EDP Sciences logo
Subscriber Authentication Point
Search
Menu
Home All issues Volume 623 (March 2019) A&A, 623 (2019) L13 Full HTML
Open Access
Issue
A&A
Volume 623, March 2019
Article Number L13
Number of page(s) 9
Section Letters to the Editor
DOI https://doi.org/10.1051/0004-6361/201935040
Published online 25 March 2019

© A. Coutens et al. 2019

Licence Creative CommonsOpen Access article, published by EDP Sciences, under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

1. Introduction

The interstellar medium (ISM) is characterised by a rich and varied chemistry with closely connected groups of species found to be prominent in regions with differing physics. An example is the group of nitrogen oxides, i.e. molecules containing nitrogen-oxygen-hydrogen bonds. Secure interstellar detections have been made for three molecules: nitric oxide (NO; e.g. Liszt & Turner 1978; McGonagle et al. 1990; Ziurys et al. 1991; Caux et al. 2011; Codella et al. 2018; Ligterink et al. 2018), nitrosyl hydride (HNO; Snyder et al. 1993) and nitrous oxide (N2O; Ziurys et al. 1994; Ligterink et al. 2018). These species, in particular NO, are thought to be critical for the overall nitrogen chemistry of the ISM as they may lock up significant amounts of atomic nitrogen, and are often only second in abundance to molecular nitrogen (e.g. Herbst & Leung 1986; Nejad et al. 1990; Pineau des Forêts et al. 1990; Visser et al. 2011). Nitrogen oxides can be at the basis of greater chemical complexity, as demonstrated, for example, with the solid-state hydrogenation of NO into hydroxylamine (NH2OH; Congiu et al. 2012; Fedoseev et al. 2012, 2016) or energetic processing of N2O ice (de Barros et al. 2017).

Despite the relevance of nitrogen oxides as a nitrogen reservoir and as precursors of complex molecules, a number of important members of this group have not yet been detected in the ISM. Examples are nitrogen dioxide (NO2), nitrous acid (HONO), and nitric acid (HNO3), which on Earth play a role in atmospheric pollution (e.g. Possanzini et al. 1988). In particular, the photodissociation of HONO results in abundant formation of OH radicals, which in turn engage in various oxidation reactions and the formation of ground-level ozone (O3; Ren et al. 2003; Lee et al. 2013; Gligorovski 2016; Zhang et al. 2016). Because of its relevance in atmospheric chemistry, the formation, destruction, and characteristics of HONO have been well studied (e.g. Cox & Derwent 1976; Jenkin et al. 1988; Joshi et al. 2012).

In this work, HONO and other nitrogen oxides were searched for towards the low-mass protostar IRAS 16293–2422 (hereafter IRAS 16293), located at a distance of ∼140 pc in the ρ Ophiuchus cloud complex (Dzib et al. 2018). This Class 0 object is known for its chemical complexity and is considered an astrochemical reference among solar-type protostars (e.g. van Dishoeck et al. 1995; Cazaux et al. 2003; Caux et al. 2011; Jørgensen et al. 2016). A large number of species have first been detected towards a low-mass source in this object. These detections include the small species NO and N2O (Caux et al. 2011; Ligterink et al. 2018), the simplest “sugar” glycolaldehyde (HOCH2CHO; Jørgensen et al. 2012, 2016), the peptide-like molecules formamide (NH2CHO) and methyl isocyanate (CH3NCO; Kahane et al. 2013; Coutens et al. 2016; Ligterink et al. 2017; Martín-Doménech et al. 2017), cyanamide (NH2CN; Coutens et al. 2018), methyl isocyanide (CH3NC; Calcutt et al. 2018), ethylene oxide (c-C2H4O, Lykke et al. 2017), and the isomers of acetone (CH3COCH3) and propanal (C2H5CHO, Lykke et al. 2017). Recently, the first interstellar detection of the organohalogen CH3Cl was also reported towards this source (Fayolle et al. 2017).

In this Letter, we present the first interstellar detection of HONO. Further constraints on the nitrogen oxide chemistry towards IRAS 16293 are given, and a first attempt is made at modelling the HONO formation network.

2. Observations and analysis

Data from the Protostellar Interferometric Line Survey (PILS) of the low-mass protobinary IRAS 16293 were used to search for nitrogen oxides. This survey, taken with the Atacama Large Millimeter/submillimeter Array (ALMA), is fully described in Jørgensen et al. (2016). A short overview is given in this section. The survey covers part of Band 7 in the spectral range 329.147–362.896 GHz, at a spectral resolution of 0.2 km s−1, and with a sensitivity of 6–10 mJy beam−1 channel−1 (i.e. 4–5 mJy beam−1 km s−1). A circular restoring beam of was used to produce the final dataset. IRAS 16293 is a binary. HONO is identified towards source B, but not towards source A. Source B is analysed at a position offset by one beam with respect to the continuum peak position in the south-west direction (αJ2000 = 16h32m, δJ2000 = −24°28′32.8″). The very narrow line widths (1 km s−1) at this position limit line blending and facilitate easier identification of molecules (e.g. Lykke et al. 2017).

To analyse the spectra and identify the HONO lines, the CASSIS line analysis software1, as well as the Jet Propulsion Laboratory (JPL2) spectroscopic database (Pickett et al. 1998) and the Cologne Database for Molecular Spectroscopy (CDMS3; Müller et al. 2001, 2005) were used. The spectroscopy of HONO available in the JPL database was studied by Guilmot et al. (1993a,b) and Dehayem-Kamadjeu et al. (2005). HONO has two different conformers, trans and cis. The JPL entry assumes that the isomers are in thermal equilibrium. The trans/cis energy difference (130.2 cm−1) is from Varma & Curl (1976). Since the spectra of IRAS 16293 are very line-rich, a careful check was performed to exclude blended or partially blended lines. To achieve this, we compared all lines tentatively identified as HONO with a template containing the lines of the molecules previously detected in this source (see Appendix A). Similar to previous PILS studies (e.g. Ligterink et al. 2018), the observed spectra were fitted with a synthetic spectrum, assuming local thermodynamic equilibrium (LTE) conditions, using a source size of and a VLSR velocity of 2.5 km s−1. As the line emission is coupled with dust emission in IRAS 16293, a correction to the background temperature (TBG = 21 K) was applied (see also Calcutt et al. 2018; Ligterink et al. 2018). A χ2 minimisation routine was employed to find the best-fit model to the observed data and derive the column density (N) and excitation temperature (Tex; see also Lykke et al. 2017; Calcutt et al. 2018; Ligterink et al. 2018). The grid covers excitation temperatures between 50 and 300 K with steps of 25 K. After a first estimate of the column density, the grid was refined between 5 × 1014 and 3 × 1015 cm−2 with a step of 1 × 1014 cm−2. To avoid any bias in the determination of the best-fit model with the χ2 calculation, we included some undetected transitions (333925.02, 348264.91, and 358979.13 MHz) that are predicted to be above the noise limit for certain models in the grid.

3. Observational results

In total, we found 12 lines that could be identified as (trans-) HONO, which are not blended with any known species (see Fig. 1 and Table A.1). The intensities of nine out of these lines are higher or equal to 5σ. Two lines are 3 or 4σ detections and one is a marginal (2σ) detection. The best-fit model is obtained for an excitation temperature of 100 K and a column density of 9 × 1014 cm−2. The column density is not very sensitive to the excitation temperature. For a fixed excitation temperature of 300 K, which is derived for several complex organic molecules (see Jørgensen et al. 2018), the best-fit column density is 1.4 × 1015 cm−2, i.e. only 50% larger. Nevertheless, the model at 300 K overproduces some undetected lines at 333925.02, 348264.91, and 358979.13 MHz (Table A.2) and does not properly reproduce the line at 353468.14 MHz. The model at 300 K however better reproduces the line at 329519.48 MHz than the model at 100 K (see Fig. 1). The best-fit excitation temperature of 100 K is consistent with the excitation temperature obtained for the other nitrogen oxides, especially NO (Ligterink et al. 2018). Three lines (329519.48, 329685.92, and 355001.15 GHz) have their fluxes underproduced by the best-fit model and could be blended with unknown species, although the first line is only detected at 3σ. Alternatively, it could be that for molecules with low-frequency vibrational modes such as HONO, the excitation does not need to be in LTE, but there could be infrared pumping for selected lines.

thumbnail Fig. 1.

Lines of HONO observed towards the protostar IRAS 16293 B (in black). The first 12 lines are the identified lines of HONO in the ALMA-PILS band 7 survey. On the last row, the first 3 lines correspond to the undetected transitions that are used to constrain the best-fit model and the last two lines are those identified in other ALMA data (see Sect. 3 for more details). The 3σ limit is indicated by a dotted line. The best-fit model with Tex = 100 K is shown in blue, while the model in red corresponds to a higher Tex of 300 K. The spectrum at 93 GHz is extracted at the continuum peak position, given the lower spatial resolution of the data. The column density was multiplied by a factor 2 to take this difference into account (Jørgensen et al. 2016). The upper energy level is indicated in green in the bottom left corner of each panel.

Lines of HONO were also searched towards other high sensitivity ALMA observations of the low-mass protostar IRAS 16293. One line is present at 93008.6 MHz in the lower spatial resolution data of the ALMA-PILS observations carried out in band 3 (Jørgensen et al. 2016, see Fig. 1). None are present in the band 6 data. According to our calculations, one HONO transition at 236131.076 MHz should also be observed in the ALMA data presented in Taquet et al. (2018) with an intensity of 7 mJy for a similar spatial resolution of . An unidentified line is present at the same frequency, but its intensity is a factor 3 higher, which could mean that the observed line is blended with another species (see Fig. 1).

Maps of HONO (see Fig. 2) show that the emission is very compact around IRAS 16293 B, similar to the majority of the molecules detected in this source, especially the complex organic molecules (see e.g. Coutens et al. 2016, 2018; Lykke et al. 2017) and NO (Ligterink et al. 2018).

thumbnail Fig. 2.

Integrated intensity maps of two transitions of HONO towards IRAS 16293 B. The position of the continuum peak is indicated with a red triangle, while the position analysed for IRAS 16293 B (full-beam offset) is indicated with a red circle. The beam size is indicated in grey in the bottom right corner. Left panel: contours are 5, 10, 15, and 20σ. Right panel: contour levels are 3, 6, and 9σ.

Four other nitrogen-oxides, nitrosyl hydride (HNO), nitrosyl cation (NO+), nitrogen dioxide (NO2), and nitric acid (HNO3) were searched for, but not identified (see Appendix B for details). Table 1 gives an overview of the derived column densities of the detected and unidentified species (upper limits) towards IRAS 16293 B and includes results on NO, N2O, and NH2OH from Ligterink et al. (2018).

Table 1.

Column densities at the one beam offset position of IRAS 16293 B from the ALMA-PILS data.

4. Chemical modelling of HONO

To describe HONO and other NxOyHz species, we updated the gas and grain chemical network used in Loison et al. (2019, and references therein) introducing various species such as HONO, s-HONO, s-HNO2, s-NH2O, s-HNOH, NH2OH, s-NH2OH, s-NO3, s-HNO3, and s-H3NO2 (s- indicates species on grains). The reactions involving HONO are summarised in Table C.1 (we do not present the full network in this Letter). The chemistry of HONO is well described for Earth atmosphere chemistry where it is produced through the barrierless three body OH + NO + M reaction (Forster et al. 1995; Atkinson et al. 2004). However, this reaction is inefficient at the low densities of interstellar clouds and the radiative rate constant is negligible because of the small size of the system. All other known gas-phase reactions producing HONO have negligible rates in the ISM. In our model, HONO is therefore produced on grains through s-O + s-HNO, s-H + s-NO2, and s-OH + s-NO surface reactions, all of which are barrierless in the gas phase (Inomata & Washida 1999; Du et al. 2004; Michael et al. 1979; Nguyen et al. 1998; Su et al. 2002; Forster et al. 1995; Atkinson et al. 2004).

This network was then used with the Nautilus gas-grain model (Ruaud et al. 2016), which computes the gas and grain chemistry. The chemical modelling was carried out in two steps as in similar previous studies of IRAS 16293 (see for instance Andron et al. 2018): a cold core phase (a gas and dust temperature of 10 K, atomic H density of 104 cm−3, visual extinction (AV) of 15, and cosmic-ray ionisation rate of 1.3 × 10−17 s−1) during 106 yr followed by a collapse phase. For the collapse, we used the physical structure derived from a 1D radiative hydrodynamical model (see Aikawa et al. 2008) for parcels of material collapsing towards the central star. For these simulations, we used these parcels arriving at 62.4 au at the end of the simulations (see Fig. 5 of Aikawa et al. 2008). The resulting abundance ratios at this radius at the end of the simulation are presented in Table 2.

Table 2.

Abundances of HONO derived in IRAS 16293 B and with the chemical model.

In our model, HONO is essentially formed during the cold core phase. The final HONO/CH3OH ratio predicted by the model is close to the observed value within a factor of 2. The model ratios HONO/N2O and HONO/NO2 are also in agreement with the observed upper and lower limits, respectively. However, our model produces too little NO and too much HNO at high temperatures in the gas phase, resulting in a HONO/NO ratio much larger and a HONO/HNO ratio much smaller than the respective observed values. In our model, most of the NO reacts on grains with other radicals such as s-NH, when the temperature increases and NO becomes mobile. An explanation for the large NO/HNO ratio observed in IRAS 16923 B could be that thermal desorption of s-HNO mainly results in its destruction to NO, owing to the weak H-NO bond of HNO (2.02 eV; Dixon 1996), as the formation of s-HNO is very likely due to the absence of a barrier for the s-H + s-NO reaction (Tsang & Herron 1991; Nguyen et al. 2004; Washida et al. 1978; Glarborg et al. 1998). It should be noted that our model, as well as other published models, overproduce the abundance of NH2OH, which has so far not been detected in the ISM (Pulliam et al. 2012; McGuire et al. 2015; Ligterink et al. 2018). It has been suggested that NH2OH cannot desorb without destruction by Jonusas & Krim (2016), although this is in contradiction with the laboratory experiments of Congiu et al. (2012). Despite their differences, both experimental studies used very similar Temperature Programmed Desorption (TPD) set-ups and new experiments are therefore clearly needed to address these discrepancies. Other processes such as UV photodestruction of these species in ices could also explain the discrepancy between the model and observations (Fedoseev et al. 2016). In addition, the chemical network on grains and in the gas phase may not be fully relevant at protostellar temperatures. Some reactions with barriers, absent from the current network, may be significant.

5. Conclusions

We report the first detection of HONO in the ISM. This molecule, which is known to play a major role in the atmosphere of our planet, was found with ALMA towards the well-studied solar-type protostar IRAS 16293 B. This discovery complements the recent detection of N2O in the same source (Ligterink et al. 2018) and expands our knowledge of the chemical network of nitrogen oxides. Our updated model allows the abundances of HONO, N2O, and NO2 to be reproduced satisfactorily, but not those of NO, HNO, and NH2OH. One reason could be that HNO and NH2OH are destroyed upon thermal desorption, an occurrence which deserves to be experimentally studied in detail. Other explanations could be that they are destroyed by UV photons in ices or that some grain surface or gas-phase reactions, potentially relevant at protostellar temperatures, are missing from the network.

1

CASSIS has been developed by IRAP-UPS/CNRS (http://cassis.irap.omp.eu/)

Acknowledgments

This paper makes use of the ALMA data ADS/JAO.ALMA#2013.1.00278.S. ALMA is a partnership of ESO (representing its member states), NSF (USA) and NINS (Japan), together with NRC (Canada) and NSC and ASIAA (Taiwan), in cooperation with the Republic of Chile. The Joint ALMA Observatory is operated by ESO, AUI/NRAO, and NAOJ. A.C. postdoctoral grant is funded by the ERC Starting Grant 3DICE (grant agreement 336474). V.W. and J.-C.L. acknowledge the CNRS programme Physique et Chimie du Milieu Interstellaire (PCMI) co-funded by the Centre National d’Etudes Spatiales (CNES). M.N.D. acknowledges the financial support of the SNSF Ambizione grant 180079, the Center for Space and Habitability (CSH) Fellowship and the IAU Gruber Foundation Fellowship. J.K.J. acknowledges support from ERC Consolidator Grant “S4F” (grant agreement 646908). Research at the Centre for Star and Planet Formation is funded by the Danish National Research Foundation.

References

  1. Aikawa, Y., Wakelam, V., Garrod, R. T., & Herbst, E. 2008, ApJ, 674, 984 [NASA ADS] [CrossRef] [Google Scholar]
  2. Andron, I., Gratier, P., Majumdar, L., et al. 2018, MNRAS, 481, 5651 [NASA ADS] [CrossRef] [Google Scholar]
  3. Atkinson, R., Baulch, D. L., Cox, R. A., et al. 2004, Atmos. Chem. Phys., 4, 1461 [NASA ADS] [CrossRef] [Google Scholar]
  4. Burkholder, J. B., Mellouki, A., Talukdar, R., & Ravishankara, A. 1992, Int. J. Chem. Kinet., 24, 711 [CrossRef] [Google Scholar]
  5. Calcutt, H., Fiechter, M. R., Willis, E. R., et al. 2018, A&A, 617, A95 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  6. Caux, E., Kahane, C., Castets, A., et al. 2011, A&A, 532, A23 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  7. Cazaux, S., Tielens, A. G. G. M., Ceccarelli, C., et al. 2003, ApJ, 593, L51 [NASA ADS] [CrossRef] [Google Scholar]
  8. Codella, C., Viti, S., Lefloch, B., et al. 2018, MNRAS, 474, 5694 [NASA ADS] [CrossRef] [Google Scholar]
  9. Congiu, E., Fedoseev, G., Ioppolo, S., et al. 2012, ApJ, 750, L12 [NASA ADS] [CrossRef] [Google Scholar]
  10. Coutens, A., Jørgensen, J. K., van der Wiel, M. H. D., et al. 2016, A&A, 590, L6 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  11. Coutens, A., Willis, E. R., Garrod, R. T., et al. 2018, A&A, 612, A107 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  12. Cox, R., & Derwent, R. 1976, J. Photochem., 6, 23 [CrossRef] [Google Scholar]
  13. de Barros, A. L. F., da Silveira, E. F., Fulvio, D., Boduch, P., & Rothard, H. 2017, MNRAS, 465, 3281 [NASA ADS] [CrossRef] [Google Scholar]
  14. Dehayem-Kamadjeu, A., Pirali, O., Orphal, J., Kleiner, I., & Flaud, P.-M. 2005, J. Mol. Spectr., 234, 182 [NASA ADS] [CrossRef] [Google Scholar]
  15. Dixon, R. N. 1996, J. Chem. Phys., 104, 6905 [NASA ADS] [CrossRef] [Google Scholar]
  16. Du, B., Zhang, W., Feng, C., & Zhou, Z. 2004, J. Mol. Struct. THEOCHEM, 712, 101 [CrossRef] [Google Scholar]
  17. Dzib, S. A., Ortiz-León, G. N., Hernández-Gómez, A., et al. 2018, A&A, 614, A20 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  18. Fayolle, E. C., Öberg, K. I., Jørgensen, J. K., et al. 2017, Nat. Astron., 1, 703 [NASA ADS] [CrossRef] [Google Scholar]
  19. Fedoseev, G., Ioppolo, S., Lamberts, T., et al. 2012, J. Chem. Phys., 137, 054714 [NASA ADS] [CrossRef] [Google Scholar]
  20. Fedoseev, G., Chuang, K.-J., van Dishoeck, E. F., Ioppolo, S., & Linnartz, H. 2016, MNRAS, 460, 4297 [NASA ADS] [CrossRef] [Google Scholar]
  21. Florescu-Mitchell, A., & Mitchell, J. 2006, Phys. Rep., 430, 277 [NASA ADS] [CrossRef] [Google Scholar]
  22. Forster, R., Frost, M., Fulle, D., et al. 1995, J. Chem. Phys., 103, 2949 [NASA ADS] [CrossRef] [Google Scholar]
  23. Fournier, J. A., Shuman, N. S., Melko, J. J., Ard, S. G., & Viggiano, A. A. 2013, J. Chem. Phys., 138, 154201 [NASA ADS] [CrossRef] [Google Scholar]
  24. Geppert, W. D., Ehlerding, A., Hellberg, F., et al. 2004, ApJ, 613, 1302 [NASA ADS] [CrossRef] [Google Scholar]
  25. Glarborg, P., Østberg, M., Alzueta, M. U., Dam-Johansen, K., & Miller, J. A. 1998, Symp. (Int.) Combust., 27, 219 [CrossRef] [Google Scholar]
  26. Gligorovski, S. 2016, J. Photochem. Photobiol. A Chem., 314, 1 [CrossRef] [Google Scholar]
  27. Guilmot, J. M., Godefroid, M., & Herman, M. 1993a, J. Mol. Spectr., 160, 387 [NASA ADS] [CrossRef] [Google Scholar]
  28. Guilmot, J. M., Melen, F., & Herman, M. 1993b, J. Mol. Spectr., 160, 401 [NASA ADS] [CrossRef] [Google Scholar]
  29. Herbst, E., & Leung, C. M. 1986, ApJ, 310, 378 [NASA ADS] [CrossRef] [Google Scholar]
  30. Hsu, C.-C., Lin, M., Mebel, A., & Melius, C. 1997, J. Chem. Phys. A, 101, 60 [CrossRef] [Google Scholar]
  31. Inomata, S., & Washida, N. 1999, J. Phys. Chem. A, 103, 5023 [CrossRef] [Google Scholar]
  32. Jenkin, M., & Cox, R. 1987, Chem. Phys. Lett., 137, 548 [NASA ADS] [CrossRef] [Google Scholar]
  33. Jenkin, M., Cox, R., & Williams, D. 1988, Atmos. Environ., 22, 487 [NASA ADS] [CrossRef] [Google Scholar]
  34. Jonusas, M., & Krim, L. 2016, MNRAS, 459, 1977 [NASA ADS] [CrossRef] [Google Scholar]
  35. Jørgensen, J. K., Favre, C., Bisschop, S. E., et al. 2012, ApJ, 757, L4 [NASA ADS] [CrossRef] [Google Scholar]
  36. Jørgensen, J. K., van der Wiel, M. H. D., Coutens, A., et al. 2016, A&A, 595, A117 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  37. Jørgensen, J. K., Müller, H. S. P., Calcutt, H., et al. 2018, A&A, 620, A170 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  38. Joshi, P. R., Zins, E.-L., & Krim, L. 2012, MNRAS, 419, 1713 [NASA ADS] [CrossRef] [Google Scholar]
  39. Kahane, C., Ceccarelli, C., Faure, A., & Caux, E. 2013, ApJ, 763, L38 [Google Scholar]
  40. Lee, B. H., Wood, E. C., Herndon, S. C., et al. 2013, J. Geophys. Res. (Atmos.), 118, 12 [Google Scholar]
  41. Ligterink, N. F. W., Coutens, A., Kofman, V., et al. 2017, MNRAS, 469, 2219 [NASA ADS] [CrossRef] [Google Scholar]
  42. Ligterink, N. F. W., Calcutt, H., Coutens, A., et al. 2018, A&A, 619, A28 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  43. Liszt, H. S., & Turner, B. E. 1978, ApJ, 224, L73 [NASA ADS] [CrossRef] [Google Scholar]
  44. Loison, J.-C., Wakelam, V., Gratier, P., et al. 2019, MNRAS, in press [arXiv:1902.08840] [Google Scholar]
  45. Lykke, J. M., Coutens, A., Jørgensen, J. K., et al. 2017, A&A, 597, A53 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  46. Martín-Doménech, R., Rivilla, V. M., Jiménez-Serra, I., et al. 2017, MNRAS, 469, 2230 [NASA ADS] [CrossRef] [Google Scholar]
  47. McGonagle, D., Ziurys, L. M., Irvine, W. M., & Minh, Y. C. 1990, ApJ, 359, 121 [NASA ADS] [CrossRef] [Google Scholar]
  48. McGuire, B. A., Carroll, P. B., Dollhopf, N. M., et al. 2015, ApJ, 812, 76 [NASA ADS] [CrossRef] [Google Scholar]
  49. Michael, J. V., Nava, D. F., Payne, W. A., Lee, J. H., & Stief, L. J. 1979, J. Phys. Chem., 83, 2818 [CrossRef] [Google Scholar]
  50. Müller, H. S. P., Thorwirth, S., Roth, D. A., & Winnewisser, G. 2001, A&A, 370, L49 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  51. Müller, H. S. P., Schlöder, F., Stutzki, J., & Winnewisser, G. 2005, J. Mol. Struct., 742, 215 [NASA ADS] [CrossRef] [Google Scholar]
  52. Nejad, L. A. M., Williams, D. A., & Charnley, S. B. 1990, MNRAS, 246, 183 [NASA ADS] [Google Scholar]
  53. Nguyen, M. T., Sumathi, R., Sengupta, D., & Peeters, J. 1998, Chem. Phys., 230, 1 [CrossRef] [Google Scholar]
  54. Nguyen, H., Zhang, S., Peeters, J., Truong, T., & Nguyen, M. 2004, Chem. Phys. Lett., 388, 94 [NASA ADS] [CrossRef] [Google Scholar]
  55. Pickett, H. M., Poynter, R. L., Cohen, E. A., et al. 1998, J. Quant. Spectr. Rad. Transf., 60, 883 [Google Scholar]
  56. Pineau des Forêts, G., Roueff, E., & Flower, D. R. 1990, MNRAS, 244, 668 [NASA ADS] [Google Scholar]
  57. Plessis, S., Carrasco, N., Dobrijevic, M., & Pernot, P. 2012, Icarus, 219, 254 [Google Scholar]
  58. Possanzini, M., Buttini, P., & Di Palo, V. 1988, Sci. Total Environ., 74, 111 [NASA ADS] [CrossRef] [Google Scholar]
  59. Pulliam, R. L., McGuire, B. A., & Remijan, A. J. 2012, ApJ, 751, 1 [NASA ADS] [CrossRef] [Google Scholar]
  60. Ren, X., Harder, H., Martinez, M., et al. 2003, Atoms. Environ., 37, 3639 [NASA ADS] [CrossRef] [Google Scholar]
  61. Ruaud, M., Wakelam, V., & Hersant, F. 2016, MNRAS, 459, 3756 [NASA ADS] [CrossRef] [Google Scholar]
  62. Snyder, L. E., Kuan, Y.-J., Ziurys, L. M., & Hollis, J. M. 1993, ApJ, 403, L17 [NASA ADS] [CrossRef] [Google Scholar]
  63. Su, M. C., Kumaran, S. S., Lim, K. P., et al. 2002, J. Phys. Chem. A, 106, 8261 [CrossRef] [Google Scholar]
  64. Taquet, V., van Dishoeck, E. F., Swayne, M., et al. 2018, A&A, 618, A11 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  65. Tsang, W., & Herron, J. 1991, J. Phys. Chem. Ref. Data, 20, 609 [NASA ADS] [CrossRef] [Google Scholar]
  66. van Dishoeck, E. F., Blake, G. A., Jansen, D. J., & Groesbeck, T. D. 1995, ApJ, 447, 760 [NASA ADS] [CrossRef] [Google Scholar]
  67. Varma, R., & Curl, R. F. 1976, J. Phys. Chem., 80, 402 [CrossRef] [Google Scholar]
  68. Visser, R., Doty, S. D., & van Dishoeck, E. F. 2011, A&A, 534, A132 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  69. Wakelam, V., Smith, I., Herbst, E., et al. 2010, Space Sci. Rev., 156, 13 [NASA ADS] [CrossRef] [Google Scholar]
  70. Wakelam, V., Herbst, E., Loison, J.-C., et al. 2012, ApJS, 199, 21 [NASA ADS] [CrossRef] [Google Scholar]
  71. Washida, N., Akimoto, H., & Okuda, M. 1978, J. Phys. Chem., 82, 2293 [CrossRef] [Google Scholar]
  72. Zhang, L., Wang, T., Zhang, Q., et al. 2016, J. Geophys. Res. (Atmos.), 121, 3645 [NASA ADS] [CrossRef] [Google Scholar]
  73. Ziurys, L. M., McGonagle, D., Minh, Y., & Irvine, W. M. 1991, ApJ, 373, 535 [NASA ADS] [CrossRef] [Google Scholar]
  74. Ziurys, L. M., Apponi, A. J., Hollis, J. M., & Snyder, L. E. 1994, ApJ, 436, L181 [NASA ADS] [CrossRef] [Google Scholar]

Appendix A: Lines of HONO

The detected HONO transitions that are not found to be blended with known species are listed in Table A.1. To check the potential blending of the HONO lines with other species, we defined a template based on the molecules previously identified in the ALMA-PILS survey. This template includes the following species (ranked by mass): CCH, HCN, HNC, H13CN, HC15N, DNC, CO, 13CO, C17O, H13C15N, CH2NH, NO, C18O, DCO+, H2CO, HDCO, , H2C17O, D2CO, H2C18O, CH3OH, CH2DOH, CH3OD, 13CH3OH, , H2S, , HDS, HD34S, c-C3H2, CH3CCH, CH3CN, CH3NC, NH2CN, H2CCO, 13CH3CN, , CH3C15N, CH2DCN, H2C13CO, , HDCCO, HNCO, CHD2CN, , NHDCN, CH3CHO, N2O, DNCO, HN13CO, CS, c-C2H4O, SiO, CH3CDO, 13CH3CHO, , C33S, NH2CHO, C34S, t-HCOOH, H2CS, , cis-NHDCHO, trans-NHDCHO, NH2CDO, CH3OCH3, C2H5OH, DCOOH, HCOOD, t-H13COOH, HDCS, a-CHCH2OH, a-13CH3CH2OH, a-CH3CH2OD, a-CH3CHDOH, a-a-CH2DCH2OH, a-s-CH2DCH2OH, 13CH3OCH3, a-CH2DOCH3, sym-CH2DOCH3, SO, C36S, CH3SH, CHCl, HC3N, , C2H3CN, C2H5CN, CH3NCO, CH3COCH3, C2H5CHO, CH3OCHO, CH2(OH)CHO, OCS, CH3COOH, O13CS, OC33S, CH2(OH)13CHO, 13CH2(OH)CHO, CH3O13CHO, CH2(OD)CHO, CHD(OH)CHO, CH2(OH)CDO, CH3OCDO, CH2DOCHO, CHD2OCHO, aGg’-(CH2OH)2, gGg’-(CH2OH)2, OC34S, 18OCS, CHD2OCHO, SO2, and 34SO2. Figure A.1 presents the HONO lines over a larger spectral range with the overlaid template model in green and the HONO model in red.

Table A.1.

List of the detected and unblended HONO transitions.

Table A.2.

List of the undetected HONO transitions used in the χ2 calculation.

thumbnail Fig. A.1.

Lines of HONO observed towards the protostar IRAS 16293 B over a larger spectral range. The HONO best-fit model is shown in red, while the template model used to check the potential blending of the lines is overlaid in green.

Appendix B: Upper limit determination of HNO, NO+, NO2, and HNO3

The molecules HNO, NO+, NO2, and HNO3 were searched for in the PILS data without success. Upper limit column densities of 3σ were determined for Tex = 100 K. When possible, line-free regions of the observed data, where transitions are expected, were used. For HNO, the 41, 3–31, 2 transition at 332106.6 MHz, which is close to the transition of an unidentified species, was used. For NO+, only the 3–2 transition at 357.564 GHz is covered in the PILS range. It is found to be blended with a line of ethylene glycol. We determined a conservative upper limit based on the total flux of this line. For NO2, the undetected transitions at 348062.5 and 348820.7 MHz were used. For HNO3, many undetected lines are covered in the spectral range of the PILS survey. The upper limit was derived based on the brightest lines predicted in line-free regions. At Tex = 100 K, this yields 3σ upper limit column densities of 3 × 1014, 2 × 1014, 2 × 1016, and 5 × 1014 cm−2 for HNO, NO+, NO2, and HNO3, respectively.

Appendix C: Chemical reactions for HONO

The reactions involving HONO are listed in Table C.1.

Table C.1.

Summary of the reactions involving HONO.

All Tables

Table 1.

Column densities at the one beam offset position of IRAS 16293 B from the ALMA-PILS data.

In the text
Table 2.

Abundances of HONO derived in IRAS 16293 B and with the chemical model.

In the text
Table A.1.

List of the detected and unblended HONO transitions.

In the text
Table A.2.

List of the undetected HONO transitions used in the χ2 calculation.

In the text
Table C.1.

Summary of the reactions involving HONO.

In the text

All Figures

thumbnail Fig. 1.

Lines of HONO observed towards the protostar IRAS 16293 B (in black). The first 12 lines are the identified lines of HONO in the ALMA-PILS band 7 survey. On the last row, the first 3 lines correspond to the undetected transitions that are used to constrain the best-fit model and the last two lines are those identified in other ALMA data (see Sect. 3 for more details). The 3σ limit is indicated by a dotted line. The best-fit model with Tex = 100 K is shown in blue, while the model in red corresponds to a higher Tex of 300 K. The spectrum at 93 GHz is extracted at the continuum peak position, given the lower spatial resolution of the data. The column density was multiplied by a factor 2 to take this difference into account (Jørgensen et al. 2016). The upper energy level is indicated in green in the bottom left corner of each panel.
In the text
thumbnail Fig. 2.

Integrated intensity maps of two transitions of HONO towards IRAS 16293 B. The position of the continuum peak is indicated with a red triangle, while the position analysed for IRAS 16293 B (full-beam offset) is indicated with a red circle. The beam size is indicated in grey in the bottom right corner. Left panel: contours are 5, 10, 15, and 20σ. Right panel: contour levels are 3, 6, and 9σ.
In the text
thumbnail Fig. A.1.

Lines of HONO observed towards the protostar IRAS 16293 B over a larger spectral range. The HONO best-fit model is shown in red, while the template model used to check the potential blending of the lines is overlaid in green.
In the text

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.