Evaluation of Measurement Uncertainty in an Environmental Test Laboratory by Quality Assurance, Control Charting and Robust Statistics

There are broad application prospects for evaluation of measurement uncertainty in the environmental test laboratory based on quality control data accumulated in long-term routine analysis. The quality control charting method is used only for the same concentration data. Linear calibration using reference materials can be used in different concentration measurement data but the complete quality control data cover different concentrations with the same number of measurements and should be prepared before the mathematical mode is established, which makes its application in most testing laboratories unsuitable. Robust statistics is a type of statistical analysis method where it is unnecessary to identify and delete outliers but it can also reduce the effect of outliers on the final results based on all measurement data. Quality control charting methods and robust statistics (iteration method), when outliers exist, are used to calculate intermediate precision (s_R′) after normalizing different concentration data by recovery rate and are described in this paper. Five sets of data collected in our laboratory and 19 sets of data from the other laboratories, which cover routine testing items in environmental protection field, were used to verify the feasibility of the new method. It can be shown that the average difference of relative intermediate precision (Δs_R′_-rsd) between robust statistics and quality control charting methods are almost in agreement (i.e. 0.15%) for the single concentration data. For the multi-level concentration data after normalization, the average difference (Δs_R′_-rsd) between quality control charting and linear calibration, between robust statistics and linear calibration, are 0.43% and 0.20%, respectively. The average of difference (Δs_R′_-rsd) between robust statistics and quality control charting method is 0.26%, which indicates that the results of all three methods are generally in line with each other. The principle of the new methods proposed in this paper is easy to understand and the calculation procedure is significantly simplified, making it suitable for cases of linear calibration using reference materials with direct proportion mode.