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Article

Investigation of Absorption Bands around 3.3 μm in CRISM Data

by
Paola Manzari
1,*,
Cosimo Marzo
2 and
Eleonora Ammannito
1
1
Agenzia Spaziale Italiana, Via del Politecnico, 00133 Roma, Italy
2
Centro Spaziale dell’ Agenzia Spaziale Italian di Matera, Località Terlecchia, 75100 Matera, Italy
*
Author to whom correspondence should be addressed.
Remote Sens. 2022, 14(19), 5028; https://doi.org/10.3390/rs14195028
Submission received: 18 July 2022 / Revised: 25 September 2022 / Accepted: 28 September 2022 / Published: 9 October 2022
(This article belongs to the Special Issue Planetary Exploration Using Remote Sensing)
Browse Figures
Versions Notes

Abstract

:
Absorptions in the range 3.1 μm to 3.6 μm are under the spotlight in the context of planetary research, because hydrocarbon molecules show absorption bands in this range. Consequently, even knowing that the Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) was designed for the detection of mineralogical features on Mars’s surface, we exploited CRISM data in the range 3.2 μm to 3.4 μm to search for potential hydrocarbon compounds. To date, methane has been the only hydrocarbon detected on Mars. Therefore, we began our investigation into CRISM data in locations in which methane had been detected and where it could form due to the mineralogy of the specific site. The datasets chosen for this study included observation sites in the Oxia Planum, the Gale Crater, and Nili Fossae areas. We mapped the modified Gaussian model (MGM) to fit the CRISM data in order to extract the band parameters of the absorptions in the 3.3 μm spectral region. As a result, we found clusters of pixels with spectra that exhibited band centers between approximately 3.28 and 3.35 μm. The hydrocarbons showing absorptions in this range included polycyclic aromatic compounds as well as methane, ethane, and aliphatic compounds. We speculated that some absorptions of approximately 3.3 μm could be related to methane, so we calculated a theoretical lower limit of detection for each observation in the selected CRISM datasets. This was performed by simulating the CRISM spectra for the different sites, with diverse concentrations of CH4, using NASA’s Planetary Spectrum Generator online tool. These simulations established the relationship between the concentration and methane band depths, as detected by the CRISM. Methane band depths exceeding the thresholds varied from one observation to another, in the range of 0.0136 to 0.0237, which corresponded to a range of theoretically lower limits of concentration between 180 and 600 ppbv. Although we could not confirm or deny the occurrences of methane seepages or hydrocarbons in the investigated datasets, we demonstrated a possible method for searching for hydrocarbons in other CRISM data and for assessing a confidence limit in the detection of the methane band in CRISM data.

Graphical Abstract

1. Introduction

Significant portions of the missions on Mars are focused on research regarding past or present life on the surface and subsurface. Over the last decade, some evidence has been detected in the Mars environment that could be considered a proxy for the development of primitive lifeforms. In this sense, the findings related to methane on Mars continue to be intriguing with regard to methane’s potential as a biosignature, given that on Earth, methane was formed by microbes from the Archaea domain under anoxic conditions during the Proterozoic eon [1]. Methane and other hydrocarbon compounds can result from abiogenic geological processes [2,3]. For methane gas, these processes have resulted from the serpentinization of basalts [4], gas absorbed in the regolith [5,6] or through geothermal processes [2], or a release from subsurface clathrates [6,7].
Various instruments, both orbiting and onboard rovers, have detected this methane on Marss surface. Since 2003, several puzzling detections of methane in the Mars atmosphere have been found [8]. For example, from Earth, researchers using the Cryogenic Near-IR Facility Spectrograph (CSHELL) at the Infrared Telescope Facility (IRTF) and the Gemini ground telescopes [9] detected localized points with >250 ppbv of methane. This concentration value was then corrected to 45 ppbv, comparing data with planetary Fourier spectrometer (PFS) measurements, in another paper on the methane mapping of Mars [10]. The Fourier transform spectrometer (FTS) at the Canada–French–Hawaii Telescope (CFHT) facility measured 10 ppbv [11]. From Mars, the PFS on board the Mars Express mission obtained a methane concentration of approximately 10 ppbv [12].
Therefore, looking at the successive measurements from 2003, a distinction has to be made between the types of methane detection on Mars: background detections in the atmosphere versus the detection of “spikes” and “plumes” of methane, which differ by orders of magnitude in terms of ppb concentration.
Regarding the quantitative measurement of methane, the first measurements of the Exomars 2016 Trace Gas Orbiter (TGO), which worked in solar occultation, provided an upper limit of methane of <0.05 ppbv in the atmosphere above 5 km, according to [13]. However, the 3 years of measurements from the Tunable Laser Spectrometer (TLS) of the Mars Science Laboratory (MSL) onboard the Curiosity rover identified a background mixing ratio in the Gale Crater of 0.2 ppbv to 0.6 ppbv [14,15,16] near the surface at night. To account for these two measurements, ref. [17] hypothesized a diurnal cycle for methane, in which it was essentially diluted during the Martian day for the effect of current convection, thus justifying the methane abundance found by the TGO. During the night, the planetary boundary layer (PBL) drastically decreases, along with the diffusivity of the Martian atmosphere [18], making it possible for the surface to retain small quantities of methane.
Regarding the spikes, Mumma et al. [10] observed a strong release of methane, up to 50 ppbv, during the Northern Hemisphere summer of 2003. Their observations were acquired for up to 3 years, during which they observed a progressive decrease in the methane mixing ratio over that period and a substantial variation according to latitude. They concluded that the occurrence of this strong release of methane was limited spatially and temporarily. In addition, other spatiotemporal investigations with other instruments confirmed this conclusion.
Using the measurements of the Mars Express Planetary Fourier Spectrometer (MEX-PFS) in spot-tracking mode, Giuranna et al. [19] successfully detected an increase in methane in the atmosphere one terrestrial day after the first methane spike was detected on the surface by the Curiosity rover on 15 June 2013. The amount of methane detected by PFS was approximately 15 ppbv, compared with the 9 ppbv detected as a result of the sample analysis by the Sample Analysis at Mars–Tunable Laser Spectrometer (SAM-TLS) [14]. The last detection of a methane spike was found by the SAM-TLS onboard the Curiosity rover on 19 June 2019, measuring an abundance of methane that was never previously detected by a rover, at approximately 21 ppbv [17].
These findings provide insights into the constraints on the occurrence of methane on Mars. According to the results from the previous observations, the source of methane should be spatially restricted, but also temporally restricted with potential sources in the form of seepages [20]—from micro-seepages [17,21] and mini-seepages [21] to macro-seepages [22]. Furthermore, the different amounts detected in spikes (Table 1), the seasonal oscillations, and the non-detections are compatible with geological seepage dynamics. According to [23], these dynamics involve changes in the pressure gradient and in the permeability of rocks that are activated by different processes [14,15,16,22,23], such as rock fracturing by serpentinization [24].
The variability in the amount of methane observed in these measurements [10,13,14,15,16,17,19] and the estimated time for methane sequestration by photochemistry and oxidation that spans from hours to 300 years [25,26] allowed us to hypothesize that the plumes observed were recent at the time of measurement.
In summary, the seasonal and local variations in the amount of methane suggest that the sources could have an extension of meter-to-km scale.
For such spatially limited detections, it is helpful to localize the point sources for further consideration regarding the origin of these detections. In this sense, high-resolution imagery data, acquired under the same conditions and at the same time as the spectral data, should theoretically support this aim. With this in mind, the objective of this study was to search the hyperspectral data acquired by the Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) over selected areas for spectral absorptions that could be linked to the presence of hydrocarbons. Hydrocarbon compounds show absorptions in the IR range between 3.1 μm and 3.6 μm. However, CRISM has an IR range of up to 3.92 μm, with a spatial resolution capable of investigating the surface at a 10 m scale, which is compatible with localized hydrocarbon sources.
Oheler and Etiope (2017) [22] suggested that, due to the transient nature of the methane detected on Mars and the uncertainty concerning its lifetime in the Martian atmosphere, the only method for studying methane seepages on Mars’s surface would be by placing probes on the ground at fixed positions. This would allow for the constant sampling of methane to determine fluxes, while minimizing the effects of the isotopic fractionation of CH4 in the atmosphere, which would make it easier to trace back to the original isotopic ratio. However, if macro seepages could first be localized from remote sensing data, it would be possible to plan a landing mission with ground instruments and to measure methane fluxes directly at these macro-seepage sources.
Notwithstanding the low concentration of methane in Mars’s atmosphere, we analyzed CRISM data for methane absorptions at approximately 3.3 μm, generated by eventual spikes and plumes. We considered the following premises:
(1)
In June 2019, the CH4 abundance on Mars’s surface was estimated at approximately 20 ppbv by SAM-TLS [17], and the distance of the Curiosity rover from the source of the detected spike was unknown.
(2)
The detection of a plume with a peak value of approximately 40 ppbv from ground telescopes during 2003 [9,10] covered a wide area. We hypothesized that this abundance over a broad area would potentially mean a greater concentration in the source sites.
(3)
The time of survival of CH4 in the atmosphere spans from hours to 300 years [26].
(4)
Since August 2012, Curiosity has detected only two methane spikes, during 2013 and 2019. Assuming, in our work, that these sudden increases in methane concentration were sporadic, we looked for CH4 absorption that would eventually correspond to spikes in CH4 at the scene; that is, a concentration of methane greater than the values found for the background at tens/hundreds of ppb. Consequently, we expected to eventually observe few featured pixels/no featured pixels in the greater part of the investigated images.
In addition to methane, different studies, such as [27,28,29], found that hydrocarbons, which represent the main group among organic compounds, show strong absorptions in the near infrared range (NIR) of approximately 2.3 μm and in the infrared range (IR) of approximately 3.3 μm.
Absorptions at longer wavelengths (3.3 μm to 3.6 μm) are characteristic of aliphatic compounds, whereas the absorptions of aromatic compounds are between 3.1 μm and 3.3 μm [28].
Diverse remote hyperspectral systems have detected absorptions in these ranges on planetary surfaces. The Visual and Infrared Imaging Spectrometer (VIR) on Ceres detected several spectral features, in a range between 3.3 μm and 3.6 μm, of the stretching modes of the methyl (CH3) and methylene (CH2) functional groups [30].
Features at 3.3 μm are also typical of other more complex C–H compounds, the polycyclic aromatic hydrocarbons (PAHs) [31]. PAHs are the result of the degradation of organisms [32]. In this case, the eventual detection in CRISM data would be related to the time of a single observation, with fewer opportunities to detect PAHs during later missions, for two reasons: (1) the origin and nature of PAHs could only be studied by in situ chemical facilities, and (2) the short survival duration of approximately 3 days [26], when PAHs are exposed to UV rays on the surface.
Moreover, ethane has shown absorptions at 3.3 μm, but the only data were from [33], obtained using Cryogenic Near-IR Facility Spectrograph (CSHELL)–Infrared Telescope Facility (IRTF), which placed an upper limit of ethane in the Mars atmosphere at 0.3 ppb. This was similar to the background values of the methane concentration on Mars’ surface. We did not search, or expect to detect, spectral features in the 3.3 μm region at such concentrations.
Finally, CO2 ice also shows a strong absorption at 3.3 μm [34]. The phase diagram of CO2 for Mars has shown that, at average temperatures of approximately −50 °C at average latitudes and pressure of approximately 6 millibar, CO2 should be present in gaseous form [35]. Therefore, we considered CRISM data acquired at mid-latitudes, where CO2 should occur in gaseous form.

Area Selection

To date, there have not been any data recorded regarding occurrences of hydrocarbons other than methane on Mars’s surface. Therefore, the first datasets used for searching C–H absorptions were chosen from sites in which methane was detected or in which it could theoretically form. We considered three areas: the Oxia Planum, a prospected landing site for future mission [36], to compare the results of this work with data collected on the Martian surface by the Rosalind Franklin rover [37]; the Gale Crater, where the increase in methane has been shown by an orbiter and on the ground; and Nili Fossae, whose mineralogy is compatible with methane formation [38] and the peak value of 40 ppbv of methane was estimated from ground telescopes [10]. These three areas, chosen for our research, are indicated with stars in Figure 1.

2. Data and Methods

To search for potential hydrocarbon absorptions, CRISM IR cubes were processed to obtain a map of 3.3 μm absorption depth, band center, and width. Then, spectra with potentially true absorptions (i.e., absorptions due to surface or atmospheric compounds) were selected, based on the statistics of the depth map at 3.3 μm (see Section 2.3) and excluding those pixels clearly related to artifacts.
Finally, assuming the hypothesis that some of the true absorptions would be related to methane, we conducted simulations with NASA’s Planetary Spectrum Generator (PSG) tool https://psg.gsfc.nasa.gov/ (accessed on 11 November 2019) [39] to obtain a relationship that linked spectral properties (e.g., absorption depth) to CH4 concentrations.

2.1. CRISM Data Processing

The CRISM is a hyperspectral imaging spectrometer on the Mars Reconnaissance Orbiter (MRO). It was designed to detect and discriminate the mineralogical signatures on Mars’s surface. It collects images in a spectral range from 0.4 μm to 4 μm [40], with a spectral resolution of 6.5 nm and a full width at half maximum (FWHM) of 7.9 nm to 10.1 nm in VNIR and 9 nm to 19 nm in IR. It operates in two modes: (1) a 72-channel mapping mode that provides global coverage at 200 m/pixel, and (2) a full 544-channel targeted mode that provides a resolution of 15 m/pixel to 38 m/pixel. For this study, we considered Version 3 of the IR data, 1001 nm to 3936 nm, labeled with “L”, as collected by the L-detector. We used full-resolution reflectance and radiance targeted observations—FRS and FRT—which had a spatial resolution of approximately 20 m/pixel; half-resolution long and short (HRL-HRS) targeted observations that had a spatial resolution of 36 m/pixel; and along-track undersampled (ATU) observations that had a resolution of 18 m/pixel cross-track and 36 m/pixel downtrack. Radiance data were used to verify that the eventual absorptions were not introduced by the calibration in reflectance. For each area, the CRISM observations considered are listed in Table 2. On the basis of the literature [40,41] and a review of the data products associated with wavelength calibration, we considered that a possible shift in wavelength values could not be ruled out.
The analyses of CRISM I/F data (where I/F is the ratio of the radiance measured by the CRISM to the solar irradiance at Mars’s surface) followed two processing chains: the first followed the steps implemented in the CRISM Analytical Toolkit (CAT), Version 7.4, as a package in the Envi software. This kind of processing was necessary to remove atmospheric and photometric effects and to remove instrument artifacts. Specifically, the reflectance (I/F) data [40,42] were divided by the cosine of the solar incidence angle, and finally the atmospheric contribution was removed using the Volcano Scan method. In fact, CRISM observations contain contributions from atmospheric gases such as CO2, CO, and H2O, as well as aerosols (dust and water ice). In the Volcano Scan method, an atmospheric transmission spectrum is derived from observations at the base and top of Olympus Mons [43] for the characterization of absorption bands.

2.2. Processing of 3.3 μm Absorption

For absorption bands of approximately 3.3 μm, another chain of processing was created. Each whole CRISM I/F cube was processed through a procedure that first removed spectral spikes and resulted in a hyperspectral cube with a range of I/F values between 0.0 and 0.3. The spikes occurred on single spectral channels and not in the same channel for different pixels. We considered spike values as I/F higher than 1. The values were corrected by substituting them with the median value of the neighboring pixels. After this step, a de-striping process was applied, according to the procedure described in [44]. This last type of processing was followed by another procedure that searched for the 3.3 μm absorption, in the portion of spectrum between 3.2 and 3.4 μm, for each pixel in the scene. As we were considering a narrow range, the continuum was removed by subtracting a linear function passing through the reflectance values of the first and last points in the range.
After continuum removal, a modified Gaussian model [45] function was fitted to obtain a map of the absorption parameters: band center, depth, width, and bias.

2.3. Noise Estimation and Choice of the Thresholds

In CRISM data, there are different sources of noise. In fact, there is noise with a Poisson distribution characteristic from the VNIR S-detector and the IR L-detector, and thermal noise that characterizes the IR-L detectors [40,46]. In particular, the degradation over time of the cryogenic cooler of the L-detector generated an increase in the noise in CRISM scenes [40]. Stochastic noise occurs as spectral spikes related to sudden changes in brightness [47]. Finally, some CRISM data showed vertical striping, due to misalignment in the calibration of detectors.
To find the detection limit of methane concentration in the CRISM data, we calculated the statistics of depth values on the absorption map in the range between 3.2 μm and 3.4 μm. Considering all the noise sources and the variability of the different CRISM scenes, the standard deviation had to be calculated for every observation. For each image, a threshold was sets at μ + n × σ, where μ and σ were, respectively, the average value and the standard deviation of depth map. Due to the high noise in the CRISM data in the IR region, on the first analyses of the data, we found that a value of n = 5 assures, in an image with 100,000 pixels, no pixels with false absorptions that could be related to statistical noise. This threshold on the 3.3 μm depth set the lower concentration limit for detection of methane through the CRISM data.

2.4. Mars’s Surface Modeling

To determine if the quantities of methane estimated by the literature data would be observable by the CRISM, we used NASA’s Planetary Spectrum Generator (PSG). The PSG for surface modeling using CRISM data combines a realistic Hapke scattering model and the capability to include a broad range of optical constants, allowing us to accurately compute surface reflectance and emissivity [39]. To simulate spectra of Mars’s surface for each CRISM observation, the PSG tool requested some parameters: date and season of the observation, position of the target and the geometry of the view, the atmosphere and surface properties, and the characteristics of the observing instrument, such as altitude of observation, spectral range, and resolution. The noise was not simulated, but directly computed for each CRISM observation.
To compute the concentration of gases, the PSG refers to several databases. In particular, to calculate the concentration of methane, the PSG uses the HITRAN 2016 database. According to PSG simulations, the deepest absorption band of methane is located at 3.3115 μm. The simulation of the absorptions of the methane was conducted for all the featured clusters found during this investigation.
The code that PSG uses for modeling the atmosphere is called Planetary and Universal Model of Atmospheric Scattering (PUMAS). The scattering analysis is based on a Martian scattering model [48,49]. With the PSG tool, simulating each CRISM observation, we found the relationship, expressed by the diagrams in figures in Section 3.2 between increasing methane concentration and the band depth at 3.31 μm. Then, using CRISM data, we converted the calculated threshold for depth into lower limits of methane detection for each observation.

3. Results

3.1. Spectral Investigation of CRISM I/F Observations

The depth map highlighted a few isolated clusters, consisting of isolated groups of at least 4 pixels not aligned along columns, as well as pixels aligned along columns. The spatial distribution of pixels featured along columns was deemed suspicious; thus, these spectra were investigated further to exclude potential artefacts. We found that the spectra of those pixels presented false absorption features that can be assigned to artifacts looking at the distribution of pixels along columns and/or suspicious jumps in the spectra around the 3.2 μm to 3.4 μm range. For example, as shown in Figure 2a, the image of observation frs0002a9b2 was considered. The map of the 3.3 μm band was then overlaid on this image. In this map, several pixels (sea green color) appear to be distributed along columns, while others were in isolated clusters. Figure 2b shows, in sea green color, two spectra with absorptions typical of pixels aligned along columns, which we assigned to an artifact, and two spectra of pixels related to isolated clusters (dark red) that could represent potential true absorptions.
In all the investigated data, the positions of artifact absorptions were variable spatially and spectrally between 3.34 μm and 3.4 μm. To avoid the interpretation of absorption artifacts, we considered only those pixels in clusters that did not show a distribution along the columns of the images. Despite this precaution, there may still have been absorption artifacts in the selected pixels.
In Table 3, for each selected cluster, we listed the x and y coordinates of the pixels with the highest value of depth; for the band center, the number of pixels of the average value (μc) and the standard deviation (σc) of the depth of the cluster.
Figure 3, Figure 4 and Figure 5 show the results for the band minima in the range of 3.2 μm to 3.4 μm for the three observations in the three investigated areas. In the observation frs0003a896, the depth of the deeper pixel in the cluster (red, Figure 3) was 0.0123 (σc = 0.005), with a band center at 3.34 μm.
In the observation frs00028346, the depth of the deepest pixel in the cluster (red, Figure 4) was 0.0200 (σc = 0.007), with a band center at 3.35 μm.
In Figure 5, the image frs0002a9b2 is shown. Red pixels indicate the 3.297 μm absorption. The maximum value of absorption depth in the red cluster was 0.045 (σc = 0.005).
In each cluster, one or two pixels occurred with increased depth, as compared to the others that showed shallower depths. With respect to the hypothesis that these absorptions were not related to artifacts, this kind of distribution could be reminders of diffusion/distribution patterns.
Next, to establish a threshold for the depth to discriminate between signal noise and potential absorption, we computed the average μ and the standard deviation σ of the depth map of absorptions in the 3.3 μm region, for each dataset.
For each image, the average depth value ranged from 0.01 to 0.003 and the standard deviation of depth maps ranged from 0.002 to 0.004; see Table 4.
Therefore, we considered, as a threshold, only depth values greater than μ + 5σ for each image. Within the considered dataset, the resulting threshold values ranged from 0.0136 to 0.0237.

3.2. Simulated Spectrum of Methane Gas on Mars’s Surface

The simulation of surface spectra, in addition to the increasing content of methane (in ppbv), was computed by the PSG using different parameters, depending on the position, with respect to the Sun, of the investigated CRISM observation site. The use of the PSG simulator estimated the empirical function that would link absorption depths, as they would be detected by the CRISM, to methane abundances.
As an example, the simulated I/F spectrum, in the 3.2 μm to 3.8 μm range of the observation frs0003a896 in the Oxia Planum area, showed a weakly visible band absorption of 3.3 μm (Figure 6 and Figure 7), corresponding to the CH4 input value of 100 ppbv. To study how the band could vary in depth according to different concentrations, we also simulated 40, 100, 300, and 500 ppbv (Figure 8) and plotted the corresponding depths for each area investigated (Figure 9, Figure 10 and Figure 11). The depth values were calculated as the depths of the minima in the spectrum absorption in the range 3.2 μm to 3.4 μm.
As previously mentioned, each CRISM observation of this study was collected during a different year, season, and time (Table 2). However, the three plots of the increasing simulated CH4 band absorption vs. the depth in the simulated spectra showed a general agreement among the depths, independently from the season and year of observation. Therefore, in general, we concluded that the depths of the absorption band at 3.3 μm of methane corresponded to approximately 0.008 for 100 ppbv, for all the sites. One exception was for the observation frs00041a28, where the concentration of 100 ppbv corresponded to a deeper value of absorption (depth = 0.012).
Comparing the simulations (Figure 9, Figure 10 and Figure 11) with the depths of the absorptions in Table 3, we found that the minimum detectable value of methane concentrations varies between 180 and 600 ppbv, depending on the considered site (Table 5).

4. Discussion

The simulations for each site (Figure 9, Figure 10 and Figure 11) showed that the depths corresponding to the same concentration of methane did not vary significantly from site to site. For example, 100 ppbv corresponded to a range of depths from 0.008 to 0.012.
In these simulations, one exception was the observation frs00041a28 in the Nili Fossae area, which showed greater depths compared to the other sites. This could be related to either the viewing geometry, the season/hour, or a combination of these variables.
According to our investigations in respect of the CRISM data, the depths of the deepest pixels in these featured clusters in the CRISM observations showed different values that ranged from 0.013 to 0.057 (Table 3). To avoid false absorption data due to unknown artifacts, the threshold for depth was set at μ + 5σ in the depth maps. The thresholds ranged from 0.0136 to 0.0237 (Table 4). The difference in band centers of the absorptions was approximately 80 nm for the considered dataset. This difference could be explained by hypothesizing that some of the featured clusters consisted of other kinds of hydrocarbon compounds.
Furthermore, the statistics of the depth map showed that the thresholds for the absorption depth for calculating the lower limit of methane concentrations varied, depending on the considered CRISM observation. In general, we concluded that for concentrations lower than 180 ppbv to 600 ppbv, depending on the considered site, a potential true absorption would be interpreted as an artifact.

4.1. Good Candidates but Artifacts

Despite the precautions taken to exclude artifacts and noise-related absorptions from our interpretations, not all of the remaining absorptions may have been accurate, and some may have been well-masked artifacts. Among the known artifacts of the CRISM IR range, there was an optical effect due to out-of-band leakage in Zone 3 of the IR order-sorting filter. According to Murchie et al., this leakage peak appeared at 3.4 μm [40]. This kind of artifact generated positive signal peaks. A probable artifact was found in the CRISM IR data at 3.18 μm [47,50], i.e., another artifact named “spurious absorptions or absorption-like features”. This last artifact consisted of absorptions in over 20 channels, showing gradual shoulders from the continuum value.
To exclude, at least, the artifact that was introduced by the I/F pipeline, we analyzed radiance and I/F data. As shown in Figure 12, the featured pixels from the image frs00029b2 showed a 3.3 μm absorption both in the radiance spectrum and in I/F. Therefore, 3.3 μm absorption was not related to the I/F correction.

4.2. Good Candidates, Potential Methane Spikes?

There was also the possibility, however, that some of the identified locations with absorptions at 3.31 μm could be localized methane sources (Figure 13).
In this work, we found that if methane plumes were present in the selected dataset, the CRISM could detect the methane spectral features for concentrations >180 ppb to 600 ppb, depending on the site.
Unfortunately, it was not possible to calculate the flux of the potential sources, as the CRISM did not collect data periodically in fixed areas, as it was designed for studying the mineralogy of Mars’s surface. However, for the clusters that satisfied the two criteria—pixels not vertically stacked and a conservative threshold for depth values—we determined that potential methane detection in the CRISM data consisted of relatively few pixels, i.e., 4 to 15. For each cluster, the values of the pixels with the deepest absorptions were considered and listed in Table 3. In general, the remaining pixels in the cluster showed shallower absorptions. If these absorptions were methane, the clusters could represent the diffusion of gas in the atmosphere from a source point, or diffusion by multiple sources on the surface. Even if, at present, there are no clues about the size of the possible sources of methane spikes or plumes on Mars’s surface, we can refer to the studies on the typology of methane sources on Earth, even considering that Earth and Mars have different geologic histories. Typologies of methane sources include micro-seepages and macro-seepages; their extension can consist of meters to kilometer squares (for example, see [22]). The size of the clusters found in this work could be consistent with emissions from fracture or fissure networks.
The concentrations resulting from the PSG simulations were high, as compared with previous spikes and plume detections. The difference can be explained, considering that the high spatial resolution of the CRISM allows the direct spotting of the eventual methane sources with local high concentrations (>180 ppb to 600 ppb in the considered sites). Such high concentrations can fit with concentrations found by other instruments, if we consider the time of the methane removal/sinks from the atmosphere.
According to [8,51], the oxidation process on Mars destroys methane in approximately 300 years. Nevertheless, this mechanism is too long to explain, for example, the detection of the last spike of 21 ppbv by MSL [17] and the non-detection by the Mars Express and ExoMars TGO (ESA’s Mars orbiters did not observe the latest Curiosity methane burst after several hours of observing the same area; see [13]).
Several hypotheses have been formulated for a shorter lifetime of CH4 that include gas–solid reactions [52,53]; however, according to Lefevre and Forget, a faster mechanism proposed for methane removal is the oxidation CH4 by the action of hydrogen peroxide in the regolith [25]. This mechanism could shorten methane life from 200 days to a few hours near the surface.
Finally, the spectral features at 3.3 μm could also be assigned to the magnetic dipole CO2 absorption bands detected by ACS [54]. Nevertheless, the measurements of the CO2 magnetic dipole were collected at northern latitudes (>65° N) and in solar occultation conditions.
In our study, we analyzed CRISM data acquired on mid-latitudes at nadir, just to exclude potential contributes of CO2 ice.

4.3. Organic Matter and PAHs

Some clusters that showed absorptions at longer wavelengths could be related to aliphatic hydrocarbons, such as methane, as well as to other aliphatic compounds that showed absorptions at approximately 3.3 μm to 3.6 μm.
In addition to aliphatic compounds, the absorptions found in some clusters with bands of approximately 3.28 μm to 3.3 μm (Figure 14) could also be assigned to some aromatic hydrocarbons, such as PAHs; for example, naphthalene, anthracene, and phenanthrene.
In a previous study, Campbell et al. [55] investigated hydrocarbon detection on Mars’s south polar cap, although the feature at 3.3 μm was difficult to interpret, due to strong absorption by CO2 ice.
Even if some studies [26,56] on Mars’s surface revealed a short lifetime and a rapid degradation of PAHs in the shallow surface, due to UV and ionizing radiation, the eventual occasional occurrence of PAHs on surface images and the related 3.3 μm absorption band in the CRISM data could be linked to PAH-bearing impacting bodies on Mars’s surface, or correspond with fresh crater outcrops [57].

5. Conclusions

In this work, we exploited CRISM IR data in the range 3.2 μm to 3.4 μm to search for hydrocarbon compounds on Mars’s surface. To date, the only hydrocarbon detected and localized on Mars’s surface, by the SAM-TLS onboard the Curiosity rover, is methane. Therefore, we analyzed hydrocarbon features of approximately 3.3 μm in the CRISM data, starting the investigation from those sites where a hydrocarbon (methane) had been detected or its formation had been predicted on the basis of mineralogy.
We found clusters of pixels in which the band center of the absorptions ranged from 3.28 μm to 3.37 μm. These band centers were typical of different types of hydrocarbon compounds, from PAH to aliphatic. The found clusters consisted of 4 to 15 pixels with sizes of a few thousand square meters.
We adopted criteria to exclude the interpretation of false absorptions related to noise and to clear artifacts. Nevertheless, we could not assume that all artifacts and noise effects that could simulate or mask absorptions were eliminated.
Hypothesizing that absorptions of approximately 3.3 μm could have been related to methane, we used an online simulator, the PSG tool, to convert different methane concentrations into band depths.
Then, the statistics of the depth map between 3.2 μm and 3.4 μm were calculated for each image, in order to set a conservative threshold on depth.
As a consequence, hypothesizing that some of the absorptions were related to methane, the thresholds determined the theoretical lower limit of methane detection in each CRISM observation.
Among the analyzed clusters, we found interesting spectra in some observations of the three investigated locations.
If some clusters were related to methane emissions, these findings would strengthen the hypothesis of localized sources of methane in the subsurface. In fact, data on Martian methane concentrations have included background values [15,16], spikes [10], non-detections [13], and seasonality [17]. The results of this investigation could fit well with sources of methane in the form of gas seepages [23].
Because the CRISM was designed to discover the mineralogy of Mars’s surface, and not to detect hydrocarbons, it did not collect data periodically to monitor spectral changes in the same zone.
Furthermore, the comparison with other instruments conceived to detect trace gas in the atmosphere, such as ACS-TGO, had various challenges: time of persistence of methane in the Mars atmosphere (hours, months, years?), different spatial (18 m/pixel for the CRISM) and spectral resolutions, different viewing geometry, and/or the non-correspondence of the time of the observations
Because it is generally agreed that methane on Mars comes from the surface or subsurface, the method to confirm seepages involves the placing of probes for soil gas sampling, analyses, and monitoring on the planet’s surface. The first site to investigate could be the Gale Crater, where methane was effectively detected. Other possible sites to investigate for potential methane formation include areas that are characterized by intense faulting, such as mud volcano-like structures and olivine-bearing terrains.
Due to artifacts and noise, we could not confirm the presence of methane or other hydrocarbons in the analyzed datasets, nor could we exclude those absorptions in some pixels that could have been related to C–H compounds. Overall, we demonstrated a method to exploit CRISM data to search for C–H signatures on Mars’s surface. The method illustrated in this work could be applied to hundreds of images to explore potential methane macro-seepages and other hydrocarbon signatures on Mars’s surface.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/rs14195028/s1, Figure S1: Modified Gaussian Model (MGM) plots of all the pixel spectra of the cluster found in frs0002a9b2 observation.

Author Contributions

P.M.: conceptualization, investigation, elaboration of the code tool for hyperspectral data, and writing—review and editing; C.M.: elaboration of the code tool for hyperspectral data, and conceptualization; E.A.: writing—review and editing. All the authors discussed the results and implications and commented on the manuscript at all stages. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by the Italian Space Agency, Rome, Italy.

Data Availability Statement

The dataset analyzed in this work can be downloaded from https://ode.rsl.wustl.edu/mars/ (accessed on 3 March 2019); the planetary simulator tool is available at this address https://psg.gsfc.nasa.gov/ (accessed on 11 November 2019).

Conflicts of Interest

The authors declare that they have no conflict of interest.

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Figure 1. Area selection. Colorized terrain base image from the Mars Orbiter Laser Altimeter (MOLA). Investigated areas: cyan asterisk = Oxia Planum; purple asterisk = Nili Fossae, yellow asterisk = Gale Crater. Image source from https://www.planetary.org/space-images/mars-orbiter-laser-altimeter (accessed on 17 July 2022).
Figure 1. Area selection. Colorized terrain base image from the Mars Orbiter Laser Altimeter (MOLA). Investigated areas: cyan asterisk = Oxia Planum; purple asterisk = Nili Fossae, yellow asterisk = Gale Crater. Image source from https://www.planetary.org/space-images/mars-orbiter-laser-altimeter (accessed on 17 July 2022).
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Figure 2. Examples of investigated artifacts. (a) One band in grayscale of CRISM I/F observation frs0002a9b2, center latitude/center longitude 20.9575°, 75.4673°, in the Nili Fossae area. The image has an x-axis corresponding to the width of the slit and a y-axis that corresponds to the along-track direction. The map of 3.3 μm absorption was superimposed on this image (sea green color); (b) examples of two spectra corresponding to two pixels in the sea green color clusters, showing the artifact absorptions in the 3.2 μm to 3.5 μm range; in dark red are shown two possible true absorptions, related to two pixels in the clusters, indicated by the two arrows in the image.
Figure 2. Examples of investigated artifacts. (a) One band in grayscale of CRISM I/F observation frs0002a9b2, center latitude/center longitude 20.9575°, 75.4673°, in the Nili Fossae area. The image has an x-axis corresponding to the width of the slit and a y-axis that corresponds to the along-track direction. The map of 3.3 μm absorption was superimposed on this image (sea green color); (b) examples of two spectra corresponding to two pixels in the sea green color clusters, showing the artifact absorptions in the 3.2 μm to 3.5 μm range; in dark red are shown two possible true absorptions, related to two pixels in the clusters, indicated by the two arrows in the image.
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Figure 3. Cluster in frs0003a896 (about 5000 m2). (a) frs0003a896 CRISM stamp overlapped on MRO Context Camera (CTX) global mosaic; (b) not georeferenced frs0003a896 image with a red cluster featured by spectral absorptions at 3.34 μm; (c) zoom of the cluster; (d) spectrum with the highest absorption in the cluster (blue asterisks) and fitting with MGM curve to extract spectral parameters.
Figure 3. Cluster in frs0003a896 (about 5000 m2). (a) frs0003a896 CRISM stamp overlapped on MRO Context Camera (CTX) global mosaic; (b) not georeferenced frs0003a896 image with a red cluster featured by spectral absorptions at 3.34 μm; (c) zoom of the cluster; (d) spectrum with the highest absorption in the cluster (blue asterisks) and fitting with MGM curve to extract spectral parameters.
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Figure 4. Cluster in frs00028346 (about 8000 m2). (a) frs00028346 CRISM stamp overlapped on MRO Context Camera (CTX) global mosaic; (b) not georeferenced frs00028346 image with a red cluster featured by spectral absorptions at 3.35 μm; (c) zoom of the cluster; (d) spectrum with the highest absorption in the cluster (blue asterisks) and fitting with MGM curve to extract spectral parameters.
Figure 4. Cluster in frs00028346 (about 8000 m2). (a) frs00028346 CRISM stamp overlapped on MRO Context Camera (CTX) global mosaic; (b) not georeferenced frs00028346 image with a red cluster featured by spectral absorptions at 3.35 μm; (c) zoom of the cluster; (d) spectrum with the highest absorption in the cluster (blue asterisks) and fitting with MGM curve to extract spectral parameters.
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Figure 5. Cluster in frs0002a9b2 (about 9000 m2) (a) frs0002a9b2 CRISM stamp overlapped on MRO Context Camera (CTX) global mosaic; (b) not georeferenced frs0002a9b2 image with a red cluster featured by spectral absorptions at 3.3 μm; (c) zoom of the cluster; (d) spectrum with the highest absorption in the cluster (blue asterisks) and fitting with MGM curve to extract spectral parameters. More plots related to this cluster are shown in the supplementary materials.
Figure 5. Cluster in frs0002a9b2 (about 9000 m2) (a) frs0002a9b2 CRISM stamp overlapped on MRO Context Camera (CTX) global mosaic; (b) not georeferenced frs0002a9b2 image with a red cluster featured by spectral absorptions at 3.3 μm; (c) zoom of the cluster; (d) spectrum with the highest absorption in the cluster (blue asterisks) and fitting with MGM curve to extract spectral parameters. More plots related to this cluster are shown in the supplementary materials.
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Figure 6. Planetary Spectrum Generator (PSG) tool simulation. Simulated spectrum of frs0003a896 image, input parameters for the surface: 100% abundance Mars spectrum (PSG library) plus 100 ppbv of CH4, for which the corresponding absorption is highlighted by the dotted circle.
Figure 6. Planetary Spectrum Generator (PSG) tool simulation. Simulated spectrum of frs0003a896 image, input parameters for the surface: 100% abundance Mars spectrum (PSG library) plus 100 ppbv of CH4, for which the corresponding absorption is highlighted by the dotted circle.
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Figure 7. Enlargement of 3.2 μm to 3.4 μm spectral region of Figure 6.
Figure 7. Enlargement of 3.2 μm to 3.4 μm spectral region of Figure 6.
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Figure 8. Simulated transmittance spectra in the 3.2 μm to 3.6 μm range of the frs0003a896 image in Oxia Planum, with increasing concentration of CH4 from 40 ppbv to 500 ppbv.
Figure 8. Simulated transmittance spectra in the 3.2 μm to 3.6 μm range of the frs0003a896 image in Oxia Planum, with increasing concentration of CH4 from 40 ppbv to 500 ppbv.
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Figure 9. Simulations for the Gale Crater site. Quantification of the absorption depths for increasing concentration of CH4 for the selected observations in the Gale Crater area.
Figure 9. Simulations for the Gale Crater site. Quantification of the absorption depths for increasing concentration of CH4 for the selected observations in the Gale Crater area.
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Figure 10. Simulations for the Oxia Planum site. Quantification of the absorption depths for increasing concentration of CH4 for the selected observations in the Oxia Planum area.
Figure 10. Simulations for the Oxia Planum site. Quantification of the absorption depths for increasing concentration of CH4 for the selected observations in the Oxia Planum area.
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Figure 11. Simulations for the Nili Fossae site. Quantification of the absorption depths for increasing concentration of CH4 for the selected observations in the Nili Fossae area.
Figure 11. Simulations for the Nili Fossae site. Quantification of the absorption depths for increasing concentration of CH4 for the selected observations in the Nili Fossae area.
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Figure 12. Green: radiance spectrum of featured pixels in the cluster of the frs0002a9b2 image; black: corresponding I/F spectrum. The two spectra show that the absorption feature of approximately 3.3 μm was present in the radiance data and was not caused by the I/F calibration pipeline.
Figure 12. Green: radiance spectrum of featured pixels in the cluster of the frs0002a9b2 image; black: corresponding I/F spectrum. The two spectra show that the absorption feature of approximately 3.3 μm was present in the radiance data and was not caused by the I/F calibration pipeline.
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Figure 13. Comparison between the 3.31 μm feature in a CRISM spectrum and methane spectrum from the National Institute of Standards and Technology (NIST) database. In the CRISM spectrum, the continuum was removed in the range of 3.29 to 3.34 to remove absorption-like bands attributable to signal noise.
Figure 13. Comparison between the 3.31 μm feature in a CRISM spectrum and methane spectrum from the National Institute of Standards and Technology (NIST) database. In the CRISM spectrum, the continuum was removed in the range of 3.29 to 3.34 to remove absorption-like bands attributable to signal noise.
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Figure 14. Comparison of some PAH compounds with an absorption band in one of the investigated CRISM observations.
Figure 14. Comparison of some PAH compounds with an absorption band in one of the investigated CRISM observations.
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Table
Table 1. List of the Mars sites in which methane increases were observed by means of ground telescopes and orbiting spectrometers (the Planetary Fourier Spectrometer and the Tunable Laser Spectrometer). Acronyms: Planetary Fourier Spectrometer (PFS); Cryogenic Near-IR Facility Spectrograph (CSHELL); Infrared Telescope Facility (IRTF); Near Infrared Spectrograph (NIRSPEC, a cross-dispersed echelle spectrograph designed for Keck II); Sample Analysis at Mars-Tunable Laser Spectrometer (SAM-TLS); Trace Gas Orbiter (TGO).
Table 1. List of the Mars sites in which methane increases were observed by means of ground telescopes and orbiting spectrometers (the Planetary Fourier Spectrometer and the Tunable Laser Spectrometer). Acronyms: Planetary Fourier Spectrometer (PFS); Cryogenic Near-IR Facility Spectrograph (CSHELL); Infrared Telescope Facility (IRTF); Near Infrared Spectrograph (NIRSPEC, a cross-dispersed echelle spectrograph designed for Keck II); Sample Analysis at Mars-Tunable Laser Spectrometer (SAM-TLS); Trace Gas Orbiter (TGO).
AreaSensorUTCLs, DegreeSeasonCH4 Mix. Ratio (ppbv)Reference
Mars globalPFSJanuary–May 2004326–327Northern Hemisphere
Spring Equinox		10 ± 5Formisano et al., 2004 [12]
Terra Sabae,
Nili Fossae,
SE Syrtis Major		CSHELL/IRTF, NIRSPEC/Keck-212 January 2003122Northern Hemisphere
Summer		40Mumma et al., 2004, 2009 [9,10]
Gale CraterSAM-TLS3 Mars years All seasonsav. ∼0.41 ± 0.16 Webster et al., 2018 [15]
Gale CraterSAM-TLS16 June 2013336Northern Hemisphere
Winter		6–10;Webster et al., 2015, 2018 [14,15]
PFS 15Giuranna et al., 2019 [19]
Gale CraterSAM-TLS19 June 201941Northern Hemisphere
Spring 		21Moores et al., 2019 [17]
Mars globalTGOApril–August 2018163–234Northern Hemisphere
Autumn Equinox		Upper limit 0.05 Korablev et al., 2019 [13]
Table
Table 2. List of the investigated CRISM observations (frs, frt, atu, hrs, and hrl) and the corresponding Martian season (solar longitude).
Table 2. List of the investigated CRISM observations (frs, frt, atu, hrs, and hrl) and the corresponding Martian season (solar longitude).
AreaCRISM-MRO ObservationUTCSolar Longitude, Ls,
in Degree
Gale Craterfrs0002834613 January 2013243.7
frt0000a09120 February 200834.5
frt000196821 June 2010107.4
hrs0000336a30 November 2006143.2
Oxia Planumfrs0003a89623 February 2016112.8
frs0003152321 July 2014165.1
frt00010fe911 February 2009208
atu00041805 February 2017312
hrl0000a3de4 March 200840.3
hrs000117255 March 2009221.2
Nili Fossaefrs00041a2814 February 2017317.2
frs0002a9b230 July 2013359.6
frs0002adc416 August 20137.7
frs0003993623 December 201585.2
Table
Table 3. List of the pixels that show features in the range of 3.2 μm to 3.4 μm. The pixels belong to clusters, but the x and y coordinates refer to pixels with greater depth. The variables μ and σ are, respectively, the average value and the standard deviation of depth map. Symbol “-” means no absorptions found overcoming the calculated thresholds on depth.
Table 3. List of the pixels that show features in the range of 3.2 μm to 3.4 μm. The pixels belong to clusters, but the x and y coordinates refer to pixels with greater depth. The variables μ and σ are, respectively, the average value and the standard deviation of depth map. Symbol “-” means no absorptions found overcoming the calculated thresholds on depth.
AreaCRISM-MRO ObservationCoordinate of the Deepest Pixel in the ClusterBand CenterDepthNumber of Pixels in the Clusterμc σc Depth
of the Cluster
Gale Craterfrs00028346x355y883.350.02250.009, 0.007
frt0000a091-----
frt00001968x121y1063.350.05750.05, 0.007
hrs0000336a-----
Oxia Planumfrs0003a896x420y1333.290.02460.002, 0.005
frs00031523x459y1653.320.04070.03, 0.013
frt00010fe9x120y1393.310.03250.03, 0.007
atu0004180x345y1723.280.03680.03, 0.007
hrl0000a3de----
hrs00011725x182y83.290.02350.17, 0.003
Nili Fossaefrs00041a28x506y223.370.04260.03, 0.007
frs0002a9b2x47y33.290.045150.044, 0.005
frs0002adc4--- -
frs00039936x135y493.290.01440.013, 0.0005
Table
Table 4. Threshold estimation for each site.
Table 4. Threshold estimation for each site.
AreaCRISM-MRO ObservationNumber of Pixels in Depth MapStandard Deviation on Depth Map (σ)Average (μ)Threshold
μ + 5σ
Gale Craterfrs0002834684,4750.0030.00550.0205
frt0000a091228,6600.0030.0050.02
frt00001968221,4000.0040.0070.027
hrs0000336a51,9400.0020.010.02
Oxia Planumfrs0003a89683,5500.0020.0050.015
frs0003152373,9200.0030.0040.019
frt00010fe9228,9000.0030.0060.021
atu000418091,5750.0030.0030.018
hrl0000a3de112,5180.0040.00370.0237
hrs0001172551,9000.0020.0050.015
Nili Fossaefrs00041a2882,5000.0030.00360.0186
frs0002a9b290,2340.0020.0040.014
frs0002adc487,9200.0020.00360.0136
frs0003993679,7500.0020.0040.014
Table
Table 5. Overview table. Conversion from thresholds at 3.3 μm band depth to lower detection limit of methane concentration, according to PSG simulations.
Table 5. Overview table. Conversion from thresholds at 3.3 μm band depth to lower detection limit of methane concentration, according to PSG simulations.
AreaCRISM-MRO ObservationThreshold
μ + 5σ		Lower Limit of Concentrations
Gale Craterfrs000283460.0205300
frt0000a0910.02350
frt000019680.027600
hrs0000336a0.02400
Oxia Planumfrs0003a896 0.015220
frs000315230.019350
frt00010fe90.021300
atu00041800.018280
hrl0000a3de0.0237320
hrs000117250.015200
Nili Fossaefrs00041a280.0186180
frs0002a9b20.014210
frs0002adc40.0136200
frs000399360.014200
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Manzari, P.; Marzo, C.; Ammannito, E. Investigation of Absorption Bands around 3.3 μm in CRISM Data. Remote Sens. 2022, 14, 5028. https://doi.org/10.3390/rs14195028

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Manzari P, Marzo C, Ammannito E. Investigation of Absorption Bands around 3.3 μm in CRISM Data. Remote Sensing. 2022; 14(19):5028. https://doi.org/10.3390/rs14195028

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Manzari, Paola, Cosimo Marzo, and Eleonora Ammannito. 2022. "Investigation of Absorption Bands around 3.3 μm in CRISM Data" Remote Sensing 14, no. 19: 5028. https://doi.org/10.3390/rs14195028

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Manzari, P., Marzo, C., & Ammannito, E. (2022). Investigation of Absorption Bands around 3.3 μm in CRISM Data. Remote Sensing, 14(19), 5028. https://doi.org/10.3390/rs14195028

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