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Abstract. We present a new methodology, which we call Single Pair of Observations Technique with Eddy Covariance (SPOT-EC), to estimate regional-scale surface fluxes of 222 Rn from tower-based observations of 222 Rn activity concentration, CO 2 mole fractions and direct CO 2 flux measurements from eddy covariance. For specific events, the regional ( 222 Rn) surface flux is calculated from short-term changes in ambient ( 222 Rn) activity concentration scaled by the ratio of the mean CO 2 surface flux for the specific event to the change in its observed mole fraction. The resulting 222 Rn surface emissions are integrated in time (between the moment of observation and the last prior background levels) and space (i.e. over the footprint of the observations). The measurement uncertainty obtained is about ±15 % for diurnal events and about ±10 % for longerterm (e.g. seasonal or annual) means. The method does not provide continuous observations, but reliable daily averages can be obtained. We applied our method to in situ observations from two sites in the Netherlands: Cabauw station (CBW) and Lutjewad station (LUT). For LUT, which is an intensive agricultural site, we estimated a mean 222 Rn surface flux of (0.29 ± 0.02) atoms cm −2 s −1 with values > 0.5 atoms cm −2 s −1 to the south and southeast. For CBW we estimated a mean 222 Rn surface flux of (0.63 ± 0.04) atoms cm −2 s −1 . The highest values were observed to the south-west, where the soil type is mainly river clay. For both stations good agreement was found between our results and those from measurements with soil chambers and two recently published 222 Rn soil flux maps for Europe. At both sites, large spatial and temporal variability of 222 Rn surface fluxes were observed which would be impractical to measure with a soil chamber. SPOT-EC, therefore, offers an important new tool for estimating regional-scale 222 Rn surface fluxes. Practical applications furthermore include calibration of process-based 222 Rn soil flux models, validation of atmospheric transport models and performing regional-scale inversions, e.g. of greenhouse gases via the SPOT 222 Rntracer method.