Use of Mathematical–Statistical Methods for Evaluating Data from Chemical Analysis Referring to the State of the Environment

The necessity for using appropriate evaluation methods in environmental chemical analysis is demonstrated in examples from the River Sajó and the urban air of Miskolc. River Sajó is a natural ecosystem, whereas the city of Miskolc is an artificial environment. Chemical analysis was performed on Rive...

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Vydáno v:Microchemical journal Ročník 59; číslo 2; s. 258 - 268
Hlavní autoři: Paksy, L., Lengyel, A., Bánhidi, O.
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York, NY Elsevier B.V 01.06.1998
Elsevier
Témata:
Analytical chemistry
Applied sciences
Chemistry
Continental surface waters
Exact sciences and technology
Natural water pollution
Pollution
Spectrometric and optical methods
Water treatment and pollution
Trace analysis
Data analysis
Chemical analysis
Pneumatic nebulization
Multivariate analysis
Inductive coupling plasma spectrometry
Inorganic element
Environmental control
Emission spectrometry
Multicomponent analysis
Ultrasonic nebulization
Water pollution
River water
Chemometrics
ISSN:0026-265X, 1095-9149
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Popis
Shrnutí:The necessity for using appropriate evaluation methods in environmental chemical analysis is demonstrated in examples from the River Sajó and the urban air of Miskolc. River Sajó is a natural ecosystem, whereas the city of Miskolc is an artificial environment. Chemical analysis was performed on River Sajó water at regular, weekly intervals to determine the following inorganic components: Na, Mg, Si, P, K, Ca, Cr, Fe, Co, Ni, Cu, Zn, As, Sr, Cd, Ba, Pb. The behavior of the assumed natural and polluting components was studied, characterizing them by their distribution, trend, occurrence of outliers and cross-correlation. Similarly, some polluting components of the urban air of Miskolc were studied, and characteristic features of the changes were observed. Because of the rapidly changing distributions and frequently occurring trend, nonparametric methods can be recommended for evaluation and forecasting.
ISSN:0026-265X
1095-9149
DOI:10.1006/mchj.1998.1570