A priori knowledge on large-scale sub-surface conductivity structure is required in many applications investigating electrical properties of the lithosphere. A map on crustal conductivity for the Fennoscandian Shield and its surrounding oceans, sea basins and continental areas is presented. The map is based on a new database on crustal conductance, i.e. depth integrated conductivity, where all available information on the conductivity of the bedrock, sedimentary cover and seawater are compiled together for the first time for the Fennoscandian Shield. The final model consists of eight separate layers to allow a 3D description of conductivity structures. The first three layers, viz. water, sediments and the first bedrock layer, describe the combined conductance of the uppermost 10 km. The other five bedrock layers contain the data of the crustal conductance from the depth of 10 km to the depth of 60 km. The database covers an area from 0• E to 50• E and 50• N to 85• N. Water conductances are estimated from bathymetric data by converting depths to conductances and taking into account the salinity variations in the Baltic Sea. Conductance of the sedimentary cover includes estimates on the conductance of both marine and continental sediments. Bedrock conductances are extrapolated from 1D-and 2D-models. Extrapolations are based on data from magnetometer array studies, airborne electromagnetic surveys and other electromagnetic investigations as well as on other geophysical and geological data. The crustal conductivity structure appears to be very heterogeneous. Upper crust, in particular, has a very complex structure reflecting a complex geological history. Lower crust seems to be slightly more homogeneous although large regional contrasts are found in both the Archaean and Palaeoproterozoic areas.

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Ð A crustal velocity model has been developed for Fennoscandia, the Baltic shield and adjacent areas. This model represents a simpli®ed average of various models developed for parts of this region. We show that P-wave travel times calculated with this model provide an excellent ®t to observations at the Fennoscandian, KRSC and IRIS station networks for a set of seismic events with known or very well-constrained locations. The station-event paths cover large parts of Western Russia and the Barents Sea, thus indicating that this model, which we denote the Barents model, is appropriate for this entire region. We show by examples that signi®cant improvements in event location precision can be achieved compared to using the IASPEI model. We ®nally use the Barents model to calculate locations of recent small seismic events in the Novaya Zemlya region of interest in a CTBT monitoring context.

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