International scale implementation of the CNOSSOS-EU road traffic noise prediction model for epidemiological studies. (November 2015) - Morley, D.W.; de Hoogh, K.; Fecht, D.; Fabbri, F.; Bell, M.; Goodman, P.S.; Elliott, P.; Hodgson, S.; Hansell, A.L.; Gulliver, J.
Abstract: The EU-FP7-funded BioSHaRE project is using individual-level data pooled from several national cohort studies in Europe to investigate the relationship of road traffic noise and health. The detailed input data (land cover and traffic characteristics) required for noise exposure modelling are not always available over whole countries while data that are comparable in spatial resolution between different countries is needed for harmonised exposure assessment. Here, we assess the feasibility using the CNOSSOS-EU road traffic noise prediction model with coarser input data in terms of model performance. Starting with a model using the highest resolution datasets, we progressively introduced lower resolution data over five further model runs and compared noise level estimates to measurements. We conclude that a low resolution noise model should provide adequate performance for exposure ranking (Spearman's rank = 0.75; p < 0.001), but with relatively large errors in predicted noise levels (RMSE = 4.46 dB(A)). Graphical abstract: Highlights: The first implementation of CNOSSOS-EU for national scale noise exposure assessment. Road traffic noise model performance with varying resolution of inputs is assessed. Model performance is good with low resolution inputs (rs = 0.75). This model will be applied in epidemiological studies of European cohorts. Abstract : The CNOSSOS-EU road traffic noise model estimates can be used for international scale exposure assessment when parameterised with freely available low resolution covering a large geographic area.