The global burden of atmospheric methane has been increasing over the past decade, but the causes are not well understood. National inventory estimates from the U.S. Environmental Protection Agency ...indicate no significant trend in U.S. anthropogenic methane emissions from 2002 to present. Here we use satellite retrievals and surface observations of atmospheric methane to suggest that U.S. methane emissions have increased by more than 30% over the 2002–2014 period. The trend is largest in the central part of the country, but we cannot readily attribute it to any specific source type. This large increase in U.S. methane emissions could account for 30–60% of the global growth of atmospheric methane seen in the past decade.
Key Points
We identify a large increase in U.S. methane emissions over the past decade
Increase occurred during a time when emission inventories indicate no change in U.S. emissions
The U.S. could account for 30‐60% of the global increase in atmospheric methane over the past decade
We use 2009-2011 space-borne methane observations from the Greenhouse Gases Observing SATellite (GOSAT) to estimate global and North American methane emissions with 4 degree 5 degree and up to 50 km ...50 km spatial resolution, respectively. GEOS-Chem and GOSAT data are first evaluated with atmospheric methane observations from surface and tower networks (NOAA/ESRL, TCCON) and aircraft (NOAA/ESRL, HIPPO), using the GEOS-Chem chemical transport model as a platform to facilitate comparison of GOSAT with in situ data. This identifies a high-latitude bias between the GOSAT data and GEOS-Chem that we correct via quadratic regression. Our global adjoint-based inversion yields a total methane source of 539 Tg a-1 with some important regional corrections to the EDGARv4.2 inventory used as a prior. Results serve as dynamic boundary conditions for an analytical inversion of North American methane emissions using radial basis functions to achieve high resolution of large sources and provide error characterization. We infer a US anthropogenic methane source of 40.2-42.7 Tg a-1, as compared to 24.9-27.0 Tg a-1 in the EDGAR and EPA bottom-up inventories, and 30.0-44.5 Tg a-1 in recent inverse studies. Our estimate is supported by independent surface and aircraft data and by previous inverse studies for California. We find that the emissions are highest in the southern-central US, the Central Valley of California, and Florida wetlands; large isolated point sources such as the US Four Corners also contribute. Using prior information on source locations, we attribute 29-44 % of US anthropogenic methane emissions to livestock, 22-31 % to oil/gas, 20 % to landfills/wastewater, and 11-15 % to coal. Wetlands contribute an additional 9.0-10.1 Tg a-1.
•CO2 flux measurement errors (IRGASON & EC150) scale with kinematic temperature flux.•Relative errors are most pronounced when true CO2 flux is small and heat flux large.•Using a fast-response air ...temperature to scale CO2 absorption minimizes bias.•Agreement between open- and closed-path IRGA CO2 fluxes is substantially improved.•Fast-instead of slow-response air temperature should be used to scale CO2 absorption.
Across a global network of eddy covariance flux towers, two relatively new open-path infrared gas analyzers (IRGAs), the IRGASON and the EC150, are increasingly used to measure net carbon dioxide (CO2) fluxes (Fc_OP). Differences in net CO2 fluxes derived from open- and closed-path IRGAs in general remain poorly constrained. In particular, the performance of the IRGASON and the EC150 for measuring Fc_OP has not been characterized yet. These IRGAs measure CO2 absorption, which is scaled with air temperature and pressure before converting it to instantaneous CO2 density. This sensor-internal conversion is based on a slow-response thermistor air temperature measurement. Here, we test if the high-frequency temperature attenuation causes selectively systematic Fc_OP errors that scale with kinematic temperature fluxes. First, we examine the relationship between wintertime Fc_OP and kinematic temperature fluxes for eight northern ecosystems. Second, we investigate how residuals between Fc_OP and CO2 fluxes from co-located closed-path IRGAs (FC_CP) are related to kinematic temperature fluxes for three different ecosystem types (i.e., boreal forest, grassland, and irrigated cropland). We find that kinematic temperature fluxes, but not mean ambient air temperatures or CO2 flux regime, consistently determine the absolute magnitude of Fc_OP errors. This selectively systematic bias causes the most pronounced relative Fc_OP errors to occur when “true” CO2 fluxes are low and kinematic temperature fluxes are high (e.g., northern ecosystems during the winter). The smallest relative errors occur during periods with large “true” CO2 fluxes and low kinematic temperature fluxes. To address this bias, we replace the slow-response air temperature in the absorption-to-CO2 density conversion with a fast-response air temperature derived from sonic anemometer measurements. The use of the fast-response air temperature improves the agreement between half-hourly Fc_OP and FC_CP for all open- versus closed-path IRGA comparisons. Additionally, cumulative Fc_OP and Fc_CP sums are more comparable as differences drop from 63 %–13 % to 20 %–8 %. The improved IRGASON and EC150 performance enhances the ability and confidence to synthesize flux measurements across multiple sites including these two relatively new IRGAs.
Column-averaged dry air mole fractions of carbon dioxide (XCO2 ) retrieved from Greenhouse gases Observing SATellite (GOSAT) Short-Wavelength InfraRed (SWIR) observations were validated with aircraft ...measurements by 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 HIAPER Pole-to-Pole Observations (HIPPO) program, and the GOSAT validation aircraft observation campaign over Japan. To calculate XCO2 based on aircraft measurements (aircraft-based XCO2 ), tower measurements and model outputs were used for additional information near the surface and above the tropopause, respectively. Before validation, we investigated the impacts of GOSAT SWIR column averaging kernels (CAKs) and the shape of a priori profiles on the aircraft-based XCO2 calculation. The differences between aircraft-based XCO2 with and without the application of GOSAT CAK were evaluated to be less than ±0.4 ppm at most, and less than ±0.1 ppm on average. Therefore, we concluded that the GOSAT CAK produces only a minor effect on the aircraft-based XCO2 calculation in terms of the overall uncertainty of GOSAT XCO2 . We compared GOSAT data retrieved within ±2 or ±5° latitude/longitude boxes centered at each aircraft measurement site to aircraft-based data measured on a GOSAT overpass day. The results indicated that GOSAT XCO2 over land regions agreed with aircraft-based XCO2 , except that the former is biased by -0.68 ppm (-0.99 ppm) with a standard deviation of 2.56 ppm (2.51 ppm), whereas the averages of the differences between the GOSAT XCO2 over ocean and the aircraft-based XCO2 were -1.82 ppm (-2.27 ppm) with a standard deviation of 1.04 ppm (1.79 ppm) for ±2° (±5°) boxes.
An increase in photosynthetic activity of the northern hemisphere terrestrial vegetation, as derived from satellite observations, has been reported in previous studies. The amplitude of the seasonal ...cycle of the annually detrended atmospheric CO2 in the northern hemisphere (an indicator of biospheric activity) also increased during that period. We found, by analyzing the annually detrended CO2 record by season, that early summer (June) CO2 concentrations indeed decreased from 1985 to 1991, and they have continued to decrease from 1994 up to 2002. This decrease indicates accelerating springtime net CO2 uptake. However, the CO2 minimum concentration in late summer (an indicator of net growing-season uptake) showed no positive trend since 1994, indicating that lower net CO2 uptake during summer cancelled out the enhanced uptake during spring. Using a recent satellite normalized difference vegetation index data set and climate data, we show that this lower summer uptake is probably the result of hotter and drier summers in both mid and high latitudes, demonstrating that a warming climate does not necessarily lead to higher CO2 growing-season uptake, even in high-latitude ecosystems that are considered to be temperature limited.
The continued warming of the Arctic could release vast stores of carbon into the atmosphere from high-latitude ecosystems, especially from thawing
permafrost. Increasing uptake of carbon dioxide ...(CO2) by vegetation during longer growing seasons may partially offset such release of carbon. However, evidence of significant net annual release of carbon from site-level observations and model simulations across tundra ecosystems has been inconclusive. To address this knowledge gap, we combined top-down observations of atmospheric CO2 concentration enhancements from aircraft and a tall tower, which integrate ecosystem exchange over large regions, with bottom-up observed CO2 fluxes from tundra
environments and found that the Alaska North Slope is not a consistent net source nor net sink of CO2 to the atmosphere (ranging from −6 to
+6 Tg C yr−1 for 2012–2017). Our analysis suggests that significant biogenic CO2 fluxes from unfrozen terrestrial soils, and likely inland waters, during the early cold season (September–December) are major factors in determining the net annual carbon balance of the North Slope, implying strong sensitivity to the rapidly warming freeze-up period. At the regional level, we find no evidence of the previously reported large late-cold-season (January–April) CO2 emissions to the atmosphere during the study period. Despite the importance of the cold-season CO2 emissions to the annual total, the interannual variability in the net CO2 flux is driven by the variability in growing season fluxes. During the growing season, the regional net CO2 flux is also highly sensitive to the distribution of tundra vegetation types throughout the North Slope. This study shows that quantification and characterization of year-round CO2 fluxes from the heterogeneous terrestrial and aquatic ecosystems in the Arctic using both site-level and atmospheric observations are important to accurately project the Earth system response to future warming.
Soil temperature has been recognized as a property that
strongly influences a myriad of hydro-biogeochemical processes and
reflects how various properties modulate the soil thermal flux. In spite
of ...its importance, our ability to acquire soil temperature data with high
spatial and temporal resolution and coverage is limited because of the high
cost of equipment, the difficulties of deployment, and the complexities of
data management. Here we propose a new strategy that we call distributed
temperature profiling (DTP) for improving the characterization and
monitoring near-surface thermal properties through the use of an
unprecedented number of laterally and vertically distributed temperature
measurements. We developed a prototype DTP system, which consists of
inexpensive, low-impact, low-power, and vertically resolved temperature probes
that independently and autonomously record soil temperature. The DTP system
concept was tested by moving sequentially the system across the landscape
to identify near-surface permafrost distribution in a discontinuous
permafrost environment near Nome, Alaska, during the summertime. Results
show that the DTP system enabled successful acquisition of vertically
resolved profiles of summer soil temperature over the top 0.8 m at numerous
locations. DTP also enabled high-resolution identification and lateral
delineation of near-surface permafrost locations from surrounding zones with
no permafrost or deep permafrost table locations overlain by a perennially
thawed layer. The DTP strategy overcomes some of the limitations associated
with – and complements the strengths of – borehole-based soil temperature
sensing as well as fiber-optic distributed temperature sensing (FO-DTS)
approaches. Combining DTP data with co-located topographic and vegetation
maps obtained using unmanned aerial vehicle (UAV) and electrical resistivity
tomography (ERT) data allowed us to identify correspondences between surface
and subsurface property distribution and in particular between topography,
vegetation, shallow soil properties, and near-surface permafrost. Finally,
the results highlight the considerable value of the newly developed DTP
strategy for investigating the significant variability in and complexity of
subsurface thermal and hydrological regimes in discontinuous permafrost
regions.
We evaluate vertical profile retrievals of CO2 from 0.02 cm-1 resolution ground-based near-infrared solar absorption spectra with the GFIT2 algorithm, using improved spectroscopic line lists and line ...shapes. With these improvements, CO2 profiles were obtained from sequential retrievals in five spectral windows with different vertical sensitivities using synthetic and real spectra. A sensitivity study using synthetic spectra shows that the leading source of uncertainty in the retrieved CO2 profiles is the error in the a priori temperature profile, even with 3-hourly reanalysis a priori profiles. A 2 ∘C error in the temperature profile in the lower troposphere between 0.6 and 0.85 atm causes deviations in the retrieved CO2 profiles that are larger than the typical vertical variations of CO2. To distinguish the effect of errors in the a priori meteorology and trace gas concentration profiles from those in the instrument alignment and spectroscopic parameters, we retrieve CO2 profiles from atmospheric spectra while using an a priori profile built from coincident AirCore, radiosonde, and surface in situ measurements at the Lamont, Oklahoma (USA), Total Carbon Column Observing Network station. In those cases, the deviations in retrieved CO2 profiles are also larger than typical vertical variations of CO2, suggesting that remaining errors in the forward model limit the accuracy of the retrieved profiles. Implementing a temperature retrieval or correction and quantifying and modeling an imperfect instrument alignment are critical to improve CO2 profile retrievals. Without significant advances in modeling imperfect instrument alignment, and improvements in the accuracy of the temperature profile, the CO2 profile retrieval with GFIT2 presents no clear advantage over scaling retrievals for the purpose of ascertaining the total column.
We present carbon dioxide (CO2 ) estimates from the Tropospheric Emission Spectrometer (TES) on the EOS-Aura satellite launched in 2004. For observations between 40° S and 45° N, we find about 1 ...degree of freedom with peak sensitivity at 511 hPa. The estimated error is ~10 ppm for a single target and 1.3-2.3 ppm for monthly averages on spatial scales of 20°×30°. Monthly spatially-averaged TES data from 2005-2008 processed with a uniform initial guess and prior are compared to CONTRAIL aircraft data over the Pacific ocean, aircraft data at the Southern Great Plains (SGP) ARM site in the southern US, and the Mauna Loa and Samoa surface stations. Comparisons to Mauna Loa data show a correlation of 0.92, a standard deviation of 1.3 ppm, a predicted error of 1.2 ppm, and a ~2% low bias, which is subsequently corrected. Comparisons to SGP aircraft data over land show a correlation of 0.67 and a standard deviation of 2.3 ppm. TES data between 40° S and 45° N for 2006-2007 are compared to surface flask data, GLOBALVIEW, the Atmospheric Infrared Sounder (AIRS), and CarbonTracker. Comparison to GLOBALVIEW-CO2 ocean surface sites shows a correlation of 0.60 which drops when TES is offset in latitude, longitude, or time. At these same locations, TES shows a 0.62 and 0.67 correlation to CarbonTracker at the surface and 5 km, respectively. We also conducted an observing system simulation experiment to assess the potential utility of the TES data for inverse modeling of CO2 fluxes. We find that if biases in the data and model are well characterized, the averaged data have the potential to provide sufficient information to significantly reduce uncertainty on annual estimates of regional CO2 sources and sinks. Averaged pseudo-data at 10°×10° reduced uncertainty in flux estimates by as much as 70% for some tropical regions.
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