Improving sample representativeness in environmental studies: a major component for the uncertainty budget
For environmental quality assessment, INAA has been applied for determining chemical elements in small (200 mg) and large (200 g) samples of leaves from 200 trees. By applying the Ingamells’ constant, the expected percent standard deviation was estimated in 0.9–2.2% for 200 mg samples. Otherwise, fo...
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Veröffentlicht in: | Journal of radioanalytical and nuclear chemistry 2009-10, Vol.282 (1), p.125-132 |
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container_title | Journal of radioanalytical and nuclear chemistry |
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creator | De França, Elvis J. De Nadai Fernandes, Elisabete A. Bacchi, Márcio A. Bode, Peter van Soldt, Rob T. M. |
description | For environmental quality assessment, INAA has been applied for determining chemical elements in small (200 mg) and large (200 g) samples of leaves from 200 trees. By applying the Ingamells’ constant, the expected percent standard deviation was estimated in 0.9–2.2% for 200 mg samples. Otherwise, for composite samples (200 g), expected standard deviation varied from 0.5 to 10% in spite of analytical uncertainties ranging from 2 to 30%. Results thereby suggested the expression of the degree of representativeness as a source of uncertainty, contributing for increasing of the reliability of environmental studies mainly in the case of composite samples. |
doi_str_mv | 10.1007/s10967-009-0326-x |
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M.</creatorcontrib><title>Improving sample representativeness in environmental studies: a major component for the uncertainty budget</title><title>Journal of radioanalytical and nuclear chemistry</title><addtitle>J Radioanal Nucl Chem</addtitle><description>For environmental quality assessment, INAA has been applied for determining chemical elements in small (200 mg) and large (200 g) samples of leaves from 200 trees. By applying the Ingamells’ constant, the expected percent standard deviation was estimated in 0.9–2.2% for 200 mg samples. Otherwise, for composite samples (200 g), expected standard deviation varied from 0.5 to 10% in spite of analytical uncertainties ranging from 2 to 30%. Results thereby suggested the expression of the degree of representativeness as a source of uncertainty, contributing for increasing of the reliability of environmental studies mainly in the case of composite samples.</description><subject>Assessments</subject><subject>Budgeting</subject><subject>Chemical elements</subject><subject>Chemistry</subject><subject>Chemistry and Materials Science</subject><subject>Diagnostic Radiology</subject><subject>Environmental studies</subject><subject>Hadrons</subject><subject>Heavy Ions</subject><subject>Inorganic Chemistry</subject><subject>Mathematical analysis</subject><subject>Nuclear Chemistry</subject><subject>Nuclear Physics</subject><subject>Physical Chemistry</subject><subject>Standard deviation</subject><subject>Uncertainty</subject><issn>0236-5731</issn><issn>1588-2780</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2009</creationdate><recordtype>article</recordtype><recordid>eNp9kEtPwzAQhC0EEqXwA7j5xsngR5o43FDFo1IlLnC2HGdTHCV2sJ2q_HtclTOn1e7MrDQfQreM3jNKq4fIaF1WhNKaUMFLcjhDC7aSkvBK0nO0oFyUZFUJdomuYuxpNkopFqjfjFPwe-t2OOpxGgAHmAJEcEknuwcHMWLrMLi9Dd6Nx_uAY5pbC_ERazzq3gds_Dh5l0Xc5S19AZ6dgZC0dekHN3O7g3SNLjo9RLj5m0v0-fL8sX4j2_fXzfppS4woRSJcd7Jou6Jh0pQcTC3rirEGTAOFgJYWTDdVIWjbFlVXmkYC1ZRnrW67rm4KsUR3p7-52PcMManRRgPDoB34OapqJcqaU86yk52cJvgYA3RqCnbU4Ucxqo5Y1QmryrTUEas65Aw_ZWL2uh0E1fs5uFzon9AvQTV_FQ</recordid><startdate>20091001</startdate><enddate>20091001</enddate><creator>De França, Elvis J.</creator><creator>De Nadai Fernandes, Elisabete A.</creator><creator>Bacchi, Márcio A.</creator><creator>Bode, Peter</creator><creator>van Soldt, Rob T. 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subjects | Assessments Budgeting Chemical elements Chemistry Chemistry and Materials Science Diagnostic Radiology Environmental studies Hadrons Heavy Ions Inorganic Chemistry Mathematical analysis Nuclear Chemistry Nuclear Physics Physical Chemistry Standard deviation Uncertainty |
title | Improving sample representativeness in environmental studies: a major component for the uncertainty budget |
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