Author: Ari A. Zwick
Institution: University of Illinois at Chicago
Carbon capture and sequestration (CCS) technologies are currently being researched as a potential component of a global portfolio of technologies to help reduce anthropogenic emissions of carbon dioxide (CO2) to the atmosphere. In China, currently a leading emitter of CO2 and a potentially critical player in future carbon emissions reduction strategies, it is important to evaluate the economic feasibility of CCS to understand its potential for large-scale deployment. This paper describes the development of a high resolution geospatial model to assist in efforts to estimate the construction costs of pipelines for transport of CO2from sources to storage sites. The model assigns relative weights to geographic features throughout mainland China to form a relative prioritization map that may be used to model pipeline routing along paths that are likely to represent the lowest cost paths. The final routing priority map (RPM) differentiates between areas according to their relative cost for routing from sources to sinks. The RPM represents the weighted combination of all overlapping geographic and cultural features included in the model. By using the RPM in conjunction with a routing protocol, grid cells with low priority values (i.e., those for which construction and/or societal costs would be higher) would be avoided in favor of cells with higher priority values, all else equal. This mode of estimating least-cost pipeline routing could represent a significant enhancement to existing methodologies used to estimate CO2 transport costs for CCS in China.
The Journal of Young Investigators is not affiliated with the US Department of Energy. This paper was written by a student intern with the Department of Energy and does not constitute a declarative position of either the Department of Energy or the Journal of Young Investigators.