Multivariate Tiered Approach To Highlight the Link between Large-Scale Integrated Pesticide Concentrations from Polar Organic Chemical Integrative Samplers and Watershed Land Uses.

This paper presents a multi-step methodology to identify relationships between integrative pesticide quantifications and land uses on a given watershed of the Adour-Garonne Basin (Southwestern France). In fact, a large amount of pesticide concentration data was collected from 51 sites located in the Adour-Garonne Basin for a 1 year monitoring period in 2016. The sampling devices used here were polar organic chemical integrative samplers (POCIS), which provided time-weighted average concentration estimates. For each study site, its associated watershed and land cover distribution were determined using Corine Land Cover 2012 (CLC 2012) and Geographic Information System (GIS). The large-scale data were analyzed using multivariate statistical analyses, such as hierarchical cluster analysis (HCA) and principal component analysis (PCA). HCA grouped the 51 sites into five clusters with similar primary land uses. Next, the integrated pesticide concentration and land use distribution data sets were analyzed in a PCA. The key variables responsible for discriminating the sample sites showed distribution patterns consistent with specific land uses. To confirm these observations, pesticide fingerprints from sites with contrasting land uses were compared using a waffle method. The overall multivariate approach allowed for the identification of contamination sources related to their likely initial use, at the watershed level, that could be useful for preventing or containing pesticide pollution beyond simply acting on areas at risk.

Diffusive gradients in thin films (DGT): A suitable tool for metals/metalloids monitoring in continental waterbodies at the large network scale.

The contribution of Diffusive Gradients in Thin films (DGT) passive sampling to continental water quality monitoring was assessed in a real measurement network (6 sampling campaigns, 17 stations). Ten metals/metalloids (Al, Zn, Ni, Cd, Cu, Pb, Cr, As, Se and Sb) were studied using the control laboratory's working conditions with grab and DGT passive sampling. The DGT field deployments were robust, with a 3% sampler loss rate and a <65% average relative deviation between duplicates. Compared to grab sampling, DGT showed a similar quantification frequency for half of the targeted elements but showed a higher frequency for the other half (e.g., Cd quantification at 20% with grab sampling vs. 97% with DGT). Similar concentration trends were established using DGT and grab sampling at most sites throughout the year. Notably, for some elements, trends were only provided by DGT sampling. A study of several DGT blanks showed that the device contamination was occasional and originated primarily from cross-contamination during the disassembly step. Considering this contamination, the operational sensitivity by DGT was at least between 1 and 5 times greater in comparison to that by grab sampling. Estimations of the economic cost revealed that measurement networks cost 2 to 3 times more when monitored by DGT compared to standard grab monitoring. However, the information obtained based on each type of sampling method is different. Grab sampling is easy to implement and can highlight high contamination peaks. The DGT concentrations are averaged over time and are relevant to chronic exposure evaluations. Considering the good performance of the DGT sampling highlighted in this study and its complementarity with grab sampling in terms of water quality assessments, a combination of these two types of sampling, which can be affordable, should improve the water quality evaluation within monitoring networks.

Combination of passive and grab sampling strategies improves the assessment of pesticide occurrence and contamination levels in a large-scale watershed.

Fifty-one monitoring stations from the Water Framework Directive network (2000/60/CE) were selected in the Adour-Garonne basin (117,650 km2, SW France). These stations were characterized by a diversity of land use, implying different water pesticide contamination profiles. In each, Polar Organic Chemical Integrative Sampler (POCIS) deployment (14 days) and grab water samples (1 per period) were performed 6 times in 2016 in order to obtain contamination levels (29 pesticides monitored). The large amount of data collected during this 1-year monitoring required specific graphical and map processing to compare the information provided by POCIS and grab samples. Graphical projections demonstrated that with POCIS the number of quantified pesticides and the quantification frequencies were higher than with grab samples. Additionally, projections showed that POCIS provided better temporal representativeness of monthly contamination levels. Indeed, the POCIS data showed seasonal trends which were directly linked with the use of each pesticide (application period) and the land use of each sampling site, that was not visible with the grab samples data. Map projections of the measured concentrations, using a common scale for the two sampling strategies, clearly showed the strengths of the POCIS deployment and the link between measured contamination levels, quantified pesticides and land use. Finally, this study shows that the combination of grab sample data (magnitude of contamination peaks) and POCIS data (average concentration over a given period) provided more complete and reliable knowledge of the contamination levels in the Basin than either method alone.