Abstract
In industrial hygiene, the statistical evaluation of the exposure of a worker to a chemical agent or to noise in an industrial site during a shift is needed. The data consists typically of time series, but occasionally spatial location can also be relevant. It appears that the autocorrelation, as characterized by the variogram, is usually well structured at least within an hourly scale. For exploring and modeling the data, estimating means with corresponding confidence intervals, simulating and planning sampling, geostatistics provides tools to characterize the interplay of support (integration time), autocorrelation (time dependence), stratification (qualitative changes of working activity) and distributional transformations within a unified framework.
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Wackernagel, H., Lajaunie, C., Thiery, L., Vincent, R., Grzebyk, M. (1997). Applying Geostatistics to Exposure Monitoring Data in Industrial Hygiene. In: Soares, A., Gómez-Hernandez, J., Froidevaux, R. (eds) geoENV I — Geostatistics for Environmental Applications. Quantitative Geology and Geostatistics, vol 9. Springer, Dordrecht. https://doi.org/10.1007/978-94-017-1675-8_38
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DOI: https://doi.org/10.1007/978-94-017-1675-8_38
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