Prediction and Understanding of Dynamics of Naturally & Artificially Released CO2 into a Vadose Zone using a Numerical Simulator

As the atmospheric CO₂ concentration is increasing, the international community have adopted the Geological Carbon Storage is one of the ways to reduce CO₂. However, CO₂ in targeted storage site can be released through unexpected faults or abandoned wells. In the event that abundant CO₂ is released to the surface, elevated CO₂ concentration will significantly damage the surface water and ecological system. Therefore, detecting initial flux of released CO₂ is important. However, when monitoring CO₂ flux, there also exist the natural background CO₂ produced by the respiration of plants and microorganisms. Hence, prediction of the natural CO₂ level at storage site is practical for making a distinction between background CO₂ fluctuation and anthropogenic release of CO₂.

In Eumseong, Republic of Korea, controlled CO₂ release site was developed by the Korea CO₂ Storage Environmental Management (K-COSEM) Research Center. CO₂ was released from the 50 m length PVC pipe buried at 2.5 m-depth, and CO₂ fluxes were monitored. Extra parameters such as meteorological data, soil moisture and temperature were monitored at the same time. Two simulators were used to simulate the dynamics of CO₂ at the unsaturated zone: HYDRUS with SOILCO2 package for natural background CO₂, and TOUGH3 EOS7C for anthropogenic CO₂ release. Furthermore, simulated surface CO₂ fluxes were compared with field-observed data to validate the CO₂ transport model and evaluate CO₂ release process with more precision.

Our research concluded that, without the CO₂ release, Hydrus-SOILCO2 simulator provided more precise prediction of the background soil-surface CO₂ flux. In addition, both measured and simulated data identified atmospheric temperature and precipitation to be major environmental factors controlling the CO₂ fluxes. In addition, the study demonstrated that the dynamics of anthropogenic CO₂ release at the unsaturated zone can be represented by TOUGH3 EOS7C.

This research was supported by Basic Science Research Project through the Korea Environmental Industry Technology Institute (KEITI) funded by the Ministry of Environment (Grant Number: 2018001810004)