S UPPORTING S TATEMENT FOR I NFORMATION C OLLECTION R EQUEST FOR W ILLINGNESS TO P AY S URVEY FOR §316( B ) E XISTING F ACILITIES C OOLING W ATER I NTAKE S TRUCTURES : I NSTRUMENT , P RE - TEST , AND I MPLEMENTATIONi TABLE OF CONTENTS

PART A OF THE SUPPORTING STATEMENT

................................ ................................ ......... 1

1. Identification of the Information Collection

................................ ................................ ....... 1 1(a) Title of the Information Collection

................................ ................................ ..................... 1 1(b) Short Characterization (Abstract)

................................ ................................ ....................... 1

2. Need For and Use of the Collection

................................ ................................ .................... 5 2(a) Need/Authority for the Collection

................................ ................................ ...................... 5 2(b) Practical Utility/Users of the Data

................................ ................................ ...................... 5

3. Non

- duplication, Consultations, and Other Collection Criteria

................................ .......... 6 3(a) Non

- duplication

................................ ................................ ................................ .................. 6 3(b) Public Notice Required Prior to I CR Submission to OMB

................................ ................ 7 3(c) Consultations

................................ ................................ ................................ ..................... 13 3(d) Effects of Less Frequent Collection

................................ ................................ .................. 14 3(e) General Guidelines

................................ ................................ ................................ ............ 14 3(f) Confidentiality

................................ ................................ ................................ .................. 14 3(g) Sensitive Questions

................................ ................................ ................................ ........... 15

4. The Respondents and the Information Requested

................................ ............................ 15 4(a) Respondents

................................ ................................ ................................ ...................... 15 4(b) Informatio n Requested

................................ ................................ ................................ ...... 17 (I) Data items, including recordkeeping requirements

................................ .......................... 17 (II) Respondent activities

................................ ................................ ................................ ........ 21

5. The Information Collected

- Agency Activities, Collection Methodology, and Information Management

................................ ................................ ................................ .............. 21 5(a) Agency Activities

................................ ................................ ................................ .............. 21 5(b) Collection Methodology and Information Management

................................ ................... 22 5(c) Small Entity Flexibility

................................ ................................ ................................ ..... 23 5(d) Collection Schedule

................................ ................................ ................................ .......... 24ii 6. Estimating Respondent Burden and Cost of Collection

................................ ................... 24 6(a) Estimating Respondent Burden

................................ ................................ ......................... 24 6(b) Estimating Respondent Costs

................................ ................................ ........................... 25 6(c) Estimating Agency Burden and Costs

................................ ................................ .............. 25 6(d) Respondent Universe and Total Burden Costs

................................ ................................ . 26 6(e) Bottom Line Burden Hours and Costs

................................ ................................ .............. 26 6(f) Reasons for Cha nge in Burden

................................ ................................ ......................... 26 6(g) Burden Statement

................................ ................................ ................................ .............. 26

PART B OF THE SUPPORTING STATEMENT

................................ ................................ ....... 28

1. Survey Objectives, Key Variables, and Other Preliminaries

................................ ............ 28 1(a) Survey Objectives

................................ ................................ ................................ ............. 28 1(b) Key Variables

................................ ................................ ................................ .................... 28 1(c) Statistical Approach

................................ ................................ ................................ .......... 29 1(d) Feasibility

................................ ................................ ................................ .......................... 29

2. Survey De sign

................................ ................................ ................................ ................... 30 2(a) Target Population and Coverage

................................ ................................ ....................... 30 2(b) Sampling Design

................................ ................................ ................................ ............... 30 (I) Sampling Frames

................................ ................................ ................................ .............. 30 (II) Sample Sizes

................................ ................................ ................................ ..................... 31 (III) Stratification Variables

................................ ................................ ................................ ..... 31 (IV) Sampling Method

................................ ................................ ................................ .............. 32 (V) Multi

- Stage Sampling

................................ ................................ ................................ ....... 33 2(c) Precision Requirements

................................ ................................ ................................ .... 33 (I) Precision Targets

................................ ................................ ................................ ............... 33 (II) Non

- Sampling Errors

................................ ................................ ................................ ........ 34 2(d) Questionnaire Design

................................ ................................ ................................ ........ 36

3. Pretests and Pilot Tests

................................ ................................ ................................ ..... 38

4. Collection Methods and Follow

- up

................................ ................................ .................. 38 4(a) Collection Methods

................................ ................................ ................................ ........... 38iii 4(b) Survey Response and Follow

- up

................................ ................................ ...................... 39

5. Analyzing and Reporting Survey Results

................................ ................................ ......... 39 5(a) Data Preparation

................................ ................................ ................................ ................ 39 5(b) Analysis

................................ ................................ ................................ ............................. 40 5(c) Reporting Results

................................ ................................ ................................ .............. 57

REFERENCES

................................ ................................ ................................ ............................. 59

ATTACHMENTS
Attachment 1: Full Text of Regional Stated Preference Survey Component

............................... 68 Attachment 2: Full Text of National Stated Preference Survey Component

................................ 88 Attachment 3: Federal Register Notice

................................ ................................ ....................... 108 Attachment 4: Description of Statistical Survey Design

................................ ............................ 114 Attachment 5: Description of Internet

- based Sampling Alternative

................................ ........... 119 Attachment 6: Telephone Screener Script

................................ ................................ .................. 123 Attachment 7: Cover Letter to Mail Survey Recipients

................................ .............................. 130
Attachment 8: Post Card Reminder to Mail Survey Recipients

................................ ................. 131

TABLES
Table A1: Geographic Stratification Design

................................ ................................ ................. 16
Table A2: Schedule fo r Survey Implementation

................................ ................................ .......... 24 Table A3: Total Estimated Bottom Line Burden and Cost Summary

................................ .......... 26
Table B1: Number of Households and H ousehold Sample for Each EPA Study Region

............ 34 Table B2: Illustration of an External Scope Test

................................ ................................ ......... 551 PART A OF THE SUPPORTING STATEMENT

1. Identification of th e Information Collection 1(a) Title of the Information Collection

Willingness to Pay Survey for Section 316(b) Existing Facilities Cooling Water Intake Structures: Instrument, Pre

- test, and Implementation

1(b) Short Characterization (Abstract)

On Febr uary 16, 2004, the U.S. Environmental Protection Agency (EPA) took final action on the Phase II rule governing cooling water intake structures at existing facilities that are point sources; that, as their primary activity, both generate and transmit electr ic power or generate electric power for sale to another entity for transmission; that use or propose to use cooling water intake structures with a total design intake flow of 50 MGD or more to withdraw cooling water from waters of the United States; and th at use at least 25 percent of the withdrawn water exclusively for cooling purposes. See 69 FR 41576 (July 9, 2004). Industry and environmental stakeholders challenged the Phase II regulations. On judicial review, the Second Circuit (Riverkeeper, Inc. v. EP A, 475 F.3d 83, (2d Cir., 2007)) remanded several provisions of the Phase II rule. Some key provisions remanded are as follows: EPA improperly used a cost

benefit analysis as a criterion for determining Best Technology Available (BTA), and EPA inappropriat ely used ranges in setting performance expectations. In response, EPA suspended the Phase II regulation in July 2007 pending further rulemaking. The U.S. Supreme Court granted Entergy Corporation’s petition for writ of certiorari, solely on the question of whether EPA had the authority under §316(b) of the Clean Water Act to consider costs and benefits in decision

making. On April 1, 2009, the Court, in Entergy Corp. v. Riverkeeper Inc., decided that “EPA permissibly relied on cost

- benefit analysis in setti ng the national performance standards ... as part of the Phase II regulations.” EPA is now taking a voluntary remand of the rule, thus ending
Second Circuit review.
On June 1, 2006, EPA promulgated the 316(b) Phase III Rule for existing manufacturers,
small flow power plants (facilities that use cooling water intake structures with a total design intake flow of less than 50 MGD to withdraw cooling water from waters of the United States;2 and that use at least 25 percent of the withdrawn water exclusively for c ooling purposes), and new offshore oil and gas facilities. Offshore oil and gas firms and environmental groups petitioned for judicial review, which was to occur in the Fifth Circuit, but was stayed pending the Supreme Court decision on the Phase II case. EPA has petitioned the Court for a voluntar y remand of the existing facilities portion of the Phase III rulemaking. In developing the Phase III regulation, EPA began, but did not complete, a similar stated preference survey effort. The
current effort buil ds on that earlier work. EPA is now combining the two phases into one rulemaking covering all existing facilities. EPA will develop regulations to provide national performance standards for controlling impacts from existing cooling water intake structures (CWIS) under Section 316(b) of the Clean Water Act (CWA). Under Executive Order 12866, EPA is required to estimate the potential benefits and costs to society for economically significant rules . To assess the public policy significance or importance of t he ecological gains from the section 316(b) regulation for existing facilities, EPA requests approval from the Office of Management and Budget to conduct a stated preference

survey

. Data from the stated preference survey will be used to estimate the value s (willingness to pay, or WTP) derived by households for changes related to the reduction of fish losses at
CWIS
, and to provide information to assist in the interpretation and validation of survey

responses . As indicated in the prior literature (Cummings and Harrison 1995; Johnston et al.
2003 a , 2005), it is virtually impossible to justify, theoretically, the decomposition of empirical
estimates of use and non

- use values. The survey will provide the flexibility, however, to estimate nonuser values, using various nonuser definitions drawn from responses to survey question 10 . The structure of choice attribute questions will also allow the analysis to separate value components related to the most common sources of use values

— effect on harvested
recreationa l and commercial fish. In summary, the survey will provide estimates of total values (including use and nonuse) , will allow estimates of value associated with specific choice attributes (following standard methods for choice experiments), and will also al low the flexibility to provide some insight into the relative importance of use versus non

- use values in the 316(b)

context. Within rulemaking, among the most crucial concerns is the avoidance of benefit (or cost) double counting. Here, for example, the W TP estimates will include use and non

- use values among a representative population sample. These may overlap

— to a potentially substantial3 extent

— with use value estimates that might be provided through some other methods, including revealed preference meth ods that might be used to estimate use values of recreational anglers for fish kill reductions (i.e., through related improvements in fishing quality). While using the proposed stated preference value estimates for benefit estimation, particular care will be given to avoid any possible double counting of values that might be derived from alternative valuation methods. In doing so, EPA will rely upon standard theoretical tools for non

- market welfare analysis, as presented by authors including Freeman (2003 ) and Just et al. (2004). From a purely mechanistic perspective, survey results will be used to derive total values following standard practice for choice experiments (Adamowicz et al. 1998). The target population for this stated preference survey is all individuals from continental U.S. households who are 18 years of age or older. The population of households will be
stratified into four study regions: Northeast
, Southeast , Inland, and Pacific. The Northeast survey region includes t he North Atlantic and Mid Atlantic 316(b) benefits regions
, the Southeast

survey region includes t he South Atlantic and Gulf of Mexico 316(b) benefits regions , the Pacific region includes states on the Pacific coast, and the Inland region includes all non

- coastal

states. In ad dition, EPA will administer a national version of the survey that does not require
stratification. R espondents will be recruited using a random digit dialing ( RDD ) sample (overlapping dual frame; land and cell phone numbers ) and a brief telephone question naire. Participation in the survey is voluntary. If the person in the household agrees, the r ecruited respondent will be asked to complete the survey questionnaire by mail. EPA intends to administer the mail survey to 5, 720 households in order to achieve 2, 288 completed responses assuming a 40% completion rate for households agreeing to participate. EPA is also considering implementing the proposed survey as an internet

- based, choice experiment questionnaire. This alternative approach is described in At tachment 5

. For the selection of households, the population of households in the 48 states and the
District of Columbia will be stratified by the four study regions. The sample is allocated to each region in proportion to the total number of households in that region with the restriction that we get at least 288 completed responses in each region. A sample of 288 households completing the national survey version would be distributed among the study regions based on the percentage of regional survey sample to ensure that respondents to the national survey version are distribu ted
across the continental U.S. Non

- response bias has the potential to occur due to households declining to participate in the mail survey when contacted by phone or households which fa il to4 return a completed survey after agreeing to participate. To conduct a non

- response study, EPA
will use a brief telephone questionnaire to collect sample characteristics in the course of the telephone contact. EPA will analyze the characteristics of the completed and non

- completed cases from the random digit dialing sample to determine whether there is any evidence of significant non

- response bias in the completed sample. This analysis will suggest whether any weighting or statistical adjustment is necessary to minimize the non

- response bias in the completed sample

. As part of the testing of the survey instrument , EPA conducted a series 7 focus groups
with 8

- 10 participants per focus group
, with approval from the Office of Management and Budget ( OMB control # 2090

- 0028 ). The Agency conducted focus group s in several regions to account for the potentially distinct information relevant to survey design. These focus groups

were conducted following standard, accepted practices in the stated preference li terature, as outlined by Mitchell and Carson (1989), Desvousges et al. (1984), Desvousges and Smith (1988) and Johnston et al. (1995). One of the focus groups incorporated individual cognitive interviews, as detailed by Kaplowicz et al. ( 2004). The focus groups and cognitive interviews allow ed EPA to better understand the public's perceptions and attitudes concerning fishery resources, to frame and define survey questions, to pretest draft survey questions, to test for and reduce potential biases that may be associated with stated preference methodology, and to ensure that both researchers and respondents have similar interpretations of survey language and scenarios. In particular, cognitive interviews allowed for in

- depth exploration of the cognitive pro cesses used by respondents to answer survey questions, without the potential for interpersonal dynamics to sway respondents’ comments (Kaplowicz et al. 2004). Transcripts from these seven focus groups can be found in the docket for this ICR (ICR # 2402.01 ). EPA revised the survey based on the findings of the seven focus groups. These seven focus groups were conducted in addition
to f ocus groups conducted previously by EPA under ICR #2155.01 to test the draft survey for the Phase III benefits analysis . T ranscripts from the previously conducted focus groups for the Phase III analysis can be found in the docket for EPA ICR #2155.02 (Besedin et al., 2005)

. Findings from these previous focus groups were also incorporated into the development of the

current s urvey. The total national burden estimate for all components of the survey is 1, 938 hours. The
burden estimate is based on 9,533 participants in telephone screening interviews and 2, 288 respondents to the 5, 720 mailed questionnaires. EPA assumes an ave rage burden estimate of 55 minutes per telephone screening participant and 30 minutes per mail survey respondent including the time necessary to complete and mail back the questionnaire. Given an average wage rate of $ 20

. 42 , the total respondent cost is $ 3 9,583

.

2. Need For and Use of the Collection 2(a) Need/Authority for the Collection

The project is being undertaken pursuant to section 104 of the Clean Water Act dealing
with research. Section 104 of the Clean Water Act authorizes and directs the EPA Administrator to conduct research into a number of subject areas related to water quality, water pollution, and water pollution prevention and abatement. This section also authorizes the EPA Administrator to conduct research into method s of analyzing the costs and benefits of programs carried out under
the Clean Water Act. This project is exploring how public values for fishery resources are affected by fish losses from impingement and entrainment (I&E) mortality at cooling water intake structures. Understanding total public values for fishery resources , including the more difficult to estimate

non

- use values 1 , is necessary to determine the full range of benefits associated with reductions in I&E mortality losses, and whether the benefit s of government action to reduce I&E mortality
losses at existing facilities are commensurate with the costs of such actions. Because non

- use values may be substantial, failure to recognize such values may lead to improper inferences regarding benefits and costs. The findings from this study will be used by EPA to improve estimates of the economic benefits of the section 316(b) regulation for existing facilities as required under Executive Order 12866

.

2(b) Practical Utility/Users of the Data

EPA plans t o use the results of the survey to improve estimates of the economic benefits of the section 316(b) regulation for existing facilities. Specifically, the Agency will use the survey results to estimate total values for preventing losses of fish through I&E mortality at CWIS, following standard practices outlined in the literature (Freeman 2003; Bennett and Blamey 2001; Louviere et al. 2000; U.S. EPA 2000).

1 The stated preference format was chosen because it is the only method that allows t he estima tion of non

- use values, which are potentially significant in this case.6 3. Non

- duplication, Consultations, and Other Collection Criteria 3(a) Non

- duplication

There are ma ny studies in the environmental economics literature that quantify benefits or willingness to pay (WTP) associated with various types of water quality and aquatic habitat changes. However, none of these studies allows the isolation of non

- market WTP associ ated with quantified reductions in fish losses for forage fish. Most available studies estimate WTP for broader, and sometimes ambiguously defined, policies that simultaneously influence many different aspects of aquatic environmental quality and ecosyste m services, but for which WTP associated with fish or aquatic life alone cannot be identified. Other studies provide benefit estimates associated with improvements in fish (or aquatic) habitat, but do not link this to well

defined and quantified changes i n affected or supported organisms. Still other studies address willingness to pay for changes in charismatic or recreational species that have little relationship to the types of forage fish that are the vast majority of species affected by cooling water intake

structures. For example, choice experiment studies such as Hanley et al. (2006a, 2006 b) and Morrison and Bennett (2004) estimate WTP for aquatic ecosystem changes that affect fish, but
the effects on fish are quantified and valued solely in terms of the presence/absence of different types of fish species. This approach renders associated results unsuitable for 316(b) benefit estimation. Also, many of these studies were conducted outside the U.S. (e.g., the European
Union or Australia), making their use for benefit transfer to a U.S. policy context more challenging. Other studies have estimated the value of changes in catch rates or populations of select recreational and commercial species, charismatic species such as salmon, or changes in water quali ty that affect fish, but none have specifically valued changes in forage fish populations. For example, Olsen et al. (1991) conducted a survey of Pacific Northwest residents, including both anglers and non

- anglers, to determine their WTP for doubling the s ize of the Columbia River Basin salmon and steelhead runs. EPA’s proposed survey approach differs from this study and others like it (such as Cameron and Huppert 1989) in that it would include respondents from various geographic regions in the United Stat es and would provide values for the full range of7 forage, recreational, and commercial species affected by 316(b) regulations, instead of valuing a few recreational species in one specific geographical area. Among available studies, the most closely relate d is Johnston et al. (20 10 ), which estimates total willingness to pay (WTP) for multi

- attribute aquatic ecosystem changes related to improvements in forage fish in Rhode Island . Unlike other studies, the choice experiment data of Johnston et al. (20 10 ) all ow estimation of WTP associated with quantified changes in forage fish (e.g., WTP per fish or percentage change in fish), holding other ecological effects constant. That is, unlike results provided by other studies in the literature, WTP estimates of John ston et al. (20 10 ) are not confounded with values for other changes including water quality, habitat, overall ecological condition, charisma of species, etc. In addition, the choice experiment of Johnston et al. (20 10 ) addresses species such as alewife and blueback herring that are neither subject to recreational or commercial harvest in Rhode Island, nor are charismatic species. Hence, the species affected are a close analog to the forage fish affected in the 316(b) policy context. Although the methods an d data of Johnston et al. (20 10 ) allow estimation of total values associated with specific improvements in forage and/or recreational fish, the policy context and
scale of the survey prevent its direct use for analysis of national benefits of the 316(b) re gulation. Specifically, Johnston et al. (20 10 ) estimate Rhode Island residents’ preferences for the restoration of migratory fish passage over dams in the Pawtuxet and Wood

- Pawcatuck watersheds. Hence, the case study is for a watershed

- level policy with s tatewide welfare implications. In contrast, 316(b) policies would have nationwide implications, both on ecosystems and on affected facilities.

3(b) Public Notice Required Prior to ICR Submission to OMB

In accordance with the Paperwork Reduction Act (4 4 U.S.C. 3501 et seq.), EPA published a notice in the Federal Register on July 21 , 20 10
, announcing that the survey questionnaire and sampling methodology were available for comment. A copy of the first Federal Register notice is attached at the end of th is document ( EPA ICR #2 402.01 .02) (See
Attachment 3 ) . EPA received a number of comments on the proposed information collection, which are summarized in the following paragraphs. Also see docket # EPA

- HQ

- OW

- 2010

- 0595

. EPA considered relevant comments on the draft survey when developing the survey questionnaire and sampling methodology for the current survey for existing facilities.8 Some c ommenters expressed concern that the draft survey questionnaire and sampling methodology would not provide accurate e stimates of WTP. Some stated that the proposed stated preference survey would overestimate WTP to prevent fish losses. A nother commenter argued the opposite: that the proposed contingent valuation survey is biased against protecting ecosystems, and will drastically undervalue non

- use benefits. EPA agrees that certain details of the stated preference survey and supporting documentation for the July 21, 2010 Federal Register notice required revision. Following OMB approval of the focus groups, EPA conduc ted seven focus groups ( including one set of cognitive interview s ) to pretest the draft survey materials, to test for and reduce potential biases that may be associated with stated preference methodology, and to ensure that both researchers and respondents have similar interpretations of survey language and scenarios. As a result of this extensive pre

- testing, a number of revisions were
made to the draft survey that significantly improved its reliability and reduced its potential for
bias

. Hence, many of the survey design elements on which commenters took issue have already been removed or changed. In many other instances, however, focus groups showed little cause for concern, suggesting that many of the speculative claims raised by commenters have little value to the population being surveyed

. EPA also notes that number of focus groups and interviews conducted for this survey

— and the draft survey tested in 2005

- 06

— far exceeds the number conducted for most stated preference surveys found in the published literature. EPA notes that the survey proposed in this ICR is different in many ways from the draft survey for the Phase III benefits analysis that was peer reviewed in 2005 (Versar 2006) . While findings from pre

- testing of the previous draft survey wer e considered when developing the present survey, the present survey has undergone various revisions based on additional analysis and the results of recent focus groups. Due to these differences, EPA notes that many of the peer
review comments received on the Phase III draft survey are no longer relevant for the survey proposed in this ICR. The Agency, however, takes all peer review comments very seriously, and has accounted for these comments in all survey revisions and in the development of the present

s tated preference survey. One commenter argue d that in conducting the stated preference survey, EPA should use the willingness

- to

- accept (WTA) metric in place of or in addition to WTP. EPA notes that good practice guidelines for stated preference surveys a lmost universally indicate the use of WTP elicitation mechanisms over WTA elicitation mechanisms. This is due to the potential for biases in WTA stated preference surveys that can be ameliorated by the use of the WTP format. WTP9 is also considered to be t he more conservative choice, but in most cases, the divergence between WTA and WTP, as predicted, by theory, should be very small. EPA follows standard practice in proposing a WTP format in order to avoid these biases, comply with guidance and practice in the stated preference literature, and ensure a conservative benefit estimate.
Some commenter s argued that hypothetical bias in the survey questionnaire would inhibit respondents ability to provide meaningful survey responses. EPA agrees that hypothetical bias is an important concern with stated preference surveys

— and has taken this very seriously in survey development and testing. EPA does not agree that this inhibits respondents or that the literature suggests that hypothetical bias is unavoidable; in f act , the published literature includes approaches to mitigate such biases. The Agency followed the published literature in designing mitigation strategies to eliminate or at a minimum reduce the potential for hypothetical bias. This includes explicitly d esigning the survey to maximize the consequentiality of choice experiment questions through direct linkages to proposed EPA regulatory efforts. Moreover, the survey explicitly incorporates elements such as certainty follow

- up question to enable mitigation of any remaining hypothetical bias (Ready et al. 2010). Focus group and interview transcripts show that, when asked explicitly, respondents almost universally indicated that their answers to choice questions in the survey instrument would be identical if the same questions were encountered in a binding referendum. This indicates that there is little evidence of hypothetical bias within the draft survey. A commenter argued that the respondents to the survey would be informed and
conditioned based on the information included in the survey and that this would lead to the creation of preferences where none existed before. EPA believes that this result is entirely expected, and is consistent with the academic literature. The Agency emphasizes that the
sensi tivity of values (and behavior) to information is true of both market and non

- market values (Bateman et al. 2002, p. 298), and in no way invalidates the proposed non

- market values that would be estimated through the proposed stated preference approaches. It is common practice in such surveys to provide substantial information to survey respondents. The survey information was pretested extensively during the seven focus group sessions and EPA revised or removed
informational ele ments which respondents foun d confusing or misleading.
Some commenters argued that the survey results will be unreliable because the survey questionnaire contains inaccurate statements and comparisons which overstate the resource impacts from baseline I&E mortality and the regulatory options presented in the survey . EPA10 recognizes the importance of accurately characterizing resource and regulatory impacts and notes that the survey is based on the best biological and engineering data available. Despite the general observation that I& E impacts are small compared to other effects, I&E has been shown to have measurable impacts on local fish populations and communities. Importantly, increases in
fisher y sustainability and fish population values presented in the survey instrument are smal l. Overall, the Agency rejects the claims from commenters , based largely on feedback from focus group participants, that impacts are misrepresented, and emphasizes that the survey is explicitly designed to provide respondent s with an understanding of the proposed policies that is as accurate as possible given the best available ecological science.
Commenters also questioned whether survey respondents would have sufficient comprehension of the issues in order to provide meaningful responses to the survey’ s valuation questions. EPA agrees that in order to receive meaningful responses, a stated preference survey should provide information to respondents about the hypothetical commodity so that they understand and accept it and can give mean ingful answers to the valuation questions. Given the importance of commodity comprehension, EPA devoted considerable attention to comprehension of the hypothetical commodity and related issues (e.g., understanding of payment vehicle
, understanding of the ecological scores ) during the recent focus groups and cognitive interviews and focus groups conducted for the original version of the Phase III survey instrument in 2005

. F ocus groups participants showed no difficulty understanding the format of the payment vehicle
and tha t selecting Options A or B would result in inc reased costs to their household . They also correctly understood this cost as ongoing. In addition to the comments regarding the payment vehicle
, commenters expressed

concern regarding respondent comprehension of the ecological scores used in the survey. EPA emphasizes that the reaction and understanding of likely respondents , as opposed to experts, is crucial when testing the communication of ecological information in stated preference surveys. The survey ha s undergone substantial changes in the way it communicates ecological information based on the results of the seven focus group sessions. For example
, in the revised

survey, EPA provides more precise information regarding the definition of “young adult fis h” on Page 4 , which currently states : “After accounting for the number of eggs and larvae that would be expected to survive to adulthood, scientists estimate that the equivalent of about 1.1 billion young adult fish (the equivalent of one year old) are los t each year in Northeast coastal and fresh waters due to cooling water use.” Overall, focus group and interview p articipants’ statements11 implied different opinions about the importance of preventing fish losses versus increasing fish population or improvi ng the condition of aquatic ecosystems. Also, t here did not appear to be any confusion over the fact that scores of 100 for various attributes are generally unattainable through reductions in CWIS fish losses alone. One commenter argues that the stated p reference survey fails to account for effects on a number of non

- fish species as well as effects on threatened, endangered, and other protected species. In response to this comment, EPA agrees but notes that focus group respondents suggested that addition s to the survey’s length should be
avoided

. Thus EPA will not be able to use these survey results to represent absolutely complete benefits estimation, but will be able to say that a potentially substantial category of benefits, non

use benefits, has been included. As is common in surveys, EPA has chosen to present policy scenarios in simplified form to facilitate respondent comprehension, and to encourage respondents to focus on the most important policy characteristics related to fish losses. Such simp lification of the survey helps to balance the provision of detailed policy information against respondents’ cognitive abilities to consider a large number of attributes simultaneously (Louviere et al. 2000).
Some commente rs stated that EPA did not suffic iently emphasize the uncertainty
associated with effects and costs of the proposed policies presented within the survey. EPA agrees that there is uncertainty regarding the number of fish killed annually, as well as the effects and costs of the regulatory policies presented within the survey. Additionally, EPA does note uncertainty within the current existing facilities survey . For example, the following statement s

are included in the current survey version for the Northeast region : “Although scientists c an predict the number of fish saved each year, the effect on fish populations is uncertain. This is because scientists do not know the total number of fish in Northeast water and because many
factors

– such as cooling water use, fishing, pollution, and wa ter temperature

– affect fish populations”, and “Policy costs and effects depend on many factors.” EPA has also included debriefing questions in the survey instrument that are designed to identify individuals whose responses are based on incorrect interpr etation of the environmental changes described in the survey, including the uncertainty of the expected changes. EPA points out that debriefing sessions during focus groups and cognitive interviews showed that respondents clearly
understood that the ecolo gical changes described in the survey were uncertain. Furthermore, when asked, focus group respondents indicated that they were comfortable making decisions in the presence of uncertainty.12 Another commente r questioned various components of EPA proposed sa mpling methodology, experimental design , and methods for accounting for non

- response bias

. In

response, EPA emphasizes that methods for WTP estimation from ecological choice experiment
data

— of exactly the type proposed by EPA

— are very well established in the published literature. More broadly, when designing the proposed methods, EPA closely followed accepted contemporary methods in the published literature for the estimation of WTP distributions under statistical uncertainty. In the absence of concrete and established alternatives for the choice of sampling weights, EPA has proposed a more conservative approach of reliance on accepted and standard methods from the stated preference literature. EPA believes

— following guidance
in the literature and its ow n guidance documents (Arrow et al. 1993; US EPA 2000) for a weighting and extrapolation approach

— that established stated preference methods are capable
of estimating reliable and accurate welfare measures , if surveys and approaches are appropriately design ed

. Regarding the potential for non

- response bias, EPA has proposed standard approaches for non

- response assessments and calibrations in proposing tests and
corrections for non

- response based on a small number of attitudinal and behavioral questions,
comb ined with demographic characteristics. These currently reflect standard practice within the
literature. Another commenter argued that although the Supreme Court held that Clean Water Act section 316(b) does not prohibit the consideration of costs in relat ion to benefits of proposed rule
it did not find that cost benefit analysis is required ( Entergy Corp. v. Riverkeeper, Inc. )

. EPA has the authority to decide whether to conduct cost benefit analysis of proposed rule options

. The commenter, however, recog nized that Executive Order 12866, “Regulatory Planning and Review,” requires EPA to estimate potential costs and benefits to society of proposed rule options. In response to the commenter’s claim about utility of cost

- benefit analysis in
environmental cont ext, EPA notes that cost

- benefit analysis is only one tool that can be used to inform policy decisions. EPA is conducting this survey because of Executive Order 12866, “Regulatory Planning and Review,” which requires Federal Agencies to conduct economic
im pact and cost

- benefit analysis for all major rules. Furthermore, cost

- benefit analysis requires a comprehensive, estimate of total social benefits, including non

- use values. The current information collection would provide valuable information regarding total social benefits of the 316(b) regulation for existing facilities, thus enabling the Agency to perform cost

- benefit13 analysis for the regulation , if it should choose to, without ignoring a potentially important category of benefits (non

- use values), an d to satisfy the requirements of Executive Order 12866. For a more detailed discussion of the issues raised by commenters on this ICR
, see EPA’s response to pubic comments on the Federal Register notice published on November 23, 2004 ( 69
FR 68140 ). For a discussion of the issues raised by commenters on the previous Phase III survey ICR, see EPA’s response to pubic comments on the Federal Register notice published on June 9, 2005 (70 FR 33746). For a discussion of issues raised by commenters on the previou s Phase III focus group ICR, see EPA's response to public comments on the Federal Register notice published on November 23, 2004 (69 FR 68140).

3(c) Consultations The Principal Investigator for the stated

- preference portion of this effort is Dr. Robert
J ohnston. Dr. Johnston is assisted by Dr. Elena Besedin, a Senior Economist at Abt Associates Inc. Dr. Erik Helm at the U.S. Environmental Protection Agency serves as the project manager
and a contributor to this research.
Robert J. Johnston is Director of the George Perkins Marsh Institute and Professor of Economics at Clark University. He is President

- elect of the Northeastern Agricultural and Resource Economics Association (NAREA), on the Program Committee for the Charles Darwin Foundation, the Scien ce Advisory Board for the Communication Partnership for Science and the Sea (COMPASS), and is the Vice President of the Marine Resource Economics Foundation. Professor Johnston has published extensively on the valuation of non

- market commodities (goods, s ervices, and resources), benefit cost analysis, and resource management. His recent research emphasizes coordination of ecological and economic models to estimate ecosystem service values, with particular emphasis on the role of aquatic ecological indicat ors. He has also worked extensively in methodologies for benefit transfer, including the use of meta

- analysis. Professor Johnston’s empirical work on non

- market valuation and benefit transfer has contributed to numerous benefit cost analyses conducted by federal, state and local government agencies in the US, Canada and elsewhere. Elena Y. Besedin, a senior economist at Abt Ass o ciates Inc., specializes in the economic analysis of environmental policy and regulatory programs

. Her work to support EPA has concentrated on analyzing economic benefits from reducing risks to the environment and human health and assessing environmental impacts of regulatory programs for many EPA program14 offices. She has worked extensively on valuation of non

- market benefits ass ociated with environmental improvements of aquatic resources. Dr. Besedin’s empirical work on non

- market
valuation include s design and implementation of stated and revealed preference studies and benefit transfer methodologies. Her recent work has focuse d on developing integrated frameworks to value changes in ecosystem services stemming from environmental regulations.
EPA notes that the current survey instrument is built upon an earlier version that was peer reviewed in January 2006. It incorporates rec ommendations received from the first peer review panel. Because the final product of this study meets the major technical work criteria specified in the Peer Review Handbook (U.S. EPA 200 6 ) the Agency also plans to convene a peer

- review panel to review th e entire survey process, including the survey instrument, study results, and EPA’s final estimated results for the 316(b) Existing Facilities rulemaking, after the survey is completed. 3(d) Effects of Less Frequent Collection

The survey is a one

- time act ivity. Therefore, this section does not apply

.

3(e) General Guidelines

The survey will not violate any of the general guidelines described in 5 CFR 1320.5 or in
EPA’s ICR handbook.

3(f) Confidentiality

All responses to the survey will be kept strictly anonymous. To ensure that the final survey sample includes a representative and diverse population of individuals, the survey questionnaire will elicit basic demographic information, such as age, household size, employment status, and income. However, th e detailed survey questionnaire will not ask respondents for personal identifying information, such as names, phone numbers, or addresses. Addresses will be collected during telephone screening, but the telephone screening and mail survey databases will n ot be matched or combined. Prior to taking the survey, respondents will be informed that their responses will be held strictly anonymous. The survey data will be made15 public only after it has been thoroughly vetted to ensure that all potentially identify ing
information has been removed.

3(g) Sensitive Questions

The survey questionnaire will not include any sensitive questions pertaining to private or personal information, such as sexual behavior or religious beliefs.

4. The Respondents and the Informat ion Requested

4(a) Respondents The target population for the Stated Preference Survey is all individuals from continental U.S. households who are 18 years of age or older. Survey participants are recruited randomly through random digit dialing

. EPA wil l identify a random stratified sample of 5, 720 adults who

express their willingness to participate in a mail survey when contact ed by telephone through random digit dialing . All of these recruits will be sent a copy of the mail survey. Approximately 2, 288 of the adults of the 5, 720 adults sent a survey are expected to return a completed survey

. For the selection of households, the population of households in the 48 states and the
District of Columbia will be stratified by four study regions. There are a t otal of seven study regions for purposes of evaluating the 316(b ) existing facilities rule benefits. For the purpose s of the stated preference survey implementation
, EPA uses four geographic regions: Northeast, Southeast, Inland, and Pacific. The Northeast region includes t he North Atlantic and Mid Atlantic regions
, the Southeast region includes t he South Atlantic and Gulf of Mexico regions
, the Pacific region includes states on the Pacific coast, and the Inland region includes all non

coastal states.
A sa mple of 2,000 households would complete a version of the survey which specifically addresses policies within their region. The total sample completing regional survey versions is allocated to each region in proportion to the total number households in that region with the restriction that at least 288 persons respond in each region. This is the number required to estimate the main effects and interactions under an experimental design model. T he total sample
size for each region is much larger then the min imum sample size required for model estimation for all but one region ( Pacific ). An additional sample of 288 household s w ill receive a national survey version which addresses policies at the national scale. This sample would be distributed16 among the stud y regions based on the percentage of regional survey sample (as shown in Table A1) to ensure that respondents to the national survey version are distributed throughout the
continental U.S. Part B of this document provides detail on sampling methodology.
Table A 1 shows the stratification design for the geographic regions covered by the sample for this survey. More detail on planned sampling methods and the statistical design of the survey can be found in Part B of this supporting statement.

Table A 1 : Geo graphic Stratification Design

Region States Included Sample Size a Percentage of Sample

Northeast CT, DC, DE, MA, MD, ME, NH, NJ, NY, PA, RI, VT 417 21 %

Southeast AL, FL, GA, LA, MS, NC, SC, TX, VA 562 28 %

Inland AR, AZ, CO, ID, IA, IL, IN, KS, KY, MI, MN, MO, MT, NM, OK, ND, NE, NV, OH,TN, SD, UT, WI, WV, WY 732 37 %

Pacific CA, OR, WA 288 14 %

Total for Regional Surveys Versions U.S. (excluding AK and HI) 2,000 100%

National Survey Version U.S. (excluding AK and HI) 288

-

a Sample sizes presented in this table include only the 2, 288 individuals returning completed mail surveys.17 4( b ) Information Requested (I) Data items, including re cord keeping requirements
Individuals who agree to participate in the survey will be mailed a copy of the survey.
The full text of the regional version of the mail survey for the Northeast region is provided in
Attachment 1 and the full text of the national version of the mail survey is provided in
Attachment 2. EPA revised the survey based on the findings of a series o f seven focus groups conducted as part of survey instrument development (OMB control # 2090

- 0028). Additional information regarding focus group implementation is provided in Section 5(b). EPA has determined that all questions in the survey are necessary to achieve the goal of this information collection, i.e., to collect data that can be used to support an analysis of the total benefits of the 316(b) regulation. The following is an outline of the major sections of the survey. Relative Importance of Issues Associated with Industrial Cooling Water

. The first survey question asks respondents to rate the general importance of ( a ) preventing the loss of fish caught by humans
, ( b ) preventing the loss of fish not caught by humans
, ( c ) maintaining ecological
heal th in rivers, lakes, and bays
, ( d ) keeping the cost of goods and services low, (e) making sure there is enough government regulation on industry, and (f) making sure there is not too much government regulation on industry. This question is designed to eli cit the respondent’s general preferences for regulation, reductions in fish losses, and ecological health. It also places respondents in the mindset where they are cognizant of the range of issues associated with the use of cooling water by industrial fac ilities

. Concern for Policy Issues. The second survey question asks respondents to rate the general importance of protecting aquatic ecosystems compared to other issues that the government might
address. This question is designed to remind respondents th at there are other issues (such as public safety, education, and health) to which the government could direct funds, rather than spending these funds to prevent fish losses. Such questions are commonly used in introductory sections of stated preference su rveys (e.g., Mitchell and Carson 1984), in order to place respondents in a mindset in which they are cognizant that there are substitute goods and policy issues to which they might direct their scarce household budgets. Relative Importance of Effects

. Que stion 3 asks the respondent to rate the importance of each
of the effects captured by the five scores: ( a ) commercial fish populations ( b ) fish populations (for all fish)
, ( c ) fish losses prevented
, ( d ) condition of aquatic ecosystems, and ( e ) cost to my18 h ousehold

. This question is designed to prom ote understanding of the scores by placing respondents in a mindset where they consider the meaning of each score and consider their general preferences for effects prior to considering specific policy options. The question also promotes understanding by telling the respondent that they can return to previous pages for
reminders of what the scores mean. Voting for Regulations to Prevent Fish Losses in the Respondent’s R egion

. Questions 4, 5,
and 6 are “choice experiment” or “choice modeling” questions (Adamowicz et al. 1998; Bennett and Blamey 2001), and ask respondents to choose how they would vote, if presented with two hypothetical regulatory options (and a third “status quo” choice to reject both options) for waters within the respondents’ region (e.g., Northeast waters) . Each of the multi

- attribute options is characterized by ( a ) commercial fish populations (in 3

- 5 years) (b) fish populations (all fish; in
3

- 5 years), (c) fish saved per year (out of [tota l] fish los t in water intakes )
, ( d ) condition of aquatic ecosystems (in 3

- 5 years), and ( e ) an unavoidable cost of living increase for the respondent’s household. Following standard choice experiment methods, respondents choose the regulatory options that they prefer, based on their preferences. Respondents always have the option to vote for neither option

— providing the status quo option is necessary for appropriate welfare estimation (Adamowicz et al. 1998). Advantages of choice experiments, and the man y examples of the use of such approaches in the literature, are discussed in later sections of this ICR. Following standard approaches (Opaluch et al. 1993, 1999; Johnston et al. 2002 a; 2002b
, 2003 b ), respondents are instructed to answer each of the three choice questions independently, and not to “add up or compare programs across different pages.” This is included to avoid biases associated with sequence aggregation effects (Mitchell and Carson 1989). EPA will also vary the order in which the policy op tion attributes are presented across respondents, such as presenting household cost first or presenting fish saved per year lower in the list of choice question attributes. While complete randomization is impractical for the mail survey, the change
in ord er would allow for a potential test of ordering effects. Reasons for Voting “No Policy”

. Question 7 is a follow

- up to the prior voting questions, and
ask s respondents to identify the primary reason for voting no, if they always voted for “no policy” in qu estions 4

- 6. It is designed to identify respondents whose “no policy” responses are based on their budget constraint, respondents who do not consider fish losses important enough to vote for a policy, or respondents who ignored information presented in th e survey and answered questions based on their general convictions and principles. In an electronic survey19 format, respondents who voted for a policy would not see this question, potentially reducing
burden. Respond ent Certainty and Reasons for Voting

. Q uestions 8 and 9 are follow

- up questions to the prior voting. Question 8 assesses the certainty that respondents feel in their choice experiment responses, following methods of Champ et al. (2004 ; 2009 )
, Akter et al. (2009), Kobayashi et al. (2010), and o thers. It is designed to identify respondents whose responses are based on incorrect interpretation of the resource changes and the uncertainty of ecological outcomes from policy options. EPA will evaluate respondent understanding when completing
stated preference survey s using methods and approaches discussed in Boyle (2003)
, Kaplowitz et
al. ( 2004 ) , Bateman et al. ( 2002 ) , Powe ( 2007 ) and others

. Question 9 asks respondents to rate the effect of factors on their choices, and why they voted for or agains t the regulatory programs. Responses to such questions have been used in the literature to successfully control for hypothetical bias. Recreational Experience. Questions 10 ask s respondents how often they participate in specific types of water

- related r ecreational activities within the last year. This question can be used to identify non

- users of the fishery resource

— thereby allowing the estimation of non

- user values
for I&E mortality reductions

. 2

Demographics. Questions 11

- 21 ask respondents to provide basic demographic information, including age, gender, highest level of education, household size, household composition, location, employment status, and household income. This information will be used in the analysis of survey results, as well as in the nonres ponse analysis. Examples of this approach to estimation of non

- user valu es are provided by Johnston et al. (2005 a ), Whitehead et al. (1995), Croke et al. (1986), Olsen et al. (1991), Cronin (1982), Whitehead and Groothuis (1992), and Mitchell and Carson (1981).

Comments. The survey offers respondents a chance to comment on the survey.

The Agency will modify the survey instrument for each region relative to the regional

survey shown in Attachment 1 for the Northeast region as follows:

**•** Cover

– The text on the cover reads “A Survey of Northeast Residents (CT, DC, DE, MA, MD, ME, NH, NJ, NY, PA, RI, VT)”. “Northeast Residents” and the list of included states will be changed to match the respondent’s region.

2 Non

- user values are by definition n on

- use values. Users can also hold non

- use values. However, user’s non

- use values may differ from non

- users value s due to familiarity with the resource. Thus, non

- user values are not necessarily representative of average non

- use values.20 **•** Cover

– The photo on the cover is of a fo rage species (silversides) in found in the Northeast region. If that species isn't found in other regions, EPA will replace the cover photo with a similar substitute photo for a forage species relevant to that region.

**•** Page 1

– The survey states that it “as ks for your opinions regarding policies that would
affect fish and habitat in the Northeast U

. S.” “Northeast U

. S

. ” will be replaced with the respondent’s region or simply, “the U.S.” for the national version

.

**•** Page 1

– Includes the statement that “Northeast fresh and salt waters support billions of fish.” “Northeast” will be replaced with the respondent’s region or “the U.S.” for the
national version and “salt water” will be removed from the Inland and Great Lakes regions.

**•** Page 2

- The survey states that “Co oling water use affects fresh and salt waters throughout the Northeast US, but almost all fish losses are in salt waters such as coastal bays.” For the Southeast and Pacific regions, which include both salt water and freshwater facilities, reference to th e Northeast region would be replaced with the name of the respondent’s region or “the U.S.” for the national version of the survey . For the
Inland region, which only include freshwater facilities, reference to salt water will be
removed.

**•** Page 2

– A map of the Northeast region and facility locations is presented. A comparable map will be produced for each region or the U.S. , and map included in the survey will correspond to the respondent’s region or the U.S.

.

**•** Page 4

- This page provides an example for two Northeast coastal species and includes a figure comparing estimates of young fish lost to the total number of adult fish. The estimate of total losses will be modified to describe species and losses occurring within the respondent’s region.

**•** Page 5

- The total losses (1.1 billion) included within the survey corresponds to losses from facilities in Northeast coastal waters. This total would be replaced with the total losses for the respondent’s region or total losses for the U.S. for the national version

. The pie charts will be updated based on the regional (national) total while maintaining the 25% and 95% reductions used in the example.

**•** Page 7

- The table text describing each score will be changed to include the current scores for the respondent’s regio n.21 **•** Page 8

- Text describing the commercial fish populations score and fish population s (all fish) score will be changed to describe the current score for the respondent’s region
relative to its maximum.

**•** Page 10

– The included figure illustrates the locati on of “ Facilities Using Cooling Water
Intake ”. The figure will be replaced with a map showing facility locations within the respondent’s region or in the U.S. for the national version

.

**•** Pages 11

- 14

– Regional references within the table headings in Questi ons 4, 5, and 6 (e.g., “Policy Effect NE Waters ”, “Option A NE Waters ”) will be modified to refer to the policy effects and options for the respondent’s region. The “Fish Saved per Year” score includes a note reminding the respondent of total fish lost wi thin the region due to I&E (e.g., 1. 1 billion); this number will be changed to reflect total losses within the respondent’s region. The values describing the current situation and Options A and B within experiment questions 4, 5, and 6 will also vary acro ss regions.

(II) Respondent activities

EPA expects individuals to engage in the following activities during their participation in the contingent valuation survey :

**•** Review the background information provided in the beginning of the survey document

.

**•** Co mplete the survey questionnaire and return it by mail

. A typical subject participating in the mail survey is expected to take 30 minutes to complete the survey. These estimates are derived from focus groups and cognitive interviews in which respondents we re asked to complete a survey of similar length and detail to the current

survey.

5. The Information Collected

- Agency Activities, Collection Methodology, and Information Management

5(a) Agency Activities

The survey is being developed, conducted, and a nalyzed by Abt Associates Inc. and is funded by EPA contract No. EP

- C

- 07

- 023 which provide s funds for the purpose of analyzing the22 economic benefits of the proposed rule for existing facilities subject to the section 316(b) regulation. Agency activities as sociated with the survey consist of the following:

**•** Develop the survey questionnaire and sampling design.

**•** Printing of questionnaires

.

**•** Telephone screening of respondents.

**•** Mailing of questionnaires.

**•** Mailing of postcard reminder s

.

**•** Follow

- up with non

- respondent s to the mail survey/resending of questionnaire if needed

.

**•** Data e ntry and cleaning of data file.

**•** Analy sis of survey results. Although not covered under this ICR, EPA will primarily use the survey results to estimate the social value of changes in I&E mor tality losses of forage, recreational, and commercial species of fish, as part of the Agency’s analysis of the benefits of the 316(b) rule for existing facilities. If reliable environmental data were to be developed for population changes and other ecosys tem impacts
, social values for these benefit types may also be assessed for the rulemaking using survey results.

5(b) Collection Methodology and Information Management

To pretest the survey questionnaire, EPA conduct ed a series of seven focus groups,
inc luding one using cognitive interview methodologies under a different ICR (OMB control #
2090

- 0028). Focus groups provided valuable feedback which allowed EPA to iteratively edit and refine the questionnaire, and eliminate or improve imprecise, confusing, and redundant questions. Focus groups and cognitive interviews were conducted following standard approaches in the literature, as outlined by Desvousges et al. (1984), Desvousges and Smith (1988), Johnston et al. (1995), Schkade and Payne (1994), Kaplowic z et al. (2004), and Opaluch et al. (1993). EPA plans to implement the proposed survey as a mail choice experiment questionnaire. First, EPA will use a telephone screener to solicit respondents to receive the mail questionnaire. A dual frame, random di git dial design will be used, including both landline and cell phone
numbers. This ensures that even cell

- phone

- only households have an opportunity to participate in the survey to reduce potential bias . The telephone screener , shown in Attachment in 6,23 i ncludes not only an invitation to participate in the mail survey, but also some attitudinal and behavioral questions that are also included in the mail survey, as well as demographic
characteristics. EPA will use this information for the non

- response anal ysis to compare respondents and non

- respondents to the mail questionnaire. It is anticipated that approximately 60 percent of respondents to the telephone screener will agree to participate in the mail survey. EPA will then send the mail survey to those w ho agree to participate, along with a cover letter explaining the purpose of the survey

. All of these respondents will receive a reminder postcard approximately one week after the initial questionnaire mailing. The cover letter and postcard reminder are i ncluded as Attachments 7 and 8, respectively.
A pproximately three weeks after the reminder postcard, all those who have not responded will receive a second copy of the questionnaire with a revised cover letter. The following week, another reminder postcar d will be sent. Based on this approach to mail data collection, it is anticipated that approximately 40 percent of those who agree to participate in the mail survey will actually do so. Since the desired number of complete d surveys is 2, 288 , it will be n ecessary to recruit 5, 720 respondents by telephone who agree to participate (Dilman 2000)

. Data quality will be monitored by checking submitted surveys for completeness and consistency, and by asking respondents to assess their own responses to the survey

. Question 8 asks respondents to rate their understanding of the survey and their confidence in their responses. Questions 7 and 9 are designed to assess the presence or absence of potential response biases by asking respondents to indicate their reasonin g and rate the influence of various factors on their responses to the choice experiment questions

. Responses to the survey will be stored in an electronic database. This database will be used to generate a data set for a regression model of
total values for reductions in fish I&E mortality by section 316(b) existing facilities. To protect the confidentiality of survey respondents, the survey data will be released only after it has been thoroughly vetted to ensure that all potentially identifying informati on has been
removed

. Alternatively, EPA is consider ing implement ing the proposed survey as an internet

based, choice experiment questionnaire. This alternative method is described in Attachment 5

.

5(c) Small Entity Flexibility24 This survey will be admi nistered to individuals, not businesses. Thus, no small entities will be affected by this information collection.

5(d) Collection Schedule

The schedule for implementation of the survey will be as follows:

Table A 2 : Schedule for Survey Implementation

A ctivity Duration of Each Activity Printing of questionnaires Weeks 1 to 2 Telephone screening of respondents Weeks 1 to 5

Mailing of questionnaires Weeks 3 to 8 Postcard reminder (one week after initial questionnaire mailing) Weeks 4 to 9

Follow

- up w ith non

- respondents to the mail survey/resending of questionnaire if needed (4 weeks after initial questionnaire mailing) Weeks 6 to 13

Data entry Weeks 4 to 16 Cleaning of data file Week 17 Delivery of data Week 18

6. Estimating Respondent Burden an d Cost of Collection 6(a) Estimating Respondent Burden

Subjects who participate in the survey and follow

- up interviews will expend time on
several activities. Based on the administration of the mail survey to 5, 720 households
, the
national burden estimat e for all respondents is 1, 938 hours assuming that 9 , 533 households will participate in telephone screening and 2, 288 respondents complete and return the survey, EPA estimates that telephone screening interviews will take 5 minutes (0.08 hours) per
inter view for each of the 9,533 screened households. Based on pretests conducted in focus groups, EPA estimates that on average each respondent mail ed the survey will spend 30 minutes reviewing the introductory materials and completing the survey questionnaire . Thus, the average burden per respondent is 30 minutes ( 0. 5 hours) for these 2, 288 respondents.25 These burden estimates reflect a one

- time expenditure in a single year.

6(b) Estimating Respondent Costs

According to the Bureau of Labor Statistics, the average hourly wage for private sector workers in the United States is $ 20.42 ( 2009 $) (U.S. Department of Labor 2009)

. Assuming an

average per

- respondent burden of 0.08 hours for each of the 9 , 533 screening participants and an average hourly wage of $20.4 2, the average cost per screening participant is $1.70

. Therefore the total cost to participants in the telephone screening phase would be $ 16
, 223

. Assuming an

average per

- respondent burden of 0. 5 hours for individuals mail ed the survey and an average
ho urly wage of $ 20.42 , the average cost per respondent is $ 10

. 2 1. Of the 5, 720 individuals receiving the mail survey, 2, 288 are expected to return their completed survey

. The total cost for all individuals that return surveys would be $ 23
, 360

. EPA does not anticipate any capital or operation and maintenance costs for respondents.

6(c) Estimating Agency Burden and Costs

This project will be undertaken by Abt Associates Inc. with funding of $ 446,000 from
EPA contract EP

- C

- 07

- 023 , which provide s funds for th e purpose of analyzing the economic benefits of the proposed rule for existing facilities subject to the section 316(b) regulation. Abt
Associates Inc. staff is expected to spend 1, 155 hours pre

- testing the survey questionnaire and sampling methodology, c onducting the survey, and tabulating and analyzing the survey results. The cost of this contractor time is $ 77,000

. In addition to the effort expended by EPA’s contractors, EPA staff is expected to spend 320 hours managing and reviewing this project and

c ontributing to the analysis at a cost of $ 31,000

. A gency and contractor burden is 1, 475 hours, with a total cost of $ 108,000 excluding the costs of survey printing and mailing and telephone screening

. Telephone screening is expected to take 8
, 400 hours a nd cost $ 247,000 while m ailing and printing of the survey is expected to take 1 61 hours and cost $ 122,000 , including the cost of survey printing and mailing

. Thus, the total A gency and contractor burden would be 10
, 036
hours and would cost $ 477,000.26 6(d) Respondent Universe and Total Burden Costs

EPA expects the total cost for survey respondents to be $ 3 9 , 583 ( 2009 $), based on a total
burden estimate of 1, 938 hours and an hourly wage of $ 20.42

.

6(e) Bottom Line Burden Hours and Costs

The following tabl e presents EPA’s estimate of the total burden and costs of this
information collection:

Table A3 : Total Estimated Bottom Line Burden and Cost Summary

Affected Individuals Total Burden Total Cost ( 2009 $) Participants in Telephone Screening 794 hours $ 16
, 223 Mail Survey Respondents 1, 114 hours $ 23
, 360

Total for Survey R espondents 1, 938 hours $ 39
, 583

EPA S taff 320 hours $ 31,000 Telephone Screening 8
, 400 hours $ 247,000 Survey Printing and Mailing 161 hours $ 122,000

EPA’s C ontractors 1, 155 hours $ 77,00 0

Total Burden and Cost 11
, 974 hours $ 516,583

6(f) Reasons for Change in Burden

The survey is a one

- time data collection activity.

6(g) Burden Statement

EPA estimates that the public reporting and record keeping burden associated with the
mail surve y will average 0. 5 hours per respondent (i.e., a total of 1, 144 hours of burden divided

among 2, 288 survey respondents). Households included in telephone screening are expected to average 0.08 hours per screening interview participant (i.e., a total of 79 4 hours of burden divided among 9 , 533 screening interview participants )

. This results in a total burden estimate o f27 1, 938 hours including both the telephone screening interview s and mail survey. Burden means the total time, effort, or financial resources expended by persons to generate, maintain, retain, or disclose or provide information to or for a Federal agency. This includes the time needed to review instructions; develop, acquire, install, and utilize technology and systems for the purposes
of coll ecting, validating, and verifying information, processing and maintaining information, and disclosing and providing information; adjust the existing ways to comply with any previously applicable instructions and requirements; train personnel to be able to respond to a collection of information; search data sources; complete and review the collection of information; and transmit or otherwise disclose the information. An agency may not conduct or sponsor, and a person is not required to respond to, a collect ion of information unless it displays a currently valid OMB control number. The OMB control numbers for EPA's regulations are listed in 40 CFR part 9 and 48 CFR chapter 15. To comment on the Agency's need for this information, the accuracy of the provide d burden estimates, and any suggested methods for minimizing respondent burden, including the use of automated collection techniques, EPA has established a public docket for this ICR under
Docket ID No. EPA

- HQ

- OW

- 2010

- 0595
, which is available for online vi ewing at www.regulations.gov, or in person viewing at the Office of Water Docket in the EPA Docket Center (EPA/DC), EPA West, Room 3334, 1301 Constitution Ave., NW, Washington, DC. The EPA/DC Public Reading Room is open from 8:30 a.m. to 4:30 p.m., Monday through Friday, excluding legal holidays. The telephone number for the Reading Room is 202

- 566

- 1744, and the telephone number for the Office of Water Docket is 202

- 566

- 1752

. Use www.regulations.gov to obtain a copy of the draft collection of information , submit or view public comments, access the index listing of the contents of the docket, and to access those documents in the public docket that are available electronically. Once in the system, select “search,” then key in the docket ID number
, EPA

- HQ

- O W

- 2010

- 0595

.28 PART B OF THE SUPPORTING STATEMENT

1. Survey Objectives, Key Variables, and Other Preliminaries 1(a) Survey Objectives

The overall goal of this survey is to explore how public values (including non

- use values) for fish and aquatic organi sms are affected by I&E mortality at cooling water intake structures (CWIS) located at existing 316(b) facilities, as reflected in individuals’ willingness to pay for programs that would prevent such losses. EPA has designed the survey to provide data to support the following specific objectives:

**•** To estimate the total values , including non

- use values, that individuals place on preventing losses of fish and other aquatic organisms caused by CWIS at existing 316(b)
facilities.

**•** To understand how much individ uals value preventing fish losses, increasing fish populations, improvements in aquatic ecosystems , and increasing commercial and
recreational catch rates.

**•** To understand how such values depend on the current baseline level of fish populations
and fish loss es, the scope of the change in those measures, and the certainty level of the predictions.

**•** To understand how such values vary with respect to individuals’ economic and demographic characteristics.

Understanding total public values for fish resources lost to I&E mortality is necessary to determine the full range of benefits associated with reductions in impingement and entrainment
losses at existing 316(b) facilities. Because non

- use values may be substantial, failure to recognize such values may lead to im proper inferences regarding policy benefits (Freeman 2003).

1(b) Key Variables

The key questions in the survey ask respondents whether or not they would vote for policies that would increase their cost of living, in exchange for specified changes in : ( a ) I&E29 mortality losses of fish, ( b ) commercial fish sustainability, ( c ) long

- term fish populations, and ( d ) condition of aquatic ecosystems 3 . More specifically, the choice experiment framework allows respondents to view pairs of multi

- attribute policies as sociated with the reduction of I&E mortality losses. Respondents are asked to choose the program that they would prefer, or to choose to reject both policies. This follows well

- established choice experiment methodology and format (Adamowicz et al. 1998; Louviere et al. 2000; Bennett and Blamey 2001; Bateman et al. 2002). Important variables in the analysis of the choice questions are how the respondent votes, the amount of the cost of living increase, the number of fish losses that are prevented, the

sus tainability of commercial fishing, the change in fish populations, and the condition of aquatic ecosystems . Other important variables include whether or not the respondent is a user of the affected aquatic resources, household income, and other respondent demographics.

1(c) Statistical Approach

EPA believes that a statistical survey approach is appropriate . A census approach is impractical because contacting all households in the U.S. would require an enormous expense. On the other hand, an anecdotal a pproach is not sufficiently rigorous to provide a useful estimate
of the total value of fish loss reductions for the 316(b) case . Thus, a statistical survey is the most reasonable approach to satisfy EPA’s analytic needs for the 316(b) regulation benefit analysis.
EPA has retained Abt Associates Inc. (55 Wheeler Street, Cambridge, MA 02138) as a
contractor to assist in questionnaire design, sampling design, and analysis of the survey results.

1(d) Feasibility

3 The environmen tal attributes to be compared against the cost of living increases where designed based on the Johnston et al. (2009) Bioindicator

- Based Stated Preference Valuation (BSPV) method which was developed to promote ecological clarity and closer integration of ecological and economic information within SP studies. In contrast to traditional SP valuation, BSPV employs a more structured and formal use of ecological indicators to characterize and communicate welfare

- relevant changes. It begins with a formal basis i n ecological science, and extends to relationships between attributes in respondents’ preference functions and those used to characterize policy outcomes. Specific BSPV guidelines ensure that survey scenarios and resulting welfare estimates are characteriz ed by: (1) a formal basis in established and measurable ecological indicators, (2) a clear structure linking these indicators to attributes influencing individuals’ well

- being, (3) consistent and meaningful interpretation of ecological information, and (4) a consequent ability to link welfare measures to measurable and unambiguous policy outcomes. The welfare measures provided by BSPV method can be unambiguously linked to models and indicators of ecosystem function, are based on measurable ecological outcom es, and are more easily incorporated into benefit cost analysis. This methodology was developed in part to address the EPA Science Advisory Board’s call for improved quantitative linkages between ecological services and economic valuation of those service s.30 The survey instrument was repeatedly pre

- te sted during a series of seven focus groups (conducted under a different ICR with OMB control # 2090

- 0028)
, in addition to the twelve focus groups conducted for the Phase III survey ( EPA

- HQ

- OW

- 2004

- 0020 )
, and it will be subject to peer review by reviewers i n academia and government, so EPA does not anticipate that respondents will have difficulty interpreting or responding to any of the survey questions. Additionally, since the survey will be administered as a mail survey, it will be easily accessible

to re spondents. Thus, EPA believes that respondents will not face any obstacles in completing the survey, and that the survey will produce useful results. EPA has dedicated sufficient funding (under EPA contracts No. EP

- C

- 07

- 23 ) to design and implement the su rvey. Given the timetable outlined in Section A.5(d) of this document, the survey results will be available for timely use in
the final benefits analysis for the 316(b) existing facilities rule.

2. Survey Design 2(a) Target Population and Coverage

The t arget population for this survey includes individuals from continental U.S. households who are 18 years of age or older. The sample will be chosen to reflect the demographic characteristics of the general U.S. population.

2(b) Sampling Design (I) Samplin g Frames

The sampling frame for this survey is the panel of individuals recruited by random digit dialing ( over

- lapping dual frame; land and cell) to participate in a mail survey. The overall sampling frame from which these individuals would be selected is the set of all individuals in continental U.S. households who are 18 years of age or older and who have listed phone numbers. Individuals in the panel are recruited using a list

- assisted random digit dialing telephone methodology, thus providing a prob ability

- based starting sample of U.S. telephone
households. The telephone screening will use an overlapping dual frame design of landline and cell phone numbers to increase the coverage of the sample. The inclusion of cell phone numbers will
allow EPA t o reach potential respondents who only have cell phones and would be missed if31 only a sample of landlines was selected. The dual frame design also avoids bias because the cell

phone

- only population skews heavily towards lower

- income and younger individuals . The cell and landline samples w ill be weighted to correct for each individual’s probability of being included in the survey. People who live in a household with more than one person are less likely to be chosen for the survey, and people with more than one telephone line (e.g., both cell and landline) are more likely to be chosen for the survey. All landline respondents to the telephone screener will be asked the number of eligible respondents in their household and every respondent (cell and landline) will be asked whether they have a landline only, a cell phone only, or both. Next, the survey data will be weighted to match national data (U.S. Census and
National Hea l th Interview Survey) by a set of demographic variables (e.g., age and gender) as
well as phone usage (cell

- only users, landline

- only users and people who use both cell phones and landline phones). For January through June 2009, the National Health Interview Survey indicated that 15.5 percent of households are landline only, 22.7 percent ar e cell phone only, and 59.4 percent have both landline and cell phone service. About two percent of households have no telephone service. It is anticipated that estimates for landline and cell phone service from the January to June 2010 National Health I nterview Survey will be available for weighting purposes by the time the survey would be implemented. For discussion of techniques that EPA will use to minimize non

- response and other non

sampling errors in the survey sample, refer to Section 2(b)(II), bel ow.

(II) Sample Sizes

The intended sample size for the survey is 2
, 288 households including only households providing completed mail surveys. This sample size was chosen to provide statistically robust regression results while minimizing the cost and bu rden of the survey. Given this sample size, the level of precision (see section 2(c)) achieved by the analysis will be more than adequate to meet the analytic needs of the benefits analysis for the 316(b) regulation. For further discussion
of the level o f precision required by this analysis, see Section 2(c)(I) below.

(III) Stratification Variables32 The survey sample will be selected using a stratified selection process . For the selection of households, the population of households in the contiguous 48 states and the District of
Columbia will be stratified by the geographic boundaries of four study regions : Northeast
, Southeast , I nland
, and Pacific. As de sc ribed previously, t he Northeast region includes t he North
Atlantic and Mid Atlantic 316(b) benefi ts regions
, the Southeast region includes t he South
Atlantic and Gulf of Mexico 316(b) benefits regions , the Pacific region includes states on the Pacific coast, and the Inland region includes all non

- coastal states. The sample is allocated to each region in proportion to the total number of households in that region
, with at least 288 completed surveys in each region. This is the number required to estimate the main effects and interactions under an experimental design model as described in Section 4(a) o f Part A

. To accommodate this requirement the sample sizes in other regions will be slightly reduced. A sample of 288 households completing the national survey version would be distributed among the study regions based on the percentage of regional survey sample (as shown in Table A1) to ensure that respondents to the national survey version are distributed across the continental U.S.

(IV) Sampling Method

Using the stratification design discussed above, respondents will be randomly selected

. First, a la rger sample of households will be selected through random digit dialing in each of the 4 regions. The household to which the selected telephone number belongs will be called and the respondent will be asked whether he or she is willing to provide informat ion required by the survey. If the person in the household agrees, then a questionnaire will be mai l ed to that
household. If it is assumed that 40 % of the households which agreed to provide information actually return a completed mail survey (completion rate) then 5, 720 questionnaires will need to
be mailed to households. 4
If we assume that 60% of the households that are called say “yes” they are willing to receive a questionnaire ( the screening response rate) , then we need to screen 9 , 533 households.
A dual frame random digit dialing design
, including both landline and cell phone numbers , will be used for telephone screening

. If we assume that 40 % of the households called will participate in the telephone screener
, then we will need to call 23
, 833 numb ers. The actual number of telephone number s selected through random digit dialing sampling will be larger than the

4 The assumed response rate is based on a similar stated preference studies conducted by Johnston et al. (2010) in the Northeast U.S. Actual response rates could vary across study regions.33 number of households called. T his is because we are expecting that 40% of the telephone numbers initially selected will be screened out as non

- working or business numbers. Therefore the actual number of telephone numbers selected will be around 39
, 722

. The quantity of telephone numbers that we need to select in each region can be obtained by allocating the total number in proportion to the t otal households in that region. For obtaining population

- based estimates of various parameters, each responding household will be assigned a sampling weight. This weight combines a base sampling weight which is the inverse of the probability of selection of the household and then an adjustment for

non

- response. The weights will be used to produce estimates that are generalizable to the population from which the sample was selected (e.g., percent of population participating in

water

- based recreation such as fishing and shellfishing). Proportional allocation of the sample to regions ensures an equal probability sample. T o estimate total WTP for the quantified environmental benefits of the 316(b) existing facilities rulemaking data will be analyzed
statisti cally using a standard random utility model framework.

(V) Multi

- Stage Sampling

Multi

- stage sampling will not be necessary for this survey.

2(c) Precision Requirements (I) Precision Targets

Table B1, below, shows the target samples sizes for both the U.S. (excluding A laska and
H awaii ) and each of the four EPA study regions

. At the regional level , a sample of 2,000 households (complete d surveys ) will provide estimates of population percentages with a margin
of error ranging from 3.6 to 5.8 percentage p oints at the 95% confidence level. A sample of 288
household for the national survey version (completed surveys) will provide an estimate of population percentages with a margin of error no greater than 5.8 percentage points at the 95%
confidence level.34 Table B1: Number of Households and Household Sample for Each EPA Study Region

Region Household Population Household Sample

Northeast 23,281,296 417

Southeast 31,378,122 562

Inland 40,852,983 732

Pacific 16,158,206 288

T otal for Regional Survey Vers ions 111,670,607 2,000

National Survey Version 111,670,607 288

Source: The number of households in each region was obtained based on the estimated population size and average household size from the 200 6

- 200 8 American Community Survey (ACS)

.

(II) Non

- S ampling Errors

One issue that may be encountered in stated preference surveys is the problem of protest responses. Protest responses are responses from individuals who reject the survey format or question design, even though they may value the resources being considered (Mitchell and Carson 1989). For example, some respondents may feel that any amount of I&E is unacceptable, and choose not to respond to the survey. To deal with this issue, EPA has included several questions, including an open

- ended comm ents section, to help identify protest responses. The use of such methods to identify protest responses is well

- established in the literature (Bateman et al. 2002). Moreover, many researchers (e.g., Bateman et al. 2002) suggest that a choice experiment f ormat, such as that proposed here, may ameliorate such responses (over the earlier contingent valuation format)

. A different type of non

- sampling error is non

- response bias . Non

- response rates in this survey are affected by non

- response at each stage of s ampling. There are two types of non

respondents to this survey: respondents unwilling to complete a questionnaire when initially contacted by phone and respondents who agree but do not complete the questionnaire. EPA will
conduct several additional activ ities to minimize the potential for non

- response bias in the current survey:35 (1) The telephone interviews will be conducted by trained interviewers who are experienced in encouraging response. Calls will be placed on different days of the
week and at differe nt times to maximize response. (2) The mail survey will be designed to maximize response. A mail survey will be sent to all those who agree to participate. Then, one week later, a postcard reminder will be sent. Three weeks later, a second copy of the ques tionnaire with a revised cover
letter will be sent to non

- respondents. As final follow

- up, another postcard reminder
will be sent one week later. (3) Response rates will be tracked on a daily basis for both the telephone screener and mail survey. If any unex pected declines are encountered, corrective action can immediately be undertaken. (4) EPA will undertake non

- response bias analysis as detailed in the following section. If necessary, EPA will use appropriate weighting or other statistical adjustment to corre ct the
bias because of non

- response

.

Non

- response Interviews To determine whether there is any evidence of significant non

- response bias in the completed sample
, EPA will compare the characteristics of the completed and non

- completed
cases from the random digit dialing sample. There are two main stages of non

- response: non

response to the telephone survey and non

- response to the mail survey. To assess the potential for telephone non

- response bias, EPA will collect sample
characteristics in the course of th e telephone survey as follows: (1) prior to household contact, (2) at respondent selection for the survey, and (3) after beginning the interview. EPA will then analyze the data available for respondents and non

- respondents prior to household contact and a t respondent selection. Because the telephone instrument is very short, we do not expect many people prematurely terminat ing the call after the selected household member has started the
interview. The drawn sample of random digit dialing numbers from the l andline frame that are released to telephone interviewers for contact attempts can be coded for certain contextual characteristics. The “hundreds bank” from which the RDD number is drawn (e.g., 301

- 608

- 38xx) is classified geographically according to the u nit from which the majority of listed numbers in that bank are located. This permits us to classify all of the numbers drawn by EPA36 region, State, and urbanicity (central city, metro remainder, and non

- metropolitan area). It also permits us to classify t hose numbers by demographic characteristics, such as percentage of
African

- American and Hispanic, based on Census data linked to telephone exchanges. EPA will

compare the characteristics of all dialed residential numbers in which an interview had not been completed with those that had been completed using these variables to determine whether non

response bias is present

. Once contact is achieved with a household, one adult is selected in each household as the designated respondent. If there is more than o ne eligible respondent per household, then a random selection is done for the individual with the most recent/next birthday. EPA will identify

t he age and gender of this individual if callbacks are necessary. This information permits additional compariso ns of any differences in the age and gender of respondents in the completed sample and those in the non

- completed sample after household contact and respondent selection
have been made. The telephone screener includes not only an invitation to participate in the mail survey, but also some attitudinal (relative importance of various government activities) differences and behavioral differences (recreational activities), as well as demographic characteristics (see
Attachment 6 for detail) . EPA will use the t elephone screening data to compare mail survey respondents and non

- respondents. The items of information collected during telephone screening will help determine the type of person that is likely to not respond to the survey and may help in forming weighti ng classes for adjusting weights of respondents to account for non

- response and
minimize the bias because of non

- response.

2(d) Questionnaire Design

The information requested by the survey is discussed in Section 4(b)(I) of Part A of the supporting stat ement. The full text of the draft questionnaire for the Northeast region is provided
in Attachment 1 and the full text of the draft questionnaire for the national survey version is provided in Attachment 2

. The following bullets discuss EPA’s reasons fo r including the questions in the survey:

**•** Relative Importance of Issues Associated with Industrial Cooling Water . EPA included this section to prepare respondents to answer the stated preference questions by37 motivating respondents to consider the relative importance of key issues associated with the use of cooling water by industrial facilities.

**•** Concern for Policy Issues. EPA included this section to prepare respondents to answer the stated preference questions by motivating respondents to think about the relative importance of different policy issues.

**•** R elative Importance of Effects. This section was included to promote understanding of the metrics included in the stated preference questions by asking them to consider their relative importance prior to eva luating policy options and by encouraging respondents to

re

- read previous pages for reminders if necessary.

**•** Voting for Regulations to Prevent Fish Losses in the Respondent’s Region (or
N ationally)

. The questions in this section are the key part of the su rvey. Respondents’ choices when presented with specific fish

- related resource changes within their region and household cost increases are the main data that allow estimation of willingness

- to

pay. The questions are presented in a choice experiment (A, B , or neither) format because this is an elicitation format that has been successfully used by a number of previous valuation studies (Adamowicz et al. 1998; Bateman et al. 2002; Bennett and Blamey 2001; Louviere et al. 2000; Johnston et al. 2002a, 2005; Op aluch et al. 1993). Furthermore, many focus group participants indicated that they have some previous experience making choices within a framework in which they are asked to vote for one of a series of options, and are comfortable with this format.

**•** Reason s for Voting “No Policy”

. This question provide s information that will be used by EPA to identify protest responses

.

**•** Respondent Certainty and Reasons for Voting

. This section is designed to identify respondents who incorrectly interpreted the choice quest ions o r the uncertainty of

outcomes

. Responses to these questions are important to successfully control for hypothetical bias.

**•** Recreational Experience. This question elicit s recreational experience data to test if certain respondent characteristics inf luence responses to the referendum questions. This question will also allow EPA to identify resource non

- users, for purposes of estimating

non

- user WTP (to gauge the relative importance of non

- use values to overall benefits)

.

**•** Demographics. Responses to t hese questions will be used to estimate the influence of demographic variables on respondents’ voting choices, and ultimately, their WTP to38 prevent I&E mortality losses of fish. This information will allow EPA to use regression
results to estimate WTP for populations in different regions affected by the 316(b) rule
for existing facilities.

**•** Comments. This section is primarily intended to help identify protest responses, i.e. responses from individuals who rejected the format of the survey or the way the qu estions were phrased.

3. Pretests and Pilot Tests

EPA conduct ed extensive pretests of the survey instrument during a set of seven focus

groups (EPA ICR # 2090

- 0028 )
, in addition to the twelve focus groups conducted for the Phase III survey . These focus groups included individual cognitive interviews with survey respondents (Kaplowicz et al. 2004), and think

- aloud or verbal protocol analyses (Schkade and Payne 1994). Individuals in these focus groups completed draft survey questionnaires and provide d com ments and feedback about the survey format and content, their interpretations of the questions, and other issues relevant to stated preference estimation. Particular emphasis in these survey pretests

was on testing for the presence of potential biases ass ociated with poorly

- designed stated preference surveys, including hypothetical bias, strategic bias, symbolic (warm glow) bias, framing effects, embedding biases, methodological misspecification, and protest responses (Mitchell and Carson 1989). Based on focus group and cognitive interview responses, EPA made various improvements to the survey questionnaire including changes to ameliorate and minimize these biases in the final survey instrument

.

4. Collection Methods and Follow

- up 4(a) Collection Method s

The survey will be administered as a mail survey. Respondents identified by random digit dialing who agree to participate will be mailed a copy of the survey questionnaire.
Re s pondents will be asked to mail the completed survey back to EPA.39 4(b) Su rvey Response and Follow

- up

The target response rate for the mail survey is 40 percent . That is, 40 percent of households which agreed to par ti cipate in the mail survey are expected to return a completed

survey. However, the actual response rate compare d to the general population is lower, given that the telephone screening process is expected to have a response rate of 6 0 percent among
contacted households. The resolution rate (determining the status of a telephone number), the screener response rate a nd the survey completion rate will contribute to the overall response rate in the survey . The actual number of telephone numbers selected for inclusion will be much larger to account for the exclusion of non

- working and business numbers. The number of

te lephone numbers needed for selection in each region can be obtained by allocating the total number in proportion to the number of households in that region. To improve the response rate, a ll of these respondents will receive a reminder postcard approximat ely one week after the initial questionnaire mailing. Then, approximately three weeks after the reminder postcard, all those who have not responded will receive a second copy of the questionnaire with a revised cover letter. The following week, another re minder postcard will be

sent. As noted in Section 2(b), the survey sample will be selected using a stratified selection process. For the selection of households, the population of households in the contiguous 48

states and the District of Columbia will be stratified by the geographic boundaries of four EPA study regions. In addition, EPA will administer a national version of the survey that does not require stratification. We will keep track of the response rates for each of regional surveys and
the na tional version of the survey to ensure that the rates are reasonable. We will also look at the
frame characteristics of non

- respondents to determine if there are any substantial biases in the
estimates because of an imbalance in the distribution of certai n important subgroups in the sample

.

5. Analyzing and Reporting Survey Results 5(a) Data Preparation

Since the survey will be administered as a mail survey, survey responses will manually
entered into an electronic database after they are returned . Af ter all responses have been entered
,40 the database contents will be converted into a format suitable for use with a statistical analysis software package. The mail survey, database management, and data set conversion will be conducted by Abt Associates Inc

. All survey responses will be vetted for completeness. Additionally, respondents’ answers to the choice experiment questions will be tested to ensure that they are internally consistent with respect to scope and other expectations of neoclassical prefere nce theory , such as transitivity. Responses which satisfy transitivity exhibit relational relationships when separate choices among policy options are compared. For example, if values for policy 1 are greater than policy 2 , and values for policy 2 are gr eater than Policy 3 , then values for policy 1 should also be greater than values for Policy 3

.

5(b) Analysis

Once the survey data has been converted into a data file, it will be analyzed using statistical analysis techniques. The following section dis cusses the model that will be used to analyze the stated preference data from the survey.

Analysis of Stated Preference Data The model for analysis of stated preference data is grounded in the standard random utility model of Hanemann (1984) and McConnel l (1990). This model is applied extensively within stated preference research, and allows well

- defined welfare measures (i.e., willingness to pay) to be derived from choice experiment models (Bennett and Blamey 2001; Louviere et al. 2000). Within the sta ndard random utility model applied to choice experiments, hypothetical policy alternatives are described in terms of attributes that focus groups (Johnston et al. 1995; Adamowicz et al. 1998; Opaluch et al. 1993) reveal as relevant to respondents’ utility, or well

being. One of these attributes would include a mandatory monetary cost to the respondent’s
household. Applying this standard model to choices among policies to reduce I&E mortality losses, EPA defines a standard utility function U i ( . ) that inc ludes environmental attributes of an I&E reduction plan and the net cost of the plan to the respondent. Following standard random utility41 theory, utility is assumed known to the respondent, but stochastic from the perspective of the researcher, such that

(1) U i ( . ) = U( X i , D , Y

- F i ) = v( X i , D , Y

- F i ) + ε i

where:
X i = a vector of variables describing attributes of I&E reduction plan i ; D = a vector characterizing demographic and other attributes of the respondent.
Y = disposable income of the respondent.
F

i = mandatory additional cost faced by the hous ehold under plan i ; v( . ) = a function representing the empirically estimable component of utility;

ε i = stochastic or unobservable component of utility, modeled as an econometric error.

Econometrically, a model of such a preference function is obtained b y methods designed for limited dependent variables, because researchers only observe the respondent’s choice among alternative policy options, rather than observing values of U i (.) directly (Maddala, 1983; Hanemann, 1984). Standard random utility models a re based on the probability that a respondent’s utility from a policy Plan i , U i (.) , exceeds the utility from alternative Plans j , U j (.) , for all potential plans j ≠ i considered by the respondent. In this case, the respondent’s choice set of potential policies also includes maintaining the status quo. T he random utility model presumes that the respondent assesses the utility that would result from each I&E reduction plan i (including the status quo)
, and chooses the plan that would offer the highest utility.
When faced with k distinct plans defined by their attributes, the respondent will choose plan i if the anticipated utility from plan i exceeds that of all othe r k

- 1 plans. Drawing from (1), the respondent will choose plan i if

(2) (v( X i , D , Y

- F i ) + ε i ) ≥ (v( X k , D , Y

- F k ) + ε k ) **∀** k ≠i.

If the ε i are assumed independently and identically drawn from a type I extreme value (Gumbel) distribution, the model may be estimated as a conditional logit model, as detailed by Maddala (1983), Greene (2003) an d others. This model is most commonly used when the respondent considers more than two options in each choice set (e.g., Plan A, Plan B, Neither42 Plan), and results in an econometric (empirical) estimate of the systematic component of utility v( . ) , based o n observed choices among different policy plans. Based on this estimate, one may calculate welfare measures (willingness to pay) following the well

- known methods of Hanemann (1984), as described by Freeman (2003) and others. Following standard choice expe riment methods (Adamowicz et al. 1998; Bennett and Blamey 2001), each respondent will consider questions including three potential choice options (i.e., Plan A, Plan B, Neither Plan)

— choosing the option that provides the highest utility as noted above. Fo llowing clear guidance from the literature, a “neither plan” or status quo option is always included in the visible choice set, to
ensure that WTP measures are well

- defined (Louviere et al. 2000). EPA also anticipates that respondents will consider more t han one choice question within the same survey, to increase information obtained from each respondent. This is standard practice within choice experiment and dichotomous choice contingent valuation surveys (Poe et al. 1997; Layton 2000). While respondent s will be instructed to consider each choice question as independent of other choice questions , it is nonetheless standard practice within the literature to allow for the potential of correlation among questions answered within a single survey by a single respondent. That is, responses provided by individual respondents may be correlated even though responses across different respondents are considered independent and identically distributed (Poe et al. 1997; Layton 2000; Train 1998).
There are a variet y of approaches to such potential correlation. Following standard practice, EPA anticipates the estimation of a variety of models to assess their performance. Models to be assessed include random effects and random parameters (mixed) discrete choice
mode ls, now common in the stated preference literature (Greene 2003; McFadden and Train 2000; Poe et al. 1997; Layton 2000). Within such models, selected elements of the coefficient vector are assumed normally distributed across respondents, often with free c orrelation allowed among parameters (Greene 2002). If only the model intercept is assumed to include a random component, then a random effects model results. If both slope and intercept parameters may vary across respondents, then a random parameters mode l is estimated. EPA anticipates that such models will be estimated using standard maximum likelihood for mixed conditional logit techniques , as described by Train (1998), Greene (2002) and others. Mixed logit m odel performance of alternative specificatio ns will be assessed by EPA using standard statistical measures of model fit and convergence, as detailed by Greene (2002
, 2003) and Train (1998).43 Advantages of Choice Experiments Choice experiments following the random utility model outlined above are fa vored by many researchers over other variants of stated preference methodology (Adamowicz et al. 1998; Bennett and Blamey 2001), and may be viewed as a “natural generalization of a binary discrete
choice CV [contingent valuation] ” (Bateman et al. 2002, p. 271). Advantages of choice experiments include a capacity to address choices over a wide array of potential policies, ground ed in well

- developed random utility theory, and the similarity of the discrete choice context to familiar referendum or voting form ats (Bennett and Blamey 2001). Compared to other types of stated preference valuation, choice experiments are better able to measure the marginal value of changes in the characteristics or attributes of environmental goods, and avoid response difficulties and biases (Bateman et al. 2002). For example, choice experiments may reduce the potential for ‘yea

- saying’ and symbolic biases (Blamey et al. 1999; Mitchell and Carson 1989), as many pairs of multi

- attribute policy choices (e.g., Plan A, Plan B, Neither ) will offer no clearly superior choice for a respondent wishing to express solely symbolic environmental motivations. For similar reasons choice experiments may ameliorate protest responses (Bateman et al. 2002). An additional advantage of such methods is that they permit straightforward assessments of the impact of resource scope and scale on respondents’ choices. This will enable EPA to easily conduct scope tests and other assessments of the validity of survey responses (Bateman et al. 2002, p. 296

- 34 2). Finally, such methods are well

- established in the stated preference literature (Bennett and Blamey 2001). Additional details of choice experiment methodology (also called choice modeling) are provided by Bennett and Blamey (2001), Adamowicz et al. (1 998), Louviere et al. (2000) and many other sources in the literature. An additional advantage of choice experiments in the present application is that they are commonly applied to assess WTP for ecological resource improvements of a type quite similar t o those at issue in the 316(b) policy case. Examples of the application of choice experiments to estimate WTP associated with changes in aquatic life and habitat include Hoehn et al. (2004), Johnston et al. (2002b), and Opaluch et al. (1999), among others . EPA has drawn upon these and other examples of successful choice experiment design to provide a basis for survey design in the present case. A final key advantage of choice experiments in the present application is the ability to estimate respondents ’ W TP for a wide range of different potential outcomes of 316(b) policies, differentiated by their attributes. The proposed choice experiment survey versions will allow44 different respondents to choose among a wide variety of hypothetical policy options, some with larger and other with very small changes in the presented attributes (annual fish losses, long

- term fish populations, recreational and commercial catch, ecosystem condition, and household cost). That is, because the survey is to be implemented as a choice experiment survey, levels of attributes in choice scenarios will vary across respondents (Louviere et al. 2000). The experimental design will also explicitly allow for variation in baseline population and harvest levels, following standard practice in the literature (Louviere et al. 2000; Bateman et al. 2002). Aside from providing the capacity to estimate WTP for a wide range of policy outcomes, it also frees EPA from having to predetermine a single policy outcome for which WTP will be
estimated. Given the potential biological uncertainty involved in the 316(b) policy case, the ability to estimate values for a wide range of potential outcomes is critical. The ability to estimate WTP for a wide range of different policy outcomes is a fundamental pr operty of the choice experiment method (Bateman et al. 2002; Louviere et al. 2000; Adamowicz et al. 1998). For the purpose of stated preference survey implementation
, EPA will use four geographic regions: Northeast, Southeast, Inland, and Pacific. The No rtheast regional survey is included in this ICR as Attachment 1. In addition, EPA will administer a national version of the survey that is included as Attachment 2. EPA emphasizes that the survey version s included in this ICR are for illustration only; t hey are but two of what will ultimately be a large number of different survey versions covering a wide range of potential policy outcomes
as described in Attachment 4

. T he experimental design (see below) will allow for survey versions showing a range of di fferent baseline and resource improvement levels, where these levels are chosen to (almost certainly) bound the “actual” levels. Given that there will almost certainly be some biological uncertainty regarding the specifics of the “actual” baselines and
im provements, the resulting valuation estimates will allow flexibility in estimating WTP for a wide range of different circumstances. Additional details on the statistical (experimental) design
of the choice experiment is provided in later sections of this ICR

.

Comment on Survey Preparation and Pretesting Following standard practice in the stated preference literature (Johnston et al. 1995; Desvousges and Smith 1988; Desvousges et al. 1984; Mitchell and Carson 1989), all survey
elements and methods were s ubjected to extensive development and pretesting in focus groups to45 ameliorate the potential for survey biases (cf. Mitchell and Carson 1989), and to ensure that respondents have a clear understanding of the policies and goods under consideration, such tha t informed choices may be made that reflect respondents’ underlying preferences. Following the guidance of Arrow et al. (1993), Johnston et al. (1995), and Mitchell and Carson (1989), focus

groups were used to ensure that respondents are aware of their bu dget constraints, the scope of the resource changes under consideration, and the availability of substitute environmental

resources. As noted above, survey pretests included individual cognitive interviews with survey respondents (Kaplowicz et al. 2004), and think

- aloud or verbal protocol analyses (Schkade and Payne 1994). Individuals in these pretests completed draft survey questionnaires and provided comments and feedback about the survey format and content, their interpretations of the questions, and other issues relevant to stated preference estimation. Based on their responses,
EPA made improvements to the survey questionnaire. Of particular emphasis in these survey pretests was testing for the presence of potential biases including hypothetical bi as, strategic bias, symbolic (warm glow) bias, framing effects, embedding biases, methodological misspecification, and protest responses (Mitchell and Carson 1989). Based on focus group and cognitive interview responses, EPA made various improvements to t he survey questionnaire including changes to ameliorate and minimize these biases in the final survey instrument. Results from focus groups and cognitive interviews provided evidence that respondents answer the stated preference survey in ways appropriate for stated preference WTP estimation, and that their

responses generally do not reflect the biases noted above. The number of focus groups used in survey design , seven ( excluding the 12 focus groups conducted for the Phase III survey)
, exceeds the number of focus groups used in typical applications of stated preference valuation. Moreover, EPA incorporated cognitive interviews as detailed by Kaplowicz et al. (2004). We note that the current survey instrument is built upon an earlier version that was pee r reviewed in January 2006 (Versar 2006) an d it incorporates
recommendations received from that peer review panel. Given this extensive effort in survey design

— applying the most state

- of

- the

- art methods available in the literature

— EPA believes that

survey design far exceeds standards that are typical in the published literature. The details of focus groups conducted for the previous Phase III survey are discussed by EPA in a prior ICR (#2155.01 ).46 Econometric Specification Based on prior focus groups, exp ert review, and attributes of the policies under consideration, EPA anticipates that four attributes will be incorporated in the vector of variables describing attributes of an I&E reduction plan (vector X i ), in addition to the attribute characterizing una voidable household cost F i . 5

Although the literature offers no firm guidance regar ding the choice of specific functional
forms for v( . ) within choice experiment estimation, in practice
, linear forms are often used (Johnston et al. 2003b), with some researchers applying more flexible (e.g., quadratic) forms (Cummings et al. 1994). Stand ard linear forms are anticipated as the simplest form to be estimated by EPA, from which more flexible functional forms (able to capture interactions among model variables) will be derived and compared. Anticipated extensions to the simple
linear model in clude more fully

- flexible forms that allow for systematic variations in slope and intercept coefficients associated with demographic or other attributes of respondents. Such variations may be incorporated by appending the simple linear specification with quadratic
interactions between variables in vector D and the variables X i and F i (cf. Johnston et al. 2003b). These attributes will characterize the annual reduction in I&E losses ( x 1 ), anticipated effects on fish populations (all fish) ( x 2 ), anticipated
effects on commercial fish populations ( x 3 ) , and anticipated effects on aquatic ecosystem condition ( x

4 ) . These variables will allow respondents’ choices to reveal the potential impact of both annual fish losses and long

- term population effects on utility. Based on results of focus groups and expert opinion, these will be presented as averages across identified aggregate species groups. The survey will also allow for changes in baseline population levels, to assess whether WTP depends on the “starting point” of fish populations.

One may also incorporate quadratic interactions between policy attributes X i and F i , (cf. Johnston et al. 2002b). Such quadratic extensions of the basic linear model allow for additional flexibility in modeling the relationship between policy attributes (including cost) and utility, as suggested by Hoehn (1991) and Cummings et al. (1994). EPA anticipates estimating both simple linear specificat ions, as well as more fully

- flexible quadratic specifications following Hoehn (1991) and Cummings et al. (1994), to identify those models which provide the most satisfactory statistical fit to the data and correspondence to theory. EPA anticipates estimat ing all models

5 EPA plans to complete focus group testing of the instrument before the second Federal Register notice of this information collection request. The inclusion of all four attributes is an important aspect of focus group testing. If focus groups find this number cognitively challenging, the number will be reduced, an d if cognitive issues are minimal as identified by randomly selected focus group participants, all four will remain.47 within the mixed logit framework outlined above. Model fit will be assessed following standard practice in the literature (e.g., Greene 2003; Maddala 1983). Linear and quadratic functional
forms discussed here, as they are common practice in the literature, are presented and discussed in many existing sources (e.g., Hoehn 1991, Cummings et al. 1994, Johnston et al. 1999, and Johnston et al. 2003b). For example, for each choice occasion, the respondent may choose Option A, Option B,
or Neit her, where “neither” is characterized by 0 values for all attributes (except Baseline population levels). Assuming that the model is estimated using a standard approximation for the observable component of utility, an econometric specification of the desir ed model (within the overall multinomial logit model) might appear as:

v(

**⋅** ) = **β** 0 + **β** 1 ( Fish Saved ) + **β** 2 ( Change in Population s of All Fish ) + **β** 3 ( Change in Commercial Fish Population s ) + **β** 4 ( Change in Condition of Aquatic Ecosystem ) + **β** 5 (Cost)
+ **β** 6 ( Fish Sav ed )(Baseline) + **β** 7 ( Change in Population s of All Fish )(Baseline) + **β** 8 ( Change in Commercial Fish Population s )(Baseline) + **β** 9 (Change in Aquatic Ecosystem)(Baseline) + **β**

10 (Cost)(Baseline) + **β** 11 (Fish Saved)( Change in Population s of All Fish ) + **β** 12 (Fish Saved)( C hange in Commercial Fish Population s ) + **β** 13 (Fish Saved)(Change in Aquatic Ecosystem) + **β** 14 ( Change in Population s of All Fish )( Change in Commercial Fish Population s )
+ **β** 15 ( Change in Population s of All Fish )(Change in Aquatic Ecosystem) + **β** 16 (Change in Comme rcial Fish Population s )(Change in Aquatic Ecosystem)

Main effects are in bold. Interactions are in italics. This sample specification

— one of many to be estimated by EPA

— allows one to estimate the relative “main effects” of policy attributes (annual red uction in I&E losses, long

- term effects on populations of all fish , long

- term effects on commercial fish populations ) on utility, effects on aquatic ecosystem condition, as well as interactions between these main effects. This specification also allows EP A to assess the impact of baseline fish populations on the marginal value of changes in other model attributes. In sum, specifications such as this allow WTP to be estimated for a wide

- range of potential policy outcomes, and allow EPA to test for a wide

- r ange of main effects and interactions within the utility function of respondents. Such flexible utility specifications for stated preference estimation are recommended by numerous sources in the literature, including Johnston et al. (2002b), Hoehn (1991), and Cummings et al. (1994), and follow standard practice in choice modeling outlined by Louviere et al. (2000) and others.

Experimental Design48 Experimental design for the choice experiment surveys will follow established practices.
Fractional factorial design will be used to construct choice questions with an orthogonal array of attribute levels, with questions randomly divided among distinct survey versions (Louviere et al. 2000). Based on standard choice experiment experimental design procedures (Lou viere et al. 2000), the number of questions and survey versions will be determined by, among other factors:

a ) the number of attributes in the final experimental design and complexity of questions, b ) the extent to which estimation of interactions and high er

- level effects is desired, and c ) pretests revealing the number of choice experiment questions that respondents are willing/able to answer in a single survey session, and the number of attributes that may be varied within each question while maintaining respondents’ ability to make appropriate neoclassical tradeoffs.
Based on the models proposed above and recommendations in the literature, EPA anticipates an experimental design that allows for an ability to estimate main effects, quadratic effects, and two

- way interactions between policy attributes (Louviere et al. 2000). Choice sets (Bennett and Blamey 2001), including variable level selection, will be designed by EPA based on the goal of illustrating realistic policy scenarios that “span the range ove r which we expect respondents to have preferences, and/or are practically achievable” (Bateman et al. 2002, p. 259), following guidance in the literature. This includes guidance with regard to the statistical implications of choice set design (Hanemann an d Kanninen 1999) and the role of focus groups in developing appropriate choice sets (Bennett and Blamey 2001). Based on these guiding principles, the following experimental design framework is proposed by EPA. The experimental design will be conducted by Abt Associates Inc. The experimental design will allow for both main effects and selected interactions to be efficiently estimated, based on a choice experiment framework. For a more detailed discussion of the experimental design, refer to Attachment 4

. Each treatment (survey question) includes two choice Options (A and B), characterized by four attributes and a cost variable that vary across the two choice options ( Commercial Fish Populations
, Fish Populations (all fish)
, Fish Saved per Year, Condition o f Aquatic Ecosystems,
and Increase in Cost of Living of Your Household ). Hence, there are a total of ten attributes for each treatment. Based on focus groups and pretests, and guided by realistic ranges of attribute
outcomes, EPA allows for three differe nt potential levels for Commercial Fish Populations, Fish Population s (all fish)
, Fish Saved per Year, and Condition of Aquatic Ecosystems , and allows for
six different levels of annual Household Cost for the regional or national choice questions. The49 sur vey versions also include two separate treatments of location, or geographic scope; the first
version refers to policies only within the respondent’s region and the second version refers to national policies.
The number of combinations for each attribute may be summarized as follows:

 Location A , Location B (2 levels)  Commercial Fish Populations A , Commercial Fish Populations B (3 levels)  Fish Population s (all fish) A , Fish Population s (all fish) B (3 levels)  Fish Saved per Year A , Fish Saved per Year B ( 3 levels)  Condition of Aquatic Ecosystems A , Condition of Aquatic Ecosystems B ( 3 levels )  Cost A, Cost B ( 6 levels )
Beyond the levels specified above, each question will include a “ no policy ” option, characterized by baseline levels for each attr ibute including a household cost of $0. Following standard practice, EPA constrained the design somewhat in response to findings in seven focus groups and the prior literature. For example, the focus groups showed that respondents react negatively and oft en protest when offered choices in which one option dominates the other in all attributes. Given that such choices provide negligible statistical information compared to choices involving non

- dominant/dominated pairs, they are typically
avoided in choice experiment statistical designs. For example, Hensher and Barnard (1990) recommend eliminating profiles including dominating or dominated profiles, because such profiles generally provide no useful information. Following this guidance, EPA constrained the design to eliminate such dominant/dominating pairs. EPA also constrained the design to eliminate the possibility of pairs in which, when looking across two options, one of the options offers both a greater reduction in fish losses and a smaller increase i n the population. The elimination of such nonsensical (or non

- credible) pairs is common practice, and is done to avoid protest bids and confusion among respondents (Bateman et al. 2002). The resulting experimental design is characterized by 72 unique A vs . B option pairs, where attribute levels for option A and B differ across each of the pairs. Each pair represents a unique choice modeling question

— with a unique set of attribute levels distinguishing options A and B. Following standard practice for mail surveys, these questions will be randomly assigned to survey respondents, with each respondent considering three questions.

Information Provision50 According to Arrow et al. (1993, p. 4605), if “surveys are to elicit useful information about willingness to pay, respondents must understand exactly what it is they are being asked to
value.” It is also well known that the provided information can influence WTP estimates derived from stated preference survey instruments and that respondents must be provided with sufficient information to make an informed assessment of policy impacts on utility (e.g., Bergstrom and Stoll 1989; Bergstrom et al. 19 8 9 ; Hoehn and Randall 2002). As stated clearly by Bateman et al. (2002, p. 122), “[d]escribing the good and the pol icy context of interest may require a combination of textual information, photographs, drawings, maps, charts and graphs. ...[V]isual aids are helpful ways of conveying complex information...while simultaneously enhancing respondents’ attention and interest.” Given that many respondents may not be fully familiar with the details of programs to reduce I&E mortality losses and potential impacts on aquatic life, the survey will inclu de introductory figures to aid respondents’ comprehension of the goods and polici es addressed by the survey instrument, and to encourage appropriate neoclassical tradeoffs in responding to choice experiment questions. Following this guidance of Bateman et al. (2002) and prior examples of Opaluch et al. (1993) and Johnston et al. (2002 a), among others, EPA extensively pretested all graphics used in
the draft mail survey , to ensure that these graphical elements were not prejudicial, and that they did not bias responses. Graphics judged to be prejudicial or confusing to respondents durin g the seven focus groups and cognitive interviews were revised or replaced. EPA acknowledges that certain types of graphics can be prejudicial in certain contexts

— and hence all graphical elements were pretested extensively

. EPA found that focus group resp ondents endorsed the use of graphics in the survey booklet and indicated that they helped them to visualize how fish are entrained and impinged, technological solutions, facilities locations, and ecosystem effects. Participants made such statements as , “Y eah, I’d rather have them” and “I like on page 2 the graph and illustration because the adage a picture is worth a thousand words”. EPA also emphasizes that there is no precedent or support in the literature for the total elimination of graphics in survey instruments. To the contrary, the literature explicitly indicates that pictures and graphics may be necessary and useful components of survey instruments in many cases (Bateman et al. 2002). EPA highlights that numerous peer

- reviewed surveys described i n the literature include pictures and graphics both in survey instruments and in introductory materials such as slide shows. For example, see Horne et al. (2005), Ready et al. (1995), Powe and Bateman (2004)
, Duke and Ilvento (2004), Opaluch et al. (1993) , Johnston et al. (1999, 2002a,51 2002b), and Mazzotta et al. (2002). Bateman et al. (2002) also includes examples of various types of survey materials including pictures and graphical elements.

Amelioration of Hypothetical Bias
EPA considers the amelior ation of hypothetical bias to be a paramount concern in survey design. However, the agency acknowledges

— based on prior evidence from the literature

— that hypothetical bias is not unavoidable. For example, not all research finds evidence of hypothetical bi as in stated preference valuation (Champ and Bishop 2001; Smith and Mansfield 1998; Vossler and Kerkvliet 2003; Johannesson 1997), and some shows that hypothetical bias may be ameliorated using cheap

- talk, certainty adjustments, or other mechanisms (Champ et al. 1997; Champ et al. 2004; Cummings and Taylor 1999; Loomis et al. 1996). To obtain reliable estimates of WTP, the Agency tested and design ed all survey elements to promote incentive compatible preference elicitation mechanisms

. Incentive compatible stated preference surveys provide no incentive for non

- truthful preference revelation (Carson and Groves 2007). The literature is clear regarding the importance of incentive compatibility in stated preference value elicitation and the role of both questio n format and scenario consequentiality in ensuring this property (Carson et al. 2000; Carson and Groves 2007; Collins and Vossler 2009; Herriges et al. 2010; Johnston 2006; Vossler and Evans 2009). It has been established that
referendum

- type stated prefe rence choices are incentive compatible given that certain conditions are met, including the condition that responses are believed by respondents to be consequential, or potentially influencing public policy decisions (Carson and Groves 2007; Herriges et al

. 2010). The survey is explicitly designed to emphasize the importance of the budget constraint and program cost. For example, the survey asks respondents to compare protecting aquatic ecosystems to other policy issues which the government could potentia lly ask households to pay

costs. The survey itself includes explicit reminders of program cost and the budget constraint. The survey has also been explicitly designed to maximize the consequentiality of choice experiment questions, thereby maximizing inc entive compatibility (i.e., reducing strategic and hypothetical biases), following clear guidance of Carson et al. (2000). Elements specifically designed to maximize consequentiality include : a ) explicit ly mention ing that this survey is
associated with as sessment of proposed policies that are being considered, b ) numerous details provided in the survey concerning specifics of the proposed policies, and c ) emphasis that the52 type of policy enacted will depend in part on survey results and that their vote is important

. Johnston and Joglekar (2005) show the capacity of such information to eliminate hypothetical
bias in choice

- based stated preference WTP estimation. Focus groups and cognitive interviews indicated that r espondents viewed choices as consequenti al, that they considered their budget constraints when responding to all questions, and that they would answer the same way were similar questions asked in a binding referendum.
W hen asked if they thought about the program cost in the same way as “money c oming out of their pocket,” the vast majority of focus group and interview respondents indicated that they treated program costs the same way that they would have if there were actual money consequences. For example, respondents made statements such as “ N o. [M y vote] would have been the same actually” and “ If I believed that it was gonna affect regulations, I think I would have voted the exact same way

. ” EPA does not anticipate significant hypothetical bias in the proposed survey based on focus group resul ts. Focus groups respondents took the survey questions seriously and indicated that they though that their choices would actually influence policy. Regarding the potential use of cheap talk mechanisms or other devices to further address the potential for hypothetical bias, the Agency emphasizes that the literature is mixed as to their performance. For example, the seminal work by Cummings and Taylor (1999) shows that cheap talk is able to reduce hypothetical biases. Similar results are shown by Aadland a nd Caplan (2003). However, other authors (e.g., Cummings et al. 1995; List 2001; Brown et al. 2003) find that a cheap talk script is only effective under certain circumstances, and for certain types of respondents. For example, Cummings et al. (1995) fin d that a relatively short cheap talk script actually worsens hypothetical bias, while a longer script appears to ameliorate bias. Brown et al. (2003) finds cheap talk only effective at higher bid amounts

— a result mirrored by Murphy et al. (2004). Still

o ther authors find no effect of cheap talk, including Poe et al. (2002). Given the clearly mixed experiences with such mechanisms, EPA is not convinced that cheap talk scripts are likely to provide a panacea for hypothetical bias in the present case

— althou gh they appear to reduce bias
in a limited set of circumstances

– and cheap talk is not included in the survey.

Amelioration of Symbolic Biases and Warm

- Glow Effects Following clear guidance of Arrow et al. (1993) and others, EPA has taken repeated steps to ensure that survey responses reflect the value of the affected fish resources only, and do not53 reflect symbolic or warm glow concerns (Mitchell and Carson 1989). Following explicit guidance of the NOAA Blue Ribbon Panel on Contingent Valuation (Arrow et al. 1993, p. 4609), EPA has explicitly designed all elements of the survey to “deflect the general ‘warm glow’ of giving or the dislike of ‘big business’ away from the specific program that is being valued.” This was done in a variety of ways, based on prior examples in the literature , such as asking respondents to reflect on importance of attributes before making selections, and using a payment vehicle that doesn’t raise trust issues (cost of living increase rather than an electric bill increase)

. The focus group and cognitive interview results indi cated that most participants answered the choice questions based on the effects discussed in the survey, not on a desire to help the environment in general. The survey includes clear language to instruct res pondents only to consider the specific attributes in the survey, and not to base answers on broader environmental concerns including
the statement that:

“ Scientists expect that effects on the environment and economy not shown explicity will be small. For example, studies of industry suggest that effects on employment will be close to zero. ” This is also consistent with the statement from Arrow et al. (1993) that a referendum

- type format may limit the warm

- glow effect. Some focus group participants indica ted that they were inclined to support environmental causes and would like “to do a good thing” but still considered the cost and effects under the policy options. For example, respondents stated, “[...] if we can do something to help as long as the price is right, then do it” and “I feel if it’s going to be benefit everyone and be better for the economy, I’m OK with paying a little bit more. ” This evidence notwithstanding, EPA believes that it is important to include follow

- up questions to ensure that respo nses do not reflect symbolic biases. Question 9 in the survey
instrument

— which address es the rationale for choice responses given earlier in the draft

survey

— explicitly test s for the presence of symbolic or warm

- glow biases. Follow

- up questions
such as t hese are common in stated preference survey instruments, to assess the underlying reasons for the observed valuation responses (e.g., Mitchell and Carson 1984).

Assessing Scope Sensitivity The NOAA Blue Ribbon Panel on Contingent Valuation (CV) (Arrow et al. 1993, p. 4605) states clearly that if “surveys are to elicit useful information about willingness to pay, respondents must understand exactly what it is they are being asked to value (or vote upon)...”54 They further indicate that surveys providing “sketch y details” about the results of proposed policies call “into question the estimates derived there from,” and hence suggest a high degree of detail and richness in the descriptions of scenarios. Similar guidance is provided by other key
sources in the CV l iterature (e.g., Mitchell and Carson 1989; Louviere et al. 2000). Among the reasons for this guidance is that such descriptions tend to encourage appropriate framing and sensitivity to scope. Following Arrow et al. (1993), Mitchell and Carson (1989), and others, while noting the clear limitations in scope tests discussed by Heberlein et al. (2005), EPA believes that it is important that survey responses in this case show sensitivity to scope. This is one of the primary
reasons for the use of the choice ex periment methodology, which is better able to capture WTP differentials related to changes in resource scope (Bateman et al. 2002). Unlike open

- ended questions, in which scope insensitivity is a primary concern, EPA emphasizes that choice experiments gene rally have shown much less difficulty with respondents reacting appropriately to the scope and scale of resource changes. Moreover, as clearly noted by Bennett and Blamey (2001, p. 231), “internal scope tests are automatically available from the results o f a [choice modeling] exercise.” That is, within choice experiments, sensitivity to scope is indicated by the statistical significance and sign of parameter estimates associated with program attributes (Bennett and Blamey 2001). Internal scope sensitivi ty will therefore be assessed through model
results for the variables Commercial Fish Populations, Fish Populations (all fish)
, Fish Saved per Year, and Condition of Aquatic Ecosystems . Statistical significance of these variables

— along with a positive sig n

— indicates that respondents, on average, are more likely to choose plans with larger quantities of these variables. In addition to internal scope tests implicit in all choice experiment statistical analysis, EPA will also conduct external scope tests (c f. Giraud et al. 1999). The primary difference between internal and external tests is that the former assess sensitivity to scope across choices of a single respondent, while the latter involves split

- sample assessments across different respondents. With in a choice modeling context, external scope tests are generally considered “stronger,” although also more likely to be confounded by differences in the implied choice frame (Bennett and Blamey 2001). A variety of options for external scope tests exist, d epending
on the structure of the stated choice questions under consideration. In the present case, attribute

- by

- attribute external scope tests will be conducted over a split sub

- sample of respondents considering a specific set of choices, with all held con stant55 across the considered choices except the scope of the attribute for which the test is to be conducted. For example, to conduct an external scope test for reductions in annual fish losses,
one would consider a set of choices that is identical over tw o respondent groups, except that one considers a choice with a greater reduction in fish losses. Assessing the choices over this split sample allows for an external test of scope. To illustrate this test, consider the following stylized choice between Op tion A and Option B. The generic labels “Level 0”, “Level 1”, and “Level 2” are used to denote attribute levels, where for all attributes Level 2 > Level 1 > Level 0.

Table B2: Illustration of an External Scope Test

Variable Option A Option B
Fish Saved per Year Sample 1: Fish Saved Level 1 Sample 2: Fish Saved Level 2 Fish Saved Level 0

Commercial Fish Populations Commercial Fish Populations
Level 0 Commercial Fish Populations
Level 0
Fish Populations (all fish) Population (all fish) Level 0 Population (all fish) Level 0
Condition of Aquatic Ecosy s tems Aquatic Ecosystem Condition
Level 0 Aquatic Ecosystem Condition
Level 0
Increase in Cost of Living for Your Household Cost Level 1 Cost Level 0

In the above example, only Fish Saved per Year and Cost vary across the choice options.
Because both Fish Saved per Year (at Level 1 and Level 2) and Cost are higher in Option A than in Option B, neither option is dominant. In the illustrated split

- sample test, respondent sample 1
view s the choice with Fish Saved per Year at Level 1, while respondent sample 2 views an
otherwise identical choice with Fish Saved per Year at Level 2, where Level 2 > Level 1. If responses are externally sensitive to scope in Fish Saved per Year , this will manifest in a greater proportion of sample 2 respondents choosing Option A than sample 1 respondents. This hypothesis may be easily assessed using a test of equal proportions across the two sub

- samples, and provides a simple attribute

- by

- attribute test of external scope. Analogous tests may be conducted for all attributes within the choice experiment design, using parallel methods. EPA emphasizes that the formal applicability of the above

- noted scope test is contingent upon the specific choice frame impli ed by levels of other attributes in the choice question. This is a56 characteristic of nearly all external scope tests applied in choice experiment frameworks (Bennett and Blamey 2001). Split

- sample tests such as those proposed above often require the addit ion of question versions to the experimental design, to accommodate the specific structural needs of the
attribute

- by

- attribute external scope test. Otherwise, confounding effects of other varying
attributes (including demographic information) can render results of scope tests ambiguous. In the present case, the proposed tests would require the addition of up to six unique question versions to the experimental design, enabling scope tests for the three non

- cost attributes within the 316(b) choice experime nt scenarios. If scope tests in additional question frames are desired (e.g., the same scope test illustrated above, but given Level 1 for commercial fish populations
, fish population (all fish) , and aquatic ecosystem condition attributes ), still addition al question versions would be added. While small numbers of questions added to the experimental design should have minimal impacts on overall efficiency (e.g., orthogonality of the design), larger numbers may have a more significant impact. Hence, given constraints on the total number of survey respondents, there is a potential empirical tradeoff between the number of external scope tests that may be conducted and the efficiency of the experimental design and statistical analysis.

Communicating Uncertain ty to Respondents
EPA believes that the role of risk and uncertainty is an important issue to be addressed in the development of benefits estimates, and points out that the literature provides numerous examples of cases in which appropriate survey design, including focus groups, was used to successfully address such concerns. For example, as stated by Desvousges et al. (1984), “using contingent valuation to estimate the benefits of hazardous waste management regulations requires detailed information on how and the extent to which respondents understand risk (or probability) and how government regulatory actions might change it... Using focus groups helped make this determination...” EPA also emphasizes that all regulatory analyses involve uncertainty of some t ype (Boardman et al. 2001). The ecological outcome of I&E reductions is subject to considerable uncertainty. EPA believes that it is important that survey respondents be aware of this uncertainty, and that their responses reflect the knowledge that the resource changes reflected in the survey are scientific estimates. However, EPA is also aware of the clear advice from the choice modeling literature (e.g., Bennett and Blamey 2001; Louviere et al. 2000) to avoid cognitive burden on respondents.57 Hence, t he proposed survey materials clearly indicate the uncertainty involved with the described resource changes in choice modeling scenarios, yet do so in a way designed to minimize cognitive burden. For example, prior to answering choi c e experiment questions, respondents are told :

“ Although scientists can predict the number of fish saved each year, the effect on fish population s is uncertain. This is because scientists do not know the total number of fish in Northeast waters and because many factors

– such as cooling water use, fishing, pollution and water temperature

– affect fish populations. ” Th is statement clearly indicate s the uncertainty involved with scientific estimates of the outcomes of I&E regulations. This is followed by a further reminder of unce rtainty:

“ Depending on the type of technology and other factors, effects on fish and ecosystems may be different

– even if the annual reduction in fish losses is similar .” Focus groups and cognitive interviews participants understood that the ecological c hanges described in the survey were uncertain, and most participants were comfortable making decisions in the presence of this uncertainty. Their responses indicated that they understood this uncertainty based on the information presented in the introducto ry material and considered it when evaluating policy options. Respondents made such statements as: “My guess is that it did come from studies but I have a healthy dose of skepticism about the accuracy of it. I don’t think it’s been in any way skewed purpos efully, but I know that this is a best guess, reasonable guess perhaps”
, “it shows me that they are being honest for the most part. You know, you can't obviously be accurate on everything, but this is a kind of a best guess ” , “[...] They had more
numbers on the commercial fish population. The rest was more of a guesstimat e”, and “you don’t know the exact number and nobody knows

. ”
In previous focus groups conducted for the Phase III survey
, EPA tested alternative
versions of the Phase III survey instrument in which choice experiment attributes were presented as 90% confidence ranges, rather than as point estimates. Focus group r espondents were explicitly asked whether the ranges were helpful in understanding the uncertainty of estimates presented in the choice question or whether they were a source of confusion. Seven out of the eight respondents interviewed on that occasion indicated that th e use of ranges was more confusing than the use of point estimates

. Furthermore, respondents were comfortable making
de cisions in the presence of this uncertainty.

5(c) Reporting Results58 The results of the survey will be made public as part of the benefits analysis for the 316(b) regulation for existing facilities. Provided information will include summary statistics f or the survey data, extensive documentation for the statistical analysis, and a detailed description of the final results. The survey data will be released only after it has been thoroughly vetted to ensure that all potentially identifying information has been removed.59 REFERENCES

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- 178.68 Attachment 1: Full Text of Regional State d Preference Survey Component (Northeast Regional Example)69 

# Fish and Aquatic Habitat

A Survey of Northeast Residents (CT, DC, DE, MA, MD, ME , NH, NJ, NY, PA, RI, VT)

The public reporting and recordkeeping burden for this collection of information is estimated to average 30 minutes per response. Send comments on the Agency's need for this information, the accuracy of the provided burden estima tes, and any suggested methods for minimizing respondent burden, including through the use of automated collection techniques to the Director, Collection Strategies Division, U.S. Environmental Protection Agency (2822T), 1200 Pennsylvania Ave., NW, Washing ton, D.C. 20460. Include the OMB control number in any correspondence. Do not send the completed survey to this address. OMB Control No. 2040

- XXXX Approval expires XX/XX/XX70 

# HUMAN ACTIVITIES, AQ UATIC HABITAT AND FISH

This survey asks for your opinions regarding policies that would affect fish and habi tat in the Northeast U.S

. Your answers will help the government decide which policies will be enacted. Background information in this survey was provided by the National Marine Fisheries Service, U.S. Environmental Protection Agency, U.S. Geological Surve y and other state and federal offices

. Northeast fresh and salt waters support billions of fish. These include fish that are used by humans, as well as forage fish that are not used by humans, but serve as food for larger fish, birds, and animals.

Th is survey concerns proposed policies that would reduce fish losses caused by cooling water use by industrial facilities, including factories and power plants. These policies would benefit aquatic ecosystems but would increase the costs of some goods and se rvices you buy, including electricity and common household products.

1



## 1 Natural factors such as weather have always i nfluenced fish, but in recent years human activities have had an increasing effect.
Activities that affect fish include fishing, pollution, commercial and residential development, and the extraction of cooling water at industrial facilities.

Declines i n fish can affect the condition of ecological systems, food webs, and related human uses such as fishing. Food Web Birds/Mammals Fish Micro

organisms71 

# HOW DOES COOLING WAT ER AFFECT FISH?

The water that industrial facilities use to cool equipment is pumped from bays, rivers, and lakes. The largest amount is used by power plants that produce electricity.

The equipment that pumps the cooling water kills small fish and fish eggs.
Juvenile fish and eggs move through screens and into the cooling system where they are killed by high temper ature. Large fish may be injured or killed against screens or filters.
Pumping warm water back into the environment (called thermal discharge ) also affects ecological systems. Cooling Water Intake Screen



## 2 Cooling water use affects fresh and salt waters throughout the Northeast US, but the majority of all fish losses are in salt waters such as coastal bays. How Fish Are Affected by Water Intake72 

# WHAT KINDS OF FISH A RE AFFECTED?

Cooling water use is not the largest cause of fish loss in most areas (fishing causes greater losses), but has affected some fish populations.

About 1/6 of the fish lost are specie s caught by commercial and recreational fishermen. Examples include striped bass
, flounder , and cod

.

The other 5/6 of the fish lost are forage species not caught by humans but are part of the food web. Examples include killifish
, silverside , and stickleb ack

. Question 1. When thinking about how industrial facilities use cooling water, please rate the importance of the following to you. Check one box for each.

Not Important Somewhat Important Very Important



### 1. Preventing the loss of fish that are caught by humans 1 2 3 4 5



### 2. Preventing the loss of fish that are not caught by humans 1 2 3 4 5



### 3. Maintaining the ecological health of rivers, lakes and bays 1 2 3 4 5



### 4. Keeping the cost of goods and services low 1 2 3 4 5



### 5. Making s ure there is enough government regulation of industry 1 2 3 4 5



### 6. Making sure there is not too much government regulation of industry 1 2 3 4 5



## 373 

# HOW MANY FISH ARE AF FECTED?

After accounting for the number of eggs and larvae that would be ex pected to survive to adulthood, scientists estimate that the equivalent of about 1.1 billion young adult fish (the equivalent of one year old) are lost each year in Northeast coastal and fresh waters due to cooling water use.
Scientists can predict the number of these fish that will be saved under different policies. This number ranges from 0.3 to 1.0 billion fish saved per year.
For commercial fish species, losses of young fish in cooling water intakes vary by species, from the equivalent of less tha n 0.1% to about 10% of total populations.
Yearly effects on fish species are between these levels. For example, the number of young fish lost in cooling water intakes relative to the total number of fish in the water is relatively high for some species, b ut low for others.

Although scientists can predict the number of fish saved each year, the effect on fish populations is uncertain. This is because scientists do not know the total number of all fi sh in Northeast waters and because many factors

– such as cooling water use, fishing, pollution and water temperature

– affect fish populations.
The following page provides information on policies that would be required to reduce these fish losses. Largest Fish Losses per Year

Total Fish Population Losses 10% Smallest Fish Losses per Year

Losses < 0.1%

Total Fish Population

Smaller effect on Str iped Bass Larger effect on Winter Flounder 

## 4 Smaller effect on Striped Bass Larger e ffect on Winter Flounder74 

# NEW REGULATIONS ARE BEING PROPOSED TO PROTECT FISH

Current Situation

1.1 Billion Fish Lost per Year (0% saved)

With Advanced Filters

0.8 Billion Fish Lost per Year ( 25% Saved) 0.3 Billion Fish Saved per Year

With Closed Cycle Cooling

<0.1 Billion Fish Lost per Year (95% saved) >1.0 Billion Fish Saved per Year



### Advanced filters and closed cycle cooling are already in use at many facilities and are proven technologies. New regulations would require a mix of advanced filters and closed cycle cooling at all facilities

— with reductions in fish losses between 25% and 95%.

The government is considering policie s that would require new measures to protect fish.

One policy would require advanced filters that block fish from entering cooling water facilities. Requiring advanced filters could reduce fish losses about 25%

.

Another possibility is closed cycl e cooling that recycles and reuses cooling water, so that less water is needed. Requiring closed cycle cooling could reduce fish losses by 95% and also reduces thermal discharge

. However, costs are higher than for advanced filters.



## 575 

# HOW IMPORTANT ARE TH ESE ISSUES TO YOU?

While these policies would reduce fish losses, they would also increase the costs of producing many goods and services

— these costs would be passed on to consumers like you.

Question 2. Compared to other issues that the government might address

— such as public safety, education and health

— how important is protecting aquatic ecosystems to you? Check one b ox.

Not Important Somewhat Important Very Important

Protecting aquatic ecosystems is 1 2 3 4 5



### The government needs to know whether households are willing to pay the costs of these new policies.
This survey will ask you to co mpare policies with different effects on cooling water use, fish, and costs to your household. You will be asked to vote for the options you prefer.
You will also have the opportunity to support the current situation, with no new policies, and no new cost s to your household.



## 676 

# THIS SURVEY IS SIMIL AR TO A PUBLIC VOTE

The next part of this survey will ask you to consider different types of policies to protect fish, and indicate how you would vote. Effects of each possible policy will be described using the following scores:


## Effect of

Policy What It Means

Commercial Fish Populations (Fish Used by People) 

### A score between 0 and 100 showing the overall health of commercial and recreational fish populations . Higher scores mean more fish and greater fish ing potential. A score of 100 means that these fish populations are at a size that maximizes long

- term harvest; 0 means no harvest. The current score in Northeast waters is 43.

Fish Populations (All Fish) 

### A score between 0 and 100 showing the estimated size of all fish populations compared to natural levels without human influence. A score of 100 means that populations are the largest natural size possible; 0 means no fish. The current score in Northeast waters is 31.

Fish Saved

(per Year) 

### A score between 0 and 100 showing the reduction in young fish lost because of the new policy. A score of 100 means that no fish are lost in cooling water intakes (all fish are saved ). The current score in Northeast waters is 0; this represents the status quo with no new policies.

Condition of Aquatic Ecosystems 

### A score between 0 to 100 showing the ecological condition of affected areas , compared to the most natural waters in the Northeast. The score is determined by many factors including water quality and tem perature, the health of aquatic species, and habitat conditions. Higher scores mean the area is more natural

. The current score in Northeast waters is 48. 

# $ Cost per Year 

### How much the policy will cost your household, in unavoidable price increases for p roducts and services you buy, including electricity and common household products.



## 777 

# HOW WOULD YOU RATE T HE IMPORTANCE OF THESE EFFECTS?

Question 3. When considering policies that affect how facilities use cooling water, how important to you are effects on each of the following scores? Check one box for each. (For reminders of what the scores mean, please see page 7).

Not Important Somewhat Important Very Important

1. Effect on commercial fish populations 1 2 3 4 5



### 2. Effect on the fish populations (for all fish) 1 2 3 4 5



### 3. Effect on fish saved 1 2 3 4 5



### 4. Effect on the condition of aquatic ecosystems 1 2 3 4 5



### 5. Effect on cost to my household 1 2 3 4 5



### The next questions will ask you to choose between different po licy options that would affect fish losses in cooling water systems. You will be given choices and asked to vote for the choice you prefer by checking the appropriate box. Questions will look similar to the sample on the next page.



## 878 

# SAMPLE QUESTION Quest ions will look like the s ample below

.

Policy Effect Current Situation

(No policy) 

## Option A Option B

Commercial Fish Populations (in 3

- 5 Years) 

# 43 %
(100% is populations that allow for maximum harvest) 

# 45 %
(100% is populations that allow for maximum h arvest) 

# 47 %
(100% is populations that allow for maximum harvest)

Fish Populations (all fish) (in 3

- 5 Years) 

# 31 %
(100% is populations without human influence) 

# 34 %
(100% is populations without human influence) 

# 38 %
(100% is populations without human influ ence)

Fish Saved per Year (Out of 1.1 billion fish lost in water intakes) 

# 0 %
No change in status quo 

# 25 %

0.3 billion fish saved 

# 50 %

0.6 billion fish saved

Condition of Aquatic Ecosystems (in 3

- 5 Years) 

# 48 %
(100% is pristine condition) 

# 48 %
(100% i s pristine condition) 

# 50 %
(100% is pristine condition) 

# $

Increase in Cost of Living for Your Household 

# $0

No cost increase 

# $24

per year ($2 per month) 

# $36

per year ($3 per month)



### HOW WOULD

YOU VOTE? (CHOOSE ONE ONLY) I would vote for NO POL ICY I would vote for OPTION A I would vote for OPTION B

If you prefer Option A, che ck this box If you do not want A or B, check this box If you prefer Option B, check this box 

# X X X

979 

# AS YOU VOTE PLEASE R EMEMBER

**•** The map below shows the facilities and areas that would be affected by the proposed policies.

**•** The policy options (A and B) given to you each require a dif ferent mix of advanced filters and closed cycle cooling in different areas, so effects on fish are different.

**•** You will be shown different questions, with different combinations of technology and different costs

**•** Depending on the policies chosen, costs to your household could range from $0 per month to a maximum of $6 per month.

**•** Depending on the type of technology required and other factors, effects on fish and ecosystems may be different

— even if the annual reduction in fish losses is similar.

**•** Consider each pair of policy options separately

— do not add them up or compare programs from different pages

**•** Scientists expect that effects on the environment and economy not shown explicitly will be small. For example, studies of industry suggest that effects on emplo yment will be close to zero. .

**•** Your votes are important. Answer all questions as if this were a real, binding vote.



## 1080 

## Question 4. Assume that Options A and B would require a different mix of filters and closed cycle cooling in different areas. Assume all types of fish are affected. How would you vote?

Policy Effect

NE Waters Current Situation

(No policy) 

## Option A NE Waters Option B NE Waters

Commercial Fish Populations (in 3

- 5 Years) 

# 43 %
(100% is populations that allow for maximum harvest) 

# 44 %
(100% is populations that allow for maximum harvest) 

# 45 %
(100% is populations that allow for maximum harvest)

Fish Populations (all fish) (in 3

- 5 Years) 

# 31 %
100% is populations without human influence) 

# 32 %
(100% is populations without human influence) 

# 35 %
(100% is populations without human influence)

Fish Saved per Year

(Out of 1.1 billion fish lost in water intakes) 

# 0 %
No change in status quo 

# 25 %

0.3 billion fish saved 

# 50 %

0.6 billion fish saved

Condition of Aquatic Ecosystems (in 3

- 5 Years) 

# 48 %
(100% is pristine condition) 

# 49 %
(100% is pristine condition) 

# 50 %
(100% is pristine condition) 

# $

Increase in Cost of Living for Your Household 

# $0

No cost increase 

# $24

per year ($2 per month) 

# $36

per year ($3 per month)



### HOW WOULD

YOU VOTE? (C HOOSE ONE ONLY) I would vote for NO POLICY I would vote for OPTION A I would vote for OPTION B



## 1181 

# POLICIES COULD REQUI RE DIFFERENT COMBINATIONS OF TECH NOLOGY

Now you will be asked to consider a new set of policy options for Northeast waters. A s you vote, please remember

—

**•** Questions 5 and 6 present new sets of policy options. These options require a different mix of technologies in different areas.

**•** Each question is a separate vote. Questions 5 and 6 cannot

**•** be directly compared to each other, or to Question 4. Do not add up

**•** effects or costs across different questions. Policy costs and effects depend on many factors . Saving more fish does not



## 12 necessarily mean that all effects will improve.82 

## Question 5. Assume that Options A and B would require a different mix of filters and closed cycle cooling in different areas. Assume all types of fish are affected. How would you vote?

Policy Effect

NE Waters Current Situation

(No policy) 

## Option A NE Waters Option B NE Waters

Commercial Fish Population s (in 3

- 5 Years) 

# 43 %
(100% is populations that allow for maximum harvest) 

# 45 %
(100% is populations that allow for maximum harvest) 

# 47 %
(100% is populations that allow for maximum harvest)

Fish Populations (all fish) (in 3

- 5 Years) 

# 31 %
(100% is populat ions without human influence) 

# 33 %
(100% is populations without human influence) 

# 36 %
(100% is populations without human influence)

Fish Saved per Year

(Out of 1.1 billion fish lost in water intakes) 

# 0 %
No change in status quo 

# 25 %

0.3 billion fish saved 

# 75 %

0.8 billion fish saved

Condition of Aquatic Ecosystems (in 3

- 5 Years) 

# 48 %
(100% is pristine condition) 

# 48 %
(100% is pristine condition) 

# 52 %
(100% is pristine condition) 

# $

Increase in Cost of Living for Your Household 

# $0

No cost increase 

# $36

per year ($3 per month) 

# $60

per year ($5 per month)



### HOW WOULD

YOU VOTE? (CHOOSE ONE ONLY) I would vote for NO POLICY I would vote for OPTION A I would vote for OPTION B



## 1383 

## Question 6. Assume that Options A and B would require a different mix of filters and closed cycle cooling in different areas. Assume all types of fish are affected. How would you vote?

Policy Effect

NE Waters Current Situation

(No policy) 

## Option A NE Waters Option B NE Waters

Commercial Fish Populations (in 3

- 5 Year s) 

# 43 %
(100% is populations that allow for maximum harvest) 

# 50 %
(100% is populations that allow for maximum harvest) 

# 47 %
(100% is populations that allow for maximum harvest)

Fish Populations (all fish) (in 3

- 5 Years) 

# 31 %
(100% is populations without h uman influence) 

# 39 %
(100% is populations without human influence) 

# 36 %
(100% is populations without human influence)

Fish Saved per Year

(Out of 1.1 billion fish lost in water intakes) 

# 0 %
No change in status quo 

# 95 %

1.0 billion fish saved 

# 50 %

0.6 billi on fish saved

Condition of Aquatic Ecosystems (in 3

- 5 Years) 

# 48 %
(100% is pristine condition) 

# 52 %
(100% is pristine condition) 

# 52 %
(100% is pristine condition) 

# $

Increase in Cost of Living for Your Household 

# $0

No cost increase 

# $72

per year ($6 p er month) 

# $24

per year ($2 per month)



### HOW WOULD

YOU VOTE? (CHOOSE ONE ONLY) I would vote for NO POLICY I would vote for OPTION A I would vote for OPTION B



## 1 484 

### Question 7. If you always voted for NO POLICY in questions 4

- 6 , what was the pri mary reason? Check one. (Skip this question if you voted for Option A or B in any question above.) ____ The cost to my household was too high ____ Preventing fish losses is not important to me ____ I do not trust the government to fix the problem ____ I w ould rather spend my money on other things ____ I did not believe the choices were realistic ____ Since the problem was created by private facilities, they should fix it without passing costs on to consumers

Question 8. Indicate how strongly you agree wi th the following statements about questions 4

- 6 and the information provided. Check one box for each.

Strongly Disagree Disagree Neutral Agree Strongly Agree



### The survey provided enough information for me to make informed choices 1 2 3 4 5



### I fe el confident about my answers 1 2 3 4 5 

### Information in the survey was easy for me to understand 1 2 3 4 5 

### Information in the survey was fair and unbiased 1 2 3 4 5 

### Questions were easy for me to answer 1 2 3 4 5


### I would vote the sam e way in an actual public vote 1 2 3 4 5 

### The effect of the proposed policies depends on many factors 1 2 3 4 5 

### Future ecological conditions are never 100% guaranteed 1 2 3 4 5



## 1585 

### Question 9. How much did the following factors affect you r answers to questions 4

– 6 ? Check one box for each row

.

Effect on my answers to questions 4

- 6 

### Very Small Effect Moderate Effect Very Large Effect

. 

### Wanting to reduce taxes or costs to my household. 1 2 3 4 5 

### Wanting to prevent th e loss of industrial jobs. 1 2 3 4 5 

### Wanting to preserve fish for commercial fishing. 1 2 3 4 5 

### Wanting to send a message that all environmental issues are important regardless of cost. 1 2 3 4 5


### Wanting to preserve fish for recreation (f ishing, etc.). 1 2 3 4 5 

### Wanting to preserve fish to benefit aquatic ecosystems. 1 2 3 4 5 

### Wanting to know that fish exist in local lakes, rivers and bays. 1 2 3 4 5 

### Wanting to pay my fair share for government programs. 1 2 3 4 5


### Wa nting to sustain the competitiveness of US business 1 2 3 4 5 

### Wanting to preserve fish as a source of food for people. 1 2 3 4 5 

### Wanting to preserve fish and ecosystems for future generations. 1 2 3 4 5



## 1686 

### Question 10. How many days did you participate in the following during the last year? For trips longer than one day, please count each day separately. Check one box for each row

.

Number of days you did the activity during the past year

0 1
- 5 6
- 10 11
- 15 16+
Boating / Canoe ing / Kayaking 1 2 3 4 5 Swimming / Going to the Beach 1 2 3 4 5 Recreational Fishing (Fresh Water) 1 2 3 4 5 Recreational Fishing (Salt Water) 1 2 3 4 5 Shellfishing / Crabbing 1 2 3 4 5 Scuba Diving / Snorkeling 1 2 3 4 5

18


## 1787 

## The following questions ensure that all groups are fairly represented. **All answers are anonymous and confidential.**

11. What is your age?

___ years

12. What is your gender?  Male  Female

13. What is the highest level of education that you have comp leted?  Less than high school  One or more years of college  High school or equivalent  Bachelor’s Degree  High school + technical school  Graduate Degree

14. How many people

15. How many of these people are 16 years of age or older? ____ live in your household?

______________

16. How many of these people are 6 years of age or younger? ____

17. What is your zip code?

_____________________________
18. What town and state do you live in? Town:

_____________ State:____

19. Are you currently employed?

___ Yes

_____ No

20. What category comes closest to your total household Less than $10,000 

### income? $60,000 to $79,999 $10,000 to $19,999 $80,000 to $99,999 $20,000 to $39,999 $100,000 to $249,999 $40,000 to $59,999 $250,000 or more



### 21. If you have any comments on this survey, please write them below:

**Thank you f or your participation in this important survey!** 



## 1888 Attachment 2 : Full Text of National Stated Preference Survey Component89 

# Fish and Aquatic Habitat

A Survey of US Households

The public reporting and recordkeeping burden for this collection of informat ion is estimated to average 30 minutes per response. Send comments on the Agency's need for this information, the accuracy of the provided burden estimates, and any suggested methods for minimizing respondent burden, including through the use of automated collection techniques to the Director, Collection Strategies Division, U.S. Environmental Protection Agency (2822T), 1200 Pennsylvania Ave., NW, Washington, D.C. 20460. Include the OMB control number in any correspondence. Do not send the completed
surv ey to this address. OMB Control No. 2040

- XXXX Approval expires XX/XX/XX90 

# HUMAN ACTIVITIES, AQ UATIC HABITAT AND FISH

This survey asks for your opinions regarding policies that would affect fish and habitat in the U.S

. Your answers will help the government decide which policies will be enacted. Backgroun d information in this survey was provided by the National Marine Fisheries Service, U.S. Environmental Protection Agency, U.S. Geological Survey and other state and federal offices

. Northeast fresh and salt waters support billions of fish. These include f ish that are used by humans, as well as forage fish that are not used by humans, but serve as food for larger fish, birds, and animals.

This survey concerns proposed policies that would reduce fish losses caused by cooling water use by industrial facilities, including factories and power plants. These policies would benefit aquatic ecosystems but would increase the costs of some goods and services you buy, including electricity and common household products. Natural factors such as weather have always influenced fish, but in recent years human activities have had an increasing effect.
Activities that affect fish include fishing, pollution, commercial and residential developm ent, and the extraction of cooling water at industrial facilities.

Declines in fish can affect the condition of ecological systems, food webs, and related human uses such as fishing. Food Web

1



## 1 Birds/Mammals Fish Micro

organisms91 

# HOW DOES COOLING WAT ER AFFECT FISH?

The water that industrial facilities use to cool equipment is pumped from bays, rivers, and lakes. The largest amount is used by power plants that produce electricity.

The equipment that pumps the cooling water kills small fish and fish eggs.
Juvenile fish and eggs move throug h screens and into the cooling system where they are killed by high temperature. Large fish may be injured or killed against screens or filters.
Pumping warm water back into the environment (called thermal discharge ) also affects ecological systems. Cooling Water Intake Screen



## 2 Cooling water use affects fresh and salt waters throughout the US, but almost all fish losses are in salt waters such as coastal bays. How Fish Are Affected by Water Intake92 

# WHAT KINDS OF FISH A RE AFFECTED?

Cooling water use is not the larges t cause of fish loss in most areas (fishing causes greater losses), but has affected some fish populations.

About 1/3 of the fish lost are species caught by commercial and recreational fishermen. Examples include striped bass
, flounder , and cod

.

The ot her 2/3 of the fish lost are forage species not caught by humans but are part of the food web. Examples include killifish
, silverside , and stickleback

. Question 1. When thinking about how industrial facilities use cooling water, please rate the importance of the following to you. Check one box for each.

Not Important Somewhat Important Very Important



### 1. Preventing the loss of fish that are caught by humans 1 2 3 4 5



### 2. Preventing the loss of fish that are not caught by humans 1 2 3 4 5



### 3. Maintaining the ecological health of rivers, lakes and b 1 2 3 4 5



### 4. Keeping the cost of goods and services low 1 2 3 4 5



### 5. Making sure there is enough government regulation of id t 1 2 3 4 5



### 6. Making sure there is not too much gover nment regulation of industry 1 2 3 4 5



## 393 

# HOW MANY FISH ARE AF FECTED?

After accounting for the number of eggs and larvae that would be expected to survive to adulthood, scientists estimate that the equivalent of about 2.7 billion young adult fish (the equivalent of one year old) are lost each year in U.S. coastal and fresh waters due to cooling water use.
Scientists can predict the number of these fish that will be saved under different policies. This number ranges from 0.7 to 2.6 billion fish saved per year.
For commercial fish species, losses of young fish in cooling water intakes vary by species, from the equivalent of less than 0.1% to about 10% of total populations.
Yearly effects on fish species are between these levels. For example, t he number of young fish lost in cooling water intakes relative to the total number of fish in the water is relatively high for some species, but low for others.

Although scientists can predict the number of fish saved each year, the effect on fish populations is uncertain. This is because scientists do not know the total number of all fish in U.S. waters and because many factors

– such as cooling water use, fishing, pollution and water temperature

– affect fish populations.
The following page provides information on policies that would be required to reduce these fish losses. Largest Fish Losses per Year

Total Fish Population Losses 10% Smallest Fish Losses per Year

Losses < 0.1%

Total Fish Population

Smaller effect on Striped Bass Larger effect on Winter Flounder 

## 4 Smaller effect on Striped Bass L arger effect on Winter Flounder94 

# NEW REGULATIONS ARE BEING PROPOSED TO PROTECT FISH

Current Situation

2.7 Billion Fish Lost per Year (0% Saved)

With Advanced Filters

2.1 Billion Fish Lost per Year (22% Saved) 0.6 Billion Fish Saved per Year

With Closed Cycle Cooling

0.1 Billion Fish Lost per Year (95% Saved) 2.6 Billion Fish Saved per Year



### Advanced filters an d closed cycle cooling are already in use at many facilities and are proven technologies. New regulations would require a mix of advanced filters and closed cycle cooling at all facilities

— with reductions in fish losses between 25% and 95%.

The government is considering policies that would require new measures to protect fish.

One policy would require advanced filters that bloc k fish from entering cooling water facilities. Requiring advanced filters could reduce fish losses about 25%

.

Another possibility is closed cycle cooling that recycles and reuses cooling water, so that less water is needed. Requiring closed cycle cool ing could reduce fish losses by 95% and also reduces thermal discharge

. However, costs are higher than for advanced filters.



## 595 

# HOW IMPORT ANT ARE THESE ISSUES TO YOU?

While these policies would reduce fish losses, they would also increase the costs of producing many goods and services

— these costs would be passed on to consumers like you.

Question 2. Compared to other issues that the government might address

— such as public safety, education and health

— how important is protecting aquatic ecosystems to you? Check one box.

Not Important Somewhat Important Very Important

Protecting aquatic ecosystems is 1 2 3 4 5



### The government needs to know whether households are willing to pay the costs of these new policies.
This survey will ask you to compare policies with different effects on cooling water use, fish, and costs to your household. You will be asked to vote for the options you prefer.
You will also have the opportunity to support the current situation, with no new policies, and no new costs to your household.



## 696 

# THIS SURVEY IS SIMIL AR TO A PUBLIC VOTE

The next part of this survey will ask you to conside r different types of policies to protect fish, and indicate how you would vote. Effects of each possible policy will be described using the following scores:


## Effect of

Policy What It Means

Commercial Fish Populations (Fish Used by People) 

### A score bet ween 0 and 100 showing the overall health of commercial and recreational fish populations . Higher scores mean more fish and greater fishing potential. A score of 100 means that these fish populations are at a size that maximizes long

- term harvest; 0 means no harvest. The current score in U.S. waters is 43.

Fish Populations (All Fish) 

### A score between 0 and 100 showing the estimated size of all fish populations compared to natural levels without human influence. A score of 100 means that populations are the largest natural size possible; 0 means no fish. The current score in U.S. waters is 31.

Fish Saved

(per Year) 

### A score between 0 and 100 showing the reduction in young fish lost because of the new policy. A score of 100 means that no fish are lost i n cooling water intakes (all fish are saved ). The current score in U.S. waters is 0; this represents the status quo with no new policies.

Condition of Aquatic Ecosystems 

### A score between 0 to 100 showing the ecological condition of affected areas , comp ared to the most natural waters in the U.S.. The score is determined by many factors including water quality and temperature, the health of aquatic species, and habitat conditions. Higher scores mean the area is more natural

. The current score in U.S. wat ers is 48. 

# $ Cost per Year 

### How much the policy will cost your household, in unavoidable price increases for products and services you buy, including electricity and common household products.



## 797 

# HOW WOULD YOU RATE T HE IMPORTANCE OF THESE EFFECTS?

Questi on 3. When considering policies that affect how facilities use cooling water, how important to you are effects on each of the following scores? Check one box for each. (For reminders of what the scores mean, please see page 7).

Not Important Somewhat Important Very Important

1. Effect on commercial fish populations 1 2 3 4 5



### 2. Effect on the fish populations (for all fish) 1 2 3 4 5



### 3. Effect on fish s aved 1 2 3 4 5



### 4. Effect on the condition of aquatic ecosystems 1 2 3 4 5



### 5. Eff ect on cost to my household 1 2 3 4 5



### The next questions will ask you to choose between different policy options that would affect fish losses in cooling water systems. You will be given choices and asked to vote for the choice you prefer by che cking the appropriate box. Questions will look similar to the sample on the next page.



## 898 

# SAMPLE QUESTION Ques tions will look like the s ample below

.

Policy Effect Current Situation

(No policy) 

## Option A Option B

Commercial Fish Populations (in 3

- 5 Yea rs) 

# 53 %
(100% is populations that allow for maximum harvest) 

# 55 %
(100% is populations that allow for maximum harvest) 

# 57 %
(100% is populations that allow for maximum harvest)

Fish Populations (all fish) (in 3

- 5 Years) 

# 39 %
(100% is populations without human influence) 

# 42 %
(100% is populations without human influence) 

# 42 %
(100% is populations without human influence)

Fish Saved per Year (Out of 2.7 billion fish lost in water intakes) 

# 0 %
No change in status quo 

# 25 %

0.7 billion fish saved 

# 50 %

1.4 billi on fish saved

Condition of Aquatic Ecosystems (in 3

- 5 Years) 

# 46 %
(100% is pristine condition) 

# 46 %
(100% is pristine condition) 

# 48 %
(100% is pristine condition) 

# $

Increase in Cost of Living for Your Household 

# $0

No cost increase 

# $24

per year ($2 per month) 

# $48

per year ($3 per month)



### HOW WOULD

YOU VOTE? (CHOOSE ONE ONLY) I would vote for NO POLICY I would vote for OPTION A I would vote for OPTION B

If you prefer Option A, check this b ox If you do not want A or B, check this box If you prefer Option B, check this box 

# X X X

999 

# AS YOU VOTE PLEASE R EMEMBER

**•** The map below shows the facilities and area s that would be affected by the proposed policies.

**•** The policy options (A and B) given to you each require a different mix of advanced filters and closed cycle cooling in different areas, so effects on fish are different.

**•** You will be shown different quest ions, with different combinations of technology and different costs

**•** Depending on the policies chosen, costs to your household could range from $0 per month to a maximum of $6 per month.

**•** Depending on the type of technology required and other factors, effect s on fish and ecosystems may be different

— even if the annual reduction in fish losses is similar.

**•** Consider each pair of policy options separately

—

**•** Scientists expect that effects on the environment and economy not shown explicitly will be small. For example, studies of industry suggest that effects on employment will be close to zero. do not add them up or compare programs from different pages.

**•** Your votes are important. Answer all questions as if this were a real, binding vote.



## 10100 

## Question 4. Assume tha t Options A and B would require a different mix of filters and closed cycle cooling in different areas. Assume all types of fish are affected. How would you vote?

Policy Effect US Current Situation

(No policy) 

## Option A US Option B US

Commercial Fis h Populations (in 3

- 5 Years) 

# 53 %
(100% is populations that allow for maximum harvest) 

# 55 %
(100% is populations that allow for maximum harvest) 

# 57 %
(100% is populations that allow for maximum harvest)

Fish Populations (all fish) (in 3

- 5 Years) 

# 39 %

100% is populations without human influence) 

# 40 %
(100% is populations without human influence) 

# 43 %
(100% is populations without human influence)

Fish Saved per Year

(Out of 2.7 billion fish lost in water intakes) 

# 0 %
No change in status quo 

# 25 %

0.7 billion fish saved 

# 50 %

1.4 billion fish saved

Condition of Aquatic Ecosystems (in 3

- 5 Years) 

# 46 %
(100% is pristine condition) 

# 47 %
(100% is pristine condition) 

# 48 %
(100% is pristine condition) 

# $

Increase in Cost of Living for Your Household 

# $0

No cost incre ase 

# $24

per year ($2 per month) 

# $48

per year ($3 per month)



### HOW WOULD

YOU VOTE? (CHOOSE ONE ONLY) I would vote for NO POLICY I would vote for OPTION A I would vote for OPTION B



## 11101 

# POLICIES COULD REQUI RE DIFFERENT COMBINATIONS OF TECH NOLOGY

Now you will be asked to consider a new set of policy options for U.S. waters. As you vote, please remember

—

**•** Questions 5 and 6 present new sets of policy options. These options require a different mix of technologies in different areas.

**•** Each questio n is a separate vote. Questions 5 and 6 cannot

**•** be directly compared to each other, or to Question 4. Do not add up

**•** effects or costs across different questions. Policy costs and effects depend on many factors . Saving more fish does not



## 12 necessarily mean that all effects will improve.102 

## Question 5. Assume that Options A and B would require a different mix of filters and closed cycle cooling in different areas. Assume all types of fish are affected. How would you vote?

Policy Effect US Current Situation

( No policy) 

## Option A US Option B US

Commercial Fish Populations (in 3

- 5 Years) 

# 53 %
(100% is populations that allow for maximum harvest) 

# 55 %
(100% is populations that allow for maximum harvest) 

# 57 %
(100% is populations that allow for maximum harvest)

Fish Populations (all fish) (in 3

- 5 Years) 

# 39 %
(100% is populations without human influence) 

# 41 %
(100% is populations without human influence) 

# 43 %
(100% is populations without human influence)

Fish Saved per Year (Out of 2.7 billion fish lost in water intakes) 

# 0 %
No change in status quo 

# 25 %

0.7 billion fish saved 

# 75 %

2.0 billion fish saved

Condition of Aquatic Ecosystems (in 3

- 5 Years) 

# 46 %
(100% is pristine condition) 

# 46 %
(100% is pristine condition) 

# 50 %
(100% is pristine condition) 

# $

Increase in Cost of Living for Your Household 

# $0

No cost increase 

# $36

per year ($3 per month) 

# $60

per year ($5 per month)



### HOW WOULD

YOU VOTE? (CHOOSE ONE ONLY) I would vote for NO POLICY I would vote for OPTION A I would vote for OPTION B



## 13103 

## Questio n 6. Assume that Options A and B would require a different mix of filters and closed cycle cooling in different areas. Assume all types of fish are affected. How would you vote?

Policy Effect US Current Situation

(No policy) 

## Option A US Option B US

Commercial Fish Populations (in 3

- 5 Years) 

# 53 %
(100% is populations that allow for maximum harvest) 

# 60 %
(100% is populations that allow for maximum harvest) 

# 57 %
(100% is populations that allow for maximum harvest)

Fish Populations (all fish) (in 3

- 5 Years) 

# 39 %
(100% is populations without human influence) 

# 47 %
(100% is populations without human influence) 

# 44 %
(100% is populations without human influence)

Fish Saved per Year (Out of 2.7 billion fish lost in water intakes) 

# 0 %
No change in status quo 

# 95 %

2.6 billion fish saved 

# 50 %

1.4 billion fish saved

Condition of Aquatic Ecosystems (in 3

- 5 Years) 

# 46 %
(100% is pristine condition) 

# 50 %
(100% is pristine condition) 

# 50 %
(100% is pristine condition) 

# $

Increase in Cost of Living for Your Household 

# $0

No cost increase 

# $96

per year ($6 per month) 

# $48

per year ($2 per month)



### HOW WOULD

YOU VOTE? (CHOOSE ONE ONLY) I would vote for NO POLICY I would vote for OPTION A I would vote for OPTION B



## 14104 

### Question 7. If you always voted for NO POLICY in questions 4

- 6 , what was the primary reason? Check one. (Skip this question if you voted for Option A or B in any question above.) ____ The cost to my household was too high ____ Preventing fish losses is not important to me ____ I do not trust t he government to fix the problem ____ I would rather spend my money on other things ____ I did not believe the choices were realistic ____ Since the problem was created by private facilities, they should fix it without passing costs on to consumers

Questi on 8. Indicate how strongly you agree with the following statements about questions 4

- 6 and the information provided. Check one box for each.

Strongly Disagree Disagree Neutral Agree Strongly Agree



### The survey provided enough information for me to ma ke informed choices 1 2 3 4 5


### I feel confident about my answers 1 2 3 4 5 

### Information in the survey was easy for me to understand 1 2 3 4 5 

### Information in the survey was fair and unbiased 1 2 3 4 5 

### Questions were easy for me to an swer 1 2 3 4 5 

### I would vote the same way in an actual public vote 1 2 3 4 5 

### The effect of the proposed policies depends on many factors 1 2 3 4 5 

### Future ecological conditions are never 100% guaranteed 1 2 3 4 5



## 15105 

### Question 9. How much did the following factors affect your answers to questions 4

– 6 ? Check one box for each row

.

Effect on my answers to questions 4

- 6 

### Very Small Effect Moderate Effect Very Large Effect

. 

### Wanting to reduce taxes or costs to my househo ld. 1 2 3 4 5 

### Wanting to prevent the loss of industrial jobs. 1 2 3 4 5 

### Wanting to preserve fish for commercial fishing. 1 2 3 4 5 

### Wanting to send a message that all environmental issues are important regardless of cost. 1 2 3 4 5



### W anting to preserve fish for recreation (fishing, etc.). 1 2 3 4 5 

### Wanting to preserve fish to benefit aquatic ecosystems. 1 2 3 4 5 

### Wanting to know that fish exist in local lakes, rivers and bays. 1 2 3 4 5 

### Wanting to pay my fair share fo r government programs. 1 2 3 4 5 

### Wanting to sustain the competitiveness of US business 1 2 3 4 5 

### Wanting to preserve fish as a source of food for people. 1 2 3 4 5 

### Wanting to preserve fish and ecosystems for future generations. 1 2 3 4 5



## 16106 

### Question 10. How many days did you participate in the following during the last year? For trips longer than one day, please count each day separately. Check one box for each row

.

Number of days you did the activity during the past year

0 1
- 5 6
- 10 11
- 15 16+
Boating / Canoeing / Kayaking 1 2 3 4 5 Swimming / Going to the Beach 1 2 3 4 5 Recreational Fishing (Fresh Water) 1 2 3 4 5 Recreational Fishing (Salt Water) 1 2 3 4 5 Shellfishing / Crabbing 1 2 3 4 5 Scuba Diving / Snorkeling 1 2 3 4 5

18


## 17107 

## The following questions ensure that all groups are fairly represented. **All answers are anonymous and confidential.**

11. What is your age?

___ years

12. What is your gender?  Male  Female

13. What is the hig hest level of education that you have completed?  Less than high school  One or more years of college  High school or equivalent  Bachelor’s Degree  High school + technical school  Graduate Degree

14. How many people

15. How many of these people are 16 years of age or older? ____ live in your household ?

______________

16. How many of these people are 6 years of age or younger? ____

17. What is your zip code?

_____________________________
18. What town and state do you live in? Town:

_____________ State:____

19. Are you currently employed?

___ Yes

_____ No

20. What category come s closest to your total household Less than $10,000 

### income? $60,000 to $79,999 $10,000 to $19,999 $80,000 to $99,999 $20,000 to $39,999 $100,000 to $249,999 $40,000 to $59,999 $250,000 or more



### 21. If you have any comments on this survey, please write them below:

**Thank you for your participation in this important survey!**



## 18108 Attachment 3 : Federal Register Notice

ENVIRONMENTAL PROTECTION AGENCY
[EPA

- HQ

- OW

- 2010

- 0595; FRL

- ]
Agency Information Collection Activities; Submission to OMB f or Review and Approval; Willingness to Pay Survey for § 316(b) Existing Facilities Cooling Water Intake Structures (New) , EPA ICR N o. 2402.01, OMB Control No. 2040

- NEW

AGENCY: Environmental Protection Agenc y (EPA)

.
ACTION: Notice.

SUMMARY: In complianc e with the Paperwork Reduction Act (PRA) (44 U.S.C. 3501 et seq .),

this document announces that an Information Collection Request (ICR) has been forwarded to
the Office of Management and Budget (OMB) for review and approval

. This is a request for a

new co llection. The ICR, which is abstracted below, describes the nature of the information

collection and its estimated burden and cost.

DATES: Additional comments may be submitted on or before [ insert date 30 days after
publication in the Federal Register

ADDRESSES: Submit your comments, identified by Docket ID No

. EPA

- HQ

- OW

- 2010

- 0595

to: ].

(1) EPA by one of the following methods:

**•** www.regulations.gov : Follow the on

- line instructions for submitting comments.

**•** Email: OW

- Docket@epa.gov, Attention Docket ID No. EPA

- HQ

- OW

- 2010

- 0595

**•** Mail: Water Docket, Environmental Protection Agency, Mailcode: 28221T , 1200 Pennsylvania

Ave. , NW., Washington, DC 20460, Attention Docket ID No. EPA

- HQ

- OW

- 20 10

- 0595. Please

include a total of 3 copies.

**•** Hand Delivery: Water Docket, EPA Docket Center, EPA West, Room 3334, 1301109 Constitution Ave., NW., Washington, DC, Attention Docket ID No. EPA

- HQ

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- 20 10

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0595. Such deliveries are only accepted during the Docket’s normal hours of operation
and special arrangements should be made.

(2) OMB by mail to: Office of Information and Regulatory Affairs, Office of Management and
Budget (OMB), Attention: Desk Officer for EPA, 725 17 th Street, NW, Washington, DC 20503.

FOR FURTHER INFORMATION CONTACT: Erik Helm, Office of Water, Office of

Scienc e and Technology, Engineering and Analysis Division, Economic and Environmental

Assessment Branch , 4303T, Environmental Protection Agency, 1200 Pennsylvania Ave., NW,
Washington, DC 20460; telephone number: 202

- 566

- 1049; fax number: 202

- 566

- 1053; email

add ress: Helm. E rik@epa.gov.

SUPPLEMENTARY INFORMATION: EPA has submitted the following ICR to OMB for
review and approval according to the procedures prescribed in 5 CFR 1320.12. On July 21, 2010
( 74 FR 42438 ), EPA sought comments on this ICR pursuant to 5 C FR 1320.8(d). EPA received

five comments during the comment period, which are addressed in the ICR

. Any additional
comments on this ICR should be submitted to EPA and OMB within 30 days of this notice.
EPA has established a public docket for this ICR un der Docket ID No. EPA

- HQ

- OW

2010

- 0595 which is available for online viewing at www.regulations.gov , or in person viewing at

the Water Docket in the EPA Docket Center (EPA/DC), EPA West, Room 3334, 1301
Constitution Ave., NW, Washington, DC. The EPA/DC Pub lic Reading Room is open from
8:30 a.m. to 4:30 p.m., Monday through Friday, excluding legal holidays. The telephone number
for the Reading Room is 202

- 566

- 1744, and the telephone number for the Water Docket is 202

-
566

- 1752.110 Use EPA’s electronic docket an d comment system at www.regulations.gov , to submit or
view public comments, access the index listing of the contents of the docket, and to access those
documents in the docket that are available electronically. Once in the system, select “docket
search,” then key in the docket ID number identified above. Please note that EPA’s policy is
that public comments, whether submitted electronically or in paper, will be made available for
public viewing at www.regulations.gov as EPA receives them and without chan ge, unless the
comment contains copyrighted material, CBI, or other information whose public disclosure is
restricted by statute. For further information about the electronic docket, go to
www.regulations.gov

.
Title: Willingness to Pay Survey for Sectio n 316(b) Existing Facilities Cooling Water Intake

Structures: Instrument, Pre

- test, and Implementation

ICR numbers: EPA ICR No. 2402.01 , OMB Control No. 2040

- NEW

.
ICR status: This ICR is for a new information collection activity. An Agency may not con duct
or sponsor, and a person is not required to respond to, a collection of information, unless it
displays a currently valid OMB control number. The OMB control numbers for EPA's
regulations in title 40 of the CFR, after appearing in the Federal Registe r w hen approved, are

listed in 40 CFR part 9, are displayed either by publication in the Federal Register

Abstract: Section 316(b) of the Clean Water Act (CWA) requires EPA to ensure that the
location, design, construction, and capacity of cooling water intake structures (CWIS) reflect the
best technology availa ble (BTA) to protect aquatic organisms from being killed or injured by
impingement or entrainment. At que stion here is the regulation of the existing steam electric and
manufacturing facilities

. or by other
appropriate means, such as on the related collection instrument or form, if applicable. The
display of OMB control numbers in certain EPA regulations is consolidated in 40 CFR part 9.111 Under Executive Order 12866, EPA is required to estimate th e potential benefits and
costs to society of proposed rule options of significant rules . To assess th e importance of the
ecological gains from the section 316(b) re gulation , EPA requests approval from the OMB to
conduct a stated preference survey . Data f rom the associated stated preference survey will be
used to estimate values (willingness to pay, or WTP) derived by households for changes related
to the reduction of fish losses at CWIS, and to provide information to assist in the interpretation

and valid ation of survey responses. EPA has designed the survey to provide data to support the
following specific objectives: [a] the estimation of the total values that individuals place on
preventing losses of fish and other aquatic organisms caused by 316(b) fa cilities; [b] to
understand how much individuals value preventing fish losses, increasing fish populations, and
increasing commercial and recreational catch rates; [c] to understand how such values depend on
the current baseline level of fish populations a nd fish losses, the scope of the change in those
measures, and the certainty level of the predictions; and [d] to understand how such values vary
with respect to individuals’ economic and demographic characteristics.
The key elicitatio n questions ask resp ondents whether or not they would vote for policies
that would increase their cost of living, in exchange for specified multi

- attribute changes in [a]
impingement and entrainment losses of fish, [b] commercial fish populations , [c] long

- term
populations of all fish , and [d] condition of aquatic ecosystems. The respondents’ stated
preferences with respect to levels of environmental goods and cost to households , when used in
conjunction with other information collected in the survey on the use of the affecte d aquatic
resources, household income, and other demographics, can be analyzed statistically (using a
mixed logit framework) to estimate total WTP for the quantified environmental benefits of the
316(b) rulemaking. Data analysis and interpretation is groun ded in a standard random utility

model.112 The welfare values that can be derived from this stated pref erence survey along with
those that are estimated apart from the survey effort will offer insight into the composition of the
value people place on the 316( b) environmental impacts. WTP estimates deri ved from the
survey may overlap

- to a potentially substantial extent

- with estimates that can be provided
through some other methods

. T herefore, particular care will be given to avoid any possible

double count ing of values that might be derived from alternative valuation methods.

Burden Statement: The annual public reporting and recordkeeping burden for this collection of
information is estimated to average 5 minutes per telephone screening participant and 30 m inutes
per mail survey respondent including the time necessary to complete and mail back the
questionnaire. Burden means the total time, effort, or financial resources expended by persons to
generate, maintain, retain, or disclose or provide information to or for a Federal agency. This
includes the time needed to review instructions; develop, acquire, install, and utilize technology
and systems for the purposes of collecting, validating, and verifying information, processing and
maintaining information, an d disclosing and providing information; adjust the existing ways to
comply with any previously applicable instructions and requirements which have subsequently
changed; train personnel to be able to respond to a collection of information; search data sourc es; complete and review the collection of information; and transmit or otherwise disclose the

information.
The ICR provides a detailed explanation of the Agency’s estimate, which is only briefly

summarized here:
Respondents: Individuals from US house holds
Estimated total number of potential respondents: 9 , 5 33 for telephone screening and 2, 288
for mailed questionnaires.
Frequency of response: one

- time response.113 Estimated total average number of responses for each respondent: one

- time response.

Est imated total burden hours: 1, 938 hours.
Estimated total costs: $ 39
, 583 . EPA estimates that there will be no capital and operating
and maintenance cost burden to respondents.

Dated: ________________

__________________________________ John Moses, Di rector, Collection Strategies Division.114 Attachment 4 : Description of Statistical Survey Design

The following represents an anticipated experimental design for survey implementation, along with the associated number of completed surveys that will be req uired. Part B of this supporting statement provides detail on the sampling design. The proposed design and sampling plan is based on standard design and sampling theory for choice experiments and population surveys, as outlined by Louviere et al. (2000), K uhfeld (2009) and Dillman (2000). EPA notes that the anticipated experimental design described here is preliminary and it may be subject to refinements during design evaluations to account for issues such as dominate or dominated pairs, ecological feasibi lity, and to remove attribute combinations which do not provide information for
estimation. The purpose of the 316(b) survey is to calculate average per household parameters (e.g., willingness to pay and choice probabilities) within a given survey populati on. No sub

- population estimates are required. The anticipated experimental design for the choice experiment includes
two multi

- attribute choice options or alternatives , A and B, together with a fixed status quo or “no policy” option. Options A and B are c haracterized by levels for the following six attributes:

1. Location in A and B (x 1A ; x 1B )

– 2 possible levels 2. Fish Saved per Year in A and B (x 2A ; x 2B )

– 3 possible levels 3. Commercial Fish Populations in A and B (x 3A ; x 3B )

– 3 possible levels 4. Fish Population s (all fish) in A and B (x 4A ; x 4B )

– 3 possible levels 5. Aquatic Ecosystem Condition in A and B (x 5A ; x 5B )

– 3 possible levels 6. Cost in A and B (x 6A ; x 6B )

- 6 possible levels

This implies an experimental design characterized by [2 × 3 4 × 6] for each alternative , or [2 2 × 3 8 × 6 2 ] for alternatives A and B combined. To construct a preliminary main effects design that is sufficiently flexible to estimate alternative specific main effects and response patterns (i.e., a non

- generic design), we begin with
the smallest ava ilable 100% efficient linear main effects plan for a full 2 2 3 8 6 2 design. This treats each attribute of each alternative as a separate design element. The result is a design with 72 profiles, with attributes labeled following the above notation, and leve ls indicated by integers 1...N, where N for each attribute is the number of levels identified above:115 Table 1: Set of 72 Design Profiles Obs x1A x2A x3A x4A x5A x6A x1B x2B x3B x4B x5B x6B 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 2 2 2 2 2 2 2 2 3 1 1 1 3 1 6 2 2 3 3 1 3 4 1 1 1 3 3 5 2 1 1 2 3 2 5 1 1 2 2 1 3 1 1 3 2 2 3 6 1 1 2 2 2 1 2 3 1 1 2 4 7 1 1 2 2 3 4 1 2 2 2 1 1 8 1 1 2 2 3 6 1 3 2 3 3 6 9 1 1 3 1 1 2 1 3 2 3 2 5 10 1 1 3 1 2 3 2 1 3 1 3 6 11 1 1 3 3 2 4 1 2 1 3 3 4 12 1 1 3 3 3 5 2 3 3 1 1 5 13 1 2 1 1 2 4 2 3 3 2 1 6 14 1 2 1 2 2 5 1 3 3 3 2 1 15 1 2 1 2 3 2 1 3 1 1 3 3 16 1 2 1 3 1 3 2 3 2 2 3 4 17 1 2 2 1 1 5 2 1 2 3 1 4 18 1 2 2 1 3 1 2 2 3 2 3 5 19 1 2 2 3 1 2 1 2 1 1 1 6 20 1 2 2 3 2 6 1 1 1 2 2 5 21 1 2 3 1 3 4 1 1 1 3 2 3 22 1 2 3 2 1 1 1 2 3 3 3 2 23 1 2 3 2 2 6 1 1 2 1 1 2 24 1 2 3 3 3 3 1 2 2 1 2 1 25 1 3 1 1 3 6 2 2 3 1 2 4 26 1 3 1 2 1 4 2 1 2 1 3 5 27 1 3 1 2 2 3 1 2 1 3 1 5 28 1 3 1 3 3 1 1 1 2 3 2 6 29 1 3 2 1 2 5 2 2 2 1 3 3 30 1 3 2 1 3 3 2 3 1 3 1 2 3 1 1 3 2 3 1 4 2 3 3 1 2 2 32 1 3 2 3 2 2 2 1 3 3 3 1 33 1 3 3 1 1 6 1 3 1 2 3 1 34 1 3 3 2 1 5 2 2 1 2 2 6 35 1 3 3 2 3 2 1 1 3 2 1 4 36 1 3 3 3 2 1 2 3 2 2 1 3 37 2 1 1 1 1 1 2 1 1 1 1 1 38 2 1 1 1 2 2 1 2 2 2 2 2 39 2 1 1 3 1 6 1 2 3 3 1 3 40 2 1 1 3 3 5 1 1 1 2 3 2 41 2 1 2 2 1 3 2 1 3 2 2 3 42 2 1 2 2 2 1 1 3 1 1 2 4 43 2 1 2 2 3 4 2 2 2 2 1 1 44 2 1 2 2 3 6 2 3 2 3 3 6 45 2 1 3 1 1 2 2 3 2 3 2 5 46 2 1 3 1 2 3 1 1 3 1 3 6116 47 2 1 3 3 2 4 2 2 1 3 3 4 48 2 1 3 3 3 5 1 3 3 1 1 5 49 2 2 1 1 2 4 1 3 3 2 1 6 50 2 2 1 2 2 5 2 3 3 3 2 1 51 2 2 1 2 3 2 2 3 1 1 3 3 52 2 2 1 3 1 3 1 3 2 2 3 4 53 2 2 2 1 1 5 1 1 2 3 1 4 54 2 2 2 1 3 1 1 2 3 2 3 5 55 2 2 2 3 1 2 2 2 1 1 1 6 56 2 2 2 3 2 6 2 1 1 2 2 5 57 2 2 3 1 3 4 2 1 1 3 2 3 58 2 2 3 2 1 1 2 2 3 3 3 2 59 2 2 3 2 2 6 2 1 2 1 1 2 60 2 2 3 3 3 3 2 2 2 1 2 1 61 2 3 1 1 3 6 1 2 3 1 2 4 62 2 3 1 2 1 4 1 1 2 1 3 5 63 2 3 1 2 2 3 2 2 1 3 1 5 64 2 3 1 3 3 1 2 1 2 3 2 6 65 2 3 2 1 2 5 1 2 2 1 3 3 66 2 3 2 1 3 3 1 3 1 3 1 2 67 2 3 2 3 1 4 1 3 3 1 2 2 68 2 3 2 3 2 2 1 1 3 3 3 1 69 2 3 3 1 1 6 2 3 1 2 3 1 70 2 3 3 2 1 5 1 2 1 2 2 6 71 2 3 3 2 3 2 2 1 3 2 1 4 72 2 3 3 3 2 1 1 3 2 2 1 3

Following common examples in the environmental economics literature, we anticipate three choice question s per survey. This will allow the 72 profiles to be included (orthogonally blocked) in 24 unique survey booklets. Monte Carlo experiments indicate that approximately 6 completed responses are required for each profile in order to achieve large sample stat istical properties for choice experiments (Louviere et al. 2000, p. 104, citing Bunch and Batsell 1989). Following this guidance, the above design will require 24×6 = 144 completed surveys, or 6 completed surveys for each unique survey booklet. This will provide a total of 432 profile

responses.

Sample Sizes for Maximum Acceptable Sampling Error The goal of the choice experiment is to estimate regression coefficients from mixed or conditional logit models that may be used to estimate willingness to pay f or multi

- attribute policy alternatives, or the likelihood of choosing a given multi

- attribute alternative, following standard random utility modeling procedures (Haab and McConnell 2002). Required sample117 sizes to estimate population parameters with given d egrees of freedom are drawn from standard statistical theory, as described by Dillman (2000). The maximum acceptable sampling error for predicting response probabilities (the likelihood of choosing a given alternative) in the present case is ±10%, assuming a true response probability of 50% associated with a utility indifference point. Given the survey population size, this level of precision requires a minimum sample size of approximately 96 observations. The number of observations (completed surveys) req uired to obtain large sample properties for the choice experiment design provide more than sufficient observations to obtain this required precision for population parameters. The choice experiment design requires 432 completed profile responses from 144 surveys. Statistical theory shows that 400 assumed

- independent profile responses will allow a 50% choice probability to be estimated within ±4.9 percent, at a 95% confidence level. With only a single choice question per survey (144 responses), the same

pro bability and confidence level can be obtained within approximately ±8.2 percent; this is also within acceptable limits.

Experimental Design Allowing Two

- Way Interactions with Location (x 1A ; x 1B ) In order to estimate a parallel design that allows for inte ractions with policy location, and insulates main effects from these interactions, we follow the suggested design strategies of Louviere et al. (2000). First, we estimate the smallest available 100% efficient linear main effects plan for non

- location fact ors (X 2 – X 6 ) across both alternatives A and B, [3 8 × 6 2 ]. This results in a main effects design with 36 profiles:

Table 2: Set of 36 Design Profiles Obs x2A x3A x4A x5A x6A x2B x3B x4B x5B x6B 1 1 1 1 1 1 1 1 1 1 1 2 1 1 2 2 2 2 2 2 1 2 3 1 1 2 3 4 3 2 1 1 6 4 1 1 3 2 6 3 1 2 2 4 5 1 2 1 1 4 2 1 3 2 5 6 1 2 2 2 3 1 3 1 3 5 7 1 2 2 3 5 3 3 2 3 1 8 1 2 3 3 2 1 1 3 1 3 9 1 3 1 2 6 3 3 1 2 3 10 1 3 1 3 3 2 2 3 3 4 11 1 3 3 1 1 2 3 2 3 6 12 1 3 3 1 5 1 2 3 2 2 13 2 1 1 1 5 2 3 1 1 4118 14 2 1 2 2 5 2 1 3 3 3 15 2 1 3 2 1 3 2 3 3 5 16 2 1 3 3 3 1 3 1 2 2 17 2 2 1 1 3 3 2 2 1 3 18 2 2 2 3 1 1 1 2 2 4 19 2 2 3 2 4 2 2 1 2 1 20 2 2 3 3 6 2 3 3 1 6 21 2 3 1 2 2 1 1 1 3 6 22 2 3 1 3 4 3 1 2 3 2 23 2 3 2 1 2 3 3 3 2 1 24 2 3 2 1 6 1 2 2 1 5 25 3 1 1 3 2 2 3 2 2 5 26 3 1 1 3 6 1 2 3 3 1 27 3 1 2 1 3 3 1 3 2 6 28 3 1 3 1 4 1 3 2 3 3 29 3 2 1 2 1 3 3 3 1 2 30 3 2 1 2 5 1 2 2 2 6 31 3 2 2 1 6 2 1 1 3 2 32 3 2 3 1 2 3 2 1 3 4 33 3 3 2 2 4 1 3 3 1 4 34 3 3 2 3 1 2 2 1 2 3 35 3 3 3 2 3 2 1 2 1 1 36 3 3 3 3 5 3 1 1 1 5

This design is then repeated for each of the four possible combinations of values for x 1A and x 1B (i.e., 1,1; 2,2; 1,2; 2,1) creating a candidate design of 36×4 = 144 profiles. The resulting design fully insulates all main effe cts (eliminates aliasing) from interactions with location
attributes x 1A and x 1B , and allows associated location interactions to be estimated independent of
main effects. The number of required survey versions (48) is calculated by dividing the 144 profil es by the three choice questions per survey. The total number of completed surveys required (288) is based on a requirement of six completed surveys per survey version (48) to estimate the main effects and interactions

. As above, the number of observatio ns (completed surveys) required to obtain large sample properties for the choice experiment design provide sufficient observations to obtain required precision for population parameters. 1 Also as above, this candidate design may be subject to refinements based on design evaluations, as described by Louviere et al. (2000) and Kuhfeld (2009), but this is unlikely to alter design dimensions.

1 Alternatively, the smallest possible main effects plan for all attributes (72 profiles) may be folded over to make another 72 profiles, f or a combined set of 144 profiles. This protects main effects from all unobserved 2

- way interactions, but does not guarantee that specific interactions may be estimated. The required sample size is the same as that which would guarantee that location int eractions can be estimated.119 Attachment 5: Description of Internet

- based Sampling Alternative

EPA is also considering the use of an internet

- base d (i.e., web

- based) sampling approach as an alternative to the mail survey described in Part B of the supporting statement. The survey content, pre

- testing, review process, and data analysis would be identical to the mail survey
described in Parts A and B of the supporting statement. To support implementation of the web

based alternative, EPA would retain a vendor that maintains a preexisting representative national panel. This attachment provides a brief summary of the web

- based alternative, focusing on differences from the mail survey approach described in Part B of the supporting statement.

Sampling Frame The sampling frame for the web

- based survey is the panel of individuals previously recruited by a vendor to participate in online surveys. The over all sampling frame would be the set of all individuals in continental U.S. households who are 18 years of age or older and who have listed phone numbers. Individuals in the panel most likely be recruited using a list

- assisted random digit dialing telephon e methodology, thus providing a probability

- based starting sample of U.S. telephone households. Panels of this type are usually routinely supplemented to account for panel attrition. The preexisting panel would have to closely tracks the U.S. population on age, race, Hispanic ethnicity, geographical region, employment status, and other demographic elements. If differences between the panel and the U.S. population do exist, sample weights using U.S. Census demographic benchmarks could be developed to redu ce error due to non

coverage of non

- telephone households and to reduce bias due to non

- response and other non

sampling errors.

Sample Size The intention is to obtain 2,288 completed web

- based surveys from the preexisting panel. The same geographically stratified design will be implemented following the same the same regions and sample sizes as described in Part B of the supporting statement under the mail survey approach. Within each region, the sample will be stratified by demographic variables inclu ding age, education, Hispanic ethnicity, race, gender, and household income. The actual number of panel members contacted for this survey will be determined by the vendor’s knowledge of within panel response rates. Most likely, the stratification design used in the web

- based survey will120 systematically oversamples groups that tend to have lower response and consistency rates so that the demographic characteristics of respondents who provide valid completed surveys will mirror the Census demographic benchma rks more closely. This potential oversampling correction technique will reduce error due to non

- coverage of non

- telephone households in the original panel member recruitment process, and will also reduce bias due to non

- response and other non

sampling err ors.

Survey Response The target response rate for the survey among panel members that are sampled is 80 percent. However, the actual response rate compared to the general population is lower, given that the telephone recruitment process for a preexisting panel has an expected response rate in the 30 to 40 percent range. This will produce a lower cumulative response rate. Panel members who are selected for the survey will be contacted to inform them that the survey is available
online and reminders will be sent to panel members who do not complete the survey within a short period of time. Although the cumulative response rate for this survey may be low compared to response rates typically achieved using other survey methods (e.g., phone and mail surveys ), the web

based format facilitates geographic and demographic stratification, which will substantially improve the quality of the survey.

Non

- response and Other Non

- Sampling Error Corrections Approaches to minimize non

- response bias in internet surveys a re established in the literature (Dillman 2000) and include initial RDD probability sampling, careful panel management, and effective survey sampling procedures. The representativeness of preexisting panel survey sample is generally comparable to those te lephone surveys sponsored by various Federal agencies. Nonetheless, EPA would conduct several additional activities to minimize the potential for non

- response bias if the survey were implemented through the use of a preexisting panel including: (1) use of a stratified survey sample to mitigate the effect of non

- response bias, (2) use of non

- response follow

- up interviews to increase the overall response rate, and (3) statistical correction for unobserved heterogeneity that might be present in the data from respondents interviewed for this study121 Non

- response Interviews
In order to minimize non

- response bias from individuals who chose not to respond during some stage of panel recruitment, EPA will conduct non

- response follow

- up interviews within the
initial s ample for all stages of panel attrition. Respondents will include individuals who were contacted but did not join the preexisting panel, who agreed to join the panel but did not connect
to the vendors web

- site, who connected but did not complete the first survey, who completed the first survey but did not complete any following surveys, and who completed following surveys but did not complete the 316(b) survey. The end result of this effort will be a direct
measurement of non

- response bias and EPA will us e the information to increase the effective cumulative response rate by using a weighted response rate formulation.

Statistical Correction for Unobserved Heterogeneity EPA is also considering the use of a statistical technique to correct for unobserved heterogeneity, based on work by Heckman (Heckman, 1979). This correction would be conducted as a complement to a non

- response study effort. The technique will provide the probabilities of participation for each subpopulation grouping (as defined by Censu s long form data, voting data, and other data sources) included in the initial sample frame. These probabilities of participation will demonstrate the extent of self

- selection bias in the actual survey sample. The selection correction technique will take fully into account each stage of the panel recruitment and sampling process: that is, all stages in between construction of the sample frame for panel recruitment and interviewing of the panel respondents. The technique could be used to produce both adj usted and unadjusted estimates of WTP. Because the technique yields regression estimates that explain survey outcomes using subpopulation data related to neighborhood characteristics, it can be used to identify the sources of differences between the adjus ted and unadjusted estimates. As described above, EPA will use statistical techniques to correct for unobserved heterogeneity in the survey sample and non

- response follow

- up interviews to increase the effective survey response rate. Combined, these techni ques will reduce error due to non

coverage of non

- telephone households in the original panel recruitment process, and also reduce
bias due to non

- response and other non

- sampling errors. For an example of a similar research effort that successfully used th is web

- based survey approach to evaluate WTP for changes in water quality, see Viscusi et al. ( 2008 ).122 Data Preparation Since the survey will be administered as an online survey, survey responses will be automatically entered into an electronic database a t the time they are submitted. After all responses are submitted, the database contents will be converted into a format suitable for use in
EPA’s statistical analysis.123 Attachment 6 : Telephone Screener Script

Fish and Aquatic Habitat Telephone Screener
Hello, this is _________________calling from the Abt Associates. We are conducting an important survey of U.S. residents for the Environmental Protection Agency, or EPA. This is not a sales call.

SL1 [ASK IF SAMPLE=LANDLINE]
Could you please tell me how many people, age 18 and older, live in this household?
IF NEEDED: This study will help us to better understand the value of environmental protection and public programs. Any answers you give are kept strictly confidential.

IF ASKED: This is a short survey which should take no more than five minutes.

0 None THANK AND SCREEN OUT 1 One __ Number of persons 16+ SKIP TO SL1c 98 Refused (VOL) THANK AND TERMINATE

– Soft Refusal 99 Refused (VOL) THANK AND TERMINATE

– Hard Refusal

SL1b [A SK IF SAMPLE=LANDLINE]
May I speak with that person?

1 R spn on line SKIP TO SL2 2 R spn called to phone SKIP TO SL1d 3 R spn unavailable SCHEDULE CALLBACK 8 Refused THANK AND TERMINATE

– Soft Refusal 9 Refused THANK AND TERMINATE

– Hard Refusal

SL 1c [ASK IF SAMPLE=LANDLINE]
In order to select just one person to interview, may I please speak to the person in your household, age 18 or older, who (has had the most recent/will have the next) birthday?

1 Rspn on line SKIP TO SL2 2 Rspn called to phon e 3 Rspn unavailable SCHEDULE CALLBACK 8 Refused THANK AND TERMINATE

– Soft Refusal 9 Refused THANK AND TERMINATE

– Hard Refusal

SL1d [ASK IF SAMPLE=LANDLINE]124 Hello, this is _________________calling from the Abt Associates. We are conducting an i mportant survey of U.S. residents for the Environmental Protection Agency, or EPA. Could we begin now?

IF ASKED: This is a short survey which should take no more than five minutes.

1 Yes 2 No time SCHEDULE CALLBACK 8 Refused THANK AND TERMINATE

– Soft Refusal 9 Refused THANK AND TERMINATE

– Hard Refusal

SL2 [ASK IF SAMPLE=LANDLINE]
Do you have a cell phone in addition to the line on which we’re speaking right now?

1 Yes, also have cell phone 2 No, this is only phone SKIP TO SA2 8 (VOL) D on’t know THANK AND END, screen out 9 Refused THANK AND END, soft refusal

SC1 [ASK IF SAMPLE = CELL]
Are you in a safe place to talk right now?
IF NEEDED: Are you Driving? [IF RESPONDENT ANSWERS YES, DRIVING, SCHEDULE CALLBACK AND TERMINATE

- CODE AS 2]

IF ASKED: This is a short survey which should take no more than five minutes.

1 Yes, safe place to talk 2 No, call me later SCHEDULE CALLBACK 3 No, CB on land

- line RECORD NUMBER, schedule call back 4 Cell phone for business only THANK & END

- BUSINESS# 8 Refused THANK AND TERMINATE

– Soft Refusal 9 Refused THANK AND TERMINATE

– Hard Refusal

SC2 [ASK IF SAMPLE=CELL]
Are you at least 18 years old?
IF NEEDED: This study will help us to better understand the value of environmental protection and public programs. Any answers you give are kept strictly confidential.

1 Yes 2 Yes, no time SCHEDULE CALLBACK 3 No SCREEN OUT125 8 Refused THANK AND TERMINATE

– Soft Refusal 9 Refused THANK AND TERMINATE

– Hard Refusal

SC3 [A SK IF SAMPLE=CELL]
Do any other people age 18 or older regularly ANSWER your cell phone, or just you?
INTERVIEWER: This question refers to the physical phone and not to their calling plan

1 Yes, others 2 No, just respondent SKIP TO SC4 9 Don’t know/Re fused SKIP TO SC4

SC3b [ASK IF SAMPLE=CELL]
How many other people age 18 or older regularly answer your cell phone?

__ [ENTER NUMBER 1

- 10] 99 Don’t know/Refused

SC4 [ASK IF SAMPLE=CELL]
Not counting any that are used strictly for business purposes, are there other cell phones that you use regularly, or is it just the one?

1 Yes, use other cell phones 2 No SKIP TO SC5 9 Don’t know/Refused SKIP TO SC5

SC4b [ASK IF SAMPLE=CELL]
How many other cell phones do you use regularly, excluding those u sed only for business purposes?

__ [ENTER NUMBER 1

- 10] 99 Don’t know/Refused

SC5 [ASK IF SAMPLE=CELL]
Not counting (this/these) cell phone(s), do you also have a regular land

- line phone at home?

1 Yes, has a regular phone at home 2 No, cell is only phone SKIP TO SA2 7 Don’t know (VOL) THANK AND TERMINATE

– Screen out 8 Refused (VOL) THANK AND TERMINATE

– Soft Refusal 9 Refused (VOL) THANK AND TERMINATE

– Hard Refusal126 SA1 [ASK BOTH SAMPLES]
Of all of the phone calls that you or your family re ceives, are...(Read List)

1 all or almost all calls received on cell phones, 2 some received on cell phones and some received on land lines, or 3 very few or none on cell phones. 8 (VOL) Don’t know 9 (VOL) Refused

SA2 [ASK BOTH SAMPLES]
Record gender f rom observation. (Ask only if Necessary)

1 Male 2 Female
Q1 [ASK BOTH SAMPLES]
First, compared to other issues that the government might address

– such as public safety, education and health

– how important is protecting aquatic ecosystem to you, on a scale of 1 to 5 where 1 is “not important” and 5 is “very important” ? (MATCHES QUESTION 2 IN THE MAIL SURVEY)

1 2 3 4 5 (VOL) Don’t Know (VOL) Refused
Q2 [ASK BOTH SAMPLES]
People have ideas about the extent to which the government sho uld be involved in protecting the environment. On a scale of 1 to 5 where 1 is “not at all involved” and 5 is “highly involved”, how involved do you think the government should be in environmental protection?

1 2 3 4 5 (VOL) Don’t Know ( VOL) Refused127 Q3 [ASK BOTH SAMPLES]
Could you please tell me if you participated in each of following activities during the last year? (DO NOT ROTATE)

1 Yes 2 No 8 (VOL) Don’t Know 9 (VOL) Refused
Boating, canoeing, or kayaking 1 2 8 9 Swimming/going to the beach 1 2 8 9 Fresh Water Recreational fishing 1 2 8 9 Salt Water Recreational fishing 1 2 8 9 Fresh Water Recreational fishing 1 2 8 9 Shell fishing or crabbing 1 2 8 9 Scuba diving or snorkeling 1 2 8 9
Now, I have just a few questions for classification purposes.

D1 [ASK BOTH SAMPLES]
What is your age?

________ Years D on’t Know Ref used

D2 [ASK BOTH SAMPLES]
What is the highest level of education that you have completed? Is it... (READ LIST)

1 Less than high school 2 High school or equivalent 3 High school and technical school 4 One or more years of college 5 Bachelor’s degree 6 Graduate degree

D3 [ASK BOTH SAMPLES]
Including everyone living in your household, which of the following categories best describes your total ho usehold income before taxes? Is it ... (READ LIST)

1 $10,000 or Less, 2 Between $10,001 and $20,000, 3 Between $20,001 to $35,000, 4 Between $35,001 to $50,000,128 5 Between $50,001 to $75,000, 6 Between $75,001 to $100,000, or 7 More than $100,000 8 (VOL) Do n’t know 9 (VOL) Refused

D4 [ ASK BOTH SAMPLES]
Are you of Hispanic or Latino origin?

1 Yes 2 No 8 (VOL) D on’t know 9 (VOL) Refused

D5 [ ASK BOTH SAMPLES]
Which of the following racial categories describes you? You may select more than one. Would it b e... (READ LIST

– MULTIPLE RECORD)

1 American Indian or Alaskan Native, 2 Asian, 3 Black or African American, 4 Native Hawaiian or Other Pacific Islander, or 5 White 6 (VOL) Hispanic / Latino 8 (VOL) Other 9 (VOL) Refused

D6 [ ASK BOTH SAMPLES]
Do you... (RE AD LIST)

1 Rent your home or apartment 2 Own your own home 3 Live with family or friends and pay part of the rent or mortgage 4 Live with family or friends and do not pay rent 7 (VOL) Other, Specify 8 (VOL) Other 9 (VOL) Refused

RECRUITMENT :

In addition to thi s telephone survey, we are also conducting a mail survey to help U.S. policymakers to better understand your The survey t akes most people about 30 minutes to complete. priorities for the environment and the use of public funds. This survey will be mailed to households along with a free reply envelope129 I1 [ ASK BOTH SAMPLES]
Would you be willing to participate in this mail survey?

1 Yes 2 No THANK FOR PARTICIPATION AND TERMINATE 3 Don’t know THANK FOR PARTICIPATION AND TERMINATE 4 Refused THANK FOR PA RTICIPATION AND TERMINATE

I2 [ ASK BOTH SAMPLES]
To what name and address should we mail the survey? (RECORD NAME, ADDRESS, CITY, STATE, AND ZIP CODE AND REPEAT BACK)

I3 [ ASK BOTH SAMPLES]
And is this the best number to reach you at if we should have a problem mailing your survey?

1 Yes SKIP TO CLOSING 2 No

I4 [ ASK BOTH SAMPLES]
What is the best number to reach you? (RECORD NUMBER AND REPEAT BACK)

CLOSING:
Thank you. The survey will be sent to you in approximately one to two weeks. The pac ket will include information about the study, how to return your survey, and additional contact information in case you have questions. Thank you very much for your time, and have a great evening/day.130 Attachment 7: Cover Letter to Mail Survey Recipients

<date>
<given name> <surname> <address> <city>, <state> <zip code>

- <zip+4>

Dear <title> <surname>:
A few days ago you agreed to take a short survey regarding environmental protection and government regulations in the Northeast U.S. Thank you fo r agreeing to participate

— the survey booklet is enclosed with this letter. Your answers to the survey will help officials from the Environmental Protection Agency (EPA) to better understand the value of policies which would affect the future of fish and a quatic habitat in the Northeast. By filling out this survey, you will be participating in an important study that will help government officials understand your priorities for the environment and regulations.
Your responses to this survey are very import ant. Over time, human activities have caused many changes in Northeast’s rivers, streams and bays. The Environmental Protection Agency is considering policies that could impact the quality of fish and aquatic habitat in these areas. These policies can h ave different effects and costs. Because of this, it is important to know what types of policies are supported by Northeast residents.
All answers to the survey are confidential. Once we have received your survey, we will delete your name from all lists, so that your responses can never be traced back to you. Of course, your participation is voluntary and you may refuse to answer any or all questions.
We hope that you find this survey important and interesting, and thank you for your assistance in th is important project. We would greatly appreciate if you could return the survey in the near future.

Sincerely,

Mary T. Smith, Director U. S. Environmental Protection Agency Engineering and Analysis Division131 Attachment 8 : Post Card Reminder to Mail S urvey Recipients

FRONT

BACK Abt SRBI Government Services Divison 8403 Colesville Road, Suite 820 Silver Spring, MD, 20910

Last week a survey was mailed to you concerning environmental protection and government regulations in the Northeast U.S. If you have already returned your completed survey, please accept our sincere thanks. If you have not yet completed your survey, we ask that you plea se do so today. You are one of a select few who have been chosen to participate

— your answers will help us understand your priorities for the environment and regulations in the Northeast U.S. If you have misplaced your survey, please contact Ryan Stapler at (617) 520

- 3524 or ryan_stapler@abtassoc.com for a replacement.
Regards,
Mary T. Smith Environmental Protection Agency