Average volume mixing ratio profile of ozone for established positive detections.

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Ozone at the top of the clouds

More recently, an analysis of SPICAV UV nadir dayside observations established an abundance of O3 around 10-20 ppbv at the cloud top (~70 km) at latitudes over 50° in the both hemispheres (Figure 2.4, Marcq et al., 2019). Those values correspond to the column ozone amount above the clouds of about 0.1-0.5 DU (Marcq et al., 2019) that is ~10 times less abundant than on Mars (Perrier et al., 2006), and ~103 times less than on the Earth.
The IPSL Venus GCM (Lebonnois et al., 2010) was able to predict the ozone formation spatially distributed at the cloud tops in correspondence with the SPICAV observations (Figure 2.4). It is linked to a circulation in Hadley cells which contributes to oxygen accumulation in the polar regions. Since the polar ozone layers are a consequence of dynamic processes, a 1D model was not able to reproduce this effect. The GCM indicates that the O3 layer formation is similar to a mechanism that was established for the Martian upper atmosphere (Montmessin and Lefèvre, 2013). But in the case of Venusian ozone, no obvious seasonal effect and/or temporal trend was noted.

Photochemistry: a review of atmospheric models for SO2 and O3

A study of the mesosphere holds the key of fundamental components of the main chemical cycles determining the current atmospheric content. The major position is occupied by carbon dioxide and sulphur dioxide cycles. The carbon dioxide is dominant on Venus that intensifies a role of the CO2 cycle in the mesosphere. The great issue of theoretical comprehension is the stability of the CO2 mixing ratio being equal to 0.965 (von Zahn et al., 1983). Main processes of the cycle are a photolysis of CO2 on the day side, a production of O2, and a recombination of CO and O2 with a formation of CO2. The mixing ratio of CO has been observed at 20-30 ppmv at 36 km (Pollack et al 1993). A theoretical estimation shows that photolysis should produce this amount of the gas in a short period, 50 ppmv demand about 200 years (McElroy et al., 1973). The large volume of CO2 and correspondingly low abundance of CO also coincide with the very small upper limit of oxygen in its ground state. The ground-state oxygen amount was obtained to be lower than 2 ppm above 60 km from observations of the mid-latitudinal region of Venus (Mills, 1999). This limit indicates that the production of CO2 is approximately balanced by its loss via photolysis. However, the existence of oxygen emission at 1.27 μm observed on Venus argues the fast formation of O2 in the ground state (Connes et al., 1979; Crisp et al., 1996). The reproduction of CO2 from CO and O2 is a slower process (Nair et al., 1994; Mills, 1998). Thus, the stability of CO2 requires another process different from a simple oxidation. There might be a net of catalytic reactions (Yung and DeMore, 1982), however, it is not evidently resolved which process is the general one.
The sulphur cycle drives the cloud formation of a thick sulphuric acid droplets layer enshrouding Venus globally. A central position in the net of reactions is occupied by the sulphur dioxide. SO2 is the third most abundant gas in the Venusian CO2-atmosphere (<150 ppm) after the dominant carbon dioxide at 96.5% and nitrogen (3.5%). Its oxidation is a primary process leading to a formation of the H2SO4 acid. The latter further condenses at the cool cloud tops region and descends until its evaporation and dissipation becomes prevailed. The resulting SO2 and H2O are transferred upward supplying the mesospheric SO2 content. Sulphur acid synthesis is a prevailing process independent of the local time, and it results in a sharp decrease of SO2 in the upper cloud layer (Figure 2.2).

The stellar occultation technique: retrieving the atmospheric composition from transmittance spectra

Stellar occultation occurs when a star is tracked through the atmosphere of a planet while a spacecraft is moving along its orbit. On board the spacecraft, an instrument is collecting a sequence of spectra of the stellar light partially absorbed by the atmospheric species while the star is rising or setting behind the planet (Figure 3.1A). It is an efficient way to study the vertical distribution of atmospheric absorbers such as gas molecules or aerosol particles. Venus has a very dense atmosphere and very opaque clouds. This makes the method of stellar occultation usable only for studying the atmosphere above them. Occultations can probe up to an altitude where absorption features in the spectrum are overwhelmed by signal noise (Figure 3.2). The line of sight (LOS) of the instrument gradually crosses layers of the atmosphere, sensing atmospheric gases with a varying density. Absorption by the upper haze particles is what eventually limits the depth of sounding. As a result, the UV stellar occultation technique is only effective in the upper mesosphere and the lower thermosphere. SPICAV starts to be sensitive above 83-85 km (pressure ~1 mbar) up to 145 km (pressure ~10-6 mbar) (Bertaux et al., 2007a) and allows one to study the vertical structure of the planet’s night-time atmosphere. On the dayside the scattered solar light does not allow one to observe weaker sources like stars. It should be noted that at the considered altitudes, atmospheric refraction can be neglected due to the low gas concentrations.

UV Signal considerations with SPICAV

Venus Express orbited around Venus from 2006 to December 2014. During a stellar occultation the SPICAV FOV is pointed to the star. The vertical step in one observation session varies from 1 to 8 km, depending on viewing geometry. A typical occultation lasts 30 minutes, during which a reference stellar spectrum is collected based on the average of the stellar spectra collected above 200 km. Observations cover all latitudes of the night side from 18:00 to 06:00.
Typical SPICAV data, like the one used in this work, is a sequence of observations where each acquisition consists of five individual UV spectra (corresponding to the five bins mentioned earlier. A raw (so-called Level 0) spectrum is a 408-spectel vector on values in ADU, where only 384 spectels contain an actual signal. Level 1 data are obtained after removing pixel dark current, also known as DC, whose pattern across the detector was estimated from dedicated technological observations (see next paragraphs). Level 1 also includes a correction for readout systematic, and cosmic ray outbreaks that contaminate nearby pixels. Also, to minimize bias in weak signals, pixel readout includes a fixed offset that is accounted for as well as other instrument artefacts.
The CCD of the SPICAV UV channel is characterized by an average DC of about 10-20 ADU per second while pixel dynamics is limited to 4095 ADU (12-bit conversion). DC increases with temperature at a rate specific to each pixel. However, this non-uniformity pattern of the DC is stable and has been monitored throughout the mission. Special observation sessions carried out at HT = 0, preventing any photo-event to reach the CCD, allowed one to collect only the dark signal (sum of DC and offset). Then, a DC non-uniformity (DCNU) model for the entire detector could be inferred by fitting the recorded dark signal with a linear law, such as: 𝐷𝐶𝑁𝑈𝑖𝑗=𝑆𝑑𝑎𝑟𝑘 𝑖∙𝑎𝑖𝑗+𝑏𝑖𝑗.

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Wavelength-to-pixel registration

To extract information on gas absorption from the measured spectra, it is necessary to perform a number of calibrations. First, raw data remains in analogue to digital units (ADU) and has no spectral registration. During the SPICAV UV ground-based calibrations, a parabolic law was determined describing the dependence of the wavelength (λ) on the pixel or spectel number (Npix), presented in Equation 2.10 (Villard, 2008). Under flight conditions, this dependence may shift by some value of Δλ, which had to be retrieved for each observation session. 𝜆(𝑁𝑝𝑖𝑥,Δ𝜆)=Δ𝜆+325.48−0.54596∙(𝑁𝑝𝑖𝑥+9)−4.9096∙10−6∙(𝑁𝑝𝑖𝑥+9)2 (2.10).
To solve this problem, each spectrum of a star measured above the dense layers of the atmosphere, i.e. unaffected by absorption, was aligned with our catalogue of UV stellar spectra, that is the International UV Explorer (IUE) dataset. The IUE operated at the near-Earth orbit in 1978–1996 (Boggess et al., 1978) and its channels covered wavelengths from 115 to 320 nm, which corresponds to the SPICAV UV range. The instrument spectral resolution reached 0.02 nm. During one occultation from tens to hundreds of spectra of stars were measured without distortion by atmospheric absorption depending on the duration of the session and the geometry of the observations. For each of these spectra, calibration is carried out individually, then for the entire session, the average value of the shift Δλ is found depending on 𝜆(𝑁𝑝𝑖𝑥,Δ𝜆).

Table of contents :

СONTENTS
ACKNOWLEDGMENTS
PURPOSE OF THE WORK
CHAPTER 1. Venus and its atmosphere
1.1. The Earth’s evil twin
1.2. A new view of Venus
1.3. History of observations
1.3.1. Venus space missions
1.3.2. Venus Express
1.3.3. Future missions
1.4. The surface of Venus
1.5. The atmosphere of Venus
1.5.1. Composition
1.5.2. Structure of the atmosphere
1.5.3. The cloud layer
1.5.4. Transparency windows
1.5.5. Mesosphere and atmospheric dynamics
1.6. The SPICAV instrument
1.6.1. Ultraviolet channel of the SPICAV spectrometer
1.6.2. Infrared channel of the SPICAV spectrometer
CHAPTER 2. Sulphur dioxide and ozone in the atmosphere of Venus
2.1. Overview of sulphur dioxide research
2.1.1. Temporal and spatial distributions of sulphur dioxide
2.1.2. Vertical profile of SO2 obtained by SPICAV/SOIR instrument on board Venus Express and ground based facilities in the mesosphere
2.2. Ozone in the atmosphere of Venus.
2.2.1. Discovery of ozone in the atmosphere
2.2.2. Ozone at the top of the clouds
2.3. Photochemistry: a review of atmospheric models for SO2 and O3
CHAPTER 3. Data processing of stellar occultation spectra
3.1. The stellar occultation technique: retrieving the atmospheric composition from transmittance spectra
3.2. Calibrations and stray light correction in the raw data.
3.2.1. Studied trace gases
3.2.2. UV Signal considerations with SPICAV
3.2.3. Estimation of errors in atmospheric transmission spectra.
3.2.4. Sources of an additional emission registered by the UV channel of SPICAV
3.2.4.1. Lyman-α emission
3.2.4.2. Airglow of nitric oxide
3.2.4.3. Solar radiance in the stellar occultation spectra
3.2.5. Wavelength- to-pixel registration
3.2.6. Spectral inversion
3.2.6.1. Cases of positive gas detection
3.2.6.2. Upper detection limits for two gases.
3.2.6.3. Chlorine oxide absorption band
3.2.7. Vertical inversion problem
3.2.8. Calibration influence on the spectral inversion
3.2.9. Stray light elimination technique
3.2.9.1. Method #1
3.2.9.2. Method #2
3.2.9.3. Comparison of methods
3.2.9.4. Atmospheric transmission and error bars estimation.
3.2.10. Altitude assignment
3.3. Summary
CHAPTER 4. Sulphur dioxide
4.1. CO2 and SO2 retrievals: from column abundances to profile and its variability.
4.1.1. Carbon dioxide distribution in the upper mesosphere and the lower thermosphere.
4.1.2. SO2 in the upper mesosphere
4.2. SO2 profiles: Comparison with data from previous studies.
4.3. Variations of SO2 mixing ratio
4.3.1. Short term variations
4.3.2. Long term variations of SO2 mixing ratio.
4.3.3. Diurnal variations of SO2
4.3.4.1. Local time and latitude distribution
4.3.4.2. Variations with a solar zenith angle
4.3.4.3. Establishing independence from topography
4.4. Discussion.
4.4.1 Rapid changes in the SO2 content
4.4.2. Global patterns in the SO2 behaviour
4.5. Summary
CHAPTER 5. Ozone
5.1. Ozone retrievals
5.1.1. The main feature of the ozone positive detections
5.2. Ozone positive detections distribution
5.2.1. Average volume mixing ratio profile of ozone for established positive detections.
5.2.2. Spatial variations of ozone positive detections
5.2.3. Temporal variations of ozone based on positive detections
5.3. Detection limits of ozone
5.4. Review of possible correlations with other chemical compounds
5.5. Comparative analysis of ozone layers in Earth, Mars and Venus atmospheres.
5.5.1. Ozone on the Earth
5.5.2. Ozone on Mars and Venus
5.6. Summary
CHAPTER 6. O2 (α1Δg) emission in the upper mesosphere
6.1. The infrared emissions in the night atmosphere
6.2. SPICAV observations of lower atmosphere thermal emission
6.3. Modelling of the night thermal emission
6.3.1. Direct model
6.3.2. Inverse problem
6.4. Mapping water vapour and aerosols and uncertainties
6.5. Map of oxygen airglow in the night mesosphere
6.6. Summary
CONCLUSION
PERSPECTIVES
LIST OF PUBLICATIONS
LIST OF CONFERENCES
ANNEX 1. Positive detections of SO2 presented individually
ANNEX 2. Positive detections of O3 presented individually
ANNEX 3. Parameters of stellar occultation sessions
ANNEX 4. Weighted mean
ANNEX 5. Estimation of an impact of diffrent stray light types
ANNEX 6. Résumé de la thèse en français
REFERENCES

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