SHERPA A. Clappier 1 SHERPA SHERPA means, S creening for H igh E - PowerPoint PPT Presentation

Introduction to SHERPA A. Clappier 1

SHERPA SHERPA means, S creening for H igh E mission R eduction P otentials on A ir quality. SHERPA aims to screen the space of all possible emission abatement scenarios. 2

Air Quality Model Air Quality Models can screen all possible abatement scenarios, Meteorological conditions: Wind, Temperature, Solar radiation Boundary conditions Concentrations BUT: Emissions CPU time: days to simulate 1 year 3

SHERPA Features Full Air Quality simulations Source/Receptor relationship Concentrations Algebraic relation between the emission changes of every cell and the concentration changes of every cell        C f E , E , E i i 1 2 n SPEED: Emissions CPU time: minutes to simulate 1 year 4

SHERPA Features Training simulations (10) EASY SET UP  E   Europe wide C Source/Receptor relationship        Application C f E , E , E i i 1 2 n  E   SPATIAL Country / region C FLEXIBILITY 5

SHERPA Features Input SHERPA Shapes AQ Modelling S/R Relationships 10-15 ADAPTABILITY Gridded emissions Sectors Precursors Emission Inventory 6

SHERPA Options Scenario Assessment Concentration changes (i. e. Delta values) Selection of: - a region - an Air Quality Index - activity sectors or precursors HOW MUCH impacts? 7

SHERPA Options Average source apportionment for the selected region Source Apportionment Selection of: - a region - an Air Quality Index - activity sectors or precursors Average source apportionment for a selected point WHAT can I influence? WHICH sectors/pollutants? 8

SHERPA Options Governance control area Selection of: - a NUTS level Contribution per regions (the selected NUTS level) - a point - an Air Quality Index - activity sectors or precursors WITH WHOM should I coordinate actions? 9

Example: London Source Apportionment 7x7 km 2 cell over London (51.53° ; -0.073°), concentration: 18 m g.m -3 . Reduction of: 2. London region 1. all European countries 0.25% 3.27% 1.29% 25.8% 18.5% London region: 35.6% 35.6% 1.21% 1.84% 2.53% 6.59% 6.68% 2.34% 83.8% 25.3% Europe outside London 2.59% region: 48.2% 3.98% 64.4% 4.22% 12.9% Outside Europe + natural 16.2% + shipping: 16.2% MS1: Energy production MS7: Road transport MS2: Residential MS8: Other mobile sources MS3 and 4: Industrial production MS9: Waste MS5: Energy extraction and transport MS10: Agriculture 10 MS6: Solvent

Example: London Governance control area MS 7: Road transport all Europe 25.3% 2.4% 18.5% 2.9% MS 10: Agriculture all Europe 25.8% 1% 1% 3.2% 0.25% 1% 3.1% 1.6% 11

Example: Bruxelles Source Apportionment Governance control area MS 7: Road transport MS 10: Agriculture 2.3% 4% 1.2% 12.8% 20.7% 3.8% 12

SHERPA’s Assumptions - Annual or seasonal average concentration - Linear relationship between emissions and concentrations - Isotropic relationship between emissions and concentrations n    n p           C 1 d i , p E i i i , p ij j , p i   p 1 j 1 13

SHERPA’s Assumptions Reduction over countries Percentage bias France Percentage bias Poland 14

SHERPA’s Assumptions Reduction over small regions Percentage bias ACCURACY: 90% Percentage bias i.e. 10% bias 15

Overview Shapes SHERPA Emission Inventory AQ Modelling S/R Relationships 10-15 scenarios 16

Adaptability Other Shapes domain SHERPA Emission Inventory emissions AQ Modelling S/R Relationships AQ model 10-15 scenarios 17

Quality Assessment Shapes SHERPA Emission Inventory AQ Modelling S/R Relationships 10-15 scenarios 18

Quality Assessment Shapes SHERPA Emission Inventory AQ Modelling S/R Relationships 10-15 scenarios 19

Quality Assessment Shapes SHERPA Emission Inventory Measurements AQ Modelling S/R Relationships 20

Quality Assessment Shapes SHERPA Emission Inventory Measurements AQ Modelling S/R Relationships 21

Next 14:00-14:30 Discussion (questions, remarks, comments) SHERPA, a useful tool for AQ planning in European regions? SHERPA, a useful tool for FAIRMODE WG? 14:30-16:00 Exercise (Example SHERPA Practice) 22

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