A composite random sampling design was used to estimate the concentrations of hydrocarbons in sediments from two near-shore areas of Scotland (Firth of Clyde and Firth of Forth). The aim of this work was to estimate a mean value for each parameter in these areas, and to determine whether this can be done with more thorough coverage (better representation), better precision and less variance at lower analytical cost through a composite random sampling scheme rather than a simple random sampling scheme, and thereby contribute to the re-design of the UK National Marine Monitoring Programme (NMMP), re-named the UK Clean Seas Environmental Monitoring Programme (CSEMP) in 2006. Samples were collected using a simple random sampling design during 2005. All sediment samples were analysed for their particle size distribution and total organic carbon (TOC). All sediments were analysed for polycyclic aromatic hydrocarbons (PAHs) and n-alkanes. The concentrations of PAHs and n-alkanes in the study areas are described, and sources of PAHs were investigated through the PAH distributions and n-alkane profiles. Individual sediment samples from each area were combined to give a series of composite sub-samples, each comprised of 5 individual sediment samples. These composite samples were re-analysed for the same parameters as the individual samples. Mean total PAH (2- to 6-ring parent and branched) concentrations, based on the individual original sediment samples collected through simple random sampling, were 1858 μg kg−1 dry weight (SE = 196 μg kg−1 dry weight, n = 25) and 532.4 μg kg−1 dry weight (SE = 59 μg kg−1 dry weight, n = 25) in the Clyde and Forth, respectively. Mean total PAH concentrations of the composite samples were 1745 μg kg−1 dry weight (SE = 121.0 μg kg−1 dry weight, n = 5) in the Clyde and 511.6 μg kg−1 dry weight (SE = 37.4 μg kg−1 dry weight, n = 5) in the Forth. No significant differences were found between the mean PAH concentrations from the two sampling designs. This study demonstrated that the composite random sampling design gave a mean value with less variance than the simple random sampling design, at significantly reduced analytical effort (and cost).
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