Cellulose nanocrystals (CNCs) are negatively charged nanorods that present challenges for characterization of particle size distribution and surface area-two of the common parameters for characterizing nanomaterials. CNC size distributions have been measured by two microscopy methods: atomic force microscopy (AFM) and transmission electron microscopy (TEM). The agreement between the two methods is good for length measurements, after taking into consideration tip-convolution effects for AFM. However, TEM widths are almost twice as large as AFM heights-an effect that we hypothesize is due to counting of a larger fraction of laterally associated CNCs in the TEM images. Overall, the difficulty of selecting individual particles for analysis and possible bias due to selection of a specific particle size during sample deposition are the main limitations associated with the microscopy measurements. The microscopy results were compared to Z-average data from dynamic light scattering, which is a useful method for routine analysis and for examining trends in size as a function of sample treatment. Measurements as a function of sonication energy were used to provide information on the presence of aggregates in the sample. Magic-angle-spinning solid-state NMR was employed to estimate the surface area of CNCs based on the ratio of integrated spectral intensities of resonances stemming from C4 sites at the crystallite surfaces and from all C4 sites. Our approach was adapted from the application of solid-state NMR to characterize larger cellulose microfibers and appears to provide a useful estimate that overcomes the limitations of using the BET method for measuring surface areas of highly aggregated nanomaterials. The solid-state NMR results show that the lateral dimension of the CNCs is consistent with that of elementary cellulose crystallites.