Statistical modeling of sediment and oyster PAH contamination data collected at a South Carolina estuary (complete and left-censored samples)

Abstract

This paper presents an analysis of polycyclic aromatic hydrocarbon (PAH) sediment and oyster contamination data collected at Murrells Inlet, South Carolina. Murrells Inlet is a high salinity estuary located in a heavily urbanized area south of Myrtle Beach, South Carolina. In the first part, lognormal and Weibull distributions are determined that best fit the data, as measured by P–P and Q–Q probability plots. The results indicate that the Weibull gives an adequate fit for almost all the PAH analytes considered. In fact, the Weibull almost always provides a better fit to the data than the lognormal distribution. The second part addresses issues associated with non-detection points, as they are regularly encountered in environmental analyses. In statistical terms, the existence of non-detection points corresponds to data that are left-censored. Several statistical methods for estimating the Weibull parameters from such left-censored data are explored. The overall result is in agreement with recent findings reported by other investigators: methods based on the underlying distribution of the data give more consistent results than those obtained by commonly used substitution methods. Copyright © 2000 John Wiley & Sons, Ltd.