An insight into soil bioremediation through respirometry.
Respirometric tests on a soil contaminated by crude oil were performed. Continuous measurements of oxygen and carbon dioxide concentrations and temperature in the soil atmosphere resulted in a large volume of data. Time series and system identification theories were used to analyze data as a biological signal, allowing us to detect some particularities related to daily cycles of the studied variables as well as its time relationships through autocorrelation and cross-correlation functions. Using system identification techniques, it was possible to build black box models, namely autoregressive moving average models which enable to predict oxygen concentration at the outlet in a good agreement with measured data.
Fiúza
António M A
AM
Faculty of Engineering of University of Porto, Rua Roberto Frias 4200-465 Porto, Portugal. afiuza@fe.up.pt
Vila
M Cristina C
MC
D001673:Biodegradation, Environmental; D002245:Carbon Dioxide / Q000032:analysis*; D004784:Environmental Monitoring; D008962:Models, Theoretical; D010100:Oxygen / Q000032:analysis*; D012989:Soil Pollutants / Q000378:metabolism*; D013696:Temperature
D012989:Soil Pollutants; D002245:Carbon Dioxide; D010100:Oxygen