Monitoring on the Auto-Analyzer System in-Statistical-Control for SO_2 in Atmosphere With Top-Down Uncertainty Evaluation

摘要

In this paper, the top-down approach (CNAS-GL34: Guidance for Measurement Uncertainty Evaluation Based on Quality Control Data in Environmental Testing, China National Accreditation Service for Conformity Assessment, Beijing, China, 2013) for A type evaluation of empirical model can be applied to qualify the S0_2 by using analyzer and primary test method (PTM) (GB/T 27408: Quality Control in Laboratories-Evaluating Validity of Non-Standard Test Method-Practice for a Linear Relationship, Standardization Administration of the People's Republic of China, Beijing, China, 2010), whereupon a large number of real-time data, in multi-sites at different levels, were accumulated under site precision (s_(R')) in-statistical-control condition (GB/T 27411: Routine Methods for Evaluation and Expression of Measurement Uncertainty in Testing Laboratory, Standardization Administration of the People's Republic of China, Beijing, China, 2012). The data-transformed-system under investigation cannot be considered suspect as none of the Anderson Darling (AD) statistics were failed in acceptance at the 95 % confidence level for the hypothesis of normality and independence. Our survey was originated from the fog-haze over a period of time for S0_2 in air, with its boundary of 100 x 10~(-9)~400 x 10~(-9.) Finally, the top-down approach, based on closeness sum of squares (CSS), gave the reliable and valid evaluation as the expanded uncertainty, U = 8.5 μg/m~3, which maximized the combination of the effects on various variances, refrained from the complicated relativity by bottom-up for uncertainty evaluation.