Alignment of retention time obtained from multicapillary column gas chromatography used for VOC analysis with ion mobility spectrometry

Multicapillary column (MCC) ion mobility spectrometers (IMS) are increasingly in demand for medical diagnosis, biological applications and process control. In a MCC-IMS, volatile compounds are differentiated by specific retention time and ion mobility when rapid preseparation techniques are applied, e.g. for the analysis of complex and humid samples. Therefore, high accuracy in the determination of both parameters is required for reliable identification of the signals. The retention time in the MCC is the subject of the present investigation because, for such columns, small deviations in temperature and flow velocity may cause significant changes in retention time. Therefore, a universal correction procedure would be a helpful tool to increase the accuracy of the data obtained from a gas-chromatographic preseparation. Although the effect of the carrier gas flow velocity and temperature on retention time is not linear, it could be demonstrated that a linear alignment can compensate for the changes in retention time due to common minor deviations of both the carrier gas flow velocity and the column temperature around the MCC-IMS standard operation conditions. Therefore, an effective linear alignment procedure for the correction of those deviations has been developed from the analyses of defined gas mixtures under various experimental conditions. This procedure was then applied to data sets generated from real breath analyses obtained in clinical studies using different instruments at different measuring sites for validation. The variation in the retention time of known signals, especially for compounds with higher retention times, was significantly improved. The alignment of the retention time—an indispensable procedure to achieve a more precise identification of analytes—using the proposed method reduces the random error caused by small accidental deviations in column temperature and flow velocity significantly

Evaluation of floral volatile patterns in the genus Narcissus using gas chromatography–coupled ion mobility spectrometry

Premise: Daffodils (Narcissus, Amaryllidaceae) are iconic ornamentals with a complex floral biology and many fragrant species; however, little is known about floral plant volatile organic compounds (pVOCs) across the genus and additional sampling is desirable. The present study investigates whether the floral scent of 20 species of Narcissus can be characterized using gas chromatography–coupled ion mobility spectrometry (GC–IMS), with the aim of building a comparative pVOC data set for ecological and evolutionary studies. Methods: We used a commercial GC–IMS equipped with an integrated in-line enrichment system for a fast, sensitive, and automated pVOC analysis. This facilitates qualitative and (semi)-quantitative measurements without sample preparation. Results: The GC–IMS provided detailed data on floral pVOCs in Narcissus with very short sampling times and without floral enclosure. A wide range of compounds was recorded and partially identified. The retrieved pVOC patterns showed a good agreement with published data, and five “chemotypes” were characterized as characteristic combinations of floral volatiles. Discussion: The GC–IMS setup can be applied to rapidly generate large amounts of pVOC data with high sensitivity and selectivity. The preliminary data on Narcissus obtained here indicate both considerable pVOC variability and a good correspondence of the pVOC patterns with infrageneric classification, supporting the hypothesis that floral scent could represent a considerable phylogenetic signal

Processos de remoção de material particulado atmosférico: uma modelagem numérica de estudo de casos

Below cloud scavenging processes have been investigated considering a numerical simulation, local atmospheric conditions and particulate matter (PM) concentrations, at different sites in Germany. The below cloud scavenging model has been coupled with bulk particulate matter counter TSI (Trust Portacounter dataset, consisting of the variability prediction of the particulate air concentrations during chosen rain events. The TSI samples and meteorological parameters were obtained during three winter Campaigns: at Deuselbach, March 1994, consisting in three different events; Sylt, April 1994 and; Freiburg, March 1995. The results show a good agreement between modeled and observed air concentrations, emphasizing the quality of the conceptual model used in the below cloud scavenging numerical modeling. The results between modeled and observed data have also presented high square Pearson coefficient correlations over 0.7 and significant, except the Freiburg Campaign event. The differences between numerical simulations and observed dataset are explained by the wind direction changes and, perhaps, the absence of advection mass terms inside the modeling. These results validate previous works based on the same conceptual model.Os processos de remoção atmosféricos foram investigados em simulação numérica, levando-se em conta as condições atmosféricas locais e a concentração de matéria particulada (MP) em diferentes lugares na Alemanha. Um modelo de remoção foi desenvolvido com intuito de predizer a variabilidade da concentração no ar da matéria particulada observada por um contador de partículas totais TSI, durante eventos de precipitação. As amostras de TSI, bem como os dados meteorológicos, foram coletadas em três Campanhas em Deuselbach, em três diferentes eventos; Sylt e Freiburg, respectivamente durante os meses de março de 1994, abril de 1994 e março de 1995. Os resultados mostram boa concordância entre os dados modelados e observados, com altos coeficientes de correlação quadráticos acima de 0.70, dentro da significância, exceto na Campanha de Freiburg. As diferenças apresentadas são devidas a alterações significativas da direção do vento e, talvez, devido à ausência de advecção de massa dentro do modelo. Estes resultados auxiliam a validação de trabalhos prévios baseados no mesmo modelo conceitual

Ion mobility spectrometry for microbial volatile organic compounds: a new identification tool for human pathogenic bacteria

Presently, 2 to 4 days elapse between sampling at infection suspicion and result of microbial diagnostics. This delay for the identification of pathogens causes quite often a late and/or inappropriate initiation of therapy for patients suffering from infections. Bad outcome and high hospitalization costs are the consequences of these currently existing limited pathogen identification possibilities. For this reason, we aimed to apply the innovative method multi-capillary column–ion mobility spectrometry (MCC-IMS) for a fast identification of human pathogenic bacteria by determination of their characteristic volatile metabolomes. We determined volatile organic compound (VOC) patterns in headspace of 15 human pathogenic bacteria, which were grown for 24 h on Columbia blood agar plates. Besides MCC-IMS determination, we also used thermal desorption–gas chromatography–mass spectrometry measurements to confirm and evaluate obtained MCC-IMS data and if possible to assign volatile compounds to unknown MCC-IMS signals. Up to 21 specific signals have been determined by MCC-IMS for Proteus mirabilis possessing the most VOCs of all investigated strains. Of particular importance is the result that all investigated strains showed different VOC patterns by MCC-IMS using positive and negative ion mode for every single strain. Thus, the discrimination of investigated bacteria is possible by detection of their volatile organic compounds in the chosen experimental setup with the fast and cost-effective method MCC-IMS. In a hospital routine, this method could enable the identification of pathogens already after 24 h with the consequence that a specific therapy could be initiated significantly earlier

Evaluation and application of static headspace-multicapillary column-gas chromatography-ion mobility spectrometry for complex sample analysis.

An evaluation of static headspace-multicapillary column-gas chromatography-ion mobility spectrometry (SHS-MCC-GC-IMS) has been undertaken to assess its applicability for the determination of 32 volatile compounds (VCs). The key experimental variables of sample incubation time and temperature have been evaluated alongside the MCC-GC variables of column polarity, syringe temperature, injection temperature, injection volume, column temperature and carrier gas flow rate coupled with the IMS variables of temperature and drift gas flow rate. This evaluation resulted in six sets of experimental variables being required to separate the 32 VCs. The optimum experimental variables for SHS-MCC-GC-IMS, the retention time and drift time operating parameters were determined; to normalise the operating parameters, the relative drift time and normalised reduced ion mobility for each VC were determined. In addition, a full theoretical explanation is provided on the formation of the monomer, dimer and trimer of a VC. The optimum operating condition for each VC calibration data was obtained alongside limit of detection (LOD) and limit of quantitation (LOQ) values. Typical detection limits ranged from 0.1ng bis(methylthio)methane, ethylbutanoate and (E)-2-nonenal to 472ng isovaleric acid with correlation coefficient (R(2)) data ranging from 0.9793 (for the dimer of octanal) through to 0.9990 (for isobutyric acid). Finally, the developed protocols were applied to the analysis of malodour in sock samples. Initial work involved spiking an inert matrix and sock samples with appropriate concentrations of eight VCs. The average recovery from the inert matrix was 101±18% (n=8), while recoveries from the sock samples were lower, that is, 54±30% (n=8) for sock type 1 and 78±24% (n=6) for sock type 2. Finally, SHS-MCC-GC-IMS was applied to sock malodour in a field trial based on 11 volunteers (mixed gender) over a 3-week period. By applying the SHS-MCC-GC-IMS database, four VCs were identified and quantified: ammonia, dimethyl disulphide, dimethyl trisulphide and butyric acid. A link was identified between the presence of high ammonia and dimethyl disulphide concentrations and a high malodour odour grading, that is, ≥ 6. Statistical analysis did not find any correlation between the occurrence of dimethyl disulphide and participant gender

Towards a multisensor station for automated biodiversity monitoring

Rapid changes of the biosphere observed in recent years are caused by both small and large scale drivers, like shifts in temperature, transformations in land-use, or changes in the energy budget of systems. While the latter processes are easily quantifiable, documentation of the loss of biodiversity and community structure is more difficult. Changes in organismal abundance and diversity are barely documented. Censuses of species are usually fragmentary and inferred by often spatially, temporally and ecologically unsatisfactory simple species lists for individual study sites. Thus, detrimental global processes and their drivers often remain unrevealed. A major impediment to monitoring species diversity is the lack of human taxonomic expertise that is implicitly required for large-scale and fine-grained assessments. Another is the large amount of personnel and associated costs needed to cover large scales, or the inaccessibility of remote but nonetheless affected areas. To overcome these limitations we propose a network of Automated Multisensor stations for Monitoring of species Diversity (AMMODs) to pave the way for a new generation of biodiversity assessment centers. This network combines cutting-edge technologies with biodiversity informatics and expert systems that conserve expert knowledge. Each AMMOD station combines autonomous samplers for insects, pollen and spores, audio recorders for vocalizing animals, sensors for volatile organic compounds emitted by plants (pVOCs) and camera traps for mammals and small invertebrates. AMMODs are largely self-containing and have the ability to pre-process data (e.g. for noise filtering) prior to transmission to receiver stations for storage, integration and analyses. Installation on sites that are difficult to access require a sophisticated and challenging system design with optimum balance between power requirements, bandwidth for data transmission, required service, and operation under all environmental conditions for years. An important prerequisite for automated species identification are databases of DNA barcodes, animal sounds, for pVOCs, and images used as training data for automated species identification. AMMOD stations thus become a key component to advance the field of biodiversity monitoring for research and policy by delivering biodiversity data at an unprecedented spatial and temporal resolution. (C) 2022 Published by Elsevier GmbH on behalf of Gesellschaft fur Okologie

Ion mobility spectrometry-mass spectrometry (IMS-MS) of small molecules: separating and assigning structures to ions

The phenomenon of ion mobility (IM), the movement/transport of charged particles under the influence of an electric field, was first observed in the early 20th Century and harnessed later in ion mobility spectrometry (IMS). There have been rapid advances in instrumental design, experimental methods, and theory together with contributions from computational chemistry and gas-phase ion chemistry, which have diversified the range of potential applications of contemporary IMS techniques. Whilst IMS-mass spectrometry (IMS-MS) has recently been recognized for having significant research/applied industrial potential and encompasses multi-/cross-disciplinary areas of science, the applications and impact from decades of research are only now beginning to be utilized for "small molecule" species. This review focuses on the application of IMS-MS to "small molecule" species typically used in drug discovery (100-500 Da) including an assessment of the limitations and possibilities of the technique. Potential future developments in instrumental design, experimental methods, and applications are addressed. The typical application of IMS-MS in relation to small molecules has been to separate species in fairly uniform molecular classes such as mixture analysis, including metabolites. Separation of similar species has historically been challenging using IMS as the resolving power, R, has been low (3-100) and the differences in collision cross-sections that could be measured have been relatively small, so instrument and method development has often focused on increasing resolving power. However, IMS-MS has a range of other potential applications that are examined in this review where it displays unique advantages, including: determination of small molecule structure from drift time, "small molecule" separation in achiral and chiral mixtures, improvement in selectivity, identification of carbohydrate isomers, metabonomics, and for understanding the size and shape of small molecules. This review provides a broad but selective overview of current literature, concentrating on IMS-MS, not solely IMS, and small molecule applications. © 2012 Wiley Periodicals, Inc