# A Herschel study of G214.5-1.8: a young, cold and quiescent giant molecular
filament on the shell of a HI superbubble

S. D. Clarke1, Á Sánchez-Monge2, G. M. Williams3, A. D. P. Howard4,S. Walch2,5
and N. Schneider2.
1Academia Sinica, Institute of Astronomy and Astrophysics, Taipei, Taiwan
2I. Physikalisches Institut, Universität zu Köln, Zülpicher Str. 77, D-50937
Köln, Germany
3School of Physics and Astronomy, University of Leeds, Leeds, LS2 9JT, UK
4School of Physics and Astronomy, Cardiff University, Cardiff, CF24 3AA, UK
5Cologne Centre for Data and Simulation Science, University of Cologne,
Cologne, Germany E-mail<EMAIL_ADDRESS>www.cds.uni-koeln.de

###### Abstract

We present an analysis of the outer Galaxy giant molecular filament (GMF)
G214.5-1.8 (G214.5) using Herschel data. We find that G214.5 has a mass of
$\sim$ 16,000 M⊙, yet hosts only 15 potentially protostellar 70 $\mu$m
sources, making it highly quiescent compared to equally massive clouds such as
Serpens and Mon R2. We show that G214.5 has a unique morphology, consisting of
a narrow ‘Main filament’ running north-south and a perpendicular ‘Head’
structure running east-west. We identify 33 distinct massive clumps from the
column density maps, 8 of which are protostellar. However, the star formation
activity is not evenly spread across G214.5 but rather predominantly located
in the Main filament. Studying the Main filament in a manner similar to
previous works, we find that G214.5 is most like a ’Bone’ candidate GMF,
highly elongated and massive, but it is colder and narrower than any such GMF.
It also differs significantly due to its low fraction of high column density
gas. Studying the radial profile, we discover that G214.5 is highly asymmetric
and resembles filaments which are known to be compressed externally.
Considering its environment, we find that G214.5 is co-incident, spatially and
kinematically, with a HI superbubble. We discuss how a potential interaction
between G214.5 and the superbubble may explain G214.5’s morphology, asymmetry
and, paucity of dense gas and star formation activity, highlighting the
intersection of a bubble-driven interstellar medium paradigm with that of a
filament paradigm for star formation.

###### keywords:

ISM: clouds - ISM: kinematics and dynamics - ISM: structure - stars: formation

††pagerange: A Herschel study of G214.5-1.8: a young, cold and quiescent giant
molecular filament on the shell of a HI superbubble–B††pubyear: 2002

##  1 Introduction

It has long been known that filaments have been connected to the star
formation process and contain large quantities of high-density molecular gas
(Barnard, 1907; Schneider & Elmegreen, 1979). The Herschel Space Observatory
sparked renewed interest in filaments due to their ubiquity in observations
across numerous environments (André et al., 2010; Arzoumanian et al., 2013;
Könyves et al., 2015; Cox et al., 2016; Marsh et al., 2016; Miettinen, 2018;
Williams et al., 2018; Arzoumanian et al., 2019; Howard et al., 2019; Suri et
al., 2019; Bonne et al., 2020b, a; Zavagno et al., 2020). As a consequence,
there has been a number of recent theoretical works studying the stability,
fragmentation and collapse of filaments to better understand what role they
play in star formation (Fischera & Martin, 2012; Heitsch, 2013; Smith, Glover
& Klessen, 2014; Gómez & Vázquez-Semadeni, 2014; Clarke & Whitworth, 2015;
Heigl, Burkert & Hacar, 2016; Clarke, Whitworth & Hubber, 2016; Clarke et al.,
2017; Zamora-Avilés, Ballesteros-Paredes & Hartmann, 2017; Heigl, Burkert &
Gritschneder, 2018; Clarke et al., 2018; Li & Klein, 2019; Smith et al., 2020;
Clarke, Williams & Walch, 2020).

In the past decade a class of large-scale ($\gtrapprox 10$ pc) filaments
called Giant Molecular Filaments (GMFs) has been studied (Jackson et al.,
2010; Goodman et al., 2014; Ragan et al., 2014; Wang et al., 2015; Abreu-
Vicente et al., 2016; Wang et al., 2016; Zucker, Battersby & Goodman, 2018;
Zhang et al., 2019; Wang et al., 2020; Colombo et al., 2021). These objects
are of interest due to the fact they are sufficiently long as to be shaped by
the large-scale environment and Galactic dynamics, whilst also being active
star forming sites; thus illuming the influence of the large-scale ISM on the
star formation process. It is currently thought that the majority of these
GMFs are formed due to a combination of shear and the Galactic potential
elongating gas and aligning it with spiral arms (Duarte-Cabral & Dobbs, 2016,
2017; Smith et al., 2020).

Zucker, Battersby & Goodman (2018) collected data from multiple studies to
produce a standardized catalogue of 45 GMFs in the inner Galaxy. Using the
aspect ratio and the cold & high column density fraction of the clouds,
Zucker, Battersby & Goodman (2018) identify three categories: Elongated Giant
Molecular Clouds with low aspect ratios ($\sim 8$) and low cold & high column
density fractions ($<10\%$); Elongated Dense Core Complexes with moderate
aspect ratios ($\sim 10$) and high cold & high column density fractions
($10-75\%$); and ’Bone’ candidates with high aspect ratios ($>20$) and
moderate cold & high column density fraction ($10-50\%$). The Zucker,
Battersby & Goodman (2018) catalogue is complemented by the recent work of
Colombo et al. (2021) which provides a catalogue of 37 GMFs in the outer
Galaxy; however, they use only 12CO (2-1) data and so cannot determine the
cold & high column density fraction. Colombo et al. (2021) find that on
average GMFs in the outer Galaxy have masses and line-masses an order of
magnitude smaller than their inner Galaxy counterpoints while having
comparable sizes and aspect ratios. Also focused on the inner Galaxy, Zhang et
al. (2019) collate a total of 57 GMFs using the GRS and ThrUMMS CO surveys,
studying their star formation rates and efficiencies using near- and mid-
infrared data.

To further this study of GMFs, especially in the outer Galaxy, we present a
comprehensive study using Herschel data of the GMF G214.5-1.8. The paper is
structured in the following manner: in section 2 we describe G214.5-1.8 and
previous studies of it; in section 3 we discuss the Herschel observational
data used; in section 4 we present the column density and temperature maps of
G214.5-1.8, as well as a catalogue of its 70 $\mu$m sources; in section 5 we
study the properties of the clumps and the main filament of G214.5-1.8 and
compare to observational and theoretical results in the literature; in section
6 we argue that G214.5-1.8 lies on the shell of a HI superbubble which impacts
its evolution and star formation; and in section 7 we summarize our results.

##  2 The giant molecular filament G214.5-1.8

G214.5-1.8 (hereafter G214.5) is a satellite cloud associated with the larger
Maddalena’s cloud in the 3rd galactic quadrant, lying at a distance of
approximately 2.3 kpc towards the outer Galaxy (Maddalena & Thaddeus, 1985;
Lee, Snell & Dickman, 1991; Yan et al., 2019). The distance estimate comes
from considering the extinction of GAIA identified stars and has an error of
2301${}^{+142}_{-149}$pc (Yan et al., 2019; Zucker et al., 2020), and is
consistent with the kinematic distance estimates which have larger errors,
2620${}^{+840}_{-740}$pc (Yan et al., 2019) and 2540$\pm 758$pc (Mège et al.,
2021). Note that G214.5 has sometimes been referred to as S287-North as this
is the name given to the bright IRAS source contained within the cloud, IRAS
06453-0205. Both Maddalena’s and it satellite clouds, including G214.5, have
low CO excitation temperatures and are rather quiescent when compared to
similarly sized inner Galaxy counterparts (Lee, Snell & Dickman, 1991).

G214.5 can be seen in figure 1, with Maddalena’s cloud lying to the south out
of the field of view. One can see that G214.5 has a unique morphology,
consisting of two distinct regions: a long and thin filament seen lying north
to south and a wide structure lying east to west. We refer to these two
regions as the main filament and the head structure respectively. The dashed
polygons in figure 1 show the boundary definitions of these structures which
we use in this work. We define the combined area of these regions as the GMF
G214.5-1.8 and the area outside the polygons as the cloud’s
environment/surroundings. The two structures, the main filament and the head
structure, are velocity coherent (Lee, Snell & Dickman, 1994) when observed in
12CO and 13CO, meaning that it is highly unlikely for them to be two unrelated
structures along the line-of-sight. There exists a smooth velocity gradient
from the southern to the northern tip, from $\sim 22$ km/s to $\sim 32$ km/s.
The length of G214.5, from north to south, is approximately 35 pc and the
width of the head structure is approximately 20 pc.

Due to its location in the outer Galaxy, the cloud G214.5 has not been covered
in most CO Galactic surveys; however, G214.5 does host the bright source IRAS
06453-0209 (seen in roughly the centre of the main filament region) which has
been included as a target in surveys looking for signs of star formation.
These have included surveys looking for CO molecular outflows, K-band point
sources, H2O masers as well as class I and II methanol masers (Fukui, 1989;
Felli, Palagi & Tofani, 1992; Hodapp, 1994; Codella et al., 1995; Lee, Snell &
Dickman, 1996; Larionov et al., 1999; Furuya et al., 2003; Sunada et al.,
2007). The results show that there exists a bipolar outflow emanating from
this source which is associated with at least two stars in the K-band. There
have been no detections of maser emission. This has lead to the conclusion
that the star formation in the source is currently limited to only low-mass
star formation despite its brightness (L${}_{\rm IR}\sim 230$ L⊙, Larionov et
al., 1999).

Recently the MWISP CO project has covered a large area of the third quadrant
which includes G214.5 (for details on the project see Su et al., 2019). The
MWISP data from the region $209.75\degree\leq l\leq 219.75\degree$ and
$|b|\leq 5\degree$ was studied by Yan et al. (2019) and G214.5 was identified
as a distinct cloud using a dendrogram analysis (their cloud 7). They confirm
a distance of $\sim$ 2.3 kpc and the velocity coherence of the structure.
Moreover, using an XCO factor Yan et al. (2019) estimate that G214.5 has a
mass of $2.6\times 10^{4}$ M⊙.

With its distinct morphology, high mass and apparent lack of high-mass star
formation, G214.5 is an interesting object to study and provides an example of
a GMF in the outer Galaxy.

Figure 1: A plot showing the 250 $\mu$m emission covering the G214.5-1.8 giant
molecular filament and its environment. G214.5-1.8 is enclosed by the dashed
yellow and white polygons, which is further sub-divided into the main filament
(yellow) and the head structure (white). The solid yellow rectangle in the top
left shows the region used to determine the contamination of the column
density in section 4.1. The blue scale shows the apparent size of 10 pc at a
distance of 2.3 kpc.

##  3 Observations

The Herschel observations of G214.5 were taken as part of the Herschel
infrared Galactic Plane Survey (Molinari et al., 2010, Hi-GAL). They consist
of $70\mu{\rm m}$ and $160\mu{\rm m}$ data from PACS (Poglitsch et al., 2010),
and $250\mu{\rm m}$, $350\mu{\rm m}$ and $500\mu{\rm m}$ data from SPIRE
(Griffin et al., 2010). The scans were taken in the fast scan
($60^{\prime\prime}\,\rm{s}^{-1}$) PACS/SPIRE parallel mode, and two pairs of
nominal and orthonormal scans, one pair observing the northern part of the
structure (observation IDs 1342245150 and 1342245151), and the other pair
observing the southern part (observation IDs 1342253429 and 1342253430).

The observations were reduced using the HIPE User Release v15.0.1. PACS maps
were produced using a modified version of the `JScanam` task, whilst SPIRE
maps were produced with the `mosaic` script operating on Level 2 data
products. We determined the Zero-Point Offsets for the PACS maps through
comparison with Planck and iras observations of the same region (cf. Bernard
et al., 2010). The adopted offsets were $-5.4\,\rm{MJy\,sr^{-1}}$ and
$59.4\,\rm{MJy\,sr^{-1}}$ for the $70\mu{\rm m}$ and $160\mu{\rm m}$ bands,
respectively. The SPIRE Zero-Point Offsets were applied automatically as part
of the HIPE reduction process.

The fwhms of the circular beam profiles are 8.5”, 13.5”, 18.2”, 24.9”, and
36.3”, for – respectively – the $70\mu{\rm m}$, $160\mu{\rm m}$, $250\mu{\rm
m}$, $350\mu{\rm m}$ and $500\mu{\rm m}$ wavebands (Herschel Explanatory
Supplement Vol. III, Vol. IV). In reality, the PACS beams are distorted by the
fast scan PACS/SPIRE parallel mode, producing effective non-circular beamsizes
of $\sim 6^{\prime\prime}\times 12^{\prime\prime}$ for the $70\mu{\rm m}$
waveband, and $\sim 12^{\prime\prime}\times 16^{\prime\prime}$ for the
$160\mu{\rm m}$ waveband, but this is not generally considered due to the
addition of the cross scans which lead to an averaging of the beam profiles.

The final images from each band are placed on identical grids with a size of
1.5 $\degree$ by 1.5 $\degree$, and a pixel size of 2”. These images can be
seen in appendix A, as well as an RGB image (R: 500 $\mu$m, G: 250 $\mu$m, B:
160 $\mu$m).

Figure 2: A plot showing the column density distribution of the uncorrected
column density map (in blue), the distribution in the contamination region (in
orange), and the distribution for the corrected column density map (in green).
The column density distributions are expressed in $\eta$ where
$\eta=\ln{(\mathrm{N}_{H_{2}}/<\mathrm{N}_{H_{2}}>)}$. Figure 3: (Top) The
corrected column density map of G214.5-1.8 at 18.2” resolution. (Bottom) The
dust temperature map of G214.5-1.8 at 36.3” resolution. The contours in both
panels shows where the visual extinction is equal to 1 magnitude, i.e.
$0.94\times 10^{21}$ cm-2.

##  4 Results

###  4.1 Column density and dust temperature maps

We use the 160 $\mu$m, 250 $\mu$m, 350 $\mu$m and 500 $\mu$m Herschel images
to produce ‘super-resolution’ (18.2”) H2 column density map and a standard
(36.3”) resolution dust temperature map using the procedure described in
Palmeirim et al. (2013). We outline it here for completeness.

Assuming the dust emission to be optically thin in the wavelengths considered
and that a single temperature may be used to describe it, one may fit a
modified blackbody function to each pixel independent of each other to
determine a column density, $\Sigma$, and a dust temperature, $T_{d}$. This
modified blackbody function takes the form:

$I_{\lambda}(\Sigma,T_{d})=\kappa(\lambda)\;\Sigma\;\left(\frac{2hc^{2}}{\lambda^{5}}\frac{1}{e^{hc/\lambda
k_{B}T_{d}}-1}\right),$ (1)

where $h$ is Planck’s constant, $k_{B}$ is the Boltzmann constant, $c$ is the
speed of light and $I_{\lambda}$ is the surface brightness at wavelength
$\lambda$. We use a mean molecular mass of 2.8 to convert from the total
column density, $\Sigma$, to the column density of H2 molecules,
$\mathrm{N}_{H_{2}}$. The first term, $\kappa(\lambda)$, is the dust opacity
per unit mass111Here a gas-to-dust ratio of 100 has been assumed and $\kappa$
is the dust opacity per unit total gas and dust mass. as a function of
wavelength. We adopt the power-law approximation:

$\kappa(\lambda)=\kappa_{300}\left(\frac{300\mathrm{\mu
m}}{\lambda}\right)^{\beta},$ (2)

where $\kappa_{300}$ is the opacity per unit mass at 300 $\mu$m and $\beta$ is
the dust emissivity index. We set $\kappa_{300}=0.1$ cm2/g and $\beta=2$
(Hildebrand, 1983).

To fit the modified black body equation we use a bounded least-squared fitting
method. Each data point involved in the fit has an error. The error has two
parts: the absolute calibration error and the map noise error. The absolute
calibration error at 160 $\mu$m is given as 20$\%$ of $I_{160}$ and for the
SPIRE bands it is given as 10$\%$ of $I_{250}$, $I_{350}$, and $I_{500}$
respectively (Könyves et al., 2015). The map noise error is estimated as the
standard deviation of the intensity in that band from a small region in the
top left of the considered map (100 x 100 pixels) as this region shows
little/uniform emission. The total error is calculated by adding these two
errors in quadrature to produce a conservative estimate of the total error.

To produce the ‘super-resolution’ column density map, $\Sigma_{s}$, one first
produces three column density maps, $\Sigma_{500}$, $\Sigma_{350}$ and
$\Sigma_{250}$, at the angular resolution of their corresponding Herschel
band, i.e. 36.3”, 24.9” and 18.2”. The column density map $\Sigma_{500}$ is
made by first smoothing the 160, 250 and 350 $\mu$m maps to the resolution of
the 500 $\mu$m band. We fit the 4-band data with a modified black body as
described above. The column density map $\Sigma_{350}$ is produced in a
similar manner, but the 500 $\mu$m data is excluded and only the 160 and 250
$\mu$m image maps are smoothed to the resolution of the 350 $\mu$m band. This
3-band data is then fit with a modified black body. The column density map
$\Sigma_{250}$ is produced by smoothing the 160 $\mu$m image map to the
resolution of the 250 $\mu$m band and using these two bands to fit the
modified black body function. Due to the limited information, the temperature
is not a free parameter in the fitting but is given by the flux ratio
$F_{250}/F_{160}$. This is achieved by using the bisector method to determine
the root of the equation:

$\frac{F_{250}}{F_{150}}=\left(\frac{250\,\mu m}{160\,\mu
m}\right)^{3+\beta}\left(\frac{\exp{(\lambda_{T}/160\,\mu
m)}-1}{\exp{(\lambda_{T}/250\,\mu m)}-1}\right),$ (3)

where $\lambda_{T}=hc/k_{B}T$ (Shetty et al., 2009). The smoothing described
above is achieved by convolving the image maps with a Gaussian kernel with a
full width half maximum (FWHM) in arcseconds of
$\sqrt{\theta_{D}^{2}-\theta_{B}^{2}}$, where $\theta_{D}$ is the desired
resolution and $\theta_{B}$ is the native resolution of the image map.

Combining the three column density maps one can produce the ‘super-resolution’
column density map, $\Sigma_{s}$, using the following equation:

$\Sigma_{s}=\Sigma_{500}+\Sigma_{350}-\Sigma_{350}\circledast G_{1}\\\
+\Sigma_{250}-\Sigma_{250}\circledast G_{2},$ (4)

where $\circledast$ denotes a convolution and, $G_{1}$ and $G_{2}$ are
Gaussian kernels with FWHMs in arcseconds of $\sqrt{36.3^{2}-24.9^{2}}$ and
$\sqrt{24.9^{2}-18.2^{2}}$ respectively. At this stage we re-grid the final
column density map to a 6” pixel size.

Quantity |  Total map |  G214.5-1.8 |  Main filament |  Head structure
---|---|---|---|---
Total mass |  40,800 M⊙ |  16,200 M⊙ |  11,900 M⊙ |  4,280 M⊙
Mass above Av=1 |  11,100 M⊙ |  8,660 M⊙ |  5,930 M⊙ |  2,730 M⊙
$<\mathrm{\overline{N_{H_{2}}}}>$ above Av=1 |  $1.57\times 10^{21}$ cm-2 |  $1.65\times 10^{21}$ cm-2 |  $1.69\times 10^{21}$ cm-2 |  $1.56\times 10^{21}$ cm-2
Area above Av=1 |  317 pc2 |  236 pc2 |  157 pc2 |  78 pc2
Median $T_{d}$ above Av=1 |  13.8 K |  13.8 K |  13.8 K |  13.9 K
Table 1: A table showing global properties of the total map, the G214.5-1.8
GMF, the main filament and the head structure (as defined in section 2). All
values are given to 3 significant figures. Figure 4: The column density
distributions of the whole G214.5 GMF (blue), the main filament section
(orange), and the head structure (green) above a column density of $10^{21}$
cm-2.

The column density maps which result from the procedure as described suffer
from line-of-sight contamination from unrelated dust emission. We follow the
procedure outlined in Schneider et al. (2015) and Ossenkopf-Okada et al.
(2016) to estimate this contamination and correct for it. We first define a
small rectangular region close to the border of the map (the same as that used
to estimate map noise error, seen in figure 1) which we assume is
predominately dominated by the line-of-sight contamination. We determine a
column density probability distribution (N-PDF) from the pixels within this
region (plotted in figure 2) and derive the peak and the width of this
distribution. The peak of the contamination distribution is $1.2\times
10^{21}$ cm-2 compared to the peak of the uncorrected cloud distribution at
$1.8\times 10^{21}$ cm-2. As this ratio is below one, and the width of the
contamination is considerably narrower than that of the cloud distribution (as
seen in figure 2), the assumption of a simple uniform line-of-sight
contamination is likely valid (as justified in Ossenkopf-Okada et al. (2016)).
We thus subtract $1.2\times 10^{21}$ cm-2, the peak of the contamination
distribution, from every pixel of our uncorrected column density map to
produce a ‘corrected’ column density map. The column density distribution of
the corrected map is also shown in figure 2. Using multiple different small
rectangular areas around the map edge yields contamination estimates of
between $1.1\times 10^{21}$ cm-2 and $1.5\times 10^{21}$ cm-2. This variation
adds an uncertainty in the final column density maps of only $\sim 0.2\times
10^{21}$ cm-2, smaller than the possible error in Herschel column density
maps, $\sim 30\%$, due to variations in dust properties, potential dust
temperature gradients along the line-of-sight, and assumptions about the
opacity law (see Russeil et al., 2013, for a discussion on this uncertainty).

Finally, we manually trim the edges of the map to exclude the regions in which
only the SPIRE band data is present, as well as the regions close to the map
boundary where one sees clear mapping artefacts. The corrected column density
map and the dust temperature map resulting from this process are shown in
figure 3. We also show the contour relating to a visual extinction of 1 mag in
figure 3; we use a conversion factor of 1 mag = $0.94\times 10^{21}$ cm-2
(Bohlin, Savage & Drake, 1978) here and throughout the paper.

###  4.2 Cloud properties

From figure 3 one sees that the majority of gas above an $A_{v}$ of 1 mag is
located within the G214.5 GMF, although there are a few small surrounding
clumps. It is within the main filament and head structures which one sees the
cold dust, as expected from well-shielded dense regions, and a number of small
localised hot regions related to on-going star formation.

Using the corrected column density map, and the assumption of a distance of
2.3 kpc, we determine a number of global properties of the cloud and the GMF.
These are summarised in table 1. The majority of the cloud mass above an
$A_{v}$ of 1 is located within the GMF ($\sim 78\%$ of the total cloud). This
is split between the main filament, containing $\sim 68\%$ of G214.5’s mass
above an $A_{v}$ of 1, and the head structure, which contains the remaining
$\sim 32\%$. The average column density of the gas above an $A_{v}$ of 1 is
comparable across both subregions, at $\sim 1.6\times 10^{21}$ cm-2
($A_{v}\sim 1.7$ mag). However, defining dense gas as that above an $A_{v}$ of
7 mag one sees a stark difference. The main filament contains $\sim$374 M⊙ of
dense gas in comparison to the head structure containing only $\sim$3 M⊙. This
is further seen in figure 4 which shows the N-PDFs of the two subregions above
a column density of $10^{21}$ cm-2 ($A_{v}\sim 1$ mag). Up to a column density
of $\sim 3\times 10^{21}$ cm-2 ($A_{v}\sim 3$ mag), the head structure and the
main filament show a comparable proportion of gas but above this quantity the
distribution for the head structure rapidly falls while the main filament
subregion extends up to $\sim 2\times 10^{22}$ cm-2 ($A_{v}\sim 20$ mag).
Considering the whole GMF (it’s N-PDF is also shown in figure 4), out of the
8,660 M⊙ of gas above an $A_{v}$ of 1 mag only 377 M⊙ is dense, corresponding
to a dense gas mass fraction of 4.4%. This paucity of dense gas in the GMF may
be linked to the quiescence of G214.5. We do note that the dense gas mass
fraction is a lower limit due to the beam dilution of the compact high column
density structures; the 18.2” column density map resolution corresponds to
approximately 0.2 pc.

Source ID |  RA [deg] |  DEC [deg] |  Peak $I_{70}$ [MJy/sr] |  SNR |  Total flux density [Jy] |  $A_{v}$ [mag] |  Peak? |  Other known names
---|---|---|---|---|---|---|---|---
Main filament |  |  |  |  |  |
S0 |  102.075 |  -2.613 |  94.2 |  22.8 |  0.235 |  9.0 |  Y |  IRAS 06458-0233
S1 |  102.085 |  -2.601 |  236 |  57.3 |  0.692 |  8.0 |  Y |  IRAS 06458-0233
S2 |  102.126 |  -2.548 |  53.9 |  13.1 |  0.107 |  7.4 |  Y |  -
S3 |  102.079 |  -2.532 |  47.9 |  11.6 |  0.067 |  6.9 |  Y |  -
S4 |  101.984 |  -2.390 |  96.6 |  23.4 |  0.223 |  11.3 |  Y |  -
S5 |  101.984 |  -2.383 |  51.2 |  12.4 |  0.111 |  11.3 |  Y |  -
S6 |  101.959 |  -2.214 |  5628.9 |  1364.7 |  27.614 |  20.3 |  Y |  IRAS 06453-0209, S287-North1
S7 |  101.978 |  -2.143 |  1635.0 |  396.4 |  6.234 |  10.5 |  Y |  IRAS 06453-0205
S8 |  101.962 |  -2.082 |  103.9 |  25.2 |  0.164 |  18.5 |  Y |  IRAS 06453-0201
S9 |  101.963 |  -2.077 |  858.0 |  208.0 |  2.823 |  18.5 |  Y |  IRAS 06453-0201
Head structure |  |  |  |  |  |
S10 |  102.091 |  -2.751 |  25.2 |  6.1 |  0.037 |  2.8 |  n |  -
S11 |  102.063 |  -2.736 |  224.0 |  54.3 |  0.718 |  6.8 |  Y |  -
S12 |  101.817 |  -2.708 |  171.6 |  41.6 |  0.375 |  2.6 |  Y |  IRAS 06447-0239
S13 |  101.822 |  -2.707 |  142.8 |  34.6 |  0.592 |  1.5 |  Y |  IRAS 06447-0239
S14 |  102.312 |  -2.696 |  36.0 |  8.7 |  0.045 |  0.8 |  n |  -
Surroundings |  |  |  |  |  |
S15 |  101.349 |  -3.018 |  1783.1 |  432.3 |  22.154 |  7.1 |  Y |  IRAS 06428-0257
S16 |  102.573 |  -2.859 |  65.1 |  15.8 |  0.241 |  0.5 |  n |  PGC076120, a galaxy2
S17 |  101.766 |  -2.762 |  57.4 |  13.9 |  0.120 |  0.8 |  n |  -
S18 |  102.617 |  -2.738 |  68.0 |  16.5 |  0.162 |  1.3 |  n |  -
S19 |  101.267 |  -2.686 |  56.9 |  13.8 |  0.129 |  0.6 |  n |  -
S20 |  101.490 |  -2.654 |  31.6 |  7.7 |  0.052 |  0.6 |  n |  -
S21 |  102.621 |  -2.653 |  73.9 |  17.9 |  0.153 |  2.4 |  Y |  -
S22 |  101.313 |  -2.442 |  45.9 |  11.1 |  0.079 |  0.6 |  n |  MSX6C G214.4023-02.4899, M-type star 3
S23 |  102.259 |  -1.658 |  94.3 |  22.9 |  0.268 |  0.3 |  n |  IRAS 06465-0136, V377 Mon 4
Table 2: A table showing the 24 sources identified in the 70 $\mu$m map as
described in section 4.3. The columns are: the source ID, the right ascension
and declination (J2000) in degrees, the peak 70 $\mu$m intensity in the source
in MJy/sr, the signal to noise ratio of the peak intensity, the total flux of
the source in Jy, the peak $A_{v}$ in the source, if the source is associated
with a column density peak, and other names and descriptors of the source. The
references for the final column are: 1 - Bica, Dutra & Barbuy (2003), 2 - van
den Bosch et al. (2015), 3 - MacConnell (2010), 4 - Kerschbaum & Hron (1994).
The sources are split into three groups: those located in the main filament
(top), those located in the head structure (middle), and those located in the
surroundings (bottom).

Comparing G214.5 to the collection of clouds analysed in the same manner in
Schneider et al. (2022), one sees that G214.5 is very similar to the clouds
they classify as ‘intermediate-mass star forming regions’. It has a mass above
an $A_{v}$ of 1 greater than Mon R2 and Mon OB1 ($\sim$4,700 M⊙), and slightly
lower than that of NGC 2264 and Serpens (11,000-14,000 M⊙). It also has a
comparable mean column density and area above an $A_{v}$ of 1 to these clouds
($1.5-2.6\times 10^{21}$ cm-2, 60-270 pc2). Despite the similarity in global
properties, G214.5 is considerably more quiescent than these intermediate-mass
star forming regions which are characterised by wide-spread low- and
intermediate-mass star formation, as well as some high-mass star formation.

We note that we find a total mass for G214.5 of 16,000 M⊙ which is nearly half
that estimated by Yan et al. (2019) using CO emission. Considering the errors
associated with using the constant canonical XCO factor to determine mass,
these results are not in strong disagreement (Borchert et al., 2021).
Interestingly, Borchert et al. (2021) note that young molecular clouds, i.e.
before widespread star formation occurs, should have low XCO factors ($\sim
1.0\times 10^{20}$ cm-2 (K km/s)-1) which would bring the CO mass estimate
into much better alignment with the dust emission estimate.

One may also study the global dust temperatures. The median dust temperature
above an $A_{v}$ of 1 is 13.8 K and is nearly equal in both sub-regions of
G214.5. When comparing to the catalogue of 45 GMFs presented in Zucker,
Battersby & Goodman (2018), one sees that G214.5 has a lower median dust
temperature than any of those presented, making it the coldest giant molecular
filament. The low temperature may be related to the lower interstellar
radiation field in the outer Galaxy and the low level of internal heating
(seen in figure 3), indicative of an early evolutionary state.

###  4.3 70 micron sources

As mentioned in section 2, G214.5 and the nearby Maddalena’s cloud are
quiescent compared to similar clouds in the inner galaxy. Here we use the
Herschel data to compile a catalogue of 70 $\mu$m sources to determine the
location and spread of active star formation in G214.5 and its immediate
environment.

To identify sources we use the dendrogram package
Astrodendro222http://www.dendrograms.org/. To compute the dendrogram three
parameters are needed: min_value, the minimum value a pixel must have to be
considered in the dendrogram; min_delta, the minimum contrast needed to split
a structure further; and min_npix, the minimum number of pixels a structure
must have. We set min_value to 5 times the noise level of the 70 $\mu$m map,
min_delta to the noise level, and min_npix to 16. The choice of min_npix
corresponds roughly to the area of a circle with a diameter the same as the
FWHM of the 70 $\mu$m beam, 8.5”. The noise level of the map is determined by
calculating the standard deviation of a 100 x 100 pixel region devoid of
emission; it is found to be 4.1 MJy/sr. The exact choice of area does not
greatly affect the noise level. We consider all leaves of the dendrogram (i.e.
the structures which contain no substructure) to be 70 $\mu$m sources. Note
that sources are only considered if they exist within the footprint of the
column density map in figure 3.

In total 24 sources are identified in the map; these are shown in figure 5 and
their properties are summarised in table 2. We separate the sources into two
groups: those which are located within 18” (the resolution of the column
density map) of a column density peak and those which are not. This is done by
visual inspection. There are 15 sources associated with column density peaks
and 9 which are not. One sees that those 15 associated with column density
peaks are predominately confined to the G214.5 GMF as expected and are most
likely proto-stellar objects. All IRAS point sources (Joint Iras Science,
1994) in the region (shown as black triangles) have corresponding 70 $\mu$m
point sources, with three of them resolved into two distinct sources. Sources
with no corresponding column density peaks are likely contaminants in the form
of external galaxies or IR-bright stars. This is known to be the case for
source S23 (co-incident with IRAS 06465-0136) which is a semi-regular variable
star called V377 Mon (Kerschbaum & Hron, 1994), for source S16 which is a
massive external galaxy known as PGC076120 (van den Bosch et al., 2015) and
for source S22 which is a cool M-type star (MacConnell, 2010). Investigating
the 15 sources which are associated with column density peaks, one sees that
they are associated with high column density gas, typically greater than an
$A_{v}$ of 6 mag (see figure 6). Thus these sources are mostly deeply
embedded, supporting their prestellar origin.

Comparing the number of embedded sources in the G214.5 GMF, 13 of the 15 total
embedded sources, to the widespread and large-scale proto-stellar activity in
similar mass and size clouds such as Serpens, NGC 2264, Mon R2 and Mon OB1,
one sees a clear deficit in G214.5’s star formation (Rayner et al., 2017;
Fiorellino et al., 2021; Nony et al., 2021). Moreover, some of these clouds
are forming high-mass stars, containing OB stars/clusters; however, source S6,
which is coincident with IRAS 06453-0209 and is the brightest 70 $\mu$m source
in G214.5, was found to show no sign of high mass star formation activity
(Larionov et al., 1999; Furuya et al., 2003; Sunada et al., 2007), only two
highly reddened sources in the K-band (Lee, Snell & Dickman, 1996). Thus we
conclude that the G214.5 GMF is quiescent for its size and mass. If G214.5 is
a young cloud and in a early phase of its evolution, then this quiescence, the
scarcity of dense gas and the low average dust temperature shown in section
4.2 are naturally explained.

Figure 5: A plot showing the location of the 24 70 $\mu$m sources overlaid on
the 250 $\mu$m map. Sources which lie on, or close to, a column density peak
are shown as blue circles and those which do not are shown as black circles.
IRAS point sources in the region are shown as black triangles. Figure 6: A
cumulative distribution of the peak $A_{v}$ of those 70 $\mu$m sources which
lie on or close to a column density peak (i.e. the blue circles in figure 5).

##  5 Discussion

###  5.1 Clump properties

Figure 7: A map showing the outlines of the 33 clumps identified overlaid on the column density map. Clumps shown in green harbour a 70 $\mu$m source inside their boundaries. Those which do not are shown in black. The grey contour shows the $A_{v}$ = 1 mag threshold for reference. Clump ID |  RA [deg] |  DEC [deg] |  Peak $A_{v}$ [mag] |  Mass [M⊙] |  Bmaj [pc] |  Bmin [pc] |  $<T_{d}>$ [K] |  Lbol [L⊙] |  70 $\mu$m assoc.
---|---|---|---|---|---|---|---|---|---
Main filament |  |  |  |  |  |  |
C0 |  102.078 |  -2.605 |  9.0 |  98.6 |  0.81 |  0.40 |  12.7 |  62.2 |  S0,S1
C1 |  102.007 |  -2.608 |  3.8 |  20.4 |  0.40 |  0.30 |  13.0 |  9.1 |  None
C2 |  102.087 |  -2.562 |  4.9 |  28.5 |  0.53 |  0.22 |  12.8 |  10.9 |  None
C3 |  102.004 |  -2.563 |  2.3 |  7.9 |  0.54 |  0.13 |  13.4 |  4.6 |  None
C4 |  102.069 |  -2.535 |  6.9 |  106.5 |  1.04 |  0.57 |  12.9 |  67.0 |  S3
C5 |  102.119 |  -2.545 |  7.4 |  88.0 |  0.87 |  0.37 |  12.8 |  50.1 |  S2
C6 |  102.021 |  -2.531 |  2.5 |  16.1 |  0.46 |  0.26 |  13.3 |  8.9 |  None
C7 |  102.007 |  -2.468 |  4.2 |  29.9 |  0.61 |  0.29 |  13.3 |  15.3 |  None
C8 |  101.984 |  -2.394 |  11.3 |  214.1 |  1.57 |  0.60 |  13.0 |  139.0 |  S4,S5
C9 |  101.913 |  -2.275 |  2.4 |  9.1 |  0.54 |  0.16 |  13.7 |  5.8 |  None
C10 |  101.983 |  -2.275 |  4.4 |  18.2 |  0.33 |  0.23 |  13.0 |  7.4 |  None
C11 |  101.962 |  -2.216 |  20.3 |  227.3 |  1.19 |  0.36 |  13.9 |  505.2 |  S6
C12 |  102.004 |  -2.204 |  2.8 |  11.8 |  0.30 |  0.25 |  13.6 |  7.1 |  None
C13 |  101.981 |  -2.171 |  9.0 |  79.8 |  0.73 |  0.26 |  12.5 |  24.5 |  None
C14 |  101.979 |  -2.143 |  12.4 |  33.6 |  0.41 |  0.18 |  13.2 |  69.5 |  S7
C15 |  101.965 |  -2.085 |  18.5 |  204.4 |  1.61 |  0.31 |  12.6 |  123.9 |  S8,S9
C16 |  101.947 |  -2.030 |  5.8 |  19.6 |  0.42 |  0.15 |  12.5 |  6.1 |  None
C17 |  101.922 |  -1.999 |  5.9 |  70.5 |  0.81 |  0.46 |  13.0 |  28.9 |  None
C18 |  101.903 |  -1.952 |  4.4 |  13.4 |  0.34 |  0.22 |  13.2 |  6.4 |  None
C19 |  101.895 |  -1.898 |  4.9 |  55.3 |  0.78 |  0.36 |  13.1 |  25.0 |  None
Head structure |  |  |  |  |  |  |
C20 |  102.063 |  -2.745 |  7.3 |  124.4 |  0.94 |  0.54 |  13.0 |  83.1 |  S11
C21 |  101.962 |  -2.748 |  3.0 |  22.4 |  0.43 |  0.35 |  13.5 |  13.0 |  None
C22 |  102.190 |  -2.737 |  3.7 |  43.0 |  0.75 |  0.31 |  13.5 |  23.8 |  None
C23 |  102.113 |  -2.736 |  6.4 |  121.4 |  1.13 |  0.52 |  13.2 |  56.6 |  None
C24 |  102.159 |  -2.727 |  3.9 |  44.3 |  0.70 |  0.37 |  13.5 |  24.2 |  None
C25 |  102.224 |  -2.713 |  5.4 |  63.7 |  1.00 |  0.32 |  13.2 |  30.2 |  None
C26 |  102.028 |  -2.717 |  3.0 |  21.8 |  0.68 |  0.21 |  13.3 |  11.7 |  None
C27 |  102.128 |  -2.712 |  4.4 |  46.8 |  0.68 |  0.35 |  13.4 |  24.5 |  None
C28 |  102.284 |  -2.706 |  6.7 |  87.1 |  0.77 |  0.61 |  13.0 |  38.1 |  None
C29 |  101.966 |  -2.691 |  3.3 |  23.3 |  0.67 |  0.19 |  13.5 |  12.6 |  None
C30 |  101.940 |  -2.684 |  3.7 |  16.7 |  0.35 |  0.26 |  13.4 |  8.6 |  None
C31 |  101.880 |  -2.677 |  2.3 |  7.4 |  0.30 |  0.18 |  13.8 |  4.9 |  None
C32 |  101.927 |  -2.666 |  2.4 |  8.5 |  0.36 |  0.17 |  13.8 |  5.7 |  None
Table 3: A table showing the properties of the 33 clumps identified in section
5.1. The columns are: the clump ID, the right ascension and declination
(J2000) in degrees, the peak $A_{v}$ within the clump, the mass of the clump,
the major and minor axes of the equivalent ellipse, the average dust
temperature within the clump, the bolometric luminosity of the clump, and the
associated 70 $\mu$m source (if there is one). The clumps are split into two
groups, those located in the main filament (top) and those located in the head
structure (bottom).

Due to the fact the resolution of the column density map (18.2”) at 2.3 kpc is
approximately 0.2 pc, we are unable to resolve individual core structures.
However, slightly larger scale clumps, which could be fragmented into a number
of cores, are resolved. To further investigate the quiescence of the G214.5
GMF we here study the properties of the numerous clumps which make up the GMF.

To identify clumps we use the same dendrogram technique as used to identify 70
$\mu$m sources, considering all dendrogram leaves to be clumps. We construct
the dendrogram using the corrected column density map produced in section 4.1
using the parameters: $\textsc{min\\_value}\,=\,1.86\times 10^{21}$ cm-2
($A_{v}$ = 2 mag), $\textsc{min\\_delta}\,=\,2.35\times 10^{20}$ cm-2 ($A_{v}$
= 0.25 mag), and $\textsc{min\\_npix}\,=\,36$ (approximately four 18.2” beam
sizes). These values are chosen as they ensure that only dense and well
resolved clumps are selected. The exact choice of min_delta has little result
on the identified clumps. Increasing the value of min_value leads to lower
mass clumps being excluded, while decreasing the value leads to numerous,
unwanted small fluctuations being included; the value of $1.86\times 10^{21}$
cm-2 is thus a good compromise. Figure 7 shows the outline of the 33 clumps
overlaid on the column density map, and table 3 summaries the properties of
these clumps.

One can see that the clumps are solely located within the boundaries of the
GMF, and are split between the main filament structure and the head structure.
Each clump may be approximated as an ellipse with the same moments of inertia
as its dendrogram structure, resulting in a major and minor axis. Note that
these values are not deconvolved with the beam. The average radius, defined as
the geometric average of the major and minor axes, range from 0.23 to 0.97 pc
and has a median of 0.42 pc. The aspect ratio ranges from 1.2, roughly
spherical, to 5.2, highly elongated, with a median of 2.1. Calculating the
clump masses from the exact dendrogram structure one finds that it ranges from
7.4 to 227.3 M⊙, with a median mass of 33.6 M⊙. Thus the clump population
consists of small low mass clumps as well as larger high mass clumps. The
total mass in clumps is 1984 M⊙, making up $\sim 23$ % of the mass of G214
above an $A_{v}$ of 1 mag.

We use the RJ-plots package from Clarke, Jaffa & Whitworth
(2022)333https://github.com/SeamusClarke/RJplots to automatically classify the
morphology of the clumps. Using the column density maps of the clumps, this
provides two RJ-values, $R_{1}$ and $R_{2}$, which approximately separate
elongation from central over-/under-density respectively. Figure 8 shows the
RJ-plot resulting from considering the column density maps of the 33 clumps in
G214.5. In total 18 of the 33 clumps are defined as being elongated (being in
the green or magenta regions of the plot), and 17 of the 33 clumps are
centrally over-dense (being in the yellow or green regions of the plot). In
general the distribution is consistent with the clump morphology expected from
filament fragmentation, as seen when comparing to the results of simulations
presented in figure 8 of Clarke, Jaffa & Whitworth (2022), where clumps range
from quasi-circular to highly elongated ($R_{1}>0.8$) and lie close to the
$R_{2}=0$ line.

Figure 8: An RJ-plot considering the column density maps of the 33 clumps
identified in G214.5. The $R_{1}$ value increases with increasing elongation
of a structure. Negative $R_{2}$ values are associated with central under-
density, typically due to the curvature and asymmetry, while positive $R_{2}$
values indicate central over-density. The red, solid line is the boundary
identified by Clarke, Jaffa & Whitworth (2022) which separates quasi-circular
objects, to the left of the line, from elongated structures, those to to the
right. In conjunction with the $R_{2}=0$ line this produces the four
classifications: (yellow) quasi-circular and centrally over-dense, (blue)
quasi-circular and centrally under-dense, (green) elongated and centrally
over-dense, and (magenta) elongated and centrally under-dense.

Cross referencing the embedded 70 $\mu$m sources found in the GMF with these
clumps one finds that 8 of the 33 clumps harbour sources. We identify these
clumps as protostellar as the presence of a 70 $\mu$m source is a reliable
indicator of active star formation (Dunham et al., 2008; Ragan et al., 2012).
Those without associated 70 $\mu$m sources we call starless clumps. Following
Ragan et al. (2016), we define the star-forming fraction (SFF) as the number
of clumps harbouring a 70 $\mu$m source over the total number of clumps 444We
caution direct comparison between the SFF values quoted here and those in
Ragan et al. (2016) due to the significantly different compact source
extraction methods used.. Seven of the eight protostellar clumps are located
in the main filament. The split of all clumps between the structures is 20 to
13, resulting in a difference of the star-forming fraction of 35.0% to 7.6%.
Thus the main filament is the preferential region for star formation in G214.5
while the clumps in the head structure are distinctly non-active.

We determine the bolometric luminosity of the clumps in a manner similar to
Elia et al. (2017). We use the Herschel flux density at 160, 250, 350 and 500
$\mu$m to fit a modified blackbody spectral energy distribution as done on a
pixel by pixel basis in section 4.1. For starless clumps, the bolometric
luminosity is equal to the integral of the fitted modified black body function
from 1 $\mu$m to 10 cm. For protostellar clumps, the excess at shorter
wavelengths must be taken into account; as such the bolometric luminosity is
split into two: the infra-red luminosity ($<160$ $\mu$m) and the sub-
millimetre luminosity ($>160$ $\mu$m). The sub-millimetre luminosity is
determined by the integration of the modified blackbody function from 160
$\mu$m to 10 cm. For the infra-red luminosity we use the 70 $\mu$m flux
density of the associated source, and take the 22 $\mu$m flux density as the
sum of contributions of the point sources from the ALLWISE source catalogue
(Cutri et al., 2021) which lie within the clump. This is done as some clumps,
such as C11, can be seen to harbour multiple WISE sources. To calculate the
luminosity we linearly interpolate between the 22, 70 and 160 $\mu$m flux
densities and integrate the area below this line. The resulting bolometric
luminosities range from 4.6 to 505.2 L⊙ with a median value of 23.8 L⊙,
leading to luminosity-mass ratios ranging from 0.31 to 2.22 L⊙/M⊙ and a median
value of 0.55 L⊙/M⊙. Bolometric luminosities are also included in table 3.

###  5.2 Clump statistics

Figure 9: A plot showing the mass-radius relationship of the main filament
clumps (black) and the head clumps (red). Circles denote that the clump is
starless, triangles show that the clump is protostellar. Power-law fits to the
clump distributions are shown in dashed lines of their respective colour. Also
shown as small dots are the protostellar (blue) and starless (green) clumps
taken from the Hi-GAL survey (Elia et al., 2017) for reference, the high-mass
star formation criterion of Baldeschi et al. (2017) is shown as a purple solid
line, and the efficient star formation threshold of 116 M⊙ pc-2 proposed by
Lada, Lombardi & Alves (2010) as a yellow solid line. The error-bars on the
radius are given by the difference between the major and minor axes of the
ellipse fitted to each clump; thus, more elongated clumps will have greater
‘errors’. The error-bars on the mass are calculated by adding in quadrature
the uncertainty introduced by the background subtraction and the $30\%$
uncertainty from the column density estimation (as discussed in section 4.1).
As such they should be considered highly conservative estimates of the error.
Figure 10: A plot showing the mass-luminosity relationship of the main
filament clumps (black) and the head clumps (red). Circles denote that the
clump is starless, triangles show that the clump is protostellar. Also shown
as small dots are the protostellar (blue) and starless (green) clumps taken
from the Hi-GAL survey (Elia et al., 2017). The dashed black line shows the
luminosity to mass ratio of 1 L⊙/M⊙.The error-bars on the mass are calculated
by adding in quadrature the uncertainty introduced by the background
subtraction and the $30\%$ uncertainty from the column density estimation (as
discussed in section 4.1). As such they should be considered highly
conservative estimates of the error. The error-bars on the bolometric
luminosity are determined by propagating the flux errors through the
bolometric luminosity calculation described in section 5.1 in a Monte-Carlo
manner. They are of the order of $\sim 1\%$. Figure 11: A plot showing the
correlation matrix considering all 33 clumps in G214.5 and the eight clump
features: peak $A_{v}$, mass, radius, aspect ratio, average dust temperature,
bolometric luminosity, and the RJ-values $R_{1}$ and $R_{2}$. Significant
$\tau$ values (i.e. where $p<0.05$) are shown as black text and non-
significant values (i.e. where $p>0.05$) are shown as blue text in each
element of the matrix.

As there is a clear difference in star formation activity between clumps found
in the main filament and those in the head structure we use statistical
techniques to investigate if there are differences in the two clump
populations’ properties. Moreover, this can be extended to compare between the
G214.5 clumps and the wider clump population found as part of the Hi-GAL
survey by Elia et al. (2017, 2021).

We begin by studying the clump mass-radius relationship (shown in figure 9).
One sees that there is a tight correlation between the quantities and that
there is no clear difference between the filament and the head clumps, despite
the vast difference in SFF. Using a least-squared method to fit a power-law
relationship (M $\propto$ rα) between the two quantities results in nearly
identical exponents of 2.32 and 2.33. Comparing the masses and radii of the
G214.5 clumps to the Elia et al. (2017, 2021) sample, one sees that the G214.5
clumps are typically less massive for their size than the Hi-GAL clumps,
indicative of lower average surface densities. However, this difference is due
to the difference in clump identification techniques; the CuTEx method
employed by Elia et al. (2017, 2021) returns a considerably smaller clump
compared to the dendrogram method used here. This is shown in appendix B where
we show a comparison of the 16 co-incident clumps in the Elia et al. (2021)
sample and the catalogue compiled here. Excluding the background subtraction
performed in section 4.1 has only a small effect on the clump masses ($\sim
20\%$) and does not affect any trends seen in clump properties.

Examining figure 9, all 33 clumps lie below the high-mass star formation
criterion from Baldeschi et al. (2017), which is consistent with the lack of
high-mass star formation tracers found when the most massive and brightest
clump C11 (IRAS 06453-0209) was observed (Larionov et al., 1999; Furuya et
al., 2003; Sunada et al., 2007). Additionally one sees that the majority of
the clumps lie below the constant surface density line of 116 M⊙ pc-2 which is
proposed by Lada, Lombardi & Alves (2010) as a threshold for efficient star
formation. The lack of high surface density clumps is likely linked to the
general quiescence of G214.5 despite its high mass. However, the median
surface density of the filament and head clumps, 67 and 59 M⊙ pc-2
respectively, are very similar and cannot explain the difference in clump star
formation fraction (35.0% to 7.6%) between the two regions.

Figure 12: Normalised histograms showing the distribution of (left) peak
$A_{v}$ and (right) dust temperature of the clumps located in the main
filament (black) and the head structure (red).

In figure 10 we show the mass-luminosity relationship of the G214.5 clumps, as
well as the wider Hi-GAL sample. One sees little difference between the head
and main filament clumps and a strong correlation between the two quantities.
All 33 clumps are consistent with the distribution of Hi-GAL sample, with the
majority of the clumps lying in the overlap region between the starless and
protostellar distributions, or solely in the starless region. Only C11 and C14
lie in the clear protostellar region, likely due to hosting the two brightest
70 $\mu$m sources in the GMF, S6 and S7 respectively. These clumps have
bolometric luminosity to mass ratios of $\sim 2.1$ L⊙/M⊙; the other 31 clumps
have a ratio below 1 with a median value of 0.54 L⊙/M⊙. Considering the
evolutionary tracks of Molinari et al. (2008), the positions of the G214.5
clumps in the luminosity-mass plane are indicative of an early evolutionary
state, consistent with the fact that G214.5 may be a young GMF.

To avoid investigating the correlation between each pair of clump features
individually we use a correlation matrix to condense the information. We use
the Kendall rank correlation test, quantified as Kendall’s $\tau$, as a
measure of the correlation due to its non-parametric nature and robustness
(Kendall, 1938). We consider eight features of the clumps: the peak $A_{v}$,
the mass, the radius, the aspect ratio, the average dust temperature, the
bolometric luminosity, and the RJ-values $R_{1}$ and $R_{2}$. Figure 11 shows
the correlation matrix derived for all 33 clumps; significant $\tau$ values
(i.e. where $p<0.05$) are shown as black text and non-significant values (i.e.
where $p>0.05$) are shown as blue text.

One can see that there exist strong and significant correlations between most
pairs of clump features, except the aspect ratio, and the RJ-values $R_{1}$
and $R_{2}$. Thus, it appears that in G214.5, clump morphology plays little
role in determining clump properties. The dust temperature is the only feature
which exhibits negative correlations with other features. Comparing the
correlation matrices of the clumps found in the head structure and the main
filament yields no striking differences between the two clump populations. In
general, the correlations shown are expected and are in agreement with those
seen in the Hi-GAL data 555Peak $A_{v}$, aspect ratio, $R_{1}$ and $R_{2}$
values are not included in the Elia et al. (2017) sample and so could not be
compared.; however, the weak negative correlation between average dust
temperature and bolometric luminosity is unexpected and does not agree with
the Hi-GAL sample where a weak positive correlation is found. The weak
negative correlation found is a combination of the very small range of dust
temperatures ($\sim$ 12.5 to 14 K) but the large range of clump masses ($\sim$
7 to 230 M⊙), and the fact that the dust temperature is negatively correlated
with the clump mass (due to the majority of clumps being starless) while the
clump mass is very strongly correlated to the bolometric luminosity
($\tau=0.88$).

Despite the vast difference in the star formation fraction of the clumps
located in the main filament and those located in the head structures there
appear to be no clear differences in the populations when considering
correlations. Thus, we use the two-sided Anderson-Darling (AD) and Mann-
Whitney U (MW) null hypothesis tests to compare the 1D distributions of the
clump properties. We use the same properties as used in the correlation
matrix. Out of the six properties only the peak $A_{v}$ (MW: $p=0.04$) and
dust temperature (AD: $p=0.008$ and MW: $p=0.005$) distributions show
statistically significant differences between the clumps in the main filament
and the head structure. These distributions are shown in figure 12. There
exists a tail of high peak $A_{v}$ values in the filament clump distribution
which is absent in the head clump distribution. Taking a limit of 5.5 mag (as
this is $\sim$ 116 M⊙ pc-2, the efficient star formation threshold proposed by
Lada, Lombardi & Alves (2010)), 50 $\%$ of filament clumps have a peak $A_{v}$
above this value but this is the case for only 23 $\%$ of the head clumps. As
expected from the strong anti-correlation between temperature and peak $A_{v}$
($\tau=-0.51$, figure 11) the filament clumps having higher peak $A_{v}$
values than the head clumps are also colder than them. The overlap in
distributions is due predominately to the internal heating from protostellar
sources in the filament clumps.

Thus, one sees that while the clumps in the main filament are not considerably
different to those located in the head structure, and also show similar
relationships (i.e. figures 9, 10), that they are more deeply embedded
resulting in higher peak column densities and colder dust. This leads to a
larger proportion of filament clumps having peak column densities lying close
to, or above, the efficient star formation regime (see figure 12) and it is
this difference which results in the higher star formation fraction in the
filament compared to the head structure.

###  5.3 The main filament

Figure 13: A column density map showing the filament spine as a dashed, cyan
line. Contours show the boundaries of the clumps located in the main filament
(C0 to C19). Clumps shown in green harbour a 70 $\mu$m source inside their
boundaries. Those which do not are shown in white. The horizontal, dotted,
orange line denotes the separation between the upper and lower sections of the
filament.

Numerous giant molecular filaments have been studied by other authors (e.g.
Ragan et al., 2014; Zucker, Battersby & Goodman, 2018; Zhang et al., 2019) and
their physical properties, such as length, line-mass and widths, have been
reported. Due to the unique morphology of G214.5 we perform such an analysis
only on the main filament region, excluding the head structure. We follow the
methods presented in Clarke et al. (2019) and Clarke, Williams & Walch (2020)
to determine the filament properties and fragmentation.

We determine the main filament spine by following the same procedure laid out
in section 4.2.2 of Clarke, Williams & Walch (2020): the column density map is
convolved with a circular Gaussian kernel (here of size 10 pixels) to reduce
the impact of sub-structure, a column density threshold (here 1.5 $\times
10^{21}$ cm-2) is used to produce a binary image, a skeleton is built from the
binary image using a medial axis transformation, and finally the skeleton is
trimmed of unwanted side-branches, gaps are repaired and small manual
corrections are made to ensure high column density ridges are followed. The
exact choices of the smoothing length and column density threshold for this
process do not greatly affect the spine found; these values are used as they
reduce the number of side-branches and gaps in the skeleton. The resulting
spine is shown in figure 13 as a dashed cyan line.

From figure 13 one can see that the majority of the clumps located in the main
filament lie close to or on the filament spine. Moreover, all of those which
are protostellar lie on the spine, or close to the end in the cases of C0 and
C4 in the south. The current star formation activity in G214.5 is thus
confined to the dense ridge of the filament spine and is not widely
distributed.

| Whole | Upper | Lower
---|---|---|---
Length [pc] | 27.2 | 13.7 | 13.5
Width [pc] | 0.87 | 0.71 | 2.16
Aspect ratio | 31.2 | 19.3 | 6.25
Mass [M⊙] | 6570 | 3780 | 2790
Line-mass [M⊙/pc] | 242 | 277 | 207
Spine $A_{v}$ [mag] | 4.07 | 6.12 | 2.40
Spine $T_{d}$ [K] | 13.0 | 12.7 | 13.4
Table 4: A table showing the global properties of the main filament when
considering the whole filament, as well as when considering the upper and
lower sections separately. The spine $A_{v}$ and $T_{d}$ quantities are median
values along the filament spine defined in section 5.3.

As discussed in Clarke et al. (2019) one ought to straighten a filament, i.e.
map it to the orthogonal radius-longitudinal distance space, before analysis
to remove the complexity of the filament’s curvature. We use the Python code
FragMent666https://github.com/SeamusClarke/FragMent for this purpose. The
column density and dust temperature maps of the straightened filament is shown
in figure 14, as well as the corresponding longitudinal profiles. One can also
see the clear presence of the cores located along the spine as local column
density maxima, and those with embedded sources showing corresponding peaks in
dust temperature.

When looking at figure 14 one can also see that the filament can be split into
two distinct sections: a lower filament which is comprised of less dense,
warmer and more flocculent material, and an upper filament which has a
continuous, cold, dense spine and harbours the three brightest 70 $\mu$m
sources in the GMF (S6, S7, S9) corresponding to localised high temperatures.
Thus we consider these regions separately in our analysis using a boundary at
l = 13.5 pc. Using this boundary we may quantify the difference between the
two sections by looking at the median values of the column density and dust
temperature along the spine. For the upper filament these values are 6.12 mag
and 12.7 K, and for the lower filament they are 2.40 mag and 13.4 K.

The entire straightened filament has a length of 27.2 pc, resulting in similar
lengths of the upper and lower sections, 13.7 and 13.5 pc respectively. The
total mass within a radius of 4 pc of the entire filament spine is $\sim$ 6570
M⊙, leading to an average line-mass of 242 M⊙/pc. Considering the upper and
lower sections separately, the total masses are 3780 M⊙ and 2790 M⊙
respectively with corresponding line-masses of 277 M⊙/pc and 207 M⊙/pc. The
average line-mass of the filament is far in excess of the critical line-mass
of $\sim 16$ M⊙/pc for a thermally supported filament with gas temperature of
10 K (Ostriker, 1964), making G214.5 highly supercritical. These global
filament properties are summarised in table 4.

Figure 14: (Top) The column density map of the straightened filament. (Middle)
The dust temperature map of the straightened filament. (Bottom) The
longitudinal profiles of the column density and dust temperature of the
filament. The dashed vertical white/black line denotes the boundary between
the lower and upper filament at l = 13.5 pc. The dashed purple and green
vertical lines in the lower panel shows the mapped location of the starless
and protostellar clumps respectively (discussed in section 5.3.2).

####  5.3.1 The radial column density profile

Another important aspect of the filament to study is the radial column density
profile. The radial profile of the filament is shown in figure 15. Each
profile is centred such that the maximum column density occurs at $r=0$ pc as
there is no guarantee that the spine will perfectly trace this point. From
this centred radial profile we can define the left-hand side as $r<0$ pc and
the right-hand side as $r>0$ pc, consistent with figure 14.

One can see from figure 15 that that there exists variation between the
individual slices along the filament as well as considerable substructure to
the sides of the filament spine. To reduce the complexity we can characterise
the filament’s radial profile by taking the mean of the individual slices
(shown as solid lines in figure 15). One can see that the mean profile of the
whole filament is approximately symmetric, and this is also true when
considering the upper section only. However, in the lower section there exists
a clear asymmetry where the left-hand side is broader and shows a strong
excess at larger radii compared to the right-hand side. This is not a result
of averaging and can also be seen in the individual slices as well as the
column density map of the straightened filament (figure 14). Due to this
asymmetry, when determining the widths we treat the left- and right-side of
the profiles separately.

It is interesting to note that the asymmetric radial profiles seen in the
lower section are qualitatively similar to those seen by Peretto et al. (2012)
and Zavagno et al. (2020) who studied compressed filaments influenced by winds
in the Pipe nebula and HII regions in RCW 120 respectively. However, here it
is on the GMF scale rather than the $\sim 1$ pc length filaments observed
previously. It is also interesting to note the recent work by Bonne et al.
(2020a) investigating the Musca filament which links the asymmetric radial
profiles of the filament to the influence of large-scale asymmetric HI flows.

As is common when studying filament profiles (e.g. Arzoumanian et al., 2011),
we use a Plummer profile of the form:

$\Sigma_{P}(r)=\frac{\Sigma_{o}}{\left(1+(r/r_{o})^{2}\right)^{\left(\frac{p-1}{2}\right)}},$
(5)

where $\Sigma_{o}$ is the central column density, $r_{o}$ is the flattening
radius and $p$ is the radial profile’s power-law slope when $r\gg r_{o}$.
Note, we do not intend to claim that this is the true underlying radial
profile of the filament, it is clearly more complicated as shown by the
variety of individual slices, but it is an efficient method of characterising
the filament’s mean radial profile to readily compare to other examples. We
also take into account the fact that the profile is beam-smeared by convolving
the Plummer model, $\Sigma_{P}(r)$ ,with $g(r^{\prime})$, a Gaussian function
(FWHM = 0.203 pc, 18.2” at 2.3 kpc). Written explicitly:

$\Sigma(r)=\Sigma_{P}(r)*g(r^{\prime}).$ (6)

The fitting is achieved with a least-squared method and only the inner 2 pc
region is used to avoid undue influence from side structures. The results are
recorded in table 5 and the best fits are shown in figure 15 as dashed lines;
the Plummer models are seen to fit well to the observed column density
profiles, even beyond the 2 pc fitting range. We do not perform background
subtraction before fitting as correcting the column density map (section 4.1)
removes unrelated line-of-sight dust; thus, all material in the radial
profiles is material associated with the filament.

Figure 15: The radial profiles of the (top) whole filament, (middle) the upper section, and (bottom) the lower section of the filament where the transparent black dots show the individual radial slices and the solid blue and orange lines show the mean radial profile constructed from those slices of the left and right sides of the profile respectively. The corresponding error bars shows the error on the mean. Also show as dashed blue and red lines are the Plummer fits to the inner 2 pc of each profile. The vertical blue and orange dotted lines show the observed HWHM of the right and left sides respectively. Whole filament |  |
---|---|---
| Left side | Right side
$r_{o}$ [pc] | 0.009 $\pm$ 0.004 | 0.131 $\pm$ 0.009
$p$ | 1.36 $\pm$ 0.01 | 1.64 $\pm$ 0.01
$\Sigma_{o}$ [mag] | 9.04 $\pm$ 1.49 | 5.45 $\pm$ 0.16
$W$ [pc] | 0.380 | 0.490
Upper section |  |
| Left side | Right side
$r_{o}$ [pc] | 0.026 $\pm$ 0.007 | 0.097 $\pm$ 0.007
$p$ | 1.49 $\pm$ 0.01 | 1.64 $\pm$ 0.01
$\Sigma_{o}$ [mag] | 10.65 $\pm$ 1.08 | 7.90 $\pm$ 0.22
$W$ [pc] | 0.335 | 0.379
Lower section |  |
| Left side | Right side
$r_{o}$ [pc] | 0.027 $\pm$ 0.012 | 0.129 $\pm$ 0.017
$p$ | 1.24 $\pm$ 0.01 | 1.53 $\pm$ 0.01
$\Sigma_{o}$ [mag] | 3.43 $\pm$ 0.33 | 3.18 $\pm$ 0.17
$W$ [pc] | 1.472 | 0.691
Table 5: A table showing the fitting parameters of the convolved Plummer
profile model when applied to the left- and right-side of the whole filament,
upper section only and lower section only mean column density profiles. The
width reported, $W$, is the width at half-maximum of the corresponding column
density profile.

In all fits the resulting $r_{o}$ are found to be smaller than the beam-size,
some as small as $0.01$ pc. These values should not be considered real, but
rather show that the inner region is highly beam-smeared and that the true
narrowness of the filament is unresolved. Thus widths resulting from these
Plummer fits, or from other forms of fitting in the inner region, would result
in unreliable width estimation. As such we use the observed radius at which
the profile reaches half the maximum of the column density profile to quantify
the width (shown as vertical dotted lines in figure 15). This should be
considered as an upper estimate of the true underlying width. We see that the
whole filament has a width of 0.87 pc, the upper section is slightly narrower,
0.71 pc, and that the lower section is considerably wider, 2.16 pc. Moreover,
the asymmetry in the lower section is shown by the fact the the left-hand
profile has a width over twice that the of the right-hand side, while the
upper section is near symmetric.

Unlike the flattening radius, $r_{o}$, the power-law exponents, $p$, resulting
from the fits are unaffected by beam-dilution and are robust. These reveal an
additional asymmetry in the profiles, that the left-hand profiles have
shallower slopes compared to the right-hand profiles. This is apparent in both
the upper and lower sections of the filament.

To further investigate the asymmetry between the two sides of the filament we
use the asymmetry parameter developed by Peretto et al. (2012). The asymmetry
parameter, $A_{p}$, is defined as:

$A_{p}=\log{\left(\frac{\int_{-r^{\prime}}^{0}\Sigma_{L}(r)dr}{\int_{0}^{r^{\prime}}\Sigma_{R}(r)dr}\right)},$
(7)

where $\Sigma_{L}$ is the observed column density profile on the left-hand
side, $\Sigma_{R}$ is the same for the right-hand side, and $r^{\prime}$ is
the maximum radius of the shortest side of the profile to ensure the left- and
right-hand profiles are integrated over the same radial extent. Here we have
modified the original parameter by taking the logarithm so that the parameter
is now symmetric around a value of 0 (meaning perfect symmetry between the
left- and right-hand profiles). Considering the mean profiles of the lower and
upper sections separately, the asymmetry parameter is 0.292 and 0.001
respectively. Thus the lower section of the filament has nearly twice as much
mass on its left-hand side than on its right-hand side, while the upper
section is close to perfectly symmetric in terms of mass.

To ensure that this is not due to averaging along the lengths of the filament
sections we consider the asymmetry parameter locally. We calculate the mean
radial profile of 5 consecutive individual slices to avoid excessive noise and
determine the asymmetry parameter for this mean. As can be seen in figure 16,
the lower section of the filament is consistently asymmetric in favour of the
left-hand side and in some places reaches $A_{p}\sim 0.5$, i.e. the left-hand
side has more than triple the mass than the right-hand side. The upper section
oscillates between being left- and right-side heavy but rarely reaches the
asymmetry seen in the lower section. The asymmetry parameters measured in the
lower section are comparable to those found in the wind-compressed filaments
in the Pipe nebula (0.15 - 0.45, Peretto et al., 2012). Thus, from this
analysis, we conclude that there is robust evidence that the lower section of
G214.5 is asymmetric and likely being compressed from the east (this will be
further discussed in section 6).

Figure 16: The asymmetry parameter (equation 7) as a function of length along
the filament. The vertical, dotted, black line at l=13.5 pc denotes the
boundary between the lower and upper filament sections. The horizontal, dashed
orange and green lines show the asymmetry parameter for the mean column
density radial profile of the lower and upper sections respectively. The
horizontal, dashed, black line is at $A_{p}=0$, denoting perfect symmetry, to
help orientate the reader.

####  5.3.2 Is there a characteristic fragmentation length-scale?

Figure 17: (Left) The nearest neighbour (blue) and minimum spanning tree
(orange) clump separation spacings. (Right) The two-point correlation function
where the blue-shaded area is the 1$\sigma$ error. The horizontal dashed line
at $y=0$ denotes no deviation from randomness and is added to aid the reader.
Figure 18: A comparison between the properties of G214.5 and those of the GMFs
included in the Z18 catalogue. The median property value is shown as a white
circle and a black bar shows the interquartile range. The dashed, black,
horizontal line in each violin plot shows the property value for G214.5. In
the violin plot corresponding to mass, the dashed line is equal to 6570 M⊙,
the mass within 4 pc of the filament spine defined in section 5.3, and the
dotted line is equal to 16,200 M⊙, the total mass in the whole G214.5-1.8
region defined in section 4.2.

Equilibrium models of filament fragmentation result in the prediction of a
characteristic fragmentation length-scale, i.e. scales of 0.1 - 2 pc for
quasi-periodic core/clump spacing respectively, at approximately 4 times the
filament width (e.g. Inutsuka & Miyama, 1992). However, more dynamic models
including accretion and turbulence show that there may not be a clear
signature of quasi-periodic spacings for multiple reasons such as two-tier
hierarchical fragmentation, turbulent dominated fragmentation and/or the
presence of sub-filaments (Clarke, Whitworth & Hubber, 2016; Clarke et al.,
2017; Clarke, Williams & Walch, 2020).

We perform a statistically robust investigation of the possible presence of a
characteristic fragmentation length-scale following the recommendations made
by Clarke et al. (2019), using the nearest neighbour separations (NN), minimum
spanning tree separations (MST) and two-point correlation function methods. We
use the functions provided in FragMent for this purpose.

We map the 20 clumps located in the main filament section (C0-C19, seen in
figure 13) onto the same orthogonal radius-longitudinal distance space as the
straightened filament shown in figure 14. We consider only clumps located on,
or close to, the filament spine as we may assume that these are clumps formed
from the result of filament fragmentation. This is done by taking clumps which
are located within 0.7 pc of the spine. This value is chosen as it is
approximately twice the filament width, ensuring all clumps close to the
filament spine are included. The next closest clump is $\sim$ 1.3 pc away from
the spine. Using a 0.7 pc cut, 11 clumps are found with a maximum radial
distance of 0.36 pc (locations seen in the bottom panel of figure 14 as
vertical. dashed lines). For the null hypothesis tests we use a boundary box
with a length the same as the filament, $l=27.2$ pc, and a maximum radius of r
= $\pm 0.7$ pc. We also use 10,000 runs to sample the null hypothesis
distribution that 11 clumps are randomly placed within this boundary box. A
minimum separation distance of 0.84 pc is used when generating the null
hypothesis distribution as it corresponds to approximately four 18.2” beams.
Such a multiple of the beam size is used to account for the radial extent of
the clumps which on average have size of $\sim$ 0.4 pc (see section 5.1). This
minimum separation is sufficient as the smallest separation between any two
clumps is 1.21 pc.

The results of the three methods may be seen in figure 17. The median and
interquartile range of the NN distribution are 1.65 pc and 1.08 pc, and those
of the MST distribution are 2.61 pc and 1.39 pc. Both separation distributions
are peaked, with the nearest neighbour separation distribution containing a
possible second maximum at $\sim 3$ pc. One may thus conclude that such a
peaked distribution may be indicative of a characteristic fragmentation
length-scale but results from the AD test comparing these distributions from
those of randomly placed clumps results in $p-$values of 0.087 and $>$0.25 for
the NN and MST distributions respectively. Therefore, we cannot detect a
statistically significant departure from randomly placed clumps. This is
corroborated by the results of the two-point correlation function which is
consistently flat and close to zero. There is a possible deficiency of closely
spaced clumps below 2 pc but this is likely due to the non-zero size of the
clumps. Thus, we find no clear evidence of a characteristic fragmentation
length-scale in G214.5 which is consistent with observations of local
molecular filament fragmentation in the Gould belt (e.g. André et al., 2014;
Könyves et al., 2015). It would be of interest to investigate the further
fragmentation of the clumps into cores (as has been done in previous works
using interferometers, e.g. Sanhueza et al., 2019; Tang et al., 2019; Saha et
al., 2022) as Kainulainen et al. (2017) suggest that, with such data, one may
discover a two-tier fragmentation pattern. As Clarke et al. (2019) show that
such a pattern may only be robustly detected with a large enough number of
cores ($N>20$), the high number of clumps in G214.5 makes it a promising
target for such a follow up study.

####  5.3.3 Comparing G214.5 to other GMFs

It is pertinent to compare G214.5 to other known GMFs. As such we compare to
the sample of Zucker, Battersby & Goodman (2018) which comprises 45 GMFs found
in the inner Galaxy; hereafter known as the Z18 catalogue. In figure 18 we
compare G214.5’s median dust temperature, mass, length, line-mass, width and
aspect ratio to the Z18 sample. One can see that G214.5 is comparable to the
Z18 filaments in most regards; however, there are two properties which make
G214.5 unique. As previously noted in section 4.2, G214.5 is considerably
colder than the GMFs found in the Z18 catalogue, likely due to the lower
interstellar radiation field in the outer galaxy and the low level of internal
heating from the scant number of protostars. Moreover, G214.5 is the narrowest
GMF known when compared to the Z18 filaments seen in emission, with a width of
0.87 pc compared to Nessie’s 0.90 pc. We note that G214.5 is closer than most
of the GMFs studied in Z18 (distance range of 1.9-9.9 kpc), though is at a
distance comparable to Nessie, 2.8 kpc.

Zhang et al. (2019) present a catalogue of 57 inner galaxy GMFs, with some
GMFs also included in the Z18 catalogue, mostly using 13CO data. Comparing to
this dataset we see a similar picture to that seen when comparing to Z18;
G214.5 is comparable in its mass and length, though less massive and shorter
than the median, but it has an extremely high aspect ratio, $\sim$31 vs.
1.1-6.7.

Comparing to the recent work by Colombo et al. (2021) which covers 37 GMFs in
the outer Galaxy, we find that G214.5 has a length consistent with their
sample, but due to its narrowness has an aspect ratio greater than any GMF
they considered. One finding of Colombo et al. (2021) is that the average mass
and line-mass of the GMFs in the outer Galaxy is an order of magnitude below
that of those in the inner Galaxy. G214.5 is an exception here and is quite
massive in comparison, being more massive than all but 3 GMFs in the Colombo
et al. (2021) sample. This exceptionalism is also evident in the fact that
G214.5’s position is consistent with it lying within the Perseus arm while
Colombo et al. (2021) find that nearly all of their sample are associated with
inter-arm regions. Thus, G214.5 appears distinct, neither fully resembling an
inner or an outer Galaxy GMF.

Zucker, Battersby & Goodman (2018) additionally report the radial profile
exponent, $p$, from their Plummer-fits of the Bone and large-scale Herschel
filament sub-samples and find that they range between 2 and 5.5. Thus they lie
separate from the small-scale local filaments studied by Arzoumanian et al.
(2011) which find radial profile exponents in the range 1 to 2.5. In contrast,
G214.5 possesses a radial profile exponent of 1.3 - 1.6 (dependent on which
side of the radial profile is considered) making it unique amongst GMFs while
being typical of smaller-scale filaments.

Defining the cold and high column density fraction (CCDF) as the number of
pixels with a column density above $10^{22}$ cm-2 divided by the number with a
column density above $3\times 10^{21}$ cm-2 while having a dust temperature
below 20 K, Zucker, Battersby & Goodman (2018) use this quantity in
conjunction with the aspect ratio to separate their catalogue sample into 3
populations. These are: elongated giant molecular clouds that appear to be
high aspect ratio giant molecular clouds (aspect ratio $\sim$ 8, CCDF $<$
0.1); elongated dense core complexes which are networks of dense and compact
clumps embedded in giant molecular clouds (aspect ratio $\sim$ 10, 0.1 $<$
CCDF $<$ 0.75); and Bone candidates which are highly elongated and dense
filaments (aspect ratio $>$ 20, 0.1 $<$ CCDF $<$ 0.5). With an aspect ratio of
31.2, G214.5 is consistent with the Bone candidate population but due to its
deficiency of high column density gas it has a CCDF of 0.03, meaning that
G214.5 lies outside of these 3 populations. It is unclear what causes the cold
and high column density of G214.5 to be so low and for it to lie so far from
the Bone candidate population. Connecting this to the low rate of star
formation in the cloud, it could be that G214.5 is a young cloud which has not
evolved sufficiently to acquire a large amount of dense gas. Or, combined with
the asymmetric column density profiles and the evidence for compression, the
wider environment, and possible formation mechanism of G214.5, prevents the
assembly of a large quantity of dense gas; this is further discussed in the
following section.

##  6 A HI superbubble compressing G214.5?

Figure 19: (Top) A channel map of the HI 21 cm line intensity at 17 km/s taken
showing the environment surrounding G214.5-1.8. The dashed ellipse outlines
the HI superbubble GSH214.0+00.0+017.5 identified by Ehlerová & Palouš (2013)
to be centred at 17.5 km/s. The white contour shows the $A_{v}$ = 1 mag level
of the G214.5 GMF. The HI data is taken from the full-sky HI survey HI4PI
(HI4PI Collaboration et al., 2016). (Bottom) The mean HI brightness in the
region $b=\pm 3\degree$ as a position-velocity diagram. The green dashed
ellipse shows the HI superbubble’s location in position-velocity space and the
white dashed ellipse shows the location of G214.5 using the kinematic
information from Yan et al. (2019).

It has long been known that there exist large-scale bubbles within the ISM
(Heiles, 1979, 1984; McClure-Griffiths et al., 2002; Churchwell et al., 2006;
Ehlerová & Palouš, 2013). In HI surveys these features appear as superbubbles
with radii above 100 pc which are thought to form due to stellar wind and
supernova feedback (McCray & Snow, 1979; Bruhweiler et al., 1980; McCray &
Kafatos, 1987; Inutsuka et al., 2015). Using the catalogue of HI shells in the
Leiden/Argentina/Bonn (LAB) HI survey by Ehlerová & Palouš (2013) we find that
G214.5-1.8 is co-incident, both spatially and kinematically, with the
superbubble GSH214.0+00.0+017.5 (figure 19).

Ehlerová & Palouš (2013) find that this superbubble is located approximately 2
kpc away with a major axis of $\sim$ 350 pc and minor axis of $\sim$ 170 pc,
and lies in the velocity range 8.2 - 23.7 km/s, centred at 17.5 km/s. It is
thus possible that G214.5 may lie in the far-side of the shell of this
superbubble as Yan et al. (2019) find that G214.5 lies at a distance of
2.15-2.45 kpc and with a velocity range of $\sim$ 22-32 km/s. The presence of
a bubble is apparent in the HI channel map at 17 km/s taken from the full-sky
survey HI4PI, shown in the top panel of figure 19, which has better angular
resolution than the LAB HI survey data used by Ehlerová & Palouš (2013) to
identify it. The kinematic connection can be seen in the HI position-velocity
diagram in the bottom panel of figure 19, which uses the velocity information
from Yan et al. (2019) to show the location of G214.5. Furthermore, the bubble
is also evidenced by a highly porous morphology seen within the bubble ellipse
when observing dust continuum emission from WISE 12 $\mu$m to the Herschel 500
$\mu$m. Additionally, recent work using Gaia and 2MASS data to infer 3D maps
of the the Galactic dust distribution find a cavity devoid of significant dust
extinction between l $\sim 205\degree$ and l $\sim 220\degree$ in front of
G214.5’s location, in agreement with the placement of the superbubble by
Ehlerová & Palouš (2013) (see figure 9 of Lallement et al., 2019). This strong
evidence of association means that discussing the consequences of an
interaction between the superbubble and G214.5 may be highly fruitful.

The signs of large-scale radial compression in the G214.5 filament shown in
section 5.3.1 is highly compatible with the presence of a co-incident,
interacting superbubble. In such a hypothetical scenario the large-scale flow
driven by the superbubble compresses the main filament structure, most clearly
seen in the lower section of the filament, while the head structure has been
strongly ablated and torn apart. This would also explain the unique morphology
of G214.5: the north-south filament has been compressed from the east and lies
completely perpendicular to the head structure which has been disrupted and
elongated along the east-west axis by the flow. Moreover, if the filament is
mostly compressed by the superbubble while the head structure has
predominately been ablated then it could explain the extreme disparity in the
location of dense gas in G214.5, 99$\%$ being in the main filament, and thus
why star formation is concentrated in the main filament. The origin of why the
interaction between G214.5 and the superbubble is different between the
filament and the head could be due to a combination of the angle of
interaction and a pre-existing north-south density gradient across G214.5;
from Yan et al. (2019) one sees that the head structure is kinematically
closer to the bubble than the main filament, lying at $\sim 22-24$ km/s
compared to $\sim 28-32$ km/s.

It is important to also note that the main filament is not purely compressed.
As can be seen in the column density plots, there is a large volume of
flocculent gas seen to the west of the main filament, predominately in the
lower section. Goldsmith & Pittard (2020) show that a shock interacting with a
filament may compress a portion of the gas while leading to a steady turbulent
stripping of material producing a flocculent wake. This two-sided interaction,
in addition to G214.5’s potential youth (evidenced by the low star formation
activity and low clump luminosity-to-mass ratios), may explain the relatively
poor amount of dense gas in G214.5’s main filament and why the cloud lies so
far from other GMFs in this respect when it is similar in other global
quantities, i.e. total mass, length, aspect ratio. Further simulation work
investigating such two-sided interaction as well self-gravity and pre-existing
density gradients in filaments would be beneficial.

To determine the feasibility of this possible interaction one may consider the
timescales of the processes involved. Works studying the interaction of shocks
with clouds (Klein, McKee & Colella, 1994; Xu & Stone, 1995) show that the
most relative dynamical timescale is the cloud-crushing time,
$t_{cc}=r_{c}\chi^{0.5}/v_{s}$, where $r_{c}$ is the equivalent spherical
cloud radius, $\chi$ the ratio of cloud density by ambient medium, and $v_{s}$
is the shock speed in the ambient medium. Taking the area above an $A_{v}$ of
1 for G214.5 from table 1 results in an equivalent circle radius of 8.7 pc. To
estimate $\chi$ we use the radial profiles determined in section 5.3.1 and
take the ratio of the central column density and column density at $r=4$ pc,
resulting in a range of approximately $4-10$. Ehlerová & Palouš (2013) give an
expansion speed of $\sim$8 km/s for GSH214.0+00.0+017.5 and we use this for
$v_{s}$. Combined this gives an estimate of the the cloud-crushing time of 2-3
Myr.

To compare to the cloud-crushing time we calculate the free-fall time for a
filamentary cloud using the equation given by Clarke & Whitworth (2015):
$t_{ff}=(0.49+0.26A_{o})/\sqrt{G\rho}$, where $A_{o}$ is the initial aspect
ratio of the filament and $\rho$ the average volume density. The initial
aspect is unknown but we may instead take the current calculated aspect ratio
of 31.2 to produce a lower limit. To estimate the average density we take the
average column density on the spine and divide by the filament width (both
taken from table 4), resulting in $\rho=6.7\times 10^{-21}$ g/cm-3 ($n\sim
1500$ cm-3). This gives a lower limit on the free-fall time of $\sim$ 13 Myr.
From this one sees that the cloud-crushing time is sufficiently small compared
to the free-fall time that an interaction with the superbubble would dominate
the evolution of G214.5 and is fast enough for stripping to occur before
gravity may regather material. Moreover, as clouds are fully disrupted by a
shock on the order of one to two cloud-crushing times (here a few Myr), G214.5
would have to be relatively youthful for it to be observed in the contiguous
state that it is if impacted by the HI superbubble.

To more fully support our hypothesis that G214.5 is impacted by the
superbubble GSH214.0+00.0+017.5, kinematic studies are necessary and is the
aim of a future paper (Clarke et al. in prep.). Speculating on what one may
see if there is an interaction between G214.5 and the superbubble, the
resulting compression may appear as a radial velocity gradient across the
filament spine while the stripped material may show signs such as higher
levels of turbulence. The head structure, if strongly ablated, would consist
of lower volume density gas and show a highly turbulent structure. Moreover,
careful examination of HI data and CO data in PPV space may further strengthen
the association between the superbubble and G214.5, as for example been done
by Dawson et al. (2008) when studying the Carina Flare superbubble’s
interaction with molecular clouds.

##  7 Conclusions

In this paper we have used Herschel data to construct column density and dust
temperature maps of the giant molecular filament G214.5-1.8, as well as a 70
$\mu$m source catalogue and a clump catalogue. These data have shown that
G214.5 is a unique GMF in multiple ways.

We show that G214.5 is a giant molecular filament consisting of two distinct
regions, a narrow north-south main filament and a perpendicular, flocculent,
east-west head structure. Investigating the global properties of G214.5, we
find that it is a massive GMF, $\sim 16,000$ M⊙, yet hosts only 15 potential
protostellar 70 $\mu$m sources, making it distinctly quiescent compared to
equally massive clouds such as Mon R2 and Serpens. This unusually quiescence,
and G214.5’s paucity of dense gas, may be due it being a young cloud which has
yet to begin star formation in earnest but a more in-depth audit of its star
formation history is needed to determine this with certainty.

When investigating the fragmentation of the cloud into clumps, we find a total
of 33 clumps with masses ranging from 7 to 227 M⊙. These clumps are similar in
their general properties to those found in the Hi-GAL sample from Elia et al.
(2017, 2021) but fall below the high-mass star formation criterion of
Baldeschi et al. (2017), compatible with previous surveys failing to detect
any tracers of high-mass star formation in G214.5. Furthermore, we find that 8
of the 33 clumps are associated with a 70 $\mu$m source and are thus
protostellar; however, these protostellar clumps are not distributed evenly
across G214.5 but predominately located in the main filament (a star-forming
fraction of 35$\%$ in the main filament versus 7.6$\%$ in the head structure).
We find no statistically significant difference between the clumps in the main
filament and the head structure to explain this striking difference in star
forming potential, except that the clumps located in the main filament are
colder and reach higher peak column densities. From this we infer that the
main filament clumps are more deeply embedded and contain a higher proportion
of dense gas, both properties promoting star formation. This is supported by
the fact that the main filament hosts 99$\%$ of the dense gas ($A_{v}>$ 7 mag)
in G214.5.

Focusing on the main filament structure, we find that it is approximately 27
pc long and has a width of 0.87 pc, resulting in an aspect ratio of 31.
Further, we see that it has a line-mass of 242 M⊙/pc, making it highly super-
critical and requiring turbulent or magnetic support to remain long-lived.
There exist 11 clumps which lie on the filament spine which when studied
reveal no statistically significant characteristic fragmentation separation,
in agreement with recent filament fragmentation models (e.g. Clarke, Williams
& Walch, 2020) and Herschel observations of local filaments (e.g. André et
al., 2014; Könyves et al., 2015).

Studying the radial profile of the main filament, we find that the filament
may be split into two roughly equal halves with distinct properties, the upper
and the lower section. The upper section shows a continuos, cold and dense
spine with a narrow and symmetric radial profile (0.71 pc), and the lower
section is less dense, warmer, more flocculent and possesses a wide and
asymmetric radial profile (2.16 pc). The asymmetry of the lower section is
such that the left-hand side of the filament has twice the mass of the right-
hand side, and a width over twice the size. The asymmetric radial profiles are
highly reminiscent of the profiles of compressed smaller-scale filaments and
have comparable asymmetry parameters to those wind-compressed filaments found
in the Pipe nebula (Peretto et al., 2012).

Comparing G214.5 to other giant molecular filaments studied in the Zucker,
Battersby & Goodman (2018) catalogue, we find that it is similar in most
global properties to those clouds classified as ’Bone’ candidates (highly
elongated and massive filaments) but is both colder and narrower than any
other. While being most similar to these ’Bone’ candidate GMFs out of the 3
population groups suggested by Zucker, Battersby & Goodman (2018), G214.5
differs significantly from them due to its low cold and high column density
fraction: 0.03 compared to the typical range of 0.1 - 0.5. Comparing to the
outer Galaxy GMFs studied by Colombo et al. (2021), we find that G214.5 is
comparable in size but is one of the most elongated and massive GMFs.

Considering the wider environment of G214.5, we find evidence that the GMF
lies at the edge of the HI superbubble GSH214.0+00.0+017.5 found by Ehlerová &
Palouš (2013). From considering the distances to the bubble and G214.5, as
well as the kinematics, we suggest that G214.5 lies on the far-side of the
superbubble’s shell. A hypothetical interaction of G214.5 with a superbubble
has the potential to explain the large-scale compression seen as well as the
unique morphology of a dense, compressed main filament lying perpendicular to
an eroded, diffuse head structure. From considering the relevant timescales we
show that it is possible for such an evolution to occur within a fraction of a
cloud free-fall time. It is unclear whether G214.5 may have formed in the
shell of the superbubble, or if it was a pre-existing structure which has been
impacted by the shell’s expansion. Both scenarios are consistent with the
bubble-driven ISM picture presented by Inutsuka et al. (2015) which emphasises
the important role of large-scale feedback bubbles in promoting cloud
formation. We wish to highlight that while such bubbles may compress material,
G214.5 is a potential example where they may simultaneously erode gas from
structures leading to a complex interplay of compression and ablation which
has consequences on the resulting star formation; a scenario supported by the
simulations of Goldsmith & Pittard (2020).

We conclude that G214.5-1.8 is a cold, massive and quiescent giant molecular
filament which is potentially still young and in an early stage of its
evolution. While being similar to the highly elongated and massive ’Bone’
candidate filaments, G214.5 is unique in its paucity of dense gas which is
likely connected to its quiescence and possible youth. A potential interaction
with a HI superbubble may have lead to the large-scale compression of parts of
the GMF while simultaneously ablating other regions, resulting in uneven star
formation activity across the cloud. Thus, G214.5 may serve as an example of
the intersection of the bubble-driven ISM paradigm of Inutsuka et al. (2015)
and the filament paradigm of star formation presented by André et al. (2014),
an idea developed in the upcoming PPVII chapter Pineda et al. (2022), making
it a unique and interesting object worthy of further study.

##  8 Acknowledgments

SDC would like to thank Ya-Wen Tang and Ana Duarte-Cabral for discussions
which have improved the paper. The authors also thank the anonymous referee
for their helpful comments. SDC is supported by the Ministry of Science and
Technology (MoST) in Taiwan through grant MoST 108-2112-M-001-004-MY2. ASM
acknowledges support from the Collaborative Research Centre (SFB 956, sub-
project A6), funded by the Deutsche Forschungsmeneinschaft (DFG). GMW
acknowledges support from the UK’s Science and Technology Facilities Council
(STFC) under grant number ST/W00125X/1. ADPH gratefully acknowledges the
support of a PhD studentship from the UK Science and Technology Facilities
Council (STFC). SW acknowledges support from the ERC starting grant No. 679852
‘RADFEEDBACK’ and thanks the DFG for funding through the Collaborative
Research Center (SFB956) on the ‘Conditions and impact of star formation’
(sub-project C5). NS acknowledges support by the Agence National de Recherche
(ANR/France) and the Deutsche Forschungsgemeinschaft (DFG/Germany) through the
project ‘GENESIS’ (ANR-16-CE92-0035-01/DFG1591/2-1).

##  9 Data availability

The data underlying this article will be shared on reasonable request to the
corresponding author. The analysis tool of this work, FragMent, is made freely
available at https://github.com/SeamusClarke/FragMent.

## References

  * Abreu-Vicente et al. (2016) Abreu-Vicente J., Ragan S., Kainulainen J., Henning T., Beuther H., Johnston K., 2016, A&A, 590, A131
  * André et al. (2014) André P., Di Francesco J., Ward-Thompson D., Inutsuka S.-I., Pudritz R. E., Pineda J. E., 2014, Protostars and Planets VI, 27
  * André et al. (2010) André P. et al., 2010, A&A, 518, L102
  * Arzoumanian et al. (2011) Arzoumanian D. et al., 2011, A&A, 529, L6
  * Arzoumanian et al. (2019) Arzoumanian D. et al., 2019, A&A, 621, A42
  * Arzoumanian et al. (2013) Arzoumanian D., André P., Peretto N., Könyves V., 2013, A&A, 553, A119
  * Baldeschi et al. (2017) Baldeschi A. et al., 2017, MNRAS, 466, 3682
  * Barnard (1907) Barnard E. E., 1907, ApJ, 25
  * Bernard et al. (2010) Bernard J. P. et al., 2010, A&A, 518, L88
  * Bica, Dutra & Barbuy (2003) Bica E., Dutra C. M., Barbuy B., 2003, A&A, 397, 177
  * Bohlin, Savage & Drake (1978) Bohlin R. C., Savage B. D., Drake J. F., 1978, ApJ, 224, 132
  * Bonne et al. (2020a) Bonne L. et al., 2020a, A&A, 644, A27
  * Bonne et al. (2020b) Bonne L. et al., 2020b, A&A, 641, A17
  * Borchert et al. (2021) Borchert E. M. A., Walch S., Seifried D., Clarke S. D., Franeck A., Nürnberger P., 2021, arXiv e-prints, arXiv:2102.00778
  * Bruhweiler et al. (1980) Bruhweiler F. C., Gull T. R., Kafatos M., Sofia S., 1980, ApJ, 238, L27
  * Churchwell et al. (2006) Churchwell E. et al., 2006, ApJ, 649, 759
  * Cigan (2019) Cigan P., 2019, MultiColorFits: Colorize and combine multiple fits images for visually aesthetic scientific plots
  * Clarke, Jaffa & Whitworth (2022) Clarke S. D., Jaffa S. E., Whitworth A. P., 2022, MNRAS, 516, 2782
  * Clarke & Whitworth (2015) Clarke S. D., Whitworth A. P., 2015, MNRAS, 449, 1819
  * Clarke et al. (2017) Clarke S. D., Whitworth A. P., Duarte-Cabral A., Hubber D. A., 2017, MNRAS, 468, 2489
  * Clarke, Whitworth & Hubber (2016) Clarke S. D., Whitworth A. P., Hubber D. A., 2016, MNRAS, 458, 319
  * Clarke et al. (2018) Clarke S. D., Whitworth A. P., Spowage R. L., Duarte-Cabral A., Suri S. T., Jaffa S. E., Walch S., Clark P. C., 2018, MNRAS
  * Clarke et al. (2019) Clarke S. D., Williams G. M., Ibáñez-Mejía J. C., Walch S., 2019, MNRAS, 484, 4024
  * Clarke, Williams & Walch (2020) Clarke S. D., Williams G. M., Walch S., 2020, MNRAS, 497, 4390
  * Codella et al. (1995) Codella C., Palumbo G. G. C., Pareschi G., Scappini F., Caselli P., Attolini M. R., 1995, MNRAS, 276, 57
  * Colombo et al. (2021) Colombo D. et al., 2021, A&A, 655, L2
  * Cox et al. (2016) Cox N. L. J. et al., 2016, A&A, 590, A110
  * Cutri et al. (2021) Cutri R. M. et al., 2021, VizieR Online Data Catalog, II/328
  * Dawson et al. (2008) Dawson J. R., Mizuno N., Onishi T., McClure-Griffiths N. M., Fukui Y., 2008, MNRAS, 387, 31
  * Duarte-Cabral & Dobbs (2016) Duarte-Cabral A., Dobbs C. L., 2016, MNRAS, 458, 3667
  * Duarte-Cabral & Dobbs (2017) Duarte-Cabral A., Dobbs C. L., 2017, MNRAS, 470, 4261
  * Dunham et al. (2008) Dunham M. M., Crapsi A., Evans, Neal J. I., Bourke T. L., Huard T. L., Myers P. C., Kauffmann J., 2008, ApJS, 179, 249
  * Ehlerová & Palouš (2013) Ehlerová S., Palouš J., 2013, A&A, 550, A23
  * Elia et al. (2021) Elia D. et al., 2021, MNRAS, 504, 2742
  * Elia et al. (2017) Elia D. et al., 2017, MNRAS, 471, 100
  * Felli, Palagi & Tofani (1992) Felli M., Palagi F., Tofani G., 1992, A&A, 255, 293
  * Fiorellino et al. (2021) Fiorellino E. et al., 2021, MNRAS, 500, 4257
  * Fischera & Martin (2012) Fischera J., Martin P. G., 2012, A&A, 542, A77
  * Fukui (1989) Fukui Y., 1989, in European Southern Observatory Conference and Workshop Proceedings, Vol. 33, European Southern Observatory Conference and Workshop Proceedings, pp. 95–117
  * Furuya et al. (2003) Furuya R. S., Kitamura Y., Wootten A., Claussen M. J., Kawabe R., 2003, ApJS, 144, 71
  * Goldsmith & Pittard (2020) Goldsmith K. J. A., Pittard J. M., 2020, MNRAS, 491, 4783
  * Gómez & Vázquez-Semadeni (2014) Gómez G. C., Vázquez-Semadeni E., 2014, ApJ, 791, 124
  * Goodman et al. (2014) Goodman A. A. et al., 2014, ApJ, 797, 53
  * Griffin et al. (2010) Griffin M. J. et al., 2010, A&A, 518, L3
  * Heigl, Burkert & Gritschneder (2018) Heigl S., Burkert A., Gritschneder M., 2018, MNRAS, 474, 4881
  * Heigl, Burkert & Hacar (2016) Heigl S., Burkert A., Hacar A., 2016, MNRAS, 463, 4301
  * Heiles (1979) Heiles C., 1979, ApJ, 229, 533
  * Heiles (1984) Heiles C., 1984, ApJS, 55, 585
  * Heitsch (2013) Heitsch F., 2013, ApJ, 769, 115
  * HI4PI Collaboration et al. (2016) HI4PI Collaboration et al., 2016, A&A, 594, A116
  * Hildebrand (1983) Hildebrand R. H., 1983, QJRAS, 24, 267
  * Hodapp (1994) Hodapp K.-W., 1994, ApJS, 94, 615
  * Howard et al. (2019) Howard A. D. P., Whitworth A. P., Marsh K. A., Clarke S. D., Griffin M. J., Smith M. W. L., Lomax O. D., 2019, MNRAS, 489, 962
  * Inutsuka et al. (2015) Inutsuka S.-i., Inoue T., Iwasaki K., Hosokawa T., 2015, A&A, 580, A49
  * Inutsuka & Miyama (1992) Inutsuka S.-I., Miyama S. M., 1992, ApJ, 388, 392
  * Jackson et al. (2010) Jackson J. M., Finn S. C., Chambers E. T., Rathborne J. M., Simon R., 2010, ApJ, 719, L185
  * Joint Iras Science (1994) Joint Iras Science W. G., 1994, VizieR Online Data Catalog, II/125
  * Kainulainen et al. (2017) Kainulainen J., Stutz A. M., Stanke T., Abreu-Vicente J., Beuther H., Henning T., Johnston K. G., Megeath S. T., 2017, A&A, 600, A141
  * Kendall (1938) Kendall M. G., 1938, Biometrika, 30, 81
  * Kerschbaum & Hron (1994) Kerschbaum F., Hron J., 1994, A&AS, 106, 397
  * Klein, McKee & Colella (1994) Klein R. I., McKee C. F., Colella P., 1994, ApJ, 420, 213
  * Könyves et al. (2015) Könyves V. et al., 2015, A&A, 584, A91
  * Lada, Lombardi & Alves (2010) Lada C. J., Lombardi M., Alves J. F., 2010, ApJ, 724, 687
  * Lallement et al. (2019) Lallement R., Babusiaux C., Vergely J. L., Katz D., Arenou F., Valette B., Hottier C., Capitanio L., 2019, A&A, 625, A135
  * Larionov et al. (1999) Larionov G. M., Val’tts I. E., Winnberg A., Johansson L. E. B., Booth R. S., Golubev V. V., 1999, A&AS, 139, 257
  * Lee, Snell & Dickman (1991) Lee Y., Snell R. L., Dickman R. L., 1991, ApJ, 379, 639
  * Lee, Snell & Dickman (1994) Lee Y., Snell R. L., Dickman R. L., 1994, ApJ, 432, 167
  * Lee, Snell & Dickman (1996) Lee Y., Snell R. L., Dickman R. L., 1996, ApJ, 472, 275
  * Li & Klein (2019) Li P. S., Klein R. I., 2019, MNRAS, 485, 4509
  * MacConnell (2010) MacConnell D. J., 2010, VizieR Online Data Catalog, III/170B
  * Maddalena & Thaddeus (1985) Maddalena R. J., Thaddeus P., 1985, ApJ, 294, 231
  * Marsh et al. (2016) Marsh K. A. et al., 2016, MNRAS, 459, 342
  * McClure-Griffiths et al. (2002) McClure-Griffiths N. M., Dickey J. M., Gaensler B. M., Green A. J., 2002, ApJ, 578, 176
  * McCray & Kafatos (1987) McCray R., Kafatos M., 1987, ApJ, 317, 190
  * McCray & Snow (1979) McCray R., Snow, T. P. J., 1979, ARA&A, 17, 213
  * Mège et al. (2021) Mège P. et al., 2021, A&A, 646, A74
  * Miettinen (2018) Miettinen O., 2018, A&A, 609, A123
  * Molinari et al. (2008) Molinari S., Pezzuto S., Cesaroni R., Brand J., Faustini F., Testi L., 2008, A&A, 481, 345
  * Molinari et al. (2010) Molinari S. et al., 2010, A&A, 518, L100
  * Nony et al. (2021) Nony T. et al., 2021, A&A, 645, A94
  * Ossenkopf-Okada et al. (2016) Ossenkopf-Okada V., Csengeri T., Schneider N., Federrath C., Klessen R. S., 2016, A&A, 590, A104
  * Ostriker (1964) Ostriker J., 1964, ApJ, 140, 1056
  * Palmeirim et al. (2013) Palmeirim P. et al., 2013, A&A, 550, A38
  * Peretto et al. (2012) Peretto N. et al., 2012, A&A, 541, A63
  * Pineda et al. (2022) Pineda J. E. et al., 2022, arXiv e-prints, arXiv:2205.03935
  * Poglitsch et al. (2010) Poglitsch A. et al., 2010, A&A, 518, L2
  * Ragan et al. (2012) Ragan S. et al., 2012, A&A, 547, A49
  * Ragan et al. (2014) Ragan S. E., Henning T., Tackenberg J., Beuther H., Johnston K. G., Kainulainen J., Linz H., 2014, A&A, 568, A73
  * Ragan et al. (2016) Ragan S. E., Moore T. J. T., Eden D. J., Hoare M. G., Elia D., Molinari S., 2016, MNRAS, 462, 3123
  * Rayner et al. (2017) Rayner T. S. M. et al., 2017, A&A, 607, A22
  * Russeil et al. (2013) Russeil D. et al., 2013, A&A, 554, A42
  * Saha et al. (2022) Saha A. et al., 2022, MNRAS, 516, 1983
  * Sanhueza et al. (2019) Sanhueza P. et al., 2019, ApJ, 886, 102
  * Schneider et al. (2015) Schneider N. et al., 2015, MNRAS, 453, L41
  * Schneider et al. (2022) Schneider N. et al., 2022, arXiv e-prints, arXiv:2207.14604
  * Schneider & Elmegreen (1979) Schneider S., Elmegreen B. G., 1979, ApJS, 41, 87
  * Shetty et al. (2009) Shetty R., Kauffmann J., Schnee S., Goodman A. A., Ercolano B., 2009, ApJ, 696, 2234
  * Smith, Glover & Klessen (2014) Smith R. J., Glover S. C. O., Klessen R. S., 2014, MNRAS, 445, 2900
  * Smith et al. (2020) Smith R. J. et al., 2020, MNRAS, 492, 1594
  * Su et al. (2019) Su Y. et al., 2019, ApJS, 240, 9
  * Sunada et al. (2007) Sunada K., Nakazato T., Ikeda N., Hongo S., Kitamura Y., Yang J., 2007, PASJ, 59, 1185
  * Suri et al. (2019) Suri S. et al., 2019, A&A, 623, A142
  * Tang et al. (2019) Tang Y.-W., Koch P. M., Peretto N., Novak G., Duarte-Cabral A., Chapman N. L., Hsieh P.-Y., Yen H.-W., 2019, ApJ, 878, 10
  * van den Bosch et al. (2015) van den Bosch R. C. E., Gebhardt K., Gültekin K., Yıldırım A., Walsh J. L., 2015, ApJS, 218, 10
  * Wang et al. (2016) Wang K., Testi L., Burkert A., Walmsley C. M., Beuther H., Henning T., 2016, ApJS, 226, 9
  * Wang et al. (2015) Wang K., Testi L., Ginsburg A., Walmsley C. M., Molinari S., Schisano E., 2015, MNRAS, 450, 4043
  * Wang et al. (2020) Wang Y. et al., 2020, A&A, 641, A53
  * Williams et al. (2018) Williams G. M., Peretto N., Avison A., Duarte-Cabral A., Fuller G. A., 2018, A&A, 613, A11
  * Xu & Stone (1995) Xu J., Stone J. M., 1995, ApJ, 454, 172
  * Yan et al. (2019) Yan Q.-Z., Yang J., Sun Y., Su Y., Xu Y., 2019, ApJ, 885, 19
  * Zamora-Avilés, Ballesteros-Paredes & Hartmann (2017) Zamora-Avilés M., Ballesteros-Paredes J., Hartmann L. W., 2017, MNRAS, 472, 647
  * Zavagno et al. (2020) Zavagno A. et al., 2020, A&A, 638, A7
  * Zhang et al. (2019) Zhang M., Kainulainen J., Mattern M., Fang M., Henning T., 2019, A&A, 622, A52
  * Zucker, Battersby & Goodman (2018) Zucker C., Battersby C., Goodman A., 2018, ApJ, 864, 153
  * Zucker et al. (2020) Zucker C., Speagle J. S., Schlafly E. F., Green G. M., Finkbeiner D. P., Goodman A., Alves J., 2020, A&A, 633, A51

##  Appendix A Herschel band images

In figure 20 we show the maps of the 70, 160, 250, 350 and 500 $\mu$m Herschel
images used to produce the column density and dust temperature maps in section
4.1. Figure 21 is an RGB image of G214.5 to help compare the distributions of
the Herschel emission in different bands. The image was made using the Python
package MultiColorFits (Cigan, 2019,
https://github.com/pjcigan/multicolorfits).

Figure 20: Herschel band images of the (top left) 70 $\mu$m, (top right) 160
$\mu$m, (middle left) 250 $\mu$m, (middle right) 350 $\mu$m and (bottom) 500
$\mu$m emission. The intensity is shown in base 10 logarithm to enhance the
visibility of the surrounding emission, and all colour bars are set to the
same scale for comparison between the bands.  Figure 21:  A RGB image (R: 500
$\mu$m, G: 250 $\mu$m, B: 160 $\mu$m) of G214.5. The colour bar of each band
is logarithmically scaled and ranges from the minimum to the maximum of that
band.

##  Appendix B Clump comparison with Elia et al. (2021)

In this appendix we compare the properties of the clumps identified in this
work (hereafter dendrogram clumps) with the co-incident clumps identified by
Elia et al. (2021) (hereafter referred to as Hi-GAL clumps). Figure 22 shows
the 250 micron image of G214.5 overlaid with the 33 clumps identified in this
work (blue triangles) and the 20 Hi-GAL clumps identified (black circles)
which lie in this area. In general one sees good agreement between the two
samples. Nearly all Hi-GAL clumps are identified as dendrogram clumps in this
work, though there are a number of dendrogram clumps which are not associated
with Hi-GAL clumps. This difference in distribution is due to the very
different identification techniques: a dendrogram constructed from the column
density map vs. CuTEx identified peaks in Herschel band images which are
subsequently cross-matched.

Figure 22: A 250 micron image with the centres of the dendrogram clumps
identified in this work (section 5.1) overlaid as blue triangles, and the Hi-
GAL clumps identified by Elia et al. (2021) overlaid as black circles.

There are 16 dendrogram clumps with co-incident Hi-GAL clumps, defined as
having centres within 1 arcminute of each other. Two of the dendrogram clumps
are co-incident with 2 Hi-GAL clumps: for comparison the mass, bolometric
luminosity, and size of the two Hi-GAL clumps is summed, while the mean of the
two is taken for all other quantities. Figure 23 shows the comparison between
the mass of the co-incident clumps derived in this work and the mass derived
in Elia et al. (2021), as well a comparison of the clump radii 777The Elia et
al. (2021) catalogue does not provide uncertainty estimates for clump radii or
bolometric luminosity, only for their mass. For this reason we do not show the
uncertainties in figures 23 and 24. One can see that the sizes of the Hi-GAL
clumps are considerably smaller than the dendrogram clumps, with sizes close
to the beam size ($\sim 0.11$ pc). This is because CuTEx fits two-dimensional
Gaussians to identified peaks in the Herschel emission maps, thus only the
inner brightest region is fitted which is comparable to the beam size.
Further, Elia et al. (2021) compute deconvolved radii allowing for sizes below
the beam. This is not done in this work because of the elongated nature of a
number of the clumps making it non-obvious how best to do this deconvolution.
Moreover, because the area over which the clump is defined is much smaller for
the Hi-GAL clumps they typically have smaller masses than the dendrogram
clumps.

Figure 23: (Top) The mass of the 16 co-incident clumps as measured in this
work ($x$-axis) and in Elia et al. (2021) ($y$-axis). (Bottom) The radius of
the 16 co-incident clumps as measured in this work ($x$-axis) and in Elia et
al. (2021) ($y$-axis). The dashed line in both panels shows the 1:1 ratio.

In figure 24 one sees the effect of the different identification techniques
has on the placement of the clumps in the mass-radius plot and the mass-
luminosity plot. In the mass-radius plot, the Hi-GAL values place the clumps
considerably to the left due to their reduced size, and thus all clumps now
lie above the Lada, Lombardi & Alves (2010) threshold. This shift shows the
degree of care which must be taken when comparing thresholds and clumps
identified from different studies due to the different techniques employed, a
point raised by Elia et al. (2021). In the mass-luminosity plot, most of the
Hi-GAL derived bolometric luminosities are lower than those derived here in
this work. This is because the majority of the clumps do not have far-infrared
counter-parts (i.e. $<70$ micron sources) and thus their bolometric luminosity
is strongly linked to their size (as seen in figure 11). Regardless of if the
Hi-GAL or dendrogram clump values are considered, the conclusion that the
majority of the clumps have low luminosity-to-mass ratios, and are thus
evolutionarily young, is the same.

Figure 24: (Top) The mass-radius relation for the 16 co-incident clumps as
measured in this work (black circles) and as measured by Elia et al. (2021)
(blue circles). Also shown are the (purple) high-mass star formation threshold
from Baldeschi et al. (2017) and the (yellow) efficient star formation
threshold from Lada, Lombardi & Alves (2010). (Bottom) The mass-luminosity
relation for the 16 co-incident clumps as measured in this work (black
circles) and as measured by Elia et al. (2021) (blue circles) with the 1:1
line shown as a dashed line.