VOC emissions in the Middle East

from bottom-up inventories &

as seen by OMI

J.-F. Müller, T. Stavrakou, I. De Smedt, M. Van Roozendael

Belgian Institute for Space Aeronomy (BIRA-IASB)

GLOBEMISSION USER CONSULTATION MEETING Doha, Qatar, 24-25 November 2015

Outline

• The view from below: a first look at emission inventories over the Middle East

• First confrontation with satellite (OMI) HCHO

• Revising NMVOC emission inventories over the Middle East

• Apply inverse modelling of OMI data using a global CTM to quantify NMVOC emissions over Middle East

• Conclusions

A first look at inventories: natural vs anthropogenic

Impact of soil moisture stress on biogenic isoprene

• In Middle East: huge effect of soil moisture stress on emissions according to MEGAN

• However, very poorly constrained parameterization ! Does not account for the fact that plants are accustomed to lack of soil water

Anthropogenic emission inventories (here at 0.5°x0.5°)

• Large discrepancies between inventories • MACCity similar to RETRO, only higher • Poor representation of cities, oil/gas

related emissions • EDGAR4 : better but with strange features

Contributions of different emission sectors to NMVOC

emissions in the Middle East in EDGAR4.2

60%

26.5%

4.8%

6.5%

In summary : • Residential sector:

unimportant in Gulf area • Solvent industry: only at few

large cities • Road transport: many cities

missing! (Riyadh, Dubai, Basrah, etc.)

• Fossil fuel production: many

point sources, but distribution is questionable

Confronting EDGAR4.2 with OMI (at 0.5°x0.5°)

high oil-related EDGAR emissions in NE S.Arabia

low EDGAR emissions

in Southern Iraq not supported by OMI data!

Also: emission underestimations in Qatar, Emirates, Southern Iran coast, Northern Iraq…

Data provided by I. De Smedt @ BIRA-IASB Here only clear-sky pixels are used

x10-11

Can we improve the distribution of road emissions?

Obvious flaws in available population density map in the Middle East – e.g. from the SEDAC (http://sedac.ciesin.columbia.edu)

For highly urbanized countries*, use urban population distribution constructed from database of cities (Geonames, http://download.geonames.org/)

* : UAE, Qatar, S. Arabia, Bahrein, Iraq, Oman

Disparities in country-level

road emissions from EDGAR

Very low per capita emissions in e.g. Turkey & Egypt likely unrealistic

0 20 40 60

U.A.E.

Qatar

Oman

Kuwait

Iran

S. Arabia

Bahrein

Iraq

Lebanon

Jordan

Israel

Syria

Turkey

Egypt

Per capita NMVOC emissions (kg/year) in

2007

Adopt minimum of 10 kg NMVOC / year for all countries

Road emission adjustment

NMVOC sources due to oil/gas production :

• Evaporative losses (oil spills, etc.)

• Gas flaring and venting (mostly at oil wells)

• Gas leakages during transmission, storage, loading

• Transformation in refineries and petrochemical plants

Can we improve the distribution of emissions

related to oil/gas production?

Complex !

Need proxies for oil/gas extraction &

handling

Can we improve oil/gas emissions?

1. Refineries

Country Name (owner) Capacity

‘000 bpd

Latitude Longitude

EGYPT Alexandria El Mex (EGPC) 117 31.04 29.67

EGYPT Cairo Mostorod (EGPC) 142 27.02 31.00

EGYPT El Nasr (EGPC) 132 29.96 32.53

EGYPT El Sokhna (Bashandy Oil) 300 29.60 32.32

IRAN Arvand (Private) 115 30.44 48.18

IRAN Tabriz (NIOC) 112 38.08 46.29

IRAN Abadan (NIOC) 450 30.34 48.30

IRAN Arak (NIOC) 250 34.09 49.69

IRAN Tehran (NIOC) 225 35.69 51.42

IRAN Isfahan (NIOC) 265 32.65 51.67

IRAN Bandar Abbas (NIOC) 335 27.19 56.28

IRAQ Basrah (INOC) 210 30.53 47.80

IRAQ Daurah (INOC) 180 33.20 44.40

IRAQ Kirkuk (INOC) 170 35.47 44.39

IRAQ Baiji North (INOC) 150 34.94 43.49

ISRAEL Haifa (Oil Ref Ltd.) 196 32.82 34.99

KUWAIT Mina Al-Ahmadi (KNPC) 470 29.07 48.08

KUWAIT Mina Abdullah (KNPC) 270 29.32 47.49

KUWAIT Shuaiba (KNPC) 200 29.03 48.17

OMAN Sohar SRC (ORPIC) 116 24.35 56.73

QATAR Um Said (QP) 147 24.98 51.55

QATAR Lafan 146 25.91 51.55

S. ARABIA Rabigh (Aramco/Smitomo) 400 22.80 39.03

S. ARABIA Riyadh (Aramco) 120 24.46 46.82

S. ARABIA Ras Tanura (Aramco) 550 26.65 50.17

S. ARABIA Yanbu SAMREF (Aramco/Exxon) 400 24.08 38.07

S. ARABIA Jubail SATORP (Aramco/Total) 400 27.00 49.67

S. ARABIA Yanbu YASREF (Aramco/Sinopec) 400 24.08 38.07

S. ARABIA Jubail SASREF (Aramco/Shell) 305 27.00 49.67

UAE Takreer Ruwais 420 24.13 52.71

UAE Jebel Ali 120 25.00 55.05

Database of large refineries (here >100 000 bpd)

2. Terminals & other facilities

Country Name Capacity latitude longitude

IRAN Kharg Island 3 29.23 50.31

IRAN Lavan Isl. 0.2 26.81 53.26

IRAN Sirri Isl. 0.1 25.91 54.54

QATAR Halul Isl. 0.25 25.68 52.42

QATAR Ras Laffan 0.2 25.91 51.55

IRAQ Al Basrah 3 29.68 48.81

S. ARABIA Ras Tanura 3.4 26.65 50.17

S. ARABIA Ras al Ju’aymayah 3.0 26.95 50.05

S. ARABIA Yanbu 1.3 24.09 38.06

S. ARABIA Abqaiq 5.0 25.99 49.67

KUWAIT Mina al Ahmadi 2.0 29.13 48.13

UAE Fujairah 2.0 25.12 56.35 Database of terminals & processing sites

3. Gas flares Use flare CO2 emissions from nighttime VIIRS observations in the infrared

Rumailah oil fields, Iraq

Ghawar oil fields, Saudi Arabia

Can we improve oil/gas emissions?

Oil/gas-related emission adjustment

Methodology : • Keep EDGAR4 total emission over the area (5.4 Tg/year) • Re-distribute using the proxies : 3 Tg for flaring, 2 Tg refineries, 0.5 Tg/yr terminals

Are our proxies appropriate? Confront to OMI

Zooming into the Gulf area

Use oversampling to increase horizontal resolution of OMI data : map 7 years of OMI data to a 0.1°x0.1° grid

Zooming into the Gulf area

The impact of gas flares

Zooming into Egypt

Inverse modelling of emissions

• Use monthly averaged HCHO data averaged over 2009-2014

• Global CTM IMAGESv2 at 2°x2.5°

• Isoprene a priori emissions: neglect soil moisture stress

• Express e.g. anthropogenic emissions as

and optimize emission parameters fj

• Same for biogenic emissions

• Use adjoint model technique

m

j

jjj txfftxG1

),()exp(),,(

A priori emissions

Inverse modelling results: emission updates

• Moderate changes (mostly increases) in isoprene fluxes • Anthropogenic VOC emissions decreased over Gulf area, especially Southern Iraq • Anthropogenic VOC emissions increased over Turkey

Inverse modelling results: HCHO columns

• Nice posterior agreement over Gulf area and Turkey

• Underestimations persist e.g. over Egypt

Inverse modelling results: HCHO columns

Inverse modelling results: HCHO columns

Impact of anthropogenic emissions on ozone

• Ozone production is primarily NOx-limited in

the Middle East

• EDGAR4.2 requires substantial revision in the Middle East

• Isoprene emissions in MEGAN-MOHYCAN inventory is likely strongly

underestimated due to poor parameterization of soil moisture stress

• Inversion of emissions using OMI data indicate

overestimation of oil-related (flares) emissions

underestimation (factor 2) of anthropogenic emissions over Turkey

biogenic isoprene emissions are significant in Northern Iran, Iraq, Syria

• Ozone production in summer is primarily NOx-limited, although VOC

emission reduction would have a measurable effect (up to ~6 ppbv)

Conclusions