title: An insight into soil bioremediation through respirometry.
abstract: 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.
authors.affiliation: Faculty of Engineering of University of Porto, Rua Roberto Frias 4200-465 Porto, Portugal. afiuza@fe.up.pt
authors.forename: António M A
authors.initials: AM
authors.lastname: Fiúza
authors.forename: M Cristina C
authors.initials: MC
authors.lastname: Vila
mesh_terms: 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
chemical_list: D012989:Soil Pollutants; D002245:Carbon Dioxide; D010100:Oxygen