A new method for the spatially differentiated assessment of impacts of airborne pollutants on human health is presented. It is applicable to primary pollutants with linear exposure response functions. This includes the most important primary air pollutants from transportation and energy generation. The article looks at the spatial differentiation of impacts due to emission height and the local population density distribution around the emission site, as has been predicted using a Gaussian plume model. The differentiation due to population density is captured by way of five generic spatial classes: large cities in agglomerations, highly densified districts in agglomerations, cities in urbanized regions, country average districts, and low density rural districts in rural regions. Average impacts are calculated for each class. The method is simple enough to be applied to a large number of emissions within Life Cycle Assessments. It was used to calculate site-dependent exposure efficiencies for a variety of primary pollutants emitted at different heights. For traffic emissions of pollutants with short atmospheric residence times, the exposure efficiencies vary by a factor of 5 across Germany and by a factor of 75 across Europe. This differentiation due to population density decreases significantly with an increasing atmospheric residence time of the pollutants and with an increasing emission height.