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Use of satellite and suborbital observations to constrain North American methane e missions in the Carbon Monitoring System. Daniel Jacob (PI), Steven Wofsy (Co-I ), Kevin Wecht , Alex Turner, Greg Santoni , Melissa Sulprizio. Harvard University. - PowerPoint PPT Presentation
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Use of satellite and suborbital observations to constrain North American methane emissions
in the Carbon Monitoring System
Daniel Jacob (PI), Steven Wofsy (Co-I), Kevin Wecht, Alex Turner, Greg Santoni, Melissa Sulprizio
Harvard University
Vivienne Payne (Co-I), Kevin Bowman (Co-I), Meemong Lee (Co-I), John Worden
NASA JPL
Importance of methane for the Carbon Monitoring System
• Present-day emission-based forcing of methane is 0.95 W m-2 (IPCC AR5)
• Climate impact of methane is comparable to CO2 over 20-year horizon
• Methane is a low-hanging fruit for climate policy
• Natural gas and hydrofracking are changing US sources
• Methane is a central piece of the President’s Climate Action Plan
Building a methane monitoring system for N Americaintegrated into the CMS
EDGAR emissionInventory 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
2002 2006 2009 20015 2018
Thermal IR
SCIAMACHY 6-day
GOSAT3-day, sparse
TROPOMI GCIRI 1-day geoShortwave IR
Suborbital
CalNex
INTEX-A
SEAC4RS
1/2ox2/3o 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 adjoint1/2ox2/3o over N. America
nested in 4ox5o global domain
Observations
Bayesianinversion
Optimized emissionsat 1/2ox2/3o resolution
Validation Verification
EDGAR 4.2 + LPJa priori bottom-up emissions
The same CMS inverse analysis system is used at JPL for CO2 (K. Bowman, PI)
Optimization of state vector for adjoint inversion of SCIAMACHY data
Optimal clustering of 1/2ox2/3o gridsquares
Correction factor to bottom-up emissions
Number of clusters in inversion1 10 100 1000 10,000
34
28
Optimized US anthropogenic emissions (Tg a-1)
posterior cost function
Native resolution 1000 clusters
SCIAMACHY data cannot constrainemissions at 1/2ox2/3o resolution;use 1000 optimally selected clusters
Kevin Wecht, Harvard
North American methane emission estimatesoptimized by SCIAMACHY + INTEX-A data (Jul-Aug 2004)
1700 1800ppb
SCIAMACHY column methane mixing ratio Correction factors to a priori emissions
Livestock Oil & Gas Landfills Coal Mining Other0
5
10
15US anthropogenic emissions (Tg a-1)
EDGAR v4.2 26.6
EPA 28.3
This work 32.7
Wecht et al., in prep.
1000 clusters
Livestock emissions are underestimated by EPA, oil/gas emissions are not
GOSAT methane column mixing ratios, Oct 2009-2010
Retrieval from U. Leicester
Inversion of GOSAT Oct 2009-2010 methane
Nested inversionwith 1/2ox2/3o resolution
Correction factors to prior emissions (EDGAR 4.2 + LPJ)
Alex Turner, Harvard
Next step: clustering of emissions in the inversion, use of ACOS data
Testing the information content of satellite datawith CalNex inversion of methane emissions
CalNex observations GEOS-Chem w/EDGAR v4.2
0.1 1 3
Correction factors to EDGAR(analytical inversion)
1800 2000ppb
May-Jun2010
State of California Los Angeles Basin0
0.51
1.52
2.53
3.5CA Air Resources BoardEDGAR v4.2Santoni et al. Lagrangian (STILT) inversionGEOS-Chem inversion
Emis
ssio
ns, T
g a-1
Wecht et al., in prep.
2x underestimateof livestock emissions
S. Wofsy (Harvard)
GOSAT observations are too sparseto spatially resolve California emissions
GOSAT data (CalNex period))Correction factors to methane emissions from inversion
GOSAT (CalNex period) GOSAT (1 year)
CalNex aircraft data
GOSAT(CalNex)
GOSAT(1 year)
Degrees of Freedom for Signal (DOFS) in inversion of methane emissions
15 1.2 2.8
Each point =1-10 observations
0.5 1.5
Wecht et al., in prep.
TROPOMI and GCIRI constrain state-level methane emissions better than a dedicated aircraft mission
TROPOMI (global daily coverage) GCIRI (geostationary 1-h return coverage)Correction factors to EDGAR v4.2 a priori emissions from a 1-year OSSE
A priori CalNex TROPOMI GCIRI TROPOMI+GCIRI
DOFS 15 17 23 26
California emissions (Tg a-1) 1.9 3.1 3.0 3.0 3.0
0.2 1 5
Wecht et al., in prep.
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+landfillsis just not there
0 1 2correction factor
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