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L. Pirjola et al., Environ. Chem. 2005, 2, 271–281. doi:10.1071/EN05075
Modelling Iodine Particle Formation and Growth from Seaweed
in a Chamber
L. Pirjola,A,E C. D. O’Dowd,B Y. J. Yoon,B,C and K. SellegriB,D
A
Helsinki Polytechnic, Department of Technology, Helsinki, Finland and University of Helsinki,
Department of Physical Sciences, Helsinki, Finland.
B Department of Experimental Physics and Environmental Change Institute, National University of Ireland,
Galway, Ireland.
C Korea Polar Research Institute/KORDI/Ansan P.O. Box 29, Seoul 425-600 Korea.
D Univesité Blaise Pascal, Laboratoire de Météorologie Physique, Clermont-Ferrand, France.
E Corresponding author. Email: [email protected]
Environmental Context. Iodine is an important trace species in the marine atmosphere. It contributes
to ozone depletion and new particle formation. In recent years, its importance has been realised; however,
there is still a gap in our knowledge, from a theoretical framework, of the dominant mechanisms leading
to new particle formation and previous theoretical frameworks have not been adequately developed or well
understood.This paper presents a state-of-the-art theoretical framework for evaluating the prediction of iodine
oxide nucleation and subsequent aerosol growth.
Abstract. A sectional atmospheric chemistry and aerosol dynamics box model (AEROFOR) was further developed and used to simulate ultra-fine particle formation and growth from seaweed in a chamber flushed with
particle-free atmospheric air. In the model, thermodynamically stable clusters were formed by dimer nucleation of
OIO vapour, whose precursor was assumed to be molecular I2 emitted by seaweed. Fractal geometry of particles
was taken into account. For the I2 fluxes of (0.5–1.5) × 109 cm−3 s−1 the model predicted strong particle bursts, the
steady state concentrations of I2 vapour and particles larger than 3 nm were as high as 4 × 109−1.2 × 1010 cm−3 and
5.0 × 106 –9.2 × 106 cm−3 respectively. The steady state was reached in less than 150 s and the predicted growth
rates of 3–6 nm particles varied in the range of 1.2–3.6 nm min−1 . Sensitivity of the size distribution against I2 O3
cluster formation, an extra condensable vapour, the photolysis rate of the OIO vapour as well as against the density
of (OIO)n -clusters was discussed. The modelled results were in good agreement with the chamber measurements
performed during the BIOFLUX campaign in September, 2003, in Mace Head, Ireland, confirming that I2 emissions
and nucleation of iodine oxides can largely explain the coastal nucleation phenomenon.
Keywords.
aerosol dynamics — growth rate — iodine chemistry — modelling — natural emissions
Manuscript received: 21 September 2005.
Final version: 21 October 2005.
Introduction
Formation of marine aerosols and their further growth to
cloud condensation nuclei (CCN) play an important role
in atmospheric processes. The particles scatter incoming
solar radiation back to space directly as well as indirectly
after activating as cloud droplets.[1] There still exist large
uncertainties in their cooling effect on the Earth’s radiation
budget,[2] and secondary particle formation plays a major
role in it.
The origin of marine aerosol particles is still poorly understood. Strong coastal new particle formation events have been
observed almost daily under low tide and sunny conditions at
the Scottish coast,[3] at western Ireland,[4] Tasmania,[5] and
Antarctica.[6] The nucleation mechanism is not yet understood. It has been suggested that homogeneous ternary
© CSIRO 2005
271
H2 SO4 –H2 O–NH3 nucleation produces thermodynamically
stable clusters that in addition require some extra condensable
vapour to grow to detectable sizes and further.[7–9] Sulphuric
acid is the oxidation product of dimethyl sulphide (DMS)
emitted from macroalgae in the sea. Recent laboratory chamber experiments have demonstrated that new particles can
form from condensable iodine-containing vapours, which are
the photolysis products of biogenic iodocarbons emitted from
marine algae.[10–14]
Hoffmann et al., O’Dowd et al., Jimenez et al. and
Burkholder et al.[10–13] have suggested, based on their laboratory measurements, that photolysis of CH2 I2 emitted
from seaweed produces I atoms whose oxidation products,
OIO molecules, participate in secondary particle formation.
Recently, McFiggans et al.[14] have presented a hypothesis
1448-2517/05/040271
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L. Pirjola et al.
for molecular iodine release from intertidal macroalgae and
due to its fast photolysis rate[15] atomic iodine is likely to
result primarily from molecular I2 rather than CH2 I2 . Also
recently, some modelling studies have been presented focusing on atmospheric particle formation and growth from iodine
vapours.[13,16,17] Burkholder et al.[13] developed a sectional
kinetic nucleation model where particle formation occurs by
homogeneous nucleation of OIO vapour molecules and particle growth by coagulation and condensation/evaporation
by OIO vapour molecules. Their model calculations demonstrated that IO and OIO concentrations reported from field
measurements were not sufficient to explain coastal or open
ocean particle bursts without elevated iodine species emissions. The model presented by Saiz-Lopez et al.[16] is also a
sectional box model including the gas-phase iodine chemistry
coupled to an aerosol coagulation-condensation algorithm.
The smallest particles in the first size bin can be either I2 O2 ,
I2 O3 or I2 O4 formed via gas phase reactions of IO and
OIO vapours. Their model studies and simultaneous measurements of I2 and ultra-fine particles in the coastal marine
boundary layer strongly indicated that I2 is the major precursor of the particle bursts. Pechtl et al.[17] considered both
homogeneous ternary sulphuric acid–ammonia–water nucleation and homomolecular homogeneous OIO nucleation in
their one-dimensional marine boundary layer model to study
particle bursts in clean and continental marine boundary
layer.
In this paper, based on in-situ chamber measurements
model simulations were performed to investigate processes
affecting particle formation and growth from iodine vapours
emitted by seaweed. A sectional atmospheric chemistry and
aerosol dynamic model (AEROFOR) was further developed with the following novel steps: (1) gaseous iodine
chemistry mechanism was added; (2) formation of thermodynamically stable clusters was studied by dimer formation
of OIO molecules, additionally I2 O3 cluster formation was
included; (3) coagulation coefficients were modified taken
into account fractal geometry of particles; (4) condensation of OIO and an extra organic vapour along with Kelvin
and nanoKohler effects were added and condensation in the
free molecular regime was implemented so that it is free of
numerical diffusion;[18] and (5) the modelled results were
compared with the chamber measurements performed during the BIOFLUX campaign in 2003, Mace Head, Ireland.
A full description of the BIOFLUX chamber experiments are
reported in Sellegri et al.[19]
The processes included in the model are: (1) chemical
reactions in the gas phase; (2) emissions of gases;
(3) dry deposition of gases; (4) homogeneous binary
H2 SO4 –H2 O[23] or ternary H2 SO4 –H2 O–NH3 [24] nucleation; (5) dimer formation from OIO molecules; (6) multicomponent condensation of H2 SO4 and H2 O, OIO and
organic vapours onto particles along with the Kelvin[25]
and nanoKohler[26] effects; (7) uptake of INO and INO2
molecules onto particles; (8) inter- and intra-mode coagulation of particles including their fractal geometry; (9) dry
deposition of particles;[27] and (10) ventilation with ambient
air. Since the model is running under clear sky conditions,
aqueous phase chemistry and cloud processing, coalescence
as well as wet deposition are not taken into account. Only the
processes and changes added in AEROFOR in this work will
be discussed below.
To minimize numerical diffusion typical for fixed sectional models,[28] we have used 94 size sections in the size
range of 0.47 nm–2 µm. The first 40 sections are for (OIO)n
clusters (1≤ n ≤ 40) so that the spacing is done moleculeby-molecule. The first size section refers to gaseous OIO.
To determine the diameters of the particles in each section the density of the clusters should be known. However,
there are different values given in the literature. Daehlie
and Kjekshus[29] have reported the bulk density of I2 O4 to
be 4.97 g cm−3 , but have also reported a lower bulk value
2.57 g cm−3 .[30] On the other hand, for I2 O5 whose structure is expected to be very similar to I2 O4 , the bulk density
of 5.08 g cm−3 has also been reported.[31] We have used for
all (OIO)n -clusters a density value of 4.97 g cm−3 but sensitivity of the results against cluster density has been tested.
For example, the fractal structure of iodine oxide particles
might lower the density of nucleated particles.[12] In the
present model the diameter of the first size section for the
OIO molecules was calculated to equal 0.47 nm, the diameter of the second section for the (OIO)2 dimer equals 0.63 nm.
The sizes of the next sections are calculated by a formula of
0.47 nm × i(1/3) , 2 ≤ i ≤ 40 (density = 4.97 g cm−3 ) leading
to a particle size of 1.6 nm in section 40. The following 54
size sections are evenly distributed in the logarithmic space
as in the previous versions of AEROFOR.
Iodine Chemistry
The scheme of the iodine chemical mechanisms associated
with the particle production used in this work is presented
in Fig. 1. It is based on the schemes presented in the
literature,[11,12,32] however, the main source of I atoms is
the molecular I2 flux from the seaweed instead of CH2 I2 as
reported recently.[14,16] I2 is rapidly photolyzed (see photolysis rate[15] ) releasing I atoms that are oxidized by ozone
to produce monoxide (IO) radicals, IO in turn reacts with
itself to produce OIO (38%) and I2 O2 (62%).[33,34] However, IO photodissociates producing I atoms but also reacts
with NO2 , NO, HO2 , and DMS. The reaction of IO and
O3 is also taken into account as suggested by Burkholder
et al.[13] The gaseous iodine reaction mechanism (10 species,
15 chemical and 8 photochemical reactions), the rate coefficients and references are given in Table 1. In this complicated
Model Description
AEROFOR[9,11,20–22] is a Lagrangian type sectional box
model used to investigate the formation and growth of particles under clear sky atmospheric conditions. The model
includes the gas-phase chemistry and aerosol dynamics,
and calculates the number size distribution and composition distribution of particles as a function of time. In this
work AEROFOR has been further developed to include
coastal iodine chemistry and particle formation from iodine
compounds.
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Modelling Iodine Particle Formation and Growth from Seaweed in a Chamber
HI
HO2
I2
INO2
OH
NO2
hn
HOI
hn
OH
O3, NO3
hn
I
hn
hn
NO
NO2
IONO2
IO
hn
O3
IO
hn
HO2
OIO
Aerosol
IO
?
I2O2
Fig. 1. Iodine chemistry scheme used in the model.
Table 1. Chemical mechanism of the gaseous iodine compounds
Unimolecular reactions in s−1 , bimolecular reactions cm3 molecule−1 s−1 , photolysis rate constants s−1
Reaction
Rate coefficient
Reference
I + O3 → IO + O2
I + HO2 → HI + O2
I + NO2 + M → INO2 + M
2.0 × 10−11
[47]
[32,48]
[48]
IO + NO → I + NO2
IO + HO2 → HOI + O2
IO + IO → OIO + I (38%) → I2 O2 (62%)
IO + O3 → OIO + O2
IO + NO2 → IONO2
IONO2 → IO + NO2
OH + HI → I + H2 O
HOI + OH → IO + H2 O
IO + DMS → products
INO2 → I + NO2
I + NO3 → IO + NO2
IO + OIO → I2 O3
exp(−890/T)
1.5 × 10−12 exp(−1090/T)
K0 = 3.0 × 10−31 [N2 ]/(T/300)
K∞ = 6.6 × 10−11
Fc = exp(−T/650) + exp(−2600/T)∧
7.3 × 10−12 exp(330/T)
9.0 × 10−12 exp(680/T)
1.5 × 10−11 exp(500/T)
5 × 10−15
K0 = 7.7 × 10−31 [N2 ]/(300/T)−5
K∞ = 1.6 × 10−11
Fc = 0.4∧
2.07 × 1015 exp(−11859/T)
1.6 × 10−11 exp(440/T)
2 × 10−13
1.2 × 10−14
2.4/0.005 × 2.07 × 1015 exp(−11859/T)
4.5 × 10−10
2 × 10−10
Photolysis reactions
I2 O2 + hν → 2I + O
I2 + hν → 2I
OIO + hν → IO + O
IO + hν → I + O
HOI + hν → I + OH
INO2 + hν → 0.5(I + NO2 ) + 0.5(IO + NO)
IONO2 + hν → 0.5(IO + NO2 ) + 0.5(I + NO3 )
CH2 I2 + hν → CH2 + 2I
∧ K = (K
b
0 /(1 + K0 /K∞ )) ∗ Fc ,
[48]
[49]
[33,34,50]
[13]
[47]
[32]
[48]
[32]
[48]
[32]
[32]
[16]
[32,51]
[15]
[32,33]
[34]
[52]
[32]
[32]
[53]
where b = (1 + (log10 (K0 /K∞ ))2 )−1 .
system there are many uncertainties, one of the most serious
is the photolysis rate of OIO. The maximum value for JOIO
under clear sky conditions during local noon at 53◦ N in July
is 0.48 s−1 based on the assumption that the quantum yield is
1 across all the absorption band between 480 and 650 nm.[32]
Cox et al.[33] reported that JOIO is 0.28 s−1 assuming that
absorption in the visible spectrum occurs with unit quantum
yield. These values were tested and the results are presented
in the sensitivity analysis section. The spectral actinic flux in
the UV range was decreased by a factor of 2 characterizing
the conditions in a chamber whose transmittance for UV
radiation was about 50%.
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L. Pirjola et al.
The inorganic and organic chemistry are mainly based on
the EMEP mechanism,[35] however, the DMS chemistry is
adopted from Saltelli and Hjorth.[36]
In Eqn 3 N1 refers to the OIO vapour molecules, and Qa is
the chemical net effect of productions and losses in the gas
phase, Jdim is the dimer nucleation rate (n∗ = 2), and CS1 is
the condensation sink defined by
CS1 = 2π
(d1 + dj )(D1 + Dj )β1j Nj .
(7)
Aerosol Dynamics
The initial step of formation of thermodynamically stable
clusters is assumed to occur by dimer formation of the OIO
vapour molecules with a nucleation rate (Jdim ) proportional
to the square of the OIO concentration by the equation[37]
Jdim = b11 [OIO]2 ,
where the collision rate of monomers
√ 6 3V 6kB T
b11 = 4 2
,
4π
ρ
j≥2
This formula takes into account molecular dimensions in
comparison with particle sizes when the particle dimensions
are in the regime of free-molecular sizes (see e.g.[18] ). The
correction factor for the transition regime is based on the
semi-empirical formula by Fuchs and Sutugin[38]
(1)
β1j =
(2)
The Knudsen number is defined as
2λj
Knj =
d1 + d j
where V is the OIO molecular volume (spherical size is
assumed), ρ the density of the clusters, kB the Boltzmann
constant and T the temperature. These clusters grow by coagulation and condensation of OIO vapour. All (OIO)n -clusters
(n ≥ 2) are assumed to be stable unlike in the model by
Burkholder et al.[13] where evaporation of these clusters was
important to the interpretation of their laboratory experiments. The (OIO)2 or I2 O4 is crystalline solid considered
to be ‘ionic species’ [IO]+ [IO3 ]− and thus should be very
stable.[10] Due to uncertainties in the nucleation mechanism
sensitivity analysis of I2 O3 cluster formation has been studied
in the sensitivity analysis section
The time evolution of the number concentration of (OIO)ni
clusters (Ni ) in section i (containing ni OIO molecules) is
described by the set of differential equations
3(D1 + Di )
λi = c̄12 + c̄22
j≥2
(4)
and for i ≥ 3,
(5)
j=1 k=j
i
i Kj,k
(ni+1 − (nj + nk ))
δnj +nk ,]ni ,ni+1 ]
N j Nk
1 + δj,k
(ni+1 − ni )
where RCij = rCi + rCj , Dij = Di + Dj where Di and Dj are
the particle diffusion coefficients, c̄ij is the mean relative
thermal velocity between the particles, and σij is the square
root of the effective mean free paths of the particles (see
e.g.[40,41] ).
The third differential equation 5 describes the time evolution of the clusters Ni ;[20,42] the first two terms in the
right-hand side of Eqn 5 are due to condensation; the
j=1 k=j
−Ni
Ki,j Nj + νl (Nbgi − Ni ) − wall losses
j≥1
where Kronecker’s delta is
0, nj + nk
δnj +nk ,]ni ,ni+1 ] =
1, nj + nk
∈]ni , ni+1 ]
.
∈]ni , ni+1 ]
(10)
where r2 and ri are the radii of the dimer and the particle,
respectively, when they are assumed to be spheres. Then the
modified Fuchs formula is
4πRCij Dij
(12)
Kij = R
4Dij
Cij
RCij +σij + RCij c̄ij
i i
kj,k
((nj + nk ) − ni−1 )
+
δnj +nk ,]ni−1 ,ni ]
Nj Nk
1 + δj,k
(ni − ni−1 )
+
(9)
and c̄1 and c̄j are thermal speeds of the molecule and particle respectively. Diffusion coefficients for the OIO gas (D1 )
and (OIO)i -clusters (Di ) are calculated using simple kinetic
theory. The accommodation coefficient α is assumed to be
unity.
In the second differential equation 4 N2 (i.e. (OIO)2 clusters) are formed by dimer nucleation and are removed
by self-coagulation as well as coagulation to larger sizes.
Brownian coagulation coefficients Kij between particles in
size section i and j are calculated according to the modified Fuchs formula.[39] Since the iodine particles formed are
fractal agglomerates with mass fractal dimension Df ∼1.9–
2.6[12] fractal geometry was taken into account in this work.
To calculate the Brownian coagulation coefficients the collision radius of particles in size section i was assumed to equal
the fractal radius, defined as
3/Df
ri
rCi = r2
(11)
r2
K2,j
dN2
= Jdim − N2
Nj + νl (Nbg2 − N2 )
dt
1 + δ2,j
dNi
Ci−1
Ci
=
Ni−1 Nl −
Ni N 1
dt
ni − ni−1
ni+1 − ni
(8)
in which the mean free path is
dN1
= Q1 −n∗ Jdim − CS1 N1 +νl (Nbg1 − N1 )−wall losses
dt
(3)
− wall losses
Knj + 1
2
,
4
Knj + Knj
0.377Knj + 1 + 3α
(6)
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Modelling Iodine Particle Formation and Growth from Seaweed in a Chamber
production of clusters from the condensation onto the next
smaller section and the sink of clusters to the next larger section due to condensation onto this size section. The next two
terms account for particle production by coagulation; when
two particles collide and the total number of OIO molecules
in a new particle (nj + nk ) is between the number of OIO
molecules of particles in sections i and i − 1 or in sections
i + 1 and i, the production of particles to section i occurs. The
fourth term is the loss term due to coagulation. Note that for
the first 40 sections ni always equals i and the Eqn 5 becomes
much more simple.
In this work the height of the box is the same as the height
of the experimental chamber (1 m). The chamber volume was
2 m3 , and at a flow rate of 800 l min−1 , the chamber air was
renewed every 2.5 min, and thus the ventilation rate (νl ) in
Eqns 3–5 is 1/150 s−1 defined to be the ratio of the flow rate to
the chamber volume. The ambient air was scrubbed of background particles so Nbgi = 0 for i ≥ 2. On the other hand, the
background concentration (Nbg1 ) for the OIO vapour as well
as for the IO vapour entering into the chamber was assumed to
be 7 × 107 cm−3 (∼3 ppt) based on the measurements.[43,44]
For all other iodine containing vapours the background concentrations were set to zero, whereas for ozone the ambient
concentration of 34 ppb measured at the Mace Head station
was used.
The set of stiff differential equations was solved using
Numerical Algorithms Group, Ltd. library FORTRANroutine D02EJF.[45] The time step was 5–10 s.
atmosphere, any influence of ageing of the seaweed is
unlikely. The measured ultra-fine (3.5–50 nm) particle concentrations varied from 3 × 106 to 1 × 107 cm−3 and huge
growth rates of more than 1.2 nm min−1 were observed.[19]
Base Case Simulations
In the model simulations the molecular iodine flux was a
variable characterizing a different amount of seaweeds in
the chamber, the flux into the chamber was prescribed to
be 5 × 108 , 1 × 109 , and 1.5 × 109 molecules cm−3 s−1 (the
chamber height has been taken into account). These values
were chosen based on the experimental results in Sellegri
et al.[19] The chamber measurements provided the gaseous
I2 concentration and the particle size distribution from which
the particulate I2 concentration was calculated. Subsequently
the total I2 concentration was converted to the I2 flux by the
means of the residence time in the chamber.[19] The ambient
temperature 287 K and relative humidity 70% were used for
200 s simulation starting at 14:00 LT. As mentioned before
no evaporation of (OIO)n clusters were taken into account,
and in these base case simulations the only condensable
vapour was OIO. Thus the sulphuric acid formation from
DMS was excluded. Fractal dimension was assumed to be
2.5 as mentioned before.
Fig. 2(a) shows that in 15 s I2 has reached steady
state concentrations that are around 4 × 109 , 8 × 109 and
1.2 × 1010 cm−3 depending on the I2 flux. These values are in
good agreement with the measured gaseous I2 concentrations
that varied in the range of 1.35–4.23 ng L−1 corresponding to 3.2 × 109 –1 × 1010 molecules cm−3 . The steady state
IO concentrations and OIO concentrations are 2.8 × 109 –
4.6 × 109 cm−3 and 4.9 × 108 –9.2 × 108 cm−3 respectively.
Thus the model predicts a [IO]/[I2 ] ratio in the range of
0.7–0.4 respectively. Unfortunately, the IO and OIO concentrations were not measured during the chamber experiments.
Naturally the modelled chamber values were much higher
than the literature values for field measurements, maximum
∼3 ppt ∼7.4 × 107 cm−3 in the afternoon.[43] Dependence of
the I2 , IO and OIO concentration on the I2 flux is presented
in Fig. 2(b). Clear linear dependence can be observed for I2 ,
but slight saturation effect is seen for IO and OIO when I2
flux is higher than 1 × 109 cm−3 s−1 .
Fig. 3(a) depicts the total particle number concentration
(Ntot ) of particles larger than 0.59 nm and the concentration of
detectable particles, larger than 3 nm (N3 ). Particle formation
and growth is very efficient; for the highest I2 flux N3 starts
to increase after 30 s and has reached the steady state concentration after 80 s. In the other cases particle growth is slower
and N3 starts to increase later due to the lower OIO concentration and higher pre-existing particle concentration which
acts also as a condensation sink for the OIO vapour. At the end
of the simulation N3 concentrations are 5.0 × 106 , 8.7 × 106
and 9.2 × 106 cm−3 whereas the measured detectable particle concentration (particles larger than ∼3 nm) varied in the
range of 3.0 × 106 –1 × 107 cm−3 for the seaweed mass of
5–26 kg and I2 concentration of 3 × 109 –1 × 1010 cm−3 .[17]
Fig. 3(b) summarizes the dependence of N3 , the formation rate of the 3.1–3.5 nm particle concentration (N3.1–3.5
Results and Discussion
Chamber Experiments
The modelled results are compared against the chamber measurements performed during the BIOFLUX campaign on
the coastal site of Mace Head and its surroundings, Galway, Ireland, during 15 September–1 October, 2003.[19] The
chamber with dimensions of 2 m × 1 m × 1 m was built from
Perspex of which UV radiation transmittance was about 50%.
About a quarter of the chamber was filled with two types of
seaweeds, Laminaria and Fucus, widely found at the tidal area
near the Mace Head Atmospheric Research station (53.33 N,
9.90 W, 5 m a.s.l.).At the start the mass of seaweeds was 26 kg,
then after about half an hour the cover was opened and the seaweed mass was decreased to 16 kg, 9 kg and 5 kg. After every
operation the cover was closed and ventilation was installed
again. Due to a particle filter in the inlet the background air
entering the chamber was particle free. The particle size distributions were measured by a nano-SMPS (3–50 nm) and
ELPI (7 nm–10 µm). Chamber air was sampled using denuders to identify the gaseous molecular iodine composition.
The detailed description of the chamber measurements can
be found in Sellegri et al.[19]
In the chamber experiments strong particle formation
bursts and subsequent growth were observed. The steady
state was achieved in 2–3 min depending on the amount of
seaweeds introduced in the chamber. Since the total time
needed for the experiments was not longer than a few hours,
which is also the time seaweeds are exposed to ozone in the
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RESEARCH FRONT
L. Pirjola et al.
(a)
(a)
I2 (solid), IO (dashed), OIO (dash-dot)
1011
Ntot (solid), N3 (dashed)
109
Concentration (cm3)
Concentration (cm3)
108
1010
109
108
107
(b)
15
106
105
1.5e9
1e9
0.5e9
50
0
100
Time (s)
150
104
200
1.5e9
1e9
0.5e9
0
(b)
109
Concentration/Flux/Nucleation rate
10
5
50
100
Time (s)
150
107
106
0
0
0.5
1
I2 flux (cm3)
1.5
1010
I2
2
109
200
N3 (cm3)
N3.1–3.5 rate (cm3 s1)
Jdim (cm3 s1)
108
I2
IO
OIO
Concentration (cm3)
107
(cm3)
Fig. 3. Concentrations of total particle concentration (Ntot ) and particles larger than 3 nm (N3 ) as a function of time (a), and dependence
of N3 , the formation rate of 3.1–3.5 nm particle concentration (N3.1–3.5
rate) and the steady state dimer nucleation rate J on the I2 flux (b).
I2 flux in cm−3 s−1 is given in the legend.
Fig. 2. Concentrations of I2 , IO and OIO as a function of time (a),
and dependence of I2 , IO and OIO on the I2 flux (b). I2 flux in cm−3 s−1
is given in the legend.
rate) and Jdim on the I2 flux. The steady state dimer nucleation rate Jdim (Eqns 1 and 2) was 4.8 × 107 , 1.0 × 107 and
1.6 × 108 cm−3 s−1 , where the collision rate of monomers is
b11 = 1.9 × 10−10 cm3 s−1 . This is a somewhat higher value
than suggested by Saiz-Lopez et al.[16] who estimated that the
rate constants for IO + OIO and OIO + OIO should be about
2 × 10−10 and 5 × 10−11 cm3 molecule−1 s−1 , respectively at
1 atm and 290 K. The modelled formation rate of 3.1–3.5 nm
particles was 1.2 × 106 –2.2 × 106 cm−3 s−1 whereas the calculated flux of 3–3.4 nm particles based on the chamber
experiments was 2.5 × 1010 m−2 s−1 for a seaweed loading of
2.5 kg m−2 or 5 kg sea weed mass in the chamber[19] resulting
in the formation rate of 2.5 × 106 cm−3 s−1 that is two times
larger than the modelled lowest value.
Fig. 4 illustrates the particle size distribution at the end of
the simulation. Also shown are the measured steady state size
distributions for the 5, 9 and 26 kg seaweed masses. For the
smallest I2 flux the model overestimates the concentration
of particles smaller than around 5 nm and underestimates the
concentration of 5–15 nm particles. For the higher I2 fluxes
JOIO 0.24 s1, modelled (solid), measured (dashed)
1.5e9
1e9
0.5e9
dN/d log(Dp) (cm3)
108
106
104
102
100
109
108
107
106
Diameter Dp (m)
Fig. 4. Particle size distribution at the end of the base case simulations.
I2 flux in cm−3 s−1 is given in the legend. Also shown are the steady
state measured curves.
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Modelling Iodine Particle Formation and Growth from Seaweed in a Chamber
Diameter Dp (m)
Diameter Dp (m)
106
107
108
1.5e9 cm3 s1
1e9 cm3 s1
106
Diameter Dp (m)
0.5e9 cm3 s1
106
107
108
1e006
100000
107
10000
1000
108
100
109
200
5 kg
107
108
109
0
100
Time (s)
200
107
108
109
0
100
Time (s)
200
10
26 kg
9 kg
106
106
Diameter Dp (m)
Diameter Dp (m)
106
100
Time (s)
Diameter Dp (m)
0
1e006
100000
107
10000
1000
108
100
109
0
100
Time (s)
200
109
0
109
100
Time (s)
200
10
0
100
Time (s)
200
Fig. 5. Contour plots of the time development of the size distributions in the chamber. Upper panels: modelled results with different I2 fluxes
shown in the title. Lower panels: measured results with different seaweed masses shown in the title. The color bar shows dN/dlog(Dp) in cm−3 .
loading of 5 kg (2.5 kg m−2 ). The condensation sinks were
0.03, 0.07 and 0.1 s−1 .
the agreement is better, however, the 10–30 nm particle concentration is still underestimated. There might be two reasons
for this underestimation, (i) the I2 O2 molecules formed from
the self reaction of IO molecules might participate in the particle formation and growth, and (ii) sea weeds might also emit
some organic species whose oxidizing products might have
saturation densities low enough to make the particles grow by
condensation. This will be discussed in the sensitivity section.
The time developments of the size distribution for different
I2 fluxes are shown in Fig. 5. For comparison also shown are
the measured ones during the first 200 s after the cover in the
chamber was closed. The step function is due to the scanning
time of the SMPS instrument that is around 40 s, and the measured diameter range was 3–50 nm. For the largest seaweed
mass the steady state was achieved immediately (see details
in Sellegri et al.[19] ). The growth rates of 3 nm particles to
5–6 nm sizes were calculated by plotting the number concentration of the size sections in this size range as a function
of time. The growth rate is then GR = (Dp2 − Dp1 )/(t2 − t1 ),
where Dp1 = 3.13 nm and Dp2 = 6.1 nm are the diameters
of the particles in two size sections and t1 and t2 are the
peaking times. The calculated growth rates were 1.2, 2.2 and
3.6 nm min−1 for the different I2 fluxes, in excellent agreement with the measured value 1.2 nm min−1 at a seaweed
Sensitivity Analysis
First, sensitivity of the size distribution at the end of the simulation presented in Fig. 4 was tested against an additional
condensable vapour. Candidates for the extra vapour are a
generic organic vapour with low saturation vapour density
and/or iodine dioxide vapour I2 O2 unless its low thermal
stability made it decay before. Organic vapour is likely to
be present in the chamber, for example, the measured CO
concentrations showed an increased trend during the chamber experiments possibly indicating emissions of organic
species from the seaweed and subsequent chemical oxidation reactions. In any case, ambient organic vapour entered
the chamber during the ventilation. Unfortunately, the organic
vapour is not yet identified and thus its source rate as well
as its thermodynamic properties are not known. As a generic
vapour we have used the properties of water–hexanol mixture, however, the saturation vapour density was assumed to
be 1 × 106 cm−3 . The so called nanoKohler effect was also
taken into account and the critical diameter for condensation
was estimated to equal 1.8 nm.[26,46] Different source rates
of the organic vapour were tested. The best agreement with
277
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L. Pirjola et al.
I2 flux (cm3 s1) in legend
(a)
1.5e9
1e9
0.5e9
106
104
106
104
102
102
100
109
1.5e9
1e9
0.5e9
108
dN/d log(Dp) (cm3)
dN/d log(Dp) (cm3)
108
I2 flux (cm3 s1) in legend
(b)
108
107
Diameter Dp (m)
106
100
109
108
107
106
Diameter Dp (m)
Fig. 6. (a) The same as Fig. 4 but an extra condensable vapour with a source rate of 9 × 106 , 107 and 3 × 107 cm−3 s−1 for the different I2 fluxes
was included. (b) Both I2 O3 and I2 O4 clusters were formed into the first size section. The modelled curves are solid, the measured dashed.
the measurements was obtained by assuming a dependence
on the seaweed mass such that for the I2 flux of 0.5 × 109 ,
1 × 109 and 1.5 × 109 cm−3 s−1 the source rate of the organic
vapour was 9 × 106 , 1 × 107 and 3 × 107 cm−3 s−1 respectively (Fig. 6(a)). The ambient organic vapour concentration
from coastal sources entering the chamber was assumed to
be 107 cm−3 . The predicted steady state concentration in the
chamber was in the range of (1.3–2.7) × 108 cm−3 .
There is no clear evidence yet that dimerization of the
OIO molecules is the only nucleation mechanism. In the second sensitivity test we assumed that the clusters in the first
size section can be either I2 O3 or I2 O4 , the former formed
by the reaction IO + OIO with a reaction rate constant of
2 × 1010 cm3 molecule−1 s−1 .[16] Fig. 6(b) shows that the
model results are closer to the measurements even though the
model slightly over- or underestimates the particle concentrations. Fig. 6(b) also indicates that this reaction mechanism
might be important and is even likely.
Third, since the photolysis rate of OIO is uncertain, the
simulations were repeated by using the values of 0.12 s−1 and
0.48 s−1 as the noon value. Also the case JOIO = 0 s−1 was
tested since recent laboratory measurements[16] have pointed
out that the rate of photolysis of OIO may be lower than
initially thought or measured. Fig. 7 shows that the size distribution of the particles is rather sensitive to this value. Due to
the smaller photolysis rate and slower photodissociation more
OIO vapour is present to nucleate and condensate resulting in
larger particles and better agreement with the measurements.
The steady state concentrations of OIO were in the range
of 6.1 × 108 and 1.0 × 109 cm−3 for JOIO = 0 s−1 , 5.5 × 108
and 9.7 × 108 cm−3 for JOIO = 0.48 s−1 , and 4.2 × 108 and
8.2 × 108 cm−3 for JOIO = 0.12 s−1 . After the simulation
of 200 s and with different I2 fluxes (0.5 × 109 , 1 × 109
and 1.5 × 109 cm−3 s−1 ) the particle concentration N3 with
JOIO = 0 s−1 increased 213%, 63% and 42% of the values
with JOIO = 0.48 s−1 respectively. This shows that the formation and growth processes of particles is clearly non-linear.
Even with the smaller photolysis rate the model still slightly
underestimates the 10–30 nm particles’ growth.
Fourth, the simulations were also repeated by assuming the
density of the clusters and also the gaseous OIO molecule to
be 2.5 g cm−3 and 4.0 g cm−3 . Then the molecule radii were
calculated to be 0.29 nm and 0.25 nm, and the dimer radii
0.74 nm and 0.63 nm respectively. Consequently, the radii
of the first 40 sections changed somewhat but still the size
of the sections increased always molecule by molecule. The
density affects not only the initial situation but also nucleation, condensation and coagulation rates, for example, dimer
nucleation rate is inversely proportional to ρ2/3 (Eqn 2). The
total particle concentration as well as N3 started to increase
earlier and achieved higher maximum concentration when
the density decreased. The size distribution curves in Fig. 8
show that lowering the density makes faster particle growth
and better agreement with the observations.
Conclusion
The sectional atmospheric chemistry and aerosol dynamics
box model AEROFOR was further developed to simulate
ultra-fine particle formation and growth from seaweed in
the chamber conditions. The chemical reactions of gaseous
iodine compounds were added and combined with the aerosol
dynamics such as nucleation, condensation and coagulation.
In this work thermodynamically stable clusters were formed
by dimer nucleation of OIO vapour, the origin of which was
assumed to be the emission of I2 vapour from the seaweed.
Fractal geometry of the stable (OIO)n -clusters (n ≥ 2) was
taken into account. To avoid numerical diffusion the first 40
size sections were implemented molecule by molecule.
For the I2 fluxes of (0.5–1.5) × 109 cm−3 s−1 based on the
chamber measurements the model predicts strong particle
bursts during the 200 s simulations. The detectable particle (larger than 3 nm) concentration reaches the steady state
in less than 150 s which is in good agreement with the
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Modelling Iodine Particle Formation and Growth from Seaweed in a Chamber
JOIO 0.48 s1
(a)
1.5e9
1e9
0.5e9
106
104
102
100
109
107
108
1.5e9
1e9
0.5e9
108
dN/dlog(Dp) (cm3)
dN/dlog(Dp) (cm3)
108
JOIO 0.12 s1
(b)
106
104
102
100
109
106
Diameter Dp (m)
106
JOIO 0 s1
(c)
1.5e9
1e9
0.5e9
108
dN/dlog(Dp) (cm3)
108
107
Diameter Dp (m)
106
104
102
100
109
108
107
106
Diameter Dp (m)
Fig. 7. The same as Fig. 4 but for the cases when the photolysis rate of OIO was faster 0.48 s−1 but also slower 0.12 s−1 and 0 s−1 . The modelled
curves are solid, the measured dashed.
Density 2500 kg m3
(a)
1.5e9
1e9
0.5e9
106
104
106
104
102
102
100
109
1.5e9
1e9
0.5e9
108
dN/dlog(Dp) (cm3)
dN/dlog(Dp) (cm3)
108
Density 4000 kg m3
(b)
108
107
Diameter Dp (m)
106
100
109
107
108
Diameter Dp (m)
106
Fig. 8. The same as Fig. 4 but for two lower particle densities, 2.5 g cm−3 (a) and 4.0 g cm−3 (b). The modelled curves are solid, the measured
dashed.
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L. Pirjola et al.
chamber measurements. The steady state concentration of I2
and N3 varied in the range of 4 × 109 –1.2 × 1010 cm−3 and
5.0 × 106 –9.2 × 106 cm−3 , respectively, whereas the measured particle concentration varied in the range of 3.0 × 106 –
1 × 107 cm−3 for the seaweed mass of 5–26 kg and I2 concentration of 3 × 109 –1 × 1010 cm−3 . Also the predicted growth
rate of 3–6 nm particles was in excellent agreement with the
observations.
For the smallest I2 flux the model somewhat overestimated
the concentration of particles smaller than around 5 nm and
underestimated the concentration of 5–15 nm particles. For
the higher I2 fluxes the 10–30 nm particle concentration was
still underestimated. However, an inclusion of I2 O3 particle
formation or an extra condensable vapour with a source rate of
∼107 cm−3 s−1 improved the results and the size distributions
predicted by the model at the end of the simulation were very
close to the observations. The modelled size distributions
were sensitive to the photolysis rate of the OIO vapour as
well as to the density of (OIO)n -clusters.
As a summary, this work confirms that I2 emissions, nucleation of iodine oxides producing I2 O4 and possibly I2 O3
particles, although the role of the latter oxide is still unclear
as regards of its importance, and subsequent coagulation and
OIO condensation is a mechanism that largely explains the
coastal nucleation phenomenon. Our future work will be to
apply the model in simulating ultra-fine particle formation
and growth during low tide in the hotspot areas near the Mace
Head station.
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Acknowledgements
The authors acknowledge for Science and Engineering Technology (IRCSET) and European Commission under contract EVK-CT-2001-00127 (QUEST). Special thanks go to
Gordon McFiggans for helpful discussions.
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