The 9TH GEOSS Asia-Pacific Symposium
Earth Observations Supporting the Implementation of the SDGs in the Asia Pacific Region
Tokyo, Japan, 11 – 13 January 2017

WG3: THE GEO CARBON AND GHG INITIATIVE

Global Carbon Project (GCP) Regional Carbon Cycle Assessment
and Processes (RECCAP) in Asia
Prabir K. Patra(on behalf of the GCP, RECCAP, APN-GHG contributors)
Department of Environmental Geochemical Cycle Research (DEGCR)
Japan Agency for Marine-Earth Science and Technology (JAMSTEC)

MoE
Suishin-hiTalk outline
CO2 (2007 - )CH4 (2016 - )GCP(GlobalCarbonProject)

Global Budgets(GCP annualactivity)

Regional Budgets(RECCAP);
for IPCC AR5

N2O (2017 ? - )Supported byvarious research
projects –TransCom,TRENDY, FAO, IEA,EDGAR, etc.
Synthesised input
from regional andglobal expertiseGlobal CO2 cycle
Fossil fuel

LUC

Land

www.esrl.noaa.gov/gmd

Ocean

Global Carbon Project: www.globalcarbonproject.org
Le Quéré et al., 2016

1 Gigatonne (Gt) = 1 billion tonnes = 1×1015g =1 Petagram (Pg)
1 kg carbon (C) = 3.664 kg carbon dioxide (CO2)
1 GtC = 3.664 billion tonnes CO2 = 3.664 GtCO2

Emissions from fossil fuel use and industry
Global emissions from fossil fuel and industry: 36.3 ± 1.8 GtCO2 in 2015, 63% over 1990
Projection for 2016: 36.4 ± 2.3 GtCO2, 0.2% higher than 2015

Uncertainty is ±5% for
one standard deviation(IPCC “likely” range)

Estimates for 2014 and 2015 are preliminary. Growth rate is adjusted for the leap year in 2016.
Source: CDIAC; Le Quéré et al 2016; Global Carbon Budget 2016

Top emitters: fossil fuels and industry (absolute)
The top four emitters in 2015 covered 59% of global emissions
China (29%), United States (15%), EU28 (10%), India (6%)

Countries have a broad range of per capita
emissions reflecting their national circumstances

Statistical differences between the global estimates and sum of national totals are 1.2% of global emissions.
Source: CDIAC; Le Quéré et al 2016; Global Carbon Budget 2016

Consumption-based emissions (carbon footprint)
Allocating emissions to the consumption of products provides an alternative perspective
USA and EU28 are net importers of embodied emissions, China and India are net exporters

Consumption-based emissions are calculated by adjusting thestandard production-based emissions to account forinternational trade
Source: Peters et al 2011; Le Quéré et al 2016; Global Carbon
Project 2016

Total global emissions
Total global emissions: 41.9 ± 2.8 GtCO2 in 2015, 49% over 1990
Percentage land-use change: 36% in 1960, 9% averaged 2006-2015

Three different methods have been used to estimate
land-use change emissions, indicated here by different shades of grey
Source: CDIAC; Houghton et al 2012; Giglio et al 2013; Le Quéré et al 2016; Global Carbon Budget 2016

Fate of anthropogenic CO2 emissions (2006-2015)
16.4 GtCO2/yr

44%

34.1 GtCO2/yr

91%

Sources = Sinks

31%

11.6 GtCO2/yr

9%

3.5 GtCO2/yr

26%

9.7 GtCO2/yr

Source: CDIAC; NOAA-ESRL; Houghton et al 2012; Giglio et al 2013; Le Quéré et al 2016; Global Carbon Budget 2016

Global carbon budget
The carbon sources from fossil fuels, industry, and land use change emissions are balanced by
the atmosphere and carbon sinks on land and in the ocean

Partitioning oftotal CO2 emissions

How much flux is to Land and Ocean??
uncertainty grows quickly for regional breakdowns
Source: CDIAC; NOAA-ESRL; Houghton et al 2012; Giglio et al 2013; Jooset al 2013; Khatiwala et al 2013;
Le Quéré et al 2016; Global Carbon Budget 2016

The methane (CH4) context – new to GCP•

After carbon dioxide (CO2), methane (CH4) isthe second most important greenhouse gas
contributing to human-induced climatechange.

•For a time horizon of 100 years, CH4 has a
Global Warming Potential 28 times larger
than CO2.

•Methane is responsible for 20% of the global
warming produced by all greenhouse gases sofar.

•The concentration of CH4 in the atmosphereis 150% above pre-industrial levels (cf. 1750).

•The atmospheric life time of CH4 is 9±2 years,
making it a good target for climate change
mitigation•

Methane also contributes to troposphericproduction of ozone, a pollutant that harms
human health and ecosystems.

•Methane also leads to production of water
vapor in the stratosphere by chemical
reactions, enhancing global warming.

1 teragram (Tg) = 1 million tonnes = 1×1012g; 2.78 Tg CH4 per ppb
Sources : Saunois et al. 2016, ESDD; Kirschke et al. 2013, NatureGeo.; IPCC 2013 5AR; Voulgarakis et al., 2013

An ensemble of tools and data to estimate
the global methane budget
Bottom-up budget
Atmosphericobservations

Emission
inventories

Biogeochemistrymodels & datadriven methods

Methane sinks

Inverse models
Top-down budget

Ground-based
data fromobservation
networks (AGAGE,CSIRO, NOAA,UCI, LSCE, others).
Satellite data
(SCIAMACHY,GOSAT)

Agriculture andwaste related
emissions, fossil
fuel emissions(EDGARv4.2,USEPA, GAINS,FAO).
Fire emissions(GFED3 & 4s,FINN, GFAS, FAO).
Biofuel estimates

Ensemble of 11
wetland models,following theWETCHIMP
intercomparison
Model forTermites
emissions
Other sourcesfrom literature

From Kirschke etal., (2013) Longterm trends anddecadal variabilityof the OH sink.
ACCMIP CTMs
intercomparison.
Soil uptake &chlorine sinktaken from theliterature

Suite of eightatmospheric
inversion models(TM5-4DVAR (JRC& SRON), LMDZMIOP, PYVARLMDz, C-TrackerCH4, GELCA,
ACTM, TM3,
NIESTM).
Ensemble of 30
inversions (diff.
obs & setup)CH4 Atmospheric Growth Rate, 1983-20122000-2006:
0.6±0.1 ppb/yr

2007-2012:
5.5±0.6 ppb/yr• Slowdown ofatmospheric
growth rate
before 2006
• Resumed increase
after 2006
Figure compiled by:
Saunois et al. 2016

Atmosphericobservations

Data Source: Prinn et al., Dluegokencky et al., Blake et al., Steele et al. and others(Nakazawa et al., Tohjima et al. , Tsuboi et al.)Global Methane Budget 2003-2012

http://www.globalcarbonatlas.org

Global methane emissions 2003-2012
Bottom-up budget(TgCH4/yr)

Top-down budget

185 [40%]  Natural wetlands  167 [80%]
195 [15%]  Agriculture & waste  188 [65%]Rice
30 [10%]Enteric ferm & manure
106 [20%]
Landfills & waste
59 [20%] Fossil fuel use 121 [20%]105 [50%]Coal
42 [80%]Gas & oil79 [10%]30 [30%] Biomass/biofuel burning 34 [55%]
199 [90%] Other natural emissions 64 [150%]
Fresh waters 122 [100%]
Mean [uncertainty=Wild animals
10 [100%]
min-max range %]Wild fires
3 [100%]Termites
9 [120%]Geological40 [50%]Oceans3 [100%]
Permafrost
1 [100%]Mean [uncertainty=min-max range %]Bottom-up
budgetBottom-up budget
Process models, inventories,
data driven methods
734 TgCH4/yr [596-884]

Mean [min-max range %]Source : Saunois et al. 2016, ESSD

Top-down budget
Top-downbudgetAtmospheric inversions

559 TgCH4/yr [540-568]

REgional Carbon Cycle Assessment and Processes>130 collaborators

Land
L1 Africa
L2 Arctic tundra
L3 Australia
L4 Europe
L5 North America
L6 Russia
L7 South America
L8 East Asia
L9 Southeast Asia
L10 South Asia
OceansO1 Pacific
O2 Atlantic and Arctic
O3 Southern Ocean
O4 Indian

RECCAP (2007-2013)

Global• Fossil Fuel Emissions• Land Use Change emissions• Riverine transport• Atmospheric inversions• Marginal seas
• Interior ocean• Air-sea flux
Canadell et al., EOS, 2011
• Coastal zones

Components of Regional Syntheses
Tier 1

Tier 2Global Products

Regional-Specific Products

Regional fluxes
Atmospheric CO2
Inversion Models

Regional
application+

TransCom

Atmospheric CO2
Inversions Model+ Global Obs. Network+ Regional ghg obs.

(High resolution)(Low resolution)

Regional Carbon Balance

Regional cuts
from global land& ocean models(Low resolution)+Regional cuts
from global
data products

Tier 1 model outputs are coordinated by RECCAP+Regional specificModels(continental, oceanbasin, biome,land use change,others)+

Regional
specific
observations(fluxes, pCO2,remote sensing,forest inv., others)

Australia CO2 Budget (1990-2011)[CO2-TgC yr-1]

Atmosphere
Fossil Fuel
Emissions
Fire
[+95]
[+104]

CropConsum.
[+9]

Bottom-up
estimations
only

Livestock

1990-2011Land Use
Change
[+18]

+20
Soil
Respiration[+1997]
Net Primary
Production[-2210]

Wood
Decay
[+5]

ConsumFossil Fuels[+2]

Wood+235

Crops

Biosphere

Livestock-59
Wood
ExportLivestock[-0.3]
Export[+1]
Crop
Export[+11]

Fossil Fuel
ExportRiverine[+140]
Transport (+2)

Non-Territorial
Haverd et al. 2013 a, b.
Biogeosciences

DustExport[+2]+155

The South Asian Carbon Budget
Atmosphere
Crop &Livestock
Consump.

Nitrous
Oxide,
CarbonMonoxide& Black
CarbonHeterotr. Respir.
(+1993)
Net Primary
Production(-2213)

Wood
Decay

Bottom-up
estimations
and top-down
estimations

Asia Pacific Network (APN)
for Global Change Research(ARCP2013-01CMYPatra/Canadell)Fire(44)

LandUseChange(-14)

Biosphere-147+444
Wood,
Crop, &Livestock- Net
TradeBalanceLivestock
ExportMethane(+37)

Riverine
Transport(+43)

Dust &Aerosol
ExportNon-Territorial Carbon Stocks
Patra et al. 2013, Biogeosciences

FFEmission(+444)

FossilFuelImport

The Southeast Asian Carbon budget
Bottom-up Budget[2000-2009]
NPP(-5,100)

Rh(+4,800)

NEE(-350)[TgC yr-1]

Atmosphere
Peat Fires
LUC
Peat Oxi.
(+194) (+48)(+117)

Methane(+46)

Fossil Fuels(+254)

Biosphere
CO2 Source: 209± TgC yr-1
Net Balance (All fluxes)
Source: 588± TgC yr-1

Asia Pacific Network (APN)
for Global Change Research(ARCP2013-01CMYPatra/Canadell)Canadell, Patra et al, in preparation

River Exp.
(+37)

TradedWood(+13)

TradedCrops(+68)

TradedLivestock(-0.2)

TradedEmbodied
FF Energy Goods & Serv.
(+50)
(+37)

Non-Territorial Emissions

Current understanding (IPCC-2013)
Decadal average CO2 fluxes for 11 land regions

Land to atmosphere-: sink

IPCC AR5, 2013
Fig. 6.15 (by P. Patra)

1990’s2000’s+: source

1990’s2000’sBottom-up approach：10 DVGMs (TRENDY)
Top-down approach：10 atmos. Inversions (TransCom)1324

Data access

More information, data sources and data files:www.globalcarbonatlas.org(funded in part by BNP Paribas Foundation)

Contact: philippe.ciais@lsce.ipsl.fr

How the Earth observations
can help us further?

Our Evolved Philosophy for inverse modelling:
going multi-species and more accurate transport
Concentration

Emission/Sinks

Chemistry/Loss
Transport
CH4+OH/O1D/Cl 

CCSR/NIES/FRCGC AGCM5.7b-based Chemistry-Transport Model (ACTM) is developed in JAMSTEC(AGCM by Numaguti et al.; CTM by Takigawa et al.; GHGs/ODSs by Patra/Ishijima et al.; EnKF by Miyazaki et al.)

53-Regions (land only) Inverse Model for CH4CH4 concentration (ppb)

27.

39.

S0 = regional prior sources
CS0 = Prior source covariance = 50% of region-total emission for each monthD = atmospheric concentration data
CD = Data covariance = 10 ppb; 5 ppb for measurements + 5 ppb for model
DACTM = ACTM simulation using S0
G = Green’s functions for regional source-receptor relationships
Patra et al., J. Meteorol. Soc. Jpn., 2016

CH4 emission trends and variability –Validation using Tohoku University observations over Sendai
East Asia (China, Japan, Korea)

Tropical Land (Africa, America, Asia)

3-5%/yr increase in CH4 emission of East Asian emission; about half of the prior
Validation of emissions using Tohoku Univ. aircraft data
Umezawa et al. (2014)

APN Asian GHG project:results from CO2 inversion
In East Asia, the annual CO2 sink increased between
1996–2001 and 2008– 2012 by 0.56 (0.30–0.81) PgC,
East Asia (China, Japan, Korea, Mongolia)

Ensemble of 7 inverse models (incl. JAMSTEC’s ACTM)
Thompson et al., Nature Comm., 2016

• Afforestation・ reforestation andrevegetation ・ CO2 fertilization ??
• Error in anthropogenic emission ??

Do uncertainties in fossil fuel emission affect
East Asian CO2 inversion?
From inventories

As used in inverse models

Validation of inversion fluxes using
JAL-CONTRAIL CO2 data over the East
Asia region remained inconclusive
Thompson et al., Nature Comm., 2016

Summary• Global budgets of major greenhouse gases are being produced bysynthesizing a large amount of data sources, involving hundreds ofscientists:– GCP-CO2 (2007-) : Annual updates on global CO2 budgets and sectorial
breakdown of (1) emissions from fossil fuel and land-use change, (2) sinks in to
the terrestrial and oceanic surfaces– GCP-CH4 (2016-) : One of the complex exercise producing numerous sectorial
emissions using a variety of methods, and chemical loss budgets in thetroposphere and stratosphere– GCP-N2O (2017-) : in planning, which will prepare global sources and sinks due
to agricultural activities, natural processes, stratospheric loss etc.

• Future needs are proposed toward better assessments of regional GHGs
budgets and their trends– For monitoring, reporting and verification (MRV) of national reporting– For understanding the role of human activity and natural variability on theclimate change and their feedbacks– Most, if not all, regional GHG budgets are severely under-constrained byobservations – coverage and data types (molecular and isotopes) should be
increased– Uncertainties in global atmospheric and vegetation dynamics models –supplemental measurements of chemical and transport tracers, and carbonnitrogen poolsSatellite

The future – is brightSatellite: OCO-2 & GOSAT

in situ network&ModelNotes – day 1••AO-GEOSS : Asia-Oceanic GEOSS (Osamu Ochai), there is also AmeriGEOSS, AfrGEOSSReduction of food waste – a low hanging fruit (Sanjaasuren Oyun)•AOGEOSS:––•TG3 : Carbon cycle and response to climate change
TG9 : Himalayan task group, led by ICMODTWO QUESTIONS:–––

1. what are the data needs for transforming observations to information for decision making? Koike:
How to convince, to work together, have a protocol?; GEO-BOB: gather quality data and combine
them, GEO-Carb: something useful to the users, data scattered in different repository, BluePlanet:need both in situ and satellite data, top-down and bottom-up perspective for data – what the users
need & how data can be used, GEOGLAM: data are needed for timely crop monitoring, challenge isto transform big amount of data in to information
2. What should be discussed tomorrow? GEOGLOWS: each country should protect themselves, butfor effectiveness international communities should work together, GEO-BON: , GHG: needs of theregion, data gaps, how can be …, BluePlanet: main ocean acidification (7.9 or 8.2?), and its effect on
biosphere, data availability, GLAM: multi-platfom observations, SDG20130:
Audience: Nakajima: dialogue between the govt and GEO

Notes – day 2• Antonio:#2 Have a common platform for MRV
GEO-C: towards policy-relevant global carbon cycle observations
Lack of communication: inter- and intra- groups (obs, mod, user)
Tasks: Optimal observation network, GHG budgets
Deliverables : annual budgets – PKP: why not work towards improving the budgets –valid point?
– Q. Nakajima – what about including SLCFs? – Antonio: we focus on carbon, PKP: weactually include Methane–––––• Hiroyuki: GEO2017-2019 & SDGs
• Liu : TanSat is launched on 22 December 2016 (video shown)– Showed my Land IPCC figure, Jiang’s CT-China budget• CS Jha: Reddy et al., Env. Monit. Assess. 2015
– Most carbon sinks in Biospheric reserves in India – invasive species are the biggebst
problem– Vegetation carbon pools: many 10, 000 forest AGB obs plots, plus a lot of works (Chaveet al, Phil. Trans. Roy. Soc., 2004)– Reddy et al., Global Planetary Change, accepted. (carbon mapping for all south asiancountries)• Toshinobu: CONTRAIL– GEO should produce data summary from all data providers, with QA/QC statements

Regional Methane Sources (2003-2012)
Source: Saunois et al. 2016 ESSD (Fig 7)•Largest emissions in TropicalSouth America, South-East Asiaand China (50% of globalemissions)•Dominance of wetland
emissions in the tropics andboreal regions•

Dominance of agriculture &waste in India and China•

Balance between agriculture &waste and fossil fuels at midlatitudes•

Uncertain magnitude of wetland emissions in boreal regions between TD and BU•Chinese emissions lower in TD than in BU, African emissions larger in TD than in BU
Emission
inventories

Biogeochemistrymodels & datadriven methods

Inverse models