## 4. Analysis of the spectral energy distributionIn Fig. 4 we have plotted available observational data for IRAS 22272 5435.
Spectroscopic data plotted (shown by thin continuous lines) include
the KAO spectrum in the range 16-49 In Fig. 4 we also present two sets of photometry (from B to M bands) corrected for interstellar extinction according to the average extinction law of Cardelli et al. (1989), assuming the total extinction at V of 1.0 or 2.0 magnitudes and plotting only the smallest and largest values of the corrected fluxes for a given band. This estimate of the total extinction was inferred from Fig. 6o (304) of Neckel & Klare (1980). The total extinction in the direction of this object shows some scatter but is almost independent of distance for 1 kpc. During modelling we tried to arrange that our model energy distribution, when normalized to the NIR data, fell in between the two sets of corrected fluxes. In this way we have taken into account the effect of the interstellar extinction. This is important for the determination of the star luminosity, or more exactly for . Without taking into account the interstellar extinction, the derived value would be lower. In spite of the possible variability of the source in the visible
and UV (Hrivnak & Kwok 1991), all photometric measurements in the
NIR seem to be in agreement with each other (within the estimated
observational errors) and agree with the available NIR and MIR
spectroscopy. This is in agreement with the variability index (only
3 % over a 6 month interval) assigned to the IRAS data. There is also
an excellent agreement between the KAO observations and the IRAS
fluxes: integrating the KAO spectrum over the profile of the 25
Adopting a dust mixture made of PAHs, AC grains and including the
empirical opacity function which was discussed in Sect. 3, we derived
the fit to the spectral energy distribution of IRAS 22272 shown
in Fig. 4 by the heavy solid line (as one can see our model is able to
explain quite well almost all important aspects of the observed SED).
The dashed line with arrow indicates the beam effect of the IRAM
observations at 1.3 mm (HPBW of the telescope was
- see Walmsley et al. 1991). Our model
predicts a flux density (21.5 mJy) which is consistent with the flux
density observed by Walmsley et al. (16.5
4.3 mJy). The small difference could be easily explained by slightly
different slope of dust optical properties at sub-millimeter
wavelengths. The thin long-dashed line represents the input energy
distribution of the central star for log(g) = 0.5 and
= 5300 K according to model atmosphere
calculations by Kurucz (private communication). The inset in this
figure shows MIR part of the spectrum in some more details. The solid
line represents our best fit which takes also into account quantum
heating effects. The dotted line plotted from 4 to 11
As we can see from Fig. 4 a small amount of hot dust seems to be
necessary (about 6.75 10 To estimate the infrared emission underlying the 21 and 30
Fig. 5 presents the model results (without the observational data
and now for less than about
200
the 21 and 30 As mentioned before, the available opacity data for MgS grains does
not provide sufficient information to carry out detailed quantitative
modeling. However, we can estimate the IR emission due to sulfides by
assuming that the shell is optically thin and that quantum effects are
not important near 30 For sulfide dust grains with a size distribution given by which are in thermal equilibrium inside an optically thin shell, we can write the contribution to infrared energy emitted per cubic centimeter as follows where means dust specific density. The mass
absorption coefficient for sulfides in the far-infrared is not a
function of dust size, so the only hidden dependence on where is the density of sulfide grains at
distance where the factor 0.71 assumes a ratio of 0.1 and represents the fraction of MgS in the MgS-FeS mixture ( 0.9 was taken). Finally, with some simplifying assumptions, we obtain a formula for the volume emissivity of sulfides with the only one unknown, in fact the most important quantity, which is the dust temperature itself. In Fig. 6 we show the highest dust equilibrium temperature distribution
as obtained from the modeling of IRAS 22272 for PAH molecules with
size To compute the total IR energy emitted by the shell we took into
account the IR continuum level under the 30
Both fits require n(S)/n(H) = 4 10 Finally, to verify consistency of our model (which has been
constructed by modeling of the spectral energy distribution) we
compare its prediction with more detailed information about spatial
distribution of emission at MIR wavelength. For this purpose we
selected an image of IRAS 22272 at 11.8 In Fig. 9 we present normalized scan by means of open circles
together with a gaussian of FWHM =
representing the beam profile (dashed line). To get the model scan we
convolved the model surface brightness at 11.8
© European Southern Observatory (ESO) 1997 Online publication: July 8, 1998 |