【論文紹介】
Mid-infrared spectral variability for compositionallysimilar asteroids: Implications for asteroid particle
size distributions
P. Vernazza a, et al., 2010, Icarus鈴木絢子 (CPS)2012年5月31日木曜日

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まとめ๏ 可視・近赤外域でほとんど同じ組成を持つ（ol/[ol+px]）８つのS型小惑星の中間赤外域のスペクトルを比較したらバリエーションが見られた๏ 実は本当に組成が異なるのではなく，表面の粒子サイズが異なるからだろうと解釈（<5µm？）
๏ 実験的に，粒子サイズが変わると中間赤外域のスペクトルが変化することがわかっている [Ramsey and Christensen, 1998]
๏ 中間赤外スペクトルからだけで組成を推定するのは危険だが，組成が同じ (VNIR, アルベド) 小惑星同士の表面状態の比較には使えるかもしれない๏ 粒径を制御したり，宇宙風化の影響を考慮した，良いスペクトルライブラリが必要
2012年5月31日木曜日

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1. イントロ：小惑星の可視・近赤外分光
๏小惑星の可視・近赤外域でのスペクトルは，表面組成を知るのに強力なツール- 可視・近赤外域にケイ酸塩（かんらん石と輝石）の特徴があり- 隕石グループとその母天体の関係を見つけることができる

๏0.4-2.5µm（可視・近赤外）：ケイ酸塩
๏2.9-4.0µm：水，氷，炭酸塩- 小惑星の主成分ではない（<10%）๏8-13µm（中間赤外）：どうか？
2012年5月31日木曜日

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1. イントロ：中間赤外での観測
๏火星：中間赤外のスペクトルを用いて，長石の量を同定した [Milam, et al., 2004]- 可視・近赤外域では，長石の同定は難しい．

๏同様なことを，小惑星にも応用してみる

大竹さんの講義ファイルより本田親寿さんの CPS セミナー資料より
2012年5月31日木曜日

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2. 観測方法とデータの取扱い
๏IRTFで観測- NASA の地上赤外望遠鏡@マウナケア- 0.4-2.5µm で７つの小惑星を観測- 8-14µm で３つの小惑星を観測（パリからリモートで）๏Spitzerのデータも使用- 赤外線宇宙望遠鏡（2003年〜）- 液体ヘリウムで冷却して長波長まで観測できる- 2009年に液体ヘリウムがなくなったが現在も観測中

2012年5月31日木曜日

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3. 結果 > 3.1. 可視光域

802

P. Vernazza et al. / Icarus 207 (2010) 800–809

25143
1685
951
433
364
43
11
7

๏S型に含まれるスペクト
ルの特徴- <0.7µm に，緩やか〜急な赤化の傾き

Fig. 3. Comparison of the IRTF (Mirsi) emissivity spectrum of (7) Iris before thetelluric correction with an Earth’s atmospheric transmission spectrum computedwith ATRAN. The displayed (7) Iris spectrum has been corrected for both thethermal emission and the shape of the observed star. We do not display the error
bars accompanying the shape correction here (they appear in the following figure)to highlight the high signal to noise ratio of our observations. The comparison
shows that the numerous features seen in the (7) Iris spectrum are also seen in the
Earth’s transmission spectrum. This highlights that a simple division by a standard
star observed close in time and airmass to the asteroid observation is simply notenough to remove the telluric features.

- 1µm と 2µm に特徴的な吸Fig. 1. VNIR reflectanceof 7 Iris, 11 Parthenope, 43 Adriane, 433 Eros, 951
図1:spectra
観測したS型小惑星のスペクトル
Gaspra (since we do not have Gaspra’s NIR spectrum we use the mean spectrum of
several Flora family member spectra), 1685 Toro and 25,143 Itokawa as well as the
NIR spectrum of 364 Isara. The NIR portion of the spectra was acquired with the
IRTF; the visible portion of the spectrum was available from SMASS (see Bus andBinzel, 2002a,b). All these objects belong to the S-type class following the Bus and/or the new Bus–DeMeo taxonomy (Bus, 1999; Bus and Binzel, 2002a,b; Demeoet al., 2008).

収．かんらん石と斜方輝石のもの- 1µm を横切って中立〜急なcontinuum の傾きが存在

tion of telluric standards, ATRAN, an atmospheric modeling program developed by Lord (1992), can be used to generate artificial
telluric calibrator spectra at the target’s zenith angle and air mass.
ATRAN models allow tweaking of water vapor overpressure andother atmospheric conditions to produce optimized telluric corrections for each target.
We simulated with the ATRAN model the Earth atmospherictransmission spectrum for each observation at each different air
mass and corrected both the star and the asteroid spectrum bymultiplying their spectrum by the transmission spectrum (thetransmission spectra were binned to the resolving power of Mirsi).
In Fig. 3, we show the spectrum of (7) Iris before the ATRAN correction together with a typical transmission spectrum of the Earthatmosphere. The multiple features that can be seen in Iris’ spec-๏普通コンドライトのスペ
クトルと類似2012年5月31日木曜日

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3. 結果 > 3.1. 可視光域（つづき）

802

P. Vernazza et al. / Icarus 207 (2010) 800–809

25143
1685
951
433
364
43
11
7

๏散乱モデル [Hapke, 1993; Shkeratov etla., 1999] を用いて，かんらん石と斜方輝石の相対量を同定(ol/[ol+px])

Fig. 3. Comparison of the IRTF (Mirsi) emissivity spectrum of (7) Iris before thetelluric correction with an Earth’s atmospheric transmission spectrum computedwith ATRAN. The displayed (7) Iris spectrum has been corrected for both thethermal emission and the shape of the observed star. We do not display the error
bars accompanying the shape correction here (they appear in the following figure)to highlight the high signal to noise ratio of our observations. The comparison
shows that the numerous features seen in the (7) Iris spectrum are also seen in the
Earth’s transmission spectrum. This highlights that a simple division by a standard
Fig. 1. VNIR reflectance spectra of 7 Iris, 11 Parthenope, 43 Adriane, 433 Eros, 951
star observed close in time and airmass to the asteroid observation is simply not
Gaspra (since we do not have Gaspra’s NIR spectrum we use the mean spectrum ofenough to remove the telluric features.
several Flora family member spectra), 1685 Toro and 25,143 Itokawa as well as the804
P. Vernazza et al. / Icarus 207 (2010) 800–809
NIR spectrum of 364 Isara. The NIR portion of the spectra was acquired with the
IRTF; the visible portion of the spectrum was available from SMASS (see Bus andTable2002a,b).
4
Binzel,All these objects belong to the S-type class following the Bus and/tionmid-IRof telluric
between thecompositions
our BusS-typefromthe VNIR andrange. standards, ATRAN, an atmospheric modeling proorComparison
the new Bus–DeMeo
taxonomy(Bus, of1999;
andsample
Binzel,derived
2002a,b;Demeo
et al., 2008).
gramdeveloped
by Lord (1992), can be used to generate artificial
Asteroid
Data referencea[ol/(ol + opx)] % VNIR
[ol/(ol + opx)] % Mid-IR (case b)[ol/(ol + opx)] % Mid-IR (case c)๏どれも 75-80%

図１

telluric calibrator spectra at the target’s zenith angle and air mass.
ATRAN models allow tweaking of water vapor overpressure andother atmosphericconditions to produce optimized
66b|100ctelluric correc7 Iris
S
20 February 2004
76.5
48b|46cc
11 ParthenopeS
13 November 2005
79.5
36 target.
43c
tions for eachc
43 AdrianeS
22 November 2005
76
65
87cEarth atmosphericWe simulatedwith the ATRAN model thebb
364 Isara
03 October 200777
61 |47 (1)55b|41b (1)transmissionb spectrum for each observation atb each different air
58
433 ErosS
17 August 2002
79
37
mass and 49
corrected
both the star and the asteroid
spectrum byb
951 Gaspra
S
79
41b
b
b
multiplying
spectrum (the1685 ToroS
09 March 2005
77.5
26 their spectrum by the transmission
37
transmission
25,143 Itokawa
S
28 March 2001
75
38b spectra were binned to the resolving
43b power of Mirsi).
In Fig. 3, we show the spectrum of (7) Iris before the ATRAN correcS: smass.
2012年5月31日木曜日
tion together with a typical transmission spectrum of the Eartha
For observations reported here, we give the observation date (UT). All near-infrared (NIR) data were obtained using the NASA IRTF at Mauna Kea, Hawaii.
batmosphere. The multiple features that can be seen in Iris’ specWith Spitzer.
V

NIR

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3. 結果 > 3.2. 中間赤外域> 3.2.1. 実験室での測定

๏粉末にした隕石や鉱物の中間赤外域のスペクトルを用いて，組成同定が可能
๏粉体の粒子サイズも，スペクトルの形状に影響がある [e.g., Hunt and Vincent, 1968; Hunt and Logan, 1972; Moersch andChristensen, 1995; Mustard and Hays, 1997]- 粒子サイズが小さくなると，スペクトルの特徴が消える[Mustard and Heys, 1997]- 小惑星の表面粒子サイズは細かい (<50µm) [Dollfus et al.,1977] ので，小惑星の放射スペクトルは featureless だと想像される．

2012年5月31日木曜日

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3. 結果 > 3.2. 中間赤外域> 3.2.1. 実験室での測定(つづき)๏しかし，結果は粒子サイズに依存 [Ramsey andChristensen, 1998]- >60µm のとき，各鉱物のスペクトルの線形な重ね合わせで記述できる．
- 10-20µm ≤ d ≤ 60µm のとき，サイズ分布を正しく入れた適
切な鉱物のスペクトルを使えば，線形重ね合わせ可能．
- <10µm の場合，非線形性が増加．予測不可能．

2012年5月31日木曜日

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NIR spectrum of 364 Isara. The NIR portion of the spectra was acquired with the
IRTF; the visible portion of the spectrum was available from SMASS (see Bus andBinzel, 2002a,b). All these objects belong to the S-type class following the Bus and/or the new Bus–DeMeo taxonomy (Bus, 1999; Bus and Binzel, 2002a,b; Demeoet al., 2008).

3. 結果 > 3.2. 中間赤外域 >3.2.3. 組成解析
๏わずかに違いがある- Spitzer データ：

• Itokawa, Toro: ずっと平ら• Iris, Isara, Eros, Gaspra:• <8.7µm で赤化• >8.7µm では continuum は平らで~10.5µm, ~11.7µm に輝線

803

P. Vernazza et al. / Icarus 207 (2010) 800–809

ons. R is heliocentric distance, D
gle.
Fig. 2. Spitzer emissivity spectra of 7 Iris, 364 Isara, 433 Eros, 951 Gaspra, 1685

dtion of telluric standards, ATRAN, an atmospheric modeling program developed by Lord (1992), can be used to generate artificial
telluric calibrator spectra at the target’s zenith angle and air mass.
ATRAN models allow tweaking of water vapor overpressure andother atmospheric conditions to produce optimized telluric corrections for each target.
We simulated with the ATRAN model the Earth atmospherictransmission spectrum for each observation at each different air
mass and corrected both the star and the asteroid spectrum bymultiplying their spectrum by the transmission spectrum (thetransmission spectra were binned to the resolving power of Mirsi).
In Fig. 3, we show the spectrum of (7) Iris before the ATRAN correction together with a typical transmission spectrum of the Earthatmosphere. The multiple features that can be seen in Iris’ spectrum before the ATRAN correction are retrieved in the Earth transmission spectrum.
After completing the telluric corrections, the quotient was corrected for the stellar spectral slope and features. As noticed by Cohen et al. (1992), a SiO absorption band is present in the stellar
spectra. Thus while the division of the asteroid spectrum by thestandard star spectrum removes the telluric absorptions, it also
introduces stellar features. Finally, in order to produce the final
emissivity for each object we removed the thermal emission fromeach object spectrum. Several thermal emission models exist, fromthe simple STM (Lebofsky et al., 1986) to the refined TPM (Mueller
and Lagerros, 1998; Lagerros, 1998). In the present work, we modeled the thermal emission using the STM model. (The STM fitting
method is well described in Emery et al. (2006a,b).) The final emissivity spectrum was created by dividing the SED by the modeled
thermal continuum.
Lastly, given the uncertainty of the correction of both the telluric absorptions and the stellar spectral shape, we retrieved forcomparison public Spitzer spectra of several S-type asteroids takenwith IRS (InfraRed Spectrograph, Houck et al., 2004) using the
Leopard software (see Table 2). We selected the so-called Basic Calibrated Data (BCD) which is a 2-D output. After background removal from the BCD images, we extracted the 1-D spectra fromthese images. (See Section 3 by Emery et al. (2006a,b) for a detailed
description of the method.) Finally, we removed the thermal emission of each asteroid in order to produce its emissivity (see Table 3
for the STM best-fit parameters for both the IRTF and Spitzer observations). Figs. 2 and 4 show the Spitzer and IRTF spectra after thethermal correction.

AdrianeR (AU)

D (AU)

2.91
2.07
2.07
1.31
1.97
1.14
1.00

2.72
1.90
1.93
0.96
1.27
0.38
0.52

Toro and 25,143 Itokawa created by dividing the measured SED by the bestfit STMa (!)
for each object. Isara was observed twice and we therefore show both spectra.
Itokawa has been observed six times and we just show the data for the first
20.2
observation.
The spectra for the other observing dates are very similar and even29.0
noisier.
28.8
50.6
26.3addition, the infrared backgrounds can change during observaIn
61.6
tions
of target objects, making accurate telluric correction using
75.3

Parthenope

8

Iris

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observed standards difficult. Therefore, in addition to the observa-

2012年5月31日木曜日
Fig. 4. IRTF (Mirsi) emissivity spectra of (7) Iris, (11) Parthenope and (43) Adriane
created (1) by dividing the measured SED by the bestfit STM for each object, (2)- IRTF データ：

• Iris, Parthenope: ずっと平ら =Toro, Itokawa と類似• Adriane: 11-13µm に広い盛り上がり

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3. 結果 > 3.2. 中間赤外域

zza et al. / Icarus 207 (2010) 800–809>3.2.3. 組成解析（つづき）
805

e Spitzer
elt asterthe IRTF
elt aster364 Isara
show anctra ande spectra
elescope

gh smallence of a43) Itokars to bekinds ofra, (433)
ntinuumlm andure doesa. A lowincludes
etely flat
data may

r to haveects disge which
spectra.
splays ao 13 lm.
TF data)ences ford.

๏IRTF と Spitzer での観測の比較

Fig. 5. Comparison between both the MIRSI (IRTF) and Spitzer emissivity spectra
for 7 Iris.

๏8-13µm でほぼ良い一致

found in ordinary chondrite meteorites, namely olivine, low-Ca
pyroxene and feldspar reflectance spectra from ASTER as well as
olivine, low-Ca pyroxene and feldspar emissivity spectra fromthe BED library, iron spectra from the RELAB database and chromite spectra from ASTER. We give a list of the end-members in
the figure captions. For the meteorite spectra, we ran the codefor the following subclasses: ordinary chondrites, carbonaceouschondrites, HEDs and achondrites. The biconical reflectance spectra from the ASTER and RELAB libraries were converted to emissivity by using Kirchoff’s law: 1 " 5r = e (see Lim et al., 2005a,b).
Finally, all emissivity spectra were normalized to unity at a given
wavelength (11 lm).
Figs. 6 and 7 show the fitting results for the (a), (b), and (c) cases
listing the relative abundance of (a) H, L and LL meteorites for OCs,
the relative abundance of CM, CI and CV/CO meteorites for CCs, (b)the relative abundance of olivine and low-Ca pyroxene and (c) the
relative abundance of olivine, low-Ca pyroxene, feldspar, iron and2012年5月31日木曜日
chromite. It does not list the fitting results for the HEDs and achondrites subclasses because in these cases the derived rms was too

๏地上観測でも，宇宙からの観測と同じようなスペクトルが得られることを示した
๏Spitzer は寒剤がなくなったので，今後の地上観測に朗報
113. 結果 > 3.2. 中間赤外域>3.2.3. 組成解析（つづき）

๏中間赤外域 (8-13µm) で同様な結果が出るか調べる- Linear retrieval algorithm [Sprague et al., 2009]- 各鉱物の量のみがフリーパラメータ- 下記３つの組み合わせを用意した• (a) ASTER スペクトルライブラリにある，全ての隕石の反射スペクトル(普通コンドライト，炭素質コンドライト，HED隕石，エコンドライトの４case)• (b) かんらん石と低Ca輝石の ASTER の反射スペクトル / BED ライブラリの放射スペクトル• (c) 普通コンドライトの全ての構成鉱物（かんらん石，低Ca輝石，feldspar）の反射スペクトル (ASTER) / 上記の放射スペクトル (BED ライブラリ)，鉄のスペクトル (RELAB データベース), クロム鉄鉱のスペクトル (ASTER)

2012年5月31日木曜日

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3. 結果 > 3.2. 中間赤外域>3.2.3. 組成解析（つづき）

๏可視・近赤外域 (0.4-2.4µm) の結果を思い出しておくと- ８つの小惑星全てで ol/[ol+opx] が75-80%- スペクトルが似ているのは LL コンドライト

2012年5月31日木曜日

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3. 結果 > 3.2. 中間赤外域
806>3.2.3. 組成解析（つづき）

P. Vernazza et al. / Icarus 207 (2010) 800–809

807

P. Vernazza et al. / Icarus 207 (2010) 800–809

Fig. 7. Mirsi (IRTF) spectra for 7 Iris, 11 Parthenope and 43 Adriane are compared to best fit models computed using two different spectral libraries, namely ASTER and BED.
We indicate the abundance of each end-member as well as the rms of each fit directly on the plot.

図7:IRTF

became saturated, while the restrahlen bands showed continuous
decrease in spectral contrast and some change in the shape ofthe bands with decreasing particle size. The transparency features
showed several important changes with decreasing particle size:
the spectral contrast increased than decreased, the position of
the maximum reflectance of the transparency features shifted systematically to shorter wavelengths, and the symmetry of the features changed.
These important spectral changes observed for small variationsof the grain size may allow an explanation for the spectral differences observed among our S-type sample. While we do expect
the observed objects to have their surfaces covered by small particles (<50 lm, see Dollfus et al., 1977), there is no reason that theyshould have exactly the same distribution of particle sizes on theirsurfaces.
Most significantly, these important spectral changes for small
variations of the grain size may impede the ability to retrieve thecomposition in the mid-IR range. The spectral libraries such ASTER
and BED provide spectra for grain size intervals that are quite large(0–30 lm, 0–60 lm, 0–75 lm and 75–250 lm for ASTER and
Fig. 6. Spitzer spectra for 7 Iris, 364 Isara, 433 Eros, 951 Gaspra and 1685 Toro are compared to best fit models computed using two different spectral 0–25
libraries,
namely
ASTER
lm,
25–63
lm, 63–125 lm and 125–250 lm for BED). Thereand BED. We do not show the compositional fit to Itokawa’s spectrum due to the poor SNR of its spectrum. We indicate the abundance of each end-member as well as the rms
fore, it is very likely that the grain size of the laboratory samplesof each fit directly on the plot. For the fit using both olivine and low-Ca pyroxene spectra we used the following end-members (28 in total): olivin5f (ASTER), olivin6f (ASTER),
will not match the average grain size present on the asteroid
olivin7f (ASTER), olivin8f (ASTER), olivi10f (ASTER), olivi11f (ASTER), olivi12f (ASTER), olivi13f (ASTER), olivi10p (ASTER), olivi11c (ASTER), olivi12c (ASTER), olivi13c (ASTER),
surfaces which(BED),
could explain the wrong inferred abundances forenstat1f (ASTER), enstat1s (ASTER), enstat1c (ASTER), hypers1f (ASTER), emiss_olivine180c0_25 (BED), emiss_olivine180c25_63 (BED), emiss_olivine180c63_125
olivine and pyroxene.
emiss_olivine180c125_250 (BED), emiss_enstatite180c0_25 (BED), emiss_enstatite180c25_63 (BED), emiss_enstatite180c63_125 (BED), emiss_enstatite180c125_250(BED), For the interpretation of the actual S-type
emiss_hyperstene_a180c0_25 (BED), emiss_hyperstene_a180c25_63 (BED), emiss_hyperstene_b180c0_25 (BED), emiss_hyperstene_b180c25_63 (BED).
For
the fit using
mid-IR
spectra,a preparation of well chosen minerals such olivine
olivine, low-Ca pyroxene, feldspar, iron and chromite spectra we used the olivine and pyroxene spectra listed above as well as: labrad1f.txt (ASTER),
labrad1c.txt
andpyroxene(ASTER),
into several particle size separates of 5-lm intervals
orthoc3f.txt (ASTER), orthoc3c.txt (ASTER), albite1f.txt (ASTER), albite1c.txt (ASTER), emiss_albite180c0_25.txt (BED), emiss_anorthite180c0_25.txt(BED),
lm to 50 lm could certainly help improving the fitting refrom<5 emiss_bytow-

図6:Spitzer

2012年5月31日木曜日

ratio could be different between the VNIR and MIR because eachwavelength range is sensing different surface components (orsensing them with different strengths). It is precisely to test thispossibility that we performed the fitting of case c (including all
the minerals that are present in ordinary chondrite meteorites).
While we find that there is some variation in the ol/(ol + px) value
derived from the mid-IR spectra between cases b and c, the variation is not enough to explain the discrepancy between the VNIRand MIR analyses.
Finally, we would like to recall one clear limitation of the technique employed here, namely the fact that we did not consider the
spectral effects of space weathering processes when fitting themid-IR asteroid spectra (see Chapman (2004) for a review on theseprocesses). While their spectral effects are pretty well characterized for the VNIR range (true for OC-like material), little has been
published yet concerning their effects over the mid-IR range. Brucato et al. (2004) reported the results of ion irradiation experiments on forsterite; they collected mid-IR spectra before andafter irradiation. They found that the effect in the mid-IR is to begin
to ‘‘amorphousize” the surface. This makes sense, since space
weathering is thought to create glassy coating (with the embedded
nanophase iron). So, to first order, the effect would be to simply reduce the spectral contrast of the restrahlen bands. Besides this paper, no other work related to this topic has been published yet. We
therefore encourage researchers performing space weatheringexperiments to not only limit their spectral measurements (before
and after irradiation) to the VNIR range but to extend their measurements to the mid-IR range.

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3. 結果 > 3.2. 中間赤外域>3.2.3. 組成解析（つづき）

๏図6(b), 図6(c), 図7(b), 図7(c) それぞれで，
ol/[ol+px] が合うべきだが，全然合わない．
๏図6(b), 図7(b) で，ol, px 以外の要素も合わない．例えば Feldspar（Gaspraで 4%，Irisで33%）
๏図6(a), 図7(a) では，LL コンドライトに近くないという結果．
๏この結果だけの結論：SN比が良くても中間赤外域のスペクトルを使って組成を同定することはできない2012年5月31日木曜日

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4. 議論๏ 中間赤外域での組成のバリエーション- 実際にバリエーションがあるのではなくて，組成同定が困難になる要因（ex. 粒子サイズ，宇宙風化）があるからだろう [Hunt and Logan,
1972; Mustard and Hays, 1997; Ramsey and Christensen, 1998]

๏ 粒径が小さくなると，スペクトルの様々な特徴が消えた
り中心波長が短波長側に移動したりすることが知られている
๏ ASTER と BEDのライブラリにあるスペクトルは，粒径を粉で測るべき๏ 中間赤外域での宇宙風化作用の影響はあまり研究されていない [cf. Brucato et al., 2004]2012年5月31日木曜日

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