Dynamic Light Scattering (DLS) is a powerful and sensitive technique for characterizing particles or macromolecules in dispersion, due to its ability to resolve particle or molecular sizes ranging from sub nanometer to several microns. This sensitivity also means that DLS is a useful technique to characterize aggregated material, which may occur in far smaller quantities but is of a significant importance in many applications.  Typically, however, the presence or dust (including filter spoil, column shedding, tracer aggregates or material from dirty lab ware), can have detrimental effects on the measurement of smaller sized particles and algorithms exist to suppress these effects. In this application note we present a new approach to handling DLS data which prevents the skewing of data for small particles whilst retaining insight into the presence of aggregates that may otherwise be lost, whereby the relative abundance and size of aggregates can be deduced. 

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