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SOLVING ENVIRONMENTAL PROBLEMS: AN OVERVIEW
SOLVING ENVIRONMENTAL PROBLEMS: AN OVERVIEW
Environmental science is the interdisciplinary
study of how humanity affects other living organisms and the nonliving
physical environment. Its role is to develop the basic information on
which wise environmental decisions can be based, and in that sense it is
fundamentally a problem-solving science. Before we begin a detailed
examination of the environmental problems that face our society today,
it is useful to consider the many elements that go into the solving of
environmental problems. How is information gathered, and at what point
can conclusions be regarded as certain? Who makes the decisions, and
what are the trade-offs?
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A combination of scientific
investigation and public action can solve them; pollution of the
Earth's atmosphere, land, and water can be halted, and resources can be
protected for the future. How can this success be achieved? Viewed
simply, there are five components in the solving of any environmental
problem:
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1. Scientific Assessment. The first stage of
addressing any environmental problem is scientific assessment, the
gathering of information. Data must be collected and experiments
performed in order to construct a model that describes the situation.
Such a model can be used to make predictions about the future course of
events.
2. Risk Analysis.
Using the results of the scientific
investigation as a tool, it is possible to analyze the potential effects
of intervention—what could be expected to happen if a particular course
of action were followed, including any adverse effects the action might
create (see Focus On: An Assessment of Risks).
3. Public Education. When a clear choice can
he made among alternative courses of action, the public must be
informed. This involves explaining the problem, presenting all the
available alternatives for action, and revealing the probable costs and
results of each choice.
4. Politico! Action. The public, through its
elected officials, selects a course of action and implements it (see
Focus On: Poisons in the Environment).
5. Follow-Through. The results of any
action taken should be carefully monitored, both to see if the
environmental problem is being solved
THE SCIENTIFIC ANALYSIS OF ENVIRONMENTAL
PROBLEMS
The key to the successful solution of any
environmental problem is rigorous scientific evaluation, and it is
important that we understand clearly just what the words "scientific
investigation" mean. What is "science"? The word conjures up images of
people in white lab coats peering at instruments and shaking test tubes.
What are they doing, and why?
Science is a particular way to investigate the
world, a systematic attempt to understand the Universe. Science seeks
to reduce the apparent complexity of our world to general principles,
which can then be used to solve problems or provide new insights.
A number of areas of human endeavor are not
scientific. Ethical principles often have a religious foundation, and
political principles reflect social systems. Some general principles,
however, derive not from religion or politics, but from the physical
world around us. If you drop an apple, it will fall whether or not you
wish it to, despite any laws you may pass forbid it to do so. Science is
devoted to discovering the general principles that govern the operation
of the natural world.
The Nature of Science
How does a scientist discover such general
principles? Where are they written? They are "written" wherever we look
in the world around us. A scientist is above all an observer, someone
who examines the world in order to understand how it works. Stated
briefly, a scientist determines principles from observation.
Discovering general principles by the careful
examination of specific cases is called inductive reasoning. The
scientist begins by organizing data (facts) into manageable categories
and asking the question "What do these facts have in common?" He or she
continues by seeking a unifying explanation for the facts. Inductive
reasoning is the basis of modern experimental science.
As an example of inductive reasoning, consider
the following:
Fact; Gold is a metal that is heavier than water. Fact: Iron is a metal
that is heavier than water.
Even if inductive
reasoning makes use of facts that arc all correct, the conclusion may be
either true or false. As new facts come to light, they may show that the
generalization arrived at inductively is false. Experimental science has
shown, for example, that the density of lithium, the lightest of all
metals, is about half that of water. When one adds this fact to the
preceding list, a different conclusion must be formulated. Inductive
reasoning, then, produces new knowledge but is error-prone.
Science also makes use of deductive
reasoning, which proceeds from generalities to specifics. Deductive
reasoning adds nothing new to knowledge, but it can make relationships
among darn more apparent. For example:
General rule: All birds have
wings. A specific example: Robins are birds. Conclusion based on
deductive reasoning: All robins have wings.
This is a valid argument. The conclusion
that robins have wings follows inevitably from the information given.
No other conclusion is possible. Deductive reasoning is used by
scientists to determine the type of experiment or observations necessary
to test a hypothesis.
Testing Hypotheses
Scientists learn which general principles
are true, among the many that might he true, by attempting
systematically to demonstrate that certain proposals are not valid—that
is, are not consistent with what scientists have learned from
experimental observation—then rejecting those invalid proposals. For
the time being they retain proposals that they are not yet able to
disprove as useful, because they fit the known facts. Later, even these
proposals might be rejected if, in the light of new information, they
are found to be incorrect,
We call a proposal that might be true a
hypothesis, and the test of a hypothesis an experiment. An
experiment evaluates alternative hypotheses. Say, for example, that you
face two closed doors. "There is a tiger behind the door on the left" is
a hypothesis; an alternative hypothesis is "The door on the right has a
tiger behind it"; a third hypothesis might be "There is no tiger behind
either door." An experiment works by eliminating one or more of the
hypotheses. To test these alternative hypotheses, you might open the
door on the right. Let us say that, when you do this, a tiger leaps out
at you. Your experiment has disproved the third hypothesis, for it is
clearly incorrect to say that there is no tiger behind either door.
Note that a test such as this does not
prove that only one alternative is true, but rather demonstrates that
one of them is not true. In this instance, the fact that a tiger is
behind the door on the right does not rule out the possibility that a
tiger also lurks behind the door on the left. A successful experiment
is one in which one or more of the alternative hypotheses are
demonstrated to be inconsistent with experimental observation and thus
rejected. Scientific progress is made in the same way a wooden statue
is—by chipping away un- -wanted bits.
Controls
Most often, the
processes we want to learn about are influenced by many factors. We call
each factor that influences a process a variable. In order to
evaluate alternative hypotheses about one variable, it is necessary to
hold all the other variables constant so that we don't get misled or
confused by them.
To test a
hypothesis about a variable, we carry-out two forms of the experiment in
parallel. In the experimental test we alter the chosen variable in a
known way. In the control test we do not alter that variable. We
make sure that in all other respects the two tests are the same. We then
ask, "What difference is there between the outcomes of the two tests?"
Any difference that we see must be due to the influence of the variable
that we changed, because all other variables remained the same. Much of
the challenge of experimental science lies in designing control tests
and in successfully isolating a single variable from all other
variables.
The
Importance of Prediction
A successful
scientific hypothesis needs to be not only valid but useful—it needs to
tell you something you want to know. A hypothesis is most useful when
it makes predictions, because the predictions provide a very important
way to test the hypothesis' validity: a hypothesis that your experiment
does not reject, but which makes a prediction that your experiment
does reject, must be rejected. The more verifiable predictions a
hypothesis makes, the more valid that hypothesis is. There is something
very satisfying about a successful prediction, because the prediction
being tested to verify the hypothesis is generated by the hypothesis
itself, and the result is not known ahead of time.
Theories
A hypothesis
supported by a large body of observations and experiments becomes a
theory. A good theory relates facts that previously appeared to be
unrelated. A good theory grows as additional faces become known. It
predicts new facts and suggests new relationships among phenomena.
By demonstrating
the relationships among classes of facts, a theory simplifies and
clarifies our understanding of the natural world. Theories are the solid
ground of science, the concepts of which we tire most sure. This
definition contrasts sharply with the general public's usage of the word
"the-
ory," implying
lack of knowledge, or a guess. In this book, the word "theory" is
always used in its scientific sense, to refer to a broadly conceived,
logically coherent, and very well supported concept.
Some
theories—for example, Newton's theory of gravity, Darwin's theory of
evolution, and Einstein's theory of relativity—are so strongly
supported that the likelihood of their being rejected in the future is
very small. Yet there is no absolute truth in science—only varying
degrees of uncertainty. The possibility always remains that future
evidence will cause a theory to be revised. A scientist's acceptance of
a theory is always provisional.
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