Methane in the 21 st Century: Projections with RCP scenarios in GEOS-Chem

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Methane in the 21 st Century: Projections with RCP scenarios in GEOS-Chem Christopher D. Holmes Dept. of Earth System Science University of California, Irvine Coauthors: Michael Prather (UC Irvine) O. Amund Søvde, Gunnar Myhre, Ivar Isaksen (U. Oslo) RCP 8.5 ship NOx emissions, year 25

1. What processes control CH 4 lifetime? Simulate 1997-29, and many perturbation tests three CTMs: v9-1-2n CTM spread provides uncertainty estimate RCP emissions in all CTMs 2. Project CH 4 for the 21 st Century with a global box model of key processes RCP 8.5 ship NOx emissions, year 25

Representative Concentration Pathway (RCP) emissions Species (similar to RETRO) NO, CO, SO2, CH4, NH3, BC, OC, 23 VOCs Resolution.5 x.5 global Every decade 185-21 (and 25) 11 Sectors (similar to RETRO) Land transport Shipping Aviation Energy production and distribution Industrial combustion Residential and commercial fuel use Solvent use Waste management and disposal Agriculture Agricultural waste burning Biomass burning (grassland, forest) CH4 Agriculture CH4 NOx Energy Production NOx CO Historical data sources EDGAR, HYDE, RETRO, EPA, EMEP, Bond Similar to GC emission approach (Lamarque et al., 21; van Vuuren et al., 211; Holmes 213 GC wiki) Land Transport CO

1 Inventory comparison (25) C2H6 EDGAR/RETRO/ 2.88 Tg Regional (v9-1-2) Before RCP 2.77 Tg After 5 1 5 Difference.11 Tg (RCP GC) Difference (After Before) 1 NOx molec cm-2 s-1 27.64 Tg C3H8 26.72 Tg 11.57 Tg.92 Tg 3.26 Tg 8.31 Tg 1 12 1 1 5 1 1 1 1 1 5 1 1 8 1 1 5 1 1 1 6 1 5 1 6 1 1 1 5 8 1 1 1 1 5 1 1 1 1 7 1 1 113 112 CO 111 577.96 Tg ALK4 597.8 Tg 19.12 Tg 11 21.46 Tg 33.25 Tg 11.79 Tg 19 18 C2H6 2.77 Tg 2.88 Tg CH2O.11 Tg.4 Tg Similar 1.33 TgLocal 1-5% differences.94 Tg global totals, 1 12 1 (Holmes 213 GC wiki) 1^6 molec (or fuel atoms Figure 3. Anthropogenic emissions (fossil andc)/cm2/s biofuel) for 25 in EDGAR and RETRO plus regional

Concentration comparison (25) Figure 4. Surface CO changes (ppb) due to emissions for January, April, July and October. Inset numbers give the global mean change in surface concentrations. EDGAR RETRO plus regional Figure 4. Surface CO changes (ppb) due to emissions forlayer January, April, Julyandand October. Inset numbers inventories (Before) vs. RCP 6. inventory (After). give the global mean change in surface layer concentrations. EDGAR and RETRO plus regional inventories (Before) vs. RCP 6. inventory (After).Difference (After Before) ppb Surface O3 Change (RCP GC) Difference (After Before) Jan Jul.85 ppb 1.25 ppb 15 15 1 1 5 5 15 Jan Jul.85 ppb 1.25 ppb 1 5 5 1 1 Apr 5 Oct 1.1 ppb 15 15.57 ppb Bug in GC ICOADS-AMVER 5 ppb decrease in Figure 5. Surface O changes (ppb) due to emissions for January, April, July and October. Inset numbers ship inventory give the global mean change in surface summer layer concentrations. EDGAR and RETRO plus regional inventories (Before) vs. RCP 6. inventory (After). (v9-1-3 and earlier) 3 5 Using RCP emissions increases τ (CH4+ΟΗ) ~.5 yr* (to 1.5 yr) 1 Apr Obs: τ (CH4+ΟΗ) = 11.2 ± 1.3 yr (Prather, Holmes & Hsu 212) 1.1 ppb Oct.57 ppb 15 25 dicarbonyl simulation 2 x2.5 GEOS-5, v9-1-2n Figure 5. Surface O3 changes (ppb) due to emissions for January, April, July and October. Inset numbers give the global mean change in surface concentrations. and bug RETRO plus regional *lifetime due tolayer tropospheric OH, EDGAR after fixing in ICOADS inventory inventories (Before) vs. RCP 6. inventory (After). (Holmes 213 GC wiki)

CH 4 lifetime, y 8.9 8.8 8.7 8.6 UCI CTM R 2 =.92 water vapor +5% lifetime -1.6% UCI CTM 5-parameter model 5 parameters are sufficient to explain 9% of variability in the model 1998 2 22 24 26 28 21 252.25 Major causes of interannual variability Temperature 6.5 Lightning NOx emissions K 252. 251.75 251.5 DU g/kg 2.48 2.46 2.44 2.42 2.4 3 29 28 27 Water vapor 1998 2 22 24 26 28 21 Tg(N)/a Tg(CO)/a 6. 5.5 5. 7 6 5 4 3 2 Biomass burning emissions 1998 2 22 24 26 28 21 ln (t) =ln + X i f i (t) i Repeat in GEOS-Chem and Oslo CTM3

CH 4 lifetime in 4 CTMs 1. R 2 =.9 R 2 =.88 CH OH, y 4 9.5 9. CTM 5-Parameter Model UCI CTM Oslo CTM3 GEOS-Chem/GEOS-5 GEOS-Chem/MERRA R 2 =.9 8.5 R 2 =.92 1998 2 22 24 26 28 21 In all CTMs, 5 processes are the dominant sources of variability: temperature, water vapor, stratospheric ozone, biomass burning, lightning NOx, (Holmes et al. ACP 213)

Ingredients for future CH 4 projection Anthropogenic emissions, Tg/y 1 Atmospheric methane RCP 2.6 RCP 4.5 RCP 6. RCP 8.5 4 5 RCP2.6& RCP Emissions 2 RCP4.5& 4 RCP6.& Projections RCP8.5& 18 19 RCP2.6 2 21 35 RCP4.5 RCP6. RCP8.5 CH 4 abundance, ppb 45 Ta, K 3 25 2 RCP projections Variable b UCI CTM Oslo CTM3 CMIP5 Chemistry-climate Climate interactions Projection Air temperature e 3.9 2.8 Water vapor e.32.29 Ozone column, 4 S 4 N +.66 +.43 f Lightning CH 4 Lifetime NO x emissions Sensitivity.14.11 22 24 26 28 21 Biomass burning emissions i +.21 +.13 +.3 j CH 4 abundance k +.363 +.37 15 1 21 22 23 24 25 26 27 28 29 21 Emissions: Lamarque et al., 211 Meinshausen et al., 211 CMIP5 data: 35 models, Climate Explorer CH 4 Projections: Holmes et al., 213

Methane GWP O 3 response to +5% CH 4 CH 4 -induced O 3 CH 4 -induced O 3 via H 2 O 2 Oslo CTM3 2 Oslo CTM3 4 Includes stratospheric chemistry 4 6 8 1 2 4 6 8 1 2 4 6 8 1 +1.4 DU, +82 mw m -2 (strat) +5.1 DU, +22 mw m -2 (trop) Latitude UCI CTM +4. DU, +141 mw m -2 (trop) +2.9 DU, +123 mw m -2 (trop)..12.38 % 6 8 1 4.4 DU, 2 mw m -2 (strat).4 DU, 17 mw m -2 (trop) Latitude % CH 4 GWP includes: direct absorption tropospheric O 3 stratospheric water vapor stratospheric O 3 (new, this work) GWP 1-yr = 31.7 (this work) = 25 (IPCC 27) (Holmes et al., ACP 213)

RCP reading list Emissions to be available in v9-2 GEOS-Chem implementation: Holmes, C. D., M. J. Prather, O. A. Søvde, and G. Myhre: Future methane, hydroxyl, and their uncertainties: key climate and emission parameters for future predictions, Atmos. Chem. Phys. 13, 285-32, doi:1.5194/acp-13-285-213, 213. Wiki page: http://acmg.seas.harvard.edu/geos/wiki_docs/emissions/geos-chem_rcp_emissions.pdf RCP data: www.iiasa.ac.at/web-apps/tnt/rcpdb Historical inventory: Lamarque, J.-F., Bond, T. C., Eyring, V., Granier, C., Heil, A., Klimont, Z., Lee, D., Liousse, C., Mieville, A., Owen, B., Schultz, M. G., et al.: Historical (185-2) gridded anthropogenic and biomass burning emissions of reactive gases and aerosols: methodology and application, Atmos Chem Phys, 1(15), 717 739, doi:1.5194/acp-1-717-21, 21. Future projections: van Vuuren, D. P., Edmonds, J., Kainuma, M., Riahi, K., Thomson, A., Hibbard, K., Hurtt, G. C., Kram, T., Krey, V., Lamarque, J.-F., Masui, T., et al.: The representative concentration pathways: an overview, Climatic Change, 19, 5 31, doi:1.17/s1584-11-148-z, 211a. van Vuuren, D. P., Lowe, J., Stehfest, E., Gohar, L., Hof, A. F., Hope, C., Warren, R., Meinshausen, M. and Plattner, G.- K.: How well do integrated assessment models simulate climate change? Climatic Change, 14(2), 255 285, doi: 1.17/s1584-9-9764-2, 211b.

Contributions to future lifetime change RCP 8.5 CH4 OH, % x this work: +12.9 ± 1.8 % ACCMIP: +8.5 ± 1.4 % (Voulgarakis et al., 212) temperature water vapor O 3 column L-NOx biomass burn land NOx ship NOx aircraft NOx anthro emissions (Holmes et al. ACP 213) CO VOC CH 4 feedback Total Temperature, water vapor, land NOx and CH 4 feedback dominate in RCP 8.5, but not in all other scenarios

EMISSIONS