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Innsbruck, Austria

Kaser L.,University of Innsbruck | Kaser L.,U.S. National Center for Atmospheric Research | Karl T.,U.S. National Center for Atmospheric Research | Karl T.,University of Innsbruck | And 11 more authors.
Atmospheric Chemistry and Physics | Year: 2013

We present the first eddy covariance flux measurements of volatile organic compounds (VOCs) using a proton-transfer-reaction time-of-flight mass spectrometer (PTR-TOF-MS) above a ponderosa pine forest in Colorado, USA. The high mass resolution of the PTR-TOF-MS enabled the identification of chemical sum formulas. During a 30 day measurement period in August and September 2010, 649 different ion mass peaks were detected in the ambient air mass spectrum (including primary ions and mass calibration compounds). Eddy covariance with the vertical wind speed was calculated for all ion mass peaks. On a typical day, 17 ion mass peaks, including protonated parent compounds, their fragments and isotopes as well as VOC-H+-water clusters, showed a significant flux with daytime average emissions above a reliable flux threshold of 0.1 mg compound m-2 h-1. These ion mass peaks could be assigned to seven compound classes. The main flux contributions during daytime (10:00-18:00 LT) are attributed to the sum of 2-methyl-3-buten-2-ol (MBO) and isoprene (50%), methanol (12%), the sum of acetic acid and glycolaldehyde (10%) and the sum of monoterpenes (10%). The total MBO + isoprene flux was composed of 10% isoprene and 90% MBO.

There was good agreement between the light-and temperature dependency of the sum of MBO and isoprene observed for this work and those of earlier studies. The above canopy flux measurements of the sum of MBO and isoprene and the sum of monoterpenes were compared to emissions calculated using the Model of Emissions of Gases and Aerosols from Nature (MEGAN 2.1). The best agreement between MEGAN 2.1 and measurements was reached using emission factors determined from site-specific leaf cuvette measurements. While the modeled and measured MBO + isoprene fluxes agree well, the emissions of the sum of monoterpenes is underestimated by MEGAN 2.1. This is expected as some factors impacting monoterpene emissions, such as physical damage of needles and branches due to storms, are not included in MEGAN 2.1.

After a severe hailstorm event, 22 ion mass peaks (attributed to six compound classes plus some unknown compounds) showed an elevated flux for the two following days. The sum of monoterpene emissions was 4-23 times higher compared to emissions prior to the hailstorm while MBO emissions remained unchanged. The monoterpene emission (in mg compound m−2) during this measurement period is underestimated by 40% if the effect of this disturbance source is not considered. © 2013 Author(s). Source


Miekisch W.,University of Rostock | Herbig J.,Ionimed Analytik GmbH | Schubert J.K.,University of Rostock
Journal of Breath Research | Year: 2012

Most - if not all - potential diagnostic applications in breath research involve different marker concentrations rather than unique breath markers which only occur in the diseased state. Hence, data interpretation is a crucial step in breath analysis. To avoid artificial significance in breath testing every effort should be made to implement method validation, data cross-testing and statistical validation along this process. The most common data analysis related problems can be classified into three groups: confounding variables (CVs), which have a real correlation with both the diseased state and a breath marker but lead to the erroneous conclusion that disease and breath are in a causal relationship; voodoo correlations (VCs), which can be understood as statistically true correlations that arise coincidentally in the vast number of measured variables; and statistical misconceptions in the study design (SMSD). CV: Typical confounding variables are environmental and medical history, host factors such as gender, age, weight, etc and parameters that could affect the quality of breath data such as subject breathing mode, effects of breath sampling and effects of the analytical technique itself. VC: The number of measured variables quickly overwhelms the number of samples that can feasibly be taken. As a consequence, the chances of finding coincidental; voodoo correlations grow proportionally. VCs can typically be expected in the following scenarios: insufficient number of patients, (too) many measurement variables, the use of advanced statistical data mining methods, and non-independent data for validation. SMSD: Non-prospective, non-blinded and non-randomized trials, a priori biased study populations or group selection with unrealistically high disease prevalence typically represent misconception of study design. In this paper important data interpretation issues are discussed, common pitfalls are addressed and directions for sound data processing and interpretation are proposed. © 2012 IOP Publishing Ltd. Source


Beauchamp J.,Fraunhofer Institute for Process Engineering and Packaging | Beauchamp J.,Ionimed Analytik GmbH | Frasnelli J.,University of Dresden Medical School | Frasnelli J.,University of Montreal | And 6 more authors.
Measurement Science and Technology | Year: 2010

The performance of a commercial olfactometer instrument, which produces odorant pulses of defined duration and concentration, was characterized using proton-transfer-reaction mass spectrometry (PTR-MS). Direct coupling of the PTR-MS instrument with the olfactometer enabled on-line evaluation of the rapidly delivered aroma pulses. Tests were made with a selection of four odorous compounds: hydrogen sulfide, 2,3-butanedione, ethyl butanoate and ethyl hexanoate. Odour concentrations and stimulus durations for these compounds were monitored directly at the olfactometer delivery port via the respective PTR-MS signals. The performance of the olfactometer was found to be dependent on pulse duration. A decrease over time in maximum intensity for identical pulses over an extended duration showed headspace concentration depletions for compounds sourced from a water solution, indicative of gas/liquid partitioning. Such changes were not present using odours sourced from a cylinder or, presumably, when using liquid odours at neat concentrations. In conclusion, while an olfactometer provides stimuli with good reproducibility, the concept is subject to certain limitations that must be appreciated by the experimenter for accurate application of this technique. © 2010 IOP Publishing Ltd. Source


Beauchamp J.,Ionimed Analytik GmbH | Beauchamp J.,Fraunhofer Institute for Process Engineering and Packaging | Herbig J.,Ionimed Analytik GmbH | Herbig J.,IONICON Analytik GmbH | And 5 more authors.
Measurement Science and Technology | Year: 2013

The accuracy of quantitative volatile organic compound (VOC) detection by proton-transfer-reaction mass spectrometry (PTR-MS) is substantially enhanced if the instrument is calibrated. Although quantification of a compound is in principle possible by mathematical methods based on kinetic theory, the underlying picture can become complicated depending on the gas matrix, leading to error. A simple, reliable method to overcome this is to calibrate the instrument using standard gas mixtures containing VOCs at known concentrations, which enables the compound-dependent sensitivity of the instrument to be determined. A dynamic gas calibration unit was developed to generate variable but known quantities of selected standard compounds in a carrier gas of variable relative humidity (RH; up to 100% at 37 °C) and CO2 content (≤10%v) to reflect the changing conditions of a breath-gas sample matrix. Besides individual compound sensitivities, calibration also yields the limits of detection and quantification of the experimental method. Extensive calibrations of PTR-MS with several breath-relevant compounds were made at varying RH and CO2. Gas matrix effects of several compounds were negligible when appropriate mass-dependent transmission correction and normalization to the primary ions (m/z 21 and m/z 37) were applied. Two compounds are discussed in particular, namely acetaldehyde, which interferes with a CO2-related background, and formaldehyde, which shows a nonlinear dependence on sample gas humidity. © 2013 IOP Publishing Ltd. Source


Singer W.,Ionimed Analytik GmbH | Herbig J.,Ionimed Analytik GmbH | Gutmann R.,Ionimed Analytik GmbH | Winkler K.,Ionimed Analytik GmbH | And 2 more authors.
American Laboratory | Year: 2011

Biological systems produce a large variety of volatile metabolites. A sensitive and fast analytical instrument is needed to measure these VOCs in real time. PTR-MS technology is ideally suited for this task. The authors have presented a variety of PTR-MS application examples in the fi elds of medicine and biotechnology. The applications in medicine-based on exhaled breath analysis- can be used for diagnosis of disease, or to monitor isolated metabolic processes via ingestion of 13C-labeled compounds, or to study human exposure to harmful volatile substances, e.g., those present at the workplace. Application of PTR-MS in biotechnology allows monitoring of the composition of biogases or fermentor off-gas. Monitoring biogases in "white biotech" allows detection of u nwanted compounds such as silicon- or sulfur-containing substances. In the "red biotech" application, the gas-phase composition of VOCs in the fermentor headspace is analyzed to obtain more in-depth information on the present fermentation status, which can then be utilized for fermentation process control. (White biotechnology is the application of biotechnology for industrial purposes. Red biotechnology refers to pharmaceutical and medical biotechnology.) In contrast to conventional gas analytical techniques, which require sample preparation and off-line measurements, or are simply not sensitive enough, PTR-MS systems offer essential advantages. All of these applications benefi t from the ultrasensitive, realtime analysis and quantifi cation of VOCs offered by proton transfer reaction mass spectrometry. Source

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