COMMITTEE ON EPA 542-R-01-002 

 THE CHALLENGES OF January 2001 

 MODERN SOCIETY www.clu-in.org 

 www.nato.int/ccms 

NATO/CCMS Pilot Study

Evaluation of Demonstrated and 

Emerging Technologies for the 

Treatment of Contaminated Land 

and Groundwater (Phase III) 

2000 

SPECIAL SESSION 

Decision Support Tools 

Number 245 

NORTH ATLANTIC TREATY ORGANIZATION 
NATO/CCMS Pilot Study 

Evaluation of Demonstrated and Emerging 

Technologies for the Treatment and Clean Up 

of Contaminated Land and Groundwater 

(Phase III) 

SPECIAL SESSION ON 

Decision Support Tools 

Wiesbaden 

June 26-30, 2000 

January 2001
NOTICE 

This report was prepared under the auspices of the North Atlantic Treaty Organization s Committee on 

the Challenges of Modern Society (NATO/CCMS) as a service to the technical community by the 

United States Environmental Protection Agency (U.S. EPA). The report was funded by U.S. EPA s 

Technology Innovation Office. The report was produced by Environmental Management Support, Inc., 

of Silver Spring, Maryland, under U.S. EPA contract 68-W-00-084. Mention of trade names or specific 

applications does not imply endorsement or acceptance by U.S. EPA. 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

i 

CONTENTS 

Introduction ..................................................................................................................................... 1 

Executive Summary ........................................................................................................................ 3 

Opening Comments......................................................................................................................... 5 

Framework for Decision Support Used in Contaminated Land Management in Europe and 

North America................................................................................................................................. 9 

Geospatial Decision Frameworks for Remedial Design and Secondary Sampling ...................... 31 

Decision Support Tools: Applications in Remediation Technology Evaluation and Selection.... 42 

Common Factors in Decision Making and Their Implications For Decision Support for 

Contaminated Land in a Multiobjective Setting ........................................................................... 58 

Case Study: Cost Benefit Analysis/Multi-Criteria Analyses for a Remediation Project .............. 69 

Modelling the Financial Risks of Remediation............................................................................. 83 

Decision Support Using Life Cycle Assessment in Soil Remediation Planning .......................... 92 

Approaches to Decision Support in the Context of Sustainable Development........................... 100 

Summary and Conclusions.......................................................................................................... 113 

Country Representatives ............................................................................................................. 125 

Attendees List.............................................................................................................................. 128 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 1 

INTRODUCTION 

The Council of the North Atlantic Treaty Organization (NATO) established the Committee on the 

Challenges of Modern Society (CCMS) in 1969. CCMS was charged with developing meaningful 

programs to share information among countries on environmental and societal issues that complement 

other international endeavors and to provide leadership in solving specific problems of the human 

environment. A fundamental precept of CCMS involves the transfer of technological and scientific 

solutions among nations with similar environmental challenges. 

The management of contaminated land and groundwater is a universal problem among industrialized 

countries, requiring the use of existing, emerging, innovative, and cost-effective technologies. This 

document summarizes the special session on decision support systems from the third meeting of the Phase 

III Pilot Study on the Evaluation of Demonstrated and Emerging Technologies for the Treatment and 

Clean Up of Contaminated Land and Groundwater. The United States is the lead country for the Pilot 

Study, and Germany and The Netherlands are the Co-Pilot countries. The first phase of the pilot study 

was successfully concluded in 1991, and the results were published in three volumes. The second phase, 

which expanded to include newly emerging technologies, was concluded in 1997. Final reports 

documenting 52 completed projects and the participation of 14 countries were published in June 1998. 

Through this pilot study, critical technical information is made available to participating countries and the 

world community. 

The Phase III study focuses on the technical approaches for treating contaminated land and groundwater. 

This includes issues of sustainability, environmental merit, and cost-effectiveness, in addition to 

continued emphasis on emerging remediation technologies. The objectives of the study are to critically 

evaluate technologies, promote the appropriate use of technologies, use information technology systems 

to disseminate the products, and to foster innovative thinking in the area of contaminated land. 

The first meeting of the Phase III study was held in Vienna, Austria, on February 23-27, 1998. The 

meeting included a special technical session on treatment walls and permeable reactive barriers. The 

proceedings of the meeting and of the special technical session were published in May 1998. The second 

meeting of the Phase III Pilot Study convened in Angers, France, on May 9-14, 1999, with representatives 

of 18 countries attending. A special technical session on monitored natural attenuation was held. This 

report and the general proceedings of the 1999 annual meeting were published in October 1999. This third 

meeting was held in Wiesbaden, Germany from June 26-30, 2000. The special technical focused on 

decision support tools. 

This publication is the report from the special session on decision support tools. This session was chaired 

by Dr. Paul Bardos from r3 environmental technology Ltd (UK) and Dr. Terry Sullivan from Brookhaven 

National Laboratory (US). 

This and many of the Pilot Study reports are available online at http://www.nato.int/ccms/. General 

information on the NATO/CCMS Pilot Study may be obtained from the country representatives listed at 

the end of the report. Further information on the presentations in this decision support tools report should 

be obtained from the individual authors. 

 Stephen C. James 

 Walter W. Kovalick, Jr., Ph.D. 

 Co-Directors 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 2 

 

THIS PAGE IS INTENTIONALLY BLANK
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 3 

EXECUTIVE SUMMARY 

Environmental management of contaminated lands is a complex process requiring a wide variety of 

decisions encompassing different technical, social, and political questions. Decision support for 

contaminated land management is an emerging field. Decision support involves integration of expertise 

and data, followed by analysis and interpretation of the results to produce outcomes in terms of decision 

variables (health risk, cost, suitability, etc.). The decision support can be in the form of guidance that 

provides a framework for performing the analysis or software that has codified the expertise to allow 

more rapid analysis by many. The magnitude and similarity between contaminated land management 

problems has led to development of several decision support tools (DSTs) to address different aspects of 

the problem (site characterization, cost-benefit, risks, sustainable development, etc.). 

Four major categories of DST use were identified during the special session discussions: 

• Written guidance produced, for example, by regulatory bodies, 

• Identifying sites on a regional or organizational (e.g., corporate) basis and setting management/ 

policy goals, 

• Prioritization among different sites within a single area of responsibility, 

• Using DST for specific tasks at a single site. Examples of these approaches include analysis of 

human health risks, remedy selection, site characterization, and cost-benefit analysis. In most 

applications, a single decision criterion is evaluated. However, use of multi-criteria analysis 

(MCA) and life cycle analysis (LCA) approaches are often found. 

The session had a series of invited talks on different aspects of decision support including implementation 

of decision support tools. This report contains the following papers: 

• Framework for decision support used in contaminated land management in Europe and North 

America 

• Geospatial decision frameworks for remedial design and secondary sampling 

• Decision support tools: applications in remediation technology evaluation and selection 

• Common factors in decision-making and their implications for decision support for contaminated 

land in a multi-objective setting 

• Case Study - Cost benefit analysis/multi-criteria analyses for a remediation project 

• Modelling of financial risks of remediation 

• Decision support using Life Cycle Assessment in Soil Remediation Planning 

• Approaches to decsion support in the context of sustainable development 

• Managing environmental data 

In addition, two guided discussion sessions were conducted and one set of written questions was prepared 

and distributed to the conference participants. Responses from the questions were analyzed and the results 

were reported at the meeting. The discussion sections focused on obtaining information on the uses of 

decision support tools and the strengths and limitations of these tools. The questionnaire focused on 

gathering information on the use of decision support in the different countries participating in the 

meeting. These discussions have been summarized in the closing paper of this report: Review of 

discussions about decision support issues in Europe and North America at The NATO/CCMS Special 

Session, and overall conclusions. The main findings of this discussion are as follows. 

The major advantage of using appropriate DST's is that they can ensure the decision making process is 

robust, consistent, transparent and reproducible. Specific advantages include: 

• Providing a means of relatively easy analysis for multiple scenarios, 

• Optimizing the contaminated land management process (leading to lower costs), 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 4 

• Incorporating uncertainties into the decision framework to enhance the decision making process. 

(This permits the decision to be based on the problem holder’s aversion to failure). 

• Improving communication between various stakeholder groups. 

• Use as an educational tool. 

• Improving the transparency of the process through documenting all parameters and assumptions 

used in the analysis and explaining the approach used to reach a decision. 

However, current DSTs do suffer some limitations, which affect their usefulness. 

• Gaining acceptability of a DST with all stakeholders can be difficult. 

• Verification/validation of DST performance can be technically challenging 

• If the assumptions and data used by DST are not understood, output from the DST may be viewed 

as “black box” information and may not be trusted. Proper use of DSTs requires users and 

interested stakeholders receive training on the theory, application and limitations of the DST. 

Decision support tools must be maintained to keep current, relevant and useful. 

• Garbage In – Garbage Out: a decision support tool is only as good as the data and assumptions 

used to perform the analysis
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 5 

OPENING COMMENTS TO THE SPECIAL 

SESSION ON DECISION SUPPORT TOOLS 

Paul Bardos1 and Terry Sullivan2

1. r3 environmental technology Lt1d, PO Box 58, Ware, SG12 9UJ, UK 

2. Brookhaven National Laboratory, Upton, N.Y., 11973, USA 

BACKGROUND 

The Council of North Atlantic Treaty Organisation (NATO) established the Committee on the Challenges 

of Modern Society (CCMS) in 1969. The CCMS was charged with developing meaningful environmental 

and social programmes that complement other international initiatives in solving specific problems of the 

human environment. A major activity of the CCMS is the transfer of technological and scientific 

solutions and experiences among nations with similar environmental challenges. Further information 

about the work of the CCMS is available on www.nato.int/ccms/info.htm. 

In 1997 the NATO CCMS adopted a proposal from the USA for a Pilot Study on treatment technologies. 

It will run from 1998 to 2002, with a final report in 2003 and is under the direction of the USA, the 

Netherlands and Germany. 

The NATO/CCMS Pilot Study on the "Evaluation of Demonstrated and Emerging Technologies for the 

Treatment of Contaminated Land and Groundwater (Phase 3) is the third in a series of Pilot Studies 

considering remedial technologies. These Pilot Studies followed a Pilot Study on the problems of 

contaminated land directed by the UK and Germany. 

The three NATO/CCMS Pilot Studies on remediation technologies has been perhaps the foremost 

international forum for the exchange of practical and research experience of remedial technologies. The 

series includes: 

• Phase 1, 1986 to 1991 (Martin et al., 1997; NATO, 1993; Smith et al 1998, US EPA, 1995 & 

1998) 

• Phase 2, 1992 to 1997 (Franzius et al., 1996, US EPA, 1998a) 

• Phase 3, 1998 to 2003 (U.S. EPA, 1998b ,1998c, 1999a, 1999b, 2000). 

The Phase 3 Pilot Study has attracted participation from the following countries across the world. Australia, 

Austria, Belgium, Canada, the Czech Republic, Denmark, France, Germany, Greece, Hong Kong, Hungary, 

Italy, Japan, the Netherlands, New Zealand, Norway, Poland, Portugal, Romania, the Slovak Republic, 

Slovenia, Spain, Sweden, Switzerland, Turkey, the United Kingdom, and the United States have all been 

represented at one or more meetings by a project, government representative, CCMS Fellow, or an 

individual expert. 

The current Pilot Study continues the theme of emerging research and technology demonstration. At each 

meeting a special one-day session on a topic of particular interest for the remediation of land contamination 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 6 

is held. In 1998 the special session was on treatment walls (US EPA1998c), and in 1999 it was on 

monitored natural attenuation (US EPA 1999b). 

In 2000 the topic for the special session was decision support issues. This report presents the papers of that 

special session, and a summary paper of the session discussions and conclusions. It has been published by 

NATO and the U.S. Environmental Protection Agency as part of an ongoing series of Pilot Study 

publications. Other publications in this series are listed in the reference section. 

GOALS 

The aims of the report on the special session on decision support are to: 

1. Provide a general understanding of Decision Support (DS) approaches used in contaminated land 

remediation / risk management, their use, their features and their strengths and weaknesses, for all 

the NATO delegates whatever their level of knowledge about DS (a wide range of knowledge has 

been assumed from poor to expert) 

2. Involve the Pilot Study in discussion and to document from this debate: 

• perceived needs for and uses of DS from the perspective of end-users 

• factors seen are most important in decision making 

• evaluation of the strengths and weaknesses of existing DS and their use 

• needs for DS development, in particular to take advantages of the opportunities for international 

collaboration offered by the Pilot Study 

3. Inform both the users and potential users of DS, and also DS developers of the state of the art. 

APPROACH 

The emphasis of the session was on the use of decision support tools for actual remediation decisions. It 

considered two perspectives: 

• site-specific decision making for example choosing a particular remediation system; 

• remediation in terms of a risk management / risk reduction process as part of a wider process of 

site management. 

These were addressed both as general topics and as case studies. Case studies were included to provide 

information on decision support techniques for specific contamination problems such as remedy selection. 

In the case studies, the authors present the general process to provide decision support and then discuss 

the application to a specific problem. The intent of this approach is to provide the interested reader with 

enough knowledge to determine if the process could be used on their specific set of problems. The general 

topics included broader issues that are not directly tied to a specific problem. The general topics included 

papers on the role of stakeholders in the decision process and decision support approaches for sustainable 

development. 

Decision factors were explored from an end-user perspective, rather than what a DS developer would like 

them to be. Ultimately, it is the end-user that drives the decision process. There are a range of possible 

end-users, including regulators, property developers, local authorities, and specialist users. Furthermore, 

national perspectives on the use of DS appear to vary. Eliciting the differences in national perspectives 

was obtained through discussion and a set of questions provided to all meeting participants. The session 

sought to display the state-of-the-art in decision support for contaminated land management and define 

future directions in this area. Important issues pertaining to DS include: 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 7 

• Are DS tools perceived as being useful? 

• How are DS being used? 

• What are the advantages and disadvantages to using Decision Support Tools (DST)? 

• Are information needs for evaluating contaminated land management options understood? 

It is salient to note that DS are a topic for the next call for bids for the EU Framework 5 Programme. The 

US EPA "owns" a number of detailed data-sets for testing and validation of DS that may offer an 

opportunity for collaboration. There could well be other R&D synergies too. 

 

THE SESSION REPORT 

While the selected set of papers is not inclusive of all work being done on decision support, it is 

representative of the state-of-the-art approaches to decision support and covers the spectrum of 

approaches. The first presentation sets the framework for decision support and defines key terms and 

common approaches. The topics covered include data management, site characterisation and sample 

optimisation, life-cycle assessment, multi-criteria analysis, evaluating financial risks to land developers, 

sustainable development, and stakeholder involvement in the decision process. A range of discussion 

activities took place to permit audience participation to define issues in decision support. The other papers 

in this session report are as follows. 

• Framework for decision support used in contaminated land management in Europe and North 

America 

• Geospatial decision frameworks for remedial design and secondary sampling 

• Decision support tools: applications in remediation technology evaluation and selection 

• Common factors in decision-making and their implications for decision support for contaminated 

land in a multi-objective setting 

• Case Study - Cost benefit analysis/multi-criteria analyses for a remediation project 

• Modelling of financial risks of remediation 

• Decision support using Life Cycle Assessment in Soil Remediation Planning 

• Approaches to decsion support in the context of sustainable development 

 

• Managing environmental data 

• Review of discussions about decision support issues in Europe and North America at The 

NATO/CCMS Special Session, and overall conclusions 

REFERENCES 

Franzius, V., Grimski, D., and Stietzel, H-J. (1996) International Pilot Studies on the demonstration of 

clean-up / remediation technologies and on the reuse of former military lands. UTA International 1996 

Part 1 pp 70-73 

Martin, I., Visser, W., and Bardos, P. (1997) Review of policy papers presented to the NATO/CCMS 

Pilot Study on Research, Development and Evaluation of Remedial Action Technologies for 

Contaminated Soil and Groundwater. Land Contamination Reclamation 5 (1) 11-40. 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 8 

NATO Committee on the Challenges of Modern Society (1993) Demonstration of Remedial Action 

Technologies for Contaminated Land and Groundwater. Final Report. Published by the United States 

Environmental Protection Agency. Report EPA/600/R-93/012 (Parts a, b and c) 

Smith, M.A., James, S.C. and Kovalick, W.W. (1998) Comparative international study of soil and 

groundwater remediation technologies. pp 9-18 IN Contaminated Soil '98, Proc 6th Intern FZK/TNO 

Conference on Contaminated Soil, 17-21 May 1998, Edinburgh, UK. ISBN 07277 26757 

Thornton, S.F., Davison, R.M., Lerner, D.N. and Banwart, S.A. (1998). Electron balances in field studies 

of intrinsic bioremediation. GQ98 International IAHS conference on Groundwater Quality: Remediation 

and Protection, 21-25th September, 1998Tübingen, Germany. 

United States Environmental Protection Agency (1995) NATO/CCMS Pilot Study Evaluation of 

Demonstrated and Emerging Technologies for the Treatment and Clean Up of Contaminated Land and 

Groundwater (Phase II). EPA Report: EPA/542/R-95/006. 

United States Environmental Protection Agency (1998a) NATO Committee on Challenges to Modern 

Society: NATO/CCMS Pilot Study Evaluation of Demonstrated and Emerging Technologies for the 

Treatment and Clean Up of Contaminated Land and Groundwater. Phase II Overview Report No 219. 

EPA Report: 542-R-98-001a,b,c. 

United States Environmental Protection Agency (1998b) NATO Committee on Challenges to Modern 

Society: NATO/CCMS Pilot Study Evaluation of Demonstrated and Emerging Technologies for the 

Treatment and Clean Up of Contaminated Land and Groundwater. Phase III. Annual Report. No 228. 

EPA Report: 542-R-98-002. 

United States Environmental Protection Agency (1998c) NATO Committee on Challenges to Modern 

Society: NATO/CCMS Pilot Study Evaluation of Demonstrated and Emerging Technologies for the 

Treatment and Clean Up of Contaminated Land and Groundwater. Phase III 1998 Special Session 

Treatment Walls and Reactive Barriers. No 229. EPA Report: 542-R-98-003. 

United States Environmental Protection Agency (1999a) NATO Committee on Challenges to Modern 

Society: NATO/CCMS Pilot Study Evaluation of Demonstrated and Emerging Technologies for the 

Treatment and Clean Up of Contaminated Land and Groundwater. Phase III. Annual Report. No 235. 

EPA Report: 542/R-99/007 

United States Environmental Protection Agency (1999b) NATO Committee on Challenges to Modern 

Society: NATO/CCMS Pilot Study Evaluation of Demonstrated and Emerging Technologies for the 

Treatment and Clean Up of Contaminated Land and Groundwater. Phase III 1999 Special Session 

Monitored Natural Attenuation. No 236. EPA Report: 542/R-99/008. 

United States Environmental Protection Agency (2000) NATO Committee on Challenges to Modern 

Society: NATO/CCMS Pilot Study Evaluation of Demonstrated and Emerging Technologies for the 

Treatment and Clean Up of Contaminated Land and Groundwater. Phase III. Annual Report. No 244. 

EPA Report: 542/R-00/xxx. 

Note: Phase 2 and Phase 3 Pilot Study reports are available on http://www.clu-in.com and from 

http://www.nato.int/ccms. They are also available from the National Center for Environmental 

Publications and Information in the USA (fax +1 513 489 8695).
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 9 

FRAMEWORK FOR DECISION SUPPORT USED IN 

CONTAMINATED LAND MANAGEMENT IN EUROPE AND 

NORTH AMERICA 

Bardos1

, R.P.; Mariotti2, C.; Marot3, F.; and Sullivan4, T. 

1. r3

 environmental technology Ltd, PO Box 58, Ware, SG12 9UJ, UK 

2. Aquater SpA (ENI Group), 61043 S. Lorenzo in Campo (PS), Italy 

3. ADEME , Direction de l’Industrie, BP 406, 49004 Angers Cedex 01, France 

4. Brookhaven National Laboratory, Upton, NY, 11973, USA 

SUMMARY 

Effective contaminated land management requires a number of decisions addressing a suite of technical, 

economic and social concerns. This paper offers a common framework and terminology for describing 

decision support approaches, along with an overview of recent applications of decision support tools in 

Europe and the USA. A common problem with work on decision support approaches is a lack of a 

common framework and terminology to describe the process. These have been proposed in this paper. 

1. INTRODUCTION 

The NATO/CCMS Pilot Study on Remedial Action Technologies for Contaminated Soil and 

Groundwater Phase 3 is a multi-national forum for the exchange of information on emerging remediation 

technologies and technology demonstration. The Pilot Study is an activity of NATO Committee on 

Challenges for Modern Society (Web site: http://www.nato.int/ccms/info.htm). The Pilot Study has 

decided to hold a special session on the subject, which is the third in a series of special sessions. Previous 

topics were treatment walls (USEPA, 1998a) and monitored natural attenuation (USEPA, 1999). 

This paper has been produced for the NATO/CCMS Pilot Study Special Session on Decision Support 

(June 2000). The session was organized by Brookhaven National Laboratory (USA) and r3

 Environmental 

Technology Ltd. (UK) on behalf of the US Environmental Protection Agency and the Environment 

Agency of England and Wales, respectively. 

This paper also draws upon work carried out by CLARINET, the Contaminated Land Rehabilitation 

Network for Environmental Technologies in Europe. CLARINET is a Concerted Action within the 

Environment & Climate Program of the European Commission DGXII (web site: www.clarinet.at). 

CLARINET is a research network for soil and groundwater protection; risk assessment; remedial 

technologies; and decision support issues including socio-economic and political aspects. CLARINET 

includes a Working Group (WG2) specifically addressing decision support issues. WG2 has conducted an 

extensive survey of CLARINET countries to review both key factors for decision support and risk 

management, and to identify decision support approaches, which it is cataloguing in a Microsoft Access

database. CLARINET is also developing a range of decision support concepts and plans a web based 

contaminated land information system, if funding can be secured. 

2. BACKGROUND 

Several billion EURO are spent in the EU, as are several billions of dollars in the USA each year on 

remediation of land affected by contamination. Decision making, in the face of uncertainty and multiple 

and often conflicting objectives, is a vital and challenging role in environmental management that affects 

a significant economic activity. Although each environmental remediation problem is unique and will 

require a site-specific analysis, many of the key decisions are similar in structure. This has led many 

countries to attempt to develop standard approaches. As part of the standardization process, attempts have 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 10 

been made to codify specialist expertise into decision support tools. This activity is intended to facilitate 

reproducible and transparent decision making. The process of codifying procedures has also been found 

to be a useful activity for establishing and rationalizing management processes. 

The uses envisaged or desired for decision support include: 

• Identifying realistic management choices; 

• Integrating information into a coherent framework for analysis and decision making, discerning 

key information that impacts decision making from more basic information; 

• Providing a framework for transparency (i.e., all parameters, assumption, and data used to reach 

the decision should be clearly documented) and ensuring that the decision making process itself is 

documented. 

Decision making for environmental contamination problems involves integration of knowledge from 

many disciplines. There is also a range of contexts in which decisions have to be made, for example 

compliance with a regulatory need, enabling redevelopment, reducing liabilities, registering and mapping 

sites, and/or prioritizing use of resources. Each has its own suite of decisions. For example, consider the 

suite of decisions that have to be made when considering remediation as part of a redevelopment process 

for a particular site. 

• In a typical analysis, the first step in the process is to collect information about the site such as 

location of spills or disposal areas, the type of contamination that can be expected and the amount 

of contamination (area, volume, or concentrations). Based on this information, decisions 

pertaining to collection of site-specific data on the nature and extent of contamination must be 

made. These types of decisions include the number, frequency, and location of samples balanced 

against the cost of collecting and analyzing the samples and the value of additional data in 

arriving at a more robust decision. 

• Based on the initial site characterization data, interpolation, extrapolation, and other modeling 

techniques are often used to estimate the contamination levels between measured data locations. 

This information is often used in human health risk assessments to guide decisions on the need 

for remedial action (including monitored natural attenuation). If remedial action is required, 

decisions pertaining to what regions to treat and what level of remediation is technically and 

financially achievable must be addressed. 

• Projections of contamination levels often have a high degree of uncertainty (i.e., only a few data 

points are available for estimating contamination over large regions). This uncertainty requires a 

decision on whether more data is needed to better define the region requiring remediation or to 

improve the remedy selection or remedy design. 

• After remedial actions are complete, monitoring is often required to demonstrate the effectiveness 

of the remediation. This requires further decisions on what and where to monitor, and the 

duration of monitoring. A similar list of questions could be generated for other management 

processes or functions, such as prioritizing development of several contaminated sites or 

assessing financial risks for sustainable development. 

It is unlikely that any single person will have the knowledge to perform all of the analyses required in 

supporting all of the decisions pertaining to the management of land contamination. Typically, a number 

of people with different areas of expertise are involved in interpreting basic information and providing it 

in a form useful for others with less expertise in a given area. It is also apparent that there are many 

specialist underpinning decisions (e.g., what risk levels are acceptable, what to sample, when to sample, 

what technologies should be used, etc) that need to be made before general decisions on the reuse of 

contaminated land can be made. Table 1 lists some of the supporting secondary decisions that need to be 

made to make the overarching decision on contaminated land management. Table 1 is meant to be 

illustrative rather than exhaustive. 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 11 

The range of decisions and their inter-relationships lead to a great variety of decision support approaches. 

CLARINET WG21

 has found that these address different management problems, different segments of 

each problem, and that they operate on a variety of scales and complexities, using a variety of analysis 

and techniques. The broad range of decision support tools available in the USA has been reviewed by 

Sullivan et al. (1997, 1999-2000), and new methods are regularly announced on the US Environmental 

Protection Agency's (US EPA) "TechDirect" service2

. The language used to describe decision support 

methods has not been found to be consistent by these studies. A common terminology (as far as such a 

thing is possible), and a general conceptual framework for describing decision support methods, would 

greatly assist comparisons of methods and their applications, particularly in an international context. 

Table 1. Example issues to be addressed in evaluating 

remedial requirements and technologies for a site. (Bardos et al 2000) 

Category Example Issues 

Risk Management • What risks may be posed by the 

contamination now and in the future 

(considering the sources, pathways and 

receptors and the significance of any 

linkages found)? 

• What risks may result to workers as 

part of the remediation effort? 

• For affected aquifers: their use and 

importance 

• How can the risks best be managed? 

• What are the regulatory criteria? 

• What are the success criteria for the 

proposed remediation? 

• Fate of contaminants 

• Is there contamination entering the site 

from outside? 

Technical Suitability / Feasibility • What specific contamination properties 

need to be addressed (e.g., free-phase 

organics, concentration ranges, 

speciation, sorption, toxic by-products, 

etc.)? 

• How will remediation performance be 

measured? 

• The availability and suitability of 

existing information for the site 

• What time-scale is appropriate for 

remediation? What is the site 

availability for remediation works? 

• What is the size of the site? What space 

is available for remediation operations? 

• What are the current uses of the site? 

• Ground conditions (materials, surface 

conditions, geology) 

 

1

 Publications on this subject are forthcoming from CLARINET in the next 12 months and will be announced on its 

web site: www.clarinet.at 2

 Information on TechDirect is available at www.clu-in.org 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 12 

Technical Suitability / Feasibility (cont’d) • Does the remediation need to cope with 

underground structures and/or work 

under buildings? 

• Hydrogeology and groundwater 

monitoring 

• Site access, security, services and 

facilities 

Stakeholders' / Third Parties' views • What are the adjacent properties, who 

owns them and how are they affected? 

• How will stakeholder communication 

be managed? 

• What impact will the remediation have 

on site occupants and neighbors? 

• Restrictions: e.g., planning, covenants, 

other contract terms, confidentialities 

Sustainable Development • What impact will remediation have on 

other environmental compartments and 

are these acceptable (wider 

environmental value)? 

• Wider economic value 

• Wider social value 

• Use of resources, including land 

resources, for example: what in relation 

to the long-term use of the site and how 

this is to change 

Costs • Capital and operating costs 

• Balance of costs to benefits / costeffectiveness 

• Funding 

• Restrictions: insurances, liabilities, 

securities 

3. WHAT CONSTITUTES DECISION SUPPORT - TERMINOLOGY 

The dictionary definition of "decision" is: "the act or result of deciding; the determination of a trial, 

contest or question". The dictionary definition of "support" includes, amongst other things: "to furnish 

with necessaries, to provide for, to give assistance to, to advocate, to defend, to substantiate, to 

corroborate". So for the purpose of providing clarity "decision support" can be defined as: the assistance 

for, substantiation and corroboration of, an act or result of deciding; typically this deciding will be a 

determination of an optimal or best approach. Although obvious, it is important to point out that decision 

support is NOT the same as taking a decision. The actual deciding has to remain the shared responsibility 

of those with a legitimate stake in the outcome of the decision, i.e., the stakeholders. Stakeholders 

typically include any individuals or groups that may be affected by the environmental contamination. 

Stakeholders include federal, state, and local regulators, local businesses, citizens, citizen groups, problem 

holders, environmental industry, and public health officials (PCCRARM, 1997; SNIFFER, 1999). 

Another important point pertaining to decision support is that it can come in the form of written guidance 

or in the form of software. Written guidance is frequently provided by regulatory agencies as a means of 

obtaining a standardized, reproducible approach to reaching a decision. Most regulatory agencies view 

written guidance as an essential part of the approach to contaminated land management. In many cases, 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 13 

this guidance is translated into computer software to assist in the calculations (e.g., risk assessment). 

Software tools are also developed to assist in the decision process for computationally intensive analysis, 

e.g., flow and transport, geostatistical modeling, and multi-criteria analysis. 

The following words are often used in the context of decision support for contaminated land management: 

map, technique, tool, tree or system, e.g., "decision support tool", "decision support system". This list is 

not necessarily exhaustive, and in general, the current usage outlined in Table 2 is useful and efficient. 

Table 2. Terms Used in Decision Support 

Term Contemporary Usage Dictionary Definitions (UK) 

Map A figurative illustration of decision 

processes, the route taken for a 

decision 

A delineation: To arrange or plan in 

detail. 

Roadmap A diagram showing the major steps 

in reaching a decision. 

Colloquial: A detailed plan for 

achieving specified objectives. 

Technique A principal, series of operations 

used to assist decision making 

A mode of artistic performance or 

execution, a mechanical skill in art, 

craft etc 

Tool A document or software produced 

with the aim of supporting decision 

making, i.e., something that carries 

out a process in decision support 

Includes anything used as an instrument 

or apparatus in one's occupation or 

profession 

Tree A logical progression of decision 

making steps 

A diagram with branching lines 

System Variable: for some people "system”

is synonymous with "tool" above, 

for others "system" conveys the 

entire approach to decision making, 

including all its components. For 

them this totality is the decision 

support system, and something that 

deals with just a component part 

would be a "tool" rather than a 

"system" 

Co-ordinated arrangement; organized 

combination; method; a co-ordinated 

body of principles facts, theories 

doctrines etc; a logical grouping; an 

organized combination of things 

working together performing a 

particular function; any complex and 

co-ordinated whole 

"System" is a particularly problematic word, in that it is used to refer to both a component part of the 

overarching set of decisions necessary, or the whole, both of which are in line with the dictionary 

definition. However, for the purposes of clarity, it is necessary to select just one of the two alternative 

meanings for "system", even although this is more limiting than English language usage. Thus, "system " 

conveys the entire decision making approach, including all its components. The reasons for this selection 

are that: (1) "tool" already conveys the component part definition, and (2) there are those who believe that 

general rules can be drawn up for the overarching system, and not just its component parts. 

4. THE PROCESS OF DECISION SUPPORT 

Decision support methods codify expert knowledge and know-how into a "stored" method or process. The 

“stored” process could be written guidance on how to address a problem or software that helps to analyze 

the problem. When addressing a contaminated land management problem, the decision support methods 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 14 

use problem specific information; with the aim of providing a concise representation of the key decision 

making issues for that particular problem. Hence, decision support integrates information to produce 

usable knowledge, as illustrated in Figure 1. For example, consider the decision to select between two 

different remedial alternatives. The analyst would start with knowledge about the nature and extent of 

contamination. This information would be used to estimate the volume requiring treatment based on the 

"stored" knowledge (e.g., best practice, regulatory limits, cost data, data management and analysis 

techniques including interpolation, etc.). This information could then be used as the basis for the selection 

and/or design of the remedial options. For example, "stored" information on typical remediation costs 

could be used to estimate likely project costs. Other knowledge such as the degree of uncertainty in the 

volume requiring remediation and the reliability of the different remedial options could also be evaluated. 

The decision maker would then be presented with information on costs, probability of success, and what 

is being treated for the money spent to support the decision on a course of action. 

problem stored general decision 

specific expertise knowledge 

information 

 Figure 1. Illustration of Decision Support 

Decision support methods help to make the decision making process transparent, documented, 

reproducible, (hopefully) robust and provide a coherent framework to explore the options available. 

Figure 2 illustrates the stages used to arrive at decision support knowledge for a typical site. 

The starting point is to define the objectives for contaminated land management and the constraints on 

how to manage the land. For a single site, the objective may be to remediate the land to a levels that is 

acceptable for residential use. For a series of contaminated sites, the objective may be to prioritize which 

sites to remediate first to minimize risks while maximizing the amount of land available for use. In both 

cases, the constraints could be time, budget, technical feasibility, and public acceptability. Decision 

support can then assist the identification of the optimal way to meet the objectives within the constraints. 

The stages of the decision support process are confined within the dotted lines of Figure 2. Taking the 

decision is illustrated as being supported by the process. The first stage in the decision support process is 

to use experience and site-specific information (for example relating to the source terms, pathways and 

receptors) and site-specific data (for example, soil properties and hydrology). The second stage uses this 

information to develop simple conceptual models of the site behavior. The conceptual model is the basis 

for the analysis (third stage in the process), which combines information on the technology being 

proposed (if any) and the information used to form the conceptual model. Often all of this information is 

processed in computer software. There are several reasons for the use of software. First, the sheer amount 

of data in many problems favors electronic storage and manipulation. Second, the complexity of the 

analysis (e.g., geostatistics, groundwater flow, and transport, human health risk assessment) requires 

many calculations, which can easily be done on a computer. Third, the use of computers permits rapid 

evaluation of the effects of changing parameters or scenarios. This may permit uncertainties to be 

addressed. One perceived limitation of computers is that people tend to accept computer output as being 

correct and therefore not examine the underlying assumptions. A caveat applies to all computer-generated 

output; the output is only as good as the data and modeling assumptions used by the software. 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 15 

Figure 2. Flow chart containing the key steps in the decision support process 

For example to determine the effectiveness of different remedial options, estimates of contaminant 

concentrations before and after remediation may be determined through a combination of data, 

geostatistical interpolation and flow and transport models. Usually this information has to be interpreted 

and analyzed in terms of the decision variable (fourth stage in the process). In this example, the 

contaminant concentrations can be compared to regulatory thresholds and the region that exceeds the 

threshold can be defined for each remedial option. The computer software may facilitate the interpretation 

and analysis, but it is the responsibility of the analyst to insure that the analysis is accurate and the output 

is in a form useful for decision making. 

The knowledge supplied to the decision makers (fifth stage) should be transparent and readily 

understandable by different stakeholders, not just specialists. Indeed, even specialists might struggle with 

the sheer volume of detail that arises from many sites, and so require some form of rational abstraction of 

information into a more manageable volume and level of detail. These five stages form the basis for 

decision support, which uses information abstracted from other (and often more detailed) analyses. 

Decision knowledge is supplied to the decision makers, who then evaluate whether all stakeholders agree 

that the information provided is sufficient to support a decision. All environmental decisions are made 

with some degree of uncertainty. Complete knowledge is never available or attainable. If the stakeholders 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 16 

conclude that a decision cannot be made, they may request additional data, improved conceptual models, 

consideration of different technologies or refined analysis. The process of providing decision support is 

repeated with the new information until a decision can be reached. In some cases, it may not be possible 

to get all stakeholders to agree to an approach. When this occurs, the process may be vulnerable to 

litigation. 

There is an element of choice in which stakeholders to involve, from those possible (outlined in Section 

9). However, some, for example, the regulator, will be an obligatory consultee. There is a difficult balance 

to be drawn between who to involve and who not to involve. Involving a larger number of stakeholders in 

decision making will add to the costs, complexity and duration of decision making. However, there is a 

quid pro quo, in that this involvement may save future difficulties that might be caused by the reactions of 

aggrieved stakeholders who were not consulted early enough. 

Figure 2 also includes the idea that using models is not the same as decision support. Rather using 

models, and modeling techniques and software, is a step in information collection that precedes decision 

making. It is the integration of model results and their interpretation in terms of the decision variable that 

supplies decision support. This is an important distinction and is made on the basis that decision support 

implies making usable information available to a variety of stakeholders. A variety of stakeholders may 

play a role in contaminated land decision making. For example, land owners/problem holders; regulators 

and planners; site users; those with a financial connection to a site; the neighbors to a site including the 

local community; the consultants, contractors, researchers and vendors involved in designing and 

implementing the remediation. In some cases, advocacy groups and pressure groups may also seek 

involvement. Clearly, it would be an unlucky site manager who had to defend his decision making against 

all of these stakeholders simultaneously, but any decision made should be clear to them. In particular the 

site owner and a busy regulator, dealing with a variety of issues, not just contaminated land, will want 

reliable information that can be easily and quickly understood. 

Figure 3 shows a conceptual framework for information use in decision making and emphasizes that the 

“system” is the totality of the decision process. In this framework, models are not considered as decision 

support, but rather as input. Tools, techniques, trees and maps can represent one or more component parts 

of the decision making process, whereas a "system" supports the totality of a particular decision making 

process. 

 Decision support 

systems 

 Decision support tools, 

techniques, maps, trees 

Decision support input: 

problem specific 

information / models 

 

Figure 3. Decision Support Information, Tools and Systems 

Decision support exists within three broad sets of boundaries: the range of technical possibilities; the level 

of detail that is appropriate and the legislation and regulations pertinent to the decision. An effective 

decision support tool needs to offer options that are both technically and economically feasible and 

permitted by regulators, the public and other stakeholders. In a practical sense, it is equally important that 

the level of detail is appropriate. The level of detail provided to the decision-makers must be sufficiently 

explanatory, but it must also be readily understood (as pointed out above). The implications of excess 

detail are not only reducing the helpfulness of the decision support, but also increasing the cost of the 

decision support knowledge. 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 17 

5. TYPES OF DECISION SUPPORT 

Contaminated land management involves a series of decisions, as management for a particular site 

progresses. Decision support methods can play a role at each stage of the contaminated land management 

process: as a decision support tool, for specific issues and, in the view of some commentators, over the 

entirety of a management problem, as a decision support system. 

Types of management problems might include: dealing with a contaminated site; prioritizing a number of 

contaminated sites; or setting an overall sustainable development strategy for contaminated land 

management in a particular region. For each problem-solving role, different functional applications for 

decision support can be discerned. For example in managing an individual site, decision support might be 

required for: site investigation, risk assessment, risk management, aftercare, monitoring, evaluating wider 

impacts (environmental economic etc) and sustainability appraisal. In a broad sense, these are 

management steps separated by decision making; for example an appreciation of risk (assessment) leads 

to decision making for risk management. Within each management step more detailed information will be 

processed by specialists, for example engineers designing and implementing a remedial system; of life 

cycle assessment specialists carrying out an appraisal of the wider environmental impacts of competing 

remedial systems. Translation of the outputs of their work into decision-making knowledge constitutes 

the role of decision support. 

6. CATEGORIES OF DECISION SUPPORT 

CLARINET has been using four categories to describe decision support tools and other approaches: 

• The decision making role of the approach, 

• Functional application, i.e., the contaminated land management application 

• The analytical techniques used in the decision support approach 

• The nature of the decision support product 

The decision making role describes the type of decision making being supported, e.g., for managing a 

single site, or for prioritizing a number of sites. This deals with the overarching decision being made at 

the site. 

The functional application to contaminated land management describes whether the decision support is 

for risk management, remediation, monitoring and aftercare, sustainable development etc. This deals with 

the issues that must be addressed to support the overarching decision. 

Several different techniques can be employed to assist environmental decision-making. Pollard et al (1990 

identified the following: life cycle analysis (LCA); environmental risk assessment (ERA); environmental 

impact assessment (EIA); cost benefit analyses (CBA); multi-criteria analysis (MCA); multi-attribute 

analysis (MAT); environmental audit; and sustainability appraisal. In practice, many decision support 

tools use several of these techniques, or mixtures of different parts of them 

The nature of the product describes whether the tool is written guidance; a "map" of some sort, a series of 

procedures or a software based system. In practice, a number of decision support tools (DST) address 

multiple decision criteria. For example, software tools might combine risk assessment and cost-benefit 

analysis techniques to generate risk maps, cost comparisons between remedial options and other decision 

information. 

This framework is summarized in Table 3. 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 18 

Table 3. Categories for Decision Support Tools 

Problem 

Solving Role 

Functional Application Analyses 

Used 

Nature of the 

Product 

Identification - 

of problem sites 

Prioritization 

Comparison – 

of options 

Strategy 

development 

- policy 

- site specific 

Problem Identification 

Site investigation 

Risk assessment 

Risk Management 

Aftercare 

Monitoring 

Evaluating Wider Impacts 

(environmental economic 

etc) 

Sustainability appraisal 

Risk 

Assessment 

Cost benefit 

Life Cycle 

Multi-criteria 

analysis 

Written 

guidance 

Model 

procedure 

Software 

In practice many DST use several analytical techniques, or mixtures of different parts of them. The most 

commonly applied technique in contaminated land management is environmental risk assessment (see 

Section 8). Cost benefit analysis (CBA) often in conjunction with multi-criteria analysis (MCA) is 

increasingly being applied to decision making for remedial option selection once risk based objectives for 

a problem site have been decided. MCA is briefly described in Appendix 1. 

Interest is growing in Europe in also considering the broader impacts of remediation, in the context of 

sustainable development. For example, LCA techniques have been applied to considering wider 

environmental impacts in the Dutch “REC” system (NOBIS 1995a; 1995b). 

MCA approaches have been considered in the UK for the same purpose. One possible qualitative 

approach is to assess "wider environmental value" (WEV) in a way that makes use of the views of 

different stakeholders. Three features of this approach are (i) its use of layered sets of choices to remove 

potential decision making conflicts, (ii) the recording of these choices as individual rankings which are 

combined to provide an overall ranking at the end of the assessment process; and (iii) and consulting 

more than one stakeholder to gain a degree of objectivity in the rankings. The general assessment steps 

that might be included in such a framework are presented in Table 4 (Bardos et al 2000b). 

The involvement of different stakeholders (e.g., Consultant, community, regulator, problem owner) in a 

consistent decision making process is increasingly seen as being important (Pollard et al 1999; ESRC 

1997, PCCRARM 1997. USEPA 1995, USEPA, 1998b). Decision making also has to encompass an 

increasing range of viewpoints and disciplines, not just soil science and environmental engineering but 

also economic, political and social aspects. Environmental decision-making is in its infancy as a general 

discipline, and so current approaches tend to be fragmented and overlapping (Pollard et al., 1999; Tonn et 

al., 1999). 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 19 

Table 4. An approach to assessing wider environmental value. 

Step Action 

1 

2 

3 

4 

5 

6 

7 

Determining the objectives of the assessment 

Identifying the stakeholders for consultation 

Determining the scope of the assessment (i.e., which components should 

be included and their basis for assessment) 

Determining the boundaries for the assessment 

Making a comparison of WEV for an existing shortlist of remediation 

techniques (using an modified MCA approach) 

Refining comparisons and testing sensitivity to changes in input values 

Interpretation 

7. OVERVIEW OF DECISION SUPPORT APPROACHES CURRENTLY IN USE IN EUROPE 

AND THE USA 

The concern over potential human health effects resulting from poor environmental practices and the 

limited amount of clean land in economically desirable areas has led to the growing need to evaluate the 

extent of contamination and remediate as necessary. The magnitude of these problems has caused many 

countries to examine these problems on a national basis to develop priorities for sustainable development. 

The management of contaminated lands must support multiple goals that are often conflicting. That is the 

management decisions must be protective of human health while making appropriate use of economic 

resources and supporting sustainable development. 

The large number of contaminated land problems with similar characteristics has led to several attempts 

to develop tools (DST) that support the wide range of decisions related to contaminated land management 

and re-use. One objective of development of these tools is to obtain a consistent, reproducible and 

transparent approach to supporting decisions. Another objective is to provide a consistent methodology to 

compare contamination issues at different sites and serve as a basis for setting priorities. 

CLARINET WG2 has found that for evaluation of contamination at a single site, there is a general 

commonality of approach that is emerging internationally, albeit with some differences at the operational 

level. A similar set of management tasks has been identified for dealing with land contamination, which 

typically include: 

a. problem identification (including historical assessment and as a result the identification of 

potential sites); 

b. problem investigation determination of the need for remediation; 

c. risk identification (actual and potential); 

d. detailed risk evaluation and the identification of the remediation goal; 

e. selection and implementation of remedial measures; 

f. monitoring of sites following remediation. 

Although these tasks have been listed sequentially, in practice efficient implementation of the process 

often involves feedback and iteration between them. Recently, in the USA, there has been an emphasis on 

using a three step process involving systematic planning, dynamic work planning and on-site analysis to 

assist technical decision making at a contaminated site (Crumbling, 2000). In this approach, data (for 

characterization or monitoring) are analyzed on-site, risk assessments are updated based on the new data, 

and the need for additional samples is evaluated and the work plan is altered to reflect the most recently 

available data. The approach is intended to provide a more efficient characterization and better technical 

support for decision making as compared to following steps a-f in a sequential manner. 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 20 

Whilst this forms the broad skeleton of many flow diagrams, the actual flow diagrams are frequently 

more complex when applied to specific problems or sites. In fact, DST are often used to support all steps 

of the contaminated sites management process (from investigation through remediation and monitoring), 

with different DST applied to different steps or groups of steps. A few examples of these types of 

applications include: 

• providing a visual depiction of the extent of contamination as a means of highlighting areas of 

concern (problem and risk identification); 

• providing a technical basis for sample selection based on the existing data and the probability of 

exceeding a regulatory limit (problem investigation); 

• defining the volume of remediation required as a function of the confidence in meeting regulatory 

goals (For example, one could remediate only at sample locations that are above the limit. In this 

case, one would have little confidence that the entire site is clean. On the other hand, one could 

remediate the entire site if any single measured value was above the limit. This would lead to 

high confidence that regulatory goals were met, but would be very expensive in most cases). 

• providing estimates of current and future human health risks as a function of the amount of 

remediation (detailed risk evaluation); 

• providing cost-benefit analysis between competing remedial technologies (selection and 

implementation of remedial measures); and 

Overarching decision support systems include the "Model Procedures", written guidance under 

development in the UK (DETR and Environment Agency 2000). Overarching decision support 

systems remain the goal of a number of decision support software development teams. 

The preceding examples focused on addressing issues at a single site. DSTs are also used to address 

problems at multiple sites. For example, life cycle cost analysis tools are useful to examine a range of 

problems and to identify the problems with the largest life-cycle costs and the areas that lead to the 

greatest costs. This can be used as one basis for identifying areas of opportunity to reduce costs. 

DST has also been used to support litigation. Litigation often occurs when the responsible party is 

difficult to ascertain due to complex geology or multiple sources. In these cases, DST have been used to 

analyze the data using detailed technical models, abstract and interpret the model output to address the 

technical questions, and present this information (often through visualization techniques) for use by a 

non-technical audience (judge and jury) (Green, 2000). 

To some extent, this commonality of approach in contaminated land management should not be 

surprising. The nature of the basic steps of evaluation and remediation are determined by the practicalities 

of contaminated site management, which of course is not country dependent. Decision making in many 

countries is now increasingly seen as seeking a balance between “cost” and “benefits”. ‘Costs’ are 

increasingly seen from an environmental as well as an economic perspective. In all countries, resources 

are limited so remediation work must show a clear balance of benefits over costs. 

8. RISK-BASED DECISION FACTORS 

8.1 Human Health 

Human health risks that may be caused by contamination are becoming a primary basis for supporting 

decisions on remediation throughout the EU and the USA (USEPA, 1989, USEPA, 1996a; USEPA, 1996 

b; CLARINET and NICOLE, 1998, Ferguson et al 1998, Ferguson and Kasamas, 1999). In this process, 

risk assessment and the subsequent step of risk management are intimately related elements that form the 

basis for decisions on the fitness-for-use approach to land affected by contamination. The goal of risk 

assessment is to provide an objective, scientific evaluation of the likelihood of unacceptable impacts to 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 21 

human health and the environment. The goal of risk management is to support decisions on risk 

acceptability for specified land uses and to determine the actions to be taken. It is the process of making 

informed decisions on the acceptability of risks posed by contaminants at a site, either before or after 

treatment, and how any needed risk reduction can be achieved efficiently and cost effectively (Ferguson 

et al 1998, Ferguson and Kasamas 1999). In this way, the over riding needs for the protection of human 

health and the environment can be clearly identified and work prioritized accordingly. 

The assessment and management of land contamination risks considers three main elements, as illustrated 

in Figure 4: 

• the source of contamination (e.g., a solvent spill, or buried materials on a redevelopment site) 

• the receptor (i.e., a part of the ecosystem that could be adversely affected by the contamination, 

such as groundwater, human beings, flora and fauna) 

• the pathway (the route by which a receptor could come into contact with the contaminating 

substances). 

A hazard exists when contamination exists: i.e., a source of toxic substances. A hazard is a situation in 

which contamination in the ground has the potential to cause harm (e.g., adverse health effects, 

groundwater rendered unfit for use, damage to underground structures, etc.) to a particular receptor. Risk 

is commonly defined as the probability that a substance or situation will produce harm under specified 

conditions. Risk is a combination of two factors, the probability of exposure multiplied by the 

consequence of exposure (PCCRARM, 1997). Risk occurs when all three components are present (a 

source, a receptor and a pathway for that receptor to be exposed to the toxic substances from the source). 

Thus, if a hazard exists and there is a chance that a receptor will come in contact the hazardous material 

through any pathway, a risk exists. 

The presence of all three elements is also referred to as a pollutant linkage. Risk assessment involves the 

determination and characterization of such a relationship, including for example, delineation of the 

source, measurement/modeling of fate and transport processes along the pathway, and the potential effect 

and behavior of the receptor. A consideration of risk must also take account of not only the existing 

situation but also the likelihood of any changes in the conditions in the future. 

Risk management is the art of managing environmental contamination so that the risks posed by 

contamination are controlled or reduced to levels agreed upon by the regulators, problem owners, and 

other stakeholders. Risks should be assessed on a site-by-site basis to ensure that a site is suitable for its 

designated use. 

Figure 4. A Pollutant Linkage
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 22 

8.2 Ecological Risks 

In the United States and Europe, there has been a recent trend to include ecological risks as a decision 

variable for contaminated land management. The process of ecological risk assessment follows the same 

paradigm as human health risk assessment with the exception that the receptors are the plants and animals 

that inhabit the site. For example, guidance on which receptors should be considered in ecological risk 

assessment (USEPA, 1997, USEPA, 2000) and how to manage ecological risks (USEPA, 1999) has been 

published in the USA and the Netherlands (Ferguson et al 1998, Rutgers et al 2000). In Europe the 

pollutant linkage paradigm is used to consider human health and risks to other receptors such as 

ecosystems, groundwater and even buildings. 

9. Other Decision Making Factors 

Although human health risk is the most widely used factor to support decision making, there are a number 

of other factors that impact the decision process. These include: 

• Technical suitability / feasibility 

• Stakeholder / Third Party views 

• Costs and Benefits 

• Sustainable development 

Each of these is addressed below. 

Technical suitability/feasibility

Suitability is closely entwined with feasibility. Suitability refers to the ability of the technical solution to 

meet remedial objectives. Clearly, it is not worthwhile to attempt a remedial approach that is not suitable 

for the risk management problem posed. However, a proposed solution may appear to be suitable, but is 

not feasible. Factors that might cause concern over feasibility include: 

• Track record of the solution for the particular environmental remediation problem ; 

• Ability to offer validated performance information for previous projects; 

• Expertise of the purveyor; 

• Ability to verify the effectiveness of the solution when it is applied; 

• Confidence of stakeholders in the solution and in its costing; 

• Acceptability of the solution to stakeholders who may have expressed preferences for a favored 

solution or have different perceptions and expertise. 

Stakeholders 

The owner of the site is not the only stakeholder in contaminated land management decisions. The 

principal stakeholders in remediation are considered those with an interest in the land, its redevelopment, 

and the environmental, social and financial impacts of any risk management activities. Depending on the 

size and prominence of the site these stakeholders will include several of the following (Bardos et al

1999): 

• Land owners / problem holders; 

• Regulatory and planning authorities; 

• Site users, workers, visitors; 

• Financial community (banks, funders, lenders, insurers); 

• Site neighbors (tenants, dwellers, visitors); 

• Advocacy organizations and local pressure groups; 

• Consultants, contractors and technology vendors; and possibly 

• Researchers (in some circumstances). 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 23 

Each will have their own perspective, priorities, concerns and ambitions regarding any particular site. The 

most appropriate remedial actions will offer a balance between meeting as many needs as possible, 

including also the need to protect the environment, without unfairly disadvantaging any individual 

stakeholder. Such actions are more likely to be selected where the decision-making process is open, 

balanced, and systematic. Given the range of stakeholder interests, agreement of project objectives and 

project constraints such as use of time, money and space, can be a time consuming and expensive process. 

A diverse range of stakeholders for example, the site owner, regulators, planners, consultants, contractors, 

site neighbors and perhaps others, may need to reach agreement before specific remedial objectives can 

be set. Unsurprisingly once these remedial objectives are set, it may be hard to renegotiate them. 

Costs and Benefits

The aim of the assessment of costs and benefits is to consider the diverse range of impacts that may differ 

from one proposed solution to another such as the effect on human health, the environment, the land use, 

and issues of stakeholder concern and acceptability in a common units. Deciding which impacts to 

include or exclude from the assessment is likely to vary on a site-by-site basis. In many instances, it is 

difficult to attach a strictly monetary value to many effects. Hence, assessments can involve a 

combination of qualitative, formal CBA and MCA methods. It is also useful to include a sensitivity 

analysis step, particularly where this encourages decision-makers to question their judgements and 

assumptions through the eyes of other stakeholders. 

Sustainable Development

The concept of sustainable development was first considered at the United Nation’s Earth Summit 

conference in Rio de Janeiro in 1992 A number of definitions for sustainable development have been 

proposed, a widely used definitions is; "...development that meets the needs of the present without 

compromising the ability of future generations to meet their own needs" (Brundtland, 1987). At a 

strategic level, the remediation of contaminated sites supports the goal of sustainable development by 

helping to conserve land as a resource, preventing the spread of pollution to air and water, and reducing 

the pressure for development on green field sites. 

Interpreting sustainable development in the context of land remediation is a complex issue and requires 

guidance on specific components of the decision process, such as the environmental effect of different 

types of remedial options as well as overall guidance on the whole risk management process. The 

importance of the environmental effects for each option considered will be dependent on the site itself, for 

example, nuisance issues (e.g., odors, dust, noise) associated with remedial options for a remote site may 

be less important than for one in a city center. In addition, the significance of such effects will vary at a 

local, regional and / or national level. 

Combination of Decision Factors

Typically risks to human health risk and other receptors are used as a basis for setting remediation goals. 

In these cases, other decision factors such as technical feasibility and cost are used to select from amongst 

different remedial alternatives. In cases when the desired level of protection for receptors can not be 

attained due to costs or technical difficulties in remediating the site, treatment levels are agreed upon by 

the stakeholders on a case by case basis. If the risks are viewed to be large enough, extreme measures to 

reduce the exposure pathway may be taken (e.g., evacuation). If the risks are only slightly above 

regulatory standards cost/benefit analysis may be used to reach consensus on clean-up standards. For 

example, in the U.S. there is a screening level for risk such that if the excess human lifetime cancer risk is 

less than 1 part in 106

, no further efforts need to be made to reduce risks. A case can be made to have risk 

cleanup goals exceed 1 part in 106

 if it is not technologically or economically feasible to reduce it below 

this level. If the risk is too large, for example, if the excess lifetime cancer risk exceeds 1 part in 104 

remedial actions are required to reduce risk. 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 24 

Depending on the problem, any of these factors may become the overriding basis for making a decision. 

For example, even if a technically feasible solution that protects human health and the environment to 

within regulatory limits at an acceptable economic cost is available, if the stakeholders do not accept the 

solution, remediation should not proceed until a solution agreeable to all parties is found. If remediation 

proceeds, it is at the risk of having substantial opposition that may cause the efforts to be stopped or 

modified. This can lead to greater program costs. The literature contains several examples where 

decisions that were acceptable from a technical and regulatory perspective were not acceptable to all of 

the stakeholders. For example, siting of new waste disposal facilities and the use of the incineration as a 

treatment option have been prevented because of stakeholder concerns. 

10. DIFFERENCES IN THE DECISION MAKING PROCESS BETWEEN COUNTRIES 

Although there is a general commonality in approach to contaminated land management, differences in 

the decision making process exists between different countries and even within different regions of the 

same country. When this occurs, it is, generally because of one or more of the following: 

• differences in the applications of general principles (such as which receptors are to be 

considered); 

• differences in the use of analytical techniques, datasets and assumptions; 

• differences in priorities for environmental protection; 

• differences in administrative approach; 

• regional variation in characterization of land, land use, society and economy. 

These differences tend to mean that decision support tools intended for an operational application are not 

always directly transferable from country to country. Another important reason that DST are not always 

transferable between countries is that unless the tool has received extensive documentation, application, 

verification testing and peer review in the country its use is proposed in, the quality of the tool for use 

there may be difficult to judge. Table 5 presents the key transferability issues, providing examples in 

terms of analysis of soil or groundwater contamination. However, the major issues still apply to other 

types of analysis (e.g., Life cycle analysis, multi-criteria analysis, etc). To address the issue of quality of 

decision support software tools, the US EPA extensively tested six different tools on existing 

environmental contamination problems as part of their Environmental Technology Verification program 

(Sullivan, 1999a, b; Sullivan, 2000 a,b,c,d). 

Differences in applications of general principles can, for example, include whether or not ecological 

impacts are explicitly included in guideline values. Other differences include the characterization and 

treatment of uncertainty in the decision process and how end uses are categorized and then considered for 

risk assessment tools. 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 25 

Table 5. Issues in portability of Decision Support software tools 

Criteria Issue for Portability 

Documentation of Models 

and Assumptions 

Are the model assumptions reasonable and appropriate? Analysis 

of environmental problems requires conceptualization of the ‘real 

world’ into a construct that permits analysis using a computer. 

This conceptualization process involves a number of assumptions. 

It is important for the models and assumptions to be thoroughly 

documented to permit an evaluation of the models relevancy to 

specific problems. 

Multiple Lines of Reasoning Can the model address uncertainty in data and model parameters? 

The variability in natural systems makes analysis difficult. Often, 

multiple approaches can be used to define the extent of 

contamination. Models that can easily provide multiple 

realizations of the problem can help address uncertainty issues. 

Applications on Similar 

Problem 

Has the model been successfully used for similar applications? 

Successful application of a tool on similar problems can build 

confidence in the tool. 

Validation/Benchmarking Has the model been validated or benchmarked? Comparison of 

model predictions with analytical solutions (validation) and 

predictions of other accepted models (benchmarking) can build 

confidence in the model. 

Ease of Use Is the software easy to use? Some software has features that 

improve the usability of the product. For example, it is 

advantageous to use software that allows data to be imported or 

exported in many formats, to write scripts to perform repetitive 

tasks, to generate reports to document all model parameters, and 

to generate hardcopy graphics and visualizations. Software that is 

easy to use is more efficient at using the analyst’s time. 

Training & Technical 

Support 

Are training and technical support available? Many of the DS 

tools require specialized expertise (i.e., flow and transport 

modeling, geostatistics, human health risk). Training and the 

availability of technical support to address non-routine issues are 

crucial for effective use of many tools. 

Efficiency and Range of 

Applicability 

Is the model flexible enough to handle other problems that you 

might encounter in the future? Some DS tools are limited to 

specific problems or a narrow range of problems while others can 

simulate a wide range of problems. The tool must be applicable to 

the set of conditions anticipated for the analysis. 

Differences in priorities for environmental protection often underpin the differences in end use 

consideration. A major difference between countries is the way in which groundwater not currently in use 

is considered as a resource. This can be markedly different for countries depending on their surface water 

resources. More generally, while there is considerable awareness of the need to address issues of 

sustainability (wider economic, environmental and social effects), these are explicitly considered only in a 

limited number of cases. 

Differences in regional variations include the extent to which industrialization and industrial change has 

occurred, the attitude to accepting risks, differing social priorities, and the financial and technical 

resources that are available to deal with any problems. Both economic factors and the attitude of society 

to contaminated land problems determine the resources made available. 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 26 

11. CONCLUSIONS 

Contaminated land management is an important issue throughout Europe and the U.S.A. The need for 

developing techniques and approaches to improve the decision making process for reuse and/or 

remediation of contaminated lands is widely recognized. As a starting point, to improve communication 

on this topic, the following definition is offered. Decision support can be defined as: the assistance for, 

and substantiation and corroboration of, an act or result of deciding; typically this deciding will be a 

determination of optimal or best approach. The decision support process integrates specific information 

about a site and general information such as legislation, guidelines and know-how, to produce decisionmaking knowledge with the goal of being transparent, consistent and reproducible. The complexity of 

environmental remediation problems necessitates several layers of decision support including technical 

decisions on sample collection (how many and where), economic decisions pertaining to are the costs 

worth the benefits, and social/political decisions on sustainable land development. Each of these layers 

may need to be addressed as part of the overarching decision on land management and many of these 

‘layers’ are interdependent. In all cases, the decision support process takes basic input information 

(problem definition); uses decision support tools to integrate, analyze and abstract from the information 

and provides knowledge directly relevant to the decision. Approaches to contaminated land management 

have been found to follow a similar broad outline independent of the country where the problem is 

located. 

The large number of contaminated land problems with similar characteristics has led to several attempts 

to develop tools (DST) that support the wide range of decisions related to contaminated land management 

and re-use. One objective of development of these tools is to obtain a consistent, reproducible and 

transparent approach to supporting decisions. Another objective is to provide a consistent methodology to 

compare contamination issues at different sites and serve as a basis for setting priorities. DSTs have seen 

widespread use in all steps of the contaminated site management process (from investigation through 

remediation and monitoring). 

Contaminated land management decisions often involve a number of factors. The most widely used 

decision factor is protection of human health to regulatory prescribed levels of risk. Other factors such as 

technical suitability and feasibility, cost-benefits of remediation, stakeholder concerns, and long-term 

sustainability may also be used in the decision process. Often human health risks are used as the basis for 

setting remedial objectives. In this case, the decision often becomes what technology can meet the health 

risk goals at the lowest cost while meeting stakeholder concerns. The most appropriate remedial actions 

will offer a balance between meeting as many needs as possible, including also the need to protect the 

environment, without unfairly disadvantaging any individual stakeholder. 

Despite the similarities between contaminated land problems throughout the world, there are differences 

in the approach to these problems. These include differences in application of general principles (e.g., 

some countries consider ecological risk as one basis for analysis while others do not); differences in 

priorities (e.g., groundwater management is more important to countries with limited surface waters); 

differences in administrative and regulatory approach; and differences in social attitudes towards risk and 

the resources available for land management. 

12. ACKNOWLEDGEMENTS 

This work has been supported by the Environment Agency and the Department of the Environment 

Transport and the Regions (UK), ADEME (France) and Aquater (ENI Group) (Italy). 

The authors gratefully acknowledge the views of many from the NATO/CCMS and CLARINET 

communities, in particular Ian Martin, Joop Okx and Malcolm Lowe, and the agreement of CLARINET 

to use its material. 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 27 

The views in this paper are the authors' and are not necessarily those of their employers or sponsoring 

organizations. 

13. REFERENCES 

NATO/CCMS papers are available on: http://www.nato.int/ccms/info.htm. CLARINET papers for this 

review are published on its web site: www.clarinet.at. 

Bardos R.P. (2000) Source Management - Findings of the May 2000 NICOLE Workshop. To be 

published by NICOLE, Summer 2000 

Bardos, R.P., Martin, I.D. and Kearney, T. (1999) Framework for Evaluating Remediation Technologies. 

Presented at: IBC's 10th Conference. Contaminated Land. July 5th, Royal Marsden NHS Trust, London. 

Pub. IBC Technical Services Ltd, Gilmoora House, 57-61 Mortimer Street, London, W1N 7TD 

Bardos R.P., Kearney, T.E., Nathanail, C.P., Weenk, A. and Martin, I.D. (2000b) Assessing the Wider 

Environmental Value of Remediating Land Contamination, 7th International FZK/TNO Conference on 

Contaminated Soil, 18-22 September 2000, Leipzig, Germany. 

Bardos, R.P., Morgan, P. And Swannell, R.P.J. (2000) “Application Of In Situ Remediation Technologies –

1. Contextual Framework.” Submitted to Land Contamination and Reclamation

Brundtland. G.H. (1987) Our Common Future. World Commission on Environment and Development. 

CLARINET/NICOLE (1998) Clarinet / Nicole Joint Statement: “Better decision making now.” October 

1998. Available from http://www.nicole.org 

Crumbling, D. (2000), “Improving the cost-Effectiveness of Hazardous Waste Site Characterisation and 

Monitoring,” US EPA Technology Innovation Office, Washington, D.C. 

http://clu-in.org/tiopersp/default.htm

Department of the Environment, Transport and the Regions and Environment Agency (2000) Model 

Procedures for the Management of Contaminated Land, CLR11, Procedure for Risk Assessment, 

DETR/EA, in preparation

ESRC (1997) “The Use of Models in Policy Making: Towards a Comparison and Evaluation of 

Experiences.” Workshop Report. 10-11 April, 1997, University of Lancaster, UK. 

Ferguson, C., Darmendrail, D., Freier, K., Jensen, B.K., Jensen, J., Kasamas, H., Urzelai, A. & Vegter, J. 

(1998) “Risk Assessment for Contaminated Sites in Europe. Volume 1. Scientific Basis”, LQM Press, 

Nottingham. 

Ferguson C. C. and Kasamas, H. (1999) “Risk Assessment for Contaminated Sites in Europe. Volume 2. 

Policy Frameworks.” LQM Press, Nottingham. ISBN 0953 309010. 

Green, S., and Delaney, T., (2000). “Show and Tell: Computer animation and modeling of subsurface and 

surface conditions can aid expert witnesses testimony during contaminated litigation.” Environmental 

Protection, April 2000, pp. 50 – 56. (www.eponline.com). 

NOBIS - Netherland Onderzoeksprogramma Biotechnologische In situ Sanering (1995a). “Risk 

Reduction, Environmental Merit and Costs.” REC-Method, Phase 1. Document 95-1-03, CUR/NOBIS, 

Gouda, The Netherlands, tel. +31 182 540680. 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 28 

NOBIS - Netherland Onderzoeksprogramma Biotechnologische In situ Sanering (1995b). “Risk 

Reduction, Environmental Merit and Costs. REC-Method, Phase 2: A methodology based on Risk 

reduction, Environmental merit and Costs.” Document 95-1-03, CUR/NOBIS, Gouda, The Netherlands, 

tel. +31 182 540680. 

PCCRARM, Presidential/Congressional Commission on Risk Assessment and Risk Management (1997) 

Framework for Environmental Health Risk Management. Final Report 2 Volumes. 

http://www.riskworld.com. 

Pollard. S., Brookes A., Twigger-Ross C., and Irwin J., (1999). “Fragmentation. Convergence and 

Harmonisation: Where Are We Going with Integrated Decision-Making?“ In: facing the New 

Millennium, proceedings 9th Annual SRA-Europe Conference, Rotterdam, October 10-13, 1999, SRAEurope. 

Rutgers, M., Faber, J.H., Postma, J.F. and Eijsackers, H. (2000) Site-specific ecological risks: A basic 

approach to the function-specific assessment of soil pollution. Rapporten Programma Geintereerd 

Bodemonderzoek Volume 28 ISBN 72370448 

Tonn, B., Turner, R., Meckling, J., Fletcher, T. and Barg, S. (1999). “Environmental Decision Making 

and Information Technology: Issues Assessment.” NCEDR, Knoxville, USA,. Report NECDR/99-01 

SNIFFER 1999. “Communicating Understanding of Contaminated Land Risks.” SNIFFER Project 

SR97(11)F, SEPA Head Office, Erskine Court, The Castle Business Park, Stirling, FK9 4TR. 

Sullivan, T.M., P.D. Moskowitz, M. Gitten, and S. Schaffer, “Environmental Decision Support Software, 

Identification and Preliminary Review,” BNL-64384, Brookhaven National Laboratory, 1997. 

Sullivan, T.M., M. Gitten, and P.D. Moskowitz, “Evaluation of Selected Environmental Decision Support 

Software, “ BNL-64613, Brookhaven National Laboratory, 1997. 

Sullivan, T.M., P. Moskowitz, and M. Gitten, “Overview of Environmental Decision Support Software,”

Toxicology in Risk Assessment, Ed. Salem H. and Olajos, E.J. Taylor and Francis, Ann Arbor, MI, 2000. 

Sullivan, T., A.Q. Armstrong, A.B. Dindal, R.A. Jenkins, J. Osleeb, and E.N. Koglin (1999a). 

Environmental Technology Verification Report. Environmental Decision Support Software. 

Environmental Software, SiteProTM Version 3.0, EPA/600/R-99/093. (www.epa.gov/etv/verifrpt.htm) 

Sullivan, T., A.Q. Armstrong, A.B. Dindal, R.A. Jenkins, J. Osleeb, and E.N. Koglin (1999b). 

Environmental Technology Verification Report. Environmental Decision Support Software. ESRI, 

ArcView, EPA/600/R-99/094. (www.epa.gov/etv/verifrpt.htm) 

Sullivan, T., A.Q. Armstrong, A.B. Dindal, R.A. Jenkins, J. Osleeb, and E.N. Koglin (2000a). 

Environmental Technology Verification Report. Environmental Decision Support Software. University of 

Tennessee Research Corporation, Spatial Analysis and Decision Assistance (SADA), EPA/600/R-00/036. 

(www.epa.gov/etv/verifrpt.htm) 

Sullivan, T., A.Q. Armstrong, A.B. Dindal, R.A. Jenkins, J. Osleeb, and E.N. Koglin (2000b). 

Environmental Technology Verification Report. Environmental Decision Support Software. DecisionFX, 

Inc., GroundwaterFX, EPA/600/R-00/037. (www.epa.gov/etv/verifrpt.htm) 

Sullivan, T., A.Q. Armstrong, A.B. Dindal, R.A. Jenkins, J. Osleeb, and E.N. Koglin (2000c). 

Environmental Technology Verification Report. Environmental Decision Support Software. DecisionFX, 

Inc., SamplingFX, EPA/600/R-00/038. (www.epa.gov/etv/verifrpt.htm) 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 29 

Sullivan, T., A.Q. Armstrong, A.B. Dindal, R.A. Jenkins, J. Osleeb, and E.N. Koglin (2000d). 

Environmental Technology Verification Report. Environmental Decision Support Software. C Tech 

Development Corporation, Environmental Visualization System (EVS), EPA/600/R-00/047. 

(www.epa.gov/etv/verifrpt.htm) 

Tonn, B., Turner, R., Meckling, J., Fletcher, T. and Barg, S., (1999). Environmental Decision Making and 

Information Technology: Issues Assessment. NCEDR, Knoxville, USA,. Report NECDR/99-01 

USEPA, 1989. U.S. Environmental Protection Agency, 1989. “Risk Assessment Guidance for Superfund 

Volume I Human Health Evaluation Manual (Part A) Interim Final,” Office of Emergency and Remedial 

Response, Washington, D.C. EPA/540/1-89/002. 

USEPA, 1995. United States Environmental Protection Agency, (1995). “Guidance for Community 

Advisory Groups at Superfund Sites,” EPA-540-K-96-001, 

USEPA, 1996a. United States Environmental Protection Agency, 1996. Soil Screening Guidance: 

Technical Background Document. Office of Emergency and Remedial Response, Washington, D.C., 

EPA/540/R-95/128. (www.epa.gov/superfund/pubs.htm#h) 

USEPA, 1996 b. United States Environmental Protection Agency, 1996. Soil Screening User’s Guide. 

Office of Emergency and Remedial Response, Washington D.C., EPA/540/R-96/018. Second Edition. 

(www.epa.gov/superfund/pubs.htm#h) 

USEPA, 1997. United States Environmental Protection Agency, 1997. Ecological Risk Assessment 

Guidance for Superfund: Process for Designing and Conducting Ecological Risk Assessments. Interim 

Final. EPA 540-R97-006, OSWER 92857-25, PB 963211. 

(www.epa.gov/oerrpage/superfund/programs/risk/ecorisk/ecorisk.htm)

USEPA, 1998a. United States Environmental Protection Agency. (1998). NATO Committee on 

Challenges to Modern Society: NATO/CCMS Pilot Study Evaluation of Demonstrated and Emerging 

Technologies for the Treatment and Clean Up of Contaminated Land and Groundwater. Phase III 1998 

Special Session Treatment Walls and Reactive Barriers. No 229. EPA Report: 542-R-98-003 

USEPA, 1998b. United States Environmental Protection Agency, (1998). “Superfund Community 

Involvement,” EPA-540-R-98-027, OSWER 9205.5-12A, PB98-963235. 

(www.epa.gov/superfund/pubs.htm#h) 

USEPA, 1999. United States Environmental Protection Agency, (1999). NATO Committee on Challenges 

to Modern Society: NATO/CCMS Pilot Study Evaluation of Demonstrated and Emerging Technologies 

for the Treatment and Clean Up of Contaminated Land and Groundwater. Phase III 1999 Special Session, 

Monitored Natural Attenuation. No 236. EPA Report: 542-R-99/008. 

USEPA, 2000. U.S. Environmental Protection Agency “Ecological Soil Screening Level Guidance 

DRAFT, “ Office of Emergency and Remedial Response , Washington, DC, July 10, 2000, 

www.epa.gov/superfund/programs/risk/ecorisk/ecossl.htm 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 30 

APPENDIX: MULTI-CRITERIA ANALYSIS 

Multi-criteria Analysis (MCA) is often used in decision making. MCA is a structured system for ranking 

alternatives and making selections and decisions. Considerations are: how great an effect is (score) and 

how important it is (weight). A general outline of the MCA method is shown in Figure A.1. MCA goes 

one step further than a decision matrix by allowing scores to be combined into overall aggregates and 

allowing scores to be weighted. With MCA, ranking and decision making processes can be made very 

transparent. 

Figure A.1. A General Outline of the MCA Method 

Taken from: Bardos, R.P., Nathanail, C.P., and Weenk, A. (1999) “Assessing the Wider Environmental 

Value of Remediating Land Contamination.” Environment Agency R&D Technical Report P238. 

Available from: Environment Agency R&D Dissemination Centre, c/o WRC, Frankland Road, Swindon, 

Wilts SNF 8YF.
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 31 

GEOSPATIAL DECISION FRAMEWORKS 

FOR REMEDIAL DESIGN AND 

SECONDARY SAMPLING 

Robert Stewart, University of Tennessee, USA 

University of Tennessee, 804 Volunteer Blvd, Knoxville, TN 37996

INTRODUCTION 

This paper provides an overview of geospatially-based decision frameworks for remedial and secondary 

sampling design strategies. These methods were generated or implemented during the construction of 

Spatial Analysis and Decision Assistance (SADA), a freeware package for Windows. SADA is supported 

by the Environmental Protection Agency and the Department of Energy. For more information on SADA 

or on the methods described here, see http://www.sis.utk.edu/cis/sada/. 

Although the remedial design frameworks are quite straightforward, they rely on geospatial and human 

health risk modeling results that are beyond the scope of this paper. Therefore, this paper only presents 

how output from the modeling practices can be used explicitly in a decision-making process. 

Additionally, a general overview of geospatial analysis provides context for the methods. Three remedial 

design approaches are presented: block scale, site scale, and site-block scale. Each framework has 

important implications for both risk assessment and remedial design, and in practice each has better 

defined the area of concern and ultimately saved valuable resources during the remedial process. 

Similarly, the sampling designs in this paper rely on the same geospatial models. These secondary 

sampling designs assume that a round of sampling has already occurred, a geospatial model has been 

chosen, and a goal for taking another round of samples has been decided. Five distinct sampling strategies 

are presented, each with a separate goal. 

OVERVIEW OF GEOSPATIAL ANALYSIS 

For this paper, geospatial analysis refers to the modeling of concentration values or uncertainty at points 

that have not yet been sampled. Geospatial models estimate or predict the value of a contaminant at an 

unsampled point based on nearby sample values, spatial correlation, and a number of other possible 

parameters depending on the method chosen. These models are often called contouring algorithms and 

include well-known methods such as inverse distance weighting and minimum tension gridding. Other 

increasingly popular methods for environmental characterization include ordinary kriging, indicator 

kriging, and co-kriging. These geostatistical methods contour concentration values and also provide a 

model of uncertainty about those predicted concentration values through the use of spatial covariance 

models. For more information on this subject, see Applied Geostatistics3

, GSLIB4, or Geostatistics for 

Natural Resources Evaluation5

. 

In most cases, a geostatistical analysis begins by defining a grid over the site. 

 

3

 Issaks and Srivasta, Applied Geostatistics, Oxford University Press, 1990. 4

 Deutsch and Journel, GSLIB, Oxford University Press, 1997. 5

 Goovaerts, Geostatistics for Natural Resources Evaluation, Oxford University Press, 1997. 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 32 

 

Figure 1. Defining a grid over a sampled site. 

The blocks formed by this grid become the basis for remedial design and for secondary sampling 

strategies later. Once the grid is in place, a spatial model is run and the site is contoured. 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 33 

Figure 2. Contouring a gridded site with a geospatial model. 

REMEDIAL DECISION FRAMEWORKS 

Given a spatial model of concentration values, three frameworks are available for determining the 

remedial design: block scale, site scale, and the site-block framework. Each framework has a separate 

objective for remediation, can give a significantly different result depending on the spatial distribution of 

contamination, and is connected to a decision criteria. This criteria may include a cleanup concentration 

goal, a human or ecological risk goal, or a state or federal guideline for maximum concentration values. 

Depending on the geospatial model utilized, other goals may be a part of the criteria, including a 

confidence level about the remedial design. Once a criteria is available, it is straightforward to implement 

the following design strategies. 

Block Scale 

In the block scale framework, the decision criteria is applied to each block. In other words, each block 

must pass the acceptable criteria or be remediated. Choices for the block size include the exposure unit 

and the remedial unit size. 

Site Scale 

The site scale framework requires a region or subset of blocks to meet the decision criteria. In this case, 

the blocks may be equal in size to the remedial unit if the region is itself the exposure unit. In particular, if 

a representative statistical value of the blocks (e.g., average value or mean) fails to pass the acceptable 

criteria, then remedial action must be taken on the region. Under this system, the blocks are ordered from 

most to least contaminated. The blocks are then remediated from worst to best until the selected statistical 

value is below the acceptable criteria. This is a powerful approach that operates nicely under the concept 

of exposure unit within risk assessment . Under this concept, only the worst blocks are removed until the 

risk to an individual or species exposed to the entire site or exposure unit area is below a target risk level. 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 34 

This framework, however, may result in individual blocks exceeding the target risk value. This issue is 

addressed in the site-block framework. 

Site-Block Scale 

In this approach, there are two decision criteria. The first is the acceptable site value and the second is the 

acceptable block concentration. First, the site scale is applied to reduce the site wide exposure level to a 

suitable value. Next, a review of remaining block values is performed to determine if any single block 

value exceeds the maximum concentration value. If so, the block scale framework is applied until the 

maximum remaining block value is less than the second constraint. From a risk perspective, this may be 

the most appealing framework because the exposure unit risk is acceptable and unacceptable hot spots are 

removed. 

Ultimately, this framework is reduced to either the site scale or block scale framework in practice. The 

site-block framework is effectively the block scale framework when the site scale fails to remediate far 

enough to meet block scale requirements. Conversely the site-block framework is equal to the site scale 

framework when enough blocks are remediated such that the maximum contamination remaining also 

satisfies the block scale framework. 

Example 

Consider the following site contaminated with Arsenic. The human health risk assessment has established 

that for an industrial landuse scenario, the target carcinogenic risk will be set at 1E-6, corresponding to an 

exposure value 3.5pCi/g. The following figure shows the location of samples. Those enclosed by boxes 

exceed the target risk limit. 

Figure 3. Location of sample points exceeding acceptable risk level 

Through stakeholder discussions, the value 3.5 pCi/g becomes a cleanup goal. A geospatial analysis is 

performed on the site, yielding the following contour map. 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 35 

Figure 4. Geospatial contour of Arsenic concentrations across the site. 

At this point, any of the decision frameworks may be applied. The framework must be chosen with a 

cleanup goal in mind. 

In the block scale framework, any block exceeding 3.5pCi/g will be remediated. The following figure shows 

the remedial design for this framework. The areas shaded in gray must be remediated. 

Figure 5. Remedial zone for the block scale framework. 

Using the site scale framework, the worst areas are remediated until the site average concentration drops 

below the target risk value. This corresponds to the site-wide risk dropping below 1E-6. 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 36 

Figure 6. Remedial zone for the site scale framework. 

For the site/block framework, stakeholders decided that the site-wide risk must be less than 1E-6 risk 

(which corresponds to a site wide average concentration of less than 3.5pCi/g) and the contamination for 

each block must be less than twice this concentration value. Thus our site scale goal is 3.5 pCi/g and our 

block scale goal is 7pCi/g. The site/block framework results in the following design. 

Figure 7. Remedial zone for the site-block scale framework. 

By comparing Figure 7 with the site scale result for 3.5 pCi/g (Figure 6), the site/block framework is 

reduced to the block scale with a cleanup goal of 7pCi/g. 

SECONDARY SAMPLING STRATEGIES 

Geospatial modeling routines open avenues into other decision frameworks in sampling design. In a 

geospatially-based design, the contouring methods provide a model of concentration values or uncertainty 

at each point across the site. With this result, a suite of sampling strategies is available with unique goals 

for taking additional samples. 

In an ideal situation, the sampling design strategies described here would select a location for a new sample, 

the sample would be taken, and the result would be analyzed and put back into the model to produce the 

next optimal sample location. Under this ideal situation, the following sampling strategies could drive a 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 37 

sampling effort in real time. This is possible for sampling devices with quick turn around capabilities and 

has been a useful option on some sites already. 

Figure 8. Flow for chart for using geospatial analysis to drive a sampling design in real time. 

Without quick response time, the method must be able to predict the optimal location of several samples 

at once. This is achieved with simulated sampling. In other words, if multiple new samples are requested, 

the most optimal location is chosen first, and a modeled sample value is taken at that point and treated as 

if it where a true sample. The model is rerun, and the next optimal location is chosen for the second 

sample point. This is repeated until the number of samples requested is generated. Although the accuracy 

of each additional request is reduced as more and more dependency is placed on modeled values, this 

sampling is a valuable alternative when faced with producing a plan for multiple samples at once. 

Five sampling strategies are demonstrated on the following sample site. The suggested new sample 

locations are highlighted with circles. Each block center becomes a candidate for a new sample location. 

Figure 9. Gridded site used for building a secondary sampling design. 

Adaptive Fill 

The goal of this strategy is to fill spatial data gaps by sampling in those areas where data are far apart 

relative to the rest of the set. It is easy to implement this strategy because it is not dependent on a 

contouring method. 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 38 

Figure 10. Adaptive fill results. 

Estimate Rank 

The goal of estimate rank is to place new sample locations where the highest concentrations are predicted 

to be. This corresponds to a confirmation type sampling design. The result is a design that will determine 

if the area has relatively high concentration values – hot spot confirmation. 

 

Figure 11. Concentration Contours and estimate rank results. 

Variance Rank 

This sampling strategy is based on the ordinary kriging method, where model variances are produced 

along side concentration estimates. These two quantities define a distribution of possible concentration 

values at each point. This sampling strategy will place new samples where the model variances are the 

highest and will result in a sampling design that reduces modeled variability. 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 39 

Figure 12. Model variances and variance rank sample design. 

Percentile Rank 

Geostatistical routines, such as ordinary and indicator kriging, will provide a distribution of possible 

concentration values at any unsampled point. This distribution describes the magnitude and variability in 

the modeled response to the sample data. In percentile rank, the goal is to identify those points with the 

potential to have extremely high value due to the span of the distribution rather than those points that have 

the highest predicted value (usually corresponds to the mean type value for geostatistics). This approach 

is useful to sample for potential hotspots. The following figure is based on the 90th percentile. 

Unfortunately, a graph of the 90th percentile map is not available. 

Figure 13. Percentile rank results 

Uncertainty Rank 

The uncertainty rank, like variance and percentile rank, assumes a geostatistical approach to contouring 

has been utilized. Uncertainty rank differs from the former methods in that it is directly connected to a 

decision criteria. In uncertainty rank, new samples are placed where the model is most uncertain about 

exceeding the specified criteria (i.e., Prob > Criteria ~ .50). This is primarily useful for delineating the 

boundaries of the area of concern. 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 40 

Figure 14. Probability of exceeding risk limit and resulting uncertainty rank sample design. 

Secondary Engineering Constraint 

For all strategies except adaptive fill, a secondary constraint is often required to create a viable sampling 

design. In each case, the mathematically optimal location is selected as the next new sample location. 

This location may be extremely close to another sample and therefore not practically optimal. As a result, 

a minimum distance constraint may be useful. In this secondary engineering constraint, new samples are 

forced to be separated from existing data as well as themselves by a specified distance. This results in 

sampling designs that optimize with respect to a design goal while spreading samples apart to also give 

better spatial coverage within the area of interest. A secondary constraint of 100 feet was used for all the 

examples in this section. 

Figure 15. Secondary distance constraint. The limiting sphere applies to all new and old samples. 

When to Stop Sampling: A Value of Information/Economic approach 

A number of criteria for when to stop sampling are available. Most are statistically based and assume 

independence among the data or require the user to know something about the sampled object. A straightforward "economic value of information" approach may provide another tool for determining when to 

stop sampling. This approach integrates the geospatial analysis, decision criteria, sampling design, and 

cost. Simply stated, when new samples are not producing new information, sampling may stop. 

This approach is presented in this paper from the perspective of geospatial and decision analysis. The 

particulars of what is meant by "no new information" will vary widely within characterization studies. 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 41 

In the following exercise, the concept of "value of information" is demonstrated with a simple geospatial 

analysis. The modeling results are shown for each round of sampling. As the number of samples 

increases, the model changes less. 

Figure 16. Subsequent analysis result with each round of new samples. 

With each new sample, less new information is provided to the process. In fact, upon visual inspection, 

one can see that the difference between 40 and 50 samples if very little. The implications of using this 

approach are great for remedial design. For sampling designs that intend to refine the remedial process 

this approach is directly applicable. 

CONCLUSION 

Geospatial analyses can have an explicit and influential impact on environmental decision making 

processes. Delineating information within a spatial context aids in the definition of many decision 

processes and the quantification of their impact on cost and risk reduction. These impacts can result in 

enormous cost savings over traditional approaches. The methods presented in this paper represent the 

basic approaches in this area; more methods are being developed. All the described methods are available 

in the SADA software package, which can be freely downloaded at http://www.sis.utk.edu/cis/sada/.
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 42 

DECISION SUPPORT TOOLS: APPLICATIONS 

IN REMEDIATION TECHNOLOGY 

EVALUATION AND SELECTION 

S. Vranes, E. Gonzalez-Valencia, A. Lodolo, S. Miertus, International Centre 

for Science and High Technology 

United Nations Industrial Development Organization (ICS-UNIDO) Padriciano 

99, 34012 Trieste, Italy 

ABSTRACT 

Soil remediation is a difficult, time-consuming and expensive operation. A variety of mature and 

emerging soil remediation technologies is available and future trends in remediation will include 

continued competition among environmental service companies and technology developers, which will 

definitely result in further increase in the clean-up options. Consequently, the demand has enhanced 

developing decision support tools that could help the decision makers to select the most appropriate 

technology for the specific contaminated site, before the costly remedial actions are taken. Therefore, a 

Decision Aid for Remediation Technology Selection (DARTS) is currently being developed with the aim 

of closely working with human decision makers (site owners, local community representatives, 

environmentalists, regulators, etc.) to assess the available technologies and preliminarily select the 

preferred remedial options. The analysis for the identification of the best remedial options is based on 

technical, financial, environmental, and social criteria. These criteria are ranked by all involved parties to 

determine their relative importance for a particular project. 

Key words: decision support tools, multicriteria optimization, soil remediation 

INTRODUCTION 

Remediation of contaminated soils is a field of technology that has developed and grown recently. 

Development and use of remediation technologies has progressed and a large number of clean-up 

alternatives have evolved and improved over the past decade. In addition, the technology developers and 

environmental service companies have sprung up in the hope of secure a place for their process in the 

market. Therefore, there has been a remarkable decrease in unit cost for land treatment options. 

Remediation has become affordable, allowing owners of small- and medium-sized contaminated sites to 

undertake soil clean-up programs in a more cost–effective manner. However, both site owners and 

environmental managers confront the challenge of making decisions to select and deploy the most 

suitable soil remediation technologies to address a variety of problems and, in some cases, satisfy a 

number of conflicting criteria. 

These choices are increasingly more complex because a greater variety of contamination problems are 

being defined and innovative technologies are becoming available every day as potential (sometimes 

cheaper and/or more effective) alternatives to existing technologies (1-3). Innovative remediation 

technologies, which lack a long history of full-scale applications, do not have, in some cases, the 

extensive documentation necessary to make them a standard choice in the engineering/scientific 

community. However, many innovative technologies have been successfully used at contaminated sites in 

the United States, Canada, and Europe despite incomplete verification of their overall performances. 

Some of the technologies were developed in response to hazardous waste problems and some have been 

adapted from other industrial uses. Only after a technology has been used at many different types of sites, 

and the results fully documented and assessed, it is commonly considered as a well-established 

technology. 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 43 

Decision makers are also asked to integrate information about remedial options and are required to 

balance information about technology performance with limited budgetary resources and regulatory 

constraints. In addition, information about the concerns of stakeholders, as well as their meaningful 

involvement in the larger decision process, influences the ultimate technology selection and deployment 

decision. Therefore, all involved parties (environmentalist, policy makers, local community 

representatives, site owners, other stakeholders) need some tools to help them assembling and 

synthesizing information to respond to these challenges and conflicting issues. 

Therefore, this problem has been chosen to develop DARTS in order to perform evaluation and 

comparison of technologies for environmental remediation. DARTS provides a set of criteria for 

evaluating technologies to address site-specific clean-up activities, and would accomplish the following 

tasks: 

• To enable users to identify and systematically compare information about innovative and 

conventional technologies to meet remediation goals, highlighting their strengths and weaknesses 

• To establish a structure of technology evaluation and selection process, which simplifies the 

decision-making and streamlines the variety of factors involved in the remediation process 

• To define consistent, qualitative and quantitative indicators for key technical, environmental, 

economic, and legal criteria that influence selection and deployment of technologies 

• To provide documented, reproducible evaluation which can be updated as needed information 

becomes available 

• To provide flexible, multicriteria optimization approach allowing trade-offs among criteria on the 

basis of contaminant type and site-specific needs 

• To enhance communications and help focus dialogue between local community, environmental 

managers and stakeholders, including regulators and policy makers 

• To enable explanation and justification of the choice by offering evidence on the advantages and 

disadvantage of the possible choices in a concise and consistent way. 

• To fasten development of feasibility study of the remedial options 

• To provide site owners, environmental managers and other stakeholders with the opportunity to 

explore alternative options, etc. 

Before a treatment technology can be selected for a contaminated site, detailed information about the site 

and contaminants characteristics must be collected. DARTS uses this information to determine which of 

the possible remedies will be capable of meeting the clean-up standards set by its users, respecting the 

previously mentioned constraints (technical, economical, legal, etc.). The following section will further 

clarify the role of DARTS in supporting remedial actions. 

DARTS functionality

Remedial actions usually involve these main tasks: 

• Site discovery, preliminary assessment, and site inspection, conducted to quickly determine if 

there is a contamination problem. 

• Site assessment that determines the type and extent of contamination 

• Evaluation of clean-up alternatives, and selection of remediation technology, based on the type 

and extent of contamination, clean-up time required, physical, and geological site characteristics, 

available technologies, resource requirements, social acceptance, and compliance with federal 

and state laws, etc. 

• Site clean-up, application of selected remediation technique, and 

• Site closure and compliance monitoring, ensuring that the identified contamination problems 

have been adequately addressed 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 44 

DARTS aims at providing a decision support for the evaluation of clean-up alternatives and selection of 

the best available technology for the site concerned, simultaneously taking into account a number of 

different technical, economic, social, legal and environmental criteria. Each criterion could be weighted 

by the panel of experts, environmental managers, technology providers, policy makers, local community 

representatives, to capture its relative importance in the overall balance. 

There are many actors in the decision-making process, which have their own interests and perspectives. 

For instance, the person(s) responsible for contamination and the owner of the polluted plot of the land 

can be mainly interested in the financial issues, while the user of the plot and the direct environment, 

including nearby residents, are mainly interested in health and environmental issues. Another group is 

composed by representatives of public bodies. They should consider the overall interests, which includes 

socio-economic and environmental issues. 

The aim of DARTS is working with all mentioned actors to perform a preliminary selection of the most 

efficient remediation technologies, by analyzing simultaneously some key criteria of available remedial 

techniques. These criteria can be ranked by all involved parties to determine their relative importance for 

a particular project. 

Multicriteria analysis of all these factors determines whether a remediation strategy is a feasible, effective 

and efficient solution and whether it satisfies all criteria and constraints defined by the user. Depending 

on the context in which remediation technology assessment and selection are performed, the users can 

tailor decision strategy balancing out various effectiveness and efficiency parameters, other criteria and 

constraints. From the user’s point of view, a general algorithm for DARTS analysis is described in Figure 

1. 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 45 

An example of practical approach using DARTS is when applying a soil remediation decision tree (4) 

(Figure 2); in this case, the user is able to analyze and compare subgroups of technologies, or to compare 

technologies within the same subgroup. The technologies available in the current stage of DARTS are 

indicated in Figure 2. This approach also applies for groundwater remediation programs, which can be 

integrated in the remediation decision tree supported with DARTS. 

The user selects one ore more target contaminants and

defines 

il *

The program displays the classified tree of available

technologies for the specific contaminants and soils, 

and the classified tree of criteria

The user rates each criterion depending how critical it is

considered (weight ranges between 0 and 100%) 

From the tree of technologies the user removes

technologies or groups of technologies that doesn’t want to

id

Multicriteria analysis is performed and recommended

technologies are shown and sorted (together with ranked

alternatives)

Want to iterate again? 

The user selects a remediation technology 

No 

Yes 

* Soil type option in current implementation 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 46 

Figure 2. Soil remediation decision tree supported with DARTS. 

CRITERIA TO ASSESS AND SELECT REMEDIATION TECHNOLOGIES 

DARTS’ user selects a subset of technologies in which is interested, or uses a full set of technologies and 

ranked criteria (6,7); selects the criteria, preference functions (or use default functions chosen by the 

DARTS developers) and corresponding weighting factors, defines the contaminant (or a group of 

contaminants), soil type and then performs a multicriteria analysis. 

The criteria included in the current stage of DARTS prototype are applicability, overall cost, minimum 

achievable concentration, clean-up time required, reliability and maintenance and public acceptability 

(that varies depending on the country and site location); two more criteria are currently being 

implemented: by-products/wastestreams post treatment required and decontaminated soil quality. A 

numerical rating of 1 (= better), 2 (= average) or 3 ( = worse) is given to each technology in each category 

(6). These categories are taken from the ratings reported in UN-ECE Compendiums of soil remediation 

technologies (6,7), and are mainly based on the US-EPA’s evaluations. The categories are briefly 

explained below. 

Overall cost. Includes design, construction, operation and maintenance costs of the core process that 

defines each technology. It does not include site preparation or post-treatment costs. Excavation costs of 

$55/metric ton are assumed for ex situ technologies. 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 47 

Ratings: 1= Less than $110/metric ton; 

2= $110 - $330/metric ton; 

3= More than $330/metric ton 

Minimum achievable concentration. Refers to the minimum pollutant concentration achievable by the 

technology. 

Ratings: 1= Less than 5 mg/kg soil; 

2= 5-50 mg/kg soil; and 

3= More than 50 mg/kg soil 

Clean-up time required. This refers to a "standard" site of .41 hectare and 3.04 m depth. The soil mass is 

18,200 metric tons. 

Ratings for ex situ techniques: Ratings for in situ techniques: 

1= Less than 6 months; 1= Less than 1 year; 

2= 6 months -1 year; and 2= 1-3 years; and 

3= More than 1 year. 3= More than 3 years. 

Reliability and maintenance. Refers to the level of complexity of the system or technology, and how easy 

it is to maintain. 

Ratings: 1= High reliability and low maintenance; 

2= Average reliability and maintenance; and 

3= Low reliability and high maintenance 

Public Acceptability 

Degree to which the technology is acceptable to the public. This category can, of course, vary widely 

depending on the country and the level of community involvement. 

Ratings: 1= Minimal opposition from the community is likely; 

2= Public involvement usually occurs, but the technology is generally accepted; 

3= Serious public involvement is likely and the outcome is uncertain. 

Other ratable criteria that will be included in the system prototype are: data needs/characterization (refers 

to the extent of pre-remediation investigations) and safety requirements (refers to the measures required to 

ensure safety of workers, public and environment). 

MULTICRITERIA ANALYSIS ALGORITHM 

A multicriteria analysis performed by DARTS is the process during which the relative merits of the 

remediation alternatives are compared to each other and the most appropriate is selected from among 

them for site clean-up implementation. 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 48 

There are a number of fundamental problems when there are multiple objectives. For instance, consider 

the case where there are a number of decision makers, each with a preference ordering over a number of 

alternatives. The goal is to choose the ``fair'' alternative that aggregates the preferences of the decision 

makers. This is an example of multiple criteria decision making (each decision-maker represents one 

criterion), and those objectives need to balance in a fair way. The situation is even more complicated 

when there are also multiple and even conflicting criteria like in the DARTS (where for instance, 

minimizing cost and clean-up time could be conflicting requirements). The decision-maker is asked to 

specify goals and relative weightings for the different criteria. Relative weightings are used to find most 

preferred solutions. The weighting can be changed to assess sensitivity of solution or to reflect different 

opinions. 

The explicit consideration of multiple, even conflicting objectives in a decision model has made the area 

of multiple criteria decision-making (MCDM) very popular among researchers during the last two 

decades. It is quite conceivable that certain modifications in the existing MCDM procedures provide the 

long awaited bridge between the important fields of Operations Research and Decision Support Systems. 

In order to support the decision maker that must solve multicriteria problems, three kinds of methods 

were essentially considered - aggregation methods using utility functions, interactive methods and 

outranking methods. In our work, we adopted the last ones, actually a special outranking method, based 

on extensions of the notion of criterion (5) (PROMETHEE I, providing a partial preorder, and 

PROMETHEE II, providing a total preorder on the set of possible decisions). 

These extended criteria can be easily defined by the decision maker, because they represent the natural 

notion of intensity of preference, and the parameters to be fixed (maximum 2) have a real world meaning. 

The extension is based on the introduction of a preference function, giving the preference of the decision 

maker for an action a with regard to b. This function is defined separately for each criterion, where its 

value is between 0 and 1 (meaning a range between 0 and 100%), within the same defined criterion. The 

smaller the function, the greater the indifference of the decision maker; the closer to one, the greater his 

preference. In case of strict preference, the preference function is 1. Numerous practical applications of 

the PROMETHEE method have shown that it is very easily accepted and understood by the practitioners, 

being the easiest approach for solving a multicriteria problem by considering simultaneously extended 

criteria and outranking relations. 

A preference function, Pab h(, ), is usually presented by a function p x( ): 

px x x f a f b ( ): [ , ] ( ) ( ) → =− 0 1 and , 

where f a( ) and f b( ) represent the values of a particular criterion, h, for actions a and b respectively. 

Using a preference index, π(, ) a b , we can determine the preference for a with regard to b over all 

criteria: 

π(, ) (, ) a b

W

WP a b

h

h h

h

k

h

k

 =

=

= ∑

∑ 1

1

1

where k represents the number of criteria, Wh is a weight for the criterion h, and Pab h(, ) is the 

preference function for the criterion h. 

A valued outranking graph consists of nodes represented by actions and arcs, where each arc (, ) a b has a 

value π(, ) a b . When obtained, the valued outranking graph offers a decision-maker means for 

determining a partial preorder (PROMETHEE I), or a total preorder (PROMETHEE II). 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 49 

In order to rank the actions by a partial preorder, we must evaluate the outgoing flow: 

φ π +

∈

() (, ) a ax = ∑

x K

, 

where K is the set of all actions, and the incoming flow: 

φ π −

∈

() (, ) a xa = ∑

x K

. 

The outgoing flow φ+ ( ) a describes the degree to which a dominates the other actions in K, while the 

incoming flow φ− ( ) a represents the degree to which a is dominated. Using the outgoing and incoming 

flows, the two total preorders (P+, I+), and (P-, I-) can be defined, such that: 

a P b if (a) (b), + + + φ > φ

a P b if (a) (b); − − − φ > φ

a I b if (a) (b), + + + φ = φ

a I b if (a) (b). − − − φ = φ

Then the partial preorder (P(1), I(1), R) can be determined by considering their intersections: 

and are incomparable ( ) otherwise.

isindifferent to ( ) if and ,

and ,

and ,

and ,

outranks ( ) if 

(1)

(1)

































+ −

+ −

+ −

+ −

a b a R b

a b a I b a I b a I b

a I b a P b

a P b a I b

a P b a P b

a b a P b

The net-flow: φ() () () a aa = − φ φ + −

is used to rank the alternatives by a total preorder (P(2), I(2)): 









=

>

isindifferent to ( ) if ( ) ( ).

outranks ( ) if ( ) ( ),

(2)

(2)

a b a I b a b

a b a P b a b

φ φ

φ φ

DARTS EXPERIMENTAL PROTOTYPE 

A laboratory prototype of DARTS has been developed as JAVA application, using Symantec Visual Café

dbDE development environment. 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 50 

The DARTS presents its users with a variety of configuration and input parameters from which to choose. 

Several are mandatory (such as identifying technologies to be evaluated), but there are many that the user 

can choose to leave blank or use the supplied default values. This way, the user decides how to tailor the 

analysis to satisfy specific needs. 

Prototype configuration and data entry process involves several tasks: 

• Entering available technologies and their descriptions 

• Entering criteria to be considered simultaneously 

• Setting values of chosen criteria and selecting the type of preference function for each criterion 

The application’s main window (Figure 3) consists of the current state of configuration, and a few dialogs 

for data entry purposes. It is connected to the database that contains previously entered information on 

available technologies and selection criteria; database should be registered by the user and/or software 

administrator. An application window consists of the following sections: 

• Technologies tree structure 

• Buttons for manipulating nodes of the technologies tree 

• Criteria tree structure 

• Buttons for manipulating nodes of the criteria tree 

• Button for setting values of the selected criteria 

• Button for starting multicriteria decision making process 

• Button for selecting contaminants for multicriteria decision making process 

A dialogue box requesting the user to select the technologies to be simultaneously evaluated and 

compared with one another is shown in Figure 3. 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 51 

Figure 3. Main application window

A dialogue box Technology Properties (Figure 4) is used for entering and updating information on 

particular technology. It consists from a few text fields and standard OK and Cancel buttons. Main fields 

are for technology identification code, name and description. Three other text fields are disabled, and they 

are used for presentation of multicriteria analysis results. Radio buttons On and Off are used for 

including/excluding selected technology in multicriteria analysis. 

A dialogue box Criterion Properties (Figure 5) is used for entering and updating attributes of particular 

criterion. It consists of several text fields, four radio buttons, and standard OK and Cancel buttons. Main 

fields are for criterion identification code, name, weighting factor, function ID, i.e., he identification code 

of the selected preference function for the criterion, and its parameters. Radio buttons On and Off are used 

for including/excluding selected criterion in multicriteria analysis. Min and Max radio buttons show 

whether selected criterion is maximized or minimized. 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 52 

Figure 4. Technology properties dialogue box. 

Figure 5. Criterion properties dialogue box.
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 53 

A dialogue box Criterion-Technology Properties (Figure 6) is used for entering and updating a value of 

the specific criterion for selected technology. 

Figure 6. Criterion-Technology properties dialog box. 

A window Technology Criteria Overview (Figure 7) is used to overview the values of all selected criteria 

for particular technology. 

Figure 7. Complete Technology criteria overview

A window Multicriteria analysis results (Figure 8) is used for the presentation of the results of 

multicriteria analysis process. The best technology (with maximum net flow) is emphasized using red 

color. Here, the decision has been made upon the arbitrary choice of input parameters, so the results must 

not be taken seriously. 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 54 

Figure 8. Multi-Criteria analysis results 

Please note that the above results are obtained for arbitrary set of contaminants, selection criteria and their 

values and preference functions. Soil Vapor Extraction Technology has been recommended as the best 

choice for this random selection of input parameters. We deliberately avoided presentation of the real 

world, interactive decision-making session with DARTS. 

DARTS TESTING 

Several tests have been made in order to verify the accuracy of DARTS results against reported real cases. 

Some criteria considered by Brownfields Technology Support Center (8) for selecting and recommending 

remediation technologies for the Union Pacific Railroad Site (UPRS), Clinton, Iowa, are presented in 

Table1. 

In the first step, the conditions measured in the study case were translated to parameters in DARTS, 

which are presented in Table 2. In order to make the DARTS analysis results comparable to those of 

Brownfields, the analysis was separately performed for each group of contaminants (VOCs and heavy 

metals). 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 55 

Table 1. Parameters obtained from Environmental Assessments performed on 

UPR Site, Clinton, Iowa. 

Criteria / Parameter Description 

Applicability 

VOCs and Petroleum 

hydrocarbons in soil and 

groundwater 

Arsenic in soil 

Arsenic and lead in groundwater 

Risk-based clean-up level 

* 

22 ppm (benzene in soil) 

0.36 ppb (benzene in gw.) 

3.8 ppm (arsenic in soil) 

0.045 ppm (arsenic in gw) 

50 ppm (lead in gw) 

Clean-up time required < 1 year < 1 year 

Cleaned soil availability To be used as a light industrial and/or commercial retail area 

 

Table 2. Criteria translated to parameters in DARTS. 

Criteria / Parameter Description

Weight ( % )

Applicability VOCs / Hydrocarbons 

100% 

Heavy metals 

100% 

Minimum achievable 

concentration 

5 – 50 mg/kg (benzene)+ 

>50 mg/kg (other hydrocarbons) 

30 – 50% 

< 5 mg/kg (arsenic) 

100% 

Clean-up time required < 1 year 

50% 

< 1 year 

50% 

+Benzene concentrations detected during Environmental Assessments were always below 22 ppm. 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 56 

Table 3. Comparison of recommendations made by Brownfields and 

those obtained with DARTS. 

Brownfields recommendation DARTS Multicriteria Analysis results* DARTS 

ranked list 

VOCs / Hydrocarbons 

Air sparging Thermal desorption 1.302 

Bioremediation (ex-situ) Chemical treatment 1.036 

Bioslurry (ex-situ) † Thermally enhanced soil vapor 

extraction 

1.036 

Bioremediation gw (in-situ) Soil Vapor Extraction/ Air sparging (insitu) 0.770 

Bioventing † Bioreactors 0.770 

Chemical treatment Soil Vapor Extraction (ex-situ) 0.770 

Dual phase extraction † Solvent extraction 0.504 

Soil flushing Land farming 0.504 

Soil vapor extraction Bioremediation (in-situ) 0.504 

Thermal desorption Soil flushing 0.238 

Heavy metals 

Chemical treatment Chemical treatment 1.232 

Phytoremediation Phytoremediation 0.700 

Soil flushing Solidification/stabilization (ex or in-situ) 0.700 

Solidification/stabilization Solvent extraction 0.700 

Solvent extraction Containment systems / Barriers 0.168 

 Soil flushing 0.168 

* “Overall cost” not included as criteria. † Technologies not available in current DARTS prototype. 

DARTS results are presented and ranked in Table 3, and are compared against recommendations made by 

Brownfields. Most of the technologies proposed by DARTS are included in Brownfields 

recommendations, only some variations of Bioremediation (Landfarming and Bioreactors) do not match 

since these technologies are grouped in DARTS as Bioremediation. Soil flushing is ranked on the last 

place, because its low ability to clean until acceptable levels which DARTS considers as more than 50 

mg/kg soil. UPRS case requires between 5-50 mg/kg for benzene and less than 5 mg/kg. 

Some biological remediation technologies (bioremediation in-situ and landfarming) are also classified on 

the last places because of their high times required to complete the clean-up (usually more than 1 year). In 

the UPRS case, it was proposed a restriction of time: less than one year. If the overall cost were 

considered, the bioremediation technologies would increase the ranked level because of its lower cost 

compared to other thermal or physical-chemical technologies. 

Coming to the end, the selection of the remediation technology is a matter of balancing out environmental 

achievements against reasonable cost. Different technologies have different performance, and this holds 

for technical and financial aspects as well as for environmental aspects. The aim of DARTS is to help 

integrating all these aspects and make a comparative analysis of the best available technologies, taking 

into account site-specific requirements, and various criteria set by environmental managers, policy 

makers, site owners and other stakeholders. 

Internet accessible version of DARTS is currently under construction. The client-server architecture 

adopted for Internet version, assumes that all the analysis and database administration is done at the 

server side, while a light client (i.e., a distant user) needs only a standard Web browser and proper 

authorization to access and use the DARTS. 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 57 

ACKNOWLEDGMENTS 

The authors wish to express their gratitude to Vladimir Simeunovic for his precious contribution during 

the development of the experimental prototype of the software. The authors also thank Branislav Opacic 

for his support during the project. 

SUPPORT INFORMATION AVAILABLE 

Information about conventional and innovative remediation technologies is available free of charge via 

the Internet at http://www.environment.gov.au/epg/swm/swtt/contents.html, http://www.frtr.gov and 

http://www.epareachit.com. The Compendium of soil clean-up technologies and soil remediation 

companies, edited by ICS-UNIDO and UNECE, offers three sections: soil clean-up technologies and 

criteria to assess the options, list of web sites describing remediation technologies and a worldwide 

directory of companies dealing with soil remediation. 

Additional information about Multicriteria Decision Making (MCDM) Methodologies can be found in: 

• Buchanan, John T., Erez J. Henig and Mordecai I. Henig (1998), "Objectivity and subjectivity in 

the decision making process", Annals of Operations Research (Issue on Preference 

Modelling),80, 333-345. 

• Buchanan, John T. and James L. Corner (1997), "The effects of anchoring in interactive MCDM 

solution methods", Computers and Operations Research, 24(10), 907-918. 

• Corner, James L. and John T. Buchanan (1997), "Capturing decision maker preference: 

Experimental comparison of decision analysis and MCDM techniques", European Journal of 

Operational Research, 98(1), 85-97. 

• Henig, Mordechai I. and John Buchanan (1997), "Tradeoff directions in multiobjective 

optimization", Mathematical Programming, 78(3),357-374. 

• Buchanan, John (1997), "A naive approach for solving MCDM problems: The GUESS method", 

Journal of the Operational Research Society, 48(2), 202-206. 

• Henig, Mordechai I. and John T. Buchanan (1996), "Solving MCDM problems: Process 

concepts", Journal of Multi Criteria Decision Analysis, 5(1), pp. 3-12. 

LITERATURE CITED 

(1) USEPA, Remediation and Characterization Innovative Technologies (REACHIT), EPA’s 

Technology Information Office, 2000. 

(2) FRTR, Remediation Technologies Screening Matrix and Reference Guide, Third edition, Federal 

Remediation Technology Roundtable, 1997. 

(3) CMPS&F Environment Australia, Appropriate Technologies for the Treatment of Scheduled 

Wastes, Technology Reviews, Review Report Num. 4, 1997. 

(4) Freeman, H.; Hazardous waste treatment and disposal, Castaldi, F., McGraw Hill, 1997. 

(5) Brans, J.P. and Vincke, P., A Preference Ranking Organisation Method, Management Science. 

1985, 31, 647-656.

(6) UNECE, Compendium of soil clean-up technologies and soil remediation companies, first 

edition, New York and Geneva, 1997. 

(7) ICS-UNIDO and UNECE, Compendium of soil clean-up technologies and soil remediation 

companies, second edition, New York and Geneva, 2000. 

(8) Brownfields Technology Support Center, Technical Assistance for the Union Pacific Railroad 

Site, Clinton, Iowa, 1999.
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 58 

COMMON FACTORS IN DECISION MAKING AND 

THEIR IMPLICATIONS FOR DECISION SUPPORT FOR 

CONTAMINATED LAND IN A MULTIOBJECTIVE SETTING

J.P. Okx 

Tauw BV, Research & Development, 

P.O. Box 133, 7400 AC Deventer, The Netherlands 

E-mail: jpo@tauw.nl

ABSTRACT 

Arriving at the best soil remediation alternative involves a decision process. Tools can support some of 

the routines within the decision process. Support, however, is not the same as taking a decision. The 

actual deciding is not provided by a tool, but remains the shared responsibility of the stakeholders. 

Decision processes can be seen as goal-oriented systems. The informationless paradigm – giving it a try - 

is the least powerful in achieving a high performance. The feedback paradigm performs better since it 

allows learning from experience. The feedforward paradigm allows anticipation. The full-information 

paradigm combines the benefits of both the feedback and the feedforward paradigm. Although we like to 

focus on the decision process our attention should be stretched to the resulting remedial actions and 

feedbacks and feedforwards should consequently enable those involved to anticipate and learn from the 

results of the actions. Different stakeholders often have different objectives and, thus, their preference for 

remedial alternatives may differ. Nevertheless multiattribute models are useful tools when trying to make 

a decision. Three decision support tools are discussed in terms of their role in the decision process, the 

way they allow for feedback and feedforward, and, the way they support decision making in a 

multiobjective setting. 

ONCE UPON A TIME ...

Quite a few years ago I had to visit one of our offices in Germany. When I arrived from the Netherlands I 

found a rather depressed team. They just received some very negative comments on what they considered 

as an almost perfect report on a chlorinated hydrocarbon problem. Still unaware of the nature of the 

comments I started reading the report, and after a few hours I had to admit that it was an excellent report. 

It gave very complete and detailed insight in the situation, and I could not detect the flaws. I did some 

more talking with the guys involved, to discover what could be wrong, but it was not very helpful. After 

that I called the problem owner, made an instant appointment, took my bike, and cycled across the Rhinebridge to pay him a visit. The problem owner – an experienced manager – told me that it was the first 

time that he was confronted with contaminated land issues. After a half-hour the problem was a lot 

clearer: the problem owner expected a report listing the complete consequences for his company, and all 

he got was an expensive report that stated that his site was contaminated! It took me another hour to fill in 

the communication gap completely. At the end of our session we made another appointment to discuss the 

remedial options, and I managed to convince him to involve the (city) authorities. Back at the office I 

explained what went wrong, and they were happy that things had been solved. Since I promised the 

problem owner to invite the authorities, the next thing I did was making a phone-call to the city hall. Very 

soon after I got the responsible guy on the telephone I knew that I was talking to a fundamentalist: 

“Multifunctionality! No compromises to the environment!” I started hating myself to involve the 

authorities as early as I did. We had one week to prepare the meeting. My team members worked out a 

number of alternatives: the geohydrologist had worked out a geohydrological containment option, our 

civil engineer had worked out something that would put ‘his’ Caterpillars and Komatsus at work, and our 

chemical engineer came up with an innovative in situ alternative in which phenol was proposed as a cosubstrate for chloroethene degrading bacteria. We just had success with such an alternative in the 

Netherlands, and so I asked our chemical engineer to prepare for the meeting. 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 59 

Finally, we all met to discuss the options. Everybody had spelled every letter of the proposed alternatives. 

Within three minutes the situation was clear: the problem owner made his choice for the containment, the 

cheapest solution; the authorities made their choice for the excavation, the safest but most expensive 

solution; and our chemical engineer expressed his preferences for the smart and elegant in situ alternative. 

The authorities made it perfectly clear that infiltration of things like phenol were forbidden. By law! I 

tried to start a discussion, but after half an hour everybody had disappeared in his own trench. Within the 

hour I had managed to succeed in three things: the problem owner – our client – was confronted with the 

highest remediation costs possible, the local authorities would never accept any Tauw alternative for the 

next decade, and my colleagues would never take any communication lesson from me again. This time 

depression was mine ...

Three weeks later we had the next meeting. By that time I had spend many hours doing my homework, 

and lost my day and night rhythm completely. For each of the alternatives I had figured out the effects 

from every possible perspective. My reasoning, which was based on a newly developed method for the 

comparison of remedial alternatives, pointed out that the cheapest alternative – the geohydrological 

containment – was save, required a lot of energy and renewable sources, but solved little. Moreover, the 

alternative could give problems in case of a future take-over of the site. The safest option – excavation –

was very expensive and required a huge amount of energy and renewable resources. In terms of 

environmental merits the alternative had a negative score. The in situ alternative was not the cheapest, but 

still a lot closer to the price of the containment, than to that of the excavation. It would not yield quite the 

same reduction of pollutant concentration as the excavation, but it would be very close to that. In terms of 

environmental merit it was outperforming the other alternatives completely: low energy use, the use of 

renewable resources was negligible, and so on. Last but not least: with the predicted results, the owner 

could sell the site without any problem, and phenol as co-substrate could be replaced by something more 

acceptable. To make a long story short: we were asked to work out the in situ alternative; it was 

implemented; it took one year longer than predicted; and after four years we all celebrated the completion 

of the project, and we all agreed to publish our bloopers. 

The story above never happened to me as a whole. It was not in Germany. I never did meet such ugly 

caricatures, and I was most certainly not always the hero I liked to be! Yet, I lived through most of the 

scenes that I have combined above: they are scenes of the profession collected all over the place, and I 

feel that the whole story could have happened to me. Fortunately, caricatures such as described do not 

exist, and they never met each other, but some people do at least remind me of these caricatures, and they 

could have met. 

There are patterns in decision making, in the way we anticipate, in the way we learn, and in the way 

people interact when defending their own interest. Such patterns are described within alien sciences such 

as systems science and management. Having the made-up story at hand makes it easier for me to explain, 

and that is exactly why I started as a storyteller. 

DECISION MAKING PROCESSES 

Arriving at the best soil remediation technique involves a decision process. A general model for decision 

processes (Figure 1) is given in Mintzberg et al. (1976). The seven central routines in the figure can be 

linked to the three main phases of decision-making: problem identification, development of problem solving 

alternatives and selection of the best alternative. The identification phase consists of the central routines: 

recognition, in which the problem is recognised and evokes decisional activity and diagnosis, in which the 

decision makers seek to comprehend the evoking stimuli and determine the cause-effect relations for the 

decision situation. In our made-up story the problem owner recognised that he was having a problem, and 

asked a number of experts to work it out. The experts mistook this request for a diagnostic one. They used 

all their skills and tools such as geographical information systems, geohydrological models, laboratory 

experiments to provide the initially unwanted diagnosis. The development phase contains a search routine to 

find ready-made solutions and a design routine to develop tailor-made solutions. This was what the problem 

owner expected, but did not get at first. The selection phase contains a screen routine to reduce the number 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 60 

of generated ready-made solutions, an evaluation/choice routine, which operates in three different modes - 

judgment, bargaining and analysis - and an authorisation routine to obtain approval. This is what happened 

after the first disastrous meeting. We used an analytical tool to compare the different remedial alternatives, 

and bargaining and personal expert judgment did the rest. These phases and routines can also easily be 

identified in most guidelines for contaminated soil (Gotoh and Udoguchi, 1993; Dreschmann, 1992; 

Eikelboom and Von Meijenfeldt, 1985). 

Interrupts – act so as to prevent from proceeding continuously - may occur in the process, originating from 

the decision environment, and can delay, accelerate, stop or restart the decision process. Interrupts are 

caused by disagreement on the need to make a strategic decision. Internal and external interrupts are 

common in soil remediation and are related to the nature of the strategic decision. In our made-up project we 

faced an internal interrupt when the negative comments of the problem owner could not be processed by our 

experts. We faced an external interrupt when the stakeholders could not agree on a solution, and 

consequently could not make a decision. New option interrupts occurring when the decision scope is 

suddenly broadened by technological development or changing policy are less common, but may occur in 

cases of considerable timelag between authorisation and the final realisation of a project. 

Figure 1. A general model for decision processes (Mintzberg et al., 1976)

Seven types of decision processes according the path taken through the Mintzberg's model are identified 

(Mintzberg et al., 1976; Nutt, 1984; Janssen, 1992). Only two of these will be referred to in this paper: 

1. Modified search decision processes consisting of finding and modifying ready-made solutions. 

2. Dynamic design decision processes, involving complex search and design cycles. These are the 

most complex decision processes. 

For most remediation problems ready-made solutions do not exist. Therefore, the search and screen 

routines are always followed by a design routine in which ready-made in situ concepts are modified into 

solutions. Thus, selection of a remedial technology then should be considered as a modified search 

decision process, characterised by a development routine in which in situ concepts are modified into 

tailor-made solutions. 

In some cases the development routine involves complex search and design cycles and encounters 

multiple interrupts. This corresponds to a so-called dynamic design decision process. 

UHF RJ QL

WLRQ

GLD JQRVL V

VHDUFK VFUHHQ

GHVLJ Q

DXWKRUL 

VDWLRQ

MXGJ HPHQW

HY DOXD WL RQ

FKRLFH

DQDO\VL V

HY DOXD WL RQ

EDUJ DLQL QJ

HY DOXD WL RQ

FKRLFH

,'(17,),& $7,21 '(9(/230 (17 6(/(&7,21
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 61 

Tools can support some of the routines within the decision process. This kind of support is defined by 

Bardos et al. (2000) as: the assistance for, and substantiation and corroboration of, an act or result of 

deciding; typically this deciding will be a determination of optimal or best approach. More important 

than the definition is remark that decision support is not the same as taking a decision. The actual 

deciding remains the shared responsibility of those with a legitimate stake in the outcome of the decision, 

i.e., the stakeholders (Bardos et al., 2000). 

1. INFORMATION PARADIGMS 

Decision processes can be seen as goal-oriented systems (Klir, 1991). The most primitive paradigms of 

goal-oriented systems are usually conceived as structure systems with two elements. One of the elements 

is a system in terms of which the goal is defined. It is usually called a goal-implementing element A. 

You could call it the planned action. The other element, which is called the goal-seeking element B, 

generates states of a goal-seeking variable. It is equal to the actual experience. By using experience as an 

additional input to the goal-implementing element, its performance with respect to the goal increases. 

Block diagrams of four paradigms are displayed in Figure 2. 

Figure 2. Four information paradigms

The informationless paradigm – act and hope for the best – is the least powerful in achieving a high 

performance. An example: people trying to sell standard solutions are often working this way. Whatever 

the situation is: they do not want to know about the specific situation, because they cannot anticipate and 

change the solutions they sell. And, as long as they cannot change the product, the performance of their 

solution is of no importance to them. 

The feedback paradigm is less restrictive since it allows utilising information about the output variable. 

In plain English: it allows you to learn. Methods based on this paradigm are well developed. In the madeup story the experience from another project was used to develop the ‘winning’ alternative. Thus, the 

paradigm allows to learn and react, but does not provide for anticipation. 

The feedforward paradigm provides the possibility to anticipate future events. In our made-up story we 

should have anticipated the reaction of the stakeholders involved. 

However, both feedback and feedforward paradigms are inferior to the full-information paradigm. The 

full-information paradigm is the combination of the feedback and the feedforward paradigm. 

Note: anticipation as well as learning can be applied to the reaction of stakeholders, as well as to physical 

phenomena such as the reaction of physical the contaminated soil to remedial actions. Watzlawick et al. 

,Q IRUPDWLRQOHVV

SDUDGLJP

)HHGEDFN

SDUDGLJP

)HHGIRUZ DUG

SDUDGLJP

)XOOLQ IRUPDWLRQ

SDUDGLJP

$ %

[

\

] $

[

\

%

]

$

[

\

$

[

\

% % ] ]
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 62 

(1967) – a classical work for psychologist – give some fine examples of patterns/models related to human 

interaction. 

If A is a good and deterministic model of the corresponding real phenomenon, then the feedforward 

mechanism may give better results than the feedback mechanism. If A is not a good model, then the 

feedback mechanism may lead to a higher performance (Klir, 1991). Thus, the feedback and the 

feedforward paradigms are not comparable and their performance depends on the circumstances. 

So much for systems science, let us talk business again. Within the development phase of decision 

process we can try – for instance by involving the stakeholders - to anticipate to what might happen in the 

selection phase. Moreover, in an adaptive decision process such as the modified search or the dynamic 

design decision process each iteration allows including the ‘lessons learned’ from the selection phase. 

Thus, the decision process allows for the full-information paradigm. Although this is a promising start, 

we should not be satisfied. Our target – or goal-seeking element - is not the decision process, but the 

effect and the efficiency of the resulting action. After all in our made-up project we would not have been 

satisfied by an authorised failure! This implies that the decision process is only a part of the goal-oriented 

system. For full optimisation the system should stretch out to the resulting actions and feedbacks and 

feedforwards should consequently enable those involved to anticipate and react to the results of the 

remedial actions. This requires remedial designs that can be operated adaptively. If we do not provide this 

type of adaptive designs, then we cannot change the outcomes of our action, and the only option is to use 

the experience for some future project. 

2. THE MULTIOBJECTIVE SETTING 

 

The majority of decision situations in soil remediation share important similarities. First, stakeholders 

evaluate a set of remedial alternatives, which represent the possible choices. The objectives to be 

achieved drive the design (or screening) of alternatives and determine their overall evaluation. Clearly the 

stakeholders in the made-up project do have different objectives. Attributes are the measurement rods –

the decision makers ruler - for the objectives and specify the degree to which each remedial alternative 

matches the objectives. We have used these attributes in the second stakeholder meeting of the made-up 

project to show that the in situ alternative came very close to the objectives. Finally, factual information 

and value judgments jointly establish the overall merits of each option and highlight the best compromise 

solution (Beinat, 1997). Figure 3 summarises the information that plays a role in a multiattribute model. 

The information items are the multiattribute profiles (A1,..,Am) allowing measurement of the achievements 

of the (remedial) alternatives, the value functions (vi , i=1,..,n) representing human judgments, the weights 

(wi , i=1,..,n), and the multiattribute value function that associates an overall value with each alternative 

(v(Aj ), j=1,..,n). 

DGGLWLYH

UHSUHVHQWDWLR Q

YDOXH IXQF WLRQV

YL

L Q

ZHLJKWV

ZLL Q

0 XOWLDWWULEX WH SUR ILOHV

$ [ [Q

« 

$P [ P[QP

RYHUDOO YDOXHV

Y$M

 ZY[M  ZQYQ[ QMM P

Figure 3. Information items in a multiattribute model (Beinat, 1997) 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 63 

In this example, the overall merit of a decision alternative is computed as a weighted sum of singleattribute performances regarding all attributes. Although this evaluation scheme is very common and 

widely used, it is important to stress that it can be applied only under very precise conditions. Without 

going into this topic (see Beinat 1997 for an overview), it is sufficient to say that the additive rule can be 

applied only if independence conditions across attributes are met. This, in turn, calls for a careful 

structuring of the decision problems and a careful choice of the attributes. 

Simple enough! Unfortunately different stakeholders often have different objectives and, thus, their 

multiattribute profiles, their functions and their weights are not identical. In our made-up project the 

stakeholders had different objectives, and their multiattribute profiles, functions and weights were 

different. Calculating an overall value for one stakeholder is possible, calculating one overall value for 

more than one stakeholder is only possible if objectives, profiles, functions and weights are identical. 

Consequently, what you normally get is an overall value or a score for a proposed alternative seen 

through the eyes of a particular stakeholder. Agreement in our project is not only reached by the fact that 

the objective attribute scores were more identical than expected, but also because we managed to unify 

the multiattribute profiles a little. In other words: the stakeholders gradually agreed upon the selection 

criteria. 

Not all of the attributes can be expressed in the form of some number and often these attributes will not be 

explicit. In other words, the overall quality of an alternative within a specific decision context is a 

function of the explicit and implicit attributes. This function can in turn be explicitly or implicitly used for 

negotiations between actors. In formula: 

( ) ( ( ),.., ( ), ) 1 1 1 v A f w v x w v x implicit values j = j n n nj

Where v(A) is the quality of alternative A; w1v1 (x1j), .. , wnvn (xnj) the explicit values for that alternative; 

and f is the decision rule, explicitly or implicitly used. On this basis, there are several possible approaches 

to the decision on the basis of the multiattribute model outcomes. They can be broadly classified as shown 

in Table 1. 

Table 1. Possible uses of the multiattribute model outcomes 

 Multiattribute model outcomes are 

sufficient to make a decision 

Other factors contribute to the 

decision 

The decision rule is 

explicitly known as a 

function of 

attributes. 

(1) The alternatives are evaluated by 

applying the decision rule and are 

ranked from best to worst and the 

decision is reached through analysis 

and evaluation. 

(2) The alternatives are evaluated by 

applying the decision rule and are 

ranked from best to worst. The 

decision rule can than be extended to 

include other aspects and the 

decision is reached through analysis 

and evaluation. 

The decision rule is not 

made explicit. 

(3) The evaluation of alternatives is 

based on the multiattribute model 

outputs, but the pros and cons are 

discussed between stakeholders and 

the decision is reached through expert 

judgment or bargaining and 

negotiation. 

(4) The evaluation of alternatives is 

based on the multiattribute outputs 

and on additional attributes, but the 

pros and cons are discussed between 

stakeholders and the decision is 

reached through expert judgment or 

bargaining and negotiation. 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 64 

4. TOOL 1: BEST AVAILABLE TECHNIQUES 

4.1. SEARCH AND SCREEN (AND ANALYSIS/EVALUATION) SUPPORT 

BAT (Best Available Techniques) is an MS-Access/Virtual Basic product for Windows. Tauw and VITO 

(Flemish Institute for Technology Development) have developed it. BAT is a decision support tool that is 

aimed at supporting soil remediation experts, policy makers and environmental managers (Gevaerts et al., 

1998). 

The knowledge base of the tool consists of a large number of factsheets related to remedial concepts and 

techniques. As input BAT requires four types of information: soil characteristics, contamination 

characteristics, other characteristics such as presence of buildings and infrastructure and, finally, remedial 

targets and duration. As soon as the input is entered the tool starts to compare the input data with the 

factsheet data and the output is a list of suitable concepts and techniques, unsuitable concepts and 

techniques, concepts and techniques for which a decision requires additional data and, finally, concepts 

and techniques which are not relevant to the problem described. 

For soil remediation experts the tool supports during the search and screen routines of a modified search 

or dynamic design decision process and as such it is related to the development phase of the decision 

process. Its goal is to give the user an overview of remedial alternatives that could be worked out. For policy 

makers and environmental managers the tool enables to check the work of environmental experts. As check 

it is probably more in line with the screen and analysis/evaluation routines and thus with the selection 

phase of the decision process. Note that in case of second opinion soil remediation experts can use the tool 

to check the work of their colleagues. 

4.2. FEEDBACK AND FEEDFORWARD 

The selection of a number of possible remedial alternatives is an important stage in the process. Although 

trying to anticipate to the preferences of the stakeholders by presenting a specific subset of the outcomes 

of the BAT model is possible, we feel that the total set of outcomes of the BAT model should be 

discussed with the stakeholders. This may tempt the stakeholders to change their preference profile, and, 

as a designer you can never be accused of having a narrow scope. Thus, when using the BAT model 

within the decision process we recommend not using the feedforward paradigm. After the results have 

been discussed in the selection phase of adaptive decision processes such as the modified search or the 

dynamic design decision process the ‘lessons learned’ should be included in the next iteration. 

As has been discussed before our target is not the decision process, but the effect and the efficiency of the 

resulting action. If we stretch our attention to the remedial actions, then we can make use of the 

experiences with the remedial alternatives. These experiences should be included in the knowledge base 

of the tool, i.e., in the factsheets. This kind of feedback requires clear guidelines for the maintenance of 

the model. If the outcomes of certain remedial alternatives are more uncertain than those of others, then 

this should be communicated. This kind of feedforward/anticipation (see Okx and Stein, 2000) should 

avoid disappointment. 

4.3. THE MULTIOBJECTIVE SETTING 

The BAT models goal is to give the user an overview of remedial alternatives that could be worked out. 

In this stage the decision rules are not made explicit yet, and other factors than those used by the model 

do contribute to the decision. Thus, the evaluation of alternatives is based on the model outputs and on 

additional attributes, but the pros and cons are discussed between stakeholders and the decision is reached 

through bargaining and negotiation. 

Our observation is that in this stage the legal authorities are seldom involved, and discussions are held at a 

technical level. This should be considered as a missed opportunity. Discussions like ‘what if that and that 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 65 

happens’ are most valuable and could result in modified solutions capable of handling less likely 

situations as well as the expected situation. 

5. TOOL 2: IN SITU AIR SPARGING 

5.1. DESIGN SUPPORT 

In situ air sparging – A technical guide, Version 1.1 has been developed by Tauw and GeoDelft. We 

gratefully acknowledge the views and comments of many people, in particular Terry Walden of BP Oil 

Europe UK and Rick Johnson of Oregon Graduate Institute in the United States. The technical guide is a 

tool for consultants/designers to help plan the remediation process and to design and operate an in situ air 

sparging (IAS)/soil vapour extraction (SVE) system. The guide should be able to support decisions for the 

clean-up of different types of sites ranging from small sites with permeable soil to large industrial estates 

with strongly heterogeneous and stratified soils (Pijls et al., 2000). Its predecessor – Version 0.1 – had a 

totally different appearance. It was structured around a large number of flowcharts and meant to lead the 

expert via a series of questions to an optimal design. Its structure was ideal for the envisaged software 

implementation. During the test period, however, the future users rejected the product for two reasons: 

• They preferred a reference guide rather than some kind of workflow oriented tool; and 

• They were questioning the systems ability for special cases. 

Although I am still not convinced whether it was the only option, we decided to capitulate and developed 

the classical technical guide. We were reported that in the same period a similar project in the United 

States faced a similar fate (Leeson et al., 1998). 

The present tool is organised in a number of chapters covering: the theoretical background, remediation 

concepts, feasibility studies, design, hardware/equipment, installation of the IAS/SVE system, operation 

of the IAS/SVE system, shutdown and postclosure measures and costs. Thus, it follows more or less the 

designers’ logical steps. However, if the designer has a particular question on blowers and compressors, 

then he can skip everything except the section on injection equipment In Version 0.1 skipping sections 

was less easy. 

For soil remediation experts the tool supports during the design routine of a modified search or dynamic 

design decision process and as such it is related to the development phase of the decision process. Its output 

is a detailed IAS/SVE design. 

5.2. FEEDBACK AND FEEDFORWARD 

IAS/SVE design takes place after the selection of a number of remedial alternatives by the stakeholders. 

Again I feel that all possible options in IAS/SVE should be discussed, but, as long as technical choices do 

not lead to different results, not all of the stakeholders need to be involved. The processes induced by 

IAS/SVE are rather complicated, and, in order to discuss items such as blowers your discussion partner 

should have some knowledge about lateral rotary blowers, rotating lobe blowers, rotary sliding vane 

blowers, and so on. Selection is based on expert judgment rather than on analysis or bargaining. Thus, 

when using the technical guide in a modified search or the dynamic design decision process the expert 

judgment or ‘lessons learned’ should be included in the next iteration. 

If we stretch our attention to the remedial actions, as we did with the BAT model, then we can make use 

of the experiences with IAS/SVE concepts, feasibility studies, design features, hardware/equipment, 

installation, operation, postclosure measures, and costs. These detailed experiences should become part of 

the next versions of the technical guide. This kind of detailed feedback requires even more clear 

guidelines for the maintenance of the guide. Again negative and positive experiences allow for 

anticipation. 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 66 

5.3. THE MULTIOBJECTIVE SETTING 

The IAS/SVE guide supports IAS/SVE design. In this stage the decision rules are connected to the 

implicit knowledge of experts, and other factors than those used by the guide do practically not contribute 

to the decision. Thus, the evaluation of alternatives is based on the model outputs, but the pros and cons 

are discussed and the decision is reached through expert judgment. Our observation is that legal 

authorities are seldom involved in this stage, and discussions are held at a technical level. As long as 

technical choices are unlikely to change the effect and efficiency of the clean-up operation, it should not 

be considered as a missed opportunity. 

6 TOOL 3: COMPARISON OF REMEDIAL ALTERNATIVES 

6.1. Analysis/evaluation support 

REC is an Excel/Virtual Basic Decision Support Tool for Windows for the analysis and evaluation of 

possible clean-up strategies for a contaminated site. REC was developed by Tauw, the Institute for 

Environmental Studies of the Free University of Amsterdam and Berenschot Osborne of Utrecht. The aim 

of REC is to support the choice of the most effective and efficient strategy for soil remediation in terms of 

risk reduction, environmental merit and costs for the site concerned (Okx et al., 1998; Okx, 1999). 

The core of the model consists of a database comparable to those of Life Cycle Analysis (LCA) tools and 

a large number of formulas able to calculate risk, reduction, environmental merit, and costs. As input 

REC requires three types of detailed design data of the chosen remedial alternatives: risk characteristics 

such as type of contamination, risk profile, land use, the area involved, environmental characteristics such 

as expected amount of clean ground and ground water, use of resources like clean ground, ground water 

and energy, air emissions, pollution of surface water, production of final waste and spatial occupation, 

and, finally cost characteristics such as preparation costs, demolition costs, remedial costs, replacement 

costs and discount rate. The output of REC is a set of three indices for each clean-up alternative: the risk 

reduction index, the environmental merit index and the costs index. Together, these indices summarise the 

overall performances of each option (see Figure 4). 









, ,, ,,,







, ,, ,,,

(QYLURQPHQWDO PHULW













5LVN UHGXFWLRQ &RVWV

, ,, ,,,

Figure 4. R-, E- and C-indices of three remedial alternatives I, II and III 

Thus, the tool supports the analysis/evaluation routine and, thus, is linked with the selection phase of the 

decision process. 

6.2. FEEDBACK AND FEEDFORWARD 

The selection of the remedial action is seen as the most important stage in the process. In general the 

decision rules of the different stakeholders are known. Three strategies are quite common: a focus on 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 67 

effectiveness, which aims for the selection of the most effective option provided the budget available is 

sufficiently high; a focus on costs, which aims for the selection of the cheapest solution provided some 

significant risk reduction is achieved; and, finally, a focus on efficiency, which aims for the selection of 

the solution that gives the best ratio between risk reduction, environmental merits and costs. 

We saw in practice that the designers who worked with REC developed – by using the models feedback –

a feeling for the relation between design features and the R-, E- and C-indices and they gradually 

developed into designers able to anticipate the results of the REC model. Their designs became smarter: 

an advantage of the use of the full-information paradigm. 

Stretching our attention to the remedial action means that we will be able to improve the LCA-like 

database of the tool, and that the model will improve steadily. Again we need to organise this kind of 

feedback. If we don’t we will not benefit from our experiences. If the outcomes of certain remedial 

alternatives in terms of the R-, E- and C-indices prove to be uncertain, then this should be communicated. 

The present model presents the cost uncertainties. 

6.3. MULTIOBJECTIVE SETTING 

The REC model gives the stakeholders user an overview of the consequences of remedial actions in terms of 

risk reduction, environmental merit, and costs. In this stage the stakeholders have their decision rules set, but 

are not always willing to expose them. Other factors than those used by the model do contribute to the 

decision. Thus, the evaluation of alternatives is based on the model outputs and on additional attributes, 

but the pros and cons are discussed between stakeholders and the decision is reached through bargaining 

and negotiation. 

Our observation is that in this kind of analysis/evaluation routines the legal authorities are nearly always 

involved. Although the multiattribute profiles and specially the weights attached to the attributes differ for 

the stakeholders involved, our experience is that quite frequently one alternative outclasses the others 

regardless of profiles, weights and values. Such an alternative is easily accepted by all of the stakeholders, 

which gives them almost a co-responsibility for the chosen alternative. Note that co-responsibility is not 

the same as co-liability! Discussions like ‘what if that and that happens’ are again a common feature and 

frequently result in modified solutions capable of handling less likely situations as well as the expected 

situation. 

HAPPILY EVER AFTER ...

There are many tools, which supports the decision process. In this article we have shown only a few of 

them: a tool that lists the best available techniques for the problem at hand, a tool that enables IAS/SVE 

design, and, finally a tool that enables to select the best design on the basis of risk reduction, 

environmental merit and costs. Presently the tools are used independently of each other, but signs of 

integration by using feedbacks and feedforwards are observed. The case of the REC using designers give 

rise to a project trying to formalise the design rules which were implicitly used by our designers. Once 

these rules are explicit, they should be fed to tools such as BAT or the IAS/SVE guide. The reduction of 

the designers’ degrees of freedom, however, should be avoided. This can be realised by simply enabling 

the users of the tool to switch the rules off or on. In my opinion this kind of development does not mean 

that we should aim for an all-including integrated decision support tool which does it all. Instead we 

should develop a number of smaller tools that are almost invisibly interlinked by feedbacks and 

feedforwards, but they have to be used independently of each other. The boundary of the decision process 

as described by Mintzberg does not include the actual actions, and this inhibits a gradually improving 

decision quality. Feedback and feedforward should include the actions. If not, then a proper evaluation of 

our decisions will remain impossible. Involving the stakeholders in the decision process is necessary and 

beneficial. An alternative accepted by all of the stakeholders, is the best alternative. 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 68 

REFERENCES 

BARDOS, R.P., MARIOTTI, C., MAROT, F. AND SULLIVAN, T., 2000. Decision support for contaminated 

land in Europe and North America. In: Proceedings of the Seventh International FZK/TNO Conference on 

Contaminated Soil 2000,Leipzig. 

BEINAT, E., 1997. Value functions for environmental management. Kluwer Academic Publishers, 

Dordrecht 

DRESCHMANN, P., (1992). Altlastensanierung in den USA am Beispiel des RI/FS-Process. AltlastenSpektrum, 1/92 

EIKELBOOM, R.T. AND VON MEIJENFELDT, H., 1985. The soil clean-up operation in the Netherlands. 

Further developments after five years of experience. In : Proceedings of First International TNO 

Conference on Contaminated Soil '85, Assink, J.W. and Brink, W.J. van de (eds.). Martinus Nijhoff 

Publishers, Dordrecht. 

GEVAERTS, W., LAURYSSEN, K., PIJLS, C.G.J.M., DIJKMANS, R. AND DRIES, V., 1998. Best available 

techniques for contaminated sites. In: Proceedings of the Sixth International FZK/TNO Conference on 

Contaminated Soil 1998, Edinburgh. 

GOTOH, S. AND UDOGUCHI, A., 1993. Japan's policy on soil environment protection - history and present 

status. In : Proceedings of the Fourth International KfK/TNO Conference on Contaminated Soil, 3-7 May 

1993, Berlin. 

JANSSEN, R., 1991. Multiobjective decision support for environmental problems. Thesis of the Free 

University of Amsterdam, Amsterdam. 

KLIR, G.J., 1991, Facets of systems science, IFSR International Series on Systems Science and Engineering, 

Volume 7, Plenum Publishing Corporation, New York 

LEESON, A., JOHNSON, P.L., JOHNSON, R.L., HINCHEE, R.E. AND MCWORTHER, D.B., 1998. Air sparging 

design paradigm. Battelle, Columbus, Ohio. 

MINTZBERG, H., RAISINGHANI, D. AND THÉORÊT, A., 1976. The structure of unstructured decision 

processes. Administrative Science Quarterly, 21. 

NUTT, P.C., 1984. Types of organizational decision processes. Administrative Science Quarterly, 29.

OKX, J.P., BEINAT, E., VAN DRUNEN, M.A. AND NIJBOER, M.H., 1998. The REC-framework: integral 

risk management for contaminated soil. In: Proceedings of the CARACAS-Workshop, Berlin 

OKX, J.P., 1999. The REC decision support tool for comparing soil remediation alternatives (in Japanese). 

In: Proceedings of the 2nd International Workshop of Geo-Environmental Restoration,Yokohama. 

OKX, J.P. AND STEIN, A., 2000. Use of decision trees to value investigation strategies for soil pollution 

problems. Environmetrics, Volume 11, Issue 3 

PIJLS, C.G.J.M., BOELSMA, F., MARNETTE, E.C.L., VAN REE, C.C.D.F., VREEKEN, C., 2000. In situ air 

sparging – A technical guide, Version 1.1. CUR/NOBIS report 95-1-13, Gouda. 

WATZLAWICK, P., BEAVIN, J.H. AND JACKSON, D.D., 1967. Pragmatics of Human Communications.

W.W. Norton & Company, Inc., New York.
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 69 

CASE STUDY: COST BENEFIT ANALYSIS / 

MULTI -CRITERIA ANALYSES FOR A 

REMEDIATION PROJECT 

Dieter Weth 

Mull und Partner Ingenieurgesellschaft, Germany 

Osteriede 5, 30827 Garbsen, Germany

E-mail: weth@mullundpartner.de 

SUMMARY 

Transparent planning processes are necessary to increase acceptance of remediation projects with the 

general public and those affected. Compared to simple cost estimates, an evaluation of remediation 

schemes, compatible with the space, that is carried out using an economic and ecologic assessment of a 

remediation concept can ensure a uniform comparison of various remediation measures. Further planning 

may then be carried out on that basis. 

The following instruments are used when preparing an overall remediation concept that is compatible 

with the site in the planning phase of a remediation scheme: 

1. A dynamic efficiency calculation considering also – expressed in monetary terms – the loss of use 

of a contaminated site and the duration of the remediation measure, and 

2. A value in use analysis of the ecological effects of a remediation scheme. 

This results in a scope for decision, which ensures optimal planning results for the remediation concept. 

This scope relates to identifying the optimal economic and ecologic remediation solution in each case for 

the remediation process to be used in a particular case of damage. The economic costs and the ecological 

benefits of a remediation concept need to describe the effectiveness and/or compatibility with the site of a 

remediation scheme and thus allow justifiable decisions to be made. 

1. INTRODUCTION INTO THE ECONOMIC AND ECOLOGIC OPTIMISATION WHEN 

SELECTING REMEDIATION PROCESSES 

When following a line of action in the remediation planning that is compatible with the site the selection 

of the remediation process or method used is optimised by the technical, economic and ecologic 

requirements in an iterative process. Alternative possible uses are considered to come to a solution that is 

economically and ecologically viable. As a rule, the owner of the land is free to define the target 

parameters for the remediation of contaminated sites within the given general statutory and technical 

conditions (see figure 1). In this, steps to avoid dangers for a non-sensitive use represent the lower limit 

(minimal concept). In enhancement of the ecological use of a remediation can even lead to the realization 

of a maximum concept that would allow universal subsequent use under even the most sensitive 

requirements. 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 70 

Scope for Decisions

Minimal concept

Ecological benefit

Economic expenditure

Maximum concept

Minimal expenditure

Maximum expenditure 

Scope for Decisions

Which of the remediation concepts is in

regard of

• economic aspects favourable?

• ecological aspects favourable?

Which decisions lead at additional low

economic expenses to high ecological

benefit?

Figure 1. Scope for Decisions

Taking into consideration the avoidance of danger the following criteria need to be considered when 

selecting the remediation process and/or a combination of processes in addition to the costs: 

• Precedence of the destruction of harmful substances over separation 

• Minimizing masses and mass flows 

• Waste avoidance, minimizing residuals 

• Substance recycling 

• Resource conservation 

To evaluate the remediation concept in terms of its economic and ecological aspects, all technically 

feasible remediation processes together with their costs and uses in the form of ratios need to be included 

as alternatives in the decision making process, in order to provide as wide a base a possible for arriving at 

a decision (Gehrke 1993). 

2. ECONOMIC VALUE LEVELS 

The remediation processes that could be used need to be assessed in respect of their economic value 

levels: 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 71 

Table 1. Economic value levels 

Value level Description Process Efficiency 

calculation 

approach 

Cost level Costs of the remediation process Comparative cost 

method 

static 

Expense level Benefit due to increased value of 

decontaminated site 

Comparative profit 

method 

static 

Investment 

level 

Costs due to different lengths of 

time needed for remediation 

Capital value method dynamic 

(according to Gehrke 1993) 

The costs of a remediation process, however, depend primarily on the amounts to be treated. In addition 

the various fix costs for site setting up and safety at work need to be taken into account (see figure 2). 

Cost comparison calculation

mi X ki = Sum of the quantity dependent method costs

i = Index for different remediation methods

mi = Contaminated soil and groundwater quantity

ki = Method specific quantity dependent cost attempt [$/m3]

Figure 2. Cost comparison calculation 

On the other hand, varying revenue is obtained as a consequence of a remediation, in particular revenue 

derived from subsequent use of the remediated site, but also the avoidance of higher remediation costs at 

a later date, the enhanced image of the landowner or the avoidance of claims for damages put forward by 

the owners of adjacent land that would be affected by the pollution spreading. The revenue from any 

subsequent use is important and can be assessed from a business costing point of view and it needs to be 

compared to the costs of carrying out the remediation. 

The alternative remediation options can differ widely as regards the duration of their use. A significant 

influence on the economic results, which is calculated by the capital value method is brought to bear by 

the 

• loss of interest due to having to pay procedural costs 

• loss of interest due to lost monetary use of the site 

(Figure 3). The capital value is composed of the following elements: 

1. Costs of the procedure 

2. Loss of monetary use due to a permanent limitation of the use of the building plot on completion 

of the remediation 

3. Loss of interest due to varying durations of the measures, and 

4. Loss of interest due to the varying length of occupation of building plots (Gehrke, 1993) 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 72 

Figure 3. Capital value method 

The economically most advantageous process is that which yields the maximum final sum in relation to 

the alternatives. The criteria of advantage for a comparison of the alternatives is therefore: 

• An investment I is more advantageous that an alternative II, if its negative capital value is smaller 

than the negative capital value of alternative II (Gehrke 1993). 

3 ECOLOGICAL VALUE LEVELS 

Soil and groundwater remediation is carried out to change the state of the contaminated site to such an 

extent that they do not pose a risk in respect of the use of the property/assets to be protected. Assets to be 

protected are primarily people’s health. Carrying out a remediation project, however, also involves other 

affects. Two value levels should therefore be distinguished for an evaluation (see figure 4): 

Ecological deciding factors:

Primary effects: Secondary effects:

Effects on the location

Ecological benefit

Effects of technical activities

on the environment

(material and energy flow)

Ecological rucksack

A B

Figure 4. Ecological value levels 

Primary effects = effects caused by the measurements on the environment of the site (figure 5) 

• Quality and structure of the soil 

• Biotope quality 

• Groundwater quality and recharge 

• Topography/relief 

• Climate regulation potential 

Capital value method

Capital value: - Method costs

 - Loss of monetary due to a permanent limitation of the use of the building plot on completion of the

 remediation

 - Loss of interest due to varying durations of the measures

 - Loss of interest due to the varying length of occupation of building plots

K(t) = K(t=0) X [ 1 + r ]n

K(t) : Capital value at the time of (t)

r : Internal interest rate

n : Period

Calculation of

the capitel value:
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 73 

Ecological deciding factors:

Quality change

Soil structure

Groundwater

recharge Groundwater

quality

Topography/

Relief

Soil quality

Air exchange

Fresh air

emergence

Biotope quality

Primary effects: A Ecological quality of the location

Figure 5. Primary effects 

The individual primary ecologic effects (Figure 6) are ranged and weighted in relation to the local 

conditions. 

1. Secondary effects = ecologic rucksack (supra-regional effects through the technical activities of 

the use of the process on the environment) (see Figure 7): 

• Substance streams 

• Energy streams 

• Damage to the environment and health 

Assessment of the results of remediation measures Assessment of the results of remediation measures

Ecological deciding factors

Condition improvement in the concerned media by

remediation

 Soil quality

 Soil structure

 Topography/relief

 Groundwater recharge

 Groundwater quality

 Fresh air emergence

 Air exchange

 Biotope quality

Level of the method conditional remaining loads

Risks by the remaining loads

Durability of the success of the remediation measure

Ecology value I

Degree of the

attainment of

targets

Criteria Weighting Result

Figure 6. Ranging and weighting the primary effects 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 74 

Secondary effects: B Ecological rucksack

Effect of technical activities on the environment

Material flow

Energy flow

Technical activities Environmental and

health damages

Ecological deciding factors

Figure 7. Secondary effects

With the secondary ecological effects too a weighting is done before both levels are combined into one 

ecologic value (Figure 8). 

Figure 8. Ranging and weighting the secondary effects 

The procedure followed when developing the ratios is a follows in the context of the comparison of 

procedures: 

1. Defining an objective for the problem to be investigated 

2. Translating an objective into evaluation criteria 

3. Subjective weighting of the criteria according to certain comprehensible and controllable rules 

4. Evaluation of alternatives based on profit targets 

The effects that can be felt vary in the extent to which they occur both as regards quality as well as 

quantity. By using the ‘value in use analysis’ the effects on the environment are represented in the form of 

ratios and can thus be compared. 

Assessment of the execution of remediation measures Assessment of the execution of remediation measures

Criteria

Ecology value II

Ecological deciding factors

Degree of the

attainment of

targets

Weighting Result

Waste and sewage issues

Waste disposal

Sewage elimination

Protection of the human health

Air emissions of contaminants

Dust issues

Water emissions of contaminants

Noise issues

Resource saving

Energy

Additional chemical substances

Natural raw materials 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 75 

4. CONCLUSION 

The model makes clear the connection between the economic effort and the ecological benefit of a 

remediation concept (figure 9). The ecologically best overall remediation concepts consists of the process 

alternatives with the smallest capital values with the benefit as a result of an increase in value of the 

rehabilitated site and the costs due to the varying timescales of the remediation also being taken into 

account in addition to the costs for the remediation scheme itself. The ecologically best overall 

remediation concept is expressed by the highest values in use. These result on the one hand from the 

extent and the sustainability of the improvement of the state in respect of the exposition of human beings 

and the environment by the remediation measure and on the other from process related environmental 

pollution by the remediation project itself, which have supra-regional ecologic effects. 

Ecological

benefit

Economic profit

Ecological

damage

A

B C

D

E F

G

Treatment optimized economically and ecologically

Economic loss

Primary effect on the

environment

(Ecological benefit)

Economy value

Ecology value I Ecology value II

Business management

consequences

Secondary effect on the

environment

(“Ecological rucksack")

Weighting

Cost benefit analysis

Assessment of the

execution of

remediation measures

Assessment of the

results of remediation

measures

Ecology value

Weighting Weighting

Figure 9. Treatment optimized economically and ecologically

The combination of the ratio pairs of the investigated remediation concepts is illustrated by the two 

extremes – the ecologically best concept that does not take into account economic considerations (Figure 

9; case D) and the economically most advantageous concept, which does not consider the ecological 

benefit (Figure 9; case F). Where the economically best remediation concept varies from the ecologically 

best scheme, a scope for decision results. Purely formally, that concept will show the best “economicecological effect” by which the ration of increase in ecological benefit to the increase in the capital value 

is the largest (Figure 9; case E). 

When calculating the economic and ecological ratios there are naturally uncertainties. With the economic 

ratios these are largely the result of the risk of changes in the volume, for the ecological ratios they relate 

mainly to the previously relatively subjective setting of the objectives and the weighting that needs to be 

carried out. Those ratio pairs are decisive in the comparison of the results of several remediation concepts 

which, as regards the identified bandwidth are on “the safe side”, i.e., the – in respect of the amount –

smallest ecological benefit with the largest economic expenditure. 

To be able to carry out the effectiveness of remediation measures in the context of the preplanning fast 

and transparently, we developed the DV supported effectiveness analysis model "WILMA". The 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 76 

economic and ecological standards can be described and covered with the corresponding code numbers so 

that the economic and ecological effectiveness of a remediation is determined. 

With WILMA different use scenarios can be simulated in connection with location specific factors. The 

use scenarios of the redeveloped area depend on toxicologic examining results, in which we distinguish 

in: 

• Children's playground 

• Living use, general 

• Park/public green space 

• Fallow area 

• Industry and trade area 

At the moment we are able to carry the calculation with WILMA for the approx. 20 most important 

remediation methods. By the flexible conception of the model the standard details of the database can be 

adapted to regional conditions. An individual case obtained use of the planning instrument gets possible 

so. Prerequisite is an exact knowledge of the damage and this one for the location specific conditions 

essential for remediation and use. 

5. SALZWEDEL CASE STUDY 

Using WILMA a remediation involving a site contaminated with petroleum-derived hydrocarbons and 

BTEX (benzene, toluene, xylene) on the former helicopter port of the East German border troops at 

“Salzwedel - Fuchsberg” that has already been completed was subsequently calculated for calibration and 

testing purposes (see figure 10). 

Case study: “Salzwedel"

Helicopter base of the former GDR - border troops

Contaminations of soil and groundwater in the area of a gas station by kerosene,

diesel oil and gasoline

Soil:

Initial concentrations: MKW up to 17.800 mg/kg

BTEX up to 200 mg/kg

Remediation aim: MKW: 150 mg/kg

BTEX: 2,5 mg/kg

Volume to be

redeveloped: approx. 1.100 m3

Soil type: fine - middle grained sand

Groundwater:

Initial concentrations: BTEX up to 50 mg/l

Remediation aim: BTEX: 20 )g/l

Figure 10. Case study ‘Salzwedel’ – Basic information 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 77 

5.1 BRIEF DESCRIPTION OF THE SALZWEDEL CASES 

On the former filling station site mean petroleum-derived hydrocarbon concentration of 2,000 mg/kg 

(max. 17,800 mg/kg) and/or BTEX levels of approx. 200 mg/kg were found in the soil. The aromatic 

hydrocarbons had already entered the groundwater, which had BTEX levels of up to 50 mg/l. The soil 

contamination affected approx. 500 m2, groundwater contamination affected approx. 5000 m2. The 

volume of soil to be rehabilitated was approx. 1,100 m. 

The site is partly used for residential purposes (renovation of the old barracks building), and part of it is 

derelict (still owned by the federal government) and used by a school. 

5.2 RESULTS 

As an initial step using the WILMA model a selection of the processes that could be used for the 

contaminants identified was made based on the details regarding the type and extent of contamination. 

After entering the site-specific soil properties and the available resources the program narrowed down the 

applicable processes. Resources are those site conditions that have a bearing on the construction or setting 

up of the remediation plant such as the necessary space (for the facility or for intermediate storage of soil, 

etc.), water, power, etc. Figure 11 shows the results of this pre-selection. 

Possible remediation methods

(MKW/soil):

R Soil clean-up on-site

Soil clean-up off-site

Microbiological treatment on-site

Microbiological treatment off-site

K Microbiological treatment in-situ

Pyrolysis off-site

Incineration off-site

B Slot-wall

B Steel sheet-pile wall

B Depositing

Possible remediation methods

(BTEX/soil):

R Soil clean-up on-site

Soil clean-up off-site

Microbiological treatment on-site

Microbiological treatment off-site

K Microbiological treatment in-situ

Pyrolysis off-site

Incineration off-site

Soil venting with active coal

Soil venting with catalytic oxidation

B Slot wall

B Steel sheet-pile wall

B Depositing

Exclusion of the method by:

R: Lack of location specific resources (available areas, water, energy etc.)

K: Location specific criteria (e.g. grain size, too low groundwater level referred to ground elevation)

B: Editor

Case study: “Salzwedel"

Figure 11. Case study ‘Salzwedel’ - Possible remediation methods 

After calculating the economic costs of the processes left and the ecological benefits, and after combining 

the individual processes the result shown in Figure 12 was arrived at. 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 78 

0 

500.000 

1.000.000 

1.500.000 

2.000.000 

2.500.000 

3.000.000 

0 2 4 6 8 10

E cological valu e [-]

E con omic expen se [D M]

%7(; 6RLO YHQWLQJ

DFWLYH FRDO

0.: ,QFLQHUDWLRQ RIIVLWH

%7(; 6RLO YHQWLQJ

FDWDO\WLF R[LGDWLRQ

0.: 0LFURELRORJ\ RIIVLWH

%7(; 6RLO YHQWLQJ

DFWLYH FRDO

0.: 0LFURELRORJ\ RIIVLWH

%7(; 6RLO YHQWLQJ

FDWDO\WLF R[LGDWLRQ

0.: 0LFURELRORJ\ RQVLWH

%7(; 6RLO YHQWLQJ

DFWLYH FRDO

0.: 3\URO\VLV RIIVLWH

%7(; 6RLO FOHDQXS RQVLWH

0.: 6RLO FOHDQXS RQVLWH

%7(; 6RLO YHQWLQJ

DFWLYH FRDO

0.: 0LFURELRORJ\ RQVLWH

Case study: “Salzwedel"

Figure 12. Case study ‘Salzwedel’ – Results

It became apparent that the combination of soil air extraction with cleaning of the extracted air by 

activated charcoal for eliminating the volatile BTEX from the unsaturated soil zone with a 

microbiological on-site process (clamp) – and when ignoring the ecological benefits – involved the lowest 

economic costs. On the other hand additional ecological benefits would only have resulted – involving a 

significant increase in the economic costs –from the combination of “soil air extraction with catalytic 

oxidation” with “microbiology off-site.” This combination of processes showed the highest eco benefits 

when ignoring the economic costs. Cleaning the soil from the petroleum-derived hydrocarbons by means 

of a thermal process (off-site incineration) too would have meant a significant increase of economic costs 

at only small increases in ecological benefits due to the transport costs involved. 

6. LIFE CYCLE ASSESSMENTS AS METHODS IN THE QUALITATIVE AND 

QUANTITATIVE EVALUATION OF ENVIRONMENTAL EFFECTS IN THE 

REMEDIATION OF CONTAMINATED SITES 

Apart from the value in use analysis shown a further method for assessing the effects of the 

environmental pollution through the remediation project itself can be calculated by means of life cycle 

assessments. 

In the ‘value in use analysis’ a methodological comparison of processes is made. Similar to the 

methodological steps of the environmental impact assessment under the UVP Act this involves the 

assessment of the ecological benefit and all the effects of the remediation scheme on the environment, 

which are described, forecast regarding both quality and quantity, assessed and summarized as a ratio, in 

order to obtain a comparison and be able to arrive at a decision as regards the selection of the method. 

The ‘life cycle assessment’ too should take into account as far as possible ecological criteria when 

specifying possible remediation processes in order to achieve long-term ecological optimisation. For this 

it is necessary to know what effects the methods considered may have on the environment. The Federal 

Environment Office suggests the following definition of the term: 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 79 

The life cycle assessment is a comparison, which is as comprehensive as 

possible, of the environmental effects of two or more different products, product 

groups, systems, process or behaviours. It serves to point out weak points, to 

improve the environmental properties of products, the decision making process 

in procurement and purchasing, to promote environmentally friendly products 

and processes, to compare alternative courses of action and to back up 

recommendations for action to be taken. Depending on the underlying question 

this comparison is supplemented by further aspects, e.g., an assessment of the 

environmental protection efficiency of funds. (from Schmidt-Bleek 1993) 

The Federal Environment Office suggest to standardize the method as follows: 

1. step: Definition of the objective of the report 

2. step: Operation balance: setting up a data basis by analysing all environmental influences on 

the lifecycle of a product starting with raw material procurement to disposing of the waste 

in life periods, the modules (vertical analysis). Considering the entries and exits of the 

modules in respect of the use of primary energy, raw materials, water and the emission 

into the air, the wastewater and solid waste (horizontal analysis). Examining the link 

between the modules (lifecycle criteria). Selection of the data. 

3. step: Impact balance: Description of the impact of the substance streams covered in the 

operation balance on the environment. 

 

4. step: Balance assessment 

The concept centres on the method prepared on behalf of the LfU Baden-Wurtemberg, “Environmental 

balances of the remediation of contaminated sites” by C.A.U. GmbH. 

Using this method it is possible, as has already been shown, to calculate remediation caused 

environmental effects as a result of an operating balance in which the potential effects, differentiated by 

certain impact criteria, has been calculated (Figure 13). In practice, however, the problem will often have 

to be solved as part of the necessary assessment of the balance, to weigh advantages and disadvantages of 

the individual remediation measures, in order to identify “the best possible method”. In cases where not 

one single method combines all the advantages over the other methods the person dealing with it at the 

building authorities is faced with difficult questions: 

• Which disadvantages for the environment are so serious that any measures that include those 

disadvantages must be excluded as a matter of principle? 

• Which environmental benefits balance out which disadvantages and to what extent? 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 80 

"Umweltbilanzierung von Altlastensanierungsverfahren" (LfU / C.A.U.)

“Environmental balance of

remediation measures for

contaminated sites“ (LfU / C.A.U.)

Life cycle assessment of the secondary effects Life cycle assessment of the secondary effects

• Use of energy

• Use of area

• Greenhouse effect

...

Balance sheet of masses und energy Balance sheet of masses und energy

Balance sheet of the effects Balance sheet of the effects

1

2

Effect categories Effect categories Results of the effects Results of the effects

x1 GJ

x2 m2

x3 kg CO2

...

3 Assessment Assessment

Ecological deciding factors

Figure 13. Ecological deciding factorsLife cycle assessment of a measure 

A part objective is therefore to be able to calculate and overall index from the many indices calculated by 

means of the “CAU method”, which allows a statement to be made on the best ecological remediation 

concept. 

To do so it is necessary to obtain cost factors that are as objective as possible for the individual impact 

categories of the CAU method which, by multiplying them with the result of the impact balance, yield the 

external costs of that particular remediation scheme (Figure 14). 

So the key aspect of the model presented here is “monetarisation”. Calculating monetary values for all 

relevant decision criteria allows a direct link and comparison of economy and ecology. Simply summing 

of the economic value, the ecological values I and II result in a quantitative basis for selecting the optimal 

remediation method from business and economic aspects. If it is possible to minimize existing 

uncertainties in the monetarisation no further weighting of the above mentioned elements is necessary, 

such as would be the case in an assessment in which verbal arguments are put forward to evaluate 

ecologic concerns. 

In a further step standards have to be developed for comparing the primary and secondary environmental 

impacts that present the local effects of the scheme at the site in an objective way. This can be achieve by 

monetarising the primary effects: 

• Quality and structure of the soil 

• Biotope quality 

• Groundwater quality and recharge 

• Topography/relief 

• Climate regulation potential 

As a result a ratio for the ecological effectiveness of a remediation scheme is obtained that, again together 

with the economic ratio from the cost/benefit analysis, delivers an objective basis for the decision making 

process for the most effective remediation scheme.
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 81 

Assessment by comparison of the

monetary consequences of the effect categories

Assessment by comparison of the

monetary consequences of the effect categories 3

Category result Category result x = Cost base Cost base Costs Costs

x1 GJ

x2 kg CO2

...

Effect category Effect category

2.80 $/GJ

0.022 $/kg CO2

...

Use of energy:

Greenhouse effect:

...

y1 $

y2 $

...

Ecology value II 

Economic damage by the

external effects of the measure

(external costs)

Figure 14. Ecological deciding factorsAssessment by comparison of the 

monetary consequences of the effect categories 

7. SUMMARY AND CONCLUSION – ASSESSMENT OF THE RESULTS SO FAR 

The results obtained by means of a value in use analysis in respect of the evaluation of any impact on the 

environment of the remediation of contaminated sites are well suited to a praxis-based comparison of 

alternative remediation methods. However, the weighting of the individual elements contained therein 

also reflects a subjective judgement. Contrary to that, a more “objective” from of evaluation could be 

carried out by a life cycle assessment plus subsequent monetarisation of the impact categories. 

However, the results obtained from the various studies so far are based on different mathematical 

approaches (avoidance costs, damage costs, etc.), something which asks for criticism of aggregating the 

individual categories. The current state of environment economic research, however, makes it necessary 

to accept this mixture of methodologies. The problem of a “limited comparability” cannot be solved at the 

moment. For almost all impact categories taken into account there exist substantial gaps in research and 

that is the reason why the costs identified in many cases are not more than “rough estimates”. 

For these reasons we work with a value in use analysis to quantify the ecological consequences of 

remediation measures. One receives a two parametric result representation which serves as basis for the 

decision-making process. 

8. REFERENCES 

Bundesministerium für Raumordnung, Bauwesen und Städtebau, Bundesministerium der Verteidigung 

1996: Arbeitshilfen Altlasten zur Anwendung der baufachlichen “Richtlinien für die Planung und 

Ausführung der Sicherung und Sanierung belasteter Böden” des BMBau für Liegenschaften des Bundes. 

Hannover: OFD Hannover -HausdruckereiC.A.U. GmbH 1996: Umweltbilanz von Altlastensanierungsverfahren. - Bericht für die Landesanstalt für 

Umwelt Baden-Würrtemberg. - Dreieich. 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 82 

Commission of the European Communities 1995: Towards Fair and Efficient Pricing in Transport. - 

Policy options for internalising the external costs of transport the European Union. Green Paper. - 

Brüssel. 

DOETSCH, P. u. A. RÜPKE 1998: Revitalisierung von Altstandorten versus Inanspruchnahme von 

Naturflächen. - „Texte 15/97“ des Umweltbundesamtes. - Berlin. 

Gehrke, D. 1993: Die Entwicklung von Sanierungskonzepten für Altstandorte. Fortschritt-Berichte VDI, 

Reihe 4: Bauingenieurwesen, Nr. 122, Diss. Düsseldorf 

F. SCHMIDT-BLEEK 1993: Wieviel Umwelt braucht der Mensch? MIPS - Das Maß für ökologisches 

Wirtschaften. - Berlin. 

M&P Ingenieurgesellschaft mbH 1997: M&P report; WILMA - Wirksamkeitsanalysemodell für 

Altlastensanierung. Ulrich Eggert GWK, Hannover 

Weth, D. 1999: Nachhaltigkeitsbetrachtungen bei der Sanierungsplanung von Altlasten. DEA-A-94-GE 

1520 Environmental Technology, 12TH General Meeting 1999, Proceedings. Bundesamt für Wehrtechnik 

und Beschaffung (BWB), Koblenz
Decision Support Tools NATO/CCMS Pilot Project Phase III 

83 

MODELLING THE FINANCIAL RISKS OF REMEDIATION 

Jim Finnamore, Environmental Finance Unit, WSP Environmental, 

Buchanan House, 20-30 Holborn, London, EC1N 2HS, UK 

Tel: +44 (0) 207 314 5000; Fax +44 (0) 207 314 5005 

E-Mail: jim.finnamore@wspgroup.com

ABSTRACT 

The performance of remediation represents a significant source of financial risk, which, if ignored or 

mismanaged, can have a serious effect on the commercial success of a project or business. Risk 

management relies heavily on accurate forecasts of the probability that remediation will fail to meet its 

objectives as well as the associated financial implications - typically expressed as a reduction in net 

present value or internal rate of return. This paper discusses an analytical approach and methodology, 

based on stochastic modelling, to translate the technical risks of remediation into monetary expressions of 

risk. This approach provides an invaluable management tool that can generate real business benefits. Most 

importantly, commercial decisions - which inevitably require a company to take a risk - are made with 

greater confidence and certainty. There are then opportunities to optimise the management of risk by 

contractual mechanisms and structuring of project finance. 

Key Words: commercial risk, financial forecasting, modelling, internal rate of return, net present value, 

expenditure, revenue, asset value 

INTRODUCTION 

For many businesses, remediation of soil and groundwater has assumed greater importance through its 

potential to influence liquidity, solvency and overall financial performance. This trend is likely to 

continue throughout Europe as pressure mounts to re-use previously developed ‘brownfield’ land, a 

proportion of which will inevitably be found to be contaminated. Some companies view the role of 

remediation as simply protecting and maintaining asset (property) value whilst avoiding legal liabilities. 

Others recognise the commercial opportunities that remediation can generate in terms of enhancing the 

value of brownfield sites. Whatever the business case, there are corresponding financial risks relating to a 

company’s ability to meet its corporate and project objectives. These risks can have favourable and 

unfavourable effects depending on whether there is a downward or upward variation from the expected 

costs, revenue and asset value. The positive and negative variation can in turn cause a company to 

perform better or worse than expected. 

The precise nature and extent of financial risk depends on the context in which remediation is undertaken. 

Where remediation forms part of an investment project, such as brownfield site reclamation, the 

underlying financial risk surrounds the internal rate of return (IRR) or Net Present Value (NPV). The 

IRR, which represents the return that can be earned on the capital invested in a project, can be greatly 

reduced to a point at which a project becomes non-viable commercially. The IRR reflects the volatility in 

the risk - the two factors tending to show a positive correlation (see Figure 1). NPV represents the present 

day cost of some action taken at some time in the future; in essence the present day value of that distant 

cost is discounted by the applicable interest rate over that period of time. 

Remediation performance increasingly features as one of the principal sources of project risk and 

uncertainty to which organisations involved in brownfield development and reclamation are exposed. 

Thus, lenders providing finance on built projects (i.e., which do not involve remediation) will generally 

set a floor IRR (i.e., a minimum rate of return) that is lower than the rate for a brownfield reclamation, 

other factors being equal (see Figure 1). Interestingly, lenders in the UK do not necessarily set different 

rates of return for similar projects on brownfield sites and land that has not been previously developed
Decision Support Tools NATO/CCMS Pilot Project Phase III 

84 

(Finnamore et al, 2000). Instead, borrowers are normally required to demonstrate increased levels of due 

diligence and risk management where contamination is a known or perceived issue. 

Where remediation forms part of a defence plan to avoid liabilities, the principal risks surround escalation 

in costs and the realisation of liabilities if the remediation fails to meet the risk management objectives. 

Of particular concern are potential third party liabilities for bodily injury and property damage, which can 

cause unlimited financial impact. There are also knock-on effects in terms of reduced confidence amongst 

a company’s stakeholders, which can translate directly into reduced share value or indirectly into 

increased cost of future financing and insurance. Independent research carried out on behalf of Citibank 

suggests that around 70% of a company’s net worth is determined by the markets’ perception of the 

company. 

Figure 1. Illustration of the relationship between IRR, project risk and project acceptability 

The effectiveness of remediation can be judged financially in terms of: 

• meeting, or preferably beating, projected cost estimates (project costs) 

• ensuring timely release of the property asset for income generating use (revenue) 

• maintaining, or preferably, enhancing the value of the property (asset value) 

• increasing the liquidity of the asset (liquidity) 

• reducing/avoiding existing liabilities whilst avoiding creating new liabilities (risk management) 

The financial risk associated with remediation stems from an inability, or perceived inability, to forecast 

its effectiveness in meeting these project objectives. The difficulty in forecasting this risk stems from the 

inherent volatility in, and complexity of, project costs and revenues, asset value, liquidity and risk 

management. The volatility is due to variation in remediation-specific factors and other external technical, 

scientific, regulatory, financial and economic factors. Certain variables are well understood and defined. 

Others show considerable natural variation that is poorly defined. Understanding these variables and the 

relationships that link them underpins any approach that seeks to forecast the financial risk of 

remediation. 

Generally, the process of estimating the financial risks of remediation is improving, and will continue to 

do so. This is due in large part to growing experience of using various remedial technologies. 

Nevertheless, considerable uncertainty persists, whilst the levels of confidence that can be attached to 

financial forecasts show significant variation according to, amongst other factors, the technology under 

Internal rate of return

Investment risk

 IRR = ~7%

Government lending

e.g. Treasury bonds

(essentially risk-free

investment)

Brownfield

reclamation

IRR > floor IRR

(project/investment acceptable)

Floor IRR

Built projects

Greenfield

development

IRR < floor IRR

(investment

unacceptable)
Decision Support Tools NATO/CCMS Pilot Project Phase III 

85 

consideration. This reflects the different uptake, application and, hence, experience of working with some 

technologies. 

FINANCIAL RISK ANALYSIS 

The process of financial risk analysis for remediation is no different to the appraisal techniques applied to 

other project risks, and can be broken down into the following steps (Institution of Civil Engineers and 

the Faculty and Institute of Actuaries (1998). 

Risk Identification 

The main objective of the risk identification stage is to identify events, which, if they arose, could 

threaten the achievement of the project’s objectives. Such events are summarised in the form of a risk 

matrix, which outlines the risks that exist throughout the various stages of a project, along with the 

underlying causes. Each event can be triggered by one of more causes and can generate a number of 

financial outcomes, as illustrated in Figure 2. 

Figure 2. The likelihood of possible outcomes 

(Institution of Civil Engineers and the Faculty and Institute of Actuaries, 1998).

1. RISK EVALUATION 

The risk evaluation stage generates forecasts of the impact of remediation risk on the financial 

performance of a project. The impact is analysed using bespoke financial models, which describe the 

financial performance of remedial technologies under multiple scenarios. The basis of each model is a 

series of algorithms. These describe mathematically the relationship between the variables which 

determine the probability of a risk event arising, as well as the probability and impact of the associated 

financial consequences (if the event occurs). Each model runs stochastically (probabilistically). Using this 

approach, discrete input values for variables are replaced by probability distribution functions (PDF’s) 

which are sampled randomly many times by Monte Carlo simulation to build up a probability distribution 

of possible financial outcomes. The stochastic approach can avoid ‘creeping’ conservatism of 

deterministic models caused by sequential selection of ‘worst-case’ input values. However, stochastic 

models may suffer from systematic error caused by inaccuracies in constructing the model and defining 

PDFs for each variable or in generating the random numbers used to sample the PDFs. 

Cause A

Cause B

Cause C

Cause D

Outcome 1

Outcome 4

Outcome 3

Outcome 2

1. Probability of

event arising

2. Probability of outcome occurring

(if event occurs)

Event
Decision Support Tools NATO/CCMS Pilot Project Phase III 

86 

The process of generating a financial model is illustrated in Figure 3. 

function (a,b,c,d,e...)

a bc d e

Cost of environmental risk

Cumulative

Probability

iii) Generate the equation which links the

 variables

ii) Assign values to each variable

NB. Values are provided in the form of

probability density functions (PDFs)

rather than discrete values

iv) Run Monte Carlo or Latin

 Hypercube simulation

 to generate aggregate

 financial risk profile

i) Identify the variables which

 affect the risk

(1) Identify contaminated land scenario /

risk events e.g. aborted development, failure

to secure tenant

(2) Assess company’s exposure to each

scenario

Scenario x Scenario y Scenario z etc

(3) Discount financial impact to present

value

 

Figure 3. Simplified illustration of the modelling process 

The structure and composition of the algorithms depends on the type of remediation and site/project specific 

characteristics. Algorithms are constructed by ‘process mapping’ remedial technologies and applying 

deductive methods. Alternatively, empirical or data-based methods may be used. 

Process mapping breaks the remediation process down into various components, addressing inputs and 

outputs such as energy, waste etc. PDF’s are assigned to variables based on: 

• empiric data which relies on site-specific measurements and observations; 

• default data from similar projects; or 

• informed judgement 

For remediation techniques that are relatively well understood, such as excavation and disposal, process 

mapping is relatively straightforward. In such cases, constructing the cost model algorithm and assigning 

PDF’s is also relatively simple. For more complex remediation projects, or those involving innovative, 

untested process-based technologies, the process can be more complex and systematic errors are likely to 

increase. The use of probabilistic models in valuing contaminated land has been described by Kennedy, et 

al. (1996). In their work Kennedy et al built in uncertainty regarding remediation cost and duration in to a 

spreadsheet of NPV for the redevelopment of a fictitious site. They used Latin Hypercube Sampling 

(LHS) – a more computationally efficient variant of Monte Carlo (Nathanail 1994) for sampling the 

PDFs. 

Critical model variables in terms of the importance of obtaining site-specific data include those relating to 

the nature and extent (lateral and vertical) of contamination. Interpolating from point information (such as 

trial pits or boreholes) to model the spatial distribution of contamination is frequently carried out using 

deterministic interpolators such as triangulation or inverse distance squared or by manual methods. Such 

approaches fail to adequately recognise the uncertainty in interpolation. Geostatistical techniques such as 

kriging do recognise this uncertainty and provide a qualitative indicator of uncertainty in the interpolation 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

87 

through the kriging variance. However kriging, in common with other weighted average interpolators, 

tends to smooth the raw data – effectively underestimating in areas of high values and overestimating in 

areas of low values. Geostatistical conditional simulations on the other hand preserve the variability in the 

original measurements and can be used to produce estimates of the probability of exceeding threshold 

values – such as risk based levels. Conditional simulations may therefore be used to inform cost models 

of the uncertainty in the extent and volume of contamination to be `tackled – and therefore the cost of 

remediation (Nathanail et al. 1998; Nathanail & Rosenbaum 1991). 

Models are constructed in three sections - ‘front end’, processing and data presentation – reflecting the 

three functions of the model. The front end comprises a system for downloading information relating to 

the risk being analysed. The processing section of the model contains the algorithms that compute and 

‘score’ the risks on the basis of the entered information. The data presentation component contains the 

macros that enable interrogation of the model. 

1. FINANCIAL RISK MANAGEMENT 

The findings of the risk analysis can be used to formulate an appropriate risk management strategy, typically 

based on a combination of risk control (reduction and mitigation) financing and transfer techniques. Two 

techniques are discussed below: 

a. Contractual risk transfer 

In the example shown in Figure 4, the remediation costs of development are expected to be £10 million. The 

contract incorporates an excess layer of insurance, which covers cost overruns of up to £20 million for a 

premium of £1 million. The £1.5 million deductible is covered in full by the contractor, which puts all of its 

profits at risk. The problem holder bears the unlikely risk that costs exceed the insurance cover (i.e., any 

project costs in excess of £30 million, whilst sharing any cost savings (if the project costs less than £10 

million) with the contractor according to a predetermined formula. 

£10 million

estimated

development

cost to owner

?

Cost cap:

£18.5 million

insurance limit

£1 million

insurance premium

Owner remains responsible for

development costs exceeding £30 million

Insurer responsible for development

costs in excess of £11.5 million and

less than £30 million

£1.5 million insurance

deductible

Expected

remediation

cost

Potential

liability

covered by

insurance

Potential

liability not

covered by

insurance

If actual costs are below expected

£10 million, owner and contractor share

savings

Contractor responsible for development

costs in excess of £10 million and less

than £11.5 million

Figure 4. Illustration of a risk sharing remediation contract involving insurance 

(Merkl, A and Robinson, H (1997) 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

88 

b. Insurance 

Clean up cost cap policies indemnify the insured for remediation costs, as defined in the remedial 

strategy, that exceed a cost estimate agreed with the insurer. This value may be defined by modelling the 

remedial plan in order to express technical risks in financial terms. The policy attaches over a prescribed 

self-insured retention (SIR), which is generally equal to the expected costs of remediation plus a buffer 

layer. 

Payment is triggered by increased projects costs caused, for example, by the discovery of unknown 

contamination or greater amounts of known contamination. Cover is also provided for extra costs to 

change the remediation works, in the event that the enforcing authority requires these changes. Cover may 

also be available for additional site investigation and any legal costs that could not have been reasonably 

anticipated under the remediation plan. 

The buffer that is set will reflect the insurer’s confidence in the insured’s initial cost estimates and 

contingencies. The premium will normally depend on the cost and type of remedial work, the 

comprehensiveness of the remedial strategy and the amount of self-insurance. 

CASE STUDY: A Site in East London, UK 

Background 

This case study is based on a site in East London, which was undergoing development for a combination of 

residential and light industrial purposes. A comprehensive site investigation had identified widespread 

contamination for which excavation and disposal had been put forward as an appropriate remedial strategy. 

A quantitative risk assessment had defined site-specific target levels (SSTLs) for remediation. 

Using an investment model, the expected value of the project was £6 million based on future earnings from 

renting the commercial premises and from sales of the residential plots. The costs associated with 

development of the site were estimated at £4.5 million, including the purchase price of the land and 

construction costs, but excluding remediation costs. Thus the maximum potential net present value for the 

project was £1.5 million. 

Financial analysis 

The potential impact of remediation costs on the project NPV was simulated using a separate cost model. 

Based on site investigation data, the lateral and vertical extent of contamination was modelled using 

geostatistics. The outputs comprised a series of 3-d contour plots of contamination exceeding the SSTLs 

at various degrees of confidence. For each plot, the corresponding volume of soil (as measured in the 

ground) was calculated, creating an empirical probability distribution of contaminated soil volumes. In 

this case, the data approximated to a lognormal distribution, which was incorporated into the cost model.

The re-use of clean, inert excavated material as backfill for other areas of the site was also incorporated 

into the model. 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

89 

Examples of the variables on which the model was constructed are illustrated in Table 1. 

Table 1. Examples of the variables for the cost model

Variable PDF Data source 

A. Quantity of soil requiring disposal 

Volume of contamination exceeding SSTL (m3) Lognormal Empirical (based on geostatistics) 

Excavation bulking factor (excavation) Triangular Default 

B. Cost of excavation and disposal of contaminated soils 

Distance to landfill site (miles) Triangular Site-specific data 

Trimming and excavation charges Uniform Default 

Volume of waste per lorry load (m3) Triangular Default 

Disposal charge (landfill) (£ per m3) Triangular Default 

Special waste consignment charges (£ per load) Discrete Default 

Haulage rates (£ per m3) Uniform Default 

Importation of clean fill material (£ per m3) Triangular Default 

Figure 5. Cost forecast chart

 

Cumulative Chart

Certainty is 94.92% from -Infinity to 268,333.33

.000

.250

.500

.750

1.000

0

30000

0.00 437,500.00 875,000.00 1,312,500.00 1,750,000.00

30,000 Trials 40 Outliers

Forecast: TOTAL COSTS

Number of 

Monte Carlo 

trials 

Maximum cost in range 

Display range 

Cost forecasts

lying outside

range
Decision Support Tools NATO/CCMS Pilot Project Phase III 

90 

Table 2. Remediation cost forecasts and associated limits of confidence 

Limit of confidence in cost forecast (%) Maximum remediation costs (£) 

99.99 ~4,800,000 

99.9 ~2,000,000 

99.6 1,500,000 

99.0 702,000 

95.0 270,000 

90.0 160,000 

80.0 86,000 

70.0 55,000 

60.0 40,000 

50.0 26,000 

40.0 18,000 

30.0 12,000 

20.0 8,000 

The results of the financial analysis of remediation costs were compared with the NPV generated by the 

investment model. The results of the analysis confirmed that at a level of confidence of 99.6% 

(representing a remediation cost forecast of £1.5 million), the remediation costs would not impact on the 

projected NPV to an extent that would make the project non-viable. 

CONCLUSIONS 

Probabilistic modelling of remediation costs can be used to analyse the financial risks arising from land 

contamination and determining where the largest uncertainty and potential impacts on company or project 

performance are to be found. In this way remediation related risks can be managed in a way best suited to 

the organisation facing the risk and unforeseen consequences arising from land contamination can be 

minimised. 

Detailed guidance tailored to the UK situation is forthcoming (Finnamore et al. 2000). 

ACKNOWLDEGEMENTS 

The author gratefully acknowledges review comments received from Dr Paul Nathanail (Land Quality 

Management, UK) during the preparation of this paper. 

REFERENCES 

Finnamore, et al. (2000) Land contamination: management of financial risk. CIRIA Report, CIRIA, 

London. (In publishing) 

Institution of Civil Engineers and the Faculty and Institute of Acutaries (1998) Risk Analysis and 

Management for Projects, Thomas Telford Ltd, London. ISBN: 0 7277 2697 8 

Kennedy, P.J., Nathanail, C.P., Abbachi, A., and Martin, I.D. 1996. Impact of spatial distribution of land 

contaminants and property investment appraisal. In: Proc. AGI ’96. Association for the Geographic 

Industry, London 25 Sept 1996 

Merkl, A. and Robinson, H (1997) Environmental risk management: take it back from the lawyers and 

engineers” The McKinsey Quarterly, 1997, No.3 

Nathanail C P, Ferguson C C, Browne M J & Hooker P J. 1998. A geostatistical approach to spatial risk 

assessment of lead in urban soils to assist planners. Proc 8th Int Congress IAEG, Balkema, 369-376. 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

91 

Nathanail, C. P. & Rosenbaum, M. S. (1991) Spatial interpolation in GIS for environmental studies. 

Proceedings of the Third National Conference of the Association of Geographical Information,

Birmingham. Association of Geographical Information, Great George Street, London, pp 2.20.1 - 2.20.7. 

Nathanail, C. P. (1994) Systematic modelling and analysis of digital data for slope and foundation 

engineering. PhD Thesis, London University (unpublished).
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 92 

DECISION SUPPORT USING LIFE CYCLE ASSESSMENT IN 

SOIL REMEDIATION PLANNING 

S. Volkwein, C.A.U. GmbH, Germany 

Daimler Str. 23, 63303 Dreieich, Germany, www.cau-online.de

Key words: Decision support tool, environmental balancing, environmental management, life cycle 

assessment, planning, soil remediation, sustainability, "Umweltbilanzierung von 

Altlastensanierungsverfahren" 

ABSTRACT 

Sustainable soil remediation shall be based on decision support systems that cover the evaluation of the 

environmental burdens caused by the remediation itself. The basic tool life cycle assessment can fulfill 

this task. Since the year 2000, all four elements of the life cycle assessment method are described by 

international standards (1SO 14040, ISO 14041, ISO 14042, ISO 14043). Since the year 1999, a life cycle 

assessment based tool is publicly available as software, which can help soil remediation planners to 

evaluate the environmental burdens of remedial actions itself. Today, a state of the art soil remediation 

planning tool-box includes life cycle assessment based tools. 

1 INTRODUCTION 

The requirement of sustainable development restricts the right to development (principle 3 of the Rio 

declaration on environment and development; UNEP, 1992). The right to development must be fulfilled 

so as to equitably meet developmental and environmental needs of present and future generations. One 

important issue in sustainable development is the management of soil. Soil management has often to 

tackle with contaminated soil. Many sites have been contaminated due to incompetent or criminal 

industrial or governmental management. Some sites are additionally or primary contaminated due to 

military industrial activities or military actions. Table 1 lists some contaminated sites and some soil 

pollutants. 

Table 1. Some contaminated sites made by NATO or NATO member states

Contaminated sites made in peace Contaminated sites made in war (UNEP, 1999) 

Kelly Airforce Base, San Antonio, 

Texas, USA: hydrocarbons (BMBF, 

1996) 

Pancevo (Serbia) "HIP Azotara" fertilizer plant and 

"HIP Petrohemija Pancevo" petrochemical plant, 

waste water canal to Danube and Yugoslavian, 

Romanian and Bulgarian Danube (4 April - 7 June 

1999): 2,1 gigagram 1,2-dichloroethane (EDC), 8 

Megagram mercury, oil, chlorinated solvents, depleted 

uranium 

Building 360 at Naval Air Station 

Alameda (California, USA, 

Department of Defense): chloroethene 

compounds (NATO, 1999) 

Kragujevac (Serbia) Zastava car plant (9 - 12 April 

1999): 1 Megagram polychlorinated biphenyls (PCB) 

and polychlorinated dibenzodioxins (dioxins) 

Carswell Air Force Base, Fort Worth 

(Texas, USA): Chlorinated solvents 

(NATO, 1998) 

Novi Sad (Serbia) oil refinery (5 April - 2 May 1999): 

oil products, depleted uranium 

Kleingötz near Günzburg, Germany, 

air base, ammunition testing: 

Bor (Serbia) capacitors (15 May 1999): 

polychlorinated biphenyls (PCB) 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 93 

Contaminated sites made in peace Contaminated sites made in war (UNEP, 1999) 

trinitrotoluol (TNT), heavy metals, 

polycyclic aromatic hydrocarbons 

(PAH), 1,1,1-trichloro-2,2-bis(4-

chlorophenyl)ethane (DDT) 

(Heuschneider et al., 2000) 

The requirement of sustainable development demands the prevention of contamination of soil. 

Furthermore, the requirement of sustainable development often can only be fulfilled if the contaminated 

sites are remediated. The way of cleaning-up contaminated soil is also relevant for sustainable 

development. 

Since 1993, the German state Baden-Württemberg requires by law (VwV, 1993) the consideration of the 

environmental burdens of the remediation action itself. Six years later, the legislation for whole Germany 

(BBodSchV, 1999) followed Baden-Württemberg (table 2). In the mean time, Baden-Württemberg 

directed the development of a method for the evaluation the potential environmental impacts of soil 

remediation options (Volkwein 2000a, 2000b, 2000c; Volkwein et al., 1999, Bender et al. 1998, 

Volkwein et al. 1998). Finally in 1999, Baden-Württemberg released a software tool (LFU, 1999) 

"Umweltbilanzierung von Altlastensanierungsverfahren" ("Environmental balancing of soil remediation 

measures") which should be easily used by soil remediation planners in the planning process. 

Table 2. Foundation for looking at environmental burdens caused by soil remediation measures itself

Foundation of looking at 

environmental burdens caused by soil 

remediation measures itself 

Example 

International legislation or conventions Rio Declaration, sustainability principle (UNEP, 

1992) 

National legislation German legislation about soil remediation 

(BBodSchV, 1999) 

Local legislation Baden-Württemberg legislation about soil 

remediation (VwV, 1993) 

International standards Environmental management systems for 

organizations: continuous improvement of overall 

environmental performance of activities (ISO 

14001:1996) 

Between 1996 and 2000 several international standards about environmental management emerged. The 

starting point is the standard ISO 14001:1996. ISO 14001 addresses to organizations. An environmental 

management system of an organization must include a commitment for a continuous improvement of the 

overall environmental performance of the activities of the organization. The overall environmental 

performance of an activity (service) can be measure with the management tool life cycle assessment (ISO 

14040:1997, ISO 14041:1998, ISO 14042:2000, ISO 14043:2000). Due to the standardization, life cycle 

assessment is an internationally accepted tool. No other tool for the determination of the overall 

environmental performance of services has such detailed description of the methodology in ISO 

standards. Life cycle assessment is applied since 30 years under different names in industrial and other 

organizations (Hunt and Franklin, 1996). Life cycle assessment is the first choice for the evaluation of the 

overall environmental performance of a service. 

The overall environmental performance of a site clean-up can be explored using life cycle assessment 

based tools. The decision support tool "Umweltbilanzierung von Altlastensanierungsverfahren" 

("Environmental balancing of soil remediation measures") allows the fulfillment of the 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 94 

• sustainable development principle for soil remediation and 

• the organizational requirements of ISO 14001 for soil remediation organizations. 

2 LIFE CYCLE ASSESSMENT FRAMEWORK 

The life cycle assessment (LCA) method is still under development, but practitioners can refer to four 

international standards (ISO 14040:1997, ISO 14041:1998, ISO 14042:2000, ISO 14043:2000). 

According to the ISO standards, every life cycle assessment consists of four parts (Figure 1): 

• goal and scope definition 

• life cycle inventory 

• life cycle impact assessment 

• life cycle interpretation 

Direct applications:

•„Umweltbilanzierung von Altlastensanierungsverfahren“

(Environmental

balancing of soil

remediation

measures)

LCA framework

Goal and 

scope 

definition

Inventory

analysis

Impact

assessment

Interpretation

Figure 1. Life cycle assessment (LCA) framework adapted from ISO 14040:1997 with 

special direct applications for soil remediation planning 

Life cycle assessment can analyse whole life cycles of services (products). The primary application of 

LCA is the analysis of the use phase of a product (service). Also important is the application in the 

manufacturing phase (design phase, eco-design). Another field for the application of LCA is the end of 

life analysis or end of pipe service analysis. 

3 SOIL REMEDIATION PROCESSES 

The soil remediation planning often starts with a historical reconnaissance of the contaminated site. A 

more detailed investigation of the pollutants, the amount of the pollutants and the distribution of the 

pollutants follows. Preliminary site remediation options are developed. At this point, the evaluation of the 

environmental burdens of the different site remediation options can start. The soil remediation planner 

can then use the result of this environmental evaluation together with the results of financial, legal, social 

and risk assessments to select the finally applied soil remediation option. 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 95 

The future regular evaluation of the environmental burdens of the contaminated sites remediation has the 

following requirements: 

• soil remediation planner should be able to make this evaluation himself 

• low demand of time for this evaluation 

Therefore, a tool for the evaluation of the environmental burdens should speak the "language" of the soil 

remediation planner. This language includes phrases like the following: 

• mass of soil to be treated 

• volume of soil to be treated 

• transport distances for soil transport 

• time of the clean-up 

• type of the applied technologies for soil remediation 

The tool for the evaluation of the environmental burdens should have predefined processes. Such a feature 

can support a quick application of the tool. The process names should be those which the soil remediation 

planner uses. The input data for the processes should be in the "language" of the soil remediation planner. 

Table 3 lists several processes that might be necessary to make a full soil remediation option. 

Table 3. Processes often used in soil remediation measures

General type of 

process 

Group of 

processes 

Processes, detailed for soil remediation option selection 

Soil washing – mobile facility 

Soil washing – semi-mobile facility 

Soil washing 

Soil washing – stationary facility 

Microbiological soil treatment – turning bed 

Microbiological soil treatment - rotting/composting 

Microbiological soil treatment – reactor 

Microbiological 

soil treatment 

Microbiological soil treatment – near to the surface zone 

in-situ 

Thermal treatment – Herne 

Thermal treatment – Deutzen 

Thermal 

treatment 

Vacuum distillation 

Pneumatic tech. Pneumatic techniques 

Microbiological groundwater treatment in-situ 

Decontamination 

(clean-up) 

Groundwater 

treatment in-situ Reactive walls 

Immobilization Immobilization 

Sheet-pile wall 

Narrow wall 

Sealing walls, 

leak proof walls 

High-pressure injection wall 

Capillary break 

Ensuring 

technologies 

Surface sealing 

Surface covering 

Asphalt covering 

Foundation, floor plate 

Consolidating, compacting 

Material consumption - processed earth materials 

Material consumption – plastics and concrete 

Material transport on-site 

Distribution with bulldozer 

Secondary 

technologies 

Civil 

engineering 

Wells 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 96 

General type of 

process 

Group of 

processes 

Processes, detailed for soil remediation option selection 

Excavation work 

Soil treatment: sieving, crushing 

Adsorptive waste air cleaning 

Catalytic waste air cleaning 

Waste air 

cleaning 

Biological waste air cleaning 

Extraction of ground-water 

Ground-water cleaning – stripping 

Ground-water cleaning – sedimentation 

Ground-water cleaning – precipitation, flocculation 

Ground-water cleaning – chemical oxidation 

Ground-water cleaning – adsorption 

Ground-water cleaning – ion exchange 

Ground-water 

cleaning 

Ground-water cleaning – dewatering 

Mobilization, demobilization 

Soil transport street lorry 

Soil transport river ship 

Soil transport rail train 

Transport 

Transport of persons by car 

The processes listed in table 3 are some of the processes included in the software tool "Environmental 

balancing of soil remediation measures" (LFU, 1999). The software tool "Environmental balancing of soil 

remediation measures" links these process data to generic life cycle assessment data and to a life cycle 

impact assessment model. The calculation of the life cycle impact assessment is automated. Results of the 

life cycle impact assessment and the life cycle inventory are transformed to an easy to interprete 

disadvantage factor table. An example is given in the following section. 

4 CASE STUDY “FORMER COMPANY REINIG IN SINSHEIM”

The example "former company Reinig in Sinsheim" includes the comparison of three remedial 

alternatives. The contaminated site of the former company Reinig in Sinsheim has an area of 20000 

square meter. Mineral oil contaminates 530 cubic meter, polycyclic aromatics (PAH) 750 cubic meter, 

and chromium 530 cubic meter soil. 

"On-site ensuring" means the excavation and on-site redumping of the contaminated soil. The second 

remedial option ("soil sealing") is the simple sealing of the surface by asphalt. The "decontamination" 

option requires the excavation and three different treatments. 75 m3

 of contaminated concrete is included 

in the “on-site ensuring” option, but not in the other two options “soil sealing” and “decontamination”. In 

the option “on-site ensuring”, only 50 % of the PAH contaminated soil is excavated. The other 50 % of 

the PAH contaminated soil is under the clamp of the redeposited contaminated soil. 

The details of the environmental balancing of the case study "former company Reinig in Sinsheim" are 

described in LFU (1999) and Volkwein et al. (1999). The disadvantage factor table 4 shows one important 

result. A disadvantage factor 1 means that the parameter value for the remediation option is the lowest 

among the compared remediation options. The cumulative energy demand (one of several parameters) is 

for the "on-site ensuring" lower than for "soil sealing" and "decontamination". Therefore, the 

disadvantage factor for the cumulative energy demand of "on-site ensuring" is one. The "soil sealing" 

requires a 20 times higher cumulative energy demand than on-site ensuring. 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 97 

Table 4. Disadvantage factors for the case study "former company Reinig in Sinsheim" 

Impact categories and energy and waste On-site ensuring Soil 

sealing 

Decontamination 

Cumulative energy demand 1 20 4 

Waste total 1 2 40 

Waste from contaminated site to landfill ! 

Fossil resources 1 30 4 

Water 1 5 5 

Land 2 7 1 

Global warming 1 5 5 

Acidification 1 5 3 

Photo-oxidant formation 1 20 4 

Toxicity air – remote emissions 1 3 4 

Toxicity water 1 30 4 

Toxicity soil 1 30 4 

Odor – remote emissions 1 5 3 

Toxicity air – near emissions 1 1 1 

Odor – near emissions 1 1 1 

Noise immission 60 dB(A) 1 1 1 

Noise immission 66 dB(A) ! 

Sum of disadvantage factors NOT ALLOWED 

A "!" indicates that the other options have a parameter value "0". Soil washing in the option 

"decontamination" results in a certain amount of waste from the contaminated site. The options "on-site 

ensuring" and "soil sealing" have no "waste from the contaminated site" (parameter value = 0). This is the 

reason for the disadvantage factor "!" for the "decontamination" option. 

One among several conclusions of this case study is, that the option "soil sealing" is in all analyzed 

parameters in table 4 equal or worse than the "on-site ensuring" option. A more detailed discussion of the 

results can be found in Volkwein et al. (1999) and LFU (1999). 

5 CONCLUSIONS 

Life cycle assessment is in use for analyzing whole life cycles of services (products). The primary 

application of LCA is the analysis of the use phase of a product (service). Also important is the 

application in the manufacturing phase (design phase). Another field for the application of LCA is the end 

of life analysis or end of pipe service analysis. The remediation of contaminated sites is a end of pipe 

service (repairing service for upstream industrial processes). 

A necessity exists for knowing the environmental burdens of remedial actions itself if the sustainable 

development principle is applied or if compliance with ISO 14001 is desired. Life cycle assessment is the 

tool with the biggest international acceptance for evaluating environmental burdens of services 

(products). There are 30 years of industrial experience with life cycle assessment. There are three years of 

experience with an international standard about the basics of life cycle assessment (ISO 14040:1997). 

There is one year of experience with a publicly available software tool based on life cycle assessment. A 

state-of-the-art soil remediation tool-box shall include life cycle assessment based tools. 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 98 

6 REFERENCES 

BBodSchV: Bundes-Bodenschutz- und Altlastenverordnung (BBodSchV). Bundesministerium für 

Umwelt, Naturschutz und Reaktorsicherheit, Berlin 16.6.1999. TerraTech 1999, 4, 22 - 36 

Bender, A.; Volkwein, S.; Battermann, G.; Klöpffer, W.; Hurtig, H.-W.; Kohler, W.: Life cycle 

assessment for remedial action techniques: methodology and application. ConSoil ’98, Sixth international 

FZK/TNO Conference on contaminated soil. Thomas Telford, London. 367 - 376 

BMBF: Forschungsvorhaben bilaterale Zusammenarbeit BMBF – U. S. EPA. Vorbereitung, 

Koordinierung, Durchführung und Auswertung der im Rahmen der deutsch-amerikanischen 

Zusammenarbeit geplanten zusätzlichen Untersuchungen an ausgewählten Altlastensanierungsfällen. 

Schlußbericht für den Bearbeitungszeitraum 1991 bis 1996. Band 3: Im den USA durchgeführte 

Technikdemonstrationen. Umweltbundesamt, Projektträger Abfallwirtschaft und Altlastensanierung des 

BMBF (Bundesministerium für Bildung, Wissenschaft, Forschung und Technologie). 1 - 320 

Heuschneider, P.; Beyer, J.; Kesselheim, J.; Abstein, G.: Konversion einer Rüstungsaltlast zum 

Freizeitpark. altlasten spektrum (Berlin) 2000, 2, 115 - 124 

Hunt, R. G.; Franklin, W.: LCA – How it came about. Personal reflections on the origin and the development 

of LCA in the USA. Int. J. LCA 1, 1996, 4 – 7 

ISO 14001:1996: Environmental management systems. Specification with guidance for use. International 

Standards Organization, Geneva 1996 (www.iso.ch) 

ISO 14040:1997: Environmental Management. Life cycle assessment. Principles and framework. 

International Standards Organization, Geneva 1997 (www.iso.ch) 

ISO 14041:1998: Environmental Management. Life cycle assessment. Goal and scope definition and 

inventory analysis. International Standards Organization, Geneva 1998 (www.iso.ch) 

ISO 14042:2000: Environmental Management. Life cycle assessment. Life cycle impact assessment. 

International Standards Organization, Geneva 2000 (www.iso.ch) 

ISO 14043:2000: Environmental Management. Life cycle assessment. Life cycle interpretation. 

International Standards Organization, Geneva 2000 (www.iso.ch) 

LFU: Umweltbilanzierung von Altlastensanierungsverfahren. Version 1.0 Rev. 16. 1999 CDROM 

including description of methodology. Landesanstalt für Umweltschutz Baden-Württemberg (LFU). 

Available from AHK Gesellschaft für Angewandte Kartographie mbH, Rehlingstraße 9, 79100 Freiburg, 

Germany, FAX +49 - 7 61 – 7 05 22 – 20, www.ahk-freiburg.de 

NATO: NATO/CCMS Pilot study. Evaluation of demonstrated and emerging technologies for the 

treatment of contaminated land and groundwater (Phase III). 1999 Annual report. Number 235. North 

Atlantic Treaty Organization (NATO), Committee on the challenges of modern society (CCMS). 1 – 187. 

www.clu-in.org 

NATO: NATO/CCMS Pilot study. Evaluation of demonstrated and emerging technologies for the 

treatment of contaminated land and groundwater (Phase III). 1998 Annual report. Number 228. North 

Atlantic Treaty Organization (NATO), Committee on the challenges of modern society (CCMS). 1 – 135. 

www.clu-in.org 

UNEP: The Kosovo conflict. Consequences for the environment & human health settlements. United 

Nations Environment Programme (UNEP), Nairobi. United Nations Centre for Human Settlements 

(UNCHS), Nairobi. 1999, 1 – 107. www.unep.org 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 99 

UNEP: Rio declaration on environment and development. The United Nations conference on environment 

and development, Rio de Janeiro from 3 to 14 June 1992. United Nations Environment Programme 

(UNEP), Nairobi. www.unep.org/Documents 

Volkwein, S.: Governmental policy for soil remediation regarding overall environmental performance. 

Proceedings of ConSoil 2000a. 7th International FZK/TNO Conference on Contaminated Soil. Thomas 

Telford, London. Submitted 

Volkwein, S.: Life cycle assessment of soil remediations with a software tool. Proceedings of ConSoil 

2000b. 7th International FZK/TNO Conference on Contaminated Soil. Thomas Telford, London. 

Submitted 

Volkwein, S.: Comparison of software tools: "REC" and "Umweltbilanzierung von 

Altlastensanierungsverfahren". Proceedings of ConSoil 2000c. 7th International FZK/TNO Conference on 

Contaminated Soil. Thomas Telford, London. Submitted 

Volkwein, S.; Bender, A.; Klöpffer, W.; Hurtig, H.-W.; Battermann, G.; Kohler, W.: Life cycle 

assessment method for remediation of contaminated sites. ConSoil ’98, Sixth International FZK/TNO 

Conference on Contaminated Soil. Thomas Telford, London. 1069 – 1070 

Volkwein, S., Hurtig, H.-W., Klöpffer, W.: Life Cycle Assessment of Contaminated Sites Remediation. 

Int. J. LCA 1999, 4, 263 – 274 

VwV: Gemeinsame Verwaltungsvorschrift (VwV) des Umweltministeriums und des Sozialministeriums 

über Orientierungswerte für die Bearbeitung von Altlasten und Schadensfällen. Umwelt- und 

Sozialministerium Baden-Württemberg. 1115 - 1123. Gemeinsames Amtsblatt ISSN 0939-2726. 41 (33) 

30.11.1993.
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 100 

APPROACHES TO DECISION SUPPORT IN 

THE CONTEXT OF SUSTAINABLE 

DEVELOPMENT

Simon J T Pollard, Jonathan Fisher, Clare Twigger-Ross and Andrew 

Brookes, National Centre for Risk Analysis and Options Appraisal, 

Environment Agency, UK 

Steel House, 11 Tothill Street, London, SW1H 9NF, UK

ABSTRACT 

Decisions on the management of risks from contaminated land and groundwater have much in common 

with many modern environmental decisions. The desire to integrate technical, socio-political and 

economic factors during risk management has resulted in the development of decision “frameworks” that 

allow an holistic approach within a context of sustainable development1

. The application of integrated 

decision-making is in its relative infancy, however, and only recently have practitioners in contaminated 

land management considered its use. Here, we explore some of the decision tools that are available and, in 

the context of contaminated land remediation, explore the practical challenges with respect to integrated 

decision-making. Our aim is to set out some of the support tools that might be applied to contaminated 

site remediation, particularly at the site level. 

INTRODUCTION 

Environmental decision-makers have at their disposal a vast array of support tools that have been 

developed over the last 30 years2

. These tools are typically applied to assist with screening environmental 

impacts, for the assessment of risk / benefit trade-offs, for engaging a wider stakeholder community 

within decision-making processes and to the integration of technical, socio-political and economic factors 

that inform decisions on environmental management3

. Decision support tools for environmental appraisal 

are being used increasingly at the policy, programme, plan and project level across a spectrum of 

environmental issues4

. This presents opportunities for the cross-fertilisation of expertise and experience 

between disciplines and decision-making contexts (Table 1). 

Over a similar period, policy makers and practitioners in contaminated land management have been 

developing decision-making frameworks of their own5, 6, centering on well-established processes of risk 

assessment, risk management and risk communication (e.g., Figure 1). These frameworks embody many 

of the tools and component processes used by decision-makers elsewhere, including, but not restricted to: 

• brainstorming techniques (for hazard identification and conceptual model development for 

example); 

• scoping and screening (in qualitative risk assessment; in remedial technology selection); 

• environmental fate and transport modelling (as a component of exposure assessment); 

• sensitivity and uncertainty analysis (in quantitative risk assessment); 

• economic appraisal of costs and benefit (in comparing remedial approaches, including the costs of 

‘do nothing’ and the assessment of appropriate times for intervention) 

• data analysis (in site investigation); and 

• the collection of opinions and lay-perspectives on risk (for risk communication). 
Table 1. Synopsis of Decision Support Tools for Environmental Decision-Makers 

Tool Use Environmental arena in which tool has been 

conventionally applied 

Contaminated site context 

Environmental risk assessment 

Estimation of probability and consequence, usually for adverse environmental impacts at the sitespecific level, but can be applied at policy level as strategic risk assessment (SRA). 

Chemical product licensing, manufacture and use; production plant safety; environmental health protection; flood defence; liability auditing; contaminated land assessment; policy analysis; strategy setting. 

Context well established; identification and analysis of hazards and potential environmental harm from contaminated sites; use of probabilistic techniques for dealing with uncertainties in exposure assessment; sensitivity analysis to assist in remedial technology selection. 

Environmental (impact) assessment 

Environmental, social and economic impacts of proposed developments; summarised in non-technical language; participatory approach advocated; can also be applied at the policy or sectoral level as strategic environmental assessment (SEA). 

Environmental planning; siting of contentious installations (e.g., incinerators, landfills, tidal barrage); policy analysis; business sector analysis. 

Siting of plant for the long-term treatment of residuals (e.g., secondary treatment of pumped groundwater); siting of containment facilities: scoping matrix approach for principal environment impacts. Strategic environmental assessment might extend to land regeneration programmes. 

Social impact assessment 

Assessment of the impacts of planned developments on the social fabric of communities, includes equity issues and impacts on social processes. 

Not as yet conventionally applied in UK, more focused in USA and developing countries, but might provide useful basis for assessing the “social” part of sustainable development. 

On more complex sites, SIA could be used to analyse the social context of a site or regeneration programme and to identify key pressures and benefits / possible constraints on remediation 

Health Impact Assessment 

Assessment of the health impacts of a development or process. 

Recent call for it to be integrated into EIA 

– little 

distinction in practice from human health risk assessment within a planning context. Application in the context of air quality impact assessments for siting incinerators. 

Nested within human health risk assessment 
Table 1. (cont’d) Synopsis of Decision Support Tools for Environmental Decision-Makers 

Cost-benefit analysis 

Systematic and consistent appraisal and evaluation of economic and environmental costs and benefits of alternative projects, strategies and policies. 

Appraisal of proposed investments in flood defence projects; BATNEEC and BPEO assessments of pollution control measures; policy appraisal and regulatory impact assessments. 

Comparative assessment of risk reduction and costs for a variety of remedial technologies; assessing intervention times for groundwater plume remediation; at the strategic level may contribute to policy appraisal of statutory instruments and regulatory policies for contaminated sites. 

Multi-criteria analysis (MCA) and multi-attribute techniques (MAT) 

Integrated assessment of technical, social and economic impacts of alternative projects, strategies and policies. This incorporates monetisable/ quantifiable and nonmonetisable/quantifiable impacts. 

Assessment of risk management options; consistent appraisal of environmental benefits of water quality improvements by water industry so as to prioritise these measures in terms of their cost-effectiveness of securing environmental benefits. 

Assessment of technical, socio-political and economic factors associated with a range of remedial options; integrating ‘soft’ data on risk perception and political risks with quantitative cost estimates and remediation efficiencies. 

Environmental audit 

Account of activities and production and resulting effects on environment; usually undertaken by an independent team with management support; the collation, analysis, interpretation and documentation of practices relevant to environmental requirements; checklist and Y/N guide approaches are common. 

Improvement plans; setting insurance premiums; corporate environmental accounting and statements; liability (mergers, acquisitions and divestitures); regulatory compliance; efficiency of environmental management systems (EMS); due diligence; waste minimisation. 

Well established for multi-site comparisons; focus is on qualitative risk assessment: sourcepathway-receptor approach, worst-case and ‘reasonable’ worst case scenarios to drive remedial cost (liability) estimates. Considerable uncertainty in absence of site-specific information; multi-site comparisons undertaken by reference to source, receptor characteristics and regulatory pressure. 

Life cycle analysis Energy and mass balance from cradle 

to grave of products. 

Manufacture; product replacement and substitution; supply and product chain management. 

The design of sustainable remediation technologies and programmes; extension beyond simple capital and operational expenditure to issues of energy consumption and the secondary issues of residual products, off-gases and leachates and decommissioning, for example. See Volkwein et al.9
Table 1. (cont’d) Synopsis of Decision Support Tools for Environmental Decision-Makers 

Sustainability appraisal 

Developing area. Appraisal framework using sustainability objectives; potential application at all levels; flexible iterative process; indicators to monitor process; matrix/checklist approach. 

Appraisal of regional planning guidance and regional strategies; policy and strategy appraisal. 

Potential application to the appraisal of national or regional land regeneration programmes. Best viewed in terms of the integration of the above techniques. 

Stakeholder analysis 

Approach to analyzing the stakeholders involved in the decision process. Informal to formal approaches available; enables systematic consideration of all relevant parties and the relationships between those parties. Can provide an audit trail. 

Carried out in an informal way within the EIA process. Associated more with social impact assessment advocated by stakeholder dialogue practitioners as a component of other decisionmaking processes. 

Enables a systematic approach to understanding the range of stakeholders involved with a site / regeneration programme. Potential application to understanding the potential range of opinions and values that might be expressed regarding specific remediation options. 

Engagement techniques10

Citizen's juries – Involves major stakeholders in the process of the identifying and appraising of options - lay people brought together to deliberate on an issue, call witnesses and come to a verdict. Citizen's advisory groups - lay people bought together over a period of weeks to act as the voice of the community - can turn into a monitoring group once the decision has been made. 

Applied in the context of hazardous and radioactive waste management. 

Potential application for complex sites where a number of remediation options are possible and an informed public debate is desirable. 
Figure 2: Contaminated Land Decision-Support System

Key

Path to next step or activity.Iterative path.

Option to collect more data.

Notes

1

2

Assessors may decide to proceed directly from desk study andsite reconnaissance to detailed investigation and then toselection of Remedial Strategy (see text)

Increasing detail

Increasing cost

Data

Exploratory investigation may indicate need for emergencyaction in addition to further investigation. This may also bean outcome from site reconnaisance.

Risk Assessment Hazard

Identification

Hazard

Assessment

Risk

Estimation

Risk

Evaluation

Risk Management Evaluation and Selection

of Remedial Measures Implementation of Risk Management Actions

R Reiterative option - review management context and return to

appropriate point in the process

Phase 1 Phase 2

Remedial

Strategy

Design and

Implementation

Are Data

Sufficient?

Evaluate

Outcome

Document

and exit the

process

Long-Term

Monitoring

Evaluate

Outcome

Document

and exit the

process

No

No

Yes

Decide

Option

Decide

Option Yes

Yes

No

Nontechnical

action

Nontechnical

action

Data

Data

Is further

action

required?

Is further

action

required?

R

R

No

Document and

exit the process

START

Desk Study and

Site

Reconnaissance

Is further action

Evaluate

Findings

required?

Document and

exit the process

Exploratory

Investigation

Evaluate

Findings

Document and

exit the process

Detailed

Investigation

Evaluate

Findings

No

No

No

DecideOption

DecideOption

DecideOption

Yes

Yes

Yes

1

Remedial

Strategy Selection

Are Data

Sufficient?

Evaluate

Outcome

Is it Satisfactory?

Yes

No Yes

Emergency action 2

Non-technical

action

Non-technical

action

Non-technical

Action

Define Management

Context

Data

Is further action

required?

Is further action

required?

R

R

R

Are data

sufficient?

Yes

No

Are data

sufficient? No

Yes

Figure 1. Framework for the Management of Contaminated Land (after DETR and Environment Agency, 20006) 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 105 

Recent international reports and conference proceedings have pointed to a need to develop and adopt a 

broader range of decision support tools within the community of contaminated land practitioners7,8. Here 

we examine how some of the existing decision support tools might be applied to the challenges of 

contaminated land within a context of sustainable development.

SUSTAINABLE DEVELOPMENT: ISSUES IN INTEGRATED DECISION-MAKING 

A widely used international definition of sustainable development11 is ‘development which meets the 

needs of the present without compromising the ability of future generations to meet their own needs’. The 

UK strategy for sustainable development12, which sets about establishing a better quality of life for 

present and future generations, establishes as its key objectives: 

• social progress which recognises the need of everyone (equity within and among generations); 

• effective protection of the environment (proactive approach to limiting environmental damage); 

• prudent use of natural resources (clean and efficient use of non-renewable and renewable 

resources); and 

• maintenance of high and stable levels of economic growth and employment (improved living 

standards for all; quality goods and services; education and skills). 

This agenda gives weight to the integration of technical, socio-political and economic factors that inform 

decisions across Government, decisions that include, for example, about when and how to remediate 

contaminated sites. For practitioners, integration offers an opportunity to bring together appraisal and 

decision support tools historically used in isolation. Practical application, however, involves some 

considerable challenges, not least in resolving the differences in terminology, philosophy and output that 

are associated with individual tools (Table 2). The interface between the sustainable development agenda 

and the issue of land contamination is focussing on issues both relating to historic land contamination and 

those associated with the wider aspects of soil quality, including but not restricted to13-15

: 

• bringing land back into early beneficial use; 

• the efficient use of national resources to tackle issues of highest risk at priority sites; 

• reducing pressure on greenfield sites, thus conserving agricultural land and natural habitats; 

• adoption of a suitable-for-use approach towards land remediation; 

• prioritisation of remedial action so as to address the worst risks first in relation to the use of the 

land concerned; 

• distribution of impacts on communities; 

• the application of sustainable remediation technologies that conserve land and resources; 

• the consideration of point and diffuse sources of soil pollution over the long term; 

• the development and maintenance of new partnerships and fora among key stakeholders with 

agreements on a common research agenda; and 

• the development of monitoring systems that allow early detection of adverse soil changes. 

Addressing these issues requires a combination of policy, regulatory and technological responses that in 

themselves may require application of integrated decision support tools for a variety of policies, plans, 

programmes and projects. For example, the prioritisation of remedial measures in terms of which sites to 

act on first, the technology to be used and the appropriate times for intervention are increasingly subject 

to economic appraisal alongside issues of risk and technical feasibility16. As one contribution to the 

appraisal of sustainable remediation, economic appraisal brings new considerations to the decisionmaking process. We use this example below to illustrate some of the integration issues identified in Table 

2. A similar discussion can be had for social and environmental components.
Table 2. Integrating decision-support tools: some key challenges 

Challenge General commentary Contaminated sites context Identifying the full aspects of a problem 

Time needs to be invested at the outset to determine all these aspects. For example, there may be a mix of traditional EIA issues, risk and potential social and economic impacts. Application of brainstorming and ‘risk register’ techniques. Wide consideration of stakeholder views. Key practical challenge is of how to include all diverse impacts, aspects and considerations of a problem in a systematic manner without ‘double-counting’. 

Emphasis is usually on scoping out technical detail and conceptual model development, but often less emphasis on economic and social aspects of remedial programmes at the outset. Less the case for land regeneration subject to strategic assessment under the auspices of, for example, a local or regional plan. 

Setting boundaries for the analysis 

These need to be established and agreed both for consistency and for transparency and to make the appraisal practical. For example, there is a growing interest in EIA approaches encapsulating the entire life cycle of a project, ranging from the winning of raw materials to the final decommissioning and disposal stages. But there is a danger of becoming overwhelmed in excessive and unnecessary detail, so the analysis should concentrate on issues of significance to the environmental, economic and social impacts. 

Tend to be established by regulatory context and owner/developer. Often technically, or financially driven with less emphasis on social issues. Greater consideration and involvement of the range of audiences earlier on can help avoid difficulties later with respect to disagreements over the scope of studies, the communication of risk assessment output and remedial technology selection. 

Selecting individual techniques to potentially solve a problem 

It is difficult to find off-the-peg techniques that are scientifically, professionally and socially acceptable. There is a dearth of guidance. At present a wide range of methods exist from formal frameworks such as Risk Assessment, EIA and CBA to deliberative approaches. Any single problem may require unique or novel approaches tailored to the case in question, or adaptation of an existing decision-making tool. This can take time in the short run, but can avoid significant problems at a later stage. 

Most decision tools require tailoring to the specific circumstances because the context of application often requires an emphasis on certain aspects. An obvious example is the emphasis put on exposure assessment within the application of risk assessment for contaminated land. 

Maintaining professional rigour whilst working in a multidiscipline fashion to integrate techniques 

It is essential to apply rigorous professional standards in each discipline’s contribution, while still enabling their combination for the development of integrated techniques. 

Clear specification of the impacts of remediation option across disciplines (technical, economic, social), without double counting, during appraisal. 
Table 2. (cont’d) Integrating decision-support tools: some key challenges

Linking tools and techniques together as appropriate 

This is difficult because of the specific boundaries that surround techniques and the form in which each technique produces its findings. For example, risk assessment may report on the significance of a contaminant exceeding a threshold, whereas options appraisal techniques also need an analysis of risk reduction and residual risk to allow decisions to be made. Often it will be necessary to combine qualitative and quantitative information. Furthermore, models on which techniques are based may be incompatible. 

Clearest example is of using risk assessment output to inform remedial design and selection. These processes still often viewed as distinct, however. There is a greater need to practice early iteration of risk management decisions following screening level risk assessments, so as to refine detailed risk assessment work. 

Appropriate terminology to avoid misinterpretation of key terms and jargon 

The above challenges are compounded by differences in the language and jargon customarily used by different disciplines and the interpretations attached to specific terms. 

A common problem across the field of risk. Terminological differences can be overcome by focusing attention on the fundamental questions for which answers are sought. For example: hazard identification – what hazards are present on 

site? How might the consequences be realised? Who or what is at risk from these consequences? etc. 

Non-dominance No single technique or discipline must dominate the others or be 

perceived as dominating in reaching a final decision. 

Historically, technical issues have dictated remedial selection. Structured, integrated analysis made explicit may result in challenges to the way that this is presented. 

Consideration of increased public involvement 

Current calls for increased public participation. There is considerable experience in EIA but less so in risk assessment, CBA or technology assessment. Structured and focused approaches are necessary, together with an examination of institutional structures and their capacity for meaningful public involvement. Monitoring and validation of these mechanisms is critical. 

Increasing interest in risk assessment design and output. Mechanisms for participatory risk assessment not well established. Approach to date has been on technical risk assessment followed by ‘risk communication’ exercises to 

discuss output. US experience suggests limited success in this regard and many commentators now point to a need to apply engagement and participatory approaches. 

Considering values Deliberation is one way of uncovering people’s values, but there are 

challenges as to how those values are incorporated meaningfully into decision-making and how representative groups are, such that deliberative analysis of small groups views may need to be supplemented by surveys of a larger sample of the relevant population. 

Likely to have a complex range of values associated with a contaminated site. 

Risk perceptions and lay epidemiology 

Understanding the perspectives from which lay people address problems and valuing their local knowledge - challenge as to how local knowledge sits alongside expert knowledge. 

Local effects attributed to sites by individuals / communities. Difficulties of establishing causality and reconciling reported observations alongside exposure assessments. 
Table 2. (cont’d) Integrating decision-support tools: some key challenges

Handling uncertainty Recognition that in addition to uncertainty, there may be areas of 

ignorance where, in the presence of significant risk, the precautionary principle may be appropriate. To reflect the prevailing uncertainties results of appraisals need to be shown as ranges rather than discrete numbers. Uncertainty and sensitivity analysis can assist in highlighting the significance of ranges. 

Integral to most environmental decision-making tools. Issues of blight and financial risk ensure this is problematic for most contaminated sites. Emphasis on quality assurance and control with respect to consulting advice, site investigation design and practice and remedial monitoring. 

Using experts The appraisal community is now taking on board participatory 

methods, combining scientists and non-experts. This raises important challenges and methods of eliciting and sharing technical information need to be developed and interrogated. 

Use of experts at public inquiry especially with respect to remedial design and exposure assessments. Issues with respect to human health effects and toxicological data are difficult and tend to be addressed with reference to the deliberations of authoritative expert panels and committees. Application of expert elicitation techniques is common place in radioactive performance assessment for elicitation of receptor characteristics and representative ‘futures’. 

Deciding which timescale is appropriate 

For example, sustainable development requires a longer-term perspective to be taken. There may be a need to undertake ‘scenariobuilding’ in parallel with a particular appraisal technique. 

Issues of deciding when to intervene, for example, with respect to plume transport towards a public supply. Balancing times required for detailed assessment alongside plume advancement. Use of ‘what-if’ scenarios and futures to 

compare decisions. 

Trading-off one option against another 

There are particular challenges regarding how to present information on the trade-offs concerning risk management options. This also raises issues surrounding the choice of decision factors, the use of ranking, rating or scaling and, more controversially, weightings. 

Challenges are particularly difficult where there is considerable uncertainty in the component parts of the decision. Issue of comparing quantitative and qualitative information is heightened. 

Post-project analysis It is imperative that the process is evaluated and lessons learned. Improved project design and decision-making processes. 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 109 

THE EXAMPLE OF ECONOMIC APPRAISAL 

Economic appraisal is an important part of the appraisal of risk management options. It builds on the 

findings of the risk assessment and might typically involve the following generic steps: 

(i). determine whether there are any existing binding statutory requirements or remedial objectives set 

by a higher authority (e.g., Government department such as DETR or the EC), already subject to 

their own economic appraisal. If so, then the economic appraisal by regulatory agencies should 

comprise examining how to achieve these objectives as cost-effectively as possible. It may be that 

the statutory requirements stipulate some caveats regarding the stringency with which Agencies 

should apply them such as ‘unless excessively costly’ or ‘unless there are overriding public 

interests’ (see EC’s Habitats Directive). In such cases, the analysis would have to consider whether 

such caveats apply; 

(ii). where there are no existing binding requirements, it will be necessary to identify the alternative 

remediation and risk management approaches and strategies that are available. This should include 

issues of the timing of the remediation; 

(iii). it is then necessary to appraise the environmental, economic and social impacts of these options to 

determine an appropriate remedial objective. This appraisal should include the costs of the options 

and their environmental impacts. The environmental impacts might include some impacts that could 

readily be assessed in monetary terms (e.g., impacts on local properties). There are likely to be other 

important intangible impacts that are difficult to value in monetary terms (eg impacts on human 

health and ecosystems). The appraisal should therefore set out fully as possible the level, nature and 

significance of these intangible impacts. This assessment should build on the scientific and risk 

assessments of the reductions in the likelihood, level and nature of the environmental impacts or 

risks that the remediation options could achieve; 

(iv). once a remedial objective has been defined, then the appraisal should assess the cost-effectiveness 

of the available alternative remedial technologies for achieving it. 

The purpose of an economic appraisal is not only to estimate the level of the costs and benefits of the 

options, but also to identify the key factors determining them so as to seek out and refine better options 

for all concerned with lower costs and greater environmental benefits. An economic appraisal brings the 

following essential considerations to the discussion and decision-making processes regarding risk 

management options. 

(a) Market Failure. Environmental economics focuses on efficiently addressing market failures – which 

are external impacts that, in the absence of government action, private producers and consumers do 

not take into account. For example, market failure might covers cases whereby the costs to a 

developer for remediating a site exceed any increase in the value (gain) of the site as a result of the 

remediation so that, in the absence of any government action, the developer would not remediate 

the site (to a necessary standard). 

(b) Costs. The economic appraisal assesses the costs of the options. These are often (in economics) called 

the ‘opportunity’ costs of the options because the options use resources that could be used for other 

beneficial opportunities or purposes. 

(c) Law of Diminishing marginal Returns. This is the economist’s equivalent of the law of 

thermodynamics. It basically means that operators can face increasing constraints (eg extra 

resources and time required) as they reduce further the contaminants on a site and achieve extra 

environmental benefit. The law of diminishing returns has significant implications for the economic 

appraisal of remedial options because the trade offs between reducing the environmental damage 

from the contamination and the costs of this reduction become more significant as remediation 

progresses.
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 110 

(d) Valuation. Finally economic appraisal entails the rigorous and consistent valuation of diverse impacts 

(apples and oranges) so that, as far as possible, they can be readily aggregated (without double 

counting) in terms of a single commensurate unit (usually money). This can then aid the 

comparison of the impacts of the options.

PRACTICAL DECISION-MAKING 

A recurrent theme of the application of structured decision support tools to complex decisions is that of 

practicality and the associated issues of cost and quality of the final decision. Alongside the current 

demands for transparency in decision-making are issues of cost-effectiveness that extend beyond the 

remediation technologies employed to the costs of the project cycle as a whole. For example, pragmatists 

may argue that the incremental costs associated with the environmental appraisal of remediation projects 

can not be justified when viewed in terms of the final outcome, which could have been arrived at through 

professional judgement without structured analysis17. One response to this is to view not only the costeffectiveness but also the uptake of a decision by stakeholders (including the risk takers) as a critical 

indicator of a successful outcome. It is also important also not to regard an appraisal tool as an 'add on' 

and, therefore, a burden. Appraisal should be integral to the decision-making process and regarded as an 

iterative process. 

Apart from the cost issue there is also the question of availability of an adequate skills base to carry out 

the appraisal. This is particularly the case for the application of specialised economic, social and 

environmental appraisals at the policy18, plan and programme levels. Linkages between different levels of 

decision-making need further elucidation and development. In practice, many appraisals can be completed 

using inexpensive, but transparent screening techniques (rapid appraisal3

) with more sophisticated tools 

(technical appraisal) being reserved for complex, higher priority projects. Screening is an accepted 

methodology in EIA and is becoming recognised (in the UK) as a means of targeting resources at the 

most deserving issues at more strategic levels. Checklist approaches, although with recognised 

limitations, have been used widely. The distinction between different ‘tiers’ of analysis is familiar to 

contaminated land practitioners in the application of risk assessment techniques. Furthermore, many 

appraisals will have core (fixed) and non-core (variable) aspects to their analysis19, 20 and decision-makers 

can streamline their appraisal efforts by identifying core issues at a screening stage and focusing any 

additional effort on decision critical aspects of the analysis. This ‘tiered’ philosophy of approach is a 

common feature of most site investigations and familiar to practitioners in contaminated land assessment. 

CONCLUDING REMARKS 

Risk management frameworks and their decision support tools have historically offered a systems 

approach to addressing environmental risk problems. The sustainable development agenda requires a 

more holistic approach, often with the integration of qualitative judgements alongside quantitative 

information1

. At present, the debate amongst contaminated land professionals as to applicability of these 

tools has extended as far as the valuation of the intangible benefits of land remediation, but will need to 

extend to address explicitly the social impacts in order to embrace fully the objectives of sustainable 

development. Integrated decision support tools are required to assist this. In applying them however, it 

will be critical not to lose sight of the practicalities of application, the need for a transparency of approach 

alongside the defensibility of the technique and the over-riding objective, which is to make quality 

decisions on bringing contaminated land back into beneficial use. 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 111 

ACKNOWLEDGEMENTS 

The authors gratefully acknowledge review comments received from Ian Martin (Environment 

Agency), Paul Bardos (r3

 Environmental Technology Limited) and Malcolm Lowe (DETR) 

during the preparation of this paper. 

BIBLIOGRAPHY 

1. See: Bell, S. and Morse, S. (1999) Chapter 4. In: Sustainability Indicators, Earthscan, London, pp. 77-

103. 

2. Pollard, S.J.T., Brookes, A., Twigger-Ross, C. and Irwin, J. (1999) In: Risk Analysis: Facing the New 

Millennium, (ed. L.H.J. Goossens), Proceedings 9th Annual Conference, Rotterdam, October 10-13, 

1999, Delft University Press: 559-563 

3. Department of the Environment, Transport and the Regions (1998) Review of Technical Guidance on 

Environmental Appraisal, A Report by EFTEC, Department of the Environment, Transport and the 

Regions, London, 86pp (ISBN 1 85112 130 7) 

4. USEPA (1999) Integrated Decision-Making in the 21st Century, Peer Review Draft, May 1999; 

available at: www.epa.gov/science1/irp/

5. Canadian Council of Ministers of the Environment (1991) National Guidelines for Decommissioning 

Industrial Sites, CCME, CCME Secretariat, Winnipeg, Publication CCME-TS/WM-TR013E 

6. Department of the Environment, Transport and the Regions and Environment Agency (2000) Model 

Procedures for the Management of Contaminated Land, CLR11, Procedure for Risk Assessment, 

DETR/EA, in preparation

7. Ferguson, C. et al. (eds.) (1998) Risk Assessment for Contaminated Sites in Europe, Volume 1. 

Scientific Basis, LQM Press, Nottingham, pp.144-146 

8. See, for example: Nijboer, M.N. et al. (1998) REC: A Decision Support System for Comparing Soil 

Remediation Options based on Risk Reduction, Environmental Merit and Costs. In: Contaminated 

Soil ’98, Thomas Telford, London, pp.1173-1174. 

9. Volkwein, S. et al. (1998) Life Cycle Assessment Method for Remediation of Contaminated Sites. In: 

Contaminated Soil ’98, Thomas Telford, London, pp.1069-1070. 

10. For a more general discussion, see for example: House of Lords (2000) Science and Society, 3rd

Report of the Select Committee on Science and Technology, HL Paper 38, The Stationery Office, 

London, pp.37-44. 

11. World Commission on Environment and Development (1987) Our Common Future (The Brundtland 

Report), Oxford University Press (ISBN 0 019 282080 X) 

12. Cm4345, A Better Quality of Life: A Strategy for Sustainable Development for the United Kingdom, 

96pp., The Stationery Office, London, 1999 

13. Circular 2/2000, Environmental Protection Act 1990 – Part IIA – Contaminated Land, Department of 

Environment, Transport and the Regions, Annex I, paras. 6-7 

14. Pollard, S.J.T. and Herbert, S.M. (1998) Contaminated Land Regulation in the UK: The Role of the 

Environment Agency (EA) and the Scottish Environment Protection Agency. In: Contaminated Soil 

‘98, Thomas Telford, London, pp.33-42. 

15. Puri, G. and Gordon, J.E. (1998) Soils and Sustainability – A Natural Heritage Perspective. In: 

Contaminated Soil ‘98, Thomas Telford, London, pp1-5. 

16. Environment Agency (2000) Costs and Benefits Associated with Remediation of Contaminated 

Groundwater: A Framework of Assessment, R&D Technical Report P279, Environment Agency 

R&D Dissemination Centre, WRc, Swindon, SN5 8YF, UK 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 112 

17. For a discussion of views offered, see: Bardos, P., Nathanail, P. and Weenk, A. (1999) Added 

Environmental Value: A Tool to Help Understand the Effects of Remediation within the Context of 

Sustainable Development. Summary of a Workshop held at University of Nottingham, R&D Project 

P5-23/01, Environment Agency, Olton Court, Solihull, UK, B92 7HX 

18. Pollard, V. (2000) Integrated Appraisal of Environment Agency Policies, National Centre for Risk 

Analysis and Options Appraisal, Guidance Note 35, Environment Agency, London. 

19. Bardos, R.P., Kearney, T.E., Nathanail, C.P., Weenk, A. and Martin, I.D. (2000) Assessing the Wider 

Environmental Value of Remediating Land Contamination, Proceedings 7th International FZK/TNO 

Conference on Contaminated Soil, in press

20. Gray, P.C.R. and Wiedermann, P.M. (1999) Risk Management and Sustainable Development: Mutual 

Lessons from Approaches to the use of Indicators, J. Risk Research, 2(3), 201-218.
Decision Support Tools NATO/CCMS Pilot Project Phase III 

113 

REVIEW OF DISCUSSIONS ABOUT DECISION SUPPORT 

ISSUES IN EUROPE AND NORTH AMERICA AT THE 

NATO/CCMS SPECIAL SESSION, AND OVERALL 

CONCLUSIONS 

Sullivan1

, T.; vanVeen2 H.J.; Davidson3, L.; and Bardos4, R.P 

Brookhaven National Laboratory, Upton, N.Y., 11973, USA 

1. TNO MEP, Postbus 342, 7300 AH Apeldoorn, The Netherlands, 

2. EarthFX, Inc., Ottawa Ontario Canada, K1V 8J5 

3. r3

 environmental technology Ltd, PO Box 58, Ware, SG12 9UJ, UK 

1. INTRODUCTION 

Environmental management of contaminated lands is a complex process requiring a wide variety of 

decisions encompassing different technical, social, and political questions. Decision support for 

contaminated land management is an emerging field. Currently, a consensus for the best approach for 

using decision support does not exist. A special session on decision support was conducted at the 

NATO/CCMS meeting held in Wiesbaden Germany in June 2000. The NATO/CCMS Pilot Study on 

Remedial Action Technologies For Contaminated Soil and Groundwater Phase 3 is a multi-national 

forum for the exchange of information on emerging remediation technologies and technology 

demonstration. The Pilot Study is an activity of NATO Committee on Challenges for Modern Society 

(Web site: http://www.nato.int/ccms/info.htm). 

During the special session two guided discussion sessions were conducted and one set of questions to the 

conference participants was prepared. The discussion sections focused on obtaining information on the 

uses of decision support tools and the strengths and limitations of these tools. The questionnaire focused 

on gathering information on the use of decision support in the different countries participating in the 

meeting. This paper summarizes the findings of this information gathering exercise. 

2. TECHNICAL BACKGROUND TO THE DECISION SUPPORT SPECIAL SESSION 

Environmental management of contaminated lands is a complex process requiring a wide variety of 

decisions encompassing different technical, social, and political questions. The scope of contaminated 

land management problems range from minor contamination of a single site with a single contaminant, to 

multiple sources of different contaminants on a single site, to management of numerous contaminated 

sites in terms of sustainable development. The types of decisions that have to be made include: 

• Identification / registration of problem sites 

• Overarching decisions involving technical and social criteria (e.g., setting contaminated land 

policies) 

• Setting management goals in a regional planning context (or corporate planning context) 

• Prioritization of actions between sites 

• Determining a course of action for a particular site 

• Determinations within the individual steps of risk assessment / management for a particular site 

(e.g., how many samples are needed to support decisions on where to remediate). 

The breadth in scope and sheer number of decisions required for contaminated land management has led 

to confusion as to what constitutes decision support. In this discussion decision support is taken to be: the

assistance for, substantiation and corroboration of, an act or result of deciding; typically this deciding 

will be a determination of an optimal or best approach (Bardos et al ibid.). Although obvious, it is 

important to point out that decision support is NOT the same as making a decision. Decision support is 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

114 

the process of taking experience, data, and problem specific knowledge and the analysis and integration 

of this information to produce knowledge that assists the decision maker(s). 

Decision support is one component of several in the decision making system. The others are: 

information/data, the management of that information/data, means of modeling / visualization of 

complicated information in a way that facilitates its interpretation, and gray matter. Gray matter means 

the human intellectual input that: sets out the technical approach to the decision making process; 

interprets decision making knowledge and reaches the decision. Figure 1 presents these components in a 

simple schematic. Figure 1 emphasizes the interdependence and feedback between different aspects of the 

problems through the two-way arrows. Eventually, the information is used in the decision making 

process. 

An example of a decision making process might be the determination of which remedial options to use for 

a particular site. In this scenario, the problem begins with definition of a technical approach to the 

problem. Data are collected and managed. The data includes any information used to assess the problem 

including measurements of contamination and soil and groundwater properties, technical performance of 

remedial options, and costs of remedial options. The data are utilized directly for decision support in some 

cases. In most cases, the data are used in models that further analyze the data to provide information 

necessary for supporting decisions. The outputs from the modeling require interpretation on issues such as 

are the proper models and parameters being used for the analysis. The decision support variables also 

have to be interpreted in terms of their adequacy in supporting decisions (e.g., what uncertainties are there 

in the variables and will these uncertainties possibly lead to a different decision). 

Figure 1 highlights the need for detailed thinking about the problem using gray-shaded boxes that use the 

term ’gray matter.’ Decision support tools and techniques can supplement the decision process but cannot 

replace critical thinking, analysis, and judgment. 

Figure 1. Flow diagram of the decision making process.
Decision Support Tools NATO/CCMS Pilot Project Phase III 

115 

A number of tools are possible to support the decision maker. This discussion paper takes "decision 

support tool" to be anything used as an instrument or apparatus in one's occupation or profession 

(Bardos et al., ibid. ). Thus, a decision support tool (DST) is some kind of a product, which has the aim of 

supporting decision making. 

In all cases contaminated land problems are resolved as a result of a series of inter-related decisions. A 

DST typically facilitates one or more of these decisions, as illustrated in Figure 2. 

Figure 2. Schematic representation of the relationship between decision tools and decision making. 

A DST can be written guidance on how to assemble and analyze information needed to support a decision 

(e.g., regulatory guidance on risk assessment, sustainable development, cost-benefit analysis, etc.). 

Alternatively, it can be a software tool that facilitates the data analysis and produces decision knowledge 

(e.g., costs, risks, etc.). In some cases, the software tools have 

codified the regulatory guidance to permit relatively easy and more consistent application of the guidance. 

 

Figure 2 also shows that several decision support tools may be used in addressing contaminated land 

management. The entirety of the decision steps is the decision making system. No current single tool 

addresses the entire process. This is an important distinction, as many people would like a single tool (a 

decision support system) that could address all of the decisions. This would increase transparency (i.e., 

clarity of the process to all stakeholders) and reproducibility of the decision making process. However, 

because of the breadth and scope of decisions that need to be made this is not practical. 

The system boundaries represent the constraints to addressing the problem and include regulations, time, 

money, and other limitations. Decision tools work within the system boundaries to provide information 

that supports the decisions. As shown in the figure, some tools will address a single decision (e.g., what 

region needs to be remediated to reduce human health risks to an acceptable level), while others will 

address multiple decision variables (e.g., selection of a remedial approach based on economic costs, 

protection of human health, technical feasibility of the approach, and stakeholder concerns). 

Decisions

Tools

System Boundaries
Decision Support Tools NATO/CCMS Pilot Project Phase III 

116 

In general, the use of decision support tools and techniques is an emerging field in contaminated land 

management. While some principles such as the use of human health risk assessment in decision making 

are widely accepted approaches for decision making, many areas such as ecological risk, multi-criteria 

analysis, life-cycle analysis, and financial risk analysis are only emerging as decision support tools. Even 

for human health risk assessment where guidance has been published in many countries, there is still 

much debate over the best approach (e.g., should specialized risk assessments be done for the young and 

old who may be more susceptible to exposure from contamination) to perform the analysis. 

3. OUTLINE OF DISCUSSION SECTIONS 

Two guided discussions took place during the special session, reviewing the papers presented (and 

included elsewhere in this report) and bringing to bear the delegates' own range of experiences from many 

countries. In addition, many delegates also provided written feedback over the course of the meeting. A 

list of delegates who attended is presented as an Annex to this report. 

Ing Johan Van Veen led the first discussion section and focused on addressing the following questions 

1) Are decision support tools useful? 

2) How are DST being used? 

3) What is the role of stakeholders in the decision process? 

4) What common factors emerge between decision support tools? 

Mr. Laurence Davidson led the second discussion section with the intent of determining the advantages 

and disadvantages of using DST. 

The list of questions provided to the participants were: 

1. How is DS considered in your country as a discipline or technique? 

2. How is DS for remediation used in your country (e.g., types of applications, frequency of use? - 

Always, sometimes, almost never)? 

3. In your view how well are information needs for decision making about remediation understood? 

4. What is your view of the usefulness of Decision Support for selection of remedial options / risk 

management? Is DS used to support technology selection? 

Participants from Austria, Belgium, Canada, the Czech Republic, Germany, Greece, Italy, Japan, the 

Netherlands, Norway, Switzerland, Turkey, the United Kingdom, and the United States supplied answers 

to these questions. 

The following summarizes the results of the discussions and responses to the questions. In several cases, 

there was an overlap between the different discussions and questions. The following reports the findings 

as they occurred. No attempt was made to consolidate the different thoughts into a more concise manner. 

4 FIRST DISCUSSION SECTION: APPLICATIONS OF DECISION SUPPORT TOOLS 

4.1 ARE DECISION SUPPORT TOOLS USEFUL? 

There was a consensus that DST can be useful not only in facilitating decision making, but also in helping 

to ensure consistency and transparency across decisions. However, this was strongly dependent on the 

DST approach. Unintelligent use of DST was perceived as counterproductive. 

Written guidance on how to provide decision support knowledge was felt particularly useful. An example 

of these types of tools include written guidance on the approach and parameters to be used in human 

health risk assessment. Several people felt that these guidance types of tools were essential and in some 

cases adhering to the guidance is required by national laws. 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

117 

There was less agreement on how useful software tools were in supporting the different decisions in the 

contaminated land management process. For example, most delegates agreed that human health risk 

assessment and cost-benefit software tools were valuable and widely used. Delegates could also see the 

usefulness of sample selection based on geostatistical analysis - yet these types of approaches are not 

widely used. However, while a number felt that DST could be useful for remedy selection, others felt that 

the use of software DST for remedy selection was not particularly useful, given the site-specific 

complexity of contamination problems and the absence of reliable general cost data. 

A number of concerns were raised about the use of software DSTs in general. Often these tools use 

specific datasets and extensive assumptions. While the data and conceptual model are, in reality, the 

technical foundation of decision support, if it is unclear what the datasets and assumptions are, their 

relevance to the problem in question is unclear, and misuse of the tool a strong possibility. One delegate 

went further. He felt that even where a DST made transparent use of data, knowledge and assumptions, 

the mere availability of easy to use DST software presented risks of decision making being undertaken by 

inadequately skilled individuals. 

These criticisms do not reflect a meeting consensus, but rather part of the range of views expressed. Other 

delegates felt that the way in which DST could improve the accessibility of data, analysis, and 

interpretation beyond those with expertise in the field was fundamentally a good thing. It allowed many 

stakeholders to actually "have" their stake in decision making. Those ultimately paying for or approving 

remediation decisions, and many of those wishing to influence decision making, are not necessarily 

contaminated land specialists. 

However, it was suggested that the use of the tools still requires training and expertise in the different 

aspects of the decision making process and the analyses used by particular tools. The training should 

include guidance on the range of conditions over which the tool is applicable. This supports the notion 

that the tools can not be used to replace expertise, but only to enhance it. 

The majority of delegates agreed with aspirations for decision support to help to make the decision 

making process transparent, documented, reproducible, (hopefully) robust and provide a coherent 

framework to explore the options available (Bardos et al ibid.). However, not all DST match up to these 

aspirations, and indeed the supporting datasets and assumptions of some DST are questionable for many 

applications. 

4.2 WHAT IS THE ROLE OF THE STAKEHOLDERS IN THE DECISION PROCESS? 

A stakeholder is any individual or group that has an interest in the particular contaminated land 

management problem. Stakeholders can include problem holders, environmental service providers, 

federal, state, and local regulators and public health officials, local businesses, citizens, and citizen 

groups. (PCCRARM, 1997; SNIFFER, 1999). The different perspectives held by stakeholders often leads 

to conflict in determining an approach to contaminated land management. In most countries, the problem 

holder or their consultant(s) analyzes the problem and suggests a remedy to the regulatory body. 

Typically, the public and other stakeholders are often informed of these recommendations at a later stage, 

often when decisions in principle have already been taken. 

Many delegates felt that early stakeholder involvement is beneficial both to avoid later delay and 

costs from subsequent arguments with unconsulted stakeholders and for reasons of open 

"governance". Inclusivity in decision making is a part of sustainable development, which is an important 

policy driver in many countries. However, concern was expressed by several delegates that this 

inclusivity could lengthen the time taken to make a decision and in some cases be counterproductive. On 

the other hand, failure to include stakeholder viewpoints can often lead to more severe management 

problems later. Several suggested that stakeholders must be made part of the decision making process, but 

they should not be given control of the decision making process. Strong leadership and communication 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

118 

skills were identified as being crucial to dealing with all of the interested stakeholders, but maintaining an 

ability to actually make decisions. 

4.3 HOW ARE DST BEING USED? 

A number of applications of DST were mentioned during the discussions. Four major categories of use 

were identified. 

• The first is written guidance produced, for example, by regulatory bodies. The guidance 

approach is used in a number of countries to enable a more consistent approach to contaminated 

land management. 

• The second category is use in identifying sites on a regional or organizational (e.g., 

corporate) basis and setting management / policy goals, Activities supported include the 

identification of suspect sites, cataloguing suspect sites and setting broad "policy" objectives, 

which may be linked to a variety of spatial planning considerations, for example zoning of 

development and regional economic policy such as attracting inward investment.

• The third category is the use of DST for prioritization among different sites within a single 

area of responsibility. This activity is necessary where a number of suspect sites have been 

identified. Resources are not available to treat all simultaneously so the most urgent must be 

treated first. 

• The fourth category, which is the most commonly recognized application, is use of DST for 

specific tasks at a single site. Examples of these type of approaches include analysis of human 

health risks, remedy selection, site characterization, and cost-benefit analysis. In most 

applications, a single decision criterion is evaluated. However, use of multi-criteria analysis 

(MCA) and life cycle analysis (LCA) approaches are often found. 

Other important findings from the discussion were: 

• Human health risk tools are the most widely used of any DST. 

• For the most part, implementation of the tools is in the hands of the consultants and other 

technical specialists. Regulatory staff use them to a much lesser extent and the public and other 

stakeholders rarely use DST. 

• When DST are used they tend to be only a small part of the decision process. 

4.4 WHAT ARE THE COMMON FACTORS FOR DECISION SUPPORT? 

Many decisions are required for contaminated land management. The decisions range from site and 

problem-specific questions that are largely based on technical and economic concerns (e.g., what is the 

best remedy to clean the site) to national questions that are largely based on societal concerns (e.g., 

prioritization of resources for the management of contaminated land to permit sustainable development). 

Although the emphasis on the decision variables may differ between different problems, they are 

interrelated. Site-specific problems can be influenced by societal concerns (e.g., neighbors may object to a 

technically viable solution such as incineration of wastes because they are concerned over airborne 

releases). 

Decision support tools integrate data and report results in terms of a simplified but representative 

decision information. For example, assume that human health risk is one decision parameter for deciding 

if monitored natural attenuation is acceptable, or if a more aggressive remediation scheme is required. 

Many software programs predict the groundwater flow path and rate. While this information is required to 

analyze a contaminated aquifer, it alone does not address the consequence of the contamination and, 

hence, it is not a decision support tool. A decision support tool would take the information from the 

groundwater flow simulation and integrate it with information on the source strength and duration, 

contaminant transport processes (for example, removal by biodegradation), and exposure pathways and 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

119 

parameters (e.g., receptor location and use of contaminated water) to estimate human health risks over 

time. 

Stakeholder involvement is an important aspect of the decision process and helps to achieve a 

solution for contaminated land management that is acceptable to all. Stakeholders may not always 

agree on an approach for contaminated land management. In this case, the regulators are often the 

mediators between the different stakeholders. 

Risk management decision support tools are the most commonly used decision support tools. A number 

of delegates also identified cost-benefit decision support tools as having widespread application. 

5. SECOND DISCUSSION SECTION: ADVANTAGES AND DISADVANTAGES OF DST AND 

GENERAL ISSUES ARISING FROM THEIR USE 

5.1 WHAT ARE THE ADVANTAGES OF USING DECISION SUPPORT TOOLS? 

The major advantage of using appropriate DST's is in helping to ensure the decision making process is 

robust, consistent, transparent and reproducible. Specific advantages of DST include: 

• DSTs provide a method to analyze multiple scenarios. Consideration of a range of scenarios can 

increase the confidence when making a decision. 

• DST can be used to optimize contaminated land management (leading to lower costs). 

• Some DSTs can incorporate uncertainties into the decision framework. Decisions in contaminated 

land management are always made with some degree of uncertainty. Addressing this directly can 

enhance the decision making process. For example, DST can estimate the volume and costs of 

remediation required as a function of the degree of certainty in achieving human health risk goals 

(Stewart, 2000) or financial risks (Finnamore, 2000). This permits the decision to be based on the 

problem holder’s aversion to failure. 

• DSTs can provide means to document all parameters and assumptions used in the analysis for a 

particular decision (see subsequent discussion of data management systems). 

• DST can improve communication between various stakeholder groups. 

• DST can be used as an educational tool. For example, the effects of changing parameters on the 

decision variable can be demonstrated. 

• DST can improve the transparency of the process through documenting assumptions and 

explaining the approach used to reach a decision. 

5.2 WHAT ARE THE DISADVANTAGES TO USING DST? 

• Gaining acceptability of the tool with all stakeholders is often difficult. It takes time and effort to 

educate other stakeholders on the use of a tool. If the tool is perceived to be a ‘black box’

stakeholders not involved in the application of the tool will not trust the results. 

• A common approach to DST is to provide output in the form of a single set of decision variables, 

and in some cases a single variable or index. In reporting only the decision variable the rationale 

behind its algorithms, supporting data and assumptions may not be understood. The effect of this 

reporting approach may be to perpetuate a lack of trust of the analysis, which may be viewed as 

"black box" information. This is likely to be a particular problem where DST are used or 

interpreted by "non-experts". It also flags the need for clarity and good supporting information on 

the part of the system designer AND user. 

• Decision support tools must be maintained to keep current. For example, for remedial options as 

new cost data are obtained they must be incorporated into the appropriate database for use in the 

analysis. In addition, human health risk decision support tools often have a database for risk 

parameters. These parameters are continually being updated to reflect the latest scientific 

findings. 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

120 

• Garbage In – Garbage Out. A decision support tool is only as good as the data and assumptions 

used to perform the analysis. The assumptions include not only those used to develop the DST, 

but also those used in the conceptual model of how to represent the problem. Therefore, the 

analyst should be trained in the use of the tool and in the approach to represent the contamination 

problem. (See also Section 4.1). 

5.3 WHAT ARE THE ISSUES IN THE USE OF DST? 

During the discussion it became apparent that there were many issues that could not be claimed to be an 

advantage or disadvantage. For example, ease of use of the decision support tools was cited as an issue. 

Many people wanted tools that were easy to use, while others were concerned that without proper training 

the easy to use tools could be prone to misuse. For this reason, a third category, issues in using DST was 

added and the following issues identified. 

• The use of many types of DSTs is in its infancy. In general, DSTs need to gain acceptance from 

all of the stakeholders, provide training on how to effectively use them and guidance on when 

they would be useful. 

• The value added by using DSTs needs to be demonstrated. Purchasing a DST, learning how to 

properly operate a DST and getting other stakeholders to agree that the DST is appropriate for the 

problem can be expensive and time consuming. If all of this work does not lead to a better 

decision or more efficient process to reach the decision, use of the DST could be considered 

inappropriate. Anecdotal evidence was presented at the meeting indicating that in one case, use of 

a DST saved several million dollars on the remediation project. Situations like this need to be 

thoroughly documented and subjected to independent peer review. 

• Contaminated land management requires good data management practice. It was suggested that a 

data management system is not a DST but it is an adjunct that supports the quality of DST 

analysis. As such, the data management system should be independent of individual DST or 

visualization tools. An ideal situation might be where a single data management system was used 

both to store basic data from its various sources and the interpretation of that data provided by 

visualization tools and DST. Indeed the data management package might be handed on across 

organizations on a CD-ROM to ensure that source and interpreted data is kept secure and well 

referenced. Providing everyone with the same data will allow independent analysis by other 

stakeholders using the same data. Maintaining a centralized data management system can also 

lead to better quality control of the data as all changes to the database will go through the data 

administrator. This will help insure that all data analyses will be performed with a common data 

set. 

• There are gaps between the latest developments in decision theory and their implementation in 

DST. This is to be expected because the development of the theory generally precedes the 

implementation in DST. However, it highlights the need to continually maintain and update the 

DST, as new information becomes available. 

• Validation/Verification of a DST is required, but difficult to perform. Validation refers to the 

demonstration that the DST performs as expected. Validation can be achieved by comparison of 

DST results with known solutions or with results from other accepted DST. Verification refers to 

the demonstration that the DST can accurately predict the behavior of the system. Due to the 

natural variability in contaminated land problems, lack of data, and the need for simplifying 

assumptions to represent the actual conditions it is generally not possible to verify the DST. 

• DSTs are supposed to enhance transparency of the decision process. However, their development 

requires highly specialized knowledge and skills. For example, DST may implement state-of-theart models for any or all of the following: geostatistics, subsurface flow and transport, human 

health risk assessment, ecological risk assessment, economic analysis, and decision theory. This 

highlights the previously identified need to educate and train stakeholders in the use of DST and 

the limitations in their use. 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

121 

• The results from using DST may receive unwarranted credibility through the cloak of scientific 

rigor. The concern expressed was that if a well-accepted DST is used in the analysis, people will 

blindly accept the results without critically analyzing the assumptions and parameters. This 

highlights the need to remember that although the DST may be quite sophisticated in its analysis 

techniques it is just a tool. The decision process should still be based on thinking. 

5.4 THE IMPORTANCE OF DATA MANAGEMENT 

Decision support can be greatly improved through the use of data management tools that store the 

information electronically and permit its use by all stakeholders. A concern was expressed by some of the 

participants that if each DST had its own dataset this could lead to inconsistencies. Proper data 

management would remove this problem and can lead to improved quality control of data. Ideally, the 

data management system would contain all of the data related to the contaminated land management 

problem and be the sole source of data for decision support analyses. The different DSTs would access 

the database and extract the data needed for their analysis. Use of a centralized data management system 

would help improve consistency. 

5.5 WHAT ARE THE ISSUES IN MULTI-CRITERIA ANALYSIS (MCA)? 

Multi-criteria analysis is a well-established technique for optimizing decision making, however, use of 

MCA for decision support of contaminated land management is an emerging technique. In MCA, several 

alternatives are ranked against a list of criteria. These criteria can include costs, human and ecological risk 

reduction, societal values for the benefits of remediation, technical feasibility, and so on. From the 

preceding example, it is clear that each of these criteria will have different measurement scales and may 

rely on subjective judgement. Each alternative is evaluated against each criterion and given a score. The 

scores are then normalized to a single scale. Often economic cost is used for the scale. Using the 

normalized score, each criterion is given a weight to reflect its relative importance to the decision. For 

example, meeting societal values may be given a weight of 0.3, while meeting ecological values may be 

given a weight of 0.1. Then, for each alternative, the individual scores for meeting each criterion are 

multiplied by the weight for the criterion and a total score is obtained. The total scores for each alternative 

are then ranked to support the decision on selection of an alternative. As MCA is an emerging practice in 

this field, there is little guidance on how to score the different criteria, normalize to a single scale or select 

the weights applied to each criterion. This has led to the following questions for the use of MCA. 

• Does it make sense to normalize all criteria to a single scale? Often everything is assigned a socalled monetary value. Is this the best choice? 

• What is the best way to integrate more subjective data (e.g., societal values) with more technical 

data (e.g., costs or risks)? 

• What is the basis for obtaining the criteria weighting factors? Optimally, they would be obtained 

by consensus among all of the stakeholders. 

• How is transparency in the decision process maintained when weights and scoring are subjective? 

• Is the process rigorous and robust when using subjective normalization and weighting? 

It is clear that there are major concerns about the process of quantifying subjective data and comparison 

of dissimilar criteria. In order for MCA to become an important tool for contaminated land management, 

these issues will have to be addressed and general guidance on acceptable approaches is needed. 

6. RESPONSES TO THE QUESTIONNAIRE 

6.1 HOW IS DECISION SUPPORT USED IN YOUR COUNTRY? 

In general, three categories of response to this question were obtained: a) not used at all; b) used in the 

form of guidance for best practices; or c) used for site-specific problems. In some countries, DS is not 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

122 

widely used. In most countries, DS in the form of regulatory guidance is frequently used and its 

application is required by some nations. When DS is being used, human health risk assessment and costbenefit analysis were the most frequent applications. Multi-criteria analysis and ecological risk 

assessment are emerging uses for DS. LCA is being used on a limited basis for special problems. All 

respondents considered DS to be a technique rather than a separate discipline. 

The following example applications were supplied in the responses: 

• Regulatory guidance for conducting human health risk assessment or best practices for 

remediation. 

• Prioritization of projects for obtaining state funding, and for social and land-use planning; 

• Data management, 

• Human and ecological risk assessment, 

• As a communication tool for the spatial context for risk and through visualization of data, 

• As a method to insure uniform application of regulations, 

• To support selection of monitored natural attenuation as a risk management strategy, 

• Optimization of remedial technology operation parameters to minimize costs. 

6.2 HOW WELL ARE INFORMATION NEEDS FOR DS UNDERSTOOD? 

There was a range of perceptions on this issue. Some people believed that information needs were well 

understood, while most did not. Most people felt that the needs were understood at the thematic level (i.e., 

contamination data, risk data, etc.), but not at the working level (amount of data required to make a 

defensible decision). Most agreed that the information needs were well understood by specialists and 

researchers, less understood by project management and regulators and not understood by stakeholders 

that are not involved in the analysis process. A few responses identified the following issues in 

information needs. 

• Several areas of science are not well understood. Improved understanding could lead to better 

decision-making. Areas identified include long-term performance and cost data for remedial 

techniques, better understanding of subsurface flow and transport, and toxicology data. 

• For MCA, using subjective criteria such as the value of remediation to society, approaches to 

quantify the value in monetary terms are needed. 

• Data quality needs are not well understood. The impact of natural variability and uncertainties in 

the data on the decision need to be addressed. 

One respondent pointed out that the challenge for decision support tools is to simplify the systems so that 

data needs are reasonable in terms of the number of parameters and the cost to collect the data. The 

simplifications have to be balanced against the loss of technical accuracy in the results (i.e., does the loss 

of technical accuracy and, therefore, increased uncertainty impact the decision?). Accuracy is only one of 

several required attributes for decision information. The overarching question being asked is how to best 

manage the contaminated land given the problem constraints. For example, in the UK the emphasis is 

now on data quality that is fit for purpose – in some circumstances this may imply that a fixed budget is 

spent on more information but of lower (but adequate) quality. 

6.3 WHAT IS YOUR VIEW OF THE USEFULNESS OF DECISION SUPPORT FOR 

SELECTION OF REMEDIAL OPTIONS / RISK MANAGEMENT? IS DS USED TO 

SUPPORT TECHNOLOGY SELECTION? 

Many respondents felt that DS was useful for initial screening in the selection of remedial options. A few 

respondents felt that it was also useful in the final selection of a remedy. Those that did not feel DS was 

useful for final remedy selection indicated that the uncertainties in the cost and performance data were too 

high for new and emerging remedial technologies to permit use of decision support tools. Most 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

123 

respondents agreed that decision support is useful for risk management. In many countries, guidance on 

risk assessment is available, and risk assessment is routinely used. 

Many respondents generalized the question to express how decision support was most useful in their 

country. Most respondents felt that decision support was very useful in the form of regulatory guidance to 

obtain a consistent analysis framework. This helped set the stage for dealing with the different 

stakeholders in a fair and consistent manner. Other advantages cited for decision support included: 

• Improved communication with stakeholders. Visualization of data was acknowledged as an 

important method of communication. 

• Better management, integration and use of data. The use of an overarching data management 

system that managed the data for all decision support tools can improve quality control and 

permit greater access to the data. 

• Ability to determine key processes and parameters that impact the decision. 

• Better transparency to the decision process. 

7. CONCLUSIONS AND FUTURE DIRECTIONS 

Many decisions are required for contaminated land management. The decisions range from site and 

problem-specific questions that are largely based on technical and economic concerns (e.g., what is the 

best remedy to clean the site) to national questions that are largely based on societal concerns (e.g., 

prioritization of resources for the management of contaminated land to permit sustainable development). 

Although the emphasis on the decision variables may differ between different problems, they are 

interrelated. Site-specific problems can be influenced by societal concerns (e.g., neighbors may object to a 

technically viable solution such as incineration of wastes because they are concerned over airborne 

releases). 

Decision Support involves integration of expertise and data, followed by analysis and interpretation of the 

results to produce outcomes in terms of decision variables (health risk, cost, suitability, etc.). For 

example, assume that human health risk is one decision parameter for deciding if monitored natural 

attenuation is acceptable, or if a more aggressive remediation scheme is required. Many software 

programs predict the groundwater flow path and rate. While this information is required to analyze a 

contaminated aquifer, it alone does not address the consequence of the contamination and, hence, it is not 

a decision support tool. A decision support tool would take the information from the groundwater flow 

simulation and integrate it with information on the source strength and duration, contaminant transport 

processes (for example, removal by biodegradation), and exposure pathways and parameters (e.g., 

receptor location and use of contaminated water) to estimate human health risks over time. 

The decision support can be in the form of guidance that provides a framework for performing the 

analysis or software that has codified the expertise to allow more rapid analysis by many. The magnitude 

and similarity between contaminated land management problems has led to development of several 

computer software DSTs to address different aspects of the problem (site characterization, cost-benefit, 

risks, sustainable development, etc.). 

Regulatory guidance is the most widely used type of decision support. In several countries, adherence to 

the guidance is required or strongly recommended. For software based DSTs, human health risk 

assessment and cost-benefit are the most commonly used. Ecological risk assessment and multi-criteria 

analysis are starting to see more use. 

Stakeholder involvement is an important aspect of the decision process and helps to achieve a solution for 

contaminated land management that is acceptable to all. Stakeholders may not always agree on an 

approach for contaminated land management. In this case, the regulators are the mediators between the 

different stakeholders. Effectively integrating the stakeholders into the decision process is a difficult task 

requiring strong leadership and good communication skills. 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

124 

The strengths, limitations, and applications of DST have been identified and discussed in this paper. The 

major strengths identified were the ability to provide a consistent, reproducible process for decision 

making and the ability to enhance communication between different stakeholder groups. The major 

disadvantage in using DST was in gaining acceptability of the tool to all stakeholders. This can be a time 

consuming process. A secondary disadvantage that was cited involved concerns that making the tools 

easy to use could lead to their misuse. Careful review is required for all results that support a decision. 

Decision support can be greatly improved through the use of data management tools that store the 

information electronically and permit its use by all stakeholders. A concern was expressed that if each 

DST had its own dataset this could lead to inconsistencies. Proper data management would remove this 

problem and lead to improved quality control of data and would help improve consistency. 

A number of unresolved issues pertaining to the use of DST were identified. Based on these findings 

several areas for improvement were identified. Some of the more important areas requiring further 

development include: 

• Improved methods for valuation of criteria and determination of weights for MCA approaches. 

This includes the need for improved methods and approaches for handling subjective (soft data). 

Work needs to be done to develop a consistent agreed upon approach to using MCA. 

• Improved transparency for the concepts behind decision support to all stakeholders. Greater 

stakeholder involvement is needed to gain acceptance of DST. 

• Improved transparency in the output from DST. Decision support tools often involve abstraction 

from multiple sources of data and involve complex technical analysis. 

• Improved methods for verification of the performance of DST. This is especially true in 

computationally intensive areas that require extensive experience to use correctly and are often 

based on data sets that permit multiple interpretations. These areas include flow and transport 

calculations, geostatistical modeling and optimization of remedy performance. 

• Improved methods for understanding the impacts of natural variability and uncertainty on the 

decision process. Some DST address the role of uncertainty in making a decision, but this is an 

emerging field that needs further development. 

• Critical evaluation of the successes and failures in the use of DSTs. This evaluation would help to 

focus future development work. 

8. REFERENCES 

Bardos, R.P.; Mariotti, C.; Marot, F.; and Sullivan, T., “Framework for Decision Support used in 

Contaminated Land Management in Europe and North America, “ in NATO Committee on Challenges to 

Modern Society: NATO/CCMS Pilot Study Evaluation of Demonstrated and Emerging Technologies for 

the Treatment and Clean Up of Contaminated Land and Groundwater. Phase III 2000 Special Session 

Decision Support For Contaminated Land Management. Ibid. 

Finnamore, J., “Modeling the Financial Risks of Remediation,” in NATO Committee on Challenges to 

Modern Society: NATO/CCMS Pilot Study Evaluation of Demonstrated and Emerging Technologies for 

the Treatment and Clean Up of Contaminated Land and Groundwater. Phase III 2000 Special Session 

Decision Support For Contaminated Land Management,. ibid. 

Stewart, R. “Geospatial Decision Frameworks for Remedial Design and Secondary Sampling,” in NATO 

Committee on Challenges to Modern Society: NATO/CCMS Pilot Study Evaluation of Demonstrated and 

Emerging Technologies for the Treatment and Clean Up of Contaminated Land and Groundwater. Phase 

III 2000 Special Session Decision Support For Contaminated Land Management,. ibid.
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 125 

COUNTRY REPRESENTATIVES 

Directors

Stephen C. James (Co-Director) 

National Risk Management Research Laboratory 

U.S. Environmental Protection Agency 

26 Martin Luther King Drive 

Cincinnati, Ohio 45268 

United States

tel: 513-569-7877 

fax: 513-569-7680 

e-mail: james.steve@epa.gov 

Walter W. Kovalick, Jr. (Co-Director) 

Technology Innovation Office 

U.S. Environmental Protection Agency 

1300 Pennsylvania Ave, NW (5102G) 

Washington, DC 20460 

United States

tel: 703-603-9910 

fax: 703-603-9135 

e-mail: kovalick.walter@epa.gov 

Co-Pilot Directors 

Volker Franzius 

Umweltbundesamt 

Bismarckplatz 1 

D-14193 Berlin 

Germany 

tel: 49/30-8903-2496 

fax: 49/30-8903-2285 or -2103 

e-mail: volker.franzius@uba.de 

H. Johan van Veen 

TNE/MEP 

P.O. Box 342 

7800 AN Apeldoorn 

The Netherlands

tel: 31/555-493922 

fax: 31/555-493921 

e-mail: h.j.vanveen@mep.tno.nl 

Country Representatives 

Anahit Aleksandryan 

Ministry of Nature Protection 

35, Moskovyan Strasse 

375002 Yerevan 

Armenia 

tel: +37/42-538-838 

fax: +37/42-151-938 

e-mail: goga@arminco.com 

Nora Meixner 

Federal Ministry of Environment, Youth and 

Family Affairs 

Dept. III/3 

Stubenbastei 5 

A-1010 Vienna 

Austria

tel: 43/1-515-22-3449 

fax: 43/1-513-1679-1008 

e-mail: Nora.Auer@bmu.gv.at 

Jacqueline Miller 

Brussels University 

Avenue Jeanne 44 

1050 Brussels 

Belgium

tel: 32/2-650-3183 

fax: 32/2-650-3189 

e-mail: jmiller@ulb.ac.be 

Lisa Keller 

Environmental Technology Advancement 

Directorate 

Environment Canda – EPS 

12th Floor, Place Vincent Massey 

Hull, Quebec K1A 0H3 

Canada

tel: 819/953-9370 

fax: 819/953-0509 

e-mail: lisa.keller@ec.gc.ca 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 126 

Hana Kroová

Czech Ministry of the Environment 

Vrsovická 65 

100 10 Prague 10 

Czech Republic

tel: 420/2-6712-1111 

fax: 420/2-6731-0305 

Kim DahlstrUm 

Danish Environmental Protection Agency 

Strandgade 29 

DK-1401 Copenhagen K 

Denmark

tel: +45/3266-0388 

fax: 45/3296-1656 

e-mail: kda@mst.dk 

Ari Seppänen 

Ministry of Environment 

P.O. Box 399 

00121 Helsinki 

Finland

tel: +358/9-199-197-15 

fax: +358/9-199-196-30 

e-mail: ari.seppanen@vyh.fi 

Andreas Bieber 

Federal Ministry for the Environment 

Ahrstrasse 20 

53175 Bonn 

Germany 

tel: 49/228-305-305-3431 

fax: 49/228-305-305-2396 

e-mail: bieber.andreas@bmu.de

Anthimos Xenidis 

National Technical University Athens 

52 Themidos Street 

15124 Athens 

Greece 

tel: 30/1-772-2043 

fax: 30/1-772-2168 

Pál Varga 

National Authority for the Environment 

Fö u.44 

H-1011 Budapest 

Hungary

tel: 36/1-346-8310 

fax: 36/1-315-0812 

e-mail: vargap@mail5.ktm.hu 

Matthew Crowe 

Environmental Management and Planning 

 Division 

Environmental Protection Agency 

P.O. Box 3000 

Johnstown Castle Estate 

County Wexford 

Ireland

tel: +353 53 60600 

fax: +353 53 60699 

e-mail: m.crowe@epa.ie 

Francesca Quercia 

ANPA - Agenzia Nazionale per la Protezione 

dell'Ambiente 

Via V. Brancati 48 

I - 00144 Rome 

Italy 

tel. 39/6-5007-2510 

fax 39/6-5007-2531 

e-mail: quercia@anpa.it

Masaaki Hosomi 

Tokyo University of Agriculture and 

Technology 

2-24-16 Nakamachi 

Tokyo 184-8588 

Japan

tel: +81-42-388-7070 

fax: +81-42-381-4201 

e-mail: hosomi@cc.tuat.ac.jp 

Bjørn Bjørnstad 

Norwegian Pollution Control Authority 

P.O. Box 8100 Dep 

N-0032 Oslo 

Norway

tel: 47/22-257-3664 

fax: 47/22-267-6706 

e-mail: bjorn.bjornstad@sft.telemax.no 

Marco Estrela 

Instituto de Soldadura e Qualidade 

Centro de Tecnologias Ambientais 

Tagus Park 

EC Oeiras – 2781-951 Oeiras 

Portugal

tel: +351/21-422 90 05 

fax: +351/21-422 81 04 

e-mail: maestrela@isq.pt 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

 127 

Ioan Gherhes 

EPA Baia Mare 

I/A Iza Street 

4800 Baia Mare 

Romania 

tel: 40/4-62-276-304 

fax: 40/4-62-275-222 

e-mail: epa@multinet.ro 

Branko Druzina 

Institute of Public Health 

Trubarjeva 2-Post Box 260 

6100 Ljubljana 

Slovenia

tel: 386/61-313-276 

fax: 386/61-323-955 

e-mail: branko.druzina@gov.si 

V5tor A.P.M. dos Santos 

Spanish National Research Council 

Professor Aubareoal 

18008 Granada 

Spain 

tel: 34/958-121-011 

fax: 34/958-129-600 

e-mail: vasantos@eez.csis.es 

Ingrid Hasselsten 

Swedish Environmental Protection Agency 

Blekholmsterrassen 36 

S-106 48 Stockholm 

Sweden 

tel: 46/8-698-1179 

fax: 46/8-698-1222 

e-mail: inh@environ.se

Bernard Hammer 

BUWAL 

3003 Bern 

Switzerland 

tel: 41/31-322-9307 

fax: 41/31-382-1456 

e-mail: bernard.hammer@buwal.admin.ch 

Kahraman Ünlü

Depratment of Environmental Engineering 

Middle East Technical University 

Inönü Bulvari 

06531 Ankara 

Turkey

tel: 90-312-210-1000 

fax: 90-312-210-1260 

e-mail: kunlu@metu.edu.tr 

Ian D. Martin 

Environment Agency 

Olton Court 

10 Warwick Road 

Olton, West Midlands 

United Kingdom 

tel: 44/121-711-2324 

fax: 44/121-711-5830 

e-mail: ianmartin@environment-agency.gov.uk
Decision Support Tools NATO/CCMS Pilot Project Phase III 

128 

ATTENDEES LIST 

Anahit Aleksandryan (c.r.) 

Ministry of Nature Protection 

35 Moskovyan str. 

375002 Yerevan 

Republic of Armenia 

tel: 37/42-538-838 

fax: 37/42151-938 

e-mail: goga@arminco.com 

P.A. (Arne) Alphenaar 

TAUW 

P.O. Box 133 

7400 AK Deventer 

The Netherlands 

tel: 31/570 699 911 

fax: 31/570 699 666 

e-mail: pah@tauw.nl 

Paul Bardos 

R3 Environmental Technologies Ltd. 

P.O. Box 58 

Ware-Hertfordshire SG12 9UJ 

United Kingdom 

tel: 44/1920-484-571 

fax: 44/1920-485-607 

e-mail: p-bardos@r3-bardos.demon.co.uk 

Paul M. Beam (c.r.) 

U.S. Department of Energy 

19901 Germantown Rd. 

Germantown, MD 20874-1290 

United States 

tel: 301-903-8133 

fax: 301-903-3877 

e-mail: paul.beam@em.doe.gov 

Jörg Becht 

Hessisches Ministerium für Umwelt, 

Landwirtschaft und Forsten 

Mainzer Str. 98 – 102 

65189 Wiesbaden 

Germany 

tel: 49/611-815-1380 

fax: 48/611-815-1947 

e-mail: abteilung.3@mue.hessen.de 

Eberhard Beitinger 

WCI Umwelttechnik GmbH 

Heinrich-Hertz-Straße 3 

63303 Dreieich 

Germany 

tel: 49-61 03-9 38 90 

fax: 49-61 03-9 38 999 

e-mail: eberhard_beitinger@urscorp.com 

Andreas Bieber (c.r.) 

Federal Ministry for the Environment 

Ahrstrasse 20 

53175 Bonn 

Germany 

tel: 49/228-305-305-3431 

fax: 49/228-305-305-2396 

e-mail: bieber.andreas@bmu.de 

Bjørn Bjørnstad (c.r.) 

Norwegian Pollution Control Authority 

P.O. Box 8100 Dep 

N-0032 Oslo 

Norway 

tel: 47/22-257-3664 

fax: 47/22-267-6706 

e-mail: bjorn.bjornstad@telemax.no 

Volker Böhmer 

Hessische Industriemüll GmbH 

Bereich Altlastensanierung 

Kreuzberger Ring 58 

65205 Wiesbaden 

Germany 

tel: 49/611-7149-700 

fax: 49/611-7149-322 

e-mail: volker@boehmer@him.de 

Michael Bosley 

International Engineering Center 

US Army Corps of Engineers-Europe 

Konrad Adennauar Ring 39 Box 20 

65187 Wiesbaden 

Germany 

tel: 49-611-816-2692 

e-mail: 

MICHAEL.J.BOSLEY@nau02.usace.army.mil 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

129 

Harald Burmeier 

Fachhochschule North-East Lower Saxony 

Department of Civil Engineering 

Herbert Meyer Strasse 7 

29556 Suderburg 

Germany 

tel: 49/5103-2000 

fax: 49/5103-7863 

e-mail: h.burmeier@t-online.de 

Laurence Davidson 

c/o EarthFx Inc. 

2635 Ulster Crescent 

K1V 8J5 Ottawa, Ontario 

Canada 

tel: 613.260.2020 

fax: 613.260.252 

e-mail: ld@earthfx.com 

Branko Druzina (c.r.) 

Institute of Public Health 

Trubarjeva 2-Post Box 260 

6100 Ljubljana 

Slovenia 

tel: 386/1-313-276 

fax: 386/1-323-955 

e-mail: branko.druzina@ivz-rs.si 

Vítor A.P.M. Dos Santos (c.r.) 

Spanish National Research Council 

Professor Aubareoal 

18008 Granada 

Spain 

tel: 34/958-121-011 

fax: 34/958-129-600 

David Edwards 

Leader ExSite 

VHE Holdings plc. 

CEO's Office 

Shafton, Barnsley, S72 8SP 

United Kingdom 

tel: 44/1977-683300 

fax: 44/870-1314537 

e-mail: exSite@btinternet.com 

Erol Erçag 

Istanbul University 

Dept. of Chemistry 

Avcilar Campus, Avcilar 34850 

Istanbul 

Turkey 

tel: 90/212-5911-998 

fax: 90/212-5911-997 

e-mail: ismailb@istanbul.edu.tr 

James Finnamore 

WSP Environmental 

Buchanan House 

24-30 Holborn 

London EC1N 2HS 

United Kingdom 

tel: 44/20-7314-5000 

fax: 44/20-7314-5005 

e-mail: jim.finnamore@wspgroup.com 

Volker Franzius 

Umweltbundesamt 

Bismarckplatz 1 

D-14193 Berlin 

Germany 

tel: 49/30-8903-2496 

fax: 49/30-8903-2285 or -2103 

e-mail: volker.franzius@uba.de 

Ioan Gherhes (c.r.) 

EPA Baia Mare 

1/A Iza Street 

4800 Baia Mare 

Romania 

tel: 40/4-62-276-304 

fax: 40/4-62-275-222 

e-mail: IGherhes@apmbm.ro 

Detlef Grimski 

Umweltbundesamt 

Bismarckplatz 1 

14 193 Berlin 

Germany 

tel: 49/30-8903-2266 

fax: 49/30-8903-2103 

e-mail: detlef.grimski@uba.de 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

130 

Karl Grundler 

Hessisches Ministerium für Umwelt, 

Landwirtschaft und Forsten 

Mainzer Str. 98 – 102 

65189 Wiesbaden 

Germany 

tel: 49/611-815-1373 

fax: 49/611-81-1947 

e-mail: abtrilung.3@mue.hessen.de 

Bernhard Hammer (c.r.) 

Federal Office of the Environment, 

Forests & Landscape (BUWAL) 

Federal Department of the Interior 

Buwal Laupenstrausse 20 

3003 Bern 

Switzerland 

tel: +41/31-322-6961 

fax: +41/31-382-1546 

e-mail: Bernhard.Hammer@buwal.admin.ch 

Gregory Harvey 

Aeronautical Systems Center 

Environmental Safety and Health Division 

1801 10th St. 

Bldg. 8, Suite 200 - Area B 

WPAFB, OH 45433 

United States 

tel: 937-255-7716 (ext. 302) 

fax: 937-255-4155 

e-mail: gregory.harvey@wpafb.af.mil 

R.A.A. (Rolf) Hetterschijt 

P.O. Box 6012 

2600 JA Delft 

The Netherlands 

tel: +31 152 696 257 

fax: +31 152 564 800 

e-mail r.hetterschijt@nitg.tno.nl 

Howard Hornfeld 

Programme Coordinator for the Chemical 

Industry 

United Nations Economic Commission for 

Europe 

Palais des Nations 429-3 

CH-1211 Geneva 10 

Switzerland 

tel.: 41 22 917 3254 

fax.: 41 22 917 0178 

e-mail: chem@unece.org 

Masaaki Hosomi (c.r.) 

Tokyo University of Agriculture and 

Technology 

2-24-16 Nakamachi, Koganei 

Tokyo 184 

Japan 

tel: 81/3-423-887-070 

fax: 81/3-423-814-201 

e-mail: hosomi@cc.tuat.ac.jp 

Stephen C. James (Co-Director) 

U.S. Environmental Protection Agency 

26 Martin Luther King Dr. 

Cincinnati, OH 45268 

United States 

tel: 513-569-7877 

fax: 513-569-7680 

e-mail: james.steve@epa.gov 

Harald Kasamas 

EU Concerted Action CLARINET 

Breitenfurterstr. 97 

A-1120 Vienna 

Austria 

tel: 43/1-804 93 192 

fax: 43/1-804 93 194 

e-mail: 101355.1520@compuserve.com 

Lisa Keller 

Environmental Technology Advancement 

Directorate 

Environment Canada - EPS 

12th floor, Place Vincent Massey 

Hull, Quebec K1A 0H3 

Canada 

tel: 819-953-9370 

fax: 819-953-0509 

e-mail: Lisa.Keller@ec.gc.ca 

Peter Kontny 

Probiotec GmbH 

Schillingstraße 33 

52355 Düren-Gürzenich 

Germany 

tel: 49/2421-6909-65 

fax: 49/2421-6909-61 

e-mail: info@probiotec.ac-euregio.de 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

131 

Hans-Peter Koschitzky 

Technical director, VEGAS, Research Facility 

Chair for Hydraulics and Groundwater 

University of Stuttgart 

Pfaffenwaldring 61 

D - 70550 Stuttgart 

Germany 

tel: 49/711-686 - 4717 

fax: 49/711-685-7020 

Kazuhide Kuzawa 

Japan Environment Agency 

1-2-2 Kasumigaseki 

100-8975 Chiyoda-ku, Tokyo 

Japan 

tel: 81/3-5521-8322 

fax: 81/3-3593-1438 

e-mail: KAZUHIDE_KUZAWA@eanet.go.jp 

Walter W. Kovalick, Jr. (Co-Director)

Technology Innovation Office 

U.S. Environmental Protection Agency 

1200 Pennsylvania Ave. (5102G) 

Washington, DC 20460 

United States 

tel: 703-603-9910 

fax: 703-603-9135 

e-mail: kovalick.walter@epa.gov 

Hana Kroová (c.r.) 

Czech Ministry of the Environment 

Vrsovická 65 

100 10 Prague 10 

Czech Republic 

tel: 420/2-6712-1111 

fax: 420/2-6731-0305 

Andrea Lodolo 

ICS-UNIDO 

Pure and Applied Chemistry 

Area Science Park Building L2 

Padriciano, 99 

34012 Trieste 

Italy 

tel.: 39-040-9228114 

fax: 39-040-9228115 

e-mail: emanuela.corazzi@ics.trieste.it 

Ian D. Martin (c.r.) 

The Environment Agency 

Olton Court, 10 Warwick Road 

Olton, West Midlands 

United Kingdom 

tel: 44/121-711-2324 

fax: 44/121-711-5830 

e-mail: ian.martin@environment-agency.gov.uk 

Nora Meixner (c.r.) 

Federal Ministry of Environment, Youth and 

Family Affairs 

Dept. III/3 

Stubenbastei 5 

A-1010 Vienna 

Austria 

tel: 43/1-515-22-3449 

fax: 43/1-513-1679-1008 

e-mail: Nora.Meixner@bmu.gv.at 

Jochen Michels 

DECHEMA 

Theodor-Heuss-Allee 25 

60486 Frankfurt am Main 

Germany 

tel: 49-69-75 64-2 35 

fax: 49-69-75 64-2 35 

e-mail: michels@dechema.de 

Jacqueline Miller (c.r.) 

Brussels University 

Avenue Jeanne 44 

1050 Brussels 

Belgium 

tel: 32/2-650-3183 

fax: 32/2-650-3189 

e-mail: jmiller@ulb.ac.be 

Walter Mondt 

Ecorem n.v. 

Zwartzustersvest 22 

B-2800 Mechelen 

Belgium 

tel: 32/15-21 17 35 

fax: 32/15-21 65 98 

e-mail: ecorem@glo.be 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

132 

Christoph Munz 

Env. Eng., Dept. Head Chemical Risk 

Assessment 

BMG Engineering AG 

Ifangstrasse 11 

CH-8952 Zurich 

Switzerland 

tel. 41/1-732-92 77 

fax. 41/1-732-92 21 

e-mail: christoph.munz@bmgeng.ch 

Joop Okx 

Tauw Milieu bv 

PO Box 133 

7400 AC Deventer 

The Netherlands 

tel: 31 570 699911 

fax: 31 570 699666 

e-mail: jpo@tauw.nl 

Johannes Pastor 

Bundesministerium für Umwelt 

Naturschutz und Reaktorsicherheit 

Postfach 12 06 29 

53048 Bonn 

Germany 

tel: 49-2 28-3 05-34-30 

fax: 49-2 28-3 05-23 96 

Simon Pollard 

The Environment Agency 

Steel House 

11 Tothill Street 

London SW1H 9NF 

United Kingdom 

tel: 44 20 7664 6832 

fax: 44 20 7664 6836 

e-mail: simon.pollard@environmentagency.gov.uk 

Francesca Quercia (c.r.) 

ANPA - Agenzia Nazionale per la Protezione 

dell'Ambiente 

Via V. Brancati 48 

I - 00144 Rome 

Italy 

tel. 39/6-5007-2510 

fax 39/6-5007-2531 

e-mail quercia@anpa.it 

Charles Reeter 

Naval Facilities Engineering Service Center 

U.S. Navy 

1100 23rd Avenue, Code 411 

Port Hueneme, CA 93043 

United States 

tel: 805-982-4991 

e-mail: reetercv@nfesc.navy.mil 

Mathias Schluep 

BMG Engineering AG 

Ifangstrasse 11 

8952 Schlieren 

Switzerland 

tel: 41/1-730-6622 

fax: 41/1-730-6622 

Ari Seppänen (c.r.) 

Ministry of Environment 

P.O. Box 399 

00121 Helsinki 

Finland 

tel: 358/9-199-197-15 

fax: 358/9-199-196-30 

e-mail: Ari.Seppanen@vyh.fi 

Rainer Siebert 

Bundesministerium für Umwelt, 

Naturschutz und Reaktorsicherheit 

Postfach 12 06 29 

53048 Bonn 

Germany 

tel: 49-228-305-3434 

fax: 49-228-305-2396 

e-mail: siebert.rainer@bmu.de 

Roberrt Siegrist 

Colorado School of Mines 

Environ.Science and Eng.Division 

1500 Illinois Ave. 

Golden, CO 80401-1887 

United States 

tel: 303-273-3490 

fax: 303-273-3413 

e-mail: rsiegris@mines.edu 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

133 

Sjef Staps 

TNO Institute of Environment, Energy, and 

Process Innovation 

Department of Environmental Biotechnology 

P.O. Box 342 

7300 AH Apeldoorn 

The Netherlands 

tel: 31 55 549 3351 

fax: 31 55 549 3523 

e-mail: s.staps@mep.tno.nl 

Kai Steffens 

PROBIOTEC GmbH 

Schillingsstra e 333 

D 52355 Düren-Gürzenich 

Germany 

tel: 49/2421-69090 

fax: 49/2421-690961 

e-mail: steffens@probiotec.de 

Rita Hermanns Stengele 

Professor for Environmental Geotechnics 

Institute of Geotechnical Engineering 

ETH Hönggerberg/HIL 

CH-8093 Zurich 

Switzerland 

tel. 41/1-633-2524 or 633-2525 (secreatriat) 

fax. 41/1-633-10 9 

e-mail: hermanns@igt.baum.ethz.ch 

Robert Stewart 

University of Tennessee 

1060 Commerce Park 

Oak Ridge, TN 37830 

United States 

tel: 865-241-5741 

fax: 865-574-0004 

e-mail: u47@ornl.gov 

Terry Sullivan 

Environmental Sciences Department 

34 North Railroad Street, Building 830 

Upton, NY 11973-5000 

United States 

tel: 631-344-3840 

fax: 631-344-4486 

e-mail: tsullivan@bnl.gov 

Jan Svoma 

Aquatest a.s. 

Geologicka 4 

152 00 Prague 5 

Czech Republic 

tel: 420/2-581-83-80 

fax: 420/2-581-77-58 

e-mail: aquatest@aquatest.cz 

Bert-Axel Szelinski 

Bundesministerium für Umwelt 

Naturschutz und Reaktorsicherheit 

Alexanderplatz 6 

11055 Berlin 

Germany 

tel: 49-30-2 85 50-42 70 

fax: 49-30-2 85 50-43 75 

e-mail: szelinski.axel@bmu.de 

Safieh Taghavi 

Vlaamse Instelling voor Technologisch 

Onderzoek (Vito) 

Environmental Technology Expertise Center 

Boeretang 200 

B.2400 Mol 

Belgium 

tel: 32/14-335162 

fax: 32/14-580523 

e-mail: safiyh.taghavi@vito.be 

Georg Teutsch 

University of Tübingen 

Sigwartstrasse 10 

72076 Tübingen 

Germany 

tel: 49/707-1297-6468 

fax: 49/707-150-59 

e-mail: georg.teutsch@uni-tuebingen.de 

Steven Thornton 

University of Sheffield 

Mappin Street 

Sheffield 

United Kingdom 

tel: 44/114-222-5700 

fax: 44/114-222-5700 

e-mail: S.F.Thornton@sheffield.ac.uk 
Decision Support Tools NATO/CCMS Pilot Project Phase III 

134 

Kahraman Ünlü (c.r.) 

Depratment of Environmental Engineering 

Middle East Technical University 

Inönü Bulvari 

06531 Ankara 

Turkey 

tel: 90/312-210-1000 

fax: 90/312-210-1260 

e-mail: kunlu@metu.edu.tr 

H. Johan van Veen (c.r.) 

TNO/MEP 

P.O. Box 342 

7800 AN Apeldoorn 

The Netherlands 

tel: 31/555-493922 

fax: 31/555-493921 

e-mail: H.J.vanVeen@mep.tno.nl 

Joop Vegter 

The Technical Committee on Soil Protection 

(TCB) 

Postbus 30947 

2500 GX The Hague 

The Netherlands 

tel: 31/70-339-30-34 

fax 31/70-339-13-42 

e-mail: tcb@euronet.nl 

John Vijgen 

Consultant 

Elmevej 14 

DK-2840 Holte 

Denmark 

tel: 45/45 41 03 21 

+fax: 45/45 41 09 04 

e-mail: john.vijgen@get2net.dk 

Stephan Volkwein 

C.A.U. 

Daimlerstraße 23 

63303 Dreieich 

Germany 

tel: 49-61 03-9 83-25 

fax: 49-61 03-9 83-10 

e-mail: c.a.u.@t-online.de 

Christian Weingran 

Hessische Industriemüll GmbH 

Müllerwegstannen 46 

35260 Stadtallendorf 

Germany 

tel: 49/6428-9235-11 

fax: 49/6428-9235-35 

e-mail: asq.stadtallendorf@t-online.de

Holger Weiss 

UFZ-Umweltforschungszentrum 

Leipzig-Halle GmbH 

Postfach 2 

Germany 

tel: 49-3 41-2 35-20 58 

fax: 49-3 41-2 35-21 26 

e-mail: weiss@pro.ufz.de 

Paul Wersin 

Geochemist/Project Manager Safety Analysis 

NAGRA (National Cooperative for the Disposal 

 of Radioactive Waste) 

Hardstrasse 73 

CH-5430 Wettingen 

Switzerland 

tel. 41/56-437-12 80 

fax. 41/56 -437-1317 

e-mail: paul.wersin@nagra.ch 

Dieter Weth 

Mull & Partner Ingenieurgesellschaft 

Osterlede 5 

30827 Garbsen 

Germany 

tel: 49-513-1 46 94-0 

fax: 49-513-1 46 94-90 

e-mail: weth@mullundpartner.de 

Uwe Wittmann 

Umweltbundesamt 

Seecktstraße 8-10 

13581 Berlin 

Germany 

tel: 49-30-89 03- 

fax: 49-30-89 03-38 33 

e-mail: uwe.wittmann@uba.de
Decision Support Tools NATO/CCMS Pilot Project Phase III 

135 

Anthimos Xenidis 

National Technical University Athens 

52 Themidos Street 

15124 Athens 

Greece 

tel: 30/1-772-2043 

fax: 30/1-772-2168 

 

Mehmet Ali Yukselen 

Marmara University 

Environmental Engineering Department 

Goztepe 81040 Istanbul 

Turkey 

tel: 90/216-348-1369 

fax: 90/216-348 -0293