|Title||The BROWSE model for predicting exposures of residents and bystanders to agricultural use of plant protection products: An overview|
|Author(s)||Butler Ellis, M.C.; De Zande, Jan C. Van; Berg, Frederik Van Den; Kennedy, Marc C.; O'sullivan, Christine M.; Jacobs, Cor M.; Fragkoulis, Georgios; Spanoghe, Pieter; Gerritsen-ebben, Rianda; Frewer, Lynn J.; Charistou, Agathi|
|Source||Biosystems Engineering 154 (2017). - ISSN 1537-5110 - p. 92 - 104.|
PPO/PRI AGRO Field Technology Innovations
Alterra - Climate change and adaptive land and water management
Marketing and Consumer Behaviour
|Publication type||Refereed Article in a scientific journal|
|Abstract||New models have been developed, with the aim of improving the estimate of exposure of residents and bystanders to agricultural pesticides for regulatory purposes. These are part of a larger suite of models also covering operators and workers. The population that is modelled for residents and bystanders relates to people (both adults and children) who have no association with the application (i.e. not occupational exposure) but are adjacent to the treated area during and/or after the application process. The scenarios that the models aim to describe are based on consideration of both best practice and of real practice, as shown in surveys and from expert knowledge obtained in stakeholder consultations.
The work has focused on three causes of exposure identified as having potential for improvement: boom sprayers, orchard sprayers and vapour emissions.
An overview of the models is given, and a description of model input values and proposed defaults. The main causes of uncertainty in the models are also discussed. There are a number of benefits of the BROWSE model over current models of bystander and resident exposure, which includes the incorporation of mitigation measures for reducing exposure and the use of probabilistic modelling to avoid an over-conservative approach.
It is expected that the levels of exposure that the BROWSE model predicts will, in some cases, be higher than those predicted by the current UK regulatory model. This is largely because the modelled scenarios have been updated to account for current practice and current scientific knowledge.