Distributions of Key Exposure Factors Controlling the Uptake of Xenobiotic Chemicals in an Estuarine Food Web

Iannuzzi, Timothy J.; Harrington, Natalie W.; Shear, N.M.; Curry, Cynthia L.; Carlson-Lynch, Heather; Henning, Miranda H.; Su, Steave H.; Rabbe, David E.

doi:10.1897/1551-5028(1996)015<1979:dokefc>2.3.co;2

Cited by 3 publications

(6 citation statements)

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“…Multiparameter alternatives to the simple equilibrium partitioning model have been developed [40–42]. One such model [40] uses fugacity calculations and considers diet, feeding behavior, chemical disequilibrium between sediment and water, and other factors for a total of about 40 input variables.…”

Section: Discussionmentioning

confidence: 99%

“…Uncertainty for these models, based on the 10th to 90th percentile range, was reported as a factor of 3.3 to 5.5 for the Gobas model and 3.3 to 8.7 for the Thomann model. A probabilistic food web model developed by Iannuzzi et al [42] to predict bioaccumulation of xenobiotic chemicals from sediment produced distributional results that were generally within an order of magnitude or less of the range of concentrations of five coplanar PCB congeners measured in organisms from the tidal Passaic River, USA. Uncertainty factors for this model were not reported.…”

Section: Discussionmentioning

confidence: 99%

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Uncertainty analysis for an equilibrium partitioning‐based estimator of polynuclear aromatic hydrocarbon bioaccumulation potential in sediments

Clarke

McFarland

2000

Enviro Toxic and Chemistry

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Abstract-In regulatory evaluations of contaminated sediments, an equilibrium partitioning-based screening test called theoretical bioaccumulation potential (TBP) is often performed to estimate the probable concentrations of neutral organic contaminants that would eventually accumulate in aquatic organisms from continuous exposure to a sediment. The TBP is calculated from contaminant concentration and organic carbon content of the sediment, lipid content of target organisms, and a partition coefficient, usually the biota-sediment accumulation factor (BSAF). However, routine applications of TBP have not included analysis of uncertainty. This paper demonstrates two methods for uncertainty analysis of TBP: a computational method that incorporates random and systematic error and a simulation method using bootstrap resampling of replicated model input parameters to calculate statistical uncertainty measures. For prediction of polynuclear aromatic hydrocarbon (PAH) bioaccumulation in bivalves exposed to contaminated sediments, uncertainty as a factor of TBP ranged from 1.2 to 4.8 using the computational method and 0.5 to 1.9 based on bootstrap 95% confidence intervals. Sensitivity analysis indicated that BSAF parameters, especially tissue contaminant concentration and lipid content, contributed most to TBP uncertainty. In bootstrap tests of significance, TBP significantly over-or underestimated actual PAH bioaccumulation in bivalves in 41% and 10% of comparisons, respectively.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Uncertainty analysis for an equilibrium partitioning‐based estimator of polynuclear aromatic hydrocarbon bioaccumulation potential in sediments

Clarke

McFarland

2000

Enviro Toxic and Chemistry

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“…Mummichogs have limited home and foraging ranges and occupy tidal creeks, coves, and inlets. ( 21,29,30 ) The top‐level predator, summer flounder ( Paralichthys dentatus ), is a piscivorous fish, with adults occupying the top of the aquatic food chain. ( 31,32 )…”

Section: Methodsmentioning

confidence: 99%

“…The model incorporates both sediment and water sources in predicting PCB uptake based on prey consumption, direct water uptake across the gill, and food‐web dynamics. This analysis uses sediment chemistry and 28‐day bioaccumulation test results from New York‐New Jersey Harbor (NY‐NJ) sediments characteristic of dredged sediments proposed for disposal and literature values ( 20,21 ) to develop distributions for input parameters. These input parameters include: sediment and water column concentrations of PCBs, weight and lipid content of aquatic organisms, total organic carbon in sediment, dissolved organic carbon and particulate organic carbon in the water column, and K ow .…”

Section: Introductionmentioning

confidence: 99%

Importance of Uncertainty and Variability to Predicted Risks from Trophic Transfer of PCBs in Dredged Sediments

Stackelberg¹,

Burmistrov²,

Vorhees³

et al. 2002

Risk Analysis

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Biomagnification of organochlorine and other persistent organic contaminants by higher trophic level organisms represents one of the most significant sources of uncertainty and variability in evaluating potential risks associated with disposal of dredged materials. While it is important to distinguish between population variability (e.g., true population heterogeneity in fish weight, and lipid content) and uncertainty (e.g., measurement error), they can be operationally difficult to define separately in probabilistic estimates of human health and ecological risk. We propose a disaggregation of uncertain and variable parameters based on: (1) availability of supporting data; (2) the specific management and regulatory context (in this case, of the U.S. Army Corps of Engineers/U.S. Environmental Protection Agency tiered approach to dredged material management); and (3) professional judgment and experience in conducting probabilistic risk assessments. We describe and quantitatively evaluate several sources of uncertainty and variability in estimating risk to human health from trophic transfer of polychlorinated biphenyls (PCBs) using a case study of sediments obtained from the New York-New Jersey Harbor and being evaluated for disposal at an open water off-shore disposal site within the northeast region. The estimates of PCB concentrations in fish and dietary doses of PCBs to humans ingesting fish are expressed as distributions of values, of which the arithmetic mean or mode represents a particular fractile. The distribution of risk values is obtained using a food chain biomagnification model developed by Gobas by specifying distributions for input parameters disaggregated to represent either uncertainty or variability. Only those sources of uncertainty that could be quantified were included in the analysis. Results for several different two-dimensional Latin Hypercube analyses are provided to evaluate the influence of the uncertain versus variable disaggregation of model parameters. The analysis suggests that variability in human exposure parameters is greater than the uncertainty bounds on any particular fractile, given the described assumptions.

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“…For certain sediment‐associated contaminants, such as heavy organics including PCBs and some pesticides, the processes governing bioaccumulation are well understood based on first principles and have been mathematically well‐defined (Thomann ; Thomann et al ; Gobas ; Arnot and Gobas ). There have been a number of bioaccumulation model reviews (Burkhard ; Imhoff et al ; Barber ) and analyses of sensitivity and uncertainty in trophic transfer (Ianuzzi et al ; von Stackelberg, Burmistrov, Vorhees et al ; Barber ); however, questions remain concerning the ability of these approaches to adequately capture true relationships among sediment and water exposures and resulting tissue concentrations in aquatic food webs (Glaser and Bridges ; Thompson et al ). For example, participants of a Department of Defense workshop (Thompson et al ) identified the “evaluation of food web models in setting remedial goals and long term monitoring requirements” as a critical research area given these food web models represent a critical component of decision making at sediment contaminated sites (Gustavson et al ).…”

Section: Introductionmentioning

confidence: 99%

Spatially explicit bioaccumulation modeling in aquatic environments: Results from 2 demonstration sites

Stackelberg¹,

Williams

Clough³

et al. 2017

Integr Envir Assess & Manag

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Bioaccumulation models quantify the relationship between sediment and water exposure concentrations and resulting tissue levels of chemicals in aquatic organisms and represent a key link in the suite of tools used to support decision making at contaminated sediment sites. Predicted concentrations in the aquatic food web provide exposure estimates for human health and ecological risk assessments, which, in turn, provide risk-based frameworks for evaluating potential remedial activities and other management alternatives based on the fish consumption pathway. Despite the widespread use of bioaccumulation models to support remedial decision making, concerns remain about the predictive power of these models. A review of the available literature finds the increased mathematical complexity of typical bioaccumulation model applications is not matched by the deterministic exposure concentrations used to drive the models. We tested a spatially explicit exposure model (FishRand) at 2 nominally contaminated sites and compared results to estimates of bioaccumulation based on conventional, nonspatial techniques, and monitoring data. Differences in predicted fish tissue concentrations across applications were evident, although these demonstration sites were only mildly contaminated and would not warrant management actions on the basis of fish consumption. Nonetheless, predicted tissue concentrations based on the spatially explicit exposure characterization consistently outperformed conventional, nonspatial techniques across a variety of model performance metrics. These results demonstrate the improved predictive power as well as greater flexibility in evaluating the impacts of food web exposure and fish foraging behavior in a heterogeneous exposure environment. Integr Environ Assess Manag 2017;13:1023-1037. © 2017 SETAC.

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Distributions of Key Exposure Factors Controlling the Uptake of Xenobiotic Chemicals in an Estuarine Food Web

Cited by 3 publications

References 0 publications

Uncertainty analysis for an equilibrium partitioning‐based estimator of polynuclear aromatic hydrocarbon bioaccumulation potential in sediments

Uncertainty analysis for an equilibrium partitioning‐based estimator of polynuclear aromatic hydrocarbon bioaccumulation potential in sediments

Importance of Uncertainty and Variability to Predicted Risks from Trophic Transfer of PCBs in Dredged Sediments

Spatially explicit bioaccumulation modeling in aquatic environments: Results from 2 demonstration sites

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