VIEWPOINT

Sediment Quality Values (SQVs) andEcological Risk Assessment (ERA)PETER M. CHAPMAN* and GARY S. MANNEVS Environment Consultants, 195 Pemberton Avenue, North Vancouver, BC, Canada V7P 2R4

A wide variety of sediment quality values (SQVs) havebeen promulgated. Ecological risk assessment (ERA)provides a framework for objectively and systematicallyevaluating the risks posed by environmental contamina-tion to ecological resources. SQV application to ERAshould be restricted to the initial problem formulationstage where they can be used either alone (i.e., in juris-dictions with accepted SQVs) or in a weight-of-evidenceapproach (i.e., multiple SQV types; in jurisdictions with-out accepted SQVs) to screen out contaminants posingnegligible risks to ecological receptors. Ó 1999 ElsevierScience Ltd. All rights reserved

Keywords: ecological risk assessment; sediment; sedimentquality; criteria; guidelines; values.

Sediments have long been recognized as a sink for manycontaminants discharged into surface water bodies.Contaminated sediments can result in adverse ecologicale�ects to sediment-associated biota (e.g., macrophytes,benthos, demersal ®sh) and to higher-level biota (e.g.,pelagic ®sh and aquatic birds). Regulatory environ-mental protection e�orts in most jurisdictions now rec-ognize sediments as a critical portion of aquaticecosystems, and require their evaluation for dredgingactivities or for other potential remediation. Assessingpotential impacts of contaminated sediments has tradi-tionally relied on comparison of sediment chemistry tosediment quality values (SQVs), and/or ®eld and labo-ratory studies. Most SQVs were not intended as reme-diation criteria; therefore, management decisions basedon their use will likely be overly conservative. While ®eldand laboratory studies can provide valuable site-speci®cinformation on contaminant bioavailability, toxicityand ecological e�ects, they can be expensive and inef-fective if focused too broadly. Ecological risk assessment(ERA) provides a framework for evaluating contami-

nated sediments, which can incorporate a range of as-sessment tools in a logical and cost-e�ective manner.

However, ERAs can also be relatively expensive; thesearch continues for a cost-e�ective ``silver bullet'' whichwill save time and money (e.g., eliminate having to dosite-speci®c bioe�ects testing), while still providing re-alistic clean-up goals if such are required. SQVs areparticularly appealing in this regard because they couldbe that alternative ``if only'' one could determine exactlywhat the proper e�ects/no-e�ects threshold values arefor all contaminants of potential concern (COPCs). Todate this remains beyond the limits of our technicalknowledge or abilities, but the search continues. Whilerecognizing that this search might one day be successful,this paper deals with the present role of sediment qualityvalues in ecological risk assessment.

Ecological Risk Assessment (ERA)

Risk assessment of sediments (and other media) consistsof three major steps which may be further subdivided insome jurisdictions (US EPA, 1992): problem formula-tion; analysis (exposure and e�ects characterization);and, risk characterization. The overall intent of anyERA is to evaluate risk to populations and communitiesin the ®eld (US EPA, 1997), the overall objective ofsediment ERAs is generally to evaluate the risks ofvarious sediment management strategies (e.g., dredge orleave in place) to ecological resources.

Problem formulation is the systematic planning andinformation-gathering phase that sets the stage for theentire risk assessment process. For sediments, one of thekey issues is the type and magnitude of potential adversee�ects that could occur due to the presence of contam-inants. Whether this potential may be realized dependson the magnitude of the exposure, which may be non-existent or minimal if elevated bulk concentrations ofcontaminants in sediments are not bioavailable eithertemporally or spatially. The exposure component of theanalysis phase provides information on emissions,pathways, and rates of movement of contaminants into

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and out of sediments in order to estimate the concen-trations to which biological systems may be exposed.The e�ects component of the analysis phase assesses therelationship between sediment contaminant concentra-tions and the incidence and/or severity of adverse ef-fect(s). The ®nal step, risk characterization, integratesthe previous steps to estimate the incidence and severityof any adverse e�ects likely to occur. Risk character-ization also includes an uncertainty assessment of eachcomponent and of the overall risk assessment.Risk assessments of sediment contaminants typically

involve quotient approaches, speci®cally comparingtheir predicted environmental concentration (PEC ±determined from the exposure assessment) with theirpredicted no e�ect concentration (PNEC ± determinedfrom the e�ects assessment). PECs can be measured(e.g., sediment or porewater concentrations); PNECscannot be measured, particularly in sediments, butrather are based on predictions including best profes-sional judgement and weight of evidence (Menzie et al.,1996).

Types of SQVs

Numerous types of SQVs have been developed toassist in the assessment of sediment quality (e.g., see USEPA, 1996). While there are substantial di�erences in

derivation procedures (and hence resulting SQVs)among SQV types, no one type is necessarily better thanthe others for use in ERA, provided of course that suchvalues are within the bounds of reason, e.g., not belowaccepted background concentrations. SQVs in commonusage may be classi®ed as conservative or non-conser-vative (i.e., they may tend towards Type I errors, de-claring a sample to be toxic when it is not; or to Type IIerrors, declaring a sample to be non-toxic when it istoxic). The range of SQVs presently available is illus-trated in Fig. 1, which shows this range for some metalsand a metalloid in fresh and salt waters (data fromWang and Chapman, 1998). The ranges in each casespan orders of magnitude; a similar situation exists fororganic substances (Chapman et al., in press). Theranges shown could be narrowed if SQVs were dividedinto those which show a threshold below which e�ectsare very unlikely to occur and those for which thethreshold is the opposite, in other words, where e�ectsare very likely to occur. However, such divisions are noteasy as not all SQVs clearly fall into one category or theother, and there is overlap between the di�erentthresholds.

Some SQVs are derived to be protective of the envi-ronment for a wide range of locations and physicalconditions. To achieve this protection objective, envi-ronmental factors that in¯uence bioavailability are

Fig. 1 Range of world-wide sediment quality values for selected metalsand a metalloid (F� freshwater; S� saltwater). Not all valuescould be di�erentiated as indicating a concentration below whichadverse e�ects were unlikely or, conversely, a concentrationabove which adverse e�ects were likely. Thus all values devel-oped by any means, anywhere in the world, are shown.

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conservatively assumed to always be at levels which re-sult in maximum contaminant availability to biota.Other SQVs are derived using ®eld sediments and resi-dent and/or laboratory biota, thus di�erential bioavail-ability is already incorporated into these values and theyare not conservative.

Moreover, bioavailability varies by location and sit-uation, and sometimes by season. This fact has majorimplications relative to the conservatism of SQVs. Forinstance, if bioavailability was low at site(s) used todevelop SQVs based on correlative analyses, and theseSQVs were then used at a site which had high bio-availability, the values will be underprotective. The re-verse is, of course, also true. Thus, SQVs do not implymaximum contaminant bioavailability and are not al-ways necessarily conservative. Nor will e�ects neces-sarily occur even when sediment contaminantconcentrations greatly exceed conservative SQVs (e.g.,Paine et al., 1996).

The key to successful use of SQVs lies in under-standing how they were derived and their limitations.This is essential since many jurisdictions have adopted asingle set of SQVs for regulatory use, which may con-strain the risk assessor to limit use of SQVs to one type.While the goal of this paper is not to serve as a com-prehensive review of SQV types, a short overview of twocommon types representing di�ering protection goals isprovided below for illustrative purposes.Apparent E�ects Threshold (AET): This approach

(e.g., Barrick et al., 1988) considers synoptic ®eld datarelating sediment contaminant concentrations to at leastone indicator of adverse ecological e�ects (e.g., sedimenttoxicity tests, benthic infaunal community structure,histopathological abnormalities in ®sh). The data arethen analysed to determine the concentration of a par-ticular contaminant above which statistically signi®cantadverse biological e�ects are always expected. The de-gree of conservatism for a particular AET value dependson how clean the break is between distributions of ef-fects and no-e�ects data. The necessity to always ob-serve statistically signi®cant e�ects in the data set meansthat AET values may err towards underprotection insome cases (i.e., frequency of adverse e�ects at lowerconcentrations may be relatively high, but just notfound ``always''). The ``always'' stipulation was includ-ed to minimize the in¯uence of false-positives poten-tially caused by other co-occurring chemicals. The AETapproach was originally derived to help assess signi®-cantly contaminated (i.e., in extent and magnitude)sediments in largely urban settings. Consequently, thedegree of conservatism of AET SQVs represents a bal-ance between environmental protection and availableresources.

Biological E�ects Database for Sediments (BEDS):This approach (e.g., Long et al., 1995, 1998; Environ-ment Canada, 1995; MacDonald et al., 1996; Smith etal., 1996) is based on a compilation of synoptic chemicaland biological e�ects data from numerous studies con-

ducted throughout North America. BEDS includes re-sults from a variety of analysis approaches including co-occurrence, apparent a�ects thresholds, equilibriumpartitioning, sediment quality objectives, sedimentquality guidelines, spiked sediment bioassays, andscreening-level criteria. Two values are typically derivedfrom the database: one representing concentrations be-low which adverse e�ects are expected to rarely occur(e.g., e�ects range-low [ER-L] or threshold e�ects level[TEL] values) and one representing concentrationsabove which adverse e�ects are predicted to frequentlyoccur (e.g., e�ects range-median [ER-M] or probablee�ects level [PEL] values). Deriving these values involvesarbitrarily selecting a percentile (e.g., 10th for ER-L;50th for ER-M) from the distribution of e�ects. TEL/PEL derivation is slightly di�erent in that it considersthe geometric mean of percentiles from both the e�ectsand no-e�ects distributions (e.g., TEL is the geometricmean of the lower 15th percentile of e�ects data and the50th percentile of no-e�ect data; PEL is the geometricmean of the 50th percentile of e�ects data and the 85thpercentile of no-e�ect data). The resulting SQVs repre-sent a range of conservatism.

SQVs such as AETs and ERL/ERM, TEL/PEL arebased on a correlation approach which does not addresscause and e�ect. Only SQVs based on equilibrium par-titioning (EqP ± DiToro et al., 1991) begin to addresscause and e�ect because these values are based not oncorrelation but rather on strong theoretical foundations.SQVs that are generated based on multi-contaminantdata from ®eld-collected sediments are only as robust asthe size of the data set used in establishing the SQV, andare not based on a measured relationship between ex-posure and toxicity. There may or may not be a directrelationship between such an SQV and e�ects in or-ganisms.

Major Limitations of SQVs

The previous section touched on some of the inherentlimitations of concentration-based SQVs. Understand-ing these limitations will help to determine how promi-nent a role SQVs can serve in sediment ERA. Keylimitations are summarized as follows:

Degree of conservatism: As discussed above, di�erentSQV derivation procedures have inherently di�erentprotection goals. The more conservative SQVs areskewed towards producing more false-positive results(i.e., predicting e�ects when none are actually occur-ring), while the less-conservative SQVs tend to result inmore false negatives (i.e., predicting no e�ects when ef-fects are actually occurring). These tendencies severelylimit the use of SQVs in ERA.

Bioaccumulation/biomagni®cation: SQVs are typicallybased on direct toxicity (acute or chronic) to aquaticspecies. As such, they cannot be considered either pro-tective or predictive of any risks associated with long-term bioaccumulation, or for the relatively rare phe-

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nomenon of biomagni®cation. Bioaccumulation andbiomagni®cation need to be assessed separately as partof any ERA. Bioaccumulation can result in two adversee�ects of concern: potential e�ects on long-term repro-ductive capacity (e.g., organochlorines ± Murdoch et al.,1997); and, secondary poisoning. Secondary poisoningrefers to increased concentrations of a contaminantacross a single trophic level which may result in toxicityto a predator. Biomagni®cation refers to increasedconcentrations of a contaminant across two or moretrophic levels and is relatively rare, arguably restrictedto a handful of contaminants, in particular: 2,3,4,7,8-TCDD; PCBs; methyl mercury; DDT. Biomagni®cationis of particular concern when any of these four con-taminants are present and the ERA includes non-aquatic receptor species, which is the case for manyshallow water sites.

Bioavailability: Site-speci®c sediment characteristics(e.g., grain size, organic carbon, pH, redox potential,acid volatile sulphides) and biotic factors (e.g., biotur-bation, bioirrigation) can signi®cantly in¯uence thebioavailability (and hence toxicity) of contaminants.While SQVs are typically derived from data from manylocations representing a range of sediment conditions,the resulting contaminant concentration values cannotpossibly be applied to all sediment conditions.

Contaminant mixtures: SQVs are intended for use toevaluate the potential for adverse e�ects associated withsingle contaminants. While the data used to derive SQVsoften include ®eld sediments which may contain multi-ple contaminants, the concentrations of individualcontaminants are considered separately in the derivationprocess. The inclusion of ®eld data is often consideredan advantage because it represents realistic exposuresituations (i.e., exposure to more than one contami-nant); however, more than one contaminant may beselected as being responsible for observed e�ects whichcan introduce confounding results into the SQV data-base.

Predictability: Proponents of SQVs have shown thatthey are reasonably ``predictive'' of adverse ecologicale�ects (Long et al., 1995, 1998). This conclusion wasbased on comparisons of SQV e�ect/no e�ect predic-tions for an extensive sediment chemistry data base(i.e.,>1000 samples from west, east and south coasts ofNorth America) with actual synoptic biological e�ectsinformation. However, others have countered that thoseresults are irrelevant from a validation perspective be-cause they are an artifact of the derivation process. Forinstance, Sampson et al. (1996) found that the incidenceof false positives was greater than 25% for most ER-Lvalues and many of the ER-M values. Indeed, our ownexperience evaluating sediment chemistry and toxicityresults from a number of sites shows a relatively highpercentage of false positives for BEDS-based SQVs. ForSQVs geared towards ``always'' predicting biologicale�ects (e.g., AETs), the opposite problem is encountered(i.e., a high percentage of false-negatives).

SQV Usage in ERA

ERA has evolved as a tool to help make sound en-vironmental decisions. It provides a framework withinwhich to conduct site-speci®c investigations geared to-wards assessing risks associated with present (i.e.,baseline or retrospective ERA) or future (i.e., predictiveERA) conditions. The current popularity of ERA ispartly based on its ``common sense'' approach, whichincorporates site-speci®c information to identify the``real'' risks that require managing. Minimizing Type Iand II errors in sediment ERA is essential to balanceadequate environmental protection with the notoriouslyhigh cost of remediation. While some regulators wouldprefer managing sites with concentration-based SQVs,the reality is that they are not typically appropriate foruse in isolation to make management decisions. How-ever, they can play an important role in screening con-taminants of potential concern (COPCs) during theproblem formulation stage of aquatic ERAs.

Identi®cation of COPCs is typically conducted in athree step screening process (Fig. 2):

1. Evaluation of historical and/or present site use in-formation to determine the broad groups of con-taminants potentially present in the receivingenvironment.

2. Comparison of available site data to acceptedbackground concentrations (this is particularlyuseful for contaminants for which no SQVs exist).Non-elevated contaminants are not consideredfurther in the ERA; all elevated contaminants areconsidered in the next step.

3. Comparison of available site data to SQVs. Non-elevated contaminants are not considered further;contaminants exceeding SQVs are carried throughthe ERA process.

As previously noted, there are a variety of SQVs. Thereare also a variety of opinions as to which SQVs are most

Fig. 2 Problem formulation contaminant screening process.

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appropriate for generic use. Not surprisingly, the de-velopers of speci®c SQVs are also their most ardentadvocates. Although it is arguably possible to separateSQVs on the basis of conservatism (i.e., Type I versusType II errors), the validity of such separations is alsoarguable in many cases, and it is not possible to deter-mine the ``best'' SQV to use in all situations. Theproblem formulation screening process should err on theconservative side so that there is no question that con-taminants dropped from further consideration pose norisks (i.e., we need to avoid false negatives). In juris-dictions without accepted SQVs, a ``weight of evidence''screening approach comparing observed sediment con-taminant concentrations to a variety of recognizedSQVs, e.g., AETs, ERL/ERMs, TEL/PELs, EqP couldbe used. However, many jurisdictions either have theirown SQVs or have their own preferences as to whichSQVs are acceptable. Consequently, a signi®cantproportion of problem formulation COPC screeningswill likely be conducted using a single SQV type.The risk assessor needs to know the SQV developmentprocess and its inherent degree of conservatism inorder to understand the limitations and uncertaintiesassociated with using any particular SQVs for COPCscreening.

In our experience, many regulators often equate SQVswith remediation criteria. The default expectation is thatsites with non-trivial exceedances (e.g., high magnitudeof exceedances or exceedances over a large spatial ex-tent) require some form of remediation. The proponentmust show that the site does not pose risks to the en-vironment (i.e., through ERA) in order to avoid or re-duce remediation (i.e., risk manage only those areaswhich may cause, or be causing, adverse ecological ef-fects). The other option is to move directly to cleaningup the site based on the SQVs. This latter approachmight be followed only if the cost of complete remedi-ation is less than the ERA and risk management ap-proach, which is not often the case.

The intensity of ®eld investigations likely required tosupport the ERA will depend on the degree of perceivedhazard, as indicated by the frequency and magnitude ofSQV exceedances. Long and MacDonald (1998) haveput forward a scheme to prioritize contaminated sitesusing the frequency and mean magnitude of PEL ex-ceedances. While such an approach may aid regulatorsin directing e�ort and available resources towards pri-ority sites, it is not likely to preclude the need for sedi-ment ERAs at any sites with SQV exceedances.

Following screening using SQVs, direct site-speci®cmeasurements (e.g., toxicity tests, benthic communityanalyses) are then required to fully assess risk. Theparticular type of testing required would depend on theCOPCs (e.g., is bioaccumulation likely a separate is-sue?), site (e.g., what are the resident organisms?), andsituation (e.g., what is the intended site usage?). Suchmeasurements are substantially more expensive thansimply conducting chemical analyses and comparing the

results with SQVs. However, the costs are relativelyminor compared to the costs for remediation (or ofmaking an incorrect decision).

Example ± Dredging

EPA/USACE (1998) detail procedures for the evalu-ation of dredged material which, although not based onERA, are consistent with our recommendations above.Speci®cally, they suggest that SQVs, when ready for use,be applied in Tier II of a four-tier evaluation process.Tier III consists of standardized laboratory bioe�ectsand bioaccumulation testing; Tier IV consists of casespeci®c evaluations to be used in the eventuality that adecision cannot be made in Tier III. Tier I consists of areview of available information; Tier II consists presentlyonly of a theoretical calculation of bioaccumulation po-tential and only exists because EPA/USACE (1998)recognize the eventual need for a separate tier for SQVs.

The Puget Sound Sediment Dredged Disposal Anal-ysis Program (PSDDA) has implemented this approachregionally for dredged material management (US EPAet al., 1997). Speci®c regional SQV, which are regularlyupdated, are used as a screening tool. If sediment con-centrations are all below the screening level (SL) SQVthen the material is acceptable for open water disposalwithout further testing. If concentrations exceed the SLSQV, then direct testing is required before a decision canbe made regarding suitability for open water disposal.This usage is consistent with screening level usage in theproblem formulation phase of an ERA, as recom-mended herein.

Conclusion

Notwithstanding their limitations, we suggest thatSQVs should be used in the problem formulation stageof ERA to identify contaminants of potential concernby comparing sediment concentrations to SQVs in ascreening process. Speci®cally we suggest that bioavail-able sediment contaminants which will result in directtoxicity (whatever the exposure pathway, i.e., from wa-ter [interstitial or overlying] or food) can probably bepredicted, to the extent necessary for hazard identi®ca-tion/problem formulation, by comparing sedimentcontaminant concentrations to SQVs in a screeningprocess. The more complex (and comprehensive) phasesof an ERA require data that directly address cause-e�ectrelationships for COPCs (i.e., that address risk). Thus,SQVs should not be used further in ERA until andunless future research provides new SQVs which can beused to provide cause-and-e�ect information. The costimplications of isolated application of SQVs for deci-sion-making purposes are far too high (i.e., the costs ofmaking an incorrect decision). Until then, ®nal decision-making requires site-speci®c data focused on assessingcontaminant bioavailability.

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This paper bene®ted greatly from discussions and input with col-leagues at EVS Environment Consultants. In particular we thank:Michael Johns, Joe Germano, Kathy Godtfredsen. However, the au-thors bear full responsibility for the opinions expressed in this paper.We also thank David Moore (US Army Corps of Engineers) for in-viting one of us (PMC) to give a talk on this subject and thus stimu-lating us to write this paper.

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