Utilising CoDA methods for the spatio-temporal geochemical characterisation of groundwater; a case study from Lisheen Mine, south central Ireland. (April 2021)
- Record Type:
- Journal Article
- Title:
- Utilising CoDA methods for the spatio-temporal geochemical characterisation of groundwater; a case study from Lisheen Mine, south central Ireland. (April 2021)
- Main Title:
- Utilising CoDA methods for the spatio-temporal geochemical characterisation of groundwater; a case study from Lisheen Mine, south central Ireland
- Authors:
- Wheeler, Seán
Henry, Tiernan
Murray, John
McDermott, Frank
Morrison, Liam - Abstract:
- Abstract: Lisheen Mine in County Tipperary, Ireland exploited an underground Pb/Zn massive sulphide deposit hosted in Carboniferous (Mississippian) carbonates. During the extraction phase, the mine workings (located at an average depth of 170 m below ground level), were continuously pumped to lower the groundwater level. Following mine closure in 2015, pumping ceased and eight groundwater wells in the surrounding area were sampled monthly over an 11-month period to monitor the effects of groundwater rebound. These wells draw water from the upper 30 m of a limestone/dolostone aquifer and the monthly samples were analysed for the concentration of 31 elements and compounds (SO4, Cl, NO3, F, NH4, NO2, P, Ca, Na, K, Mg, Fe, Mn, Cu, Zn, Pb, Al, Ni, Ba, As, Hg, B, Cr, Cd, Mo, Ag, Co, Sr, Be, Sb and U). All of the water can be described as Ca–HCO3 type as expected. Standard methods for analysing groundwater geochemistry data (e.g. piper diagrams etc.) are useful, differentiating groundwaters with first-order contrasting chemical signatures, for example, distinguishing Ca–HCO3 -type from Na–HCO3 -type water. Samples from the 8 monitoring wells appear to be broadly similar, using this approach. However, these major ion methods fail to further distinguish between different groundwaters. The use of multivariate statistical analytical techniques has become more common in groundwater studies in recent years, allowing the interaction of all the elements and compounds to be consideredAbstract: Lisheen Mine in County Tipperary, Ireland exploited an underground Pb/Zn massive sulphide deposit hosted in Carboniferous (Mississippian) carbonates. During the extraction phase, the mine workings (located at an average depth of 170 m below ground level), were continuously pumped to lower the groundwater level. Following mine closure in 2015, pumping ceased and eight groundwater wells in the surrounding area were sampled monthly over an 11-month period to monitor the effects of groundwater rebound. These wells draw water from the upper 30 m of a limestone/dolostone aquifer and the monthly samples were analysed for the concentration of 31 elements and compounds (SO4, Cl, NO3, F, NH4, NO2, P, Ca, Na, K, Mg, Fe, Mn, Cu, Zn, Pb, Al, Ni, Ba, As, Hg, B, Cr, Cd, Mo, Ag, Co, Sr, Be, Sb and U). All of the water can be described as Ca–HCO3 type as expected. Standard methods for analysing groundwater geochemistry data (e.g. piper diagrams etc.) are useful, differentiating groundwaters with first-order contrasting chemical signatures, for example, distinguishing Ca–HCO3 -type from Na–HCO3 -type water. Samples from the 8 monitoring wells appear to be broadly similar, using this approach. However, these major ion methods fail to further distinguish between different groundwaters. The use of multivariate statistical analytical techniques has become more common in groundwater studies in recent years, allowing the interaction of all the elements and compounds to be considered simultaneously. Compositional Data Analysis (CoDA) was used on the Lisheen dataset to gain a better understanding of the spatial and temporal variation in groundwater geochemistry. Ilr-ion plotting, Hierarchical Cluster Analysis (HCA) and Principal Component Analysis (PCA) through CoDA highlights the elements and compounds that account for the majority of the variance and at Lisheen these are nitrate, manganese, ammonium, sulphate and potassium. By displaying these data visually in a CoDA bi-plot, each location can be reliably 'geochemically fingerprinted' despite similar concentrations of major ions within a relatively small geographical area (<30 km 2 ). Relabeling the bi-plot observations by date of recovery reveals how one particular groundwater well (PH) subtly varies over time, most likely as a result of seasonal land-use changes (input of compounds associated with fertiliser). This type of statistical analysis has broad applications in hydrology and hydrogeology including contaminant tracing and interaction, environmental studies, land-use planning and mineral exploration. Highlights: CoDA is currently an unparalleled method of geochemical data exploration and analysis. 8 sample locations with Ca–HCO3 groundwater at Lisheen can be 'geochemically fingerprinted' using CoDA. Geochemistry at Lisheen is influenced by geogenic and/or anthropogenic inputs. Redox reactions play a key role in defining final geochemical make-up of the groundwater at each sample location. CoDA is sensitive to geochemical changes through time and can therefore be used effectively for environmental monitoring. … (more)
- Is Part Of:
- Applied geochemistry. Volume 127(2021)
- Journal:
- Applied geochemistry
- Issue:
- Volume 127(2021)
- Issue Display:
- Volume 127, Issue 2021 (2021)
- Year:
- 2021
- Volume:
- 127
- Issue:
- 2021
- Issue Sort Value:
- 2021-0127-2021-0000
- Page Start:
- Page End:
- Publication Date:
- 2021-04
- Subjects:
- Groundwater -- Geochemistry -- Compositional data analysis (CoDA) -- Lisheen mine -- Carboniferous -- Mississippian -- Limestone -- Base metal mineralisation
Environmental geochemistry -- Periodicals
Water chemistry -- Periodicals
Geochemistry -- Social aspects -- Periodicals
Geochemistry -- Periodicals
551.9 - Journal URLs:
- http://www.elsevier.com/journals ↗
- DOI:
- 10.1016/j.apgeochem.2021.104912 ↗
- Languages:
- English
- ISSNs:
- 0883-2927
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 1572.585000
British Library DSC - BLDSS-3PM
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- 22323.xml