Calibration Method and Uncertainty Evaluation for X-Ray Fluorescence Chlorine Analyzers

X-ray fluorescence (XRF) chlorine analyzers are widely used for chlorine determination in crude oil and petroleum products. Although analytical test procedures are standardized, a calibration-oriented uncertainty framework for the analyzer itself remains insufficiently developed. This study establishes a metrological framework for relative indication error and limit of detection (LOD), supported by repeatability and linearity evaluations, and compares uncertainty propagation using the Guide to the Expression of Uncertainty in Measurement (GUM) and the Monte Carlo method (MCM). For relative indication error, residual matrix mismatch was quantified using paired isooctane-based light-oil and 75 cSt mineral-oil reference materials and incorporated with measurement repeatability and certified-value uncertainty. At 100, 300 and 500 mg/L, GUM and MCM produced closely agreeing standard uncertainties of approximately 0.0115, 0.0103 and 0.0081, respectively. For LOD, both methods used the same dual-axis error-weighted regression, accounting for uncertainties in certified concentrations and mean instrumental responses; in the MCM, the regression was repeated for every simulated calibration data set. The resulting standard uncertainties were 0.0048 mg/L (GUM) and 0.0047 mg/L (MCM), and the MCM equal-tailed 95% coverage interval was 0.0122–0.0307 mg/L. The framework’s distinctive value is the consistent treatment of calibration measurands, matrix transfer and dual-axis error-weighted regression across both propagation methods. It provides an auditable GUM budget for routine calibration and certificate reporting, while MCM offers a verification route when repeated regression, finite-sample blank dispersion or asymmetric output intervals are important.