The Principal Component Analysis (PCA) is a method widely used to process experimental data. The PCA aims to reduce the dimensionality of a data set composed of many interrelated variables, preserving the variation as much as possible. This can be achieved by transforming the data set to a new one, containing the principal components (PCs), which are uncorrelated, and which maximize the variance of the original data. In this study, the PCA was applied to experimental tests on aerobic bioremediation of soil polluted with diesel oil. Twelve microcosms (200 g of soil) were prepared, polluted with commercial diesel oil (70 g/kg of dry soil), and hydrated with a mineral salt solution suitable to stimulate the indigenous bacteria. The aerobic process for diesel oil degradation was studied changing two operative parameters, namely, water content (u%) and carbon to nitrogen ratio (C/N). Three values of water content (u% = 8%, 12% and 15% by weight) and four of carbon to nitrogen ratio (C/N = 60, 120, 180 and 300) were tested. The microcosms were monitored for 30 days by the measurements of these parameters: 1) the CO2 production, to evaluate the microbial respiration, 2) the fluorescein production, to check the microbial activity, and 3) the diesel oil concentration, to assess the pollutant degradation and calculate the removal efficiency. The Principal Component Analysis was done considering the water content values as variables and the carbon to nitrogen ones as systems to be analyzed. By a linear transformation, two principal components were achieved, namely PC1 and PC2. There sults for the CO2 production, fluorescein production, and diesel oil removal efficiency were used, and overall variances always over 94% were obtained. The results showed that two microcosms stood out from the others, namely: - the microcosm with u% = 12% b.w. and C/N = 180,since it gave the highest amount of CO2 and fluorescein; - the microcosm with u% = 8% b.w. and C/N = 120,due to the highest diesel oil removal efficiency.

Application of the Principal Component Analysis (PCA) to aerobic biodegradation process / Raffa, CARLA MARIA; Vergnano, Andrea; Chiampo, Fulvia; Godio, Alberto. - In: INTERNATIONAL JOURNAL OF CHEMICAL AND ENVIRONMENTAL SCIENCES. - ISSN 2689-6389. - ELETTRONICO. - 2:2(2021), pp. 7-17.

Application of the Principal Component Analysis (PCA) to aerobic biodegradation process

Carla Maria Raffa;Andrea Vergnano;Fulvia Chiampo;Alberto Godio
2021

Abstract

The Principal Component Analysis (PCA) is a method widely used to process experimental data. The PCA aims to reduce the dimensionality of a data set composed of many interrelated variables, preserving the variation as much as possible. This can be achieved by transforming the data set to a new one, containing the principal components (PCs), which are uncorrelated, and which maximize the variance of the original data. In this study, the PCA was applied to experimental tests on aerobic bioremediation of soil polluted with diesel oil. Twelve microcosms (200 g of soil) were prepared, polluted with commercial diesel oil (70 g/kg of dry soil), and hydrated with a mineral salt solution suitable to stimulate the indigenous bacteria. The aerobic process for diesel oil degradation was studied changing two operative parameters, namely, water content (u%) and carbon to nitrogen ratio (C/N). Three values of water content (u% = 8%, 12% and 15% by weight) and four of carbon to nitrogen ratio (C/N = 60, 120, 180 and 300) were tested. The microcosms were monitored for 30 days by the measurements of these parameters: 1) the CO2 production, to evaluate the microbial respiration, 2) the fluorescein production, to check the microbial activity, and 3) the diesel oil concentration, to assess the pollutant degradation and calculate the removal efficiency. The Principal Component Analysis was done considering the water content values as variables and the carbon to nitrogen ones as systems to be analyzed. By a linear transformation, two principal components were achieved, namely PC1 and PC2. There sults for the CO2 production, fluorescein production, and diesel oil removal efficiency were used, and overall variances always over 94% were obtained. The results showed that two microcosms stood out from the others, namely: - the microcosm with u% = 12% b.w. and C/N = 180,since it gave the highest amount of CO2 and fluorescein; - the microcosm with u% = 8% b.w. and C/N = 120,due to the highest diesel oil removal efficiency.
File in questo prodotto:
File Dimensione Formato  
IJCAES 2021.pdf

non disponibili

Descrizione: Articolo
Tipologia: 2a Post-print versione editoriale / Version of Record
Licenza: Non Pubblico - Accesso privato/ristretto
Dimensione 500.53 kB
Formato Adobe PDF
500.53 kB Adobe PDF   Visualizza/Apri   Richiedi una copia
Pubblicazioni consigliate

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2875536