Bioaerosols are released in elevated quantities from composting facilities and are associated with negative health effects, although dose-response relationships are not well understood, and require improved exposure classification. Dispersion modelling has great potential to improve exposure classification, but has not yet been extensively used or validated in this context. We present a sensitivity analysis of the ADMS dispersion model specific to input parameter ranges relevant to bioaerosol emissions from open windrow composting. This analysis provides an aid for model calibration by prioritising parameter adjustment and targeting independent parameter estimation. Results showed that predicted exposure was most sensitive to the wet and dry deposition modules and the majority of parameters relating to emission source characteristics, including pollutant emission velocity, source geometry and source height. This research improves understanding of the accuracy of model input data required to provide more reliable exposure predictions.
Bibliographical noteFunding Information:
This work was jointly funded by the EPSRC and the Environment Agency through an industrial CASE award (EPSRC CASE award EP/G501319/1 ), and partly funded by the National Institute for Health Research Health Protection Research Unit (NIHR HPRU) in Health Impact of Environmental Hazards at King's College London in partnership with Public Health England (PHE) and collaboration with Imperial College London. The work of the UK Small Area Health Statistics Unit is funded by Public Health England as part of the MRC-PHE Centre for Environment and Health, funded also by the UK Medical Research Council . MW benefitted from Study Leave granted by the University of Leicester. The authors would like to thank Patricia Bellamy for advice on data analysis, and Joao Delgado and Kerry Pearn for their help developing the VBA code used to perform the analysis. The views expressed are those of the authors and not necessarily those of the Environment Agency or EPSRC.
- Dispersion modelling
- Sensitivity analysis