Background: MSc in Geology at Lund University

My project:

I am focusing on the degradation processes of chlorinated solvents, both natural and stimulated, where my main medium is groundwater. We know that induced polarization (IP) signals can help us visualize changes in the contamination over time in the ground (see Fig. 1).However, we are not sure what is giving rise to the signal and why or how it changes. To be able to answer these questions, I am working on characterizing changes in groundwater pollutants and changes of major ions within them. I will also investigate the microbial activity involved in the degradation process as well as compound-specific isotope data of carbon to quantify the degradation. To completely understand the changes in the IP-signals, we need to study the distribution and relationship of dissolved pollutants and adhesion to the grains. Over time, the contamination will move, therefore the dispersal patterns need to be understood and kept in mind when interpreting our IP-data.

Fig 1. An IP-survey over a CAH contamination, measured over time to investigate changes within the in-situ treated source zone (Sparrenbom C.J.et al., STOTEN 575 (2017) 767–778).

Background:

MSc in Geophysics (2016) from Aarhus University, Denmark.
http://pure.au.dk/portal/en/persons/id(9e5e14d1-c032-4469-bde5-e1fba2710bf2).html

My project:
The aim of the PhD project is to develop an algorithm for forward modelling and inversion of three-dimensional direct current (DC) and induced polarization (IP) data. The inversion code will be applied to field data to retrieve three-dimensional models of the subsurface geology, hydraulic permeability, and possible contamination.

The PhD project is carried out in the HydroGeophysics Group at Aarhus University.

PhD finish 2019

Background:

MSc in Geology at Lund University

https://lup.lub.lu.se/student-papers/search/publication/8944985

My project:
The aim of my project is to use hydrogeological and geochemical modelling as a tool to better understand the in situ remediation processes. The models will be created using a variety of building blocks, such as lithological observations (e.g. soil samplings, soil probings, drill cores), geophysical observations (refraction seismics, ERT), hydrogeological observations (groundwater level data loggers, slug tests) and soil- and groundwater chemistry data. Simulations of groundwater flow, mass transport and geochemical reactions will be calibrated and evaluated using past and future data.

By observing and visualizing changes in the contaminated area before, during and after remediation, the subsurface processes can be described. Results can then be used as calibration data for the integrated monitoring and verification method currently in development by researchers in the MIRACHL project.

PhD finish in 2022.

Background:

MSc in Applied Geophysics, Aristotle University of Thessaloniki

My project:

My project: My research focus is to optimize the geophysical monitoring with the DCIP (Direct Current resistivity and time-domain Induced Polarization) method to follow initiated remediation processes in situ and acquire a better understanding of the conditions in the subsurface.

The geophysical data needs to be analyzed in time and space and then processed with advanced algorithms to identify changes in the subsurface. The identified changes should be evaluated to exclude exogeneous effects (i.e. seasonal variations, rainfall events etc.) and the remaining anomalies should be linked with the remediation effects through “ground-truthing” (i.e. sampling).

My work involves data acquisition, digital signal processing, time series analysis, numerical modelling, inversion and data visualization.

PhD finish 2021