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Atmos. Meas. Tech., 17, 1545–1559, 2024
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Absorption of volatile organic compounds (VOCs) by polymer
tubing: implications for indoor air and use as a simple
gas-phase volatility separation technique
Melissa A. Morris1, Demetrios Pagonis1,a, Douglas A. Day1, Joost A. de Gouw1, Paul J. Ziemann1, and
Jose L. Jimenez1
1Department of Chemistry and Cooperative Institute for Research in Environmental Sciences (CIRES),
University of Colorado Boulder, Boulder, CO 80303, USA
anow at: Department of Chemistry and Biochemistry, Weber State University, Ogden, UT 84408, USA
Correspondence: Jose L. Jimenez (jose.jimenez@colorado.edu)
Received: 8 June 2023 – Discussion started: 18 September 2023
Revised: 1 February 2024 – Accepted: 1 February 2024 – Published: 12 March 2024
Abstract. Previous studies have demonstrated volatility-
dependent absorption of gas-phase volatile organic com-
pounds (VOCs) to Teflon and other polymers. Polymer–VOC
interactions are relevant for atmospheric chemistry sampling,
as gas–wall partitioning in polymer tubing can cause delays
and biases during measurements. They are also relevant to
the study of indoor chemistry, where polymer-based materi-
als are abundant (e.g., carpets and paints). In this work, we
quantify the absorptive capacities of multiple tubing mate-
rials, including four nonconductive polymers (important for
gas sampling and indoor air quality), four electrically con-
ductive polymers and two commercial steel coatings (for gas
and particle sampling). We compare their performance to
previously characterized materials. To quantify the absorp-
tive capacities, we expose the tubing to a series of ketones
in the volatility range 104–109µg m−3and monitor trans-
mission. For slow-diffusion polymers (e.g., perfluoroalkoxy
alkane (PFA) Teflon and nylon), absorption is limited to a
thin surface layer, and a single-layer absorption model can
fit the data well. For fast-diffusion polymers (e.g., polyethy-
lene and conductive silicone), a larger depth of the polymer is
available for diffusion, and a multilayer absorption model is
needed. The multilayer model allows fitting solid-phase dif-
fusion coefficients for different materials, which range from
4×10−9to 4 ×10−7cm2s−1. These diffusion coefficients
are ∼8 orders of magnitude larger than literature values for
fluorinated ethylene propylene (FEP) Teflon film. This enor-
mous difference explains the differences in VOC absorption
measured here. We fit an equivalent absorptive mass (CW,
µg m−3) for each absorptive material. We found PFA to be the
least absorptive, with CW∼105µg m−3, and conductive sili-
cone to be the most absorptive, with CW∼1013 µg m−3. PFA
transmits VOCs easily and intermediate-volatility species
(IVOCs) with quantifiable delays. In contrast, conductive
silicone tubing transmits only the most volatile VOCs, de-
nuding all lower-volatility species. Semi-volatile species
(SVOCs) are very difficult to sample quantitatively through
any tubing material. We demonstrate a system combining
several slow- and fast-diffusion tubing materials that can be
used to separate a mixture of VOCs into volatility classes.
New conductive silicone tubing contaminated the gas stream
with siloxanes, but this effect was reduced 10 000-fold for
aged tubing, while maintaining the same absorptive proper-
ties. SilcoNert (tested in this work) and Silonite (tested in
previous work) steel coatings showed gas transmission that
was almost as good as PFA, but since they undergo adsorp-
tion, their delay times may be humidity- and concentration-
dependent.
1 Introduction
It is well known that gas-phase volatile organic compounds
(VOCs) partition in and out of polymers by absorption.
Absorption and diffusion of organic species through poly-
mers has been studied since the 1940s (Crank and Henry,
Published by Copernicus Publications on behalf of the European Geosciences Union.
1546 M. A. Morris et al.: Polymer tubing for VOC separation by volatility
1949) due to practical applications such as polymer dye ef-
ficiency (Chantrey and Rattee, 1974) and permeation of aro-
mas through food packaging (Johansson and Leufven, 1997).
Polymers compose a large fraction of surfaces in indoor
environments, including painted surfaces, carpets and syn-
thetic fabrics. Manuja et al. (2019) measured total surface
area for 10 bedrooms, 9 kitchens and 3 office spaces in the
US. On average, the percent of surface area attributed to car-
pets and fabrics ranged from 2 % (kitchens) to 22 % (bed-
rooms). Paint was the largest contributor overall, averaging
40 % of total surface area across all room types (see Table S1
in the Supplement). VOCs found indoors are lost primar-
ily through ventilation and deposition and can be emitted
or re-emitted from polymers (Pagonis et al., 2019; Price et
al., 2019). Understanding the extent, dynamics and mecha-
nism for polymer absorption of VOCs is therefore important
for understanding and better quantifying the loss processes
for VOCs in indoor environments. Most past indoor studies
quantified the first-order deposition rate constant for VOCs
to a surface or film but did not discuss the absorption mech-
anism or diffusion into the bulk of the material. Algrim et
al. (2020) demonstrated the extremely high absorptive ca-
pacity of paint films, as VOCs diffused through the entire
thickness of the paint film in a matter of hours, making paint
a likely major sink and reservoir for VOCs in indoor environ-
ments. Won et al. (2000) found that synthetic carpets take up
large quantities of VOCs when concentrations are high and
re-emit VOCs when concentrations are low, acting as large
indoor reservoirs of VOCs. Synthetic carpets, therefore, are
expected to increase the indoor persistence of VOCs through
reversible partitioning. However, the partitioning of VOCs to
carpets has not been studied at a level of detail that may allow
predictive modeling, to our knowledge.
Polymer tubing is used extensively to sample air and gases
for studies of indoor air and outdoor atmospheric chemistry,
due to properties such as inertness, flexibility and low cost.
However, if the gas contains VOCs, interactions between
those compounds and the tubing walls can lead to delays and
detection biases. Several recent studies (Pagonis et al., 2017;
Deming et al., 2019; Liu et al., 2019) quantified the VOC ad-
sorptive properties of perfluoroalkoxy alkane Teflon (PFA),
fluorinated ethylene propylene Teflon (FEP) and other poly-
mer tubing. These studies grew from the literature on va-
por losses to Teflon walls of environmental chambers (Mat-
sunaga and Ziemann, 2010; Krechmer et al., 2016; Huang et
al., 2018). Absorption of VOCs by polymer tubing is chro-
matographic in nature, reversible, and independent of com-
pound concentration or humidity (Pagonis et al., 2017; Dem-
ing et al., 2019). Absorption varies strongly with the polymer
material, with, e.g., the same VOC species resulting in 1 min
of delay per 1 m of PFA for a given setup and 10 min of delay
per 1 m of polytetrafluoroethylene (PTFE) Teflon in the same
setup (Deming et al., 2019). Delays are also a strong func-
tion of saturation mass concentration (C∗, i.e., vapor pressure
in mass units) with a delay which is an order of magnitude
longer for an order-of-magnitude decrease in C∗or flow rate
(Pagonis et al., 2017).
A single-layer, one-dimensional, mass flow model was de-
veloped to describe VOC absorption by PFA and other less-
sorbing polymers, where diffusion into the bulk of the poly-
mer is assumed to be much slower compared to gas flow
down the length of the tubing (Pagonis et al., 2017). Us-
ing the model, experimental partitioning delays can be fit
to find an equivalent absorbing mass or absorptive capac-
ity of the tubing walls (CW, in µg m−3). For more absorp-
tive polymers, like paint, where diffusion into the bulk of the
polymer cannot be assumed to be much slower than gas flow
down the length of the tubing, a multilayer absorption model
was needed to capture the experimental features (Algrim et
al., 2020).
Non-polymer tubes (including metal and glass tubes) in-
duce longer partitioning delays than PFA. Unlike polymers,
the partitioning delays through metal and glass tubes depend
on competition for surface sites between the species sampled,
and thus concentration, humidity and exposure history affect
the transmission times (Deming et al., 2019).
Most previous studies of tubing–wall interactions thus far
have been aimed at increasing the accuracy of measurements,
by reducing and/or accounting for VOCs lost or delayed by
the sampling setup. However, this phenomenon may also
have some practical applications. For example, polymer tub-
ing was recently used to separate isomers and identify frag-
ments of the same species in a proton-transfer-reaction mass
spectrometry (Jenks et al., 2023). Additionally, the tubing
geometry provides major advantages over larger reactors,
chambers or rooms for studying material–VOC interactions.
Tubing studies have high experimental reproducibility due
to repeated opportunities for contact with the walls and the
decreased influence of convection and mixing compared to
larger spaces (Krechmer et al., 2016; Pagonis et al., 2017).
In this work, we experimentally characterize VOC absorp-
tion in polymer materials and commercial steel coatings and
compare our results with previous literature. The polymers
we test and model in this work are significantly more sorp-
tive than previously studied materials, and the application
and further development of a multilayer sorption model were
necessary to explain observations and determine their sorp-
tive capacities. A subset of these materials (nylon, polyester,
polypropylene and polyethylene) are highly relevant to in-
door air quality, as they are prevalent polymers that compose
synthetic carpet. We investigate both electrically conductive
and nonconductive polymer tubing, which are used for gas
and particle sampling and gas-only sampling, respectively.
Data are fit with the single and multilayer absorption models
to extract relevant parameters for each tubing material. Fi-
nally, we demonstrate how a given polymer tubing, charac-
terized by VOC absorption, can be used to selectively trans-
mit higher-volatility species (a “volatility high-pass filter”)
and how a combination of tubing materials can allow for the
characterization of VOC mixtures by volatility ranges.
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M. A. Morris et al.: Polymer tubing for VOC separation by volatility 1547
2 Methods
2.1 Measurements
2.1.1 Measurements of partitioning delays
To test polymer tubing for VOC sorption, we employ the
same methodology as previous studies (Pagonis et al., 2017;
Deming et al., 2019; Liu et al., 2019). A schematic of the
sampling setup is shown in Fig. 1a. In short, a large (either 20
or 7 m3) FEP chamber was used to provide a stable reservoir
of VOCs, and the tubing of interest was installed between the
chamber and the detector. In previous works (Matsunaga and
Ziemann, 2010; Liu et al., 2019), n-alkanes, 1-alkenes, 2-
alcohols, 2-ketones, hydroxynitrates, dihydroxynitrates and
dihydroxycarbonyls were tested for absorption in Teflon tub-
ing. The relative trend in absorption was well described by
the vapor pressure estimates of these compounds, with an
apparent activity coefficient effect for more polar compounds
(Krechmer et al., 2016; Liu et al., 2019; Huang et al., 2018).
Since polarity and functional group effects were reasonably
understood from previous works, we decided to use a series
of 2-ketones to test the materials in this study. Measurements
of C6–C12 2-ketones through seven different tubing materi-
als were conducted; the relevant details for the compounds
and materials are listed in Table S2. The chamber contained
approximately 20 ppb of each ketone. This was prepared by
injecting known amounts of liquid ketones into a sealed glass
bulb, attaching the bulb to the chamber with a flow of ni-
trogen (∼5 L min−1), and gently heating the outside of the
bulb to evaporate and transfer the ketones. The chamber was
left to equilibrate for at least 30 min prior to experiments
so that gas–wall partitioning was complete (Matsunaga and
Ziemann, 2010; Krechmer et al., 2016). A Vocus proton-
transfer-reaction mass spectrometer (Vocus PTRMS, here-
after referred to as “Vocus”) (Krechmer et al., 2018) was used
to monitor ketone concentrations at 1 Hz time resolution. The
Vocus was connected to the chamber using short (<1 m) PFA
lines and fittings. Flow from the chamber to the Vocus was
controlled using a critical orifice to 2 L min−1. The tubing
materials were tested for VOC absorption by installing them
one at a time between the PFA lines in the sample path. With
the tubing of interest installed, first the chamber was sam-
pled for up to an hour or until concentrations plateaued, and
then room air was sampled until the concentrations returned
to levels that were similar to instrument backgrounds.
We define the partitioning delay time as the time it takes to
depassivate to 10 % of the maximum concentration, as was
done in previous studies (Pagonis et al., 2017; Deming et
al., 2019; Liu et al., 2019). The instrument and the short PFA
lines caused short partitioning delays, which were subtracted
from the total delay time, to quantify just the delay time asso-
ciated with the tubing being tested. Delay times for the setup
were on the order of 0.01–1 min m−1and were significantly
smaller than for the polymers studied, except for nylon, con-
Figure 1. Schematics for the two sampling setups used in this study.
(a) Setup for testing the absorptive capacity of one polymer tub-
ing material at a time. (b) Schematic of the gas volatility separator
(GVS). In both cases, VOCs are injected into a large FEP chamber,
allowed to equilibrate and then sampled through the polymer tub-
ing with a Vocus proton-transfer-reaction mass spectrometer. Solid
black lines represent PFA tubing; all unions and valves were also
made of PFA.
ductive PFA and conductive PTFE. Given the time resolution
of the system, the shortest quantifiable delays were of ∼1 s.
For longer desorption periods, the time series were fit with
a single exponential between 5 % and 15 % of the maximum
concentration, and the 10 % time was calculated using the
fit, reducing the effect of noise. For the few desorption pe-
riods that were very long (∼hours) and did not reach 10 %
of the maximum concentration during the absorption period,
the desorption periods were fit with double exponentials, and
the delay times were extrapolated out to the 10 % concentra-
tion. The extrapolated delay times are consistent with trends
measured in lower-capacity materials. All final tubing delay
times were normalized by dividing by the tubing length.
2.1.2 Measurements of partitioning delays with the gas
volatility separator
The gas volatility separator (GVS) is a multi-tube autosam-
pler. A schematic is shown in Fig. 1b. The GVS is designed
to flow a sample gas stream through multiple tubing mate-
rials simultaneously to separate VOCs of different volatility
ranges. In the design used here, a common inlet is split into
four flow paths, each containing one tubing material. Up-
stream of each inlet tube is an automated PTFE three-way
solenoid valve (Cole-Parmer, part no. EW-01540-18), which
allows each tube to ingest either a sample gas stream or clean
air. Downstream of each tubing material, another automated
PTFE three-way solenoid valve directs the flow to either the
common sampling outlet or a vacuum pump exhaust (with
critical orifices to match sampling flow rates). This configu-
ration ensures that the VOC analytes enter all tubing materi-
als at a constant flow rate, regardless of which inlet path is
being sampled by the Vocus. The valves are wired to a solid-
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1548 M. A. Morris et al.: Polymer tubing for VOC separation by volatility
state relay board and are operated by the control and acquisi-
tion software (MICAS, Original Code Consulting, Boulder,
CO) within LabVIEW. Figure S1 in the Supplement shows
the custom user interface. The user can manually switch
which tubing material stream is sent to the outlet or set up a
software sequence to cycle through all of the materials with a
set dwell time for each. The GVS can switch between tubing
materials as fast as every 30 s, but we found that switching
tubing materials every 3 min gives more interpretable results
with the tube lengths used in this study, as time is required
for the PFA lines (after the outflows of all the tubing ma-
terials join at the same point) to repassivate after switching.
The common outlet can be sampled by an instrument directly.
The whole system is mounted on a custom aluminum rack
(80/20, https://8020.net/, last access: 7 June 2023) so that
it can be easily transported for field studies. Photos of this
system are shown in Fig. S2. For this work, the inlet of the
GVS was connected to a chamber containing 2-ketones as in
Sect. 2.1, and the outlet was connected to the Vocus, using a
4 m PFA line. The four tubing materials installed for the tests
described here were PFA, polypropylene, polyethylene and
conductive silicone (lengths of 1.2–4.5 m; see Table S2).
2.2 Modeling
2.2.1 Single-layer model for slow-diffusion materials
A single-layer absorption numerical model developed and
published by Pagonis et al. (2017) (freely available at Morris
et al., 2024) was used to quantify the absorptive capacities of
slow-diffusion polymers and to provide a rough estimate of
those of fast-diffusion polymers. A detailed description of the
model is available in that publication (Pagonis et al., 2017).
In short, the model is a linear kinetic chromatography model
that calculates gas-to-wall partitioning, as compounds move
down the length of the tube with the gas flow, according to
Eq. (1):
FW=1
1+C∗
CW
,(1)
where FWis the fraction of compound in the tubing wall at
equilibrium; C∗(µg m−3) is the saturation vapor pressure of
the compound; and CW(µg m−3) is the equivalent absorbing
mass, or absorptive capacity, of the tubing material per unit
volume of air in the tube. Values for C∗were estimated us-
ing the SIMPOL.1 group contribution method (Pankow and
Asher, 2008). Molar mass of the partitioning phase (polymer)
is assumed to be 250 g mol−1, with an activity coefficient of
1. This molar mass is typical of organic compounds in at-
mospheric aerosol particles, where activity coefficients are
usually assumed to be 1, and is used in place of the poly-
mer molecular weights, which are typically unknown (Al-
grim et al., 2020). The gas-phase diffusion coefficient used
for all ketones was 0.067 cm2s−1, which was estimated for
dodecanone (Tucker and Nelken, 1982). This value was not
changed for each individual ketone, as it has little effect on
the delay time (Pagonis et al., 2017). The model assumes dif-
fusion into the bulk of the tubing material is very slow, so ab-
sorption occurs in a thin, homogeneous, near-surface layer.
For example, for PFA tubing the thickness of that layer is es-
timated to be about 2.2 nm (Krechmer et al., 2016; Pagonis
et al., 2017). The model output is a time series of compound
concentration exiting the tube, which can be compared to ex-
perimental data.
We fit a CWvalue to each slow-diffusion material by min-
imizing the sum of the squared residual between the experi-
mental time series and modeled time series for all ketones si-
multaneously. For fast-diffusion materials, we employed the
method of Pagonis et al. (2017) and Deming et al. (2019):
experimental delays for all ketones were plotted in log–log
space as a function of C∗(as shown in Fig. 5), the model was
run with a range of CWvalues, modeled delays as a function
of C∗were calculated and the CWvalue that provided delays
closest to the experimental ones (based on an orthogonal dis-
tance regression) was chosen.
2.2.2 Multilayer model for fast-diffusion materials
A multilayer absorption–diffusion numerical model was de-
veloped on top of the single-layer model to simulate absorp-
tion of VOCs by thick (a few hundred µm) paint films (Al-
grim et al., 2020). In short, the model shares the same gas
flow and gas–wall partitioning framework as the single-layer
model but also includes diffusion of the compounds into the
bulk of the polymer, according to Fick’s second law of diffu-
sion:
∂ C(x , t)
∂t =Df
∂2C
∂x2,(2)
where Dfis the solid-phase diffusion coefficient and C(x, t )
is the concentration at depth xand time t. The equation is
used in Cartesian (instead of cylindrical) coordinates, since
the diffusion depth is small compared to the tubing diam-
eter (<10 % and much less for most materials) and given
other uncertainties in the model. Equation (2) is incorporated
in the model as a finite-difference approximation with the
same Euler time step as the gas–surface layer partitioning
calculation. Each layer in the multilayer model is 2 µm thick,
and the number of layers simulated depends on the expected
partitioning depth calculated from the input diffusion coeffi-
cient and run time. The model simulates enough layers to en-
sure that diffusion is not artificially halted but does not sim-
ulate the entire thickness of the wall to prevent very long run
times. When run without diffusion into the bulk, the multi-
layer model collapses onto the single-layer model. As in the
previous case, the model output is a time series that can be
compared to experimental data.
Changes were made to the Algrim multilayer model for
use in this work. The Algrim multilayer model fits a VOC-
paint system with three parameters: a solid-phase diffusion
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M. A. Morris et al.: Polymer tubing for VOC separation by volatility 1549
coefficient (Df, cm2s−1), a surface roughness factor (R, unit-
less) and an absorptive capacity (CW, µg m−3). The surface
roughness factor scales the surface absorption rate coeffi-
cient, to simulate turbulence at the gas–polymer interface,
and allows the amount of surface layer absorption at short
times to be adjusted. The updated model fits a VOC–polymer
system with a solid-phase diffusion coefficient (Df, cm2s−1),
a surface roughness factor (R, unitless) and a mass fraction
availability parameter (γ, unitless). Instead of fitting CW, the
updated model calculates CWbased on the modeled parti-
tioning depth (which is a function of Df) and the density
of the polymer. The mass fraction availability parameter is
a new fitting parameter that scales the now-calculated CW
value by the fraction of the polymer mass available for gas–
wall partitioning. Without γ, the model could not reproduce
the experimental time series; consistent overestimation of ab-
sorption occurred when it was assumed that all the mass in
the surface layer of the polymer was available for partition-
ing. The mass fraction parameter is mathematically equiva-
lent to the inverse of an activity coefficient (resulting from
the chemical interaction between the absorbing species and
the polymer). The same result could be obtained by using a
larger value for the polymer molecular weight (vs. the con-
stant value of 250 gmol−1used here). For example, γ=0.03
is mathematically equivalent to an effective polymer molec-
ular weight of ∼8000 g mol−1, which is physically plausi-
ble. A possible physical interpretation is that larger polymer
chains, potentially with more cross-linking, may leave less
space for the absorbing species to occupy. Figure S3 com-
pares the fit values for γfrom this work with activity coeffi-
cients from the literature. From the currently available data it
remains unclear whether this effect is the result of chemical
activity, physical exclusion or some combination of the two.
This topic should be explored further in future studies.
The multilayer model fits three parameters (Df,R,γ ) for
each ketone–polymer system. Dfwas allowed to vary with
each ketone, but Rand γwere held constant for each poly-
mer, as they are more empirically related to the material than
to individual VOCs. To do this, we carried out a brute-force
method to fit the three parameters. The model was automated
to run with every combination of input parameters and then
calculate the sum of the squared residual between the ex-
perimental and modeled time series. This created a three-
dimensional cube of fit errors, which was manually evalu-
ated for each ketone and also across ketones. This process
was done iteratively at an increasingly fine scale until we
converged on a set of parameters that best modeled all the
ketone time series for a given polymer. Calculated CWvalues
were averaged across ketones after fitting. Often, the smaller
ketones were less sensitive to changes in the Rand γvalues
than the larger ones, so it was useful to start by fitting the
time series of the larger ketones and then fit the smaller ones
and then iterate.
3 Results and discussion
3.1 Characterizing tubes as either fast- or
slow-diffusion polymers
3.1.1 Experimental time series
Figure 2 shows the experimental time series of C6–C14 ke-
tones sampled through several different tubing materials. If
the tubing had not absorbed any VOCs, these traces would
be square waves; instead they show partitioning delays ac-
cording to the volatility of the compounds and the absorp-
tive capacity of the material. Figure S4 shows a simplified
version of the ketone transmission through these polymers
using a “stoplight” categorization. While materials like PFA
and nylon transmitted the ketones with measurable delays,
polypropylene and polyethylene demonstrated continued ab-
sorption over the 20 min sampling period, and the C14 ketone
was lost to the walls in both tubes (C12 and C13 were also lost
to the walls of the polyethylene tube).
3.1.2 Fitting absorptive capacities and diffusion
coefficients
The single-layer model was used to fit all of the materials
with an absorptive capacity. The single-layer model can re-
produce time series through slow-diffusion materials very
well. While the single-layer model can reproduce partition-
ing delays as large as those seen through the fast-diffusion
materials, when the modeled time series and experimental
time series are compared, it is clear that the single-layer
model is not capturing the true behavior of the absorption.
In Fig. 3a and b, the modeled and experimental time se-
ries for nylon agree fairly well, and the multilayer model
is not necessary. In Fig. 3c and d, the single-layer model
matches the experimental partitioning desorption delay time
for polypropylene but does not capture the continued absorp-
tion seen in the time series, so the multilayer model is neces-
sary. The multilayer model was able to reproduce time series
through fast-diffusion materials fairly well. Figure S5 shows
the final model fits compared to the experimental time series
for all ketone–polymer systems. We defined the normalized
fit error as follows:
normalized error =XCmodel(t) −Cexperimental (t)2/n , (3)
where Cexperimental(t ) is the concentration (normalized to the
chamber value) at time t,Cmodel(t ) is the normalized concen-
tration predicted by the model at time tand nis the number
of data points. Any materials that had a normalized fit error
larger than 0.01 with the single-layer model (SLM) showed
significant deviations from the experimental data in the time
series. They were deemed fast-diffusion polymers and were
modeled with the multilayer model (MLM) instead. A list of
normalized fit errors is included in Table S4. Table 1 summa-
rizes all tubes as fast-diffusion, slow-diffusion or adsorptive
materials.
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1550 M. A. Morris et al.: Polymer tubing for VOC separation by volatility
Figure 2. Time series for 2-ketones of different carbon numbers through a variety of tubing materials. In the absence of tubing absorption,
these time series would be square waves. Interactions between the tubing wall and the ketones cause partitioning delays. Materials are ordered
from least to most absorptive: PFA (5.8 m length), nylon (1.5 m), polyester (1.8 m), polypropylene (4.6m) and polyethylene (2.5 m). The C13
and C14 traces were smoothed by ∼5 s to reduce noise.
Figure 3. Model runs with the single-layer model (SLM) and multilayer model (MLM), evaluated against the experimental time series
of ketones through two materials. (a, b) For a slow-diffusion polymer like nylon, the single-layer model is adequate for fitting, although
not perfect (see text). (c, d) For a fast-diffusion polymer like polypropylene, the multilayer model is required, as the single-layer model
performs poorly. The lack of symmetry in the experimental absorption and desorption periods (for both types of polymers) is discussed
below (Sect. 3.1.3).
A summary of the fit parameters and calculated partition-
ing depths is given in Table 2, and more details are included
in Table S3. Since CWis dependent on the geometry of the
tubing, we included dimensions in Table S2 so that CWval-
ues fit here can be scaled for other surface-to-volume ratios
(Pagonis et al., 2017). Table 2 also includes an estimated par-
titioning depth for each of the materials. To estimate the par-
titioning depths for slow-diffusion polymers, we employ the
method of Krechmer et al. (2016), where CWand polymer
density are used to estimate partitioning depth. To estimate
the partitioning depths for fast-diffusion polymers, we em-
ploy Eq. (6) from Algrim et al. (2020), which uses the diffu-
sion coefficient and timescale to estimate partitioning depth.
Figure S6 shows good agreement between estimated parti-
tioning depths and multilayer model simulations; details are
in the caption.
Unlike the single-layer model, the multilayer model fits
a diffusion coefficient for each VOC in each tubing mate-
rial, in addition to the absorptive capacity. Figure 4 compares
the fit diffusion coefficients in this work to literature values
for other polymers. Our fit values are consistent with litera-
ture values for polymers that are not FEP. The Dfestimates
for FEP included in Fig. 4 are 8 orders of magnitude lower
than for the other polymers and show a similar C∗depen-
dence at the higher C∗values. This enormous difference in
diffusion coefficients is consistent with how we can easily
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M. A. Morris et al.: Polymer tubing for VOC separation by volatility 1551
Table 1. Categorization of polymer-containing materials tested in this study and in other literaturea,b.
Diffusion regime Used for gas transmission Used for gas and particle transmission
Slow-diffusion PFA, PTFE, nylon, FEPa, PEEKacPFA, cPTFE
Fast-diffusion Polypropylene, polyethylene cSI, cPUN
Adsorption only SilcoNert, Dursan, Siloniteb
aDeming et al. (2019). bLiu et al. (2019).
Table 2. Fitted model parameters for absorption of 2-ketones in polymer tubing materials from this study and the literature.
Tubing material Average mass log10 diff. Mass fraction Surface Estimated diffusion
absorptivity, coeff. for availability roughness depth at 20 min
CWC6ketone parameter parameter for C6ketone
(µg m−3) (cm2s−1) (unitless) (unitless) (µm)
Perfluoroalkoxy alkane∗8.0×105– – – 0.0018
cPFA∗1.3×106– – – 0.0029
Fluorinated ethylene propylene∗2.0×106– – – 0.0043
Polyether ether ketone∗8.0×106– – – 0.023
Polytetrafluoroethylene∗1.2×107– – – 0.026
cPTFE∗1.6×107– – – 0.035
Polyester 2.4×107– – 1.3 0.11
cPFA (cond. perfluoroalkoxy alkane) 2.5×107– – 1 0.055
Nylon 3.5×107– – 1.4 0.098
cPTFE (cond. polytetrafluoroethylene) 9.3×107– – 1 0.20
Polypropylene 3.0×1010 −7.4 0.02 2.9 110
Polyethylene 3.0×1011 −6.4 0.03 2.75 340
cSI (conductive silicone) 6.9×1013 −6.5 1 9.2 310
∗Results for CWfrom Deming et al. (2019). Depths calculated here from CWresults.
categorize materials as either slow-diffusion or fast-diffusion
polymers. Notably, FEP tubing is often used as a permeation
tube for VOCs. Due to its slow-diffusion properties, VOCs
will permeate its walls at a steady rate over the course of sev-
eral months. Our tests are performed over 10–90 min periods,
so VOC diffusion into slow-diffusion materials is effectively
confined to a very thin surface layer.
3.1.3 Modeling complexities of fast-diffusion materials
While the multilayer model was able to reproduce the ex-
perimental time series for fast-diffusion materials fairly well,
it was limited in its ability to capture the different absorp-
tion behavior shown by these materials. The desorption of
the fast-diffusion materials proceeded at a changing rate, ini-
tially being faster than the corresponding absorption rate and
later being slower than the corresponding absorption rate (as
shown in Fig. S7). This meant that, early in the absorption
period, compounds diffused out of the polymer faster than
they went in and later in the absorption period, compounds
diffused out of the polymer slower than they went in. The be-
havior at later times is expected; to enter the polymer, com-
pounds just partition to the surface, but to exit the polymer,
compounds must diffuse back to the surface before reparti-
tioning into the gas phase, therefore taking longer to exit than
to enter. The behavior early in the absorption period was a
surprise. However, this anomaly has been published in poly-
mer absorption literature from the 1950s and remains a com-
plex phenomenon, with factors like non-Fickian solid-phase
diffusion coefficients, polymer relaxation, and rearrangement
rates or changing surface concentrations cited as possible ex-
planations (Crank, 1951; Crank and Park, 1951). We noticed
this anomaly in our data while modeling. When the model
was asked to optimize the fit parameters to just the absorp-
tion period of the data, the resulting desorption period had
high model error (as shown in Fig. S8). The inverse was
true when the model was asked to optimize the fit parame-
ters to just the desorption period. When the model was asked
to optimize the fit parameters to the whole time series, they
fell in between the absorption-only and desorption-only fit
parameters and provided an adequate but not perfect fit to
both periods. We tried to account for this anomaly by mod-
eling a depth dependence and a concentration dependence
for the solid-phase diffusion coefficient, but none of the at-
tempted dependences recreated the experimental time series
better than the original model. At the expense of an improved
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1552 M. A. Morris et al.: Polymer tubing for VOC separation by volatility
Figure 4. Log–log plot of diffusion coefficients of VOCs in poly-
mers against VOC saturation mass concentration values (estimated
using SIMPOL.1 for 298 K). Data from this study are plotted along-
side literature values with consistent results. Of note is the ∼8 or-
ders of magnitude difference between diffusion coefficients for the
fast-diffusion polymers and FEP.
fit, we opted to keep the model simple as it fits the data fairly
well and so that it can remain applicable with good accuracy
to the wide range of materials found in indoor environments
and sampling tubes.
3.2 Summary of materials for gas transmission and
separation
The time it took each ketone to return to 10 % of the max-
imum concentration is shown for each material in Fig. 5.
As expected from prior literature results, the delays caused
by partitioning for a given tubing material increase with de-
creasing saturation vapor pressure. The relative trend is very
similar for different materials, despite a difference of several
orders of magnitude in response times. PFA continues to be
the best tubing material for fast gas transmission. One inter-
esting material to note is nylon, which has very short delay
times, similar to those of PFA. While nylon is able to trans-
mit the 2-ketones very quickly, it is not an inert material like
PFA and thus is less suitable for general-purpose sampling.
Due to the basic amide in its monomer unit, nylon wool is
highly efficient at scrubbing acids from a gas stream (Huey
et al., 1998).
The desorption delay times are used to create Fig. 5, in-
stead of the absorption delay times, because the fast-diffusion
materials plateaued at different concentrations depending
on their absorptive capacities. It is worth noting that for
slow-diffusion materials, the absorption and desorption de-
lay times are not identical; often, the absorption delay times
are larger than the desorption times (Fig. S9a and b). There
was also more run-to-run variability in the absorption times
than desorption times (see Fig. S9c). Using the desorption
delay times to summarize this work does not affect the fit
values because the entire time series are used for fitting.
There are some differences between the values of CWde-
termined in our experiments and those of previous studies.
Deming et al. (2019) report CWvalues about an order of
magnitude smaller than those determined here. The Deming
et al. (2019) experiments were conducted with a quadrupole
PTRMS that had a much longer response time than the Vo-
cus PTRMS used in our work. The quadrupole response time
was subtracted from the tubing time, and this procedure may
have introduced some inaccuracy in those results. The flow
rate was also ∼10 times lower in the Deming et al. (2019)
work, although that should not affect the results in principle.
Liu et al. (2019) report CWvalues much lower than expected
when extrapolated to the ketone volatility range. The main
reason for this difference is that CWhas been shown to de-
crease strongly as C∗decreases (Liu et al., 2019; Krechmer
et al., 2016; Huang et al., 2018). This effect is thought to
be due to increasing activity coefficients in nonpolar Teflon
for the more polar multifunctional species used by Liu et
al. (2019) compared to the less polar ketones used in our
work. We recommend that users of this method constrain the
CWvalues for their tubing by fitting their data with the mod-
els we provide.
3.3 Summary of materials for gas and particle
transmission and separation
3.3.1 Conductive polymers
In many applications, the transmission of both gases and
particles is critical. A substantial fraction of ambient parti-
cles are electrically charged. Those particles are lost very
quickly when sampled through nonconductive materials such
as PFA, as surface charges build up that attract the parti-
cles, leading to electrophoretic losses (McMurry and Rader,
1985). For this reason, particle sampling is often accom-
plished with metal tubes such as steel or copper. On the other
hand, sampling of gases with minimum perturbation of the
chemical composition requires inert polymer tubing such as
PFA because uncoated metal tubes can produce large and un-
predictable partitioning delays (Deming et al., 2019). Previ-
ous studies concluded that aluminum-foil-wrapped conduc-
tive PFA (cPFA) was the best known tubing for transmission
of both phases (Liu et al., 2019). Deming et al. (2019) tested
cPFA tubing for particle losses and found them to be compa-
rable to copper tubing. In this work, we did not come across
any tubing that performs better than aluminum-foil-wrapped
cPFA. However, there are multiple other conductive tubing
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M. A. Morris et al.: Polymer tubing for VOC separation by volatility 1553
Figure 5. Experimental partitioning delays in different tubing materials (measured at a flow rate of 1.86L min−1) vs. saturation mass
concentration for 2-ketones. On the left are polymer tubes used for sampling gases, and on the right are conductive polymer tubes and coated
metal tubes used for sampling gases and particles. Single-layer model results are shown as dashed lines, and multilayer model runs are
shown as solid lines (for the fast-diffusion polymers). The coated metal tubes were not modeled but fit linearly in log space with a slope that
matched the single-layer model runs of other materials to guide the eye for comparison. Nonconductive PFA is shown on both sides to aid
comparison, even though it does not transmit particles well. Data points with open markers indicate that delays may be smaller than the 1 s
measurement limitation. One data point from Deming et al. (2019) for Silonite™ tubing is shown for comparison; this data point was taken
at a flow rate of ∼0.3 L min−1, so it may be biased high. Deming et al. (2019) report Silonite™ tubing to be similar in delay times to PFA
when tested at the same flow rate. Additionally, one data point from Deming et al. (2019) for Nafion is included here for comparison, which
has been scaled for flow rate.
materials, which may be of interest for applications such as
volatility separation of gases.
In Fig. 6a, 2-ketones are sampled through several con-
ductive polymers: cPFA, conductive polytetrafluoroethylene
(cPTFE), conductive polyurethane (cPUN) and conductive
silicone (cSI), as well as nonconductive PFA. The cPFA and
cPTFE tubes gave similar, although slightly longer, delays
than nonconductive PFA, while the cPUN and cSI tubing de-
nuded the ketones majorly. The cSI tubing completely de-
nuded all but the two most volatile ketones, transmitting C6
and C8at ∼80 % and ∼30 % of their respective chamber
values after an hour of sampling. cSI has trouble transmit-
ting species with C∗<107µg m−3.
Since cPUN and cSI appeared potentially useful for de-
nuding gases according to volatility, we investigated the re-
lease of impurities from these materials. It has been previ-
ously reported (Timko et al., 2009; Yu et al., 2009; Asbach
et al., 2016) that conductive silicone tubing emits siloxanes,
particularly polydimethylsiloxane (PDMS). Figure 6b shows
the mass spectra of gas-phase emissions from cSI tubing
(new and >5-year-old pieces of tubing) and cPUN tubing
(new). The mass spectra confirm the presence of siloxanes
when sampling through cSI, as previously reported in the lit-
erature. To our knowledge, VOC emissions from cPUN tub-
ing have not been reported before, so suspected peaks are
labeled with mass-to-charge ratios. There is no significant
difference between the VOC absorption of the new and old
cSI tubing, indicating that age does not affect the absorp-
tive capacity of the tubing, consistent with previous results
for an FEP chamber (Matsunaga and Ziemann, 2010). How-
ever, contaminant emissions are significantly reduced with
age. Figure 6b demonstrates a decrease of a factor of 10 000
in emissions between the new and old cSI tubing. This sug-
gests the impact of siloxane contaminant emissions on mea-
surements using old cSI tubing may be significantly reduced
compared to new tubes. The emissions from cPUN tubing are
2 orders of magnitude lower than for cSI tubing but may still
cause significant interference in VOC measurements.
Figure 5 shows a summary of the partitioning delays
through all the materials in this study that can be used for
gas and particle transmission. Of note is how much more ab-
sorptive cSI tubing is than any other material we have tested,
causing partitioning delays that are 2–3 orders of magnitude
larger.
3.3.2 Stainless steel coatings
In addition to the polymer tubes discussed so far, three stain-
less steel tubes were tested for VOC partitioning delays,
one uncoated and two with commercial passivation coat-
ings (SilcoNert®and Dursan®from SilcoTek®, https://www.
silcotek.com/, last access: 6 July 2023). The time series when
sampling a step function of the ketone mixture through the
steel tubes is shown in Fig. 7. The coated tubes caused par-
titioning delays that were an order of magnitude larger than
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1554 M. A. Morris et al.: Polymer tubing for VOC separation by volatility
Figure 6. (a) Time series of 2-ketones sampled as step functions through different conductive tubing materials (cPFA, cPTFE, cPUN and
cSI) compared to standard nonconductive PFA. The C13 and C14 traces were smoothed by ∼5 s to reduce noise. (b) Vocus mass spectra of
the suspected emissions from new cSI tubing, >5-year-old cSI tubing and new cPUN tubing. Both old and new cSI tubing emit siloxanes
(labeled with elemental formulas from the literature); however, the new tubing emits ∼10 000 times more than the old tubing. The inset
graph shows the scale of emissions from the old tubing. The cPUN tubing emits VOCs at concentrations 2 orders of magnitude lower than
the new cSI tubing.
through PFA, with SilcoNert performing better than Dursan.
As discussed previously, VOC delays through metal tubes
are dependent on humidity, concentration and history. The
desorptions for these tubes were carried out with humid air
(∼40 % RH), while the ketone sampling was performed with
dry air. The desorption process can proceed faster than the
absorption process for an adsorptive material exposed to wa-
ter vapor, as water can outcompete less polar compounds
(like the ketones) for adsorptive sites. This effect is not ap-
parent for the SilcoNert coated tube, but it is clear for the
Dursan-coated tube and the bare stainless steel. The spike at
the beginning of the uncoated stainless steel tube is an artifact
of competitive adsorption and consistent with prior observa-
tions (Deming et al., 2019). In comparison, the PFA absorp-
tion and desorption timescales are unaffected by changes in
humidity (Deming et al., 2019).
The coated tubes were also tested for particle transmis-
sion. Ambient particles were pulled through the tubing to a
condensation particle counter, and there was no significant
difference between the particle transmission for the uncoated
steel tube and coated tubing, as shown in Fig. S10. Some
losses are apparent for all tubes compared to the room, and
they are tentatively attributed to the loss of ultrafine particles
(often observed in room air at this location) via diffusion to
the tubing walls. The partitioning delays through these mate-
rials are compared to those of conductive polymers in Fig. 5.
The absorption models were not used to fit the results from
these materials, as only adsorption of compounds to surface
sites plays a role for metal tubing (Deming et al., 2019).
One possible application of conductive commercial coat-
ings is to potentially increase gas transmission inside atmo-
spheric chemistry reactors. For example, oxidation flow re-
actors (OFRs) are typically built with chromate-coated alu-
minum interiors, which have been shown to cause significant
losses of gases via humidity-dependent adsorption (Deming
et al., 2019). In the Supplement, we compare gas and parti-
cle transmission through a chromate-coated aluminum OFR
with an OFR that had been coated with a commercial conduc-
tive PTFE-based coating and discuss when it may be useful
to use a coated one.
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M. A. Morris et al.: Polymer tubing for VOC separation by volatility 1555
Figure 7. Time series when sampling step functions of 2-ketones through cPFA tubing (149 cm) and three stainless steel tubes (61 cm).
One tube was coated with SilcoNert®2000, the second was coated with Dursan®and the third was left uncoated. The C13 and C14 ketone
traces for both panels were smoothed by ∼5 s to reduce noise. The sampled air from the chamber (periods with white background) was
dry (<1 %RH), while the room air sampled during desorption periods (blue background) contained ∼40 % relative humidity. Transmission
through metal tubes is typically affected by humidity as water competes for adsorption sites (Deming et al., 2019). The spike in the stainless
steel time series continues up to a value of 10.
3.4 Using the GVS for gas-phase separation
The gas volatility separator (GVS) was used to sample C4–
C16 ketones with four different polymer tubes. All four tubes
sampled the ketones continuously, but only the output of one
of the tubes was measured at a given time, which was alter-
nated every 60 s. An example time series for this experiment
is shown in Fig. 8a. The top of the graph indicates which tub-
ing is being sampled at a given time; the experiment starts
with sampling through PFA, which was the least absorptive
tubing, and then samples through polypropylene; polyethy-
lene; and finally cSI, which was the most absorptive tubing,
before cycling again to PFA. As time progresses, all the ke-
tone signals increase at different rates through each tube. The
system has a shared outlet (∼1.5 m PFA tube) that connects
to the mass spectrometer. When the inlet material is a highly
sorptive material like cSI, the shared outlet is partially depas-
sivated and then requires time to be passivated again when
the system switches to using PFA as the inlet material. This
is seen in the time series, as every time the inlet material is
PFA, there is a steeper transient in the concentrations of the
species. This effect can be minimized by sampling each tube
for a longer period of time (e.g., 3 min) and only recording
concentrations at the end of the 3 min period. This experi-
ment clearly demonstrates the large differences in transmis-
sion of VOCs between polymers. These results can be ex-
pressed as a fractional transmission vs. C∗for a given mate-
rial and sampling time. Figure 8b shows the fractional trans-
mission curves for the experiment in Fig. 8a after 10 min of
sampling.
Figure 8b shows the model–measurement comparison for
PFA and cSI, while Fig. S11 shows the rest of the polymers.
The PFA model runs were convolved with the Vocus instru-
ment response (Liu et al., 2019) to better represent the experi-
mental data. The model results compare well with the experi-
mental data, except for the higher-volatility ketones and PFA,
where experimental delays are larger than predicted. While
the three-way solenoid valves could not be incorporated in
the modeling runs, experiments showed that the solenoid
valve effects on gas transmission are undetectable for C12
and more volatile species and small for C13 and C14 ketones
(see Fig. S12).
Two modeled fraction transmission curves for PFA are
also shown, after 1 min and at 10 min of sampling, to il-
lustrate how these curves change with sampling time. Fig-
ure 8b makes clear that PFA transmits VOCs easily and
intermediate-volatility species (IVOCs) with quantifiable
delays. In contrast, conductive silicone tubing transmits
only the most volatile VOCs, denuding all lower-volatility
species. Semi-volatile species (SVOCs) are very difficult to
sample quantitatively through any tubing material we have
tested, since none perform better than PFA.
Analogous to gas chromatography, there are several ex-
perimental variables that affect the transmission curves, in-
cluding the C∗of the VOCs, the CWof the tubing material,
the length and diameter of the tubing, temperature, and flow
rate (Pagonis et al., 2017). Some of these can be adjusted
to optimize the setup for a particular sampling application.
Analysis of data from such experiments is complicated by
the time dependence of the transmission curves. However,
the single-layer and multilayer models can be used to model
different setups. A grid of delay times as a function of C∗of
the VOCs and CWof the transmitting material is shown in
Fig. S13, which can act as a guide for the separation of gases
using polymer tubes.
There are many applications where separation of gases by
volatility class with polymer tubing would be useful. One
demonstration was published by Jenks et al. (2023), who
use PFA tubing to identify parent–fragment ion relationships
in the time series of measurements from a chemical ioniza-
tion mass spectrometer, where otherwise two different reac-
tion products may have been assigned. This was achieved
by flowing reaction products from a 1-carene oxidation ex-
periment through a 50 m coil of PFA tubing and identifying
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1556 M. A. Morris et al.: Polymer tubing for VOC separation by volatility
Figure 8. (a) Time series of C4–C16 ketones through the gas volatility separator (GVS). The GVS inlet tubing was automatically switched
every minute, and the inlet tubing material is labeled above the data. (b) Cityscape lines show experimental fraction transmission after about
10 min of sampling, according to C∗, for various polymer tubing materials. Smooth lines show model runs for cSI after 10 min and PFA after
1 and 10 min. Model runs for all other polymers are consistent with experimental data and are shown in Fig. S11. See text for a discussion of
the PFA modeling. Compound names have been added to the top of the graph for reference to relevant C∗values.
signals at different m/zvalues that had the same desorption
profiles through the tubing, suggesting a parent–fragment ion
relationship.
Another application of this technique would involve sam-
pling air into an oxidation flow reactor (OFR) through one
or several conductive polymer tubes. An OFR can be used to
quantify the amount of secondary aerosol mass formed from
gas-phase precursors (Ortega et al., 2016; Kang et al., 2007).
When put in front of an OFR, conductive polymer tubes
act as volatility high-pass filters, only transmitting higher-
volatility VOCs while also transmitting particles. This would
allow one to quantify the amount of aerosol formed from
species above a certain volatility cutoff. Measurements of
total OH or ozone reactivity could be made according to
volatility class in a similar manner.
4 Conclusions
Polymer absorption of VOCs is known to be dependent on
compound volatility and the absorptive capacity of the poly-
mer. In this work, the absorptive capacities of many poly-
mers, relevant for new air sampling techniques and indoor
air quality, were quantified. Experimental time series were fit
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M. A. Morris et al.: Polymer tubing for VOC separation by volatility 1557
with either a single-layer or a multilayer absorption model,
and polymers were categorized as either slow-diffusion or
fast-diffusion. Both of the models used in this study are
freely available in Morris et al. (2024). VOCs penetrated
only a surface layer <1 µm (often only tens of nm) thick
for slow-diffusion polymers during our experiments. In con-
trast, fast-diffusion polymers took compounds into the bulk
of the material on a timescale of minutes, with penetration
depths of 10–100 µm after 20 min. This finding has signif-
icant implications for indoor air, as a large number of sur-
faces in indoor environments are made of polymers, and
it is usually assumed that sorption only happens in a thin
near-surface layer or simply just on the surface of materi-
als. Nylon, polyester, polypropylene and polyethylene are the
main polymers found in synthetic carpets, and quantifying
their absorptive capacities adds to the growing literature that
indoor polymers can provide a huge sorptive reservoir for
VOCs.
Materials in this study were also categorized by applica-
tion: nonconductive polymers for gas transmission and con-
ductive polymers and coated metal tubes for gas and parti-
cle transmission. The best material for gas transmission was
PFA Teflon tubing, and the best material for gas and particle
transmission was foil-wrapped conductive PFA; both of these
findings are consistent with previous tubing literature. The
most sorptive material was cSI tubing, which did not transmit
species with C∗<107µg m−3. The cSI tubing (as well as the
cPUN tubing, which also showed significant denuding) could
be used to purposefully denude species of lower volatilities
from a sample gas stream. However, cSI contaminates the
gas stream with siloxanes, which is problematic for sam-
pling applications (cPUN tubing also emits unknown com-
pounds in significant amounts). Older cSI tubing off-gassed
significantly less contamination, and it may be possible to
accelerate such aging (e.g., with controlled heating in an in-
ert atmosphere). SilcoNert (tested in this work) and Silonite
(tested in previous work) performed almost as well as PFA
in terms of gas transmission. However, since these are steel
coatings, they undergo adsorption, which makes their delay
times potentially dependent on humidity, concentration and
history. These effects are very difficult to predict or correct
for in the real world, so non-polymer tubing is only recom-
mended when gas–wall interactions are not important (e.g.,
when sampling dust or metal particles or very volatile gases).
Additionally, using a series of polymer tubes with different
absorptive capacities, we demonstrate how partitioning de-
lays caused by polymer tubing can be exploited as a volatility
class separation technique for atmospheric chemistry sam-
pling. This technique can be utilized in future studies to mea-
sure volatility dependence of compound characteristics like
secondary organic aerosol (SOA) formation potential or rad-
ical reactivity.
Code and data availability. The models used in this work
are freely available at https://gitlab.com/JimenezGroup/JG_
SurfacePartitioning/ (Morris et al., 2024).
Supplement. The supplement related to this article is available on-
line at: https://doi.org/10.5194/amt-17-1545-2024-supplement.
Author contributions. MAM and JLJ designed the experiments.
MAM performed the measurements, analyzed the data and wrote
the paper. DP and DAD assisted with performing the measurements.
JLJ and DP assisted with measurement interpretation and model-
ing. All authors provided input during review meetings during the
project and reviewed and edited the paper.
Competing interests. The contact author has declared that none of
the authors has any competing interests.
Disclaimer. Publisher’s note: Copernicus Publications remains
neutral with regard to jurisdictional claims made in the text, pub-
lished maps, institutional affiliations, or any other geographical rep-
resentation in this paper. While Copernicus Publications makes ev-
ery effort to include appropriate place names, the final responsibility
lies with the authors.
Acknowledgements. We thank Jesse Bischof of SilcoTek for sup-
plying the coatings and for useful discussions, Andy Lambe of
Aerodyne for supplying a coated OFR from Aerodyne Inc. and
for useful discussions, David Osborn of Sandia National Labs for
providing the halocarbon-wax-coated glass tube and useful discus-
sions, and Pedro Campuzano-Jost and Anne Handschy for help with
laboratory work.
Financial support. This research has been supported by the Alfred
P. Sloan Foundation (grant no. 2019-12444), the National Science
Foundation (NSF) Division of Atmospheric and Geospace Sciences
(grant no. 2206655), and CIRES’ Innovative Research Program.
Review statement. This paper was edited by Pierre Herckes and re-
viewed by two anonymous referees.
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