Response to Comment on “Regulatory FOCUS Surface Water Models Fail to Predict Insecticide Concentrations in the Field”

Knäbel, Anja; Stehle, Sebastian; Schäfer, Ralf B.; Schulz, Ralf

doi:10.1021/es3040957

Cited by 4 publications

(11 citation statements)

References 3 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Figure 1a shows that there is no positive relationship in terms of a statistically significant slope with a value greater than 0 between MFCs and PEC FOCUS values for the complete data set. The same has been shown for insecticides 9,30 and fungicides. 10 In addition, only a very weak significant relationship between MFCs and PEC FOCUS values with a maximum r 2 of 0.096 was found for organochlorine insecticides when the linear relationship was determined for individual substance classes (Figure S8).…”

Section: Environmental Science and Technologysupporting

confidence: 71%

“…Nevertheless, there are several reasons why it is likely that measured concentrations are still lower than the actual peak concentrations. 10,27,30 Di Guardo et al 29 compared herbicide runoff measured in two different basins with concentrations predicted with a fugacity model. They showed that the model has a tendency to overestimate actual measured concentrations and concluded that the worst-case scenario results in concentrations "protective for the environment".…”

Section: ■ Discussionmentioning

confidence: 99%

See 1 more Smart Citation

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

Knäbel

Scheringer

Stehle

et al. 2016

Environ. Sci. Technol.

Self Cite

View full text Add to dashboard Cite

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.

show abstract

Section: Environmental Science and Technologysupporting

confidence: 71%

Section: ■ Discussionmentioning

confidence: 99%

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

Knäbel

Scheringer

Stehle

et al. 2016

Environ. Sci. Technol.

Self Cite

View full text Add to dashboard Cite

show abstract

“…This result clearly indicates that the FOCUS model is even less protective for fungicide field concentrations typical for conditions in Europe, as was demonstrated for insecticides. 10,29 Environmental Science & Technology In addition to model inaccuracies, the underestimation of MFCs might also be a result of farmers' malpractice, for example the nonadherence to spray buffer zones. But this would only explain a theoretical maximum of 13% (i.e., difference between 28% and 15% underestimation in step 4 and step 3, respectively) of the cases in which step 4 underestimates respective MFC sw , since step 3 does not consider mitigation options.…”

Section: ■ Discussionmentioning

confidence: 99%

“…The same was shown for insecticides. 10,13 In response to the results obtained for insecticides, 10 Reichenberger 27 criticized that one modeled data point was plotted against several measured data points and claimed that only the maximum measured concentration should be used to evaluate the linear relationship (see also 13 ). Even if the fungicide concentrations considered here were measured either during different seasons or originated from clearly distinguishable entry events, it cannot be ensured that they are absolute peak concentrations.…”

Section: ■ Discussionmentioning

confidence: 99%

“…From the selected field studies, all of the fungicide concentrations measured during independent events in surface waters and sediments were extracted instead of only using the maximum measured concentrations, which might rather result in a data set biased toward worst-case conditions. If multiple fungicide concentrations per active ingredient were reported in one field study, then only those peak concentrations that originated from different entry events (i.e., measured after different precipitation or application events or in different seasons) 13 were selected. Therefore, multiple fungicide concentrations in one publication can be regarded as independent even though some of these peak values might be lower than others.…”

Section: ■ Materials and Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Fungicide Field Concentrations Exceed FOCUS Surface Water Predictions: Urgent Need of Model Improvement

Knäbel

Meyer

Rapp

et al. 2013

Environ. Sci. Technol.

Self Cite

View full text Add to dashboard Cite

FOCUS models are used in European regulatory risk assessment to predict the frequency and magnitude of individual pesticide surface water concentrations. A recent study showed that these models are not protective in the prediction of insecticide concentrations in surface waters and sediments. Since fungicides differ with regard to their physicochemical properties, application patterns, and entry routes, we compared a larger data set of 417 measured field concentrations (MFC) of agricultural fungicides in surface waters and sediments from 56 studies to the respective predicted environmental concentrations (PEC) calculated with FOCUS step 1-4. Although the fraction of the underestimation of fungicide MFC values was generally lower than that obtained for insecticides, 12% of step 3 and 23% of step 4 PECs were exceeded by surface water MFCs. Taking only the 90th percentile concentration of every substance and only E.U. studies into account (E.U. studies: n = 327; 90th percentile + E.U. studies: n = 136), a maximum of 25% of the step 3 and 43% of the step 4 PECs were exceeded by surface water MFCs, which is an even worse outcome than that obtained for insecticides. Our results demonstrate that FOCUS predictions are neither protective nor appropriate for predicting fungicide concentrations in the field in the context of European pesticide risk assessment.

show abstract

Prevention and management of plant protection product transfers within the environment: A review

Tournebize,

Bedos,

Corio-Costet

et al. 2024

Environ Sci Pollut Res

View full text Add to dashboard Cite

Response to Comment on “Regulatory FOCUS Surface Water Models Fail to Predict Insecticide Concentrations in the Field”

Cited by 4 publications

References 3 publications

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

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

Fungicide Field Concentrations Exceed FOCUS Surface Water Predictions: Urgent Need of Model Improvement

Prevention and management of plant protection product transfers within the environment: A review

Contact Info

Product

Resources

About