A multivariate chemical map of industrial chemicals: Assessment of various protocols for identification of chemicals of potential concern
2009 (English)In: Chemosphere, ISSN 0045-6535, E-ISSN 1879-1298, Vol. 76, no 7, 878-884 p.Article in journal (Refereed) Published
In present study the Industrial chemical map was created, and investigated. Molecular descriptors were calculated for 56 072 organic substances from the European inventory of existing commercial chemical substances (EINECS). The resulting multivariate dataset was subjected to principal component analysis (PCA), giving five principal components, mainly reflecting size, hydrophobicity, flexibility, halogenation and electronical properties. It is these five PCs that form the basis of the map of organic, industrial chemicals, the Industrial chemical map. The similarities and diversity in chemical characteristics of the substances in relation to their persistence (P), bioaccumulation (B) and long-range transport potential were then examined, by superimposing five sets of entries obtained from other relevant databases onto the Industrial chemical map. These sets displayed very similar diversity patterns in the map, although with a spread in all five PC vectors. Substances listed by the United Nations Environment Program as persistent organic pollutants (UNEP POPs) were on the other hand clearly grouped with respect to each of the five PCs. Illustrating similarities and differences in chemical properties are one of the strengths of the multivariate data analysis method, and to be able to make predictions of, and investigate new chemicals. Further, the results demonstrate that non-testing methods as read-across, based on molecular similarities, can reduce the requirements to test industrial chemicals, provided that they are applied carefully, in combination with sound chemical knowledge.
Place, publisher, year, edition, pages
Elsevier, 2009. Vol. 76, no 7, 878-884 p.
Hazard identification, Persistent organic pollutants, Risk assessment, Molecular similarities, Non-testing methods, Read-across
IdentifiersURN: urn:nbn:se:umu:diva-23516DOI: 10.1016/j.chemosphere.2009.05.011OAI: oai:DiVA.org:umu-23516DiVA: diva2:224883
Accepted 13 May 2009. Available online 9 June 2009.