Mapping environmental partitioning properties of nonpolar complex mixtures by use of GC × GC
Comprehensive two-dimensional gas chromatography (GC × GC) is effective for separating and quantifying nonpolar organic chemicals in complex mixtures. Here we present a model to estimate 11 environmental partitioning properties for nonpolar analytes based on GC × GC chromatogram retention time infor...
Published in: | Environmental Science & Technology |
---|---|
Main Authors: | , , , |
Format: | Article in Journal/Newspaper |
Language: | English |
Published: |
American Chemical Society
2014
|
Subjects: | |
Online Access: | https://doi.org/10.1021/es501674p |
id |
fteawag:oai:dora:eawag_7717 |
---|---|
record_format |
openpolar |
spelling |
fteawag:oai:dora:eawag_7717 2024-09-09T19:26:14+00:00 Mapping environmental partitioning properties of nonpolar complex mixtures by use of GC × GC Nabi, Deedar Gros, Jonas Dimitriou-Christidis, Petros Arey, J. Samuel 2014 https://doi.org/10.1021/es501674p eng eng American Chemical Society Environmental Science and Technology--Environ. Sci. Technol.--journals:872--0013-936X--1520-5851 eawag:7717 journal id: journals:872 issn: 0013-936X e-issn: 1520-5851 ut: 000337646000036 local: 16856 scopus: 2-s2.0-84902590904 doi:10.1021/es501674p Text Journal Article 2014 fteawag https://doi.org/10.1021/es501674p 2024-08-05T03:04:28Z Comprehensive two-dimensional gas chromatography (GC × GC) is effective for separating and quantifying nonpolar organic chemicals in complex mixtures. Here we present a model to estimate 11 environmental partitioning properties for nonpolar analytes based on GC × GC chromatogram retention time information. The considered partitioning properties span several phases including pure liquid, air, water, octanol, hexadecane, particle natural organic matter, dissolved organic matter, and organism lipids. The model training set and test sets are based on a literature compilation of 648 individual experimental partitioning property data. For a test set of 50 nonpolar environmental contaminants, predicted partition coefficients exhibit root-mean-squared errors ranging from 0.19 to 0.48 log unit, outperforming Abraham-type solvation models for the same chemical set. The approach is applicable to nonpolar organic chemicals containing C, H, F, Cl, Br, and I, having boiling points ≤402 °C. The presented model is calibrated, easy to apply, and requires the user only to identify a small set of known analytes that adapt the model to the GC × GC instrument program. The analyst can thus map partitioning property estimates onto GC × GC chromatograms of complex mixtures. For example, analyzed nonpolar chemicals can be screened for long-range transport potential, aquatic bioaccumulation potential, arctic contamination potential, and other characteristic partitioning behaviors. Article in Journal/Newspaper Arctic DORA Eawag Arctic Environmental Science & Technology 48 12 6814 6826 |
institution |
Open Polar |
collection |
DORA Eawag |
op_collection_id |
fteawag |
language |
English |
description |
Comprehensive two-dimensional gas chromatography (GC × GC) is effective for separating and quantifying nonpolar organic chemicals in complex mixtures. Here we present a model to estimate 11 environmental partitioning properties for nonpolar analytes based on GC × GC chromatogram retention time information. The considered partitioning properties span several phases including pure liquid, air, water, octanol, hexadecane, particle natural organic matter, dissolved organic matter, and organism lipids. The model training set and test sets are based on a literature compilation of 648 individual experimental partitioning property data. For a test set of 50 nonpolar environmental contaminants, predicted partition coefficients exhibit root-mean-squared errors ranging from 0.19 to 0.48 log unit, outperforming Abraham-type solvation models for the same chemical set. The approach is applicable to nonpolar organic chemicals containing C, H, F, Cl, Br, and I, having boiling points ≤402 °C. The presented model is calibrated, easy to apply, and requires the user only to identify a small set of known analytes that adapt the model to the GC × GC instrument program. The analyst can thus map partitioning property estimates onto GC × GC chromatograms of complex mixtures. For example, analyzed nonpolar chemicals can be screened for long-range transport potential, aquatic bioaccumulation potential, arctic contamination potential, and other characteristic partitioning behaviors. |
format |
Article in Journal/Newspaper |
author |
Nabi, Deedar Gros, Jonas Dimitriou-Christidis, Petros Arey, J. Samuel |
spellingShingle |
Nabi, Deedar Gros, Jonas Dimitriou-Christidis, Petros Arey, J. Samuel Mapping environmental partitioning properties of nonpolar complex mixtures by use of GC × GC |
author_facet |
Nabi, Deedar Gros, Jonas Dimitriou-Christidis, Petros Arey, J. Samuel |
author_sort |
Nabi, Deedar |
title |
Mapping environmental partitioning properties of nonpolar complex mixtures by use of GC × GC |
title_short |
Mapping environmental partitioning properties of nonpolar complex mixtures by use of GC × GC |
title_full |
Mapping environmental partitioning properties of nonpolar complex mixtures by use of GC × GC |
title_fullStr |
Mapping environmental partitioning properties of nonpolar complex mixtures by use of GC × GC |
title_full_unstemmed |
Mapping environmental partitioning properties of nonpolar complex mixtures by use of GC × GC |
title_sort |
mapping environmental partitioning properties of nonpolar complex mixtures by use of gc × gc |
publisher |
American Chemical Society |
publishDate |
2014 |
url |
https://doi.org/10.1021/es501674p |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic |
genre_facet |
Arctic |
op_relation |
Environmental Science and Technology--Environ. Sci. Technol.--journals:872--0013-936X--1520-5851 eawag:7717 journal id: journals:872 issn: 0013-936X e-issn: 1520-5851 ut: 000337646000036 local: 16856 scopus: 2-s2.0-84902590904 doi:10.1021/es501674p |
op_doi |
https://doi.org/10.1021/es501674p |
container_title |
Environmental Science & Technology |
container_volume |
48 |
container_issue |
12 |
container_start_page |
6814 |
op_container_end_page |
6826 |
_version_ |
1809895900634415104 |