Copernicus Atmosphere Monitoring Service

CAMS General Assembly, Athens, 14-16 June 2016

Claire GRANIERLaboratoire d'Aerologie, Toulouse, France

Anthropogenic emissions

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Co-authors:• Claire Granier, Laboratoire d'Aerologie, Toulouse, France• Katerina Sindelarova: UPMC, Paris and University of

Prague, Czech Republic• Thierno Doumbia: LATMOS, CNRS, Paris• Louise Granier, UPMC, Paris• Hugo Denier van der Gon, Jeroen Kuenen, TNO,

The Netherlands

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What needs to be provided for the CAMS simulations and analyses:

- Anthropogenic emissions at the global scale- Anthropogenic emissions in Europe- Biogenic VOCs emissions

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Anthropogenic emissions at the global scale

Currently used in CAMS = MACCity (inventory developed as part of the MACC and CityZen EU projects) (details in Granier et al., 2011)

Advantages: 1960-2016 (extended using RCP 8.5 scenario) consistent among all species VOCs speciation available Very simple seasonal variation

Main issues: Emissions after 2000 based on the RCP 8.5 scenario only MACCity does not take into account recent work in different world regions 0.5x0.5 degree resolution, 0.1x0.1 degree would be much better

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Preparation of the new global inventory used in CAMS (resolution of 0.1x0.1 degree globally)Will be based on recent developments- EDGAR 4.2 and EDGAR 4.3- HTAPv2- ECLIPSEv5- Regional inventories (TNO-MACC, EPA, Env. Canada and Asian

emissions)+ use of the work currently under way for developing the new inventory for the IPCC runs. Currently called CEDS

Evaluation of all these inventories to define the methodology to build the new dataset

Major shortcoming: just preparatory work – building the new dataset exceeds what can be done under short term continuity contracts

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Comparison of inventories: CO

Large differences among the datasets – Major issues found in the CEDS dataset work with the CEDS group to improve emissions in some regions

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Very large differences in spatial distributions More work needed to define the best spatial resolution, for example using global/regional models.

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Global scale: how to make up-to-date emissions for CAMS?

- Extrapolate from the past 2-3 years

- Use inverse modeling results from eithersurface or satellite observations

Several questions on the use of inverse techniques: Results are strongly model-dependent Uncertainties on other sources (biomass burning and/or biogenic) could lead to errors in the optimization of anthropogenic emissions The emissions of one species (either CO, or NO2, or VOCs) are

optimized in each system. What about the other co-emitted species? Use of optimized emissions for of only one species could lead to inconsistencies

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Evaluation of inverse modeling results

The IGAC (International Global Atmospheric Chemistry Project) will launch on September 30th an assessment of inverse modeling techniques and results (during the IGAC 2016 conference)

Co-chairs of the assessment: Greg Frost (USA), Claire Granier (France) + 1-2 more co-chairs to be added

Outcome: a detailed report with review of previous work,Recommendations for use, recommendations for future work+ 2-3 review papers

Involvement of several CAMS partners + users expected

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How to improve the speciation of VOCs

Most inventories provide only information on total VOCs emissions

But:- Modeling needs information on each individual VOC- Conversion to concentration requires the knowledge of the mass

(or composition) of the compound

Very few inventories provide information on VOCs speciation:- MACCity (global, speciation based on RETRO developed in 2000)- REAS v2 (2003-2008)- MEIC (2008 and 2010)- MIX (2008 and 2010)

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Formaldehyde emissions in China

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How to implement such temporal profiles?

detailed data only easily and freely available for UK

Are there any recent data available?

How to better define the short-term temporal variation of emissions

NOx diurnal emissions

From work done in the 1990s at TNO: not much details on differences between countries, etc.

CO weekly emissions

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How to implement such temporal profiles?

detailed data only easily and freely available for UK

Are there any recent data available?

How to better define the short-term temporal variation of emissions

NOx diurnal emissions

From work done in the 1990s at TNO: not much details on differences between countries, etc.

CO weekly emissions

What could be done, if observations exist

Friday Saturday Sunday Monday

NO

x em

issi

ons (

1000

kg

/hr)

GasolineDiesel

1990

Harley et al., Environ. Sci. Technol., 2005Based on road-side monitoring in California

19902000

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Overview – European emission inventories

High resolution, consistent European emission inventories developed under EU FP MACC I & II and EU H2020 MACC–III• TNO_MACC-I, II & III for air pollutants 2000-2011• TNO_MACC-III – CAMS European emission inventory for CO2 2000-2011

Activities under the CAMS service continuity subcontracts• Contact with new users, providing emissions data, clarification of the

emission set if needed, etc.• Documenting and releasing the CAMS CO2 grids• Influence of “dieselgate”on the TNO-MACC emission totals? • Investigation for a better distribution for international shipping emissions

14 | European emissions 12 June 2016

Major shortcoming: most recent year still 2011 – updating to more recent years exceeds what can be done under short term continuity contracts

TNO_MACC-III AIR POLLUTANTS 2000-2011The most used emission inventory for air quality modelling in Europe by

MACC and CAMS air quality forecasts and re-ananlysisThe AQMEII project ( JRC – US EPA AQ model Intercomparison Initiative)Many individual research teams and policy support studies

12 June 201615 | European emissions

Consistent emission trends 2000-2011 Individual countries in the EU-15+NOR+CHE; EU-NMS (13); Non-EU

Example EU15:

For all details, see Kuenen et al., ACP, 2014http://www.atmos-chem-phys.net/14/10963/2014/acp-14-10963-2014.pdf

Example gridded ~ 7 x 7 km TNO-MACC_III emissions data NOx emissions in 2009 for all sectors

TNO-CAMS CO2 INVENTORY (2000-2011) ~7 X7 KM DETAILED BY SECTORS

Here: CO2 2009 all sectors

increasing interest and need for high resolution CO2 data TNO-CAMS provides split between fossil and biofuel CO2

A QUESTION FROM USERS: HOW MUCH WILL THE TNO-MACC DATA FOR NOX CHANGE DUE TO “DIESELGATE”The problem: EU Emission Standards much lower than real world emissions

In the EU about 40% of the NOx emission is from road transport This 40% is about half due to passenger cars and light duty vehicles and the other half due to heavy duty vehicles (HDV)

We analyzed the emissions from PC and LDV byMaking a bottom-up inventory and applying consistent emission factors (EFs) following real world EFs, type approval EFs and comparing with country reported data as used in TNO-MACC_III. Quantify the differences and the impact on NO2 concentrations

12 June 201618 | European emissions

Official Reported (OR)

Bottom-Up (BU)

BU Emission standards

PC 1348 1338 789LDV 242 397 154Total 1590 1735 943Compared to OR 109% 59%

12 June 201619 | European emissions

EU28 NOx from PC and LDV (Gg/yr) in 2013

Preliminary Conclusions• Overall countries report for similar to a real world bottom-up estimate but LDV is

underestimated. Impact of dieselgate on TNO-MACC_III is limited.• But… There is large country variation! (next slide)• If Euro standards would be representative emissions would be > 40% lower• This is a conservative estimate, recent studies suggest that real world emission

factors may need further upward correction. Also HDV not included

PRELIMINARY RESULT OF USING THE EMISSION SCENARIOS IN THE LOTOS-EUROS AQ MODEL

Change in NO2 concentration Bottom-Up minus Official Reported (Blue: OR emission is higher).

Difference between countries varying from ± 10% in NO2

12 June 201620 | European emissions

Reduction in NO2 concentration if the emissions standard would be “real world”

Up to 15% lower NO2 compared to official reported emissions (important for exceedances and exposure)

MEGAN-MACC emission dataset

time resolutionmonthly means

spatial coverage globalspatial resolution 0.5° x 0.5°

isoprenea-pineneb-pinene

other monoterpenessesquiterpenes

COhydrogen cyanide

ethanepropane

butane and higher alkanesethene

propene butene and higher alkenes

methanolethanol

formaldehydeacetaldehyde

other aldehydesacetone

other ketonesformic acidacetic acid

toluene

List of modeled species(Sindelarova et al., 2014, ACP)

• dataset of biogenic VOC emissions• modeled by the MEGANv2.1 (Model of

Emissions of Gases and Aerosols from Nature, Guenther et al. 2012)

• driving meteorology from MERRA reanalysis (NASA Goddard Space Flight Center)

• actual MODIS Leaf Area Index data after 2000, climatological values prior 2000

• landcover distribution defined by 16 plant funtional types from CLM4 (Community Land Model)

Isoprene annual mean / mg.m-2.day-1

mon

thly

glo

bal t

otal

sla

titud

ean

nual

tota

lsm

onth

ly z

onal

mea

ns

mg.m-2.day-1

Tg.year-1

Tg.month-1

• temporal coverage of the MEGAN-MACC dataset developed under the MACC project was 31 years (1980-2010)

Isoprene emissions

mon

thly

glo

bal t

otal

sla

titud

ean

nual

tota

lsm

onth

ly z

onal

mea

ns

mg.m-2.day-1

Tg.year-1

Tg.month-1

Isoprene emissions

• the dataset was extended with 5 more years up to 2015 applying the same methodology

• hourly emission fields from the MEGAN-MACC dataset serve to improve representation of the diurnal cycle of biogenic VOC emissions in the C-IFS system

• the revised diurnal cycle scheme to be implemented for the CAMS reanalysis

Isoprene diurnal cycle in various regionsSolid line = MEGAN-MACC Dashed line = Current representation in the C-IFS

Dot-and-dashed line = Revised representation for the C-IFS

(courtesy of Vincent Huijnen, KNMI)

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Where can you get access to most of these datasets + tools to analyze the emissionsECCAD = Emissions of Atmospheric Compounds and Compilation of Ancillary data http://pole-ether.fr/eccadCurrently: 2350 users from 848 institutes

Interested in ECCAD?Ask me

during the breaks

Example of usage of ECCAD: MEGAN-MACC downloaded 750 times

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Thank you for your attention