Propagation of uncertainties in soil and pesticide properties to pesticide leaching

Statement of the Scientific Panel on Plant Protection Products and their Residues (PPR Panel) on the design and conduct of groundwater monitoring studies supporting groundwater exposure assessments of pesticides

Groundwater monitoring is the highest tier in the leaching assessment of plant protection products in the EU. The European Commission requested EFSA for a review by the PPR Panel of the scientific paper of Gimsing et al. (2019) on the design and conduct of groundwater monitoring studies. The Panel concludes that this paper provides many recommendations; however, specific guidance on how to design, conduct and evaluate groundwater monitoring studies for regulatory purposes is missing. The Panel notes that there is no agreed specific protection goal (SPG) at EU level. Also, the SPG has not yet been operationalised in an agreed exposure assessment goal (ExAG). The ExAG describes which groundwater needs to be protected, where and when. Because the design and interpretation of monitoring studies depends on the ExAG, development of harmonised guidance is not yet possible. The development of an agreed ExAG must therefore be given priority. A central question in the design and interpretation of groundwater monitoring studies is that of groundwater vulnerability. Applicants must demonstrate that the selected monitoring sites represent realistic worst-case conditions as specified in the ExAG. Guidance and models are needed to support this step. A prerequisite for the regulatory use of monitoring data is the availability of complete data on the use history of the products containing the respective active substances. Applicants must further demonstrate that monitoring wells are hydrologically connected to the fields where the active substance has been applied. Modelling in combination with (pseudo)tracer experiments would be the preferred option. The Panel concludes that well-conducted monitoring studies provide more realistic exposure assessments and can therefore overrule results from lower tier studies. Groundwater monitoring studies involve a high workload for both regulators and applicants. Standardised procedures and monitoring networks could help to reduce this workload.

Modeling pesticides in global surface soils: Evaluating spatiotemporal patterns for USEtox-based steady-state concentrations

To better manage pesticide pollution in surface soils, we introduced a first-order-kinetics-based screening model to evaluate the steady-state concentrations of pesticides in surface soils while considering degradation, volatilization, plant uptake, and precipitation processes. For each process, we developed a spatiotemporal-pattern-based model using spatiotemporal variables, including air temperature (T_A), relative humidity (RH_A), and rainfall intensity (I_R^A), to characterize the overall dissipation rates (k_T) of pesticides in the soil. These dissipation rates were converted to fate factors (FFs), which are commonly used in life cycle analyses. The results indicate that, in general, the k_T values increase with increasing T_A and I_R^A and decrease with increasing RH_A. This is because increased T_A boosts the degradation, volatilization, and plant uptake processes, whereas increased RH_A lowers the plant transpiration rate. Also, the simulation for over 700 pesticides indicated that the degradation process dominates the overall dissipation of most pesticides in the soil, and the volatilization process contributes the least. In addition, we simulated chlorpyrifos FFs for Brazil, China, the US, and the European Union (EU) using the annual average T_A, RH_A, and I_R^A values. The results indicate that, in general, Brazilian federal units have the smallest FFs and the narrowest simulated FF range because of their humid tropical climates. Meanwhile, the EU member states have the largest FFs and the widest FF range because of their range in locations. In addition, our simulated results show that the surface soils in the high-latitude regions could accumulate more chlorpyrifos than those in low-latitude regions because of the larger simulated FFs. Furthermore, we parameterized our model using 737 pesticides with the USEtox, thereby providing an alternative approach to simulate the steady-state concentration of pesticides in surface soils from the USEtox available data. The model developed herein is a useful screening tool for predicting pesticide concentrations in surface soil worldwide to improve soil and ecological health risk management.

Bixafen, a succinate dehydrogenase inhibitor fungicide, causes microcephaly and motor neuron axon defects during development

Succinate dehydrogenase inhibitors (SDHIs), the most widely used fungicides in agriculture today, act by blocking succinate dehydrogenase (SDH), an essential and evolutionarily conserved component of mitochondrial respiratory chain. Recent results showed that several SDHIs used as fungicides not only inhibit the SDH activity of target fungi but also block this activity in human cells in in vitro models, revealing a lack of specificity and thus a possible health risk for exposed organisms, including humans. Despite the frequent detection of SDHIs in the environment and on harvested products and their increasing use in modern agriculture, their potential toxic effects in vivo, especially on neurodevelopment, are still under-evaluated. Here we assessed the neurotoxicity of bixafen, one of the latest-generation SDHIs, which had never been tested during neurodevelopment. For this purpose, we used a well-known vertebrate model for toxicity testing, namely zebrafish transparent embryos, and live imaging using transgenic lines labelling the brain and spinal cord. Here we show that bixafen causes microcephaly and defects on motor neuron axon outgrowth and their branching during development. Our findings show that the central nervous system is highly sensitive to bixafen, thus demonstrating in vivo that bixafen is neurotoxic in vertebrates and causes neurodevelopmental defects. This work adds to our knowledge of the toxic effect of SDHIs on neurodevelopment and may help us take appropriate precautions to ensure protection against the neurotoxicity of these substances.

Combining Restricted Grazing and Nitrification Inhibitors to Reduce Nitrogen Leaching on New Zealand Dairy Farms

Intensification of pastoral dairy systems often means more nitrogen (N) leaching. A number of mitigation strategies have been proposed to reduce or reverse this trend. The main strategies focus on reducing the urinary N load onto pastures or reducing the rate of nitrification once the urine has been deposited. Restricted grazing is an example of the former and the use of nitrification inhibitors an example of the latter. A relevant concern is the cost effectiveness of these strategies, independently and jointly. To address this concern, we employed a modeling approach to estimate N leaching with and without the use of these mitigation options from a typical grazing dairy farm in New Zealand. Three restricted grazing options were modeled with and without a nitrification inhibitor (dicyandiamide, DCD) and the results were compared with a baseline farm (no restricted grazing, no inhibitor). Applying DCD twice a year, closely following the cows after an autumn and winter grazing round, has the potential to reduce annualized and farm-scale N leaching by ∼12%, whereas restricted grazing had leaching reductions ranging from 23 to 32%, depending on the timing of restricted grazing. Combining the two strategies resulted in leaching reductions of 31 to 40%. The abatement cost per kilogram of N leaching reduction was NZ$50 with DCD, NZ$32 to 37 for restricted grazing, and NZ$40 to 46 when the two were combined. For the range analyzed, all treatments indicated similar cost per percentage unit of mitigated N leaching, demonstrating that restricted grazing and nitrification inhibitors can be effective when used concurrently.

A coupled stochastic/deterministic model to estimate the evolution of the risk of water contamination by pesticides across Canada

Periodic assessments of the risk of water contamination by pesticides help decision makers improve the sustainability of agricultural management practices. In Canada, when evaluating the risk of water contamination by pesticides, 2 main constraints arise. First, because the area of interest is large, a pesticide transport model with low computational running time is mandatory. Second, some relevant input data for simulations are not known, and most are known only at coarse scale. This study aims to develop a robust methodology to estimate the evolution of the risk of water contamination by pesticides across Canada. To circumvent the 2 aforementioned issues, we constructed a stochastic model and coupled it to the 1-dimensional pesticide fate model Pesticide Root Zone Model (PRZM). To account for input data uncertainty, the stochastic model uses a Monte Carlo approach to generate several pesticide application scenarios and to randomly select PRZM parameter values. One hundred different scenarios were simulated for each of over 2000 regions (Soil Landscapes of Canada [SLC] polygons) for the years 1981 and 2006. Overall, the results indicated that in those regions in which the risk increased from 1981 to 2006, the increase in risk was mainly attributable to the increased area treated by pesticides or an increase in the number of days with runoff. More specifically, this work identifies the areas at higher risk, where further analyses with finer-scale input data should be performed. The model is specific for Canadian data, but the framework could be adapted for other large countries.

European scenarios for exposure of soil organisms to pesticides

Standardised exposure scenarios play an important role in European pesticide authorisation procedures (a scenario is a combination of climate, weather and crop data to be used in exposure models). The European Food Safety Authority developed such scenarios for the assessment of exposure of soil organisms to pesticides. Scenarios were needed for both the concentration in total soil and for the concentration in the liquid phase. The goal of the exposure assessment is the 90th percentile of the exposure concentration in the area of agricultural use of a pesticide in each of three regulatory European zones (North, Centre and South). A statistical approach was adopted to find scenarios that are consistent with this exposure goal. Scenario development began with the simulation of the concentration distribution in the entire area of use by means of a simple analytical model. In the subsequent two steps, procedures were applied to account for parameter uncertainty and scenario uncertainty (i.e. the likelihood that a scenario that is derived for one pesticide is not conservative enough for another pesticide). In the final step, the six scenarios were selected by defining their average air temperature, soil organic-matter content and their soil textural class. Organic matter of the selected scenarios decreased in the order North-Centre-South. Because organic matter has a different effect on the concentration in total soil than it has on the concentration in the liquid phase, the concentration in total soil decreased in the order North-Centre-South whereas the concentration in the liquid phase decreased in the opposite order. The concentration differences between the three regulatory zones appeared to be no more than a factor of two. These differences were comparatively small in view of the considerable differences in climate and soil properties between the three zones.