Estimating global and North American methane emissions with high spatial resolution using GOSAT satellite data

Abstract

Abstract. We use 2009–2011 space-borne methane observations from the Greenhouse Gases Observing SATellite (GOSAT) to constrain global and North American inversions of methane emissions with 4° × 5° and up to 50 km × 50 km spatial resolution, respectively. The GOSAT data are first evaluated with atmospheric methane observations from surface networks (NOAA, TCCON) and aircraft (NOAA/DOE, 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. The surface and aircraft data are subsequently used for independent evaluation of the methane source inversions. Our global adjoint-based inversion yields a total methane source of 539 Tg a−1 and points to a large East Asian overestimate in 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 full 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 South-Central US, the Central Valley of California, and Florida wetlands, large isolated point sources such as the US Four Corners also contribute. We attribute 29–44% of US anthropogenic methane emissions to livestock, 22–31% to oil/gas, 20% to landfills/waste water, and 11–15% to coal with an additional 9.0–10.1 Tg a−1 source from wetlands.

Assessment of Anthropogenic Methane Emissions over Large Regions Based on GOSAT Observations and High Resolution Transport Modeling

“…This shows a mismatch between observations based and inventory based XCH4 anomalies over northern America and thereby a potential underestimation in the emission inventory. This result is in agreement with recent studies by Miller et al [12] and Turner et al [18] who showed anthropogenic CH4 emission in North America is underestimated by 30-50%, attributable to oil and natural gas and livestock emissions. Over the East Asian region, the model-observation mismatch is approximately 30%, emission being higher than suggested by observation derived enhancements.…”

“…Similarly, differences between EPA and EDGAR in various emission sectors are discussed in Maasakkers et al [17]. Turner et al [18] applied a 50 km resolution inverse model utilizing GOSAT data over North America to conclude that EPA emission inventory is underestimating emissions by some sectors. Further, since the emission of methane from anthropogenic sources are highly variable within same source category, the quantification is much more difficult than anthropogenic emission of CO 2 which are deduced from better known fuel use data.…”

Contributions of the troposphere and stratosphere to CH<sub>4</sub> model biases

“…Especially in the polar region, the tropopause height varies strongly and the dynamical processes are complex. Turner et al (2015) compared GOSAT CH 4 with GEOS-Chem simulations, and found large differences at high latitudes. They proposed that the model bias in total column CH 4 at high latitudes comes from the stratosphere since the validation with TCCON (Total Carbon Column Observing Network), NOAA surface and aircraft measurements, and HIPPO shows good performances of the model in the troposphere.…”

Tropospheric emissions: Monitoring of pollution (TEMPO)

“…To properly exploit disparate data sources with differing spatio-temporal resolutions it will be useful to employ chemical models as intercomparison platforms. This methodology has been used previously to compare satellite measurements of ozone [124] and satellite measurements of methane and formaldehyde with in situ data [106,126].…”