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Elsevier, Atmospheric Pollution Research, 3(1), p. 132-140, 2010

DOI: 10.5094/apr.2010.017

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Using multiple regression in estimating (semi) VOC emissions and concentrations at the European scale

Journal article published in 2010 by Patrik Fauser, Marianne Thomsen ORCID, Alberto Pistocchi, Hans Sanderson ORCID
This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Abstract

This paper proposes a simple method for estimating emissions and predicted environmental concentrations (PECs) in water and air for organic chemicals that are used in household products and industrial processes. The method has been tested on existing data for 63 organic high-production volume chemicals available in the European Chemicals Bureau risk assessment reports (RARs). The method suggests a simple linear relationship between Henry's Law constant, octanol-water coefficient, use and production volumes, and emissions and PECs on a regional scale in the European Union. Emissions and PECs are a result of a complex interaction between chemical properties, production and use patterns and geographical characteristics. A linear relationship cannot capture these complexities; however, it may be applied at a cost-efficient screening level for suggesting critical chemicals that are candidates for an in-depth risk assessment. Uncertainty measures are not available for the RAR data; however, uncertainties for the applied regression models are given in the paper. Evaluation of the methods reveals that between 79% and 93% of all emission and PEC estimates are within one order of magnitude of the reported RAR values. Bearing in mind that the domain of the method comprises organic industrial high-production volume chemicals, four chemicals, prioritized in the Water Framework Directive and the Stockholm Convention on Persistent Organic Pollutants, were used to test the method for estimated emissions and PECs, with corresponding uncertainty intervals, in air and water at regional EU level. (C) Author(s) 2010. This work is distributed under the Creative Commons Attribution 3.0 License.