ICE AND DUST IN THE PRESTELLAR DARK CLOUD LYNDS 183: PREPLANETARY MATTER AT THE LOWEST TEMPERATURES

Initial target selection was carried out using the Two Micron All Sky Survey (2MASS) database to identify objects with near-infrared colors consistent with those of reddened background field stars located beyond L183. We followed the procedure adopted by Shenoy et al. (2008) for their survey of the Taurus dark cloud. A survey area with a radius of 15 arcmin centered on the nominal position of L183⁶ was chosen, which includes the entire high-density region of the cloud. Our search criteria selected stars with high quality photometry (lack of confusion, contamination, and other "bad data" flags, and with signal-to-noise ratios >20 in each of the three 2MASS passbands; see Shenoy et al. 2008), and with values of the color index H − K_s > 0.35 (to eliminate unreddened stars). This yielded a sample of 32 candidates, listed in Table 1 together with all available photometry in the wavelength range 1–12 μm. The photometry includes data in the J (1.24 μm), H (1.66 μm), and K_s (2.16 μm) passbands from 2MASS and data in the 3.4, 4.6, and 11.6 μm passbands from the preliminary release of the Wide-field Infrared Survey Explorer (WISE) point-source catalog; both of these catalogs were accessed using the general catalog query engine of the NASA/IPAC Infrared Science Archive.⁷

In addition to 2MASS and WISE data, we also present photometry extracted from images obtained with the Infrared Array Camera (IRAC; Fazio et al. 2004) of the Spitzer Space Telescope (Werner et al. 2004) in the standard IRAC passbands centered at 3.6, 4.5, 5.8, and 8.0 μm. The raw IRAC images were obtained from the Spitzer Heritage Archive (program no. 94, PI: Charles Lawrence; see also Steinacker et al. 2010). The raw images were processed with Spitzer pipeline S18.7.0 to produce corrected basic calibrated data (cBCD). The Mosaicking and Point Source Extraction package was used to reduce the data. Overlap corrections were performed to remove mismatches in the background emission due to bias fluctuations, following standard procedures that include masking bright objects, interpolating all cBCD to a common grid, and removing the background fluctuation by calculating the offset of each image with respect to a common level. Corrected cBCD were then used to generate the final mosaic of L183. The overlap-corrected cBCD were interpolated to a common grid and corrected for cosmic-ray hits and bad pixels. The images were then co-added to produce four tiles, which were then combined to create a mosaic that included the entire cloud. We then performed aperture photometry of point sources in the mosaics for each of the IRAC bands. As the images for bands 1 and 2 (3.6 and 4.5 μm) appear moderately crowded, we used a small aperture radius for photometry and an annulus close to each star to estimate the background. Aperture and color corrections were done using data from Tables 4.7 and 4.3, respectively, in the IRAC Instrument Handbook. A pixel phase correction was done for all the point sources in band 1. Finally, we performed a simple positional matching in a radius of 3.0 arcsec to associate the IRAC point sources with corresponding point sources in the 2MASS catalog. The resulting photometry for our selected program stars is listed in Table 1 and has a typical uncertainty of ±0.02. The brightest program star is saturated in all four bands, and two others show evidence of saturation in bands 1 and 2: these data have been omitted from Table 1.

Representative color–color diagrams based on the photometry listed in Table 1 are plotted in Figure 1. These include the standard J − H versus H − K_s diagram based on 2MASS data, and J − H versus H − [4.5] as an example of a color–color diagram extending to longer wavelengths than available with 2MASS data alone. Figure 1 may be compared with Figures 2 and 3 of Shenoy et al. (2008), which display the equivalent data for Taurus field stars and young stellar objects (YSOs), respectively. All of the L183 targets fall within or very close to zones expected for normal reddened photospheres in these plots, consistent with classification as background field stars with visual extinctions ranging up to A_V ∼ 14 mag. Indeed, none of the available photometry shows evidence of infrared excess emission at these wavelengths that might be indicative of warm circumstellar material around YSOs or other types of embedded stars. This result is fully consistent with the assumed status of L183 as a prestellar core (Section 1).

Zoom In Zoom Out Reset image size

Stars in Table 1 were prioritized as candidates for spectroscopy according to apparent brightness and the goal of covering the available range of extinction. Nine stars for which spectroscopic data are presented below are highlighted in red in Figure 1 and listed in Table 2. Their distribution with respect to the cloud core is shown in Figure 2, which overlays extinction contours from Pagani et al. (2004) on a mosaic of 3.6 μm IRAC images; program stars are labeled alphabetically in order of increasing extinction (see Table 3 and Section 3.1). Of these, star H (J15542044−0254073, A_V ≈ 12.5 mag) proves to be a particularly valuable probe of interstellar features, as it is among both the brightest and the most reddened in the set. We note, however, that all of our program stars are separated by at least 3 arcmin from the dense core of the cloud, in which extinctions as high as A_V ∼ 150 mag have been estimated (Pagani et al. 2004).

Zoom In Zoom Out Reset image size

The SpeX instrument (Rayner et al. 2003) was used on NASA's Infrared Telescope Facility (IRTF) at Mauna Kea Observatory in 2008 April 3–6 to obtain spectra for the nine program stars listed in Table 2. The spectral range from 2.0 to 4.1 μm was covered in the long-wavelength cross-dispersed (LXD) SpeX mode at a resolving power of R ≈ 1500. This range encompasses the strong interstellar H₂O–ice absorption feature centered near 3.1 μm, and also includes the 2.3–2.5 μm gaseous CO overtone bands, which are prominent in late-type photospheres and thus useful as an aid to spectral classification. Observations of nearby standard stars were used to provide flux calibration and elimination of telluric features. Data reductions were carried out using the SpeXtool package (Cushing et al. 2004), which includes all necessary routines to produce flux- and wavelength-calibrated spectra from the raw spectral images. The final spectra are shown in Figure 3.

Zoom In Zoom Out Reset image size

We also make use of archival data obtained with the United Kingdom Infrared Telescope (UKIRT) at Mauna Kea Observatory for one program star (H). The UKIRT cooled grating spectrometer (CGS2) was used to obtain spectra at resolving power of R ≈ 600, covering (1) the 2.85–3.75 μm spectral region (observing date 1988 June 4) and (2) the 4.6–4.8 μm spectral region (observing date 1990 May 19). Data reduction procedures follow those described by Chiar et al. (1994) for similar observations made with the same instrument, and are analogous to those used for the SpeX data. The resulting spectra are shown in Figure 4 and compared with our SpeX data for this star over the same spectral range. Allowing for the lower resolution and somewhat poorer signal-to-noise ratio of the CGS2 data, the agreement in the region of overlap is well within the uncertainties. The importance of the UKIRT/CGS2 dataset is that it provides coverage of the 4.6–4.8 μm spectral region, yielding a detection of the 4.67 μm CO ice feature.

Zoom In Zoom Out Reset image size

Mid-infrared spectra were obtained for six program stars⁸ with the Infrared Spectrograph (IRS; Houck et al. 2004) on board the Spitzer Space Telescope. Standard staring-mode observations were executed with the low-resolution (R ≈ 60) IRS modules short-low (SL) and long-low (LL), covering the spectral range 5–21 μm. Additionally, a higher-resolution spectrum of star H was obtained with the short-high module (SH; R ≈ 600) over the spectral range 10–19 μm. The observations are identified by the Astronomical Observation Request (AOR) keys listed in Table 2. The majority of the observations (AORs beginning with 2300) were obtained between 2007 August 31 and 2008 March 23 as part of our Spitzer Cycle 4 General Observer program 40432 (PI: Douglas Whittet); the remaining two observations were obtained on 2005 August 6 and 7, and are from program 3290 (PI: William Langer).

The SH observation of J15542044−0254073 (AOR 23003648) utilized six ramp cycles, yielding a total on-source integration time of 1748 s. A dedicated spectrum of the sky background in the region (AOR 23003904) was obtained to provide background subtraction. The raw spectra were processed by the standard Spitzer pipeline (version 15.3.0) to produce basic calibrated data. Further reductions to produce the final calibrated spectra were carried out using the SMART software package (Higdon et al. 2004) and standard procedures to remove bad pixels and other artifacts, as in our previous work described in Section 2 of Whittet et al. (2007).

The low-resolution observations utilized the standard two-position nod pattern along the slit axis, one-third of the way from the slit ends. The exposures obtained at the "off" nod positions were used as background exposures and to compensate for detector artifacts and cosmic-ray events. Initial data reductions were performed using basic calibrated data and subsequent analysis with SMART. However, final extracted spectra were retrieved from the Cornell Atlas of Spitzer IRS sources⁹ (CASSIS v.4; Lebouteiller et al. 2011), which provided improvements over our initial reductions. Post-extraction processing was performed to scale the flux density of the SL module to that of the LL module at 14 μm. The uncertainties in the flux density are estimated to be half the difference of the two independent spectra from each nod position.

The final low-resolution flux spectra, shown in Figure 5, exhibit continua consistent with stellar photospheres in the Rayleigh–Jeans limit, as expected for normal field stars. The broad amorphous silicate absorption feature centered at 9.7 μm is present and most prominent in the spectra of stars with the highest extinction, as expected. The SH spectrum of star H was obtained specifically to search for the 15.2 μm CO₂ bending-mode ice feature in this line of sight, and to place constraints on its profile shape. The 14–17 μm spectrum displaying this feature is plotted in Figure 6 and compared with the corresponding low-resolution data from Figure 5.

Zoom In Zoom Out Reset image size

Zoom In Zoom Out Reset image size

The final flux spectra were converted to optical depth in the normal way using the relation

$$\begin{equation} \tau (\lambda) = \ln \lbrace F_{\rm cont}(\lambda)/F_{\rm obs}(\lambda)\rbrace, \end{equation} \tag{ 1 }$$

where F_obs(λ) and F_cont(λ) are the observed and continuum flux densities at wavelength λ, respectively. In the case of the IRTF/SpeX spectra, the local continuum for the broad 3.05 μm H₂O–ice absorption feature was determined using a second-order polynomial fit to the data in the 2.0–2.3 μm and 3.65–4.0 μm regions, which lie beyond the wings of the feature and are relatively free of photospheric lines; the fits and the resulting optical depth spectra are shown in Figures 3 and 7, respectively. For the CO–ice feature observed in the UKIRT/CGS spectrum (Figure 4), we adopted a simple linear continuum fit to the relatively "clean" adjacent regions at 4.62–4.65 μm and 4.75–4.78 μm. Similarly, for the 15.2 μm CO₂–ice feature in the Spitzer SH spectrum (Figure 6), we adopted a linear continuum fit to the adjacent regions at 14.2–14.8 μm and 16.0–16.6 μm. Optical depth spectra for the H₂O, CO and CO₂ ice features in star H are shown in Figures 8–10, respectively.

Zoom In Zoom Out Reset image size

Zoom In Zoom Out Reset image size

A different approach was adopted for the Spitzer low-resolution spectra, as these span a wider range of wavelengths and contain several interstellar features, some of which are overlapping. A global continuum was determined for each spectrum using a nonlinear least-squares fitting technique, which simultaneously determines the unabsorbed background continuum and the solid-state extinction over the entire 5.2–20.5 μm wavelength range. Details of the spectral decomposition analysis are described elsewhere (Poteet 2012). Briefly, the continua are simulated by a low-order polynomial, with a maximum degree of three, and the dust and ice opacities are modeled as a linear combination of amorphous silicates (Dorschner et al. 1995), H₂O–ice (Hudgins et al. 1993), and the empirical absorption profiles of the 5–8 μm ice components (Boogert et al. 2008). To account for the intrinsic photospheric absorption of blended gas-phase CO and SiO near 4.7 and 8.0 μm, respectively, we additionally derive photospheric optical depth spectra from Ardila et al. (2010) for K- and M-type giants of luminosity class III (see Section 3 below). The modeled spectral energy distributions (SEDs) and optical depth spectra for the three program stars with the highest quality spectra are shown in Figure 11. Using the same method, an analysis of archival Spitzer IRS data for the Taurus field star Elias 16 (AOR 5637632) is also shown for comparison.

Spectral classifications were estimated for our program stars, based on comparisons between our spectra and those in the Infrared Telescope Facility (IRTF) Spectral Library: Cool Stars (Rayner et al. 2009) and the Spitzer Atlas of Stellar Spectra (Ardila et al. 2010). The primary constraint is provided by the IRTF data in the 2.0–2.5 μm window (Figure 3), specifically the CO overtone bands (increasingly prominent in cool giants of type K0 or later) and the H Brγ line at 2.165 μm (discernible in giants of type K0 or earlier). A further constraint is provided by the low-resolution Spitzer spectra, as available (Figure 5), in which the 7.6–8.1 μm band of SiO becomes increasingly prominent in cool giants later than K0 (its depth is comparable to that of the 9.7 μm silicate dust feature in the spectrum of the M-type star A; see Figure 11). The resulting spectral types for all program stars are listed in Table 3 and are considered accurate to ±3 subclasses.

The infrared color excess E_{J − K} is used to quantify the interstellar reddening arising from extinction by dust toward each program star. This was calculated from the J − K_s color index in the 2MASS photometric system (the sum of Columns 2 and 3 in Table 1) by first transforming to the Bessell & Brett (1988) homogenized system, using the relation

$$\begin{equation} [J-K]_{\rm BB} = ([J-K_{\rm s}]_{\rm 2MASS}+0.011)/0.972 \end{equation} \tag{ 2 }$$

(Carpenter 2001). E_{J − K} is then calculated in the usual way as the difference between the observed and intrinsic color indices, with the latter taken from Bessell & Brett (1988) for the appropriate spectral type. Results, listed in Table 3, are considered accurate to ±0.07, the main source of uncertainty being the spectral type. The observed range of 0.3–2.5 in E_{J − K} corresponds to an approximate range of 1.6–13.3 in A_V if the mean conversion factor determined for the Taurus cloud is assumed (A_V ≈ 5.3E_{J − K}; Whittet et al. 2001). Our results are consistent with the loci of the stars (Figure 2) relative to the extinction contours of Pagani et al. (2004) to within expected uncertainties.

The column density of an observed molecule in the ice phase is calculated from the optical depth spectrum using the relation

$$\begin{equation} N_{\rm ice} = {1\over A}\int \tau (\nu)\,d\nu, \end{equation} \tag{ 3 }$$

where ν is the wavenumber and A is the band strength of the vibrational feature. Taking A-values from Gerakines et al. (1995), results were estimated for H₂O, based on the 3.0 μm feature observed in all program stars (Figure 7), and also for CO (4.67 μm) and CO₂ (15.2 μm), based on the features observed in star H (Figures 9 and 10, respectively). Additionally, the low-resolution Spitzer spectra (Figure 5) were deemed of sufficient quality at 15.2 μm to place useful limits on CO₂ for two program stars (A and D). All results are listed in Table 3. The mean composition of the ices toward star H is H₂O:CO:CO₂ ≈ 100:40:24, which lies within the range of compositions observed in other prestellar and star-forming dark clouds (e.g., Gibb et al. 2004; Öberg et al. 2011), albeit with an above average CO:CO₂ ratio. The correlation of N(H₂O) with dust opacity (as measured by color excess and silicate optical depth) is presented and discussed in Section 4. The nature of the ices toward star H is discussed in greater detail in Section 5.

Zoom In Zoom Out Reset image size

Zoom In Zoom Out Reset image size

The 9.7 μm features detected in our program stars (Figure 5) are consistent with absorption by submicrometer-sized amorphous silicate particles in L183 that presumably provide substrates for the growth of ice mantles. The contributions of silicates to the optical-depth spectra of stars A, D, and H are illustrated in Figure 11. The observations are not of high enough quality to yield detailed information on profile shapes, but they do provide adequate measures of the peak optical depth (τ_9.7) of the silicate feature in six lines of sight. Results are listed in Table 3.

Zoom In Zoom Out Reset image size

A plot of τ_9.7 versus E_{J − K} is shown in Figure 12, combining data for L183 (Table 3) with data for the Taurus dark cloud and IC 5146. Silicate data for Taurus is from a reanalysis of Spitzer IRS low-resolution spectra, as available from the Infrared Science Archive for four stars (3, 13, 15, and 16 in the catalog of Elias 1978), and from Whittet et al. (1988) otherwise; silicate data for IC 5146 are from Chiar et al. (2011). In all cases, E_{J − K} was calculated from 2MASS photometry using the method described in Section 3.1 above. The solid line in Figure 12 is the correlation observed in the diffuse ISM (τ_9.7 ≈ A_V/18 ≈ 0.33E_{J − K}; Whittet 2003, and references therein). Previous studies have shown that molecular clouds tend to exhibit "normal" silicate strengths (i.e., consistent with the diffuse-ISM correlation) at low to moderate color excess (E_{J − K} ≲ 1.5), and "below-normal" strengths at higher values (see Figure 1 of Chiar et al. 2007). This general behavior is seen in Figure 12, and there is no convincing evidence for a systematic difference from cloud to cloud. If we make the reasonable assumption that the grains responsible for silicate absorption and near-infrared extinction are well mixed in the ISM, the relation between τ_9.7 and E_{J − K} is expected to pass through the origin: this would clearly not be the case for a linear fit to the distribution in Figure 12, even if the most highly reddened stars are excluded; it therefore appears that the relationship between these quantities is not a simple linear correlation.

Zoom In Zoom Out Reset image size

The cause of this behavior is not fully understood. Detailed comparisons of spectra for diffuse and molecular-cloud environments indicate that systematic changes in the silicate absorption profile cannot account for the anomaly (van Breemen et al. 2011). A more probable explanation is that systematic changes in the optical properties of the dust in the near-infrared are being driven by grain growth within the clouds (Chiar et al. 2007), and these are affecting E_{J − K}, independent of the depth of the silicate feature.

The observed optical-depth profiles of the H₂O, CO and CO₂ ice features at 3.0, 4.67 and 15.2 μm in Elias 16 are overlaid on those of star H (with appropriate scaling) in Figures 8–10. This comparison shows that the profiles in these two lines of sight are identical to within the observational uncertainties, and consistent with ices in an amorphous state. In particular, structure that would be indicative of crystallization of the ices in response to heating (see, e.g., Smith et al. 1989 and Ehrenfreund et al. 1999 for discussions of the 3.0 μm and 15.2 μm features, respectively) appears to be absent in both lines of sight, as expected for low grain temperatures (≲ 15 K). The excellent signal-to-noise ratio of the 3 μm spectrum of star H (Figure 8) provides a significant test for grain size effects as well as temperature (see Figure 3 in Smith et al. 1989). There is consistency with the Elias 16 profile not only in the position and width of the main feature but also in the extent and depth of the long-wavelength wing attributed to larger grains, suggesting that no major differences exist in the typical size of the ice-mantled grains between the two clouds. The observed profiles of the CO and CO₂ ice absorptions in star H are not of high enough quality to justify detailed attempts to deconvolute them into the individual polar and nonpolar components typically used to model the profiles of other (generally brighter) sources such as YSOs (e.g., Pontoppidan et al. 2003, 2008); we simply conclude that the general concordance in profile suggests a distribution similar to that observed in Elias 16 and other well-studied field stars, with most of the CO₂ mixed with H₂O in the polar ices (e.g., Whittet et al. 2009) and most of the CO in the relatively H₂O-poor nonpolar ices (e.g., Chiar et al. 1995).

The Spitzer-IRS optical depth spectra of stars A, D, and H, shown in Figure 11, are adequately modeled by the absorption profiles of amorphous silicates and amorphous H₂O–ice (Section 2.4). The resulting ensemble of particles is simulated in each line of sight by submicrometer-sized, irregular (DHS; Min et al. 2007) and spherical (Boogert et al. 2008) shaped silicate and ice grains, respectively. Additionally, simulating the optical depth spectra of stars A and D required gaseous CO and SiO photospheric absorption from M- and K-type background giants, respectively. As the 12.5 μm H₂O–ice libration-mode feature is blended with and weaker than the 9.7 μm silicate feature, its strength cannot be reliably and independently determined by fitting spectra of this quality; the peak optical depth of the libration feature used in the models was therefore fixed with respect to that of the 3.05 μm stretching mode in each source: the stretch/libration optical depth ratio is approximately 4.5, based on our models.

The solid-state features in the 5–8 μm region toward star H are modeled (Figure 11) using the empirical component profiles (C1–C5) from Boogert et al. (2008). For comparison, the optical depth spectrum of Elias 16 is also modeled using the same spectral decomposition technique.¹¹ In this formulation, the 6.0 μm feature is composed of components C1 (peaking at 5.84 μm and attributed to C=O carbonyl bonds in ices containing molecules such as H₂CO and HCOOH) and C2 (6.18 μm, a blend of absorptions associated with NH₃ ices and embedded polycyclic aromatic hydrocarbons), superposed on the H₂O–ice bending mode. The 6.85 μm feature is also composed of two components, C3 (6.76 μm) and C4 (6.94 μm), which lack specific identifications (an attribution to the NH$_4^{+}$ ion is sometimes suggested). The fifth component, C5, exhibits a broad profile from 5.5 to 7.8 μm and is also unidentified. Significantly, the strengths of components C4 and C5 correlate with thermal processing (Boogert et al. 2008) and are therefore expected to be weak or absent in cold, quiescent clouds such as L183. The 6.0 μm feature toward star H is modeled satisfactorily by H₂O–ice absorption alone and does not require additional absorption by components C1 and C2. This is not particularly surprising as C1 and C2 are only weakly present in Elias 16, which has ice features typically a factor ∼2 stronger, suggesting that they could be present at a level just below our detection limit in star H. The 6.85 μm feature in star H is reasonably well-matched by components C3 and C4, but with a stronger contribution from C4, in contrast to the model for Elias 16. There is no significant C5 component in either case. On the face of it, the unexpectedly large C4 component toward star H suggests thermal processing of the ices in L183, but as there is no other evidence for this, either in our spectra or in the previous literature (e.g., Pagani et al. 2003, 2004), it seems more likely to be a product of the relatively low signal-to-noise ratio of the spectrum within the 5–8 μm range. It would be worthwhile to obtain a higher-quality spectrum in the future.

Methanol (CH₃OH) is an important species in astrochemistry, representing a significant link in the chain of evolution that leads from simple C-bearing molecules formed at low temperatures in dark clouds to complex organic species synthesized by thermal or energetic processing in the vicinity of young stars (e.g., Öberg et al. 2009). The primary formation mechanism for CH₃OH is thought to be hydrogenation of adsorbed CO on grain surfaces (Tielens & Whittet 1997; Watanabe & Kouchi 2002; see Whittet et al. 2011 for detailed discussion and additional references). Abundances of CH₃OH in interstellar ices extend from upper limits and weak detections of no more than a few percent relative to H₂O in many lines of sight to substantial levels of up to 30% toward some YSOs (Dartois et al. 1999; Pontoppidan et al. 2004). First detections of CH₃OH in quiescent regions of dark clouds toward background field stars were reported by Chiar et al. (2011) and Boogert et al. (2011).

Our data allow a limit to be set on the abundance of ice-phase CH₃OH in L183. The best constraint is provided by a search for its C–H stretching-mode absorption feature in the IRTF spectrum of star H (Figure 8). The feature observed in other regions is centered at 3.54 μm with a full-width-half-maximum of about 0.04 μm, superposed on the wing of the H₂O–ice feature (see Figure 12 in Pontoppidan et al. 2004 for examples). Careful examination of our spectrum shows no evidence for structure that can be identified with CH₃OH, to a limiting optical depth of τ_3.54 < 0.015. Using a band strength of 5.3 × 10⁻¹⁸ cm molecule⁻¹ (Hudgins et al. 1993) for CH₃OH, this corresponds to a column density of <1.1 × 10¹⁷ cm⁻² and an abundance relative to H₂O–ice of <10%. This result is fully consistent with previous findings, which suggest that CH₃OH ice is detectable in quiescent molecular clouds only at extinctions A_V ≳ 17 (Whittet et al. 2011), substantially higher than that toward star H or others in our sample.

Plots of H₂O–ice column density against those of CO and CO₂ are shown in Figures 15 and 16, respectively, combining our results for L183 (Table 3) with data from the literature for other clouds. In the case of N(H₂O) versus N(CO), the distribution over all clouds is broadly consistent with a linear correlation (solid line in Figure 15; Pearson's correlation coefficient r = 0.88), displaying a positive intercept on the N(H₂O) axis. This intercept is predicted by the accepted general model for mantle growth (Tielens et al. 1991), in which an early H₂O-dominated growth phase transitions to a phase dominated by direct freeze-out of CO from the gas: it is thus expected that the grain population in a line of sight passing through a typical cloud may include particles with H₂O-rich mantles that lack the more volatile CO-rich mantles, but not conversely. In the case of L183 (star H), N(CO) is marginally higher than predicted by the overall correlation, suggesting CO freeze-out may be more advanced (e.g., in comparison to Taurus; see Section 5.4 below).

Zoom In Zoom Out Reset image size

Zoom In Zoom Out Reset image size

The N(H₂O) versus N(CO₂) correlation (Figure 16) is statistically similar but qualitatively different. The unconstrained linear fit to all points (solid line) yields r = 0.89. However, as previously noted (Whittet et al. 2009), there is evidence of systematically lower CO₂ abundances in Taurus compared with IC 5146 and Serpens, as suggested by the dotted line fitted to Taurus data alone. The available data for L183 are consistent with either trend. The correlations are consistent with a relatively small (and possibly null) intercept in comparison to that for N(H₂O) versus N(CO): this arises from the fact that the majority of the CO₂ is expected to be in the polar (water-rich) ice layer, as the result of efficient CO oxidation during the initial phase of mantle growth (Whittet et al. 2009 and references therein).

Pagani et al. (2005) used millimeter-wave radio observations of gas-phase CO and other molecules in L183 to investigate the degree to which they are depleted by freeze-out onto dust within the cloud core. They find a rather tight correlation between the J = 1–0 integrated line intensity of C¹⁸O and visual extinction for values 0 < A_V < 15 (their Figure 10), transitioning to a plateau at higher extinction, indicating that CO becomes strongly depleted at A_V ≳ 20. Pagani et al. (2012) subsequently developed a model to predict the behavior of gas-phase CO depletion from observations of the daughter species DCO⁺ inside prestellar cores: constrained by available observations of L183, the model predicts extreme (effectively 100%) CO depletion within ∼50 arcsec of the central core (see their Figure 3).

Our detections of solid-phase CO and CO₂ toward star H show that some CO is also being depleted onto dust in L183 at a somewhat lesser extinction (A_V ≈ 12.5) and greater distance (∼180 arcsec) from the central core. Available J = 1–0 and 2–1 spectra provide an estimate of the gas-phase column density toward star H of $N({\rm C^{18}O) \approx 1.8 \times 10^{15}\ {\rm cm}}^{-2}$, and assuming a C¹⁶O/C¹⁸O ratio of 560 (Wilson & Rood 1994), this yields

$$\begin{equation*} N({\rm CO)_{{\rm gas}} \approx 1.0 \times 10^{18}\ {\rm cm}}^{-2}. \end{equation*}$$

In the solid phase, CO₂ forms by oxidation of adsorbed CO, as noted above, and no other CO-bearing species approach the abundances of CO and CO₂ in a typical dense cloud (e.g., Gibb et al. 2004; Öberg et al. 2011). Hence, the column density of CO depleted into ices is effectively the sum

$$\begin{equation*} N({\rm CO})_{\rm ice} = N({\rm CO + CO_2)_{{\rm ice}} \approx 7.3 \times 10^{17} \ {\rm cm}}^{-2} \end{equation*}$$

(Table 3), and the total (gas plus ice) column density is therefore

$$\begin{equation*} N({\rm CO)_{{\rm total}} = N({\rm CO})_{\rm gas} + N({\rm CO})_{\rm ice}\approx 1.7 \times 10^{18} \ {\rm cm}}^{-2}. \end{equation*}$$

Combining these results, the depletion factor is δ_CO = N(CO)_ice/N(CO)_total ∼ 0.42 or 42%. This result may be compared with those of our detailed study of CO depletion in the Taurus dark cloud at extinctions A_V ≲ 25 (Whittet et al. 2010), in which we find a steady trend of increasing depletion with extinction, reaching typical values of ∼30%–40% at extinctions A_V ∼ 12.5, corresponding to that of star H in L183. Overall, it seems probable that CO depletion proceeds in a similar manner in the two clouds, but more observations of solid-phase CO and CO₂ in L183 would be needed to determine whether there is a significant quantitative difference.