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The concentration of cloud condensation nuclei (CCN) is an essential parameter affecting aerosol-cloud interactions within warm clouds. Long-term CCN number concentration (N-CCN) data are scarce; there are a lot more data on aerosol optical properties (AOPs). It is therefore valuable to derive parameterizations for estimating N-CCN from AOP measurements. Such parameterizations have already been made, and in the present work a new parameterization is presented. The relationships between N-CCN, AOPs, and size distributions were investigated based on in situ measurement data from six stations in very different environments around the world. The relationships were used for deriving a parameterization that depends on the scattering Angstrom exponent (SAE), backscatter fraction (BSF), and total scattering coefficient (sigma(sp)) of PM10 particles. The analysis first showed that the dependence of N-CCN on supersaturation (SS) can be described by a logarithmic fit in the range SS < 1 :1 %, without any theoretical reasoning. The relationship between N-CCN and AOPs was parameterized as N-CCN approximate to ((286 +/- 46)SAE ln(SS/(0.093 +/- 0.006))(BSF - BSFmin) + (5.2 +/- 3.3))sigma(sp), where BSFmin is the minimum BSF, in practice the 1st percentile of BSF data at a site to be analyzed. At the lowest supersaturations of each site (SS approximate to 0 :1 %), the average bias, defined as the ratio of the AOP-derived and measured N-CCN, varied from similar to 0.7 to similar to 1.9 at most sites except at a Himalayan site where the bias was > 4. At SS > 0 :4% the average bias ranged from similar to 0.7 to similar to 1.3 at most sites. For the marine-aerosol-dominated site Ascension Island the bias was higher, similar to 1.4-1.9. In other words, at SS > 0:4% N-CCN was estimated with an average uncertainty of approximately 30% by using nephelometer data. The biases were mainly due to the biases in the parameterization related to the scattering Angstrom exponent (SAE). The squared correlation coefficients between the AOP-derived and measured N-CCN varied from similar to 0.5 to similar to 0.8. To study the physical explanation of the relationships between N-CCN and AOPs, lognormal unimodal particle size distributions were generated and N-CCN and AOPs were calculated. The simulation showed that the relationships of N-CCN and AOPs are affected by the geometric mean diameter and width of the size distribution and the activation diameter. The relationships of N-CCN and AOPs were similar to those of the observed ones.