Electrochemical Cells and Cell PotentialsHands-On Labs, In.docx

Electrochemical Cells and
Cell Potentials
Hands-On Labs, Inc.
Version 42-0153-00-02
Review the safety materials and wear goggles when
working with chemicals. Read the entire exercise
before you begin. Take time to organize the materials
you will need and set aside a safe work space in
which to complete the exercise.
Experiment Summary:
You will learn about galvanic cells and how cell
potential is calculated. You will prepare a copper/
zinc galvanic cell and measure the cell potential of
the reaction. You will monitor the potential of the
cell as the reaction proceeds.
EXPERIMENT
© Hands-On Labs, Inc. www.HOLscience.com 1
Learning Objectives
Upon completion of this laboratory, you will be able to:
● Define electrochemistry and compare redox, oxidation, and
reduction reactions.
● Describe electrochemical cells including the flow of

electricity through a galvanic cell.
● Predict the anode and cathode of a redox reaction using the
standard reduction potentials.
● Construct a galvanic cell.
● Operate a multimeter and interpret voltage data.
● Calculate the standard cell potential for a redox reaction.
Time Allocation: 4 hours
www.HOLscience.com 2 ©Hands-On Labs, Inc.
Experiment Electrochemical Cells and Cell Potentials
Materials
Student Supplied Materials
Quantity Item Description
1 Camera, digital or smartphone
1 Pair of scissors
1 Roll of paper towels
HOL Supplied Materials
Quantity Item Description
1 Digital multimeter
1 Filter paper, 20 cm x 20 cm
2 Glass beakers, 100 mL
2 Jumper cables
1 Pair of gloves
1 Pair of safety goggles

1 Plastic cup, 9 oz
1 Experiment Bag: Electrochemical Cells and Cell Potentials
1 - Copper sulfate (CuSO4), 1.0 M, 75 mL
1 - Potassium chloride (KCl), 1.0 M, 30 mL
3 - Strips of copper metal, 2 in. x ¼ in.
3 - Strips of zinc metal, 2 in. x ¼ in.
1 - Zinc sulfate (ZnSO4), 1.0 M, 75 mL
Note: To fully and accurately complete all lab exercises, you
will need access to:
1. A computer to upload digital camera images.
2. Basic photo editing software, such as Microsoft Word® or
PowerPoint®, to add labels, leader
lines, or text to digital photos.
3. Subject-specific textbook or appropriate reference resources
from lecture content or other
suggested resources.
Note: The packaging and/or materials in this LabPaq kit may
differ slightly from that which is listed
above. For an exact listing of materials, refer to the Contents
List included in your LabPaq kit.
Background
Electrochemistry

Electrochemistry is the study of the electrical aspects of
chemical reactions, concerned with two
processes: the generation of an electrical current resulting from
a spontaneous chemical reaction,
and the use of an electrical current to produce a chemical
reaction. These two processes describe
oxidation-reduction (redox) reactions. A redox reaction is a
chemical reaction in which there is
a transfer of electrons (change in oxidation state) from one
substance to another. The reaction
is termed “redox” because it is composed of two half-reactions:
an oxidation reaction in which
electrons are lost and a reduction reaction during which
electrons are gained. In the oxidation
reaction the loss of electrons causes an increase in the oxidation
number. Likewise, in a reduction
reaction the gain of electrons causes a decrease in the oxidation
number. See Figure 1.
Figure 1. Redox reaction between zinc and copper. The full
reaction is shown in the top line. In
the middle line is the oxidation reaction; notice that zinc loses
two electrons to form the zinc
ion. In the bottom line is the reduction reaction; notice that
copper ion gains two electrons to
form the copper atom. The electrons gained and lost in the half-
reactions cancel each other out
in the full redox reaction.
Electrochemical and Galvanic Cells
A device that uses redox reactions to either use or produce
electricity is called an electrochemical
cell. There are two types of electrochemical cells: electrolytic
cells, which use electrical energy,

and galvanic cells, which produce electrical energy from a
spontaneous redox reaction. A
spontaneous reaction occurs naturally and does not require
external influence (such as electrical
energy). The focus of this experiment will be on galvanic cells.
See Figure 2.
Figure 2. A simple galvanic cell for the redox reaction between
zinc and copper. Oxidation
occurs at the anode end, as copper gains electrons. Reduction
occurs at the cathode end, as
zinc donates electrons. The voltmeter measures the amount of
electrical energy produced by
the cell.
In a galvanic cell the oxidation and the reduction portions of the
redox reaction occur in separate
locations (such as glass beakers), with a wire to facilitate the
transfer of electrons between the
locations. As shown in Figure 2, the wire may be attached to a
voltmeter that measures the
potential difference of electrical charge between the two
locations. If a light bulb were hooked
up to the wire, the light would burn dimly when a small
potential difference exists and brightly
when a large potential difference exists. In each of the two
locations, an electrode is placed in a
solution containing the same ion as the electrode. For example,
in Figure 2, a copper electrode

is placed in the copper solution and a zinc electrode is placed in
the zinc solution. The electrode
where oxidation occurs is called the anode, and the electrode
where reduction occurs is called the
cathode. To complete the cell (electrical circuit), the two
locations are connected with a medium
that facilitates the transfer of the ions (zinc ions and copper
ions) from one location to another.
This connection between the two half-cells is called the salt
bridge, and it contains an inert
electrolyte solution. A solution is inert if it does not react with
the ions of either the electrodes
or the solutions holding the electrodes. When the galvanic cell
is complete, the electrons flow
through the cell, from the anode to the cathode.
Reduction Potentials
A galvanic cell produces electrical energy that can be measured
by a voltmeter. The cell voltage is
the difference in electric potential between the cathode and the
anode. The total amount of electric
energy that a cell is expected to produce is called the standard
cell potential (E°cell). Standard cell
potential is calculated based on the assumption that the cell is
in standard state conditions: the
concentration of anode solution and cathode solution is 1M, the
pressure is 1 atmosphere, and
the temperature is 25°C. The standard cell potential is the
contribution of standard reduction

potential from the reduction half-reaction (E°cathode) and the
standard reduction potential from
the oxidation half-reaction (E°anode), as shown in the equation
below:
The standard reduction potentials of half-reactions are
constants. See Table 1 for a list of standard
reduction potentials for a number of half-cell reactions. All
half-reactions are shown as reduction
reactions, hence standard reduction potentials.
Table 1. Standard Reduction Potentials.
Half-Reaction E°(Volts)
F2(g) + 2e
- → 2F-(aq) +2.87
Cl2(g) + 2e
- → 2Cl-(aq) +1.36
Br2(l) + 2e
- → 2Br-(aq) +1.07
Ag+(aq) + e- → Ag(s) +0.80
Fe3+(aq) + e- → Fe2+(aq) +0.77
Cu2+(aq) + 2e- → Cu(s) +0.34
One of the most common galvanic cells is the
battery. A battery contains a positive electrode (the
cathode) and negative electrode (the anode). These are denoted
by “+” and “-“ symbols on the side of the battery. The
electrodes
take up most of the internal space inside the battery and access
areas where chemical reactions occur. The anode experiences an

oxidation reaction in which charged ions interact with the anode
to
produce and release electrons. The cathode experiences a
reduction
reaction, whereby electrons are absorbed. The reactions result
in
the production of electricity, energy that travels in a circuit to
power cell phones, flashlights, and cars.
© Eric Strand, © ekler
Half-Reaction E°(Volts)
2H+(aq) + 2e- → H2(g) 0.00
Fe2+(aq) + 2e- → Fe(s) -0.44
Zn2+(aq) + 2e- → Zn(s) -0.76
Al3+(aq) + 3e- → Al(s) -1.66
Mg2+(aq) + 2e- → Mg(s) -2.37
Ca2+(aq) + 2e- → Ca(s) -2.87
K+(aq) + e- → K(s) -2.93
The more positive the reduction potential, the larger the ability
of the half-reaction to behave as
the oxidizing agent. Likewise, the more negative the potential,
the larger the ability of the half-
reaction to behave as the reducing agent. Given two half
reactions, the one with more negative
potential value will be the oxidizer. For example, consider the

role of zinc as a reducer in Equation
1 below and as an oxidizer in Equation 2 below:
In equation 1, the cell potential of the half-reaction of zinc is -
0.76V and the cell potential of
the half-reaction of copper is +0.34V. In this reaction, the cell
potential of the zinc is much more
negative than the copper, and thus the zinc acts as the reducing
agent (anode) in the reaction.
In equation 2, the cell potential of the half-reaction of zinc is -
0.76V and the cell potential of the
half-reaction of calcium is -2.87V. The cell potential of the
calcium is much more negative than the
zinc, and thus the calcium acts as the reducing agent (anode) in
the reaction. The driving force of
a reaction, pulling electrons from the anode in one location to
the cathode in the other location,
is dependent on the difference between the cell potentials of the
half-reactions. The larger the
difference, the more electrical energy the redox reaction will
create.
The standard cell potentials for Equation 1 and Equation 2 are
calculated below:
From the calculations, more electrical energy will be produced
from the reaction occurring in
Equation 2 (2.11V) than the reaction occurring in Equation 1
(1.00V). As a redox reaction proceeds,

and the electrons travel from the anode to the cathode, the total
cell potential for the reaction
will decrease.
In the experiment, a galvanic cell for the redox reaction
between copper and zinc will be prepared.
In a galvanic cell, the Ecell must be positive for a spontaneous
reaction to occur. The zinc solution
will be zinc sulfate (ZnSO4) and the copper solution will be
copper sulfate (CuSO4). The direction
of electron transfer in the redox reaction will be tested by
dipping the copper electrode directly
into the zinc solution and the zinc electrode directly in the
copper solution to see which electrode
becomes plated with the ion of the solution. The total potential
of the cell will be calculated and
compared to the total amount of electrical energy produced in
the galvanic cell, as measured with
a multimeter.
Exercise 1: Construction of a Galvanic Cell
In this exercise, you will create and experiment with a galvanic
cell.
Procedure
1. Gather all of the supplies listed in the materials list.
2. Use the scissors to cut a strip of the filter paper
approximately 1.5 inches in width (1/4 the size

of the sheet of filter paper). See Figure 3.
Figure 3. Cutting a strip of filter paper.
3. Fold the strip of filter paper in half (widthwise) and then in
half again. See Figure 4.
Figure 4. Folding the filter paper in half and then in half again.
4. Put on the safety gloves and goggles.
5. Create the salt bridge by carefully winding the folded filter
paper into a circle so that it fits into
the bottom of the 9 oz plastic cup. Add the potassium chloride
to the cup with the filter paper
until the paper is completely covered with the potassium
chloride. See Figure 5.
Figure 5. Folding filter paper in cup. The potassium chloride is
added to the cup to over the
filter paper.
6. Allow the paper to soak up the potassium chloride for a
minimum of 10 minutes or until you
are ready to add it to the galvanic cell, as described later in the
experiment.
7. Place the 2 glass beakers on a table. Add approximately 45
mL of zinc sulfate (approximately ½
of the bottle) to one of the beakers. To the second beaker, add

approximately 45 mL of copper
sulfate.
8. Pick up a fresh strip of zinc and insert one end of it into the
copper sulfate solution. After
approximately 5 seconds, remove the zinc from the copper
sulfate and place it on a piece of
paper towel. See Figure 6.
9. Pick up a fresh strip of copper and insert one end of it into
the zinc sulfate solution. After
approximately 5 seconds, remove the copper from the zinc
sulfate and place it on the piece
of paper towel. See Figure 6.
Figure 6. Metal in solutions. A. Zinc being inserted into copper
sulfate. B. Copper being inserted
into zinc sulfate.
10. Observe the 2 metal strips and record observations in Data
Table 1 in your Lab Report
Assistant.
11. From the observations, determine which of the 2 reactions is
spontaneous. Record this in the
observations section of Data Table 1.
12. Set up the multimeter as follows and see Figure 7:
a. Make sure the on/off switch of the multimeter is in the “off”

position.
b. Place the end of the black probe into the bottom right hole of
the multimeter.
c. Place the end of the red probe into the hole directly above the
location of the black
probe. Ensure that the probes are pushed all the way into the
multimeter.
d. Turn the voltage dial so that the arrow end of the dial is
pointing to 20 DCV.
e. Add 1 jumper cable clip to each end of the probes. It does
not matter what color
jumper cable clips are provided in your kit, or which color is
attached to either probe.
Figure 7. Multimeter setup.
13. Put the salt bridge into place by submerging 1 end on the
copper sulfate and the other end in
the zinc sulfate. Adjust the beakers as necessary so that the salt
bridge does not sink between
the beakers. See Figure 8.
Figure 8. Salt bridge. Notice that either end of the salt bridge is
fully submerged in solution.
14. Clip a fresh piece of zinc onto one of the jumper cable clips

and clip a fresh piece of copper
onto the other jumper cable clip.
15. Place the zinc into the zinc sulfate solution, so that the
metal is submerged in the solution,
but the jumper cable clip is above, and not touching, the
solution or salt bridge. See Figure 9.
16. Place the copper into the copper sulfate solution, so that the
metal is submerged in the
solution, but the jumper cable clip is above, and not touching
the solution or salt bridge. See
Figure 9.
Note: It may take a few minutes to find the correct placement of
the copper and zinc into the
solutions to keep the jumper cable clip above the solution.
Adjust the jumper cable clips as necessary
to find the correct placement.
Figure 9. Metals placed into their solutions. Notice the
placement of the metal and the jumper
cable clips relative to the solution.
17. Turn the multimeter on, and observe whether the total
voltage is positive or negative. If
the voltage reads positive, the galvanic cell was prepared
correctly and can be allowed to
progress. If the voltage is negative, quickly turn off the
multimeter and swap the jumper cable

clips from one metal to the other. For example, if a negative
voltage was measured with the
setup in Figure 9, the black jumper cable clip would be
switched to hold the zinc, and the
yellow jumper cable clip would be switched to hold the copper.
18. When the metals and jumper cable clips are arranged so that
the multimeter has a positive
reading, allow approximately 5 minutes for the multimeter
reading to stabilize. When the
multimeter reading has stabilized record the voltmeter reading
in Data Table 2 in your Lab
Report Assistant, under 0 minutes.
19. Look at a clock or watch and record the multimeter reading
for the galvanic cell every 15
minutes for 2.5 hours.
20. While the reaction in the galvanic cell is progressing, use
Table 1 in the Background section
to determine the 2 half-reactions and standard reduction
potentials for the redox reaction
occurring in your galvanic cell. Record the half reactions,
identifying which is the oxidation
and which is the reduction half-reaction. Also record the
corresponding reduction potentials
in Data Table 3 in your Lab Report Assistant.
21. Record the equation for the complete redox reaction
occurring in the galvanic cell in Data
Table 3.
22. Calculate the standard cell potential for the redox reaction
occurring in the galvanic cell, and
record in Data Table 3.

23. When all multimeter readings have been taken and recorded
in Data Table 2, take a photograph
of your galvanic cell. In the photograph, include a small piece
of paper that displays your name
and the date. Resize and insert the photograph in Data Table 4
in your Lab Report Assistant.
Refer to the appendix entitled, “Resizing an Image” for
guidance.
24. When you are finished uploading photos and data into your
Lab Report Assistant, save and
zip your file to send to your instructor. Refer to the appendix
entitled “Saving Correctly,” and
the appendix entitled “Zipping Files,” for guidance with saving
the Lab Report Assistant in the
correct format.
Cleanup:
25. Turn the multimeter off and carefully take apart the galvanic
cell.
26. Properly dispose of solutions, metal pieces, and the salt
bridge.
27. Wash lab equipment with soap and water and thoroughly
dry.
28. Return cleaned equipment to the lab kit for future use.

Questions
A. What were the concentrations of the solutions (zinc solution,
copper solution, and salt
bridge)? Were the concentrations consistent with those of
standard state conditions? Explain
your answer.
B. Was the amount of electric energy produced in your galvanic
cell consistent with the standard
cell potential of the reaction (as calculated in Data Table 3)?
Hypothesize why it was or was
not consistent.
C. Was there evidence of electron transfer from the anode to the
cathode? Use your data in
Data Table 2 to explain your answer.
D. For the following redox reaction in a galvanic cell, write the
oxidation half-reaction and the
reduction-half reaction, and calculate the standard cell potential
of the reaction. Use Table 1
in the Background as needed. Explain how you identified which
half-reaction is the oxidizer
and which is the reducer. Show all of your work.
Tackling ocean plastic in the laundry room

Author(s): Jen Fela
Source: Frontiers in Ecology and the Environment, Vol. 13, No.
5 (June 2015), p. 238
Published by: Wiley on behalf of the Ecological Society of
America
Stable URL: https://www.jstor.org/stable/24891178
Accessed: 04-12-2019 04:53 UTC
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Tackling ocean plastic in
the laundry room
Jen Fela

DISPATCHES DISPATCHES
Tackling ocean plastic in
the laundry room
Jen Fela
In late April, athletic company
Adidas (Herzogenaurach, Germany)
announced that it is partnering with
the group Parley for the Oceans (New
York, NY) to begin incorporating plas
tic refuse retrieved from oceans and
coastal areas into its clothing and
shoes, as well as phasing out the use of
plastic bags in its retail stores world
wide. This long-term initiative will
focus on communication and educa
tion, research and innovation, and
direct actions to reduce ocean plastic,
according to the Adidas press release.
Cyrill Gutsch, Founder of Parley for
the Oceans, says, "An important part of
the partnership is to look at the virgin
plastic that is being used right now and
to cut down what is possible. That
makes a big difference right away. Then
- together - we're creating innovative
production methods, materials, and
new product design concepts, which
will hopefully inspire other industries to
follow and establish a new way of col

The laundry room - a little-known source
of plastic waste in the oceans.
laborative thinking between creators,
environmentalists, and major brands".
Maria Westerbos, Founder and Direc
tor of the Plastic Soup Foundation
(Amsterdam, Netherlands), applauds
the fact that companies like Adidas
want to help solve the ocean plastic
problem but says that "making clothes
and shoes from 'plastic soup' [sea-based
plastic waste] is not a solution". She
emphasized that synthetic clothing,
such as artificial fleece, is one of the
biggest sources of plastic microfibers
making their way to the world's oceans.
Westerbos points to a new effort by a
European research consortium to tackle
the issue. Launched in late January, the
EU Life+ Mermaids project is a cooper
ative effort between Italian, Spanish,
and Dutch researchers to reduce the
amount of microscopic synthetic fibers
released through the process of washing
clothes. The group says that up to
200000 fibers can be released in one
load of washing, a number that it aims
to reduce by at least 70% in Europe,
possibly through the treatment of
clothes or fibers with protective sub

stances. "It would be a lot more mean
ingful if clothing companies were to
support the development of washing
machine filters that can stop the plastic
fibers from entering the environment",
continues Westerbos. "That way they
would actually contribute to the reduc
tion of plastic soup. It would give a new
meaning to the term 'greenwashing'."
Gutsch hopes to keep addressing
the problem from as many angles as
possible, including raising consumer
awareness through the production of
materials made from ocean plastic.
"We can only fix this through collab
oration", he insists. "If people know
and are given alternatives, they do
the right thing." ■
Delhi to phase out old
cars to cut pollution
Dinesh C Sharma
India's National Green Tribunal
has directed the government to
phase out diesel-run automobiles
older than 10 years in a bid to
decrease air pollution in the
National Capital Region (NCR)
of Delhi. This is the first time such
a step has been proposed to address

air pollution in India. The nation's
capital, along with adjoining
towns that make up the NCR,
contains 8 million vehicles. The
ban will not affect taxis and public
transport buses, which already use
compressed natural gas.
The proposal has evoked mixed
reactions from experts. "Aging
vehicles are known to be more pol
luting. Phasing them out, therefore,
will improve air quality. Whether
the impact is substantial or not, it
does not diminish the importance
of such measures", asserts Ashish
Verma, Assistant Professor at the
Indian Institute of Science
(Bangalore, India). However, the
New Delhi-based independent re
search group UrbanEmissions.info
has presented data showing that the
ban will only marginally affect air
quality, bringing average ambient
PM2.5 concentrations — particles
less than 2.5 micrometers in size -
down from 150 micrograms per
cubic meter (jig m~3) to 143 pg rrT3.
"This is because the percentage of
older automobiles is relatively
small, and 10-year-old vehicles are
driven 40% less than newer vehi

cles", explains Geetam Tiwari,
Professor of Transport Policy at the
Indian Institute of Technology
(New Delhi, India).
Experts also fear unintended envi
ronmental impacts from the ban.
"The local government lacks infra
structure and technology to deal
with the scrapping of older vehicles
in huge numbers in an environmen
tally friendly manner. Discarded
automobiles may end up being sold
in neighboring states", defeating the
purpose of the ban, cautions Nalin
Sinha, Director of the Initiative for
Transportation and Development
Programmes (New Delhi, India).
Verma suggests that a longer-term
solution would be to implement
measures like higher taxes on per
sonal cars and charges for driving in
congested areas - both of which
could discourage ownership and
usage of private vehicles - along
with developing public transport
and infrastructure for non-motor
ized transport. Tiwari agrees:
"Nearly 45% of trips in Delhi are
shorter than five kilometers. Even if
30% of these trips shift to bicycles,
there can be a substantial reduction

in pollution level." ■
www.frontiersinecoIogy.org © The Ecological Society of
America
The laundry room - a little-known source
of plastic waste in the oceans.
© R Smart/www.iStockphoto.com
Delhi to phase out old
cars to cut pollution
Dinesh C Sharma
India's National Green Tribunal
has directed the government to
phase out diesel-run automobiles
older than 10 years in a bid to
decrease air pollution in the
National Capital Region (NCR)
of Delhi. This is the first time such
a step has been proposed to address
air pollution in India. The nation's
capital, along with adjoining
towns that make up the NCR,
contains 8 million vehicles. The
ban will not affect taxis and public
transport buses, which already use
compressed natural gas.
The proposal has evoked mixed
reactions from experts. "Aging

vehicles are known to be more pol
luting. Phasing them out, therefore,
will improve air quality. Whether
the impact is substantial or not, it
does not diminish the importance
of such measures", asserts Ashish
Verma, Assistant Professor at the
Indian Institute of Science
(Bangalore, India). However, the
New Delhi-based independent re
search group UrbanEmissions.info
has presented data showing that the
ban will only marginally affect air
quality, bringing average ambient
PM2.5 concentrations — particles
less than 2.5 micrometers in size -
down from 150 micrograms per
cubic meter (jig m~3) to 143 pg nT3.
"This is because the percentage of
older automobiles is relatively
small, and 10-year-old vehicles are
driven 40% less than newer vehi
cles", explains Geetam Tiwari,
Professor of Transport Policy at the
Indian Institute of Technology
(New Delhi, India).
Experts also fear unintended envi
ronmental impacts from the ban.
"The local government lacks infra
structure and technology to deal
with the scrapping of older vehicles

in huge numbers in an environmen
tally friendly manner. Discarded
automobiles may end up being sold
in neighboring states", defeating the
purpose of the ban, cautions Nalin
Sinha, Director of the Initiative for
Transportation and Development
Programmes (New Delhi, India).
Verma suggests that a longer-term
solution would be to implement
measures like higher taxes on per
sonal cars and charges for driving in
congested areas - both of which
could discourage ownership and
usage of private vehicles - along
with developing public transport
and infrastructure for non-motor
ized transport. Tiwari agrees:
"Nearly 45% of trips in Delhi are
shorter than five kilometers. Even if
30% of these trips shift to bicycles,
there can be a substantial reduction
in pollution level." ■
This content downloaded from 144.96.52.186 on Wed, 04 Dec
2019 04:53:41 UTC
All use subject to https://about.jstor.org/terms
Contentsp. 238Issue Table of ContentsFrontiers in Ecology and
the Environment, Vol. 13, No. 5 (June 2015) pp. 235-288Front
MatterGUEST EDITORIALScience, policy, and the fate of the
greater sage-grouse [pp. 235-235]DispatchesFAA gives
approval to pesticide-spraying drone [pp. 236-236]China
redesigns cities for flood control and water conservation [pp.

236-236]Microbial mats clean fracking wastewater [pp. 237-
237]Ontario restricts use of bee-killing pesticides [pp. 237-
237]Tackling ocean plastic in the laundry room [pp. 238-
238]Delhi to phase out old cars to cut pollution [pp. 238-
238]Could agriculture and forestry one day aid biodiversity?
[pp. 239-239]Two US mussels get miles of critical habitat [pp.
239-239]Crickets won't feed the world after all [pp. 240-
240]Traffic noise drowns out fish flirtation [pp. 240-
240]WRITE BACKSoil and the city [pp. 241-241]Peer-review
warning: system error, reviewers not found [pp. 241-
242]Engineered artificial flooding: more questions than answers
[pp. 242-243]RESEARCH COMMUNICATIONSThe potential
for local croplands to meet US food demand [pp. 244-
248]REVIEWSClimate-change adaptation on rangelands:
linking regional exposure with diverse adaptive capacity [pp.
249-256]The portfolio concept in ecology and evolution [pp.
257-263]CONCEPTS AND QUESTIONSInterval squeeze:
altered fire regimes and demographic responses interact to
threaten woody species persistence as climate changes [pp. 265-
272]Crafting and evaluating Broader Impact activities: a theory-
based guide for scientists [pp. 273-279]NATURAL HISTORY
NOTESYellow-cedar: climate change and natural history at
odds [pp. 280-281]WRITING COMPETITIONA letter from the
Dean [pp. 282-282]The President's speech [pp. 283-283]A day
in the life [pp. 284-284][Frontiers Trading Post] [pp. 285-
286]LIFE LINESLearning to live with leopards [pp. 288-
288]Back Matter
American Behavioral Scientist
56(1) 3 –23
© 2012 SAGE Publications
Reprints and permission: http://www.
sagepub.com/journalsPermissions.nav

DOI: 10.1177/0002764211408585
http://abs.sagepub.com
ABS408585ABS56110.1177/0002764211408585Gill et
al.American Behavioral Scientist
1Oklahoma State University, Stillwater, OK, USA
2University of South Alabama, Mobile, AL, USA
3University of Colorado, Boulder, CO, USA
Corresponding Author:
Duane A. Gill, Oklahoma State University, 431 Murray Hall,
Stillwater, OK 74078
Email: [email protected]
The Exxon Valdez and
BP Oil Spills: A Comparison
of Initial Social and
Psychological Impacts*
Duane A. Gill1, J. Steven Picou2, and Liesel A. Ritchie3
Abstract
The 1989 Exxon Valdez oil spill and the 2010 BP oil spill were
the largest and most
ecologically damaging releases of oil in North American
history. This research provides
a comparison of the social and mental health impacts of these
two major technological
disasters. Random samples of residents of Cordova, Alaska, and
south Mobile County,
Alabama, were collected 5 months after each event. A
standardized indicator of event-
related stress was used for both samples. The analysis revealed
similarly high levels of

initial psychological stress for survivors of both disasters. The
strongest predictors
of stress were family health concerns, commercial ties to
renewable resources, and
concern about economic future, economic loss, and exposure to
the oil. Drawing on
more than 20 years of research on the Exxon Valdez disaster,
we discuss implications
for residents of Gulf Coast communities.
Keywords
disasters, oil spills, social impacts, stress
On April 20, 2010, the Deepwater Horizon drilling rig owned by
Transocean Ltd. and
contracted to BP exploded and started burning in the northern
Gulf of Mexico. Located
50 miles off the Louisiana coast, the rig eventually sank,
leaving a breached wellhead
gushing an estimated 55,000 barrels of oil per day. Initial
attempts to stop the spill
were unsuccessful, and the well released an estimated 185 to
205 million gallons of
Article
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4 American Behavioral Scientist 56(1)
crude oil before it was capped on July 15 and permanently
sealed on September 19,
2010. The BP oil spill was declared a “spill of national

significance” by Homeland
Security Secretary Janet Napolitano on April 29 as oil began
washing ashore along the
Louisiana coast. Within 2 weeks after the explosion, the
National Oceanic and Atmo-
spheric Administration (NOAA) began restricting fishing in
federal waters between
Louisiana and Florida and slowly began opening them after the
well was capped and
sealed. However, in late November, NOAA banned deepwater
trawling for shrimp for
a 4,313-square-mile area of the Gulf, suggesting continuing
risks for seafood safety
(Kent & Specker, 2010).
The spill severely damaged and threatened several “at-risk”
industries along the
northern Gulf, including commercial and recreational fishing,
tourism, and other enter-
prises tied to natural resources. Initial social impacts have been
profound and will con-
tinue to evolve over time. Issues relating to long-term
ecological impacts, seafood safety,
water and air quality, dispersant use, beach contamination,
tourism, and the claims
process have spawned contentious debates among scientists,
politicians, government
officials, and other stakeholders, including area residents.
The BP disaster invites comparison to the 1989 Exxon Valdez
oil spill (EVOS), which
resulted in immediate and chronic ecological, economic, social,
and cultural damages
(see Ritchie, Gill, & Picou, in press). Given what is known
about that environmental
disaster, what might be expected to occur in the wake of the BP

disaster? In the past
21 years, we and other colleagues have conducted empirical
research that documents
various community and human impacts of the EVOS (Arata,
Picou, Johnson, &
McNally, 2000; Dyer, Gill, & Picou, 1992; Gill, 1994, 2007;
Gill & Picou, 1997, 1998,
2001; Picou, 1996a, 1996b, 1996c, 2000, 2009a, 2009b; Picou &
Arata, 1997; Picou
& Gill, 1996, 1997, 2000; Picou, Gill, & Cohen, 1997; Picou,
Gill, Dyer, & Curry, 1992;
Picou, Marshall & Gill, 2004; Picou & Martin, 2007; Ritchie,
2004; Ritchie & Gill,
2007, 2010). Most of these studies were conducted in Cordova,
Alaska, noted as “ground
zero” for the EVOS. Cordova is a small, isolated fishing
community with strong eco-
nomic, social, and cultural ties to renewable resources—
particularly, fishery resources
damaged by the EVOS. Prior to the spill, Cordova was
consistently in the top 10 of the
nation’s most profitable seafood ports; 21 years later, it is not
even in the top 25. In addi-
tion, a subsistence heritage rooted in Alaska Native culture is
integrated into commu-
nity lifestyles. Comparatively, communities along the northern
Gulf of Mexico are
larger, with easy highway access and diverse economies, but
many are closely tied to
renewable resources affected by the BP disaster and have
diverse occupational, ethnic,
and subsistence lifestyles.
This research builds on and extends our understanding of the
social impacts of oil
spills in the context of the unfolding disaster in the Gulf of

Mexico. Specifically, we
focus on south Mobile County, Alabama. This area is bounded
on the north by Interstate
10 and Highway 163, on the east by Mobile Bay, on the south
by Dauphin Island and
the Gulf of Mexico, and on the west by the Alabama state line.
This geographical area
includes two incorporated communities, Bayou La Batre and
Dauphin Island, and
numerous unincorporated rural communities.
Gill et al. 5
Similar to Cordova, the local economy and people of this area
are largely dependent
on renewable natural resources. Bayou La Batre is known as the
“Seafood Capital”
of Alabama and is dependent on resources such as shrimp,
oysters, crabs, mullet, and
other finfish. Gulf waters, where a high volume of these
resources are typically har-
vested, were contaminated by the oil spill. In addition,
community commerce includes
shipbuilding, marine supply businesses, marine repair shops,
and other businesses that
cater to the commercial harvesting and processing of seafood.
On the other hand,
Dauphin Island relies on tourism based on beaches and beach
house rentals, boating,
recreational fishing, and charter boat tours, which are all tied to
natural resources
affected by the oil spill.
The goal of our study was to document how the BP oil spill

affects renewable resource
communities and groups. Three research questions guided our
research: (a) What are the
mental health impacts of the BP spill, and how do they compare
with data collected in
Cordova 5 months after the EVOS? (b) What social factors
contribute to elevated levels
of stress in south Mobile County? and (c) What are the
implications of our analysis for
the future of communities and residents along the Gulf Coast?
To address these ques-
tions, we provide a brief overview of the EVOS and a summary
of social science research
that has been conducted on that disaster in the past 20 years.
Next, we discuss theoretical
and conceptual foundations that provide an understanding of the
human impacts caused
by this technological disaster to guide our research on the BP
spill. The primary depen-
dent variable is a measure of psychosocial stress that provides
direct comparisons with
research findings in Cordova. Next, we describe our
independent variables, indicate
their relationships with psychological stress, and conduct a
regression analysis to deter-
mine sociological variables that independently predict stress.
We conclude with a sum-
mary and discussion of our results.
Overview of the EVOS
On March 24, 1989, the supertanker Exxon Valdez ran aground
on Bligh Reef in Prince
William Sound (PWS), Alaska, spilling more than 11 million
gallons of North Slope
crude oil. The resulting oil slick contaminated 44,000 km2,
including more than 1,900

km of coastline, and caused widespread environmental damage
that was exacerbated
by controversial cleanup techniques. An estimated 250,000
seabirds, 144 bald eagles,
4,400 sea otters, and 20 whales were among the initial
casualties (Spies, Rice, Wolfe,
& Wright,1996), and billions of salmon and herring eggs were
destroyed or damaged.
Twenty years after the EVOS, only 10 of 26 resources and
species had recovered from the
oil spill (EVOS Trustee Council, 2010). Research has
documented long-term impacts for
the PWS ecosystem, including persistence of volatile levels of
Exxon Valdez oil in inter-
tidal regions, on beaches, and in salmon streams (Peterson,
2001; Peterson et al., 2003;
Rice, 2009; Short et al., 2004, 2007) and significant declines in
local fisheries, most notably,
herring (Knudsen, 2009; Mitchell, 1999; Rice, 2009; Willette,
1996).
The EVOS had harmful consequences on local communities,
particularly, those with
strong economic, social, and cultural ties to renewable natural
resources. In PWS,
Alaska Native villages, such as Tatitlek and Chenega Bay,
resemble traditional subsis-
tence communities with a lifestyle and cultural lifescape
intimately tied to the environ-
ment (Dyer et al., 1992; Gill & Picou, 1997, 2001; Ritchie &
Gill, 2010). Commercial

fishing communities, such as Cordova, have strong economic
and lifestyle ties to fish-
eries and other ecological resources damaged by the EVOS.
Initial human impacts
within these communities included high levels of collective
trauma, social disruption,
economic uncertainty, community conflict, and psychological
stress. Analysis of quan-
titative data revealed that as important commercial and
subsistence resources failed
to recover and litigation remained unresolved, many local
residents, particularly, those
most closely tied to ecological resources (i.e., Alaska Natives
and commercial fishermen),
experienced chronic psychological stress, social disruption, and
collective trauma (Arata
et al., 2000; Gill, 2007; Picou & Martin, 2007; Picou et al.,
2004; Picou, Formichella,
Marshall, & Arata, 2009). These findings were supported by
ensuing in-depth qualitative
research (Gill, 2007; Ritchie, 2004; Ritchie & Gill, 2010).
EVOS Social Impact Literature Review
Several major studies have examined human impacts of the
EVOS at various points in
time. In addition to our longitudinal research projects, the Oiled
Mayors Study assessed
cultural, social, economic, and psychological impacts across 11
oiled communities one
year after the spill (Impact Assessment, 1990); Minerals
Management Service included
an EVOS component in its ongoing Social Indicators Study of
Alaskan Coastal
Villages (Endter-Wada et al., 1993; Reynolds, 1993); and the
Alaska Department of Fish
and Game examined patterns of subsistence in the impact area

(Fall & Field, 1996; Fall
& Utermohle, 1995). These studies generally address three
interrelated levels of impacts:
macro, middle range, and micro (Picou et al., 2009).
Macrolevel community impacts include infrastructure overloads,
disruption to eco-
nomic and occupational structures, and interrupted civic
processes. For example, initial
housing and lodging shortages and excessive demands for
services occurred in local
communities as EVOS cleanup workers inundated the area
(Endter-Wada et al., 1993;
Impact Assessment, 1990, 1998). A temporary economic boom
disrupted economies
as locals sought higher-paying cleanup jobs, leaving businesses
with an inadequate
workforce. Local governments depleted financial reserves
responding to the spill, par-
ticularly in dealing with increased demands for public services,
such as law enforcement,
emergency response, and community mental health (Endter-
Wada et al., 1993; Impact
Assessment, 1990; Rodin, Downs, Petterson, & Russell, 1992).
Middle-range cultural impacts of the EVOS included social
disruption and strained
community relations, prolonged uncertainty, and disruption to
subsistence lifestyles.
Research documented social disruption, corrosive community
characteristics, and loss
of social capital (Gill, 1994; Gill & Picou, 1998; Picou et al.,
2004; Ritchie, 2004).
Technological disasters create uncertainty and people who
experienced the EVOS were
particularly uncertain about long-term effects on natural and

social environments (Gill,
1994, 2007; Picou & Martin, 2007; Ritchie, 2004). Additional
uncertainty was fueled
Gill et al. 7
by litigation languishing in the courts for 14 years after a 1994
jury trial (Gill, 2007, 2008;
Picou, 2009b; Picou & Martin, 2007; Ritchie, 2004).
Microlevel effects of the EVOS included disruptions to daily
routines, family life,
work, and future plans as well as serious mental health
problems. Examples of stress
included increased drug and alcohol use and domestic violence;
chronic feelings of
helplessness, betrayal, and anger; elevated levels of depression,
anxiety, and posttrau-
matic stress disorder (PTSD); and adoption of avoidance coping
strategies (Arata et al.,
2000; Endter-Wada et al., 1993; Gill, 2007; Gill & Picou, 1998;
Impact Assessment,
1990; Palinkas, Downs, Petterson, & Russell, 1993; Palinkas,
Petterson, Russell, & Downs,
1993; Palinkas, Russell, Downs, & Petterson, 1992; Picou et al.,
1992; Picou & Martin,
2007). Early negative effects on children included fear of being
left alone, decline in
academic performance, and difficulty interacting with others
(Impact Assessment, 1990,
1998; Rodin et al., 1992). Longitudinal research indicated that
much of the chronic,
EVOS-related stress, anxiety, and social disruption was a by-
product of being part of

prolonged litigation (Gill, 2007; Picou, 2009b; Picou et al.,
2004; Picou & Martin,
2007; Ritchie, 2004).
The numerous community-level social, economic, and mental
health impacts docu-
mented for the EVOS suggest that similar consequences may be
forthcoming for Gulf
of Mexico communities affected by the BP oil spill. Indeed,
there have been a number
of suicides, increases in police calls, observable community
conflict, and increased
requests for mental health services throughout the impact
region. Although these accounts
have been reported in newspaper articles, few systematic data
have been collected to
verify these severe patterns of social disruption (Busby, 2010).
Theoretical and Conceptual Foundations
This article advances theoretical and conceptual developments
derived from a grow-
ing body of research on technological and natural disasters.
Considering factors
contributing to psychological stress, we draw on vulnerability
(Cutter, 2005) and how
it relates to resource dependency (Picou & Gill, 1996), the
conservation-of-resources
(COR) stress model (Arata et al., 2000; Hobfoll, 1988, 1991),
recreancy (Freudenburg,
2000), and risk perceptions (Beck, 1996, 2002; Erikson, 1994;
Giddens, 1990,
1991).
Vulnerability is a multidimensional, dynamic process based on
levels of exposure
to stressors, which typically relate to physical location, social

class, and demographic
characteristics. Moreover, a group may be highly vulnerable to
one type of risk yet
may be much less vulnerable to other types of risks, depending
on the resources at
stake and the efficacy to prepare and respond. In terms of
disasters, physical location
is a major factor, but attributes such as socioeconomic class,
age, gender, race-ethnic-
ity, and local culture contribute to vulnerability. Technological
disasters highlight
issues associated with vulnerability to hazardous substances,
and evidence suggests
that higher levels of exposure—including perceptions of
exposure—contributes to
increased levels of stress.
Oil spill disasters illustrate a type of vulnerability based on
dependence on environ-
mental resources damaged or threatened by the oil and cleanup
response. Picou and
Gill (1996) introduced the “renewable resource community”
(RRC) concept to describe
communities “whose primary cultural, social and economic
existences are based on
the harvest and use of renewable natural resources” (p. 881).
The RRC concept is
grounded in ecological-symbolic theory, which postulates that
interpretive processes
mediate how humans experience environmental trauma and that
these processes are
influenced by the type of environment that is damaged (Kroll-

Smith & Couch, 1991,
1993). This perspective focuses attention on how communities
and groups are affected
by losses and threats to ecosystem resources. Individuals,
groups, and communities
with close economic, social, and cultural ties to damaged or
threatened resources are
particularly vulnerable to technological disasters (Ritchie &
Gill, 2010).
The COR approach is based on the proposition that stress is
related to loss of resources,
threat of resource loss, and/or when resources are invested
without gain or return
(Hobfoll, 1988, 1989, 1991; Hobfoll & Lilly, 1993). Resources
are categorized into four
types: objects (e.g., physical possessions, natural resources),
conditions (e.g., a good
marriage, quality relationships), personal characteristics (e.g.,
high self-esteem, social
competence), and energies (e.g., money, knowledge). Rapid loss
of highly valuable
resources assails basic values, places disproportionate demands
on individual and col-
lective resources, is beyond the typical range of resource use,
and evokes powerful
mental images, all of which contribute to psychological stress
(Hobfoll, 1991).
Recreancy is defined by Freudenburg (2000) as “the failure of
experts or special-
ized organizations to execute properly responsibilities to the
broader collectivity with
which they have been implicitly or explicitly entrusted” (p.
116). This concept directs
our attention to issues of institutional trust, specifically to

institutions entrusted to
protect the public, “control” technology, and respond to crises.
Applied to disasters,
recreancy is linked to causes or “triggering events”
(Freudenburg, 1997). Disasters
caused by meteorological, hydrological, or geological processes
(i.e., natural disasters)
are believed to be beyond human control, but society generally
believes technology
can be controlled and entrusts specific social organizations to
do so. Technological
disasters have an identifiable “primary responsible party”
(PRP), providing a focus for
blame and compensation as well as anger, frustration, fear, and
hostility. Although
focus is on the PRP, other organizations, including the
government, usually share some
culpability. These perceptions of recreancy shake confidence in
the social order and
contribute to community disruption and psychological stress.
Disasters such as the BP oil spill are what Erikson (1994)
describes as a “new species
of trouble” that “scare human beings in new and special ways, .
. . [and] elicit an uncanny
fear in us” (p. 144). These disasters also present a new species
of risk that is a major fea-
ture of contemporary society (Beck, 1996). Technological
disasters tend to create chronic
uncertainty, particularly with respect to health effects,
economic impacts, extent of envi-
ronmental damage and recovery, fair and just reparations, and
sociocultural recovery
and closure. Perceptions of increased, uncontrolled risk
contribute to chronic uncer-
tainty, pose threats to ontological security, and add to anxiety

and psychological stress
(Giddens, 1990, 1991).
Gill et al. 9
These theoretical and conceptual foundations provide insights
into the profound
psychological stress experienced in communities affected by
technological disasters,
such as the BP oil spill. Psychological stress is heightened
among individuals and com-
munity groups who are vulnerable because of their ties to
damaged or threatened
resources. More generally, stress increases as resources are lost,
threatened, and/or
invested without gain. Corrosive communities are characterized
by a loss of trust in
institutions and organizations charged with protecting them
from the risks of modern
technology (Picou et al., 2004). These new forms of risk
contribute to psychological
stress by prolonging uncertainty and undermining ontological
security.
Methods
A telephone survey of residents of south Mobile County was
administered by the
University of South Alabama Polling Group from September 6
through 28. A random-
digit dialing technique was used, and to be eligible, respondents
had to be age 18 or
older and had to have lived in the area for more than 1 year. A
sample of 412 residents
responded to the telephone survey.1 The survey was modeled

after those we had used in
our EVOS research and included a standardized measure of
psychological stress as well
as measures of ties to resources, resource loss, perceptions of
recreancy, risk percep-
tions, and demographic characteristics.
Sample characteristics show that 6 out of 10 respondents were
female, 7 out of 10 were
married, 9 out of 10 were White, and the median age was 56.
More than 87% of the
respondents were high school graduates, and 57% reported a
total household income of
less than $50,000. Within the sample area, 36% were from
Bayou La Batre and adjacent
unincorporated communities, 29% were from Grand Bay, 15%
were from Dauphin
Island, and 19% were located throughout rural areas of the
county. The sample aver-
aged 33 years of residence in the area. The average household
size was three persons,
and 44% lived in two-person households. One third of the
households had children
younger than the age of 18.
Our analysis begins by examining psychological stress as a
dependent variable. We
describe the operationalization of stress and stress
characteristics of the sample and
compare the results to those observed in Cordova across 11
years. Next, we describe
each set of independent variables in terms of operationalization
of variables, sample
characteristics, and relationships with psychological stress.
Finally, we develop a linear
regression model to further delineate social contextual variables

that predict increased
psychological stress.
Findings
Psychological Stress: The Impact of Event Scale (IES)
Psychological stress was assessed using the IES (Horowitz,
1974, 1986a, 1986b;
Horowitz, Wilner, & Alvarez, 1979). A proxy for a measure of
PTSD, the IES measures
event-specific psychological stress given the underlying
rationale that highly stressful
events are likely to produce high levels of recurring,
unintentional, distressing feelings
and thoughts (intrusive stress) as well as high levels of
intentional efforts to suppress
these feelings and avoid reminders of the event (avoidance
symptoms). The scale con-
sists of 15 items and respondents are asked how frequently
during the past 7 days they
experienced each item in the context of a specific event (in this
case, the BP oil spill).2
Responses are coded as never (0), rarely (1), occasionally (3),
and often (5). The IES
has a range of 0 to 75, with higher scores indicative of higher
levels of stress. Two
standardized subscales, Intrusive Stress and Avoidance
Symptoms, can be separated
from the total IES to more clearly identify stress issues.
Clinical applications of the
IES as well as its application in other disasters, including our

research in Cordova,
provide a basis for a comparative analysis.
Our south Mobile County sample had a mean IES score of 25.0,
and the means for
the Intrusive Stress and Avoidance Symptoms subscales were
13.7 and 11.3, respec-
tively (Table 1). These results are comparable to findings from
Cordova 5 months after
the EVOS. A t test comparison of the two communities revealed
no significant differ-
ence between south Mobile County and 1989 Cordova
community samples with regard
to the total IES and Avoidance Systems subscale, but the two
samples did differ on
Table 1. Mean Intrusive Stress, Avoidance Symptoms, and Total
Impact of Event Scale (IES)
Scores for South Mobile County 2010 and Cordova, 1989 to
2006, With Comparisons to
Selected Clinical Cases
Year Total IES Intrusive Stress Avoidance Symptoms
South Mobile County,
Alabama
2010 (n = 412) 25.0 13.7 11.3
Cordova, Alaska
1989 (n = 117) 27.6 16.6** 11.0
1990 (n = 69) 19.6 10.1 9.6
1991 (n = 221) 19.9 9.5 7.5
1992 (n = 159) 16.6 8.5 8.1
2000 (n =372) 21.2 11.1 10.9
Clinical casesa

Bereavement from
parental death
3-6 weeks after death No data 21.6 No data
6 months after death No data 13.8 No data
Rape victims
Initial assessment 49.8 23.8 26.0
2 years after the rape 27.4 11.4 16.0
aData for clinical patients obtained from Horowitz (1986b).
Data for rape victims obtained from Seidner,
Amick, and Kilpatrick (1988).
**T test significant at the .002 level (South Mobile County–
Cordova comparison).
Gill et al. 11
Intrusive Stress (Cordova was higher). Table 1 also reveals that
the mean level of IES
in south Mobile County was similar to that of victims of rape 2
years after the assault.
IES scores can be used to clinically classify individuals into
subclinical, mild, mod-
erate, and severe stress categories (Hutchings & Devilly, 2005).
As shown in Figure 1,
one fifth of south Mobile County respondents were in the severe
category, and another
one fourth were in the moderate range. This compares to the
sample from Cordova, in
which more than one half were classified as either severe or
moderate.

In summary, event-related psychological stress among residents
of south Mobile
County, 5 months after the BP oil spill, was similar to that of
residents of Cordova
5 months after the EVOS. These stress levels are relatively
high, and if the trends observed
in Cordova in the years following the EVOS hold (see Table 1),
we can expect signifi-
cant spill-related psychological stress to continue in south
Mobile County in the next
decade.
Independent Variables
Four sets of independent variables were examined to understand
their relationships with
the IES and Intrusive Stress and Avoidance Symptoms
subscales. This section describes
each set in terms of how variables were operationalized, sample
characteristics based
on the variables, and how each variable was related to the IES
and its subscales.3
Vulnerability and exposure. Indicators of vulnerability
included basic demographic
and social variables as well as measures of exposure to oil and
dependence on ecological
Figure 1. A comparison of Impact of Event Scale clinical
categories: South Mobile County,
2010, and Cordova, 1989
resources. Demographic characteristics, such as gender, race,

and marital status, were
measured on a 0-1 categorical basis (male or female, non-White
or White, unmarried
or married). Although not provided in tabular form, t test
comparisons revealed race to
be the only variable significantly related to the IES and its
subscales, with non-Whites
experiencing higher stress levels than Whites. A correlation
analysis revealed that
income and education were significantly related to the IES and
its subscales, with those
in lower income categories and lower levels of education more
likely to experience
high levels of stress.
Our exposure variable was based on items indicating whether
the respondent had
worked on shoreline cleanup (6.3% did), had worked on the
Vessel of Opportunity
program (8.3% did), owned property that was damaged by oil
(5.1% did), and had con-
tact with oil in other ways (27.2% did). Respondents who had
experienced any one
item were coded as exposed (1), and the remainder were coded
as not exposed (0).
Approximately 1 out of 3 respondents experienced some type of
exposure to oil, and
a t test analysis indicated that exposure was significantly
related to the IES and its
subscales.
Renewable resource ties were measured by asking residents how
much they used
coastal areas along the Gulf of Mexico for commercial activities
before the spill.
Responses were coded as either connected (1) or not (0), with 4

out of 10 respondents
(43%) reporting a commercial connection to coastal resources.
T test analysis indicated
a significant relationship with the IES and subscales: Those
with commercial connec-
tions to damaged or threatened resources were more likely to
experience higher levels
of stress.
Resource loss. The survey contained two items concerning
economic effects
related to the oil spill. We first assessed economic loss by
asking, “How would you
describe the overall economic impact of the oil spill on your
household?” Responses
were coded on a 5-point Likert-type scale from very positive (1)
to very negative (5).
The economic impact variable had a mean of 3.73, with 22%
indicating they experi-
enced very negative impacts and almost 40% reporting
somewhat negative impacts.
A second item examined the threat of economic loss by asking
respondents to indi-
cate their confidence in their economic future using a 5-point
Likert-type scale where
higher scores indicated greater concern. The economic future
variable had a mean of
2.69 and more than one half (56%) were very concerned or
concerned. A correlation
analysis of both indicators indicated a significant relationship
with the IES and its
subscales.
Perceptions of recreancy: Trust in institutions. Perceptions of
recreancy were

measured by asking respondents to indicate how much they
trusted 10 different enti-
ties involved in the oil spill disaster. Each entity was rated from
no trust (1) to a lot
of trust (5). As indicated in Table 2, the BP Corporation, the
federal government, fed-
eral court system, and the Minerals Management Service were
the least trusted entities.
On the other hand, the Coast Guard and NOAA were the most
trusted entities. Three
entities—BP, local government, and state government—were
significantly correlated
with the IES and subscales. That is, a lack of trust in these
entities resulted in increased
psychological stress.
Gill et al. 13
Risk perceptions. We developed indicators of concern about
family health impacts,
health effects of dispersants, air quality, seafood safety, and
oiled seafood harvesting areas
using a 5-point Likert-type scale where higher scores indicated
greater concern. As shown
in Table 3, all five risk concerns were significantly related to
the IES.
Regression Analysis
On the basis of correlation analysis and t tests, 17 variables
were initially found to
have a statistically significant relationship with the IES and/or
the Intrusive Stress and
Avoidance Symptoms subscales. These were race, income,
education, exposure to oil,

commercial ties to damaged resources, economic loss, concern
for economic future,
trust in BP, trust in state government, trust in local government,
trust in federal courts,
trust in the Food and Drug Administration, and risk concerns
about family health,
dispersants, air quality, seafood safety, and oiled harvest areas.
A separate regression
model was initially run for each set of independent variables.4
This analysis confirmed
that the vulnerability variables of ties to commercial resources
and exposure to oil as
well as the two resource loss variables were significant
predictors of stress. Trust in BP,
however, was the only recreancy variable that remained
significant, and two risk per-
ception variables, concern for seafood safety and concern about
the health effects of
dispersants, were not significant predictors of stress in the
initial regression and were
dropped from further regression analysis.
Table 2. Perceptions of Recreancy (Trust in Institutions) Among
South Mobile County Residents
4 Months After the 2010 BP Oil Spill: Means and Correlations
With Psychological Stress
Institution M SD
Correlations
Impact of
Event Scale
Intrusive

Stress
Avoidance
Symptoms
Coefficient Coefficient Coefficient
BP Corporation 2.12 1.21 −.237*** −.242*** −.202***
Federal government 2.25 1.32 −.032 −.063 .003
Federal courts 2.60 1.28 −.052 −.103* .005
U.S. Coast Guard 4.21 1.03 −.045 −.027 −.058
Minerals Management Service 2.73 1.35 −.007 −.070 .057
Environmental Protection Agency 2.87 1.36 .025 −.018 .065
National Oceanic and Atmospheric
Administration
3.51 1.19 −.067 −.056 −.069
Food and Drug Administration 3.00 1.32 −.074 −.104* −.033
Alabama state government 2.77 1.24 −.147** −.171*** −.104**
Local government 3.01 1.31 −.187*** −.196*** −.153**
*p < .05. **p < .01. ***p < .000 (one tailed).
Final regression models were developed for the IES and the
Intrusive Stress and
Avoidance Symptoms subscales. Each model included basic
demographic control vari-
ables and the other variables found to be significant in the
initial regression analysis
(Table 4). Six variables were statistically significant across all
three models. For the

IES, the strongest predictors were threats to economic future
and family health concerns,
followed by economic loss, commercial ties to natural
resources, exposure to oil, and
age. Moreover, age became a significant predictor of stress in
the regression model, with
older respondents reporting higher levels of stress. The model
for Intrusive Stress was
similar to that of the IES; however, the Avoidance Symptoms
model included trust in BP
as a significant predictor variable. The final regression models
accounted for 44% of
the variance in the IES, 42% in the Intrusive Stress subscale,
and 36% in the Avoidance
Symptoms subscale.
Summary and Discussion
These results document significant mental health impacts for
residents of south Mobile
County resulting from the BP oil spill. The analysis revealed a
consistent relationship
between increasing levels of event-related psychological stress
and family health con-
cerns, economic loss, concern for future economic loss, ties to
ecosystem resources, and
exposure to oil. These findings are also consistent with research
in the immediate after-
math of the EVOS and empirically validate the importance of
vulnerability, resource
loss, recreancy, and risk perceptions for understanding social
and psychological conse-
quences of the BP oil spill.
These findings are also consistent with and expand several
previous systematic stud-
ies of the emotional impacts of the BP spill. A study conducted

by the National Center
for Disaster Preparedness found that parents reported mental
health problems for
approximately 19% of their children, with these problems being
more pronounced for
Table 3. Risk Perceptions Among South Mobile County
Residents 4 Months After the 2010
BP Oil Spill: Means and Correlations With Psychological Stress
Risk Issue M SD
Correlations
Impact of
Event Scale
Intrusive
Stress
Avoidance
Symptoms
Coefficient Coefficient Coefficient
Family health 2.10 1.22 .432*** .414*** .395***
Dispersants 3.97 1.19 .240*** .273*** .176***
Air quality 2.72 1.35 .359*** .338*** .332***
Seafood safety 2.82 1.39 .200*** .224*** .150***
Oiled harvest area 3.56 1.15 .335*** .338*** .290***
*p < .05. **p < .01. ***p < .000 (one tailed).

Gill et al. 15
families with incomes less than $25,000 annually and for those
families who reported
that they may move from their current residence (Abramson et
al., 2010, pp. 8-10). A
Gallup Poll revealed that residents in Gulf Coast counties
suffered a decline in “overall
emotional health,” particularly for depression, stress, worry,
and sadness, following the
BP spill (Witters, 2010). A telephone poll of residents of south
Louisiana found that
“self-rated stress levels” had more than doubled following the
BP spill. Furthermore,
60% to 80% of the 900 respondents interviewed were worried
about the spill and the
future economic impacts that could result for residents of their
communities (Lee &
Blanchard, 2010). These studies reveal a convergence of
evidence that the BP spill has
seriously disrupted Gulf Coast communities and that residents
are worried about
their health and the environment and are fearful about
additional negative economic
consequences.
Instead of using very general indicators of stress, depression,
anxiety, and worry,
our research used a standardized indicator of spill-related stress
that can be directly
Table 4. Final Regression Models for Impact of Event Scale
(IES) and Intrusive Stress and
Avoidance Symptoms Subscales: South Mobile County
Residents 5 Months After the 2010 BP
Oil Spill

IES Model
Intrusive
Stress Model
Avoidance
Symptoms
Model
Predictor Variable Beta p Beta p Beta p
Vulnerability variables
Renewable resource ties .165 .000 .097 .037 .213 .000
Exposed to oil .128 .004 .143 .001 .098 .038
Resource loss variables
Economic future concern .281 .000 .311 .000 .215 .000
Economic damages .170 .000 .190 .000 .127 .007
Recreancy variables
Trust in BP −.080 .067 −.056 .207 −.094 .045
Risk perception variables
Family health concern .198 .000 .195 .000 .176 .001
Oiled harvesting areas .079 .092 .090 .060 .058 .249
Air quality concern .078 .120 .063 .217 .087 .122
Demographic control variables
Age .099 .022 .093 .035 .093 .044
Income .003 .959 .001 .978 .004 .948
Education −.037 .456 −.019 .706 −.051 .344
Gender .034 .439 .031 .493 .033 .483
Race −.065 .142 −.031 .487 −.090 .056
Marital status −.031 .471 −.038 .378 −.019 .673

Adjusted R2 .44 .42 .36
compared to the psychological outcomes of other disasters and
various traumatic events
(Gill & Picou, 1998). The IES serves as a proxy for symptoms
of PTSD, and our results
suggest that post-BP spill mental health sequelae include
symptoms of PTSD at levels
similar to those experienced shortly after the EVOS. It is
apparent that the BP spill has
created a social context in south Mobile County that is
characterized by uncertainty
regarding exposure to oil and contamination of renewable
resources that are the founda-
tion for community survival. This context of uncertainty has
produced significant levels
of psychological stress and is likely to continue.
Given our research findings, efforts to diminish psychological
stress among survi-
vors of the BP disaster should focus on dealing with health and
economic concerns and
focus on vulnerable populations, particularly, those with
commercial ties to damaged
natural resources. Within this context, our data may
underestimate the severity of psy-
chological stress, given that minorities; commercial shrimpers,
particularly, Vietnamese
shrimping families; and others associated with seafood
processing are underrepresented
in our sample.

After 20 years of research on the social and psychological
impacts of the EVOS,
what can we expect to unfold in Gulf Coast areas, such as south
Mobile County? First,
there is a high probability of chronic mental health problems. In
Cordova, community
IES levels, as well as indicators of depression, remained
relatively high for more than
11 years (see Table 1). Chronic psychological stress was
particularly pronounced
among commercial fishermen and Alaska Natives because of
their close ties to dam-
aged resources. This long-term pattern of distress was caused by
uncertainty regard-
ing prolonged litigation and emerging damage to ecosystem
resources, such as herring
(Knudsen, 2009).
Class action litigation connected to the EVOS went through a
series of appeals that
ultimately led to consideration by the U.S. Supreme Court 14
years after a 1994 jury
decision (Gill, 2008; Gill, Picou & Ritchie, 2010). Our research
found that being involved
in unresolved litigation became the strongest factor explaining
chronic psychological
stress (Picou et al., 2004). Moreover, the Supreme Court ruling
cut punitive damages
by 90%, and the process left many survivors with a lack of
closure. For the BP disaster,
the claims process has become a bureaucratic and legal obstacle
and a source of conten-
tion and stress. Indeed, the governor of Alabama has described
the process as “extortion”
(Murtaugh, 2010). The start of BP litigation will be delayed

until 2013 and promises
to be a prolonged process with a precedent in Exxon v. Baker
that will most likely limit
punitive damage awards. If damage awards through the BP
claims process and courts
are delayed, serious community disruption and mental health
problems will persist
along the Gulf Coast.
The prolonged failure of the PWS herring population
contributed to uncertainty of
ecological recovery in the EVOS disaster. Prior to the EVOS,
commercial herring activi-
ties contributed to more than one third of Cordova’s fishery
revenues, and the market
price of PWS herring permits averaged $240,000. In 1994, the
herring population col-
lapsed and to date, there has not been a viable commercial
season for herring and herring
permits are worth less than $8,000 (Knudsen, 2009). The BP oil
spill damaged marine
Gill et al. 17
ecosystems and resources. In particular, if recovery of shrimp,
oysters, crab, and other
fish is slow, groups tied to these resources will probably
continue to experience psy-
chological stress. As was the case in Cordova, members of these
groups are not
inclined to seek professional treatment for mental health issues
and may require spe-
cialized programs to deliver services (Picou, 2009a).

However, it is apparent that recovery along the northern Gulf
Coast involves more
complex issues than was evident in the EVOS. The coastal
economy is more diverse and
local community impacts are more nuanced than in Alaska’s
oiled communities. For
example, community impacts and recovery in Louisiana are also
related to economic ties
to the oil and gas industry, which experienced a decline
following a temporary federal
moratorium on deepwater drilling. Community impacts in areas
such as Baldwin County,
Alabama, and Pensacola, Florida, are related to tourism based
on attractive beaches and
recreational marine boating and fishing. Given that the
economic and social impacts
of Hurricane Katrina still linger across this area, recovery from
the BP spill becomes
increasingly problematic.
It is also important to note that recovery along the northern
Gulf Coast involves per-
ceptions held by the broader U.S. public. In particular,
perceptions held by tourists and
potential consumers of seafood products are critical. Tourists
need to be assured that
the beaches are safe, the water is clean, and the fish they catch
are safe to eat. Likewise,
consumers of seafood, particularly, shrimp, need to be assured
that products from the
Gulf of Mexico are not contaminated. This is essential to
rebuild the tourism and sea-
food industries and to restore local economies based on these
resources. Specifically,
trustworthy sources are needed to address health issues,
including air quality, disper-

sants, and seafood safety. Clearly, there is a general lack of
trust in BP because it has a
vested interest in limiting perceptions of damage and harm.
Although social capital appears to be strong and intact in the
immediate aftermath
of the BP disaster, our experience with the EVOS suggests that
this may change over
time. Long-term social disruption manifested as community
fragmentation, tension,
and even open conflict may affect trust and social ties—social
capital. If this occurs,
such an environment would contribute to social capital loss
spirals, as found years after
the EVOS. Similarly, loss of social capital may further increase
stress levels, diminish-
ing overall community well-being. Moreover, given that one
third of our sample indicated
a desire to move from their community, there is also potential
for outmigration in the
long term as a result of declining economic conditions, which
are at least in part related
to the spill. This would also alter community relations,
diminishing not only social capi-
tal but human capital as well. At the very least, these issues
warrant monitoring and
attention in communities along the Gulf of Mexico by both
researchers and policy
makers.
Like the EVOS, and technological disasters in general, the BP
oil spill will continue
to reveal “contested” scientific evidence concerning ecological
damages; emerging sec-
ondary traumas, such as the claims process and litigation; and
serious community

conflict and mental health problems (Kroll-Smith & Couch,
1990). Our data reveal initial
mental health impacts that parallel those observed in 1989
immediately following the
EVOS. Given the social scientific evidence amassed over time
in PWS, we can conclude
that social disruption and psychological stress will characterize
residents of gulf coast
communities for decades to come.
Acknowledgments
We acknowledge the assistance of all individuals, in Alaska and
Alabama, who have responded
to our surveys and interviews. The technical support provided
by Keith Nicholls, Deborah
Colburn, Mike Long, and Pat Picou is most appreciated. The
contents and interpretations in this
article are the sole responsibility of the authors and do not
reflect policy or position of the
National Science Foundation.
Declaration of Conflicting Interests
The author(s) declared no conflicts of interest with respect to
the authorship and/or publication
of this article.
Funding
The author(s) disclosed receipt of the following financial

support for the research and/or author-
ship of this article: Major funding for this research was
provided by grants from the National
Science Foundation, Arctic Social Science Division (ARC-
1042926, DDP-910109, OPP-
0082405, OPP-002572, and OPP-0852932). Additional support
was provided by the Department
of Sociology and College of Arts and Sciences at Oklahoma
State University, the Polling Center
and the Department of Sociology and Anthropology at the
University of South Alabama, and
the Natural Hazards Center, Institute of Behavioral Science, at
the University of Colorado.
Notes
1. The refusal rate was 54%.
2. (a) I thought about it when I didn’t mean to. (b) Pictures
about it popped into my mind.
(c) Other things kept making me have thoughts about it. (d) I
had to stop myself from getting
upset when I thought about it. (e) I tried to remove it from my
memory. (f) I had trouble falling
asleep or staying asleep. (g) I had waves of strong feelings
about it. (h) My feelings about it
were kind of numb. (i) I had a lot of feelings about it that I
didn’t know how to deal with. (j)
I had dreams about it. (k) I stayed away from reminders of it. (l)
I felt as if it had not really hap-
pened. (m) I tried not to talk about it. (n) I tried not to think
about it. (o) Reminders of it brought
back feelings I first felt about it.
3. Our survey included social capital indicators, but none was
significantly correlated with the

Impact of Event Scale. The data will serve as baseline measures
for future research.
4. Space limitations prevent these initial models from being
presented in tabular form.
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oil spill. University of St. Thomas Law Journal, 7(1), 55-67.
Ritchie, L. A. (2004). Voices of Cordova: Social capital in the
wake of the Exxon Valdez oil spill
(PhD dissertation). Mississippi State University, Mississippi
State.
Ritchie, L. A., & Gill, D. A. (2007). Social capital theory as an
integrating framework for techno-
logical disaster research. Sociological Spectrum, 27, 1-26.
Ritchie, L. A., & Gill, D. A. (2010). Fostering resiliency in
renewable resource communities:
Subsistence lifescapes and social capital. In J. D. Rivera & D.
S. Miller (Eds.), How ethnically
marginalized Americans cope with catastrophic disasters:
Studies in suffering and resiliency
(pp. 51-81). Lewiston, NY: Edwin Mellen Press.
Ritchie, L. A., Gill, D. A., & Picou, J. S. (in press). The BP
disaster as an Exxon Valdez rerun.
Contexts.
Rodin, M., Downs, M., Petterson, J. S., & Russell, J. (1992).
Community impacts resulting from
the Exxon Valdez oil spill. Industrial Crisis Quarterly, 6, 219-
234.

Gill et al. 23
Seidner, A. L., Amick, A. E., & Kilpatrick, D. G. (1988).
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& A. S. Bellack (Eds.), Dictionary of behavioral assessment
techniques (pp. 255-257).
New York, NY: Pergamon Press.
Short, J. W., Irvine, G. V., Mann, D. H., Maselko, J. M., Pella,
J. J., Lindeberg, M. R., . . .
Rice, S. D. (2007). Slightly weathered Exxon Valdez oil persists
in Gulf of Alaska beach
sediments after 16 years. Environmental Science and
Technology, 41, 1245-1250.
Short, J. W., Lindeberg, M. R., Harris, P. M., Maselko, J. M.,
Pella, J. J., & Rice, S. D. (2004).
Estimate of oil persisting on the beaches of Prince William
Sound 12 years after the Exxon
Valdez oil spill. Environmental Science and Technology, 38(1),
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The effects of the Exxon Valdez oil
spill on the Alaskan coastal environment. American Fisheries
Society Symposium, 18, 1-16.
Willette, M. (1996). Impacts of the Exxon Valdez oil spill on
the migration, growth, and survival
of juvenile pink salmon in Prince William Sound. In S. D. Rice,
R. B. Spies, D. A. Wolfe,
& B. A. Wright (Eds.), Proceedings of the Exxon Valdez Oil
Spill Symposium (pp. 533-550).
Bethesda, MD: American Fisheries Society.

Witters, D. (2010). Gulf Coast residents worse off emotionally
after BP oil spill. Retrieved from
http://www.gallup.com/poll/143240/gulf-coast-residents-worse-
off-emotionally-oil-spill.aspx
Bios
Duane A. Gill is Professor and Head of Sociology at Oklahoma
State University. He is part of
a research team that has been investigating human impacts of
the 1989 Exxon Valdez Oil Spill in
Alaska through a series of longitudinal studies. He has also
conducted research on community
impacts of the 2004 Selendang Ayu shipwreck and oil spill in
the Aleutian Islands and the 2007
Cosco Busan oil spill in San Francisco Bay.
J. Steven Picou is a professor of sociology at the University of
South Alabama. He has primary
research interests in disasters, environmental sociology and
sociological practice. He has pub-
lished over 100 articles and book chapters on these topics and is
a contributor and co-editor of
The Sociology of Katrina: Perspectives on a Modern
Catastrophe (2010). He is currently
directing research projects on the long-term social impacts of
the Exxon Valdez Oil Spill and
Hurricane Katrina. He previously served on the faculties of The
Ohio State University and
Texas A&M University.
Liesel Ashley Ritchie is the Assistant Director for Research at
the University of Colorado’s
Natural Hazards Center. Since 2001, her focus has been on the
social impacts of disasters. She

has engaged in field studies following four marine oil spills,
including the 1989 Exxon Valdez
oil spill (EVOS) and the 2010 BP Deepwater Horizon disaster.
Her research on the EVOS
examines the relationship between technological disasters and
social capital, as well as social
impacts associated with protracted EVOS-related litigation. She
is currently leading a National
Science Foundation (NSF)-funded study of the 2008 TVA
Kingston Fossil Plant ash release and
is also co-PI on an NSF-funded RAPID response grant to study
temporary housing following
the January 12, 2010 Haiti earthquake. She is co-chair of the
American Evaluation Association’s
interest group on Disaster and Emergency Management
Evaluation. Ritchie has served as guest
editor for two disaster-related journal issues: New Directions
for Evaluation and the Journal of
Public Management and Social Policy.
Reproduced with permission of the copyright owner. Further
reproduction prohibited without permission.
Ocean pollution
Haven, David
Marine Technology Society. Marine Technology Society
Journal; Summer 2000; 34, 2;
SciTech Premium Collection
pg. 59

12/3/2019 Plastic waste taints the ocean floors : Nature News &
Comment
https://www.nature.com/news/plastic-waste-taints-the-ocean-
floors-1.16581 1/3
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Related stories
Fate of ocean plastic
remains a mystery
Policy: Classify plastic
waste as hazardous
Plastic particles surf
polluted waves
NATURE | NEWS
Plastic waste taints the ocean floors
Tiny particles found in sea-floor sediment point to partial
solution to 'missing plastic' problem.
17 December 2014

Billions of tiny plastic fragments are littering each square
kilometre of the deep sea, an analysis of sea-floor sediments
suggests1.
Although the study sampled a small number of sites, the
locations ranged from the subpolar Atlantic to the Indian Ocean,
enabling
researchers to design future studies that could determine where
much of the plastic manufactured by humans ends up.
Plastic waste has long been recognized as a problem for the
oceans: it pollutes beaches; accumulates in floating, nation-
sized
'garbage patches'; and is consumed by seabirds, fish and other
creatures. In a study published last week2, scientists estimated
that more
than 250,000 tonnes of plastic litter the ocean’s surface.
Yet that is only a minuscule fraction of the plastic produced
each year, says Richard Thompson, a marine biologist at
Plymouth
University, UK. Slightly less than half of the material ends up
recycled or in landfills, according to some studies, and much of
the rest
goes 'missing', he notes (see 'Fate of ocean plastic remains a
mystery').
In the latest study, published in Royal Society Open Science 1,
Thompson and his colleagues scrutinized samples of sediment
and coral
retrieved from 16 sites in the Mediterranean Sea, the North
Atlantic Ocean and southwestern Indian Ocean. Each of the
dozen sediment
samples contained colourful fibre fragments around 2–3
millimetres in length and 0.1 mm in diameter (about the
thickness of a human

hair), says Thompson. The team tallied, on average, more than
13 bits of fibre per 50 millilitres of sediment (or about 4 bits
per
tablespoon).
Current affairs
All four coral samples also carried synthetic fibres, but it is not
clear how the microplastics would have become attached to the
creatures,
says Lucy Woodall, a marine biologist at the Natural History
Museum in London and first author on the paper. She notes,
however, that it
seems that the current-wafted fragments became stuck to the
outside of the mucus-covered animals rather than being
consumed by
them.
Extrapolating from the Indian Ocean samples, each square
kilometre of sea floor in that region could hold 4 billion bits of
fibre, the
researchers estimate. Because every sample the team analysed
included such fragments, the contaminants are likely ubiquitous
in the
deep sea worldwide, the researchers contend. “The deep sea
floor could be the ultimate resting ground for the products of
our
disposable society,” says Thompson.
Almost 57% of the fibre fragments were made of rayon (a
synthetic material made mostly of wood pulp),
and more than half of the rest were polyester. Potential sources
for such synthetic materials are
numerous, and include ropes, fishing lines, clothing and even
cigarette filters.
The team’s results are “a big step forward” in understanding

where some of the world's plastic ends up,
says Kara Lavender Law, a physical oceanographer with the Sea
Education Association in Woods Hole,
Massachusetts. “This may be a case of ‘the more we look, the
more we’ll find’,” she says.
Sid Perkins
Pham CK et al. doi:10.1371/journal.pone.0095839
Litter such as this net — found entangled in a coral off the
Scottish coast in a survey published earlier
this year3 — is only the most visible part of the waste that
accumulates at the bottom of the sea.
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https://www.nature.com/doifinder/10.1038/nature.2014.16508
https://www.nature.com/doifinder/10.1038/494169a
https://www.nature.com/doifinder/10.1038/news040503-8
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12/3/2019 Plastic waste taints the ocean floors : Nature News &
Comment
https://www.nature.com/news/plastic-waste-taints-the-ocean-

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