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Appendix A: Tests of the dust model

	Fig. A.1 Fits of the far-infrared (λ> 20 μm) SED of the nebula around AG Car. The dust composition (optical constants of silicates with a 50/50 Mg-to-Fe abundance given by Dorschner et al. 1995) and acen are kept constant while the value of amax changes.
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	Fig. A.2 Fits of the far-infrared (λ> 20 μm) SED of the nebula around AG Car. The dust composition (optical constants of silicates with a 50/50 Mg-to-Fe abundance given by Dorschner et al. 1995) and amax are kept constant while the value of acen changes.
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In Sect. 4 the model of the dust nebula is presented and the necessity of a population of large dust grains is stressed. Several tests have been performed using the 2-Dust code in an effort to reproduce the observed data with different populations of dust grains from those adopted in Sect. 4. Our main concern was to investigate the influence of the dust grain size and composition on the model SED. For this reason, we calculated many models by changing one parameter and keeping the other ones constant. Keeping in mind that two different populations of grains were used to reproduce the broad observed SED in Sect. 4, we consider one population of small grains with radii a_min<a<a_cen and one population of large grains with radii a_cen<a<a_max. For the dust composition, we used the optical constants given by Dorschner et al. (1995) for three different abundances of Mg to Fe, 0.5/0.5 (the model presented in Sect. 4), 0.4/0.6, and 0.8/0.2. For the dust grain sizes, the values of 20, 50, and 80 μm were considered for a_max and the values of 0.1, 0.3, 1, and 3 μm were considered for a_cen, with the value of a_min being kept constant and equal to 0.005 μm.

The comparison of these tests shows that large grains are necessary to reproduce the data. The influence of the change of a_cen on the fit of the observed SED is almost negligible. Furthermore, the fit depends little on the dust abundance of Mg to Fe. This is illustrated in Figs. A.1–A.3. In Fig. A.1 three dust models are illustrated. The dust composition is the same (optical constants of silicates with a 50/50 Mg-to-Fe abundance given by Dorschner et al. 1995) and the only parameter that changes is a_max. We see that better fits to the data are achieved when large grains are considered, in particular when a_max = 50 μm. In all cases, when adjusting the observed flux at 250 μm, a value for a_max that is too small (<20 μm) gives too much flux at 60−100 μm. In Fig. A.2 the comparison of three models with the same a_max and dust composition but with different a_cen is illustrated. The model SED depends little on a_cen. In Fig. A.3 the comparison of three models with the same grain sizes but different dust composition (in terms of the abundance Mg to Fe) is illustrated. Again, the model SED depends little on this dust abundance ratio, with a slightly better adjustment for Mg/Fe = 50/50. We finally note that changing the power law index of the grain size distribution does not significantly affect these results.

	Fig. A.3 Fits of the far-infrared (λ> 20μm) SED of the nebula around AG Car. amax = 50μm and acen = 1μm are kept constant while the dust composition changes. The optical constants of silicates given by Dorschner et al. (1995) are used for different Mg-to-Fe abundances.
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Appendix B: Modified blackbody fit on the SED

	Fig. B.1 Same as Fig. 5 but the infrared SED of the nebula around the LBV AG Car is fitted by the sum of two modified blackbody curves.
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The observed SED (Fig. 5) can also be reproduced with a simpler model that is the sum of two modified BB curves F_ν ∝ B_ν(T_d)ν^β. Only the photometric points were considered for making the fit illustrated in Fig. B.1. The mass of the dust can then be derived using the equation (B.1)where κ_ν is the mass absorption coefficient, i.e. the absorption cross section per unit mass, B_ν the Planck function and D the distance to the nebula (Hildebrand 1983). For this calculation, the two populations of dust grains are considered independently. The fluxes measured at 25 μm and 250 μm are used, i.e., at those wavelengths where the contribution of each population dominates (Fig. B.1). At 25 μm, κ_ν = 483 cm² g^-1 for the silicates of Dorschner et al. (1995). For grains of radii smaller than the wavelengths at which dust radiates, κ_ν is roughly independent of the radius and behaves as ν^β in the far-infrared. However the second population of dust grains involves large grains (up to 50 μm) so that this hypothesis is no longer valid. The value of κ_ν is then taken from the 2-Dust results where it is explicitly

computed for the adopted grain population. At 250 μm, κ_ν = 13.6 cm² g^-1, which is significantly higher than expected under the small-grain approximation. With such large grains the frequency dependence of κ_ν also differs from the ν² law, being closer to ν¹ below 100 μm. A fit with such a composite modified BB gives T_dust,1 = 76 K and T_dust,2 = 31 K (which is only slightly different from the values obtained with ν² only). Using T_dust,1 = 76−78 K and T_dust,2 = 31−33 K in Eq. (B.1), we then derive M_dust,1 = 0.05−0.04M_⊙ and M_dust,2 = 0.22−0.19 M_⊙ for the small and the large grains respectively, in very good agreement with the 2-Dust results.

Appendix C: Emission line fluxes for each spaxel

The results of the emission line flux measurements for each spaxel are given in Table C.1. The first column contains the detected ions along with the spectral band in which the corresponding line was measured. The following columns contain the line fluxes, expressed in W/m², along with their errors. The spaxel numbers (Fig. 6) are mentioned in every cell of the table. The quoted uncertainties are the sum of the line-fitting uncertainty plus the uncertainty due to the position of the continuum.

© ESO, 2015