Robust multivariate analysis of compositional data of treated wastewaters

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27360%2F19%3A10242031" target="_blank" >RIV/61989100:27360/19:10242031 - isvavai.cz</a>
Alternative codes found
RIV/61989100:27710/19:10242031
Result on the web
<a href="https://link.springer.com/article/10.1007%2Fs12665-019-8248-6" target="_blank" >https://link.springer.com/article/10.1007%2Fs12665-019-8248-6</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/s12665-019-8248-6" target="_blank" >10.1007/s12665-019-8248-6</a>

Result language
angličtina
Original language name
Robust multivariate analysis of compositional data of treated wastewaters
Original language description
A dataset of water samples collected behind a biological wastewater treatment plant (BWWTP) during a year were processed as compositional data by a logratio transformation and then analysed by a robust principal component analysis (RPCA) and characterized the robust Mahalanobis distances (RMDs). For this purpose, covariance matrices were computed using a minimum covariance determinant (MCD) algorithm. Raw and transformed 11 physico-chemical parameters were reduced to 4 robust principal components (RPCs). Correlations between centre logratio (clr) transformed parameters and RPCs were found to be more realistic than those between the parameters and RPCs of raw data. The 1st and 2nd RPCs represented nitrogen and phosphorus compounds, respectively. Their temporal changes were explained by some processes occurring during biological wastewater treatment. A nitrification process was also demonstrated by the temporal changes of the raw and clr transformed concentrations of ammonium. The robust and classical Mahalanobis distances were computed from the raw and isometric logratio (ilr) transformed data to show the overall temporal changes of treated wastewater composition and to detect outlaying samples.
Czech name
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Czech description
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Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
20701 - Environmental and geological engineering, geotechnics

Project
<a href="/en/project/EF16_019%2F0000853" target="_blank" >EF16_019/0000853: Institute of Environmental Technology - Excellent Research</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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