Portland State University. Department of Physics
Christopher L. Butenhoff
Term of Graduation
Date of Publication
Master of Science (M.S.) in Physics
Atmospheric methane -- Mathematical models, Atmospheric methane -- Measurement, Methane -- Research
1 online resource (xv, 303 pages)
Methane (CH4) is the second most important greenhouse gas with a radiative forcing of 0.97 W/m2 including both direct and indirect effects and a global warming potential of 28 over a 100-year time horizon. Unlike CO2 whose rate of growth in the atmosphere has remained positive and increased in recent decades, the behavior of atmospheric methane is considerably more complex and is much less understood on account of the spatiotemporal variability of its emissions which include biogenic (e.g., wetlands, ruminants, rice agriculture), thermogenic (fossil fuels), and pyrogenic (i.e., biomass burning) sources. After sustained growth during most of the 20th century, the CH4 growth rate declined to fall from ~15 ppb/year during the 1980s to ~6 ppb/year in the 1990s to near-zero and even negative values in the early 2000s. With some surprise, however, the growth rate rebounded in 2007 and the annual increase in globally-averaged atmospheric methane abundance has been 7.86 ppb/year on average during the past 14 years from 2007 to 2020. During this same period, the 13CH4/12CH4 ratio of atmospheric CH4 also declined to suggest the post-2006 CH4 growth was caused by an increase in 13CH4-depleted biogenic emissions. Recent papers have attributed this growth to increasing emissions from wetlands, rice agriculture, and ruminants. This work provides additional insight into the recent behavior of atmospheric methane by performing a global three-dimensional Bayesian inversion of atmospheric CH4 and 13CH4/12CH4 ratios over the period 1983-2015 using NOAA Global Monitoring Laboratory (GML) CH4 measurements obtained from surface observation sites located worldwide and the GEOS-Chem chemical transport model (CTM) at a horizontal grid resolution of 2° x 2.5°. The use of the 3-D model allowed us to exploit spatial patterns in the global CH4 and 13CH4/12CH4 fields that provide additional constraints on the retrieval of the time-dependent CH4 fluxes from 10 different methane sources such as Gas and oil, coal, livestock, waste, rice agriculture, biomass burning from C3 and C4 vegetation, and wetlands separated into 3 latitudinal zones (90°N-30°N, 30°N-0°, 0°-90°S) in order to reduce aggregation error and to account for isotopic measurements that indicate northern high latitude wetlands are isotopically depleted in 13CH4 relative to tropical wetlands. Spatially re-gridded monthly varying prior emission fields were constructed from several sources and also included sinks such as reaction with OH, stratospheric loss, and soil sink at the same spatial resolution. In this work, one year of the monthly varying three-dimensional OH field was used in GEOS-Chem where CH4 loss due to reaction to OH was calculated at every grid cell for each timestep. GEOS-Chem used NASA Global Modeling and Assimilation Office (GMAO) data product GEOS-5 meteorological fields available for years 2004 to 2010 and these 6 years of meteorological variables were recycled for the entire inversion time. This work follows up on previous CH4 inversion where a 4° x 5° horizontal grid was used for GEOS-Chem to retrieve fluxes from 1984 to 2009 with GLOBALVIEW methane measurement data. A set of sensitivity tests were conducted to assess the impact of discontinuity in the data coverage over the entire time of inversion for different observation sites on the methane flux trends.
At a higher resolution, more information is extracted from the observations due to improved model skill and a smaller number of stations aggregated within model grid cells. This increases the weights of the measurements relative to the a priori fluxes in the inversion producing stronger observational constraints on the optimized fluxes. This work assesses the contribution of spatial heterogeneities in the observed CH4 record to the retrieval of global CH4 fluxes and provides a new look into the causes of more than a decade-long growth in atmospheric methane. The comparison between the results of optimized methane emissions from this current inversion work (2° x 2.5°) and previously done inversion work (4° x 5°) up through the end of 2008 revealed some prominent differences in the emission anomalies plots of the individual source categories of gas and oil, coal, livestock and waste and in the aggregated source categories of fossil fuels, wetlands and all biogenic.
The model simulated concentrations using the a posteriori emission estimates match remarkably well for both the long-term trend and magnitude of the observed NOAA concentrations as well as the seasonal cycle of the measurements, except for a few small discrepancies. The inversion analysis indicates that the total averaged global methane emission over years 1983 to 2015 is estimated to be 530±50 Tg/year, over the decade of 2006-2015 is 543±44 Tg/year which is ~20 Tg/year more than that during the previous decade, over years 2006 to 2010 it is estimated to be 539±44 Tg/year, whereas over years 2011 to 2015, it is estimated to be 547±45 Tg/year. The global methane emissions over the years of 1983 to 2015 from all biogenic sources of both natural and anthropogenic origin account for ~73% of the total global CH4 emissions. Anthro-biogenic sources contribute about 39% of the total global CH4 emissions, whereas natural wetlands contribute about 34.5% of the total CH4 emissions. Emissions from the fossil fuels sector constitute about 18.5% of the total global CH4 emissions and biomass burning about 8.3% of the total global CH4 emissions.
The averaged emission estimate of emissions from all biogenic sources (both natural and anthropogenic) shows an increase of about ~25 Tg/year during 2006-2015 than that during 1994-2005, whereas the anthro-biogenic sources show the highest increase in averaged emission estimate of about ~43 Tg/year during 2006-2015 than that during 1994-2005. The results of this study conclude that the major contribution of emissions from all biogenic sources both natural and anthropogenic as well as a minor contribution from biomass burning may have caused the increase in global methane levels since post-2006. It is revealed that the emissions from individual source categories of livestock, wastes, coal, northern high latitude wetlands, and biomass burning of C3 vegetations had increased during 2006-2015. Although a persistent increase in total methane levels was observed until the end of the study period, a shift in relative contributions from the emissions of individual source categories may have occurred from 2011 onwards. With the decline in emissions from anthro-biogenic sources of livestock and rice, northern tropical wetlands, fossil fuel source of coal, and biomass burning of C4 vegetations, the increase in global methane levels from 2011 until the end of the study period may possibly be due to the contribution of increased emissions from sources of wastes, natural wetlands (southern hemisphere and northern high latitudes), fossil fuel source of gas and oil and biomass burning of C3 vegetations globally.
The sensitivity test inversion scenarios for all of the source categories maintained the same trends of methane emissions throughout the study period as base case inversion scenarios discussed above but, in some cases, with a significantly wider range in the mean values of the emissions. Emissions from sources like fossil fuels, livestock, and wastes are more sensitive to the variation in network densities of observational sites with continuous data coverage.
© 2021 Sayantani Karmakar
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Karmakar, Sayantani, "Inverse Modeling of Atmospheric CH4 and δ13C-CH4 Measurements from Surface Observation Sites to Understand Trends in Global Methane Emissions Over More Than Three Decades" (2022). Dissertations and Theses. Paper 5889.