Modeling Radiological Risks to Human Health from Contaminated Soils: Comparing MEPAS,MMSOILS, and RESRAD

Computer-based multimedia models are key analytical tools for assessing potential exposure to environmental contaminants as the U.S. Department of Energy remediates its sites at the nuclear weapons complex. This study applies MEPAS, MMSOILS, and RESRAD to actual release site data from the 903 Pad Source Area within Operating Unit 2 at the Rocky Flats Environmental Technology Site using a common set of assumptions. The analysis compares the similarity of multimedia model output in terms of (1) prediction of transport, (2) determination of an individual's lifetime exposure, and (3) estimation of radiological risks to human health from contaminated soils. This case study presents fairly routine exposure pathways and offers a good illustration of the way in which multimedia models can be used to assess potential radiological risk to human health from contaminated soils.     

Self-generated Analogical Models of Respiratory Pathways

Self-generated analogical models have emerged recently as alternatives to teacher-supplied analogies and seem to have good potential to promote deep learning and scientific thinking. However, studies of the ways and contexts in which students generate these models are still too limited to allow a fuller appraisal of these models’ effectiveness in enhancing conceptual learning in science. This study explores how biology students aged 15–17 generated physical concrete models to represent their understanding of the respiration pathway after learning about it through a conventional flow diagram model. The analogies portrayed in students’ self-generated models provide teachers with a supplementary channel to explore students’ conceptual understandings of this complicated topic and allow students to reflect on ways in which the abstract pathway portrayed in textbooks actually makes sense to them.     

Analysis of Multiply Matched Retrospective Studies When Risk Factor Under Study is Discrete,With Two or More Levels

The odds ratio is known to closely approximate the relative risk when the disease is rare. Logistic regression models are often used to estimate such odds ratios, but here a different model is used which avoids the assumptions implicit in logistic modelling; it also has the advantage of providing a test of homogeneity for odds rat os in situations where the logistic model cannot.     

Review of chemical,physical, and toxicologic properties of components of total petroleum hydrocarbons

Risk is a function of exposure and hazard, and both aspects must be incorporated into sound risk assessment efforts. However, risk assessment for sites contaminated with petroleum products is complicated by a general lack of information relevant to exposure to and toxicity of petroleum mixtures (especially total petroleum hydrocarbons, or TPH). Specifically, there is often inadequate information about the components of the TPH present at the site and the physical and chemical properties and toxicities of these components. Such information is crucial to developing a strong conceptual model of exposure to and risk from petroleum hydrocarbons at contaminated sites. This article presents information that can be incorporated into risk assessments for sites contaminated with petroleum hydrocarbons.     

An Approach for Incorporating Information on Chemical Availability in Soils into Risk Assessment and Risk-Based Decision Making,Prepared by: The New England Environmentally Acceptable Endpoints Workgroup

A regional workgroup comprised of individuals from regulatory agencies, uni versities, and consulting companies was formed to develop an approach for incor porating information on chemical availability in soils into risk assessment and risk based decision making. The approach consists of the following decision framework for including information on chemical availability: (1) Determine the usefulness of incorporating information on bioavailability; (2) Identify information needs from a conceptual model of exposure for the site and from exposure pathways judged critical to the assessment; (3) Identify soil factors that affect bioavailability; (4) Determine the type or form of information (measures and/or models) that can be used within the risk assessment and risk management process; (5) Select methods (measures and/or models) based on the “weight of evidence” or strength of the bioavailability information they will provide and how that information will be used for risk assessment and risk based decision making; (6) Incorporate information into the risk assessment and risk based decision making. These fac tors can be integrated into existing risk based approaches for site management such as Superfund, state approaches, and the ASTM Risk Based Corrective Action Process (RBCA). Consistent with risk assessment guidance, an assessment of chemical availability in soils must consider current as well as reasonably foresee able conditions. The approach recognizes that information on chemical availabil ity is contextual and depends on the receptor and pathway. Further, the value of information depends on how well it is accepted and/or validated for use in regulatory decision making. The workgroup identified four principles for select ing methods (measures and/or models) for obtaining information on chemical availability and for evaluating information on chemical availability for use in risk assessments: (1) soil chemical relevance, (2) pathway relevance, (3) receptor relevance, and (4) acceptance of the method.     

Analytic formulas for discrete stochastic models of cell populations with both differentiation and de-differentiation

Cell differentiation often appears to be a stochastic process particularly in the hemopoietic system. One of the earliest stochastic models for the growth of stem cell populations was proposed by Till et al. in 1964. In this model there are just two cell types: stem cells and specialized cells. At each time step there is a fixed probability that a stem cell differentiates into a specialized cell and a fixed probability that it undergoes mitosis to produce two stem cells. Even though this model is conceptually simple the myriad of possible outcomes has made it difficult to analyse. We present original closed-form expressions for the probability functions and a fast algorithm for computing them. Renewed interest in stem cells has raised questions about the effect de-differentiation has on stem cell populations. We have extended the stochastic model to include de-differentiation and show that even a small amount of de-differentiation can have a large effect on stem cell population growth.     

污染场地土壤生态风险评估研究进展

随着我国快速城市化以及产业结构的调整,遗留下了大量的污染场地,发展和实施污染场地土壤生态风险评估是进行大规模污染场地修复行动的必要条件。本文围绕污染场地土壤生态风险评估的科学原理、框架构建及技术方法等方面的关键问题: 1)评估框架的场地实际针对性;2)概念模型的不确定性;3)土壤复合污染毒性机制;4)评估终点筛选;5)评估方法和框架构建等展开讨论,指出土壤复合污染的制毒机制,即污染物生物有效性和联合效应是污染场地土壤生态风险评估的关键科学问题。耦合美国环保局四步法和欧盟层级法的“证据-权重法”评估框架适用于野外复杂环境条件下的土壤污染生态风险评估。建议今后重点开展以下5个方面的工作: 1)污染场地土壤生态风险评估技术框架与风险管控技术框架之间的联合;2)概念模型研究;3)基于过程的场地土壤污染物反应运移模型研究;4)场地土壤复合污染生态毒理学机制研究;5)生态系统高水平生态风险评估终点研究。旨在为形成我国本土污染场地土壤生态风险评估技术指南提供理论基础和构架。     

Development and field validation of a regional,management‐scale habitat model: A koala Phascolarctos cinereus case study

Species distribution models have great potential to efficiently guide management for threatened species, especially for those that are rare or cryptic. We used MaxEnt to develop a regional‐scale model for the koala Phascolarctos cinereus at a resolution (250 m) that could be used to guide management. To ensure the model was fit for purpose, we placed emphasis on validating the model using independently‐collected field data. We reduced substantial spatial clustering of records in coastal urban areas using a 2‐km spatial filter and by modeling separately two subregions separated by the 500‐m elevational contour. A bias file was prepared that accounted for variable survey effort. Frequency of wildfire, soil type, floristics and elevation had the highest relative contribution to the model, while a number of other variables made minor contributions. The model was effective in discriminating different habitat suitability classes when compared with koala records not used in modeling. We validated the MaxEnt model at 65 ground‐truth sites using independent data on koala occupancy (acoustic sampling) and habitat quality (browse tree availability). Koala bellows (n = 276) were analyzed in an occupancy modeling framework, while site habitat quality was indexed based on browse trees. Field validation demonstrated a linear increase in koala occupancy with higher modeled habitat suitability at ground‐truth sites. Similarly, a site habitat quality index at ground‐truth sites was correlated positively with modeled habitat suitability. The MaxEnt model provided a better fit to estimated koala occupancy than the site‐based habitat quality index, probably because many variables were considered simultaneously by the model rather than just browse species. The positive relationship of the model with both site occupancy and habitat quality indicates that the model is fit for application at relevant management scales. Field‐validated models of similar resolution would assist in guiding management of conservation‐dependent species.     

The human toxicity potential and a Strategy for Evaluating Model Performance in Life Cycle Impact Assessment

The Human Toxicity Potential (HTP) is a quantita tive toxic equivalency potential (TEP) that has been introduced previously to express the potential harm of a unit of chemical released into the environment. HTP includes both inherent toxicity and generic source-to-dose relationships for pollutant emissions. Three issues associated with the use of HTP in Life Cycle Impact Assessment (LCIA) are evaluated here. First is the use of regional multimedia models to define source-to-dose relationships for the HTP. Second is uncertainty and variability in sourceto-dose calculations. And third is model performance evaluation for TEP models. Using the HTP as a case study, we consider important sources of uncertainty/variability in the development of source-to-dose models — including parameter variability/uncertainty, model uncertainty, and decision rule uncertainty. Once sources of uncertainty are made explicit, a model performance evaluation is appropriate and useful and thus introduced. Model performance evaluation can illustrate the relative value of increasing model complexity, assembling more data, and/or providing a more explicit representation of uncertainty. This work reveals that an understanding of the uncertainty in TEPs as well as a model performance evaluation are needed to a) refine and target the assessment process and b) improve decision making.     

Chemical mutagens: Dosimetry,Haber's rule and linear systems

We present an overall scheme for chemical mutagen risk assessment, which leads naturally to consideration of Haber's rule, a classical concept of toxicology. A rationale is given for considering compartmental models based on mammalian anatomy and physiology as the most reasonable and practical conceptual framework for risk assessment. Haber's rule is extended to the area of chemical dosimetry, defined in terms of our compartmental models. Then it is proved that Haber's rule holds for any system of linear ordinary differential equations with constant coefficients which is physically realizable. Finally, we comment on non-linearities and on the Blum-Druckey model for time-to-occurrence of tumors.     

The use of structural dynamic models to explain successes and failures of biomanipulation

A development of a structural dynamic model, i.e. a model with current change of the most important parameters according to a goal function, is presented with the aim to explain the structural changes observed in lakes, when the nutrient concentration is increased or decreased. This type of models may be important in lake management as it may be possible qualitatively to predict the success or failure of biomanipulation. The answer to the crucial question: àt which phosphorus level will the success of biomanipulation be most probable?' will probably require the development of model which takes into account site specific processes and properties, i.e., a more complicated model. As goal function is proposed the thermodynamic function, exergy, which is defined as the work content of the system (model) compared with the system at thermodynamic equilibrium. It is shown that the structural dynamic modelling approach has been able to explain the shift from large to small zooplankton species at a certain level of phosphorus concentration, accompanied by a shifts from a dominance of zooplankton, and predatory fish to a system dominated by planktivorous fish and phytoplankton. The shift in zooplankton species cannot be explained by application of catastrophe theoretical models, which have been used to explain the hysteresis reaction. The results show that the shift should be expected at approximately 0.12 mg P l-1 and that a typical hysteresis reaction occurs at this concentration in accordance with the expectations. These results are consistent with many observations but should be interpreted with great caution, as the model is simple and general and don't account for a number of processes which may influence the results significantly in specific lake studies. The structural dynamic approach has previously been used in ten case studies with good agreement with the observations, but more case studies are needed before a general recommendation of the use of this type of models can be given. The results from this study point toward to apply this type of models for lake management where biomanipulation is involved, although it should be recommended to improve the presented general model with introduction of site specific properties for a considered lake study.     

Characterizing the spatio-temporal exposure and health risks of polycyclic aromatic hydrocarbons in an oilfield,China

Regional-scale mass balance models are often used to simulate the multimedia environmental behaviors of organic contaminants. Variables with spatial and temporal characteristics in these models are important factors of their authenticity. The BETR-MFG(IV) model was developed to characterize the spatial and temporal variations as well as health risks of 16 priority polycyclic aromatic hydrocarbons (PAHs) in Daqing City, a typical petroleum industrial city in the Heilongjiang Province, China. The non-carcinogenic and carcinogenic health risks of these contaminants are assessed on the basis of the BETR-MFG(IV) modeled results. The simulated results showed that the temporal trends of the PAHs in the multimedia environments are in a relative steady state, and the most seriously contaminated area is the municipal districts of Daqing City. It was also demonstrated that the soil is the dominant sink and that the contaminants in the water and sediment are mainly concentrated in the Nanyin Reservoir and Daqing Reservoir. The health risks of the ΣPAHs in the study area primarily come from the pathways of soil ingestion and skin exposure. These findings are helpful to determine the spatio-temporal exposure characteristics of the contaminants, which will provide a scientific guideline for environmental protection and risk management.     

Testing models of trophic dynamics: The problem of translating from model to nature

Abstract Mathematical models of interacting populations have a prominent position in population and community ecology, but are often criticized for not being testable. The authors reviewed tests of a particular model, the exploitation ecosystem hypothesis as it was formulated in Oksanen et al. (1981), in order to study problems that may be encountered when testing models. A general problem is how to determine if an experimental system should be regarded as within the model's theoretical domain or not. The theoretical domain defines the type of system the model is meant to apply to. It is noted that both liberal and strict domain definitions can be problematic. Most important is that a too liberal domain definition can result in false understanding (i.e. that it is falsely concluded that the processes included in the model are controlling the study system). Other problems encountered were more system‐specific. Equilibrium predictions were tested in experiments that were too short to reach steady state and in several studies ambiguous definitions and measurements of model variables were found such as productivity, biomass and the number trophic levels. It is concluded that a major obstacle when performing tests is the conceptual and methodological problems encountered when translating model abstractions into an empirical reality.     

The 3MRA Risk Assessment Framework—A Flexible Approach for Performing Multimedia,Multipathway, and Multireceptor Risk Assessments Under Uncertainty

A flexible framework for conducting nationwide multimedia, multipathway and multireceptor risk assessments (3MRA) under uncertainty was developed to estimate protective chemical concentration limits in a source area. The framework consists of two components: risk assessment and uncertainty analysis. The risk component utilizes linked source, fate/transport, exposure and risk assessment models to estimate the risk exposures for the receptors of concern. Both human and ecological receptors are included in the risk assessment framework. The flexibility of the framework is based on its ability to address problems varying in spatial scales from site-specific to regional and even national levels; and its ability to accommodate varying types of source, fate/transport, exposure and risk assessment models. The uncertainty component of the 3MRA framework is based on a two-stage Monte Carlo methodology. It allows the calculation of uncertainty in risk estimates, and the incorporation of the effects of uncertainty on the determination of regulatory concentration limits as a function of variability and uncertainty in input data, as well as potential errors in fate and transport and risk and exposure models. The framework can be adapted to handle a wide range of multimedia risk assessment problems. Two examples are presented to illustrate its use, and to demonstrate how regulatory decisions can be structured to incorporate the uncertainty in risk estimates.     

Ecology,Environmental Impact Statements,and Ecological Risk Assessment: A Brief Historical Perspective

Ecological risk assessment will continue to increase in importance as a conceptual and methodological basis for evaluating environmental impacts as required by the National Environmental Policy Act. Understanding the historical strengths and limitations of more traditional environmental assessments performed in support of the NEPA can facilitate the effective incorporation of ecological risk assessment into the NEPA process. Such integration will also benefit from a knowledge of the historical and continuing development of the ecological risk assessment process, as well as from a recognition of the contri butions from modern quantitative ecology and ecosystem science. Adopting a risk-based approach can improve the NEPA process by providing a framework for consistent and comprehensive ecological assessment and by providing a conceptual and methodological basis for addressing the varied uncertainties attendant to environmental assessments. The primary concern in integrating ecological risk assessment into the NEPA process is that ecological risk assessment not merely become a new name for traditional environmental impact assessments. While the integration of ecological risk assessment into the NEPA process occurs, it is important to begin to outline the next transition in environmental assessment capabilities. Operationally linking ecological risk assessment methods with formal decision models appears as a worthwhile objective in beginning this transition.     

Improving the Development and Use of Biologically Based Dose Response Models (BBDR) in Risk Assessment

Biologically based dose-response (BBDR) models predict health outcomes (response) resulting from the presence of a toxicant at a biological target (dose). The benefits of BBDR models are many, and research programs are increasingly focusing on mechanistic research to support model development; however, progress has been slow. Impediments to progress include the complexity of dose response modeling, the need for a multidisciplinary team and consistent funding support, and difficulty in identifying and extracting the needed data. Of immediate concern is the lack of transparency of published models to the supporting data and literature, difficulty in accessing model code and simulation conditions sufficient to allow independent replication of results, and absence of well-defined quality criteria. Suggestions are presented to improve the development and use of BBDR models in risk assessment and to address the above limitations. Examples from BBDR models for methylmercury neurotoxicity and 5-fluorouracil embryotoxicity are presented to illustrate the suggestions including what kinds of databases are needed to support model development and transparency, quality assurance for modeling, and how the internet can advance database development and collaboration within the biological modeling community.     

Promotion time models with time-changing exposure and heterogeneity: application to infectious diseases

Promotion time models have been recently adapted to the context of infectious diseases to take into account discrete and multiple exposures. However, Poisson distribution of the number of pathogens transmitted at each exposure was a very strong assumption and did not allow for inter-individual heterogeneity. Bernoulli, the negative binomial, and the compound Poisson distributions were proposed as alternatives to Poisson distribution for the promotion time model with time-changing exposure. All were derived within the frailty model framework. All these distributions have a point mass at zero to take into account non-infected people. Bernoulli distribution, the two-component cure rate model, was extended to multiple exposures. Contrary to the negative binomial and the compound Poisson distributions, Bernoulli distribution did not enable to connect the number of pathogens transmitted to the delay between transmission and infection detection. Moreover, the two former distributions enable to account for inter-individual heterogeneity. The delay to surgical site infection was an example of single exposure. The probability of infection was very low; thus, estimation of the effect of selected risk factors on that probability obtained with Bernoulli and Poisson distributions were very close. The delay to nosocomial urinary tract infection was a multiple exposure example. The probabilities of pathogen transmission during catheter placement and catheter presence were estimated. Inter-individual heterogeneity was very high, and the fit was better with the compound Poisson and the negative binomial distributions. The proposed models proved to be also mechanistic. The negative binomial and the compound Poisson distributions were useful alternatives to account for inter-individual heterogeneity.     

Cancer cell biology: a student-centered instructional module exploring the use of multimedia to enrich interactive,constructivist learning of science

Multimedia has the potential of providing bioscience education novel learning environments and pedagogy applications to foster student interest, involve students in the research process, advance critical thinking/problem-solving skills, and develop conceptual understanding of biological topics. Cancer Cell Biology, an interactive, multimedia, problem-based module, focuses on how mutations in protooncogenes and tumor suppressor genes can lead to uncontrolled cell proliferation by engaging students as research scientists/physicians with the task of diagnosing the molecular basis of tumor growth for a group of patients. The process of constructing the module, which was guided by scientist and student feedback/responses, is described. The completed module and insights gained from its development are presented as a potential "multimedia pedagogy" for the development of other multimedia science learning environments.     

Comparison,Validation, and Use of Models for Predicting Indoor Air Quality from Soil and Groundwater Contamination

The use of models to predict indoor air quality and health risk for the soil vapor transport to indoor air pathway is commonplace; however, there is significant uncertainty surrounding processes and factors affecting this pathway, and the accuracy of models used. Available screening models were evaluated through a review of model characteristics and sensitivity, and through comparisons to measured conditions at field sites. Model simulations and comparisons to field data indicate that the vapor attenuation ratio (α) is highly sensitive to certain processes (e.g., biodegradation and ad-vection) and input parameters. Comparisons of model predicted to measured a values indicate that models based on the Johnson and Ettinger (1991) framework in most cases result in predictions that are conservative by up to one to two orders of magnitude for field sites that were assessed, providing that appropriate input parameters are used. However, for sites where the advection potential is high, these models may not be conservative. The potential for advective transport of vapors into building may be significant for sites with shallow contamination, high permeability soil and foundation and high building underpressurization. The paper concludes with possible tiered management framework for the soil vapor pathway.