Thermal monitoring of natural source zone depletion - Karimi Askarani, Kayvan, author; Sale, Thomas, advisor; Ham, Jay, committee member; Scalia, Joseph, committee member; Bailey, Ryan, committee member (Colorado State University. Libraries, 2019)
Natural Source Zone Depletion (NSZD) has emerged as a viable remedial approach for mature releases of petroleum liquids in soils and groundwater. Herein, petroleum liquids in soils and groundwater are referred to as LNAPL. In recent years, gradient, dynamic chamber, and carbon trap methods have been developed to quantify NSZD rates based on measuring the consumption of O2 or the generation of CO2 associated with biodegradation of LNAPL. A promising alternative approach to resolving LNAPL NSZD rates is real-time monitoring of subsurface temperatures. Transformation of temperature data to NSZD rates involves use of background-corrected temperature data, energy balances to resolve NSZD energy, and an estimate of heat produced through NSZD. All current computational methods for quantifying NSZD rates using temperature data have the drawbacks of: 1) incomplete energy balances 2) ignoring the effect of water table fluctuation, and 3) using linear extrapolations of temperature profiles to calculate thermal gradients. A regression algorithm is advanced to overcome the primary drawbacks of current computational methods that convert subsurface temperature data to NSZD rates using background correction. The regression algorithm is demonstrated using 42 million temperature measurements from a fuel terminal. An 8% difference between NSZD rates from the CO2 Trap method and the regression algorithm supported the validity of regression algorithm for estimation of NSZD rates using subsurface temperatures. In addition, seasonal behavior of NSZD rates is captured and correlated water content in shallow soils and depth to the water table. It is concluded that as the water table rises, the apparent NSZD rates increase, while larger water content in shallow soil causes a reduction in the apparent NSZD rates. Imperfection with background-correction approaches can be attributed to many factors, including differing infiltration of precipitation, vegetative cover, soil properties, and net solar radiation, at background versus impacted locations. Differences between the background location and the impacted area cause anomalous background-corrected temperatures leading to over/under estimation of NSZD rates. A new computational model is developed to eliminate the need for background correction of temperature data in calculating NSZD rates. Since the new model uses only the temperature data collected from the temperature sensors attached to a single solid stick, the model is referred to as the "single stick" method. The validity of the single stick model is evaluated using a numerical model and field temperature data. Agreement between the results from a numerical model with imposed heat fluxes, and estimated heat fluxes using temperature data derived from the numerical model, supports the validity of single stick model. In addition, a close match between single stick simulated temperatures using estimated heat fluxes and actual measure temperatures supports the validity of the single stick model. Furthermore, comparison of NSZD rates from the single stick model with the rates from background correction methods at background locations shows that the single stick model is the only algorithm that consistently provides near zero NSZD rates in clean areas. Lastly, per thermodynamic calculations and preliminary lab studies, it is observed that negative NSZD rates may be due to endothermic methanogenic process. Thermal conductivity is one of the key input parameters for all computational methods converting temperature data to NSZD rates. An integrated Internet of Things (IoT) instrument and computational model is developed to measure real-time in-situ thermal conductivity of soils. Favorable agreement between measure ex-situ and in-situ thermal conductivities values supports the validity of the demonstrated in-situ techniques for estimating thermal conductivities. Favorable attributes of the new in-situ methods include lower cost, automated data acquisition and an ability to acquire in-situ estimates of thermal conductivities through time. Overall, this work demonstrated that monitoring subsurface temperature is a viable technique to resolve NSZD rates for LNAPLs. A promising next step for evaluating the validity of thermal NSZD rates is to periodically collect and analyze cryogenic cores from field sites to independently validate NSZD rates. Also, further work is needed to better resolve NSZD thermodynamics.
Keywords: LNAPL; remediation; thermal monitoring; natural source zone depletion rate; biodegradation; subsurface temperature