Characterizing the size and settling velocity of pyroclastic fragments injected into the atmosphere during volcanic eruptions (i.e., tephra) is crucial to the forecasting of plume and cloud dispersal. Optical disdrometers have been integrated into volcano monitoring networks worldwide in order to best constrain these parameters in real time. Nonetheless, their accuracy during tephra fallout still needs to be assessed. A significant complication is the occurrence of particle aggregates that modify size and velocity distributions of falling tephra. We made the first use of the Thies Clima Laser Precipitation Monitor (LPM) for tephra-fallout detection at Sakurajima volcano (Japan), which is characterized by a lower size detection window with respect to more commonly used disdrometers (e.g., Parsivel ² ) and can more easily distinguish different falling objects. For the first time, individual particles have been distinguished from most aggregates based on disdrometer data, with the potential to provide useful grain-size information in real time. In case of negligible aggregation, LPM and collected sample-based estimates are in agreement for both grain-size and sedimentation rate. In case of significant aggregation, particle shape analyses and a dedicated drag equation are used to filter out aggregates from LPM data that also provide good agreement with collected tephra samples.