How to confirm identified toxicants in effect-directed analysis. Anal Bioanal Chem
Department Effect-Directed Analysis, UFZ Helmholtz Centre for Environmental Research, Leipzig, Germany. Analytical and Bioanalytical Chemistry
(Impact Factor: 3.44).
05/2008; 390(8):1959-73. DOI: 10.1007/s00216-007-1808-8
Due to the production and use of a multitude of chemicals in modern society, waters, sediments, soils and biota may be contaminated with numerous known and unknown chemicals that may cause adverse effects on ecosystems and human health. Effect-directed analysis (EDA), combining biotesting, fractionation and chemical analysis, helps to identify hazardous compounds in complex environmental mixtures. Confirmation of tentatively identified toxicants will help to avoid artefacts and to establish reliable cause-effect relationships. A tiered approach to confirmation is suggested in the present paper. The first tier focuses on the analytical confirmation of tentatively identified structures. If straightforward confirmation with neat standards for GC-MS or LC-MS is not available, it is suggested that a lines-of-evidence approach is used that combines spectral library information with computer-based structure generation and prediction of retention behaviour in different chromatographic systems using quantitative structure-retention relationships (QSRR). In the second tier, the identified toxicants need to be confirmed as being the cause of the measured effects. Candidate components of toxic fractions may be selected based, for example, on structural alerts. Quantitative effect confirmation is based on joint effect models. Joint effect prediction on the basis of full concentration-response plots and careful selection of the appropriate model are suggested as a means to improve confirmation quality. Confirmation according to the Toxicity Identification Evaluation (TIE) concept of the US EPA and novel tools of hazard identification help to confirm the relevance of identified compounds to populations and communities under realistic exposure conditions. Promising tools include bioavailability-directed extraction and dosing techniques, biomarker approaches and the concept of pollution-induced community tolerance (PICT). [figure: see text]
Available from: Annette Bérard
- "Following the detection of PICT to mixtures, further examination of tolerance to a single or group of chemicals (e.g. sharing specific modes of action) that have been identified as having the highest toxic unit in the mixture by tools like effect-directed analysis (Brack et al., 2008) might allow identification of the specific chemical causing community change (Fig. 3). "
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ABSTRACT: A major challenge in environmental risk assessment of pollutants is establishing a causal relationship between field exposure and community effects that integrates both structural and functional complexity within ecosystems.Pollution-induced community tolerance (PICT) is a concept that evaluates whether pollutants have exerted a selection pressure on natural communities. PICT detects whether a pollutant has eliminated sensitive species from a community and thereby increased its tolerance. PICT has the potential to link assessments of the ecological and chemical status of ecosystems by providing causal analysis for effect-based monitoring of impacted field sites.Using PICT measurements and microbial community endpoints in environmental assessment schemes could give more ecological relevance to the tools that are now used in environmental risk assessment. Here, we propose practical guidance and a list of research issues that should be further considered to apply the PICT concept in the field.
Freshwater Biology 04/2015; DOI:10.1111/fwb.12558 · 2.74 Impact Factor
Available from: Lulu Zhang
- "Chemical analysis of environmental matrices is the most direct approach to reveal the heavy metal pollution status in the environmental compartments, but this technique with many disadvantages, such as cannot provide meaningful information regarding the possible toxicity to organisms and ecosystems (Zhou et al., 2008a,b), and not feasible when intensive and large scale samplings are needed (Blasco and Picó, 2009). Under such circumstances, a chemicaldriven strategy for assessing the ecological risk from pollutants based on a combination of both biological responses and chemical data is necessary to explore and to develop new risk assessment strategies (Rodriguez-Mozaz et al., 2006; Gonzalez-Martinez et al., 2007; Brack et al., 2008; Fernandez et al., 2009; Ginebreda et al., 2010; Pesce et al., 2010). Compared with conventional physical and chemical analyses of the aquatic environment, biomonitoring exhibits some advantages, including high sensitivity, high integration, and wide practicability (Zhou et al., 2008a,b). "
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ABSTRACT: With the aim of evaluating and comparing the correlation relationship between metal pollution and benthic structural and functional metrics, we carried out samplings of three anthropogenic disturbance levels at eight sites located in the Lake Baiyangdian that are strongly influenced by wastewater discharge (Sites 1 and 2), aquaculture and densely populated villages (Sites 3, 6, and 8), and the least human disturbances (Sites 4, 5, and 7). Benthic communities were studied in eight sample sites, and Cu, Ni, Pb, Zn, Hg, Cd, and Cr were simultaneously determined. The potential ecological risk index (RI) was calculated by Hakanson's methodology. The results showed that the RI for all three habitats was lower than 94, and they are in decreasing order: Habitat 1, Habitat 2, and Habitat 3. When the three sampling seasons were compared, August appeared to show the highest risk, followed by April and November. For the periphyton metrics, the best correlation was detected between chlorophyll c/chlorophyll a (Chl c/a) ratio and Eri Hg (r = −0.851, p < 0.01); for the benthic macroinvertebrate metrics, the best correlation was established between Eri Hg and community similarity index (CSI) (r = −0.983, p < 0.01). When periphyton and benthic macroinvertebrate metrics were compared, benthic macroinvertebrate metrics appeared to be more sensitive, especially the metrics of number of diptera taxa (NDT), community loss index (CLI), and CSI. Our results suggest that the benthic community would be used in biomonitoring for heavy metal pollution in the Lake Baiyangdian, China.
Ecological Indicators 05/2014; 40:162–174. DOI:10.1016/j.ecolind.2014.01.021 · 3.44 Impact Factor
Available from: Lulu Zhang
- "explore and to develop new risk assessment strategies (Rodriguez-Mozaz et al. 2006; Gonzalez-Martinez et al. 2007; Brack et al. 2008; Fernandez et al. 2009; Ginebreda et al. 2010; Pesce et al. 2010). Compared with conventional physical and chemical analyses of the aquatic environment, bio-monitoring exhibits some obvious advantages, including high sensitivity , high integration, and wide practicability (Zhou et al. 2008). "
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ABSTRACT: Heavy metals may adversely affect the structure and function of the periphyton community in lake ecosystems. We carried out samplings of three habitats at eight sites located in the Lake Baiyangdian that is strongly influenced by wastewater discharge (Sites 1 and 2), aquaculture and densely populated villages (Sites 3, 6, and 8), and the least disturbed (Sites 4, 5, and 7). Cu, Ni, Pb, Zn, Hg, Cd, and Cr were determined in these samples, and the periphyton community was simultaneously studied. The contamination factor (C f (i) ) was estimated for every metal as the ratio between pre-industrial records from sediments (C n (i) ) and present concentration values (C (i) ), and the individual potential risk (E r (i) ) was calculated by multiply the toxic response factor (Tr (i) ) and C f (i) for a given substance were based on Hakanson's methodology. The RI was obtained for each sampling site by summing the values of E r (i) first and the average was calculated across the sampling sites. The results showed that the RI for all three habitats was lower than 94, and they are in decreasing order: wastewater discharge, aquaculture and densely populated villages, and the least anthropogenic impacted. When the three sampling seasons were compared, August appeared to show the highest risk, followed by April and November. The RI values showed negative correlations (r = -0.444 to -0.851, p < 0.05) with the structural and functional metrics. The best correlation was detected between chlorophyll c/chlorophyll a (Chl c/a) ratio and E r (i) Hg (r = -0.851, p < 0.01). Our results suggest the periphyton community can be used in bio-monitoring.
Ecotoxicology 02/2014; 23(4). DOI:10.1007/s10646-014-1175-0 · 2.71 Impact Factor
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