We report national scale estimates of CO₂ emissions from fossil-fuel combustion and cement production in the United States based directly on atmospheric observations, using a dual-tracer inverse modeling framework and CO₂ and [Formula: see text] measurements obtained primarily from the North American portion of the National Oceanic and Atmospheric Administration's Global Greenhouse Gas Reference Network. The derived US national total for 2010 is 1,653 ± 30 TgC yr^-1 with an uncertainty ([Formula: see text]) that takes into account random errors associated with atmospheric transport, atmospheric measurements, and specified prior CO₂ and ¹⁴C fluxes. The atmosphere-derived estimate is significantly larger ([Formula: see text]) than US national emissions for 2010 from three global inventories widely used for CO₂ accounting, even after adjustments for emissions that might be sensed by the atmospheric network, but which are not included in inventory totals. It is also larger ([Formula: see text]) than a similarly adjusted total from the US Environmental Protection Agency (EPA), but overlaps EPA's reported upper 95% confidence limit. In contrast, the atmosphere-derived estimate is within [Formula: see text] of the adjusted 2010 annual total and nine of 12 adjusted monthly totals aggregated from the latest version of the high-resolution, US-specific "Vulcan" emission data product. Derived emissions appear to be robust to a range of assumed prior emissions and other parameters of the inversion framework. While we cannot rule out a possible bias from assumed prior Net Ecosystem Exchange over North America, we show that this can be overcome with additional [Formula: see text] measurements. These results indicate the strong potential for quantification of US emissions and their multiyear trends from atmospheric observations.

We use global airborne observations of propane (C₃H₈) and ethane (C₂H₆) from the Atmospheric Tomography (ATom) and HIAPER Pole-to-Pole Observations (HIPPO), as well as U.S.-based aircraft and tower observations by NOAA and from the NCAR FRAPPE campaign as tracers for emissions from oil and gas operations. To simulate global mole fraction fields for these gases, we update the default emissions' configuration of C₃H₈ used by the global chemical transport model, GEOS-Chem v13.0.0, using a scaled C₂H₆ spatial proxy. With the updated emissions, simulations of both C₃H₈ and C₂H₆ using GEOS-Chem are in reasonable agreement with ATom and HIPPO observations, though the updated emission fields underestimate C₃H₈ accumulation in the arctic wintertime, pointing to additional sources of this gas in the high latitudes (e.g., Europe). Using a Bayesian hierarchical model, we estimate global emissions of C₂H₆ and C₃H₈ from fossil fuel production in 2016-2018 to be 13.3 ± 0.7 (95% CI) and 14.7 ± 0.8 (95% CI) Tg/year, respectively. We calculate bottom-up hydrocarbon emission ratios using basin composition measurements weighted by gas production and find their magnitude is higher than expected and is similar to ratios informed by our revised alkane emissions. This suggests that emissions are dominated by pre-processing activities in oil-producing basins.

Changes in atmospheric CO₂ variability during the twenty-first century may provide insight about ecosystem responses to climate change and have implications for the design of carbon monitoring programs. This paper describes changes in the three-dimensional structure of atmospheric CO₂ for several representative concentration pathways (RCPs 4.5 and 8.5) using the Community Earth System Model–Biogeochemistry (CESM1-BGC). CO₂ simulated for the historical period was first compared to surface, aircraft, and column observations. In a second step, the evolution of spatial and temporal gradients during the twenty-first century was examined. The mean annual cycle in atmospheric CO₂ was underestimated for the historical period throughout the Northern Hemisphere, suggesting that the growing season net flux in the Community Land Model (the land component of CESM) was too weak. Consistent with weak summer drawdown in Northern Hemisphere high latitudes, simulated CO₂ showed correspondingly weak north–south and vertical gradients during the summer. In the simulations of the twenty-first century, CESM predicted increases in the mean annual cycle of atmospheric CO₂ and larger horizontal gradients. Not only did the mean north–south gradient increase due to fossil fuel emissions, but east–west contrasts in CO₂ also strengthened because of changing patterns in fossil fuel emissions and terrestrial carbon exchange. In the RCP8.5 simulation, where CO₂ increased to 1150 ppm by 2100, the CESM predicted increases in interannual variability in the Northern Hemisphere midlatitudes of up to 60% relative to present variability for time series filtered with a 2–10-yr bandpass. Such an increase in variability may impact detection of changing surface fluxes from atmospheric observations.

Long-term atmospheric CO₂ mole fraction and δ¹³CO₂ observations over North America document persistent responses to the El Niño-Southern Oscillation. We estimate these responses corresponded to 0.61 (0.45 to 0.79) PgC year^-1 more North American carbon uptake during El Niño than during La Niña between 2007 and 2015, partially offsetting increases of net tropical biosphere-to-atmosphere carbon flux around El Niño. Anomalies in derived North American net ecosystem exchange (NEE) display strong but opposite correlations with surface air temperature between seasons, while their correlation with water availability was more constant throughout the year, such that water availability is the dominant control on annual NEE variability over North America. These results suggest that increased water availability and favorable temperature conditions (warmer spring and cooler summer) caused enhanced carbon uptake over North America near and during El Niño.

U.S. national and regional emissions of HFC-134a are derived for 20082012 based on atmospheric observations from ground and aircraft sites across the U.S. and a newly developed regional inverse model. Synthetic data experiments were first conducted to optimize the model assimilation design and to assess model-data mismatch errors and prior flux error covariances computed using a maximumlikelihood estimation technique. The synthetic data experiments also tested the sensitivity of derived national and regional emissions to a range of assumed prior emissions, with the goal of designing a system that was minimally reliant on the prior. We then explored the influence of additional sources of error in inversions with actual observations, such as those associated with background mole fractions and transport uncertainties. Estimated emissions of HFC-134a range from 52 to 61 Gg yr-1 for the contiguous U.S. during 20082012 for inversions using air transport from Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model driven by the 12km resolution meteorogical data from North American Mesoscale Forecast System (NAM12) and all tested combinations of prior emissions and background mole fractions. Estimated emissions for 20082010 were 20% lower when specifying alternative transport from Stochastic Time-Inverted Lagrangian Transport (STILT) model driven by the Weather Research and Forecasting (WRF) meteorology. Our estimates (for HYSPLIT-NAM12) are consistent with annual emissions reported by U.S. Environmental Protection Agency for the full study interval. The results suggest a 1020% drop in U.S. national HFC-134a emission in 2009 coincident with a reduction in transportation-related fossil fuel CO2 emissions, perhaps related to the economic recession. All inversions show seasonal variation in national HFC-134a emissions in all years, with summer emissions greater than winter emissions by 2050%.

Ozone depleting substances (ODSs) controlled by the Montreal Protocol are potent greenhouse gases (GHGs), as are their substitutes, the hydrofluorocarbons (HFCs). Here we provide for the first time a comprehensive estimate of U.S. emissions of ODSs and HFCs based on precise measurements in discrete air samples from across North America and in the remote atmosphere. Derived emissions show spatial and seasonal variations qualitatively consistent with known uses and largely confirm U.S. Environmental Protection Agency (EPA) national emissions inventories for most gases. The measurement-based results further indicate a substantial decline of ODS emissions from 2008 to 2014, equivalent to ~50% of the CO2-equivalent decline in combined emissions of CO2 and all other long-lived GHGs inventoried by the EPA for the same period. Total estimated CO2-equivalent emissions of HFCs were comparable to the sum of ODS emissions in 2014, but can be expected to decline in the future in response to recent policy measures.

We describe a method for removing systematic biases of column-averaged dry air mole fractions of CO2 (XCO2) and CH4 (XCH4) derived from short-wavelength infrared (SWIR) spectra of the Greenhouse gases Observing SATellite (GOSAT). We conduct correlation analyses between the GOSAT biases and simultaneously retrieved auxiliary parameters. We use these correlations to bias correct the GOSAT data, removing these spurious correlations. Data from the Total Carbon Column Observing Network (TCCON) were used as reference values for this regression analysis. To evaluate the effectiveness of this correction method, the tnzuncorrected/corrected GOSAT data were compared to independent XCO2 and XCH4 data derived from aircraft measurements taken for the Comprehensive Observation Network for TRace gases by AIrLiner (CONTRAIL) project, the National Oceanic and Atmospheric Administration (NOAA), the US Department of Energy (DOE), the National Institute for Environmental Studies (NIES), the Japan Meteorological Agency (JMA), the HIAPER Pole-to-Pole observations (HIPPO) program, and the GOSAT validation aircraft observation campaign over Japan. These comparisons demonstrate that the empirically derived bias correction improves the agreement between GOSAT XCO2/XCH4 and the aircraft data. Finally, we present spatial distributions and temporal variations of the derived GOSAT biases.