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Updated: Jun 28, 2026

Split Point Analysis and Uncertainty Quantification of Thermal-Optical Organic/Elemental Carbon Measurements

Split Point Analysis and Uncertainty Quantification of Thermal-Optical Organic/Elemental Carbon Measurements

Published on: September 7, 2019

Generalization of a new calibration method based on linear correlation.

Gábor Galbács¹, Igor B Gornushkin, James D Winefordner

¹Department of Inorganic and Analytical Chemistry, University of Szeged, Dóm tér 7., 6720 Szeged, Hungary.

|October 31, 2008

Summary

This study introduces a generalized linear correlation method (GLCM) for spectroscopic quantitation. The enhanced calibration technique improves accuracy for trace element analysis in complex samples.

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Area of Science:

Analytical Chemistry
Spectroscopy

Background:

Existing calibration methods have limitations in quantitation, especially for trace elements.
Previous linear correlation methods required specific conditions for application.

Purpose of the Study:

To present a generalized linear correlation method (GLCM) extending calibration applicability.
To demonstrate GLCM's utility in various spectroscopic techniques.
To validate the method's accuracy in complex analytical scenarios.

Main Methods:

Modification and generalization of a linear correlation calibration approach.
Application of the generalized linear correlation method (GLCM) to UV-Vis spectrophotometry.
Implementation of GLCM for inductively coupled plasma mass spectrometry (ICP-MS) analysis.

Main Results:

The generalized linear correlation method (GLCM) demonstrated broad applicability across spectroscopic techniques.
Successful application to UV-Vis spectrophotometry and ICP-MS.
Achieved good accuracy, typically within 1-5%, in all tested applications.

Conclusions:

The generalized linear correlation method (GLCM) offers a versatile and accurate calibration solution.
GLCM enhances quantitation capabilities for trace element analysis and incomplete sample data.
The method is suitable for diverse spectroscopic applications, improving analytical reliability.