2014
DOI: 10.3920/qas2012.0.236
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Quality assurance and quality control in environmental radioactivity monitoring

Abstract: To assure that radiological monitoring is reasonably valid, organisations performing such measurements have found it necessary to establish quality assurance (QA) and quality control (QC) programs. These programs are needed to identify deficiencies in the sampling and measurement processes. In addition, validation of the monitoring aims to prove whether the results are acceptable. The major aim of QA and QC in analytical laboratories is to address measures used to verify the validity of the final results. In t… Show more

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Cited by 2 publications
(3 citation statements)
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“…The accuracy and reproducibility of gamma spectrometry systems are verified on a weekly basis. The detector-shield background, detector efficiency, peak shape and peak drift are measured and verified to be within the acceptance limits [3].…”
Section: Experimental Technique and Methods Of Measurementsmentioning
confidence: 94%
See 1 more Smart Citation
“…The accuracy and reproducibility of gamma spectrometry systems are verified on a weekly basis. The detector-shield background, detector efficiency, peak shape and peak drift are measured and verified to be within the acceptance limits [3].…”
Section: Experimental Technique and Methods Of Measurementsmentioning
confidence: 94%
“…In Serbia two HP Ge p-type detectors Canberra with relative efficiencies of 20 % and 50 % were used for gamma spectrometry measurement. Duration of each measurement was 60000 s. Calibration of detectors for sediment measurements was performed using silicone resin matrix spiked with a series of radionuclides ( 241 Am, 109 3 . Duration of measurement was 60000 s for the sediment and 250000 s for the fish samples.…”
Section: Experimental Technique and Methods Of Measurementsmentioning
confidence: 99%
“…• Land Cover is created using multispectral satellite imagery: Sentinel 2 satellite imagery was downloaded from Copernicus Sci-Hub (Copernicus, 2020) to create a land cover map using the Dzetsaka classification plugin (Karasiak, 2016) in QGis (QGIS, 2022). The research used Sentinel 2 S2B MSIL2A 20210913T093029 N0301 R136 T34TEN 20210913T114013 cloud-free imagery collected on September 13th, 2021.…”
Section: Input Datamentioning
confidence: 99%