A new application of PC-ANN in spectrophotometric determination of acidity constants of PAR

The acidity constants of the PAR were determined by Principal Component Analysis Artificial Neural Networks, using simulated and experimental spectral data. Triprotic acid mass balance equations and corresponding spectral profiles generated by a Gaussian model were used to simulate all required absorbance-pH data. A constant noise with zero mean and different standard deviations (1-3% of the maximum absorbance values) was superimposed on the generated simulated spectra. A triangular experimental design was used to select and produce the different simulated acidity constants. The effects of white noise at different levels were also studied to check the prediction ability of the model. A fully experimental data set, photometric titration data of PAR at pH=1.50-13.00 range was used as a test set. The obtained acidity constants are in a good agreement with previously reported values using DATAN software

Local versus field scale soil heterogeneity characterization – a challenge for representative sampling in pollution studies

This study is a contribution to development of a heterogeneity characterization facility for "next-generation" soil sampling aimed, for example, at more realistic and controllable pesticide variability in laboratory pots in experimental environmental contaminant assessment. The role of soil heterogeneity in quantification of a set of exemplar parameters is described, including a brief background on how heterogeneity affects sampling/monitoring procedures in environmental pollutant studies. The theory of sampling (TOS) and variographic analysis has been applied to develop a more general fit-for-purpose soil heterogeneity characterization approach. All parameters were assessed in large-scale transect (1–100 m) vs. small-scale (0.1–0.5 m) replication sampling point variability. Variographic profiles of experimental analytical results from a specific well-mixed soil type show that it is essential to sample at locations with less than a 2.5 m distance interval to benefit from spatial auto-correlation and thereby avoid unnecessary, inflated compositional variation in experimental pots; this range is an inherent characteristic of the soil heterogeneity and will differ among other soils types. This study has a significant carrying-over potential for related research areas, e.g. soil science, contamination studies, and environmental monitoring and environmental chemistry