Modelling short-term ultraviolet exposure as an alternative to individual dosimetry

TitleModelling short-term ultraviolet exposure as an alternative to individual dosimetry
Publication TypeConference Paper
Year of Publication2008
AuthorsVernez, D, Milon, A, Moccozet, L, Bulliard, J-L, Droz, P-O
Conference NameISEE 20th Annual Conference, Pasadena, California, October 12-16, 2008
ISBN Number1044-3983
Accession Numberserval:BIB_4E7920D64623
KeywordsComputer Simulation, Models, Occupational Exposure, Posture, Sunlight, Theoretical, Ultraviolet Rays
Abstract

Background:
Excessive exposure to solar Ultra-Violet (UV) light is the main cause of most skin cancers in humans. Factors such as the increase of solar irradiation at ground level (anthropic pollution), the rise in standard of living (vacation in sunny areas), and (mostly) the development of outdoor activities have contributed to increase exposure. Thus, unsurprisingly, incidence of skin cancers has increased over the last decades more than that of any other cancer. Melanoma is the most lethal cutaneous cancer, while cutaneous carcinomas are the most common cancer type worldwide. UV exposure depends on environmental as well as individual factors related to activity. The influence of individual factors on exposure among building workers was investigated in a previous study. Posture and orientation were found to account for at least 38% of the total variance of relative individual exposure. A high variance of short-term exposure was observed between different body locations, indicating the occurrence of intense, subacute exposures. It was also found that effective short-term exposure ranged between 0 and 200% of ambient irradiation, suggesting that ambient irradiation is a poor predictor of effective exposure. Various dosimetric techniques enable to assess individual effective exposure, but dosimetric measurements remain tedious and tend to be situation-specific. As a matter of facts, individual factors (exposure time, body posture and orientation in the sun) often limit the extrapolation of exposure results to similar activities conducted in other conditions.
Objective:
The research presented in this paper aims at developing and validating a predictive tool of effective individual exposure to solar UV.
Methods:
Existing computer graphic techniques (3D rendering) were adapted to reflect solar exposure conditions and calculate short-term anatomical doses. A numerical model, represented as a 3D triangular mesh, is used to represent the exposed body. The amount of solar energy received by each "triangle is calculated, taking into account irradiation intensity, incidence angle and possible shadowing from other body parts. The model take into account the three components of the solar irradiation (direct, diffuse and albedo) as well as the orientation and posture of the body. Field measurements were carried out using a forensic mannequin at the Payerne MeteoSwiss station. Short-term dosimetric measurements were performed in 7 anatomical locations for 5 body postures. Field results were compared to the model prediction obtained from the numerical model.
Results:
The best match between prediction and measurements was obtained for upper body parts such as shoulders (Ratio Modelled/Measured; Mean = 1.21, SD = 0.34) and neck (Mean = 0.81, SD = 0.32). Small curved body parts such as forehead (Mean = 6.48, SD = 9.61) exhibited a lower matching. The prediction is less accurate for complex postures such as kneeling (Mean = 4.13, SD = 8.38) compared to standing up (Mean = 0.85, SD = 0.48). The values obtained from the dosimeters and the ones computed from the model are globally consistent.
Conclusion:
Although further development and validation are required, these results suggest that effective exposure could be predicted for a given activity (work or leisure) in various ambient irradiation conditions. Using a generic modelling approach is of high interest in terms of implementation costs as well as predictive and retrospective capabilities.

Notes

oai:serval.unil.ch:BIB_4E7920D64623

DOI10.1097/01.ede.0000340055.39065.ae
Citation Key / SERVAL ID4954

                         

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