“AMORE” Decision Support System for probabilistic Ecological Risk Assessment - Part II: Effect assessment of the case study on cyanide
Graphical abstract
Introduction
Ecological Risk Assessment (ERA) is defined as the estimation of both the magnitude and the probability of environmental harm caused by human activities (Barnthouse and Suter II, 1986). ERA can be divided in two main tiers: Screening ERA and site-specific ERA (Critto and Suter II, 2009). The definition of Environmental Quality Criteria (EQC) is included in the context of screening ERA. EQC (or standards) are threshold numerical values that indicate a level beyond which there is a significant risk that the associated environmental quality objective has not been achieved and for which the assessors should adopt actions for the preservation of the ecosystems, including the development of a site-specific risk assessment (EPA, 2005).
The EQC can be derived either through deterministic or probabilistic approaches, with the latter being preferred in the recent advances in the sector as they allow to take into consideration species variability and uncertainty in sensitivity towards chemicals (Gottschalk and Nowack, 2013). The most widely adopted probabilistic approach used for this purpose is the Species Sensitivity Distribution (SSD).
A complete description of SSD is presented in Posthuma et al. (2002) and a detailed critique of SSD is presented in Forbes and Callow (2002) in which the most significant assumptions made in SSD-theory are reported and appraised. Specifically, Forbes and Callow (2002) raised a number of questions regarding the effect of intraspecies variation, proportion of data between the different taxonomic groups and adopted statistical methods in SSD. To tackle these considerations, Duboudin et al. (2004) have introduced the concept of Species Sensitivity Weighted Distributions (SSWD) in which various statistical methods, as well as weights for the ecotoxicological data, are used in the production of SSDs.
In their study, Duboudin et al. (2004) have proposed a weighting coefficient combining two different criteria that allow taking into account: (1) the intraspecies variation in effect response and (2) the taxonomic groups' abundance. Though, this weighting coefficient is neither related with the quality of the assessed data nor with their reliability and relevance for the ecosystem of concern, elements which are considered highly important for the derivation of robust and reliable EQC/S (Duboudin et al., 2004).
The derivation of robust and reliable EQC/S mainly depends on the availability and quality of relevant ecotoxicological data. Ecotoxicological data can be obtained through many different approaches and conditions (e.g., the protocol can be standardised or not; time duration can vary among experiments, leading to chronic or acute data), different physiological endpoints can be observed (e.g. mortality, growth, reproduction and more), statistics used for interpreting data can differ, leading to e.g. NOEC or ECx and more. It is therefore of high interest the analysis of their reliability and relevance that will allow the derivation of more significant and relevant EQ criteria to be adopted in screening ERA, as well as more reliable site-specific ERA.
Several frameworks have been proposed in order to address the issue of the relevance of ecotoxicological data for use in risk assessment processes (Roth and Ciffroy, 2016). Isigonis et al. (2015) have analysed the most important frameworks for the assessment of ecotoxicological data and presented a novel framework, which is based on a Multi-Criteria Decision Analysis (MCDA) - Weight of Evidence (WoE) approach.
This paper aims at presenting and verifying the innovative ‘Effect Assessment’ module of the newly developed software (AMORE DSS) for probabilistic Ecological Risk Assessment. The complete functionalities, architecture and framework of the AMORE DSS are presented in detail in the companion paper (Isigonis et al., 2019). The presented module allows the use of state-of-the-art methodologies for the systematic assessment of quality of ecotoxicological data, the production of reliable weighted data quality SSD graphs (SSD-WDQ) and the estimation of Hazardous Concentrations, in a robust and effective quantitative way, by using derived expert knowledge and modern computerised capabilities. These results are used further in the complete Ecological Risk Assessment process, for the estimation of risk indices of pollutants in aquatic environments, which is presented in the companion paper (Isigonis et al., 2019).
Section snippets
AMORE DSS
The AMORE Decision Support System has been developed as part of the AMORE research project (French National Research Agency project) and consists of three modules which aim in assisting environmental researchers and experts in assessing environmental risks of chemicals in aquatic systems. To this end, it provides a set of tools for analysing and integrating both exposure and effect information (i.e. modelling as well as experimental data). The complexity of the topic outlines the necessity of
Results and discussion
In this study, the MCDA methodology (Isigonis et al., 2015) has been used for the assessment of the available ecotoxicological data and the SSD-WDQ method was applied to the dataset of ecotoxicological data on cyanide, which has been described in paragraph 2.3. Moreover, for comparison purposes, the conventional SSWD (all data equally weighted) was applied to the same set of data. The weighting coefficients used for the production of the SSD-WDQ is the reliability and relevance scores that have
Conclusions
A new methodology has been developed for the assessment of ecotoxicological data, in a quantitative and systematic way and our study demonstrates the feasibility of producing weighted by Data Quality Species Sensitivity Distribution (SSD-WDQ) graphs with the use of the MCDA based methodology.
The analysis of the available ecotoxicological data for the toxicity of common European species, has allowed the production of relevant SSD-WDQ graphs that predict the sensitivity of species and the
Acknowledgements
The authors acknowledge the contribution and support for this study by the French National Research Agency, within the research project AMORE (contract 2009 CESA 15 01).
The authors would like to thank each member of the expert panel for their outstanding contribution to the project: Dr. Agerstrand Marlene, Dr. Andres Sandrine, Dr. Beaugelin Karine, Dr. Bisson Michele, Dr. Casas Stellio, Dr. Cauzzi Nicolas, Dr. Ciffroy Philippe, Dr. Emmanouil Christina, Dr. Geoffroy Laure, Dr. Gilbin Rodolphe,
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A novel fluorescent sensor based on triphenylamine with AIE properties for the highly sensitive detection of CN<sup>−</sup>
2021, Dyes and PigmentsCitation Excerpt :Cyanide and cyanide-containing compounds are currently extensively found in various areas of industrial manufacturing, including paint, electroplating, rubber, herbicides, and so on, causing CN− to reach the organism through the drinkable water system [6–9]. In turn, cyanide is toxic and can cause damage to human health and the ecological environment [10–12]. However, the World Health Organization (WHO) specifies 1.9 × 10−6 mol/L as the permissible acceptable concentration of drinking water [13].