Abstract：The mercury content in 641 iron ore samples imported from Caofeidian port was determined. The normality of data was verified by normal probability distribution function, and the polymorphism of data analyzed by kernel density distribution estimation. The repetitive simulation sampling of entire sample and subsample was conducted by Bootstrap method, respectively. The representative value and confidence interval of mercury content were estimated. The results indicated that the mercury content in entire sample showed abnormal distribution, while the kernel density distribution diagram could intuitively reflect the polymorphism of mercury content distribution. The representative value of mercury content in entire sample was 0.066 3 μg/g. The representative value of iron ore from Australia, Brazil, Peru, Japan, South Africa, Ukraine, Chile and India was 0.057 3, 0.077 4, 0.056 8, 0.003 0, 0.007 8, 0.013 0, 0.002 9 and 0.047 8 μg/g. The estimation of representative mercury content in finite samples through repetitive simulation sampling by Bootstrap method was robust and effective. It provided a new method for the estimation of elemental content in risk assessment of harmful elements.
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