Comparison and evaluation of pesticide monitoring programs using a process-based mixture model

Linking chemical surface water monitoring and pesticide regulation in selected European countries

The progress in chemical analytics and understanding of pesticide dynamics in surface waters allows establishing robust data on compounds with frequent exceedances of quality standards. The current chemical, temporal, and spatial coverage of the pesticide monitoring campaigns differs strongly between European countries. A questionnaire revealed differences in monitoring strategies in seven selected European countries; Nordic countries prioritize temporal coverage, while others focus on spatial coverage. Chemical coverage has increased, especially for non-polar classes like synthetic pyrethroids. Sweden combines monitoring data with agricultural practices for derived quantities, while the Netherlands emphasizes spatial coverage to trace contamination sources. None of the EU member states currently has established a process for linking chemical surface water monitoring data with regulatory risk assessment, while Switzerland has recently established a legally defined feedback loop. Due to their design and objectives, most strategies do not capture concentration peaks, especially 2-week composite samples, but also grab samples. Nevertheless, for substances that appear problematic in many data sets, the need for action is evident even without harmonization of monitoring programs. Harmonization would be beneficial, however, for cross-national assessment including risk reduction measures.

Proportional contributions to organic chemical mixture effects in groundwater and surface water

Semi-quantitative GC-MS and LC-MS measurements of organic chemicals in groundwater and surface waters were used to assess the overall magnitude and contribution of the most important substances to calculated mixture hazard. Here we use GC-MS and LC-MS measurements taken from two separate national monitoring programs for groundwater and surface water in England, in combination with chronic species sensitivity distribution (SSD) HC50 values published by Posthuma et al. (2019, Environ. Toxicol. Chem, 38, 905-917) to calculate individual substance hazard quotients and mixture effects using a concentration addition approach. The mixture analysis indicated that, as anticipated, there was an increased hazard from the presence of a cocktail of substances at sites compared to the hazard for any single chemical. The magnitude of the difference between the hazard attributed to the most important chemical and the overall mixture effect, however, was not large. Thus, the most toxic chemical contributed ≥ 20% of the calculated mixture effect in >99% of all measured groundwater and surface water samples. On the basis of this analysis, a 5 fold assessment factor placed on the risk identified for any single chemical would offer a high degree of in cases where implementation of a full mixture analysis was not possible. This finding is consistent with previous work that has assessed chemical mixture effects within field monitoring programs and as such provides essential underpinning for future policy and management decisions on how to effectively and proportionately manage mixture risks.

A fuzzy knowledge-based model for assessing risk of pesticides into the air in cropping systems

Pesticide use in current cropping systems has become a key input to improve productivity. However, their potential risk to nature demands tools for designing a sustainable use. In this work, a fuzzy knowledge-based model was developed for assessing risk of pesticides into the air. The model was based on fuzzy logic theory which provides a means for representing uncertainty by including knowledge about different processes related to pesticide dynamics using functions, control rules and logical inference systems. All these elements were built through a literature review. Results from the sensitivity analysis on the final model structure showed that the Henry's law constant was the most influential input variable related to the active ingredient identity, while the most influential management and environmental input variables on the pesticide air risk values were the droplet size together with the application method and the current wet bulb temperature depression value, respectively. Results from an independent model validation showed a significant goodness-of-fit between the simulated risk of drift and volatilization and the observed values under experimental conditions. Long-term simulations in a real soybean production system in Argentina showed results of drift reduction in post-emergence conditions of the crop under aerial application condition, and a significant effect of the identity of the active ingredient in the risk values. Simulated risk values from the developed model allow to identify ex ante the combination of agronomic decisions, together with environmental conditions that can reduce the risk of pesticides in the air in real production systems. Further combination with ecotoxicological classification tools should improve pesticide use assessment in agricultural systems.

Effect Modeling Quantifies the Difference Between the Toxicity of Average Pesticide Concentrations and Time-Variable Exposures from Water Quality Monitoring

Synthetic chemicals are frequently detected in water bodies, and their concentrations vary over time. Water monitoring programs typically employ either a sequence of grab samples or continuous sampling, followed by chemical analysis. Continuous time-proportional sampling yields the time-weighted average concentration, which is taken as proxy for the real, time-variable exposure. However, we do not know how much the toxicity of the average concentration differs from the toxicity of the corresponding fluctuating exposure profile. We used toxicokinetic-toxicodynamic models (invertebrates, fish) and population growth models (algae, duckweed) to calculate the margin of safety in moving time windows across measured aquatic concentration time series (7 pesticides) in 5 streams. A longer sampling period (14 d) for time-proportional sampling leads to more deviations from the real chemical stress than shorter sampling durations (3 d). The associated error is a factor of 4 or less in the margin of safety value toward underestimating and an error of factor 9 toward overestimating chemical stress in the most toxic time windows. Under- and overestimations occur with approximate equal frequency and are very small compared with the overall variation, which ranged from 0.027 to 2.4 × 10¹⁰ (margin of safety values). We conclude that continuous, time-proportional sampling for a period of 3 and 14 d for acute and chronic assessment, respectively, yields sufficiently accurate average concentrations to assess ecotoxicological effects. Environ Toxicol Chem 2020;39:2158-2168. © 2020 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Higher than … or lower than ….? Evidence for the validity of the extrapolation of laboratory toxicity test results to predict the effects of chemicals and ionising radiation in the field

Single species laboratory tests and associated species sensitivity distributions (SSDs) that utilise the resulting data can make a key contribution to efforts to prospective hazard assessments for pesticides, biocides, metals and ionising radiation for research and regulatory risk assessment. An assumption that underlies the single species based toxicity testing approach when combined in SSD models is that the assessments of sensitivities to chemical and ionising radiation measured across a range of species in the laboratory can inform on the likely effects on communities present in the field. Potential issues with the validity of this assumption were already recognised by Van Straalen and Denneman (1989) in their landmark paper on the SSD methodology. In this work, they identified eight major factors that could potentially compromise the extrapolation of laboratory toxicity data to the field. Factors covered a range of issues related to differences in chemistry (e.g. bioavailability, mixtures); environmental conditions (optimal, variable), ecological (compensatory, time-scale) and population genetic structure (adaptation, meta-population dynamics). This paper outlines the evidence pertaining to the influence of these different factors on toxicity in the laboratory as compared to the field focussing especially on terrestrial ecosystems. Through radiological and ecotoxicological research, evidence of the influence of each factor on the translation of observed toxicity from the laboratory to field is available in all cases. The importance of some factors, such as differences in chemical bioavailability between laboratory tests and the field and the ubiquity of exposure to mixtures is clearly established and has some relevance to radiological protection. However, other factors such as the differences in test conditions (optimal vs sub-optimal) and the development of tolerance may be relevant on a case by case basis. When SSDs generated from laboratory tests have been used to predict chemical and ionising radiation effects in the field, results have indicated that they may often seem to under-predict impacts, although this may also be due to other factors such as the effects of other non-chemical stressors also affecting communities at polluted sites. A better understanding of the main factors affecting this extrapolation can help to reduce uncertainty during risk assessment.

Dynamic energy budget models in ecological risk assessment: From principles to applications

In ecological risk assessment of chemicals, hazard identification and hazard characterisation are most often based on ecotoxicological tests and expressed as summary statistics such as No Observed Effect Concentrations or Lethal Concentration values and No Effect Concentrations. Considerable research is currently ongoing to further improve methodologies to take into account toxico kinetic aspects in toxicological assessments, extrapolations of toxic effects observed on individuals to population effects and combined effects of multiple chemicals effects. In this context, the principles of the Dynamic Energy Budget (DEB), namely the conserved allocation of energy to different life-supporting processes in a wide variety of different species, have been applied successfully to the development of a number of DEB models. DEB models allow the incorporation of effects on growth, reproduction and survival within one consistent framework. This review aims to discuss the principles of the DEB theory together with available DEB models, databases available and applications in ecological risk assessment of chemicals for a wide range of species and taxa. Future perspectives are also discussed with particular emphasis on ongoing research efforts to develop DEB models as open source tools to further support the research and regulatory community to integrate quantitative biology in ecotoxicological risk assessment.

Pesticide Risks in Small Streams-How to Get as Close as Possible to the Stress Imposed on Aquatic Organisms

The risks associated with pesticides in small streams remain poorly characterized. The challenges reside in understanding the complexities of (1) the highly dynamic concentration profiles of (2) several hundred active substances with (3) differing seasonality. The present study addressed these three challenges simultaneously. Five small streams in catchments under intensive agricultural land use were sampled using half-day composite samples from March to August 2015. Of 213 active substances quantified using liquid chromatography-high resolution mass spectrometry, a total of 128 was detected at least at one of the sites. Ecotoxicological acute and/or chronic quality criteria were exceeded for a total of 32 different active substances. The evaluation of risks over time revealed the necessity to evaluate the sequences of different active substances that are imposed on aquatic organisms. In contrast, a substance-specific perspective provides only a very limited assessment. Scenarios for reduction of either temporal resolution, number of substances or seasonal coverage were defined. It could be shown that risks can be underestimated by more than a factor of 10 in vulnerable catchments and that an increased temporal resolution is essential to cover acute risks but that a focused selection of substances is a possibility to reduce expenditures.

Toxicokinetic models and related tools in environmental risk assessment of chemicals

Environmental risk assessment of chemicals for the protection of ecosystems integrity is a key regulatory and scientific research field which is undergoing constant development in modelling approaches and harmonisation with human risk assessment. This review focuses on state-of-the-art toxicokinetic tools and models that have been applied to terrestrial and aquatic species relevant to environmental risk assessment of chemicals. Both empirical and mechanistic toxicokinetic models are discussed using the results of extensive literature searches together with tools and software for their calibration and an overview of applications in environmental risk assessment. These include simple tools such as one-compartment models, multi-compartment models to physiologically-based toxicokinetic (PBTK) models, mostly available for aquatic species such as fish species and a number of chemical classes including plant protection products, metals, persistent organic pollutants, nanoparticles. Data gaps and further research needs are highlighted.