Now and in the future, the ever-growing demand for drinking water will lead many cities to implement indirect water reuse programs, where wastewater effluent becomes part of the drinking water sources. Pollution of those sources with emerging contaminants (micropollutants) such as endocrine disrupting compounds, pharmaceutically active compounds, pesticides and personal care products is a fact known worldwide. Although the risks of micropollutants in sources of water are partly recognized, interpretation of consequences are controversial; thus, the future effects of altered water with micropollutants remains uncertain and may constitute a point of concern for human beings when potable water consumption is involved. Therefore, many drinking water utilities target as an important goal high-quality drinking water production to lessen quality considerations that may arise from the consumers. In this thesis, nanofiltration (NF) and reverse osmosis (RO) are demonstrated to be appropriate technologies for removing a large number of micropollutants; however, the performance of NF and RO can be questioned because there are limited tools that optimise quantification of the removal of contaminants. Therefore, in this thesis, by means of the use of multivariate data analysis techniques, removal quantification is effectively determined and more understanding of the separation of micropollutants by membranes is achieved.