1. Anthropogenic emissions
Claire GRANIER
Laboratoire d'Aerologie, Toulouse, France

2. 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

3. What needs to be provided for the CAMS simulations and analyses:
Anthropogenic emissions at the global scale
Anthropogenic emissions in Europe
Biogenic VOCs emissions

4. 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:
(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

5. Will be based on recent developments EDGAR 4.2 and EDGAR 4.3 HTAPv2
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

6. 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

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

8. Global scale: how to make up-to-date emissions for CAMS?
Extrapolate from the past 2-3 years
Use inverse modeling results from either
surface 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

9. 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

10. 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 ( )
MEIC (2008 and 2010)
MIX (2008 and 2010)

11. Formaldehyde emissions in China

12. How to better define the short-term temporal variation of emissions
How to implement such temporal profiles?
detailed data only easily and freely available for UK
Are there any recent data available?
CO weekly emissions
NOx diurnal emissions
From work done in the 1990s at TNO: not much details on differences between countries, etc.

13. How to better define the short-term temporal variation of emissions
What could be done, if observations exist
How to implement such temporal profiles?
detailed data only easily and freely available for UK
Are there any recent data available?
Friday Saturday Sunday Monday
NOx emissions (1000 kg/hr)
Gasoline
Diesel
1990
CO weekly emissions
Harley et al., Environ. Sci. Technol., 2005
Based on road-side monitoring in California
1990
2000
NOx diurnal emissions
From work done in the 1990s at TNO: not much details on differences between countries, etc.

14. 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
TNO_MACC-III – CAMS European emission inventory for CO
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
Major shortcoming: most recent year still 2011 – updating to more recent years exceeds what can be done under short term continuity contracts
14 | European emissions
12 June 2016

15. TNO_MACC-III air pollutants 2000-2011
The most used emission inventory for air quality modelling in Europe by
MACC and CAMS air quality forecasts and re-ananlysis
The AQMEII project ( JRC – US EPA AQ model Intercomparison Initiative)
Many individual research teams and policy support studies
Consistent emission trends
Individual countries in the EU-15+NOR+CHE; EU-NMS (13); Non-EU
Example EU15:
15 | European emissions
12 June 2016

16. Example gridded ~ 7 x 7 km TNO-MACC_III emissions data
NOx emissions in 2009 for all sectors
For all details, see Kuenen et al., ACP, 2014

17. TNO-CAMS CO2 inventory (2000-2011) ~7 x7 km detailed by sectors
increasing interest and need for high resolution CO2 data
TNO-CAMS provides split between fossil and biofuel CO2
Here: CO all sectors

18. 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 by
Making 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
18 | European emissions
12 June 2016

19. Official Reported (OR)
EU28 NOx from PC and LDV (Gg/yr) in 2013
Official Reported (OR)
Bottom-Up (BU)
BU Emission standards PC
1348
1338
789
LDV
242
397
154
Total
1590
1735
943
Compared to OR
109%
59%
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
19 | European emissions
12 June 2016

20. 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
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)
20 | European emissions
12 June 2016

21. MEGAN-MACC emission dataset
List of modeled species
(Sindelarova et al., 2014, ACP)
isoprene
a-pinene
b-pinene
other monoterpenes
sesquiterpenes CO
hydrogen cyanide
ethane
propane
butane and higher alkanes
ethene
propene
butene and higher alkenes
methanol
ethanol
formaldehyde
acetaldehyde
other aldehydes
acetone
other ketones
formic acid
acetic acid
toluene
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
time resolution monthly means
spatial coverage global
spatial resolution 0.5° x 0.5°

22. temporal coverage of the MEGAN-MACC dataset developed under the MACC project was 31 years ( )
Isoprene emissions
monthly global totals
Tg.month-1
monthly zonal means
latitude
mg.m-2.day-1
annual totals
Tg.year-1

23. the dataset was extended with 5 more years up to 2015 applying the same methodology
Isoprene emissions
monthly global totals
Tg.month-1
monthly zonal means
latitude
mg.m-2.day-1
annual totals
Tg.year-1

24. Isoprene diurnal cycle in various regions
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 regions
Solid 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)

25. Ask me during the breaks
Where can you get access to most of these datasets + tools to analyze the emissions
ECCAD = Emissions of Atmospheric Compounds and Compilation of Ancillary data
Currently: 2350 users from 848 institutes
Interested in ECCAD?
Ask me during the breaks
Example of usage of ECCAD: MEGAN-MACC downloaded 750 times

26. Thank you for your attention