Spatially Resolved Spectroscopy of Io's Pele Plume and SO2 Atmosphere

Icarus 146, 476–493 (2000) doi:10.1006/icar.1999.6412, available online at http://www.idealibrary.com on

Spatially Resolved Spectroscopy of Io’s Pele Plume and SO2 Atmosphere Melissa A. McGrath Space Telescope Science Institute, 3700 San Martin Drive, Baltimore, Maryland 21218 E-mail: [email protected]

Michael J. S. Belton National Optical Astronomy Observatories, Tucson, Arizona

John R. Spencer Lowell Observatory, Flagstaff, Arizona

and Paola Sartoretti Institute d’Astrophysique, Paris, France Received August 5, 1999; revised February 11, 2000

We report on the first successful, spatially resolved spectroscopic observations of Io’s SO2 atmosphere. Observations made with the Hubble Space Telescope Faint Object Spectrograph on 1 August 1996 using the 0.2600 aperture have provided detections of SO2 gas in absorption in three locations on the Io disk: the Pele volcano, the Ra volcano, and T3 (a control region at latitude 45◦ S, longitude 300◦ W). The column densities of SO2 at these three locations have been determined by best-fit models of the geometric albedo and vary by a factor of five, with N SO2 = 3.25 × 1016 , 1.5 × 1016 , and 7 × 1015 cm−2 for Pele, Ra, and T3, respectively. Thus, SO2 gas is found to be present, and collisionally “thick” (N & 6 × 1014 cm−2 ), in all three locations. The factor of five difference in column densities among the three targets provides the first direct evidence that the Io atmosphere is spatially inhomogeneous. Models of the SO2 gas band absorption at different temperatures give best-fit models with temperatures of T = 280 (Pele), 150 (Ra), and 200 K (T3). Addition of SO to the models in the amounts NSO ∼ 2.5 × 1015 (Pele), 5 × 1014 (Ra), and 1.5 × 1015 cm−2 (T3) provides improved (χ2 ) fits to the data for all three locations and gives reasonably good agreement with the previous detection of SO in the Io atmosphere at an abundance ∼0.1 times that of SO2 . We set an upper limit of 2 × 1014 cm−2 on the abundance of CS2 . Observations with the HST WFPC2 obtained on 24 July 1996, 7 days earlier than our FOS spectra, showed an active plume over the Pele volcano. If Pele was still active on 1 August, our results imply that the regions of highest SO2 gas density on Io may be associated with active volcanic plumes and not sublimation from the visibly bright SO2 frost patches common on the surface of the satellite. As a result of the positive detection ˚ multiplet from two of atomic sulfur emission from the SI] 1900 A of our three targets (∼3.6 kR, Pele; ∼1.6 kR, T3; <1.5 kR, Ra) our spectra also provide the first concurrent measurements of S, SO, and

SO2 gases in the atmosphere and give a ratio of S/SO2 abundance of ∼0.003–0.007. The SO2 distribution we observe falls off much more slowly with latitude than the best available sublimation atmosphere models, but matches well the latitudinal distribution of the more realistic sublimation-driven atmosphere models that include hydrodynamic flow and photochemistry. °c 2000 Academic Press Key Words: atmospheres, structure; abundances, atmospheres; Io; satellites of Jupiter.

1. INTRODUCTION

A fundamental scientific problem in studies of the jovian satellite Io concerns the spatial distribution, dynamics, and composition of its tenuous (Psurf < few nanobars) neutral atmosphere which lies as a reservoir between volcanic and sublimation– condensation sources of volatiles at the surface and the loss of exospheric atoms and molecules to the magnetosphere and torus. In this contribution we report on new spatially resolved Hubble Space Telescope (HST) spectroscopic observations of SO2 and S over Pele and two other regions of the surface that reveal lateral inhomogeneities in the neutral atmosphere. Sulfur dioxide (average column density ∼1016 /cm2 ) appears to be the primary atmospheric component on Io (cf., the comprehensive review by Lellouch (1996) of work done since the original discovery of gaseous SO2 by Pearl et al. (1979)). SO (Lellouch et al. 1996) has been positively detected at the ∼6% level, and stringent upper limits have been placed on the presence of other polar gases, e.g., CO and H2 S (Lellouch et al. 1992). Carbon- and nitrogen-bearing volatiles are not expected

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to be important because of the observed lack of appreciable amounts of C and N, and the dominance of S and O and their ions, in the torus and magnetosphere (Belcher 1983). Other volatiles that may be present at significant but uncertain levels, particularly in the vicinity of volcanic sources, include O, O2 , S2 O, and S. These result from a presently undetermined mix of the photochemical derivatives of SO2 (Summers and Strobel 1996, Wong and Johnson 1996), surface and upper atmospheric reactions (e.g., O2 ; Kumar and Hunten 1982), and gaseous effluents from discrete volcanic sources (e.g., McEwen and Soderblom 1983, Zolotov and Fegley 1998a, 1998b). Traces of Na, NaX , and K must also exist in the atmosphere to provide a source for their presence in the torus (Schneider et al. 1991). Until now most Earth-based atmospheric observations (Lellouch et al. 1992, 1996, Ballester et al. 1994 (hereafter B94), Trafton et al. 1996 (hereafter T96)) have been averages over the disk of the satellite and little has been learned from them of the details of the actual distribution of gas over the surface. However, indirect inferences from the contrast and width of microwave lines of SO2 (Lellouch et al. 1992), comparisons between UV and microwave spectra of SO2 (B94; Lellouch 1996), and the interpretation (unfortunately ambiguous) of brightness contrasts in spatially resolved, spectrally broadband, UV images (Sartoretti et al. 1994, 1996) have pointed to global scale spatial inhomogeneities in the atmosphere, possibly associated with major volcanic sources, in particular, around Pele. Voyager and Pioneer observations (Pearl et al. 1979, Kliore et al. 1975) of the distribution of SO2 surface frost (e.g., Howell et al. 1984) and subsequent theoretical investigations (e.g., Ingersoll 1989, Moreno et al. 1991, Wong and Johnson 1996) also point to strong density gradients over linear scales in excess of a few hundred km and a dynamic atmosphere near the surface. Surveys of the characteristics of volcanic plumes and observations of the properties of the surface surrounding their vents suggest significant differences in the relative amounts of S and SO2 issuing from volcanic sources (McEwen and Soderblom 1983) and a highly dynamic regime at the surface (Lee and Thomas 1980). Recent Galileo and HST observations of plumes and the discovery of unexpectedly high temperatures of volcanic source regions (Spencer et al.

1997b, McEwen et al. 1998) indicate, as predicted by Johnson et al. (1995), that many substantial volcanic sources may exist that have no visual expression in terms of a detectable plume carrying condensate aerosols. Galileo observations of diffuse atmospheric airglow (Geissler et al. 1999) show a ring of emission around the limb and global scale patchiness, which is perhaps due as much to a variation in excitation as to composition. Finally, a Galileo Ultraviolet Spectrometer (UVS) observation of ˚ (Hendrix et al. 1999) Io’s reflection spectrum from 2000–3200 A indicates the co-existence of regions of atmosphere with large (N > 1017 /cm−2 ) column densities of SO2 that differ by as much as 25 although these are not mapped out. An improved understanding of the spatial distribution clearly requires spatially resolved measurements with relatively high spectral resolution. To this end, and to shed light on the two specific questions of whether SO2 gas covers only a small fraction of Io’s surface and whether there is SO2 gas over Pele, we designed a set of spatially resolved HST spectroscopic measurements using a small aperture to point at three distinct locations on the satellite. We describe the observations and data reduction in Section 2, the details of the modeling in Section 3, and discuss the results in Section 4. 2. OBSERVATIONS AND DATA REDUCTION

We present results from an observation of Io made with the Hubble Space Telescope Faint Object Spectrograph (FOS) on 1 August 1996 using the 0.2600 circular aperture, the red detector, and the G190H grating which covers the spectral region ˚ at a dispersion of 1.45 A/diode. ˚ 1590–2312 A The FOS has a one-dimensional, linear diode array detector, with each diode subtending 0.300 × 1.300 parallel (X) and perpendicular (Y) to the dispersion direction, respectively, which is comparable to the size of the aperture in the dispersion direction. The entire observing sequence spanned seven HST orbits, with the first 1.75 orbits used to perform a multi-stage acquisition and peak-up on a small, visibly bright region on Io and the following ∼5.25 orbits used to obtain spectra of the three target regions. Basic information on the targets and exposures obtained are given in Table I.

TABLE I Observation Summary Exposure number y3cw0101 y3cw0102 y3cw0103 y3cwa101 y3cwb101-5 y3cwb106-8 y3cwb109-a a

Length (min)

Target

82 45 48.8

Acquisition bright spot Acquisition bright spot Acquisition bright spot Acquisition bright spot Pele UV bright spot (T3) Visible bright spot (Ra)

δ, α a (degrees)

Io CMLa (degrees)

θ, φ

17N, 222W

—

—

18S, 257W 45S, 300W 7S, 318W

274 303 319

−18, 107 −45, 93 −7, 91

δ, α: latitude, longitude; CML, central meridian longitude.

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The three target regions were chosen to reflect the different physical conditions on the surface which are expected to influence the SO2 atmospheric source rate. The Pele volcano was chosen because of indirect evidence that it is enshrouded by a relatively large column of SO2 gas (NSO2 & few × 1017 cm−2 ; Sartoretti et al. 1994, 1996, Spencer et al. 1997b). The other two target regions were chosen to be representative of an SO2 frost sublimation source, and a control region with neither a known active volcano nor visibly abundant surface frost deposits. Inferences about the physical characteristics of the target regions are based on their reflectivities in broadband images taken at ˚ (which we call UV) and λ ∼ 4500 A ˚ (which we λ ∼ 2850 A call visible) obtained from both Voyager and HST cameras. The three target regions were Pele (dark at both visible and UV wavelengths), Ra (bright at visible, dark at UV wavelengths, implying abundant SO2 frost), and a control region, which we call T3, at 45◦ S latitude, 300◦ W longitude (bright at UV, dark at visible wavelengths). Three visible wavelength images are shown in Fig. 1 with the FOS aperture superposed on the three target regions, illustrating the location and different reflectivities of the three. Very accurate pointing was crucial to the scientific goals of the program, since the apparent size of the Pele volcano (.0.300 ) is significantly smaller than the size of the Io disk (∼100 ). To obtain accurate pointing for such small targets superposed on a larger extended object, a multi-stage, peak-up acquisition of something much smaller than the Io disk must be performed. We note that blind offsets to a target like Pele after coarse acquisition of the Io disk with a large aperture, such as those done in earlier HST FOS programs, would have a small probability of acquiring the desired target region on Io due to the limited accuracy of such acquisition strategies. We therefore designed a time-consuming, four-stage acquisition and peak-up of a visibly bright region on Io at 17◦ N latitude, 222◦ W longitude which had a small apparent size because it was severely foreshortened due to its

location near the limb of the satellite. Given the very low flux ˚ wavelengths, the acquisition has from Io at UV (λ . 3000 A) ˚ and we chose grating G270H to be performed at λ & 3000 A, ˚ because we had WFPC2 and FOC images (λ ∼ 2275–3300 A) of Io corresponding to the approximate bandpass of this grating, so that accurate location, size, and flux (for estimating the correct exposure times) for the target regions could be estimated. Stage 1 of the acquisition is a coarse locate of the Io disk using the largest (3.6600 × 1.300 ) FOS aperture and is accomplished by taking three integrations in non-overlapping steps of the aperture across the initial blind pointing location in the Y direction, returning to the step with the highest number of counts. During Stage 1 Io was found in the center of the three steps. Successive stages of the peak-up map areas corresponding to the size of the aperture used in the previous stage of the acquisition and return to the brightest step in the mapped area. Stage 2 maps the 3.6600 (X direction) × 1.300 (Y direction) area of Stage 1 using the 0.900 round aperture with six overlapping steps in X and two in Y, which improves the pointing for the Io disk because the aperture size is matched to the size of the disk. Stage 3 uses the 0.2600 round aperture to map five overlapping steps in X and five in Y and is expected to acquire the brightest region on the disk, which is the bright acquisition target near the limb. Because the acquisition is constrained to occur when a particular longitude is at the central meridian, the location of the acquisition target relative to the Io disk is known, so the accuracy of this stage of the acquisition can be verified post facto. Stage 4 of the acquisition consists of stepping the 0.2600 aperture across this bright acquisition region in a much finer grid of highly overlapping steps (six in X, six in Y) to optimize centering of the acquisition target in the 0.2600 aperture, which is used for the subsequent science observations. After peak-up on the acquisition target, a small angle maneuver corresponding to the difference in location of the bright spot and the first science target (Pele) was performed. Although quite difficult and time-consuming,

a FIG. 1. Voyager violet filter images (λ ∼ 3200–5000 A ) of Io illustrating the location of the three target regions and the size of the FOS aperture (0.2600 ) used for the observations presented in this paper.

IO’S PELE PLUME AND SO2 ATMOSPHERE

post-facto analysis showed that the acquisition was very successful, with the acquisition target being found in the correct location (near the limb of the disk) in Stage 3. We are confident that accurate pointing to the three desired science targets was achieved for these observations. The FOS science observations were made in a standard fashion using the ACCUM mode, which accumulates photons continuously throughout the exposure. The standard FOS quarterstepping strategy was employed, which provides four spectral samples per diode, a technique used to provide optimal (Nyquist) sampling for point sources. For extended sources such as Io, this means the raw spectrum is slightly oversampled. We therefore rebin the raw data by a factor of four to increase the signal to noise ratio (S/N), which somewhat degrades the technically achievable spectral resolution. The data we use for analysis have one spectral sample per resolution element and are therefore ˚ The absolute fluxes have been converted sampled every 1.45 A. to geometric albedo in the usual manner (see, e.g., B94, Yelle and McGrath 1995, McGrath et al. 1998) using a UARS/Solstice solar spectrum (Rottman et al. 1993, Woods et al. 1993). A previous successful FOS detection of SO2 in disk-averaged measurements (B94) used the FOS blue detector and the 4.300 × 1.400 aperture. For our observations, given the small aperture size of 0.2600 which reduces the detected flux by a factor of ∼15 compared to the B94 observations, we chose instead to use the FOS red detector, which has the advantage of more than a factor of two higher quantum efficiency than the blue detector over the wavelength range of the G190H grating. This choice was crucial, since similar disk-resolved observations done in earlier HST programs using the blue detector (e.g., HST programs 4600 and 6316) have not resulted in positive detections of SO2 gas. However, both FOS configurations suffer from grating scattered light, a well-known, serious problem for FOS observations of late spectral-type targets such as solar system objects and latetype stars. It is caused by the non-solar-blind FOS detectors which have significant “red leak,” i.e., grating scatter of visible photons to shorter wavelengths, where they are detected in significant quantities particularly with the G130H and G190H gratings. This problem has been discussed extensively by many authors with regard to HST FOS observations (e.g., Blair et al. 1989, Kinney 1993, Yelle and McGrath 1995, McGrath et al. 1998). The number of anomalous scattered photons is directly proportional (at the 0.01–0.02% level) to the number of longer wavelength photons but unfortunately, as shown by the work of Blair et al., the measured scattered light from grating G190H with the red detector is not smoothly varying with wavelength like that from the blue detector, which causes an anomalous ˚ We use enhancement in the counts between ∼1900–2100 A. the measured Blair et al. scattering function to correct for the scattered light (see Fig. 2), as described in detail by McGrath et al. (1998). A more accurate correction is not feasible given the poorly known properties of the scattered light, especially for the red detector. After fairly extensive testing, we have found that it makes no difference to the physical quantities derived

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from the albedo because it is conveniently incorporated into the only free parameter in the modeling (see Section 3) and does not significantly affect the SO2 band contrast (see, e.g., Fig. 2a), which is the primary factor constraining the SO2 abundance and temperature determinations. We show the flux-calibrated spectrum with and without the correction for grating scattered light for one target, Pele, in Fig. 2a, and the corresponding geometric albedo in Fig. 2b. ˚ is seen in the Strong atomic sulfur emission at 1900 and 1914 A spectrum, and absorption bands due to SO2 are obvious even in the flux spectrum. An anomalous instrumental artifact (perhaps caused by grating scatter), seen previously in FOS spectra of extended objects (e.g., Yelle and McGrath 1995), is present at ˚ The quality of the data degrade toward shorter wave1935 A. lengths, where the detector sensitivity falls off rapidly. Due to ˚ the inthese several factors, SI emission at 1900 and 1914 A, ˚ and the lower S/N and increased strumental artifact at 1935 A, anomalous grating scatter contribution toward shorter wave˚ The lengths, we model the albedos only longward of 1975 A. geometric albedos for the three targets are shown in Fig. 3. They have also been smoothed with a 3-pt running boxcar routine before detailed modeling. Figure 3 shows the location of the peaks in the SO2 absorption cross section, which correspond closely to (non-solar) absorption features present in the flux spectra of all three targets. We emphasize the quality of these data by showing our Pele albedo overplotted on the earlier disk-averaged albedo of B94 (Fig. 4), which provided the first positive detection of SO2 gas absorption in the UV. The higher sensitivity of the red detector, the longer exposure time, and the smaller aperture size compared with the B94 observation combine to provide much higher spectral resolution of the SO2 bands and therefore increased contrast of the bands compared to the continuum. Also noticeable is the bluer ˚ compared with color of the Pele albedo shortward of ∼2050 A the B94 disk-averaged albedo, which is most likely due to the different scattered light properties of the two detectors discussed above. At all other wavelengths the measured albedos are in remarkably good agreement, both in the features present and in the absolute value of the albedo derived. 3. MODELING AND ANALYSIS

A first order analyses of the data can be made by inspection using simple ratios of the albedos. One of the biggest questions to be answered is whether Io’s SO2 atmosphere is spatially homogeneous or strongly affected by localized sources such as volcanos or localized frost patches. Recall that Pele is dark at both ˚ and visible wavelengths, Ra is bright in the near-UV (∼2850 A) visible and dark in the near-UV, and T3 is bright in the nearUV and dark in the visible. This is thought to imply that Ra has more optically thick SO2 frost than the other two targets since SO2 frost is bright at visible wavelengths, but dark at nearUV wavelengths (McEwen et al. 1988). Figure 5 shows the albedo ratios of Pele/Ra, Ra/Pele, Ra/T3, and Pele/T3. These

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FIG. 2. (a) The Pele flux spectrum without (top line) and with (bottom line)a the correction for grating scattered light discussed in the text. (b) The geometric albedo corresponding to the corrected flux spectrum of (a). The feature at 1935 A marked with an X is an instrumental artifact.

ratios make the following qualitative interpretations possible. (1) Pele is the darkest of the three targets in our spectral region, as evidenced by a ratio that is less than one in Figs. 5a and 5d, and T3 is the brightest. These color and brightness ratios are very similar to those obtained from the near-UV images at ˚ (2) SO2 gas is somewhat longer UV wavelength (∼2850 A). seemingly more abundant over Pele than the other two regions, as evidenced by the appearance of the SO2 bands in Figs. 5a and 5d and the appearance of features anti-correlated with the SO2 bands in Fig. 5b. However, given the different solar zenith angles (airmass) for the three targets, this conclusion has to be verified by detailed modeling of the three albedos. (3) The overall shape of the Ra/Pele ratio spectrum (Fig. 5b) matches well the reflectivity of SO2 frost, which we have overplotted on the ratio using the measured frost reflectance of Wagner et al. (1987).

3.1. Geometric Albedo Modeling Detailed modeling of the albedos has been performed in order to extract as much information as possible about the surface reflectance (and therefore surface composition), the SO2 frost abundance, and the SO2 and SO gas abundances from the data. The observed flux from Io consists of solar photons reflected from Io’s surface, photons which pass through Io’s atmosphere twice before reaching Earth. The geometric albedo ( p) is therefore a function of the surface reflectance (R), and the atmospheric transmission (t), p(λ, θ, φ, δ, α) = R(λ, δ, α) × t 2 (λ, θ, φ, N◦ (δ, α), T (δ, α)) cos θ sin2 φ, (1)

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FIG. 3. The geometric albedos for the three targets, Pele (top), Ra (middle), and T3 (bottom), are shown by the dark lines. Overplotted on each albedo are the error bars derived from propagated photon counting statistics which are used as weights (σi ) in the χ 2 fitting.

where N◦ is the vertical column density, T the vertically averaged temperature of the absorbing gas, and δ and α are latitude and longitude on the surface of Io. We use a spherical coordinate system with φ (the azimuthal angle) oriented parallel to Io longitude and θ oriented parallel to Io latitude. φ ranges from 0◦ to 180◦ and is equal to 90◦ at the subsolar point; θ ranges from −90◦ to +90◦ and is 0◦ at the subsolar point. While the phase angle is important for determining surface properties, it has virtually no effect on our determination of gas abundances, so we assume for simplicity 0◦ phase angle, which means that the sub-Earth and sub-solar points coincide at θ = 0◦ , φ = 90◦ , and the solar and Earth zenith angles are equal. For a particular

target, the relationship between the spherical coordinates (θ, φ) and latitude and longitude (δ, α) is then θ = |δ| φ = CML − α + 90◦ , where CML is the central meridian longitude of Io at the time of the observation. The average values of the parameters δ, α, θ, φ, and CML for each target are given in Table I. We assume zero limb-darkening for the surface reflectance, in agreement with Voyager and HST FOC imaging results (Simonelli and Ververka 1986, Sartoretti et al. 1994).

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FIG. 4. The geometric albedo of Pele compared with the disk-averaged geometric albedo of Io’s trailing hemisphere from B94, illustrating the improved SO2 band contrast obtained in the disk-resolved observations presented in this paper. The difference in the absolute value of the two albedos at shorter wavelengths is discussed in the text.

In the presence of absorbing gas in the atmosphere, the geometric albedo represents the competing effects of darkening due to varying surface reflectance and opacity due to the absorbing atmospheric gas. The goal of the observations is to derive information about the atmospheric gas abundance and temperature from the observed geometric albedo. Unfortunately, this process is not straightforward because the surface composition, and therefore the surface reflectance, is very poorly constrained, especially in the ultraviolet. Thus the geometric albedo effectively has three unknowns, R, N , and T , and their variation with both spatial location and wavelength are also unknown. For diskaveraged observations, p is integrated over 180◦ in both θ and φ, making it significantly more difficult to disentangle the actual spatial distribution of the gas. Spatially resolved observations mitigate the uncertainty introduced into the modeling by the spatial distribution variables (δ, α) because of the relatively small area of the aperture. Nevertheless, even for these small aperture observations, there is obvious variation of the reflectivity across the aperture (cf., Ra in Fig. 1) which we ignore. In an extreme case, if the aperture covered only regions with SO2 gas overlying a zero-reflectivity surface and regions with no SO2 gas overlying a perfectly reflecting surface, we could not detect the gas. Finally, the dependence of t on the solar zenith angle (airmass) must be accounted for and is accomplished by using the appropriate values of θ and φ for our targets in Eq. (1). 3.1.1. Surface reflectance. Based on analysis of multi-color, broadband images taken by the Voyager spacecraft cameras (McEwen et al. 1988), the general view of the surface material on Io has been that it consists of three major end members, only

one of which (SO2 frost) is positively identified. Component 2 is thought to be elemental sulfur, while component 3 is unknown. McEwen et al. derived the abundance and distribution of SO2 frost using an intimate mixing model and assuming that the grain sizes of SO2 and the other components on Io were the same as laboratory samples. Intimate mixing means that the photon mean free path is much longer than the scale of compositional change, and intimate mixtures may be strongly nonlinear with respect to the observed reflectivities. Mixtures that are linear with respect to the observed reflectivities follow what is called macroscopic mixing, which occurs when the mixing is on a scale larger than the optical path length. The SO2 frost grain size, and whether it is intimately or macroscopically mixed, both strongly affect its reflectance. Previous models of Io’s reflectance in the UV (Ballester et al. 1990, B94, Sartoretti et al. 1994) have assumed a small SO2 frost grain size, and that the SO2 is macroscopically mixed, and formulated the surface reflectance as R(λ, δ, α) = Rx (λ)X x (δ, α) + RSO2 (λ) X SO2 (δ, α),

(2)

where RSO2 is the reflectance of SO2 frost and X SO2 is its abundance, and the reflectances of possible components other than SO2 have been combined into a single effective reflectance parameter, Rx (λ), with a spatial distribution given by X x (δ, α) = 1.0 − X SO2 (δ, α). We choose instead to use a single parameter, R, for the surface reflectance for several reasons. First, there are no laboratory reflectance data available for possible candidates other than ˚ While the two measurements of RSO2 at SO2 below 2400 A.

IO’S PELE PLUME AND SO2 ATMOSPHERE

483

FIG. 5. Ratios of geometric albedos for (a) Pele/Ra, along with the stick diagram showing the locations of the SO2 absorption cross section peaks; (b) Ra/Pele, along with the measured reflectance of SO2 frost (Hapke et al. 1981); (c) Ra/T3; and (d) Pele/T3. A dashed line is shown at a ratio of unity to aid in interpretation of the ratios. The correlation ((a), (c), and (d)) and anti-correlation (b) of the structure in these ratios with the SO2 absorption band peaks illustrates qualitatively that the SO2 bands are the strongest at Pele. The relative values of the ratios show that Pele is the darkest and Ra the brightest of the three targets in this wavelength region, which is similar to the reflectivities of these three regions in somewhat longer-wavelength UV imaging observations (Sartoretti et al. 1996).

˚ by Hapke et al. (1981) and Wagner et al. (1987) are λ . 2400 A in reasonable agreement, they disagree in absolute value with the more detailed laboratory measurements by Nash et al. (1980) by approximately a factor of 5 (depending on the frost grain size ˚ The Hapke–Wagner results are therefore assumed) at 2400 A. generally scaled down to match the Nash et al. value. Second, the assumption of macroscopic mixing leads to a large discrepancy in the fractional coverage of SO2 frost (X SO2 in Eq. (2)) derived from UV (Nelson et al. 1986) and IR (Howell et al.

1984) measurements which is largely resolved when intimate mixing is assumed (McEwen et al. 1988). In past treatments the spatial distribution of SO2 frost, X SO2 (δ, α), has been taken to be the distribution of the brightest white plains regions obtained from the Voyager image reflectivity maps by McEwen et al. (1988), assuming that these white regions are 100% SO2 frost, although this is still undetermined (Nash et al. 1986). The SO2 frost abundance outside these white regions, at Pele for example, is generally quite low (.20%). However, recent results from

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the Galileo NIMS experiment (Carlson et al. 1997) have shown that SO2 frost is pervasive on the surface of Io, being present virtually everywhere. Their results show that the optically thick, white patches identified by McEwen et al. as 80–100% SO2 frost are actually regions of large-grained SO2 frost, whereas NIMS is sensitive to a much wider range of SO2 frost grain sizes. The regions of lower frost abundance in the McEwen et al. analysis in fact still contain abundant amounts of SO2 frost, but with smaller grain sizes. Unfortunately, quantitative abundance determinations useful in constraining X SO2 (δ, α) for a reflectance model are not yet available from the NIMS data. Given that RSO2 and X SO2 are both poorly known (thereby making X x poorly known), and the magnitude of this uncertainty has previously been absorbed into Rx , it does not make sense to use four poorly constrained parameters instead of one to characterize the surface reflectance. Unless the UV surface reflectance derived from the data is to be quantitatively analyzed, which has not been done in the past, using a single unknown (R) is simpler than using four equally unconstrained ones. In fact, it is important to note that in our models R is essentially a catchall and represents all low-frequency contributions (i.e., those that change slowly with wavelength) to the geometric albedo including the surface reflectance, residual instrumental scattered light contamination, and any additional low-frequency contributors to the atmospheric transmission function such as dust (see Spencer et al. 1997b and Section 4 for more on this point). Our determination of the SO2 gas abundance depends almost exclusively on reproducing the high-frequency component of the geometric albedo, i.e., the gas absorption bands. This also means that it is virtually impossible for us to identify broadband gaseous absorbers such as H2 S and OCS without a much better characterization of the actual surface reflectance, the instrumental uncertainties such as the scattered light, and the importance of dust. We therefore make no claim that R provides an accurate representation of the true surface reflectance, although it does provide some quantitative guidance to the actual value. It is taken as a free parameter in our modeling. A representative example of R vs wavelength determined from the χ 2 fitting is shown in Fig. 6B(b). The steep rise shortward of ˚ is very likely caused by residual instrumental scattered 2100 A light. 3.1.2. Atmospheric transmission function The atmospheric transmission function accounts for the opacity of the atmospheric gas overlying the surface, which is assumed to be dominated by absorption due to SO2 gas. The only other known constituents of the Io atmosphere are SO (∼0.1 × SO2 ; Lellouch et al. 1996), S, O (Ballester et al. 1987), Na (Brown 1974), and K (Trafton 1975). Of these minor constituents, only SO absorbs at UV wavelengths, and its UV absorption cross section closely resembles that of SO2 (Phillips 1981). We consider other plausible candidates as possible based on the availability of UV photoabsorption cross sections. The SO2 transmission can be determined exactly by performing a line-by-line integration of the transmission function,

FIG. 6A. (a) The χ 2 contour grid for NSO2 vs temperature showing that the best-fit model values are NSO2 = 3.25 × 1016 cm−2 and T = 280 K. (b) The best-fit SO2 only model overplotted on the data.

tν = exp(−σν N ), over frequency, where σν is the photoabsorption cross section and N is the SO2 column density. Unfortunately, as pointed out by Belton (1982), the SO2 absorption spectrum has a very complex structure consisting of many densely packed lines which have not been resolved in laboratory measurements, so that accurate line positions and spacings are not known. A line-by-line integration is therefore infeasible, and a band model is required in order to estimate the effects of line saturation on the band transmission. The best band model currently available for SO2 is by Ballester et al. (1994), who employ a Malkmus model developed by Goody and Yung (1989) for the band transmission. We use Eqs. (7), (8a), and (8b) from B94 for the atmospheric transmission tSO2 (λ, θ, φ, T, N◦ ) ¸¶ ·µ ¶1/2 µ 4σ¯ (λ, T ) N◦ π −1 = exp − y(λ) 1 + 2 π y(λ) cos θ sin φ µ tSO2 (λ, θ, φ, T, N◦ ) → exp −σ¯ (λ)

N◦ cos θ sin φ

¶

(3)

N◦ → 0 (optically thin limit; Beer’s law)

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sorption cross section with temperature. The principal features of this behavior are that the skewness of the bands changes significantly with temperature and that much higher band contrast occurs at lower temperature. We add one cautionary remark with regards to the B94 band model. Although the SO2 lines are expected to have Doppler profiles, as noted by B94 there are currently no closed expressions for band transmission using Doppler profiles that cover both short and long absorption paths (Goody and Yung 1989). On the other hand, Zhu (1988) derived several closed expressions for the band transmission using Voigt profiles. The B94 band model relies on the simplifying assumption that when there is significant line overlap, the distinction among Doppler, Voigt, and Lorentz profiles is insignificant and only the envelope of line clusters, rather than individual properties of the lines, needs to be accurately modeled. They therefore perform the modeling using a set of Lorentz line profiles whose expression for the band transmission is extremely simple when a Malkmus distribution is adopted for the line intensity distribution. For all other minor constituents, we assume Beer’s law because the nonlinear curve of growth effects are assumed to be negligible at the low column densities of these species, and random band models are not available. We use the SO cross section

FIG. 6B. Same as Fig. 6A for Ra, with best-fit values of NSO2 = 1.5 × 1016 cm−2 and T = 150 K.

µ · tSO2 (λ, θ, φ, T, N◦ ) → exp − π y(λ)σ¯ (λ)

N◦ cos θ sin φ

¸1/2 ¶

N◦ → ∞ (optically thick limit), where N◦ is the vertical column density, σ¯ is the mean cross section over relatively narrow spectral intervals corresponding to the sampling of the FOS data, and y is proportional to the ratio of the line half-width to the mean line spacing. B94 derived the parameters y and σ¯ using the high spectral resolution laboratory data of Freeman et al. (1984). They concluded that a pseudo-continuum is generated in the SO2 bands because of the considerable overlap among the closely packed rotational lines (y is generally >1), which prevents curve-of-growth effects from becoming important until σ¯ N◦ /y À 1. Over the wavelength region of interest in our FOS data, the B94 model has a mean y value of ∼15 and a maximum σ¯ of ∼10−17 , indicating column densities of N◦ > 1018 would be required. As discussed further below, this is about two orders of magnitude larger than the column densities we derive from our data. The temperature dependence of SO2 band absorption was also modeled by B94 using the Freeman et al. data and data from Martinez and Joens ˚ spectral resolution. Figure 7 (1992) obtained at 300 K with 1 A of B94 shows the behavior of the random band model SO2 ab-

FIG. 6C. Same as Fig. 6A for T3, with best-fit values of NSO2 = 7 × 1015 cm−2 and T = 200 K.

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from Phillips (1981) and the CS2 cross section from Wu and Judge (1981). 3.1.3. Least squares fitting technique and results. We calculate a model p as follows. First, since SO2 gas appears to be the dominant contributor to t, we initially calculate models using only SO2 gas. We calculate t 2 , using Eq. (3), for a grid of N◦ and T values. The only unknown in the model p (Eq. (1)) is then the surface reflectance, R, and its variation with wavelength. We determine R(λ) by minimizing χ2 =

N X (data(λi ) − model(λi ))2 i

σi2

˚ wavelength intervals (where σi are the errors in the data) in 30 A ˚ Acceptable over the spectral region of interest (1975–2300 A). fits require the reduced χ 2 parameter, χν2 = χ 2 /(N − n − 1), to be .1, where N is the number of data points (=227) and n (=1) is the number of free parameters. The results are insensitive to the width of this wavelength interval. However, since R is intended to account only for the broadband, low frequency component of the albedo, it is important to keep the wavelength interval significantly broader than any of the higher-frequency absorption or emission features in the spectrum or they will be unrealistically modeled out by being included in R. After calculating SO2 only models, we subsequently test for the presence of other contributors by adding them to the models and evaluating whether they reproduce observed features in the albedos and provide improved χν2 in the fitting. The χν2 contour plots (N◦ vs T ) for the SO2 only models, and the resulting best fit models overplotted on the data, are shown in Fig. 6(A–C) for the three targets. The best-fit SO2 column densities and temperatures are 3.25 × 1016 , 1.5 × 1016 , and 7 × 1015 cm−2 , and 280, 150, and 200 K, for Pele, Ra, and T3, respectively. The χ 2 contours reflect the general behavior of the SO2 cross section band model: at higher temperatures, more SO2 is required because the band contrast is less than at lower temperatures. Generally speaking, the band contrast is ˚ because of the σ 2 better fit at wavelengths longward of 2100 A i weighting of the fits; that is, the error bars on the data points are significantly larger toward shorter wavelengths (see Fig. 3, which shows the error bars used in the σi2 weighting). The SO2 only models illustrate the general problem in trying to accurately assess the SO2 gas abundance on Io. It is not currently possible, given the limited availability of high-resolution SO2 cross section data at varying temperatures, to adequately reproduce the SO2 band depths over a broad wavelength range. While some bands are matched reasonably well, others (e.g., ˚ are not well modeled. Although it is possible that λ . 2000 A) there are additional unaccounted for absorbers, as suggested by T96, until the atmospheric transmission models can be improved, it is difficult to assess this hypothesis quantitatively. Because it is known to be present in the Io atmosphere (Lellouch et al. 1996), it is logical to test for the presence of

FIG. 7A. (a) The χ 2 contour grid for NSO2 vs NSO showing that the bestfit model value for NSO2 remains unchanged by the addition of SO to the model and results in a best-fit value for NSO of 2.5 × 1015 cm−2 . (b) The best-fit SO2 + SO model overplotted on the data.

SO gas in the albedo, in addition to SO2 . The unambiguous identification of SO bands in the UV albedo is very difficult because the SO cross section is very similar to SO2 , with very few bands clearly separated from those of SO2 . Adopting the best-fit value for T found in the SO2 only models of Fig. 6, we construct chi-squared grids of NSO2 vs NSO to see if the addition of SO improves the model fits to the data and if any SO bands are clearly identifiable at the best-fit model abundance. These grids are shown in Fig. 7, along with the corresponding best-fit models overplotted on the data. We identify in Fig. 7A(b) several wavelengths at which distinct SO bands appear, some of which show corresponding features in the data. Given the nature of the SO cross section available (no temperature dependence, not high resolution), this correspondence seems to provide fairly strong evidence for the presence of SO absorption in the albedos. The addition of SO also improves the χ 2 values in all three cases, and since it is a minor contributor to the atmospheric transmission compared with SO2 , the addition of SO has little effect on the best-fit values for the SO2 column densities and temperatures, which we have tested by re-running the NSO2 vs T grids with the best-fit SO abundance included. The best-fit SO values are 2.5 × 1015 , 5 × 1014 , and 1.5 × 1015 cm−2 for Pele, Ra, and T3,

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1 (1.18 and 1.11), and significantly less than 1.5, the number of degrees of freedom is so large (ν = 225) that the probability Pχ is significantly less than 0.5, indicating that these are not particularly statistically significant fits. The result is different for the Pele data not because the difference between data and model is larger, but because the integration time for that observation is nearly twice as long as for the other observations (see Table I), so the statistical errors (σi ) are smaller. It is easy to produce statistically significant fits (χν2 . 1) by reducing the wavelength interval ˚ which improves the fit in one used in the fitting from 30 to 28 A, ˚ where there is an obvious mismatch place only, near 2060 A, between model and data. It is impossible to assess on the basis of a single observation whether this feature is real, possibly an ˚ shown in instrumental artifact analogous to the feature at 1935 A Fig. 1, or a result of imperfect SO2 cross sections or transmission models. Only further relatively high spectral resolution data or improvements in the transmission models or cross sections can resolve this issue. We therefore attach no significance to the fact that χν2 has a value slightly larger than 1 for the Pele fits. Although we have emphasized the uncertainties inherent in the different components of our model and in our modeling technique, we can nevertheless draw firm conclusions from our data. Because our models have only one free parameter (R) we do not have uniqueness problems with the fitting. While the detailed

FIG. 7B. Same as Fig. 7A for Ra, with NSO = 5 × 1014 cm−2 .

respectively, which give SO abundances relative to SO2 of 0.08, 0.03, and 0.21. The average value of 0.1 is in excellent agreement with the disk-averaged value of ∼0.1 from Lellouch et al. (1996). Using the cross sections from Wu and Judge (1981), we have also searched for CS2 , and from lack of definite features ˚ we set an upper corresponding to CS2 between 1975 and 2150 A, limit of 2 × 1014 cm−2 on its column abundance. Our discussion and assessment of the goodness of fits is based on the treatment presented in Bevington (1969). The value of χν2 provides a measure of the probability of obtaining a particular value of χ 2 as large or larger from the correct fitting function. If the fitting function is a good approximation to the parent function, the χν2 value should be close to 1, and the probability, Pχ , should be approximately 0.5. Unfortunately, interpretation of the probability can be ambiguous because even the correct fitting function can sometimes yield a large value of χ 2 . The probability is generally either reasonably close to 0.5, indicating a good fit, or unreasonably small, indicating a bad fit. For most purposes, the probability is reasonably close to 0.5 as long as χν2 is reasonably close to 1, i.e., less than 1.5. A value of χν2 less than 1 does not indicate a better fit. All of our fits except those for the Pele data (Figs. 6A, 7A) have values of χν2 < 1, indicating an acceptable fit (Pχ > 0.9). For the Pele models, while the minimum χν2 values are close to

FIG. 7C. Same as Fig. 7A for T3, showing NSO = 1.5 × 1015 cm−2 .

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variation of R with wavelength is uncertain, its uncertainty is probably no more than about a factor of two at any wavelength, based on the good agreement of the average value with that from several independent sets of observations (B94, T96, Sartoretti et al. 1994, Hendrix et al. 1999). It also has little effect on the results for two reasons: it is allowed to vary by any amount, and it is the band contrast, and not R, which is the single largest constraint on the derived SO2 gas abundance and temperature. We can readily exclude the possibility of very large column densities (N & 3 × 1017 /cm−2 ), since such models are totally inconsistent with our data under any circumstances. They produce huge values of χν2 no matter how much the free parameter is varied or how small we make the wavelength interval in the fitting. Such models, even though they do not produce good fits, require the surface reflectance to be greater than 1, which is physically unreasonable. Column densities larger than ∼1018 /cm−2 require the reflectivity to be as large as 106 . It is very doubtful that the SO2 transmission models are in error by this much. Similarly, models with much smaller column densities than the best fits do not produce nearly as much band contrast as observed. The bestfit models of Hendrix et al. (1999), which inferred SO2 column densities greater than 1017 /cm−2 over 60% of the surface, are inconsistent with our data. Unless there are very large errors in the SO2 band model, we estimate that our SO2 column densities are accurate to about a factor of 3, a conclusion supported by the statistical anaylsis of the goodness of the fits. 3.2. Analysis of the Atomic Emission Lines In addition to molecular species, we detect emission from ˚ atomic sulfur in the intercombination doublet SI] 1900,1914 A, which is prominent in the Pele flux spectrum shown in Fig. 2. We ˚ region for the three targets in Fig. 8, where SI show the 1900 A emission is evident from Pele and T3 but not from Ra. The bright˚ multiplets we detect are 3.6 (Pele) nesses of the SI] 1900,1914 A and 1.6 kR (T3), and the upper limit for Ra is <1.5 kR, which

correspond to photon fluxes of 3.5 × 10−4 (Pele) and 1.6 × 10−4 (T3), for a total of 5.1 × 10−4 photons/cm2 /s. The range of values observed for the disk-averaged line flux from the trailing/dusk hemisphere is 2–6 × 10−3 photons/cm2 /s (Ballester 1989). The ˚ multiplet flux we observe is a factor of 4–12 lower SI] 1900 A than the disk-integrated value, implying that SI emission over the localized spots of our targets is a small fraction of the diskintegrated value. Our observed line brightnesses therefore appear to be consistent with the previous result that most of the disk integrated emission comes from bright equatorial spots at the limbs of the satellite (Trauger et al. 1997, Roesler et al. 1999) which are apparently not associated with active volcanos. Galileo visible eclipse images of Io detect the equatorial spots, as well as localized emission within the disk, apparently concentrated over active volcanos (Belton et al. 1996, Geissler et al. 1999). The “volcano glow” could be related to the emission we see, especially at Pele. Emissions from atomic sulfur and oxygen both near Io and in the plasma torus far from Io have been observed for many years (Brown 1981, Ballester et al. 1987, Scherb and Smyth 1993, Clarke et al. 1994, Roesler et al. 1999) and are known to be excited by electrons from the Io plasma torus (cf., Brown et al. 1983). In the low electron density regime applicable for the Io torus plasma, which has a peak electron density n e ∼ 103 , collisional de-excitation is unimportant and every excitation is balanced by a spontaneous emission. Under such conditions, the volume emission rate of a particular transition from upper state j to lower state i is given by (Osterbrock 1989) ²i j = n j A ji = n e n i qi j (Te ) (cm−3 s−1 ) = ne ni

¯ i j e−Ei j /kTe 8.63 × 10−6 Ä , √ ωi Te

(4)

where n e is the electron density, Te is the electron temperature in degrees Kelvin, n i and n j are the densities of the upper and

a FIG. 8. The 1850–1950 A region of the flux spectra for the three targets, Pele (left), Ra (middle), and T3 (right).

IO’S PELE PLUME AND SO2 ATMOSPHERE

lower states of the emitting species, A ji is the transition probability from level j to level i, qi j is the electron excitation rate ¯ i j is the effective (thermally averaged) collision coefficient, Ä strength, E i j is the energy of the transition, and ωi is the statistical weight of the lower state. Assuming isotropic emission and integrating ²i j along the line of sight through the nebula gives the apparent emission rate, 4π J , which is equal to the observed line brightness Bi j expressed in units of Rayleighs (106 photons cm−2 s−1 ) (Brown et al. 1983). Although they are expected to vary significantly along the line of sight, especially near Io, it is common to assume average line of sight values for n e and Te so that an estimate can be made of the column density of the emitter N ∼

106 Bi j (cm−2 ). n¯ e qi j (T¯ e )

(5)

In addition, brightness ratios of lines in a multiplet can be used to perform basic plasma diagnostics. For instance, in the low electron density regime and the optically thin limit, the brightness ratios of lines originating from a common upper level (as ˚ doublet) is (from Eq. (4)) equal is the case for the SI] 1900 A to the ratio of the A values. Line ratios that differ significantly from the optically thin ratios imply that the medium is optically thick to the transitions of interest. The probability that a photon emitted at a particular point in a particular direction and with a normalized frequency from line center will escape without further scattering and absorption is e−τν , where τν = kν N . The optical depth is generally so small for forbidden transitions in every direction, even at line center, that the mean escape probability from all points is essentially unity. Assuming that only thermal Doppler broadening and radiative damping are important, absorption of photons in the core of the line has the Doppler form (Osterbrock 1989) kν = ko e−(1ν/1ν D )

2

√ 2 λi2j ωi A ji π e fi j ko = = 8π 3/2 ω j 1ν D m e c 1ν D

1ν = ν − νo r 2kT 1ν D = νo , mc2 where f i j is the oscillator strength of the transition, m e and e are the electron mass and charge, c is the speed of light, λi j is the wavelength of the transition, ν√o is the line center frequency, m is the mass of the emitter, and 2kT /m is the thermal speed of the emitting particles. If the line ratios show that the nebula is optically thin (thick), an upper (lower) limit on the column density can be estimated assuming unit optical thickness and using the absorption cross section at line center, N =

m e c1ν D 1 =√ 2 . ko πe f i j

(6)

A summary of the theoretical and experimental values for the oscillator strengths and transition probabilities for atomic sulfur

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transitions has been published recently by Tayal (1998). For the SI] 1900 multiplet only two values of the oscillator strength exist (Tayal 1998, M¨uller 1968) and these disagree by more than an order of magnitude. In fact, all the Tayal (1998) oscillator strengths and transition probabilities for the intercombination lines are substantially smaller than the other published results, which they attribute to the fact that their wave functions are designed to represent triplet states more accurately than quintet states. We therefore use the M¨uller values for the oscillator strength and transition probability for the SI] 1900 transition. The A values are A1900 , A1914 = 6.6 × 104 , 1.8 × 104 , which imply an optically thin intensity ratio for the SI] 1900 multiplet lines, I1900 : I1914 , of 3.7 : 1. We observe the following line ratios in our targets: 3 : 1 (Pele) and &3.5 : 1 (T3; the SI 1914 component of the multiplet is not positively detected). The observed SI] 1900 line ˚ ratios are therefore close to the optically thin value. The 1900 A line, which has the larger oscillator strength of 6 × 10−5 , provides the better constraint on the sulfur column density, which from Eq. (6) is a maximum of 7 × 1015 cm−2 . Unfortunately, a major impediment to estimating the S column density using Eq. (5) is the complete lack of collision ¯ i j ) for the SI] 1900,1914 transitions. Approximate strengths (Ä techniques are required to estimate them, and we follow the method suggested by Strobel (personal communication, 1998) and detailed in Ballester (1989) which exploits the similar ground state electronic configurations of S and O to estimate the SI] 1900 collision strength by analogy with the similar transitions for OI, for which much better atomic data are available. The ratio of the electron excitation rates for SI 1814 and SI] 1900 should be comparable to the ratio of the analogous oxygen multiplets OI 1304 and OI] 1356. The only change we make from the Ballester (1989) treatment is to update their SI 1814 collision strength from the Ho and Henry (1985) value using a newer value of the oscillator strength from Tayal (1998) by multiplying by the ratio of the Tayal to Ho and Henry values, 0.093/0.073. (For the SI 1814 multiplet, numerous determinations of the oscillator strength (see references in Tayal 1998) give a range of values, 0.073–0.12, that agree to within 25%. The Tayal (1998) value of 0.093 is very close to the average and is within the error range of the two experimental values from M¨uller (1968) and Savage and Lawrence (1966).) Since the rate coefficient is not published by Ballester (1989), and because we have updated it using the more recent atomic data quoted above, we show the final excitation rate coefficient curve we derive as a function of Te in Fig. 9a. We also plot in Figs. 9b and 9c the sulfur column densities inferred from our observed SI line brightnesses via Eq. (5) as a function of Te for several values of n e . Since n e and Te are not well known, we assume the canonical plasma torus values of n¯ e ∼ 1000/cm3 and T¯e ∼ 5 eV for the sulfur columns we quote: N S ∼ 5 × 1013 cm−2 (T3) and 1 × 1014 cm−2 (Pele), which are consistent with the upper limit derived above. These estimates of the S column density allow us to make the first concurrent estimates of relative SO2 , SO, and S abundances in the same column of Io atmosphere for two of our targets

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FIG. 9. (a) The electron excitationa rate coefficient we use to derive sulfur column densities from the SI] 1900 A emission shown in Fig. 8. The sulfur column densities derived for (b) Pele and (c) T3 shown as a function of electron temperature (Te ) for a range of electron densities (n e ). The dashed line indicates the upper limit of 7 × 1015 cm−2 to the column density derived from the optically thin ratio of the two components of the SI intercombination doublet.

(Pele and T3), which are: S/SO/SO2 = 0.003 − 0.007 : 0.03 − 0.21 : 1. These results provide an observational test for photochemical models of the Io atmosphere, which we discuss further in Section 4. 4. DISCUSSION

The best-fit SO2 column densities we derive vary by a factor of 5 among the three targets, providing the first direct evidence that Io’s atmosphere is spatially inhomogeneous. We survey about 20% of the projected area of the trailing hemisphere and find SO2 gas in all three locations in abundances significantly greater than collisionally “thick” (N & 6 × 1014 cm−2 ) amounts, leading us to infer that SO2 gas, like SO2 frost, is ubiquitous on Io. The fact that we deliberately chose three very different target regions makes it unlikely that we serendipitously hit three gas-rich areas and strengthens the case for widespread distribution of SO2 gas.

There have been several previous direct detections of SO2 gas on Io, by Pearl et al. (1979), Lellouch et al. (1992, 1996), Ballester et al. (1994), and Trafton et al. (1996), with the latter three involving disk-averaged (spatially unresolved) measurements. In several additional observations the presence of SO2 gas has been inferred indirectly (Sartoretti et al. 1994, 1996, Spencer et al. 1997a, Hendrix et al. 1999). For most of these observations, the best-fit models used to constrain SO2 gas abundance are not unique because of the difficulty in trying to simultaneously optimize the numerous unconstrained free parameters (cf., N (δ, α), T (δ, α), and R(δ, α)) which often have offsetting effects. Generally speaking, the observations can be fit nearly equally well by a large range of models with the extremes of the range being, at one end, areal coverage of a small fraction of the surface by a relatively large column (N & 1 × 1017 cm−2 ) of SO2 gas; or, at the other extreme, areal coverage of 100% of the surface by a relatively small column (N . 1 × 1017 cm−2 ) of SO2 gas. Multicomponent models (such as the B94 two-component model and the Hendrix et al. three-component model), which involve various combinations of fractional coverage and column density, are also consistent with the observations in some instances. Our results are much more consistent with the [larger fractional coverage, smaller column abundance] regime of previous models than with the [smaller fractional coverage, larger column abundance] regime. Our abundances are in reasonably good agreement with the B94 and T96 trailing side, hemispherically averaged (i.e., 100% coverage) model results of 5–6 × 1015 cm−2 , while our temperatures are in reasonable agreement with the best-fit temperature range of 200–250 K for the hemispherically averaged models of B94. Our observations do not show evidence for the high column densities (N & 1 × 1017 cm−2 ) detected or inferred previously by a number of different techniques, both spectroscopic and imaging (Pearl et al. 1979, Lellouch et al. 1992, Sartoretti et al. 1994, 1996, Spencer et al. 1997b, Hendrix et al. 1999), which are approximately one to three orders of magnitude larger than the largest column density we detect, despite the fact that we targeted two known active volcanic centers, Pele and Ra. It is impossible to know whether these regions were active during our observations, as there are no other concurrent data available. HST WFPC2 images taken on 24 July 1996 (Spencer et al. 1997b), 7 days before our spectroscopic observations, showed a 420-km high plume over Pele. Galileo images taken before and after (June, September, November 1996) do not show a Pele plume, while December 1996 images do (McEwen et al. 1998). The Ra region underwent dramatic change between March 1994 and March 1995, exhibiting a much larger white area centered in a slightly different location in 1995 that remained bright in March 1996 (Spencer et al. 1997a) and in June 1996, when it also showed an active plume (McEwen et al. 1998). It appears to have faded by December 1996 (Simonelli et al. 1998) and remained that way in February and June 1997 Galileo and HST images. By contrast, the T3 region has never been observed to have an active plume, although this region (Aten Patera)

IO’S PELE PLUME AND SO2 ATMOSPHERE

does seem to have experienced a Pele-like eruption between the two Voyager encounters and is close to the site of a known hot spot (Lopes-Gautier et al. 1999). The presence of a large column of SO2 gas over Pele, combined with the lack of any other obvious source that could produce a factor of 5 larger column of SO2 gas there compared to the other target regions, leads us to assume that Pele was active during our observation. The relatively smaller column of SO2 gas over T3 compared to the Ra region could be accounted for by the difference in vapor pressure of SO2 resulting from the larger solar zenith angle. Using the observed extinction of Jupiter light by the plume, Spencer et al. inferred an SO2 column density of NSO2 ∼ 3.7 × 1017 cm−2 if all the extinction is due to SO2 gas. Large (N & 5 × 1017 cm−2 ) column densities of SO2 gas have also been inferred over Pele from disk-resolved HST FOC images (Sartoretti et al. 1994, 1996). The Sartoretti and Spencer SO2 columns are larger by factors of 11 (Spencer) and 12–60 (Sartoretti) than ours. It is certainly possible that the source rate could vary by such a large amount given the evidence for rapid Pele plume variability over a time period as short as 21 h (Spencer et al. 1997a). Although Spencer and Sartoretti do not derive vertical column densities, the airmass effect is too small (. a factor of 2 assuming a Pele plume height of 420 km, and that it is hemispherically shaped, as Spencer et al. assume) to account for the large difference in our SO2 columns. However, as Spencer et al. point out, small dust particles can also contribute some or all of the observed extinction. Our unambiguous detection of SO2 gas over Pele implies that at least some of the extinction is due to gas. The extinction ˚ effective wavelength of the Spencer et al. plume at the 2550 A detection image due to our observed column of SO2 gas is a very small fraction of the total plume opacity they derive (τgas ∼ 0.02, compared with τtot ∼ 0.19). Thus, either the gas output decreased substantially in the 7 days between our observations or, if it did not, only a small fraction of the plume opacity is due to SO2 gas. The latter conclusion, that both dust and gas contribute to the UV opacity, would tend to bring the SO2 column densities deduced from our work, Sartoretti et al., and from Spencer et al. into better agreement. The UV opacity at Pele in the Sartoretti et al. images is τ ∼ 1.4. Assuming the same ratio of dust to gas opacity for these data as above (τgas /τtot = 0.11, implying 89% of the opacity is due to dust, and 11% is due to gas) implies SO2 column densities about a factor of 10 lower. We also note that the Pele plume as observed by us and Spencer et al. is rich in SO2 gas but largely undetectable in visible wavelength images, which qualifies it as a “stealth” plume (Johnson et al. 1995). McEwen and Soderblom (1983) favored sulfur as the driving volatile for the large class, Pele-type volcanic eruptions and SO2 for the smaller class eruptions on Io, although they recognized the possibility that SO2 could drive the large class plumes as well. Detection of SO2 and S gas over Pele lends credence to the scenario of both SO2 and S as drivers for large class eruptions, and the lack of S emission over Ra (a small class plume) is consistent with the absence of S as a driving volatile for the small

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class plumes. Zolotov and Fegley (1998a) have shown that SO can have a volcanic origin as well. The fact that the S emission (and therefore abundance) is not correlated with the SO2 abundance for our targets seems to argue against dissociation of SO2 as the primary origin for the S, since we would then expect to see S at Ra as well. Since the SI] 1900 emission we see is optically thin, the derived abundance reflects the extent to which the column of S gas is accessed by electrons energetic enough to excite it. If only the uppermost portion of the plume is accessed, the actual S abundance may be significantly higher, and the S/SO/SO2 ratio may therefore be inaccurate. Despite this ambiguity, we compare our SO2 : S ratios with photochemical models (below), which assume all S comes from photodissociation of SO2 . As noted earlier, the S emission we see is distinct from the equatorial bright spots observed by Roesler et al. (1999) and especially at Pele seems more consistent with the “volcano glow” observed by Galileo (Geissler et al. 1999) when Io was in eclipse. Our spatially resolved observations provide a point of comparison with several of the theoretical models currently available for the Io atmosphere. We can readily exclude the Matson and Nash (1983) sublimation atmosphere models, which produce far too little SO2 compared to what we observe. In the new, more sophisticated buffered atmosphere models of Kerton et al. (1996)—which have sublimation of SO2 frost as the only atmospheric source, and now account for latent heat of SO2 frost, the rotation rate of Io, thermal conduction and Io’s interior heat flow, and a component of the so-called icy greenhouse effect—the gas distribution for all permutations of their models falls off much more rapidly with latitude than we observe. Their C/R/L model produces more SO2 gas than we observe, and the C/R/L High and SSGH models do not produce enough gas at any latitude compared to what we observe. As they point out, their models are meant to represent the Io atmosphere in a global sense and do not include the effect of strong winds away from the subsolar point driven by the steep pressure gradients in a sublimation atmosphere, making them inappropriate for detailed comparisons on a smaller scale. The three-dimensional axisymmetric models of Wong and Johnson (1996), on the other hand, also assume a sublimationdriven atmosphere but include hydrodynamic flow and photochemistry. Their models show a factor of 5 decrease in the SO2 column density at solar zenith angles corresponding to the those of the Ra/Pele and T3 targets, which is very close to the difference in SO2 column density we observe between these two regions. Although the peak and average SO2 column densities in their published model are about an order of magnitude higher than those we observe, the fall off with solar zenith angle is similar even with smaller column densities (Wong, personal communication, 1999). The comparisons with the Wong and Johnson models are very encouraging, since theirs are the most realistic to date for the Io atmosphere. Comparison with the latest one-dimensional photochemical model of Io’s atmosphere shows that we match most closely

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the low density SO2 atmosphere case of Summers and Strobel (1996), which has an SO2 column density about a factor of 5 lower than we observe at Pele. Their high density case has an SO2 column density about a factor of 30 larger than the largest we observe. For their low density case (presented in their Fig. 9), they find SO to be more abundant than S by about an order of magnitude, which is close to what we infer from our S and SO abundances. Based on a comparison with their low density atmosphere SO column density vs eddy mixing coefficient, our observed columns of SO would imply a relatively low value of the eddy mixing coefficient. Wong and Johnson (1996) also include photochemistry in their model and find SO À S in the high density case they present, irrespective of the assumed sticking coefficient for O2 in their model. Their SO abundance falls off more rapidly (factor of ∼2.5) with solar zenith angle than we observe (factor of ∼2); however, this discrepancy is not large. Finally, it is important to note that there remain many unexplained discrepancies between data and models, evident in Figs. 6 and 7. These are almost certainly due in part to imperfect modeling of the SO2 band transmission and its temperature dependence. The longer-wavelength emission-like features near ˚ are from portions of the spectrum with the 2270 and 2290 A highest S/N, and we do not believe these features are artifacts resulting from incomplete cancelation of solar features when generating the albedos. We find no strong evidence for the addi˚ discussed by T96 when tional absorbers near 2114 and 2131 A ˚ we fit the entire 1975–2300 A spectral region, whereas if we model the two T96 bands only, we do see some difference be˚ which could be interpreted tween model and data at 2131 A as excess absorption in the data. However, in the context of the inability of our best-fit models to accurately reproduce the observed spectral features and contrast over a much larger wavelength range, this difference is insignificant. Future observations may reveal whether any of these features are real and perhaps have an origin other than SO2 . Mapping the SO2 gas distribution simultaneously over an entire Io hemisphere, especially at times when the volcanic (plume) activity can be quantitatively characterized, would be useful in elucidating the degree to which the SO2 atmosphere is spatially and temporally variable and whether this is directly connected to volcanic activity. ACKNOWLEDGMENTS The invaluable assistance of Alex Storrs and Tony Roman with the design and implementation of our HST observing program is gratefully acknowledged. We acknowledge support of this research through NASA/STScI Grant G005-495.

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