Where do uncertainties reside within environmental risk assessments? Expert opinion on uncertainty distributions for pesticide risks to surface water organisms

Abstract

A reliable characterisation of uncertainties can aid uncertainty identification during environmental risk assessments (ERAs). However, typologies can be implemented inconsistently, causing uncertainties to go unidentified. We present an approach based on nine structured elicitations, in which subject-matter experts, for pesticide risks to surface water organisms, validate and assess three dimensions of uncertainty: its level (the severity of uncertainty, ranging from determinism to ignorance); nature (whether the uncertainty is epistemic or aleatory); and location (the data source or area in which the uncertainty arises). Risk characterisation contains the highest median levels of uncertainty, associated with estimating, aggregating and evaluating the magnitude of risks. Regarding the locations in which uncertainty is manifest, data uncertainty is dominant in problem formulation, exposure assessment and effects assessment. The comprehensive description of uncertainty described will enable risk analysts to prioritise the required phases, groups of tasks, or individual tasks within a risk analysis according to the highest levels of uncertainty, the potential for uncertainty to be reduced or quantified, or the types of location-based uncertainty, thus aiding uncertainty prioritisation during environmental risk assessments. In turn, it is expected to inform investment in uncertainty reduction or targeted risk management action.

Pesticide prioritization approaches and limitations in environmental monitoring studies: From Europe to Latin America and the Caribbean

“…During 2016-2017, prioritization studies on both pharmaceuticals and pesticides have been published (Donnachie et al 2016;Al-Khazrajy and Boxall, 2016;Guo et al 2016;Skinner et al 2016;Casado-Martinez et al, 2018;Gros et al 2017;Tousova et al 2017;Munthe et al 2017). Donnachie et al (2016) group the pharmaceutical prioritization approaches used by environmental scientists into those based on: a) sales and usage, b) occurrence in the environment, c) risk ratio, and d) multiple variables schemes (persistency; bioaccumulation; ecotoxicity; chemical properties; weather conditions).…”

“…In order to manage uncertainty effectively, all the compartments in its dimension should be identified and characterized and actions then implemented to reduce the uncertainty. Skinner at al. (2016) presented a detailed approach, based on subject-matter experts' opinion, to define the sources of uncertainty in pesticide RA.…”

A new risk probability calculation method for urban ecological risk assessment

“…In urban ecosystems, due to the uncertainties of model parameters and input data, the results of model simulation have a large difference from the real value (Refsgaard et al 2007, Skinner et al 2016. In fact, model parameters and independent variables obey their respective probability distributions (van Oijen et al 2011).…”

Big Data Approaches for coastal flood risk assessment and emergency response

“…Inclusion of BN as a BDA derives from an ability to handle missing data, impressive prediction accuracy even with small sample sizes (Kontkanen, Myllymaki, Silander, Tirri, & Grunwald, ), an ability to incorporate domain knowledge alongside quantitative data (Heckerman, Geiger, & Chickering, ) and explicit treatment of uncertainty in a probabilistic sense (Aguilera, Fernández, Fernández, Rumí, & Salmerón, ; Uusitalo, ). The probabilistic set‐up of BNs provides a quantitative approach to dealing with the veracity associated with bringing together such a diverse range of data sources, each of which are accompanied with different types and magnitudes of uncertainty (Skinner, Rocks, & Pollard, ). For example, Bertin et al () report that for storm Xynthia flooding extents were overestimated in some locations and underestimated in others, in part because of wave run‐up and infragravity wave effects.…”