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Conceptual Bayesian networks for contaminated site ecological risk assessment and remediation support.

ABSTRACT: The causal pathways of stressors that lead to impacts on individuals, populations, and communities of organisms are useful to know for designing alternatives that manage or remediate ecological risks. The ecological risk assessment (ERA) framework (USEPA, 1998b) can help to identify and prioritize management of risks. One key product of the problem formulation step in an ERA, that captures and represents causal knowledge, is the conceptual site model (CSM). The CSM is a graphical depiction of the risk environment that traces the fate and transport pathways of contaminants from sources of contamination (e.g., a leaking storage tank) to receptors (i.e., the ecological endpoints of concern in the risk assessment). The CSM guides the development of methods for assessing ecological risk scenarios and for remediation design alternatives. The qualitative and quantitative aspects of Bayesian networks may support CSM development and risk characterization. Bayesian networks provide a graphical platform geared toward probabilistic modeling making them important candidates for calculating risks in environmental assessments. The diagrammatic representation of causal Bayesian networks (i.e., the directed acyclic graphs) also adds explanatory depth for developing the evidence-base for risk characterization and remediation interventions. We call these qualitative graphs conceptual Bayesian networks (CBNs). The components of CBNs can be used to represent the variables and relationships between sources of contamination, media transfer, bioaccumulation, and risk. The connections help to compose, piece together, and explore hypothesized relationships that bring about high-risk scenarios. Causal pathway analysis of the CBNs provides visualizations of exposure pathways from initial and intermediate sources to receptors. Remediation options that would interrupt or stop the transport of contaminants to ecological receptors can then be identified. Even if the CBN is not quantified, the structures can support mechanistic and statistical designs for exposure and effects analysis and risk characterization and evaluate information needs for resolving uncertainties. This paper will examine these and other unexplored benefits of CBNs to assessment and management of contaminated sites.

SUBMITTER: Carriger JF

PROVIDER: S-EPMC7736506 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:This study presents data on the detailed evaluation (tier 2) of a site-specific ecological risk assessment (ssERA) in a former smelter area contaminated with metals (Santo Amaro, Bahia, Brazil). Combining information from three lines of evidence (LoE), chemical (ChemLoE), ecotoxicological (EcotoxLoE) and ecological (EcoLoE), in the Triad approach, integrated risk values were calculated to rank sites and confirm the potential risk disclosed with tier 1. Risk values were calculated for the habitat and for the retention functions in each sampling point. Habitat function included the ChemLoE calculated from total metal concentrations. The EcotoxLoE was based on reproduction tests with terrestrial invertebrates (Folsomia candida, Enchytraeus crypticus, Eisenia andrei), shoot length and plant biomass (Avena sativa, Brassica rapa). For the EcoLoE, ecological parameters (microbial parameters, soil invertebrate community, litter breakdown) were used to derive risk values. Retention function included the ChemLoE, calculated from extractable metal concentrations, and the EcotoxLoE based on eluate tests with aquatic organisms (Daphnia magna reproduction and Pseudokirchneriella subcapitata growth). Results related to the habitat function indicated that the metal residues are sufficient to cause risk to biota, while the low metal levels in extracts and the general lack of toxicity in aquatic tests indicated a high soil retention capacity in most sampling points. Integrated risk of tier 2 showed the same trend of tier 1, suggesting the need to proceed with remediation actions. The high risk levels were related to direct toxicity to organisms and indirect effects, such as failure in the establishment of vegetation and the consequent loss of habitat quality for microorganisms and soil fauna. This study shed some light on the selection of tools for the tier 2 of an ssERA in tropical metal-contaminated sites, focusing on ecological receptors at risk and using available chemical methods, ecological surveys and ecotoxicity tests.

Project description:Remediation of mercury (Hg) contaminated sites has long relied on traditional approaches, such as removal and containment/capping. Here we review contemporary practices in the assessment and remediation of industrial-scale Hg contaminated sites and discuss recent advances. Significant improvements have been made in site assessment, including the use of XRF to rapidly identify the spatial extent of contamination, Hg stable isotope fractionation to identify sources and transformation processes, and solid-phase characterization (XAFS) to evaluate Hg forms. The understanding of Hg bioavailability for methylation has been improved by methods such as sequential chemical extractions and porewater measurements, including the use of diffuse gradient in thin-film (DGT) samplers. These approaches have shown varying success in identifying bioavailable Hg fractions and further study and field applications are needed. The downstream accumulation of methylmercury (MeHg) in biota is a concern at many contaminated sites. Identifying the variables limiting/controlling MeHg production-such as bioavailable inorganic Hg, organic carbon, and/or terminal electron acceptors (e.g. sulfate, iron) is critical. Mercury can be released from contaminated sites to the air and water, both of which are influenced by meteorological and hydrological conditions. Mercury mobilized from contaminated sites is predominantly bound to particles, highly correlated with total sediment solids (TSS), and elevated during stormflow. Remediation techniques to address Hg contamination can include the removal or containment of Hg contaminated materials, the application of amendments to reduce mobility and bioavailability, landscape/waterbody manipulations to reduce MeHg production, and food web manipulations through stocking or extirpation to reduce MeHg accumulated in desired species. These approaches often rely on knowledge of the Hg forms/speciation at the site, and utilize physical, chemical, thermal and biological methods to achieve remediation goals. Overall, the complexity of Hg cycling allows many different opportunities to reduce/mitigate impacts, which creates flexibility in determining suitable and logistically feasible remedies.

Project description:A recent advancement in modeling was the development of quantum Bayesian networks (QBNs). QBNs generally differ from BNs by substituting traditional Bayes calculus in probability tables with the quantum amplification wave functions. QBNs can solve a variety of problems which are unsolvable by, or are too complex for, traditional BNs. These include problems with feedback loops and temporal expansions; problems with non-commutative dependencies in which the order of the specification of priors affects the posterior outcomes; problems with intransitive dependencies constituting the circular dominance of the outcomes; problems in which the input variables can affect each other, even if they are not causally linked (entanglement); problems in which there may be >1 dominant probability outcome dependent on small variations in inputs (superpositioning); and problems in which the outcomes are nonintuitive and defy traditional probability calculus (Parrondo's paradox and the violation of the Sure Thing Principle). I present simple examples of these situations illustrating problems in prediction and diagnosis, and I demonstrate how BN solutions are infeasible, or at best require overly-complex latent variable structures. I then argue that many problems in ecology and evolution can be better depicted with ecological QBN (EcoQBN) modeling. The situations that fit these kinds of problems include noncommutative and intransitive ecosystems responding to suites of disturbance regimes with no specific or single climax condition, or that respond differently depending on the specific sequence of the disturbances (priors). Case examples are presented on the evaluation of habitat conditions for a bat species, representing state-transition models of a boreal forest under disturbance, and the entrainment of auditory signals among organisms. I argue that many current ecological analysis structures-such as state-and-transition models, predator-prey dynamics, the evolution of symbiotic relationships, ecological disturbance models, and much more-could greatly benefit from a QBN approach. I conclude by presenting EcoQBNs as a nascent field needing the further development of the quantum mathematical structures and, eventually, adjuncts to existing BN modeling shells or entirely new software programs to facilitate model development and application.

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Conceptual Bayesian networks for contaminated site ecological risk assessment and remediation support.

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