Organic pollutants that resist degradation in the environment can accumulate in body tissues and cause unavoidable intoxications to organisms in wild life as well as humans. The possible effects, usually increasing with the cumulative exposure to such chemicals, are not always addressed adequately in risk assessment procedures evaluating long and short-term contact hazard. Thus, chemicals accumulation, degradation and environmental fate are of prime concern for REACH when defining side effects due to chronic exposure. Characteristics and behavior of organic pollutants have been investigated experimentally during the last decades by use of various methods of trace analysis. However, the available data still contains several gaps. In this aim, REACH promotes the use of alternative methods to reduce the number of animal tests and suggests in-silico methods such as Quantitative Structure-Activity Relationships (QSARs) to fill the lack of knowledge. The goal of this work, in the framework of the ECO-ITN project, was to build QSAR models with high reliability based on good experimental data for optimal estimation of environmental endpoints of interest for REACH.