1. US methane emissions and relevance for climate policy Daniel J. Jacob with Alexander J. Turner, J.D. (Bram) Maasakkers Supported by the NASA Carbon Monitoring System “ The Administration is announcing a new goal to cut methane emissions from the oil and gas sector by 40 – 45 percent from 2012 levels by 2025” [President’s Updated Climate Action Plan, 2015]

2. Gorillas and chimpanzees of climate change CO 2 : the 800-lbs gorilla Methane and black carbon: the chimps Do we care about the chimps?

3. Radiative forcing of climate change Solar flux F in Terrestrial flux F out =σ T 4 Global radiative equilibrium: F in = F out Perturb greenhouse gases or aerosols radiative forcing  F = F in - F out Global equilibrium surface temperature response:  T o ~  F

4. Radiative forcing referenced to emissions, 1750-2011 Radiative forcing from methane emissions is 0.97 W m -2, compared to 1.68 W m -2 for CO 2 Radiative forcing from black carbon aerosol (BC) is 0.65 W m -2, highly uncertain Together methane and BC have radiative forcing comparable to CO 2  they have made comparable contribution to past climate change But atmospheric lifetimes of methane (10 years) and BC (~1 week) are shorter than CO 2 (> 100 years) What does that mean for priorities in controlling future emissions? [IPCC, 2014]

5. Climate policy metrics consider the integrated future impact of a pulse unit emission of a radiative forcing agent Inject 1 kg of agent X at time t = 0 time Concentration C(t) from pulse time Impact from pulse = f(C(t)) time Discount rate Climate metric = (impact)  (discount rate)  dt …usually normalized to CO 2

6. Standard IPCC metric: Global Warming Potential (GWP) Integrated radiative forcing over time horizon [0, H] CO 2 methane BC Radiative forcing  F vs. time for pulse unit emission of X at t = 0 GWP for methane vs. chosen time horizon: 28 for H = 100 years  1 Tg CH 4 = 28 Tg CO 2 (eq) IPCC [2014] GWP is easy to compute, but it does not correspond to any physical impact H Discount rate: step function time

7. Towards a temperature-based climate metric Cancun UN Climate Change Conference: hold global surface temperature change to less than 2 o C above pre-industrial levels Intent is to avoid catastrophic climate change

8. Global temperature potential (GTP) metric introduced by IPCC AR5 Global mean surface temperature change at t = H CO 2 methane BC Temperature change vs. time for pulse unit emission at t = 0 Temperature response to actual 2008 emissions taken as a 1-year pulse IPCC [2014] Methane as important as CO 2 for 10-year horizon, unimportant for 100-year horizon Discount rate: Dirac function H time

9. Why does methane cause only a short-term temperature response? ToTo ToTo T o +  T o ToTo F in t < 0 t = 0 t = 20 years t = 100 years climate equilibrium emission pulse climate response back to original equilibrium F out  F = 0  F < 0  F > 0

10. Implication of GTP-based policy for near-term climate forcers GTP potential Right now we’ll just worry about CO 2. But in 70 years please start acting on methane, and in 95 years go all after black carbon, baby! Aiming to optimize for a maximum temperature change on a 100-year horizon:

11. Sole focus on temperature change over long-term horizon sacrifices immediate climate emergencies No summer Arctic sea ice in 20 years? More hurricane Sandys?

12. Methane and BC should be part of climate policy … but for reasons totally different than CO 2 It addresses climate change on time scales of decades – which we care about It offers decadal-scale results for accountability of climate policy It is an alternative to geoengineering by aerosols It has important air quality co-benefits Reducing methane emissions makes money BC has additional regional, hydrological climate impacts

13. Global and US inventories of methane emissions (2012) Global: 540 Tg a -1 Contiguous US: 33 Tg a -1 Wetlands: 160 Fires: 20 Livestock: 110 Rice: 40 Oil/Gas: 70 Coal: 50 Waste: 60 Other: 30 5.9 9.2 0.4 5.6 2.9 1.1 7.7 0.1 EDGAR4.2 and EPA greenhouse gas inventories US is second oil/gas source after Russia according to UNFCCC

14. Satellite observations of methane Instruments: SCIAMACHY (2002-2005), GOSAT (2009-), TROPOMI (2016 launch) Turner et al. [2015] Methane column mixing ratio

15. Satellite observations of methane Instruments: SCIAMACHY (2002-2005), GOSAT (2009-), TROPOMI (2016 launch) Turner et al. [2015] Methane column mixing ratio

16. “Top-down” constraints on emissions from satellite data Satellite observations of methane concentrations Chemical transport model Emissions Concentrations Inverse Prior “bottom-up”inventory (EDGAR + wetlands) Optimal estimation Optimized “top=down” inventory Aircraft and surface observations verification

17. Correction factors to bottom-up EDGAR inventory CONUS anthropogenic emission of 40-43 Tg a -1 vs. EPA value of 27 Tg a -1 Is the underestimate in livestock or oil/gas emissions or both? Turner et al. [2015]

18. Optimized top-down inventory CONUS anthropogenic emission of 40-43 Tg a -1 vs. EPA value of 27 Tg a -1 Is the underestimate in livestock or oil/gas emissions or both? Turner et al. [2015]

19. Attribution of emission correction to oil/gas or livestock is complicated by uncertainty in location, spatial overlap Oil/gas fields and cattle often share quarters Gas emissions occur at exploration, production, processing, transmission, distribution EDGAR inventory oil/gas source pattern likely overemphasizes distribution vs. production Turner et al. [2015] Eagle Ford Shale, Texas

20. Constructing a gridded version of the EPA national inventory Best process-based knowledge of sources, granular representation of processes, national inventory reported to the UNFCCC Large point sources (oil/gas/coal, waste) reporting emissions to EPA GIS data for location of wells, pipelines, coal mines,… Livestock and rice data at sub-county level Process-level emission factors including seasonal variation National bottom-up US inventory of methane emissions at 0.1 o x0.1 o monthly resolution J.D. Maasakkers (in prep.) with M. Weitz, T. Wirth, C. Hight, M. DeFiguereido [EPA]

21. New EPA-based gridded emission inventory: natural gas production J.D. Maasakkers (in prep.)

22. Natural gas processing J.D. Maasakkers (in prep.) New EPA-based gridded emission inventory: natural gas production + processing

23. Natural gas transmission J.D. Maasakkers (in prep.) New EPA-based gridded emission inventory: natural gas production + processing + transmission

24. Total natural gas: production + processing + transmission + distribution J.D. Maasakkers (in prep.) New EPA-based gridded emission inventory: natural gas production + processing + transmission + distribution

25. Difference with EDGAR J.D. Maasakkers (in prep.) Using the EPA gridded emission inventory as prior will considerably increase The quality of information from inverse modeling estimates