A web-based pesticide risk assessment tool for drinking water protection zones in Sweden.

To protect human health, wildlife and the aquatic environment, "safe uses" of pesticides are determined at the EU level while product authorization and terms of use are established at the national level. In Sweden, extra precaution is taken to protect drinking water, and permits are therefore required for pesticide use within abstraction zones. This paper presents MACRO-DB, a tool for assessing pesticide contamination risks of groundwater and surface water, used by authorities to support their decision-making for issuing such permits. MACRO-DB is a meta-model based on 583,200 simulations of the physically-based MACRO model used for assessing pesticide leaching risks at EU and national level. MACRO-DB is simple to use and runs on widely available input data. In a qualitative comparative assessment for two counties in Sweden, MACRO-DB outputs were in general agreement with groundwater monitoring data and matched or were more protective than the national risk assessment procedure for groundwater.

Quantifying pesticide emissions for drift deposition in comparative risk and impact assessment.

Estimating emissions of chemical pesticides used in agriculture is an essential component in evaluating the potential toxicity-related impacts on humans and ecosystems in various comparative risk and impact assessment frameworks, such as life cycle assessment, environmental footprinting, absolute environmental sustainability assessment, chemical substitution, and risk prioritization. Emissions related to drift deposition-usually derived from drift experiments-can reach non-target areas, and vary as a function of crop characteristics and application technique. We derive cumulative drift deposition fractions for a wide range of experimental drift functions for use in comparative and mass-balanced approaches. We clarify that cumulative drift deposition fractions require to integrate the underlying drift functions over the relevant deposition area and to correct for the ratio of deposition area to treated field area to arrive at overall mass deposited per unit mass of applied pesticide. Our results show that for most crops, drift deposition fractions from pesticide application are below 0.03 (i.e. 3% of applied mass), except for grapes and fruit trees, where drift fractions can reach 5% when using canon or air blast sprayers. Notably, aerial applications on soybeans can result in significantly higher drift deposition fractions, ranging from 20% to 60%. Additionally, varying the nozzle position can lead to a factor of five differences in pesticide deposition, and establishing buffer zones can effectively reduce drift deposition. To address remaining limitations in deriving cumulative drift deposition fractions, we discuss possible alternative modelling approaches. Our proposed approach can be implemented in different quantitative and comparative assessment frameworks that require emission estimates of agricultural pesticides, in support of reducing chemical pollution and related impacts on human health and the environment.

Risk mitigation measures for pesticide runoff: How effective are they?

BACKGROUND: One of the most important sources of pesticide pollution of surface waters is runoff and erosion from agricultural fields after rainfall. This study analyses the efficacy of different risk mitigation measures to reduce pesticide runoff and erosion inputs into surface waters from arable land excluding rice fields. RESULTS: Three groups of risk mitigation measures were quantitatively analyzed: vegetative filter strips, micro-dams in row crops and soil conservation measures. Their effectiveness was evaluated based on a meta-analysis of available experimental data using statistical methods such as classification and regression trees, and exploratory data analysis. Results confirmed the effectiveness of vegetative filter strips and micro-dams. Contrary to common assumption, the width of vegetative filter strips alone is not sufficient to predict their effectiveness. The effectiveness of soil conservation measures (especially mulch-tillage) varied widely. This was in part due to the heterogeneity of the available experimental data, probably resulting from the inconsistent implementation and the inadequate definitions of these measures. CONCLUSION: Both vegetative filter strips and micro-dams are effective and suitable, and can therefore be recommended for quantitative assessment of environmental pesticide exposure in surface waters. However, the processes of infiltration and sedimentation in vegetative filter strips should be simulated with a mechanistic model like Vegetative Filter Strip Modeling System, VFSMOD. The reduction effect of micro-dams can be modelled by reducing the runoff curve number, e.g., in the pesticide root zone model, PRZM. Soil conservation measures are in principle promising, but further well-documented data are needed to determine under which conditions they are effective. © 2023 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Dynamic prediction of effective runoff sediment particle size for improved assessment of erosion mitigation efficiency with vegetative filter strips.

The most widely implemented mitigation measure to reduce transfer of surface runoff pesticides and other pollutants to surface water bodies are vegetative filter strips (VFS). The most commonly used dynamic model for quantifying the reduction by VFS of surface runoff, eroded sediment, pesticides and other pollutants is VFSMOD, which simulates reduction of total inflow (∆Q) and of incoming eroded sediment load (∆E) mechanistically during the rainfall-runoff event. These variables are subsequently used to calculate the reduction of pesticide load by the VFS (∆P). Since errors in ∆Q and ∆E propagate into ∆P, for strongly-sorbing compounds an accurate prediction of ∆E is crucial for a reliable prediction of ∆P. The most important incoming sediment characteristic for ∆E is the median particle diameter (d50). Current d50 estimation methods are simplistic, yielding fixed d50 based on soil properties and ignoring specific event characteristics and dynamics. We derive an improved dynamic d50 parameterization equation for use in regulatory VFS scenarios based on an extensive dataset of 93 d50 values and 17 candidate explanatory variables compiled from heterogeneous data sources and methods. The dataset was analysed first using machine learning techniques (Random Forest, Gradient Boosting) and Global Sensitivity Analysis (GSA) as a dimension reduction technique and to identify potential interactions between explanatory variables. Using the knowledge gained, a parsimonious multiple regression equation with 6 predictors was developed and thoroughly tested. Since three of the predictors are event-specific (eroded sediment yield, rainfall intensity and peak runoff rate), predicted d50 vary dynamically across event magnitudes and intensities. Incorporation of the improved d50 parameterization equation in higher-tier pesticide assessment tools with VFSMOD provides more realistic quantitative mitigation in regulatory US-EPA and EU FOCUS pesticide risk assessment frameworks. The equation is also readily applicable to other erosion management problems.

Recalibration and cross-validation of pesticide trapping equations for vegetative filter strips (VFS) using additional experimental data.

Vegetative filter strips (VFS) are widely used for mitigating pesticide inputs into surface waters via surface runoff and erosion. To simulate the effectiveness of VFS the model VFSMOD is frequently used. While VFSMOD simulates infiltration and sedimentation mechanistically, the reduction of pesticide load in surface runoff by the VFS is calculated with the empirical Sabbagh equation. This multiple regression equation has not been widely accepted by regulatory authorities, because its reliability has not been sufficiently demonstrated yet. A major drawback is the small number of calibration data points (n = 47). To corroborate and improve the predictive capability of the Sabbagh equation, additional experimental VFS data were compiled from the available literature. The enlarged dataset (n = 244) was used to recalibrate the Sabbagh equation, the recently proposed Chen equation and a set of "reduced" Sabbagh equations with fewer independent variables, with ordinary least squares (OLS) regression and to test an alternative, regression-free mass balance approach. The Sabbagh equation fitted the dataset slightly better than the Chen equation (coefficient of determination R2 = 0.82 vs. 0.79). The purely predictive mass balance approach performed slightly worse (Nash-Sutcliffe Efficiency NSE = 0.74), but significantly better than the Sabbagh and Chen equations with their old coefficients. In a k-fold cross validation analysis to assess the predictive capability of the various regression equations, both the full Sabbagh and the reduced Sabbagh equations with two or more variables outperformed the Chen equation. Finally, a maximum-likelihood-based calibration and uncertainty analysis were conducted for the Sabbagh equation using the DREAM_ZS algorithm and two different likelihood functions. The DREAM simulations corroborated the parameter values obtained with OLS regression. The study confirmed the suitability of the Sabbagh equation for regulatory modelling of pesticide trapping in VFS. However, the regression-free mass balance approach turned out to be a viable alternative.

Pesticide exposure assessment for surface waters in the EU. Part 2: Determination of statistically based run-off and drainage scenarios for Germany.

BACKGROUND: In order to assess surface water exposure to active substances of plant protection products (PPPs) in the European Union (EU), the FOCUS (FOrum for the Co-ordination of pesticide fate models and their USe) surface water workgroup introduced four run-off and six drainage scenarios for Step 3 of the tiered FOCUSsw approach. These scenarios may not necessarily represent realistic worst-case situations for the different Member States of the EU. Hence, the suitability of the scenarios for risk assessment in the national authorisation procedures is not known. RESULTS: Using Germany as an example, the paper illustrates how national soil-climate scenarios can be developed to model entries of active substances into surface waters from run-off and erosion (using the model PRZM) and from drainage (using the model MACRO). In the authorisation procedure for PPPs on Member State level, such soil-climate scenarios can be used to determine exposure endpoints with a defined overall percentile. CONCLUSION: The approach allows the development of national specific soil-climate scenarios and to calculate percentile-based exposure endpoints. The scenarios have been integrated into a software tool analogous to FOCUS-SWASH which can be used in the future to assess surface water exposure in authorisation procedures of PPPs in Germany. © 2017 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Modelling survival: exposure pattern, species sensitivity and uncertainty.

The General Unified Threshold model for Survival (GUTS) integrates previously published toxicokinetic-toxicodynamic models and estimates survival with explicitly defined assumptions. Importantly, GUTS accounts for time-variable exposure to the stressor. We performed three studies to test the ability of GUTS to predict survival of aquatic organisms across different pesticide exposure patterns, time scales and species. Firstly, using synthetic data, we identified experimental data requirements which allow for the estimation of all parameters of the GUTS proper model. Secondly, we assessed how well GUTS, calibrated with short-term survival data of Gammarus pulex exposed to four pesticides, can forecast effects of longer-term pulsed exposures. Thirdly, we tested the ability of GUTS to estimate 14-day median effect concentrations of malathion for a range of species and use these estimates to build species sensitivity distributions for different exposure patterns. We find that GUTS adequately predicts survival across exposure patterns that vary over time. When toxicity is assessed for time-variable concentrations species may differ in their responses depending on the exposure profile. This can result in different species sensitivity rankings and safe levels. The interplay of exposure pattern and species sensitivity deserves systematic investigation in order to better understand how organisms respond to stress, including humans.

Pesticide exposure assessment for surface waters in the EU. Part 1: Some comments on the current procedure.

In 2001, the European Commission introduced a risk assessment project known as FOCUS (FOrum for the Coordination of pesticide fate models and their USe) for the surface water risk assessment of active substances in the European Union. Even for the national authorisation of plant protection products (PPPs), the vast majority of EU member states still refer to the four runoff and six drainage scenarios selected by the FOCUS Surface Water Workgroup. However, our study, as well as the European Food Safety Authority (EFSA), has stated the need for various improvements. Current developments in pesticide exposure assessment mainly relate to two processes. Firstly, predicted environmental concentrations (PECs) of pesticides are calculated by introducing model input variables such as weather conditions, soil properties and substance fate parameters that have a probabilistic nature. Secondly, spatially distributed PECs for soil-climate scenarios are derived on the basis of an analysis of geodata. Such approaches facilitate the calculation of a spatiotemporal cumulative distribution function (CDF) of PECs for a given area of interest and are subsequently used to determine an exposure concentration endpoint as a given percentile of the CDF. For national PPP authorisation, we propose that, in the future, exposure endpoints should be determined from the overall known statistical PEC population for an area of interest, and derived for soil and climate conditions specific to the particular member state. © 2016 Society of Chemical Industry.

Identification of key climatic factors regulating the transport of pesticides in leaching and to tile drains.

BACKGROUND: Key climatic factors influencing the transport of pesticides to drains and to depth were identified. Climatic characteristics such as the timing of rainfall in relation to pesticide application may be more critical than average annual temperature and rainfall. The fate of three pesticides was simulated in nine contrasting soil types for two seasons, five application dates and six synthetic weather data series using the MACRO model, and predicted cumulative pesticide loads were analysed using statistical methods. RESULTS: Classification trees and Pearson correlations indicated that simulated losses in excess of 75th percentile values (0.046 mg m(-2) for leaching, 0.042 mg m(-2) for drainage) generally occurred with large rainfall events following autumn application on clay soils, for both leaching and drainage scenarios. The amount and timing of winter rainfall were important factors, whatever the application period, and these interacted strongly with soil texture and pesticide mobility and persistence. Winter rainfall primarily influenced losses of less mobile and more persistent compounds, while short-term rainfall and temperature controlled leaching of the more mobile pesticides. CONCLUSIONS: Numerous climatic characteristics influenced pesticide loss, including the amount of precipitation as well as the timing of rainfall and extreme events in relation to application date. Information regarding the relative influence of the climatic characteristics evaluated here can support the development of a climatic zonation for European-scale risk assessment for pesticide fate.

Mitigation strategies to reduce pesticide inputs into ground- and surface water and their effectiveness; a review.

In this paper, the current knowledge on mitigation strategies to reduce pesticide inputs into surface water and groundwater, and their effectiveness when applied in practice is reviewed. Apart from their effectiveness in reducing pesticide inputs into ground- and surface water, the mitigation measures identified in the literature are evaluated with respect to their practicability. Those measures considered both effective and feasible are recommended for implementing at the farm and catchment scale. Finally, recommendations for modelling are provided using the identified reduction efficiencies. Roughly 180 publications directly dealing with or being somehow related to mitigation of pesticide inputs into water bodies were examined. The effectiveness of grassed buffer strips located at the lower edges of fields has been demonstrated. However, this effectiveness is very variable, and the variability cannot be explained by strip width alone. Riparian buffer strips are most probably much less effective than edge-of-field buffer strips in reducing pesticide runoff and erosion inputs into surface waters. Constructed wetlands are promising tools for mitigating pesticide inputs via runoff/erosion and drift into surface waters, but their effectiveness still has to be demonstrated for weakly and moderately sorbing compounds. Subsurface drains are an effective mitigation measure for pesticide runoff losses from slowly permeable soils with frequent waterlogging. For the pathways drainage and leaching, the only feasible mitigation measures are application rate reduction, product substitution and shift of the application date. There are many possible effective measures of spray drift reduction. While sufficient knowledge exists for suggesting default values for the efficiency of single drift mitigation measures, little information exists on the effect of the drift reduction efficiency of combinations of measures. More research on possible interactions between different drift mitigation measures and the resulting overall drift reduction efficiency is therefore indicated. Point-source inputs can be mitigated against by increasing awareness of the farmers with regard to pesticide handling and application, and encouraging them to implement loss-reducing measures of "best management practice". In catchments dominated by diffuse inputs at least in some years, mitigation of point-source inputs alone may not be sufficient to reduce pesticide loads/concentrations in water bodies to an acceptable level.