Impact of high-resolution CEMAP emission data on EMEP model output - - PowerPoint PPT Presentation

Impact of high-resolution CEMAP emission data

• n EMEP model output

(The mosiac bottom-up inventory)

Kees Cuvelier ex European Commission JRC-Ispra Fairmode Technical meeting Madrid, 7-9 October 2019

Towards a mosaic EU inventory?

European top-down National Region City

Assumption: local is better

Towards a mosaic EU inventory?

“Mosaic” inventory “Mosaic” scenarios “Mosaic” SHERPA SRR “Mosaic” base-case map AQM

Towards a mosaic EU inventory?

 One of the criticism made to SHERPA relates to the quality of the emission inventories. The mosaic inventory would solve (at least partially) this issue and provide a SHERPA tool based on local data.  The mosaic concentration can be included in the composite mapping for comparison  The mosaic (inventory and concentrations) will present inconsistencies (e.g. border effects) which can trigger discussions and (hopefully) lead to improvements

• At this stage, this work is a proposal that need to be discussed within the FAIRMODE

community (starting today!)

• Sensibilities on emissions (especially data sharing) are important. It is important to stress that

data is kept within FAIRMODE. At a later stage, only open emission sources could be included.

Context:

• Composite mapping of emissions WG2 Fairmode
• Contributions from …
• Contributions: scale and resolution
• All in SNAP activity sectors
• Web application for visualization – VITO
• High-resolution inventories, CEMAP
• EMEP model for air quality
• EMEP-CAMS emission inventory
• Resolution .1 x .05 degrees
• Based on the GNFR activity sectors

Question: What is the impact on EMEP model output of an implementation

• f the high-resolution CEMAP emission data into the EMEP-CAMS

inventory.

X Y

CEMAP inventory Local CS – EPSG code

Lon Lat

Subdivision Δ <= 1 km CS transformation based on EPSG to WGS84 (EPSG 4326) Subdivision Δ (~3 km) Aggregation to EMEP-CAMS Δ cells EMEP-CAMS

After aggregation No Scaling For each {pollutant & sector} For each pollutant {sum of sectors} Scaling wrt EMEP-CAMS country totals: New Inventory Outside Domain Scaling (Regional) Country Scaling

Example: Poland, Małopolska, CAMS, NOx, S2 (GNFR3), [Ton/cell]

max=4349. Krakow=175.8 Warsaw=397.0

Add EI inv EMEP-CAMS: Europe Poland Małopolska CEMAP Małopolska data NOx SNAP2

• 1. x 1. km2

235 x 136

NOx & GNFR3 (No Scaling) Poland Total = 89773. [Ton] Diff (NoScaling) = - 2623.

W=0. K=-16.1 (-9.2%)

Krakow

[Ton/cell] [Ton/cell] [% CAMS] W

NewInv - CAMS

NOx & GNFR3 (Region) Scaling) NOx & GNFR3 (Country Scaling)

W=+9.36 (+2.4%) K=-11.31 (-6.4%) W=+11.94 (+3.0%) K=-16.1 (-9.2%)

Krakow

[Ton/cell] [Ton/cell] W W

Example: Poland, Małopolska, CAMS, PM10, S7 (GNFR6), [Ton/cell]

max=295. Krakow=24.45 Warsaw=32.13

Add EI inv EMEP-CAMS: Europe Poland Małopolska CEMAP Małopolska data PM10 SNAP7

• 1. x 1. km2

235 x 136

W=0. K=60.2 (246%)

PM10 & GNFR6 (No Scaling) NewInv - CAMS

W

Krakow

[Ton/cell] [Ton/cell] [% CAMS]

Poland Total = 11665. [Ton] Diff (NoScaling) = + 4364.

W=-8.75 (-27.2%) K=37.17 (152%) W=-14.1 (-44.0%) K=60.2 (246%)

New Inv - CAMS PM10 & GNFR6 (Country Scaling)

[Ton/cell] [Ton/cell] W

Krakow PM10 – GNFR6 (Region) Scaling

W

Preliminarissimi results

The following CEMAP inventories have been implemented into EMEP-CAMS:

• Italy: 2010, All pollutants, All SNAP sectors

Domain: 261 x 291, ~ 4.x4. km2, EPSG 32632 AMS-MINNI_ENEA

• Małopolska-Poland: 2016, All Pollutants, All SNAP sectors

Domain: 235 x 136, ~ 1.x1. km2, EPSG 4326 UM_Malopolska,GEM-AQ

• Sofia – Bulgaria: 2014, {PM10, PM2.5, NOx}, {S1,S2,S4,S7}

Domain: 103 x 107, ~ .5x.5 km2, EPSG 32634 EducationEnvironmentConsulting

• Slovenia: 2013, All Pollutants, All SNAP sectors

Domain: 2759 x 1253, ~ .1x.1 km2, EPSG 4326 SlovenianEnvironmentAgency-ARSO

• Stockholm – Sweden: 2015, PM10, S2

Domain: 143 x 192, ~1.x1. km2, EPSG 3006 EHAC- AIRVIRO

EMEP-CAMS PM10 & GNFR6 (SNAP7) PL & Małop: [11.7 + 4.2] IT & Italy: [21.6 – 1.65] SVN & Slovenia: [1.4 + 1.2] BGR & Sofia: [2.7 + .44] [kTon + kΔ]

[Ton/cell] Max = 295.

Max=28.3 Min=-2.69

NOx [ug/m3] BC - Cscaling

Krakow Krakow

Max=13.6 Min=-32.8

PM10 [ug/m3] BC - Cscaling

EMEP model run - by Alexander de Meij (JRC-Ispra)

Technical details

• Δ CEMAP inventory
• Δ EMEP-CAMS inventory (for country totals)
• Calculation of country totals
• Country shape files
• Correspondance SNAP vs GNFR
• Priority order of CEMAP data
• Speed up of calculations
• etc

Thank you

Following slides not used

Questions regarding the EMEP_CAMS emission inventory used in the EMEP model

Inventory: EMEP-CAMS_v2_1_1_01005deg_2015.nc Σ All sectors

PM10 PM2.5 PMco NOx NMVOC NH3 SO2

PM10 PM2.5 PMco

Cell Krakow = 45.4483 Cell Madrid = 35.3529 Krakow = 27.4092 Madrid = 35.3529 Krakow = 18.0391 Madrid = 0.9769 Krakow = 35.21892 Madrid = 30.8381 Krakow = 38.5137 Madrid = 28.8228 NL=0, FR=0, ES=0, PT=0

NOx NMVOC NH3

Inventory: EMEP-CAMS_v2_1_1_01005deg_2015.nc

Sector GNFR3 (SNAP2)

Inventory: EMEP-CAMS_v2_1_1_01005deg_2015.nc

Sector GNFR5 (SNAP6) PM10 NOx NMVOC

ES=0, IT=0, PT=0,CZ=0, SVK=0 Only S, NL, B, DE, FR, Rest=0 Ok

NH3 SO2

Only NL, UK, DE, CH, Rest=0 Only S, Rest=0

GNFR versus SNAP

• There is no 1-1 correspondance !

GNFR A 1 – PublicPower (S1) B 2 – Industry (S3) C 3 – ‘OtherStationaryComb (S2) D 4 – Fugitive (S4) E 5 – Solvents (S6) F 6 – RoadTransport (S7) G 7 – Shipping (S8) H 8 – Aviation (S8) I 9 – OffRoad (S8) J 10 – Waste (S9) K 11 – AgriLiveStock (S10) L 12 – AgriOther (S10) M 13 – Other (S5) SNAP 1 – Combustion in energy and transformation industries 2 – Non-industrial combustion plants 3 – Combustion in manufacturing industry 4 – Production processes 5 – Extraction & distribution of fossil fuels and geothermal energy 6 – Solvents and other product use 7 – Road transport 8 – Other mobile sources and machinery 9 – Waste treatment and disposal 10 – Agriculture 11 – Other sources and sinks

EMEP-CAMS inventory

• Subdivision of CEMAP into small cells
• Transformation of local CS to WGS84
• Put each green small cell into EMEP-CAMS

POLAND, Małopolska, CEMAP inventories for all SNAP sectors and all pollutants

X Y

CEMAP inventory Local CS – EPSG code

Lon Lat

Subdivision Δ <= 1 km CS transformation based on EPSG to WGS84 (EPSG 4326) Subdivision Δ (~3 km) Aggregation to EMEP-CAMS Δ cells

X Y

CEMAP inventory Local CS – EPSG code

Lon Lat

Subdivision Δ <= 1 km CS transformation based on EPSG to WGS84 (EPSG 4326) Subdivision Δ (~3 km) Aggregation to EMEP-CAMS Δ cells