Detecting anomalous metal concentrations in the regolith using cross‒compositional detrending
Deciphering element associations and affinities in the regolith is important for understanding mineral hosts and geological processes, such as sorting and pedogenesis. This has implications in environmental sciences in terms of distinguishing natural vs. anthropogenic element distributions and establishing realistic remediation targets. In mineral exploration, the strongest elements associations often drive distribution patterns in geochemical maps, yet these are not always the most useful ones to consider.
In this contribution, we use National Geochemical Survey of Australia (NGSA) data to (1) identify the strongest controls of mineralogy (using major element total concentrations as a proxy) on trace metal distribution (using aqua regia Cu as an exemplar), and (2) remove the trend driven by the strongest major‒trace element association to calculate and map standardised residuals of the metals. In the coarse fraction (<2 mm) of NGSA top outlet sediments (0‒10 cm depth), which are similar to floodplain sediments, aqua regia Cu is most strongly correlated with total Fe of all the major total elements (r = 0.76 based on log‒transformed concentrations). Thus the aqua regia Cu map mostly shows regions where Fe‒oxyhydroxides in the regolith are abundant (or not) and naturally adsorb dissolved cationic metals from surrounding solutions. The predicted Cu map based purely on the total Fe concentrations and on the Fe‒Cu correlation is visually similar to the raw map. Only when calculating the standardised residuals between actual and predicted aqua regia Cu does additional information become apparent in the form of completely different geochemical patterns. These highlight areas where Cu that is not related to Fe (and therefore not in the form of Cu adsorbed onto Fe‒oxyhydroxides) is abundant (or not). For instance this Cu could be associated with silicate, carbonate or sulfate minerals. Thus this approach allows both environmental management and exploration strategies targeting different types of metal associations to be more effectively implemented, thereby reducing risk and cost.
This Abstract & Poster were presented at the 2017 Goldschmidt Conference ( https://goldschmidt.info/2017/)
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- Date (Creation)
- 2017-03-28T00:00:00
- Date (Publication)
- 2023-10-26T02:00:34
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- Geoscience Australia Persistent Identifier/https://pid.geoscience.gov.au/dataset/ga/104884
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Role Organisation / Individual Name Details Author de Caritat, P.
MEG Internal Contact Author Rate, A.W.
External Contact Publisher Commonwealth of Australia (Geoscience Australia)
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Goldschmidt Conference 13-18 August 2017, Paris
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Submitted and Presented to the 2017 Goldschmidt Conference
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Role Organisation / Individual Name Details Point of contact Commonwealth of Australia (Geoscience Australia)
Voice Resource provider Minerals, Energy and Groundwater Division
External Contact Point of contact Main, P.
MEG Internal Contact
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Product data repository: Various Formats
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EARTH SCIENCES
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mineralogy
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trace metal distribution
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Cu map
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Published_External
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Creative Commons Attribution 4.0 International Licence
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CC-BY
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4.0
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© 2017 Commonwealth of Australia (Geoscience Australia)
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Download Poster (pdf) [6.7 MB]
Download Poster (pdf) [6.7 MB]
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pdf
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Submitted and Presented to the 2017 Goldschmidt Conference
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urn:uuid/e2322eaf-ac8a-4e0f-b64b-33c40e23f121
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Role Organisation / Individual Name Details Point of contact Commonwealth of Australia (Geoscience Australia)
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Conference Abstract and Poster
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https://internal.ecat.ga.gov.au/geonetwork/srv/eng/search?uuid=e2322eaf-ac8a-4e0f-b64b-33c40e23f121
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- Date info (Creation)
- 2017-03-28T04:24:30
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- 2017-08-02T02:22:39
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AU/NZS ISO 19115-1:2014
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ISO 19115-1:2014
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ISO 19115-3
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Geoscience Australia Community Metadata Profile of ISO 19115-1:2014
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Version 2.0, April 2015