and some shows that hypothetical bias may be ameliorated using
cheap-talk, certainty adjustments, or other mechanisms (Champ et al.
1997; Champ et al. 2004; Cummings and Taylor 1999; Loomis et al. 1996).

To obtain reliable estimates of WTP, the Agency tested and designed 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 question format and scenario consequentiality in ensuring this
property (Carson et al. 2000; Carson and Groves 2007; Collins and
Vossler 2009; Herriges et al. 2010; Johnston 2006; Vossler and Evans
2009).  It has been established that referendum-type stated preference
choices are incentive compatible given that certain conditions are met,
including the condition that responses are believed by respondents to be
consequential, or potentially influencing public policy decisions
(Carson and Groves 2007; Herriges et al. 2010).

The survey is explicitly designed to emphasize the importance of the
budget constraint and program cost.  For example, the survey asks
respondents to compare protecting aquatic ecosystems to other policy
issues which the government could 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, thereby maximizing
incentive compatibility (i.e., reducing strategic and hypothetical
biases), following clear guidance of Carson et al. (2000).  Elements
specifically designed to maximize consequentiality include: a)
explicitly mentioning that this survey is associated with assessment of
proposed policies that are being considered, b) numerous details
provided in the survey concerning specifics of the proposed policies,
and c) emphasis that the type of policy enacted will depend in part on
survey results and that their vote is important.  Johnston and Joglekar
(2005) show the capacity of such information to eliminate hypothetical
bias in choice-based stated preference WTP estimation.

Focus groups and cognitive interviews indicated that respondents viewed
choices as consequential, 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 coming
out of their pocket,” the vast majority of focus group and interview
respondents indicated that they treated program costs the same way that
they would have if there were actual money consequences.  For example,
respondents made statements such as “No. [My vote] would have been the
same actually” and “If I believed that it was gonna affect
regulations, I think I would have voted the exact same way.”

EPA does not anticipate significant hypothetical bias in the proposed
survey based on focus group results. Focus groups respondents took the
survey questions seriously and indicated that they though that their
choices would actually influence policy.  Regarding the potential use of
cheap talk mechanisms or other devices to further address the potential
for hypothetical bias, the Agency emphasizes that the literature is
mixed as to their performance.  For example, the seminal work by
Cummings and Taylor (1999) shows that cheap talk is able to reduce
hypothetical biases.  Similar results are shown by Aadland 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 types of respondents.  For
example, Cummings et al. (1995) find that a relatively short cheap talk
script actually worsens hypothetical bias, while a longer script appears
to ameliorate bias.  Brown et al. (2003) finds cheap talk only effective
at higher bid amounts—a result mirrored by Murphy et al. (2004).
Still other authors find no effect of cheap talk, including Poe et al.
(2002).  Given the clearly mixed experiences with such mechanisms, EPA
is not convinced that cheap talk scripts are likely to provide a panacea
for hypothetical bias in the present case—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 Warm-Glow Effects

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

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

This is also consistent with the statement from Arrow et al. (1993) that
a referendum-type format may limit the warm-glow effect.  Some focus
group participants 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 responses do not reflect
symbolic biases.  Question 9 in the survey instrument—which addresses
the rationale for choice responses given earlier in the draft
survey—explicitly tests for the presence of symbolic or warm-glow
biases.  Follow-up questions such as these are common in stated
preference survey instruments, to assess the underlying reasons for the
observed valuation responses (e.g., Mitchell and Carson 1984).

Assessing Scope Sensitivity

The NOAA Blue Ribbon Panel on Contingent Valuation (CV) (Arrow et al.
1993, p. 4605) states clearly that if “surveys are to elicit useful
information about willingness to pay, respondents must understand
exactly what it is they are being asked to value (or vote upon)…”
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 literature (e.g., Mitchell and Carson
1989; Louviere et al. 2000).  Among the reasons for this guidance is
that such descriptions tend to encourage appropriate framing and
sensitivity to scope.

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 generally have shown much less difficulty with respondents
reacting appropriately to the scope and scale of resource changes.
Moreover, as clearly noted by Bennett and Blamey (2001, p. 231),
“internal scope tests are automatically available from the results of
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 sensitivity will therefore be assessed
through model results for the variables Commercial Fish Populations,
Fish Populations (all fish), Fish Saved per Year, and Condition of
Aquatic Ecosystems.  Statistical significance of these variables—along
with a positive sign—indicates that respondents, on average, are more
likely to choose plans with larger quantities of these variables.

In addition to internal scope tests implicit in all choice experiment
statistical analysis, EPA will also conduct external scope tests (cf.
Giraud et al. 1999).  The primary difference between internal and
external tests is that the former assess sensitivity to scope across
choices of a single respondent, while the latter involves split-sample
assessments across different respondents.  Within a choice modeling
context, external scope tests are generally considered “stronger,”
although also more likely to be confounded by differences in the implied
choice frame (Bennett and Blamey 2001).  A variety of options for
external scope tests exist, depending 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 constant across the considered choices
except the scope of the attribute for which the test is to be conducted.
 For example, to conduct an external scope test for reductions in annual
fish losses, one would consider a set of choices that is identical over
two respondent groups, except that one considers a choice with a greater
reduction in fish losses.  Assessing the choices over this split sample
allows for an external test of scope.  To illustrate this test, consider
the following stylized choice between Option A and Option B.  The
generic labels “Level 0”, “Level 1”, and “Level 2” are used
to denote attribute levels, where for all attributes Level 2 > Level 1 >
Level 0.

Table B2:  Illustration of an External Scope Test

Variable	Option A	Option B

Fish Saved per Year

	Sample 1:  Fish Saved Level 1

Sample 2:  Fish Saved Level 2	Fish Saved Level 0

Commercial Fish 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 Ecosystems	Aquatic Ecosystem Condition

Level 0	Aquatic Ecosystem Condition

Level 0

Increase in Cost of Living for Your Household	Cost Level 1	Cost Level 0

In the above example, only Fish Saved per Year and Cost vary across the
choice options.  Because both Fish Saved per Year (at Level 1 and Level
2) and Cost are higher in Option A than in Option B, neither option is
dominant.  In the illustrated split-sample test, respondent sample 1
views the choice with Fish Saved per Year at Level 1, while respondent
sample 2 views an otherwise identical choice with Fish Saved per Year at
Level 2, where Level 2 > Level 1.  If responses are externally sensitive
to scope in Fish Saved per Year, this will manifest in a greater
proportion of sample 2 respondents choosing Option A than sample 1
respondents.  This hypothesis may be easily assessed using a test of
equal proportions across the two sub-samples, and provides a simple
attribute-by-attribute test of external scope.  Analogous tests may be
conducted for all attributes within the choice experiment design, using
parallel methods. EPA emphasizes that the formal applicability of the
above-noted scope test is contingent upon the specific choice frame
implied by levels of other attributes in the choice question.  This is a
characteristic of nearly all external scope tests applied in choice
experiment frameworks (Bennett and Blamey 2001).

Split-sample tests such as those proposed above often require the
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 ecosystem condition attributes),
still additional 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 Uncertainty to Respondents

EPA believes that the role of risk and uncertainty is an important issue
to be addressed in the development of benefits estimates, and points out
that the literature provides numerous examples of cases in which
appropriate survey design, including focus groups, was used to
successfully address such concerns.  For example, as stated by
Desvousges et al. (1984), “using contingent valuation to estimate the
benefits of hazardous waste management regulations requires detailed
information on how and the extent to which respondents understand risk
(or probability) and how government regulatory actions might change
it… Using focus groups helped make this determination…”  EPA also
emphasizes that all regulatory analyses involve uncertainty of some 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.  Hence,
the proposed survey materials clearly indicate the uncertainty involved
with the described resource changes in choice modeling scenarios, yet do
so in a way designed to minimize cognitive burden.

For example, prior to answering choice experiment questions, respondents
are told:

 “Although scientists can predict the number of fish saved each year,
the effect on fish populations is uncertain. This is because scientists
do not know the total number of fish in Northeast waters and because
many factors – such as cooling water use, fishing, pollution and water
temperature – affect fish populations.”

This statement clearly indicates 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 changes 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 introductory
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 purposefully, but I know
that this is a best guess, reasonable guess perhaps”, “it shows me
that they are being honest for the most part. You know, you can't
obviously be accurate on everything, but this is a kind of a best
guess”, “[…] They had more numbers on the commercial fish
population. The rest was more of a guesstimate”, 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 the use of ranges was more confusing than the
use of point estimates.  Furthermore, respondents were comfortable
making decisions in the presence of this uncertainty.

5(c)	Reporting Results

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

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Questionnaires, eds. S. Presser, J.M. Rothget, M.P. Coupter, J.T.
Lesser, E. Martin, J. Martin, and E. Singer.  New York:  John Wiley and
Sons.

Kobayashi, M.K. Rollins, and M.D.R Evans. 2010. “Sensitivity of WTP
Estimates to Definition of 'Yes': Reinterpreting Expressed Response
Intensity.” Agricultural and Resource Economics Review 39(1): 37-55.

Kuhfeld, W.F. 2009. “Experimental Design:  Efficiency, Coding and
Choice Designs.”  SAS Institute.  HYPERLINK
"http://support.sas.com/techsup/tnote/tnote_stat.html" \l "market"
http://support.sas.com/techsup/tnote/tnote_stat.html#market .

Layton, D.F. 2000.  “Random coefficient models for stated preference
surveys.” Journal of Environmental Economics and Management 40(1):
21-36.

List, J.A. 2001. “Do Explicit Warnings Eliminate the Hypothetical Bias
in Elicitation Procedures? Evidence from Field Auctions for
Sportscards.” American Economic Review 91(5): 1498-1507.

Loomis, J., T. Brown, B. Lucero, and G. Peterson. 1996. “Improving
Validity Experiments of Contingent Valuation Methods: Results of Efforts
to Reduce the Disparity of Hypothetical and Actual Willingness to
Pay.” Land Economics 72(4): 450-461.

Louviere, J.J., D.A. Hensher, and J.D. Swait. 2000. Stated Preference
Methods:  Analysis and Application. Cambridge, UK: Cambridge University
Press.

Maddala, G.S. 1983. “Limited-Dependent and Qualitative Variables in
Econometrics.”  Econometric Society Monographs No. 3, Cambridge
University Press, Cambridge.

Mazzotta, M.J., J.J. Opaluch, G. Magnuson, and R.J. Johnston. 2002.
“Setting Priorities for Coastal Wetland Restoration: A GIS-Based Tool
That Combines Expert Assessments And Public Values.” Earth System
Monitor 12(3): 1-6.

McConnell, K.E. 1990. “Models for Referendum Data:  The Structure of
Discrete Choice Models for Contingent Valuation.” Journal of
Environmental Economics and Management 18(1): 19-34.

McFadden, D., and K. Train. 2000. “Mixed Multinomial Logit Models for
Discrete Responses.” Journal of Applied Econometrics 15(5): 447-470.

  SEQ CHAPTER \h \r 1 Mitchell, R.C., and R.T. Carson. 1981. An
Experiment in Determining Willingness to Pay for National Water Quality
Improvements. Preliminary draft of a report to the U.S. Environmental
Protection Agency. Resources for the Future, Inc., Washington.

Mitchell, R.C., and R.T. Carson. 1984. A Contingent Valuation Estimate
of National Freshwater Benefits: Technical Report to the U.S.
Environmental Protection Agency.  Washington, DC: Resources for the
Future.

Mitchell, R.C., and R.T. Carson. 1989. Using Surveys to Value Public
Goods: The Contingent Valuation Method. Resources for the Future,
Washington, D.C.

Morrison, M., and J. Bennett. 2004. Valuing New South Wales rivers for
use in benefit transfer. Australian Journal Of Agricultural And Resource
Economics 48(4): 591-611.

Murphy, J.J., T. Stevens, and D. Weatherhead. 2004. “Is Cheap Talk
Effective at Eliminating Hypothetical Bias in a Provision Point?”
Working Paper No. 2003-2. Department of Resource Economics, University
of Massachusetts, Amherst.

  SEQ CHAPTER \h \r 1 Olsen, D., J. Richards, and R.D. Scott. 1991.
“Existence and Sport Values for Doubling the Size of Columbia River
Basin Salmon and Steelhead Runs.” Rivers 2(1): 44-56.

Opaluch, J.J., T.A. Grigalunas, M. Mazzotta, R.J. Johnston, and J.
Diamantedes. 1999. Recreational and Resource Economic Values for the
Peconic Estuary.  Prepared for the Peconic Estuary Program.  Peace Dale,
RI: Economic Analysis Inc.  124 pp.

Opaluch, J.J., S.K. Swallow, T. Weaver, C. Wessells, and D. Wichelns.
1993. “Evaluating impacts from noxious facilities:  Including public
preferences in current siting mechanisms.” Journal of Environmental
Economics and Management 24(1): 41-59.

Poe, G. L., J.E. Clark, D. Rondeau, and W.D. Schulze. 2002. “Provision
Point Mechanisms and Field Validity Tests of Contingent Valuation.”
Environmental and Resource Economics 23: 105-131.

Poe, G.L., M.P. Welsh, and P.A. Champ. 1997. “Measuring the Difference
in Mean Willingness to Pay when Dichotomous Choice Contingent Valuation
Responses are not Independent.” Land Economics 73(2): 255-267.

Powe, N.E. 2007. Redesigning Environmental Valuation: Mixing Methods
within Stated Preference Techniques. Cheltenham, UK: Edward Edgar.

Powe, N.A., and I.J. Bateman. 2004. “Investigating Insensitivity to
Scope:  A Split-Sample Test of Perceived Scheme Realism.” Land
Economics 80(2): 258-271.

Ready, R.C., P.A. Champ, and J.L. Lawton. 2010. “Using Respondent
Uncertainty to Mitigate Hypothetical Bias in a Stated Choice
Experiment.” Land Economics 86(2): 363-381.

Ready, R.C., J.C. Whitehead, and G.C. Blomquist. 1995. “Contingent
Valuation When Respondents are Ambivalent.” Journal of Environmental
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Hypothetical Offers.” Journal of Environmental Economics and
Management 36: 209-224.

Schkade, D.A. and J.W. Payne. 1994. “How People Respond to Contingent
Valuation Questions:  A Verbal Protocol Analysis of Willingness to Pay
for an Environmental Regulation.” Journal of Environmental Economics
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"http://www.bls.gov/news.release/ecec.t01.htm"
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Value of Water Quality.”  Environmental and Resource Economics 41(2):
169-187.

Vossler, C.A., and M.F. Evans. 2009. “Bridging the gap between the
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the Contingent Valuation Method:  Comparing Hypothetical and Actual
Voting Behavior for a Public Referendum.” Journal of Environmental
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“Assessing the Validity and Reliability of Contingent Values: A
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Attachment 1: Full Text of Regional Stated Preference Survey Component
(Northeast Regional Example)

Fish and Aquatic Habitat

A Survey of Northeast Residents

(CT, DC, DE, MA, MD, ME, NH, NJ, NY, PA, RI, VT)

Human Activities, Aquatic 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.

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

How Does Cooling Water 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.

what kinds of Fish are Affected?

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

About 1/6 of the fish lost are species 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 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

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

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

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

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

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

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

how many fish are affected?

After accounting for the number of eggs and larvae that would be
expected to survive to adulthood, scientists estimate that the
equivalent of about 1.1 billion young adult fish (the equivalent of one
year old) are lost each year in Northeast coastal and fresh waters due
to cooling water use.

Scientists can predict the number of these fish that will be saved under
different policies.  This number ranges from 0.3 to 1.0 billion fish
saved per year.

For commercial fish species, losses of young fish in cooling water
intakes vary by species, from the equivalent of less than 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,
but low for others.

Although scientists can predict the number of fish saved each year, the
effect on fish populations is uncertain. This is because scientists do
not know the total number of all fish in Northeast waters and because
many factors – such as cooling water use, fishing, pollution and water
temperature – affect fish populations.

New Regulations are Being Proposed to protect fish

Advanced filters and closed cycle cooling are already in use at many
facilities and are proven technologies. New regulations would require a
mix of advanced filters and closed cycle cooling at all
facilities—with reductions in fish losses between 25% and 95%.

How important are these issues to you?

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

Question 2. Compared to other issues that the government might
address—such as public safety, education and health—how important is
protecting aquatic ecosystems to you? Check one box.

	Not Important

	Somewhat Important

Protecting aquatic ecosystems is	(1	(2	(3	(4	(5

The government needs to know whether households are willing to pay the
costs of these new policies.

This survey will ask you to compare policies with different effects on
cooling water use, fish, and costs to your household. You will be asked
to vote for the options you prefer.

You will also have the opportunity to support the current situation,
with no new policies, and no new costs to your household.

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:

Commercial Fish Populations

Fish Populations

Fish Saved

Condition of

Aquatic Ecosystems

A score between 0 to 100 showing the ecological condition of affected
areas, compared to the most natural waters in the Northeast. The score
is determined by many factors including water quality and temperature,
the health of aquatic species, and habitat conditions.  Higher scores
mean the area is more natural. The current score in Northeast waters is
48.

$

Cost per Year

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

How Would you rate tHE IMPoRTANCE OF TheSE EFFECTS?

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

	Not Important

	Somewhat Important

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

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

Effect on fish saved	(1	(2	(3	(4	(5

Effect on the condition of aquatic ecosystems	(1	(2	(3	(4	(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 checking
the appropriate box. Questions will look similar to the sample on the
next page.

SAMPLE QUESTION

Questions will look like the sample below.

Policy Effect

Current Situation

Commercial Fish Populations

(in 3-5 Years)

43%

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

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

Fish Populations

(all fish)

(in 3-5 Years)

31%

(100% is populations without human influence)	34%

(100% is populations without human influence)	38%

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%

Condition of Aquatic Ecosystems

(in 3-5 Years)

48%

(100% is pristine condition) 	48%

(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?

(

I would vote for

(

I would vote for

(

I would vote for

As you vote please remember

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

Consider each pair of policy options separately—do not add them up or
compare programs from different pages.

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

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

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

Policy Effect

NE Waters

Current Situation

(No policy)	Option A

NE Waters	Option B

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%

Fish Populations

(all fish)

(in 3-5 Years)

31%

100% is populations without human influence)	32%

(100% is populations without human influence)	35%

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%

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?

(CHOOSE ONE ONLY)

(

I would vote for

 NO POLICY	(

I would vote for

OPTION A	(

I would vote for

POLICIES COULD REQUIRE DIFFERENT COMBINATIONS OF TECHNOLOGY

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

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

Each 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.

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

Policy Effect

NE Waters

Current Situation

(No policy)	Option A

NE Waters	Option B

Commercial Fish Populations

(in 3-5 Years)

43%

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

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

Fish Populations

(all fish)

(in 3-5 Years)

31%

(100% is populations without human influence)	33%

(100% is populations without human influence)	36%

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%

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

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

Policy Effect

NE Waters

Current Situation

(No policy)	Option A

NE Waters	Option B

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%

Fish Populations

(all fish)

(in 3-5 Years)

31%

(100% is populations without human influence)	39%

(100% is populations without human influence)	36%

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%

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 per month)

 	$24

per year

($2 per month)

HOW WOULD YOU VOTE?

(CHOOSE ONE ONLY)

(

I would vote for

 NO POLICY	(

I would vote for

OPTION A	(

I would vote for

OPTION B

Question 7.  If you always voted for NO POLICY in questions 4-6, what
was the primary reason?  Check one. (Skip this question if you voted for
Option A or B in any question above.)

____ The cost to my household was too high

____ Preventing fish losses is not important to me

____ I do not trust 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 with the following
statements about questions 4 - 6 and the information provided. Check one
box for each.

Question 9.  How much did the following factors affect your answers to
questions 4 – 6?  Check one box for each row.

Moderate Effect

Very Large Effect

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

	Number of days you did the activity during the past year

	0	1-5	6-10	11-15	16+

	Boating / Canoeing / Kayaking	(1	(2	(3	(4	(5

Swimming / Going to the Beach	(1	(2	(3	(4	(5

Recreational Fishing (Fresh Water)	(1	(2	(3	(4	(5

Recreational Fishing (Salt Water)	(1	(2	(3	(4	(5

Shellfishing / Crabbing	(1	(2	(3	(4	(5

Scuba Diving / Snorkeling	(1	(2	(3	(4	(5

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

What is your age?	years

What is your gender?   Male    Female

What is the highest level of education that you have completed?

Less than high school               	One or more years of
college

High school or equivalent	Bachelor’s Degree

High school + technical school  Graduate Degree

How many people live in your household?

How many of these people are 16 years of age or older? ____

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

What is your zip code?

What town and state do you live in? Town:			State:____

Are you currently employed?	Yes	No

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

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

Thank you for your participation in this important survey!Attachment
2: Full Text of National Stated Preference Survey Component

Fish and Aquatic Habitat

A Survey of US Households

Human Activities, Aquatic 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. 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.

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

How Does Cooling Water 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.

what kinds of Fish are Affected?

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

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

The other 2/3 of the fish lost are 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

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

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

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

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

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

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

how many fish are affected?

After accounting for the number of eggs and larvae that would be
expected to survive to adulthood, scientists estimate that the
equivalent of about 2.7 billion young adult fish (the equivalent of one
year old) are lost each year in U.S. coastal and fresh waters due to
cooling water use.

Scientists can predict the number of these fish that will be saved under
different policies.  This number ranges from 0.7 to 2.6 billion fish
saved per year.

For commercial fish species, losses of young fish in cooling water
intakes vary by species, from the equivalent of less than 0.1% to about
10% of total populations.

Yearly effects on fish species are between these levels. For example,
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,
but low for others.

Although scientists can predict the number of fish saved each year, the
effect on fish populations is uncertain. This is because scientists do
not know the total number of all fish in U.S. waters and because many
factors – such as cooling water use, fishing, pollution and water
temperature – affect fish populations.

New Regulations are Being Proposed to protect fish

Advanced filters and closed cycle cooling are already in use at many
facilities and are proven technologies. New regulations would require a
mix of advanced filters and closed cycle cooling at all
facilities—with reductions in fish losses between 25% and 95%.

How important are these issues to you?

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

Question 2. Compared to other issues that the government might
address—such as public safety, education and health—how important is
protecting aquatic ecosystems to you? Check one box.

	Not Important

	Somewhat Important

Protecting aquatic ecosystems is	(1	(2	(3	(4	(5

The government needs to know whether households are willing to pay the
costs of these new policies.

This survey will ask you to compare policies with different effects on
cooling water use, fish, and costs to your household. You will be asked
to vote for the options you prefer.

You will also have the opportunity to support the current situation,
with no new policies, and no new costs to your household.

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:

Commercial Fish Populations

Fish Populations

Fish Saved

Condition of

Aquatic Ecosystems

A score between 0 to 100 showing the ecological condition of affected
areas, compared to the most natural waters in the 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. waters is 48.

$

Cost per Year

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

How Would you rate tHE IMPoRTANCE OF TheSE EFFECTS?

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

	Not Important

	Somewhat Important

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

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

Effect on fish saved	(1	(2	(3	(4	(5

Effect on the condition of aquatic ecosystems	(1	(2	(3	(4	(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 checking
the appropriate box. Questions will look similar to the sample on the
next page.

SAMPLE QUESTION

Questions will look like the sample below.

Policy Effect

Current Situation

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%

Fish Populations

(all fish)

(in 3-5 Years)

39%

(100% is populations without human influence)	42%

(100% is populations without human influence)	42%

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%

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?

(

I would vote for

(

I would vote for

(

I would vote for

As you vote please remember

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

Consider each pair of policy options separately—do not add them up or
compare programs from different pages.

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

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

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

Policy Effect

US

Current Situation

(No policy)	Option A

US	Option B

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%

Fish Populations

(all fish)

(in 3-5 Years)

39%

100% is populations without human influence)	40%

(100% is populations without human influence)	43%

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%

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 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

POLICIES COULD REQUIRE DIFFERENT COMBINATIONS OF TECHNOLOGY

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

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

Each 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.

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

Policy Effect

US

Current Situation

(No policy)	Option A

US	Option B

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%

Fish Populations

(all fish)

(in 3-5 Years)

39%

(100% is populations without human influence)	41%

(100% is populations without human influence)	43%

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%

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

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

Policy Effect

US

Current Situation

(No policy)	Option A

US	Option B

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%

Fish Populations

(all fish)

(in 3-5 Years)

39%

(100% is populations without human influence)	47%

(100% is populations without human influence)	44%

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%

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

Question 7.  If you always voted for NO POLICY in questions 4-6, what
was the primary reason?  Check one. (Skip this question if you voted for
Option A or B in any question above.)

____ The cost to my household was too high

____ Preventing fish losses is not important to me

____ I do not trust 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 with the following
statements about questions 4 - 6 and the information provided. Check one
box for each.

Question 9.  How much did the following factors affect your answers to
questions 4 – 6?  Check one box for each row.

Moderate Effect

Very Large Effect

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

	Number of days you did the activity during the past year

	0	1-5	6-10	11-15	16+

	Boating / Canoeing / Kayaking	(1	(2	(3	(4	(5

Swimming / Going to the Beach	(1	(2	(3	(4	(5

Recreational Fishing (Fresh Water)	(1	(2	(3	(4	(5

Recreational Fishing (Salt Water)	(1	(2	(3	(4	(5

Shellfishing / Crabbing	(1	(2	(3	(4	(5

Scuba Diving / Snorkeling	(1	(2	(3	(4	(5

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

What is your age?	years

What is your gender?   Male    Female

What is the highest level of education that you have completed?

Less than high school               	One or more years of
college

High school or equivalent	Bachelor’s Degree

High school + technical school Graduate Degree

How many people live in your household?

How many of these people are 16 years of age or older? ____

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

What is your zip code?

What town and state do you live in? Town:			State:____

Are you currently employed?	Yes	No

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

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

Thank you for your participation in this important survey!

Attachment 3: Federal Register Notice

ENVIRONMENTAL PROTECTION AGENCY

[EPA-HQ-OW-2010-0595; FRL - ]

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

AGENCY:	Environmental Protection Agency (EPA).

ACTION:	Notice.

SUMMARY:	In compliance with the Paperwork Reduction Act (PRA) (44 U.S.C.
3501 et seq.), this document announces that 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 collection.
The ICR, which is abstracted below, describes the nature of the
information collection and its estimated burden and cost.

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

ADDRESSES:  Submit your comments, identified by Docket ID No.
EPA-HQ-OW-2010-0595 to:

(1) EPA by one of the following methods:

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

Email<EMAIL_ADDRESS>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-2010-0595. Please include a total of 3 copies.

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

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

FOR FURTHER INFORMATION CONTACT:  Erik Helm, Office of Water, Office of
Science and Technology, Engineering and Analysis Division, Economic and
Environmental Assessment Branch, 4303T, Environmental Protection Agency,
1200 Pennsylvania Ave., NW, Washington, DC 20460; telephone number:
202-566-1049; fax number:<PHONE_NUMBER>; email address:
<EMAIL_ADDRESS>
SUPPLEMENTARY INFORMATION:  EPA has submitted the following ICR to OMB
for review and approval according to the procedures prescribed in 5 CFR
1320.12. On July 21, 2010 (74 FR 42438), EPA sought comments on this ICR
pursuant to 5 CFR 1320.8(d).  EPA received five comments during the
comment period, which are addressed in the ICR.  Any additional comments
on this ICR should be submitted to EPA and OMB within 30 days of this
notice.

	EPA has established a public docket for this ICR 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 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<PHONE_NUMBER>, and the telephone
number for the Water Docket is<PHONE_NUMBER>.

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

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

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

ICR status:  This ICR is for a new information collection activity.  An
Agency may not conduct or sponsor, and a person is not required to
respond to, a collection of information, unless it displays a currently
valid OMB control number.  The OMB control 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 by other appropriate means, such
as on the related collection instrument or form, if applicable.  The
display of OMB control numbers in certain EPA regulations is
consolidated in 40 CFR part 9.

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

Under Executive Order 12866, EPA is required to estimate the potential
benefits and costs to society of proposed rule options of significant
rules.  To assess the importance of the ecological gains from the
section 316(b) regulation, EPA requests approval from the OMB to conduct
a stated preference survey.  Data from the associated stated preference
survey will be used to estimate values (willingness to pay, or WTP)
derived by households for changes related to the reduction of fish
losses at CWIS, 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 by 316(b) facilities;
[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 and 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 elicitation questions ask respondents whether or not they would
vote for policies that would increase their cost of living, in exchange
for specified multi-attribute changes in [a] impingement and entrainment
losses of fish, [b] commercial fish populations, [c] long-term
populations of all fish, and [d] condition of aquatic ecosystems.  The
respondents’ stated preferences with respect to levels of
environmental goods and cost to households, when used in conjunction
with other information collected in the survey on the use of the
affected aquatic resources, household income, and other demographics,
can be analyzed statistically (using a mixed logit framework) to
estimate total WTP for the quantified environmental benefits of the
316(b) rulemaking. Data analysis and interpretation is grounded in a
standard random utility model.

The welfare values that can be derived from this stated preference
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 minutes per mail survey
respondent including the time necessary to complete and mail back the
questionnaire. Burden means the total time, effort, or financial
resources expended by persons to generate, maintain, retain, or disclose
or provide information to or for a Federal agency.  This includes the
time needed to review instructions; develop, acquire, install, and
utilize technology and systems for the purposes of collecting,
validating, and verifying information, processing and maintaining
information, and disclosing and providing information; adjust the
existing ways to comply with any previously applicable instructions and
requirements which have subsequently changed; train personnel to be able
to respond to a collection of information; search data sources; complete
and review the collection of information; and transmit or otherwise
disclose the information.

	The ICR provides a detailed explanation of the Agency’s estimate,
which is only briefly summarized here:

	Respondents:  Individuals from US households

Estimated total number of potential respondents: 9,533 for telephone
screening and 2,288 for mailed questionnaires.

	Frequency of response:  one-time response.

	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.

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 required. Part B of this supporting statement provides
detail on the sampling design. The proposed design and sampling plan is
based on standard design and sampling theory for choice experiments and
population surveys, as outlined by Louviere et al. (2000), Kuhfeld
(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 feasibility, 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 population. 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
characterized by levels for the following six attributes:

Location in A and B (x1A; x1B) – 2 possible levels

Fish Saved per Year in A and B (x2A; x2B) – 3 possible levels

Commercial Fish Populations in A and B (x3A; x3B) – 3 possible levels

Fish Populations (all fish) in A and B (x4A; x4B) – 3 possible levels

Aquatic Ecosystem Condition in A and B (x5A; x5B) – 3 possible levels

Cost in A and B (x6A; x6B) -  6 possible levels

This implies an experimental design characterized by [2×34×6] for each
alternative, or [22×38×62] 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 22 38 62
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 levels indicated by
integers 1...N, where N for each attribute is the number of levels
identified above:

Table 1: Set of 72 Design Profiles

Obs	x1A	x2A	x3A	x4A	x5A	x6A	x1B	x2B	x3B	x4B	x5B	x6B

1	1	1	1	1	1	1	1	1	1	1	1	1

2	1	1	1	1	2	2	2	2	2	2	2	2

3	1	1	1	3	1	6	2	2	3	3	1	3

4	1	1	1	3	3	5	2	1	1	2	3	2

5	1	1	2	2	1	3	1	1	3	2	2	3

6	1	1	2	2	2	1	2	3	1	1	2	4

7	1	1	2	2	3	4	1	2	2	2	1	1

8	1	1	2	2	3	6	1	3	2	3	3	6

9	1	1	3	1	1	2	1	3	2	3	2	5

10	1	1	3	1	2	3	2	1	3	1	3	6

11	1	1	3	3	2	4	1	2	1	3	3	4

12	1	1	3	3	3	5	2	3	3	1	1	5

13	1	2	1	1	2	4	2	3	3	2	1	6

14	1	2	1	2	2	5	1	3	3	3	2	1

15	1	2	1	2	3	2	1	3	1	1	3	3

16	1	2	1	3	1	3	2	3	2	2	3	4

17	1	2	2	1	1	5	2	1	2	3	1	4

18	1	2	2	1	3	1	2	2	3	2	3	5

19	1	2	2	3	1	2	1	2	1	1	1	6

20	1	2	2	3	2	6	1	1	1	2	2	5

21	1	2	3	1	3	4	1	1	1	3	2	3

22	1	2	3	2	1	1	1	2	3	3	3	2

23	1	2	3	2	2	6	1	1	2	1	1	2

24	1	2	3	3	3	3	1	2	2	1	2	1

25	1	3	1	1	3	6	2	2	3	1	2	4

26	1	3	1	2	1	4	2	1	2	1	3	5

27	1	3	1	2	2	3	1	2	1	3	1	5

28	1	3	1	3	3	1	1	1	2	3	2	6

29	1	3	2	1	2	5	2	2	2	1	3	3

30	1	3	2	1	3	3	2	3	1	3	1	2

31	1	3	2	3	1	4	2	3	3	1	2	2

32	1	3	2	3	2	2	2	1	3	3	3	1

33	1	3	3	1	1	6	1	3	1	2	3	1

34	1	3	3	2	1	5	2	2	1	2	2	6

35	1	3	3	2	3	2	1	1	3	2	1	4

36	1	3	3	3	2	1	2	3	2	2	1	3

37	2	1	1	1	1	1	2	1	1	1	1	1

38	2	1	1	1	2	2	1	2	2	2	2	2

39	2	1	1	3	1	6	1	2	3	3	1	3

40	2	1	1	3	3	5	1	1	1	2	3	2

41	2	1	2	2	1	3	2	1	3	2	2	3

42	2	1	2	2	2	1	1	3	1	1	2	4

43	2	1	2	2	3	4	2	2	2	2	1	1

44	2	1	2	2	3	6	2	3	2	3	3	6

45	2	1	3	1	1	2	2	3	2	3	2	5

46	2	1	3	1	2	3	1	1	3	1	3	6

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 questions per survey.  This will allow the 72
profiles to be included (orthogonally blocked) in 24 unique survey
booklets. Monte Carlo experiments indicate that approximately 6
completed responses are required for each profile in order to achieve
large sample 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 for 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 sample sizes to estimate population parameters with given
degrees of freedom are drawn from standard statistical theory, as
described by Dillman (2000).

The maximum acceptable sampling error for predicting response
probabilities (the likelihood of choosing a given 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
surveys. Statistical theory shows that 400 assumed-independent profile
responses will allow a 50% choice probability to be estimated within
±4.9 percent, at a 95% confidence level. With only a single choice
question per survey (144 responses), the same probability and confidence
level can be obtained within approximately ±8.2  percent; this is also
within acceptable limits.

Experimental Design Allowing Two-Way Interactions with Location (x1A;
x1B)

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 (X2 – X6) across both
alternatives A and B, [38×62].  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	4

14	2	1	2	2	5	2	1	3	3	3

15	2	1	3	2	1	3	2	3	3	5

16	2	1	3	3	3	1	3	1	2	2

17	2	2	1	1	3	3	2	2	1	3

18	2	2	2	3	1	1	1	2	2	4

19	2	2	3	2	4	2	2	1	2	1

20	2	2	3	3	6	2	3	3	1	6

21	2	3	1	2	2	1	1	1	3	6

22	2	3	1	3	4	3	1	2	3	2

23	2	3	2	1	2	3	3	3	2	1

24	2	3	2	1	6	1	2	2	1	5

25	3	1	1	3	2	2	3	2	2	5

26	3	1	1	3	6	1	2	3	3	1

27	3	1	2	1	3	3	1	3	2	6

28	3	1	3	1	4	1	3	2	3	3

29	3	2	1	2	1	3	3	3	1	2

30	3	2	1	2	5	1	2	2	2	6

31	3	2	2	1	6	2	1	1	3	2

32	3	2	3	1	2	3	2	1	3	4

33	3	3	2	2	4	1	3	3	1	4

34	3	3	2	3	1	2	2	1	2	3

35	3	3	3	2	3	2	1	2	1	1

36	3	3	3	3	5	3	1	1	1	5

This design is then repeated for each of the four possible combinations
of values for x1A and x1B (i.e., 1,1; 2,2; 1,2; 2,1) creating a
candidate design of 36×4 = 144 profiles.  The resulting design fully
insulates all main effects (eliminates aliasing) from interactions with
location attributes x1A and x1B, 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 profiles
by the three choice questions per survey.  The total number of completed
surveys required (288) is based on a requirement of six completed
surveys per survey version (48) to estimate the main effects and
interactions.  As above, the number of observations (completed surveys)
required to obtain large sample properties for the choice experiment
design provide sufficient observations to obtain required precision for
population parameters.  Also as above, this candidate design may be
subject to refinements based on design evaluations, as described by
Louviere et al. (2000) and Kuhfeld (2009), but this is unlikely to alter
design dimensions.

Attachment 5: Description of Internet-based Sampling Alternative

EPA is also considering the use of an internet-based (i.e., web-based)
sampling approach as an alternative to the mail survey described in Part
B of the supporting statement.  The survey content, pre-testing, review
process, and data analysis would be identical to the mail survey
described in Parts A and B of the supporting statement.  To support
implementation of the web-based alternative, EPA would retain a vendor
that maintains a preexisting representative national panel.  This
attachment provides a brief summary of the web-based alternative,
focusing on differences from the mail survey approach described in Part
B of the supporting statement.

Sampling Frame

The sampling frame for the web-based survey is the panel of individuals
previously recruited by a vendor to participate in online surveys.  The
overall sampling frame would be the set of all individuals in
continental U.S. households who are 18 years of age or older and who
have listed phone numbers.  Individuals in the panel most likely be
recruited using a list-assisted random digit dialing telephone
methodology, thus providing a probability-based starting sample of U.S.
telephone households.  Panels of this type are usually routinely
supplemented to account for panel attrition.  The preexisting panel
would have to closely tracks the U.S. population on age, race, Hispanic
ethnicity, geographical region, employment status, and other demographic
elements.  If differences between the panel and the U.S. population do
exist, sample weights using U.S. Census demographic benchmarks could be
developed to 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 surveys from the
preexisting panel.  The same geographically stratified design will be
implemented following the same the same regions and sample sizes as
described in Part B of the supporting statement under the mail survey
approach.  Within each region, the sample will be stratified by
demographic variables including age, education, Hispanic 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 will systematically oversamples groups that
tend to have lower response and consistency rates so that the
demographic characteristics of respondents who provide valid completed
surveys will mirror the Census demographic benchmarks more closely.
This potential oversampling correction technique will reduce error due
to non-coverage of non-telephone households in the original panel member
recruitment process, and will also reduce bias due to non-response and
other non-sampling 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 typically achieved using other survey methods
(e.g., phone and mail surveys), the web-based format facilitates
geographic and demographic stratification, which will substantially
improve the quality of the survey.

Non-response and Other Non-Sampling Error Corrections

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

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 sample 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 use 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 Census long
form data, voting data, and other data sources) included in the initial
sample frame.  These probabilities of participation will demonstrate the
extent of self-selection bias in the actual survey sample.  The
selection correction 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 adjusted and unadjusted
estimates of WTP.  Because the technique yields regression estimates
that explain survey outcomes using subpopulation data related to
neighborhood characteristics, it can be used to identify the sources of
differences between the adjusted 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 techniques will reduce error due to non-coverage of non-telephone
households in the original panel recruitment process, and also reduce
bias due to non-response and other non-sampling errors.  For an example
of a similar research effort that successfully used this web-based
survey approach to evaluate WTP for changes in water quality, see
Viscusi et al. (2008).

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.

Attachment 6: Telephone Screener Script

Fish and Aquatic Habitat Telephone Screener

Hello, this is _________________calling from the Abt Associates.  We are
conducting an important survey of U.S. residents for the Environmental
Protection Agency, or EPA. This is not a sales call.

SL1	[ASK IF SAMPLE=LANDLINE]

Could you please tell me how many people, age 18 and older, live in this
household?

IF NEEDED:  This study will help us to better understand the value of
environmental protection and public programs. Any answers you give are
kept strictly confidential.

IF ASKED:  This is a short survey which should take no more than five
minutes.

0	None					THANK AND SCREEN OUT

1	One

__  Number of persons 16+		SKIP TO SL1c

98	Refused (VOL)			THANK AND TERMINATE – Soft Refusal

99	Refused (VOL)			THANK AND TERMINATE – Hard Refusal

SL1b	[ASK IF SAMPLE=LANDLINE]

May I speak with that person?

1	Rspn on line		SKIP TO SL2

2	Rspn called to phone	SKIP TO SL1d

3	Rspn unavailable		SCHEDULE CALLBACK

8	Refused			THANK AND TERMINATE – Soft Refusal

9	Refused  			THANK AND TERMINATE – Hard Refusal

SL1c	[ASK IF SAMPLE=LANDLINE]

In order to select just one person to interview, may I please speak to
the person in your household, age 18 or older, who (has had the most
recent/will have the next) birthday?

1	Rspn on line		SKIP TO SL2

2	Rspn called to phone

3	Rspn unavailable		SCHEDULE CALLBACK

8	Refused			THANK AND TERMINATE – Soft Refusal

9	Refused			THANK AND TERMINATE – Hard Refusal

SL1d	[ASK IF SAMPLE=LANDLINE]

Hello, this is _________________calling from the Abt Associates.  We are
conducting an important survey of U.S. residents for the Environmental
Protection Agency, or EPA.  Could we begin now?

IF ASKED:  This is a short survey which should take no more than five
minutes.

1	Yes

2	No	time			SCHEDULE CALLBACK

8	Refused			THANK AND TERMINATE – Soft Refusal

9	Refused  			THANK AND TERMINATE – Hard Refusal

SL2	[ASK IF SAMPLE=LANDLINE]

Do you have a cell phone in addition to the line on which we’re
speaking right now?

1	Yes, also have cell phone

2	No, this is only phone		SKIP TO SA2

8	(VOL) Don’t know			THANK AND END, screen out

9	Refused				THANK AND END, soft refusal

SC1	[ASK IF SAMPLE = CELL]

Are you in a safe place to talk right now?

IF NEEDED: Are you Driving?  [IF RESPONDENT ANSWERS YES, DRIVING,
SCHEDULE CALLBACK AND TERMINATE - CODE AS 2]

IF ASKED:  This is a short survey which should take no more than five
minutes.

1	Yes, safe place to talk

2	No, call me later			SCHEDULE CALLBACK

3	No, CB on land-line			RECORD NUMBER, schedule call back

4	Cell phone for business only	THANK & END - BUSINESS#

8	Refused				THANK AND TERMINATE – Soft Refusal

9	Refused				THANK AND TERMINATE – Hard Refusal

SC2	[ASK IF SAMPLE=CELL]

Are you at least 18 years old?

IF NEEDED:  This study will help us to better understand the value of
environmental protection and public programs. Any answers you give are
kept strictly confidential.

1	Yes

2	Yes, no time				SCHEDULE CALLBACK

3	No					SCREEN OUT

8	Refused				THANK AND TERMINATE – Soft Refusal

9	Refused				THANK AND TERMINATE – Hard Refusal

SC3	[ASK IF SAMPLE=CELL]

Do any other people age 18 or older regularly ANSWER your cell phone, or
just you?

INTERVIEWER: This question refers to the physical phone and not to their
calling plan

1	Yes, others

2	No, just respondent			SKIP TO SC4

9	Don’t know/Refused		SKIP TO SC4

SC3b	[ASK IF SAMPLE=CELL]

How many other people age 18 or older regularly answer your cell phone?

__	[ENTER NUMBER 1-10]

99	Don’t know/Refused

SC4	[ASK IF SAMPLE=CELL]

Not counting any that are used strictly for business purposes, are there
other cell phones that you use regularly, or is it just the one?

1	Yes, use other cell phones

2	No					SKIP TO SC5

9	Don’t know/Refused		SKIP TO SC5

SC4b	[ASK IF SAMPLE=CELL]

How many other cell phones do you use regularly, excluding those used
only for business purposes?

__	[ENTER NUMBER 1-10]

99	Don’t know/Refused

SC5	[ASK IF SAMPLE=CELL]

Not counting (this/these) cell phone(s), do you also have a regular
land-line phone at home?

1	Yes, has a regular phone at home

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 Refusal

SA1	[ASK BOTH SAMPLES]

Of all of the phone calls that you or your family receives, are…(Read
List)

1	all or almost all calls received on cell phones,

2	some received on cell phones and some received on land lines, or

3	very few or none on cell phones.

8	(VOL) Don’t know

9	(VOL) Refused

SA2	[ASK BOTH SAMPLES]

Record gender from observation.  (Ask only if Necessary)

1	Male

2	Female

Q1	[ASK BOTH SAMPLES]

First, compared to other issues that the government might address –
such as public safety, education and health – how important is
protecting aquatic ecosystem to you, on a scale of 1 to 5 where 1 is
“not important” and 5 is “very important”? (MATCHES QUESTION 2
IN THE MAIL SURVEY)

1     2     3     4     5	(VOL) Don’t Know	(VOL) Refused

Q2	[ASK BOTH SAMPLES]

People have ideas about the extent to which the government should be
involved in protecting the environment.  On a scale of 1 to 5 where 1 is
“not at all involved” and 5 is “highly involved”, how involved
do you think the government should be in environmental protection?

1     2     3     4     5	(VOL) Don’t Know	(VOL) Refused

Q3	[ASK BOTH SAMPLES]

Could you please tell me if you participated in each of following
activities during the last year? (DO NOT ROTATE)

1	Yes

2	No

8	(VOL) Don’t Know

9	(VOL) Refused

Boating, canoeing, or kayaking		1	2	8	9

Swimming/going to the beach		1	2	8	9

Fresh Water Recreational fishing 	1	2	8	9

Salt Water Recreational fishing		1	2	8	9

Fresh Water Recreational fishing 	1	2	8	9

Shell fishing or crabbing		1	2	8	9

Scuba diving or snorkeling		1	2	8	9

Now, I have just a few questions for classification purposes.

D1	[ASK BOTH SAMPLES]

What is your age?

________ Years        Don’t Know       Refused

D2	[ASK BOTH SAMPLES]

What is the highest level of education that you have completed?  Is
it… (READ LIST)

1	Less than high school

2	High school or equivalent

3	High school and technical school

4	One or more years of college

5	Bachelor’s degree

6	Graduate degree

D3	[ASK BOTH SAMPLES]

Including everyone living in your household, which of the following
categories best describes your total household income before taxes?  Is
it … (READ LIST)

1	$10,000 or Less,

2	Between $10,001 and $20,000,

3	Between $20,001 to $35,000,

4	Between $35,001 to $50,000,

5	Between $50,001 to $75,000,

6	Between $75,001 to $100,000, or

7	More than $100,000

8	(VOL) Don’t know

9	(VOL) Refused

D4	[ASK BOTH SAMPLES]

Are you of Hispanic or Latino origin?

1	Yes

2	No

8	(VOL) Don’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 be… (READ LIST – MULTIPLE RECORD)

1	American Indian or Alaskan Native,

2	Asian,

3	Black or African American,

4	Native Hawaiian or Other Pacific Islander, or

5	White

6	(VOL) Hispanic / Latino

8	(VOL) Other

9	(VOL) Refused

D6	[ASK BOTH SAMPLES]

Do you… (READ LIST)

Rent your home or apartment

Own your own home

Live with family or friends and pay part of the rent or mortgage

Live with family or friends and do not pay rent

7 	(VOL) Other, Specify

8	(VOL) Other

9	(VOL) Refused

RECRUITMENT:

In addition to this telephone survey, we are also conducting a mail
survey to help U.S. policymakers to better understand your priorities
for the environment and the use of public funds.  This survey will be
mailed to households along with a free reply envelope

The survey takes most people about 30 minutes to complete.

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 packet will include information about the study, how to
return your survey, and additional contact information in case you have
questions.  Thank you very much for your time, and have a great
evening/day.

Attachment 7: Cover Letter to Mail Survey Recipients

<date>

<given name> <surname>

<address>

<city>, <state>  <zip code>-<zip+4>

Dear <title> <surname>:

A few days ago you agreed to take a short survey regarding environmental
protection and government regulations in the Northeast U.S.  Thank you
for agreeing to participate—the survey booklet is enclosed with this
letter.  Your answers to the survey will help officials from the
Environmental Protection Agency (EPA) to better understand the value of
policies which would affect the future of fish and aquatic habitat in
the Northeast.  By filling out this survey, you will be participating in
an important study that will help government officials understand your
priorities for the environment and regulations.

Your responses to this survey are very important.  Over time, human
activities have caused many changes in Northeast’s rivers, streams and
bays.  The Environmental Protection Agency is considering policies that
could impact the quality of fish and aquatic habitat in these areas.
These policies can have different effects and costs.  Because of this,
it is important to know what types of policies are supported by
Northeast residents.

All answers to the survey are confidential. Once we have received your
survey, we will delete your name from all lists, so that your responses
can never be traced back to you.  Of course, your participation is
voluntary and you may refuse to answer any or all questions.

We hope that you find this survey important and interesting, and thank
you for your assistance in this important project. We would greatly
appreciate if you could return the survey in the near future.

Sincerely,

Mary T. Smith, Director

U. S. Environmental Protection Agency

Engineering and Analysis Division	Attachment 8: Post Card Reminder to
Mail Survey Recipients

FRONT

BACK

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.

 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 values due to familiarity with the resource. Thus, non-user
values are not necessarily representative of average non-use values.

 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 was
developed to promote ecological clarity and closer integration of
ecological and economic information within SP studies. In contrast to
traditional SP valuation, BSPV employs a more structured and formal use
of ecological indicators to characterize and communicate
welfare-relevant changes. It begins with a formal basis in 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 characterized 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 improved quantitative linkages between
ecological services and economic valuation of those services.

 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.

 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.

 Alternatively, the smallest possible main effects plan for all
attributes (72 profiles) may be folded over to make another 72 profiles,
for a combined set of 144 profiles.  This protects main effects from all
unobserved 2-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.

  PAGE  i

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  PAGE  90

 PAGE

  PAGE  119

18

19

18

19

18

17

16

15

14

13

12

11

11

10

If do not want A or B, check this box.

9

If you prefer Option A, check this box

If you do not want A or B, check this box

If you prefer Option B,

check this box

X

X

X

8

7

6

5

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.

Smaller effect on Striped Bass

Larger effect on Winter Flounder

4

4

3

3

2

Cooling water use affects fresh and salt waters throughout the US, but
almost all fish losses are in salt waters such as coastal bays.

18

17

OMB Control No. 2040-XXXX

Approval expires XX/XX/XX

15

14

13

12

11

11

10

If do not want A or B, check this box.

9

If you prefer Option A, check this box

If you do not want A or B, check this box

If you prefer Option B,

check this box

X

X

X

8

7

6

Abt SRBI

Government Services Divison

8403 Colesville Road, Suite 820

Silver Spring, MD, 20910

5

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.

Smaller effect on Striped Bass

Larger effect on Winter Flounder

4

4

3

3

Smallest Fish Losses per Year

Losses

< 0.1%

Total Fish Population

Largest Fish Losses per Year

1

1

Micro-organisms

Fish

Birds/Mammals

Food Web

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.

How Fish Are Affected by Water Intake

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.

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᠀Cooling Water Intake Screen

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

Micro-organisms

Fish

Birds/Mammals

Last week a survey was mailed to you concerning environmental protection
and government regulations in the Northeast U.S.  If you have already
returned your completed survey, please accept our sincere thanks.

If you have not yet completed your survey, we ask that you please do so
today.  You are one of a select few who have been chosen to
participate—your answers will help us understand your priorities for
the environment and regulations in the Northeast U.S.

If you have misplaced your survey, please contact Ryan Stapler at

(617) 520-3524 or<EMAIL_ADDRESS>for a replacement.

Regards,

Mary T. Smith

Environmental Protection Agency

2

Cooling water use affects fresh and salt waters throughout the Northeast
US, but the majority of all fish losses are in salt waters such as
coastal bays.

How Fish Are Affected by Water Intake

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

Total Fish Population

Losses

10%

4

Larger effect on Winter Flounder

Smaller effect on Striped Bass

Smallest Fish Losses per Year

Losses

< 0.1%

Total Fish Population

Largest Fish Losses per Year

Total Fish Population

Losses

10%

OMB Control No. 2040-XXXX

Approval expires XX/XX/XX

4

Larger effect on Winter Flounder

Smaller effect on Striped Bass

16