Evaluation of work-related volatile organic compounds (VOCs) exposition in automotive painting cabins industrial cleanings

Automotive painting cabins are cleaned with several solvents, being great part of them mixtures of volatile organic compounds (VOCs), where the three xylene isomers are the most important constituents. To evaluate the work-related exposition of the cleaners that use these mixtures of solvents, xylenes have been determined in the working ambient air as well as its metabolite, o-m-p-methyl hippuric acid, has been analysed in urine to establish the dermal and respiratory exposition. This evaluation has been done in order to assess the occupational exposure to VOCs and to know the working conditions of the cleaners, but also to evaluate the effectiveness of personal protective equipment (PPE), the engineering control and the work practices.The xylenes have been chosen as indicators of exposition because they are the main components in the cleaning solvents used, with a level of concentration between 50% and 85%.The Xylenes have an occupational exposure limit (8 h TWA) of 50 ppm (221 mg/m3) and a short-term exposure limit (STEL) of 100 ppm (442 mg/m3). On the other hand, the biological exposure index (BEI) for xylenes is the sum of the total methyl hippuric acids in urine at the end of the work-shift, being the value 1500 mg/g creatinine.

Headspace needle-trap analysis of priority volatile organic compounds from aqueous samples: application to the analysis of natural and waste waters

Combining headspace (HS) sampling with a needle-trap device (NTD) to determine priority volatile organic compounds (VOCs) in water samples results in improved sensitivity and efficiency when compared to conventional static HS sampling. A 22 gauge stainless steel, 51-mm needle packed with Tenax TA and Carboxen 1000 particles is used as the NTD. Three different HS-NTD sampling methodologies are evaluated and all give limits of detection for the target VOCs in the ng L−1 range. Active (purge-and-trap) HS-NTD sampling is found to give the best sensitivity but requires exhaustive control of the sampling conditions. The use of the NTD to collect the headspace gas sample results in a combined adsorption/desorption mechanism. The testing of different temperatures for the HS thermostating reveals a greater desorption effect when the sample is allowed to diffuse, whether passively or actively, through the sorbent particles. The limits of detection obtained in the simplest sampling methodology, static HS-NTD (5 mL aqueous sample in 20 mL HS vials, thermostating at 50 °C for 30 min with agitation), are sufficiently low as to permit its application to the analysis of 18 priority VOCs in natural and waste waters. In all cases compounds were detected below regulated levels

A Headspace needle-trap method for the analysis of volatile organic compounds in whole blood

Needle trap devices (NTDs) are a relatively new and promising tool for headspace (HS) analysis. In this study, a dynamic HS sampling procedure is evaluated for the determination of volatile organic compounds (VOCs) in whole blood samples. A full factorial design was used to evaluate the influence of the number of cycles and incubation time and it is demonstrated that the controlling factor in the process is the number of cycles. A mathematical model can be used to determine the most appropriate number of cycles required to adsorb a prefixed amount of VOCs present in the HS phase whenever quantitative adsorption is reached in each cycle. Matrix effect is of great importance when complex biological samples, such as blood, are analyzed. The evaluation of the salting out effect showed a significant improvement in the volatilization of VOCs to the HS in this type of matrices. Moreover, a 1:4 (blood:water) dilution is required to obtain quantitative recoveries of the target analytes when external calibration is used. The method developed gives detection limits in the 0.020–0.080 μg L−1 range (0.1–0.4 μg L−1 range for undiluted blood samples) with appropriate repeatability values (RSD < 15% at high level and <23% at LOQ level). Figure of merits of the method can be improved by using a smaller phase ratio (i.e., an increase in the blood volume and a decrease in the HS volume), which lead to lower detection limits, better repeatability values and greater sensibility. Twenty-eight blood samples have been evaluated with the proposed method and the results agree with those indicated in other studies. Benzene was the only target compound that gave significant differences between blood levels detected in volunteer non-smokers and smokers

Degradation of pheromone and plant volatile components by a same Odorant-Degrading Enzyme in the cotton leafworm, Spodoptera littoralis

Background: Odorant-Degrading Enzymes (ODEs) are supposed to be involved in the signal inactivation step within the olfactory sensilla of insects by quickly removing odorant molecules from the vicinity of the olfactory receptors. Only three ODEs have been both identified at the molecular level and functionally characterized: two were specialized in the degradation of pheromone compounds and the last one was shown to degrade a plant odorant. Methodology: Previous work has shown that the antennae of the cotton leafworm Spodoptera littoralis , a worldwide pest of agricultural crops, express numerous candidate ODEs. We focused on an esterase overexpressed in males antennae, namely SlCXE7. We studied its expression patterns and tested its catalytic properties towards three odorants, i.e. the two female sex pheromone components and a green leaf volatile emitted by host plants. Conclusion: SlCXE7 expression was concomitant during development with male responsiveness to odorants and during adult scotophase with the period of male most active sexual behaviour. Furthermore, SlCXE7 transcription could be induced by male exposure to the main pheromone component, suggesting a role of Pheromone-Degrading Enzyme. Interestingly, recombinant SlCXE7 was able to efficiently hydrolyze the pheromone compounds but also the plant volatile, with a higher affinity for the pheromone than for the plant compound. In male antennae, SlCXE7 expression was associated with both long and short sensilla, tuned to sex pheromones or plant odours, respectively. Our results thus suggested that a same ODE could have a dual function depending of it sensillar localisation. Within the pheromone-sensitive sensilla, SlCXE7 may play a role in pheromone signal termination and in reduction of odorant background noise, whereas it could be involved in plant odorant inactivation within the short sensilla.

Avaluació econòmica i ambiental de tractament de compostos orgànics volàtils

L'estudi tracta sobre una empresa fabricant de tints i pintures que tot i està conscienciada amb el medi ambient i utilitzar tècniques de prevenció en origen per disminuir l’emissió de COV a l’atmosfera (les seves emissions es troben dins dels rangs permesos per la legislació en aquest sector), els seus directius pretenen conèixer les alternatives possibles per valorar la possibilitat d'aplicar algun sistema de tractament dels Compostos Orgànics Volàtils a la sortida de la xemeneia, amb la finalitat de recuperar o reduir l’emissió d’aquests contaminants a l’atmosfera. Es presenta una avaluació econòmica i ambiental de diferents sistemes de tractament dels COV aplicables a l’empresa

Noves metodologies d’anàlisi de compostos volàtils mitjançant trampes d’agulla. Aplicació a l’anàlisi d’alè, atmosfèrica i d’aigües

New methodologies for the analysis of volatile compoundsusing needle traps. Applications to breath, atmospheric andwater analysis. A new preconcentration technique has been developed for the analysis of volatile compounds based on the use of needle traps. These traps are based on stainless steel needles filled with one or more adsorbents, which allows the preconcentration of the anilities inside the trap by passing a gas flow through the needle. The parameters affecting the sorption/desorption process have been assessed (e.g. needle and liner dimensions, injector temperature, split less time, memory effects, and stability inside the needle). For liquid samples, four different sampling methodologies were studied, including passive and active sampling methods. The best results, considering the simplicity and sensitivity, are obtained by sampling the headspace volume using various cycles of a small and fix volume. Once the best conditions of analysis have been found, the method has been validated for gas and liquid samples. The results obtained show that needle traps are a good analytical methodology for the analysis of breath, environmental and liquid samples

Evaluation of potential breath biomarkers for active smoking: assessment of smoking habits

Different compounds have been reported as biomarkers of a smoking habit, but, to date, there is no appropriate biomarker for tobacco-related exposure because the proposed chemicals seem to be nonspecific or they are only appropriate for short-term exposure. Moreover, conventional sampling methodologies require an invasive method because blood or urine samples are required. The use of a microtrap system coupled to gas chromatography–mass spectrometry analysis has been found to be very effective for the noninvasive analysis of volatile organic compounds in breath samples. The levels of benzene, 2,5-dimethylfuran, toluene, o-xylene, and m- p-xylene have been analyzed in breath samples obtained from 204 volunteers (100 smokers, 104 nonsmokers; 147 females, 57 males; ages 16 to 53 years). 2,5-Dimethylfuran was always below the limit of detection (0.005 ppbv) in the nonsmoker population and always detected in smokers independently of the smoking habits. Benzene was only an effective biomarker for medium and heavy smokers, and its level was affected by smoking habits. Regarding the levels of xylenes and toluene, they were only different in heavy smokers and after short-term exposure. The results obtained suggest that 2,5-dimethylfuran is a specific breath biomarker of smoking status independently of the smoking habits (e.g., short- and long-term exposure, light and heavy consumption), and so this compound might be useful as a biomarker of smoking exposure

Growth and functionalization of carbon nanotubes on quartz filter for environmental applications

Background: Air pollution has become an important issue worldwide due to its adverse health effects. Among the different air contaminants, volatile organic compounds (VOCs) are liquids or solids with a high vapor pressure at room temperature that are extremely dangerous for human health. Removal of these compounds can be achieved using nanomaterials with tailored properties such as carbon nanotubes. Methods: Vertically-aligned multiwall carbon nanotubes (CNTs) were successfully grown on quartz filters by means of plasma enhanced chemical vapor deposition (PECVD). Furthermore, a plasma treatment was performed in order to modify the surface properties of the CNTs. The adsorption/desorption processes of three chlorinated compounds (trichloroethylene, 1,2-dichlorobenzene and chloroform) on the CNTs were studied using mass spectrometry measurements with a residual gas analyzer. Results: The adsorption capability of the CNTs increased after functionalization of their surface with a water plasma treatment. In addition, it was found that the presence of aromatic rings, water solubility and polarity of the VOCs play an important role on the adsorption/desorption kinetics at the CNTs surface. Conclusions: This study demonstrates the applicability of CNTs deposited on quartz filters for the removal or selective detection of volatile organic compounds (VOCs). The presence of aromatic rings in VOCs results in π -stacking interactions with a significant increase of their adsorption. On the other hand, it was found that CNTs surface interactions increase with water solubility and polarity of the VOC.

Capillary thermal desorption unit for near real-time analysis of VOCs at sub-trace levels. Application to the analysis of environmental air contamination and breath samples

A capillary microtrap thermal desorption module is developed for near real-time analysis of volatile organic compounds (VOCs) at sub-ppbv levels in air samples. The device allows the direct injection of the thermally desorbed VOCs into a chromatographic column. It does not use a second cryotrap to focalize the adsorbed compounds before entering the separation column so reducing the formation of artifacts. The connection of the microtrap to a GC–MS allows the quantitative determination of VOCs in less than 40 min with detection limits of between 5 and 10 pptv (25 °C and 760 mmHg), which correspond to 19–43 ng m−3, using sampling volumes of 775 cm3. The microtrap is applied to the analysis of environmental air contamination in different laboratories of our faculty. The results obtained indicate that most volatile compounds are easily diffused through the air and that they also may contaminate the surrounding areas when the habitual safety precautions (e.g., working under fume hoods) are used during the manipulation of solvents. The application of the microtrap to the analysis of VOCs in breath samples suggest that 2,5-dimethylfuran may be a strong indicator of a person's smoking status

Evaluation of potential breath biomarkers for active smoking: assessment of smoking habits

Different compounds have been reported as biomarkers of a smoking habit, but, to date, there is no appropriate biomarker for tobacco-related exposure because the proposed chemicals seem to be nonspecific or they are only appropriate for short-term exposure. Moreover, conventional sampling methodologies require an invasive method because blood or urine samples are required. The use of a microtrap system coupled to gas chromatography–mass spectrometry analysis has been found to be very effective for the noninvasive analysis of volatile organic compounds in breath samples. The levels of benzene, 2,5-dimethylfuran, toluene, o-xylene, and m- p-xylene have been analyzed in breath samples obtained from 204 volunteers (100 smokers, 104 nonsmokers; 147 females, 57 males; ages 16 to 53 years). 2,5-Dimethylfuran was always below the limit of detection (0.005 ppbv) in the nonsmoker population and always detected in smokers independently of the smoking habits. Benzene was only an effective biomarker for medium and heavy smokers, and its level was affected by smoking habits. Regarding the levels of xylenes and toluene, they were only different in heavy smokers and after short-term exposure. The results obtained suggest that 2,5-dimethylfuran is a specific breath biomarker of smoking status independently of the smoking habits (e.g., short- and long-term exposure, light and heavy consumption), and so this compound might be useful as a biomarker of smoking exposure

Analytical challenges in breath analysis and its application to exposure monitoring

There is an increasing interest in the use of breath analysis for monitoring human physiology and exposure to toxic substances or environmental pollutants. This review focuses on the current status of the sampling procedures, collection devices and sample-enrichment methodologies used for exhaled breath-vapor analysis. We discuss the different parameters affecting each of the above steps, taking into account the requirements for breath analysis in exposure assessments and the need to analyze target compounds at sub-ppbv levels. Finally, we summarize the practical applications of exposure analysis in the past two decades

A semi-grand canonical Monte Carlo simulation model for ion binding to ionizable surfaces: Proton binding of carboxylated latex particles as a case study

In this paper, we present a computer simulation study of the ion binding process at an ionizable surface using a semi-grand canonical Monte Carlo method that models the surface as a discrete distribution of charged and neutral functional groups in equilibrium with explicit ions modelled in the context of the primitive model. The parameters of the simulation model were tuned and checked by comparison with experimental titrations of carboxylated latex particles in the presence of different ionic strengths of monovalent ions. The titration of these particles was analysed by calculating the degree of dissociation of the latex functional groups vs. pH curves at different background salt concentrations. As the charge of the titrated surface changes during the simulation, a procedure to keep the electroneutrality of the system is required. Here, two approaches are used with the choice depending on the ion selected to maintain electroneutrality: counterion or coion procedures. We compare and discuss the difference between the procedures. The simulations also provided a microscopic description of the electrostatic double layer (EDL) structure as a function of pH and ionic strength. The results allow us to quantify the effect of the size of the background salt ions and of the surface functional groups on the degree of dissociation. The non-homogeneous structure of the EDL was revealed by plotting the counterion density profiles around charged and neutral surface functional groups. © 2011 American Institute of Physics.

Seasonal dynamics and net production of disolved organic carbon in an oligotrophic coastal environment

To understand dissolved organic carbon (DOC) seasonal dynamics in a coastal oligotrophic site in the north-western Mediterranean Sea, we monitored DOC concentrations monthly over 3 yr, together with the meteorological data and the food-web-related biological processes involved in DOC dynamics. Additional DOC samples were taken in several inshore−offshore transects along the Catalan coast. We found DOC concentrations of ~60 µmol C l−1 in winter, with increasing values through the summer and autumn and reaching 100 to 120 µmol C l−1 in November. There was high inter-annual variability in this summer DOC accumulation, with values of 36, 69 and 13 µmol C l−1 for 2006, 2007 and 2008, respectively. The analysis of the microbial food-web processes involved in the DOC balance did not reveal the causes of this accumulation, since the only occasion on which we observed net DOC production (0.3 ± 1 µmol C l−1 d−1 on average) was in 2007, and the negative DOC balance of 2006 and 2008 did not prevent DOC accumulating. The DOC accumulation episodes coincided with low rates of water renewal (average 0.037 ± 0.021 d−1 from May to October) compared with those of winter to early spring (average 0.11 ± 0.048 d−1 from November to April). Indeed, the amount of DOC accumulated each year was inversely correlated with the average summer rainfall. We hypothesize that decreased DOC turn-over due to photochemical or biological processes mostly active during the summer and low water renewal rate combine to determine seasonal DOC accumulation and influence its inter-annual variability.

Self-Organising Maps and Correlation Analysis as a Tool to Explore Patterns in Excitation-Emission Matrix Data Sets and to Discriminate Dissolved Organic Matter Fluorescence Components

Dissolved organic matter (DOM) is a complex mixture of organic compounds, ubiquitous in marine and freshwater systems. Fluorescence spectroscopy, by means of Excitation-Emission Matrices (EEM), has become an indispensable tool to study DOM sources, transport and fate in aquatic ecosystems. However the statistical treatment of large and heterogeneous EEM data sets still represents an important challenge for biogeochemists. Recently, Self-Organising Maps (SOM) has been proposed as a tool to explore patterns in large EEM data sets. SOM is a pattern recognition method which clusterizes and reduces the dimensionality of input EEMs without relying on any assumption about the data structure. In this paper, we show how SOM, coupled with a correlation analysis of the component planes, can be used both to explore patterns among samples, as well as to identify individual fluorescence components. We analysed a large and heterogeneous EEM data set, including samples from a river catchment collected under a range of hydrological conditions, along a 60-km downstream gradient, and under the influence of different degrees of anthropogenic impact. According to our results, chemical industry effluents appeared to have unique and distinctive spectral characteristics. On the other hand, river samples collected under flash flood conditions showed homogeneous EEM shapes. The correlation analysis of the component planes suggested the presence of four fluorescence components, consistent with DOM components previously described in the literature. A remarkable strength of this methodology was that outlier samples appeared naturally integrated in the analysis. We conclude that SOM coupled with a correlation analysis procedure is a promising tool for studying large and heterogeneous EEM data sets.

Self-Organising Maps and Correlation Analysis as a Tool to Explore Patterns in Excitation-Emission Matrix Data Sets and to Discriminate Dissolved Organic Matter Fluorescence Components

Dissolved organic matter (DOM) is a complex mixture of organic compounds, ubiquitous in marine and freshwater systems. Fluorescence spectroscopy, by means of Excitation-Emission Matrices (EEM), has become an indispensable tool to study DOM sources, transport and fate in aquatic ecosystems. However the statistical treatment of large and heterogeneous EEM data sets still represents an important challenge for biogeochemists. Recently, Self-Organising Maps (SOM) has been proposed as a tool to explore patterns in large EEM data sets. SOM is a pattern recognition method which clusterizes and reduces the dimensionality of input EEMs without relying on any assumption about the data structure. In this paper, we show how SOM, coupled with a correlation analysis of the component planes, can be used both to explore patterns among samples, as well as to identify individual fluorescence components. We analysed a large and heterogeneous EEM data set, including samples from a river catchment collected under a range of hydrological conditions, along a 60-km downstream gradient, and under the influence of different degrees of anthropogenic impact. According to our results, chemical industry effluents appeared to have unique and distinctive spectral characteristics. On the other hand, river samples collected under flash flood conditions showed homogeneous EEM shapes. The correlation analysis of the component planes suggested the presence of four fluorescence components, consistent with DOM components previously described in the literature. A remarkable strength of this methodology was that outlier samples appeared naturally integrated in the analysis. We conclude that SOM coupled with a correlation analysis procedure is a promising tool for studying large and heterogeneous EEM data sets.