Aquatic exposure assessments using surface water quality monitoring data are often challenged by missing extreme concentrations if sampling frequency is less than daily. A bias factor method has been previously proposed to address this concern for peak concentrations, where a bias factor is a multiplicative quantity to upwardly adjust estimates so that the true value is exceeded 95% of the time. In other words, bias factors are statistically protective adjustments. We evaluate this method using a research data set of 69 near-daily sampled site-years from the Atrazine Ecological Monitoring Program, dividing the data set into 23 reference and 46 validation site-years. Bias factors calculated from the reference data set are used to evaluate the method using the validation set for 1) point estimation, 2) interval estimation, and 3) decision-making. Sampling designs are every 7, 14, 28, and 90d; and target quantities of assessment interest are the 90th and 95th percentiles and maximum m-day rolling averages (m=1, 7, 21, 60, 90). We find that bias factors are poor point estimators in comparison with alternative methods. For interval estimation, average coverage is less than nominal, with coverage at individual site-years sometimes very low. Positive correlation of bias factors and target quantities, where present, adversely affects method performance. For decision rules or screening, the method typically shows very low false-negative rates but at the cost of extremely high false-positive rates. Environ Toxicol Chem 2018;37:1864-1876. (c) 2018 SETAC
