This paper demonstrates statistical methods that estimate measurement error from available industrial hygiene data. Errors in measuring a continuous exposure variable may arise when all individuals in a work area are assigned the same exposure. An example is when the mean of exposure measurements obtained on a sample of individuals is assigned to all workers with similar jobs. This may lead to inaccurate point and interval estimates in exposure-response modeling. A method of simulating the distribution of true (i.e., unobserved) individual exposures is described in order to estimate the mean and variance of measurement error. The minimum variance unbiased estimator approximates the mean of lognormally distributed exposure measurements. The distribution of true individual exposures is approximated by the distribution of simulated estimates of mean exposure. The methodology is illustrated by exposure data from work areas manufacturing refractory ceramic fiber (RCF) and RCF products. Results show that exposure is slightly underestimated in work areas with between 25 and 113 exposure measurements; measurement error variance averages about 1.3% of the total variance.