Using satellites to estimate US methane emissions Daniel J. Jacob with Kevin Wecht, Alex Turner, Melissa Sulprizio with support from the NASA Carbon Monitoring.

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Using satellites to estimate US methane emissions Daniel J. Jacob with Kevin Wecht, Alex Turner, Melissa Sulprizio with support from the NASA Carbon Monitoring System

Importance of methane for climate policy Present-day emission-based forcing of methane is 0.95 W m -2, compared to 1.8 W m -2 for CO 2 (IPCC AR5) Climate impact of methane is comparable to CO 2 over 20-year horizon Methane emission control is a low-cost option for climate policy Increases in natural gas production/use, hydrofracking have potential to increase US source of methane Methane is a central piece of the President’s Climate Action Plan

Building a methane monitoring system for N America EDGAR emission Inventory for methane Can we use satellites together with suborbital observations of methane to monitor methane emissions on the continental scale and test/improve emission inventories in a manner useful to stakeholders?

Methane bottom-up emission inventories for N. America: EDGAR 4.2 (anthropogenic), LPJ (wetlands) N American totals in Tg a -1 Surface/aircraft studies suggest that these emissions are too low by ~factor 2

AIRS, TES, IASI Methane observing system in North America Satellites Thermal IR SCIAMACHY 6-day GOSAT 3-day, sparse TROPOMI GCIRI 1-day geo Shortwave IR Suborbital CalNex INTEX-A SEAC 4 RS 1/2 o x2/3 o grid of GEOS-Chem chemical transport model (CTM)

High-resolution inverse analysis system for quantifying methane emissions in North America GEOS-Chem CTM and its adjoint 50 km resolution over N. America nested in 4 o x5 o global domain Observations Bayesian inversion Optimized emissions at 50 km resolution Validation Verification EDGAR LPJ a priori bottom-up emissions The same inverse analysis system is used at JPL for CO 2 (K. Bowman, PI)

North American methane emission estimates optimized by SCIAMACHY + INTEX-A data (Jul-Aug 2004) ppb SCIAMACHY column methane mixing ratio Correction factors to EDGAR emissions US anthropogenic emissions (Tg a -1 ) EDGAR v EPA 28.3 This work 32.7 Wecht et al., in prep clusters Livestock emissions are underestimated by EPA, oil/gas emissions are not

GOSAT methane column mixing ratios, Oct Retrieval from U. Leicester

Inversion of GOSAT Oct methane Nested inversion with 50x50 km 2 resolution Correction factors to prior emissions (EDGAR LPJ) Alex Turner, Harvard Next step: clustering of emissions in the inversion, use new NASA retrieval

Testing the information content of satellite data with CalNex inversion of methane emissions CalNex observationsGEOS-Chem w/EDGAR v4.2 Correction factors to EDGAR ppb May-Jun 2010 Wecht et al., in prep. S. Wofsy (Harvard) California emissions (Tg a -1 ) EDGAR v CARB 1.51 This work 2.86

GOSAT observations of methane are too sparse to constrain California emissions GOSAT data (CalNex period)) Correction factors to EDGAR emissions Each point = 1-10 observations Wecht et al., in prep. …but they do provide qualitative indication of corrections to emission inventories

TROPOMI (2015 launch) will constrain methane emissions as well as a CalNex-type aircraft campaign Wecht et al., in prep. Correction factors to EDGAR emissions in observation system simulation experiment (OSSE) inversions for CalNex period A geostationary mission (several current proposals) would allow fine-scale monitoring

Working with stakeholders at the US state level State-by-state analysis of SCIAMACHY correction factors to EDGARv4.2 emissions with Iowa Dept. of Natural Resources (Marnie Stein) State emissions computed w/EPA tools too low by x3.5; now investigating EPA livestock emission factors with New York Attorney General Office (John Marschilok) State-computed emissions too high by x0.6, reflects overestimate of gas/waste/landfill emissions Melissa Sulprizio and Kevin Wecht, Harvard Hog manure? Large EDGAR source from gas+landfills is just not there correction factor

What next? Develop a clustering algorithm to extract the maximum information from the GOSAT satellite data Impose a temperature dependence on livestock emissions (can we assume no seasonality for oil/gas emissions?) Conduct a 2009-present inversion of GOSAT data together with surface observations (NOAA, TCCON), interpret results Interact with stakeholders (API!) on the implications of results and to guide future work Get ready for TROPOMI!

satellites suborbital platforms models AQAST Pollution monitoring Exposure assessment AQ forecasting Source attribution Quantifying emissions External influences AQ processes Climate interactions AQAST

AQAST members Daniel Jacob (leader), Loretta Mickley (Harvard) Tracey Holloway (deputy leader), Steve Ackerman (U. Wisconsin); Bart Sponseller (Wisconsin DNR) Greg Carmichael (U. Iowa) Dan Cohan (Rice U.) Russ Dickerson (U. Maryland) Bryan Duncan, Yasuko Yoshida, Melanie Follette-Cook (NASA/GSFC); Jennifer Olson (NASA/LaRC) David Edwards (NCAR) Arlene Fiore (Columbia Univ.); Meiyun Lin (Princeton) Jack Fishman, Ben de Foy (Saint Louis U.) Daven Henze, Jana Milford (U. Colorado) Edward Hyer, Jeff Reid, Doug Westphal, Kim Richardson (NRL) Pius Lee, Tianfeng Chai (NOAA/NESDIS) Yang Liu, Matthew Strickland (Emory U.), Bin Yu (UC Berkeley) Richard McNider, Arastoo Biazar (U. Alabama – Huntsville) Brad Pierce (NOAA/NESDIS) Ted Russell, Yongtao Hu, Talat Odman (Georgia Tech); Lorraine Remer (NASA/GSFC) David Streets (Argonne) Jim Szykman (EPA/ORD/NERL) Anne Thompson, William Ryan, Suellen Haupt (Penn State U.)

What makes AQAST unique? All AQAST projects connect Earth Science and air quality management:  active partnerships with air quality managers with deliverables/outcomes  self-organizing to respond quickly to demands  flexibility in how it allocates its resources  INVESTIGATOR PROJECTS (IPs): members adjust work plans each year to meet evolving AQ needs  “TIGER TEAM” PROJECTS (TTs): multi-member efforts to address emerging, pressing problems requiring coordinated activity Recently selected Tiger Team projects include: Web-enabled AQ management tools AQ reanalysis Dynamical natural inputs for AQ models Source attribution for O 3 and PM events over EUS Oil & gas emissions Satellite-derived NO x emissions and trends click on “projects” for brief descriptions + link to pdf describing each project

Scope of current AQAST projects AQ agency Local: RAQC, BAAQD State: TCEQ, MDE, Wisconsin DNR, CARB, Iowa DNR, GAEPD, GFC Regional: LADCO, EPA Region 8 National: EPA, NOAA, NPS Theme SIP Modeling AQ processes Monitoring AQ-Climate Background IC/BC for AQ models Forecasting Emissions Future satellites Earth Science resource Satellites: MODIS, MISR, MOPITT, AIRS, OMI, TES, GOES, GOME-2 Suborbital: ARCTAS, DISCOVER-AQ, ozonesondes, PANDORA Models: MOZART, CAM, AM-3, GEOS-Chem, RAQMS, STEM, GISS, CMIP We need to find Industry partners!

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Semiannual AQAST meetings Share knowledge and experience in using Earth Science data and tools for serving AQ management Educate AQ managers in the use of Earth Science data and tools, educate Earth scientists on AQ needs Hear about pressing AQ management issues, and determine how AQAST can help AQAST meeting at U. Maryland (June 9-11, 2013) Next meeting (AQAST 6) is January in Houston: We hope to have API members attend, and present!