Olivier Briand

Multi-class pesticide analysis in human hair by gas chromatography tandem (triple quadrupole) mass spectrometry with solid phase microextraction and liquid injection.

A method for the simultaneous detection and quantification of 22 pesticides from different chemical classes was developed using solid-phase microextraction (SPME) and gas chromatography tandem (triple quadrupole) mass spectrometry. Pesticides were extracted from 50mg of pulverized hair with acetonitrile. The extract was submitted to two successive steps of direct immersion-SPME at 30°C and 90°C or to a liquid injection without SPME in order to obtain optimized conditions for each of the 22 analytes investigated. Validation parameters were significantly influenced by both the injection mode (SPME vs liquid injection) and the temperature of SPME. Limits of quantification ranged from 0.05 pg mg(-1) for trifluralin to 10 pg mg(-1) for pentachlorophenol. The application of the validated method to the analysis of samples collected from non-occupationally exposed volunteers demonstrated the presence of pesticides in all the samples tested. Altogether, 13 different analytes were detected at concentration above the limit of quantification.

Sampling atmospheric pesticides with SPME: laboratory developments and field study.

To estimate the atmospheric exposure of the greenhouse workers to pesticides, solid phase microextraction (SPME) was used under non-equilibrium conditions. Using Ficks law of diffusion, the concentrations of pesticides in the greenhouse can be calculated using pre-determined sampling rates (SRs). Thus the sampling rates (SRs) of two modes of SPME in the lab and in the field were determined and compared. The SRs for six pesticides in the lab were 20.4-48.3 mL min(-1) for the exposed fiber and 0.166-0.929 mL min(-1) for the retracted fiber. In field sampling, two pesticides, dichlorvos and cyprodinil were detected with exposed SPME. SR with exposed SPME for dichlorvos in the field (32.4 mL min(-1)) was consistent with that in the lab (34.5 mL min(-1)). SR for dichlorvos in the field (32.4 mL min(-1)) was consistent with that in the lab (34.5 mL min(-1)). The trends of temporal concentration and the inhalation exposure were also obtained.

Application of XAD-2 resin-based passive samplers and SPME–GC–MS/MS analysis for the monitoring of spatial and temporal variations of atmospheric pesticides in Luxembourg

Passive air sampling has been shown to be a very interesting alternative to high-volume sampling by overcoming its disadvantages (size, weight, expensiveness). However, to date, only limited data is available about passive air sampling of current-use pesticides. In order to test if passive samplers allow monitoring of spatial and temporal variations of atmospheric pesticide concentrations, five XAD-2-resin based passive air samplers were deployed at five locations in Luxembourg. Samplers were analyzed using accelerated solvent extraction coupled to solid-phase microextraction and gas chromatography with tandem mass spectrometry. Collected data was used to study the spatial and temporal variations of the concentrations of the compounds. Twenty two pesticides were detected between March and October, while no pesticides were detected from November to February. Highest concentrations were measured on the rural sites, suggesting that the used XAD-2 resin-based passive samplers allow the simultaneous monitoring of multiple current-use pesticides and identifying spatial and temporal variations.

Which persistent organic pollutants can we map in soil using a large spacing systematic soil monitoring design? A case study in Northern France.

Persistent organic pollutants (POPs) impact upon human and animal health and the wider environment. It is important to determine where POPs are found and the spatial pattern of POP variation. The concentrations of 90 molecules which are members of four families of POPs and two families of herbicides were measured within a region of Northern France as part of the French National Soil Monitoring Network (RMQS: Réseau de Mesures de la Qualité des Sols). We also gather information on five covariates (elevation, soil organic carbon content, road density, land cover and population density) which might influence POP concentrations. The study region contains 105 RMQS observation sites arranged on a regular square grid with spacing of 16 km. The observations include hot-spots at sites of POP application, smaller concentrations where POPs have been dispersed and observations less than the limit of quantification (LOQ) where the soil has not been impacted by POPs. Fifty nine of the molecules were detected at less than 50 sites and hence the data were unsuitable for spatial analyses. We represent the variation of the remaining 31 molecules by various linear mixed models which can include fixed effects (i.e. linear relationships between the molecule concentrations and covariates) and spatially correlated random effects. The best model for each molecule is selected by the Akaike Information Criterion. For nine of the molecules, spatial correlation is evident and hence they can potentially be mapped. For four of these molecules, the spatial correlation cannot be wholly explained by fixed effects. It appears that these molecules have been transported away from their application sites and are now dispersed across the study region with the largest concentrations found in a heavily populated depression. More complicated statistical models and sampling designs are required to explain the distribution of the less dispersed molecules.

Fungicide Volatilization Measurements: Inverse Modeling, Role of Vapor Pressure, and State of Foliar Residue

Few data sets of pesticide volatilization from plants at the field scale are available. In this work, we report measurements of fenpropidin and chlorothalonil volatilization on a wheat field using the aerodynamic gradient (AG) method and an inverse dispersion modeling approach (using the FIDES model). Other data necessary to run volatilization models are also reported: measured application dose, crop interception, plant foliage residue, upwind concentrations, and meteorological conditions. The comparison of the AG and inverse modeling methods proved the latter to be reliable and hence suitable for estimating volatilization rates with minimized costs. Different diurnal/nocturnal volatilization patterns were observed: fenpropidin volatilization peaked on the application day and then decreased dramatically, while chlorothalonil volatilization remained fairly stable over a week-long period. Cumulated emissions after 31 h reached 3.5 g ha(-1) and 5 g ha(-1), respectively (0.8% and 0.6% of the theoretical application dose). A larger difference in volatilization rates was expected given differences in vapor pressure, and for fenpropidin, volatilization should have continued given that 80% of the initial amount remained on plant foliage for 6 days. We thus ask if vapor pressure alone can accurately estimate volatilization just after application and then question the state of foliar residue. We identified adsorption, formulation, and extraction techniques as relevant explanations.

Spatial distribution of lindane in topsoil of Northern France.

Lindane is a persistent organochlorine insecticide and the use of this insecticide in agriculture was banned in France in 1998. In this study we investigated the concentrations of lindane in top soil in Northern France and used robust geostatistics to map the geographical distribution of lindane. The study was based on a 16 km x 16 km grid covering an area of ca 25,000 km(2). Lindane was found in all soils, even those from non-agricultural-application areas. Very low ratios of alpha-/gamma-HCH and delta-/gamma-HCH suggested that a long time had passed since technical HCH was used in the studied area, or that emission sources of lindane were still present. A strong gradient in lindane concentration was observed, with the highest lindane concentrations in an area located in the northern region. Results suggested that some of the lindane observed in the high concentration area may have come from volatilization of old lindane applied to intensively cultivated areas, which was then transported by prevailing winds coming from the south-west and deposited in a densely inhabited depression.

Flexibility of solid-phase microextraction for passive sampling of atmospheric pesticides.

For low volatile pesticides, the applications of solid-phase microextraction (SPME) as an air sampler were reported with sampling time chosen in the linear stage of the sorption kinetics because of long equilibrium time. In these pre-equilibrium conditions, sampling rates (SRs) expressed as the volume of air sampled by the SPME sampler per unit of time, were used to estimate analytes concentrations in air. In the present study, to achieve good extraction performance and accurate calibration, the sorption kinetics of several pesticides with SPME were investigated in detail, with a focus on parameters influencing SRs. Linear air velocity was found to be the main parameter affecting SRs. For exposed fibers, with air velocities below 20-25 cms(-1), SRs increased with increasing air velocity. When linear air velocity was equal to or greater than 25-30 cms(-1), it had little effect on SRs. To improve the flexibility of SPME, different configurations of SPME were compared, i.e. different lengths of fibers exposed, retracted fibers, exposed fibers with grids. SRs were linearly proportional to exposed lengths of fibers. Using grids, lower SRs and wider calibration time range were achieved. SRs for retracted fibers were the lowest among the different experimented configurations. The accuracy of calibration was improved and more flexibility of SPME was provided.

First evidence of large-scale PAH trends in French soils

Polycyclic aromatic hydrocarbons (PAHs) are widespread organic pollutants. Soils are a reservoir of PAHs because some soil constituents favour PAH accumulation. Therefore, soil is a key indicator of the degree of contamination. So far, studies mapping soil PAH levels over large territories are very rare. Here, we report the first nation-wide maps of soil PAHs in France. Results were obtained within the French National Soil Monitoring Network, which is the first European network monitoring systematically soil PAHs. We used advanced geostatistics to map PAH distribution over the whole French territory. Our results show clear trends of PAH levels at the nation scale. For instance, the highest PAH levels are found in Northern and Eastern France. This high contamination is explained by the intense industrial activity of these regions during the last century. High levels of PAH are also found near some coastlines. This observation could be explained by long-range atmospheric transportation. In addition, we found that light PAHs are rarely found in French topsoils.

Spatial distribution of Lindane concentration in topsoil across France.

Lindane [γ-hexachlorocyclohexane (γ-HCH)] is an organochlorine pesticide with toxic effects on humans. It is bioaccumulative and can remain in soils for long periods, and although its use for crop spraying was banned in France in 1998, it is possible that residues from before this time remain in the soil. The RMQS soil monitoring network consists of soil samples from 2200 sites on a 16 km regular grid across France, collected between 2002 and 2009. We use 726 measurements of the Lindane concentration in these samples to (i) investigate the main explanatory factors for its spatial distribution across France, and (ii) map this distribution. Geostatistics provides an appropriate framework to analyze our spatial dataset, though two issues regarding the data are worth special consideration: first, the harmonization of two subsets of the data (which were analyzed using different measurement processes), and second, the large proportion of data from one of these subsets that fell below a limit of quantification. We deal with these issues using recent methodological developments in geostatistics. Results demonstrate the importance of land use and rainfall for explaining part of the variability of Lindane across France: land use due to the past direct input of Lindane on cropland and its subsequent persistence in the soil, and rainfall due to the re-deposition of volatilized Lindane. Maps show the concentrations to be generally largest in the north and northwest of France, areas of more intensive agricultural land. We also compare levels to some contamination thresholds taken from the literature, and present maps showing the probability of Lindane concentrations exceeding these thresholds across France. These maps could be used as guidelines for deciding which areas require further sampling before some possible remediation strategy could be applied.

Analyzing the spatial distribution of PCB concentrations in soils using below-quantification limit data

Polychlorinated biphenyls (PCBs) are highly toxic environmental pollutants that can accumulate in soils. We consider the problem of explaining and mapping the spatial distribution of PCBs using a spatial data set of 105 PCB-187 measurements from a region in the north of France. A large proportion of our data (35%) fell below a quantification limit (QL), meaning that their concentrations could not be determined to a sufficient degree of precision. Where a measurement fell below this QL, the inequality information was all that we were presented with. In this work, we demonstrate a full geostatistical analysis-bringing together the various components, including model selection, cross-validation, and mapping-using censored data to represent the uncertainty that results from below-QL observations. We implement a Monte Carlo maximum likelihood approach to estimate the geostatistical model parameters. To select the best set of explanatory variables for explaining and mapping the spatial distribution of PCB-187 concentrations, we apply the Akaike Information Criterion (AIC). The AIC provides a trade-off between the goodness-of-fit of a model and its complexity (i.e., the number of covariates). We then use the best set of explanatory variables to help interpolate the measurements via a Bayesian approach, and produce maps of the predictions. We calculate predictions of the probability of exceeding a concentration threshold, above which the land could be considered as contaminated. The work demonstrates some differences between approaches based on censored data and on imputed data (in which the below-QL data are replaced by a value of half of the QL). Cross-validation results demonstrate better predictions based on the censored data approach, and we should therefore have confidence in the information provided by predictions from this method.