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Reducing the impact of industrial disaster surprises: The range of choice
While we await the development of tools to manage surprises, it is both possible and necessary to improve the existing means of responding to them. Four broad sets of choices are available at present: (1) do nothing; (2) undertake research; (3) engage in mitigation; and (4) encourage adaptation. Which choice (or choices) offer(s) the best prospects for improvement?
Doing nothing is ruled out because of the stakes that are involved. If the scale of human intervention in natural systems is growing, and industrial hazards are an active ingredient of this process, it would be risky to ignore new types of industrial hazard - even if immediate losses are not heavy (e.g. Seveso). This is certainly one lesson of recent experience with ozone depletion, forest death, and greenhouse gases. However, doing nothing has often been a preferred alternative for governments that are accustomed to short-term decision-making.
Scientific and technical research to develop a better basis for action is clearly a second possible alternative. Given the novelty of industrial surprises, it is important to find out more about them so that adequate responses can be formulated. But the lack of similar cases poses difficulties in generalizing from a single experience or a small number of related experiences. Research findings are likely to emerge slowly and haltingly. This calls to mind an example from Japan. Most of what is known about the medical effects of atomic weapons explosions comes from the tragic experience of Hiroshima and Nagasaki (Harwell and Hutchinson 1985). But we are still debating the interpretation of these data almost 50 years after the events. A recent dispute concerns discrepancies between calculations of radiation emitted from the bombs and radiation doses received at ground level (Marshall 1992). Previous findings may have overstated or understated the hazard, though this has not prevented the data from playing a role as evidence in debates about nuclear policy. I am not saying here that it is impossible to make policy decisions about hazards without copious and reliable data on their observed effects. Obviously, one can conclude that nuclear weapons pose unacceptable risks or hazards, on the basis of other information. For example, scenario-building and simulation are alternative approaches. The point is that scientific research on surprises is usually slow and difficult and it does not necessarily produce results that can be replicated in the future.
Mitigation refers to actions that are designed to prevent, avoid, or reduce a hazard. Clearly, it is in the long-term interests of society to develop mitigation measures because they offer the best hope of permanent solutions to hazards of all kinds. For example, two types of mitigation have been proposed to combat the anticipated hazard of global warming, which is connected with the rapid industrialization of the Earth. The first focuses on reducing the emission of greenhouse gases that are believed to be the driving forces of warming. This would probably entail major restrictions on the burning of fossil fuels. The second type of mitigation turns the issue around and focuses not on reducing greenhouse gas emissions but on increasing the capacity of environments to absorb these gases. This involves reducing deforestation and encouraging reforestation as well as somewhat visionary technological fixes such as seeding the oceans with carbon-absorbing chemicals. Both types of mitigation are controversial, in part because there is no consensus that human-induced global warming is indeed taking place. Although growing concentrations of carbon in the atmosphere have been confirmed and constitute a clear case of surprise, there are still major gaps in knowledge that might confirm that actual warming is under way. So the policy arrangements are being developed on the basis of what are admittedly incomplete scientific data. It is expected to be many years, perhaps decades, before the scientific basis of global warming can be confirmed. By then, it may be too late to do anything but live with the consequences. What this example suggests is that it is very difficult to mitigate surprises - in part because it is difficult to analyse the surprises and in part because it may be necessary to adopt presumed countermeasures that have high costs and uncertain efficacy.
This brings us to the final major strategy - adaptation. Here the intent is not so much to prevent a surprise occurring but to make sure that society is able to cope with the resulting impacts. Attention is mainly focused on improving management of the emergency and subsequent recovery. Of the four possible sets of alternative adjustments to surprise, adaptation is perhaps the most promising. I will focus on one aspect of adaptation - improving the process of recovery. It should be possible to improve recovery from events such as Bhopal and Exxon Valdez, because many of the problems and issues of recovery are not specific to a particular hazard, they are generic across most or all hazards. For example, victims must be tended to and provided with assistance that will allow them to continue their lives, whether the distress is caused by toxic waste, or nuclear radiation, or any other hazard. Damaged or destroyed buildings must be rebuilt or replaced, whether the agent of destruction is a flood or a bomb. Degraded natural resources must be restored, whether contaminated by an oil spill or leached by acid precipitation. It is not necessary to wait for detailed scientific analysis of surprises before beginning recovery.
Fig. 1.4 The disaster cycle
Recovering from surprise
What is known about disaster recovery comes mainly from studies of natural disasters (Anderson and Woodrow 1989; Bolin 1982; Bolin and Bolton 1986; Drabek 1986; Friesma et al. 1979; Geipel 1991; Hall and Landreth 1975; LaPlante 1988; May 1985, 1988; Perry and Mushkatel 1984; Rubin et al. 1985). These suggest that disasters are discrete phenomena with more or less well-marked beginnings and ends. They are also sequential phenomena, with each one helping to shape the one that follows (Haas, Kates, and Bowden 1977). In the wake of a disaster, communities are believed to pass through successively longer overlapping stages that are characterized by different problems, issues, and responses. These are commonly given labels like "emergency," "rehabilitation," "reconstruction," "revival," and "symbolic recovery" (fig. 1.4). As recovery progresses, attention turns from efforts to recoup past losses to planning for the future, including preparing for the next disaster. The characteristics of each period have been summarized by LaPlante:
The first period, the emergency phase, is typically a period of high consensus in the community, with much altruistic behavior aimed at preventing or reducing human suffering. Next, activities that will return the community to normal functioning are undertaken and initiate the second period, called the restoration phase. When a semblance of normal functioning is achieved, activities aimed at permanence begin the reconstruction phase: families return to home, work or school and community rebuilding gets under way. Family and individual needs may come into conflict with community goals at this stage of recovery... a final stage... reflects activity at essentially the community level, called the commemorative, betterment, and development reconstruction phase. During this time of second-stage community reconstruction, plans and actions decided upon during the earlier reconstruction are implemented. (LaPlante 1988, 220)
The entire cycle may take many years to reach completion, depending on such factors as the magnitude of the initial disaster, the amount of resources that are available to provide assistance, and whether the affected community is urban or rural. Though the speed and timing of recovery vary in different settings, the process is held to be essentially similar everywhere.
This stage model of disaster is widely employed by researchers. However, it is not universally accepted. For example, students of rural third world disasters have suggested that the pace of recovery is often strongly distorted by the demand for agricultural labour. In farming villages, recovery may occur in spurts during times when the community is not occupied with planting crops or harvesting them. Thus, recovery may take place in several cycles of activity of varying intensity separated by periods when little recovery occurs (Cuny 1983). Other analysts have criticized the stage model for focusing too much on aggregate conditions and economic factors and overlooking the more varied suite of problems that affects individuals and families. Recovery at the family level is believed to be a fourfold process that involves - in addition to economic recovery - emotional recovery, housing recovery, and quality of life recovery (Bolin 1982). A community might appear to be recovering from disaster but it could contain many families that are not recovering and may never do so. Thus, it is argued that the general stage model glosses over the multidimensionality of recovery and its internal contradictions.
Relatively little is known about the process of recovery from industrial disasters, particularly surprises, but the available information is not comforting. As pointed out earlier, some communities that are affected by industrial disasters simply cease to exist. That is what happened at Times Beach and it may also be the fate of communities near Chernobyl. Such a dire outcome is almost unheard of among communities stricken by natural disasters. The post-World War II increase in global interconnectedness has made it possible for people everywhere to be aware of storm- and earthquakeravaged communities and to facilitate the transfer of sustaining aid to them. Whereas Drabek could well say that (natural) disasters caused "... relatively minor ripples in the long term developmental cycle" (Drabek 1986, 251), industrial disasters can bring fundamental changes to impacted communities.
Industrial surprises are often protracted; some are, perhaps, interminable. It is questionable that one can speak of recovery from disaster when the process is not complete within the life-span of victims. In Minamata, recovery has taken at least four decades and is still incomplete. Awareness of toxic chemical wastes is a relatively recent phenomenon in most countries, but already there are communities that can look back on more than twenty years of experience, concern, and action. The entire planet may face the prospect of significant climate changes, whose effects will stretch from now well into the twenty-first century - and perhaps beyond. How long will recovery take for populations affected by such changes?
Recovery from industrial disasters is usually conflict laden. Probably the most enduring conflict revolves around the attribution of responsibility and blame. Although human agency can play a role in natural disasters, people are not generally held accountable for the occurrence of extreme natural events. It is easier for communities that are affected by natural disasters to unite around themes of common loss, common interests, and common action in support of community-wide goals for recovery. This does not necessarily mean that postdisaster conflicts are thereby avoided, but they are less likely to occur than in the accusatory atmosphere that surrounds many industrial disasters. Conflicts also tend to create winners and losers, with the potential for acrimony, recrimination, and resentment. Groups that seek to help can become embroiled in unrewarding actions. Speaking of one experience, Brown and Mikkelsen note:
It is important to remember that community efforts... are difficult, painful, and lengthy. We have looked at efforts taking five or ten years or even longer, sapping energy, bringing loss and the pain of publicity, creating tensions in families and communities, and standing a good chance of failure. (Brown and Mikkelsen 1990,198-199)
Not only are industrial surprises like Chernobyl likely to have very longlived effects that effectively postpone and extend recovery into succeeding generations but also there is considerable doubt that recovery will take the form of a return to a stable pre-disaster state. Based on a review of several case-studies, Edelstein concluded that "... recovery to a 'post-disaster equilibrium' is difficult if not impossible" (Edelstein 1988, 9). Others have come to similar conclusions. In other words, it may be impossible to return to "normal" after a surprise. This suggests that the range of recovery strategies may include other choices. For example, instead of attempting to resurrect the status quo ante, "surprised" communities might either chose to (1) make recovery a process for realizing an entirely new and different future in situ, or (2) accept that recovery in any form is not possible at the existing site and make plans for relocation elsewhere.
What is known about recovery from industrial disaster surprises suggests that the process is disjointed, conflict ridden, long lasting and highly uncertain. Such characteristics are difficult to reconcile with the image of disaster recovery that is projected by existing research models and the professional literature. These sources tend to assume that recovery involves continuity of effort, a minimum level of agreement about community goals, and the attainment of identifiable short-term objectives on the way to a definite endpoint when recovery is completed - usually within the lifetimes of victims. The gap between the hopeful expectations of this model and reality is wide. Too often, the length of time that is required to engage in and to complete recovery from industrial disasters has been underestimated. Too often, these disasters have been viewed as temporary perturbations, whose effects will cease sooner or later, thereby permitting affected communities to return to "normal". Too often, the predominant response has been to address disasters as separate and discrete events, and to ignore the broader contexts that facilitate disaster by promoting far-reaching changes in technology, environments, and society. In short, responses to industrial disasters are often flawed by inaccurate perceptions of the recovery process.
Society needs industrial technology; we will not be well served by rejecting it in fruitless pursuit of Arcadian or Utopian myths about a riskless society. However, if recovery from industrial disaster surprises is to be improved, it will be necessary to acquire a more sophisticated understanding of how the process actually takes place in specific communities. By chronicling the process of recovery in a wide range of disasters, the chapters in this volume aid in achieving that objective. As a fund of experience is accumulated from a large number of communities, we will be in a better position to identify the responses that have proved to be most effective and to replicate them. Improving recovery from events like Minamata and Bhopal is an essential and feasible step in building the global capacity to manage surprises. Beyond lies the considerably more difficult task of mitigating surprises.
1. For up-to-date information on industrial risk issues, the following periodicals provide useful starting points: Industrial and Environmental Crisis Quarterly, Industry and Environment, Risk Analysis, and Risk: Health, Safety and Environment. There is also a vast journal literature on the more general subject of industrial safety.
2. Many problems of statistical inference about uncertainty and extreme events seriously hamper risk analysis. See, for example, Hacking (1986) and Haimes, Barry, and Lambert (1994).
3. The term "hazard" is preferred over "risk" because it connotes an interactive system of risks and responses that affects industrial systems not just single types of incident risks. This system includes various feedback relationships among different types and levels of risks, exposed populations, vulnerable groups, and deliberate or inadvertent responses, the whole being set within different socio-temporal and spatial contexts.
4. Throughout this volume, prices expressed in dollars are US dollars, and the term "billion" means a thousand million (109).
5. The interpretation of workplace fatalities is complicated by different definitions of "major industrial disasters." For example, in 1992 approximately 15,000 workers were killed in job-related industrial accidents in China - an increase of 3% over 1991 (International Labor Review 1993). Most of these deaths probably occurred singly and in small facilities, therefore failing to merit the label "major disasters." Such a pattern clearly exists in the United States. A recent analysis of 500,000 federal and state safety-inspection records, carried out by the Occupational Health and Safety Administration, lists 4,464 on-the-job deaths in US companies between 1988 and 1992 (Wall Street Journal, 3 February 1994). The vast majority of these deaths (4,337) occurred in workplaces with fewer than 20 employees.
6. It should be noted that problems resulting from two of these events (Seveso and Times Beach) were downgraded in revised assessments made by scientists several years after public concern was first raised. This in no way minimizes the extent to which each event constituted a disaster for the human populations that were affected when the events first came to light.
7. The first person to be killed in a railroad accident in the United States was the fireman on the country's first passenger locomotive, the boiler of which exploded in 1831. In 1865 a boiler explosion and fire on board the Sultana, a Mississippi sternwheeler, killed more than 1,500 people - the largest loss of life in any American marine disaster.
8. Most natural hazards can be classified as routine. The International Decade for Natural Disaster Reduction (1990-2000), a UN-sponsored programme of collaborative actions among participating nations, assumes that a thoroughgoing commitment to applying existing unused knowledge about natural disasters would be sufficient to bring about major reductions in losses.
9. As defined by Resources for the Future, industrial accidents included explosions, fires, and toxic vapours associated with industrial materials or facilities but excluded mining accidents and passenger transportation accidents; see Glickman, Golding, and Silverman (1992).
10. Forest death (Waldsterben) is the name given to a collection of symptoms of die-back and die-off among trees in Germany that are believed to be linked to increased air pollution among other factors; see "Multiple pollutants and forest decline," in World Resources 1986 (World Resources Institute 1986).
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