Federal Register I Vol. 45, No. 231 I Friday, November 28, 1980 I Notices '79347 

Residue Value .1.ax~ per.is.ible tissue concentration) 

(mean norBalized BCF)(appropriate pereent lipids) 

a. For an FDA action level for fish oil, 

the appropriate percent lipids value is 

100. 

b. For an FDA action level for fish. the 

appropriate percent lipids value is 15 for 

freshwater criteria and 16 for saltwater 

criteria because FDA action levels are 

applied on a species-by-species basis to 

commonly consumed species. The edible 

portion ofthe freshwater lake trout 

averages about 15 percent lipids, and 

the edible portion of the saltwater 

Atlantic herring averages about 16 

percent lipids (Sidwell. V. D.• et al. 1974 

Composition of the Edible Portion of 

Raw (Fresh or Frozen) Crustaceans, 

Finfish. and Mollusks. I. Protein, Fat, 

Moisture. Ash, Carbohydrate, Energy 

Value. and Cholesterol. Marine Fisheries 

Review 36:21-35). 

c. For a maximum acceptable dietary 

intake derived from a chronic feeding 

study with wildlife. the appropriate 

percent lipids is the percent lipids of an 

aquatic species or group of aquatic 

species which constitute a major portion 

of the diet of the wildlife species. 

F. The Final Residue Value is 

obtained by selecting the lowest of the 

available residue values. It should be 

noted that in many cases the Final 

Residue Value will not be low enough. 

For example. a residue value calculated 

from an FDA action level would result in 

an average concentration in the edible 

portion of a fatty species that is at the 

action level. On the average half of the 

individuals of the species would have 

concentrations above the FDA action 

level. Also. the results of many chronic. 

feeding studies are concentrations that 

cause adverse effects. 

X. Other Data 

Pertinent information that could not 

be used in earlier sections may be 

available. concerning adverse effects on 

aquatic organisms and their uses. The 

most important.ofthese are data on 

flavor impairment. reduction in survival, 

growth. or reproduction. or any other 

adverse effect that has been shown to 

be biologically significant. Especially 

important are data for species for which 

exceeded on the average in a 24-hour 

period and one that should not be 

exceeded at any time during the 24·hour 

period. This two-number criterion is 

intended to identify water quality 

conditions that should protect aquatic 

life and its uses from acute and chronic 

adverse effects of both cumulative and 

noncumulative substances without being 

as restrictive as a one-number criterion 

would have to be to provide the same 

degree of protection. 

B. The maximum concentration is the 

Final Acute Value or is obtained from 

the Final Acute Equation. 

C. The 24-hour average concentration 

is obtained from the Final Chronic 

Value. the Final Plant Value. and the 

Final Residue Value by selecting the 

lowest available value. unless other 

data (see Section X) from tests in which 

the toxicant concentrations were 

measured show that a lower value 

should be used. If toxicity is related to a 

water quality characteristic, the 24-hour 

average concentration is obtained from 

the Final Chronic Equation, the Final 

Plant Value. and the Final Residue 

Value by selecting the one that results in 

the lowest concentrations in the normal 

range of the water quality characteristic. 

unless other data (see Section X) from 

tests in which the toxicant 

concentrations were measured show 

that a lower value should be used. 

D. The criterion is (the 24-hour 

average concentration) as a 24-hour 

average and the concentration should 

not exceed (the maximum 

concentration) at any time. 

XII Review 

A. On the basis of all available 

pertinent laboratory and field 

information. determine if the criterion is 

consistent with sound scientific 

evidence. Ifit is not. another criterion, 

either higher or lower. should be derived 

using appropriate modifications of the 

Guidelines. 

These Guidelines were written by 

Charles E. Stephan. Donald I. Mount, 

David J. Hansen, John H. Gentile. Gary 

A. Chapman and William A. Brungs of 

Appendix C-Guidelines and . 


Methodology Used in the Preparation of 


Health Effect Assessment Chapters of 


the Consent Dec::ree Water Criteria 


Documents 


I Objective 

The objective of the health effect 


assessment chapters of the ambient 


water criteria documents is to estimate 


ambient water concentrations which do 


not represent a significant risk to the 


public. These assessments should 


constitute a review of all relevant 


information on individual chemicals or 


chemical classes in order to derive 


criteria that represent, in the case of 


suspect or proven carcinogens, various 


levels of incremental cancer risk. or. in 


the case of other pollutants, estimates of 


no-effect levels. 


Ideally, ambient water quality criteria 


should represent levels for compounds 


in ambient water that do not pose a 


hazard to the human population. 


However, in any realistic assessment of 


human health hazard. a fundamental 


distinction must be made between 


absolute safety and the recognition of 


some risk. Criteria for absolute safety 


would have to be based on detailed 
 ., knowledge of dose-response .j relationships in humans. including all 


sources of chemical exposure, the types 


of toxic effects elicited, the existence of 


thresholds for the toxic effects. the 


Significance of toxicant interactions. and 


the variances of sensitivities and 


exposure levels within the human 


population. In practice. such absolute 


criteria cannot be established because 


of deficiencies in both the available data 


and the means of interpreting this 


information. Consequently. the 


individual human health effects chapters 


propose criteria which minimize or 


specify the potential risk of adverse 


human effects due to substances in 


ambient water. Potential social or 


economic costs and benefits are not 
 I 

considered in the formulation of the 


criteria. 
 I . II Types ofCriteria . i 

Ambient water quality criteria are 1 

based on three types of biological 

endpoints: carcinogenicity, toxicity (i.e., 

all adverse effects other than cancer]. 

and organoleptic effects. 

For the purpose of deriving ambient 


water quality criteria, carcinogenicity is 
 no other data are available. Data from 

behavioral. micorcosm, field. and 

physiological studies may also be 

available. 

XI. Criterion 

A. The criterion consists of two 

concentrations, one that should not be 

the U.S.E.P.A. Environmental Research 

Laboratories in Corvallis. Oregon. 

Duluth. Minnesota. Gulf Breeze. Florida. 

and Narragansett. Rhode Island. 

Numerous other people. many of whom 

do not work for U.S.E.P.A.. provided 

assistance and suggestions. 

regarded as a non-threshold 

phenomenon. Using this assumption, 

"safe" or "no effect" levels for 

carcinogens cannot be established 

because even extremely small doses 

must be assumed to elicit a finite 

increase in the incidence of the 

response. Consequently. water quality 
-


79348 Federal Register I VoL 45. No. 231 I Friday, November 28, 1980 I Notices

criteria for carcinogens are presented as 

a range of pollutant concentrations 

associated with corresponding 

incremental risks. 

For compounds which do not manifest 

any apparent carcinogenic effect, the 

threshold assumption is used in deriving 

a criterion. This assumption is based on 

the premise that a physiological reserve 

capacity exists within the organism 

which is thought to be depleted before 

clinical disease ensues. Alternatively. it 

may be assumed that the rate of damage 

will be insignificant over the life span of 

the organism. Thus. ambient water 

quality criteria are derived for non­ carcinogenic chemicals. and presumably 

result in no observable-adverse-,effect 

levels (NOAELs) in the exposed human 

population. 

In some instances. criteria are based 

on organoleptic characteristics, i.e., 

thresholds for taste or odor. Such 

criteria are established when 

insufficient information is available on 

toxicologic effects or when the estimate 

of the level of the pollutant in ambient 

water based on organoleptic effects is 

lower than the level calculated from 

toxicologic data. It should be recognized 

that criteria based solely on 

organoleptic effects do not necessarily 

represent approximations of acceptable 

risk levels for human health. 

Several ambient water quality criteria 

documents deal with classes of 

compounds which include chemicals 

exhibiting varying degrees of structural 

similarity. Bel(ause prediction of 

biological effects based solely on , structural parameters is difficult, the 

derivation of compound-specific criteria 

is preferable to a class criterion. A 

compound-specific criterion is defined 

as a level derived from data on each 

individual subject compound that does 

not represent a significant risk to the 

public. For some chemical classes. 

however. a compound-specific criterion 

cannot be derived for each member of a 

class. In such instances. it is sometimes 

justifiable to derive a class criterion in 

which available data on one member of 

a class may be used to estimate criteria 

for other chemicals of the-class because 

a sufficient data base is not available 

for those compounds. 

For some chemicals and chemical 

classes. the data base was judged to be 

insufficient for the derivation of a 

criterion. In those cases. deficiencies in 

the available information are detailed. 

III. Approach 

The human health effects chapters " 

attempt to summarize all information on 

the individual chemicals or classes of 

chemicals which might be useful in the 

risk assessment process to develop 

water quality criteria. Although primary 

emphasis is placed on identifying 

epidemiologic and toxicologic data. 

these assessments typically contain 

discussions on four topics: existing 

levels of human exposure. 

pharmacokinetics, toxic effects. and 

criterion formulation. 

For all documents. an attempt is made 

to include the known relevant , 

information. Review articles and reports 

are often used in the process of data 

evaluation and synthesis. Scientific 

judgment is exercised in the review and 

evaluation of the data in each document 

and in the identification of the adverse 

effects against which protective criteria are sought. In addition. each of these 

documents is reviewed by a peer 

committee of scientists familiar with the 

specific compound(s). These work 

groups evaluate the quality of the 

available data, the completeness of the 

data summary, and the validity of the 

derived criterion. 

In the analysis and organization of the 

data, an attempt is made to be 

consistent with respect to the format 

and the application of acceptable 

scieHtific principles. Evaluation 

procedures used in the hazard 

assessment process follow the principles 

outlined by the National Academy of 

Sciences in Drinking Water and Health 

(1977) and the guidelines of the . Carcinogen Assessment Group of the 

U.S. EPA. 

A.Exposure 

The exposure section of the health 

effects chapters reviews known 

information on current levels of human 

exposure to the individual pollutant 

from all sources. Much of the data was 

obtained from monitoring studies of air. 

water. food. soil. and human or animal 

tissue residues. The major purpose of 

this section is to provide background 

information on the contribution of water 

exposure relative to all other sources. Consequently. the exposure section 

includes subsections reviewing different 

routes of exposure including water and ' 

food ingestion. inhalation, and dermal 

contact. 

Information on exposure can be 

valuable in developing and assessing a water quality criterion. In these 

documents exposure from consumption 

of contaminated water and 

contaminated fish and shellfish products 

is used in criterion formulation. Data for 

all modes of exposure are useful in 

relating total intake to the expected 

contribution from contaminated water. 

fish, and shellfish. In a.ddition. ' 

information for all routes of exposure. 

nof limited to drinking water and fish 

and shellfish ingestion, can be used to 

iustify or assess the feasibility of the 

formulation of criteria for ambient 

water. 

The use of fish consumption as an 

exposure factor requires the 

quantitation of pollutant residues in the 

edible portions of the ingested species. 

Accordingly, bioconcentration factors 

{BCFs} are used to relate pollutant 

residues in aquatic organisms to the 

pollutant concentration in the ambient 

waters in which they reside. 

To estimate the average per capita 

intake of a pollutant due to consumption 

of contaminated fish and shellfish the 

results of a diet survey were analyzed to 

calculate the average consumption of 

freshwater and estuarine fish and 

shellfish '(U.S. EPA, 198O). A species is 

considered to be a consumed freshwater 

or estuarine fish and shellfish species if 

at some stage in its life cycle. it is 

harvested from fresh or estuarine water 

for human consumption in significant 

quantities (Stephan. 1980). 

Three different procedures are used to 

estimate the weighted average BCF 

depending upon the lipid solubility of 

the ch,emical and the availability of 

bioconcentration data. 

For lipid-soluble compounds. the 

average BCF is calculated from the 

weighted average percent lipids in the 

edible portions of consumed freshwater 

and estuarine fish and shellfish which 

was calculated from data on 

consumption of each species and its 

corresponding percent lipids to be 3.0 

percent (Stephan, 1980). Because the 

steady-state BCFs for lipid-soluble 

compounds are proportional to percent 

lipids, bioconcentration factors for fish 

and shellfish can be adjusted to the 

average percent lipids for aquatic 

organisms consumed by Americans. For 

many lipid-soluble pollutants. there 

exists at least one BCF for which the 

percent lipid value was measured for the 

tissues for which the BCF is determined. 

With 3.0 percent as the weighted 

average percent lipids for freshwater 

and estuarine fish and shellfish in the 

average diet, a BCF. and a 

corresponding percent lipid value. the 

weighted average bioconcentration 

factor can be calculated. ' 

Example: 

Weighted average percent lipids for 

average diet=3.0 percent 

Measured BCF of 17 for 

trichloroethylene with bluegills at 

4.8 percent lipids 

Weighted average BCF for average 

diet equals 

17 X 3.0% =10.6 

4.8% 
79349 

n 

o 

o 

r 

le 

1. 

Federal Register },.yo1. 45. No. 231 I Friday, November 28, 1980 I Notices 

As an estimate. 10.6 is used for the 

BCF. 

In those cases where an appropriate 

bioconcentration factor is not available. 

the equation "Log BCF=(0.85 Log P)­

0.70" can be used (Veith. et ai. 1979) to 

estimate the BCF for aquatic organisms 

containing about 7.6 percent lipids 

(Veith. 1980) from the octanol/water . 

partition coefficient P. An adjustment 

for percent lipids in the average diet 

versus 7.6 percent is made in order to 

derive the weighted average 

bioconcentration factor. 

For non-lipid-soluble compounds. the 

available BCFs for the edible portion of 

consumed freshwater and estuarine fish 

and shellfish are weighted according to 

consumption factors to determine a 

weighted BCF representative of the 

average diet. 

B. Pharmacokinetics 

I 

This section summarizes the available 

information on the absorption, 

distribution. metabolism, and 

elimination of the compound(s) in 

humans and experimental mammals. 

Conceptually. such information is useful 

in validation of inter- and intra species 

extrapolations, and in characterizing the 

modes of toxic action. Sufficient 

information on absorption and excretion 

in animals, together with a knowledge of 

ambient concentrations in water, food. 

and air. could be useful in estimating 

body burdens of chemicals in the human 

population. Distribution data which 

suggest target organs or tissues are 

desirable for interspecies comparison 

techniques. In terms of the derivation of 

criteria. pharmacokinetic data are essential to estimate equivalent oral 

doses based on data from inhalation or 

other routes of exposure. 

C. Effects 

This section summarizes information 

on biological effects in both humans and 

experimental mammals resulting in: 

acute. subacute. and chronic toxicity, 

synergism andlor antagonism. 

teratogenicity. mutagenicity. or 

carcinogenicity. 

The major goal of this section is to 

survey the suitability of the data for use 

in assessment of hazard and to 

determine which biological end-point. 

i.e., non-threshold. threshold. or _ 

organoleptic. should be selected for use 

in criterion formulation. 

Because this section attempts to assess potential human health effects. 

data on documented human effects are 

thoroughly evaluated. However, several 

factors inherent in human 

epidemiological studies usually preclude 

the use of such data in generating water 

quality criteria. These problems. as 

. summarized by the National Academy 

of Sciences (NAS. 1977) are as folloWs: 

1. Epidemiology cannot tell what 


effects a material will have until after 


humans have been exposed. One must 


not conduct what might be hazardous 


experiments on man. 
 2. If exposure has been ubiquitous, it 


may be impossible to assess the effects 


of a material, because there is no 


unexposed control group. Statistics of 


morbidity obtained before use of a new 


material can sometimes be useful. but 


when latent periods are variable and 


times of introduction and removal of 


materials overlap. historical data on 


chronic effects are usually 


unsatisfactory. 


3. It is usually difficult to determine 


doses in human exposures. 


4. Usually. it is hard to identify small ' 

changes in common effects. which may 

nonetheless be important if the 

population is large. 

5. Interactions in a "nature-designed" 

experiment usuaHy cannot be 

controlled. , Although these problems often 

prevent the use of epidemiological data 

in quantitative risk assessments. 

qualitative similarities or differences 

between documented effects in humans 

and observed effects in experimental 

mammals are extremely useful in testing 

the validity of animal-to-man 

extrapolations. Consequently, in each 

case. an attempt is made to identify and 

utilize both epidemiologic and animal 

dose-response data. Criteria derived 

from such a conftrmed data base are considered to be reliable. 

The decision to establish a criterion 

based on a noncthreshold model is made 

after evaluating all available 

information on carcinogenicity and 

supportive information on mutagenicity. 

The approach and conditions for the 

qualitative decision of carcinogenicity 

are outlined in the U.S. EPA Interim 

Cancer Guidelines (41 FR 214.02). in a report by Albert. et a1. (1977). and in the 

Interagency Regulatory Liaison Group 

(IRLG) guidelines on carcinogenic risks 

(IRLG. 1979). It is assumed that a 

substance which induces a statistically 

significant carcinogenic response in 

animals has the capacity to cause 

cancer in humans. A chemical which 

has not induced a significant cancer 

response in humans or experimental 

animals is not identified as a 

carcinogen, even though its metabolites 

or close structural analogues might 

induce a carcinogenic response or it was 

shown to be mutagenic in an in vitro 

system. 

It is recognized that some potential 

human carcinogens may not be 

identified by the guidelines given above. 

For example. compounds for which 

there is plausible but weak qualitative 

evidence of carcinogenicity in 

experimental animal systems (such as 

data from mouse skin painting or strain 

A mouse pulmonary adenoma) would be 

included in this category. The derivation 

of a criterion for human consumption 

from these studies in not valid. 

regardless of the qualitative outcome. In 

addition. there are certain compounds 

(e.g., nickel and beryllium] which were 

. shown to be carcinogenic in humans 

after inhalation exposure by chemical 

form. but have induced thus far no 

response in animals or humans via 

ingesting their soluble salts. 

Nevertheless, a non-threshold criterion 

is developed for beryllium because 

tumors have been produced in animals 

at a site removed from the site of 

administration; in contrast. a threshold 

criterion is recommended for nickel 

because there is no evidence of tumors 

at sites distant resulting from 

administration of nickel solutions by 

either ingestion or injection. 

For those compounds which were not 

reported to induce carcinogenic effects 

or for those compounds for which 

carcinogenic data are lacking or 

insufficient. an attempt is made to 

estimate a no-effect level. In many 

respects. the hazard evaluation from 

these studies is similar to that of 

bioassays for carcinogenicity. In order 

to more closely approximate conditions 

of human exposure, preference is given 

to chronic studies involving oral 

exposures in water or diet over a 

significant portion of the animal life 

span. Greatest confidence is placed in 

those studies which demonstrate doserelated adverse effects as well as noeffect levels. 

There is considerable variability in 

the biological endpoints used to define a 

no-effect level. They may range from 

gross effects, such as mortality. to more 

subtle biochemical. physiological. or 

pathological changes. Teratogenicity, 

reproductive impairment, and 

behavioral effects are significant toxic 

consequences of environmental 

contamination. In instances where 

carcinogenic or other chronic effects 

occur at exposure levels below those 

causing teratogenicity. reproductive 

impairment. or behavioral effects. the 

former are used in deriving the criterion. 

For most of the compounds evaluated 

thus far. teratogenicity and reproductive 

impairment occur at doses near 

. maximum tolerated levels with dose 

administration schedules well above 

estimated environmental exposure 

levels. Moreover. information on 

behavioral effects. which could be of 
79350 Federal Register / Vol. 45, No. 231 / Friday, November 28, 1980 / Notices 

significance, is not available for most of 

the compounds under study. 

Consequently. most NOAELs derived 

from chronic studies are based either on 

gross toxic effects or on effects directly 

related to functional impairment or 

defined pathological lesions. 

For compounds on which adequate 

chronic toxicity studies are not 

available. studies on acute and subacute 

toxicity assume greater significance. 

Acute toxicity studies usually involve 

. single exposures at lethal or near lethal 

doses. Subacute studies often involve 

exposures exceeding 10 percent of the 

life span of the test organism. e.g.• 90 

days for the rat with an average life 

span of 30 months. Such studies are useful in establishing the nature of the 

compound's toxic effects and other 

parameters of compound toxicity, such 

as target organ effects. metabolic 

behavior. physiological/biochemical 

effects, and patterns of relention and 

tissue distribution. The utility of acute 

and subacute studies in deriving 

environmentally meaningful NOELs is 

uncertain, although McNamara (1976) 

has developed application factors for 

such derivations. 

In some cases where adequate data are not available from studies utilizing 

oral routes of administration, no-effect 

levels for oral exposures may be 

estimated from dermal or inhalation 

studies. Such estimates involve 

approximationlf of the total dose 

administered based on assumptions.. . about breathing rates and/or magnitude· 

of absorption. 

D. Criterion Rationale 

This section reviews existing 


standards for the chemical(s), 


summarizes data on ·current levels of 


human exposure, attempts to identify 


special groups at risk, and defines the 


basis for the recommended criterion. 


Information on existing standards is 

included primarily for comparison with 

the proposed water quality criteria. 

Some of the present standards, such as those recommended by the 

Occupational Safety and Health 

Administration (OSHA) or the American 

Conference of Governmental Industrial 

Hygienists (ACGlH), are based on toxicologic.data but are intended as 

acceptable levels for occupational 

rather than environmental exposure. 

Other levels. such as those 

recommended by the National Academy 

of Sciences in Drinking Water and 

Health (1977) or in the U.S. EPA Interim 

Primary Drinking Water Standards. are 

more closely related to proposed water 

quality criteria. Emphasis is placed on 

detailing the basis for the existing 

standards wherever possible. 

Summaries of current levels of human 

exposure. presented in this section, 

specifically address the suitability of the 

data to derive water quality criteria. The 

identification of special groups at risk, 

either because of geographical or 

occupational differences in exposure or 

biological differences in susceptibility to 

the compound(s), focuses on the impact 

that these groups should have on the 

development of water quality criteria. 

The basis for the recommended 

crileria section summarizes and 

qualifies all of the data used in 

developing the criteria. 

IV. Guidelines for Criteria Derivation 

The derivation of water quality 

criteria from laboratory animal toxicity 

data is essentially atwo-step procedure. 

First, a total daily intake for humans 

must be estimated which establishes 

either a defined level of risk for nOnthreshold effects or a no-effect level for 

threshold effects. Secondly, assumptions 

must be made about the contribution of 

contaminated water and the 

consumption of fish/shellfish to the total 

daily intake of the chemical. These 

estimates are then used to establish the 

tolerable daily intake and consequently 

the water quality criterion. 

A. Non-Threshold Effects 

After the decision has been made that 

a compound has the potential for 

causing cancers in humans and that 

data exist which permit the derivation 

of a criterion. the water concentration 

which is estimated to cause a lifetime 

carcinogenic risk of 10- 5 is determined. 

The lifetime carCinogenicity risk is the 

probability tha t a person would get cancer sometime in his or her life 

assuming continuous exposure to the 

compound. The water concentration is 

calculated by USing the low-dose 

extrapolation procedure proposed by 

Crump (1980). This procedure is an 

improvement on the multistage low dose 

extrapolation procedure by Crump. et al. 

(1977). 

The data used for quantitative 

estimates are of two types: (1) lifetime 

animal studies. and (2) human studies 

where excess cancer risk has been 

associated with exposure to the agent. 

In animal studies it is assumed. unless 

evidence exists to the contrary, that if a 

carcinogenic response occurs at the 

dose levels used in the study. then 

proportionately lower responses will 

also occur at all lower doses. with an 

incidence determined by the 

extrapolation model discussed below. 

1. Choice of Model. 

There is no really solid scientific basis 

for any mathematical extrapolation ­

model which relates carcinogen 

exposure to cancer risks at the 

extremely low levels of concentration 

that must be dealt with in evaluating the 

environmental hazards. For practical 

reasons, such low levels of risk cannot 

be measured directly either using animal 

experiments or epidemiologic studies. 

We must. therefore. depend on our 

current understanding of the 

mechanisms of carcinogenesis for 

guidance as to which risk model to use. 

At the present time. the dominant view 

of the carcinogenic process involves the 

concept that most agents which cause 

cancer also cause irreversible damage to 

DNA This position is reflected by the 

fact that a very large proportion of 

agents which cause cancer are .. also 

mutagenic. There is reason to expect 

that the quantal type of biological 

response that is characteristic of 

mutagenesis is associated with a linear 

non-threshold dose-response 

relationship. Indeed. there is substantial 

evidence from mutagenesis studies with 

both ionizing radiation and with a wide 

Variety of chemicals that this type of 

dose-response model is the appropriate 

one to use. This is particularly true at 

the lower end of the dose-response 

curve; at higher doses. there can be an 

upward curvature. probably reflecting 

the effects of multistage processes on 

the mutagenic response. The linear nonthreshold dose-response relationship is 

also consistent with the relatively few 

epidemiological studies of cancer 

responses to specific agents that. contain 

enough information to make the 

evaluation possible (e.g.• radiationinduced leukemia. breast and thyroid 

cancer. skin cancer induced by arsenic 

in drinking water. and liver cancer 

induced by aflatoxin in the diet). There 

. is also some evidence from animal 

experiments that is consistent with the 

linear non-threshold hypothesis (e.g .• 

liver tumors induced in mice by 2­

acetylaminofluorene in the large scale 

EDoI study at the National Center of 

Toxicological Research. and the 

initiation stage of the two-stage 

carcinogenesis model in the rat liver and 

the mouse skin). 

Because it has the best, albeit limited. 

scientific basis of any of the current 

ma!hematical extrapolation models, the 

linear non-threshold model has been 

adopted as the primary basis for risk 

extrapolation to low levels of the doseresponse relationship. The risk 

assessments made with this model 

should be regarded as conservative, 

representing the most plausible upper 

limit for the risk; i.e., the true risk is not 

likely to be higher than the estimate. but 

it could be smaller. 

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Federal Register! VoL 45, No. 231 I Friday, November 28, 1980 I Notices 79351 

The mathematical fDrmulation chDsen 

to' describe the linear. nDn-threshDld 

dDse-response relationship at low doses 

is the imprDved multistage mDdel 

develDped by Crump (1980]. This model 

employs enDugh arbitrary constants to' 

be able to' fit almDst any monotDnically 

increasing dose-response data and it 

incorporates a prDcedure for estimating 

the largest pDssible linear slope (in the 

95 percent cDnfidence limit sense] at low 

extrapDlated dDses that is cDnsistent 

with the data at all dDse levels of the 

experiment. Fur this reason. it may be 

called a "linearized" multistage model. 

2. PrDcedure of LDw-DDse 


ExtrapDlatiDn Based Dn Animal 


Carcinogenicity Data. 


A. Description of the Extrapolation 

Model 

Let P(d] represent the lifetime risk 

(prDbability} of cancer at dose d .. The 

multistage model has the form 

p(d)=l-exp [-(q.+qt d+q.d2+ ..• +qkdk)) 

where: 

ql~O, and i=O, 1, 2••••• k 

Equivalently. 

A(d)=l-exp (-(q,d+q.d2+ ..• +qkdk)) 

where: 

. A(d) == P(d) - P{o), 

1 	- P(o) 

is the extra risk over background rate at 

dose d. 

The point estimate of the coefficients 

ql. i=O. I, 2•..• ,k. and consequently 

the extra risk function A(d) at any given 

dDse d. is calculated by maximizing the 

likelihood functiDn of the data. 

The point estimate and the 95 percent 

upper confidence limit of the extra risk 

A(d) are calculated by using the 

computer program GLOBAL 79 

developed by Crump and Watson (1979). 

Upper 95 percent confidence limits on 

> 	 the extra risk and lower 95 percent 

cDnfidence limits on the dDse producing 

a given risk are determined frDm a 95 

percent upper confidence limit. qt·, on 

parameter ql. Whenever ql ;cO. at IDW 

dDses extra risk A(d) has apprDximately 

the form A(d)=qlxd. Therefore. qlXa 

is a 95 percent upper confidence limit on 

the extra risk and R/ql* is a 95 percent 

lower confidence limit on the dose 

producing an extra risk of R. Let Lo be 

the maximum value of the 10g-likelihoDd 

function. The upper limit ql * is 

calculated buy increasing ql to a vah,le 

qt· such that when the log-likelihood is 

again maximized subject to this fixed 

value ql * for the linear coefficient, the 

resulting maximum value of the IDglikelihood Ll satisfies the equatiDn 

20"..0-Lt)=2.70554 

where 2.70554 is the cumulative 90 

percent point of the chi-square 

distribution with one degree of freedom. 

which correspDnds to a 95 percent upper 

limit (Dne-sided). This approach of 

cDmputing the upper cDnfidence limit for 

the extra risk A(d] is an improvement on 

the Crump, et al. (1977} model. The 

upper confidence limit for the extra risk 

calculated at low dDses is always linear. 

This is conceptually consistent with the 

linear non threshold cDncept discussed 

earlier. The slope q,. is taken as an 

upper bDund Df the potency of the 

cpemical in inducing cancer at IDW 

doses. 

In fitting the dose-response model. the 

number of terms in the polynomial g is 

chosen equal to [h-1). where h is the 

number of dose groups in the 

experiment. including the control group. 

Whenever the multistage mDdel dDes 

nDt fit the data sufficiently. data at the 

highest dose is deleted and the model is 

refitted to the rest of the data. This is 

continued until an acceptable fit to the 

data is obtained. To determine whether 

or nDt a fit is acceptable. the chi-square 

statistic: 

h 

X2 (Xi - Ni Pi)2 = 

NiPi (1 - Pi) i=1 . is calculated. where NI is the number of 

animals in the i

lb dose group. XI is the 

number of animals in the jib dDse group 

with a tumDr response. PI is the 

probability of a response in the ith dose 

group estimated by Jitting the multistage 

model to the data. and h is the number 

of remaining groups. 

The fit is determined to be • unacceptable whenever chi-square (XI) 

is larger than the cumulative 99 percent 

point of the chi-square distributiDn with 

f degrees of freedom, where f equals the 

number of dose groups minus the 

number of non-zerO' multistage 

cDefficients. 

3. Selection and Form of Data used to 

Estimate Parameters in the 

ExtrapDlation Model. 

FDr some chemicals. several studies in 

different animal species. strains. and 

sexes each conducted at several dDses 

and different routes of exposure are 

available. A chDice must be made as to 

which of the data sets from several 

studies are to be used in the model. It is 

alsO' necessary to CDrrect fDr metabolism 

differences between species-and for 

differences in absorption via different 

routes of administratiDn. The 

procedures. listed below, used in 

evaluating these data are cDnslstent 

with the estimate of a maximum-likely.. 

risk. 

a. The tumor incidence data are separated according to organ sites or 

tumor types. The set data (i.e., dose and 

tumor incidence) used in the model is 

set where the incidence is statistically 

significantly higher than the control fDr 

at leas"Dne test dose level and/or 

where the tumor incidence rate shows a 

statistically significant trend with 

respect to dose level. The data set which 

gives the highest estimate of lifetime 

carcinogenic risk qt· is selected in most 

cases. HDwever. efforts are made to 

exclude data sets which produce 

spuriDusly high risk estimates because 

of a small number of animals. That is. if 

two sets of data ShDW a similar dDseresponse relationship and one has a very small sample size, the set of data 

which has the larger sample size is 

selected fDr calculating the carcinogenic 

potency. 

b. If there are two or more data sets of 

comparable size which are identical 

with respect to species. strain. sex. and 

tumor sites, the geometric mean Df ql•• 

estimated from each of these data sets is 

used for risk assessment. The geometric 

mean of numbers Al•A,••••• Am is 

defined as (AlxA,x ••• XAmP/m c. Ifsufficient data exist for two or 

more significant tumor sites in the same study, the number Df animals with at 

least one of the specific tumor sites 

under consideration is used as incidence 

data in the model. 

d. Following the suggestion of Mantel 

and Schneiderman {1975]. we assume 

that mg/surface area/day is an 

equivalent dose between species. Since 

to a close approximation the surface 

area is proportional to' the o/ards power 

of the weight as would be the case for a 

perfect sphere, the expO'sure in mgt o/srds 

power of the body weight/day is 

similarly considered to bean equivalent 

exposure. In an animal experiment. this 

equivalent dDse is computed in the 

following manner: Let: 

L.=duration of experiment 

I.=duration of exposure 

m=average dose per day in mg during 

adrilinistration of the agent (I.e .• during 1.) 

W =average weight of the experimental 

anilnal. 

Then. the lifetime average exposure is 

le X m 

d • ----:O=~ Le X W2/3 

Often exposures are ~Dt given in units 

ofmg/day. and it becomes necessary to' 

convert the given exposures into mgt 

day. FDr example. in most feeding 

studies. exposure is expressed as ppm in 

the diet. In this case the exposure (mgl 

day) is derived by: m=ppm X F X r 
79352 Federal Register r Vol. 45, No. 231 I Friday, November 28. 1980 I Notices 

-== 

where ppm is parts per million of the Case 1 	 of species, it follows that m=k W2/s x v 

carcinogenic agent in the diet. F is the 

weight of the food consumed per day in 

kgm,s. and r is the absorption fraction. 

In the absence of any data to the 

contrary. r is assumed to be one. For a 

uniform diet the weight of the food 

consumed is proportional to the calories :d 

~ : 	 required. which, in tum. is proportional 

to the surface area or the %rds power of 

the weight. so that: mappm X \y2/ 3X r or 

m ppm Cl 

rW2/ 3 

As a result. ppm in the diet is often 

assumed to be an equivalent exposure 

between species. However. we feel that 

this is not justified since the calories/kg 

of food is significantly different in the 

diet of man vs. laboratory animals, 

primarily due to moisture content 

differences. Instead. we use an 

empirically derived food factor, f=F/W, 

which is the fraction of a species body 

weight that is consumed per day as 

food. We use the rates given below. 

species w 

Man .......................................................................... 70 0.028 
 Rat ........................................................................... 0.35 0.05 
 Mice .............................................................•........... 0.03 0.13 


Thus, when the exposure is given as a certain dietary concentration in ppm, the 

exposure in mg/W21 3 is 

m = ppm x F = 
 ,

Ii 

" r x W2/3 W2/3
 .. ppm x fxW = ppm x f x Wl/3 . W2/3 

When exposure is given in terms of 

mg/kg/day=m/Wr=s the conversion is 

simply: 

m .. S X Wl/3 

rW2/3 

When exposure is via inhalation. the 

calculation of dose can be considered 

for two cases where (1) the carcinogenic 

agent is either a completely watersoluble gas or an aerosol and is . 

absorbed proportionally to the amount 

of air breathed in, and (2) where the 

carcinogen is a poorly water-soluble gas 

which reaches an equilibrium between 

the air breathed and the body 

compartments. After equilibrium is 

reached. the rate of absorption of these 

agents is expected to be proportional to 

metabolic rate, which in tum is 

proportional to the rate of oxygen 

consumption, which in turn is a function 

of surface area. 

Agents that are in the form of 

particulate matter or virtually 

completely absorbed gases such as SO, 

can reasonably be expected to be 

absorbed proportional to the breathing 

rate. In this case the exposure in mg/day 

may be expressed as: m=IXvXr where 

I is inhalation rate per day in mS. v is 

mg/m 3 of the agent in air, and r is the 

absorption fraction. 

The inhalation rates. I, for various 

species can be calculated from the 

observation (FASEB. 1974) that 25 gm 

mice breathe 34.5 liters/day and 113 gm 

rats breathe 105 liters/day. For mice and 

rats of other weights. W. (expressed in 

kg). the surface area proportionality can be used to determine breathing rates (in m3/day) as follows: . For mice. 1=0.0345 (W/0.025)21 'm3/ 

day 

For rats. 1=0.105 (W/0.113) 2/ 'ms

/day 

For humans, the values of 20 m3/day· 

is adopted as a standard breathing rate 

(ICRP. 1977). 

The equivalent exposure in mg/W2/s 

for these agents can be derived from the 

air intake data in a way analogous to 

the food intake data. The empirical 

factors for the air intake per kg per day. 

i=I/W based upon the previously stated 

relationships. are as tabulated below: 

i=1I Species w W 

Man ............................................................................ 70 0.29 
 Rat ............................................................................. 0.35 0.64 
 Mice ............................................... , ............. _ ......._. 0.03 1.3 


Therefore. for particulates or completely 

absorbed gases. the equivalent exposure 

in mg/W2T3 is: 

m • Ivr. iWvr • iwl/3 vr 


W2/3 W2/3 W2/3 


In the absence of empirical data or a 

sound theoretical argument to the 

contrary, the fraction absorbed. r, is 

assumed to be the same for all species. 

Case 2 

The dose in mg/day of partially 

soluble vapors is proportional to the ~ 

consumption which in turn is 

proportional to W2/s and to the 

solubility of gas in body fluids, which 

can be expressed as an absorption 

coefficient r for the gas. Therefore, when 

expressing the 0, consumption as O,=k 

W2/3, where k is a constant independent 

• From "Recommendation of the International 

Commission on Radiological Protection." page 9. the 

average breathing rate is 10'em' per &-hour work 

day and ZX10' em' in Z4 hours. 

x r or 

d.. m .. kvr 

W2/3' 

As with Case 1. in the absence of 

experimental information or a sound 

theoretical argument to the contrary. the 

absorption fraction. r. is assumed to be 

the same for all species. Therefore, for 

these substances a certain concentration 

in ppm or p./m 3 in experimental animals 

is equivalent to the same concentration 

in humans. This is supported by the 

observation that the minimum alveolar 

concentration, necessary to produce a 

given "stage" of anesthesia. is similar in man and animals (Dripps. et a1. 1977). 

When the animals were exposed via the 

oral route and human exposure is via 

inhalation or vice-versa, the assumption 

is made. unless there is pharmacokinetic 

evidence to the contrary, that absorption 

is equal by either exposure route. e. If the duration of experiment (1...) is 

less than the natural· life span of the test 

animal (L). the slope ql·, or more 

generally the exponent g(d). is increased 

by multiplying a factor (L/L.P. We 

assume that if the average dose. d. is 

continued. the age specific rate of 

cancer will continue to increase as a 

constant function of the background 

rate. The age specific rates for humans 

increase at least by the 2nd power of the 

age and often by a considerably higher 

power. as demonstrated by Doll (1971). 

Thus, we would expect the cumulative 

tumor rate to increase by at least the 3rd 

power of age. Using this fact. we assume 

that the slope ql *, or more generally, the 

exponent g(d), would also increase by at 

least the 3rd power of agEf. As a result, if 

the slope ql· [or g(d)) is calculated at 

age 1.... we would expect that if the 

experiment had been continued for the 

full life span. L. at the given average 

exposure. the slope ql * [or g(d)) would 

have been increased by at least (L/L.P. 

This adjustment is conceptually 

consistent to the proportional hazard 

model proposed by Cox (1972) and the 

tim!!-to-tumor model considered by 

Crump, et al, (1977) where the 

probability of cancer at age t and dose d 

is given by P(d.t)=l-exp[-f(t)xg(d)] 

4. Calculation of Carcinogenic Potency 

Based on Human Data. If human 

epidemiology studies and sufficiently 

valid exposure information are available 

for the compound. they are always used 

in some way. If they show a 

carcinogenic effect. the data are 

analyzed to give an estimate of the 

linear dependence of cancer rates on 

lifetime average dose. which is 

equivalent to the factor ql •. If they show 
Federal Register IVoI. 45. No.- 231 I Friday. November 28. 1980 I Notices 79353 

v 

e 

In 

S 

e 

1 

IC 

in 

t 

d 

e 

d 

.e 

e 

It 

if 

y 

.e 

l 

'i 

no carcinogenic effect when positive 

animal evidence is available. then it is 

assumed that a risk does exist but it is 

smaller than could have been observed 

in the epidemiologic study, and an upper 

limit of the cancer incidence is 

calculated assuming hypothetically that 

the true incidence is just below the level 

of detection in the cohort studied. which 

is determined largely by the cohort size. 

Whenever possible. human data are 

used in perference to animal bioassay 

data. 

Inhuman studies, the response is 

measured in terms of the relative risk of 

the exposed cohort of individuals 

compared to the control group. In the 

analysis of this data. it is assumed that 

the excess risk. or relative risk minus 

one. R(X) -1. is proportional to the 

lifetime average exposure. X. and that it 

is the same for all ages. It follows that 

the carcinogenic potency is equal to _ 

[R(X)-l]/X multiplied by the lifetime 

risk at that site in the generar 

popula tion. Except for an unusually 

well-documented human study, the 

confidence limit for the excess risk is 

not calculated. due to the difficulty in 

accounting for the uncertainty inherent 

in the data (exposure and cancer 

response). 

5. Calculation of Water Quality 

Criteria. After the value of ql" in (mg/ 

kg/day)"'1 has been determined. the 

lifetime risk. P. from an average daily 

exposure of x mg/kg/day is found from 

the equation P=ql·x. Therefore. if the 

lifetime risk is set at P=10- 5 for 

calculation purposes. the intake. I, in 

mg/ day for a 70 kg person can be found 

by the equation: 1=70X 10- 5

/ql" 

The intake of the agent from ambient 

water is assumed to come from two 

sources: (1) drinking an average of 2 

liters of water per day, and (2) ingesting 

an average of 6.5 grams of fish per day. 

Because of accumulation of residues in 

fish. the amount of the pollutant in fish 

(mg/kg of edible fish) is equal to a factor 

R times the water concentration (mg/kg 

of water). Therefore, the total intake I 

can be written as sum of two terms: 

I(mg/day)=C(mg/l)XR(l/kg 

fish) X 0.0065 kg fish/day + C(mg/l X 21/ 

day=C(2+0.0065R) where C is the 

water concentration in mg/1. Therefore. 

the water concentration in mg/l . 

corresponding to a lifetime risk of 10-a 

for a 70 kg person is calculated by the 

formula: 

70 X 10-5 c .. 01*(2 + 0.0065 R} 

B. Threshold Effects 

1. Use of Animal Toxicity Data (Oral). 

In developing guidelines for deriving 

criteria based on noncarcinogenic 

responses, five types of response levels 

are considered: 

NOEL-No-Observed-Effect-Level 

NOAEL-No-Observed-Adverse-Effect-Level 

LOEL-Lowest-Observed-Effect-Level 

WAEL-Lowest-Observed-Adverse-EffectLevel· 

FEL-Frank-Effect-Level 

Adverse effects are defined as any 

effects which result in functional 

impairment and/or pathological lesions 

which may affect the performance of the 

whole organism, or which reduce an 

organism's ability to respond to an additional challenge. 

One of the major problems 

encountered in consideration of these 

concepts regards the reporting of 

"observed effect levels" as contrasted to 

"observed adverse effect levels". The 

terms "adverse" vs. "not adverse" are at 

times satisfactorily defined. but due to 

increasingly sophisticated testing 

protocols. more subtle responses are 

being identified. resulting in a need for 

judgment regarding the exact definition 

of adversity. 

The concepts listed above (NOEL, 

NOAEL, LOEL, LOAEL) have received 

much attention because they represent 

landmarks which help to define the 

threshold region in specific experiments. 

Thus, if a single experiment yields a 

NOEL. a NOAEL. a LOAEL. and a 

clearly defined FEL in relatively closely 

spaced doses •. the threshold region has 

been relatively well defined; such data 

are very useful for the purpose of 

deriving a criterion. On the other hand. a 

clearly defined FEL has little utility in 

establishing criteria when it stands 

alone, because such a level gives no 

indication how far removed the data 

point is from the threshold region. 

Similarly, a free-standing NOEL has 

little utility, because there is no 

indication of its proximity to the LOEL, 

since a free-standing NOEL may be 

many orders of magnitude below the 

threshold region. 

Based on the above dose-response 

classU'ica tion system. the following 

guidelines for deriving criteria have 

been adopted: a. A free-standiilg FEL is unsuitable 

for the deriva:tion of criteria. 

b. A free-standing NOEL is unsditable 

for the derivation of criteria. Ifmultiple 

NOELs are available without additional 

data on LOELs, NOAELs. or LOAELs. . 

the highest NOEL should be used to 

derive a criterion. c. A NOAEL. LOEL, 01' LOAEL can be 

suitable for criteria derivation. A well· 

defined NOAEL from a chronic (at least 

OO-day) study may be used directly, 

applying the appropriate uncertainty 

factor. For a LOEL. a judgment needs to 

be made whether it actually corresponds 

to a NOAEL or a LOAEL. In the case of 

a LOAEL. an additional uncertainty 

factor is applied; the magnitude of the 

additional uncertainty factor is 

judgmental and sho\lld lie in the range of 

1 to 10. Caution must be exercised not to 

substitute "Frank-Effect-Levels" for 

"Lowest-Observable-Adverse-EffectLevels". ' 

d. If for reasonably closely spaced 

doses only a NOEL and a LOAEL of 

equal quality are available. then the 

appropriate uncertainty factor is applied 

to the NOEL. 

In using this approach, the selection 

and justification of uncertainty factors 

are critical. The basic definition and 

guidelines for using uncertainty factors 

has been given by the National 

Academy of Sciences (1977). "Safety 

Factor" or "Uncertainty Factor" is 

defined as a number that reflects the 

degree or amount of uncertainty that 

must be considered when experimental 

data in animals are extrapolated to man. 

When the quality and quantity of 

experimental data are satisfactory. a 

low uncertainty factor is used; when 

data is judged to be inadequate or 

equivocal. a larger uncertainty factor is 

used. The following general guidelines 

have been adopted in establishing the 

uncertainty factors: 

a. Valid experimental results from 

s~udies on prolonged ingestion by man. with no indication of carcinogenicity. 

Uncertainty Factor=10 

b. Experimental results of studies of 

human ingestion not availabl~ or scanty 

(e.g.• acute exposure only) with valid 

results of long-term feeding studies on 

experimental animals. or in the absence 

of human studies. valid animal studies 

on one or more species. No indication of 

carcinogenicity. Uncertainty Factor = 100 

c. No long-term or acute human data. 

Scanty results on experimental animals 

with no indication of carcinogenicity. 

Uncertainty Factor = 1.000 

Considerable judgment must be used in 

selecting the appropriate safety factors 

for deriving a criterion. In those cases 

where the data do not completely fulfill 

the conditions for one category and 

appear to be intermediate between two 

categories an intermediate uncertainty 

factor is used. Such an intermediate 

uncertainty factor may be developed 

based on a logarithmic scale (e.g .. 33. 

being halfway between 10 and 100 on a 

logarithmic scale). 

In determining the appropriate use of 

the uncertainty factors, the phrase "no 
79354 Federal Register I Vol. 45. No. 231 I Friday.- November 28. 1980 I Notices·

indication of carcinogenicity" is 

interpreted as the absence of 

carcinogenicity data from animal 

experimental studies or human 

epidemiology. Available short-term 

carcinogenicity screening tests are ­

reported in the criteria documents. but 

they are not used either for derivation of 

numerical criteria nor to rule out the 

uncertainty factor approach. 

Because of the high degree of 

judgment involved in the selection of a 

• 	 safety factor. the criterion derivation 

section of each document should 

provide a detailed discussion and 

justification for both the selection of the 

safety factor and the data to which it is 

applied. This discussion should reflect a 

critical review of the available data 

base. Factors to be considered include 

number of animals. species. and 

parameters tested; quality of controls; 

dose levels; route; and dosing schedules. 

An effort should be made to 

differentiate between results which 

constitute a toxicologically sufficient 

data base and data which may be 

spurious in nature. 

2. Use of Acceptable Daily Intake 

(ADI). For carcinogens. the assumption 

of low dose linearity precludes the 

necessity for defining total exposure in 

the estimation of increased incremental 

risk. For non-carcinogens. ADIs and 

criteria derived therefrom are calculated 

from total exposure data that include 

contributions from the diet and air. The 

equation used to derive the criterion (C) . 

is: G=ADI-(DT+IN)/[21+(0.OO65 kg 

x R)] where 21 is assumed daily water 

consumption. 0.0065 kg is assumed daily 

fish consumption. R is bioconcentration 

factor in units of I/kg. DT is estimated 

non-fish dietary intake. and IN is 

estimated daily intake by inhalation. 

If estimates of IN and DT cannot be 

provided from experimental data. an 

assumption must be made concerning 

total exposure. It is recognized that 

either the inability to estimate DT and 

IN due to lack of data or the wide 

variability in DT and IN in different 

states may add an additional element of 

uncertainty to the criterion formulation 

process. In terms of scientific validity. 

the accurate estimate of the Acceptable 

Daily Intake is the major factor in 

satisfactory derivation of water quality 

criteria. 

3. Use of Threshold Limit Values or 

Animal Inhalation Studies. Threshold 

Limit Values (TLVs) are established by 

the American Conference of 

Governmental and Industrial Hygienists 

(ACGIH) and represent a.hour timeweighted average concentrations in air 

that are intended to protect workers 

from various adverse health effects over 

a normal working lifetime. Similar 

values are set by NIOSH (criteria) and 

OSHA (standards) for 10- and 8-hour 

exposures. respectively. To the extent 

that these values are based on sound 

toxicologic assessments and have been 

protective in the work environment. they 

provide useful information for deriving 

or evaluating water quality criteria. 

However. each TLV must be carefully 

examined to determine if the basis of 

the TLV contains data which can be 

used directly to derive a water quality 

criterion using the uncertainty factor 

approach. In addition. the history of 

each TLV must be examined to assess 

the extent to which it has assured 

worker safety. In each case. the types of 

effects against which TLVs are designed 

to protect are examined in terms of their 

relevance to exposure from water. It 

must be demonstrated that the chemical 

is not a localized irritant and that there 

is no significant effect at the site of 

entry irrespective of the routes of 

exposure (i.e .• oral or inhalation). 

If the TLV or similar value is 

recommended as the basis of the 

criterion. consideration of the above. 

points is explicitly stated in the criterion 

derivation section of the document. 

Particular emphasis is placed on the 

quality of the TLV relative to the 

available toxicity data that normally is 

given priority over TLVs or similar 

established values. If the TLV can be 

justified as the basis for the cirterion. 

then the problems associated with the 

estimation of acceptable oral doses from 

inhalation data must be addressed. 

Estimating equivalencies of doseresponse relationships from one route of 

exposure to another introduces an 

additional element of uncertainty in the 

derivation of criteria. Consequently. 

whenever possible. ambient water 

quality criteria should be based on data 

involving oral exposures. if oral data are 

insufficient. data from other routes of 

exposure may be useful in the criterion 

derivation process. ­

Inhalation data. including TLVs or 

similar values. are the most common 

alternatives to oral data. Estimates of 

equivalent doses can be based upon: (1) 

available pharmacokinetic data for oral 

and inhalation routes. (2) measurements 

of absorption efficiency from ingested or 

inhaled chemicals. or (3) comparative 

excretion data when the associated 

metaboUc pathways are equivalent to 

those following oral ingestion or 

inhalation. Given that sufficient 

pharmacokinetic data are available. the 

use of accepted pharmacokinetic models 

provides the most satisfactory approach 

for dose conversions. However. if 

available pharmacokinetic data are 

marginal or of questionable quality. 

pharmacokinetic modeling is 

inappropriate. 

The Stokinger and Woodward (1958) 

approach. or similar models based on 

assumptions of breathing rate and 

absorption efficiency. represents 

possible alternatives when data are not 

sufficient to justify pharmacokinetic 

modeling. Such alternative approaches. 

however. provide less satisfactory 

approximations because they are not 

based on pharmacokinetic data. 

Consequently. in using the Stokinger 

and Woodward or related models. the 

uncertainties inherent in each of the 

assumptions and the basis of each 

assumption must be clearly stated in the 

derivation of the criterion. 

The use of data pertaining to other 

routes of exposure to derive water 

quality criteria may also be considered. 

As with inhalation data. an attempt is 

made to use accepted toxicologic and 

pharmacokinetic principles to estimate 

equivalent oral doses. If simplifying 

assumptions are used. their bases and 

limitations must be clearly specified. 

Because of the uncertainties involved 

in extrapolating from one route of 

exposure to another and the consequent 

limitations that this may place on the 

derived criterion. the decision to 

disallow such extrapolation and 

recommend no criterion is highly 

judgmental and must be made on a c~ 

by-case basis. A decision for or against 

criteria derivation must balance the 

quantity and quality of the available 

data against a perceived risk to the 

human population. 

If the Stokinger and Woodward (1958) 

approach is used to calculate an ADI 

from a TLV. the general equation is: 

ADI=TLVxBRxDExdxAA/(AoxSF) 

where: 

ADI=Acceptable daily intake in mg 

TLV=Concentration in air in mg/m3 

DE = Duration of exposure in hours per day 

d=5 days/7 days 

AA=Efficiency of absorption from air 

Ao=Efficiency of absorption from oral 

exposure 

SF=Safety factor following guidelines given above·· 

BR=Amount of air breathed per day: assume 10m3 

For deriving an ADI from animal 

toxicity data. the equation is: 

ADI=CAXDE xdxAAxBRX70 kgl 

(BWAX AoX SF) where: 

ADI=Acceptable daily intake in mg 

CA=Concentration in air in mg/m3 

DE=Duration of exposure in hours per day 

d=Number of days exposed/number of days observed 

AA=Efficiency of absorption from air 

BR=Volume of air breathed per day in m3 

70 kg=Assumed human body weight 

BWA=Body weight of experimental animals 

in kg 
Federal Register I Vol. 45. No. 231 I Friday; November 28, 1980 I Notices 79355 

Ao=Efficiency of· absorption from oral 

exposure 

SF= Safety factor following guidelines given 

above. 

More formal pharmacokinetic models 

must be developed on a compound-bycompound basis. 

It should be noted that the safety 

factors used in the above formulae are 

intended to account for species 

variability. Consequently, the rug/ 

surface area/day conversion factor is 

not used in the derivation of toxicity 

based criterion. 

C. Organoleptic Criteria 

Organoleptic criteria define 

concentrations of materials which 

impart undesirable taste and/or odor to 

water. In developing and utilizing such 

criteria two factors must be appreciated: 

the limitations of most organoleptic data 

and the human health significance of 

organoleptic properties. 

The publications which report taste 

and odor thresholds are, with very few 

exceptions, cryptic in their descriptions 

of test methodologies. number of 

subjects tested, concentration: response 

relationships, and sensory 

characteristics at specific 

concentrations above threshold. Thus, 

the quality of organoleptic data is often 

significantly less than that of toxicologic 

data used in establishing other criteria. 

Consequently. a critical evaluation of 

the available organoleptic data must be 

made and the selection of the most 

appropriate data base for the criterion 

must be based on sound scientific 

judgment. 

Organoleptic criteria are not based on 

toxicologic information and have no 

direct relationship to potential adverse 

human health effects. Although 

sufficiently intense organol-eptic 

characteristics could result in depressed 

fluid intake which. in turn. might 

aggravate a variety of functional disease 

states (i.e.• kidney and circulatory 

diseases), such effects are not used in 

the derivation process of organoleptic 

criteria unless available data would 

indicate an indirect human health effect 

via decreased fluid consumption. 

criteria derived solely from organoleptic 

data are based upon aesthetic qualities 

only. 

Since organoleptic and human health 

effects criteria are based on different 

endpoints. a distinction must be made 

between these two sets_of information. 

In criteria summaries involving Itoth 

types of data. the following format is 

used: 

For comparison purposes. two approaches 

Were used to derive criterion levels for 

-.Based on available toxicity data. 

for the protection of public health the derived 

level is --. Using available organoleptic 

data. for controlling undesirable taste and 

odor quality of ambient water the estimated 

level is --. It should be recognized that 

organoleptic data as a basis for establishing a 

water quality criteria have no demonstrated 

relationship to potential adverse human 

health effects. 

In those instances where a level to 


limit toxicity cannot be derived. the 


following statement is to be 


appropriately inserted: 


Sufficient data are not available for 

---to derive a level which would 

protect against the potential toxicity of this 

compound. 

D. Criteria for Chemical Classes 

A chemical class is broadly defined as any group of chemical compounds which are reviewed in a single risk assessment 

document. In criterion derivation. 

isomers should be regarded as a part of 

a chemical class rather than as a single 

compound. A class criterion is an estimate of risk/safety which applies to 

more than one member of a class. It 

involves the use of available data on 

one or more chemicals of a class to 

derive criteria for other compounds of 

the same class in the event that there 

are insufficient data available to derive 

compound-specific criteria. 

A class criterion usually applies to 

each member of a class rather than to 

the sum of the compounds within the 

class. While the potential hazards of 

multiple toxicant exposure are not to be 

minimized. a criterion. by definition, 

most often applies to an individual 

compound. Exceptions may be made for 

complex mixtures which are produced. 

released. and toxicologically tested as 

mixtures (e.g., toxaphene and PCBs). For 

such exceptions. some attempt is made 

to assess the effects of environmental 

partitioning (i.e., different patterns of 

environmental transport and 

degradation) on the validity of the 

criterion. H these effects cannot be, 

assessed. an appropriate statement of 

, uncertainty should accompany the 

criterion. 

Since relatively minor structur.al 

changes within a class of compounds 

can have pronounced effects on their 

biological activities. reliance on class 

criteria should be minimized. Whenever 

sufficient toxicologic data are available 

on a chemical within a class. a 

compound-specific criterion should be 

derived. Nonetheless, for some chemical 

classes. scientific judgment may suggest 

a sufficient degree of similarity among 

chemicals within a class to justify a 

class criterion applicable to some of all 

members of a class. 

The development of a class criterion 

takes into consideration the following: 

1. A detailed review of the chemical and 

physical properties of chemicals within the 

group should be made. A close relationship 

within the class with respect to chemical 

acitivity would suggest a similar potential to 

reach common biological sites within tissues. 

Likewise. similar lipid solubilities would 

suggest the possibility of comparable 

absorption and tissue distribution. 

2. Qualitative and quantitative data for 

chemicals within the group are examined. 

Adequate toxicologic data on a number of 

compounds within a group provides a more 

reasonable basis for extrapolation to other 

chemicals of the same class than minimal 

data on ope chemical or a few chemicals 

within the group. 

3. Similarities in the nature of the 

toxicologic response to chemicals in the class 

provides additional support for the prediction 

that the response 10 olher members of the 

class may be similar. In contrast, where the 

biological response has been shown to differ 

markedly on a qualitative and quantitative 

basis for chemicals within a class. the 

extrapolation of a criterion to other members 

of that class is not appropriate. 

4. Additional support for the validity of 

extrapolation of a criterion to other members 

of a class could be provided by evidence of 

similar metabolic and pharmacokinetic data" 

for Borne members of the class. 

Based on the above considerations. it 

may be reasonable in some cases to 

divide a chemical class into various 

subclasses. Such divisions could be 

based on biological endpoints (e.g.• 

carcinogens/ non-carcinogens). potency. 

and/or sufficiency of data (e.g., a 

criterion for some members of a class 

but no criterion for others). While no a 

priori limits can be placed on the .extent 

of subclassification. each 

subclassification must be explicitly 

justified by the available data. 

Class criteria. if properly derived and 

supported. can constitute valid scientific 

assessments of potential risk/ safety. 

Conversely. the-development of a class 

criterion from an insufficient data base 

can lead to serious errors in 

underestimating or overestimating risk/ 

safety and should be rigorously avoided. 

Although scientific judgment has a 

proper role in the development of class 

criteria, such criteria are useful and 

defensible only if they are based on 

adequate~ata and scientific reasoning. 

The definition of sufficient data on 

similarities in physical, chemical, 

pharmacokinetic.-or toxicologic 

properties to justify a class criterion 

may vary markedly depending on the 

degree of structural similarity and the 

gravity of the per:ceived risk. 

Consequently. it is imperative that the 

criterion derivation section of each 

document in which a class criterion is 

recommended explicity address each of 

the key issues discussed above. and 

define. as clearly as possible. the 
79356 Federal Register l Vol. 45, No. 231 I l'rlOay, 1'10VeIJIuer "'0, ~~ou I !~v .....c" 

limitations of the proposed criterion as 

well as the type of daJa needed to 

generate a compound-specific criterion. 

A class criterion should be abandoned 

when there is sufficient data availabe to 

derive a compound-specific criterion 

which protects against the biological 

effect of primary concel'li;'e.g., the 

availability of a good subchronic study 

would not necessarily result in the 

abandonment of a class criterion based 

on potential carcinogenicity. 

The inability to derive a valid class 

criterion does not, and should not, 

preclude regulation of a compound or 

group of compounds based on concern 

for potential human health effects. The 

failure to recommend a criterion is 

simply a statement that the degree of 

concern cannot be quantified based on 

the available data and risk assessment 

methodology. 

E. Essential Elements 

Some chemicals. particularly certain 

metals, are essential to biological 

organisms at low levels but may be 

toxic andl or carcinogenic at high levels. 

Because of potential toxic effects, it is 

legitimate to establish criteria for such 

essential elements. However, criteria 

must consider essentiality and'cannot 

be established at levels which would 

result in deficiency of the element in the 

human population. 

Elements are accepted as essential if 

listed by NAS Food and Nutrition Board 

or a comparably qualified panel. 

Elements not yet determined to be 

essential but for which supportive data 

on essentiality exists need to be further 

reviewed by such a panel. 

To modify the toxicity and 

carcinogenicity based criteria, 

essentiality must be quantified either as 

a "recommended daily allowance" 

(RDA) or "minimum daily requirement" 

(MDR). These levels are then compared 

to estimated daily doses associated with 

the adverse effect of primary concern. 

The difference between the RDA or 

MDR and the daily doses causing a 

specified risk level for carcinogens or 

ADls for non-carcinogens defines the 

spread of daily doses from which the 

criterion may be derived. Because errors 

are inherent in defining both essential 

and maximum tolerable levels, the 

criterion is derived from dose levels 

near the center of such a dose range. 

The decision to use either the MDR or 

RDA is guided by the spread of the 

doses and the quality of the essentiality 

and toxicity estimates. 

The modification of criteria by 

consideration of essentiality must take . 

into account aU routes of exposure. If 

water is a significant source of the MDR 

or RDA, the criterion must allow for 

attainment of essential intake. 

Conversely, even when essentiality may 

be attained from nonwater sources, 

standard criteria derivation methods 

may be adjusted if the derived criterion 

represents a small fraction of the ADl or 

MDR. On a case-by-case basis, the 

modification in the use of the guidelines 

may include the use of different safety 

factors for non-carcinogens or other 

modifications which can be explicitly 

justified. 

F. Use ofExisting Standards 

For some chemicals for 'which criteria 

are to be established, drinking water 

standards already exist. These 

standard's represent not only a critical 

assessment of literature, but also a body 

of human experience since their 

promulgation. Therefore, it is valid to ' 

accept the existing standard unless 

there is compelling evidence to the 

contrary. This decision should be made 

after considering the existing standards 

vs. new scientific evidence which has 

accumulated since the standards have 

been established. There are several 

instances where the peer review process 

recommended usage of the present 

drinking water standards. 

Bibliog~aphy 

Albert. R.E., et al. 1977. Rationale 

developed by the Environmental Protection 

Agency for the assessment of carcinogenic 

risks. Jour. Natl. Can. Inst. 58: 1537. 

Cox, C.R. 1972. Regression model and life 

tables. Jour. Roy. Stat. Soc. B. 34: 187. 

Crump, KS. 1979. Dose-response problems 

in carcinogenesis. Biometrics. 35: 157. 

Crump. KS. 1980. An improved procedure 

for low-dose carcinogenic risk assessment 

from animal data. Jour. Environ. Path. 

Toxico!. (In press). 

Crump. KS. and W.W. Watson. 1979, 

GLOBAL 79. A FORTRAN program to 

extrapolate dichotomous animal 

carcinogenicity data to low dose. Nat!. Inst. 

Environ. Health Sci. Contract No. 1-ES-2123. 

Crump, KS., et al. 1977. Confidence 

intervals and test of hypotheses concerning 

dose·response relations inferred from animal 

carcinogenicity data. Biometri£s. 33: 437. 

Doll. R. 1971. Weibull distribution of cancer: Implications for models of 

carcinogenesis. Jour. Roy. Stat. Soc. A. 13: 

133. 

Dripps, R.D.. et al. 1977. Introduction to 

Anesthesia, the Principles of Safe Practice. 

5th ed. W.B. Saunders Co., Philadelphia, 

Pennsylvania. p. 121. 

Druckrey, H. 1967. Quantitative Aspects of 

Chemical Carcinogenesis. In: R. Turhaut (ed.), 

Potential Carcinogenic Hazards from Drugs, 

Evaluation of Risks. UICC Monograph Series. 

Vol. 7. Springer Verlag, New York. 

Federation of American Societies for 

Experimental Biology. 1974. Biological Data 

Books, 2nd ed. Vol. III. P.L. Altman and D.S. 

Dittment (eds.] Federation of American 

Societies for Experimental Biology. Bethesda, 

Maryland. Library of Congress No. 72-87738. 

Guess, H.. et al. 1977. Uncertanity 

estimates for low dose rate extrapolations of 

animal carcinogenicity data. Can. Res. 37: 

3475. 

Interagency Regulatory Liaison Group. 

1979. Scientific bases for identifying potential 

carcinogens and estimating their risks. 

February 6. 

International Commission on Radiological 

Protection. 1977. Recommendation of the 

ICRP, Pub!. No. 26. adopted January 17. 1977. 

Pergamon Press, Oxford. England. 

Mantel. N. and M.A. Schneiderman. 1975. 

Estimating "safe lave Is." a hazardous 

undertaking. Can. Res. 35: 1379. 

McNamara. B.P. 1976. Concepts in Health 

Evaluation of Commercial and Industrial 

Chemicals. In: M.A. Mehlman, et a!. (eds.). 

Advances in Modern Toxicology. Vol. 1, Part 

1. Wiley and Sons. New York. p. 61 

National Academy of Sciences. 1977. 


Drinking Water and Health. National 


Academy of Sciences. Washington, D.C. 


National Cancer Institute. 1976. Guidelines 

for carCinogen bioassay in small rodents. NCI 

Carcinogenesis Technical Report Series, No. 

1. February. 1976. 

Peto. R. 1973. Weibull distribution for 


continuous-carcinogenesis experiments. 


Biometrics. 29: 457. 


Stephan. C.E. 1980. Memorandum to J. 


Stara. U.S. EPA. July 3. 


Stokinger. M.E. and R.L. Woodward. 1958. 

Toxicologic methods for establishing drinking 

water standards. Jour. Am. Water Works 

Assoc. 50: 517. 

U.S. EPA. 1976. National Interim Primary 

Drinking Water Regulations. Office of Water 

Supply. EPA 570/9-76-003. U.S. Envlran. Prot. 

Agency. 

U.S. EPA. 1980. Seafood consumption data 

analysis. Stanford Research Institute 

International. Menlo Park, California. Final 

report, Task 11. Contract No. 68-{)1-3687. 

Veith. G.D.1980. Memorandum to C.R 


Stephan. U.S. EPA April 14. 


Veith. G.D., et a!. 1979. Measuring and 

estimating the bioconcentration factors of 

chemicals in fish. Jour. Fish Res. Board Can. 

36: 1040. 

Health Effects Methodology-Authors, 

Contributors and Reviewers 

Jerry F. Stara, ECAO-Cin, U.S. Environmental 

Protection Agency 

Elizabeth L. Anderson. OHEA. U.S. 

Environmental Protection Agency 

Roy E. Albert, N.Y. University Medical 

School. New York, NY . Patrick R. Durkin. Syracuse Research 

Corporation, Syracuse. NY 

Steven D. Lutkenhoff, ECAO, U.S. 

Environmental Protection Agency 

Robert E. McGaughy, CAC, U.S. 

Environmental Protection Agency 

Charles Ris. OHEA, U.S. Environmental 

Protection Agency 

Lawrence Anderson. CAG, U.S. 

Environmental Protection Agency 

Dolph Arnicar, CAG. U.S. Environmental 

Protection Agency 

Steven Bayaro, CAG. U.S. Environmental 

Protection Agency 

Edward Calabrese, University of 

Massachusetts, Amherst, MA 

Thomas Clarkson. University of Rochester, 

Rochester,NY 
Federal Re~ilrter tVol. 45, No. 231'/ Friday, November 28, 1980 / Notices 79357 

! 

I 


\ 


Joseph Cotruvo. ODW, U.S. Environmental 

Protection Agency 

Christopher DeRosa. ECAO-Cin. U.S. 


Environmenta! Protection Agency 


Kurt Enslein. Genesee Computer Center. Inc .. 

Syraeuse. NY 

Jeffrey Gaba. OGC. U.S. Environmental 


Protection Agency 


• 	 Frank Gostomski. OWRS. U.S. Environmental 

Protection Agency 

Daniel Greathouse. HERL-Cin. U.S. 

Environmental Protection Agency 

Joseph Arcos. Tulane University. New 

Orleans. LA 

Dev Barnes. OWRS. U.S. Environmental 

Protection Agency 

David L. Bayliss. CAG. U.S. Environmental 

Protection Agency 

Chao W. Chen. CAG. U.S. Environmental 

Protection Agency 

Herbert Cornish. University of Michigan. Ann 

Arbor. MJ 

Kenneth Crump. Science Research Systems. 

Ine.. Ruston. LA 

Michael Dourson, ECAO-Cin, U.S. 

Environmental Protection Agency 

John R. Fowle III; CAG. U.S. Environmental 

Protection Agency 

R. John Garner. HERL-Cin. U.s. 

Environmental Protection Agency 

T~rrence Grady, ECAO-Cin. U.S. 

Environmental Protection Agency 

Bernard Haberman. CAG. U.S. Environmental 

Protection Agency 

Paul Hammond. University of Cincinnati. 

Cincinnati. OH 

Charalingayya Hiremath. CAG. U.S. 

Environmental Protection Agency 

Dinko Kello, Institute for Medical Research 

and Occupational Health. Zagreb. Yugo. 

Chang S. Lao. CAG, U.S. Environmental 

Protection Agency 

Marvin Legator. University of Texas Medical 

Branch. Galveston, TX 

Jack McGinnity, OTS. U.S. Environmental 

Protection Agency 

Debdas Mukerjee. ECAO·Cin. U.S. 

Environmental Protection Agency 

Ellen O·F1aherty. University of Cincinnati. 

Cincinnati. OH 

Fred Passman. Energy Resources Co .. Inc. 

Cambridge. MA .. 

John F. Risher. ECAO·Cin. U.S. 

Environmental Protection Agency 

Jeffery Rosenblatt. OTS. U.S. Environmental 

Prote<:tion Agency 

Samuel Shibko, US FDA. Washington. DC 

Harry T. Skalsky, Reynolds Metal Company 

Todd W. Thorslund. CAG. U.S. 

Environmental Protection Agency 

Benjamin VanDuuren, N.Y. University 

Medical School. New York, NY 

James R. Withey. National Health and 

Welfare Canada, Ottawa. Canada 

Rolf Hartung. University of Michigan. Ann 

Arbor. MI 

Rudolf Jaeger. Harvard School of Public 

Health. Cambridge, MA 

Arnold M. Kuzmac.k. CAG. U.S. 

Environmental Protection Agency 

Si Duk Lee. ECAO-Cin. U.S. Environmental 

Protection Agency 

Leland McCabe, HERL-Cin. U.s. 

Environmental Protection Agency 

Myron Mehlman. Mobil Oil Corporation. New 

York. NY 

Jean Munson. University of Cincinnati. 


Cincinnati. OH 


Nancy Othmet. OGC. U.S. Environmental 


Protection Agency 


David J. Reisman. ECAO-Cin. U.S. 


Environmental Protection Agency 


Paula K Roberson. U.s. Environmental 


Protection Agency 


H. Daniel Roth. Roth Associates 

Dharm V. Singh. CAG. U.S. Environmental 

Protection Agency 

Robert G. Tardiff. National Academy of 

Sciences. Washington. DC 

Anne W. TrontelL Energy Resources Co., Inc.• 

Cambridge. MA . 

John Van Ryzin. Columbia University. New 

York. NY 

Ronald E. Wyzga. Electric Power Research 


Institute 


Appendix D-Response to Comments on 

Guidelines for Deriving Water Quality 

Criteria for the Protection of Aquatic 

Life and Its Uses 

IntroducUon 

Two versions of the Guidelines were 

published in the Federal Register for 

comment. The first version (43 FR 21506, 

May 18, 1978 and 43 FR 29028. July 5. 

1979) was simply published for 

comment. The second (44 FR 15926. 

March 15. 1979) was published as part of 

the request for comments on the water 

quality criteria for 27 of the 65 

pollutants. The second version was 

meant to be clearer and more detailed 

than the first. but very similar 

technically. Since the two versions were 

so similar, comments on both will be 

dealt with simultaneously. 

Many comments were received that 

no draft water quality criteria for any of 

the 65 pollutants should have been 

issued for public comment until the 

comments on the first version of the 

Guidelines had been dealt with 

adequately and the Guidelines changed 

appropriately. The comments on the first 

version were read and the Guidelines 

were revised in an attempt to make the 

second version dearer and more 

detailed than the first. However, an 

. extensive revision of the technical 

content of the Guidelines was not 

attempted between the first and second 

versions because the Agency was 

preparing water quality criteria based 

on the Guidelines. The Agency could 

have avoided this criticism simply by 

not publishing any version of the 

Guidelines for comment until March 15, 

1979. but this would have greatly 

reduced the length of time available for 

people to consider the Guidelines and 

comment on them. As it was. some 

people commented that the comment 

period announced on March 15, 1979. 

was too short. 

1. Comment-The procedures used to 

derive criteria in the "Red Book" were 

upheld in court and probably should still 

be used. 

Response-The procedures used in 

the Guidelines are similar to some of the 

procedllres used to develop criteria in / 

the "Green Book". "Blue Book", and 

"Red Book". The Guidelines are 

designed to be more objective and 

systematic, to deal more adequately 

with residues. and to incorporate the 

concept of a minimum data base. 

2. Comment-Criteria should be 

compilations of critically reviewed data 

with no synthesis or interpretation. 

Response-Neither P.L. 92-500 nor the 

Consent Decree specify the form which 

a criterion must take. The Consent 

Decree (para. 11, p. 14) specifies that 

such criteria "shall state, inter alia. 

recommended maximum permissible 

concentrations". Adequate precedents 

have been set in the "Green Book", 

"Blue Book", and "Red Book" for the 

form of criteria used in the Guidelines. 

3. Comment-The Guidelines and 

criteria should be developed by a 

consensus of aquatic toxicologists rather 

than by EPA personnel only. 

Response-EPA certainly wants the 

Guidelines and the criteria to be as good 

as possible and as acceptable to as 

many interested people as possible. To 

this end. EPA has widely distributed 

draft versions of the Guidelines and the 

criteria documents. discussed them with 

many people. considered the comments 

received. and made many significant 

technical changes and editorial 

revisions. It is questionable whether.or 

not a true consensus could have been 

reached by any means within the time 

available. In addition, EPA has a 

legislative responsibility which it should 

not delegate to someone else. 

4. Comment-The Guidelines should 

be updated regularly. 

Response-The Guidelines are not 

being promulgated as a regulation or 

directive. The purpose of presenting 

these Guidelines is to show how the 

water quality criteria for aquatic life 

were derived for the 65 pollutants. If 

EPA uses these Guidelines again, they 

willbe revised to take into account new 

data. concepts. and ideas. 

5. Comment-The objectives, purpose. 

and limitations of the Guidelines should 

be stated. 

Response-The introductory portion 

of the Guidelines has been expanded to 

address these subjects more fully. 

6. Comment-The Guidelines are too 

ambiguous. 

Response-The Guidelines have been 

revised and rewritten. partly to improve 

clarity and provide additional details. It 

is not possible to provide explicit details 

on all items: in some areas only general 

guidance can be provided at this time.