A&A 565, A103 (2014)
DOI:
10.1051
/
0004-6361
/
201322612
c
ESO 2014
Astronomy
&
Astrophysics
Planck
intermediate results. XV. A study of anomalous microwave
emission in Galactic clouds
Planck Collaboration: P. A. R. Ade
77
, N. Aghanim
53
,M.I.R.Alves
53
,M.Arnaud
66
, F. Atrio-Barandela
18
, J. Aumont
53
, C. Baccigalupi
76
,
A. J. Banday
82
,
10
,R.B.Barreiro
60
, E. Battaner
83
, K. Benabed
54
,
80
, A. Benoit-Lévy
24
,
54
,
80
,J.-P.Bernard
82
,
10
,M.Bersanelli
32
,
46
,P.Bielewicz
82
,
10
,
76
,
J. Bobin
66
, A. Bonaldi
62
,J.R.Bond
9
, J. Borrill
13
,
78
, F. R. Bouchet
54
,
80
, F. Boulanger
53
,C.Burigana
45
,
30
, J.-F. Cardoso
67
,
1
,
54
,S.Casassus
81
,
A. Catalano
68
,
65
, A. Chamballu
66
,
15
,
53
,X.Chen
52
,H.C.Chiang
26
,
7
,L.-Y.Chiang
56
, P. R. Christensen
73
,
35
,D.L.Clements
51
, S. Colombi
54
,
80
,
L. P. L. Colombo
23
,
61
, F. Couchot
64
, B. P. Crill
61
,
74
, F. Cuttaia
45
,L.Danese
76
,R.D.Davies
62
,R.J.Davis
62
,P.deBernardis
31
,
A. de Rosa
45
, G. de Zotti
41
,
76
, J. Delabrouille
1
, F.-X. Désert
50
, C. Dickinson
62
,
,J.M.Diego
60
,S.Donzelli
46
,O.Doré
61
,
11
,X.Dupac
38
,
T. A. Enßlin
70
,H.K.Eriksen
58
, F. Finelli
45
,
47
, O. Forni
82
,
10
, E. Franceschi
45
,S.Galeotta
43
, K. Ganga
1
,R.T.Génova-Santos
59
, T. Ghosh
53
,
M. Giard
82
,
10
, J. González-Nuevo
60
,
76
,K.M.Górski
61
,
84
,A.Gregorio
33
,
43
,
49
, A. Gruppuso
45
,F.K.Hansen
58
,D.L.Harrison
57
,
63
,G.Helou
11
,
C. Hernández-Monteagudo
12
,
70
,S.R.Hildebrandt
11
,E.Hivon
54
,
80
, M. Hobson
6
, A. Hornstrup
16
,A.H.Ja
ff
e
51
,T.R.Ja
ff
e
82
,
10
,W.C.Jones
26
,
E. Keihänen
25
, R. Keskitalo
21
,
13
, R. Kneissl
37
,
8
, J. Knoche
70
, M. Kunz
17
,
53
,
3
, H. Kurki-Suonio
25
,
40
, A. Lähteenmäki
2
,
40
, J.-M. Lamarre
65
,
A. Lasenby
6
,
63
,C.R.Lawrence
61
,R.Leonardi
38
, M. Liguori
29
, P. B. Lilje
58
, M. Linden-Vørnle
16
, M. López-Caniego
60
, J. F. Macías-Pérez
68
,
B. Ma
ff
ei
62
,D.Maino
32
,
46
, N. Mandolesi
45
,
5
,
30
,D.J.Marshall
66
,P.G.Martin
9
, E. Martínez-González
60
,S.Masi
31
,M.Massardi
44
,S.Matarrese
29
,
P. Mazzotta
34
, P. R. Meinhold
27
,A.Melchiorri
31
,
48
,L.Mendes
38
, A. Mennella
32
,
46
, M. Migliaccio
57
,
63
, M.-A. Miville-Deschênes
53
,
9
,A.Moneti
54
,
L. Montier
82
,
10
, G. Morgante
45
, D. Mortlock
51
, D. Munshi
77
,P.Naselsky
73
,
35
,F.Nati
31
,P.Natoli
30
,
4
,
45
, H. U. Nørgaard-Nielsen
16
, F. Noviello
62
,
D. Novikov
51
, I. Novikov
73
,C.A.Oxborrow
16
,L.Pagano
31
,
48
,F.Pajot
53
, R. Paladini
52
, D. Paoletti
45
,
47
, G. Patanchon
1
,T.J.Pearson
11
,
52
,
M. Peel
62
, O. Perdereau
64
,F.Perrotta
76
, F. Piacentini
31
,M.Piat
1
,E.Pierpaoli
23
, D. Pietrobon
61
, S. Plaszczynski
64
, E. Pointecouteau
82
,
10
,
G. Polenta
4
,
42
, N. Ponthieu
53
,
50
,L.Popa
55
,G.W.Pratt
66
, S. Prunet
54
,
80
, J.-L. Puget
53
, J. P. Rachen
20
,
70
,R.Rebolo
59
,
14
,
36
,W.Reich
71
,
M. Reinecke
70
, M. Remazeilles
62
,
53
,
1
,C.Renault
68
, S. Ricciardi
45
, T. Riller
70
, I. Ristorcelli
82
,
10
, G. Rocha
61
,
11
,C.Rosset
1
, G. Roudier
1
,
65
,
61
,
J. A. Rubiño-Martín
59
,
36
, B. Rusholme
52
, M. Sandri
45
,G.Savini
75
,D.Scott
22
,L.D.Spencer
77
, V. Stolyarov
6
,
63
,
79
, D. Sutton
57
,
63
,
A.-S. Suur-Uski
25
,
40
, J.-F. Sygnet
54
,J.A.Tauber
39
, D. Tavagnacco
43
,
33
, L. Terenzi
45
,C.T.Tibbs
52
,L.To
ff
olatti
19
,
60
,M.Tomasi
46
, M. Tristram
64
,
M. Tucci
17
,
64
, L. Valenziano
45
, J. Valiviita
40
,
25
,
58
,B.VanTent
69
,J.Varis
72
, L. Verstraete
53
,P.Vielva
60
, F. Villa
45
,B.D.Wandelt
54
,
80
,
28
,
R. Watson
62
, A. Wilkinson
62
,N.Ysard
25
,D.Yvon
15
, A. Zacchei
43
, and A. Zonca
27
(A
ffi
liations can be found after the references)
Received 5 September 2013
/
Accepted 19 February 2014
ABSTRACT
Anomalous microwave emission (AME) is believed to be due to electric dipole radiation from small spinning dust grains. The aim of this paper is
a statistical study of the basic properties of AME regions and the environment in which they emit. We used WMAP and
Planck
maps, combined
with ancillary radio and IR data, to construct a sample of 98 candidate
AME sources, assembling SEDs for each s
ource using apert
ure photometry
on 1
◦
-smoothed maps from 0.408 GHz up to 3000 GHz. Each spectrum is fitted w
ith a simple model of free-free, synchrotron (where necessary),
cosmic microwave background (CMB), thermal dust, and spinning dust components. We find that 42 of the 98 sources have significant (
>
5
σ
)
excess emission at frequencies between 20 and 60 GHz. An analysis of the
potential contribution of optically thick free-free emission from ultra-
compact H
ii
regions, using IR colour criteria, reduces the significant AME sample to 27 regions. The spectrum of the AME is consistent with
model spectra of spinning dust. Peak frequencies are in the range 20
−
35 GHz except for the California nebula (NGC 1499), which appears to have
a high spinning dust peak frequency of (50
±
17) GHz. The AME regions tend to be more spatially extended than regions with little or no AME.
The AME intensity is strongly co
rrelated with the sub-millimetre
/
IR flux densities and comparable to previous AME detections in the literature.
AME emissivity, defined as the ratio of AME to dust optical depth, varies by an order of magnitude for the AME regions. The AME regions tend
to be associated with cooler dust in the range 14
−
20 K and an average emissivity index,
β
d
,of
+
1.8, while the non-AME regions are typically
warmer, at 20
−
27 K. In agreement with previous studies, the AME emissivity appears to decrease with increasing column density. This supports
the idea of AME originating from small grains that are known to be depleted in dense regions, probably due to coagulation onto larger grains. We
also find a correlation between the AME emissivity (and to a lesser degree the spinning dust peak frequency) and the intensity of the interstellar
radiation field,
G
0
. Modelling of this trend suggests that both radiative and collisi
onal excitation are important for t
he spinning dus
t emission. The
most significant AME regions tend to have relatively less i
onized gas (free-free emission), a
lthough this could be a selection e
ff
ect. The infrared
excess, a measure of the heating of dust associated with H
ii
regions, is typically
>
4 for AME sources, indicating that the dust is not primarily
heated by hot OB stars. The AME regions are associated with known dark nebulae and have higher 12
μ
m
/
25
μ
m ratios. The emerging picture is
that the bulk of the AME is coming from the polycyclic aromatic hydrocarbons and small dust grains from the colder neutral interstellar medium
phase.
Key words.
HII regions – radiation mechanisms: gener
al – radio continuum: I
SM – submillimeter: ISM
Corresponding author: C. Dickinson,
e-mail:
clive.dickinson@manchester.ac.uk
1. Introduction
Anomalous microwave emission (AME) has been observed in
a few directions of the Galaxy and is an important foreground
Article published by EDP Sciences
A103, page 1 of
28
A&A 565, A103 (2014)
for the cosmic microwave background (CMB) (
Kogut et al.
1996
;
Leitch et al. 1997
;
Finkbeiner et al. 2002
;
Finkbeiner
2004
;
de Oliveira-Costa et al. 2004
;
Dobler & Finkbeiner 2008
;
Miville-Deschênes et al. 2008
;
Gold et al. 2011
). There is strong
evidence, particularly in the Perseus and
ρ
Ophiuchi clouds
(
Watson et al. 2005
;
Casassus et al. 2008
;
Planck Collaboration
XX 2011
), that AME is due to electric dipole radiation from
small spinning dust grains. Along these sight lines, there is
highly significant excess emission above free-free, synchrotron,
CMB, and thermal dust in the frequency range 10
−
100 GHz.
The spectral energy distributions (SEDs) are peaked at about
30 GHz, and can be fitted by physically-motivated theoretical
models of spinning dust (
Draine & Lazarian 1998
;
Ali-Haïmoud
et al. 2009
;
Hoang et al. 2010
,
2011
). AME has been detected
in H
ii
regions (
Dickinson et al. 2006
,
2007
,
2009
;
Todorovi
́
c
et al. 2010
), dust clouds (
Casassus et al. 2006
,
2008
;
Scaife et al.
2009
), a supernova remnant (
Scaife et al. 2007
), and in one ex-
ternal galaxy (
Murphy et al. 2010a
;
Scaife et al. 2010b
). There is
also evidence for AME in the di
ff
use emission at high Galactic
latitudes (
Peel et al. 2012
;
Macellari et al. 2011
;
Ghosh et al.
2012
).
Definitive evidence for spinning dust was provided by
Planck Collaboration XX
(
2011
). Accurate SEDs of the Perseus
and
ρ
Ophiuchi clouds were easily fitted by a physically mo-
tivated model for the clouds, including spinning dust compo-
nents associated with the atomic and molecular phases of the
interstellar medium (ISM). The model was found to be an ex-
cellent fit with physical parameters that were reasonable for
these regions.
Planck Collaboration XXI
(
2011
) applied an in-
version technique to separate the various contributions of the
ISM in Galactocentric rings along the Galactic plane and found
that 25
±
5% of the 30 GHz emission comes from AME and was
consistent with spinning dust associated with atomic and molec-
ular gas but not with the ionized phase. Component separation
of the di
ff
use emission at intermediate latitudes in the southern
Gould Belt region (
Planck Collaboration Int. XII 2013
) revealed
an AME component consistent with spinning dust emitting at a
peak frequency of (25
.
5
±
1
.
5) GHz (in flux density units), com-
patible with plausible values for the local density and radiation
field.
To date there has been no detailed study of AME in a rea-
sonable sample of sources.
Dickinson et al.
(
2007
) observed
six southern H
ii
regions with the Cosmic Background Imager
at 31 GHz and found tentative evidence for excess emission
from the RCW49 complex.
Scaife et al.
(
2008
) observed a sam-
ple of 16 compact H
ii
regions at 15 GHz with the Arcminute
Microkelvin Imager (AMI) and found no evidence for excess
emission; the spectrum was consistent with optically thin free-
free emission from warm ionized gas.
Todorovi
́
cetal.
(
2010
)
surveyed the Galactic plane at longitudes 27
◦
≤
l
≤
46
◦
with
the Very Small Array (VSA) at 33 GHz and found statistical ev-
idence for AME in nine regions, but with an emissivity relative
to 100
μ
m brightness that was 30
−
50% of the average high lati-
tude value.
In this paper, we have assembled a sample of 98 Galactic
clouds selected at
Planck
1
frequencies to investigate their SEDs
and constrain the contribution of AME. Due to the large beam
1
Planck
(
http://www.esa.int/Planck
) is a project of the
European Space Agency (ESA) with instruments provided by two sci-
entific consortia funded by ESA member states (in particular the lead
countries France and Italy), with contributions from NASA (USA) and
telescope reflectors provided by a collaboration between ESA and a sci-
entific consortium led and funded by Denmark.
size of the lowest WMAP
/
Planck
channels and the low fre-
quency radio data, there is sometimes a mix of sources within
the beam. Many of the sources can be classed as di
ff
use H
ii
re-
gions, although we have found a few AME sources with no ob-
vious associated H
ii
region and very weak free-free emission.
Many of the regions are in large star-forming complexes, which
at 1
◦
resolution contain many individual sources. These are of-
ten located in the vicinity of molecular clouds, which produce
strong thermal dust emission. Nevertheless, combining
Planck
data with ancillary radio and far-infrared data we assemble their
SEDs from 0.408 GHz to 5000 GHz. We fit the SEDs with a sim-
ple model of free-free, synchrotron (where appropriate), thermal
dust, CMB, and AME (spinning dust) components to determine
whether there is evidence for AME at frequencies 20
−
60 GHz
and if so, if it agrees with spinning dust models. For the most
significant (
≥
5
σ
) AME detections, we investigate the observa-
tional properties of these regions and compare them with each
other and with regions that do not show strong AME. In particu-
lar, we would like to distinguish AME and “non-AME” regions
using observational and physical properties. This is the first sta-
tistical study of AME regions to date.
In Sect.
2
we describe the
Planck
and ancillary data used in
our analysis. Section
3
describes the sample selection, aperture
photometry, and mode
l-fitting. Section
4
presents the results of
the quantification of AME in these sources. Section
5
investi-
gates the correlation of AME with source properties. Section
6
gives a brief discussion and conclusions.
2. Data
2.1. Planck data
Planck
(
Tauber et al. 2010
;
Planck Collaboration I 2011
)is
the third generation space mission to measure the anisotropy
of the CMB. It observes the sky in nine frequency bands cov-
ering 30
−
857 GHz with high sensitivity and angular resolution
from 31
to 5
. The Low Frequency Instrument (LFI;
Mandolesi
et al. 2010
;
Bersanelli et al. 2010
;
Mennella et al. 2011
)cov-
ers the 30, 44, and 70 GHz bands with amplifiers cooled to
20 K. The High Frequency Instrument (HFI;
Lamarre et al.
2010
;
Planck HFI Core Team 2011a
) covers the 100, 143, 217,
353, 545, and 857 GHz bands with bolometers cooled to 0.1 K.
Polarization is measured in all but the highest two bands (
Leahy
et al. 2010
;
Rosset et al. 2010
). A combination of radiative
cooling and three mechanical c
oolers produces the tempera-
tures needed for the detectors and optics (
Planck Collaboration
II 2011
). Two data processing centers (DPCs) check and cali-
brate the data and make maps of the sky (
Planck HFI Core Team
2011b
;
Zacchei et al. 2011
).
Planck
’s sensitivity, angular reso-
lution, and frequency coverage make it a powerful instrument
for Galactic and extragalactic astrophysics as well as cosmol-
ogy. Early astrophysics results are given in
Planck Collaboration
VIII
−
XXVI
2011
, based on data taken between 13 August 2009
and 7 June 2010. Intermediate astrophysics results are now be-
ing presented in a series of papers based on data taken between
13 August 2009 and 27 November 2010.
In this paper we use
Planck
data from the 2013 distri-
bution of released products (
Planck Collaboration I 2014
),
based on data acquired during the “nominal” operations pe-
riod from 13 August 2009 to 27 November 2010, and avail-
able from the
Planck
Legacy Archive
2
. Specifically, we use the
nine temperature maps summarized in Table
1
.Wealsousea
2
http://www.sciops.esa.int/index.php?
project=planck\&page=Planck_Legacy_Archive
A103, page 2 of
28
Planck Collaboration: A study of AME in Galactic clouds
Table 1.
Sources of the datasets used in this paper, as well as centre frequencies, angular resolutions, and references.
Frequency
Telescope
/
Survey
[GHz]
Resolution
Coverage
Reference
Haslam .........................
0.408
51.
0Fullsky
Haslam et al.
(
1982
)
Reich ..........................
1.42
35.
4Fullsky
Reich
(
1982
);
Reich & Reich
(
1986
);
Reich et al.
(
2001
)
Jonas...........................
2.3
20.
0
Southern sky
Jonas et al.
(
1998
)
WMAP9-year....................
22.8
51.
3
a
Full sky
Bennett et al.
(
2013
)
Planck
..........................
28.4
32.
3Fullsky
Planck Collaboration I
(
2014
)
WMAP9-year....................
33.0
39.
1
a
Full sky
Bennett et al.
(
2013
)
WMAP9-year....................
40.7
30.
8
a
Full sky
Bennett et al.
(
2013
)
Planck
..........................
44.1
27.
1Fullsky
Planck Collaboration I
(
2014
)
WMAP9-year....................
60.7
21.
1
a
Full sky
Bennett et al.
(
2013
)
Planck
..........................
70.4
13.
3Fullsky
Planck Collaboration I
(
2014
)
WMAP9-year....................
93.5
14.
8
a
Full sky
Bennett et al.
(
2013
)
Planck
..........................
100
9.
7Fullsky
Planck Collaboration I
(
2014
)
Planck
..........................
143
7.
3Fullsky
Planck Collaboration I
(
2014
)
Planck
..........................
217
5.
0Fullsky
Planck Collaboration I
(
2014
)
Planck
..........................
353
4.
8Fullsky
Planck Collaboration I
(
2014
)
Planck
..........................
545
4.
7Fullsky
Planck Collaboration I
(
2014
)
Planck
..........................
857
4.
3Fullsky
Planck Collaboration I
(
2014
)
COBE-DIRBE . . . . . . . . . . . . . . . . . . . .
1249
37.
1Fullsky
Hauser et al.
(
1998
)
COBE-DIRBE . . . . . . . . . . . . . . . . . . . .
2141
38.
0Fullsky
Hauser et al.
(
1998
)
COBE-DIRBE . . . . . . . . . . . . . . . . . . . .
2997
38.
6Fullsky
Hauser et al.
(
1998
)
IRAS (IRIS) Band 4 (100
μ
m) . . . . . . . . .
3000
4.
7
Near-full sky
Miville-Deschênes & Lagache
(
2005
)
IRAS (IRIS) Band 3 (60
μ
m) . . . . . . . . . .
5000
3.
6
Near-full sky
Miville-Deschênes & Lagache
(
2005
)
IRAS (IRIS) Band 2 (25
μ
m)..........
12000
3.
5
Near-full sky
Miville-Deschênes & Lagache
(
2005
)
IRAS (IRIS) Band 1 (12
μ
m)..........
25000
3.
5
Near-full sky
Miville-Deschênes & Lagache
(
2005
)
Spitzer
IRAC
/
MIPS ................
8,24
μ
m2
,6
Partial
Fazio et al.
(
2004
);
Rieke et al.
(
2004
)
Notes.
(
a
)
We use the symmeterized, 1
◦
-smoothed version.
CMB-subtracted version for testing the robustness of the de-
tections, using the
SMICA
CMB map (
Planck Collaboration XII
2014
). We use the standard conversion factors from CMB to
Rayleigh-Jeans (RJ) units and updated colour corrections de-
scribed in
Planck Collaboration I
(
2014
). The
Planck
bands
centred at 100 and 217 GHz are known to be contaminated by
CO lines. We corrected these channels using the
Dame et al.
(
2001
) integrated CO map smoothed to 1
◦
resolution and scaled
with the conversion factors described in
Planck Collaboration
XIII
(
2014
); however, for some sources, we still see discrepan-
cies with the spectral model at the
>
10% level. We therefore
did not include these two channels in our fitting of the spectral
model. The CO contamination in the 353 GHz channel is small,
typically
<
1% (
Planck Collaboration XIII 2014
),andwedonot
see significant deviations in our SEDs. Therefore, no correction
was made for CO lines in the 353 GHz band.
Although we limit ourselves to bright Galactic regions with
typical flux densities at 30 GHz far greater than 10 Jy, at 1
◦
an-
gular scales the integrated flux density of CMB fluctuations
can be 10 Jy or more at 100 GHz, a significant fraction of
the total flux density of some of the sources in our sample.
CMB-subtracted maps would, in principle, be most appropriate
for our analysis. However, in bright regions near the Galactic
plane, significant foreground residuals remain in the CMB maps
produced by the
Planck
component separation codes in 2013
(
Planck Collaboration XII 2014
), which used only
Planck
data
and frequencies for separation. These regions can be masked for
cosmological work, but they are precisely the regions that we
need here. Investigations comparing CMB-subtracted with non-
CMB-subtracted maps revealed biases in the plane at the level
of 10
−
15%. Furthermore, incorrect subtraction, particularly at
frequencies near 100 GHz, resulted in high
χ
2
values for some
SEDs, and poorly fitted thermal dust components. We therefore
use the CMB-subtracted maps only for finding regions of AME,
and use non-CMB-subtracted maps for the photometric analy-
sis, where we fit for a CMB component in the spectrum of each
source, using the full data available in Table
1
(see Sect.
2.2
). In
this way we do not bias the flux densities (due to the component
separation process), and more im
portantly, we can characterize
and propagate the uncertainty due to the CMB fluctuation. The
AME amplitudes from both datasets agree within a fraction of
the uncertainty for the majority of sources. In the future,
Planck
component separation will also make use of many of the external
datasets listed in Table
1
, and it may be possible to subtract the
CMB directly.
2.2. Ancillary data
We use a range of ancillary data to allow the SEDs to be
determined from radio (around 1 GHz) to far-infrared (around
3000 GHz). All ancillary data are summarized, along with the
Planck
data, in Table
1
. These data have been smoothed to a
common resolution of 1
◦
since some of the maps have only
slightly higher resolution than this. The smoothing also reduces
the e
ff
ects of any residual beam asymmetry in some cases, e.g.,
WMAP and
Planck
, where non-circular beams vary across the
map.
We analysed the northern sky survey at 12–18 GHz from
the COSMOSOMAS experiments (
Gallegos et al. 2001
);
however, due to the filtering of emission on large an-
gular scales and large intrinsic beam width, the majority
of the sources were strongly a
ff
ected by negative filtering
A103, page 3 of
28
A&A 565, A103 (2014)
artefacts from neighbouring bright sources. The exceptions were
G160.26
−
18.62 and G173.6
+
2.8, which were previously re-
ported by
Planck Collaboration XX
(
2011
). We therefore did not
consider further the COSMOSOMAS data in our analysis.
In the following sections, we describe the ancillary data in
more detail.
2.2.1. Radio surveys
Data at low frequencies (around 1 GHz) are important for ex-
cluding regions with synchrotron emission, and for estimating
the level of free-free emission. Ideally, we would have sev-
eral frequency channels in the range 1
−
10 GHz; however, no
large area surveys exist above 2.3 GHz, except for higher reso-
lution surveys that do not retain large-angular-scale information.
We therefore use the three well-known surveys at 0.408, 1.42,
and 2.326 GHz.
The all-sky survey of
Haslam et al.
(
1982
) at 0.408 GHz is
widely used as a tracer of synchr
otron emission at high Galactic
latitudes; however, it also contains strong free-free radiation
from the Galactic plane and from H
ii
regions, where the free-
free typically dominates over synchrotron emission even at these
lower frequencies.
A number of di
ff
erent versions of the 0.408 GHz map are
available. The most widely used is the NCSA
3
destriped and des-
ourced version available on the LAMBDA website
4
at an angular
resolution of 1
◦
. This map has been Fourier filtered to remove
large-scale striations, and bright sources have been subtracted,
including many of the bright H
ii
regions. Since we want to re-
tain all the sources for this work, we use a less-processed ver-
sion of the map
5
at 51
resolution that was originally sampled
in a 2D Cartesian projection with 0.
◦
33
×
0.
◦
33 square pixels
and B1950 coordinate frame. This version retains all the bright
compact sources, although striations are much more visible by
eye. However, at low latitudes and in bright regions, the stria-
tions are negligible compared to the sky signal. This map was
regridded into the
HEALPix
format (
Górski et al. 2005
)usinga
procedure that computes the surface intersection between indi-
vidual pixels of the survey with the intersecting
HEALPix
pixels
(see Appendix A of
Paradis et al. 2012a
). After smoothing the
resulting map with a 31.
6 FWHM Gaussian kernel to bring it
to 1
◦
resolution, this new map gave results more consistent with
the 1.42 and 2.326 GHz maps.
The Reich et al. full-sky 1.42 GHz map (
Reich 1982
;
Reich
& Reich 1986
;
Reich et al. 2001
)has36
resolution, and the
Jonas et al.
(
1998
) 2.326 GHz map of the southern hemisphere
has 20
resolution. These have been destriped but not source-
subtracted. Although the 2.326 GHz map covers up to
+
15
◦
,we
do not use declinations
>
+
10
◦
because the smoothing operation
a
ff
ects the edges of the map.
The 0.408 GHz map is formally calibrated on angular scales
of 5
◦
by comparison with the 404 MHz survey of
Pauliny-Toth
&Shakeshaft
(
1962
), while the 1.42 GHz and 2.326 GHz maps
are tied to absolute sky horn measurements by
We b s t e r
(
1974
)
and
Bersanelli et al.
(
1994
), respectively. Our study is at 1
◦
reso-
lution, with some regions being extended to 2–3
◦
. Therefore one
would expect the brightness temperature (and thus flux density)
3
National Center for Supercomputing Applications (NCSA), located
at the University of Illinois at Urbana-Champaign;
http://www.ncsa.
illinois.edu
4
http://lambda.gsfc.nasa.gov/
5
Available from the Bonn Survey Sampler webpage
http://www.
mpifr-bonn.mpg.de/survey.html
to be under-estimated for many of our sources. The maximum
correction factor is given by the full-beam to main-beam ratio,
which quantifies the power in the full beam (including sidelobes)
compared to the main beam. The la
rgest correction factor we ap-
plied is 1.55 for the Reich et al. 1.42 GHz survey, based on com-
parisons with bright calibrator sources. We did not make any
corrections to the 0.408 and 2.326 GHz maps, since they were
found to be consistent to within 10% of the 1.4 GHz data for the
majority of the sources in our sample and for bright extragalac-
tic sources. We also note that the positional accuracy of these
maps, particularly the 0.408 GHz map, is not particularly good.
Visual inspection of the maps suggests inconsistencies of bright
sources at the level of up to 15
at 0.408 GHz. For our analysis,
however, this is not likely to be a major source of error, since our
integration aperture has a diameter of 2
◦
.
We assumed a 10% uncertainty in the radio data at all three
frequencies. For the 408 MHz map, which has striations, we
added an additional 3.8 Jy uncertainty corresponding to the base-
line uncertainty of
±
3K (
Haslam et al. 1982
)at1
◦
angular
scales. This is required to bring the
χ
2
value to within acceptable
levels for some sources. This additional uncertainty is not always
required for sources in our sample, and we find, in fact, that we
overestimated our uncertainties in many cases (see Sect.
4.4
).
2.2.2. WMAP
WMAP 9-year data are included in our analysis (
Bennett et al.
2013
). The data span 23 to 94 GHz and thus complement
Planck
data, particularly the
K
-band (22.8 GHz) channel. The
1
◦
-smoothed maps available from the LAMBDA website are
used. We apply colour corrections to the central frequencies us-
ing the recipe described by
Bennett et al.
(
2013
); the local spec-
tral index across each band is calculated using the best-fitting
model (see Sect.
3.5
). This does not exactly take into account
curvature of the spectrum, but is a good approximation given
that the colour corrections are typically a few percent. For the
majority of sources studied in this paper we are not limited
by instrumental noise and we assume a 3% overall calibration
uncertainty.
2.2.3. Submm/infrared data
To sample the peak of the blackbody curve for temperatures
greater than 15 K, we include the COBE-DIRBE data at 240
μ
m
(1249 GHz), 140
μ
m (2141 GHz), and 100
μ
m (2997 GHz). The
DIRBE data are the Zodi-Subtracted Mission Average (ZSMA)
maps (
Hauser et al. 1998
) regridded into the
HEALPix
format
using the same procedure as used for the 408 MHz map de-
scribed in Sect.
2.2.1
. Colour corrections are applied as de-
scribed in the DIRBE explanatory supplement version 2.3. Data
at higher frequencies are not included in the spectral fits, since
they are dominated by transien
tly heated grains not in ther-
mal equilibrium with the interstellar radiation field and there-
fore not easily modelled by a single modified blackbody curve.
Furthermore, at wavelengths
40
μ
m the spectrum contains
many emission
/
absorption lines, whi
ch complicates the mod-
elling. For the statistical comparison, we also include the shorter
wavelengths of DIRBE band 7 (4995 GHz) and the IRAS 12
μ
m
(25 000 GHz) and 25
μ
m (12 000 GHz) bands. We use the IRIS
maps of
Miville-Deschênes & Lagache
(
2005
), which have had
bright sources and a model of zodiacal light removed. Residuals
from zodiacal-light subtractio
n are known to be an issue at
wavelengths shorter than about 25
μ
m, but are not expected
A103, page 4 of
28
Planck Collaboration: A study of AME in Galactic clouds
to be significant for the bright regions in this study because
the zodiacal light is relatively smooth spatially except for a
narrow band at low ecliptic latitudes. We test this assump-
tion by comparing the flux densities from improved zodiacal-
light-subtracted maps (Marc-Antoine Miville-Deschênes, priv.
comm.) where the residuals are clearly much smaller. We ob-
tained consistent results within a fraction of the errors; the scat-
ter is less than 5% at the worst band (12
μ
m). Sources were not
removed for
|
b
|
>
5
◦
and therefore do not a
ff
ect the majority of
the sources in our sample.
We u s e
Spitzer
data where available at 8 and 24
μ
m as a dust
diagnostic for the polycyclic aromatic hydrocarbons (PAHs) and
very small grains (VSGs), respectively. The
Spitzer
data are ob-
tained from the
Spitzer
data archive
6
, and are reprocessed for the
purposes of this paper in order to mitigate possible systematics.
An extended emission correction is applied to the 8
μ
m data, and
the zodiacal light contribution i
s subtracted from both the 8 and
24
μ
m data. Bright point sources are extracted from both bands
to enable us to investigate the extended emission, and an over-
lap correction is applied to ensure a consistent background level.
Finally, all the reprocessed data are combined to produce the fi-
nal maps used in this analysis; see
Tibbs et al.
(
2011
)formore
details. We are able to measure flux densities for 24 regions.
3. Sample selection and SED fitting
In this section we cover the methods we use to create the
sample of sources. Section
3.1
describes the source detection
method that forms the main sample. Section
3.2
describes the
component subtraction method for detecting potential AME re-
gions. Section
3.3
summarizes the final sample of 98 sources.
Section
3.4
describes the aperture photometry method used to
extract the flux densities of the sources. Section
3.5
describes the
model-fitting that is adopted to qua
ntify the various components
and to assess the contribution of AME. Section
3.6
presents ex-
ample SEDs
7
and a summary of what is observed in our sample.
3.1. Detection of bright sources
At high radio frequencies (30–70 GHz), synchrotron and ther-
mal dust emission are expected to be relatively faint. The domi-
nant emission mechanism is thought to be optically thin free-free
emission (
α
≈−
0
.
14, where
S
∝
ν
α
), with a possible contribu-
tion from AME. Free-free emission is expected to be particularly
strong near the Galactic plane due to the presence of H
ii
regions
and ionized gas near OB stars. This allows H
ii
regions to be de-
tected by simply searching for bright sources in individual fre-
quency maps. However, in this paper we are mainly interested in
constructing accurate SEDs across the radio
/
submillimetre
/
far-
infrared wavelength range, which requires the detection of the
brightest clouds at
all
WMAP
/
Planck
frequencies. We used the
SExtractor
software (
Bertin & Arnouts 1996
), which was used
in the “Sextra” pipeline for the Planck Early Release Compact
Source Catalogue (
Planck Collaboration VII 2011
), to detect
bright sources at each
Planck
frequency of the CMB-subtracted
maps.
We begin with a
SExtractor
catalogue of 1194 sources
detected at 70 GHz. To increase reliability and to ensure the
6
http://sha.ipac.caltech.edu/applications/Spitzer/
SHA/
7
Strictly speaking, the SED is frequency multiplied by the flux density
(with units W m
−
2
). Here we use the term for the flux density spectrum
(units W m
−
2
Hz
−
1
).
region is bright at all
Planck
frequencies, this catalogue is fur-
ther cross-matched with the 28.4 and 100 GHz catalogues, us-
ing a matching radius of the largest beam FWHM (16.
38).
This results in 462 sources that are well-detected across the
30
−
100 GHz range. We remove extragalactic sources by search-
ing the NASA Extragalactic Database (NED
8
) for radio galax-
ies. Approximately half of all detected sources, and a majority at
|
b
|
5
◦
, are found to be extragalactic, most of which are likely
blazars. We also remove a small number of sources associated
with known bright supernova remnants (
Green 2009
) and plan-
etary nebulae (
Acker et al. 1992
). The SIMBAD
9
database is
found to be useful for confirming that a region is dominated by
Galactic emission and that many of our sources are in fact large
H
ii
complexes or parts of molecular clouds. These regions often
contain several individual sources.
The final stage of catalogue trimming is made by visual in-
spection of the maps and preliminary SEDs made by aperture
photometry (Sects.
3.4
,
3.5
,and
3.6
). We make visual inspec-
tion at this resolution, since the final SEDs are to be constructed
using 1
◦
-smoothed maps (to ensure that the response to di
ff
use
emission is the same at all frequencies). To ensure a robust sam-
ple, sources that are not well-defined after smoothing to 1
◦
(i.e.,
do not show a definite peak of emission on scales of
2
◦
), or
are relatively faint (
10 Jy at a frequency of 30 GHz), are dis-
carded, except for a few cases at several degrees distance from
the Galactic plane. We find a few sources whose positions are
not exactly centred on the peak of the emission at frequencies
of 20
−
60 GHz, with o
ff
sets as large as 10
−
20
. This can oc-
cur because of the complexity of
the Galactic plane, which af-
ter filtering can produce multiple
peaks in close proximity to
each other. In these cases, we manually shift the position to
the approximate centre of the hotspot. Since we are using a
large 1
◦
radius aperture (see Sect.
3.4
), this makes little di
ff
er-
ence to the SEDs. We identify 94 candidate AME sources using
this technique.
3.2. Detection of AME regions by component subtraction
We use a simple CMB
/
foreground subtraction method to iso-
late AME from the other di
ff
use components. This method is
essentially the same as was used by
Planck Collaboration XX
(
2011
), where potential AME regions were located by a sim-
ple subtraction of the non-AME components from the 28.4 GHz
Planck
CMB-subtracted map. The one di
ff
erence is that here we
only use the 0.408 GHz map to trace the synchrotron emission,
which is extrapolated with a single power law and a spectral in-
dex
β
=
−
3
.
0(
T
∝
ν
β
). This is a typical value of the slope be-
tween 408 MHz and WMAP
/
Planck
frequencies (
Davies et al.
2006
;
Gold et al. 2011
). The combination of the 1.4 GHz and
2.3 GHz maps is not used, as it creates large-scale artefacts.
Although there is some evidence of flattening (
β
≈−
2
.
7) of
the synchrotron index at low Galactic latitudes (e.g.,
Gold et al.
2009
), we use the typical high latitude value. For most sources
on the Galactic plane, the synchrotron emission is a minor com-
ponent at frequencies above 23 GHz. For the free-free compo-
nent we use the dust-corrected H
α
map of
Dickinson et al.
(
2003
). For thermal dust, we use model 8 of
Finkbeiner et al.
(
1999
). Both are calculated at a frequency of 28.4 GHz.
We smooth the
Planck
CMB-subtracted maps to a res-
olution of 1
◦
and subtract the non-AME components from
the
Planck
28.4 GHz map to create a map of residuals. A
8
http://ned.ipac.caltech.edu/
9
http://simbad.u-strasbg.fr/simbad/
A103, page 5 of
28
A&A 565, A103 (2014)
Fig. 1.
Map of residuals at 28.4 GHz after subtracting o
ff
synchrotron,
free-free, thermal dust, and CMB components (see text), in mK (R-J)
units. A 5
◦
-smoothed version of the map is subtracted to remove ex-
tended di
ff
use emission to more easily identify bright, relatively com-
pact sources. This map is shown in the Mollweide projection, with
l
=
0
◦
in the centre and increasing to the left.
5
◦
-smoothed version is also cr
eated and subtracted from the
1
◦
map to remove large-scale emission and highlight the com-
pact regions most suited for this analysis. The di
ff
use emission
removed here will be the focus of future papers.
The resulting map of residuals at 28.4 GHz is shown in
Fig.
1
. The large-scale features, including negative artefacts,
are not of concern here. Instead, we used this map as a “find-
ing chart” to identify new regions that emit detectable levels of
AME. Approximately 100 bright well-defined sources are lo-
cated by eye and a spectrum is produced for each one using
aperture photometry (see Sect.
3.4
). The well-known AME re-
gions in Ophiuchus and Perseus stand out in this map. Lots
of free-free emission (usually because it can be self-absorbed
at lower frequencies) and synchrotron point sources (with a
flatter spectral index than
β
=
−
3
.
0, and hence not removed
completely by extrapolating the synchrotron map assuming a
steep spectrum) can be found in this residual map. Most of
the 100 AME candidates are H
ii
regions; 20 sources show ev-
idence for excess emission at 30 GHz based on an initial spec-
tral fit, out of which 16 have already been identified using the
source-detection method (Sect.
3.1
). The four additional sources
found using this technique are G037.79
−
00.11, G293.35
−
24.47,
G317.51
−
00.11, and G344.75
+
23.97.
3.3. Final sample
The final sample contains 98 sources, listed in Table
3
.The
superscript letter after the name indicates which method the
source is chosen from. Most of the sources are located using
the
SExtractor
detection technique, with a few of the AME-
dominated sources being detected using the component sub-
traction method. We also indicate if a source is already known
from previous AME studies. A few previously identified AME
candidates are not on this list because they are not detected at
high significance in the
Planck
data, mostly due to the lim-
ited angular resolution of this study. These include
RCW175
(
Dickinson et al. 2009
), LDN1621 (
Dickinson et al. 2010
), M78
(
Castellanos et al. 2011
), LDN1780 (
Vidal et al. 2011
), and
LDN1111
/
675
/
1246 (
Scaife et al. 2009
,
2010a
). Associations
with known objects are listed in the notes column of Table
3
.
The
Planck
CMB-subtracted map with the locations of the
sources is shown in Fig.
2
. Most of the sources lie within a few
degrees of the Galactic plane. A few sources are in the well-
known regions of Ophiuchus (
l
=
0
◦
), Perseus (
l
=
160
◦
), Orion
(
l
=
200
◦
), and the Gum nebula (
l
=
260
◦
). The most signifi-
cant (
σ
AME
>
5and
f
UCH
ii
max
<
0
.
25; see Sect.
4
) AME sources
are shown as thick squares; sources that have excess emission
(
σ
AME
>
5) but have a potentially large contribution of opti-
cally thick free-free emission from ultra-compact H
ii
(UCH
ii
)
regions (
f
UCH
ii
max
>
0
.
25) are shown as stars. It is interesting to
see that these AME-bright sources appear to cluster in certain
regions, particularly along the local Gould Belt region (
Planck
Collaboration Int. XII 2013
). There seem to be no bright AME
regions along the lines-of-sight to the local spiral arm at
l
=
90
◦
and
l
=
270
◦
. In general, few of the most significant AME
sources lie on the plane. This is partly explained by the removal
of AME sources that have a potential UCH
ii
contribution, based
on infrared sources (see Sect.
4.2
), which preferentially lie in
the Galactic plane. In addition, there is a selection e
ff
ect, since
the high free-free brightness temperatures and overall confusion
in the plane make it more di
ffi
cult to identify individual AME-
bright objects. It may also be that these sight-lines contain a
strong component of free-free emission from warm ionized gas,
which is thought to exhibit less AME than cold neutral medium
(CNM) or molecular clouds (
Planck Collaboration XXI 2011
).
With our incomplete sample, such claims cannot be confirmed
in this study.
3.4. Aperture photometry
We use the
HEALPix
aperture photometry code developed for
Planck Collaboration XX
(
2011
) to extract the flux densities of
the regions from the maps. This software has also been used
to investigate at the polarization of AME from
ρ
Ophiuchi
in
Dickinson et al.
(
2011
). After converting from CMB ther-
modynamic units (
K
CMB
) to RJ units (
K
RJ
) at the central fre-
quency, the maps are converted to units of Jy pixel
−
1
using
S
=
2
kT
RJ
Ω
ν
2
/
c
2
,where
Ω
is the
HEALPix
pixel solid angle.
The pixels are then summed in a circular aperture of 60
to ob-
tain an integrated flux density. An estimate of the background is
subtracted using a median estimator of pixels lying at radii be-
tween 80
and 100
. By using Monte Carlo injection of sources,
we find that this choice of aperture and annulus size provides
the least scatter in recovered flux densities, and is a reasonable
balance for obtaining an appropriate background level without
subtracting appreciable flux d
ensity from the source itself.
The flux density uncertainties are estimated from the rms
of the values in the background annulus and added in quadra-
ture to the absolute calibratio
n uncertainties for each map (see
Sect.
2.2
). Simulations of injected point-like sources show that
the flux density estimates are unbiased and that the uncertainties
are reasonable; however, the exact value of flux density uncer-
tainty for each source is di
ffi
cult to quantify, since it depends
very strongly not only on the brightness of the source and back-
ground, but also on the morphology of the emission in the vicin-
ity of the source. This will be discussed further in Sect.
4.4
.
Colour corrections, based on the local spectral index across each
band, are applied during the model-fitting, as described in the
next section.
3.5. Model fitting
We take the flux density
S
for each source from the aperture
photometry and fit a simple model of free-free, synchrotron
(where appropriate), CMB, thermal dust, and spinning dust
components:
S
=
S
ff
+
S
sync
+
S
td
+
S
CMB
+
S
sp
.
(1)
A103, page 6 of
28
Planck Collaboration: A study of AME in Galactic clouds
Fig. 2.
CMB-subtracted
Planck
28.4 GHz map covering the entire Galactic plane and latitudes
|
b
|
<
30
◦
. The colour scale has a logarithmic stretch.
Regions with the most significant AME are highlighted as thick squares while the rest of the sample are shown as circles. Regions with significant
excess emission but with a potential UCH
ii
contribution (
f
UCH
ii
max
>
0
.
25) are shown as star symbols (see Sect.
4.2
).
The free-free flux density
S
ff
is calculated from the brightness
temperature
T
ff
, based on the optical depth
τ
ff
, using the standard
formula
S
ff
=
2
kT
ff
Ω
ν
2
c
2
,
(2)
where
k
is the Boltzmann constant,
Ω
is the solid angle of the
aperture, and
ν
is the frequency, with
T
ff
=
T
e
(1
−
e
−
τ
ff
)
,
(3)
and the optical depth
τ
ff
is given by
τ
ff
=
5
.
468
×
10
−
2
T
−
1
.
5
e
ν
−
2
EM
g
ff
,
(4)
in which the Gaunt factor can be approximated
10
by
g
ff
=
ln
⎛
⎜
⎜
⎜
⎜
⎝
exp
⎡
⎢
⎢
⎢
⎢
⎣
5
.
960
−
√
3
π
ln(
Z
i
ν
9
T
−
3
/
2
4
)
⎤
⎥
⎥
⎥
⎥
⎦
+
2
.
71828
⎞
⎟
⎟
⎟
⎟
⎠
.
(5)
For the analysis of AME, we assume a fixed electron temperature
of 8000 K for
T
e
for all regions, fitting only for the emission
measure (EM). Note that this is not the true EM, but an e
ff
ective
EM over the 1
◦
radius aperture. For compact sources, the quoted
EM will be underestimated.
For six sources, we also include a synchrotron component
modelled as a power law with amplitude
A
sync
and variable flux
density spectral index
α
,
S
sync
=
A
sync
ν
GHz
α
·
(6)
The thermal dust is fitted using a modified blackbody model,
S
td
=
2
h
ν
3
c
2
1
e
h
ν/
kT
d
−
1
τ
250
(
ν/
1
.
2THz)
β
d
Ω
,
(7)
fitting for the optical depth
τ
250
, the dust temperature
T
d
,andthe
emissivity index
β
d
. The CMB is fitted using the di
ff
erential of a
blackbody at
T
CMB
=
2
.
7255 K (
Fixsen 2009
)
S
CMB
=
2
k
Ω
ν
2
c
2
Δ
T
CMB
.
(8)
Here
Δ
T
CMB
is the CMB fluctuation temperature in thermody-
namic units. The spinning dust is fitted using
S
sp
=
A
sp
j
(
ν
+
ν
shift
)
Ω
,
(9)
10
Here we use the approximation given by
Draine
(
2011
), which is ac-
curate to better than 1% even up to frequencies of 100 GHz and higher.
whereweuseamodelfor
j
ν
calculated using the
SPDUST
(v2)
code (
Ali-Haïmoud et al. 2009
;
Silsbee et al. 2011
). We choose a
model corresponding to the warm ionized medium (WIM) with a
peak at 28.1 GHz to give the generic shape, and allow for a shift
of this model with frequency. We therefore fit for two parame-
ters corresponding to the AME amplitude
A
sp
, and a frequency
shift
ν
shift
. Note that the units of
A
sp
are formally of column den-
sity (cm
−
2
). If the spinning dust model was appropriate for the
line-of-sight, and no frequency shift was applied, then this would
indeed be the column density
N
H
; however, since this quantity is
model-dependent and there is pot
entially a shift in frequency, we
do not take this to be a reliable estimate of
N
H
. Similarly, in this
paper we do not attempt to fit specific spinning dust models to
each source, hence the derived column density is not necessarily
physical;
A
sp
is essentially the flux density at the peak normal-
ized to the spinning dust model. Given the large uncertainties
and di
ffi
culty in separating the various spectral components, we
have not attempted to look for deviations from the basic spinning
dust model (
Hoang et al. 2011
).
The least-squares fit is calculated using the
MPFIT
11
(
Markwardt 2009
) package written in IDL, with starting val-
ues estimated from the data and with amplitude parameters con-
strained to be positive except for the CMB, which is allowed
to go negative.
MPFIT
also provides estimates of the 1
σ
uncer-
tainties for each parameter, taken as the square root of the di-
agonal elements of the parameter covariance matrix. We note
four special cases in Table
3
(G068.16
+
01.02, G076.38–00.62,
G118.09
+
04.96 and G289.80–01.15) where the fitting returned
A
sp
=
0
.
0
±
0
.
0. These could be mitigated by removing the posi-
tivity prior, with best-fitting negative values still being consistent
with zero. Instead, for these special cases, we fixed
A
sp
to zero
to make the fits more physically meaningful, since the spinning
dust spectrum should not go negative.
3.6. Example SEDs
Some example SEDs for regions with weak AME are shown in
Fig.
3
; see Sect.
4.3
and Fig.
8
for SEDs with significant AME.
Filled circles are used for data included in the fit, and unfilled
circles are for display purposes only. We begin by including data
from 0.408 GHz up to 3000 GHz and make a least-squares fit
to the data. In general, the SEDs are well-fitted by our simple
model, although the uncertainties appear to be over-estimated.
This can be seen in some of the example SEDs in Fig.
3
and in
the reduced
χ
2
values in Table
3
; the mean value for the entire
11
http://purl.com/net/mpfit
A103, page 7 of
28
A&A 565, A103 (2014)
Fig. 3.
Example SEDs (see text for description of individual SEDs) of sources with little or no AME (see Fig.
8
for SEDs with significant AME).
Data points are shown as circles with errors and are colour-coded for radio data (cyan), WMAP (red),
Planck
(blue), and DIRBE
/
IRAS (black).
The best-fitting model of free-free (do
tted line), synchrotron (long-dashed
line), thermal dust (short-dashed lin
e), CMB (triple-
dot-dashed line
),
and spinning dust (dot-dashed line) are shown. Data included in the fit are shown as filled circles, while the other data are unfilled. The residual
spectrum, after subtraction of free-free, synchrotron, CMB and thermal dust components, is shown as an
insert
.
sample is
̄
χ
2
=
0
.
59. However, our uncertainties are justified for
some sources where the scatter is consistent with our assigned
uncertainties. An example of this is G017.00
+
00.85, where there
is considerable scatter at low frequencies.
All sources show a strong thermal dust component peaking
at about 2000–3000 GHz, indicative of dust grains at
T
d
≈
20 K.
The one-component modified blackbody function reproduces
the spectrum above 100 GHz remarkably well for the majority
of our sources; however, the 100
/
217 GHz data points are of-
ten inconsistent with the model due to the CO line contamina-
tion within the
Planck
bands. For this reason, as previously ex-
plained, we exclude the 100
/
217 GHz data from all our fits.
Another e
ff
ect seen in our SEDs is that of the fluctuations
in the CMB. Although the CMB fluctuations are faint (with an
rms of 70
μ
Kat1
◦
scales), the large aper
ture that we integrate
over results in a typical integrated CMB flux density of 7 Jy
at 100 GHz, based on the standard deviation of flux densities
from Monte Carlo simulations of a CMB-only sky, assuming the
WMAP 7-year power spectrum (
Larson et al. 2011
). It is impor-
tant to note that these fluctuations are about the mean CMB tem-
perature, and thus can be negative or positive. Figure
3
shows ex-
amples of both; G209.01
−
19.38 contains a large positive CMB
fluctuation (
Δ
T
CMB
=
371
±
102
μ
K), and G274.01
−
01.15,
showing a strong negative fluctuation (
Δ
T
CMB
=
−
37
±
10
μ
K).
The negative CMB flux densities cause a dip in the spectrum
at frequencies near 100 GHz, which could be misinterpreted as
spinning dust at lower frequencies.
Similarly, over-fitting by a strong positive CMB fluctuation
could a
ff
ect the AME intensity. This could happen when there
is a flattening of the thermal dust spectral index at frequen-
cies below 353 GHz (Planck Collaboration, in prep.), which can
be accounted for by the CMB component. A clear example of
this is G015.06
−
00.69, shown in Fig.
3
. There is an appar-
ent flattening of the thermal dust spectral index, which appears
as an excess at frequencies
≈
100
−
353 GHz relative to the one
component dust model, an e
ff
ect that has been observed before
(
Paradis et al. 2009
,
2012b
). In this case, the fitted CMB tem-
perature,
Δ
T
CMB
=
(533
±
251)
μ
K, is larger than what could
realistically be attributed to a pure CMB fluctuation (
150
μ
K).
Fortunately, because the uncertainties are large and the CMB
does not contribute strongly at frequencies where AME is dom-
inant (10
−
60 GHz), this does not have a major impact on the
AME results. This will be discussed further in Sect.
4.4
.
At frequencies below 100 GHz, optically thin free-free emis-
sion is seen in many sources and is sometimes consistent with
the low frequency radio data at
≈
1 GHz and WMAP
/
Planck
data
at 20
−
100 GHz (e.g., G265.15
+
01.45 and G289.80
−
01.15 in
Fig.
3
). These sources justify our use of the 0.408, 1.42, and
2.326 GHz data, and show that the overall calibration factors are
within the uncertainties assumed in this study. Where there is
evidence of absorption at low frequencies, or if there is a dis-
crepancy between 0.408 GHz and the other low frequency data
at 1.4
/
2.3 GHz, we omit the 0.408 GHz data point (and occasion-
ally the 1.42 GHz data point) in the fit (e.g., G123.13
−
06.27,
A103, page 8 of
28