title: Application of the Nordtest method for "real-time" uncertainty estimation of on-line field measurement.
abstract: Field sensor measurements are becoming more common for environmental monitoring. Solutions for enhancing reliability, i.e. knowledge of the measurement uncertainty of field measurements, are urgently needed. Real-time estimations of measurement uncertainty for field measurement have not previously been published, and in this paper, a novel approach to the automated turbidity measuring system with an application for "real-time" uncertainty estimation is outlined based on the Nordtest handbook's measurement uncertainty estimation principles. The term real-time is written in quotation marks, since the calculation of the uncertainty is carried out using a set of past measurement results. There are two main requirements for the estimation of real-time measurement uncertainty of online field measurement described in this paper: (1) setting up an automated measuring system that can be (preferably remotely) controlled which measures the samples (water to be investigated as well as synthetic control samples) the way the user has programmed it and stores the results in a database, (2) setting up automated data processing (software) where the measurement uncertainty is calculated from the data produced by the automated measuring system. When control samples with a known value or concentration are measured regularly, any instrumental drift can be detected. An additional benefit is that small drift can be taken into account (in real-time) as a bias value in the measurement uncertainty calculation, and if the drift is high, the measurement results of the control samples can be used for real-time recalibration of the measuring device. The procedure described in this paper is not restricted to turbidity measurements, but it will enable measurement uncertainty estimation for any kind of automated measuring system that performs sequential measurements of routine samples and control samples/reference materials in a similar way as described in this paper.
authors.affiliation: Environmental Measurement and Testing Laboratory, Finnish Environment Institute, Hakuninmaantie 6, 00430, Helsinki, Finland. teemu.naykki@ymparisto.fi.
authors.forename: Teemu
authors.initials: T
authors.lastname: Näykki
authors.affiliation: Data and Information Centre, Finnish Environment Institute, Mechelininkatu 34a, 00251, Helsinki, Finland.
authors.forename: Atte
authors.initials: A
authors.lastname: Virtanen
authors.affiliation: Environmental Measurement and Testing Laboratory, Finnish Environment Institute, Hakuninmaantie 6, 00430, Helsinki, Finland.
authors.forename: Lari
authors.initials: L
authors.lastname: Kaukonen
authors.affiliation: Chemistry, Materials and Surfaces, SP Technical Research Institute of Sweden, 50115, Borås, Sweden.
authors.forename: Bertil
authors.initials: B
authors.lastname: Magnusson
authors.affiliation: Environmental Measurement and Testing Laboratory, Finnish Environment Institute, Paavo Havaksen tie 3, 90570, Oulu, Finland.
authors.forename: Tero
authors.initials: T
authors.lastname: Väisänen
authors.affiliation: Institute of Chemistry, University of Tartu, Ravila 14a, 50411, Tartu, Estonia.
authors.forename: Ivo
authors.initials: I
authors.lastname: Leito
mesh_terms: D004784:Environmental Monitoring / Q000379:methods* / Q000706:statistics & numerical data; D008962:Models, Theoretical; D009391:Nephelometry and Turbidimetry; D015203:Reproducibility of Results; D045483:Rivers / Q000737:chemistry*; D012984:Software; D035501:Uncertainty
keywords: Field measurement; Measurement uncertainty; Nordtest approach; Quality control; Turbidity; Water quality monitoring