Partitioning between polyurethane foam and the gas phase: data compilation, uncertainty estimation and implications for air sampling.

Polyurethane foam (PUF) is frequently applied for sampling semi-volatile organic compounds (SVOCs) in the gas phase. Equilibrium partition coefficients (KPUF/G) often are used to estimate the potential for breakthrough during active air sampling (AAS) and to correct for non-linear uptake during passive air sampling (PAS). KPUF/G is either determined experimentally or estimated, in both cases incurring uncertainties that can be carried over to other parameters. Here, a dataset of 547 measured KPUF/G values and chemical information for 281 distinct chemicals was compiled from the peer reviewed literature. Measured log KPUF/G were compared with predicted values to identify potential bias in data generated with a particular experimental approach. An analysis of the measured data suggests that the uncertainty of unbiased log KPUF/G values is at best 0.2 log units at 15 °C (e.g. for hexachlorobenzene and fluoranthene), but most likely much higher. This implies that inherent passive air sampling rates obtained from the loss of a depuration compound (SR) and breakthrough volumes during AAS can presently not be known with an uncertainty of less than ca. 50%. During short PAS deployment periods, the uncertainty in the effective sampling volume (Vair) derives mainly from the uncertainty in the SR, whereas the uncertainty in KPUF/G of the target compound will become important and even the main source of uncertainty for Vair if deployments are long or target chemicals are relatively volatile. This in turn implies that the uncertainty of Vair cannot be smaller than the uncertainty of SR and KPUF/G and therefore again is at least ca. 50%. We strongly recommend that the uncertainty of air concentrations obtained by non-linear PAS is quantified and reported and we outline a procedure on how to do that. Because the uncertainty in KPUF/G of target and depuration chemicals generally exceeds 30%, it may often be necessary to conduct Monte Carlo simulation.