Evaluating the applicability of regulatory leaching tests for assessing the hazards of Pb-contaminated soils.

Soil contamination is a major environmental problem due to the ecological threat it poses. In this work, electron probe microanalysis (EPMA), X-ray diffraction (XRD), and leaching studies were employed to explain the different leaching behaviors of non-stabilized and stabilized soils. The applicability of the leaching fluids used in the toxicity characteristic leaching procedure (TCLP) and Australian Standards, AS 4439.1-1997 for assessing the hazards of contaminated soils was investigated as was the leaching of lead from soil stabilized by cement and buffered phosphate techniques. The results showed Pb speciation in the soil highly influenced metal leaching. The synthetic leaching fluids were unable to provide a reliable estimation of Pb concentration in the municipal landfill leachate (ML) due to the absence of organic ligands capable of forming stable complexes with the lead. Water provided the closest representation of lead leaching from the non-stabilized and phosphate stabilized soils while sodium tetraborate buffer was found to be suitable for cement-stabilized soil in a non-putrescible landfill leachate system. A comparison of stabilization methods revealed that the buffered phosphate technique was more suitable for stabilizing the lead in the soil relative to cement stabilization.

Comparison of spectra using a Bayesian approach. An argument using oil spills as an example.

The problem of assigning a probability of matching a number of spectra is addressed. The context is in environmental spills when an EPA needs to show that the material from a polluting spill (e.g., oil) is likely to have originated at a particular site (factory, refinery) or from a vehicle (road tanker or ship). Samples are taken from the spill, and candidate sources and are analyzed by spectroscopy (IR, fluorescence) or chromatography (GC or GC/MS). A matching algorithm is applied to pairs of spectra giving a single statistic (R). This can be a point-to-point match giving a correlation coefficient or a Euclidean distance or a derivative of these parameters. The distributions of R for same and different samples are established from existing data. For matching statistics with values in the range {0,1} corresponding to no match (0) to a perfect match (1) a beta distribution can be fitted to most data. The values of R from the match of the spectrum of a spilled oil and of each of a number of suspects are calculated and Bayes' theorem is applied to give a probability of matches between spill sample and each candidate and the probability of no match at all. The method is most effective when simple inspection of the matching parameters does not lead to an obvious conclusion; i.e., there is overlap of the distributions giving rise to dubiety of an assignment. The probability of finding a matching statistic if there were a match to the probability of finding it if there were no match, expressed as a ratio (called the likelihood ratio), is a sensitive and useful parameter to guide the analyst. It is proposed that this approach may be acceptable to a court of law and avoid challenges of apparently subjective opinion of an analyst. Examples of matching the fluorescence and infrared spectra of diesel oils are given.

Kriging method evaluation for assessing the spatial distribution of urban soil lead contamination.

Describing contaminant spatial distribution is an integral component of risk assessment. Application of geostatistical techniques for this purpose has been demonstrated previously. These techniques may provide both an estimate of the concentration at a given unsampled location, as well as the probability that the concentration at that location will exceed a critical threshold concentration. This research is a comparative study between multiple indicator kriging and kriging with the cumulative distribution function of order statistics, with both local and global variograms. The aim was to determine which of the four methods is best able to delineate between "contaminated" and "clean" soil. The four methods were validated with a subset of data values that were not used in the prediction. Method performance was assessed by calculating the root mean square error (RMSE), analysis of variance, the proportion of sites misclassified by each method as either "clean" when they were actually "contaminated" or vice versa, and the expected loss for each misclassification type. The data used for the comparison were 807 topsoil Pb concentrations from the inner-Sydney suburbs of Glebe and Camperdown, Australia. While there was very little difference between the four methods, multiple indicator kriging was found to produce the most accurate predictions for delineating "clean" from "contaminated" soil.