Aquatic Exposure Predictions of Insecticide Field Concentrations Using a Multimedia Mass-Balance Model

Publikation: Beiträge in ZeitschriftenZeitschriftenaufsätzeForschungbegutachtet

Standard

Aquatic Exposure Predictions of Insecticide Field Concentrations Using a Multimedia Mass-Balance Model. / Knäbel, Anja; Scheringer, Martin; Stehle, Sebastian et al.

in: Environmental Science & Technology, Jahrgang 50, Nr. 7, 05.04.2016, S. 3721-3728.

Publikation: Beiträge in ZeitschriftenZeitschriftenaufsätzeForschungbegutachtet

Harvard

APA

Vancouver

Bibtex

@article{87d58ac9dc29421181827dd55733e1c3,
title = "Aquatic Exposure Predictions of Insecticide Field Concentrations Using a Multimedia Mass-Balance Model",
abstract = "Highly complex process-driven mechanistic fate and transport models and multimedia mass balance models can be used for the exposure prediction of pesticides in different environmental compartments. Generally, both types of models differ in spatial and temporal resolution. Process-driven mechanistic fate models are very complex, and calculations are time-intensive. This type of model is currently used within the European regulatory pesticide registration (FOCUS). Multimedia mass-balance models require fewer input parameters to calculate concentration ranges and the partitioning between different environmental media. In this study, we used the fugacity-based small-region model (SRM) to calculate predicted environmental concentrations (PEC) for 466 cases of insecticide field concentrations measured in European surface waters. We were able to show that the PECs of the multimedia model are more protective in comparison to FOCUS. In addition, our results show that the multimedia model results have a higher predictive power to simulate varying field concentrations at a higher level of field relevance. The adaptation of the model scenario to actual field conditions suggests that the performance of the SRM increases when worst-case conditions are replaced by real field data. Therefore, this study shows that a less complex modeling approach than that used in the regulatory risk assessment exhibits a higher level of protectiveness and predictiveness and that there is a need to develop and evaluate new ecologically relevant scenarios in the context of pesticide exposure modeling.",
keywords = "Chemistry, FAIL, SURFACE-WATER, ORGANIC-CHEMICALS, RISK-ASSESSMENT, ENVIRONMENT, ECOSYSTEMS, FUGACITY",
author = "Anja Kn{\"a}bel and Martin Scheringer and Sebastian Stehle and Ralf Schulz",
year = "2016",
month = apr,
day = "5",
doi = "10.1021/acs.est.5b05721",
language = "English",
volume = "50",
pages = "3721--3728",
journal = "Environmental Science & Technology",
issn = "0013-936X",
publisher = "ACS Publications",
number = "7",

}

RIS

TY - JOUR

T1 - Aquatic Exposure Predictions of Insecticide Field Concentrations Using a Multimedia Mass-Balance Model

AU - Knäbel, Anja

AU - Scheringer, Martin

AU - Stehle, Sebastian

AU - Schulz, Ralf

PY - 2016/4/5

Y1 - 2016/4/5

N2 - Highly complex process-driven mechanistic fate and transport models and multimedia mass balance models can be used for the exposure prediction of pesticides in different environmental compartments. Generally, both types of models differ in spatial and temporal resolution. Process-driven mechanistic fate models are very complex, and calculations are time-intensive. This type of model is currently used within the European regulatory pesticide registration (FOCUS). Multimedia mass-balance models require fewer input parameters to calculate concentration ranges and the partitioning between different environmental media. In this study, we used the fugacity-based small-region model (SRM) to calculate predicted environmental concentrations (PEC) for 466 cases of insecticide field concentrations measured in European surface waters. We were able to show that the PECs of the multimedia model are more protective in comparison to FOCUS. In addition, our results show that the multimedia model results have a higher predictive power to simulate varying field concentrations at a higher level of field relevance. The adaptation of the model scenario to actual field conditions suggests that the performance of the SRM increases when worst-case conditions are replaced by real field data. Therefore, this study shows that a less complex modeling approach than that used in the regulatory risk assessment exhibits a higher level of protectiveness and predictiveness and that there is a need to develop and evaluate new ecologically relevant scenarios in the context of pesticide exposure modeling.

AB - Highly complex process-driven mechanistic fate and transport models and multimedia mass balance models can be used for the exposure prediction of pesticides in different environmental compartments. Generally, both types of models differ in spatial and temporal resolution. Process-driven mechanistic fate models are very complex, and calculations are time-intensive. This type of model is currently used within the European regulatory pesticide registration (FOCUS). Multimedia mass-balance models require fewer input parameters to calculate concentration ranges and the partitioning between different environmental media. In this study, we used the fugacity-based small-region model (SRM) to calculate predicted environmental concentrations (PEC) for 466 cases of insecticide field concentrations measured in European surface waters. We were able to show that the PECs of the multimedia model are more protective in comparison to FOCUS. In addition, our results show that the multimedia model results have a higher predictive power to simulate varying field concentrations at a higher level of field relevance. The adaptation of the model scenario to actual field conditions suggests that the performance of the SRM increases when worst-case conditions are replaced by real field data. Therefore, this study shows that a less complex modeling approach than that used in the regulatory risk assessment exhibits a higher level of protectiveness and predictiveness and that there is a need to develop and evaluate new ecologically relevant scenarios in the context of pesticide exposure modeling.

KW - Chemistry

KW - FAIL

KW - SURFACE-WATER

KW - ORGANIC-CHEMICALS

KW - RISK-ASSESSMENT

KW - ENVIRONMENT

KW - ECOSYSTEMS

KW - FUGACITY

UR - http://www.scopus.com/inward/record.url?scp=84964258043&partnerID=8YFLogxK

U2 - 10.1021/acs.est.5b05721

DO - 10.1021/acs.est.5b05721

M3 - Journal articles

C2 - 26889709

VL - 50

SP - 3721

EP - 3728

JO - Environmental Science & Technology

JF - Environmental Science & Technology

SN - 0013-936X

IS - 7

ER -

DOI