暴露评估中稻米重金属汞污染的适宜采样量

Appropriate Sample Sizes for Risk Assessment of Mercury Exposure in Milled Rice

稻米中的重金属汞是风险评估的热点。考虑其污染检测数据呈右偏分布的特殊性,在暴露评估中,适宜的采样量是评估高效准确的保证。本研究用Weibull分布拟合稻米中汞的检测数据,就评估关注的高百分位数估计与采样量的关系进行模拟研究。结果表明:峰右侧的百分位数越高,准确估计其所需的采样量就越大。且估计值随采样量的加大趋近理论值,精度也随之增大。采样量达到400、70 0和150 0时,即可保证相应的P95、P97.5和P99估计值的准确度与精确度。但1500的采样量仅能保证对P99.9估计值的准确度,无法满足精度要求。而采样量的不足极可能造成对高百分位数的低估,而最终导致对风险的低估。在实施稻米重金属汞的暴露评估时,对其污染检测数据采样量的关注可避免结果偏差及人力物力的浪费。

The mercury exposure in milled rice has become a hotspot in risk assessment.Considering the positively skewed contamination data,an economic and effective assessment must be based on an appropriate sample size.With the benefit of computer simulation,this paper set out to study the relationship between sample size and percentile estimate with Weibull distribution,which was used to fit the mercury contamination data.The simulation results showed that accurately estimating a higher percentile of positively skewed distribution,specially the one on the right side of peak,would require a larger sample size.And a larger sample size always resulted in a more accurate and more stable estimated percentile.As sample size increased to exceed 400,700 and 1500,estimates of P95,P97.5 and P99 could obtain guaranteed accuracy and precision respectively,while a sample size of 1500 could only satisfy the accuracy but not precision of P99.9 estimates.Furthermore,insufficient samples would always lead to an underestimate of high percentile,and then lead to an underestimate of risk.When it comes to risk assessment of mercury exposure in milled rice,the in-depth study of sample size promises not only a possibility of an accurate result,but also an economical resource allocation.