Guide for developing data quality objectives for ecological risk assessment at DOE Oak Ridge Operations facilities

For the past several years the US Environmental Protection Agency (EPA) has been attempting to streamline and increase the efficiency of field data collection programs, especially Comprehensive Environmental Response, Compensation, and Liability Act (CERCLA) Remedial Investigation (RI) programs, by encouraging project managers to develop Data Quality Objectives (DQOs) prior to sampling. The DQO process is a strategic planning approach that is used to prepare for a data collection activity. It provides a systematic procedure for defining the criteria that a data collection design should satisfy, including when to collect samples, where to collect samples, the tolerable level of decision errors for study, and how many samples to collect. It is important to note that DQOs are developed through a process that ties data collection to specific problems and decisions

Estimating Fuel Cycle Externalities: Analytical Methods and Issues, Report 2

The activities that produce electric power typically range from extracting and transporting a fuel, to its conversion into electric power, and finally to the disposition of residual by-products. This chain of activities is called a fuel cycle. A fuel cycle has emissions and other effects that result in unintended consequences. When these consequences affect third parties (i.e., those other than the producers and consumers of the fuel-cycle activity) in a way that is not reflected in the price of electricity, they are termed ''hidden'' social costs or externalities. They are the economic value of environmental, health and any other impacts, that the price of electricity does not reflect. How do you estimate the externalities of fuel cycles? Our previous report describes a methodological framework for doing so--called the damage function approach. This approach consists of five steps: (1) characterize the most important fuel cycle activities and their discharges, where importance is based on the expected magnitude of their externalities, (2) estimate the changes in pollutant concentrations or other effects of those activities, by modeling the dispersion and transformation of each pollutant, (3) calculate the impacts on ecosystems, human health, and any other resources of value (such as man-made structures), (4) translate the estimates of impacts into economic terms to estimate damages and benefits, and (5) assess the extent to which these damages and benefits are externalities, not reflected in the price of electricity. Each step requires a different set of equations, models and analysis. Analysts generally believe this to be the best approach for estimating externalities, but it has hardly been used! The reason is that it requires considerable analysis and calculation, and to this point in time, the necessary equations and models have not been assembled. Equally important, the process of identifying and estimating externalities leads to a number of complex issues that also have not been fully addressed. This document contains two types of papers that seek to fill part of this void. Some of the papers describe analytical methods that can be applied to one of the five steps of the damage function approach. The other papers discuss some of the complex issues that arise in trying to estimate externalities. This report, the second in a series of eight reports, is part of a joint study by the U.S. Department of Energy (DOE) and the Commission of the European Communities (EC)* on the externalities of fuel cycles. Most of the papers in this report were originally written as working papers during the initial phases of this study. The papers provide descriptions of the (non-radiological) atmospheric dispersion modeling that the study uses; reviews much of the relevant literature on ecological and health effects, and on the economic valuation of those impacts; contains several papers on some of the more complex and contentious issues in estimating externalities; and describes a method for depicting the quality of scientific information that a study uses. The analytical methods and issues that this report discusses generally pertain to more than one of the fuel cycles, though not necessarily to all of them. The report is divided into six parts, each one focusing on a different subject area

Traits and stress: keys to identify community effects of low levels of toxicants in test systems

Community effects of low toxicant concentrations are obscured by a multitude of confounding factors. To resolve this issue for community test systems, we propose a trait-based approach to detect toxic effects. An experiment with outdoor stream mesocosms was established 2-years before contamination to allow the development of biotic interactions within the community. Following pulse contamination with the insecticide thiacloprid, communities were monitored for additional 2 years to observe long-term effects. Applying a priori ecotoxicological knowledge species were aggregated into trait-based groups that reflected stressor-specific vulnerability of populations to toxicant exposure. This reduces inter-replicate variation that is not related to toxicant effects and enables to better link exposure and effect. Species with low intrinsic sensitivity showed only transient effects at the highest thiacloprid concentration of 100 μg/l. Sensitive multivoltine species showed transient effects at 3.3 μg/l. Sensitive univoltine species were affected at 0.1 μg/l and did not recover during the year after contamination. Based on these results the new indicator SPEARmesocosm was calculated as the relative abundance of sensitive univoltine taxa. Long-term community effects of thiacloprid were detected at concentrations 1,000 times below those detected by the PRC (Principal Response Curve) approach. We also found that those species, characterised by the most vulnerable trait combination, that were stressed were affected more strongly by thiacloprid than non-stressed species. We conclude that the grouping of species according to toxicant-related traits enables identification and prediction of community response to low levels of toxicants and that additionally the environmental context determines species sensitivity to toxicants

Effects of the fungicide metiram in outdoor freshwater microcosms: responses of invertebrates, primary producers and microbes

The ecological impact of the dithiocarbamate fungicide metiram was studied in outdoor freshwater microcosms, consisting of 14 enclosures placed in an experimental ditch. The microcosms were treated three times (interval 7 days) with the formulated product BAS 222 28F (Polyram®). Intended metiram concentrations in the overlying water were 0, 4, 12, 36, 108 and 324 μg a.i./L. Responses of zooplankton, macroinvertebrates, phytoplankton, macrophytes, microbes and community metabolism endpoints were investigated. Dissipation half-life (DT50) of metiram was approximately 1–6 h in the water column of the microcosm test system and the metabolites formed were not persistent. Multivariate analysis indicated treatment-related effects on the zooplankton (NOECcommunity = 36 μg a.i./L). Consistent treatment-related effects on the phytoplankton and macroinvertebrate communities and on the sediment microbial community could not be demonstrated or were minor. There was no evidence that metiram affected the biomass, abundance or functioning of aquatic hyphomycetes on decomposing alder leaves. The most sensitive populations in the microcosms comprised representatives of Rotifera with a NOEC of 12 μg a.i./L on isolated sampling days and a NOEC of 36 μg a.i./L on consecutive samplings. At the highest treatment-level populations of Copepoda (zooplankton) and the blue-green alga Anabaena (phytoplankton) also showed a short-term decline on consecutive sampling days (NOEC = 108 μg a.i./L). Indirect effects in the form of short-term increases in the abundance of a few macroinvertebrate and several phytoplankton taxa were also observed. The overall community and population level no-observed-effect concentration (NOECmicrocosm) was 12–36 μg a.i./L. At higher treatment levels, including the test systems that received the highest dose, ecological recovery of affected measurement endpoints was fast (effect period < 8 weeks)

Impact of impingement on the Hudson River white perch population. Final report

This report summarizes a series of analyses of the magnitude and biological significance of the impingement of white perch at the Indian Point Nuclear Generating Station and other Hudson River power plants. Included in these analyses were evaluations of: (1) two independent lines of evidence relating to the magnitude of impingement impacts on the Hudson River white perch population; (2) the additional impact caused by entrainment of white perch; (3) data relating to density-dependent growth among young-of-the-year white perch; (4) the feasibility of performing population-level analyses of impingement impacts on the white perch populations of Chesapeake Bay and the Delaware River; and (5) the feasibility of using simple food chain and food web models to evaluate community-level effects of impingement and entrainment. Estimated reductions in the abundances of the 1974 and 1975 white perch year classes, caused by impingement and entrainment, were high enough that the possibility of adverse long-term effects cannot be excluded

Impact of entrainment and impingement on fish populations in the Hudson River estuary. Volume I. Entrainment-impact estimates for six fish populations inhabiting the Hudson River estuary

This volume is concerned with the estimation of the direct (or annual) entrainment impact of power plants on populations of striped bass, white perch, Alosa spp. (blueback herring and alewife), American shad, Atlantic tomcod, and bay anchovy in the Hudson River estuary. Entrainment impact results from the killing of fish eggs, larvae, and young juveniles that are contained in the cooling water cycled through a power plant. An Empirical Transport Model (ETM) is presented as the means of estimating a conditional entrainment mortality rate (defined as the fraction of a year class which would be killed due to entrainment in the absence of any other source of mortality). Most of this volume is concerned with the estimation of several parameters required by the ETM: physical input parameters (e.g., power-plant withdrawal flow rates); the longitudinal distribution of ichthyoplankton in time and space; the duration of susceptibility of the vulnerable organisms; the W-factors, which express the ratios of densities of organisms in power plant intakes to densities of organisms in the river; and the entrainment mortality factors (f-factors), which express the probability that an organism will be killed if it is entrained. Once these values are obtained, the ETM is used to estimate entrainment impact for both historical and projected conditions

Impact of entrainment and impingement on fish populations in the Hudson River Estuary. Volume II. Impingement impact analyses, evaluations of alternative screening devices, and critiques of utility testimony relating to density-dependent growth, the age-composition of the striped bass spawning stock, and the LMS real-time life cycle model

This volume includes a series of four exhibits relating to impacts of impingement on fish populations, together with a collection of critical evaluations of testimony prepared for the utilities by their consultants. The first exhibit is a quantitative evaluation of four sources of bias (collection efficiency, reimpingement, impingement on inoperative screens, and impingement survival) affecting estimates of the number of fish killed at Hudson River power plants. The two following exhibits contain, respectively, a detailed assessment of the impact of impingement on the Hudson River white perch population and estimates of conditional impingement mortality rates for seven Hudson River fish populations. The fourth exhibit is an evaluation of the engineering feasibility and potential biological effectiveness of several types of modified intake structures proposed as alternatives to cooling towers for reducing impingement impacts. The remainder of Volume II consists of critical evaluations of the utilities&#x27; empirical evidence for the existence of density-dependent growth in young-of-the-year striped bass and white perch, of their estimate of the age-composition of the striped bass spawning stock in the Hudson River, and of their use of the Lawler, Matusky, and Skelly (LMS) Real-Time Life Cycle Model to estimate the impact of entrainment and impingement on the Hudson River striped bass population