FREE ELECTRONIC LIBRARY - Abstracts, books, theses

Pages:     | 1 |   ...   | 8 | 9 || 11 | 12 |   ...   | 36 |

«This page left intentionally blank. United States Environmental Protection Agency EPA-540-R-05-012 Office of Solid Waste and Emergency Response OSWER ...»

-- [ Page 10 ] --

Project managers should assess the impacts of contaminant release on potential receptors on a site-specific basis, using information generated during the baseline human health and ecological risk assessments. Where natural recovery is being evaluated, project managers should recognize that not only the rate of net sedimentation, but also the frequency of erosive episodes, can help determine the rate of recovery for surface sediment and biota. Where in-situ capping is being evaluated, project managers should recognize that some amount of erosion and sediment transport may be acceptable and can be incorporated into plans for remedial design and cap maintenance. Increased risk to human or ecological receptors due to contaminant releases during dredging may be a related analysis when considering dredging. Comparing the increased risks, costs, or other consequences of sediment disruption due to natural causes or the remedy itself also may be an important part of the remedy selection process.

When evaluating remedy alternatives, the significance of potential harm due to reexposure of contaminated sediment or contaminated sediment redistribution is an important consideration. Factors to be considered include the nature of the contaminants, the nature of the potential receiving environment and biological receptors, and the potential for repair or recovery from the disturbance. These factors can be used to evaluate risks, costs, and/or other effects of different events on existing contaminated sediment or sediment remedies.


Models are tools that are used at many sediment sites when characterizing site conditions, assessing risks, and/or evaluating remedial alternatives. A complex computer model (e.g., multidimensional numerical model) may not be needed if there is widespread agreement about the best remedial strategy based on an adequate understanding of site conditions, however, this is not often the case. At some sites, significant uncertainties exist about site characterization data and the processes that contribute to relative effectiveness of available remedial alternatives. Models can help fill gaps in knowledge and allow investigation of relationships and processes at a site that are not fully understood.

For this reason, simple or complex modeling can play a role at most sediment sites.

There is a wide range of simpler empirical models and more robust computer models that can be applied to contaminated sediment sites. Simple models that aggregate processes or consider only some portion of a problem can provide significant insights and should be applied routinely at sediment sites, even complex sites. For example, simple steady-state mass balance models applied during a time period where there are no disruptive events can be used to determine whether external contaminant sources have been identified and properly quantified. Hydrodynamic model predictions of currents and associated bottom shear stresses can provide information about the potential for erosion and the degree of interaction between backwater and main channel areas. Even if a complex fate and transport model is never developed, simple modeling can be used to develop a better understanding of current and future site conditions and lead to selection of the most appropriate remedial alternative.

More complex fate and transport models are frequently applied to the most complex sites. These sites typically have a long history of data collection, have documented contaminant concentrations in sediment and biota, and often have fish consumption advisories already in place. Fate and transport models can be useful tools, even though they can be time consuming and expensive to apply at complex 2-32 Chapter 2: Remedial Investigation Considerations sediment sites. Most of these modeling efforts require large quantities of site-specific data, and typically a team of experienced modelers is needed. Nevertheless, these models are helpful in that they give, when properly applied, a more complete understanding of the transport and fate of contaminants than typically can be provided by empirical data (from field or laboratory) alone.

Whether and when to use a model, and what models to use, are site-specific decisions and modeling experts should be consulted. Modeling of contaminated sediment, just as with other modeling, should follow a systematic planning and implementation process. Technical assistance is available to project managers from EPA’s Superfund Sediment Resource Center (SSRC), where experts from inside and outside the Agency may be accessed. Additional research about contaminated sediment transport and food web modeling is underway at the Office of Research and Development (ORD) (e.g., U.S. EPA in preparation 1 and 2). Project managers should monitor the Superfund sediment Web site at http://www.epa.gov/superfund/resources/sediment or contact their region’s ORD Hazardous Substance Technical Liaison for more information.

In most cases, simple or complex models are expected to complement environmental measurements and address gaps that exist in empirical information. Examples of the uses of models

include the following:

• Identifying data gaps during the initial phases of a site investigation;

• Illustrating how contaminant concentrations vary spatially at a site. Empirical information can provide useful benchmarks that can be interpolated or modeled to get a better understanding of the distribution of contaminants;

• Predicting contaminant fate and transport over long periods of time (e.g., decades) or during episodic, high-energy events (e.g., tropical storm or low-frequency flood event);

• Predicting future contaminant concentrations in sediment, water and biota to evaluate relative differences among the proposed remedial alternatives, ranging from monitored natural recovery to extensive removal; and • Comparing modeled results to observed measurements to show convergence of information. Both modeling results and empirical data usually will have a measure of uncertainty, and modeling can help to examine the uncertainties (e.g., through sensitivity analysis) and refine estimates, which may include indications for where to sample next.

The use of models at sediment sites is not limited to the remedy selection phase. Most sites that use models for evaluation of proposed remedies have previously developed a mass balance or other type of model during the development of the baseline risk assessment. These models are often used to quantify the relationships among contaminant sources, exposure pathways, and receptors. At these sites, the same model is often used to predict the response of the system to various cleanup options. Where this is done, it is important to continue to test the model predictions by monitoring during the remedy implementation and post-remedy phases to assess whether cleanup is progressing as predicted by the model. Where it is not, information should be relayed to the modeling team so the model can be modified or recalibrated and then used to develop more accurate future predictions.

–  –  –

2.9.1 Sediment/Contaminant Transport and Fate Model Characteristics A sediment/contaminant transport and fate model typically is a mathematical or conceptual representation of the movement of sediment and associated contaminants, and the chemical fate of those contaminants, as governed by physical, chemical and biological factors, in water bodies. Currently, there are two basic types of sediment transport models: conceptual and mathematical models. In addition, there are several different types of mathematical models. General types of models are described in Highlight 2and an example of a conceptual site model is presented in Highlight 2-13.

Highlight 2-12: Key Characteristics of the Major Types of Sediment/Contaminant Transport and Fate Models

Conceptual Model:

Identifies the following: 1) contaminants of potential concern; 2) sources of the contaminants; 3) physical and biogeochemical processes and interactions that control the transport and fate of sediment and associated contaminants; 4) exposure pathways; and 5) ecological and human receptors.

Mathematical Model:

A set of equations that quantitatively represent the processes and interactions identified by the conceptual model that govern the transport and fate of sediment and associated contaminants. Mathematical models include analytical, regression, and numerical models.

Analytical Model:

An analytical model is one or more equations (e.g., simplified - a linearized, one-dimensional form of the advection-diffusion equation) for which a closed-form solution exists. This type of model may not be applicable at most sites due to the complexities associated with the forcing hydrodynamics and spatial and temporal heterogeneities in sediment and contaminant properties/characteristics.

Regression Model:

A regression model is a statistically determined equation that relates a dependent variable to one or more independent variables. A stage-discharge rating curve is an example of a regression model in which stage (e.g., water level) and discharge (e.g., amount of water flow) are the independent and dependent variables, respectively.

Numerical Model:

In a numerical model, an approximate solution of the set of governing differential equations is obtained using a numerical technique. Examples of numerical techniques include finite difference and finite element methods. A numerical model is used when the processes being modeled are represented by nonlinear equations for which closed-form solutions do not exist.

2-34 Chapter 2: Remedial Investigation Considerations Highlight 2-13: Sample Conceptual Site Model Focusing on Sediment-Water Interaction

–  –  –

Source: Modified from Sediment Management Workgroup (SMWG) Typically, transport and fate models are inherently limited by our current understanding of the factors governing these processes and our ability to quantify them (i.e., represent mathematically their interactions and effects on the transport and fate of sediment and contaminants). Even the most complex sediment model may be a relatively simplistic representation of the movement of sediment through

natural and engineered water bodies. It may be simplistic due to the following:

–  –  –

Nevertheless, sediment/contaminant transport and fate models generally are useful tools when properly applied, although they are data intensive and require specialized expertise to apply and interpret the results.

2.9.2 Determining Whether A Mathematical Model is Appropriate Since mathematical transport and fate models can be time-intensive and expensive to apply, their use and interpretation generally require specialized expertise. Because of this, mathematical modeling is not recommended for every sediment site. In some cases, existing empirical data and new monitoring data may be sufficient to support a decision. A mathematical modeling study is usually not warranted for very small (i.e., localized) sites, where cleanup may be relatively easy and inexpensive. Mathematical modeling generally is recommended for large or complex sites, especially where it is necessary to predict contaminant transport and fate over extended periods of time to evaluate relative differences among possible remedial approaches.

Project managers should use the following series of questions to help guide the process for

determining the appropriate use of site-specific mathematical models:

• Have the questions or hypotheses the model is intended to answer been determined?

• Are historical data and/or simple quantitative techniques available to answer these questions with the desired accuracy?

–  –  –

• Are time and resources available to perform the modeling study itself?

If the decision is made that some level of mathematical modeling is appropriate, the following section should assist project managers in deciding what type of model should be used.

2.9.3 Determining the Appropriate Level of Model When the decision is made that a mathematical model is appropriate at a site, project managers should generally consider three steps in determining what level of modeling to use. It is important to consider all three steps in order. In some cases, these three steps may be more useful when performed in 2-36 Chapter 2: Remedial Investigation Considerations an iterative fashion (for example, based on additional data analysis or from results obtained during Step 3, it may become apparent that the conceptual site model (CSM) should be modified).

Step 1: Develop Conceptual Site Model Development of a CSM is recommended as the key first step in this process in determining the level of modeling. As described in Section 2.2, a CSM identifies the processes and interactions that typically control the transport and fate of contaminants, including sediment associated contaminants. If this step is not performed, then the decision of what level of modeling is appropriate may be made with less than the requisite information that might be needed to make a scientifically defensible decision.

The development of a CSM usually requires examination of existing site data to assist in determining the significant physical and biogeochemical processes and interactions. Relatively simple quantitative expressions of key transport and fate processes using existing site data, such as presented by Reible and Thibodeaux (1999) or Cowen et al. (1999), may help in identifying those processes most significant at the site.

Step 2: Determine Processes that Can and Cannot be Currently Modeled

This step concerns determining if the most significant processes and interactions that control the transport and/or fate of sediment contaminants, as identified in the CSM, can be simulated with one or more existing sediment transport and fate models. Mathematical models (in particular numerical models) that have been developed can simulate most of the processes controlling the transport and fate of sediment and contaminants in water bodies (including a wide variety of physical, chemical, and biological processes). Highlight 2-14 depicts the inter-relationship of some major processes and the type of model with which they are associated. If it is determined that there are existing models capable of simulating at a minimum the most significant (i.e., first-order) processes and interactions, then the project manager should (using the appropriate technical experts) identify the types of models (e.g., analytical, regression, numerical) having this capability and eliminate from further consideration those types of models not having this capability.

Depending on the needs at the site, models or model components (“modules”) may link many of these processes presented in Highlight 2-14 into one model. Examples of the processes that can be

modeled include the following:

• Land and air: Physical processes that result in loading of contaminants to water bodies may include point discharges, overland flow (i.e., runoff), discharge of ground water, NAPL seeps, and air deposition;

• Water column: Physical processes that may result in movement of dissolved or sedimentsorbed contaminants include transport via the water’s ambient flow (advection), diffusion, and settling of sediment particles containing sorbed contaminants;

• Sediment bed: Important physical processes include the movement of pore water and dissolved contaminants, seepage into and out of the sediment bed and banks, and the mixing of dissolved and sediment-sorbed contaminants by bioturbation. In addition, both sorbed and dissolved material may be exchanged between the water column and sediment bed due to sediment deposition and resuspension or erosion; and

–  –  –

Pages:     | 1 |   ...   | 8 | 9 || 11 | 12 |   ...   | 36 |

Similar works:

«Securikett Comments and Consultation Sanco.ddg1.d.3(2011)1342823 Inhalt Introduction About Securikett About Kurz About Brainority About the Authors Remarks on the Meaning of Safety Features vs. Unique Identifiers in the Directive Securikett’s Opinion on Unique Identifiers and whether they May be Considered as Safety Features, under a Cost Perspective Thoughts about Exceptions from a Security Point of View Proposing an Open Architecture for Unique Identifier Systems UID systems are more than...»

«Sponsored by the Government of Japan OECD-ADBI Roundtable on Capital Market Reform in Asia 4-5 April 2013, Tokyo, Japan AGENDA Chair: Dr. Malcolm Edey, Assistant Governor (Financial System), Reserve Bank of Australia and Chair of the OECD Committee on Financial Markets DAY ONE: 4 April 2013 (Thursday) 09:00 – 09:30 Registration of participants 09:30 – 10:10 Opening remarks  Dr. Masahiro Kawai, Dean and CEO, ADBI  Mr. Rintaro Tamaki, Deputy Secretary General, OECD  Dr. Malcolm Edey,...»

«MISSISSIPPI INSURANCE DEPARTMENT Report of Examination of AMERICAN FEDERATED INSURANCE COMPANY as of December 31, 2014 TABLE OF CONTENTS Examiner’s Affidavit Salutation Scope of Examination Comments and Recommendations of Previous Examination History of the Company Corporate Records Holding Company Structure Organizational Chart Parent and Affiliated Companies..5 Related Party Transactions Management and Control Board of Directors Officers Conflict of Interest Fidelity Bond and Other...»

«American Association of School Librarians National Research Forum White Paper December 2014 This project was made possible in part by the Institute of Museum and Library Services grant number LG-62-13-0212-13. December 2014 Abstract Introduction Research and Causality Discussion Recommended Plan of Action Community of Scholars Conclusion Works Cited Appendix A: Participants Appendix B: Further Reading Appendix C: Timetable Appendix D: Communication Plan 2 AASL National Research Forum – White...»

«1 Semantic Paradox and Alethic Undecidability Forthcoming in Analysis Steve Barker, University of Nottingham: stephen.barker@nottingham.ac.uk In what follows, I use the principle of truth-maker maximalism, TM below, to provide a new solution to the semantic paradoxes: TM: If a sentence is true (or false), then it is true (or false) in virtue of non-alethic facts. In TM, the term non-alethic facts means facts that have nothing to do with the truth or falsity of sentences, like the fact that snow...»

«Testicular Cancer What is testicular cancer? Cancer starts when cells in the body begin to grow out of control. Cells in nearly any part of the body can become cancer, and can spread to other areas of the body. To learn more about how cancers start and spread, see What Is Cancer? Cancer that starts in the testicles is called testicular cancer. To understand this cancer, it helps to know about the normal structure and function of the testicles. Testicles (also called the testes; a single...»

«Psychological Test and Assessment Modeling, Volume 56, 2014 (1), 25-44 The impact of group pseudo-guessing parameter differences on the detection of uniform and nonuniform DIF W. Holmes Finch1 & Brian F. French Abstract Differential item functioning (DIF) is an important aspect of item development and validity assessment. Traditionally DIF is divided into two broad types, focusing on conditional group differences of the item difficulty (uniform DIF) and discrimination (nonuniform DIF)...»

«CASE NO. A-94-1249 IN THE COURT OF APPEALS OF THE STATE OF NEBRASKA THE STATE OF NEBRASKA, Plaintiff-Appellee, vs. BRIAN E. DODSON, Defendant-Appellant Appeal from the District Court eE~~ Douglas County, Nebraska The Honorable Robert v. Burkhard e-ly, d, ole{Jtwv. Jvl. 0uuor)'fr ctpfRa I OVi BRIEF OF APPELLANT BRIAN E. DODSON Julianne M. Dunn #15046 716 Keeline Building 319 South 17th Street Omaha, Nebraska 68102-1911 (402) 341-0727 Attorney for Defendant-Appellant BRIAN E. DODSON TABLE OF...»

«Blucher Design Proceedings Novembro de 2014, Número 4, Volume 1 www.proceedings.blucher.com.br/evento/11ped Gramado – RS De 29 de setembro a 2 de outubro de 2014 HISTÓRIA DA MODA E HISTÓRIADA ARQUITETURA: do frívolo ao efêmero João Gabriel Farias Barbosa de Araújo Universidade de São Paulo araujojg@usp.br Lara Leite Barbosa Universidade de São Paulo barbosall@usp.br Resumo: O presente artigo trata das aproximações estabelecidas entre o design de moda e a arquitetura, em especial a...»

«THE MINUTES OF THE REGULAR MEETING OF THE DISTRICT SCHOOL BOARD OF NIAGARA BOARD ROOM – EDUCATION CENTRE January 27, 2015 6:15 – 7:00 p.m. (Private Session) 7:00 – 10:00 p.m. (Public Session) ATTENDANCE: Board: Sue Barnett (Chair), Dale Robinson (Vice-Chair), Jennifer Ajandi, Helga Campbell, Lora Campbell, Diane Chase, Linda Crouch, Jonathan Fast, Cheryl Keddy Scott, Kevin Maves, Dave Schaubel Regrets: Student Trustees Nick Molkoski and Vinay Sharma Officials: Warren Hoshizaki (Director...»

«THE ALTAR GUILD HANDBOOK Peace Lutheran Church 10625 Ranch Road 620 North Austin, Texas 78726 Table of Contents Prayers for the Altar Guild 2 Altar Guild Checklist 3 Altar Guild Coordinator Checklist 5 Preparing for Services in the Church 6 The Ministry of Altar Guild 6 Altar Guild Procedures 8 Before church Preparing for Holy Communion Altar Guild Scheduling 14 Appendix A Communion Bread(recipe) 15 Appendix B Church Calendar – Colors of the Church 17 Appendix C Eucharistic Items 21 -1Prayers...»

«Oracle Active Data Guard Real-Time Data Protection and Availability ORACLE WHITE PAPER | OCTOBER 2015 Table of Contents Introduction 1 Oracle Active Data Guard – An Overview 2 How Data Guard Synchronizes Standby Database(s) 3 Transport Services 3 Redo Apply Services 5 Continuous Oracle Data Validation 5 Protection Modes 5 Managing a Data Guard Configuration 6 Role Management Services Switchover and Failover 6 Fast-Start Failover 7 Automating Client Failover 7 Using Data Guard to Reduce...»

<<  HOME   |    CONTACTS
2017 www.sa.i-pdf.info - Abstracts, books, theses

Materials of this site are available for review, all rights belong to their respective owners.
If you do not agree with the fact that your material is placed on this site, please, email us, we will within 1-2 business days delete him.