S UPPORTING S TATEMENT FOR I NFORMATION C OLLECTION REQUEST FOR

WILLINGNESS TO PAY S URVEY FOR §316(B ) E XI STING FACILITIES C OOLING WATER I NTAKE

S TRUCTURES : I NSTRUMENT , P RE - TEST , AND I MPLEMENTATIONi TABLE OF CONTENTS
PART A OF THE SUPPORTING STATEMENT
................................ ................................ ......... 1 1. Id entification of the Information Collection
................................ ................................ ....... 1 1(a) Title of the Information Collection
................................ ................................ ..................... 1 1(b) Short Characterization (Abstract)
................................ ................................ ....................... 1 2. Need For and Use of the Collection
................................ ................................ .................... 5 2(a) Need/Authority for the Collection
................................ ................................ ...................... 5 2(b) Practical Utility

/Users of the Data
................................ ................................ ...................... 5 3. Non
- duplication, Consultations, and Other Collection Criteria
................................ .......... 6 3(a) Non
- duplication
................................ ................................ ................................ .................. 6 3(b) Public Notice Required Prior to I CR Submission to OMB
................................ ................ 7 3(c) Consultations
................................ ................................ ................................ ..................... 13 3(d) Effects of Less Frequent Collection
................................ ................................ .................. 14 3(e) General Guidelines
................................ ................................ ................................ ............ 14 3(f) Confidentiality
................................ ................................ ................................ .................. 14 3(g) Sensitive Questions
................................ ................................ ................................ ........... 15 4. The Respondents and the Information Requested
................................ ............................ 15 4(a) Respondents
................................ ................................ ................................ ...................... 15 4(b) In formatio n Requested
................................ ................................ ................................ ...... 17 (I) Data items, including recordkeeping requirements
................................ .......................... 17 (II) Respondent activities
................................ ................................ ................................ ........ 21 5. The Information Collected
- Agency Activities, Collection Methodology , and In formation Management
................................ ................................ ................................ .............. 21 5(a) Agency

Activities
................................ ................................ ................................ .............. 21 5(b) Collection Methodology and Information Management
................................ ................... 22 5(c) Small Entity

Flexibility
................................ ................................ ................................ ..... 23 5(d) Collection Schedule
................................ ................................ ................................ .......... 24ii

6. Estimating Respondent Burden and Cost of Collection
................................ ................... 24 6(a) Estimating Respondent Burden
................................ ................................ ......................... 24 6(b) Estimating Respondent Costs
................................ ................................ ........................... 25 6(c) Estimating Agency Burden and Costs
................................ ................................ .............. 25 6(d) Respondent Universe and Total Burden Costs
................................ ................................ . 26 6(e) Bottom Line Burden Hours and Costs
................................ ................................ .............. 26 6(f) Reasons for Change in Burden
................................ ................................ ......................... 26 6(g) Burden Statement
................................ ................................ ................................ .............. 26 PART B OF THE SUPPORTING STATEMENT
................................ ................................ ....... 28 1. Survey

Objectives, Key

Variables, and Other Preliminaries
................................ ............ 28 1(a) Survey

Objectives
................................ ................................ ................................ ............. 28 1(b) Key

Variables
................................ ................................ ................................ .................... 28 1(c) Statistical Approach
................................ ................................ ................................ .......... 29 1(d) Feasibility
................................ ................................ ................................ .......................... 29 2. Survey

De sign
................................ ................................ ................................ ................... 30 2(a) Target Population and Coverage
................................ ................................ ....................... 30 2(b) Sampling Design
................................ ................................ ................................ ............... 30 (I) Sampling Frames
................................ ................................ ................................ .............. 30 (II) Sample Sizes
................................ ................................ ................................ ..................... 31 (III) Stratification Variables
................................ ................................ ................................ ..... 31 (IV) Sampling Method
................................ ................................ ................................ .............. 32 (V) Multi
- Stage Sampling
................................ ................................ ................................ ....... 33 2(c) Precision Requirements
................................ ................................ ................................ .... 33 (I) Precision Targets
................................ ................................ ................................ ............... 33 (II) Non
- Sampling Errors
................................ ................................ ................................ ........ 34 2(d) Questionnaire Design
................................ ................................ ................................ ........ 36 3. Pretests and Pilot Tests
................................ ................................ ................................ ..... 38 4. Collection Methods and Follow
- up ................................ ................................ .................. 38 4(a) Collection Methods
................................ ................................ ................................ ........... 38iii

4(b) Survey

Response and Follow
- up ................................ ................................ ...................... 39 5. Analyzing and Reporting Survey Results
................................ ................................ ......... 39 5(a) Data Preparation
................................ ................................ ................................ ................ 39 5(b) Analy sis
................................ ................................ ................................ ............................. 40 5(c) Reporting Results
................................ ................................ ................................ .............. 57 REFERENCES
................................ ................................ ................................ ............................. 59 ATTACHMENTS Attachment 1: Full Text of Regional Stated Preference Survey Component
............................... 68 Attachment 2: Full Text of National Stated Preference Survey Component
................................ 88 Attachment 3: Federal Register Notice
................................ ................................ ....................... 108 Attachment 4: Description of Statistical Survey Design
................................ ............................ 114 Attachment 5: Description of Internet
- based Sampling Alternative
................................ ........... 119 Attachment 6: Telephone Screener Script
................................ ................................ .................. 123 Attachment 7: Cover Letter to Mail Survey Recipients
................................ .............................. 130 Attachment 8: Post Card Reminder to Mail Survey Recipients
................................ ................. 131 TABLES Table A1: Geographic Stratification Design
................................ ................................ ................. 16 Table A2: Schedule fo r Survey Implementation
................................ ................................ .......... 24 Table A3: Total Estimated Bottom Line Burden and Cost Summary
................................ .......... 26 Table B1: Number of Households and H ousehold Sample for Each EPA Study Region
............ 34 Table B2: Illustration of an External Scope Test
................................ ................................ ......... 551 PART A OF THE SUPPORTING STATEMENT
1. Identification of th e Information Collection 1(a) Title of the Information Collection Willingness to Pay

Survey for Section 316(b) Existing Facilities Cooling Water Intake Structures: Instrument, Pre
- test, and Implementation 1(b) Short Characterization (Abstract)
On Febr uary 16, 2004, the U.S. Environmental Protection Agency (EPA) took final action on the Phase II rule governing cooling water intake structures at existing facilities that are point sources; that, as their primary activity, both generate and transmit electric power or generate electric power for sale to another entity for transmission; that use or propose to use cooling water intake structures with a total design intake flow of 50 MGD or more to withdraw cooling water from waters of the United States; and th at use at least 25 percent of the withdrawn water exclusivel y for cooling purposes. See 69 FR 41576 (July 9, 2004). In dustry

and environmental stakeholders challenged the Phase II regulations. On judicial review, the Second Circuit (Riverkeeper, Inc. v. EP A, 475 F.3d 83, (2d Cir., 2007)) remanded several provisions of the Phase II rule. Some key provisions remanded are as follows: EPA improperly used a cost
benefit anal ys is as a criterion for determining Best Technology Available (BTA), and EPA inappropriat el y used ranges in setting performance expectations. In response, EPA suspended the Phase II regulation in July 2007 pending further rulemaking. The U.S. Supreme Court granted Entergy Corporation’s petition for writ of certiorari, solely on the question of whether EPA had the authority

under §316(b) of the Clean Water Act to consider costs and benefits in decision
making. On April 1, 2009, the Court, in Entergy Corp. v. Riverkeeper Inc., decided that “EPA permissibly

relied on cost
- benefit analy sis in setting the national performance standards ... as part of the Phase II regulations.” EPA is now taking a voluntary remand of the rule, thus ending Second Circuit review. On June 1, 2006, EPA promulgated the 316(b) Phase III Rule for existing manufacturers, small flow power plants (facilities that use cooling water intake structures with a total design intake flow of less than 50 MGD to withdraw cooling water from waters of the United States;2

and that use at least 25 percent of the withdrawn water exclusivel y for c ooling purposes), and new offshore oil and gas facilities. Offshore oil and gas firms and environmental groups petitioned for judicial review, which was to occur in the Fifth Circuit, but was stayed pending the Supreme Court decision on the Phase II case. EPA has petitioned the Court for a voluntary remand of the existing facilities portion of the Phase III rulemaking. In developing the Phase III regulation, EPA began, but did not complete, a similar stated preference survey effort. The current effort buil ds on that earlier work. EPA is now combining the two phases into one rulemaking covering all existing facilities. EPA will develop regulations to provide national performance standards for controlling impacts from existing cooling water intake structures (CWI S) under Section 316(b) of the Clean Water Act (CWA). Under Executive Order 12866, EPA is required to estimate the potential benefits and costs to society for economically significant rules . To assess the public policy significance or importance of the ecological gains from the section 316(b) regulation for existing facilities, EPA requests approval from the Office of Management and Budget to conduct a stated preference survey . Data from the stated preference survey will be used to estimate the value s (willingness to pay , or WTP) derived by households for changes related to the reduction of fish losses at CWI S , and to provide information to assist in the interpretation and validation of survey responses . As indicated in the prior literature (Cummings and Harrison 1995; Johnston et al. 2003 a , 2005), it is virtually impossible to justify , theoreticall y, the decomposition of empirical estimates of use and non - use values. The survey will provide the flexibility , however, to estimate nonuser values, using various nonuser definitions drawn from responses to survey question 10 . The structure of choice attribute questions will also allow the anal ys is to separate value components related to the most common sources of use values

— effect on harvested recreational and commercial fish. In summary , the survey will provide estimates of total values (including use and nonuse) , will allow estimates of value associated with specific choice attributes (following standard methods for choice experiments), and will also al low the flexibility to provide some insight into the relative importance of use versus non - use values in the 316(b) context. Within rulemaking, among the most crucial concerns is the avoidance of benefit (or cost) double counting. Here, for example, the W TP estimates will include use and non - use values among a representative population sample. These may overlap

—to a potentially substantial3

extent

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

authors including Freeman (2003 ) and Just et al. (2004). From a purel y mechanistic perspective, survey results will be used to derive total values following standard practice for choice experiments (Adamowicz et al. 1998). The target population for this stated preference survey is all individuals from continental U.S. households who are 18 years of age or older. The population of households will be stratified into four study regions: Northeast , Southeast , Inland, and Pacific. The Northeast survey region includes the North Atlantic and Mid Atlantic 316(b) benefits regions , the Southeast survey region includes the South Atlantic and Gulf of Mexico 316(b) benefits regions , the Pacific region includes states on the Pacific coast, and the Inland region includes all non
- coastal states. Inaddition, EPA will administer a national version of the survey that does not require stratification. Respondents will be recruited using a random digit dialing ( RDD ) sample (overlapping dual frame; land and cell phone numbers ) and a brief telephone questionnaire. Participation in the survey is voluntary . If the person in the household agrees, the recruited respondent will be asked to complete the survey questionnaire by mail. EPA intends to administer the mail survey to 5, 720 households in order to achieve 2, 288 completed responses assuming a 40% completion rate for households agreeing to participate. EPA is also considering implementing the proposed survey as an internet
- based, choice experiment questionnaire. This alternative approach is described in Attachment 5
. For the selection of households, the population of households in the 48 states and the District of Columbia will be stratified b y the four study regions. The sample is allocated to each region in proportion to the total number of households in that region with the restriction that we get at least 288 completed responses in each region. A sample of 288 households completing the national survey

version would be distributed among the study regions based on the percentage of regional survey

sample to ensure that respondents to the national survey version are distributed across the continental U.S. Non
- response bias has the potential to occur due to households declining to participate in the mail survey when contacted by

phone or households which fail to4

return a completed survey after agreeing to participate. To conduct a non
- response study , EPA will use a brief telephone questionnaire to collect sample characteristics in the course of the telephone contact. EPA will analyze the characteristics of the completed and non
- completed cases from the random digit dialing sample to determine whether there is any evidence of significant non
- response bias in the completed sample. This analy sis will suggest whether any weighting or statistical adjustment is necessary to minimize the non - response bias in the completed sample
. As part of the testing of the survey instrument , EPA conducted a series 7 focus groups with 8
- 10 participants per focus group , with approval from the Office of Management and Budget ( OMB control # 2090
- 0028 ). The Agency conducted focus group s in several regions to account for the potentially distinct information relevant to survey design. These focus groups were conducted following standard, accepted practices in the stated preference li terature, as outlined by

Mitchell and Carson (1989), Desvousges et al. (1984), Desvousges and Smith (1988) and Johnston et al. (1995). One of the focus groups incorporated individual cognitive interviews, as detailed b y Kaplowicz et al. ( 2004). The focus groups and cognitive interviews allow ed EPA to better understand the public's perceptions and attitudes concerning fishery resources, to frame and define survey

questions, to pretest draft survey questions, to test for and reduce potential biases that may be associated with stated preference methodology , and to ensure that both researchers and respondents have similar interpretations of survey language and scenarios. In particular, cognitive interviews allowed for in
- depth exploration of the cognitive pro cesses used by respondents to answer survey questions, without the potential for interpersonal dy namics to sway respondents’ comments (Kaplowicz et al. 2004). Transcripts from these seven focus groups can be found in the docket for this I CR (ICR # 2402.01 ). EPA revised the survey based on the findings of the seven focus groups. These seven focus groups were conducted in addition to f ocus groups conducted previously by EPA under ICR #2155.01 to test the draft survey for the Phase III benefits analy sis . Transcripts from the previously conducted focus groups for the Phase III anal ys is can be found in the docket for EPA I CR #2155.02 (Besedin et al., 2005)
. Findings from these previous focus groups were also incorporated into the development of the current s urvey . The total national burden estimate for all components of the survey is 1, 938 hours. The burden estimate is based on 9,533 participants in telephone screening interviews and 2, 288 respondents to the 5, 720 mailed questionnaires. EPA assumes an ave rage burden estimate of 55

minutes per telephone screening participant and 30 minutes per mail survey respondent including the time necessary

to complete and mail back the questionnaire. Given an average wage rate of $ 20
. 42 , the total respondent cost is $ 3 9,583
. 2. Need For and Use of the Collection 2(a) Need/Authority for the Collection The project is being undertaken pursuant to section 104 of the Clean Water Act dealing with research. Section 104 of the Clean Water Act authorizes and directs the EPA Administrator to conduct research into a number of subject areas related to water quality, water pollution, and water pollution prevention and abatement. This section also authorizes the EPA Administrator to conduct research into method s of anal yz ing the costs and benefits of programs carried out under the Clean Water Act. This project is exploring how public values for fishery resources are affected by fish losses from impingement and entrainment (I &E) mortality at cooling water intake structures. Understanding total public values for fishery resources , including the more difficult to estimate non - use values 1 , is necessary to determine the full range of benefits associated with reductions in I&E mortality losses, and whether the benefit s of government action to reduce I&E mortality losses at existing facilities are commensurate with the costs of such actions. Because non
- use values may

be substantial, failure to recognize such values may lead to improper inferences regarding benefits and costs. The findings from this study will be used b y EPA to improve estimates of the economic benefits of the section 316(b) regulation for existing facilities as required under Executive Order 12866
. 2(b) Practical Utility/Users of the Data EPA plans t o use the results of the survey to improve estimates of the economic benefits of the section 316(b) regulation for existing facilities. Specificall y, the Agency will use the survey results to estimate total values for preventing losses of fish through I&E mortality at CWI S, following standard practices outlined in the literature (Freeman 2003; Bennett and Blamey 2001; Louviere et al. 2000; U.S. EPA 2000).

1 The stated preference format was chosen because it is the only method that allows the estimation of non - use values, which are potentially significant in this case.6

3. Non - duplication, Consultations, and Other Collection Criteria 3(a) Non - duplication
There are many

studies in the environmental economics literature that quantify benefits or willingness to pay

(WTP) associated with various ty pes of water quality

and aquatic habitat changes. However, none of these studies allows the isolation of non
- market WTP associ ated with quantified reductions in fish losses for forage fish. Most available studies estimate WTP for broader, and sometimes ambiguously defined, policies that simultaneously influence many different aspects of aquatic environmental quality and ecos ys tem services, but for which WTP associated with fish or aquatic life alone cannot be identified. Other studies provide benefit estimates associated with improvements in fish (or aquatic) habitat, but do not link this to well
defined and quantified changes in affected or supported organisms. Still other studies address willingness to pay

for changes in charismatic or recreational species that have little relationship to the ty pes of forage fish that are the vast majority of species affected by

cooling water intake structures. For example, choice experiment studies such as Hanley et al. (2006a, 2006 b) and Morrison and Bennett (2004) estimate WTP for aquatic ecos ys tem changes that affect fish, but the effects on fish are quantified and valued solely in terms of the presence/absence of different ty pes of fish species. This approach renders associated results unsuitable for 316(b) benefit estimation. Also, many

of these studies were conducted outside the U.S. (e.g., the European Union or Australia), making their use for benefit transfer to a U.S. policy context more challenging. Other studies have estimated the value of changes in catch rates or populations of select recreational and commercial species, charismatic species such as salmon, or changes in water quali ty that affect fish, but none have specificall y valued changes in forage fish populations. For example, Olsen et al. (1991) conducted a survey of Pacific Northwest residents, including both anglers and non
- anglers, to determine their WTP for doubling the s ize of the Columbia River Basin salmon and steelhead runs. EPA’s proposed survey approach differs from this study and others like it (such as Cameron and Huppert 1989) in that it would include respondents from various geographic regions in the United Stat es and would provide values for the full range of7

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

fish passage over dams in the Pawtuxet and Wood
- Pawcatuck watersheds. Hence, the case study is for a watershed
- level policy with s tatewide welfare implications. In contrast, 316(b) policies would have nationwide implications, both on ecos ys tems and on affected facilities. 3(b) Public Notice Required Prior to ICR Submission to OMB In accordance with the Paperwork Reduction Act (4 4 U.S.C. 3501 et seq.), EPA published a notice in the Federal Register on July 21 , 20 10 , announcing that the survey questionnaire and sampling methodology were available for comment. A copy of the first Federal Register notice is attached at the end of this document ( EPA ICR #2 402.01 .02) (See Attachment 3 ) . EPA received a number of comments on the proposed information collection, which are summarized in the following paragraphs. Also see docket # EPA
- HQ
- OW
- 2010
- 0595
. EPA considered relevant comments on the draft survey when developing the survey questionnaire and sampling methodology for the current survey

for existing facilities.8

Some c ommenters expressed concern that the draft survey questionnaire and sampling methodology would not provide accurate e stimates of WTP. Some stated that the proposed stated preference survey

would overestimate WTP to prevent fish losses. Another commenter argued the opposite: that the proposed contingent valuation survey is biased against protecting ecos ys tems, and will drastically undervalue non
- use benefits. EPA agrees that certain details of the stated preference survey and supporting documentation for the July 21, 2010 Federal Register notice required revision. Following OMB approval of the focus groups, EPA conduc ted seven focus groups ( including one set of cognitive interview s ) to pretest the draft survey materials, to test for and reduce potential biases that may be associated with stated preference methodology , and to ensure that both researchers and respondents have similar interpretations of survey language and scenarios. As a result of this extensive pre
- testing, a number of revisions were made to the draft survey

that significantl y improved its reliability and reduced its potential for bias
. Hence, many of the survey design elements on which commenters took issue have already been removed or changed. In many other instances, however, focus groups showed little cause for concern, suggesting that many of the speculative claims raised by commenters have little value to the population being surveyed
. EPA also notes that number of focus groups and interviews conducted for this survey

— and the draft survey tested in 2005
- 06

—far exceeds the number conducted for most stated preference survey s found in the published literature. EPA notes that the survey proposed in this I CR is different in many ways from the draft survey for the Phase III benefits anal ys is that was peer reviewed in 2005 (Versar 2006) . While findings from pre
- testing of the previous draft survey wer e considered when developing the present survey , the present survey has undergone various revisions based on additional anal ys is and the results of recent focus groups. Due to these differences, EPA notes that many of the peer review comments received on the Phase III draft survey are no longer relevant for the survey proposed in this I CR. The Agency , however, takes all peer review comments very seriousl y, and has accounted for these comments in all survey revisions and in the development of the present s tated preference survey
. One commenter argue d that in conducting the stated preference survey , EPA should use the willingness
- to - accept (WTA) metric in place of or in addition to WTP. EPA notes that good practice guidelines for stated preference surveys a lmost universally indicate the use of WTP elicitation mechanisms over WTA elicitation mechanisms. This is due to the potential for biases in WTA stated preference surveys that can be ameliorated by the use of the WTP format. WTP9

is also considered to be the more conservative choice, but in most cases, the divergence between WTA and WTP, as predicted, b y theory, should be very small. EPA follows standard practice in proposing a WTP format in order to avoid these biases, compl y with guidance and practice in the stated preference literature, and ensure a conservative benefit estimate. Some commenter s argued that hy pothetical bias in the survey questionnaire would inhibit respondents ability

to provide meaningful survey responses. EPA agrees that hy pothetical bias is an important concern with stated preference surveys

—and has taken this very seriously in survey development and testing. EPA does not agree that this inhibits respondents or that the literature suggests that hypothetical bias is unavoidable; in f act , the published literature includes approaches to mitigate such biases. The Agency followed the published literature in designing mitigation strategies to eliminate or at a minimum reduce the potential for hy pothetical bias. This includes explicitly

d esigning the survey to maximize the consequentiality of choice experiment questions through direct linkages to proposed EPA regulatory efforts. Moreover, the survey explicitly

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

of values (and behavior) to information is true of both market and non
- market values (Bateman et al. 2002, p. 298), and in no way invalidates the proposed non
- market values that would be estimated through the proposed stated preference approaches. It is common practice in such survey s to provide substantial information to survey respondents. The survey information was pretested extensively during the seven focus group sessions and EPA revised or removed informational elements which respondents foun d confusing or misleading. Some commenters argued that the survey results will be unreliable because the survey questionnaire contains inaccurate statements and comparisons which overstate the resource impacts from baseline I& E mortality and the regulatory options presented in the survey . EPA10

recognizes the importance of accuratel y characterizing resource and regulatory impacts and notes that the survey

is based on the best biological and engineering data available. Despite the general observation that I& E impacts are small compared to other effects, I&E has been shown to have measurable impacts on local fish populations and communities. Importantly, increases in fishery sustainability

and fish population values presented in the survey instrument are smal l. Overall, the Agency

rejects the claims from commenters , based largel y on feedback from focus group participants, that impacts are misrepresented, and emphasizes that the survey is explicitly designed to provide respondent s with an understanding of the proposed policies that is as accurate as possible given the best available ecological science. Commenters also questioned whether survey respondents would have sufficient comprehension of the issues in order to provide meaningful responses to the survey ’ s valuation questions. EPA agrees that in order to receive meaningful responses, a stated preference survey should provide information to respondents about the hypothetical commodity so that they understand and accept it and can give meaningful answers to the valuation questions. Given the importance of commodity comprehension, EPA devoted considerable attention to comprehension of the hy pothetical commodity

and related issues (e.g., understanding of pay ment vehicle , understanding of the ecological scores ) during the recent focus groups and cognitive interviews and focus groups conducted for the original version of the Phase III survey instrument in 2005
. F ocus groups participants showed no difficulty understanding the format of the pay ment vehicle and that selecting Options A or B would result in inc reased costs to their household . They also correctly understood this cost as ongoing. In addition to the comments regarding the payment vehicle , commenters expressed concern regarding respondent comprehension of the ecological scores used in the survey. EPA emphasizes that the reaction and understanding of likely respondents , as opposed to experts, is crucial when testing the communication of ecological information in stated preference surveys. The survey ha s undergone substantial changes in the way it communicates ecological information based on the results of the seven focus group sessions. For example , in the revised survey , EPA provides more precise information regarding the definition of “young adult fis h” on Page 4 , which currentl y s tates : “After accounting for the number of eggs and larvae that would be expected to survive to adulthood, scientists estimate that the equivalent of about 1.1 billion yo ung adult fish (the equivalent of one year old) are los t each ye ar in Northeast coastal and fresh waters due to cooling water use.” Overall, focus group and interview p articipants’ statements11

implied different opinions about the importance of preventing fish losses versus increasing fish population or improving the condition of aquatic ecosystems. Also, t here did not appear to be any confusion over the fact that scores of 100 for various attributes are generally unattainable through reductions in CWI S fish losses alone. One commenter argues that the stated p reference survey fails to account for effects on a number of non
- fish species as well as effects on threatened, endangered, and other protected species. In response to this comment, EPA agrees but notes that focus group respondents suggested that addition s to the survey ’s length should be avoided
. Thus EPA will not be able to use these survey results to represent absolutely complete benefits estimation, but will be able to say that a potentially

substantial category

of benefits, non
use benefits, has been included. As is common in survey s, EPA has chosen to present policy scenarios in simplified form to facilitate respondent comprehension, and to encourage respondents to focus on the most important policy characteristics related to fish losses. Such simp lification of the survey helps to balance the provision of detailed policy information against respondents’ cognitive abilities to consider a large number of attributes simultaneously (Louviere et al. 2000). Some commenters stated that EPA did not suffic iently emphasize the uncertainty associated with effects and costs of the proposed policies presented within the survey
. EPA agrees that there is uncertainty regarding the number of fish killed annually , as well as the effects and costs of the regulatory policies presented within the survey . Additionally , EPA does note uncertainty within the current existing facilities survey . For example, the following statement s are included in the current survey version for the Northeast region : “Although scientists c an predict the number of fish saved each ye ar, the effect on fish populations is uncertain. This is because scientists do not know the total number of fish in Northeast water and because many factors

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

– affect fish populations”, and “Policy costs and effects depend on many factors.” EPA has also included debriefing questions in the survey instrument that are designed to identify individuals whose responses are based on incorrect interpretation of the environmental changes described in the survey , including the uncertainty of the expected changes. EPA points out that debriefing sessions during focus groups and cognitive interviews showed that respondents clearl y understood that the ecolo gical changes described in the survey were uncertain. Furthermore, when asked, focus group respondents indicated that they were comfortable making decisions in the presence of uncertainty
.12

Another commente r questioned various components of EPA proposed sampling methodology , experimental design , and methods for accounting for non
- response bias
. In response, EPA emphasizes that methods for WTP estimation from ecological choice experiment data

—of exactl y the type proposed b y EPA

—are very well established in the published literature. More broadl y, when designing the proposed methods, EPA closely followed accepted contemporary

methods in the published literature for the estimation of WTP distributions under statistical uncertainty. In the absence of concrete and established alternatives for the choice of sampling weights, EPA has proposed a more conservative approach of reliance on accepted and standard methods from the stated preference literature. EPA believes

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

— that established stated preference methods are capable of estimating reliable and accurate welfare measures , if surveys and approaches are appropriately designed
. Regarding the potential for non
- response bias, EPA has proposed standard approaches for non
- response assessments and calibrations in proposing tests and corrections for non
- response based on a small number of attitudinal and behavioral questions, comb ined with demographic characteristics. These currently reflect standard practice within the literature. Another commenter argued that although the Supreme Court held that Clean Water Act section 316(b) does not prohibit the consideration of costs in relation to benefits of proposed rule it did not find that cost benefit anal ys is is required ( Entergy Corp. v. Riverkeeper, Inc. )
. EPA has the authority

to decide whether to conduct cost benefit anal ys is of proposed rule options
. The commenter, however, recognized that Executive Order 12866, “Regulatory Planning and Review,” requires EPA to estimate potential costs and benefits to society of proposed rule options. Inresponse to the commenter’s claim about utility of cost
- benefit analy sis in environmental cont ext, EPA notes that cost
- benefit analy sis is only one tool that can be used to inform policy

decisions. EPA is conducting this survey because of Executive Order 12866, “Regulatory

Planning and Review,” which requires Federal Agencies to conduct economic impact and cost
- benefit analy sis for all major rules. Furthermore, cost
- benefit analy sis requires a comprehensive, estimate of total social benefits, including non
- use values. The current information collection would provide valuable information regarding total social benefits of the 316(b) regulation for existing facilities, thus enabling the Agency to perform cost
- benefit13

anal ys is for the regulation , if it should choose to, without ignoring a potentially important category of benefits (non
- use values), an d to satisfy the requirements of Executive Order 12866. For a more detailed discussion of the issues raised by commenters on this ICR , see EPA’s response to pubic comments on the Federal Register notice published on November 23, 2004 ( 69 FR 68140 ). For a discussion of the issues raised by commenters on the previous Phase III survey ICR, see EPA’s response to pubic comments on the Federal Register notice published on June 9, 2005 (70 FR 33746). For a discussion of issues raised by commenters on the previou s Phase III focus group ICR, see EPA's response to public comments on the Federal Register notice published on November 23, 2004 (69 FR 68140). 3(c) Consultations The Principal Investigator for the stated
- preference portion of this effort is Dr. Robert J ohnston. Dr. Johnston is assisted by Dr. Elena Besedin, a Senior Economist at Abt Associates In c. Dr. Erik Helm at the U.S. Environmental Protection Agency serves as the project manager and a contributor to this research. Robert J. Johnston is Director of the George Perkins Marsh Institute and Professor of Economics at Clark University . He is President
- elect of the Northeastern Agricultural and Resource Economics Association (NAREA), on the Program Committee for the Charles Darwin Foundation, the Scien ce Advisory Board for the Communication Partnership for Science and the Sea (COMPASS), and is the Vice President of the Marine Resource Economics Foundation. Professor Johnston has published extensively on the valuation of non
- market commodities (goods, s ervices, and resources), benefit cost analy sis, and resource management. His recent research emphasizes coordination of ecological and economic models to estimate ecos ys tem service values, with particular emphasis on the role of aquatic ecological indicators. He has also worked extensively

in methodologies for benefit transfer, including the use of meta
- anal ys is. Professor Johnston’s empirical work on non
- market valuation and benefit transfer has contributed to numerous benefit cost analyses conducted by federal, state and local government agencies in the US, Canada and elsewhere. Elena Y. Besedin, a senior economist at Abt Ass o ciates Inc., specializes in the economic anal ys is of environmental policy and regulatory

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

EPA program14

offices. She has worked extensively on valuation of non
- market benefits ass ociated with environmental improvements of aquatic resources. Dr. Besedin’s empirical work on non
- market valuation include s design and implementation of stated and revealed preference studies and benefit transfer methodologies. Her recent work has focuse d on developing integrated frameworks to value changes in ecos ys tem services stemming from environmental regulations. EPA notes that the current survey instrument is built upon an earlier version that was peer reviewed in January

2006. It incorporates rec ommendations received from the first peer review panel. Because the final product of this study meets the major technical work criteria specified in the Peer Review Handbook (U.S. EPA 200 6 ) the Agency also plans to convene a peer
- review panel to review th e entire survey process, including the survey instrument, study

results, and EPA’s final estimated results for the 316(b) Existing Facilities rulemaking, after the survey is completed. 3(d) Effects of Less Frequent Collection The survey

is a one
- time activity . Therefore, this section does not appl y . 3(e) General Guidelines The survey

will not violate any

of the general guidelines described in 5 CFR 1320.5 or in EPA’s I CR handbook. 3(f) Confidentiality All responses to the survey will be kept strictly anony mous. To ensure that the final survey sample includes a representative and diverse population of individuals, the survey questionnaire will elicit basic demographic information, such as age, household size, employ ment status, and income. However, th e detailed survey questionnaire will not ask respondents for personal identifying information, such as names, phone numbers, or addresses. Addresses will be collected during telephone screening, but the telephone screening and mail survey databases will n ot be matched or combined. Prior to taking the survey , respondents will be informed that their responses will be held strictly anonym ous. The survey data will be made15

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 religious beliefs.
4. The Respondents and the Information Requested 4(a) Respondents The target population for the Stated Preference Survey is all individuals from continental U.S. households who are 18 years of age or older. Survey participants are recruited randomly through random digit dialing
. EPA wil l identify a random stratified sample of 5, 720 adults who express their willingness to participate in a mail survey when contact ed by telephone through random digit dialing . All of these recruits will be sent a cop y of the mail survey
. Approximately 2, 288 of the adults of the 5, 720 adults sent a survey are expected to return a completed survey
. For the selection of households, the population of households in the 48 states and the District of Columbia will be stratified b y four study regions. There are a total of seven study regions for purposes of evaluating the 316(b ) existing facilities rule benefits. For the purpose s of the stated preference survey implementation , EPA uses four geographic regions: Northeast, Southeast, Inland, and Pacific. The Northeast region includes the North Atlantic and Mid Atlantic regions , the Southeast region includes the South Atlantic and Gulf of Mexico regions , the Pacific region includes states on the Pacific coast, and the Inland region includes all non
coastal states. A sample of 2,000 households would complete a version of the survey which specifically addresses policies within their region. The total sample completing regional survey versions is allocated to each region in proportion to the total number households in that region with the restriction that at least 288 persons respond in each region. This is the number required to estimate the main effects and interactions under an experimental design model. The total sample size for each region is much larger then the minimum sample size required for model estimation for all but one region (Pacific ). An additional sample of 288 household s w ill receive a national survey version which addresses policies at the national scale. This sample would be distributed16

among the study regions based on the percentage of regional survey sample (as shown in Table A1) to ensure that respondents to the national survey version are distributed throughout the continental U.S. Part B of this document provides detail on sampling methodology
. Table A 1 shows the stratification design for the geographic regions covered by the sample for this survey
. More detail on planned sampling methods and the statistical design of the survey

can be found in Part B of this supporting statement.

Table A 1 : Geo graphic Stratification Design Region States Included Sample Size a Percentage

of Sample Northeast CT, DC, DE, MA, MD, ME, NH, NJ, NY, PA, RI, VT 417 21 % Southeast AL, FL, GA, LA, MS, NC, SC, TX, VA 562 28 % Inland AR, AZ, CO, ID, IA, IL, IN, KS, KY, MI, MN, MO, MT, NM,

OK, ND, NE, NV, OH,TN, SD, UT, WI, WV, WY 732 37 % Pacific CA, OR, WA 288 14 % Total for Regional Surveys Versions U.S. (excluding AK and HI) 2,000 100% National Survey Version U.S. (excluding AK and HI) 288
-

a Sam ple sizes presented in this table include only the 2, 288 individuals returning completed mail surveys.17

4(b ) Information Requested (I) Data items, including record keeping requirements Individuals who agree to participate in the survey will be mailed a cop y of the survey. The full text of the regional version of the mail survey for the Northeast region is provided in Attachment 1 and the full text of the national version of the mail survey is provided in Attachment 2. EPA revised the survey based on the findings of a series o f seven focus groups conducted as part of survey instrument development (OMB control # 2090
- 0028). Additional information regarding focus group implementation is provided in Section 5(b). EPA has determined that all questions in the survey are necessary to achieve the goal of this information collection, i.e., to collect data that can be used to support an anal ys is of the total benefits of the 316(b) regulation. The following is an outline of the major sections of the survey
. Relative Importance of Issues Associated with Industrial Cooling Water . The first survey question asks respondents to rate the general importance of ( a) preventing the loss of fish caught by humans , (b ) preventing the loss of fish not caught by humans , ( c ) maintaining ecological health in rivers, lakes, and bay s , ( d) keeping the cost of goods and services low, (e) making sure there is enough government regulation on industry, and (f) making sure there is not too much government regulation on industry
. This question is designed to eli cit the respondent’s general preferences for regulation, reductions in fish losses, and ecological health. It also places respondents in the mindset where they are cognizant of the range of issues associated with the use of cooling water by

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

might direct their scarce household budgets. Relative Importance of Effects . Que stion 3 asks the respondent to rate the importance of each of the effects captured b y the five scores: ( a) commercial fish populations (b ) fish populations (for all fish) , ( c ) fish losses prevented , ( d) condition of aquatic ecos ys tems, and ( e ) cost to my18

h ousehold
. This question is designed to prom ote understanding of the scores by placing respondents in a mindset where they consider the meaning of each score and consider their general preferences for effects prior to considering specific policy options. The question also promotes understanding by telling the respondent that they can return to previous pages for reminders of what the scores mean. Voting for Regulations to Prevent Fish Losses in the Respondent’s Region . Questions 4, 5, and 6 are “choice experiment” or “choice modeling” questions (Adamowicz et al. 1998; Bennett and Blamey

2001), and ask respondents to choose how they would vote, if presented with two hy pothetical regulatory

options (and a third “status quo” choice to reject both options) for waters within the respondents’ region (e.g., Northeast waters) . Each of the multi
- attribute options is characterized b y ( a) commercial fish populations (in 3
- 5 years) (b) fish populations (all fish; in 3
- 5 years), (c) fish saved per year (out of [total] fish los t in water intakes ) , ( d) condition of aquatic ecosy stems (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 alway s have the option to vote for neither option

— providing the status quo option is necessary for appropriate welfare estimation (Adamowicz et al. 1998). Advantages of choice experiments, and the many examples of the use of such approaches in the literature, are discussed in later sections of this ICR. Following standard approaches (Opaluch et al. 1993, 1999; Johnston et al. 2002 a; 2002b , 2003 b ), respondents are instructed to answer each of the three choice questions independently , and not to “add up or compare programs across different pages.” This is included to avoid biases associated with sequence aggregation effects (Mitchell and Carson 1989). EPA will also vary the order in which the policy op tion attributes are presented across respondents, such as presenting household cost first or presenting fish saved per ye ar lower in the list of choice question attributes. While complete randomization is impractical for the mail survey , the change in order would allow for a potential test of ordering effects. Reasons for Voting “No Policy” . Question 7 is a follow
- up to the prior voting questions, and ask s respondents to identify the primary

reason for voting no, if they always voted for “no policy” in qu estions 4
- 6. It is designed to identify respondents whose “no policy” responses are based on their budget constraint, respondents who do not consider fish losses important enough to vote for a policy , or respondents who ignored information presented in th e survey and answered questions based on their general convictions and principles. In an electronic survey19

format, respondents who voted for a policy would not see this question, potentially reducing burden. Respond ent Certainty and Reasons for Voting . Q uestions 8 and 9 are follow
- up questions to the prior voting. Question 8 assesses the certainty that respondents feel in their choice experiment responses, following methods of Champ et al. (2004 ; 2009 ) , Akter et al. (2009), Kobayashi et al. (2010), and o thers. It is designed to identify respondents whose responses are based on incorrect interpretation of the resource changes and the uncertainty of ecological outcomes from policy

options. EPA will evaluate respondent understanding when completing stated preference survey s using methods and approaches discussed in Bo yl e (2003) , Kaplowitz et al. ( 2004 ) , Bateman et al. ( 2002 ) , Powe ( 2007 ) and others
. Question 9 asks respondents to rate the effect of factors on their choices, and why the y voted for or agains t the regulatory programs. Responses to such questions have been used in the literature to successfully control for hy pothetical bias. Recreational Experience. Questions 10 ask s respondents how often they participate in specific ty pes of water
- related r ecreational activities within the last year. This question can be used to identify non - users of the fishery

resource
—thereby

allowing the estimation of non - user values for I&E mortality reductions
. 2 Examples of this approach to estimation of non
- user valu es are provided b y J ohnston et al. (2005 a), Whitehead et al. (1995), Croke et al. (1986), Olsen et al. (1991), Cronin (1982), Whitehead and Groothuis (1992), and Mitchell and Carson (1981). Demographics. Questions 11
- 21 ask respondents to provide basic demographic information, including age, gender, highest level of education, household size, household composition, location, employ

ment status, and household income. This information will be used in the anal ys is of survey

results, as well as in the nonres ponse anal ys is. Comments. The survey

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

will modify

the survey

instrument for each region relative to the regional survey shown in Attachment 1 for the Northeast region as follows:
 Cover

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

2 Non
- user values are by definition non - use values. Users can also hold non
- use values. However, user’s non
-use values may differ from non
-users value s due to familiarity with the resource. Thus, non
- user values are not necessarily representative of average non
-use values.20

 Cover

– The photo on the cover is of a fo rage species (silversides) in found in the Northeast region. If that species isn't found in other regions, EPA will replace the cover photo with a similar substitute photo for a forage species relevant to that region.
 Page 1

– The survey

states that it “as ks for your opinions regarding policies that would affect fish and habitat in the Northeast U
. S.” “Northeast U
. S
. ” will be replaced with the respondent’s region or simply , “the U.S.” for the national version
.  Page 1

– Includes the statement that “Northeast fresh and salt waters support billions of fish.” “Northeast” will be replaced with the respondent’s region or “the U.S.” for the national version and “salt water” will be removed from the Inland and Great L akes regions.
 Page 2
- The survey

states that “Co oling water use affects fresh and salt waters throughout the Northeast US, but almost all fish losses are in salt waters such as coastal bay s.” For the Southeast and Pacific regions, which include both salt water and freshwater facilities, reference to th e Northeast region would be replaced with the name of the respondent’s region or “the U.S.” for the national version of the survey . For the Inland region, which only include freshwater facilities, reference to salt water will be removed.
 Page 2

– A map of the Northeast region and facility locations is presented. A comparable map will be produced for each region or the U.S. , and map included in the survey will correspond to the respondent’s region or the U.S.
.  Page 4
- This page provides an example for two Northeast coastal species and includes a figure comparing estimates of young fish lost to the total number of adult fish. The estimate of total losses will be modified to describe species and losses occurring within the respondent’s region.
 Page 5
- The total losses (1.1 billion) included within the survey corresponds to losses from facilities in Northeast coastal waters. This total would be replaced with the total losses for the respondent’s region or total losses for the U.S. for the national version
. The pie charts will be updated based on the regional (national) total while maintaining the 25% and 95% reductions used in the example.
 Page 7
- The table text describing each score will be changed to include the current scores for the respondent’s regio n.21

 Page 8
- Text describing the commercial fish populations score and fish population s (all fish) score will be changed to describe the current score for the respondent’s region relative to its maximum.
 Page 10

– The included figure illustrates the locati on of “ Facilities Using Cooling Water Intake ”. The figure will be replaced with a map showing facility locations within the respondent’s region or in the U.S. for the national version
.  Pages 11
- 14

– Regional references within the table headings in Questi ons 4, 5, and 6 (e.g., “Policy

Effect NE Waters ”, “Option A NE Waters ”) will be modified to refer to the policy effects and options for the respondent’s region. The “Fish Saved per Year” score includes a note reminding the respondent of total fish lost wi thin the region due to I&E (e.g., 1. 1 billion); this number will be changed to reflect total losses within the respondent’s region. The values describing the current situation and Options A and B within experiment questions 4, 5, and 6 will also vary acro ss regions. (II) Respondent activities EPA expects individuals to engage in the following activities during their participation in the contingent valuation survey :
 Review the background information provided in the beginning of the survey document
.  Co mplete the survey

questionnaire and return it by mail
. A ty pical subject participating in the mail survey is expected to take 30 minutes to complete the survey
. These estimates are derived from focus groups and cognitive interviews in which respondents 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, and analyzed by Abt Associates Inc. and is funded b y EPA contract No. EP
- C
- 07
- 023 which provide s funds for the purpose of analyzing the22

economic benefits of the proposed rule for existing facilities subject to the section 316(b) regulation. Agency

activities as sociated with the survey consist of the following:
 Develop the survey

questionnaire and sampling design.
 Printing of questionnaires
.  Telephone screening of respondents.
 Mailing of questionnaires.
 Mailing of postcard reminder s .  Follow
- up with non
- respondent s to the mail survey/resending of questionnaire if needed
.  Data entry

and cleaning of data file.
 Analy sis of survey

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

results. 5(b) Collection Methodology and Information Management To pretest the survey

questionnaire, EPA conduct ed a series of seven focus groups, inc luding one using cognitive interview methodologies under a different ICR (OMB control # 2090
- 0028). Focus groups provided valuable feedback which allowed EPA to iteratively edit and refine the questionnaire, and eliminate or improve imprecise, confusing, and redundant questions. Focus groups and cognitive interviews were conducted following standard approaches in the literature, as outlined b y Desvousges et al. (1984), Desvousges and Smith (1988), Johnston et al. (1995), Schkade and Pay ne (1994), Kaplowic z et al. (2004), and Opaluch et al. (1993). EPA plans to implement the proposed survey as a mail choice experiment questionnaire. First, EPA will use a telephone screener to solicit respondents to receive the mail questionnaire. A dual frame, random di git dial design will be used, including both landline and cell phone numbers. This ensures that even cell
-phone
- onl y households have an opportunity to participate in the survey to reduce potential bias . The telephone screener , shown in Attachment in 6,23

includes not only

an invitation to participate in the mail survey , but also some attitudinal and behavioral questions that are also included in the mail survey , as well as demographic characteristics. EPA will use this information for the non
- response anal ys is to compare respondents and non
- respondents to the mail questionnaire. It is anticipated that approximately 60 percent of respondents to the telephone screener will agree to participate in the mail survey . EPA will then send the mail survey to those who agree to participate, along with a cover letter explaining the purpose of the survey
. All of these respondents will receive a reminder postcard approximately one week after the initial questionnaire mailing. The cover letter and postcard reminder are included as Attachments 7 and 8, respectivel y. 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. Based on this approach to mail data collection, it is anticipated that approximately 40 percent of those who agree to participate in the mail survey will actually

do so. Since the desired number of complete d survey s is 2, 288 , it will be n ecessary to recruit 5, 720 respondents by telephone who agree to participate (Dilman 2000)
. Data quality will be monitored by checking submitted surveys for completeness and consistency , and b y asking respondents to assess their own responses to the survey
. Question 8 asks respondents to rate their understanding of the survey and their confidence in their responses. Questions 7 and 9 are designed to assess the presence or absence of potential response biases by asking respondents to indicate their reasonin g and rate the influence of various factors on their responses to the choice experiment questions
. Responses to the survey will be stored in an electronic database. This database will be used to generate a data set for a regression model of total values for reductions in fish I&E mortality by section 316(b) existing facilities. To protect the confidentiality of survey respondents, the survey

data will be released only after it has been thoroughly vetted to ensure that all potentially identifying informati on has been removed
. Alternativel y, EPA is considering implementing the proposed survey as an internet
based, choice experiment questionnaire. This alternative method is described in Attachment 5
. 5(c) Small Entity Flexibility24

This survey

will be administered to individuals, not businesses. Thus, no small entities will be affected b y this information collection. 5(d) Collection Schedule The schedule for implementation of the survey will be as follows:

Table A 2 : Schedule for Survey Implementation
A ctivity Duration of Each Activity Printing of questionnaires Weeks 1 to 2 Telephone screening of respondents Weeks 1 to 5 Mailing of questionnaires Weeks 3 to 8 Postcard reminder (one week after initial questionnaire mailing) Weeks 4 to 9 Follow
- up 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 Burden an d Cost of Collection 6(a) Estimating Respondent Burden Subjects who participate in the survey and follow
- up interviews will expend time on several activities. Based on the administration of the mail survey to 5, 720 households , the national burden estimat e for all respondents is 1, 938 hours assuming that 9 , 533 households will participate in telephone screening and 2, 288 respondents complete and return the survey , EPA estimates that telephone screening interviews will take 5 minutes (0.08 hours) per inter view for each of the 9,533 screened households. Based on pretests conducted in focus groups, EPA estimates that on average each respondent mail ed the survey will spend 30 minutes reviewing the introductory materials and completing the survey questionnaire . Thus, the average burden per respondent is 30 minutes ( 0. 5 hours) for these 2, 288 respondents.25

These burden estimates reflect a one
- time expenditure in a single year. 6(b) Estimating Respondent Costs According to the Bureau of Labor Statistics, the average hourl y wage for private sector workers in the United States is $ 20.42 ( 2009 $) (U.S. Department of Labor 2009)
. Assuming an average per- respondent burden of 0.08 hours for each of the 9 , 533 screening participants and an average hourl y wage of $20.4 2, the average cost per screening participant is $1.70

. Therefore the total cost to participants in the telephone screening phase would be $ 16 , 223
. Assuming an average per- respondent burden of 0. 5 hours for individuals mail ed the survey and an average ho urly wage of $ 20.42 , the average cost per respondent is $ 10
. 2 1. Of the 5, 720 individuals receiving the mail survey, 2, 288 are expected to return their completed survey
. The total cost for all individuals that return survey s would be $ 23 , 360
. EPA does not anticipate any capital or operation and maintenance costs for respondents. 6(c) Estimating Agency Burden and Costs This project will be undertaken b y Abt Associates Inc. with funding of $ 446,000 from EPA contract EP
- C
- 07
- 023 , which provide s funds for th e purpose of analyzing the economic benefits of the proposed rule for existing facilities subject to the section 316(b) regulation. Abt Associates Inc. staff is expected to spend 1, 155 hours pre
- testing the survey questionnaire and sampling methodology , c onducting the survey , and tabulating and anal yz ing the survey results. The cost of this contractor time is $ 77,000
. Inaddition to the effort expended by EPA’s contractors, EPA staff is expected to spend 320 hours managing and reviewing this project and c ontributing to the analysis at a cost of $ 31,000
. A gency and contractor burden is 1, 475 hours, with a total cost of $ 108,000 excluding the costs of survey printing and mailing and telephone screening
. Telephone screening is expected to take 8 , 400 hours and cost $ 247,000 while m ailing and printing of the survey is expected to take 1 61 hours and cost $ 122,000 , including the cost of survey printing and mailing
. Thus, the total A gency and contractor burden would be 10 , 036 hours and would cost $ 477,000.26

6(d) Respondent Universe and Total Burden Costs EPA expects the total cost for survey respondents to be $ 3 9 , 583 ( 2009 $), based on a total burden estimate of 1, 938 hours and an hourl y wage of $ 20.42
. 6(e) Bottom Line Burden Hours and Costs The following tabl e presents EPA’s estimate of the total burden and costs of this information collection:

Table A3 : Total Estimated BottomLine Burden and Cost Summary Affected Individuals Total Burden Total Cost ( 2009 $) Participants in Telephone Screening 794 hours $ 16 , 223 Mail Survey Respondents 1, 114 hours $ 23 , 360 Total for Survey Respondents 1, 938 hours $ 39 , 583 EPA S taff 320 hours $ 31,000 Telephone Screening 8 , 400 hours $ 247,000 Survey Printing and Mailing 161 hours $ 122,000 EPA’s C ontractors 1, 155 hours $ 77,00 0 Total Burden and Cost 11 , 974 hours $ 516,583 6(f) Reasons for Change in Burden The survey

is a one
- time data collection activity
. 6(g) Burden Statement EPA estimates that the public reporting and record keeping burden associated with the mail surve y will average 0. 5 hours per respondent (i.e., a total of 1, 144 hours of burden divided among 2, 288 survey

respondents). Households included in telephone screening are expected to average 0.08 hours per screening interview participant (i.e., a total of 79 4 hours of burden divided among 9 , 533 screening interview participants )
. This results in a total burden estimate o f27

1, 938 hours including both the telephone screening interview s and mail survey
. Burden means the total time, effort, or financial resources expended by persons to generate, maintain, retain, or disclose or provide information to or for a Federal agency
. This includes the time needed to review instructions; develop, acquire, install, and utilize technology and systems for the purposes of coll ecting, validating, and verifying information, processing and maintaining information, and disclosing and providing information; adjust the existing way s to compl y with any previously applicable instructions and requirements; train personnel to be able to respond to a collection of information; search data sources; complete and review the collection of information; and transmit or otherwise disclose the information. An agency may not conduct or sponsor, and a person is not required to respond to, a collection of information unless it display s a currently valid OMB control number. The OMB control numbers for EPA's regulations are listed in 40 CFR part 9 and 48 CFR chapter 15. To comment on the Agency's need for this information, the accuracy of the provide d burden estimates, and any suggested methods for minimizing respondent burden, including the use of automated collection techniques, EPA has established a public docket for this I CR under Docket ID No. EPA
- HQ
- OW
- 2010
- 0595 , which is available for online vi ewing at www.regulations.gov, or in person viewing at the Office of Water Docket in the EPA Docket Center (EPA/DC), EPA West, Room 3334, 1301 Constitution Ave., NW, Washington, DC. The EPA/DC Public Reading Room is open from 8:30 a.m. to 4:30 p.m., Monday through Friday , excluding legal holidays. The telephone number for the Reading Room is 202
- 566
- 1744, and the telephone number for the Office of Water Docket is 202
- 566
- 1752
. Use www.regulations.gov to obtain a copy of the draft collection of information , submit or view public comments, access the index listing of the contents of the docket, and to access those documents in the public docket that are available electronicall y. Once in the system, select “search,” then key

in the docket ID number , EPA
- HQ
- O W
- 2010
- 0595
.28 PART B OF THE SUPPORTING STATEMENT
1. Survey Objectives, Key Variables, and Other Preliminaries 1(a) Survey Objectives The overall goal of this survey is to explore how public values (including non
- use values) for fish and aquatic organi sms are affected b y I& E mortality at cooling water intake structures (CWI S) located at existing 316(b) facilities, as reflected in individuals’ willingness to pay for programs that would prevent such losses. EPA has designed the survey to provide data to support the following specific objectives:

 To estimate the total values , including non
- use values, that individuals place on preventing losses of fish and other aquatic organisms caused b y CW IS at existing 316(b) facilities.
 To understand how much individ uals value preventing fish losses, increasing fish populations, improvements in aquatic ecos ys tems , and increasing commercial and recreational catch rates.
 To understand how such values depend on the current baseline level of fish populations and fish loss es, the scope of the change in those measures, and the certainty level of the predictions.
 To understand how such values vary with respect to individuals’ economic and demographic characteristics. Understanding total public values for fish resources lost to I&E mortality is necessary to determine the full range of benefits associated with reductions in impingement and entrainment losses at existing 316(b) facilities. Because non
- use values may be substantial, failure to recognize such values may lead to improper inferences regarding policy benefits (Freeman 2003). 1(b) Key Variables The key questions in the survey

ask respondents whether or not they would vote for policies that would increase their cost of living, in exchange for specified changes in : ( a) I&E29

mortality losses of fish, (b ) commercial fish sustainability , ( c ) long
- term fish populations, and ( d) condition of aquatic ecosystems 3 . More specifically, the choice experiment framework allows respondents to view pairs of multi
- attribute policies as sociated with the reduction of I&E mortality losses. Respondents are asked to choose the program that they would prefer, or to choose to reject both policies. This follows well
- established choice experiment methodology and format (Adamowicz et al. 1998; Lo uviere et al. 2000; Bennett and Blamey 2001; Bateman et al. 2002). Important variables in the anal ys is of the choice questions are how the respondent votes, the amount of the cost of living increase, the number of fish losses that are prevented, the sus tainability

of commercial fishing, the change in fish populations, and the condition of aquatic ecos ys tems . Other important variables include whether or not the respondent is a user of the affected aquatic resources, household income, and other respondent demographics. 1(c) Statistical Approach EPA believes that a statistical survey approach is appropriate . A census approach is impractical because contacting all households in the U.S. would require an enormous expense. On the other hand, an anecdotal a pproach is not sufficientl y rigorous to provide a useful estimate of the total value of fish loss reductions for the 316(b) case . Thus, a statistical survey is the most reasonable approach to satisfy EPA’s anal ytic needs for the 316(b) regulation benefit anal ys is. EPA has retained Abt Associates Inc. (55 Wheeler Street, Cambridge, MA 02138) as a contractor to assist in questionnaire design, sampling design, and anal ys is of the survey results. 1(d) Feasibility

3 The environmental attributes to be compared against the cost of living increases where designed based on the Johnston et al. (2009) Bioindicator
- Based Stated Preference Valuation (BSPV) method which wa s developed to promote ecological clarity and closer integration of ecological and economic information within SP studies. In contrast to traditional SP valuation, BSPV employs a more structured and formal use of ecological indicators to characterize and communicate welfare
- relevant changes. It begins with a formal basis i n ecological science, and extends to relationships between attributes in respondents’ preference functions and those used to characterize policy outcomes. Specific BSPV guidelines ensure that survey scenarios and resulting welfare estimates are characteriz ed by: (1) a formal basis in established and measurable ecological indicators, (2) a clear structure linking these indicators to attributes influencing individuals’ well
-being, (3) consistent and meaningful interpretation of ecological information, and (4) a consequent ability to link welfare measures to measurable and unambiguous policy outcomes. The welfare measures provided by BSPV method can be unambiguously linked to models and indicators of ecosystem function, are based on measurable ecological outcomes, and are more easily incorporated into benefit cost analysis. This methodology was developed in part to address the EPA Science Advisory Board’s call for im proved quantitative linkages between ecological services and economic valuation of those service s.30

The survey

instrument was repeatedl y pre - te sted during a series of seven focus groups (conducted under a different I CR with OMB control # 2090
- 0028) , in addition to the twelve focus groups conducted for the Phase III survey ( EPA
- HQ
- OW
- 2004
- 0020 ) , and it will be subject to peer review b y reviewers in academia and government, so EPA does not anticipate that respondents will have difficulty interpreting or responding to any of the survey

questions. Additionally , since the survey will be administered as a mail survey , it will be easil y accessible to re spondents. Thus, EPA believes that respondents will not face any obstacles in completing the survey , and that the survey will produce useful results. EPA has dedicated sufficient funding (under EPA contracts No. EP
- C
- 07
- 23 ) to design and implement the survey . Given the timetable outlined in Section A.5(d) of this document, the survey results will be available for timel y use in the final benefits anal ys is for the 316(b) existing facilities rule.
2. Survey Design 2(a) Target Population and Coverage
The t arget population for this survey includes individuals from continental U.S. households who are 18 years of age or older. The sample will be chosen to reflect the demographic characteristics of the general U.S. population. 2(b) Sampling Design (I) Sampling Frames The sampling frame for this survey is the panel of individuals recruited by random digit dialing ( over- lapping dual frame; land and cell) to participate in a mail survey
. The overall sampling frame from which these individuals would be selected is the set of all individuals in continental U.S. households who are 18 ye ars of age or older and who have listed phone numbers. Individuals in the panel are recruited using a list
- assisted random digit dialing telephone methodology , thus providing a prob ability
- based starting sample of U.S. telephone households. The telephone screening will use an overlapping dual frame design of landline and cell phone numbers to increase the coverage of the sample. The inclusion of cell phone numbers will allow EPA t o reach potential respondents who only have cell phones and would be missed if31

only a sample of landlines was selected. The dual frame design also avoids bias because the cell
phone
- onl y population skews heavil y towards lower
- income 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 likel y to be chosen for the survey
. All landline respondents to the telephone screener will be asked the number of eligible respondents in their household and every respondent (cell and landline) will be asked whether they have a landline only , a cell phone onl y, or both. Next, the survey data will be weighted to match national data (U.S. Census and National Health Interview Survey) b y a set of demographic variables (e.g., age and gender) as well as phone usage (cell
- only users, landline
- only

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

would be implemented. For discussion of techniques that EPA will use to minimize non
- response and other non
sampling errors in the survey sample, refer to Section 2(b)(II), bel ow. (II) Sample Sizes The intended sample size for the survey is 2 , 288 households including onl y households providing completed mail surveys. This sample size was chosen to provide statistically robust regression results while minimizing the cost and burden of the survey . Given this sample size, the level of precision (see section 2(c)) achieved by the anal ys is will be more than adequate to meet the anal ytic needs of the benefits anal ys is for the 316(b) regulation. For further discussion of the level o f precision required by this anal ys is, see Section 2(c)(I) below.

(III) Stratification Variables32

The survey

sample will be selected using a stratified selection process . For the selection of households, the population of households in the contiguous 48 states and the District of Columbia will be stratified by the geographic boundaries of four study regions : Northeast , Southeast , Inland , and Pacific. As de sc ribed previously , the Northeast region includes the North Atlantic and Mid Atlantic 316(b) benefi ts regions , the Southeast region includes the South Atlantic and Gulf of Mexico 316(b) benefits regions , the Pacific region includes states on the Pacific coast, and the Inland region includes all non
- coastal states. The sample is allocated to each region in proportion to the total number of households in that region , with at least 288 completed surveys in each region. This is the number required to estimate the main effects and interactions under an experimental design model as described in Section 4(a) o f Part A
. To accommodate this requirement the sample sizes in other regions will be slightly reduced. A sample of 288 households completing the national survey version would be distributed among the study regions based on the percentage of regional survey sample (as shown in Table A1) to ensure that respondents to the national survey version are distributed across the continental U.S. (IV) Sampling Method Using the stratification design discussed above, respondents will be randomly selected
. First, a larger sample of households will be selected through random digit dialing in each of the 4 regions. The household to which the selected telephone number belongs will be called and the respondent will be asked whether he or she is willing to provide information required b y the survey . If the person in the household agrees, then a questionnaire will be mai l ed to that household. If it is assumed that 40 % of the households which agreed to provide information actuall y return a completed mail survey (completion rate) then 5, 720 questionnaires will need to be mailed to households. 4 If we assume that 60% of the households that are called say “yes” they

are willing to receive a questionnaire (the screening response rate) , then we need to screen 9 , 533 households. A dual frame random digit dialing design , including both landline and cell phone numbers , will be used for telephone screening
. If we assume that 40 % of the households called will participate in the telephone screener , then we will need to call 23 , 833 numb ers. The actual number of telephone number s selected through random digit dialing sampling will be larger than the

4 The assumed response rate is based on a similar stated preference studies conducted by Johnston et al. (2010) in the Northeast U.S. Actual response rates could vary across study regions.33

number of households called. This is because we are expecting that 40% of the telephone numbers initially

selected will be screened out as non - working or business numbers. Therefore the actual number of telephone numbers selected will be around 39 , 722
. The quantity of telephone numbers that we need to select in each region can be obtained by allocating the total number in proportion to the total households in that region. For obtaining population
- based estimates of various parameters, each responding household will be assigned a sampling weight. This weight combines a base sampling weight which is the inverse of the probability of selection of the household and then an adjustment for non - response. The weights will be used to produce estimates that are generalizable to the population from which the sample was selected (e.g., percent of population participating in water- based recreation such as fishing and shellfishing). Proportional allocation of the sample to regions ensures an equal probability sample. T o estimate total WTP for the quantified environmental benefits of the 316(b) existing facilities rulemaking data will be anal yz ed statisti cally using a standard random utility model framework. (V ) Multi

- Stage Sampling
Multi
- stage sampling will not be necessary for this survey
. 2(c) Precision Requirements (I) Precision Targets Table B1, below, shows the target samples sizes for both the U.S. (excluding A laska and H awaii ) and each of the four EPA study regions
. At the regional level , a sample of 2,000 households (complete d survey s ) will provide estimates of population percentages with a margin of error ranging from 3.6 to 5.8 percentage p oints at the 95% confidence level. A sample of 288 household for the national survey version (completed survey s) will provide an estimate of population percentages with a margin of error no greater than 5.8 percentage points at the 95% confidence level.34

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

Region Household Population Household Sample Northeast 23,281,296 417 Southeast 31,378,122 562 Inland 40,852,983 732 Pacific 16,158,206 288 T otal for Regional Survey Vers ions 111,670,607 2,000 National Survey Version 111,670,607 288 Source: The number of households in each region was obtained based on the estimated population size and average household size from the 200 6
- 200 8 American Community Survey (ACS)
. (II) Non -

S ampling Errors One issue that may

be encountered in stated preference surveys is the problem of protest responses. Protest responses are responses from individuals who reject the survey format or question design, even though they may value the resources being considered (Mitchell and Carson 1989). For example, some respondents may feel that any

amount of I&E is unacceptable, and choose not to respond to the survey . To deal with this issue, EPA has included several questions, including an open
- ended comm ents section, to help identify protest responses. The use of such methods to identify protest responses is well
- established in the literature (Bateman et al. 2002). Moreover, many researchers (e.g., Bateman et al. 2002) suggest that a choice experiment f

ormat, such as that proposed here, may ameliorate such responses (over the earlier contingent valuation format)
. A different ty

pe of non
- sampling error is non
- response bias . Non
- response rates in this survey are affected by non - response at each stage of s ampling. There are two ty pes of non respondents to this survey : respondents unwilling to complete a questionnaire when initially contacted b y phone and respondents who agree but do not complete the questionnaire. EPA will conduct several additional activ ities to minimize the potential for non - response bias in the current survey :35

(1) The telephone interviews will be conducted b y 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 maximize response. A mail survey will be sent to all those who agree to participate. Then, one week later, a postcard reminder will be sent. Three weeks later, a second cop y of the ques tionnaire with a revised cover letter will be sent to non
- respondents. As final follow
- up, another postcard reminder will be sent one week later. (3) Response rates will be tracked on a dail y basis for both the telephone screener and mail survey . If any

unexpected declines are encountered, corrective action can immediately

be undertaken. (4) EPA will undertake non
- response bias anal ys is as detailed in the following section. If necessary , EPA will use appropriate weighting or other statistical adjustment to corre ct the bias because of non
- response . Non

- response Interviews To determine whether there is any evidence of significant non
- response bias in the completed sample , EPA will compare the characteristics of the completed and non
- completed cases from the random digit dialing sample. There are two main stages of non
- response: non response to the telephone survey and non
- response to the mail survey
. To assess the potential for telephone non
- response bias, EPA will collect sample characteristics in the course of th e telephone survey as follows: (1) prior to household contact, (2) at respondent selection for the survey , and (3) after beginning the interview. EPA will then anal yz e the data available for respondents and non
- respondents prior to household contact and at respondent selection. Because the telephone instrument is very short, we do not expect many people prematurel y terminating the call after the selected household member has started the interview. The drawn sample of random digit dialing numbers from the l andline frame that are released to telephone interviewers for contact attempts can be coded for certain contextual characteristics. The “hundreds bank” from which the RDD number is drawn (e.g., 301
- 608
- 38xx) is classified geographicall y 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 EPA36

region, State, and urbanicity (central city , metro remainder, and non
- metropolitan area). It also permits us to classify

those numbers by

demographic characteristics, such as percentage of African
- American and Hispanic, based on Census data linked to telephone exchanges. EPA will compare the characteristics of all dialed residential numbers in which an interview had not been completed with those that had been completed using these variables to determine whether non
response bias is present
. Once contact is achieved with a household, one adult is selected in each household as the designated respondent. If there is more than o ne eligible respondent per household, then a random selection is done for the individual with the most recent/next birthday
. EPA will identify the age and gender of this individual if callbacks are necessary. This information permits additional compariso ns of any differences in the age and gender of respondents in the completed sample and those in the non
- completed sample after household contact and respondent selection have been made. The telephone screener includes not only an invitation to participate in the mail survey , but also some attitudinal (relative importance of various government activities) differences and behavioral differences (recreational activities), as well as demographic characteristics (see Attachment 6 for detail) . EPA will use the t elephone screening data to compare mail survey respondents and non
- respondents. The items of information collected during telephone screening will help determine the ty pe of person that is likely to not respond to the survey and may help in forming weighting classes for adjusting weights of respondents to account for non - response and minimize the bias because of non
- response. 2(d) Questionnaire Design The information requested by the survey

is discussed in Section 4(b)(I) of Part A of the supporting stat ement. The full text of the draft questionnaire for the Northeast region is provided in Attachment 1 and the full text of the draft questionnaire for the national survey version is provided in Attachment 2
. The following bullets discuss EPA’s reasons fo r including the questions in the survey :
 Relative Importance of Issues Associated with Industrial Cooling Water . EPA included this section to prepare respondents to answer the stated preference questions by37

motivating respondents to consider the relative importance of key issues associated with the use of cooling water by industrial facilities.
 Concern for Policy Issues. EPA included this section to prepare respondents to answer the stated preference questions by motivating respondents to think about the relative importance of different policy issues.
 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 for reminders if necessary
.  Voting for Regulations to Prevent Fish Losses in the Respondent’s Region (or N ationally) . The questions in this section are the key part of the survey . Respondents’ choices when presented with specific fish
- related resource changes within their region and household cost increases are the main data that allow estimation of willingness
- to pay . The questions are presented in a choice experiment (A, B , or neither) format because this is an elicitation format that has been successfull y used b y a number of previous valuation studies (Adamowicz et al. 1998; Bateman et al. 2002; Bennett and Blamey 2001; Louviere et al. 2000; Johnston et al. 2002a, 2005; Op aluch et al. 1993). Furthermore, many focus group participants indicated that they have some previous experience making choices within a framework in which they are asked to vote for one of a series of options, and are comfortable with this format.
 Reason s for Voting “No Policy” . This question provide s information that will be used by EPA to identify

protest responses
.  Respondent Certainty and Reasons for Voting . This section is designed to identify respondents who incorrectly interpreted the choice questions o r the uncertainty of outcomes
. Responses to these questions are important to successfull y control for hy pothetical bias.
 Recreational Experience. This question elicit s recreational experience data to test if certain respondent characteristics inf luence responses to the referendum questions. This question will also allow EPA to identify resource non - users, for purposes of estimating non - user WTP (to gauge the relative importance of non
- use values to overall benefits)
.  Demographics. Responses to these questions will be used to estimate the influence of demographic variables on respondents’ voting choices, and ultimately , their WTP to38

prevent I&E mortality losses of fish. This information will allow EPA to use regression results to estimate WTP for populations in different regions affected b y the 316(b) rule for existing facilities.
 Comments. This section is primarily intended to help identify protest responses, i.e. responses from individuals who rejected the format of the survey or the way the qu estions were phrased.
3. Pretests and Pilot Tests
EPA conduct ed extensive pretests of the survey instrument during a set of seven focus groups (EPA I CR # 2090
- 0028 ) , in addition to the twelve focus groups conducted for the Phase III survey . These focus groups included individual cognitive interviews with survey respondents (Kaplowicz et al. 2004), and think
- aloud or verbal protocol anal ys es (Schkade and Pay ne 1994). Individuals in these focus groups completed draft survey questionnaires and provide d comments and feedback about the survey format and content, their interpretations of the questions, and other issues relevant to stated preference estimation. Particular emphasis in these survey pretests was on testing for the presence of potential biases ass ociated with poorl y- designed stated preference surveys, including hy pothetical bias, strategic bias, s ymbolic (warm glow) bias, framing effects, embedding biases, methodological misspecification, and protest responses (Mitchell and Carson 1989). Based on focus group and cognitive interview responses, EPA made various improvements to the survey questionnaire including changes to ameliorate and minimize these biases in the final survey instrument
.

4. Collection Methods and Follow - up 4(a) Collection Method s The survey

will be administered as a mail survey . Respondents identified by random digit dialing who agree to participate will be mailed a cop y of the survey questionnaire. Re spondents will be asked to mail the completed survey back to EPA.39

4(b) Su rvey Response and Follow - up The target response rate for the mail survey is 40 percent . That is, 40 percent of households which agreed to par ti cipate in the mail survey are expected to return a completed survey . However, the actual response rate compare d to the general population is lower, given that the telephone screening process is expected to have a response rate of 6 0 percent among contacted households. The resolution rate (determining the status of a telephone number), the screener response rate and the survey completion rate will contribute to the overall response rate in the survey . The actual number of telephone numbers selected for inclusion will be much larger to account for the exclusion of non
- working and business numbers. The number of te lephone numbers needed for selection in each region can be obtained b y allocating the total number in proportion to the number of households in that region. To improve the response rate, all of these respondents will receive a reminder postcard approximat ely

one week after the initial questionnaire mailing. Then, approximately three weeks after the reminder postcard, all those who have not responded will receive a second cop y 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 households in the contiguous 48 states and the District of Columbia will be stratified by the geographic boundaries of four EPA study regions. In addition, EPA will administer a national version of the survey that does not require stratification. We will keep track of the response rates for each of regional survey s and the national version of the survey to ensure that the rates are reasonable. We will also look at the frame characteristics of non - respondents to determine if there are any substantial biases in the estimates because of an imbalance in the distribution of 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 are returned . Af

ter all responses have been entered ,40

the database contents will be converted into a format suitable for use with a statistical anal ys is software package. The mail survey , database management, and data set conversion will be conducted b y Abt Associates Inc
. All survey

responses will be vetted for completeness. Additionally, respondents’ answers to the choice experiment questions will be tested to ensure that they are internall y consistent with respect to scope and other expectations of neoclassical preference theory , such as transitivity
. Responses which satisfy

transitivity

exhibit relational relationships when separate choices among policy options are compared. For example, if values for policy 1 are greater than policy 2 , and values for policy 2 are gr eater than Policy 3 , then values for policy 1 should also be greater than values for Policy 3
.
5(b) Analysis Once the survey

data has been converted into a data file, it will be anal yz ed using statistical analysis techniques. The following section dis cusses the model that will be used to anal yz e the stated preference data from the survey
. Analysis of Stated Preference Data The model for anal ys is of stated preference data is grounded in the standard random utility model of Hanemann (1984) and McConnel l (1990). This model is applied extensively within stated preference research, and allows well
- defined welfare measures (i.e., willingness to pay) to be derived from choice experiment models (Bennett and Blamey 2001; L ouviere et al. 2000). Within the standard random utility model applied to choice experiments, hy pothetical policy alternatives are described in terms of attributes that focus groups (Johnston et al. 1995; Adamowicz et al. 1998; Opaluch et al. 1993) reveal as relevant to respondents’ utility, or well
being. One of these attributes would include a mandatory monetary

cost to the respondent’s household. Applying this standard model to choices among policies to reduce I&E mortality losses, EPA defines a standard utility function U

i ( . ) that inc ludes environmental attributes of an I&E reduction plan and the net cost of the plan to the respondent. Following standard random utility41

theory , utility

is assumed known to the respondent, but stochastic from the perspective of the researcher, such that (1) U i ( . ) = U(X i , D , Y
- F i ) = v(X i , D , Y
- F i ) + ε i where: X i = a vector of variables describing attributes of I&E reduction plan i ; D = a vector characterizing demographic and other attributes of the respondent. Y = disposable income of the respondent. F i = mandatory

additional cost faced b y the hous ehold under plan i ; v( . ) = a function representing the empiricall y estimable component of utility ; ε i = stochastic or unobservable component of utility , modeled as an econometric error.
Econometricall y, a model of such a preference function is obtained b y methods designed for limited dependent variables, because researchers only observe the respondent’s choice among alternative policy

options, rather than observing values of U i (.) directly

(Maddala, 1983; Hanemann, 1984). Standard random utility models 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 b y the respondent. Inthis case, the respondent’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 plan that would offer the highest utility
. When faced with k distinct plans defined by their attributes, the respondent will choose plan i if the anticipated utility from plan i exceeds that of all 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(Xk , D , Y
- F k) + εk)  k≠i
. If the ε i are assumed independently and identicall y drawn from a type I extreme value (Gumbel) distribution, the model may be estimated as a conditional logit model, as detailed b y Maddala (1983), Greene (2003) an d others. This model is most commonly used when the respondent considers more than two options in each choice set (e.g., Plan A, Plan B, Neither42

Plan), and results in an econometric (empirical) estimate of the systematic component of utility v( . ) , based o n observed choices among different policy plans. Based on this estimate, one may calculate welfare measures (willingness to pay) following the well
- known methods of Hanemann (1984), as described b y Freeman (2003) and others. Following standard choice experiment methods (Adamowicz et al. 1998; Bennett and Blamey 2001), each respondent will consider questions including three potential choice options (i.e., Plan A, Plan B, Neither Plan)

—choosing the option that provides the highest utility as noted above. Fo llowing clear guidance from the literature, a “neither plan” or status quo option is always included in the visible choice set, to ensure that WTP measures are well
- defined (Louviere et al. 2000). EPA also anticipates that respondents will consider more 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 valuation surveys (Poe et al. 1997; L ay

ton 2000). While respondent s will be instructed to consider each choice question as independent of other choice questions , it is nonetheless standard practice within the literature to allow for the potential of correlation among questions answered within a single survey by a single respondent. That is, responses provided by individual respondents may be correlated even though responses across different respondents are considered independent and identically distributed (Poe et al. 1997; L ay ton 2000; Train 1998). There are a variety of approaches to such potential correlation. Following standard practice, EPA anticipates the estimation of a variety of models to assess their performance. Models to be assessed include random effects and random parameters (mixed) discrete choice mode ls, now common in the stated preference literature (Greene 2003; McFadden and Train 2000; Poe et al. 1997; L ay ton 2000). Within such models, selected elements of the coefficient vector are assumed normally distributed across respondents, often with free c orrelation allowed among parameters (Greene 2002). If onl y the model intercept is assumed to include a random component, then a random effects model results. If both slope and intercept parameters may vary across respondents, then a random parameters mode l is estimated. EPA anticipates that such models will be estimated using standard maximum likelihood for mixed conditional logit techniques , as described by Train (1998), Greene (2002) and others. Mixed logit m odel performance of alternative specificatio ns will be assessed by EPA using standard statistical measures of model fit and convergence, as detailed by Greene (2002 , 2003) and Train (1998).43

Advantages of Choice Experiments Choice experiments following the random utility model outlined above are favored b y many researchers over other variants of stated preference methodology (Adamowicz et al. 1998; Bennett and Blamey

2001), and may

be viewed as a “natural generalization of a binary discrete choice CV [contingent valuation] ” (Bateman et al. 2002, p. 271). Advantages of choice experiments include a capacity to address choices over a wide array of potential policies, ground ed in well
- developed random utility theory, and the similarity of the discrete choice context to familiar referendum or voting form ats (Bennett and Blamey 2001). Compared to other ty pes of stated preference valuation, choice experiments are better able to measure the marginal value of changes in the characteristics or attributes of environmental goods, and avoid response difficulties and biases (Bateman et al. 2002). For example, choice experiments may reduce the potential for ‘yea - saying’ and s ymbolic biases (Blamey et al. 1999; Mitchell and Carson 1989), as many pairs of multi
- attribute policy choices (e.g., Plan A, Plan B, Neither) will offer no clearly

superior choice for a respondent wishing to express solely sy mbolic environmental motivations. For similar reasons choice experiments may ameliorate protest responses (Bateman et al. 2002). An additional advantage of such methods is that they permit straightforward assessments of the impact of resource scope and scale on respondents’ choices. This will enable EPA to easily conduct scope tests and other assessments of the validity of survey responses (Bateman et al. 2002, p. 296
- 34 2). Finall y, such methods are well
- established in the stated preference literature (Bennett and Blamey 2001). Additional details of choice experiment methodology (also called choice modeling) are provided b y Bennett and Blamey (2001), Adamowicz et al. (1 998), Louviere et al. (2000) and many other sources in the literature. An additional advantage of choice experiments in the present application is that they are commonly

applied to assess WTP for ecological resource improvements of a ty pe quite similar to those at issue in the 316(b) policy case. Examples of the application of choice experiments to estimate WTP associated with changes in aquatic life and habitat include Hoehn et al. (2004), Johnston et al. (2002b), and Opaluch et al. (1999), among others . EPA has drawn upon these and other examples of successful choice experiment design to provide a basis for survey design in the present case. A final key

advantage of choice experiments in the present application is the ability to estimate respondents ’ W TP for a wide range of different potential outcomes of 316(b) policies, differentiated b y their attributes. The proposed choice experiment survey versions will allow44

different respondents to choose among a wide variety of hyp othetical policy

options, some with larger and other with very small changes in the presented attributes (annual fish losses, long
- term fish populations, recreational and commercial catch, ecos ys tem condition, and household cost). That is, because the survey is to be implemented as a choice experiment survey , levels of attributes in choice scenarios will vary across respondents (Louviere et al. 2000). The experimental design will also explicitly allow for variation in baseline population and harvest levels, following standard practice in the literature (Louviere et al. 2000; Bateman et al. 2002). Aside from providing the capacity to estimate WTP for a wide range of policy outcomes, it also frees EPA from having to predetermine a single policy outcome for which WTP will be estimated. Given the potential biological uncertainty involved in the 316(b) policy case, the ability to estimate values for a wide range of potential outcomes is critical. The ability

to estimate WTP for a wide range of different policy outcomes is a fundamental property of the choice experiment method (Bateman et al. 2002; Louviere et al. 2000; Adamowicz et al. 1998). For the purpose of stated preference survey implementation , EPA will use four geographic regions: Northeast, Southeast, Inland, and Pacific. The No rtheast regional survey

is included in this I CR as Attachment 1. In addition, EPA will administer a national version of the survey that is included as Attachment 2. EPA emphasizes that the survey version s included in this ICR are for illustration only ; they are but two of what will ultimately be a large number of different survey versions covering a wide range of potential policy outcomes as described in Attachment 4
. The experimental design (see below) will allow for survey versions showing a range of di fferent baseline and resource improvement levels, where these levels are chosen to (almost certainl y) bound the “actual” levels. Given that there will almost certainl y be some biological uncertainty regarding 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. Additional details on the statistical (experimental) design of the choice experiment is provided in later sections of this IC R
.
Comment on Survey Preparation and Pretesting Following standard practice in the stated preference literature (Johnston et al. 1995; Desvousges and Smith 1988; Desvousges et al. 1984; Mitchell and Carson 1989), all survey elements and methods were s ubjected to extensive development and pretesting in focus groups to45

ameliorate the potential for survey biases (cf. Mitchell and Carson 1989), and to ensure that respondents have a clear understanding of the policies and goods under consideration, such that informed choices may

be made that reflect respondents’ underl ying preferences. Following the guidance of Arrow et al. (1993), Johnston et al. (1995), and Mitchell and Carson (1989), focus groups were used to ensure that respondents are aware of their budget constraints, the scope of the resource changes under consideration, and the availability of substitute environmental resources. As noted above, survey

pretests included individual cognitive interviews with survey respondents (Kaplowicz et al. 2004), and think
- aloud or verbal protocol analy ses (Schkade and Pay ne 1994). Individuals in these pretests completed draft survey questionnaires and provided comments and feedback about the survey format and content, their interpretations of the questions, and other issues relevant to stated preference estimation. Based on their responses, EPA made improvements to the survey questionnaire. Of particular emphasis in these survey pretests was testing for the presence of potential biases including hypothetical bi as, strategic bias, sy mbolic (warm glow) bias, framing effects, embedding biases, methodological misspecification, and protest responses (Mitchell and Carson 1989). Based on focus group and cognitive interview responses, EPA made various improvements to the survey questionnaire including changes to ameliorate and minimize these biases in the final survey instrument. Results from focus groups and cognitive interviews provided evidence that respondents answer the stated preference survey

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

— applying the most state
- of
- the
- art methods available in the literature

—EPA believes that survey design far exceeds standards that are ty pical in the published literature. The details of focus groups conducted for the previous Phase III survey are discussed b y EPA in a prior ICR (#2155.01 ).46

Econometric Specification Based on prior focus groups, exp ert review, and attributes of the policies under consideration, EPA anticipates that four attributes will be incorporated in the vector of variables describing attributes of an I&E reduction plan (vector X i), in addition to the attribute characterizing unavoidable household cost F i . 5 These attributes will characterize the annual reduction in I&E losses (

x 1 ), anticipated effects on fish populations (all fish) ( x2 ), anticipated effects on commercial fish populations ( x 3 ) , and anticipated effects on aquatic ecos ys tem condition (

x4 ) . These variables will allow respondents’ choices to reveal the potential impact of both annual fish losses and long
- term population effects on utility . Based on results of focus groups and expert opinion, these will be presented as averages across identified aggregate species groups. The survey will also allow for changes in baseline population levels, to assess whether WTP depends on the “starting point” of fish populations. Although the literature offers no firm guidance 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 applying more flexible (e.g., quadratic) forms (Cummings et al. 1994). Standard linear forms are anticipated as the simplest form to be estimated by

EPA, from which more flexible functional forms (able to capture interactions among model variables) will be derived and compared. Anticipated extensions to the simple linear model in clude more fully
- flexible forms that allow for s ys tematic variations in slope and intercept coefficients associated with demographic or other attributes of respondents. Such variations may

be incorporated b y appending the simple linear specification with quadratic interactions between variables in vector D and the variables X i and F i (cf. Johnston et al. 2003b). One may also incorporate quadratic interactions between policy attributes X i and F i , (cf. Johnston et al. 2002b). Such quadratic extensions of the basic linear model allow for additional flexibility in modeling the relationship between policy attributes (including cost) and utility , as suggested b y Hoehn (1991) and Cummings et al. (1994). EPA anticipates estimating both simple linear specifications, as well as more full y- flexible quadratic specifications following Hoehn (1991) and Cummings et al. (1994), to identify those models which provide the most satisfactory statistical fit to the data and correspondence to theory . EPA anticipates estimating all models

5 EPA plans to complete focus group testing of the instrument before the second Federal Register notice of this information collection request. The inclusion of all four attributes is an important aspect of focus group testing. If focus groups find this number cognitively challenging, the number will be reduced, and if cognitive issues are minimal as identified by randomly selected focus group participants, all four will remain.47

within the mixed logit framework outlined above. Model fit will be assessed following standard practice in the literature (e.g., Greene 2003; Maddala 1983). Linear and quadratic functional forms discussed here, as they are common practice in the literature, are presented and discussed in many existing sources (e.g., Hoehn 1991, Cummings et al. 1994, Johnston et al. 1999, and Johnston et al. 2003b). For example, for each choice occasion, the respondent may choose Option A, Option B, or Neither, where “neither” is characterized by 0 values for all attributes (except Baseline population levels). Assuming that the model is estimated using a standard approximation for the observable component of utility, an econometric specification of the desired model (within the overall multinomial logit model) might appear as: v(  ) =  0 +  1 (Fish Saved ) +  2 ( Change in Population s of All Fish ) +  3 ( Change in Commercial Fish Population s ) +  4 ( Change in Condition of Aquatic Ecosystem ) +  5 (Cost) +  6 ( Fish Saved

)(Baseline) + 

7 ( Change in Populations of All Fish )(Baseline) + 

8 ( Change in Commercial Fish Populations )(Baseline) + 

9 (Change in Aquatic Ecosystem)(Baseline) +  10 (Cost)(Baseline) +  11 (Fish Saved)(

Change in Populations of All Fish ) +  12 (Fish Saved)( C hange in Commercial Fish Populations ) +  13 (Fish Saved)(Change in Aquatic Ecosystem) + 

14 ( Change in Populations of All Fish )( Change in Commercial Fish Populations ) +  15 ( Change in Populations of All Fish )(Change in Aquatic Ecosystem) +  16 (Change in Commercial Fish Populations )(Change in Aquatic Ecosystem)
Main effects are in bold. Interactions are in italics. This sample specification

—one of many to be estimated b y EPA

—allows one to estimate the relative “main effects” of policy attributes (annual red

uction in I&E losses, long
- term effects on populations of all fish , long
- term effects on commercial fish populations ) on utility, effects on aquatic ecosy stem condition, as well as interactions between these main effects. This specification also allows EP A to assess the impact of baseline fish populations on the marginal value of changes in other model attributes. In sum, specifications such as this allow WTP to be estimated for a wide
- range of potential policy outcomes, and allow EPA to test for a wide
- range of main effects and interactions within the utility function of respondents. Such flexible utility specifications for stated preference estimation are recommended by numerous sources in the literature, including Johnston et al. (2002b), Hoehn (1991), and Cummings et al. (1994), and follow standard practice in choice modeling outlined b y Lo uviere et al. (2000) and others. Experimental Design48

Experimental design for the choice experiment surveys will follow established practices. Fractional factorial design will be used to construct choice questions with an orthogonal array of attribute levels, with questions randomly divided among distinct survey versions (L ouviere et al. 2000). Based on standard choice experiment experimental design procedures (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 experimental design and complexity of questions, b ) the extent to which estimation of interactions and high er- level effects is desired, and c ) pretests revealing the number of choice experiment questions that respondents are willing/able to answer in a single survey

session, and the number of attributes that may be varied within each question while maintaining respondents’ ability to make appropriate neoclassical tradeoffs. Based on the models proposed above and recommendations in the literature, EPA anticipates an experimental design that allows for an ability to estimate main effects, quadratic effects, and two - way

interactions between policy attributes (Louviere et al. 2000). Choice sets (Bennett and Blamey

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

question) includes two choice Options (A and B), characterized by four attributes and a cost variable that vary across the two choice options ( Commercial Fish Populations , Fish Populations (all fish) , Fish Saved per Year, Condition o f Aquatic Ecos ys tems, and Increase in Cost of Living of Your Household). Hence, there are a total of ten attributes for each treatment. Based on focus groups and pretests, and guided b y realistic ranges of attribute outcomes, EPA allows for three different potential levels for Commercial Fish Populations, Fish Population s (all fish) , Fish Saved per Year, and Condition of Aquatic Ecosystems , and allows for six different levels of annual Household Cost for the regional or national choice questions. The49

sur vey versions also include two separate treatments of location, or geographic scope; the first version refers to policies only within the respondent’s region and the second version refers to national policies. The number of combinations for each attribute may be summarized as follows:  LocationA , LocationB (2 levels)  Commercial Fish Populations A , Commercial Fish Populations B (3 levels)  Fish Population s (all fish) A , Fish Population s (all fish) B (3 levels)  Fish Saved per YearA , Fish Saved per YearB ( 3 levels)  Condition of Aquatic Ecosystems A , Condition of Aquatic Ecos ys tems B ( 3 levels )  CostA, CostB ( 6 levels ) Be yond the levels specified above, each question will include a “no policy” option, characterized by baseline levels for each attribute including a household cost of $0. Following standard practice, EPA constrained the design somewhat in response to findings in seven focus groups and the prior literature. For example, the focus groups showed that respondents react negativel y and oft en protest when offered choices in which one option dominates the other in all attributes. Given that such choices provide negligible statistical information compared to choices involving non
- dominant/dominated pairs, they are typically avoided in choice experiment statistical designs. For example, Hensher and Barnard (1990) recommend eliminating profiles including dominating or dominated profiles, because such profiles generall y provide no useful information. Following this guidance, EPA constrained the design to eliminate such dominant/dominating pairs. EPA also constrained the design to eliminate the possibility

of pairs in which, when looking across two options, one of the options offers both a greater reduction in fish losses and a smaller increase 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 characterized by 72 unique A vs . B option pairs, where attribute levels for option A and B differ across each of the pairs. Each pair represents a unique choice modeling question

— with a unique set of attribute levels distinguishing options A and B. Following standard practice for mail survey s, these questions will be randoml y assigned to survey respondents, with each respondent considering three questions. Information Provision50

According to Arrow et al. (1993, p. 4605), if “survey s are to elicit useful information about willingness to pay , respondents must understand exactly what it is they

are being asked to value.” It is also well known that the provided information can influence WTP estimates derived from stated preference survey instruments and that respondents must be provided with sufficient information to make an informed assessment of policy impacts on utility

(e.g., Bergstrom and Stoll 1989; Bergstrom et al. 19 8 9 ; Hoehn and Randall 2002). As stated clearly by Bateman et al. (2002, p. 122), “[d]escribing the good and the pol icy context of interest may

require a combination of textual information, photographs, drawings, maps, charts and graphs. ...[V]isual aids are helpful ways of conveying complex information...while simultaneously enhancing respondents’ attention and interest.” Given that many respondents may

not be fully

familiar with the details of programs to reduce I&E mortality losses and potential impacts on aquatic life, the survey will include introductory figures to aid respondents’ comprehension of the goods and polici es addressed b y the survey instrument, and to encourage appropriate neoclassical tradeoffs in responding to choice experiment questions. Following this guidance of Bateman et al. (2002) and prior examples of Opaluch et al. (1993) and Johnston et al. (2002 a), among others, EPA extensively pretested all graphics used in the draft mail survey , to ensure that these graphical elements were not prejudicial, and that they did not bias responses. Graphics judged to be prejudicial or confusing to respondents durin g the seven focus groups and cognitive interviews were revised or replaced. EPA acknowledges that certain types of graphics can be prejudicial in certain contexts

—and hence all graphical elements were pretested extensively
. EPA found that focus group resp ondents endorsed the use of graphics in the survey

booklet and indicated that they helped them to visualize how fish are entrained and impinged, technological solutions, facilities locations, and ecosy stem effects. Participants made such statements as , “Y eah, I’d rather have them” and “I like on page 2 the graph and illustration because the adage a picture is worth a thousand words”. EPA also emphasizes that there is no precedent or support in the literature for the total elimination of graphics in survey instruments. To the contrary , the literature explicitly indicates that pictures and graphics may

be necessary

and useful components of survey instruments in many

cases (Bateman et al. 2002). EPA highlights that numerous peer
- reviewed surveys described in the literature include pictures and graphics both in survey instruments and in introductory materials such as slide shows. For example, see Horne et al. (2005), Ready et al. (1995), Powe and Bateman (2004) , Duke and Ilvento (2004), Opaluch et al. (1993) , Johnston et al. (1999, 2002a,51

2002b), and Mazzotta et al. (2002). Bateman et al. (2002) also includes examples of various ty pes of survey

materials including pictures and graphical elements. Amelioration of Hypothetical Bias EPA considers the amelioration of hypothetical bias to be a paramount concern in survey design. However, the agency acknowledges

— based on prior evidence from the literature

—that hy pothetical bias is not unavoidable. For example, not all research finds evidence of hy pothetical bi as in stated preference valuation (Champ and Bishop 2001; Smith and Mansfield 1998; Vossler and Kerkvliet 2003; Johannesson 1997), and some shows that hy pothetical bias may be ameliorated using cheap
- talk, certainty adjustments, or other mechanisms (Champ et al. 1997; Champ et al. 2004; Cummings and Taylor 1999; L oomis et al. 1996). To obtain reliable estimates of WTP, the Agency tested and design ed all survey elements to promote incentive compatible preference elicitation mechanisms
. Incentive compatible stated preference surveys provide no incentive for non
- truthful preference revelation (Carson and Groves 2007). The literature is clear regarding the importance of incentive compatibility in stated preference value elicitation and the role of both questio n format and scenario consequentiality in ensuring this property (C arson 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
- ty

pe stated prefe rence choices are incentive compatible given that certain conditions are met, including the condition that responses are believed b y respondents to be consequential, or potentially

influencing public policy decisions (Carson and Groves 2007; Herriges et al
. 2010). The survey

is explicitly

designed to emphasize the importance of the budget constraint and program cost. For example, the survey asks respondents to compare protecting aquatic ecos ys tems to other policy issues which the government could potentially ask households to pay costs. The survey

itself includes explicit reminders of program cost and the budget constraint. The survey

has also been explicitly

designed to maximize the consequentiality of choice experiment questions, thereb y maximizing inc entive compatibility (i.e., reducing strategic and hy pothetical biases), following clear guidance of Carson et al. (2000). Elements specificall y designed to maximize consequentiality include : a) explicitly mentioning that this survey is associated with as sessment of proposed policies that are being considered, b ) numerous details provided in the survey concerning specifics of the proposed policies, and c ) emphasis that the52

ty pe of policy

enacted will depend in part on survey results and that their vote is important
. Johnston and Joglekar (2005) show the capacity of such information to eliminate hy pothetical bias in choice
- based stated preference WTP estimation. Focus groups and cognitive interviews indicated that respondents viewed choices as consequenti al, that they

considered their budget constraints when responding to all questions, and that they

would answer the same way were similar questions asked in a binding referendum. When asked if they

thought about the program cost in the same way as “money

c oming out of their pocket,” the vast majority of focus group and interview respondents indicated that they treated program costs the same way that they would have if there were actual money consequences. For example, respondents made statements such as “N o. [M y vote] would have been the same actuall y” and “ If I believed that it was gonna affect regulations, Ithink I would have voted the exact same way
. ” EPA does not anticipate significant hypothetical bias in the proposed survey based on focus group results. Focus groups respondents took the survey questions seriously

and indicated that they though that their choices would actuall y influence policy
. Regarding the potential use of cheap talk mechanisms or other devices to further address the potential for hy pothetical bias, the Agency

emphasizes that the literature is mixed as to their performance. For example, the seminal work b y Cummings and Taylor (1999) shows that cheap talk is able to reduce hy pothetical 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) find that a cheap talk script is only effective under certain circumstances, and for certain ty pes of respondents. For example, Cummings et al. (1995) fin d that a relativel y short cheap talk script actuall y worsens hy pothetical bias, while a longer script appears to ameliorate bias. Brown et al. (2003) finds cheap talk onl y effective at higher bid amounts

—a result mirrored b y Murphy et al. (2004). Still o ther authors find no effect of cheap talk, including Poe et al. (2002). Given the clearl y mixed experiences with such mechanisms, EPA is not convinced that cheap talk scripts are likel y to provide a panacea for hypothetical bias in the present case

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

– and cheap talk is not included in the survey
. Amelioration of Symbolic Biases and W arm - Glow Effects Following clear guidance of Arrow et al. (1993) and others, EPA has taken repeated steps to ensure that survey

responses reflect the value of the affected fish resources only , and do not53

reflect sy mbolic or warm glow concerns (Mitchell and Carson 1989). Following explicit guidance of the NOAA Blue Ribbon Panel on Contingent Valuation (Arrow et al. 1993, p. 4609), EPA has explicitly

designed all elements of the survey to “deflect the general ‘warm glow’ of giving or the dislike of ‘big business’ away from the specific program that is being valued.” This was done in a variety of way s, based on prior examples in the literature , such as asking respondents to reflect on importance of attributes before making selections, and using a pay ment vehicle that doesn’t raise trust issues (cost of living increase rather than an electric bill increase)
. The focus group and cognitive interview results indi cated that most participants answered the choice questions based on the effects discussed in the survey , not on a desire to help the environment in general. The survey includes clear language to instruct res pondents only to consider the specific attributes in the survey , and not to base answers on broader environmental concerns including the statement that:

“ Scientists expect that effects on the environment and economy not shown explicity will be small. For example, studies of industry suggest that effects on employment will be close to zero. ” This is also consistent with the statement from Arrow et al. (1993) that a referendum
- ty pe format may limit the warm
- glow effect. Some focus group participants indicated that they were inclined to support environmental causes and would like “to do a good thing” but still considered the cost and effects under the policy options. For example, respondents stated, “[...] if we can do something to help as long as the price is right, then do it” and “I feel if it’s going to be benefit everyone and be better for the economy, I’m OK with paying a little bit more. ” This evidence notwithstanding, EPA believes that it is important to include follow
- up questions to ensure that respo nses do not reflect sy mbolic biases. Question 9 in the survey instrument

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

test s for the presence of s ymbolic or warm
- glow biases. Follow
- up questions such as these are common in stated preference survey instruments, to assess the underl ying reasons for the observed valuation responses (e.g., Mitchell and Carson 1984). Assessing Scope Sensitivity The NOAA Blue Ribbon Panel on Contingent Valuation (CV) (Arrow et al. 1993, p. 4605) states clearl y that if “surveys are to elicit useful information about willingness to pay , respondents must understand exactly what it is they

are being asked to value (or vote upon)...”54

They further indicate that surveys providing “sketchy details” about the results of proposed policies call “into question the estimates derived there from,” and hence suggest a high degree of detail and richness in the descriptions of scenarios. Similar guidance is provided by other key sources in the CV l iterature (e.g., Mitchell and Carson 1989; Louviere et al. 2000). Among the reasons for this guidance is that such descriptions tend to encourage appropriate framing and sensitivity

to scope. Following Arrow et al. (1993), Mitchell and Carson (1989), and others, while noting the clear limitations in scope tests discussed by Heberlein et al. (2005), EPA believes that it is important that survey

responses in this case show sensitivity to scope. This is one of the primary reasons for the use of the choice experiment methodology , which is better able to capture WTP differentials related to changes in resource scope (Bateman et al. 2002). Unlike open
- ended questions, in which scope insensitivity is a primary

concern, EPA emphasizes that choice experiments generall y have shown much less difficulty with respondents reacting appropriatel y to the scope and scale of resource changes. Moreover, as clearl y noted b y Bennett and Blamey (2001, p. 231), “internal scope tests are automatically available from the results o f a [choice modeling] exercise.” That is, within choice experiments, sensitivity to scope is indicated by

the statistical significance and sign of parameter estimates associated with program attributes (Bennett and Blamey

2001). Internal scope sensitivi ty will therefore be assessed through model results for the variables Commercial Fish Populations, Fish Populations (all fish) , Fish Saved per Year, and Condition of Aquatic Ecos ys tems . 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 anal ys is, EPA will also conduct external scope tests (c f. Giraud et al. 1999). The primary difference between internal and external tests is that the former assess sensitivity to scope across choices of a single respondent, while the latter involves split
- sample assessments across different respondents. With in a choice modeling context, external scope tests are generall y considered “stronger,” although also more likely to be confounded by

differences in the implied choice frame (Bennett and Blamey 2001). A variety of options for external scope tests exist, d epending on the structure of the stated choice questions under consideration. In the present case, attribute
- by
- attribute external scope tests will be conducted over a split sub
- sample of respondents considering a specific set of choices, with all held con stant55

across the considered choices except the scope of the attribute for which the test is to be conducted. For example, to conduct an external scope test for reductions in annual fish losses, one would consider a set of choices that is identical over tw o respondent groups, except that one considers a choice with a greater reduction in fish losses. Assessing the choices over this split sample allows for an external test of scope. To illustrate this test, consider the following styl ized choice between Op tion A and Option B. The generic labels “Level 0”, “Level 1”, and “Level 2” are used to denote attribute levels, where for all attributes Level 2 > Level 1 > Level 0.
Table B2: Illustration of an External Scope Test Variable Option A Option B Fish Saved per Year Sample 1: Fish Saved Level 1 Sample 2: Fish Saved Level 2 Fish Saved Level 0
Commercial Fish Populations Commercial Fish Populations Level 0 Commercial Fish Populations Level 0 Fish Populations (all fish) Population (all fish) Level 0 Population (all fish) Level 0 Condition of Aquatic Ecosy s tems Aquatic Ecosystem Condition Level 0 Aquatic Ecosystem Condition Level 0 Increase in Cost of Living for Your Household Cost Level 1 Cost Level 0
In the above example, only Fish Saved per Year and Cost vary across the choice options. Because both Fish Saved per Year (at Level 1 and L evel 2) and Cost are higher in Option A than in Option B, neither option is dominant. In the illustrated split
- sample test, respondent sample 1 view s the choice with Fish Saved per Year at Level 1, while respondent sample 2 views an otherwise identical choice with Fish Saved per Year at Level 2, where Level 2 > Level 1. If responses are externall y sensitive to scope in Fish Saved per Year , this will manifest in a greater proportion of sample 2 respondents choosing Option A than sample 1 respondents. This hy pothesis may

be easil y assessed using a test of equal proportions across the two sub
- samples, and provides a simple attribute
- by
- attribute test of external scope. Analogous tests may be conducted for all attributes within the choice experiment design, using parallel methods. EPA emphasizes that the formal applicability of the above
- noted scope test is contingent upon the specific choice frame impli ed by levels of other attributes in the choice question. This is a56

characteristic of nearl y all external 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 accommodate the specific structural needs of the attribute
- by
- attribute external scope test. Otherwise, confounding effects of other varying attributes (including demographic information) can render results of scope tests ambiguous. In the present case, the proposed tests would require the addition of up to six unique question versions to the experimental design, enabling scope tests for the three non
- cost attributes within the 316(b) choice experiment scenarios. If scope tests in additional question frames are desired (e.g., the same scope test illustrated above, but given Level 1 for commercial fish populations , fish population (all fish) , and aquatic ecos ys tem condition attributes ), still addition al question versions would be added. While small numbers of questions added to the experimental design should have minimal impacts on overall efficiency (e.g., orthogonality of the design), larger numbers may

have a more significant impact. Hence, given constraints on the total number of survey respondents, there is a potential empirical tradeoff between the number of external scope tests that may

be conducted and the efficiency of the experimental design and statistical analysis. Communicating Uncertain ty to Respondents EPA believes that the role of risk and uncertainty is an important issue to be addressed in the development of benefits estimates, and points out that the literature provides numerous examples of cases in which appropriate survey design, including focus groups, was used to successfull y address such concerns. For example, as stated b y Desvousges et al. (1984), “using contingent valuation to estimate the benefits of hazardous waste management regulations requires detailed information on how and the extent to which respondents understand risk (or probability) and how government regulatory actions might change it... Using focus groups helped make this determination...” EPA also emphasizes that all regulatory analyses involve uncertainty of some type (Boardman et al. 2001). The ecological outcome of I&E reductions is subject to considerable uncertainty . EPA believes that it is important that survey respondents be aware of this uncertainty , and that their responses reflect the knowledge that the resource changes reflected in the survey are scientific estimates. However, EPA is also aware of the clear advice from the choice modeling literature (e.g., Bennett and Blamey 2001; Louviere et al. 2000) to avoid cognitive burden on respondents.57

Hence, the proposed survey materials clearl y indicate the uncertainty involved with the described resource changes in choice modeling scenarios, yet do so in a way designed to minimize cognitive burden. For example, prior to answering choi c e experiment questions, respondents are told :

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

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

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

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

– even if the annual reduction in fish losses is similar .” Focus groups and cognitive interviews participants understood that the ecological c hanges described in the survey

were uncertain, and most participants were comfortable making decisions in the presence of this uncertainty. Their responses indicated that they understood this uncertainty based on the information presented in the introducto ry material and considered it when evaluating policy

options. Respondents made such statements as: “My guess is that it did come from studies but I have a healthy dose of skepticism about the accuracy of it. I don’t think it’s been in any way skewed purpos efully , but I know that this is a best guess, reasonable guess perhaps” , “it shows me that they are being honest for the most part. You know, you can't obviously be accurate on every

thing, but this is a kind of a best guess ” , “[...] They had more numbers on the commercial fish population. The rest was more of a guesstimat e”, and “you don’t know the exact number and nobody knows
. ” In previous focus groups conducted for the Phase III survey , EPA tested alternative versions of the Phase III survey instrument in which choice experiment attributes were presented as 90% confidence ranges, rather than as point estimates. Focus group respondents were explicitly asked whether the ranges were helpful in understanding the uncertainty of estimates presented in the choice question or whether they were a source of confusion. Seven out of the eight respondents interviewed on that occasion indicated that th e use of ranges was more confusing than the use of point estimates
. Furthermore, respondents were comfortable making de cisions in the presence of this uncertainty. 5(c) Reporting Results58

The results of the survey

will be made public as part of the benefits anal ys is for the 316(b) regulation for existing facilities. Provided information will include summary statistics f

or the survey

data, extensive documentation for the statistical analysis, and a detailed description of the final results. The survey data will be released only after it has been thoroughl y vetted to ensure that all potentiall y identifying information has been removed.59 REFERENCES
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Attachment 1: Full Text of Regional State d Preference Survey Component (Northeast Regional Example)69 

# Fish and Aquatic Habitat

A Surveyof Northeast Residents (CT, DC, DE, MA , MD, ME , NH, NJ, NY, P A, RI, VT)

The public reporting and recordkeeping burden for this collection of information is estimated to average 30 mi nutes per response. Send comments on the Agency's need for this information, the accuracy of the provided burden estima tes, and any suggested methods for minimizing respondent burden, including through the use of automated collection techniques to the Director, Collection Strategies Division, U.S. Environmental Protection Agency (2822T), 1200 Pennsylvania Ave., NW , W ashing ton, D.C. 20460. Include the OMB control number in any correspondence. Do not send the completed survey to this address. OM B Control No. 2040
-XXXX Approval expires XX/XX/XX70 

# HUMAN ACTIVITIES, AQ UATIC HABITAT

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

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

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

Th is survey

concerns proposed policies that w ould reduce fish losses caused by cooling w ater use by

industrial facilities, including factories and powe r plants. These policies w ould benefit aquatic ecosystems but w ould increase the costs of some goods and se rvices you buy , including electricity and common household products.
1


## 1 Natural factors such as weather have always influenced fish, but in recent years human activities have had an increasing effect. Activities that affect fish include fishing, pollution, commercial and residential development, and the extraction of cooling water at industrial facilities. Declines in fish can affect the condition of ecological systems, food webs, and related human uses such as fishing. Food Web Birds/Mammals Fish Micro organisms71



# HOW DOES COOLING WAT ER AFFECT FISH? The water that industrial facilities use to cool equipment is pumped from bays, rivers, and lakes. The largest amount is used by power plants that produce electricity.
The equipment that pumps the cooling water kills small fish and fish eggs. Juvenile fish and eggs move through screens and into the cooling system where they are killed by high temperature. Large fish may be injured or killed against screens or filters. Pumping warm water back into the environment (called thermal discharge ) also affects ecological systems. Cooling Water Intake Screen



## 2 Cooling water use affects fresh and salt waters throughout the Northeast US, but the majority of all fish losses are in salt waters such as coastal bays. HowFish A re A ffected by

Water Intake72 

# WHAT KINDS OF FISH A RE AFFECTED?

Cooling water use is not the largest cause of fish loss in most areas (fishing causes greater losses), but has affected some fish populations.
Ab out 1/6 of the fish lost are specie s caught by commercial and recreational fishermen. Examples include striped bass , flounder , and cod

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

. Question 1. When thinking about how industrial facilities use cooling water, please rate the importance of the following to you. Check one box for each. Not Important Somewhat Important Very Important


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

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

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

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

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

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



## 373 

# HOW MANY FISH ARE AF FECTED?

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

Al though scientists can predict the number of fish saved each ye ar, the effect on fish populations is uncertain. This is because scientists do not know the total number of all fi sh in Northeast w aters and because many factors – such as cooling w ater use, fishing, pollution and w ater temperature – affect fish populations. The following page provides information on policies that would be required to reduce these fish losses. Largest Fish Losses per Year

Total Fish Population Losses 10% Smallest Fish Losses per Year Losses < 0.1%

Total Fish Population



## 474 

# NEW REGULATIONS ARE BEING PROPOSED TO PROTECT FISH

Current Situation

1.1 Billion Fish Lost per Year

(0% saved)

With Advanced Filters

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

Saved per Year

With Closed Cycle Cooling

<0.1 Billion Fish Lost per Year

(95% saved) >1.0 Billion Fish

Saved per Year



### Advanced filters and closed cycle cooling are already in use at many facilities and are proven technologies. Newregulations w ould require a mix of advanced filters and closed cycle cooling at all facilities — with reductions in fish losses betw een 25 % and 95 %. The government is considering policies that would require new measures to protect fish.

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

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

. However, costs are higher than for advanced filters.



## 575 

# HOW IMPORTANT ARE TH ESE ISSUES TO

YOU?

While these policies w ould reduce fish losses, they w ould also increase the costs of producing many goods and services — these costs w ould be passed on to consumers like you.

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

—such as public safety, education and health

— how important is protecting aquatic ecosystems to you? Check one b ox. Not Important Somew hat

Important Very

Important Protecting aquatic ecosystems is 1 2 3 4 5



### The government needs to know wh ether households are w illing to pay the costs of these new policies. This survey

w ill ask you to co mpare policies w ith different effects on cooling wa ter use, fish, and costs to your household. You w ill be asked to vote for the options yo u prefer. You w ill also have the opportunity to support the current situation, w ith no new policies, and no newcost s to your household.



## 676



# THIS SURVEY IS SIMILAR TO A

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

## Effect of Policy What It Means

Commercial Fish Populations (Fish Used by People) 

### A score between 0 and 100 showing the overall health of commercial

and recreational fish populations . Higher scores mean more fish and greater fish ing potential. A score of 100 means that these fish populations are at a size that maximizes long
- term harvest; 0 means no harvest. The current score in Northeast waters is 43.
Fish Populations (A ll Fish) 

### A score between 0 and 100 showing the estimated size of all fish

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

Fish Saved (per Year) 

### A score between 0 and 100 showing the reduction in young fish

lost because of the new policy. A score of 100 means that no fish are lost in cooling water intakes (all fish are saved ). The current score in Northeast w aters is 0; this represents the status quo with no new policies.

Condition of Aq uatic Ecosystems 

### A score between 0 to 100 showing the ecological condition of

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

. The current score in Northeast waters is 48. 

# $ Cost per Year 

### How much the policy will cost y our household, in unavoidable price

increases for p roducts and services y ou buy , including electricity and common household products.



## 777



# HOW WOULD YOU RATE T HE IMPORTANCE OF THESE EFFECTS?
Question 3. When considering policies that affect how facilities use cooling water, how important to you are effects on each of the following scores? Check one box for each. (For reminders of what the scores mean, please see page 7). Not Important Somew hat

Important Very

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

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

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

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

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



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



## 878



# SAMPLE QUESTION Quest ions w ill look like the sample below . PolicyEffect Current

Situation (No policy) 

## Option A Option B

Commercial Fish Populations (in 3 - 5 Years) 

# 43 %

(100% is populations that allow for maximum harvest) 

# 45 %

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

# 47 %

(100% is populations that allow for maximum harvest)
Fish Populations (all fish) (in 3 - 5 Years) 

# 31 %

(100% is populations without human influence) 

# 34 %

(100% is populations without human influence) 

# 38 %

(100% is populations without human influ ence)

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

# 0 %

No change in status quo 

# 25 % 0.3 billion fish saved 

# 50 % 0.6 billion fish saved

Condition of Aquatic Ecosystems (in 3 - 5 Years) 

# 48 % (100% is pristine condition) 

# 48 % (100% i s pristine condition) 

# 50 % (100% is pristine condition) 

# $ Increase in Cost of Living for Your Household 

# $0 No cost increase 

# $24 per year ($2 per month) 

# $36 per year ($3 per month) 

### HOW WOULD YOU VOTE? (CHOOSE ONE ONLY) 

# 

I would vote for NO POL ICY 

# 

I would vote for OPTION A 

# 

I would vote for OPTION B If you prefer Option A , check this box If y ou do not wa nt A or B, check this box If you prefer Option B, check this box 

# X X

X

979 

# AS YOU VOTE PLEASE R EMEMBER

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

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

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

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

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

— ev en if the annual reduction in fish losses is similar.

 Consider each pair of policy options separately

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

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

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



## 1080 

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

PolicyEffect NE Waters Current

Situation (No policy) 

## Option A

NE Waters Option B

NE Waters

Commercial Fish Populations (in 3 - 5 Years) 

# 43 %

(100% is populations that allow for maximum harvest) 

# 44 %

(100% is populations that allow for maximum harvest) 

# 45 %

(100% is populations that allow for maximum harvest)
Fish Populations (all fish) (in 3 - 5 Years) 

# 31 %

100% is populations without human influence) 

# 32 %

(100% is populations without human influence) 

# 35 %

(100% is populations without human influence)

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

# 0 % No change in status quo 

# 25 % 0.3 billion fish saved 

# 50 % 0.6 billion fish saved

Condition of Aquatic Ecosystems (in 3 - 5 Years) 

# 48 % (100% is pristine condition) 

# 49 % (100% is pristine condition) 

# 50 % (100% is pristine condition) 

# $ Increase in Cost of Living for Your Household 

# $0 No cost increase 

# $24 per year ($2 per month) 

# $36 per year ($3 per month) 

### HOW WOULD YOU VOTE? (C HOOSE ONE ONLY) 

# 

I would vote for NO POLICY 

# 

I would vote for OPTION A 

# 

I would vote for OPTION B



## 1181 

# POLICIES COULD REQUI RE DIFFERENT COMBINATIONS OF TECH NOLOGY

Nowyou w ill be asked to consider a newset of policy options for Northeast wa ters. A

s yo u vote, please remember —

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

 Each question is a separate vote. Questions 5 and 6 cannot be directly compared to each other, or to Question 4.

 Do not add up effects or costs across different questions.

 Policy costs and effects depend on many factors . Saving more fish does not necessarily mean that all effects will improve.



## 1282 

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

Situation (No policy) 

## Option A

NE Waters Option B

NE Waters

Commercial Fish Population s (in 3 - 5 Years) 

# 43 %

(100% is populations that allow for maximum harvest) 

# 45 %

(100% is populations that allow for maximum harvest) 

# 47 %

(100% is populations that allow for maximum harvest)
Fish Populations (all fish) (in 3 - 5 Years) 

# 31 %

(100% is populat ions without human influence) 

# 33 %

(100% is populations without human influence) 

# 36 %

(100% is populations without human influence)

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

# 0 % No change in status quo 

# 25 % 0.3 billion fish saved 

# 75 % 0.8 billion fish saved

Condition of Aquatic Ecosystems (in 3 - 5 Years) 

# 48 % (100% is pristine condition) 

# 48 % (100% is pristine condition) 

# 52 % (100% is pristine condition) 

# $ Increase in Cost of Living for Your Household 

# $0 No cost increase 

# $36 per year ($3 per month) 

# $60 per year ($5 per month) 

### HOW WOULD YOU VOTE? (CHOOSE ONE ONLY) 

# 

I would vote for NO POLICY 

# 

I would vote for OPTION A 

# 

I would vote for OPTION B



## 1383 

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

Situation (No policy) 

## Option A

NE Waters Option B

NE Waters

Commercial Fish Populations (in 3 - 5 Years) 

# 43 %

(100% is populations that allow for maximum harvest) 

# 50 %

(100% is populations that allow for maximum harvest) 

# 47 %

(100% is populations that allow for maximum harvest)
Fish Populations (all fish) (in 3 - 5 Years) 

# 31 %

(100% is populations without h uman influence) 

# 39 %

(100% is populations without human influence) 

# 36 %

(100% is populations without human influence)
Fish Saved per Year (Out of 1.1 billion fish lost in water intakes) 

# 0 % No change in status quo 

# 95 % 1.0 billion fish saved 

# 50 % 0.6 billi on fish saved

Condition of Aquatic Ecosystems (in 3 - 5 Years) 

# 48 % (100% is pristine condition) 

# 52 % (100% is pristine condition) 

# 52 % (100% is pristine condition) 

# $ Increase in Cost of Living for Your Household 

# $0 No cost increase 

# $72 per year ($6 p er month) 

# $24 per year ($2 per month) 

### HOW WOULD YOU VOTE? (CHOOSE ONE ONLY) 

# 

I would vote for NO POLICY 

# 

I would vote for OPTION A 

# 

I would vote for OPTION B



## 1 484 

### Question 7. If you alw ays voted for NO POLICY in questions 4
- 6 , what was the pri mary reason? Check one. (Skip this question if you voted for Option A or B in any question above.) ____ The cost to my household was too high ____ Preventing fish losses is not important to me ____ I do not trust the government to fix the problem ____ I 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 Question 8. Indicate how strongly you agree wi th the following statements about questions 4
- 6 and the information provided. Check one box for each. Strongly Disagree Disagree Neutral Ag ree Strongly Ag ree 

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

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

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

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

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

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

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

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



## 1585 

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

– 6 ? Check one box for each row .

Effect on my answ ers to questions 4 - 6 

### Very Small Effect Moderate

Effect Very Large Effect

. 

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

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

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

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

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

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

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

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

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

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

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



## 1686 

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

Number of days you did the activity during the past year 0 1 - 5 6 - 10 11 - 15 16+ Boating / Canoe ing / Kayaking 1 2 3 4 5 Swimming / Going to the Beach 1 2 3 4 5 Recreational Fishing (Fresh W ater) 1 2 3 4 5 Recreational Fishing (Salt W ater) 1 2 3 4 5 Shellfishing / Crabbing 1 2 3 4 5 Scuba Diving / Snorkeling 1 2 3 4 5

18 

## 1787 

## The following questions ensure that all groups are fairly represented.

All answers are anonymous and confidential.

11. What is your age?

___ years 12. What is your gender?  Male  Female 13. What is the highest level of education that you have comp leted?  Less than high school  One or more years of college  High school or equivalent  Bachelor’s Degree  High school + technical school  Graduate Degree 14. How many people live in your household?

______________ 15. How many of these people are 16 years of age or older? ____ 16. How many of these people are 6 years of age or younger? ____ 17. What is your zip code?

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

_____________ State:____ 19. Are you currently employed?

___ Yes

_____ No 20. What category comes closest to your total household 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 

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

Thank you f

or your participation in this important survey!



## 1888

Attachment 2 : Full Text of National Stated Preference Survey Component89 

# Fish and Aquatic Habitat

A Surveyof US Households

The public reporting and recordkeeping burden for this collection of informat ion is estimated to average 30 mi nutes per response. Send comments on the Agency's need for this information, the accuracy of the provided burden estimates, and any suggested methods for minimizing respondent burden, including through the use of automated collection techniques to the Director, Collection Strategies Division, U.S. Environmental Protection Agency (2822T), 1200 Pennsylvania Ave., NW , W ashington, D.C. 20460. Include the OMB control number in any correspondence. Do not send the completed surv ey to this address. OM B Control No. 2040
-XXXX Approval expires XX/XX/XX90 

# HUMAN ACTIVITIES, AQ UATIC HABITAT

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

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

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

This survey

concerns proposed policies that w ould reduce fish losses caused by cooling w ater use by

industrial facilities, including factories and powe r plants. These policies w ould benefit aquatic ecosystems but w ould increase the costs of some goods and services you buy , including electricity and common household products. Natural factors such as weather have always influenced fish, but in recent years human activities have had an increasing effect. Activities that affect fish include fishing, pollution, commercial and residential developm ent, and the extraction of cooling water at industrial facilities. Declines in fish can affect the condition of ecological systems, food webs, and related human uses such as fishing. Food Web

1


## 1 Birds/Mammals

Fish Micro organisms91



# HOW DOES COOLING WAT ER AFFECT FISH? The water that industrial facilities use to cool equipment is pumped from bays, rivers, and lakes. The largest amount is used by power plants that produce electricity.
The equipment that pumps the cooling water kills small fish and fish eggs. Juvenile fish and eggs move through screens and into the cooling system where they are killed by high temperature. Large fish may be injured or killed against screens or filters. Pumping warm water back into the environment (called thermal discharge ) also affects ecological systems. Cooling Water Intake Screen



## 2 Cooling water use affects fresh and salt waters th roughout the US, but almost all fish losses are in salt waters such as coastal bays. HowFish A re A ffected by

Water Intake92 

# WHAT KINDS OF FISH A RE AFFECTED?

Cooling water use is not the larges t cause of fish loss in most areas (fishing causes greater losses), but has affected some fish populations.
Ab out 1/3 of the fish lost are species caught by commercial and recreational fishermen. Examples include striped bass , flounder , and cod

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

. Question 1. When thinking about how industrial facilities use cooling water, please rate the importance of the following to you. Check one box for each. Not Important Somewhat Important Very Important


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

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

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

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

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

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



## 393 

# HOW MANY FISH ARE AF FECTED?

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

Al though scientists can predict the number of fish saved each ye ar, the effect on fish populations is uncertain. This is because scientists do not know the total number of all fish in U.S. w aters and because many factors – such as cooling wa ter use, fishing, pollution and w ater temperature – affect fish populations. The following page provides information on policies that would be required to reduce these fish losses. Largest Fish Losses per Year

Total Fish Population Losses 10% Smallest Fish Losses per Year Losses < 0.1%

Total Fish Population



## 494 

# NEW REGULATIONS ARE BEING PROPOSED TO PROTECT FISH

CurrentS itu at io n

2.7 B illio n Fi sh Lost per Ye ar (0% S aved)

Wi th Ad vanced Fi lte rs

2.1 B illio n Fi sh Lost per Ye ar (2 2% S aved) 0. 6 B illion F ish Sav ed per Y ear

Wi th Closed Cycle Cooling

0.1 B illio n Fi sh Lost per Year (95% S aved) 2. 6 Billion Fis h Saved pe r Y

ear



### Advanced filters an d closed cycle cooling are already in use at many facilities and are proven technologies. Newregulations w ould require a mix of advanced filters and closed cycle cooling at all facilities — with reductions in fish losses betw een 25 % and 95 %. The government is considering policies that would require new measures to protect fish.

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

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

. However, costs are higher than for advanced filters.



## 595 

# HOW IMPORTANT ARE THESE ISSUES TO

YOU?

While these policies w ould reduce fish losses, they w ould also increase the costs of producing many goods and services — these costs w ould be passed on to consumers like you.

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

—such as public safety, education and health

— how important is protecting aquatic ecosystems to you? Check one box. Not Important Somew hat

Important Very

Important Protecting aquatic ecosystems is 1 2 3 4 5



### The government needs to know wh ether households are w illing to pay the costs of these new policies. This survey

w ill ask you to compare policies w ith different effects on cooling wa ter use, fish, and costs to your household. You w ill be asked to vote for the options yo u prefer. You w ill also have the opportunity to support the current situation, w ith no new policies, and no newcosts to your household.



## 696



# THIS SURVEY IS SIMILAR TO A

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

## Effect of Policy What It Means

Commercial Fish Populations (Fish Used by People) 

### A score between 0 and 100 showing the overall health of commercial

and recreational fish populations . Higher scores mean more fish and greater fishing potential. A score of 100 means that these fish populations are at a size that maximizes long
- term harvest; 0 means no harvest. The current score in U.S. waters is 43.
Fish Populations (A ll Fish) 

### A score between 0 and 100 showing the estimated size of all fish

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

Fish Saved (per Year) 

### A score between 0 and 100 showing the reduction in young fish

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

Condition of Aq uatic Ecosystems 

### A score between 0 to 100 showing the ecological condition of

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

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

# $ Cost per Year 

### How much the policy will cost y our household, in unavoidable price

increases for products and services y ou buy , including electricity and common household products.



## 797



# HOW WOULD YOU RATE T HE IMPORTANCE OF THESE EFFECTS?
Questi on 3. When considering policies that affect how facilities use cooling water, how important to you are effects on each of the following scores? Check one box for each. (For reminders of what the scores mean, please see page 7). Not Important Somew hat

Important Very

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

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

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

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

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



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



## 898



# SAMPLE QUESTION Questions w

ill look like the sample below . PolicyEffect Current

Situation (No policy) 

## Option A Option B

Commercial Fish Populations (in 3 - 5 Yea rs) 

# 53 %

(100% is populations that allow for maximum harvest) 

# 55 %

(100% is populations that allow for maximum harvest) 

# 57 %

(100% is populations that allow for maximum harvest)
Fish Populations (all fish) (in 3 - 5 Years) 

# 39 %

(100% is populations without human influence) 

# 42 %

(100% is populations without human influence) 

# 42 %

(100% is populations without human influence)

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

# 0 %

No change in status quo 

# 25 % 0.7 billion fish saved 

# 50 % 1.4 billi on fish saved

Condition of Aquatic Ecosystems (in 3 - 5 Years) 

# 46 % (100% is pristine condition) 

# 46 % (100% is pristine condition) 

# 48 % (100% is pristine condition) 

# $ Increase in Cost of Living for Your Household 

# $0 No cost increase 

# $24 per year ($2 per month) 

# $48 per year ($3 per month) 

### HOW WOULD YOU VOTE? (CHOOSE ONE ONLY) 

# 

I would vote for NO POLICY 

# 

I would vote for OPTION A 

# 

I would vote for OPTION B If you prefer Option A , check this box If y ou do not wa nt A or B, check this box If you prefer Option B, check this box 

# X X

X

999 

# AS YOU VOTE PLEASE R EMEMBER

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

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

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

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

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

— ev en if the annual reduction in fish losses is similar.

 Consider each pair of policy options separately

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

 Scientists expect that effects on the environment and economy not shown ex plicitly will be small. For example, studies of industry suggest that effects on employment will be close to zero.

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



## 10100 

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

PolicyEffect US Current

Situation (No policy) 

## Option A

US Option B

US

Commercial Fis h Populations (in 3 - 5 Years) 

# 53 %

(100% is populations that allow for maximum harvest) 

# 55 %

(100% is populations that allow for maximum harvest) 

# 57 %

(100% is populations that allow for maximum harvest)
Fish Populations (all fish) (in 3 - 5 Years) 

# 39 %

100% is populations without human influence) 

# 40 %

(100% is populations without human influence) 

# 43 %

(100% is populations without human influence)

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

# 0 % No change in status quo 

# 25 % 0.7 billion fish saved 

# 50 % 1.4 billion fish saved

Condition of Aquatic Ecosystems (in 3 - 5 Years) 

# 46 % (100% is pristine condition) 

# 47 % (100% is pristine condition) 

# 48 % (100% is pristine condition) 

# $ Increase in Cost of Living for Your Household 

# $0 No cost incre ase 

# $24 per year ($2 per month) 

# $48 per year ($3 per month) 

### HOW WOULD YOU VOTE? (CHOOSE ONE ONLY) 

# 

I would vote for NO POLICY 

# 

I would vote for OPTION A 

# 

I would vote for OPTION B



## 11101 

# POLICIES COULD REQUI RE DIFFERENT COMBINATIONS OF TECH NOLOGY

Nowyou w ill be asked to consider a newset of policy options for U.S. waters. A s yo u vote, please remember —

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

 Each questio n is a separate vote. Questions 5 and 6 cannot be directly compared to each other, or to Question 4.

 Do not add up effects or costs across different questions.

 Policy costs and effects depend on many factors . Saving more fish does not necessarily mean that all effects will improve.



## 12102 

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

Situation ( No policy) 

## Option A

US Option B

US

Commercial Fish Populations (in 3 - 5 Years) 

# 53 %

(100% is populations that allow for maximum harvest) 

# 55 %

(100% is populations that allow for maximum harvest) 

# 57 %

(100% is populations that allow for maximum harvest)
Fish Populations (all fish) (in 3 - 5 Years) 

# 39 %

(100% is populations without human influence) 

# 41 %

(100% is populations without human influence) 

# 43 %

(100% is populations without human influence)

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

# 0 %

No change in status quo 

# 25 % 0.7 billion fish saved 

# 75 % 2.0 billion fish saved

Condition of Aquatic Ecosystems (in 3 - 5 Years) 

# 46 % (100% is pristine condition) 

# 46 % (100% is pristine condition) 

# 50 % (100% is pristine condition) 

# $ Increase in Cost of Living for Your Household 

# $0 No cost increase 

# $36 per year ($3 per month) 

# $60 per year ($5 per month) 

### HOW WOULD YOU VOTE? (CHOOSE ONE ONLY) 

# 

I would vote for NO POLICY 

# 

I would vote for OPTION A 

# 

I would vote for OPTION B



## 13103 

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

Situation (No policy) 

## Option A

US Option B

US

Commercial Fish Populations (in 3 - 5 Years) 

# 53 %

(100% is populations that allow for maximum harvest) 

# 60 %

(100% is populations that allow for maximum harvest) 

# 57 %

(100% is populations that allow for maximum harvest)
Fish Populations (all fish) (in 3 - 5 Years) 

# 39 %

(100% is populations without human influence) 

# 47 %

(100% is populations without human influence) 

# 44 %

(100% is populations without human influence)
Fish Saved per Year (Out of 2.7 billion fish lost in water intakes) 

# 0 %

No change in status quo 

# 95 % 2.6 billion fish saved 

# 50 % 1.4 billion fish saved

Condition of Aquatic Ecosystems (in 3 - 5 Years) 

# 46 % (100% is pristine condition) 

# 50 % (100% is pristine condition) 

# 50 % (100% is pristine condition) 

# $ Increase in Cost of Living for Your Household 

# $0 No cost increase 

# $96 per year ($6 per month) 

# $48 per year ($2 per month) 

### HOW WOULD YOU VOTE? (CHOOSE ONE ONLY) 

# 

I would vote for NO POLICY 

# 

I would vote for OPTION A 

# 

I would vote for OPTION B



## 14104 

### Question 7. If you alw ays voted for NO POLICY in questions 4
- 6 , what was the primary reason? Check one. (Skip this question if you voted for Option A or B in any question above.) ____ The cost to my household was too high ____ Preventing fish losses is not important to me ____ I do not trust t he government to fix the problem ____ I would rather spend my money on other things ____ I did not believe the choices were realistic ____ Since the problem was created by private facilities, they should fix it without passing costs on to consumers Questi on 8. Indicate how strongly you agree with the following statements about questions 4
- 6 and the information provided. Check one box for each. Strongly Disagree Disagree Neutral Ag ree Strongly Ag ree 

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

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

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

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

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

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

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

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



## 15105 

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

– 6 ? Check one box for each row .

Effect on my answ ers to questions 4 - 6 

### Very Small Effect Moderate

Effect Very Large Effect

. 

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

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

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

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

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

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

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

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

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

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

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



## 16106 

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

Number of days you did the activity during the past year 0 1 - 5 6 - 10 11 - 15 16+ Boating / Canoeing / Kayaking 1 2 3 4 5 Swimming / Going to the Beach 1 2 3 4 5 Recreational Fishing (Fresh W ater) 1 2 3 4 5 Recreational Fishing (Salt W ater) 1 2 3 4 5 Shellfishing / Crabbing 1 2 3 4 5 Scuba Diving / Snorkeling 1 2 3 4 5

18 

## 17107 

## The following questions ensure that all groups are fairly represented.

All answers are anonymous and confidential.

11. What is your age?

___ years 12. What is your gender?  Male  Female 13. What is the hig hest level of education that you have completed?  Less than high school  One or more years of college  High school or equivalent  Bachelor’s Degree  High school + technical school  Graduate Degree 14. How many people live in your household ?

______________ 15. How many of these people are 16 years of age or older? ____ 16. How many of these people are 6 years of age or younger? ____ 17. What is your zip code?

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

_____________ State:____ 19. Are you currently employed?

___ Yes

_____ No 20. What category come s closest to your total household 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 

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

Thank you for your participation in this important survey!


## 18108

Attachment 3 : Federal Register Notice
ENVIRONMENTAL PROTECTION AGENCY [EPA - HQ - OW- 2010 - 0595; FRL - ] Agency Information Collection Activities; Submission to OMB f or Review and Approval; Willingness to Pay Survey for § 316(b) Existing Facilities Cooling Water Intake Structures (New) , EPA ICR N o. 2402.01, OMB Control No. 2040 -NEW AGENCY: Environmental Protection Agenc y (EPA)
. ACTION: Notice. SUMMARY: In complianc e with the Paperwork Reduction Act (PRA) (44 U.S.C. 3501 et seq .), this document announces that an Information Collection Request (ICR) has been forwarded to the Office of Management and Budget (OMB) for review and approval
. This is a request for a
new co llection. The IC R, which is abstracted below, describes the nature of the information collection and its estimated burden and cost. DATES: Additional comments may be submitted on or before [ insert date 30 day s after publication in the Federal Register]. ADDRESSES: Submit your comments, identified by Docket ID No
. EPA
- HQ
- OW
- 2010
- 0595 to: (1) EPA by

one of the following methods:

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

 Email: OW
- Docket@epa.gov, Attention Docket ID No. EPA
- HQ
- OW
- 2010
- 0595

 Mail: Water Docket, Environmental Protection Agency, Mailcode: 28221T, 1200 Pennsylvania Ave. , NW., Washington, DC 20460, Attention Docket ID No. EPA
- HQ
- OW
- 20 10
- 0595. Please include a total of 3 copies.

 Hand Delivery : Water Docket, EPA Docket Center, EPA West, Room 3334, 1301109

Constitution Ave., NW., Washington, DC, Attention Docket ID No. EPA
- HQ
- OW
- 20 10
- 0595. Such deliveries are only accepted during the Docket’s normal hours of operation and special arrangements should be made.
(2) OMB b y m ail to: Office of Information and Regulatory Affairs, Office of Management and Budget (OMB), Attention: Desk Officer for EPA, 725 17 th Street, NW, Washington, DC 20503.

FOR FURTHER INFORMATION CONTACT: Erik Helm, Office of Water, Office of Scienc e and Technology , Engineering and Anal ys is 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: EPA has submitted the following ICR to OMB for review and approval according to the procedures prescribed in 5 CFR 1320.12. On July 21, 2010 ( 74 FR 42438 ), EPA sought comments on this I CR pursuant to 5 C FR 1320.8(d). EPA received five comments during the comment period, which are addressed in the IC R
. Any additional comments on this I CR should be submitted to EPA and OMB within 30 days of this notice. 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 Water Docket in the EPA Docket Center (EPA/DC), EPA West, Room 3334, 1301 Constitution Ave., NW, Washington, DC. The EPA/DC Pub lic Reading Room is open from 8:30 a.m. to 4:30 p.m., Monday through Friday , excluding legal holiday s. The telephone number for the Reading Room is 202
- 566
- 1744, and the telephone number for the Water Docket is 202
- 566
- 1752.110

Use EPA’s electronic docket an d comment s ys tem at www.regulations.gov , to submit or view public comments, access the index listing of the contents of the docket, and to access those documents in the docket that are available electronically . Once in the s ys tem, select “docket search,” then key

in the docket ID number identified above. Please note that EPA’s policy is that public comments, whether submitted electronically or in paper, will be made available for public viewing at www.regulations.gov as EPA receives them and without chan ge, unless the comment contains cop yri ghted material, CBI, or other information whose public disclosure is restricted b y statute. For further information about the electronic docket, go to www.regulations.gov
. Title: Willingness to Pay Survey for Sectio n 316(b) Existing Facilities Cooling Water Intake Structures: Instrument, Pre
- test, and Implementation ICR numbers: EPA I CR No. 2402.01 , OMB Control No. 2040
-NEW
. ICR status: This ICR is for a new information collection activity
. An Agency may not con duct or sponsor, and a person is not required to respond to, a collection of information, unless it display s a currently

valid OMB control number. The OMB control numbers for EPA's regulations in title 40 of the CFR, after appearing in the Federal Register when approved, are listed in 40 CFR part 9, are displayed either by publication in the Federal Register or b y other appropriate means, such as on the related collection instrument or form, if applicable. The display of OMB control numbers in certain EPA regulations is consolidated in 40 CFR part 9. Abstract: Section 316(b) of the Clean Water Act (CWA) requires EPA to ensure that the location, design, construction, and capacity of cooling water intake structures (CWI S) reflect the best technology

availa ble (BTA) to protect aquatic organisms from being killed or injured by impingement or entrainment. At que stion here is the regulation of the existing steam electric and manufacturing facilities
.111

Under Executive Order 12866, EPA is required to estimate th e potential benefits and costs to society

of proposed rule options of significant rules . To assess th e importance of the ecological gains from the section 316(b) re gulation , EPA requests approval from the OMB to conduct a stated preference survey . Data f rom the associated stated preference survey will be used to estimate values (willingness to pay , or WTP) derived b y households for changes related to the reduction of fish losses at CWI S, and to provide information to assist in the interpretation and validation of survey

responses. EPA has designed the survey to provide data to support the following specific objectives: [a] the estimation of the total values that individuals place on preventing losses of fish and other aquatic organisms caused b y 316(b) fa cilities; [b] to understand how much individuals value preventing fish losses, increasing fish populations, and increasing commercial and recreational catch rates; [c] to understand how such values depend on the current baseline level of fish populations a nd fish losses, the scope of the change in those measures, and the certainty level of the predictions; and [d] to understand how such values vary with respect to individuals’ economic and demographic characteristics. The key elicitatio n questions ask resp ondents whether or not they would vote for policies that would increase their cost of living, in exchange for specified multi
- attribute changes in [a] impingement and entrainment losses of fish, [b] commercial fish populations , [c] long
- term populations of all fish , and [d] condition of aquatic ecos ys tems. The respondents’ stated preferences with respect to levels of environmental goods and cost to households , when used in conjunction with other information collected in the survey on the use of the affecte d aquatic resources, household income, and other demographics, can be anal yz ed statistically (using a mixed logit framework) to estimate total WTP for the quantified environmental benefits of the 316(b) rulemaking. Data anal ys is and interpretation is groun ded in a standard random utility model.112

The welfare values that can be derived from this stated pref erence survey along with those that are estimated apart from the survey effort will offer insight into the composition of the value people place on the 316(b) environmental impacts. WTP estimates derived from the survey may overlap
- to a potentially substantial extent
- with estimates that can be provided 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. Burden Statement: The annual public reporting and recordkeeping burden for this collection of information is estimated to average 5 minutes per telephone screening participant and 30 m inutes per mail survey

respondent including the time necessary to complete and mail back the questionnaire. Burden means the total time, effort, or financial resources expended by persons to generate, maintain, retain, or disclose or provide information to or for a Federal agency . This includes the time needed to review instructions; develop, acquire, install, and utilize technology and sy stems for the purposes of collecting, validating, and verifying information, processing and maintaining information, and disclosing and providing information; adjust the existing way s to comply with any previously

applicable instructions and requirements which have subsequentl y changed; train personnel to be able to respond to a collection of information; search data sourc es; complete and review the collection of information; and transmit or otherwise disclose the information. The I CR provides a detailed explanation of the Agency ’s estimate, which is only briefly summarized here: Respondents: Individuals from US households Estimated total number of potential respondents: 9 , 5 33 for telephone screening and 2, 288 for mailed questionnaires. Frequency

of response: one
- time response.113

Estimated total average number of responses for each respondent: one
- time response. Estimated total burden hours: 1, 938 hours. Estimated total costs: $ 39 , 583 . EPA estimates that there will be no capital and operating and maintenance cost burden to respondents.
Dated: ________________

________________

____________

______ John Moses, Director, Collection Strategies Division.114

Attachment 4 : Description of Statistical Survey Design The following represents an anticipated experimental design for survey implementation, along with the associated number of completed surveys that will be req uired. Part B of this supporting statement provides detail on the sampling design. The proposed design and sampling plan is based on standard design and sampling theory for choice experiments and population survey s, as outlined by

Louviere et al. (2000), K uhfeld (2009) and Dillman (2000). EPA notes that the anticipated experimental design described here is preliminary and it may be subject to refinements during design evaluations to account for issues such as dominate or dominated pairs, ecological feasibi lity , and to remove attribute combinations which do not provide information for estimation. The purpose of the 316(b) survey is to calculate average per household parameters (e.g., willingness to pay

and choice probabilities) within a given survey populati on. No sub
- population estimates are required. The anticipated experimental design for the choice experiment includes two multi
- attribute choice options or alternatives , A and B, together with a fixed status quo or “no policy” option. Options A and B are c haracterized by levels for the following six attributes:
1. Location in A and B (x 1A ; x 1B )

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

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

– 3 possible levels 4. Fish Population s (all fish) in A and B (x 4A ; x4B )

– 3 possible levels 5. Aquatic Ecos ys tem Condition in A and B (x 5A ; x 5B )

– 3 possible levels 6. Cost in A and B (x 6A ; x 6B )
- 6 possible levels This implies an experimental design characterized by [2 × 3 4 × 6] for each alternative , or [2 2 × 3 8 × 6 2 ] for alternatives A and B combined. To construct a preliminary main effects design that is sufficiently flexible to estimate alternative specific main effects and response patterns (i.e., a non
- generic design), we begin with the smallest 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 above notation, and leve ls indicated by integers 1...N, where N for each attribute is the number of levels identified above:115 Table 1: Set of 72 Design Profiles Obs x1A x2A x3A x4A x5A x6A x1B x2B x3B x4B x5B x6B 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 2 2 2 2 2 2 2 2 3 1 1 1 3 1 6 2 2 3 3 1 3 4 1 1 1 3 3 5 2 1 1 2 3 2 5 1 1 2 2 1 3 1 1 3 2 2 3 6 1 1 2 2 2 1 2 3 1 1 2 4 7 1 1 2 2 3 4 1 2 2 2 1 1 8 1 1 2 2 3 6 1 3 2 3 3 6 9 1 1 3 1 1 2 1 3 2 3 2 5 10 1 1 3 1 2 3 2 1 3 1 3 6 11 1 1 3 3 2 4 1 2 1 3 3 4 12 1 1 3 3 3 5 2 3 3 1 1 5 13 1 2 1 1 2 4 2 3 3 2 1 6 14 1 2 1 2 2 5 1 3 3 3 2 1 15 1 2 1 2 3 2 1 3 1 1 3 3 16 1 2 1 3 1 3 2 3 2 2 3 4 17 1 2 2 1 1 5 2 1 2 3 1 4 18 1 2 2 1 3 1 2 2 3 2 3 5 19 1 2 2 3 1 2 1 2 1 1 1 6 20 1 2 2 3 2 6 1 1 1 2 2 5 21 1 2 3 1 3 4 1 1 1 3 2 3 22 1 2 3 2 1 1 1 2 3 3 3 2 23 1 2 3 2 2 6 1 1 2 1 1 2 24 1 2 3 3 3 3 1 2 2 1 2 1 25 1 3 1 1 3 6 2 2 3 1 2 4 26 1 3 1 2 1 4 2 1 2 1 3 5 27 1 3 1 2 2 3 1 2 1 3 1 5 28 1 3 1 3 3 1 1 1 2 3 2 6 29 1 3 2 1 2 5 2 2 2 1 3 3 30 1 3 2 1 3 3 2 3 1 3 1 2 3 1 1 3 2 3 1 4 2 3 3 1 2 2 32 1 3 2 3 2 2 2 1 3 3 3 1 33 1 3 3 1 1 6 1 3 1 2 3 1 34 1 3 3 2 1 5 2 2 1 2 2 6 35 1 3 3 2 3 2 1 1 3 2 1 4 36 1 3 3 3 2 1 2 3 2 2 1 3 37 2 1 1 1 1 1 2 1 1 1 1 1 38 2 1 1 1 2 2 1 2 2 2 2 2 39 2 1 1 3 1 6 1 2 3 3 1 3 40 2 1 1 3 3 5 1 1 1 2 3 2 41 2 1 2 2 1 3 2 1 3 2 2 3 42 2 1 2 2 2 1 1 3 1 1 2 4 43 2 1 2 2 3 4 2 2 2 2 1 1 44 2 1 2 2 3 6 2 3 2 3 3 6 45 2 1 3 1 1 2 2 3 2 3 2 5 46 2 1 3 1 2 3 1 1 3 1 3 6116 47 2 1 3 3 2 4 2 2 1 3 3 4 48 2 1 3 3 3 5 1 3 3 1 1 5 49 2 2 1 1 2 4 1 3 3 2 1 6 50 2 2 1 2 2 5 2 3 3 3 2 1 51 2 2 1 2 3 2 2 3 1 1 3 3 52 2 2 1 3 1 3 1 3 2 2 3 4 53 2 2 2 1 1 5 1 1 2 3 1 4 54 2 2 2 1 3 1 1 2 3 2 3 5 55 2 2 2 3 1 2 2 2 1 1 1 6 56 2 2 2 3 2 6 2 1 1 2 2 5 57 2 2 3 1 3 4 2 1 1 3 2 3 58 2 2 3 2 1 1 2 2 3 3 3 2 59 2 2 3 2 2 6 2 1 2 1 1 2 60 2 2 3 3 3 3 2 2 2 1 2 1 61 2 3 1 1 3 6 1 2 3 1 2 4 62 2 3 1 2 1 4 1 1 2 1 3 5 63 2 3 1 2 2 3 2 2 1 3 1 5 64 2 3 1 3 3 1 2 1 2 3 2 6 65 2 3 2 1 2 5 1 2 2 1 3 3 66 2 3 2 1 3 3 1 3 1 3 1 2 67 2 3 2 3 1 4 1 3 3 1 2 2 68 2 3 2 3 2 2 1 1 3 3 3 1 69 2 3 3 1 1 6 2 3 1 2 3 1 70 2 3 3 2 1 5 1 2 1 2 2 6 71 2 3 3 2 3 2 2 1 3 2 1 4 72 2 3 3 3 2 1 1 3 2 2 1 3 Following common examples in the environmental economics literature, we anticipate three choice question s per survey . This will allow the 72 profiles to be included (orthogonall y blocked) in 24 unique survey booklets. Monte Carlo experiments indicate that approximately 6 completed responses are required for each profile in order to achieve large sample 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. Sample Sizes for Maximum Acceptable Sampling Error The goal of the choice experiment is to estimate regression coefficients from mixed or conditional logit models that may be used to estimate willingness to pay f or multi
- attribute policy alternatives, or the likelihood of choosing a given multi
- attribute alternative, following standard random utility

modeling procedures (Haab and McConnell 2002). Required sample117

sizes to estimate population parameters with given d egrees of freedom are drawn from standard statistical theory , as described by Dillman (2000). The maximum acceptable sampling error for predicting response probabilities (the likelihood of choosing a given alternative) in the present case is ±10%, assuming a true response probability

of 50% associated with a utility indifference point. Given the survey population size, this level of precision requires a minimum sample size of approximately 96 observations. The number of observations (completed surveys) required to obtain large sample properties for the choice experiment design provide more than sufficient observations to obtain this required precision for population parameters. The choice experiment design requires 432 completed profile responses from 144 survey s. Statistical theory shows that 400 assumed
- independent profile responses will allow a 50% choice probability to be estimated within ±4.9 percent, at a 95% confidence level. With only a single choice question per survey (144 responses), the same probability

and confidence level 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 allows 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 available 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 effects design with 36 profiles:

Table 2: Set of 36 Design Profiles Obs x2A x3A x4A x5A x6A x2B x3B x4B x5B x6B 1 1 1 1 1 1 1 1 1 1 1 2 1 1 2 2 2 2 2 2 1 2 3 1 1 2 3 4 3 2 1 1 6 4 1 1 3 2 6 3 1 2 2 4 5 1 2 1 1 4 2 1 3 2 5 6 1 2 2 2 3 1 3 1 3 5 7 1 2 2 3 5 3 3 2 3 1 8 1 2 3 3 2 1 1 3 1 3 9 1 3 1 2 6 3 3 1 2 3 10 1 3 1 3 3 2 2 3 3 4 11 1 3 3 1 1 2 3 2 3 6 12 1 3 3 1 5 1 2 3 2 2 13 2 1 1 1 5 2 3 1 1 4118 14 2 1 2 2 5 2 1 3 3 3 15 2 1 3 2 1 3 2 3 3 5 16 2 1 3 3 3 1 3 1 2 2 17 2 2 1 1 3 3 2 2 1 3 18 2 2 2 3 1 1 1 2 2 4 19 2 2 3 2 4 2 2 1 2 1 20 2 2 3 3 6 2 3 3 1 6 21 2 3 1 2 2 1 1 1 3 6 22 2 3 1 3 4 3 1 2 3 2 23 2 3 2 1 2 3 3 3 2 1 24 2 3 2 1 6 1 2 2 1 5 25 3 1 1 3 2 2 3 2 2 5 26 3 1 1 3 6 1 2 3 3 1 27 3 1 2 1 3 3 1 3 2 6 28 3 1 3 1 4 1 3 2 3 3 29 3 2 1 2 1 3 3 3 1 2 30 3 2 1 2 5 1 2 2 2 6 31 3 2 2 1 6 2 1 1 3 2 32 3 2 3 1 2 3 2 1 3 4 33 3 3 2 2 4 1 3 3 1 4 34 3 3 2 3 1 2 2 1 2 3 35 3 3 3 2 3 2 1 2 1 1 36 3 3 3 3 5 3 1 1 1 5 This design is then repeated for each of the four possible combinations of values for x 1A and x 1B (i.e., 1,1; 2,2; 1,2; 2,1) creating a candidate design of 36×4 = 144 profiles. The resulting design full y insulates all main effe cts (eliminates aliasing) from interactions with location attributes x 1A and x 1B , and allows associated location interactions to be estimated independent of main effects. The number of required survey versions (48) is calculated by dividing the 144 profil es b y the three choice questions per survey. The total number of completed surveys required (288) is based on a requirement of six completed surveys per survey version (48) to estimate the main effects and interactions
. As above, the number of observatio ns (completed survey s) required to obtain large sample properties for the choice experiment design provide sufficient observations to obtain required precision for population parameters. 1 Also as above, this candidate design may be subject to refinements based on design evaluations, as described b y Louviere et al. (2000) and Kuhfeld (2009), but this is unlikely to alter design dimensions.

1 Alternatively, the smallest possible main effects plan for all attributes (72 profiles) may be folded over to make another 72 profiles, f

or a combined set of 144 profiles. This protects main effects from all unobserved 2
- way interactions, but does not guarantee that specific interactions may be estimated. The required sample size is the same as that which would guarantee that location interactions can be estimated.119

Attachment 5: Description of Internet- based Sampling Alternative EPA is also considering the use of an internet
- base d (i.e., web
- based) sampling approach as an alternative to the mail survey described in Part B of the supporting statement. The survey content, pre - testing, review process, and data analy sis would be identical to the mail survey described in Parts A and B of the supporting statement. To support implementation of the web
based alternative, EPA would retain a vendor that maintains a preexisting representative national panel. This attachment provides a brief summary of the web
- based alternative, focusing on differences from the mail survey approach described in Part B of the supporting statement. Sampling Frame The sampling frame for the web
- based survey is the panel of individuals previously recruited b y a vendor to participate in online surveys. The over all sampling frame would be the set of all individuals in continental U.S. households who are 18 ye ars of age or older and who have listed phone numbers. Individuals in the panel most likely be recruited using a list
- assisted random digit dialing telephon e methodology , thus providing a probability
- based starting sample of U.S. telephone households. Panels of this ty pe are usuall y routinel y supplemented to account for panel attrition. The preexisting panel would have to closel y tracks the U.S. population on age, race, Hispanic ethnicity , geographical region, employ ment status, and other demographic elements. If differences between the panel and the U.S. population do exist, sample weights using U.S. Census demographic benchmarks could be developed to reduce error due to non
coverage of non
- telephone households and to reduce bias due to non
- response and other non
sampling errors. Sample Size The intention is to obtain 2,288 completed web
- based survey s 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 ethnicity , race, gender, and household income. The actual number of panel members contacted for this survey will be determined by

the vendor’s knowledge of within panel response rates. Most likely, the stratification design used in the web
- based survey will120

sy stematically

oversamples groups that tend to have lower response and consistency rates so that the demographic characteristics of respondents who provide valid completed surveys will mirror the Census demographic benchmarks more closel y. This potential oversampling correction technique will reduce error due to non
- coverage of non
- telephone households in the original panel member recruitment process, and will also reduce bias due to non
- response and other non
sampling errors. Survey Response The target response rate for the survey among panel members that are sampled is 80 percent. However, the actual response rate compared to the general population is lower, given that the telephone recruitment process for a preexisting panel has an expected response rate in the 30 to 40 percent range. This will produce a lower cumulative response rate. Panel members who are selected for the survey will be contacted to inform them that the survey is available online and reminders will be sent to panel members who do not complete the survey within a short period of time. Although the cumulative response rate for this survey may be low compared to response rates typicall y achieved using other survey methods (e.g., phone and mail surveys ), the web
based format facilitates geographic and demographic stratification, which will substantially improve the quality

of the survey
. Non

- response and Other Non

- Sampling Error Corrections Approaches to minimize non
- response bias in internet survey s are established in the literature (Dillman 2000) and include initial RDD probability sampling, careful panel management, and effective survey sampling procedures. The representativeness of preexisting panel survey

sample is generall y comparable to those te lephone survey s sponsored by various Federal agencies. Nonetheless, EPA would conduct several additional activities to minimize the potential for non
- response bias if the survey were implemented through the use of a preexisting panel including: (1) use of a stratified survey sample to mitigate the effect of non
- response bias, (2) use of non
- response follow
- up interviews to increase the overall response rate, and (3) statistical correction for unobserved heterogeneity that might be present in the data from respondents interviewed for this study121

Non

- response Interviews In order to minimize non
- response bias from individuals who chose not to respond during some stage of panel recruitment, EPA will conduct non
- response follow
- up interviews within the initial s ample for all stages of panel attrition. Respondents will include individuals who were contacted but did not join the preexisting panel, who agreed to join the panel but did not connect to the vendors web
- site, who connected but did not complete the first survey , who completed the first survey

but did not complete any following surveys, and who completed following surveys but did not complete the 316(b) survey . The end result of this effort will be a direct measurement of non
- response bias and EPA will us e the information to increase the effective cumulative response rate by using a weighted response rate formulation. Statistical Correction for Unobserved Heterogeneity EPA is also considering the use of a statistical technique to correct for unobserved heterogeneity , based on work by Heckman (Heckman, 1979). This correction would be conducted as a complement to a non
- response study effort. The technique will provide the probabilities of participation for each subpopulation grouping (as defined by Censu s long form data, voting data, and other data sources) included in the initial sample frame. These probabilities of participation will demonstrate the extent of self
- selection bias in the actual survey sample. The selection correction technique will take fully into account each stage of the panel recruitment and sampling process: that is, all stages in between construction of the sample frame for panel recruitment and interviewing of the panel respondents. The technique could be used to produce both adj usted and unadjusted estimates of WTP. Because the technique yi elds regression estimates that explain survey outcomes using subpopulation data related to neighborhood characteristics, it can be used to identify the sources of differences between the adjus ted and unadjusted estimates. As described above, EPA will use statistical techniques to correct for unobserved heterogeneity

in the survey

sample and non
- response follow
- up interviews to increase the effective survey

response rate. Combined, these techni ques will reduce error due to non
coverage of non
- telephone households in the original panel recruitment process, and also reduce bias due to non
- response and other non
- sampling errors. For an example of a similar research effort that successfull y used this web
- based survey approach to evaluate WTP for changes in water quality, see Viscusi et al. ( 2008 ).122

Data Preparation Since the survey

will be administered as an online survey , survey responses will be automatically

entered into an electronic database 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.123

Attachment 6 : Telephone Screener Script

Fish and Aquatic Habitat Telephone Screener Hello, this is _________________calling from the Abt Associates. W e 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 w ill help us to better understand the value of environmental protection and public programs. Any answers you give are kept strictly confidential. IF ASKED: This is a short survey which should take no more than five minutes. 0 None THANK AND SCREEN OUT 1 One __ Number of persons 16+ SKIP TO SL1c 98 Refused (VOL) THANK AND TERMINATE

– Soft Refusal 99 Refused (VOL) THANK AND TERMINATE

– Hard Refusal SL1b [A SK IF SAMPLE=LANDLINE] May Ispeak with that person? 1 R spn on line SKIP TO SL2 2 R spn called to phone SKIP TO SL1d 3 R spn unavailable SCHEDULE CALLBACK 8 Refused THANK AND TERMINATE

– Soft Refusal 9 Refused THANK AND TERMINATE

– Hard Refusal SL 1c [ASK IF SAMPLE=LANDLINE] In order to select just one person to interview, may Iplease speak to the person in yo ur household, age 18 or older, who (has had the most recent/will have the next) birthday? 1 Rspn on line SKIP TO SL2 2 Rspn called to phon e 3 Rspn unavailable SCHEDULE CALLBACK 8 Refused THANK AND TERMINATE

– Soft Refusal 9 Refused THANK AND TERMINATE

– Hard Refusal SL1d [ASK IF SAMPLE=LANDLINE]124 Hello, this is _________________calling from the Abt Associates. W e are conducting an important survey o f U.S. residents for the Environmental Protection Agency , or EPA. Could we begin now? IF ASKED: This is a short survey which should take no more than five minutes. 1 Yes 2 No time SCHEDULE CALLBACK 8 Refused THANK AND TERMINATE

– Soft Refusal 9 Refused THANK AND TERMINATE

– Hard Refusal SL2 [ASK IF SAMPLE=LANDLINE] Do you have a cell phone in addition to the line on which we’re speaking right now? 1 Yes, also have cell phone 2 No, this is only

phone SKIP TO SA2 8 (VOL) D on’t know THANK AND END, screen out 9 Refused THANK AND END, soft refusal SC1 [ASK IF SAMPLE = CELL] Are you in a safe place to talk right now? IF NEEDED: Are you Driving? [ IF RESPONDENT ANSWERS YES, DRIVING, SCHEDULE CALLBACK AND TERMINATE
- CODE AS 2] IF ASKED: This is a short survey which should take no more than five minutes. 1 Yes, safe place to talk 2 No, call me later SCHEDULE CALLBACK 3 No, CB on land
- line RECORD NUMBER, schedule call back 4 Cell phone for business only THANK & END - BUSINESS# 8 Refused THANK AND TERMINATE

– Soft Refusal 9 Refused THANK AND TERMINATE

– Hard Refusal SC2 [ASK IF SAMPLE=CELL] Are you at least 18 years old? IF NEEDED: This study w ill help us to better understand the value of environmental protection and public programs. Any answers you give are kept strictly confidential. 1 Yes 2 Yes, no time SCHEDULE CALLBACK 3 No SCREEN OUT125

8 Refused THANK AND TERMINATE

– Soft Refusal 9 Refused THANK AND TERMINATE

– Hard Refusal SC3 [A SK IF SAMPLE=CELL] Do any other people age 18 or older regularl y ANSWER your cell phone, or just you? IN TERVIEWER: This question refers to the phy sical phone and not to their calling plan 1 Yes, others 2 No, just respondent SKIP TO SC4 9 Don’t know/Re fused SKIP TO SC4 SC3b [ASK IF SAMPLE=CELL] How many other people age 18 or older regularl y answer your cell phone?

__ [ENTER NUMBER 1
- 10] 99 Don’t know/Refused SC4 [ASK IF SAMPLE=CELL] Not counting any that are used strictl y for business purposes, are there other cell phones that you use regularl y, 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 regularl y, excluding those u sed only for business purposes?

__ [ENTER NUMBER 1
- 10] 99 Don’t know/Refused SC5 [ASK IF SAMPLE=CELL] Not counting (this/these) cell phone(s), do you also have a regular land
- line phone at home? 1 Yes, has a regular phone at home 2 No, cell is only phone SKIP TO SA2 7 Don’t know (VOL) THANK AND TERMINATE

– Screen out 8 Refused (VOL) THANK AND TERMINATE

– Soft Refusal 9 Refused (VOL) THANK AND TERMINATE

– Hard Refusal126

SA1 [ASK BOTH SAMPLES] Of all of the phone calls that you or your family re ceives, are...(Read List) 1 all or almost all calls received on cell phones, 2 some received on cell phones and some received on land lines, or 3 very few or none on cell phones. 8 (VOL) Don’t know 9 (VOL) Refused SA2 [ASK BOTH SAMPLES] Record gender f

rom observation. (Ask onl y if Necessary) 1 Male 2 Female Q1 [ASK BOTH SAMPLES] First, compared to other issues that the government might address

– such as public safety, education and health

– how important is protecting aquatic ecosystem to you, on a scale of 1 to 5 where 1 is “not important” and 5 is “very important” ? (MATCHES QUESTION 2 IN THE MAIL SURVEY) 1 2 3 4 5 (VOL) Don’t Know (VOL) Refused Q2 [ASK BOTH SAMPLES] People have ideas about the extent to which the government should be involved in protecting the environment. On a scale of 1 to 5 where 1 is “not at all involved” and 5 is “highl y involved”, how involved do you think the government should be in environmental protection? 1 2 3 4 5 (VOL) Don’t Know (VOL) Refused127

Q3 [ASK BOTH SAMPLES] Could you please tell me if you participated in each of following activities during the last ye ar? (DO NOT ROTATE) 1 Yes 2 No 8 (VOL) Don’t Know 9 (VOL) Refused Boating, canoeing, or kayaking 1 2 8 9 Swimming/going to the beach 1 2 8 9 Fresh Water Recreational fishing 1 2 8 9 Salt Water Recreational fishing 1 2 8 9 Fresh Water Recreational fishing 1 2 8 9 Shell fishing or crabbing 1 2 8 9 Scuba diving or snorkeling 1 2 8 9 Now, I have just a few questions for classification purposes. D1 [ASK BOTH SAMPLES] What is your age? ________ Years D on’t Know Ref used D2 [ASK BOTH SAMPLES] What is the highest level of education that you have completed? I s it... (READ LI ST) 1 Less than high school 2 High school or equivalent 3 High school and technical school 4 One or more ye ars of college 5 Bachelor’s degree 6 Graduate degree D3 [ASK BOTH SAMPLES] In cluding everyone living in your household, which of the following categories best describes your total household income before taxes? I s it ... (READ LIST) 1 $10,000 or Less, 2 Between $10,001 and $20,000, 3 Between $20,001 to $35,000, 4 Between $35,001 to $50,000,128

5 Between $50,001 to $75,000, 6 Between $75,001 to $100,000, or 7 More than $100,000 8 (VOL) Do n’t know 9 (VOL) Refused D4 [ ASK BOTH SAMPLES] Are you of Hispanic or Latino origin? 1 Yes 2 No 8 (VOL) D on’t know 9 (VOL) Refused D5 [ ASK BOTH SAMPLES] Which of the following racial categories describes you? You may select more than one. Would it b e... (READ LIST

– MULTIPLE RECORD) 1 American Indian or Alaskan Native, 2 Asian, 3 Black or African American, 4 Native Hawaiian or Other Pacific Islander, or 5 White 6 (VOL) Hispanic / Latino 8 (VOL) Other 9 (VOL) Refused D6 [ ASK BOTH SAMPLES] Do you... (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 mortgage 4 Live with family

or friends and do not pay rent 7 (VOL) Other, Specify 8 (VOL) Other 9 (VOL) Refused RECRUITMENT : In addition to thi s telephone survey , we are also conducting a mail survey to help U.S. policy makers 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 repl y envelope The survey

t akes most people about 30 minutes to complete.129

I1 [ ASK BOTH SAMPLES] Would you be willing to participate in this mail survey? 1 Yes 2 No THANK FOR PARTICIPATION AND TERMINATE 3 Don’t know THANK FOR PARTICIPATION AND TERMINATE 4 Refused THANK FOR PARTICIPATION AND TERMINATE I2 [ ASK BOTH SAMPLES] To what name and address should we mail the survey? (RECORD NAME, ADDRESS, CITY, STATE, AND ZIP CODE AND REPEAT BACK) I3 [ ASK BOTH SAMPLES] And is this the best number to reach you at if we should have a problem mailing your survey? 1 Yes SKIP TO CLOSING 2 No I4 [ ASK BOTH SAMPLES] What is the best number to reach you? (RECORD NUMBER AND REPEAT BACK) CLOSING: Thank you. The survey

will be sent to you in approximately one to two weeks. The pac ket will include information about the study , how to return your survey , and additional contact information in case you have questions. Thank yo u very much for your time, and have a great evening/day
.130

Attachment 7: Cover Letter to Mail Survey Recipients

<date> <given name> <surname> <address> <city>, <state> <zip code>
- <zip+4> Dear <title> <surname>: A few day s ago you agreed to take a short survey regarding environmental protection and government regulations in the Northeast U.S. Thank you fo r agreeing to participate

—the survey booklet is enclosed with this letter. Y our answers to the survey w ill help officials from the Environmental Protection Agency ( EPA) to better understand the value of policies which would affect the future of fish and aquatic habitat in the Northeast. B y filling out this survey , you will be participating in an important study that will help government officials understand your priorities for the environment and regulations. Your responses to this survey are very import ant. Over time, human activities have caused many changes in Northeast’s rivers, streams and bays. The Environmental Protection Agency i s considering policies that could impact the quality of fish and aquatic habitat in these areas. These policies can h ave different effects and costs. Because of this, it is important to know what ty pes of policies are supported by Northeast residents. All answers to the survey are confidential. Once we have received your survey , we will delete yo ur name from all lists, so that your responses can never be traced back to you. Of course, your participation is voluntary and you may refuse to answer any or all questions. We hope that you find this survey important and interesting, and thank you for your assistance in this important project. We would greatly a ppreciate if you could return the survey in the near future.
Sincerel y, Mary T. Smith, Director U. S. Environmental Protection Agency Engineering and Anal ys is Division131

Attachment 8 : Post Card Reminder to Mail S urvey Recipients
FRONT

BACK Abt SRBI Government Services Divison 8403 Colesville Road, Suite 820 Silver Spring, MD, 20910

Last we ek a survey was mailed to you concerning environmental protection and government regulations in the Northeast U.S. If you have already returned your completed survey, please accept our sincere thanks. If you have not yet completed your survey, we ask that you plea se do so today. You are one of a select few who have been chosen to participate

— yo ur answers will help us understand your priorities for the environment and regulations in the Northeast U.S. If you have misplaced your survey, please contact Ryan Stapler at (617) 520
- 3524 or ryan_stapler@abtassoc.com for a replacement. Regards, Mary T. Smith Environmental Protection Agency