Applicability of risk-based management and the need for risk-based economic decision analysis at hazardous waste contaminated sites

Environment International 29 (2003) 503 – 519 www.elsevier.com/locate/envint

Applicability of risk-based management and the need for risk-based economic decision analysis at hazardous waste contaminated sites Ibrahim Khadam, Jagath J. Kaluarachchi * Department of Civil and Environmental Engineering, and Utah Water Research Laboratory, Utah State University, 8200 Old Main Hill, Logan, UT 84322-8200, USA Received 18 September 2002; accepted 31 December 2002

Abstract Decision analysis in subsurface contamination management is generally carried out through a traditional engineering economic viewpoint. However, new advances in human health risk assessment, namely, the probabilistic risk assessment, and the growing awareness of the importance of soft data in the decision-making process, require decision analysis methodologies that are capable of accommodating nontechnical and politically biased qualitative information. In this work, we discuss the major limitations of the currently practiced decision analysis framework, which evolves around the definition of risk and cost of risk, and its poor ability to communicate risk-related information. A demonstration using a numerical example was conducted to provide insight on these limitations of the current decision analysis framework. The results from this simple ground water contamination and remediation scenario were identical to those obtained from studies carried out on existing Superfund sites, which suggests serious flaws in the current risk management framework. In order to provide a perspective on how these limitations may be avoided in future formulation of the management framework, more matured and well-accepted approaches to decision analysis in dam safety and the utility industry, where public health and public investment are of great concern, are presented and their applicability in subsurface remediation management is discussed. Finally, in light of the success of the application of risk-based decision analysis in dam safety and the utility industry, potential options for decision analysis in subsurface contamination management are discussed. D 2003 Elsevier Science Ltd. All rights reserved. Keywords: Risk-based management; Contaminated sites; Soft data; Remediation

1. Introduction The last few years have witnessed the replacement of the drinking water standard by the risk-based standards as the criterion for ground water cleanup. This shift was a result of many critiques and problems encountered following the enforcement of the Comprehensive Environmental Response, Compensation, and Liability Act (CERCLA) and the Resource Conservation and Recovery Act (RCRA) in the US. Many practical issues relating to the implementation of remediation programs have hindered the restoration of contaminated aquifers. These issues include the economical constraints due to the unexpected high cost of remediation and political concerns about the allocation of finite resources to problems with continuously increasing size and magnitude of scope (Readnour et al., 1999; Day et al., 1997; * Corresponding author. Tel.: +1-435-797-3918; fax: +1-435-7973663. E-mail address: [email protected] (J.J. Kaluarachchi).

Van Houtven and Cropper, 1996; Sharefkin et al., 1994; Ricci and Molton, 1984). The experience gained through two decades of aggressive effort to restore contaminated ground water to its native conditions indicated that complete cleanup of ground water may not be possible using the existing technologies (NRC, 1994). Although some sites can be restored to the drinking water standard or more specifically to the maximum contaminant level (MCL), it is understood that this can be achieved only under favorable hydrogeological conditions, limited extent of contamination, and/or exceptionally active natural attenuation (NRC, 1994). In addition to the subsurface complexity, unfavorable characteristics of chemicals present in the ground water also add to the difficulty of the task. For example, the presence of dense non-aqueous phase liquids (DNAPL) typically indicate that complete cleanup may not be possible, at least using the current technologies. These practical limitations to achieve complete restoration of the subsurface brought forward many questions and doubts on the possibility of achieving ground water restoration.

0160-4120/03/$ - see front matter D 2003 Elsevier Science Ltd. All rights reserved. doi:10.1016/S0160-4120(03)00009-6

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Due to the concerns discussed earlier, the costs of remediation reached unexpected heights that produced concerns for federal, state, and local governments as well as for the private polluters who are held liable for contamination (Van Houtven and Cropper, 1996; Ricci and Molton, 1984). The economical concerns were further deepened when it was realized that a substantial part of the cost was directed towards contamination present at residual levels that pose little health or environmental hazards. It was clear that there was a need to establish realistic cleanup criteria that would direct efforts and resources to actual hazards; otherwise, efforts would be directed towards cleanup efforts where little or no potential risk exists (Viscusi et al., 1997). Despite the large effort being made to clean up contaminated sites, the list of contaminated sites that require cleanup continued to increase over the past years. This increase is partly due to the fact that pollution increase is directly related to the industrial growth that has continued at high rates; and partly due to the fact that following the implementation of CERCLA and RCRA, large-scale subsurface contamination was detected, and only then the full extent of the problem was fully acknowledged (NRC, 1994). The major reason to this serious contamination was largely from leaking underground storage tanks at gasoline stations, fuel tank depots, and industries and federal agencies where chlorinated solvents are widely used in industrial operations. It was then evident that a new management policy was needed to permit efficient allocation of limited resources to manage the increasing subsurface contamination in a rational manner. It took many years of debate about the merits and disadvantages of a risk-based management policy and many more years of active research to generate the necessary supporting data before health risk was finally established as the decision criterion for cleanup management. The riskbased management approach was officially born in the early 1990s and advocated by the US Environmental Protection Agency (US EPA) through its guidelines for risk-based cleanup levels (US EPA, 1989a,b, 1991). Thus, health risk became an integral component of subsurface contamination control and management. Although risk-based remediation appeared to be attractive at its onset compared to using MCL as the decision criterion, there are many shortcomings and limitations of the overall approach. These limitations are partly due to (a) lack of detailed information on supporting data; for example, toxicology data on many carcinogens are lacking or subject to limited knowledge (Asante-Duah, 1993; Louvar and Louvar, 1998); (b) uncertainty and variability of field data (also known as ‘‘hard data’’); for example, hydrogeologic or population characteristic data (McKone and Bogen, 1991; McKone, 1994; Andricˇevic´ and Cvetkovic´, 1996; Frey and Rhodes, 1996; Gorelick, 1997), and (c) inadequate representation of qualitative data (also known as ‘‘soft data’’); for example, public perception or political consideration. Due to these limitations, it is now apparent that even the risk-based

management of contaminated sites may have serious shortcomings especially when substantial resources are spent on reducing residual risks, thereby limiting valuable resources to a small set of large sites (Viscusi, 1998). The purpose of this manuscript is to discuss the concerns and limitations related to the existing framework of riskbased management of contaminated sites and to explore the need to extend our understanding to a formal health riskbased economic decision analysis. It is not the intent of this work to present a formal health risk-based economic decision analysis framework, but to provide a review of current and previous approaches for ground water cleanup, discuss the limitations and the reasons for the limitations of the existing framework through data from environmental laws and regulations, and to provide justification to address the limitations through a more formal decision analysis methodology that can comprehensively balance economic costs and human health risk.

2. Risk-based remediation The current framework of contamination control and management is composed of two stages—risk assessment and risk management (Asante-Duah, 1993). Risk assessment includes two steps: (i) the quantification of the probability of occurrence of harm to human health, e.g., cancer risk; and (ii) the evaluation of the significance of this probability. Risk management becomes important when the risk is found unacceptable. Risk management has two stages; identification of possible remedial options and the decision-making process to choose the best remedial option that will achieve regulatory compliance irrespective of the economic costs (see Fig. 1). 2.1. Risk assessment Health risk is quantified through a risk model that assumes a linear relationship between the intake chemical dose and the risk to individual health. The relationship is based on the coefficient called the slope factor in the case of carcinogens, and the coefficient called the reference dose in the case of non-carcinogens. Slope factor is the potential of

Fig. 1. Framework for risk-based cleanup of contaminated subsurface.

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developing cancer for a certain daily dose taken over the lifetime. Reference dose is an expression of the adverse noncarcinogenic health effects associated with high intake of chemicals (Asante-Duah, 1993; Louvar and Louvar, 1998). These coefficients are estimated for humans by extrapolating the laboratory results on animals. Estimation of the received chemical dose requires the identification of the possible scenarios of exposure to the chemical, i.e., through the exposure pathways. This risk model is also used to estimate the risk-based cleanup level corresponding to a specified risk level through simple back-calculation. The evaluation of risk significance follows the acceptable and significant risk levels defined by the US EPA (US EPA, 1989b). The acceptable risk is below 10
6 while the significant risk is usually higher that 10
4. The acceptable risk warrants no-active remediation while significant risk requires immediate measures to control and reduce the high risk. Since the risk quantification encompasses many uncertainties and controversial assumptions, the evaluation of risk significance usually takes into account some site-specific considerations such as qualitative information or ‘‘soft data’’ in addition to the estimated risk. As a result, the significant and insignificant risk levels are not treated as ‘‘bright lines’’ as in other engineering standards (Morris, 1997). Risk assessment requires the identification of the feasible remedial alternatives that can be implemented to achieve the ultimate goal of public health protection. This process requires a remedial investigation and a feasibility study for different potential remedial alternatives. Once the supporting data are available, decision-making is performed to select the best alternative. Generally, the criteria that would decide the best alternative include the performance of the alternative in controlling the contamination, efficiency defined by the time to accomplish the required cleanup, and cost-effectiveness (Freeze et al., 1990). Most of the research work performed in the past few years concentrated on risk assessment and these studies identified many shortcomings of the existing risk assessment framework. One of the serious limitations of the methodology is the use of conservative point estimates for input parameters to ensure that actual risk is not underestimated due to the wide range of uncertainty. Such use of high-end values for input parameters yields the upper percentile estimates of risk, which was thought to be the best approach to ensure public health safety. However, this approach does not quantify the extent to which the conservative estimate may overstate the actual risks to the decision-maker, and thereby enforcing costly and unjustified cleanup measures and goals (Viscusi et al., 1997). Other problems of the risk quantification model included the focus on cancer risk only while neglecting other adverse health effects, the use of an empirical linear model to describe the complex and not well-understood phenomenon of cancer, and the accuracy and representativeness of exposure scenarios and pathways. Some critics advocate that consideration of health risk only is not appropriate and

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socioeconomic impacts on the affected group are equally important (Sharefkin et al., 1994). In the presence of these limitations in the existing risk-based management approach, the focus over the past few years has been on the uncertainty and variability of key input parameters (Finley and Paustenbach, 1993; McKone and Bogen, 1991). The remaining shortcomings of the linear risk model are considered to be intractable with the current level of understanding. The main sources of uncertainty in risk estimates are the uncertainties in site-specific hydrogeological and geochemical properties and the variability of population behavioral and physical characteristics. Substantial research work was performed to better understand the effects of hydrogeologic uncertainties and population variability on the risk estimate (Evans and Bedient, 1993; Hoffman and Hammonds, 1994; McKone, 1994; Frey and Rhodes, 1996; Maxwell et al., 1998, 1999; Zhao and Kaluarachchi, 2002). The results of these efforts gave birth to probabilistic risk assessment, which has become the standard of practice in risk assessment. Probabilistic risk assessment describes each uncertain input parameter to the risk model as a statistical distribution. The model output is a statistical distribution of risk estimate, usually obtained using the Monte Carlo method. The risk distribution provides the risk estimate corresponding to a given percentile of the population variability with a certain degree of confidence (Bogen, 1995; Frey and Rhodes, 1996; Chang, 1999; Lahkim and Garcia, 1999; Maxwell et al., 1999; Simon, 1999; Cohen et al., 1996). Probabilistic risk assessment, although more complex and costly in terms of analysis time and effort compared to the point estimates, provides a plausible scientific tool to identify and quantify the uncertainties of risk estimates. Of its many advantages, the elimination of the disputes over the best-point estimates between regulatory and liable parties is the most noteworthy contribution that has arisen from probabilistic risk assessment. Moreover, the risk managers and decision-makers, having more insight into the distribution of risk estimate, will explicitly know how conservative is the final decision or recommendation. 2.2. Risk management A literature review on decision analysis related to subsurface contamination indicates that risk management, through proper decision analysis, is not keeping pace with the advances in risk assessment, especially after the introduction of probabilistic risk assessment. Decision analysis is still carried out through a traditional engineering economic point of view. The new advances in risk assessment require a decision analysis methodology that will allow the inclusion of improved information derived from probabilistic risk assessment. However, the qualitative nature of soft data makes the development of a decision analysis methodology a complex task. Classical decision analysis in engineering applications is performed using an economic analysis of the different

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alternatives. The relative desirability of each alternative, with respect to the others, is measured by an economic index such as the total revenue, benefit/cost ratio, or rate of return. The best alternative is decided following a decision criterion such as the maximum, maximin, minimax regret, or robustness criteria. A popular approach for a decision analysis problem is to maximize the total revenue objective function that incorporates the net present value of a stream of benefits and costs. The objective function also includes uncertainties by incorporating the expected cost of failure. The uncertainty of each alternative can thus be included in the objective function through the cost of failure. Using the cost of failure, the decision problem is maintained in one dimension, i.e., dollars and cents. A general form of this objective function is as follows: /¼

X

1 ¯ ½BðtÞ
CðtÞ
PðtÞCðtÞ ð1 þ iÞt

where / is the net present value ($); B is the benefit ($); C is the cost associated with remediation actions ($); P is the probability of failure; C¯ is the cost of failure ($); i is the discount rate; and t is the time horizon. This formulation of the risk –cost –benefit (RCB) objective function was widely used because of its simplicity, flexibility, capability of treating uncertainties, and above all due to the ease of interpreting the results in monetary terms. In fact, the RCB analysis is a powerful approach in the sense that it managed to provide an easy tool that reasonably compares different alternatives given that the estimated benefits and costs are accurate. The use of this decision analysis framework in subsurface remediation was initiated by a series of papers by Massmann and Freeze (1987a,b), Freeze et al. (1990), and Massmann et al. (1991). In their work, they made use of the flexibility of the RCB framework that accommodates uncertainties by establishing the linkage between the uncertainty of the hydrological model and the performance of the proposed design using the reliability theory and the costs and benefits of each design. Typically, the RCB analysis in subsurface remediation is performed from the polluter’s viewpoint rather than from the regulatory standpoint. In the formulation of the RCB analysis for a hydrologic problem, the benefits are the expected revenue from the proposed facility, e.g., landfill. However, this term is usually neglected in remediation since there are no anticipated benefits to the owner except the benefit of maintaining clean ground water. The other costs are due to the construction and operation of the remediation system. If the RCB analysis is performed from a regulatory point of view, the evaluation of benefits is a necessary task. In the context of defining the economic benefit, the social benefit of maintaining good quality ground water is difficult to define explicitly (Carson and Mitchell, 1993; Raucher, 1983). Although this requirement is always considered to be an important issue in the eyes of the public, the benefit

cannot be readily quantified in a decision analysis environment except through a simplistic approach (Raucher, 1983). Instead, the impacts of using poor quality ground water for drinking purposes can be quantified through the probable health risk. The probability of the failure term in the objective function reflects the uncertainty of the hydrologic parameters and the engineering reliability of the system. The failure costs are the regulatory penalty, litigation costs, and the costs of possible corrective remedial actions imposed by regulators. If engineering reliability is ignored, assuming perfect performance of the design, the probability of failure converges to the probability of failure to comply with a given regulatory criterion. This criterion is usually the exceedance of the MCL, or the migration of the contaminant plume beyond the compliance boundary. The probability of failure is estimated using the hydrologic models in stochastic mode to derive the statistical estimate of failure probability. Attitudes towards the risk can also be included in the probability of failure by using a utility function that expresses risk aversion, seeking, or neutrality of the decision-maker. Thus, the probability of failure is increased, decreased, or left unchanged depending on the type of utility function used. The utility function depends on the magnitude of cost of failure; high failure consequences can lead to conservative estimates of probability of failure.

3. Limitations of the risk –cost –benefit analysis Despite the advantages of the RCB analysis discussed previously, this approach has some serious limitations too. Some of these limitations are the imprecise nature of the failure cost term, the failure definition on which the failure probability is based, the incompatibility with the health riskbased framework, and the inadequate representation of important soft data. Some of this information may be critical to the decision-makers, e.g., magnitude of risk of each alternative posed to workers. 3.1. Definition of risk The risk in the RCB analysis, which is typically the probability of failure, should not be confused with the health risk, which is the probability of harm to human health. The definition of failure, through which risk or failure probability is calculated, is based on the exceedance of ground water concentration beyond the MCL. Information from risk assessment can be included in the RCB formulation by using risk-based cleanup levels instead of the MCL. Riskbased cleanup levels are estimated through back-calculation using the risk quantification model. However, back-calculation implies the use of the point estimates in the risk model, because probabilistic risk assessment that depends on the propagation of uncertainties is difficult to use in a

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back-calculation mode. This difficulty may cause elimination of important information on variability and uncertainty of health risk estimates in the RCB framework. This serious flaw in the failure definition shows that the RCB methodology is not the best approach to address risk-based environmental management. 3.2. Definition of risk/failure cost The failure cost term used in the RCB objective function can never be guaranteed to be inclusive nor precise due to the nature of post-failure consequences that are inherently difficult to predict. The litigation cost, regulatory penalty, loss of opportunity or investment, and damage to public relations cannot be quantified or even predicted. The magnitude of the failure cost affects directly the alternative that is chosen. Decisions made using an RCB analysis are regularly subject to high sensitivity to the failure cost (Russell and Rabideau, 2000; Waldis et al., 1999; Rosen and LeGrand, 1997). Moreover, double ambiguity results when the failure costs are associated with the uncertainty of failure. The final result is expressed as a monetary value that does not represent the actual expected cost of alternative to an acceptable degree of confidence. 3.3. Communication of risk information Public interest in health and environmental impacts of pollution has grown considerably in recent years due to the increased awareness of health effects of environmental pollution. This interest has made it vital to include the public in the decision-making process. The key advantages of public participation are that important environmental projects are implemented under immense public pressure, expensive and non-effective projects are forced to terminate, and liable polluters are forced to perform necessary cleanup through the litigation process. In order to obtain the best feedback from the public, communication and education of the public are vital. However, communication of risk information is inherently difficult and complex due to the complexity of the technical information. Even in the presence of this difficulty, it is still important to encourage public participation to avoid situations of serious misunderstandings. The difficulties in risk communication are further deepened because of the nature of RCB analysis that tends to conceal the degree of uncertainty in the outcome. Typically, an RCB analysis provides the information on the current and future scenarios in monetary terms, which is easy to understand. However, the information from the RCB analysis does not provide important information such as the actual risk, the significance of the risk, and the confidence of risk estimates. Most importantly, the consequences of the risk are not well presented, since the non-monetary benefits and consequences are typically ignored.

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4. Demonstration example As discussed in the previous sections, the existing framework of risk-based cleanup is much more effective and efficient than the earlier approach of using the MCL criterion. Although uncertainty and variability have been adequately addressed in the risk assessment literature, there are many limitations to the existing framework that need to be addressed and overcome in order to manage contaminated sites in a better way. The next section will demonstrate the inherent difficulty of making decisions by using the health risk alone as the decision criterion without considering the overall economic cost of remediation. Although the demonstration example is relatively simple and straightforward, the information derived from the results is broadbased and illustrates the shortcomings and ill-defined areas of the existing framework. 4.1. Problem formulation Consider a classical scenario of a leaking underground storage tank (LUST) of a gasoline station that produced a dissolved organic plume moving towards a municipal drinking water supply well (see Fig. 2). The well is providing drinking water for a population of 4000 with 2000 m3 of drinking water daily. In a typical scenario, the exact history of the contamination event is not known and field investigations will be conducted to determine the extent of the plume and the future fate and transport behavior. In order to focus on the overall goal of this demonstration example, the complete scenario is developed through a numerical experiment. In this case, the water supply well is located 2000 m downgradient of the LUST and the representative organic is benzene, which is a carcinogen. The leak occurred at a concentration of 500 mg/l for a period of 30 years at which time the leak was detected and the source removed. The influent concentration of 500 mg/l is much less than the solubility of benzene of 1780 mg/l and comparable to values reported by Althoff et al. (1981). The focus of the field investigation at this time will be to determine the fate and transport of the dissolved plume and the potential health risk to the exposed community. For demonstration purposes, the remediation options under consideration will be natural attenuation or pump and treat (PAT). The first step of the investigation will be to perform field investigations to assess the site hydrogeology and fate and transport characteristics of the dissolved plume so that a conceptual model of fate and transport can be developed. The second step will be to perform a baseline risk assessment to determine the potential health risk to the exposed population. If natural attenuation alone can destroy the plume to an acceptable risk, then no further action will be needed except monitoring of the plume. However, if the potential risk is too high, then active remediation is needed.

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Fig. 2. Schematic showing the physical layout of the contamination event.

4.2. Site hydrogeology The idealized aquifer considered in this study is a sandy gravel confined aquifer with a uniform thickness of 100 m, length of 4 km, and a width of 2 km. A natural hydraulic gradient of 0.002 m/m is producing steady ground water flow from west to east, while the north and south sides of the aquifer are considered no-flow boundaries. The geologic formation of the aquifer has an effective porosity of 0.2, a bulk density of 1.75 g/cm3, and a soil carbon fraction, foc, of 0.01, and these values are similar to those described by Bedient et al. (1994). The longitudinal dispersivity is approximated, for a flow path of 2000 m (the distance from the source to the municipal well), to be 15 m (Fetter, 1999) and this value represents the heterogeneity at the existing scale. Assuming a dispersivity ratio of 10, the transverse dispersivity is about 1.5 m. A uniform hydraulic conductivity field of 20 m/day is assumed. The major subsurface processes that control the fate and transport of benzene are advection, dispersion, sorption, and biodegradation while diffusion is neglected. The retardation coefficient, which is 2.3, was estimated using the organic carbon partition coefficient, Koc, for benzene of 1.5 (Fetter, 1999). Biodegradation of benzene was simulated using the instantaneous reaction model (Borden and Bedient, 1986). Commonly used biodegradation kinetic models, such as first-order or monod-type kinetics, require substantial sitespecific data that are not readily available. However, the instantaneous model requires minimum data, but is subject to limitations such as complete biodegradation of the organic assuming completing mixing of electron acceptor, organic substrate, and nutrients, and instantaneous degradation of the organic substrate without rate limitation. Given the purpose of this simulation, we believe that the instantaneous reaction model can provide adequate insight to

biodegradation kinetics without significant errors in the overall results. The instantaneous model simulates biodegradation by the reduction of electron acceptors commonly found in ground water such as oxygen, nitrate, iron, sulfate, and CO2. Since biodegradation of benzene by nitrate is almost negligible, nitrate reduction was not considered here (Barker and Wilson, 1997). Typical values of background concentrations of electron acceptors used here are similar to the values report by Bedient et al. (1994) and are summarized in Table 1. 4.3. Simulation of fate and transport In order to perform the risk assessment, a fate-andtransport simulation should be conducted to determine the breakthrough curve at the municipal well under different management scenarios. In the flow simulation, constant head boundaries are specified on the east and west boundaries that produce the natural hydraulic gradient over the domain. The model domain was discretized horizontally into 40 columns and 40 rows with a cell size of 50  100 m2. The vertical domain was discretized into two layers. The top layer, in which the contamination is present, is 10 m in depth and the second layer is 90 m in depth. The widely used ground water model MODFLOW (McDonald and Harbaugh, 1988; Harbaugh and McDonald, 1996) was Table 1 Information of electron acceptors used in the simulation Electron acceptor

Stoichiometric ratio

Background concentration (mg/l)

Concentration in plume (mg/l)

O2 Fe+ 3 2 SO
4 CO2

3.08 21.48 4.62 2.12

3.0 3.5 10 0.001

0.5 100 1 0.1

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employed to simulate steady flow and transient fate and transport with instantaneous biodegradation using the RT3D module (Clement et al., 1998). The first scenario corresponds to the leak event in the first 20 years followed by natural attenuation without the source during the remaining period of time. Since the health risk under natural attenuation was found to be excessive, a second simulation was conducted for the pump-and-treat scenario. In this case, the same source was simulated for 20 years followed by pump-and-treat for different remediation periods. 4.4. Risk assessment The municipal well supplies drinking water to a population of 4000. The average point estimate representing the reasonably maximum exposed individuals, RME, was used to represent the exposed population (US EPA, 1989b). The risk calculation for the base case used the peak concentration of the 30-year average BTC (see also Fig. 3). Table 2 summarizes the risk-related input parameters used in the risk calculations. The risk assessment was conducted for an offsite scenario with common ground water exposure pathways of ingestion of water, inhalation of volatiles in water, and dermal contact. The risk assessment for the base case with natural attenuation produced risks due to ingestion, inhalation, and dermal contact of 2.8  10
3 , 1.03  10
2 , and 5  10
4, respectively, and the total risk was 1.4  10
2 or 14 cancer cases per 1000 residents. Since this total risk is far beyond the acceptable value of 10
4 or 0.1 per 1000 residents, active remediation is needed. In the second hydrogeologic simulation, a simple pump-and-treat (PAT) scenario was modeled with two pumping wells. The first pumping well is located 600 m downgradient from the source and the second pumping well is located 250 m downgradient from the source. A constant pumping rate of 500 gpm in the first downgradient well was found sufficient

Fig. 3. Breakthrough curve and the corresponding 30-year average curve obtained for the natural attenuation scenario.

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Table 2 Population- and chemical-based parameters used in the risk assessment (US EPA, 1989a) Parameter

Value

Unit

Ingestion rate, Ig Inhalation rate, Ih Exposed skin surface-area, Sa Body weight, WB Average lifetime, AT Shower duration, ET Exposure frequency, EF Exposure duration, ED Skin permeability constant, Pc Benzene volatilization factor, K Benzene slope factor (ingestion), SFg Benzene slope factor (inhalation), SFh Benzene slope factor (dermal contact), SFd

2 15 18,150 70 70 0.2 350 30 0.1 0.5 0.029 0.029 0.029

l/day m3/day cm2 kg years h/day day/year years cm/h l/m3 (mg/kg day)
1 (mg/kg day)
1 (mg/kg day)
1

to develop a capture zone that encapsulated the complete contaminated area. The second pumping well was used primarily to accelerate contaminant mass recovery with a constant pumping rate of 300 gpm. This capture zone was further verified using the particle-tracking model MODPATH (Pollock, 1994), which confirmed the capability of the developed capture zone of containing the plume. Seven periods of cleanup consisting of 2, 4, 6, 8, 10, 15, and 20 years were considered. The increase in cleanup time produces additional mass recovery, and eventually a lower risk to the exposed community. At the end of each cleanup period, the pumping is stopped and natural attenuation became the only mode of remediation. The extracted contaminated ground water is treated using an air-stripping system and then discharged into a sewer system. 4.5. Decision analysis As discussed earlier, predicting the health risk alone cannot assess the applicability of a remedial alternative. Instead, both the health risk and cost-effectiveness of the alternative should be carefully studied through a consistent and systematic decision analysis protocol that can address these two critical issues in a balanced manner. However, the purpose of this demonstration example is to illustrate this critical need, not to discuss or present a suitable decision analysis methodology. Therefore, the remaining discussion will focus on the need to consider such a systematic approach in future decision-making. The economic cost model considered in the present study is described in the RACER software (Talisman Partners, 1999) developed for the US Department of Defense. This model allows the computation of the total remedial cost by considering various cost modules relevant for a given set of site conditions. In this study, we considered the most common cost components in a typical PAT remedial scenario which are the monitoring cost, capital implementation cost, operational and maintenance costs, water treatment through air-stripping, and disposal of clean water. The cost

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Fig. 6. Cost-per-life-saved versus remediation cost for various PAT scenarios involving 0, 2, 4, 6, 8, 10, 15, and 20 years of pump and treat. Fig. 4. Predicted cancer risk versus remediation cost for various PAT scenarios involving 0, 2, 4, 6, 8, 10, 15, and 20 years of pump and treat.

values described hereafter refer to the net present values. Fig. 4 shows the predicted cancer risk versus the remediation cost for different remediation periods. Each point on this curve describes the risk and cost for a given operation time of the PAT system; for example, the highest risk and lowest cost is for natural attenuation followed by 2, 4, 6, 8, 10, 15, and 20 years of operation of the PAT system. The computed total costs for the proposed PAT systems of different time durations are displayed in Fig. 5. The results show that remediation costs of the proposed PAT systems can vary from $1.5 million to $8.5 million, indicating a nearly sixfold increase of remediation costs between different schemes. This sixfold increase in the remediation cost produced a reduction of total health risk from approximately 10
2 to less than 10
6, which according to Fig. 6 is more than 99% reduction in the risk. However, in typical decision-making, a percentage reduction may not always produce the true reality and acceptability of a decision unless the other decision-relevant factors are taken into consideration. In order to illustrate the cost-effectiveness of the different scenarios, the cost-per-life-saved (CPLS) of each scenario was computed and is shown in Fig. 7. These results indicate that the CPLS can vary by five orders of magnitude, or more precisely, from $1000 to close to $100 million. The initial 10% of the expenditures eliminated 99%

Fig. 5. Residual risk versus remediation cost for various PAT scenarios involving 0, 2, 4, 6, 8, 10, 15, and 20 years of pump and treat.

of the total expected cases of cancer while the remaining 90% of the cleanup cost achieved virtually no human health risk reduction. In effect, the bulk of the cleanup resources are used to eliminate the residual health risk and these results are in agreement with the results of Viscusi et al. (1997) observed from data from 15 Superfund sites (see Fig. 8). The question now is what is the most appropriate remediation alternative and how this decision should be made. The potential decision criteria may be, but not restricted to, the total cost, residual health risk, risk reduction, and/or CPLS. Despite the fact that each of these decision criteria seems attractive immediately, there is no consistent approach for the decision-making process. One may argue that the decision should be based purely on the residual risk using the 10
4 to 10
6 range advocated by the US EPA. In this example, the risk of 10
4 corresponds to a remediation cost of $1.7 million that produced a reduction of 99.2% of the risk at a CPLS of less than 1000:Ontheoth erhand; ariskof 106producedaremediationcostof 4.8 million that corresponds to a reduction of 99.99% risk at a CPLS of $10 million. These results clearly show that these decisionrelevant values are substantially far apart causing decisionmaking difficult and ambiguous. The earlier discussion of this manuscript discussed that many of these ‘‘fuzzy’’ values proposed by the US EPA in similar settings have no clear

Fig. 7. Cost-per-life-saved versus remediation cost from data from 15 Superfund sites (Viscusi et al., 1997).

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Fig. 8. Cost-effectiveness of asbestos regulations issued by US EPA (from Van Houtven and Cropper, 1996).

scientific basis and cannot sometimes be justified nor defended in a court of law. On the other hand, the polluter as well as other stakeholders such as state and local agencies with limited resources may be hesitant to invest public funds to reduce the health risk by 99% or more at a CPLS of more than $2 million. In such a political environment, the decision may be biased to reduce the risk ‘‘substantially’’ while not exceeding the CPLS by the potential cost that the polluter may have to bear in an actual situation of affecting the public health due to this contamination event. The simple numerical example described here is not perfect and has many limitations since the problem did not address hydrogeologic uncertainty, population variability, sophisticated remediation technologies that may be able to reduce remediation time and cost, and more complex

contamination scenarios involving the vadose zone, fractured media or dense non-aqueous phase liquids. Despite these limitations, the qualitative nature of the results and the decision-relevant questions produced by this demonstration example are still valid, persistent, and continue to remain unanswered in most large-scale contaminated sites. It is reasonable to argue that success has been achieved in major cleanup efforts over the past years where there are formal closures of sites and aquifers that have been brought up to drinking water standards. The answer to that argument as well as the point of this discussion is not that some hazardous waste sites are not adequately cleaned up from existing technologies, but to what level should the cleanup be performed such that the eventual effort is cost-effective within the available resources without increasing public health risk.

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5. Challenges to the existing framework 5.1. Need for a decision analysis methodology It is generally believed that if the results of a scientific analysis of a management problem are difficult to interpret and use in the decision-making process, decision-makers will often rely on other, mostly non-technical, criteria to make the decisions. Examples of these non-technical criteria are environmental guidance and regulations (where arbitrary safety factors are often built into the regulatory standards), social considerations, political influence, and unaccountable costs. Complete reliance on non-technical criteria for decision-making can generate too conservative and costly decisions that may or may not reflect the reality and risks. To overcome this limitation, the presence of a structured and uniform decision process is important to guarantee rational decisions. The structured decision process should evolve around a decision analysis methodology that makes use of the scientific analysis of the different aspects of the problem. This decision analysis methodology should provide the decision-maker with a noncomplex, but deep insight into the technical and non-technical issues of the problem. The results from the previous numerical experiment clearly showed that there is no consistent and scientific decision analysis methodology currently available in environmental management of hazardous waste sites. Our understanding of physical, chemical, and biological processes and conceptualization of different site-specific scenarios, site characterization techniques including improved monitoring techniques, remediation technologies, and mathematical tools and computation resources to simulate field conditions have matured substantially over the past few decades due to the strong commitment from researchers and regulators. However, the area of risk-based decision analysis in hazardous waste management is still at its infancy and important decision are still made on the basis of unjustifiable conservative design factors, lack of consideration for costeffectiveness, or using non-justifiable soft data. 5.2. Balancing risk reduction and cost Traditionally, public and private investments are justified by evaluating the benefit/cost ratio or a rate of return. However, projects related to public health and safety, for example dam safety projects, seldom fair well in such evaluations because the probability of risk is often small and thus the expected benefits are small relative to the investment of capital and maintenance funds (Bowles et al., 1997). Yet, the benefit/cost ratio could be increased by adding a value of saving a statistical human life or the value of avoiding an adverse health effect to the assessment of benefits. However, this would raise serious ethical and moral issues relating to the worth of a human life. Moreover, the value of a lost human life, which is subjected to involuntary exposure of risk, is subject to inconsistent

estimates by economists, thus making the comparison even more difficult (Sharefkin et al., 1994). Bowles and coworkers (1997) found that a useful approach for considering the benefits of increased public safety in dam risk assessment is to evaluate the cost-effectiveness of each alternative. The cost-per-life-saved (CPLS) for each alternative is calculated, and then compared with similar costs for other existing facilities that expose the public to risk of life loss. By pursuing alternatives with cost-per-life-saved that are similar to or less than those in other fields, an owner is at least being consistent with the extent to which other areas are investing in public safety (public communication with David Bowles, Utah State University). Following the same reasoning, remediation costs may be justified only if their cost-effectiveness, in terms of cost per cancer case avoided or simply CPLS, is comparable to the cost-effectiveness of similar projects. In fact, this approach of evaluating cost-effectiveness as a measure for justifying expenditures in general public safety is used extensively by the government. Government agencies used this approach to justify different regulations that are related to public health and safety measures despite the fact that most of these evaluations are made implicitly. An insight into the manner of how the US EPA banned some asbestos products under the Toxic Substance Control Act (TSCA) is shown in Fig. 8. The data reveal that the existing regulations could be economically justified in almost 85% of the cases (Van Houtven and Cropper, 1996). An implicit value of $43 million for a single statistical life-saved was established as a cutoff value beyond which banning is considered unjustified in spite of the fact that a cancer risk exists. However, the basis on which this cutoff value is established, which is 10 times higher than a typical civil jury award in cases of workplace accidents resulting in death or permanent disability, is not clear. Economically unjustified asbestos products have a high cost-per-life-saved compared to the cutoff value, but additional justifications may exist for their banning; for example, the actual cost of banning might be small, the banning might have taken place under public pressure as a result of adverse publicity, the risk is for a small group, e.g., workers, might have been high, or unspecific political constraints. Nevertheless, the point that can be established here is that economic effectiveness expressed as CPLS is an important consideration in justifying the investment of resources in public health and safety projects. The major drawback of the CPLS approach is the inconsistency in defining a value for a given scenario or product (Arrow et al., 1996). For example, consider the CPLS values established by the US EPA under various environmental regulations and shown in Table 3. The data clearly show that there is a wide variation of the values of CPLS in the order of several hundred thousands to several trillions of dollars. This large variation indicates the existence of non-specific criteria, in addition to the cost-effectiveness, that affect health and safety.

I. Khadam, J.J. Kaluarachchi / Environment International 29 (2003) 503–519 Table 3 Values of CPLS established by US EPA in various environmental regulations (from the US Office of Management and Budget, fiscal year 1992) Regulation

CPLS ($M)

Trihalomethane drinking water standards Standards for radionuclide in uranium mines Benzene NESHAP (original: fugitive emissions) Ethylene dibromide drinking water standard Benzene NESHAP (revised: coke by products) Arsenic emission standards for glass plants Arsenic/copper NESHAP Hazardous waste listing for petroleum refining sludge Cover/move uranium mill tailings (inactive sites) Benzene NESHAP (revised: transfer operations) Cover/move uranium mill tailings (active sites) Benzene NESHAP (revised: waste operations) Dichloropropane drinking water standard Hazardous waste land disposal ban (first and third) Municipal solid waste landfill standards (proposed) Trazine/alachlor drinking water standard Hazardous waste listing for wood preserving chemicals

0.2 3.4 3.4 5.7 6.1 13.5 23 27.6 31.7 32.9 45 168 653 4190 19,107 92,069 5,700,000

The other limiting criteria are the extent to which one should invest in public health and safety and this dilemma can best be explained by considering the vinyl chloride case in 1987. In this legal case, the Natural Resources Defense Council litigated the softness of the National Emission Standard for Hazardous Air Pollutants applicable to the MCL of vinyl chloride issued by the US EPA. The council considered that the MCL described in the standard is high compared to the non-observable adverse effects defined using appropriate safety factors. Thus, as the council alleged, the standard would place a high risk of developing cancer on exposed individuals. The US EPA defended its regulation indicating that the level is the best that can be achieved from existing technology and that enforcement of a lower MCL is non-feasible and can result in high costs that cannot be justified. However, the US Court of Appeals for the District of Columbia ruled that the US EPA had improperly considered the costs in setting the standard. The US EPA was directed to consider costs and technological feasibility only after an ‘‘acceptable risk’’ level had been established (Van Houtven and Cropper, 1996). On the other hand, cost-effectiveness and technology feasibility cannot justify actions to reduce risk unless it is a ‘‘significant risk.’’ In 1980, the Occupational Safety and Health Administration (OSHA) promulgated a rule in which the standard for any carcinogen was to be lowered to the extent of being technologically and economically feasible. Nevertheless, in a 1980 decision, the Supreme Court vacated the rule that established a standard for exposure to benzene based on statutory interpretation. The court stated that an agency had to make a finding that the risk was ‘‘significant’’ before the agency could consider regulating the chemical (Byrd and Lave, 1987). Due to subsurface complexity and the large extent of contamination in most sites, the task of ground water

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restoration can be, in many situations, practically impossible. The estimated time for some highly complex sites can amount to decades or centuries of active remediation. Under such circumstances, a legal issue arises about the extent of action that should be taken after understanding the infeasibility of cleanup. The question then remains hard to answer; i.e., do infeasibility, high cost, and lack of cost-ineffectiveness warrant no action to reduce the risk in such situations of subsurface contamination? 5.3. Individual risk and population risk Certainly, the risk to an individual is the major consideration in public health and safety regulations and actions. However, this risk falls between two soft terms called ‘‘significant’’ and ‘‘acceptable’’ risks for which no exact numerical definitions exist. A range of risk values that ranges between 10
3 and 10
7, i.e., the probability of death due to a disease and being struck by lightning, respectively, is encountered frequently in the risk literature. A major drawback of the individual risk estimate is that this estimate does not indicate the degree of risk on the exposed population. The size of the population can affect how much risk an individual in the population can tolerate. For a large population, even small individual risk can result in significant consequences whereas a small population can tolerate a higher individual risk. In fact, the individual risk alone cannot establish a criterion for health and safety measures; instead, the population risk is needed and always used to balance the individual risk criterion. Travis and Richter (1987) reviewed the existing cancer risk data to investigate regulatory decisions concerning carcinogenic substances. They revealed that the key to understanding regulatory practices is in the relationship between the individual lifetime risk and population risk. The data used by several regulatory agencies suggest that for a small population risk, such as fewer than 10
1 cancer deaths per year in the exposed population, regulatory action is seldom taken if the individual lifetime risk is less than about 10
4. As the population risk approaches 250 cancer deaths per year such as in the case of the US population, the tolerable individual risk drops to 10
6. The formulation of these findings is presented in Table 4. The first range corresponds to the high risk that is posed on a small population, e.g., risk in the workplace, and the last range Table 4 Relationship between individual risk and population risk in decisionmaking (from Travis and Richter, 1987)

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corresponds to the risk posed on a large population, e.g., risk in large metropolitan centers.

6. Risk-based decision analysis in other fields Since risk-based decision analysis is in its infancy in the area of subsurface remediation, it is important to improve our knowledge on this subject through work carried out in other disciplines that invest in public health and safety. A literature review conducted on decision analysis work carried out by other disciplines showed that a substantial knowledge base exists in dam safety, nuclear, and utility industries. The next section will focus on the advances made by these industries to address public risk in public investment projects in a cost-economic manner. The discussion will emphasize the formulation of the problem, the structure of the management framework, and the decision analysis methodology. 6.1. Dam safety Risk management for dam safety is one of the fields where risk-based decision analysis has witnessed considerable development and contributions in recent years. The approach used by this industry has become the standard of management practices in many countries, e.g., US, Canada, UK, and Australia (Bowles, 2001). Here, the risk assessment and risk treatment (or reduction) are combined to form the management framework. Risk assessment comprises risk analysis and risk evaluation. Risk analysis involves both risk identification and risk estimation. Risk identification is the process of recognizing the plausible failure modes for a dam. Risk estimation is the process of quantifying probabilities and consequences of the failure modes. The process of examining and judging the significance of risk is termed risk evaluation, which typically involves the consideration of tolerable risk criteria, and a range of other economic factors (Bowles et al., 1998). The management framework is organized in a three-tier hierarchy. The first tier is to ensure that the current engineering conditions of the dam satisfy the latest requirements of regulatory and engineering standards. The second tier is to ensure through risk assessment that current conditions of the dam satisfies risk-based criteria, for both life safety and economic/financial considerations. The third tier requires the evaluation of economic-based criteria to justify and prioritize repairs to the dam if found necessary in the second tier. The risk-based criteria describe the tolerable risk levels for life loss and economic/financial risks. The life loss criteria have two considerations, the average population risk (or the societal risk), and the maximum risk posed on any individual in the population (or the individual risk). Typically, life-loss criteria define upper and lower bounds for societal and individual risks. The upper bound is the

maximum acceptable risk, while the lower bound is the limit for trivial risk, below which risk is not of concern. There are a number of life-safety decision criteria that are being enforced around the world, e.g., Australian National Committee on Large Dams (ANCOLD, 1998), US Bureau of Reclamation (USBR, 1997), and British Columbia Hydro (BC Hydro, 1993) (Bowles, 2001). The other important considerations in the risk-based criteria are the economic and financial risks and damages. Generally, the dam owner/operator will decide whether these economic/financial risks are acceptable or not. However, there exists some regulator guidelines to evaluate the significance of economic risks, e.g., New South Wales Total Asset Management Risk Matrix (Bowles, 2001). This risk matrix rates the economic risk as major, medium, or low risk. The major risk recommends immediate actions to control and reduce these risks, while low risk recommends the evaluation of economic considerations to decide if management actions are justified. In case the evaluation of the risk-based decision criteria recommends risk reduction and control measures, these measures should be justified economically, phased, and prioritized based on economic efficiency. In order to select from the alternative plans for risk reduction, or to prioritize a single-plan element, economic criteria are employed. These criteria include the benefit/cost ratio, which is the commonly used parameter, the cost-effectiveness of risk reduction, which applies to life loss and economic damages, the net present value, and the internal rate of return. In case of low risks, dam repairs can be carried out only if they can be economically justified. Economic justification is achieved by applying the principle of ‘‘as low as reasonably practicable’’ (ALARP), and the ‘‘de minimis risk’’ principle (Bowles, 2001). The ALARP principle states that risk should be reduced continuously until it reaches a level where it is no longer cost-effective to reduce the risk any further. The decision as to when it is no longer cost-effective is a subjective judgment that is usually made by comparing published costs for risk reduction in similar public safety projects. The term, de minimis, comes from the Latin, ‘‘de minimis non curatlex,’’ meaning that the law does not concern itself with trifles (Travis and Richter, 1987). In the dam safety context, ‘‘de minimis risk’’ means that a dam owner may have a legal obligation to implement a relatively low-cost fix (risk-reduction measure), even if it is not cost-effective (Bowles et al., 1998). The strength of de minimis risk justification is related to the capital costs of risk-reduction measures, but it can be expected to vary with the resources available to different dam owners and to operator willingness to avoid risk. 6.2. Utility and nuclear industries Nuclear and electrical utilities face decisions that have considerable impacts on the environment and human health.

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The impacts stem from the by-products, processes, equipment, and different hazardous waste, including nuclear waste used by the industry. These potential impacts require the use of risk-based decision analysis to evaluate costeffective measures needed to overcome specific scenarios. In addition, emphasis on the use of risk management has increased because damages to health and the environment caused by measures that are due to lack of compliance with regulatory standards are no longer defendable in the legal system (Balson et al., 1992). The remaining discussion is based on the management practices at BC Hydro (Keeney and McDaniels, 1992), and the US Department of Energy Richard Operations Office overseeing the Hanford nuclear site (Hesser and Mosely, 1995). The management objective in the context of the utility industry is to control health and environmental risks to reduce economic risks. Due to the strictly regulated decision environment, risk is being applied in the utility and nuclear industries more often than any other fields. It is an important part of any operational decision such as replacement of an electrical generator, transport of a chemical, or storage of waste. Decision analysis in the utility and nuclear industries is performed in three stages; risk assessment, risk management, and risk communication (Balson et al., 1992). Risk assessment involves the identification and evaluation of potential health and environmental risks caused by different proposed or existing practices. In the case of a significant risk, management alternatives are defined and analyzed to ensure compliance with management objectives, including risk reduction. Risk management involves the evaluation of the proposed alternatives to produce a ranking of these alternatives, or a prioritization of the plan elements. Communication of risk to involved parties is usually integrated in the risk management stage. All involved parties, public, regulatory, and stakeholders, are informed about the current risk levels, their significance, and proposed plans to manage these risks. The input from these parties through risk communication directly affects the management choices and decisions. Due to the complex decision environments present in these industries where multiple objectives need to be satisfied, decision analysis is usually performed using the multi-attribute theory. A typical set of decision objectives may include ensuring public safety, ensuring worker safety, complying with regulations, conducting cost-effective operations, and developing stakeholder and public confidence. In order to satisfy these objectives, a scoring system is used. This scoring system assigns weights to each objective based on a value eliciting process. The value eliciting process ranks the management objectives and assigns relative weights to indicate the importance of different objectives. The value eliciting process also provides a weight for the risk attitude of the decision-maker. Once the scoring system is set and approved, it is used to calculate the utility of different decision alternatives, which are subsequently ranked.

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It should be mentioned that the RCB analysis is central to the decision-making process in the utility industry. The quantified costs and benefits of a proposed plan, in addition to the risks of failure, are used to calculate the net benefit resulting from the plan. This net benefit is then considered as one of the major criteria when setting scores for that proposed plan.

7. Opportunities to improve the existing framework Previous discussions clearly showed that industries such as dam construction and management, utility and nuclear power, among many others not discussed here, have applied comprehensive decision analysis methodologies to address public risk and cost-effectiveness in projects related to public safety and utilities. The previous discussion distinguished two different frameworks for risk-based decision analysis; i.e., the structured explicit decision analysis (SEDA) illustrated in Fig. 9, in the case of dam safety, and the implicit multi-criteria decision analysis (IMDA) illustrated in Fig. 10, in the case of the utility and nuclear industries. The SEDA framework develops consistency to a complex decision problem through simplification. The major decision objectives and goals, which are summarized in regulatory compliance, risk control, and cost-effectiveness, are used to structure the process. The structured process needs to: (a) satisfy regulatory standards, (b) identify actions and measures to control life-loss and economic risks, and (c) evaluate costs and cost-effectiveness to justify, rank, select, and prioritize actions. Since no ‘‘bright lines’’ exist that describe how much safe is safe, and how much costly is costly, such as in engineering standards, the process is centered on professional judgment and experience of the decision-makers. Thus, the decision analysis process requires an explicit analysis of each decision criterion based on case-specific considerations. The IMDA framework is aimed at formalizing the decision analysis process to reduce the bias. The decision process requires the identification of the decision criteria relevant to the problem in hand, and the specification of the relative importance of the criteria by means of value eliciting from managers or stakeholders. Once this information is in place, decision alternatives are scored against the decision criteria and then ranked based on the multi-attribute theory, which is an implicit evaluation of the desirability of each alternative based on the decision criteria. Although the ranking process described for the BC Hydro and Hanford nuclear site uses the additive weighted criteria method, there exists different schemes for ranking alternatives given a certain criteria order of importance. Commonly used ranking schemes are fuzzy logic and those using heuristic methods. Although the decision environments in subsurface contamination, dam safety, and the utility and nuclear industries have the common goal of reducing human

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Fig. 9. Structured explicit decision analysis approach.

health risk and eventual life loss, there exist also some important differences in the decision environment. One of these differences is the extent of regulatory involvement in the decision-making process. It is well known that the nuclear and utility industries are strictly regulated in terms of facility location, design, and operation. This strict oversight is opposed to the practice in dam operations where the dam owner/operator has more flexibility in the decision-making. On the other hand, regulatory involvement in the operation of hazardous waste sites is probably the least strict compared to other public utility industries. Another important distinction is in the nature of the decision problem; subsurface contamination issues have corrective actions and the problem is apparent after the failure of the system. On the other hand, the decision problem in dam safety or in the utility industry is focused on prevention and there is little to no remedial measures after a failure. Another important difference is the presence of the economic risk, which is an important factor in dam safety and the utility and nuclear industries, compared to hazardous waste sites. Economic risk represents the risk of loss of benefits or opportunity, which is an additional dimension to the problem. Finally, the post-

failure consequences are sudden and cause higher public emotional backlash and anger in the case of dam projects and the utility industry whereas the opposite is true with hazardous waste sites. Hence, the public pressure, to invest more on public safety and health and strict regulatory oversight, is typically higher in the utility industry and dam projects compared to hazardous waste storing facilities. In light of the previous discussions, we believe that there are many opportunities to improve the existing framework of decision-making at hazardous waste contaminated sites. The SEDA and the IMDA approaches, which are notably successful in dam safety and the utility and nuclear industries, are candidate methodologies despite the apparent dissimilarities in the decision environments. However, in order to formulate a new decision analysis framework for subsurface contamination problems, a few important issues need to be addressed in detail. One of the important issues is the reformulation of the decision problem to acknowledge the multi-objective nature of the problem rather than the current formulation as a risk cost –benefit problem. The redefinition of acceptable and trivial risk to incorporate both individual and population risk is also an important issue to

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Fig. 10. Implicit multi-criteria decision analysis approach (Wenger and Rong, 1987).

be resolved. Finally, the trade-offs between the risk reduction and the associated costs need to be recognized and appropriately addressed.

8. Conclusions Decision-making in subsurface contamination scenarios requires solving a puzzle of interconnected issues consisting of technical concerns of a quantitative nature and qualitative issues that are typically politically biased. In decisionmaking, trade-offs should be made between economic considerations, legal liabilities, technical feasibility, hydrological complexity, uncertainty of the extent of harm to the public and the environment, and finally the ethical considerations and commitments to society’s welfare. The most urgent and important challenge to decision analysis in subsurface contamination management is how to balance human health risk and the high cost of risk control measures. A sound risk-based decision analysis methodology should include the cost-effectiveness of each measure as a justification for implementation. The actual cost of the measures and feasibility should be considered, and the balance between cost and acceptable risk should be maintained. Finally, the relation between the size of the exposed population and individual risk should be considered.

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