Abstract
Integrative sampling enables the collection of analyte mass from environmental liquids over extended timeframes from hours to months. While the incentives to complement or replace conventional, time-discrete sampling have been widely discussed, the data quality implications of employing alternative, integrative methods have not yet been systematically studied. A critical analysis of contemporary literature reports showed the data quality of integrative samplers, whether active-advection or passive-diffusion, to be governed by uncertainty in both sampling rate and analyte recovery. Derivation of two lumped parameters, representing the coefficient of accumulation (α) of a contaminant from an environmental fluid and the coefficient of subsequent recovery (ρ) of its mass from the sampler, produced a conceptual framework for quantifying error sources in concentration data derived from accumulative samplers. Whereas the precision associated with recovery was found to be fairly consistent across eight passive-diffusion and active-advection devices (averaging 5-16% relative standard deviation, RSD), active-advection samplers effectively improve precision in sampling rate (analyte uptake), as determined for two active-advection devices (2-7% average RSD) and five passive devices (12-42% average RSD). In summary, an approach is presented whereby the data quality implications of integrative sampler design can be compared, which can inform the selection, optimization, and development of sampling systems to complement the state of the art.