Assessment of Metal Contamination in Doñana National Park (Spain) using Crayfish (Procamburus Clarkii)

Water quality assessment in the Aznalcollar area was attempted using multivariate methods based on heavy metal concentrations in red swamp crayfish (Procamburus clarkii). Trace levels of four heavy metals, copper (Cu), zinc (Zn), cadmium (Cd) and lead (Pb), were detected in crayfish from eleven different stations. Principal component analysis (PCA) highlighted a gradient of contamination between the sampling stations. Cluster analysis (CA) distinguished three groups of stations. Discriminant analysis also differentiated three groups. The group centroids of the first discriminant function were used to devise an index that varies according to the source of the crayfish. These standardized values are proposed for use as a water quality index. The ability of this index to successfully predict environmental quality was proved with random samples.     

Dermal exposure to pesticides in greenhouses workers: discrimination and selection of variables for the design of monitoring programs

Dermal exposure to pesticides is one of the main sanitaryproblems which greenhouses workers face. With the dual aimsof establishing both the body part that receives the greatestexposure and the variable that has greatest influence on this exposure level, 22 pesticide application trials were performed. Trials were carried out in different greenhouse vegetable crops,using different pesticides and different spray diameters from the spray gun. In order to determine dermal exposure, the wholebody method was used. Pieces of the applicator suit were subject to an extraction procedure and their pesticide contentdetermined using GC-NPD analysis. Multivariate analysis were applied to the data obtained. Principal component analysis showed that all trials produced a high exposure level on lowerleft leg and lower right leg. Cluster analysis distinguished between three sample groups. The most and the least affectedparts were clearly distinguished. Discriminant analysis indicated that the thin drop size of the spray gun is responsible for both the differences between groups and the minimum or maximum exposure level measured on the applicatorsuit. Therefore, selecting the variables, lower legs and thindrop size, is considered fundamental in designing programs formonitoring pesticide exposure.     

PLS and PCR Methods in the Assessment of Coastal Water Quality

Partial least squares regression analysis (PLS) and principal component regression analysis (PCR) were examined asmethodological procedures for assessing the quality of coastalwaters in a tourist area. Four variables related to the trophicstate of waters, namely nitrate, nitrite, ammonia and phosphate were analyzed. The models resulting from PLS and PCR were verysimilar. Both defined three groups of water masses characterizedby different nutrient loadings. These groups were in accordancewith those obtained by numerical classification. The PLS methodwas selected as the optimal model, on the basis of its lowerprediction errors (lower Press and Rmsd values). For managementpurposes, this statistical model allows mesotrophic conditions,reflecting some nutrient enrichment over background conditions,to be characterized and the successful diagnosis of additionalsamples within this context.