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Updated: May 5, 2026

Soil Lysimeter Excavation for Coupled Hydrological, Geochemical, and Microbiological Investigations

Soil Lysimeter Excavation for Coupled Hydrological, Geochemical, and Microbiological Investigations

Published on: September 11, 2016

Multivariate Strategy for Understanding Soil Features from Rare-Earth Element Profiles: A Focus on Data

Marcella Barbera¹, Sara Gariglio^2,3, Cristina Malegori²

¹Department of Earth and Marine Sciences, University of Palermo, Palermo 90123, Italy.

ACS Measurement Science Au

|April 21, 2025

Summary

This study introduces a new method using Principal Component Analysis (PCA) to map rare-earth element (REE) distributions in soils. This approach simplifies data interpretation and reveals soil properties without normalization challenges.

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Area of Science:

Environmental Science
Geochemistry
Chemometrics

Background:

Rare-earth elements (REE) are crucial in technology and environmental studies.
Current REE analysis relies on normalization, which can lead to inconsistent results.
Interpreting REE distribution in natural environments requires robust analytical methods.

Purpose of the Study:

To develop an alternative, more interpretable method for analyzing REE concentration profiles.
To create REE chemometric maps using Principal Component Analysis (PCA).
To correlate REE patterns with soil properties for enhanced environmental monitoring.

Main Methods:

Application of Principal Component Analysis (PCA) to REE concentration data.
Creation of REE chemometric maps using an RGB color scale based on principal components.
Analysis of non-normalized REE data to assess methodological consistency.

Main Results:

PCA effectively visualizes REE distribution on geographical maps, highlighting compositional similarities and differences.
The method provides unsupervised insights into soil properties by correlating them with REE patterns.
Results obtained from non-normalized data are consistent with those from normalized data.

Conclusions:

The proposed PCA-based chemometric mapping offers a powerful, interpretable alternative to traditional REE analysis.
This approach overcomes normalization challenges and enhances understanding of soil characteristics and evolution.
The methodology facilitates environmental monitoring and reveals new connections between seemingly unrelated soil samples.