Abstract. We present 60 years of 14 CO 2

This article describes a new capability for high-precision 14 C measurement of CO 2 from air at the Rafter Radiocarbon Laboratory, GNS Science, New Zealand. We evaluate the short-term within-wheel repeatability and long-term between-wheel repeatability from measurements of multiple aliquots of control materials sourced from whole air. Samples are typically measured to 650,000 14 C counts, providing a nominal accelerator mass spectrometry (AMS) statistical uncertainty of 1.3‰. No additional uncertainty is required to explain the within-wheel variability. An additional uncertainty factor is needed to explain the long-term repeatability spanning multiple measurement wheels, bringing the overall repeatability to 1.8‰, comparable to other laboratories measuring air materials to high precision. This additional uncertainty factor appears to be due to variability in the measured 14 C content of OxI primary standard targets, likely from the combustion process. We observe an offset of 1.4‰ in our samples relative to those measured by the University of Colorado INSTAAR, comparable to interlaboratory offsets observed in recent intercomparison exercises.

Abstract. We use the Kapuni Gas Treatment Plant to examine methodologies for atmospheric monitoring of point source fossil fuel CO 2 (CO 2 ff) emissions. The Kapuni plant, located in rural New Zealand, removes CO 2 from locally extracted natural gas and vents that CO 2 to the atmosphere, at a rate of ∼ 0.1 Tg carbon per year. The plant is located in a rural dairy farming area, with no other significant CO 2 ff sources nearby, but large, diurnally varying, biospheric CO 2 fluxes from the surrounding highly productive agricultural grassland. We made flask measurements of CO 2 and 14 CO 2 (from which we derive the CO 2 ff component) and in situ measurements of CO 2 downwind of the Kapuni plant, using a Helikite to sample transects across the emission plume from the surface up to 100 m above ground level. We also determined the surface CO 2 ff content averaged over several weeks from the 14 C content of grass samples collected from the surrounding area. We use the WindTrax plume dispersion model to compare the atmospheric observations with the emissions reported by the Kapuni plant, and to determine how well atmospheric measurements can constrain the emissions. The model has difficulty accurately capturing the fluctuations and short-term variability in the Helikite samples, but does quite well in representing the observed CO 2 ff in 15 min averaged surface flask samples and in ∼ one week integrated CO 2 ff averages from grass samples. In this pilot study, we found that using grass samples, the modeled and observed CO 2 ff emissions averaged over one week agreed to within 30 %. The results imply that greater verification accuracy may be achieved by including more detailed meteorological observations and refining 14 C sampling strategies.

Independent estimates of fossil fuel CO 2 (CO 2 ff) emissions are key to ensuring that emission reductions and regulations are effective and provide needed transparency and trust. Point source emissions are a key target because a small number of power plants represent a large portion of total global emissions. Currently, emission rates are known only from self-reported data. Atmospheric observations have the potential to meet the need for independent evaluation, but useful results from this method have been elusive, due to challenges in distinguishing CO 2 ff emissions from the large and varying CO 2 background and in relating atmospheric observations to emission flux rates with high accuracy. Here we use time-integrated observations of the radiocarbon content of CO 2 ( 14 CO 2 ) to quantify the recently added CO 2 ff mole fraction at surface sites surrounding a point source. We demonstrate that both fast-growing plant material (grass) and CO 2 collected by absorption into sodium hydroxide solution provide excellent time-integrated records of atmospheric 14 CO 2 . These timeintegrated samples allow us to evaluate emissions over a period of days to weeks with only a modest number of measurements. Applying the same time integration in an atmospheric transport model eliminates the need to resolve highly variable short-term turbulence. Together these techniques allow us to independently evaluate point source CO 2 ff emission rates from atmospheric observations with uncertainties of better than 10%. This uncertainty represents an improvement by a factor of 2 over current bottom-up inventory estimates and previous atmospheric observation estimates and allows reliable independent evaluation of emissions.fossil fuel CO 2 | radiocarbon | greenhouse gas emissions | emission verification F ossil fuel carbon dioxide (CO 2 ff) emissions are the main driver of the increasing atmospheric CO 2 mole fraction (1). Of the ∼10 GtC/y of CO 2 ff now emitted globally, the largest 1,000 power plants emit 22% of the total (2). Thus, large power plants are an obvious target for regulating and reducing CO 2 ff emissions. They are already subject to regulation or emission trading schemes in some regions (3, 4), and the Paris Agreement requires transparency in emission reporting (5). The success of such regulations requires the ability to reliably monitor and verify emissions, which is currently achieved through "bottom-up" inventory data, in which CO 2 ff emission estimates are based on self-reported fuel use and carbon content statistics (6). Uncertainties in this method are on the order of 20% for individual power plants (7). Some studies suggest significant errors in emission reporting may already be occurring (8, 9) and under a regulatory environment, there may be incentive for deliberate misreporting. Independent, objective evaluation of emissions is needed to establish trust and ensure that self-reported bottom-up emission rates are unbiased (5, 10, 11). As power plants represent such a large proportion of total emissions, reducing t...

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