The reduction of anthropogenic methane emissions is a priority due to its potent global warming potential. Radiocarbon (14C) can distinguish between methane from natural biogenic and fossil fuel sources, however, the analysis of methane 14C by conventional accelerator mass spectrometry (AMS) techniques is demanding. At SUERC, a prototype positive ion mass spectrometer (PIMS) is set up to directly analyze 14C in methane with minimal sample preparation. Methane gas was mixed with a stoichiometric amount of oxygen in an open split and admitted directly into the source. A series of modern, blank and unknown methane samples were clearly distinguishable by their 14C/13C raw ratios. The collision cell gas flowrate was then increased to lower the limit of detection. We obtained a corrected 14C/13C raw ratio of less than 2 × 10–13 for blank fossil methane which corresponds to a radiocarbon age greater than 50 kyr. Modern biogenic methane had a measured 14C/13C raw ratio approaching 1 × 10–10 which is consistent with the nominal value of contemporary atmospheric methane. These first results indicate that PIMS has the potential to be a valuable new analytical technique for screening the 14C content of biogas and in climate research studies.

The financial market assumptions of the Pension Benefit Guaranty Corporation (PBGC)'s Pension Insurance Modeling System model are critical inputs to simulations for most apparent uses of the system. They currently appear to be based on a reduced form, ‘classical’ approach to assessing and forecasting the distribution of returns on various classes of input assets, allowing for a fairly sophisticated and useful approach to understanding simulated distributions of potential pension insurance outcomes as well as the net financial status of the PBGC. This technical note discusses some of the capital market side assumptions utilized in the model. It also comments on important related assumptions including the assumed asset allocations of insured plans, making suggestion for possible modification of input assumptions of the model to reflect time variation in financial market return behavior as well as time variation in observed plan allocations.