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RRojas Databank Journal/ January 1997
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SCIENCE, RISK ANALYSIS AND
ENVIRONMENTAL POLICY DECISIONS
by John M. Stonehouse and John D. Mumford
UNITED NATIONS ENVIRONMENT PROGRAMME |
| The United
Nations Environment Programme was launched by the UN Conference on the Human Environment,
held in Stockholm in 1972. Its mandate is to catalyze and coordinate activities to
increase scientific understanding of environmental change and develop environmental
management tools. Among its milestones over the past two decades is the creation of
Earthwatch to gather, analyse and convey information about the state of the global
environment. In the form of environmental management tools, UNEP's efforts have led to
conventions to protect stratospheric ozone, to control the transboundary movement of
hazardous wastes and to protect the planet's biological diversity, among others. |
ENVIRONMENT AND TRADE SERIES
UNEP's Environment and Trade Series is intended to provide both trade and environmental
decision-makers with background analysis of various policy issues of relevance to the
trade and environment debate. Views expressed in this paper are not necessarily those of
the United Nations Environment Programme. To obtain additional free copies of this
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| FOREWORD The 1992 "Earth Summit" found common ground upon
which human development can be put on an environmentally sustainable footing. In 1993,
completion of negotiations for the Uruguay Round set the course for a further
liberalisation of international trade. One of the most pressing and complex challenges
facing our generation is the search for a workable synthesis of the two, of economic
relations and environmental realities.
We must embark upon this course, not because it is easy, but because it is necessary. Our
planet's ecological vital-signs continue to warn us of an accelerating rate of degradation
-- depletion of the ozone layer that shields us from harmful solar radiation, erosion of
productive soils needed to grow food, contamination of freshwater with hazardous wastes,
depletion of fish stocks, the massive loss of biodiversity, the threat of climate change
and global warming.
An important challenge identified at the Earth Summit is ensuring that trade and
environment are "mutually supportive." It is hoped that this series, providing
analysis on selected environmental issues of relevance to the environment - trade debate,
will contribute to the search for solutions now underway.
Elizabeth Dowdeswell
Executive Director
THE AUTHORS
This paper was prepared for the United Nations
Environment Programme by JOHN M. STONEHOUSE and JOHN D. MUMFORD, of the Environmental Law
Group of the Imperial College Centre for Environmental Technology.
John Stonehouse studied history at Oxford University and zoology at Imperial College,
London University. He was awarded a PhD degree at the Imperial College Centre for
Environmental Technology, for a study of the economic and social context of pesticide use
by smallholder farmers in Colombia. As a researcher and administrator in the science and
policy of the environment and development, he has also worked for the European Commission
in Brussels, and in the commercial and nongovernmental sectors.
John Mumford is a Senior Lecturer in the Department of Biology and the Centre for
Environmental Technology at Imperial College, London. He studied at Purdue University, USA
and Imperial College, London, and has worked extensively in developing countries. He
teaches courses in resource management, pest management and decision analysis. His
research interests cover economics, risk assessment and public policy in pest management
and related fields of resource management.
ACKNOWLEDGEMENTS
The authors wish to thank Dr Helen ApSimon, Martin
Hession and Steve Hollins, of Imperial College, and Professor Peter Calow, of the
University of Sheffield, for useful information and comments. All opinions expressed, and
responsibility for any errors, remain with the authors.
The Environmental Law Group (ELG) of the Imperial College Centre for Environmental
Technology (ICCET)
The The Enviornmental Law Group was formed as s distinct research and teaching group
within Imperial College of Science and Technology and other University of London colleges,
and is dedicated to advanced legal research in the areas of national, European and
international environmental law. The Group's location within Impmerial College gives it a
distinct ability to work with leading scientists and engineers, and input from other
disciplines features very highly in much of its activity.
For further infromation contact:
Environmental Law Group Centre for Environmental Technology Imperial College of Science,
Technology and Medicine
48 Prince's Gardens
London SW7 SPE
United Kingdom
Phone: 44 71 589 5111 (Ext.: 7220)
Fax: 44 71 823 7892
|
CONTENTS
1. Introduction
- Problems in the Interpretation of Scientific Data for the Making of Environmental Policy
- Issues of the Philosophy of Science
- Testing Hypotheses in the Probabilistic Sciences
- The Environmental Sciences
- Conclusion - Categorization of Environmental Risk
2. Risk Analysis
- Risk Assessment
A. The Hypothetical Case of "Fully Probabilized Risk"
i. Hazard Identification
ii. Assignment of Probabilities
iii. Consequence Modelling
B. Breakdowns of the Fully Probabilized Ideal, and Tools Used to Manage Them
C. The Use of Expert Judgment
- Risk Evaluation
- Conclusions
3. Environmental Risk Analysis
- The Toxicology of a Single Species
A. Hazard Identification
B. Dose: Response Assessment
C. Exposure Assessment
D. Risk Characterization
E. Risk Management
F. Post Facto Monitoring
- Ecosystem Toxicology
A. The Assessment of Ecosystem as Represented by Individual Species
B The Holistic Assessment of Ecosystems
- Nontoxicological ans Systematic Stress
- Conclusions
- Paradigms for Ecological Risk Assessment
4. Conclusion
5. References
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1. INTRODUCTION
PROBLEMS IN THE INTERPRETATION OF SCIENTIFIC DATA FOR THE MAKING OF ENVIRONMENTAL POLICY
The worlds of science and policy are not well suited for mutual communication (Stewart,
1993). In the sorts of information which they provide and require, the attitudes and
priorities of their practitioners, and in their operational vocabularies, including the
meaning given to the same words, the fields of science, economics, law and politics differ
in subtle and sometimes frustrating ways. This paper addresses the uncertainties and
imperfections of scientific information for the shaping of environmental policy, and how a
suite of decision tools, under the broad title of "Environmental Risk
Assessment", is being developed to assis decision making in the light of these
imperfections.
Environmental risk assessment tools, therefore, have arisen as a response to the
shortcomings of scientific information for policy purposes, and so it is in these
shortcomings themselves that the logical roots of the field lie. These shortcomings extend
throughout the field of environmental science, from the fundamental philosophy of science,
through the inferential nature of the probabilistic sciences, to the multidisciplinary
complexity of the environmental sciences.
ISSUES OF THE PHILOSOPHY OF SCIENCE
The philosophical problem at the heart of science is known as Hume's Problem: stated
briefly, this is that no matter how many times a phenomenon is observed, we cannot be sure
that this represents a universal pattern or "law" - logically, even large
numbers of past examples cannot guarantee that the same events and relationships will
continue to be found in future.
Even when "laws" provide convincing and effective explanations for phenomena, we
cannot be sure that such "laws" will continue to hold true, nor that we have not
imperfectly devised them and that new exceptions will not arise in circumstances which
differ in ways we have not foreseen. The most successful approach (so far) to Hume's
Problem, that of Karl Popper, does not "solve" it, but allows scientific
theories to be tested. This approach takes advantage of the logical asymmetry that,
although a theory cannot be proved, it can be disproved, by the finding of contrary
examples.
No matter how many times we observe the sun rise in the East, we cannot prove the
statement "the sun always rises in the East" to be true; yet one observation of
it rising in the West (or anywhere else) will disprove it.
In Popper's approach, therefore, a good scientific theory must be phrased so that it may
be shown to be wrong, or falsified, by the finding of examples which contradict it, and
so, although not verifiable, it is testable, by systematic attempts to disprove it. Under
this view falsifiability is the hallmark of scientific statements, distinguishing them
from non-scientific ones, such as those arising from tradition, emotion or authority. This
allows competing theories to be compared one to another, and useful ones (i.e. those that
appear to hold true) are employed with a provisional and qualified approval, until such
time as they may be disproved or, more often, refined and improved as exceptions to them
are found, investigated and incorporated. This qualified and provisional nature of the
acceptance of scientific theories, which therefore can never be proved as "laws"
in the popular sense of universal, unbreakable and true generalizations, is not always
understood by the layman who may demand certainty of the scientist, and may be
uncomfortable with information which, instead, although part of a field of theories which
are continually improving by a rigourous process of comparison and testing, is only
"the best generally applicable thing we have found so far". In fact, however,
this causes few problems in the real world: scientific "laws" are more commonly
evaluated, for practical purposes, by their usefulness than by their truth. The confidence
we may have in the usefulness of "laws" builds up, over time, as they are seen
to be of service in practical applications.
A second philosophical problem at the heart of science is that two objects or phenomena,
such as two pieces of steel loosely describable as "centimetre cubes" cannot be
shown to be identical - even with the most refined means of chemical, physical and
electromagnetic measurement, we can never be sure that the two do not differ in some
subtle way, either because they differ on a scale so fine it is beyond our powers of
measurement, or because they differ in some unfamiliar way of which we are ignorant.
However, just as a theory can never be proved but can be disproved, they may be shown to
be different: measurement may reveal differences in size, composition or properties.
These two asymmetries - that theories cannot be proved, but can be tested by attempts to
disprove them if they are falsifiable, and that two things cannot be proved to be the same
but can be proved to be different - lie at the heart of the approach taken to the testing
of scientific hypotheses. A hypothesis is "a supposition put forward in explanation
of observed facts" (Uvarov & Isaacs, 1986), and their testing is the core of
science. For example, one may wish to determine whether the trout in a polluted river are
thinner (or fatter) than those in an unpolluted river nearby. The fish can be weighed or
measured. The hypothesis "One trout population is thinner than the other" cannot
be falsified, as they cannot be shown to be the same; the alternative, however, "The
two trout populations are identical in weight" can be falsified (by showing them to
differ) and can therefore be tested, and so it is this latter hypothesis which the
scientist will test. If one were sure that the only possible effect of interest were that
the fish in the polluted river would be thinner, then a similarly testable hypothesis
would be "The trout in the polluted river are the same weight or fatter" - a
so-called "one-tailed test". However as, in fact, any anomaly is likely to be
operationally relevant, two-tailed tests, whereby the tested hypothesis is "They are
identical in weight", allowing deviation to be shown either way, are much more widely
used.
TESTING HYPOTHESES IN THE PROBABILISTIC SCIENCES
All sciences are in a sense probabilistic, that the statements which they may produce are
not certainties but "best guesses", but some are more probabilistic than others.
In particular, the biological sciences have to address the problem that organisms differ,
in their genes and in the effects wrought on them by their environments. For example, the
trout populations of any two rivers will be different, due to inherent variability. This
creates serious problems for the testing of hypotheses such as the one outlined above - if
the two populations differ, how can we conclude that those in the polluted river are
thinner or fatter than those in the unpolluted one due to a meaningful difference between
the rivers and not due to the random effects of inherent variability? In addition, in a
case such as this the fish populations will be sampled, measurements being made of a
selection of individuals, rather than the entire population, and the extent to which the
sample genuinely represents its parent population will vary. These thorny problems are
approached by the large and powerful set of tools known as statistical analysis.
The essential function of statistics in this sense is to assess variation due to different
causes - in our case the inherent variation in the two trout populations and that between
the populations in the two rivers - and to formulate the probability that the variation
source of interest (that between the rivers) is so large, relative to the general
variation, that it may be considered to be "significant". In our example, our
hypothesis that "the two populations are identical" may be tested by a
statistical tool (such as the versatile, simple and ubiquitous t-test) which will produce
a conclusion such as "there is a 97% probability, taking account of the general
variation in both populations, that this hypothesis is wrong" - i.e. we can say with
97% confidence that the two populations are not the same.
The usefulness and relevance of such conclusions are limited in several ways, which in
turn are addressed by a suite of techniques.
First, the power of statistical tools to provide significant results depends, more or
less, on two things. First is the size of the sample taken - one can see intuitively, as
well as mathematically, that the more samples are taken, the greater will be the
confidence in the conclusions made. As a result, any test will fail to produce a
significant difference if its sample size is too small; on the other hand, any two
populations will, in the real world, differ due to inherent biological variability and so,
conversely, a statistically significant difference may almost always be obtained if the
sample size is large enough, regardless of whether or not the difference has any
ecological meaning in the real world.
Second, statistical tools differ in their power to resolve differences. As a rule, the
more powerful tests rely on certain properties of the data (principally how the tested
characteristics are distributed among the populations) meeting certain conditions, which
must be assumed to be the case. (These conditions are expressed as "parameters",
and tests of this type are called "parametric statistics"). For the test to be
reliable, these conditions must hold, and so the employment of the test assumes that they
do. Tests can be carried out to compare the observed conditions with some of these
assumptions but, as these tests employ hypotheses which themselves are falsifiable, they
can, like the central hypothesis, indicate that the conditions are not the same as those
assumed, but not that they are the same: the correctness of the assumptions can never be
proved, allowing the validity of a parametric test to be questioned. When these
assumptions are not considered valid, alternative test techniques, with less demanding
assumptions ("nonparametric statistics"), may be used, but such tests have
lesser resolving power than their more demanding parametric cousins: for example, the
nonparametric Mann-Whitney test has about 95% of the power-efficiency of its parametric
analogue, the t-test (Siegel & Castellan, 1988).
This has real-world implications: the same data may be tested by two different tests, and
a significant effect (at any level) found with a more powerful and demanding test, but not
with one which is less so - the meaningful interpretation of the importance of the test
results will therefore require a knowledge of which test was used, why, and how its power
compares with that of alternatives.
Second, the principle of cause is not necessarily demonstrated. The detection of a
significant difference between the two populations cannot automatically be attributed to
pollution - the rivers and their populations may differ in other ways, even in ways
undetected. In fact, the common-sense notion of "cause" is, like all theories,
impossible to prove to exist in any case, because of Hume's problem, and the inference of
cause is another large field of scientific philosophical study. Statistical techniques can
provide evidence of the strength of the association between two variables, but such
associations can mislead: a famous example is that urban fox populations in Britain are
closely associated with the political representation of areas, being much more abundant in
Conservative areas than in Labour ones - these two phenomena are clearly not causing each
other, by some bizarre mechanism such as foxes somehow bringing out the Conservative vote,
but both are to be explained by a third, less obvious variable, composed of social and
economic factors. (For many years, supporters of the tobacco industry argued that the
association between smoking and lung cancer was such a "proxy association").
Tools exist to help the inference of causes. One of the most powerful of these is
experimentation. This has three central advantages over nonexperimental observations.
First, the causes whose effects are under investigation can be precisely applied by the
experimenter. Second, their effects can be evaluated with reference to "control"
cells where conditions are, as far as possible, identical to those in the test cells,
except solely for the influence of the causal candidate under study, advancing
considerably the ability to infer causation. Third, experimental and control cells can be
repeated or replicated, increasing confidence that observed effects are not random.
Convincing experimental results rely heavily on the care with which conditions other than
the test or "forcing" variable are controlled and maintained, and the training
of scientists emphasizes this as a crucial part of "good laboratory practice".
In nonexperimental research, logical tools, such as a systematic consideration of
alternative explanations, can be employed (Blalock, 1961). However, despite the usefulness
of such tools, the inference of causation, like all scientific "laws", of which
it is in effect a particularly useful and important subset, causation can not be
conclusively proven.
Essentially, therefore, the convincing demonstration of hypothesized causes depend on two
things. The first is plausibility, or common sense. The second is, as for all
"laws", the usefulness of the relationship in practical, real-world
applications, in which confidence builds with use over time.
This is important because understanding of likely causes is central to the meaning and
usefulness of science. When causal mechanisms are understood with some confidence,
scientific information can be used with greater precision and flexibility, and the
importance of the inference of causes is a recurring theme in the pages below.
Resolving these two issues, the use of statistics and the inference of cause, depends
heavily on the skill and competence of scientists. In the case of a failure of elementary
principles of scientific good practice, its detection by the scientists' audience is
difficult. Two additional techniques are used by the scientific community to address these
problems. The first is the concept of replicability - results are presented to the
scientific audience with sufficient detail of the experimental and analytical methods to
allow another researcher to repeat the experiment or observation exactly, and thus to
confirm its findings. This principle has a somewhat archaic air, and tends to the
publication of scientific papers filled with long and, to the casual reader, boring
descriptions of materials, equipment and procedures; but its central point is a critical
check on scientific competence, allowing contested reports to be checked by any interested
party.
The second is the concept of peer review, whereby articles submitted for publication are
anonymously checked by established practitioners in the same field, allowing their
judgement to be used to check that of the author in important decisions such as the
formulation of hypotheses, choice of statistical tests and interpretation of results.
Third among the practical limitations of probabilistic scientific procedures is that the
asymmetry of the formulation of the hypothesis, as described above, does not permit the
contrary hypothesis to be tested. A failure to reject the hypothesis that the populations
are the same is not to conclude that they are the same. Scientists often treat "not
significantly different" as equivalent to "the same", but this is
inconvenient, to say the least, for many policy applications - politicians and the public
may wish to know how sure we are that the two trout populations are the same, but a
confidence value for this cannot be given.
Fourth, the significance level itself is subjectively chosen. When presenting findings to
their peers, by means of scientific journals, scientists traditionally accept the level of
95% to assign "significance".
Some argue that this is too low. If, for example, twenty hypotheses are tested, and all
rejected by the criterion of just exceeding 95% confidence, then, on average, one of these
findings (1 in 20) will simply be wrong. On the other hand, for policy purposes 95% may be
considered too high - many people would not be happy if a 92% probability of the existence
of an adverse effect was dismissed as "not significant". This is, at root, due
to the different objectives of scientists and policy makers. The scientist seeks the
accurate generalization of findings. The policy maker seeks a level of confidence reliable
and robust enough to achieve social goals in a variety of cases, and the high political
cost of a single error produces a tendency to caution. The social and political evaluation
of a significance level is a subjective area where statistical probabilities found by
science must be evaluated in a social context.
These latter two issues, which limit the usefulness of scientific results to real-world
decision makers, have led to efforts to define "significance" other than the 95%
criterion of the rejection of the hypothesis of sameness. Approaches are advocated to a
search for "environmental significance". One is that differences, instead of
merely being assessed for significance, be quantified wherever possible. This may be done
by calculating expressions of statistical confidence in the sizes of the differences
between populations; or by "regression", a statistical technique which fits a
mathematical description to the relationship between two or more variables, for example
between the weights of fish and the concentrations of pollutants in their habitats.
Another approach is the replacement of the tested hypothesis "these two populations
are the same in weight" with that "the difference in weight between these two
populations is delta or larger", where delta is a preset value of environmental
significance and meaning, and the outcome sought is that, by the rejection of this
hypothesis, the difference is shown to be less than delta. Adoption of such techniques,
ideally simultaneously in several countries in a harmonized way, may go far to enhance the
facility with which nonscientist decision makers can digest statistical scientific
information.
The above is a brief summary of the scientific and statistical tools used for the
inference of conclusions in the probabilistic sciences. Two issues arise.
First, the output of the scientific method is complex, not always obvious, probabilistic
and heavily dependent on the details of the methods employed, and the skill of the
scientists in choosing and executing them. For these reasons it is important that the
workings, assumptions and limitations of these tools be known when scientific information
is being presented to decision makers and policy formers. To take an extreme example, an
unscrupulous scientist, working for a company suspected of causing pollution, may wish to
fail to show that fish in two polluted and unpolluted rivers were significantly different,
in order to support the case of his employer: in such a case, failure to find a
significant difference could be rigged, by the use of a weak test or of a small sample
size. Understanding of statistics would be needed to detect this.
Second, this scientific output is not always presented, or indeed presentable, in a way
which to the layman obviously has economic, social or environmental "meaning".
The interpretation of the policy significance of scientific findings is particularly
complex in the environmental sciences.
THE ENVIRONMENTAL SCIENCES
Turning to the environmental sciences, the complex, probabilistic and provisional nature
of statistical data is amplified. For the making of policy, a critically important issue
is the difficult and questionable concept of "ecological health" - how is the
health of an ecosystem to be defined or assessed, in either scientific or ethical terms?
These problems may be considered by a progression through the levels of ecosystem
organization.
The smallest point of ecological measurement is generally the individual organism. The
health of an organism may be measured in many ways - by its death or survival, or by its
behaviour, reproductive success or susceptibility to disease. These multiple points, which
in the case of human beings are well known from the field of medicine, require different
and imaginative methods of analysis. In a sense, individual organisms are therefore not
the smallest point of ecological measurement, which can be carried back to organs, such as
the liver, brain or blood supply, or to less tangible aspects such as contentedness,
irritability or dissatisfaction. When the value to be protected is the individual, as is
most evident in the case of human beings, but also in intelligent, "charismatic"
animals such as elephants or dolphins, these values need to be assessed.
Above the organism in the scale of ecological organisation is the population - the group
of organisms, of the same species, which routinely interact and interbreed. Populations,
and the species which together they compose, are often the value whose protection is
desired. The health of a population is to be measured most obviously by the survival of
its members.
The impact of damage on population survival is experimentally assessed by
"dose:response" techniques. These use regression methods to fit mathematical
descriptions to the percentage of the population killed or affected at points along a
scale of increasing levels of stress, typically doses of poison (or "toxin").
Dose:response analysis is an important field of "bioassays" - the use of living
material for the measurement of effects.
From the derived relationship one can calculate the doses likely to affect any fraction of
the population, and the toxicities of chemicals are traditionally compared by the use of
the dose which kills 50% - the 50% Lethal Dose, or "LD50". This is because, as
in all statistical techniques, the confidence of the estimates is greatest for those
values which are central in the range of values tested, which is the LD50 if all doses are
tested between those which kill no test organisms and those which kill them all. The
confidence is much lesser at the extremes of the distribution, which is awkward because it
is generally the lower extreme, the dose which kills very few individuals or none at all,
which is of importance for policy. For this reason, and concern at the distress caused to
large number of animals in conventional LD50 testing, attention has now shifted to tests
at the lower limits of toxicity, particularly to the identification of the largest dose
which causes No Observed Adverse Effect - the NOAE Level, or "NOAEL". Toxicity
tests clearly can hardly be carried out on humans, or on many other animals, either
because they are endangered (the platypus), large and unruly to work with (the bison),
charismatic animals whose suffering is painful to contemplate (the chimpanzee) or, more
usually, all three (the white rhinoceros, the blue whale). In such cases, estimates must
be extrapolated from similar or related species, which is not always easy (as for whales).
Extrapolation is the inference of values outside the scale which has actually been
measured, by the extension of relationships inferred where it has been measured. It is a
recurring, critical and contentious issue in environmental risk analysis, and will be
treated further.
Beyond relatively simple estimates of individual survival other criteria come into play. A
population may provide an ecological function of value to society, such as fish or game
which provide food, trees which protect a watershed from erosion or insect predators which
kill farm pests, and in such cases these functions may be more important than the
population per se. For conservation, the long term viability of a species is related to
its genetic diversity and this, assessed by techniques to measure the diversity within the
population of the structure of proteins or DNA, is a widespread conservation goal, which
has policy implications such as the attachment of greater importance to the maintenance of
a small, isolated population of a species than to a similar but larger one, as the total
genetic diversity is more threatened by the reduction of the former.
Beyond the protection of populations is that of their physical environment. As well as by
environmental toxins, this can be disturbed by, for example, temperature changes (as in
the water above and below dams) and soil erosion. Some of these effects can be subtle, and
they vary between locations and circumstances - for example, eroded soil, whose loss from
the land is itself deterioration, becomes a pollutant in rivers, blocking sunlight and
affecting concentrations of dissolved gases such as oxygen.
Environmental complexity is dramatically enhanced at the level of ecosystems. The
disruption of ecosystems is hard to predict, taking place across an array of trophic
levels (i.e. stages up food chains, from plants to herbivores to predators) and ecological
interactions. First, tests cannot be carried out on all species present, or even on an
extrapolable analogue of each. Second, pollutants themselves can and do move up food
chains, often by a process of "ecoaccumulation", by which toxins accumulate in
the bodies of predators, eaten in their prey, which can exceed concentrations in the prey
themselves, leading to unforeseen problems, such as the effects of ecoaccumulated DDT in
bird predators. Third, influences on one species can have effects on others through their
ecological interactions, by the process of "ecological mediation", often
"knockon effects" reverberating up and down food chains - predator and herbivore
populations will suffer from losses of their food organisms and, conversely, populations
may expand following losses of their competitors (as Southern Ocean seals and penguins
following the virtual elimination of whales) or of their predators (as Californian sea
urchins following the near-extinction of the sea otters which eat them, which in turn led
to decimation by the sea urchins of kelp beds). The assessment of ecological effects, even
post facto, relies on the careful selection and sampling of species, and of indices of
species diversity and function, such as energy budgets - the choice and measurement of
these variables requires considerable scientific expertise as well as clear political
priorities as to the "ecological value" of concern.
Finally, studies of the global environment rely on the addition of atmospheric and oceanic
sciences. Although some such phenomena can be experimentally assessed, as by the release
of harmless substances to evaluate the likely behaviour and dispersal of plumes of toxic
gases or liquids, their evaluation on a global scale depends on mathematical models which
are currently variable and imprecise. For example, estimates of the impact of industrial
carbon dioxide on the Greenhouse Effect vary widely, causing proposed levels of reduction
to lack consensual scientific validity (Rotmans & Swart, 1990), and allowing the
leaders of industrialized and petroleum-producing countries to question the existence of
the Effect.
The concept of "ecosystem health" implies an analogy with the health of an
organism, such as a person. In fact, this analogy is imperfect and may be misleading.
"Health" implies a stable, equilibrium state, to which a system tends to return,
by self-regulating processes developed by evolution, as when an animal such as a person
recovers from disease or injury. This process of control helps us to define
"health", but there is no evidence that ecosystems do regulate themselves in
this way - that there is an objective "optimal state" which may be used for
defining ecosystem health (Calow, 1992).
The original, "normal" state of an ecosystem, before any human disturbance, may
be used to define its "health", but ecosystems are themselves dynamic, in
constant flux rather than a steady state. This makes the concept of "normality"
itself hard to assess, as changes in ecosystem structure and function occur naturally, and
whether and which changes in ecosystems may be attributable to human disturbance are hard
to demonstrate with conviction (Barlow et al., 1992). One approach to this problem is,
where possible, to discover the limits of historical fluctuations, and to aim not to
exceed them - this approach has been used to define "acceptable" fluctuations in
wildlife populations around oilfields (Maki, 1992) and in the temperature of the planet.
Yet many, if not most, ecosystems are in fact the product of inevitable human disturbance.
This raises two issues. First, the original state may not be knowable - archaeological
research has shown that even the Amazon basin, apparently a "wilderness", has
been shaped by human communities for centuries. Second, many human-dominated systems also
have ecological functions - agricultural fields, for example, are highly
"unnatural", yet have values as ecosystems which we would wish to protect.
In the event, the properties which we use to define the qualities of ecosystems which we
wish to protect are almost always chosen by human value judgements - such as biodiversity
or natural beauty. In general, people tend to be conservative, wishing merely to keep
ecosystems as they have come to know them, i.e. as they are now. For example, the rough
grazing common lands of southern England, since the abandonment of their traditional use
for animal grazing, are being invaded by small trees such as birches, which used to be
held in check by the animals. Wishing to maintain the heath ecosystems, themselves rich in
wildlife, "conservation" volunteers spend weekends uprooting these trees, and
yet their arrival is merely the first step in the return of these areas to their natural
state before human disturbance - mature deciduous forest - which is therefore prevented by
society because of the higher value that it places on familiar than on original ecosystems
in this case.
It is also important to distinguish between change and harm in the disturbance of
ecosystems. Harm is, as discussed above, largely defined by subjective human value
judgements, and not all changes may be harmful in this sense. For example, if a population
of beneficial insects such as honeybees is exposed to a pesticide but, after initial
reduction of the population, a resistant type emerges, so that the population recovers to
its initial levels and remains unaffected by the pesticide thereafter, ecological change
has clearly taken place but many would argue that no harm has been done. On a larger
scale, the global extermination of the smallpox virus received little condemnation from
conservationists, and the extermination of other "pests" such as, say, the
Anopheles mosquitoes which transmit malaria, might generally be seen by society as a good
thing.
CONCLUSION - CATEGORIZATION OF ENVIRONMENTAL RISK
This bewildering complexity and interaction of environmental components has led to the
concept of "Environmental Risk Analysis" being employed in different ways, and
"Environment" itself to mean different things in science and in policy making.
As is the nature of environmental phenomena, these interact and overlap, but a
categorization can be discerned:
1) Toxic threats, whether chemical or by radiation, to human health through the
environment, often called "environmental risk" but now, because of confusion,
increasingly being referred to as "environmental health risk".
2) Toxic threats to the natural environment, or ecosystems. Threats to humans through the
environment and those to ecosystems, the latter now coming to be called "ecosystem
risk", have suffered in the past from being too infrequently distinguished, though
this is now increasingly emphasized (Norton et al., 1992). The distinction can, however,
be overstated (Barlow et al., 1992), as the two have many points in common, as human
beings are at the top of many food chains, and so environmental toxins attack ecosystems
and people together, as in the Minamata Bay tragedy.
3) Nontoxic threats to ecosystems, such as construction projects, for example of roads or
dams, land clearance for agriculture or the removal of individuals from a population by
hunting, fishing or treecutting.
Toxicology, the study of the action of toxins, comprises the bulk of environmental risk
analysis, as toxins are perhaps the best known and most disconcerting of the stresses man
applies to the environment, and some authors (e.g. Calabrese & Baldwin, 1993) treat
ecosystem risk as almost entirely toxicological. The extent to which these and
nontoxicological equivalents can be treated in consistent ways is debatable. Generally
speaking the two may be distinguished in legal terms, for setting of standards. Chemical
environmental threats, being found wherever the products are used or transported, are not
precisely controlled in their distribution, and thus generally addressed as products,
whose use and concentrations are controlled on the market by standards. Nontoxic threats
are generally site-specific, being effectively caused by processes, and thus limited to
their sites, such as nuclear power stations or logged forests, and are regulated by local
monitoring and evaluated by the site-specific subdiscipline of environmental risk
assessment known as Environmental Impact Assessment. Nonetheless, this distinction is not
perfect: a chemical manufacturing plant will pose site-specific toxic risks, such as
possible leaks of intermediary chemicals used in the manufacturing process, quite
different from those encountered in the use of its products, and the risks from the
introduction to an environment of an alien species will be found wherever the species may
spread. Also, with regard to trade implications, it can no longer be argued that product
standards, affecting goods traded, are the sole concern of national environmental policy
as process standards affect only the host country: increasingly states are reluctant to
import products, however satisfactory their intrinsic qualities, that are produced with
serious environmental process risks (Charnowitz, 1993).
There is therefore a case to be made for treating toxic and nontoxic environmental dangers
as essentially similar. In the USA, the Environmental Protection Agency (USEPA) is
developing framework guidelines for such a harmonized approach, arguing, sometimes
implicitly, that ecological "stressors" can be treated alike, with
"extents" of nontoxic factors, such as the number of inches drop in the water
level of a wetland, or the percentage of trees in a forest felled, treatable as
essentially like doses of chemicals (Norton et al., 1992). The distinction between product
and process standards remains a useful one, however, and can be maintained in discussions
over the international harmonization of environmental risk analysis processes.
A more meaningful division of the field may be into the evaluation of those environmental
threats which are essentially incremental in their effects, such as most toxins, or the
erosion of the ozone layer, whose effects may be considered in some way additive, and
those which are systematic, a single event producing widespread repercussions, such as the
extermination of a species, the introduction of an exotic species, or the construction of
a dam. Incremental stressors may be essentially transient, the effects of each encounter
with them declining over time, as in the case of a pesticide which decomposes relatively
quickly, in the environment or in the bodies of organisms, or cumulative, as in the case
of a pesticide which decomposes only slowly, and therefore may build up, over a series of
encounters, in organisms or their environment. Especially if they are transient, they can
to some extent be controlled after their action, as monitoring may reveal when their
build-up approaches a critical level; the risks of systematic stresses must be considered
a priori, and often without the option of laboratory or small-scale testing. Ecosystems
may be able to recover from incremental stresses, such as by "negative feedback"
processes whereby an increase in a phenomenon itself produces ecological responses to
lower its levels back towards an equilibrium; systematic stresses may trigger
"positive feedback" whereby the departure from equilibrium accelerates itself,
so that relatively small initial departures can spiral uncontrollably into a collapse of
the system.
A critical question for the risk analyst is often whether a specific phenomenon may be
incremental or systematic, or may switch from one to the other. For example, selective
forestry in North America may be incremental in its effects, as natural tree regeneration
restores the forest to equilibrium; the same approach in Tropical America may be
systematic as, even if few trees are removed, the opening of the forest by access roads
often permits the settlement of the land by colonizers, who clear the remaining trees for
agriculture, bringing about a collapse of the system. More seriously, the contribution of
anthropogenic carbon dioxide to global warming has apparently been governed by negative
feedback processes so far, as not all the carbon dioxide released since the industrial
revolution is still in the atmosphere (though nobody knows quite where it is); but in
future, under some scenarios, such as the shrinking of the boreal forest belt as it
retreats towards the North Pole or the large scale melting of ice caps, these processes
may change to those of positive feedback, the effects of global warming producing further
warming, with serious consequences for the global environment. Partly because of the large
scientific uncertainties surrounding these processes, the consideration of whether
environmental threats are likely to be incremental or systematic and which, if any,
feedback processes may apply, are critical questions for the management of environmental
risk. "For risk to a phenomenon as complex as the environment, it can never be
certain that the process of hazard identification has been sufficiently imaginative and
rigourous."
2. RISK ANALYSIS
"Risk" is defined many ways, in different technical fields and among laypeople.
In general, it is the probability of something bad happening. The something bad is known
as "damage" - defined formally as "the loss of inherent quality suffered by
an entity" (Warner, 1992) or, more generally, as "something you would like to
avoid".
"Probability" itself is a somewhat slippery concept. The probability of an event
happening is the mathematically expressed chance of it doing so, usually as a fraction of
1. To be meaningful, probabilities have to be bounded, usually within a certain period of
time, such as before the end of the week, or in association with a particular event, such
as a single toss of a coin: unbounded probabilities tend to be 1, or certainty - it is
certain that all life on planet Earth will end one day, but the probability of it
happening this year is smaller. They are also generally conditional, the probability of
events, such as risks, varying with circumstances, such as between populations exposed or
susceptible to them to different degrees.
For example, the probability of being hit by a car while crossing the road in Los Angeles,
California, is higher than that in a small rural village.
As formally expressed in mathematical terms, probabilities are useful in the real world
because they can be manipulated by arithmetic - added, subtracted, multiplied and so
forth.
Probabilities are generally approximated by frequencies: if a coin tossed 1000 times comes
up "heads" 500 of them, we estimate a probability of 0.5 that it will do so next
time. However, probabilities cannot be truly known, for the same reason as that behind
Hume's problem - we have no way of knowing that the next 1000 tosses will not all be
"tails". Nonetheless, over a large number of replications frequencies tend to
represent probabilities. The frequencies of rare events, on the other hand, are little use
for the estimation of probabilities. For example there has never been a recorded
earthquake in Manchester, England - but there remains a small probability that there will
be (Stewart, 1990). In a sense, therefore, all probability estimates are subjective.
"Hazard" is an inherent capacity to cause damage - an intrinsic property. DDT
therefore simply is hazardous, but this is a property, and so is not probabilistic and
therefore not risky - risk is applied to events, not properties. Risk is the probability
of the potential of hazard becoming realised as damage.
Risk can be defined in at least ten ways (Pidgeon et al., 1992), but in risk analysis two
definitions are most common - risk is either "the probability of an adverse
event" or "the probability of an adverse event multiplied by the extent of the
damage caused." The former is the formal economic definition, and widely used, but
the latter is gaining currency.
The former, under which the latter is called "detriment" (Warner, 1992), will be
followed here. The reason for this is that the quantified assessment of detriment implies
the quantification of damage, and in much environmental risk assessment this
quantification, implicit though it may be, is not performed.
The quantification of environmental values is a field in itself.
Damage, and therefore risk, can broadly be categorized as economic, safety or
environmental - in order of decreasing ease of quantifiability. Economic risk is a well
worked field, having being studied for centuries by the profession of its analysis, the
insurance industry. Much progress has been made in the quantification and even economic
valuation of safety risks too, by estimation of the prices people are apparently willing
to pay for specified reductions in the risk of injury or death. Economic valuation of the
environment is performed and advocated, on the grounds that "any decision implies
valuation" and that if environmental valuation is not tried in the taking of an
environmentally relevant decision "we do not know whether the decision was a sound
one or not in terms of economic efficiency" (Barde & Pearce, 1991). Environmental
assets can be valued in essentially two ways. One is variants of "hedonic
pricing" using real world data, by estimating values from, for example, house and
hotel prices which may be expected to reflect preparedness to pay for proximity to
environmental resources, or from spending on travel to visit them. The other is variants
of "contingent valuation", which estimate how much people are willing to pay for
environmental assets by asking hypothetical questions (Barde & Pearce, 1991). However,
the valuation of the environment is not necessary for environmental risk assessment and
is, in fact, only rarely carried out. The ways in which environmental values are
considered are various and subtle, and will be discussed below.
In contrast, the benefits of taking risks are commonly more easily valued - the financial
benefits from logging a forest, using a pesticide or building a nuclear power station are
usually worked out by the people who propose to do it. It should be remembered that to
avoid risk has its costs - pesticides, timber and energy are valuable and useful things.
The decision of whether or not to take risk is one of balance.
All action, including inaction, carries some risk, and so all decisions entail risk
judgement, even if subconsciously (Calow, 1994; Stewart, 1993). "Risk analysis"
is a more explicit, systematic and communicable extension of this. It risk comprises two
interconnecting parts. "Risk assessment" is the structured assembly of an
estimate or representation of the total risk from an activity. In principle, it is
scientific, deterministic and objective. Its results are then used for "Risk
evaluation", the consideration of the significance and meaning of risk, used for
making the decision of whether the risk is to be taken. Risk evaluation is necessarily
subjective, political and value-laden. Assessment and evaluation together form the whole
process of "Risk analysis".
RISK ASSESSMENT
A. THE HYPOTHETICAL CASE OF "Fully Probabilized Risk" The concept of risk as the
probability of an event is most readily conceived in the contemplation of accidents, the
province of Engineering Risk assessment (Crossland et al., 1992). A typical such
assessment looks at the sequence of events which may lead to a system failure in a
factory, leading to a leak of toxic chemicals to the environment. This process, the
assembly of a composite representation of risk or "risk model", entails the
sequential consideration of the events which, happening one after the other, together
finally manifest themselves as the total risk.
i. Hazard Identification
The process begins with "Hazard Identification", the formal listing of what
hazards may exist and what risky situations may arise, and how. For the analysis of an
engineering plant, this entails a systematic examination of plant components, functions
and interconnections. For environmental risks, involving more complex and loosely bounded
systems, the process is more a question of imagination, to consider problems which may
arise, within an attempt to bound the exercise to prevent the consideration of risks
spreading ever-outward to the limits of the environmental field.
ii. Assignment of Probabilities
Hazards which are identified as both serious and realistic are broken down into the
sequential events which may bring them into effect, for example the release of chemicals
from a system may require the failure of a valve, followed by the failure of a pump,
followed by the failure of a control system and of a warning alarm (or the failure of a
human operator to recognise the alarm and to act on it). The "Assignment of
Probabilities" to each of these events is performed in appropriate ways - for
example, the failure rate of a certain valve or pump may be well known from records of its
performance in other systems (large technical databases exist of this information), others
may be estimated from expert opinions. The probability of the final, disastrous failure,
is derived by the multiplication of the component probabilities. For example, if every ten
years failure "A" has a probability of 1 in 20 (i.e. 0.05) and failure
"B" one of 1 in 100 (i.e. 0.01) the probability of their both occurring at once
is 0.05 x 0.01 = 0.0005 (i.e. 1 in 2000).
iii. Consequence Modelling
From the derivation of the probability of an accident, the analysis proceeds to
"Consequence Modelling". At this point the assessment begins to lose analytical
rigour. The dispersal of pollutants may be affected by the wind or water currents at the
time, to be derived from meteorological information or models of flows in estuaries or the
atmosphere; the population of organisms exposed will be site-specific and, in cases such
as humans at work or home or migratory animals, may vary in time, and this must be
recorded. These techniques are used to estimate the likely exposure of a population.
Following on from them, the uptake of pollutants by organisms must be estimated, both
biophysically, whether through the skin, gut or lungs, and behaviourally if, for example,
birds are likely to eat contaminated insects, worms or fish. From the projected uptake
values the likely toxic damage must be estimated by dose:response information, from LD50
or NOAEL values, these relationships generally estimated by extrapolation from tests on
laboratory organisms such as rats.
Environmental risk assessment is not always assessing the likelihood of an accident: the
use of agricultural pesticides, for example, is risky but deliberate. In this case, the
assessment is of risk not in the sense of an accident happening, but of something having
effects that cannot be precisely foreseen, and consequence modelling comprises the whole
operation. The tools used for their analysis are similar because we do not know what will
happen - risk analysis is therefore in a sense "ignorance analysis".
This analysis can be assembled in several ways to provide a holistic picture. At the
simplest level, the probabilities of certain levels of damage can be calculated as single
number values, by the multiplicative combination of probability estimates at each step.
For the decision maker to make a more informed judgement, a more detailed picture of the
chain of events may be needed. One way to do this is by means of branching
"trees" of sequential failures and their ramifications. "Event trees"
follow the possible consequences onward from an initial failure; "fault trees"
proceed the other way, moving backward up the chain of causes needed to result in a
specified undesirable outcome, the dramatically named "top event" (Crossland et
al., 1992).
A more sophisticated synthesis may be in the form of a computer model. Such models
express, in a quantified way, the flow of events or material through the system. They are
particularly useful, and widely used, for consequence modelling, using information about
the flows of air or water, and the passage of food up food chains through ecosystems, to
estimate likely movements of toxins through the environment and ecological compartments.
However, they require careful validation and testing, and confidence in their reliability
is generally built up only over time, as their relevance to the real world is shown
(Barlow et al., 1992; Geraghty, 1993).
From such a synthesis, risk management has options for action. At the extremes, it may be
decided that no risk is present worth considering further; or that the risk is
unacceptable, and the construction of the plant, sale of the pesticide or whatever, simply
forbidden (in fact, in either of these cases, such a decision may be reached before
completion of the full risk assessment process). Otherwise, the process allows risk
managers to identify critical points on the trees where preventative measures may be
focused to reduce risk, such as the addition of another safety system or the doubling up
of control personnel where human alertness and competence is of importance.
B. BREAKDOWNS OF THE FULLY PROBABILIZED IDEAL, AND TOOLS USED TO MANAGE THEM
In reality, allocations of probabilities to top events can only very rarely be assessed
with even the level of accuracy implied above. These are only some of the areas of
uncertainty.
1) For risk to a phenomenon as complex as the environment, it can never be certain that
the process of hazard identification has been sufficiently imaginative and rigourous. This
is important because the hazards identified dictate the whole of the subsequent
structuring of the risk model, and so the model may be inappropriate if hazards are
unforeseen, arising out of, say, ecological interactions or unexpected conditions such as
violent weather. Tools exist to facilitate this. For example a well established routine
for chemical plants, "HAZOP", which involves a dissection of the process pathway
into all its discrete steps, and the application to each step of code phrases such as
"more than", "less than" or "other than" to force
consideration of how the process may deviate from intention, has been modified, as
"GENHAZ", to structure a similarly systematic exploration of the potential
hazards from the experimental release of genetically modified organisms to the environment
(Royal Commission, 1992). Even with such tools, however, the need remains for imagination
and for judgement - in particular, the exercise must be logically limited to prevent the
endless expansion of "the universe of discourse" (Crossland et al., 1992).
2) In sciences such as biology and meteorology, where the data to be worked with are both
variable and influenced by a large number of factors, the very measurement of variables is
often fiendishly difficult. For example, bioassays performed in supposedly identical ways
by different laboratories may produce widely different results without strict control of a
plethora of conditions and variables. This can be investigated and controlled by
"ring tests", whereby the same test is performed by a group of laboratories with
identical test materials, and their results compared.
The usefulness of this, and the dangers it may illustrate, was shown by a ring test
carried out in 1986 by the European Community (EC) of toxicity to laboratory clone
populations of Daphnia magna (a small freshwater shrimp widely used as a test organism for
laboratory bioassays; a clone population is one in which all individuals are genetically
identical, being derived asexually from a single parent). Among the 22 laboratories which
reported results, the conclusions varied by the maximum amount possible (i.e. the
estimated toxic doses ranged from below the minimum concentration specified by the test
procedure to above the maximum). Subsequent investigation found that not only did the
clones of D. magna used differ between laboratories (including one case where a clone
deviated, apparently by spontaneous random mutation, to produce a new genetic type) but
also so did their rearing diets and conditions. Research found that both clones and
rearing conditions did produce differences in the toxic susceptibility of populations,
often in subtle ways - for example, susceptibility differed in shrimps whose mothers were
fed different diets (Baird et al., 1989). It is for the discovery of problems like this
that ring tests are carried out, and efforts have been and are being made, in the EC and
elsewhere, to standardize procedures to avoid them, but they remain a disturbing source of
potential inaccuracy.
3) The accuracy of statistical estimation decreases away from the centre of a probability
distribution (usually the average or "mean") towards its edges, or
"tails". This is inconvenient because it is at the tails that human interest is
concentrated - particularly in the probabilities of very unlikely but very serious
incidents, or disasters.
This is because in human perception the probabilities of risk are clearly not treated
arithmetically: people will not, for example, treat a certain loss of $1, a 1 in 10 chance
of a loss of $10 and a 1 in 1000 chance of a loss of $1000 as equally undesirable - if
they did, nobody would ever insure anything. The estimation of the probabilities of rare
but severe events is even less reliable than that of others.
4) In the assembly of probabilistic risk models probabilities are assumed to be
independent from each other, yet may not be so: in the case of accidents, if a human
operator fails to adjust a piece of equipment correctly, the same operator may fail to
notice an emergency warning, due to tiredness, negligence or alcohol consumption; in
environmental systems risks may, as outlined above, become systematic if positive feedback
processes are activated.
5) Another assumption too often made is that the response of the natural world to stresses
is linear, that is, that the response to an incremental increase in stress at one level
will be related (albeit perhaps in a logarithmic, multiplicative way rather than an
additive one) to the response at other levels. Yet this is not always the case: above
threshold levels the system may respond in quite different ways. This applies in
toxicology (for example, oxygen is highly toxic at high concentrations) and also in
ecology, where work with mathematical models has shown that even simple ecological systems
may, when disturbed beyond narrow boundaries, show violently erratic, chaotic behaviour.
Increasingly, however, scientists are moving away from the assumption of linearity,
although this greatly increases the complexity of analysis.
6) Yet another assumption often made is that the effects of processes are independent, so
that when more than one is encountered together their effects are additive. This
assumption, however, the base of the approach that complex processes may be reduced to
their components, or reductionism, is often mistaken, interactive effects being commonly
found. As with the assumption of linearity, scientists are moving beyond this assumption,
however, although, again, this increases analytic complexity.
7) The processes of extrapolation are ubiquitous in environmental risk assessment, and lie
at the heart of many of its difficulties. For ecological risk assessment, toxicological
extrapolation is needed within species, to estimate the toxic susceptibility of the
population from the sample tested; between species, from the species tested to those
likely to be exposed; from laboratory to field conditions; from acute to chronic effects;
and from effects in tests to those likely in real ecosystems. For example, extrapolation
is needed to assess the likely effects of pulsed or episodic as opposed to steady-state
exposure (Seager & Maltby, 1989); of cumulative build-up of effects (Spalding &
Smit, 1993); of bioaccumulation of toxins in the tissues of organisms, or ecoaccumulation
such as that of DDT in the progression up food chains; and the effects of simultaneous
exposure to multiple stresses, whether these will be additive or interact in mutually
reinforcing ways.
Because of their ubiquity and difficulty, much research effort has been spent on
extrapolation techniques. In particular, attention has been focused on the search for
understanding of the mechanisms in toxic processes - of how toxins are absorbed,
distributed, modified and take effect. However, this search for understanding of the
causes of toxic effects has produced little success - there are currently few
"laws" inferred about toxic processes which are not merely extrapolations
derived from observations of correlations (Barlow et al., 1992). Studies of parallel
tests, to investigate the reliability of extrapolation between species, have been carried
out in many cases, but have produced conflicting results. For example, between species
reliable extrapolability has been found between some species with some chemicals, but not
others (Emans et al., 1993; Greig-Smith, 1992). Similarly, progress is being made in the
extrapolation from laboratory to field conditions (Munawar et al., 1992) and from acute
effects to chronic (Giesy et al., 1989). Interactions, where two stresses encountered
together exert greater stress than the sum of either alone, have been found with pesticide
combinations in some species but not in others (Johnston et al., 1994). A good deal of
work is needed for understanding the extrapolability of these effects and, indeed, it
seems reasonable to suppose it will never be reliable.
8) This is just one example of the general situation that mechanisms are poorly
understood. The problems of the convincing demonstration of causality have been discussed
above, and are particularly severe in the complex and variable world of the environment.
Some tools can assist the inference of causation even from nonexperimental observations,
such as "falsification routines", the use of structured approaches (not unlike
GENHAZ) to evaluate alternative possible causes for effects. For reliable prediction of
environmental effects in any but the most general ways, for example for the building of
precise computer models of systems, understanding of mechanisms is required, but is not
well advanced (Calow, 1993a).
9) The complexity of environmental variables and their interactions through effects such
as ecological mediation are another source of uncertainty in the interpretation of
environmental risk information. Data may be of different types, from bioassays, computer
models, published scientific papers or engineering or meteorological data, whose
contributions must be balanced and evaluated. Inconsistencies in data sets, such as higher
toxic susceptibilities in some species than others or accumulation in certain organs more
than others, must be interpreted. The scale and scope of such information make its
interpretation as much of an art as a science.
The outcome of all the problems raised above is twofold.
First, the results obtained often cannot be quantified. Instead, they may be qualitative
only, or categorized - for example into "high", "medium" and
"low" risks. Categorized conclusions lend themselves to understanding, recognise
the inherent uncertainty of the knowledge and allow cross-comparisons and standardization,
but they are themselves imprecise by their nature, and difficult to define in a
standardizable way (GreigSmith, 1992). Findings of this sort have their uses, but their
significance must be assessed with skill.
Second, the assessment of environmental risk is the evaluation not only of risk, which is
a situation whose outcome is unknown but where the probabilities of each possible outcome
are known, but also of uncertainty, where the probabilities themselves are unknown.
Uncertainty is principally addressed by the use of "safety factors", whereby
levels estimated to be "safe" are multiplied to provide those that will be
treated as "safe", to reflect lack of confidence in extrapolations and so forth
(Talcott, 1992).
In some fields the practice, and the factors used, are well established, for example the
traditional but widespread factor of 100 applied when extrapolating rat toxicity data to
humans. Yet even at this level other factors are not widely accepted (e.g. the proposed
analogous factors of 500 for reproductive toxins and 1000 for carcinogens) (Barlow et al.,
1992), and factors for other areas, such as ecosystem risks, are even less so. An
alternative approach is uncertainty analysis.
Uncertainty analysis is by its nature an imprecise field, and indeed the expression
"uncertainty analysis" may be considered something of an oxymoron. However there
are tools which can be employed in situations of uncertainty. Chief of these is the
attempt to express the likely degree of error of an estimate. Often these can only be
verbal, but attempts have been made to draw up scales of such verbal descriptions, with
rough analogues of quantified error estimates, for example "extremely uncertain"
to indicate "probability of 0.025 that the true value is more than 100 times the
estimate or less than 1/100 of it" (Talcott, 1992). The attachment of such estimates,
rough as they may be, to each probability in a risk model helps to identify where the
uncertainty arises, so that further research or particular efforts at risk reduction may
be applied to them. For practical risk management purposes, another useful tool is
sensitivity analysis, whereby highly uncertain values may be hypothetically considered to
be in truth higher or lower than estimated, and the impact of these different values on
the whole risk assessment considered. When the risk model is fully quantified and in the
form of a computerized mathematical model, this may be done by the random insertion, one
after the other, of large numbers of varying values for uncertain estimates, and the
distribution of the final estimates evaluated, in a process poetically known as
"Monte Carlo analysis" (Talcott, 1992). Nonetheless, uncertainty is sometimes
irreducible, on the principle that "there are things that we know we don't know, but
others that we don't know we don't know".
C. THE USE OF EXPERT JUDGEMENT
In the light of these sources of error and uncertainty, very often the only solution
possible is the application of expert judgement. The employment of judgement, which is
often essentially subjective, the "hunch" of an experienced practitioner, may
seem something of a retreat from the rigours of scientific discipline, but in practical
terms is not only inevitable, as many risks cannot be formally quantified, but productive
- the experience and judgement of experts is, by its nature, generally not quantified,
formalized or published, but remains valuable and relevant information, and to fail to
make use of such expertise would be to fail to use all the relevant information available.
Given this situation, attempts are being made to formalize and rationalize the use of
expert judgement. Its integration with more formal scientific methods is uneasy and
uncertain, as certain principles of scientific research (such as replicability) are
clearly undermined - indeed, it was largely to remove the need for such subjective
judgement that many elements of the scientific method, such as replicability and the
formal statement of falsifiable hypotheses, were developed in the first place. The
application of some discipline and rigour to its use is important, both for the
credibility of conclusions and also for the free transferability of assessments and their
conclusions for the harmonization of processes in the interests of open trade.
The central tool for the rationalization of expert judgement is documentation. All authors
in the fuzzier areas of environmental risk assessment are in agreement over the importance
of a careful, explicit and comprehensive "document trail", in which the
decisions reached and criteria used are clearly described and justified, so that the
process can be evaluated, per se or for its subsequent applicability to other cases.
The employment of subjective probability values can be made coherent and useful by the
employment of Bayesian probabilities. This approach is a way of combining probability
information from different sources, incorporating, for example, old data or those which
are considered to be relevant but not strictly applicable (such as fieldwork from
different but similar geographical areas) so that the use of relevant information is
maximized and none is lost or wasted. Additionally, new information as it arrives can be
incorporated to upgrade the composite probability values, and the information incorporated
can be weighted (for example by giving lesser weights to uncertain sources or those whose
relevance is questionable), to give appropriate emphasis to those component information
sources which are more or less reliable or important (Dillon & Officer, 1971).
The problems of the maximization of the objectivity of experts can also be addressed, at
the simplest level by the widespread use of contractually independent consultants rather
than inhouse teams, or by more sophisticated approaches such as "Delphi
techniques". Delphi techniques allow the views of a group of experts to be canvassed
and synthesized, by the polling of the individuals, usually by a questionnaire, the
circulation to them of a synthesis of the results, and then repeating the process,
allowing comment and debate, until a consensus is reached or, at worst, disagreements have
been systematically explored and the reasons for them made clear and explicit, all usually
carried out under anonymity for each member, to allow free expression and criticism.
The technique has advantages over a physical gathering of experts in that all views are
heard, neither the majority nor a vocal minority dominating the debate, and that it is
generally cheaper, as simultaneous attention by all parties is not needed and travel costs
are saved. Sampling research has suggested that as few as ten members can comprise an
effective group, as long as they are carefully chosen to be representative. The role of
subjective input is not eliminated, however, as the effectiveness of the approach depends
on the skill and judgement of the central "monitor team" who choose the
participants and questions, and write the syntheses (Richey et al., 1985a).
The demand for expert judgement for environmental risk assessment is large and growing
and, although educational systems are expanding to meet this, is likely to exceed supply
for the near future. This problem, together with the desire to standardize and harmonize
expert findings, has led to interest in the use of expert systems, computer models of
human expertise which, relative to a real person, are cheaper and faster and, being
deterministic information processors, produce consistent and therefore standardized
conclusions. The snag with these systems is that their construction, requiring the formal
expression of subjective and intuitive inference processes and exhaustive subsequent
checking of the output, is very slow, taking several years. However, several have been in
development for some time, and their arrival in operation may substantially increase their
use (Geraghty, 1993).
RISK EVALUATION
There comes a point where the assessment of risk hands over to the process of its
evaluation: at this point we reach the limits of science and the need for social and
political values. The need for subjective expert judgement in the face of the limits of
environmental information, described above, can be termed "assessment
subjectivity" - in theory, it is subjectivity of estimation, and not value-laden; it
is therefore different in principle from "evaluation subjectivity", which
expressly weighs ethical and social values.
The cleanliness of the distinction between assessment and evaluation is not absolute, the
subject of much debate, and currently in decline. This is for two reasons. First, progress
in the psychological and social sciences is beginning to shed some light onto the meaning
and derivation of "subjective" risk perception. Second, the essentially
subjective nature of the use of expert judgement in the process of risk assessment, while
it can be reduced by methods such as Delphi techniques and expert systems, cannot be
eliminated. The significance of the latter point has been shown by anthropological and
sociological studies of communities of scientists themselves, which have shown their
assumptions, opinions and beliefs to be shaped by the institutions and conditions in which
they develop.
Scientists can be shown to tend to share bodies of knowledge, accepted procedures,
attitudes and confidence in institutions among themselves more than they do with other
people, which has caused environmentalists often to view the use of their opinions with
suspicion. The public reaction to discoveries about the safety of nuclear facilities in
the former Warsaw Pact countries has shown how quickly the validity of the opinions of
scientific bodies can be discredited when political circumstances change (Pidgeon et al.,
1992).
However, the assessment-evaluation distinction, at least as a concept, for the
understanding of the risk analysis process, is valid and useful. It is broadly analogous
to that between the functions of technocratic "civil servants" and
representative "politicians": in principle, at least, the evaluator of risk
should be politically accountable, whereas the assessor is "simply doing a job".
The evaluation of risk is a direct function of its perception. Risk perception has been
studied for some time by behavioural scientists. Its assessment is a bit like
environmental valuation - a choice between researching "expressed preferences"
from peoples' answers to hypothetical questions and "revealed preferences" from
actual behaviour, such as willingness to work in risky jobs for higher wages, implicitly
valuing risk, with the latter currently losing credibility to the former.
The central conclusion is that risk perception is multidimensional, perceptions differing
between individuals and contexts, so that for policy purposes "risk" as rated by
the public is not reducible to a single value such as a function, albeit a subjective one,
of probability x damage (Pidgeon et al., 1992). As a result, risk policy making inevitably
involves confrontation, balance and compromise. People also differ in their willingness to
take risks, apparently as part of inherent personality diversity.
Risk may not be "accepted" and therefore "acceptable" in the sense
that it is consciously balanced against a perceived good, but "tolerated" where
necessary: in general people are risk averse, which has led to caution in the acceptance
of risk in policy making. This, together with the imprecision of the safety factors by
which it is commonly expressed, has led to frustration among many scientists that
overcautious risk avoidance is leading to losses of social benefits through worthwhile
risks not being taken, and some predictions that "de minimis" risk analyses are
losing credibility and will not be sustainable (Berry, 1990). However, the view that the
public "fails" to appreciate true risk levels and that public intolerance of
"small" risks, that scientists consider to be worth taking, may be addressed by
education and explanation of real risk levels in rational terms, is currently losing
ground to the view that risk perceptions are deeply seated. Therefore, public
confrontations may be better averted if these perceptions are not treated as
"problems" to be "rectified" by education but as, in themselves, valid
elements of the background to the public management of risk, which should be addressed and
incorporated from the beginning in risk analyses. The "acceptability" of risk is
therefore widely estimated using entirely political processes, being subjectively set by
politically accountable bodies such as parliaments. Despite its imprecision, this in fact
works adequately well as the best available way to allow public opinions of acceptability
to be used (Pidgeon et al., 1992).
A well known finding about risk perception is that several factors, other than the
absolute probabilistic risk level, influence peoples' perceptions of risk as intolerable.
These "outrage factors" have been extensively researched for safety risks, and
reasons for some of them investigated. In general, risks are less tolerable if they are:
- with inadequate, unclear or selective corresponding benefits;
- imposed, not being undertaken voluntarily by the risk bearer;
- outside personal control, the risk bearer having to trust to others the management of
risk;
- seen as unethical or unfair in the distribution of the risk burden;
- publicly managed by untrustworthy information sources;
- artificial as opposed to natural;
- insidious, with damage happening in unseen ways (e.g. poisoning);
- of unknown time duration, particularly slow-acting damage which may affect subsequent
generations;
- unfamiliar;
- associated with memorable events such as disasters. (People appear to have a peculiar
dread of mass-scale disasters; also it appears that an event is conceived as
"probable" if it is easily imagined or remembered, due to a convenient internal
"rule of thumb" to facilitate the building of mental models of the world, known
as the "availability heuristic" - memorable events such as disasters are by
definition mentally "available" in this way [Pidgeon et al., 1992].)
In fact, most of these criteria seem intuitively apparent to the layman. The importance of
the trustworthiness of institutions, for example, is readily appreciable, and it has been
argued that failing public trust in state organizations is an endemic threat to public
consensus on risk analysis, arising from inherent properties in current political and
media structures, amplified by rapid social and technical change (Slovic, 1993).
Clearly, some risks fulfill these criteria more than others.
Recreational mountaineering, for example, is an extremely dangerous activity, yet widely
popular because it entails so few outrage factors - for example, the benefits in enjoyment
value are considerable and risks are under personal control, voluntarily undertaken and
not insidious (as they basically entail falling off mountains). By contrast, environmental
risks, whether health risks such as air pollution or food additives or ecological risks
such pesticide use or the risks of oil tanker accidents, rate highly on many of these
criteria: environmental risks are particularly prone to outrage factors.
Beyond the psychological study of individual risk perception stretches the relatively new
research field of how it is influenced by social and cultural structures. Some of this
work, such as suggestions that group dynamics and coherence are critical in risk
perception, and even that people may in a sense choose perceptions in order to defend
their group's way of life, is revolutionary in its ideas, deeply controversial, but still
untested by convincing field evidence (Pidgeon et al., 1992).
Increasing understanding of the way in which risk perception is modified by psychological
and social factors has accelerated developments in Risk Communication. The importance of
this field is being increasingly recognized, due in part to the increase of legal
requirements of the practitioners of risky activities to inform the public of risk levels,
but also of the manifest political problems encountered by policy makers in the social
tolerance of risk. The latter are amply illustrated by the widespread failure over the
years of campaigns by authorities to convince the public of the acceptability of risks,
and the analysis of the deep seated roots of outrage factors has illuminated the failings
of the conventional approach of risk comparisons, for example, by comparing the risks of
living near a nuclear reactor with that of walking across the road, to have much effect on
public risk tolerance. Developments in this field are proceeding, and have so far few
empirical studies to clarify issues currently only guessed at, but two developments seem
clear (Pidgeon et al., 1992). First is that risk communication itself is currently an
uncertain venture, which may "backfire" on its practitioners, exemplified in the
cautionary conclusion that "one should no more release an untested communication than
an untested product" (Warner, 1992). Second is that risk communication is becoming
more of a two-way, interactive process, with the opinions of the public and of risk
evaluators to be incorporated from the beginning of the risk analysis process, and
constant feedback to be provided between assessors and evaluators in a "looped"
process of analysis, to ensure the public relevance of the direction of investigation.
CONCLUSIONS
First, the traditional distinction between objective risk assessment and subjective risk
evaluation is breaking down, for the two reasons given above.
The distinction drawn here between the roles of "assessment subjectivity", to
assign probable damage levels in the face of incomplete data, and "evaluation
subjectivity", for the consideration of the ethical or social significance of
results, may clarify this problem to some extent but does not solve it. Nonetheless, the
distinction remains a useful one, not least for the problems of the international
harmonization of risk analysis procedures. At root, proposals for such harmonization
entail the standardization and/or mutual recognition of risk assessment procedures, while
leaving the value-laden risk evaluation process to sovereign states; yet the distinction
is inadequately drawn in many national risk analysis processes, and the point on the chain
of political responsibility where the line is drawn varies widely between countries.
Second, and contributing further to the problems of a clear assessment/evaluation
distinction as a basis for harmonization, consensus is emerging that public perceptions of
risk are best not treated as "problems" to be overcome but as valid inputs to
the risk analysis process.
An important implication of this is that between nations with different risk perception
cultures and traditions the entire process of risk analysis may be carried out in
fundamentally different ways.
Third, the perception of risk across society varies between individuals in fundamental
ways. As a result, the weighting of the risk perceptions of social groups, even when these
can of themselves be adequately characterized, will always depend on political
negotiation, compromise and the resolution of conflicts of perception.
"The interactive nature of ecosystems means that the testing of any selection of
individual species will not gurantee that ecologically mediated effects will be
detected."
3. ENVIRONMENTAL RISK ANALYSIS
THE TOXICOLOGY OF A SINGLE SPECIES
Typically, the assessment of toxic risk to a species follows a variant of the chain from
hazard identification to risk evaluation discussed above. This typically takes the form,
as exemplified here by the European Commission's Directive 93/67/EEC, "laying down
the principles for the assessment of risks to man and the environment" of hazardous
substances (European Commission, 1993), of: (1) Hazard identification, (2) Dose:response
assessment, (3) Exposure assessment and (4) Risk characterization.
A. Hazard identification, the same in principle as the same process discussed in an
engineering context above, here being "identification of the adverse effects which a
substance has an inherent capacity to cause" (European Commission, 1993).
B. Dose: response assessment, carried out by the EC Principles to apply to both humans and
"environmental compartments". A problem with this approach is the need for
extrapolation, as discussed above. Another is the level of response to be assessed. The EC
advocates, for risks to humans, the No Observed Adverse Effect Level (NOAEL) or, for
environmental compartments, the No Observed Adverse Effect Concentration (NOAEC) or, where
these are not feasible, the best or most appropriate equivalent such as applying an
"assessment factor" to the LD50 or, if all else fails, using subjective or
qualitative best guesses. The NOAEC is used to derive a Predicted No Effect Concentration
(PNEC).
The use of this basic statistic is inevitable although it has difficulties. For example,
at a conceptual level, the existence of "no effect" cannot be proved - the
specification of no "observed" effect implies that unobserved ones may be
present. Also, if dose:response relationships are continuous, a "threshold" may
not exist, being a concept more of convenience than of science (Calow, 1993a, 1993b).
Furthermore, the interval steps used for toxin concentrations in assays are sometimes
large, and so NOAECs derived from them may be to some extent arbitrary (Barlow et al.,
1992). The application of safety factors is intended, though it cannot guarantee, to
remedy these difficulties, and thus the liberality of safety factors can be seen as a
substitute for the precision of information.
The PNEC value is therefore in a sense itself a risk - the (low) risk of damage if a toxin
is encountered at a certain concentration. It is thought to be zero, but this cannot be
guaranteed: PNECs are "thought to be levels at which the probability of an effect is
very low. This probability remains undefined; but the exercise of caution in the
application of safety factors guarantees that it ought to be near zero" (Calow,
1993b).
C. Exposure assessment, whereby the likely exposure of susceptible components is assessed,
whether by accidental releases or by conventional use of products such as cleaners,
pesticides and paints, to obtain a Predicted Exposure Concentration (PEC). Exposure
assessment, with a shorter history than toxicological dose:response assessment, is a
science still in its infancy. It requires estimates of levels of production of the
substance, patterns of its use, its distribution in the environment, including ways in
which be transported in air or water, or bioaccumulated in organisms, and of its rates of
degradation, as it may be broken down by sunlight, heat or organisms. Information about
production and use may be available, and rates of bioaccumulation and degradation be
researched by assays, but the remaining information is generally estimated by the use of
mathematical computer models (Calow, 1993b). These are increasing in sophistication with,
for example, the extension of the model past the periphery of the individual organism to
the consideration of individual organs, and by kinetic models able to estimate the effects
of pulsed and multiple doses and non-steady states (Landrum et al., 1992). However, they
still require detailed calibration to be accepted (Calow, 1993a) and full quantification
of the PEC is still unlikely. Regulators recognise that sometimes only qualitative
estimates will be possible (European Commission, 1993). Like the PNEC, therefore, the PEC
is also in a sense itself a risk - the risk of a certain concentration being encountered
under envisaged conditions.
D. Risk characterization, the final step, is the estimation of the severity of likely
effects. Its ideal is typically based on the risk that the PEC will exceed the NOAEC -
most simply by the PEC/PNEC ratio (or "toxicity/exposure" or "T/E
ratio"), to produce a convenient single figure by the socalled "quotient
method". However, on the one hand the European Commission (1993) acknowledges that
T/E ratios are only obtainable in the most accessible cases, being therefore an ideal
which many analyses will fail to achieve, and on the other they are a rather simplistic
expression of probabilistic information: as one observer commented on the use of the T/E
ratio in the EC guidelines, "This is not quite risk assessment, in the sense of
explicitly characterizing the probability of populations or communities becoming impaired
to defined extents" (Calow, 1993a). In particular, the T/E ratio cannot meaningfully
be a single figure, but should take account of the probability distributions of T and E:
even if the average PEC is less than the PNEC, it may exceed it in certain areas if the
toxin is unevenly distributed in the environment. Recommendation that these distributions
be explicitly addressed is included in the Framework for Ecological Risk Assessment
guidelines of the USA Environmental Protection Agency (USEPA) (Norton et al., 1992). Both
the EC and USEPA guidelines emphasize the need for judgemental consideration of factors
and information which are likely to be relevant in the interpretation of the "weight
of evidence", but the USEPA is more precise in indicating that the details of T and E
should be considered, such as their probability distributions and the possible influence
of specific factors such as the vulnerability of species at different points in their life
cycles. Final risk characterizations may, in view of the limitations of the data, be
qualititative, by the T/E ratio, by estimation of the probability distribution of T and E
or by more sophisticated presentations such as simulation models (Norton et al., 1992).
Some regulatory systems are essentially based only on toxicological data, the PNEC alone
being used to inform the classification and labelling of products and so on. As the PNEC
describes only properties of products, this approach is effectively the assessment of
hazard, not of risk, and so may perhaps be better termed "hazard
characterization", whereas the assessment of true risk by the comparison of PNECs
with PECs, as required by the EC, has been called "risk assessment proper" -
"specifying the likelihood of these effect concentrations being exceeded and hence
having an effect on the target" (Calow, 1994).
E. The completion of risk characterization leads to recommendations for risk management.
Decisions may be made in several ways: the ideal is by the acceptance of scientifically
demonstrated quantified findings, but this is not always possible and, in fact, political
evaluations often dictate conclusions as much as scientific findings. Policies may
therefore be set by criteria of the cost of measures, by a process of political consensus
or, indeed, by a more or less arbitrary decision of a standard which broadly satisfies
political opinion - for example the commitment of industrialized countries, in Toronto in
1988, to reduce carbon dioxide emissions by 20% from 1988 levels by 2005 was largely made
"regardless of the effectiveness of such a reduction" (Rotmans & Swart,
1990).
The conclusion reached may be, firstly, that the substance is too dangerous to be released
or, secondly, that it may be released to the market provisionally and conditionally, until
more information becomes available, possibly with risk management qualifications, such as
limits on the total tonnage to be marketed or restrictions of use, such as its limitation
to trained professionals, or stipulations for classification, labelling, packaging or the
contents of the accompanying safety data sheet (European Commission, 1993;
Greig-Smith,1992).
Many regulatory systems consider the total tonnage of products on the market, with
assessment requirements incrementally increased as increasing tonnages marketed pass a
series of threshold totals (European Commission, 1993).
Such management tools may be implemented in five basic ways, depending on the certainty of
conclusions, the seriousness of errors and social and political factors. The first is by
legal commands, such as statutory controls or bans, particularly appropriate when possible
damage is serious and irreversible, such as potentially systematic risks. Second, policy
may attempt to manipulate outcomes, such as by taxes or subsidies. Third, they may be
broadly directed, a goal being stated and individuals being encouraged to meet it without
specific statutory commands, such as by recommendations to use "Best Practical
Means", the "Best Available Technology Not Entailing Excessive Cost", and
so on. Fourth, there may be requirements for information, such as the provision of data to
the public. Fifth, processes may be specified, such as public enquiry structures to
reconcile conflicts in specific cases.
In general, the trend in many countries is of a move away from recommendations based
solely on hazard characterization, such as attempts to influence use so that the PNEC is
not exceeded, such as by specifying various "Best Available Technology"
practices, or simply to require that it be not exceeded. Instead, there is a move to the
use of EC-style risk assessments proper, taking into account the patterns of use, which
allows management by other means, such as limiting the total tonnage of product released
to the market (Calow, 1993b).
On the other hand, the conclusion may be that the analysis is not yet over, and that more
information is required, to be obtained by further laboratory tests or by field trials, in
which case, as funds for such research are not unlimited, objectives must be prioritized
by their likely cost-effectiveness (Calow, 1993a).
F. Researchers in the field are in agreement over the importance, after a decision has
taken effect (such as the evaluated product being released for sale), of post facto
monitoring of impact to evaluate the risks and risk analysis procedures involved, but
regulatory requirements have been slow to incorporate this. Such monitoring may bring
several benefits, both for the risk management of the case in question and for the
gathering of information of wider use to the development of the field as a whole.
First, failures of the risk evaluation may be rectified, and conclusions revised, such as
by the withdrawal of a product; second, predictions can be checked; third, the capacity of
environmental systems for recovery from impact may be evaluated; fourth, unforeseen
ecologically mediated effects may be evaluated; and, fifth, information may be gained to
assist the all-important understanding of processes. The ideal would be a continuous,
rolling process of checking and evaluation, continually updating the status of knowledge
by, for example, the incorporation of post-release findings, whether from similar products
or different cases and countries, into the base of risk information, to be integrated by
methods such as Bayesian techniques for the ongoing refinement of the understanding of
risks. For incremental risks, indeed, post-release monitoring may to some extent draw the
sting from the entire risk management process: if errors in the initial risk analysis can
be made good, then the risk of irreversible catastrophic failure is effectively removed.
Here, indeed, may lie a danger of permitting a false sense of security - errors may not be
rectifiable in the cases of human suffering or of systematic and irreversible damage to
ecosystems, and indeed this principle is the whole point of risk analysis in the first
place.
ECOSYSTEM TOXICOLOGY
In the light of the difficulties of the description of ecosystems due to their inherent
complexity, the tangled web of ecologically mediated effects such as competition,
predation and bioaccumulation, and of the variety of ways in which they may be considered
to be important or significant, their effective risk analysis depends on the choice of
"endpoints" (Lipton et al., 1993). These are the specific criteria which are to
be assessed for damage by the stressor in question, chosen to embody or to represent the
ecosystem features which are considered to be of value. A panel of experts surveyed by a
Delphi process was in agreement that good endpoints, which may be considered as hypotheses
to be tested, should have accurate measurability, utility, relevance, importance in the
ecosystem (however defined) and, ideally, a body of accompanying information such as
toxicological and ecological background knowledge and the possibility of controls such as
measurements on comparable but undisturbed sites. It also considered that endpoints are
rarely clearly enough defined and that, even when they are, the logistic arrangements for
their measurement, particularly in the long term, are underestimated and inadequate, such
as in the use of too small samples (Richey et al., 1985b).
There is a danger that endpoints be applied to the symptoms of ecological damage, rather
than to their fundamental causes, by damage to functions. Symptoms are by their nature
more easily detectable, and so attention may be focused on them. However, less visible
damage to functions, such as the oxidising capacity of the atmosphere, may be of critical
importance, particularly if it is not identified in time for remedial action to be taken.
Endpoints can be divided into the final criteria to be the objects of the assessment
("assessment endpoints") and their more readily measurable proxies which are
actually assessed ("measurement endpoints") (Suter, 1990). The assessment
endpoint is a "formal expression of the actual environmental value to be
protected". As qualities, they should have social and biological relevance,
unambiguous operational definition and susceptibility to the stressor being assessed.
Examples include recreational value, the size of an important population, biological
diversity, beauty, soil stability or the resistance of the system to outbreaks of pests or
fires. The selection of assessment endpoints is essentially subjective and political -
individuals of charismatic or endangered species may be considered more important than
entire populations of small and unexciting invertebrates. Species may be given relative
importance in different ways, such as a simple checklist, a ranking or weighted scores:
these may also be combined, for example to protect a few important species, and then
maximize the diversity of all the others.
Sometimes balanced decisions must be made, such as one recent evaluation which explicitly
gave greater importance to populations of (rarer) geese than those of (more abundant)
pigeons (Greig-Smith, 1992).
Measurement endpoints should be easily, quickly and cheaply measurable and clearly related
both to the operation of the stressor and to the assessment endpoints they are intended to
represent, preferably in a quantifiable way. Examples include estimates of population
density, counts of species or diversity indices, quantified descriptors of landscape
quality, assessments of soil loss in water runoff, and the frequency of pest or fire
outbreaks (Suter, 1990).
A. THE ASSESSMENT OF ECOSYSTEMS AS REPRESENTED BY INDIVIDUAL SPECIES
Clearly, not every species in an ecosystem can be evaluated for vulnerability. As a
result, certain particular species are chosen as measurement endpoints. One view of the
selection of these is that critically vulnerable species can serve as "sentinel
species", a substance found harmless to which can be presumed to be harmless to all
the others.
It has been argued that single-species tests of this sort can be reliable if the species
is carefully and skillfully chosen, but the risks of such a choice themselves make the use
of a suite of species more attractive - species vary in their sensitivities to different
toxins, so that one sensitive to one stressor class may be relatively resistant to another
(Cairns, 1989).
Test species can be chosen by several criteria, principally as being particularly
sensitive, important, whether to the structure or function of an ecosystem or,
economically or aesthetically, to humans, representative of a taxonomic or trophic group
or convenient, being suitable to be reared, housed and tested in adequate numbers. Most
test species are chosen for the last of these criteria, convenience, and efforts are being
made to enhance the reliability of extrapolation of data from a handful of convenient
species to those likelier to be selected as assessment endpoints. Progress is being made
in this field. For example, although most easily laboratory-rearable species such as
Daphnia magna tend to be rather insensitive to toxins, being fecund, robust, ubiquitous
and herbivorous (herbivores, tending to encounter natural poisons in their plant food,
tend to be more resilient to toxins than carnivores), not all are, and the use of
relatively sensitive test organisms, such as oyster larvae, may be expected to increase
(Gray, 1989). Also, evidence is emerging that the mechanisms of slow-acting chronic
toxicity, which is by its nature more time-consuming to assess than acute toxicity, are,
luckily, in general more widespread than those of acute, and thus that chronic toxicity
data may be more easily extrapolable (Barlow et al., 1992).
Attempts are also being made to introduce some meaningful harmonization of tested species,
either by loose classifications, such as "a typical 25g seed-eating bird"
(Greig-Smith, 1992), or by aggre-gation to form categories such as "the biomass of
bottom-feeding fish" (Richey et al., 1985).
In general, a pattern is emerging of a process of detailed, highly replicated and
expensive tests in research laboratories supporting the reliability and extrapolability of
cheaper and simpler tests carried out in testing laboratories. Integration of these two
activities may enable a coherent process to emerge - test laboratories using a few easily
rearable and well understood test organisms, and detailed research results being used to
draw inferences about extrapolation to assessment endpoints. For example, testing for
damage done by a stressor, when the test organism does not actually die, is in fact not
easy, no single technique being easily selectable. General tests for toxic damage do
exist, taking advantage of the fact that energy is needed to resist any stress, to measure
a stress by looking at cellular respiration rates and other basic processes such as
protein synthesis. Unfortunately, such elegant and versatile techniques are difficult and
expensive, and so not widely used in testing, but they may be used by research
laboratories for studies of extrapolation. Also the tools developed over decades for
extrapolation of toxicological data to humans are now generally well established and
internationally recognised, and may be used as models for similar extrapolations to other
species (Barlow et al., 1992).
This emphasis on extrapolation is ultimately inevitable, in the context of international
harmonization, to resolve the fundamental opposition of the needs of harmonization and
relevance. Ecosystems vary - a chemical in the environment in, say, Canada may well
encounter none of the same species in Indonesia - and so the likely responses of
indigenous species must be addressed in risk characterization if the process is to have
any relevance. If, therefore, some extrapolation is essential if assays are not to be
duplicated in virtually every country where a product may be launched, the test species
may as well be from a relatively small selection, as long as the toxicology of the species
is well understood and the assessments are controlled by ring tests, and detailed research
results may then be used to inform the extrapolation of these findings for specific
national ecosystems.
B. THE HOLISTIC ASSESSMENT OF ECOSYSTEMS
The interactive nature of ecosystems means that the testing of any selection of individual
species will not guarantee that ecologically mediated effects will be detected. Again, for
more holistic analyses of ecosystems, endpoints must be carefully chosen and formally
stated because, as outlined above, the value attached by society to an ecosystem may
depend on its diversity, functions or the presence of glamorous species.
Endpoints chosen may be aspects of ecosystem structure (which species are present and
their abundance), such as total diversity or the presence of rare or attractive species,
or ecosystem function (the processes which it carries out), such as carbon dioxide uptake.
The former are generally chosen, as the maintenance of the structure of an ecosystem will
usually maintain its functions, but not vice versa. In other ways endpoints may overlap
and coincide: many glamorous species, with high political, social and cultural values,
such as the tiger or the monkey-eating eagle (a national symbol of the Philippines), are
"top predators" at the summit of food chains, roving over large areas, and as a
result a viable population of individuals requires a huge area of habitat - so the
protection of such a species necessarily entails the protection of such areas of habitat,
with the corollary of simultaneously protecting its other plant and animal species.
Logically, the extension of toxicological risk analysis from individuals to ecosystems is
simply one more step up a chain of levels of organisation; from biochemical tests to tests
in vitro, and thence on to organs, to organisms and so to ecosystems (Barlow et al.,
1992). However, they add more than one incremental level of complexity, entailing the
addition of wildlife ecology and ecological toxicology to the scientific disciplines of
analytical and biochemical toxicology etcetera used for lower levels of organization
(Kendall & Akerman, 1992). Above all, there is the possible existence of "risk
cascades", in which human disturbances hoped to be incremental turn out to be
systematic, and ecological interactions magnify the effects of damage in reverberations
through the whole system (Lipton et al., 1993).
The most obvious tool which can be employed in the light of these difficulties is
experimental toxicological tests on multispecies systems.
Such systems are notoriously difficult to maintain in equilibrium even when undisturbed,
as in closed systems of any manageable size predators tend to eat all their prey and then
starve, but much good progress has been made in the design of these systems, by
unglamorous but valuable "bread and butter" research to evaluate how manageably
small systems may be stabilized: for example, ways have recently been described in which
woodlice and bacteria in a laboratory system together decompose leaf litter, an important
ecological process in deciduous forests (van Wensem, 1989), and in which predator and prey
fishes may be maintained together in smaller tanks than was previously thought possible,
if vegetation provides an environment of sufficient structural complexity to allow the
prey some refuge to prevent them from all being eaten (Harick et al., 1993). Toxicological
tests can be carried out in such systems, and some regulatory authorities do now demand
multispecies testing for the registration process of toxins.
Another possibility is presented by the fact that, unlike in human toxicology, limited
studies in the field can be carried out - single streams or ponds, whether artificial or
natural, for example, may be experimentally contaminated, or otherwise disturbed, and the
results assessed without risk of serious damage to the wider environment. Such experiments
are particularly important, because the data they provide can be used for the calibration
of laboratory test results, for the extrapolation of these results to estimate likely
effects in the field. At the moment, work is proceeding on the issues needed for this
extrapolation, including some very detailed and long-term studies, with some success,
though more field tests are needed for reliability (Emans et al., 1993).
This work is important to the goal of the USEPA and other authorities to moving towards
holistic whole-ecosystem evaluation, away from a "pollutant-by-pollutant and
medium-by-medium" approach (Bretthauer, 1992).
Ultimately, however, not all ecosystem risks can be quantified by tests prior to release.
Subtle effects on wildlife, such as behavioural changes, for example reductions in success
in courting a mate, caring for young or avoiding predators, may only slowly become
apparent. Three activities are important as a result - the continual monitoring of effects
after release, the development of computer models of ecosystems and the use of imaginative
"what if?" examinations, using expert judgement, to attempt to consider what
unforeseen complications may arise.
Post-release monitoring of ecosystems, like that of individual species, is useful not only
to look for failures in the specific release in question, but for general lessons for use
in future: for example, the survival of the species originally used for laboratory tests
may provide information about its usefulness as a test species, and the validity of
extrapolation processes can be assessed with the benefit of hindsight.
Ideally, a monitoring programme should be fully thought out in advance, as part of the
original risk assessment design, so that the information it provides is directly relevant
to the rest of the process. A comprehensive monitoring programme would include initial
surveys of species present and their toxicological status, including natural levels of
variation against which the effects of disturbance may be assessed, as well as subsequent
recording of all status changes, including those initially not apparently attributable to
human disturbance. At present, such procedures are not much internationally harmonized,
and they may benefit from a coordinated approach, for example by the extension of systems
such as Britain's River InVertebrate Prediction And Classification System (RIVPACS), a
checklist of species expected to be found in pristine rivers, ranked in order of
sensitivity to pollution, so that any particular water body can be awarded a value for
ecological health by which species are present (Barlow et al., 1992).
Mathematical and computer models of ecosystems, allowing the quantification of
relationships between species, are difficult to build and test, and have indeed been an
objective of ecological scientists for several decades. However, some progress is being
made, such as in energy budget models, which model the flows of energy as nutrients
through food chains, and which can be used to assess complex outcomes such as the impact
on the viability of a population of delays in its reproduction cycle, and with further
work their use should bring considerable benefits (Barlow et al., 1992).
For the time being, much reliance is placed on subjective expert consideration of likely
ecological effects. Here too there is scope for the formalization, and thereby
harmonization, of procedures. For example, an ecosystem may be considered as, in effect, a
huge three-dimensional table, the three axes being species, effects and assessment
purposes. Each cell of the table may be addressed in turn, consideration being given to
the appropriateness of the available information and the adequacy of the risk
characterization, thus giving systematic structure to the consideration of failings in the
holistic picture (in a manner rather reminiscent of the use of hazard identification
procedures such as GENHAZ).
Such procedures may also help the formalization of the documentation trail, and the
development of consistency in their use would benefit the clarity and cross-compatibility
of risk analyses (Greig-Smith, 1992).
NONTOXICOLOGICAL AND SYSTEMATIC STRESSES
The nature of nontoxicological and systematic stresses ensures that their risk analysis
must be more flexible and specific than those of toxins.
This is because they come in a wider array of types, requiring flexibility, and tend to be
site-specific, applicable to processes, not products, from activities such as timber
cutting and civil engineering projects such as water diversion, roads or airports. Whether
or not factors such as "percentage deforestation" can be treated as analogous to
toxic doses, as proposed by the USEPA (Norton et al., 1992) is still in some doubt, and
may well not be the case.
The setting of endpoints and the quantification of responses to disturbance, on the other
hand, are broadly analogous to those in toxicological assessments. For example,
disturbances to Alaskan Caribou by traffic around oil field developments have been
assessed by simple but illustrative "activity budgets" which evaluate changes in
the time animals spend on various activities, such as eating, in response to passing
vehicles (Murphy & Curatolo, 1987); and even an endpoint as elusive as landscape
beauty can be both quantified, by landscape descriptors, and rated for value (and
therefore the gravity of damage be assessed), by either hedonic or contingent valuation
techniques (Willis & Garrod, 1993).
Risks of systematic disturbance to ecosystems, being by nature imponderable, specific and
difficult to test in advance, rely particularly heavily on expert estimation of likely
impacts, and expert selection of the best approach to the analysis. As a result,
generalizations about the specific techniques which may be used is hard, and the issues
raised tend to be less technical than those discussed above, and more in terms of the
sociopolitical and institutional frameworks in which they are considered and discussed.
This can be seen from an example of the analysis of a systematic risk, the proposed
introduction of an exotic fish, the channel catfish, to New Zealand.
New Zealand, as an "ecological island" whose aboriginal wildlife has already
been ravaged by the injudicious introduction of exotic species in the past, is sensitive
to their risks. The proposed catfish introduction was not to the wild, but for fish
farming, and an initial Environmental Impact Assessment (EIA), including consideration of
the consequences of escapes to the wild, suggested the risks would be acceptable. Because
of public concern, however, two independent experts were mandated to assess all the
available existing information. Largely as a result of efforts by a pressure group opposed
to the introduction (themselves, as it happens, not defenders of New Zealand's precarious
aboriginal wildlife, but sport anglers concerned at possible impacts on their prey
populations of trout introduced decades earlier), new information came to light which had
not been considered before. This included documented cases of catfish escapes to the wild
from farms, and reports from fish ecologists, in areas where the catfish had been
introduced, of its rapid spread into a variety of habitats and of damage through predation
and competition to many indigenous species, including some similar in many respects to
endangered species in New Zealand. Reviewing the lessons to be learnt from their final,
accepted, recommendation that the introduction was unacceptably risky and should not be
carried out, the independent experts drew several conclusions. One was that an independent
review should be the last stage before release. Another, more important, was of the role
of publicity in uncovering the maximum possible amount of relevant information: as they
put it, "It is not enough to expect that the compiler of the EIA will have uncovered
all salient facts about the proposed species". In this case, much important
scientific information was obtained from areas where introductions had been studied, often
from obscure, local journals, and even as personal communications from scientists of
findings which had never been published. The publication of requests for information
relevant to an EIA, particularly through specialist organs such as professional
associations and journals, is a useful proposal to maximize the information obtained
(Townsend & Winterbourn, 1992).
CONCLUSIONS:
Paradigms for Ecological Risk Assessment
Attempts are being continued to establish a general paradigm for ecological risk
assessment: the paradigm for human environmental health, of the basic sequence of hazard
identification, dose:response estimation, exposure assessment and risk characterization,
has achieved a wide consensus, but is not strictly or directly applicable to ecosystem
risk analysis, with its multitudes of stressors, species, orders of organization and
interactions between them. One recent suggestion (Lipton et al., 1993) has been for the
following structure:
1). Receptor identification of species and functions of concern;
2). Hazard identification;
3). Endpoint identification, of the response of which receptors to which stressors are to
assessed;
4). Relationship assessment, for the consideration of ecologically mediated effects and
the possibility of risk cascades, the results of which may, if necessary, be fed back to
(2) as the identification of new hazards;
5). Exposure assessment;
6). Response assessment (renamed, in view of the imperfect quantifiability of many
ecological stresses, from "dose:response assessment");
7). Risk characterization and uncertainty analysis.
Paradigms such as this are still in development. A feature which they share, however, is
allowance for feedback of information in loops, so that earlier points of the process may
be returned to for reevaluation in the light of later findings, and mutual communication
between the evaluator and assessor to ensure the political relevance of the factors
assessed (Norton et al., 1992).
4. CONCLUSION
The field of environmental risk analysis is developing fast: changes are currently under
way, and more may be expected in the near future. Changes are driven by three main motors.
First is the growing demand for it, thanks to continual growth both of public awareness of
environmental issues, and of the organization and knowledgeability of environmentalist
public opinion, raising public expectations of the quality of environmental risk analyses
and demanding the publicization of risk analyses for informed public debate. Increasingly
the public is not prepared to leave the discussion of environmental risks to
"experts", but is coming to expect their debate in more open fora. The
production of skilled, experienced and articulate environmental specialists currently
seems to be lagging behind this demand.
Second is a growing search for ways to formalize and to rationalize environmental risk
analyses. In spite of the variability, uncertainty and value judgements encountered in
environmental analysis (or often, in fact, because of them), it is becoming felt that they
cannot be left to woolly and subjective techniques relying heavily on largely intuitive
expert judgement. The result is a search both for tools which can rationalize the
application of expert judgements, and for logical and formal structures and frameworks
within which risk analyses can be carried out.
Third is the desire, driven by attempts to promote international trade, whether on
regional (NAFTA; the European Community) or global (GATT) scales, to harmonize
environmental risk analysis procedures, in ways which retain the rights of sovereign
states to set their own environmental policies and priorities and yet do not needlessly
inhibit international commerce. Ideally, technical issues such as procedures, tests, the
types of data needed and the manner of their collection could be harmonized, by
international agreement, while leaving the level of acceptable risk to be set by sovereign
states.
These three developments have many qualities in common. Harmonization and
rationalization/formalization of procedures clearly go hand in hand, the former requiring
the latter, and in many instances will both reduce the workload of individual experts
(such as by the use of expert systems) and increase the transparency of the analysis
process.
Harmonization of environmental risk analysis procedures therefore brings four advantages.
First are the economies of scale from mutual recognition of processes and results,
removing the need to duplicate in each country tests already performed elsewhere. Second
are the benefits of the enhancement of trade. Third is the impetus it adds to the ongoing
process of the rationalization of procedures, the development, refinement and evaluation
of techniques, and a fruitful debate, in panels, workshops and publications, of what
environmental risk analysis is for and how it may be best fitted to our purposes. Fourth
is its contribution to the development of common databases and pools of information and
knowledge. At a basic, technical level many of these are well advanced, such as the EC
"black" and UK "red" lists of chemicals with data on their toxicity,
persistence and capacity for bioaccumulation. Higher level databases can also be
developed, but require flexibility in their construction, to allow for the inclusion of
estimates of the uncertainty of information, detailed background information such as the
genotypes, rearing conditions and diets of organisms tested, and comments and opinions by
the scientists involved.
At the technical level, much progress has been made over the last two decades, such as
laboratory ring tests and the OECD's recommendation of standard tests, good laboratory
practice guidelines and test protocols. The European and Mediterranean Plant Protection
Organization and Council of Europe scheme for the risk assessment of plant protection
products is another example (Barlow et al., 1992).
Another development is the arrival at consensus over the importance of information and its
communication, in five interconnecting ways.
First is the importance of the documentation of analyses, as full "documentation
trails", so that individual analyses can be case-specific but their components
assessed, per se and for possible use elsewhere. These should include the subjectively
estimated components, with rationales and justifications of why decisions were taken the
way they were - these decisions cannot be understood without some documentation of the
reasoning processes used, and of the background knowledge and awareness of the experts
participating, as the New Zealand catfish example shows.
Second are the implications of the widening understanding of the fallibility of the
distinction between "objective" risk assessment and "subjective" risk
evaluation, as understanding advances both of the deep-seated nature of public risk
perceptions and of the limits to the objectivity of expert scientists. The operational
conclusion of this is recommendations that the information flow in risk analysis should be
a two-way process of information feedback, both between the risk evaluator and the
scientific assessors (Norton et al., 1992) and between the public and the risk analysis
team (Pidgeon et al., 1992), so that the criteria of final subjective acceptability can be
recognised and incorporated throughout the analysis process from its beginning.
Third is recognition that for meaningful evaluation, the presentation of scientific
results of risk assessment should include estimates, and discussion of the possibility, of
uncertainty about values and estimates, so that each datum is presented with a
"pedigree" allowing the evaluator to assess the confidence held in it. The
results of uncertainty and sensitivity analyses can usefully also be included in this
context.
Fourth, the usefulness of post facto evaluation, validation and monitoring is widely
acknowledged. Its usefulness for the all-important development of the understanding of
mechanisms and for the calibration of extrapolation would be enhanced if it were more
widespread than at present, particularly if done in a standardized, harmonized way so that
a large body of knowledge from validation monitoring could be built up (Greig-Smith,
1992), and if its findings were accessible with the documentation trail of the original
analysis, so that lessons could be learnt from the consideration of the two together.
Fifth, the importance of political and institutional processes is a recurrent theme. Risk
analyses proceed better in institutional environments which allow the gathering and
communication of information to be maximized.
This principle extends to the discussion of risk in the public sphere, where the
trustworthiness of institutions, and their openness to the reception of public views and
effectiveness in communication are important, and increasing requirements are placed on
operators of risky facilities to inform the public of their natures.
On the other hand, several aspects of the rationalization and harmonization of
environmental risk analysis procedures are contentious.
There are principally three issues to be balanced against their benefits.
First is the question of differences in cost and technical sophistication between
techniques. The most expensive and sophisticated tools may not always be considered
cost-effective, or even be available to poorer countries, particularly if they rely on
patented processes held elsewhere. As assessment technology develops particularly quickly,
some geographical and other areas will inevitably move faster than others in the adoption
of new techniques.
Second is the importance of flexibility in analysis procedures to allow the precise
tailoring of an analysis to its circumstances. This is particularly true of the
geographically specific field of Environmental Impact Analysis, which applies chiefly to
process rather than product standards, but these too are increasingly under discussion in
the trade and the environment debate. Product risk analyses also need tailoring to
specific cases, as ecosystems and their vulnerability vary throughout the world, and so
does the capacity of environmental processes to degrade, immobilize or disperse
contaminants.
Third is the inevitable issue of differences in the values which societies attach to
environmental risks - how they rank the environment, development, employment, mobility and
other economic and social goals. The frailty of the distinction between risk assessment
and evaluation means that it is not easy to distinguish, as free trade interests would
hope, that risk assessment can be internationally harmonized on the sole criterion of
"sound science" and evaluation left to sovereign states (Morris, 1993).
The ways in which these three criteria conflict and interact with the aims of
harmonization are manifold. They may be considered further by a look at the areas in which
the objectives come into conflict (Greig-Smith, 1992).
1) The choice of a test protocol, whether to use extrapolation, modelling, a standard test
or a test chosen for its appropriateness. Here a standard protocol will enhance
compatibility and the evolution of a usefully comprehensive knowledge base. On the other
hand, flexibility of choice allows for selection to suit particular conditions, the use of
information from a wider variety of sources and the rapid adoption of newer techniques as
they become available. In particular, the relative advantages of these four approaches may
not remain the same: models are inherently holistic, and do not rely on a large supporting
base of information, but may not yet be empirically validated, and so their usefulness may
grow. A possible compromise may be to advocate the use of standard procedures but to
permit deviation from them when good reasons can be stated and justified.
2) When a test protocol is chosen, how tightly it may be standardized. This is shown by
the question of whether in bioassays to use clones of test organisms such as Daphnia
magna, or to use a more diverse spread of genotypes by, for example, taking them from the
wild. The use of standard, identified clones is the only way to ensure compatibility of
results. On the other hand, clone populations may poorly predict the responses of wild
populations - lacking genetic diversity, they may be peculiarly susceptible to certain
stressors (for example, by lacking a resistance mechanism which is in fact widespread in
the wild), and they may simply not be representative of wild populations, particularly on
an international scale.
The only solution to this problem is to search for reliable extrapolation techniques so
that clones may be used for tests internationally, and the results of detailed research
used for extrapolation from the internationally standardized findings to the likely
situation in any particular national case.
3) Whether to take a balanced view of risk-taking, or a safety-first "presumption of
hazard" approach, with the burden of proof resting on those who would benefit from
the taking of the risk. This decision is not the sole concern of risk evaluation, but
permeates risk analysis, as the choice made will affect issues such as experimental design
and sample sizes.
Presumption of hazard is cautious and reassuring, but may be overcautious, and has
scientific difficulties in the impossibility of proof of "no effect". It may be
possible to combine these approaches to some extent by, for example, varying the value of
delta in tests of "environmental significance".
4) Whether or not to use "trigger" values in testing, to simplify the decision
to advance the procedure to the next step. Trigger values enhance harmonization and reduce
the need for unnecessary testing, but are less flexible and realistic than variable
levels.
5) The flexibility of safety factors. Rigid factors enhance confidence, objectivity and
harmonization, but flexible ones reduce the risks of overcaution and of loss of
information, and can be modified in consideration of, for example, the importance of the
species in question or the uncertainty of the information.
6) The use of expert opinion. To use expert opinion maximizes flexibility and the use of
information, but ultimately cannot be fully consistent as opinions are bound to differ in
some ways.
7) Whether to summarize risks by categorization as "high", "medium" or
"low", or to attempt to present precise values. Scoring systems, which are
growing in use (Calow, 1994), may be seen as intermediate between the two.
Categorization allows for some basic harmonization and recognizes the uncertain nature of
risk information - gross classes may best reflect uncertainty. Yet it may underuse
information, and the category definitions themselves are subjective and imprecise.
Procedures can be used, however, to allocate results to categorization classes and then to
extend research when, and only when, findings are felt to be near the boundary between two
classes, so adding precision only when necessary.
8) Whether to use similar categorization for levels of uncertainty in estimates, with
similar arguments for and against.
9) Whether to base risk analysis and management essentially on hazard characterization, by
recommendations intended to ensure that Predicted No Effect Concentrations are not
exceeded, or whether to attempt full risk assessment by the consideration of Predicted
Environmental Concentrations as well. In fact, for international harmonization purposes,
this need not be important, as PNECs may be expected to be more widely applicable than
PECs, the latter varying more widely between countries with differences in levels of
industrialization, agricultural practices and so on, and so it may be possible to proceed
towards harmonization of PNEC procedures and data, while leaving PEC assessment to
national authorities.
10) Whether to regard environmental risks as absolutely to be avoided, or explicitly to
balance them against the benefits of taking risks, by a comparison such as Risk:Benefit
Analysis. Again, it may be possible to standardize estimations of risk, while leaving the
questions of whether to balance them against benefits and, if so, what benefit level may
justify risks, to sovereign states.
It can be seen from this list that precise and universal regulation of the issues
surrounding harmonization may not be possible, but also that integration of more than one
approach can sometimes be done.
Broadly speaking, it may be possible to harmonize the entire structure of environmental
risk analysis in two ways. The first would be to maintain or clarify the distinction
between objective assessment and subjective evaluation, on the assumption that the
scientific groundings of assessments may be universally recognised, and the evaluative
phase added on as a superstructure by sovereign states. Despite differences in basic
evaluations of the significance of risk assessment, this may be possible, at least between
countries with similar environmental priorities (such as those within the European
Community). The second would be to leave all subjective and evaluative components in risk
analysis open to modification, by full documentation of the decision processes at every
point of an analysis. Many practitioners in the field argue that this is desirable anyway,
for the establishment of a knowledge base and the transparency of the process to risk
evaluators and to the public. These two outlines are not mutually incompatible and may be
pursued together.
Below the grand structural framework of analyses there is an enormous amount which can be
and is being done in the formalization and harmonization of tests, decision-making
procedures and the use and documentation of expert judgement. These developments are not
only driven by international issues, nor do they contribute solely to them, but also
derive intrinsically from the progress of environmental risk analysis itself as it matures
into a coherent field of scientific endeavour.
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RRojas Research Unit/1997
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