Fall 2013 BCD Research

8/13/2019 Fall 2013 BCD Research

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Dust to Gas Ratio as a Function of Metallicity,

Focusing on Blue Compact Dwarfs and Other Extremely

Metal-Deficient Galaxies

Kevin M. Goehring1

Astronomy Department, University of Virginia, Charlottesville, VA, 22904

[email protected]

ABSTRACT

I present the dust-to-gas ratio (DGR) of a selection of 85 diverse galaxies covering a wide rangeof morphological types and with oxygen abundances ranging from 7.10


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taining a fairly diverse sample.

In the hierarchical model of galaxy formationlarger spiral and elliptical galaxies form through

the merging of smaller dwarf galaxies. There-fore metal-deficient dwarf galaxies are of criti-cal importance to the cosmic landscape. Whilethe exact age of these galaxies is still a subjectof much debate (Kunth & Ostlin 2006), as theleast chemically evolved galaxies thus far discov-ered in the local Universe, they represent the op-portunity to study star formation and metal en-richment in conditions that may be analogous toearly, high-redshift galaxies (Mateo (1998); Thuan(2008)). BCDs are the most promising candidatesdue to their bright emission lines and high sur-face brightness. It is thus more likely to discover

them, derive their metal content, and obtain highquality data, although there exists examples ofother extremely metal-poor types of dwarf galax-ies. This paper references a definition of ex-tremely metal deficient galaxy (XMD) as thosehaving 12+log(O/H)7.65 (Pustilnik & Martin2007). This value is approximately 10% or lessthan the solar abundance 12+log(O/H) = 8.69(Asplund et al. 2009).

The organization of this paper is as follows.In 2 I describe the selection and basic charac-teristics of the galaxy sample. In 3 interstellar

dust, dust model evaluation, and implementationof the selected dust model are discussed. I coverthe calculation of the total gas mass in 4, with aparticular emphasis on attempts to estimate themass of molecular hydrogen in galaxies with nodetected CO emissions by using star formationrates (SFR). The dust-to-gas ratio is evaluatedand compared to other DGRs found throughoutthe literature in 5. Finally, summary of the re-sults may be found in 6. This study adopts aHubble constant of H0 = 73 km s

1 Mpc1 andrescales results from the literature where applica-ble.

2. Galaxy Sample

The following conditions predicate the galaxysample. [1]: A wide range of metallicites witha focus on gathering as many galaxies with12+log(O/H)8.2. This has been found to bea critical threshold for mid-infrared (MIR) poly-

cyclic aromatic hydrocarbon (PAH) features, withgalaxies at lower metallicites having weaker fea-tures (e.g. Thuan et al. (1999); Galametz et al.

(2011)). In 3.2 the implementation of our se-lected dust model will show why this is a keyparameter.[2]: Dust warmed by starlight is promi-nent in MIR emission while cooler dust is revealedin the far-infrared (FIR). Therefore, to estimatethe dust mass effectively, our sample includesgalaxies with positive detections from the SpitzerSpace Telescope provided by the Infrared ArrayCamera (IRAC) and the Multiband Image Pho-tometer for Spitzer (MIPS). [3]: A diverse samplingof galaxy morphological types for unbiased homo-geneity [4]: For total gas mass estimation galaxiesneed 21 cm emissions for atomic gas and, in or-

der of preference, either CO emission to trace themolecular gas or H to indirectly estimate H2using star formation rates.

I first examined the samples from Lisenfeld &Ferrara (1998) and Engelbracht et al. (2008). Thisprovided a good starting point with low-Z galax-ies and also would allow for dust mass compar-isons. The sample was augmented by includinggalaxies from the Spitzer Infrared Nearby Galax-ies Survey (SINGS) as described in Kennicutt etal. (2003) for comparison with the Draine & Li(2007) dust model and the dust mass estimatesof Draine et al. (2007). I searched the liter-ature, mainly utilizing the NASA/IPAC Extra-galactic Database (NED) and the Lyon-MeudonExtragalactice Database (LEDA), in order to sat-isfy the aforementioned conditions and increasethe sample size. The resulting galaxy sample isprovided in Table 1 and listed in order of in-creasing oxygen abundance. It achieves the de-sired balance in metallicity with 50% of our85 galaxies having 12+log(O/H)


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Table 1

Galaxy Sample and Basic Information

DGalaxy 12+log(O/H) References (J2000) (J2000) (Mpc) Morphological Type

SBS 0335-052 W 7.10 2 03h 37 43.8 -05 02 40 53.83.8 BCDI Zw 18 7.20 1 09h 34 02.1 55 14 25 13.91.0 i0 BCD

SBS 0335-052 E 7.25 2 03h 37 43.8 -05 02 40 543.8 BCDUGCA 292 7.27 2 12h 38 40.1 32 45 59 3.210.25 Im

HS 0822+3542 7.46 1 08h 25 55.4 35 32 32 11.0a iI,C BCDESO 489-G56 7.49 2 06h 26 17.8 -26 15 58 4.230.3 dIrr

Sextans A 7.49 3 10h 11 00.8 -04 41 34 1.43b IBmTol 1214-277 7.50 2 12h 17 17.1 -28 02 33 105.77.4 HII

UGC 4483 7.53 2 08h 37 03.3 69 46 29 5.000.35 iI,C BCDDDO 154 7.54 4 12h 54 05.4 27 08 55 3.660.27 DIrr

Tol 65 7.54 6 12h 25 46.9 -36 14 01 36.3c i0 BCD

KUG 1013+381 7.59 6 10h 16 24.5 37 54 46 15.8c BCDSBS 1415+437 7.59 5 14h 17 01.9 43 30 18 11.660.83 iI,C BCD

DDO 53 7.60 4 08h 34 07.2 66 10 54 2.420.17 ImHolmberg I 7.61 4 09h 40 32.4 71 10 56 4.740.34 dIrr

SBS 1102+606 7.62 6 11h 05 53.7 60 22 29 19.9c BCDDDO 165 7.63 4 13h 06 24.8 67 42 24 3.01 0.21 dIrr

ESO 146-G14 7.66 2 22h 13 00.0 -62 04 05 21.31.5 SBdVII Zw 403 7.71 2 11h 27 58.8 78 59 38 1.420.10 iE BCDHolmberg II 7.72 4 08h 19 05.0 70 43 12 4.890.35 BCD

UM 461 7.78 5 11h 51 33.1 -02 22 23 12.40.9 BCDDDO 187 7.79 2 14h 15 56.6 23 03 16 2.070.15 Im

NGC 5408 7.81 4 14h 03 21.0 -41 22 42 4.540.32 IBmMrk 209 7.82 1 12h 26 16.1 48 29 39 4.760.34 iE BCDMrk 153 7.83 2 10h 49 05.0 52 20 08 32.9d BCD

M81 Dw B 7.84 4 10h 05 30.6 70 21 52 8.250.59 ImIC 2574 7.85 4 10h 28 23.6 68 24 44 3.090.22 SABm

Mrk 178 7.88 1 11h 33 29.1 49 14 12 4.20.29 iI,M BCDUGC 4393 7.95 2 08h 26 04.6 45 58 03 32.02.2 SB

UM 462 7.95 5 11h 52 37.5 -02 28 10 13.20.9 pec, HIINGC 2366 7.96 7 07h 28 54.6 69 12 57 3.44e IBm

Pox 4 7.96 2 11h 51 11.6 -20 36 02 49.03.7 iI,M BCDMrk 1450 7.99 2 11h 38 35.7 57 52 27 17.81.3 nE BCDUM 448 7.99 5 11h 42 12.3 00 20 02 76.95.4 Sb, pec

NGC 4861 8.01 2 12h 59 00.2 34 50 39 10.7e iI,C BCDMrk 930 8.08 5 23h 31 58.6 28 56 52 77.45.4 Wolf-RayetMrk 170 8.09 2 11h 26 50.4 64 08 20 18.41.3 BCD

NGC 6822 8.12 6 19h 44 57.8 -14 48 11 0.496f IBmII Zw 40 8.13 1 5h 55 42.8 3 23 30 10.40.7 iI,M BCD

NGC 1569 8.13 2 4h 30 49.3 64 50 53 1.450.12 IBmMrk 1094 8.15 2 5h 10 48.0 -02 40 54 37.42.6 iI BCD

NGC 3310 8.18 2 10h 38 45.9 53 30 11 18.01.3 SABbc pecNGC 1156 8.19 2 02h 59 42.3 25 14 16 6.920.48 IBm

NGC 5253 8.19 2 13h 39 56.0 -31 38 36 2.790.2 pecTol 2 8.22 2 9h 59 21.2 -28 08 00.0 11.30.8 iE BCD

NGC 4449 8.23 2 12h 28 10.9 44 05 33 3.230.23 IBmNGC 7714 8.26 2 23h 36 14.2 02 09 16 39.12.7 SBb, pec

Haro 2 8.3 6 10h 32 31.8 54 24 04 24.21.7 nE BCDUGC 4703 8.31 2 08h 58 29.8 06 19 16 50.73.6 Wolf-Rayet

UM 311 8.31 5 01h 15 30.8 -00 51 38 231.6 Wolf-Rayet

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Table 1Continued

DGalaxy 12+log(O/H) References (J2000) (J2000) (Mpc) Morphological Type

NGC 1140 8.32 2 02h 54 33.4 -10 01 43 19.41.4 IBm, pecNGC 1510 8.33 2 04h 03 32.5 -43 24 01 10.00.7 S0/a

Haro 3 8.34 1 10h 45 22.4 55 57 36 17.41.2 iE BCDNGC 628 8.35 4 01h 36 41.7 15 47 01 10.480.74 SAc

NGC 4214 8.36 2 12h 15 39.1 36 19 41 3.430.25 IABmNGC 2976 8.36 4 09h 47 15.4 67 54 59 2.180.15 SAc, pecNGC 4670 8.38 2 12h 45 17.1 27 07 31 21.01.5 nE BCDNGC 6946 8.40 4 20h 34 52.3 60 09 14 5.520.39 SABcdNGC 3031 8.43 4 09h 55 33.2 69 03 55 1.680.13 SAabNGC 3773 8.43 4 11h 38 12.9 12 06 43 10.10.7 SA0NGC 2537 8.44 2 08h 13 14.6 45 59 29 7.660.54 iE BCDNGC 2552 8.44 8 08h 19 20.5 50 00 35 9.600.68 SAmNGC 4254 8.45 4 12h 18 49.6 14 24 59 36.32.6 SAcNGC 1097 8.47 4 02h 46 19.0 -30 16 30 15.41.1 SBb

IC 342 8.49 6 03h 46 49.1 68 05 48 4.000.29 SABcdNGC 4321 8.50 4 12h 22 54.8 15 49 19 13.11.0 SABbcNGC 3034 8.51 4 09h 55 52.7 69 40 46 5.680.41 I0NGC 3184 8.51 4 10h 18 16.8 41 25 27 9.270.65 SABcdNGC 3049 8.53 4 09h 54 49.5 09 16 16 21.91.6 SBabNGC 4826 8.54 4 12h 56 43.6 21 40 59 3.540.27 SAabNGC 2841 8.54 4 09h 22 02.6 50 58 35 11.520.82 SAbNGC 5194 8.55 4 13h 29 52.7 47 11 43 8.330.59 SAbc, pec

He 2-10 8.55 2 08h 36 15.2 -26 24 35 9.80.7 dIrrNGC 1512 8.56 4 04h 03 54.3 -43 20 56 9.840.7 SBaNGC 3079 8.57 2 10h 01 58.5 55 40 50 19.71.4 SBcNGC 3628 8.57 2 11h 20 16.8 13 35 28 7.90.6 Sb, pecNGC 2782 8.59 2 09h 14 05.3 40 06 47 37.62.6 SABa, pecNGC 3077 8.60 2 10h 03 20.1 68 44 01 2.420.18 I0, pecNGC 5236 8.62 2 13h 37 00.2 -29 52 04 4.430.31 SABcNGC 3367 8.62 2 10h 46 35 13 45 01 43.43.1 SBcNGC 4194 8.67 2 12h 14 09.6 54 31 35 38.82.7 BCDNGC 5953 8.67 2 15h 34 32.5 15 11 39 31.22.2 SAa, pecNGC 2146 8.68 2 06h 18 37.7 78 21 21 16.91.2 SBab, pecNGC 2903 8.68 2 09h 32 09.7 21 30 02 6.630.47 SABbc

Mrk 331 8.76 2 23h 51 18.6 20 34 41 77.55.4 S

Note.The columns are as follows. Column [1]: Galaxy name. Column [2]: Metallicites as represented by theiroxygen abundance, 12+log(O/H) . Column [3[: References for oxygen abundances. Column [4]: Right ascension forJ2000 epoch. Column [5]: Declination for J2000 epoch. Column [6]: Distance in megaparsecs. Unless otherwiseindicated, distance are taken from NED using the Virgo Infall flow model for H 0 = 73 km s1 Mpc1. Column [7]:Morphological types taken from NED.

References. [1] Thuan & Izotov (2005); [2] Engelbracht et al. (2008); [3] Mateo (1998); [4] Moustakas et al.(2010); [5] Izotov & Thuan (1997); [6] Pustilnik & Martin (2007); [7] Walter et al. (2008); [8] Pilyugin & Thuan(2007)

aDistance from Chengalur et al. (2006). bDistance from Tully et al. (2006).

cDistance from Pustilnik & Martin (2007). dDistance from Thuan & Martin (1981).

eDistance from Thuan et al. (2004). fDistance is NED median from 45 individual distance measurements.

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objects. BCDs account for30% of our sampleand 9/17 of our XMDs. For this reason I willattribute a small section to the discussion of blue

compact dwarfs, their general properties, and whythey are useful galaxies for gaining insight into theevolution of the cosmic landscape.

2.1. A Discussion of Blue Compact Dwarfs

Dwarf galaxies are undoubtedly the most com-mon class of extragalactic objects found through-out the Universe. The absence of spiral struc-ture allows for the investigation of star forma-tion mechanisms more directly, and ISM condi-tions play a much more dynamic part in the SFRof dwarf galaxies than they do in larger spiraltypes. Zwicky (1971) catalogued a large number ofcompact objects that were stellar in appearance.Thuan & Martin (1981) introduced the term bluecompact dwarf to describe a particular subset ofdwarfs undergoing intense starbursts. Due to theirsignificant appearance in the galaxy sample I willgive a brief summary of their characteristics.

The understanding of galactic evolution beginswith how stars form from primordial gas and theirsubsequent interaction with the surrounding en-vironment. Thuan (2008) gives an overview ofwhy BCDs are good, low-redshift candidates forrevealing how hot, massive, young stars react to a

highly metal-deficient ISM. These characteristicsare thought to give a good representation of con-ditions in the early Universe. Indeed, BCDs arealso studied to further constrain the primordialabundances and support Big Bang Nucleosynthe-sis (Izotov & Thuan 1997).

The spectra of BCDs more closely resemblethose of galactic HII regions although they havemuch lower metallicity, with Z1/3 to 1/40 Z.They are low-luminosity(MB -18mag) and com-pact, with starburst diameters 1-2 kpc. As per-tains to their blue color Thuan & Martin (1981) re-quired the optical spectra to contain narrow emis-

sion lines over a blue continuum. Gil de Paz etal. (2003) suggest an additional criterion on the(B-R) color such thatB,peak R,peak 1. Thiseliminates some dwarfs that are actually quite redand better segregates the BCD types from dwarfirregulars and ellipticals.

Blue compact dwarfs can be further differen-tiated in to morphological classifications beyond

the previously mentioned criteria. Loose & Thuan(1986) used CCD surveys to define different groupsof BCDs based on the morphology of their star

forming regions as well as that of the underlyinghost galaxy. The groups are summarized as fol-lows:

1. iE BCDs.These galaxies have an irregular (i)central isophote composed of complex star-forming regions superposed on an elliptical(E), diffuse, low-surface brightness (LSB)halo. These are the most common type ofBCDs (Thuan 2008).

2. ne BCDs.These objects have a clearly de-fined, star-forming nucleus (n) and an ellip-tical (E) LSB halo.

3. iI BCDs.These BCDs have irregular (i) star-forming regions as well as an irregular (I)outer halo. Loose and Thuan also definedtwo subtypes:

i. iI, CCometary morphology, withthe star-forming regions representing thehead, and the LSB halo the tail.

ii. iI, MThese BCDs are classified asapparent mergers.

4. i0 BCDs.Irregular (i) star-forming regions

with no (0) diffuse, extended component in-dicative of an older, underlying stellar pop-ulation.

The majority of the BCD classifications listedin our galaxy sample are taken from Gil de Pazet al. (2003). Their H images showed that someBCDs have more complex HII regions not revealedby the shape of the inner isophotes alone, thusaltering their morphological type from nE to themore irregular iE.

As with the other types of galaxies in the sam-ple, BCD classifications are listed to look for possi-

ble trends amongst type upon computing the dust-to-gas ratios and evaluating how it scales withmetallicity.

3. Dust Mass

The major influence interstellar dust plays inthe field of astrophysics cannot be overstated. Oneneed only look to the thick dust lanes permeating

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the Galaxy to recognize its affects on observationalastronomy. Indeed, the properties of attenuation,extinction, and reddening have been studied for

over a century and much work has been done tocorrect for these effects and improve observa-tions. In addition to observational implications,dust in the ISM greatly contributes to temper-atures, elemental abundances, chemical composi-tion, and the dynamics of interstellar gas (Draine2009). The bulk of this information arises fromthe scattering, absorption, and emission of dustthrough its interaction with electromagnetic ra-diation. The understanding of interstellar dustis assisted by physical models that use observa-tional constraints in an attempt to determine var-ious properties of the dust.

Metals are created in the hearts of stars viastellar nucleosynthesis and subsequently radiatedoutward. Most of a stars mass, and thereby itsmetal content, is ejected late in its lifetime. Specif-ically, massive stars that undergo a supernova ex-plosion likely account for the majority of ISM dustLisenfeld & Ferrara (1998). SN1987A in the LargeMagellanic Cloud (LMC) confirmed the detectionof dust directly following an observed supernova.This dust also condenses in supernova shells thatresult from the outward shockwave. It would beexpected that starbursting galaxies that producemassive stars at a high rate would therefore con-tain a lot of dust. These O and B type stars emitheavily at ultraviolet (UV) wavelengths and theseUV photons are absorbed by dust grains and re-emitted in the IR. Thus infrared emission has be-come the most effective technique to constrain agalaxys dust properties, although very high UVluminosities actually destroy PAH particles (Li &Draine 2001).

The dust contents of low-metallicity galaxies isless well understood than it is for objects withZ. Indeed, it was initially thought that BCDswould not contain much dust at all. However, MIR

observations of SBS 0335-052E using the InfraredSpace Observatory showed that the galaxy was ra-diating 75% of its total luminosity in the mid-infrared (Thuan 2008). One of the major focusesof this paper then is to check broad trends at alarge range of metallicities with an interest in howcurrent dust models estimate dust properties atlow-Z.

In3.1 I will summarize the dust models stud-

ied to assist in the understanding of both dust for-mation and destruction in the ISM and how thesemodels can be used to estimate the dust mass for

a galaxy.

3.1. Evaluating Previous Dust Models

-Lisenfeld & Ferrara (1998) examined a se-lection of both blue compact dwarfs and dwarfirregulars. A simple single temperature black-body model was used to fit the spectral energydistributions (SED) of 60 and 100 m fluxesobtained from the Infrared Astronomical Satel-lite (IRAS). This does not consider any of thesmaller dust grains or cold dust (Draine 2009).The DGR also only included atomic hydrogen inthe gas mass due to the inability to obtain COemissions for their sample. They found a log-arithmic relation between the DGR and metal-licty of the dIrrs, but no relation for the BCDs.This was at odds with the expected linear rela-tion for galaxies having Z. The relation was12+log(O/H)(0.520.25)log(MDust/MH1).The lack of correlation might be related to vari-ations in star formation rates, with the BCDshaving higher SFRs.

-Hirashita (1999) modelled ISM dust using thesame sample as Lisenfeld & Ferrara (1998). The

model adopted the Instantaneous Recycling Ap-proximation (IRA) and a Salpeter Initial MassFunction (IMF). The IMF is a probability func-tion to describe the distribution of a population ofstars while the IRA assumes all stars1M to live forever. Thetwo can combine to approximate the evolution of agalaxys stars. The dust model included dust cre-ation and destruction from both supernovae andstar forming regions, i.e. dust is both formed anddestroyed quickly in heavy star-forming galaxies.Hirashita included terms for dust formation fromheavy elements ejected by stars, destruction by

supernova shocks, destruction in star-forming re-gions, and accretion of elements onto pre-existingdust grains. The model was able to reproduceobservational data, however, it is again limited bythe narrow range of IR wavelengths used.

-Calzetti et al. (2000) used a two blackbodymodel to fit the SEDs of eight starburst galaxiesusing 150 and 205 m photometry. The result-

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ing DGR values were within a factor of 2 withaverages for the Galaxy once corrected for metal-licity. They suggested that the contribution of a

cool dust component is important even in warmerstarbursting systems, although it could vary bymany factors from galaxy to galaxy. Another con-clusion was that at higher redshifts there could belittle contribution from an aged stellar populationto the dust heating. This may be relevant to thetype i0BCDs in our sample that do not show anolder, underlying component.

-Galametz et al. (2009) modelled the MIR andFIR SEDs of three low-metallicity galaxies. Theirstudy found that the use of sub-millimeter con-straints reveals a larger fraction of the dust. Thus

they added a 10K cold dust component whichimproved the fits to their 870 m observations.This resulted in a much higher DGR than typi-cally expected for low-Z galaxies. The PAH massabundance is very low in these galaxies, between5 and 50 times lower than the PAH mass fractionof our Galaxy.

-Engelbracht et al. (2008) was the study thatformed the basis of our galaxy sample. The dustmasses were estimated using 70 and 160 m colortemperatures and the absorption coefficients of Li

& Draine (2001). The gas mass did not includeany HII estimates. They found that the DGRdropped off steeply from the typical linear relationat 12+log(O/H)8.2 and that the trend quicklyflattened at very low metallicities. For this paper Iwanted to make every effort to improve upon theDGRs by estimating molecular hydrogen mass;additionally, our dust masses were estimated us-ing an update model by Draine & Li (2007) thatwill be summarized in 3.2.

3.2. Draine & Li 2007 Model

Our galaxy sample contains objects observed bySpitzerIRAC and MIPS photometry at 3.6, 8, 24,70, and 160 m. The data and sources are listed inTable 2. I estimated the dust masses using theseIR wavelength emissions and the model of Draine& Li (2007); hereafter DL07. Their model includesdust heated by a distribution of starlight intensi-ties and a mixture of silicate, graphite, and PAHgrains. It assumes dust grain sizes to be consistent

with observations in the Galaxy and seeks to re-produce wavelength-dependent extinction. Usingonly MIR and NIR emissions the DL07 model also

intends to reproduce FIR and even submm wave-length dust emissions. This is ideal as two of thedust models evaluated in 3.1 express concern overcold dust requiring submm constraints(Calzettiet al. (2000); Galametz(2009) & (2011)). DL07conclude that their model successfully reproducesISM dust out to 2mm without the need to intro-duce additional wavelength components.

Another attractive feature of the DL07 modelis the outline of a graphical procedure that canaccurately implement the estimation of dust fea-tures. This is appropriate for my study as thegalaxy sample is quite large. By using graphical

estimation I could more quickly obtain the resultsrequired to view the general DGR trends.

3.2.1. Graphical Method

The DL07 model relies on a variety of param-eters. In this section, I briefly outline the param-eters and procedure required to make graphicalestimates of a galaxys dust mass based off of itsSpitzer photometry. Define the PAH-mass frac-tion to be qPAH. IRAC 3.6 m flux is mostly dueto starlight. Nonstellar fluxes at 8 and 24 m canthus be estimated as

Fns (7.9m) = F(7.9m) 0.232F(3.6m)(1)

and

(2)Fns (24m) =F(24m)0.032F(3.6m) .

Next define three ratios of IR observables as

(3)P7.9 Fns 7.9

F71+ F160

(4)P24

Fns 24

F71+ F160

(5)R71 F71F160

where R71is sensitive to grains that dominate FIRemissions and is thus a good indicator of starlightintensity and P7.9 is proportional to dust powerradiated by PAHs.

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Table 2

Infrared Data for Galaxy Sample

F3.6 F8 F24 F70 F160Galaxy (Jy) (Jy) (Jy) (Jy) (Jy) References

SBS 0335-052 W 2.34E-5 1.86E-6


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Now refer to Figure 1 which shows the P7.9 andR71 observables for for various grain models hav-ing different PAH abundances. For each individ-

ual galaxy the best qPAHis estimated by findingits value such that the point (R71, P7.9) falls justabove the = 0 curve.

Each given qPAH is paramaterized by a min-imum starlight intensity, Umin, and the fractionof dust mass exposed to starlight, . Larger dustgrains can be heated to the point that they con-tribute significantly to the 24 m emission, there-fore the R24 ratio is sensitive to the value . Usingthe value of qPAH, locate the appropriate graph inFigure 2 and locate (R71, P24) to estimate Uminand.

At this point all of the DL07 free parametershave been obtained with the exception of MDust.They define the following coefficient

MDustU

[Fns 24+ F71+ F160]D2

(6)

by considering that MDust is proportional to to-tal dust luminosity. Now referring to Figure 3, can be found by using the previously obtainedvalues of qPAH, Umin, and . DL07 suggest amaximum starlight intensity of Umax = 10

6. Themean starlight intensity is then

(7)U

UdMDustdMDust

= (1 )Umin+Uminln(UMax/UMin )

1 UMin/UMax

and the dust mass is finally estimated via

MDust =

U[F24+ F71+ F160]D

2 .

(8)

In order to interpret the general results I lookedat Herrera-Camus et al. (2012) and their study ofthe dust-to-gas ratio of I Zw 18. This is a low-metallicity i0 BCD that is also part of our sample.By comparing results I found their DGR upperlimit of 5 x 105 to be a factor of 10 lower thanwhat I obtained with the DL07 graphical proce-dure. In3.2.2 I introduce the empirical calibra-tions used to resolve this problem.

3.2.2. Mathematical Method

The associated equations for the DL07 modelwere solved by Munoz-Mateos et al. (2009b).Theyused linear fitting procedures for the free parame-ters and substituted the best fit relations into theDL07 equations. I could then check my graphicalestimates using

(9)MDustM

= 4

1.616 1013

D

Mpc

2F70F160

1.801

0.95Fns 8.0+ 1.150F

ns 24+ F70+ F160

erg s1

cm2

.

Figure 4 shows a comparison of the results ob-tained from the graphical method versus those ob-tained from the empirical method. The graphi-cal procedure of DL07 is clearly very well definedand the equations of Munoz-Mateos et al. (2009b)reproduce the results almost exactly. It seemsthere may have been human error in estimatingthe graphical parameters for the case of I Zw 18.Since the equation reproduces the DL07 estimatesso accurately the dust masses used in the DGRcalculations for this paper were taken from the

mathematical method described here.For galaxies not detected by IRAC there is also

an equation that uses MIPS bands only. Munoz-Mateos et al. (2009b) show that the IRAC+MIPScalibration is almost identical to the MIPS-onlycalibration. This helps increase the size of ourgalaxy sample. The MIPS-only equation is

(10)MDustM

= 4

1.616 1013

D

Mpc

2F70F160

1.801

1.559F24+ 0.7686F70+ 1.347F160

erg s1 cm2 .

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Fig. 1. Figure 20 from Draine & Li (2007)

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Fig. 4. A comparison of MDust(M) for a sub-set of our sample resulting from the Draine & Li(2007) dust model. The graphical procedure out-

lined therein is plotted against the mathematicalresults from the formulae for the same model de-rived in Munoz-Mateos et al. (2009b).

4. Gas Mass

Neutral hydrogen is the most abundant ele-ment in the Universe and thus a key componentof the ISM in all galaxies that provides constraintson their evolution (Koribalski et al. 2004). The21 cm HI emission line is a well-defined radiationspectral line created by a hyperfine energy transi-

tion in the ground state of neutral hydrogen. Thestarbursting galaxies in our sample all contain animportant neutral gas component that fuels theirstar formation (Thuan & Martin 1981). There isalso often diffuse HIenvelopes that extend beyondthe optical diameter of a galaxy in the form oftidal tails, bridges, or rings, especially in dIrrsand BCDs. As 21 cm emission is optically thin(Walter et al. 2008), HI seen over a given line of

sight may be converted into a density and inte-grated into a total HI mass.

The bulk of our HIdata was retrieved from theLyon-Meudon Extragalactic Database (LEDA).The 21 cm magnitudes were converted to fluxesusing

m21 = 2.5log(0.2366

S dv) + 15.84 (11)

where S is the flux density in janskys and dv isin km s1. Total HI masses have been calculatedfrom the fluxes using

MHI= 2.36 10

5 SdvD

2

M (12)

and the HI data is provided in Table 3.

4.1. Estimating H2

Molecular hydrogen, H2, is the most abundantmolecule in the Universe and is the main compo-nent that fuels star formation. Like neutral hydro-gen, H2 is also critical in the analysis of galactic

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Table 3

HI Data for Galaxy Sample

m21 m21 S dv MHIGalaxy (Mag) (Err) (Jy km s1) (M) References

SBS 0335-052 W 17.14 0.27 1.276 8.72E+008 13I Zw 18 16.31 0.14 2.741 1.25E+008 13

SBS 0335-052 E 17.14 0.27 1.276 8.78E+008 13UGCA 292 14.82 0.31 10.81 2.63E+007 13

HS 0822+3542 0.27 7.70E+007 1ESO 489-G56 16.41 0.26 2.5 1.06E+007 13

Sextans A 131.8 6.36E+007 2Tol 1214-277


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Table 3Continued

m21 m21 S dv MHIGalaxy (Mag) (Err) (Jy km s1) (M) References

NGC 1140 13.84 0.21 26.67 2.37E+009 13NGC 1510 12.83 0.23 67.61 1.60E+009 13

Haro 3 14.81 0.2 10.914 7.80E+008 13NGC 628 302 7.83E+009 4

NGC 2976 45.4 5.09E+007 8NGC 4214 11.69 0.2 193.2 5.36E+008 13NGC 4670 14.8 0.34 11.02 1.15E+009 13NGC 6946 506 3.64E+009 4NGC 3031 1169 7.79E+008 4NGC 3773 2.49 5.99E+007 10NGC 2537 14.44 0.15 15.35 2.13E+008 13

NGC 2552 14.06 0.21 21.78 4.74E+008 13NGC 4254 76.69 2.38E+010 10NGC 1097 142.6 7.98E+009 11

IC 342 6.8 0.39 17457.6 6.59E+010 13NGC 4321 49.47 2.00E+009 10NGC 3034 700 5.33E+009 8NGC 3184 105 2.13E+009 4NGC 3049 11.55 1.31E+009 12NGC 2841 183 5.73E+009 4NGC 4826 41.5 1.23E+008 4

He 2-10 14.67 0.21 12.416 2.81E+008 13NGC 5194 169 2.77E+009 4NGC 1512 259.3 5.88E+009 11NGC 3079 12.75 0.09 72.78 6.67E+009 13NGC 3628 11.55 0.3 219.8 3.24E+009 13NGC 2782 14.75 0.3 11.53 3.85E+009 13

NGC 3077 11.01 0.34 361.4 4.99E+008 13NGC 3367 14.62 0.15 13 5.78E+009 13NGC 5236 8.93 0.35 2454 1.14E+010 13NGC 4194 15.4 0.26 6.338 2.25E+009 13NGC 5953 15.39 0.27 6.397 1.47E+009 13NGC 2146 13.04 0.24 55.72 3.76E+009 13NGC 2903 11.88 0.2 162.2 1.68E+009 13

Mrk 331 15.58 0.15 5.37 7.61E+009 13

Note.The columns are as follows. Column [1]: Galaxy name. Column[2]: Mean homogenized 21 cm magnitude. Column [3]: Mean error on m21.Column [4]: Integrated HI line flux density. Column [5]: HI mass calculatedusing Eq.(2). For galaxies with no 21 cm magnitude the HI mass was takendirectly from the literature and scaled to the distance used in this paper.

References. [1] Chengalur et al. (2006); [2] Hogg et al. (2007); [3] Pustilnik& Martin (2007); [4] Walter et al. (2008); [5] Thuan & Martin (1981); [6]Thuan et al. (2004); [7] Lopez-Sanchez (2010); [8] Huchtmeier et al. (2005);[9] Theureau et al. (2005); [10] Kennicutt et al. (2003); [11] Koribalski et al.(2004); [12] Stierwalt et al. (2009) [13] Paturel et al. (2003).

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evolution, stellar systems, and the ISM in gen-eral. Unfortunately it is not directly observableas emission because it has no permanent dipole

moment and no dipolar rotational transition (Bo-latto, Wolfire & Leroy 2013). The most abundantmolecules in molecular clouds outside of H2 areoxygen and carbon which easily combine to formCO in the surrounding conditions. The low en-ergy of the CO dipole moment allows it to becomeexcited even in cold clouds thus allowing observa-tion of the J = 1 0 and J = 2 1 transitions(Leroy et al. 2009). There are plenty data for COemissions for our spiral galaxies of average metal-licity but, in general, there are not many positivedetections for low-Z galaxies.

It is possible that low-metallicity objects have

less of a molecular hydrogen content. For BCDsin particular there is an absence of diffuse H2 dueto a low HIdensity, high UV photon emission thatdestroys H2 molecules, and a low metal contentthat makes grains on which to form H2 moleculesscarce Thuan (2008). In the next two sections Iwill describe my efforts to estimate the molecu-lar hydrogen mass using the traditional CO tracermethod as well as by using star formation rates.

4.1.1. CO to H2 Conversion

The greatest uncertainty in using CO trac-

ers to estimate H2 mass lies in the so-calledCO-to-H2 conversion factor (XCO ). Bolatto,Wolfire & Leroy (2013) recommend XCO = 2 x1020 cm2 (Kkm s1)1 for the Galaxy but thisincludes up to 30% uncertainty. Such potentialdeviations in the conversion factor for the MilkyWay itself indicates how tenuous the determina-tion of XCO can be for other galaxies.

The conversion factor is believed to increasewith decreasing metallicity. CO and H2 line opac-ity can create a condition where the molecules areself-shielded, an effect which can be efficient forhiding H2 in regions where CO is photodissociated

(Galametz et al. 2011). This can result in conver-sion factors upwards of a factor of 10 higher thanin normal spiral galaxies. Bolatto et al. (2011)studied molecular gas column density in the SmallMagellanic Cloud (SMC). They used IR dust emis-sions and localized DGRs to map molecular gas in-dependently of any CO tracers. They found H2 inthe SMC to far exceed what would be expected byapplying a Galactic conversion factor. For these

reasons our sample evaluates H2 mass by using 3different XCO factors, including the Milky Wayconversion factor mentioned above.

The CO data and sources are listed in Table4. Both J = 1 0 and J = 2 1 transitionswere obtained, therefore two separate equationswere used depending on which observational datawas available for each galaxy. From Draine et al.(2007) I follow their method to estimate H2 massusing

MH2 = 1.57

104M

XCO

4 1020 cm2 (Kkms1)1

D

Mpc

2

SCO

Jykms1

(13)

where SCO is the integrated flux from the 12CO

J = 1 0 transition line. I followed Leroy et al.(2009) for the other data using

FCO [Jykms1] = 0.036FCO [Kkms

1 arcsec2]

(14)

where FCO is the integrated flux from the 12CO

J = 2 1 transition line. This can then be con-verted to luminosity and then H2 mass via

(15)MH2 = 5.5XCOR210.8

LCO [Kkms1 pc2]M

where LCO is the associated luminosity and R21 isthe J = 2 1 to J = 1 0 ratio with a recom-mended value of 0.8 based on observational com-parisons.

All galaxies had their molecular gas content es-timated using the following three XCO factors

1:

X1CO = 2 x 1 020 cm2 (K km s1)1; this is

the Galactic value as recommended by Bolatto,Wolfire & Leroy (2013).

X2CO = 4 x 1 020 cm2 (Kkm s1)1; this con-

version factor is suggested by Draine et al. (2007)based on the SINGS galaxy sample.

1Superscripts refer to Table 4 and the H2 masses that resultfrom a particular conversion factor.

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Table 4

CO Data for Subset of Galaxies

SCOa FCO

b LCOb M1

H2M2

H2M3

H2

Galaxy (Jy km s1) (Jy km s1) (K km s1pc2) References (M) (M) (M)

DDO 154 1.80E+2d 2.10E+6d 1 6.69E+006 1.34E+007 1.30E+008Holmberg I 1.22E+5d 9.40E+6d 1 6.42E+007 1.28E+008 1.06E+009

Holmberg II 3.60E+2 d 3.30E+6d 1 3.01E+007 6.02E+007 3.82E+008Mrk 209 2.00E+1e 3 3.56E+006 7.11E+006 4.27E+007IC 2574 2.66E+3d 2.80E+7d 1 7.30E+007 1.46E+008 6.84E+008II Zw 40 2.00E+1e 3 1.70E+007 3.40E+007 1.00E+008

NGC 1569 6.00E+1 3 9.90E+005 1.98E+006 5.80E+006NGC 3310 1.40E+2 3 3.56E+008 7.12E+008 1.86E+009NGC 4449 1.50E+2 3 1.23E+007 2.46E+007 5.71E+007NGC 7714 1.30E+2 3 1.56E+009 3.12E+009 6.75E+009

Haro 3 2.00E+1e 3 4.75E+007 9.51E+007 1.72E+007NGC 628 1.51E+3 2 4.58E+009 2.60E+009 1.31E+009

NGC 2976 1.44E+4 1.20E+7 1 1.05E+007 2.10E+00 2.96E+007NGC 4214 3.24E+4 1.70E+6 1 1.94E+007 3.87E+007 5.48E+007NGC 6946 9.27E+3 2 2.22E+009 4.44E+009 6.92E+009NGC 4254 3.00E+3 3 3.41E+010 6.83E+01 9.50E+010

IC 342 9.85E+3 2 1.24E+009 2.47E+009 3.14E+009NGC 4321 2.97E+3 2 4.01E+009 8.01E+009 9.93E+009NGC 3034 1.82E+4 3 9.20E+008 1.84E+00 1.83E+009NGC 3184 3.60E+3 3.00E+8 1 4.61E+009 9.22E+009 1.12E+010NGC 2841 2.20E+5 2.80E+8 1 1.81E+008 3.63E+00 4.10E+008NGC 4826 1.85E+3 2 8.32E+008 1.66E+009 1.54E+009

He 2-10 1.78E+4 4 2.63E+007 5.26E+007 5.80E+007NGC 5194 1.01E+4 2 5.50E+009 1.10E+01 1.21E+010NGC 3079 2.28E+3 3 1.86E+009 3.72E+009 3.92E+009NGC 3628 3.80E+3 3 6.95E+009 1.39E+010 1.46E+010

NGC 2782 2.30E+3 3 2.55E+009 5.11E+009 5.13E+009NGC 3077 1.00E+2 3 4.60E+006 9.19E+006 9.02E+006NGC 5236 1.63E+4 3 2.51E+009 5.02E+009 4.70E+009NGC 4194 1.80E+2 3 2.45E+009 4.89E+009 4.08E+008NGC 5953 3.20E+2 3 3.48E+009 6.96E+009 5.81E+009NGC 2146 2.84E+3 3 1.12E+009 2.25E+009 1.83E+009NGC 2903 3.25E+3 2 6.37E+009 1.27E+010 1.04E+010

Mrk 331 4.50E+2 3 2.12E+010 4.24E+010 2.87E+010

Note.All data are quoted as they appear in the associated references and luminosities were later corrected to thedistances used in this paper. The superscripts 1, 2, and 3 refer to the different XCO factors used to estimate the given H2mass as outlined in 4.1.1.

References. [1] Leroy et al. (2009); [2] Helfer et al. (2003); [3] Young et al. (1995); [4] Santangelo et al. (2009).

aSCO integrated flux from 12CO J = 1 0 transition line.

bFCO integrated flux and LCO luminosity from 12CO J = 2 1 transition line.

d5 upper limit.

eThese fluxes are at the limit of the instruments resolution and thus are likely not highly accurate.

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logX3CO = -1.01(12+log(O/H)+29.28; this conver-sion factor was used by Galametz et al. (2011) andscales XCO based on metallicity.

The scaling XCO factor does indeed alter themolecular gas mass for the lowest metallicitygalaxies in the sample by up to a factor of 10.Due to the uncertainties all three estimates willbe used to determine separate DGRs. CO datawas available for only 34 of the 85 galaxies in thesample so an effort was made to supplement theH2 mass data by estimating it via star formationrates (SFR).

4.1.2. Schmidt Law

I investigated the application of the globalKennicutt-Schmidt law (Kennicutt 1998) to a sub-set of the galaxies, specifically focusing on low-metallicity BCDs. It would seem reasonable toexpect that, as starbursting galaxies, the Schmidtlaw would not only fit but could be used to extractinformation about the gas content in the absenceof CO emission detections.

Thuan (2008) discusses two modes of star for-mation in blue compact dwarfs: (1) An activemode showing super star cluster formation, a highstar formation rate, compact size, hot dust, andsignificant amounts of molecules such as H2. (2)

A passive mode with small knots of star forma-tion at a lower rate, less compact, cooler dust andno significant amount of H2. Thus, SFR rates inBCDs are not well defined and it is possible thatthey vary greatly. The same can be said for themolecular gas content.

Young, massive stars produce large amounts ofphotons that ionize surrounding gas. Hydrogenrecombination produces emissions, including thewell known Balmer series lines of H(0.6563m)and H (0.4861 m), which represent the tradi-tional star formation indicators (Calzetti 2008).The SFR can be estimated using the Kennicutt

(1998) relation

SFR(Myr1) =

L(H)

1.26 1041ergss1 (16)

The Hdata for the BCDs was obtained from Gilde Paz et al. (2003). However, these SFR need tobe corrected for dust-attenuation. Kennicut et al.

(2009) updated his earlier work using a combina-tion of H and IR continuum emissions. The re-sulting recommendation to best constrain the SFR

is:

(17)SFR(Myr1) = 7.9 1042 [L(H)obs

+ aL](ergs1)

where a is a dust-scaling coefficient that de-pends on which wavelength band, L, is used.Since our sample already had Spitzer IRAC andMIPS data it was then possible to use the totalinfrared luminosity (LTIR) to best constrain theSFR of each galaxy. Equation (17) then becomes

(18)SFR(Myr1) = 7.9 1042 [L(H)obs

+ 0.0024LTIR ](ergs1)

with the coefficient provided by Kennicutt (1998).The required LTIR was calculated using themethod:

(19)LTIR = 1L(24m) + 2L(70m)

+ 3L(160m)

with the coefficients being redshift-dependentand the entire procedure being outlined in Dale

& Helou (2002). Equation (18) could now be usedto calculate the SFR for the BCD subsample. Theresulting star formation rates are within the rangeof what is generally expected for BCDs, being be-tween a few 103 to a few 101Myr

1 ( Zhao,Gu, & Ghao (2011); Hopkins, Schulte-Ladbeck, &Drozdovsky (2002)).

With reasonable star formation rates in hand,mean SFR surface densities were calculated bydividing the total SFR by the deprojected areawithin the RC3 radius. Total gas surface densitycould then be estimated by solving:

SFR= (2.5 0.7)

104

gas1Mpc2

1.40.15Myr

1 kpc2

(20)

where the exponent is the best fit power-law indexdetermined by Kennicutt (1998). There is

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Table 5

Data Associated with SFR Estimation of H2 Mass

logLTIR logLHa

SFR log SFR log Gas MGas MH2Galaxy (ergs s1) (ergs s1) (M yr1) (M yr1 kpc2) (M pc2) (M) (M) MH2/MHI

I Zw 18 40.90 40.36 0.184 -0.804 2.137 1.60E+8 3.52E+7 0.28II Zw 40 42.89 41.75 4.580 1.260 3.261 4.60E+8 9.92E+7 0.27

VII Zw 403 39.88 38.60 0.003 -2.328 1.048 7.81E+6 1.74E+6 0.10Tol 2 41.97 40.71 0.423 -0.848 1.842 2.07E+8 4.55E+7 0.28

Tol 65 41.95 41.05 0.892 -0.804 2.137 7.78E+8 1.17E+8 0.59UGC 4483 40.33 39.48 0.024 -1.281 2.187 7.05E+7 9.55E+6 0.16

Mrk 178 40.33 39.81 0.051 -0.950 1.498 1.43E+7 4.65E+6 0.48NGC 4861 42.41 41.33 0.076 -1.121 1.910 1.89E+9 4.39E+8 0.30Mrk 1094 43.03 41.64 0.125 -0.904 1.928 2.49E+9 4.24E+8 0.20

NGC 4670 43.17 41.51 2.852 -0.618 2.119 1.55E+9 4.05E+8 0.35NGC 2537 42.39 40.68 0.423 -1.335 1.447 2.56E+8 4.34E+7 0.20

Note.The columns are as follows. Column [1]: Galaxy name. Column [2]: 3-1100 m luminosity calculated using methoddescribed in Dale & Helou (2002). Column [3]: H luminosity corrected to distances used in this paper. Column [4]: Star formationrate. Column [5]: Mean star formation rate surface density. Column [6]: Total gas surface density. Column [7]: Total gas mass.Column [8]: H2 mass estimate. Column [9]: Ratio of H2 to HI mass.

aHluminosities from Gil de Paz et al. (2003).

some uncertainty in the index value. Bolatto etal. (2011) found a steeper relation for the SMC,with a power-law index, N 2.2 0.1, similarto that observed in the outer disks of large spiralgalaxies.

The SFR method could then utilize the HI

masscalculations by taking the total gas surface density,projecting a total gas mass over the same area, andsubtracting out the HI. The results are summa-rized in Table 5. Ratios for H2to HImass are pro-vided to check if they are reasonable. In general,the ratios are between 0.10 and 0.30. The 28%value for I Zw 18 compares favorably to the valueof 30% found by Herrera-Camus et al. (2012).Only Tol 65 and Mrk 178 have rather high ratios,with 50-60% of the total gas mass coming fromH2.

In Figure 5, the BCD subset is plotted on

a Kennicutt-Schmidt diagram. The galaxies fallalong the expected relation for a Schmidt lawwith index N 1.55 and mostly cluster betweenthe normal spirals, represented by triangles, andthe starbursting galaxies, represented by squares.Kennicutt (1998) warns that the main errors in thegas densities are variation in the CO/H2 conver-sion factor, combined with the limited samplingof CO measurements in some galaxies. Overall,

the results from using SFR to estimate H2 seemreasonable.

Fig. 5. Figure 6 from Kennicutt (1998) with ourdata from Table 5 superposed as red circles. The

surface density of hydrogen gas is plotted againstthat of star formation rate. The best fit relationis a Schmidt law paramaterization with index N 1.55 and variations in the data by up to a factorof 2 would result in a fit with slope represented bythe solid line to the right of the figure.

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5. Dust to Gas Ratio

Data for the DGRs are presented in Table 6.The DGRs are plotted in Figures 5-7 based onwhich XCO factor was used to calculate the H2mass. The solid line is the expected relation if theISM heavy element content of all galaxies wereproportional to oxygen abundances at the samefraction as in the Milky Way. The linearly scaledrelation is

MDustMH

0.010 (O/H)

(O/H)MW(21)

with (O/H)MW being the central oxygen abun-dance of the Galaxy using the value 12+log(O/H)= 8.90 (Pilyugin et al. 2003). The graphical re-sults show that the linear relation does not holdas metallicity decreases. At 12+log(O/H)8.2 theDGR drops drastically. Unfortunately a best fitrelation for low-Z was unable to be determined dueto the many upper limits on the various masses.Particularly at low metallicity there were non-detections fromSpitzerand generally no CO emis-sion has been detected from these objects.

It is difficult to compare the DGR results toothers from the literature. In general, not manystudies focus solely on low-Z objects. Our studywas based off the sample of Engelbracht et al.

(2008) but it is not entirely comparable due tothe differing dust models and the fact that theydid not attempt to include any H2 estimates. Thesingular case study of I Zw 18 by Herrera-Camuset al. (2012) offers the best direct comparison withthe DGR obtained in this paper. Additionally, theSFR method employed to estimate the molecularhydrogen content is nearly identical. The SINGSgalaxy sample modelled by Draine et al. (2007)agrees well with this sample which is not surpris-ing as the same dust model was used.

6. Summary and Conclusions

The results of this paper are as follows:

1. A large sample of galaxies is obtained. The fo-cus is on low-metallicity objects but, in orderto study broad trends, the resulting sampleranges from 7.1


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Fig. 7. DGR plotted using an XCO factor thatscales with metallicity. The symbols are the sameas in Figure 6.

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Table 6

Various Dust-to-Gas-Ratio Estimates

Galaxy DGRa DGR1 DGR2 DGR3

SBS 0335-052 W 1.10E-3 I Zw 18 5.42E-005

SBS 0335-052 E 1.50E-3 UGCA 292 2.41E-5

HS 0822+3542 1.60E-4 ESO 489-G56 4.20E-4

Sextans A 7.11E-5 Tol 1214-277 5.15E-3

UGC 4483 3.07E-5 DDO 154 1.15E-4 1.11E-4 1.08E-4 6.84E-5

Tol 65 1.38E-3

KUG 1013+381 4.77E-4 SBS 1415+437 3.96E-5

DDO 53 1.17E-4 Holmb erg I 1.43E-4 1.07E-4 8.56E-5 2.19E-5

SBS 1102+606 1.13E-4 DDO 165 7.15E-5

ESO 146-G14 1.03E-4 VII Zw 403 6.10E-5 Holmb erg I I 9.44E-5 9.21E-5 9.00E-5 7.21E-5

UM 461 3.68E-5 DDO 187 7.59E-5

NGC 5408 1.95E-4 Mrk 209 5.55E-5 5.11E-5 4.73E-5 2.72E-5Mrk 153 2.74E-4

M81 Dw B 3.31E-4 IC 2574 3.68E-4 3.40E-4 3.15E-4 2.06E-4

Mrk 178 1.82E-4 UGC 4393 6.40E-3 UM 462 4.33E-4

NGC 2366 1.32E-4 Pox 4 2.82E-4

Mrk 1450 9.88E-4 UM 448 3.20E-3

NGC 4861 1.45E-4 Mrk 930 9.40E-4 Mrk 170 6.24E-4

NGC 6822 8.86E-4 II Zw 40 9.14E-4 8.73E-4 8.35E-4 7.16E-4

NGC 1569 5.35E-3 5.14E-3 4.95E-3 4.32E-3Mrk 1094 5.46E-4

NGC 3310 4.10E-3 3.75E-3 3.45E-3 2.75E-3NGC 1156 2.28E-4

NGC 5253 3.42E-3

Tol 2 3.17E-4 NGC 4449 9.06E-3 9.15E-3 8.74E-3 7.82E-3NGC 7714 3.08E-3 2.40E-3 1.96E-3 1.38E-3

Haro 02 6.08E-3 UGC 4703 7.31E-4

UM 311 5.57E-3

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Table 6Continued

Galaxy DGRa DGR1 DGR2 DGR3

NGC 1140 1.18E-3 NGC 1510 6.75E-5

Haro 3 2.03E-3 1.91E-3 1.81E-3 1.66E-3NGC 628 1.06E-2 6.66E-3 7.93E-3 9.05E-3

NGC 2976 8.86E-4 8.69E-4 8.53E-4 8.40E-4NGC 4214 1.43E-2 1.04E-2 8.13E-3 6.89E-3NGC 4670 2.54E-3 NGC 6946 2.04E-2 1.27E-2 9.21E-3 7.05E-3NGC 3031 7.92E-3 NGC 3773 1.08E-2 NGC 2537 3.55E-3 NGC 2552 1.65E-3 NGC 4254 4.45E-2 1.83E-3 1.15E-2 8.92E-3NGC 1097 2.21E-2

IC 342 8.62E-4 8.46E-4 8.31E-4 8.23E-4NGC 4321 8.35E-2 2.78E-2 1.67E-2 1.40E-2NGC 3034 2.63E-2 1.84E-2 1.41E-2 1.42E-2NGC 3184 5.25E-3 2.82E-3 1.92E-3 1.69E-3NGC 3049 4.90E-3 NGC 2841 2.11E-2 8.52E-3 5.33E-3 4.86E-3NGC 4826 2.01E-2 1.75E-2 1.56E-2 1.58E-2

He 2-10 8.90E-3 8.14E-3 7.49E-3 7.37E-3NGC 5194 7.04E-2 2.36E-2 1.42E-2 1.31E-2NGC 1512 1.67E-3 NGC 3079 8.59E-3 5.69E-3 4.17E-3 4.05E-3

NGC 3628 1.14E-2 5.57E-3 3.68E-3 3.56E-3NGC 2782 7.87E-3 4.73E-3 3.38E-3 3.37E-3NGC 3077 2.83E-4 2.80E-4 2.77E-4 2.78E-4NGC 3367 7.96E-3 6.52E-3 5.52E-3 5.63E-3NGC 5236 1.51E-2 1.10E-2 6.78E-3 2.29E-2NGC 4194 2.93E-2 NGC 5953 1.19E-2 4.68E-3 2.91E-3 3.33E-3NGC 2146 1.54E-2 9.21E-3 6.56E-3 7.35E-3NGC 2903 1.20E-2 4.45E-3 2.74E-3 3.19E-3

Mrk 331 1.52E-2 4.03E-3 2.32E-3 3.19E-3

Note.The superscripts 1, 2, and 3 refer to DGR es-timates using the three different XCO factors to estimatethe H2 masses as outlined in 4.1.1.

aThe total gas mass in this DGR only includes the H Igas component.

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