基于氨氮实测结果的水质自动监测系统数据质量分析

为提高水质自动监测数据质量，在地表水水质自动监测系统实际监测运行环境中，基于统计分析方法，探讨水质自动监测日常运行维护质控手段对运行维护质量监督考核结果的影响，探索提高水质自动监测质控考核结果合格率的运行维护质控技术要求。结果表明：零点漂移检查、量程/跨度漂移检查对水质自动监测质控考核结果虽无显著影响，但却是保障水质自动监测数据质量的基础；水质自动监测仪标准物质核查结果相对误差的合格判定标准由±10%加严至±6%时，水质自动监测仪标准物质核查、实际水体样品比对测试、实际水体样品加标回收率测试及盲样考核结果的合格率均显著提升；标准物质核查合格率由74.6%~77.9%提升为98.4%~100%，实际水体样品比对测试的合格率由62.5%提升为75.9%，实际水体样品加标回收率测试的合格率由75.0%提升为87.5%~100%，盲样考核合格率由75.0%提升为100%；标准物质核查及实际水体样品比对测试相对误差均不服从正态分布，且数据分布为正偏态分布；实验所用水质自动监测仪器可能存在负偏离的系统误差，手工比对实验环节对实际水体样品比对测试结果也可能存在一定干扰。综合上述结果，在进行水质自动监测仪器设计和选型时，应消除可能的系统偏差；在开展实际水体样品比对测试过程中，应加强对比对实验相关环节的质量监督和检查；在水质自动监测系统运行维护时，应采用更严格的标准物质核查结果相对误差合格判定标准，以提高和保障自动监测数据质量。相关研究成果可为水质自动监测系统运行维护采取的质量控制措施和评价标准的制定提供技术支持。

Data quality analysis of water quality automatic monitoring system based on ammonia nitrogen test results

In order to improve the data quality of water quality automatic monitoring, in the actual monitoring and operation environment of surface water quality automatic monitoring system, based on the statistical analysis method, the impact of quality control means for daily operation and maintenance of water quality automatic monitoring on the quality supervision and assessment results of operation and maintenance was discussed, and the technical requirements of operation and maintenance quality control to improve the qualified rate of quality control assessment results of water quality automatic monitoring were explored. The results showed that the zero drift check and range/span drift check had no significant impact on the quality control assessment results of water quality automatic monitoring, but they were the basis to ensure the data quality of water quality automatic monitoring. When the qualification criteria for the relative error of the reference material verification results of water quality automatic monitoring instrument was tightened from ±10% to ±6%, the qualification rates of the reference material verification of water quality automatic monitoring instrument, the comparison test of the actual water samples, the standard addition recovery rate test of the actual water samples and the blind sample examination increased significantly. The corresponding qualified rates increased from 74.6%~77.9% to 98.4%~100%, from 62.5% to 75.9%, from 75.0% to 87.5%~100%, and from 75.0% to 100%, respectively. The relative errors of the reference material verification and comparison test of the actual water sample didn’t conform to the normal distribution, and the data distribution was a normal skew distribution. A negative systematic error could occur in the water quality automatic monitoring instrument used in the experiment, and the manual comparison experiment could interfere the comparison test results of actual water samples. Based on the above results, the possible system deviations should be eliminated when designing and selecting water quality automatic monitoring instruments. During the comparison test of actual water samples, the quality supervision and inspection of relevant links in the comparison test should be strengthened; During the operation and maintenance of water quality automatic monitoring system, more strict qualified criteria for the relative error of standard material verification results should be used to improve and ensure the quality of automatic monitoring data. Relevant research results will provide a technical support for the formulation of quality control measures and evaluation standards for the operation and maintenance of water quality automatic monitoring system.