A considerable amount of work has been conducted developing exposure estimate
models for quantitative evaluation of Hg intake and human health risks, but few have
assessed the applicability and the validity for evaluating the risks posed by Hg in the
environment and have achieved very mixed results. The present study focused on
verifying the daily Hg intake estimates using exposure estimate models. Deterministic
methods and the probabilistic methods (the Monte Carlo) were applied to simulate the
daily Hg intake doses which were verified by comparing the estimates to those
established from measured Hg concentrations in the hair of 289 participants. The
results showed that the single-value deterministic method for simulating Hg exposure
levels overestimated the level of risk by a factor of 1.5 when compared with the
highest concentration of the Hg observed in the hair of the study population. The
average daily Hg intake doses simulated using the probabilistic simulation were
similar in distribution to the biomarker data, with the variability of 23%. The
difference between the probabilistic simulation and the data derived from hair Hg
levels was considered to be most likely due to the uncertainties in unconfirmed
questionnaire-based survey data, small sampling sizes and the surrogates used in the
exposure models. When the reference dose (RfD) of 0.1 ?g/kg body weight/day was
adopted as the acceptable dose for daily intake rate, there were approximately 19%
estimated to have potential Hg exposure risks based on the Monte Carlo simulation.
This percentage was favourably similar to the 17% determined from Hg
concentrations in the hair samples. The findings implied that the existing exposure
models together with the probabilistic approach were appropriate for the research of
human exposure to Hg. On the other hand, low Hg levels in the participants’ hair
indicated that Hg accumulated in the study population was not very serious, probably
due to the good Hg absorptivity of the on-site fly ash. However, it should be advised
that consumption of river fish elevates the health risks to the local population