Journal Published Online: 18 March 2024
Volume 52, Issue 4

Optimization of Data Quality Objective on Ammonia Nitrogen System in Water through ASTM Top-Down Approach for Independence Identical Distribution



Ammonia nitrogen (NH3-N) coming from the instantaneous effluent in urban water is something that is necessary to measure through routine testing. In order to reduce the long-term potentially harmful impacts to ecosystems and human health, we monitor the NH3-N system through an ASTM top-down approach. As the background effect treatments have been debated, the actual extraction efficiency (naturally existing matrix matched) may not be measured for unstable samples greatly fluctuated in wastewater. In this article, we do not spike the matrixes at multiple concentrations; instead, we directly use the parallel samples, within each level consistent differing from each other by up to 5 %. To determine whether the residual or pretreated results derived from the NH3-N system are under the independence identical distribution, we recommend using the more robust Anderson Darling (AD) hypothesis test for the confirmation. If the AD null hypothesis is held, we can believe that the reliability of NH3-N system is validated, and, under the site precision (sR′), incorporate all cumulative effects, even with the interaction and matrix, into the data quality objective (DQO) of the NH3-N system. Our DQO, with variations across all matrices, can be compared to the results obtained historically or subsequently, or with ASTM performance. Our final goal is to meet clients’ needs in a way that allows for operation of the NH3-N system that is consistent, impartial, and competent.

Author Information

Wang, Douwen
Liaoning Inspection and Quarantine Bureau, Dalian, China
Sun, Zhijing
Dalian Product Quality Inspection and Testing Institute Co., Ltd., Shahekou District, Dalian, China
Zhang, Weiqi
Dalian Product Quality Inspection and Testing Institute Co., Ltd., Shahekou District, Dalian, China
Ma, Dongchang
Zhongren Guozhi (Beijing) Testing Technology Research Institute, Beijing, China
Pages: 18
Price: $25.00
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Stock #: JTE20230392
ISSN: 0090-3973
DOI: 10.1520/JTE20230392