cellulose, a
homopolymer of D-glucose (Pöhlker et al., 2011), is the
most frequently occurring biopolymer in the terrestrial
environment (Butler and Bailey, 1973; Sánchez-Ochoa
et al., 2007), although other biopolymers and structural
components (e.g. lignin, chitin) may also be atmospherically relevant (Pöhlker et al., 2011). Cellulose is a major
component of plant tissue and pollen and can be produced
by some bacteria (Cannon and Anderson, 1991) but is not
present in insects and animalian tissue (Winiwarter et al.,
2009). Atmospheric concentrations of cellulose thus exhibit
a strongly seasonal cycle and have been shown to have
mass concentrations at least in the order of 0.5 mg m 3
(Puxbaum and Tenze-Kunit, 2003). Presence of cellulose in
atmospheric aerosols has also been frequently used as a
proxy for total concentrations of plant debris (e.g. SánchezOchoa et al., 2007; Winiwarter et al., 2009). Due to large
particles of biological material being lifted into the atmosphere (e.g. air-dispersed seeds), the actual concentration of
cellulose and related materials in total air particulate
matter may be substantially higher under windy conditions.
Emissions of liquid and solid secretions from organisms
are also found in the atmosphere. Brochosomes and
epicuticular wax (Wittmaack, 2005; Wittmaack et al.,
2005) are expelled from leafhoppers and do not contain
cells. Brochosomes serve as a highly water-repellent body
coating of leafhoppers. They usually become airborne not
as individuals but in the form of large clusters containing
up to 10 000 individuals or even more, but then usually
separate into individual brochosomes or small clusters.
They are extremely widespread and can be found in aerosol
samples from all continental regions (Bigg, 2003). Exopolymer secretions (EPS) of microalgae and bacteria in water
become airborne with the bubble- bursting mechanism
(Leck and Bigg, 2005a, 2005b). EPS might deteriorate the
ability of sea spray particles acting as Cloud condensation
nuclei (CCN, see studies in Section 4.1).
Other sources of PBAP are fur fibres, dandruffs and skin
fragments of animals (including humans) that are shed in
large amounts per day and can also be airborne (Cox and
Clark, 1973). Insect fragments have also been observed in a
number of studies and thus may represent an important class
of physically large PBAP in some areas (e.g. Wittmaack,
2005). Whole macroscopic organisms, such as spiders
lofted to air by silk ‘ballooning’ lines, have been observed
to travel extremely long distances (several 100 km) and
to high altitudes (stratosphere) (e.g. Thomas et al., 2003).
These organisms may contribute to PBAP dispersal efficiently through body or silk fragments.
2.8. Characteristic concentrations and emission
estimates
Biological particles cover an extremely broad range of sizes
and are morphological very diverse. Thus, measurements of
ambient PBAP concentrations are extremely challenging
and reports from literature have been very few. PBAP have
unique properties, such as large particle size, cell viability
concerns and physical changes associated with environmental variables (see Section 3.1). In addition, biological
material suspended in the atmosphere undergoes drastic
changes as a function of manifold biological variables such
as species and ecosystem health, seasonal and episodic
cycles and meteorology. As a result, average concentrations
for PBAP are extremely difficult to estimate without
rigorously taking all of these variables into account.
However, PBAP concentrations have been estimated to
be up to 25% of total aerosol mass on a global basis
(Jaenicke, 2005), and so more detailed measurements are
desperately needed.
As a first overview of global importance, Table 3
present a survey of global emission estimates and characteristic magnitudes for the number and mass concentration of major PBAP classes, respectively. Such synthesis
provides means for discussion and motivation of future
measurements.
3. Techniques for PBAP collection and analysis
3.1. PBAP sampling methods
The sampling and collection of atmospheric aerosols
requires a sound understanding of the physical principles
that govern interactions with suspended particles ( B100
mm). As such, particle size is by far the most important
characteristic for choosing a sampling procedure for both
PBAP and all other classes of airborne particles (Nicholson, 1995). Losses of particles within inlets, inlet lines and
instruments can cause huge biases in both quantitative and
qualitative understanding, and therefore sampling procedures must be designed properly (Zimmermann et al.,
1987). While small particles (B0.1 mm) are most susceptible to Brownian diffusion and electrostatic forces, large
particles ( 5 mm) are more influenced by losses due to
PRIMARY BIOLOGICAL AEROSOL PARTICLES IN THE ATMOSPHERE
gravitational settling and inertial surface impaction. In
addition, losses of particles to surfaces due to air turbulence can affect particles of all sizes. These issues are dealt
with in detail elsewhere (e.g. Hinds, 1999; Baron and
Willeke, 2001).
However, the sampling of biological aerosols often
requires special handling procedures as compared to the
sampling of inert particles and these are introduced briefly
here. Although sampling issues due to particle size effects
are not unique to biological aerosol sampling, PBAP size
and mass are often hard to predict based on complicated
relationships between the biological tissue and environmental variables such as temperature and relative humidity
(e.g. Madelin and Johnson, 1992; Reponen et al., 1996). In
addition, many biological particles (e.g. chain agglomerates
of fungal spores) can have very elongated morphologies
that can create large differences between physical and
aerodynamic diameter measurements (Lacey, 1991; Reponen et al., 2001). Collection of living, or viable, material
requires care in order not only to sample microorganisms
appropriately but also to keep them alive until the desired
analysis or cultivation can be performed. Certain species of
bacteria and fungal spores are more easily cultivated than
others, and in many cases this relates to the ability of
sampled particles to survive harsh conditions related to
sample collection (i.e. sun exposure, extended period of
high airflow). Bacteria, in particular, are susceptible to
damage or death when impacted too forcefully onto
collection substrates (e.g. Stewart et al., 1995). Samples
also must often be immediately frozen after collection to
preserve DNA for later analysis. This can complicate
sampling of PBAP in remote environments and add both
uncertainty and bias to measurements. Small biological
particles (e.g. viruses, bacteria) may also be attached to
larger, non-biological particles such as mineral dust and
thus be sized much larger than the microorganism by itself.
This fact must be kept in mind when analysing sizeresolved PBAP measurements. Due to the additional
complexities in determining the biological nature of a
collected set of particles compared to that of non-biological
particles, PBAP measurements should be carefully scrutinised and in many circumstances taken as lower limit
values.
As a result of the issues specific to biological aerosol
sampling, a number of sampling methods have been
developed primarily for PBAP collection. Again, a review
of these topics can be found elsewhere (e.g. Henningson
and Ahlberg, 1994; Madelin, 1994; Crook and SherwoodHigham, 1997; Levetin, 2004; Xu et al., 2011) and so only a
very brief overview of key classes of PBAP samplers will be
given here. Devices that collect aerosol based on inertial
forces have been particularly well utilised for PBAP
measurement. The most common single-stage impactor
21
used for microbiological sampling has been the relatively
simple slit-to-agar sampler (Henningson and Ahlberg,
1994), first developed by Bourdillon et al. (1941) and
capable of providing CFU counts with high time resolution
of approximately 1 h. Many different cascade impactors
(multiple stages) have also been developed and extensively
used for PBAP sampling (Mitchel, 1995). Probably, the
most widely used of these has been the Andersen sampler
(Andersen, 1958). This device has been frequently used as a
reference method for sampling of culturable microorganisms, providing six or eight stages of particle sizing but due
to physical constraints, the inner jets on each plate have a
different sampling efficiency than the outer jets. An
alternative in which this phenomenon is considered is the
Berner-Impactor (Hillamo et al., 1991). The Marple 8-stage
impactor is a personal cascade impactor design that
provides size-resolved PBAP information directly from
the breathing zone of an individual who wears it (Rubow
et al., 1987). The Burkhardt spore trap has been an
important sampler for collecting large PBAP such as fungal
spores and pollen (Hirst, 1952). In it, air is brought in
through a small slit in a housing designed to face the
prevailing wind, and material collected continuously for up
to a week can later be analysed via microscopy. Impingers
collect airborne particles into liquid media and offer the
possibilities of extended sampling times and increased
collection efficiency with respect to many agar samplers
(Crook, 1995a). Greenburg and Smith (1922) developed the
first liquid impinger, and many types have since been
designed for PBAP sampling (e.g. Henderson, 1952.). The
AGI-30 has been particularly important and has been used
as a reference sampler for the collection of viable organisms
(Brachman et al., 1964; Henningson and Ahlberg, 1994).
Other inertial samplers that have been commonly applied
to PBAP collection include rotary arm samplers and both
single- and multiple-stage centrifugal cyclones (e.g. IPCC
2007b; Crook, 1995a).
Non-inertial sampling methods such as passive settling
and filtration have also both been widely used for PBAP
collection. Many types of filter substrates have been used,
including fibrous, flat (e.g. NucleoporeTM) and membrane
(Crook, 1995b). Each have their own advantages and
disadvantages and these should be investigated thoroughly
by the individual investigator. Electrostatic (Mainelis et al.,
1999, 2002; Tan et al., 2011) and thermal precipitators
(Kethley et al., 1952; Orr et al., 1956) have been developed
in an attempt to collect viable aerosols with less damaging
force. Recently, methods for online detection of biological
aerosols have been developed using a variety of optical and
additional techniques. These will be discussed in detail in
Section 3.3.
22
V. R. DESPRÉS ET AL.
3.2. Traditional analysis methods
Before the invention of molecular and other physicochemical methods, the diversity, identity and concentration of
airborne microorganisms were primarily studied via microscopic analysis and cultivation methods on both selective
and non-selective media. These methods have long and rich
histories within aerobiological studies and still remain
useful tools for PBAP analysis. Thus, the terms provided
here (‘traditional’ and ‘modern’) are historical and somewhat arbitrary, but helpful for rough categorisation. A
detailed discussion of these methods is beyond the scope of
this text and can be found elsewhere (e.g. Cox and Wathes,
1995).
3.2.1. Cultivation. Cultivation methods are only capable
of collecting and detecting certain viable bacteria, fungi and
algae, whereas they are incapable of detecting all other
biological aerosol particles from these and other organism
groups (e.g. dead bacteria and fungi, tissue fragments such
as cell walls or cytoplasmic material). Although not capable
of directly infecting a host, non-viable PBAP classes are
still extremely important because they can provoke deleterious health effects (Gorny et al., 2002; Green et al., 2006)
and may still be relevant for cloud formation.
As mentioned, studies investigating only the culturable
fraction of PBAP have historically comprised a large
portion of reported measurements. However, studies investigating cell viability suggest that the vast majority of
environmental microbiota is non-culturable, even when
viable (Staley and Konopka, 1985; Roszak and Colwell,
1987; Amann et al., 1995; Colwell, 2000; Rappé and
Giovannoni, 2003; Wainwright et al., 2004b). Thus, studies
based on culturing alone usually drastically underestimate
microbial diversity (Fierer et al., 2008) and concentration.
Only 17% of known fungal species can be grown in
culture (Bridge and Spooner, 2001) and for bacteria, the
fraction is typically less than 10%, with an observed range
of 0.01%75%, and average values estimated at 1%
(Heidelberg et al., 1997; Lighthart, 2000; Chi and Li, 2007).
In addition, the culturability of bacteria decreases rapidly
following aerosolisation, (Heidelberg et al., 1997) and
bacteria can be easily damaged when impacted via traditional sampling devices (Stewart et al., 1995). Within the
culturing processes, additional biases may occur. For
example, the sampling efficiency and culturability of viable
bacteria depend strongly not only on the bacterial strain
but also on experimental and environmental factors,
including the growth medium used (ZoBell and Mathews,
1936; Kelly and Pady, 1954; Shahamat et al., 1997; Griffin
et al., 2006), the choice of impaction versus filtration as a
collection method (Stewart et al., 1995), the incubation
temperature and length of incubation time (Amato et al.,
2007c; Wang et al., 2007; Wang et al., 2008), the air
sampler volume (Griffin et al., 2006), relative humidity
(Wang et al., 2001), time of day (Tong and Lighthart, 1999)
and even the collection season (Amato et al., 2007c).
Finally, single particles containing bacteria may represent
a colony consisting of many cells, leading to a further
underestimation of their abundance (Tong and Lighthart,
2000).
Despite these limitations, cultivation methods have the
advantage that they are far less expensive than molecular
techniques and can give an indication of the number of
viable cells in the air, for species that respond well to the
culturing method used. Cultivation is particularly useful for
targeting individual species or groups of microorganisms
and for creating culture collections. Culture studies can
also characterise certain bacterial strains by various
biochemical methods and give qualitative information
about relative changes in the concentration over the course
of days or season.
3.2.2. Light microscopy. In addition to cultivation,
microscopic techniques have been extremely important to
the history and development of PBAP analysis and
continue to be invaluable tools. Light microscopy of
various types has been applied to the characterisation of
collected PBAP (Spurny, 1994; Cox and Wathes, 1995 and
references therein). For pollen, it still remains the most
common analysis method. Simple optical microscopy was
the first technique to be applied to PBAP analysis in the
seventeenth century (e.g. Miquel, 1883) and continues to be
utilised extensively. But, it has to be taken into consideration that particles B2 mm are only visible as dots under an
optical microscope and thus cannot be analysed in detail
according to their size and shape. Aerosol samples collected
by sedimentation and impaction devices can be directly
visualised and counted by light microscopy. If the sampling
device used is volumetric, the concentration of particles in
the air can be quantified. However, the identification of
biological particles via direct counting is both very tedious
and somewhat subjective, as the particles must be counted
by eye. Various traditional stains can be used in combination with light microscopy, including methylene blue for
simple examination, and Gram staining and other differential staining techniques that aid classification into groups
of species. Protein staining gives an estimate of all (total)
PBAP (Matthias-Maser and Jaenicke, 1995). For the
analysis of the diversity and composition of bacteria and
fungi, microscopic analyses are not usually reliable, as
small non-descript spores and hyphae or fragments of
fungal tissues cannot be classified (Pitt and Hocking, 1997).
Some fungi or bacteria may remain morphologically
PRIMARY BIOLOGICAL AEROSOL PARTICLES IN THE ATMOSPHERE
undistinguishable or may only be identifiable to a class or
family level.
3.2.3. Fluorescence microscopy. Fluorescence microscopy has been applied both to look at the autofluorescence
of PBAP (Pöhlker et al., 2011), and especially with the use
of fluorescent dye labelling (Karlsson and Malmberg, 1989;
Hernandez et al., 1999). The most common traditional
method for determining the total count of environmental
microorganism is direct fluorescence microscopy, either by
taking advantage of the autofluorescence of certain biological compounds or by using samples that have been
treated with a fluorescent dye, most commonly 4.6diamidino-2-phenylindole (DAPI) or acridine orange
(Francisco et al., 1973; Hobbie et al., 1977; Kepner and
Pratt, 1994; Matthias-Maser and Jaenicke, 1995; Harrison
et al., 2005). Acridine orange binds to both DNA and
RNA, fluorescing green when bound to DNA and red
when bound to RNA and some mucins. DAPI fluoresces
blue when bound to DNA and yellow when unbound or
bound to a non-DNA material. Traditionally, particles
have been classified and counted by a human investigator,
taking into account the size and morphology of stained
particles. Epifluorescence microscopy permits counting of
the total number of unlysed cells containing DNA; a
number that includes both viable and non-viable microorganisms. It is not always possible to unambiguously
distinguish different types of biological particles, such as
bacterial and fungal spores, via fluorescence microscopy.
However, the colour of autofluorescence combined with
the application of fluorescent stains can be used to
distinguish some broad groups of microorganisms. Fluorescence microscopy is both tedious and labour intensive,
although the use of fluorescence aids the identification of
biological particles compared to light microscopy. Recently, more automatic techniques have been attempted,
including computer analysis of microscopic images (Carrera et al., 2005) and fluorescence spectroscopy (Reyes
et al., 1999; Courvoisier et al., 2008). Other modern
fluorescence-based techniques will be described in the
next section.
3.3. Modern analysis methods
3.3.1. Molecular techniques
3.3.1.1. Chemical tracers: Chemical tracers, such as the
sugar alcohols mannitol and arabitol, can be used to not
only assess the abundance of PBAP, especially fungal
spores in air particulate matter, but also characterise other
aerosol types (Hensel and Petzhold, 1995; Graham et al.,
2003; Graham et al., 2004; Lau et al., 2006; Elbert et al.,
23
2007; Yttri et al., 2007; Bauer et al., 2008a; Engling et al.,
2009; IInuma et al., 2009; Burshtein et al., 2011). A
number of other chemical tracers have been used as proxies
for various types of biological aerosol particles, such as
endotoxins, mycotoxins, glucan, ergosterol, extracellular
polymeric substances, carbohydrates, proteins, peptides,
sugars and adenosine triphospate (ATP). These can be
analysed by a wide range of instrumental and bioanalytical
techniques such as chromatography coupled to mass
spectrometry, spectrophotometry, fluorescence spectroscopy, immunoassays, dye assays, etc. (Griffith and DeCosemo, 1994; Reponen et al., 1995; Franze et al., 2005;
Pöschl, 2005; Demirev and Fenselau, 2008).
Chemical tracer analysis has the advantage of providing
quantitative information, but it does usually not provide
information about the identity and biodiversity of PBAP
on the species level.
3.3.1.2. Nucleic acid sampling and extraction: For the study
of biological aerosols molecular techniques, e.g. those
based on molecular genetic analyses, have some advantages
compared to traditional methods. The results can enable
the identification and quantification of culturable as well as
uncultivable microorganisms, of viable and dead cells, and
of plant and animal fragments (Després et al., 2007).
To analyse biological aerosols with molecular genetic
tools, biological aerosols need to be collected and the
nucleic acids extracted. Biological aerosols are either
collected in culturing media (liquid or plates) or water
(Boreson et al., 2004), special biological aerosol particle
collectors (e.g. the Wetted-wall Cyclone sampler (Biotrace)
in Maron et al. (2006)) or on appropriate air filter samples.
Several different filter types have already successfully been
used for the DNA analysis but not been compared
quantitatively to each other (e.g. glass fibre filters (Després
et al., 2007; Fröhlich-Nowoisky et al., 2009); quartz fibre
filters and polypropylene filtres (Després et al., 2007);
cellulose nitrate filtres (Després et al., 2007; Bowers et al.,
2010); Celanex polyethylene terephthalate filtres (Brodie
et al., 2007); borosilicate filtres (DeSantis et al., 2005) etc.).
The basis for most molecular analyses techniques is the
successful extraction of DNA. Every cell carries this
molecule: eukaryotes carry DNA in the form of chromosomes within the cell nucleus, whereas prokaryotes and
archaea lack a nucleus and carry DNA in genophores
directly within their cell body. During the DNA extraction
processes, proteins are denatured and separated together
with lipids, pigments, cell wall fragments and organelle
structures.
DNA extraction protocols vary according to the tissue
for which they are used. Plant cells, with strong cell walls,
present different extraction challenges than animal tissue
cells. Endospores of bacterial and fungal spores have very
24
V. R. DESPRÉS ET AL.
strong cell walls that need to be broken down before DNA
extraction. Thus, some compromise is always required in
selecting a DNA extraction method for ambient air filter
samples that contain a mixture of various organisms and
tissue types. Either the DNA is extracted using a generic
method that does not exclude any tissue type but is also not
ideally matched to any specific type such that some
organisms and tissue types are undersampled, or the
DNA is extracted using a method specific to a particular
organism or tissue type, and other types are undersampled.
Thus, for ambient samples that include a mixture of many
types of biological material, PBAP that contain thick
membranes or cell walls could elude extraction of DNA
by a generic method, leading to an underestimation of such
species. Usually, commercial kits can be used for the
extraction (e.g. soil DNA extraction kit (Després et al.,
2007; Fröhlich-Nowoisky et al., 2009)); Fast Prep 120
agitator together with Spin column of MolBio Laboratories (DeSantis et al., 2005); alternatively, some investigators develop their own extraction methods (e.g. Boreson
et al., 2004; Maron et al., 2005).
3.3.1.3. Amplification of genomic DNA: The DNA extract
of an air filter sample still contains the genomic DNA of all
sorts of organisms; thus, it is a mixture of DNA from living
and dead material of fungi, bacteria, archaea, plants,
animals or viruses. To be able to identify single genera or
species, it is necessary to enrich the DNA of the organism
of interest relative to other genomes. The PCR efficiently
amplifies characteristic regions of the DNA of a species, or
a group of species, for detailed analyses. The method is
based on thermal cycling in which the DNA is heated,
thereby separating the double strands. Short DNA sequences, called primers, attach to matching sequences on
the single stranded DNA that mark the borders of the
region of interest on the genome. In the final step of PCR,
the DNA polymerase enzymatically assembles a new
matching DNA strand in the target region using single
nucleotides. PCR, followed by genetic sequencing of the
amplified DNA, can be used to identify organisms, to
understand phylogenetic relationships or to study specific
genes. Thus, it is an essential technique when studying the
identity, diversity and composition of biological aerosols.
Within every genomic DNA, there are areas that are
highly conserved between organisms such as housekeeping
genes, whereas other areas vary enormously. The primers
used in PCR should ideally attach to highly conserved
areas, whereas the sequence between the primers should be
diverse and thus uniquely present in the targeted organisms
or group of organisms. Areas such as ribosomal RNA
genes or the ITS-regions with a huge variability are often
used in taxonomic identification studies, as they enable to
differentiate between genera or even species and thus can
be used as a fingerprint of a species. For bacteria, e.g. often
the 16S rRNA genes are amplified (Moffett et al., 2000).
While amplification followed by taxonomic analysis
allows the identification of PBAP species within aerosol
samples, it gives no information about the quantity of
particular species in the air. Quantitative PCR allows the
calculation of the number of DNA template molecules in
the DNA extract. Thus, when studying, e.g. a single copy
gene within a single bacterial species, it is possible to
estimate the number of individuals of this particular species
that was present in the air filter sample. This could be an
especially valuable tool for studying pathogenic biological
aerosol particles.
Although molecular techniques are thought to detect
biological aerosols unambiguously, they may not amplify
all airborne bacteria in a sample (Peccia and Hernandez,
2006; Fierer et al., 2008). Theoretically, the DNA polymerase can amplify a single DNA copy and thus detect
even organisms that are present in minor quantities. But,
the sensitivity of the PCR depends on several factors. One
major issue is the choice of the primer pair used for the
amplification process. Different primer pairs have different
specificity and sensitivity (Alvarez et al., 1995; Polz and
Cavanaugh, 1998). Thus, while one primer pair might start
the amplification from just a single DNA strand, a less
sensitive primer pair might need 100 molecules to get
started. It is also possible that a primer pair is more
sensitive to some species than to others within a targeted
group. Although a primer pair might have been designed to
perfectly match the target organism, it might also coamplify other organisms. This is especially important for
biological aerosol DNA extracts where many competing
DNA molecules may be present, possibly even in higher
concentrations than the organism of interest. Literature
research can help to find suitable specific primers, but often
the specificity of primers is overstated in the literature (e.g.
Fröhlich-Nowoisky et al., 2009).
Another important point that must be considered is the
possible presence of PCR inhibitors. Substances such as
humic acids inhibit the DNA amplification process either
by hindering the attachment of polymerase to the primers
to initiate amplification, or by binding to the DNA and
thereby preventing primers or enzymes from attaching.
Different PCR primers as well as DNA polymerases vary in
their ability to overcome inhibitory factors. In addition,
filter materials on which biological aerosol particles are
collected can inhibit PCR (Després et al., 2007).
Finally, although DNA is a stable molecule, which under
cool, dark and dry conditions can sometimes be preserved
for several thousand years (Pääbo et al., 2004), DNA starts
to degrade, breaks into smaller pieces and is chemically
modified as soon as an organism dies (Pääbo, 1989;
Lindahl, 1993; Höss et al., 1996; Smith et al., 2001). UV
PRIMARY BIOLOGICAL AEROSOL PARTICLES IN THE ATMOSPHERE
light, ozone and melting-freezing processes speed up these
degradation processes, and thus a long residence time of
biological material in air leads to deterioration of DNA
and loss of genetic information. Pollen grains, as well as
many spores of fungi and bacteria, are encased by thick cell
walls to protect their DNA from DNA-destroying environmental processes.
3.3.1.4. Restriction fragment length polymorphism
techniques: A standard molecular genetic technique is the
fragmentation of DNA by a restriction enzyme that cuts
the DNA wherever a specific target sequence occurs. The
resulting restriction fragments are separated according to
their lengths by gel electrophoresis. It can be applied
following colony PCR (confirmation of plasmid insertion)
to select as many different clones as possible for the
sequencing reaction (Fröhlich-Nowoisky et al., 2009). For
a broad characterisation of the community structure and
diversity of a PBAP sample, the terminal restriction
fragment length polymorphism (T-RFLP) technique can
be used to get a rough estimate of the diversity and relative
abundances (Després et al., 2007; Georgakopoulos et al.,
2009). The first step of a T-RFLP is a PCR amplification in
which one primer is fluorescently labelled. The PCR
products are then digested with a restriction enzyme that
cuts each DNA strand at the target sequence, resulting in
shorter, labelled fragments. Because the position of the
target sequence on the genome varies among bacterial
strains, the length of the labelled fragments also varies. The
fluorescently labelled end fragments are separated by
electrophoresis, and the strand lengths and fluorescence
intensities are calculated. The fluorescence intensity of
strands of a given length indicates the frequency of the
corresponding bacterial strains in the original sample. The
genetic diversity indicated by a T-RFLP profile (as
measured by the number of different strand lengths) is
highly dependent on the choice of the restriction enzyme
and the part of the gene used to generate the terminal
fragments. If the PCR products are simultaneously cloned
and sequenced, the size of the terminal fragment that each
will produce can be calculated, and so each sequence can be
attributed to a T-RFLP peak (Després et al., 2007;
Georgakopoulos et al., 2009).
3.3.1.5. Sequencing methods: To determine the identity of
the genomes obtained from atmospheric aerosol samples,
the PCR products are often cloned and sequenced (e.g.
Boreson et al., 2004; Maron et al., 2005; Després et al.,
2007; Fierer et al., 2008; Bowers et al., 2009; FröhlichNowoisky et al., 2009; Georgakopoulos et al., 2009).
Species can often be identified by comparing the obtained
sequences with those that are already available in online
databases, e.g. that of the National Center for Biotechno-
25
logy Information (NCBI). The BLAST search4 is the
easiest way to search for matching sequences. If a new
organism (e.g. new bacterial strain) is found, it is possible
to identify the most closely matching sequences already
available in the database. For bacteria, the generally
accepted levels of discrimination are 9799% similarity
for species and 9597% for genera; for fungi, clustering
sequences with 97% or greater sequence similarity are
accepted (O’Brien et al., 2005; Bowers et al., 2009; Fröhlich-Nowoisky et al., 2009; Georgakopoulos et al., 2009).
The traditional sequencing technique is using a chain
termination (Sanger and Coulson, 1975; Sanger, 1981).
The sequencing process is essentially another PCR but only
one primer instead of two is used. The reaction mix
contains not only the standard DNA bases (deoxynucleotide-triphosphate, dNTP) but also chain terminator dideoxynucleotide-triphosphates (ddNTPs) that are labelled
with fluorescent dyes that emit light at different wavelengths (dye-terminator sequencing). The incorporation of
a ddNTP results in a chain termination, and the fluorescence peaks are detected after capillary electrophoresis
resulting in the DNA sequence.
The high demand for low-cost sequencing in recent years
has led to the development of high-throughput sequencing
technologies. In these technologies, the sequencing process
is parallelised for several samples, and thus in a short time
thousands or millions of sequences are produced. One highthroughput technique, 454 pyrosequencing, has been applied successfully several times in biological aerosol research (Bowers et al., 2009, 2011). The DNA is amplified
within an oil droplet by the so-called emulsion PCR. Each
oil droplet contains a single DNA template attached to a
single primer-coated bead that then forms a clonal colony.
The sequencing machine contains many picolitre-volume
reactions areas, each containing a single bead and sequencing enzyme. Pyrosequencing uses luciferase to generate
light for detection of the individual nucleotides added to
the nascent DNA, and the combined data are used to
generate sequence readouts. For studies in which the
taxonomic identification of biological aerosols is anticipated, the amplified sequences must have a minimum
length to enable differentiation at the genus or species
level. Often, this minimum length is around 6001000 bp
(base pairs). In traditional sequencing, this length can be
reached easily, whereas in high throughput sequencing the
length of the different sequences is usually only around
300400 bp. Thus, with current high-throughput techniques, it is often not possible to identify biological aerosol
particles on a species or genus level.
4
Provided by NCBI http://blast.ncbi.nlm.nih.gov/Blast.cgi, 28
March 2011.
26
V. R. DESPRÉS ET AL.
3.3.1.6. Hybrid and chip technology: Microarrays can be
used for the characterization of PBAP (Wilson et al., 2002;
Brodie et al., 2007; Georgakopoulos et al., 2009). Species
or group specific probes (e.g. bacterial 16S rRNA genes of
DNA; Loy and Bodrossy, 2006) are fixed on glass slides.
DNA from atmospheric samples is fluorescently labelled
and can hybridise with the DNA on the microarray if
complementary sequences exist in the microarray. The
sequence is determined from the position of the fluorescence on the chip. This technology was recently used on
atmospheric aerosol samples for bacterial 16S rRNA genes
(Wilson et al., 2002; Brodie et al., 2007). Both studies
compared the cloning and sequencing method with microarray technology that was found to be more sensitive in
detecting bacterial taxa.
3.3.2. Optical methods. Most of the above-mentioned
methods for detecting PBAP are limited to offline analyses
that can be time consuming, costly and which often provide
measurements that suffer from poor time resolution (hours/
days). However, much effort has been invested in the last
decades, largely by military research facilities interested in
quick detection of bio-warfare agents, to be able to detect
biological aerosols in real time and with high time
resolution. However, a comprehensive review of all modern
methods for PBAP detection is well beyond the scope of
this text and the following section is intended to present an
overview of the most important classes of techniques. It
focuses on field-based techniques, although some techniques that are primarily laboratory based are also discussed,
as they may have important relevance to ambient detection.
3.3.2.1. On-line autofluorescence methods: All biological
materials contain fluorophores that may be helpful for
identification. Among most existing instruments that utilise
biological auto-fluorescence for online determination of
biological aerosol particle concentration, the choices of
wavelength for the excitation source can generally be
classified into one of two regions. Sources that provide
light in the region of approximately 350370 nm enable
detection of reduced pyridine nucleotides (e.g. NAD(P)H)
and riboflavin that are biological molecules linked to
cellular metabolism (Harrison and Chance, 1970; Eng
et al., 1989; Kell et al., 1991; Li et al., 1991; Iwami et al.,
2001). Detection of auto-fluorescence under these conditions may indicate the presence of viable biological material
in the aerosol particles, although other biological molecules
(e.g. chlorophyll, cellulose) can also auto-fluoresce under
many environmental conditions. The second region of
fluorescence excitation commonly utilised by biological
aerosol instrumentation is approximately 260280 nm and
highlights amino acids, such as tryptophan, tyrosine and
phenylalanine that are present in all proteins (e.g. Teale
and Weber, 1957; Pöhlker et al., 2011).
Thus, it can be broadly stated that detection of
fluorescence by this class of instruments allows determination of fluorescent biological aerosol particles (FBAP).
However, different instrument designs measure and report
different fractions of the PBAP and comparisons across
instruments should be conducted with this in mind. Among
the uncertainties involved is the possibility that material of
non-biological origin will also fluoresce within a given
particle, causing a positive artifact. However, non-biological particles producing such artefacts are unlikely to
contribute significantly to the coarse (1 mm) fraction of
ambient particulate mass (Huffman et al., 2010) and may
also exhibit much weaker fluorescence than biological
particles. For example, results of a study performed in
remote Amazonia indicated that coarse FBAP closely
approximated PBAP concentrations and size distributions
(Pöschl et al., 2010). It is also known that not all biological
microorganisms or fractions will fluoresce under the
experimental conditions of such instruments, and opaque
or absorbing PBAP are likely to fluoresce only very weak at
best (Pöhlker et al., 2011). The weak fluorescence of some
PBAP suggests that fluorescence measurements underestimate the total biological material present. Further
investigation will be required to achieve full understanding
of the response of fluorescence-based biological aerosol
particle detectors to all types of biogenic aerosol particles,
and to quantify potential interferences by fluorescence of
non-biological particles. However, our present understanding is that FBAP can generally be regarded as an
approximate lower limit for the actual abundance of
PBAP (Huffman et al., 2010).
The Ultraviolet Aerodynamic Particle Sizer5 (UV-APS)
was the first commercially available, fluorescence-based
instrument for real-time analysis of biological aerosols
(Hairston et al., 1997; Brosseau et al., 2000). The UV-APS
measures the aerodynamic diameter and side scatter
parameter (analogous to the optical diameter) of incoming
particles by measuring their time-of-flight between two
lasers (633 nm) and then detects fluorescence in the
wavelength range of 420575 nm after excitation by a
pulsed ultraviolet laser (Nd:YAG, 355 nm). An example of
UV-APS measurement data is given in Fig. 4. This shows
time series and size distributions of FBAPs detected with a
UV-APS at a site in central Europe (Mainz, Germany,
October 2006). The figure highlights the ability of the UVAPS to measure FBAP size distributions of discrete particle
events with much higher time and size resolution than is
5
UV-APS; TSI Inc., Model 3314, St. Paul, MN
PRIMARY BIOLOGICAL AEROSOL PARTICLES IN THE ATMOSPHERE
10
-2
10
-4
NF,c
NF,c / NT,c
-3
dNF/dlogDa (cm )
4
0
0.04
0.08
0.12
10
Da (µm)
2
10
6
3
1
-1
Mean
Median
0.25
-3
10
Period 6: 11 Oct. 2006 07:01 - 14:51
dNF/dlogDa (cm )
-3
NF,c (cm )
10
0.3
0
NF,c / NT,c (%)
10
27
th
25 - 75 Percent.
th
5 - 95 Percent.
0.2
0.15
0.1
0.05
2
1
0
6
00:00
06:00
12:00
18:00
24:00
11 October 2006
5
6 7 8 9
2
3
4
1
5 6 7 8 9
2
10
(µm))
Da (µ
Fig. 4. Characteristic time series and number size distribution of fluorescent biological aerosol particles (FBAPs) measured with an ultraviolet aerodynamic particle sizer (UV-APS) in central Europe (Mainz, Germany, October 2006). The peaks at 1.5, 3 and 13 mm can
be attributed to bacteria, fungal spores, and pollen. NF,c is the number concentration of FBAPs, and NT,c is the number concentration of
total aerosol particles with aerodynamic diameters Da 1 mm; dNF/dlogDa is the number size distribution function of FBAPs (Huffman
et al., 2010).
achievable by most traditional sampling and detection
methods (Huffman et al., 2010).
The Wide Issue Bioaerosol Spectrometer (WIBS) is also
available in limited commercial production and not only
provides conceptually similar information to the UV-APS
but also provides a rough estimate of particle sphericity
(Kaye et al., 2000, 2005). Incoming particles are first
optically sized by measurement of scattered laser light.
UV pulses at 280 and 370 nm from a xenon flash lamp
excite each particle, and multiple bands of fluorescent
emission in the range of 310400 nm (for 280 nm
excitation) and 420650 nm (for 280 and 370 nm excitation) are recorded.
A number of other instruments have been developed for
military research use and have not been commercialised or
widely used for measurements published within peerreviewed literature. However, these technical and scientific
developments have been significant contributions to the
scientific community (e.g. Hill et al., 1995; Cheng et al.,
1999; Reyes et al., 1999; Seaver et al., 1999; Kopczynski
et al., 2005; Cabredo et al., 2007; Campbell et al., 2007;
Manninen et al., 2008; Pan et al., 2009; Sivaprakasam
et al., 2009).
Although the development of such instruments has left a
detailed trail in publically accessible military reports and
peer-reviewed literature, ambient measurements by such
techniques have been less frequently documented or declassified. An early generation UV-APS (Ho, 2002) was
used for short periods to measure background FBAP
concentrations at several military locations within Canada
and Sweden (Ho and Spence, 1998; Ho et al., 2004), and a
different LIF spectrometer design was utilised for detection
of FBAP in ambient air in several US locations (Pinnick
et al., 2004; Pan et al., 2007; Pan et al., 2009). Recently,
fluorescence measurements of biological aerosols have also
been reported in more detail for tropical rainforest air
(Prenni et al., 2009; Gabey et al., 2010; Pöschl et al., 2010)
as well as in two urban European locations (Huffman
et al., 2010; Gabey et al., 2011).
3.3.2.2. Flow cytometry: Flow cytometry has also long been
an important tool in the investigation of ambient PBAP.
Among the papers that report successful applications of
flow cytometry to real-time investigation of biological
aerosol are those by Sincock et al. (1999), Chen and Li
(2005) and Chen and Li (2007). Fluorescent in situ
hybridization (FISH) flow cytometry has been used by a
number of groups to characterise airborne bacteria and
aerosolised byproducts (e.g. Lange et al., 1997). Using a
flow, cytometric system (Ho and Fisher, 1993) investigated
Bacillus subtilis bacterial spores, and Prigione et al. (2004)
developed a flow cytometer that could be selectively
applied to the investigation of airborne fungi.
3.3.2.3. LIght Detection And Ranging (LIDAR) and remote
sensing: The LIght Detection And Ranging (LIDAR)
technique has been utilised to quickly and remotely
monitor the presence of PBAP over a larger spatial range.
A LIDAR system (Evans et al., 1994) was operated to
determine its sensitivity to aerosolised Bacillus subtilis
spores, and subsequent efforts have investigated LIDAR
performance for PBAP detection in more detail (e.g.
Simard et al., 2004; Glennon et al., 2009). The detection
of fluorescent ambient aerosol was reported for the first
time using a LIDAR system (Immler et al., 2005), attributing the signals to a combination of PAH-containing
28
V. R. DESPRÉS ET AL.
particles and/or PBAP. Furthermore, it was shown (Sassen,
2008) that pollen can generate strong laser depolarisation
in LIDAR backscatter during Alaskan springtime measurements and suggested that pollen plumes may be mistaken
for upper cirrus clouds and therefore introduce important
errors into identifying aerosols in the atmosphere. Atmospheric optical phenomena caused by pollen also have been
reported,6 and will be discussed briefly in Section 5.
3.3.2.4. Fluorescent and Raman spectroscopy: Fluorescent
properties of collected biological aerosols have been widely
used for assessment of concentrations and properties of
ambient PBAP. Fisar et al. (1990) showed that fluorescence
detected from dyed biological aerosol particles could be
effectively scaled to more traditionally measured CFUs.
Raman spectroscopy has been used for investigation and
characterisation of individual pollen grains in a number of
different manners by various groups (Laucks et al., 2000;
Boyain-Goitia et al., 2003; Kano and Hamaguchi, 2006;
Schulte et al., 2008). A particularly interesting technique
utilised fluorescence measured from particles impacted on a
surface as a pre-selector, before Raman spectroscopy
enabled bacterial identification in more detail (Rosch
et al., 2006). Surface-enhanced Raman spectroscopy has
also been employed to sensitively detect and characterise
pollen and bacteria after injection into a silver suspension
(Sengupta et al., 2005, 2006, 2007). Raman microscopy has
been utilised by Ivleva et al. (2005) for the chemical
investigation and discrimination of ambient PBAP. They
used a combination of Raman microscopy with multivariate analyses to characterise sampled pollen with the
goal of differentiating between allergenic species.
3.3.2.5. Additional optical methods: While the classes of
optical techniques mentioned have been most commonly
utilised for biological aerosol analysis, a review of the
literature highlights the virtually endless list of techniques
that have been and could be applied. Among notable
additional efforts include the use of X-ray fluorescence
(Pepponi et al., 2004) and total internal reflection fluorescence microscopy (TIRFM) (Axelrod, 2008) for the investigation of biological aerosol properties. Infrared
vibrational spectroscopy has also been widely used for
pollen identification (Pappas et al., 2003; Gottardini et al.,
2007; Dell’Anna et al., 2009; Zimmermann, 2010). Scanning electron microscopy (SEM) has been particularly
useful at the investigation of PBAP, allowing a close look
at the morphology and surface of particles (Karlsson and
Malmberg, 1989; Wittmaack et al., 2005; Coz et al., 2010;
Pöschl et al., 2010; Gilardoni et al., 2011).
6
http://www.atoptics.co.uk/droplets/pollen1.htm, 28 March 2011
A recent study has applied Scanning Transmission X-ray
Microscopy with Near-Edge X-ray Absorption Fine Structure (STXM-NEXAFS) spectroscopy to the study of PBAP
(Pöhlker, personal communication). This technique allows
the structural examination of particles with a resolution
down to about 30 nm, combined with spatially resolved
chemical characterisation. It is suitable for the determination
of the major elements, carbon, nitrogen and oxygen, as well
as some minor elements, e.g. iron and chlorine. In addition to
the measurement of elemental abundances, it can also yield
information on the bonding state of the various elements.
Using STXM-NEXAFS, Pöhlker (personal communication) could show that the coarse fraction of the Amazonian
aerosol consisted predominantly of intact PBAP.
3.3.3. Non-optical methods. Several reviews of modern
techniques of biological aerosol detection and analysis have
been published (Spurny, 1994; Ho, 2002; Douwes et al.,
2003; Lim et al., 2005; Kuske, 2006) and so, again, only
highlights of important classes of non-optical modern
techniques will be discussed here.
3.3.3.1. Mass spectrometry: Advances in mass spectrometry (MS) have been utilised in many areas of physical
and biological science in the last decades to provide
detailed information about chemical composition. The
analysis of biological aerosols has been no different, and
many different MS techniques have been employed for
PBAP characterisation. Matrix-Assisted Laser Desorption
Ionization Time-Of-Flight (MALDI-TOF) has been successfully applied in several PBAP studies (Kim et al.,
2005; van Wuijckhuijse et al., 2005; Kleefsman et al.,
2008; Russell, 2009). Parker et al. (2000) developed an
instrument that utilised ion-trap mass spectrometry for
detection and analysis of pollen, bacteria and other
aerosol types. Stowers et al. (2006) demonstrated the
utility of laser-induced fluorescence as a pre-selector
before more detailed MS identification. Lawrence Berkeley National Lab has also utilised a similar concept for its
biological aerosol mass spectrometry (BAMS) instrument
(e.g. Fergenson et al., 2004) and has deployed the instrument in a number of field locations. Other real-time MS
instruments designed primarily for other aerosol-related
detection purposes have also been applied to PBAP
characterisation. For example, an Aerodyne Aerosol
Mass Spectrometer (AMS) was deployed in Amazonia,
Brazil and was able to detect molecular ion markers in
submicron aerosol consistent with the presence of biological aerosols (Chen et al., 2009; Pöschl et al., 2010;
Schneider et al., 2011). Pratt et al. (2009) utilised an
Aerosol Time-of-Flight Mass Spectrometer (ATOFMS) to
detect the presence of biological aerosols as ice nuclei
PRIMARY BIOLOGICAL AEROSOL PARTICLES IN THE ATMOSPHERE
during some flights of an aircraft campaign in the
Western United States. While not technically a mass
spectrometer, both Dworszanski (1997) and Snyder et al.
(2001) report development of automated instruments that
utilise pyrolysis-gas chromatography in front of an ion
mobility spectrometer for rapid detection of biological
aerosol particles in the field.
3.3.3.2. Breakdown spectroscopy: Many groups have also
utilised different types of breakdown spectroscopy (BS) to
identify elemental composition as means of biological
aerosol detection and analysis, although these have not
been as widely applied to ambient measurements. Laserinduced breakdown spectroscopy (LIBS) has easily been
the most common form of BS method and has been
employed to characterise pollen (Boyain-Goitia et al.,
2003), and fungal spores (Hybl et al., 2003), bacteria
(Morel et al., 2003) and a variety of biological aerosol
particle types (Samuels et al., 2003). Other forms of
elemental analysis such as spark-induced breakdown spectroscopy (SIBS), particle-induced X-ray emission (PIXE)
and various forms of combustion analysis have also been
utilised for laboratory study of biological aerosol (Sarantaridis and Caruana, 2010; Schmidt and Bauer, 2010).
3.3.3.3. Miscellaneous non-optical-methods: As has been the
case for recently developed optical methods of biological
aerosol analysis, a large variety of non-optical techniques
of chemical and physical analysis have been employed.
Bioluminescence and chemiluminescence have been extensively explored for potential analytical benefits, and much
of this effort has focused on the detection of ATP within
collected aerosol (e.g. Lee et al., 2008; Seshadri et al., 2009;
Yoon et al., 2010). Electrochemical, immunochemical and
immune biological methods have also been investigated for
ambient PBAP characterisation (Rishpon et al., 1992;
Spurny, 1994; Sarantaridis and Caruana, 2010; Schmidt
and Bauer, 2010). It should be noted here that complementary instruments such as biological aerosol particle
concentrators have also helped enable analyses by a variety
of instruments (e.g. Pan et al., 2004).
4. Atmospheric relevance
4.1. Atmospheric transport of biological particles
Particles in the atmosphere, both biological and nonbiological, are transported primarily together with air
currents, as well as vertically downwards by gravitational
sedimentation and inside of airborne water droplets and ice
crystals. Particles are removed from the air either by
sedimentation and deposition onto the ground and plant
or other surfaces, or through washout by precipitation.
29
Depending on their size and aerodynamic properties, the
average residence time of various biological particles in the
atmosphere can range from less than a day to a few weeks.
We do not attempt a complete review of atmospheric
transport processes and their particular impact on biological aerosols here, but only give a brief overview of some key
research areas. Existing reviews cover aspects of this topic
in more detail (Gregory, 1973; Niklas, 1985; Aylor, 1986;
Nagarajan and Singh, 1990; Brown and Hovmøller, 2002).
Dry deposition (sedimentation and interception/impaction onto surfaces) is the most important removal mechanism for particles tens of microns in diameter or larger. Dry
deposition rates are characterised primarily by the particle’s aerodynamic diameter (diameter of a spherical particle
of unit density with the same terminal velocity in air as the
particle in question (e.g. Hinds, 1999)). Because biological
particles often have complex structure (rough surfaces,
internal pores and asymmetric shape), their physical and
aerodynamic sizes can differ significantly. In particular,
certain fungal spores, pollen and seeds are adapted to be
aerodynamically buoyant, to promote long-range airborne
transport. Observations show that the aerodynamic diameter may be either larger or smaller than the physical
diameter, with considerable variation between species
(Gregory, 1973; Fig. 3, p. 17; Madelin and Johnson,
1992; Reponen et al., 1998; Reponen et al., 2001), and
microorganisms may sometimes be present in the atmosphere in clumps or attached to other particles (Lacey,
1991; Tong and Lighthart, 2000).
For particles 0.110 mm in diameter, washout by
falling precipitation is the most efficient removal mechanism. A single rain event (even a slight drizzle) can efficiently
remove a large percentage of particles from the air in many
circumstances (McDonald, 1962).
In spite of limited differences related to buoyancy and IN
activity, biological particles can be expected, to a good first
approximation, to be transported in the atmosphere similarly to mineral dust and are treated similarly to dust in most
model studies of atmospheric dispersion. Desert dust
particles of a similar size to bacteria-carrying particles are
well known to be transported over long distances, particularly during intermittent dust storms that are visible to
satellites. Biological particles, undistinguishable to satellites,
can be transported over long distance in a similar fashion, as
is borne out by case studies showing marked changes in the
concentration and composition of airborne microorganisms
during some dust transport events (e.g. Bovallius et al.,
1978; Prospero et al., 2005; Jeon et al., 2011); global atmospheric model simulations produce similar results (Burrows
et al., 2009b; Wilkinson et al., 2012).
A wide variety of approaches have been used for
modelling the transport of biological particles on different
spatial scales: Gaussian plume models (distances up to
30
V. R. DESPRÉS ET AL.
100 m; Ganio et al., 1995; Skelsey et al., 2008), Lagrangian stochastic models (Jarosz et al., 2004), regional-scale
models (Helbig et al., 2004; Sofiev et al., 2006) and global
climate and transport models (Burrows et al., 2009b;
Wilkinson et al., 2012). Most studies of the airborne
dispersal of biological particles have focused on the spread
of specific human, animal and plant diseases on the local or
regional scale (Donaldson et al., 1982; Gloster et al., 1982;
Aylor et al., 2003; Isard et al., 2005). Others have addressed the potential for dispersal and cross-fertilization of
GM organisms (Aylor et al., 2003; Jarosz et al. 2004) and
seed dispersal (Nathan et al., 2002).
4.2. PBAP as cloud condensation nuclei
Aerosol particles form the nucleus for the condensation of
cloud droplets, and their number and properties influence
cloud microphysical properties. How active particles are
as cloud condensation nuclei (CCN) depends on their size
and hygroscopicity (Petters and Kreidenweis, 2007). Primary biological aerosol particles are generally assumed to
be efficient CCN, provided that their surfaces are wettable
(Andreae and Rosenfeld, 2008; Ariya et al., 2009). It has
been suggested that the largest PBAP (e.g. pollens grains)
may act as the so-called ‘giant CCN’, i.e. they may form
cloud droplets at lower supersaturations than most other
aerosol particles and quickly grow to large droplet sizes,
thereby facilitating rain formation (Dingle, 1966; Möhler
et al., 2007; Pope, 2010).
Table 5 lists measurements of hygroscopic growth of
bacteria, fungal spores, pollen and algal exudate below
water saturation and shows critical supersaturations that
have been determined for some bacterial species and algal
exudate (exopolymer secretions, EPS). Below the saturation
point of water, hygroscopicity is quantified by the diameter
increase relative to the dry diameter (‘diameter growth
factor’) or by the mass of the water taken up at a certain
relative humidity (RH) compared to the dry mass. The
diameter growth factors (GF) observed for bacteria and
fungal spores are usually modest (GF 1.05 to 1.3 at
RH 98%) compared to those of inorganic salt particles
such as sodium chloride (GF 1.65 at RH 98%) (Lee
et al., 2002). Pollen grains usually show no or only little
increase in geometric size at increasing relative humidities,
but can take up substantial amounts of water, e.g. up to three
times their dry weight at RH 95% (Diehl et al., 2001).
Critical supersaturations for bacteria have been reported
over a wide range between 0.07 and more than 2% (Franc
and DeMott, 1998; Bauer et al., 2003). Algal exudate, which
is mixed into sea spray particles, reduces the hygroscopicity
and CCN activity relative to artificial seawater devoid of
exudate (Wex et al., 2010; Fuentes et al., 2011).
4.3. PBAP as ice nuclei
Cloud water droplets do not freeze directly at 08C but can
remain in a supercooled liquid state down to temperatures
of approximately 388C. At higher temperatures, aerosol
particles are required as ice nuclei to initiate ice formation
via heterogeneous freezing, i.e. the formation of ice germs
by the aid of crystal-like structure elements or other the socalled active sites on the particle surface. If an ice nucleus
(IN) is contained inside a liquid droplet when initiating
freezing, the process is termed ‘immersion freezing’. ‘Condensation freezing’ is a special case of immersion freezing,
in which the CCN of a cloud droplet acts as an IN during
the condensational growth phase. If a supercooled droplet
collides with an aerosol particle and freezes as a result of
the collision, one speaks of ‘contact nucleation’. On dry
particles (‘deposition nucleation’), ice can also form
directly from the vapour phase (Pruppacher and Klett,
1997). Freezing of a relatively small number of cloud
droplets can trigger glaciation, i.e. turning a whole cloud or
a region within a cloud into pure ice. Glaciation is driven
by the different values of the saturation vapour pressure
over supercooled liquid water and over ice, which leads to
depositional growth of the ice crystals at the expense of
evaporating droplets once the relative humidity falls below
water saturation (Wegener-Bergeron-Findeisen process,
Findeisen, 1938). This process is connected to the formation of large crystals that tend to fall out as precipitation.
Furthermore, ice-multiplication processes can occur, in
which additional ice crystals are produced from existing ice
crystals, for example due to the formation of ice splinters
during riming of ice particles (Hallett and Mossop, 1974).
In numerous studies, it has been established that mineral
dust particles are relatively efficient ice nuclei. At lower
temperatures, soot particles also can nucleate ice. Interestingly, the most active IN (those nucleating ice at the highest
subzero temperatures) discovered so far are of biological
origin. Overviews of biological ice nucleation measurements and discussions of their possible implications are
given in previous reviews (Lee et al., 1995; Szyrmer and
Zawadzki, 1997; Möhler et al., 2007; Delort et al., 2010;
DeMott and Prenni, 2010). Here, we summarise the
observational basis of biological ice nucleation seen in
laboratory experiments and, as far as available, in the
atmosphere, including both, historical and recent measurements. With the help of modelling studies, the observations
are put into the context of typical atmospheric concentrations and atmospherically relevant processes.
4.3.1. Laboratory studies of ice nucleation active
biological particles. Since the first ice-nucleating biological
particles were discovered, numerous microorganisms have
Table 5.
Compilation of laboratory measurements of the hygroscopic properties of biological particles (n.a. data not available)
.
Measurements at supersaturation
Critical supersaturation
CCN/CN
ratio
References
Bacteria
Pseudomonas syringae, Erwinia
herbicola
Erwinia carotovora
Arthrobacter agilis
‘‘new species’’
Sphingomonas echinoides
Sphingomonas echinoides fixed
Saccharomonospora viridis
Streptomyces albus
Bacillus subtilis
Pseudomonas syringae
Escherichia coli
Bacillus subtilis
n.a.
3 mm (maximum cellular
dimension)
1.1 mm Dve
1.1 mm Dve
1.2 mm Dve
1.2 mm Dve
1.15 mm Dgma
1.15 mm Dgma
0.94 mm Dmma
0.89 mm Dmma
0.63 mm Da
0.75 mm Da
activation observed
at 0.5%
0.2% to 2.2%
1.3 at 95%
1.09 at 95%
1.22 at 90%
1.15 at 90%
1.34 at 98%
1.16 at 98%
95%
95%
1090%
1090%
2098%
2098%
0.11%
0.11%
0.09%
0.07%
3.3
1.9
2.3
2.5
2.6
1.6
5.1
2.9
2.4
2.1
2.1
1.8
1.15
1.16
1.12
1.06
1.07
1.12
1.08
1.05
1.08
1.07
1.06
1.04
95%
and 98%
and 98%
and 98%
and 98%
and 98%
95%
30100%
30100%
30100%
30100%
30100%
n.a.
Snider et al. (1985)
5 0.5
Franc and DeMott (1998)
1.0390.7
0.8890.5
0.9290.6
0.9990.4
Bauer et al. (2003)
Bauer et al. (2003)
Bauer et al. (2003)
Bauer et al. (2003)
Madelin and Johnson (1992)
Madelin and Johnson (1992)
Johnson et al. (1999)
Johnson et al. (1999)
Lee et al. (2002)
Lee et al. (2002)
Fungal spores
Aspergillus flavus
Aspergillus fumigatus
Cladosporium cladosporioides
Paecilomyces variotii
Penicillium chrysogenum
Penicillium minioluteum
Scopulariopsis brevicaulis
Penicillium brevicompactum
Penicillium melinii
Aspergillus versicolor
Aspergillus fumigatus
Cladosporium cladosporioides
mm
mm
mm
mm
mm
mm
mm
mm
mm
mm
mm
mm
Dgma
Dgma
Dgma
Dgma
Dgma
Dgma
Dgma
Dgma
Dgma
Dgma
Dgma
Dgma
at
at
at
at
at
at
at
at
at
at
at
at
95%
98%
98%
98%
98%
98%
95%
90%
90%
90%
90%
90%
95
95
95
95
95
Madelin and Johnson
Madelin and Johnson
Madelin and Johnson
Madelin and Johnson
Madelin and Johnson
Madelin and Johnson
Madelin and Johnson
Reponen et al. (1996)
Reponen et al. (1996)
Reponen et al. (1996)
Reponen et al. (1996)
Reponen et al. (1996)
(1992)
(1992)
(1992)
(1992)
(1992)
(1992)
(1992)
PRIMARY BIOLOGICAL AEROSOL PARTICLES IN THE ATMOSPHERE
Species
Measurements at subsaturation
Diameter, Dve volume
equivalent, Dgma geometric
mass aerodynamic, Dmma
RH at which
Maximum
mass median aerodynamic, growth factor at hygroscopic growth was
Da aerodynamic
measured
RH
31
32
Table 5 (Continued )
.
Species
Measurements at subsaturation
Diameter, Dve volume
equivalent, Dgma geometric
mass aerodynamic, Dmma
RH at which
Maximum
mass median aerodynamic, growth factor at hygroscopic growth was
Da aerodynamic
measured
RH
n.a.
Ambrosia artemisiifolia
20 mm
various pollens (deciduous trees,
conifers and grasses)
22 to 115 mm
Daffodil, water birch and pussy
willow pollens
25 mm (birch pollens)
Mass increase by
up to a factor of
2
Effective density
increase: 1.52 at
93100%, no
geometric growth
Mass increase by
up to a factor of
4 at 95%
Mass increase by
up to a factor of
1.3 at 85%
Critical supersaturation
CCN/CN
ratio
‘very dry’ to ‘moist’
Durham (1943)
11100%
Harrington and Metzger (1963)
73 and 95%
Diehl et al. (2001)
References
2 85%
50.002% (calculated)
Pope (2010)
4592%
0.1 to 0.5% for sizes
between 40 and 105 nm
Fuentes et al. (2011)
7599%
0.1 to 0.4% for diameters
between 40 and 100 nm
Wex et al. (2010)
Algal exudates (extracellular polymeric substances, EPS)
Artificial seawater with
diatomaceaous and
nanoplancton exudates
40105 nm
Artificial seawater with exudate of
four different algal species
25500 nm
2.5 at 92%,
lower than for
artificial
seawater devoid
of exudates
4 at 99%,
lower than for
artificial
seawater devoid
of exudates
V. R. DESPRÉS ET AL.
Pollen
various ragweed, amaranthchenopod and grass pollens
Measurements at supersaturation
PRIMARY BIOLOGICAL AEROSOL PARTICLES IN THE ATMOSPHERE
been screened for ice nucleation activity. A selection of
results is summarised in Table 6. Listed are the highest
temperatures at which ice nucleation was observed, which
are often cited as key findings of the experiments. Equally
important is the fraction of ice-nucleating particles to total
particles because often the apparent freezing onset depends
on the particle concentration (Yankofsky et al., 1981). For
many biological species, only a small fraction of the total
particles (i.e. in the case of bacteria: cells) actually nucleates
ice, even at relatively low temperatures. Nevertheless, the
entire species or strain is referred to as ‘ice nucleation
active’ (INA). The IN number fractions at different
temperatures, as far as they are available from the
experiments in Table 6, are displayed in Fig. 5.
Many studies listed in Table 6 used biological particles
sampled not from the atmosphere, but from plants, lichens,
soils, ocean water and insect guts. Some of them were
cultivated under favourable conditions being tested for IN
activity. It can thus be questioned whether the investigated
samples are representative of biological aerosols. Most
studies employ the so-called droplet freezing assay with
rather large volumes (several ml) of particle suspensions
(thus testing for immersion freezing). Only a few experiments employ atmospherically relevant droplet sizes (e.g.
Möhler et al., 2008) or test for other nucleation modes (e.g.
Levin and Yankofsky, 1983).
Among bacterial ice nucleators, Pseudomonas syringae is
the most common. Other INA species include Pseudomonas
fluorescens and Erwinia herbicola. In general, not all strains
within a species are INA, and also within the INA strains,
the fraction of ice-nucleating cells varies significantly
(Hirano and Upper, 1995). Active number fractions
between 10 8 and close to 1 are reported, and the onset
of ice nucleation can be seen at temperatures between 2
and 108C (Table 6 and Fig. 5). Species with intermediate
IN activity begin ice nucleation only at lower temperatures
(e.g. Mortazavi et al., 2008).
A number of fungi (both free living and lichen fungi) were
found to nucleate ice at temperatures comparable to INA
bacteria (Table 6), some even at 18C. Fungal spores,
which are more likely to become airborne than other parts of
the fungal thallus, have been observed to nucleate ice at
lower temperatures ( 10 to 28.58C, Jayaweera and
Flanagan, 1982; Iannone et al., 2011). Lichen photobionts
(algae or cyanobacteria) are in general less efficient IN than
the corresponding lichen fungi (Kieft and Ahmadjian,
1989).
Pollen of various plant species have been shown by a
number of studies (Diehl et al., 2001, 2002; von Blohn
et al., 2005) to nucleate ice starting at temperatures around
108C (Table 6). Very high active fractions (up to 1.0) can
be reached at 188C (Diehl et al., 2001). Other biological
materials, such as algae, leaf litter and plankton initiate
33
freezing at temperatures comparable to bacteria and fungi.
IN numbers are usually given in relation to the mass of the
bulk material, which is of only limited relevance for
atmospheric applications, where particle surface area and
number fractions matter.
Also shown in Fig. 5 are ice nucleating number fractions
for mineral dust particles of atmospherically relevant sizes
(median diameters of 0.21 mm) in the immersion freezing
mode (Niemand, personal communication). The observed
ice nucleating fractions for dust range from about 10 4 to
10 2 at temperatures between 15 and 288C. Larger dust
particles (not shown) exhibit larger ice-nucleating number
fractions because ice nucleation is proportional to the
particle surface area. Conen et al. (2011) showed that soil
with high organic content exhibits higher IN activity than
montmorillonite and postulate that ice active proteins in the
soil from fragments of decaying biological material are likely
the cause. The atmospheric importance of different INA
materials depends not only on their ice-nucleating fractions
that are shown in Fig. 5 but also on their number concentrations at cloud altitudes and the prevailing environmental
conditions (e.g., temperature and humidity).
4.3.2. Observation of biological ice nuclei in the
atmosphere. The plant pathogenic bacteria Pseudomonas
are frequent in the biosphere, and Pseudomonas bacteria
are also frequently found as airborne particles or in cloud
droplets (e.g. Fuzzi et al., 1997; Amato et al., 2005, 2007a,
2007c). However, in these studies, the ice nucleation
activity of the isolated Pseudomonas strains was not
determined. Little is known about the atmospheric abundance of INA lichen and fungal spores. Pollen, for which
ice nucleation activity seems to be a common property of
many species, can reach peak concentrations on the order
of several per litre during the pollination season (Vogel
et al., 2008).
Direct observations of the involvement of biological
particles in cloud ice and precipitation formation are difficult
to obtain. The presence (or absence) of INA biological
particles in the air, cloud condensate or precipitation can
give some indications on their role in the atmosphere. Such
observations are discussed in the following section.
Kumai (1961) found indirect evidence of the possible
involvement of biological particles in atmospheric ice
nucleation by microscopically identifying bacteria at the
centre of 3 out of 307 examined snow crystals. In the
pioneering studies by Maki and Willoughby (1978) and
Sands et al. (1982), ice-nucleating bacteria were isolated
from rain and snow. Some were even sampled at altitudes
up to 2500 m above ground (Sands et al., 1982). Jayaweera
and Flanagan (1982) and Lindemann et al. (1982) were the
first to determine the ice nucleation activity of biological
34
Table 6.
Compilation of laboratory measurements of the IN properties of biological particles (n.a. data not available)
Species
Highest T,8C where INA
observed
Highest observed
Freezing mode (Immersion
active
Active number fraction or
fraction and corresponding freezing If, Contact freezing Ctf,
active IN per unit mass
Condensation freezing Cdf)
temperature
at highest INA temperature
References
Bacteria isolated from air or precipitation
Bacteria isolated from air other habitats (list
not exhaustive)
Pseudomonas syringae
Pseudomonas syringae, different strains
Pseudomonas syringae strain 31R1
Pseudomonas syringae
Pseudomonas viridiflava/Pseudomonas
syringae mixture
Pseudomonas syringae isolated from
decaying alder leaves (Alnus tenuifolia)
Pseudomonas sp. isolated from the guts of
sub-Antartic beetles
Pseudomonas Antarctica
Erwinia herbicola
Erwinia herbicola, cell-free centrifuged
suspensions
M1
M1
10
0.02
0.94 (T 168C)
If
4
0.05
1 (T 188C)
If
9
0.1
n.a.
If
Maki and Willoughby
(1978)
Jayaweera and
Flanagan (1982)
Jayaweera and
Flanagan (1982)
Sands et al. (1982)
4
n.a.
n.a.
If
10
n.a.
n.a.
If
Lindemann et al.
(1982)
5
n.a.
n.a.
If
21 to 29
n.a.
n.a.
If
Constantinidou et al.
(1990)
Ahern et al. (2007)
n.a.
If
Morris et al. (2008)
n.a.
If
Mortazavi et al.
(2008)
5×10 5 (T 158C)
n.a.
0.5 (T 128C)
n.a.
n.a.
If
If
If
If/Cdf
If/Cdf
2 to 6
13 to 18
5
5
1
891
9.7
10
7
n.a.
2×10 6
0.0043 to 10 7
10 8
0.0032
0.005
Vali et al. (1976)
Gross et al. (1983)
Lindow et al. (1989)
Möhler et al. (2008)
Möhler et al. (2008)
3
10 6
0.01(T 208C)
If
Maki et al. (1974)
3.4
10 6
n.a.
If
0.2 (T 108C)
n.a.
n.a.
If
If/Cdf
If
Worland and Block
(1999)
Obata et al. (1999)
Möhler et al. (2008)
Phelps et al. (1986)
0.01 (T 108C)
If
n.a.
Ctf
4
991
3
3
3
10
7
0.0007
n.a.
10 6
n.a.
Yankofsky et al.
(1981)
Levin and Yankofsky
(1983)
V. R. DESPRÉS ET AL.
Pseudomonas fluorescens isolated from
leaves, lake/stream water and/or snow
Unidentified microbacterium isolated from
air above the Arctic Ocean
Pseudomonas sp. isolated from air above the
Arctic Ocean
Pseudomonas syringae isolated from rain and
hail
Pseudomonas syringae and Erwinia herbicola
isolated from air above plant canopies and
bare soil
Pseudomonas syringae isolated from air and
rainwater sampled over a soybean field
Pseudomonas sp. isolated from cloud and
rain water
Pseudomonas syringae isolated from rain,
snow, alpine streams, lakes and wild
plants
Microbacterium, Xanthomonas, Bacillus,
Acinetobacter, Luteimonas,
Stenotrophomonas and unspecified
bacteria isolated from snow
Table 6 (Continued )
Species
M1
Snomax
Snomax
INA bacteria on oat leaves
several representative Arctic and Antarctic
sea-ice bacterial isolates
n.a.
3
n.a.
n.a.
n.a.
4×10
5.6
4
0.01
1.3×1012 g 1
5.3
26, Rhi 11696%
n.a.
0.0010.01
10 7
n.a.
2.5
40 to 42
Lichens
Rhizoplaca chrysoleuca (the most active of 15
investigated lichen species)
Psora decipiens (the least active of 15
investigated lichen species)
18 lichen mycobionts
4.1 to 10
Lecanora dispersa (lichen fungus)
103 g 1, grinded material
8
103 g 1, grinded material
(T 108C)
0.23 (T 8918C)
5.5 ×1012 g 1 (T 128C)
n.a.
n.a.
0.008 (T B 48C)
n.a.
If
If
If/Cdf
Cdf
If
Deposition nucleation (no
experiments at warmer T)
If
If
Levin and Yankofsky
(1983)
Ponder et al. (2005)
Möhler et al. (2008)
Ward and DeMott
(1989)
Wood et al. (2002)
Chernoff and Bertram
(2010)
Hirano et al. (1985)
Junge and Swanson
(2008)
If
Kieft (1988)
If
Kieft (1988)
n.a.
108 g 1 (T 3C), grinded
material
105 g 1 (T 12 8C),
grinded material
n.a.
If
4.2
104 g 1
7×107 g 1 (T 8 8C)
If
Cladonia cristatella (lichen fungus)
6.3
106 g 1
5×106 g 1( (T 12 8C)
If
Ascospora fuscata (lichen fungus)
9.1
2×104 g 1
2×105 g 1 (T 128C)
If
Kieft and Ahmadjian
(1989)
Kieft and Ahmadjian
(1989)
Kieft and Ahmadjian
(1989)
Kieft and Ahmadjian
(1989)
Kieft and Ahmadjian
(1989)
Kieft and Ahmadjian
(1989)
Kieft and Ahmadjian
(1989)
Kieft and Ahmadjian
(1989)
Kieft and Ahmadjian
(1989)
Henderson-Begg et al.
(2009)
Rhizoplaca chrysoleuca (lichen fungus),
different clones
13 lichen photobionts
2.3
7
References
4.6 to 4.8
5.1 to 16
4
5
10 to 2×10 g
1
4
2×10 g
Trebouxia erici (lichen photobiont)
9.2
6×105 g 1
Unspecified lichen fragments from Norway,
Faroe Islands, Ethiopia, UK, Australia,
Antartica
5.1
Fungi
Penicillium digitatum spores isolated from air
1
4
6×10 g
(T 128C)
1
n.a.
6×10 g
(T 128C)
106 g 1 (T 128C)
6
10 g
1
If
If
If
If
(T 128C)
If
n.a.
If
10
0.01
n.a.
If
15
0.01
n.a.
If
Jayaweera and
Flanagan (1982)
Jayaweera and
Flanagan (1982)
35
Cladosporium herbarum spores isolated from
air
4
2×10 g
n.a.
1
9.1
6
1
n.a.
Trebouxia incrustata (lichen photobiont)
Trebouxia sp. (lichen photobiont)
7
PRIMARY BIOLOGICAL AEROSOL PARTICLES IN THE ATMOSPHERE
Flavobacterium sp., Psychrobacter sp., and
Sphingomonas sp. isolated from
permafrost soil
Snomax
Snomax
Highest T,8C where INA
observed
Highest observed
Freezing mode (Immersion
active
Active number fraction or
fraction and corresponding freezing If, Contact freezing Ctf,
active IN per unit mass
Condensation freezing Cdf)
temperature
at highest INA temperature
36
Table 6 (Continued )
Species
Highest T,8C where INA
observed
Highest observed
Freezing mode (Immersion
active
Active number fraction or
fraction and corresponding freezing If, Contact freezing Ctf,
active IN per unit mass
Condensation freezing Cdf)
temperature
at highest INA temperature
References
Penicillium notatum spores isolated from air
22
0.01
n.a.
If
Penicillium frequentes spores isolated from
air
Rhizopus stolonifera spores isolated from air
22.5
0.01
n.a.
If
23
0.01
n.a.
If
1011 g 1 (T 108C)
n.a.
n.a.
If
If
If
Jayaweera and
Flanagan (1982)
Jayaweera and
Flanagan (1982)
Jayaweera and
Flanagan (1982)
Pouleur et al. (1992)
Pouleur et al. (1992)
Tsumuki et al. (1992)
2.5
5
5
105 g 1
n.a.
n.a.
1
n.a.
n.a.
If
Richard et al. (1996)
1
n.a.
n.a.
If
Richard et al. (1996)
0.002
0.2 to 1 (T 358C)
If
Iannone et al. (2011)
0.1
n.a.
n.a.
n.a.
0.9 (T 188C)
n.a.
n.a.
0.98 (T 188C)
n.a.
n.a.
0.5 (T 188C)
n.a.
n.a.
0.8 (T 188C)
n.a.
n.a.
n.a.
Cdf
If
Ctf
Cdf
If
Ctf
Cdf
If
Ctf
Cdf
If
Ctf
If
28.5
Pine pollen
Pine pollen
Pine pollen
Birch pollen
Birch pollen
Birch pollen
Oak pollen
Oak pollen
Oak pollen
Grass pollen
Grass pollen
Grass pollen
Alder pollen
8
16
12
8
10
6
8
14
10
8
14
10
10
Alder pollen
10
n.a.
n.a.
Ctf
Lombardy poplar pollen
18
n.a.
n.a.
If
Lombardy poplar pollen
14
n.a.
n.a.
Ctf
Redtop grass pollen
16
n.a.
n.a.
If
Redtop grass pollen
16
n.a.
n.a.
Ctf
Kentucky blue pollen
14
n.a.
n.a.
If
Kentucky blue pollen
10
n.a.
n.a.
Ctf
Various pollen, including crushed pollen
no IN observed
n.a.
n.a.
0.04
n.a.
n.a.
0.03
n.a.
n.a.
0.02
Deposition nucleation
Diehl et al. (2001)
Diehl et al. (2002)
Diehl et al. (2002)
Diehl et al. (2001)
Diehl et al. (2002)
Diehl et al. (2002)
Diehl et al. (2001)
Diehl et al. (2002)
Diehl et al. (2002)
Diehl et al. (2001)
Diehl et al. (2002)
Diehl et al. (2002)
von Blohn et al.
(2005)
von Blohn et al.
(2005)
von Blohn et al.
(2005)
von Blohn et al.
(2005)
von Blohn et al.
(2005)
von Blohn et al.
(2005)
von Blohn et al.
(2005)
von Blohn et al.
(2005)
Diehl et al. (2001)
V. R. DESPRÉS ET AL.
Fusarium avanaceum
Fusarium acuminatum
Fusarium sp. isolated from the guts of insect
larvae
Fusarium oxysporum (12 out of 42 isolates,
from plants)
Fusarium tricinctum (8 out of 14 isolates,
from plants and soil)
Cladosporium spores
Pollen
Species
Highest T,8C where INA
observed
Highest observed
Freezing mode (Immersion
active
Active number fraction or
fraction and corresponding freezing If, Contact freezing Ctf,
active IN per unit mass
Condensation freezing Cdf)
temperature
at highest INA temperature
Algae
25 algae species isolated from Antarctic soils 5 (-8 for 4 out of 25 species)
n.a.
n.a.
If
Seaweed (8 species)
7
n.a.
n.a.
If
Leaf litter
Poplar mulch
5
105 g 1
5×109 g 1 (T 158C)
If
Sage leaf litter
6
103 g 1
107 g 1 (T 178C)
If
Green poplar leaves
9
2×102 g 1
2×104 g 1 (T 178C)
If
Leaf litter of several trees and grasses in
tropical climate zones
Leaf litter of several trees and grasses in
humid mesothermal climate zones
Leaf litter of several trees and grasses in
humid microthermal climate zones
Tea leaf litter
7
102 g 1
4×104 g 1 (T 188C)
If
6
102 g 1
4×108 g 1 (T 238C)
If
Plankton
Cachonina Niei
Ochromonus danica and Porphyridium
aerugineum
Unspecified mixture of 95% phytoplankton,
5% zooplankton and associated debris
4
2
10 g
1
10
4×10 g
1
(T 228C)
If
References
Worland and
Lukesova (2000)
Lundheim (1997)
Schnell
(1972)
Schnell
(1972)
Schnell
(1972)
Schnell
(1976)
Schnell
(1976)
Schnell
(1976)
Schnell
Schnell
and Vali
and Vali
and Vali
and Vali
and Vali
and Vali
5
102 g 1
5×104 g 1 (T 128C)
If
3
102 g 1
1 (T 148C); 106 g 1
(T 108C)
n.a.
If
Schnell (1975)
If
Schnell (1975)
106 g 1 (T 108C)
If
Schnell and Vali
(1975)
15
3.5
n.a.
102 g 1
and Tan(1982)
PRIMARY BIOLOGICAL AEROSOL PARTICLES IN THE ATMOSPHERE
Table 6 (Continued )
37
38
V. R. DESPRÉS ET AL.
Fig. 5. Ice nucleating number fraction fIN at the observed IN onset and maximum activity temperatures from the experiments listed in
Table 6. For comparison, fIN data for immersion freezing on mineral dust (natural soil samples, median diameters of 0.21 mm) are included (M. Niemand, personal communication).
particles sampled directly from the atmosphere. In the
Arctic, two types of bacteria (an unidentified strain and a
Pseudomonas strain) and five fungal spores were observed
with moderate to high ice nucleation activity (Jayaweera
and Flanagan, 1982). Lindemann et al. (1982) found
significant concentrations of INA bacteria at 108C above
different plant canopies and bare soil and identified them
as Pseudomonas syringae and Erwinia herbicola. The INA
bacteria accounted for 04% of the total bacteria.
Constantinidou et al. (1990) isolated Pseudomonas syringae
from rainwater and aerosol samples over a soy bean field
and tested them as INA at 58C. Recently, Morris et al.
(2008) studied Pseudomonas syringae strains isolated from
rain, snow, alpine streams, lakes and wild plants and found
that all the strains isolated from snow showed ice nucleation activity at 2 to 58C, while this property was rare
among the other strains. However, other samples of
bacteria isolated from precipitation exhibited only moderate ice nucleation activity (Ahern et al., 2007; Mortazavi
et al., 2008).
Christner et al. (2008a, b) demonstrated that snow and
rain samples from around the world contain ice nuclei
active at temperatures above 108C. A majority of these
ice nuclei was found to be inactivated through heat
treatment (at 958C) and/or lysozyme digestion, indicating
a probable bacterial and/or proteinaceous origin. The
observed concentrations of warm-temperature ice nuclei
ranged between below 10 and several hundred per litre of
snow/rain water, which is much lower than the estimated
numbers of hydrometers per litre precipitation (Diehl and
Wurzler, 2010; Hoose et al., 2010a). Ice nuclei sampled
from the urban atmosphere (Henderson-Begg et al., 2009),
which were also active at temperatures above 108C, were
not deactivated by lysozyme treatment and heating to
60 8C (but by heating to 90 8C). This was interpreted as an
indication that these ice nuclei were not bacterial, but
rather from lichen or fungi. Also, ice nuclei concentrations
at 108C in air and snow at a high-elevation mountain site
did not correlate with the relative abundances of wellknown INA bacteria species such as Pseudomonas syringae
and Erwinia herbicola (Bowers et al., 2009). It was suggested that ice nucleation at this site was due to other
bacterial species, varying expression of the bacterial icenucleation capacities, or other biological particles.
It can be expected that biological ice nuclei are particularly abundant in regions with active vegetation. Prenni
et al. (2009) investigated aerosol particles sampled above
the canopy in the Amazon forest and inferred that the
majority of the ice nuclei at 258C and warmer were of
biological origin (but absolute concentrations of ice nuclei
at these temperatures were low, on the order of 12 l 1).
Ice nuclei at colder temperatures were in large part
contributed by mineral dust. At cirrus cloud altitude, Pratt
et al. (2009) observed a case of co-occurrence of biological
material with mineral dust after long-range transport:
From mass-spectroscopic measurements of ice crystal
residues in wave clouds, 50% mineral dust particles and
33% biological particles were identified. But, only in one
out of many research flights was a measurable fraction of
biological material observed.
PRIMARY BIOLOGICAL AEROSOL PARTICLES IN THE ATMOSPHERE
In summary, the presently available observations do not
give a consistent picture. The strongest indications of icenucleation activity in clouds are available for bacterial or
fungal ice nucleators. Quantitative measurements are unfortunately rare and cover only anecdotal events. In
particular, more studies quantifying the atmospheric concentrations of INA biological particles in comparison to
other ice-nucleating agents, such as mineral dust and soot,
would be desirable.
4.3.3. Modelling of biological ice nuclei. Numerical
simulations of the effects biological ice nuclei in clouds
began with Levin et al. (1987), who studied the efficiency of
cloud seeding with INA bacteria for precipitation enhancement in a 1.5-dimensional cloud model. Later, Diehl and
Wurzler (2004); Diehl et al. (2006) parameterised freezing of
droplets containing or colliding with unknown amounts of
different biological ice nucleators for a parcel model with
detailed microphysics. In a follow-up study (Diehl and
Wurzler, 2010), the freezing rates were scaled with typical
fractions of droplets containing bacteria, mineral dust and
soot particles, respectively, and it was shown that typical
bacteria concentrations yielded much lower ice crystal
concentrations than typical mineral dust concentrations.
Ariya et al. (2009), in studies with a 1.5-dimensional model of
a convective cloud, and employing INA biological aerosol
concentrations of less than 1 l 1, pointed out that even such
low IN concentrations can trigger cloud glaciation through
ice-multiplication processes. The comprehensive empirical
ice nucleation parameterisation by Phillips et al. (2008)
includes biological material as part of the ‘insoluble organic’
particles. In a cloud-system resolving model, cloud microand macrophysical properties, including precipitation, were
sensitive to variations of the ‘insoluble organic’ aerosol by a
factor of 100 (Phillips et al., 2009). The first global model
studies of the impact of biological particles by Hoose et al.
(2010a), Hoose et al. (2010b) used simple emission parameterisations for bacteria, fungal spores and pollens to
simulate their concentration in the atmosphere. The freezing
rates were derived from classical nucleation theory and
laboratory data (Chen et al., 2008a). The average contribution of biological particles to heterogeneous ice nucleation in
mixed-phase clouds (integrated over all temperature regions
in the troposphere) was calculated to be only 0.00001%, with
an uppermost estimate of 0.6%. Instead, atmospheric ice
nucleation was found to be dominated by mineral dust,
which is also in agreement with recent observations (Choi
et al., 2010; DeMott and Prenni, 2010; DeMott et al., 2010;
Klein et al., 2010). The contribution of biological particles to
ice nucleation in relatively warm cloud layers (above
108C) might be higher but was not quantified in these
studies.
39
In summary, the effect of biological particles as ice nuclei
on clouds and precipitation is strongly dependent on the
atmospheric concentrations of INA species. Most likely,
these concentrations exhibit strong temporal and spatial
variations, and any effect on clouds is therefore likely
seasonal and local in nature. However, more quantitative
observations of INA biological particles in the atmosphere
are necessary to allow better estimates of their effects on
clouds.
4.4. Optical properties
The absorption and scattering of radiation by aerosol
particles are important physical properties that influence
regional and global radiation budgets. Better understanding of the effect that natural aerosols have on the atmosphere is necessary to constrain effects that anthropogenic
influence may have on global climate. Because PBAP can
be a major fraction of aerosol number and surface area in
certain locations, it is possible that they may also affect
climate forcing both directly (by absorbing or scattering
radiation) and indirectly (through cloud processes). Certain
fungal spores and other PBAP classes can be highly
coloured and absorbing, which may increase their direct
influence on the surrounding atmosphere (e.g. Adams
et al., 1968; Troutt and Levetin, 2001). However, there
have been very few studies estimating the direct effect of
PBAP on climate, in part because geographically or
temporally comprehensive PBAP measurements are not
yet available. A theoretical description of the interaction
between electromagnetic radiation and PBAP is difficult
because the Mie theory is only valid for spheres, and thus
many biological aerosol particles cannot be well described
(Bohren and Huffman, 1983).
Some work has been done to directly measure certain
optical properties of PBAP that could be relevant to the
investigation of atmospheric aerosol. Spankuch et al.
(2000) showed that down-welling infrared flux was significantly increased when pine pollen concentrations were
higher, suggesting that emissions of certain pollens may
cause localised atmospheric warming events. Several
groups have shown that pollen can cause visible coronae
around the sun and moon and could therefore influence
local solar radiation properties (Parviainen et al., 1994;
Trankle and Mielke, 1994; Mims, 1998; Schneider and
Vollmer, 2005).
Most work involving the optical properties of PBAP has
used detailed physical measurements in the laboratory and,
as such, has only limited obvious application to the
atmosphere at large. Surbek et al. (2009) characterised
the elastic light scattering of a number of pollen species.
Several groups have made detailed measurements of the
polarisation and scattering properties specific to bacteria
40
V. R. DESPRÉS ET AL.
and other biological aerosol types (Bickel et al., 1976 and
references therein; Bohren and Huffman, 1983; Vandemerwe et al., 1989). Gurton et al. (2001) measured infrared
extinction by bacterial spores. Harding and Johnson (1984)
measured quasi-elastic light scattering, and Gittins et al.
(1999) measured infrared absorption of Bacillus
subtilis bacteria. Yabushita and Wada (1985) performed
IR and UV absorption measurements of E. coli and yeast
organisms.
In view of the much higher abundance of mineral dust
discussed by Hoose et al. (2010b), the influence of
biological material on aerosol optical properties may be
relatively small on global scales. However, on regional
scales PBAP may sometimes have a substantial influence
on the total scattering and absorption of light by aerosols.
Using chemical tracers and multivariate statistical analysis,
Guyon et al. (2004) showed that up to 66% of aerosol mass
and 47% of the light absorption in air over the Amazon
Rainforest were attributable to biogenic particles during
the wet season. During the wet-to-dry transition period,
biogenic particles still accounted for up to 35% of light
absorption, even though there was already a substantial
amount of biomass burning aerosol present. These results
are consistent with many earlier measurements (e.g. Artaxo
et al., 1988, 1998), which showed that biogenic aerosol
makes up a large fraction of the Amazonian aerosol mass
burden, especially in the coarse fraction. In the absence of
definitive identification, earlier studies assumed that it
consisted mostly of PBAP (Andreae and Crutzen, 1997).
This was confirmed with less uncertainty using multiple
techniques by Pöschl et al. (2010), who showed that PBAP
accounted for 67% of the aerosol mass (or volume) of all
particle sizes sampled above the rainforest in a remote
section of Amazonia, Brazil during a time period of very
low influence from airborne mineral dust or anthropogenic
pollution. In addition, biological organisms or material
may often be attached to mineral dust particles and might
also influence the optical properties of these combined
particles. Thus, PBAP need to be considered when modelling local and regional optical properties above and downwind of biologically active regions. Additional direct
atmospheric measurements of light absorption and scattering by biogenic particles will likely be necessary to help
provide suitable model inputs and such measurements are
strongly recommended.
decade, there has been a surge in interest within the
atmospheric community based partly on the development
of new measurement techniques and on studies indicating
that PBAP may play an important role as ice nuclei
influencing the formation of clouds and precipitation.
Depending on the character of the biological particle of
interest, as well as on the scope of the scientific questions
asked, manifold methods are available to study PBAP.
Thus, we have included an overview of current methods for
sampling and analysis of biological aerosols including
traditional and modern techniques.
Further studies of biological aerosols will lead to a better
understanding of their role in climate and atmospheric
processes and will also help to improve understanding of
their impacts on humans. Recently developed and emerging
techniques for sampling and analysing airborne biological
particles have bolstered efforts to understand the properties
of ambient PBAP. However, for better comparison among
different datasets, sampling and analysis techniques have to
be standardised. Efficient and reliable analytical techniques
must be developed for the identification and quantification
of PBAP as well as for the determination of the abundance
and diversity of PBAP and their seasonal variation on
regional and global scales (atmospheric biogeography).
One of the main influences of PBAP on climate and
atmosphere is through the capability of certain PBAP to
function as excellent ice nuclei. Future research should thus
concentrate on the determination of actual emission rates
and optical properties of PBAP and to link results from
laboratory experiments concerning the IN ability of PBAP
to atmospheric measurements.
Global modelling is one of the rising methods to track
and understand the worldwide global distribution of
PBAP. Atmospheric models can estimate the atmospheric
effects of IN active biological aerosol particles on clouds
and help identify targets for experimental research. However, the models need to be constrained and confirmed by
experimental data. Future research should use field and
laboratory data to better constrain numerical models of
PBAP sources, their transformation in the atmosphere and
effects on climate. An important task is the delivery of
larger and more comprehensive datasets from sampling
sites worldwide and their incorporation into atmospheric
models, to ground model efforts in a solid empirical
foundation.
5. Conclusions and outlook
6. Acknowledgements
Scientific investigations of biological aerosol particles in
the atmosphere have a long history going back to the
nineteenth century. Since then, the topic has attracted
attention in various different research areas. In the last
We would like to thank M. Hummel, I. Mueller-Germann,
C. Pöhlker and H. Paulsen for support and the members of
the bioaerosol community for stimulating discussions. This
research was funded in part by the Max Planck Society, the
PRIMARY BIOLOGICAL AEROSOL PARTICLES IN THE ATMOSPHERE
German Research Foundation (DE1161/2-1) and the
LEC Geocycles. C.H. acknowledges support by the President’s Initiative and Networking Fund of the Helmholtz
Association.
STXM
TIRFM
T-RFLP
7. Appendix
AMS
ATOFMS
ATP
BAMS
Bp
BS
CCN
CFU
DAPI
ddNTP
DNA
dNTP
EPS
FBAP
FISH
GF
Hulis
IN
INA
IPCC
ISI
ITS
LDD
LIBS
LIDAR
MALDITOF
MS
NCBI
OC
PBAP
PCR
PIXE
PM
RH
RNA
rRNA
SEM
SIBS
SOA
Aerodyne Mass Spectrometer
TSI Aerosol Time-of-Flight Mass Spectrometer
Adenosine Triphosphate
Bioaerosol Mass Spectrometry
Base Pairs
Break-Down Spectroscopy
Cloud Condensation Nuclei
Colony Forming Units
4.6-diamidino-2-phenylindole
dideoxynucleotidetriphophate
Deoxyribonucleic Acid
deoxynucleotidetriphosphate
Exopolymer Secretions
Fluorescent Biological Aerosol Particles
Fluorescent in-situ hybridization
Growth Factor
Humic Like Substances
Ice Nuclei
Ice Nucleation Active
Intergovernmental panel on climate change
Institute for Scientific Information
Internal Transcribed Spacer
Long Distance Dispersal
Laser-Induced Breakdown Spectroscopy
LIght Detection And Ranging
Matrix-Assisted Laser Desorption Ionization
Time-of-Flight
Mass Spectrometry
National Center for Biotechnology Information
Organic Carbon
Primary Biological Aerosol Particles
Polymerase Chain Reaction
Particle-Induced x-ray Emission
Patriculate Matter
Relative Humidity
Ribonucleic Acid
Ribosomal RNA
Scanning Electron Microscopy
Spark-Induced Breakdown Spectroscopy
Secondary Organic Aerosol
TSP
UV
UV-APS
WIBS
41
Scanning Transmission X-ray Microscopy with
Near-Edge X-ray Absorption Fine Structure
Total Internal Reflection Fluorescence Microscopy
Terminal Restriction Fragment Length Polymorphism
Total Suspended Particles
Ultraviolet Light
Ultraviolet Aerodynamic Particle Sizer
Wide Issue Bioaerosol Spectrometer
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