Abstract
Abstract CO2 sources vary widely in emission characteristics including concentration, pressure, contaminants and intermittency. In addition, the ability to initiate carbon capture and storage (CCS) of particular sources are influenced by geographic location, land use, regulatory environment, and the proximity to potential geologic storage sites that can provide safe, secure storage over long periods of time (such as oil and gas fields, deep coal seams and saline aquifers). Differences in these multiple characteristics can dramatically impact the cost of capture and geologic storage. Large stationary anthropogenic sources of CO2 that provide the best opportunities for CCS include cement kilns, ethanol plants, natural gas plants, refineries, ammonia manufacturing plants and power generation (coal and natural gas). The United States Department of Energy's Regional Carbon Sequestration Partnerships (RCSPs) have generated data that provides the foundation of a carbon cyber-infrastructure (CCI). This geospatial data is available online and can be used by the private and public sectors to improve the implementation of CCS for a single CO2 emission source or group of sources. An integrated learning approach using large amounts of geospatial data is proposed to evaluate CO2 sources in relation to an integrated system of capture, transport and geologic storage will be discussed. Use of geospatial data for source and geologic storage sites in southeast Kansas provides an example of integration within a changing regulatory and economic environment of multiple industrial sources of CO2 emissions of widely varying characteristics with multiple stacked geologic storage opportunities.
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