Novel approaches to modelling and monitoring of heavy metal - contaminated sites

Abstract

Soil contamination is becoming more prevalent, and with increasing global population, more people are being affected. Contaminated site assessment informs management of contaminant sources, affected soil and groundwater. Inaccuracy of assessment can lead to misclassification of sites, resulting in unnecessary remediation, or failing to remediate where it is required. The research presented in this thesis sought to reduce the risk of misclassification by addressing four key aspects of assessment; sampling, detection, mapping and monitoring. The study sought to refine sample size requirements by estimating the number of samples required to determine if the mean at a site exceeded Australian contamination thresholds. A large number of samples were required, yet this may be unrealistic due to time and cost. Portable X-ray Fluorescence spectroscopy (PXRF) provides real-time analysis of soil heavy metal concentrations, enabling more samples to be collected. There is room for improvement in the accuracy of PXRF measurements, so the study explored the potential of integrating these with spectra obtained from visible-near infrared spectroscopy (vis-NIR). Integration of the two spectral methods provided a measure of precision, yet only a marginal increase in accuracy. To improve mapping methods this study obtained measurements from within the Sydney estuary catchment and integrated these, alongside freely available covariates, into linear mixed models to predict lead and zinc concentrations in soil across the catchment. The final chapter of the thesis combined linear mixed models from two time points to predict change in heavy metal concentrations over time at a remediated Sydney parkland. The models provided a detailed snapshot of heavy metal distributions and factors influencing these distributions over time. It is evident in this thesis that much can be done to improve contaminated site assessment and help ensure land is safe and secured for future generations.