期刊
MOLECULES
卷 27, 期 11, 页码 -出版社
MDPI
DOI: 10.3390/molecules27113628
关键词
biochemical oxygen demand; manganese molar concentration; guard bands; pH; non-parametric methods; Escherichia coli
资金
- Brazilian funding agency CNPq
- Brazilian funding agency CAPES
- Brazilian funding agency FINEP
- Brazilian funding agency FAPERJ
- Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior-Brasil (CAPES) [001]
This study introduces the use of non-parametric tests and guard bands to assess the compliance of river water properties with Brazilian environmental regulations. The study proposes a robust method to calculate measurement uncertainty and evaluates compliance using guard bands. The methodology considers the heterogeneity of data and non-Gaussian distribution, providing a satisfactory approach to compliance assessment.
This study aimed to introduce non-parametric tests and guard bands to assess the compliance of some river water properties with Brazilian environmental regulations. Due to the heterogeneity of the measurands pH, Biochemical Oxygen Demand (BOD), manganese molar concentration, and Escherichia coli, which could be wrongly treated as outliers, as well as the non-Gaussian data, robust methods were used to calculate the measurement uncertainty. Next, based on guard bands, the compliance assessment was evaluated using this previous uncertainty information. For these four measurands, partial overlaps between their uncertainties and the specification limit could generate doubts about compliance. The non-parametric approach for calculating the uncertainty connected to the guard bands concept classified pH and BOD as conform, with a risk to the consumer of up to 4.0% and 4.9%, respectively; in contrast, manganese molar concentration and Escherichia coli were not conform, with a risk to the consumer of up to 25% and 7.4%, respectively. The methodology proposed was satisfactory because it considered the natural heterogeneity of data with non-Gaussian behavior instead of wrongly excluding outliers. In an unprecedented way, two connected statistical approaches shed light on the measurement uncertainty in compliance assessment of water analysis.
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