Spatial representativeness of a monitoring station and spatial extent of an exceedance zone in case of non-compliance with environmental objectives are notions appearing in the European legislation on ambient air quality. No speci c approach is prescribed to delimit such areas. We developed a probabilistic methodology based on a preliminary kriging estimate of atmospheric concentrations at each point of the domain. In the proposed de nition, a point is considered as belonging to the area of representativeness of a station if its concentration di ers from the station measurement by less than a given threshold. Additional criteria related to distance or environmental characteristics may also be introduced. The standard deviation of the estimation error is then used, to select the points, at a xed risk, where the di erence of concentration with respect to the station is below the threshold and to provide the probability of overshooting a limit value. Stability in time and sensitivity to the selected criteria are rst tested with NO2 annual concentration data produced by combining surface monitoring observations and outputs from the CHIMERE chemistry transport model. On the local scale, data from passive sampling surveys and high resolution auxiliary variables are used to provide a more precise estimate of background pollution. Tra c related pollution can also be accounted for in the map with help of additional information such as distance to the road, tra c-related NOx emissions, or road tra c counts. The methodology is applied to NO2 experimental datasets for di erent French cities to assess the spatial representativeness of stations and delimit areas of exceedance of the NO2 annual limit value.