# Cospatial ice mapping of H2O with CO2 and CO across a molecular cloud with JWST/NIRCam

Z L Smith, H J Dickinson, H J Fraser, M K Mcclure, Jennifer A. Noble, A C

A Boogert, F. Sun, E. Egami, E. Dartois, J. Erkal, et al.

► To cite this version:

Z L Smith, H J Dickinson, H J Fraser, M K Mcclure, Jennifer A. Noble, et al. Cospatial ice mapping of H2O with CO2 and CO across a molecular cloud with JWST/NIRCam. Nature Astronomy, 2025, 9 (6), pp.883-894. 10.1038/s41550-025-02511-z. hal-05382395

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# Cospatial ice mapping of H₂O with CO₂ and CO across a molecular cloud with JWST/NIRCam

Received: 5 July 2024

Accepted: 18 February 2025

Published online: 24 March 2025

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Z. L. Smith©¹,²✉, H. J. Dickinson©¹, H. J. Fraser©¹, M. K. McClure©², J. A. Noble©³, A. C. A. Boogert©⁴, F. Sun⁵,⁶, E. Egami⁶, E. Dartois©⁷, J. Erkal©⁴, T. Shimonishi⁸, T. L. Beck⁹, J. B. Bergner©¹⁰, P. Caselli©¹¹, S. B. Charnley¹², L. Chu©¹³, M. N. Drozdovskaya©¹⁴, R. Garrod¹⁵, D. Harsono©¹⁶, S. Ioppolo©¹⁷, I. Jimenez-Serra©¹⁸, J. K. Jørgensen©¹⁹, G. J. Melnick©⁵, K. I. Öberg©⁵, M. E. Palumbo©²⁰, Y. J. Pendleton©²¹, G. Perotti©²², K. M. Pontoppidan©²³, D. Qasim²⁴, W. R. M. Rocha©²⁵, J. A. Sturm©², A. Taillard©¹⁸, R. G. Urso©²⁰ & E. F. van Dishoeck©²

In the coldest regions of molecular clouds, carbon and oxygen are incorporated into icy dust grains. Despite its outsized role in star and planet formation, sequential formation of ice is poorly constrained. Infrared spectroscopy probes ice chemistry, but previous telescopes observed insufficient lines of sight to map a single cloud. Here we present cospatial maps of H₂O, CO₂ and CO ice over the central region of the Chamaeleon I molecular cloud, using 44 lines of sight observed with the James Webb Space Telescope. Correlations at column densities ten times larger than previous work suggest additional CO₂ ice formation in CO ice for the densest lines of sight. This large statistical sampling within a single cloud represents a step change in ice mapping, eliminating averaging over clouds with different intrinsic chemical environments. Mapping opens the door to probing gas-grain exchanges, snow lines and chemical evolution in the densest regions and drawing conclusions on the impact of ice chemistry on wider astrophysics.

In the cold, dense molecular clouds where stars form, carbon and oxygen atoms are carried predominantly on icy grains by H₂O and CO, which are the second and third most abundant molecules after H₂. A third ice species, CO₂, is expected to carry a substantial amount of carbon as well, although the final abundance of CO₂ depends on whether it formed early within H₂O-rich ice or later within CO-rich ice¹. The fundamental vibrational modes of all three ice species have proven to be powerful tracers of the complex physics and chemistry in star-forming molecular clouds²⁻⁴, where they are typically seen in absorption against infrared continuum sources¹. Despite the importance of these ices, few studies have obtained measurements of all three species within the quiescent regions of molecular clouds where they first form, as the two main

vibrational absorption features of CO₂ (4.27 and 15.2 µm (refs. 5,6)) and the blue wing of the H₂O stretching mode vibration at ~3 µm are blocked by Earth's atmosphere. Only space infrared telescopes, such as ISO and AKARI, can simultaneously observe these two ice species along with the stretching absorption mode of CO at 4.67 µm (refs. 6–10).

Previous generations of infrared space telescopes have been able to detect thermally processed ices towards several hundred lines of sight probing protostellar envelopes¹,⁸,¹¹, where star formation has already begun. However, the background stars that provide the infrared continuum needed to detect pristine ices absorbing in prestellar environments, such as foreground molecular clouds, were typically too faint for those observatories. Therefore space observations of ices

<figure><img src="image_4.png" /></figure>
in dense clouds were biased towards the brightest individual lines of sight sampled from individual clouds, for a total of 23 background star spectra in which all three main ice species were detected<sup>8,10,12–23</sup>. So far, no studies have observed large numbers of background stars towards a single molecular cloud on spatial scales comparable to the size of protostellar cores, which limits astrochemists’ ability to compare the primary solid-state carriers of carbon and oxygen across different physical conditions.

To overcome the limitations of extrapolating observations of multiple clouds and to determine spatially resolved abundances across a given cloud, spatially resolved ice mapping is necessary. Within the same cloud, ice mapping can determine whether common formation conditions give rise to a common chemistry or whether local variations can be observed. The first ice map collated individual ground-based observations (from the PASP2 spectrophotometer on the Wyoming Infrared Observatory and the Mount Lemmon Observing Facility) of a single ice species, H<sub>2</sub>O, towards 61 lines of sight through a 1.58-square-degree region of the Taurus molecular cloud complex<sup>16</sup>. More recent efforts have mapped the abundances of the three major ice species H<sub>2</sub>O, CO<sub>2</sub> and CO towards several embedded protostars in the Ophiuchus-F star-forming core with a spatial resolution of ~5,000 AU (ref. 24) or multiple lines of sight across four cores with spatial resolutions as high as ~2,200 AU (ref. 25). Both studies showed that CO<sub>2</sub> formation occurs in both the H<sub>2</sub>O-rich and CO-rich phases of ice formation and, importantly, that there is chemical variation within individual clouds that can be revealed only by comparing multiple lines of sight. The latter study also demonstrated the improved efficiency gained by mapping ices towards multiple lines of sight concurrently using slitless spectroscopy.

The new infrared space facility, the James Webb Space Telescope (JWST), has the spatial resolution, sensitivity and wavelength coverage to make superlative ice observations and small maps of heavily extincted single sources<sup>26–30</sup>. It has two undemonstrated observing modes capable of mapping ices on spatial scales of a molecular cloud: NIRSpec's micro-shutter assembly multi-object spectroscopy (MSA MOS) mode<sup>31</sup> and NIRCam's wide-field slitless spectroscopy (WFSS)<sup>32</sup> mode. Here, we demonstrate the power of NIRCam WFSS by tripling the total number of detections of all three main ice species towards background stars. These measurements, made simultaneously towards a single molecular cloud core, allow us to test whether we detect a dramatic increase in CO<sub>2</sub> ice predicted by the onset of CO ice freeze-out. We present ice maps of H<sub>2</sub>O, CO and CO<sub>2</sub> constructed from observations of 44 lines of sight towards the Chamaeleon I (ChaI) molecular cloud with a median spatial resolution of ~2,000 AU and probing resolutions as high as 250 AU. Our sample size is similar to that in the H<sub>2</sub>O map of ref. 16, but over only 0.0017 square degrees, that is, with an improvement of three orders of magnitude in spatial sampling and covering multiple ice bands simultaneously.

## Results

Observations of ChaI were made with the NIRCam WFSS spectral mode using two different filters to cover the 2.5–5 µm spectral region. Each observational set-up had a different footprint (Methods and Extended Data Fig. 1). Within the overlapping region in the densest part of ChaI, 44 spectra were extracted containing absorption features of all three major ice species: H<sub>2</sub>O (3.0 µm), CO<sub>2</sub> (4.27 µm) and CO (4.67 µm). Figure 1 shows five representative 2.5–5 µm spectra extracted from NIRCam WFSS spectral frames as detailed in the Methods. Objects are ordered from top to bottom in decreasing flux density, spanning values from ~0.5 mJy down to ~0.01 mJy at 4.1 µm. The spectra exhibit deep absorption features corresponding to H<sub>2</sub>O, CO<sub>2</sub> and CO ices, while less intense ice absorption features including the so-called dangling OH features<sup>33</sup> (~2.7 µm), OCN<sup>-</sup> (4.59 µm) and the <sup>13</sup>C isotopologues (4.38 and 4.78 µm)<sup>27</sup> as well as grain scattering signatures<sup>34</sup> can also be observed, most easily in the highest-flux sources.

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**Fig. 1** | The 2.5–5 µm spectra along five lines of sight towards background stars behind the ChaI molecular cloud. Objects #077 (NIR38), #268, #273 (J110621), #265 and #267 are ordered from top to bottom in decreasing flux at 4.1 µm and are representative of the dataset, spanning flux values from ~0.6 mJy down to ~10 µJy. All spectra include absorption features corresponding to H<sub>2</sub>O (3.0 µm, blue), CO<sub>2</sub> (4.27 µm, purple) and CO (4.67 µm, green) ices. Sources NIR38 (object #077, top panel) and J110621 (object #273, third panel), whose spectra were recently published<sup>27,33,34</sup>, were the two background stars with known coordinates in the observed field of view before these JWST measurements. Pixel-to-pixel variation results in occasional large error bars (blue-grey); see Methods for details of the strategy developed in-house to extract several tens of spectra from a single spectral frame.

The brightest source in our sample is NIR38 (object #077, F<sub>4,1µm</sub> ≈ 0.5 mJy)<sup>27</sup>, a background star of spectral type K7V<sup>34</sup> that is fainter than the faintest background star sources extracted from slitless spectroscopy measurements with AKARI, that is, the next-most sensitive infrared telescope with a sensitivity limit of ~1 mJy (ref. 10), and orders of magnitude lower in flux than background stars observed with Spitzer (fluxes ~100 mJy (ref. 35)) or ISO (fluxes ~10 Jy (ref. 15)). At this flux density, signal to noise (S/N) is high in the JWST spectra (for NIR38, S/N of 140 at 3.97 µm; see ref. 27 for the equivalent NIRSpec Fixed Slit value), and any apparent variability in the baseline (for example, between 2.5 µm and 2.7 µm or around 4.5 µm) can be attributed instead to gas-phase absorption features in the stellar photosphere of the background star<sup>36</sup>. Upon visual inspection, absorption bands of H<sub>2</sub>O and CO<sub>2</sub> can be seen to be saturated (zero flux and flat) for the brightest spectra in Fig. 1. At lower flux densities, the inherent noise level in the spectrum becomes comparable in intensity with stellar photospheric features and with some very weak solid-phase absorption features such as <sup>13</sup>CO (ref. 37), <sup>13</sup>CO<sub>2</sub> (ref. 5) or dangling OH (ref. 33), but the pixel-to-pixel variations begin to dominate the extraction only at fluxes approaching the sensitivity limit of the JWST (~µJy). The extraction limit set for these observations is 2 µJy, corresponding to the limit beyond which errors in background correction or spectral extraction dominate the extracted flux (see Methods for technical details). Owing to the high S/N of spectra down to fluxes of approximately a few microjanskies, column densities of H<sub>2</sub>O, CO<sub>2</sub> and CO could be derived for tens of lines of sight from a single set of NIRCam observations in the region where spectral coverage of all three species was achieved.

Figure 2 shows the H<sub>2</sub>O, CO<sub>2</sub> and CO ice column density distributions, on the left-hand side plotted on a log scale as a function of right ascension (RA) and declination (dec.) position in a ~6.2 arcmin<sup>2</sup> field around the most extinction star-forming core of the cloud. This area corresponds to the region within which 44 spectra were observed for objects in which all three molecular species were detected (see Extended Data Fig. 1 for the spatial coverage of H<sub>2</sub>O, CO<sub>2</sub> and CO across the wider cloud and Extended Data Fig. 2 for the object positions). These ice maps cover the densest region, including the deeply embedded Cha MMS1 class 0 protostar<sup>38</sup> (which was not detected at all in these JWST observations), and the two lines of sight towards the background sources NIR38 and J110621, whose spectra were previously
<figure><img src="image_6.png" /></figure>

**Fig. 2 | Cospatial ice maps and correlations of ice column densities with H₂ column density in Cha I.** Left, cospatial ice maps of H₂O (blue), CO₂ (purple) and CO (green) column densities across the 44 sources where all three ices were detected towards Cha I. The positions of the 44 individual background sources are indicated by circles with a symbol size reflecting the object's flux density at 4.1 µm, with the background stars NIR38 (NE) and J110621 (SW)²⁷,³³,³⁴ labelled in white. The positions of the deeply embedded class O YSO Cha MMS1 and a possible prestellar core identified by ref. 38 are indicated by a yellow star and a

white cross, respectively. The log-scale H₂ column density contours derived from Herschel far-infrared observations³⁹⁻⁴¹ are overplotted. For details of the ice map construction, see Methods. Right, correlation plots for H₂O (blue), CO₂ (purple) and CO (green) column densities against H₂ column density. Open symbols denote sources for which there was partial wavelength coverage of the H₂O absorption band. Ice column densities are presented as mean values with error bars of 95% confidence intervals, except for open symbols where the extremes of the fitted templates were used (see Methods for full details).

reported²⁷,³³,³⁴. All eight spectra presented in ref. 33 are included in these maps. Column density derivation and map construction are described in the Methods and illustrated in Extended Data Fig. 3. Column density values are provided in Table 1 and are presented as a function of H₂ column density on the right of Fig. 2. This is the first time that such a large dataset of this kind has been assembled for a single molecular cloud. The combined dataset of background star spectra collected by previous space missions (ISO, Spitzer and AKARI) and ground-based telescopes numbers in the few tens, does not always cover the same spectral range and is spread over multiple molecular clouds¹.

In the cospatial ice maps in Fig. 2, the observed column densities of the three species can be easily compared. We observe that H₂O is the most abundant of the three species across the mapped region, with column densities typically around double that of the other two species combined. The maximum column densities of H₂O ice (9.6 × 10¹⁸ cm⁻²), CO₂ ice (4.0 × 10¹⁸ cm⁻²) and CO ice (3.7 × 10¹⁸ cm⁻²) are indicative of the absolute ice column densities, which remain large across the region

probed, representing the most extincted part of Cha I, where the visual extinction may reach values in excess of 100 mag (ref. 38). In Elias 16, the only background star towards which ice was extensively probed with ISO, the column densities of H₂O, CO₂ and CO were 2.5 × 10¹⁸ cm⁻², 4.6 × 10¹⁷ cm⁻² and 6.5 × 10¹⁷ cm⁻², respectively⁸. These values measured towards the Taurus molecular cloud lie on the lower end of the columns probed in our study. In Cha I, most CO ice column densities exceed 10¹⁸ cm⁻² but are typically lower than this along lines of sight towards quiescent regions¹. Generally speaking, the ice column density broadly follows the H₂ contours (that is, the dust density)³⁹⁻⁴¹ with the darkest regions of the ice maps (highest ice column densities) coinciding with the highest-density regions towards Cha MMS1. This is as expected given that, if there is more dust present along a line of sight, there will be more ice¹,¹¹,²³. However, the ice maps and correlation plots also clearly illustrate that the relationship is nonlinear, and one would not be able to precisely predict the ice column density just by knowing N(H₂) (Extended Data Fig. 4). It should be noted that the density of
<table><caption>Table 1 | Ice column densities for lines of sight towards Cha I</caption><thead><tr><th rowspan="2">ID</th><th rowspan="2">RA</th><th rowspan="2">Dec</th><th colspan="3">N<sub>H<sub>2</sub>O</sub></th><th colspan="3">N<sub>CO</sub></th><th colspan="3">N<sub>CO</sub></th><th rowspan="2">N<sub>H<sub>2</sub></sub></th><th rowspan="2">F410M</th></tr><tr><th>(J2000)</th><th>(J2000)</th><th>(10<sup>18</sup> cm<sup>-2</sup>)</th><th>(10<sup>18</sup> cm<sup>-2</sup>)</th><th>(10<sup>18</sup> cm<sup>-2</sup>)</th><th>CO<sub>2</sub><br>H<sub>2</sub>O</th><th>CO<br>H<sub>2</sub>O</th><th>CO<sub>2</sub><br>CO</th><th>(10<sup>22</sup> cm<sup>-2</sup>)</th><th>(mJy)</th></tr></thead><tbody><tr><td>13*</td><td>166.52798</td><td>-77.41515</td><td>4.82<sup>+1.04</sup><sub>-0.67</sub></td><td>1.54<sup>+0.08</sup><sub>-0.08</sub></td><td>0.81<sup>+0.81</sup><sub>-0.66</sub></td><td>0.32<sup>+0.07</sup><sub>-0.05</sub></td><td>0.17<sup>+0.17</sup><sub>-0.14</sub></td><td>1.90<sup>+1.90</sup><sub>-1.55</sub></td><td>1.54</td><td>0.013</td></tr><tr><td>16*</td><td>166.53697</td><td>-77.41404</td><td>5.75<sup>+1.47</sup><sub>-1.26</sub></td><td>1.18<sup>+0.05</sup><sub>-0.05</sub></td><td>1.55<sup>+0.74</sup><sub>-0.68</sub></td><td>0.21<sup>+0.05</sup><sub>-0.05</sub></td><td>0.27<sup>+0.15</sup><sub>-0.13</sub></td><td>0.76<sup>+0.37</sup><sub>-0.33</sub></td><td>1.78</td><td>0.012</td></tr><tr><td>28</td><td>166.58333</td><td>-77.40956</td><td>6.30<sup>+1.18</sup><sub>-1.68</sub></td><td>2.57<sup>+0.04</sup><sub>-0.04</sub></td><td>2.87<sup>+0.29</sup><sub>-0.32</sub></td><td>0.41<sup>+0.08</sup><sub>-0.11</sub></td><td>0.46<sup>+0.10</sup><sub>-0.13</sub></td><td>0.89<sup>+0.09</sup><sub>-0.10</sub></td><td>2.46</td><td>0.017</td></tr><tr><td>30*</td><td>166.51774</td><td>-77.40859</td><td>5.51<sup>+2.17</sup><sub>-1.61</sub></td><td>1.10<sup>+0.04</sup><sub>-0.04</sub></td><td>1.84<sup>+0.53</sup><sub>-0.59</sub></td><td>0.20<sup>+0.08</sup><sub>-0.06</sub></td><td>0.33<sup>+0.16</sup><sub>-0.14</sub></td><td>0.60<sup>+0.17</sup><sub>-0.19</sub></td><td>1.44</td><td>0.006</td></tr><tr><td>33</td><td>166.55776</td><td>-77.40736</td><td>4.76<sup>+0.99</sup><sub>-1.24</sub></td><td>1.10<sup>+0.01</sup><sub>-0.01</sub></td><td>1.38<sup>+0.17</sup><sub>-0.17</sub></td><td>0.23<sup>+0.05</sup><sub>-0.06</sub></td><td>0.29<sup>+0.07</sup><sub>-0.08</sub></td><td>0.80<sup>+0.10</sup><sub>-0.10</sub></td><td>2.34</td><td>0.011</td></tr><tr><td>34*</td><td>166.52572</td><td>-77.40734</td><td>5.65<sup>+2.04</sup><sub>-1.47</sub></td><td>0.99<sup>+0.08</sup><sub>-0.08</sub></td><td>2.27<sup>+0.40</sup><sub>-0.44</sub></td><td>0.17<sup>+0.06</sup><sub>-0.05</sub></td><td>0.40<sup>+0.16</sup><sub>-0.13</sub></td><td>0.44<sup>+0.09</sup><sub>-0.09</sub></td><td>1.52</td><td>0.008</td></tr><tr><td>36*</td><td>166.53468</td><td>-77.40576</td><td>5.53<sup>+1.15</sup><sub>-1.08</sub></td><td>1.28<sup>+0.03</sup><sub>-0.03</sub></td><td>1.64<sup>+0.02</sup><sub>-0.02</sub></td><td>0.23<sup>+0.05</sup><sub>-0.05</sub></td><td>0.30<sup>+0.06</sup><sub>-0.06</sub></td><td>0.78<sup>+0.02</sup><sub>-0.02</sub></td><td>1.66</td><td>0.045</td></tr><tr><td>37</td><td>166.56797</td><td>-77.40469</td><td>7.83<sup>+0.64</sup><sub>-0.70</sub></td><td>2.77<sup>+0.05</sup><sub>-0.06</sub></td><td>2.79<sup>+0.04</sup><sub>-0.04</sub></td><td>0.35<sup>+0.03</sup><sub>-0.03</sub></td><td>0.36<sup>+0.03</sup><sub>-0.03</sub></td><td>0.99<sup>+0.02</sup><sub>-0.03</sub></td><td>2.91</td><td>0.023</td></tr><tr><td>38</td><td>166.60048</td><td>-77.40448</td><td>7.40<sup>+0.79</sup><sub>-0.94</sub></td><td>2.50<sup>+0.06</sup><sub>-0.06</sub></td><td>2.34<sup>+0.22</sup><sub>-0.23</sub></td><td>0.34<sup>+0.04</sup><sub>-0.04</sub></td><td>0.32<sup>+0.04</sup><sub>-0.05</sub></td><td>1.07<sup>+0.10</sup><sub>-0.11</sub></td><td>3.05</td><td>0.031</td></tr><tr><td>50*</td><td>166.52102</td><td>-77.39760</td><td>4.00<sup>+1.21</sup><sub>-0.87</sub></td><td>0.98<sup>+0.15</sup><sub>-0.17</sub></td><td>1.45<sup>+0.94</sup><sub>-1.13</sub></td><td>0.24<sup>+0.08</sup><sub>-0.07</sub></td><td>0.36<sup>+0.26</sup><sub>-0.29</sub></td><td>0.68<sup>+0.45</sup><sub>-0.54</sub></td><td>1.37</td><td>0.012</td></tr><tr><td>59*</td><td>166.52684</td><td>-77.39426</td><td>5.74<sup>+1.09</sup><sub>-1.36</sub></td><td>1.00<sup>+0.02</sup><sub>-0.02</sub></td><td>1.81<sup>+0.08</sup><sub>-0.08</sub></td><td>0.17<sup>+0.03</sup><sub>-0.04</sub></td><td>0.32<sup>+0.06</sup><sub>-0.08</sub></td><td>0.55<sup>+0.03</sup><sub>-0.03</sub></td><td>1.47</td><td>0.014</td></tr><tr><td>68</td><td>166.53690</td><td>-77.39139</td><td>4.85<sup>+1.16</sup><sub>-1.63</sub></td><td>1.42<sup>+0.04</sup><sub>-0.04</sub></td><td>2.21<sup>+0.08</sup><sub>-0.09</sub></td><td>0.29<sup>+0.07</sup><sub>-0.10</sub></td><td>0.46<sup>+0.11</sup><sub>-0.15</sub></td><td>0.64<sup>+0.03</sup><sub>-0.03</sub></td><td>1.82</td><td>0.024</td></tr><tr><td>69*</td><td>166.47557</td><td>-77.39091</td><td>1.06<sup>+0.73</sup><sub>-0.73</sub></td><td>0.17<sup>+0.03</sup><sub>-0.03</sub></td><td>0.20<sup>+0.95</sup><sub>-0.20</sub></td><td>0.16<sup>+0.11</sup><sub>-0.11</sub></td><td>0.19<sup>+0.90</sup><sub>-0.19</sub></td><td>0.84<sup>+4.00</sup><sub>-0.84</sub></td><td>0.62</td><td>0.071</td></tr><tr><td>77</td><td>166.60577</td><td>-77.38768</td><td>7.81<sup>+0.75</sup><sub>-0.88</sub></td><td>2.03<sup>+0.04</sup><sub>-0.04</sub></td><td>2.80<sup>+0.04</sup><sub>-0.04</sub></td><td>0.26<sup>+0.03</sup><sub>-0.03</sub></td><td>0.36<sup>+0.03</sup><sub>-0.04</sub></td><td>0.72<sup>+0.02</sup><sub>-0.02</sub></td><td>2.91</td><td>0.483</td></tr><tr><td>85</td><td>166.56458</td><td>-77.38523</td><td>4.49<sup>+1.20</sup><sub>-1.71</sub></td><td>1.13<sup>+0.06</sup><sub>-0.07</sub></td><td>1.64<sup>+0.19</sup><sub>-0.20</sub></td><td>0.25<sup>+0.07</sup><sub>-0.10</sub></td><td>0.36<sup>+0.11</sup><sub>-0.15</sub></td><td>0.69<sup>+0.09</sup><sub>-0.10</sub></td><td>1.52</td><td>0.040</td></tr><tr><td>89</td><td>166.58519</td><td>-77.38427</td><td>6.37<sup>+0.86</sup><sub>-1.07</sub></td><td>2.08<sup>+0.10</sup><sub>-0.11</sub></td><td>2.38<sup>+0.20</sup><sub>-0.22</sub></td><td>0.33<sup>+0.05</sup><sub>-0.06</sub></td><td>0.37<sup>+0.06</sup><sub>-0.07</sub></td><td>0.87<sup>+0.08</sup><sub>-0.09</sub></td><td>1.94</td><td>0.021</td></tr><tr><td>91</td><td>166.60861</td><td>-77.38354</td><td>8.17<sup>+0.91</sup><sub>-1.14</sub></td><td>2.00<sup>+0.06</sup><sub>-0.06</sub></td><td>3.21<sup>+0.11</sup><sub>-0.11</sub></td><td>0.25<sup>+0.03</sup><sub>-0.04</sub></td><td>0.39<sup>+0.05</sup><sub>-0.06</sub></td><td>0.63<sup>+0.03</sup><sub>-0.03</sub></td><td>2.41</td><td>0.049</td></tr><tr><td>92</td><td>166.59629</td><td>-77.38352</td><td>5.98<sup>+0.87</sup><sub>-1.16</sub></td><td>1.35<sup>+0.08</sup><sub>-0.09</sub></td><td>1.79<sup>+0.22</sup><sub>-0.24</sub></td><td>0.23<sup>+0.04</sup><sub>-0.05</sub></td><td>0.30<sup>+0.06</sup><sub>-0.07</sub></td><td>0.75<sup>+0.10</sup><sub>-0.11</sub></td><td>2.01</td><td>0.089</td></tr><tr><td>93</td><td>166.55184</td><td>-77.38343</td><td>2.38<sup>+1.26</sup><sub>-1.26</sub></td><td>0.81<sup>+0.04</sup><sub>-0.04</sub></td><td>0.77<sup>+0.15</sup><sub>-0.15</sub></td><td>0.34<sup>+0.18</sup><sub>-0.18</sub></td><td>0.32<sup>+0.18</sup><sub>-0.18</sub></td><td>1.06<sup>+0.22</sup><sub>-0.21</sub></td><td>1.05</td><td>0.026</td></tr><tr><td>103</td><td>166.59337</td><td>-77.38107</td><td>4.94<sup>+0.75</sup><sub>-0.90</sub></td><td>1.80<sup>+0.06</sup><sub>-0.06</sub></td><td>1.51<sup>+0.40</sup><sub>-0.45</sub></td><td>0.37<sup>+0.06</sup><sub>-0.07</sub></td><td>0.31<sup>+0.09</sup><sub>-0.11</sub></td><td>1.19<sup>+0.32</sup><sub>-0.36</sub></td><td>1.55</td><td>0.015</td></tr><tr><td>106</td><td>166.54920</td><td>-77.37857</td><td>1.50<sup>+0.52</sup><sub>-0.56</sub></td><td>0.40<sup>+0.02</sup><sub>-0.02</sub></td><td>0.32<sup>+0.06</sup><sub>-0.06</sub></td><td>0.27<sup>+0.09</sup><sub>-0.10</sub></td><td>0.21<sup>+0.08</sup><sub>-0.09</sub></td><td>1.26<sup>+0.25</sup><sub>-0.25</sub></td><td>0.75</td><td>0.328</td></tr><tr><td>107</td><td>166.62111</td><td>-77.37819</td><td>3.57<sup>+1.35</sup><sub>-1.95</sub></td><td>1.17<sup>+0.07</sup><sub>-0.08</sub></td><td>1.18<sup>+0.35</sup><sub>-0.35</sub></td><td>0.33<sup>+0.13</sup><sub>-0.18</sub></td><td>0.33<sup>+0.16</sup><sub>-0.21</sub></td><td>0.99<sup>+0.30</sup><sub>-0.31</sub></td><td>2.08</td><td>0.014</td></tr><tr><td>109*</td><td>166.53376</td><td>-77.37780</td><td>1.72<sup>+0.73</sup><sub>-1.05</sub></td><td>0.31<sup>+0.09</sup><sub>-0.08</sub></td><td>0.35<sup>+0.21</sup><sub>-0.19</sub></td><td>0.18<sup>+0.09</sup><sub>-0.12</sub></td><td>0.20<sup>+0.15</sup><sub>-0.17</sub></td><td>0.89<sup>+0.59</sup><sub>-0.54</sub></td><td>0.65</td><td>0.049</td></tr><tr><td>113</td><td>166.59004</td><td>-77.37494</td><td>2.96<sup>+0.69</sup><sub>-0.98</sub></td><td>0.78<sup>+0.03</sup><sub>-0.03</sub></td><td>0.77<sup>+0.29</sup><sub>-0.29</sub></td><td>0.26<sup>+0.06</sup><sub>-0.09</sub></td><td>0.26<sup>+0.12</sup><sub>-0.13</sub></td><td>1.01<sup>+0.39</sup><sub>-0.38</sub></td><td>1.01</td><td>0.045</td></tr><tr><td>150</td><td>166.59725</td><td>-77.38322</td><td>7.12<sup>+1.64</sup><sub>-3.21</sub></td><td>1.99<sup>+0.14</sup><sub>-0.16</sub></td><td>1.91<sup>+0.70</sup><sub>-0.76</sub></td><td>0.28<sup>+0.07</sup><sub>-0.13</sub></td><td>0.27<sup>+0.12</sup><sub>-0.16</sub></td><td>1.05<sup>+0.39</sup><sub>-0.42</sub></td><td>2.01</td><td>0.016</td></tr><tr><td>155*</td><td>166.52598</td><td>-77.38851</td><td>3.55<sup>+1.14</sup><sub>-1.01</sub></td><td>0.58<sup>+0.03</sup><sub>-0.03</sub></td><td>0.97<sup>+0.23</sup><sub>-0.24</sub></td><td>0.16<sup>+0.05</sup><sub>-0.05</sub></td><td>0.27<sup>+0.11</sup><sub>-0.10</sub></td><td>0.60<sup>+0.15</sup><sub>-0.15</sub></td><td>1.00</td><td>0.015</td></tr><tr><td>160*</td><td>166.54326</td><td>-77.41031</td><td>5.82<sup>+1.16</sup><sub>-1.21</sub></td><td>1.45<sup>+0.05</sup><sub>-0.05</sub></td><td>2.14<sup>+0.31</sup><sub>-0.34</sub></td><td>0.25<sup>+0.05</sup><sub>-0.05</sub></td><td>0.37<sup>+0.09</sup><sub>-0.10</sub></td><td>0.68<sup>+0.10</sup><sub>-0.11</sub></td><td>1.75</td><td>0.019</td></tr><tr><td>265</td><td>166.57474</td><td>-77.40491</td><td>7.10<sup>+1.12</sup><sub>-1.61</sub></td><td>2.08<sup>+0.10</sup><sub>-0.12</sub></td><td>3.65<sup>+0.24</sup><sub>-0.26</sub></td><td>0.29<sup>+0.05</sup><sub>-0.07</sub></td><td>0.51<sup>+0.09</sup><sub>-0.12</sub></td><td>0.57<sup>+0.05</sup><sub>-0.05</sub></td><td>3.11</td><td>0.014</td></tr><tr><td>266</td><td>166.57635</td><td>-77.40452</td><td>8.81<sup>+0.78</sup><sub>-0.92</sub></td><td>2.67<sup>+0.05</sup><sub>-0.05</sub></td><td>3.25<sup>+0.15</sup><sub>-0.16</sub></td><td>0.30<sup>+0.03</sup><sub>-0.03</sub></td><td>0.37<sup>+0.04</sup><sub>-0.04</sub></td><td>0.82<sup>+0.04</sup><sub>-0.04</sub></td><td>3.11</td><td>0.036</td></tr><tr><td>267</td><td>166.62387</td><td>-77.40302</td><td>4.95<sup>+1.50</sup><sub>-2.43</sub></td><td>2.27<sup>+0.06</sup><sub>-0.07</sub></td><td>2.28<sup>+0.45</sup><sub>-0.49</sub></td><td>0.46<sup>+0.14</sup><sub>-0.23</sub></td><td>0.46<sup>+0.17</sup><sub>-0.25</sub></td><td>1.00<sup>+0.20</sup><sub>-0.22</sub></td><td>3.40</td><td>0.010</td></tr><tr><td>268</td><td>166.58162</td><td>-77.40297</td><td>9.08<sup>+0.80</sup><sub>-0.95</sub></td><td>2.50<sup>+0.04</sup><sub>-0.04</sub></td><td>3.11<sup>+0.03</sup><sub>-0.03</sub></td><td>0.28<sup>+0.02</sup><sub>-0.03</sub></td><td>0.34<sup>+0.03</sup><sub>-0.04</sub></td><td>0.80<sup>+0.01</sup><sub>-0.02</sub></td><td>3.33</td><td>0.078</td></tr><tr><td>269</td><td>166.56546</td><td>-77.40152</td><td>5.92<sup>+1.63</sup><sub>-3.02</sub></td><td>2.09<sup>+0.10</sup><sub>-0.11</sub></td><td>2.24<sup>+0.04</sup><sub>-0.04</sub></td><td>0.35<sup>+0.10</sup><sub>-0.18</sub></td><td>0.38<sup>+0.10</sup><sub>-0.19</sub></td><td>0.93<sup>+0.05</sup><sub>-0.05</sub></td><td>2.86</td><td>0.013</td></tr></tbody></table>
<table><caption>Table 1 (continued) | Ice column densities for lines of sight towards Cha I</caption><thead><tr><th rowspan="2">ID</th><th rowspan="2">RA</th><th rowspan="2">Dec</th><th>N<sub>H2O</sub></th><th>N<sub>CO2</sub></th><th>N<sub>CO</sub></th><th>CO<sub>2</sub><br>H<sub>2</sub>O</th><th>CO<br>H<sub>2</sub>O</th><th>CO<sub>2</sub><br>CO</th><th>N<sub>H2</sub></th><th>F410M</th></tr><tr><th>(J2000)</th><th>(J2000)</th><th>(10<sup>18</sup> cm<sup>-2</sup>)</th><th>(10<sup>18</sup> cm<sup>-2</sup>)</th><th>(10<sup>18</sup> cm<sup>-2</sup>)</th><th>(10<sup>22</sup> cm<sup>-2</sup>)</th><th>(mJy)</th></tr></thead><tbody><tr><td>270</td><td>166.61729</td><td>-77.40081</td><td>4.94<sup>+1.64</sup><sub>-2.83</sub></td><td>2.38<sup>+0.11</sup><sub>-0.13</sub></td><td>3.38<sup>+0.26</sup><sub>-0.28</sub></td><td>0.48<sup>+0.16</sup><sub>-0.28</sub></td><td>0.68<sup>+0.23</sup><sub>-0.40</sub></td><td>0.70<sup>+0.06</sup><sub>-0.07</sub></td><td>4.04</td><td>0.011</td></tr><tr><td>271</td><td>166.67457</td><td>-77.40035</td><td>7.43<sup>+0.74</sup><sub>-1.04</sub></td><td>2.62<sup>+0.02</sup><sub>-0.02</sub></td><td>2.39<sup>+0.10</sup><sub>-0.11</sub></td><td>0.35<sup>+0.04</sup><sub>-0.05</sub></td><td>0.32<sup>+0.04</sup><sub>-0.05</sub></td><td>1.10<sup>+0.05</sup><sub>-0.05</sub></td><td>2.92</td><td>0.016</td></tr><tr><td>273</td><td>166.59044</td><td>-77.39820</td><td>9.56<sup>+1.10</sup><sub>-1.52</sub></td><td>3.96<sup>+0.04</sup><sub>-0.05</sub></td><td>2.98<sup>+0.12</sup><sub>-0.13</sub></td><td>0.41<sup>+0.05</sup><sub>-0.07</sub></td><td>0.31<sup>+0.04</sup><sub>-0.05</sub></td><td>1.33<sup>+0.06</sup><sub>-0.06</sub></td><td>3.71</td><td>0.051</td></tr><tr><td>277</td><td>166.58604</td><td>-77.39576</td><td>4.80<sup>+0.90</sup><sub>-1.13</sub></td><td>1.54<sup>+0.16</sup><sub>-0.19</sub></td><td>2.11<sup>+0.44</sup><sub>-0.50</sub></td><td>0.32<sup>+0.07</sup><sub>-0.09</sub></td><td>0.44<sup>+0.12</sup><sub>-0.15</sub></td><td>0.73<sup>+0.17</sup><sub>-0.19</sub></td><td>3.40</td><td>0.008</td></tr><tr><td>279</td><td>166.56310</td><td>-77.39154</td><td>6.60<sup>+0.87</sup><sub>-1.10</sub></td><td>2.28<sup>+0.08</sup><sub>-0.09</sub></td><td>2.69<sup>+0.08</sup><sub>-0.09</sub></td><td>0.35<sup>+0.05</sup><sub>-0.06</sub></td><td>0.41<sup>+0.06</sup><sub>-0.07</sub></td><td>0.85<sup>+0.04</sup><sub>-0.04</sub></td><td>2.44</td><td>0.016</td></tr><tr><td>282</td><td>166.59253</td><td>-77.38763</td><td>9.19<sup>+0.76</sup><sub>-0.89</sub></td><td>2.02<sup>+0.05</sup><sub>-0.05</sub></td><td>2.77<sup>+0.05</sup><sub>-0.05</sub></td><td>0.22<sup>+0.02</sup><sub>-0.02</sub></td><td>0.30<sup>+0.03</sup><sub>-0.03</sub></td><td>0.73<sup>+0.02</sup><sub>-0.02</sub></td><td>2.38</td><td>0.111</td></tr><tr><td>285</td><td>166.63364</td><td>-77.38652</td><td>4.83<sup>+1.35</sup><sub>-1.99</sub></td><td>1.63<sup>+0.08</sup><sub>-0.08</sub></td><td>1.85<sup>+0.38</sup><sub>-0.42</sub></td><td>0.34<sup>+0.10</sup><sub>-0.14</sub></td><td>0.38<sup>+0.13</sup><sub>-0.18</sub></td><td>0.88<sup>+0.19</sup><sub>-0.21</sub></td><td>4.44</td><td>0.006</td></tr><tr><td>287</td><td>166.61472</td><td>-77.38278</td><td>3.83<sup>+2.08</sup><sub>-2.76</sub></td><td>1.13<sup>+0.02</sup><sub>-0.02</sub></td><td>1.79<sup>+0.51</sup><sub>-0.54</sub></td><td>0.29<sup>+0.16</sup><sub>-0.21</sub></td><td>0.47<sup>+0.29</sup><sub>-0.36</sub></td><td>0.63<sup>+0.18</sup><sub>-0.19</sub></td><td>2.68</td><td>0.011</td></tr><tr><td>288</td><td>166.60876</td><td>-77.38241</td><td>6.02<sup>+1.86</sup><sub>-3.71</sub></td><td>1.87<sup>+0.06</sup><sub>-0.06</sub></td><td>2.31<sup>+0.64</sup><sub>-0.69</sub></td><td>0.31<sup>+0.10</sup><sub>-0.19</sub></td><td>0.38<sup>+0.16</sup><sub>-0.26</sub></td><td>0.81<sup>+0.23</sup><sub>-0.24</sub></td><td>2.28</td><td>0.013</td></tr><tr><td>292</td><td>166.66850</td><td>-77.40506</td><td>7.43<sup>+0.83</sup><sub>-1.26</sub></td><td>1.97<sup>+0.03</sup><sub>-0.03</sub></td><td>2.45<sup>+0.19</sup><sub>-0.19</sub></td><td>0.26<sup>+0.03</sup><sub>-0.05</sub></td><td>0.33<sup>+0.05</sup><sub>-0.06</sub></td><td>0.80<sup>+0.06</sup><sub>-0.06</sub></td><td>2.62</td><td>0.016</td></tr><tr><td>294</td><td>166.65721</td><td>-77.39785</td><td>9.41<sup>+0.87</sup><sub>-1.06</sub></td><td>2.97<sup>+0.05</sup><sub>-0.06</sub></td><td>3.69<sup>+0.17</sup><sub>-0.18</sub></td><td>0.32<sup>+0.03</sup><sub>-0.04</sub></td><td>0.39<sup>+0.04</sup><sub>-0.05</sub></td><td>0.81<sup>+0.04</sup><sub>-0.04</sub></td><td>4.54</td><td>0.036</td></tr><tr><td>296</td><td>166.63839</td><td>-77.40737</td><td>7.54<sup>+0.81</sup><sub>-0.95</sub></td><td>2.55<sup>+0.04</sup><sub>-0.04</sub></td><td>2.25<sup>+0.26</sup><sub>-0.24</sub></td><td>0.34<sup>+0.04</sup><sub>-0.04</sub></td><td>0.30<sup>+0.05</sup><sub>-0.05</sub></td><td>1.13<sup>+0.13</sup><sub>-0.12</sub></td><td>2.78</td><td>0.023</td></tr></tbody></table>

All objects are identified using their source catalogue IDs and their RA and dec. coordinates. Each column density value, reported in units of 10¹⁸ molecules cm⁻², is accompanied by error bars derived from the 95% confidence interval on the column density, as described in the Methods. Source IDs marked with an asterisk are those with partial wavelength coverage of the H₂O absorption band feature. Their column densities were derived in a manner different from fully sampled H₂O absorption band features. The ice column ratios plotted in Fig. 3, the hydrogen column densities taken from the Herschel far-infrared observations³⁹⁻⁴¹ and the flux density at 4.10 µm derived from direct imaging frames are also given. Objects #077 and #273 are NIR38 and J110621, respectively, as previously published²,³⁴, and NIRCam WFSS spectra for objects #077, #085, #089, #092, #268, #273, #282 and #294 were previously published³⁵.

background sources decreases as we move to the densest part of the cloud, coherent with the high gradient in N(H₂) rapidly obscuring the lines of sight at the highest column.

## Discussion

Differences in the relative abundances of H₂O, CO and CO₂ are key to unravelling which chemical pathways are active in the darkest regions of molecular clouds. In Fig. 3 (left), we present novel maps of the ratios between column densities of CO, CO₂ and H₂O ices that highlight spatial variation in these species across the observed field of view. More traditional correlation plots are shown in the right-hand panels, while in Extended Data Fig. 4 we compare the ice column densities at high extinction in Cha I with those observed at lower columns from available data across multiple clouds in the literature. Overall, the correlations observed previously at lower extinctions globally hold for column densities an order of magnitude higher, that is, total ice column densities greater than 10¹⁹ cm⁻² for these three major ices. Despite the increase in cloud depth probed by these observations of Cha I, the correlations between all three ice species are broadly constant across the cloud, probably because the field of view is restricted to the densest regions of the Cha I cloud. However, there are small but consequential spatial variations in the ice abundances that can be seen in the ice ratio maps (Fig. 3). In addition, by following the trends in the ice ratios as a function of variation in the Herschel-derived H₂ column density contours, we can trace the dependence of ice ratios on density. For example, it can be seen that, where the dust column densities are lowest, the CO₂/H₂O ratio exhibits its lowest values (-0.15), while this ratio increases steadily to -0.4 towards the densest observed region of the Cha I cloud. The ratio map of CO and H₂O shows that the CO abundance is greatest in the same dense regions where the CO₂ abundance peaks.

We can interpret these results in terms of the chemical pathways by which the different ice species form. Whereas H₂O is known to form

on the grains in molecular clouds, CO is already present in the gas phase and freezes out—either trapped within the H₂O layer as the ice is forming, owing to temporary sticking and entrapment, or predominantly during the catastrophic freeze-out that accompanies core collapse¹⁲,⁴³. CO₂ has been observed to form either early, in a water-dominated ice, or later in a CO-dominated ice¹,⁶,¹⁰,¹⁷,⁴⁴. These maps suggest that we not only see the formation of CO₂ in H₂O ice but also probe the onset of the CO₂ formation within the CO ice at higher densities. Because this region of Cha I is denser compared with previously observed targets at lower extinction, more CO should be frozen out, subsequently enabling more CO₂ ice production on the grains. The amount of CO ice on the grains suggests that CO freeze-out is well underway, although gas-phase data are needed to determine how complete the freeze-out is. Consistent with increased CO freeze-out, the CO/H₂O ratio increases towards the densest region of the map, where Cha MMS1 is located. We see two additional regions with high CO/H₂O, at around 5,000 and 10,000 AU southwest of the position of this class 0 object. Both appear along a dense dust ridge, with the second clump being in approximately the same location as (around 2,000 AU southeast of) a potential prestellar core identified in the Herschel dust maps³⁸. The greater sensitivity of JWST allows access to such lines of sight in a cloud.

To see whether there are substantial differences in composition between our results for the three major ices in a single molecular cloud with literature results from a melange of different clouds, we plot the Cha I data against the existing literature in Fig. 4. The ternary plot presented on the left clearly illustrates that our single observational dataset with 44 new objects has tripled the total number of molecular cloud H₂O–CO₂–CO ice abundance values derived from background stars. In the plot, most Cha I data points fall within the preexisting spread, although overall tending towards higher CO₂ and CO contributions than the datasets in Fig. 4. This is not unexpected; the Cha I dataset probes higher extinctions than previous molecular cloud studies, and thus we
<figure><img src="image_7.png" /><figcaption>**Fig. 3** | Correlations between the three main ice species, H₂O, CO and CO₂, in Cha I. Left, maps of the ice ratios CO₂ to H₂O, CO to H₂O and CO₂ to CO. These maps are obtained by dividing one ice species' column density map (Fig. 2) by another. Right, correlation plots between CO₂ and H₂O, CO and H₂O, and CO₂ and CO measured towards background stars. Ice column densities and errors</figcaption></figure>

are presented as those in Fig. 2. Our data for Cha I are compared with literature values from studies on all three main ice species in Extended Data Fig. 4. The two representations of the same ice column density correlations allow visualization of the distribution as a function of spatial position (left) or total column density (right).

expect higher CO abundances due to probing more advanced stages of freeze-out. This can be seen on the right of Fig. 4 where the mean and median values of our whole sample are plotted against the ensemble of background star sources from the ternary plot. The median values in Cha I are 29.3% for CO₂/H₂O and 33.8% for CO/H₂O compared with 16.9% and 27.0%, respectively, in the literature values. The lower panel shows data for the five individual lines of sight in Fig. 1. It is immediately apparent that there are considerable variations in relative ice abundances of the three major ice species. CO₂ is one of the more difficult of the major ice species to quantify and compare between different observational campaigns, as it can be observed only from non-ground-based observatories, often by only one of its two fundamental modes (at 4.27 or 15.2 µm), and may be quantified using different band strengths. Our values for Cha I are narrowly clustered at 15–25% of the total ice mixture and near the upper end of CO₂/H₂O ratios previously probed across a range of different molecular cloud environments in H₂O, CO₂ and CO.

In dense clouds, a large fraction of atomic oxygen is locked into dust components, with roughly 16–24% in refractory silicates⁴⁵. At the high densities probed here in Cha I, the observed H₂O, CO₂ and COices are abundant species that also contain a large fraction of the available oxygen. Cosmic O abundances are debated, but studies typically find a value in the 450–575 ppm range⁴⁶⁻⁴⁸. When we compare the O component from our derived ice column densities with the H₂ column density estimated from far-infrared emission³⁹⁻⁴¹, we observe high levels of O depletion of 255 ± 113ppm (the error is given as two times the standard deviation on the mean, 2σ) over the range of sampled H₂O ice column densities spanning an order of magnitude. Although we include the major species, this total O-bearing ice column remains a lower limit because we do not include less abundant species (such as CH₃OH, OCN⁻ or complex organic molecules). Their inclusion will moderately increase this estimate at the H₂ densities considered here. Although the H₂ column density was taken from dust emission studies³⁹⁻⁴¹ and
<figure><img src="image_8.png" /></figure>

**Fig. 4** | **Comparison of ice column densities in Cha I with other clouds.** Left, the total ice column densities presented as a ternary plot, showing the sum of the fractional column densities for the three ice species, that is, $[H_2O] + [CO_2] + [CO] = 1$ for each object. Marker size corresponds to the total ice column density $N_{H_2O} + N_{CO_2} + N_{CO}$. The 44 Cha I lines of sight are marked in black. Literature data points for other cloud background stars are shown in coloured symbols: red from ref. 8, orange from ref. 20 including data from refs. 12–14,16,19, pink from ref. 22 including data from refs. 12–14,16–18,21,23, and cyan from ref. 10. Note that the axis ranges are truncated for all three species, but the range sampled in each case is 0.55 (for CO and $CO_2$ we plot 0–0.55, while for $H_2O$ we plot 0.45–1). Right, the relative column densities of CO and $CO_2$ to $H_2O$ for the five representative spectra shown in Fig. 1 are plotted as bars in the bottom panel,

<figure><img src="image_9.png" /></figure>

with $N_{CO}/N_{H_2O}$ in green and $N_{CO_2}/N_{H_2O}$ in purple. The error bars on the ratios are the propagated column density errors. $N_{H_2O}/N_{H_2O} = 100\%$ is marked as a dashed blue line. Median and mean values for the 44 objects in this study and the 23 background stars for which all three ices have been measured in the literature are shown in the top panel for reference. In each case, the median abundance of CO and $CO_2$ ice (relative to $H_2O$ ice) is indicated by the orange line on the bar and the mean is shown as a solid black line. The coloured bar (green for CO and purple for $CO_2$) displays the range lying between the first and third quartiles of the data (interquartile range). The dashed black lines show the first quartile minus 1.5 times the interquartile range and the third quartile plus 1.5 times the interquartile range. Data points outside of this range (outliers) are shown as black crosses.

intrinsically has uncertainty in the absolute value, the O/H numbers derived here make $H_2O$, $CO_2$ and CO ices the major O-containing species at the high densities probed in the central region of Cha I, effectively locking up in the ices about half of the oxygen, that is therefore not available for gas-phase chemistry. This calculation is consistent with most of the CO being frozen out. Previous estimates of CO freeze-out towards NIR38 and J110621 found that the carbon-rich ices could account for at most ~40% of the expected CO gas column, based on preliminary extinction estimates²⁷. However, updated extinction values 50% lower were recently found by ref. 34, effectively doubling the expected CO freeze-out to 85%.

In this study, we have focused on mapping ices across the core of the Cha I molecular cloud, where the sensitivity of JWST allowed us to probe ice column densities an order of magnitude higher than previous studies along lines of sight towards background stars. The ice ratio maps in Fig. 3 demonstrate the power of observing several tens of objects in one observation. In particular, compared with the traditional correlation plots, the spatial distribution information reveals lines of sight deviating from the broad trends across the cloud. The power of this type of large-scale survey is that the statistical significance and causes of these deviations can now start to be investigated. This was previously not possible, when lines of sight through an individual cloud or core measured by a single observational campaign were limited to a few objects¹, sometimes targeting particular spectral bands¹⁷,¹⁹ This ice mapping approach could be applied to lower-density cloud regions, including for Cha I using data being acquired with the JWST, complementing the dynamic range of densities that can be probed in a single cloud and extending the investigation to the ice onset at cloud edges. Sampling ice in this way also opens the path to comparing solid-phase with gas-phase maps on a similar spatial scale. Cospatial mapping of the entire molecular inventory, both gas and solid phase, would provide the key to tackling open questions around gas–grain exchange phenomena, such as the CO freeze-out accompanying the transition to higher densities and the impact of such an extreme chemistry switch. Ultimately, placing constraints on the oxygen budget in the

ice is decisive for setting the initial elemental budget for subsequent star and planet formation chemistry.

## Methods

### Outline of the observations

The observing programme from which these results are derived was briefly described elsewhere²⁷,³³. The observations and the data reduction method are summarized here and described in detail in Smith et al. (manuscript in preparation). JWST/NIRCam WFSS observations of a region of the Cha I molecular cloud were taken across seven observing periods on 3 July, 11 August and 12 August 2022, as part of the Director's Discretionary Early Release Science (ERS) programme, IceAge (PID 1309, principal investigator McClure⁴⁹). Spectral observations covered both Grism C and Grism R dispersion directions, with both the F322W2 and F444W filters, with three primary (set to the INTRAMODULEBOX primary dither pattern) and four subpixel dithers, in a mosaic of one row by two columns or two rows by one column, resulting in up to 48 spectral frames per filter per detected background source, with a total exposure time of 15.5 h. The set-up resulted in full or partial spectral coverage ($\lambda = 2.413$ µm to 5.084 µm) for many hundreds of detected background sources behind the most extincted central core region of Cha I, encompassing spectral features from material within the extincted cloud region including the $H_2O$, $CO_2$ and CO ice features (see Extended Data Fig. 1 for filter footprints). A subset (44) of these spectra from the central core region feature in this Article. Eight of these spectra were presented in a recent study where the dangling OH stretching mode absorption features of $H_2O$ at -2.7 µm were detected for the first time³³. Two of those eight NIRCam spectra correspond to the background stars NIR38 (11:06:25.39-77:23:15.70, J2000; object #077) and J110621 (SSTSL2J110621.63-772354.1, 11:06:21.70-77:23:53.50, J2000; object #273), which were also observed in pointed observations with NIRSpec Integral Field Unit and Mid-Infrared Instrument (MIRI) Low Resolution Spectroscopy spectrometers by the JWST ERS programme Ice Age²⁷,³⁴,⁴⁹. The lines of sight towards NIR38 and J110621 have been extensively analysed to determine the chemical composition of the
ice²⁷ and the extent to which icy grains have grown relative to the dif-
fuse ISM grain distribution³⁴. Short-wavelength imaging was obtained
concurrently with the spectral frames, in F150W (with F322W2) and
F200W (with F444W). To generate the source catalogue and pho-
tometry and subsequently extract the dispersed spectral data, these
short-wavelength imaging frames as well as additional direct imaging,
using F182M and F430M (with the F444W filter) and F140M and F410M
(with the F322W2 filter), were used.

Data reduction and spectral extraction

The data reduction pathway and spectral extraction from the crowded
fields in our NIRCam WFSS data are briefly outlined in ref. 33. Data
reduction starts with image processing, which follows that in ref. 50,
combining the outputs up to and including stage 2 of the JWST/NIRCam
direct imaging operational pipeline with custom treatment of NIRCam
direct images by members of the NIRCam calibration team⁵¹,⁵². Direct
imaging frames (F150W, F200W, F410M and F430M) were cleaned,
astrometry corrected with Gaia data, cross-matched and mosaicked.
Individual source catalogues for each filter were derived from the
mosaicked image in a three-step approach. First, photutils was run to
derive an initial catalogue, optimized to identify point sources. Manual
corrections were performed to remove the small number of false posi-
tives, such as hot pixels, and to add in extra sources of extended geom-
etries, such as galaxies or jets. Finally, the peak finding function from
photutils was used to ensure that the manually added positions were
accurately centred on their sources. The final source catalogue was
made by combining the source catalogues from the individual filters.

The standard JWST WFSS spectral pipeline products fail to pro-
duce accurate spectra in confused fields such as Cha I. The custom
spectral extraction programme developed by the IceAge ERS team is
briefly outlined here. To obtain the final spectral data, we first reduced
each individual grism spectroscopic image frame with the standard
JWST calibration pipeline v1.6.2 up to and including stage 2a, using
the default Calibration Reference Data System (CRDS) set-up with
JWST's operational pipeline, OPS, and no modifications (CRDS context
0953), as reported previously²⁷. Following this, flat-field correction
was applied using the imaging flat data obtained with the same filter,
then two-dimensional sky-background subtraction was performed
using sigma-clipped median images that were constructed from our
spectral frames.

Beyond JWST pipeline stage 2a, an in-house 1D point spread func-
tion (PSF) fitting method (as illustrated in Extended Data Fig. 2) was
used to extract spectra of each observable source from every individual
dispersed frame in the WFSS observations. These individual dispersed
frame spectra are then recombined to produce the final spectrum for
each source. We were limited to extracting spectral data from sources
with flux densities of down to 2 µJy. To extract the flux values at every
spectral element of each source's spectral trace, the 1D PSF fitting is
applied to a one-pixel wide, cross-dispersion direction cut-out of the
dispersed image, where all the source's traces that are present are fit-
ted concurrently to correctly attribute flux to the appropriate source
in the confused field. χ² minimization is performed with the iminuit⁵³
Python fitting package to optimize the 1D PSF fit, and WebbPSF (https://
www.stsci.edu/jwst/science-planning/proposal-planning-toolbox/
psf-simulation-tool) is used to account for positional changes in the PSF
on the detector. This provides a wavelength–flux (with flux errors) data
point for each source, from each grism spectral frame in which each
source appears. This results in up to 48 individually extracted spectra
per source, per filter. Because the central region of Cha I is slightly larger
than the size of a single dispersed image, some sources near the outer
edges of this region are observed in a subset of the 48 dispersed image
frames that are analysed here. These individual dispersed frame spectra
are all regridded onto a common wavelength grid with 1.006-nm wave-
length steps using the SpectRes⁵⁴ Python package. Once regridded,
they are recombined using the weighted median values of each spectral

data point from all the individual dispersed frame spectra. The process
is repeated for each filter separately. This spectral regridding results in
trace lengths of 1,638 for the F322W2 filter (equivalent to ground-based
L-band coverage). This is almost equivalent to the preflight-measured
F322W2 trace lengths of 1,670. For the F444W filter (equivalent to the
ground-based M-band coverage), the trace length is 1,209, again almost
equivalent to the preflight-measured F444W trace lengths of 1,249.
This means that our spectra have *R* values very close to those measured
preflight for F322W2 and F444W. The preflight *R* values can be derived
for each wavelength using the formula given in ref. 32, and thus, for the
reference wavelength of our two spectral filters, we derive *R* of 1,441 at
λ<sub>ref</sub> = 3.231976 and 1,654 at λ<sub>ref</sub> = 4.404315 µm.

Wavelength and flux calibrations were performed using the
in-flight measurements obtained with JWST Commissioning Program
#1076 (corrected by CRDS context 1090 in late January 2023 for the flux
calibration, and by using the S6 sensitivity curves (private communi-
cation Dr Nor Pirzkal) for the wavelength calibration). These updates
account for the minor flux and wavelength differences between NIR-
Cam spectral data presented in refs. 27,34 for NIR38, and the spectral
data of the same object in this Article and in ref. 33. In some cases, a
slight oversubtraction of the local background near the spectral trace
during the grism image correction processing stage of the extraction
can lead to the PSF fitting returning real spectral shape profiles but
(unphysical) negative flux. To account for this oversubtraction in the
F444W spectra (where the F410M photometry lies within the filter
wavelength range), spectra were shifted up to match the photometric
points, a commonplace approach in ice spectral data processing¹⁰,¹¹,²³,³⁵.
Aperture photometry was performed on the F410M mosaicked images,
applying a circular aperture with a radius of 4 pixels centred on each
source position to determine the source flux, and correcting for the
background flux measured within a 10-pixel-wide annulus from 15 to
25 pixels. The sources to which this shift was applied had to match two
conditions. First, the photometric flux had to be higher than the aver-
age flux of the continuum of a rolling-median-smoothed F444W fully
combined spectrum between 4.03 µm and 4.17 µm. Second, the aver-
age flux in the peak of the CO₂ feature of a rolling-median-smoothed
F444W fully combined spectrum, between 4.259 µm and 4.277 µm, had
to be negative. The shift applied was the difference between the aver-
age continuum 4.03–4.17 µm flux value and the F410M photometric
point. The maximum shift applied to a F444W spectrum was 10 µJy.
For the F322W2 spectra, there is no photometric point within the filter
wavelength range to shift the spectrum to. Therefore to account for
the oversubtraction in F322W2 spectra, the average flux in the peak of
the H₂O feature of a rolling-median-smoothed F322W2 fully combined
spectrum between 2.98 µm and 3.1 µm was calculated. If this was nega-
tive, a shift equivalent to this value was added to the F322W2 spectrum.
The maximum shift applied to a F322W2 spectrum was 2 µJy, that is, the
same as the spectral extraction limit. Although, strictly speaking, the
oversubtraction of the local background may not be constant along
the spectral trace for a given source, the pixel-to-pixel variations in this
densest region of the cloud will be extremely low owing to the lack of
extraneous light sources.

The total number of detected sources in the imaging frames within
the central region of Cha I was 372. After discounting objects below the
flux limit for spectral extraction 2 µJy at 4.1 µm and those where the S/N
was too low to allow clear detections of all three absorption features for
H₂O, CO₂ and CO ices, 44 lines of sight remain from which to construct
ice maps of the central region of Cha I. All objects are identified using
their source catalogue IDs. JWST is so sensitive that we now observe
lines of sight towards galaxies behind the cloud in addition to the lines
of sight that have traditionally been used to probe molecular cloud
ices, that is, towards background (field) stars and towards embedded
young stellar objects (YSOs). In this case, we can distinguish galaxies
from background stars in the direct imaging frames because they are
extended sources and not point sources like the background stars.
However, we choose not to include the two lines of sight towards galaxies observed in the Cha I central region as (1) there may be issues with undersampling of the flux in these extended sources that are wider than the PSF, and (2) their spectra may intrinsically contain ice absorption features that would confuse the determination of cloud ices.

## Spectral analysis and ice map construction

Extracted spectra were analysed to determine ice column densities. The process of spectral analysis is illustrated in Extended Data Fig. 3a. In brief, local baselines were fitted to the continuum around each absorption band using a Gaussian process regression implementation provided by the scikit-learn Python package³⁵. The Gaussian process regression models the baseline as the mean vector of a multi-dimensional Gaussian probability density function and are fitted to a rolling-median-smoothed version of the spectrum based upon conditioning data points that tether the fit to the continuum at two to three points on each side of each band. The H₂O baseline Gaussian process regression model is tethered to flux values at wavelengths 2.55, 2.67, 2.72, 3.86 and 3.91 µm; CO₂ at 3.97, 4.1, 4.365, 4.47 and 4.51 µm; and CO at 4.47, 4.53, 4.76, 4.82 and 4.86 µm. The uncertainty at each wavelength in the model is the standard deviation of the Gaussian process along the dimension corresponding to that wavelength, and the best-fitting model minimizes the overall variance, ensuring the statistically most likely baseline.

Optical depth spectra $\tau(\lambda)$ were derived using

$$ \tau(\lambda) = -\ln\left(\frac{F_{\text{obs}}(\lambda)}{F_{\text{cont}}(\lambda)}\right), \qquad (1) $$

where $F_{\text{obs}}(\lambda)$ is the observed flux density and $F_{\text{cont}}(\lambda)$ is the continuum baseline model. In this type of slitless spectroscopy study, where tens or hundreds of spectra are extracted simultaneously, the spectrum-specific approach of deriving column densities by determining the spectral energy distribution of the background source to fit the continuum and correct for photospheric absorption features, then fitting each individual absorption feature with grain shape- and size-corrected laboratory spectra of pure and mixed ices, is very labour intensive. Following a strategy similar to those in studies such as refs. 56,57, the column densities of CO and H₂O were determined by integrating the optical depth spectra between two wavelength limits, and dividing by the band strength⁵⁸. The values are as follows: H₂O integrated between 2.716 µm and 3.35 µm, band strength $2 \times 10^{-16}$ cm per molecule; CO integrated between 4.65 µm and 4.705 µm, band strength $1.1 \times 10^{-17}$ cm per molecule⁵⁸. Errors on the derived column densities are computed by applying a toy Monte Carlo approach, based on 1,000 baselines produced from the Gaussian process regression model described above. The column density is calculated for each of the 1,000 baselines, and the final error estimates are determined from the 95% confidence interval ($2\sigma$ in flux space) on the distribution of derived column densities.

Among the 44 sources analysed here, 11 have truncated or partial spectra across the 3 µm H₂O absorption feature due to their proximity to the filter edge. Column densities are estimated for these sources through fitting of a set of nine unsaturated template H₂O features measured in mapped regions outside the central region presented here (see F322W2 footprint in Extended Data Fig. 1). This is completed in two stages, illustrated in Extended Data Fig. 3b. First, the template spectra and partial spectrum are shifted in flux space by calculating and subtracting the average continuum flux value of a smoothed (rolling median) spectrum between 3.82 µm and 3.92 µm. The shifted templates are then fitted (rescaled with a limited localy shift) to the shifted partial spectrum to the data points in the range 3.17–3.29 µm, where the best fit is found through $\chi^2$ minimization (Extended Data Fig. 3b(i)). The same shift and scale is then applied to the baseline of the best-fit template spectrum, which is used to produce an optical depth spectrum of the

truncated source. In optical depth space, the template source's optical depth spectrum is then fitted by scaling to the partial optical depth spectrum, following ref. 57 (Extended Data Fig. 3b(ii)). The column density of H₂O is then derived from the area under the scaled template spectrum, as described above. Column density errors are derived from the extremes of fitted scaled template spectra.

To estimate CO₂ column densities, the area under the peak integration method was not used, as illustrated in Extended Data Fig. 3c. After visual inspection of the spectra, it was determined that the CO₂ absorption feature was saturated along almost all observed lines of sight (zero flux, with a flat base). Thus, instead of integrating the area under the whole band, the area under the spectral wings of CO₂—defined to be between 4.24 µm and 4.249 µm and between 4.281 µm and 4.29 µm (red areas under optical depth spectrum of CO₂ feature in Extended Data Fig. 3c)—is first calculated. These wing limits were chosen primarily to avoid the saturated region of the band but also to avoid the edges of the feature where radiative transfer and scattering effects may affect the band profile. The CO₂ column densities for saturated bands were derived using $N_{\text{CO}_2} = \alpha \times N_{\text{CO}_2,\text{wings}}$, where $\alpha$ is the ratio between the total area under the CO₂ band and the area under the wings. This constant was derived from eight unsaturated bands taken from less dense regions of the full cloud area observed (Extended Data Fig. 1) and has a value of 7.62 ± 0.96. CO₂ column densities were derived using the band strength $7.6 \times 10^{-17}$ cm per molecule as reported in ref. 58 based on the original data of ref. 59. Errors on the CO₂ column densities are found by calculating the errors on the column density of the CO₂ wing regions and applying the same mean ratio scale factor as to the column density itself.

This method for determination of column density via the band wings could not be applied to saturated H₂O or CO features within our dataset. As is well known in the field, the derivation of column densities from ice absorption features is complicated by many factors, including but not limited to correct determination of the continuum, overlapping of absorption features from different molecules (functional groups) and scattering due to grain size and shape effects. In particular, for H₂O, the broad 3-µm feature's red wing overlaps with other functional group absorption features from molecules such as CH₃OH, CH₄ and NH₃ and includes a scattering contribution due to the grain size and shape distributions along the line of sight, while the blue wing includes both radiative transfer and extinction effects. For CO, the absorption cross section area is far lower than CO₂. In addition to this, CO has a narrower band profile, and so this means only a few spectral elements would be available to define wings from. Within these few spectral elements, noise, potential photospheric lines and radiative transfer and scattering effects cause too much variation in the area under these wings to produce a reliable ratio of wings to total area. Various approaches have been implemented in previous studies to try to mitigate these effects. A few examples include deconvolving spectral contributions from different molecules using laboratory spectra (with or without grain correction)⁶,¹⁰,²⁷, modelling the grain scattering effects²,³⁴ and component fitting across different spectra⁶⁰. Other studies have taken a more direct approach to estimating the contribution of molecular absorption, using the optical depth as a tracer¹⁶, or integrating the area under the peak⁵⁶,⁵⁷. As stated above, we adopt a methodology similar to refs. 56,57, and overall, despite the difference in analytical approach, for all three molecules studied here, the column densities derived here agree with those derived by ref. 27 towards the sources NIR38 and J110621. Thus, column densities for all CO and H₂O features were derived by integrating the area under the band in optical depth space, as described above.

The derived column densities of H₂O, CO₂ and CO ice for 44 lines of sight are reported in Table 1. The H₂O column densities presented here have been slightly revised compared with those originally presented for objects #077, #085, #089, #092, #268, #273, #282 and #294 in ref. 33, but all values lie within the uncertainties given in Table 1 and
this impacts neither the values derived nor the conclusions drawn in ref. 33. For objects #077 and #273, prior quantification of the column densities of H₂O, CO₂ and CO was derived by two spectral fitting approaches in refs. 27,34. The values derived here for H₂O and CO agree with those in ref. 27 within the error bars. It should be noted that, in ref. 27, a band strength of 1.1 × 10⁻¹⁶ cm per molecule was used for CO₂, as reported in ref. 61 based on the original data of refs. 58,59. Here, we choose to use the value 7.6 × 10⁻¹⁷ cm per molecule to be consistent when comparing our observations to the CO₂ values derived from the 4.27-µm band in literature data from previous studies using ISO and AKARI. For objects #077 and #273, we derive CO₂ values of 1.40±0.03 and 2.74±0.03 × 10¹⁸ cm⁻², respectively, if using the band strength 1.1 × 10⁻¹⁶ cm per molecule. The column densities derived for H₂O, CO₂ and CO can be converted to total O-in-ice column by: N₀ = N₉₂₀ + 2 × Nₐ₂₀ + Nₑ₀. The O/H ratio for the three ice components is derived by N₀/2 × N₉₂. Our derived O abundance can be compared with the cosmic O abundance to determine the fraction in the ice, corresponding to the O depleted from the gas phase.

To construct ice maps, the discrete natural neighbour interpolation method was implemented for the column density values between each source within the maps. The natural neighbor Python package (https://github.com/innolitics/natural-neighbor-interpolation) was used to perform this task, the methods of which are outlined in ref. 62. Ice maps were regridded on the same pixel grid as the Herschel high-resolution N<sub>h2</sub> maps<sup>39–41</sup>. The interpolated map contains values of column density at all locations within the field of view, regardless of the sparsity (or density) of nearby column density measurements. To avoid including potentially misleading column density values within the interpolated ice maps, regions of the map for which the projected offset from any background source is greater than 4,000 AU are removed (assuming that the distance to Cha I is 192 pc)<sup>63</sup>. Finally, the boundaries of the ice map were spatially clipped to exclude any region outside a convex hull connecting the outermost mapped sources. This produces a map footprint with primarily straight boundaries and avoids misleading sections at the map boundaries where the interpolated column density value is dominated by the measurement from a single spectrum.

## Data availability

Observational data are available to download from MAST. Extracted 2.5–5 µm spectra will be made available on the JWST Ice Age Early Release Science program repository via Zenodo at https://zenodo.org/communities/jwst-iceage-ers/.

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## Acknowledgements

Z.L.S. acknowledges support from the Open University for his research PhD studentship, the DAN III network for his postdoctoral funding and E.A. Milne Travelling Fellowship from the RAS. H.J.F. and H.J.D. acknowledge support for astrochemistry at the Open University from STFC under grant agreements ST/T005424/1, ST/X001164/1 and ST/Z510087/1. M.K.M. acknowledges financial support from the Dutch Research Council (NWO; grant number VI.Veni.192.241). J.A.N. and E.D. acknowledge support from French Programme National 'Physique et Chimie du Milieu Interstellaire' (PCMI) of the CNRS/INSU with the INC/INP, cofunded by the CEA and the CNES. A.C.A.B. and J.E. acknowledge support from the Space Telescope Science Institute for programme JWST-ERS-01309.019. F.S. acknowledges funding from the JWST/NIRCam contract to the University of Arizona, NAS5-02105. T.S. acknowledges support from JSPS KAKENHI (grant numbers JP20H05845 and JP21H01145) and Leading Initiative for Excellent Young Researchers, MEXT, Japan. S.B.C. was supported by the Goddard Center for Astrobiology and the NASA Planetary Science Division Internal Scientist Funding Program through the Fundamental Laboratory Research work package (FLaRe). M.N.D. acknowledges the Holcim Foundation Stipend. D.H. is supported by a Center for Informatics and Computation in Astronomy (CICA) grant and grant number 110J035319 from the Ministry of Education of Taiwan. D.H. also acknowledges support from the National Science and Technology Council, Taiwan (grant numbers NSTC111-2112-M-007-014-MY3, NSTC113-2639-M-A49-002-ASP and NSTC113-2112-M-007-027). S.I. acknowledges support from the Danish National Research Foundation through the Center of Excellence 'InterCat' (grant agreement number DNRF150). I.J.-S. acknowledges financial support from grant number PID2019-105552RB-C41 from the Spanish
Ministry of Science and Innovation/State Agency of Research MCIN/AEI/10.13039/501100011033 and from the ERDF 'A way of making Europe'. This work was supported by a grant from the Simons Foundation (grant number 686302, K.I.Ö.) and an award from the Simons Foundation (award number 321183FY19, K.I.Ö.). A portion of this research was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration (80NM0018D0004). W.R.M.R. and E.F.v.D. acknowledge support from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (grant agreement number 101019751 MOLDISK). A.T. acknowledges funding from the European Research Council (ERC) under the European Union's Horizon 2022 research and innovation programme (grant agreement number 101096293 SUL4LIFE).

## Author contributions

Authorship is defined according to the CRediT taxonomy: Z.L.S. (conceptualization, methodology, software, validation, formal analysis, investigation, resources, data curation, writing – original draft, writing – review and editing, and visualization); H.J.D. (conceptualization, methodology, software, validation, formal analysis, investigation, writing – original draft, writing – review and editing, and supervision); H.J.F. (conceptualization, methodology, validation, formal analysis, investigation, resources, data curation, writing – original draft, writing – review and editing, supervision, project administration and funding acquisition); M.K.M. (conceptualization, methodology, validation, formal analysis, investigation, resources, data curation, writing – original draft, writing – review and editing, supervision, project administration and funding acquisition); J.A.N. (conceptualization, methodology, validation, formal analysis, investigation, resources, writing – original draft, writing – review and editing, visualization, project administration and funding acquisition); A.C.A.B. (conceptualization, methodology, investigation, resources, writing – review and editing, supervision, project administration and funding acquisition); F.S. (conceptualization, methodology, software, validation, formal analysis, investigation, and writing – review and editing); E.E. (conceptualization, methodology, validation, formal analysis, investigation, writing – review and editing, and supervision); E.D. (conceptualization, methodology, validation, formal analysis, investigation, resources, writing – original draft, writing – review and editing, and project administration); J.E. (conceptualization,

methodology, validation, formal analysis, investigation, and writing – review and editing); T.S. (conceptualization, methodology, validation, formal analysis, investigation, and writing – review and editing); P.C., S.I., I.J.-S., J.K.J., K.I.Ö., M.E.P., Y.J.P., K.M.P. and E.F.v.D. (conceptualization and writing – review and editing); T.L.B. and R.G. (conceptualization); J.B.B., S.B.C., L.C., M.N.D., D.H., G.J.M., G.P., D.Q., W.R.M.R., J.A.S., A.T. and R.G.U. (writing – review and editing).

## Competing interests

The authors declare no competing interests.

## Additional information

Extended data is available for this paper at
https://doi.org/10.1038/s41550-025-02511-z.

Correspondence and requests for materials should be addressed to
Z. L. Smith.

Peer review information *Nature Astronomy* thanks the anonymous reviewers for their contribution to the peer review of this work.

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© The Author(s) 2025

<footnote n="1">¹School of Physical Sciences, The Open University, Milton Keynes, UK. ²Leiden Observatory, Leiden University, Leiden, the Netherlands. ³Physique des Interactions Ioniques et Moléculaires, CNRS, Aix Marseille Université, Marseille, France. ⁴Institute for Astronomy, University of Hawaiʻi at Manoa, Honolulu, HI, USA. ⁵Center for Astrophysics, Harvard and Smithsonian, Cambridge, MA, USA. ⁶Steward Observatory, University of Arizona, Tucson, AZ, USA. ⁷Institut des Sciences Moléculaires d'Orsay, CNRS, Université Paris-Saclay, Orsay, France. ⁸Institute of Science and Technology, Niigata University, Nishi-ku, Japan. ⁹Space Telescope Science Institute, Baltimore, MD, USA. ¹⁰Department of Chemistry, University of California, Berkeley, CA, USA.</footnote>

<footnote n="11">¹¹Max-Planck-Institut für extraterrestrische Physik, Garching bei München, Germany. ¹²Astrochemistry Laboratory, Solar System Exploration Division, NASA Goddard Space Flight Center, Greenbelt, MD, USA. ¹³Infrared Processing and Analysis Center, California Institute of Technology, Pasadena, CA, USA. ¹⁴Physikalisch-Meteorologisches Observatorium Davos und Weltstrahlungszentrum, Davos Dorf, Switzerland. ¹⁵Departments of Astronomy and Chemistry, University of Virginia, Charlottesville, VA, USA. ¹⁶Institute of Astronomy, Department of Physics, National Tsing Hua University, Hsinchu, Taiwan.</footnote>

<footnote n="17">¹⁷Center for Interstellar Catalysis, Department of Physics and Astronomy, Aarhus University, Aarhus, Denmark. ¹⁸Centro de Astrobiología, CSIC-INTA, Torrejón de Ardoz, Spain. ¹⁹Niels Bohr Institute, University of Copenhagen, Copenhagen, Denmark. ²⁰INAF – Osservatorio Astrofisico di Catania, Catania, Italy. ²¹Department of Physics, University of Central Florida, Orlando, FL, USA. ²²Max Planck Institute for Astronomy, Heidelberg, Germany. ²³Jet Propulsion Laboratory, California Institute of Technology, Pasadena, USA. ²⁴Southwest Research Institute, San Antonio, TX, USA. ²⁵Laboratory for Astrophysics, Leiden Observatory, Leiden University, Leiden, the Netherlands. e-mail: zak.smith@open.ac.uk</footnote>
<figure><img src="image_10.png" /></figure>

**Extended Data Fig. 1** | The JWST NIRCam Ice Age observational footprints. The overlapping ~6.2 arcmin² field outlined in dark blue was used to derive spatial ice maps for H₂O, CO₂ and CO. F150W and F200W short wavelength NIRCam imaging is shown in grey-scale. The H₂ column density contours derived from Herschel far-IR observations from refs. 39–41 are overplotted in a heat color table. The outline footprint for each of the spectral filters is identified by cyan

(F322W2) or purple (F444W) lines. These regions are limited by observational constraints but share a common central region (outlined in dark blue), where all three ice species could be detected. Two black circles mark the positions of the background stars NIR38 (NE) and J110621 (SW)27,33,34 and two yellow stars mark the positions of the Class I YSO CED110 IRS 4a (NE) and the deeply embedded Class 0 YSO Cha MMS1 (SW)38.
<figure><img src="image_11.png" /><figcaption>**Extended Data Fig. 2 | Object positions and spectral extraction procedure. a)**</figcaption></figure>

Object positions across the ~6.2 arcmin² field used to derive cospatial ice maps for H₂O, CO₂ and CO. The positions of the 44 individual background sources are given by black crosses. The H₂ column density contours derived from Herschel far-IR observations from refs. 39–41 are overplotted. The yellow star marks the position of the deeply embedded Class 0 YSO Cha MMS1³⁸. b) A dispersed frame with the object positions overlaid. A black arrow marks the dispersion in the direction of increasing λ and a yellow box marks the position of a cross-dispersion direction cutout of the dispersed frame (20 by 100 pixels). c) The cutout of the

dispersed frame is shown in close-up on the left, with the position of the 1 pixel-wide data column that is analysed in each step of our pipeline highlighted in dark blue. At this scale, one high flux trace is visible against the red background, but actually there are six traces in this one column (marked with light blue lines). Data from this one pixel column are plotted in dark blue on the right. Overlaid on top of these data is the 1D PSF fit to these sources (in light blue). This fitting happens for every source that lies within each 1 pixel column cutout, along the full trace length of each source, and for every source in the field.
<figure><img src="image_12.png" /></figure>

**Extended Data Fig. 3** | Illustration of the baseline determination and column density derivation methods. **a)** The baseline derivation method for the 3 µm absorption feature of H₂O. Data are in black, the mean derived baseline in red, the 1σ baseline errors in dark red and the conditioning points for the Gaussian Process Regression model as blue crosses. **b(i):** The baseline determination method for F322W2 spectra with partial wavelength coverage of the 3 µm absorption feature of H₂O. On a flux scale, a template spectrum (red) is fitted to the data range in orange to derive the continuum (blue). **b(ii):** On the optical depth scale, the flux-space-fitted template spectrum (blue) is fitted to

determine the column density. **c)** the column density derivation method for the CO₂ absorption feature at 4.27 µm. The wings of a saturated CO₂ band (red) are multiplied by the α ratio (derived from unsaturated bands) to determine its column density. The inset in panel **C** shows a typical unsaturated CO₂ feature, one of eight averaged to determine the ratio α. The total CO₂ area (purple) is divided by the area under the wings (red) to derive an average α = 7.62 ± 0.96. Note that in panels **b(ii)** and **c** the y axis scale is not inverted, as would be usual in the optical depth space. This choice visually highlights those panels containing data on an optical depth scale.
<figure><img src="image_13.png" /></figure>

<figure><img src="image_14.png" /></figure>

<figure><img src="image_15.png" /></figure>

<figure><img src="image_16.png" /></figure>

<figure><img src="image_17.png" /></figure>

<figure><img src="image_18.png" /></figure>

Extended Data Fig. 4 | See next page for caption.
**Extended Data Fig. 4** | **Comparison of correlations to literature studies.** Left: Correlation plots between H₂ column density from refs. 39–41 and H₂O (blue), CO₂ (purple), and CO (green) ice column densities derived in our study.

The visual extinction is estimated from N(H₂) by applying the conversion factor A_ν = 10⁻²¹ × N(H₂) from ref. 64. For each ice species, a linear fit is made to the data below A_ν = 22 that is the largest value for which column densities are reported for all three major ice species in ref. 1 It is clear that at higher column densities, the ice columns measured towards Cha I deviate from the linear trend fitted at the lowest extinctions. Ice column densities and errors are presented as those in

Fig. 2. Right: Correlation plots between H₂O and CO₂, H₂O and CO, and CO₂ and CO column densities measured towards background stars. Our datapoints and errorbars for Cha I are plotted in black (as in Fig. 3) and literature values from studies on all three main ice species, that is refs. 8,10,12–14,16–23, are shown in red. Where available for the literature data, the error bars derived in those studies are shown. Linear fits to the Cha I data points and to the data points from the literature are shown as black and red lines, respectively. Both the gradient and its standard deviation change for each correlation with the larger statistical sampling and wider column density range of the Cha I dataset.