Identification of carbon dioxide in an exoplanet atmosphere

Carbon dioxide (CO2) is a key chemical species that is found in a wide range of planetary atmospheres. In the context of exoplanets, CO2 is an indicator of the metal enrichment (that is, elements heavier than helium, also called ‘metallicity’)1–3, and thus the formation processes of the primary atmospheres of hot gas giants4–6. It is also one of the most promising species to detect in the secondary atmospheres of terrestrial exoplanets7–9. Previous photometric measurements of transiting planets with the Spitzer Space Telescope have given hints of the presence of CO2, but have not yielded definitive detections owing to the lack of unambiguous spectroscopic identification10–12. Here we present the detection of CO2 in the atmosphere of the gas giant exoplanet WASP-39b from transmission spectroscopy observations obtained with JWST as part of the Early Release Science programme13,14. The data used in this study span 3.0–5.5 micrometres in wavelength and show a prominent CO2 absorption feature at 4.3 micrometres (26-sigma significance). The overall spectrum is well matched by one-dimensional, ten-times solar metallicity models that assume radiative–convective–thermochemical equilibrium and have moderate cloud opacity. These models predict that the atmosphere should have water, carbon monoxide and hydrogen sulfide in addition to CO2, but little methane. Furthermore, we also tentatively detect a small absorption feature near 4.0 micrometres that is not reproduced by these models

Early Release Science of the exoplanetWASP-39b with JWST NIRISS

This is the author accepted manuscript. The final version is available from Nature Research via the DOI in this recordData Availability: The raw data from this study are publicly available via the Space Science Telescope Institute's Mikulski Archive for Space Telescopes (https://archive.stsci.edu/). The data which was used to create all of the figures in this manuscript are freely available on Zenodo and GitHub (Zenodo Link;https://github.com/afeinstein20/wasp39b_niriss_paper). All additional data is available upon request.Code Availability: The following are open-source pipelines written in Python that are available either through the Python Package Index (PyPI) or GitHub that were used throughout this work: Eureka! (https://github.com/kevin218/Eureka); nirHiss (https://github.com/afeinstein20/nirhiss); supreme-SPOON (https://github.com/radicamc/supreme-spoon); transitspectroscopy (https://github.com/nespinoza/transitspectroscopy/tree/dev); iraclis (https://github.com/uclexoplanets/Iraclis); juliet (https://github.com/nespinoza/juliet); chromatic (https://github.com/zkbt/chromatic); chromatic_fitting (https://github.com/catrionamurray/chromatic_fitting); ExoTiC-LD54, 121 (https://github.com/Exo-TiC/ExoTiC-LD); ExoTETHyS122 (https://github.com/uclexoplanets/ExoTETHyS); PICASO88,89 (https://github.com/natashabatalha/picaso); Virga94, 95 (https://github.com/natashabatalha/virga); CHIMERA (https://github.com/mrline/CHIMERA); PyMultiNest (https://github.com/JohannesBuchner/PyMultiNest); MultiNest (https://github.com/JohannesBuchner/MultiNest)The Saturn-mass exoplanet WASP-39b has been the subject of extensive efforts to determine its atmospheric properties using transmission spectroscopy. However, these efforts have been hampered by modelling degeneracies between composition and cloud properties that are caused by limited data quality. Here, we present the transmission spectrum of WASP-39 b obtained using the SOSS mode of the NIRISS instrument on JWST. This spectrum spans 0.6–2.8m in wavelength and reveals multiple water absorption bands, the potassium resonance doublet, and signatures of clouds. The precision and broad wavelength coverage of NIRISS-SOSS allows us to break model degeneracies between cloud properties and the atmospheric composition of WASP-39b, favouring a heavy element enhancement (“metallicity”) of ~10–30x the solar value, a sub-solar carbon-to-oxygen (C/O) ratio, and a solar-to-super-solar potassium-to-oxygen (K/O) ratio. The observations are also best explained by wavelength-dependent, non-gray clouds with inhomogeneous coverage of the planet’s terminator.Leverhulme TrustUK Research and Innovatio

Early Release Science of the exoplanet WASP-39b with JWST NIRSpec G395H

This is the author accepted manuscript. The final version is available from Nature Research via the DOI in this recordData Availability: The data used in this paper are associated with JWST program ERS 1366 (observation #4) and are available from the Mikulski Archive for Space Telescopes (https://mast.stsci.edu). Science data processing version (SDP_VER) 2022_2a generated the uncalibrated data that we downloaded from MAST. We used JWST Calibration Pipeline software version (CAL_VER) 1.5.3 with modifications described in the text. We used calibration reference data from context (CRDS_CTX) 0916, except as noted in the text. All the data and models presented in this publication can be found at 10.5281/zenodo.7185300.Code Availability: The codes used in this publication to extract, reduce and analyze the data are as follows; STScI JWST Calibration pipeline45 (https://github.com/spacetelescope/jwst), Eureka!53 (https://eurekadocs.readthedocs.io/en/latest/), ExoTiC-JEDI47 (https://github.com/ExoTiC/ExoTiC-JEDI), juliet71 (https://juliet.readthedocs.io/en/latest/), Tiberius15,49,50, transitspectroscopy51 (https://github.com/nespinoza/transitspectroscopy). In addition, these made use of batman65 (http://lkreidberg.github.io/batman/docs/html/index.html), celerite86 (https://celerite.readthedocs.io/en/stable/), chromatic (https://zkbt.github.io/chromatic/), Dynesty72 (https://dynesty.readthedocs.io/en/stable/index.html), emcee69 (https://emcee.readthedocs.io/en/stable/), exoplanet83 (https://docs.exoplanet.codes/en/latest/), ExoTEP75–77, ExoTHETyS79 (https://github.com/ucl-exoplanets/ExoTETHyS), ExoTiCISM57 (https://github.com/Exo-TiC/ExoTiC-ISM), ExoTiC-LD58 (https://exoticld.readthedocs.io/en/latest/), george68 (https://george.readthedocs.io/en/latest/) JAX82 (https://jax.readthedocs.io/en/latest/), LMFIT70 (https://lmfit.github.io/lmfit-py/), Pylightcurve78 (https://github.com/ucl-exoplanets/pylightcurve), Pymc3138 (https://docs.pymc.io/en/v3/index.html) and Starry84 (https://starry.readthedocs.io/en/latest/), each of which use the standard python libraries astropy139,140, matplotlib141, numpy142, pandas143, scipy64 and xarray144. The atmospheric models used to fit the data can be found at ATMO[Tremblin2015,Drummond2016,Goyal2018,Goyal2020]88–91, PHOENIX92–94, PICASO98,99 (https://natashabatalha.github.io/picaso/), Virga98,107 (https://natashabatalha.github.io/virga/), and gCMCRT115 (https://github.com/ELeeAstro/gCMCRT).Measuring the abundances of carbon and oxygen in exoplanet atmospheres is considered a crucial avenue for unlocking the formation and evolution of exoplanetary systems. Access to an exoplanet’s chemical inventory requires high precision observations, often inferred from individual molecular detections with low-resolution space-based and high-resolution ground-based facilities. Here we report the medium-resolution (R≈600) transmission spectrum of an exoplanet atmosphere between 3–5 μm covering multiple absorption features for the Saturn-mass exoplanet WASP-39b, obtained with JWST NIRSpec G395H. Our observations achieve 1.46× photon precision, providing an average transit depth uncertainty of 221 ppm per spectroscopic bin, and present minimal impacts from systematic effects. We detect significant absorption from CO2 (28.5σ ) and H2O (21.5σ ), and identify SO2 as the source of absorption at 4.1 μ m (4.8σ ). Best-fit atmospheric models range between 3× and 10× solar metallicity, with sub-solar to solar C/O ratios. These results, including the detection of SO2, underscore the importance of characterising the chemistry in exoplanet atmospheres, and showcase NIRSpec G395H as an excellent mode for time series observations over this critical wavelength range.Science and Technology Facilities Council (STFC)UKR

Identification of carbon dioxide in an exoplanet atmosphere

Carbon dioxide (CO2) is a key chemical species that is found in a wide range of planetary atmospheres. In the context of exoplanets, CO2 is an indicator of the metal enrichment (that is, elements heavier than helium, also called ‘metallicity’), and thus the formation processes of the primary atmospheres of hot gas giants. It is also one of the most promising species to detect in the secondary atmospheres of terrestrial exoplanets. Previous photometric measurements of transiting planets with the Spitzer Space Telescope have given hints of the presence of CO2, but have not yielded definitive detections owing to the lack of unambiguous spectroscopic identification. Here we present the detection of CO2 in the atmosphere of the gas giant exoplanet WASP-39b from transmission spectroscopy observations obtained with JWST as part of the Early Release Science programme. The data used in this study span 3.0–5.5 micrometres in wavelength and show a prominent CO2 absorption feature at 4.3 micrometres (26-sigma significance). The overall spectrum is well matched by one-dimensional, ten-times solar metallicity models that assume radiative–convective–thermochemical equilibrium and have moderate cloud opacity. These models predict that the atmosphere should have water, carbon monoxide and hydrogen sulfide in addition to CO2, but little methane. Furthermore, we also tentatively detect a small absorption feature near 4.0 micrometres that is not reproduced by these models

Inhomogeneous terminators on the exoplanet WASP-39 b

This is the author accepted manuscript. The final version is available from Nature Research via the DOI in this recordData Availability: The raw data from this study is available as part of the Early Release Science Observations (ERS) via the Space Science Telescope Institute’s Mikulski Archive for Space Telescopes (https://archive.stsci.edu/). All the figures in this manuscript, along with the associated data and code to reproduce them, can be found at https://github.com/nespinoza/wasp39-terminators. Reduced data along with prior and posterior distributions for our wavelength-dependant catwoman (NE) light curve fits used to obtain the main results of this work can be found at https://stsci.box.com/s/rx7u56zviu3up2p8p34qh3btwop6lgl6. Reduced data along with prior and posterior distributions for our white-light light curve fit performed for WASP-39 b and described in the Methods section can be found at https://stsci.box.com/s/wet5xmacrk26ughr8y2j8wpyjdsumco1. Both datasets contain human-readable outputs, and are packaged to be explored using the juliet software library, which is publicly available at https://github.com/nespinoza/juliet.Code Availability: Light curves were fitted using juliet (https://github.com/nespinoza/juliet), batman (https://github.com/lkreidberg/batman), catwoman (https://github.com/KathrynJones1/catwoman) and Tiberius (https://github.com/JamesKirk11/ Tiberius), all of which are publicly available.Heising-Simons Foundatio

Recently developed GC/MS and LC/MS methods for determining NSAIDs in water samples

12 pages, 5 tables, 1 figure.-- PMID: 17203255 [PubMed].-- Printed version published Feb 2007.Pharmaceuticals have become major targets in environmental chemistry due to their presence in aquatic environments (following incomplete removal in wastewater treatment or point-source contaminations), threat to drinking water sources and concern about their possible effects to wildlife and humans. Recently several methods have been developed for the determination of drugs and their metabolites in the lower nanogram per litre range, most of them using solid-phase extraction (SPE) or solid-phase microextraction (SPME), derivatisation and finally gas chromatography mass spectrometry (GC-MS), gas chromatography tandem mass spectrometry (GC-MS/MS) and liquid chromatography electrospray tandem mass spectrometry (LC-ES/MS/MS). Due to the elevated polarity of non-steroidal anti-inflamatory drugs (NSAIDs), analytical techniques based on either liquid chromatography coupled to mass spectrometry (LC-MS) and gas chromatography coupled to mass spectrometry (GC-MS) after a previous derivatisation step are essential. The most advanced aspects of current GC-MS, GC-MS/MS and LC-MS/MS methodologies for NSAID analysis are presented.This work has been supported by the EU through the project NORMAN (Contract No. 018486). Marinella Farré thanks the support from the Ministerio de Educación y Ciencia through the Juan de la Cierva program.Peer reviewe

Early release science of the exoplanet WASP-39b with JWST NIRCam

This is the author accepted manuscriptData Availability: The data used in this paper are associated with JWST program ERS 1366 (observation #2) and are available from the Mikulski Archive for Space Telescopes (https://mast.stsci.edu). We used calibration data from program 1076. All the data and models presented in this publication can be found at https://doi.10.5281/zenodo.7101283.Code Availability: The codes used in this publication to extract, reduce and analyse the data are as follows: Batman, emcee, Eureka!, jwst, chromatic, chromatic-fitting, PyMC359, Exoplanet, gCMCRT, CONAN, ExoTiC-LD, LACOSMIC, PICASO, Virga, VULCANMeasuring the metallicity and carbon-to-oxygen (C/O) ratio in exoplanet atmospheres is a fundamental step towards constraining the dominant chemical processes at work and, if in equilibrium, revealing planet formation histories. Transmission spectroscopy provides the necessary means by constraining the abundances of oxygen- and carbon-bearing species; however, this requires broad wavelength coverage, moderate spectral resolution, and high precision that, together, are not achievable with previous observatories. Now that JWST has commenced science operations, we are able to observe exoplanets at previously uncharted wavelengths and spectral resolutions. Here we report time-series observations of the transiting exoplanet WASP-39b using JWST’s Near InfraRed Camera (NIRCam). The long-wavelength spectroscopic and short-wavelength photometric light curves span 2.0 – 4.0 µm, exhibit minimal systematics, and reveal well-defined molecular absorption features in the planet’s spectrum. Specifically, we detect gaseous H O in the atmosphere and place an upper limit on the abundance of CH . The otherwise prominent CO feature at 2.8 µm is largely masked by H O. The best-fit chemical equilibrium models favour an atmospheric metallicity of 1–100× solar (i.e., an enrichment of elements heavier than helium relative to the Sun) and a sub-stellar carbon-to-oxygen (C/O) ratio. The inferred high metallicity and low C/O ratio may indicate significant accretion of solid materials during planet formation or disequilibrium processes in the upper atmosphere.UK Research and InnovationInstitute of PhysicsLeverhulme TrustScience and Technology Facilities Counci

Early Release Science of the exoplanet WASP-39b with JWST NIRSpec PRISM.

Transmission spectroscopy1-3 of exoplanets has revealed signatures of water vapour, aerosols and alkali metals in a few dozen exoplanet atmospheres4,5. However, these previous inferences with the Hubble and Spitzer Space Telescopes were hindered by the observations' relatively narrow wavelength range and spectral resolving power, which precluded the unambiguous identification of other chemical species-in particular the primary carbon-bearing molecules6,7. Here we report a broad-wavelength 0.5-5.5 µm atmospheric transmission spectrum of WASP-39b8, a 1,200 K, roughly Saturn-mass, Jupiter-radius exoplanet, measured with the JWST NIRSpec's PRISM mode9 as part of the JWST Transiting Exoplanet Community Early Release Science Team Program10-12. We robustly detect several chemical species at high significance, including Na (19σ), H2O (33σ), CO2 (28σ) and CO (7σ). The non-detection of CH4, combined with a strong CO2 feature, favours atmospheric models with a super-solar atmospheric metallicity. An unanticipated absorption feature at 4 µm is best explained by SO2 (2.7σ), which could be a tracer of atmospheric photochemistry. These observations demonstrate JWST's sensitivity to a rich diversity of exoplanet compositions and chemical processes