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Connecting atmospheric composition with climate variability and change

Connecting atmospheric composition with climate variability and change Seminar in Atmospheric Science, EESC G9910. 9/19/12 Observed methane trends in recent decades: Emission trends or climate variability? Aydin et al., Nature, 2011 (fossil fuel)

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Connecting atmospheric composition with climate variability and change

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  1. Connecting atmospheric composition with climate variability and change Seminar in Atmospheric Science, EESC G9910 • 9/19/12 Observed methane trends in recent decades: • Emission trends or climate variability? • Aydin et al., Nature, 2011 (fossil fuel) • Study period: 20th century; ethane:methane in firn air • Kai et al., Nature, 2011 (NH microbial sources) • study period: 1984-2005; isotopic source signature • Hodson et al., GRL, 2011 (ENSO and wetlands) • study period: 1950-2005; process modeling

  2. GMD monitoring network http://www.esrl.noaa.gov/gmd/dv/site/map1.php

  3. The Methane Mystery: Leveling Off then Rebounding http://www.esrl.noaa.gov/gmd/aggi/ The uptick: observational evidence suggests natural sources in 2007 and 2008: 2007 Arctic depleted in 13C (wetlands)  Warm Arctic Temp 2008 tropics (zero growth rate in Arctic)  La Nina, tropical precip Dlugokencky et al., GRL, 2009 • Help characterizing sources from isotopes + co-emitted species • Inverse constraints on sinks (confidence?) • [Montzka et al., 2011]

  4. The Methane Mystery: Leveling Off then Rebounding Heimann, Science, 2011, “news and views”

  5. Possible sources of variability/trends in recent decades SOURCES: 1. Wetlands: At present 2/3 tropics, 1/3 boreal; estimated at 170-210 Tg CH4 (ENSO-driven; Hodson et al.) -- T and water table (seasonal, interannual) 2. Biomass burning 3. clathrate/permafrost degassing 4. fossil fuel (also landfills/waste management) Aydin et al. 5. rice agriculture Kai et al. (+ wetlands – they can distinguish “microbial”) 6. ruminants SINKS: Atmospheric Oxidation (primarily lower tropical troposphere) -- feeds back on any source change -- amplified by changes in biogenic VOC (but chemistry uncertain!) -- photolysis rates (e.g., due to overhead O3 columns; affects OH source) -- water vapor (affects OH source) -- shift in magnitude / location of NOx emissions (OH source)

  6. Aydin et al., Nature, 2011 • Use Ethane as a proxy for fossil fuel methane • 2nd most abundant constituent in naturalgas • Released mainly during production+distribution (same as CH4) • Major loss by OH, ~2 month lifetime METHODS: 1) Firn air measurements (flasks) at 3 sites: Summit, South Pole, WAIS-D, analyzed with GC-MS 2) Derive annual mean high latitude tropospheric abundances of ethane (1-D firn-air model + synthesis inversion) 3) Explore role of biomass burning + fossil fuel in contributing to observed ethane time histories (2-box model, informed by 3-D model)

  7. contemporary Ethane mixing ratios in firn air at three sites, and the Atmospheric histories derived from these measurements. modeled M Aydinet al.Nature476, 198-201 (2011) doi:10.1038/nature10352 Shaded regions not constrained Due to uncertainties in PI levels S Pole can constrain ramp-up Starting 1910  5x by 1980 All 3 site show 1980 peak, then decline(~10%) despite increase in FF use Not used in inversion Possible atmospheric histories (different PI ethane)

  8. Ethane source emissions and the resulting atmospheric histories. • Derived with 2-box model •  3D model used to relate • how air reaching firn responds to changing hemispheric mean ethane levels FF dominates observed time history Decline of CH4 growth rate parallels ethane decline 3. Now steady  recent “uptick” not due to FF CH4 M Aydinet al.Nature476, 198-201 (2011) doi:10.1038/nature10352

  9. Ethane and methane emissions from fossil fuels, biofuels and biomass burning. FF ethane differs from bottom-up CH4 BB agrees with independent estimates Are the CH4 inventories wrong? Could methane-to-ethane Emission ratios have changed? Less venting while production increased? 15-30 Tg CH4 yr-1 decrease 1980 to 2000 Shift in distribution / Cl sink estimated to be small M Aydinet al.Nature476, 198-201 (2011) doi:10.1038/nature10352

  10. Kai et al., Nature, 2011 Use CH4 abundance plus 13C/12C of CH4 to distinguish microbial vs. fossil sources, also distinguish sinks by looking at D/H  information in inter-hemispheric difference (IHD) Conclusion: Isotopic constraints exclude reductions in fossil fuel as primary cause of slowdown. Rather, large role for Asian rice agriculture (+fertilizer, -water use METHODS: measurements from UCI, NIWA, and SIL networks 2) Examine various hypotheses for explaining decline in CH4 growth rate (2-box model including CH4 and its isotopes) 3) Empirical, process-based biogeochemical model to estimate changes in rice agriculture

  11. Kai et al., Nature, 2011 Kai et al., Nature, 2011

  12. Kai et al., Nature, 2011

  13. Long-term trends in atmospheric CH4, 13C-CH4, and D-CH4. FM Kaiet al.Nature476, 194-197 (2011) doi:10.1038/nature10259

  14. Long-term trends in atmospheric CH4, 13C-CH4, and D-CH4. FM Kaiet al.Nature476, 194-197 (2011) doi:10.1038/nature10259 FM Kaiet al.Nature476, 194-197 (2011) doi:10.1038/nature10259

  15. Possible driving factors of trend towards NH enriched C isotopes of CH4 Decrease in isotopically depleted source (microbial: agriculture, landfills, wetlands) Increase in enriched source (FF or BB) Increase in removal by OH (but dD relatively constant  suggests no change in sink) Considering CH4 alone, leveling off can be explained by both FF and agricultural emissions but isotopic time histories differ for FF / agriculture  dig deeper into the isotopic constraints FM Kaiet al.Nature476, 194-197 (2011) doi:10.1038/nature10259

  16. Variations in CH4 fluxes and the impacts of source composition on isotopic trends. 31 Tg CH4 yr-1 decrease (~6% total budget) Conclusions from scenario analysis: • Assume all change due to FF, • IHD of d13C-CH4 widens, not • Consistent with obs • Agricultural source changes can • (or wetlands / better landfill management) • They posit wetland source hasn’t changed in consistent way FM Kaiet al.Nature476, 194-197 (2011) doi:10.1038/nature10259

  17. Evidence for intensification of rice agriculture in Asia. FM Kaiet al.Nature476, 194-197 (2011) doi:10.1038/nature10259 Increase in chemical fertilizer use Increase in industrial water use; New mid-season drainage of rice paddies 15.5 +/- 1.9 Tg CH4 yr-1 1984 to 2005

  18. Follow-up (2012 Nature: Levin et al.) Different isotope datasets Do not support change in IHD (so flat microbial source) Response of Kai et al: Need to bring together all datasets; value of isotopic measurements.

  19. Hodson et al. GRL, 2011 Method: Use simple dynamic vegetation wetland model and compare with ENSO index Conclusions: Repeated El Nino events in 1980s and 1990s contributed to reducing CH4 emissions and atmospheric abundance leveling off E (x,t) = F(x) b Rh(x,t) S(x,t) • x= each 0.5° grid cell • t = monthly • E = wetland emission flux (Tg CH4 grid cell-1 month-1) • F=ecosystem dependent scaling factor • = 0.03 mol CH4/mol C respired • Rh = heterotrophic respiration (mol C respired) from LPJ DGVM (T, CO2) • S = areal extent of wetland (satellite 1993-2000); fitted to runoff in LPJ  Also account for differences in emitting capacity btw boreal + tropics (empirical)

  20. Multivariate Enso index “An index of six observed variables (such as pressure, air and sea-surface temperatures, winds, cloudiness) over the tropical Pacific is used to monitor the coupled ocean-atmosphere phenomenon known as the El Ni ño-Southern Oscillation (ENSO). Areas with large positive values of the index (large red spikes) depict the "El Niño" warm phase of the ENSO phenomenon. [From the NOAA Climate Diagnostics Center” http://www.research.noaa.gov/climate/observing1.html

  21. Hodson et al., GRL, 2011: FIGURE 1 N. Temperate (27%) and Tropics (44%) Dominate variability Tropics responds to Variability in inundated area; Boreal to Rh (T) R2 = 0.56

  22. Hodson et al., GRL, 2011: TABLE 1 During events, wetland response > prior estimates for fires; Possibility of offsetting influences during El Nino (+fires; -wetlands)  Contributed to slow down (citing other work for anthropogenic sources)

  23. Hodson et al., GRL, 2011: Table 2 Potential amplification if boreal wetland emissions increase in the future

  24. Some overall discussion points Why so many competing hypotheses? How strong a constraint is there on the OH sink and trends therein? Confidence in proxies we have for CH4 source attribution? How well do we know isotopic source/sink signatures? Representativeness of “reference” measurement stations Large interannual “wiggles” in data: real? Artifacts of combining measurements for different places / periods? Connections of microbial emissions to other pollutants/GHGs (acid deposition; N2O production)

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