Search criteria and rules for comprehensive two-dimensional gas chromatography-time-of-flight mass spectrometry analysis of airborne particulate matter

Vinegar Volatile Organic Compounds: Analytical Methods, Constituents, and Formation Processes

Vinegar is an acid condiment shared all over the world. According to the raw materials, vinegar can be mainly divided into fruit and cereal ones, both of which possess unique aroma and flavor characteristics and corresponding volatile organic compounds (VOCs). Many studies about vinegar VOCs' (VVOCs) sorts, analytical methods, and forming mechanisms have been done. In this review, the main categories of vinegar and their distribution in the world are briefly introduced, then VVOCs' analytical and identified methods, types, and forming processes are summarized. Additionally, the VVOCs' research directions are discussed and prospected. According to the searched literatures, this study is the first to systematically review the analytical methods, sorts, and formation mechanisms of VVOCs, which will make the readers better understand the vinegar's aromas and flavors and their producing mechanisms.

Automated Screening and Filtering Scripts for GC×GC-TOFMS Metabolomics Data

Comprehensive two-dimensional gas chromatography mass spectrometry (GC×GC-MS) is a powerful tool for the analysis of complex mixtures, and it is ideally suited to discovery studies where the entire sample is potentially of interest. Unfortunately, when unit mass resolution mass spectrometers are used, many detected compounds have spectra that do not match well with libraries. This could be due to the compound not being in the library, or the compound having a weak/nonexistent molecular ion cluster. While high-speed, high-resolution mass spectrometers, or ion sources with softer ionization than 70 eV electron impact (EI) may help with some of this, many GC×GC systems presently in use employ low-resolution mass spectrometers and 70 eV EI ionization. Scripting tools that apply filters to GC×GC-TOFMS data based on logical operations applied to spectral and/or retention data have been used previously for environmental and petroleum samples. This approach rapidly filters GC×GC-TOFMS peak tables (or raw data) and is available in software from multiple vendors. In this work, we present a series of scripts that have been developed to rapidly classify major groups of compounds that are of relevance to metabolomics studies including: fatty acid methyl esters, free fatty acids, aldehydes, alcohols, ketones, amino acids, and carbohydrates.

Application of thermal desorption methods for airborne polycyclic aromatic hydrocarbon measurement: A critical review

Thermal desorption (TD) is a universal solvent-free pre-concentration technique. It is often used to pre-concentrate semi-volatile and volatile organic compounds in various sample types. Polycyclic aromatic hydrocarbons (PAHs) are widespread contaminants from incomplete combustion of organic matter and fossil fuel, which have carcinogenic effects on human health. Conventional methods for determining PAHs, represented by solvent extraction, are gradually being replaced by solvent-free methods, typically the TD technique, because of TD's many advantages, including time savings and environmentally friendly treatment. This work presents an extensive review of the universal methods used to determine PAHs in the atmosphere based on the TD technique. The methods currently used for collection and detection of both gas- and particle-phase PAHs in the air are critically reviewed. In addition, the operating parameters of the TD unit are summarized and discussed. The design shortcomings of existing studies and the problems that researchers should address are presented, and promising alternatives are suggested. This paper also discusses important parameters, such as reproducibility and limit of detection, that form a crucial part of quality assurance. Finally, the limitations and the future prospects of the TD technique for use in airborne PAH analyses are addressed. This is the first review of the latest developments of the TD technique for analysis of PAHs and their derivatives in the atmosphere.

Characterising Particulate Organic Nitrogen at A Savannah-Grassland Region in South Africa

Although atmospheric organic N compounds are considered to be important, especially in new particle formation and their contribution to brown carbon, these species are not that well understood. This can be partially attributed to their chemical complexity. Therefore, the aim of this study was to assess the characteristics of organic N compounds utilising comprehensive two-dimensional gas chromatography coupled with a time-of-flight mass spectrometer (GCxGC-TOFMS) in aerosol samples that were collected at a savanna-grassland background region and to determine the possible sources. 135 atmospheric organic N compounds were tentatively characterised and semi-quantified, which included amines, nitriles, amides, urea, pyridine derivatives, amino acids, nitro-and nitroso compounds, imines, cyanates and isocyanates, and azo compounds. Amines contributed to 51% of the semi-quantified concentrations, while nitriles, pyridine derivatives, and amides comprised 20%, 11%, and 8%, respectively, of the semi-quantified concentrations. Amines, nitriles, amides, and pyridine derivatives concentrations were higher during the dry season, which were attributed to meteorology and open biomass burning. Anthropogenic sources impacting air masses measured at Welgegund, as well as regional agricultural activities, were considered as the major sources of amines, while the regional influence of household combustion was most likely the main source of nitriles, amides, and pyridine derivatives. The other organic N species were most likely related to the influence of local and regional agricultural activities.

Molecular Characterization of Atmospheric Organic Aerosol by Mass Spectrometry

Atmospheric aerosol, particulate matter suspended in the air we breathe, exerts a strong impact on our health and the environment. Controlling the amount of particulate matter in air is difficult, as there are many ways particles can form by both natural and anthropogenic processes. We gain insight into the sources of particulate matter through chemical composition measurements. A substantial portion of atmospheric aerosol is organic, and this organic matter is exceedingly complex on a molecular scale, encompassing hundreds to thousands of individual compounds that distribute between the gas and particle phases. Because of this complexity, no single analytical technique is sufficient. However, mass spectrometry plays a crucial role owing to its combination of high sensitivity and molecular specificity. This review surveys the various ways mass spectrometry is used to characterize atmospheric organic aerosol at a molecular level, tracing these methods from inception to current practice, with emphasis on current and emerging areas of research. Both offline and online approaches are covered, and molecular measurements with them are discussed in the context of identifying sources and elucidating the underlying chemical mechanisms of particle formation. There is an ongoing need to improve existing techniques and develop new ones if we are to further advance our knowledge of how to mitigate the unwanted health and environmental impacts of particles.

Quartz filter-based thermal desorption gas chromatography mass spectrometry for in-situ molecular level measurement of ambient organic aerosols

Thermal desorption aerosol gas chromatography (TAG) is an effective technique for online chemical characterization of organics in atmospheric fine particulate matter (PM_2.5) on the molecular level. Unlike the previously reported impactor- or metal filter-based TAG, in this study, a replaceable quartz filter-based TAG (Q-TAG) was developed to achieve online measurement of organic constituents in ambient PM_2.5. A homemade device for automatic online sampling and pretreatment of aerosols was developed and coupled with gas chromatography-mass spectrometry (GC-MS) by a 4-port valve. Performance of the Q-TAG system was evaluated using C7 - C40 n-alkanes to cover a wide range of volatility. C11 - C40 could be measured by Q-TAG. The response of their peaks depends on their volatility and thermal desorption conditions (the desorption time and the flow rate). Under the optimized conditions, good precision (<12%), acceptable linearity (R²> 0.98) and high sensitivity (detection limits from 0.02 to 0.01 ng) of C13 - C40 were obtained. The developed Q-TAG system was applied for online analysis of organic species in ambient PM_2.5. The Q-TAG is suitable for detection of semi and low volatile organic species in particulate matter, and its filter can be easily changed, making it a useful tool in molecular characterization of ambient organic aerosols.

Leaf-deposited semi-volatile organic compounds (SVOCs): An exploratory study using GCxGC-TOFMS on leaf washing solutions

Airborne particulate matter (PM) includes semi-volatile organic compounds (SVOCs), which can be deposited on vegetation matrices such as plant leaves. In alternative to air-point measurements or artificial passive substrates, leaf monitoring offers a cost-effective, time-integrating means of assessing local air quality. In this study, leaf washing solutions from ivy (Hedera hibernica) leaves exposed during one-month at different land use classes were explored via comprehensive two-dimensional gas chromatography with time-of-flight mass spectrometry (GCxGC-TOFMS). The composition of leaf-deposited SVOCs, corrected for those of unexposed leaves, was compared against routinely monitored pollutants concentrations (PM₁₀, PM_2.5, O₃, NO₂, SO₂) measured at co-located air monitoring stations. The first study on leaf-deposited SVOCs retrieved from washing solutions, herein reported, delivered a total of 911 detected compounds. While no significant land use (rural, urban, industrial, traffic, mixed) effects were observed, increasing exposure time (from one to 28 days) resulted in a higher number and diversity of SVOCs, suggesting cumulative time-integration to be more relevant than local source variations between sites. After one day, leaf-deposited SVOCs were mainly due to alcohols, N-containing compounds, carboxylic acids, esters and lactones, while ketones, diketones and hydrocarbons compounds gained relevance after one week, and phenol compounds after one month. As leaf-deposited SVOCs became overall more oxidized throughout exposure time, SVOCs transformation or degradation at the leaf surface is suggested to be an important phenomenon. This study confirmed the applicability of GCxGC-TOFMS to analyze SVOCs from leaf washing solutions, further research should include validation of the methodology and comparison with atmospheric organic pollutants.

Differences among Unique Nanoparticle Protein Corona Constructs: A Case Study Using Data Analytics and Multi-Variant Visualization to Describe Physicochemical Characteristics

Gold nanoparticles (AuNPs) used in pharmaceutical treatments have been shown to effectively deliver a payload, such as an active pharmaceutical ingredient or image contrast agent, to targeted tissues in need of therapy or diagnostics while minimizing exposure, availability, and accumulation to surrounding biological compartments. Data sets collected in this field of study include some toxico- and pharmacodynamic properties (e.g., distribution and metabolism) but many studies lack information about adsorption of biological molecules or absorption into cells. When nanoparticles are suspended in blood serum, a protein corona cloud forms around its surface. The extent of the applications and implications of this formed cloud are unknown. Some researchers have speculated that the successful use of nanoparticles in pharmaceutical treatments relies on a comprehensive understanding of the protein corona composition. The work presented in this paper uses a suite of data analytics and multi-variant visualization techniques to elucidate particle-to-protein interactions at the molecular level. Through mass spectrometry analyses, corona proteins were identified through large and complex datasets. With such high-output analyses, complex datasets pose a challenge when visualizing and communicating nanoparticle-protein interactions. Thus, the creation of a streamlined visualization method is necessary. A series of user-friendly data informatics techniques were used to demonstrate the data flow of protein corona characteristics. Multi-variant heat maps, pie charts, tables, and three-dimensional regression analyses were used to improve results interpretation, facilitate an iterative data transfer process, and emphasize features of the nanoparticle-protein corona system that might be controllable. Data informatics successfully highlights the differences between protein corona compositions and how they relate to nanoparticle surface charge.

Analysis of Polycyclic Aromatic Hydrocarbons in Ambient Aerosols by Using One-Dimensional and Comprehensive Two-Dimensional Gas Chromatography Combined with Mass Spectrometric Method: A Comparative Study

Advanced separation technology paired with mass spectrometry is an ideal method for the analysis of atmospheric samples having complex chemical compositions. Due to the huge variety of both natural and anthropogenic sources of organic compounds, simultaneous quantification and identification of organic compounds in aerosol samples represents a demanding analytical challenge. In this regard, comprehensive two-dimensional gas chromatography with time-of-flight mass spectrometry (GC×GC-TOFMS) has become an effective analytical method. However, verification and validation approaches to quantify these analytes have not been critically evaluated. We compared the performance of gas chromatography with quadrupole mass spectrometry (GC-qMS) and GC×GC-TOFMS for quantitative analysis of eighteen target polycyclic aromatic hydrocarbons (PAHs). The quantitative obtained results such as limits of detection (LODs), limits of quantification (LOQs), and recoveries of target PAHs were approximately equivalent based on both analytical methods. Furthermore, a larger number of analytes were consistently identified from the aerosol samples by GC×GC-TOFMS compared to GC-qMS. Our findings suggest that GC×GC-TOFMS would be widely applicable to the atmospheric and related sciences with simultaneous target and nontarget analysis in a single run.

In-depth compositional analysis of water-soluble and -insoluble organic substances in fine (PM2.5) airborne particles using ultra-high-resolution 15T FT-ICR MS and GC×GC-TOFMS

Airborne particulate matter consisting of ionic species, salts, heavy metals and carbonaceous material is one of the most serious environmental pollutants owing to its impacts on the environment and human health. Although elemental and organic carbon compounds are known to be major components of aerosols, information on the elemental composition of particulate matter remains limited because of the broad range of compounds involved and the limits of analytical instruments. In this study, we investigated water-soluble and -insoluble organic compounds in fine (PM_2.5) airborne particles collected during winter in Korea to better understand the elemental compositions and distributions of these compounds. To collect ultra-high-resolution mass profiles, we analyzed water-soluble and -insoluble organic compounds, extracted with water and dichloromethane, respectively, using an ultra-high-resolution 15 T Fourier transform ion cyclotron resonance (15T FT-ICR) mass spectrometer in positive ion mode (via both electrospray ionization [ESI] and atmospheric pressure photoionization [APPI] for water-extracts and via APPI for dichloromethane-extracts). In conjunction with the FT-ICR mass spectrometry (MS) data, subsequent two-dimensional gas chromatography time-of-flight mass spectrometry (GC×GC-TOFMS) data were used to identify potentially hazardous organic components, such as polycyclic aromatic hydrocarbons. This analysis provided information on the sources of ambient particles collected during winter season and partial evidence of contributions to the acidity of organic content in PM_2.5 particles. The compositional and structural features of water-soluble and -insoluble organic compounds from PM_2.5 particles are important for understanding the potential impacts of aerosol-carried organic substances on human health and global ecosystems in future toxicological studies.

Improved molecular level identification of organic compounds using comprehensive two-dimensional chromatography, dual ionization energies and high resolution mass spectrometry

A new analytical methodology combining comprehensive two-dimensional gas chromatography (GC×GC), dual ionization energies and high resolution time of flight mass spectrometry has been developed that improves molecular level identification of organic compounds in complex environmental samples. GC×GC maximizes compound separation providing cleaner mass spectra by minimizing erroneous fragments from interferences and co-eluting peaks. Traditional electron ionization (EI, 70 eV) provides MS fragmentation patterns that can be matched to published EI MS libraries while vacuum ultraviolet photoionization (VUV, 10.5 eV) yields MS with reduced fragmentation enhancing the abundance of the molecular ion providing molecular formulas when combined with high resolution mass spectrometry. We demonstrate this new approach by applying it to a sample of organic aerosol. In this sample, 238 peaks were matched to EI MS library data with FM ≥ 800 but a fifth (42 compounds) were determined to be incorrectly identified because the molecular formula was not confirmed by the VUV MS data. This highlights the importance of using a complementary technique to confirm compound identifications even for peaks with very good matching statistics. In total, 171 compounds were identified by EI MS matching to library spectra with confirmation of the molecular formula from the high resolution VUV MS data and were not dependent on the matching statistics being above a threshold value. A large number of unidentified peaks were still observed with FM < 800, which in routine analysis would typically be neglected. Where possible, these peaks were assigned molecular formulas from the VUV MS data (211 in total). In total, the combination of EI and VUV MS data provides more than twice as much molecular level peak information than traditional approaches and improves confidence in the identification of individual organic compounds. The molecular formula data from the VUV MS data was used, in conjunction with GC×GC retention times and the observed EI MS, to generate a new, searchable EI MS library compatible with the standard NIST MS search program. This library is deliberately dynamic and editable so that other end users can add new entries and update existing entries as new information becomes available.

Aerosol emissions of a ship diesel engine operated with diesel fuel or heavy fuel oil

Gaseous and particulate emissions from a ship diesel research engine were elaborately analysed by a large assembly of measurement techniques. Applied methods comprised of offline and online approaches, yielding averaged chemical and physical data as well as time-resolved trends of combustion by-products. The engine was driven by two different fuels, a commonly used heavy fuel oil (HFO) and a standardised diesel fuel (DF). It was operated in a standardised cycle with a duration of 2 h. Chemical characterisation of organic species and elements revealed higher concentrations as well as a larger number of detected compounds for HFO operation for both gas phase and particulate matter. A noteworthy exception was the concentration of elemental carbon, which was higher in DF exhaust aerosol. This may prove crucial for the assessment and interpretation of biological response and impact via the exposure of human lung cell cultures, which was carried out in parallel to this study. Offline and online data hinted at the fact that most organic species in the aerosol are transferred from the fuel as unburned material. This is especially distinctive at low power operation of HFO, where low volatility structures are converted to the particulate phase. The results of this study give rise to the conclusion that a mere switching to sulphur-free fuel is not sufficient as remediation measure to reduce health and environmental effects of ship emissions.

Untargeted Identification of Wood Type-Specific Markers in Particulate Matter from Wood Combustion

Residential wood combustion emissions are one of the major global sources of particulate and gaseous organic pollutants. However, the detailed chemical compositions of these emissions are poorly characterized due to their highly complex molecular compositions, nonideal combustion conditions, and sample preparation steps. In this study, the particulate organic emissions from a masonry heater using three types of wood logs, namely, beech, birch, and spruce, were chemically characterized using thermal desorption in situ derivatization coupled to a GCxGC-ToF/MS system. Untargeted data analyses were performed using the comprehensive measurements. Univariate and multivariate chemometric tools, such as analysis of variance (ANOVA), principal component analysis (PCA), and ANOVA simultaneous component analysis (ASCA), were used to reduce the data to highly significant and wood type-specific features. This study reveals substances not previously considered in the literature as meaningful markers for differentiation among wood types.

Recent advances in the application of 2-dimensional gas chromatography with soft and hard ionisation time-of-flight mass spectrometry in environmental analysis

Two-dimensional gas chromatography has huge power for separating complex mixtures. The principles of the technique are outlined together with an overview of detection methods applicable to GC × GC column effluent with a focus on selectivity. Applications of GC × GC techniques in the analysis of petroleum-related and airborne particulate matter samples are reviewed. Mass spectrometric detection can be used alongside spectral libraries to identify eluted compounds, but in complex petroleum-related and atmospheric samples, when used conventionally at high ionisation energies, may not allow differentiation of structural isomers. Available low energy ionisation methods are reviewed and an example given of the additional structural information which can be extracted by measuring mass spectra at both low and high ionisation energies, hence greatly enhancing the selectivity of the technique.

Advanced scripting for the automated profiling of two-dimensional gas chromatography-time-of-flight mass spectrometry data from combustion aerosol

Multidimensional gas chromatography is an appropriate tool for the non-targeted and comprehensive characterisation of complex samples generated from combustion processes. Particulate matter (PM) emission is composed of a large number of compounds, including condensed semi-volatile organic compounds (SVOCs). However, the complex amount of information gained from such comprehensive techniques is associated with difficult and time-consuming data analysis. Because of this obstacle, two-dimensional gas chromatography still receives relatively little use in aerosol science [1-4]. To remedy this problem, advanced scripting algorithms based on knowledge-based rules (KBRs) were developed in-house and applied to GCxGC-TOFMS data. Previously reported KBRs and newer findings were considered for the development of these algorithms. The novelty of the presented advanced scripting tools is a notably selective search criterion for data screening, which is primarily based on fragmentation patterns and the presence of specific fragments. Combined with "classical" approaches based on retention times, a fast, accurate and automated data evaluation method was developed, which was evaluated qualitatively and quantitatively for type 1 and type 2 errors. The method's applicability was further tested for PM filter samples obtained from ship fuel combustion. Major substance classes, including polycyclic aromatic hydrocarbons (PAH), alkanes, benzenes, esters and ethers, can be targeted. This approach allows the classification of approximately 75% of the peaks of interest within real PM samples. Various conditions of combustion, such as fuel composition and engine load, could be clearly characterised and differentiated.

Sources and characteristics of carbonaceous aerosols at Agra "World heritage site" and Delhi "capital city of India"

Agra, one of the oldest cities "World Heritage site", and Delhi, the capital city of India are both located in the border of Indo-Gangetic Plains (IGP) and heavily loaded with atmospheric aerosols due to tourist place, anthropogenic activities, and its topography, respectively. Therefore, there is need for monitoring of atmospheric aerosols to perceive the scenario and effects of particles over northern part of India. The present study was carried out at Agra (AGR) as well as Delhi (DEL) during winter period from November 2011 to February 2012 of fine particulate (PM₂.₅: d < 2.5 μm) as well as associated carbonaceous aerosols. PM₂.₅ was collected at both places using medium volume air sampler (offline measurement) and analyzed for organic carbon (OC) and elemental carbon (EC). Also, simultaneously, black carbon (BC) was measured (online) at DEL. The average mass concentration of PM₂.₅ was 165.42 ± 119.46 μg m(-3) at AGR while at DEL it was 211.67 ± 41.94 μg m(-3) which is ~27% higher at DEL than AGR whereas the BC mass concentration was 10.60 μg m(-3). The PM₂.₅ was substantially higher than the annual standard stipulated by central pollution control board and United States Environmental Protection Agency standards. The average concentrations of OC and EC were 69.96 ± 34.42 and 9.53 ± 7.27 μm m(-3), respectively. Total carbon (TC) was 79.01 ± 38.98 μg m(-3) at AGR, while it was 50.11 ± 11.93 (OC), 10.67 ± 3.56 μg m(-3) (EC), and 60.78 ± 14.56 μg m(-3) (TC) at DEL. The OC/EC ratio was 13.75 at (AGR) and 5.45 at (DEL). The higher OC/EC ratio at Agra indicates that the formation of secondary organic aerosol which emitted from variable primary sources. Significant correlation between PM₂.₅ and its carbonaceous species were observed indicating similarity in sources at both sites. The average concentrations of secondary organic carbon (SOC) and primary organic carbon (POC) at AGR were 48.16 and 26.52 μg m(-3) while at DEL it was 38.78 and 27.55 μg m(-3), respectively. In the case of POC, similar concentrations were observed at both places but in the case of SOC higher over AGR by 24 in comparison to DEL, it is due to the high concentration of OC over AGR. Secondary organic aerosol (SOA) was 42% higher at AGR than DEL which confirms the formation of secondary aerosol at AGR due to rural environment with higher concentrations of coarse mode particles. The SOA contribution in PM₂.₅ was also estimated and was ~32 and 12% at AGR and DEL respectively. Being high loading of fine particles along with carbonaceous aerosol, it is suggested to take necessary and immediate action in mitigation of the emission of carbonaceous aerosol in the northern part of India.

Analysis of mainstream tobacco smoke particulate phase using comprehensive two-dimensional gas chromatography time-of-flight mass spectrometry

Comprehensive 2D GC coupled to time-of-flight mass spectrometry was applied for the characterization of the particulate phase of mainstream tobacco smoke particulate. Five 3R4F research cigarettes were smoked on a rotary smoking machine under standardized conditions, total particular matter was collected on Cambridge filter pads and extracted using methanol-based liquid extraction and dynamic headspace (DHS) approaches. Automated peak finding and mass spectral deconvolution combined with scripting and manual revision of library hits were used to evaluate the library search results. The revised peak table contained nearly 1800 individual compounds for the DHS sample and over 900 for the solvent extracted sample. These methods of extraction were shown to be complementary, leading to only 11% of repeated analytes, and their combination gave rise to a list of almost 2500 individual compounds.

AN IMPROVED QSPR STUDY OF REVERSE FACTOR OF NANOPARTICLES IN ROADSIDE ATMOSPHERE ON KERNEL PARTIAL LEAST SQUARES AND GENETIC ALGORITHM

Thermal desorption-comprehensive two-dimensional gas chromatography high-resolution time-of-flight mass spectrometry (TD–GC × GC–HRTOF-MS) is one of the most powerful tools in analytical nanoparticle compounds. Genetic algorithm and partial least square (GA-PLS) and kernel PLS (GA-KPLS) models were used to investigate the correlation between reverse factor (RF) and descriptors for 50 nanoparticles fraction with a diameter of 29–58 nm in roadside atmosphere which obtained by TD–GC×GC–HRTOF-MS. The correlation coefficient leave-group-out cross validation (LGO-CV (Q2)) of prediction for the GA-PLS and GA-KPLS models for training and test sets were (0.761 and 0.718) and (0.825 and 0.814), respectively, revealing the reliability of these models. This is the first research on the quantitative structure-property relationship (QSPR) of the nanoparticles in roadside atmosphere using the GA-PLS and GA-KPLS.

Particle-associated organic compounds and symptoms in myocardial infarction survivors

CONTEXT

The aerosol components responsible for the adverse health effects of the exposure to particulate matter (PM) have not been conclusively identified, and there is especially little information on the role of particulate organic compounds (POC).

OBJECTIVE

This study evaluated the role of PM and POC with regard to daily symptoms.

METHODS

One hundred and fifty-three myocardial infarction survivors from Augsburg, Germany, recorded daily occurrence of different symptoms in winter 2003/2004. Ambient concentrations of PM with a diameter <2.5 μm (PM(2.5)), particle number concentration (PNC), PM(2.5)-bound hopanes, and polycyclic aromatic hydrocarbons (PAH) were quantified. Data were analyzed using generalized estimating equations adjusting for meteorological and other time-variant confounders.

RESULTS

The odds for avoidance of physically demanding activities due to heart problems increased immediately associated with most POC measures (e.g. 5% per 1.08 ng/m(3) increase in benzo[a]pyrene, 95%-confidence interval (CI):1-9%) and tended to a delayed decrease. After a 2-day delayed decrease associated with hopanes, the odds for shortness of breath increased consistently after 3 days with almost all POC measures (e.g. 4% per 0.21 ng/m(3) increase in 17α(H), 21β(H)-hopane, CI: 1-8%). The odds for heart palpitations marginally increased immediately in association with PNC (8% per 8146 cm(-3) increase in PNC, CI: 0-16%).

CONCLUSIONS

The study showed an association between PM, particle-bound POC, and daily symptoms. The organic compounds may be causally related with cardiovascular health or act rather as indicators for traffic- and combustion-related particles.

The Progress in Electron Microscopy Studies of Particulate Matters to Be Used as a Standard Monitoring Method for Air Dust Pollution

The present article reviews studies on air solid particles carried out with the use of electron microscopy. Particle analysis combining scanning and transmission electron microscopy (SEM and TEM) can be used to derive size-resolved information of the composition, mixing state, morphology, and complex refractive index of atmospheric aerosol particles. It seems that electron microscopy is more widely used in atmospheric particulate matter analysis, but the usage of this method is sometimes problematic. First of all, there is no standard methodology adapted for dust analysis, and it is difficult to compare the results coming from different laboratories. Nevertheless, it was shown that this method has potential to be used in the future as a standard monitoring procedure of air solid particles.

Real-time gas-phase analysis of mono- to tri-chlorobenzenes generated from heated MSWI fly ashes containing various metal compounds: application of VUV-SPI-IT-TOFMS

We measured sensitive real-time change of low-chlorinated (Cl(1)-Cl(3)) benzenes in gas phase from heated model and real solid samples using the recently developed vacuum ultraviolet (VUV) single-photon ionization (SPI) ion trap time-of-flight mass spectrometer (VUV-SPI-IT-TOFMS). Model solid samples that contained activated carbon, potassium chloride, silicon dioxide, and trace metallic compounds (copper, iron, lead, and zinc) were used to simulate fly ash at a municipal solid waste incinerator (MSWI). The concentrations of chlorobenzenes determined by integrating the area for 30 min using VUV-SPI-IT-TOFMS were correlated with gas-phase concentrations analyzed by GC/MS. Real-time changes had characteristic patterns dependent on metal species and compounds. Comparing gas-phase real-time patterns of low-chlorinated benzenes between real and model fly ashes, copper chloride- and oxide-like compounds in real fly ash at the postcombustion zone in a MSWI may play key factors in the formation of low-chlorinated benzenes. Lead and zinc compounds and iron oxide in solid phase did not affect the formation of low-chlorinated benzenes in gas phase. VUV-SPI-IT-TOFMS can be applied to the time-dependent characterization of volatile low-chlorinated benzenes in gas phase in various artificial and environmental processes.

Capillary electrophoresis with electrospray ionization mass spectrometric detection for single-cell metabolomics

A method that enables metabolomic profiling of single cells and subcellular structures is described using capillary electrophoresis coupled to electrospray ionization time-of-flight mass spectrometry. A nebulizer-free coaxial sheath-flow interface completes the circuit and provides a stable electrospray, yielding a signal with a relative standard deviation of under 5% for the total ion electropherogram. Detection limits are in the low nanomolar range (i.e., <50 nM (<300 amol)) for a number of cell-to-cell signaling molecules, including acetylcholine (ACh), histamine, dopamine, and serotonin. The instrument also yields high-efficiency separations, e.g., approximately 600,000 for eluting ACh bands. The utility of this setup for single-cell metabolomic profiling is demonstrated with identified neurons from Aplysia californica--the R2 neuron and metacerebral cell (MCC). Single-cell electropherograms are reproducible, with a large number of metabolites detected; more than 100 compounds yield signals of over 10(4) counts from the injection of only 0.1% of the total content from a single MCC. Expected neurotransmitters are detected within the cells (ACh in R2 and serotonin in MCC), as are compounds that have molecular masses consistent with all of the naturally occurring amino acids (except cysteine). Tandem MS using a quadrupole time-of-flight tandem mass spectrometer distinguishes ACh from isobaric compounds in the R2 neuron and demonstrates the ability of this method to characterize and identify metabolites present within single cells.

Liquid chromatography-tandem quadrupole mass spectrometry and comprehensive two-dimensional gas chromatography-time-of-flight mass spectrometry measurement of targeted metabolites of Methylobacterium extorquens AM1 grown on two different carbon sources

Complementary methods using liquid chromatography-tandem quadrupole mass spectrometry (LC-MS/MS) and comprehensive two-dimensional gas chromatography-time-of-flight mass spectrometry (GCxGC-TOF-MS) were developed and applied to determine targeted metabolites involved in central carbon metabolism [including tricarboxylic acid cycle, serine cycle, ethylmalonyl-coenzyme A (ethylmalonyl-CoA) pathway and poly-beta-hydroxybutyrate cycle] of the bacterium Methylobacterium extorquens AM1 grown on two carbon sources, ethylamine (C2) and succinate (C4). Nucleotides, acyl-CoAs and a few volatile metabolites in cell extracts of M. extorquens AM1 were readily separated using either hydrophilic interaction liquid chromatography or reversed-phase liquid chromatography, and detected with good sensitivity by MS/MS. However, volatile intermediates within a low mass range (<300 m/z), especially at low abundance (such as glyoxylic acid and others <500nM), were more effectively analyzed by GCxGC-TOF-MS which often provided better sensitivity, resolution and reproducibility. The complementary nature of the LC-based and GC-based methods allowed the comparison of 39 metabolite concentrations (the lowest level was at 139.3nM). The overlap between the LC-based and GC-based methods of seven metabolites provided a basis to check for consistency between the two methods, and thus provided some validation of the quantification accuracy. The abundance change of 20 intermediates further suggested differences in pathways linked to C2 and C4 metabolism.