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### MEMORANDUM

TO: Donald Anderson, USEPA

FROM: Kathleen Wu, Betsy Bicknell, and Anne Jones, ERG

DATE: August 1, 2011

SUBJECT: Report of Quality Activities Supporting Alaska Seafood Proces sing

Questionnaire Database Development and Analysis

1. PURPOSE

ERG supported EPA in a data collection effort throu gh the Questionnaire for Canned and Preserved Seafood processing Facilities in Certain Locations of Alaska (hereafter, the questionnaire). The questionnaire was sent to nine Alaska seafood processing companies from which EPA expected responses for 68 facilities. Thi s report describes the data collection effort, the compilation of data from the questionnaire resp onses, the evaluation procedures for the collected information, and the quality assurance st eps taken. The activities ERG performed to control the quality of the collected information ar e detailed in Revised Draft Quality Assurance Project Plan: Support for EPA Response to Industry Petition on ELGs for Non-Remote Alaskan

Seafood Processors , dated November 12, 2010 and conditionally approve d by EPA on November 29, 2010 (hereafter, the QAPP).

2. QUESTIONNAIRE PROCESSING AND QC PROCEDURES

The questionnaire requested information about each facility that the company operates in Alaska. Among other things, the questionnaire requested inf ormation about the facility’s operation, processing capacity, seafood processing waste gener ation, and current waste recycle/recovery and disposal practices. The questionnaire also aske d for financial information to characterize the economic status of each facility and its owner firm , and to estimate the possible economic impacts associated with alternative waste disposal practices.

ERG developed a Microsoft Access® database to store questionnaire responses. With this database, ERG compiled and analyzed facility inform ation submitted in response to the questionnaire. This effort included:

• Developing a tracking sheet to record the receipt o f the questionnaire responses and completion of all the major questionnaire component s;

• Entering questionnaire responses into the database (key entry) and 100% QC of key

entry;

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### • Developing and executing database queries to check the range a nd logic of responses and notifying EPA of problematic responses;

• Analyzing the questionnaire database to prepare input for the c ost calculation.

ERG also supported EPA in collecting and analyzing informa tion collected via telephone, e-mail, and or letter requests, and analyzing additional informatio n from Annual Reports provided by EPA Region 10. Finally, ERG supported EPA during site visits a t Alaskan seafood processing plants and one stand-alone seafood processing plant. Duri ng these site visits, ERG collected detailed information about plant waste management activitie s. These additional data sources were used to supplement information provided in the questionnaire where needed.

2.1. 

### Receipt of Questionnaires

Upon receipt of a completed questionnaire, a 

### CBI-cleared ERG employee recorded receipt details in a tracking spreadsheet and processed the questionnaire thr ough a general completeness check. These checks allowed ERG to address any immediate compl eteness issues and determine whether the questionnaire should be handled as CBI. This c heck did not include a thorough review of each question in the questionnaire, but did determi ne overall completeness of the tables within the questionnaire. Table 1 shows the informat ion documented in the tracking spreadsheet for both the financial and technical portions o f the questionnaire.

Table 1 - Questionnaire Tracking and Completeness Check Cri teria

Financial Section Technical Section

Tracking

Documentation Date of Receipt Date of Receipt

Person tracking/conducting the check Person tracking/conducting the check Copy log of all electronic and hardcopies Copy log of all electronic and hardcopies

Confirmation email Confirmation email

Tracking and Completeness

Check Criteria Company Name Facility Name

Financial Contact Information Technical Contact Information Assigned Document Control Number Assigned Document Control Number All q uestionnaire sections are present All q uestionnaire sections are present

CBI Claims CBI Claims

Attachments Attachments Signed and completed Certification

Statement NA

NA Questionnaire submitted for all facilities requested

NA A dditional facilities included voluntarily

NA NPDES Permit Number

NA Copy Number

NA Facility Location



### Any clearly deficient responses or major inconsistencie s were first discussed with EPA who individually followed up with the individual respondents. Min or issues were resolved through confirmation with EPA Region 10, facility’s Annual Repor ts, site visit report information, or direct phone call with a facility contact. Because th e majority of questionnaires included responses that were claimed as CBI, ERG treated all ques tionnaire information as such, and

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### stored all electronic and hardcopy surveys in the same CBI network and CBI file storage area, regardless of CBI status. Respondents with questionnaires that met the completeness check criteria were sent an email conformation and a duplicate hardcopy of the questionnaire was sent to ERG’s Lexington office for processing and review of econ omic information by ERG economists. The original responses were retained at ERG’ s Chantilly office for further processing and review of the technical information by ERG scientists and engineers.

2.2. 

### Data Entry

CBI-cleared ERG employees with prior experience relate d to questionnaire data entry transcribed responses from hardcopy questionnaires into th e questionnaire database. For simple questions they typed responses directly into the database tables, and they used Access Forms to enter responses provided in table form. This combination appr oach minimized both data entry errors and database programming. In addition to question res ponses, the database identifies all responses industry respondents claimed as CBI. Skipped questions or questions left blank were left as blanks within the questionnaire database.

EPA received questionnaires from both land-based facilit ies and off-shore vessel based facilities operated by the nine seafood processing companies. ERG tracked receipt of questionnaires from

all of the off-shore based facilities but did not enter all survey responses into the database. Of the nine seafood processing companies surveyed, ERG received respo nses from 58 facilities but only

entered technical information from 52 facilities into the database. The remaining six facilities not entered were off-shore vessel based processing faculties . In one unique scenario, EPA received survey responses from three Inlet Fish Producers faciliti es. Due to site-specific operational management of their facilities, ERG and EPA combined the responses of three facilities into one survey response included in the 52 total facilities entered i n the database. All remaining analyses were solely based on the 52 facilities entered into the database. Information from the 6 off-shore

facilities was excluded.

2.3. Database QC

To ensure accuracy of the database, a second CBI-cleared ERG staff member independently reviewed 100% of the database entries for data entry accura cy. When errors in database entry were discovered during review, ERG corrected the erroneous data fields. An ERG staff member not involved in the data entry corrections performed a 1 00% check of the corrected fields to

ensure that resolved errors were corrected in the Micro soft Access database. In addition, any formatting errors or field names changes associated wit h the original database design were also corrected when issues were identified. In total, ERG ma de 32 fixes to the database design and corrected 102 data entry errors.

3. RANGE AND LOGIC CHECKS

After all responses were entered into the database, ER G executed a series of queries to determine whether any responses were missing, did not add to a reporte d total, were outliers, were inconsistent with responses to other questions, or are oth erwise problematic for a given question for a given questionnaire response. ERG reviewed the logic an d programming for database queries and documented this review in a database table. ERG prepared a report documenting the

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### findings of these checks. After follow up with responde nts, ERG added clarified or supplemental responses obtained by EPA and ERG into the database. Some examples include:

• Requesting missing financial (Part-A) information;

• Clarifying ambiguous or missing NPDES permit numbers;

• Verifying company ownership organization;

• Verifying vessel ownership; and

• Clarifying by-product recovery activities.

3.1. Part A: Corporate Financial Information

Part A of the questionnaire collected financial informat ion on the corporation level for the nine seafood processing companies. For this section, ERG crea ted five queries encompassing the following range and logic checks for this section:

• Mandatory questions;

• Optional questions;

• Dependent questions (i.e., did they follow the skip patter n);

• Consistency of answers between related questions;

• Priority of the question;

• Minimum and maximum ranges for numerical responses;

• Tally of responses for Yes/No questions;

• Completion quality (number of responses received out of total number of responses expected); and

• Issues identified.

ERG also reviewed the answers to specific questions that were extracted manually prior to database delivery to determine whether they seemed consist ent with what was expected. All data extracted was entered into the financial modeling spreadshee ts by one analyst, checked by another analyst, and any changes made were confirmed by a third analyst.

3.2. Part B: Facility Information

Part B of the questionnaire requested technical and financia l information for individual facilities operated by the nine corporate entities. ERG entered questi onnaire responses from 52 facilities into the Access database and analyzed the responses using range and logic checks described in

the subsections below.

3.2.1. Prioritization

ERG will use the information collected by the questionnair e to support EPA’s analysis of certain “processing centers 1 

### ”, but EPA received survey responses for facilities acro ss all of Alaska. As a

1 Processing centers are defined as subcategories of al l Alaska seafood processors generally sorted by remote or nonremote geographic regions and type of fish or shellfish harvested. By doing so, EPA can take into account the unique characteristics of seafood processing facilitates an d how they process the seafood in their region.

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### result, ERG prioritized the 52 facilities into “High”, “Medium” and “Lower” categories depending on their processing center. ERG also organized the facilities in the priority table by parent company, NPDES permit number, and location. Priori tizing the survey responses for analysis in this manner allowed for a more focused revie w of the quality of responses from facilities located in the specific locations of intere st. Table 2 shows the priority level of each processing center.

Table 2 - Prioritization of Processing Centers in Alaska

High Med ium Low er Ketchikan Kenai Peninsula /Seward Akutan Petersburg Kodiak Sand Point

Cordova Dutch Harbor Naknek

Juneau Sitka St Paul Chignik Wrangell

Larsen Egegik

Alitak Craig King Cove Dillingham

Port Moller

Valdez Anchorage



### 3.2.2. Database Queries

ERG performed range and logic checks on the three priori tization categories separately. By QCing the categories separately ERG could focus on data nee ded to support EPA’s current efforts. ERG created over 100 queries to check the range an d logic for all the responses provided in Part B of the questionnaire. The following is the list of range and logic checks performed on

this section.

• Mandatory questions;

• Optional questions;

• Dependent questions (i.e., did they follow the skip patter n);

• Consistency of answers between related questions;

• Priority of the question;

• Minimum and maximum ranges for numerical responses;

• Tally of responses for Yes/No questions;

• Completion quality (number of responses received out of total number of responses expected); and

• Issues identified were noted.

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### ERG followed the same general method to create each quer y but customized certain tallies, calculations, or assessments of completeness depending on the specifics of the question. The following is the generalized method used to create each query

.

1. The facility responses table were linked to the priority c ategory using NPDES permit number;

2. The fields of interest were pulled in the query.

3. The questions were assessed as either mandatory, optiona l, or dependant.

4. If a question is dependent on the response to a prior questi on, the prior question was assessed to determine if a response was expected.

5. After establishing the total number of responses expected, a tally of responses was made to assess response completeness. ERG assumed that quest ions left blank indicated no response. For questions with multiple parts and an expected numerical response, ERG assumed that blanks in a partially comple ted question indicated a zero and a completed question.

6. All numerical responses were extracted and analyzed for their minimum and maximum ranges. Any outliers were identified.

7. The tally of responses to yes/no questions was extracte d.

8. A consistency check was conducted for questions that were linked or partially dependent. For example, a check was performed to assess w hether the species of seafood processed at the plant were consistent with the species of seafood reported in that annual production rates.

9. Inconsistencies within questionnaires, clear misinterpre tation of questions, or questions with very low completion rates were identifi ed as a possible questionnaire wording or formatting issues.

3.3. Range and Logic Summary Tables

ERG designed and created four summary tables to report the f indings of the range and logic checks. One table presented the results for Part A of t he questionnaire and the three other tables presented the results for Part B of the questionnaire by t heir “High”, “Medium”, and “Low” priority listing (see Attachment A). The final tallies and range calculations from the queries were imported electronically “as is” from the database into t he summary table and edited for presentation in some cases. Where applicable, some val ues and notes were manually key entered into the tables. Each table listed the questions in the appr opriate section and presented an analysis of each range and logic check criteria mention ed in the section 3.2.

3.4. QC of Range and Logic Tables

To ensure the accuracy of the range and logic tables, a s econd CBI-cleared ERG staff member independently reviewed 100% of the table entries. The reviewer started with the query development and design and then reviewed that values were transferred to the summary tables without errors. In addition, several values reported in t he summary table were also manually checked with the original database, by creating new queries. The reviewer then highlighted any

inconsistencies identified and confirmed that errors were c orrected.

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### 3.5. Range and Logic Results

In general, the range and logic checks helped ERG quickly ide ntify weaknesses in the questionnaire responses. Note that results reported below are based on the facility responses at the time of the range and logic check analysis 2 

### . Below is a summary of the quality of responses in each of the range and logic summary tables.

Company Level Part A

– For questions in Part A, completion ranged from 50% to 100% for all but one questions. The majority of the questions had a comp letion rate of 100%. Questions A-9 and A-19, which pertained to NAICS codes and the total number of US facilities in operation and total number of employees, had poor percent completion . This may be due to the nature of the industry where there are several layers of owner ship of facilities; the variability of off-shore facilities; and the use of many part-time migrant workers . ERG did not identify issues with following skip patters, units, or interpretation of questio ns. No outliers were identified.

High Priority Facility Level Part B

– ERG classified 10 facilities as “high’ priority. For this group of facilities, response completion ranged for most questions in Part B from about 80% to 100%. ERG noted some confusion with units in questions B-12 and B-26. Where the questionnaire requested production and wastewater rates at aver age pounds or gallons per day, responses were occasionally in units of average pounds or gallons per days of operation. Because the questionnaire did not ask the total number of days of operation the true average could not be determined. This confusion is likely a result of the questi onnaire wording and that facilities normally report production rates at average pounds per day o f operation through their annual reports to the Alaska Department of Environmental Conserva tion.

Medium Priority Facility Level Part B

– ERG classified 8 facilities as “medium” priority. For this group of facilities, the completion ranged for most questions in Part B from about 60% to 100%. Only 3 out of 47 questions were completed by all 8 facili ties. One facility failed to complete the majority of the questionnaire. ERG noted inco nsistencies in units for question B16. ERG also noted inconsistencies in reporting how process wastewater was managed within one facility.

Lower Priority Facility Level Part B – ERG classified 33 facilities as “lower” priority. For t his group of facilities, for most questions in Part B, comple tion ranged from about 42% to 100%. Again, only 3 out of 47 questions were completed by all 33 facil ities. Seven facilities left entire sections of the questionnaire blank. ERG noted inconsist encies in units for question B-16. ERG also noted inconsistencies in reporting how process waste water was managed within one facility. For example, facilities that claim to discharge to the sewer were unable to provide names of municipalities. ERG used several secondary sources to repla ce the missing treatment plant information. For this reason, ERG concluded respondents m ay have confused outfalls and municipal sewer systems.

Clarifications and confirmations made using secondary data we re not made directly in the database. Instead, ERG extracted database information in to tables and compared it to secondary

2 Several facilities submitted supplemental information lat e and while subjected to the same tracking and QC processes, those late responses were not included in the range and logic check analysis.

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### references. Changes were made to only these external t ables that were eventually used for cost

calculations. ERG documented all sources for cost calcu lations in the comment section of the costing table. Below are some examples of how ERG com pleted some the missing questionnaire

information.

• Where financial information was missing, EPA contacted the parent company to follow up and receive additional information.

• Where production rates, water use, species processed, and uni ts were inconsistent, ERG used annual reports to verify questionnaire responses. Whe re available, ERG also used annual reports to identify the number of days in operation for facilities that reported average pounds or gallons per days of operation.

• ERG also used site visit reports and direct contact with facility operators to complete missing information in regards to facility operations, such as wastewater management, seafood processing, waste management, by product management, site layout/dock space, and waste hauling practices. ERG visited 9 out of 10 of the high priority facilities and 3 facilities in the other categories.

• Where percent yield rates were missing, ERG used from Bim bo, 2010 3 

### as reasonable estimates of salmon byproduct yields. These values are co nsistent with estimates of the weight of solids in the raw waste provided by Bechtel and Smiley, 2009 4 

### . The rationale for this assumption is summarized in the memoranda Byproduc t Yield Assumption for Alaska Seafood Processing Cost Estimate (March 8, 2011).

4. DATA QUALITY ASSESSMENT: MEETING QAPP SPECIFICATION S

The quality specifications for “qualified: best available data” from the questionnaire are discussed in section 2.4.1.1 of the QAPP. These six crite ria include Unambiguous, Internal Consistency, Completeness, Reasonableness, Representa tiveness, and Comparability. The sections that follow assess each criteria for questio nnaire data used for cost estimates meet the specification. While most of the questionnaire data was r eviewed, ERG had selected six questions to focus on in this analysis and to present in thi s section. ERG selected these six questionnaire responses because they were intended to be use d directly in the costing exercise and could be evaluated well under each criteria. These ques tions include:

• B-11: Total Pounds of Raw Product Processed Annually from 2005-2009 by Species

• B-12: Seasonal Average Pounds per Day of Seafood Processes By Month and Species

• B-13: Peak Week and Day Production Rates by Species

• B-18: By-Product Production Totals

• B-24: Estimates of Product, By-Product and Waste Yields by S pecies

• B-26: Average Volume of Seafood Processing Wastewater Dis charged by Month

3 Anthony Bimbo, Alaska Seafood Byproducts: 2008 Update on Potential Products, Markets, a nd Competing
Product, 2009.

4 Peter J. Bechtel, Scott Smiley.“A Sustainable Future: Fish Processing Byproducts”. February 25-26, 2009.

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### 4.1. Unambiguous

Unambiguous responses are clear and easily interpreted without confusion. Table 3 shows how the questionnaire responses meet the unambiguous specifi cations.

Table 3 - Unambiguous Acceptance Criteria Assessment

Question

Number Units of Measure are

Identified Responses to Open-ended Questions are Clear The Question was Interpreted Consistently by Multiple Respondents

Number of responses for

which the criteria is true out of total applicable responses Number of responses for

which the criteria is true out of total applicable responses True/False

B

- 11 47/52 14/14 True

B-12 48/52 13/13 True

B-13 48/52 12/12 True

B

- 18 11/17 6/6 True

B-24 48/52 11/12 True

B-26 23/52 NA False a

NA – Not Applicable a. Flows were provided in average gallons per day o f operation, and the questionnaire did not ask for the total number of days of operation. Due to the variability of salmon season and operati ng days, the true average flow per day is unclear.



### 4.2. Internal Consistency

ERG evaluated internal consistency by checking that the a nswers to questions were consistent with answers to other related questions. ERG evaluated this criterion by looking at the species of seafood processed and reported for questions B-11, B-12, B-13, and B-24. Table 4 shows how the questionnaire responses meet the in ternal consistency specifications.

Table 4 - Unambiguous Acceptance Criteria Assessment

Question

Number Responses Follow Questionnaire Skip

Patterns Responses to Multiple Questions Asking for

Similar or Related Information are Comparable and Consistent Number of responses for which the criteria is true out of total applicable

responses Number of responses for which the criteria is true out of total applicable responses a, b

B-11 NA 45/48

B-12 NA 45/48

B

- 13 NA 46/48

B-18 46/52 facilities either completed or

skipped this question appropriately NA

B

- 24 NA 36/48

B-26 NA NA

NA – Not Applicable a. Consistency between reported species of seafood was used as the comparison criteria. b. Note that of the 52 facility responses four faci lities left these questions blank and were not incl uded in the consistency criteria resulting in a total of 48 total applicable responses.

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### 4.3. Completeness

ERG evaluated completeness by checking that all faciliti es provided responses to all applicable questions. Table 5 below shows the number of faci lities that to provided responses to the six specific questions out of the total number of f acilities the question applied to. Table 6 shows the number of questions each facility answered ou t of the total number of questions applicable to each facility.

Table 5 - Completeness Acceptance Criteria Assessment

Question

Number Question Answered by All Respondents to Which it Applies Number of responses for which the criteria is true out of total applicable responses

B

- 11 47/52

B

- 12 48/52

B

- 13 48/52

B

- 18 11/17

B

- 24 48/52

B

- 2 6 48/52



### Table 6 – Completion by Facility

Plant Name Number of Questions Answered Total Number of

Applicable Questions % Completion

Alyeska Seafoods, Inc 28 31 90%

Trident

- Akutan 29 31 94%

Westward

- Dutch Harbor 28 31 90%

Peter Pan

- King Cove 22 26 85%

Trident

- Sand Point 29 31 94%

Icicle

- Northern Victor, Udagak Bay 30 31 97%

Icicle

- P/V Arctic Star, Pribilof Islands 17 19 89%

Icicle

- RM Thorstenson, Pribilof Islands 17 19 89% E.C. Phillips and Sons 16 19 84%

Trident

- Ketchikan Cannery 31 31 100%

Trident

– North Naknek 17 19 89%

Peter Pan Seafoods

- Dillingham 17 19 89%

Peter Pan Seafoods

- Port Moller 17 19 89% Ocean Beauty Seafoods

- Alitak 17 19 89%

Icicle

- Larsen 17 19 89%

Icicle

- Egegik Plant 17 19 89%

Trident

- M/V Alaska Packer 16 19 84%

Trident

– Chignik Plant 16 19 84%

Trident

- Wrangell 16 26 62% Ocean Beauty Seafoods

- Excursion Inlet 17 19 89%

Icicle

- P/V Arctic Star 17 19 89%

Icicle

- P/V Bering Star 17 19 89% Ocean Beauty Seafoods

- Naknek 17 19 89% Trident / Norquest

- M/V Pribilof 17 19 89%

Trident

- M/V Independence 17 19 89% Trident / Norquest

- Chignik 15 19 79% Trident / Norquest

- Ketchikan 16 26 62%

### 11 Plant Name Number of Questions Answered Total Number of

Applicable Questions % Completion

Icicle

- P/V Discovery Star 17 19 89%

Peter Pan Seafoods

- Valdez 16 26 62% Trident / Norquest

- Aleutian Falcon 17 19 89%

Icicle Seafoods

- Petersburg Fisheries 22 26 85% Supreme Alaska Seafoods

- M/V E xcellence 4 31 13% Ocean Beauty Seafoods

- Nikiski 17 19 89% E.C. Phillips and Sons

– Craig Fisheries 14 24 58% Trident / Norquest

- Petersburg STB Mitkof 20 24 83% Trident / Norquest

- Petersburg Plant 17 19 89% Ocean Beauty Seafoods

- Petersburg 17 19 89%

K enai River Plant/Kasilof River Plant/K

- Beach

Plant 17 19 89% Snug Harbor Seafoods 27 31 87%

Icicle

- Seward Fisheries 30 31 97%

Trident

- Cordova South Plant 17 19 89%

Trident

- Cordova North 28 31 90% Ocean Beauty Seafoods

- Cordova 17 19 89%

C opper River

- Cordova 17 19 89%

Alaska Glacier Seafoods 23 24 96%

Icicle

- P/V Northern Victor 2 31 6%

Trident

- St. Paul 17 19 89% Ocean Beauty Seafoods

- Kodiak Plant ( Gibson Cove) 2 31 6% Ocean Beauty Seafoods

- Kodiak Facility 24 24 100%

Westward

- Kodiak 23 24 96%

Trident

- Kodiak (vessel) 20 24 83% Copper River

- Anchorage 15 24 63%



### 4.4. Reasonableness

Reasonable responses include reported values and facts that are consistent with operating seafood processing plant information gathered from ADEC, EPA Region 10, and other EPA approved resources. Details there were checked include the variety of species processed; pounds of seafood processed monthly; and annual production rates. Wh ere data was available a percent

error was calculated to determine reasonableness.

4.5. Representativeness

ERG evaluated representativeness by looking at how the fa cilities that responded to the questionnaire reflect the population of seafood processing plan ts in non-remote Alaska locations that are the subject of the industry petition. Table 8 s hows the count of the number of facilities surveyed and visited out of all the facilities in each of the processing centers in non-remote Alaska locations that are the subject of the industry pet ition.12Table 8 – Representativeness Acceptance Criteria AssessmentProcessingCenterNumberofSurveyedFacilitiesNumber ofFacilitiesWhere aSite VisitwasConductedTotalNumber ofFacilitiesin theProcessingCenterFacilities not SurveyedFacilities Where a SiteVisit was ConductedNumber ofFacilities Outof Total ThatWereSurveyed and/or VisitedDo theFacilitiesSurveyed and/orVisited Representthe Population ofSeafood ProcessingPlants at EachCenter?Ketchikan3 4 5Alaska General SeafoodsPacific SunTrident Seafoods(Norquest)Trident SeafoodsAlaska GeneralE.C. Phillips 4 of 5 YesPetersburg3 2 3 noneIcicle Petersburg FisheriesTrident (Norquest) 3 of 3 YesJuneau1 2 2 Taku FisheriesAlaska Glacier SeafoodsTrident (Norquest 2 of 2 YesCordova4 4 4 noneCopper RiverSeafoodsOcean Beauty SeafoodsTrident (Norquest)Trident North 4 of 4 YesSitka0 0 3Silver Bay SeafoodNorth Pacific Seafoods(Sitka Sound Seafoods)Seafood Producers Coop none 0 of 3 NoKenai/Seward4 0 13Polar Seafoods, IncResurrection BaySealevel SeafoodsPacific Star SeafoodsSalamatof SeafoodsKenai Landing/KenaiRiver Seafoods1,2Sea Level SeafoodsCarlson's SeafoodsPort & Harbor of Homer none 4 of 13 PartialDutchHarbor34 05Harbor Crown Seafoods none 2 of 54Yes1The only operations at Kenai Landing is the fish oil plant operated by Scientific Fisheries.2For the costing analysis, ERG has considered all Inlet facilities on Kenai as one facility.3Only land-based facilities are included in this assessment4Two facilities did not complete the questionnaire.

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### 4.6. Comparability

ERG compared questionnaire information to production informa tion in annual reports. More specifically, ERG compared the pounds of raw product processe d between 2005 through 2009

for four facilities. These four facilities were chose n based on its processing center priority; completeness of the questionnaire; and completeness of annual reports. The comparability goals according to the QAPP include 5 

### :

• Questionnaire-reported discharge flows, production, and/or po unds of waste discharged

are not more than 15% different from values included in t he facility annual report.

Table 9 shows the relative percent difference for aver age pounds of raw product processed from 2005 through 2009 for four plants whose annual report information w as extracted. Two of the four facilities met the 15% comparability goal. Based on t he Table 9, questionnaire production was always underreported when compared to the annual report s. It is possible that some species processing was not reported in the questionnaire.

Table 9 – Comparability Acceptance Criteria Assessment

Facility Name From Questionnaire From Annual Reports

Relative

Percent

Difference Production (lbs of raw product/year averaged over 2005-2009) Production (lbs of raw product/year averaged over 2005-2009)

E.C. Phillips and Sons 13,646,656 17,093,595 20%

Trident Ketchikan Cannery 18,633,400 21,731,708 14% Ocean Beauty Seafoods

- Nikiski 3,150,200 4,397,238 28%

Kenai River Plant/Kasilof River Plant/K-Beach Plant 6,172,800 6,260,643 1%



### 5. EVALUATION OF DATA USED FOR COSTING

After the review of the data quality and the closer eval uation of responses to six costing questions for their compliance with the six data quality acceptance criteria, ERG determined

which data would be suitable for use in the cost calculat ions. In addition, ERG evaluated the questionnaire response quality by processing center before decid ing to accept or reject questionnaire data for costing purposes. These six questions had been preselected to be used directly for cost estimates, but not all met the qualit y criteria. Due to quality issues with responses to two of the six questions (B-18 and B26) they w ere ultimately not used. Instead ERG changed their costing approach in order to use other data i n place of those two questions.

• 5 The QAPP comparability goals included: “Questionna ire-reported discharge flows, production, and/or
pounds of waste discharged are not more than 50% di fferent from the values reported in the Notice of Intent (NOI).” NOI do not provide sufficient detail to compare to questionnaire-reported values, so ER G did not use this goal to evaluate questionnaire dat a quality.

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### 5.1. Accepted Data

Based on the data quality assessment, responses to questio ns B-11, B-12, B-13, and B-24 for the high priority facilities met the criteria and were used for costing inputs with a few exceptions.

• B-11: Total Pounds of Raw Product Processed Annually from 2005-2009 by Species

• B-12: Seasonal Average Pounds per Day of Seafood Processes By Month and Species

• B-13: Peak Week and Day Production Rates by Species

• B-24: Estimates of Product, By-Product and Waste Yields by S pecies

The responses to these questions were most importantly una mbiguous, included units, and while not all facilities provided responses, the responses that were provided were sound. In addition, ERG was able to spot check many of the responses with ann ual reports and site visit reports to verify reasonable response ranges. Species processed, produc tion rates, and production yields were compared to annual reports. Dates for peak production days and weeks were compared to typical salmon season. In addition, ERG checked that pe ak rates were within reason of their reported average production rates (i.e., not less than aver age rate). Any questionable responses were flagged and double checked with a secondary reference. Any missing information was supplemented with available data in the annual reports fo r the purpose of costing.

Where the production rates were reported for average pounds per days of operation (instead of average pounds per day over the month), ERG extracted the number of operating days from annual reports and calculated the average production rates pe r day. Where production days were not available, ERG assumed that during salmon season (i. e., June, July, and August) the facilities operated a total of 91 days. Facilities that reported oper ating days in their annual reports ranged from 26 days to 31 days per month during those months.

5.2. Rejected or Incomplete Data

The data collected in question B-18 regarding byproduct production was not completed by 6 out of 17 facilities that had a byproduct operation. Further, th e by-product yield value for a few facilities were too large as compared to their production rates and by products produced. Based on site visits, Alaska Protein Recovery and Trident Cordo va plants only processed salmon heads

for salmon oil. The information that was collected wa s determined to be reliable based on verification with by-product plant operators and site visit reports. ERG worked to fill in missing

information from the six facilities that failed to com plete the question using similar resources, such as communication with the industry, site visit repo rts, and EPA Region 10. However, the final dataset was not used in the final costing calculati ons.

Question B-26, which asked for average volume of seafood pr ocessing wastewater discharged, did not meet the quality assurance acceptance criteria. Further, ERG was unable to fill in missing information with secondary sources. In addition, the ques tion gave responders the option of providing waste water flow or water use flow. Unfortunate ly, this option resulted in further misinterpretation of the question.

Although completeness does not appear to be an issue for a ny questions addressed in Table 5, it was because most of the facilities did attempt to provide responses. However, only 23 of 52

### 15



### facilities provided units. Those that did provide units reporte d gallons per day (others reported gallons per month or gallons per days of operation), but wa ter use ranged from 36,000 gpd to 27,780,979 gpd in July. As a result, ERG was unable to identify which end of the range was unreasonable or a result of a unit error. The reported value s also did not have a secondary data source for which to compare.

ERG also identified inconsistencies with flow rates a nd salmon season (B-18 and B-26). For example, some facilities the months when production was the greatest did not always correlate to the months with highest waste water flow. ERG suspects this inconsistnacy may be due to variability in water use for processing various species, but was unable to confirm whether the responses were reasonable or followed internal consist ency with spikes in production. Overall, ERG concluded that the question was confusing and led to a vari ety of interpretations. As a result, ERG did not use the information provided in question B-18 and B-26. To determine facility waste water generation for costing, ERG inste ad used the production normalized flow reported in the original 1979 industry report 6 

### to determine each facility’s waste water generation flow based on each facility’s production rates.

ERG also did not use responses to B-30 in regards to waste transport vessels and vessel ownership for cost estimates. These were open ended quest ions that did not apply to many facilities and could not be fully evaluated by the accepta nce criteria. However, based on the
information that was received, ERG still felt that th ese responses would not be appropriate to use

in the cost calculations. Instead ERG relied on informa tion collected during site visits and follow-up communication with by-product plant operators.

6. QUESTIONNAIRE DATA QUALITY: RESPONSES TO KEY INDIVI DUAL RESPONSES (FACILITY AND FIRM ECONOMIC INFORMATION)

The questionnaire data used in the financial modeling were r eviewed by the lead economist and her staff. All questionnaire data used directly in the fina ncial modeling were extracted manually and input directly into the economic model. These data in cluded data found in Questions A-13 and A-16, in Part A and Questions B-43 and B-44 in Part B. T he Part A answers were assessed individually by the lead economist to determine if they see med reasonable in light of what was known about the firm regarding employment size and corpora te structure and what seemed reasonable with respect to prevailing interest rates, both among all the firms surveyed and those generally available in the market place. The part B quest ions on revenues and costs for the years requested was reviewed by the lead economist for consistenc y with financial reports submitted by the firms, to ensure that line items added properly to tot als, that each line item seemed appropriate in terms of magnitude, given the known sizes of facilities, and that line items across years seemed to change in reasonable ways. These judgmen ts do not rely on any hard and fast rules because financial data can vary in many ways, and g iven that there are little publicly available data with which to compare, the ability to fine-t une any reality checking of the
financial data is minimal. Addition checks did, howeve r, identify one small error in addition,

6 E.C. Jordan Co, 1979 Reassessment of Effluent Guidelines and New Source Performance Standards for the Canned and Preserved Seafood Processing Point Source Category. Pre pared for USEPA Effluent Guidelines Division

December 1979.

### 16



### which was corrected so that the reported costs summed t o the reported total for one year at one facility.

For single-facility firms, however, ERG was able to r eview annual reports or tax returns that provided the same line items at the firm level as those a t the facility level provided in Questions

B-43 and B-44. These reviews were done to determine the accur acy of the survey-reported information. In a few instances, the information submi tted for a facility did not seem consistent with the information in the annual report or tax return submitted for its firm (which should be the same for single-facility firms, or at least the fir m’s line items should not be less than the facility’s). Annual reports are generally considered mo re accurate than survey entries, since they are typically reviewed by more than one person and might even be audited in some cases. Tax returns are also granted greater consideration than surv ey responses. The following documents the changes made to survey data based on reviews of firm-l evel financial statements.

• The reported depreciation for one facility was greater than that listed in the firm’s annual report. For this facility, we replaced the facility depre ciation with that reported at the firm

level.

• For one facility, none of the facility numbers in Qu estions B-43 or B-44 could be reconciled with the firm-level financial information, and the facility information provided did not seem reasonable given the financial statements provided. We determined that the annual report numbers should be used instead for the facility and the firm.

• For one facility, only one year’s total cost in Questi on B-44 did not match the firm’s financial statement submission (all other year’s costs matched), so ERG used the total cost reported in the financial statement to replace t he questionable cost in that year.

• For one facility, we determined that the facility’s re ported costs did not, in fact, include depreciation by comparing the survey-reported costs with the financial statements. This observation allowed us to modify the calculation of ca sh flow for this one facility to accommodate this difference in reporting.

Once all numbers were confirmed to be reasonable and addin g properly, an ERG analyst hand

entered the numbers into the economic model. A second analyst reviewed the transcribed numbers, and the lead analyst reviewed any final changes mad e to the numbers.

ERG imputed financial line item data for two facilities and one firm for certain years. One of the facilities had been purchased in 2008, so no data were availa ble for 2005, 2006, and 2007. Since the facility was previously operational, ERG used the ave rage percent change in costs and revenues for all other facilities in that facility’s processing center between 2008 and 2007 and 2007 to 2006 to estimate costs and revenues for the facility with missing data. For the other facility (and its firm), data were missing from 2005 and 2006. For this firm and facility, for reasons provided in ERG’s CBI results memo, 7 

### the firm’s (and facility’s) 2007 financial data were used as a proxy for 2005 and 2006 financial data.

7 ERG, 2011. Final Costs and Impact Analysis for Alaska Seafood Processors (Facilities and Firms). CBI document

, draft dated August 8, 2011

### 17



### Interest rates, requested in Question A-16, were missing fo r a few firms. OMB 8 

### provides a recommended discount rate of 7 percent, which is routinely used in economic analysis when

interest rates are not available or are considered out of line with market rates. The OMB rate is generally higher than the real rates charged by lending inst itutions at the time of the survey, so using the OMB rate yields a higher estimate of the cos t of capital (that is, results in higher estimates of impacts) than had the average interest ra te for all firms been used instead.

Additionally, a couple of firms did not provide their corp orate structure. For these firms, we assigned the corporate structure that resulted in the lowest assumed marginal tax rate because the lower the marginal tax rate, the higher the estimate of the post-tax cost of compliance would be, thereby avoiding the possibility of underestimating aggregat e costs and impacts.

8 OMB, 2003. Office of Management and Budget (OMB), 2003. Circular A-4, Subject: Regulatory Analysis,

November.

### 18 

### ATTACHMENT A:

RANGE AND LOGIC CHECK TABLES19Table 1 - Range and Logic Checks for Questionnaire Part AQuestionDependantQuestionsTopicConsistency CheckMinMaxYesNoPriorityCompletionQualityIssues/Notes IdentifiedQuery/TableNameA1 Contact Info NA NA 9/9 A01:Q1-5A2 Ownership TypeIf "Yes" A3-A11should be completedNA NA4* 3 High 7/9EC Phillips and Snug Harbor didnot answer 3/4 "Yes" were fromMaruha Nichiro003-A2-11A3 Ownership NA NA 4/4 003-A2-11A4 Business Type NA NA 4/4 003-A2-11A5 Accounting Reports NA NA 3 1 4/4 003-A2-11A6 State NA NA 4/4 003-A2-11A7 Highest Corporate NA NA 3 1 4/4 003-A2-11A8 Corp Contry NA NA 3/3 003-A2-11A9 NAICS NA NA0/4 Poor Completion Quality 003-A2-11A10 Total Employment 7 2988 3/4 003-A2-11A11 Total Revenue10Mil 9.97 Bil 3/4 003-A2-11A12FishingVesselsOwned 0 10 7/9 001-A12A12 Barges Owned 0 2 7/9 001-A12A12 Scows Owned 0 1 7/9 001-A12A12 Tugs Owned 0 0 7/9 001-A12A12ProcessingVesselsOwned 0 5 7/9 001-A12A13BusinessOrganization NA NA 9/9 004-A13-15A14 State of Legal Entity NA NA 9/9 All are Alaska 004-A13-15A15 Fiscal Year NA NA 9/9 All start in Jan 004-A13-15A16 Interest Rate 2% 8% 9/9 0002-A16-19A17 Accounting Reports NA NA 9 0 High 9/9 0002-A16-19A18 Single FacilityIf "No" A19-A21should be completedNA NA 54* 9/9 0002-A16-19A19 US Facilities 2 102/4 Poor Completion Quality 0002-A16-19A19 US Employees 213 5162/4 Poor Completion Quality 0002-A16-19A20 Revenues0.2Mil 405 Mil High 5/4Copper River completed butanswered "Yes" in A18 A04:Q20A21 Operating Costs16Mil 424 Mil High 5/4Copper River completed butanswered "Yes" in A18 A05:Q21*Number of Answers expected on dependent Questions20Table 2 - Range and Logic Checks for Questionnaire Part B -High PriorityQuestionDependantQuestionsTopicConsistency CheckMinMaxYesNoPriorityCompletionQualityIssues/NotesIdentifiedQuery/Table NameB1 Facility Name NA NA 10/10 005-B1-4HighB2 Lat/Long NA NA 10/10 005-B1-4HighB3 NPDES# NA NA 10/10 005-B1-4HighB4 Contact Info NA NA 10/10 005-B1-4HighB5 ProductsIf answer is "only2ndary products"survey is complete NA NA High 10/103/10 producedbyproducts too -None where onlysecondary 006-B5-8HighB6 Type of FacilityIf answer is "Offshore Vessel" surveyis complete NA NA 10/10All are shorebased 006-B5-8HighB7Year OperationsBegan 1996 1904 10/10 006-B5-8HighB8 Capacity (lbs/day) 120,000 6,798,238 High 10/10 006-B5-8HighB9 Expansion 0 500,000 7/10 007-B9HighB10Type of MarineLifeAnswer should beconsistent with B11-B13, B18, B24 NA NA High 10/10008-B10-11HighSpeciesB11 lbs Processed/yrSeequery See query High 10/10Completion forall years is good008-B10-11High-2005008-B10-11High-2006008-B10-11High-2007008-B10-11High-2008008-B10-11High-2009B12Average lbsprocessed/daySeequery See query High 10/10total of 33unique speciesby facility 009-B12HighB13 Peak ProductionSeequery See query High 10/10total of 32unique speciesby facility 010-B13HighB14SecondaryByproductsIf answer is "Yes"B15-B22 should becompleted NA NA3* 6 9/10 011-B14-19HighB15When Byproductbegan 2009 1974 3/3 012-B15-19HighB16ByproductCapacity240000lbs/day 960000lbs High 3/3units areinconsistent 012-B15-19High21QuestionDependantQuestionsTopicConsistency CheckMinMaxYesNoPriorityCompletionQualityIssues/NotesIdentifiedQuery/Table NameB17 Why Byproducts NA NA 2/3 012-B15-19HighB18Production bytype&year 145 706000 High 3/31 facility did notprovide days ofoperation 012-B15-19HighB19RawMaterials/Waste 1750000 11310738 3/3 012-B15-19HighB20Accept from otherfacilityIf answer is "Yes"B21-B22 should becompleted NA NA2* 8 10/10 013-B20,22,23HighB21Distance/Transportation 0 1.5 0/2 B12:Q21B22Cost ofTransportation 20 20 1/2neither providedannual cost 013-B20,22,23HighB23 Process Schematic NA NAHigh 10/10 013-B20,22,23HighB24Percent toproduct/waste NA NA High 10/10 014-B24HighB25WastewaterDisposal method NA NA 10/10All dischargethrough outfall(Inconsistentwith 1 sewerdischarge)015-B25aHigh015-B25bHighB26Volume of waste tooutfall (gpd) 025.06million High 9/10EC Phillipsprovided no data3 other facilitiesdid not provideyear 016-B26HighB27 Solids SeparationsIf answer is "Yes"B28-B34 should becompleted NA NA2* 8 10/10Ocean Beauty-AKG520494should be a"Yes" 017-B27-31HighB28 Storage Capacity 0 40,000 lbs 2/2 017-B27-31HighB29SolidsManagement NA NA 2/2 017-B27-31HighB30Vessel used forSolids Transport NA NA 2/2 017-B27-31HighB31Location ofdisposal site NA NA 2/2 017-B27-31HighB32 Unable to Haul NA NA 0 2 2/2Assume blankanswer is a "No" B17:Q3222QuestionDependantQuestionsTopicConsistency CheckMinMaxYesNoPriorityCompletionQualityIssues/NotesIdentifiedQuery/Table NameB33Accept waste fromother facility NA NA 1 2 2/2 018-B33-37HighB34Use of separatecompany fordisposal NA NA 0 2 2/2 018-B33-37HighB35Use of separatecompany fortransport NA NA 0 10 10/10 018-B33-37HighB36Sufficient DockSpace NA NA 2 8 10/10 018-B33-37HighB37% ofshoreline/dockspace used35%Dock0%Shore100%Dock100%Shore 10/10 018-B33-37HighB38Distance to OffsiteByproduct 0 mi 713 mi 8/10 019-B38-41HighB39Long termagreements NA NA 5 3 8/10 019-B38-41HighB40Dormant Facilities NA NA 8/10Alaska ProteinRecovery wasthe only dormantfacility 019-B38-41HighB41Facilities in theNear Future NA NA 0 8 8/10 019-B38-41HighB42Financial Contact NA NA 10/10 020-B42,46,47HighB43RevenuesSeequery See query 10/10 021-B43,44HighB44Operating CostsSeequery See query 10/10 021-B43,44HighB45Employees totalSeequery See query 9/10 022-B45HighB46Employees duringpeak 63 530 9/10 020-B42,46,47HighB47Max Labor Hours 24 8332 9/10 020-B42,46,47High*Number of Answers expected on dependent Questions23Table 3 - Range and Logic Checks for Questionnaire Part B -Medium PriorityQuestionDependantQuestionsTopicConsistencyCheckMinMaxYesNoPriorityCompletionQualityIssues/NotesIdentifiedQuery/Table NameB1 Facility Name NA NA 8/8 005-B1-4MedB2 Lat/Long NA NA 8/8 005-B1-4MedB3 NPDES# NA NA 8/8 005-B1-4MedB4 Contact Info NA NA 7/8 005-B1-4MedB5 ProductsIf answer is "only2ndary products"survey is complete NA NA High 7/83/seafoodonly, 1/secbyproductonly, 3/both 006-B5-8MedB6 Type of FacilityIf answer is "Off-shore Vessel"survey is complete NA NA 6/8All are shorebased 006-B5-8MedB7Year OperationsBegan 2002 1910 6/8 006-B5-8MedB8 Capacity (lbs/day) 300000 2000000 High 7/8 006-B5-8MedB9 Expansion 50000 600000 4/8 007-B9MedB10 Type of Marine LifeAnswer should beconsistent withB11-B13, B18,B24 NA NA High 6/8AKG520483-Snug Harbordid notprovideproductioninformation008-B10-11MedSpeciesB11 lbs Processed/yrSeequery See query High 6/8Completionfor all yearsis good008-B10-11Med-2005008-B10-11Med-2006008-B10-11Med-2007008-B10-11Med-2008008-B10-11Med-2009B12Average lbsprocessed/daySeequery See query High 7/8total of 26uniquespecies byfacility 009-B12MedB13 Peak ProductionSeequery See query High 7/8total of 26uniquespecies byfacility 010-B13MedB14SecondaryByproductsIf answer is "Yes"B15-B22 should becompleted NA NA3* 4 7/8 011-B14Med24QuestionDependantQuestionsTopicConsistencyCheckMinMaxYesNoPriorityCompletionQualityIssues/NotesIdentifiedQuery/Table NameB15When Byproductbegan 2007 1974 3/3 012-B15-19MedB16 Byproduct Capacity30tons/yr 800000lbs/day High 3/3units areinconsistent 012-B15-19MedB17 Why Byproducts NA NA 3/3 012-B15-19MedB18Production bytype&year 65 17445791 High 3/3 012-B15-19MedB19RawMaterials/Waste 8074463 194107612 2/3Snug Harborstated theygenerated 0 012-B15-19MedB20Accept from otherfacilityIf answer is "Yes"B21-B22 should becompleted NA NA0* 7 7/8 013-B20,22,23MedB21Distance/Transportation 0/0 B12:Q21B22Cost ofTransportation 0/0 013-B20,22,23MedB23 Process Schematic NA NA High 7/8 013-B20,22,23MedB24Percent toproduct/waste NA NA High 7/8B25WastewaterDisposal method NA NA 7/8All dischargethroughoutfall (noinconsistencies)015-B25aMed015-B25bMedB26Volume of waste tooutfall (gpd) 0 2.62 Million High 6/8Snug Harborprovided nodata 016-B26MedB27 Solids SeparationsIf answer is "Yes"B28-B34 should becompleted NA NA6* 1 7/8 017-B27-31MedB28 Storage Capacity 0 300000 lbs 5/6 017-B27-31MedB29 Solids Management NA NA 6/6 017-B27-31MedB30Vessel used forSolids Transport NA NA 6/6 017-B27-31MedB31Location of disposalsite NA NA 2/6 017-B27-31Med25QuestionDependantQuestionsTopicConsistencyCheckMinMaxYesNoPriorityCompletionQualityIssues/NotesIdentifiedQuery/Table NameB32 Unable to Haul NA NA 0 6 6/6Assume noanswer is a"No" B17:Q32B33Accept waste fromother facility NA NA 0 6 6/6 018-B33-37MedB34Use of separatecompany fordisposal NA NA 0 6 6/6 018-B33-37MedB35Use of separatecompany fortransport NA NA 0 7 7/8 018-B33-37MedB36Sufficient DockSpace NA NA 1 6 7/8 018-B33-37MedB37% of shoreline/dockspace used50%Dock0%Shore100% Dock100% Shore 7/8 018-B33-37MedB38Distance to OffsiteBy producty 1 Mi 150 Mi 6/8 019-B38-41MedB39Long termagreements NA NA 2 4 6/8 019-B38-41MedB40Dormant Facilities NA NA 6/8 None known 019-B38-41MedB41Facilities in the NearFuture NA NA 0 6 6/8 019-B38-41MedB42Financial Contact NA NA 7/8 020-B42,46,47MedB43RevenuesSeequery See query 7/8 021-B43,44MedB44Operating CostsSeequery See query 7/8 021-B43,44MedB45Employees totalSeequery See query 7/8 022-B45MedB46Employees duringpeak 63 674 7/8 020-B42,46,47MedB47Max Labor Hours 756 8000 7/8 020-B42,46,47Med*Number of Answers expected on dependent Questions26Table 4 - Range and Logic Checks for Questionnaire Part B -Low PriorityQuestionDependantQuestionsTopicConsistencyCheckMinMaxYesNoPriorityCompletionQualityIssues/NotesIdentifiedQuery/Table NameB1 Facility Name NA NA 33/33 005-B1-4LowB2 Lat/Long NA NA23/33Many areVessels 005-B1-4LowB3 NPDES# NA NA 33/33 005-B1-4LowB4 Contact Info NA NA 33/33 005-B1-4LowB5 ProductsIf answer is"only 2ndaryproducts"survey iscomplete NA NA High 31/3323/seafoodonly, 1/secbyproductonly, 7/both 006-B5-8LowB6 Type of FacilityIf answer is"Off-shoreVessel"survey iscomplete NA NA 30/33All are shorebased 006-B5-8LowB7Year OperationsBegan 2009 1895 31/33 006-B5-8LowB8 Capacity (lbs/day) 140000 3000000 High 28/33 006-B5-8LowB9 Expansion 0 350000 12/33 007-B9LowB10Type of MarineLifeAnswershould beconsistentwith B11-B13, B18,B24 NA NA High 30/33008-B10-11LowSpeciesB11 lbs Processed/yr See query See query High 30/33008-B10-11Low-2005008-B10-11Low-2006008-B10-11Low-2007008-B10-11Low-2008008-B10-11Low-2009B12Average lbsprocessed/day See query See query High 29/33Alaska Glacier- AK520528had all zerostotal of81uniquespecies &facility 009-B12Low27QuestionDependantQuestionsTopicConsistencyCheckMinMaxYesNoPriorityCompletionQualityIssues/NotesIdentifiedQuery/Table NameB13 Peak Production See query See query High 30/33total of 79unique speciesby facility 010-B13LowB14SecondaryByproductsIf answer is"Yes" B15-B22 shouldbecompleted NA NA5* 24 29/33 011-B14LowB15When Byproductbegan 1998 1987 5/5 012-B15-19LowB16ByproductCapacity 6hours 2640000lbs/day High 5/5units areinconsistent 012-B15-19LowB17 Why Byproducts NA NA 4/5 012-B15-19LowB18Production bytype & year 125811 28546920 High 5/5 012-B15-19LowB19RawMaterials/Waste 1036390 428362333 5/5 012-B15-19LowB20Accept from otherfacilityIf answer is"Yes" B21-B22 shouldbecompleted NA NA0* 31 31/33 013-B20,22,23LowB21Distance/Transportation (miles) 0/0 B12:Q21B22Cost ofTransportation 0/0 013-B20,22,23LowB23ProcessSchematic NA NA High 30/33 013-B20,22,23LowB24Percent toproduct/waste NA NA High 30/33 014-B24LowB25WastewaterDisposal method NA NA 29/335 did notdischarge atoutfalls, 2dischargethrough sewer(3inconsistenciesand 1municipalitynot provided)015-B25aLow015-B25bLow28QuestionDependantQuestionsTopicConsistencyCheckMinMaxYesNoPriorityCompletionQualityIssues/NotesIdentifiedQuery/Table NameB26Volume of wasteto outfall 0 59.24 million High 30/3313 facilitiesdid not provideyear 016-B26LowB27 Solids SeparationsIf answer is"Yes" B28-B34 shouldbecompleted NA NA7* 23 30/33MaruhaNichiroAK0052388should be a"yes" 017-B27-31LowB28 Storage Capacity 0 800000 lbs 4/7 017-B27-31LowB29SolidsManagement NA NA 6/7 017-B27-31LowB30Vessel used forSolids Transport NA NA 7/7 017-B27-31LowB31Location ofdisposal site NA NA 3/7 017-B27-31LowB32 Unable to Haul NA NA 1 6 7/7Assume noanswer is a"No"Only AlaskaGlacier -AKG520528indicated nohauling B17:Q32B33Accept wastefrom other facility NA NA 0 7 7/7 018-B33-37LowB34Use of separatecompany fordisposal NA NA 0 7 7/7 018-B33-37LowB35Use of separatecompany fortransport NA NA 0 31 31/33 018-B33-37LowB36Sufficient DockSpace NA NA 5 26 31/33 018-B33-37LowB37% ofshoreline/dockspace used0% Dock0% Shore100% Dock100% Shore 31/33 018-B33-37LowB38Distance toOffsite Byprod 1 Mi 792 Mi 26/33 019-B38-41LowB39Long termagreements NA NA 2 24 26/33 019-B38-41Low29QuestionDependantQuestionsTopicConsistencyCheckMinMaxYesNoPriorityCompletionQualityIssues/NotesIdentifiedQuery/Table NameB40DormantFacilities NA NA 26/33 None known 019-B38-41LowB41Facilities in theNear Future NA NA 0 26 26/33 019-B38-41LowB42FinanacialContact NA NA 30/33 020-B42,46,47LowB43Revenues See query See query 29/33 021-B43,44LowB44Operating Costs See query See query 29/33 021-B43,44LowB45Employees total See query See query 26/33Copper RiverAncorage LeftBlank 022-B45LowB46Employees duringpeak 40 970 27/33 020-B42,46,47LowB47Max Labor Hours 431.25 13900 27/33 020-B42,46,47Low*Number of Answers expected on dependent Questions

### 30



### Table 5 - List of Companies and Facilities Included in the Range and Logic Checks

Companies Checked for Questionnaire Part A

Icicle
Ocean Beauty

Alaska Glacier
EC Phillips

Maruha Nichiro

Maruha Nichiro

Maruha Nichiro
Snug Harbor
Copper River
Facilities Checked for Questionnaire Part B - High Prio rity
Company Name Plant/Vessel Name (Part B) Permit Number Facil ity Location

1-Trident Trident - Cordova South Plant AKG520491 Cordova
1-Trident Trident / Norquest - Petersburg Plant AKG520476 Petersburg
1-Trident Trident / Norquest - Ketchikan AKG520132 Ketchi kan
1-Trident Trident - Ketchikan Cannery AKG520002 Ketchikan

1-Trident Trident - Cordova North AKG520493 Cordova
2 - Icicle Icicle Seafoods - Petersburg Fisheries A KG520303 Petersburg
3 - Ocean Beauty Ocean Beauty Seafoods - Cordova AKG520494 Cordova
3 - Ocean Beauty Ocean Beauty Seafoods - Petersburg AKG520477 Petersburg
6 - EC Phillips E.C. Phillips and Sons AKG520001 Ketchikan
9 - Copper River Copper River - Cordova AKG520524 Cordova

Total 10 Facilities

Facilities Checked for Questionnaire Part B - Medium P riority
Company Name Plant/Vessel Name (Part B) Permit Number Facil ity Location
1-Trident Trident - Kodiak (vessel) AKG528833 Kodiak

2 - Icicle Icicle - Seward Fisheries AKG520488 Sewa rd
3 - Ocean Beauty Ocean Beauty Seafoods - Nikiski AKG520402 Kenai Peninsula
3 - Ocean Beauty Ocean Beauty Seafoods - Kodiak Plant (Gibs on Cove) AKG528486 Kodiak
3 - Ocean Beauty Ocean Beauty Seafoods - Kodiak Facility AKG528493 Kodiak

7 - Maruha Nichiro Westward - Dutch Harbor AK0049786 Dut ch Harbor

7 - Maruha Nichiro Westward - Kodiak AKG528825 Kodiak
8 - Snug Harbor Snug Harbor Seafoods AKG520483 Kenai Peninsula

Total 8 Facilities
Facilities Check for Questionnaire Part B - Low Priori ty Company Name Plant/Vessel Name (Part B) Permit Number Facil ity Location
1-Trident Trident / Norquest - Chignik AKG520103 Chignik
1-Trident Trident – Chignik Plant AKG520053 Chignik

1-Trident Trident – North Naknek AKG520003 Naknek

1-Trident Trident - Akutan AK0037303 Akutan

1-Trident Trident - Sand Point AK0052787 Sand Point
1-Trident Trident -Wrangell AKG520058 Wrangell

1-Trident Trident - St. Paul AKG527702 St Paul
1-Trident Trident / Norquest - M/V Pribilof AKG520096 off shore
1-Trident Trident / Norquest - Aleutian Falcon AKG520253 offshore
1-Trident Trident - M/V Independence AKG520100 offshore
1-Trident Trident / Norquest - Petersburg STB Mitkof AKG 520475 Petersburg

1-Trident Trident - M/V Alaska Packer AKG520052 offshore
2 - Icicle Icicle - Egegik Plant AKG520048 Egegik

### 31 Facilities Check for Questionnaire Part B - Low Priori ty Company Name Plant/Vessel Name (Part B) Permit Number Facil ity Location

2 - Icicle Icicle - Larsen AKG520047 Larsen
2 - Icicle Icicle - P/V Discovery Star AKG520163 off shore

2 - Icicle Icicle - P/V Northern Victor AKG520533 of fshore
2 - Icicle Icicle - P/V Bering Star AKG520082 offshore

2 - Icicle Icicle - P/V Arctic Star AKG520062 offsho re 2 - Icicle Icicle - RM Thorstenson, Pribilof Islands AK0053520 offshore
2 - Icicle Icicle - Northern Victor, Udagak Bay AK005286 8 offshore

2 - Icicle Icicle - P/V Arctic Star, Pribilof Islan ds AK0053503 offshore
3 - Ocean Beauty Ocean Beauty Seafoods - Alitak AKG520036 Alitak
3 - Ocean Beauty Ocean Beauty Seafoods - Excursion Inlet AKG520059 Excursion Inlet
3 - Ocean Beauty Ocean Beauty Seafoods - Naknek AKG520092 Naknek
7 - Maruha Nichiro Alyeska Seafoods, Inc AK0000272 Unala ska
7 - Maruha Nichiro Peter Pan - King Cove AK0052388 Kin g Cove
7 - Maruha Nichiro Peter Pan Seafoods - Dillingham AK G520012 Dillingham

7 - Maruha Nichiro Peter Pan Seafoods - Port Moller AKG520014 Port Moller

7 - Maruha Nichiro Peter Pan Seafoods - Valdez AKG520244 Valdez
7 - Maruha Nichiro Supreme Alaska Seafoods - M/V Excellen ce AKG520333 offshore

5 - Alaska Glacier Alaska Glacier Seafoods AKG520528 Petersb urg 6 - EC Phillips E.C. Phillips and Sons – Craig Fisheries AKG520445 Craig

9 - Copper River Copper River - Anchorage No Permtit - to City Sewer Anchorage

Total 33 Facilities