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Polymeric nanoparticles (NP) are of increasing importance for a wide range of applications in the material and life sciences, including their use as drug carriers, fluorescent sensors and multimodal reporters in a large variety of bioassays and bioimaging studies. Application-relevant properties of NP include their size (and size distribution), shape, optical properties, and ease of subsequent functionalization, e.g. with linkers, sensor molecules, and bioligands. In this respect, knowledge of the chemical nature, the total number of surface groups and the number of groups accessible for subsequent coupling reactions is mandatory.1 Commercially available polystyrene NP often contain different additives like stabilizers, radical starters and crosslinkers, which can influence the quantification of surface functionalities. Moreover, they often have unknown surface group densities that may vary from batch to batch, which complicates or even hampers their reliable use in many (bio)applications. To circumvent these issues, we synthesized amino- and carboxy-functionalized, monodisperse 100 nm polystyrene NP with three different, well-defined surface group densities. Using a recently developed approach for the quantification of functional groups on nano- and microparticles with cleavable reporters,2 we quantified the assessible functional groups on the self-synthesised PS particles via optical spectroscopy (photometry) and inductively coupled optical emission spectrometry (32S ICP-OES). In addition, we developed a fluorimetric approach for the quantification of surface functional groups on nanoparticles based on the labelling with luminescent lanthanide complexes (LLC). In contrast to common organic dyes, LLC are not prone to photo¬luminescence quenching arising from reabsorption or dye aggregation, and thus, enable a reliable fluorometric quantification of the assessible functional groups on NP surfaces. Moreover, lanthanide tags can be detected with high specificity and sensitivity with analytical techniques such as XPS and ICP-MS, which allow for the multimodal validation of the fluorometric quantification approach.