Methane Emission Estimates by the Global High-Resolution Inverse Model Using National Inventories

Abstract

We present a global 0.1 • × 0.1 • high-resolution inverse model, NIES-TM-FLEXPART-VAR (NTFVAR), and a methane emission evaluation using the Greenhouse Gas Observing Satellite (GOSAT) satellite and ground-based observations from 2010-2012. Prior fluxes contained two variants of anthropogenic emissions, Emissions Database for Global Atmospheric Research (EDGAR) v4.3.2 and adjusted EDGAR v4.3.2 which were scaled to match the country totals by national reports to the United Nations Framework Convention on Climate Change (UNFCCC), augmented by biomass burning emissions from Global Fire Assimilation System (GFASv1.2) and wetlands Vegetation Integrative Simulator for Trace Gases (VISIT). The ratio of the UNFCCC-adjusted global anthropogenic emissions to EDGAR is 98%. This varies by region: 200% in Russia, 84% in China, and 62% in India. By changing prior emissions from EDGAR to UNFCCC-adjusted values, the optimized total emissions increased from 36.2 to 46 Tg CH 4 yr −1 for Russia, 12.8 to 14.3 Tg CH 4 yr −1 for temperate South America, and 43.2 to 44.9 Tg CH 4 yr −1 for contiguous USA, and the values decrease from 54 to 51.3 Tg CH 4 yr −1 for China, 26.2 to 25.5 Tg CH 4 yr −1 for Europe, and by 12.4 Tg CH 4 yr −1 for India. The use of the national report to scale EDGAR emissions allows more detailed statistical data and country-specific emission factors to be gathered in place compared to those available for EDGAR inventory. This serves policy needs by evaluating the national or regional emission totals reported to the UNFCCC.is slowing down [1][2][3]. Methane (CH 4 ) plays a growing role in anthropogenic climate change with its share of more than 20% of the total greenhouse gas (GHG) concentration [4][5][6]. Reducing methane emissions would make a significant contribution to climate change mitigation on a shorter time scale, due to its relatively short lifetime compared with that of CO 2 [7,8]. The determination of national emission reduction targets and policies is directly affected by the amount of methane emissions produced by individual countries [9]. However, studies on emission estimates suggest that there are still large uncertainties in methane budgets, and more effort should be made to better quantify the methane emissions [10][11][12][13][14][15]. Still, it is challenging to verify the accuracy of methane emissions on a country scale. The national reports submitted to the United Nations Framework Convention on Climate Change (UNFCCC) by different countries might use different methods to estimate emissions, which could be different from global inventory datasets produced by the scientific community, such as the Global Carbon Project (GCP) [16], and the Emissions Database for Global Atmospheric Research (EDGAR) [17][18][19]. Complementary to these bottom-up emission estimations, top-down estimations by inverse models combined with atmospheric measurements have been widely used and have proven worthy for emission inventory evaluation (e.g., [20][21][22][23][24][25][26]). Houweling et al. [27] reviewed the devel...

Country-Scale Analysis of Methane Emissions with a High-Resolution Inverse Model Using GOSAT and Surface Observations

“…Here, we reported the results of our analysis using a high-resolution global Eulerian-Lagrangian coupled inverse model of methane using national reports of anthropogenic methane emissions to the United Nations Framework Convention on Climate Change (UNFCCC) ( [23]) as prior anthropogenic fluxes and evaluated the posterior emissions optimized in two emission categories of natural and anthropogenic on a country scale. This study is an extension to one by Wang et al (2019) [24], where they compared methane emissions for 2010-2012 for large regions with UNFCCC reports using either Emission Database for Global Atmospheric Research (EDGAR) or UNFCCC reported values as prior, whereas, in this study, we reported results for country-scale analysis of methane emissions for 2011-2017, with more detailed discussion and use of independent validation for India using optimized forward simulations of aircraft CH 4 observations.…”

“…The top fifteen emitting countries based on EDGAR v4.3.2 estimate for 2012 and other four countries Germany, France, United Kingdom, and Japan were selected to adjust the inventory according to UNFCCC reports (see Table A2). These nineteen countries emit 66% of the global total methane for the year 2012 ( [24]). The new gridded prior emission based on the UNFCCC reports was produced by scaling the annual total to EDGAR v4.3.2 values.…”

“…Beyond 2012, we used the EDGAR values for 2012. More details on the data preparation could be found in [24]. Monthly variability was incorporated using the emission seasonality data available for one year for 2010 from EDGAR.…”

“…The changes in the current version with respect to the study by [47] include revision in the transport matrix, indexing and sorting algorithms to allow efficient memory usage for handling large matrixes of Lagrangian responses to surface fluxes required when using GOSAT data in the inversion. More details could be found in [24].…”

“…The optimal solution, as the minimum of the cost function J, was calculated iteratively with an efficient Broyden-Fletcher-Goldfarb-Shanno (BFGS) algorithm, as implemented by [52]. More details on the implementation could be found in [24,53].…”