Impact of grass cover on the magnetic susceptibility measurements for assessing metal contamination of soil
Abstract
The assessment of magnetic properties of soils is becoming widely established as a non-invasive in-situ proxy for metal contamination. However, it is recognised that soil vegetative cover can impede on the measurements... [ view full abstract ]
The assessment of magnetic properties of soils is becoming widely established as a non-invasive in-situ proxy for metal contamination. However, it is recognised that soil vegetative cover can impede on the measurements obtained while the removal of this layer can increase the costs and fieldwork duration of magnetic monitoring studies. This study provides the first field-based examination of the effects of a grass vegetative cover on magnetic susceptibility measurements of underlying soils. Magnetic measurements were taken under two conditions to determine the effects of grass height on MSĸ (volume magnetic susceptibility): 1.) MSĸ GRASS - When the grass layer was present. 2.) MSĸ NO GRASS - After the grass layer was trimmed to the root. The height of the grass was also recorded. Soil samples (n=194) were taken from the same locations and MSχlf (low frequency mass specific magnetic susceptibility) measurements (MSχlf SOIL) were assessed in the laboratory. Metal concentrations (Cu, Fe, Pb, Zn (mg kg-1)) of soil samples were analysed for comparative purposes. Laboratory-based mass specific susceptibility is the most efficient method of soil susceptibility determination. However, importantly both MSĸ GRASS (ln) and MSĸ NO GRASS(ln) are also strongly correlated to each of the metals. Spatial distribution maps were created using IDW and LISA to identify common patterns across the determined soil characteristics. Notably, MSĸ GRASS and MSĸ NO GRASS are highly correlated [r = 0.967, n=194, p=.000]. The results suggest that it is not necessary to remove a vegetative layer prior to obtaining in-situ susceptibility measurements of soil.
Authors
-
Nessa Golden
(School of Geography and Archaeology, National University of Ireland, Galway)
-
Chaosheng Zhang
(GIS Centre, Ryan Institute and School of Geography and Archaeology, National University of Ireland Galway, Galway, Ireland)
-
Aaron Potito
(School of Geography and Archaeology, National University of Ireland Galway, Galway, Ireland)
-
Paul J. Gibson
(Environmental Geophysics Unit, Department of Geography, National University of Ireland, Maynooth)
-
Norma Bargary
(Department of Mathematic & Statistics, University of Limerick)
-
Liam Morrison
(Earth and Ocean Sciences, School of Natural Sciences and Ryan Institute, National University of Ireland Galway)
Topic Area
Choose your Organised Session from the list below: Spatial prediction of pollutant distrib
Session
PS » Poster Session Available from 14th - 17th August (16:45 - Wednesday, 17th August, Arts/Science Concourse)