Liquid Chromatography – Organic Carbon Detection (LC-OCD)

  • Villacorte L
N/ACitations
Citations of this article
13Readers
Mendeley users who have this article in their library.
Get full text

Abstract

Liquid chromatography-organic carbon detection (LC-OCD) is an analytical technique for identification and quantification of natural organic matter (NOM) constituents in aquatic environments and water-soluble synthetic organic matter in technical waters. This technique has several specific applications including NOM investigation in drinking water, wastewa-ter, and marine waters and quality control monitoring of ultrapure water used in power plants and the semiconductor industry (Huber and Frimmel 1994; Huber et al. 2011). It is widely applied in membrane-based water treatment to characterize the different NOM constituents in the source waters (e.g. The principle behind NOM fractionation by LC-OCD is based on three separation processes, namely, size exclusion, ion interaction, and hydrophobic interaction. Since NOM constituents are highly heterogeneous in terms of size and majority of which are hydrophilic and weakly acidic, size exclusion is considered as the dominant mechanism of separation (DOC-Labor 2006). Size exclusion chromatography (SEC) is based on steric interactions or physical sieving where the difference in speed of diffusion for smaller and larger molecules is used to identify the different NOM fractions in the mobile phase (e.g., buffered water sample). The stationary phase is a packing of porous beads which allows smaller molecules to diffuse into the bead interior while preventing the larger molecules to diffuse through. As a consequence, larger molecules have less volume to traverse and travel faster through the chromatogram column (shorter elu-tion time) than smaller molecules.

Cite

CITATION STYLE

APA

Villacorte, L. O. (2014). Liquid Chromatography – Organic Carbon Detection (LC-OCD). In Encyclopedia of Membranes (pp. 1–3). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-642-40872-4_714-6

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free