A comprehensive data-processing workflow was tailored for acidic components including peak detection settings optimised for detection of low concentration compounds with poor ionization efficiency; comprehensive feature reduction to remove interferences generated by the analytical process rather than by the sample; a novel filter to eliminate features generated by DOM; a database for SS tailored for acidic compounds of interest. The application of the DOM filter proved to significantly reduce the number of incorrect library hits without generating false negatives. Analysis of 10 municipal water samples from across London showed the presence of 22 confirmed substances including several scarcely investigated contaminants. In particular, occurrence of dibromomethanesulfonic acid and halogenated HCDs indicate the need for further investigation to rule out potential threats to public health from these substances. Although further work is required to automate the entire data-processing workflow, overall, this method constitutes an optimal platform for improved detection and identification of acidic contaminants and pollutants in drinking water and likely to find wider qualitative and quantitative applications for such substances.