Combined cluster and discriminant analysis (CCDA) as a chemometric tool in compound specific isotope analysis of diesel fuels was studied. The stable carbon isotope ratios (δ13C) of n-alkanes in diesel fuel can be used to characterize or differentiate diesels originating from different sources. We investigated 25 diesel fuel samples representing 20 different brands. The samples were collected from 25 different service stations in 11 European countries over a 2 year period. The n-alkane fraction of diesel fuels was separated using solid-state urea clathrate formation combined with silica gel fractionation. The stable carbon isotope ratios of C10–C24 n-alkanes were measured with gas chromatography–isotope ratio mass spectrometry (GC–IRMS) using perdeuterated n-alkanes as internal standards. Beside the 25 samples one additional diesel fuel was prepared and measured three times to get totally homogenous samples in order to test the performance of our analytical and statistical routine. Stable isotope ratio data were evaluated with hierarchical cluster analysis (HCA), principal component analysis (PCA) and CCDA. CCDA combines two multivariate data analysis methods hierarchical cluster analysis with linear discriminant analysis (LDA). The main idea behind CCDA is to compare the goodness of preconceived (based on the sample origins) and random groupings. In CCDA all the samples were compared pairwise. The results for the parallel sample preparations showed that the analytical procedure does not have any significant effect on the δ13C values of n-alkanes. The three parallels proved to be totally homogenous with CCDA. HCA and PCA can be useful tools when the examining of the relationship among several samples is in question. However, these two techniques cannot be always decisive on the origin of similar samples. The initial hypothesis that all diesel fuel samples are considered chemically unique was verified by CCDA. The main advantage of CCDA is that it gives an objective index number about the level of similarity among the investigated samples. Thus the application of CCDA supplemented by the traditionally used multivariate methods greatly improves the efficiency of statistical analysis in the CSIA of diesel fuel samples.

Ten locations in the Notranjska region, Slovenia, with different land use in the catchment (town, village and agricultural areas), including reference points with different geological composition considered as unpolluted sites, were sampled for water and aquatic moss to evaluate environmental assessment in fresh water systems of the Sava River watershed. Samples of fresh water and Fontinalis antipyretica were taken in all four seasons during the years 2010 and 2012. The water chemistry of the investigated locations was dominated by , while concentrations of seasonally ranged from 2.1 to 6.4 mg L−1 and at one of the reference sites did not exceed 1.3 mg L−1. δ13CDIC values seasonally ranged from −13.3 to −8.1 ‰ and indicated waters dominated by degradation of organic matter and dissolution of carbonates. δ13Cplant values of F. antipyretica seasonally ranged from −45 to −32.9 ‰ and of δ15Nplant from −0.2 to 6.5 ‰. The higher δ15N value of 6.5 ‰ found in F. antipyretica was related to agricultural activity i...

Compound-specific isotope analysis (CSIA) receives increasing interest for its ability to detect natural degradation of pesticides and pharmaceuticals. Despite recent laboratory studies, CSIA investigations of such micropollutants in the environment are still rare. To explore the certainty of information obtainable by CSIA in a near-environmental setting, a pulse of the pesticide bentazone, the pesticide metabolite 2,6-dichlorobenzamide (BAM), and the pharmaceuticals diclofenac and ibuprofen was released into a mesoscale aquifer with quasi-two-dimensional flow. Concentration breakthrough curves (BTC) of BAM and ibuprofen demonstrated neither degradation nor sorption. Bentazone was transformed but did not sorb significantly, whereas diclofenac showed both degradation and sorption. Carbon and nitrogen CSIA could be accomplished in similar concentrations as for “traditional” priority pollutants (low μg/L range), however, at the cost of uncertainties (0.4−0.5‰ (carbon), 1‰ (nitrogen)). Nonetheless, invariant carbon and nitrogen isotope values confirmed that BAM was neither degraded nor sorbed, while significant enrichment of 13C and in particular 15N corroborated transformation of diclofenac and bentazone. Retardation of diclofenac was reflected in additional 15N sorption isotope effects, whereas isotope fractionation of transverse dispersion could not be identified. These results provide a benchmark on the performance of CSIA to monitor the reactivity of micropollutants in aquifers and may guide future efforts to accomplish CSIA at even lower concentrations (ng/L range).

Stable isotope tools are increasingly applied for in-depth evaluation of biodegradation of organic pollutants at contaminated field sites. They can be divided into three methods i) determination of changes in natural abundance of stable isotopes using compound-specific stable isotope analysis (CSIA), ii) detection of incorporation of stable-isotope label from a stable-isotope labelled target compound into degradation and/or mineralisation products and iii) determination of stable-isotope label incorporation into biomarkers using stable isotope probing (SIP). Stable isotope tools have been applied as key monitoring tools for multiple-line-of-evidence-approaches (MLEA) for sensitive evaluation of pollutant biodegradation. This review highlights the application of CSIA, SIP and MLEA including stable isotope tools for assessing natural and stimulated biodegradation of organic pollutants in field studies dealing with soil and groundwater contaminations.