Air quality models are often used to simulate how emission scenarios influence the concentration of primary as well as secondary pollutants in the atmosphere. In some cases, it is necessary to replace these air quality models with source–receptor relationships, to mimic in a faster way the link between emissions and concentrations. Source–receptor relationships are therefore also used in Integrated Assessment Models, when scenario responses need to be known in very short time. The objective of this work is to present a novel approach to design a source–receptor relationship for air quality modeling. Overall the proposed approach is shown to significantly reduce the number of simulations required for the training step and to bring flexibility in terms of emission source definition. A regional domain application is also presented, to test the performances of the proposed approach. 
A new approach to design source–receptor relationships for air quality modelling