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ADIENT / APPRAISE CP2 Technical Report, DRAFT V2, 5 August 2009
Suggested refractive indices and aerosol size parameters for use in radiative effect calculations and
satellite retrievals.
E.J. Highwood, Department of Meteorology, University of Reading.
Files available from http://www.met.rdg.ac.uk/~adient
1. Introduction:
In the ADIENT project, and many others, it is desirable to provide an estimate of radiative effect of
aerosols for comparison with aircraft measurements and for calculation of the radiative forcing due to
anthropogenic aerosols. Several different communities require information on the fundamental means
by which aerosols interact with radiation. For the purposes of this report we consider the requirements
of the ADIENT consortium which includes 3 groups developing satellite retrievals of aerosol properties
(Imperial College, Oxford University and RAL), one aerosol transport modelling group (University of
Leeds) and one group estimating the radiative effect of aerosols using radiative transfer models and
performing radiative closure studies using FAAM data (University of Reading). These groups expressed a
desire for consistency across the ADIENT project, and attempts to justify the use of various choices have
resulted in this report. However, it is expected that the reviews and recommendations described in this
report will be of interest to the wider community.
2. Methodology:
A survey of the groups in ADIENT was undertaken to ascertain how aerosol properties were used and
therefore required within the individual activities. A literature review was then conducted by Reading
into the appropriateness of the choices already used, and whether recent work presented alternatives.
The main difference in the use of aerosol radiative properties between the various groups concerned
the use of aerosol “components” – building blocks such as ammonium sulphate, black carbon, nitrates,
sea salt, dust etc by the modelling groups, and the use of aerosol “types” or “models” e.g. “urban”,
“water soluble”, “insoluble” by the satellite retrieval groups. Aerosol “types” are usually built from
components, although some, such as “mineral dust” were in use by both groups (although not
necessarily with the same properties). It was also evident that some new components were required for
which the previously used aerosol models (e.g. OPAC, Hess et al, 1998) did not contain information. This
reflects the rapid growth of aerosol measurements and process studies in recent years.
The quantities of fundamental importance are refractive index (preferably at multiple wavelengths) and
size. While it is obvious that especially in terms of the latter there will be variation from case to case and
place to place, representative sizes are often required for modelling studies. Aerosol “types” are also
specified in terms of aerosol components – i.e. urban (Hess et al, 1998) = 56% water sol, 36% insol and
8% soot. The final parameter that is of importance is a measure of the aerosol’s growth with relative
humidity. In this report we present most detailed discussion of the refractive indices, and more limited
discussion of the sizes and growth parameters for aerosol. We hope that these will be useful to people,
but respectfully remind users that these tables and data files are merely the educated (we hope) opinion
of one group, and it is important to bear in mind that substantial variations can and do occur!
3. Initial survey results:
Table 1 shows the results of the refractive indices used by the various different groups within ADIENT at
the 18 month stage of the consortium. It is worth noting that the usage of these is very different. For
example, Leeds uses wavelength independent values, taking the 550nm value across the visible
spectrum. RAL and Oxford require spectral variation values for channels that are used in their aerosol
retrievals. Imperial considers mainly mineral dust which is almost the only aerosol having major
radiative impact at longer wavelengths in the terrestrial spectrum. In this case, Reading is most
interested in values at 550nm for radiative closure comparisons with aircraft measurements, however a
wider spectral range is needed for radiative effect calculations and comparison with ground based e.g.
AERONET measurements.
4. Recommendations:
We hope that these will be useful to people, but respectfully remind users that these tables and data
files are merely the educated (we hope) opinion of one group, and it is important to bear in mind that
substantial variations, as well as difference of opinion can and do occur!
4.1 Refractive Indices:
Table 2 shows the recommendations for refractive index for each aerosol type/component as suggested
from a review of literature and the availability of measurements from field campaigns or laboratory
studies. The table includes methodology proposed for extending the dataset to multi-wavelength values
and provides links to filenames for data which can be found at http://www.met.rdg.ac.uk/~adient.
Please use with consideration and caution. Justification also follows for the decisions made in each case.
The files are provided with values at standard wavelengths initially in agreement with OPAC/GADS
resolution (61 wavelengths from 0.25 micron to 40 micron). Users requiring data at other wavelengths
will need to adjust them accordingly. Please note that the files follow the convention of giving the real
and imaginary parts of the refractive index (n,k) assuming that the Mie code with which they are to be
used follows the convention (n-ik). However, the value for the refractive index in the table is written in
its complex form. There is some confusion in the literature over the appropriate sign for the imaginary
part. We have tried to be consistent such that all else being equal, a larger magnitude imaginary
component indicates stronger absorption.
4.1.1
(Ammonium) Sulphate
Most data sets of refractive indices used across the community for ammonium sulphate stem from the
same source, Toon et al (1976). They are well used and there seems no justification for changing these.
4.1.2
(Ammonium) nitrate
Nitrate has only recently come to the attention of the aerosol community as an important contributor to
light scattering. Many aerosol transport models do not yet include this species, partly due to the need
to model ammonia well. The few studies which have attempted to calculate a radiative forcing due to
aerosol containing nitrate (e.g. Cook et al, 2007) have used a single value from Weast (1985) which was
valid only in the mid-visible and has no absorption. Given the apparent abundance of nitrate during at
least some of the ADIENT flights, and its elevated real part of the refractive index, it is important to
know the wavelength dependence of these properties. Two recent laboratory studies have measured
the refractive index of ammonium nitrate. Jarzembski et al (2003) used high-resolution Fouriertransform infrared absorbance and transmission data to infer the imaginary refractive index for 2 to 20
micron. The corresponding real part was found using Kramers-Konig mathematical relations. Gosse et al
(1997) measured the imaginary part of the refractive index of nitrates between 0.7 and 2.6 microns. In
order to provide a refractive index from 0.25nnm through to the infrared, we have used the values of
Weast et al (2005) below 0.7 microns, Gosse et al (1997) in the intermediate range and Jarzembski et al
(2003) in the infrared. Consistency between the latter two studies was tested in the overlap range
between 2 and 2.6 microns.
4.1.3
Organic carbon (OC)
This discussion applies to the component of organic aerosol that is not black carbon and generally
derives from fossil fuel burning. Since the composition of this aerosol depends on combustion type and
material it is problematic to prescribe parameters suitable for all occasions. Atmospheric organic crabon
is often described as HULIS – Humic-Like Substances. HULIS samples have been recorded with refractive
indices of 1.595-0.049i (Pollution, Dinar et al, 2007), 1.622-0.048i (wood burning smoke, Dinar et al
2007), 1.56-0.003i (rural continental, Dinar et al, 2007), 1.65-0.0019i (biomass burning, Hoffer et al,
2006), 1.45-0.001i (Kreckov et al, 1993 – used in ADRIEX), 1.53-0.0055, (Koepke et al, 1997, used for
POM in ECHAM). Measurements of the absorption properties of atmospheric HULIS use a variety of
techniques to extract the HULIS from the aerosol. Some of these techniques can enhance the
hydrophilic compounds for pollution and smoke samples. Perhaps for this reason, Swannee River Fulvic
Acid (SRFA) has been used as proxy for atmospheric HULIS in numerous studies (e.g. Dinar et al, 2007) as
it is available for laboratory measurements although some caution must be attached. Laboratory SRFA
has a density of 1.47 g cm-3 and a refractive index of 1.634-0.021i at 532nm. Other groups use
information from observations of biomass or fossil fuel burning to constrain their optical properties. For
example, HADGEM2, the Met Office climate model, has separate optical properties for FFOC (fossil fuel
organic carbon), SOA (secondary organic aerosol), and fresh and aged biomass aerosol. The real part of
the refractive index for aged OC in HadGEM2 is taken to be the same as that for Biomass Burning (which
is constrained by measurements at some wavelengths – 1.54 at 550nm) and the imaginary part of the
refractive index is assumed to be wavelength independent at -0.006 (compared to that for aged biomass
burning of 0.02 at 550nm). This value for OC is at the low end of the estimates for absorption from
HULIS measured in the atmosphere and also lower than the absorption from SRFA.
It is clear that there is a range of uncertainty in the imaginary part of the refractive index that is
appropriate for organic carbon. Even if one accepts that HULIS is appropriate, then this varies according
to source and location. The aging process is also a complicating factor. The situation becomes more
difficult if values at wavelengths other than 550nm are required. Kirchstetter et al (2004) report that the
spectral dependence of light absorbing aerosols is dependent on the temperature and completeness of
combustion – with high temperature combustion processes (such as diesel burning) exhibiting much less
spectral dependence of absorption. They suggest a wavelength dependence of the mass absorption
efficiency according to σ = Kλ-α where α is the absorption angstrom exponent and α=2.5 for biomass
aerosols but only 1 for motor vehicle emissions of light absorbing aerosol. Kirchstetter et al (2004) also
provide values of the imaginary part of OC refractive index between 350 and 700nm.
No single study or sample provides values for real, imaginary and wavelength dependent refractive
index for OC. The recommendation made here is that SRFA refractive indices at 532nm be used as the
anchor point for a wavelength dependent refractive index that retains the dependence of Kirchstetter et
al (2004) between 350 and 700nm for the absorption part, but is wavelength independent in the real
part (there being a lack of information regarding the wavelength dependence above 532nm) for the
visible part of the spectrum. The value at 550nm is more absorbing than that used in HadGEM2, but still
substantially less absorbing than HULIS isolated from several samples from different combustion and
aerosol conditions. For longer wavelengths still (above 4 micron), Hess et al (1998) wavelength
dependence for WASO (water soluble type) is used as in Stier et al (2007). Extreme caution should be
attached to the values at longer wavelengths.
4.1.4
Biomass burning aerosol
It is widely recognised that whilst biomass burning aerosol is undoubtedly a complex cocktail of organic
and inorganic aerosol components, it is the predominant aerosol type over considerable regions of
particularly the subtropics and tropics and therefore we believe it merits a unique refractive index
alongside the other more specific aerosol compounds measured above. In addition, many of the aircraft
and ground based measurements of aerosol properties that inform choices of optical properties are only
able to measure the bulk aerosol rather than the species within it. Most observations of biomass aerosol
properties come from the Amazon and subsahelian Africa. Dubovik et al (2002) use the AERONET
network to define refractive indices for 4 types of biomass burning aerosol: Amazon (1.47, -0.0093),
Cerrado, Brazil (1.52, -0.015), Africa (1.51, -0.021) and Boreal (1.50, -0.009). Other measurements in the
Amazon reported in Guyon et al (2003) and Chand et al(2006) record refractive indices of 1.41, -0.013i
and 1.5, -0.015 respectively. The SAFARI campaign in southern Africa reported a campaign average value
of 0.018i for the imaginary part of the refractive index, and this as been adopted as a wavelength
independent value for aged biomass burning in HADGEM2. This model uses (1.54, -0.029) for fresh
biomass and includes some wavelength dependence. The more recent Met Office campaign, DABEX,
showed ranges of 1.53-1.59 and -0.045i for aged biomass in the Sahel (Johnson et al, 2008) but the
authors point to large variability in these values and warn against using them more widely to represent
biomass burning aerosol. Some of the HULIS measurements referred to in section 4.1.3 also relate to
biomass burning aerosol.
The recommendation here is given in the context of regional scale radiative effect calculations and
suggests values closer to the aged biomass burning measurements. It is worth noting that for
applications close to biomass source, a more absorbing refractive index might be appropriate. There are
also likely to be substantial differences between geographical region depending on type of fire and fuel.
In recommending the use of refractive indices based on the SAFARI campaign we may not be
representing Amazonian biomass sufficiently. A value at 550nm of 1.54, -0.018 is recommended on the
basis of observations. This is towards the higher end of observational studies for biomass aerosols, but is
still slightly less absorbing than the recommendation for organic carbon in the previous section which is
broadly consistent with studies mentioned there who looked at HULIS from both sources. In terms of
spectral dependence, there is little information available, although Kirchstetter et al (2004) suggests
absorption should be more spectrally dependent than the case of organic carbon. Here we use the same
spectral variation method as for Organic carbon: Kirchstetter et al (2004) below 700nm, wavelength
independent for the rest of the visible spectrum and Hess et al (1998) WASO above 4 micron. As in the
previous section, extreme caution should be used when considering the impact at longer wavelengths.
4.1.5
Secondary organic aerosols (SOA)
The main issue with regard to SOA properties is whether there should be any difference between SOA
and OC – and partly this depends on the users definition of these aerosols and, in the case of models,
the model capability to represent emissions and transformation of these as different aerosol types. In
this report we have recommended a refractive index for OC which has considerable absorption in the
visible. Dinar et al (2007) report that HULIS from a remote continental site was considerably less
absorbing than HULIS from more polluted examples, having refractive indices of 1.56 -0.003i. HADGEM2
assumes that there is no absorbing component to SOA – this is based on the refractive indices retrieved
from remote forested AERONET sites in Russia. Myhre and Neilsen (2004) state that “organic aerosols
consisting only of aqueous organic acids and water have a pure scattering effect”. However a more
recent study by Shapiro et al (2009) suggests that when glyoxal is present in conjunction with
ammonium sulphate or ammonium nitrate, the aerosol formed develops absorption capabilities at 400600nm within a few days. We therefore recommend that SOA is given different refractive indices if
practicable. Models which carry POM (particulate organic matter) rather than OC or SOA may wish to
adopt one or other of the values given in this report. We have tested the impact of both Dinar et al
(2007) and the values used in HadGEM2, for a log normal size distribution with radius=0.095 micron and
sigma = 1.5, density =1300 kgm-3 . There is no information on wavelength dependence available and
therefore we assume wavelength independent refractive indices.
Using the slightly absorbing refractive indices of Dinar et al (2007) results in a 60% increase in mass
extinction coefficient (due to the different real part of the refractive index), a 1.5% decrease in single
scattering albedo and a 5% decrease in asymmetry parameter. Since we have recommended a relatively
absorbing refractive index for OC, we recommend here a non-absorbing refractive index for SOA.
However, both data files are available should the user prefer to use the Dinar et al (2007) values.
4.1.6
Black Carbon (BC)
Black carbon is the atmospheric aerosol responsible for considerable absorption in the visible. However,
attempts to measure its abundance and its optical properties have been subject to technical issues
resulting in a range of values for refractive index at 550nm. In particular, Bond and Bergstrom (2006)
note that the value in the OPAC (Hess et al, 2008) data base of 1.74, -0.44i at 550nm, which is widely
used by climate modellers) is drawn from incompletely graphitised carbon and has a lower absorption
refractive index than most atmospheric soot. That study provides a range of refractive indices for black
carbon, but also discusses the inappropriateness of homogenous sphere Mie theory for this aerosol
component and it is not obvious whether the highest values of 1.95,-0.79i are appropriate for use with
homogenous Mie theory. Stier et al (2007) found that using the medium absorbing values of 1.85,-0.71i
from Bond and Bergstrom (2006) together with Mie theory and internal mixture with other aerosol
types gave the best global agreement of aerosol absorption optical depth when compared to the
AERONET network. Kirchstetter et al (2004) also measured refractive indices around 0.72 in BC samples
from urban environments, additionally finding very little wavelength dependence. Bond and Bergstrom
(2006) also recommended that the density for soot (or BC) be changed to 1.8 kg m-3, substantially higher
than that used in OPAC (1.0 kg m-3).
BC and OC both have absorbing components, and are both poorly defined. Their presence in a particular
aerosol sample is also often strongly correlated. It is therefore possible that compensation occurs
between the refractive indices – in other words it is possible to get agreement with observations by
having a too absorbing OC component and a too weakly absorbing BC component or vice versa. We
have used the more absorbing refractive indices from Bond and Bergstrom (2006) in our ADIENT
calculations, however we urge users of this document to consider the uncertainty introduced by testing
the medium absorbing refractive indices used by Stier et al (2007) if black carbon is a substantial fraction
of the aerosol. Using a spherical homogenous Mie code for lognormal distribution mean radius 0.11
micron, we tested both these refractive indices, as well as the original SOOT refractive index from Hess
et al (1998). Table 3 shows the resulting optical properties. The main difference in the mass extinction
co-efficient is due to the different density used by the OPAC study, rather than the refractive index. The
difference between optical properties using BC high and BC mid is small (~2% in kmass, SSA and g).
Testing is still underway as to the impact of the chosen refractive indices on optical closure studies
during ADIENT and EUCAARI (July 2009), but it is anticipated that this is likely to be small compared to
other uncertainties. Wavelength dependence is uncertain, but some observations suggest little
wavelength dependence and therefore wavelength independent values are used here.
4.1.7
Mineral dust (draft only, to be supplemented by information from Oxford).
Mineral dust presents some additional challenges for radiative properties. Since mineral dust occurs at a
wider range of sizes (both accumulation and coarse mode), it can have a significant impact on infrared
radiation, a fact which as led to both challenges and opportunities for the remote sensing of dust. The
refractive index of dust is also very sensitive to its mineralogy and therefore its source (e.g. McConnell et
al, 2009), particularly in the infrared region (e.g. Highwood et al, 2003). The OPAC definition of mineral
dust uses refractive indices from Patterson et al (1977) and additionally there is a WCP definition which
is also widely used. At 550nm the Patterson et al (1977) refractive indices are 1.56, -0.006 whilst the
WCP definition is 1.53, -0.008. However, recent in-situ measurements (e.g. Haywood et al, 2003,
McConnell et al, 2008) and remote sensing observations (Kaufman et al, 2001 and Dubovik et al, 2002)
suggest that mineral dust from the dominant global source, the Sahara, is substantially less absorbing in
the visible part of the spectrum than these earlier assumptions. Estimates covering both the dry andwet
seasons in the Sahara suggest an imaginary refractive index of between -0.0005 and -0.0014 (McConnell
et al, 2008). Stier et al (2007) also use a substantially less absorbing refractive index for dust at 550nm
(1.52,-0.001). One caveat that should be mentioned here is that all these results essentially apply to the
accumulation mode of the dust. More absorption is seen if the coarse mode is included (e.g. Otto et al,
2009), however the validity of specifying different refractive indices for different parts of the size
distribution is as yet unjudged. The effect of altering refractive indices in general is particularly
pronounced on the phase function for dust, which is utilised in satellite retrievals. Testing of the impact
of different refractive indices on the phase function and other properties is currently underway at
ADIENT partner the university of Oxford. During the ADIENT and EUCAARI flights, mineral dust has not
been observed. Our recommendation in the visible part of the spectrum is therefore based on work
from the Dust Outflow and Deposition to the Ocean (DODO) project, and consideration of other studies.
We recommend the adoption of the imaginary part from Kinne et al (2003) AERONET value (1.52,-0.001)
for global use in the visible part of the spectrum (with wavelength dependence in visible as in WCP),
given that this is a value between the wet and dry season values from DODO (McConnell, 2009). In the
long wave, Highwood et al (2003) found that the use of the Fouquart et al (1987) refractive indices for
dust gave the best agreement with high spectral resolution measurements of the radiative effect of dust
in the atmospheric window region between 8 and 12 micron. These values have been used from 5
microns upwards for the imaginary part of the refractive index.
Finally, the use of Mie code with dust has some significant drawbacks. Dust is most definitely not
spherical and asphericity effects can modify the optical properties derived from Mie theory. This is
particularly important for the phase function which is required by satellite retrievals. Measurements of
the phase function of mineral dust, and the development of new models for scattering are being
developed and evaluated under both ADIENT and APPRAISE CP2 projects (Hertfordshire partner).
4.1.8
Sea salt
Marine aerosols provide a significant contribution to the aerosol environment. Sea salt aerosol is usually
considered to be a component of marine aerosol consisting of seawater and dry sea salt particles and
produced by any mechanism releasing spray from the surface. The refractive index for sea salt i both
OPAC and HITRAN are obtained from the same database using reflectance and transmission
measurements made by Volz (1972) on bulk samples and calculations performed by Shettle and Fenn
(1979). Since the refractive index of sea salt will depend on relative humidity, if the pellets used in the
measurements do not remain dry there will be some ambiguity in measurements of refractive index.
The Edwards and Slingo (1996) radiation code uses refractive indices for “oceanic” aerosol, and also
provides values for NaCl. In both cases the imaginary part of the refractive index is very small, but it is 2
orders of magnitude higher for “oceanic”. It is not obvious how these should be used. At this time, we
are aware of only one additional set of measurements for sea salt refractive indices by Irshad et al
(2008). This data set suggests significant differences to the HITRAN dataset used widely, however we
have since become aware of some issues concerning the representativeness of the sample used
(Grainger, pers, comm., 2009). Until new measurements are made and the effect of these technical
issues assessed, we recommend the continued use of the Shettle and Fenn (1979) indices as in OPAC.
Note that despite the provision of separate files for coarse mode and accumulation mode in OPAC, the
refractive indices used for each are identical.
4.1.9
Other OPAC aerosol components and OPAC types
We do not think it advisable to alter the composition of the OPAC aerosol components WASO and INSO
that are in wide usage in model and satellite retrievals. It is important to note that the SOOT type in
OPAC is substantially different to the Black Carbon recommendations above, as is the MINERAL DUST.
Issues will also arise with the use of OPAC aerosol types for 2 reasons. Firstly the values for the
components might not be in agreement with those recommended above (e.g. SOOT), and secondly, the
composition of the types (e.g. URBAN) might not be appropriate in terms of recent observations.
Examining the appropriateness of all the OPAC types is beyond the scope of the present review,
however preliminary examinations of the URBAN type suggests that it has too high a fraction of SOOT
(7.9% by mass fraction) compared to urban and suburban measurements in western Europe ( 5-10%
Putaud et al, 2004; 5% Ramanathan et al, 2003), but perhaps too low a fraction for urban
measurements in developing nations (e.g. 7-15% in India, Tripathi et al, 2005; 4-12% in Mexico City,
Baumgardner et al, 2007). These errors are compounded by too low an imaginary refractive index for
soot and too low a density (Bond and Bergstrom, 2006 and Stier et al, 2007). We recommend that OPAC
types with substantial SOOT components are treated with extreme caution, and that the mineral dust
properties be updated to reflect the discussion in section 4.1.7 above.
4.2 Sizes and densities
In order to use the recommended refractive indices with Mie code to generate optical properties for
different aerosol components, we must also specify size parameters and densities. Whilst it is
recognised that size distributions vary, and an ideal situation would be to use a measured size
distribution from in-situ or AERONET retrievals in a region appropriate for your uses, or to model the
size distribution explicitly in an aerosol transport model, we acknowledge the requirement for “typical”
size parameters for various aerosol components. For ease of comparison with previous studies, we
retain the general assumption that aerosol number distributions follow a log-normal distribution of the
form:
  ln r  ln r 2 
Ntot
dN
g


exp  
1
2

dr  2  2 r ln 
2  ln  g  
g

The key parameters for definition are therefore rg the geometric mean radius and σg, the geometric
standard deviation. Table 4 gives recommendations (and sources of these) for the aerosol components
for which we have discussed refractive indices. Many of these are taken directly as used in the OPAC
database (Hess et al, 1998) due to lack of additional information. In addition, it is recognised that
representing a size distribution with a single log-normal distribution is an over-simplification. Many
measurement studies find that 3 or even more modes represent the observed size distribution more
completely. Physically this can be understood as nucleation, accumulation and coarse modes. However,
the values assigned to these will vary substantially from study to study. The user should consider
whether they wish to represent a particular case (in which case multiple modes may be required) or
whether they wish for some representative value – most likely biased towards the accumulation mode
as this is the size range thought to be most significant for shortwave radiative effects. We provide some
information on bimodal distributions where it is available, as well as a value for the accumulation mode
where possible. If using multiple modes, the relative weight of each mode (in terms of number) is also
required. The process would be to calculate the Mie properties for each mode and then compute a
weighted mean.
4.3 Calculated optical properties for single aerosol components at 550nm
We have used the Mie code of Wiscombe together with the recommended refractive indices and size
distributions to calculate optical properties Kmass, single scattering albedo and asymmetry parameter.
These are presented for 550nm in Table 5. Users wanting values at other wavelengths are advised to run
a Mie code themselves using the available files or to request data from Reading.
4.4 Mixed aerosol
OPAC has some aerosol types (e.g. URBAN) which are external mixtures of aerosol components. This
means that the optical properties for the individual components (e.g. WASO, INSO and SOOT in this
case) have been calculated and then a mixing rule applied to produce the optical properties of the
mixture. This is straightforward to do. However, many studies suggest that even a short distance away
from the source, the aerosol is not externally mixed but internally mixed – i.e. different components are
present within individual aerosol particles. In order to calculate the optical properties for an internal
mixture it is necessary to assume all the aerosol components are present in one size distribution and to
mix the refractive indices according to some mixing rules BEFORE running the Mie code to get the
optical properties of the internal mixture. This would also be appropriate if the refractive indices for
moist aerosol is required – the refractive index for the aerosol component and for water would be
mixed internally according to the mass of water (and a size change assumed using RH growth curves)
and the optical properties for the water/aerosol mix calculated using Mie code. The aerosol component
properties recommended here are suitable for use in any of these methods, but different sizes would
need to be used for internal mixtures and therefore the optical properties in Table 5 might not be
appropriate for the internally mixed aerosol.
4.5 Growth with relative humidity – hygroscopicity
It was intended to complete an evaluation of the growth of various aerosol types with RH as part of this
assessment. However, this has proved to be beyond the scope of the study in the time available. In
addition, this is an area of much recent development in terms of laboratory and in-situ studies and
process modelling. The user is therefore encouraged to make their own assessment of refractive indices
appropriate at other humidities. If this is not possible, the general OPAC and GADS data bases do
contain files for refractive indices at other relative humidities for the components and types they
consider to be hygroscopic. Using these, and taking into account the modifications to the dry aerosol
above, would give a basic idea of the likely effect of relative humidity on a particular aerosol
component. If time allows, we will extend this assessment at some point in the future. However, a basic
methodology is outlined here for internally mixing aerosol with water, and adapting the refractive index
and size to account for RH. The steps to take are:
1. Find growth factor (GF) for approximately the right size of aerosol component at relative
humidity RH GF(RH)=radius(RH)/radius (dry)
Various measurements or modelling studies can be used. Example values for main anthropogenic
aerosols of different sizes at 90% can be found in Table 6. BC and Mineral dust are assumed to have a
GF=1.
2. Calculate volume of aerosol droplet at new and old radii – the difference in volume will give you
the volume of water that has been added.
3. Then use the volume weighted mixing rule to work out new refractive index and density of the
combined aerosol and water
4. If you have multi-component aerosol, then one plausible assumption is the ZSR assumption
whereby the uptake of water by each component is independent of what the other components
of the aerosol are doing. The GF of the mixture is then just a volume weighted average of the GF
for individual components such that
GFmix
 V j GFj 3 
 j



 V j 
j


1
3
Aerosol
component or
type
Sulphate
Sea salt
Black carbon
(BC)
Leeds –
GLOMAP
RAL (0.512
micron)
1.53, -6e-03
1.5, -1e-08
OLD 1.75, -0.44
NEW 1.95, -0.79
As Leeds
As Leeds
As Leeds
Organic
carbon (OC)
OLD 1.60, -0.001
NEW 1.63, -0.021
As Leeds
Secondary
organic
aerosol (SOA)
Nitrate
OLD 1.60, -0.001
NEW 1.63, -0.021
As Leeds
Oxford
Reading
(ADIENT)
1.53, 0
1.95, -0.79 (Bond
and Bergstrom,
2006)
1.634, -0.021
(Dinar et al, 2008
– note this is valid
at 532 nm)
1.44, +0.0 in
visible
Volz (1974)
and OPAC in
infrared
Dust
Biomass
burning
aerosol
Water Soluble
Insoluble
Sea salt
(accumulation
and coarse)
Mineral dust
(nucleation,
accumulation,
coarse)
Notes
Imperial
College
1.61, 0 i (Weast,
1985)
1.53, -0.005 to 0.0014 (Saharan
dust, McConnell,
2009)
1.52, -0.015 (Cerrado
value from Dubovik et
al 2002)
OPAC 1.53, -0.006
OPAC 1.53, -0.008
OPAC 1.51, -0.1e-07
(same for both
modes)
OPAC 1.53, 0.55 e-02
for all 3 modes
Uses wavelength
independent
value
Also uses types
Dust value
maritime clean,
depends on
continental clean,
season/source
desert dust and urban
Table 1: Use of refractive indices for aerosol as at April 2009 by ADIENT groups. “Components” are in bold, “types”
– typically made up of some of these components – are italic. Unless otherwise specified values quoted are (Re,
Im) of refractive index for 550nm: values may or may not be available at other wavelengths. Negative values imply
absorption. For Leeds, OLD refers to values used before the ADIENT project, NEW refers to those currently in use
based on discussions within ADIENT. Blank cells suggest that this type or component is not utilised by this group.
OPAC refers to models defined by Hess et al (1998).
Aerosol
component
Recommended
value at 550nm
Sulphate
1.53 -0i
Suggestion for
extension to multiwavelengths
Included in data file
Data file available (at
ADIENT site)
References (see also
separate notes in
main text)
refract_ammoniumsulphate
_lf
Refract_ssam_opac
Refract_bc_high
Refract_bc_med
Toon et al (1976) and
numerous others.
Sea salt
Black carbon
(BC)
1.50-1e-08i
1.95-0.79i
(1.85 -0.71i)
Included from OPAC
Wavelength
independent.
Organic
carbon (OC)
1.63-0.021i
refract_organicc_new
Secondary
organic
aerosol (SOA)
1.43-0i
(1.53-0.003i)
Included based on
Kirchstetter et al for
absorp. And Hess et
al (1998) for IR.
Wavelength
independent
Nitrate
1.60-0i
Included in data file
refract_nitrate
Dust
1.52-0.001i
Wavelength
dependency from
WCP to 5 microns,
Fouquart (1987) at
longer wavelengths
refract_dust_wcp_fou
Biomass
burning
aerosol
1.54-0.018i
refract_biomass_new
SAFARI
Sulphuric Acid
(stratospheric
aerosol)
1.43-1e-07i
Included for
imaginary part from
Kirchstetter et al,
Hess et al (1998)
WASO dependency
for IR.
included
Refract_sulphuric
75% H2SO4 as suggested
for stratospheric
aerosols. Comes from
d’Almeida et al, 1991
refract_soa_hadgem2
(refract_soa_dinar)
Table 2: Recommendations for DRY (0% RH) refractive indices
Shettle and Fenn
Bond and Bergstrom
(2006)
Alternate from Stier et al
(2007)
Dinar et al (2007),
Kirchstetter et al (2004)
Remote russion forested
AERONET sites
(HADGEM2). (Alternate
is rural HULIS from Dinar
et al (2007))
Weast (1985) below 0.7
micron, Gosse et al
(1997) 0.7 to 2.0 micron
and Jarzembski et al
(2003) 2.0-20 microns
Kinne et al (2003), WCP
(2003), McConnell
(2009) and Highwood
(2003)
(Alternate wavelength
independent in visible)
BC refractive indices
k (m2 g-1)
ssa
Asymmetry parameter,
g
BC high
7.36
0.20
0.27
BC mid
6.97
0.18
0.28
Soot OPAC
9.04
0.19
0.32
Table 3. Optical properties for lognormal distribution of BC with mean radius 0.011 micron, s.dev 2.0. For BC high
and BC mid the density of BC is assumed to be 1800 kg/m3 as recommended in Bond and Bergstrom (2006). For
Soot OPAC, the value of 1000 kg/m3 is used as recommended by Hess et al (1998).
Aerosol component
rg (µm)
σg
Density (kg m-3)
Reference
Sulphate
0.05
2.0
1769
Numerous including Penner et al
(1998)
Sea salt
0.209 (Accumulation
mode)
2.03 (both
modes)
2200
Hess et al (1998), Koepke (1997)
1.75 (coarse mode)
Black carbon (BC)
0.0118
2.0
1800
Hess et al, (1998); Bond and
Bergstrom (2006)
Organic carbon (OC)
0.12
1.3
1470
HADGEM2 FFOC
Dinar et al (2007)
Secondary organic
aerosol (SOA)
0.095
1.5
1300
HADGEM2 AERONET remote
forested sites (N. Bellouin, pers
comm. 2009)
Nitrate
0.065
2.0
1725
Weast (1985)
Some suggestions from Jimenez et
al (2003) that nitrate is slightly
larger than sulphate in
anthropogenic aerosol. Very little
information found
Dust
0.31
1.5
2650
Accumulation mode from
McConnell (2009) – sigma here is
probably an underestimate
Biomass burning
aerosol
0.16
1.25
1350
Aged mode from Johnson et al
(2008)
(0.08)
(1.5)
Additional mode is present at
smaller radii – this is similar to
parameters for fresh biomass. No.
Fraction is 0.75 in small mode and
0.25 in larger mode if combining
Sulphuric acid
(stratospheric
aerosols)
0.07
1.6
1700
Deshler et al (2003) Background
stratospheric aerosol (volcanic is
larger)
Table 4. Recommendations for size parameters for the log-normal distribution and densities outlined in section
4.2
Aerosol component
Ke (m2/g)
SSA (ω)
Asymmetry parameter,
g
Sulphate
3.62
1.00
0.643
Sea salt
1.26
1.00
0.689
Black carbon (BC)
7.50 (7.19)
0.21 (0.19)
0.280 (0.291)
Organic carbon (OC)
6.20
0.91
0.576
Secondary organic
aerosol (SOA)
Nitrate
3.48 (5.55)
1.00 (0.99)
0.630 (0.601)
0.42
1.00
0.616
Dust
1.92
0.99
0.678
Biomass burning aerosol
6.45 (0.43)
0.92 (0.90)
0.652 (0.564)
Stratospheric aerosol
2.26
1.00
0.599
Table 5. Aerosol optical properties at 550nm (0 % RH) calculated using the refractive indices and size distributions
recommended in this report. Values in brackets are for alternative refractive indices data as in table 2.
Aerosol component
GF(90%)
GF(90%)
GF(90%)
GF(90%)
R=30nm
R=45nm
R=69nm
R=108 nm
Sulphate (ammonium sulphate)
1.66
1.69
1.70
1.72
Sulphuric acid
2.02
2.04
2.05
2.06
Ammonium nitrate
1.74
1.78
1.80
1.82
Organics
1.11
1.12
1.12
1.12
Table 6: Example growth factors for 4 aerosol components at 90% RH and 4 different submicron sizes. Taken from
Topping et al (2005a). Note that sulphuric acid has a growth factor of 1.15 at RH = 5-10%. This excess water
content is accounted for when calculating the predicted g at RH=90%.
References
D’Almeida, G.A, P. Koepke and E.P. Shettle (1991) Atmospheric Aerosols: Global Climatology and
Radiative Characteristics. A. Deepak Publishing, 561 pages.
Baumgardner, D., G.L. Kok and G.B. Raga (2007) On the diurnal properties related to Mexico City. Atmos,
Chem. Phys. Disc., 7, 1623-1653
Bond, T.C. and R. W. Bergstrom (2006) Light absorption by carbonaceous particles: An investigative
review, Aerosol Sci Tech, 30, 582-600
Chand, D. P. Guyon, P. Artaxo, O. Schmid, G.P. frank, L.V. Rizzo, O.L. Mayol-Bracero, L.V. Gatti and M.O.
Andreae (2006) Optical and physical properties of aerosol in the boundary layer and free troposphere
over the Amazon basin during the biomass burning season., A.C. P., 6, 2911-2925
Cook, J., E. J. Highwood, H. Coe, P. Formenti, J.M. Haywood and J. Crosier (2007) A comparison of
aerosol optical and chemical properties over the Adriatic and Black Seas during summer 2004: two case
studies from ADRIEX., Q. J.R.Met.S., 133 (S1), 33-45
Deshler, T., M.E. Hervig, D.J. Hoffmann, J.M. Rosen and J.B. Liley (2003) Thirty years of in situ
stratospheric aerosol size distribution measurements from Laramie, Wyoming (41N) using balloon-borne
instruments, J. Geophys. Res., 108, doi:10.1029/2002JD002514
Dinar, E., A. Abo Riziq, C. Spindler, C. Erlick, G. Kiss and Y. Rudich (2007): The complex refractive index of
atmospheric and model humic-like substances (HULIS) retrieved by a cavity ring down aerosol
spectrometer (CRD-AS). Faraday Discussions, 137, 279-295.
Dubovik, O., B. Holben, T.F.Eck, A. Smirnov, Y.J. Kaufman, M.D. King, D. Tanre and I. Slutsker (2002)
Variability of absorption and optical properties of key aerosol types observed in worldwide locations, J.
Atmos. Sci., 59, 590-608
Fouquart, Y., B. Bonnel, G. Brogniez, J.C. Buriez, L. Smith ad J.J. Morcrette (1987) Observations of
Saharan aerosols: Results of ECLATS field experiment part II, Broadband radiative characteristics of
aerosols and vertical flux divergence, J. Clim., Appl. Meteorol., 26, 38-52.
Gosse, S.F., M. Wang, D. Labrie and P. Chylek, (1997) Imaginary part of the refractive index of sulphates
and nitrates in the 0.7-2.6 micron spectral region. Applied optics, 36,3622-3634
Guyon P., B. Grham and G.C. Roberts et al (2004) Sources of optically active aerosol particles over the
Amazon forest. Atmos. Environ., 38, 1039-1051
Haywood, J., P. Francis, S. Osborne, M. Glew, N. Loeb. E. Highwood, D. Tanre, G. Myhre, P. Formenti, and
E. Hirst (2003) Radiative properties and direct radiative effect of Saharan dust measured by the C-130
aircraft during SHADE:1. Solar spectrum. J. Geophys. Res., 108, doi:10.1029/2002JD002687
Hess, M. Koepke, P. , and I. Schult (1998) optical properties of aerosols and clouds: The software
package OPAC, B. Am. Meteorol. Soc., 79, 831-844
Highwood, E., Haywood, J., Silverstone, M., S. Newman and J. Taylor (2003) Radiative properties and
direct effect of Saharan dust measured by the C-130 aircraft during Saharan Dust Experiment (SHADE) 2.
Terrestrial spectrum. J. Geophys. Res., 108, doi:10.1029/2002JD002552
Hoffer, A., A. Gelencser, P. Guyon, G. Kiss, O. Scmid, G.P. Frank, P. Artaxo and M.O. Andreae (2006)
Optical properties of humic-like substances (HULIS) in biomass-burning aerosols. Atmos. Chem. Phys., 6,
3563-3570.
Irshad, R., R.G. Grainger, D.M.Peters, R.A. McPheat, K.M. Smith and G. Thomas. Laboratory
measurements of the optical properties of sea salt aerosol, Atmos. Chem. Phys. Discuss., 8,71-94 (2008)
Jarzembski, M.A., M.L. Norman, K.A. Fuller, V. Srivastave and D.R. Cutten (2003) Complex refractive
index of ammonium nitrate in the 2-20 micron spectral range. Applied optics, 42, 922-930.
Jimenez, J.L. et al (2003) Ambient aerosol sampling using the Aerodyne Aerosol Mass Spectrometer, J.
Geophys. Res., 108, doi:10.1029/2001JD001213
Johnson, B.T., S.R. Osborne, J.M. Haywood and M.A.J. Harrison (2008): Aircraft measurements of
biomass burning aerosol over West Africa during DABEX. J. Geophys. Res., 113,
doi:10.1029/2007JD009451
Kinne, S. et al (2003) Monthly averages of aerosol properties: A global comparison among models,
satellite data and AERONET ground data. J. Geophys. Res. 108, 4634, doi:10.1029/2001JD001253
Kirchstetter, T., T. Novakov and P. Hobbs (2004) Evidence that the spectral dependence of light
absorption by aerosols is affected by organic carbon. J. Geophys. Res., 109, doi:10.1029/2004JD004999
Koepke, P., m. Hess, I. Schult and E.P. Shettle (1997) Global aerosol data set. MPI Meteorologie Hamburg
Rep.243 44 pp
Kreckov, GM (1993) Models of atmospheric aerosols. In Aerosol Effects on Climate, Jennings SG
(Ed),University of Arizona Press: Tucson, Arizona
McConnell, C. (2009) Aircraft measurements of Saharan dust. PhD Thesis, University of Reading.
McConnell, C., E. Highwood, H. Coe, P. Formenti, B. Anderson, S. Osborne, S. Nava, K. Desboeufs, G.
Chen and M. Harrison (2008) Seasonal variations in the physical and optical characteristics of Saharan
mineral dust: results from the Dust outflow and Deposition to the Ocean Experiment. J. Geophys. Res.
113, doi:1029/2007JD009606
McConnell, C., P. Formenti, E.J. Highwood and M.A.J. Harrison (2009) Using aircraft measurements to
determine the refractive index of Saharan dust during the DODO Experiments, Submitted A.C.P.D., 2009
Myhre, C and C. Nielsen (2004) Optical properties in the UV and visible spectral region of organic acids
relevant to tropospheric aerosols, A.C.P., 4, 1759-1769
Otto, W., E. Bierwith, B. Weinsierl, K. Kandler, M. Esselborn, M. Tesche, A. Schladitz, M. Wendisch, and
T. Trautmann (2009) Solar radiative effects of a Saharan dust plume observed during SAMUM assuming
spheroidal model particles, Tellus B, 61B, 270-296
Patterson, E., D. Gillette and B. Stockton (1977) Complex index of refraction between 300 and 700nm
for Saharan aerosols, J. Geophys. Res., 82, 3152-3160
Penner, J., C. Chuang and K. Grant (1998) Climate forcing by carbonaceous and sulphate aerosols,
Climate Dynamics, 14,839-851
Putaud, J.P. et al (2004) A European aerosol phenomenology – 2: chemicat characteristics of particulate
matter at kerbside, urban, rural and background sites in Europe. Atmospheric Environment. v38. 25792595.
Ramanathan, V. and P. Crutzen (2003) New directions: atmospheric brown clouds, Atmospheric
Environment, 37, 4033-4035
Shapiro, E.L., J., Szprengiel, N. Sareen et al (2009) Light-absorbing secondary organic material formed by
glyoxal in aqueous aerosol mimics. A.C.P., 9, 2289-2300
Shettle, E.P. and R.W. Fenn (1979) Models for the aerosols of the lower atmosphere and the effects of
humidty variations on their optical properties. AFGL-TR-79-0214.
Stier, P. J.H. Seinfeld, S. Kinne and O. Boucher (2007) Aerosol absorption and radiative forcing. Atmos.
Chem. Phys., 7, 5237-5261
Toon, O.B., J.B. Pollack and B.N. Khare (1976) The optical constants of several atmospheric aerosol
species: ammonium sulphate, aluminium oxide and sodium chloride” J. Geophys. Res., 81, 5733-3748
Topping, D., et al (2005) A curved multicomponent aerosol hygroscopicity model framework: Part 1 –
Inorganics. Atmos. Chem. Phys. Disc., 4, 8627-8676
Tripathi, S., S. Dey and Tare (2005) Aerosol black carbon radiative forcing at an industrial city in northern
India, Geophys. Res. Letts, 32, L08802, doi:10.1029/2004JD004548
Volz, F.E. (1972) Infrared refractive index of atmospheric aerosol substances, Appl. Optics, 11, 755-759.
Volz, F.E. (1974) infared optical constrants of ammonium sulphate, Sahara dust, volcanic pumice and
flyash, Appl. Opt., 12(3) 564-567.
Weast, R. (ed) (1985) Handbook of Chemistry and Physics, 66th edition. CRC Press: Florida.
WCP, editor (1983) WMO Report of the Experts’ Meeting on Aerosols and their Climatic Effects, number
WCP-55, Geneva, Switzerland, World Meteorol. Org.