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Valuation of market uncertainties for contaminated land/Rinkos netikrumo vertinimas uzterstu sklypu atveju.


Potential investors are reluctant to reuse contaminated land due to the diversity of perceived risks. Occasionally they demand that all pollution should be removed from a site contrary to the statements of environmental experts that residual contamination of the site would by adequate for the intended future use. Considerable value diminutions for actual or potential contamination from previous use (soil or groundwater pollution, warfare agents, listed buildings etc.) severely impair the marketability of derelict land. These reductions depend not so much on the (level of) expected rehabilitation costs but rather on their uncertainty and remaining stigma effects. If such brownfields are to be merchantable and, particularly, contaminated properties reactivated, a transparent value appraisal for these uncertainties is vital.

Whereas in decision theory risk is defined as a state of complete probabilistic knowledge, in practice, the valuation of contaminated sites is characterised by heterogeneous sources of often incomplete information and thus only partial probabilistic knowledge, i.e. uncertainty. Contaminated sites are characterised by uncertainties influencing the assessment of remediation costs due to the variability in soil physics and the complexity of the contamination in the subsurface (Norrman, 2001; NRC, 2005). Behind this background, assessing the market value remains challenging as the remediation to meet specific cleanup goals might be incomplete and some pollution goes undetected due to inaccurate investigation modelling and technologies. Moreover, some substances in the ground may not be known as pollutants at the time of the investigation but are discovered later. Resultantly, market reluctance occurs due to perceived liability, insurability and marketability risks (Bartke, 2010).

Adams et al. (1985) and Beattie (1990) already found that the appraisal of contaminated land is one of the most vexed issues in the valuation of regeneration projects and that there are shortcomings in traditional valuation methodologies. Since the 1990s, a number of papers have dealt with the valuation of contaminated properties. At the same time, The European Group of Valuers' Associations (TEGoVA) has recognized the appraisal of contaminated land as a key subject for future research (Adair et al., 2001). As Weber et al. (2008) note, scientific processes need to be established for valuers. Nevertheless and despite acceptance of elements of a general valuation framework (cf. below USPAP, AO9), no generally accepted and practicable method has so far been found for evaluating market uncertainties for contaminated land.

In the following, the article introduces the relevant international valuation standards and gives a survey of expert valuation concepts proposed in the literature for sites polluted by previous use. As a next step, a synopsis of the main categories of uncertainties driving market perceived risks is provided. Based on a literature review and a poll of German professional appraisers, it is shown how determinants of value diminutions can be better understood and integrated into a simple valuation system for risk assessment in property valuation. The proposed method has been applied in a case study approach. Based on these results, final conclusions will be drawn.


The concept of contaminated sites has no uniform definition in the various scientific disciplines and national environmental and soil protection laws (cf. Dasgupta and Tam, 2009). Following Hilse and Bischoff (2005), this paper refers to contamination in the sense of pollution due to previous use, including all characteristics of a property (built on or not) deriving from local use in the past and coming under the value-related scope of inter-/national environmental law and/or sections of other technical legislation pertaining to the environment.

The United States have a generally accepted framework for analyzing issues pertinent to the appraisal of contaminated sites that include definitions of contamination, property value diminution, environmental stigma and many others. They are laid down in the Appraisal Opinion (AO 9) by the Uniform Standards of Professional Appraisal Practice--USPAP (Appraisal Foundation, 2008) and discussed by Appraisal Institute (2008) and among others by Jackson (2003a, 2010). International guidelines for appraisers, i.e. norms set next to USPAP by the International Valuation Standards--IVS (IVSC, 2007), European Valuation Standards--EVS (TEGoVA, 2009) and the Royal Institute of Chartered Surveyors Valuation Standards (known as the Red Book) (RICS, 2008), touch the problem without specifying methods how to assess uncertainties influencing the marketers' behavior (cf. USPAP AO9, IVS GN7).

The basic procedure for the valuation of brownfields is a residual value approach where expected rehabilitation costs calculated by independent environmental experts are deducted from the value of a comparable uncontaminated site (Sheard, 1992) further taking into account use and risk effects (cf. USPAP AO 9). According to Chalmers and Jackson (1996) and Woestmann et al. (2011), the determination of environment-specific estimations and problems should be left to environmental engineers (costs) and attorneys (liabilities) separated from appraisal as such. However, in practise valuation reports do not pay enough attention to risks resulting from previous use, even though international appraisal standards invariably demand that all value-related information of a site should be considered when establishing market values.

Neglect for previous pollution in determining market values is due not only to a lack of market data for appraisal but often to terminological differences between appraisers and environmental specialists whose judgments are frequently based on disparate or even contradictory concepts. If not given concrete instructions, for example, environmental experts looking at contamination merely in terms of hazard defence as codified in the national soil protection laws will derive rehabilitation costs without allowing for intended use. Though in economic terms, the most probable highest and best use (EVS1 5.4.2., IVSC, 2007, 28) should be assumed when determining market values.

In practice despite rising awareness amongst appraisers of new technologies of decontamination, a lack of environmental know-how among appraisers, missing market data and uncertain estimates for rehabilitation costs often prevent costing for cleanups and follow-up with a precision required to determine market values. As a result, (previous) contamination is often seen as a technicality (left aside or taken care of by special assumptions) or there are merely verbal qualifications or pure subjective increments (cf. Grossmann et al., 2001; Kinnard et al., 2002; Chan, 2009; Moser, 2009). Sometimes, appraisers apply a general non-specified lump-sum deduction for so-called stigma effects in order to take into account risks perceived by market participants.

A poll of German appraisers gave evidence that transparent and easy to use methods are missing to assess the value diminution due to perceived risks of contaminated sites.


The rehabilitation and reuse of contaminated land carries many risks that are influencing market participants' perceptions on what is the fair market value of such a site. Marketing risks have been studied in the United States since the 1980s, with Patchin (1988) being among the first to develop a framework for appraising contaminated sites. Apart from rehabilitation costs for hazard defence, his valuation concept includes possible litigation expenses, exemptions from liability, financing costs and stigma effects as adjusted risk premiums. Higher risk premiums, in this approach, reflect the difficult marketing conditions for contaminated areas. Patchin also points to the potentially lower marketability of a property after rehabilitation, the so-called stigma effect from a history of contamination. In another study, Patchin (1991) takes a closer look at the cost risks exceeding rehabilitation expense and detracting from the value of (suspected) contaminated sites. He points out that these perceived cost risks need not be rational in order to reduce value. He identifies several determinants that constitute stigmatization: a fear of more claims being made by the state or the public, unwillingness of market third parties to provide mortgages or other financing instruments, and a fear of hidden or underrated rehabilitation costs. These factors affect the market value and marketability prior to the complete rehabilitation and cause buyer resistance and value reduction, even thereafter. Compared with a greenfield site, an investor would have to carry extra burdens from the organization, execution and monitoring of rehabilitation work, which Patchin (1991) refers to as trouble factors.

Mundy (1992a) studies contradictions between actual risks and those perceived by marketers in relation to polluted sites. He depicts that value reductions of a (previously) contaminated property exceeding the difference between the value of a non-polluted site used for comparison and the actual rehabilitation costs, i.e. stigma, are directly related to the level of uncertainty and subjectively perceived risks of (former) contamination. In addition, this stigma effect depends on the scope of information on contamination and rehabilitation available to marketers, which eventually lessened stigma as rehabilitation proceeded.

Chalmers and Roehr (1993) take up Mundy's argument that risk premiums are related to information and outline the dependence on the progress of investigation and remediation. Similar to Patchin (1991), they emphasize that marketers propose markdowns from their perception of risks rather than the actual pollution load. Hence, the extent of risk awareness depends on the perception of changes (better physical condition of the property, cleanup completed) in the rehabilitation process (cf. McClelland et al., 1990; and Slovic et al., 1991), but also on positive or negative media reporting about progress made in reclamation (Siemens, 2003). Chalmers and Roehr (1993, 33) therefore define stigma as "the reduction in value caused by contamination resulting from the increased risk associated with the contaminated property". Syms (1997, 179) lists determinants of value reduction and defines stigma as "that part of any diminution in value attributable to the existence of land contamination, whether treated or not, which exceeds the costs attributable to a) the remediation of the subject property, b) the prevention of future contamination, c) any known penalties or civil liabilities, d) insurance, and e) future monitoring."

Several approaches have been proposed as methods of valuation appropriate to assess contaminated market value diminution. Jackson (2003b) presents a range of possible valuation techniques and methods (cf. also Tonin, 2006; Simons and Sementelli, 2006), including comparative purchase price analysis (cf. Patch-in, 1994; Sym and Weber, 2003), multiple regression analysis which may be used to define the strength and significance of purchase price determining factors (cf. also Dotzour, 1997), or the surveying of market participants to collect and understand data which is important to the valuation as such (cf. also Greenberg and Huges, 1993; and McLean and Mundy, 1998a). In Jackson (2004a), the author also discusses analyses of case studies, emphasizing the need for using a variety of procedures for evaluation and for relying on market data where possible. Further methods for valuation were proposed such as option pricing methods (Lentz and Tse, 1995), mortgage-equity analysis (Chalmers and Jackson, 1996), adjusting all-risk-yield and by percent value reduction (Richards, 1997), Monte-Carlo-Simulation (Weber, 1997), a science-based integrated Triad approach (Weber et al., 2008) or fuzzy real options (Wang et al., 2009). Syms (1997) introduces a risk assessment model for the assessment of stigma attached to the past or present industrial use of a site. This risk assessment is based on the observed range of stigma by Patchin (1994) and adjusts this for a specific site by a scoring of the relevant professionally perceived riskiness out of 26 industrial activities, and, based on empirical research, for the perceived impacts on value before and after redevelopment as well as due to the chosen method of treatment. However, the methods proposed require extensive data collection and evaluation which, in practice, is often impossible due to time constraints and cost limitations.

A large number of empirical studies in the literature use market data to explore whether previous contamination has an effect on prices and, if this is the case, whether these effects are related to the remediation progress. Another aspect are the implications of the general market situation (real estate boom/ slump) on these effects (for this and a detailed list of literature see Jackson, 2001a, 2002; Hurd, 2002; and Longo and Alberini, 2005). In contrast to residential properties, less real estate data is available for industrial sites that could be used for market price studies so that mostly individual cases have been analyzed in the past. Jackson (2001b), for example, conducts a metaanalysis of seven case studies and in each significant value reductions for industrial properties are found, as reflected in reduced marketability and less willingness to finance on the part of lenders, however, the author found no evidence of post-remediation stigma. The literature on detrimental conditions affecting industrial properties in general supports the view that stigma effects are temporary and values recover following remediation.

In the last decade, controversial discussions increasingly focused on enhancing the appraisers' capabilities to assess marketability risks through methodologies such as sample surveys and market interviews (e.g. Jackson, 2004b) or approaches of stated preferences, such as contingent valuation (e.g. McLean and Mundy, 1998b; Wilson, 2006; Frey and Roddewig, 2006). In general, these methods are helpful for providing background to understanding the possible impacts of contamination, but typically they are not seen as methods to determining actual market behavior and market values, which should be based on data of actual transactions (cf. Jackson, 2003b)--whenever available. Nevertheless, a growing literature is using these techniques to broaden the understanding of determinants and assess marketability risks.

Table 1 summarizes a number of studies into the effects of risks related to pollution from previous use on the market value of (formerly) contaminated sites.


A potential buyer or developer of a site (presumably) polluted by previous use faces a number of detrimental conditions. In the literature (Patchin, 1991; Syms, 1997; Bell, 2008; Kerth and Griendt, 2000; Rodewig, 2002; Bell, 2003; Woestmann et al., 2011) a variety of determinants leading to markdowns are found. These can be stylized to fit into four categories representing different risk dimensions that are often related to uncertainties (i.e. the probability and extent of the risk for value reduction cannot be contained):

1. Risk of liability claims: Under civil law, private claims for damages may be made on the property owner/purchaser while, under public law, the public may demand measures to be taken for hazard defence. This risk exists regardless of the intended use if there was previous soil or groundwater pollution. It thus establishes a duty to redress for the problem owner even if she has no interest in developing the site. Legally, hazard defence requires precautionary action. Costs will particularly accrue under ordinances for hazard investigation and prevention. At the stage of mere suspected contamination, there is a large-scale uncertainty with regard to the risk of liability claims which lessens as authority and, possibly, private claims become more concrete. After rehabilitation and when private claims have been met, the risk is basically zero. However, sites will often carry a residual uncertainty of subsequent and unexpected claims even after rehabilitation, for example if stricter legislation is suspected (cf. Bond et al., 2001) and that further remediation might be required in the future (Weber et al., 2008). Uncertainties with regard to the risk of liability claims will impair marketability (cf. Slutzky and Frey, 2010).

2. Investment risks: The intended use of a site will normally cause extra costs, e.g. for the disposal of polluted but non-hazardous materials and for the excavation of soil for building work. All of them are categorized as site treatment costs. There may also be use-related additional costs for soil remediation in case of particularly sensitive uses such as playgrounds. Burdens not under duty of redress from the viewpoint of hazard defence may still lead to higher and uncertain investment risks if restrictions of use are to be avoided. This risk itself in as much as the uncertainty to quantifying it affects the market value. The expenditure which may be allocated to the planned investment is sometimes referred to as the literal investment cost or "investment risk" (a quantity with uncertainty).

3. Usability risks: Where remediation costs are out of proportion, authorities have to impose additional precautionary measures and restrictions. Value may be particularly reduced by use restrictions, e.g. for playgrounds, green spaces, civil engineering, etc. While such clearly defined restrictions are not an obstacle for the assessment of value, it is quite difficult (and insecure) to determine uncertain future use restrictions at an early stage of revitalization planning.

4. Stigma and marketability risks: Even if all authority requirements for use and private claims are met, properties with a history of contamination will still have a battered image. Potential buyers will be biased against

sites which have been polluted by previous use and harbour fears (often without any objective or legal justification) of hidden risks and uncertainties. In business terms, this widespread empirical phenomenon of stigmatizing contaminated sites leads to long holding periods and/or higher marketing costs and should therefore be calculated as a hard fact when it comes to appraisal and investment. Stigma in this context is understood to be phobia or fear of negative effects or follow-up costs that can cause a diminution of the market value even after a proper site remediation was completed.


It is crucial for understanding and economically assessing these quantities outlined above that at best they are risks. Although the professional appraiser's measurement of value and impacts to value should be made objectively and should always be based on market data (cf. USPAP AO9), these risks are factors which by potential investors and developers usually can only be determined and sometimes have to be subjectively estimated within upper and lower limits (cost margins) or predict actual costs only in a probability distribution. Stigma as phobia and the uncertainties with regard to these quantities therefore add up and may easily be perceived as extreme if they are not addressed and quantified in a transparent way. The value of sites polluted by earlier use may improve considerably when these uncertainties are restricted through better information (quantification), public rehabilitation contracts and private insurance. Objectifying risks and uncertainties in this respect is a central concern of valuation. Thus, European standards point to the appraiser's duty to consider and report any risks, uncertainties, volatilities and other aspects which come to her knowledge and may affect the value determined (EVS4 6.7.).

In the economic valuation of (previously) contaminated sites the amalgam of these uncertainties will influence market behavior and cause a markdown which hereafter is referred to as Mercantile Value Reduction (MVR). The term mercantile is derived from the Latin verb mercari meaning to trade, to market, to do business. It is used to emphasize the market based origin of a value reduction (1) usually associated with stigma and (2) arising from uncertainties in assessing risks associated with contamination as perceived by market participants.

In economics terms, MVR is the difference between the market value of an uncontaminated site and that of a site awaiting rehabilitation, less treatment costs and less rehabilitation costs, including an assessment of above mentioned risks, as estimated by an environmental expert. It will invariably be greater than the appraised property stigma or risk effect as set in USPAP AO9 (cf. Jackson, 2010) because it makes allowance for uncertain rehabilitation, treatment, marketability costs and usability risks. The effect of MVR on the market value of sites polluted by previous use is illustrated in Figure 1.


The amount of MVR depends on the level of information for the assessment of rehabilitation, treatment and marketability costs. It shrinks as this level rises but certainly not goes down to zero as psychological effects of stigma from the history of contamination often persist even after when rehabilitation is completed. In principle, levels of information and experience rise as rehabilitation and reuse proceed so that there is less uncertainty regarding value reduction from undetermined costs. Mercantile value reduction, then, invariably drops over time. Chalmers and Jackson (1996), just like Roddewig (1996), introduced this so-called life cycle hypothesis. It claims that risks caused by contamination are greatest prior to rehabilitation, decrease during site treatment and lessen even further after the end of remediation. Dale et al. (1999) empirically confirmed this life cycle hypothesis. All of these authors conceive these time conditions as pricing/explanatory determinants of market value.

Figure 2 shows the elements of MVR as a function of time and respective information levels, with the funnel shape indicating greater certainty in defining risk components. It is assumed that this is the average development for (formerly) polluted properties.

If an approach to assess MVR was to be adopted by appraisers, it would go a long way towards improving transparency, clarifying and demarcating risk structures and (thus) limiting value reductions on contaminated sites. What is missing so far--similar to other appraisal methods proposed in the literature or elsewhere--is a transparent procedure for determining and assessing those uncertainties. This is where the risk assessment method for mercantile value reduction comes in.


The literature on valuation has not come up with simple methods of quantifying market-related value deductions for risks or stigma effects so far. Most proposals for determining risk-oriented value reductions call for the market resistance to be identified via specific comparative values (cf. Syms and Weber, 2003; Jackson, 2010). Thus, according to Bell (2003), estimated "stigma effects" on market values should be "supported by actual market case studies or data" (ibid. 1510). However, such data is not readily available or cannot be gathered by appraisal experts due to financial or temporal constraints. Moreover, Weber et al. (2008) emphasize that the uniqueness of environmental risk due to site the specific heterogeneous nature of subsurfaces is vulnerable to comparison as an approach to valuation. Caveats need to be considered when using case studies to estimate stigma and its resultant loss in value. The authors note that only assuming that sites have been polluted with the same type of contaminant possessing equivalent risk does justify a sales comparison approach to value, but "the heterogeneity of the soil in the subsurface results in unique problems, so comparisons (comparables) are not valid" (ibid, 14).


The method proposed here combines

1) the requirement made by Bell, Jackson and others to incorporate market knowledge and data as far as possible,

2) the concept of expert polls to identify and understand the effect and size of value reductions as applied by Syms (1997) (cf. also Bond and Kennedy, 2000; Kinnard et al., 2002 for examples of expert polling), and

3) the findings from the literature on the determinants of value diminutions of (previously) polluted sites.

The aim is to provide a practicable and easy-to-use tool which blends general market data/experience and specific property features in determining the particular Mercantile Value Reduction (MVR) of a property being appraised.

In line with Crocoll et al. (2007), Moser (2009) and Syms (2010), the separate determination of a market-related reduction at the end of a conventional appraisal procedure is recommended as best suited for the transparent quantification of risks and uncertainties. This summary reduction is equivalent to MVR and, in appraisal terms, equals the difference between the market value of a non-contaminated site and that of a comparable property awaiting cleanup, less rehabilitation and treatment costs estimated on the basis of good practice taking into account highest and best use. At any time, this comprises the uncertainties that remain even after cleanup and, possibly, during follow-up use (i.e. stigma, marketability and liability uncertainties). The combined valuation of cost uncertainties before, during and from rehabilitation and of the marketing of contaminated sites is typical for the concept of Mercantile Value Reduction.


This clear definition of the concept is necessary for a uniform, objective and comprehensive approach of value reductions for sites polluted by previous use, and therefore is the first and most important step for the risk assessment method developed here (Figure 3).

Factors which normally affect the amount of value reduction are established from the literature review and a number of technical discussions and workshops. Semi-structured individual interviews addressing the issues filtered out from the literature survey were conducted on a face-to-face basis with eight sworn appraisers active in the valuation of real estate and remediation cost assessment, selected for their proven expertise in these disciplines. In spring 2008, a questionnaire based on the interviews was designed for a major survey among German professional appraisers to review the valuation methods employed in the appraisal of (previously) contaminated sites and to collect the average extent and determinants of the type and scope to establish stigma and market reluctance basic to MVR assessment based on the surveyed professional appraisers' observations of average market transactions of sites actually or previously polluted from earlier use. The poll was pretested in an online survey, readjusted and than mailed to 285 appraisers. It had a rate of return of 32.3% (n=92). In June 2008, the MVR assessment concept was introduced, reviewed and discussed with leading experts from academia and practice in a workshop. Three factors to calculate the (absolute) Mercantile Value Reduction can be summarized as a result:

(I) Local factors [right arrow] [F.sub.L],

(II) Informational factors (time) [right arrow] [F.sub.T],

(III) Risk passing-on factors [right arrow] [F.sub.R].

Equation (1) presents the interrelation of the factors andtherespectiw components, which will be explained in detail.


Ad (1) Local Factor [right arrow] [F.sub.L]

In the literature review different local determinants were identified which are presumed to have a significant impact for market value diminution. Based on the expert interviews, 13 easily traceable characteristics were compiled defining the value reduction as key determinants due to the particular local character of a site compared to an average diminution level in the limits between 5% and 30% as observed in the literature (e.g. Jackson, 2002; Kleiber et al., 2010) and verified on mean by the polled experts. The analysis yields a risk-related reduction of 12.25% for a contaminated property on average in the point in time of suitable-for-reuse remediation completion. For the 13 detected local property characteristics, different weights ml reflecting the influence on the overall diminution were assigned in the expert poll (cf. Figure 4) as medians of responses to specify the extent of marketability reduction given the respective characteristics are known or supposed to be true based on the polled professionals' oberservations of previous market transactions (cf. Figure 4).

According to the oberservations of the experts polled, these local characteristics l for instance have a small (-), moderate (--) or strong (---) effect on the amount of marketability reduction:

--Visible safeguards such as barriers and fences (-)

--Poor demarcation of (supposed) contamination (-)

--Property listed in an official register of suspected contaminated sites (--)

--Large size of (supposed) contaminated area relative to total area (>15%) (--)

--Great media attention for contamination risk (---)

--Groundwater contamination is confirmed or very likely (---)

In a risk scoring approach where an expert appraiser relates local conditions to average conditions prevailing for sites contaminated from earlier use, the sum of these property characteristics results in a proportionate value reduction [F.sub.L] between 5% and 30%, which is subsequently adjusted by the factors "time" [F.sub.T] and "risk passing" [F.sub.R] as indicated in above mentioned equation (1). For [F.sub.L], appraiser's input [I.sub.l] indicates the extent of actual application of each characteristic l for the site to be evaluated. The expert is to give a score between I = 1 "not at all / much less than on average" and I = 5 "totally true / much more than on average" for each factor that states the actual existence and extent of each determinant on the site to be evaluated; [m.sub.l] represent median values for characteristics l according to the poll, and [w.sub.Il] are weights to transform the summed up medians into the interval of 5% to 30%.


These characteristics are used to define the particular local character of MVR. For example, an intensive local debate on pollution hazards and severe indications for ground-water pollution will considerably increase the risk-related reduction, e.g. from the average of 12.25% (i.e. when [I.sub.l] = 3 for all l, e.g. when there is no particular media attention and no knowledge on the extent of contamination in the groundwater) to 16.60% (if media attention is very high and groundwater damage appears certain). The specific conditions for the model, i.e. the weights wl and medians [m.sub.l] for the characteristics, reference values for average conditions (i.e. lower boundary of 5%, average of 12.25% and upper boundary of 30%), etc., can result from the appraiser's expert opinion regarding the conditions on the relevant property market or may be obtained in the case of missing market data, for higher-ranking or as practical aids from market observation or polls of experts such as the one applied here.

Noteworthy, the expert poll is not applied here in a contingent valuation approach for the hypothetical market of the site to be assessed. Contrary, observations by the professional appraisers are used to characterise the market resistance and behavior with regard to an averagely site remediated suitable-for-reuse based on their experienced proficient and independent observation of market transactions. When local or current market data is missing, this approach to characterize an average diminution level, which is adjusted for the specific local characteristics, is assumed to be applicable and more appropriate than hypothetical studies or market interviews, which can often capture only partial value determining market perceptions (cf. for critique Jackson, 2004b, Wilson, 2006).

Ad (2) Informational Factor (Time) [right arrow] [F.sub.T]

The local risk of value reduction will decrease as the date of valuation is moved forward in the planning and cleanup process (cf. Chalmers and Roehr, 1993). Over time, more information emerges on liabilities and the cost of rehabilitation, etc. and the MVR goes down as progress is made (stylized funnel shape in Figure 2). In line with Wiltshaw (1998) who categorized the market perception of stigma into pre and post-remediation, the calculation of a correction factor "time" [F.sub.T] for these influences is divided in the model here for points in time prior and post ready for use cleanup completion, as represented by the weights [w.sub.Iti]. This reflects the fact that MVR drops over time [t.sub.i] (i = 1) before site rehabilitation due to increasing availability of detailed information about remediation and rehabilitation costs, and (i = 2) after site rehabilitation, when remaining negative impacts diminish.

At a higher level, factors [t.sub.i=1] for assessing this risk as a function of time/information can be gathered from looking at cleanup cost margins at different planning stages. Using data from the Netherlands, in an approximation procedure for estimating lower and upper rehabilitation cost limits Kerth and Griendt (2000) obtain uncertainty factors (with a confidence level of 80%) shown in Table 2. If, for example, the only information available comes from a historical investigation study, actual costs after the cleanup will be between 20 and 260% of the current estimated value in four out of five cases. Risk assessment factors with t being points in time (characterized as information levels and to be stated by the expert as input for the site to be evaluated) before remediation completion can thus be determined so that, for instance, the MVR of an appraisal based on an initial historical investigation will be 1.40 times that obtained after rehabilitation completion (standardized = 1).

Time as a factor has an effect beyond that formal date of suitable-for-use-remediation-completion ([t.sub.i = 2]). The results of the poll of experts undertaken by the authors show, in line with the international literature (cf. Mundy 1992b; Weber et al., 2008) that an ongoing perception of risks and reduced marketability for contaminated sites, greatly diminishes over time as use of the area continues. According to the survey results, these risks and stigma surrounding such a site disappear almost completely within 10 years--during the first year of use even more than in the 10th year. This decline for factors [t.sub.i = 2] is incorporated into the model using an exponential function [I.sub.t] [right arrow] [e.sup.-0,5t] with I being the input of the expert user and t being the point in time (in years) after suitable-for-use-remediation completion of the site to be analysed. Due to missing data, this curve progression in the model is not based on empirical data. However, reasonable assumptions on the declining shape support the approximation. It is confirmed by the expert interview and the survey result that the function value for the point in time of remediation completion ([F.sub.T] = 1) equals 12.25% on average followed by a downward slope. A time/information level adjusted local risk of value reduction can be determined by linking the informational risk to the local MVR.

Ad (3) Risk Passing-on Factor [right arrow] [F.sub.R]

However, the actual amount of risk-related reduction will depend on the type and regional location of the property. As Wilson (1996) already points out, allowance has to be made for general market conditions, i.e. cyclical supply and demand fluctuations above or below average, as a variable affecting the actual impact of awareness of previous contamination on the effective market prices of real estate. Also, Patchin (1994) and Simons and Sementelli (1997) find stigma-related value reductions for industrial land, which grow with the substitutability of a property, i.e. depended on the market situation.

The factor "risk" [w.sub.Ir] reflects this market dependency. Risks can be passed on from the sellers to the buyers of a site, thus, reducing the value reduction. The MVR "risk" factor [F.sub.R] is based on the following theoretical assumption: The extent to which potential buyers lower a price due to perceived uncertainties depends on market dynamics and risk passing possibilities. During a boom, in a booming region or in the case of premium properties, sellers can pass on most of the risks, thus, reducing observed value reductions. In a slump or shrinking region where there is little demand for particular types of property, buyers will have many options to invest in alternative sites and therefore may obtain greater value reductions. Therefore, the amount of a specific market-based reduction depends on the concrete market situation with a factor [w.sub.Ir] equal to zero (acute shortage and great demand in a booming market) to one (big oversupply of similar properties). In a balanced market, the factor should be 0.5 with the risk shared by buyers and sellers. This market adjustment is a result of the expert users input [I.sub.r] indicating the market condition for the site to be appraised. This statement in particular calls for the expertise of an appraiser in the specific region and for the concrete type of use. Other factors for passing on risks include insurance contracts, public grants or deeds of release whereby some of the cleanup and liability risks are transferred to third parties. They are included in the model at this stage.

The absolute mercantile value reduction [right arrow] [MVR.sub.abs]

The product of introduced risks factors for location, time and feasibility of passing on risks equals the MVR in percent. This unit-free measure is proportional to [V.sub.CL], the theoretical comparative land value adjusted for quality of location and state of development. As indicated in equation (1) and shown in the following application example, MVR and [V.sub.CL], are combined to determine the absolute value reduction for a specific property to be appraised.


In order to be useful, Syms (1997) states that a model must replicate realistic considerations and resist testing against case study scenarios of actual transactions: "Any proposed model needs to conform, so far as is possible, to the procedures recommended by the surveying profession, otherwise it is unlikely to be accepted by practitioners" (Syms, 1997, 197).

Therefore, the risk scoring and assessment method developed here was applied (1) in different real world case studies and (2) tested separately by independent experts who are active in the marketing of contaminated and conversion sites in a with-and-without-test approach.

Application in the case of Krampnitz

To illustrate the application of the MVR methodology, the appraisal of risk effects of the former military site Krampnitz (Germany) is presented. This case study site is located approximately 10 km North of Potsdam in a suburb close to the German capital Berlin (c.f. for this and more detailed site description Schaedler et al., 2011). Krampnitz having an area of approximately 113 ha (280 acres) was used by armoured infantry of Nazi-German and Soviet armed forces until 1991. The operation of petrol stations and a chemical cleaning facility caused immense contamination, in particular by chlorinated solvents such as trichloroethylene (TCE) and tetrachloroethylene (PCE). The site contains both listed historical buildings and economically useless buildings. At present, the site is idle and not used. The adjacent area is characterised by a suburban residential area in the South, two lakes in the East and Southwest, parcels used for agriculture in the West and a nature reserve in the North. The site is aimed at being re-used for commercial and residential purpose.

To assess the impaired market value, a Comparative Land Value [V.sub.CL] is calculated in a residual valuation approach (i.e. the impaired value excluding MVR). As further described in Schaedler et al. (in press), [V.sub.CL] is assessed by deducting from the hypothetical as-if-clean value referring to the specific location quality adjusted market data of comparable uncontaminated sites in the Krampnitz region (1) the site's preparation and development costs, losses due to holding periods, planning and construction of infrastructure and (2) estimated costs for suitable-for-reuse remediation actions and related costs. MVR was applied as follows to assess the impaired market value of Krampnitz by taking into account potential marketability risks and uncertainties regarding the cost estimations as a diminution of [V.sub.CL]. All evaluations were made with regard to the same present effective date of evaluation.

Firstly, local determinants characterising the site were judged to gauge the Location Factor [F.sub.L]. Table 3 presents the evaluation of local characteristics l. Each characteristic was rated giving input [I.sub.l] against the extent that on average is to be expected, i.e. [I.sub.l] = 1 if the condition did not apply at all to the Krampnitz site, via [I.sub.l] = 2 if it did apply but less than in average cases, up to [I.sub.l] = 5 if it applied fully and much more then on average.

Next, the Informational Factor (Time) [F.sub.T] representing the actual level of available information is gauged. In the case of Krampnitz, different groups of consultants and researchers conducted several historical and orientating investigations. As no detailed investigation had been conducted by the effective date of valuation, according to Table 2, [F.sub.T] for Krampnitz equals 1.25.

Thirdly, the Risk P assing-on Factor [F.sub.R] was assessed. In the case of Krampnitz for the planed reuse option and the effective date of valuation, the market condition was appraised by a professional local appraisal expert as "balanced". Therefore, [F.sub.R] is set 0.5 indicating that the seller and any potential average buyer in an arm's length transaction will share the risk.

Combination of factors [F.sub.L], [F.sub.T] and [F.sub.R] gives the property specific MVR:

[F.sub.L]--Local "Mercantile Value Reduction (MVR)": -18.00%

[F.sub.T]--Multiplier for planning phase: * 1.25

[F.sub.R]--Multiplier for feasibility of passing on risks: * 0.50


MVR: = -11.25 %

[V.sub.CL]--Comparative land value (as for developed land less clean-up and other development costs) * 4,210,000 CU[degrees]

[MVR.sub.abs]--Estimated absolute MVR: = 470,000 CU[degrees]

[degrees]CU = Currency Unit

Applications by independent experts

The MVR assessment was applied in a broader case study approach on a sample of properties in Germany in a with-and-without-test approach. This type of testing is common in natural sciences and considered a proper conceptual measure of indirect impacts (Litman, 1995). Starting without knowledge of the MVR method, experts were asked to list at least five properties of their choice from their own practice and to rank them according to their perceived marketability. Afterwards, the experts were introduced to the MVR concept and asked to assess the mercantile value reductions accordingly.

An exemplary case study with six sites evaluated by four experts with different professional backgrounds is illustrated in Table 3, introducing the case study sites in the German federal state of Thuringia, and Table 4, showing the initial ranking and MVR assessment results of the experts.

In Table 5, the initial rankings R for each expert from a first individual estimation of the sites A to F and the MVR assessment results in percent are shown. Additionally, a ranking [R.sub.MVR] derived from MVR results are presented and for information the differences between the two rankings. As can be seen, initial and MVR rankings follow a similar pattern which indicates, that both are mirroring the same effects with regard to the marketability of the contaminated sites. Moreover, measuring the statistical dependence between these two variables with Spearman's rank correlation coefficients PRRMVR, indicates a strong relationship supported by high significance levels ([sigma]). Except for the environmental expert, all coefficients are significant, most so for the appraiser (probability of error < 5%) and the estate agent (< 1%). Finally, calculating the average of the experts' estimates and taking the mean of their MVR assessments again confirms a significant and strong relationship between the knowledge of the local experts for the validated case study sites and the general MVR assessment.

Results support a high level of validity for the MVR assessment method, with marketability rankings in initial appraisals being in line with MVR valuations by risk scoring. Therefore, it can be expected, that the MVR method in general allows assessing the value diminution of a contaminated site.

The concept of MVR has been introduced to different authorities, state development companies, independent appraisers and experts in contaminated site valuation. It has been found that the proposed factors are highly practicable because they are valuation-relevant and readily accessible with minimal information gathering efforts. The MVR technique was seen as generally suitable to objectify risks leading to stigma and uncertainties of market participants. It was considered a valuable contribution to make sales of derelict land more attractive for potential investors by authorities.


A review of success factors for derelict site revitalization projects has identified the real estate market as essential for the reuse of land polluted by earlier use. A high demand for land will increase its value, with the general price increase on the one hand suggesting potential reuse and, on the other, improving returns on investment into revitalization projects (Argus and Opper, 2008). With its more transparent assessment of contamination-related risks, the method proposed in this paper also helps to raise the awareness for cleanup projects and reduce land consumption.

Risk scoring and the algorithm presented here are one way of identifying market-perceived risks for sites polluted by earlier use in a transparent and comprehensible manner. Quantities such as location, time and feasibility of passing on risks can be combined in an assessment approach to determine the absolute value reduction for a specific property to be appraised. Results help appraisers, international investors and portfolio managers to deepen their understanding of valuation of risks associated with (previously) contaminated land.

Alternative approaches can be imagined and may be practicable. The scoring method proposed here appears to be particularly suitable because it is widespread in property appraisal (excluding contaminated sites) (e.g. TEGoVA, 2003). To achieve a similar amount of reliability, it should be given more concrete basis and be tested against the background of empirical and market studies. From the procedures proposed here we generally expect better transparency, harmonization and objective results in the valuation of contaminated sites, which will reduce perceived uncertainties.

However, whether such an effect can be achieved will not be seen until these procedures have been integrated into the practice of appraisal. Until then, a large number of political and legal hurdles remain to be cleared.


This paper reports results (1) of the BMBF funded research project "Strategies for the Revitalization of Brownfield Areas in the Larger Potsdam Region" (cf. Schaedler et al., 2011) and (2) of the SAFIRA II project, sponsored by the Helmholtz-Centre for Environmental Research--UFZ (cf. The support by and fruitful discussions with Reimund Schwarze and Paul Syms are greatly acknowledged. Recommendations from the journal's reviewers, the encouragement by the editors and proof-reading by Nina Hagemann and Oliver Gebhardt are highly appreciated.


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Stephan BARTKE

Helmholtz Centre for Environmental Research--UFZ, Department of Economics and Department Groundwater Remediation, Permoserstr. 15, 04318 Leipzig, Germany E-mail:; Phone: +49 341 235 1683; Fax: +49 341 235 1836; Web:

Received 13 September 2010; accepted 28 July 2011
Table 1. Survey of exemplary empirical studies
on the assessment of marketability risks of
(formerly) contaminated sites

Study                   Type of real   Observed impact

Gamble and              Residential    Temporarily reduced
Dawning, 1982                          marketability of
                                       properties in neighborhood
                                       of nuclear power plants

Kohlhase, 1991;         Residential    Depressed sales prices of
Thayer et al., 1992;                   properties bordering on a
Reichert et al., 1992                  (potentially) contaminated
                                       site; sales prices of
                                       neighboring properties rise
                                       with distance from
                                       contaminated site

Page and                Industrial     Significant effect of risks
Rabinowitz, 1993                       from contaminated sites on
                                       sales prices

Patchin, 1994           Industrial     Stigma causes loss in value from
                                       20.9-69% and more if demand
                                       is low (a)

Simons and              Industrial     Less financeability and 50% less
Sementelli, 1997                       market sales for contaminated
                                       vs. uncontaminated sites

Guntermann, 1995        Industrial     Neighborhood effect from open
                                       landfill, prices of adjacent
                                       industrial sites reduced by
                                       up to 51%

Dale et al., 1999       Residential    Value adjustment for nearby
                                       properties to properties
                                       farther away after successful
                                       rehabilitation of a
                                       contaminated site

Jackson, 2001b          Industrial     Reduced market sales/willingness
                                       of banks and investors to
                                       finance contaminated sites

Jackson, 2002           Industrial     Less stigma as remediation
                                       progresses; property value
                                       recovers from environmental
                                       risk-related reductions
                                       of 27.8-30.5% after completion
                                       of rehabilitation

Longo and               Industrial     No significant neighborhood
Alberini, 2005                         effects

Jackson, 2005           Industrial     93.2% of lenders refuse to grant
                                       mortgage for contaminated site
                                       before remediation, thereafter
                                       65.3% grant a credit, risk
                                       assessment of investors is lower
                                       than that of banks

Simons and              Residential    Negative valuation effects on
Winson-Geideman, 2005                  prope impacted by leaking
                                       underground sto
                                       tanks (LUST) of 25-33%

Messer et al.,          Residential    Stigma may result in sale prices
2006                                   to 5 to 10 years to recover
                                       after contamination has been
                                       cleaned up

Boyle et al.,           Residential    A property-specific
2010                                   contamination incident that is
                                       treatable may not
                                       have a long-lasting effect on
                                       sale prices

Simons and              Industrial     Property losses from 0-40%
                                       depending on environmental
Saginor, 2010                          conditions and proximity
                                       to the source (LUST)

Shelem et al.,          Residential    Significant neighborhood effects
(in press)                             after the general public became
                                       aware of the contamination of a
                                       defence fore site

Study                   Method

Gamble and              Multiple regression analysis
Dawning, 1982

Kohlhase, 1991;         Hedonic price model
Thayer et al., 1992;
Reichert et al., 1992

Page and                Case studies
Rabinowitz, 1993

Patchin, 1994           Case studies

Simons and              Sales price collection
Sementelli, 1997

Guntermann, 1995        Hedonic price model

Dale et al., 1999       Hedonic price model

Jackson, 2001b          Metaanalysis

Jackson, 2002           Multiple regression analysis

Longo and               Hedonistic price model
Alberini, 2005

Jackson, 2005           Survey

Simons and              Contingent valuation
Winson-Geideman, 2005

Messer et al.,          Psychology & hedonic
2006                    price model

Boyle et al.,           Hedonic price model

Simons and              Contingent valuation
Saginor, 2010

Shelem et al.,          Hedonic price model
(in press)

(a) Patchin (1994) describes eight case studies, one
indicating a stigma effect of 93.7%. In correspondence with
Paul Syms he agreed that not all reduction in value
could be due to stigma. Therefore, this case study was
omitted (cf. Syms 1997, 185).

Table 2. Informational risk factors

              i = 1

level for     No      Historical      Orientating     Deatailed
[w.sub.Iti]   study   investigation   investigation   investigation

Lower limit   10%     20%             50%             70%

Upper limit   280%    260%            200%            160%

Resulting     1.45    1.40            1.25            1.15

                                                              i = 2

Information                                               Points
level for     Remedial        Remediation   Remediation   in time for
[w.sub.Iti]   investigation   Plan          completed     subsequent

Lower limit   80%             85%           100%          --

Upper limit   140%            130%          100%          --

Resulting     1.1             1.08          1.0           t [right
factor                                                    arrow][e.sup.
[F.sub.T]                                                 -0,5t]

Source: Own presentation with lower and upper limits for
i = 1 based on Kerth and Griendt (2000), 8f.

Table 3. Assessment of Local Factor [F.sub.L] for Krampnitz

Characteristic 1                Situation in the
                                Krampnitz case

Poor demarcation of             Hot spots of contamination
(supposed) contamination        probably known but not

(Supposed) Contaminated         Contaminated area is
area > 15% of total site        expected to be 15% of
                                total area

Groundwater contamination is    Severe contamination is
confirmed or very likely        confirmed

Unclean look of property        It is worse than average

Visible safeguards such as      Fences only at site boarders--no
barriers and fences             unusual safeguards

Known requirements              Authorities stated clear
of authorities                  remediation requirements

Property listed in an           Site is listed in public
 official register              register of contaminated sites

Legally binding public          No such contracts exist
rehabilitation contract

Long period of unuse of         Property is idle for 15 years,
property > 5 years.             so more than on average but not
                                what is known as worst

Property located adjacent       This is true, but residential
to a residentially used area.   area is only small

(Potential) contamination       Not directly, but groundwater
is on edge of property          flow is toward nature reserve
                                North of the site

Great media attention for       Local media rarely reports on
contamination risk              contamination

Public discussion about         The economic perspectives
development of property         of redeveloping the site are
                                discussed regularly

Location Factor [F.sub.L]

                                Input           Mean
Characteristic 1                [I.sub.1]       [m.sub.1]

Poor demarcation of             3               -2
(supposed) contamination

(Supposed) Contaminated         3               -2
area > 15% of total site

Groundwater contamination is    5               -3
confirmed or very likely

Unclean look of property        4               -1

Visible safeguards such as      3               -1
barriers and fences

Known requirements              4               -2
of authorities

Property listed in an           5               -2
 official register

Legally binding public          1               -2
rehabilitation contract

Long period of unuse of         4               -1.5
property > 5 years.

Property located adjacent       3               -2
to a residentially used area.

(Potential) contamination       4               -1
is on edge of property

Great media attention for       3               -3
contamination risk

Public discussion about         4               -2
development of property

Location Factor [F.sub.L]       -18.00

                                 Weight      [I.sub.1] *
                                 [w.sub.1]   [m.sub.1] *
Characteristic 1                 in %        [w.sub.1] in %

Poor demarcation of              0.167       -1.00
(supposed) contamination

(Supposed) Contaminated          0.167       -1.00
area > 15% of total site

Groundwater contamination is     0.245       -3.67
confirmed or very likely

Unclean look of property         0.216       -0.86

Visible safeguards such as       0.167       -0.50
barriers and fences

Known requirements               0.216       -1.72
of authorities

Property listed in an            0.245       -2.45
 official register

Legally binding public           0.204       -0.41
rehabilitation contract

Long period of unuse of          0.216       -1.29
property > 5 years.

Property located adjacent        0.167       -1.00
to a residentially used area.

(Potential) contamination        0.216       -0.86
is on edge of property

Great media attention for        0.167       -1.50
contamination risk

Public discussion about          0.216       -1.72
development of property

Location Factor [F.sub.L]

Table 4. Case study sites in Thuringia, Germany

Case site              Area in hectares       Last use

A--ROTASYM, Possneck   3.60                   trade / industry

B--WGT-Site Forst,     34.10                  military /
Jena                                          conversion /

C--WGT-Site Fuel       1.10                   trade
Depot, Jena

D--Weimar-Factory,     0.63                   trade / industry
Bad Lobenstein

E--Freight Station,    7.00                   rail freight station

F--Tar Basins,         1.60                   tar basins / storage
Sattelstadt                                   area

Case site              Current use            Proposed use

A--ROTASYM, Possneck   none / demolition      trade

B--WGT-Site Forst,     none / vacancy /       ecological compen-
Jena                   demolition             sation area for
                                              highway extension
C--WGT-Site Fuel
Depot, Jena            underused trade        trade

D--Weimar-Factory,     vacancy / demolition   trade
Bad Lobenstein

E--Freight Station,    95 % vacancy /         mixed use area /
Sonneberg              temporary use of       temporary use as
                       engine-house           an urban park

F--Tar Basins,         partially storage      renaturation
Sattelstadt            area

Table 5. Thuringian case study ranking and MVR
assessment by experts

Case Site                      A                 B

Expert 1         R             3                 5
(developer)      MVR           16.0%             17.4%
                 [R.sub.MVR]   3                 5
                 [[DELTA]      0                 0

Expert 2         R             1                 6
(developer)      MVR           13.1%             16.0%
                 [R.sub.MVR]   3                 5
                 [[DELTA]      2                 1

Expert 3         R             1                 6
(environmental   MVR           11.4%             12.6%
expert)          [R.sub.MVR]   2                 4
                 [[DELTA]      1                 2

Expert 4         R             2                 5
(estate agent)   MVR           14.0%             20.2%
                 [R.sub.MVR]   3                 5
                 [[DELTA]      1                 0

Avarage of       R             1.75              5.5
Experts          MVR           13.6%             16.6%
                 [R.sub.MVR]   2.75              4.75
                 [[DELTA]      1                 0.75

Case Site                      C                 D

Expert 1         R             1                 4
(developer)      MVR           1.3%              17.9%
                 [R.sub.MVR]   1                 6
                 [[DELTA]      0                 2

Expert 2         R             4                 5
(developer)      MVR           15.7%             17.6%
                 [R.sub.MVR]   4                 6
                 [[DELTA]      0                 1

Expert 3         R             5                 3
(environmental   MVR           16.5%             16.3%
expert)          [R.sub.MVR]   6                 5
                 [[DELTA]      1                 2

Expert 4         R             3                 4
(estate agent)   MVR           13.4%             18.6%
                 [R.sub.MVR]   2                 4
                 [[DELTA]      1                 0

Avarage of       R             3.25              4
Experts          MVR           11.7%             17.6%
                 [R.sub.MVR]   3.25              5.25
                 [[DELTA]      0                 1.25

Case Site                      E                 F

Expert 1         R             2                 6
(developer)      MVR           5.7%              17.8%
                 [R.sub.MVR]   2                 4
                 [[DELTA]      0                 2

Expert 2         R             3                 2
(developer)      MVR           8.6%              4.0%
                 [R.sub.MVR]   2                 1
                 [[DELTA]      1                 1

Expert 3         R             2                 4
(environmental   MVR           8.6%              11.6%
expert)          [R.sub.MVR]   1                 3
                 [[DELTA]      1                 1

Expert 4         R             1                 6
(estate agent)   MVR           12.3%             22.5%
                 [R.sub.MVR]   1                 6
                 [[DELTA]      0                 0

Avarage of       R             2                 4.5
Experts          MVR           8.8%              14.0%
                 [R.sub.MVR]   1.5               3.5
                 [[DELTA]      0.5               1

Case Site                      [summation]       [[rho].sub.R,RMVR]
                               [[DELTA].sub.R]   ([sigma])

Expert 1         R             4                 0.829 **
(developer)      MVR                             (0.042)

Expert 2         R             6                 0.771 *
(developer)      MVR                             (0.072)

Expert 3         R             8                 0.657
(environmental   MVR                             (0.156)
expert)          [R.sub.MVR]

Expert 4         R             2                 0.943 ***
(estate agent)   MVR                             (0.005)

Avarage of       R             4.5               0.782 *
Experts          MVR                             (0.066)

R = Rank, MVR = Mercantile Value Reduction, [R.sub.MVR] = Rank MVR,
[[DELTA].sub.R] = [absolute value of R - [R.sub.MVR]
= Sum of Ar per Expert, Pr rmvr = Correlation Coefficient
(Pearson) of R and Rmvr a = Significance with * < 10%, **
< 5%, *** < 1% probability of error
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Author:Bartke, Stephan
Publication:International Journal of Strategic Property Management
Article Type:Abstract
Geographic Code:4EUGE
Date:Dec 1, 2011
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