Inferring 222Rn soil fluxes from ambient 222Rn activity and eddy covariance measurements of CO2

摘要

We present a new methodology, which we call Single Pair of ObservationsTechnique with Eddy Covariance (SPOT-EC), to estimate regional-scale surfacefluxes of Rn fromtower-based observations of Rn activity concentration,CO mole fractions and direct CO fluxmeasurements from eddy covariance. For specific events, the regional(Rn) surface flux is calculated from short-term changesin ambient (Rn) activity concentration scaled by theratio of the mean CO surface flux for the specific event tothe change in its observed mole fraction. The resultingRn surface emissions are integrated in time (between themoment of observation and the last prior background levels) and space (i.e.over the footprint of the observations). The measurement uncertainty obtainedis about ±15 % for diurnal events and about ±10 % for longer-term(e.g. seasonal or annual) means. The method does not provide continuousobservations, but reliable daily averages can be obtained. We applied ourmethod to in situ observations from two sites in the Netherlands: Cabauwstation (CBW) and Lutjewad station (LUT). For LUT, which is an intensiveagricultural site, we estimated a mean Rn surface fluxof (0.29 ± 0.02) atoms cm s withvalues   0.5 atoms cm s to the southand south-east. For CBW we estimated a mean Rn surfaceflux of (0.63 ± 0.04) atoms cm s.The highest values were observed to the south-west, where the soil type is mainlyriver clay. For both stations good agreement was found between our resultsand those from measurements with soil chambers and two recently publishedRn soil flux maps for Europe. At both sites, largespatial and temporal variability of Rn surface fluxeswere observed which would be impractical to measure with a soil chamber.SPOT-EC, therefore, offers an important new tool for estimating regional-scaleRn surface fluxes. Practical applications furthermoreinclude calibration of process-based Rn soil fluxmodels, validation of atmospheric transport models and performing regional-scale inversions, e.g. of greenhouse gases via the SPOTRn-tracer method.