Developing a management-oriented simulation model of pesticide emissions for use in the life cycle assessment of paddy rice cultivation

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  • Longlong Tang
  • Kiyotada Hayashi
  • Keiya Inao
  • Morten Birkved
  • Bruun, Sander
  • Kazunori Kohyama
  • Motoko Shimura

Management of the negative environmental impact of pesticides used in paddy fields requires the quantification of the emissions reaching relevant environmental compartments and the determination of the factors that influence such emissions. The present study is the first to develop a simulation model for estimating the fractions emitted to the air (fair), surface water (fsw), and the fractions that leach vertically (fvl) of pesticides applied in paddy fields for life cycle assessments (LCA). The emission quantification methods are based on the properties of the active ingredients of the pesticides and management aspects such as formulations (granular or liquid) and the water-holding period following application. The emission fractions of 37 pesticides used commonly in Japan were estimated using the presented model. A sensitivity analysis was conducted by adjusting parameters applied in the model to reveal their influence on the emission fractions. The parameters influencing fair included the formulation applied, while the water-holding period and waterproofing of the levee influenced fsw regardless of the formulation adopted, suggesting that local management could effectively reduce emissions to surface water. In addition, soil organic carbon content influenced fvl greatly, suggesting considerable regional variation in the emission factor. The developed model is expected to greatly improve the realism of impact assessment of pesticide in LCAs for paddy rice cultivation, considering it fills a gap in the fate model used in LCAs to estimate pesticide emissions to air, surface water, and soil in paddy fields.

OriginalsprogEngelsk
Artikelnummer137034
TidsskriftScience of the Total Environment
Vol/bind716
Antal sider10
ISSN0048-9697
DOI
StatusUdgivet - 2020

ID: 255694133