• Energy Research

AbstractThe FLUXNET2015 dataset provides ecosystem-scale data on CO2, water, and energy exchange between the biosphere and the atmosphere, and other meteorological and biological measurements, from 212 sites around the globe (over 1500 site-years, up to and including year 2014). These sites, independently managed and operated, voluntarily contributed their data to create global datasets. Data were quality controlled and processed using uniform methods, to improve consistency and intercomparability across sites. The dataset is already being used in a number of applications, including ecophysiology studies, remote sensing studies, and development of ecosystem and Earth system models. FLUXNET2015 includes derived-data products, such as gap-filled time series, ecosystem respiration and photosynthetic uptake estimates, estimation of uncertainties, and metadata about the measurements, presented for the first time in this paper. In addition, 206 of these sites are for the first time distributed under a Creative Commons (CC-BY 4.0) license. This paper details this enhanced dataset and the processing methods, now made available as open-source codes, making the dataset more accessible, transparent, and reproducible.

AbstractWe report simulation experiments estimating the uncertainties in California regional fossil fuel and biosphere CO2 exchanges that might be obtained by using an atmospheric inverse modeling system driven by the combination of ground‐based observations of radiocarbon and total CO2, together with column‐mean CO2 observations from NASA's Orbiting Carbon Observatory (OCO‐2). The work includes an initial examination of statistical uncertainties in prior models for CO2 exchange, in radiocarbon‐based fossil fuel CO2 measurements, in OCO‐2 measurements, and in a regional atmospheric transport modeling system. Using these nominal assumptions for measurement and model uncertainties, we find that flask measurements of radiocarbon and total CO2 at 10 towers can be used to distinguish between different fossil fuel emission data products for major urban regions of California. We then show that the combination of flask and OCO‐2 observations yields posterior uncertainties in monthly‐mean fossil fuel emissions of ~5–10%, levels likely useful for policy relevant evaluation of bottom‐up fossil fuel emission estimates. Similarly, we find that inversions yield uncertainties in monthly biosphere CO2 exchange of ~6%–12%, depending on season, providing useful information on net carbon uptake in California's forests and agricultural lands. Finally, initial sensitivity analysis suggests that obtaining the above results requires control of systematic biases below approximately 0.5 ppm, placing requirements on accuracy of the atmospheric measurements, background subtraction, and atmospheric transport modeling.

AbstractWe present the first sector‐specific analysis of methane (CH4) emissions from the San Francisco Bay Area (SFBA) using CH4 and volatile organic compound (VOC) measurements from six sites during September – December 2015. We apply a hierarchical Bayesian inversion to separate the biological from fossil‐fuel (natural gas and petroleum) sources using the measurements of CH4 and selected VOCs, a source‐specific 1 km CH4 emission model, and an atmospheric transport model. We estimate that SFBA CH4 emissions are 166–289 Gg CH4/yr (at 95% confidence), 1.3–2.3 times higher than a recent inventory with much of the underestimation from landfill. Including the VOCs, 82 ± 27% of total posterior median CH4 emissions are biological and 17 ± 3% fossil fuel, where landfill and natural gas dominate the biological and fossil‐fuel CH4 of prior emissions, respectively.