Abstract:
Providing safe and high quality drinking water is essential for a high quality of life. However, the water resources in Europe are threatened by various sources of
contamination. This has led to the development of concepts and technologies to create a basis for provision of safe and high quality drinking water, which had thus resulted in the formation of the Artificial Recharge Demonstration project (ARTDEMO). The
overall aim of this thesis in relation to the ARTDEMO project was to develop a realtime
automated water monitoring system, capable of using data from various complementary sources to determine the amounts of inorganic and organic pollutants.
The application of multivariate calibration to differential pulse anodic stripping
voltammograms and fluorescence spectra (emission and excitation-emission matrix) is
presented. The quantitative determination of cadmium, lead and copper acquired on
carbon-ink screen-printed electrodes, arsenic and mercury acquired on gold-ink
screen-printed electrodes, in addition to the quantitative determination of anthracene,
phenanthrene and naphthalene have been realised. The statistically inspired
modification of partial least squares (SIMPLS) algorithm has been shown to be the
better modelling tool, in terms of the root mean square error of prediction (RMSEP),
in conjunction with application of data pre-treatment techniques involving rangescaling,
filtering and weighting of variables. The % recoveries of cadmium, lead and
copper in a certified reference material by graphite furnace atomic absorption
spectrometry (GF-AAS) and multivariate calibration are in good agreement.
The development of a prototype application on a personal digital assistant (PDA)
device is described. At-line analysis at potential contamination sites in which an
instant response is required is thus possible. This provides quantitative screening of target metal ions. The application imports the acquired voltammograms, standardises
them against the laboratory-acquired voltammograms (using piecewise direct
standardisation), and predicts the concentrations of the target metal ions using
previously trained SIMPLS models.
This work represents significant progress in the development of analytical techniques
for water quality determination, in line with the ARTDEMO project's aim of
maintaining a high quality of drinking water.