A conceptual framework for landscape-based environmental risk assessment (ERA) of pesticides.

While pesticide use is subject to strict regulatory oversight worldwide, it remains a main concern for environmental protection, including biodiversity conservation. This is partly due to the current regulatory approach that relies on separate assessments for each single pesticide, crop use, and non-target organism group at local scales. Such assessments tend to overlook the combined effects of overall pesticide usage at larger spatial scales. Integrative landscape-based approaches are emerging, enabling the consideration of agricultural management, the environmental characteristics, and the combined effects of pesticides applied in a same or in different crops within an area. These developments offer the opportunity to deliver informative risk predictions relevant for different decision contexts including their connection to larger spatial scales and to combine environmental risks of pesticides, with those from other environmental stressors. We discuss the needs, challenges, opportunities and available tools for implementing landscape-based approaches for prospective and retrospective pesticide Environmental Risk Assessments (ERA). A set of "building blocks" that emerged from the discussions have been integrated into a conceptual framework. The framework includes elements to facilitate its implementation, in particular: flexibility to address the needs of relevant users and stakeholders; means to address the inherent complexity of environmental systems; connections to make use of and integrate data derived from monitoring programs; and options for validation and approaches to facilitate future use in a regulatory context. The conceptual model can be applied to existing ERA methodologies, facilitating its comparability, and highlighting interoperability drivers at landscape level. The benefits of landscape-based pesticide ERA extend beyond regulation. Linking and validating risk predictions with relevant environmental impacts under a solid science-based approach will support the setting of protection goals and the formulation of sustainable agricultural strategies. Moreover, landscape ERA offers a communication tool on realistic pesticide impacts in a multistressors environment for stakeholders and citizens.

Assessing the similarity of nanoforms based on the biodegradation of organic surface treatment chemicals.

A substance may have one or more nanoforms, defined for regulatory purposes under EU chemicals legislation REACH based on differences in physicochemical properties such as size, shape, specific surface area and surface chemistry including coatings. To reduce the burden of testing each unique nanoform for the environmental risk assessment of nanomaterials, grouping approaches allow simultaneous assessment of multiple nanoforms. Nanoforms with initially different intrinsic properties, could still be considered similar if their environmental fate and effects can be demonstrated to be similar. One hypothesis to group nanoforms with different organic surface modifications is to use parameters linked to biodegradation of the organic surface. The hypothesis contends that nanoforms with a similar core chemistry, but different organic surface treatments may be grouped, if the surface treatment is likely to be lost through biodegradation rapidly upon entering an environmental compartment, such that it no longer modulates fate, exposure and toxicity of the nanoform. To implement grouping according to surface treatment biodegradability, a robust approach to measure the breakdown of particle surface treatments is needed. We present a tiered testing strategy to assess the biodegradation of organic surface treatments used with nanomaterials that can be implemented as part of an Integrated Approach to Testing and Assessment (IATA) for grouping based on surface treatment stability. The tiered approach consists of an initial pre-screening MT2 colorimetric carbon substrate utilisation assay, to provide a rapid assessment of coating degradation, and a second tier of testing using OECD Test Guideline 301F for assessing organic chemical biodegradability. Six common surface treatment substances are assessed using the tiered testing strategy to refine rules for escalating between tiers. Similarity assessment using absolute Euclidean distances and x-fold difference concluded that the Tier 1 assessment can be used as conservative binary screening for biodegradability (no false positive results in Tier 1), whilst for substances showing intermediate biodegradation (10-60% in OECD 301F, Tier 2), similarity assessments can be informative for grouping surface treatments not considered readily biodegradable. Further validation using higher tier tests (e.g., mesocosms) is needed to define acceptable limits of similarity between intermediately biodegradable substances, where differences in biodegradability of the surface coating lead to negligible differences in fate, behaviour and toxicity of the nanoforms, and this is critically discussed.

Reproducibility of methods required to identify and characterize nanoforms of substances.

Nanoforms (NFs) of a substance may be distinguished from one another through differences in their physicochemical properties. When registering nanoforms of a substance for assessment under the EU REACH framework, five basic descriptors are required for their identification: composition, surface chemistry, size, specific surface area and shape. To make the risk assessment of similar NFs efficient, a number of grouping frameworks have been proposed, which often require assessment of similarity on individual physicochemical properties as part of the group justification. Similarity assessment requires an understanding of the achievable accuracy of the available methods. It must be demonstrated that measured differences between NFs are greater than the achievable accuracy of the method, to have confidence that the measured differences are indeed real. To estimate the achievable accuracy of a method, we assess the reproducibility of six analytical techniques routinely used to measure these five basic descriptors of nanoforms: inductively coupled plasma mass spectrometry (ICP-MS), Thermogravimetric analysis (TGA), Electrophoretic light scattering (ELS), Brunauer-Emmett-Teller (BET) specific surface area and transmission and scanning electron microscopy (TEM and SEM). Assessment was performed on representative test materials to evaluate the reproducibility of methods on single NFs of substances. The achievable accuracy was defined as the relative standard deviation of reproducibility (RSDR) for each method. Well established methods such as ICP-MS quantification of metal impurities, BET measurements of specific surface area, TEM and SEM for size and shape and ELS for surface potential and isoelectric point, all performed well, with low RSDR, generally between 5 and 20%, with maximal fold differences usually <1.5 fold between laboratories. Applications of technologies such as TGA for measuring water content and putative organic impurities, additives or surface treatments (through loss on ignition), which have a lower technology readiness level, demonstrated poorer reproducibility, but still within 5-fold differences. The expected achievable accuracy of ICP-MS may be estimated for untested analytes using established relationships between concentration and reproducibility, but this is not yet the case for TGA measurements of loss on ignition or water content. The results here demonstrate an approach to estimate the achievable accuracy of a method that should be employed when interpreting differences between NFs on individual physicochemical properties.

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

A number of European countries run large-scale pesticide monitoring schemes in watersheds aimed at identifying and evaluating the presence of pesticide residues in the environment. These schemes provide national and regional scale assessments of pesticide concentrations within the context of environmental quality assessment, aiming to ensure some degree of ecological protection. The present study is aimed at evaluating the joint effects of the pesticide mixtures detected in monitoring programs, using a process-based mixture model that was parameterized for Daphnia magna. In total, over 15 000 samples containing over 1 million individual measurements were evaluated for effects. It was found that there are only a small number of places where one can expect to have effects on daphnids, based on measured concentrations. The most polluted samples would cause extinction of a daphnid population within only 30 h. The results show that effects are mostly triggered by a limited number of pesticide residues at locations with high emissions. It was also shown that the analytical detection limits are basically too high to exclude mixture effects. So, despite all the effort that is put into chemical monitoring programs, it remains a challenge to make statements on whether or not the environment is protected. Recommendations are offered for a different setup of monitoring programs to improve this situation. Environ Toxicol Chem 2016;35:3113-3123. © 2016 SETAC.