Hydrogen Column Density Variability in a Sample of Local Compton-Thin AGN

Astronomy & Astrophysics manuscript no. main ©ESO 2023
January 19, 2023
Hydrogen Column Density Variability in a Sample of Local
Compton-Thin AGN
N. Torres-Albà1, S. Marchesi12, X. Zhao3, I. Cox1, A. Pizzetti1, M. Ajello1, and R. Silver1
1
Department of Physics and Astronomy, Clemson University, Kinard Lab of Physics, Clemson, SC 29634, USA
e-mail: nuriat@clemson.edu
2
INAF - Osservatorio di Astrofisica e Scienza dello Spazio di Bologna, Via Piero Gobetti, 93/3, 40129, Bologna, Italy
3
Center for Astrophysics | Harvard & Smithsonian, 60 Garden Street, Cambridge, MA 02138, USA
Received September 15, 1996; accepted March 16, 1997
ABSTRACT
We present the analysis of multiepoch observations of a set of 12 variable, Compton-thin, local (z<0.1) active galactic
nuclei (AGN) selected from the 100-month BAT catalog. We analyze all available X-ray data from Chandra, XMM-
Newton, and NuSTAR, adding up to a total of 53 individual observations. This corresponds to between 3 and 7
observations per source, probing variability timescales between a few days and ∼ 20 yr. All sources have at least one
NuSTAR observation, ensuring high-energy coverage, which allows us to disentangle the line-of-sight and reflection
components in the X-ray spectra. For each source, we model all available spectra simultaneously, using the physical
torus models MYTorus, borus02, and UXCLUMPY. The simultaneous fitting, along with the high-energy coverage, allows
us to place tight constraints on torus parameters such as the torus covering factor, inclination angle, and torus average
column density. We also estimate the line-of-sight column density (NH) for each individual observation. Within the 12
sources, we detect clear line-of-sight NH variability in 5, non-variability in 5, and for 2 of them it is not possible to fully
disentangle intrinsic-luminosity and NH variability. We observe large differences between the average values of line-of-
sight NH (or NH of the obscurer) and the average NH of the torus (or NH of the reflector), for each source, by a factor
between ∼ 2 to > 100. This behavior, which suggests a physical disconnect between the absorber and the reflector,
is more extreme in sources that present NH variability. NH-variable AGN also tend to present larger obscuration and
broader cloud distributions than their non-variable counterparts. We observe that large changes in obscuration only
occur at long timescales, and use this to place tentative lower limits on torus cloud sizes.
Key words. Galaxies: active – X-rays: galaxies – AGN: torus – Obscured AGN
1. Introduction
Active galactic nuclei (AGN) are powered by accreting su-
permassive black holes (SMBHs), surrounded by a torus
of obscuring material. According to the unification theory
(Urry & Padovani 1995), this torus is uniform and ob-
scures certain lines of sight, preventing us from observing
the broad line region (BLR, composed of gas clouds closely
orbiting the black hole) from certain lines of sight. However,
more recent studies based on infrared (IR) spectral energy
distributions (SEDs) favor a scenario in which this torus is
clumpy or patchy, rather than uniform (e.g. Nenkova et al.
2002; Ramos Almeida et al. 2014). This has been further
confirmed by direct observations of changes in the line-of-
sight (l.o.s.) obscuration (NH,los) in the X-ray spectra of
nearby AGN (e.g. Risaliti et al. 2002).
Obscuration variability in X-rays has been detected
in a large range of timescales, from . 1 day (e.g. Elvis
et al. 2004; Risaliti et al. 2009) to years (e.g. Markowitz
et al. 2014). Similarly, a large range of obscuring den-
sity variations have been observed: from small variations
of ∆(NH,los) ∼ 1022
cm−2
(e.g. Laha et al. 2020) to the
so-called ‘Changing-Look’ AGN, which transition between
Compton-thin (NH,los < 1024
cm−2
) and Compton-thick
(NH,los > 1024
cm−2
) states (e.g. Risaliti et al. 2005;
Bianchi et al. 2009; Rivers et al. 2015).
Despite the multiple works that detect a ∆(NH,los) be-
tween two different observations of the same source, very
few have observations covering a complete eclipsing event
(e.g. Maiolino et al. 2010; Markowitz et al. 2014). This is be-
cause oserving the ingress and egress of single clouds across
the line of sight may require daily observations across years.
In fact, the most extensive statistical study of NH,los vari-
ability to date is the result of frequent monitoring of 55
sources, spanning a total of 230 years of equivalent observ-
ing time with RXTE (Markowitz et al. 2014). And it re-
sulted in the detection of variability in only 5 Seyfert 1
(Sy1) and 3 Seyfert 2 (Sy2) galaxies, with a total of 8 and
4 eclipsing events respectively. This study has been used to
calibrate the most recent X-ray emission models based on
clumpy tori (e.g. Buchner et al. 2019).
While it is clear that further studies such as the one
mentioned are not possible with the current X-ray tele-
scopes, due to time constraints of pointed observations,
studies including large samples of sources with sporadic ob-
servations can still be particularly helpful in understanding
the torus structure. The ∆(NH,los) between two different
observations, separated by a given ∆t, has been used to
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Jan
2023

A&A proofs: manuscript no. main
set upper limits to cloud sizes and/or their distances to the
SMBH (e.g. Risaliti et al. 2002, 2005; Pizzetti et al. 2022;
Marchesi et al. 2022).
Recently, Laha et al. (2020) studied the variability of
20 Sy2s and found that only 7/20 sources showed changes
in NH,los over timescales from months to years. A partic-
ularly interesting source also showed an increase of NH,los
over a period of 3.5 yr, and then remained seemingly con-
stant for ∼11 yr. Laha et al. (2020) further argued that
obscured AGN in which NH,los variability is not present, or
is only present on ∼yearly timescales, are difficult to rec-
oncile with a simple clumpy torus scenario. The presence
of a two-phase medium (e.g. Siebenmorgen et al. 2015),
or important contributions of larger-scale structures in the
galaxy (e.g. gas lines or filaments) have been suggested as
possible alternatives to obscuration in such cases.
Even now, the number of well-studied sources in the
literature still remains small. In particular, very few works
exist dedicated to analyzing larger samples of AGN with
multiepoch X-ray observations. Even in such cases, they
tend to use phenomenological models (e.g. Markowitz et al.
2014; Laha et al. 2020), which do not allow for a comparison
between the NH,los variability and general torus properties.
Recently, a variety of self-consistent physical torus mod-
els aiming to better-fit the reflection component of AGN
X-ray spectra have been developed. Some are based on a
uniform torus assumption, such as MYTorus (Murphy &
Yaqoob 2009) or borus02 (Baloković et al. 2018), and have
been widely tested. Others, while more recent and perhaps
not as robustly tested, include the option of a clumpy or
patchy torus, such as UXCLUMPY (Buchner et al. 2019) and
XCLUMPY (Tanimoto et al. 2019). All these models, both
uniform and patchy, take advantage of the high-energy cov-
erage of telescopes such as the Nuclear Spectroscopic Tele-
scope Array (hereafter NuSTAR, Harrison et al. 2013) to
accurately model the reprocessed emission of the torus (i.e.
the reflection component). Through this process, quantities
such as the torus covering factor, the inclination angle, and
the average torus column density can be estimated.
In this work, we aim to analyze a sample of 12 likely-
variable AGN that have multiple X-ray observations, cover-
ing timescales of weeks to decades. These have been selected
from a parent sample of BAT-detected, Compton-thin AGN
at low (z < 0.1) redshift, which have archival NuSTAR ob-
servations. We use three different physical torus models,
with the objective of comparing our results on NH,los vari-
ability to various torus properties.
The sample selection and data reduction processes are
discussed in Sect. 2. In Sect. 3 we discuss the physical torus
models used to model the spectra of the sources, and the
various torus properties that can be derived from each of
them. In Sect. 4 we discuss the methods we use to classify a
source as NH,los-variable, or non-variable. And finally, our
results and a discussion on those are provided in Sects. 5
and 6, respectively. We add a conclusion in Sect. 7. Further
information, such as tables listing fit parameters, images
of the spectra, and comments on individual sources can be
found in Appendixes A, B, and C, respectively.
2. Sample Selection and Data Reduction
The sample in this work has been selected from Zhao
et al. (2021), a work performing a broadband X-ray spec-
tral analysis of an unbiased sample of 93 heavily obscured
AGN (with line-of-sight column density 23≤log(NH)≤24;
i.e. Compton-thin AGN) in the nearby Universe, for which
high-quality archival NuSTAR data are available. This sam-
ple, derived from the Swift-BAT catalog (Burst Alert Tele-
scope, observing in the 15-150 KeV range, Oh et al. 2018) is
the largest NuSTAR dataset analyzed to date. Zhao et al.
(2021) estimated torus geometry and NH,los for the whole
sample by jointly fitting a NuSTAR observation and a non-
simultaneous soft X-ray observation, from either XMM-
Newton, Chandra, or Swift.
It is an ideal starting sample, first of all because a BAT
detection already guarantees that the sources are X-ray
bright and are typically at low redshift (z < 0.12). Secondly,
all sources analyzed already have one NuSTAR observation,
which is essential in breaking the degeneracy between re-
flection and line-of-sight components, allowing us to con-
strain torus parameters. On top of that, it is a sample of
Compton-thin AGN. These are obscured enough to let the
reflection component shine through, allowing us to study
the torus geometry, while being unobscured enough to al-
low us to constrain NH,los with low uncertainty (compared
to e.g. Compton-thick AGN).
Through a preliminary study performed in their analy-
sis of the sample, Zhao et al. (2021) found that at least 311
of the sources presented variability (either in NH,los or flux).
Flux variability can often be confused with NH,los variabil-
ity when the data quality is low; therefore we consider all
these sources possible candidates to perform an in-depth
study of NH,los variability.
Out of the mentioned 31 sources, only 18 had additional
archival data to that analyzed by Zhao et al. (2021)2
. Out
of those, NGC 7479 was analyzed and published as a pilot
project (Pizzetti et al. 2022), and Mrk 477 is currently the
subject of a monitoring campaign (Torres-Albà et al. in
prep.). ESO 201-IG004 is part of a double system, which is
not clearly resolved in the NuSTAR data, and was therefore
removed from our sample, given the sensitivity required of
the proposed analysis. 4C+73.08 was also removed as the
XMM-Newton observations (additional to the one used by
Zhao et al. 2021) were corrupted by flares. NGC 7582 and
NGC 6300 both have a large number of observations, and
have been studied in depth in previous works (e.g. Rivers
et al. 2015; Jana et al. 2020, respectively) regarding NH,los
variability. Both sources require a more careful comparison
with previous results, which is beyond the scope of this
work. In order to complete a self-consistent analysis of the
whole sample, we will present their in-depth analysis in
future works (Sengupta et al. in prep., Torres-Albà et al. in
prep.)
This leaves us with 12 sources, with a total of 54 obser-
vations. These are listed in Table 1.
1
We note that 22 out of the 93 sources analyzed in Zhao et al.
(2021) have simultaneous NuSTAR and soft X-ray observations.
Moreover, 13 additional sources were analyzed using Swift-XRT
data, which typically has very low signal-to-noise ratio. It is
therefore more accurate to say that 31 out of 58 sources pre-
sented some form of variability.
2
As of January 2021

N. Torres-Albà et al.: Hydrogen Column Density Variability in a Sample of Local Compton-Thin AGN
Source Name R.A. Decl. z Telescope Obs ID Exp. Time Obs Date
[deg (J2000)] [deg (J2000)] [ks]
(1) (2) (3) (4) (5) (6) (7) (8)
NGC 612 01 33 57.75 -36 29 35.80 0.0299 XMM-Newton 0312190201 9.5 June 26 2006
NuSTAR 60061014002 16.7 September 14 2012
Chandra 1 16099 10.9 December 23 2014
Chandra 2 17577 25.1 February 2 2015
NGC 788 02 01 06.46 -06 48 57.15 0.0136 Chandra 11680 15.0 September 6 2009
XMM-Newton 0601740201 15.6 January 15 2010
NuSTAR 60061018002 15.4 January 28 2013
NGC 835/833 02 09 24.61 -10 08 09.31 0.0139 XMM-Newton 0115810301 28.5 January 1 2000
Chandra 1 923 12.7 November 16 2000
Chandra 2 10394 14.2 November 23 2008
Chandra 3 15181 50.1 July 16 2013
Chandra 4 15666 30.1 July 18 2013
Chandra 5 15667 59.1 July 21 2013
NuSTAR 60061346002 20.7 September 13 2015
3C 105 04 07 16.44 +03 42 26.33 0.1031 Chandra 9299 8.2 December 17 2007
XMM-Newton 0500850401 4.2 February 25 2008
NuSTAR 1 60261003002 20.7 August 21 2016
NuSTAR 2 60261003004 20.7 March 14 2017
4C+29.30 08 40 02.34 +29 49 02.73 0.0648 Chandra 1 2135 8.5 April 8 2001
XMM-Newton 0504120101 18.0 April 11 2008
NuSTAR 60061083002 21.0 November 8 2013
NGC 3281 10 31 52.09 -34 51 13.40 0.0107 XMM-Newton 0650591001 18.5 January 5 2011
NuSTAR 1 60061201002 20.7 January 22 2016
Chandra 21419 10.1 January 24 2019
NGC 4388 12 25 46.82 +12 39 43.45 0.0086 Chandra 1 1619 20.2 June 8 2001
XMM-Newton 1 0110930701 6.6 December 12 2002
XMM-Newton 2 0675140101 20.6 June 17 2011
NuSTAR 1 60061228002 21.4 December 27 2013
XMM-Newton 3 0852380101 17.8 December 25 2019
NuSTAR 2 60061228002 50.4 December 25 2019
IC 4518 A 14 57 40.42 -43 07 54.00 0.0166 XMM-Newton 1 0401790901 7.4 August 07 2006
XMM-Newton 2 0406410101 21.2 August 15 2006
NuSTAR 60061260002 7.8 August 2 2013
3C 445 22 23 49.54 -02 06 12.90 0.0564 XMM-Newton 0090050601 15.4 June 12 2001
Chandra 1 7869 46.2 October 18 2007
NuSTAR 60160788002 19.9 May 15 2016
Chandra 2 21506 31.0 September 9 2019
Chandra 4 22842 55.1 September 12 2019
Chandra 5 23113 44.2 January 1 2020
NGC 7319 22 36 03.60 +33 58 33.18 0.0228 XMM-Newton 0021140201 32.7 July 7 2001
Chandra 1 789 20.0 July 19 2001
Chandra 2 7924 94.4 August 20 2008
NuSTAR 1 60061313002 14.7 November 9 2011
NuSTAR 2 60261005002 41.9 September 27 2017
3C 452 22 45 48.787 +39 41 15.36 0.0811 Chandra 2195 80.9 August 21 2001
XMM-Newton 0552580201 54.2 November 30 2008
NuSTAR 60261004002 51.8 May 1 2017
Table 1. Notes: (1): Source name. (2) and (3): R.A. and decl. (J2000
Epoch). (4): Redshift. (5): Telescope used in the analysis. (6): Observa-
tion ID. (7): Exposure time, in ks. XMM-Newton values are reported for
EPIC-PN, after cleaning for flares. (8): Observation date.

2.1. Data reduction
The data retrieved for both NuSTAR Focal Plane Modules
(FPMA and FPMB; Harrison et al. 2013) were processed
using the NuSTAR Data Analysis Software (NUSTARDAS)
v1.8.0. The event data files were calibrated running the
nupipeline task using the response file from the Calibra-
tion Database (CALDB) v. 20200612. With the nuproducts
script, we generated both the source and background spec-
tra, and the ancillary and response matrix files. For both
focal planes, we used a circular source extraction region
with a 5000
diameter centered on the target source. For the
background, we used an annular extraction region (inner
radius 10000
, outer radius 16000
) surrounding the source, ex-
cluding any resolved sources. The NuSTAR spectra have
then been grouped with at least 20 counts per bin.
We reduced the XMM-Newton data using the SAS
v18.0.0 after cleaning for flaring periods, adopting stan-
dard procedures. The source spectra were extracted from
a 3000
circular region, while the background spectra were
obtained from a circle that has a radius 4500
located near
the source (avoiding contamination by nearby objects). All
spectra have been binned with at least 15 counts per bin.
The Chandra data was reduced using CIAO v4.12 (Fr-
uscione et al. 2006). The source spectra were extracted from
a 500
circular region centered around the source, while the
background spectra were obtained using an annulus (inner
radius 600
, outer radius 1500
) surrounding the source, exclud-
ing any resolved sources. All spectra have been binned with
at least 15 counts per bin.
All spectrum extracting regions have sizes and charac-
teristics as specified above unless otherwise stated in the
source comments in Appendix C. Likewise, any exceptions
on the mentioned minimum counts per bin (which ensure
good usage of χ2
statistics) are mentioned in the same ap-
pendix.
We fitted our spectra using the XSPEC software (Ar-
naud 1996, in HEASOFT version 6.26.1), taking into ac-
count the Galactic absorption measured by Kalberla et al.
(2005). We used Anders & Grevesse (1989) cosmic abun-
dances, fixed to the solar value, and the Verner et al. (1996)
photoelectric absorption cross-section. The luminosity dis-
tances are computed assuming a cosmology with H0=70
km s−1
Mpc−1
, and ΩΛ=0.73. We used χ2
as the fitting
statistic unless otherwise mentioned.
3. X-ray Spectral Analysis
All sources are fit using a physically-motivated torus model,
with the addition of a soft component, generally of thermal
origin. Three torus models, responsible for the reflection of
the AGN emission in the spectra, are used (and described
below): MYTorus (Murphy & Yaqoob 2009), borus02
(Baloković et al. 2018) and UXCLUMPY (Buchner et al.
2019). To account for the soft excess present in most galax-
ies, we use the thermal emission model apec (Smith et al.
2001). In multiple occasions, sources required the use of
two apec components to accurately describe the soft ex-
cess. This has been shown to reproduce the complex ther-
mal emission in star-forming galaxies (Torres-Albà et al.
2018)3
.
3
We note however that this approach is not necessarily superior
to using a single thermal emission model with non-solar metal-
X-ray data for each source are fit simultaneously. That
is, parameters that are not expected to change in the con-
sidered timescales (of up to ∼ 20 yr), are linked between
different observations, and thus keep a constant value. As
shown in previous works, this strategy can significantly re-
duce the error of the common parameters (e.g. Marchesi
et al. 2022). Parameters kept constant include the intrinsic
photon index of the AGN (i.e. Γ) and torus geometry pa-
rameters (see individual torus model sections for details).
Any caveats and/or implications of this approach are dis-
cussed in Sect. 6.
The model used is
Model = C ∗ phabs ∗ (Soft Model + AGN Model), (1)
where C accounts for intrinsic flux variability and/or
cross-calibration effects between different observations; and
phabs is a photoelectric model that accounts for the Galac-
tic absorption in the direction of the source (Kalberla et al.
2005). We note that, for the purposes of this paper, we con-
sider NH,los free to vary at all epochs. However, this is not
the case for C. In order to minimize the number of free pa-
rameters in the models4
, we do not consider intrinsic flux
variability between two observations (A and B) when: 1) χ2
does not improve significantly when adding the additional
free parameter (which we ensure via f-test); 2) CA and CB
are compatible with each other within errors at 1σ; and 3)
forcing CA = CB does not result in a source that was NH,los
variable to become non-NH,los variable (and vice-versa).
The Soft Model can take the two following forms:
Soft Model = apec, or (2)
Soft Model = apec1 + zphabs ∗ apec2, (3)
and in which kT2 > kT1. As mentioned above, this is a
first approximation to a multiphase medium, in which the
material closer to the nucleus of the galaxy is hotter, as well
as more obscured (Torres-Albà et al. 2018).
The AGN Model accounts for both line of sight and re-
flection components, as well as a scattered component. The
latter characterizes the intrinsic powerlaw emission of the
AGN that either leaks through the torus without interact-
ing with it, or interacts with the material via elastic colli-
sions. This component is set equal to the intrinsic powerlaw,
multiplied by a constant, Fs, that represent the fraction of
scattered emission (typically of the order of few percent, or
less).
All sources have been fit in the range from 0.6 keV to
25−55 keV, with the higher energy limit depending on the
point in which NuSTAR data is overtaken by the back-
ground. For every source, all models have been consistently
applied to the same energy range. Results of the X-ray spec-
tral analysis of each source can be found in Sect. 4 and
Appendix A. The obtained spectra along with the simul-
taneous borus02 best-fit can be found, for all sources, in
Appendix B. Comments on the specific fitting details of
each source can be found in Appendix C.
icity. In any case, thermal emission in the centers of galaxies is
likely to come from a complex, multi-phase medium, and derived
values should be used only as a first-order approximation. See
(Torres-Albà et al. 2018) for an in-depth discussion
4
This number can be as high as ∼ 25, which results in compu-
tational difficulties.

3.1. MYTorus
The MYTorus model (Murphy & Yaqoob 2009) assumes a
uniform, neutral (cold) torus with half-opening angle fixed
to 60º, containing a uniform X-ray source. It is decomposed
into three different components: an absorbed line-of sight
emission, a reflected continuum, and a fluorescent line emis-
sion. These components are linked to each other via the
same power-law normalization and torus parameters (i.e.
torus absorbing column density, NH, and inclination angle
θi). The inclination angle is measured from the axis of the
torus, so that θi=0º represents a face-on AGN, and θi=90º
an edge-on one.
Both the reflected continuum and line emission can be
weighted via multiplicative constants, AS and AL, respec-
tively. When left free to vary, these can account for differ-
ences in the fixed torus geometry (i.e. metallicity or torus
half-opening angle) and time delays between direct, scat-
tered and fluorescent line photons.
We use MYTorus in ‘decoupled configuration’ (Yaqoob
2012), so as to better represent the emission from a clumpy
torus. Generally, a better description of the data is possible
when decoupling the line-of-sight emission from the reflec-
tion component (e.g. Marchesi et al. 2019; Torres-Albà et al.
2021). That is, the NH associated to absorption, NH,los, and
the NH associated to reflection, NH,av, are not fixed to the
same value. This allows for the flexibility of having a partic-
ularly dense line of sight in a (still uniform) Compton-thin
torus, or vice versa.
In this configuration, the line of sight inclination angle is
frozen to θi = 90◦
. In order to better represent scattering,
two reflection and line components are included. One set
with θi = 90◦
(forward scattering), weighted with AS,L90;
and one set with θi = 0◦
(backward scattering), weighted
with AS,L0. In this configuration θi is no longer a variable.
We note however that the ratio between forward to back-
ward scattering (i.e. AS,L90/AS,L0), can give a qualitative
idea of the relative orientation of the AGN, as it indicates
the predominant direction reflection comes from.
In the particular case of fitting multiple observations to-
gether, we consider that NH,av does not vary with time, and
neither do the constants AS and AL. All of these parameters
are representative of properties of the overall torus, which
is assumed to not vary in the considered timescales. How-
ever, NH,los can change as the torus rotates and our line of
sight pierces a different material. Therefore, each individual
observation is associated to a different NH,los.
In XSPEC this model configuration is as follows,
AGN Model = mytorus_Ezero_v00.fits ∗ zpowerlw +
AS,0 ∗ mytorus_scatteredH500_v00.fits +
AL,0 ∗ mytl_V 000010nEp000H500_v00.fits +
AS,90 ∗ mytorus_scatteredH500_v00.fits +
AL,90 ∗ mytl_V 000010nEp000H500_v00.fits +
+Fs ∗ zpowerlw. (4)
We fix AS,90 = AL,90 and AS,0 = AL,0, as is standard.
3.2. BORUS02
borus02 (Baloković et al. 2018) is also a uniform torus
model, but with a more flexible geometry: the opening angle
is not fixed, and can be changed via the covering factor, CF,
parameter (CF ∈ [0.1, 1]). The model consists of a reflection
component, which accounts for both the continuum and
lines. Therefore, an absorbed line-of-sight component must
be added.
We also use this model in a decoupled configuration,
with NH,los and NH,av set to vary independently. In this
case, however, θi (with θi ∈ [18 − 87]) can still be fitted in
a decoupled configuration. borus02 also includes a high-
energy cutoff (which we freeze at ∼ 300 keV, consistent
with the results of Baloković et al. 2020, on the local ob-
scured AGN population) and iron abundance (which we
freeze at 1) as free parameters. We are not able to con-
strain these two parameters with the data available.
When considering our variability analysis, we again al-
low NH,los to vary between different observations, but force
all torus parameters (NH,av, CF, θi) to remain constant.
AGN Model = borus02_v170323a.fits+
zphabs ∗ cabs ∗ zpowerlw
+Fs ∗ zpowerlaw,
(5)
where zphabs and cabs are the photoelectric absorption
and Compton scattering, respectively, applied to the line-
of-sight component.
3.3. UXCLUMPY
UXCLUMPY is a clumpy torus model, which uses the
Nenkova et al. (2008) formalism to describe the distribu-
tion and properties of clouds. Possible torus geometries are
further narrowed down using known column density distri-
butions (Aird et al. 2015; Buchner et al. 2015; Ricci et al.
2015), as well as by reproducing observed frequencies of
eclipsing events (Markowitz et al. 2014).
Clouds are set in a Gaussian distribution of width σ
(with σ ∈ [6−90]) away from the equatorial plane. This dis-
tribution is viewed from a given inclination angle, θi (with
θi ∈ [0◦
− 90◦
]).
The model consists of one single component, which in-
cludes both reflection and line of sight in a self-consistent
way, allowing for a high-energy cutoff, which we again freeze
at Ecut = 300 keV. Although this model has the advantage
of providing a clumpy distribution of material, it does not
provide an estimate of the average column density of the
torus, NH,av, which can be compared to the that provided
by MYTorus and borus02. Therefore, NH,los is the sole
column density provided by the model.
In addition to the cloud distribution, UXCLUMPY offers
the possibility of adding an inner ‘thick reflector’ ring of
material, which was shown to be needed to fit sources with
strong reflection (Buchner et al. 2019; Pizzetti et al. 2022).
This material has a covering factor, CF (with CF ∈ [0−0.6]).
Sources with CF = 0 do not require this additional inner
reflector.
When considering our variability analysis, we again al-
low NH,los to vary between different observations, but force
all torus parameters (CF, θi, σ) to remain constant.
AGN Model = uxclumpy.fits+
+Fs ∗ uxclumpy − scattered.fits,
(6)

where uxclumpy-scattered is the scattered emission
that leaks through the torus. UXCLUMPY however provides
a more realistic version than a simple powerlaw, which in-
cludes the emission that leaks after being reflected.
4. Variability Estimates
The main objective of this work is to measure the variabil-
ity in obscuring column density, or NH,los, for the proposed
sample of sources. As such, a method to determine whether
sources are variable is needed. Here, we propose two esti-
mators of source variability. A detailed explanation on the
interpretation of these comparisons for each source can be
found in Appendix C.
4.1. Reduced χ2
Comparison
The parameters of the best-fit models to the data are re-
ported in Table 4.2, and Tables A through A. The reduced
χ2
(χ2
red) of the best-fit is reported for all three models used.
As a further test for the need to introduce variability in
the models, we present a comparison with χ2
red for the best
fit under three different assumptions:
• There is no variability, either in intrinsic flux or NH,los,
at any epoch (χ2
red No Var).
• There is no intrinsic flux variability at any epoch, but
NH,los variability is allowed at all epochs (χ2
red No C
Var.).
• There is no NH,los variability at any epoch, but intrinsic
flux variability is allowed at all epochs (χ2
red No NH
Var.).
A χ2
distribution approximates a Gaussian for large
values of N (number degrees of freedom), with a variance
σ = 1/
√
N. χ2
red can then be used to compare different
models to select the one that best fits the data. The χ2
red of
the ‘true’ model, the one with the ‘true’ parameter values,
is a Gaussian distributed around the mean value of 1 with
standard deviation σ (see e.g. Andrae et al. 2010). A ten-
sion can then be defined between the proposed model and
the data, as T = |1 − χ2
red|/σ.
We consider that a model fits a source significantly bet-
ter than another when the former has a T < 3σ, and the
latter yields T > 5σ (see e.g., Andrae et al. 2010). We
use this system to classify sources as NH,los-variable, by
comparing the best-fit T with the no-NH,los-variability T.
When both models yield T < 3σ we interpret that NH,los-
variability is not required to fit the data, and thus classify
the source as non-variable. Disagreement between the dif-
ferent torus models used will result in classifying the source
as ‘Undetermined’.
An exception to this rule is made for NGC 4388. No
model fits the data with T < 3σ (see discussion in Appendix
C), but the difference in significance between the best-fit
(which includes NH,los variability) and the non-variability
scenarios is of 30−40σ. Therefore, we consider that includ-
ing NH,los variability results in a significant improvement to
the fit, and thus we classify this source as NH,los-variable.
We note that for two sources in our sample, NGC 612
and 4C+29.30, the fitting statistic used is a mix of C-stat
and χ2
(due to one or more of the spectra having very
few cts/bin. See Sect. 5, and individual source comments
in Appendix C). In such cases, we use T = |1 − Statred|/σ.
However, given how this distribution does not necessarily
approximate a Gaussian, the interpretation of T in such
cases is not straightforward. We opt to still provide this
value as a reference.
4.2. P-value
We take the derived best-fit values of NH,los for all epochs
(as depicted in Figures 2 and 3) and estimate the proba-
bility that they all result from the same ‘true’ value. Here
the null-hypothesis is that no NH,los variability was found
among different observations of the source. That is, the
probability that the source is not NH,los-variable. We do
this via a χ2
computation, that we later convert into a p-
value (probability of the hypothesis: the source is not NH,los
variable). The χ2
is generally computed as follows:
χ2
=
n
X
i=1
(NH,los,i − hNH,losi)2
δ(NH,los,i)2
(7)
However, in our particular scenario, the errors of the NH,los
determinations are asymmetric (i.e. not Gaussian). In or-
der to calculate the equivalent to Equation 7 one needs to
know (or, in its default, assume) the probability distribu-
tion of the error around the best-fit value. We follow the
formalism detailed in Barlow (2003) and opt to assume a
simple scenario to describe this function: two straight lines
which meet at the central value. In such a case, in order
to evaluate the χ2
one needs only to assume as the error δ
either σ+
or σ−
, as appropriate.
From the obtained χ2
we obtain the probability (p-
value) of the null-hypothesis.
• We classify a source as NH,los-variable if p-value
< 0.01 for all three models used (MYTorus,
borus02,UXCLUMPY).
• We classify a source as not NH,los-variable if p-value
> 0.01 for all three models used.
• We classify a source as ‘Undetermined’ if p-value is
above the given threshold for at least one model, and
below it for the others.
5. Results
In this section we present results on the analysis of all
sources. Table 4.2 is an example of the tabulated best-fit
parameters for NGC 612. The table lists, for each of the
three models used, the best-fit statistics (reduced χ2
and
χ2
/d.o.f., i.e. degrees of freedom; or a mix of χ2
and C-
stat for sources with at least one spectra binned with < 15
cts/bin5
) in the first block. It also includes the tension, T,
between the data and the obtained best-fit model, derived
as described in Sect. 4.1.
The second block shows parameters related to the soft
emission. The third block shows the parameters correspond-
ing to the AGN emission models. The fourth and fifth
blocks refer to source variability, either of NH or intrinsic
flux (C, the cross-normalization constant), respectively.
5
See Appendix C for details.

Table 2. NGC 612 fitting results
Model MYTorus borus02 UXCLUMPY
Statred 1.01 0.99 1.05
Stat/d.o.f. 271.96/268 265.91/268 281.77/268
T 0.2σ 0.2σ 0.8σ
kT 0.72+0.11
−0.11 0.70+0.12
−0.08 0.64+0.12
−0.13
Γ 1.54+0.16
−u 1.43+0.02
−u 1.52+0.17
−0.14
NH,av 0.67+1.63
−0.33 0.50+0.13
−0.10 −
AS90 0* − −
AS0 0.12+0.06
−0.04 − −
CF − 0.10+0.03
−u 0*
Cos (θObs) − 0.05+0.05
−u 0.00+0.08
−u
σtor − − 0.91+10.82
−0.31
Fs (10−3
) 0.84+0.51
−0.38 1.13+0.20
−0.19 0.15+5.29
−0.03
norm (10−3
) 5.20+0.42
−0.22 3.58+0.10
−0.10 19.9+6.47
−0.77
NH,xmm 0.90+0.11
−0.10 0.89+0.02
−0.02 0.92+0.11
−0.13
NH,nus 0.84+0.13
−0.11 0.81+0.02
−0.02 0.79+0.17
−0.08
NH,Ch1 1.29+0.29
−0.22 1.27+0.18
−0.13 0.93+0.18
−0.19
NH,Ch2 1.39+0.28
−0.22 1.55+0.19
−0.14 1.10+0.29
−0.14
Cxmm 1.14+0.43
−0.33 1.22+0.06
−0.06 2.62+1.24
−0.77
Cnus 0.68+0.38
−0.26 0.70+0.03
−0.02 1.37+0.90
−0.49
CCh1 1* 1* 1*
CCh2 = CCh1 1.22+0.16
−0.14 1.31+0.77
−0.43
Statred No Var. 1.73 1.72 1.87
T 12.1σ 11.9σ 14.4σ
Statred No C Var. 1.03 1.02 1.19
T 0.5σ 0.3σ 3.1σ
Statred No NH Var. 1.09 1.63 1.07
T 1.5σ 10.4σ 1.2σ
p-value 5.0e-1 1.42e-28 1.00
Notes:
red χ2
(or Stat): reduced χ2
or total Statistic
χ2
(or Stat)/d.o.f.: χ2
(or total Statistic) over degrees of freedom.
kT : apec model temperature, in units of keV.
Γ: Powerlaw photon index.
NH,av: Average torus column density, in units of 1024
cm−2
.
AS90: Constant associated to the reflection component, edge-on.
AS0: Constant associated to the reflection component, face-on.
CF: Covering factor of the torus.
cos (θi): cosine of the inclination angle. cos (θi)=1 represents a
face-on scenario.
Fs: Fraction of scattered continuum
Norm: Normalization of the AGN emission.
NH,inst.,num.: Line-of-sight hydrogen column density for a given ob-
servation, in units of 1024
cm−2
.
Cinst.,num.: Cross-normalization constant for a given observation,
with respect to the intrinsic flux of the first Chandra observation.
The last block shows the reduced χ2
(or Stat) of the best-fit when
considering a) No variability between different observations; b) No
intrinsic flux (i.e. C) variability; c) No NH,los variability.
(−u) refers to a parameter being compatible with the hard limit
of the available range. Article number, page 7 of 35

10−6
10−5
10−4
10−3
0.01
keV
2
(Photons
cm
−2
s
−1
keV
−1
)
NGC 612
1 10
1
2
3
4
ratio
Energy (keV)
Fig. 1. borus02 fit to the data for NGC 612. Color code is as
explained in Appendix B.
The final blocks show the best fit statistics that could
be achieved when considering: a) No variability at all be-
tween observations; b) No intrinsic flux variability between
observations; c) No obscuring column density variability be-
tween observations. For each of these scenarios, the tension
between the data and the best-fit models is also computed,
as described in Sect. 4.1. Finally, we compute the probabil-
ity of the source being not variable in NH,los (p-value), as
described in Sect. 4.2.
Tables containing the best-fit results for the rest of the
sample can be found in Appendix A. Table 5 contains a
summary of the results of applying the variability determi-
nation methods described in Sect. 4 to all sources, for all
three models used.
We classify a source as NH,los-variable or as not NH,los-
variable if at least 5 out of 6 classifications (accounting for
both variability estimation methods, applied on the NH,los
determinations from all three used models) agree on the
classification. If two or more determinations disagree for
any source, we classify it as ‘Undetermined’. This is the case
for only two sources within the sample: NGC 612, for which
borus02 results in variability according to both determi-
nations; and IC 4518 A, for which the p-value and the χ2
red
determinations disagree for both MYTorus and borus02.
Further commentary on these disagreements can be found
in Appendix C.
Following the method described above, out of the 12
sources analyzed in this work, 5 are not NH,los-variable, 5
are NH,los-variable, and 2 remain undetermined. It is worth
noting that all sources require at least one type of variability
(either NH,los or intrinsic flux) in order to explain the data,
as expected from our sample selection. This can be appreci-
ated when comparing the best-fit χ2
red to the no-variability
χ2
red in the tables presented in Appendix A.
Figures 2 and 3 show the NH,los variability as a func-
tion of time for all the sources analyzed, considering
all three physical torus models: MYTorus, borus02 and
UXCLUMPY. The dashed horizontal lines represent the best
fit values for NH,av obtained with MYTorus and borus02.
The shaded areas correspond to the uncertainties associated
to those values. All values of NH depicted can be found in
Table 4.2, and Tables A−A.
6. Discussion
Using the comparison between χ2
red in the no-variability
scenario and the best-fit scenario, it is easy to see that all
sources in the sample require some form of variability in or-
der to fit the data. About 42% of the sample (5/12) presents
NH,los variability for certain; a number that could be as high
as ∼ 58% if all our ‘Undetermined’ cases turned out to be
NH,los variable. For 5 sources in the sample we can confi-
dently say no NH,los variability is present between the given
observations.
When analyzing the results, however, one must take into
account the following two factors: 1) The sample was inten-
tionally biased toward variable sources, meaning that we
expect to detect more NH,los variability than in a blind sur-
vey. 2) The fact that we did not detect NH,los variability
for any given source does not mean it has never varied in
NH,los.
For the two ‘Undetermined’ sources, we are not able to
claim whether flux variability or NH,los variability is needed
to fit the source, but we can claim that at least one of them
is required. This showcases the difficulty in disentangling
the two types of variability in X-ray datasets, even when
dealing with nearby, bright AGN. In particular, this behav-
ior is amplified when fitting NuSTAR data: for both 3C 445
and NGC 7319 the clumpy model UXCLUMPY favors higher
flux variability and smaller NH,los variability between other
observations and the NuSTAR one, while the opposite is
true for borus02 and MYTorus, the homogeneous models.
It is likely that simultaneous NuSTAR and XMM-Newton
observations would allow to properly disentangle the two
scenarios.
6.1. Disagreement between average torus NH and l.o.s. NH
One of the most obvious results of our analysis can be ap-
preciated at first glance when looking at the plots in Figures
2 and 3. For the majority of sources, there is a large differ-
ence between the column density in the line-of-sight (at all
times) and the average column density of the torus.
If one assumes that the whole (or the majority) of the
torus is responsible for both obscuration and reflection, one
would expect that the time-averaged value of NH,los (i.e.
hNH,losi) would be similar to the value of NH,av. This is be-
cause, as the torus rotates, our line-of-sight should intercept
a variety of cloud densities, representative of the density of
the torus.
To estimate the feasibility that we are probing a sig-
nificant fraction of the torus, we make some simple cal-
culations. We assume Keplerian velocities, with black hole
masses in the range MSMBH = 107
− 108
M (representa-
tive of the local Universe), distances in the range 1 − 10 pc
(representative of the torus scales), and timescales in the
8 − 20 yr range (representative of our sample). Under these
assumptions, we estimate the torus to have rotated between

Table 3. NH,los Variability Results
Source MYTorus borus02 UXCLUMPY Classification
χ2
red P-val. χ2
red P-val. χ2
red P-val.
NGC 612 N N Y Y N N Undetermined
NGC 788 N N N N N Y Not Variable
NGC 833 N N N N N N Not Variable
NGC 835 Y Y Y Y Y Y Variable
3C 105 N N N N N N Not Variable
4C+29.30 N N N N N N Not Variable
NGC 4388 Y* Y Y* Y Y* Y Variable
IC 4518 A Y N Y N Y Y Undetermined
3C 445 N N N N N Y Not Variable
3C 452 Y Y Y Y Y Y Variable
Notes: NH,los-variability determinations using the χ2
red and the p-value
methods described in Sect. 4.
N: Not variable. Y: Variable.
*: See Sect. 4.1 and Source Notes on NGC 4388.
0.003 − 0.3◦
within the timespan of our observations6
. At
the mentioned distances, this corresponds to a physical size
of 6 × 10−4
− 6 × 10−3
pc.
The number of works that place constraints on torus
cloud/clump size (hereafter rc) is small. For reference, we
list here a few determinations and/or commonly used values
in the literature. Maiolino et al. (2010) place the most di-
rect lower limit on cloud size, based on their X-ray observa-
tions of a whole eclipsing event (i.e. from ingress to egress).
They estimate the size of the cloud head (i.e. denser, spher-
ical region) to be rc > 10−7
pc, while the size of the
following ‘cometary tail’ of less-dense material would be
rtail > 3 × 10−6
pc. However, one must take into account
these estimates correspond to a cloud placed in the broad
line region (BLR), which does not necessarily have the same
size as clouds orbiting the SMBH at larger distances.
Infrared emission models of patchy/clumpy tori only re-
quire the clouds to be ‘small enough’ in order to reproduce
the observed MIR SEDs (e.g. Nenkova et al. 2008). X-ray
clumpy models based on the previous work assume cloud
sizes of the order of rc = 2 × 10−3
pc (Tanimoto et al.
2019), or θc = 0.10
− 1◦
. All of these are larger than the re-
gion sizes we estimate. These, however, do not necessarily
correspond to observed cloud sizes, but rather to modeling
or computational requirements.
The region sizes we obtain from our estimates (6×10−4
−
6 × 10−3
pc) would not correspond to the size of a single
cloud, given how multiple of our sources show variability
at shorter timescales. However, in order to explain why
we systematically see this NH,los variability at a level in-
compatible to NH,av, this would need to be the size of the
underdense/overdense region.
6
We note that this is a very simplified calculation, given how
the torus is composed of individual clouds, with independent
orbits, which are not necessarily circular.
While this is in principle not unfeasible, one needs to
take into consideration the chances of systematically look-
ing through overdense regions (as is the case of at least
6/12 of our sources), while in only 1 (or 2, depending on
the model considered for NGC 3281) are observed through
underdense ones. Furthermore, one should consider that the
overdense regions are so by a factor 2−10 with respect to
the torus average, while the underdense regions are so by
orders of magnitude (see not only IC 4518 A and NGC 3281
in this work, but also NGC 7479 in Pizzetti et al. 2022).
A study of the actual feasibility of this geometry would
require: 1) A dynamical model to generate and sustain these
underdense/overdense regions within a torus; and 2) An
analysis of the probability of systematically observing over-
dense regions in a sample of 12 sources. Both of these stud-
ies are beyond the scope of this paper.
In the sections below we explore other possibilities that
could explain the observed disagreement, by assuming that
the material responsible for obscuration (characterized by
NH,los and, hereafter, the obscurer) and the material re-
sponsible for reflection (characterized by NH,av and, here-
after, the reflector) are not the same.
6.1.1. Inner Reflector Ring
The need for an additional, thick reflector, disentangled
from the rest of the torus material, has been proposed in
the past. As already mentioned above, Pizzetti et al. (2022)
suggested this possibility to explain the NH,los variability
curve in NGC 7479. Furthermore, the only clumpy model
used in this work, UXCLUMPY, requires the addition of one
such thick ring to reproduce the spectrum of sources with
strong reflection (Buchner et al. 2019). In fact, both IC
4518 A and NGC 7479 require this inner ring component
to model the spectrum when using UXCLUMPY, which is

Fig. 2. NH,los as a function of time (data points) for MYTorus, borus02 and UXCLUMPY. Dashed horizontal lines and shaded areas
correspond to the best-fit values of NH,av, and their error, respectively, for MYTorus and borus02. This quantity is considered
constant with time.
in agreement with the large column densities invoked by
MYTorus and borus02.
This theory could explain the large differences in NH
between the two structures in the torus (of factors between
10 − 100) without the need to invoke a particularly under-
dense region of size up to ∼ 0.3◦
through which we observe
the source. It has been suggested that such a ring could cor-
respond to a launch site for a Compton-thick cloud wind
(e.g. Krolik & Begelman 1988), an inner wall (e.g. Light-
man & White 1988), the inner rim of a hot disk, as seen in
proto-planetary disks (e.g. Dullemond & Monnier 2010), or
a warped disk (e.g. Buchner et al. 2019, 2021, particularly
suitable to explain the spectrum of Circinus).

Fig. 3. Same as Fig. 2.
6.1.2. Multiple reflectors
The majority of sources in our sample have a thin reflector,
rather than a thick one. This is of particular interest, given
how even if one assumes a disentangled thinner reflector
near the SMBH, one needs to explain why then the thicker
cloud distribution does not reflect.
Figure 5 shows the overall X-ray spectrum in the 1 − 50
keV range resulting from an obscured l.o.s. (with NH,los =
1024
cm−2
, in red), a scattered component (with FS = 10−2
,
in green), a medium-thick reflector (with NH,av = 1024
cm−2
, in blue), and a thin reflector (with NH,av = 1023
cm−2
, in cyan).
As can be appreciated in the model, thin reflectors have
more significant contributions in the 2−5 keV range, where
the line-of-sight component (in the case of heavily obscured
AGN) does not contribute. The medium-thick reflector,
while also having a minor contribution in that range, has a
shape more similar to that of the line-of-sight component.
It is thus possible that when only one reflector is consid-
ered, the thin reflector is made necessary by the detected

Fig. 4. Histograms containing the averaged best-fit properties of all sources in the sample, grouped by variability class. All models
providing the plotted parameter are shown (MYTorus in blue, borus02 in orange, UXCLUMPY in red). Source properties are as
follows: Top left, time average of all NH,los (i.e. average value of the obscurer column density) for each single source. Top right,
NH,av (i.e. column density of the reflector) considered constant with time. Middle left, absolute value of the difference between the
two properties plotted above. Middle right, cosine of the inclination angle, θObs. Bottom left, covering factor of the torus. Bottom
right, dispersion of the torus cloud distribution.
emission in the 2−5 keV range. However, the medium-thick
reflector, if present, could could be more difficult to recog-
nize given the degeneracies with the combined contribution
of the line-of-sight component and the thin reflector.
While this possibility is brought forward when observing
the spectra in Figure 5, it must be thoroughly tested. We
propose to do that in future works, using sources with good
quality data, in which we may be able to disentangle the
three components.
If such was the case, the idea of a two-phase medium (as
propsoed by e.g., Siebenmorgen et al. 2015) could explain
the observations: a thinner, inter-cloud medium could act as

1 10
2 5 20
10
−5
10
−4
10
−3
keV
2
(Photons
cm
−2
s
−1
keV
−1
)
Energy (keV)
Two Reflectors
Fig. 5. borus02 AGN X-ray spectrum resulting from an ob-
scured l.o.s. (NH,los = 1024
cm−2
, in red), a scattered component
(FS = 10−2
, in green), a medium-thick reflector (NH,av = 1024
cm−2
, in blue), and a thin reflector (NH,av = 1023
cm−2
, in
cyan). We use Γ = 1.8, CF = 0.5 and cos(θObs) = 0.5.
the thin reflector, while the cloud distribution itself would
be the medium-thick reflector.
6.2. Torus geometry as a function of Variability
Figure 4 shows a series of histograms, which showcase how
certain torus properties depend on source variability. We
computed the plots by averaging a given parameter for
sources in each of the three variability categories defined
(i.e. Variable, Not Variable, and Undetermined).
Each of these categories contains a low number of
sources (particularly, we only classify 2 sources as ’Unde-
termined’, which results in large error bars), and thus we
are unable to make strong claims about torus geometry
differences for (NH,los-) variable and non-variable sources.
However, a few trends are seen in the plots in Figure 4.
The top, left panel of the figure shows the histogram
for the average value of NH,los across time. Meaning, the
average column density of the obscurer. We observe a ten-
dency for NH,los-variable sources to have thicker obscurers
compared to their non-variable counterparts.
When it comes to the average torus column density,
NH,av, this trend is not necessarily maintained. When con-
sidering the MYTorus results, we find overall thin reflectors
for the whole sample, as already mentioned. However, the
results are apparently different when considering borus02.
We note that the error bar of the borus02 bar for Variable
sources is particularly large, and that the high average value
is largely due to the borus02 model yielding NH,av > 1025
cm−2
for a single source (NGC 3281, but also IC 4518 A
for the Undetermined sources data point).
This effect is similarly present in the middle, left plot. In
here, we show the absolute value of the difference between
the NH of the obscurer and that of the reflector. The large
value and large error bar of borus02 are again due to
the two sources mentioned above. However, MYTorus also
suggests a larger difference between the absorber and the
reflector for variable sources. Meaning, non-variable sources
are much more consistent with having homogeneous tori.
We see no significant difference between inclination an-
gles for the two different source populations. This means
the observed variability (or lack thereof) is not a result of
relative orientation.
We again see no difference between the two samples
when it comes to CF, as determined by borus02. How-
ever, a difference is present when considering σT, as deter-
mined by UXCLUMPY. This is interesting, as both param-
eters are representative of the height of the material re-
sponsible for reflection. It is not obvious what could be the
cause of such discrepancy, but it likely lays in the different
shapes assumed for the reflector: for borus02, a homo-
geneous sphere with two conical cut-outs; for UXCLUMPY,
a cloud distribution of different densities. UXCLUMPY thus
already contains the ‘multiple reflector’ concept, and is per-
haps more representative of the whole shape of the torus.
If we assume, however, that borus02 only models the thin
reflector, the actual CF of the medium-thick material is
left unknown. In any case, UXCLUMPY results suggest that
NH,los-variable sources have broader cloud distributions.
Previous work by Marchesi et al. (2022) successfully
used a small borus02 CF to select a variable source, NGC
1358. They argued that, in some cases, as small CF can rep-
resent a patchy and broad cloud distribution, rather than
a homogeneous and flat one. If the theory is correct, one
should expect a difference in the average values for variable
and non-variable sources. However, once again, the discrep-
ancy may be due to our inability to model all reflectors in
the source.
We observe no clear difference in average X-ray lumi-
nosity among the three different populations.
6.3. ∆(NH,los) vs. ∆(t)
Fig. 6. borus02-obtained values of ∆(NH,los) between two con-
secutive observations, as a function of the time difference be-
tween said observations, for the whole sample.
Figure 6 shows the change in NH,los between any two
consecutive observations, as a function of the time differ-
ence between said observations. We opt to show results of

only one model, borus02, in order to make the plot more
easily readable.
As can be appreciated in the figure, while small changes
in NH,los can be observed at all given time differences be-
tween observations (∆(t) ∼ 1 − 5000 days), large changes
in NH,los (∆(NH,los) > 50 × 1022
cm−2
) are only observed
with large ∆(t) (> 100 d).
This is likely a consequence of the fact that individ-
ual clouds are not homogenous in NH (as already shown
for BLR clouds by e.g. Maiolino et al. 2010), but rather
present a density gradient toward their centers. Performing
calculations similar to those in Sect. 6.1, imposing that a
∆(t) > 100 d is needed for a significant change in NH,los im-
plies clouds are generally larger than rc > 6×10−6
−2×10−5
pc, depending on underlying assumptions (such as black
hole mass and cloud distance to the black hole).
Considering that events with ∆(NH,los) > 50 ×
1022
cm−2
are still rare for ∆(t) < 1000 d, one could fur-
ther infer that the majority of clouds have minimum sizes
rc > 6 × 10−5
− 2 × 10−4
pc. The lower limits we derive are
∼ 2 − 60 times larger than the ones for the ‘cometary tails’
of BLR clouds obtained by (Maiolino et al. 2010).
However, this estimate is highly dependent on the fact
that the majority of timescales probed are at ∆(t) > 1000 d.
A much larger sample than the one considered in this work
is needed to fully populate the plot in Fig. 6 and derive
more reliable constraints on typical torus cloud size.
6.4. Constant Parameters and Treatment of Reflection
In order to fit the data across multiple observations we have
assumed that the following parameters remain unchanged
across time: Γ for all three models, NH,av for MYTorus and
borus02, θObs and CF for borus02 and UXCLUMPY, and
σT for UXCLUMPY.
The inclination angle of the torus with respect to the ob-
server, θObs is not a quantity that is expected to change with
time. Similarly, due to the large scale of the torus (∼ 1−10
pc), its overall geometry is not expected to vary significantly
in timescales of up to ∼ 20 yr. Therefore, all parameters as-
sociated to the reflection component (NH,av,CF,σT), can be
considered constant across different observations.
A recent work on multiepoch observations of NGC 1358
performed by Marchesi et al. (2022) found that fitting the
torus parameters individually at each epoch produced re-
sults that were compatible with those of the joint fit, but
with much higher uncertainties. This is compatible with our
assumption. We note that an equivalent test cannot easily
be performed unless one possesses multiple sets of simulta-
neous XMM-Newton and NuSTAR observations, which is
unlikely to be the case for any other source.
For a handful of sources in the literature, with extremely
good data quality, further tests on the treatment of the re-
flection component may also be performed. One such exam-
ple is NGC 4388 in this work, which is not well-fit under our
assumptions. While large variations of torus geometry still
seem unlikely, other assumptions are present in our treat-
ment of reflection. One of them is the already-discussed
assumption of one single reflector. As such, NGC 4388 is
a good candidate for a future study including multiple re-
flectors. Another assumption lays in the relation between
the normalization of the line-of-sight component and the
reflection component. In the analysis of obscured AGN, the
widely-used assumption is that the two components have
the same normalization (e.g. Baloković et al. 2018; March-
esi et al. 2019; Zhao et al. 2021; Torres-Albà et al. 2021;
Esparza-Arredondo et al. 2021; Tanimoto et al. 2022). How-
ever, due to the non-simultaneous origin of the intrinsic and
the reflected emission, this is not necessarily the case. In
sources with very large flux variability, it is possible that
the normalization of the reflection component corresponds
to a past flux level of the intrinsic emission. We will explore
these possibilities for sources with good data quality in the
future.
We also assume that the photon index does not vary
between different observations. While some works have sug-
gested variability of Γ with strong luminosity variability in
AGN (e.g. Connolly et al. 2016)7
, we note that none of
the sources for which we had multiple NuSTAR observa-
tions suggested a need for Γ variability. Furthermore, we
do not observe extreme intrinsic luminosity variability for
the sources in this sample8
.
6.5. Agreement with previous results and model comparison
Our results show satisfactory agreement with those ob-
tained by Zhao et al. (2021). However, for 4/12 sources we
obtain NH,av values that are incompatible with (and in 3
sources, much lower than) those of their work. This could be
a result of introducing the 0.5 − 2 keV emission into the fit,
which Zhao et al. (2021) did not do. If the hypothesis of the
thin reflector is correct, this could result in a different sub-
component disentanglement needed to explain the emission
at around ∼ 2 keV. Alternatively, it could also mean that
a larger number of observations is needed to break degen-
eracies between parameters, and obtain reliable values of
NH,av (i.e. not pinned at the model hard limit).
Within our sample, there is reasonable agreement within
the three used models. The most notable differences are the
following:
• As already mentioned, borus02 has a slight tendency
to move to very large values of NH,av, sometimes even
pegged at the upper limit, in sources for which MYTorus
suggests more moderate densities.
• UXCLUMPY may favor scenarios in which, instead of
higher obscuration, a combination of lower obscuration
and lower intrinsic flux is preferred. This is particularly
true for NuSTAR data (see Fig. 3, sources 3C 445 and
NGC 7319).
• The three models tend to give slightly different NH,los
results. While the agreement is still remarkable, and
very often the values stay within errors, Fig. 4 (top,
left) shows a systematic trend between the three mod-
els. MYTorus yields the highest NH,los values, followed
by borus02 and further followed by UXCLUMPY, with
the lowest values. Interestingly, this is in disagreement
with the results obtained by Saha et al. (2022) (see their
Fig. 13), who saw large agreement between MYTorus
and borus02 while UXCLUMPY had a tendency to yield
7
We note that the mentioned work used Swift-XRT data, which
makes the disentanglement of NH,los, Γ and intrinsic luminosity
variability additionally complicated.
8
The largest flux variation observed is of a factor of ∼ 4, and
all others are under a factor of 3.

larger NH,los values. Both our results and theirs, how-
ever, agree that these differences tend to remain small.
7. Conclusions
In this work we have analyzed multiepoch X-ray data for
a sample of 12 local Compton-thin AGN, selected from the
work of Zhao et al. (2021). We have derived the amount
of obscuring column density in our line-of-sight (NH,los) for
each source, for each epoch available. We have also obtained
values of the average torus column density, NH,av, covering
factor, CF, inclination angle, θObs, and cloud dispersion,
σT, among others. In this section we summarize our main
conclusions:
• At least 42% (5/12) sources in the sample present
NH,los variability (through the available observations).
All sources require some form of variability, either in
flux, in NH,los, or both. This is expected, given how the
sample was selected to target variable sources.
• The majority of sources show strong disagreement be-
tween the time-average of NH,los (or average density
of the obscurer) and NH,av (average density of the re-
flector). This behavior is particularly strong in NH,los-
variable sources. The difference between the two oscil-
lates between a factor of ∼ 2 − 100.
• Based on the previous point, if the reflector and the ob-
scurer are the same (and representative of the density of
the torus), we must be observing the torus through over-
dense/underdense regions. We estimate those to have
angular sizes between 0.003 − 0.3◦
(i.e. 6 × 10−4
− 6 ×
10−3
pc). These regions would have to contain a number
of clouds of different densities to explain the observed
NH,los variability at shorter timescales. Furthermore, it
is unclear how statistically feasible it is that we observe
6/12 sources through underdense regions, while observ-
ing only 1 (or 2) through an overdense one. It is equally
unclear if such structures are dynamically feasible.
• We provide alternative explanations to the disagreement
between NH,los and NH,av. These imply the possibility
that the material responsible for reflection and the ma-
terial responsible for obscuration are not the same. We
suggest the possible presence of an inner, thicker ring
for sources with NH,av>NH,los. We suggest the possibil-
ity of a two-phase medium (or the presence of multiple
reflectors) for sources with NH,los>NH,av.
• We observe a tendency for NH,los-variable sources to
have, on average, larger obscuring density (i.e. NH,los)
and broader cloud distributions than their non-variable
counterparts.
• We observe no difference between inclination angle or
torus covering factors for variable and non-variable
sources.
• We observe small changes in ∆(NH,los) at all timescales,
but we only observe large changes (∆(NH,los) > 50 ×
1022
cm−2
) at large timescales (>100d). This suggests
clouds are extended, with a density profile increasing
toward their centers. While this is not unexpected, we
use these numbers to place rough constraints on min-
imum cloud sizes. We obtain that, even in the most
rapid variability scenarios, rc > 6 × 10−6
− 2 × 10−5
pc
for smaller clouds. And, for the majority of cases, rc >
6 × 10−5
− 2 × 10−4
pc. However, we note that these
estimates are highly dependent on availability of obser-
vations spanning smaller timescales.
• We observe a tendency for UXCLUMPY to result in
systematically lower NH,los values than MYTorus and
borus02. This is in disagreement with behavior ob-
served in previous works.
Future work will extend this analysis to include the fol-
lowing: 12 more sources, for which new observations have
been taken since 2019 (Pizzetti et al. in prep.); NGC 6300
(Sengupta et al. in prep.), Mrk 477 and NGC 7582 (Torres-
Albà et al. in prep.) and NGC 4507 (Cox et al. in prep.).
This will result in the completion of the ∼ 30 source sample
of variable sources selected from Zhao et al. (2021). We will
further expand the sample by selecting potential NH,los-
variable galaxies by applying the newly-developed method
of Cox et. al 2023.
8. Acknowledgments
N.T.A., M.A., R.S., A.P. and I.C. acknowledge fund-
ing from NASA under contracts 80NSSC19K0531,
80NSSC20K0045 and, 80NSSC20K834. S.M. acknowledges
funding from the INAF “Progetti di Ricerca di Rile-
vante Interesse Nazionale” (PRIN), Bando 2019 (project:
“Piercing through the clouds: a multiwavelength study of
obscured accretion in nearby supermassive black holes”).
The scientific results reported in this article are based on
observations made by the X-ray observatories NuSTAR
and XMM-Newton, and has made use of the NASA/IPAC
Extragalactic Database (NED), which is operated by
the Jet Propulsion Laboratory, California Institute of
Technology under contract with NASA. We acknowledge
the use of the software packages XMM-SAS and HEASoft.
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Appendix A: X-ray Fitting Results
This Appendix is a compilation of tables showing the best-
fit results for all sources analyzed in this work (except for
NGC 612, which can be found in Table 4.2, in the main
text).

Table A.1. NGC 788 fitting results
Model MYTorus borus02 borus02 UXCLUMPY
χ2
red 1.13 1.13 1.13 1.17
χ2
/d.o.f. 572/508 571/507 570/507 596/508
T 2.9σ 2.9σ 2.9σ 3.8σ
kT 0.25+0.07
−0.05 0.24+0.04
−0.05 0.24+0.04
−0.05 0.24+0.01
−0.03
E1 0.89+0.01
−0.01 0.90+0.01
−0.01 0.90+0.01
−0.01 0.90+0.01
−0.01
E2 1.86+0.04
−0.05 1.86+0.04
−0.06 1.86+0.04
−0.06 1.87+0.03
−0.04
E3 2.38+0.07
−0.05 2.39+0.05
−0.05 2.39+0.04
−0.05 2.39+0.05
−0.05
Γ 1.92+0.11
−0.12 1.77+0.04
−0.04 1.88+0.09
−0.04 1.87+0.07
−0.09
NH,av 0.19+0.02
−0.02 0.21+0.06
−0.03 31.6−u
−18.2 −
AS90 0.92+0.21
−0.16 − − −
AS0 0* − − −
CF − 0.34+0.05
−0.05 0.44+0.05
−0.23 0*
Cos (θObs) − 0.21+0.05
−0.13 0.46+0.13
−0.14 1.00−u
−0.47
σtor − − − 7.5+12.0
−0.5
Fs (10−3
) 2.96+1.04
−0.95 4.07+2.00
−1.31 5.09+1.18
−0.29 0.15+1.28
−u
norm (10−2
) 1.45+0.74
−0.51 0.906+0.091
−0.098 0.731+0.675
−0.282 43.4+2.8
−1.1
NH,Ch 0.79+0.08
−0.08 0.73+0.05
−0.05 0.62+0.04
−0.03 0.55+0.05
−0.2
NH,xmm 0.82+0.08
−0.08 0.76+0.04
−0.04 0.65+0.02
−0.02 0.59+0.08
−0.08
NH,nus 1.10+0.10
−0.09 1.04+0.07
−0.07 0.86+0.05
−0.04 0.83+0.03
−0.05
CCh 1* 1* 1* 1*
Cxmm =CCh =CCh =CCh =CCh
Cnus =CCh =CCh =CCh =CCh
χ2
red No Var. 1.47 1.47 1.37 1.49
T 10.6σ 10.6σ 8.4σ 11.1σ
χ2
red No C Var. 1.13 1.13 1.13 1.17
T 2.9σ 2.9σ 2.9σ 3.8σ
χ2
red No NH Var. 1.15 1.15 1.13 1.19
T 3.4σ 3.4σ 2.9σ 4.3σ
P-value 1.4e-1 2.0e-1 1.7e-5
Notes: Same as Table 4.2, with the following additions:
En: Central energy of the added nth Gaussian line, in keV.

χ2
red 0.93 0.93 0.93
χ2
/d.o.f. 193/208 193/206 192/207
T 1.0σ 1.0σ 1.0σ
kT 0.60+0.05
−0.08 0.59+0.06
−0.11 0.59+0.06
−0.11
Γ 1.69+0.26
−0.25 1.58+0.26
−u 1.55+0.37
−0.32
NH,av 0.06+0.08
−u 0.08+u
−u −
AS90 1* − −
AS0 1* − −
CF − 0.52+0.30
−u 0*
Cos (θObs) − 0.15+u
−u 0.0+u
−u
σtor − − 3.8+u
−u
Fs (10−2
) 0.61+0.59
−0.31 1.24+0.41
−0.77 0.90+7.41
−0.86
norm (10−4
) 4.44+4.62
−2.28 3.19+3.03
−1.24 6.50+6.05
−4.75
NH,xmm 0.34+0.07
−0.06 0.31+0.07
−0.07 0.26+0.04
−0.03
NH,Ch1 0.21+0.07
−0.06 0.19+0.05
−0.05 0.16+0.04
−0.03
NH,Ch2 − − −
NH,Ch3 0.33+0.06
−0.05 0.34+0.07
−0.06 0.28+0.05
−0.03
NH,Ch4 0.27+0.05
−0.05 0.27+0.05
−0.05 0.22+0.04
−0.04
NH,Ch5 0.28+0.05
−0.04 0.29+0.05
−0.06 0.24+0.04
−0.04
NH,nus 0.18+0.10
−0.10 0.14+0.08
−0.09 0.10+0.09
−0.06
Cxmm 1.20+0.33
−0.17 1.18+0.13
−0.14 1.21+0.29
−0.18
CCh1 1* 1* 1*
CCh2 − − −
CCh3 0.55+0.16
−0.12 0.66+0.14
−0.10 0.66+0.16
−0.12
CCh4 = CCh3 = CCh3 = CCh3
Cnus = CCh1 = CCh1 = CCh1
χ2
red No Var. 1.98 2.00 1.69
T 14.3σ 14.6σ 10.1σ
χ2
red No C Var. 1.18 1.19 1.19
T 2.6σ 2.7σ 2.7σ
χ2
red No NH Var. 0.99 1.02 1.05
T 0.1σ 0.3σ 0.7σ
P-value 9.7e-1 9.2e-1 8.5e-1
Notes: Same as Table 4.2. The second Chandra observation
of the system formed by NGC 833 and NGC 835 did not in-
clude the former, hence the missing parameters corresponding
to the observation. See Appendix C for details.

χ2
red 1.07 1.08 1.05
χ2
/d.o.f. 479/446 479/445 468/446
T 1.5σ 1.7σ 1.1σ
kT 0.61+0.02
−0.02 0.61+0.04
−0.03 0.61+0.02
−0.02
E1 0.68+0.03
−0.02 0.68+0.03
−0.19 0.68+0.02
−0.03
E2 1.29+0.06
−0.09 1.29+0.05
−0.10 1.29+0.06
−0.06
Γ 1.68+0.13
−0.13 1.63+0.15
−0.12 1.55+0.22
−0.25
NH,av 0.19+0.08
−0.09 0.21+0.10
−0.10 −
AS90 0.52+0.18
−0.18 − −
AS0 0* − −
CF − 0.18+0.08
−0.04 0*
Cos (θObs) − 0.05+0.17
−u 0.86+0.04
−0.45
σtor − − 6.8+3.8
−4.5
Fs (10−3
) 7.06+1.94
−1.68 6.88+1.82
−1−38 4.93+12.16
−u
norm (10−3
) 1.08+0.41
−0.29 0.96+0.38
−0.24 1.90+0.19
−0.48
NH,xmm 1.53+1.07
−0.26 1.48+1.50
−0.23 1.35+0.05
−0.02
NH,Ch1 0.89+0.25
−0.14 0.88+0.28
−0.14 1.04+0.18
−0.19
NH,Ch2 0.86+0.32
−0.14 0.85+0.33
−0.14 0.94+0.24
−0.16
NH,Ch3 0.31+0.02
−0.03 0.30+0.03
−0.02 0.28+0.04
−0.03
NH,Ch4 0.32+0.03
−0.03 0.32+0.03
−0.03 0.31+0.04
−0.04
NH,Ch5 0.33+0.03
−0.03 0.32+0.03
−0.03 0.32+0.03
−0.03
NH,nus 0.46+0.06
−0.05 0.45+0.06
−0.05 0.27+0.16
−0.12
Cxmm 1.34+0.10
−0.09 1.25+0.07
−0.07 1.28+0.18
−0.16
CCh1 1* 1* 1*
Cnus = CCh1 = CCh1 0.63+0.12
−0.22
χ2
red No Var. 4.44 4.63 4.55
T 73.2σ 77.2σ 75.6σ
χ2
red No C Var. 1.17 1.18 1.18
T 3.6σ 3.8σ 3.8σ
χ2
red No NH Var. 2.31 3.84 3.85
T 27.6σ 59.9σ 60.2σ
P-value 4.7e-20 3.1e-13 5.7e-52
En: Central energy of the added nth Gaussian line, in keV.

Table A.4. 3C 105 fitting results
χ2
red 1.01 1.01 1.01
χ2
/d.o.f. 240/237 240/236 240/237
T 0.2σ 0.2σ 0.2σ
kT 0.21+0.03
−0.03 0.20+0.03
−0.03 0.20+0.03
−0.03
Γ 1.48+0.15
−u 1.44+0.14
−u 1.57+0.17
−0.03
NH,av 0.40+0.57
−0.21 0.43+0.24
−0.15 −
AS90 0.75+0.48
−0.40 − −
AS0 0* − −
CF − 0.30+0.13
−0.12 0*
Cos (θObs) − 0.10+0.80
−u 0.00−u
−u
σtor − − 15.9+20.8
−6.9
Fs (10−3
) 2.67+1.18
−1.13 2.75+0.95
−0.93 2.93+4.21
−1.26
norm (10−3
) 2.92+1.65
−0.84 2.50+0.06
−0.69 5.09+2.64
−1.56
NH,ch 0.45+0.08
−0.05 0.46+0.04
−0.04 0.49+0.03
−0.09
NH,xmm 0.39+0.05
−0.04 0.39+0.03
−0.03 0.39+0.02
−0.03
NH,nus1 0.45+0.08
−0.07 0.45+0.03
−0.03 0.44+0.03
−0.08
NH,nus2 0.39+0.06
−0.06 0.39+0.06
−0.03 0.40+0.03
−0.07
Cch 1* 1* 1*
Cxmm 0.63+0.16
−0.15 0.62+0.04
−0.08 0.59+0.03
−0.13
Cnus1 0.28+0.08
−0.07 0.27+0.02
−0.06 0.25+0.08
−0.06
Cnus2 =Cnus1 =Cnus1 =Cnus1
χ2
red No Var. 2.66 2.67 2.65
T 25.8σ 26.0σ 25.7σ
χ2
red No C Var. 1.20 1.21 1.23
T 3.1σ 3.3σ 3.6σ
χ2
red No NH Var. 1.05 1.02 1.01
T 0.8σ 0.3σ 0.2σ
P-value 9.2e-1 9.2e-1 8.0e-1
Notes: Same as Table 4.2.

Table A.5. 4C+29.30 fitting results
Statred 425/432 421/431 437/433
Stat/d.o.f. 0.98 0.98 1.01
T 0.4σ 0.4σ 0.2σ
kT 0.640.04
−0.04 0.63+0.04
−0.04 0.64+0.04
−0.04
Γ 1.72+0.22
−0.20 1.70+0.19
−0.19 1.90+0.14
−0.20
NH,av 0.21+0.04
−0.02 0.22+0.07
−0.03 −
AS90 0.81+0.19
−0.15 − −
AS0 0* − −
CF − 0.28+0.06
−0.03 0*
Cos (θObs) − 0.10+0.09
−u 0.16+0.14
−u
σtor − − 17.5+8.6
−7.4
Fs (10−3
) 2.07+1.79
−0.88 1.75+0.70
−0.68 2.22+1.58
−0.80
norm (10−3
) 2.66+2.47
−1.36 2.14+1.45
−0.56 3.22+2.18
−1.69
NH,Ch1 0.72+0.16
−0.16 0.68+0.14
−0.06 0.61+0.10
−0.11
NH,xmm 0.87+0.18
−0.19 1.08+0.04
−0.11 0.98+0.08
−0.10
NH,Ch2 0.65+0.06
−0.06 0.65+0.06
−0.03 0.61+0.04
−0.04
NH,Ch3 0.59+0.05
−0.05 0.60+0.05
−0.01 0.55+0.04
−0.02
NH,Ch4 0.60+0.06
−0.05 0.60+0.05
−0.02 0.56+0.04
−0.02
NH,Ch5 0.62+0.07
−0.06 0.58+0.05
−0.02 0.54+0.03
−0.02
NH,nus 0.61+0.17
−0.13 0.62+0.16
−0.13 0.63+0.09
−0.14
CCh1 1* 1* 1*
Cxmm 1.31+0.59
−0.35 1.61+0.70
−0.07 1.82+0.83
−0.47
CCh2 1.15+0.50
−0.29 1.30+0.49
−0.29 1.38+0.37
−0.25
Cnus 0.73+0.18
−0.13 0.84+0.04
−0.28 = CCh1
Statred No Var. 2.40 2.41 2.41
T 29.4σ 29.6σ 29.7σ
Statred No C Var. 0.99 0.99 1.03
T 0.2σ 0.2σ 0.6σ
Statred No NH Var. 0.98 1.16 1.07
T 0.4σ 3.3σ 1.5σ
P-value 9.9e-1 6.7e-1 5.4e-1

χ2
red 1.10 1.04 1.07
χ2
/d.o.f. 469/427 444/427 460/428
T 2.1σ 0.8σ 1.4σ
kT 0.58+0.05
−0.09 0.58+0.04
−0.11 0.57+0.10
−0.06
Γ 1.65+0.11
−0.12 1.81+0.14
−0.07 1.75+0.04
−0.05
NH,av 0.31+0.10
−0.06 31.6−u
−8.4 −
AS90 0.21+0.23
−u − −
AS0 0.31+0.30
−0.17 − −
CF − 0.52+0.04
−0.14 0*
Cos (θObs) − 0.53+0.15
−0.08 0.00−u
−u
σtor − − 28.0+16.5
−8.4
Fs (10−4
) 8.17+6.76
−3.39 17.3+6.8
−3.2 51.9+24.6
−51.6
norm (10−2
) 1.65+1.15
−0.75 0.90+0.48
−0.24 1.06+0.45
−0.15
NH,xmm 1.16+0.17
−0.16 0.86+0.09
−0.10 0.89+0.06
−0.07
NH,nus 2.25+0.24
−0.26 2.05+0.28
−0.38 3.01+0.62
−0.35
NH,Ch 1.04+0.17
−0.17 0.76+0.10
−0.10 0.76+0.08
−0.06
Cxmm =CCh =CCh =CCh
Cnus 1.43+0.22
−0.17 1.53+0.16
−0.15 1.53+0.14
−0.15
CCh 1* 1* 1*
χ2
red No Var. 1.53 1.43 1.99
T 11.0σ 8.9σ 20.6σ
χ2
red No C Var. 1.16 1.10 1.18
T 3.3σ 2.1σ 3.7σ
χ2
red No NH Var. 1.43 1.25 1.48
T 8.9σ 5.2σ 9.9σ
P-value 8.3e-3 2.4e-5 1.2e-27

χ2
red 1.28 1.25 1.31
χ2
/d.o.f. 6708/5224 6532/5224 6847/5225
T 20.2σ 18.0σ 22.4σ
kT 0.28+0.02
−0.02 0.26+0.02
−0.02 0.27+0.02
−0.02
kT2 0.70+0.03
−0.04 0.68+0.06
−0.04 0.69+0.14
−0.06
NH,apec 0.59+0.09
−0.10 0.62+0.12
−0.17 0.60+0.09
−0.09
Γ 1.58+0.01
−0.01 1.53+0.02
−0.02 1.81+0.03
−0.03
NH,av 0.10+0.01
−0.01 0.12+0.01
−0.01 −
AS90 1.23+0.20
−0.21 − −
AS0 0.53+0.12
−0.12 − −
CF − 0.52+0.04
−0.04 0*
Cos (θObs) − 0.45+0.03
−0.03 0.00+0.14
−u
σtor − − 66.7+8.7
−5.0
Fs (10−3
) 1.01+0.59
−0.52 0.84+0.56
−0.54 11.52.0
−0.9
norm (10−2
) 1.54+0.10
−0.10 1.40+0.05
−0.05 2.41+0.24
−0.14
NH,Ch1 0.71+0.03
−0.03 0.71+0.04
−0.03 0.66+0.08
−0.05
NH,xmm1 0.37+0.01
−0.01 0.36+0.02
−0.01 0.33+0.01
−0.01
NH,xmm2 0.235+0.003
−0.003 0.231+0.003
−0.003 0.211+0.002
−0.003
NH,Ch2 0.91+0.05
−0.05 0.93+0.05
−0.04 0.90+0.04
−0.03
NH,nus1 0.30+0.01
−0.01 0.29+0.02
−0.02 0.26+0.02
−0.02
NH,xmm3 0.267+0.004
−0.004 0.260+0.004
−0.004 0.243+0.003
−0.003
NH,nus2 0.219+0.004
−0.005 0.214+0.004
−0.005 0.195+0.003
−0.003
CCh 1* 1* 1*
Cxmm1 1.25+0.07
−0.05 1.20+0.06
−0.06 = CCh2
Cxmm2 1.57+0.08
−0.07 1.53+0.09
−0.08 1.55+0.09
−0.08
CCh2 1.11+0.06
−0.06 1.13+0.06
−0.05 1.16+0.07
−0.06
Cnus1 0.35+0.02
−0.02 0.33+0.02
−0.02 0.33+0.02
−0.01
Cxmm3 1.40+0.07
−0.08 1.36+0.07
−0.07 1.38+0.08
−0.07
Cnus2 = Cxmm3 = Cxmm3 = Cxmm3
χ2
red No Var. 23.9 23.9 24.1
T 1727σ 1727σ 1741σ
χ2
red No C Var. 1.61 1.62 1.80
T 44.1σ 44.8σ 57.8σ
χ2
red No NH Var. 1.84 1.71 1.73
T 60.7σ 51.3σ 52.7σ
P-value 0 0 0
kT2: Second (hotter) apec component temperature, in units of
keV.
NH,apec: Obscuring column density associated to the second
apec component, in units of 1022
cm−2
.

Table A.8. IC 4518 A fitting results
χ2
red 1.07 1.06 1.16
χ2
/d.o.f. 413/386 408/385 448/385
T 1.4σ 1.2σ 3.1σ
kT 0.66+0.03
−0.03 0.67+0.03
−0.03 0.67+0.03
−0.03
Γ 1.91+0.15
−0.14 1.84+0.09
−0.08 1.76+0.03
−0.06
NH,av 3.46−u
−1.29 14.0−u
−11.1 −
AS90 0* − −
AS0 2.65+0.75
−0.58 − −
CF − 0.87+0.02
−0.19 0.29+0.03
−0.09
Cos (θObs) − 0.95−u
−0.57 0.50+0.42
−0.24
σtor − − 84.0−u
−0.14
Fs (10−2
) 1.22+0.46
−0.37 1.26+0.25
−0.34 23.5+0.30
−0.62
norm (10−3
) 2.18+0.85
−0.60 1.85+0.46
−0.31 2.19+0.27
−0.13
NH,xmm1 0.21+0.02
−0.02 0.21+0.02
−0.01 0.21+0.08
−0.06
NH,xmm2 0.31+0.04
−0.03 0.33+0.03
−0.03 0.32+0.01
−0.02
NH,nus 0.14+0.04
−0.03 0.15+0.04
−0.03 0.13+0.02
−0.02
Cxmm1 1* 1* 1*
Cxmm2 0.88+0.06
−0.06 0.90+0.06
−0.06 0.93+0.05
−0.05
Cnus 1.45+0.15
−0.13 1.49+0.15
−0.14 1.44+0.10
−0.05
χ2
red No Var. 2.66 2.94 3.04
T 32.7σ 38.3σ 40.2σ
χ2
red No C Var. 1.25 1.24 1.27
T 4.9σ 4.7σ 5.3σ
χ2
red No NH Var. 1.33 1.32 1.43
T 6.5σ 6.3σ 8.5σ
P-value 3.6e-2 1.8e-2 1.7e-5

χ2
red 1.02 1.03 1.00
χ2
/d.o.f. 2220/2178 2248/2177 2180/2178
T 0.9σ 1.4σ 0.0σ
kT 0.62+0.04
−0.04 0.56+0.09
−0.08 0.56+0.10
−0.31
kT2 0.71+0.56
−0.24 1.63+0.09
−0.09 1.29+0.33
−0.09
NH,apec 26.1+5.7
−5.4 5.14+0.16
−0.15 6.04+0.65
−0.74
Γ 1.75+0.07
−0.07 1.62+0.01
−0.01 1.60+0.04
−0.03
NH,av 0.14+0.02
−0.01 0.13+0.02
−0.03 −
AS90 7.99+5.70
−u − −
AS0 4.26+7.29
−u − −
CF − 0.93+0.04
−0.03 0*
Cos (θObs) − 0.95−u
−0.02 0.00−u
−u
σtor − − 84.0−u
−5.9
Fs (10−2
) 0.60+0.41
−0.37 1.96+0.16
−0.06 21.8+2.3
−3.1
norm (10−3
) 4.36+0.95
−1.11 2.76+0.03
−0.03 3.31+0.24
−0.20
NH,xmm 0.28+0.03
−0.03 0.24+0.01
−0.01 0.20+0.01
−0.01
NH,Ch1 0.26+0.03
−0.01 0.23+0.01
−0.01 0.22+0.02
−0.01
NH,nus 0.33+0.03
−0.03 0.29+0.01
−0.01 0.13+0.01
−0.02
NH,Ch2 0.33+0.03
−0.03 0.30+0.01
−0.01 0.25+0.02
−0.02
NH,Ch3 0.32+0.03
−0.03 0.28+0.01
−0.01 0.24+0.01
−0.01
NH,Ch4 0.33+0.03
−0.03 0.28+0.01
−0.01 0.25+0.01
−0.01
NH,Ch5 0.31+0.02
−0.02 0.27+0.01
−0.01 0.26+0.01
−0.01
Cxmm = CCh4 = CCh4 = CCh4
CCh1 1* 1* 1*
Cnus = CCh2 = CCh2 0.77+0.05
−0.05
CCh2 1.16+0.07
−0.06 1.14+0.03
−0.03 1.11+0.05
−0.05
CCh4 1.26+0.08
−0.05 1.21+0.02
−0.02 1.21+0.05
−0.04
χ2
red No Var. 1.16 1.18 1.18
T 7.5σ 8.4σ 8.4σ
χ2
red No C Var. 1.04 1.06 1.07
T 1.9σ 2.8σ 3.3σ
χ2
red No NH Var. 1.03 1.05 1.06
T 1.4σ 2.3σ 2.8σ
P-value 9.9e-1 6.3e-1 2.7e-3
kT2: Second (hotter) apec component temperature, in units
of keV.
cm−2
.

χ2
red 1.08 1.07 1.10
χ2
/d.o.f. 542.71/501 538.10/501 553.84/502
T 1.8σ 1.6σ 2.2σ
kT 0.41+0.11
−0.09 0.35+0.10
−0.06 0.34+0.06
−0.06
kT2 0.73+0.16
−0.12 0.67+0.15
−0.07 0.66+0.14
−0.06
NH,apec 0.72+0.14
−0.20 0.71+0.13
−0.14 0.72+0.09
−0.09
Γ 1.73+0.15
−0.17 1.75+0.15
−0.14 2.04+0.22
−0.13
NH,av 0.25+0.07
−0.04 0.33+0.09
−0.07 −
AS90 0.95+0.30
−0.44 − −
AS0 0.15+0.27
−u − −
CF − 0.31+0.06
−0.04 0*
Cos (θObs) − 0.26+0.03
−0.04 0.00−u
−u
σtor − − 77.9−u
−10.7
Fs (10−4
) 9.78+10.0
−9.61 3.23+9.88
−u 0*
norm (10−3
) 3.55+0.15
−0.12 3.70+1.59
−1.03 7.92+2.96
−2.50
NH,xmm 0.87+0.05
−0.05 0.87+0.06
−0.05 0.84+0.07
−0.08
NH,Ch1 0.46+0.04
−0.04 0.47+0.04
−0.04 0.47+0.04
−0.05
NH,Ch2 0.46+0.03
−0.03 0.47+0.03
−0.03 0.46+0.03
−0.05
NH,nus1 2.17+0.36
−0.26 2.11+0.26
−0.22 0.71+0.25
−0.15
NH,nus2 1.78+0.34
−0.34 1.73+0.30
−0.32 0.98+0.14
−0.17
Cxmm 1.31+0.08
−0.08 1.32+0.09
−0.08 1.29+0.09
−0.08
CCh1 1* 1* 1*
Cnus1 = CCh1 = CCh1 0.32+0.11
−0.07
Cnus2 0.83+0.13
−0.16 0.85+0.13
−0.15 0.44+0.08
−0.08
χ2
red No Var. 5.44 5.47 5.71
T 99.9σ 100σ 106σ
χ2
red No C Var. 1.19 1.19 1.20
T 4.3σ 4.3σ 4.5σ
χ2
red No NH Var. 1.91 1.88 1.92
T 20.4σ 19.7σ 20.6σ
P-value 5.3e-46 4.5e-42 8.0e-5
kT2: Second (hotter) apec component temperature, in units of
keV.
cm−2
.

χ2
red 1.03 1.03 1.08
χ2
/d.o.f. 1394/1353 1388/1352 1459/1353
T 1.1σ 1.1σ 2.9σ
kT − − −
Γ 1.53+0.05
−0.05 1.42+0.03
−u 1.57+0.01
−0.01
NH,av 0.05+0.01
−0.01 0.06+0.01
−0.01 −
AS90 2.55+0.46
−0.40 − −
AS0 0* − −
CF − 1.00−u
−0.10 0*
Cos (θObs) − 0.00+0.13
−u 1.00−u
−0.73
σtor − − 7.10+22.41
−0.10
norm(10−3
) 2.24+0.41
−0.32 1.72+0.02
−0.18 1.87+0.06
−0.06
Γjet 1.40+0.19
−0.18 1.36+0.09
−0.09 0.75+0.06
−0.05
NH,ch 0.55+0.03
−0.03 0.52+0.02
−0.03 0.44+0.03
−0.02
NH,xmm 0.52+0.03
−0.03 0.49+0.01
−0.03 0.46+0.02
−0.02
NH,nus 0.39+0.03
−0.03 0.36+0.01
−0.02 0.28+0.01
−0.01
norm jet,ch(10−6
) 8.26+1.01
−1.01 7.52+0.82
−0.82 8.13+0.73
−0.73
normjet,xmm(10−5
) 2.46+0.47
−0.37 2.00+0.08
−0.08 2.40+0.63
−0.03
normjet,nus =normjet,xmm =normjet,xmm =normjet,xmm
χ2
red No Var. 1.50 1.49 1.55
T 18.4σ 18.0σ 20.2σ
χ2
red No C Var. 1.25 1.25 1.31
T 9.2σ 9.2σ 11.4σ
χ2
red No NH Var. 1.25 1.26 1.33
T 9.2σ 9.6σ 12.1σ
P-value 1.4e-3 1.9e-16 2.5e-8
normjet,instrument: Variable normalization on the added jet component
required to model the source.

Appendix B: Source Spectra
In this section we present the best fit borus02 models to
the multiepoch spectra of all sources in the sample, shown
in Figs. B.1 and B.2. We opt to show the borus02 fits
over those of the other models, since MYTorus has a re-
flection component divided into four different individual
sub-components, which makes the spectra much more dif-
ficult to interpret. UXCLUMPY, on the other hand, does not
show a distinction between l.o.s. and reflection components,
therefore providing less information in the spectral decom-
position. The spectra shown in Figs. B.1 and B.2 should be
read as follows:
• All observations for a single source are shown together,
each one in a different color. Meaning, all detectors in
the same telescope are colored the same in each indi-
vidual observation (i.e. MOS1, MOS2, PN for XMM-
Newton, and FPMA, FPMB for NuSTAR).
• Soft band observations (XMM-Newton and Chandra)
are colored chronologically, as listed in Tables 4.2 and
A-A. The color order is as follows, from first to last
observation: Black, red, green, blue, cyan, magenta.
• Hard band observations (i.e. NuSTAR) are colored, also
chronologically, but separated from the soft-band obser-
vations. This is done to avoid confusion between differ-
ent bands. From first to second, the colors are: Grey,
orange.
• For each individual observation, we plot the overall best-
fit model as a solid line, the l.o.s. component as a dashed
line, the reflection as a dotted line, the scattering as a
dot-dash line, and the soft emission component (single
or double mekal and any added lines) as a dash-dot-
dot-dot. We note that 3C 452 has a jet component in-
stead of a soft component + scattering, and we use a
dash-dot-dot-dot (equivalent to the soft emission com-
ponent) to represent it.

10−4
10−3
0.01
keV
2
(Photons
cm
−2
s
−1
keV
−1
)
NGC 788
1 10
2 5 20 50
0.5
1
1.5
2
ratio
Energy (keV)
10−5
10−4
10−3
keV
2
(Photons
cm
−2
s
−1
keV
−1
)
NGC 833
1 10
2 5 20
0.5
1
1.5
2
2.5
ratio
Energy (keV)
10−5
10−4
10−3
keV
2
(Photons
cm
−2
s
−1
keV
−1
)
NGC 835
1 10
2 5 20
0.5
1
1.5
2
2.5
ratio
Energy (keV)
10−5
10−4
10−3
0.01
keV
2
(Photons
cm
−2
s
−1
keV
−1
)
3C 105
1 10
2 5 20
0.5
1
1.5
ratio
Energy (keV)
10−5
10−4
10−3
0.01
keV
2
(Photons
cm
−2
s
−1
keV
−1
)
4C+29.30
1 10
2 5 20
1
1.5
2
ratio
Energy (keV)
10−4
10−3
0.01
keV
2
(Photons
cm
−2
s
−1
keV
−1
)
NGC 3281
1 10
0.5
1
1.5
2
2.5
ratio
Energy (keV)
Fig. B.1. From left to right, top to bottom: borus02 fits to the data for NGC 788, NGC 833, NGC 835, 3C 105, 4C+29.30, NGC
3281. Color code is as explained in Appendix B.

10−4
10−3
0.01
0.1
keV
2
(Photons
cm
−2
s
−1
keV
−1
)
NGC 4388
1 10
0.5
1
1.5
2
ratio
Energy (keV)
10−4
10−3
0.01
keV
2
(Photons
cm
−2
s
−1
keV
−1
)
IC 4518 A
1 10
2 5 20 50
1
1.5
2
ratio
Energy (keV)
10−4
10−3
0.01
keV
2
(Photons
cm
−2
s
−1
keV
−1
)
3C 445
1 10
2 5 20
0.5
1
1.5
2
2.5
ratio
Energy (keV)
10−5
10−4
10−3
0.01
keV
2
(Photons
cm
−2
s
−1
keV
−1
)
NGC 7319
1 10
2 5 20
1
2
ratio
Energy (keV)
10−5
10−4
10−3
0.01
keV
2
(Photons
cm
−2
s
−1
keV
−1
)
3C 452
1 10
2 5 20 50
0.5
1
1.5
2
2.5
ratio
Energy (keV)
Fig. B.2. From left to right, top to bottom: borus02 fits to the data for NGC 4388, IC 4518 A, 3C 445, NGC 7319 and 3C 452.
Color code is as explained in Appendix B.

Appendix C: Comments on Individual Sources
In this section we provide a detailed explanation about spe-
cific analysis and fitting details for each source, that may
deviate (or need clarification) from the methods described
in sections 2 and 5. We also comment on the fitting results
for each specific source, add comments on model compari-
son if discrepancies are present, and compare the obtained
fitting parameters to those obtained by Zhao et al. (2021),
from which this sample is selected, and who used borus02
on only two observations per source.
Appendix C.1: NGC 612
Data reduction/fitting: C-statistic was used to fit Chan-
dra observations 1 and 2, given how the data quality forced
us to bin them with 3 and 5 cts/bin, respectively. Table
4.2 thus refers to Stat. (total statistic, a mix of χ2
and C-
statistic) instead of χ2
. apec was applied to model solely
the XMM-Newton data, as the Chandra data did not show
any excess (again, probably due to the lower quality data).
Analysis of results: All models fit this source well,
and our results are compatible with those derived by Zhao
et al. (2021). The best-fit values for the torus parameters
are in good agreement, within errors, for all models. How-
ever, that is not the case when it comes to the variability
determination. While all models require some form of vari-
ability (T> 10σ for the non-variability scenario), MYTorus
is not able to discern between a pure NH,los variability sce-
nario and a pure flux variability with enough significance.
borus02, on the other hand, clearly favors an NH,los-
variable scenario9
. And finally, UXCLUMPY favors a scenario
in which the spectral variability is predominantly caused by
intrinsic flux changes, rather than absorption. We thus clas-
sify this source as ‘Undetermined’.
Data reduction/fitting: Three Gaussian lines (zgauss
in xspec) were added to model the source soft emission.
The reduced χ2
showed significant improvement for all
models, justifying this decision (1.24 to 1.13 for MYTorus,
1.27 to 1.13 for borus02 and 1.29 to 1.17 for UXCLUMPY).
Analysis of results: The models and the data show
a more significant tension than for the majority of sources
in this sample, at around the 3σ level. For this source we
present two borus02 configurations that can explain the
data with the same goodness of fit. The two configurations
can be described as a low-NH,av scenario and a high-NH,av
one. The former is statistically preferred by MYTorus,
which cannot reproduce the latter without forcing NH,av
to stay at a very high value. UXCLUMPY, while not directly
comparable (it does not provide a value for NH,av), results
in values of NH,los that are more similar to those of the high-
NH,av borus02 option. Given how the first configuration
is practically identical to the MYTorus results, we opt to
show the second borus02 configuration (the high-NH,av
scenario) in all plots regarding the source. The degeneracy
between the reflection and line-of-sight component model-
9
We note that, while MYTorus and borus02 give practucally
identical best-fit parameters, the errors of MYTorus are much
larger. This results in the source being compatible with a non
NH,los-variability scenario
ing results in different estimates for NH,los for each model,
although the upwards trend of NH,los vs time is maintained
(see Fig. 2).
The analysis of Zhao et al. (2021) favored the high-NH,av
scenario, and preferred pure flux variability over the pure
NH,los variability depicted here. However, as shown by our
χ2
red comparisons, either option can explain the data at a
similar level for all models. UXCLUMPY is the only model
that, when considering the p-value determination, flags this
source as variable. This is likely due to the smaller errors
and slightly larger differences between NH,los values at dif-
ferent epochs, compared to the MYTorus and borus02 re-
sults. However, given how the χ2
red comparison doesn’t show
a significant preference for NH,los variability over intrinsic
flux variability, we classify this source as ‘Non-variable in
NH,los’
Data reduction/fitting: NGC 833 is part of a closely in-
teracting system with NGC 835 (separation ∼ 10
). The sec-
ond Chandra observation (Obs. ID: 10394) considered for
this merging system does not include NGC 833, but rather
only NGC 835. We opted to add this observation to the
table (with blank data) to avoid confusion with the epochs
shown for NGC 835. Similarly, in the XMM-Newton obser-
vation we use data from only the MOS modules, as NGC
833 falls on a prominent CCD line on the PN observation.
The NuSTAR extraction region was limited to 4000
to avoid
contamination from NGC 835. For the same reason, the
background was extracted from a circular region (instead
of the usual annulus) of radius 6000
. Nearby source NGC
838, a starburst galaxy at ∼ 3.50
from NGC 835, shows no
NuSTAR emission, and therefore is not contaminating the
spectrum. The Chandra spectrum was also extracted from
a circular region (1500
) radius, to avoid contamination.
Analysis of results: This source is well-fit by all mod-
els. The torus parameters are highly unconstrained, likely
due to a very subdominant reflection component (see e.g.
Torres-Albà et al. 2021). The χ2
red comparison shows, for
all models, that NH,los variability is unnecessary to explain
the data. Likewise, the p-value of all NH,los being the same
is large enough that one cannot rule out the hypothesis.
Thus, we classify this source as ‘Non-variable in NH,los’.
Data reduction/fitting: The NuSTAR extraction region
was limited to 4000
to avoid contamination from NGC 833.
For the same reason, the background was extracted from
a circular region (instead of the usual annulus) of radius
6000
. Nearby source NGC 838, a starburst galaxy at ∼ 3.50
from NGC 835, shows no NuSTAR emission, and there-
fore is not contaminating the spectrum. The Chandra data
was taken using a larger-than-usual 800
circular region to
include all the soft emission (this source is a known Lu-
minous Infrared Galaxy, or LIRG), for easier comparison
to the XMM-Newton data. Again, the background was ex-
tracted from a circular region (1500
) radius, to avoid con-
tamination. To fit the soft emission in this source we tried
both adding Gaussian lines, or adding a second apec com-
ponent (justified by this source being in a merging system,
as well as a known LIRG, see Torres-Albà et al. 2018, for

details). Adding two lines improved the χ2
over adding a
second apec, and the apec addition resulted in inverted
temperatures (i.e. the ‘cooler’ gas was more obscured that
the ‘hotter’ gas, which is physically implausible). We thus
opted to use the Gaussian lines.
Analysis of results: The data is well-fitted by all
models, which are in reasonable agreement. However, the
best-fit values for cos(θObs) derived with borus02 and
UXCLUMPY are incompatible. The former favors an edge-
on configuration, while the latter favors an almost face-on
one. Our results are compatible with those of Zhao et al.
(2021), whose analysis also favors an edge-on scenario. All
models agree that this source shows significant NH,los vari-
ability. We classify this source as ‘variable in NH,los’.
Appendix C.5: 3C 105
Data reduction/fitting: No issues to report.
Analysis of results: The data is well-fitted by all mod-
els, which are in good agreement. Our results are also con-
sistent with those of Zhao et al. (2021). Introducing NH,los
variability is not necessary to explain the data, and the p-
value is also > 0.01 for all models. We thus classify this
source as ‘Non-variable in NH,los’.
Appendix C.6: 4C+29.30
Data reduction/fitting: The Chandra data shows a com-
plex morphology in the soft band, including a jet further out
from the nucleus (see e.g. Siemiginowska et al. 2012). The
usual 500
-radius source region was used, but the background
was extracted from a nearby 1000
-radius circle, rather than
an annulus, in order to avoid contamination. Furthermore,
Chandra observation 1 has low quality, forcing us to use 5
cts/bin, and fit with C-statistic. The table shows therefore
total Stat. instead of χ2
. The XMM-Newton emission was
extracted as usual (avoiding the jet emission), but the larger
region (needed to include the XMM-Newton PSF) resulted
in including a larger fraction of hot gas. An additional con-
stant was used to weight the normalization of apec, but
both Chandra and XMM-Newton data were compatible
with having the same exact kT. A second XMM-Newton
observation exists (Obs. ID: 0504120201) which was not
used, at it fell on the same day as the used XMM-Newton
observation (Obs. ID: 0504120101) and was much shorter
(see e.g. Sobolewska et al. 2012). All emission at >2 keV
originates in the nucleus, therefore the NuSTAR data is
not affected by the jet presence.
Even though the cross-normalization constants are com-
patible with 1 within errors, forcing them all to stay equal
to 1 resulted in meaningful shifts in NH,los. Therefore, we
opted to leave the necessary ones free to vary in this case.
els, which are in good agreement. We note that Chandra
observations 2−5 took place within ∼1 week, which likely
explains the lack of flux/NH,los variability among those ob-
servations. While it is clear from the χ2
red comparison that
the data requires some form of variability (T > 20σ), nei-
ther intrinsic flux nor NH,los variability is preferred over the
other. The one exception to this is perhaps borus02, which
shows a tension of > 3σ between model and data when no
NH,los variability is allowed. This is likely due to the high
obscuration the model predicts for the XMM-Newton ob-
servation. In any case, the tension is not significant enough,
and we classify this source as ‘Non-variable in NH,los’.
Data reduction/fitting: The Chandra data was ex-
tracted using a circle of radius 1000
(background region, an-
nulus 11−2000
) to include all the extended emission (thus,
making the comparison with the XMM-Newton data eas-
ier). An additional NuSTAR observation exists that was
not public at the moment this analysis took place.
els, although they are not in strong agreement: MYTorus
favors a low-NH,av scenario, while borus02 favors a high-
NH,av one. Both models are able to find an equivalent sce-
nario to the best fit of the other, although with worse
statistics (χ2
red=1.14 for a MYTorus configuration with high
NH,av, and χ2
red=1.09 for a borus02 one with low NH,av).
Our borus02 best-fit is consistent with the results of Zhao
et al. (2021).
The models show significant disagreement in the best-fit
values of NH,los, probably arising from different disentan-
glements of the degeneracy with Γ and NH,av. borus02
and UXCLUMPY show the best agreement, although the
NuSTAR observation is significantly more obscured in the
UXCLUMPY best fit. MYTorus, on the other hand, generally
prefers higher obscuration. However, the NuSTAR observa-
tion is compatible with the borus02 determination. Over-
all, this results in UXCLUMPY painting a much more variable
picture of the source. In any case, all models agree that the
source is indeed ‘NH,los variable’, and we thus classify it as
such.
Data reduction/fitting: Chandra observations with Obs.
ID 9276, 9277 and 2983 were not considered because they
used HETG/LETG grating. This galaxy has a prominent
extended emission, likely the result of star formation. We
used a 1200
-radius region (background annulus at radii
20−3000
) to include it all in the analysis of Chandra data.
The brightness and closeness of this galaxy results in great
data quality, and therefore more substructure is appreci-
ated in the soft emission. We used a two-apec model to
describe it.
Note that the third XMM-Newton and the second
NuSTAR observations took place simultaneously. Another
XMM-Newton observation (Obs. ID: 0110930301) was not
included, as it was completely affected by flares.
Analysis of results: The best-fit of all models to the
data shows significant tension (T ∼20σ). This may be a re-
sult of the large number of counts available for this source,
compared to that of the rest of the sample. It may be that
our model is too simple to adequately fit it. However, no
obvious problem is seen in the fit residuals that may point
toward any specific issues. This source is likely a good can-
didate to implement a more complex treatment of the reflec-
tion component, such as the scenarios mentioned in Sect.
6.
Despite the poorer fit, the models show remarkable
agreement, particularly in the NH,los determinations. The
largest discrepancy is in the photon index obtained by
UXCLUMPY, which is largely incompatible with those of

borus02 and MYTorus. The values of θobs obtained
via UXCLUMPY and borus02 are also incompatible, with
UXCLUMPY favoring an edge-on scenario, while borus02
suggests a much more inclined viewing angle. Our borus02
results are mostly in agreement with those of Zhao et al.
(2021), although they obtain much higher NH,av, on the
order of 1024
cm−2
.
Even if the fit to the data might be improved by using
more complex models, it is clear that allowing both intrin-
sic flux and NH,los variability significantly improves the fit.
Taking this into account, as well as the derived p-values,
we classify this source as ‘NH,los variable’.
Appendix C.9: IC 4518 A
Data reduction/fitting: For the second XMM-Newton
observation, MOS2 was not used as it was corrupted.
Analysis of results: The data is well-fitted by
MYTorus and borus02, with UXCLUMPY showing poorer
statistics. This may be a result of the strong reflection seem-
ingly needed to fit the data. In fact, this is the only source
in our sample that requires the addition of an inner, CT re-
flection ring in UXCLUMPY. This component was introduced
into the UXCLUMPY model precisely because of difficulty fit-
ting sources with strong reflection with only a cloud distri-
bution (see Buchner et al. 2019). MYTorus and borus02
also yield large values of NH,av, which agrees with this in-
terpretation. This scenario is remarkably similar to that
described in Pizzetti et al. (2022).
The results obtained from our best fit are consistent
with those of Zhao et al. (2021), although we obtain higher
values for NH,av (∼ 2 × 1024
cm−2
in the mentioned work).
While both the χ2
red comparison for all models and the
p-value obtained for UXCLUMPY suggest the need for NH,los
variability, the p-values for MYTorus and borus02 remain
above the threshold. Therefore, we classify this source as
‘Undetermined’.
Data reduction/fitting: We used an extraction region of
700
for Chandra, as some extended emission is present. The
background was taken from an annulus, of radii 10−2000
.
The source spectra shows a prominent excess at around 2
keV that is best-fit with a second, very hot apec compo-
nent. It is not obvious whether star-formation, or perhaps
the presence of a jet, could result in such very hot gas.
Torres-Albà et al. (2018) used the two-apec model to ex-
plain the soft emisson of a large sample of U/LIRGs, and
obtained a T2 distribution of median 0.97±0.18 keV, with
a long tail extending up to 4.5 keV. However, this galaxy is
not classified as a U/LIRG, nor does it show obvious mor-
phological signs of a merger (that could explain the dense
star formation required). The detection of radio emission
points toward the presence of a jet, as does the slightly
elongated Chandra morphology. However, it is not obvious
if the jet presence could justify the addition of the second
apec component, from a physical point of view. We still opt
to use it in the model, given how it is required to explain
the data.
els, although MYTorus requires unusually large reflection
constants (As90 and As0). It also results in a larger Γ than
the other models. Furthermore, MYTorus and borus02
are barely in agreement in their NH,los determinations,
while UXCLUMPY results in systematically lower values (in-
compatible with the other models in 3/5 observations). The
most remarkable difference is in the NuSTAR observation,
in which UXCLUMPY models the observed flux with lower
obscuration than the other models, and compensates this
with a lower intrinsic flux value. Precisely because of this,
UXCLUMPY is the only model that classifies the source as
‘NH,los variable’, according to the p-value. However, the
χ2
red comparison shows that, even for UXCLUMPY, an alter-
native fit exists when imposing no NH,los variability, with
T < 3σ. Therefore, we opt to classify this source as ‘Non-
variable in NH,los’.
Our borus02 results are in good agreement with those
of Zhao et al. (2021), with the exception of the NH,av, for
which they obtain a much higher value of 1024
cm−2
.
Data reduction/fitting: We used an annulus of radii
10−2000
to extract the Chandra background, in order to
avoid a nearby source. Similarly, we used a circular source
extraction region of only 1500
for XMM-Newton, to avoid
both extreme soft excesses and CCD lines present around
the source. No source was detected in XMM-Newton Obs.
ID 0021140401, and therefore it is not used in this analysis.
A double-apec model was used to fit the soft emission
of this galaxy, since it is part of a closely-interacting system,
which is known to increase star forming activity.
Analysis of results: The data is well-fitted by all
models. However, UXCLUMPY yields significantly different
values for NH,los for the NuSTAR observations. Similarly
to the case of 3C 445, it models the NuSTAR observed
flux by using both lower NH,los and lower intrinsic flux
values. This scenario is more similar to the best-fit Zhao
et al. (2021) found for the source using borus02. They
detected no significant NH,los variability between Chandra
and NuSTAR, while needing a much lower intrinsic flux
for the NuSTAR observation. We recovered this solution
with MYTorus and borus02, with worse statistics. Inter-
estingly, the Zhao et al. (2021)/UXCLUMPY solution is sta-
tistically the best when not accounting for the soft X-ray
emission (for borus02 and MYTorus). However, this so-
lution always has NH,av at the maximum value allowed by
the models.
Despite the mentioned differences, all models agree that
NH,los variability is required to explain the data, although
this effect is larger for MYTorus and borus02. We thus
classify this source as ‘NH,los variable’.
Data reduction/fitting: We used an annulus of radii
12−2000
to extract the Chandra background, in order to
avoid a nearby source. 3C 452 also shows diffuse, soft, (very)
extended emission, which is coming from a jet (see Isobe
et al. 2002). Given how the extraction region used by Chan-
dra is smaller than that of NuSTAR and XMM-Newton,
when including the jet emission it is necessary to use dif-
ferent jet normalization (i.e. the variation of the parameter
normjet does not imply that the jet is varying in flux). This

source did not require any cross-normalization for the AGN
emission, with the exception of that associated to the jet.
els, even if they are not in perfect agreement. borus02
yields a significantly smaller Γ value, and the determina-
tions of θObs by UXCLUMPY and borus02 are incompatible
within errors. borus02 favors an edge-on scenario, while
UXCLUMPY favors a face-on one, although with very large
errors. Additionally, UXCLUMPY results in a much harder
spectrum for the jet emission, when compared to MYTorus
and borus02. Our results for borus02 are compatible
with those obtained by Zhao et al. (2021), with the excep-
tion of θObs, which in their case results in a face-on scenario.
Additionally, Zhao et al. (2021) introduce some AGN flux
variability, which in our case is modeled via changes in the
normalization of jet flux.
All models agree that NH,los variability is required to
explain the data, but UXCLUMPY yields smaller values for
all observations. We thus classify this source as ‘NH,los vari-
able’.

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