Proton transfer reaction mass spectrometry (PTR-MS) and gas chromatography mass spectrometry GC-MS) are commonly used methods for automated in situ
measurements of various volatile organic compounds (VOCs) in the atmosphere.
In order to investigate the reliability of such measurements, we operated
four automated analyzers using their normal field measurement protocol side
by side at a boreal forest site. We measured methanol, acetaldehyde, acetone,
benzene and toluene by two PTR-MS and two GC-MS instruments. The measurements
were conducted in southern Finland between 13 April and 14 May 2012. This
paper presents correlations and biases between the concentrations measured
using the four instruments. A very good correlation was found for benzene and
acetone measurements between all instruments (the mean
Volatile organic compounds (VOCs) play a crucial role in atmospheric
chemistry
In remote and rural locations, biogenic compounds such as isoprene or
monoterpenes dominate the concentrations among reactive VOCs. Oxygenated VOCs
(OVOCs) are also significant
A variety of models are used to study the atmospheric processes of VOCs. Some
simulate the VOC emissions from vegetation
Often, VOC concentrations have been measured by collecting samples into
canisters or onto adsorbents with subsequent off-line analysis with gas
chromatography mass spectrometry (GC-MS) or gas chromatography connected to a
flame ionization detector
For automated VOC concentration measurements, in situ GC-MS, proton transfer
reaction mass spectrometer (PTR-MS) and other chemical ionization-mass
spectrometers (CIMS) have been used
Typically, a long-term measurement set-up consists of a single analyzer, which
is regularly calibrated. Occasionally these instruments are compared with
each other either in the laboratory or in the field. The laboratory
comparisons are usually conducted by measuring VOC concentrations of a known
standard mixture
The main aim of this study was to evaluate how reliable the in situ
measurements of aromatic and oxygenated VOCs are when a single stand-alone
instrument is used. This was achieved by comparing VOC concentration
measurements of four in situ instruments: two PTR-MSs and two GC-MSs. In
order to have a comparison as realistic as possible, no data were rejected from
the analysis based on bad correlation of the data between the instruments.
Thus, only external reasons have been used to filter the data prior the
analysis. This study was part of ACTRIS (Aerosols, Clouds and TRace gases
research InfraStructure Network,
PTR-MS1, GC-MS1 and GC-MS2 shared the same inlet, which was sampling ca. 10 m above the ground.
The measurements were conducted between 13 April and 14 May 2012 at the SMEAR
II site (Station for Measuring Forest Ecosystem-Atmosphere Relations,
61
The concentrations and sources of oxidized and aromatic VOCs at the site have
previously been characterized by
The concentrations were measured with two different gas chromatography mass
spectrometers (GC-MS1 and GC-MS2), and two similar proton transfer reaction
quadrupole mass spectrometers, which are hereafter called PTR-MS1 and
PTR-MS2. Both PTR-MS instruments were operated by the University of Helsinki,
the GC-MS1 was operated by Empa (Switzerland) and the GC-MS2 was operated by
the Finnish Meteorological Institute. The two GC-MS instruments and the
PTR-MS1 used the same ca. 20
The PTR-MS2 is part of the permanent instrumentation of the site and sampled
air from a tower about 30
Each instrument measured more than 20 different compounds. However, only methanol, acetaldehyde, acetone, benzene and toluene were measured with both PTR-MS instruments and at least with one GC-MS. As such, they were selected for the comparison study.
The proton transfer reaction is a chemical ionization technique in which VOCs
are ionized by proton transfer from hydronium ions (
The VOCs gain one proton (
Hydronium primary ions may become hydrated and thus form
The drift tube pressures and voltages of the two PTR-MS instruments were not
the same during this experiment, as the instrument parameters were optimized
individually. PTR-MS1, which is the newest of the two PTR-MS instruments, was
set to have a drift tube pressure of 2.2
A thorough description of the VMR calculation procedure is given by
The signals of primary ions are measured during each measurement cycle,
but in order to maximize the lifetime of the detector, the count rates of
the primary ions were measured at the Instrumental background signal can be caused by, for example, desorption of
impurities inside the instrument or inside the inlet system, manifesting as a
notable offset in the count rates of many of the VOCs
In order to quantify the sensitivities for the measured compounds,
calibrations were done using an automatic calibration method using mixing
units. These mixing units dilute a standard gas flow of ca.
6
Both instruments were calibrated three times during the campaign, using the
same gas standard mixture (Apel-Riemer Environmental Inc., CO, USA),
consisting of 13 different VOCs including methanol, acetaldehyde, acetone,
benzene and toluene in the range of 0.84–1.14
The detection limits of the PTR-MS instruments were calculated as 3 times
the SD (
The analysis of VOCs with gas chromatographic techniques relies on the separation of the VOC species in a chromatographic column. Traditionally, the samples have been collected into a canister or adsorbent tubes and analyzed off-line in the laboratory. With more recent in situ GC-MS systems, the samples are collected directly into adsorbent traps at the measurements site, from which they are desorbed by heating the trap in the gas chromatograph. After separating the compounds by their retention times in the chromatographic columns, they are ionized by electron ionization and detected individually with a quadrupole mass spectrometer.
The instrumental set-up of the adsorption–desorption system coupled to a gas
chromatograph-mass spectrometer (GC-MS1) is described in detail by
Methanol was only recovered at 45 %, and this was corrected for the measurement campaign. The detection limit for each compound was calculated as 3 times the SD of five zero air samples.
Measurements of GC-MS2 were conducted using an in situ thermal desorption
unit (Markes' Unity, Markes International Ltd, UK) with a gas chromatograph
(Agilent 7890A, Agilent Technologies, CA, USA) and a mass spectrometer
(Agilent 5975N, Agilent Technologies, CA, USA). The column used was the
60 m long DB-5 with an inner diameter of 0.235
The uncertainties of the VOC concentrations measured by a PTR-MS or a GC-MS
are affected by several factors. The total uncertainty (
The total measurement uncertainty of PTR-MS consists of two parts; the
uncertainty of the signal (
The measured signal and the background signal are normalized with the primary
ion signal for the VMR calculation. The normalized background signal
(
The uncertainty of the signal in Eq. (
The measured count rates (cps, counts per second) and the count rates of the
zero measurement were converted to counts (
In order to normalize
The uncertainty of the calibration (
PTR-MS sensitivity for a certain compound is determined by calibrating the
instrument with a known concentration of that compound. When the ratio of the
sensitivity and its uncertainty is assumed to be constant, the sensitivity's
uncertainty can be determined from the SD of a series of calibrations,
performed using the same instrument settings. The laboratory tests for the
similarity of the two calibration methods were done under the same instrument
conditions, making the relative sensitivity uncertainty (
By combining Eqs. (
For
Total uncertainties of 1 h were calculated for PTR-MS1 and PTR-MS2, as the data comparison was mostly done using 1-hour averages.
The total uncertainty is divided into two components: precision (
The precision is calculated as
The systematic error of GC-MS1 includes the following: the error due to uncertainty of the
calibration standard's mole fractions (
The systematic error due to the calibration gas uncertainty (
The systematic integration error (
Total relative uncertainties of the measured compounds for all the instruments. The uncertainty values of PTR-MS1 and PTR-MS2 are averages of hourly total uncertainties. For GC-MS1 and GC-MS2, the total uncertainties are for one measurement point.
The precision of acetone, acetaldehyde, benzene, and toluene was around
5 %, whereas the precision for methanol was 10 %. The total expanded
uncertainty was around 15 % for acetone, benzene, and toluene, 23 %
for acetaldehyde, and 28 % for methanol (Table
Total uncertainty (
The concentrations measured with different instruments had temporal
discrepancies, as all of the instruments had different sampling intervals and
data integration times. PTR-MS1 measured several compounds sequentially, each
with a dwell time of 2
In order to make the instrument comparison as consistent as possible, the measurements by the two PTR-MS instruments were averaged for the same time periods with each other and with the GC-MS instrument whenever possible. For the comparison between the two PTR-MS instruments and PTR-MS1 and GC-MS2, hourly averages were used. For the comparison between PTR-MS1 and GC-MS1, PTR-MS1 data were averaged for the same 12 min time periods when GC-MS1 samples were taken.
Uncertainty values for a single measurement point for PTR-MS1 and
PTR-MS2. Uncertainty of the signal statistics (
The detection limits of all the instruments were determined as 3 times the SD of the instrument noise (i.e. the zero air sample concentration). Values below the detection limits were removed from the GC-MS data. When hourly or 12 min average values were calculated from PTR-MS data, the averages were calculated for all data points. If an average value was below the detection limit, it was removed from further analysis. Data points below the detection limits were not removed before average value calculation, in order to avoid biasing the average.
The sensitivities and uncertainties of sensitivities of the two PTR-MS instruments and the performance of the two different calibration methods were evaluated in separate laboratory tests after the field campaign. The laboratory tests were done by performing a series of calibrations with both automatic and manual calibration methods, while keeping all instrument parameters constant. The same calibration tests were performed separately for both PTR-MS instruments. A constant ratio was assumed for the sensitivity and its uncertainty, thus the latter was determined as the SD of the sensitivity measurement series. The results of the calibration tests are presented in Table A1 in the Appendix.
Generally, the PTR-MS2 had higher sensitivity than the PTR-MS1 for all
compounds except isoprene. This was particularly the case for the larger
molecules (xylenes, trimethylbenzene, naphthalene and
For most of the compounds, calculated sensitivities of both automatic and manual calibration methods agreed within the sensitivity uncertainty (Table A1). However, for methanol and methyl vinyl ketone, the sensitivities obtained with the two different methods were divergent for both PTR-MS instruments. For acetonitrile, the two calibration methods resulted in different sensitivities in the case of PTR-MS2. For naphthalene, the two methods resulted in different sensitivities in the case of PTR-MS1.
The sensitivity uncertainties of both calibration methods were lower for PTR-MS2. Regarding the manual calibration method, the pump used to generate zero air for the calibration of PTR-MS1 caused some fluctuation to the zero air flow and thus increased the sensitivity variation (i.e. the SD) between different calibrations. The uncertainty of sensitivity for methanol obtained with the automatic calibration system was clearly higher than the uncertainties for all other compounds, 63 % for PTR-MS1 and 25 % for PTR-MS2.
Methanol calibration is difficult due to its strong interaction with metal
surfaces, as in mass flow controllers
In the case of PTR-MS1, the sensitivity uncertainties were higher than the
uncertainties of the signal statistics or the concentration uncertainty of
the calibration gas standard (Table
Concentrations of methanol, acetaldehyde, acetone, benzene and toluene measured with PTR-MS1, PTR-MS2, GC-MS1 and GC-MS2 and ambient temperature and relative humidity during the measurement campaign. Hourly averages were calculated for the PTR-MS instruments. For the GC-MS instruments, all data are shown.
The total uncertainties of all instruments were below 30 %, with the
exception of the methanol uncertainty of PTR-MS1 and the toluene uncertainty
of PTR-MS2 (Table
Daily median temperature, relative humidity and concentrations of compounds measured with PTR-MS1, PTR-MS2, GC-MS1 and GC-MS2 during the measurement campaign.
For acetone and acetaldehyde, the concentration uncertainties of the PTR-MS instruments were lower than those of the GC-MS instruments. In the case of methanol, GC-MS1 and PTR-MS2 had similar uncertainties, while PTR-MS1 had a very high total uncertainty (61 %). The high methanol uncertainty of PTR-MS1 was a consequence of the high sensitivity uncertainty.
The time series of methanol, acetaldehyde, acetone, benzene and toluene
concentrations measured with all instruments are presented in
Fig.
The highest concentrations of methanol, acetone and benzene were measured with PTR-MS2, while GC-MS2 measured systematically lower concentrations of acetone and benzene than the other three instruments. In the case of acetone, the lower concentrations measured by GCMS2 were probably due to the 60 min sampling time. This may have been too long, leading to break through of acetone in the microtrap. Consequently, the absolute values of the GC-MS2 were underestimations, but the concentrations trends were still observed.
The measured acetaldehyde concentrations had fairly small temporal variation. Additionally, the concentration trends measured with the three instruments are divergent until the beginning of May. After the 1 May, PTR-MS1 and GC-MS1 measurements agree rather well.
Toluene concentrations were mostly below the detection limits of the PTR-MS
instruments. This is clearly visible in Fig.
The different location of the PTR-MS2 inlet could partly explain the higher
concentrations observed for methanol, acetaldehyde and acetone. Acetaldehyde
and acetone are formed in the oxidation of, for example, monoterpenes and
methylbutenol
Benzene and toluene observed at the SMEAR II site originate from local
traffic and small-scale wood combustion, as well as from distant
anthropogenic sources
Toluene concentrations were mostly below the detection limits of the PTR-MSs.
This is clearly visible in Fig.
In order to analyze in more detail how consistent the concentration
measurements were, box plots representing the medians and quartiles were drawn
for all compounds (Fig.
Correlations between different instruments were studied using scatter plots
and by calculating Pearson's correlation coefficients (
Additionally, the overall consistency of the concentration measurements of
the four different instruments was investigated by calculating: (1) the mean
of all correlation coefficients, (2) the root mean square (RMS) difference of
the scatterplot slopes from
Median concentrations and 25th and 75th percentiles of methanol, acetone, acetaldehyde, benzene and toluene. Red plus signs show the arithmetic mean concentrations. The whiskers illustrate the most extreme data points, which are not considered outliers (99.3 %) and the notches show the 95 % confidence interval of the median value. In order to make the figure more clear, outliers are not shown. The numbers next to the instrument names indicate how many outlier points were removed in each case.
Generally, the measurements of PTR-MS2 were most scattered for all the
compounds (Fig.
In the following sections, the concentration distributions and correlations between different instruments are discussed separately for all five compounds.
Comparison of volume mixing ratios of methanol, acetaldehyde, acetone, benzene and toluene measured by four different instruments. PTR-MS1 was compared against all three other instruments and the two GC-MSs were compared to each other. Solid lines represent linear fits and the number in brackets goodness of the fits normalized to the number of data points.
Methanol was measured with three out of four instruments: PTR-MS1, PTR-MS2
and GC-MS1. There were large differences in the concentration ranges of the
methanol measurements (Fig.
Statistical parameters of the correlation analysis for the measured
compounds.
As Fig.
For methanol the correlation coefficients of this study agreed with those
found in prior research.
Methanol measurements are known to encounter some challenges. Calibrating
PTR-MS for methanol is difficult because methanol deposits on the metal
surfaces of the calibration system
The solubility of methanol in water can introduce problems to the GC-MS
measurements, because when water is removed from the sample, part of the
methanol could be removed as well. To correct for the methanol loss in water
trap we used information from two previous intercomparison campaigns. A
laboratory intercomparison campaign was conducted in 2005 in Germany, during
which OVOCs were measured with several GC-MS instruments at the SAPHIR
chamber at Forschungszentrum Jülich
Possible causes for the discrepancies between the two instrument pairs were
investigated by comparing the differences in the measured VOC concentrations
against meteorological parameters temperature, relative humidity (RH), and
wind direction and speed. In case of the two PTR-MS instruments none of these
meteorological parameters explained the discrepancy between the instruments.
The difference between methanol concentrations measured by PTR-MS1 and GC-MS1
seems to depend slightly on RH, (Fig.
Relative difference of the methanol measurements with PTR-MS1 and GC-MS1 against RH.
Three instruments out of four, PTR-MS1, PTR-MS2 and GC-MS1, measured
acetaldehyde. The concentration range was very similar for all the
instruments, between 0.3 and 0.6
The correlations of this study were weaker than the correlation reported by
Relative difference of the acetaldehyde measurements with PTR-MS1 and PTR-MS2 against RH.
Temperature and wind properties did not explain any of the concentration
divergences between different instruments. Instead, concentration difference
of both instrument pairs was observed to depend on RH. This phenomenon was
clearly stronger between PTR-MS1 and PTR-MS2 than between PTR-MS1 and GC-MS1
(Fig.
PTR-MS measures acetaldehyde with a mass of 45
Acetone concentrations were measured with all four instruments. GC-MS1 and
PTR-MS2 measured similar acetone concentrations, ranging from 0.9 to
1.3
As in previous comparison studies
Root mean square (RMS) differences of the scatter plot slopes from
PTR-MS measurements of acetone can be affected by propanal, which is detected
at the same mass (59
The measured benzene concentrations of all four instruments were in good
agreement, as found in previous studies by
In general, the correlations between different instrument pairs were good.
The two GC-MS instruments had the highest correlation (0.92), yet the slope
was not close to unity (0.77). The low slope value could be due to different
sampling times of these instruments. However, as benzene does not have local
sources at SMEAR II, changes in benzene concentration are slow and different
sampling times should not have a great effect on the measured concentrations.
PTR-MS1 correlated equally well with both PTR-MS2 and GC-MS2 (0.88 and 0.89
respectively). The slope of PTR-MS1 vs. GC-MS2 was reasonably good (0.84),
while the slope between the two PTR-MS instruments was rather high (1.38).
Between PTR-MS1 and GC-MS1, the correlation was 0.84 and the slope was very
good (0.99). The average correlation coefficient of benzene was the same as
the mean
Good correlations were expected for benzene, as the temporal and spatial
changes in benzene concentration are low at the site and there are no known
problems concerning benzene measurements with either GC-MS or PTR-MS. PTR-MS
measurements at mass 79
Toluene was measured with all four instruments. The concentration ranges of
PTR-MS1, GC-MS1 and GC-MS2 were the same from 0.02 to 0.05
Although the concentrations of the three instruments agreed well, their
correlation values were only moderate.
In the study by
Although, large measurement discrepancies were found between different
instruments, the explanation for this was unknown. For example,
meteorological parameters had no correlation with the concentration
differences of different instruments. It has been suggested that a p-cymene
fragment is detected at the same mass (93
Ambient concentrations of methanol, acetaldehyde, acetone, benzene and toluene were measured using two PTR-MS instruments and two GC-MS instruments at a rural boreal forest site in the spring of 2012. Additionally, two different calibration methods, automatic and manual, were tested for the PTR-MS instruments. The calibration tests showed that both calibration methods resulted in similar sensitivities for acetaldehyde, acetone, benzene and toluene. For methanol, sensitivities obtained with the automatic method resulted in lower apparent sensitivities than the manual calibration method did. Also the sensitivity uncertainties of both PTR-MS instruments were higher for methanol than for the other compounds.
Very good correlation was found for benzene and acetone measurements between
all instrument pairs. The mean correlation coefficient was 0.88 for both
compounds. In the case of acetone, the RMS difference from the
The correlation coefficients of acetaldehyde and toluene were quite far from unity, with respective averages of 0.50 and 0.62. The cause of the bad correlation in the case of acetaldehyde remains unresolved. Toluene concentrations were below the detection limits of the PTR-MS instruments for a considerable amount of the time, which biased the concentrations towards higher values and also reduced the amount of data points used for analysis.
Methanol measurements showed a robust correlation between the instruments.
However, the slope values were far from unity, with an RMS difference of 0.87
from the
This study raises a few open questions yet to be answered. These include the following:
the reasons for major biases between instruments for many compounds. This may be due to the
materials used in different set-ups, but the reason remains unknown for now. the reason for RH dependence of the differences in acetaldehyde measurements. the constancy of the methanol loss correction in the GC-MS1. It is assumed to be constant,
which may not be the case.
Technical recommendations arising from this experiment include the following:
GC-MS sampling time must be adjusted to prevent breakthrough of any compound of interest.
Suitable sampling time must be determined individually for each compound and
the shortest time used for the measurement protocol. for the PTR-MS, the time used for the calibration must be long enough to reach the stable
regime. The length of the calibration period must be determined individually
for all compounds in the calibration gas, and the actual calibration time is
determined as the longest.
The results of this study show that when doing long-term measurements of ambient air, occasional comparison measurements are needed to evaluate the measured concentrations and to quantify the uncertainties, even if the instrument is calibrated regularly.
Results of the PTR-MS calibration tests. “Manual calibration
method” (MCM) refers to the system in which the calibration gas standard and
zero air flows are controlled manually with a pressure regulator and needle
valves
This work was financially supported by ACTRIS Research Infrastructure Project, which is supported by the European Union Seventh Framework Programme (FP7/2007-2013) under grant agreement no. 262 254, from the ACTRIS TNA “OVOC analysis for Total Observed Organic Carbon determination (OVOC-TOOC)” and from the Academy of Finland Center of Excellence program (projects 1118615 and 272041). We thank Rae Ellen Bichell for proofreading the manuscript. Edited by: N. Yassaa