Most environmental monitoring programs on organic contaminants, such as persistent organic pollutants (POPs), have a restricted explicit geographical scope, targeting a specific country or region. Such programs often aim to support relevant policy efforts, allowing for evaluation of empirical trends, which may be further explored in concert with mathematical models to allow for a better understanding of the link between sources and environmental exposures in a given region of interest. Hence, there is typically both regulatory and scientific interest to better understand and potentially predict how source-exposure relationships may vary in space and time, for individual contaminants and across abiotic and biotic compartments. As POPs are recognized as global pollutants because of their known potential for long-range environmental transport, sources affecting a specific region could both be distant and/or of more local origin. Furthermore, the persistence of POPs implies that current exposures could be a result of both historical as well as recent emissions. This calls for regional modelling strategies that are global in context, yet dynamic, reflecting both the possible mobility and lifetime of relevant contaminants in the physical environment and in the human food-chain. Here, we introduce the initial version of an integrated Nested Exposure Model (NEM). NEM reflects the hypothesis that accurate predictions of organic contaminant exposures call for increasing resolution with increasing proximity to a study region of specific interest.