Dataset Information

Ecological Risk Assessment of a Metal-Contaminated Area in the Tropics. Tier II: Detailed Assessment.

ABSTRACT: 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.

SUBMITTER: Niemeyer JC

PROVIDER: S-EPMC4631348 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Ecological Risk Assessment of a Metal-Contaminated Area in the Tropics. Tier II: Detailed Assessment.

Niemeyer Júlia Carina JC Moreira-Santos Matilde M Ribeiro Rui R Rutgers Michiel M Nogueira Marco Antonio MA da Silva Eduardo Mendes EM Sousa José Paulo JP

PloS one 20151103 11

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 ...[more]

PMID: 26528915

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Project description:BackgroundIncreased growth of industrial activities, especially in urban centers, is one of the main sources of toxic substances in Nigeria. The level of these impacts is not well known. Soil and sediment samples from one such industrial area were examined for their mineralogical composition and heavy metals contents in order to assess the level of contamination and potential ecological risk status.MethodsMineralogical composition of the media and their heavy metals concentrations were determined using X-ray diffractometry and inductively coupled plasma-mass spectrometry methods, respectively. Ecological risk assessment was carried out using single (contamination factor, geo-accumulation index, enrichment factor) and multi-elemental (contamination degree, pollution index and modified pollution index) standard indices.ResultsThe average heavy metal concentrations in soils and sediments followed the order magnesium (Mn) > chromium (Cr) > lead (Pb) > copper (Cu) > cadmium (Cd) > cobalt (Co) > nickel (Ni), with corresponding values for soils and sediments of 324.3, 79.9, 66.1, 40.7, 14.3, 9.1, 6.8 mg kg-1 and 266.8, 78.6, 40.6, 39.8, 12.9, 8.4, 4.6 mg kg-1, respectively. Principal component (PC) analysis of the results indicated three main sources of metals (industrial, vehicular activities and geogenic input). Evaluated contamination factor (Cf), enrichment factor (Ef) and geo-accumulation index (Igeo) revealed very high contamination for Pb, Cd and Cu in all of the samples, with calculated pollution index (PI) and modified pollution index (MPI) revealing that all the samples were severely polluted. Calculated potential ecological risk factor (ERi) within the industrial area demonstrated a strong potential ecological risk for Cd, Pb and Cu.ConclusionsActivities in the industrial area have affected the quality of the analyzed environmental media, with possible detrimental health consequences. Regular environmental monitoring of the industrial area and the formulation of appropriate policies that support reduction of contamination are strongly recommended. However, due to the limitations of comparing site samples with a single control sample in this work, further study is recommended to compliment this preliminary study.Competing interestsThe authors declare no competing financial interests.

Project description: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.

Project description:Stoffenmanager®v4.5 and Advanced REACH Tool (ART) v1.5, two higher tier exposure assessment tools for use under REACH, were evaluated by determining accuracy and robustness. A total of 282 exposure measurements from 51 exposure situations (ESs) were collected and categorized by exposure category. In this study, only the results of liquids with vapor pressure (VP) > 10 Pa category having a sufficient number of exposure measurements (n = 251 with 42 ESs) were utilized. In addition, the results were presented by handling/activity description and input parameters for the same exposure category. It should be noted that the performance results of Stoffenmanager and ART in this study cannot be directly compared for some ESs because ART allows a combination of up to four subtasks (and nonexposed periods) to be included, whereas the database for Stoffenmanager, separately developed under the permission of the legal owner of Stoffenmanager, permits the use of only one task to predict exposure estimates. Thus, it would be most appropriate to compare full-shift measurements against ART predictions (full shift including nonexposed periods) and task-based measurements against task-based Stoffenmanager predictions. For liquids with VP > 10 Pa category, Stoffenmanager®v4.5 appeared to be reasonably accurate and robust when predicting exposures [percentage of measurements exceeding the tool's 90th percentile estimate (%M > T) was 15%]. Areas that could potentially be improved include ESs involving the task of handling of liquids on large surfaces or large work pieces, allocation of high and medium VP inputs, and absence of local exhaust ventilation input. Although the ART's median predictions appeared to be reasonably accurate for liquids with VP > 10 Pa, the %M > T for the 90th percentile estimates was 41%, indicating that variance in exposure levels is underestimated by ART. The %M > T using the estimates of the upper value of 90% confidence interval (CI) of the 90th percentile estimate (UCI90) was considerably reduced to 18% for liquids with VP > 10 Pa. On the basis of this observation, users might be to consider using the upper limit value of 90% CI of the 90th percentile estimate for predicting reasonable worst case situations. Nevertheless, for some activities and input parameters, ART still shows areas to be improved. Hence, it is suggested that ART developers review the assumptions in relation to exposure variability within the tool, toward improving the tool performance in estimating percentile exposure levels. In addition, for both tools, only some handling/activity descriptions and input parameters were considered. Thus, further validation studies are still necessary.

Dataset Information

Ecological Risk Assessment of a Metal-Contaminated Area in the Tropics. Tier II: Detailed Assessment.

Publications

Ecological Risk Assessment of a Metal-Contaminated Area in the Tropics. Tier II: Detailed Assessment.

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