The presence of pollutants in the aquatic environment poses a serious threat for key species in the ecosystem. Conventional approaches to assess the quality of water rely on spot or grab samples and the detection of chemical pollutants in the water. Furthermore, the presence of flora and fauna in water is characteristic of its condition. Nevertheless, these approaches do not reflect a realistic assessment of water quality since they are limited not only in sensitivity but also in their ability to detect and cover a wide range of pollutants. This lack of realism has redirected predictive ecotoxicology and risk assessment towards effect-based methods. Effect-based tools are modern approaches employed in predictive ecotoxicology and risk assessment. These approaches utilize in silico approaches and model species, such as daphnids among others, to observe the effects of different chemical compounds and provide mechanistic insight over their actions. From the main categories of emerging pollutants encountered in the ecosystem, for the context of this thesis emphasis will be given to ionic liquids, and pharmaceutical compounds, as well as complex chemical mixtures.