An approach for calculating a confidence interval from a single aquatic sample for monitoring hydrophobic organic contaminants

Abstract

The use of passive sampling devices (PSDs) for monitoring hydrophobic organic contaminants in aquatic environments can entail logistical constraints that often limit a comprehensive statistical sampling plan, thus resulting in a restricted number of samples. The present study demonstrates an approach for using the results of a pilot study designed to estimate sampling variability, which in turn can be used as variance estimates for confidence intervals for future n = 1 PSD samples of the same aquatic system. Sets of three to five PSDs were deployed in the Portland Harbor Superfund site for three sampling periods over the course of two years. The PSD filters were extracted and, as a composite sample, analyzed for 33 polycyclic aromatic hydrocarbon compounds. The between-sample and within-sample variances were calculated to characterize sources of variability in the environment and sampling methodology. A method for calculating a statistically reliable and defensible confidence interval for the mean of a single aquatic passive sampler observation (i.e., n = 1) using an estimate of sample variance derived from a pilot study is presented. Coverage probabilities are explored over a range of variance values using a Monte Carlo simulation.

Air-water exchange of PAHs and OPAHs at a superfund mega-site

“…In water, Σ 60 PAH concentrations were higher downstream at RM 3.5 and RM 1 than at upstream sites (Figure 2D). Elevated levels of 20 (±4) ng/L at RM 3.5 are similar to those observed in the PHSM during July and August of 2010 (Matzke et al, 2012). Major PAHs contributing to the sum concentration at both RM 1 and RM 3.5 were phenanthrene, pyrene and 2,3-dimethylanthracene.…”

“…Passive sampling devices (PSDs) have been increasingly used to assess dissolved water and vapor phase air concentrations, and more recently flux (Allan et al, 2012; Allan et al, 2011; Anderson et al, 2008; Bartkow et al, 2004; Khairy and Lohmann, 2012; Matzke et al, 2012; Tidwell et al, 2016). PSDs are especially well-suited for flux assessments because they sequester the freely dissolved and the vapor phase fractions of contaminants in the water and air (Tidwell et al, 2016).…”

Polycyclic Aromatic Hydrocarbon (PAH) and Oxygenated PAH (OPAH) Air–Water Exchange during the Deepwater Horizon Oil Spill

“…Confidence intervals were calculated from a Gulf of Mexico air and water replication study performed using n = 12 PSDs and represents the pooled variance. 37 The average percent difference between SUM PAH replicates in water and air at each site were 18 and 41, respectively. Principal component analysis (PCA) was used to explore changes in chemical profiles of samples; a specific description can be found in the SI .…”

Passive sampling devices enable capacity building and characterization of bioavailable pesticide along the Niger, Senegal and Bani Rivers of Africa

“…Approximate 95% confidence intervals (CIs) of mean C free pesticide concentrations were determined using methods previously described for PSDs, where log 10 measurement variances display approximately normal distributions [ 26 ]. Specific details of the calculation are provided in the electronic supplementary material.…”

“…When PRC recoveries were below 20% or above 80%, the sampling rates were determined using an improved model for calculating in situ sampling rates [21,23]. Approximate 95% confidence intervals (CIs) of mean C free pesticide concentrations were determined using methods previously described for PSDs, where log 10 measurement variances display approximately normal distributions [26]. Specific details of the calculation are provided in the electronic supplementary material.…”