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

Impact of high-resolution CEMAP emission data on 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” base -case map “Mosaic” inventory AQM SRR “Mosaic” SHERPA “Mosaic” scenarios

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 of the high-resolution CEMAP emission data into the EMEP-CAMS inventory.

CEMAP inventory Local CS – EPSG code CS transformation based on EPSG to WGS84 (EPSG 4326) Y Lat Subdivision Δ <= 1 km X Lon EMEP-CAMS Subdivision Δ (~3 km) Aggregation to EMEP-CAMS Δ cells

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

Example: Poland, Małopolska , CAMS, NOx, S2 (GNFR3), [Ton/cell] EMEP-CAMS: Europe Poland max=4349. Krakow=175.8 Warsaw=397.0 Małopolska CEMAP Małopolska data Add EI inv NOx SNAP2 1. x 1. km 2 235 x 136

NOx & GNFR3 (No Scaling) Krakow NewInv - CAMS [Ton/cell] [Ton/cell] W W=0. K=-16.1 (-9.2%) [% CAMS] Poland Total = 89773. [Ton] Diff (NoScaling) = - 2623.

NOx & GNFR3 (Country Scaling) Krakow [Ton/cell] [Ton/cell] W W=+9.36 (+2.4%) K=-11.31 (-6.4%) NOx & GNFR3 (Region) Scaling) W W=+11.94 (+3.0%) K=-16.1 (-9.2%)

Example: Poland, Małopolska , CAMS, PM10, S7 (GNFR6), [Ton/cell] EMEP-CAMS: Europe Poland max=295. Krakow=24.45 Warsaw=32.13 Małopolska CEMAP Małopolska data Add EI inv PM10 SNAP7 1. x 1. km 2 235 x 136

PM10 & GNFR6 (No Scaling) Krakow [Ton/cell] NewInv - CAMS [Ton/cell] W W=0. K=60.2 (246%) [% CAMS] Poland Total = 11665. [Ton] Diff (NoScaling) = + 4364.

PM10 & GNFR6 (Country Scaling) Krakow [Ton/cell] [Ton/cell] New Inv - CAMS W W=-8.75 (-27.2%) K=37.17 (152%) PM10 – GNFR6 (Region) Scaling W W=-14.1 (-44.0%) K=60.2 (246%)

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. km 2 , EPSG 32632 AMS-MINNI_ENEA • Małopolska -Poland: 2016, All Pollutants, All SNAP sectors Domain: 235 x 136, ~ 1.x1. km 2 , EPSG 4326 UM_Malopolska,GEM-AQ • Sofia – Bulgaria: 2014, {PM10, PM2.5, NOx}, {S1,S2,S4,S7} Domain: 103 x 107, ~ .5x.5 km 2 , EPSG 32634 EducationEnvironmentConsulting • Slovenia: 2013, All Pollutants, All SNAP sectors Domain: 2759 x 1253, ~ .1x.1 km 2 , EPSG 4326 SlovenianEnvironmentAgency-ARSO • Stockholm – Sweden: 2015, PM10, S2 Domain: 143 x 192, ~1.x1. km 2 , EPSG 3006 EHAC- AIRVIRO

EMEP-CAMS PM10 & GNFR6 (SNAP7) [Ton/cell] [kTon + k Δ ] Max = 295. PL & Małop : [11.7 + 4.2] IT & Italy: [21.6 – 1.65] SVN & Slovenia: [1.4 + 1.2] BGR & Sofia: [2.7 + .44]

EMEP model run - by Alexander de Meij (JRC-Ispra) NOx [ug/m3] Krakow BC - Cscaling Max=28.3 Min=-2.69 PM10 [ug/m3] Krakow BC - Cscaling Max=13.6 Min=-32.8

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

Inventory: EMEP-CAMS_v2_1_1_01005deg_2015.nc Sector GNFR3 (SNAP2) PM10 PM2.5 PMco Krakow = 27.4092 Krakow = 18.0391 Cell Krakow = 45.4483 Madrid = 35.3529 Madrid = 0.9769 Cell Madrid = 35.3529 NOx NH3 NMVOC Krakow = 35.21892 Krakow = 38.5137 NL=0, FR=0, ES=0, PT=0 Madrid = 30.8381 Madrid = 28.8228

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

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

CEMAP inventory Local CS – EPSG code CS transformation based on EPSG to WGS84 (EPSG 4326) Y Lat Subdivision Δ <= 1 km X Lon Subdivision Δ (~3 km) Aggregation to EMEP-CAMS Δ cells

CEMAP inventory Local CS – EPSG code CS transformation based on EPSG to WGS84 (EPSG 4326) Y Lat Subdivision Δ <= 1 km X Lon Subdivision Δ (~3 km) Aggregation to EMEP-CAMS Δ cells