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We developed the Leakage Risk Monetization Model (LRiMM) which integrates simulation of CO2 leakage from geologic CO2 storage reservoirs with estimation of monetized leakage risk (MLR). Using geospatial data, LRiMM quantifies financial responsibility if leaked CO2 or brine interferes with subsurface resources, and estimates the MLR reduction achievable by remediating leaks. We demonstrate LRiMM with simulations of 30 years of injection into the Mt. Simon sandstone at two locations that differ primarily in their proximity to existing wells that could be leakage pathways. The peak MLR for the site nearest the leakage pathways ($7.5/tCO2) was 190x larger than for the farther injection site, illustrating how careful siting would minimize MLR in heavily used sedimentary basins. Our MLR projections are at least an order of magnitude below overall CO2 storage costs at well-sited locations, but some stakeholders may incur substantial costs. Reliable methods to detect and remediate leaks could further minimize MLR. For both sites, the risk of CO2 migrating to potable aquifers or reaching the atmosphere was negligible due to secondary trapping, whereby multiple impervious sedimentary layers trap CO2 that has leaked through the primary seal of the storage formation.

A non-traditional methodology of polling in small areas, called bellwethers, improves the accuracy of forecasts drawn from a large area. Bellwether areas are small government units (such as cities or counties) which exhibit voting patterns close to actual election outcomes in the larger areas of which they are a part (such as states). The bellwether methodology of one polling organization is described in detail using data from the 2012 US Senate election in Massachusetts. An overview of the performance of the bellwether methodology is provided. In use at Suffolk University Political Research Center since 2003, bellwethers combined with state polls correctly forecast election outcomes in 97% of trials where a clear winner could be determined (i.e., no ties). The contribution of this work is to offer an open-source methodology for improving accuracy in election forecasting. [ABSTRACT FROM AUTHOR]

The article presents an essay related to efforts of the federal, state and local governments of the U.S. to collect energy consumption data to improved energy efficiency. Topics discussed include the consequences of the lack of data including difficult energy management; benefits of collecting energy consumption data including easy quantification of actual greenhouse gas emissions of cities; and developing policies governing energy consumption data.