Background/aim Pesticides can migrate from the place of application to houses via different routes (i.e. drift, volatilization, deposition, transport of contaminated soil- and dust particles). Different models exist for pesticide exposures but often these do not cover all exposure routes nor focus on residential exposures. Given the public health concern over pesticides, validated integrated models are needed.

Methods We carried out a systematic review of models describing pesticide concentration gradients related to spraying events using a boom spray. This review comprised articles published until June 2017. Subsequently we assessed the best suitable combination of models to assess residents’ exposure to pesticides. We selected these models based on how well they are described in the literature, their usability, validation, whether they can be used on different spatial scales, possibility to link with other models, open source or accessibility, sensitivity to parameterization and how they account for uncertainty.

Results We report and discuss each pathway by looking at input parameters, such as physic-chemical properties of compounds, description of surface–air interaction, meteorological variables. We present a summary of each model by commenting on the stronger features and on the less fit for the purpose of modelling residents’ exposure. We also inform on the pathways and sources that are lacking attention in literature or that need to be more emphasised when studying residents’ exposure. The resulting chain of models is presented and discussed in more detail. Finally, an integrated framework to study residents’ exposure to pesticides is proposed.

Conclusion Although identified models appear to cover all processes needed to describe residents exposure to pesticides no integrated model exists to date. We propose and describe an integrated modelling framework from source to residence and inhabitants, which takes into account all relevant routes leading to residents exposure, by combining deterministic and statistical modelling approaches.