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DOI 10.1002/ps.4149

Медицинская библиотека · Pest management science · 2015

Volatilisation of pesticides under field conditions: inverse modelling and pesticide fate models.

Houbraken Michael, van den Berg Frederik, Butler Ellis Clare M, Dekeyser Donald, Nuyttens David, De Schampheleire Mieke, Spanoghe Pieter

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Аннотация

BACKGROUND

A substantial fraction of the applied crop protection products on crops is lost to the atmosphere. Models describing the prediction of volatility and potential fate of these substances in the environment have become an important tool in the pesticide authorisation procedure at the EU level. The main topic of this research is to assess the rate and extent of volatilisation of ten pesticides after application on field crops.

RESULTS

For eight of the ten pesticides, the volatilisation rates modelled with PEARL (Pesticide Emission Assessment at Regional and Local scales) corresponded well to the calculated rates modelled with ADMS (Atmospheric Dispersion Modelling System). For the other pesticides, large differences were found between the models. Formulation might affect the volatilisation potential of pesticides. Increased leaf wetness increased the volatilisation of propyzamide and trifloxystrobin at the end of the field trial. The reliability of pesticide input parameters, in particular the vapour pressure, is discussed.

CONCLUSION

Volatilisation of propyzamide, pyrimethanil, chlorothalonil, diflufenican, tolylfluanid, cyprodinil and E- and Z-dimethomorph from crops under realistic environmental conditions can be modelled with the PEARL model, as corroborated against field observations. Suggested improvements to the volatilisation component in PEARL should include formulation attributes and leaf wetness at the time of pesticide application. © 2015 Society of Chemical Industry.

Для цитирования: Houbraken Michael, van den Berg Frederik, Butler Ellis Clare M, Dekeyser Donald, Nuyttens David, De Schampheleire Mieke, Spanoghe Pieter. Volatilisation of pesticides under field conditions: inverse modelling and pesticide fate models.. Pest management science. 2015. DOI: 10.1002/ps.4149.

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