# Identifying plasma fractionation processes in the chromosphere using IRIS

David M. Long School of Physical Sciences, Dublin City University, Glasnevin
Campus, Dublin, D09 V209, Ireland  Astrophysics Research Centre, School of
Mathematics and Physics, Queen’s University Belfast, University Road, Belfast,
BT7 1NN, Northern Ireland, UK  Deborah Baker Mullard Space Science Laboratory,
University College London, Holmbury St Mary, Dorking, Surrey, RH5 6NT, UK
Andy S. H. To ESTEC, European Space Agency, Keplerlaan 1, PO Box 299, NL-2200
AG Noordwijk, The Netherlands  Lidia van Driel-Gesztelyi Mullard Space Science
Laboratory, University College London, Holmbury St Mary, Dorking, Surrey, RH5
6NT, UK  LESIA, Observatoire de Paris, Université PSL, CNRS, Sorbonne
Université, Univ. Paris Diderot, Sorbonne Paris Cité, 5 place Jules Janssen,
92195 Meudon, France  Konkoly Observatory, Research Centre for Astronomy and
Earth Sciences, Hungarian Academy of Sciences, Konkoly Thege út 15-17.,
H-1121, Budapest, Hungary  David H. Brooks Department of Physics & Astronomy,
George Mason University, 4400 University Drive, Fairfax, VA 22030, USA  Marco
Stangalini ASI Italian Space Agency, Via del Politecnico, s.n.c I-00133—Roma,
Italy  Mariarita Murabito INAF - Osservatorio Astronomico di Roma, Via
Frascati 33 Monteporzio Catone, Italy  Space Science Data Center (SSDC) -
Agenzia Spaziale Italiana, Via del Politecnico, s.n.c., I-00133, Roma, Italy
Alexander W. James Mullard Space Science Laboratory, University College
London, Holmbury St Mary, Dorking, Surrey, RH5 6NT, UK  Mihalis Mathioudakis
Astrophysics Research Centre, School of Mathematics and Physics, Queen’s
University Belfast, University Road, Belfast, BT7 1NN, Northern Ireland, UK
Paola Testa Harvard-Smithsonian Center for Astrophysics, 60 Garden Street,
Cambridge, MA 02193, USA

###### Abstract

The composition of the solar corona differs from that of the photosphere, with
the plasma thought to fractionate in the solar chromosphere according to the
First Ionisation Potential (FIP) of the different elements. This produces a
FIP bias, wherein elements with a low FIP are preferentially enhanced in the
corona compared to their photospheric abundance, but direct observations of
this process remain elusive. Here we use a series of spectroscopic
observations of Active Region AR 12759 as it transited the solar disc over a
period of 6 days from 2-7 April 2020 taken using the _Hinode_ Extreme
ultraviolet Imaging Spectrometer (EIS) and Interface Region Imaging
Spectrograph (IRIS) instruments to look for signatures of plasma fractionation
in the solar chromosphere. Using the Si X/S X and Ca XIV/Ar XIV diagnostics,
we find distinct differences between the FIP bias of the leading and following
polarities of the active region. The widths of the IRIS Si IV lines exhibited
clear differences between the leading and following polarity regions,
indicating increased unresolved wave activity in the following polarity region
compared to the leading polarity region, with the chromospheric velocities
derived using the Mg II lines exhibiting comparable, albeit much weaker,
behaviour. These results are consistent with plasma fractionation via
resonant/non-resonant waves at different locations in the solar chromosphere
following the ponderomotive force model, and indicate that IRIS could be used
to further study this fundamental physical process.

Sun: Corona; Sun: Activity

††journal: ApJ††facilities: SDO, IRIS, _Hinode_ /EIS††software: SolarSoftWare
(Freeland & Handy, 1998), Numpy (Harris et al., 2020), Sunpy (The SunPy
Community et al., 2020), aiapy (Barnes et al., 2020), EISPAC (Weberg et al.,
2023), Seaborn (Waskom, 2021), Matplotlib (Hunter, 2007), pandas (Wes
McKinney, 2010)

##  1 Introduction

Observations of elemental composition in the solar atmosphere have revealed
distinct differences between the solar photosphere and corona (e.g., Asplund
et al., 2009; Meyer, 1985). Elements with a low first ionisation potential
(FIP) value (FIP$<10$ eV, e.g., Fe, Mg, Si) have been shown to be overabundant
in the solar corona by a factor of 2–4 when compared with elements with a high
FIP value (FIP $>10$ eV, e.g., C, N, O). This ratio between the composition of
an element in the corona vs. the photosphere is known as the “FIP bias”, and
provides a commonly used diagnostic of variations in abundance throughout
different regions of the solar atmosphere (see, e.g., Brooks et al., 2015;
Baker et al., 2021; Laming, 2015). This is an important and fundamental
property of solar plasma. Unlike other plasma properties such as temperature,
density, and emission measure, which exhibit drastic changes in the corona,
the FIP bias of a plasma is not affected by its surroundings. Instead, it is
set low down in the solar atmosphere and does not change as the plasma evolves
into the heliosphere, providing a key tool to relate remote-sensing and in-
situ measurements of the solar corona and solar wind. As a result, it is a key
plasma parameter observed by the _Solar Orbiter_ mission (see, e.g., Müller et
al., 2020; Zouganelis et al., 2020).

However, the physical processes that drive fractionation of the plasma and
produce the observed FIP bias measurements remain subject to investigation.
Initial theories suggested that the observed FIP effect was due to thermal or
ambipolar diffusion across magnetic field lines in the solar atmosphere (von
Steiger & Geiss, 1989), thermoelectric driving (Antiochos, 1994),
chromospheric reconnection (Arge & Mullan, 1998), or ion cyclotron wave
heating (Schwadron et al., 1999). While these theories successfully explain
different aspects of the FIP effect, none of them can explain the observed
Inverse FIP (IFIP) effect (Doschek & Warren, 2016), wherein high- rather than
low-FIP elements are enhanced in the corona, or low-FIP elements are depleted.
More recently, a model to explain elemental fractionation and the FIP effect
using the ponderomotive force was proposed by Laming (2004, 2009, 2015). In
this model, standing Alfvén waves within coronal loops produce an upward
directed ponderomotive force at the base of the loops (i.e., in the
chromosphere), acting on ions and pulling them up into the corona. With low-
FIP elements easier to ionise, this produces an increased FIP bias in closed
magnetic field regions.

The launch of the Extreme ultraviolet Imaging Spectrometer (EIS; Culhane et
al., 2007) onboard the _Hinode_ (Kosugi et al., 2007) spacecraft has enabled
an unprecedented opportunity to investigate and quantify FIP bias evolution in
the solar atmosphere by providing spatially resolved observations (e.g.,
Brooks et al., 2015; Warren et al., 2016; Doschek et al., 2018). A myriad of
recent _Hinode_ /EIS observations have also produced results consistent with
the ponderomotive force model. Baker et al. (2013, 2015) used the
ponderomotive force model to explain long term evolution of FIP bias in an
emerging flux region within a coronal hole (Baker et al., 2013) and an active
region (Baker et al., 2015). This work was followed by Mihailescu et al.
(2022), who found a weak dependence of FIP bias on the evolutionary stage of
an active region. Despite being a static model, the ponderomotive force model
has also been used by To et al. (2021) to explain differences in the FIP bias
measured using two different composition diagnostics in a small solar flare.
The waves which can induce the ponderomotive force have also been observed in
the chromosphere using spectropolarimetric data from the Interferometric
BIdimensional Spectrometer (IBIS) instrument and related to coronal FIP bias
measurements (Stangalini et al., 2021; Baker et al., 2021), while both
Mihailescu et al. (2023) and Murabito et al. (submitted) have noted a
relationship between resonant waves and increased FIP bias via the
ponderomotive force. Detections of the inverse FIP effect in the solar wind
also seem to be consistent with the ponderomotive force model of abundance
variations due to chromospheric fast-mode waves (Brooks et al., 2022).

However, the fractionation process in the upper chromosphere and transition
region has to date been underinvestigated. Dahlburg et al. (2016) and
Martínez-Sykora et al. (2023) have begun the process of extending the
ponderomotive force model initially proposed by Laming (2004, 2009, 2015) to
include a multi-fluid analysis and non-equilibrium ionisation effects, both of
which are important in the solar chromosphere where this process should be
occurring. Observations of this region provided by the Interface Region
Imaging Spectrometer (IRIS; De Pontieu et al., 2014) spacecraft are also being
used to investigate this process, despite the lack of suitable emission lines
for estimating FIP bias within the wavelength range probed by IRIS. Testa et
al. (2023) tracked the evolution of an active region across a period of 10
days using observations from _Hinode_ /EIS, estimating the FIP bias using a
novel technique employing a spectral inversion method. The derived FIP bias
maps were then compared with IRIS observations processed using IRIS2 (Sainz
Dalda et al., 2022) inversions to derive the chromospheric microturbulence.
This approach suggested an enhancement of microturbulence in outflow regions
exhibiting enhanced FIP bias, although no apparent relationship could be
identified between microturbulence and enhanced FIP bias in an observed
sunspot.

In this paper, we undertake a systematic analysis of an active region observed
repeatedly over the course of 6 days by both the IRIS and _Hinode_ spacecraft
to try and identify signatures of the plasma fractionation process in the
solar chromosphere. The target active region and the different datasets used
to study it are described in Section 2, with the different analysis techniques
outlined in Section 3. Section 4 describes the results of this analysis, with
these results and their implications discussed in Section 5. Finally, we draw
conclusions and suggest potential avenues for further investigation in Section
6.

##  2 Observations

Figure 1: Active Region 12759 on 3-April-2020 observed using EIS Si X/S X FIP
bias map (panel a), Ca XIV/Ar XIV line ratio (panel b), SDO/HMI line-of-sight
magnetic field (panel c), and SDO/AIA 171 Å passband (panel d). Magnetic field
has been saturated at $\pm$150 G for clarity. White pixels in panels a & b
denote non-numeric values. Red dashed box shows the full _Hinode_ /EIS field
of view, and the blue dashed box shows the full IRIS field of view.

The active region (AR) studied here rotated onto the solar disc as seen from
Earth on 2020-March-30, and was labelled AR 12759 on 2020-April-1. At the time
it was the only active region on the solar disc and appeared as a simple
bipolar decaying active region (see Figure 1). As the only observable active
region, it was chosen as the target for _Hinode_ Observing Plan (HOP) 390,
with observations from both _Hinode_ /EIS and IRIS supporting observations
made by the Karl G. Jansky Very Large Array (JVLA; Perley et al., 2011). A
more detailed discussion of the observing campaign and the relationship
between the observations made using _Hinode_ /EIS and the JVLA can be found in
To et al. (2023). As noted by To et al. (2023), the JVLA took observations of
AR 12759 on 2020-April-3 and 2020-April-7, which were then used to examine the
relationship between elemental abundance and F10.7 radio emission. However, as
the sole active region on the disc, AR 12759 was also the focus of a series of
IRIS and EIS rasters during the time period between these two JVLA
observations, providing a unique insight into its long-term evolution in both
the corona and the chromosphere/transition region.

The target active region was identified using observations from the _Solar
Dynamics Observatory_ (SDO; Pesnell et al., 2012). Images from the Atmospheric
Imaging Assembly (AIA; Lemen et al., 2012) and both line-of-sight magnetograms
and continuum images from the Helioseismic and Magnetic Imager (HMI; Schou et
al., 2012) were used in this analysis. These data were downloaded from the
Joint Science Operations Centre (JSOC) and processed using the Python aiapy
package (Barnes et al., 2020) to update the pointing, co-register the images,
correct for degradation, and normalise the exposure time.

The IRIS observations of AR 12759 described here are outlined in Table 1. All
of the rasters are very large, dense, 320-step rasters rebinned $2\times 2$
with a 9.2 s exposure time and a raster step of $0.35^{\prime\prime}$, giving
a total field of view of $112^{\prime\prime}\times 175^{\prime\prime}$ (shown
by the blue dashed box in Figure 1) with a raster cadence of $\sim$49 minutes.
IRIS calibrated level 2 data were used for this analysis, with the data
already corrected for dark current, flat field, and geometrical distortion
(see, e.g., De Pontieu et al., 2014, for more details). The IRIS data were
then aligned with SDO/AIA observations using the SDO/AIA 304 Å passband and
the 2796 Å passband from the associated IRIS slitjaw images. Detailed IRIS
analysis was performed on a subfield region-of interest corresponding to the
white box shown in Figure 2, which roughly corresponds to the core of the
observed active region. Note that the only differences between rasters with
OBSID 3610108077 and 3620108077 is the use of lossless (3610108077) vs.
default (3620108077) compression.

The 17 separate _Hinode_ /EIS observations of AR 12759 between 2 and 7 April
2020 described here were taken using the HPW021_VEL_260x512v2 study. This
study contains the Si X 258.375 Å, S X 264.233 Å, Ca XIV 193.874 Å, and Ar XIV
194.396 Å lines as well as a series of Fe lines, and has previously been used
to study active region FIP bias (e.g., Testa et al., 2023; To et al., 2023).
The HPW021_VEL_260x512v2 study scans a field-of-view of
$260^{\prime\prime}\times 512^{\prime\prime}$ with 87 raster positions of 40 s
exposure time and uses the $2^{\prime\prime}$ slit width with a raster step of
$3^{\prime\prime}$. The data were reduced using the SSWIDL eis_prep.pro
routine, which removes pixels affected by cosmic ray hits, dust, and electric
charge, and corrects the data for instrumental effects including orbital
spectrum drift and CCD spatial offset. The FIP bias here was estimated using
two distinct line ratio diagnostics, namely the Si X/S X and Ca XIV/Ar XIV
ratios. The FIP bias derived from the Si X/S X diagnostic was calculated using
the technique developed by Brooks et al. (2015) and subsequently used by Baker
et al. (2021); To et al. (2021, 2023), in which spectral lines from
consecutive ionisation stages of Fe VIII - Fe XVII were fit with single or
multiple Gaussians as appropriate (typically single Gaussians unless the line
is blended). These lines have a formation temperature of $\sim$0.5–5.5 MK, and
the diagnostic can be used to estimate the FIP bias assuming a density
estimated using the Fe XIII 202.04 Å/203.83 Å line ratio. The Ca XIV and Ar
XIV lines have a higher formation temperature of $\sim$3.5 MK, and the
diagnostic was derived by taking the ratio of the two lines as Ca XIV/Ar XIV
(cf. Baker et al., 2019). An example of the resulting composition maps derived
for both ratios is shown in Figure 1a,b, with both plots scaled using the same
FIP bias range for consistency.

##  3 Analysis techniques

Given the unknown signatures of the plasma fractionation process in the solar
chromosphere and transition region, a number of different analysis techniques
were applied to each IRIS raster. The Si IV 1394 Å, Si IV 1403 Å, C II 1336 Å,
and Mg II k & h spectral lines observed by the IRIS spectrograph are the main
focus of this work as they provide an overview of plasma processes occurring
through the chromosphere and transition region. Fortunately, all of the
rasters used here (see Table 1 for details) provided observations of each of
these spectral lines with high spectral resolution across a large field of
view which encompassed a significant fraction of the EIS field-of-view with
measureable FIP bias values.

It is clear from Table 1 that the IRIS rasters were taken in a series of 5
distinct groups, with (in most cases) multiple raster scans per observation
time. This allowed a detailed analysis of the active region within these
particular observing windows. For brevity, the different analysis techniques
are described in this section, with the evolution of different parameters
within each group then discussed in Section 4.

Table 1: Analysed IRIS observations of AR 12759. Start Time (UT) | OBSID | No. rasters | x, y | Group
---|---|---|---|---
2 Apr 22:47:09 | 3610108077 | 3 | $-386^{\prime\prime},534^{\prime\prime}$ | 1
3 Apr 01:17:35 | 3610108077 | 3 | $-368^{\prime\prime},534^{\prime\prime}$ | 1
3 Apr 04:48:09 | 3610108077 | 3 | $-356^{\prime\prime},535^{\prime\prime}$ | 1
3 Apr 07:18:35 | 3610108077 | 3 | $-325^{\prime\prime},535^{\prime\prime}$ | 1
3 Apr 09:49:21 | 3610108077 | 2 | $-309^{\prime\prime},537^{\prime\prime}$ | 1
3 Apr 11:30:41 | 3610108077 | 1 | $-294^{\prime\prime},537^{\prime\prime}$ | 1
3 Apr 20:16:44 | 3610108077 | 4 | $-233^{\prime\prime},542^{\prime\prime}$ | 2
3 Apr 23:41:07 | 3610108077 | 3 | $-203^{\prime\prime},540^{\prime\prime}$ | 2
4 Apr 02:11:53 | 3610108077 | 2 | $-183^{\prime\prime},541^{\prime\prime}$ | 2
4 Apr 12:22:19 | 3620108077 | 4 | $-109^{\prime\prime},542^{\prime\prime}$ | 3
4 Apr 15:46:16 | 3620108077 | 2 | $-79^{\prime\prime},543^{\prime\prime}$ | 3
4 Apr 17:27:38 | 3620108077 | 4 | $-66^{\prime\prime},541^{\prime\prime}$ | 3
4 Apr 20:46:55 | 3620108077 | 1 | $-40^{\prime\prime},544^{\prime\prime}$ | 3
5 Apr 12:03:35 | 3620108077 | 3 | $76^{\prime\prime},542^{\prime\prime}$ | 4
5 Apr 14:38:45 | 3620108077 | 5 | $98^{\prime\prime},543^{\prime\prime}$ | 4
5 Apr 18:46:59 | 3620108077 | 4 | $130^{\prime\prime},542^{\prime\prime}$ | 4
5 Apr 22:06:16 | 3620108077 | 3 | $158^{\prime\prime},541^{\prime\prime}$ | 4
6 Apr 00:36:36 | 3620108077 | 4 | $177^{\prime\prime},542^{\prime\prime}$ | 4
6 Apr 16:40:19 | 3620108077 | 5 | $297^{\prime\prime},542^{\prime\prime}$ | 5
6 Apr 20:48:33 | 3620108077 | 3 | $328^{\prime\prime},539^{\prime\prime}$ | 5
6 Apr 23:35:39 | 3620108077 | 4 | $344^{\prime\prime},537^{\prime\prime}$ | 5
7 Apr 02:54:56 | 3620108077 | 1 | $369^{\prime\prime},534^{\prime\prime}$ | 5
Figure 2: Plasma properties of AR 12759 at 22:47:09 UT on 2020-April-02.
Panels a, b, & c show the AIA 211 Å, HMI line-of-sight magnetic field, and HMI
continuum respectively. The white box shows the part of the IRIS raster field-
of-view roughly corresponding to the core of the active region which was the
primary focus of this work, with the coloured boxes showing the leading
polarity (blue), following polarity (orange), and emerging flux (green)
regions. Middle row shows the line width, and bottom row shows kernel density
estimator (KDE) plots of the line width distributions in the three boxes for
the Si IV 1394 Å (left), Si IV 1403 Å (middle), and C II 1336 Å (right)
spectral lines. In each case, the images and plots have been limited to a
range of 0.02-0.25 Å. Note that flux emergence had not yet started in the
“emerging flux” (green) region at the time of this figure.

Initial inspection of the magnetic evolution of the active region and the
individual groups of IRIS rasters enabled identification of three regions-of-
interest which are the focus of detailed analysis here. These regions
correspond to the leading and following polarities of the active region, and a
small emerging flux region which began emerging from $\sim$21:30 UT on
2020-April-03. Note that the regions-of-interest were defined separately for
each group due to the small variability of position within each group, while
also minimising variation in the location of these regions between the
different groups.

###  3.1 Spectral line fitting

For each raster studied, the Si IV 1394 Å, Si IV 1403 Å, and C II 1336 Å lines
were fitted using single Gaussians to derive the line intensity, width, and
Doppler velocity. In each case, the lines were fitted using iris_auto_fit.pro
from the SolarSoftWare (SSW; Freeland & Handy, 1998) database. An initial
inspection of the plasma parameters of each fitted line found that the
intensity and Doppler velocity behaved as expected for an active region core,
with no identifiable anomalous behaviour that could potentially be related to
the measured EIS FIP bias. In contrast, the line width exhibited potentially
interesting behaviour that required further inspection. Figure 2 shows the
line width for the Si IV 1394 Å, Si IV 1403 Å, and C II 1336 Å lines at
22:47:09 UT on 2020-April-02 (panels d-f), with the Kernel Density Estimation
(KDE; cf. de Jager et al., 1986; Dacie et al., 2016) plots in panels g-i
showing the distribution of pixel values within the boxes corresponding to the
leading polarity (blue), following polarity (orange), and emerging flux
(green) regions. Panels a-c of the figure show the 211 Å, HMI line-of-sight
magnetic field, and HMI continuum for context, with the white box in each
panel showing the field-of-view of the IRIS raster roughly corresponding to
the core of the active region.

Figure 3: Fitted Mg II properties of AR 12759 at 22:47:09 UT on 2020-April-02.
Top row shows maps of (a) k2 separation, (b) k3 velocity, (c) k-h separation,
and (d) k asymmetry, each calculated using iris_get_mg_features_lev2.pro.
Bottom row shows the corresponding KDE plots of the pixel values within the
regions-of-interest for each parameter.

It is clear from the KDE plots in panels g-i of Figure 2 that the line width
values corresponding to the following polarity region are consistently higher
than those corresponding to the leading polarity region, regardless of the
line studied. In contrast, the emerging flux region exhibits a much broader
range of values typically peaking at a lower value than observed for the
following polarity region (with the exception here of the C II line in panel
i). As noted by Martínez-Sykora et al. (2023), the Si IV line width provides
an insight into unresolved velocity due to Alfvén waves, so we chose the Si IV
1403 Å line width for further analysis in Section 4.

###  3.2 Derivation of Mg II properties

As discussed in detail by, e.g., Leenaarts et al. (2013), Pereira et al.
(2013) and Kerr et al. (2015), the Mg II h & k resonance lines are complex
optically thick lines that form at multiple levels in the solar chromosphere.
As a result, the lines are observed at different heights simultaneously,
corresponding to the optical depth at a given frequency $\tau=1$, which allows
the photons to escape. Both the h & k lines have distinct shapes with features
that can be used to probe different parts of the solar chromosphere (e.g.,
Figure 1 of Pereira et al., 2013). The k1 minima form near the temperature
minimum, the k2 emission peaks form in the mid-chromosphere, while the k3
emission cores form in the upper chromosphere. The h & k lines also form at
slightly different heights in the solar chromosphere, with the k line forming
a few tens of km higher due to its higher (by a factor of 2) opacity. The
lines can also be used to probe temperature and velocity gradients between the
formation heights of the k2r (red wing) and k2v (blue wing) components by
measuring the asymmetry and separation of the emission peaks. To derive these
properties, the Mg II lines from each raster were analysed here using the
SSWIDL iris_get_mg_features_lev2.pro routine (cf. IRIS Technical Note 39 and
Pereira et al., 2013).

Figure 3 shows some of the fitted Mg II line properties as derived using the
iris_get_mg_features_lev2.pro routine for the raster beginning at 22:47:09 UT
on 2020-April-02. The top row shows the corresponding images. Panel a shows
the k2 separation, which provide an estimation of the mid-chromospheric
velocity gradient, panel b shows the k3 velocity, providing an estimate of the
upper chromosphere velocity, panel c shows the k-h peak separation, which is
sensitive to the upper chromospheric velocity gradient, and panel d shows the
k asymmetry, defined as,

$k_{\textrm{asym}}=\frac{I_{k2v}-I_{k2r}}{I_{k2v}+I_{k2r}},$ (1)

where $I_{x}$ is the intensity at the defined location $x$. This gives the
sign of the velocity above the $\tau=1$ level. Note that the h line exhibits
comparable behaviour to the k line for each parameter, and is therefore not
shown here for brevity. The bottom row of Figure 3 shows the corresponding KDE
plots giving the probability density of the values contained within the
regions corresponding to the leading polarity, following polarity, and
emerging flux. A reference line has also been added to the k3 velocity, k-h
separation, and k asymmetry plots to indicate where the values equal 0.

For the raster shown in Figure 3, the region where magnetic flux begins to
emerge starting from $\sim$21:30 UT on 2020-April-03 has a higher k2
separation, indicating a higher mid-chromospheric velocity gradient than the
following or leading polarities, both of which have very broad distributions.
While all three regions have a comparable k3 (upper chromosphere) velocity and
k-h separation (indicating comparable upper chromosphere velocity gradients),
the emerging flux region does appear to have a slightly more positive upper
chromosphere velocity gradient, although the actual flux emergence episode
only starts about 23 hours later. Finally, all three regions have a comparable
mainly positive k asymmetry, indicating mostly positive velocity above
$\tau=1$.

###  3.3 IRIS2 inversion

The IRIS2 inversion database of Sainz Dalda et al. (2022) was also used to
gain an additional insight into the evolution of the chromosphere as AR 12759
transited the disc. The IRIS2 inversions use a series of representative
profiles, each with an associated Representative Model Atmosphere (RMA), where
the RMA was derived using the STockholm inversion Code (STiC; de la Cruz
Rodríguez et al., 2019). The spectral profile in each pixel of the individual
rasters is compared to a lookup table of representative profiles, with the
best fit returned. This provides an estimation of the turbulence velocity
(vturb), line-of-sight velocity (vLOS), electron density (ne), and temperature
(T) with optical depth for each pixel in the rasters. As noted by Testa et al.
(2023), the IRIS2 inversions are optimised for optical depths in the range
$-3.8<\tau<-5$, so following their lead we use IRIS2 images at $\tau=-4.2$
throughout this work.

Figure 4: Derived IRIS2 properties of AR 12759 at 22:47:09 UT on
2020-April-02. Top row shows maps of (a) line-of-sight velocity, and (b)
turbulence velocity, both at an optical depth $\tau=-4.2$ (cf. Testa et al.,
2023). Bottom row shows the corresponding KDE plots of the pixel values within
the regions of interest for each parameter. Note that flux emergence had not
yet started in the “emerging flux” (green) region at the time of this figure.

The top row of Figure 4 shows maps of the line-of-sight (a) and turbulence
velocities (b) calculated using the IRIS2 inversion for the raster starting at
22:47:09 UT on 2020-April-02. The bottom row shows the corresponding KDE plots
of line-of-sight (c) and turbulence velocity (d) for the distribution of pixel
values in the regions corresponding to the leading polarity, following
polarity, and emerging flux. Again, a vertical reference line has been added
showing the line-of-sight velocity equal to 0 to help guide the eye.

All three distributions of the line-of-sight velocity are quite broad, with
the leading and following polarity regions predominantly positive, while the
emerging flux region distribution is approximately symmetric about 0, with a
slight bias towards the negative. All three regions have a spread in
turbulence velocity from 2–7 km s-1, albeit each with two distinct peaks.

##  4 Analysis of individual groups

Figure 5: Panel (a) shows temporal evolution of SDO/HMI unsigned magnetic flux
(solid lines) and mean Hinode/EIS FIP bias for the leading polarity (blue),
following polarity (orange), and emerging flux (green) regions within the IRIS
rasters identified as Group 1. FIP bias is calculated using the Si X/S X
(dotted lines) and Ca XIV/Ar XIV (dashed lines) diagnostics. The blue shaded
region shows the uncertainty associated with the Si X/S X ratio in the leading
polarity region to provide a qualitative representation of the uncertainty
associated with the FIP bias measurement. Panels (b-e) show the temporal
evolution of KDE plots of Si IV 1403 Å line width (b), Mg II k3 velocity (c),
Mg II k2 separation (d), and turbulence velocity calculated using the IRIS2
inversions at $\tau=$-4.2 (e). In each case, colours show the different
regions-of-interest corresponding to panel a. Note that flux emergence had not
yet started in the “emerging flux” (green) region at the time of this figure.

The different analysis techniques outlined in Section 3 were applied to each
of the IRIS rasters across the entire observational period. Although not all
of the different parameters exhibited any significant change or evolution with
time, notable changes were identified for some of the parameters suggesting
that further analysis was warranted. In particular, the line width for the Si
IV 1403 Å line was chosen for further analysis as there were significant
differences in the observed behaviour between the different regions-of-
interest. This parameter has also been used by Martínez-Sykora et al. (2023)
to infer the presence of unresolved Alfvén waves. The turbulence velocity
derived from the IRIS2 inversions has previously been used by Testa et al.
(2023) to probe the fractionation process and relationship with FIP bias in
outflow regions. Mihailescu et al. (2023) have suggested that the
ponderomotive force could be acting in the mid- or upper-chromosphere
depending on the presence of resonant vs. non-resonant waves. This is
consistent with the suggestion of Martínez-Sykora et al. (2023) that in the
normal collisional environment of the chromosphere, if the ponderomotive force
is the dominant force in fractionation, waves should propagate from the
chromosphere upward (a suggestion supported by observations made by Murabito
et al., submitted). We also therefore analysed the k2 separation ($\Delta
v_{k2}$) and k3 velocity ($\Delta v_{k3}$), which can be used to probe the
velocity in the mid- and upper chromosphere respectively (Leenaarts et al.,
2013; Pereira et al., 2013).

###  4.1 Group 1

Figure 6: As Figure 5, but for IRIS Group 2. Note that flux emergence begins
in the “emerging flux” (green) region at approximately 21:30 UT during this
sequence.

Group 1 covered a time period from 22:45 UT on 2020-April-02 until 12:20 UT on
2020-April-03, and included 15 IRIS rasters across 6 separate pointings. The
active region was relatively quiet over this period, with no flares observed
and little if any change in the different parameters shown in Figures 2 \- 4.
This can be seen in Figure 5, which shows the evolution in HMI unsigned
magnetic flux density (G) and mean _Hinode_ /EIS FIP bias estimated using the
Si X/S X (dotted line) and Ca XIV/Ar XIV (dashed line) diagnostics (panel a)
and the temporal evolution of the KDE plots for the Si IV 1403 Å line width
(panel b), k2 separation (panel c), k3 velocity (panel d), and turbulence
velocity (panel e), in each case with the different colours corresponding to
the three identified regions-of-interest.

The unsigned magnetic flux density exhibits no distinct changes in this time
period, with the leading polarity region having the highest unsigned flux
density, followed by the following and emerging flux region. Note that the
flux in this region had not yet begun to emerge by this time, so this is
effectively a quiet Sun region. Although there are no _Hinode_ /EIS
observations associated with this IRIS group prior to 07:00 UT on April 3,
there is a distinct difference between the two FIP bias diagnostics estimated
in the different regions-of-interest. There is a clear separation between the
Si X/S X and Ca XIV/Ar XIV estimates in the different regions-of-interest,
with the following polarity region having the highest FIP bias value, followed
by the emerging flux region, then the leading polarity region. It is also
interesting that while the Si X/S X diagnostic values are quite close for each
of the three regions of interest (clustered about $\sim$2), the Ca XIV/Ar XIV
diagnostic values are much more separated (clustered about $\sim$1 for the
leading polarity and emerging flux regions and up to a maximum of 5 for the
following polarity region).

Figure 7: As Figure 5, but for IRIS Group 3.

There is a distinct difference in Si IV line width between the different
regions-of-interest, with the leading polarity region having a broad
distribution peaking at lower values than the narrower distribution for the
following polarity region. In contrast, the emerging flux region tends to have
a broad distribution with two peaks, at both small and large values. Each of
the three regions exhibit a broadly positive k3 velocity, indicating upward-
directed velocity in the upper chromosphere (a height of $\sim$2.5 Mm; Pereira
et al., 2013). However, the distribution associated with the leading polarity
shows a strong peak at $\Delta v_{k3}=0$, with a long positive tail, while the
following polarity and emerging flux regions both peak at positive velocities.
For the k2 separation, corresponding to the mid-chromosphere velocity (a
height of $\sim$1.5 Mm; Pereira et al., 2013), the velocity distributions in
each case are quite broad. The emerging flux and following polarity regions
tend to have distributions peaking at higher values than the leading polarity
region, which tends to have quite a low peak value. It is notable that while
the three regions exhibited relatively broad turbulence velocity
distributions, the distributions tended to have higher values in the following
polarity region than the leading polarity region, with the emerging flux
region distribution typically falling in the middle. This broadly matches the
behaviour of the FIP bias values.

###  4.2 Group 2

Group 2 covered a time period from 20:15 UT on 2020-April-03 until 04:00 UT on
2020-April-04, including 9 IRIS rasters across 3 different pointings. This
period was most notable for a small emerging flux region which emerged in the
southeast of the active region, beginning at $\sim$22:30 UT (see top panel of
Figure 6).

The emergence of magnetic flux was associated with an increase in the $\Delta
v_{k2}$ (Figure 6d) and turbulence velocity (Figure 6e) measured in this
region. However, although the $\Delta v_{k3}$ distribution measured in this
region jumps to high positive values at $\sim$22:44 UT, it then becomes a
skewed distribution peaking at 0 for subsequent rasters. This suggests that
the effects of the flux emergence are primarily limited to the mid
chromosphere and microturbulence measurements. While the leading and following
polarity $\Delta v_{k2}$ and $\Delta v_{k3}$ distributions exhibit comparable
behaviour, the distribution of turbulence velocity had typically higher values
for the following polarity region than the leading polarity region. The Si IV
line width distribution (Figure 6b) in the emerging flux region does not
exhibit any behaviour that can be directly related to the flux emergence,
while the leading and following polarity distributions behave similarly to
Group 1, with the distribution for the following polarity peaking at higher
line width values than the distribution for the leading polarity, which peaks
much closer to zero.

Figure 8: As Figure 5, but for IRIS Group 4.

Unfortunately there were only two EIS rasters associated with this group, with
both prior to the flux emergence, so no clear change in FIP bias value could
be identified as a result of this flux emergence. However, there is a clear
similarity in FIP bias measurements between the Si X/S X and Ca XIV/Ar XIV
diagnostics, with the values estimated in each region of interest comparable
for each diagnostic.

###  4.3 Group 3

Group 3 covered a time period from 12:20 UT until 21:45 UT on 2020-April-04,
and included 11 IRIS rasters across 4 different pointings. This period was
relatively quiet, with the unsigned flux density associated with the leading
polarity region exhibiting a clear decrease across the observing period (see
Figure 7a). The closest _Hinode_ /EIS observations of AR 12759 associated with
this group occurred $\sim$4 hours prior to the first IRIS raster, and as with
Groups 1 & 2, the following polarity showed the highest FIP bias values,
followed by the emerging flux region, and then the leading polarity region. As
with Group 2, the leading polarity and emerging flux regions exhibited
comparable FIP bias values for both the Si X/S X and Ca XIV/Ar XIV
diagnostics. However, the following polarity region has a separation between
values for both diagnostics, similar to Group 1.

Figure 9: As Figure 5, but for IRIS Group 5.

While the distributions of Si IV line width are comparable to the previous
groups 1 & 2 (Figure 7b), the distribution for the leading polarity peaks at a
higher value that is closer to that of the following polarity. The emerging
flux region distribution is also comparable, although again does tend to have
a second peak much closer to zero. The distributions of $\Delta v_{k3}$
(Figure 7c) are broadly comparable between the three regions of interest,
mainly positive with a peak close to 0. However, the leading polarity and
emerging flux $\Delta v_{k2}$ distributions (Figure 7d) peak at a higher
positive value than the following polarity. The turbulence velocities (Figure
7e) exhibit similar behaviour, with higher values observed in the leading
polarity region. It is clear from the top panel of Figure 7 that the unsigned
flux associated with the leading polarity is dropping significantly during
this period. However, the magnetic flux which emerged as observed in Group 2
(Section 4.2), does merge with the following polarity region. This increased
concentration of the magnetic field could explain the lower observed
turbulence and $\Delta v_{k2}$ velocities in this region.

###  4.4 Group 4

Group 4 covered a time period from 12:00 UT on 2020-April-05 until 04:00 UT on
2020-April-06, and included 19 IRIS rasters across 5 different pointings. By
this stage, the sunspot in the leading polarity region had completely
disappeared (at $\sim$01:00 UT on 2020-April-05). A filament had also begun to
form along the inversion line of the bipole at $\sim$03:00 UT on
2020-April-05. By now, the unsigned flux density of the leading polarity
region is comparable to the quiet Sun (as shown by the “emerging flux”
polarity in Figure 8a).

The behaviour and evolution of each of the FIP bias diagnostics remains
consistent in the three regions-of-interest throughout the time period of this
grouping. Once again there is a clear separation between the FIP bias values
for the Si X/S X and Ca XIV/Ar XIV diagnostics in the following polarity
region, with values of $\sim$4 ($\sim$2) in the Ca XIV/Ar XIV (Si X/S X)
diagnostic. The leading polarity and “emerging flux” regions exhibit broadly
comparable values.

The distributions of Si IV line width in the leading and following polarity
regions (Figure 8b) have broadly comparable peaks, although the distribution
is much narrower for the following polarity region than for the leading
polarity region. The “emerging flux” region now peaks very close to zero,
consistent with it now becoming part of the the background quiet Sun.

Similarly, the “emerging flux” $\Delta v_{k3}$ (Figure 8c), $\Delta v_{k2}$
(Figure 8d), and turbulence velocity (Figure 8e) distributions all exhibit low
velocity values, again consistent with this region having effectively become
background quiet Sun by this stage of its evolution. Although the leading and
following polarities have comparable $\Delta v_{k3}$ distributions, there are
clear differences between the leading and following polarity distributions for
the $\Delta v_{k2}$ and turbulence velocities, with the leading polarity
exhibiting consistently higher values. This suggests that the magnetic field
in the following polarity region is too weak to support observable activity in
the upper chromosphere.

###  4.5 Group 5

Group 5 covered a time period from 16:40 UT on 2020-April-06 until 03:00 UT on
2020-April-07 and included 12 IRIS rasters across 3 different pointings. At
this point, AR 12759 was approaching the West limb and had mostly dispersed
magnetic field (as shown by the low unsigned magnetic flux density in the top
panel of Figure 9) and a clear filament along its polarity inversion line.

Only two _Hinode_ /EIS rasters were associated with this group of IRIS
rasters, with the regions-of-interest exhibiting FIP bias values and behaviour
comparable to that seen for Groups 1-4. As before, there is a separation
between the Si X/S X and Ca XIV/Ar XIV values, particularly in the following
polarity region, but also now in the leading polarity region.

The Si IV line width distribution in the leading polarity region is now
peaking at a higher value than the distribution in the following polarity
region, although this behaviour then disappears from $\sim$23:35 UT with the
leading polarity distribution peaking close to zero. The $\Delta v_{k3}$ and
$\Delta v_{k2}$ distributions for the following polarity are centred around 0
and $\sim$30 km s-1 until $\sim$23:35:39 UT at which point they both broaden.
The turbulence velocity also starts to increase at this point. This is most
likely related to the onset of the filament eruption, observed at $\sim$01:30
UT. The leading polarity and emerging flux distributions are comparable in
each case, with the leading polarity distribution values dropping towards the
onset of the filament eruption. Note that at this point the decaying active
region is also approaching the limb, which may affect the observed
distributions.

##  5 Discussion

The best current model to understand the FIP effect has been proposed by
Laming (2004, 2009, 2015), and uses the ponderomotive force to explain
observations. In this model, Alfvén waves originating in the corona induce a
ponderomotive force when they refract and reflect at the high density gradient
at the top of the chromosphere, which carries easily ionised low-FIP elements
into the corona producing the observed FIP effect as they travel back and
forth between the loop’s adjacent footpoints. While this process should occur
near the $\beta=1$ layer in the chromosphere/transition region, it has not yet
been directly observed. Although the IRIS spacecraft regularly observes the
chromosphere/transition region and could therefore provide the missing link in
these studies, it does not observe spectral lines suitable for directly
measuring the FIP effect (cf. De Pontieu et al., 2021).

Despite its inability to directly measure FIP bias, IRIS observations have
previously been probed for signatures of elemental fractionation and the FIP
effect. Previous work by Testa et al. (2023) suggested a relationship between
turbulence velocity estimated using the IRIS2 inversions and FIP bias values
in coronal outflow regions. However, they found no clear increase in
turbulence in a high-FIP bias area close to a sunspot, and therefore they
speculated that the difference might either suggest different properties in
the underlying fractionaction mechanisms in different solar features, or could
be possibly due more to the nature of the outflow region than being a direct
signature of the fractionation process. Very little other work has been done
on identifying signatures of fractionation in IRIS observations, with most
work focussing on coronal (e.g., Baker et al., 2015; Brooks et al., 2015) or
ground-based chromospheric (e.g. Stangalini et al., 2021; Murabito et al.,
submitted) observations of FIP bias evolution or associated Alfvén waves. In
spite of this, there has been some recent work updating the ponderomotive
force model to try and explain observations of differing FIP bias values in
different loop populations within the same active region (Mihailescu et al.,
2023). In this case, the suggestion is that fractionation by the ponderomotive
force is being driven at different heights in the chromosphere by resonant or
non-resonant waves, with resonant waves acting near the top of the
chromosphere, producing a milder fractionation signature, while non-resonant
waves act lower in the chromosphere and produce a much stronger fractionation
signature. This implies that it may be possible to use IRIS data to identify
observable differences between different parts of the chromosphere consistent
with fractionation processes and these resonant/non-resonant waves.

The three regions of interest presented in Sections 3 and 4 were chosen as
previous work has suggested identifiable differences in observed FIP bias
between leading and following polarities within active regions, and emerging
flux regions (e.g., Baker et al., 2018; Mihailescu et al., 2022; To et al.,
2023). The evolution of the magnetic flux of AR 12759 during the time period
studied here clearly shows that the leading polarity region decays and
disperses with time, while the following polarity region (although initially
more dispersed than the leading polarity regions) ultimately becomes more
compact as it incorporates the emerged flux from the emerging flux region
(although a sunspot is never formed). In general, the turbulence velocity
distributions reflect the dispersive nature of the magnetic flux within the
different regions. The more dispersed the magnetic flux within a region, the
broader and more positive the values within the distribution of turbulence
velocity values. Similarly, more compact regions tend to have narrower
distributions of turbulence velocity values that peak much closer to zero.
This makes intuitive sense when considering the plasma-$\beta$; a more compact
magnetic flux region inhibits plasma motion resulting in a lower turbulence
velocity, whereas there is more opportunity for plasma motion in a more
dispersed magnetic flux region, leading to a higher turbulence velocity (cf.
To et al., 2023).

How does this then relate to plasma fractionation and the FIP bias? Mihailescu
et al. (2022) noted that FIP bias increases with magnetic flux density in the
region $\leq$200 G, with that trend stopping for regions $\geq$200 G. Here,
the leading polarity region initially corresponds to a sunspot, with an
unsigned flux density $>$200 G until the end of the third group of IRIS
rasters (approximately 22:00 UT on April 4; see Figure 7). Throughout this
time period, the leading polarity region has a consistently lower associated
FIP bias than the following polarity region where the unsigned flux density is
consistently below 200 G. The emerging flux region also follows this
hypothesis, with a FIP bias value between that of the leading and following
polarity regions and a consistent unsigned flux density value of $\sim$50–100
G. These observations are also comparable with the work of To et al. (2023)
who found a similar relationship between coronal abundance and magnetic flux
density using observations of this active region from 3 and 7 April 2020. It
is interesting that this is also consistent with the work of Martínez-Sykora
et al. (2023), who suggested that sunspots with strong flux densities approach
a “collisionless” case, where waves from the chromosphere could generate an
IFIP effect, thus lowering the FIP bias associated with the region (as noted
here) or even creating an observable IFIP bias.

In addition to the turbulence velocity, the distributions of $\Delta v_{k3}$
and $\Delta v_{k2}$ velocities and the line width of the Si IV 1403 Å emission
line within these regions-of-interest were tracked with time to identify any
differences. The $\Delta v_{k3}$ and $\Delta v_{k2}$ velocities derived from
the Mg II lines can be used to probe the velocity in the upper- and mid-
chromosphere respectively (cf. Pereira et al., 2013; Leenaarts et al., 2013),
the regions where resonant (upper chromosphere) and non-resonant (mid-
chromosphere) waves should be acting. Similarly, the line width, and by
extension the non-thermal velocity, provides an insight into unresolvable
Alfvén waves that could be the predicted resonant or non-resonant waves.

In Group 1 (Section 4.1), the leading polarity region exhibits a low mid-
chromosphere velocity ($\Delta v_{k2}$), and a distribution in upper
chromosphere velocity ($\Delta v_{k3}$) that peaks strongly at 0. It also has
a broadly constant Si X/S X and Ca XIV/Ar XIV FIP bias of $\sim$1, suggesting
little-to-no fractionation, which is a characteristic value in sunspot umbrae
(Baker et al., 2021). In contrast, the following polarity and emerging flux
regions have a higher mid- and upper-chromosphere velocity, with the mid-
chromosphere velocity for the following polarity region tending to increase
slightly with time. The following polarity region exhibits different Si X/S X
and Ca XIV/Ar XIV FIP bias values, with values of $\sim$2 (Si X/S X) and
$\sim$3-5 (Ca XIV/Ar XIV). Both the Si X/S X and Ca XIV/Ar XIV FIP bias values
in the emerging flux region also remain roughly constant, with a comparably
constant mid-chromosphere velocity. The Si IV line width distribution
consistently peaks at a much higher value in the following polarity region
than in the leading polarity region, indicating a higher non-thermal velocity
and hence increased microturbulence, consistent with increased wave activity
in the following polarity region compared to the leading polarity region.

The mid-chromosphere velocity then shows a significant jump during the period
of flux emergence (as shown by the green distributions in Figure 6), but the
upper-chromosphere velocity is unaffected. Unfortunately there is no
comparable FIP bias measurement at this time, although the two measurements
taken prior to this flux emergence show that the two diagnostics are broadly
comparable in the different regions-of-interest. This combination of
chromospheric velocities suggests that the small-scale flux emergence, when it
has just started, affected the lower solar atmosphere, but did not strongly
affect the upper chromosphere, while no clear signature of the flux emergence
is seen in the Si IV line width in the emerging flux region. The magnetic flux
density in the leading polarity region then starts to decrease with time,
(e.g., Figure 7, although there are unfortunately no corresponding FIP bias
measurements). As its previously compact magnetic flux disperses, the leading
polarity region has increased mid- and upper-chromosphere velocity, and a Si
IV line width distribution peaking at higher values, but no corresponding
increase in either observable FIP bias diagnostic. In contrast, the following
polarity region exhibits lower mid-chromosphere velocity, higher upper-
chromosphere velocity, consistently high Si IV line width values, and a clear
separation between the Si X/S X and Ca XIV/Ar XIV diagnostics, with the Ca
XIV/Ar XIV diagnostic consistently higher in the following polarity region.

As noted by Mihailescu et al. (2023), resonant waves fractionating plasma in
the upper chromosphere should produce comparable FIP bias enhancements using
both the Si X/S X and Ca XIV/Ar XIV diagnostics, whereas non-resonant waves
fractionating plasma in the lower chromosphere should produce significantly
higher Ca XIV/Ar XIV values compared to Si X/S X. The FIP bias diagnostic
values presented here are consistent with non-resonant waves fractionating
plasma in the following polarity region and resonant waves fractionating the
plasma in the leading polarity and emerging flux regions. As a relatively
simple bipolar active region with the leading and following polarities mostly
connected to each other, this interpretation would appear to be rather
anomalous. However, connectivity in a decaying active region is complex, so it
is possible that magnetic field in the selected regions-of-interest were not
connected to each other (in particular, the AIA 211 Å image in Figure 2a shows
that the following polarity is connected to a closer-by positive polarity than
the “leading polarity box”). As a result, while a broad connectivity between
the two polarities of the active region is expected, it is indeed possible
that the identified regions-of-interest here were dominated by either non-
resonant or resonant waves. There has also been some work by Giannattasio et
al. (2013) noting an imbalance of velocity oscillations between the leading
and following polarities of bipolar active regions. This could be a
contributing factor to the observations described here, and requires further
investigation. The associated IRIS observations are similarly complex, and
require further analysis to fully interpret their relationship to the wave
types predicted by the fractionation measurements. However, it is notable that
the following polarity region exhibits a consistently higher Si IV line width,
indicating a higher nonthermal width, consistent with increased unresolved
wave activity in this location compared to the leading polarity and “emerging
flux” regions.

##  6 Conclusions

Fractionation of plasma in the solar atmosphere is a long observed and poorly
understood process that has been the focus of significant research
particularly since the launch of the _Hinode_ spacecraft, which has enabled
spatially resolved observations of FIP bias. The leading model to explain this
phenomenon, the ponderomotive force model, suggests that fractionation is
driven by the ponderomotive force resulting from Alfvén waves propagating into
the chromosphere. This implies that it should be possible to observe some
spectral evidence of this fractionation process in the chromosphere. Here we
use five days of observations of a decaying active region from the IRIS
spacecraft to try and identify any signatures of plasma fractionation in the
solar chromosphere and/or transition region.

A comparison of the FIP bias values estimated using the _Hinode_ /EIS Si X/S X
and Ca XIV/Ar XIV diagnostics in the three regions-of-interest found distinct
differences between the two diagnostics in the following polarity region, but
no clear differences in the leading polarity or “emerging flux” regions. These
observations suggest weak (if any) fractionation in the leading polarity and
emerging flux regions, and enhanced fractionation in the following polarity
region.

The clear differences between the FIP bias values estimated using both
diagnostics in the leading and following polarity regions can be understood by
examining their magnetic environment. The leading polarity region is home to a
sunspot and has a high unsigned magnetic flux which drops with time as the
sunspot decays. In contrast, the following polarity region has much more
dispersed magnetic flux, and absorbs some of the emerging flux following its
emergence and dispersal. This is consistent with the suggestion of To et al.
(2023) and Mihailescu et al. (2022) of a connection between the magnetic flux
and the degree of fractionation.

The fractionation process should be occurring in the chromosphere, with
Mihailescu et al. (2023) suggesting that the ponderomotive force proposed by
Laming (2004, 2009, 2015) as the driver of plasma fractionation should be
induced in the upper or lower chromosphere if driven by resonant or non-
resonant waves respectively. Despite a thorough analysis of IRIS observations
of this region, no clear signature of this process could be identified here.
However, a comparison of the Si IV line width distributions in the different
regions-of-interest reveal clear disparities in the non-thermal broadening of
the Si IV line in these regions, indicating variations in the turbulence
velocity consistent with increased unresolved wave activity in the following
polarity region compared to the leading polarity region. The chromospheric
velocities derived from the Mg II lines also reveal some unusual behaviour,
although a full interpretation requires predictions provided by modelling of
the ponderomotive force model. Some of the observed and measured behaviour of
the IRIS parameters do therefore warrant further investigation and analysis
using a combination of observations and modelling, and we intend to follow
this line of investigation in future work.

## Acknowledgements

The authors wish to thank the anonymous referee whose suggestions helped to
improve the paper. DML is grateful to the Science Technology and Facilities
Council for the award of an Ernest Rutherford Fellowship (ST/R003246/1). DB is
funded under Solar Orbiter EUI Operations grant number ST/X002012/1 and Hinode
Ops Continuation 2022-25 grant number ST/X002063/1. LvDG acknowledges the
Hungarian National Research, Development and Innovation Office grant OTKA
K-131508. The work of DHB was performed under contract to the Naval Research
Laboratory and was funded by the NASA Hinode program. AWJ acknowledges funding
from the STFC Consolidated Grant ST/W001004/1. PT was funded for this work by
contracts 8100002705 (IRIS), and NASA contract NNM07AB07C (Hinode/XRT) to the
Smithsonian Astrophysical Observatory, and by the NASA Heliophysics grants
80NSSC21K0737, 80NSSC21K1684, and 80NSSC20K1272. MM has been supported by the
ASI-INAF agreement n. 2022-14-HH.0 and by the Italian agreement ASI-INAF
2021-12-HH.0 “Missione Solar-C EUVST—Supporto scientifico di Fase B/C/D”. IRIS
is a NASA small explorer mission developed and operated by LMSAL with mission
operations executed at NASA Ames Research Center and major contributions to
downlink communications funded by ESA and the Norwegian Space Centre. Hinode
is a Japanese mission developed and launched by ISAS/JAXA, collaborating with
NAOJ as a domestic partner, and NASA and STFC (UK) as international partners.
Scientific operation of Hinode is performed by the Hinode science team
organized at ISAS/JAXA. Support for the post-launch operation is provided by
JAXA and NAOJ (Japan), STFC (UK), NASA, ESA, and NSC (Norway). AIA data
courtesy of NASA/SDO and the AIA, EVE, and HMI science teams.

## Data Availability

No new data were generated as part of this study. The IRIS data can be
downloaded from the LMSAL IRIS website (https://iris.lmsal.com/data.html). The
Hinode EIS data can be downloaded from the Hinode Science Data Centre
(http://sdc.uio.no/sdc/).

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