scholarly journals Time-Domain Reflectometry (TDR) Monitoring at a Lab Scale of Aerobic Biological Processes in a Soil Contaminated by Diesel Oil

2019 ◽  
Vol 9 (24) ◽  
pp. 5487 ◽  
Author(s):  
Andrea Vergnano ◽  
Alberto Godio ◽  
Carla Maria Raffa ◽  
Fulvia Chiampo ◽  
Francesca Bosco ◽  
...  

This study aims to monitor the biological processes ongoing in a hydrocarbon polluted soil. The experiments were carried out at a laboratory scale by measuring the evolution of its geophysical electromagnetic parameters. Time-domain reflectometry (TDR) probes were used to measure dielectric permittivity and electrical conductivity in columns of sandy soil artificially contaminated with diesel oil (Voil/Vtot = 0.19). To provide aerobic conditions suitable for the growth of microorganisms, they were hydrated with Mineral Salt Medium for Bacteria. One mesocosm was aerated by injecting air from the bottom of the column, while the other had only natural aeration due to diffusion of air through the soil itself. The monitoring lasted 105 days. Geophysical measurements were supported by microbiological, gas chromatographic analyses, and scanning electron microscope (SEM) images. Air injection heavily influenced the TDR monitoring, probably due to the generation of air bubbles around the probe that interfered with the probe–soil coupling. Therefore, the measurement accuracy of geophysical properties was dramatically reduced in the aerated system, although biological analyses showed that aeration strongly supports microbial activity. In the non-aerated system, a slight (2%) linear decrease of dielectric permittivity was observed over time. Meanwhile, the electrical conductivity initially decreased, then increased from day 20 to day 45, then decreased again by about 30%. We compared these results with other researches in recent literature to explain the complex biological phenomena that can induce variations in electrical parameters in a contaminated soil matrix, from salt depletion to pore clogging.

Sensors ◽  
2018 ◽  
Vol 18 (12) ◽  
pp. 4403 ◽  
Author(s):  
Basem Aljoumani ◽  
Jose Sanchez-Espigares ◽  
Gerd Wessolek

Despite the importance of computing soil pore water electrical conductivity (σp) from soil bulk electrical conductivity (σb) in ecological and hydrological applications, a good method of doing so remains elusive. The Hilhorst concept offers a theoretical model describing a linear relationship between σb, and relative dielectric permittivity (εb) in moist soil. The reciprocal of pore water electrical conductivity (1/σp) appears as a slope of the Hilhorst model and the ordinary least squares (OLS) of this linear relationship yields a single estimate ( 1 / σ p ^ ) of the regression parameter vector (σp) for the entire data. This study was carried out on a sandy soil under laboratory conditions. We used a time-varying dynamic linear model (DLM) and the Kalman filter (Kf) to estimate the evolution of σp over time. A time series of the relative dielectric permittivity (εb) and σb of the soil were measured using time domain reflectometry (TDR) at different depths in a soil column to transform the deterministic Hilhorst model into a stochastic model and evaluate the linear relationship between εb and σb in order to capture deterministic changes to (1/σp). Applying the Hilhorst model, strong positive autocorrelations between the residuals could be found. By using and modifying them to DLM, the observed and modeled data of εb obtain a much better match and the estimated evolution of σp converged to its true value. Moreover, the offset of this linear relation varies for each soil depth.


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