自适应蒙特卡洛法评定肥料中苯并[a]芘含量的测量不确定度

Evaluation of Measurement Uncertainty in the Determination of Benzo[a]pyrene in Fertilizer by Adaptive Monte Carlo Method

通过Python编写计算程序,完成自适应蒙特卡洛法评定测量不确定度的代码实现,进而评定气相色谱质谱法测定肥料中苯并[a]芘含量的测量不确定度。结果表明,气相色谱质谱仪测定肥料中苯并[a]芘含量的标准不确定度为0.0179 mg/kg。探索了自适应MC法在肥料成分含量测定的测量不确定度评定中的应用,结果表明,这种方法具有适用性广、计算过程直观、计算结果可靠的优点。

The code for evaluating the measurement uncertainty by adaptive Monte Carlo method was completed by compiling the calculation program in Python,and then the measurement uncertainty of benzo[a]pyrene content in fertilizer by gas chromatography-mass spectrometry was evaluated.The result showed that the standard uncertainty for the determination of benzo[a]pyrene in fertilizers by gas chromatography mass spectrometer is 0.0179 mg/kg.The application of the adaptive MC method in the measurement uncertainty evaluation of the determination of fertilizer composition content is explored.The results show that this method has the advantages of wide applicability,intuitive calculation process and reliable calculation results.