UNITED STATES ENVIRONMENTAL PROTECTION AGENCY REGION 10 1200 Sixth Avenue, Suite 900 Seattle, WA 98101-3140

OFFICE OF WATER AND WATERSHEDS 

### November 6, 2015
Don Essig Idaho Department ofEnvironmental Quality 1410N. Hilton Boise, Idaho 83706 RE: EPA Comments on Idaho's Revised Human Health Toxic Criteria, Proposed Rule, Docket No. 58-0102-1201
Dear Don: The EPA appreciates the opportunity to provide comments to the Idaho Department of Environmental Quality (DEQ) on its proposed updated humanhealth ambient water quality criteria, which were published for public comment on October 7, 2015. The enclosed comments reflect many ofthe issues the EPA identified in ourprevious comment letters to DEQ and, in some instances, provide additional clarification. The EPA continues to recognize the challenging work undertaken thus far in revising Idaho's human health criteria. The EPA commends Idaho for using state ofthe art survey methodology to characterize current fish consumptionrates for the general population and anglers in Idaho. Given the reiDJlatory importance ofthese survey results, EPA strongly recommended that DEQ have the results peer reviewed byindividuals with the necessary expertise, and address peerreview concerns priorto fully incorporating this work into a regulatory context. EPA understands that DEQhas decided to conduct a peerreview and is supportive ofthat effort. The EPA also supports DEQ's decision to incorporate many ofthe EPA's latest scientific and policyrecommendations consistent with the EPA's 2015 updates to its 304(a) national human health criteriarecommendations. Atthe same time, the EPA remains concerned about some of DEQ'sproposed decisions in deriving human health criteria. In particular, the EPA is concerned with DEQ's approach to calculating its fish consumption rate because DEQ has not adequately demonstrated how criteria derived using the proposed fish consumption rate would be scientifically**defensible~** 

### would beprotective ofdesignated uses in Idaho (as informedbyreserved rights oftribal consumers), and would ensure the attainment and maintenance ofwater quality standards in downstream waters in Oregon and Washington.

### The EPA is available to further discuss our comments and weremain committed to providing assistance as DEQ develops the final rule. Ifyou have a ny questions, please feel free to contact me or Lisa Macchio at (206) 553

- 1834

.

Enclosures Sincerely,

# ~ Angela Chung, Manager Water Quality Standards Unit

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### EPA Comments on Idaho Department ofEnvironmental Quality's (DEQ) October7, 2015 Proposed Rule Revisions to Idaho's Human Health Criteriafor Toxics Docket No. 58-0102-1201 November 6, 2015 The Idaho Department ofEnvironmental Quality (DEQ) provided proposed new and revised surface water quality standards (WQS) found at IDAPA 58-0102-1201 to the public for review and comment on October 7, 2015.1 The EPA reviewed the state's proposed rule and associated documents and provides the following comments for DEQ's consideration. The comments are organized as follows: A. Fish Consumption Rate (FCR) 1. DEQ's Fish Consumption Survey Analysis and Results 2. Exclusion ofMarket Fish (Other than Rainbow Trout) 3. Exclusion ofAnadromous Fish · 4. Tribal Reserved Fishing Rights B. Other Input Variables 1. CancerRisk Level 2. Relative Source Contribution (RSC) 3. BioaccumulationFactor (BAF) 4. BodyWeight and Drinking Water Intake 5. ToxicityFactors: Reference Doses (RIDs) and Cancer Slope Factors (CSFs) C. Pollutant Scope D. Use ofProbabilistic Risk Assessment E. Downstream Waters Protection F. Specific Comments on DEQ's Proposed Rule Language Please note that the EPA's positions described in the comments below, regarding the state's proposed WQS, are preliminary in nature and do not constitute an approval ordisapproval bythe EPA under the Clean WaterAct (CWA) Section 303( c). Approval and/or disapproval decisions will bemadebythe EPA following adoption ofthe new and revised standards bythe state of Idaho and submittal ofrevisions to the EPA. In 

### addition, the EPA's comments do not constitute, and are not intended to be, an Administrator determination under CWA Section 303(c)(4)(B). 

### A. Fish Consumption Rate (FCR) As the EPAhas long acknowledged, it remains ourpractice to encourage states and authorized tribes to make appropriate adjustments to reflect local conditions affecting fish consumption.2 

### Thus far, Idaho has not yetpresented the EPA with a rationale that is adequate to establish that Idaho'sproposed FCR is appropriate and will lead to criteria sufficient to protect Idaho's CWA Section 101(a)(2) uses (e.g., Primary and Secondary Contact Recreation, IDAPA 58.01.02.100.02(a)&(b)), as required under40 CFR 131.11. While reserving finaljudgment on

1DEQ, Water Quality DocketNo. 58-0102-1201- ProposedRule, http://www.deg.idaho.gov/58-0102-1201. 2 USEPA. 2000. Methodology for Deriving Ambient Water Quality Criteria for the Protection ofHumanHealth. U.S. Environmental Protection Agency, Office ofWater, Washington, D.C. EPA-822-B-00-004. http://www.epa.gov/waterscience/criterialhumanhealth/method/complete.pdf.

### this issue until wereceive Idaho's final submission and supportingrationale, we emphasizethat Idaho's approach currently appears to beinconsistent with the CWA and its implementing regulations. We outline our concerns in more detail below, and recommend that Idaho modifyits approach consistent with the comments below. 

### 1. DEQ's Fish Consumption SurveyAnalysis andResults The EPA contracted with Westat, a well-known statistical consulting firm, to review DEQ's fish consumption surveyresults as reported inthe Fish Consumption Surveyreport preparedby Northwest Research Group. 3 

### Westat identified a number ofissues that DEQ should review (see attached memoranda from Westat), and EPA is available to discuss this information further. For example, Westat determined that the frequency offish consumption declined overthe seven day recall period. DEQ did not account for this trend, which couldresult in anunderestimation of fish consumption. As previouslynoted, itis important for DEQ's fish consumption surveyresults to bepeerreviewed byindividuals with the necessary expertise. TheWestatreview provides information that DEQ should consider along with the results ofits peerreview. Inparticular, 

### it is important.that the National Cancer Institute (NCI) analysis, which involves many assumptions and employs statistical methodology not generally accessible to the layperson, be adequately reviewed. In addition, it is important that DEQ's final peerreview findings bereadily available and distributed to support the credibility ofDEQ's surveyresults. 

### 2. MarketFish (Other than Rainbow Trout) CWA Section 303(c)(2)(A) requires that WQS protect "publichealth orwelfare, enhancethe quality ofwater and serve thepurposes of[theAct]." CWA Section 10l(a)(2) establishes as a national goal "waterquality which provides for the protection and propagation offish, shellfish, and wildlife and provides for recreation in and on the water [wherever attainable]." The EPA has previously interpreted the "fishable" language in Section 10l(a)(2) to refer not onlyto protecting water quality so the fish and shellfish thrive, but also so that when caught theycanbe safely eatenbyhumans. Thus, in orderto be consistent with Section 10l(a)(2), the applicable criteria for such "fishable" designateduses mustnot.onlyprotect the aquatic organisms themselves but also protecthuman health through consumption offish and shellfish.4


### The EPA'srecommended 304(a) water quality criteriato protecthumanhealth (andthe EPA's accompanying risk assessment methodologies) reflect this longstanding conclusion about the CW A: consumers offish and shellfish are to be assured that ifcriteria are metin a waterbody designated with the uses specified in Section lOl(a) ofthe CWA, then that means they can safely eat fish and shellfish drawn from that waterbody.5

### Thus, the EPA has consistentlyimplemented the CW A to ensure that the total rate ofconsumption offish and shellfish from inland, estuarine, and near-coastal waters reflects the consumption rates that are characteristic ofthepopulation of concern. In otherwords, the EPA expects that the standards will be set such thatresidents can safely consume from local waters the amount offish they would normally consume from all

3Northwest Research Group, Idaho Fish Consumption Survey. August 25,2015. 4 EPA's interpretation ofthe CWA is consistent withyears ofpastpractice. As evidence, see memorandum from Geoffrey H. Grubbs andRobert H. Wayland (October2000) posted at htto://water.epa.gov/scitech/swguidance/standards/uploadi2000 I0 31 standards shellfish.pdf 5 See discussion inRevisions to theMethodology forDerivingAmbient Water Quality Criteria for theProtection of Human Health, 65 Fed. Reg. 66465 (2000). · 

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### inland and near shore waters. The EPA recognizes that consumers offish and shellfish might not belimiting their consumption offish and shellfish to those that were sourced from their own state's fishable waters. However, the relevant objective is to assure that they can do so without concern for theirhealth. Idaho's approach is to exclude from the FCR the fraction ofthe consumption offreshwater and estuarine fish and shellfish that is currently associated with fish originating from waters outside ofIdaho.6 

### Idahojustifies its approach onthe grounds that Idaho lacks regulatory authority over fish caught outside ofits borders. Based on the information and rationale EPA has received from Idaho to date, we note the following reasons why Idaho'sjustification for this approach is not scientifically sound:

• Thepurpose ofincluding consumption from waters outside ofIdaho's borders in the FCR is not to support any purported regulation ofsuch waters by Idaho. Rather, the purpose of includingthis fish consumption in the FCR is so that a determination that a particular Idaho waterbody is "fishable" will result in adequate health protection for Idahoans should they consume, from local waters, the amount offishthey would normally consume from all inland and near shore waters. • The approach ofexcluding "market fish" appears to assume that there is no exposure to pollutants from fish that were sourced outside ofIdaho. This is because the full allowance for acceptable pollutant levels is given exclusively to local state waters. Considerifevery state took this approach. For a non-carcinogenic pollutant with a specified Reference Dose, the criteria development equation would allocate this full dose to fish originating from the individual state. Ifa person then consumes overall25 grams/day (g/day) offish, comprised of5 g/day each from 5 different states (and each state set a state-specific consumptionrate of5 g/day), then the consumer could potentiallyreceive five times the acceptable pollutant dose. 

### 3. Anadromous Fish The EPA recognizes that Idaho has included steelhead, an anadromous species, in the calculation ofits FCR. However, the EPA continues to have concerns with DEQ's proposed policy decision to exclude all other anadromous fish from the FCR, and recommends that DEQ either include all other anadromous fish in the FCR orprovide additional demonstration ofhow criteria derived using a lower FCR that excludes anadromous fish will protect downstream shared waters in the Columbia Riverbasin and protect the tribal populations exercising their treaty-reserved rights (see comments below regarding consideration oftribal reserved fishing rights). 7


### While the EPA's 304(a) recommended criteria account for exposures to non-carcinogens and nonlinear carcinogens in anadromous fish using the relative source contribution (RSC), the EPA supports and recommends that states include anadromous fish in the FCR when there is credible and compelling evidence ofsignificant consumption ofanadromous fish. For example, Oregon and Washington chose to include salmon in the FCRused to derive human health criteria due to,

6 Idaho makes one exception to this rule, withrainbow trout, on the grounds that the majority ofthe rainbow trout in the market comes from Idaho aquaculture facilities. 7 EPA reference to anadromous fish inthis letter refers to all other anadromous fish except steelhead. 

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### amongst otherreasons, the large amounts ofsalmon consumedbytribes, thevariation in individual market basketpreferences (i.e., the types offishthatpeople purchase and consume), and uncertainties in the sources ofsalmon contaminantbodyburdens from inland and near shore waters (e.g., salmonresiding inPuget Sound). The EPA approved Oregon's humanhealth criteriain 2011. Similarly, the EPA supports Washington's decision to develop humanhealth criteriausing a FCRthat includes anadromous fish consumption. The EPA also has reviewedrecent workrelated to salmon contaminant acquisition from near coastal waters ofthe Pacific Northwest and recommends that DEQ.also consider this available information. Forexample, theresearch conducted by Sandra O'Neill, James West, David Herman, and Gina Yitalo provides evidencethat certain Pacific Northwest salmon species, most notably chinook and coho, acquire organicpollutants from n.ear coastal marine waters. 8 

### O'Neill et al. assayed salmon and herring for several classes ofpersistent organicpollutants (POPs). The POPs ofinterest includedpolybrominated diphenyl ethers (PBDEs), polychlorinatedbiphenyls (PCBs), hexachlorobenzene (HCB), and the insecticide DDT. An analysis ofthese POPs in herringpopulations identifieduniqueregionally-specificpatterns ofthese chemicals or "fingerprints," thus showingherring are acquiring contaminants from waters under CW A jurisdiction. Chinook salmonharvested from specific locations were found to have the same contaminant "fingerprints" as those exhibitedbyco-located herring samples, suggestingthat they are feeding onherringin nearcoastal waters. This workprovides evidencethat certain chinook salmon species are acquiring contaminants from near coastal waters ofWashington and Oregon, as well as California and British Columbia. Similarbutmore limited databy O'Neill et al. indicate that coho salmon, whichreside in coastal waters and have feeding preferences similarto chinook salmon, are also acquiring contaminants from waters under CW Ajurisdiction. 

### Inaddition, EPAhas communicated with Laurie Weitkamp and Peter Lawson from NOAA,9 

### who have stated that chinook (and likely coho) salmon from Idaho reside in near coastal waters offthe Oregon coast. Myers at al. 1998, analyzing coated wiretagrecovery, has concluded that Snake River Chinook salmonhave a coastal residence pattem. 10 

### O'Neill et al.'s work shows that resident chinook salmon from these waters haveregional contaminant fingerprints specific to this area. Given the contaminant fingerprint correlationbetweenherring and coastal resident salmon at all locations whereboth species were analyzed, itis verylikelythat coastal salmon originating in Idaho waters are acquiring contaminants from coastal waters under CW Ajurisdiction. EPArecognizes that salmon acquire most oftheirbody weight and, therefore, most oftheirbody burden ofhighlybioaccumulative contaminants during open-ocean feeding. However, it is

8 Ms. O'Neill and Mr. West are both with the Washington Department ofFish and Wildlife. 9 L. Weitkamp,personal communication 5/19/2015. P. Lawsonpersonal communication viaphone, May, 2015.Dr. Laurie Weitkamp has extensively examined recovery ofcoated wire tags (CWTs) from adult salmonharvested in marine waters. CWTs, inserted intojuvenile salmon in hatcheries, allowresearchers to determine the relationship between spawning locations and oceanranges ofvarious salmon species. Dr. PeterLawsonhas done genetic testing ofadult salmon in marine waters. Bymatching unique DNApatterns of juvenile and adult salmonids, researchers can determine where adult salmoncame from. 10 Myers K.W., K.Y. Aydin, R.V. Walker, S. Fowler, M.L. Dahlberg. 1996. Known Ocean Ranges ofStocks of Pacific Salmon and Steelhead, as ShownbyTagging Experiments, 1956-1995. Submitted to the NorthPacific Anadromous Fish Commission. Fisheries Research Institute. University ofWashington School ofFisheries. 

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### possible that salmon may acquire less bioaccumulative contaminants directly from water during theirreturn spawning migration as adults. 11 

### EPA consulted with Frank Gobas, a well-known expert inbioaccumulation and bioconcentration in aquatic food webs, to evaluate this issue and. prepare an analysis. 12 

### The analysis first involved the development ofcontaminant concentrations in salmon tissue that were associated with either a cancerrisk of 1in 1,000,000 or a non-cancerhazard quotient of 1. These risk-based concentrations assumed a fish consumption rate of 175 grams perdayby an 80 kilogram person. Next, bioconcentration modeling was performed to determine the water concentration that results in a salmon tissue concentration associated with the aforementioned risk-levels. 13 

### The model includes quantitative structure activityrelationship biotransformation ofchemicals and the impacts ofchanging lipid content associated with migration energy expenditure. 14•15 

### The model also accounts for the time dependent nature ofchemical uptake. This modeling utilized a range ofmigration times for spawning Idaho chinook and sockeye salmon associated with several harvest locations within Idaho. The longerthe migration time, the greaterthe opportunity for contaminants to bioconcentrate. Finally, ratios ofIdaho's proposed water quality criteriato modeled water concentrations were computed. Theresults showed, for example, toxicityratios of 10 orgreater for 13 chemicals with non-carcinogenic toxicity. In other words, for 13 non-carcinogenic chemicals, Idaho's proposed criteria could result in hazard quotients of 10 ormore for populations consuming Idaho returning salmon at a rate of 175 grams perday ormore. This far exceeds EPA'srecommendation oflimiting risks to non-carcinogens to a hazard quotient of 1 or less. Therefore, DEQ should consider these results. EPA has enclosed the analysis for your review and consideration (see attached spreadsheets). Idaho cites work byHope 2012, suggesting that salmon do not acquire contaminants from waters under CW Ajurisdiction, tojustifyexcluding anadromous species from the FCRused to develop DEQ'sproposed criteria. 16 

### The Hope study's conclusions are limitedbyits focus on PCBs and not on othertaxies, and the study does not consider salmon acquisition ofcontaminants from near coastal waters as demonstrated by 0 'Neill et al. Central to the modeling is the assumption that contaminant uptake occurs largely through diet. While this is true for PCBs, depending on a chemical's lipophilicity, direct uptake from water maybe a significant contributor to an organism'scontaminantbodyburden. 17 

### The Gobas work on contaminantbioconcentration in migrating adult Idaho salmon, described above, provides evidence that adult Idaho salmonmay acquire contaminants directly from the water column through their gills, in addition to dietary

11 Less bioaccumulative contaminants refer to contaminants with log octanol-waterpartition coefficients (log Kow) between two and four. 12 Dr. Gobas is with Simon Fraser University in Vancouver BC. 13 Lo eta. 2015, Environ Toxico1 Chern. 2015 Oct;34(10):2282-94 14 US EPAEPI SUITE v. 4.11 15 Debruyn et al. 2004, Environ Sci Technol. 2004 Dec 1;38(23):6217-24 16 Hope, B.K. 2012. "Acquisition ofPolychlorinated Biphenyls (PCBs) byPacific Chinook Salmon: An Exploration ofVarious Exposure Scenarios." Integrated Environmental Assessment and Management 8:553-562. Cited byDEQ in: Considerations in Deciding Which Fish to Include in Idaho's Fish Consumption Rate Policy Summary, State of Idaho Department ofEnvironmental Quality. 17 Qiao, P., A.P.C. Gobas, and A.P. Farell. 2000. "Relative Contributions ofAqueous and Dietary Uptake of Hydrophobic Chemicals to the BodyBurden in Juvenile Rainbow Trout." Archives ofEnvironmental Contamination and Toxicology 39:369-377. 

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### uptake. Finally, the Hope study also does not discuss different patterns ofcontaminantuptake associated with the complex life histories ofother salmonids, such as steelhead. In 

### conclusion, DEQ should consider the above-referenced scientific information when making its final decision on whether to include anadromous salmonids, otherthan steelhead, in calculating the FCR. The EPA remains concerned that Idaho's decision to exclude most anadromous salmonids results inhuman health criteriathat are not adequate to protect Idaho's primary and secondary contactrecreation uses. 18


### 4. TribalReserved Fishing Rights PerEPA's regulations at§ 13l.ll(a),water quality criteriamust contain sufficientparameters or constituents to protect the designated use, and for waters withmultiple use designations, the criteriamust support the most sensitive use. In

### determining whetherWQS comply withthe CW A and EPA's regulations, when setting criteriato support the most sensitive fishing designated use in Idaho, it is necessaryto consider other applicable laws, including federal treaties. In Idaho, certain tribes hold reserved rights to take fish for subsistencepurposes, includingtreaty-reserved rights to fish at all usual and accustomed fishing grounds and stations and inunoccupied lands of the United States, which in combination appear to cover the majority ofwaters under state jurisdiction. Many areas where reserved rights are exercised cannotbedirectlyprotected orregulated bythe tribal governments and, therefore, the responsibility falls to the state and federal governments to ensure theirprotection. 19 

### In orderto effectuate and harmonize these reserved rights with the CW A, such rights appropriately must be considered when determining which criteria are necessary to adequately protect Idaho's waters used for consumption offish (designated as Primary or Secondary Contact Recreation, IDAPA 58.01.02.100.02(a)&(b)). Protecting Idaho's fishing designated uses necessitates protecting the population exercising those uses. Where a population exercising suchuses has a legally**protecte~** 

### right to do so under federal law such as a treaty, the criteriaprotecting suchuses mustbe consistent with suchright. Thus, in orderto protect the applicable fishing designated uses in areas where such rights apply, as informedbythe treaty-reserved right to continue legallyprotected culturally important subsistence fishing practices, the state must consider the tribal population exercisingtheir reserved fishing rights in Idaho as the target general population for the purposes ofderiving criteria that will protect the subsistence fishing use and allow the tribes to harvest and consume fish consistent with theirreserved rights. Thedataused to determine the FCR are critical to deriving criteria that will protect the subsistence fishing use. The data used to determine a FCR mustreasonablyrepresent tribal subsistence consumers' practices that reflect consumption unsuppressed byfish availability or

18AsDEQ has acknowledged, "ifanadromous species data are omitted from the data set, it is possible that the resulting criteria maynotbe adequatelyprotective ofIdahoans who eat salmon, steelhead, orother anadromous fish." Idaho Fish Consumption Rate andHuman Health Water Quality Criteria; Discussion Paper#5: Anadromous Fish, pg. 4, available athttp://www.deq.idaho.gov/media/1117748/58-0102-1201-discussion-paper5.pdf. 19 Note that for formal and informal reservation lands, eligible tribes can obtaintreatment in a similarmanner as a state {TAS) status and set their own WQS under the CW A, including humanhealth criteria.



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### concerns about the safety ofavailable fish. Deriving criteriausing an unsuppressed FCRfurthers the restoration goals ofthe CWA, and ensures protection ofhumanhealth as pollutant levels decrease, fish habitats are restored, and fish availability increases. Ifsufficient dataregarding unsuppressed fish consumption levels are unavailable, consultation with tribes is important in deciding which fish consumption data should beused. With these principles in mind, the EPA has concerns with whether DEQ's decision to calculate the FCRbased only on current consumption ofIdaho fish, and to use a mean FCR for high consumingpopulations, will adequatelyprotect the treaty-reserved subsistence fishing use. First, in calculating the FCR, DEQhas not considered suppression, specifically suppressed consumption amongst tribal populations in Idaho with reserved rights to fish for their subsistence. Current average FCRs for the Nez Perce and Shoshone Bannock tribes are below heritage rates documented for both ofthese tribes, as well as heritage rates for the Kootenai and Coeur d'Alene tribes, suggestingthat current tribal consumption rates couldbe suppressed.20 

### Second, given that tribal consumption rates are likely suppressed, DEQ has not provided adequatejustification for how a rate based on the mean FCR for the tribal target general population will adequately protect tribal fish consumers exercisingtheirtreaty-reservedrights, including those whose consumption is not suppressed. Finally, as discussed in greater detail above, the omission ofanadromous species from the FCR mayresult in criteria that are not adequatelyprotective ofIdaho's designated uses as informed bythe reserved fishing rights of tribal consumers. 21 

### Based on local conditions in Idaho, it is particularly appropriate to include anadromous species in the FCR, because it is well documented that a large proportion offish consumption for the tribal target population to beprotected consists ofanadromous species, such as salmon.22 

### Accordingly, EPA recommends that DEQ select a FCR that reflects the tribal subsistence consumers' unsuppressed fish consumption, including consumption ofanadromous fish. Ifsuch data areunavailable atthis time, the EPA recommends using an upperpercentile ofconsumeronlydata to account for uncertainty in the unsuppressed consumption rates oftribal consumers within the state and to help**e~sure** 

### that the resulting criteriaprotect the tribal target general

20 Polissar, N.L, AI Salisbury, C. Ridolfi, K. Callahan, M. Neradilek, D.S. Hippe,A Fish Consumption Survey of the Nez Perce Tribe Volumes I-III. Seattle, WA: The Mountain-Whisper-Light Statistics (2015); Polissar, N.L, AI Salisbury, C. Ridolfi, K. Callahan, M. Neradilek, D.S. Hippe,A Fish Consumption Survey of the Shoshone-Bannock Tribes Volumes I-III. Seattle, WA: The Mountain-Whisper-Light Statistics (2015); Ridolfi Inc., Heritage Fish Consumption Rates of theKootenai Tribe (November 17, 2014); Ridolfi Inc., Heritage Fish Consumption Rates of the Coeur d'Alene Tribe (July 

### 19, 2015). 21 AsDEQ has acknowledged, "ifanadromous species data are omitted from the data set, it is possible that the resulting criteria maynotbe adequatelyprotective ofIdahoans who eat salmon, steelhead, or other anadromous fish" and "the complexity ofPacific Northwest fish consumption and its high inclusion ofthese fish species in the diets of all means that ignoring anadromous fish would be less protective ofthose within Idaho who enjoyconsuming these types offish."Idaho Fish Consumption Rate andHuman Health Water Quality Criteria; Discussion Paper#5: AnadromousFish, pg. 4 & 5, available athttp://www.deq.idaho.gov/media/1117748/58-0102-120l-discussionpaper5.pdf. 22 "Including marine fish in the fish consumption rate maybe particularly appropriate ifa large proportion offish consumption for the population to be protected consists ofmarine fish (such as salmon) and this exposure is clearly documented." USEPA, Human Health Ambient Water Quality Criteria andFish Consumption Rates: Frequently AskedQuestions, pg 5, available at http://water.epa.gov/scitech/swguidance/standards/criteria/health/methodology/upload/hhfaqs.pdf. 

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### population exercising their treaty-reserved rights. Additionally, government-to-government communications with affected tribes could inform, among otherthings, which fish consumption data shouldbeused byDEQ. · 

### B. Idaho's OtherProposed Human Health Criteria Inputs 1. CancerRisk Level The EPA supports DEQ'sproposed policy decision to retain its 10-6 cancer risk level to derive humanhealth criteria. 

### 2. Relative Source Contribution (RSC) In

### June 2015, the EPApublished final updated ambient water quality criteriarecommendations for the protection ofhuman health for 94 chemical pollutants.23 

### Theseupdated recommendations reflect the latest scientific information and EPA policies, includingupdatedbodyweight, drinking water consumption rate, FCR, bioaccumulation factors, health toxicity values, and relative source contributions (RSCs). The EPA supports DEQ'sproposed approach to use RSC values specified in EPA's 2015 final304(a) humanhealth criteriarecommendations. 

### 3. Bioaccumulation Factors (BAFs) As stated inDEQ'sTechnical Support Document (TSD) for the humanhealth criteria, DEQ created an Idaho-specific BAF weighting equation using Idaho fish consumption survey data and stated that the approach theyused was similar to the framework that EPAused to derive the BAF weighting in the EPA's 2015 final human health criteriarecommendations.24 

### According to the TSD, DEQ used food frequency data collected for the Idaho general population and dietary recall data for the tribal population. From these data, DEQ developed a trophic level weighted BAF usingthe following equation: (FCRru x BAFn2 

### +FCRru x BAFn.J 

### + FCRn4 x BAFTu) I 

### (FCRTu 

### +FCRTLJ 

### +FCRTu). This approach is appropriate and addresses the EPA'sprevious concern that Idaho tribal populations consume larger amounts ofhigh trophic level fish relative to the U.S. general population. However, the EPA recommends that DEQ provide more information on the derivation ofthe trophic level specific FCRs used to compute weighted BAFs. 

### 4. Body Weight andDrinking Water Intake As discussed in the TSD, bodyweight estimates used in the calculation ofIdaho'sproposed humanhealth criteria are based onuse ofa bodyweight distribution DEQ developed from the general population data from DEQ's fish consumption survey. Usingthis data, a logarithmic distribution was developed for bodyweight for calculation ofProbabilistic Risk Assessment (PRA)-based proposed humanhealth criteria.25 

### EPA is supportive ofDEQ's approach to using

23 Final Updated Ambient Water QualityCriteria for the Protection ofHuman Health, (80 FR 36986, June 29, 2015). See also: USEPA, 2015. Final2015 Updated National Recommended Human Health Criteria. U.S. Environmental Protection Agency, Office ofWater, Washington, D.C. http://water.epa.gov/scitechlswguidance/standards/criteria/currentlhhfinal.cfm. 24 Idaho DepartmentofEnvironmental Quality. Idaho Human Health Criteria, Technical SupportDocument. October2015. 25 Ibid 

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### the Idaho local data for estimatingbodyweight and concurs that the bodyweight distribution was appropriately derived. As discussed in the TSD, DEQ developed drinking water intake estimates for the PRA-based calculation ofthe proposed human health criteriabased on-the National Health and Nutrition Examination Survey (NHANES) 2003-2006 data as presented in the EPA's Exposure Factors Handbook. A distribution was fit to the body-weight normalized drinking water intake values to ensure an appropriate correlation with bodyweight. This distribution was then used in the PRA approach and applied to both Idaho general and tribal populations.26 

### The EPA selected the 90th percentile ofthis distribution (2.4liters/day) to derive the EPA's 2015 final304(a) humanhealth criteriarecommendations. Although DEQ's approach to estimating drinking water intake differs from the EPA's, DEQ's drinking waterrate distribution has been_ appropriately derived. In addition, the correlationbetween drinking water ingestion rate and body weight was adequately addressed in DEQ's PRA analysis. However, DEQ should re-evaluate the correlation betweenbodyweight and fish consumptionrate using regression on log transformed fish consumption and bodyweight distributions (See enclosed Westat memoranda). 

### 5. Toxicity Factors (Reference Doses (RIDs) and CancerSlope Factors (CSFs)) The EPA supports DEQ's proposal to use RIDs and CSFs consistent with the EPA's 2015 final 304(a) humanhealth criteria recommendations or, in some cases, toxicity factors based onthe latest science. 

### C. Idaho's Proposed Pollutant Scope The EPA is supportive ofDEQ taking this opportunity to revise most ofits currently applicable human health criteria and to include additional human health criteria for pollutants with EPA 304(a) criteriarecommendations that Idaho had not previously adopted. DEQ is proposingto update or add criteria for 104 chemicals. As previouslynoted, the EPApublished updated final 304(a) recommended human health criteria for 94 pollutants inJune 2015. 

### D. Idaho's Use ofProbabilistic RiskAssessment (PRA) to Derive Human Health Criteria The EPA continues to question the fish consumption distribution that DEQ used in its PRA analysis (see the EPA's comments above regarding inclusion ofmarket and anadromous fish in developing a FCR). Use ofa FCR distribution that does not include consumption ofmarket and anadromous fish will result in PRA-based criteria that will produce fish- and water-based contaminant exposures that exceed acceptable levels. Additionally, DEQ's PRA for high fish consuming populations are derived using the assumption that, at the selected criteria, the mean ofthe hazard quotient distribution will equal one, and the mean ofthe risk distribution will equal 1 x 1 

## o-6• 

### EPA remains concerned with this approach. This approach will allow for a large fraction ofhigh fish consumers, including tribes with reserved fishing rights (see above discussion on tribal reserved fishing rights), to have exposures

26 Ibid 

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### that either exceed an acceptable dose (i.e., the reference dose) for noncarcinogens orexceed a· dose associated with a risk of 1 x 1 

## o-6 

### for carcinogens. Another concern is development ofan appropriate tribal fish consumption distribution for PRA. TheNational Cancer Institute (NCI) method cannotbeused to characterize consumption ofa particular grouping offish (e.g., fish caught in Idaho**water~)** 

### ifthe datanecessaryfor the method are not available. Idaho has used tribal Food Frequency Questionnaire (FFQ) and NCI data in an attempt to develop "NCI-like" estimates ofaverage tribal consumption offish caught in Idaho waters. As previously noted, DEQ should include market fish, including anadromous species, in the FCRused to set Idaho's AWQC. The EPA also has methodological concerns about using FFQ and NCI datato derive ''NCI-like" FCR statistics based onWestat's review ofthe PRA approach (see attached Westat memoranda). Thus, the EPA recommends that the NCI group 2 (i.e., anadromous, near coastal and inland fish and shellfish) FCR data for theNez Perce Tribebe used to develop statistics representing current fish consumption. 

### E. Idaho's Proposed Approach to Downstream Protection The EPA is encouragedby DEQ'sinclusion ofa downstream protection narrative criterion inthe proposedrule, following the language in EPA's "Templates forNarrative Downstream Protection Criteria in State Water Quality Standards" (EPApublicationNo. 820-F-14-002). However, the EPA'sProtection of Downstream Waters in Water Quality Standards: Frequently Asked Questions suggests that states consider a more tailored and specific narrative criterion and/or a numeric criterion in certain situations, such as when more stringent numeric criteria are inplace downstream and/or environmentaljusticeissues are relevant.27 

### As mentioned above, most ofIdaho's waters are inthe Columbia Riverbasin and are, therefore, upstream of Washington's and Oregon's portion ofthe Columbia River. The EPA strongly encourages DEQ to adopt numeric human health criteria (either in addition to orinstead ofa narrative criterion) that ensure the attainment and maintenance ofdownstream humanhealth water quality criteria, orto provide additional rationale detailinghow use ofa narrative downstream protection criterion in combination with Idaho's numeric humanhealth criteriawill ensure the attainment and maintenance ofdownstream human health criteria, consistent withthe EPA'sregulations at 40 CFR 131.10(b). 

### F. Other Specific Comments on Idaho's PreliminaryRule Language
Section 010. Definitions. 46. Harmonic Mean. EPA supports DEQ'sproposedrevisions to this definition. However, EPA continues to suggest DEQ consider including the following equation inthe definition for harmonic mean, as itprovides additional clarity: Q(harmonic) 

# = nj

# Lf= 1

## ~i

27 EPA. June 2014. Protection of Downstream Waters in Water Quality Standards: FrequentlyAsked Questions. http:/ /water.epa.gov/scitechlswguidance/standards/library/upload/downstream-faqs.pdf 

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### Section 210. Numeric Criteria for Toxic Substances for Waters Designated for Aquatic Life, Recreation, orDomestic Water Supply Use. 210.0l.a. Criteria for Toxic Substances. EPA supports DEQ'sproposed revisions to the application ofthe human health criteria for toxics for the protection ofconsumption ofwater and organisms such that these criteria apply only to primary and secondary contact recreation uses and no longer apply to aquatic life uses. Given that the provision in Idaho's water quality standards at Section 100.02 a. and b. states in part that secondary contact recreation mayinclude activities such as fishing, the application ofthe water and organisms humanhealth toxic criteria to onlyrecreation uses and not aquatic life is appropriate. With respect to DEQ'sproposed revision to the headings in the toxics criteriatable, specifically for the humanhealth criteria, EPA recommends DEQ retain the word "organisms" and not replace it with the word "fish." "Organisms" more closely represents the concept that consumption is meant to encompass more thanjust fish butrather fish, shellfish, and other aquatic life. 210.03. Applicability. DEQ has proposed clarifying languageregarding mixing zones as well as revising the low flow design conditions applicable to human health criteria. Consistent with the 2000 Human Health Methodology, DEQ has proposed to revise its regulations to require the harmonic mean flow beused to implement both carcinogen and noncarcinogen humanhealth criteria.28 

### EPA supports this proposed revision. 210.03.d.ii. This provisionprovides a frequency and duration for humanhealth criteriathat are not to be exceeded based on an annual harmonic mean. EPA understands DEQ is attempting to clarifythe frequency and duration for the state's human health criteria and is supportive ofthat effort. EPA's 304(a) recommendations for human health criteria are based on long-term average exposure over a lifetime (70 years). Idaho's proposed duration ofone year is protectivebecause it represents long-term orchronic exposure but within a reasonable timescale for the purposes of regularly assessing attainment ofthe criteria. However, the harmonic mean is an inappropriate measure ofcentral tendency in this context, because it is likelyto under-represent the presence of pollutants in ambient water. Harmonic means are an appropriate measure ofcentral tendency when evaluating rates with varying denominators, such as flows or speeds. However, for measures ofvarying mass pervolume, such as concentrations ofcontaminants in ambient water, the arithmetic (for skewed datasets) or the geometric mean is the more appropriate measure of central tendency. EPA recommends that DEQ delete reference to the harmonic mean and, instead, insert arithmetic mean. 210.05.a.iii. The proposed revisions update the reference from EPA's ACQUIRE database to ECOTOX database. EPA supports this revision. 210.05.b.ii. The EPA is concerned that this provision lacks specificity with regard to a fish consumption rate and the target population to beprotected that will beused to derive numeric humanhealth criteria in the future, when numeric criteria are not identified in the toxics table. It

28 FRVol65 No. 214. Pg. 66450. Revisions to the Methodology for Deriving Ambient Water Quality Criteria for the Protection ofHuman Health (2000). 

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### would seem reasonable to specify an appropriate fish consumptionrate as well as the target population and percentile ofthe target population that would beused to estimate a fish consumptionrate consistent withhow Idaho's numeric criteriain the table at Section 210 were derived. For example, the language inb.ii. refers to using a fish consumptionrate that is representative ofthe populationto beprotected. The EPA suggests DEQ include specific language identifyingthepopulationto beprotected consistent with EPA'sprevious comments. 284.04.b and c. DEQ combined the wording in 04.b. and c. and deleted any redundant language. Theserevisions are not substantive as they do not change where the criteria apply. The EPA supports the proposed revisions regarding the application ofthe site-specific criteria for the South Fork Coeurd'Alene River subbasin. 400.06 Intake Credits for Water Quality Based Effluent Limitations. This provisionrefers to the Idaho Pollutant Discharge Elimination System Program (IPDES) rules and is not a water quality standard. However, in EPA's October2, 2015letterfrom Michael Lidgard to PaulaWilson, EPA provided comments on IDAPA 58.01.25 regarding the proposed intake credit rule language as proposed in the IPDES rules. TheEPA is continuing to coordinate with DEQ's IPDES program and has recommended that, ifDEQ intends to adopt an intake creditprovision into the IPDES rules, it be consistent with the Great Lakes Initiative (GLI). Anotheroption is for DEQ to consider Oregon's intake creditprovisionrule language, as that language is most similarto the GLI and was approved by EPA.

12 

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To: From: Subject: An Employee-Owned Research Corporation 

# Memo

October 19, 2015 Greg Frey, SRA John Rogers, Rebecca Birch, and David Marker Review ofIdaho Fish Survey

Westat was requested by SRA and EPA to review three documents and a translation procedure, all related to the findings from the Idaho Fish Survey. Our comments are as follows. 1. Overall comments: In our comments, "fish" refers to fish and shellfish.
Itis notvery unclear howmany days ofdietary recall data were collected. First, the daily dietary recall questions were only answeredifquestion FFQ3 [did you eat fish in the last 7 days] is Yes. So someone who ate fish only on day 8 would be excluded from the dietary recall questions. It appears that 8 days ofdaily recall were reported for those who ate fish yesterday but only 7 days for those who did not eat fish yesterday. IfFCR24_1 [did you eat fish yesterday] is Yes, the questionnaire collects data about yesterday's fish consumption. Then the instructions for questions FCR7D_1_A through FCR7D_3_B distinguish between "excludingyesterday how many meals did you eat

... that included fish or seafood in the past 7 days"**~ooks** like 8 days total] iffish was eaten yesterday versus"

... in the past 7 days how many meals did you eat

..." and "Notincluding today, what was the most recent day ofthe week when you consumed

..." if fish was not eaten yesterday**~ooks** like 7 days total]. Given that the dietary recall data were collected only ifthe respondent said they ate fish in the past seven days, we think the fish consumption in the seven days prior to the call should be used when aggregating dietary recall data across multiple days, not 8 days. The definition ofconsumption events is unclear. Iftwo different types offish are consumed at a meal, the FFQ seems to count this as one consumption event. Is this one or two consumption events in the dietary recall? Is every snack a consumption event regardless ofsize or how many types offish were consumed? Frequency offish consumption was assessed using the FFQ and the multiple days ofdietary recall data. The report says "the total number ofconsumption events estimated**u~ing** the dietary recall questions is significantly lower than the total number ofconsumption events estimated using the food frequency questions" (page 81) but provides no data for comparison to quantify what-2- "significantly lower" means. At the same time the report notes that the reported frequency offish consumption drops as the days between the consumption event and the survey contactincreases (page 75). Might this indication ofrecall bias explain some ofthe difference? The report notes that there are differences between the portion size estimates from the FFQ and the average portion size estimates from the dietary recall. Interpretation ofthat difference is complicated by: 1) the skewed distribution ofthe amounts from the daily recalls; 2) how the respondent estimates long-term portion size; and 3) differences in what a portion means between the FFQ and dietary recall. Ifthe respondent provides an estimate ofthe median portion size (as opposed to the mean), the difference between the log-transformed portion sizes may be less significant, and more normally distributed.
Itis not clear how a."complete" survey was defined. Also the survey reportgives weighted sample sizes (is this weighted population estimate.scaled down to the sample size?). We would like to see unweighted sample sizes. Table 1 (page 10) in the IMS analysis report provides unweighted sample sizes. Howeve·r, it is still unclear concerning the number ofsubjects that were consumers versus non-consumers. In theory, usual fish intake can be estimated from 24-hour recalls ormultiple-day recalls (in this case 7 or 8 day recalls). However, ifthe best estimate ofusual fish intake is based on 24-hour recalls, then the decrease in the reported frequency offish consumptionwith increasing length of the recall period (days between the consumption event and the survey contact) indicates that the estimate based on multiple-day recalls will be biased low. Correcting this bias requires making some assumptions (such as logit(probability offish consumption) andlog( amount consumed per day) changes linearly with the length ofthe recall period). With a reasonable assumption, this bias can be correctedby 1) fitting a more complicatedversion ofthe NCI model that includes an adjustment; 2) scaling the estimated usual fish consumption from the NCI model up to adjust for the bias (applying a multiplicative factor, perhaps (probability offish consumption on Day 1)/(Probability offish consumption on any day in the recall period)); or, 3) using only the f1rst (yesterday) day ofdietary recall to estimate usual fish consumption. Usingjust the 24-hourrecall, ifseparate models are fit for anglers and non-anglers, the NCI model may not converge due to few respondents with two recalls, bothwith fish consumption. Scaling the outputwhen predicting data from several days may be the easiest option. The NCI·macro uses the NilvfiXED procedure. The weights in the NilvfiXED procedure are defined using the REPLICATE statement. The documentation for the REPLICATE statement states that "Only the last observation ofthe REPLICATE variable for each subject is used". Thus, the same weight is used for each recall within a person. The best weight to use is the weight for the respondent (used for the first recall). As a result, 1) the analysis file for the NI method should have the weight for the first recall on both the records for the first and second recall; and 2) the weight for the second recall defined by NRGis not used in the analysis.
In the IMS report, Table 1 (page 10) shows the sample sizes for anglers and non-anglers and the number ofrespondents used in the NCI model. Itis not completely clear why some cases were notincluded in the NCI model. Does the line labeled "Annual Fish Consumption Unavailable" correspond to those that did not eat fish in the last year (non-consumers)? There are 243 cases

### -3-

labeled "Recall Data Unavailable (i.e. Missing)". \Vhat does this mean? There were 

### 660 respondents that were**dropp~d** because various covariates were missing. \Vithout knowing specifics about the missing values, perhaps imputedvalues could be used ormissing values can be treated as a separate category ofthe categorical variables? How does the distribution ofthe demographic variables for those in the NCI model compare to the distribution for all fish consumers?



### 2. Idaho Fish Consumption Survey SUBMITIED TO: Idaho Department ofEnvironmental Quality SUBMITIED BY: Northwest Research Group, LLC www.nwresearchgroup.com DATE SUBMITIED: Final: August 25, 2015
\Ve are interested in identifying any survey design factors that might introduce any uncertainty or bias/loss ofaccuracy in results ofthe fish consumption survey. In addition to whatever the reviewers identify as a potential issue, we would specifically like comments on the topics listed below. 

### 2.1 Representativeness ofsample using a telephone interview. The methodology to collect data using a telephone interview using two frames (cell and landline) seems appropriate. According to the 2012 National Health Interview Survey only 2.7 percent of adults in Idaho are without a cell or land line phone. Those people will not be represented. While there may be some reason to think they have different fish consumption levels than others with otherwise similar demographics (since they are by definition living somewhat removed from society lives), there impact on overall estimates are likely to be small. 

### 2.2 Methodology used to selectland line and cell phone numbers and representativeness ofsample
The methodology to select land line and cell numbers appears to be appropriate. The resulting samples oftelephone numbers should be representative ofthe cell phone orlandline populations. See item 2.11.


### 2.3 Stratification ofsample based on Idaho health districts.
The stratification approach looks appropriate, trying to enforce geographic and gender representativeness in the sample minimizes variation in the weights.


### 2.4 Representation ofanglers and non-anglers and weighting They decided to use only the telephone landline and cell lists for sampling and classifying the anglers based on reported possession ofa fishing license. This approach appears to be reasonable. The number ofanglers estimated from the survey 

### (33°/o) differs somewhat from the number estimated by IDFW 

### (26°/o). Itis possible that anglers were more likely to respond to a survey on fish consumption then non-anglers. At the same time, the list from IDFW has some uncertainty in that two lists ofdifferent sizes were provided.

### -4-

2.5 Quotas for age, gender, and income and relation to representativeness ofthe sample
In general, enforcing the quotas helps to reduce the required effects ofweighting. However, quota sampling has been discouraged for decades in government surveys because it can introduce biases that are not necessarily accounted for through the weighting process. Inparticular, itresults in over-representing those who are easier to reach by telephone. Ofparticular interest in a fish consumption survey, those who spend a greater amount oftime away from home (including fishing) are harder to reach, and thus are underrepresented in a quota sample. Ifthey are reachable by cell phone this form ofbias may be reduced, but itis hard to know for sure. 2.6 Consideration ofrace and representativeness ofthe survey sample
The racial breakdown ofthe population is only reported as White Alone versus**Non-~te** (roughly 

### 5°lo). Race was notused for weighting. Since quotas were notused for race, the sample may notbe representative ofthe population racial distribution. A weighting adjustment based on race would improve the representativeness ofthe weighted sample with respect to race. See item 2_.11.
The proportion ofwhites in the sample is higher than in the State ofIdaho. Nationally, whites consume less fish than non-whites (EPA, 2014). Ifthe weighting were to include race it might improve the accuracy ofthe estimates.
2.7 Impact ofnotbeingable to interview 

### 5°lo ofcontacted households because of language issues. Obviously, this subpopulation will notbe represented in the survey results. To the extent that this subpopulation is similar to others with similar demographics, a weighting adjustment based on demographics might make the weighted sample more representative. They report that early analysis indicated no significant differences in consumption rates between English speaking Hispanic and non-Hispanic respondents. However, this does notmean that there will be no difference between English speaking and non-English speakingrespondents. They are assuming that English speaking Hispanics are more similar to non-English speaking Hispanics than they are to non-Hispanics in dietary behavior, which may ormay notbe true.
In particular, ifthe non-English speakers are Native Americans, their lack ofEnglish could be hypothesized to be correlated with following more traditional lifestyles, ones thatinvolve consumption ofmuch greater amounts offish. In such a case their exclusion 

### will underestimate the true fish consumption in Idaho.-5-



### 2.8 Quantifyingportion size: 2.8.1 Use ofcommon objects to describe portion size Ifthe common object is familiar to the study population, it is likely easier for respondents to report their portion size in relation to the object than to estimate weight (grams or ounces) or volume (cups or tablespoons), unless they cooked it themselves. They did qualitative research among the population ofinterest to assist them in selecting common objects to be used as portion size references.


### 2.8.2 Asking respondents to quantify portion size in ounces
Itis likely difficult for respondents to provide the amount offish they consumed in ounces, unless they prepared the fish. However, they tested the use ofp.ortion size estimation aids (PSEA) to assess ifusing PSEAs would improve reporting offish consumed in ounces. They report that the results showed saying the PSEA was equivalent to a specific number ofounces and asking respondents to then provide their consumption in ounces provided accurate estimates. This is the methodology they used. It seems reasonable and best available without pre-mailing (or directing to a website) portion size pictures like what are used in the ASA24.


### 2.8.3 Use ofa deck ofcards as the portion size estimation model According to their research, most people thought about a deck ofcards orpalm ofhand when estimating portion sizes and there was no difference in accuracy between these two PSEAs. They chose to go with a deck ofcards. This choice seems reasonable given the research fmdings and that hand sizes vary by age and gender and other factors. 

### 2.9 Use ofan 8 day recall period, (SEE: p 24, item 6 describingrecall issues for longer periods from qualitative research).
The use ofa single versus multiple-day dietary recall for assessing usual fish consumption depends on a combination ofbias and precision. The decrease in the reported frequency offish consumption with increasing length ofthe recall period (page 75) will contribute to increased bias as the number ofrecall days increases. The bias can be corrected in various ways (an adjustment factor, modifying the NCI model, orusing only the ftrst day ofdietary recall). The increasing imprecision ofthe respondent recall as the length ofthe recall period increases affects the precision ofthe estimates; but the NCI method can still be used to calculate those estimates if proper adjustments are made. As a result, increasing the recall period has diminishing benefit. \Y/e recommend either adjusting the estimates for bias associated with the longerrecall period or calculating the usual fish consumption from only the ftrst recall day. Disregarding this length bias, as was apparently done, can produce inaccurate estimates. Assuming that respondents had a difficult time recalling fish consumption events beyond a few days (like they report), an 8 day recall period probably underestimates usual fish consumption due to the likely lowered estimated probability ofconsumption (for those that were reported no consumption and may have forgotten a fish consumption event).-6-



### 2.10 Impact ofresponse rate on survey results Non-response contributes to possible bias and decreased precision ofthe survey estimates. NRG appeared to make reasonable efforts to increase or maintain response rates while collecting the data. Without independent estimates offish consumption for the non-respondents it is not. possible to truly assess the bias. A non-response adjustment to the weights can help to minimize the bias. An analysis offrequency and amount offish consumption as a function ofthe effort used to collect the data (such as number ofcontacts to get a completed survey response) can be used to approximate the possible bias due to non-response. The non-response adjustment (post stratification) provides minimal adjustment for non-response. We recommend**addi~onal** adjustments ofthe weights to account for different non-response rates for different demographic groups. NRG provided some adjustment ofthe weights forhealth region and gender; however did not provide more extensive adjustments for non-response (particularly with respect to an apparent imbalance in income) citing concerns for possible large weights in some health districts. While it is true that such adjustments may increase the variance, they willreduce the bias. In general this trade-offis worthwhile when the response rates are not high. We recommend additional non-response weight adjustments.


### 2.11 Weighting ofresults based on landvs. cell phones
The general approach to weighting the combined cell andlandline samples, as represented by BW _1, is reasonable. However some details ofthe implementation are unclear or appear incorrect, in particular: 1) On page 35 they define CP as the number ofcell phones butit appears to really be whether or not they have a cell phone used for making orreceiving phone calls (this is ok, but should be corrected in the documentation) 2) On page 35, the numbers for the universe counts (ULLand UCP) seem very implausible

....they must be larger. Ifthese are in error, then obviously the weights are wrong. 3) On page 35, the formula for B\V _1 is wrong (we assume itis just a typo, since the -1 should be an exponent) 4) They did not collect the number ofadults in the household and therefore made a "fix" based on the numberin the household; that is a potential source ofbias 5) The question they used to determine phone service (TEL on page 104) is not a standard one and might lead to some errors. Forexample, the cell phoneis based on personal use and the landline is household availability and the two are confused in this question. 6) The purpose and implementation ofthe adjustment in BW _2 on page 36 is unclear. Is the adjustment (BW _2) applied to all respondents in a health district or only the cell-phoneonly respondents? Itis not clear what some ofthe numbers in Table 12 are orwhere they came from. They appear to be household numbers; however the adjustment should be for adults; this may be a potential source ofbias. Based on the numbers in the last three columns ofTable 12, itlooks like the purpose ofBW _2 is to get the percentage ofcellonly households in the sample to equal the correspondingpercentage in the population; however, it is not clear how the equations for BW _2 and B\VFinal achieve that for the "Non\Vire-less Only" respondents.-7-



### 2.12 Implementation ofpost stratificationweighting
The post stratification provides some adjustment for**non~response.** However, it excluded adjustments by income level, household composition, and education.


### 2.13 Weighting for re-contact interviews
Theweighting for the re-contact interviews provides a simple adjustment for non-response. If these weights were important, we would recommend a more complicated adjustment. However, since the NCI model only uses one weight perrespondent (preferably the weight for the first recall, not a separate weight for each recall), the calculation ofan adjusted weight for each recall is not required when using the NCI method for analysis.


### 2.14 Imputation used to populate missingvalues
The imputation used to populate missing values is not explained in detail. The discussion on page 42 says the values were imputed based on characteristics oftheir neighbors butprovides no description ofhow "neighbors" are defmed. 

### Itis not clear whatvalues were orwere not imputed. Itis also not clear how the imputed values were used. \Vere they used to create Table 15? Were they used for weighting? The second bullet on page 42 seems to imply the imputedvalues were not used in the analysis file. 

### 2.15 Dataprocessing and calculations \Ve found no problems with what was presented. However, the description does not say how the 7 or 8 day fish consumption (average or sum?) was calculated from the daily values (only the · calculation for daily values for yesterday is presented, we assume the other days consumption was calculated in a similar manner). \Ve recommend the fish consumption be calculated for 7 and not 8 days, as noted in the overall comments. 

### 2.16 Bootstrapping approach used to develop confidence limits
The Bootstrapping approach apparendy does notincorporate the weights. As a result, for evaluating population differences, the confidence intervals may be smaller than appropriate. Itis not clear how the confidence intervals were used. The word "significant" is used in several places. Itis not clear ifit refers to statistical significance. 

### 2.17 2.17.1 Discussion Section Addressing non-response bias They say 25 percentis "significandy higher than the average response rate." Twenty-five percent is not unreasonable for a telephone survey these days, butit still leaves room for significant nonresponse bias ifthe respondents are not like the nonrespondents. Itis difficult to knowifthe 75 percent that did not respond are systematically different in their fish consumption behaviors. This is ofparticular concern given that they used a quota sample rather than a traditional random sample. This might contribute to the over-representation ofhigher income individuals and anglers-8-

- these groups may be more interestedin the survey topic thus more likely to respond. Could non-response be adjusted for with weighting factors? 

### 2.17.2 Impactofover-representation ofhigher income individuals and anglers They mention that more complicated weights couldbe applied to adjust for these differences, but that could result in large weights within individual health districts. They could assess the impact of the over-representation by applying theweights, running the analysis, and comparing the results.
In general itis always true thatweighting adjustments 

### will reduce precision Qarger standard errors for sampling), but the trade-offis thatit

### will hopefully reduce bias. This is important because the confidence intervals, or tests ofhypotheses, 

### will only have the claimed level ofaccuracy (e.g. 95 percent) ifthe bias is trivial. Ifthere are large biases all ofthese intervals will be incorrect. That is whywe do typically adjust for known under-represented groups. In some cases itmay be worthwhile to trim a few excessively large weights. This process is expected to produce smaller overall mean squared errors, and more appropriately-sized confidence intervals. 

### 2.18 Review ofthe questionnaire and identification ofany issues in accurately recording fish consumption. Ofparticularinterestis review ofthe methodology for inquiry into consumption over the·past7 days.
As noted in the general comments above, clarification ofwhen there is data for 7 days versus 8 days is needed. Also, given the decrease in the proportion ofrespondents reporting fish consumption with increasing length ofthe recall period, estimates based on multiple-day recalls are likely to be biased lowwithout an appropriate adjustment. 

### 3. NCI Method Estimates ofUsual Intake Distributions for Fish Consumption in Idaho
This reportwas prepared underDEQ Contract K079 with Information Management Services, Inc.: Dennis \'Y/. Buckman, PhD, Ruth Parsons, BA, Lisa Kahle, BA, September 9, 2015.
We are interestedin any NCI data analysis factors that mightintroduce uncertainty or bias/loss ofaccuracy in NCI results. We are particularlyinterested in whether or not the data analysis approach is sufficiently described. In addition to whatever the reviewers identify as potential issues, we would like comments on the topics listed below: 

### 3.1 Howwell are the selection and impact ofcovariate choices documented?
The covariates used in the NCI model are listed in the report (page 11). Nojustification for using these covariates is provided. In addition to these covariates, three othervariables that are apparendy available are: gender, household composition (single versus multi-person, see page 40 ofthe survey report), and amount consumed from the FFQ. An easy approach to selecting covariates is to include all available covariates. Alternatively a combination ofa weighted logistic regression (using the SAS SURVEYLOGISTIC procedure with the BRRweights created for calculating confidence intervals for usual fish consumption) predicting the probability offish-9-
consumption in a recall, and a weighted linear regression predicting log-transformed (or Box-Cox transformed) amount offish consumed (using the SAS SURVEYREG procedure), can be used to assess which predictors orinteractions ofpredictors are statistically significant when predicting the outcome. For the NCI model, we recommend including the same predictors for both the probability and amount models, including predictors that are significant·when predicting either probability ofconsumption or transformed amount. In general it is important to include predictors that are clearly significant (p<.Ol). Predictors that are believed to be related to fish consumption but not significant should also be included. We believe the amount consumed from the FFQ should be an importantpredictor ofamount consumedin the NCI model. For continuous predictors (body weight, age, and amount consumed from the FFQ) the weighted regression models can be used to assess how the variables might be transformed andwhether the relationships are linear.


### 3.2 Are there any issues associatedwith use of8 days ofdietary recall information rather than the last 24 hours?
Yes. At a minimum, compared to using only the last 24 hours, the estimates are biased without an adjustment for the decreasing frequency ofreported fish consumption as the length ofthe recall periodincreases. See the general comments above. 

### 3.3 Is the combination andweighting ofgeneral and angler populations done appropriately?
The details ofhow the NCI macros were applied to the data files are not completely clear. For each type offish consumption, we suspect the NCI methodwas applied to the data from the angler and non-angler subpopulations in separate runs, that all runs used the surveyweights, and the summary statistics calculated from the simulated usual intake values for each respondent (from the DISTRIB macro) were calculated using the survey weight associated with the first recall for each respondent. The summary statistics can be calculated after combining the output files from the runs ofthe DISTRIB macro. Ifthese procedures were used, we believe the calculations were done appropriately. 

### 3.4 How, and howwell, is it documented thatthe results meet assumptions ofthe NCI model (e.g. transformed positive fish consumption rates are normally distributed)? The report provides noinformation on the values ofBox-Cox transformation parameter**~ambda),** whether the transformed consumption amounts are normally distributed (a normal quantile plot ofthe transformed consumption amounts (not the plot from the NCI Box-Cox macro that was used) would help), whether there are any outliers, and the estimates ofthe variance components from the NCI model fit (between person for the probability model and the within and between person components for the amount model). This information would help assess the model fit and why the NCI macro had problems estimating lambda and the correlation parameter. In our experience, setting lambda instead offitting lambda in the model and ignoring the correlation parameter has little effect on the results when calculating usual intake offish. Given the relatively large number ofrespondents with two recalls with reported fish consumption we are surprised that lambda and the correlation parameter could not be fit using the MIXTRAN macro; at the same time, we have no reason to question this result.

### -10-

4. Development ofHuman Health Water Quality Criteria for the State ofIdaho (Draft), Windward Environmental, September 15, 2015
We are interested in whether or not the probabilistic analysis is adequately described. Further, we are interested in any methodological issues that were inappropriately or incompletely addressed in the PRA. In addition to anything that the reviewers might provide, we are interested in the following topics: 

### 4.1 Selection ofinput distributions, in particular development ofa Nez Perce fish consumption rate distribution.
The distribution fit to the percentiles ofbody weight appears to provide a good fit to the data. The distribution fit to the percentiles ofdrinking water intake perbodyweight appears to provide a reasonable fit to the data. Given the limited data for fish consumption for the Nez Pierce tribe, interpolating while setting the lower 5percent to the 5th percentile and setting a maximum value andinterpolation for percentiles above the 95th percentile appears reasonable.
One might question how the maximum value was obtained. Based on the footnote on page 12 of the Windward report, the maximum was based on what might be the maximum simulated value from the NCI DRISTRIB macro for the Idaho general population (1,261 g/day) multiplied by 0.242. Ifwe have understood the calculations, this approach appears somewhat arbitrary because 1) the maximum value depends on how many simulated values DISTRIB creates, and 2) the adjustment factor of0.242 seems to be based on calculations that are unrelated to the relationship between the maximum ofthe two distributions. A possible alternative is to calculate the 95th and 99.9th percentile for the general Idaho population and assume the ratio ofthose percentiles is the same for the general Idaho populations and the Nez Pierce population. 

### 4.2 Correlation 4.2.1 Between bodyweight and drinking.water ingestion rate Assuming the drinking water ingestion rate per body weight is independent ofthe bodyweight appears to be a reasonable assumption. Ifneeded, analysis ofNHANES data could be used to test the assumptions. Thus simulating body weight and independendy simulating drinking ingestion rate perbody weight appears to be reasonable. 

### 4.2.2 Between bodyweight and fish consumption rate We expect the fish consumption rate to increase with increasing body weight. The assumed distribution for the body weight appears to be a lognormal distribution. The distribution offish consumption rate can often be reasonably approximated by a lognormal distribution. Thus, when assessing correlation, we strongly recommend plotting and calculating the correlation between the log-transformed body weight and the log-transformed FCR. The statistical assessment of correlation (here using regression) assumes the prediction errors are normally distributed with roughly constant variance. That assumption is clearly not true for the data plottedin Figure 2-3 of the Windward report. 'Wje expect a plotusing the log-transformed values will have an approximate bivariate normal distribution.-11-



### 5. Translation ofNPT consumption of'Group 2' fish to equivalent consumption of 'Idaho Fish' \Y/e are interested in whether or not the approach is adequately documented and whether or not there are any issues with this analytical approach. In particular, we are interested in how IDEQ has processed weighting factors in deriving consumption rates offish caught in Idaho.
In general the re-grouping offish seems appropriate given the available data. \Y/e have three concerns: 1. The explanation ofhow the prorating was done is hard to follow. The prorating ofevent salmon (salmon+ steelhead): Ifa participant reported 10 oz. ofsalmon at events and 6 oz. ofchinook and 4 oz. ofsteelhead at nonevents, then they were assigned 4 oz. for event steelhead. Is this howit was done? 2. Why was Coho left out ofthe prorating? Is it sometimes confused with steelhead?
3. The fraction ofsalmon+ steelhead that is chinook is apparendy calcqlated separately for each respondent. \Y/here does the 81.3°/o come from? This is apparendy the weighted mean percent ofchinook (out ofsalmon+chinook+ coho+steelhead) across all participants that reported nonevent salmon, chinook, coho, and steelhead, is that correct? Although the fraction you are interested in can be calculated for each respondent, the resulting fractions can be imprecise, resulting in biased overall estimates. As an alternative, we recommend calculating the ratio ofthe weighted mean chinook non-event consumption to the weighted mean salmon+chinook+ coho+steelhead non-event consumption and using one ratio for all respondents. Ifthere is concern that the ratio may differ amongrespondents, the ratio can be calculated separately for different demographic groups. The application ofthe weights seems appropriate. The resulting fraction ofthe Group 2 that was assigned as Idaho fish (0.242) was then multiplied by the results that were obtained from the NCI Method for the original Group 2.An Employee-Owned Research Corporation 

# Memo

Date: October26, 2015 

### To: GregFrey, SRA, and Lon Kissinger, EPA 

### From: John Rogers 

### Subject: To-do list for improving the estimates ofIdaho fish consumption

At the request ofSRA, Westat provides the following recommended to-do list for predicting fish consumption from the ID survey. Note that these recommendations are based on our understanding ofthe data and the calculations used previously. The recommendations may need to be adjusted for unanticipated characteristics ofthe data. The to-do list refers to comments in our October 19, 2015 memo. The to-do list: Revise the survey weights:

• Recalculate the base weights, noting the comments in item 2.11.

• Review the imputation ofthe missing demographic variables. This needs to be described better.

• Adjust the base weights for non-response using raking. The variables used for raking would include those in Table 15 in the NRGreport. This will create respondent weights adjusted for imbalance due to the sampling process and non-response, 

### Wi. Ifa few weights are particularly large relative to most weights, those weights might be trimmed. The weights for other cases would be increased so that the sum ofthe weights is unchanged.

• Set the weight for the second recall to equal the weight for the first recall. Revise the calculations to calculate fish consumption over 7 days.

• For each respondent and recall, calculate the quantity offish consumedin each day ofthe recall ("yesterday" and the prior 7 days) as documented on page 116 ofthe NRG report, call this Aird' 

### i references the respondent (1 toN), 

### r references the recall (1 or 2), and 

### d references the day (1 to 8). Then calculate the average daily consumption over the first 7 days for each respondent and recall: Air(7 ) 

# =**L~=~**Atrd.-2-

• Using only the first**reca~** for each subject 

### (r 

# = 1), calculate the weighted mean ofthe fish consumption on the first day and the fish consumption across the first 7 days (the sums are over all completed recalls):

- L7=1Ai11 wi A1 

# = --N-:-:--- Li=1 wi

- L7=1Ai1(7)wi A(7) 

### = 

### "'t:i W,.**~t=l** L Note: this is a slightly different formula than outlined in the comments.

• .Calculate the ratio for adjusting the NCI estimate ofusual fish consumption to estimate usual fish consumption adjusted for decreased recall over time.

Fitting the NCI model 

## A1 R=--- A(7)

• Decide what cases to include in the NCI model. Is there a reasonable way to include cases with missing demographic variables, such as treating the missing values as a separate category orusing imputed demographic variables?

• Create BRRreplicate weights for calculating variances.

• Decide what predictors to use:

o Use the SAS SURVEYLOGISTIC procedure to identify significant predictors of reported fish consumption (Yes versus No) using the BRRweights. First identify significant main effects. Second identify significant two-way interactions ofthe significant main effects. Candidate predictors would be demographic variables (including bodyweight) and FFQ variables (frequency offist consumption, amount consumed). Itis worth considering transforming or categorizing the FFQ variables to handle non-linear relationships. Although it can be done different ways, we suggest 1) including main effects that are significant at the So/o level; 2) including interactions ofthe main effects that are significant at the 1°/o level; and 3) including any other main effects believed to be associated with fish consumption.

o Use the SAS SURVEYREG procedure to identify significant predictors oflogtransformed (or Box-Cox transformed) reported amount offish consumed using the BRRweights, using the steps above.

• In the NCI model, we suggest using the same covariates for the probability and amount models.

• Fit the NCI model to Air( 7). Ifnecessary, determine the Box-Cox transformation parameter (Lambda) before fitting the NCI model. Ifthe correlated model cannot be fit,-3- using the uncorrelated model is OK Report the Lambda and the magnitude ofthe variance components from the NCI model when using the full sample weight.

• Multiply the usual fish consumption from the NCI DISTRIB macro by the ratio R from above to provide an unbiased estimate ofusual fish consumption.

Do the calculations for the PRA:

• Revise the adjustmentfor estimating the top 5°/o ofthe Nez Pierce distribution, see comment4.1.

• Consider a correlation between log-transformed body weight and log-transformed usual fish consumption. Alternatively, ifthe bodyweight is a significant predictor ofusual fish consumption (in the probability and particularly the amount model), the distribution of fish consumption should be a function ofbodyweight.

• Calculate the weighted fraction ofchinook across all respondents when adjusting for different fish species categories (Group 2 versus ID fish). See comment 5, item 3.
Clarify various items, see comments, in particular:

• The process for developing imputedvalues when data were missing



### • WIeighting ofangler and general populations in developing overall results

• Discussion in the NCI analysis report as to howwell model assumptions are metReview of DEQ Approach for Developing an NCI-like Distribution of Idaho Caught Fish, 11/5/15
EPA requested Westat review DEQ's approach for developing an "NCI-Iike" fish consumption rate (FCR) distribution forfish from Idaho waters. This memo summarizes conversations between Lon Kissinger EPA Region 10 and Westat statistician Dr. John Rogers. DEQ developed a Nez Perce distribution ofconsumption of Idaho caught fish by scaling the NCI-derived distribution for consumption ofCategory 2 fish, multiplyingthe percentiles by 0.242 to calculate the percentiles ofthe distribution of Nez Perce Idaho fish consumption.**Th~** scaling factor, 0.242, was the ratio ofthe average consumption of Idaho caught fish to the average consumption ofCategory 2 fish. Both ofthese averages were obtained from the Nez Perce FFQ survey. The resulting scaled or transformed NCI-distribution is referred to here as the "NCI-Iike" distribution.
After discussions with Westat regarding the relationship between the NCI-derived distributions for differenttypes offish, we suggest that further analysis be done on the approach used to develop a Nez Perce "NCI-Iike" distribution of Idaho caught fish. It appears that the current procedure is likelyto underestimate the upper percentiles ofthe Idaho fish consumption distribution.
Given that FCR distributions are reasonably log normally distributed, there is likely a linear relationship between log transformed percentiles ofthe distribution of Idaho caught fish consumption and the distribution ofGroup 2 fish consumption (for which we have the NCI estimate ofthe distribution).
Let P1 represent percentiles ofthe distribution of Idaho caught fish consumption that are to be estimated. Let PG2,NCI represent percentiles ofthe distribution ofGroup 2 fish consumption estimated using the NCI method. Then assume: Ln(Pi) 

## = ln(S) + F*Ln(PG2,Ncl), or equivalently Pi 

## = 5 * (PG2,Nci)F.
The problem is howto estimate 5, a scaling factor, and F, a slope roughly equal to the ratio ofthe standard deviation of Ln(Pi) to the standard deviation of (lnPG2,Nc1). Using results from NHANES data previously analyzed for EPA Headquarters, Westat did a quick analysis comparing the NCI-derived distributions offish consumption for differenttypes offish. Let Requal the ratio ofthe mean fish consumption forthe fish type used as the dependent distribution to the mean fish consumption forthe fish type used as an independent distribution. When predicting the distribution ofa less consumed fish type from the distribution ofa more consumed fish type (i.e., R < 1), it appears the F should be greaterthan 1.0 with higher slopes as Rdecreases.
As an example ofthe calculations, Table 1 has the 35th through 95th percentiles ofthe consumption distributions for all fish and for Idaho caught fish from the Idaho state survey (see: NCI Method Estimates of Usual Intake Distributions for Fish Consumption in Idaho, Tables A1 and A2, using All Subjects). Lower percentiles were not included because the estimates were reported as "<.01" orwere particularly imprecise.Table 1 Percentiles offish consumption for all subjects All Fish Idaho fish Percentile Table A1 Table A2 35 8.31 0.02 40 10.09 0.04 45 12.06 0.06 

### so 14.25 0.09 55 16.61 0.14 60 19.27 0.22 65 22.29 0.34 70 25.71 0.53 75 29.74 0.84 80 34.85 1.38 85 41.44 2.42 90 51.11 4.66 95 67.66 11.24 Figure 1 shows a plot ofthe percentiles of Idaho fish consumption as a function ofthe percentiles ofall fish consumption, using Jog scales. As can be seen, the log-transformed percentiles fall on a roughly straight line.**,E!~-~~-!:_~Iot**

## o! percentiles for Idaho fish versus all**fi~~** (log.,_s_c_al_e::__)

__ _ I 100

----o-Jdaho A2

0.01 +----·**----~---------,** 

## I I L___ 1 10 100 Group 2 fish consumption percentiles

·-----------····----

## I I

Fitting a linear regression to predictthe log-transformed percentiles for Idaho fish consumption from the Jog-transformed percentiles of all fish consumption gives a slope ofF= 3.00. Although this analysis used selected percentiles,**u~ing** all percentiles between the pt and 99th percentiles and using more precision is recommended.
Different slopes will be obtained using different data or different subsets ofthe data (such as anglers only). For all subjects in the Idaho state survey the ratio ofthe means (R) is .106, smallerthan the ratioof0.242 estimated for the Nez Perce from the FFQ. Although one could use F = 3.00 for the Nez Perce, since Fappears to increase as Rdecreases and Rforthe Idaho state data is less than for the Nez Perce, an appropriate slope for predicting Nez Perce Idaho fish consumption from Group 2 fish consumption may be less than 3.00. Some judgment is required to setthe value of F. Considerations might include:

• calculations using Idaho data (as above), • calculations using NHANES data, or possibly • calculations using FFQ data (note thatthe precision and bias of FFQ data are uncertain and lower percentiles of FFQ estimated Idaho fish consumption are zero; it is not possible to calculate the log ofzero).
Once F is set, calculate R, in the case ofthe Nez Perce based on the FFQ data. R is the ratio ofthe reported means of Idaho fish consumption and Group 2 fish consumption:
R = Mean(IFFo) 

### I Mean(G2FFo) = 0.242
Also calculate the mean of PG2,NCI and (PG2,Nci)F across all percentiles (excluding the oth and 100th percentile). These means are calculated using the percentiles from the DISTRIB macro because those are the data that are available.
The calculations assume the ratio ofthe mean Idaho fish consumption to the mean Group 2 fish consumption is the same forthe FFQ data as for the NCI or "NCI-Iike11 data, i.e.,: Mean(IFFo)IMean(G2FFo)=Mean(Pi)IMean(PG2,Ncl) Since Mean(Pi) = S* Mean((PG2,Nci)F), solving for Sgives:

S = R * Mean(PG2,Ncl) 

### I Mean((PG2,Nci)F) Finally, calculate the "NCI-Iike'' distribution: Pi=

## s * (PG2,NCI)F
The mean of Pi across all percentiles (excluding the oth and 100th percentile) should be equal to Mean(IFFo). Note that ifF= 1.0, then S=Rand the scaled NCI distribution is the same as calculated previously by Idaho DEQ. Using a slope (F) greaterthan 1.0 spreads out the distribution, particularlythe uppertail, compared to using F = 1.
We expect the approach outlined above, using an estimated value ofthe slope F, will provide a better estimate of Nez Perce Idaho caught fish consumption distribution than assuming F equals 1.0.