### --- - - ____-


### 3.1.3 GeneralConsiftt?mtions infffhmt 

### Characterization There are two possible ways to characterize an effluent to determine the need for effluent limits for the protection of aquatic life and human health. First, an assessment may be made without generating effluent data; second, an assessment may be conducted after effluent data have been generated. Regulatory authorities must determine whether a discharge causes, has the “reasonable potential” lo cause, or contributes to an excursion above an applicable narrative or numeric water quality criterion. An analysis of “reasonable potential” determines an effluent’s capability to cause such excursions.
In determining the need for a permit limit for whole effluent toxicity or for an individual toxicant, the regulatory authority is required to consider, ataminimum, existing controls on point and nonpoint sources of pollution, the variability of the pollutant or pollutant parameter in the effluent, the sensitivity ofthe involved species to toxicity testing (for whole effluent), and, where appropriate, the dilution of the effluent in the receiving water (40 CfR 122.44(d)(ii)).
The regulatory authority isalso required by NPDES regulations to consider whether technology-based limits are sufficient to maintain State water quality standards. There aretwo possibilities that will need to be assessed. First, ifthe limits based on appropriate treatment technology have already been specified in a previous permit, and ifthe facility isoperating at the required level, then historical effluent and receiving water information can be used. Second, ifthe facility hasyet to achieve the required technology performance (best available technology orbest conventional technology), the regulatory authority will need to assessthe technology-based limit for reasonable potential for causing orcontributing to an excursion above the water quality standard.
In addition, the regulatory authority should consider all other available data and information pertaining to the discharger to assist in making an informed judgment. Where both effluent testing data and important other factors exist, the regulatory authority will need to exercise discretion in the determination of the need for a limit. The authority should employ the principle of “independent application” of the data and information that characterizes the effluent. In other words, effluent data alone, showing toxicity at the RWC, may be adequate to demonstrate the need for a limit for toxicity or for individual toxicants. Likewise, other factors may form an adequate basisfor determining that limits are necessary. for example, where available dilution is low and monitoring information shows that toxic pollutants arefrequently discharged at concentrations that have caused toxicity when discharged from similar facilities, the permitting authority may reason that awhole effluent toxicity limit is necessary even without whole effluent toxicity data from the specific facility. In all cases, the decision must be based upon consideration of factors cited in 40 CfR 122.44(d)(l)(ii). The regulatory authority will need to prioritize, on a case-by-case basis,the importance ofalldata and information used in making a determination. To assist in case-by-case determinations, recommended guidelines for characterizing aneffluent for the need for a permit limit for whole effluent toxicity or individual toxicants arediscussed below and summarized in Boxes 3-l through 3-3.



### Box 3-1. Determining “Reasonable Potential” for Excursions Above Ambient Criteria Using Factors Other than Facility-specific Effluent Monitoring Data
When determining the “reasonable potential” of adischarge to cause an excursion above a State water quality standard, the regulatory authority must consider allthe factors listed in40 CFR122.44(d)(l)(ii). Examples ofthe types of information relating to these factors are listed below. Existina controls on mint and nonDoint sources of Dollution

l Industry type: Primary, secondary, raw materials used, products produced, best management practices,

control equipment, treatment efficiency, etc.

l Publicly owned treatment work type: Pretreatment, industrial loadings, number of taps, unit processes,

treatment efficiencies, chlorination/ammonia problems, etc. Variability ofthe oollutant or oollutant Darameter inthe effluent

l Compliance history

l Existing chemical data from discharge monitoring reports and applications. Sensitivitv ofthe sDeciesto toxicitv testing

l Adopted State water quality criteria, or EPAcriteria

l Any available in-stream survey data applied under independent application ofwater quality standards

l Receiving water type and designated/existing uses Dilution ofthe effluent inthe receivina water

l Dilution calculations

49

## 3.2 DETERMlWlNG THE NEED FOR PERYlTUMITS WITHOUT EFFLUENT MONITORING DATA FOR A SPECIFIC FACILITY

If the regulatory authority so chooses, or if the circumstances dictate, the authority may decide to develop and impose a permit limit for whole effluent toxicity or for individual toxicants without facility-specific effluent monitoring data, or prior to the generation of effluent data. Water quality-based permit limits can besetfor asingle toxicant orforwhole effluent toxicity based on the available dilution and the water quality criterion or the State standard in the absence offacility specific effluent monitoring data. However, in doing so,the regulatory authority must satisfy allthe requirements of 40 CfR 122.44(d)(l)(ii).
When determining whether or not a discharge causes, has the reasonable potential to cause, or contributes to anexcursion ofa numeric or narrative water quality criterion for individual toxicants orfor toxicity, the regulatory authority can useavariety of factors and information where facility-specific effluent monitoring data are unavailable. These factors alsoshould beconsidered with available effluent monitoring data. Some ofthese factors are the following:

l Dilution-Toxic impact isdirectly related to available dilution for the effluent. Dilution is related to the receiving stream flow and the size of the discharge. The lower the available dilution, the higher the potential for toxic effect. Ifan effluent’s concentration atthe edge of amixing zone in a receiving water is expected to reach 1 percent or higher during critical or worst-case design periods, then such an effluent may require atoxicity limit (seediscussion in Section 3.3.3). Assessment of the amount of stream dilution available should be made at the conditions required by the water quality standards or, ifnot specified in the standards, at the harmonic mean flow and the 7QlO flow. Figure 3-3 (Pg. 57) shows that, whereas amajority of NPDES permittees nationwide discharge to areas during annual mean flow ranging in dilution from 100 to 1,000, the majority of dischargers fall into the 1 to 10 dilution range during low-flow conditions.

l Type of industry-Although dischargers should be individually characterized because toxicity problems are sitespecific, the primary industrial categories should be of principal toxicity concern. EPA’s treatment technology data base generally suggests that secondary industrial categories may have less potential for toxicity than primary industries. However, based on experience, it is virtually impossible to generalize the toxicity of effluents with any certainty. Iftwo plants produce the same type of product, one effluent may be toxic while the other may not be toxic due to the type and efficiency of the treatment applied, general materials handling practices, and the functional target ofthe compound(s) being produced.

. Type of POTW-POTWs with loadings from indirect dischargers (particularly primary industries) may be candidates for toxicity limits. However, absence of industrial input does not guarantee an absence of POTW discharge toxicity problems. Forexample, commercial pesticide applicators often discharge to POT%%, resulting in pesticide concentrations in the POTW’s effluent. Household disposal of pesticides, detergents, or other toxics may have asimilar effect, The types of industrial users, their product lines, their raw materials, their potential and actual discharges, and their control equipment should beevaluated. POlWs should also be characterized for the possibility of chlorine and ammonia problems.

l Existing data on toxic pollutants-Discharge monitoring reports (DMRs) and data from NPDES permit application forms 2C and 2A may provide some indication ofthe presence of toxicants. The presence or absence of the 126 “priority pollutants” may or may not be an indication ofthe presence or absence of toxicity. There are thousands of “nonpriority” toxicants that may cause effluent toxicity. Also, combinations of several toxicants can produce ambient toxicity where the individual toxicants would not. EPA regulations at 40 CFR122.21 (j) require POTWs with design flows equal to or greater than 1 MC0 and POTWs with approved pretreatment programs, or POlWs required to develop a pretreatment program, to submit the results of whole effluent toxicity tests with their permit applications. These regulations also provide discretion to the permitting authority to request such data from other POlWs at the time of permit application.

l History ofcompliance problems and toxic impact-Reguiatory authorities may consider particular dischargers that have had difficulty complying with limits on toxicants or that have a history of known toxicity impacts as probable priority candidates for effluent toxicity limits.

l Type of receiving water and designated use-Regulatory authorities may compile data onwater quality. Examples of available data include fish advisories or bans, reports offish kilts, State lists of priority waterbodies, and State lists of waters that are not meeting water quality standards. Regulatory authorities should usethis information asa means of identifying point sources that discharge to impaired waterbodies and that thus may be contributing to this impairment. One source of this information isthe lists of waters generated by states to comply with Section 304(l) regulations at40 CFR130.1O(d)(6); 50 FR23897-98, June2, 1989: 1) Waters where fishing or shellfish bans and/or advisories are currently in effect or are anticipated; 2) Waters where there have been repeated fish kills or where abnormalities (cancers, lesions, tumors, etc.) have been observed in fish or other aquatic lifeduring the lastten years; 3) Waters where there are restrictions on water sports or recreational contact; 4) Waters identified by the state in its most recent state section 305(b) report aseither “partially achieving” or“not achieving” designated uses;



### so

### 5)

6)

7)



### 8)



### 9)

10)

11)

12)

13) Waters identified by the states under section 303(d) ofthe Clean Water Act aswaters needing water quality-based controls;
Waters identified by the state aspriority water bodies;
Waters where ambient data indicate potential or actual excursions of water quality criteria due to toxic pollutants from an industry classified asaprimary industry inAppendix Aof40 CFRPart 122;
Waters for which effluent toxicity test results indicate possible or actual excursions of state water quality standards, including narrative “free from” water quality criteria or EPAwater quality criteria where state criteria arenot available;
Waters with primary industrial major dischargers where dilution analyses indicate exceedances ofstate narrative or numeric water quality criteria (or EPAwater quality criteria where statestandards arenot available) fortoxic pollutants, ammonia, or chlorine; Waters with POlW dischargers requiring local pretreatment programs where dilution analysesindicate exceedances ofstate water quality criteria (or EPAwater quality criteria where state water quality criteria are not available) for toxic pollutants, ammonia, orchlorine;
Waters with facilities not included inthe previoustwo categories such asmajor POlWs, and industrial minor dischargers where dilution analyses indicate exceedances of numeric or narrative state water quality criteria (or EPA water quality criteria where state water quality criteria are not available) for toxic pollutants, ammonia, or chlorine;
Water classified for usesthat will not support the “fishable/swimmable” goals of the Clean Water Act;
Waters where ambient toxicity or adverse water quality conditions have been reported by local, state, EPAor other Federal Agencies, the private sector, public interest groups, or universities; 14) Waters identified bythe state asimpaired in its most recent Clean LakeAssessmentsconducted under 314 ofthe Clean Water Act; and 15) Surface waters impaired by pollutants from hazardous waste sites on the National Priority List prepared under section 105(8)(A) of CERCIA. 16) Waters judged to be impaired asa result of a bioassessmenttbiosurvey. The presence of a combination of these factors, such as low available dilution, high-quality receiving water, poor compliance record, and clustered industrial and municipal discharges, could constitute ahigh priority for effluent limits. Regardless, the regulatory authority, if it chooses to impose an effluent limit after conducting an effluent assessment without facility-specific monitoring data, will need to provide adequate justification for the limit in its permit development rationale or in itspermit fact sheet. Aclear and logical rationale for the need for the limit covering all of the regulatory points will be necessaryto defend the limit should it be challenged. Injustification of a limit, EPA recommends that the more information the authority can acquire to support the limit, the better a position the authority will be in to defend the limit if necessary. In such acase, the regulatory authority may well benefit from the collection of effluent monitoring data prior to establishing the limit.
Ifthe regulatory authority, after evaluating allavailable information on the effluent, inthe absence ofeffluent monitoring data, is not able to decide whether the discharge causes, has the reasonable potential to cause, or contributes to, an excursion above anumeric or narrative criterion for whole effluent toxicity or for individual toxicants, the authority should require whole effluent toxicity or chemical-specific testing to gather further evidence. In such acase, the regulatory authority can require the monitoring prior to permit issuance, ifsufficient time exists, or it may require the testing as a condition of the issued/ reissued permit.
Under these circumstances, the regulatory authority may find it protective ofwater quality to include apermit reopener for the imposition ofan effluent limit should the effluent testing establish that the discharge causes, has the reasonable potential to cause, orcontributes to excursion above awater quality criteria. Adiscussion ofthese options isprovided later in this chapter.



## 3.3 DETERMINING THE NEED FOR PERMIT UMITSWITH EFFLUENT MONITORING DATA

3.3.I GeneralConslderatlons When characterizing an effluent for the need for awhole effluent toxicity limit, and/or an individual toxicant limit, the regulatory authority should use any available effluent monitoring data, together with any information like that discussed under Section 3.2 above, asthe basis for a decision. The regulatory authority may already have effluent toxicity data available from previous monitoring, or it may decide to require the permittee to generate effluent monitoring data prior to permit issuance or asacondition of the issued permit. EPAregulations at 40 Cfi? 122.21 (j) require POTWs with design flows equal to or greater than 1 MCD and POTWs with approved pretreatment programs, or POTWs required to develop apretreatment program, to submit the results of whole effluent toxicity tests with their permit applications. These regulations also provide discretion to the permitting authority to request such data from additional POTWs atthe time of permit application.

51

### ----------- __- __--_ __-__ ----
Inthe instance where the permittee isrequired to generate data in advance, data collection should begin 12 to 18months inadvance of permit development to allow adequate time for conducting toxicity tests and chemical analyses. The type of data, including toxicity testing data, should be specified by the regulatory authority at the outset so that decisions on permit actions will not be delayed. EPA recommends monitoring data be generated on effluent toxicity prior to permit limit development for the foIlowing reasons: (1) the presence or absence of effluent toxicity can be more clearly established or refuted and (2) where toxicity isshown, effluent variability can be more cleady defined. Several basic factors that should be considered ingenerating effluent monitoring data are discussed below.

All toxic effects testing and exposure assessment parameters, for both effluent toxicity and individual chemicals, have some degree ofuncertainty associated with them. The more limited the amount o!test data available, the larger the uncertainty. The leastamount of uncertainty ofan effluent’s impact on the receiving water exists where (1) acomplete data base isavailable on the effects ofacute and chronic toxicity on many indigenous species, (2) there is a clear understanding of ecosystem species composition and functional processes, and (3) actual measured exposure concentrations areavailable forallchemicals during seasonal changes and dilution situations. The uncertainty associated with such an ideal situation would be minimal. However, generation ofthese data can bevery resource intensive.
An example of uncertainty that results from limited monitoring data isifaregulatory authority hasonly one piece of effluent data (e.g., an LCso of 50 percent) for afacility. Effluent variability in such a case, given the range of effluent toxicity variability seen in other effluents, may range between 20 percent and 100 percent (seeAppendix A). It isimpossible to determine from one piece of monitoring data where in this range the effluent variability really falls. More monitoring data would need to be generated to determine the actual variability of this effluent and reduce this source of uncertainty.
To better characterize the effects ofeffluent variability and reduce uncertainty in the process of deciding whether to require an effluent limit, EPAhasdeveloped the statistical approach described below and in Box 3-2. This approach combines knowledge of effluent variability asestimated by a coefficient of variation with the uncertainty due to a limited number of data to project an estimated maximum concentration for the effluent. The estimated maximum concentration iscalculated asthe upper bound of the expected lognormal distribution of effluent concentrations at a high confidence level. The projected effluent concentration after consideration of dilution can then be compared to an appropriate water quality criterion to determine the potential for exceeding that criterion and the need for aneffluent limit.
The statistical approach hastwo parts. The first isacharacterization ofthe highest measured effluent concentration based on the desired confidence level. The relationship that describes this isthe following:
pn =(1 -confidence level)“” where pn isthe percentile represented by the highest concentration in the data and nisthe number of samples. The following are some examples of this relationship at a 99 percent confidence level:

l The largest value of 5 samples isgreater than the 40 percentile

l The largest value of 10samples isgreater than the 63 percentile

l The largest value of20 samples isgreater than the 79 percentile

l The largest value of 100 samples isgreater than the 96 percentile.
The second part of the statistical approach isa relationship between the percentile described above and the selected upper bound of the lognormal effluent distribution. EPA’s effluent data base suggests that the lognormal distribution well characterizes effluent concentrations (seeAppendix E). For example, if five samples were collected (which represents a 40th percentile), the coefficient of variation is0.6, and the desired upper bound of the effluent distribution is the 99th percentile, then the two percentiles can be related using the coefficient ofvariation (CV) asshown below:
C99 exp(2.326o -0.50~)
= =4.2 c40 exp(-0.258o -0.50~)

where & =In((X2+1) and 2.326 and -0.258 arethe normal distribution values for the 99th and 40th percentiles, respectively. The use of the 99th percentile is for illustrative purposes here. Although itdoes represent ameasure ofthe upper bound of an effluent distribution, other percentiles could be selected by aregulatory agency. The relationship shown above can be calculated for other percentiles and CVsby replacing the values in the equation.
Tables 3-l and 3-2 show the combined effects of both parts for a 99percent confidence level and upper bounds of the 99th and 95th percentiles, respectively. The factors shown in the tables are multiplied by the highest concentration in aneffluent sample to estimate the maximum expected concentration.
This procedure can be used for both single and multiple discharges to the same receiving waterbody. This is accomplished for multiple dischargers by summing the projected RWCsfor the pollutant or pollutant parameter of concern from each individual discharger, and comparing it to the water quality standard. This involves an assumption of conservative additivity ofthe pollutant after discharge, which may not accurately reflect the true behavior ofthe toxicant. To overcome this, and to further refine the proportional contribution ofeach discharger and the resultant limits, the permitting authority should supplement this evaluation with multiple source WLA modeling and/or ambient water concentration monitoring.

52 A

### Box 3-2. Determining “Reasonable Potential” for Excursions Above Ambient Criteria Using Effluent Data Only
EPA recommends finding that a permittee has “reasonable potential” to exceed a receiving water quality standard if it cannot be demonstrated with a high confidence level that the upper bound of the lognormal distribution ofeffluent concentrations isbelow the receiving water criteria at specified low-flow conditions. Step 1 Determine the number oftotal observations (“n”) for aparticular setofeffluent data (concentrations or toxic units PUS]), and determine the highest value from that data set. Step 2 Determine the coefficient of variation for the data set. Fora data set where ~10, the coefficient of variation (CVJisestimated to equal 0.6, or the CV iscalculated from data obtained from adischarger. Foradata setwhere n>lO, the CV iscalculated asstandard deviation/mean (see Figure 3-l). Forless than 10 items ofdata, the uncertainty in the CV istoo large to calculate astandard deviation or mean with sufficient confidence. Step 3 Determine the appropriate ratio from Table 3-l or 3-2. Step 4 Multiply the highest value from adata set by the value from Table 3-l or 3-2. Usethis value with the appropriate dilution to project a maximum receiving water concentration (RWC). Step 5 Compare the projected maximum RWCto the applicable standard (criteria maximum concentration, criteria continuous concentration [CCC], or reference ambient concentration). EPArecommends that permitting authorities find reasonable potential when the projected RWC isgreater than an ambient criterion. Example
Consider the following resultsoftoxicity measurements ofaneffluent that isbeing characterized: 5TU,, 2TU,, 9TU,, and 6TU,. Assume that the effluent isdiluted to 2percent atthe edge ofthe mixing zone. Further assume that the CV is0.6, the upper bound ofthe effluent distribution isthe 99th percentile, and the confidence level is99 percent. Step 1 There arefour samples, and the maximum value ofthe sample results is9TU,. Step 2 The value ofthe CV is0.6. Step 3 The value ofthe ratio for four pieces ofdata and aCVof0.6 is4.7. Step 4 The value that exceeds the 99th percentile ofthe distribution (ratio times xmax) after dilution iscalculated as: [9TU, x4.7 x0.021 =0.85 TU,. Step 5 0.85 TU, islessthan the ambient criteria concentration of 1.OTU,. There isno reasonable potential for this effluent to cause an excursion above the CCC.



### 3.3.3 

### Etfhnl CharacMzatiun tar Whh Efh?nt T~xWty Once an effluent has been selected for whole effluent toxicity characterization after consideration ofthefactors discussedabove, the regulatory authority should require toxicity testing in accordance with appropriate site-specific considerations and the recommendations discussed below. Inthe past 5years, significant additional experience has been gained in generating effluent toxicity data upon which to make decisions astowhether or not an effluent will cause toxic effects in the receiving water in both freshwater and marine environments. General Considerations and Assumptions
EPAhas revised itsinitial effluent toxicity data generation recommendations based on three observations made over the last 5 years: 1) Only rarely have effluents discharged by NPDESpermittees been observed to have LCsos lessthan 1.Opercent or no observed effect concentrations (NOECs) lessthan 0.1 percent. However, there isalways a chance that an effluent could be toxic at such low effluent concentrations.
53

### -_-___- -- - -- -.- ------

Jumbero Samples
1 2 3 4 5 6 7

a 9 10 11 12 13 

## I ! ::
16 I 17 18 I 19 20 f

# I

- Table 3-l. Reasonable Potential Multiplying Factors: 99% Confidence Level and 99% Probability Basis

0.1 0.2 0.3 0.4 0.5
1.6 2.5 3.9 6.0 9.0 1.4 2.0 2.9 4.0 5.5 1.4 1.9 2.5 3.3 4.4 1.3 1.7 2.3 2.9 3.8 1.3 1.7 2.1 2.7 3.4 1.3 1.6 2.0 2.5 3.1 1.3 1.6 2.0 2.4 2.9 1.2 1.5 1.9 2.3 2.8 1.2 1.5 1.8 2.2 2.7 1.2 1.5 1.8 2.2 2.6 1.2 1.5 1.8 2.1 2.5 1.2 1.4 1.7 2.0 2.4 1.2 1.4 1.7 2.0 2.3 1.2 1.4 1.7 2.0 2.3 1.2 1.4 1.6 1.9 2.2 1.2 1.4 1.6 1.9 2.2 1.2 1.4 1.6 1.9 2.1 1.2 1.4 1.6 1.8 2.1 1.2 1.4 1.6 1.8 2.1 1.2 1.3 1.6 1.8 2.0

# - -I

- Coefficient of Variation 0.6 0.7 0.8 0.9 1.0
13.2 18.9 26.5 36.2 48.3 7.4 9.8 12.7 16.1 20.2 5.6 7.2 a.9 11.0 13.4 4.7 5.9 7.2 a.7 10.3 4.2 5.1 6.2 7.3 8.6 3.8 4.6 5.5 6.4 7.5 T 

### t 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2.0

63.3 81.4 102.8 128.0 157.1 24 9 30.3 36.3 43.0 50.4 16.0 19.0 22.2 25.7 29.4 12.2 14.2 16.3 18.6 21.0 10.0 11.5 13.1 14.8 16.6 8.6 9.8 11.1 12.4 13.8 3.6 4.2 5.0 5.8 6.7 I 7.7 8.7 9.7 10.8 12.0 3.3 3.9 4.6 5.3 6.1 1 6.9 7.8 8.7 9.6 10.6 3.2 3.7 4.3 5.0 5.7 6.4 7.1 7.9 a.7 9.6 3.0 3.5 4.1 4.7 5.3 ; 5.9 6.6 7.3 8.0 8.8 2.9 3.4 3.9 4.4 5.0 5.6 6.2 6.8 7.4 8.1 2.8 3.2 3.7 4.2 4.7 5.2 5.8 6.4 7.0 7.5 2.7 3.1 3.6 4.0 4.5 I 5.0 5.5 6.0 6.5 7.1 2.6 3.0 3.4 3.9 4.3 ) 4.8 5.2 5.7 6.2 6.7 2.6 2.9 3.3 3.7 4.1 I 4.6 5.0 5.4 5.9 6.4 2.5 2.9 3.2 3.6 4.0 I 4.4 4.8 5.2 5.6 6.1 2.5 2.8 3.1 3.5 3.8 1 4.2 4.6 5.0 5.4 5.8 2.4 2.7 3.0 3.4 3.7 ( 4.1 4.4 4.8 5.2 5.6 2.4 2.7 3.0 3.3 3.6 4.0 4.3 4.6 5.0 5.3 2.3 2.6 2.9 3.2 3.5 3.8 4.2 4.5 4.8 5.2 

# 1

90.3 227.8 269.9 316.7 368.3 58.4 67.2 76.6 86.7 97.5 33.5 37.7 42.3 47.0 52.0 23.6 26.3 29.1 32.1 35.1 18.4 20.4 22.4 24.5 26.6 15.3 16.8 18.3 19.9 21.5 13.1 14.4 15.6 16.9 18.2 11.6 12.6 13.6 14.7 15.8 10.4 11.3 12.2 13.1 14.0 9.5 10.3 11.0 11.8 12.6 8.8 9.4 10.1 10.8 11.5 a.1 8.8 9.4 10.0 10.6 7.6 8.2 a.7 9.3 9.9 7.2 7.7 8.2 a.7 9.2 6.8 7.3 7.7 8.2 8.7 ; 6.5 6.9 7.3 7.8 8.2 I 6.2 6.6 7.0 7.4 7.8 1 5.9 6.3 6.7 7.0 7.4 [ 5.7 6.0 6.4 6.7 7.1 5.5 5.8 6.1 6.5 6.8 ;

Table 3-2. Reasonable Potential Multiplying Factors: 95% Confidence Level and 95% Probability Basis

INumberof Coefficient of Variation

Samples 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0
1 1 1.4 1.9 2.6 3.6 4.7 6.2 8.0 10.1 12.6 15.5 2 1.3 1.6 2.0 2.5 3.1 3.8 4.6 5.4 6.4 7.4 3 1.2 1.5 1.8 2.1 2.5 3.0 3.5 4.0 4.6 5.2 4 ; 1.2 1.4 1.7 1.9 2.2 2.6 2.9 3.3 3.7 4.2 5 Il.2 1.4 1.6 1.8 2.1 2.3 2.6 2.9 3.2 3.6 6 j 1.1 1.3 1.5 1.7 1.9 2.1 2.4 2.6 2.9 3.1

ii ; ::: ::; ::: ::: ::t ::i ::: :I': ::: :I", 9 1 1.1 1.2 1.4 1.5 1.7 1.8 2.0 2.1 2.3 2.4 10 ( 1.1 1.2 1.3 1.5 1.6 1.7 1.9 2.0 2.2 2.3 11 I 1.1 1.2 1.3 1.4 1.6 1.7 1.8 1.9 2.1 2.2 12 I 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.9 2.0 2.1

:: ) :;; ::; :;; ;'I 1.5 4 ;;; 1.7 6 ;:; 1.9 8 2.0 1.9 15 ' 1.1 1.2 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.8 16 ' 1.1 1.1 1.2 1.3 1.4 1.5 1.6 1.6 1.7 1.8

# c

17 I 1.1 1.1 1.2 1.3 1.4 18 I 1.1 7.1 1.2 1.3 1.3 19 ' 1.1 1.1 1.2 1.3 1.3 20 I 1.1 1.1 1.2 1.2 1.3 

# F

1 ' '

1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2.0
8.7 22.3 26.4 30.8 35.6 40.7 46.2 52.1 58.4 64.9 8.5 9.7 10.9 12.2 13.6 15.0 16.4 17.9 19.5 21.1 I 5.8 6.5 7.2 7.9 8.6 9.3 10.0 10.8 11.5 12.3 ) 4.6 5.0 5.5 6.0 6.4 6.9 7.4 7.8 a.3 8.8 I
; 3.9 4.2 4.5 4.9 5.2 5.6 5.9 6.2 6.6 6.9 3.4 3.7 3.9 4.2 4.5 I 4.7 5.0 5.2 5.5 5.7 I 3.1 3.3 3.5 3.7 3.9 ( 4.1 4.3 4.5 4.7 4.9 , 2.8 3.0 3.2 3.3 3.5 1 3.7 3.9 4.0 4.2 4.3 I 2.6 2.8 2.9 3.1 3.2 3.4 3.5 3.6 3.8 3.9 / 2.4 2.6 2.7 2.8 3.0 1 3.1 3.2 3.3 3.4 3.6 ' 2.3 2.4 2.5 2.7 2.8 ; 2.9 3.0 3.1 3.2 3.3 2.2 2.3 2.4 2.5 2.6 \ 2.7 2.8 2.9 3.0 3.0 2.1 2.2 2.3 2.4 2.5 2.5 2.6 2.7 2.8 2.9 ' 2.0 2.1 2.2 2.3 2.3 ' 2.4 2.5 2.6 2.6 2.7 1.9 2.0 2.1 2.2 2.2 2.3 2.4 2.4 2.5 2.5 1.9 1.9 2.0 2.1 2.1 1 2.2 2.3 2.3 2.4 2.4 1.4 1.5 1.6 1.7 1.7 1.8 1.9 1.9 2.0 2.0 ' 2.1 2.2 2.2 2.3 2.3 1.4 1.5 1.6 1.6 1.7 1.7 1.8 1.9 1.9 2.0 2.0 2.1 2.1 2.2 2.2 1.4 1s 1.5 1.6 1.6 , 1.7 1.8 1.8 1.9 1.4 1.4 1.5 1.5 1.6 1.7 1.7 1.8 1.8

54Long-term average

0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 Value 50 Number 01Samples 100

Figure 3-la. Frequency Distribution of Values for a Figure 3-1~. Relationship Between the Largest Value of n Lognormal Distribution with a Mean of 1.Oand a Samples and the Percentile It Exceeds Coefficient of Variation of 0.6 with 99 Percent Confidence

I/ Long-term average

0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 Value Figure 3-1b. Comparison of Relative Frequencies of

Lognormal Distributions with a Mean of 1.Ofor Different Coefficients of Variation

2) With the exception of a small number of “outliers” for which confirmation is

### not possible, acute-to-chronic ratios (ACRs) above 20 for effluents discharged by NPDES permittees have not been observed by EPA. The majority of observed ACRsarevery seldom above 10. However, higher ACRsmay befound for selected facilities. 3) The use of the three commonly used freshwater species and ofthree ofthe five commonly used marine organisms has generally been sufficient to measure any effluent’s toxicity for the purposes of projecting effluent toxicity impact and making regulatory decisions. Percentile =(1 -0.99) 1in 8

20 I I 40 60 80 100 Number of Samples

Figure 3-ld. Example of 90 Percent Confidence Intervals Around Coefficient of Variation Estimates for Numbers of Samples

Figure 3-2 isaflow chart of EPA’srecommendations for data generation for three different dilution scenarios. Itisdivided into three basic steps: determining initial dilution, developing toxicity testing procedures, and developing decision criteria for permit limit. There are certain basic assumptions built into this flow chart. The basic principle used in making decisions isto compare available dilution to known or projected toxic effect concentrations in order to place an effluent into one ofthree categories:

55STEP 1 determination l

STEP 2 Conduct toxicity testing* based on dilution determination (3species at aminimum of quarterly for 1year)

STEP 3 Acute toxicity data or Chronic toxicity data or estimate based onACR v estimate based onACR

YES A Develop permit 4 limits

4 NO

NO NO /A

NO

Require C monitoring at -= reissuance

Notes: ‘Dilution determrnations should be performed for critical flows and any applicable mixing zones. 2Toxicity testing recommendations
a. Dilution > 1OOO:l: acute testing, check CMC only. b. 100: 1 < Dilution c 1000: 1: acute or chronic testing, check CMC and CCC with data or ACR.
c. Dilution < 10o:l: conduct chronic testing, check CCC with data and CMC using acute data or ACR. 3Reasonable potential: Use procedures in Box 3-3.

Figure 3-2. Effluent Characterization for Whole Effluent Toxicity 1) The effluent causes or contributes to an excursion of a numeric or narrative water quality criterion and the permit require5 alimit on toxicity. 2) The effluent has a reasonable potential of causing or contributing to an excursion of a numeric or narrative water quality criterion and alimit isrequired. 3) The effluent has avery low probability of causing or contributing to an excursion of awater quality standard and no limit isrequired. This categorization isaccomplished by using dilution estimates in the first step and the results of the toxicity tests in the next steps. In addition, all these impact estimates assume discharge at critical conditions and imposition of any applicable mixing zone requirements. Therefore, a conservative assumption is used to determine whether or not an impact isprojected to occur. Estimates of possible toxic impact are made assuming that the effluent is most toxic to the most sensitive species or lifestage atthe time of lowest available dilution.

56dilution toxicity tests are much more variable than multiple dilution tests. Therefore, the use of single concentration toxicity tests isstrongly discouraged for this data generation process. Sincethe new data generation requirements are much lessexpensivethan the previous requirements, tiered testing (lessexpensive, single-concentration, initial screening followed by increasingly expensive definitive data generation, using multiconcentration tests, asdescribed inthe September 1985 version ofthe technical support document) isunnecessary. However, elimination of the requirement to conduct toxicity testing on the basis of projections using dilution alone isnot recommended. Although EPA’s data review suggests that an LCso of 1 percent and an NOEC of 0.1 percent are the lower bounds on effluent toxicity, there may be other effluents that are presently unmeasured that are more toxic. Testing data are always desirable for fully characterizing discharges of concern. Steps in Whole Effluent Characterization Process
The following is a detailed description of the major steps presented in Figure 3-2 and the rationale behind each. Step 1: Dilution Determination
The initial step isto determine the dilution of the effluent at the edge ofthe mixing zone, assuming the State allows mixing zones. Figure 3-4 shows a schematic representation of typical mixing zone requirements for both acute and chronic toxicity. Calculating the dilution at the edges of mixing zones for site-specific situations can be complicated. Modeling can be employed using either steady-state or dynamic approaches to calculate the dilution (see Chapter 4). However, for complex situations, such as marine and estuarine waters or lakes, dye studies (or other techniques used to assessmixing zones) may still be required.
Some State water quality standards do not allow the use of mixing in the control of acute toxicity. For these States, acute toxicity is often limited at the end of the pipe. Permit limits derived to enforce such requirements would be considered “water quality-based” because they would be based upon anambient criterion (as opposed to an arbitrary test endpoint). Regardless, both chronic and acute toxicity must be assessed in these situations. Step 2: Toxicity Testing Procedures
Where toxicity tests are required in order to make decisions regarding appropriate next steps in a screening protocol, EPA recommends asaminimum that three species (for example, a vertebrate, an invertebrate, and a plant) be tested quarterly for a minimum of 1year. Asdiscussed in Chapter 1,the useof three species isstrongly recommended. Experience indicates that marine algae can be a highly sensitive test species for some effluents. Using a surrogate species of the plant kingdom adds another trophic level to the testing regimen. Forboth freshwater and marine situations, the useofthree species is more protective than two species since awider range ofspecies sensitivity can be measured. EPAis continuing to develop toxicity test methods using additional organisms including plants. Inaddition, EPAhas revised the test for Selenastnum, which has improved the test precision. 2,467 2,771 2,064 1.626 1,241 2000

0

DiMon (stream/etfluent) (a) At Low Flow (7QlO)

6000

6000 e al P 2 x a B 4000
$ E 2 2oQo

0 3.849

2,477 

# l-b

Dilution (stream/effluent) (b) AtAnnual Mean Flow Figure 3-3. National Distribution of NPOES Dilution Conditions at 7410 and at Annual Mean Flow

The changes tothe EPA’sdata generation recommendations eliminate the application of multiple setsof safety margins that was proposed in the 1985 version of this document. Rather, general observations on effluent toxicity described above now allow regulatory authorities totighten the bounds of the initial dilution categorization, eliminate the species sensitivity uncertainty factor and target LC~I-JS of 1 percent and NOECs of 0.1 percent as the most extreme toxicity measurements that can normally be expected for the vast majority of effluents discharged by NPDES permittees for acute and chronic toxicity, respectively. The observation of toxicity was based on multiple dilution tests. The same observation may not hold for toxicity measured with single dilution tests (pass/fail). As reflected in Chapter 1, single

57

### --. --. .-. ~ - - -.~ ~.- ~- -_ - - -.-__- - -.-. - --_

No initial mlxtng allowed



### ccc b mlxlng zone

- I wer width

flow - - - +

lnlrlal mlxlng allowed:

flow - - - + I
where CMC =0.3 TU, CCC = 1.OTUc

Figure 3-4. Schematic Representation of Mixing Zone Areas Where the CMC and CCCApply

EPArecommends against selecting a“most sensitive” species for toxicity testing. For one organism to consistently be the most sensitive in a battery of toxicity tests, two conditions must occur: (1) the toxicants causing toxicity must remain the same, and (2) the ratios of the toxicants in the effluent (if more than one) must remain the same. Based on EPA’sexperience at the Duluth research laboratory, neither ofthese conditions islikely to occur. Forexample, the causesofeffluent toxicity in POlWs can vary on aseasonal basis. Toxicity in the summer can be caused by pesticides towhich invertebrates are most sensitive. However, the winter toxicity could becaused byammonia towhich fathead minnows will respond most sensitively. The most sensitive speciesfor aneffluent actually may not exist and at best isdifficult to identify. Conducting toxicity tests using three species quarterly for 1 year is recommended to adequately assess the variability of toxicity obserwd ineffluents. Below this minimum, the chances of missing toxic events increase. The toxicity test result for the most sensitive of the tested species is considered to be the measured toxicity for aparticular effluent sample.
The data generation recommendations in Figure 3-2 represent minimum testing requirements. Since uncertainty regarding whether or not an effluent causes toxic impact is reduced with more data, EPA recommends that this test frequency be increased where necessary to adequately assess effluent variability. If less frequent testing is required in the permit, it is preferable to use three species tested lessfrequently than to test the effluent more frequently with only a single species whose sensitivity to the effluent isnot well characterized.
EPA recommends that a discharger conduct acute toxicity testing ifthe dilution of the effluent isgreater than 1OOO:lat the edge of the mixing zone [3]. Such a discharger would be considered alow priority for chronic toxicity testing. The rationale for this is that the effluent concentration would be below 0.1 percent at the edge of the mixing zone and thus incapable of causing an excursion above the CCC. Aworst case NOEC of 0.1 percent translates into 1,000 TU,, which would result inaconcentration of lessthan 1.OTU, atthe edge ofthe mixing zone for this dilution category. The test resultswould becompared tothe CMC after consideration ofany allowable mixing.
EPA recommends that a discharger conduct either acute or chronic toxicity testing if the dilution of the effluent falls between 1OO:l and 1,OOO:l at the edge of the mixing zone. Effluents have been shown to be both acutely and chronically toxic within this range of receiving water dilution. Under worst-case scenarios, LCsos of 1.O percent and ACRs of 10 will result in excursions above both the CCC and CMC at the edge of the regulatory mixing zone. Although either acute or chronic testing can be required within thisdilution range, acute testing would be more appropriateat the higher end ofthis dilution range (1,OOO:l or 0.1 percent). At the lower end of this dilution range (1OO:l or 1.Opercent), chronic tests may be more appropriate. Where other factors are equal, chronic testing may be preferable since the interim results in a chronic test gives data on acute toxicity as well. The acute endpoint data can then be used to compare directly to the CMC without the need for anACR.
Whichever type of toxicity test (either acute or chronic) isspecified, the results from that test should be compared to the criterion associated with that type of test. For example, a chronic test would becompared tothe CCC. Comparisons tothe other criteria can be made by using the ACR or additional data generated to convert achronic test result to an acute endpoint and vice versa. For example, a chronic NOEC of 5 percent effluent (or 20 TU,) represents anacute LCsoof50 percent (or 2TU,) at anACRof 10.
EPA recommends that a discharger conduct chronic toxicity testing if the dilution of the effluent falls below 1OO:l at the edge of the mixing zone. The rationale for this recommendation isthat chronic toxicity has been observed in some effluents down tothe 1.Opercent effect concentration. Therefore, chronic toxicity tests, although somewhat more expensive to conduct, should be used directly inorder to make decisions about toxic impact.
There isa potential for acute toxicity within this dilution range, although this islesslikely asthe 1OO:l dilution level isapproached. Thus, the recommended screening protocol shown in Figure 3-2 includes a determination of whether excursions above the CMC are projected [4]. Thisanalysis may be performed by assuming an ACR, applying this value to the chronic toxicity testing data, and allowing for any allowable initial mixing. Alternatively, the regulatory authority may use the interim results in the chronic test to calculate the acute toxicity.

58Both the chronic and acute toxicity test data would be compared to their respective criterion. The chronic test results would be compared to the CCC, and the acute results, regardless of how calculated, would be compared to the CMC. Step 3: Decision Criteria for Permit Limit Development
Once the toxicity data have been 

### generated for adischarger, the regulatory authority must decide whether or not the results show that the permittee causes, hasthe reasonable potential to cause, or contributes to an excursion of an applicable numeric or narrative water quality criterion and therefore needs to limit effluent toxicity. To do this, these data should be used to project receiving water concentrations, which are then compared to the CCC and CMC. One offour outcomes will be reached when following the screening protocol shown in Figure 3-2: 

### 1)

2) Excursion Above CMC or CCC-Where any one data point shows an excursion above the State’s numeric or narrative criterion for the parameter toxicity, EPAregulations require a permit limit be set for whole effluent toxicity (40 CFR 122.44(d)(l)(iv or v)), unless limits on a specific chemical will allow 

### the narrative water quality criterion to be attained or maintained. Inthe absence of a State numeric criterion for the parameter toxicity, EPA recommends that 1.0TU, and 0.3 TU, be used as the CCC and CMC,.respectively. The decision to develop permit limits based upon an excursion above either the CMC or CCC will lead to protection against both acute and chronic toxicity ifthe permit derivation procedures in Chapter 5are used to seteffluent limits.
Reasonable Potential for Excursion Above CMC or CCCEPAbelieves that “reasonable potential” isshown where an effluent isprojected to cause an excursion above the CCC or CMC. This projection is based upon a statistical analysis of available data that accounts for limited sample size and effluent variability. EPA’sdetailed recommendations for making a statistical determination based upon effluent monitoring data alone areshown in Box 3-2. Where aregulatory authority finds that test results alone indicate a “reasonable potential” to 

### causean excursion above aState water quality criterion in accordance with 40 CFR 122,44(d)(l)(ii), apermit limit must be developed.
A regulatory authority may select an alternative approach for assessing reasonable potential. Forexample, an authority may opt to useastochastic dilution model that incorporates both ambient dilution and effluent variability for determining reasonable potential. Such an approach is analogous to the statistical approach shown inBox 3-2. Whatever approach selected by 

### the authority, it must use all the factors that account for all the factors listed in 40 CFR 122,44(d)(l)(ii).
Insome casesthe statistical analysis ofthe effluent data may not actually project an excursion above the CMC or CCC but may beclose. Under suchconditions, reasonable potential determinations will include an element ofjudgment on the part ofthe regulatory authority. Other factors will need to be considered and given appropriate weight in the decisionmaking process, including value ofwaterbody (e.g., high-use fishery), relative proximity to the CCC or CMC, existing controls on point and nonpoint sources, information on effluent variability, compliance history ofthe facility, and type of treatment facility. These factors are summarized in Box 3-2 and are discussed in detail in Section 3.1. EPA recommends regulatory authorities establish a written policy and procedure for making determinations of “reasonable potential” under these circumstances. 3) No Reasonable Potential for Excursions Above CMC or: a---In these situations, EPA recommends that the toxicity tests recommended above be repeated at a frequency of at least once every 5years as a part of the permit application. Such testing is required for certain POTWs under 40 CFR122.21 (j). 4) lnadeauate Information-Where a regulatory authority hasinadequate information to determine reasonable potential for an excursion of a numeric or narrative water quality criterion, there may still be abasisfor concern on the part of the authority. The permit should contain whole effluent toxicity monitoring requirements and a reopener clause. This

### clausewould require reopening of the permit and establishment of a limit based upon any test results, or other 

### newfactors, which substantiate that the effluent causes, hasthe reasonable potential of causing, or contributes to an excursion above the CCC or CMC.



### 3.3.4 UseofTuxMy TesfhginMultiple-sourMIglsclrarge SItuBtI4RF Where more than one discharge tothe same receiving waterbody contributes, or hasthe reasonable potential to contribute to an excursion of water quality standards, permit limits must be developed for each individual discharger on that waterbody. Forthe regulatory authority to make this assessment, additional testing may be needed to provide 

### the authority with the information necessary to assessthe relative impact of each source. For purposes of this discussion, a multiple-source discharge situation isdefined asasituation where impact zones overlap, or where ambient receiving water concentrations of a pollutant are elevated due to upstream discharges. In multiple-source discharge situations, additivity, antagonism, and persistence of toxicity can beofconcern. Tocollect additional data, 

### the permit authority should employ the toxicity testing procedures for multiple dischargers described in Box 3-3. Inaddition, ambient toxicity testing, asdescribed below, could be used. Assuming 

### thatscreening has been conducted that reveals the need for permit limits, two options for controlling the discharges exist. The first option isfor the permit authority to regulate each source separately using the procedures for individual point sources. In this option, the permitting authority would require useofupstream ambient water asadiluent inthe toxicity test so as to be able to evaluate the contributions of upstream sources of toxicity. A second option isto treat each discharge as an interactive component of a whole system. In this option, the permit writer would determine a total maximum daily load for the receiving waterbody and develop individual wasteload allocations for each discharger using the procedures discussed inChapter 4.

59

### Box 3-3. Recommend Multiple-source Toxicity Testing Procedures
Tests
Where the combined effluents make up 1 percent or greater of the receiving waters, conduct chronic toxicity testsfollowing the testing procedures described in Section 3.3.3.
Where the combined effluents make up lessthan 1percent ofthe receiving waters, conduct acute toxicity tests following the testing procedures described in Section 3.3.3 (see Figure 3-2) to determine ifany of the effluents are exhibiting toxicity.
An additional data requirement is the assessment of relative and absolute toxicity of each source so that appropriate permit conditions can be setfor individual dischargers. The following procedure issuggested. 1) Conduct one setoftoxicity testson the effluents using acontrol of reconstituted or uncontaminated dilution water. The setoftestswill give an absolute toxicity measurement ofthe effluent. 2) Runaparallel setoftoxicity testsonthe effluent using dilution water taken directly upstream from the point of discharge or,for estuarine waters, from anarea outside ofthe immediate discharge impact zone (this will have to be determined by adye study). This dilution water may be contaminated with upstream effluents or other toxicant sources. The purpose ofthis test isto project toxic impact ofthe effluent after it ismixed at itspoint ofdischarge. This isarelative effluent toxicity measurement. The relative testing procedure could result ina change inthe standard concentration-effect curve generated bythe testing. The dilution water forthe relative toxicity test may cause significant mortality, growth, or reproductive effects at the lower effluent concentrations (including the 100 percent diluent control concentration) ifthe diluent from the receiving water istoxic (from an upstream discharge). Such mortality does not invalidate the test. Instead, analysis oftoxicity trends resulting from the relative toxicity testscan be used to assessthe effluent’s toxicity in relation to other sources and ambient receiving water conditions. However, acontrol dilution water with notoxicity must be usedfor quality assurance and determination ofabsolute toxicity ofthe effluent. 3) Conduct ambient toxicity tests to (a) determine whether or not the effluent hasa measurable toxicity after mixing, (b) measure persistence of toxicity from all sources contributing to receiving water toxicity, and (c) determine combined toxicity resulting from the mixing of multiple, point, and nonpoint sources oftoxicity. SeeAppendix Cfor adiscussion ofambient toxicity testing procedures.
The ambient testing can be required of each discharger and conducted during low-flow or worst-case design periods. 

### Frequency for Ambient Testing
All testing should be conducted simultaneously by each discharger, ifpossible. At a minimum, the tests should be conducted concurrently starting within ashort time period (1to 2days). Repeated ambient toxicity analyses will be desirable when variable effluents are involved. Effluent toxicity data showing variability can be used to assesswhat frequency will be most applicable. The level of repetition for variability analysis should be similar to that used ineffluent variability analyses.
Other Considerations Dye studies of effluent dispersion for rivers, lakes, reservoirs, and estuaries are strongly recommended. This allows analysis ofeffluent concentration atthe selected sampling stations above and below the discharge points.
The procedures suggested in this multiple source section are based on actual multiple source site investigations conducted under the Complex Effluent Toxicity Testing Program. Site reports from that study can be used to obtain further description ofthe toxicity testing procedures used to analyze multiple source toxic impact [l, 21.

60

### 3.3.5 AmbientToxicityTesting Ambient toxicity testing also is useful in screening receiving water bodies for existing toxic conditions. The procedure described in Appendix C uses short-term chronic toxicity tests to measure the toxicity of samples of receiving water taken above, at, and below outfalls. Itcan be used infreshwater, marine, and estuarine systems. The procedure must beconducted during an appropriate low-flow orworst-case design period.
The utility of the ambient toxicity screening approach is that actual receiving water toxicity isdirectly measured. No extrapolation from exposure or ACR is needed. Further, impact from multiple source discharge situations, which may not beapparent from individual discharger data, isidentified. Finally, the technique can provide an assessment of the persistence of effluent toxicity.


### 3.3.6 SpecialConsiderationsfurDischaqestoMarineand EstuarineEnvironments Special problems are encountered when assessing and controlling impacts oftoxic pollutants discharged to marine and estuarine waterbodies. These special problems include the following:

l Determining the physical characteristics of estuaries and the complex mixing and effluent dilution situations for RWCsofeffluents.

l Generating toxicity data on nonsaline effluents that discharge to brackish orsaline waters and establishing causeeffect relationships on that basis.

l Assessing exposure and controlling impacts from persistent toxicants accumulating in fish and shellfish tissues and insediments. These factors are particularly important inestuaries and near coastal waters because of high useof estuaries asbreeding and fishing areasfor important commercial seafood supplies and recreational fishing, and because many estuaries and near coastal waters act assinks for pollutants that accumulate in sediments.
Where these special problems areencountered, additional information may need to be gathered to better quantify dilution, to determine metals partitioning, and to identify potential interferences inwhole effluent toxicity tests.
To characterize the type of whole effluent toxicity that ismost relevant for a particular discharge to marine and estuarine waters, the following questions should be considered [5]:

l What is the salinity of the receiving water, and is this important interms ofthe State standards?

l What isthe appropriate test organism to require for toxicity testing under differing salinity conditions?
The answers to these questions will enable the permitting authority to determine what type oftoxicity testing ismost suitable for effluent characterization and whole effluent toxicity control.
For most marine and estuarine discharges the choice of test species and dilution water should be made based on the characteristics ofthe receiving water at the critical conditions for flow, mixing, and salinity. Foremost in this determination should be the salinity of the receiving water and, to a lesser extent, the salinity ofthe effluent itself.
The primary objective ofwhole effluent toxicity tests isto identify sources of toxicity that can potentially cause an excursion of a State’s narrative or numeric water quality criteria. Forthis reason, the toxicity tests should reflect the natural conditions of the receiving water soto be able to measure any effluent characteristic that could contribute to ambient toxicity. The marine toxicity test methods identify 1,000 mg/l asthe point at which salinity begins to exert an effect on freshwater species. As a general rule, EPA recommends that freshwater organisms be used when the receiving water salinity islessthan 1,000 mg/l, and that marine organisms be used when the receiving water salinity equals or exceeds 1,000 mg/l.
Saline Effluent Discharges to Saltwater
The dissolved salts inthe effluent are pollutants. These salts may or may not be the same asthose present in the receiving water. Also, the proportion of dissolved salts in the effluent may be different from that ofthe saltsinthe receiving water. Inthis case, the toxicity test needs to be able to determine if these salts contribute to ambient toxicity. For this reason, marine organismsare needed.
Saline Effluent Discharged to Freshwater
Inthis case, the dissolved salts in the effluent isa pollutant that does not exist in the receiving water. The toxicity test needs to determine whether the dissolved saltscan beone ofthe toxicants that contribute to ambient toxicity. Forthis reason, freshwater organisms are needed.
Freshwater Effluent Discharged to Saltwater
In this instance, the lack of dissolved salts in the effluent can cause an apparent toxic effect to the marine organisms in the toxicity test. However, in contrast to the instances presented above, the toxicity test does not need to be able to measure this effect because a lack of salts is not a pollutant. The marine toxicity test methods account for this by requiring that the salinity ofthe effluent be adjusted to approximate the salinity of the receiving water. Asanalternative to using amarine organism, afreshwater organism can be used ifthe test isbeing conducted only on a loo-percent effluent sample and if State water quality standards do not require that amarine organism be used.


### 3.3.7 UsingaChemical-specificlimit to

### ControlToxicity EPAregulations at 40 CFR122.44(d)(l )(v) provide that limits on whole effluent toxicity are not necessary where the permitting authority demonstrates in the fact sheet or statement of basisof the NPDESpermit that chemical-specific limits for the effluent are sufficient to attain and maintain applicable numeric and narrative State water quality criteria. To make this demonstration that chemical-specific limits aresufficient, additional effluent information will be needed. EPA recommends that the discharger conduct a toxicity identification evaluation to identify the causative agent(s) in the effluent. Where the permitting authority determines that the demonstration required by 40 CFR 122.44(d)(l)(v) has been made, limits onwhole effluent toxicity

61need not be imposed. Effluent limits on the controlling chemical with concurrent whole effluent monitoring will besufficient. Where subsequent whole effluent toxicity testing reveals the presence of toxicity inthe effluent, the above process will need to be repeated, or alternatively a whole effluent toxicity limit will be needed. If continued toxicity testing shows that additional chemical-specific effluent limits are insufficient to control whole effluent toxicity, then toxicity limits may be the only practical way to control toxicity.


### 3.3.8 Eif/uentCharacterizetionior@edtic Chemkak The previous section discussed effluent characterization for whole effluent toxicity. Thissection will describe EPA’srecommendations for data generation to determine whether or not permit limits are needed to control specific chemical pollutants in effluents. While many of the same principles apply when developing chemicalspecific limits, there are some differences based upon regulatory and analytical considerations.
Characterization of impacts due to specific chemicals do not require adetermination ofthe type oftesting asisrequired for whole effluent toxicity because there isgenerally only one type oftest for specific chemicals. However, there aresome antecedent steps that are unique to effluent characterization for specific chemicals: determination of the chemicals of concern and determination of acceptable ambient levels (RAC, CMC, or CCC) for these pollutants. Steps for Chemical-specific Effluent Characterization Process Figure 3-5 illustrates EPA’s recommendations for determining whether or not permit limits need to be developed according to an evaluation of a limited data set. The following discussion corresponds to the various activities shown in Figure 3-5. (Referto the human health discussion in Section 3.3.9 for additional details on procedures to characterize the bioconcentration potential of effluents.) Step 7: ldentifj the Po//uCunCsofConcern
This process should begin with an examination ofexisting data to determine the presence of specific toxicants for which criteria, standards, or other toxicity data are available. Sources of data include the following:

l Permit application forms, DMRs, permit compliance systems (PCS), and permit files

l Pretreatment industrial surveys

l STORETfor ambient monitoring data

l SARATitle IllToxic Chemical Release Inventory

l Industrial effluent guidelines development documents

l The Treatability Manual [6]

. Effluent bioconcentration assessment (see Section 3.3.9).
Data on specific chemicals that aretypically submitted with NPDES application forms will consist ofalimited number ofanalytical test results for many of the reported parameters. Where the regulatory authority has reason to believe that additional data for key parameters ofconcern are needed inorder to adequately characterize the effluent, this information should be requested asapart of the application or, in some cases, through the use of Section 308 letters. It is recommended that 8 to 12 samples be analyzed for key parameters of concern. In some cases, special analytical protocols will need to be specified inorder to gather all appropriate information. Step2: Determine the Basis for fstablishing RAG, ChlCs, and CCCsfor the Pollutants ofConcern
The second step isto identify the appropriate water quality standard, including designated or existing use, and criteria for use. Ideally, the State water quality standards include aquatic life and human health criteria forthe pollutants ofconcern. IfaStatedoes not have a numeric water quality criterion for the pollutant of concern, then one of three options for using the narrative criterion may be used (40 CFR122.44(d)(l)(vi)) to determine whether a discharge causes, has the reasonable potential to cause, or contributes to an excursion above a narrative criteria because of an individual pollutant. Although the provisions of 40 CFR 122.44(d)(l)(vi) are presented inthe regulation in the context of permit limit development, these same considerations should be applied incharacterizing effluents in order to determine whether limits are necessary. The options available are asfollows:

l Option Aallows the regulatory authority to establish limits using a “calculated numeric water quality criterion” that the regulatory authority demonstrates will attain and maintain applicable narrative water quality criteria and fully protect the designated use. This option allows the regulatory authority to useany criterion that protects aquatic life and human health. This option also allows the useof sitespecific factors, including local human consumption rates of aquatic foods, the State’s determination of an appropriate risk level, and any other current data that may be available.

l Option Ballows the regulatory authority to establish effluent limits using EPA’sWater Quality Criteria guidance documents, if EPA has published a criteria document for the pollutant supplemented where necessary by other relevant information. As discussed earlier, EPAcriteria documents provide acomprehensive summary ofavailable data on the effects ofapollutant.

l Option C may be used to develop limits for a pollutant of concern based on an indicator parameter under limited circumstances. An example of an indicator parameter is total toxic organics (l-TO>; effluent limits on TTO are useful where an effluent contains organic compounds. However, useofthis option must bejustified to show that controls on one pollutant control one or more other pollutants to a level that will attain and maintain applicable State narrative water quality criteria and will protect aquatic life and human health (see 40 CFR 122.44(d)(l)(vi)(C)). Use of this option isrestricted by regulation tothose instances where it can be demonstrated that controls on indicator pollutants serve to control the toxicant ofconcern. Using Option Aor Option B is a more direct and perhaps more defensible approach.

62STEP 1

STEP 2 Determine RAC and/or CMUCCC for pollutants

RAC available CMC and/or CCC avarlable
STEP 3 rhiizkd Dilution determination for aquatic life

NO 

# A NO A

NO I I NO I I Require monitoring at

reissuance

Notes:

’ RAC and/or CMC/CCC: Use State numeric criterion or interpret State narrative criterion using one of three options specified under 40 CFR

122.44(d). 2 Dilution determination: Perform for critical flow and for any applicable mixing zones for aquatic life and human health protection procedures,

respectively. 3 Reasonable potential: Use procedures in Boxes 3-2 and 3-4.
Figure 3-5. Effluent Characterization for Specific Chemicals

Step 3: Dilution Determination Step 4: Decision Criteria for Permit Limit Development
The third step isto calculate the effluent dilution at the edge of the mixing zone. The pertinent factors for consideration here are the same aswere previously presented forwhole effluent toxicity with one difference: there are two levels of dilution analysis for chemical data. The first level isto usesimple fate models based on a dilution analysis and comparison with the RAC, CMC, or CCC. The second level of analysis isto use more complex fate models, including dynamic models to estimate persistence, and may be applied to lakes, rivers, estuaries, and coastal systems using a desktop calculator or microcomputer. EPA has supported development of asecond level of analysis that estimates point source wasteload allocations and nonpoint source allocations and predicts the resulting pollutant concentrations in receiving waters [7]. After this dilution analysis hasbeen performed, the projected RWC iscompared to the RAC,CMC, or CCC (either the State numeric criteria or an interpretation of the narrative criteria as described earlier). Whereas analysis ofaquatic impacts should include evaluations with respect to both the CCC and the CMC, analysis of human health impacts will only involve comparisons with the RAC. The four possible outcomes discussed above in the triggers for permit limit development discussion in Section 3.3.3 also apply here:

l Excursion above the RAC,CMC, or CCC

l Reasonable potential for excursion above the RAC,CMC, or ccc

63

### - - - -. - - _. - -.-

l No reasonable potential for excursion above the RAC,CMC, ccc

. Inadequate information.
Ifthese evaluations project excursions or the reasonable potential to cause or contribute to an excursion above the RAC, CMC, or CCC, then a permit limit is required (40 CFR 122.44(d)(l)(iii)). The statistical approach shown in Box 3-2 or an analogous approach developed by aregulatory authority can be used to determine the reasonable potential. Effluents that are shown not to cause orthat have areasonable potential to cause orcontribute to an excursion above an RAC,CMC, or CCC should be reevaluated at permit reissuance.
Where chemical-specific test results do not show a reasonable potential but indicate abasisfor concern after consideration ofthe other factors discussed in Section 3.2, or ifthere were inadequate information to make adecision, the permit should contain chemical testing requirements and areopener clause. This clausewould require reopening ofthe permit and establishment ofalimit based upon any test results that show effluent toxicity at levels that cause or have areasonable potential to cause or contribute to an excursion above the RAC,CCC, or CMC.


### 3.3.9 EffluentCharacteriwtiontarBiocunceMh? Pollutants The previous section discussed how to characterize effects of specific chemicals, including those that may threaten human health, to determine whether or not a discharge causes, has the reasonable potential to cause, or contributes to excursions above an water quality criterion. The primary disadvantage ofthis approach isthat it does not identify all effluent chemicals of potential cqntern for human health. To help address this gap, EPAisdeveloping a procedure for identifying pollutants with the propensity to bioconcentrate in fish tissue. This procedure ispresently in draft form and should not be used for establishing NPDES permit limits until EPA releases the final document on the procedure. This section describes the outline ofthis procedure.
The overall approach illustrated in Figure 3-6isaseven-step procedure that starts with collecting samples and ends with developing permit effluent limits. The effluent characterization step unique to this approach lies in Step 3. There are two alternatives under this step: fish tissue residue and effluent assessment. An analytical chemistry laboratory with residue chemistry and gas chromatograph/mass spectometer (GUMS) capability isneeded to conduct the analytical methods for both alternatives. A summary of the alternatives follows:

l Tissue ResidueAlternative: Thisalternative measures the concentrations of organic bioconcentratable chemicals in tissue samples of indigenous organisms from the receiving water. Thisanalysis involves the collection offishorshellfish samples, the extraction of the organic chemicals from the tissue and the analysis of these extracts with CC/MS to identify and quantify the bloconcentratable contaminants. The procedure provides recommendations tosortthe resultsofthisscreening analysis inorder todetermine which ofthe contaminants pose ahazard and require regulatory action. Theapproach recommends that the identity ofthose contaminants then be confirmed prior to taking subsequent action. Select di6chargerr

biOcOnCentr6tiOn

etternatlve Ti66ue n6idUe akernative

Develop RACIRTC I

DWdOQ WastelOad allocalion

I Develop permit limit6

I Conduct monitodng

Figure 3-6. Procedure for Assessment and Control of Bloconcentratable Contaminants in Surface Waters

l Effluent Alternative: This alternative measures the concentrations of organic bioconcentratable chemicals in effluent samples from point source dischargers. This analysis involves the collection of effluent samples, the extraction of the organic chemicals from the effluent sample, and the separation ofthe chemicals that have characteristics known to result in bioconcentration from the other chemical components ofthe effluent sample. This separation isachieved by way ofan analytical chemistry methodology called high64pressure liquid chromatography (HPLC). The HPLC also separates (fractionates) an effluent sample into three subsamples or “fractions.” These three fractions contain chemicals with increasing potential to bioconcentrate, with thethird fraction containing those chemicals with the highest bioconcentration rates. Following HPLC fractionation, each fraction is then analyzed with CC/MS to identify and quantify the bioconcentratable contaminants. The effluent procedure also provides recommendations to sort the results of the initial screening analysis to determine which ofthe contaminants pose ahazard and require subsequent regulatory action. The approach then recommends that the identity of those contaminants then be confirmed prior to taking further regulatory action.
While both of the assessment alternatives described above may be used for agiven discharger, generally one of these alternatives may be preferred by the regulatory authority. The regulatory authority would select the assessment approach based on the available site- and facility-specific information and the objectives ofthe application. Although the approach provides a means to identify chemicals that can bioconcentrate, it does not identify all bioconcentratable chemicals. Chemicals that bioconcentrate include many organic compounds, and a small number of metals (e.g., mercury and selenium) and organometals (e.g., tributyltin). The new approach islimited to nonpolar organic chemicals that produce measurable chemical residues in aquatic organisms or that have log octanolwater partition coefficients greater than 3.5.


### 3.3.10 AnalyticalConsiderations forChemicals Analysis of discharges for toxic substances requires special quality control procedures beyond those necessary for conventional parameters. Toxicants can occur in trace concentrations and are frequently volatile or otherwise unstable. An EPApublication entitled, Test Methods-Technical Additions to Methods for Chemical Analysis of Water and Wastes[8], contains sampling and handling procedures recommended by EPA for a number of toxic and conventional parameters. Additional methods for analyses for toxicants are described in Standard Methods ofWater and Wastewater Analyses (ASTM, 17th edition, 1989, or most recent edition) and 40 CFR Part 136. Chapter 5 discusses detection limits and sampling requirements.

65

## CHAPTER 3 REFERENCES

1. Mount, D., N. Thomas, M. Barbour, T. Norberg, T. Roush,and W. Brandes. 1984. Effluentand Ambient Toxicity Testingand Instream Community ResponseontheOttawa River,Lima,Ohio. Permits Division, Washington, DC, Office of Research and Development, Duluth, MN. EPA-600/2-84-080, August 1984. 2. Mount, D.I., and T.J. Norberg-King, eds. 1985. Validity of fffluent and Ambient Toxicity Tests for Predicting Biological Impact, ScippoCreek,Circleville, Ohio. U.S. EPA. EPAJ600/3- 85/044, 

### june 1985. 3. Peltier, W., and C.I.Weber. 1985. Methods forMeasuring the Acute Toxicity of 

### EffluentsloAquatic Organisms, 3d ed. Office of Research and Development, Cincinnati, OH. EPA600/4-85-013. 4. Weber, C.I., et al., eds. 1989. Short-Term Methods far fstimating the Chronic Toxicity of Effluentsand Receiving Waters to Freshwater Organisms, 2d ed. Office of Research and Development, Cincinnati, OH. EPA-600/4-89/001. 5. Weber, C.I., etal., eds. 1988. Short-Term Methods forfstimating the Chronic Toxicity of Effluents and Receiving Waters to Marine and fstuarine Organisms. Office of Research and Development, Cincinnati, OH. EPA-600/4-87/02. 6. U.S. EPA. 1983. TheTreataabilityManual, Volume 4. U.S. EPA Office of Research and Development. EPA600/2-82-001 (revised January 24, 1983). 7. Mills, W., et al, 1982. Water Quality Assessment: AScreening Procedure Toxicand Conventional Pollutants: Parts 1and 2. Office of Research and Development, Athens, CA. EPA 600/6-82-004 A, September 1982. 8. U.S.EPA. 1982. TestMethods -TechnicalAdditions toMethods for Chemical Analysis of Water and Wastes. Office of Research and Development, Cincinnati, OH. EPA600/4-82- 055, December 1982.



## AIIDKIONAL REFERENCES

Crane, J.L.,A. Pilli, and R.C. Russa. 1984. CfT/S: Complex DiToro, D. 1985. Exposure Assessment for Complex Effluent Toxicity Information System. CfTiS Retrieval System Effluents: Principles and Possibilities. In Environmental User’s Manual. Office of Research and Development, Hazard Assessment of ffflvents. Eds. H. Bergman, R. Duluth, MN. EPA-60018-84-030, November 1984. Kimerle, and A. Maki. Crane, J.L.,A. Pilli, and R.C. Russa. 1984. UT/S: Complex Macek, K. 1985. Perspectives on the Application ofthe

EffluentsToxicity Information System. Data Encoding Cuide- Hazard Evaluation Process. In Environmental Hazard linesand Procedures.Office of Research and Development, Assessment of fMuents. Eds. H. Bergman, R. Kimerle, Duluth, MN. EPA-60018-84-029. November 1984. and A. Maki.

66

# 4. EXPOSURE AND WASTELOAD ALLOCATION

4.1 INTRODUCTION

At this point inthe toxics control process, awater quality problem has been identified. Screening analyses may have been done to assessthe extent of toxicity, or a wasteload allocation (WLA) based on an existing total maximum daily load (TMDL) may already have been established. ATMDL isthe sum of the individual WLAs for point sources and load allocations (LAs) for nonpoint sources of pollution and natural background sources, tributaries, oradjacent segments. WLAs represent that portion of aTMDL that isestablished to limit the amount of pollutants from existing and future point sources sothat surface water quality is protected at allflow conditions.
The TMDL process uses water quality analyses to predict water quality conditions and pollutant concentrations. Limits onwastewater pollutant loads are set and nonpoint source allocations are established so that predicted receiving water concentrations do not exceed water quality criteria. TMDLs and WLAs/LAs should be established at levels necessary to attain and maintain the applicable narrative and numerical water quality standards, with seasonal variations and amargin ofsafety that takes into account any lackof knowledge concerning the relationship between point and nonpoint source loadings and water quality. Determination of WLAs/LAs and TMDLs should take into account critical conditions for stream flow, loading, and water quality parameters. Conditions that will protect the receiving water have been determined from State numeric or narrative water quality criteria.
This chapter isdivided into sections that explain the steps that precede establishment of aWLA and then the methods and tools (models) that can be used to determine the WLA. Section 4.2 briefly discusses TMDLs and how they relate to waters identified as requiring a water quality-based approach for toxics control. The section also discusses different WLA schemes. Sections 4.3 and 4.4 discuss mixing zones, areasdescribed asallocated impact zones where acute and chronic water quality criteria may be exceeded. Section 4.3 provides background information on mixing zones and discusses EPA’smixing zone policy and how this policy affects the allowable toxic load that can bedischarged from apoint source. State mixing zone dimensions and the determination of mixing zone boundaries are also discussed.
Section 4.4 discusses mixing zone analyses for situations inwhich the discharge does not mix completely with the receiving water within ashort distance. Included in Section 4.4 are discussions of outfall designs that maximize initial dilution in the mixing zone, critical design periods for mixing zone analyses, and methods to analyze and model near-field and far-field mixing.
Section 4.5 discusses the calculations ofthe WLA and LAand the types of EPA-recommended mathematical models available to determine WLAs in completely mixed situations for both aquatic life and human health. The WLA models listed in Section 4.5 can be used to predict ambient concentrations and to calculate the effluent quality required to meet the criteria and protect designated and existing usesofthe receiving water. The data requirements of each of these models are also described so that the effluent characterization procedures described in Chapter 3 can be designed to support the specific types of WLA modeling selected by the regulator. Section 4.6 discusses human health considerations and how to determine WLAs for human health toxicants.
EPAiscurrently working on methods to develop sediment criteria. Once developed, point source discharges could befurther limited to prevent accumulation of pollutants in the bed sediment; such accumulation impairs beneficial uses. Although the criteria are not yet available for this document, they will be addressed in future documents. In the meantime, some of the models discussedinSection 4.5arecapable ofsimulating interactions between the water column and sediment and between toxic transport and transformation in the sediment. EPAisencouraging the Statesto consider the role ofsediments inWLA.



## 4.2 TOTAL MAXIMUMDAILY LOADS AND WASTELOAD ALLOCATIONS

4.2.1Total Maximum dailyLoads The Federal Clean Water Act (CWA), under Section 303(d), requires the establishment of TMDLs for “water quality limited” stream segments. Insuch segments, water quality does not meet applicable water quality standards and/or isnot expected to meet applicable water quality standards even after the application of the technology-based effluent limitations. A TMDL includes a determination of the amount of a pollutant, or property of a pollutant, from point, nonpoint, and natural background sources, including a margin of safety, that may be discharged to awater quality-limited waterbody. Any loading above this loading capacity risksviolating water quality standards. TMDLs can beexpressed interms ofchemical massper unit oftime, by toxicity, or by other appropriate measures. Permits should be issued based onTMDLs where available.
The establishment ofaTMDL for aparticular waterbody isdependent on the location of point sources, available dilution, water quality standards, nonpoint source contributions, background conditions, and instream pollutant reactions and effluent toxicity. All ofthese factors can affect the allowable massof the pollutant in the waterbody. Thus, two issues must be determined in conjunction with the establishment of the TMDL: (1) the definition of upstream and downstream boundaries ofthe waterbody forwhich the TMDL isbeing determined, and (2) the definition of critical conditions. For the following discussion, the waterbody boundaries are delineated as the portion of the waterbody be

### 67

### tweenthepollutantsource(whetherpoint sourceornonpoint source)that isfarthestupstreamandthedownstreampointat which waterquality hasrecoveredto the backgroundquality foundabovethepollutantsource thatisfarthestupstream.The delineationofcriticalconditionsforstreamflow, loading,and waterqualityparameters maybespecific tothetypeofwaterbody andisdiscussed inSection 4.4. TMDLs areestablished based onwaterqualitycriteriapertinentto thedesignatedandexistinguses forthewaterbodyinquestion. TMDLs aretraditionallycalculatedusingState waterqualitystandardsasappliedtoaspecificwaterbody. Suchafitting ofthe TMDLtodesiredwaterqualitycriteriarequiresinformationconcerningthedistributionofloadings withinthewaterbody,namely, thelocationsandrelativecontributionsofpollutant-specificloadingsfrompoint, nonpoint,andbackgroundsources during all flowconditions(40CFR 130.2(f)).Low-flowTMDLs,bythemselves, willnotbeadequateinsituationswherenonpointsource loadings(LAs) duringhighorintermediate flowconditionscause excursions abovewaterqualitystandards (40CFR 130.2(f)). TheloadingcapacityofTMDLshavebeendeterminedinmany ways,but the mostcommonmethodistofindthe pollutant loadingthatwill attainand maintainapplicablewaterquality criteria. Forexample,in theTualatinRiverBasinin Oregon, loadingcapacitywasdeterminedbymultiplyingstreamflowin criticalflowperiodsbythepollutantwaterqualitystandard[1]. Anothermethodofdeterminingaloadingcapacityisbyquantifying instreamtoxicity. Thismethodwasusedindevelopinga TMDLfortheAmeliaRiverinFlorida[2]. TheallowableTMDLisdefinedasthesumoftheindividualWLAs andLAs; amarginofsafety canbeincludedwiththetwotypesof allocationstoensurethatallocatedloads,regardless ofsource, wouldnotproduceanexcursionabovewaterqualitystandards. TheWLAs arethoseportionsoftheTMDLassignedto point sources; theLAs arethoseportionsoftheTMDLassigned tothe sumofall nonpoint sourcesandbackgroundsources(40 CFR 130.2(f)). Thebackgroundsourcesrepresentloadingsto the specified waterbodyorstreamsegmentthatcomefromsources outside thedefinedsegment.For example,loadings fromregions upstream ofthesegmentandestimatedatmospheric deposition ofthepollutantwouldconstitutebackgroundsources.Sediments thatarehighlycontaminated fromupstream discharges orhistoricaldischarges mightalso actas asource oftoxicants andcontribute tothebackgroundlevels; these sediments alsomaybepartofthe nonpointsources. TheTMDLrepresents amass loadingthatmayoccuroveragiven timeperiodtoattainandmaintainwaterqualitystandards.Asa result,thedesignflowsunderwhichtheTMDLisdeterminedcan significantlyalteritsvalue. Thisphenomenonresultsinasomewhatunusualdichotomy.Thedesignflowsforaquaticlifeprotection mostapplicableto point sourceloadings(WLAs)usually involvelow-flowevents(e.g.,7Q10)because thevolumesassociatedwiththepointsources generallydonotdecrease with decreasedstreamflow. Asa result,the highestconcentrations associated with specificpointsourceloadswould beexpected underlowflowconditions.Conversely, elevated nonpointsource pollutantloadings(i.e.,urban,agricultural)generallycorrespond tostormevents.Infact,agriculturalandurbanrunoffareoften minimalornonexistentintheabsence ofprecipitation(i.e.,nonexistentunderlow-flowdroughtconditions), TheTMDLisacompositeoftheallowableloadsassociated with pointsources andnonpointsources within thedefinedboundariesofthewaterbodysegmentandthebackgroundloadingsto that segmentfrom upstreamand from in-placesediments. Therefore, theTMDLshouldbeevaluatedunderconditionsthat reflect worst-case (critical)conditionsforbothpointandnonpoint source loadings(i.e.,low-flowdroughtandhighflowconditions). DeterminationoftheTMDLunderthesetwo scenarios would identifythelowerofthetwoloadingcapacities ofthewaterbody. Thislowercapacityisnecessary to protectthewaterbodyin question. Inthecaseofdesignflowsfor humanhealthprotection,the harmonicmeanflowisrecommended asthebasis forTMDLs for carcinogens.Designflowsforhumanhealthprotectionshould consider worst-case conditions forbothpointandnonpointsource loadingsunderthisflowcondition(see Section 4.6). In manycases,LAsfornonpointsources aredifficulttoassess because theinformationneeded todescribe therunoffassociated with the high-flowstormeventsdoesnot exist. Thislackof informationisduetothehighvariabilityoftheevents.Because of theimportanceofestimatingthenonpointcontributionstothe waterbody,site-specificmodelsmaybe requiredto estimate nonpointsource loadings.Even then,detailedmodels aredifficult tocalibratewithaccuracy without intensivemonitoringstudies, andsimplisticcorrelationsbetweenloadingsandrainfallcanbe, bytheirstatistical nature,unreliable forestimatinglow-frequency events(e.g.,worst10-yearstorm).Theuncertainties associated with nonpointsourceloadingsandbackgroundsources require thattheTMDLbedetermined withasufficientmarginofsafety to allowforsignificantvariabilityinnonpointsourceloadings. CWA Section 303(d)andEPA regulations (40CFR Parts 35and130, January 11,1985)requirethatTMDLs containamarginofsafety “whichtakes intoaccountanylackofknowledgeconcerningthe relationshipbetweeneffluentlimitationsandwaterquality.” The marginofsafetyistotakeintoaccountanyuncertaintiesrelated todevelopmentofthewaterquality-based control,includingany uncertaintiesinpollutantloadings,ambientconditions,andthe modelanalysis.Thesizeoftherequiredmarginofsafety can,of course,bereducedbycollectingadditionalinformation,which reduces theamountofuncertainty.Themarginofsafety canbe providedforintheTMDLprocess byoneofthefollowing:

• 

### Reserving aportionoftheloadingcapacitytoaseparate marginofsafety.

• 

### Includingamarginofsafety withintheindividualWLAs for pointsources andwithintheLAs fornonpointsources and backgroundsources. MostTMDLsaredevelopedusingthesecondapproach,most oftenthroughtheuseofconservative designconditions. In addition, allWLAs,LAs.andTMDLsmustmeetthe State antidegradationprovisionsdevelopedprusuantto the Water QualityStandards Regulation (Section137.12of40CFR Part131,

68November 8, 1983). This regulation establishes explicit procedures that must be followed prior to lowering existing water quality to alevel that stillsupports the Section 101(a)(2) “fishable/ swimmable” goal ofthe Act. WlAs, LAS,and TMDLs that allow such adecline in water quality cannot be established unless the applicable public participation and intergovernmental review requirements ofthe antigradation provisions have been met and all existing usesarefully maintained and protected.


### 4.2.2 WastsoMAkation scrbemes WLASfor water quality-based toxics permits must be set inaccordance with EPAregulations [3, 41. EPAhasdeveloped a number of WIA guidance documents to assist regulatory authorities in developing TMDLs and WtAs. The EPAOffice of Water Regulations and Standards, Assessment and Watershed Protection Division, maintains the latest listing of all WLA guidance documents. Toxic WLA guidance documents are currently available for rivers and streams [5], lakesand reservoirs 161,and estuaries [7]. Cuidante forthe determination ofcritical design conditions for steadystate modeling of rivers and streams also isavailable [8].
Table 4-l lists 19 allocation schemes that may be used by the Statesto develop WLAs. This isnot intended to be acomplete list of approaches; regulatory authorities may use any reasonable allocation scheme that meets the antidegradation provisions and other requirements of State water quality standards [3].
The most commonly used allocation methods have been equal percent removal, equal effluent concentrations, and a hybrid method. The equal percent removal approach can be applied in two ways: the overall removal efficiencies of each pollutant source must be equal, or the incremental removal efficiencies must be equal. The equal effluent concentration approach also can be applied in two acceptable ways-equal final concentrations orequal incremental concentration reductions. This method issimilar to the equal percent removal method ifinfluent concentrations at all sources are approximately the same. However, if one point source hassubstantially higher influent levels, requiring equal effluent concentrations will result in higher overall treatment levels for that source than the equal percent removal appreach

. The final commonly used method of allocating wasteloads is a hybrid method inwhich the criteria for waste reduction may not bethe same for each point source. One facility may be allowed to operate unchanged, while another may be required to provide the entire load reduction. More often, a proportionality rule that requires the percent removal to be proportional to the input loading can be assigned. Inthese cases,larger sources would be required to achieve higher overall removals.



## 4.3 INCIMPLETELY MIXED, DISCHARGE RECEIVING WATER SITUATIOWS
Mixing zones are areas where an effluent discharge undergoes initial dilution and are extended to cover the secondary mixing in the ambient waterbody. A mixing zone isan allocated impact zone where acute and chronic water quality criteria can be exceeded as long as a number of protections are maintained, including freedom from the following:

l Materials in concentrations that settle to form objectionable deposits

. Floating debris, oil, scum, and other matter in concentrations that form nuisances

Table 41. Wasteload Allocation Methods [9]

1. Equal percent removal (equal percent treatment) 2. Equal effluent concentrations 3. Equal total massdischarge per day 4. Equal massdischarge per capita per day 5. Equal reduction of raw load (pounds per day) 6. Equal ambient mean annual quality (mg/l) 7. Equal cost per pound of pollutant removed 8. Equal treatment cost per unit of production 9. Equal massdischarged per unit of raw material used 10. Equal massdischarged per unit of production 11a. Percent removal proportional to raw load per day 11b. Larger facilities to achieve higher removal rates 12. Percent removal proportional to community effective income 13a. Effluent charges (dollars per pound, etc.) 13b. Effluent charge above some load limit 14. Seasonal limits based on cost-effectiveness analysis 15. Minimum total treatment cost 16. Best availability technology (BAT) (industry) plus some level for municipal inputs 17. hsimilative capacity divided to require an “equal effort among all dischargers” 18a. Municipal: treatment level proportional to plant size 18b. Industrial: equal percent between best practicable technology (BPT) and BAT, i.e., Allowable wasteload allocation: (WIA) = BPT- 1i. (BPT-BAT)

19. Industrial discharges given different treatment levels for different stream flows and seasons. Forexample, aplant might not be allowed to discharge when stream flow is below a certain value, but below another value, the plant would be required to use a higher level of treatment than BPT. Finally, when stream flow isabove an upper value, the plant would be required to treat to a level comparable to BPT. L

69l Substances in concentrations that produce objectionable color, odor, taste, orturbidity

l Substances in concentrations that produce undesirable aquatic life or result inadominance of nuisance species. Acutely toxic conditions are defined as those lethal to aquatic organisms that may passthrough the mixing zone. Asdiscussed in Chapter 2, the underlying assumption for allowing a mixing zone isthat asmall area of concentrations in excess of acute and chronic criteria, but below acutely toxic releases,can exist without causing adverse effects to the overall waterbody. The State regulatory agency can decide to allow ordeny amixing zone on a site-specific basis. For a mixing zone to be permitted, the discharger should prove to the State regulatory agency that all State requirements for amixing zone are met.
When wastewater is discharged into a waterbody, its transport may be divided into two stages with distinctive mixing characteristics. Mixing and dilution inthe first stage aredetermined by the initial momentum and buoyancy of the discharge. This initial contact with the receiving water iswhere the concentration ofthe effluent will be itsgreatest inthe water column. The design ofthe discharge outfall should provide ample momentum to dilute the concentrations in the immediate contact area asquickly as possible.
The second stage of mixing covers amore extensive area inwhich the effect of initial momentum and buoyancy isdiminished and the waste is mixed primarily by ambient turbulence. In large rivers or estuaries, this second-stage mixing area may extend for miles before uniformly mixed conditions are attained. In some instances, such aslarger lakes or coastal bays, completely mixed conditions are never reached in the waterbody. The general definition for acompletely mixed condition iswhen no measurable difference in the concentration of the pollutant (e.g., does not vary by more than 5percent) exists acrossany transect ofthe waterbody.
This section provides background information on the policy of mixing zones and the means to characterize them for useinWLAs (Section 4.5). The first subsection discusses the concerns that must be addressed when the boundaries and restrictions of a mixing zone are determined. The second subsection discusses the guidelines for preventing lethal conditions inthe mixing zone.


### 4.3.1 Detlmnlnatian of Mlxlog Z&w Bmtdiwk Allowable mixing zone characteristics should be established to ensure the following:

l Mixing zones do not impair the integrity ofthe waterbody asawhole.

l There is no lethality to organisms passing through the mixing zone.

l There are no significant health risks,considering likely pathways ofexposure (see Section 2.2.2). The Water Quality Criteria-l 972 [lo] recommends that mixing zone characteristics be defined on acase-by-case basisafter it has been determined that the assimilative capacity of the receiving system can safely accommodate the discharge. This assessment should take into consideration the physical, chemical, and biological characteristics of the discharge and the receiving system; the life history and behavior oforganisms inthe receiving system; and the desired usesofthe waters. Nearly all States require such an analysis before they allow amixing zone [l l]. Further, mixing zones should not be permitted where they may endanger critical areas (e.g., drinking water supplies, recreational areas, breeding grounds, areaswith sensitive biota).
EPAhas developed a holistic approach to determine whether a mixing zone is tolerable [12]. The method considers all the impacts to the waterbody and all the impacts that the drop in water quality will have on the surrounding ecosystem and waterbody uses. It is a multistep data collection and analysis procedure that is particularly sensitive to overlapping mixing zones. It includes the identification of all upstream and downstream waterbodies and the ecological and cultural data pertaining to them; the collection of data on all present and future discharges to the waterbody; the assessment of relative environmental value and level of protection needed for the waterbody; and, finally, the allocation ofenvironmental impact foradischarge applicant. Becauseofthe difficulty incollecting the data necessary for this procedure and the general lack ofagreement concerning relative values, this method will be difficult to implement in full. However, the method does serveasaguide on how to proceed in allocating amixing zone.
Most States allow mixing zones as a policy issue, but provide spatial dimensions to limit the areal extent of the mixing zones. The mixing zones arethen allowed (or not allowed) after case-bycasedeterminations. State regulations dealing with streams and rivers generally limit mixing zone widths, cross-sectional areas, and flow volumes and allow lengths to be determined on acaseby-case basis. Forlakes,estuaries, and coastal waters, dimensions are usually specified by surface area, width, cross-sectional area, and volume.
Where a mixing zone isallowed, water quality standards are met at the edge of that regulatory mixing zone during design flow conditions and generally, (1) provide a continuous zone of passage that meets water quality criteria for free-swimming and drifting organisms and (2) prevent impairment ofcritical resource areas. Individual State mixing zone dimensions are designed to limit the impact ofamixing zone onthewaterbody. Furthermore, EPA’sreview of State WLAsshould evaluate whether assumptions of complete or incomplete mixing are appropriate based on avaitable data.
In river systems, reservoirs, lakes, estuaries, and coastal waters, zones of passage are defined ascontinuous water routes of such volume, area, and quality asto allow passage of free-swimming and drifting organisms sothat no significant effects are produced on their populations. Transport of avariety of organisms in river water and by tidal movements in estuaries isbiologically important in a number of ways: food is carried to the sessile filter

70feeders and other nonmobile organisms, spatial distribution of organisms and reinforcement of weakened populations are enhanced, and embryos and larvae of some fish species develop while drifting [ll], Anadromous and catadromous species must be able to reach suitable spawning areas. Their young (and in some cases the adults) must be assured a return route to their growing and living areas. Many species make migrations for spawning and other purposes. Barriers or blocks that prevent or interfere with these types of essential transport and movement can be created by water with inadequate chemical or physical quality.
As explained above, a State regulatory agency may decide to deny a mixing zone in a site-specific case. Forexample, denial should be considered when bioaccumulative pollutants are inthe discharge. The potential for apollutant to bioaccumulate in living organisms ismeasured by (1) the bioconcentration factor (BCF), which ischemical-specific and describes the degree to which an organism or tissue can acquire a higher contaminant concentration than itsenvironment (e.g., surface water); (2) the duration of exposure; and (3) the concentration of the chemical of interest. While any BCFvalue greater than 1indicates that bioaccumulation potential exists, bioaccumulation potential isgenerally not considered to be significant unless the BCFexceeds 100 or more. Thus, achemical that isdischarged to a receiving stream, resulting in low concentrations, and that has a low BCFvalue will not create a bioaccumulation hazard. Conversely, achemical that is discharged to areceiving stream, resulting inalow concentration but having a high BCFvalue, may cause in a bioaccumulation hazard. Also, some chemicals of relatively low toxicity, such as zinc, will bioconcentrate in fish without harmful effects resulting from human consumption.
Another example ofwhen aregulator should consider prohibiting amixing zone isinsituations where aneffluent isknown to attract biota. In such cases, provision of a continuous zone of passage around the mixing area will not serve the purpose of protecting aquatic life. A review of the technical literature on avoidance/ attraction behavior revealed that the majority oftoxicants elicited an avoidance or neutral response at low concentrations [13]. However, some chemicals did elicit anattractive response, but the data were not sufficient to support any predictive methods. Temperature can be anattractive force and may counter anavoidance response to a pollutant, resulting in attraction to the toxicant discharge. Innate behavior such asmigration may alsosupersede an avoidance response and cause fish to incur asignificant exposure.


### 4.32 Minimkhg theSheofMixingZones Concentrations above the chronic criteria are likely to prevent sensitive taxa from taking up long-term residence in the mixing zone. Inthis regard, benthic organisms and territorial organisms are likely to be of greatest concern. The higher the concentrations occurring within an isopleth, the more taxa are likely to be excluded, thereby 

### affecting the structure and function of the ecological community. It is thus important to minimize the overall sizeofthe mixing zone and the sizeofelevated concentration isopleths within the mixing zone. 

### 4.3.3 PreventionofLethalftytoPassinglkgankms The WaterQuo/ity Standards Handbook [14] indicates that whether to establish a mixing zone policy isa matter of State discretion, but that any State policy allowing for mixing zones must be consistent with the CWA and is subject to approval of the Regional Administrator. The handbook provides additional discussion regarding the basisfor aState mixing zone policy. Lethality isafunction of the magnitude of pollutant concentrations and the duration an organism isexposed to those concentrations. Requirements forwastewater plumes that tend to attract aquatic life should incorporate measures to reduce the toxicity 

### (e.g., via pretreatment, dilution) to minimize lethality or any irreversible toxic effects on aquatic life.
EPA’s water quality criteria provide guidance on the magnitude and duration of pollutant concentrations causing lethality. The criterion maximum concentration (CMC) is used asa means to prevent lethality orother acute effects. h explained inAppendix D,the CMC isatoxicity level and should not be confused with an LCso level. The CMC isdefined asone-half ofthe final acute value for specific toxicants and 0.3 acute toxic unit (TU,) for effluent toxicity (seeChapter 2). The CMC describes the condition under which lethality will not occur ifthe duration ofthe exposure tothe CMC level islessthan 1hour. The CMC forwhole effluent toxicity is intended to prevent lethality or acute effects in the aquatic biota. The CMC for individual toxicants prevents acute effects in all but a small percentage of the tested species. Thus, the areal extent and concentration isopleths of the mixing zone must be such that the l-hour average exposure of organisms passing through the mixing zone is lessthan the CMC. The organism must be able to passthrough quickly orflee the hiqh-concentration area. The objective of developing water quality recommendations for mixing zones isto provide time-exposure histories that produce negligible or no measurable effects on populations of critical species inthe receiving system. Lethality to passing organisms can be prevented in the mixing zone inone offour ways. The first method isto prohibit concentrations in excess of the CMC in the pipe itself, as measured directly at the end of the pipe. Asan example, the CMC should be met in the pipe whenever acontinuous discharge ismade to an intermittent stream. The second approach isto require that the CMC be met within a very short distance from the outfall during chronic design-flow conditions for receiving waters (see Section 4.4.2).
If the second alternative is selected, hydraulic investigations and calculations indicate that the use of a high-velocity discharge with an initial velocity of 3 meters per second, or more, together with a mixing zone spatial limitation of 50 times the discharge length scale in any direction, should ensure that the CMC is met within a few minutes under practically all conditions. The discharge length scale isdefined as the square root of the cross-sectional area of any discharge pipe.
Athird alternative (applicable to any waterbody) is not to use a high-velocity discharge. Rather the discharger should provide

71

### - --

data tothe State regulatory agency showing that the most restrictive ofthe following conditions are met for each outfall:
The CMC should be met within 10 percent ofthe distance from the edge of the outfall structure to the edge of the regulatory mixing zone inany spatial direction.
The CMC should be met within adistance of 50 times the discharge length scale in any spatial direction. Inthe case of a multiport diffuser, this requirement must be met for each port using the appropriate discharge length scale of that port. This restriction will ensure adilution factor of at least 10 within this distance under all possible circumstances, including situations of severe bottom interaction, surface interaction, or lateral merging.
The CMC should be met within adistance offive times the local water depth in any horizontal direction from any discharge outlet. The local water depth isdefined as the natural water depth (existing prior to the installation ofthe discharge outlet) prevailing under mixing zone design conditions (e.g., low flow for rivers). This restriction will prevent locating the discharge invery shallow environments or very close to shore, which would result insignificant surface and bottom concentrations.
A fourth alternative (applicable to any waterbody) is for the discharger to provide data to the State regulatory agency showing that a drifting organism would not be exposed to l-hour average concentrations exceeding the CMC, orwould not receive harmful exposure when evaluated by other valid toxicological analysis, as discussed in Section 2.2.2. Such data should be collected during environmental conditions that replicate critical conditions.
For the third and fourth alternatives, examples of such data include monitoring studies, except for those situations where collecting chemical samples to develop monitoring data would be impractical, such as at deep outfalls in oceans, lakes, or embayments. Other types of data could include field tracer studies using dye, current meters, other tracer materials, or detailed analytical calculations, such as modeling estimations of concentration ordilution isopleths.
The Water Quality Criteria-l 972 [l l] outlines a method, applicable to the fourth alternative, to determine whether a mixing zone istolerable for afree-swimming or drifting organism. The method incorporates mortality rates (based on toxicity studies for the pollutant of concern and a representative organism) along with the concentration isopleths of the mixing zone and the length of time the organism may spend in each isopleth. The intent of the method is to prevent the actual time of exposure from exceeding the exposure time required to elicit aneffect [lo]:



### 1 T0-4 <, ET(X)at C(n) -
where T(n) isthe exposure time an organism isin isopleth n, and ET(X) is the “effect time.” That is, ET(X) isthe exposure time required to produce an effect (including a delayed effect) in X percent of organisms exposed to a concentration equal to C(n), the concentration in isopleth n. ET(X) is experimentally determined; the effect isusually mortality. Ifthe summation of ratios of exposure time to effect time islessthan 1,then the percent effect will not occur.


### 4.3.4 mvootho of Bio%cc~l~ioo Rvblmos for Muman

States are not required to allow mixing zones. Where unsafe fish tissue levels or other evidence indicates a lack of assimilative capacity in a particular water-body for a bioaccumuiative pollutant, care should be taken in calculating discharge limits for this pollutant or the additivity of multiple pollutants. In particular, relaxing discharge limits because of the provision of a mixing zone may not be appropriate in this situation.



## 4.4 MIXMG ZOHE ANALYSES
Proper design of a mixing zone study for a particular waterbody requires estimation of the distance from the outfall to the point where the effluent mixes completely with the receiving water. The boundary isusually defined asthe location where the concentrations across atransect of the waterbody differ by lessthan 5 percent. The boundary can bedetermined based onthe results of a tracer study or the use of mixing zone models. Both procedures, along with simple order-of-magnitude dilution calculations, are discussed inthe following subsections.
If the distance to complete mixing is insignificant, then mixing zone modeling isnot necessary and the fate and transport models described in Section 4.5 can be used to perform the WLA. It is important to remember that the assumption of complete mixing isnot aconservative assumption for toxic discharges; an assumption of minimal mixing is the conservative approach. If completely mixed conditions do not occur within a short distance ofthe outfall, the WLAstudy should rely on mixing zone monitoring and modeling. Justasin the caseofcompletely mixed models, mixing zone analysis can be performed using both steady-state and dynamic techniques. State requirements regarding the mixing zone will determine how water quality criteria are used in the TMDL.
This section isdivided into five subsections. The first discusses recommendations for outfall designs and means to maximize initial dilution. The second provides abrief description ofthe four major waterbody types and the critical design period when mixing zone analysis should be performed for each. The third provides a brief description of tracer studies and how they may be used to define a mixing zone. The fourth and fifth subsections discuss simplified methods and sophisticated models to predict the two stages of mixing (i.e., discharge-induced and ambientinduced mixing). Fora detailed explanation of the mechanisms involved in estimating both stages of mixing, two references are recommended, Halley and Jirka [15] and Fischer et al. [16]. Although the models presented in Sections 4.4.4 and 4.4.5 simplify the mixing process, the assessorshould have an understanding of the basic physical concepts governing mixing to usethese

72models appropriately. (The U.S. EPACenter for Exposure Assessment Modeling [CEAM] inAthens, Georgia, provides an overview course that teaches the basics of mixing and how the basics should be used for water quality management.)
It is important to note that the mixing zone models presented here attempt to predict the dispersion and dilution ofthe effluent plume. They do not attempt to predict any removal ortransformation ofthe pollutants. Inthe nearfield, dispersion and dilution caused by discharge-induced mixing and then ambient-induced mixing will bethe major cause oftoxicity reduction. Ifincomplete mixing persists downstream (such asinthe caseofshore hugging plumes), then some far-field processes will become important. Some of the models described in Section 4.5 that have sophisticated hydrodynamic simulation routines coupled with fate simulation routines may be used for these far-field, incomplete mixing analyses.

An important factor in maximizing the initial dilution of an effluent is the design of the effluent outfall. There are three major types ofoutfall designs: surface discharge from freeflows inapipe or canal, single-port submerged discharge, and multiport submerged discharge. The lasttype isoften referred to asmultiport diffusers. Of the three, the surface discharge type is the least favorable for toxic discharges since itoffersthe least initial mixing. In particular, surface discharges at the shoreline of awaterbody usually have an impact along the shoreline when there issignificant cross-flow and thus yield high surface concentrations. Submerged discharges offer more flexibility in meeting the design goals for toxic discharges. Submerged discharges may be in the form of asingle pipe outlet or of multiport discharges (diffusers) giving riseto one or several submerged discharge jets. Atypical diffuser section isillustrated in Figure 4-1. Submerged discharges allow the effluent to bedirected atdifferent angles tothe ambient flow to maximize the initial dilution. Diffusers are particularly effective incounteracting the buoyancy ofthe effluent. However, submerged muttiport discharges are only feasible in waterbodies that are of sufficient depth and are not subjected to periodic dredging orto considerable scour or deposition.

0.20 m x0.15 m 90” reducer elbow 0.15 m cast-iron pipe \ \ / F’ange Top of tremle encasement ‘t7i / Flannta m,nl

flange with 0.15 mcasliron trap at Invert 0.15 m 90” elbow Bottom oftremle / encasement

Figure 4-l. ATypical Diffuser Section [17] Many of the complexities of submerged diffusers have been summarized by jirka [I 81,Halley and Jirka[15], and Roberts et al. [19, 20, 211. Submerged discharges should be designed to avoid direct surface impingement and bottom attachment ofthe submerged jet or jets. Surface and bottom impacts should be evaluated at critical design conditions (low flow or high stratification) and at off-design conditions (higher flow or lower stratification) to ensure the best placement and design of the diffuser. Diffusers provide more dilution than single outlets, but the alignment ofthe diffuser with the receiving water flow direction influences how much dilution will be provided. Ifthe outlet structure isdirected parallel to the direction of flow, dilution under high ambient velocities (off-design conditions) may be lower than under low velocities (critical design conditions).
In rivers, the preferred arrangement for asubmerged discharge is to direct the outlet into the current flow direction or vertically upward. To deal with the reversing currents of estuaries and coastal bays, the preferred arrangements for offshore discharges are parallel diffuser alignment (tee diffuser) and perpendicular diffuser alignment (staged diffuser) [18]. In lakesand reservoirs, the preferred arrangement for a negatively buoyant discharge is to direct the diffuser vertically upward. A positively buoyant, vertically directed jet could penetrate stratification, sothe preference for this type of discharge isto orient the diffuser at aslight angle above the horizontal. For ocean outfalls, initial dilution is improved by longer (perpendicular to the shoreline) and deeper diffusers. Further, the ports of the diffuser should be sufficiently separated to minimize merging ofthe separate plumes [22].


### 4.4.2 CriticalDes&nPeriodsforWatehdies Thissection provides abrief description ofthefour major waterbody types and defines the critical design periods that should be used when performing mixing zone analyses ineach ofthese waterbody types. Appendix Dprovides afurther discussion on the appropriate selection of design periods. 1) Rivers and Run-of-River Reservoirs
Rivers and run-of-river reservoirs are waterbodies that have a persistent throughflow in the downstream direction and do not exhibit significant natural density stratification. Recommendations for hydrologically based and biologically based design flows for completely mixed, steady-state modeling of rivers are described inAppendix Dof this document. The biologically based design flows are determined using the averaging periods and frequencies specified inwater quality criteria [8]. Also, the hydrologically based flows 1QlO and 7410 for the CMC and CCC, respectively, have been used traditionally and may continue to be used for steady-state modeling. Run-of-river reservoirs with residence times lessthan 20 days at critical conditions also should be analyzed using biologically or hydrologically based design flows (seebelow). Regulated rivers may have aminimum flow inexcess of these toxicological flows. In such cases, the minimum flow should be used inTMDL modeling. 2) Lakes and Reservoirs
This receiving water category encompasses lakes and reservoirs with residence times in excess of 20 days at critical conditions

73[23]. Seasonal variations in the water level, wind speed and direction, and seasonal solar radiation should be determined to define the critical period [23]. In the case of long and narrow reservoirs, areas above the plunge point (i.e., areas where no stream-like flow ispresent and waters are mixed or stratified by density) can be analyzed as rivers. The areas below can be analyzed asreservoirs. Since effluent density relative to the ambient water can vary over seasons, no one season or stratification condition can beselected asthe most critical dilution situation for all cases. In general, all four seasons should be analyzed to determine the most critical periods for mixing zone analyses. All seasonal analyses should assume an ambient velocity of zero unless persistent currents have been documented. Special attention should be given to periods of rising water level since pollutants can move back into coves and accumulate under these conditions. Location of discharges in coves and dead-end embayments should be prevented whenever possible. 3) Estuaries and Coastal Bays
This receiving water category encompasses estuaries, which are defined as having a main channel reversing flow, and coastal bays, which are defined as having significant two-dimensional flow in the horizontal directions. For both waterbodies, the critical design conditions recommended here are based on astronomical, not meteorotogicat, tides. Determining the nature and extent of the discharge plume is complicated in marine systems by such conditions asdifferences in tides, riverine input, wind intensity and direction, and thermal and saline stratification. Because ofthe tidal nature ofthe estuaries and coastal systems and their complex circulation patterns, dilution ofdischarges cannot bedetermined simply by calculating the discharge rate and the rate of receiving water flow (i.e., the design flow). For example, tidal frequency and amplitude vary significantly in different coastal regions of the United States. Furthermore, tidat influences at any specific location have daily and monthly cycles. These and additional factors require that direct, empirical steps be taken to ensure that basic dilution characteristics ofadischarge to saltwater are determined.
tn estuaries without stratification, the critical dilution condition includes a combination of low-water slack at spring tide for the estuary and design low flow for riverine inflow. Inestuaries with stratification, asite-specific analysis ofaperiod of minimum stratification and a period of maximum stratification, both at lowwater slack, should be made to evaluate which one results in the lowest dilution. Ingeneral, minimum stratification isassociated with low river inflows and large tidal ranges (spring tide), whereas maximum stratification isassociated with high river inflows and low tidal ranges (neap tide).
After either stratified or unstratified estuaries are evaluated at critical design conditions, an off-design condition should be checked. The off-design condition (e.g., higher flow or lower stratification) recommended for both cases isthe period of maximum velocity during a tidal cycle. This off-design condition results in greater dilution than the design condition, but it causes the maximal extension ofthe plume. Extension ofthe plume into critical resource areas may cause more water quality problems than the high-concentration, low-dilution situation. Recommendations for a critical design for coastal bays are the same asfor stratified estuaries. The period of maximum stratification must becompared with the period of minimum stratification in order to select the worst case. The off-design condition of maximum tidal velocity should also be evaluated to predict the worst-case extent ofthe plume. 4) Oceans
Critical design periods for ocean analyses are described in two separate documents, the Section 301(h) Technical Support Document [22] and the Section 301(h) document, hitid Mixing Characteristics ofMunicipal Ocean Discharges [24]. The following subsection contains a summary from these documents. Like discharges to estuaries, discharges to ocean waters are subject to two-dimensional horizontal flows. Oceanic critical design periods must include periods with maximum thermal stratification, or density stratification. These periods shorten the distance ofvertical diffusion that occurs in the zone of initial dilution. Thus, during these periods it isdifficult to achieve the recommended loo-to-1 dilution that is to occur before the plume begins a predominantly horizontal flow ascompared to vertical flow. Periods when discharge characteristics, oceanographic conditions (spring tide and neap tide currents), wet and dry weather periods, biological conditions, or water quality conditions that indicate that water quality standards are likely to be exceeded should also be noted. The 10th percentile value from the cumulative frequency ofeach parameter should be used to define the period of minimal dilution.


### 4.4.3 lbwml Rwmmwht&as forTracer 3iudk Atracer ordye study can be used to determine the areal extent of mixing in a waterbody, the boundary where the effluent has completely mixed with the ambient water, and the dilution that results from the mixing. Analysis ofthe mixing zone with adye study that issupplemented with modeling should be performed at flow conditions that approach critical flow. Some of those design conditions are summarized above inthe subsections dealing with specific waterbodies. Once the critical design condition hasbeen selected for awaterbody, dye studies can be performed to provide data onthe dimensions and dilution ofthe wastewater plume during this critical period. Tracer studies other than dye studies (e.g., chloride, lithium) can be performed for cases in which the receiving water isamenable to such tests.
For WIA studies in which a discharge is already in operation, tracer studies can be used to determine specific concentration isopleths in the mixing zone that reflect both discharge-induced and ambient-induced mixing. The isopleth concentrations, with effluent toxic concentrations, should be superimposed over a map of Ihe various resource zones of the waterbody. The map will illustrate whether the State’s mixing zone dimensions are exceeded, whether the required zone of passage isprovided, and whether the plume avoids critical resource areas. The WLA can then be calculated to provide the appropriate zone of passage and to prevent detrimental impacts on spawning grounds, nurseries, water supply intakes, bathing areas, and other important resource areas. Obviously, ifthe outfall isnot yet in operation, it isimpossible to determine discharge-induced mixing by tracer studies. Tracer

74studies can be used inthese situations to determine characteristics of the ambient mixing. For ambient mixing studies, the tracer release can be either instantaneous or continuous. Instantaneous releases are used frequently to measure longitudinal dispersion, but can also be used to determine lateral mixing in rivers [15] and lateral and vertical mixing in estuaries, bays, reservoirs, and lakes. For waterbodies with significant flow velocities, continuous releasesoftracer are normally used to determine lateral and vertical mixing coefficients. Continuous releases can also be used to determine three-dimensional concentration isopleths for steadystate conditions. Thetracer study must be made at critical design conditions in order to usethe results directly for WlAs. Ifatracer study for ambient mixing isconducted at near-to-design conditions, the observed data can be used to determine dimensionless mixing coefficients. These coefficients can then be extrapolated to critical conditions using hydraulic parameters [15]. A tracer study at near-to-critical conditions also 

### canbe used to determine the computer model required to predict critical-condition mixing and provide the coefficients needed for that TMDL model.
A number of references provide information concerning the design, conduct, and analysis of tracer studies for mixing analyses. Techniques of Water-Resources Investigations ofthe USC.5provides the best overview of how to conduct tracer studies [25, 26, 271. The fluorescent dyes (usually Rhodamine WT), measuring equipment, fluorometers, field and laboratory procedures, and calculation methods areall discussed. The procedures essentially consist ofadding dye to the waterbody and recording concentrations of the dye at various stations at specific time intervals. Examples of tracer studies for river systems are presented in Fischer [28]; Kisiel [29]; Holley and )irka [l 51;and Yotsukura, Fisher,and Sayre [30]. Examples oftracer studies intidal systems are presented inWilson, Cobb, and 

### Yotsukura[31] and Hetling and O’Connell [32], both of which are studies of the Potomac River estuary; Baily [33], a study of Suisun Bay in California; Fischer [34], a study of Bolinas Lagoon, acoastal bay in Marin 

### County, California; and Cracker et al. [35], astudy ofCorpus Christi Bay,Texas. Methods to perform atracer study in areservoir are provided injohnson [36].
The dye study recommended for obtaining a quick saltwater dilution assessment isone inwhich Rhodamine WTdye isadministered to adischarge and monitored in the receiving waters for not lessthan 24 hours. The basic goal ofthis study isto determine the near-field nature of the effluent dilution, not the steady-state orfar-field dilution. The environmental and discharge conditions selected for the study should be those that would elicit “worstcase” conditions (i.e., highest ambient concentrations in the receiving water). These include low wind, neap tide (tide of minimum range occurring during the 1st and 3rd quarters of the moon), plume trapping by density stratification, low rainfall and low riverine input, and, ifpossible, high effluent discharge.
The dye should be administered to the effluent before discharge to the receiving water in proportion to effluent flow rate. Dye should be maintained at aconcentration in the effluent sufficient to permit detection of the dilution ratio of interest when the amount and variability of background fluorescence in the receiving water are taken into account. Measurements of dye concentration are made using afluorometer and should becorrected for water temperature. A 

### survey of background fluorescence and its variability in the anticipated mixing zone must be conducted just prior to the beginning of the study in order to permit correction of fluorescence data and to determine the dye concentration required in the effluent. Since Rhodamine Wl dye isbleached by free chlorine, a preliminary study of the degree of dye bleaching by the effluent should precede the study for chlorinated discharges to avoid underestimation of the extent of the mixing zone. Dye concentrations should be surveyed for two successive slacktides, and for any other conditions that could lead to concentration maxima. Surveys should extend from the point ofdischarge to a distance atwhich the effluent dilution ratio of interest isattained. The dye fluorescence at this point should be at least twice the variability in background fluorescence.
EPA has completed two TMDL studies to test the procedures outlined in the previous version of this document. Both studies used dye to determine the mixing zone and the dilution within it. The first study was performed on the Amelia River, an estuarine system in Florida [2]; the second was performed on the Creenwith Cove, an embayment of Narragansett Bay in Rhode Island [37]. In both studies, Rhodamine Wl dye was introduced continuously into the effluent and numerous stations were set up 

### to measure the spatial and temporal distribution of the dye. Both studies are good examples of how to perform a dye study in complex tidal systems.


### 4.4.4 Discharge-induced Mixing The first stage of mixing iscontrolled by discharge jet momentum and buoyancy ofthe effluent (see Figure 4-2). This stage generally covers most of the regulatory or near-field mixing zone. It is particularly important in lakes and reservoirs and slow moving rivers since ambient mixing inthose waterbodies is minimal.
In shallow environments, it is important to determine whether near-field instabilities occur. These instabilities, associated with surface and bottom interaction and localized recirculation cells extending over the entire water depth, can cause buildup of effluent concentrations by obstructing the effluent jet flow. There are no simple means to estimate dilution in these cases. Criteria for these instabilities and specialized predictive models have been developed to address these problems [13].
In

### the absence of near-field instabilities, horizontal or nearly horizontal discharges will create a clearly defined jet in the water column that will initially occupy only a small fraction of the available water depth. The following equations and models are designed to describe mixing under stable near-field conditions. 1) Use of aSimplistic Screening Equation
A minimum estimate ofthe initial dilution available inthe vicinity of adischarge can be made using the following equation derived from information in Holley and lirka (1986) [15]:

s=o.3 ; where 5 = flux-averaged dilution X = distance from outlet d = diameter ofoutlet.

75recelvlng waler surface /

recewmg water bottom

c) Deep-wafer, high-buoyancy, nonvertical discharge

recelvlng water surface /

receiving water bottom
d) St-tallow-water. low-buoyancy, nonvertical dischargeIFigure 42. Example of Discharge-Induced Mixing [7]

The coefficient 0.3 represents the average of two values derived from the literature, 0.28 [16] and 0.32 [38].
The equation provides aminimum estimate of mixing because it is based on the assumptions that outlet velocity iszero and the discharge isneutrally buoyant. Dilution may be underestimated for partially fuHpipes because the equation assumes afully flowing pipe. The equation can be used in inverse form to solve for the discharge x at which a desired solution-for example, that corresponding to the CMC-has been achieved. The equation is valid only close to the discharge, up to adistance corresponding to several (two to three) water depths. At longer distances, other factors are of increasing importance in jet mixing and must be included. Mixing graphs that include the effects of discharge buoyancy, ambient velocity, and stratification can be found in Halley and Jirka[15], Fischer et al. [16], and Wright [39]. They are useful to account for these other initial dilution factors and can aid in determining whether criteria will be met at the edge of the regulatory mixing zone. 2) Use of Detailed Computer Models
More detailed design data for the mixing zone can be obtained from the use of computer models based on integral jet techniques. It is important to note that most models represent an idealization of actual field conditions and must be used with caution to ensure that the underlying model assumptions hold for the site-specific situation being modeled. Ingeneral, these buoyant jet models require the following input data: discharge depth, effluent flow rates, density ofeffluent, density gradients in receiving water, ambient current speed and direction, and outfall characteristics (port size, spacing, and orientation). Model output includes the dimensions of the plume at each integration step, time of travel to points along the plume centerline, and the average dilution at each point.
Described below are six mixing zone models that are available through EPA.Allofthe models require auserwho iswell versed in mixing concepts and the data necessary to run the models. The first model, CORMIX [40, 411, may be the most useful to regulators since it isanexpert system that guides the userinselecting an appropriate modeling strategy for rivers orestuaries. Itisavailable from the National Technical Information Service (NTIS), and user support isavailable from the U.S. EPACEAM. The other models were developed and designed for ocean discharges. All but one can be used on rivers, lakes, and estuaries with appropriate input modifications; UPLUME is restricted to stagnant water environments where the ambient water current velocity is zero (e.g., lakes, reservoirs).
These five models were designed for submerged discharges in oceans. They all report dilution, and all terminate execution when the vertical ascent of the plume is zero (e.g., when the plume reaches the surface or when plume density is equal to ambient density in some stratified systems). With the exception of CORMIXl, they all assume that there is a “deep” receiving stream (i.e., no bottom interference). They too are available from NTIS, and user support is provided by the U.S. EPA Hatfield Marine Science Center in Newport, Oregon [24]. These five models have been modified such that the user inputs the data into a universal data format that allows the user to apply any of the five models with only minor input changes.

l CORMIX isaseriesofsoftware elements for the analysis and design of a submerged buoyant or nonbuoyant discharge containing conventional or toxic pollutants and entering into stratified or unstratified watercourses, with emphasis on the geometry and dilution characteristics of the initial mixing zone. Subsystem CORMlXl deals with single-port discharges, and subsystem CORMIXZ addresses multiport diffusers. The system operates on microcomputers with the MS-DOS operating system. CORMlXl can summarize dilution characteristics ofthe proposed design, flag undesirable designs, give dilution characteristics atspecified boundaries (i.e., legal and toxic mixing zones) and recommend design alterations to improve dilution characteristics. The CORMlXl program guides the user, based on the user’s input, to

76appropriate analyses of design conditions and mixing zone dimensions.

l UPLUME is an initial dilution model that can be used for stagnant waterbodies, such as lakes and reservoirs, where the ambient currents can be assumed to be zero. The model simulates a submerged single-port discharge. The bouyancy between the effluent and ambient water can be accounted for, and the discharge can be given a vertical angle. UPLUME calculates flux-averaged dilutions and, for one output option, acenterline dilution.

l UOUTPLM can be usedinflowing and stagnant waterbodies. The user specifies the current speed ofthe ambient water, and this speed isassumed to be constant with depth. The model simulates asubmerged single-port discharge. Buoyancy between the effluent and ambient water can be modeled, aswell as the discharge vertical angle. The ambient current isassumed to be perpendicular to the diffuser.

l UMERCE isa model that can also be used for both flowing and stagnant waters. It has capabilities that UOUTPLM does not have: it considers multiple submerged ports, and the user can specify arbitrary ambient current speed variations with depth. The ports are assumed to be equally spaced. The model accounts for adjacent plume interferences over the course of the plume trajectory and in the subsequent dilution calculation. Positive buoyancy isaccounted for, and the discharge vertical angle can be modified. The ambient current isassumed to be perpendicular to the diffuser.

l UDKHDEN isathree-dimensional model that can be used for flowing and stagnant waterbodies. It has all the capabilities of UMERCE plus the ability to simulate instances where the ambient current flow isnot perpendicular to the diffuser.

l ULINE models a vertical slot jet discharge into a flowing waterbody. The discharge angle isassumed to be perpendicular to ambient current. The ambient current may vary with depth, and the axis of the diffuser may range from parallel to perpendicular tothe ambient current. The buoyancy ofthe effluent can also be modeled.
An evaluation and comparison ofallthese models can befound in the Technical Guidance Manual for Performing Wastelood Allocations-&ok 3, Estuaries[ 71.

4.4.5 

### Ambieut-inducedMixing The equations for discharge-induced mixing can be used to predict concentrations in the regulatory mixing zone where strong jet mixing predominates over ambient mixing. Beyond this point, the mixing iscontrolled by ambient turbulence. Thus, ambient mixing models must be used to predict the pollutant concentration distributions up to the stage of complete lateral mixing to provide boundary conditions for the completely mixed fate and transport models described in Section 4.5. This information also may be needed to estimate concentrations encountered at important resource areas or at subsequent downstream dischargers. Ifthere is no discharge-induced vertical mixing associated with the jet action ofthe discharge, then mixing over the depth ofthe waterbody must be accomplished by ambient mixing. For a neutrally buoyant, soluble effluent discharged with low velocity at the surfaceor atthe bed ofastream, the flow distance required to achieve complete vertical mixing is on the order of 50 to 100 times the depth ofwater inthat portion ofthe channel where the effluent isdischarged [42]. Foradischarge that iseither lighter (positively buoyant) or heavier (negatively buoyant) than the ambient water, but still has no excess momentum, the flow distance for mixing over the depth will be greater. Inthe normal casewith a high-velocity jet designed to prevent lethality in the mixing zone, mixing over the depth will be accomplished primarily byjet action, and the distance required for this vertical mixing will be much shorter.
Ingeneral, ambient mixing must alsoaccomplish mixing over the width of a waterbody to bring the effluent to the completely mixed condition. Forsituations where the width ofthe zone that ismixed by the discharge-induced mixing is much smaller than the width ofthe river, the flow distance (X,) required to achieve the completely mixed condition may be estimated from anequation ofthe form [16]:

x,= mW2u DY where W = width ofthe river U = flow velocity for the critical design flow Dy = lateral dispersion coefficient asdiscussed below m = aparameter whose value depends on the degree of uniformity used to define “complete mixing” and on the transverse location ofthe outfall inthe stream.

Ifcompletely mixed conditions are defined asa S-percent variation in concentration across the stream width, the value of m would be approximately 0.1 for a discharge near the center of riverflow (not the center of riverwidth) and approximately 0.4 for a discharge near the edge of the river. If, because of other uncertainties, a25percent variation across the width isaccepted asbeing completely mixed, then the corresponding values for m would be approximately 0.06 for adischarge near the center of riverflow and approximately 0.24 for adischarge near the edge of the river. Foravery small stream, X, may be only afew hundred feet; for medium and large streams, X, isnormally several miles to several tens ofmiles.
The lateral dispersion coefficient (Dy) for most rivers can be calculated with the following equation [16]:

where Dy =0.6 du* f 50%
d = water depth at design flow u’ = shearvelocity.
The coefficient (0.6) can vary from 0.3 to above 1.Odepending on the type and degree of irregularity of the channel crosssections. The more straight and uniform the flow, the tower the

77value; the more irregular the flow (resulting from curves, sidewall interference, etc.), the higher the value. Values approaching and exceeding 1.Oare normally associated with significant channel meandering [42]. Thefollowing equation forshearvelocity should be used [16]:
u* = (gds)‘/2 where 9 = acceleration due to gravity S = slope ofthe channel d = water depth.
Fordiffusers that initially spread the discharge across asignificant part of the river width or for caseswhere the discharge-induced mixing causes mixing across asignificant part of the river width, the values of m and X, can be smaller than the ones indicated here. Fordistances greater than X,, the models for completely mixed effluents discussed in Section 4.5 can be used to calculate concentrations at these distances. For shorter distances, maximum concentrations can be much greater than those predicted by “completely mixed” models and should be estimated using the following equation: c, = 

## CeQeW

where C, = maximum pollutant concentration distance xfrom the outlet C, = effluent concentration Qe = design effluent flow Qs = design stream flow Dy = lateral dispersion coefficient X = distance from the outlet W = stream width U = flow velocity for the design flow.
Itshould be noted that this estimate of C, isaworst-case prediction since the equation assumes no significant discharge-induced mixing and aneutrally buoyant effluent. Amore accurate way to predict concentrations within this second stage ofmixing isto use the methods ofYotsukura and Sayre [42]. To usethis approach, however, the value of Dy and pollutant concentrations after discharge-induced mixing must be known from tracer studies and/ orfrom the useofone ofthe discharge-induced models.
The PSYmodel can be used to predict ambient mixing inshallow, freshwater streams where water depth issmall in proportion to the width. PSYisa steady-state, two-dimensional plume model that predicts dilution ofasurface discharge into ashallow receiving water where the plume attaches to both bottom and nearshore [43]. Uniform vertical mixing isassumed to occur atthe point of discharge.
Ambient mixing is minor for lakes and reservoirs because flow velocity is

### assumedto be minimal and mixing isaccomplished by means ofthe discharge momentum and buoyancy. Forestuaries that are completely mixed with regard to salinity, the equations presented above can be used to estimate concentrations between the outlet and the point of complete mixing with aslight modification ofshearvelocity. The above equations will beapplicable to only unstratified estuaries since the time required to mix across the estuary must be significantly lessthan the time required for the effluent to passout ofthe unstratified part ofthe estuary, the time required for the effluent to pass into a segment of greatly changed cross-section, or the time required for the substance to decay. When the above equations for estuaries are used, the velocity ofthe design flow should include the velocity associated with the inflow offreshwater aswell asthe tidal velocity; thus ut, which isbased on an average total velocity; issubstituted for u in the equations and shearvelocity becomes
lJ*=0.10 ut. The CORMlX expert system model can also be used to obtain predictions for the ambient-induced mixing. In addition to the routines for discharge-induced mixing, this model also includes predictiveelements that apply to ambient mixing in riverine, lake, or coastal situations.



## 4.5CDMPl.ElElY MIXED DtSCHARGE RECEIVING WATER SITIJATIDNS

At the present time, most Statesand EPARegions usesteady-state models that assume the wastewater iscompletely mixed with the receiving waters in order to calculate WLAS for contaminants. Thisapproach isappropriate forconventional contaminants where critical environmental effects are expected to occur far downstream from the source. WLAs for toxic chemicals require a different approach, however, because critical environmental conditions occur near the discharge before complete mixing with the receiving water occurs. Consequently, mixing analyses should be performed because many of these toxicants can exert maximal toxicity inavariety of regions spanning from the discharge point to significant distances downstream.
Ifcomplete mixing occurs near the discharge point, such as in effluent-dominated receiving streams, then steady-state models may be used to calculate TMDLs. Recent EPAdevelopments in the identification of critical design flows based on toxicological concerns provide for better use

### ofsteady-state models incalculating toxic WLAS. However, ifcomplete mixing does 

### notoccurnear the discharge point and the effluent plume isdiscernible downriver, then modeling techniques that can simulate and predict mixing conditions are more appropriate. The mixing zone models presented in the previous section may be used to define the mixing zone. However, they only determine the dispersion and dilution of the effluent and do not account for chemical or biological processes in the mixing zone. TMDL models are available that can simulate mixing processes and predict areas of maximal concentrations in the receiving stream based on chemical, biological, and physical processes.

4.5. I 

### Wastelapd Metkli~ Techuhptes 1) Steady-State Modeling Techniques
A steady-state model requires single, constant inputs for effluent flow, effluent concentration, background receiving water concentration (RWC), receiving water flow, and meteorological conditions (e.g., temperature). Thefrequency and duration ofambient concentrations predicted with a steady-state model must be assumed to equal the frequency and duration of the critical receiv78ing water conditions used inthe model. The variability ineffluent flows and concentrations also affects RWCs, but these effects cannot be predicted with constant inputs. Steady-state models can be improved for toxic WlAs by means ofthe following:

l Using design flows that will ensure criteria compliance at the appropriate duration and frequency.

l Calculating both acute and chronic WlAs.
EPAisencouraging the States to adopt two-number aquatic life water quality criteria and isusing them inWIA studies. Ambient water quality 

### criteria have been established for numerous toxic pollutants. These criteria specify an acute concentration (CMC) and a chronic concentration (criteria continuous concentration, 

### orCCC) for each toxicant, aswell asdurations and frequencies of exposure for the two concentration levels. The design flows used in steady-state modeling should be reflective of the CCC and CMC durations and frequencies. The duration ofthe design flow isbased on the maximum exposure time that will prevent acute and chronic effects. The duration offlow isassumed to apply to the duration ofthe allowable effluent concentration or load. For example, ifthe flow used isa 7-day average value, the allowable load isconsidered to be a7-day average. The return frequency is based on the number ofyears required for biological population recovery after criteria have been exceeded. Appendix Ddescribes the toxicological basisfor selecting receiving stream design flows for steady-state modeling and recommends specific design flows for CCC and CMC calculation ofTMDLs for rivers and streams.
In summary, there are two types of design flows, hydrologically based and biologically based. The hydrologically based design flows arethose traditionally used bythe States, inwhich the 7410 flow is

### usedasthe CCC design flow and the 1QlO isused asthe CMC design flow. The biologically based method usesthe 1-day, 3-year duration-frequency for determining the CMC design flow and the 4day, 3-year duration-frequency for determining the CCC design flow. Consequently, the biologically based design flows are based on specific toxicological effects ofapollutant and biological recovery times from localized stresses [6]. The advantages 

### of both types, aswell ashow they may be calculated, also are described inAppendix D.
A4-day, 3-year biological design flow does not equate to a443 hydrological design flow. EPAhasdetermined that a443 design flow would result in an excessive number ofwater quality criteria exceedances. Asexplained inAppendix D,ahydrologically based 7QlO will, for most streams, be similar to a biologically based 4- day, 3-year design flow.
At the present time, there are no recommended toxicological flows for steady-state modeling of lakes, reservoirs, or estuaries. The design conditions recommended for these waterbodies in Section 4.4.2 are based on hydrological and meteorological conditions rather than on toxicological duration and frequency data. These conditions should be used until further guidance is provided.
Another improvement in steady-state toxics modeling can be realized by performing two separate WLAS,one for the CMC and one for the CCC. Steady-state WIA models should be used to calculate the allowable effluent load that will meet the CMC at

### the acute design flow and the allowable load that will meet the CCC atthe chronic design flow. Calculation ofthese values will enable the permit writer to calculate the more limiting long-term average (LTA)for the treatment system and develop permit limits protective of both WLAs (seeChapter 5).
In addition to stream design flow, steady-state models require design temperature, pH, alkalinity, and hardness, depending 

### on the pollutants modeled at site-specific conditions. To determine stream design temperature, pH, alkalinity, and hardness, a program called DESCON was developed. (See Appendix D for additional information.) DESCON isa computer program that estimates design conditions for WIA modeling. These conditions are based on maintaining a desired limit on the frequency of water quality excursions inareceiving water. DESCON considers the effect that daily fluctuations in stream flow and water quality conditions, such astemperature and pH, have onthe variability of the capability of areceiving water to accept pollutant loadings. It specifically accounts for the within-year correlations observed between such variables asstream flow, temperature, pH, alkalinity, hardness, and dissolved oxygen. DESCON determines 

### design conditions using afour-step process (see Figure 4-3): 1) Along-term record 

### ofobserved stream flows and pertinent water quality data areassembled or synthesized. 2) The maximum allowable pollutant load that 

### the receiving water can accept without causing awater quality excursion iscomputed for each day ofthis record. 3) This synthesized record of allowable loads is searched for the critical load, i.e., the load whose frequency of not being exceeded matches the desired water quality excursion frequency. 4) Design conditions are then derived from receiving water conditions realized during the period of record when the computed allowable load was closest to the critical load.
DESCON provides the same advantages ascontinuous simulation by considering the joint occurrences of stream flow and other water quality parameters asobserved in the historical record. In addition, it is more computationally efficient; it contains afacility for extracting and analyzing flow and water quality data from STORET; it can use both the extreme value and the biologically based methods ofcalculating ofwater quality excursions; and it is specifically designed to handle such pollutants asammonia, heavy metals, pentachlorophenol, and biochemical oxygen demand (BOD) for which water quality criteria arefunctions ofsuch design condition variables astemperature, pH, alkalinity, hardness, and dissolved oxygen. The main limitations of DESCON are that it requires at least 10 years of historical daily flow data and it can only analyze a single discharger, edge-of-mixing zone situations (or a simplified Streeter-Phelps dissolved oxygen response for BOD). 2) Dynamic Modeling Techniques Steady-state modeling considers only asingle condition; effluent flow and loading are assumed to be constant. The impact of receiving water flow variability on the duration for which and frequency with which criteria are exceeded is implicitly included

79Allowable Stream Loading

Days Days

Design Temperature

Days 

### --- Final Critical Load Trial Critical Load

1 AllOWed I number I
Number of Excursions

Figure 4-3. Computational Scheme for Deriving Design Conditions
in the design conditions if these conditions reflect the desired toxicological effects regime. Dynamic modeling techniques explicitly predict the effects of receiving water and effluent flow and of concentration variability. The three dynamic modeling techniques recommended by EPAfor WLAsarecontinuous simulation, Monte Carlo simulation, and lognormal probability modeling. These methods calculate aprobability distribution for RWCsrather than a single, worst-case concentration based on critical conditions. Prediction of complete probability distributions allows the risk inherent in alternative treatment strategies to be directly quantified.
The useof probability distributions in place of worst-case conditions has been accepted practice for years in water resource engineering, where it was found to produce more cost-effective design of bridge openings, channel capacities, floodplain zoning, and water supply systems. The same cost-effectiveness can be realized for pollution controls ifprobability analyses are used. The dynamic modeling techniques have an additional advantage over steady-state modeling in that they determine the entire effluent concentration frequency distribution required to produce the desired frequency ofcriteria compliance. Maximum daily and monthly average permit limits can be obtained directly from the effluent LTA concentration and coefficient of variation (CV) that characterize this distribution. Generally, steady-state modeling has been used to calculate only a chronic WIA. Steady-state modeling generates a single allowable effluent value and no information about effluent variability. Ifthe steady-state model is used to calculate both acute and chronic wasteloads, limited information will be provided and the entire effluent distribution will not be predicted. Steady-state WLA values can be more difficult to useinpermits and enforcement because ofthe variable nature ofthe receiving waterbody and the effluent. The outcome of probabilistic modeling can be used to ensure that permit limits are determined based on best probability estimates of RWCs rather than asingle, worst-case condition. Asaresult, maximum daily and monthly average permit limits, based on compliance

80with water quality criteria over a 3-year period, can be obtained directly from the probability distribution.
Continuous Simulation Models. As shown in Figure 44, a continuous simulation model uses daily effluent flows (Q) and concentration data (Ce) with daily receiving water flow (QJ and background concentration data (C,) to calculate downstream RWCs(44). The model predicts these concentrations in chronological order with the same time sequence asthe input variables (Ch versus time). The daily RWCscan then be ranked from the lowest to the highest without regard to time sequence. A probability plot can be constructed from these ranked values, and the occurrence frequency of any 1-day concentration of interest can be determined (Cb versus frequency). Running average concentrations for 4 days (i.e., the chronic design flow), orfor any other averaging period, also can be computed from the daily concentrations (Figure 4-5).
The probability plot generated bythe continuous simulation model using existing effluent data will indicate whether criteria are predicted to beexceeded more frequently than desired. Appendix D discusses how to select the appropriate allowed frequency of excursions based on the biological recovery period required for a specific waterbody. If recurrence intervals of 10 or 20 years are desired, at least 30 years of flow data should be available to provide asufficient record to estimate the probability ofsuch rare events. Of the 30 years of required flow data, at least 20 to 25 years should be continuous daily data, with the remaining years represented with only intermittent data. The data should be examined to verify that the receiving stream has not undergone significant hydrological modification. The data also should be examined to determine ifthere were any long-term changes due to technology-based treatment or periodic changes due to industrial or municipal plant closings or expansions. The same data requirements are also true for the lognormal probabilistic and Monte Carlo methods. However, except for the continuous simulation models, other nonsteady-state models in this section

I I 

# A

c I ’dw / I

01 : : : : : : : ; : ’

. -4 99 99.5 100 Percent ofTime Concenlra!~on Is Less Than or EqUal IOConcemt~on Plotted 0.5 1 * 510.2 I I I w 20

Figure 4-4. Frequency of Occurrence of Concentrations in

Receiving Waters and Recurrence Intervals Generated by aContinuous Simulation Model cannot be used to account for the duration and frequency provisionofthe two-number water quality criteria. Usersarecautioned about the specific limitations of some of the dynamic models included here. Continuous simulation models have the following advantages compared to steady-state formulations:

l The frequency and duration oftoxicant concentrations ina receiving water can be predicted.

l The cross-correlation and interaction of time-varying pH, flow, temperature, pollutant discharges, and other parameters are incorporated.

l The effect that the serial correlation ofdaily flows and other parameters has on the persistence of criteria excursions is incorporated.

l Long-term stream flow records for ungauged rivers using precipitation and evapotranspiration data can be synthesized.

l Long simulation times can prevent the initial conditions used inthe model from affecting the calibration offate and transport processes.
Unlike steady-state models, continuous simulation models require significantly more data to apply, to calibrate, and/or to verify a specific problem and require that input information for the application ofthe model be time-series data. Also, the model results need manipulation to calculate the effluent LTA concentration and CVfor usein developing effluent limits.
Monte Carlo Simulation Models. Monte Carlo simulation combines probabilistic and deterministic analyses since it usesafate and transport mathematical model with statistically described inputs. Monte Carlo simulations have been the most frequently used approach in stochastic water quality studies [45-511. The probability distributions of effluent flow, effluent concentration, and other model input must be defined using the appropriate duration for comparison to the CMC and CCC. If 1-day average RWCs

### mustbe predicted for CMC comparisons, probability distributions of daily model input data are needed for Monte Carlo simulation. If4-day average concentrations must be predicted for CCC comparisons, the probability distributions of 4-day average input data are required. The computer selects input values from these distributions using arandom generating function. The fate and transport model is repetitively run for a large number of randomly selected input data sets. The result is a simulated sequence of RWCs. These concentrations do not follow the temporal sequence that iscalculated with the continuous simulation model, but they can be ranked in order of magnitude and used to form afrequency distribution. Monte Carlo analyses can be used with steady-state or continuous simulation models (521.
The approach for calculating the allowable pollutant load distribution using Monte Carlo simulation isthe same asthat described for the continuous simulation model. The advantages of Monte Carlo simulation are the following:

l It can predict the frequency and duration oftoxicant concentrations ina receiving water.

81It can be used with steady-state or continuous simulation models that include fate processes for specific pollutants.
It can be used with steady-state or continuous simulation models that include transport processes for rivers, lakes, and estuaries.
It can be used with steady-state or continuous simulation models that are designed for single or multiple pollutant source analyses.
Itdoes not require time seriesdata.
It does not require model input data to follow a specific statistical distribution orfunction.
It can incorporate the cross-correlation and interaction of time-varying pH, flow, temperature, pollutant discharges, and other parameters ifthe analysis isdeveloped separately for each season and the results are combined.
The primary disadvantages of Monte Carlo simulation are that it requires more input, calibration, and verification data than do steady-state models, and the model results need manipulation to calculate the effluent LTAconcentration and CVto develop effluent limits.
Lomormal Probabilistic Dilution Model. Without resorting to the continuous simulation method ofcomputing RWCsintemporal sequence, this probabilistic method usesthe lognormal prob ability distributions of the input variables to calculate probability distributions of output variables [53]. As a result, the method requires only the relevant statistical parameters of the input vatiables (medians and coefficients ofvariation) rather than the actual time series data needed for continuous simulation, If l-day average RWCsmust be predicted for comparisons with the CMC, lognormal probability distributions ofdaily input data are needed. If4-day average concentrations must be predicted, the lognormal probability distributions of4-day average input data are required. Because this probabilistic model cannot, asyet, incorporate fate and transport processes, it can be used to predict the concentration ofasubstance only after complete mixing and before degradation or transformation significantly alters the concentration.
The lognormal probabilistic dilution model has the following advantages:

l It can predict the frequency and duration oftoxicant concentrations in riverine environments.

l Itdoes not require time seriesdata,

l It can incorporate the cross-correlation and interaction of time-varying pH, flow, temperature, pollutant discharges, and other parameters ifthe analysis isdeveloped separately for each season and the results are combined.
The lognormal probability dilution model hasthe following disadvantages:

l It requires more input than asteady-state model. c b

Time

cb ,- _,-,’,__A-”-- ,/’ Standard /’

L---- - - - Frequency
Figure 4-5. Concentration Frequency Curves

l Itdoes not include instream fate processes.

l Itapplies only to rivers and streams.

l Itanalyzes multiple pollutant sources inaccurately.

l It requires model input data to be lognormally distributed.



### 4.5.2 Ca/cu/ath# t&s 

## A//uwab/e Etttumt Cuncentrath

Information concerning effluent concentration means and variabilities can be obtained from data bases on existing treatment plants and from development documents for specific industrial point source categories. This information isavailable from the Industrial Technology Division ofthe Office ofWater Regulations and Standards. These effluent data can be used with dynamic models to determine what the effluent concentration distribution must be to meet water quality standards. Two possible approaches can be taken to determine this distribution regardless of the type ofdynamic modeling technique (i.e., continuous, Monte Carlo, or lognormal probabilistic). One approach isbased on the simplifying assumption that treatment will change only the mag82nitude of effluent concentrations; no changes are assumed to occur in effluent flows or in the relative variability of effluent concentrations. With these assumptions, no additional model runs are needed to determine the allowable distribution for effluent concentrations. The other approach assumes that the required effluent concentration distribution isthe same asthe existing distribution except that it isreduced in magnitude by whichever isgreater-the percentage necessary for the 1-day average concentrations to meet the CMC, or the 4-day average concentrations to meet the CCC at the desired recurrence interval. Chapter 5 includes details on how permit limits are derived from the mean and coefficient of variation of effluent concentrations determined from this analysis.
The second approach for determining the allowable effluent concentration distribution is based on the assumption that effluent concentrations after treatment will not have the same CV as concentrations before treatment. Studies have documented that advanced secondary treatment increases the CVof BOD and total suspended solids concentrations compared to secondary treatment. Where feasible, investigations should be conducted to evaluate how treatment processesfor heavy metals, organic chemicals, and effluent toxicity will change 

### the variability of these constituents. The development documents mentioned above also provide some variability data for treatment processes. To account for achange invariability, analternative approach should be used to determine the allowable effluent distribution. Iterative model runscan be performed using different concentration means with the effluent “future treatment” variance until a mean is found that meets the criteria at the desired recurrence intervals. These iterative model runs require stochastic generation of effluent input data since daily effluent concentrations will not be available for the hypothetical treatment schemes. The required “future treatment” mean and CV of effluent concentration can then be used to setpermit limits (seeChapter 5).
EPA’sOffice of Water Regulations and Standards developed an interactive preprocessor for DYNTOX that automatically creates input for continuous simulation models, randomly selectsthe sets of input data required for Monte Carlo simulations, and performs the numerical integration calculation for the lognormal probabilistic model. DYNTOX isavailable from the EPACEAM, Environmental Research Laboratory (ERL)[54]. Ifthe observed data base isfairly complete but missing afew points, a linear interpolation scheme isused tofill in the missing data. Ifdata are scarce, alagone Markov method isused to generate daily data stochastically. The lag-one Markov method usesthe mean, standard deviation, and daily correlation coefficient of the observed data to create random sequences of data having the same statistical properties. The interactive program iswritten in FORTRANand isavailable for 

### useon mainframe or IBM PC-compatible computers.
Two common methods exist to calculate the return period for a given concentration from probabilistic modeling: the percentile method and the extrema method. The percentile method used by DYNTOX ranks a listing of all individual daily concentrations. The return period for aconcentration isthen calculated based on the percentile occurrence. In the extrema method, only annual extrema values are used in the ranking. The return periods calculated from these two methods are equally valid statistical representations. When using the percentile method, results express an average return period and multiple occurrences within any year. The extrema method describes the return period for an annual extreme and includes only 

### the extreme of multiple occurrences within ayear.

4.5.3 6uutwalRec aPnm8twb88 for 

### Model&?ktitm The reliability of the predictions from any of the modeling techniques depends on the accuracy ofthe data used in the analysis. The minimum data required for model input include receiving water flow, effluent flow, effluent concentrations, and background concentrations. In many locations, stream flow data should be sufficient for both steady-state and dynamic models. At least 30 years offlow data should be available if excursions of the CMC and CCC must beevaluated at rarefrequency ofonce in 10 or20 years. Measurements ofeffluent toxicity or individual toxicity can be much more limited.
Ifonly afew toxicant or effluent toxicity measurements are available, steady-state assessments should be used. Modeling also should be limited to steady-state procedures if a daily receiving water flow record isnot available; however, ineffluent-dominated situations, critical flow may be used to characterize the receiving stream. Appendix D describes how to select appropriate design flows if State regulations do 

### not require aspecific design flow for river WI-As. Fateand transport models ordilution calculations can be usedfor individual toxicants. At the present time, only dilution calculations or first-order decay equations are recommended for effluent toxicity 

### analyses. Chapter 1discusses the conservative/ additive assumption for toxicity.
Ifadequate receiving water flow and effluent concentration data are available to estimate frequency distributions, one of the dynamic modeling techniques should be used to develop more cost-effective treatment requirements. Ifthe effluent data exhibit significant seasonal differences or batch process trends, the continuous simulation approach may be the easiest dynamic modeling method to use. The best results will, of course, beobtained if daily effluent flows and concentrations are available for model input for an entire year. The lag-one Markov technique can be used to generate daily effluent data for the entire simulation as long asadequate measurements for the site-specific facility (or a similar one) are available to estimate a day-to-day correlation coefficient and to determine when seasonal or batch process changes in effluent quality occur.
Ifadequate receiving water flow and effluent concentration data are available and if effluent data exhibit no seasonal or batch process trends, lognormal and Monte Carlo methods may be easier and require lesscomputer time than the continuous simulation approach.

The following section recommends models for toxicity and individual toxicants for each type of receiving water-rivers, lakes, and estuaries. Detailed guidelines onthe useoffate and transport models of individual toxicants are included in the toxic TMDL guidance available from the Monitoring Branch of EPA’sOffice of Water Regulations and Standards [5, 6, 71and Office of Research and Development [55]. These manuals describe in detail the

83

### -- --. --~.- - - ~.
transport and transformation processes involved in water quality modeling. Transport processes include the dispersion and advection of a contaminant once it enters the receiving stream; its volatilization from the water; and itssorption to suspended sediment, 

### eventual settling, and possible resuspension and diffusion from the sediment. Transformation processes include the oxidation, hydrolysis, photolysis, biodegradation, and bioaccumulation ofthe chemical.
Most water quality models were developed with an emphasis on the dynamics inthe water column and the eventual water column concentrations. Several models, including some of those listed below (EXAMS-II, WASP4) are now capable of simulating water column-sediment interactions (resuspension, settling, and diffusion), however, additional work needs to be completed on the mechanisms ofsediment-water column exchange before themodels can be validated for predictive applications involving sediments. With the advent ofsediment criteria inthe next few years, it will be necessary to use models that predict concentrations in both receiving water and bed sediment. Thiswill be of particular importance inareaswhere the sediments arecontaminated to the point at which they act asthe source of a pollutant to the water column. Table 4-2 listsand summarizes models that may be used for predicting the fate and transport of toxicants and that are supported by the EPACEAM [56]. All the models, plus two bioaccumulation models, briefly are described below.

l DYNTOX 1541is a WLA model that 

### usesa probabilistic dilution technique to estimate receiving water chemical concentrations or whole effluent toxicity fractions. The model considers dilution and net first-order loss, but not sorption and benthic exchange. The net lossrate must be determined empirically on acase-by-case basisand cannot be extrapolated to different conditions of flow, temperature, solids, pH, or light.

. EXAMS-II [57] isacompartment model that can be used as either asteady-state or quasi-dynamic model designed for evaluation ofthe behavior ofsynthetic organic chemicals in aquatic ecosystems. It simulates a toxic chemical and its transformation products using second-order kinetics for all significant organic chemical reactions. EXAMS-II does not simulate the solids with which the chemical interacts. The concentration of solids must be user-specified for each compartment. The model accounts for sorbed chemical transport based onsolidsconcentrations and specified transport fields. Sediment exchanges with the water column include pore-water advection, pore-water diffusion, and solids mixing. The last describes a net steady-state exchange associated with solids that isproportional to porewater diffusion.

l WASP4 [58] isageneralized modeling framework for contaminant fate in surface waters. Based on the flexible compartment modeling approach, WASP4 can be applied in one, two, or three dimensions, given the transport of fluxes between segments. WASP4 can read output files from the link-node hydrodynamic model DYNHYD4, which predicts unsteady flow rates in unstratified rivers and estuaries,given variable tides, wind, and inflow. TOX14, asubset ofWASP4, simulates up to three interacting toxic chemicals and up to three sediment size fractions in the bed and overlying waters. First- or second-order kinetics can be used for all significant organic chemical reactions. Sediment exchanges include pore-water advection, pore-water diffusion, and deposition/scour. Net sedimentation and burial rates can be specified or calculated. The output can be used with the two bioaccumulation models FCETSand FCMZ, which are described below.
HSPF[59] simulates watershed hydrology and water quality for both conventional and toxic organic pollutants. HSPF incorporates the watershed-scale ARM and NPS models into a basin-scale analysis framework that includes transport and transformation in one-dimensional stream channels. The simulation provides a time history of the runoff flow rate, sediment load, and nutrient and pesticide concentrations, along with atime history ofwater quantity and quality at any point in awatershed. HSPFsimulates three sediment types (sand, silt, and clay) in addition to specific

Table 4-2. Toxicant Fate and Transport Models

Model
DY NTOX
EXAMS-II
WASP4
HSPF
SARAH2

MlNTEQA2 Environment
river
lake, river, estuary lake, river, estuary river

river

lake, river, estuary Time Domain dynamic steady-state, quasi-dynamic steady-state, dynamic dynamic steady-state

steady-state Spatial Domain
farfield, 1-dimensional farfield, 3-dimensional farfield, 3-dimensional farfield 1-dimensional treatment plant, near field, 2-dimensional

- Chemical organic, metal organic organic, metal organic, metal organic

metal

84

### --- ---- - --- __-----------.--.--.__~____ - -_- - -- -- ------- --.-.- _ -- - - -----___
organic chemicals and transformation products of those chemicals. The reaction and transfer processes included are hydrolysis, oxidation, photolysis, biodegradation, volatilization, and sorption. Sorption is modeled as a first-order kinetic process in which a desorption rate and an equilibrium partition coefficient for each of the three solid types must be specified. Resuspension and settling of silts and clays (cohesive solids) are defined interms ofshear stressat the sediment-water interface. For sands, the system’s capacity to transport sand at a particular flow is calculated and resuspension or settling is defined by the difference between the sand in suspension and the calculated capacity. Sediment exchanges with surficial benthic sediments are modeled assorption/desorption and deposition/scour. Underlying sediment and pore water are not modeled.

l SARAH2 [60] isasteady-state, near-field model for calculating acceptable concentrations of hazardous organic chemicals discharged to land disposal or wastewater treatment facilities. Acceptable leachate or treated industrial waste discharge constituent concentrations are estimated by a “back calculation” procedure starting from chemical safety criteria in surface water, drinking water, orfish. Forsteady or batch waste streams, SARAH.2considers the following concentration reductions: dilution and loss during treatment, initial Gaussian mixing at the edge of a stream, lateral and longitudinal diffusion in the mixing zone, sorption, volatilization, hydrolysis, and bioaccumulation infish. The user must specify appropriate concentrations for protection ofthe aquatic community and of humans exposed through consumption offish and water. The benthic community isnot presently considered. Treatment lossishandled empirically. SARAH2 contains data setsfor three disposalwatershed scenarios that can be easily modified and employed. The model isdesigned for screening analysis and contains numerous assumptions that should be verified before the model isused in actual cases.

l MINTEQA2 isan equilibrium metals speciation model for dilute aqueous systems [61]. Itdoes not have any transport and transformation processes and must be run with one of the above models. It can be used to calculate the mass distribution atequilibrium among dissolved, absorbed, and solid phases and the species distribution within each phase. MlNTEQA2 contains a chemical component data set for major ions commonly found in aqueous systems (e.g., Ca, Fe, and S), trace metals/metalloids of pollution interest (e.g., Cd, Cr, Ni, Pb, and Zn), and organic ligands of significant affinity for metal complexation. The model can be used to calculate the concentrations ofadsorbed metals via any ofseven different adsorption algorithms.

l FCETS is a toxicokinetic model that simulates the bioaccumulation ofnonpolar organic chemicals byfishfrom both water and food [62]. Both of these routes of exchange are modeled as diffusion processes that depend upon physicochemical properties ofthe pollutant and morphological/physiological characteristics of the fish. FCETS contains amoderately sizeddata baseofallometric relationships for gill morphology with which it can simulate the direct gill/water exchange of organic chemicals for essentially anyfishspecies, assuming certain default values. FCETS also contains a limited data base of physiological/morphological relationships that are used to setparameters forfood exchange. In addition to simulating bioaccumulation of organic toxicants, FCETScan calculate time to death from chemicals whose mode of action isnarcosis. This calculation is based on the existence of a single, lethal, internal chemical activity for suchchemicals. The concentrations of toxic chemical to which the food chain isexposed may be specified by the user or may be taken directly from the values calculated by the exposure concentration model WASP4. Thus FCETSmay be executed asaseparate model or asapostprocessor to WASP4.

l FCM2 isageneralized model ofthe uptake and elimination oftoxic chemicals byaquatic organisms (631. Itgenerates a mass balance calculation in which the rates of uptake and elimination are related to the bioenergetic parameters of the species. A linear food chain or a food web may be specified. Fish tissue concentrations are calculated as a function oftime and age for each species included. Exposure to the toxic chemical in food isbased on aconsumption rate and predator-prey relationships that are specified as a function of age. Exposure to the toxic chemical in water isfunctionally related to the respiration rate. Steadystate concentrations also may be calculated. The concentrations of the toxic chemical to which the food chain is exposed may be specified by the user or may be taken directly from the values calculated by the exposure concentration model WASP4. Thus FCM2 may be executed asa separate model orasapostprocessor to WASP4. Migratory species, aswell as nonmigratory species, may be considered. Separate nonmigratory food chains may bespecified, and the migratory species isexposed sequentially to each food chain based on itsseasonal movements.

To apply the steady-state, continuous simulation, or probabilistic methods to effluent toxicity modeling, the percent effluent measurements should be converted to toxic units (TUs). Asdiscussed in Chapters 1, 2,and 3, it isnecessary to convert toxicity to units that can be directly related to mass. When comparing toxicity among chemicals, the relationship between toxicity and concentration isinverse; chemicals that have toxic effects at low concentrations have agreater “toxicity” than chemicals that have toxic effects at higher concentrations. The modeling oftoxic effluents isbased on mass balance principles; therefore, toxicity needs to be in units that increase when the percent of the effluent of the receiving stream increases. Thus, a TU isthe reciprocal of the dilution that produces the test endpoint, i.e., acute toxicity endpoint (ATE) or chronic toxicity endpoint (CTE). An acute toxic unit (TU,) isthe reciprocal ofanATE. Achronic toxic unit (TU,) is the reciprocal of a CTE. The TMDL must ensure that the CMC and the CCC are met in the receiving water at the desired duration and frequency. The CMC for toxicity is recommended as0.3 TU,. This isavalue that should prevent lethality unless the duration of exposure exceeds 1hour.
The CCC fortoxicity measured with chronic tests isrecommended asthe following:
CCC = 1.OTU,.The first step in the TMDL process isto calculate the allowable acute effluent toxicity that meets the CMC in the receiving water at the duration and frequency discussed inAppendix D.
The next step in the TMDL process isto calculate the allowable chronic effluent toxicity that meets the CCC inthe receiving water at the duration and frequency discussed in Appendix D. To compare the allowable acute toxicity value tothe allowable chronic toxicity value, the numbers must be converted to the same units asfollows: TU, = (ACR)(TlJ,)
where the acute-to-chronic ratio (ACR) isdetermined from tests on the effluent. It is important that the ACR used for TMDL purposes be based on actual data and not beassumed to be 10or 20, asin the screening procedure (Chapter 3). The value ofthis ratio will influence whether the acute or chronic TMDL is more stringent and is used to calculate the permit limit using the methods described in Chapter 5.
At the present time, the fate of effluent toxicity in a receiving water isnot fully understood. Evenifadecay rate for toxicity can be measured on agiven day inasite-specific situation, there isno way asyet to know how this rate isaffected by temperature, pH, orother environmental conditions. There isalso no way to know how this rate may change when new treatment is installed. lnstream measurements oftoxicity should be made at least once per season to identify any time-varying trends in site-specific fate processes. These monitored decay rates can then be used in steady-state or continuous simulation fate and transport models to predict receiving water toxicity, assuming that the rateswill not change with future treatment.
Without specific information concerning the persistence oftoxicity, it isrecommended that effluent toxicity be limited to dilution estimates and that toxicity be assumed to be additive and conservative. Toxicity isexpected to be additive even when the toxicity ofone effluent affects selected biota while the toxicity ofadownstream discharge affects different biota. Forrivers and run-of-river reservoirs with adetention time oflessthan 20 days, the following ditution equation should be used, assuming completely mixed conditions:

where c = c, = 

### Qs= c, = Qe= c = C@s f C&e 

## Qe +Qs

downstream concentration (TU, orTU, ) upstream concentration (TU, orTU, ) upstream flow (cfs) effluent concentration (TV, orTU, )and effluent Row (cfs).
For multiple dischargers, this equation must be applied sequentially to find the concentration asa function of distance downstream. The equation can be used for asteady-state analysis ifQs isset equal to the design flow, & isset equal to the historical plant flow, and C, iscalculated to meet the CMC and CCC. This equation can also be used with the continuous simulation, lognormal probabilistic, or Monte Carlo methods. For these dynamic analyses, a series of C, Qe, C, and Qsvalues would be used. If instream toxicity measurements are available and afirst-order decay rate for toxicity can be estimated, the following equation should be used:

c =C,e-K(X/U) where C = downstream concentration (TU, orTU,) Co = concentration after the point source discharge has mixed completely with the river (TU, orTU,,) X = distance downstream of complete mix point U z velocity of river K = measured decay rate.
Additional statistical approaches are available that might provide better statistical fits to the available data. However, these models are somewhat more limited than the example provided above.
The same equations usedfor toxicity analyses in rivers canalso be used insteady-state, continuous simulation, or probabilistic analysis of long, narrow, shallow impoundments with high inflow velocities. Wider, deeper lakes require more complicated analysessince prolonged detention times (>20 days) and stratification exert asignificant impact onwater quality. The prolonged detention times make itessential that receiving water measurements of toxicity be available to estimate decay factors. These measurements should be made at least once per season to identify any time-varying trends in toxicity fate processes. Steady-state or continuous simulation fate and transport models for lakes can then be run with monitored decay rates for toxicity. A simple steady-state analysis can be performed using the following equations [64]:

where T, = v = Q = c = Gin= K = T,V=V/Q C =Ci,/(l +TwK)

mean hydraulic residence time lakevolume at design conditions mean total inflow rate at design conditions steady-state lake concentration (TV, orTU,) steady-state inflow concentration (TU, orTU,) first-order decay rate.
Ifeffluent isdischarged into astratified lake and mixes only with the hypolimnion orepilimnion, the volume ofthe layer should be used only to calculate mean hydraulic residence time (T,,.,). The mean total inflow rate (Q) and the inflow concentration (Gin) should be calculated asthe sum ofall sources to the lake, including point source, nonpoint source, and tributary inputs.
Dilution calculations for effluent toxicity discharges to an estuary are complicated by the oscillatory motion of the tides and possible stratification ofthe estuary. The prolonged detention times make it essential that field measurements of toxicity be available to estimate decay factors. These measurements should be made at least once per season to identify any time-varying trends in toxicity rate processes. Steady-state orcontinuous simulation fate and transport models for estuaries can then be run with monitored decay rates for toxicity. A simple steady-state analysis can be performed using the following equations for each nonconservative pollutant entering from the river at the head of an estuary [64]:

86where (fi>

Bi= 1 _(li$e’kt ri = exchange ratio for segment iasdefined by modified tidal prism method t = flushing time fi = fraction offreshwater in segment i Ci = nonconservative pollutant concentration insegment i(TU, orTU,) k = decay rate of pollutant.
The following equations should be usedfor each nonconservative pollutant entering along the side ofan estuary:
Forsegments downstream of outfall:
fi ri ci = 'O A c 1- (l-ri)e-kt i= 1
Forsegments upstream ofoutfall:

where Ci = 

## co=
ri =


## ; I fb = Si= so= k = t = nonconservative pollutant mean concentration in segment i(TU, orTU,) nonconservative pollutant mean concentration in segment ofdischarge exchange ratio for segment iasdefined by the modified tidal prism method number ofsegment away from outfall fraction offreshwater insegment i fraction offreshwater insegment with discharge salinity insegment i salinity insegment of discharge decay rate flushing time.
The details of how to calculate exchange ratios and flushing times for estuaries are included in Part 2 of EPA’s water quality assessment manual [64]. This manual also describes how to perform these calculations for stratified estuaries using atwo-dimensional box model analysis.



## 4.6 HUMAN HEALTH

4.6.1 Mmankal# considerations Human exposure to pollutants should beevaluated ascompletely asavailable information will allow. Exposure information isused incalculating the human health reference ambient concentration (RAC) from the formulas in Chapter 2, Water Quality Standards. This information should be usedto estimate exposures due tofish consumption and drinking water ingestion, background concentrations, and other exposure routes, such asrecreational, occupational, drinking water, dietary (other than fish), and inhalation. Factors in the formulas for which information isnot available can beomitted from the calculation. IfStateschoose, bioaccumulation factors also can be modified.


### 4.6.2 lbtem?inim.gthe TMDLBasedonlllurnanhaM~ Rdants TMDLs are typically necessary only where mixing is allowed. Mixing zones are used at the discretion of the States. Ifa State does not allow a mixing zone or the assumption of complete mixing, then the RACisapplied at the end of pipe and noTMDL determination istypically necessary.
With persistent or bioconcentlatable pollutants, special mixing zone considerations apply. Bioconcentratable pollutant criteria exceedances within the mixing zone can potentially result in tissue contamination of organisms directly or indirectly through contamination of bed sediments with subsequent incorporation into the food chain. For discharge situations with incomplete mixing (e.g., large rivers, lakes,estuaries, oceans), States need to carefully consider whether mixing zones for persistent or bioconcentratable pollutants are appropriate. Where a mixing zone isallowed, one TMDL should be calculated to achieve the RACorcriterion selected above [65]. Because most human health criteria are chronic only, aTMDL to protect against acute effects will usually not be needed, although EPA’s Office of Drinking Water does have acute criteria for some pollutants.
Forthe purpose ofthe following discussion, useofsimple, steadystate dilution models isassumed. l-lowever, these models may be inappropriate for certain situations where sediments serve as a sinkfor bioconcentratable pollutants and where additional factors need to be considered. Dynamic models, where available, are useful tools for accounting for anarray ofvariables that may have an impact on the fate of bioconcentratable pollutants in the food chain. These models may be used by Statesfor surface waters in appropriate instances.
In simple situations, the TMDL isdetermined from the RACand the design flow of the receiving water. In more complicated situations, e.g., where mixing is not rapid or where lakes or estuaries are involved, aspatial averaging scale must be chosen. Selection of the spatial scale must be consistent with reasonable assumptions about the behavior of aquatic organisms and the target human population.
In some cases, it may be necessary to apply the chronic human health criterion within a mixing zone ifit isreasonable to assume that the bioconcentrating aquatic organisms have little mobility, thus spending most oftheir time within the mixing zone; and the target human population consistently consumes fish from the mixing zone (over a 70-year lifetime, for carcinogenic risks).
The procedure for developing TMDLs/WLAs generally requires determining values for the following parameters, based upon water quality considerations: (1) the duration of the averaging period applicable to the WlA; (2) design considerations, e.g., flow; (3) the discharge &VIA) concentration that will result in meeting the ambient water quality criterion during the design condition; and (4) the allowable probability (or frequency) ofthe discharge’s exceeding the WlA, averaged over the appropriate

87duration. The technical basisfor setting these values isdiscussed in the following sections. 1) Averaging Periods
The duration of the averaging period for the WLA should be selected to be consistent with the assumptions used to derive the water quality criteria. Two categories of pollutants should be recognized: carcinogens and noncarcinogens.
The human health criteria for carcinogens are derived assuming lifetime exposure. The upper-bound risk isdirectly proportional to the lifetime arithmetic mean dose. The criteria thus apply to the ambient water concentrations averaged over a 70-year period.
The duration of exposure assumed in deriving criteria for noilcarcinogens may be ambiguous, particularly where acriterion isderved from animal studies. Furthermore, the duration may be highly variable, ranging ashigh as20 to 30years for cadmium. 2) Dilution Design Conditions u) Carcinogens: Riverand Stream Discharge Situations
Inwell-mixed situations, the RWC,C, isdetermined by the pollutant load, W (mass/time), and the combined receiving water plus effluent flow, Q, such that, C=W/Q.
The long-term harmonic mean flow ISrecommended as the design flow for carcinogens. The recommendation of long-term harmonic mean flow has been derived from the definition ofthe human health criteria (HHC) for carcinogenic pollutants. The adverse impact ofcarcinogenic pollutants isestimated interms of receptors (human) lifetime intakes. To be within the acceptable level of life-time body-burden of any carcinogen, such intakes should not exceed the HHC during the average life-time of the receptor. A life-time for exposure to carcinogenic pollutants is defined as70years, or approximately 365 (days/year) multiplied by 70years.
The HHCfor carcinogenic pollutants can be numerically expressed as: HHC =C(design) =(Cl +C2+C3+----- +C, )/n
where n=(365 days/year) x 70years C=concentrations
Basedon anassumption ofaconstant daily load from atreatment facility, the fully mixed instream concentration will go up ordown inversely with the upsand downs ofreceiving water flows. Therefore, instream concentration isafunction of, and inversely proportional to, the streamflow downstream ofthe discharge. Using this concept, 1 /Q can be substituted for C,asfollows:
1 /Q (design) =(1/QT + 1/Q2 + 1 /Q3 +----- + 1/Qn)/n.
The stream design flow (Q design) can then be shown asfollows:
Q (design) =ni(1 /QT + 1IQ2 + 1tQ3 +----- + 1/Qn) The harmonic mean isexpressed asfollows:

Q (design) =n/k (1/Qi) i=l where n=the number of recorded flows.
The harmonic mean isalways lessthan the arithmetic mean. The harmonic mean isthe appropriate design flow for determining long-term exposures using steady-state modeling of effluents. The arithmetic mean flow is not appropriate asthe design flow since it overstates the dilution available. Extreme value statistics (such as7410 or 30QS) are also not appropriate since they have no consistent relationship with the long-term mean dilution. However, for situations involving seasonably variable effluent discharge rates, hold-and-release treatment systems, and effluentdominated sites,the harmonic mean may not be appropriate. In these cases,the effluent load and downstream flow are not independent (i.e., they are correlated). Modeling techniques that can calculate an average daily concentration over a long period of time are more appropriate to determine the long-term exposure inthese cases. The harmonic mean flow may be estimated by any of several methods [8], assuming that flows are approximately lognormally distributed:

where Qhrn = 

## Qgl-l12 Qam
q, isthe geometric mean flow 

### Q

am isthe arithmetic mean flow.
ForU.S.Geological Survey flow records, summaries ofthe statistical parameters needed to estimate the harmonic mean can be quickly obtained from STORET,through auser-friendly procedure for permit writers, asdescribed inAppendix D.
WQA8 DFLOW isa software package available for computation of harmonic mean flow. The DFLOW program (as discussed below and described in Appendix D) should be used with data that are not lognormally distributed.
Todevelop some quantitative senseof how along-term harmonic mean flow of any stream compares with its 7410 flow, the Assessment and Watershed Protection Division and the RiskReduction Engineering Laboratory at Cincinnati, Ohio, analyzed flow records of 60 streams selected at random throughout the United States. These are the same stream flow records that had been analyzed for stream design flow condition for aquatic life protection aslisted in EPAguidance [8]. Basedon the long-term harmonic flow and 7-day, 1O-year low-flow estimates for these 60 streams, the long-term harmonic mean flows of all 60 streams were equal to orgreater than two times the 7410 low flow. Fiftyfour of the streams’ harmonic mean flows were equal to or greater than 2.5 times their 7QlO low flows. Finally, 40 ofthe 60 streams’ harmonic mean flows were equal to or greater than 3.5 times the 7410.
Based on the above observations, permit authorities may choose amultiplication factor of 3x 7QlO to estimate stream design flow for human health protection for carcinogenic pollutants. How88ever, it is recommended that the harmonic mean flow be calculated directly from the historical daily flow record, if possible. Alternatively, the following equation might be used to estimate harmonic mean flow [66]:
Qhm =[l .194 l (Qam)0.473] l [(7Ql O)“.552], rz =0.99.
In this equation, Qam and 7QlO are estimated using the U.S. Geological Survey computer program, FLOSTAT. b) Noncarcinogens: Riverand Stream Discharge Situations
The choice of average period represents a level-of-protection consideration inherent in the risk management decision to be made by the permitting agency. If a short-term duration of exposure ischosen (i.e., 90 days or less), design flows may be appropriately based on extreme value statistics. Because the effects from noncarcinogens aremore often associated with shortened exposures, EPAsuggests the useof 3045. However, in the comparisons offlows for smaller rivers (i.e., low flow of50cfs),the 3045 flow was, on the average, only 1.l times that ofthe 7QlO. Forlarger rivers (i.e., low flow of 600 cfs),the factor was, on the average, 1.4 times. Ifthe effects from certain noncarcinogens are manifested after a lifetime of exposure, then a harmonic mean flow may be appropriate. 3) Point of Application of the Criteria
The point at which the chronic criteria are to be met in the receiving water may be fixed by existing State standards or may be determined by considerations for managing individual and aggregate risks. The several possibilities include the following:

l Where State standards allow no mixing zone and no spatial averaging, the criterion would be met at the end of the pipe.

l Where State standards specify that the criterion must be met at the end ofthe mixing zone, the criterion would be applied atthat point.

l Where State standards allow consideration of spatial averaging, the criterion may be met as an average within a specified area, asappropriate for the individual and aggregate riskscenarios underlying the application.

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## CRAMER 4 REFERENCES

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55. McKeon, T.J., and ].I. Segna. 1987. Selection Criteria for Mathematical Models Used in ExposureAssessments Surface Water Models. U.S. EPA,Office of Health and EnvironmentalAssessment, Washington, DC. EPA/600/8-87/042. 56. Ambrose, R.B., and T.O. Barnwell. 1989. Environmental Softwore at the U.S. EPACenter for Exposure Assessment Modelrng. U.S. EPA, Environmental Research Laboratory, Athens, GA. 57. Burns, L.A., and D.M. Cline. 1985. ExposureAnalysis Modeiing System ReferenceManual for EXAMSII. U.S. EPA,Environmental Research Laboratory, Athens, GA. EPA600/3- 85-038. 58. Ambrose, R.B., T.A. Wool, J.P.Connolly, and R.W. Shantz. 1988. WASP4,AHydrodynamic and Water Quality Mode/- Model Theory, User‘sManual, and Programmer’s Guide. U.S. EPA,Center for Exposure Assessment Modeling, Athens, GA. EPAf600/3-87f039. 59. Johansen, R.C., J.C. Imhoff, J.L. Kittle, and AS. Donigian. 1984. Hydrologic Simulation PrograHORTRAN (HSPF): Users Manual for Release 8.0. U.S. EPA, Environmental Research Laboratory, Athens, GA. EPA/600/3-84-066. 60. Vandergift, S.B.,and R.B.Ambrose. 1988. SARAH2A Near Field Exposure Assessment Model for Surface Waters. U.S. EPA,Environmental Research Laboratory, Athens, GA. EPA/ 600/3-881020. 61. Brown, D.S., and 1.0.Allison. 1987. MINTEQAl Equilibrium Metal Speciation Model: AUsersManual. U.S.EPA,Environmental Research Laboratory, Athens, GA. EPA/BOO/ 3-871012. 62. Barber, M.C., L.A. Suarez, and R.R.Lassiter. 1988. FCETS (Foodand Gill Exchange for ToxicSubstances): ASimulation Model for Predicting Bioaccumulation of Nonplor Organic Pollutants by fish. U.S. EPA, Center for Exposure Assessment Modeling, Athens, GA. EPA/600/3-87/038. 63. Connolly, J,P.,and R.V.Thomann. 1985. WASTOX,AFmmework for Modeling the Fate of Toxic Chemicals in Aquatic Environments. Port2:food Chain. U.S. EPA,Environmental Research Laboratory, Gulf Breeze, FL. EPA/600/4-85/040. 64. Mills, W-B., I.D. Dean, D.B. Porcella, S.A. Cherini, R.J.M. Hudson, W.E. Frick, G.L. Rupp, and G.L. Bowie. 1982. Water Quality Assessment: A Screening Procedure for Toxic and Conventional Pollutants. U.S. EPA, Environmental Research Laboratory. Athens, GA. EPA600/6-82-004 aand b. 65. U.S. EPA. 1987. Permit Writers Guide to Water Quo&y-based Permitting for Toxic Pollutants. U.S. EPA,Office of Water Enforcment and Permits, Washington, DC. EPA/440/4-87/ 005. 66. Rossman, L.A. Design Stream Flows Based on Harmonic Means. /, ofHydraulic Engineering 116(7):946-50.

92

# 5. PERMIT REQUIREMENTS

5.1 INTRODUCTION Asthe final step in the “standards-to-permits” process, development of permit requirements is often the culmination of the activities discussed in the preceding chapters. This chapter describes the basic principles of effluent variability and permit limit derivation and provides recommendations for deriving limits from various types of wasteload allocation outputs such that water quality standards are protected. Italsoaddresses important considerations in the expression of limits and other types of permit requirements, including toxicity reduction evaluations. The first portion ofthe chapter deals principally with aquatic life protection. Permitting for protection of human health isfound in Section 5.4.4.


### 5.1.1Regulatory Requirements There are both mandatory and discretionary elements associated with the development of water quality-based permit limits to control toxic pollutants and toxicity. The mandatory elements are described in the revisions to the National Pollutant Discharge Elimination System (NPDES) Surface Water Toxics Control Program regulations (54 FR23868, June2, 1989). The regulations at 40 CFR122.44(d)(1) require that regulatory authorities first determine whether adischarge causes, hasthe reasonable potential to cause, or contributes to an excursion above water quality standards (narrative or numeric). In making these determinations, regulatory authorities must use a procedure that accounts for effluent variability, existing controls on point and nonpoint sources of pollution, available dilution, and (when using toxicity testing) species sensitivity. Each of these regulations were previously discussed in Chapter 3.
There isadegree offlexibility in the specific procedures a regulatory authority usesindetermining whether anexcursion occurs or is reasonably expected to occur and in the weight given to the various factors in conducting the evaluation of a specific discharger. The Environmental Protection Agency’s (EPA)guidance for making these determinations iscontained in the recommendations in Chapter 3.
There are also several EPA policies that reflect these regulatory requirements, including the “National Policy forthe Development of Water Quality-Based Limits for Toxic Pollutants” (Appendix B2) and EPA’s “Whole Effluent Toxicity Permitting Principles and Enforcement Strategy,” (Appendix B-4). This strategy states that “all major permits and minors of concern must be evaluated for potential or known toxicity (chronic oracute ifmore limiting).” In addition, the strategy states that “[final whole effluent toxicity limits must be included in permits where necessary to ensure that State Water Quality Standards are met. These limits must properly account for effluent variability, available dilution, and species sensitivity.” There isan element ofjudgment inherent in the specific permit limit derivation procedures used for an individual discharger once a decision has been made to develop a specific type of limit. Case-specific considerations will usually dictate the most appropriate approach to be taken in individual situations. Nevertheless, the various assumptions used in the permit limit development process should be consistent with the assumptions and principles inherent inthe effluent characterization and exposure assessment steps preceding permit limit development. The permit limit derivation procedure used by the permitting authority should be fully enforceable and should adequately account for effluent variability, consider available receiving water dilution, protect against acute and chronic impacts, account for compliance monitoring sampling frequency, and protect the wasteload allocation (WLA) and ultimately water quality standards. To accomplish these objectives, EPArecommends that permitting authorities use the statistical permit limit derivation procedure discussed in Section 5.4 with the outputs from either steady state or the dynamic wasteload allocation modeling.



## 5.2 BASIC PRINCIPLES OFEFFLUENT VARIABILITY

An understanding of the basic principles of effluent variability is central to water quality-based permitting. Many ofthe concepts are the same asthose considered in the development of technology-based limits. However, the process for applying the principles issubstantially different, asexplained below.


### 5.21 VariationsinEffluentQuality Effluent quality and quantity vary over time in terms ofvolumes discharged and constituent concentrations. Variations occur due to anumber offactors, including changes in human activity over a 24-hour period for publicly owned treatment works (POTWs), changes in production cycles for industries, variation in responses ofwastewater treatment systems to influent changes, variation in treatment system performance, and changes inclimate. Very few effluents remain constant over long periods of time. Even in industries that operate continuous processes, variations in the quality of raw materials and activities, such as back-washing of filters, cause peaks in effluent constituent concentrations and volumes.
Ifeffluent data for aparticular pollutant or pollutant parameter for atypical POTW are plotted against time, the daily concentration variations can be seen (see Figure 5-1, left-hand graphs). This behavior can be described by constructing frequency-concentration plots ofthe same data (see Figure 5-1, right-hand graphs).

93

### Figure5-1. DataRelativeFrequencyDistributionsforCeriodaphnia Toxicity,DaphniaToxicity, andZincConcentrationsforThreeDifferentEffluents
94

### 5.2.2 StatisticalParameters andRelathnsh(ptoPemdt Lhdts Based upon the shape ofthe curve of afrequency-concentration plot, the data can be described in terms of a particular type of statistical distribution. The choices for statistical distributions include normal (bell-shaped), lognormal (positively skewed), or other variations on the lognormal distribution. From the vast amount ofdata that EPAhasexamined, it isreasonable to assume (unless specific data show otherwise) that treated effluent data follow a lognormal distribution. This is because effluent values are non-negative and treatment efficiency at the low end of the concentration scale islimited, while effluent concentrations may vary widely atthe high end ofthe scale, reflecting various degrees of treatment system performance and loadings. These factors combine to produce the characteristically positively skewed appearance of the lognormal 

### curve when data are plotted in a frequency histogram. Appendix Ediscusses the basisfor concluding 

### that effluent data aretypically lognormally distributed, aswell asrecommendations for handling data setsfrom treatment plants that follow some other type of distribution.
Effluent data from any treatment system may be described using standard descriptive statistics, such asthe mean concentration of the pollutant or pollutant parameter (i.e., the long-term average [LTA] and the coefficient ofvariation [CVj). The CV isastandard statistical measure ofthe relative variations ofadistribution or set of data, defined as the ratio of the standard deviation to the mean. Using astatistical model, such asthe lognormal, an entire distribution of values can be projected from limited data, and limits can be setataspecified probability ofoccurrence. Figure 5- 1shows the frequency-concentration curve and the relative positions of the concentrations corresponding to the mean for the data.

:x----- --___---__----__----_

, Wasteloed Akxat~on cv=o9 

## s12

= 10 !z 0 Es
s 4 2 n Days

Figure S-2a. Relationship Between a Single Wasteload Allocation and Two Long-Term Averages

for Different Coefficients of Variation All permit limits, whether technology-based or water qualitybased, are set at the upper bounds of acceptable performance. The purpose of a permit limit isto specify an upper bound of acceptable effluent quality. Fortechnology-based requirements, the limits are based on proper operation of atreatment system. For water quality-based requirements, the limits are based on maintaining the effluent quality at a level that will comply with water quality standards, even during critical conditions in the receiving water. These requirements aredetermined by the WM. The WIA dictates the required effluent quality which defines the desired level oftreatment plant performance ortarget LTA.
In the development of technology-based effluent limits guidelines, the operating records ofvarious wastewater treatment facilities for a particular category of discharger are examined. Based onthe effluent data for the treatment facilities, acomposite mean or LTA value for the parameter isdetermined. This LTA value, with relevant estimates ofvariability, isthen used to derive effluent limit guidelines, which lead directly to permit limits.
Incontrast, the process operates in reverse forwater quality-based permit limits. The WV\, determined from water quality standards, defines the appropriate discharge level, which in turn determines the requisite target LTA for the treatment facility in order to meet that WIA. Permit limits may then be derived from this targeted LTA and CV. Figure 5-2 illustrates the relationship among the various statistical parameters. Asthese figures 

### show, highly variable effluents require a much lower targeted LTA to meet the WLA and account for the variability that occurs in effluent concentration above the LTA.
It isextremely important to recognize that the various statistical principles and relationships discussed above operate in any dis05 10 1.5 20 Coeffmeni of Vanatlon
Figure S-2b. Long-Term Average Per Unit Wasteload Allocation asa Function of the Coefficient of Variation

95charge situation-whether or not they are specifically recognized oraccounted for. Where apermit limit derivation procedure does not address these principles specifically, the permit writer will be implicitly assuming 

### that there are enough conservative assumptions built into other steps in the process (e.g., water quality models, “buffer” between permit limits and actual operating conditions) to ensure that there will be no reasonable potential for excursions above water quality standards.


### 5.23 &m?ssho ofPemit lhits The NPDES regulations at40 CFR122.45(d) require that all permit limits beexpressed, unlessimpracticable, asboth average monthly and maximum daily values for all discharges other than POlWs and as average weekly and average monthly limits for POTWs. The maximum daily permit limit (MDL) isthe highest allowable discharge measured during a calendar day or 24-hour period representing acalendar day. The average monthly permit limit (AML) is the highest allowable value for the average of daily discharges obtained over acalendar month. The average weekly permit limit (AWL) isthe highest allowable value for the average ofdaily discharges obtained over acalendar week.
EPAbelieves that a maximum daily permit limit can be directly usedtoexpress aneffluent limit foralltoxic pollutants or pollutant parameters except chronic whole effluent toxicity. The typical toxicity test used to measure chronic toxicity consists of samples collected from at least 3 different days over a 7-day period. Therefore, the test does not measure toxicity inany given 24-hour period or calendar day, but rather measures toxicity over a 7-day period. The toxicity could be caused by any one sample or a combination of samples. To address this situation, EPA recommends that the permit contain a notation indicating that when chronic toxicity tests are required in a permit, the MD1 should be interpreted as signifying the maximum test result for the month. Additionally, in lieu of an AWL for POTWs, EPA recommends establishing an MDL (or a maximum test result for chronic toxicity) for toxic pollutants and pollutant parameters inwater quality permitting. This isappropriate for at least two reasons. First,the basisfor the 7-day average for POTWs derives from the secondary treatment requirements. This basis isnot related to the need for assuring achievement ofwater quality standards. Second, a7-day average, which could comprise upto seven or more daily samples, could average out peak toxic concentrations and therefore the discharge’s potential for causing acute toxic effects would be missed. A MDL, which ismeasured by agrab sample, would be toxicologically protective of potential acute toxicity impacts.



## 5.3 EHSURIWG CONSISTENCY WITH THE waslEl.oao au.ocaTloH

The WLA provides adefinition ofeffluent quality that isnecessary to meet the water quality standards ofthe receiving water. The WIA isbased on ambient criteria and the exposure ofthe resident aquatic community or humans to toxic conditions. Once aWIA has been developed, accounting for all appropriate considerations, a water quality-based permit limit may be derived to enforce the WLA. The method used to derive the permit limits must be consistent with the nature ofthe WLA.
The WIA addresses variability in effluent quality. Forexample, a WLAfor human health pollutants istypically expressed asasingle level of receiving water quality necessary to provide protection against long-term or chronic effects. On the other hand, aWLA for toxic pollutants affecting aquatic life (with corresponding duration and frequency requirements) should describe levels necessary to provide protection against both short-term and longterm effects.


### 5.3.I 3tat&tlcol &onsi~~os ofbus Direct useofaWLA asapermit limit creates asignificant riskthat the WLAwill be enforced incorrectly, since effluent variability and the probability basisfor the limit are not considered specifically. Forexample, the useofasteady state WIA typically establishes a level ofeffluent quality with the assumption that it isavalue never to be exceeded. The same value used directly asa permit limit could allow the WLA to be exceeded without observing permit violations if compliance monitoring was infrequent, Confusion can also result in translating a longer duration WlA requirement (e.g., for chronic protection) into maximum daily and average monthly permit limits. The permit writer must ensure that permit limits are derived to implement a WIA requirement correctly. Potential problem areas are asfollows:
The WL4 must be enforced in a regulatory context by translating it into MDLs and AMLs; then and only then, will compliance monitoring associated with permit limits allow the regulatory authority to determine whether or not such permit limits areviolated. The WLA that assumes that the discharge issteady state (i.e., not changing over time) requires a limit derivation assumption regarding how the effluent may vary. MDLs and AMLs average monthly limits must be developed so that they are consistent with each other and mandate the required level of wastewater treatment facility performance. Ifthe acute WLA isused alone directly asthe MDL, the limit will not necessarily be protective against chronic effects. If the acute WLA isused alone directly asthe AML, the limit can allow excursions above the WIA within each month. If

### thechronic WLA isusedalone asan MDL, the limit will be protective against acute and chronic effects but at the expense of being overly stringent. Ifthe chronic WLA is used alone asthe AML, the limit may be protective against acute and chronic effects depending upon effluent variability.
The objective isto establish permit limits that result inthe effluent meeting the WL4 under normal operating conditions virtually all the time. It isnot possible to guarantee, through permit limits, that aWLAwill never be exceeded. It ispossible, however, using the recommended permit limit derivation procedures, to account forextreme values andto establish low probabilities ofexceedence

96of the WIA in conformance with the duration and frequency requirements of the water quality standards. This isnot to suggest that permit writers should assume aprobability ofexceeclence of the WIA, but rather, that they should develop limits that will make an exceedance avery small likelihood.
Since effluents arevariable and permit limits are developed based on a low probability of exceedence, the permit limits should consider effluent variability and ensure that the requisite loading from the WIA isnot exceeded under normal conditions. Ineffect then, the limits must “force” treatment plant performance, which, after considering acceptable effluent variability, will only have a low statistical probability of exceeding the WIA and will achieve the desired loadings. figure 5-3 shows a number of important aspects of the relationships among the various statistical parameters. Inthis illustration, the most limiting LTA (after comparing the LTASderived from both acute and chronic WLAs) has been chosen for the chronic limiting condition. The more restrictive LTA will automatically meet both WIA requirements. Ifthe effluent “fingerprint” for this LTA (and associated CV) is projected, it can be seen that the distribution of daily effluent values will not exceed the acute or chronic wasteload allocations for unacceptable periods of time. The duration andfrequency requirements ofthe acute and chronic criteria for the pollutant or pollutant parameter will not be exceeded. This figure also illustrates permit limits derived from the more limiting LTA. (Note that for the scenario depicted in Figure 5-3, the MDL is lower than the acute WIA and the average monthly limit is lower than the chronic WIA. This scenario will occur when a99-percent probability basis isused to calculate the LTA and a 95percent probability basis is used to calculate the permit limits from the lower of the acute and chronic LTA. For other probability assumptions, these relationships will differ.)


### 5.3.2 Tvpes ofWaterQuaMyModelsandModsIlli@wts Eachofthe two major types ofwater quality models, steady-state and dynamic, and their WlA outputs ha\‘? specific implications

I I I I I I 0 10 20 30 40 50 Days Figure 5-3. Relationship Between Daily Concnetrations, Long-Term Average, Wasteload Allocations, and Permit Limits for the subsequent permit limit development process. These implications are discussed in detail below. EPA recommends that steady-state WLA analyses generally be used by permitting authorities in most cases and especially where few or no whole effluent toxicity or specific chemical measurements are available, or where daily receiving water flow records are not available. Two-value, steady-state models, although potentially more protective than necessary, can provide toxicologically protective results and are relatively simple to use. If adequate receiving water flow and effluent concentration data are available to estimate frequency distributions, EPA recommends that one ofthe dynamic WLA modeling techniques be used to derive WiAs that will more exactly maintain water quality standards. Steady-State Modeling
Traditional single-value or two-value steady-state WIA models calculate WlAs at critical conditions, which are usually combinations of worst-case assumptions of flow, effluent, and environmental effects. Forexample, a steady-state model for ammonia considers the maximum effluent discharge to occur on the day of lowest river flow, highest upstream concentration, highest pH, and highest temperature. Each condition by itself has a low probability of occurrence; the combination of conditions may rarely or never occur. Permit limits derived from a steady-state WL4 model will be protective of water quality standards at the critical conditions and for all environmental conditions lessthan critical. However, such permit limits may be more stringent than necessary to meet the return frequency requirements ofthe water quality criterion for the pollutant of concern. On the other hand, a steady-state model approach may involve simplifying assumptions for other factors, such asambient background concentrations of atoxicant, multiple source discharges of a toxicant, number of pollutants causing toxicity, incorrect effluent variability assumptions, and infrequent compliance monitoring. Theeffect ofthesetypes offactors, especially ifunaccounted for in the WLA determination, can reduce the level of protectivenessprovided by the critical condition assumptions ofthe steadystate model approach. Therefore, when using asteady-state WIA model, the permitting authority should be aware ofthe different assumptions and factors involved and should consider these assumptions and factors adequately consideration when developing permit limits.
In general, steady-state analyses tend to be more conservative than dynamic models because they rely on worst case assumptions. Thus, permit limits derived from these outputs will generally be lower than limits derived from dynamic models. o) Sing/eValue FromaSteady-Stote Analysis
Some single-value, steady-state modeling hasbeen used to calculate only chronic WlAs. These models produce a single effluent loading value and no information about effluent variability. Single value WLAs are typically based upon older State water quality standards that do not specify levels for both acute and chronic protection but only include one level ofprotection. Such outputs alsowould be found where amodel isbased upon protection of human health, since only a single long-term ambient value isof concern.

97b) Two Valuesfrom Steady-State Analysis Steady-state modeling for protection of aquatic life can specify two setsof calculations-one for protection against acute effects and one for protection against chronic effects. These models must usewater quality criteria specifying two levels of protection. 

### Inaddition, these models include considerations of mixing zones when developing WlAs to afford two levels of protection. Like the single-value, steady-state models, these models do not produce any information about acceptable effluent variability and may require additional calculations to be translated into permit limits.
For complex discharge situations (i.e., multiple dischargers or complex environmental factors needing consideration), water quality models and associated WLASare typically developed by specialized water quality analysts in the regulatory authority. However, the permit writer isoften required to develop awater quality model and WLA prior to permit limit derivation. In the latter situation, water quality modeling usually consists ofsimple steadystate dilution models using worst-case assumptions. Dynamic Modeling Dynamic models use estimates of effluent variability and the variability of receiving water assimilation factors to develop effluent requirements in terms of concentration and variability. The outputs from dynamic models can be used to base permit limits on probability estimates of receiving water concentrations rather than worst-case conditions. The advantages and disadvantages ofvarious types of dynamic models are provided inChapter 4.
Ingeneral, dynamic models account for the daily variations ofand relationships between flow, effluent, and environmentat conditions and therefore directly determine theactual probability that a water quality standards exceedence will occur. Because of this, dynamic models can be used to develop WLAsthat maintain the water quality standards exactly at the return frequency requirements ofthe standards. Sincethis return frequency isusually one event in 3years, Wk developed bydynamic models aretypically higher than those developed by steady-state models.
Atargeted long-term average performance level and coefficient of variation can be derived from each type of dynamic model output, but some of the outputs require some additional manipulation ofthe data todevelop the LTAand the CV. These parameters are alsothe starting point for the statistical permit limit derivation procedures discussed in the next section. Continuous Simulation models offer an array of effluent data that require further manipulation to develop an LTAand a CV. Both Monte Carlo and Lognormal Probabilistic models produce an LTA and CV, which can be used directly indeveloping permit limits. Chapter 4 details the different dynamic models. Specific instructions for the useofdynamic models are available inthe references listed at the end ofChapter 4.



## 5.4 PERMlTlJMlTDERlVATlOW

There are anumber of different approaches currently being used by permitting authorities to develop water quality-based limits for toxic pollutants and toxicity. Differences inapproaches areoften attributable to the need for consistency between permit limit derivation procedures and the assumptions inherent in various types of water quality models and WlA outputs. In addition, permitting authorities also are constrained by legal requirements and policy decisions that may apply to agiven permitting situation. In some instances, however, permitting procedures have been adopted without careful consideration of the toxicological principles involved or the advantages and disadvantages of the procedure.
To avoid this problem, EPA recommends that the statistical permit limit derivation procedure described in this chapter be used for the derivation of both chemical-specific and whole effluent toxicity limits for NPDES permits. The type of WLA chosen from which to derive the limits isamatter ofcase-by-case application, asdetermined by the permitting authority. Although there are advantages and disadvantages associated with each of the procedures, EPAbelieves that the statistical derivation procedures will result in the most defensible and protective water quality-based permit limits for both specific chemicals and whole effluent toxicity.
The following section explains EPA’s recommended permitting procedures and highlights advantages and disadvantages ofvariousother approaches. With this information, permitting authoritieswill be better informed when deciding on the most appropriate permit limit derivation approach. For example, permitting authorities may decide to derive water quality-based permit limits for all dischargers using a steady-state WIA model asa baseline limit determination. Iftime and resources are available or ifthe discharger itself takes the initiative (after approval by the regulatory authority), dynamic modeling could be conducted tofurther refine the WV\ from which final permit limits would be derived. Box 5-l presents example permit limit calculations for each ofthe principal types ofWL4 outputs dlscussed in Section 5.4.1. Permit limits derived from dynamic modeling are usually higher than those based upon steady-state modeling. The difference is reflected inBox 5-l and hasbeen observed inactual applications [l, 2, 31. In addition, the case studies in Chapter 7 illustrate how water quality-based permit limits are derived and compare the results of limits derived from steady state and dynamic wasteload allocations.


### 54.1 EPA Rec~n~tituts forPmritthrg forAquatic Uf&? mtRctiun Permit Limit Derivation from Two-Value, Steady-State Outputs for Acute and Chronic Protection
A number of WL4s have two results: acute and chronic requirements. These types ofallocations will be developed more often as States begin to adopt water quality standards that provide both acute and chronic protection foraquatic life. These WLAoutputs need to be translated into MDLs and AMLs. The following methodology isdesigned toderive permit limits forspecific chemicalsaswell aswhole effluent toxicity to achieve these WLAs.

l Atreatment performance level (LTAand CV) that will allow the effluent to meet the WLA requirement is calculated.

98Box B-1. Sample Calculations of Permit Limits for Whole Effluent Toxicity from Different Wasteload Allocation Data 

## r---- ----- .- - - --- L------------ Available Data

1 Two Value wasteload Dynamic model Single warteload j ------ --- - ---~-~_ allocation ~-----------.- output allocation - ---.--.-.- --A

,Wastefoad Allocation (WLA)

____ _--_ 14.3 Acute Wasteload Allocation (WlAa) 2.60 ---_ -__- Chronic Wasteload Allocation (WlAc) 14.3 __-_ __-_ IAcute-Chronic Ratio 4.62

____ I-.- 1Coefficient of Variation (CV) 0.8 0.8 0.8 )Number of Samples per Month (n) 4 4 4 ILong Term Average (LTA) I
---- 9.44 -_.- ----- 

### --i 

# I--.-- From two-value steady state wasteload allocatlon ---7 I- - - - - - From dynamk model output I
i I WLA,,,= WlA,*ACR = 2.6094.62 = 12.0 LTA, =WfApe (0.504~-2.326041 = 14.300.440 (from Table 5-1) = 6.29 MDL = LTAc*e [2.326o-O.So*]= 9.4404.01 (from Table 5-2)= 37.9 LTAa,c = WIAa,c*e [O.S$-2.3260]= 12.0*0.249 II I (from Table S-l) = 2.99 MDL = LTA,,c*e [2.326o-O.Sa*] = 2.99*4.01 (from Table 5-2) = 12.0 II AML = LTApe [2.3260n-O.Son*]= 9.44.2.27 (from Table S-2)= 21.4 AML = LTAa,,*e [2.326o,-O.So,*~= 2.9902.27 (from Table 5-2) = 6.79 I I 

### ! 

# !i__ -~---.- - - - - - --I 

# r---- -- ---- -.--------~ From slngk warteload allocation ------- ------------J lOntion 1 I 

# I . LTA =WLA*e [0.502-2.32601 = 14.3*0.440 (from Table 5-l) = 6.29 ’ MDL = LTA-e [2.3260-O.Sa*] = 6.29*4.01 (from Table 5-2) = 25.2 ’ Note: Allcalculations usethe 99th
AML = LTA*e [2.3260,-OSo,*) = 6.29-2.27 (from Table 5-2) = 14.3 percentile zstatistic for calculation I of long-term averages and permit

:Option 2 ’ limitsMDL =wlA = 14.3 I 1 AML = MDLI2 = 7.15 I - .- - .- - -J

Where two requirements are specified based on different duration periods, two 

### performance levels are calculated (Box 5-2, Step 2).

l Forwhole effluent toxicity only, the acute WV\ isconverted into an equivalent chronic WL4 by multiplying 

### the acute WLA by an acute-to-chronic ratio (ACR). This ratio should optimally be based on effluent data, but also can be estimated as 10, based 

### on the information presented in Chap ter 1and Appendix A.

l Permit limits are then derived directly from whichever performance level is more protective (Box 5-2, Steps 3and 4). Figure 54 presents aflow 

### chart summarizing the various steps in this procedure. In addition, the equations used in Box 5-2 are based 

### on the lognormal distribution, which isexplained in more detail inAppendix E. The principal advantages ofthis procedure are described below.

l This procedure provides a mechanism for setting permit limits that will be toxicologically protective. Asteady-state WL4 usesasingle value to reflect the effluent loading and 

### thus isan inherent assumption that the actual effluent will not exceed the calculated loading value. If the WIA is simply adopted asthe permit limit, the possibility exists for exceedance ofthe WLA due to effluent variability. Clearly, however, effluents are variable. Therefore, permit limits are established using avalue corresponding to a percentile of the selected probability distribution of the effiuent (e.g., 95th or 99th percentile). . Itallows comparison oftwo independent WLAs (acute and chronic) to determine which is more limiting for a discharge. The WLAoutput provides two numbers for protection against two types of toxic effects, each based upon different mixing conditions for different durations. Acute effects are limited based upon 1-hour exposures at critical conditions, close to the point ofdischarge, orwhere necessary, 

### at the end of the pipe. Chronic effects are limited based on 4-day exposures after mixing at critical conditions. These requirements yield different effluent treatment requirements that cannot be compared to each other without calculating the LTA performance level the plant would need to maintain inorder to meet each requirement. With

### out this comparison (or in the absence 

### of procedures that address this comparison), the WLA representing the more critical condition cannot be determined. Atreatment system will only need to be designed to meet one level of

99Box 5-2. Calculating Permit Limits Based on Two-Value Wasteload Allocation

Toset maximum daily and average monthly permit limits based on acute and chronic wasteload 

### Step 1 (forwhole effluent toxicity only)

allocations, use the following four 

### WLA,, (in TU,)=WLA, (in TU,) l 

### ACR steps:Convert the acute wasteload



## 1 allocation tochronic toxic 

### Step 2 (start here forchemical specific limits) units. Skip toStep 2for chemical-specific limits. LTA, c = Wu, c l e [o.52 - “1 Calculate the long-term where o’ =fn(CV’+l) 

## 2 average wasteload that will z= 1.645for95th percentile probability basis, and satisfy the acute and chronic z=2.326 for99th percentile probability basis wasteload allocations. Determine the lower (more LTA, = W& l e [“.50z - 

### z”4]
3 limiting) ofthe two long-term where 04*=ln(CV2/4 +l) averages z= 1.645 for95th percentile probability basis, and z=2.326 for99th percentile probability basis Calculate the maximum daily



### Step 3

Term Meaning 

### LTA=min (LTA,, LTA,,)

cv 0 w%,c

w%

W”c

LTAsc LTA,

T”a T”c ACR MDL AML

Z Coefficientofvariation Standarddeviation Acutewasteloadallocation inchronic toxic units Acute wastelaad allocation inacute toxic units Chronicwasteload allocation inchronic toxic units Acutetong-termaverage wasteload inchrunic units Chronic long-term average wasteload Acutetoxicunits Chronic toxic units Acute-to-chronic ratio Maximum daily limit Average monthly limit 2statistic 

### Step 4

MDL = LTA l e iza -o.52l where d = In(CV2+1) z= 1.645 for95th percentile probability basis, and z=2.326 for99th percentile probability basis

AML = LTA l e Izon - o.50,21 where on2 = ln(CV*/n +l ) z= 1.645 for95th percentile probability basis, and z=2.326 for99th percentile probability basis

‘Full &tails ofthisprocedure are found inAppendix E.

100I 1 CakulateChmnic 1

Calculate Maximum Dally Umlt 

### / 

# I Calculate Avaraga

Monthly Llmh I Figure S-4. Flowchart for Calculating Permit Llmits From Two-Value, Steady-State Wasteload Allocatlon for Aquatic Life Protection

treatment for effluent toxicity-treatment needed to control the most limiting toxic effect.

l The actual number ofsamples can befactored into permit limit derivation procedures. The procedure provides the means to accurately determine the AML based on the number ofobservations that will be taken.
The principal disadvantages ofthis approach are:

l Some permit writers have indicated that additional mathematical calculations associated with these procedures increase the burden for the permit writer and add what isperceived to be an unnecessary step.

l The useof asteady-state WLA may result in permit limits that are more conservative due to the assumption ofcritical conditions. However, these limits arestill protective ofwater quality criteria. The level of conservatism may be necessary in those instances where limited data prevent amore precise evaluation of aWLA. This procedure provides a toxicologically sound approach. To help the permit writer, EPAhasdeveloped tables (seeTables 5-l and 5-2) to be used to quickly determine the necessary values. In addition, some permit authorities have developed their own computer programs to readily compute the necessary information from the appropriate inputs.
Permit Limit Derivation From Dynamic Model Outputs
The least ambiguous and most exact way that aWIA for specific chemicals orfor whole effluent toxicity can be specified by using dynamic modeling from which the WIA isexpressed asarequired effluent performance in terms of the LTA and CV of the daily values. When aWLA isexpressed assuch, there isno confusion about assumptions used and the translation to permit limits. A permit writer can readily design permit limits to achieve the WLA objectives. The types of dynamic exposure analyses that yield a WLA interms of required performance arethe continuous simulation, Monte Carlo, and lognormal probabilities analyses. Chapter 4provides ageneral discussion ofthese models. Guidance manualsfor developing WLASare listed in the references at the end of Chapter 4. Once the WL4 isdetermined, the permit limit derivation procedure which can be usedfor both whole effluent toxicity and specific chemicals, isasfollows:
The WL4 isfirst developed by iteratively running the dynamic model with successively lower LTAs until the model shows compliance with the water quality standards. The effluent LTAand CV must then be calculated from the model effluent inputs used to show compliance with the water quality standards. This step isonly necessary for the Monte Carlo and continuous simulation methods. The permit limit derivation procedures described in Box 5 2, Step 4 are used to derive MDLs and AMLs from the required effluent LTAand CV. Unlike these procedures for steady-state WIAS, there isonly a single LTAthat provides both acute and chronic protection, and, therefore, the comparison step indicated in Figure 5-4 and Box 5-2 is unnecessary. The principal advantages ofthis procedure are:

l It provides a mechanism for computing permit limits that are toxicologically protective. Aswith the procedure summarized below for two-value, steady-state WLA outputs, the permit limit derivation procedures used with this type of output consider effluent variability and derive permit limits from asingle limiting LTAand CV.

l Actual number of samples is factored into permit limit derivation procedures. This procedure has the same elements asdiscussed for the statistical procedures inOption 2 below.

l Dynamic modeling determines an LTA that will be adequately protective ofthe WLA, which relies on actual flow data thereby reducing the need to rely onworst casecritical flow condition assumptions.

101Table S-l. Back Calculations of Long-Term Average
---_----_---_ WIA Multipliers

.-- - --- (-J/ I e[o.5 a2-201 I

i--~-------- __ ---I 95th Percentile ____t----L------! 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.0 0.9 1.0 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2.0 0.853 0.738 0.644 0.571 0.514 0.468 0.432 0.403 0.379 0.360 0.344 0.330 0.319 0.310 0.302 0.290 0.290 0.285 0.2m 0.277 0.797 ; 0.643 ( 0.527 0.440 0.373 0.321 0.281 0.249 0.224 0.204 1 0.187 0.174 0.162 0.153 0.144 0.137 0.131 0.126 1 0.121 0.117 I I_ - -.---~ -----------____-- - - -- -- ------ _ - - --- ---- ---, AC&?


### LTA,,c=WLA,, l 

### e[“”02- ’=’

here u*= /n[CV* + 11. 2=1.645for95thpercentileoaxrnen~probebili(y,and I
z= 2.326 for9Qth percentileoccurrerxe probability I

--- ------------ I ------- 

# T-------_-------, WIA Multipliers I



### Chronic (4-day average)

where u,2= ffl[CV2/4+ 11. z = 1.645foc95thpercentileoccunenceprobability,and z =2,326for991trpercentile~~eprohabiliOl cv

0.; 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2.0 j e[o.s u4’- L u4 ] I
7---- _-- -----

0.922 0.853 0.791 0.736 0.687 0.644 0.606 0.571 0.541 0.514 0.490 0.460 0.449 0.432 0.417 0.403 0.390 0.379 0.369 0.380 I 0.891 0.797 ’ 0.715 ’ 0.643

, 0.581 / 0.527 0.481 I 0.440 1 0.404
’ 0.373
’ 0.345 0.321

, 0.300 0.261 0.264 ; 0.249 0.236

, 0.224
i 0.214 0.204 _L_ _--- -

The principal disadvantages ofthis procedure are: Permit Limit Derivation From Single, Steady-State Model Output

l Necessary data for effluent variability and receiving water flows may be unavailable, which prevents the use of this approach. Some Statewater quality criteria and the corresponding WlAs are reported as a single value from which to define an acceptable

l The amount of staff resources needed to explain how the level of effluent quality. For example, “copper concentration limits were developed and to conduct the WLA also is a must not exceed 0.75 milligrams per liter (mg/l) instream.” Steadyconcern. The permit documentation (i.e., fact sheet) will state analyses assume that the effluent isconstant and, therefore, need to clearly explain the basisfor the LTAand CVand this the WL4value will never beexceeded. This presents aproblem in

can be resource intensive. deriving permit limits because permit limits need to consider effluent variability.

102Table 5-2. Calculation of Permit Limits

LTA multipliers

cv eIzo-o.502]
95th 99th Percentile Percentile
0.1 1.17 1.25 0.2 1.36 1.55 0.3 1.55 1.90 0.4 1.75 2.27 0.5 1.95 2.66 0.8 2.13 3.11 0.7 2.31 3.56 0.8 2.40 4.01 0.9 2.64 4.46 1.0 2.78 4.90 1.1 2.91 5.34 1.2 3.03 5.76 1.3 3.13 6.17 1.4 3.23 6.56 1.5 3.31 6.93 1.6 3.38 7.29 1.7 3.45 7.63 1.8 3.51 795 1.9 3.56 6.26 2.0 360 8.55 

### Maximum Daily Limit

MDL=LTAme[Zu-o.5621

where u2 In [CV2 + 1 1. = z 1.645 for 95th percentile occurrence

= probability, and z =2.326 for 99th percentile occurrence probability

LTA Multipliers e’ 2 a, -0.5 CT"21

cv

. 95th 99th 

### Average Monthly Limit Percentile Percentile
rkl n=2 n=4 n=lO n=30 n=l n=2 n=4 n=iO n=30

0.1 1.17 1.12 1.06 106 1.03 1.25 1.18 1.12 106 1.04 0.2 1.36 1.25 1 17 1.12 1.06 1.55 1.37 1.25 116 109 0.3 1.55 1.38 1.26 1.18 1.09 1.90 159 1.40 124 113 0.4 1.75 t.52 1.36 1.25 1 12 2.27 1.83 1.55 1.33 1 16 0.5 JML=LTAee 

### [zo,-0’5n”21 0.6 1.95 1.86 1.45 1.31 1.16 2.68 2.09 1.72 1.42 1.23 2.13 1.60 1.55 1.38 1.19 3.11 2.37 190 152 1.26 0.7 2.31 1.94 1.65 1.45 1.22 3.56 2.66 2.06 162 1.33 wherean2=In[CV2/n+1], 0.8 2.48 2.07 1.75 1.52 1.26 4.01 2.96 2.27 173 1.39 09 2.64 2.20 1.65 1.59 1.29 4.46 3.28 2.48 184 1.44 z = 1.645 for 95th percentile, 1.0 2.78 2.33 1 95 1.66 1.33 4.90 3.59 2.68 1 96 150 z =2.326 for 99th percentile, and t t 2.91 2.45 2.04 '.73 1.36 5.34 3.91 2.90 2.07 156 n= number of sampletimonth 12 3.03 2.56 2.13 1.80 1.39 5.76 4.23 3.11 2.19 1.62 1.3 3.13 2.67 2.23 1.87 1.43 6.17 4.55 3.34 2.32 166 14 3.23 2.77 2.31 1.94 1.47 6 56 4.86 3.56 2.45 1 74 1.5 3.31 2.66 2.40 2.00 1.50 6.93 5.17 3.78 2.58 160 1.6 3.38 2.95 2.48 2 07 1.54 7.29 5.47 4.01 2.71 1.67 17 3.45 3.03 2.56 2.14 1.57 7.63 5.77 4.23 2.84 193 1.8 3.51 3.10 2.64 2.20 1.61 7.95 6.06 4.46 2.98 2.00 1.9 3.56 3.17 2.71 2.27 1.64 8.26 6.34 4.68 3.12 2.07 2.0 3.60 3.23 2.78 2.33 1.66 8.55 6.61 4.90 326 2 14

The proper enforcement of this type of WIA depends on the parameter limited. For nutrients and biochemical oxygen demand (BOD), the WlA value generally has been used as the average daily permit limit. However, the impact associated with toxic pollutants is more time dependent, asreflected inthe 4-day average duration for the criteria continuous concentration (CCC) (see Chapter 2). Where there isonly one water quality criterion and therefore only one WL4, permit limits can be developed using the following procedure: The principal advantages and disadvantages ofthis procedure are similar to those for the two-value permit limit derivation method discussed previously except that it does not examine two WL4s.


### 5.4.2 UthorA#mdo.s toPamittin~ forAquatfclife Other approaches for translating WLA outputs into permit limits have been used by some permitting authorities. These methods may combine elements of the statistical procedures discussed earlier with specific technical and policy requirements of the permitting authority to derive limits that may be protective of water quality and consistent with the requirements of the WLA. Such approaches may usesimplified statistical procedures. l Consider the single WLAto be the chronic WLA and derive an chronic LTAfor this WLA using the procedures in Box S2 (Step 2, Part2).

l Derive MDLs and AMLs using the procedures ‘in Box 5-2 (Step 4).

103Forexample, some permitting authorities assume avalue for the CV and an acute to chronic ratio above which the chronic WIA will always be more limiting. Where such simplifying assumptions are used, the need to compare LTAs derived from acute and chronic steady-state models is unnecessary. Similarly, for assumed values for n, CV, and exceedence probability, the various equations shown in Box S-2 can be simplified further, such that the AML will always be aconstant fraction ofthe MDL.
These approaches allow the permit writer to rapidly and easily translate the results of WL4.s into permit limits. However, the permit writer clearly should understand the underlying procedures and carefully explain the basisfor the chosen assumption. Appropriate State or regional guidance documents alsoshould be referenced.
Another approach used by some permit authorities involves the direct useofthe WIA asapermit limit. This approach sometimes involves the following steps:

l The WlA value for toxic pollutants isused asthe MDL. . Inthe absence ofother information, permit writers typically divide the MDL by 1.5 or2.0 to derive anAML (depending on the expected range ofvariability).
The principal advantage ofthis approach isthat it isvery straightforward to implement and requires minimal resources. The disadvantage ofthis option isthat the average monthly limits must be derived without any information about the variability ofthe effluent parameter; therefore, the permit writer cannot be sure that these procedures are protective of water quality criteria. Conversely, limits derived from this approach may be overly stringent and subject to challenge.
The direct application of both the acute and chronic WLASas permit limits isanother approach that has been used. The WLA developed for protection against chronic effects becomes the average monthly limit and the acute WIA becomes the MDL. EPA discourages the use of this approach. Since effluent variability has not been specifically addressed with this approach, compliance with the monthly average (30-day) effluent limit during critical conditions could exceed the chronic (4-day) WLA. Whether standards are violated with excessive frequency under such conditions would depend upon whether the conditions represented by the worst-case assumptions of the model also were occurring at the same time. Bycontrast, compliance with limits that were developed using statistical procedures have alow chance of leading to WIA excursions before effluent variability is accounted for inderiving the limits (see Figure S-3).
Another permitting approach isto use a narrative “no toxicity” limit that is measured using a toxicity testing method that employs only acontrol and asingle exposure at the receiving water concentration (RWC). This issometimes referred to asa “pass/ fail” toxicity test. Although these tests can be lessexpensive than full dilution series testing, they provide no knowledge asto the extent of toxicity present during the test and therefore no data concerning the seriousness ofthe impact orthe amount oftoxicity reduction necessary. The death of a single test animal can occur atany concentration level beyond the lethality threshold for the test organism; therefore, such a test is much less powerful from a statistical standpoint. In addition, it is not possible to determine dose-response relationships for the testorganisms without using multiple effluent concentrations. Dose-response curves are useful in determining quality assurance of the tests and in defining threshold dosages for regulatory purposes. Because the drawbacks ofthe approach generally outweigh the benefits, EPA recommends that whole effluent toxicity limits be established using a statistical derivation procedure that adequately accounts for effluent variability and that monitoring for compliance with whole effluent toxicity limits be conducted using a full dilution series.
When setting a whole effluent toxicity limit to protect against acute effects, some permitting authorities use an end-of-pipe approach. Typically, these limits are established asan LCsdl OOpercent effluent atthe end ofthe pipe. These limits are routinely setwithout any consideration asto the fate ofthe effluent and the concentrations oftoxicant after the discharge enters the receiving water. Limits derived in this way are not water quality-based limits and sufferfrom significant deficiencies since the toxicity ofa pollutant depends mostly upon concentration, duration of exposure, and repetitiveness ofthe exposure. This isespecially true in effluent dominated waters. Forexample, an effluent that hasan LCso=lOO percent contains enough toxicity to be lethal to up to 50 percent ofthe test organisms. Ifthe effluent isdischarged to a low-flow receiving waterbody that provides no more than athreefold dilution at the critical flow, significant mortality can occur in the receiving water. Furthermore, such a limit could not assure protection against chronic effects in the receiving waterbody. Chronic effects could occur ifthe dilution in the receiving water multiplied by the acute to chronic ratio is greater than 100 percent. Therefore, in effluent dominated situations, limits set using this approach may beseverely underprotective. Incontrast, whole effluent toxicity limits set using this approach invery high receiving water flow conditions may be overly restrictive. Because of these problems, EPA recommends that all whole effluent toxicity limits be set aswater quality-based limits and that to do so,the statistical permit limit derivation procedures discussed in Section 5.4.1 be followed.


### 5.4.3 specialPemlntin#lh@mmt?& Water quality-based permit limit development for discharges to marine and estuarine waters follows the same basic steps asthe water quality-based approach for freshwater discharges. There are some differences inthe water quality criteria used asthe basis for protection, the designation of mixing zones, and the water quality models used to develop WL4s; however these differences are addressed in the WL4. (See discussions of these elements in previous chapters.) Inaddition, there aresome special regulatory considerations associated with these types ofdischargers, including special reviews of permits with such programs asthe Coastal Zone Management Program. Some discharges also require an Ocean Discharge Criteria Evaluation under Section 403(c) ofthe Clean Water Act (CWA).


### 5.4.4 EPA ltmmnmmt8tions forPemMtingfbrMuman HealtlrNtection Permit development to protect against certain routes ofexposure isanother key consideration. Ingesting contaminated fish and shellfish is a toxic chemical exposure route of serious potential

104human health concern for which there is no intervening treatment process, unlike the drinking water route of exposure. Effluent limits designed to meet aquatic life criteria for individual toxicants and whole effluent toxicity are not necessarily protective oftoxic pollutant residue formation infish or shellfish tissue. Developing permit limits for pollutants affecting human health is somewhat different from setting limits for other pollutants because the exposure period isgenerally longer than 1month, and can be up to 70years, and the average exposure rather than the maximum exposure is usually of concern. Because compliance with permit limits isnormally determined on a daily or monthly basis, it isnecessary to set human health permit limits that meet a given WLA for every month. Ifthe procedures described previously for aquatic life protection were used for developing permit limits for human health pollutants, both MDLs and AMLs would exceed the WIA necessary to meet criteria concentrations. Thus, even ifafacility was discharging incompliance with permit limits calculated using these procedures, it would be possible to constantly exceed the WL4. Thisapproach clearly isunacceptable. In addition, the statistical derivation procedure isnot applicable to exposure periods more than 30 days. Therefore, the recommended approach for setting water quality-based limits for human health protection with statistical procedures isasfollows:

l Setthe AML equal to the WLA

l Calculate the MDL based on effluent variability and the number of samples per month using the multipliers provided inTable 5-3.
This approach ensures that the instream criteria will be met over the long-term and provides adefensible method for calculating a MDL. Both an MDL (weekly average limit for POTWs) and a monthly average limit are required by EPA regulations, unless impracticable (40 CfR 122.45(d)) and are applicable for human health protection. The MDL sets an upper bound on effluent values used to determine the monthly average and provides a measure of effluent compliance during operational periods between monthly sampling.



## 5.5 SPEClAlCONSlDERATlONSlHlJSEOF STATlSTlCAlPERMlTUMfTDERlVATlON TECHNIQUES

The following discussion summarizes the effect of changes in the various statistical parameters onthe permit limits that arederived. An understanding of these relationships isimportant for the permit writer. Additional considerations of each ofthese parameters with respect to the statistical methods for permit limit derivation also are discussed below.


### 5.5.I Eflect 

### ofChaqesof3fotisticol 

### Panmreters onPmnit Lfmlts

l Effect of changes in CV on derivation of LTAfrom WLA: IG the CV increases, the LTAdecreases; and conversely, as the CVdecreases, the LTAincreases (see Figure 5-S). Reason: The LTA must be lower relative to the WLA to account for the extreme values observed with high CVs. An LTAwith azero CVequals the WLA.

l Effect of changes in CVon derivation of permit limits for afixed probability basis: As

### the CV increases, the permit limits increase (become lessstringent); and conversely, as the CVdecreases, the permit limits decrease (become more stringent; see Figure S-6). Reason: Ahigher value for the permit limit isproduced for the same LTAsas the CV increases in order to allow for fluctuations about the mean. Following the steps in Box S2 to derive the LTAwill account for such fluctuations.

l Effect of changes in number of monthly samples on permit limits: Asthe value for “n” (number of observations) increases inthe average monthly permit limit derivation equations, the average monthly permit limit decreases to acertain point. The effect on the average monthly limit isminimal for values of n greater than approximately 10. Conversely, as the value for “n” decreases, the AML increases until n=l, atwhich point the AML equals the MDL (see Figure S-7). Reason: Asn increases, the probability distribution of the n-day average values becomes less variable (narrower) around the LTA. Therefore, the 95th or 99th percentile value for an n-day average decreases in absolute value asn increases. (Seeadditional discussion in Section 5.5.3.)

l Effect of changes in probability basis for permit limits: As the probability basis for the permit limits expressed in percentiles (e.g., 95 percent and 99 percent) increases, the value for the permit limits increases (becomes less stringent). The converse is true as the probability basis decreases (see Figure 5-6).

0 I

0.0 0.5 10 1.5 2. Coefficient of Vanation Figure 5-5. Long-Term Average asa Function of the Coefficient of Variation

105Reason: There isa higher probability that any randomly chosen effluent sample will be incompliance with itspermit limits, ifthose limits are statistically designed to be greater than a high percentage (e.g., 99 percent) of all possible values for agiven LTAand CV. illustrates how the CV, number of samples and probability basis affect the derivation of the AML. Figure 5-9 illustrates the combined effect ofthe CVand the probability basison the derivation ofthe MDL.

The overall combination ofthe coefficient ofvariation, number of 

### 5.52 Coemckntafvwaml samples, and the assumed probability basisfor calculating the LTA from the WLA, and the most limiting LTA, hasdifferent effects on the derived limits depending upon the selection made for each. To help illustrate the combined effect ofthese factors, Figure 5-8 Useofthe statistical method ofpermit limit derivation requires an estimate of the CV ofthe distribution of the daily measurements of

### the parameter after the plant complies with the requirements.

Table 5-3. Multipliers for Calculating Maximum Daily Permit Limits From Average Monthly Permit Limits

To obtain the maximum daily permit limit (MDL) for a bioconcentratable pollutant, multiply the average monthly permit limit (AML) (the wasteload allocation) by the appropriate value inthe following table. Eachvalue in the table isthe ratio ofthe MDL to the AML ascalculated by the followinq relationship derived from Step 4 ofthe statistically based permit limit calculation procedure. MDL = exp [z,o -0.502] AML exp [zaan -0.50n2] where un2= In(CV2/n + 1) o2 = In(CV2+1) CV = the coefficient ofvariation ofthe effluent concentration n = the number of samples per month
Zm= the percentile exceedance probability for the MDL za = the percentile exceedance probability for the AML.

Ratio Between Maximum Daily and Average Monthly Permit Limits Maximum =99th percentile Maximum =99th percentile Average =95th percentile Average =99th percentile

cv n=l n=2 n=4 n=a n=30 n=l n=2 n=4 n=8
0.1 1.07 0.2 1.14 0.3 1.22 0.4 1.30 0.5 1.38 0.6 1.46 0.7 1.54 0.8 1.61 0.9 1.69 1.0 1.76 1.1 1.83 1.2 1.90 1.3 1.97 1.4 2.03 1.5 2.09 1.6 2.15 1.7 2.21 1.8 2.27 1.9 2.32 2.0 2.37 .13 .2s .37 so .622 .73 .a4 1.94 2.03 2.11 2.18 2.25 2.31 2.37 2.42 2.42 2.52 2.56 2.60 2.64 .oo 1.16 1.18

.oo 1.22 1 .oo 1.33 1.39

.oo 1.46 1.00 1.so 1.60

.oo 1.74 / 1 .oo 1.67

.oo 1.82 2.02 - 1.00

.oo 1.84 2.04 2.32 I 1.OO 2.01 2.2s 2.62 1.00 2.16 2.45 2.91 1 .oo 2.29 2.64 3.19 1.oO 2.41 2.81 3.45 , 1 .oo 2.52 2.96 3.70 1.00 2.62 3.09 3.93 , 1 .oo 2.70 3.20 4.13 1.00 2.77 3.30 4.31 1 .oo 2.83 3.39 4.47 2.89 3.46 4.62 2.89 3.46 4.62 2.98 3.57 4.85 3.01 3.61 4.94 3.05 3.65 5.02 1.07

1.3s 1.12

1.84 1.16 1.13

2.46 1.24

1.34 1.32 1.19

1.83 1.36

2.46 1.49 1.24

1.33 1.46

1.a2 2.46 1.66 I.2a

1.32 1.56

1.80 1.81 1.31

2.45 1.64

1.31 1.9s 1.34

1.78 1.71

2.43 2.08

1.30 1.3s 1.76

1.76 2.19

2.41 1.36 1.80 2.27 1.37 1.83 2.34 1.37 1.a4 2.39 1.36 1.85 2.43 1.36 1.85 2.45

3.07 3.67 5.09 1 .oo 1.29 1.74 2.38 n=30 j \ 1.20 1 1.43 , 1.67 ’ 1.92 2.18 2.43 / 2.67 1 2.89 1 3.09 3.27 I 3.43 i 3.56 1 3.68 ; 3.77 I 3.84 3.90 3.94 3.97 j 3.99 1 4.00 (

10699% ProbabdMy Basrs ,

0.5 1.0 Coefficient of Variation 1.5 2.0

Figure S-6. Maximum Daily Permit Limit asa Function of the

1

0.6

!i 2
zi 06

z
.s 2 0.4

02

0 Coefficient of Variation

10 20 Number of Samples Per Month 30
Figure S-7. Relationship Between Average Monthly Permit Limits and Number of Samples Per Month

Ifvariability ismostly related to production, current data may be used to estimate the CV. Iffuture variability isexpected to be substantially different, the CV must be estimated. Discharges of toxic pollutants are generally more variable than discharges of conventional pollutants. Itisimportant to usethe best estimate of the CVthat can be reasonably achieved. Asexplained inChapter 3, EPA’sreview ofthe uncertainty associated with effluent variability suggests that a minimum of 10 samples isneeded to reasonably quantify the CV.
One concern with respect to using an appropriate CV in the statistical limit derivation procedures is that CVs of regulated systems may be quite different from nonregulated systems. In other words, after permit limits are in place and the permittee is operating to achieve the requisite limits, the variability associated with the parameter ofconcern may change considerably. Where the permit writer has reason to believe that the CV of the regulated system may behave differently from the nonregulated system (e.g., where changes in the treatment facility are planned), information concerning effluent concentration means and variability can be obtained from effluent guideline documents for individual chemical parameters. Variability associated with effluent levels of both individual chemicals and whole effluent toxicity is difficult to predict for any individual situation. However, it is important to recognize that failure to assign any CVto an individual toxicant orthe parameter toxicity involves an implicit assumption that there isno effluent variability present. Based upon analyses of awide variety of data from various types of plants, EPArecommends avalue of 0.6 as a default CV, if the regulatory authority does not have more accurate information on the CVfor the pollutant or pollutant parameter. Permit limits are usually not extremely sensitive to small changes inthe 0’. Thevalue of0.6 istypical ofthe range of variability of effluents measured by EPA (see Appendix A) and represents a reasonable degree of relative variability. However, wherever possible, it is recommended that data on effluent variability for the pollutant of concern be collected to define a CV rather than selecting adefault value.


### 5.53 Nmbef ofsamples The statistically based method for permit limit derivation results in an MDL that does not depend on monitoring frequency. However, the AML decreases asthe monitoring frequency increases, and agreater number for “n“ isinserted inthe relevant equations. Some permit writers are concerned with this outcome because facilities with more frequent sampling requirements appear to receive more stringent permit limits than those with lessfrequent monthly sampling requirements.
The AML decreases asthe number of monthly samples increases because an average of 10 samples, for example, iscloser to the LTA than an average based on 4 samples. This phenomenon makes AMLs based on 10 samples appear to be more stringent than the monthly limit based on 4 samples. However, the stringency ofthese procedures isconstant across monitoring frequencies because the probability basis and the targeted LTA performance are the same regardless of the number of samples taken. Thus, apermittee performing according to the LTAand variability associated with the wasteload allocation will, in fact, meet either ofthese AMLswhen taking the corresponding number ofmonthly samples.
Forwater quality-based permitting, effluent quality isdetermined bythe underlying distribution ofdaily values, which isdetermined by the LTAassociated with aparticular WLA and by the CVofthe effluent concentrations. Increasing or decreasing monitoring frequency does not affect this underlying distribution or treatment performance, which should, at a minimum, be targeted to comply with the values dictated by the WLA. Therefore, it is recommended that the actual planned frequency of monitoring normally be used to determine the value of nfor calculating the AML. However, in situations where monitoring frequency isonce per month or less,ahigher value for n must be assumed for AML derivation purposes. This is particularly applicable for addressing situations such aswhere asingle criterion isapplied atthe end ofthe pipe and asingle monthly sample

107-.-

3

2.5

2

1.5

1

0.5 a. LTA at 95% Probability Basis AML at 99% Probability Basis

0.5 1.o 1.5 2.0 Coefficient of Variation

3.5 - c. LTA at 95% Probabllity Basis

3- AML at 95% Probabllity Basis

s 6 2.5 - 2

; 2-
E 3 1.5- & a J 5 l0.5 - / n=30
0 “““‘I”“J1’-“’

0.0 0.5 1.o 1.5 2.0 Coefficient of Variation 3.5 b. LTA at 99% Probability Basis AML at 95% Probability Basls



### n=l



## 0”““““““““”

0.0 0.5 1.0 1.5 Coefficient of Variation 2.0



# -.-

^I d. LTA at 99% Probability Basis AML at 99% Probability Basis

0”““““““““”

0.0 0.5 1.0 1.5 Coefficient of Variation

Figure 5-8. Effect of Coefficient of Variation on Average Monthly Limits 2.0

1088. LTA at 9f

o”“““l”““““‘j

0.0 0.5 1.o 1.5 2.0 Coefficient of Variation

c. LTA 

### at 95% Probabiilty Basis 3 MDL at 95% Probablllty Basls

2.5

0.5 1.0 1.5 Coefficient of Variation 3.5

3- b. LTA at 99% Probability Basis MDL at 95% Probability Basis

2.5-

2-

1.5

Ol”““I”““““‘IJ

0.0 0.5 1.o 1.5 2.0 Coeff bent of Variation

3.5

3

2.5

2



### t.5

1

0.5

0 d. LTA at 99% Probability Basis MDL at 99% Probabfllty Basis

0.0 0.5 1.0 I.5 Coefficient of Variation 2.0

Figure 5-9. Effect of Coefficient of Variation on Maximum Daily Limits

109

### -- -- -

iscontemplated for compliance monitoring purposes, or where monitoring frequency is only quarterly. In this case, both the average monthly and the MDL would exceed the criterion. (For example, for a CCC of 1.Ochronic toxic unit [TUJ applied asa WLAatthe end ofthe pipe, both the MDL and AML would be 1.6 TU,; assuming CV=O.6, n=l, and a99percent probability basis.) A discharger could thus comply with the permit limit but routinely exceed the criterion. Under these circumstances, the statistical procedure should be employed using an assumed number of samples of at least fm for the AML derivatlon.


### 5.5.4 ProQaQlllly nasls Selection ofthe probability basisfor useinthe equations in Boxes 5-l and 5-2 isapermitting authority decision necessary for establishing statistically derived permit limits. Where a permitting authority does not have specific guidance for the probability basis, EPA recommends the following:
Forcalculation ofthe LTAsfrom the WLAs(Box 5-2):

l Both acute and chronic WLA-.Ol probability (99th percentile level).
Forcalculation ofpermit limits from the most limiting LTA 1):

l MDL-.Ol probability basis(99th percentile level)

l AML--.05 probability basis (95th percentile level). (Box 5-

The probability levels for deriving permit limits have been used historically in connection with development ofthe effluent limits guidelines and have been upheld in legal challenges tothe guidelines [4). It is important to note that these levels are statistical probabilities used asthe basisfor developing limits. The goal in establishing these levels is to allow the regulatory agency to distinguish between adequately operated wastewater treatment plants with normal variability from poorly operated treatment plants and to protect water quality criteria.
The level for the calculation of the LTAfrom the WLA is based upon EPA’s interpretation of the steady state model used to develop the WI-A. EPAconsiders the WLAto produce an effluent condition that should never be exceeded whenever the critical design conditions occur. To characterize this effluent condition, EPAusesthe 99th percentile concentration from the upper tail of the effluent probabilistic distribution curve. The selection ofthis value isone which can have asignificant influence on the level of conservatism in the permit limits. Permit authorities should consider 

### Figures5-8 and 5-9 to understand the effect ofthis decision along with other decisions on the AMls and MDLs.



## 5.6 PERMK GOCUMENTATION

The fact sheet and supporting documentation accompanying the permit must clearly explain the basis and the rationale for the permit limits. When the permit isin the draft stage, the supporting documentation will serveto explain the rationale and assumptions used in deriving the limits to the permittee and the general public in order to allow public comment on the draft permit. When the permit is issued, the administrative record for the facility (particularly the fact sheet) will be the primary support for defending the permit in administrative appeals including evidentiary hearings. This information also will serve to alert compliance/enforcement personnel to any special considerations that were addressed at the time of permit issuance. In addition, the accompanying documentation will be extremely important during permit reissuance and will assistthe permit writer indeveloping a revised permit.
In 40 CFRPart 124.56, afact sheet containing “[a]ny calculations or other necessary explanation of the derivation of specific effluent limitations” for many draft permits isrequired. Accordingly, the WlAs along with the required LTA and CV used and the calculations deriving them must be included or referenced in the fact sheet. The permit limit derivation method used must also be explained in the permit documentation. Where a permitting authority develops astandardized and simplified method for permit limit development asdiscussed in Section 5.4.2, the permitting authority may not need to document all of the underlying assumptions in the fact sheet, provided that the fact sheet refer

### encesa written permit limit development protocol. Any other guidance used must also be cited.



## 5.7 EXPRESSHi LIMITS AND DEVELOPING MONlTORING REQUIREMENT!3

Limits must beexpressed clearly inthe NPDESpermit sothat they clearly are enforceable and unambiguous. Chapter 6 discusses compliance monitoring and enforcement problems that can result from improperly expressed limits. All limits, both chemicalspecific and whole effluent, should appear in Part 1ofthe permit. Special considerations in the use of both chemical-specific and whole effluent toxicity limits are discussed below.


### 5.7.1 Atmdawd EftbtmtLlmtb Mass-based effluent limits are required by NPDES regulations at 40 CFR122.450. The regulation requires that all pollutants limited in NPDES permits have limits, standards, or prohibitions expressed in terms of masswith three exceptions, including one for pollutants that cannot be expressed appropriately by mass. Examples of such pollutants are pH, temperature, radiation, and whole effluent toxicity. Mass limitations in terms of pounds per day or kilograms per day can be calculated for all chemicalspecific toxics such aschlorine or chromium. Mass-based limits should be calculated using concentration limits at critical flows. Forexample, apermit limit of 10 mg/l ofcadmium discharged at an average rate of 1million gallons per day also would contain a limit of 38 kilograms/day of cadmium.
Mass-based limits are particularly important for control of bioconcentratable pollutants. Concentration-based limits will not adequately control discharges of these pollutants if the effluent concentrations are below detection levels. For these pollutants, controlling mass loadings to the receiving water is critical for preventing adverse environmental impacts. However, mass-based effluent limits atone may not assure attainment of water quality standards in waters with low dilution. In

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