Significance of Nondetects in the Mapping of Soil contaminants.

University essay from KTH/Mark- och vattenteknik (flyttat 20130630)


In the sample data of soil contaminants, the existence of nondetects is a common phenomenon. Due to their small values, they are always ignored. However, they form an essential part of the sample distribution and arbitrary changes of their values will affect the properties of the distribution, for example, the 95% upper confidence limit of the mean (95UCLM), which is an important index in risk assessment, is strongly related with the sample distribution. Statistical analysis methods for nondetects involve substitution by half of the detection limit (DL/2), maximum likelihood estimation (MLE), Kaplan-Meier and regression on ordered statistics (ROS). The significance of nondetects was examined in this study. Two large data sets of cadmium (Cd) and mercury (Hg) containing censored observations in Annedal’s park were used, where the censored observations were known from the laboratory. Large data sets were subsampled into small data sets with different sample sizes and censoring levels. The 95UCLM value of each data set was calculated by use of the statistical software ProUCL 4.1.00. Through comparison, it was found that in most cases the 95UCLM value calculated with lab values was lower than that of the censored observation for each data set. The difference in 95UCLM values between the data set with nondetects and the data set with lab values varied in each sample and was found to be related to sample size and to the censoring level. The higher the censoring level was, the bigger the 95UCLM value difference became. Either too small or too large a sample size would reduce the difference between the 95UCLM values. This result helps in certain cases, when the 95UCLM value of the sample data is a little lower than the threshold; using the lab values instead of nondetects to recalculate the 95UCLM value may supply a manageable and economic tool to classify the contaminated area.

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