Ecological Risk Assessment - Part 5 pptx

Part V Risk Characterization Statements about single events can’t be decided by a calculator; they have to be hashed out by weighing the evidence, evaluating the persuasiveness of arguments, recasting the statements to make them easier to evaluate, and all the other fallible processes by which mortal beings make inductive guesses about an unknowable future. Pinker (1997) Risk characterization is the phase of ecological risk assessment that integrates the exposure and the exposure–response profiles to evaluate the likelihood of adverse ecological effects and uses those results to synthesize a useful conclusion. In other words, it is the process of estimating and interpreting the risks and associated uncertainties. There are two fundamen- tally different types of risk characterizations. Screening assessments are intended to quickly and easily divide risks into those that need more attention and those that can be ignored (Chap ter 31). Definit ive a ssessment s are intende d to infor m a decision -making pr ocess by providi ng risk estimat es for all asses sment end points (Ch apter 32). Riskcharacterizations may bealgorithmic in thattheymay use a standard procedure basedon a standard set of input information using standard assumptions, scenarios, and models. Algorith- mic approaches are used primarily in ecological risk assessments of pesticides and industrial chemicals (Luttik and van Raaij 2003; EPPO 2004). They are desirable in that context, because they are efficient and fair to all of the competitive products that come before a chemical regulator. They are popular with regulated parties, because the data requirements are clear, and the outcome of a regulatory assessment can be predicted. Algorithmic approaches are disadvantageous when chemicals have properties that are not considered in the algorithm. The obvious example is endocrine disruptors that are not addressed by standard test batteries or effects models. Alternatively, risk characterization may be performed ad hoc. The advantage of ad hoc approaches is that they can be designed to provide the best estimate of risk and uncertainty given the types of information that are available and the particular circumstances of the assessment. Ad hoc approaches have been used for contaminated sites, because the condi- tions and information sets are highly variable. Ad hoc approaches are also employed when assessments are highly contentious or when unusual issues such as developmental deformities are involved. ß 2006 by Taylor & Francis Group, LLC. Infer ence in risk charact erization takes diff erent form s de pending on the type of assessment and the types of infor mation that are avail able. They differ in how they use the avail able lines of evidence to reach a con clusion. In risk ch aracteriza tion, a line of evidence is an estimat e of expo sure an d a corres pondi ng exposure–r esponse relationshi p. Single line of eviden ce : The classic form of infer ence uses one line of ev idence, whi ch is either the only availab le evidence or the best eviden ce. For ch emicals, the most c ommon line of evidence is an expo sure estimat e from a mathemati cal model and a num erical en dpoint from a toxic ity test. Weight of eviden ce : If mult iple lines of evidence are avail able, they may be joint ly con- sider ed. The multiple lines may be from a single type of evidence (e.g., exp osure–r esponse relation ships from different tests) or from multiple types (e.g., chemical toxic ity tests, tests of con taminate d media , and biologi cal surveys ). Risk ch aracteriza tions may also be diff erentiated by the form of the infer ence. Rule -based inference : Risk asses sors may be provided with an inferen tial rule to de termine whet her a risk is accepta ble. The sim plest an d most common is: if the e xposure estimat e exceed s the benchmark effec ts level (i.e., HQ > 1; Secti on 31.1), the risk is unacce ptable. A more complex rule is: if the 90 th percent ile of the e xposure dist ribution exceeds the 10th percen tile of the effec ts dist ribution, the risk is una cceptable (Section 30.5). Rule -based inference is most common in algorithmic assessments of new chemicals. How ever, an infer- ential rule may be developed for an individual assessment during the problem formulation (Ch apter 18). Rule-based inference may be applie d to screeni ng or defini tive asses sment s. It is usuall y limit ed to a single line of evidence but , in its original form , the sedim ent qualit y triad is a rule- based inferenti al method for three lines of evidence (Chap ter 32). Ad hoc judgment: In many cases, risk characterizations include judgments concerning acceptability of a risk without a priori rules or guidance. This approach provides the greatest flexibility and influence to the assessors, but lacks transparency and diminishes the role of stakeholders and decision makers. Structured judgment: Many risk characterizations are too complex and the evidence too ambiguous to allow rule-based inference, but ad hoc judgment gives too much latitude to assessors. In such cases, the assessor’s judgment can be guided by an inferential structure including organization of the input data by type of evidence, the use of standard consider- ations to evaluate the evidence, and scoring systems. Examples of structures for judgment for causal analys is and risk charact eriza tion are present ed in Chapt er 4 an d Chapter 32, respectively. Risk estimation: One may estimate risks and uncertainties and report them to a risk manager who interprets the estimates and makes a decision. Risk estimation is used in definitive assessments and may be based on any number of lines of evidence. Risk estimates are essential if the results of risk characterization are to be used in an economic analysis, decision analysis, or other quantitative decision-support tool. Comparison of alternatives: Rather than characteriz ing risks from an agent or activity to determine its acceptability, one may compare alternatives to determine which is preferable (Ch apter 33). Exa mples include alterna tive chemi cals with the same us e, alte rnative remedial actions for a contaminated or disturbed site, and alternative management plans for a forest. These approaches to inference are not mutually exclusive. For example, it is often appro- priate to use structured judgment to determine whether significant effects are likely and then, if the results are positive, use risk estimation to inform a decision. ß 2006 by Taylor & Francis Group, LLC. 29 Criteria and Benchmarks For various reasons , it is somet imes desir able to red uce the c omplex ities of expo sure–re sponse relationshi ps for v arious taxa, pro cesses, an d other eco logical pro perties to a single num ber that is presu med to be a suff iciently protect ive level. Those that are us ed to separat e accepta ble from unaccep table concen trations for regula tory purp oses are termed crite ria or standar ds (hencef orth, sim ply crit eria). Thos e that are used for screenin g or priori tization are termed screeni ng bench marks or screeni ng values . 29.1 CRITERIA Criter ia are con centrations of contam inants in water or other media that are intende d to consti tute the bounds of regula tory accep tability given prescr ibed co nditions (Section 2.2). The only national ecological criteria in the United States are the acute and chronic National Ambient Water Quality Criteria (NAWQC). Criteria were prop osed for sediments by the Environ mental Pro tection Agency (EP A) but wer e conve rted to screeni ng gu idelines (Sect ion 29.2.) The acu te NAW QC are calculated by the EPA as half the final acute value, whi ch is the 5th percentile of the distribution of 48 to 96 h LC 50 values or equivalent median effective concentration (EC 50 ) values for each criterion chemical (Stephan et al. 1985). The acute NAWQC are intended to correspond to concentrations that would cause less than 50% mortality in 5% of exposed species in a relative ly brief exposure. Because the criterion is not a no-effect level, the criterion is lowered if an impor tant species is among the most sensitive 5% (Figure 29.1) . The chronic NAWQC are final acute values divided by the final acute=chronic ratio, which is the geometric mean of quotients of at least three LC 50 =CV ratios from tests of organisms belonging to different families of aquatic organisms (Stephan et al. 1985). Chronic NAWQC are intended to prevent significant toxic effects in most chronic exposures. Some, termed final residue values, are based on protection of humans or other piscivorous organisms rather than protection of aquatic organisms. Because criteria are applied to an entire state or nation, they should be derived in a way that accounts for variance among sites and uncertainty. Site-specific standards may incorporate site properties to reduce either variance or uncertainty. For example, the NAWQC for many metals are functions of hardness, so that important sources of variance can be eliminated in site-specific applications (Spehar and Carlson 1984; Stephan et al. 1985). Similarly, results from testing of local species may be used to modify national criteria in deriving site-specific standards. More broadly, standards may be derived for different classes of ecosystems (e.g., freshwater and saltwater standards in the United States), different uses (e.g., agricultural, residential, commercial, and industrial land uses in Canadian soil guidelines), or different levels of protection (e.g., the designation of National Parks as Class I under the US Clean Air Act). 435 ß 2006 by Taylor & Francis Group, LLC. NAWQC are applicable regulatory criteria and are generally adequatel y protective, but they are often not good risk estimators for particular sites. If they are applied to a site, assessors should co nsider deriving site-specific criteria using the water effect ratio. This is a factor for adjusting criteria to site water that may be derived using an EPA procedure (EPA 1983; Office of Science and Technology 1994). It requires performing toxicity tests with the chemical in site waters, and, optionally, with site species (Figure 29.2). The time and expense 0 0.1 1 10 10 2 10 3 10 4 10 5 0.2 0.4 Freshwater final acute value* = 2.1 µg/L dissolved cadium @ 50 mg/L total hardness Criteria maximum concentration = 1.0 µg/L dissolved cadium @ 50 mg/L total hardness Freshwater % Rank GMAVs Ranked summary of cadmium GMAVs Cadmium effect concentration (µg/L) 0.6 0.8 1 Freshwater invertebrates Freshwater fish Freshwater amphibians (lowered to protect rainbow trout) * FIGURE 29.1 Acute and chronic ambient freshwater quality criteria for cadmium at 50 mg=L hardness (horizontal lines), and the acute species sensitivity distribution. The acute values (LC 50 s and EC 50 s) for species and genera are geometrically averaged so the points are genus mean acute values (GMAVs). (From EPA (U.S. Environmental Protection Agency), 2001 Update of Ambient Water Quality Criteria for Cadmium, EPA-822-R-01-001, Office of Water, Washington, DC, 2006a. With permission.) Toxicity in site water = 0.4 mg/L Toxicity in laboratory water = 0.1 mg/L Water effect ratio = 0.4:0.1 = 4 Site-specific criterion = 4 ϫ 0.06 = 0.24 mg/L Water quality criterion = 0.06 mg/L FIGURE 29.2 An illustration of the derivation and use of water effect ratios. ß 2006 by Taylor & Francis Group, LLC. requir ed to calculate site-spe cific criteri a co uld be worthw hile if the water ch emistry at a site differs significan tly from conven tional laborato ry test waters. Othe rwise, the effor t is be tter expend ed on tests of ambie nt waters (Sect ion 24.5). Currently, in the United States, the methodology for deriving ambient water quality criteria is being reexamined, and the risk assessment framework is being applied. In particular, derivation of new criteria will begin with a problem formulation to determine the appropriate endpoints for the chemical, important exposure pathways, and the availability and utility of unconventional effects data. The more flexible approach is reflected in recent criteria and proposed criteria that use field data or novel modeling approaches (EPA 2000a, 2003a, 2004a, 2006a). For suspended and bedded sediments, a framework for deriving regional or water- shed-specific values by multiple methods and weighing the results has been developed (EPA 2006b). Many nations have criteria for water and other media, and comments about the utility of the US criteria may not apply to them. The utility of these criteria in risk assessments should be considered where they are potentially applicable. It is often appropriate to estimate the risk of exceeding a criterion in addition to estimating risks to ecological endpo ints. 29.2 SCREENING BENCHMARKS Screening benchmarks are concentrations of chemicals that are believed to constitute thresholds for potential toxic effects on some category of receptors exposed to the chemical in some medium. Since they are used for screening chemicals, they should be somewhat conservative so that chemicals that do in fact cause effects at a particular site are not screened out of the assessment (Chap ter 31). It is mo re impor tant to ensure that hazardo us che micals are retained than to avoid retention of chemicals that are not hazardous. However, excessive conservatism decreases the value of screening assessments, because effort is wasted on nonhazardous chemicals that might better be expended on the truly hazardous ones. Because of this deliberate conservatism, it is important to avoid adoption of screening benchmarks as remedial goals or other thresholds for action without some additional assessment to determine that they are appropriate. There is little consensus about the best methods for deriving screening benchmarks. The following alternatives are based on US practices. Screening benchmarks used in Australia, Europe, and North America are reviewed by Barron and Wharton (2005). 29.2.1 CRITERIA AS SCREENING BENCHMARKS Criteria are commonly used as screeni ng benchmarks because exceedence of one of these values constitutes cause for concern. The US NAWQC have been recommended for screening at contaminated sites by the EPA (Office of Emergency and Remedial Respon se 1996). However, it is not clear that they are sufficiently conservative, since they are assumed to be sufficiently close to the true threshold of effects to justify regulatory action and because of other concerns (Suter 1996c). These concerns are supported by the finding that nickel concentrations in a waste-contaminated stream on the Oak Ridge Reservation that were below chronic NAWQC were nonetheless toxic to daphnids (Kszos et al. 1992). When used for regulation of effluents— their intended purpose—these criteria achieve additional conservatism by being applied to relatively short exposure durations. That conservatism does not app ly to contaminated sites. 29.2.2 TIER II VALUES If NAWQC are not available for a chemical, the Tier II method described in the EPA Proposed Water Quality Guidance for the Great Lakes System or a slight variation used at ß 2006 by Taylor & Francis Group, LLC. OR NL may be applied (EPA 1993e; Suter and Ts ao 1996). Tier II va lues wer e de veloped so that aquati c life crit eria could be conserva tively estimat ed with fewer da ta than are requir ed for the NAWQC . Tier II values are conc entrations that woul d be expecte d to be higher than NAW QC in no more than 20% of ca ses, if suff icient test data wer e obtaine d to calculate NAW QC. For exampl e, if there is only one acu te value (LC 50 or EC 50 ) for a ch emical, that value is divided by 20.5 if it is a daphnid and 242 if it is not. Equi valent factors are available for other numb ers of acu te values in Appen dix B of Suter and Tsao (1996) . The sources of data for the Tier II values , and the pro cedure an d fact ors used to calculate the SAVs and SCVs, are presen ted by EPA (1993e ) and Suter a nd Tsao (1996). 29.2.3 B ENCHMARKS B ASED ON EXPOSURE –RESPONSE MODELS Screen ing bench marks might be based on low percent iles of exposure–r espo nse relation ships. In particu lar, one can calcul ate an LC 0 or EC 0 for chemi cals with apparent effects thresho lds. Alternat ivel y, the practice in human healt h risk asses sment of using the lower 95 % confide nce limit on a be nchmark dos e (the EC 10 ) can be applied to nonhum an organis ms (Linder et al. 2004). Thi s value is consider ed by the US EPA to app roximatel y co rrespond to a no observed adverse effect level (NOAEL ) for human healt h effe cts, but is more consistent. 29.2.4 T HRESHOLDS FOR S TATISTICAL SIGNIFICANCE Test endpoints based on statistica l signi ficance are commonl y used as screening bench marks. The e ndpoint used varies among media and recept ors. Lowes t chroni c values : Chronic values (CVs ) are geomet ric means of no observed effect con centrations (NO ECs) and lowest observed effe ct concentra tions (LOEC s). They are used to calculate the chronic NAW QC , and may be present ed in place of ch ronic criteri a by the EPA when chro nic criteri a canno t be calcul ated (EPA 1985). CVs are not con servative ben chmark values. Wild life NO AELs : Screening ben chmarks for wildlife are conventi onally based on NOAE Ls from chronic or subch ronic toxicity tests with mamm als or birds. The major varia bles in deriva tion of wildli fe benchmarks are the test en dpoints used an d whet her allom etric scali ng or safety fact ors are used . Wildlif e bench marks use reprod uctive or other effe cts as end points, allometr ic equ ations for inter species extrap olations, and factors to allow for shortco mings in the test design (Sampl e et al. 1996c; Office of Solid Waste and Emergency Respons e 2005). The resul ting screeni ng dose, terme d the wi ldlife toxicity reference values (TRVs) must be co nverted to a concen tration in soil or other medium to screen those media (Efroy mson et a l. 1997; Office of Solid Waste and Emergency Respons e 2005). That requ ires an expo sure mod el (Chap ter 22). 29.2.5 T EST ENDPOINTS WITH S AFETY F ACTORS Some states and EPA regions ba se screeni ng benchmarks on test e ndpoints divide d by safety fact ors. These fact ors do not have the scientif ic basis of the fact ors used to derive the Tier II values (above) or the fact ors propo sed by Cal abrese and Bald win (Tab le 26.3) . However, the use of factors of 10, 100, or 1 000 have a long hist ory in the EPA (Dour son and Stara 1983; Nabho lz et al. 1 997) (Table 26.1), an d such factors ca n be easily app lied to any test endp oint. 29.2.6 DISTRIBUTIONS OF EFFECTS LEVELS Sets of screening benchmarks for sediments and soils have been derived from distributions of effects or no-effects levels. An estimate of the threshold effects concentration for a particular ß 2006 by Taylor & Francis Group, LLC. chemi cal is derive d from a pe rcentile of the distribut ion of reported effects or no-effect s concen trations. Thes e concen trations vary due to varian ce in the phy sical and chemi cal propert ies of soil s or sedimen ts, varian ce among the measur ed responses , and varia nce in the sensi tivities of the species or commun ities. Therefor e, the benchmarks de rived in this way may be tho ught to protect some propo rtion of combination s of specie s, responses , and media . The foll owing are examples of this approach . Effect s range- low and e ffects range-med ian for sediment s: The Nation al Oceani c and At- mospheri c Admi nistratio n (NOAA ) uses three method s: (1) equ ilibrium partiti oning; (2) spiked sedim ent toxic ity test s; an d (3) field su rveys to develop exposure–r esponse rela- tions hips (Lon g et al. 1995). Chem ical concentra tions obs erved or estimat ed to be associ ated with biologi cal effe cts are ranked , and the low er 10th percent ile (effect s ran ge-low, ERL ) an d the med ian (effect s range- media n, ER M) conce ntrations are identifi ed. A variant of this approac h is Florida ’s Thresh old Effect s Lev els (MacD ona ld et al. 1996). Screenin g level concent rations : Thes e bench marks are derive d from synop tic data on sedim ent ch emical concen trations and benthic inverteb rate dist ributions. They are estimat es of the highest co ncentra tion that can be tolerated by a specified percent age of benthic species. Example s include the Ontario Minis try of the Environme nt Lowest and Severe Effect Levels (Pesaud et a l. 1993). Oak Ridge Nat ional Laborat ory benchm arks for soil : Bench marks for toxic ity to plants, soil inverteb rates, an d micr obial pro cesses have been developed from the 10th percen tile dist ri- butions of toxic ity test data (Efroy mson e t al. 1997a, b). 29.2.7 EQUILIBRIUM PARTITIONING BENCHMARKS Equilibrium partitioning benchmarks are bulk sediment concentrations derive d from aqueous criteria or benchmark concentrations based on the tendency of nonionic organic chemicals to partition between the sediment pore water and sediment organic carbon and for metals to be bound to sulfides (Sect ion 22.3). The fundame ntal a ssumptions are that pore water is the principal exposure route for most benthic organisms and that the sensitivities of benthic species is similar to that of the species tested to derive the aqueous benchmarks, predominantly the water column species. Examples include the US EPA’s equilibrium partitioning sedim ent guidelines (EPA 2000b, 2002c–f) and consensus sediment guidelines for PAHs (Swartz 1999). 29.2.8 AVERAGED VALUES AS BENCHMARKS Sometimes the most sensitive response is thought to be too conservative, criteria for identi- fying the best value are not apparent, and there is no agreement concerning how to extrapo- late to a safe level. In such cases, benchmarks may be derived by simply averaging test endpoints that are deemed to be relevant and of sufficient quality. This approach was used in the US EPA’s soil screening values for plants and soil invertebrates (Office of Solid Waste and Emergency Response 2005). 29.2.9 ECOEPIDEMIOLOGICAL BENCHMARKS When effects are observed in the field and the cause has been de termined (Chapter 4), the effective exposure levels determined in those studies can be used as benchmarks at other sites. For example, tund ra swans and other waterfowl were foun d dead or suffering toxicosis in the Coeur d’Alene Basin, Idaho, an area of lead mining. Field and laboratory studies were used to relate sediment lead to dietary lead to lead body burdens and effects. The result was an estimated toxic threshold of 530 mg lead per gram sediment dry weight and a lethal level of 1800 mg=g (Beyer et al. 2000; Henny 2003). ß 2006 by Taylor & Francis Group, LLC. 29.2.10 SUMMARY OF SCREENING B ENCHMARKS Curr ently the de velopm ent of screening benchmarks is inconsi stent across media . The large and relative ly consis tent body of data for aq uatic animals has led to the de velopm ent of more than a doz en alternati ve types of ben chmarks . Simi larly there are severa l alternati ve bench- marks for sedimen ts, but they have been developed for fewer chemic als. Wildl ife benchmarks are nearly alw ays ba sed on NOEC values , so usually only one type of be nchmark is availa ble. How ever, there is consider able varian ce in what effects are included and in the exposure models used to extra polate back to soil concen trations. Finally, bench marks for plan ts, invert ebrate s, an d micro bes in soil are inconsi stent and are ava ilable only for few chemi cals. Give n the lack of valida tion or even a common definiti on of validity , no singl e type of ben chmark can be demonst rated to be consis tently reliable. When there are multiple bench- marks for a chemi cal an d none are clearly superi or, ‘‘cons ensus’ ’ ben chmark values may be sim ply derive d by av eraging. Swar tz (1999) derived a thres hold effe cts concentra tion for total PAHs (0.3 mg =g OC) as the arithmet ic mean of five divers e bench marks. He found that it was a reasonab le thres hold value for PAH effec ts in inde pendent da ta sets from PAH- con taminate d sites. Alternat ively, the unc ertainty co ncerning the most app ropriate bench- mark may be treat ed by cho osing the low est be nchmark for each chemi cal. Bec ause the degree of conserva tism of benchmarks is uncerta in, concerns that truly toxic chemi cals may be screened out may be relieved by using unc ertainty factors. An exampl e of the use of unc ertainty fact ors for this purpo se is the eco logical risk assessment for the Rocky Mo untain Arsenal, in which factors were a pplied to account for intrataxon variability, inter taxon variab ility, uncerta inty of critical effect, exp osure duratio n, en dpoint extrapo la- tion, and resid ual unc ertainty (Banton et al. 1996). For each of these six issue s, a fact or of 1, 2, or 3 was applie d signi fying low , medium , or high uncerta inty, respect ivel y. Clearl y, the magni tudes of these factors are not related to estimat es of actual varian ce or unc ertainty associ ated with each issue, and the multiplicat ion of fact ors bears no relat ionship to any estimat e of the total uncerta inty in the ben chmarks . Ho wever, uncerta inty factors pro vide an assura nce of conserva tism withou t appeari ng complet ely arbitrary . An alternati ve is to derive unc ertainty factors based on estimat es of actual varian ce or uncerta inty. An exampl e is the pred iction inter vals on the inter taxon extrap olations and the unc ertainty factors on the predict ion inter vals (PIs) for a given taxonom ic level present ed in Table 26.2 through Table 2 6.5. ß 2006 by Taylor & Francis Group, LLC. 30 Integrating Exposure and Exposure–Response The primary task of risk characterization is to integrate the exposure estimates from the analysis of exposure with the exposure–response relationships from the analysis of effects to estimate the nature and magnitude of risks. In effect, response is esti mated by solving the exposure–response function for the exposure estimate. In most assessments, this task has been performed by simple methods that require little thought. However, as more attention is paid to varia bility and uncerta inty (Chapter 5), probabil istic methods are be coming more common. 30.1 QUOTIENT METHODS If the analysis of exposure has generated a point estimate of exposure (e.g., the maximum measured concentration) and the analysis of effects has reduced the exposure–response relationship to a point (e.g., an LC 50 ), integration of the two reduces to the quotient method. The hazard quotient (HQ) is the quotient of an exposure concentration (C e ) divided by a toxicological benchmark concentration (C b ): HQ ¼ C e =C b (30:1) Because this is a widely used assessment method, the terms have many representations. In Europe, C e is usually termed the predicted environmental concentration (PEC) and C b is termed the predicted no effect concentration (PNEC). If exposure and effect are expressed as doses, the HQ is equivalent [D e =D b ]. The same simple model may be applied to a variety of agents such as temperature, percent fines, and radiation. Because of its simplicity, the quotient method is nearly always used in screening assessments, but it is also the most common method of risk characterization in definitive assessments. Although some assessors have used Monte Carlo analysis (Chapter 5) to perform prob- abilist ic analys es of HQs (as in the Hong Kon g exampl e, Sectio n 30.7.3 , an d Zolezz i et al. 2005), they may be performed analytically (IAEA 1989; Hammonds et al. 1994). The quotient model can be expressed as: ln HQ ¼ ln C e À ln C b (30:2) HQ will be approximately log-normal even if the distributions assigned to C e and C b are not (IAEA 1989; Hammonds et al. 1994). Hence, the geometric mean of HQ is the antilog of the difference of the means of the logs of C e and C b , and the geometric variance is the antilog of the sum of the variances of the logs of C e and C b . ß 2006 by Taylor & Francis Group, LLC. If the number of exposure values and effects values are finite, one may simply determine the distribution of all possible values of HQ. For example, in an assessment of risks to pond communities from pyrethroid pesticides, Maund et al. (2001) determined the distribution of quotients for 90th percentile concentrations in each of 72 pond categories with each acute and chronic toxicity datum (Figure 30.1). While the HQ expresses how bad things are, a related concept, the margin of safety, expresses how good they are. The relative margin of safety is simply the inverse of the HQ. A relative margin of safety of 100 suggests that the exposure concentration must be increased by a factor of 100 to reach a toxic level. The absolute margin of safety is the difference between a toxic level and the exposure level. An absolute margin of safety of 100 mg=L suggests that the exposure concentration must be raised by that amount to reach a toxic level. An example of the use of margins of safety in ecological risk assessment is presented by Newsted et al. (2002). 30.2 EXPOSURE IS DISTRIBUTED AND RESPONSE IS FIXED Frequently, the exposure–response relationship is reduced to a point, such as a criterion value, but the exposure estimate is distributed. The exposure distribution may come from the distribution of measured concentrations in the environment, from Monte Carlo analysis of a transport and fate model or from expert judgment. In such cases, the probability of exceeding the benchmark value (C b ) is the integral of the probability density function above C b (i.e., 1—the cumulative probability at C b ). An example of this approach is the analyses of risks to herons and egret s in Hong Kong with determ inate effects thresh olds (Sect ion 30.6). 10 −2 10 −1 Risk quotient 10 0 10 1 10 −3 0.1 Exceedance probability (%) 0.5 1 2 5 10 20 30 40 50 Water column instantaneous EEC: invertebrate acute toxicity Water column 96 h EEC: invertebrate acute toxicity Water column 21 d EEC: invertebrate chronic toxicity FIGURE 30.1 Distributions of acute and chronic quotients for invertebrates from an assessment of risks to pond communities from pyrethroid pesticides. EEC ¼ estimated exposure concentration. (From Maund, S.J., Travis, K.R., Hendley, P., Giddings, J.M., and Solomon, K.R., Environ. Toxicol. Chem., 20, 687, 2001. With permission.) ß 2006 by Taylor & Francis Group, LLC. [...]... based on Chapter 5 of Suter et al (2000) ß 2006 by Taylor & Francis Group, LLC Particular chemicals or classes of chemicals as chemicals of potential ecological concern Particular media as sources of contaminant exposure Particular ecological receptors as credible assessment endpoints Ecological risks as a consideration in the remedial action A secondary purpose of screening risk assessments is... However, Region V (2005a,b) has published screening assessments that represent the state-of-practice as part of its guidance for ecological risk assessment of contaminated sites These assessments use simple conservative assumptions such as 100% area use factor and 100% bioavailability and risk characterizations based on deterministic HQs The conclusions represent the roles that screening assessments can... of ecological risks is the integration of exposure estimates with exposure–response relationships to estimate effects or probabilities of effects ß 2006 by Taylor & Francis Group, LLC Adult Po’ouli 1.000 10,000 Frequency Probability 0. 750 Mean mortality = 0.03% 0 .50 0 0. 250 0 0.000 0.00 1.38 2.76 Percent 4.14 5. 52 Juvenile Po’ouli 1.000 10,000 Frequency Probability 0. 750 Mean mortality = 0 .57 % 0 .50 0... this three -part logic is reduced to two parts by replacing de manifestis and indeterminate risks with a single category, nontrivial risks In that case, the nontrivial risks are carried forward to subsequent assessments Screening ecological risk assessments have a number of potential uses To prompt action: In some cases, a screening assessment will reveal that risks are manifestly significant, and remedial... be taken without further data collection or assessment To determine the need for further assessment: A screening assessment may reveal that significant risks are highly unlikely or that the risks are of low priority relative to other risks or relative to the likely costs of assessment and management To define the scope of a definitive assessment: A screening assessment may screen out certain contaminants,... Characterization Risk characterization in a screening ecological risk assessment consists of using exposure and effects information to screen the risks into categories The most general categorization is: De minimis—risks that are clearly insignificant and can be ignored in subsequent assessments or decisions Indeterminate—risks that are not clearly significant or insignificant and must be resolved by further assessment. .. prevent its elimination from the assessment 31.2 .5 SCREENING SITES A site can be eliminated from a risk assessment if all endpoint receptors for that type of unit have been eliminated However, it must be noted that even when there are no significant risks due to contaminant exposures on the site, the risk assessment must address fluxes of contaminants that may cause ecological risks off site or incidental... bw) 0. 35 1.77 3.18 Diphacinone concentration in snails (µg/g) Weight of insects (g) Weight of snails (g/g bw) e Slop Dose (mg/kg bw) Probability of mortality 12 Probit Probability of mortality vs diphacinone dose 8. 45 6 0 9.18 9.91 LD 0 0.4 0.8 50 1.2 Log dose (mg/kg) Interspecies 04 extrapolation 0 0.40 1 0 .54 0.68 25 FIGURE 30.9 Diagram of a probabilistic ecological risk assessment for a single-day... may cause risks to wide-ranging wildlife populations 31.2.6 DATA ADEQUACY AND UNCERTAINTIES Screening ecological risk assessments performed at the intermediate stages of a phased assessment process or as the initial step in the definitive assessment should have adequate data quality and quantity because the data set used should be the result of a proper ß 2006 by Taylor & Francis Group, LLC assessment. .. 1998) In the Risk Assessment Guidance for Superfund, the EPA has specified that chemicals found in less than 5% of samples may be excluded These criteria are not recommended here, because they are not risk- based 31.2.1.1 Screening Against Background Waste sites should not be remediated to achieve concentrations below background; therefore, baseline risk assessments should not normally estimate risks from . the risk is una cceptable (Section 30 .5) . Rule -based inference is most common in algorithmic assessments of new chemicals. How ever, an infer- ential rule may be developed for an individual assessment. interpreting the risks and associated uncertainties. There are two fundamen- tally different types of risk characterizations. Screening assessments are intended to quickly and easily divide risks into. future. Pinker (1997) Risk characterization is the phase of ecological risk assessment that integrates the exposure and the exposure–response profiles to evaluate the likelihood of adverse ecological effects