An Objective Environmental Dictionary
This is an attempt to provide definitions of important and/or
relevant terms in an objective or value-neutral manner. OK, in
some cases my definition may be designed to make a point with one
"side" or another in the debate, but I intend to hand these out to
all sides equitably, wherever they are deserved. Mainly, though,
recognizing that dialogue can only occur if two people or groups
speak the same "language," my purpose is to provide working
definitions around which discussions might revolve. Let me know if
there's a term who's definition you'd like to see, or if you think
that a definition is incorrect.
If you see a word in italics in one definition, that
means that there is also a definition for it.
Note: you will find the words "allegation" and "claim"
on this page. A primary goal of this site is to collect facts in
the form of citations or references either supporting or refuting
these items, preferably a large number of such. Just one or two
known cases is only "anecdotal" evidence and so is not very
persuasive. If you send me something with a citation or reference
that can be checked, I will include it, no matter which "side" it
supports.
March 23, 1997: I'm posting this with the first set of
definitions. More will come as needed.
[Comment Form]
Return to main Environmental Justice page.
Terms
Benefits,
Benefits Forgone,
Brownfields,
Company Store,
ppm,
Risk Assessment,
Risk-Benefit Analysis,
Risk Management,
Science,
Statistics,
Statistical Significance,
Trust
Benefits
The fact is that there are many, many chemicals used today,
and the modern technologies that are possible because them have
given us better nutrition and longer, healthier lives than people
in the past. This is true even for the poor, though life
expectancy and health among the poor remain less than among the
healthy. Therefore, while we want to protect ourselves against
chemicals that are truly a danger, we would be worse off if we did
away with all synthetic chemicals. For example, in the US we have
a very safe water supply with respect to cholera and other
water-born diseases and parasites. Water treatment by chlorination
makes this possible in many municipalities. There may be some
cancer risk as a result of chlorination, but this is far less than
the risk of death if we did not chlorinate. Since both rich and
poor in a city usually drink from the same supply, this is a
benefit to all.
In order to determine if, for example, water chlorination
really does provide a benefit, we need good estimates of any risk
of cancer that might come from chlorination, and the risk of other
diseases if we don't use it. If we only insist on zero
cancer risk from chlorination by-products, which could only be
achieved by not chlorinating, then we might create a very large
risk of death from cholera. (This in fact has happened in some
South American countries.) On the other hand, if we allow some
cancer risk (such as one in a million) then it becomes possible
to both achieve that goal and to still avoid the risk of cholera.
Equity is also very important, but risk is unavoidable.
Allowing some small level of cancer risk from the use of chemicals
makes much greater benefits possible. The important questions are:
"How do we balance the risks (and benefits) of different choices?"
and "How do we provide equitable distribution of risks and
benefits?"
Terms
Benefits Forgone
Remediating a waste site, or controlling pollution, has costs.
In many cases those costs do come from public sources–taxes.
There are many things that could be done with that money. For
example, if there are two waste sites, and only enough money to
clean up one of them this year, then by cleaning up one site we
forgo the benefit of cleaning up the other site. Instead of
waste clean-up, the tax dollars could also be used for education,
or anything else we might desire. Therefore, and decision to take
action results in benefits forgone somewhere else. Again,
it is important to provide equity in making decisions, but if two
low-income communities are next to waste sites, and we can only
clean up one of them, it would seem prudent to pick the one which
poses the greatest risk, since this choice would minimize the
level of benefits forgone.
Terms
Brownfields
The term Brownfields was coined to describe abandoned
industrial sites which are being left unused because of existing
waste/pollution at the site. Typically the company that originally
owned the site, and is responsible for the pollution, no longer
exists, so there is no responsible party that can be forced to
perform remediation. Further, the costs of remediating the sites
to residential use standards are very high, so that government
agencies can afford the remediation and business that might
otherwise consider the site for redevelopment instead choose to
develop/build on pristine land. Since many of the Brownfields are
in urban areas, adjacent to low-income communities, potential job
opportunities in those communities are lost by leaving the site
undeveloped.
In addition to the costs of remediating the known waste
problems at the site, a developer could also face the costs of
additional clean-ups, if more waste is found, and/or the cost of
law-suites from individuals or communities suffering adverse
health effects from the existing waste. Because of these potential
costs, lending institutions (banks) are very unlikely to provide
loans needed for the development, even if the business wanted to
go forward, without assurance that costs will be limited and hence
a reasonable assurance of return on their investment. Thus, the
current or standard regulatory environment is creating an
undesirable situation: development of pristine land often distant
from low-income communities while these Brownfields sit idle.
The Brownfields Initiative is a process where government
authorities, developers, and lending institutions work together
to provide less stringent clean-up standards for a site, given
that it will be used for industry (making it unlikely that
children, for example, would come into contact with the soil at
the site), and assurances of limited responsibility for future
problems at the site not caused by the developer. To many, this
may seem an ideal resolution.
The Environmental Justice Movement (EJM) sees it differently.
First, while it is claimed that these activities will provide
additional jobs to the adjacent community, the EJM claims that
most of the jobs, particularly the well-paying jobs, go to
professionals working outside the community. Further, the business
being developed often involves chemical production or significant
chemical use. Since it is impossible to achieve zero emissions,
and there are risks of accidental releases from these sites, the
EJM sees that additional risk is being placed on the adjacent
communities with little or no benefit to those communities. One
document said of this initiative, "I smell a rat."
It seems to me that this issue of jobs is key. If adjacent
communities did derive considerable economic benefit, then they
would be more amenable to these initiatives. However, it also
appears that just the promise of jobs is insufficient. I
propose that what's needed is some form of guarantee of
jobs, either in total number or in percent of work-force, or,
perhaps best, in percent of payroll. Otherwise there will be a
breach of trust, leading to further impasse in the
future.
The only other alternative I can think of would be to force
developers to use Brownfield sites, taking full liability and
cleaning them up to strict standards, rather than using pristine
areas. Since a developer can locate in just about any city,
county, or state, the only way that this could be accomplished
would be through federal legislation. I do not think it likely
that this will occur, and hence I see no realistic alternative to
the Brownfields Initiative.
Terms
Company Store
A protest song of the labor movement regarding past practices
of the mining industry contained the line, "I owe my soul to the
company store." This reflected the economic power that the company
exerted over the local community, and the fact that this power was
used to keep employees in debt, so that they must continue to
labor for insufficient wages.
While the practice of running a "Company Store" in this way
no longer occurs, it is still true that companies in small, poor,
rural communities have and are alleged to abuse this kind of
power. In particular, if a company is the only (significant)
source of income in a community, then attempts by the community
to get the company to reduce emissions may cause the company to
close or relocate, resulting in economic devastation. I have been
told confidentially (so I won't give the details) of just such a
company where emissions and work-place exposures were horrendous,
in just such a community which cannot afford to challenge the
situation.
To me, this kind of practice should be unacceptable. Further,
it leads to a lack of trust on the part of common citizens
and low-income communities, reducing the possibility for real
dialogue and compromise. I do not have any solution to offer.
Terms
ppm
Air concentrations are typically measured in parts per
million, which is abbreviated ppm. One penny out of $10,000.00 is
a ppm.
Terms
Risk Assessment
Risk assessment (RA) is the process evaluating the likelihood
of an adverse health effect, with some statistical "confidence,"
for various levels of exposure. RA does not determine what
level of risk is allowable or acceptable. Determining what we will
be allowed or accepted is a part of Risk Management. RAs
take many forms. For example, given claims by environmental groups
that people are being or have been made sick by chemical exposure,
one could ask if there is any proof of these claims. Well,
RAs have been used to show that the health of people in certain
neighborhoods or communities are, with high probability, affected
by a particular chemical exposure, allowing those communities to
obtain relief and/or legal action. (This is why I refer to RA as a
"two-edged sword," in some cases it's use benefits low-income
communities.
RA, as it is typically performed in evaluating the potential
effects of low level chemical exposure, is the process of
extrapolating outside the realm of current observations. (A
colleague whom I admire refers to RA as "farting around in maybe
land.") In fact, a RA is a form of hypothesis: it is a proposition
about what the risks of low-level exposures are, given data on
effects at high levels of exposure. If the RA is very far from the
truth–too high or too low–then subsequent observations
can prove it to be wrong. The very fact that some old RAs have
been proven wrong shows that an RA is indeed a testable
hypothesis. So, it is true that RA is not, by itself a
science. RA is just one step in the scientific process.
When assessing the risk of chemical exposure, the science
in question is toxicology: the study of poisons.
Because we require Statistical Significance in any
data we use, and because the number of individuals (people or
experimental animals) for which we have data is always limited, the lowest level of risk we can actually measure is about 1 in a
hundred, and we are lucky if we have data as low as 1 in 10. This
means that to predict the level of exposure that would yield a risk as low as one in ten thousand or one in a million, we must
extrapolate way below the actual data. This does introduce
considerable uncertainties. Therefore, Statistics are used
in the process to compensate for the uncertainties, as well as additional safety factors.
I will use an example to better explain what an RA is, and to
give a better idea of how one should interpret the numbers that
come out of RA. I will consider a chemical, "X", which is known to
cause a form of cancer, "Y", for which we wish to describe the
risk of exposure: a risk assessment. Keep in mind that this one
way to perform an RA. It is also basically the default method used to determine cancer risk.
The primary aspect of a RA is fitting a mathematical function
to the existing data. A function is needed to predict risks at
levels below the observed data. This process is depicted in the
following figure.
Figure Depicting a Hypothetical Risk Assessment
In this figure, a linear extrapolation is used (a
straight line which only predicts zero risk at zero exposure.)
Because there is "noise" in the data (you can't draw a straight
line that goes through all the data) there is some level of
uncertainty or variability associated with the data. Therefore,
in addition to the central we also use Statistics
to obtain upper and lower 95% confidence limits. That is, given some reasonable assumptions about the randomness in the
data, two more lines are drawn such that there is a 95%
probability that the true line–the one we would draw
if we had perfect knowledge–lies between these two. There is
a 2.5% chance that the actual line lies above the upper limit and
a 2.5% chance that the actual line lies below the lower limit.
Therefore, the chance that the actual line lies below the upper
limit is 97.5%, not 95%. I have also drawn a curve that might
represent the true dose-response relationship (to spark
discussion.) The slope of the upper 95% confidence limit is
sometimes referred to as the q1* because of the
mathematical notation that is often used.
It is recognized that the noise in the data might not capture
all of the variability or uncertainty in the risk. Therefore,
additional factors of 10 are used to multiply the risk (or divide
the concentration) based on identified uncertainties. Often two or
three factors of 10 are used. I have shown what happens when 1 or
2 factors of 10 (safety margin of 10 or 100) are used.
So what does all this mean? It means that when the EPA or
other government agencies say that the risk of exposure to X at
some concentration, call it "Z", is one in a million, the actual
risk is likely to be much, much less. (The RA shown here
assumes that risk is proportional to exposure, and the
calculations also often assume that exposure lasts for an
entire lifetime.) Alternately, there is a chance
that the real risk is higher than one in a million, but I think
that the odds of this are minuscule. This also means that you
should not assume that exposure at concentration Z gives a risk of
exactly one in a million, and that exposure at concentration 2X
gives a risk of exactly two in a million. Similarly, exposure to a
mixture of ten chemicals, all at their "one in a million" level
does not necessarily cause a risk of ten in a
million–because at least one factor of ten was probably
used to divide the original q*, the actual risk is probably
still less than one in a million.
Finally, you should note that the RA does not say what
level of risk is acceptable. Any level of risk can be selected and
specified on the "Risk" axis. From there, one can draw a line
across to the regulatory risk line and then down to find the
corresponding exposure concentration. Selecting what level of risk
will be allowed, or is "acceptable", is a part of the Risk
Management process. The RA does not say what the "Target" Risk
should be.
Terms
Risk-Benefit Analysis
The fact is, we would not use chemicals unless someone derived
a benefit from their use. Likewise, the more that we work
to remediate a waste site, the greater the other benefits
forgone. Also, it is simply impossible to completely eliminate
the risk of cancer that comes from using chemicals. Zero
emissions cannot be achieved. In order for a business to operate,
and for regulations to be enforceable, the regulations must set
achievable goals. So while the idea of setting zero emissions as
a goal is attractive in some ways, it would not be a workable
solution.
By analogy, suppose that a restaurant chef set as a goal "zero
dirt" on the counter tops before she could start cooking. Well, at
some point the chef must stop cleaning and start cooking. Though
this goal sounds good, it doesn't tell the chef how to serve meals
with a reasonable level of food safety.
So to have a chemical industry, we must allow some level of
risk from chemical exposure in setting regulatory standards.
Likewise, we must set achievable standards for waste site
clean-ups. In either case we then allow some risk in return for
benefits. Risk-Benefit Analysis is any method by which one
attempts to measure or quantify the level of risk and the level of
benefit associated with a particular regulatory decision. A
similar practice is Comparative Risk Analysis, in which one seeks
to determine, in the face of a decision, which choice will lead to
the lesser risk (given that both choices have some level of
risk.)
In performing a risk-benefit analysis, it is also important to
consider who enjoys the benefit and who is subject to the risk.
But since decisions in Risk Management do trade risks for
benefits, I would think it preferable to have some measure of how
much benefit and how much risk is involved. Deciding what to do
with that information (including the "who"s) is a difficult issue,
but I cannot see how it would be better to make that decision
without these measures. And when the "benefits" are reductions in
risk to the general public, or other public services that would
otherwise be forgone, where the benefits and risks are distributed
equitably, then use of quantitative measures seems imperative.
Also see my page on the value of human
life.
Terms
Risk Management
Risk Management is the process of taking information from
various sources, including Risk Assessment, and using it to
make regulatory (decisions) about what actions should or will be
taken to control pollution or remediate waste sites. It is in Risk
Management that value judgments such as the acceptability of risk
(at some level), any consideration of the value of benefits
or benefits forgone, and comparisons of potential risks
takes place. For a much longer discussion on the topic, see the
page on Conceptual Models in Environmental
Policy.
Terms
Science
Some environmentalists say that Risk Assessment is so
uncertain that it is not even science. The Random House
dictionary gives several definitions of which I will use the 2nd:
"systematic knowledge of the material world gained through
observation and experimentation." The scientific method, upon
which any science is based, is defined as: "a method of research
in which a problem is identified, relevant data are gathered, a
hypothesis is formulated from these data, and the hypothesis is
empirically (experimentally) tested."
Note first that the definitions say nothing about certainty.
Each hypothesis may or may not be correct, so to say that the
uncertainty of Risk Assessment makes it unscientific is
spurious. Psychiatry is a science–it fits the
definition–even though there are great uncertainties in its
application.
Terms
Statistics
Statistics is a branch of mathematics that deals with
probabilities. The fact is that life and health are uncertain.
Suppose that we know of six groups of people, with 100 people in
each group. The first three groups, are not exposed to a chemical,
and the other three are exposed to 100 ppm of the chemical
in the air. Suppose also that in the number of cancers in each of
the unexposed groups is 0 in the first group, 1 in the second, and
2 in the third. Likewise, suppose that in the exposed groups the
numbers of cancers is 4 in the first, 5 in the second, and 6 in
the third. We can say that among all these groups the average
cancer rate went from 1% (1 per 100) in the unexposed group to 5%
in the exposed group, which suggests that the 100 ppm of the
chemical increases the risk of cancer 5 times. But suppose now
that we find out about two more groups of 100, one exposed and one
not, with 1 cancer in the unexposed group and 13 in the exposed
group. Then the average for all exposed groups is now 7%!
The point is that, because we cannot observe and determine the
exposures of every single person, we can never know the true risk
of some exposure–if we collect more data then our estimate
will change–so we will always be uncertain about the risk. If
we only knew about the last two groups mentioned above, we would
estimate 13% cancer in exposed groups. So whenever we estimate the
actual risk of cancer, the real number could be higher, or
lower.
But what we really want to know is that the risk is no
higher than some level. Another way to say this is that we
want an upper bound on the risk. Using statistics, one can
calculate an upper bound from the observations with some level of
certainty. For example, with only the first three groups mentioned
above, where 4, 5, and 6 out of 100 people had cancer, we could
estimate that, with 95% confidence, the actual risk is between 3%
and 7%, and that with 97% confidence the actual risk is less than
7%. (There's a 2.5% chance that the actual risk is less than 3%.)
When a level of risk is reported, it is usually based on an "upper
95% confidence limit" such as this.
So statistics makes it possible to account for the fact
that we don't have perfect knowledge, and to provide a safety
margin when we calculate a risk. We can never be 100% certain of
the answer, but we can be reasonably confident in the result.
Terms
Statistical Significance
In the definition of statistics above, three unexposed
groups of 100 people each were given as an example, with 0 cancers
in the first group, 1 in the second, and 2 in the third. This
could happen randomly. In particular, although there were more
cancers in the last group than in the other two, these were not
due to an exposure. Just because more cancers are observed in one
group than in another doesn't mean that the excess had some
definable cause. Differences can occur randomly.
Because we derive benefits from the use of chemicals,
and Risk management decisions often result in other
benefits forgone we need to determine which chemicals
present a true risk, and to accurately determine the level of that
risk. Therefore, when analyzing data or observations of cancer
incidence or other health effects, we also want some level of
certainty that an observation did not occur randomly. Statistical
Significance is a measure of the probability that an event did not
occur randomly. Insisting on significance is a way of assuring
that we do not loose or forgo tangible benefits, or incur far
greater risks of a different kind, in an attempt to avoid
insignificant risks of one kind.
Terms
Trust
I like definition #6 from the Random House dictionary:
the obligation or responsibility imposed on a person in whom
confidence or authority is placed. An important part of trust
is the placement of confidence. Currently, the Environmental
Justice movement does not trust government regulatory agencies,
let alone the chemical industry. This has occurred in part because
of actual or perceived breach of trust on the part of some
chemical companies–trust was placed and then squandered. I
submit that constructive dialogue and real solutions, to move
beyond the current impasse between Environmental Justice and the
use of Risk Assessment in Risk Management, requires
that some level of trust be re-earned. The questions are: How can
this be accomplished? And is the chemical industry, in particular,
willing to do the work required? The first question is addressed
in an article, The determinants of trust and credibility in
environmental risk communication: an empirical study, Peters,
Covello, McCallum, Risk Analysis, 17:43. The
conclusion they reach is that trust and credibility depend on 3
factors: pereceptions of knowledge and expertise (you have to look
like you know what you're talking about); perceptions of openness
and honesty; and perceptions of concern and care.
Terms
Main Environmental Justice Page