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Risk Assessment

Quantitative risk assessment of the effects of ozone depletion is a data intensive process which until recently has only been done for a few effects, most notably those affecting human health for which there are adequate data, i.e., cataract and skin cancer. With the exception of the 1989 USEPA risk assessment (1987) and regulatory impact assessment (RIA) (USEPA, 1988), the impact of increases in ambient UV-B on these diseases has previously been quantified principally by comparing two stationary situations: one with an ozone concentration constantly at a normal level and the other constantly at a lower level (UNEP report 1994, Longstreth et al., 1995, Madronich and De Gruijl, 1993). The corresponding disease incidences were estimated in two steps from the constant level of increased ambient UV radiation to the increased incidences: the first step is represented by the radiation amplification factor, RAF= (percentage increase in carcinogenic UV) per (percent decrease in ozone)(see chapter 1), and the second step by the biological amplification factor, BAF= (percentage increase in incidence) per percent increase in carcinogenic UV radiation (De Gruijl and van der Leun, 1994). The overall increase in incidence per percent ozone depletion is then represented by the amplification factor, AF= RAFxBAF.

    The future projections of ozone depleting substances in the atmosphere made in recent years have invited scenario studies on future ozone density and corresponding levels of ambient UVR. These in turn are now being translated into assessments of the risks to the biosphere in order to assess the importance of such atmospheric changes. It cannot be over-emphasized (see Chapter 1), however, that these scenario studies should not be taken as genuine forecasts. They are, at best, idealized computations on the effects of the changes in a small subset of factors leaving all other relevant modifying factors undisturbed. In the real world many of the other relevant factors may change and diminish or aggravate the effects (e.g. increased or decreased cloudiness). Nevertheless, these scenario studies serve the purpose of quantifying and comparing the potential effects of certain policies.

    As indicated above it is not currently possible to develop quantitative risk assessments for all of the health effects expected from ozone depletion. Presented below, therefore, is a mixture of quantitative and qualitative information that assesses to the extent possible, the likely impacts of ozone depletion on human health.


In the Chapter 2 of the 1989 UNEP Environmental Effects Panel Report (van der Leun et al. 1989), a static estimate was developed of the cataract risk of ozone depletion. In that effort it was estimated that the world’s population, if subjected to a sustained 1% decrease in the ozone layer, would develop between 100,000 to 150,000 additional cases annually. More recently, the USEPA has updated the work developed for their earlier RIA (USEPA 1988), using a quantitative model that incorporates the ozone depletion scenarios developed by the Scientific Assessment Panel (UNEP 1998). Presented in Fig. 2.6 are the results of that effort (R. Rubenstein, personal communication). Although these estimates were developed on the basis of U S data, they should be applicable to similar populations, i.e., those that are adequately nourished, worldwide. As discussed above, under-nourished populations may be a greater risk.


Exposure to sunlight may lead to a reddened and painful skin. This 'sunburn' is mainly caused by the UV-B radiation in sunlight. Exposures to more UV-B give more severe sunburns. An increase of sunburns by ozone depletion would be more than a nuisance; sunburn is also considered to be a risk factor for more serious effects, such as melanoma.

    Analysis of available knowledge leads to the conclusion that sunburns will not appreciably increase under a decreasing ozone layer; this is due to a powerful adaptation of the skin (van der Leun and de Gruijl, 1993). A gradual thinning of the ozone layer would, for instance, lead to 20 percent more UV-B in 10 years' time. The skin is equipped with an adaptation that can even cope with the changes in UV-B with the seasons. These are much more drastic; in mid-latitudes, the UV-B irradiance in summer is typically 10 times larger than in winter.

Fig. 2.6 Cataract risk estimates based on various scenarios.

Experience with phototherapy of skin diseases shows that one UV-B exposure, sufficient to cause a slight reddening, decreases the sensitivity of the skin by about 20 percent. In a series of exposures, this can be repeated many times. That is how the skin adapts to the UV-B changes with the seasons. A calculation shows that adaptation from winter to summer irradiance requires 13 such steps of 20 percent each. This will not change much under a UV-B irradiance increased by 20 percent due to ozone depletion. It will in fact become a bit easier, as the winter irradiance increases more than that in summer, so that the difference becomes a bit smaller.

    It is certainly possible to think of situations where adaptation cannot work in this way. For instance, if a totally unadapted skin is suddenly exposed to full sunlight, more UV-B in the sunlight will increase the likelihood of sunburn. Persons going on an expedition to the Antarctic ozone hole have reported experiences in this line. But such conditions are quite exceptional. By far the most sunburns arise from lack of care in going through the adaptation process. Such sunburns will not increase.

Skin Cancer

Using the process described above, the amplification factors for SCC and BCC have been determined to be 3, and 1.7, respectively. As discussed above in the section on BCC, the AF for SCC has a greater degree of certainty than that for BCC. Melanoma, because of uncertainties in its action spectrum could have an RAF equivalent to that of the carcinomas (1.2) or be closer to 0.1 (if the process is mainly UV-A-driven). A third possibility is that the development of melanoma can involve at least two different UV-driven processes, each with a substantially different wavelength dependence: e.g. UVA-driven initiation of transformed cells and UVB-driven immune suppressive episodes that promote the development of the tumor, or vice versa. Thus any quantitative model for the UV induction of melanoma will have significantly more uncertainty than that for SCC and probably more than that for BCC as well.

    Recent risk assessment efforts with a quantitative model that incorporate ozone depletion scenarios from the Scientific Assessment Panel, provides estimates of the additional cancer risks in populations annually based on the estimated changes in UV-B over time (Slaper et al. 1996; Arnold et al. 1998). It should be noted, however, that such efforts are not just a matter of including information on the changing concentration of ozone (and UV-B) with time. There are also a number of issues that need to be addressed with regard to the assumptions chosen for the dose-response models used to approximate the relationship between exposure and effect. The process of disease development has to be dissected in phases (steps) that are either UV-driven or not, and it should be known at which stage in the development (early or late, or both) UV is important. From experimental data and epidemiology, it can be inferred that chronic accumulation of UV exposures is important throughout the development of SCC. In contrast, for BCC and CM, acute intense exposures, particularly those acquired in childhood, may be the critical dose metric, although as discussed above, this may be true in the case of CM only if adulthood exposures are also substantial (Autier and Doré, 1998).

    Several groups are developing risk estimates using such scenario-based approaches; unpublished data from two of them developed for this assessment are presented here. Given below in Fig. 2.7 is a summary graphic from the Dutch group (Slaper et al., 1996) Calculations for skin cancer risks are performed for five scenarios applying the UV-chain methodology developed by Slaper et al. 1996, and assuming full worldwide compliance with the agreed protocols within the Vienna Convention.

Fig. 2.7 All cancer risk estimates based on various scenarios

The calculations are based on the production and depletion scenarios used in the WMO/UNEP scientific assessment of ozone depletion (WMO, 1998). Skin cancer risks are calculated for the zonal average ozone depletion observed at 45 degrees N (as reported in the 1998 ozone assessment), assuming a population with the sensitivity and age distribution as in the USA (risk in 1980 estimated at 2000 skin cancer cases per million per year). Excess cases refer to additional cases due to ozone depletion. The majority of the excess cases are nonmelanoma, and the lethality is approximately 2% of the incidence. The risks are probably conservative estimates, because:

It should also be noted that certain risk-groups (outdoor workers with a fair complexion) probably have much higher excess risks for the non-melanoma skin cancers, and also that in certain areas depletion can be larger than the zonal average used in this evaluation.


Although it is now adequately documented that UV radiation can modulate immune reactions in rodents as well as in humans, the impact of current levels of ambient solar UV radiation on infections in human populations is still unknown. Currently available epidemiological are unsuited to ascertain and quantify any such effect (De Gruijl, 1997), and given the fact that scientists have been aware of this lack of data for decades, a well-designed epidemiological study that addresses this issue is long overdue. Consequently, we are still completely ignorant when it comes to quantifying possible effects on infections of ozone depletion.

    In developing animal models for the effects of UV radiation on infections, investigators have been measuring changes in fundamental immune reactions that are associated with the course of the infection and that may also be measured in humans. Thus, the aim is to predict UV-induced effects on human resistance to infection by measuring the relevant changes in basic immune responses after UV exposure (Goettsch et al.,1998), a so-called 'parallelogram' approach. This approach is in its infancy and requires a thorough and detailed knowledge of the immunological responses that play a role in any particular infection under consideration, in order to identify the relevant measurements. This approach also has certain limitations in that the outcome of such analysis only evaluates host resistance and does not provide complete information on the spread and course of an infection in a population.

    The first conjectural calculations demonstrate that physiologically relevant exposures to solar UV radiation (e.g. 90 minutes around noon in July at 40o N) may significant hamper cellular immunity against a bacterial infection (Listeria monocytogenes) in the 5 % most sensitive individuals in a population of white Caucasians. This result is in reasonable agreement with direct measurements of the UV-induced suppression immune reactions against simple chemicals (Yosikawa et al., 1990; Cooper et al., 1992), where UVB exposures of the same order of magnitude as those calculated were found to affect a high percentage of people. In spite of these promising developments in indirect methods for assessing UV-related risks of infection, a more direct quantitative assessment of UV-induced enhanced infection remains desirable. A reliable assessment of the magnitude and breadth of effects of current ambient UV levels on infections and on success rates of vaccinations appears to be a long way off, and an expansion to include the effects of an ozone depletion delves even deeper into realm of human ignorance.

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