Publications

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Journal Article
Graven, H, Fischer ML, Lueker T, Jeong S, Guilderson TP, Keeling RF, Bambha R, Brophy K, Callahan W, Cui X, Frankenberg C, Gurney KR, LaFranchi BW, Lehman SJ, Michelsen H, Miller JB, Newman S, Paplawsky W, Parazoo NC, Sloop C, Walker SJ.  2018.  Assessing fossil fuel CO2 emissions in California using atmospheric observations and models. Environmental Research Letters. 13   10.1088/1748-9326/aabd43   AbstractWebsite

Analysis systems incorporating atmospheric observations could provide a powerful tool for validating fossil fuel CO2 (ffCO(2)) emissions reported for individual regions, provided that fossil fuel sources can be separated from other CO2 sources or sinks and atmospheric transport can be accurately accounted for. We quantified ffCO(2) by measuring radiocarbon (C-14) in CO2, an accurate fossil-carbon tracer, at nine observation sites in California for three months in 2014-15. There is strong agreement between the measurements and ffCO(2) simulated using a high-resolution atmospheric model and a spatiotemporally-resolved fossil fuel flux estimate. Inverse estimates of total in-state ffCO(2) emissions are consistent with the California Air Resources Board's reported ffCO(2) emissions, providing tentative validation of California's reported ffCO(2) emissions in 2014-15. Continuing this prototype analysis system could provide critical independent evaluation of reported ffCO(2) emissions and emissions reductions in California, and the system could be expanded to other, more data-poor regions.

Rodenbeck, C, Zaehle S, Keeling R, Heimann M.  2018.  How does the terrestrial carbon exchange respond to inter-annual climatic variations? A quantification based on atmospheric CO2 data Biogeosciences. 15:2481-2498.   10.5194/bg-15-2481-2018   AbstractWebsite

The response of the terrestrial net ecosystem exchange (NEE) of CO2 to climate variations and trends may crucially determine the future climate trajectory. Here we directly quantify this response on inter-annual timescales by building a linear regression of inter-annual NEE anomalies against observed air temperature anomalies into an atmospheric inverse calculation based on long-term atmospheric CO2 observations. This allows us to estimate the sensitivity of NEE to inter-annual variations in temperature (seen as a climate proxy) resolved in space and with season. As this sensitivity comprises both direct temperature effects and the effects of other climate variables co-varying with temperature, we interpret it as "inter-annual climate sensitivity". We find distinct seasonal patterns of this sensitivity in the northern extratropics that are consistent with the expected seasonal responses of photosynthesis, respiration, and fire. Within uncertainties, these sensitivity patterns are consistent with independent inferences from eddy covariance data. On large spatial scales, northern extratropical and tropical interannual NEE variations inferred from the NEE-T regression are very similar to the estimates of an atmospheric inversion with explicit inter-annual degrees of freedom. The results of this study offer a way to benchmark ecosystem process models in more detail than existing effective global climate sensitivities. The results can also be used to gap-fill or extrapolate observational records or to separate inter-annual variations from longer-term trends.

Cui, YY, Vijayan A, Falk M, Hsu YK, Yin DZ, Chen XM, Zhao Z, Avise J, Chen YJ, Verhulst K, Duren R, Yadav V, Miller C, Weiss R, Keeling R, Kim J, Iraci LT, Tanaka T, Johnson MS, Kort EA, Bianco L, Fischer ML, Stroud K, Herner J, Croes B.  2019.  A multiplatform inversion estimation of statewide and regional methane emissions in California during 2014-2016. Environmental Science & Technology. 53:9636-9645.   10.1021/acs.est.9b01769   AbstractWebsite

California methane (CH4) emissions are quantified for three years from two tower networks and one aircraft campaign. We used backward trajectory simulations and a mesoscale Bayesian inverse model, Mbring ratios (VI ' initialized by three inventories, to achieve the emission quantification. Results show total statewide CH4 emissions of 2.05 +/- 0.26 (at 95% confidence) Tg/yr, which is 1.14 to 1.47 times greater than the anthropogenic emission estimates by California Air Resource Board (GARB). Some of differences could be biogenic emissions, superemitter point sources, and other episodic emissions which may not be completely included in the CARB inventory. San Joaquin Valley (SJV) has the largest CH4 emissions (0.94 +/- 0.18 Tg/yr), followed by the South Coast Air Basin, the Sacramento Valley, and the San Francisco Bay Area at 0.39 +/- 0.18, 0.21 +/- 0.04, and 0.16 +/- 0.05 Tg/yr, respectively. The dairy and oil/gas production sources in the SJV contribute 0.44 +/- 0.36 and 0.22 +/- 0.23 Tg CH4/yr, respectively. This study has important policy implications for regulatory programs, as it provides a thorough multiyear evaluation of the emissions inventory using independent atmospheric measurements and investigates the utility of a complementary multiplatform approach in understanding the spatial and temporal patterns of CH4 emissions in the state and identifies opportunities for the expansion and applications of the monitoring network.