There are over 300 million acres of land in the United States for which underlying groundwater contamination is labeled a serious concern. There are many more acres for which underlying groundwater contamination, although not considered serious, threatens local groundwater quality and environmental health. The current cost of cleaning up contaminated groundwater using existing approaches to remediation is greater than the annual US Gross National Product. Thus, despite recent advances in the design of technologies for the insitu remediation of contaminated groundwater, research is still required that enables these technologies to become more cost effective and efficient. Insitu Air Sparging (IAS) is one remediation technology that has documented success for the cleanup of aquifers contaminated with Volatile Organic Compounds (VOCs), such as petroleum hydrocarbons. In fact, insitu air sparging is now thought to be the most widely used technology in the US for the remediation of hydrocarbon contaminated sites. Despite this, IAS design in practice remains largely empirical and based on information obtained from pilot scale tests involving observations surrounding a single sparge well. The research community has developed predictive models for IAS performance. However, the use of these models for design practice has been limited by their complexity and, more notably, their use of soil parameters that are not typically measured in practice. In addition, many of these models only consider a single sparge point, whereas IAS systems are engineered with multiple sparge points specifically to generate overlapping air-plumes.
The proposed work will develop a reliable, and practical, model to predict the air-flow patterns generated by multiplepoint sparging to improve the current design and optimization of IAS systems. The resulting model will be based on combined geo-centrifuge testing and the immersion method to enable direct visualization of air-plume development under capillary and fluid pressures that mimicked those in the field. Previous work resulted in an axi-symmetrical model that can predict air-flow patterns above a single sparge point in a homogeneous medium based upon input parameters typically measured in practice. The extension of the original model will enable predictions of three-dimensional air plume development above multiple sparge points in a heterogeneous medium. The researchers will validate the model using field data from pilot scale tests, and actual IAS operations.
This work will have considerable broad impact on the future design of IAS systems. Improvements in the effective application of remediation technologies, including IAS, will have direct benefit on future public and environmental health. The release of prior contaminated land for re-use also provides economic and social benefit to the country. The results will be disseminated through professional development seminars that we will run in Year 3 of the project. To encourage attendance by those in practice, we will limit each seminar to one day. The seminars will be run at cost. They will discuss the factors influencing air-flow during IAS, IAS design considerations, pilot testing, and monitoring requirements. They will also introduce the new model and provide guidance on its use in practice.
