Predictive exposure modelling--a case study with a detergent surfactant.

Abstract

Environmental exposure estimations are generally based on a knowledge of how and in what quantity a substance enters the environment and how it may subsequently be distributed and transformed. Once present within the environment, biota (including man) may be exposed. This paper outlines the tools commonly used to estimate environmental exposure to ingredients from detergents and other household products. Such products are typically manufactured in large quantities, used by many people, and disposed of after household use into the environment via the sewer. The vast majority of this waste stream is treated via domestic wastewater treatment plants (WWTPs) as documented in the sewage treatment Directive 91/275/EEC. WWTPs significantly reduce the load of chemical substances to the receiving surface waters, and have become an intrinsic part of exposure and risk assessment of household chemicals. WWTP models are generally first-order (e.g. SIMPLETREAT, WWTREAT) or mixed-order (e.g. Monod) kinetics and can exhibit, potentially, very distinct dependencies on the influent concentration. Thus, the correct representation of xenobiotic behaviour in a WWTP and modeling of their fate has a significant impact on exposure assessment. The Environmental Risk Assessment Steering Committee (ERASM) of the Association Internationale de la Savonnerie et la Détergence, et des Produits d'Entretiens (AISE) and the Comité Européen de Agents de Surface et Intermédiares Organiques (CESIO) has commissioned a joint industry Task Force of the Association to develop and apply specific methodology for the environmental monitoring of surfactants, and verification of fate models. The monitoring programmes have been designed to (1) establish the fate, distribution and concentrations of the major surfactants used in detergents-linear alkylbenzene sulfonate (LAS), alcohol ethoxylates (AE), alcohol ethoxylated sulfates (AES) and soap in relevant environmental compartments and (2) to provide the necessary data for checking the applicability of mathematical models to predict their fate and concentrations in these environmental compartments. The case study detailed here, specifically focuses on the refinement of the LAS exposure assessment for surface waters in The Netherlands.