Tallinn 26 June 2018 SHERPA in the overall context Visualisation - - PowerPoint PPT Presentation

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SHERPA Tallinn 26 June 2018 SHERPA in the overall context Visualisation & Interpretation Aim : quantify the sectoral and/or spatial origins of pollution NH 4 SHERPA NH 3 Tagging approach CTM Incremental Mass transfer - SA Input (model,

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Tallinn 26 June 2018

SHERPA

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Aim: quantify the sectoral and/or spatial origins of pollution

SHERPA in the overall context

Input (model, emissions, meteorology, city, resolution…)

SHERPA

CTM

Tagging approach Mass transfer - SA NH3 NH4 Incremental

Visualisation & Interpretation

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Segersson et al. 2017: Health Impact of PM10, PM2.5 and Black Carbon Exposure Due to Different Source Sectors in Stockholm, Gothenburg and Umea, Sweden PM2.5 Urban air quality Atlas,

2017. Based on SHERPA

Example: Stockholm

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Atlas location

ne cell south

Example: Stockholm SHERPA spatial variablity in source allocation

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1. Assumption 1: only primary emissions have a local impact
2. Assumption 2: LPS only have impacts
3. Visualization in terms of population exposure

Atlas

Test case: Stockholm

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Industry Residential Transport Local vs. Regional

Test case: Stockholm Visualization: population exposure

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Aim: identify & quantify the sectoral and/or spatial origins of pollution

SHERPA

Segersson et al. approach Gaussian high resolution modelling

Only primary emissions have a local impact
Incremental approach

SHERPA formulation, uncertainties and methodological approach CTM

Input (model resolution, emissions, meteorology, city…) Visualisation (average population exposure vs. local concentration)

Treatment of point sources

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Aim: identify & quantify the sectoral and/or spatial origins of pollution

SHERPA in the overall context

Input (model, emissions, meteorology, city, resolution…)

SHERPA

CTM

Tagging approach Mass transfer - SA NH3 NH4 Incremental

Visualisation & Interpretation

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Sectors

(Transport-Industry-Residential-Agriculture

Uncertainties of the SHERPA input data

CHIMERE EMEP

Emissions Meteorology Base year Resolution

SHERPA SHERPA

Emissions Meteorology Base year Resolution

Areas

(city-FUA-National-International)

Areas

(City-country-EU)

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Aim: identify & quantify the sectoral and/or spatial origins of pollution

SHERPA in the overall context

Input (model, emissions, meteorology, city, resolution…)

SHERPA

CTM

Tagging approach Mass transfer - SA NH3 NH4 Incremental

Visualisation & Interpretation

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CHIMERE SHERPA

SHERPA formulation & evaluation

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Aim: identify & quantify the sectoral and/or spatial origins of pollution

SHERPA

Tagging approach Mass transfer - SA

SHERPA formulation, uncertainties and methodological approach CTM

Bias 5-10 10% Agri << << Fac 2 or 3

NH3 NH4

Urban an << << 30 30-50 50%

Incremental Input (model, emissions, meteorology, city, resolution…) Visualisation & Interpretation

Concent entrat atio ion vs. expos posure: ure: industry stry << fac 2 or 3 Possib sible le change ges in prior

rities

ities

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SHERPA survey

SHERPA SURVEY  Interpretation of results  Better documentation  Speed  Exporting formats  More validation  linearity emissions/concentrations  Mountain areas, background  Treatment of point sources  Limited to screening at country level  Too coarse resolution for urban  More validation (CTM, emissions)  Geographical coverage  Inaccuracy in emission inventory  Choice of CTM model  Use of own emission inventory

Result

SHERPA

CTM Input

Assumptions

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