Studies into the effectiveness of water treatment techniques for priority substances involve high costs and are closely related to very specific conditions: treatment technique type, water type, substances present, and process conditions, such as residential times (distribution) and characteristics of the removal barrier
One method, which is not affected by the above-mentioned drawbacks, offers a possible solution, namely: if the right data on the removal of particular substances are sufficiently available, they can, in combination with molecular properties, be inter-connected statistically. The resulting relationship is known as a QSAR (quantitative structure activity relationship) or QSPR (quantitative structure property relationship). Combined with knowledge about the process, one can use the statistical relationship to predict the removal efficiency of an unknown substance.
During the course of the project, data on removal efficiencies of priority substances (pharmaceuticals and pesticides) is collected and selected. Also, process models of activated carbon filtration and reverse osmosis are linked to QSARs. A database toolbox within the tool permits the determination and visualisation of the removal efficiencies of the two treatment processes for a (possibly untested) substance.
A demo version of a QSAR toolbox is developed, which, on the basis of the substance and process properties, can determine the removal efficiency of activated carbon filtration or reverse osmosis for an (as-yet untested) substance.