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After nearly a century of use in numerous munition platforms, TNT and RDX contamination has turned up largely in the environment due to ammunition manufacturing or as part of releases from low-order detonations during training activities. Although the basic knowledge governing the environmental fate of TNT and RDX are known, accurate predictions of TNT and RDX persistence in soil remain elusive, particularly given the universal heterogeneity of pedomorphic soil types. In this work, we proposed a new solution for modeling the sorption and persistence of these munition constituents as multivariate mathematical functions correlating soil attribute data over a variety of taxonomically distinct soil types to contaminant behavior, instead of a single constant or parameter of a specific absolute value. To test this idea, we conducted experiments measuring the sorption of TNT and RDX on taxonomically different soil types that were extensively physical and chemically characterized. Statistical decomposition of the log-transformed, and auto-scaled soil characterization data using the dimension-reduction technique PCA (principal component analysis) revealed a strong latent structure based in the multiple pairwise correlations among the soil properties. TNT and RDX sorption partitioning coefficients (KD-TNT and KD-RDX) were regressed against this latent structure using partial least squares regression (PLSR), generating a 3-factor, multivariate linear functions. Here, PLSR models predicted KD-TNT and KD-RDX values based on attributes contributing to endogenous alkaline/calcareous and soil fertility criteria, respectively, exhibited among the different soil types: We hypothesized that the latent structure arising from the strong covariance of full multivariate geochemical matrix describing taxonomically distinguished soil types may provide the means for potentially predicting complex phenomena in soils. The development of predictive multivariate models tuned to a local soil's taxonomic designation would have direct benefit to military range managers seeking to anticipate the environmental risks of training activities on impact sites.
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PMID:Multivariate functions for predicting the sorption of 2,4,6-trinitrotoluene (TNT) and 1,3,5-trinitro-1,3,5-tricyclohexane (RDX) among taxonomically distinct soils. 2745 1

The objective of this work was to measure infrared spectra of high explosive materials (HE) in wide spectral range in order to acquire information for their complete characterization and find out the regions that are the most discriminatory for each material. Four HEs were measured by means of Fourier Transform Infrared (FTIR) spectroscopy in a very broad range (from near- via mid- to far-IR). Obtained spectra were subsequently evaluated using multivariate statistical methods for dimension reduction and results grouping. Clustering was assessed in terms of compactness and stability in order to distinguish which region or regions are most suitable for the identification based on spectral signature. Based on outcomes of visualization method (silhouette plot) used to compare results of implemented chemometric methods (HCA, PAM, and PCA) done on FTIR spectra collected for four high explosive materials (PETN, C-4, RDX, and TNT) within all regions, it seems that the mid-IR region is the most informative for the distinction among analyzed HE materials based on substance spectral signatures. However, it is worth noticing that also the near-IR region can be used for good differentiation.
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PMID:Broad Range FTIR Spectroscopy and Multivariate Statistics for High Energetic Materials Discrimination. 3212 27