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 SUPP ORTING 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, a nd Other Collection Criteria.......................................... 5 3(a) Non-duplication .......................................................................................................... ........ 5 3(b) Public Notice Required Prio r to ICR Submission to OMB ................................................ 7 3(c) Consultations............................................................................................................. ........ 12 3(d) Effects of Less Frequent Collection .................................................................................. 13 3(e) General Guidelines ....................................................................................................... ..... 14 3(f) Confidentiality .......................................................................................................... ........ 14 3(g) Sensitive Questions ...................................................................................................... ..... 14

4. The Respondents and the Information Requested ............................................................ 14 4(a) Respondents .............................................................................................................. ........ 14 4(b) Information Requested .................................................................................................... .. 16 (I) Data items, including re cordkeeping requirements .......................................................... 16 (II) Respondent activities .................................................................................................... .... 20

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 ...................................................................................................... .... 23ii 6. Estimating Respondent Burden and Cost of Collection ................................................... 24 6(a) Estimating Respondent Burden......................................................................................... 24 6(b) Estimating Respondent Costs ........................................................................................... 24 6(c) Estimating Agency Burden and Costs .............................................................................. 25 6(d) Respondent Universe and Total Burden Costs ................................................................. 25 6(e) Bottom Line Burden Hours and Costs .............................................................................. 26 6(f) Reasons for Change in Burden ......................................................................................... 26 6(g) Burden Statement ......................................................................................................... ..... 26

PART B OF THE SUPP ORTING 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 Design .............................................................................................................. ..... 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 ...................................................................................................... .. 33 2(d) Questionnaire Design ..................................................................................................... ... 36

3. Pretests and Pilot Tests ................................................................................................... .. 37

4. Collection Methods and Follow-up .................................................................................. 38 4(a) Collection Methods ....................................................................................................... .... 38iii 4(b) Survey Response and Follow-up ...................................................................................... 38

5. Analyzing and Reporting Survey Results ......................................................................... 39 5(a) Data Preparation ......................................................................................................... ....... 39 5(b) Analysis.................................................................................................................. ........... 40 5(c) Reporting Results ........................................................................................................ ...... 57

REFERENCES .................................................................................................................... ......... 58

ATTACHMENTS

Attachment 1: Full Text of Stat e Preference Survey Component ................................................. 68 Attachment 2: Federal Register Notice ......................................................................................... 93 Attachment 3: Description of Statistical Survey Design ............................................................ 103 Attachment 4: Description of Inte rnet-based Sampli ng Alternative ........................................... 109 Attachment 5: Telephone Screener Script .................................................................................. 113

TABLES

Table A1: Geographic St ratification Design ................................................................................. 15
Table A2: Schedule for Su rvey Implementation .......................................................................... 24 Table A3: Total Estimated Bottom Line Burden and Cost Summary .......................................... 26
Table B1: Number of Households and House hold Sample for Each EPA Study Region ............ 33
Table B2: Illustration of an External Scope Test ......................................................................... 551 PART A OF THE SUPPORTING STATEMENT

1. Identification of the 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 February 16, 2004, the U.S. Environmen tal Protection Agency (EPA) took final
action on the Phase II rule governing cooling water intake structur es at existing facilities that are point sources; that, as their primary activity, both generate and transmit electric power or generate electric power for sale to another entity for transmi ssion; that use or propose to use cooling water intake structures with a total desi gn intake flow of 50 MGD or more to withdraw cooling water from waters of the United States; and that 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 Phas e II regulations. On judi cial review, the Second Circuit (Riverkeeper, Inc. v. EPA, 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 costbenefit analysis as a criterion for determini ng Best Technology Available (BTA), and EPA inappropriately used ranges in setting performance expectations. In response, EPA suspended the Phase II regulation in July 2007 pending furthe r 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 decisionmaking. On April 1, 2009, the Court, in Entergy Corp. v. Riverkeeper Inc., decided that “EPA permissibly relied on cost-benefit analysis in setting the national performance standards ... as part of the Phase II regulations.” EPA is now ta king a voluntary remand of the rule, thus ending
Second Circuit review. On June 1, 2006, EPA promulgated the 316(b) Ph ase III Rule for existing manufacturers, small flow power plants (faciliti es that use cooling water intake structures with a total design2 intake flow of less than 50 MGD to withdraw co oling water from waters of the United States; and that use at least 25 percent of the withdr awn water exclusively fo r cooling 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. EP A has petitioned the Court for a voluntary remand of the existing facilities portion of the Phase III rulema king. In developing the Phase III regulation, EPA began, but did not complete, a similar stated pr eference survey effort. The
current effort builds on that earlier work. EPA is now combining the two phases in to one rulemaking covering all existing facilities. EPA will develop regulations to provide national performance standards for controlling impacts from existing cooling water intake stru ctures (CWIS) under Sect ion 316(b) of the Clean Water Act (CWA). Under Executive Order 12866, EPA is required to estimate the potential benefits and costs to society. To assess the public policy si gnificance or importance of the ecological gains from the section 316(b) regulation for existing fa cilities, EPA requests ap proval from the Office of Management and Budget to conduct a stated preference survey and analysis. Data from the associated stated preference survey will be used to estimate the 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 interpre tation and validation of survey responses. As indicated in the prior literature (Cummings and Harrison 1995; Johnston et al. 2003, 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 questions 11 to 13. The structure of choice attribute questions will also allow the analysis to separate value components
related to the most common s ources of use values—effect on harvested recreational and commercial fish. The remaining welfare estimate s are expected to be composed primarily of non-use components, although some use value components might also be included for some respondents. In summary, the survey will provide estimates of total use plus non-use values, will allow estimates of value associated with specific choice attributes (follo wing standard methods for choice experiments), and will also allow the flexibility to provide some insight into the relative importance of use versus no n-use values in th e 316(b) context.3 Within rulemaking, among the most crucial concerns is the a voidance of benefit (or cost) double counting. Here, for example, the WTP es timates will include use and non-use values among a representative population sample. Th ese may overlap—to a potentially substantial extent—with use value estimates that might be provided through some other methods, including revealed preference methods that might be used to estimate use values of recreational anglers for fish kill reductions (i.e., through related improve ments in fishing quality). While using the proposed stated preference value estimates for benef it estimation, particular ca re will be given to avoid any possible double counting of values that might be derived from alternative valuation methods. In doing so, the Office of Water w ill rely upon standard theoretical tools for nonmarket welfare analysis, as presented by authors including Freeman (2003) a nd Just et al. (2004). From a purely mechanistic perspective, survey re sults will be used to derive use and non-use values following standard practice for choi ce experiments (Adamowicz et al. 1998). The target population for this stated preference survey is a ll individuals from continental U.S. households who are 18 years of age or ol der. The population of households will be stratified by the geographic boundari es of 5 EPA study regions: Ca lifornia, Great Lakes, Inland, Northeast, and Southeast

. The Northeast survey region incl udes the North Atlantic and Mid Atlantic 316(b) benefits regions and the Southeast survey region includes the South Atlantic and Gulf of Mexico 316(b) benefits regions. Res pondents will be recruited using a random digit dialing (RDD) sample (overlapping dual fr ame; land and cell) and a brief telephone questionnaire. Participation in the survey is volun tary. If the person in the household agrees, the recruited respondent will be asked to complete the survey questionna ire by mail. EPA intends to administer the mail survey to 5,000 households in order to achieve 2,000 completed responses assuming a 40% completion rate for households agreei ng to participate. EP A is also considering implementing the proposed survey as an internet-b ased, choice experiment questionnaire. This alternative approach is described in Attachment 4. For the selection of households, the populati on of households in the 48 states will be stratified by the 5 EPA regions. The sample is al located to each region in proportion to the total
number of households in that re gion with the restricti on that we get at least 288 persons in each region. Non-response bias has the potential to occur due to househol ds declining to participate in the mail survey when contacted by phone and households which fail to return a completed survey after agreeing to part icipate. To conduct a non-response study, EPA will use a brief telephone questionnaire to collect sa mple characteristics in the cour se of the telephone contact.4 EPA will analyze the characterist ics of the completed and non-completed cases from the random digit dialing sample to determine whether there is any evidence of signi ficant non-response bias in the completed sample. This analysis will suggest whether any wei ghting or statistical adjustment needs to be used to minimize th e non-response bias in the completed sample. As part of the testing of th e survey instrument, EPA is in the process of requesting and obtaining approval from the Office of Management and Budget to conduct a series of eight focus groups with a total of 80 responde nts (10 participants per focus group). Because focus groups in different study regions might provi de distinct information relevant to survey design the Agency will conduct focus groups in multiple regions. These focus groups will be conducted following standard, accepted practices in the stated preference literature, as outlined by Mitchell and Carson (1989), Desvousges et al. (1984), Des vousges and Smith (1988) and Johnston et al. (1995). Some of the focus groups will incorpor ate individual cognitive interviews, as detailed by Kaplowicz et al. (2004). The focus groups a nd cognitive interviews will allow EPA to better understand the public's perceptions and attitude s concerning fishery re sources, to frame and define survey questions, to pretest draft survey questions, to test for a nd 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 will allow in-depth exploration of the cognitive processes used by respondents to answer survey quest ions, without the potential for interpersonal dynamics to sway respondents’ comments (Kaplowicz et al. 2004). These eight focus groups will be conducted in addition to focus groups conducted previously by EPA under ICR #2155.01 to test the draft survey for the Phase III benefits analysis. Transcripts from the previously conducted focus groups can be found in the docket for EPA ICR #2155.02 (Besedin et al., 2005). Findings from these previous focus groups were incorporated in to the development of the current survey.
The total national burden estimate for all co mponents of the survey is 1,527 hours. The burden estimate is based on 8,333 participants in telephone screeni ng interviews and 2,000 respondents to the 5,000 mailed questionnaires. EPA assumes an average burden estimate of 5 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 $34,600.5 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 th e Clean Water Act authorizes and directs the EPA Administrator
to conduct research into a numbe r of subject areas related to water quality, water pollution, and water pollution prevention and abatement. This s ection also authorizes th e EPA Administrator to conduct research into methods of analyzing the costs and benefits of programs carried out under
the Clean Water Act. This project is exploring how public values for fishery re sources (covering both use and non-use values) are affected by fish losses from impingement and entrainment at cooling water
intake structures. Understandi ng total public values, including the more difficult to estimate non-use values, for fishery resources is necessa ry to determine the fu ll range of benefits associated with reductions in impingement and en trainment losses, and wh ether the benefits of government action to reduce impingement and en trainment losses at ex isting facilities are
commensurate with the costs of su ch actions. Because non-use values may be substantial, failure to recognize such values may l ead 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 f acilities as required under Executive Order 12866.

2(b) Practical Utilit y/Users of the Data

EPA plans to use the results of the survey to improve estimates of the economic benefits of the section 316(b) regulation for existing faci lities. Specifically, the Agency will use the survey results to estimate tota l values for preventing losses of fish through impingement and entrainment at CWIS, following standard practi ces outlined in the lite rature (Freeman 2003; Bennett and Blamey 2001; Louviere et al. 2000; U.S. EPA 2000).

3. Non-duplication, Consultations, and Other Collection Criteria 3(a) Non-duplication6 EPA has not identified any pr evious studies that would a llow direct estimation of the
social benefits of nationwide reductions in fish losses for all species (including forage, recreational, and commercial species) affected by the proposed 316(b) regulation. Therefore, to the best of our knowledge this survey is unique and does not d uplicate other efforts. There are many studies in the environmental eco nomics literature that quantify benefits or willingness to pay (WTP) associated with va rious types of water quality and aquatic habitat changes. However, none of these studies allows the isolation of non-market WTP associated 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 qual ity and ecosystem services, but for which WTP associated with fish or aquatic life alone cannot be identified. Other studies provide benefit estimates associated with improveme nts in fish (or aquatic) habitat, but do not link this to welldefined and quantified changes in affected or supported organisms. Still other studies address willingness to pay for changes in charismatic or r ecreational species that have little relationship to the types of forage fish that are the vast ma jority of species affected by cooling water intake

structures. For example, choice experiment studies such as Hanley et al. (2006a, 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 as sociated 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 much more challenging.
Other studies have estimated th e value of changes in catch ra tes or populations of select recreational and commercial species, charismatic species such as salmon, or changes in water quality that affect fish, but none have specifically valued change s in forage fish populations. For example, Olsen et al. (1991) conducted a survey of Pacific Northwest re sidents, including both anglers and non-anglers, to de termine their WTP for doubling th e size 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, 19 89) in that it would include respondents from various geographic regions in the United States a nd would provide values for the full range of forage, recreational, and commerc ial species affected by 316(b) re gulations, instead of valuing a few recreational species in one specific geographical area.7 Among available studies, the most closely related is Johnston et al. (2009), which estimates total willingness to pay (WTP) for multi- attribute aquatic ecosyst em changes related to improvements in small migratory (diadromous) fi sh in Rhode Island. Unlike other studies, the choice experiment data of Johnston et al. ( 2009) allow 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 ot her studies in the literature, WTP estimates of Johnston et al. (2009) are not confounded with valu es for other changes including water quality, habitat, overall ecol ogical condition, etc. In addition, the choice experiment of Johnston et al. ( 2009) addresses species such as al ewife and blueback herring that are neither subject to recreati onal or commercial harvest in R hode Island, nor are charismatic species. Hence, the species affected are a close an alog to the forage fish th at are at primary issue in the 316(b) policy context. Although the methods and data of Johnston et al. (2009) allow quantification of
combined use and non-use values associated w ith specific improvements in forage and/or recreational fish, and also provide limited ability to isolate non- use values from use values, the policy context and scale of the survey prevent its direct use for analysis of national benefits of the 316(b) regulation. Specifica lly, Johnston et al. (2009) esti mate Rhode Island residents’ preferences for the restoration of migratory fish passage over dams in the Pawtuxet and WoodPawcatuck watersheds. Hence, the case study is for a watershed-level policy with statewide welfare implications. In contrast, 316(b) pol icies 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 (44 U.S.C. 3501 et seq.), EPA published a notice in the Federal Register on July 21, 2010, announcing that the survey questionnaire and sampling methodology are availabl e for comment. A copy of the first Federal Register notice is attached at the end of this document (EPA ICR #2402.01.02) (See Attachment 2). As mentioned in the abstract (section1(b)) this current survey effort grew out of work conducted for the Phase III rulemaking. EPA recei ved a number of comments on that proposed Phase III information collection, which are summa rized in the following paragraphs. Also see8 docket # EPA-HQ-OW-2005-0006. EPA considered re levant comments on the draft Phase III survey when developing the survey questionn aire and sampling methodology for the current survey for existing facilities.
Several commenters stated that the Phase II I survey would provide inaccurate estimates of WTP to prevent fish losses. One commenter argued that the presentation materials prepared by EPA contain inaccurate statements and invalid comparisons that would lead respondents to
believe that the benefits of in creased regulation of cooling wate r intakes would be substantially greater than is actually the case. A different 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 th e Phase III survey and presentation materials provided in the suppor ting documentation for the June 9, 2005 Federal Register notice require d revision. Following the June 9, 2005 Federal Register notice, EPA conducted four focus groups and two cognitive in terview sessions to improve the Agency’s understanding of the public's per ceptions and attitudes concerning fishery resources, to pretest draft survey questions and presenta tion materials, to test for and reduce potential biases that may be associated with stated preference methodol ogy, and to ensure that both researchers and respondents have similar interpreta tions of survey language and scenarios. As a result of this extensive pre-testing, a number of revisions were made to the Phase III survey that significantly improved its reliability and reduced its potential for bias. These comments were considered when developing the current existing facilities survey. One commenter argued that the Phase III su rvey did not sufficiently emphasize the uncertainty in the estimates of the fish losses th at would be prevented by the proposed policies. 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, respondents were comfor table making decisions in the presence of this uncertainty. Additionally, EPA emphasizes the uncertainty of the expected environmental changes within the current existing facilities su rvey. For example, the following statement is included in the current survey with accompa nying graphs: “Scientists know that about 1.1 billion young fish are lost per ye ar in Northeast coastal waters due to cooling water use. But,
scientists do not know the total number of fish in North east coastal waters. Studies of specific fish can provide some information on how many fi sh are lost, compared to the total number of
fish in the water. Sometimes the number of fish lost is relatively small compared to the total9 number of adult fish – an example is striped bass (see graph below). Sometimes the number of fish lost is relatively large compared to the to tal number of adult fish – an example is winter flounder (see graph below). For many types of fi sh, the number of young fish lost compared to
the total number of adult fish lies somewhere in between these extremes. Even though scientists can predict approximately the number of fish that will be saved, the ultimate effects on fish populations (the number of fish in the water) is uncertain.” EPA also a dded debriefing questions to the survey instrument that are designed to identify individuals whos e responses are based on incorrect interpretation of the environmental ch anges described in the survey, including the uncertainty of the expected changes. The same commenter on the Phase III survey al so argued that the benefits of regulating cooling water intake structures for recreationa lly and commercially significant species are already reflected in the EPA’s RI A for the proposed rule for Phase III facilities. EPA disagrees with the commenter’s statement. As stated by Freeman, “Non-use values, like use values, have their basis in the theory of individual preferences and the m easurement of welfare changes. According to theory, use and non-use values are additive” (Freeman, 2003). EPA notes that the non-use benefits of the proposed regulation are a co mpletely separate category of value from the
commercial and recreational welfare effects of the proposed rule. Furthermore, results from the previous focus groups and cognitive interviews in dicated that some individuals hold substantial non-use values for protecting fish species with direct uses, in addition to any use values that they have for those species. As indicated on pages 2 and 3 above, the survey will be used to estimate total values (WTP) derived by households for ch anges related to the reduction of fish losses at CWIS. Therefore EPA will take particular care to avoi d any possible double counting of benefits values that might be derived from a lternative valua tion methods. The commenter also argued that the survey is unnecessary because in independently conducted verbal protocol interviews with 15 individuals, respondents did not demonstrate meaningful values for marginal changes in fora ge fish populations. EPA notes that this finding contradicts the results of the EPA focus groups and cognitive interviews conducted under ICR #2155.01. These focus groups and interviews provid ed strong evidence that many individuals value forage fish and are willing to pay to prevent losses of all fish species including forage fish. Participants in the EPA focus groups and intervie ws cited a variety of motivations for preventing fish losses, including the satisfa ction of knowing that the fish exist, the desire to bequeath10 healthy fish populations to future generations, and the desire to protect the functioning of aquatic ecosystems. Furthermore, EPA notes that the ec onomic literature advises against the use of ad hoc, expert assumptions regarding the magnitude of non-use values—particularly assumptions
that non-use values are trivial. Because values are inherently subjectiv e, Bateman et al. (2002, p. 75) emphasize that “it would be wrong for experts to assume that one re source is a perfectly good substitute for another” [and hence that non-us e values are trivial or small]. As further noted by Bateman et al. (2002, p. 75), “there are, therefore, no easy rules for determining at the outset” whether non-use values are likely to be si gnificant or non-significant . Based on this clear guidance, EPA believes that empirical analysis should be used to determine the magnitude of non-use values in the 316(b) re gulation for exis ting facilities. The commenter argued that because the su rvey materials are based on unreliable population and fish losses data, the survey results will also be unreliable. In response, EPA first notes that the survey materials are based on the be st biological and engineer ing data available. Second, even if this data is uncer tain, the stated prefer ence survey will stil l produce results that are meaningful in the context of the scenarios that are presented to respondents. Different versions of the 316(b) survey will show a range of different baseline an d resource improvement levels, where these levels are chosen to almost certainly bound actual levels. Different respondents will be asked to make choices over all possible policy scenarios where impingement and entrainment reductions range from 0% (no polic y) to 98%. Given that there will almost certainly be some biological uncertainty regard ing the specifics of the actual baselines and improvements, the resulting valuation estimates will allow flexibility in estimating WTP for a wide range of different circumstances. Finally, the commenter expresse d the opinion that th e survey should be peer reviewed by an independent panel of experts. EPA conducted an external peer review of the previous version of the survey instrument focusing on (1) the a ppropriateness of the survey design for measuring fish resources affected by cooling water in take structures (CWIS), (2) sufficiency and appropriateness of information provided in the su rvey on the baseline ecological conditions, the expected changes, and the expected costs, a nd (3) whether the answers to this survey lend themselves to straightforward economic interpre tation of WTP. Reviewers offered concrete suggestions for further improvements of the surv ey instrument. EPA has incorporated many of
the reviewers’ comments in this new exis ting facilities survey (Versar, 2006).11 Another commenter argued that neither the Cl ean Water Act nor section 316(b) require or allow EPA to use monetized cost-benefit analysis to determine regulatory standards for cooling water intake structures. However, the Supreme Court ruled that EPA does have the authority to
consider costs and benefits in § 316(b) regulations. EPA is also conducting this survey because of Executive Order 12866, “Regulatory Planning and Revi ew,” which requires Federal Agencies to conduct economic impact and cost-benefit analysis fo r all major rules. Furthermore, cost-benefit analysis requires a comprehensive, estimate of total social benefits, including both use and nonuse values. The current information collection w ould provide valuable information that includes both use and non-use benefits of the 316(b) regu lation for existing facil ities, thus enabling the Agency to perform cost-benefit analysis for th e regulation and to sati sfy the requirements of
Executive Order 12866.
In addition to the comments received in res ponse to the June 9, 2005 Federal Register notice for the Phase III survey, a number of the comments received by EPA in response to the previous focus group information collection re quest (EPA ICR #2155.01) are relevant to the
current ICR. Most of these comments addresse d the more general topic of resource valuation and stated preference surveys. Many of the claims made in the submitted comments represent empirical questions that were a ppropriately addressed within th e survey design process. Some commenters argued that non-us e benefits in the Phase III policy c ontext are likely to be trivial. EPA points out that (1) these claims are unsubstan tiated by the empirical literature and (2) that the magnitude of non-use benefits in the 316(b) ex isting facilities context is an empirical issue that can only be addressed with appropriate resear ch methods. Even if non-use values for fish are small on a per-capita basis, they may be large in the aggregate. Commenters also questioned the reliability of the empirical estimates of total benefits of the Phase III regulation and thus the practical value of the information provided by the focus groups and stated preference survey. EPA believes, however, following guidance in the literature, that stated preferen ce methods are capable of measuring total values (including use and non-use) of fish affected by impingement a nd entrainment, if surveys and approaches are appropriately designed. The Offi ce of Management and Budget’s “C ircular A-4" states that “a stated preference study may be the only way to obtain quantitative information about non-use values,” and EPA’s own guidance explicitly permits the use of stated preference methods for use and non-use value estimation (US EPA 2000), following prior findings of the NOAA Blue Ribbon Panel on Contingent Valuation (Arrow et al. 1993). EPA recognizes the difficulties12 faced in the design of appropriate stated prefer ence survey instruments (focus groups), but does
not consider these difficulties to be insurmount able. As stated by Freeman (2003, p. 154), stated preference survey methods “are likely to offer th e only feasible approaches to estimating non-use values.” Furthermore, although the peer reviewed literature is highly skeptical of stated preference surveys that attempt to decompose use and non-use values, there is general conceptual acceptance that the total values of non-users can be used to approximate non-use values for all individuals (Cummings and Harri son 1995, Johnston et al. 2003a) 1

. Finally, one commenter noted th at if EPA is to consider non-use value effects on the benefit side of the regulation, then the Agency should also consider non market and non-use value effects on the cost side of the regulat ion, such as values fo r effects on mining, the efficiency of energy production, and the use of depletable resources. While EPA acknowledges the theoretical validity of this point, EPA knows of no precedents to guide design of a survey on non-use costs, nor does EPA expect economic imp acts as significant as closures that would
warrant further considerati on of non-use costs.
For a more detailed discussion of the issues raised by commenters on the previous Phase III survey ICR, see EPA’s response to pubic comm ents on the Federal Register notice published on June 9, 2005 (70 FR 33746). For a discussion of issues raised by commenters on the previous 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-pre ference portion of this effort is Dr. Robert
Johnston. 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 Presiden t-elect of the Northeastern Agricultural and Resource Economics Association (NAREA), on th e Program Committee for the Charles Darwin Foundation, the Science 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

1 Note that by definition, total values for non-users are non-use values.13 (goods, services, and resources), benefit cost analysis, and res ource management. His recent research emphasizes coordination of ecological and economic models to estimate ecosystem service values, with particular em phasis on the role of aquatic ecolo gical indicators. He has also worked extensively in methodologies for benefit transfer, including the us e of meta-analysis. Professor Johnston’s empirical work on non-ma rket valuation and be nefit transfer has
contributed to numerous benefit cost analyses conducted by fede ral, state and local government agencies in the US, Canada and elsewhere. Elena Y. Besedin, a senior economist at Abt As sociates Inc., specia lizes in the economic analysis of environmental policy and regulat ory 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 program offices. She has worked extensively on valuat ion of non-market benefits associated with environmental improvements of aquatic resources. Dr. Besedin’s empirical work on non-market valuation includes design and implementation of stated and revealed preference studies and benefit transfer methodologies. Her recent wo rk has focused on developing integrated frameworks to value changes in ecosystem serv ices stemming from environmental regulations. EPA has conducted an external peer review of the previous version of the survey instrument. The previous version of the survey instrument was review ed by Dr. Richard C. Bishop, Dr. Kevin J. Boyle, Dr. Timothy C. Haa b, Dr. James R. Kahn, and Dr. Alan J. Krupnick. The review focused on (1) the appropriateness of the survey design for measuring fish resources affected by cooling water intake structures (CWIS), (2) sufficiency and appropriateness of information provided in the survey on the base line ecological conditions, the expected changes, and the expected costs, and (3)whether the answers to this survey lend themselves to straightforward economic interp retation of WTP. The review ers acknowledged the extensive effort that was placed into survey design and noted that the 316(b) su rvey was a well-designed study. They also offered concrete suggesti ons for further improvements of the survey instrument. EPA has incorporated many of the re viewers comments in this new survey for 316(b) existing facilities (Ver sar 2006, Docket ID No. EPA-HQ-OW-2004-0002-2007).

3(d) Effects of Less Frequent Collection

The survey is a one-time activity. Ther efore, this section does not apply.14 3(e) General Guidelines

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

3(f) Confidentiality

All responses to the survey will be kept stri ctly anonymous. To ensure that the final survey sample includes a representative and diverse population of indi viduals, the survey questionnaire will elicit basic demographic information, such as age, household size, employment status, and income. However, the su rvey questionnaire will not ask respondents for personal identifying information, such as names, phone numbers, or addresses. Prior to taking the survey, respondents will be informed that thei r responses will be held strictly anonymous. The survey data will be made public only after it has been thoroughly vetted to ensure that all potentially identifying 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 reli gious beliefs.

4. The Respondents and the Information Requested

4(a) Respondents The target population for the Stated Preferen ce Survey is all indivi duals from continental U.S. households who are 18 years of age or older. Survey participants are recruited randomly through random digit dialing. EPA will identify a random stratified sample of 5,000 adults who express their willingness to par ticipate in a mail survey when contacted by telephone through random digit dialing. All of these recruits will be sent a copy of the mail survey. Approximately 2,000 of the adults of the 5,000 adults sent a survey are expected to return a completed survey. For the selection of households, the populati on of households in the 48 states will be stratified by 5 study regions. Ther e are a total of seve n study regions for purposes of evaluating15 the 316(b) existing facilities rule benefits. For the purposes of the stated preference survey implementation, EPA uses five geographic regions: California, Great Lakes, Inland, Northeast, and Southeast. The Northeast region includes the North Atlantic and Mid Atlantic regions and the Southeast region includes the South Atlantic a nd Gulf of Mexico regions. The survey sample is allocated to each region in proportion to the total number households in that region with the restriction that we get at least 288 persons in each region. This is the number required to
estimate the main effects and interactions under an experimental design model. The minimum sample size required for model estimation (i.e., 2 88 persons per region) may increase if revisions to the survey result in additional effects and interactions. However, an increase in the minimum sample size for a given region woul d have a negligible effect on the total sample size because the total sample size is much larger then the mini mum sample size required for model estimation for all but one region (Inland). Part B of this document provides detail on sampling methodology. Table A1 shows the stratification design for the geographic regions covered by the sample for this survey. More detail on planne d sampling methods and th e statistical design of the survey can be found in Part B of this supporting statement.

Table A1: Geographic Stratification Design

Region States Included Sample Size a Percentage of Sample
Northeast CT, DC,DE, MA, MD, ME, NH, NJ, NY, RI, VT 301 15%

Southeast AL, AR, FL, GA, KY, LA, MS, NC, OK, SC, TN, TX, VA, WV 626 31%

Great Lakes IA, IL, IN, MI, MN, MO, OH, PA, WI 461 23%

Inland Region CO, ID, KS, MT, NE, ND, SD, UT, WY 288 14%

Pacific Mountain AZ, CA, NM, NV, OR, WA 324 16%

Total, All Regions U.S. (excluding AK and HI) 2,000 100%

a Sample sizes presented in this table include only the 2,000 individuals returning completed mail surveys.16 4(b) Information Requested (I) Data items, including recordkeeping requirements Individuals who agree to participate in the survey will be mailed a copy of the survey. The full text of the draft mail survey is provide d in Attachment 1. EPA may revise the survey based on the findings of a series of eight additio nal focus groups designed to pretest the survey. EPA is expecting approval to conduct these focus goups under a different ICR (OMB control # 2090-0028). Additional information regarding the fo cus groups implementation is provided in Section 5(b). EPA has determined that all questio ns in the survey are ne cessary 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 th e major sections of the survey. Relative Importance of Issues Associ ated with Industrial Cooling Water. The first survey question asks respondents to rate the general importance of (a) reducing government regulations on facilities, (b) preventi ng losses of fish used by humans, (c) preventing losses of fish not used by humans, (d) maintaining ecological health in rive rs, lakes, and bays, and (e) allowing facilities to produce products and services at low cost. Th is question is designed to elicit the respondent’s general preferences for regulation, re ductions in fish losses, and ecol ogical health. It also places respondents in the mindset where th ey are cognizant of the range of issues associated with the use of cooling water by industrial facilities. Concern for Policy Issues. The second survey question asks respondents to ra te the general importance of a range of public policy i ssues, including both environmental and nonenvironmental issues. This question is designed to highlight the many important policy issues and substitute concerns to which respondents might choose to direct funds , rather than spending these funds to prevent fish losses. Such questions are commonly used in introductory sections of stated preference surveys (e.g., Mitchell and Carson 1984), in orde r to place respondents in a mindset in which they are cognizant of substitute goods and policy issues to which they might direct their scarce household budgets. Relative Importance of Effects. Question 3 asks the respondent to rate the importance of each of the effects captured by the five scores: (a) fi sh saved, (b) commercial fish sustainability, (c) fish population, (d) condition of aquatic ecosystems , and (e) cost per year. This question is designed to promote understanding of the scores by placing respondents in a mindset where they consider the meaning of each scor e and consider their general pr eferences for effects prior to17 considering specific policy options. The que stion 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 Region. Questions 4, 5, and 6 are “choice experiment” or “choice modeli ng” 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 wate rs). Each of the multi-attribute options is characterized by (a) fish saved per year (out of total fish lost in regional cooling water intakes), (b) commercial fish sustainability (in 3-5 years) , (c) fish population (all fish; in 3-5 years), (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 op tion—providing the status quo option is necessary for appropriate welfare estimation (Adamowicz et al. 1998). Adva ntages of choice experiments, and the many examples of the use of such approaches in the li terature, are discussed in later sections of this ICR. Following standard appr oaches (Opaluch et al. 1993, 1999; Johnston et al. 2002a, 2003b), respondents are instructed to answer each of the three choice questions independently, and not to “add up or compare programs across different pa ges.” This is included to avoid biases associated with sequence aggregation eff ects (Mitchell and Carson 1989). EPA will also randomize the order in which the policy option attri butes are presented acro ss respondents. This
would allow for a statistical test of potential ordering effects. Reasons for Voting “No Policy”. Question 7 is a follow-up to the prior voting questions, and asks respondents to identify th e primary reason for voting no, if they always voted for “no policy” in questions 4-6. It is designed to identify respondents whose “n o 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 the survey and answered questions based on their general convictions and principl es. In an electronic survey format, respondents who voted for a policy woul d not see this question, potentially reducing
burden. Voting for Regulations to Prevent Fish Losses in the Entire United States. Question 8 is a choice experiment question and asks respondents to choose how they would vote, if presented with two hypothetical regulatory opt ions (and a third choice to reje ct both options) for the entire18 United States. This question presents multi-attrib ute options using the same scores as questions 4-6 for region-specific policy options. However, th e scale of the policy is changed to the entire
United States and assumes that all U.S. households would pay for the programs. This question is designed to capture potential differences in th e value that respondents place on improvements within their region compared to improvements in U.S. waters outside of their region. It also captures potential differences in respondents’ pr eferences for regional and national policies. Respondent Certainty and Reasons for Voting. Questions 9 and 10 ar e follow-up questions to the prior voting. Question 9 assesses the certai nty that respondents f eel in their choice experiment responses, following methods of Champ et al. (2004; 2009), Akter (2009), Kobayashi et al. (2010), and others . It is designed to identif y respondents whose responses are based on incorrect interpretation of the resour ce changes and the uncertainty of ecological outcomes from policy options. EPA will evaluate respondent understanding when completing stated preference surveys usi ng methods and approaches discu ssed in Boyle (2003), Kaplowitz et al. (2004), Bateman et al. ( 2002), Powe (2007) and others. Qu estion 10 asks respondents to
rate the effect of factors on their choices, and why they voted for or against the regulatory programs. Responses to such questions have been used in the literature to successfully control for hypothetical bias. Recreational Experience. Questions 11, 12, and 13 ask responde nts how often they participate in specific types of water-relate d recreational activities, and wh ether those activities would be affected by changes in fish abundance. Question 11 asks respondents about their participation at all locations while Question 12 asks respondents a bout their participation within their region. These questions can be used to identify non-us ers of the fishery resource—thereby allowing the
estimation of non-user values for I&E reductions. Examples of this approach to estimation of non-user values are provided by Johnston et al . (2005), Whitehead et al. (1995), Croke et al. (1986), Olsen et al. (1991), Cr onin (1982), Whitehead and Groot huis (1992), and Mitchell and Carson (1981). Demographics. Questions 14-22 ask respondents to pr ovide 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 nonresponse analysis.
Comments. The survey offers respondents a chance to comment on the survey.19 The Agency will modify the survey instrume nt for each region relative to the current survey draft in Attachment 1 fo r the Northeast region as follows:

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

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

 Page 1 – The survey states that it “asks fo r your opinions regarding policies that would
affect fish and habitat in the Northeast US .” “Northeast US” will be replaced with the respondent’s region.

 Page 1 – Includes the statement that “Northeast fresh and salt waters support billions of fish.” “Northeast” will be replaced with the respondent’s region and “salt water” will be removed from the Inland and Great Lakes regions.

 Page 2 - The survey states that “Cooling 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 California and Southeast regions, which include both salt water and freshwater facilities, referen ce to the Northeast region would be replaced with the name of the respondent’s region. For the Great Lakes and Inland survey regions, which only include freshwater facilities, refe rence to salt water will be removed.

 Page 2 – A map of the Northeast region and fac ility locations is presented. A comparable map will be produced for each region, and map included in the survey will correspond to the respondent’s region.

 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 and example species will be modified to describe species and losses occurring within the respondent’s region.

 Page 5 - The total losses (1.1 billion) curren tly included within the survey corresponds to
losses from facilities in Northeast coastal wate rs. This total would be replaced with the total losses for the responde nt’s region. The pie charts will be updated based on the regional total while maintaining the 25% a nd 95% reductions used in the example.20  Page 7 - The table text describi ng each score will be changed to include the current scores for the respondent’s region.

 Page 8 - Text describing the commercial fi sh sustainability sc ore and fish population score will be changed to desc ribe the current score for the respondent’s regi on relative to
its maximum.

 Page 9 – The text states that the aquatic ecosystem score me asures “how close affected Northeast waters are to the most natural, undisturbed condition that is possible.” “Northeast waters” will be repl aced with a reference to wate rs within the respondent’s region.

 Page 12 – The included figure illustrates the location of “Coastal Facilities Affected by the Proposed Policies”. For other regions wh ich include both salt water and freshwater facilities, the figure will be replaced with a similar figure circling salt water facilities within the respondent’s region. For the Gr eat Lakes and Inland regions (which do not include salt water facilities), only facilities w ithin the region will be shown in the figure, making the circle unnecessary.

 Pages 13-16 – Regional references within th e table headings in Questions 4, 5, and 6 (e.g., “Policy Effect NE Coastal”, “Option A NE Coastal”) will be modified to refer to the policy effects and options for the res pondent’s region. The “Fish Saved per Year” score includes a note reminding th e respondent of total fish lo st within the region due to I&E (e.g., 1.5 billion); this number will be ch anged to reflect tota l 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 across regions.

 Page 17 – Text describing “National versus Nort heast policies” will be modified to refer to the respondent’s region.

 Page 21 – Question 12 asks the respondent how tim es he participated each of six activity categories over the last year within the “North eastern US only”. Text will be changed to reflect the respondent’s region including the list of states which the region includes.

(II) Respondent activities

EPA expects individuals to engage in the follo wing activities during thei r participation in the contingent valuation survey:21  Review the background information provided in the beginning of the survey document.

 Complete the survey questi onnaire and return it by mail. A typical subject participating in the mail su rvey is expected to take 25 minutes to complete the survey. These estimates are derived from previous focus groups and cognitive interviews for the Phase III survey in which respondents were 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, a nd analyzed by Abt Associates Inc. and is funded by EPA contract No. EP-C -07-023 which provides funds for the purpose of analyzing the economic benefits of the proposed rule for exis ting facilities subject to the section 316(b) regulation. Agency activities associated w ith the survey consis t of the following:

 Develop the survey questi onnaire and sampling design.

 Printing of questionnaires.

 Telephone screening of respondents.

 Mailing of questionnaires.

 Mailing of postcard reminders.

 Follow-up with non-respondents to the mail surv ey/resending of questionnaire if needed.

 Data Entry and cleaning of data file.

 Analysis of survey results. Although not covered under this ICR, EPA w ill primarily use the survey results to estimate the social value of changes in impi ngement and entrainment losses of forage, recreational, and commercial species of fish, as pa rt of the Agency’s analys is of the benefits of the 316(b) rule for existing facili ties. If reliable environmenta l data are developed for population changes and other ecosystem impacts, social values for these benefit types may also be assessed for the rulemaking using survey results.22 5(b) Collection Methodology and Information Management

To pretest the survey questionnaire, EPA will conduct a series of eight focus groups, including some using cognitive interview me thodologies (conducted under a separate information collection request). EPA is planni ng to conduct these focus groups under a different ICR (OMB control # 2090-0028). Focus groups will provide valuable feedback that will allow EPA to iteratively edit and refine the questi onnaire, and eliminate or improve imprecise, confusing, and redundant questions. Focus groups and cognitive interviews will be conducted following standard approaches in the literature, as outlined by Desvousges et al. (1984), Desvousges and Smith (1988), Johnston et al. (1 995), Schkade and Payne (1994), Kaplowicz 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 solic it respondents to receive the mail questionnaire. A dual frame, random digit dial design will be used, including both landline and cell phone numbers. This ensures that even cell phone onl y households have an oppor tunity to participate in the survey. The telephone sc reener includes not only an invita tion 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 characteristic s. EPA will use this information for the nonresponse analysis to compare respondents and non-respondent s to the mail questionnaire. It is anticipated that approximately 60 per cent of respondents to th e telephone screener will agree to participate in the mail survey. EPA will then send the mail survey to those who agree to participate, along with a cover letter e xplaining the purpose of th e survey. All of these respondents will receive a reminder postcard a pproximately one week after the initial questionnaire mailing. Approximately three weeks after the reminder postcard, all those who have not responded will receive a second copy of the questionnaire w ith a revised cover letter. The following week, another reminder postcard 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 completed surveys is 2,000, it will be necessary to recruit 5,000 respondents by tele phone who agree to participate. 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 923 asks respondents to rate their unde rstanding of the survey and their confidence in their responses. Questions 7 and 10 are designed to assess the presence or absence of potential response biases by asking respondents to in dicate their reasoning and rate the in fluence of various factors on their responses to the choice experiment questions. Re sponses 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 impingeme nt and entrainment by section 316(b) existing
facilities. To protect the confidentiality of survey res pondents, the survey data will be released only after it has been thoroughly vetted to ensure that all potentially identifying information has been
removed. Alternatively, EPA is considering implemen ting the proposed survey as an internetbased, choice experiment questionnaire. This a lternative method is described in Attachment 4.

5(c) Small Entity Flexibility

This survey will be administered to indivi duals, 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:24 Table A2: Schedule for Survey Implementation

Activity Duration of Each Activity Printing of questionnaires Weeks 1 to 2 Telephone screening of respondents Weeks 3 to 8

Mailing of questionnaires Weeks 3 to 8 Postcard reminder (one week after initial questionnaire mailing) Weeks 4 to 9 Follow-up with 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 Burd en and Cost of Collection 6(a) Estimating Respondent Burden

Subjects who participate in the survey and follow-up interviews will expend time on
several activities. Ba sed on the administration of the mail survey to 5,000 households, the national burden estimate for all respondents is 1,527 hours assuming that 8,333 households will participate in telephone screen ing and 2,000 respondents complete and return the survey, EPA estimates that telephone screening inte rviews will take 5 minutes (0.08 hours) per interview for each of the 8,333 screened households. Based on pretests conducted in focus groups, EPA estimates that on average each respondent mailed the survey will spend 25 minutes reviewing the introductory materi als and completing the survey que stionnaire. Thus, the average burden per respondent is 25 minutes (0.42 hours) for these 2,000 respondents. These burden estimates reflect a one-time expenditure in a single year.

6(b) Estimating Respondent Costs

According to the Bureau of La bor Statistics, the average hou rly 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 8,333 screening participants and an25 average hourly wage of $20.42, the average cost per screening pa rticipant is $1.70. Therefore the total cost to par ticipants in the telephone screeni ng phase would be $14,180. Assuming an average per-respondent burden of 0.5 hours for i ndividuals mailed the survey and an average hourly wage of $20.42, the average cost per re spondent is $10.21. Of the 5,000 individuals receiving the mail survey, 2,000 are e xpected to return their complete d survey. The total cost for
all individuals that retu rn surveys would be $20,420. EPA does not anticipate any capital or opera tion and maintenance costs for respondents.

6(c) Estimating Agency Burden and Costs

This project will be undertaken by Abt A ssociates Inc. with funding of $397,540 from EPA contract EP-C-07-023, which provides funds for the purpose of analyzing the economic benefits of the proposed rule for existing facilities subj ect to the section 3 16(b) regulation. Abt Associates Inc. staff is expected to spend 1,126 hours pre-testing the survey questionnaire and sampling methodology, conducting the su rvey, and tabulating and anal yzing the survey results. The cost of this contractor time is $74,931. In addition to the effort expended by EPA’s contractors, EPA staff is exp ected to spend 320 hours managing a nd reviewing this project and contributing to the analysis at a cost of $30,971. Agency and c ontractor burden is 1,446 hours, with a total cost of $105,902 excl uding the costs of survey printing and mailing. Telephone screening is expected to take 7,342 hours and cost $215,797 while mailing and printing of the survey is expected to take 141 hours and cost $106,812, including the cost of survey printing and mailing. Thus, the total Agency and contract or burden would be 8,929 hours and would cost $428,511

6(d) Respondent Universe and Total Burden Costs

EPA expects the total cost for survey respondents to be $34,600 (2009$), based on a total burden estimate of 1,694 hours and an hourly wage of $20.42.26 6(e) Bottom Line Burden Hours and Costs

The following table 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 694 hours $14,180 Mail Survey Respondents 1,000 hours $20,420 Total for Survey Respondents 1,694 hours $34,600 EPA Staff 320 hours $30,971 Telephone Screening 7,342 hours $215,797 Survey Printing and Mailing 141 hours $106,812 EPA’s Contractors 1,126 hours $74,931 Total Burden and Cost 10,624 hours $463,111

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 r ecord keeping burden associated with the mail survey will average 0.5 hours per respondent (i.e., a total of 1,000 hours of burden divided among 2,000 survey respondents). Households included in telephone screening are expected to average 0.08 hours per screening interview part icipant (i.e., a total of 694 hours of burden divided among 8,333 screening interview participants). This results in a to tal burden estimate of 1,694 hours including both the tele phone screening inte rviews and mail survey. Burden means the total time, effort, or financial resources expe nded by persons to generate, maintain, retain, or disclose or provide information to or for a Fede ral agency. This includes the time needed to review instructions; develop, acquire, install, and utilize technology and systems for the purposes of collecting, validating, and ve rifying information, processing and maintaining information, and27 disclosing and providing information; adjust the existing ways to comply with any previously applicable instructions and requi rements; train personnel to be able to respond to a collection of information; search data sources; complete a nd 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 collection of information unless it displays a currently
valid OMB control number. The OMB control nu mbers 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 provided 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 viewing 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 te lephone number for the Readi ng 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 th e draft collection of information, submit or view public comments, access th e index listing of the contents of the docket, and to access those documents in the public docket that are ava ilable electronically. Once in the system, select “search,” then key in th e docket ID number identif ied in this document.28 PART B OF THE SUPPORTING STATEMENT

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

The overall goal of this survey is to explor e how public values (including non-use values) for fish and aquatic organisms are affected by impingement and entrainment at cooling water intake structures (CWIS) located at existing 31 6(b) facilities, as refl ected in individuals’ willingness to pay for programs that would prevent such losses. EPA has designed the survey to provide data to support the fo llowing specific objectives:

 To estimate the total 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 individuals 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 losses, 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 values for fish resources lost to impingement and entrainment–is necessary to determine the full ra nge of benefits associated with reductions in impingement and entrainment losses at existing 3 16(b) facilities. Because non-use values may be substantial in some cases, failure to recognize such values may lead to improper inferences regarding policy benefits (Freeman 2003).

1(b) Key Variables

The key questions in the survey ask res pondents whether or not they would vote for policies that would increase th eir cost of living, in exchange for specified changes in (a) impingement and entrainment losses of fish, (b) comm ercial fish sustainabili ty, (c) long-term fish29 populations, and (d) condition of aquatic ecosystem s. More specifically, the choice experiment framework allows respondents to view pairs of multi-attribute policies associated with the reduction of I&E losses. Respondent s are asked to choose the program that they would prefer, or to choose to reject both policies. This follo ws 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 qu estions are how the respondent votes, the amount of the cost of living increase, the number of fish losses that are prevented, the sustainability of commercial fish ing, the change in fish populations , and the condition of aquatic ecosystems. Other important variables include wh ether or not the respond ent is a user of the affected aquatic resources, household in come, and other respondent demographics.

1(c) Statistical Approach

EPA believes that a statistical survey approach is appropr iate. A census approach is impractical because contacting all households in the U.S. would require an enormous expense. On the other hand, an anecdotal approach is not su fficiently rigorous to provide a useful estimate
of the total value of fish loss reduc tions for the 316(b) case. Thus, a statistical survey is the most reasonable approach to satisfy EPA’s analytic ne eds 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 questionn aire design, sampling design, and anal ysis of the survey results.

1(d) Feasibility

The survey instrument will be repeatedly pre- tested during a series of eight 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 review by reviewers in academia a nd 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 respondents. Thus, EPA believes that respond ents will not face any obstacles in completing the survey, and that the survey will produce usef ul results. EPA has dedicated sufficient funding (under EPA contracts No. EP-C-07- 23) to design and implement the survey. Given the timetable30 outlined in Section A.5(d) of this document, the su rvey results will be available for timely use in the benefits analysis for the 316(b) existing facilities rule.

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

The target population for this survey in cludes 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) Sampling Frames

The sampling frame for this survey is the pa nel of individuals r ecruited by random digit dialing (over-lapping dual frame; land and cell) to participate in a mail survey. The overall sampling frame from which these in dividuals 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 probability-b ased starting sample of U.S. telephone
households. The telephone screening will use an overlap ping dual frame design of landline and cell phone numbers to increase the coverage of the sample. The inclusion of cell phone numbers will allow us to reach potential respondents who onl y have cell phones and would be missed if only a sample of landlines was selected. The dual fram e design also avoids bi as because the cell-phone only population skews heavily towards lower-in come and younger individuals. The cell and landline samples will 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 fo r the survey. All landline res pondents to the telephone screener will be asked the number of eligible respondent s 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 Health31 Interview Survey) by a set of demographic va riables (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 are cell phone only, and 59.4 percent have both landline and cell phone service. Le ss than two percent of households have no telephone service. It is anticip ated that estimates for landlin e and cell phone service from the January to June 2010 National Health Interview Su rvey will be available for weighting purposes by the time the survey would be implemented. For discussion of techniques that EPA w ill use to minimize non-response and other nonsampling errors in the survey sample , refer to Section 2(b)(II), below.

(II) Sample Sizes

The intended sample size for the survey is 2,000 households including only households providing completed mail surveys. This sample size was chosen to prov ide statistically robust regression results while minimizing the cost and bur den of the survey. Given this sample size, the level of precision (see secti on 2(c)) achieved by the analysis wi ll be more than adequate to meet the analytic needs of the benefits analysis for the 316(b) regulation. For further discussion of the level of precision required by this analysis, see Section 2(c)(I) below.

(III) Stratification Variables

The survey sample will be selected using a stratified selection process. For the selection of households, the population of households in th e contiguous 48 states wi ll be stratified by the geographic boundaries of 5 EPA st udy regions: California, Great La kes, Inland, Northeast, and Southeast. As described previously, the North east region includes the North Atlantic and Mid Atlantic 316(b) benefits regions and the Southeast region includes th e South Atlantic and Gulf of Mexico 316(b) benefits regions. The sample is allocated to each region in proportion to the total
number of households in that region with at least 288 persons in each region. This is the number required to estimate the main effects and intera ctions under an experimental design model as32 described in Section 4(a) of Part A. To accommod ate this requirement the sample sizes in other regions will be slightly reduced.

(IV) Sampling Method

Using the stratification design discussed above , respondents will be randomly selected. First, a larger sample of househol ds will be selected through random digit dialing in each of the 5 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 info rmation required by the survey. If the person in the household agrees, then a questionnaire wi ll be mailed to that
household. If it is assumed that 40% of the households which agreed to provide information actually return a completed mail survey (complet ion rate) then 5,000 questi onnaires will need to
be mailed to households. 2
If we assume that 60% of the households th at are called say “yes” they are willing to receive a questionnaire (the scr eening response rate), then we need to screen 8,333 households. A dual frame random digit dialing design, includ ing both landline and cell phone numbers, will be used for telephone screening. If we assume th at 40% of the households called will participate in the telephone screener, then we will need to call 20,833 numbers. The actual number of telephone number selected through random digit dial ing sampling will be larger than the number
of households called. This is because we ar e expecting that 40% of the telephone numbers initially selected will be scr eened out as non-working or busine ss numbers. Therefore the actual number of telephone numbers selected w ill be around 34,721. 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 total hous eholds in that region. For obtaining population-based estimates of various parameters, each responding household will be assigned a sampling weight. Th is weight combines a base sampling weight which is the inverse of the proba bility of selection of the house hold 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 popula tion participating in water-based recreation such as fishing and shellf ishing). Proportional allocation of the sample to regions ensures an equal probability sample. To estimate total WTP for the quantified

2 The assumed response rate is based on similar stat ed preference studies (e.g., Johnston et al. 2009).33 environmental benefits of the 316(b) existing facilities rulemaking da ta will be analyzed statistically using a standard ra ndom 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 AK and HI) and each of the 5 EPA study regions. A sample of 2,000 households (completed surveys) will provide estimates of population percentages with a margin of error no greater than +/- 2.2 percentage points at the 95% confidence level. The margin of error for the estimates at the regional level will range from 3.7 to 9.3 percen tage points at the 95% confidence level.

Table B1: Number of Househol ds and Household Sample for Each EPA Study Region

Region Household Population Household Sample
Northeast 18, 936,383 301

Southeast 39, 382,881 626

Great Lakes 29, 003,114 461

Inland 6,304,690 288

Pacific Mountain 20,370,838 324

All Regions 113,997,907 2,000

Source: The number of households in each region was obtained based on the estimated population size and average household size from the 2005-2007 American Community Survey (ACS).

(II) Non-Sampling Errors

One issue that may be encountered in stated preference surveys is th e problem of protest responses. Protest responses are responses from individuals who reject the survey format or34 question design, even though they may value the resources being considered (Mitchell and Carson 1989). For example, some respondents ma y feel that any amount of impingement and entrainment is unacceptable, and choose not to re spond to the survey. To deal with this issue, EPA has included several questions, including an open-ended comments 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 res earchers (e.g., Bateman et al. 2002) suggest that a choice experiment format, such as that proposed here, may ameliorate such

responses. A different type of non-sampling error is non- response bias. Non-response rates in this survey are affected by non-res ponse at each stage of sampling. There are two types of nonrespondents to this survey: res pondents 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 activities to minimi ze the potential for non-response bias in the current survey: (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 different times to maximize response. (2) The mail survey will be designed to maximi ze response. A mail survey will be sent to all those who agree to participate. Th en, one week later, a postcard reminder will be sent. Three weeks later, a second copy of the questionnaire 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 te lephone screener and mail survey. If any unexpected 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 correct the bias because of non-response.

Non-response Interviews To determine whether there is any eviden ce of significant non-re sponse bias in the completed sample, EPA will compare the charac teristics of the completed and non-completed35 cases from the random digit dialing sample. Th ere are two main stag es of non-response: nonresponse to the telephone survey a nd non-response to the mail survey. To assess the potential for telephone non-response bias, EPA will collect sample characteristics in the course of the telephone su rvey as follows: (1) prio r to household contact, (2) at respondent selection for the survey, and (3 ) after beginning the interview. EPA will then analyze the data available for re spondents and non-respondents prio r to household contact and at respondent selection. Because the telephone instrument is very short, we do not expect many people prematurely terminating the call after the selected hou sehold member has started the
interview. The drawn sample of random digit dialing numbers from the landline frame that are released to telephone interviewers for contact attempts can be coded for certain contextual
characteristics. The “hundreds bank” fr om which the RDD number is drawn (e.g., 301-608- 38xx) is classified geographically according to the unit from which the majority of listed numbers in that bank are located. This permits us to classify all of the numbers drawn by EPA region, State, and urbanicity (cen tral city, metro remainder, and non-metropolitan area). It also permits us to classify those numbers by demogr aphic 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 resident ial numbers in which an interview had not been completed with those that had been completed using these variables to determine whether nonresponse 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 one eligible respondent per household, then a
random selection is done for the individual with th e most recent/next birthday. EPA will identify the age and gender of this indi vidual if callbacks are necessa ry. This information permits additional comparisons of any differences in the age and gender of respondents in the completed sample and those in the non-completed sample after household contact an d respondent selection
have been made. The telephone screener include s not only an invitation to participate in the mail survey, but also some attitudinal (relative importance of various government activities) differences and behavioral differences (recreati onal activities), as well as demographic characteristics (see Attachment 5 for detail). EPA will use the telephone screening data to compare mail survey respondents and non-respondents. The items of info rmation collected during telephone screening36 will help determine the type of pe rson that is likely to not respond to the survey and may help in forming weighting classes for adjusting weight s of respondents to account for non-response and
minimize the bias becau se of non-response.

2(d) Questionnaire Design

The information requested by the survey is disc ussed in Section 4(b)(I) of Part A of the supporting statement. The full text of the draft questionnaire is provided in Attachment 1. The following bullets discuss EPA’s reasons fo r including the questi ons in the survey:

 Relative Importance of Issues Associ ated with Industrial Cooling Water . EPA included this section to prepar e respondents to answer the st ated preference questions by 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 motivati ng respondents to thi nk about the relative importance of different policy issues.

 Relative 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 evaluating policy options and by encouraging respondents to re-read previous pages fo r reminders if necessary.

 Voting for Regulations to Prevent Fish Losses in the Respondent’s Region. The questions in this section ar e the key part of the surve y. Respondents’ choices when presented with specific fish-related resour ce changes within thei r region and household
cost increases are the main data that a llow estimation of will ingness-to-pay. The questions are presented in a choice experiment (A , B, or neither) format because this is an
elicitation format that has been successfu lly 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; Opaluch et al. 1993). Furthermore, many focus group participants indicated that they have some prev ious 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.37  Reasons for Voting “No Policy”. These questions provide information that will be used by EPA to identify protest responses.

 Voting for Regulations to Prevent Fish Losses in the Entire United States. This section is a key part of the survey. It uses a format consistent with the region-specific choice questions described above , however it asks respondents to value policies affecting the entire U.S. This question is designed to capture potential differences in the value that respondents place on improvements within thei r region compared to improvements in
U.S. waters outside of their region. It also captures potentia l differences in respondents’ preferences for regional and national policies.

 Respondent Certainty and Reasons for Voting. This section is designed to identify respondents who incorrectly in terpreted the choice questi ons or the uncertainty of outcomes, Responses to these questions are important to successfully control for hypothetical bias.

 Recreational Experience. These questions elicit recreationa l experience data to test if certain respondent characteristic s influence responses to the referendum questions. These questions will also allow EPA to identify re source non-users, for purposes of estimating non-user WTP (to gauge the relative importance of non-use values to overall benefits).

 Demographics. Responses to these questions will be used to estimate the influence of demographic variables on respondents’ vot ing choices, and ultimately, their WTP to prevent I&E 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 prot est responses, i.e. responses from individuals who rejected the form at of the survey or the way the questions were phrased.

3. Pretests and Pilot Tests

EPA will conduct extensive pretests of the su rvey instrument during a set of 8 focus groups (EPA ICR # 2090-0028), in addition to th e twelve focus groups conducted for the Phase III survey. These focus groups will include in dividual cognitive interviews with survey respondents (Kaplowicz et al. 2004), and think-aloud or verbal prot ocol analyses (Schkade and38 Payne 1994). Individuals in these focus groups will complete draft survey questionnaires and provide comments and feedback about the survey fo rmat and content, their interpretations of the questions, and other issues rele vant to stated preference esti mation. Based on their responses, EPA will make improvements to the survey questi onnaire. Particular emphasis in these survey pretests will be on testing for the presence of potential biases associated with poorly-designed stated preference surveys, including hypothetical bias, strategi c bias, symbolic (warm glow) bias, framing effects, embedding biases, methodolog ical misspecification, a nd protest responses (Mitchell and Carson 1989). Focus groups and cogn itive interviews may lead to changes that
ameliorate and minimize these biases in the final survey instrument. Survey pretests may also demonstrate the ability of follow-up survey questi ons (i.e., after the primary choice questions) to clearly identify the respondents whose answers to the choice questions display the influence of bias, or do not understand the survey context or information.

4. Collection Methods and Follow-up 4(a) Collection Methods

The survey will be administered as a ma il survey. Respondents identified by random digit dialing who agree to participate will be mailed a copy of the survey questionnaire. Respondents will be asked to mail the completed survey back to EPA.

4(b) Survey Response and Follow-up

The target response rate for the mail survey is 40 percent. That is, 40 percent of households which agreed to participate in the ma il survey are expected to return a completed survey. However, the actual response rate co mpared to the general popul ation is lower, given that the telephone screening pro cess is expected to have a re sponse rate of 60 percent among
contacted households. The reso lution rate (determini ng the status of a telephone number), the screener response rate and the survey completion rate will contribute to the overall response rate in the survey. The actual number of telephone nu mbers selected for inclusion will be much larger to account for the exclusion of non- working and business numbers. The number of39 telephone 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 , all of these respondents wi ll receive a reminder postcard approximately one week after the initial questio nnaire 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 reminder 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 hous eholds in the contiguous 48 states will be stratified by th e geographic boundaries of 5 EPA st udy regions. We will keep track of the response rates by region to ensure that th e rates in each region are reasonable. We will
also look at the frame characteri stics of non-respondents to determ ine if there are any substantial
biases in the estimates because of an imbalance in the distribution of certain 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 ar e returned. After all resp onses have been entered,
the database contents will be converted into a fo rmat 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 co mpleteness. Additionall y, 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 preference theory, such as transitivity. Responses which satisfy transitivity exhibit rela tional relationships when separate choices among policy options are compared. For example, if values for policy A are greater than policy B, and values for policy B are greater than Policy C, then values for polic y A should also be greater than values for Policy C.40 5(b) Analysis

Once the survey data has been converted in to a data file, it will be analyzed using statistical analysis techniques. The following s ection discusses the model that will be used to analyze the stated preferen ce data from the survey.

Analysis of Stated Preference Data The model for analysis of stated prefer ence data is grounded in the standard random utility model of Hanemann (1984) and McConnell (1990). This model is applied extensively within stated preference research, and allows we ll-defined welfare measures (i.e., willingness to pay) to be derived from choice experiment mode ls (Bennett and Blamey 2001; Louviere et al. 2000). Within the standard random utility mode l applied to choice expe riments, 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 wellbeing. 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 entrainment and impingement (I&E) losses, EPA defi nes a standard utility function U i (

. ) that includes
environmental attributes of an I& E reduction plan and the net cost of the plan to the respondent. Following standard random utility theory, ut ility 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 describi ng 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 household under plan i ; v(

. ) = a function representing the empirical ly estimable component of utility;

ε i = stochastic or unobservable component of utility, modeled as an econometric error.41 Econometrically, a model of such a preferen ce function is obtained by methods designed for limited dependent variables, because resear chers only observe the respondent’s choice among alternative policy options, rath er than observing values of U i (.) directly (Maddala, 1983; Hanemann, 1984). Standard random utility mode ls are 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 res pondent’s choice set of potential policies also includes maintaining the status quo. The 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 pl an that would offer th e 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 other 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 estimate d as a conditional logit model, as detailed by Maddala (1983), Greene (2003) a nd 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, Neither Plan), and results in an econometric (empirical) estimate of the systematic component of utility v(

. ) , based on observed choices among different polic y plans. Based on this estimate, one may calculate welfare measures (w illingness to pay) following th e well-known methods of Hanemann (1984), as described by Freeman (2003) and othe rs. Following standard choice experiment methods (Adamowicz et al. 1998; Bennett and Bl amey 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 hi ghest utility as noted above. Following clear guidance from the literature, a “neither plan” or st atus quo option is always included in the visible choice set, to
ensure that WTP measures are we ll-defined (Louviere et al. 2000). EPA also anticipates that respondents will cons ider more than 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 valu ation surveys (Poe et al. 1997; Layton 2000). While responde nts will be instructed to c onsider each choice question as42 independent of other choice questions, it is nonethel ess standard practice with in the literature to allow for the potential of correlation among quest ions answered within a single survey by a single respondent. That is, res ponses provided by individual re spondents may be correlated even though responses across different respondents ar e considered independent and identically distributed (Poe et al. 1997; Layton 2000; Train 1998). There are a variety of approaches to such potential correlation. Following standard practice, EPA anticipates the estimation of a vari ety of models to assess their performance.
Models to be assessed include random effects and random parameters (mixed) discrete choice models, now common in the stated preference literature (Greene 2003; McFadden and Train 2000; Poe et al. 1997; Layton 2000). Within such m odels, selected elements of the coefficient vector are assumed normally distributed across re spondents, often with fr ee correlation 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 model 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 model performance of alternative specifications will be assessed by EPA using standard statistical
measures of model fit and c onvergence, as detailed by Greene (2002), Greene (2003), and Train (1998).

Advantages of Choice Experiments Choice experiments following the random utili ty model outlined above are favored by many researchers over other vari ants of stated preference me thodology (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 choi ces over a wide array of potential policies, grounded in well-developed random utility theory, and the simila rity of the discrete choice context to familiar referendum or voting format s (Bennett and Blamey 2001). Compared to other types of stated preferen ce 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 symbo lic biases (Blamey et al. 1999; Mitchell and43 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 responde nt wishing to express solely symbolic
environmental motivations. For similar reasons choice experiments ma y ameliorate protest responses (Bateman et al. 2002). An additional advantage of such methods is that they permit straightforward assessments of the impact of res ource scope and scale on respondents’ choices. This will enable EPA to easily conduct scope te sts and other assessments of the validity of survey responses (Bateman et al. 2002, p. 296-342). Finally, such methods are well-established in the stated preference litera ture (Bennett and Blamey 2001). Additional details of choice experiment methodology (also called choice m odeling) are provided by Bennett and Blamey (2001), Adamowicz et al. (1998), Louvi ere 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 res ource improvements of a type quite similar to those at issue in the 316(b) policy case. Exampl es of the application of choice experiments to estimate WTP associated with changes in aquati c life and habitat include Hoehn et al. (2004), Johnston et al. (2002b), and Opal uch et al. (1999), among others. EPA has drawn upon these and other examples of successful choice experiment de sign to provide a basis for survey design in the present case. A final key advantage of choice experiments in the present applicati on is the ability to estimate respondents WTP for a wide range of di fferent potential outcomes of 316(b) policies, differentiated by their attributes. The proposed choice experiment survey versions will allow different respondents to choose am ong a wide variety of hypothetical policy options, some with larger and other with very small changes in the pr esented attributes (annual fish losses, long-term fish populations, recreational and commercial catc h, ecosystem condition, and household cost). That is, because the survey is to be implement ed as a choice experiment survey, levels of
attributes in choice scenario s will vary across respondent s (Louviere et al. 2000). The experimental design will also ex plicitly 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 uncerta inty involved in the 316(b) policy case, the ability to estimate values for a wide range of potential outcomes is critical.44 The ability to estimate WTP for a wide ra nge of different policy outcomes is a fundamental property of the choice experiment method (Bateman et al . 2002; Louviere et al. 2000; Adamowicz et al. 1998). EPA emphasizes that the survey version included in this ICR is for illustration only; it is but one of what will ultimately be a large number of survey versions covering a wide range of potentia l policy outcomes as described in Attachment 3. For the purpose of the stated preference survey implementation, EPA will use five geographic regions: California, Great Lakes, Inland, Northeast, and Sout heast. The survey vers ion included in this ICR is for the Northeast region. The experiment al design (see below) will allow for survey versions showing a range of different baseline and resource improvement levels, where these levels are chosen to (almost cer tainly) bound the “actual” levels. Given that there will almost certainly be some biological uncertainty regard ing the specifics of the “actual” baselines and improvements, the resulting valuation estimates will allow flexibility in estimating WTP for a wide range of different circumstances. Additiona l 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 will be subjected to exte nsive development and pretesting in focus groups to ameliorate the potential for survey biases (cf. Mitchell and Carson 1989), and to ensure that respondents have a clear understand ing of the policies and goods under consideration, such that informed choices may be made that reflect resp ondents’ underlying prefer ences. Following the guidance of Arrow et al. (1993) , Johnston et al. (1995), and M itchell and Carson (1989), focus groups will be used to ensure that respondents ar e aware of their budget cons traints, the scope of the resource changes under consideration, and th e availability of substitute environmental

resources. As noted above, survey pretests will also in clude individual cognitive interviews with survey respondents (Kaplowicz et al. 2004), and think-aloud or verbal protocol analyses (Schkade and Payne 1994). Individuals in th ese pretests will comp lete draft survey questionnaires and provided comments and feedback about the survey format and content, their interpretations of the questions, and other issues relevant to st ated preference estimation. Based45 on their responses, EPA will make improvements to the survey questionnaire. Of particular emphasis in these survey pretests is testi ng for the presence of pot ential biases including hypothetical bias, strategic bias, symbolic (warm glow) bias, framing effects, embedding biases, methodological misspecification, and protest re sponses (Mitchell and Carson 1989). Focus groups and cognitive interviews may lead to change s to ameliorate and minimize these biases in the final survey instrument and introductory ma terials if necessary. Re sults from focus groups and cognitive interviews used to test the final su rvey version will provide evidence as to whether respondents answer the stated preference survey in ways appropriate for stated preference WTP estimation, and that their responses do not refl ect the biases noted above. Moreover, survey pretests can demonstrate the abil ity of follow-up survey questions (i.e., after the primary choice questions) to clearly identify th e respondents whose answers to th e choice questions display the influence of bias, or do not understand the survey context or information. The number of focus groups used in survey design (8, excluding the 12 focus groups conducted for the Phase III survey) exceeds the number of focus groups used in typical applications of stated pref erence valuation. Moreover, EPA will incorporate cognitive interviews as detailed by Kaplowi cz et al. (2004). We note that th e current survey instrument is built upon an earlier version that was peer re viewed in January 2006 and it incorporates recommendations received from that peer review panel. Given this extensive effort in survey design—applying the most state-of-t he-art methods available in th e literature—EPA believes that survey design far exceeds standards that are typi cal in the published literature. The details of focus groups to be used in the survey’s de sign are discussed by EPA in a prior ICR (#2155.01).

Econometric Specification Based on prior focus groups, expert revi ew, 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 unavoidable household cost F i . 3 These attributes w ill characterize the annual reduction in I&E losses ( x 1 ), anticipated long-term ef fects on fish populations ( x 2 ), anticipated long-term effects on recreational and commercial harvest ( x 3 ), and anticipated impacts on aquatic

3 EPA plans to complete focus group testing of the instru ment 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, and if cognitive issues are minimal as identified by randomly selected focus group participants, all four will remain.46 ecosystem condition ( x 4 ). These variables will allow respondent s’ choices to reveal the potential impact of both annual fish losses and long-term p opulation effects on utility. Based on results of prior focus groups and expert opinion, these wi ll be presented as aver ages 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. Although the literature offers no firm guidan ce regarding 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 a pplying more flexible (e.g., quadratic) forms (Cummings et al. 1994). Standa rd 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 compar ed. Anticipated extensions to the simple linear model include more fully-flexible forms that allow for systematic variations in slope and intercept coefficients associated with demograp hic or other attributes of respondents. Such variations may be incorporat ed by appending the simple linea r specification with quadratic
interactions between variables in vector D and the variables X i and F i (cf. Johnston et al. 2003b). One may also incorporate quadratic in teractions between policy attributes X i and F i , (cf. Johnston et al. 2002b). Such quadr atic extensions of the basic linear model allow for additional flexibility in modeling the relationship between po licy attributes (including cost) and utility, as suggested by Hoehn (1991) and Cummings et al. (1994). EPA anticipates estimating both simple linear specifications, as well as more fully-f lexible 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 estimating all models within the mixed logit framework outlined above. Model fit will be assessed following standard practice in the literature (e .g., Greene 2003; Maddala 1983). Lin ear 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, Cumm ings 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 Neither, where “neither” is characterized by 0 values for all attributes (except Baseline population levels). Assuming that the model is es timated using a standard approximation for the observable component of utility, an econometric specification of the desired model (within the overall multinomial logit model) might appear as:47 v(

 ) =  0 +  1 (Fish Saved) +  2 (Population Change) +  3 (Change in Commercial Sustainability) +  4 (Change in Condition of Aquatic Ecosystem) +  5 (Cost) +  6 (Fish Saved)(Baseline) +  7 (Population Change)(Baseline) +  8 (Change in Commercial Sustainability)(Baseline) +  9 (Change in Aquatic Ecosystem)(Baseline) +  10 (Cost)(Baseline) + 

11 (Fish Saved)(Population Change) +  12 (Fish Saved)(Change in Commercial Sustainability) + 

13 (Fish Saved)(Change in Aquatic Ecosystem) +  14 (Population Change)(Change in Commercial Sustainability) +  15 (Population Change)(Change in Aquatic Ecosystem) + 

16 (Change in Commercial Sustainability)(Change in Aquatic Ecosystem)

Main effects are in bold. Inter actions are in italics. This sa mple specification—one of many to be estimated by EPA—allows one to estimate the relative “main effects” of policy attributes (annual reduction in I&E losses, long-term effects on fish popul ations, long-term effects on recreational and commercial harvest) on utilit y, effects on aquatic ecosystem condition, as well
as interactions between these main effects. This specification also allows EPA to assess the impact of baseline fish populations on the margin al 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-range of main effects and interactions within the utility function of respondents. Such flexib le utility specifications for stated preference estimation are recommended by numerous sources in the literature, in cluding Johnston et al. (2002b), Hoehn (1991), and Cummi ngs et al. (1994), and follow standard practice in choice modeling outlined by Louviere et al. (2000) and others.

Experimental Design Experimental design for the choice experiment surveys will follow established practices. Fractional factorial design will be used to constr uct choice questions with an orthogonal array of attribute levels, with questions randomly divided among distinct surv ey versions (Louviere et al. 2000). Based on standard choice experiment expe rimental design proced ures (Louviere 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 experime ntal design and complexity of questions, b) the
extent to which estimation of interactions and higher-level effects is de sired, and c) pretests revealing the number of choice experiment questi ons that respondents are willing/able to answer in a single survey session, and the number of at tributes that may be varied within each question while maintaining respondents’ ability to ma ke appropriate neoclassical tradeoffs.48 Based on the models proposed above and recommendations in the literature, EPA anticipates an experimental design that allows fo r an ability to estimate main effects, quadratic effects, and two-way interactions between polic y 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 scenar ios that “span the range over which we expect respondents to have preferences, and/or are practically achieva ble” (Bateman et al. 2002, p. 259), following guidance in the literature. This incl udes guidance with rega rd to the statistical implications of choice set desi gn (Hanemann and Kanninen 1999) and the role of focus groups in developing appropriate choice se ts (Bennett and Blamey 2001). Based on these guiding principles, the follo wing experimental design framework is proposed by EPA. The experimental design wi ll be conducted by Abt Associates Inc. The experimental design will allow for both main effect s and selected interacti ons to be efficiently estimated, based on a choice experiment framewor k. For a more detailed discussion of the experimental design, refe r to Attachment 3. Each treatment (survey question) includes tw o choice Options (A and B), characterized by four attributes and a cost variable that vary across the two choice options (Fish Saved, Commercial Fish Sustainability, Fish Popul ation, Condition of Aquatic Ecosystems, and Household Cost). Hence, there are a total of ten attributes fo r each treatment. Based on focus groups and pretests, and guided by realistic ranges of attribute outcomes, EPA allows for three different potential levels for Fi sh Saved, Commercial Fish Sust ainability, Fish Population, and Condition of Aquatic Ecosystems, and allows for si x different levels of monthly Household Cost for both regional and national choice questions. Su rvey questions also include two treatments of location, or geographic scope; the first refers to policies only w ithin the respondent’s region and the second refers to national policies.
The number of combinations for each attr ibute may be summarized as follows:

 Location A , Location B (2 levels)  Fish Saved A , Fish Saved B (3 levels)  Commercial Fish Sustainability A , Commercial Fish Sustainability B (3 levels)  Fish Population A , Fish Population 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 attribut e including a household cost of $0.49 Following standard practice, EPA constrai ned the design somewhat in response to findings in prior focus groups conducted for the ph ase III survey and the prior literature. For example, prior focus groups showed that res pondents react negatively and often protest when offered choices in which one op tion dominates the other in all attributes. Given that such choices provide negligible st atistical information compared to choices involving nondominant/dominated pairs, they are typically a voided in choice experiment statistical designs. For example, Hensher and Barnard (1990) reco mmend eliminating profiles including dominating or dominated profiles, because such profiles ge nerally provide no useful information. Following this guidance, EPA constrained the design to el iminate such dominant/dominating pairs. EPA also constrained the design to el iminate the possibility of pair s in which, when looking across two options, one of the options offers both a gr eater reduction in fish losses and a smaller increase in 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 char acterized by 72 unique A vs. B option pairs, where attribute levels for option A and B differ acro ss 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 surv eys, these questions wi ll be randomly assigned to survey respondents, with each resp ondent considering three questions.

Information Provision According to Arrow et al. (1993, p. 4605), “[i]f CV surveys are to elicit useful information about willingness to pay, respondent s must understand exactly what it is they are being asked to value.” It is also well known that the provide d information can influence WTP estimates derived from stated preference surv ey 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. 1989; Hoehn and Randall 2002). As stated clearly by Bateman et al. (2002, p. 122), “[d]escribi ng the good and the policy context of interest may require a combination of textual inform ation, 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 losses and potential impacts50 on aquatic life, the survey will include introductory figures to aid respondents’ comprehension of the goods and policies addressed by the survey instrument, a nd 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. (2002a ), among others, EPA extensively pretested, during the Phase III focus groups, all graphics used in the draf t mail survey, to ensure that these graphical elements were not prejudicial, and that they di d not bias responses. Graphics judged to be prejudicial based on the next round of eight fo cus groups and/or cognitiv e interviews will be removed and replaced. EPA acknowledges that certa in types of graphics can be prejudicial in certain contexts—and hence will pretest all graphi cal elements extensively. However, 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 comp onents of survey instruments in many cases (Bateman et al. 2002). EPA highlights that num erous peer-reviewed surveys described in the literature include pictures and gr aphics both in survey instrument s and in introductory materials such as slide shows. For example, see Horn e et al. (2005), Ready et al. (1995), Powe and Bateman (2004) and Duke and Ilvento (2004), Opaluch et al. (1993), Johnston et al. (1999, 2002a, 2002b), and Mazzotta et al. (2002). Batema n et al. (2002) also includes examples of various types of survey materials includi ng pictures and graphical elements.

Amelioration of Hypothetical Bias EPA considers the amelioration of hypothetical bi as to be a paramount concern in survey design. However, the agency acknowledges—ba sed on prior evidence fro m the literature—that hypothetical bias is not unavoidable. For ex ample, not all research finds evidence of hypothetical bias in stated preference valuat ion (Champ and Bishop 2001; Smith and Mansfield 1998; Vossler and Kerkvliet 2003; Johannesson 1997), and some s hows that hypothetical bias may be ameliorated using cheap-talk, certainty ad justments, or other mechanisms (Champ et al. 1997; Champ et al. 2004; Cummings and Ta ylor 1999; Loomis et al. 1996). To obtain reliable estimates of WTP, the Agen cy will test and design all survey elements to promote incentive compatible preference elicit ation mechanisms. Incentive compatible stated preference surveys provide no incentive for non- truthful preference re velation (Carson and Groves 2007). The literature is clear regarding the importance of in centive compatibility in stated51 preference value elicitation and the role of both question 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 preference choices are incentive compatible given that certain conditions are met, including the condition that responses are believed by re spondents to be consequential, or potentially influencing public policy decisions (Carson an d Groves 2007; Herriges et al. 2010). The survey is explicitly designed to empha size the importance of the budget constraint and program cost. For example, the survey re minds respondents of other policy issues (e.g., improving public safety, protecting air quality) fo r which the government could potentially ask households to pay costs. The survey itself includ es explicit reminders of program cost and the budget constraint. The survey has also been explicitly designe d to maximize the consequentiality of choice experiment questions, thereby maximizing incentiv e compatibility (i.e., reducing strategic and hypothetical biases), following cl ear guidance of Carson et al. (2000). Elements specifically designed to maximize consequentiality include a] explicitly mentioning that this survey is associated with assessment of proposed policies th at are being considered , b] numerous details provided in the survey concerning specifics of the propos ed policies, and c] emphasis that the type of policy enacted will depend in part on survey results and th at 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 w ill provide information as to whether respondents viewed choices as cons equential, 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. In previous fo cus groups conducted for the Phase III survey, when asked if they thought about the program co st in the same way as “money coming 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 statem ents such as “If this is just an exercise to see how I would react, I'd still answer the same as if the government really used it to create policy,” and “I would be very cert ain that I would answer in a r eal referendum the way I did it
here.”52 EPA does not anticipate si gnificant hypothetical bias in the proposed survey, however hypothetical bias will be eval uated based on findings from the focus groups and cognitive
interviews and indications of c onsequentiality in the survey. Regarding the potential use of cheap talk mechanisms or other devices to furt her address the potential for hypothetical bias, the Agency emphasizes that the lite rature is mixed as to their pe rformance. 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 and Caplan (2003). However, other authors (e.g., Cummings et al. 1995 ; List 2001; Brown et al. 2003) fi nd that a cheap talk script is only effective under certain circumstances, and for certain types of respo ndents. For example, Cummings et al. (1995) find th at a relatively short cheap talk script actually worsens hypothetical bias, while a longer sc ript appears to ameliorate bi as. Brown et al. (2003) finds cheap talk only effective at higher bid amounts— a result mirrored by Murphy et al. (2004). Still
other authors find no effect of ch eap talk, including Poe et al. (2002). Given the clearly mixed experiences with such mechanisms, EPA is not c onvinced that cheap talk scripts are likely to provide a panacea for hypothetical bias in the pr esent case—although they appear to reduce bias
in a limited set of circumstances – and ch eap talk is not incl uded 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 valu e of the affected fish resources only, and do not reflect symbolic or warm gl ow concerns (Mitchell and Ca rson 1989). Focus groups and cognitive interviews will be used to determine whether respondents are aware of the ecological role of fish and ground their prefer ences in the role that fish play in larger aquatic ecosystems (e.g., as food for other organisms, etc.), as indi cated in previous focus groups for the Phase III survey. They will also be used to determine whether respondents answered questions based on the specific changes in resources described in the survey, and not based on symbolic concerns. 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 va riety of ways, based on prior examples in the literature, such as asking respondents to refl ect on importance of attributes before making53 selections, and using a payment vehicle that doesn ’t raise trust issues (cost of living increase
rather than an electr ic bill increase). The survey includes clear language to instru ct respondents only to consider the specific attributes in the survey, and not to base answ ers on broader environm ental concerns including
the statement that: “Scientists expect that effects on the e nvironment and economy not shown explicity will be small.“ Focus groups will be used to determine whether survey responses reflect symbolic or warm-glow
concerns. This is also consistent with the stat ement from Arrow et al. (1993) that a referendumtype format may limit the warm-glow effect. Fo r example, one participant in a previous focus group stated, “You know, if you were telling me you were saving spiders, who cares? You know what I mean? So, it is not just to do the right thing. I think that fish are important.” Another participant stated, “No, I don't have any specific fi sh in mind. I think every fish will be equally important for one thing or another, whether it's for food or I guess some fish are food for other fish. Or even just to enjoy, you know. They ha ve a right to live like anything else, you know?” This evidence notwithstanding, EPA believes th at it is important to include follow-up questions to ensure that respons es do not reflect symbolic biases. Question 10 in the survey
instrument—which addresses the rationale for choice responses given earlier in the draft survey—explicitly tests for the presence of symbolic or warm-glow biases. Follow-up questions such as these are common in stated preference survey instruments, to assess the underlying
reasons for the observed valuation re sponses (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 CV surveys are to elicit useful information about willingness to pay, respondents must understand exactly what it is they are being as ked to value (or vote upon)...” They further indicate that surveys providing “s ketchy details” about th e results of proposed policies call “into question the estimates derived there from,” and hence suggest a high degree of
detail and richness in the descri ptions of scenarios. Similar guidance is provided by other key sources in the CV literature (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.54 Following Arrow et al. (1993), Mitchell and Carson (1989), and others, while noting the clear limitations in scope tests discussed by Hebe rlein 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 experiment me thodology, which is better able to capture WTP differentials related to change s in resource scope (Bateman et al. 2002). Unlike open-ended questions, in which scope inse nsitivity is a primary concern, EPA emphasizes that choice experiments generally have shown much less di fficulty 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 automatica lly available from the results of a [choice modeling] exercise.” That is, within choice ex periments, sensitivity to scope is indicated by the statistical significance and sign of parameter es timates associated with program attributes (Bennett and Blamey 2001). Internal scope sensi tivity will therefore be assessed through model results for the variables Fish Saved, Commerci al Fish Sustainabilit y, Fish Population, and Condition of Aquatic Ecosystems. Statistical significance of these variables—along with a positive sign—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 (cf. Giraud et al. 1999). The primary difference
between internal and external tests is that the fo rmer assess sensitivity to scope across choices of a single respondent, while the la tter involves split-sample assessments across different respondents. Within a choice m odeling context, external scope tests are generally considered “stronger,” although also more likely to be c onfounded by differences in the implied choice frame (Bennett and Blamey 2001). A variety of op tions for external scope tests exist, depending
on the structure of the stated choi ce questions under consideration. In the present case, attribute-by-attribute ex ternal scope tests will be conducted over a split sub-sample of respondents considering a speci fic set of choices, with all held constant across the considered choices except the scope of the attribute for which the test is to be conducted. For example, to conduct an external sc ope test for reductions in annual fish losses,
one would consider a set of choi ces that is identical over two respondent groups, except that one considers a choice with a greater reduction in fish losses. Asse ssing the choices over this split sample allows for an external test of scope. To i llustrate this test, consider the following stylized55 choice between Option 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 Sustainability Commercial Fish Sustainability Level 0 Commercial Fish Sustainability Level 0
Fish Populations Population Level 0 Population Level 0
Condition of Aquatic Ecosystems 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 and Co st vary across the choice options. Because both Fish Saved (at Level 1 and Level 2) and Co st are higher in Option A than in Option B, neither option is dominant. In the illustrated split-sample test, respondent sample 1 views the choice with Fish Saved at Level 1, while res pondent sample 2 views an otherwise identical choice with Fish Saved at Level 2, where Level 2 > Level 1. If responses are externally sensitive to scope in Fish Saved, th is 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 th e two sub-samples, and provides a simple attribute-by-attribute test of external scope. Analogous tests may be conducted for all attribut es within the choice experiment design, using parallel methods. EPA em phasizes that the formal applicability of the above-noted scope test is con tingent upon the specific choice fr ame implied by levels of other attributes in the choice question. This is a characte ristic of nearly all exte rnal scope tests applied in choice experiment frameworks (Bennett and Blamey 2001). Split-sample tests such as those proposed above often require the addition of question versions to the experimental design, to accomm odate the specific structural needs of the attribute-by-attribute external scope test. Otherwise, conf ounding effects of other varying attributes (including demographi c information) can render results of scope tests ambiguous. In56 the present case, the proposed tests would re quire the addition of up to six unique question versions to the experimental de sign, enabling scope tests for the th ree non-cost attributes within the 316(b) choice experiment scenarios. If scope tests in additional quest ion frames are desired (e.g., the same scope test illustrated above, but gi ven Level 1 for commercial fish sustainability, fish population, and aquatic ecosystem condition at tributes), still additional question versions would be added. While small numbers of quest ions added to the expe rimental design should have minimal impacts on overall efficiency (e .g., orthogonality of the design), larger numbers may have a more significant impact. Hence, gi ven constraints on the total number of survey respondents, there is a po tential empirical tradeoff between th e number of external scope tests that may be conducted and the efficiency of th e experimental design a nd statistical analysis.

Communicating Uncertainty to Respondents
EPA believes that the role of risk and uncertain ty is an important issue to be addressed in the development of benefits estimates, and poi nts out that the literature provides numerous examples of cases in which appropriate surv ey 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 acti ons might change it... Using focus groups helped make this determination...” EPA also em phasizes that all regul atory analyses involve uncertainty of some type (Boardman et al. 2001). The ecological outcome of I&E reductions is subject to c onsiderable uncertainty. EPA believes that it is important that survey respondent s be aware of this uncer tainty, and that their responses reflect the knowledge th at 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; Louvi ere et al. 2000) to avoid c ognitive burden on respondents. Hence, the proposed survey materials clearly indi cate the uncertainty involved with the described resource changes in choice modeling scenario s, yet do so in a way designed to minimize cognitive burden. For example, prior to answering choice e xperiment questions, respondents are told: “Scientists know that about 1.1 billion young fish are lost per year [name of region] coastal waters due to cooling water use. But, scientists do not know the total number of fish in [name of region] coastal waters.”57 “Even though scientists can pr edict approximately the number of fish that will be saved, the ultimate effects on fish populations (the numbe r of fish in the water) is uncertain.” These statements clearly indicate the uncertain ty involved with scientific estimates of the outcomes of I&E regulations. This is follo wed by a further reminder of uncertainty: “Policy costs and effects depend on many factors. Saving more fish does not necessarily mean that effects will improve.” Focus groups and cognitive interviews will be used to indicate whether repondents understood that the numbers provided in th e survey were scientific estimat es subject to uncertainty, and answered choice questions accordingly. Respondents in previous focus groups conducted for the Phase III survey were comfortable making decisi ons in the presence of this uncertainty. For example, one respondent stated, “...we know that fish populations are declining and so these are all estimates. And I accept them as estimates.” Other respondents made statements such as: “If they had stated figures as though these figures ar e it—that I would question,” and “I'll take that the estimate comes with some degree of scientif ic knowledge behind it. More than throwing a dart, but accept it for what it was.”

EPA also tested alternative versions of the Phase III survey instrument in which choice experiment attributes were presented as 90% conf idence ranges, rather than as point estimates. Focus group respondents were explicitly asked wh ether the ranges were helpful in understanding the uncertainty of estimates presented in the ch oice question or whether they were a source of confusion. Seven out of the eigh t respondents interviewed on that occasion indicated that the use of ranges was more confusing than the use of poi nt estimates, Furthermore, respondents were comfortable making decisions in the presence of this uncertainty.

5(c) Reporting Results

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 for the survey data, extensive documentation for the stat istical analysis, and a de tailed description of the final results. The survey data will be re leased only after it has been thoroughly vetted to ensure that all potentially identi fying information has been removed.58 REFERENCES

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# Fish and Aquatic Habitat

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

DRAFT FOR PRETESTING ONLY Do not quote or cite

Thank you for helping us to test an d develop this im portant survey!70 

# HUMAN ACTIVITIES, AQUATIC HABITAT AND FISH

This survey asks for your opinions regarding policies that would a ffect fish and habitat in the Northeast US. This section prov ides important background information.

Northeast fresh and salt waters support billio ns of fish. These include fish that are used by humans, as well as forage fish that are not used by humans. Natural factors such as weather have always influenced fish habit at, but in recent years human activities have had an increasing effect.

This survey concerns proposed polici es that would reduce fi sh losses caused by cooling water use by industrial facilities, including factories and power plants. Activities that affect fish include fishing, pollution, commercial and residential development, and the ex traction 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.71 

# HOW DOES COOLING WATER AFFECT FISH?

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

How Cooling Water Use Affects Fish

Cooling water use affects fresh and salt waters throughout the Northeast US, but almost all fish losses are in salt waters such as coastal bays. The equipment that pumps the cooling water kills small fish and fish eggs.

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.72 

# WHAT KINDS OF FISH ARE AFFECTED?

Question 1. When thinking about how industrial fa cilities use cooli ng 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. Allowing facilities to produce products and services at low cost 1 2 3 4 5


### 5. Reducing government regulations on facilities 1 2 3 4 5 

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

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

The other 2/3 of the fish lost are species not caught by humans but are part of the food web. Examples include killifish, silverside, and stickleback.73 

# HOW MANY FISH ARE AFFECTED? A NORTHEAST COASTAL EXAMPLE

SCIENTISTS KNOW THAT about 1.1 billion young fish are lost per year in Northeast coastal waters due to cooling water use. But, scientists do not know the total number of fish in Northeast coastal waters.

Studies of specific fish can provide some information on how many fish are lost, compared to the total number of fish in the water.

 Sometimes the number of young fish lo st is relatively small compared to the total number of adult fish—an exam ple is striped bass (see graph below).

 Sometimes the number of young fish lost is relatively large compared to the total number of adult fish—an example is winter flounder (see graph below).

 For many types of fish, the number of young fish lost compared to the total number of adult fish lies somew here in between these extremes.

 Even though scientists can predict approxim ately the number of fish that will be saved, the ultimate effects on fish popul ations (the number of fish in the water) is uncertain.

Total Number of Adult Striped Bass 24 million Total Number of Adult Winter Flounder 18 million

Young Fish Lost in

Cooling Water Intakes <0.2 million Young Fish Lost in Cooling Water Intakes 7.5 million



### 0 5,000,000 10,000,000 15,000,000 20,000,000 25,000,000

Striped Bass Winter Flounder74 

# NEW REGULATIONS ARE BEING PROPOSED TO PROTECT FISH

Current Situation

1.1 Billion Fish Lost

With Advanced Filters

0.8 Billion Fish Lost 0.3 Billion Fish Saved per Year

With Closed Cycle Cooling

<0.1 Billion Fish Lost >1.0 Billion Fish Saved per Year



### Advanced filters and closed cycle cooling a re already in use at m any facilities and are proven technologies. There are options bei ng considered by the government that would require these types of equipment at all facilities.
While these policies would reduce fish losses, they would also increase the costs of producing many goods and ser vices — these costs would be passed on to consumers like you. Under current regulations, about 1.1 billion fish are lost in coastal waters.
The government is considering policies that would require additional 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 cycle cooling that substantially reduces the need for outside cooling water. Requiring closed cycle cooling could reduce fish losses by 95%. However, costs are higher than for advanced filters.75 

# WOULD YOU VOTE FOR POLICIES TO HELP PROTECT FISH AND FISH HABITAT?

The government needs to know whether ho useholds are willing to pay the costs required to reduce fish losses and related ecological effects. This survey will help the government decide which policie s will be enacted, if any.

Question 2. Indicate the importance of the follo wing issues to you. Check one box for each.

Not Important Somewhat Important Very Important



### 1. Improving public safety 1 2 3 4 5 

### 2. Protecting air quality 1 2 3 4 5 

### 3. Reducing taxes 1 2 3 4 5 

### 4. Improving homeland security 1 2 3 4 5 

### 5. Protecting aquatic life and habitat 1 2 3 4 5 

### 6. Maintaining industry and jobs 1 2 3 4 5 

### 7. Reduce cost of living to households 1 2 3 4 5


### 8. Protecting water quality 1 2 3 4 576 

# THIS SURVEY IS SIMILAR TO A PUBLIC VOTE

This survey asks you to com pare policies with different effe cts on cooling water use, fish, and costs to your househol d. You will be asked to vote for the options you prefer. Effects of each project will be described using t he following scores :



# TWO SCORES SHOW EFFECTS ON FISH Effect of

Policy What It Means

Fish Saved

(per Year) 

### The reduction in the number of fish lost: 0 to 100 score showing the reduction in young fish lo sses because of the new policy. A score of 100 means that no fish are lost in coolin g water intakes (all fish are saved). A score of 0 represents the status quo.

Commercial Fish

Sustainability (Fish Used by People) 

### A score between 0 - 100 that shows effects on the su stainability of commercial fish. Higher scores mean that fishin g is more sustainable compared to fish population (see details on following pages). The 

### current score in the Nort heast US is 65.

Fish Population (All Fish) 

### A score between 0 - 100 that shows the size of all fish populations compared to the natural abundance without human influence. Higher scores mean more fish (see details on following pages)



### . The current score in Northeast coasta l waters is 37.

Condition of Aquatic Ecosystems 

### The effect on coastal ecos ystems and food webs: 0 to 100 score showing the ecological condition of affected areas, compared to the most natural waters in the Northeast. Higher scores mean that the area is more natural (see details on following pages). The current score in Northeast coastal waters is 48. 

# $ Cost per Year 

### How much the project will cost your household , in unavoidable price increases for products you buy.77 

## 1. Commercial Fish Sustainability Score

A score between 0 - 100 that shows effect s on the sustainability of commercial fish

. Higher scores mean that the ecosystem can maintain current fishing levels without compromising the ability of future gen erations to fish commercially.

A score of 100 means that scientists are fairly cert ain that all fish stocks are used sustainably (e.g., fishing is within biological limits).
The lowest score anywhere in the US is approximately 25 . A score this low means that ecosystems can not maintain fish populations for half of all species, and that scientists do not have reliable information on 4 out of every 10 species.

The current score in Northeast US waters is 65 4 

### — commercial fish sustainability is at 65% of maximum.


## 2. Fish Population Score

A score between 0 - 100 that shows the size of all fish populations compared to population sizes without human influenc e. Higher scores mean more fish.

A score of 100 means that populations are at the largest natural size possible in the ecosystem. This is the number of fish that existed before hum ans started fishing.

A score of 0 would mean that there are no fish at all.

The current score in Northeast US waters is 37 — current fish populations are at 37% of the size they would be wi thout human influence.

4 Technical Note : The scientific name for this score is the Fish St ock Sustainability Index (F SSI), calculated by the National Oceanic and Atmospheric Administration (NOAA). Th ree components combine to make the overall score: (1) the size of commercial fish populations compared to the most productive biological size; (2) how many fish are caught compared to sustainable levels; (3) whether scientis ts have good information regarding fish populations.78 

# THE AQUATIC ECOSYSTEMS SCORE

The Aquatic Ecosystems Score is a 0 - 100 score showing the effects of policies on the overall ecological condition of affected areas.

It measures how close affected Northeast wate rs are to the most natural, undisturbed condition that is possible. Higher sco res mean the area is more natural.

The following information is combined to make the final score:

Measurements Combined to Form the Aquatic

Ecosystems Score What Each Measure Means

Water Quality Score The score indicates whether the water is suitable for recreation and aquatic life. It is based on measures such as dissolved oxygen, nitrogen an d phosphorus pollution, water clarity, temperature and algae.

Benthic Score (bay, river or lake bottom) The health of species that live on the bottom (e.g., mussels, crayfish). Measures such things as the number of all species and presence of rare species.

Sediment Quality Score Based on the survival of bottom dwellers, level of sediment pollution and excessive organi c material on the bottom. Sediment quality will not be affected by the proposed programs.

Coastal Habitat Score Based on average hi storical changes of wetland areas compared to changes in recent years. Wetland areas will not be affected by the proposed programs.

Fish Tissue Contamination Contaminants measured in fish tissue are indicators of contaminants present in su rface waters. Fish tissue contamination will not be a ffected by the proposed programs.79 

# HOW WOULD YOU RATE THE IMPORTANCE OF THESE EFFECTS?

Question 3. When considering policies that affect how coastal facilities use cooling water, how important to you are effects on ea ch of the following scores? Check one box for each. (For reminders of w hat the scores mean, please see page 8).

Not Important Somewhat Important Very Important

1. Effect on fish losses prevented 1 2 3 4 5



### 2. Effect on commercial fish sustainability 1 2 3 4 5



### 3. Effect on the fish populations (for all fish) 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 a sk you to choose between differ ent policy options that would affect fish losses in cooling water systems.
You will be given choices and as ked to vote for the choice you prefer by checking the appropriate box. Questions will look simil ar to the sample on the next page.80 

# SAMPLE QUESTION Questions will look like the sample below

.
Policy Effect Current Situation

(No policy) 

## Option A Option B

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

# 0%
No change in status quo 

# 25%

0.3 billion fish saved 

# 50%

0.6 billion fish saved

Commercial Fish

Sustainability

(in 3-5 Years) 

# 65%

Out of 100% maximum 

# 67%

Out of 100% maximum 

# 69%

Out of 100% maximum

Fish Population (all fish) (in 3-5 Years) 

# 37%

Out of 100% maximum 

# 40%

Out of 100% maximum 

# 40%

Out of 100% maximum

Condition of Aquatic Ecosystems (in 3-5 Years) 

# 48%

Out of 100% maximum 

# 48%

Out of 100% maximum 

# 50%

Out of 100% maximum 

# $

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 POLICY I would vote for OPTION A I would vote for OPTION B

If you prefer Option A, check this box If you do not want A

or B, check this box If you prefer Option B, check this box 

# X X X81 

# AS YOU VOTE PLEASE REMEMBER

 The map below shows the coastal (salt water) facilities and areas that would be affected by the proposed policies.

 Depending on the policies chosen, cost s to your household could range from $0 per month to a maximum of $6 per month.

 Depending on the type of technology requi red 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 opt ions separately—do not add them up or compare programs from different pages.

 Scientists expect that effects on th e environment and economy not shown explicitly will be small.

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

Coastal Facilities Affected by the Proposed Policies Salt Water Facilities82 

## Question 4. Assume that Options A and B would require different technology to prevent fish losses in coastal facilities that use cooling water, and that all types of fish would be affected. How would you vote?

Policy Effect

NE Coastal Current Situation

(No policy) 

## Option A NE Coastal Option B NE Coastal

Fish Saved per Year

(Out of 1.1 billion fish lost in salt water intakes) 

# 0%
No change in status quo 

# 25%

0.3 billion fish saved 

# 50%

0.6 billion fish saved

Commercial Fish

Sustainability

(in 3-5 Years) 

# 65%

Out of 100% maximum 

# 65%

Out of 100% maximum 

# 65%

Out of 100% maximum

Fish Population (all fish) (in 3-5 Years) 

# 37%

Out of 100% maximum 

# 40%

Out of 100% maximum 

# 40%

Out of 100% maximum

Condition of Aquatic Ecosystems (in 3-5 Years) 

# 48%

Out of 100% maximum 

# 48%

Out of 100% maximum 

# 50%

Out of 100% maximum 

# $

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 POLICY I would vote for OPTION A I would vote for OPTION B83 

### Now you will be asked to consider a new set of po licy options for Northeast waters. As you vote, please remember—

 Questions 5 and 6 present a new set of policy options. These options require different technology 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 ac ross different questions.

 Policy costs and effect s depend on many factors . Saving more fish does not necessarily mean that al l effects will improve.84 

## Question 5. Assume that Options A and B would require different technology to prevent fish losses in coastal facilities that use cooling water, and that all types of fish would be affected. How would you vote?

Policy Effect

NE Coastal Current Situation

(No policy) 

## Option A NE Coastal Option B NE Coastal

Fish Saved per Year

(Out of 1.1 billion fish lost in salt water intakes) 

# 0%
No change in status quo 

# 25%

0.3 billion fish saved 

# 75%

0.8 billion fish saved

Commercial Fish

Sustainability

(in 3-5 Years) 

# 65%

Out of 100% maximum 

# 67%

Out of 100% maximum 

# 69%

Out of 100% maximum

Fish Population (all fish) (in 3-5 Years) 

# 37%

Out of 100% maximum 

# 37%

Out of 100% maximum 

# 42%

Out of 100% maximum

Condition of Aquatic Ecosystems (in 3-5 Years) 

# 48%

Out of 100% maximum 

# 48%

Out of 100% maximum 

# 52%

Out of 100% maximum 

# $

Increase in Cost of Living for Your Household 

# $0

No cost increase 

# $36

per year ($3 per month) 

# $40

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 B85 

## Question 6. Assume that Options A and B would require different technology to prevent fish losses in coastal facilities that use cooling water, and that all types of fish would be affected. How would you vote?

Policy Effect

NE Coastal Current Situation

(No policy) 

## Option A NE Coastal Option B NE Coastal

Fish Saved per Year

(Out of 1.1 billion fish lost in salt water intakes) 

# 0%
No change in status quo 

# 95%

1.0 billion fish saved 

# 50%

0.6 billion fish saved

Commercial Fish

Sustainability

(in 3-5 Years) 

# 65%

Out of 100% maximum 

# 72%

Out of 100% maximum 

# 72%

Out of 100% maximum

Fish Population (all fish) (in 3-5 Years) 

# 37%

Out of 100% maximum 

# 45%

Out of 100% maximum 

# 45%

Out of 100% maximum

Condition of Aquatic Ecosystems (in 3-5 Years) 

# 48%

Out of 100% maximum 

# 52%

Out of 100% maximum 

# 52%

Out of 100% maximum 

# $

Increase in Cost of Living for Your Household 

# $0

No cost increase 

# $72

per year ($6 per 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 B86 

### 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 vo ted 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 govern ment 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


# NATIONAL VERSUS NORTHEAST POLICIES
Now assume that the same types of policies were proposed for the entire United States instead of only the Northeast, and that affected facilities include all those shown on the map, including those in fresh and salt waters . How would you vote?87 

## Question 8. Now assume that the same types of policies were proposed for the entire United States . Assume that all US households would pay for these programs. How would you vote?

Policy Effect

ALL of US Current Situation

(No policy) 

## Option A ALL of US Option B ALL of US

Fish Saved per Year

(Out of 2.7 billion fish lost in salt water intakes) 

# 0%
No change in status quo 

# 25%

0.7 billion fish saved 

# 50%

1.4 billion fish saved

Commercial Fish

Sustainability

(in 3-5 Years) 

# 61%

Out of 100% maximum 

# 61%

Out of 100% maximum 

# 61%

Out of 100% maximum

Fish Population (all fish) (in 3-5 Years) 

# 42%

Out of 100% maximum 

# 42%

Out of 100% maximum 

# 44%

Out of 100% maximum

Condition of Aquatic Ecosystems (in 3-5 Years) 

# 46%

Out of 100% maximum 

# 46%

Out of 100% maximum 

# 48%

Out of 100% maximum 

# $

Increase in Cost of Living for Your Household 

# $0

No cost increase 

# $72

per year ($6 per month) 

# $120

per year ($10 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 B88 

### Question 9. Indicate how strongl y you agree with the following statements about questions 4 - 8 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 feel confident about my
answers 1 2 3 4 5



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



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



### Questions were easy to
answer 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 4 589 

### Question 10. How much did the following factors af fect your answers to questions 4 – 8? Check one box for each.
Effect on my answers to questions 4-8 

### 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 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


### Wanting 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 for government programs. 1 2 3 4 5 

### Wanting to increase 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 4 590 

### Question 11. How many days did you participate in the following during the last year? Please include activities in ALL LOCATIONS . Remember to count each day separately for trips longer than one day. Check one box for each.

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


### Question 12. How many days did you participate in each of the following activities during the last year, IN THE NORTHEAS TERN US ONLY ? Northeastern states include: CT, DE, MA, MD, ME, NH, NJ, NY , RI, VT. Remember to count each day separately for trips longer than one day.Check one box for each.

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 4 591 Scuba Diving / Snorkeling 1 2 3 4 5



### Question 13. For each of the following activities, i ndicate whether the activity is better or worse if there are more fi sh in the water. Check one box for each statement.
Activity is
worse if there are more fish Activity is not better or
worse if there are more fish Activity is better if there are more fish N/A I do not participate in this activity

Boating / Canoeing / Kayaking 1 2 3 4 Swimming / Going to the Beach 1 2 3 4 Recreational Fishing (Fresh Water) 1 2 3 4 Recreational Fishing (Salt Water) 1 2 3 4 Shellfishing / Crabbing 1 2 3 4 Scuba Diving / Snorkeling 1 2 3 492 

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

14. What is your age? ___ years
15. What is your gender?  Male  Female
16. What is the highest 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
16. How many people live in your household? _____________
17. How many of these people a re 16 years of age or older? ____
18. How many of these people are 6 years of age or younger? ____
19. What is your zip code?_____________________________
20. What town and state do you live in? Town: _____________ State:____
21. Are you currently employed? ___ Yes _____ No
22. What category comes clos est to your total household income? Less than $10,000 $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 

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

Thank you for your particip ation in this important survey!93 Attachment 2: Federal Register Notice

ENVIRONMENTAL PRO TECTION AGENCY
[EPA-HQ-OW-2010-0595; FRL_XXXX-X]
Agency Information Collection Activities; Proposed Collection; Comment Request; Willingness to Pay Survey for § 316(b) Existing Facilities C ooling Water Intake Structures (New), EPA ICR No. 2402.01, OMB Control No. 2040-NEW

AGENCY: Environmental Protection Agency (EPA).

ACTION: Notice.

SUMMARY: In compliance with the Paperwork Reduction Act (PRA) (44 U.S.C. 3501 et seq .),
this document announces that EPA is planning to submit a request for a new Information
Collection Request (ICR) to the Office of Mana gement and Budget (OMB). Before submitting
the ICR to OMB for review and approval, EPA is soliciting comments on specific aspects of the
proposed information collection as described below.

DATES: Comments must be submitted on or before [insert date 60 days after publication in the
Federal Register ].

ADDRESSES: Submit your comments, identified by Docket ID No. EPA-HQ-OW-2010-0595
by one of the following methods:

• www.regulations.gov: Follow the on-line instructions for submitting comments.

• Email: OW-Docket@epa.gov, Attention Do cket ID No. EPA-HQ-OW-2010-

059594 • Mail: Water Docket, Environmental Protection Agency, Mailcode: 28221T, 1200
Pennsylvania Ave., NW., Washington, DC 20460, Attention Docket ID No. EPAHQ-OW-2010-0595. Please include a total of 3 copies.

• Hand Delivery: Water Docket, EPA Dock et Center, EPA West, Room 3334, 1301
Constitution Ave., NW., Washington, DC, Attention Docket ID No. EPA-HQOW-2010-0595. Such deliveries are only accep ted during the Docket’s normal
hours of operation and special arrangements should be made.

Instructions: Direct your comments to Docket ID No. EPA-HQ-OW-2010-0595. EPA's policy

is that all comments received will be included in the public docket without change and may be

made available online at www.regulations.gov , including any personal information provided,

unless the comment includes information claimed to be Confidential Business Information (CBI)

or other information whose disclosure is restrict ed by statute. Do not submit information that you

consider to be CBI or othe rwise protected through www.re gulations.gov or e-mail. The
www.regulations.gov website is an “anonymous access” system, which means EPA will not
know your identity or contact in formation unless you provide it in the body of your comment. If
you send an e-mail comment directly to EP A without going through www.regulations.gov your
e-mail address will be automatically captured and in cluded as part of the comment that is placed
in the public docket and made av ailable on the Internet. If yo u submit an electronic comment,
EPA recommends that you include your name and other contact information in the body of your
comment and with any disk or CD-ROM you subm it. If EPA cannot read your comment due to
technical difficulties and cannot contact you for cl arification, EPA may not be able to consider
your comment. Electronic files should avoid the use of special characters, any form of
encryption, and be free of any def ects or viruses. For additional information about EPA’s public

docket visit the EPA Docket Center ho mepage at http://www.epa.gov/dockets.95 FOR FURTHER INFORMATION CONTACT: Erik Helm, Office of Water, Office of
Science and Technology, Engineering and Anal ysis 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
address: Helm.Erik@epa.gov.

SUPPLEMENTARY INFORMATION:

How Can I Access the Docket and/or Submit Comments?
EPA has established a public docket for this ICR under Docket ID No. EPA-HQ-OW2010-0595 which is available for online viewing at www.regulations.gov, or in person viewing at

the Water Docket in the EPA Docket Ce nter (EPA/DC), EPA West, Room 3334, 1301
Constitution Ave., NW, Washington, DC. The EP A/DC Public Reading Room is open from
8:30 a.m. to 4:30 p.m., Monday through Friday, ex cluding legal holidays. The telephone number
for the Reading Room is 202-566-1744, and the te lephone number for the 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 th e index listing of the contents of the docket, and to access
those documents in the public docket that are ava ilable electronically. Once in the system, select
“search,” then key in th e docket ID number identif ied in this document.

What Information is EPA Partic ularly Interested in?
Pursuant to section 3506(c)(2 )(A) of the PRA, EPA specifi cally solicits comments and

information to enable it to:
(i) evaluate whether the proposed collection of information is necessary for the proper
performance of the functions of the Agenc y, including whether the information will have
practical utility;96 (ii) evaluate the accuracy of the Agency 's estimate of the burden of the proposed
collection of information, including the valid ity of the methodology and assumptions used;
(iii) enhance the quality, utility, and clarity of the information to be collected; and
(iv) minimize the burden of the collection of information on those who are to respond,
including through the use of appropriate automated electr onic, mechanical, or other
technological collection techniques or other forms of information technology, e.g., permitting
electronic submission of responses . In particular, EPA is reques ting comments from very small
businesses (those that employ less than 25) on exam ples of specific additional efforts that EPA
could make to reduce the paperwork burden for very small businesses affected by this collection.

What Should I Consider when I Prepare My Comments for EPA?
You may find the following suggestions helpful for preparing your comments:
1. Explain your views as clearly as possible and provide specific examples.
2. Describe any assumptions that you used.
3. Provide copies of a ny technical information and/or data you used that support your

views.
4. If you estimate potential burden or co sts, explain how you arrive d at the estimate that
you provide.
5. Offer alternative ways to improve the collection activity.
6. Make sure to submit your comments by the deadline identified under DATES.
7. To ensure proper receipt by EPA, be su re to identify the docket ID number assigned to
this action in the subject line on the first page of your response. You may also provide the name,
date, and Federal Register citation.

What Information Collection Activi ty or ICR Does this Apply to?

Affected entities: Entities potentia lly affected by this action are individuals/households.97 Title: Willingness to Pay Survey for Section 316(b) Existing Facilities Cooling Water Intake
Structures: Instrument, Pr e-test, and Implementation (New)

ICR numbers: EPA ICR No. 2402.01, OMB C ontrol No. 2040-NEW.

ICR status: This ICR is for a new information collection activity. An Agency may not conduct
or sponsor, and a person is not required to re spond 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 appear ing in the Federal Register when approved, are
listed in 40 CFR part 9, are displayed either by p ublication in the Federa l Register or by other
appropriate means, such as on the related collect ion instrument or form, if applicable. The
display of OMB control numbers in certain EPA regulations is c onsolidated in 40 CFR part 9.

Abstract: Section 316(b) of the Clea n Water Act (CWA) requires EPA to ensure that the
location, design, construction, and cap acity of cooling water intake structures (CWIS) reflect the
best technology available (BTA) to protect aquatic organisms from being killed or injured by
impingement or entrainment. EP A divided this rulemaking into three phases. At question here

are the Phases II and III.
The Phase II rule, which covere d existing electric gene rating plants that withdraw at least
50 million gallons a day (MGD) of cooling wate r, was completed in July 2004. Industry and
environmental stakeholders challenged the Phas e II regulations. On judi cial review, the Second
Circuit remanded several key provisions. In July 2007, EPA suspended the Phase II Rule.
Following additional review in 2009 by the U.S. Supreme Court in Entergy Corp. v. Riverkeeper

Inc. , which decided that “EPA perm issibly relied on cost-benefit an alysis in setting the national
performance standards ... as part of the Phas e II regulations.” EPA has voluntary remanded the

rule.98 In June of 2006, EPA promulgated the 316(b) Ph ase III Rule for existing manufacturers,
small flow power plants (facil ities that withdraw less than 50 MGD), and new offshore oil and
gas facilities. Offshore oil and gas firms and envi ronmental groups petitioned for judicial review,
which was to occur in the Fifth Circuit, but wa s stayed pending the completion of the Phase II
litigation. EPA has asked the Fifth Circuit to re mand the existing faciliti es portion of the Phase
III rule so that it can consider what might be appropriate requirements for all existing facilities.
While the 5th Circuit has not yet issued a decision, EPA is anticipating combining Phases II and
III into one rulemaking covering all existing facilities.
Under Executive Order 12866, EPA is required to estimate the potential benefits and
costs to society of proposed rule options. To assess the public policy si gnificance or importance
of the ecological gains from the section 316(b) regulation for existing fa cilities, EPA requests
approval from the Office of Management and Bu dget to conduct a stated preference survey.
Data from the associated stated preference survey will be used to estimate values (willingness to
pay, or WTP) derived by households for changes re lated to the reduction of fish losses at CWIS,
and to provide information to assist in the in terpretation and validation of survey responses.
EPA has designed the survey to provide data to support the following speci fic objectives: [a] the
estimation of the total values (use plus non-us e) that individuals place on preventing losses of
fish and other aquatic organisms caused by 316( b) facilities; [b] to understand how much
individuals value preventing fish losses, increas ing fish populations, and increasing commercial
and recreational catch rates; [c] to understand ho w such values depend on the current baseline
level of fish populations and fish losses, the sc ope of the change in those measures, and the
certainty level of the predictions; and [d] to und erstand how such values vary with respect to

individuals’ economic and de mographic characteristics.99 The target population for this stated preference survey is a ll individuals from continental
U.S. households who are 18 years of age or ol der. The population of households will be
stratified by the geographic boundari es of 5 EPA study regions: Ca lifornia, Great Lakes, Inland,
Northeast, and Southeast. Surv ey participants will be recru ited randomly through random digit
dialing. The intended sample size for the survey is 2,000 house holds including only households
providing completed surveys. This sample size wa s chosen to provide sta tistically robust results
while minimizing the cost and burden of the surv ey. In addition to the sample size, EPA will
take steps to both test for and ameliorate surv ey non-response bias. EPA will follow standard
practice in stated preference de sign, including the extensive use of focus groups and pretesting to
develop survey questionnaires.
The key elicitation questions in each of the five regional surveys ask respondents whether
or not they would vote for polic ies that would increase their co st of living, in exchange for
specified multi-attribute changes in [a] impinge ment and entrainment losses of fish, [b]
commercial fish sustainability, [c] long-term fish populations, and [d] condition of aquatic
ecosystems. This “choice experiment” or “choi ce modeling” framework allows respondents to
state their preferences by ma king a voting-type selection between two hypothetical multiattribute regulatory options (and a third “status quo” choice that rejects both options). These
stated preferences with respect to levels of environmental goods and cost to households, when
used in conjunction with other in formation collected in the survey on the respondent’s use of the
affected aquatic resources, household income , and other demographics, can be analyzed
statistically (using either a fixe d or random effects mixed logit fr amework) to estimate total WTP
for the quantified environmental benefits of the 316(b) existi ng facilities rulemaking. Data
analysis and interpretation is grounded in a standard random utility model.100 In addition, to the total values , the survey will allow the es timation of values associated
with specific choice attributes (following standard methods fo r choice experiments), and will
also allow the flexibility to provide some insight into the relative importance of use versus nonuse values in the 316(b) context. Analysis also allows estimation of th e variation in WTP across
different types of households, in different areas. As indicated in prior lite rature, it is virtually
impossible to justify, theoretically, the decomposition of empirical total willingness-to-pay
estimates into separate use and non-use components. The survey will, however, provide the
flexibility to estimate nonuser values, using various nonuser definitions drawn from responses to
survey questions. The structure of the choice attr ibute questions will also allow the analysis to
separate value components related to the mo st common sources of use values—effect on

harvested recreational and commercial fish.

The various welfare values that can be deri ved from this stated preference survey
(discussed above) along with those that are esti mated apart from the survey effort will offer
insight into the composition of the value people place on the 316(b) environmental impacts. But
within rulemaking, among the most crucial concerns is the avoida nce of benefit (or cost) double
counting. Here, for example, WTP estimates derived from the survey may overlap—to a
potentially substantial ex tent—with estimates that can be pr ovided through some other methods.
Therefore, particular care will be given to avoid any possible double counting of values that
might be derived from alternative valuation methods. In doing so, the Office of Water will rely
upon standard theoretical tools for non-market welfare analysis, as presented by authors
including Freeman (2003) a nd Just et al. (2004).

Burden Statement: The annual public reporti ng and recordkeeping burden for this collection of
information is estimated to average 5 minutes per telephone screening pa rticipant and 30 minutes
per mail survey respondent including the time necessary to complete and mail back the101 questionnaire. Burden means the total time, effort , or financial resources expended by persons to
generate, maintain, retain, or disc lose or provide information to or for a Federal agency. This

includes the time needed to revi ew instructions; develop, acquire , install, and utilize technology
and systems for the purposes of collecting, valid ating, and verifying information, processing and
maintaining information, and disclosing and providi ng information; adjust the existing ways to
comply with any previously applicable instruct ions and requirements which have subsequently
changed; train personnel to be able to respond to a collection of information; search data sources;
complete and review the collection of informa tion; and transmit or otherwise disclose the

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

summarized here:
Estimated total number of potential responde nts: 8,333 for telephone screening and 2,000
for mailed questionnaires.
Frequency of response: one-time response.
Estimated total average number of respons es for each responden t: one-time response.

Estimated total burd en hours: 1,527 hours.
Estimated total costs: $ 34,600. EPA estimates that there will be no capital and operating
and maintenance cost burden to respondents.
What is the Next Step in the Process for this ICR?

EPA will consider the comments received a nd amend the ICR as appropriate. The final
ICR package will then be submitted to OMB for review and approval pursuant to 5 CFR
1320.12. At that time, EPA will issue another Federal Register notice pursuant to 5 CFR
1320.5(a)(1)(iv) to announce the submission of th e ICR to OMB and the opportunity to submit102 additional comments to OMB. If you have any questions about this ICR or the approval process,
please contact the technical person listed under FOR FURTHER INFORMATION CONTACT.

Dated: ________________

__________________________________ Ephraim S. King, Director
Office of Science and Technology103 Attachment 3: Description of Statistical Survey Design

Experimental design and sampling strategies depend on the details of the final survey instrument, which cannot be finalized prior to focus groups. The following represents an anticipated experimental design for survey impl ementation, along with the associated number of completed surveys that will be required. Part B of this supporting statement provides detail on the sampling design. The proposed design and samp ling plan is based on standard design and sampling theory for choice experiments and popul ation surveys, as outli ned by Louviere et al. (2000), Kuhfeld (2009) and Dillman (2000). The purpose of the 316(b) survey is to calcu late average per household parameters (e.g., willingness to pay and choice probabilities) w ithin a given survey population. No sub-population estimates are required. The anticip ated experimental design for th e 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 characte rized by levels for the following six attributes:

1. Location in A and B (x 1A ; x 1B ) – 2 possible levels 2. Fish Saved in A and B (x 2A ; x 2B ) – 3 possible levels 3. Commercial Fish Sustainability in A and B (x 3A ; x 3B ) – 3 possible levels 4. Fish Population 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 patt erns (i.e., a non-generic design), we begin with
the smallest available 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 ab ove notation, and levels indicated by integers 1...N, where N for each attribute is th e number of levels identified above:104 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 31 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 6105 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

This candidate design will be subject to refi nements based on results of focus groups and other design evaluations (e.g., to eliminate dominated profiles), as described by Louviere et al. (2000) and Kuhfeld (2009), but this will not significantly alter design dimensions. Following common examples in the environm ental economics literature, we anticipate three choice questions per survey. This will al low the 72 profiles to be included (orthogonally blocked) in 24 unique survey bookl ets. Monte Carlo experiments i ndicate that approximately 6 completed responses are required for each profile in order to achieve large sample statistical 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.106 Sample Sizes for Maximum Acceptable Sampling Error The goal of the choice experiment is to esti mate regression coefficients from mixed or conditional logit models that may be used to estimate willingness to pay for multi-attribute policy alternatives, or the like lihood of choosing a given multi-attr ibute alternative, following standard random utility modeling procedures (Haab and McConnell 2002). Required sample sizes to estimate population parameters with give n degrees 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 alte rnative) 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) re quired to obtain large sa mple properties for the choice experiment design provide more than su fficient observations to obtain this required precision for population parameters. The choi ce experiment design requires 432 completed profile responses from 144 surveys. Statisti cal 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 probability and confidence le vel can be obtained within approximately ±8.2 percent; this is also within acceptable limits.

Experimental Design Allowing Two-Wa y Interactions with Location (x 1A ; x 1B ) In order to estimate a parallel design that allo ws for interactions 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 avai lable 100% efficient linear main effects plan for non-location factors (X 2 – X 6 ) across both alternatives A and B, [3 8 6 2 ]. This
results in a main effect s 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 5107 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 4 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) creat ing a candidate design of 36×4 = 144 profiles. The resulting design fully insulates all main effects (eliminates aliasing) from interactions with location
attributes x 1A and x 1B , and allows associated location interac tions to be estimated independent of main effects. The number of required survey versions (48) and completed surveys (288) is doubled compared to the main effects plan outlined above. As above, the number of observations (completed surveys) required to obtain large sample properties for the choice experiment design provide suffi cient observations to obtain re quired precision for population parameters. 1 Also as above, this candidate design ma y be subject to refinements based on results

1 Alternatively, the smallest possible ma in effects plan for all attributes (72 profiles) may be folded over to make another 72 profiles, for a combined set of 144 profiles. This protects main effects from all unobserved 2-way108 of focus groups and other design evaluations, as described by Louvi ere et al. (2000) and Kuhfeld (2009), but this is unlikely to alter design dimensions.

interactions, but does not guarantee that specific interac tions may be estimated. The required sample size is the same as that which would guarantee that location interactions can be estimated.109 Attachment 4: Description of In ternet-based Sampling Alternative

EPA is also considering the us e of an internet-based (i.e., web-based) sampling approach
as an alternative to th e mail survey described in Part B of the supporting statement. The survey content, pre-testing, review process, and data analysis would be identi cal to the mail survey
described in Parts A and B of the supporting statement. To support implementation of the webbased alternative, EPA would reta in a vendor that maintains a pr eexisting representative national panel. . This attachment provides a brief su mmary of the web-based alternative, focusing on differences from the mail survey approach desc ribed 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 participat e in online surveys. The overall sampling frame would be the
set of all individuals in contin ental U.S. households who are 18 years of age or older and who have listed phone numbers. Individuals in the pa nel most likely be recrui ted using a list-assisted random digit dialing telephone methodology, thus pr oviding a probability-bas ed starting sample of U.S. telephone households. Panels of this t ype are usually routinely supplemented to account for panel attrition. The preexisting panel woul d have to closely tracks the U.S. population on age, race, Hispanic ethnicity, geographical regi on, employment status, and other demographic elements. If differences between the panel a nd the U.S. population do exist, sample weights using U.S. Census demographic benchmarks c ould be developed to reduce error due to noncoverage of non-telephone households and to reduce bias due to non-response and other nonsampling errors.

Sample Size The intention is to obtain 2,000 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 including age, education, Hispanic ethnic ity, race, gender, and household in come. 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 will110 systematically oversamples groups that tend to ha ve lower response and consistency rates so that the demographic characteristics of respondents w ho provide valid completed surveys will mirror the Census demographic benchmarks more cl osely. 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 al so reduce bias due to non-response and other nonsampling errors.

Survey Response The target response rate for the survey among panel members that are sampled is 80 percent. However, the actual response rate co mpared to the general population is lower, given that the telephone recruitment pro cess 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 wi ll be contacted to inform them that the survey is available online and reminders will be sent to panel memb ers 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 webbased format facilitates geographic and demogr aphic stratification, wh ich will substantially improve the quality of the survey.

Non-response and Other Non-Sam pling Error Corrections Approaches to minimize non-response bias in internet surveys are established in the literature (Dillman 2000) and include initia l RDD probability sampling, careful panel management, and effective survey sampling proce dures. The representati veness of preexisting panel survey sample is generally comparable to those telephone surveys sponsored by various Federal agencies. Nonetheless, EPA would conduct several additional activi ties 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 fo r unobserved heterogeneity that might be present in the data from respondents interviewed for this study111 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 cond uct non-response follow-up interviews within the initial sample for all stages of panel attrition. Respondents wi ll include indivi duals who were contacted but did not join the pree xisting panel, who agreed to jo in the panel but did not connect to the vendors web-site, who connected but did no t complete the first survey, who completed the first survey but did not comple te 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 use the information to increase the effective cumulative response rate by using a wei ghted response rate formulation.

Statistical Correction for Unobserved Heterogeneity EPA is also considering the use of a stat istical technique to correct for unobserved heterogeneity, based on work by Heckman (H eckman, 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 Census 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 techniqu e will take fully into account each stage of the panel recruitment and sampling proc ess: that is, all stages in between construction of the sample frame for panel recruitment and interv iewing of the panel respondents. The technique could be used to produce both ad justed and unadjusted estimates of WTP. Because the technique yields regression estim ates that explain survey outcomes using subpopulation data related to neighborhood characteris tics, it can be used to identify the sources of differences between the adju sted and unadjusted estimates.

As described above, EPA will use statistic al 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 techniques will reduce error due to noncoverage of non-telephone households in the origin al panel recruitment process, and also reduce bias due to non-response and othe r non-sampling errors. For an example of a similar research112 effort that successfully used this web-based su rvey approach to evaluate WTP for changes in water quality, see Viscusi et al. (2004).

Data Preparation Since the survey will be administered as an online survey, survey responses will be automatically entered into an electronic database at 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.113 Attachment 5: 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 [ASK IF SAMPLE=LANDLINE]
May I speak with that person?
1 Rspn on line SKIP TO SL2 2 Rspn called to phone SKIP TO SL1d 3 Rspn unavailable SCHEDULE CALLBACK 8 Refused THANK AND TERMINATE – Soft Refusal 9 Refused THANK AND TERMINATE – Hard Refusal
SL1c [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 phone 3 Rspn unavailable SCHEDULE CALLBACK 8 Refused THANK AND TERMINATE – Soft Refusal 9 Refused THANK AND TERMINATE – Hard Refusal114 SL1d[ASK IF SAMPLE=LANDLINE]
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. 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) Don’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 CALLBACK115 3 No SCREEN OUT 8 Refused THANK AND TERMINATE – Soft Refusal 9 Refused THANK AND TERMINATE – Hard Refusal
SC3 [ASK 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/Refused 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 used 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 SKIP TO SA1 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 Refusal116 SA1 [ASK BOTH SAMPLES]
Of all of the phone calls that you or y our family receives, 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 Record gender from observation. (Ask only if Necessary)

1 Male 2 Female

1. (MATCHES Q2 IN THE MAIL SURVEY) Firs t, would you please tell me the importance of each of the following issues to you, on a scale of 1 to 5 where 1 is “not important” and 5 is “very important”: (DO NOT ROTATE SO THAT TH E QUESTION MATCHES THE PAPER VERSION)
a. Improving public safety b. Protecting air quality c. Reducing taxes d. Improving homeland security e. Protecting aquatic life and habitat f. Maintaining industry and jobs g. Reducing your cost of living h. Protecting water quality

2. People have ideas about the extent to which the government should 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) DK (VOL) Ref
3. Could you please tell me if you participated in each of following activities during the last year? (DO NOT ROTATE)

Yes No (VOL) Don’t Know (VOL) Refused
a. Boating, canoeing, or kayaking b. Swimming/going to the beach c. Fresh Water Recreational fishing d. Salt Water Recreational fishing e. Shell fishing or crabbing f. Scuba diving or snorkeling117 Now, I have just a few questions for classification purposes.
D1. What is your age?
________ Years DK Ref
D2. 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

. Including everyone living in your household, which of the following categories best describes your total household 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, 5 Between $50,001 to $75,000, 6 Between $75,001 to $100,000, or 7 More than $100,000 8 (VOL) Don’t know 9 (VOL) Refused

D4

. Are you of Hispanic or Latino origin?

1 Yes 2 No 8 (VOL) don’t know 9 (VOL) Refused

D5

. Which of the following racial categories describes you? You may select more than one. Would it be... (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. Do you... (READ 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 mortgage118 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 this telephone survey, we are also conducting a mail survey to help U.S. policymakers to better understand your priorities for the environment and the use of public funds. This survey will be mailed to households along with a free reply envelope The survey takes most people about 25 minutes to complete.
I1. Would you be willing to participate in this mail survey?

1 Yes 2 No 3 Don’t know 4 Refused
(IF NO, DK, OR REF ) Thank you very much for your participation today.
I2. (IF I1 = 1) To what name and address should we mail the survey? (RECORD NAME, ADDRESS, CITY, STATE, AND ZIP CODE AND REPEAT BACK)
I3. And is this the best number to reach y ou at if we should have a problem mailing your survey?

1 Yes 2 No
I4. (IF I3 = 2) What is the best number to reach you? (RECO RD NUMBER AND REPEAT BACK)
Thank you. The survey will be sent to you in approximately one to two weeks. The packet will include information about the study, how to return your survey, and additional contact information in case you have questions. Thank y ou very much for your time, and have a great evening/day.