Assessing Risks to Sea Otters and the Exxon Valdez Oil Spill: New Scenarios,Attributable Risk,and Recovery

The Exxon Valdez oil spill occurred more than two decades ago, and the Prince William Sound ecosystem has essentially recovered. Nevertheless, discussion continues on whether or not localized effects persist on sea otters (Enhydra lutris) at northern Knight Island (NKI) and, if so, what are the associated attributable risks. A recent study estimated new rates of sea otter encounters with subsurface oil residues (SSOR) from the oil spill. We previously demonstrated that a potential pathway existed for exposures to polycyclic aromatic hydrocarbons (PAHs) and conducted a quantitative ecological risk assessment using an individual-based model that simulated this and other plausible exposure pathways. Here we quantitatively update the potential for this exposure pathway to constitute an ongoing risk to sea otters using the new estimates of SSOR encounters. Our conservative model predicted that the assimilated doses of PAHs to the 1-in-1000th most-exposed sea otters would remain 1–2 orders of magnitude below the chronic effects thresholds. We re-examine the baseline estimates, post-spill surveys, recovery status, and attributable risks for this subpopulation. We conclude that the new estimated frequencies of encountering SSOR do not constitute a plausible risk for sea otters at NKI and these sea otters have fully recovered from the oil spill.     

Assessing the Risk of Hydroxybenzene Contamination in Fish Raised on a Chinese Aquaculture Farm

We estimated the risk posed by hydroxybenzene in farm-raised Crucian carps (Carassius carassius) from a pond on a fish farm in Beijing, China, by analyzing a time-series of observed hydroxybenzene concentrations in fish within a culturing season in year 2006. We used the basic linear regression to model the data and forecast the probability of hydroxybenzene concentration in pond fish exceeding selected health effect criteria (the risk) using Monte Carlo simulation. The risk is highly correlated with the time a fish stays in the pond. The results indicate that the risk–days in pond relationship resembles a sigmoid function with an inflection point around 150 days. The resulting model can be used to demonstrate the benefit of improving water quality in terms of increased fish production.     

Evaluating Risks to Terrestrial Wildlife from Environmental Fluoride

Information and approaches to evaluating health risks to terrestrial wildlife from fluoride contamination in the environment are few in the literature. We use environmental field data from a phosphate ore processing site, toxicity reference values (TRVs), and bioaccumulation factors relative to site conditions to develop risk-based concentrations (RBCs) for total fluoride in terrestrial biota and soil. RBCs were derived specifically for forage that are protective of terrestrial mammalian and avian ecological receptors through multiple exposure pathways, and which can be used to evaluate site remediation or as environmental monitoring action levels. Following review of the literature, we recommend fluoride TRVs for mammalian and avian wildlife, and bioavailability factors for estimating exposures related to aerial deposition of fluoride and fluoride gases. For large ungulates, information on fluoride bioavailability from feed and soil, and related effects thresholds, are summarized from studies on grazing livestock. The resultant RBCs for fluoride in forage range from 14 to 63 mg/kg dry weight, based on no-effect and low-effect concentrations, respectively. These concentrations bracket most state, provincial, and international regulatory standards of vegetation levels for protection of livestock and wildlife.     

A Simulation-Assessment Modeling Approach for Analyzing Environmental Risks of Groundwater Contamination at Waste Landfill Sites

An integrated simulation-assessment modeling approach for analyzing environmental risks of groundwater contamination is proposed in this paper. It incorporates an analytical groundwater solute transport model, an exposure dose model, and a fuzzy risk assessment model within a general framework. The transport model is used for predicting contaminant concentrations in subsurface, and the exposure dose model is used for calculating contaminant ingestion during the exposure period under given exposure pathways. Both models are solved through the Monte Carlo simulation technique to reflect the associated uncertainties. Based on consideration of fuzzy relationships between exposure doses and cancer risks, risk levels of different exposure doses for each contaminant can be calculated to form a fuzzy relation matrix. The overall risks can then be quantified through further fuzzy synthesizing operations. Thus, probabilistic quantification of different risk levels (possibilities) can be realized. Results of the case study indicate that environmental risks at the waste landfill site can be effectively analyzed through the developed methodology. They are useful for supporting the related risk-management and remediation decisions.     

A Quantitative Ecological Risk Assessment of the Toxicological Risks from Exxon Valdez Subsurface Oil Residues to Sea Otters at Northern Knight Island,Prince William Sound,Alaska

A comprehensive, quantitative risk assessment is presented of the toxicological risks from buried Exxon Valdez subsurface oil residues (SSOR) to a subpopulation of sea otters (Enhydra lutris) at Northern Knight Island (NKI) in Prince William Sound, Alaska, as it has been asserted that this subpopulation of sea otters may be experiencing adverse effects from the SSOR. The central questions in this study are: could the risk to NKI sea otters from exposure to polycyclic aromatic hydrocarbons (PAHs) in SSOR, as characterized in 2001–2003, result in individual health effects, and, if so, could that exposure cause subpopulation-level effects? We follow the U.S. Environmental Protection Agency (USEPA) risk paradigm by: (a) identifying potential routes of exposure to PAHs from SSOR; (b) developing a quantitative simulation model of exposures using the best available scientific information; (c) developing scenarios based on calculated probabilities of sea otter exposures to SSOR; (d) simulating exposures for 500,000 modeled sea otters and extracting the 99.9% quantile most highly exposed individuals; and (e) comparing projected exposures to chronic toxicity reference values. Results indicate that, even under conservative assumptions in the model, maximum-exposed sea otters would not receive a dose of PAHs sufficient to cause any health effects; consequently, no plausible toxicological risk exists from SSOR to the sea otter subpopulation at NKI.     

A New Version of the Insertion Particle Method for Determining the Chemical Potential by Monte Carlo Simulation

A new version of the test particle method for determining the chemical potential by Monte Carlo simulations is proposed. The method, applicable to any fluid at any density, combines the Widom's test particle insertion method with the ideas of the scaled particle theory, gradual insertion method and multistage sampling. Its applicability is exemplified by evaluating the chemical potential of the hard sphere fluid at a very high density in semi-grand-canonical and grand-canonical ensembles. A theory estimating the efficiency (i.e. statistical errors) of the method is proposed and the results are compared with the Widom's and gradual insertion methods, and the analytic results.     

Practical Issues in the Use of Probabilistic Risk Assessment

Probabilistic risk assessment (PRA) represents an important step in the evolution of risk assessment methodology to assist decision-making at hazardous waste sites. Despite considerable progress in the development of PRA techniques, regulatory acceptance of PRA has been limited, in part because a number of practical issues in its use must yet be resolved. A recent workshop on PRA identified several areas to be addressed, including the need for: (1) better demonstration of the value of PRA in risk management; (2) PRA training and education opportunities; (3) the development of technical criteria for acceptability of a PRA; (4) policy decisions on acceptable risk distributions; (5) ways to deal with risk communication issues; and (6) a variety of technical issues, including ways to include estimates of variability and uncertainty associated with toxicity values. Solutions to many of these issues will require better dialog between risk assessors and risk managers than has existed in the past.     

Test of the Inverse Monte Carlo Method for the Calculation of Interatomic Potential Energies in Atomic Liquids

Abstract

The principle purpose of this paper is to demonstrate the use of the Inverse Monte Carlo technique for calculating pair interaction energies in monoatomic liquids from a given equilibrium property. This method is based on the mathematical relation between transition probability and pair potential given by the fundamental equation of the “importance sampling” Monte Carlo method. In order to have well defined conditions for the test of the Inverse Monte Carlo method a Metropolis Monte Carlo simulation of a Lennard Jones liquid is carried out to give the equilibrium pair correlation function determined by the assumed potential. Because an equilibrium configuration is prerequisite for an Inverse Monte Carlo simulation a model system is generated reproducing the pair correlation function, which has been calculated by the Metropolis Monte Carlo simulation and therefore representing the system in thermal equilibrium. This configuration is used to simulate virtual atom displacements. The resulting changes in atom distribution for each single simulation step are inserted in a set of non-linear equations defining the transition probability for the virtual change of configuration. The solution of the set of equations for pair interaction energies yields the Lennard Jones potential by which the equilibrium configuration has been determined.     

Human Exposure to Malathion during a Possible Vector-Control Intervention against West Nile Virus. II: Evaluation of the Toxicological Risks Using a Probabilistic Approach

In order to prevent the propagation of West Nile Virus (WNV), insecticide sprayings have been carried out in several locations in North America since 1999 with the objective of controlling the mosquito populations that transmit this pathogen. An attempt to quantitatively compare the risk of developing a health response to WNV infection with the toxicological risk of insecticides is presented here. First, the acute and subchronic environmental concentrations resulting from repeated spraying events were modeled according to a reasonable worst-case spraying sequence established in an intervention program proposed by the Government of Quebec (Canada). Second, probability density functions (PDF) were established for some exposure parameters according to the data for the concerned population, when feasible. Monte Carlo analyses were performed by incorporating these PDF into the equations used to calculate the daily absorbed doses resulting from the exposure scenarios presented in the companion article (this issue). The results showed that for a significant proportion of the population, aerial and, to a lesser extent, ground sprayings of malathion can generate acute and subchronic exposure that may exceed some levels of toxicological concern based on the USEPA's reference values. Indeed, in the case of acute exposure following aerial spraying for infants, toddlers, and children, these proportions were respectively 37.1%, 59.5%, and 32.8% of the individuals, and 27.3%, 41.3%, and 24.9% following subchronic exposure. For ground spraying, these values were 12.5%, 24.2%, 8.8%; and 9.8%, 16.5%, and 7.4%. These results allowed the comparison of the probability of exceeding a level of toxicological concern for malathion exposure with the probability of developing WNV symptoms. This comparison shows that in some circumstances, the toxicological risk of malathion may exceed the infectious risk of WNV.     

Probability Density Functions Describing 24-Hour Inhalation Rates For Use in Human Health Risk Assessments

A Monte Carlo simulation was undertaken to estimate the amount of air inhaled over a typical 24-hour period by six age groups of Canadians. The objective of the simulation was to derive probability density functions that could be used to describe inhalation rates in probabilistic health risk assessments involving airborne contaminants. The six age groups considered were those typically employed in human health risk assessments in Canada: infants (aged 0 to 6 months), toddlers (aged 7 months to 4 years), children (aged 5 to 11 years), teenagers (aged 12 to 19 years), adults (aged 20 to 59 years), and seniors (aged 60 years and older). The resulting distributions are considered equally applicable to Americans as Canadians, however, since the study relied heavily on time-activity information gathered in the USA. Existing time-activity and breathing rate studies were reviewed in order to define random variables describing probable durations that North Americans spend at various levels of activity and their probable inhalation rates while at each level of activity. These random variables were combined in a Monte Carlo simulation to empirically generate probability density functions describing 24-hour inhalation rates for each age group. The simulation suggested that most age groups' 24 hour inhalation rates can be represented with log-normal probability density functions. Arithmetic mean values and standard deviations for these distributions are as follows: approximately 9.3 ± 2.4?m³/day for toddlers; 14.6 ± 3.0?m³/day for children; 15.8 ± 3.7?m³/day for teenagers; 16.2 ± 3.8?m³/day for adults; and 14.2 ± 3.3?m³/day for seniors. The distribution of infants' 24-hour inhalation rates was found to be better represented by a normal distribution than a log-normal distribution. The mean and standard deviation for the infants' normal distribution are 2.1 ± 0.58?m³/day. Inhalation rates were also estimated separately for male and female toddlers, children, teenagers, adults and seniors. These estimates suggested that males inhale on average 8% to 27% more air than females of the same age. Because infants' activity patterns and minute volumes did not appear to be strongly correlated with gender, a single probability density function was deemed satisfactory to describe male and female infants' 24-hour inhalation rates.     

Using Asymmetrical Designs for Environmental Impact Assessment of Unplanned Disturbances

Environmental impact assessment of unplanned disturbances is often difficult to accomplish due to the absence of ‘before’ data for the impacted sites. In an attempt to overcome this problem, a beyond BACI model is used in order to detect possible changes in the temporal patterns of variation when no previous data are available. The model attempted to detect changes in the abundance of macroinvertebrate species inhabiting the intertidal mussel matrix after an oil spill which occurred in northern Portugal. The detection of a significant impact failed, most probably due to low temporal replication. An extension of the analysis, including the hierarchical arrangement of temporal variability in periods, suggests that increasing the number of sampling times may result in a higher efficiency of the model.     

Health Risk Assessments Based on Existing Data of Arsenic,Chromium, Lead,and Zinc in China's Air

Health risk assessments of As, Cr, Pb, and Zn in air in China were carried out from a national perspective. Concentrations of the four metals in air were gathered from published literature. Health risk assessment models recommended by the U.S. Environmental Protection Agency (USEPA) were applied to quantitatively characterize risk values of the metals by considering different age groups. Results showed that the atmospheric metal concentrations in most regions of China were lower than their inhalation reference concentrations provided by the USEPA, or limited values provided by China. Non-carcinogenic hazard values of the four metals in different regions of China were all lower than 1, indicating no or low non-carcinogenic hazard. However, the probabilities of carcinogenic risk values for As and Cr exceeding the acceptable value (1.0E-05) were 9% and 10% on a national scale, respectively. Some regions, such as Shanxi, Chongqing, Liaoning, and Shanghai, should be studied in more detail. Despite uncertainties, the results of this study provide information on the health risk of As, Cr, Pb, and Zn in air in China.     

Mathematical properties of the risk equation when variability is present

When random variables are used to represent variability, the risk equation has mathematical properties poorly understood by many risk assessors, variability represents the heterogeneity in a well‐characterized population, usually not reducible through further measurement or study. We follow the lead of most mathematicians in using random variables to represent and analyze variability. To illustrate the issues, we use LogNormal distributions to model variability.     

Developing Univariate Distributions from Data for Risk Analysis

The importance of fitting distributions to data for risk analysis continues to grow as regulatory agencies, like the Environmental Protection Agency (EPA), continue to shift from deterministic to probabilistic risk assessment techniques. The use of Monte Carlo simulation as a tool for propagating variability and uncertainty in risk requires specification of the risk model's inputs in the form of distributions or tables of data. Several software tools exist to support risk assessors in their efforts to develop distributions. However, users must keep in mind that these tools do not replace clear thought about judgments that must be made in characterizing the information from data. This overview introduces risk assessors to the statistical concepts and physical reasons that support important judgments about appropriate types of parametric distributions and goodness-of-fit. In the context of using data to improve risk assessment and ultimately risk management, this paper discusses issues related to the nature of the data (representativeness, quantity, and quality, correlation with space and time, and distinguishing between variability and uncertainty for a set of data), and matching data and distributions appropriately. All data analysis (whether “Frequentist” or “Bayesian” or oblivious to the distinction) requires the use of subjective judgment. The paper offers an iterative process for developing distributions using data to characterize variability and uncertainty for inputs to risk models that provides incentives for collecting better information when the value of information exceeds its cost. Risk analysts need to focus attention on characterizing the information appropriately for purposes of the risk assessment (and risk management questions at hand), not on characterization for its own sake.     

Risk Posed by Pesticides to Aquatic Organisms in Rivers of Northern Inland New South Wales,Australia

An ecological assessment was conducted to determine the risk posed by agricultural pesticides to inland rivers of north-west New South Wales (NSW), Australia. A preliminary screening of 30 pesticides provided a short-list of eight for further investigation (atrazine, chlorpyrifos, diuron, endosulfan, fluometuron, metolachlor, profenofos, prometryn). Selection was based on chemical characteristics, toxicity, detection frequencies and environmental concentrations. Hazard quotients were calculated for both spray and non-spray seasons. Where possible, hazard quotients were calculated for both acute and chronic exposures for crustaceans, insects, micro-organisms, molluscs, plants and vertebrates. Chlorpyrifos, endosulfan and profenofos posed a high hazard (HQ > 0.5). A probabilistic risk analysis indicated that chlorpyrifos, endosulfan and profenofos posed a risk from acute exposure during the spray season, while endosulfan also posed a risk from chronic exposure during the spray season. The risks posed by profenofos and chlorpyrifos were characterised by a low probability of detection, but these detections affected a high percentage of species. The risks posed by acute and chronic exposures of endosulfan were characterised by a high probability of detection, but only a limited number of these detections affected a high percentage of species. Risk during the non-spray season was not assessed, as the detection of pesticides was infrequent during this period.     

An Ecological Risk Assessment Methodology for Screening Discharge Alternatives of Produced Water

Previous studies on Ecological Risk Assessment (ERA) of produced water relied on the use of deterministic hydrodynamic models. The assessment was usually carried out in the North Sea context using a model such as the Chemical Hazard Assessment and Risk Management (CHARM), or in the North American context based on the output of a hydrodynamic model such as the Cornell Mixing Zone Expert System (CORMIX). In both these cases, however, probabilistic analysis has not been employed, particularly, to account for uncertainty associated with hydrodynamic models in the ERA study. In fact, it is the hydrodynamic model that has a direct linkage to the selection of the discharge alternatives. Apart from the monitoring purposes, in this article, it is suggested that criteria for evaluating discharge alternatives of produced water in a marine environment might incorporate an awareness of ecological risks by incorporating engineering and toxicological aspects. An ERA methodology consisting of problem formulation, analysis, and risk characterization is discussed in light of evaluating the discharge alternatives. A probabilistic analysis using Latin Hypercube Sampling (LHS)–based Monte Carlo (MC) simulations was employed. A depiction of associated risks for an area comparable to a regulatory mixing zone of typical effluent discharges is presented.     

Ecological Risk Assessment of DDT Accumulation in Aquatic Organisms of Taihu Lake,China

DDT (Dichlorophenyltrichloroethane) is a toxic, ubiquitous, and persistent bioaccumulative pollutant in the global environment. Although its use as an insecticide has been banned in China since 1983, residual DDT levels in the Taihu Lake are evident. Aimed at the protection of fish resources, three species of high-value fish in the Taihu Lake (Protosalanx hylocranius (Abbott), Salangichthys tangkahkeii (Wu), and Coilia nasus Temminck et Schlegel) were selected and an ecological risk assessment was used to estimate the DDT threats to fish populations. Based on a food web model, a bioaccumulation model was used to estimate the DDT concentration in zooplankton, benthos, and fish and the Monte Carlo (MC) simulation method was used to analyze the uncertainty in the bioaccumulation process. Then the chronic toxicity dose-response relationship of DDT on the Protosalanx hyalocranius (Abbott) population, estimated by ICE and ACE software, was used to calculate the mortality rates in different fish stages with the DDT concentrations. Last, the demographic modeling (Leslie matrix) was used to assess the ecological risk of DDT damage on the Protosalanx hyalocranius (Abbott) population. The results show that the estimated DDT concentrations in benthos and zooplankton were 0.14–16.56 μ g/kg, 2.15–99.30 μ g/kg, respectively. The fish DDT concentration results are a series of increasing curves and the maximal values reach 266, 101, and 211 μ g/kg for Protosalanx hylocranius (Abbott), Salangichthys tangkahkeii (Wu), and Coilia nasus Temminck et Schlegel, respectively. In the process of ecological risk quantization, a 4.06–7.25% reduction in the biomass of the Protosalanx hyalocranius (Abbott) population was estimated in 10,000 MC imulations and 4.21%, 4.89%, and 5.69% reductions were estimated in 75%, 50%, and 25% probability, respectively.