Several techniques for the detection of discontinuities in temperature series are evaluated. Eight homogenization techniques were compared using simulated datasets reproducing a vast range of possible situations. The simulated data represent homogeneous series and series having one or more steps. Although the majority of the techniques considered in this study perform very well, two methods seem to work slightly better than the others: the standard normal homogeneity test without trend, and the multiple linear regression technique. Both methods are distinctive because of their sensitivity concerning homogeneous series and their ability to detect one or several steps properly within an inhomogeneous series.

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In the first part of this article, a critical review of traditional approaches used to estimate daily inhalation rates as a function of age for health risk assessment purposes shows that such rates are not totally reliable due to various biases introduced by both quantitative and qualitative deficiencies regarding certain input parameters. In the second part, the magnitude of under-and overestimations of published inhalation rates derived from each approach is described by a comparison with new sets of physiological daily inhalation rates and distribution percentile values based on total daily energy expenditures (TDEEs) measured by the doubly labeled water (DLW) method. TDEEs are derived from the analysis of deuterium ( 2 H) and heavy oxygen-18 ( 18 O)