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Fecal indicator organisms (FIOs), such as Escherichia coli and enterococci, are often used as surrogates of contamination in the context of beach management; however, bacteriophages may be more reliable indicators than FIO due to their similarity to viral pathogens in terms of size and persistence in the environment. In the past, mechanistic modeling of environmental contamination has focused on FIOs, with virus and bacteriophage modeling efforts remaining limited. In this paper, we describe the development and application of a fate and transport model of somatic and F-specific coliphages for the Washington Park beach in Lake Michigan, which is affected by riverine outputs from the nearby Trail Creek. A three-dimensional model of coliphage transport and photoinactivation was tested and compared with a previously reported E. coli fate and transport model. The light-based inactivation of the phages was modeled using organism-specific action spectra. Results indicate that the coliphage models outperformed the E. coli model in terms of reliably predicting observed E. coli/coliphage concentrations at the beach. This is possibly due to the presence of additional E. coli sources that were not accounted for in the modeling. The coliphage models can be used to test hypotheses about potential sources and their behavior and for predictive modeling.

Microbial fate and transport in watersheds should include a microbial source apportionment analysis that estimates the importance of each source, relative to each other and in combination, by capturing their impacts spatially and temporally under various scenarios. A loosely configured software infrastructure was used in microbial source-to-receptor modeling by focusing on animal- and human-impacted mixed-use watersheds. Components include data collection software, a microbial source module that determines loading rates from different sources, a watershed model, an inverse model for calibrating flows and microbial densities, tabular and graphical viewers, software to convert output to different formats, and a model for calculating risk from pathogen exposure. The system automates, as much as possible, the manual process of accessing and retrieving data and completes input data files of the models. The workflow considers land-applied manure from domestic animals on undeveloped areas; direct shedding (excretion) on undeveloped lands by domestic animals and wildlife; pastureland, cropland, forest, and urban or engineered areas; sources that directly release to streams from leaking septic systems; and shedding by domestic animals directly to streams. The infrastructure also considers point sources from regulated discharges. An application is presented on a real-world watershed and helps answer questions such as: What are the major microbial sources? What practices contribute to contamination at the receptor location? What land-use types influence contamination at the receptor location? and Under what conditions do these sources manifest themselves? This research aims to improve our understanding of processes related to pathogen and indicator dynamics in mixed-use watershed systems.

Many watershed models simulate overland and instream microbial fate and transport, but few provide loading rates on land surfaces and point sources to the waterbody network. This paper describes the underlying equations for microbial loading rates associated with 1) land-applied manure on undeveloped areas from domestic animals; 2) direct shedding (excretion) on undeveloped lands by domestic animals and wildlife; 3) urban or engineered areas; and 4) point sources that directly discharge to streams from septic systems and shedding by domestic animals. A microbial source module, which houses these formulations, is part of a workflow containing multiple models and databases that form a loosely configured modeling infrastructure which supports watershed-scale microbial source-to-receptor modeling by focusing on animal- and human-impacted catchments. A hypothetical application – accessing, retrieving, and using real-world data – demonstrates how the infrastructure can automate many of the manual steps associated with a standard watershed assessment, culminating in calibrated flow and microbial densities at the watershed’s pour point.

This review outlines major directions of simpler model development in environmental modeling, metamodeling, statistical-regression- and machine-learning-based empirical models, and mechanistic mode...

Understanding pathogenic and indicator bacteria survival in soils is essential for assessing the potential of microbial contamination of water and produce. The objective of this work was to evaluate the effects of soil properties, animal source, experimental conditions, and the application method on temperature dependencies of manure-borne generic , O157:H7, and fecal coliforms survival in soils. A literature search yielded 151 survival datasets from 70 publications. Either one-stage or two-stage kinetics was observed in the survival datasets. We used duration and rate of the logarithm of concentration change as parameters of the first stage in the two-stage kinetics data. The second stage of the two-stage kinetics and the one-stage kinetics were simulated with the model to find the dependence of the inactivation rate on temperature. Classification and regression trees and linear regressions were applied to parameterize the kinetics. Presence or absence of two-stage kinetics was controlled by temperature, soil texture, soil water content, and for fine-textured soils by setting experiments in the field or in the laboratory. The duration of the first stage was predominantly affected by soil water content and temperature. In the model dependencies of inactivation rates on temperature, parameter estimates were significantly affected by the laboratory versus field conditions and by the application method, whereas inactivation rates at 20°C were significantly affected by all survival and management factors. Results of this work can provide estimates of coliform survival parameters for models of microbial water quality.

Modeling the fate and transport of Escherichia coli is of substantial interest because of how this organism serves as an indicator of fecal contamination in microbial water quality assessment. The efficacy of models used to assess the export of E. coli from agricultural fields is dependent, in part, on submodels they utilize to simulate E. coli release from land-applied manure and animal waste. Although several release submodels have been proposed, they have only been evaluated and compared with data from laboratory or small plot E. coli release experiments. Our objective was to evaluate and compare performances of three manure-borne bacteria release submodels at the field-scale. Models evaluated included the exponential release model (EM), the two-parametric Bradford and Schijven model (B-S), and the two-parametric Vadas-Kleinman-Sharpley model (VKS). Each model was independently incorporated and tested as a submodel within the export model KINEROS2/STWIR, using data of E. coli in runoff. Dairy manure was uniformly applied via surface broadcasting once a year for six consecutive years on a 0.28-ha experimental field site. Two irrigation events followed each application: the first immediately followed the initial application and the second occurred 1 week later. Manure and soil samples were collected before and after irrigation, respectively, and manure, soil, and edge-of-field runoff samples were analyzed for E. coli. Model performance was evaluated with the Akaike criterion, coefficients of determination, and standard error values. The percentage of exported manure-borne E. coli varied from 0.1 to 10% in most cases, generally reflecting the lag time between initiation of irrigation and initiation of edge-of-field runoff. The export model performed better when using the VKS submodel which was preferred in 52% of cases. The B-S and EM submodels were preferred in 24 and 6% of cases, respectively. Submodels were equally efficient in 18% of cases. Two-parametric submodels were ultimately preferred over the single parameter submodel.

Scientific evidence supporting recreational water quality benchmarks primarily stems from epidemiological studies conducted at beaches impacted by human fecal sources. Epidemiological studies conducted at locations impacted by non-human faecal sources have provided ambiguous and inconsistent estimates of risk. Quantitative Microbial Risk Assessment (QMRA) is another tool to evaluate potential human health risks from recreational exposures to non-human faecal contamination. The potential risk differential between human and selected non-human faecal sources has been characterized previously for direct deposition of animal feces to water. In this evaluation, we examine the human illness potential from a recreational exposure to freshwater impacted by rainfall-induced runoff containing agricultural animal faecal material. Risks associated with these sources would be at least an order of magnitude lower than the benchmark level of public health protection associated with current US recreational water quality criteria, which are based on contamination from human sewage sources. We examine the human illness potential from exposure to rainfall-induced runoff.The predicted risks are lower than the benchmark level of protection.This risk assessment should be helpful to inform public health decision-making.

Summary Infiltration is important to modeling the overland transport of microorganisms in environmental waters. In watershed- and hillslope scale-models, infiltration is commonly described by simple equations relating infiltration rate to soil saturated conductivity and by empirical parameters defining changes in infiltration rate with soil water content. For the microbial transport model KINEROS2/STWIR used in this study, infiltration in unsaturated soil is accounted for by a net capillary drive parameter, G , in the Parlange equation. Scarce experimental data and multiple approaches for estimating parameter G introduce uncertainty, reducing reliability of overland water flow and microbial transport models. Our objectives were to evaluate reliability and robustness of three methods to estimate parameter G and associated accuracy and uncertainty in predicting runoff and fecal coliform (FC) transport. These methods include (i) KINEROS2 fitting to the experimental cumulative runoff data; (ii) estimating solely on soil texture; and (iii) estimating by individual pedotransfer functions (PTFs) and an ensemble of PTFs from basic soil properties. Results show that the most accurate prediction was obtained when the G parameter was fitted to the cumulative runoff. The KINEROS2-recommended parameter slightly overestimated the calibrated value of parameter G and yielded less accurate predictions of runoff, FC concentrations and total FC. The PTFs-estimated parameters systematically deviated from calibrated G values that caused high uncertainty in the KINEROS2/STWIR predictions. Averaging PTF estimates considerably improved model accuracy, reducing the uncertainty of runoff and FC concentration predictions. Overall, ensemble-based PTF estimation of the capillary drive can be efficient for simulations of runoff and bacteria overland transport when a single effective value is used across the study area.

An increase in food-borne illnesses in the United States has been associated with fresh produce consumption. Irrigation water presents recognized risks for microbial contamination of produce. Water quality criteria rely on indicator bacteria. The objective of this review was to collate and summarize experimental data on the relationships between pathogens and thermotolerant coliform (THT) and/or generic E. coli, specifically focusing on surface fresh waters used in or potentially suitable for irrigation agriculture. We analyzed peer-reviewed publications in which concentrations of E. coli or THT coliforms in surface fresh waters were measured along with concentrations of one or more of waterborne and food-borne pathogenic organisms. The proposed relationships were significant in 35% of all instances and not significant in 65% of instances. Coliform indicators alone cannot provide conclusive, non-site-specific and non-pathogen-specific information about the presence and/or concentrations of most important pathogens in surface waters suitable for irrigation. Standards of microbial water quality for irrigation can rely not only on concentrations of indicators and/or pathogens, but must include references to crop management. Critical information on microbial composition of actual irrigation waters to support criteria of microbiological quality of irrigation waters appears to be lacking and needs to be collected.

UNLABELLED The objective of this study was to compare dependency of survival rates on temperature for indicator organisms Escherichia coli and Enterococcus and the pathogen Salmonella in surface waters. A database of 86 survival datasets from peer-reviewed papers on inactivation of E. coli, Salmonella and Enterococcus in marine waters and of E. coli and Salmonella in lake waters was assembled. The Q10 model was used to express temperature effect on survival rates obtained from linear sections of semi-logarithmic survival graphs. Available data were insufficient to establish differences in survival rates and temperature dependencies for marine waters where values of Q10 = 3 and a survival rate of 0·7 day(-1) could be applied. The Q10 values in lake waters were substantially lower in marine waters, and Salmonella inactivation in lake water was, on average, twice as fast as E. coli; data on E. coli substantially outnumber data on Enterococcus and Salmonella. The relative increase in inactivation with increase in temperature is higher in marine waters than lake water, and differences in inactivation between Salmonella and E. coli at a given temperature were significant in lake water but not in marine waters. SIGNIFICANCE AND IMPACT OF THE STUDY Microbiological quality of surface waters is of paramount importance for public health. The novelty of this work is using a large compendium of published data to develop the first comparison of temperature effects on survival of the pathogen Salmonella and water quality indicator micro-organisms Escherichia coli and Enterococcus in natural waters. The existing relatively large body of knowledge on E. coli survival appears to be useful to assess the effect of temperature on survival of Salmonella. Moreover, results of this work constitute an essential input in models to support environmental management decisions on the use of surface water sources in agriculture, aquaculture and recreation.

Integrated environmental modeling (IEM) includes interdependent science-based components that comprise an appropriate software modeling system and are responsible for consuming and producing information as part of the system, but moving information from one component to another (i.e., interoperability) is the responsibility of the IEM software system. We describe and discuss the Framework for Risk Analysis in Multimedia Environmental Systems (FRAMES), a component-based IEM system, from the standpoint of software design requirements which define system functionalities. Design requirements were identified in a series of workshops, attended by IEM practitioners, and reported in the development of a number of IEM software systems. The requirements cover issues associated with standards, component connectivity, linkage protocols, system architecture and functionality, and web-based access, all of which facilitate the creation of plug & play components from stand-alone models through a series of software support tools and standards.

Standardized methods are often used to assess the likelihood of a human-health effect from exposure to a specified hazard, and inform opinions and decisions about risk management and communication. A Quantitative Microbial Risk Assessment (QMRA) is specifically adapted to detail potential human-health risks from exposure to pathogens; it can include fate and transport models for various media, including the source zone (initial fecal release), air, soil/land surface, surface water, vadose zone and aquifer. The analysis step of a QMRA can be expressed as a system of computer-based data delivery and modeling that integrates interdisciplinary, multiple media, exposure and effects models and databases. Although QMRA does not preclude using source-term and fate and transport models, it is applied most commonly where the source-term is represented by the receptor location (i.e., exposure point), so the full extent of exposure scenarios has not been rigorously modeled. An integrated environmental modeling infrastructure is, therefore, ideally suited to include fate and transport considerations and link the risk assessment paradigm between source and receptor seamlessly. A primary benefit of the source-to-outcome approach is that it allows an expanded view of relevant cause-and-effect relationships, which facilitate consideration of management options related to source terms and their fate and transport pathways. The Framework for Risk Analysis in Multimedia Environmental Systems (FRAMES) provides software technology for analysts to insert appropriate models and databases that fit the problem statement and design and construct QMRAs that are reproducible, flexible, transferable, reusable, and transparent. A sample application using different models and databases registered with FRAMES is presented. It illustrates how models are linked to assess six different manure-based contaminant sources, following three pathogens (Salmonella eterica, Cryptosporidium spp., and Escherichia coli O157:H7) to a receptor where exposures and health risk impacts are then evaluated. The modeling infrastructure demonstrates how analysts could use the system to discern which pathogens might be important and when, and which sources could contribute to their importance. IEM FRAMES is a flexible tool to support custom-designed source-to-receptor QMRAs.FRAMES captures multiple and user-defined modeling approaches.An example QMRA assesses source apportionment and pathogens of importance.Pathogen fate and transport modeling is linked to point-of-exposure risk analysis.IEM links environmental and microbial characteristics with an uncertainty analysis.

Four seasonal rainfall simulations in 2009 and 2010 were applied to a field containing 36 plots (0.75 × 2 m each), resulting in 144 runoff events. In all simulations, a constant rate of rainfall was applied then halted 60 min after initiation of runoff, with plot-scale monitoring of runoff every 5 min during that period. Runoff was simulated with the Kinematic Runoff and Erosion/Simulator of Transport with Infiltration and Runoff (KINEROS2/STWIR) field-scale model, whose hydrodynamics are based on the kinematic wave equation. Because of the non-linear nature of the model and a highly parameterized model with respect to the available data, several approaches were investigated to upscale nine runoff-related parameters from a series of small monitored plots to the field scale. Inverse modeling was performed using the model-independent Parameter ESTimation (PEST) algorithm to individually calibrate the nine KINEROS2/STWIR parameters on 36 plots. The parameters were averaged, and bootstrapping was used to assess uncertainty of the parameters via estimation of confidence intervals (CI). A Monte Carlo simulation using the bootstrap results showed reasonable field-scale representation of flow rates. Median values of calibrated parameters were within the 95% CI obtained with bootstrapping. The simulated results for the median values associated with the 90% CI flow rates produced similar trends as those exhibited with the observed data, suggesting that median values of the calibrated parameters from the PEST inverse modeling could be used to represent the field scale. Copyright © 2013 John Wiley & Sons, Ltd.

A series of simulated rainfall-runoff experiments with applications of different manure types (cattle solid pats, poultry dry litter, swine slurry) was conducted across four seasons on a field containing 36 plots (0.75 × 2 m each), resulting in 144 rainfall-runoff events. Simulating time-varying release of Escherichia coli, enterococci, and fecal coliforms from manures applied at typical agronomic rates evaluated the efficacy of the Bradford–Schijven model modified by adding terms for release efficiency and transportation loss. Two complementary, parallel approaches were used to calibrate the model and estimate microbial release parameters. The first was a four-step sequential procedure using the inverse model PEST, which provides appropriate initial parameter values. The second utilized a PEST/bootstrap procedure to estimate average parameters across plots, manure age, and microbe, and to provide parameter distributions. The experiment determined that manure age, microbe, and season had no clear relationship to the release curve. Cattle solid pats released microbes at a different, slower rate than did poultry dry litter or swine slurry, which had very similar release patterns. These findings were consistent with other published results for both bench- and field-scale, suggesting the modified Bradford–Schijven model can be applied to microbial release from manure.

Understanding pathogenic and indicator bacteria survival in soils is essential for assessing the potential of microbial contamination of water and produce. The objective of this work was to evaluate the effects of soil properties, animal source, experimental conditions, and the application method on temperature dependencies of manure-borne generic , O157:H7, and fecal coliforms survival in soils. A literature search yielded 151 survival datasets from 70 publications. Either one-stage or two-stage kinetics was observed in the survival datasets. We used duration and rate of the logarithm of concentration change as parameters of the first stage in the two-stage kinetics data. The second stage of the two-stage kinetics and the one-stage kinetics were simulated with the model to find the dependence of the inactivation rate on temperature. Classification and regression trees and linear regressions were applied to parameterize the kinetics. Presence or absence of two-stage kinetics was controlled by temperature, soil texture, soil water content, and for fine-textured soils by setting experiments in the field or in the laboratory. The duration of the first stage was predominantly affected by soil water content and temperature. In the model dependencies of inactivation rates on temperature, parameter estimates were significantly affected by the laboratory versus field conditions and by the application method, whereas inactivation rates at 20°C were significantly affected by all survival and management factors. Results of this work can provide estimates of coliform survival parameters for models of microbial water quality.

A comprehensive benchmarking is being performed between three multimedia risk assessment models: RESRAD, MMSOILS, and MEPAS. Each multimedia model is comprised of a suite of modules (e.g., groundwater, air, surface water, exposure, and risk/hazard), all of which can impact the estimation of the human health risk. As a component of the comprehensive benchmarking exercise, the saturated-zone modules of each model were applied to an environmental release scenario, where uranium-234 was released from the waste site to a saturated zone. Uranium-234 time-varying emission rates exiting from the source and concentrations at three downgradient locations (0, 150, and 1500 m) are compared for each multimedia model. Time-varying concentrations for uranium-234 decay products (e.g., thorium-230, radium-226, and lead-210) at the 1500-m location are also presented. Different results reported for RESRAD, MMSOILS, and MEPAS are solely due to the assumptions and mathematical constructs inherently built into each mo...

Microbial quality of surface waters attracts attention due to food- and waterborne disease outbreaks. Fecal indicator organisms (FIOs) are commonly used for the microbial pollution level evaluation. Models predicting the fate and transport of FIOs are required to design and evaluate best management practices that reduce the microbial pollution in ecosystems and water sources and thus help to predict the risk of food and waterborne diseases. In this study we performed a sensitivity analysis for the KINEROS/STWIR model developed to predict the FIOs transport out of manured fields to other fields and water bodies in order to identify input variables that control the transport uncertainty. The distributions of model input parameters were set to encompass values found from three-year experiments at the USDA-ARS OPE3 experimental site in Beltsville and publicly available information. Sobol' indices and complementary regression trees were used to perform the global sensitivity analysis of the model and to explore the interactions between model input parameters on the proportion of FIO removed from fields. Regression trees provided a useful visualization of the differences in sensitivity of the model output in different parts of the input variable domain. Environmental controls such as soil saturation, rainfall duration and rainfall intensity had the largest influence in the model behavior, whereas soil and manure properties ranked lower. The field length had only moderate effect on the model output sensitivity to the model inputs. Among the manure-related properties the parameter determining the shape of the FIO release kinetic curve had the largest influence on the removal of FIOs from the fields. That underscored the need to better characterize the FIO release kinetics. Since the most sensitive model inputs are available in soil and weather databases or can be obtained using soil water models, results indicate the opportunity of obtaining large-scale estimates of FIO transport from fields based on publicly available rather than site-specific information. Keywords: Fecal indicator organisms, Release and transport, Global sensitivity analysis, Regression trees

The role of manganese (Mn) oxides in catalyzing the abiotic oxidation of polynuclear aromatic compounds (PNAs) has been investigated by monitoring the oxidation of dihydrodiol and dione PNAs and corresponding reduction of Mn in an aqueous environment. 1,4-, 1,3-, and 2,3-naphthalenediol, 1,4-naphthoquinone, and l,4-dihydroxy-9,10-anthracenedione (Quinizarin) were oxidized in an oxic, aqueous environment, where each of these organic compounds is soluble in water, except Quinizarin. A mathematical model is presented, which describes the redox reactions, and suggests that electron transfer/organic release from the oxide surface is rate limiting with the reaction apparently proceeding through a free-radical formation. Results indicate significant oxidation of the organics, that the oxidation of the diols is kinetically more favorable than that of the dione, and that lower molecular weight PNAs containing diol and dione functional groups are susceptible to abiotic-catalyzed oxidation, thereby suggesting that progressively more complex PNA molecules may also be susceptible to oxidation.

This document addresses techniques to access and integrate data for defining site-specific conditions and behaviors associated with ground-water and surface-water radionuclide transport applicable to U.S. Nuclear Regulatory Commission reviews. Environmental models typically require input data from multiple internal and external sources that may include, but are not limited to, stream and rainfall gage data, meteorological data, hydrogeological data, habitat data, and biological data. These data may be retrieved from a variety of organizations (e.g., federal, state, and regional) and source types (e.g., HTTP, FTP, and databases). Available data sources relevant to hydrologic analyses for reactor licensing are identified and reviewed. The data sources described can be useful to define model inputs and parameters, including site features (e.g., watershed boundaries, stream locations, reservoirs, site topography), site properties (e.g., surface conditions, subsurface hydraulic properties, water quality), and site boundary conditions, input forcings, and extreme events (e.g., stream discharge, lake levels, precipitation, recharge, flood and drought characteristics). Available software tools for accessing established databases, retrieving the data, and integrating it with models were identified and reviewed. The emphasis in this review was on existing software products with minimal required modifications to enable their use with the FRAMES modeling framework. The ability of fourmore » of these tools to access and retrieve the identified data sources was reviewed. These four software tools were the Hydrologic Data Acquisition and Processing System (HDAPS), Integrated Water Resources Modeling System (IWRMS) External Data Harvester, Data for Environmental Modeling Environmental Data Download Tool (D4EM EDDT), and the FRAMES Internet Database Tools. The IWRMS External Data Harvester and the D4EM EDDT were identified as the most promising tools based on their ability to access and retrieve the required data, and their ability to integrate the data into environmental models using the FRAMES environment.« less

One of the most important concerns for regulatory agencies is the concept of reproducibility (i.e., reproducibility means credibility) of an assessment. One aspect of reproducibility deals with tampering of the assessment. In other words, when multiple groups are engaged in an assessment, it is important to lock down the problem that is to be solved and/or to restrict the models that are to be used to solve the problem. The objective of this effort is to provide the U.S. Nuclear Regulatory Commission (NRC) with a means to limit user access to models and to provide a mechanism to constrain the conceptual site models (CSMs) when appropriate. The purpose is to provide the user (i.e., NRC) with the ability to “lock down” the CSM (i.e., picture containing linked icons), restrict access to certain models, or both.

Linkages to the Groundwater Modeling System have been developed at Pacific Northwest National Laboratory to enable the Nuclear Regulatory Commission (NRC) to more realistically assess the risk to the public of radioactive contaminants at NRC-licensed sites. Common software tools presently in use are limited in that they cannot assess contaminant migration through complex natural environments. The purpose of this initiative is to provide NRC with a licensing safety-analysis tool with sufficient power, flexibility, and utility that it can serve as the primary software platform for analyzing the hazards associated with licensing actions at those “complex” sites at which the traditional tools are inappropriate. As a tool designed to realistically approximate prospective doses to the public, this initiative addresses NRC’s safety-performance goal by confirming that licensing actions do not result in undue risk to the public.

The Framework for Risk Analysis in Multimedia Environmental Systems FRAMES) is decision-support middleware that provides users the ability to design software solutions for complex problems. It is a software platform that provides seamless and transparent communication between modeling components by using a multi-thematic approach to provide a flexible and holistic understanding of how environmental factors potentially affect humans and the environment. It incorporates disparate components (e.g., models, databases, and other frameworks) that integrate across scientific disciplines, allowing for tailored solutions to specific activities. This paper discusses one example application of FRAMES, where several commercialoff-the-shelf (COTS) software products are seamlessly linked into a planning and decision-support tool that helps manage water-based emergency situations and sustainable response. Multiple COTS models, including three surface water models, and a number of databases are linked through FRAMES to assess the impact of three asymmetric and simultaneous events, two of which impact water resources. The asymmetric events include 1) an unconventional radioactive release into a large potable water body, 2) a conventional contaminant (oil) release into navigable waters, and 3) an instantaneous atmospheric radioactive release.

This document provides requirements, design, data-file specifications, test plan, and Quality Assurance/Quality Control protocol for the linkage between the statistical package R and the Framework for Risk Analysis in Multimedia Environmental Systems (FRAMES) Versions 1.x and 2.0. The requirements identify the attributes of the system. The design describes how the system will be structured to meet those requirements. The specification presents the specific modifications to FRAMES to meet the requirements and design. The test plan confirms that the basic functionality listed in the requirements (black box testing) actually functions as designed, and QA/QC confirms that the software meets the client’s needs.

The Plus Operator thus provides a mechanism to group modules of similar output so that the output can be combined and supplied to downstream modules. This document provides requirements, the design, data-file specifications, the test plan, and the quality assurance/quality control (QA/QC) protocol for the Plus Operator.

This document describes concepts associated with transferring temporal and spatial boundary conditions between modules in FRAMES and how FRAMES might consider dynamic feedback.

The information in this document summarizes the approach that is used to link FRAMES-2 with GMS. This linkage will provide the user with the ability to (1) send information to a specific model in GMS, thereby modifying the models input information, as allowed by the model developer, (2) run the executable of the numerical model contained in GMS, and (3) extract, from the appropriate GMS output, information required for consumption by downstream models, which are also linked with FRAMES-2.

Because GMS provides so many features, of which some are also addressed by FRAMES, it could represent a platform to link to FRAMES, or FRAMES could represent a platform to link to GMS. The focus of this summary is to examine the strengths and weaknesses of the potential linkage direction and provide recommendations for the linkage between FRAMES and GMS.

The need for environmental systems modeling is growing rapidly because of the 1) the combination of increasing technical scope and complexity related to questions of risk-based cause and effect and 2) need to explicitly address cost effectiveness in both the development and implementation of environmental regulations. The nature of risk assessments are evolving with their increased complexity in assessing individual sites and collection of sites, addressing regional or national regulatory needs. These assessments require the integration of existing tools and the development of new databases and models, based on a comprehensive and holistic view of the risk assessment problem. To meet these environmental regulatory needs, multiple-media-based assessments are formulated to view and assess risks from a comprehensive environmental systems perspective, crossing the boundaries of several scientific disciplines. Given the consideration and the advanced states of computer hardware and software, it is possible to design a software system that facilitates the development and integration of assessment tools (e.g., databases and models). In this paper, a risk-based approach for supporting national risk assessments is presented. This approach combines 1) databases, 2) multiple media models, combining source-term, fate and transport, exposure, and risk/hazard, and 3) sensitivity/uncertainty capabilities within a software system capable ofmore » growing within the science of risk assessment. The design and linkages of the system are discussed. This paper also provides the rationale behind the design of the framework, as there is a recognized need to develop more holistic approaches to risk assessment.« less

This study investigates the effects that manganese(IV) dioxide particles have on 2,3-naphthalenediol at varying pH levels (i.e., initial pH of 4.58, 5.85, and 8.75) and under different organic concentration conditions (4×10−3, 4×10−4, and 4×10−5 M), and assesses the importance of Mn oxides on abiotic catalysis of the multiple-ringed aromatic compound. Proton concentration affected the rates of reductive dissolution; as the pH values increased, the rate of reductive dissolution decreased, as predicted by theory. Also, as the concentration of naphthalenediol increased, the rate of reductive dissolution increased, although not proportionally; thus indicating that a majority of the active sites had been occupied. In addition, the results tend to confirm that electron transfer/organic release from the oxide surface is the rate-limiting step. This study demonstrates that in an oxic environment and in the presence of 2,3-naphthalenediol, MnO2 particles undergo reductive dissolution; in the process, naphthalenediol is oxidized. An oxidation by-product of reductive dissolution is an insoluble polymerized organic. The organic by-product was deep-brown in appearance, very similar to that of "humified" material. Using infrared spectroscopy, energy-dispersive x-ray analysis, and a microelemental analysis, the "humified" products appeared to be comprised mainly of constituents originating from naphthalenediol.