Introduction
Volatile organic compounds (VOCs) are important atmospheric trace gases with
anthropogenic and biogenic emissions (e.g. Koppmann, 2007; Warneck, 1988,
and references therein). VOCs include a large variety of non-methane
hydrocarbons (NMHCs, mostly from C2–C16) such as alkanes, alkenes,
alkynes, aromatic compounds, and terpenoids as well as oxygenated VOCs
(OVOCs) such as alcohols, aldehydes, and ketones (Andreae and Merlet,
2001; Monks et al., 2009; Placet et al., 2000; Plass-Duelmer et al.,
1993; Sawyer et al., 2000). The mole fractions of these compounds vary from
below 1 pmol mol-1 to tens of nmol mol-1 in background and urban air, respectively
(e.g. Gros et al., 2007; Parrish and Fehsenfeld, 2000). Atmospheric VOCs
have an impact on the oxidising capacity of the atmosphere through their
role in the generation of photo-oxidants (e.g. ozone and organic radicals)
and are precursors of secondary organic aerosols. For these reasons,
reliable measurements of VOCs are essential, and they are consequently
included in the long-term monitoring programmes of the Global Atmosphere Watch
(GAW) of the World Meteorological Organization (WMO, 2007a),
regional programmes such as the European Monitoring and Evaluation Programme
(EMEP), and national air pollution monitoring networks.
In Europe the measurement capacity for VOCs in the atmosphere is diverse. On
the one hand, several laboratories maintain long-term and high-quality
measurements based on sophisticated quality assurance/quality control
(QA/QC) systems, high-quality standard gases, previous intercomparison
activities, and audits by the World Calibration Centre for VOCs. On the
other hand, the performance of other laboratories is limited by a lack of
such quality measures and by the fact that there are no commonly agreed-upon
guidelines concerning standards, homogenised quality assurance procedures
and measurement methods. In Table 1 of the WMO GAW Report No. 171 (WMO,
2007b) 17 priority VOCs (NMHCs and oxygenated VOCs) were identified and
general quality assurance recommendations were defined (Table 2). The
European infrastructure network project ACTRIS (Aerosols, Clouds, and Trace
gases Research InfraStructure) has expanded the priority substances to
further NMHCs described in Table 1. Furthermore, measurement guidelines and
a quality management system were developed under ACTRIS to harmonise trace
gas measurements of NMHCs in Europe
(http://www.actris.net/Project/WorkPackages/WP4/tabid/4428/Default.aspx).
One objective of ACTRIS was to assess the current NMHC measurement capacity
in Europe and to investigate the analytical performance of laboratories in
terms of data quality objectives (DQOs) for repeatability and uncertainty.
Strict DQOs were defined in ACTRIS (Table 2) and were adopted by the GAW
Scientific Advisory Group for Reactive Gases during their meeting in October 2014.
Whilst in the WMO GAW Report No. 171 DQOs are defined for accuracy and
precision, these have been replaced in ACTRIS with uncertainty (in the sense
of expanded combined uncertainty with coverage factor k= 2; JCGM,
2008) and repeatability (which characterises the short-term standard
variation in multiple measurements).
Assigned mole fractions (error-weighted means with expanded uncertainties) for NMHC_N2 and NMHC_air (nmol mol-1).
Error-weighted mean ± expanded uncertainty (nmol mol-1)
NMHC_N2
NMHC_air
cylinder 1
cylinder 2
cylinder 1
cylinder 2
Alkanes
ethane
1.071±0.016
1.118±0.016
1.871±0.037
1.904±0.041
propane
1.061±0.014
1.104±0.015
1.608±0.025
1.611±0.023
n-butane
1.025±0.028
1.076±0.015
1.407±0.019
1.407±0.015
methylpropane
1.051±0.011
1.114±0.013
0.778±0.026
0.765±0.024
n-pentane
1.031±0.012
1.092±0.017
0.834±0.012
0.834±0.014
2-methylbutane
1.011±0.011
1.075±0.014
1.669±0.029
1.654±0.028
n-hexane
1.019±0.013
1.083±0.014
0.157±0.006
0.151±0.006
2-methylpentane
1.025±0.014
1.089±0.014
0.343±0.025
0.348±0.021
3-methylpentane
0.195±0.009
0.194±0.008
2,2-dimethylbutane
0.257±0.038
0.256±0.033
2,3-dimethylbutane
0.070±0.020
0.072±0.020
cyclohexane
0.140±0.005a
0.141±0.009a
n-heptane
1.011±0.011
1.077±0.012
0.443±0.008
0.463±0.010
n-octane
1.011±0.021
1.076±0.023
0.443±0.008a
0.463±0.010a
2,2,4-trimethylpentane
1.028±0.012
1.095±0.012
0.145±0.008a
0.144±0.008a
Alkenes
ethene
1.065±0.015
1.127±0.015
2.531±0.034
2.532±0.035
propene
1.030±0.013
1.091±0.016
0.571±0.020
0.552±0.014
1-butene
1.007±0.031
1.070±0.033
0.114±0.006a
0.109±0.006a
2-methylpropene
0.858±0.039a
1.081±0.049a
trans-2-butene
1.024±0.018
1.088±0.019
0.074±0.003a
0.075±0.003a
cis-2-butene
1.008±0.011
1.069±0.013
0.066±0.002
0.067±0.002
1,3-butadieneb
1.024±0.025
1.087±0.024
0.066±0.011
0.062±0.014
1-pentene
1.001±0.012
1.086±0.036
0.048±0.014a
0.044±0.013a
trans-2-pentene
0.984±0.015
1.042±0.018
0.057±0.004
0.058±0.004
cis-2-penten
0.033±0.003
0.032±0.003
2-methyl-2-butene
0.125±0.020
0.121±0.006
isopreneb
2.039±0.038
2.178±0.034
0.021±0.008
0.022±0.006
Alkynes
ethyne
1.020±0.026
1.118±0.024
1.467±0.032
1.485±0.039
propyne
0.065±0.019a
0.065±0.017a
Aromatic compounds
benzene
1.022±0.012
1.091±0.013
0.460±0.006
0.458±0.007
toluene
1.021±0.048
1.222±0.039
1.709±0.059
1.737±0.055
ethylbenzene
1.017±0.057
1.182±0.057
0.245±0.010
0.247±0.008
m,p-xylene
2.035±0.117
2.569±0.108
0.884±0.038
0.882±0.036
o-xylene
1.047±0.097
1.180±0.095
0.279±0.019
0.282±0.023
a Assigned mole fractions were determined only with results from HPB;
b arithmetic mean of measurements instead of error-weighted mean.
Compounds: priority VOCs as defined in the WMO GAW Report No. 171 (WMO, 2007b).
Further WMO GAW priority VOCs which were not investigated here: monoterpenes,
dimethylsulfide, formaldehyde, methanol, ethanol, acetone, acetonitrile.
ACTRIS and former GAW1 data quality objectives (DQOs). Numbers
express the expanded uncertainty (coverage factor k=2), and the
repeatability (standard deviation).
GAW1
GAW1
ACTRIS2
ACTRIS2
uncertainty
repeatability
uncertainty
repeatability
alkanes
10 %
5 %
5 %
2 %
alkenes incl. isoprene
20 %
15 %
5 %
2 %
alkynes
15 %
5 %
5 %
2 %
aromatics
15 %
10 %
5 %
2 %
mole fraction
0.02 ppb
0.015 ppb
0.005 ppb
0.002 ppb
<0.1 nmol mol-1 (ppb)
1 From WMO GAW Report No. 171 (WMO, 2007b); 2 GAW VOC Expert Group and
the GAW Scientific Advisory Group for Reactive Gases during their meetings in Daejong (South Korea, Oct 2014) as new GAW DQOs.
VOC species are normally measured with gas chromatography coupled to either
a flame ionisation detector (GC-FID) or a mass spectrometer (GC-MS).
Furthermore, proton transfer reaction mass spectrometry (PTR-MS) is also
used for the measurement of oxygenated VOCs, terpenoids, dialkenes, and
aromatics. While PTR-MS analyses VOCs from air samples directly, GC-based
techniques need a preconcentration step. Here VOCs are either analysed
immediately after sampling onto suitable adsorbents (online) or they are
collected in specially treated steel or glass cylinders or on cartridges
filled with adsorbents and analysed later in the laboratory (offline).
Problems which can occur are chemical reactions in the samples (due to e.g.
reactions with ozone), adsorptive losses, memory effects or leaks, losses
during the preconcentration and the desorption steps, chemical reactions
during thermal desorption, insufficient separation on the chromatographic
column and misidentification, peak overlap, and inaccurate quantification
(Helmig, 1997, 1999; Helmig and Vierling, 1995; Koppmann et al., 1995;
Parrish and Fehsenfeld, 2000; Plass-Duelmer et al., 2002; Rudolph, 1999;
Westberg and Zimmerman, 1993).
Several NMHC intercomparisons have been carried out in the past on European
and global scales. Generally, these aimed at an evaluation of the quality of
VOC measurements without data quality objectives defining a threshold to
differentiate between higher- and lower-quality data (e.g. NOMHICE: Apel et al.,
1994, 1999, 2003; AMOHA: Plass-Duelmer et al., 2006; Slemr et al., 2002; GAW: Rappenglueck
et al., 2006; Bernardo-Bricker et al., 1995; De Saeger and
Tsani-Bazaca, 1993; Hahn, 1994; Pérez Ballesta et al., 2001; Romero,
1995; Volz-Thomas et al., 2002). NOMHICE (Nonmethane Hydrocarbon
Intercomparison Experiment) and AMOHA (Accurate Measurements of Hydrocarbons
in the Atmosphere) were two systematic multistage intercomparisons for NMHCs
performed in North America and Europe, where the complexity of the NMHC
measurements (numbers of compounds and sample gas mixtures) increased during
the experiments. While in earlier intercomparisons the use of certified NMHC
calibration standards was not common (Apel et al., 1994, 1999, 2003;
De Saeger and Tsani-Bazaca, 1993; Hahn, 1994; Pérez Ballesta et al., 2001; Romero, 1995), multicomponent standards
with certified NMHC mole fractions were circulated for analysis among the
participating laboratories in more recent intercomparisons
(Plass-Duelmer et al., 2006; Rappenglueck et al., 2006; Slemr et al.,
2002). Within these studies the calibration with multicomponent NMHC
calibration standards was superior to calibration with a single hydrocarbon
species. Therefore, also in the ACTRIS intercomparison experiments all
participating laboratories were asked to use certified multicomponent NMHC
calibration standards, traceable to the GAW scale, for calibrating their
instruments and for performing quality checks.
Eighteen stations or laboratories from nine European countries took part in
this ACTRIS intercomparison exercise for the analysis of NMHCs. OVOCs were
excluded due to their instability in pressurised cylinders at ambient mole
fractions. Pressurised cylinders filled with NMHCs in nitrogen (in the
following called NMHC_N2) and NMHCs in whole air (in the
following called NMHC_air) were analysed by the different
laboratories using their own certified multicomponent NMHC calibration
standard. The participants performed their measurements with GC-FID,
GC-MS, or PTR-MS instrumentation. The performance of the different
laboratories was examined with respect to compliance with the DQOs of ACTRIS
and GAW (Table 2). Feedback was provided to the participants during a
workshop, via analysis of technical details of each instrument, and the
provision of recommendations for further characterisations and improvements.
This paper presents the findings of the intercomparison, with a focus on
alkanes, alkenes, alkynes, and aromatic compounds. Results are used to
discuss the status of current NMHC measurement capabilities in Europe
10–20 years after AMOHA, GAW, and NOMHICE intercomparisons and to discuss and
evaluate issues with different instrumental set-ups used in the field.
Method section
Intercomparison approach
Eighteen European laboratories with 23 different GC instruments participated
in this NMHC intercomparison exercise in 2012 (Fig. 1 with laboratory
abbreviations, Tables S1–S2 in the Supplement). Additionally, two PTR-MS instruments analysed
the NMHC mixtures (Table S2; results are shown only in the Supplement).
It should be pointed out that the “PerkinElmer Online Ozone
Precursor Analyzer” is the only commercially available all-in-one
instrument tested in this study. All other instruments use combinations of
commercially available parts and custom-built units.
The intercomparison exercise was performed in two loops (with nine participants
each) in order to keep the total time for the exercise within a few months.
All participants received two cylinders, one filled with NMHC_N2 and one with NMHC_air.
The participants of the ACTRIS NMHC intercomparison in Europe.
Left: western, central, and southern Europe; right: northern Europe. AUC:
Auchencorth, CMN: Monte Cimone; DOU: Mines des Douai; FZJ: Forschungszentrum
Jülich; HAR: Harwell; HPB: Hohenpeissenberg; IPR: Ispra; JFJ:
Jungfraujoch; KOS: Kosetice; MHD: Mace Head; NILU: Norwegian Institute for
Air Research; PAL: Pallas; PUY: Puy-de-Dôme; RIG: Rigi; SIR: Sirta; SMR: GC-MS, and SMR II: PTR-MS (both at SMEAR II,
Hyytiälä); SMK: Schmücke; WCC-VOC: Garmisch-Partenkirchen; YRK: York;
ZSF: Zugspitze-Schneefernerhaus. For further details about the stations and
instruments see Table S1–S2.
Preparation of NMHC mixtures
The two NMHC mixtures, NMHC_N2 and NMHC_air, were prepared in 10 L “Quantum” passivated aluminium cylinders (Air
Products, purchased from National Physical Laboratory (NPL)).
NMHC_N2 was diluted with nitrogen (quality 5.0 from
Linde AG, Germany) from a ∼ 100 nmol mol-1 uncertified mixture
of 30 NHMCs (and several monoterpenes) in nitrogen (prepared by NPL for HPB
on demand) into two cylinders by HPB. The resulting mole fractions in
NMHC_N2 were ∼ 1 nmol mol-1 (Table 1). The
final pressure in the cylinders was ∼ 120 bar.
NMHC_air was filled with ambient air from Dübendorf (a
suburban area of Zurich, Switzerland) in two 10 L cylinders, using a
modified oil-free diving compressor (Model SA-6; RIX Industries, USA) on
31 October 2011. Due to the pressurisation, the water vapour condensed and
the final humidity in the cylinders was very low (dew point < -30 ∘C,
relative humidity ∼ 1 %). The mole
fractions of C2–C8 NMHCs in NMHC_air ranged from
0.03 to 2.5 nmol mol-1 (Table 1). The final pressure in the cylinders was
∼ 80 bar. Mole fractions in NMHC_air were in
the upper range of rural stations in Europe and higher than remote
conditions (Helmig, 1997; Helmig et al., 2008; Read et al., 2009).
Three laboratories (WCC-VOC, HPB, and Empa) assigned NMHC mole fractions to
the different cylinders before and after the intercomparison. Additionally,
these two time-separated measurements were used to assess the stability of
the NMHC mixtures. All three laboratories used certified NMHC calibration
standards from the GAW Central Calibration Laboratory for NMHCs (NPL), which
defines the scale for NMHC measurements in WMO GAW. The analytical systems
of the three reference laboratories can be considered as sufficiently
independent as different pre-concentration systems and chromatographic
columns are used (see Table S2a–b).
Since HPB and Empa acted as reference laboratories, their data measured in
the middle of the intercomparison were not used for the reference value
determination. However for completeness, their values are displayed in
Figs. 2–4 and S1–S4, and Tables S3–S6 together
with those of the other participants and correspondingly marked as no
“independent” results.
The NMHC mole fractions were usually assigned as error-weighted means
(Barlow, 1989; Bronštejn, 2007) and are displayed with their
corresponding expanded uncertainty (coverage factor k=2, corresponding to
2σ or roughly a 95 % confidence interval) in Table 1. A more
detailed description is given in the Supplement.
Measurement approach
A detailed measurement guideline was provided to the participants to ensure
consistent and comparable measurements of the NMHC mixtures. All
participants used the same provided pressure regulators (model 206A from
Scott Specialty Gases, USA) and transfer lines (Silcosteel®,
1 / 16 in., ∼ 2.5 m). The pressure regulator was mounted at least
24 h before the measurement onto the gas cylinder and connected to the
transfer line. Afterwards, the regulator and the transfer line were flushed
three times and an initial leak test was performed (observation of pressure
drop during 10 min). The pressure regulator and the transfer line were kept
pressurised for at least 24 h (with closed cylinder valve) for
equilibration of surfaces. Additionally, this setup served as a static leak
test.
All participants were asked to quantify the NMHC mole fractions using their
own calibration standard (Table S2b) and to report their expanded
measurement uncertainty (see Supplement). Within GAW and ACTRIS,
the scale for NMHC measurements is defined by the Central Calibration
Laboratory (CCL) NPL, which continuously
compares their NMHC scale and the associated expanded combined uncertainty
of typically 2 % with other NMI (National Metrology Institutes) (Grenfell
et al., 2010). Though different scales might cause a bias of results by
participants that are related to a non-NPL laboratory standard, this ACTRIS
comparison study addresses the inter-laboratory compatibility related to the
standardised GAW NMHC scale provided by NPL. The certified expanded
uncertainties of the NPL of 2 % are generally much lower than deviations
discussed in this paper, e.g. beyond the DQO of 5 %.
The composition and the mole fractions in the cylinders were unknown to all
participants, except for the reference laboratories HPB and Empa (see
above). The measurement procedure was the following: at least three calibration
standard measurements, five measurements of NMHC_N2, five
measurements of NMHC_air, at least three calibration standard
measurements, and a zero-gas measurement before and after the NMHC mixture
measurements. Fourteen analyses were by GC-FIDs and nine by GC-MSs (Table S2).
In this paper, results for 27 and 35 NMHCs are shown for
NMHC_N2 and NMHC_air, respectively. The
three trimethylbenzenes and the monoterpenes present in NMHC_N2 were not
investigated in this intercomparison paper due to the lack
of available data. The assigned NMHC mole fractions (with expanded
uncertainties) are given in Table 1.
Data quality objectives (DQOs) for NMHC measurements
In the WMO GAW Report No. 171 (WMO, 2007b) general DQOs for different
priority VOCs were defined (Table 2). Within the framework of ACTRIS, the
list of priority compounds (Table 1) was expanded, and more challenging DQOs
(ACTRIS DQOs) were defined (Table 2). Overall, ACTRIS DQOs are about a
factor of 2 stricter than those in the GAW Report 171. The reason for the
introduction of the ACTRIS DQOs was to detect trends of NMHCs more
accurately, which currently decline by 1–8 % per year in Europe
(Solberg, 2012, 2013, and references therein). These ACTRIS DQOs
were also adopted by the GAW VOC Expert Group and the GAW Scientific
Advisory Group for Reactive Gases during their meetings in Daejong (South Korea, October 2014). For the uncertainty,
which describes the deviation from a reference value, the goals are set to
5 % for alkanes, alkenes (including isoprene), alkynes, and aromatics (and
to 10 % for monoterpenes). Values express the expanded uncertainty with a
coverage factor of k=2. The goals in repeatability, defined as the
standard deviation of the NMHC measurements, are 2 % for alkanes, alkenes
(including isoprene), alkynes, and aromatics, and 5 % for monoterpenes.
For mole fractions below 0.1 nmol mol-1 an absolute value of 0.005 nmol mol-1 is
accepted as uncertainty, and 0.01 nmol mol-1 for monoterpenes.
In the results section the measurement performance is compared against these
DQOs by ACTRIS and adopted by GAW (Table 2). Hereby the uncertainties
uref of the assigned reference values (Table 1) need to be taken into
account. Thus, a result fulfils the ACTRIS DQO if the deviation from the
reference is less than the 5 % deviation class defined as
5% class=DQOACTRIS2+uref2.
For the 10 % deviation class (10 % class), the respective former GAW DQO
(Table 2) is applied.
C response for GC-FID systems
A GC-FID system can be characterised for losses or artefacts by making use
of the known carbon response, the so-called C response (Plass-Duelmer et
al., 2002). When the C responses for the various NMHC compounds are
calculated, they should agree within a few percent, except for ethyne
(Burns et al., 1983; Dietz, 1967; Faiola et al., 2012; Gong and
Demerjian, 1995; Scanlon and Willis, 1985; Sternberg et al., 1962). The
C response Ri for each compound i was calculated as follows:
Ri=Aistd-AibmistdNiVstd,
where Aistd and Aib are the peak areas of compound i in the
calibration standard (std) and the blank (b), respectively; mistd
denotes the certified mole fraction of the calibration standard; Ni
the number of C atoms in compound i; and Vstd the sampled volume of the
calibration standard.
Mole fractions for NMHC_N2 and
NMHC_air normalised to the assigned values. Circles
(O) indicate separation column one, triangles (Δ)
separation column two. Open symbols indicate NMHC_N2,
filled symbols NMHC_air. Black symbols indicate results for mixing ratios
> 0.1 nmol mol-1 (left axis, ratios to assigned values),
blue symbols for < 0.1 nmol mol-1 (right axis, difference to
assigned values, see text). Error bars show the
expanded combined uncertainties.
Continued.
Continued.
Continued.
Box plots for NMHC_N2 (left) and
NMHC_air (right) relative to the assigned mole fractions
(Table 1). (a) Overview box plot for all results, (b) box plot for the different
compound classes, (c) box plot for alkanes, (d) box plot for alkenes and
alkynes, (e) box plot for aromatics.
The white box stretches from the 25th percentile to the
75th percentile, containing the median in between. The whiskers end at
the 10th and 90th percentile. The orange box indicates the
5 % class (see Table 2 and Eq. 1). MS: mass spectrometer; FID: flame
ionisation detector; PE: PerkinElmer.
Continued.
When comparing the C response values in the calibration standard and in
NMHC_N2, the C responses should ideally be identical.
Deviation points towards either artefacts in the analytical system (e.g.
breakthrough during trapping, adsorptive losses, peak overlap, changes on
active sites) or in the FID due to sample matrix effects influencing the
flame. For easier comparison, the C responses were normalised by the average
C response of the available C4–C6 alkanes (highlighted in yellow
in Fig. 4). As some stations did not report C2–C3 alkanes (e.g.
HPB_B, FZJ_A) and additionally breakthrough in
C2 compounds could have occurred, only C4–C6 alkanes were
taken into account. For two-column systems, the average C response of the
second column was determined using C7–C8 alkanes, benzene, and
toluene (highlighted in green in Fig. 4). Any individual C response
deviating more than 10 % from the average C response was not considered
in the normalisation process.
Results and discussion
Overview of results
Mole fractions for NMHC_N2 and NMHC_air
normalised to the assigned values (Table 1) are shown for each participant
and compound in Fig. 2 (black symbols, left y axis). For compounds with
mole fractions < 0.1 nmol mol-1 the difference in nmol mol-1 to the
assigned values is shown (blue scale on the right y axis). Error bars
represent the total expanded uncertainty as stated by the participant.
Box-and-whisker plots for all results are presented in Fig. 3. Results are in
compliance with the ACTRIS DQO if they fall into the 5 % class (Eq. 1).
For compounds with mole fractions below 0.1 nmol mol-1, this class
reflects a deviation of 5 nmol mol-1 plus uncertainty of reference. In
addition, for GC-FID systems C responses were calculated and are depicted in
Fig. 4. More detailed information on the performance of different
measurement systems is given in Tables S3–S6 as well as Figs. S1–S4 in the
Supplement.
For the ∼ 1 nmol mol-1 in nitrogen (NMHC_N2)
nearly 62 % of all results were within the 5 % class (ACTRIS DQOs), and
nearly 90 % within the 10 % class (former GAW DQOs; Table 2) (Fig. 3 and
Tables S3–S4). The best performance was achieved for alkanes with 65 % of
the submitted alkane data within 5 % of the reference; for the subgroup of
C2–C3 alkanes even 81 % of the submitted data were within the
5 % class (Table S3, Fig. 3b). C4–C7 alkanes were more
challenging, and more deviations to the assigned mole fractions were observed
(Fig. 2). For alkenes and aromatic compounds the percentages of results
within the 5 % class were 58 and 47 %, respectively (Table S3, Fig. 3).
Results for aromatics reveal a distinct tendency to be underestimated in
NMHC_N2 (Fig. 3e). Nevertheless, 63 % of the results
match the 5 % class (Table S3), reflecting the rather large uncertainties
of some reference values for aromatics (e.g. o-xylene, Table 1).
For NMHC_air, generally more frequent and larger deviations
from the assigned values were observed compared to NMHC_N2, and
50 % of all results were found within the 5 % class (79 %
within the 10 % class) (Fig. 3, Tables S3 and S4). Only
C2–C3 alkanes reveal a rather good performance, with 84 % of the
respective data within the 5 % class. Compared to NMHC_N2, the
tendency to underestimate aromatic compounds is not observed
(Fig. 3e).
The repeatability of the instruments was evaluated as the standard deviation
(1σ) of the five measurements for both NMHC mixtures. The majority of
the participants submitted a relative repeatability in NMHC_N2 within the
former GAW DQO (± 5 % for alkanes and alkynes,
± 10 % for aromatics and ± 15 % for alkenes including
isoprene), 70 % even within ± 2 % (ACTRIS DQO), independent of the
detector type. Poor repeatability was mostly linked with poor
chromatographic resolution (see Tables S5 and S6).
In the following, reasons for deviations larger than the stated quality
objectives will be discussed.
Uncertainty estimations of the NMHC measurements
Performing a complete uncertainty estimation is critical to the quality of
the data. Nevertheless, only the participants DOU, KOS (both systems), RIG,
HPB (both systems), JFJ, MHD, NILU and ZSF provided a thorough analysis
(see “Determination of assigned values (error-weighted means) for NMHC
mixtures” in the Supplement) of their expanded uncertainties
(error bars in Fig. 2). All other participants calculated their
measurement uncertainties only partially (e.g. only reporting
repeatability). Generally, for many results the uncertainties were
underestimated and, even combined with the uncertainties of the reference
values, do not comprise the deviation from the assigned values. Thirty-six percent of
results in NMHC_N2 were out of the stated uncertainty
ranges, and 35 % in NMHC_air. As the expanded uncertainty
corresponds to the 95 % confidence interval, it would be expected that not
more than 5 % of the results deviate by more than the uncertainty from the
assigned values. This needs to be improved in programmes like GAW and EMEP,
as realistic uncertainty estimation is essential for the user, e.g. in model
validation.
Critical in this evaluation are the assigned values; if these are biased
relative to the “true” values, deviations may occur. However, in
NMHC_N2 there was a check by a common dilution factor
relative to a NPL-certified standard of identical relative composition,
which strongly supports the determined mole fractions within better than
2 % and does not indicate any bias. For NMHC_air, we rely
on the uncertainty evaluation of the reference values by the reference
laboratories, which is considered a realistic estimate. Though the assigned
values are generally higher than the majority of the participants' results
(Fig. 3), they are typically between the median and the 75-percentile or
90-percentile values with partially contradicting deviations for the
various techniques; e.g. alkanes derived from MS are high, whereas those from
FID are low compared to the reference (Fig. 3c). Furthermore, deviations
in participants' results are similar for NMHC_N2 and
NMHC_air (e.g. Fig. 3a, various results in Fig. 2),
supporting the assigned values in NMHC_air based on reliable
NMHC_N2 determination (see below).
Calibration procedure
One essential step on the way to high-quality NMHC data is the use of an
adequate calibration procedure. The participants calibrated their NMHC
measurements either directly against certified multicomponent standards
(one-step calibration) or against whole air working standards, which in turn
are related to a certified multicomponent standard (two-step calibration
done by CMN and Medusa systems). The systems using a NPL (the GAW Central
Calibration Laboratory for NMHCs) standard for direct, one-step calibrations
(Table S2b) generally exhibited a good performance. Since the
NMHC_N2 mixture and the NPL calibration standard
virtually comprise the same matrix, complexity, and manufacturer, observed
deviations for sites referring to the NPL scale should be within the
repeatability of the instruments. This is not the case for some participants
and compounds, and it points to unidentified sample transfer issues. The mole
fraction range of the used NPL standards (e.g. 2, 4, or 10 nmol mol-1) and
date of production apparently did not affect the quality of the results
(Fig. 2, Table S2b).
The systems FZJ_B, FZJ_A, MHD, and PUY used
different certified NMHC calibration standards (Table S2b). If a systematic
offset between different scales exists, it should result in systematic
deviations from the assigned values. FZJ_B, FZJ_A, and MHD all used calibration standards from
Apel-Riemer, but the observed deviations from the assigned values are random (e.g.
deviations for alkanes are of different extent and sign (Fig. 2m, p, and
v). Obviously other instrumental issues (e.g. chromatographic resolution,
non-linearity of MS detector) affected these results and therefore
systematic differences between the different calibration scales cannot be
assessed.
The Medusa instruments (JFJ, MHD, and NILU) generally overestimated the NMHC
mole fractions (Figs. 2u–w and 3b). However, the excellent repeatability
suggests that the systems run much better than the deviations indicate.
Thus, a significant issue might arise from the fact that Medusa instruments
and CMN are calibrated with whole air working standards using a two-step
calibration. Direct calibration by certified NMHC standards appears to be
superior to whole air working standards for NMHCs.
FID C responses as an indicator of NMHC measuring system artefacts.
Circles (O) indicate column one, triangles (Δ) column two. Filled symbols
indicate the C responses in the calibration standard, open symbols the
C responses in NMHC_N2. The C responses for column one
were normalised by the average C response of the available
C4–C6 alkanes (highlighted in yellow), column two by the average
C response of the available C7–C8 alkanes, benzene, and toluene
(highlighted in green). If an individual C response deviated by more than
10 % from the average C response, the value was not considered in the
normalisation process.
Continued.
Continued.
GC-FID systems
In order to analyse the performance of the GC-FID systems, the normalised
C response factors for the calibration standards and NMHC_N2 were
compared (Fig. 4). Though identical C- responses are
expected, several GC-FID systems tend to slightly underestimate NMHCs in
NMHC_N2 compared to the calibration standard (Figs. 4
and 2). Even more surprising was the fact that in some of the systems which
have two separation columns, a lower normalised C response for
NMHC_N2 compared to the calibration standard was
observed in only one column, e.g. AUC (in the PLOT column) and DOU
(in the CP Sil-5 CB column, Table S2b) (Fig. 4a, h). The latter excluded sample transfer problems
from the cylinder to the GC but pointed towards systematically different
carrier gas or detector sensitivity conditions between analyses of
calibration standard and NMHC_N2. Overall, these
discrepancies cannot be explained as general features but must be related
to individual technical issues of the respective GC systems.
In general, there are several potential reasons for the deviations of
C response factors between the calibration standard and the
NMHC_N2 and from the expected value of 1. They include
losses of sample due to breakthrough, incomplete desorption or losses on
walls, poor chromatographic resolution with inadequate peak separation or
shape, and other artefacts (e.g. water management) and are addressed below.
Problems with C2–C3 hydrocarbons
More than 80 % of the C2–C3 hydrocarbons were reported within
the 5 % class in NMHC_N2 (Tables S3–S4, Figs. 2 and
3b). However, a few systems reported C2–C3 hydrocarbon values
even outside the range of ± 10 %. The systems of AUC (only for
ethene and propene), HAR, PAL, SMK, and IPR showed losses of
C2–C3 hydrocarbons in the normalised C response plots, and ZSF and
AUC (only for ethane) gave enhanced values (Fig. 4a–f). All of these six
mentioned systems used a PerkinElmer TurboMatrix, which contains an
air-toxics/air-monitoring trap, applies a 2 mL min-1 outlet split between trap and
column, and has a two-column configuration with a Deans switch (Table S2).
Sample breakthrough could be a specific issue of the PerkinElmer trap for
these compounds. Badol et al. (2004) reported breakthrough for ethene and
ethyne when the sampling volume exceeded 900 mL. However, no systematic
influence of sample volume (up to 1360 mL) and trapping temperature
(-40 or -30 ∘C) could be identified (Table S2). For
example IPR used -30 ∘C as the adsorption temperature and a very large
sample volume (1360 mL) but showed only moderate loss of
C2 hydrocarbons compared to e.g. SMK with 500 mL sample volume and
larger losses (Fig. 4). For ZSF, the C responses for the
C2–C3 hydrocarbons were even enhanced (> 1) compared to
all other hydrocarbons (Fig. 4e). This system was affected by the
displacement to 2650 m a.s.l shortly before this intercomparison exercise.
Thus, most probably changed pressure and flow rates caused deviations during
thermal desorption and might have affected the chromatographic resolution
and thus the measurement quality of several of the compounds investigated in
this study. In Figs. 2e and 4e, distinct deviations are observed for many
substances, including C2–C3 compounds (Fig. 4e). Another
explanation for decreased C responses for C2–C3 hydrocarbons could
be a split issue during column injection. If a pressure pulse builds up in
the thermodesorption phase, the split ratio might vary during the injection
period causing different split ratios for high- and low-volatility
hydrocarbons. Further, this pressure pulse could potentially influence the
Deans switch. However, the systems of DOU and KOS_A also have
Deans switches (with different thermodesorbers, Markes and Entech,
respectively) and did not show losses of C2–C3 hydrocarbons.
Based on these results it is not possible to distinguish between split, and
trap issues and this needs further investigation.
In NMHC_air the results of the low-boiling alkanes (up to
C5) were more scattered compared to NMHC_N2
(Figs. 2 and 3) mainly due to limits in chromatographic resolution (see
Sect. 3.4.5). Despite apparent losses in specific
systems (C response < 1, Fig. 4), most systems did not show
deviations for the C2–C5 alkanes. However, the reference
laboratory WCC-VOC observed specific matrix problems in NMHC_air in their
GC-FID/FID system (not shown), which they attributed to
extraordinarily high OVOC levels causing unusual artefacts in their trapping
and desorption system. The high OVOC mole fractions of ∼ 200 nmol mol-1
were analysed by their PTR-MS system (see PTR-MS results in
Supplement).
Low-boiling alkenes (C2–C5) showed partly substantial deviations
to the assigned mole fractions in the AUC, PAL, SMK, ZSF, and IPR results,
especially in NMHC_air (Figs. 3, 4a, c–f). Additionally to
the aforementioned problems, alkene artefacts (see below) and, in the case of
KOS_A, poor chromatography resolution contributed. The rather
low mole fractions (< 100 ppt) did not affect the quality of the
results (Fig. 3b).
Ethyne
For ethyne large differences in the C response factors (values between
0.3 and 1.4) were observed for the different stations (Fig. 4). Furthermore,
large variations (up to 0.4) between the two C responses (calibration
standard and NMHC_N2) were evident. Based on the literature
(Dietz, 1967; Scanlon and Willis, 1985; Sternberg et al., 1962) the
effective carbon number is between 2 and 2.6, indicating a higher uncertainty
of the C response for this compound. Thus, in the normalised C response
figures ethyne is expected to be 1 or higher. This was actually observed for
DOU, YRK, and RIG. Deviations between the laboratory standard and the ACTRIS
NMHC_N2 were observed at ZSF, DOU, HPB_A, and FZJ_B. Since at ZSF and FZJ_B observed
deviations were not particular to ethyne but a general phenomenon for many
compounds, both stations are not further considered in this specific
discussion. The normalised C response of ethyne in the calibration standard
of IPR was substantially lower than that of other stations (Fig. 4f).
Together with ethene, ethyne is the most difficult compound to be retained
in air-toxics/air-monitoring traps (Badol et al., 2004). As AUC, HAR, PAL, SMK, ZSF, IPR, and KOS_A employ this
type of traps, a breakthrough might be possible. However as already
discussed, no conclusive behaviour, e.g. higher losses for higher sample
volume and higher trapping temperature, was observed.
The instruments at DOU and HPB_A had in common that both
employ an Al2O3/KCl PLOT column. However, other stations using the
same type of column (YRK, RIG) did not show this feature. We are currently
speculating about slightly different matrices between the calibration standard
and NMHC_N2 causing different interactions with active
sites of the specific PLOT column, resulting in more or fewer losses.
Despite these losses observed in the C response factors, the difference to
the assigned mole fractions were minor for six systems and moderate to
substantial for 7 of 14 systems (larger than 10 % in either or both of the
two NMHC mixtures) (Fig. 2), with often substantially different
deviations for NMHC_N2 and NMHC_air
indicating matrix effects. This shows that it is essential to have ethyne in
the calibration standard for direct calibration and that there is a need for
thorough testing of matrix effects; e.g. real ambient air samples with
higher humidity might result in higher breakthrough.
Alkene artefacts
Alkenes in NMHC_air exhibited largest differences to the
assigned values (Fig. 2), especially pronounced for all systems which used
Nafion® Dryer water traps, including PerkinElmer systems
(Fig. 3d).
When using a Nafion® Dryer to remove humidity from the sample,
potential artefacts in C2–C4 alkenes may occur depending on the
status of the Nafion® Dryer (Gong and Demerjian, 1995;
Plass-Duelmer et al., 2002, and references therein). Butene peaks (for
1-butene, trans-2-butene, and cis-butene) are frequently observed in zero-gas
measurements due to Nafion® Dryer artefacts, and these blank
values have to be subtracted in calibration or ambient air measurements.
Instruments using a Nafion® Dryer reported blank values up to
0.35 nmol mol-1 for C2–C3 alkenes and up to 0.1 nmol mol-1 for
C4 alkenes. Combined with the fact that the mole fractions of
C4–C5 alkenes were in the range of 0.02–0.12 nmol mol-1, it
is expected that substantial differences to the assigned values occur due to
blank issues. For ethene and propene, however, such effects were comparably
small due to much larger mole fractions up to 2.5 nmol mol-1 and blank values
up to 0.25 nmol mol-1. It should be noted that the samples measured here were
not humid and thus the effects of water removal from the sample and the
Nafion® Dryer behaviour cannot fully be assessed. Most
participants were aware of the effects of a Nafion® Dryer and
reported larger uncertainties of their values (Fig. 2).
Losses of aromatic compounds and C6–C8 alkanes
The C responses for the C7–C8 alkanes and for the aromatics were
lower than 1 (Fig. 4), indicating losses in the analytical system. Lower
C responses were observed either in both calibration standard and
NMHC_N2 (Fig. 4; AUC, PAL, SMK, IPR, YRK (except
benzene), RIG, FZJ_B, and less evident in HPB_A) or only in NMHC_N2 (Fig. 4; HAR, DOU,
HPB_B, and FID). This effect was apparent in both
intercomparison loops. This does not seem to be a general C response issue
for aromatics, because in many systems not all aromatics showed a reduced
C response (Fig. 4; KOS (both systems); for benzene: AUC, HAR, HPB (both
systems), RIG, YRK) and several other systems showed only a reduced
C response for NMHC_N2 (Fig. 4; HAR, DOU, and
HPB_B, FID). For these systems, systematic problems like
insufficient desorption from the trap or adsorptive losses in the GC system
can thus be excluded. However, adsorptive losses only in NMHC_N2 might have
occurred due to insufficient equilibration time and the
flushing procedure of the respective pressure regulator and transfer lines.
RIG reported lower C responses compared to the calibration standard for
C6–C8 alkanes and aromatics (Fig. 4k). This was related to
insufficient desorption temperature due to ice on the outer side of the
Peltier-cooled trap which had built up during trapping.
In general, too-low desorption temperature from the trap can be excluded for
the glass bead traps (70–130 ∘C, Table S2). For the
air-toxics traps no losses of aromatics were observed for HAR (trap at
320 ∘C) (Fig. 4a). By contrast, losses prevailed at up to
380 ∘C (IPR), which were consequently not due to too-low
desorption temperature (Fig. 4f). YRK results indicated losses which were
not due to desorption temperature (Carbopack B and Carboxen 1000 at
350 ∘C) but were ascribed to adsorption on newly installed
stainless-steel transfer lines. In the slightly more humid
NMHC_air, YRK achieved relatively higher aromatic mole
fractions compared to the assigned values (Figs. 2–3), indicating humidity
passivation of active surface sites. Thus, losses were only apparent in
their dry calibration standards (Fig. 4g). Compatible with this
observation is the fact that the box plots (Fig. 3b and e) show a
systematic underestimation of aromatics only for NMHC_N2, while for NMHC_air the results are more equally
distributed.
Different hypotheses to explain losses of aromatics and
C6–C8 alkanes did not result in simple and conclusive
explanations. Losses were observed in individual systems when desorption was
not sufficient, when adsorptive losses on inappropriate surfaces like newly
installed stainless-steel lines (heated or not) occurred, or when dry sample
gases were analysed. As long as a decrease in the C response is evident in
both the calibration and NMHC_N2, the submitted mole
fractions did not differ much from the assigned values (e.g. YRK and AUC)
(Figs. 4a, g, 2a, and i).
Chromatographic resolution
Poor peak separation or peak shape (tailing) influences the peak integration
and the results. Both effects can mask other problems if the sample matrix
is rather complex, such as in NMHC_air, where peak overlap is
likely to occur in FID systems. Due to substantially different mole
fractions in ambient air compared to NMHC_N2, the
chromatographic resolution, e.g. peak overlap, for NMHC_air
differed considerably from the characteristics seen in NMHC_N2.
Insufficient C4–C6 peak separation often resulted in mole
fractions outside the 10 % class in NMHC_air, especially for
2-, 3-methylpentane; 2,2-,2,3-dimethylbutane; and 2-methyl-2-butene (Figs. 2 and 3b).
Similar results were already reported in the AMOHA
intercomparsion, where some participants had problems in separating 1-butene
from 1,3-butadiene, cis-2-butene from 2-methylbutane, and isoprene from the
methyl pentanes (Plass-Duelmer et al., 2006; Slemr et al., 2002). The
reasons for the insufficient chromatographic separation include column
degradation (AUC, FZJ_B), inadequate oven temperature programme
(KOS), or non-baseline separation (HPB_A for C5–C6 alkanes)
(for chromatograms see Supplement).
MS systems
Compared to FID systems, MS systems allow a better compound identification
and peak separation at the cost of detector stability. With few exceptions,
HPB_B (MS) reported the NMHCs within the 5 % class (Fig. 2q).
It should be kept in mind that for HPB this was not a blind
intercomparison. However, the ACTRIS mixtures were treated like unknown
samples. Further, HPB_B was not used for the determination of
the assigned values. The instrument is operated with a FID running in
parallel to the MS detector. While the FID revealed stable behaviour of
the instrument, in the MS signal drifts were observed by HPB. Thus, in
routine measurements the MS is tuned weekly and every air sample is
accompanied by a calibration measurement. In fact the HPB_B
(MS) system was the best-performing MS system in this intercomparison,
indicating that NMHC measurements within the 5 % class (ACTRIS DQOs) are
achievable by MS systems.
The relatively large deviations from the assigned reference values in
NMHC_N2 and NMHC_air observed for CMN and
the Medusa systems (Fig. 3) were mainly due to calibration issues
(two-step calibration; see Sect. 3.3). Nevertheless,
the very good repeatability of the Medusa systems indicates the potential to
perform high-quality NMHC measurements within the 5 % class (Fig. 2u–w).
FZJ_A was optimised to perform fast chromatography as the
instrument is employed in aircraft measurements. The sample volume is kept
small in order to reduce the sampling time. With a chromatography time of
3 min, the peak resolution can hardly be compared to the other GC systems.
Nevertheless, FZJ_A performed fairly well for normal alkanes
and aromatics, whereas branched alkanes and alkenes showed larger deviations
from the assigned values (Fig. 2p). Whether this was due to the rather
complex 74-component calibration standard in the 0.1 to 10 nmol mol-1-range
(Apel-Riemer Environmental Inc.) cannot be judged from the available data.
Furthermore, breakthrough of C4 compounds was reported by
FZJ_A. In general, the blank chromatogram revealed many peaks
(chromatogram not shown), which possibly affected the results, especially in
NMHC_air.
For NMHC_N2 the MS systems of PUY and SIR reported most
values with a deviation less than 10 %, whereas for NMHC_
air more of the reported values were outside the 10 % class (Fig. 2r
and s). For PUY this was probably due to drifting calibration standard
measurements (up to 20 %) and poor repeatability; for SIR it was probably
connected to high blanks (relatively high blank values compared to assigned
values (Table S7)) and poor stability of the calibration measurements.
The MS at SMR clearly underestimated the NMHC mole fractions in
NMHC_N2 (Fig. 2t), except for isoprene. In contrast,
SMR reported all values within the 10 % class (Table S3) for
NMHC_air. SMR reported a non-linear calibration curve and low
reproducibility of the submitted calibration measurements, whereas the two
NMHC mixtures were reproducibly measured.
In summary, the calibration, drift, and non-linearity are important issues
for MS systems, which have to be handled with most care when using a GC-MS
system for the measurements of NMHCs.
Other issues
During the ACTRIS intercomparison only very dry NMHC mixtures were analysed,
and therefore a full performance assessment of water management systems
(Nafion® Dryers, cold traps, or hydrophobic adsorbents at room
temperature) cannot be made. Nevertheless, some basic conclusions can be
drawn. The cold-trap systems used by YRK and HPB_A (Table S2a) exhibited no artefacts. Such systems sometimes have a large internal
volume for water removal, and, whilst very suitable for online measurements,
they are not so well suited for conditions where limited flushing volume is
an issue, e.g. when analysing limited sample volumes. In this
intercomparison, where dry samples were analysed, this method was superior
compared to Nafion® Dryers where alkene artefacts are observed
(see Sect. 3.4.3). The use of hydrophobic adsorbents at room
temperature indicated no problems for HPB_B. However, the
weak adsorbents used in HPB_B are not appropriate for the
adsorption of low-boiling NMHCs (C2–C3).
Ozone management was not in the scope of this ACTRIS intercomparison study,
and, furthermore, ozone is rapidly destroyed on metal surfaces; thus no
ozone was present in the cylinders.
One specific issue was associated with the ZSF system, which had been
brought to 2650 m a.s.l. shortly before this intercomparison. The reduced
atmospheric pressure might have caused changes in the chromatographic
conditions which had not been adjusted at the time of the measurements.
PTR-MS results
The two NMHC mixtures were analysed with the PTR-MS systems of SMR II and
WCC-VOC. Isoprene in NMHC_N2 fitted well inside the
5 % class, whereas isoprene in NMHC_air, toluene, and
benzene in both NMHC mixtures were reported outside the 10 % class.
Detailed results and some explanations are given in the Supplement.
Comparison with previous intercomparisons
During AMOHA phase 4 (Plass-Duelmer et al., 2006) and NOMHICE phase 4 (Apel
et al., 2003) measurements of whole air and synthetic test samples were
compared. As outlined in the Introduction, conditions were different and,
accordingly, these studies cannot be compared with the ACTRIS
intercomparison in the strictest sense. However, the whole air test samples
supplied by canisters (NOMHICE and AMOHA phase 4 part 1) or sampled into
individual canisters by participants (AMOHA phase 4 part 2) had a similar
complexity to the whole air sample used in the actual intercomparison
(e.g. 20–50 % of NMHCs < 0.1 nmol mol-1). Originally introduced by
Apel et al. (2003) and modified by Plass-Duelmer et al. (2006), a ranking procedure
defining a score for quality and quantity of the provided results by each
lab was introduced:
Rank=n<+10%+0.75+10%<n<+25%+0.5+25%<n<50%N+0.3NX-0.3(k),
where n is the number of reported values falling into the given reference
intervals, N is the total number of compounds reported, X is the total
number of compared compounds, and k=∑[xref-1]N the
averaged deviation of the reported values x from the reference values “ref”. For
reference values below 0.05 nmol mol-1 the bracket term is taken as
k=∑x-ref50pmol/molN (for details, see
Plass-Duelmer et al., 2010). This “Rank” score can reach a maximum of 1.3
(all compounds measured and correct within 10 %) down to negative numbers
for substantial deviations from the reference (large k). Minimum, median, and
maximum ranks, respectively, for NOMHICE part 4 are 0.23, 0.81, and 1.16 (37
compounds); for AMOHA 4 phase 1 are 0.82, 1.02, and 1.14 and for phase 2 -0.31, 1.0, and
1.12; and in this study for NMHC_air are 0.49, 1.03, and 1.19 (the
latter excludes results by the reference laboratories). The best-performing
laboratories were in all studies similar at 1.14–1.19, the mid-quality
increased from NOMHICE to AMOHA and this study, and the lowest-performing
labs were best in AMOHA 4 phase 1 and ACTRIS. If we interpret the results as
development over time, there is a tendency of improvement of the
lower-performing labs, whereas the medium to best laboratories perform essentially
unchanged over the last 15 years. However, AMOHA was a “learning”
intercomparison with phases of increasing complexity and feedback to the
participants in between, which in the end yielded the best performance for
AMOHA 4 phase 1. Compared to this, ACTRIS may be seen as a snapshot with
reasonable performance, as well as highlighting the need of more regular
feed-back to the stations.
Conclusions
In the NMHC intercomparison exercise performed in the European
infrastructure project ACTRIS, a significant number of instruments were
capable of measuring NMHC in nitrogen (NMHC_N2) fairly
accurately: 88 % of the submitted NMHC values were within 10 %, and 58 %
even within 5 %, of the reference values, which are the DQOs of ACTRIS with
respect to the deviation to assigned values. It should be noted that
NMHC_N2 was almost identical to the NPL calibration
standards used at the stations and a substantial number of deviations was
not expected. Participants generally achieved very good repeatability in
their measurements in line with the objectives of 2 %.
In compressed whole air (NMHC_air) generally more frequent
and larger deviations to the assigned values compared to NMHC_
N2 were observed (77 % of the reported values were within 10 %, but
only 48 % were within 5 %). It should be noted that
this comparison uses test gases which do only partly reflect the complexity
of ambient air, e.g. no ozone and low water content. On the one hand, an
important contributor to insufficient results in NMHC_air was
blank issues observed in zero-gas measurements in some of the systems,
especially those using a Nafion® Dryer. On the other hand,
systems with cold traps exhibited smaller blank issues. The study highlights
the importance of good zero-gas measurements to determine realistic blank
values to be subtracted from measurement results.
Another factor contributing to the poorer NMHC_air results is
the reduced chromatographic resolution, particularly in the range of
C4–C6 compounds. Generally, those systems using direct
calibrations in the nanomole-per-mole range achieved better results than those using
whole air calibration standards. This confirms and emphasises the results
found in the AMOHA and GAW intercomparisons (Plass-Duelmer et al.,
2006; Rappenglueck et al., 2006; Slemr et al., 2002) as the two-step
calibration and more complex matrix in whole air calibration standards
introduce additional potential errors. For ethyne, losses may occur due to
breakthrough in the adsorption trap, and yet unexplained reduced C response
was observed in several systems. This intercomparison supports previous
studies, finding that it is essential to calibrate ethyne directly and carefully
characterise the response of the system in dry calibration standard and
humid ambient air sample matrices. The use of FID C responses proved to be a
powerful tool because it helped to identify problems in a number of
analytical systems. However, as long as a system behaves similarly in
different sample gas matrices, deviations in the C response may cancel,
resulting in correct mole fractions. But this requires thorough testing of
the respective GC systems. Breakthrough is generally an issue for
C2–C3 hydrocarbons in adsorptive traps. Deviations from the
expected C responses for low-boiling hydrocarbons were mainly observed in
systems using the PerkinElmer Thermodesorber with air-toxics/air-monitoring
traps. Whether these deviations were due to breakthrough or split injection
issues could not be resolved. Almost all of the participating instruments
indicated losses of C7–C8 aromatic compounds, most probably due to
adsorptive losses. Despite such losses, many participants achieved good
results for aromatics, but overall deviations were slightly larger than for
other compound groups. On average, FID systems achieved better results, but
good measurements were also obtained with GC-MS systems; however, since the
MS is less stable than FID, more frequent calibrations are required.
Another important result of this intercomparison is that in more than 25 %
of the reported results uncertainties were substantially underestimated and
major uncertainty contributions were not correctly assessed. Last but not
least, erroneous results were also caused by the occasionally inattentive
data submission, with mistakes and incomplete information. While these
problems were detected and resolved in the relatively small data set of this
intercomparison, it is an issue with submission of insufficiently controlled
data sets to public data centres and end-users.
The PerkinElmer Online Ozone Precursor Analyzer is the only
commercially available instrument used by five participants in this
intercomparison. Although these were not among the best performing in this
study, reasonable results can be achieved. We demonstrated that the ACTRIS
DQOs, albeit demanding, can be achieved with state-of-the art measurement
systems. However, equally important for achieving high-quality results are
experienced operators, comprehensive quality assurance and quality control,
well-characterised systems, and sufficient manpower to operate the systems
and evaluate the data.