CMAS Conference 2009 Johannes Bieser, Institute for Coastal Research – GKSS Science Center CMAS...

CMAS Conference 2009 Johannes Bieser, Institute for Coastal Research – GKSS Science Center

CMAS Conference 2009

Enhancing SMOKE to create European emissions with focus on Benzo[a]Pyrene

Team: Johannes Bieser, Armin Aulinger,

Volker Matthias, Markus Quante

GKSS Environmental Chemistry Department


Outline

1. Introduction

2.Data Sources

3.Changes to the SMOKE model

4.Comparison with measurements


Benzo(a)Pyrene chosen as a lead substance for PAHs

PAHs imperil humans and ecosystems

– highly bioaccumulative (food chain)

– persistent in various environmental compartments

– significant adverse effects already at low doses

• carcinogenic

• impair immune system

• impair reproduction

Why PAHs ?

B(a)P

Object of international reduction conventions and national legislationEU: 1 ng/m³ average value in ambient airGB: 0.25 ng/m³ average value in ambient air in 2010


Main BaP Sources today

BaP results from incomplete combustion

Domestic Combustion

Wood

Industrial productionIndustrial combustion

~ 50%

Coal

Coke Ovens

Vehicle exhausts

Wild fires

Diesel

Aluminium Production

Waste Incinerators


BaP Sources over time

140 40 40 40 30 25 47 40 30 25 16.3440 50 55 50 70 50 55 50 45 30 24.51

410 480 490 430 420 220 300 270 250 180 122.55710 630 650 670 480 330 505 540 570 610 653.6

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%BaP Source sectors

1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 20201970 1975 1980 1985 1990 1995 2000 2005 2010 2015 20201970 1975 1980 1985 1990 1995 2000 2005 2010 2015 20201970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020

907 839.5 794.5 727 682 664.5 647 622 597907 895.6 888 876.6 869 860 851 834 817

1300 1240 1200 1200 1200 1140 1100 1040 1000 590 590

0

200

400

600

800

1000

1200

1400 BaP total emission estimates

1970 1973 1975 1978 1980 1983 1985 1988 1990 1993 1995 2000 2003 2005 2008 2010 2013 2015 2018 20201970 1973 1975 1978 1980 1983 1985 1988 1990 1993 1995 2000 2003 2005 2008 2010 2013 2015 2018 20201970 1973 1975 1978 1980 1983 1985 1988 1990 1993 1995 2000 2003 2005 2008 2010 2013 2015 2018 2020

[t/y]


2. Data Sources


SMOKE - emissions model

Biogenic emissions model

Mobile emissions model

2D-emissions processor

Plume in GridPoint source model

Top-Down

Bottom-Up


Area Sources

Area Sources


European Monitoring and Evaluation Program (EMEP)

- Annual emission totals for Europe and surrounding countries

- Species: CO, NOx, SOx, NMVOC, NH3, PM, (POPs, HMs)

- Official national reports as well as expert estimates

- 11 different Source Sectors (SNAP Sectors)

Official Inventories


Global Population of the World

• Resolution: 1 x 1 km

• Data available for:199019952000200520102015


CORINE Land Cover database

100 x 100 m1990 & 2000


USGS Global Land cover


NUTS regions

• NUTS 0 Country

• NUTS 1 3 million to 7 million pers.

• NUTS 2 800000 to 3 million pers.

• NUTS 3 150000 to 800000 pers.


EUROSTAT

Official European statistics:

Publishes economic, business, social, energy, monetary, trade, agricultural, environmental statistics

- Temporal resolution: monthly

- Spatial resolution: county level (NUTS3)

- Employment rates for different industrial sectors

- Net working times

- Animal stocks

- Air traffic

- Fuel and Energy consumption

- …


Point Sources

Point Sources


European Point Source Emission Register

Includes:

• 12000 point sources

• plant type

• location

• activity

• pollutants

• inventory years:

2001 & 2004


Mobile Sources

Mobile Sources


openstreetmaps


TREMOVE database

Annual per country data:

- 20 European countries

- 6 different transport networks• motorway• non-urban road• urban road• rail• water• air

- Vehicle fleet size- Fleet composition- Fuel consumption- Total km driven- Annual total emissions

- 10 different on-road vehicle categories

• moped• motorcycle• car• van• bus• light duty truck• heavy duty 3.5 – 7.5t• heavy duty 7.5 – 16t• heavy duty 16 – 32t• heavy duty > 32t


Biogenic Emissions

Biogenic Sources


Biogenic Emissions

Forest cover database

• 120 different tree types

Land use data

• argicultural usage paterns • land type

Different LAI for winter and summer

Wild fires (not included)

Mineral Dust (not included) Resolution: 1 x 1 km

Inventory year: 2000


2. Changes to SMOKE


Changes to the SMOKE model

Problems:

- Very large regions (up to 675000 m² and 80mio. inhabitants)

- Temperature dependend emissions (Residential Heating)

- Much pre-processing of spatial surrogates



SMKINVEN SPCMAT GRDMAT

SMKMERGE TEMPORAL

Calculated for each day

Calculated once for each scenario



SMKINVEN SPCMAT GRDMAT

SMKMERGE TEMPORAL

Calculated for each day

Calculated once for each scenario

MODMAT

NORMAT

MCIPmeteorologic

fields



Advantages

- The additional routines can be turned on/off independent from the standard SMOKE modules

- Gives better spatial resolution for big regions

- Gives better temporal resolution

- Daily instead of monthly temporal profile- More realistic annual profile

- Can be used with any netCDF file via reference and profile ASCII files


3. Comparison with measurements


Modelling Domain

- 54x54 km grid over Europe

- 18x18 km nest North and Baltic Sea

- 30 vertical layers up to 100 hPa

- 12 min time steps

- Scenario years: 2000 & 2001

- chemical mechanisms CB IV & CB V

- meteorology MM5 & CLM

- BC from ERA40

- emissions created with SMOKE: CO, NOx, SO

2, NH3, PM, NMVOC

BaP


• 21 Measurement Stations

• Daily average values

• EMEP Measurement Network

Sulfate concentrations

Scenario:

Grid: 54x54 kmMeteorology: MM5Mechanism: CB IVYears: 2000 & 2001





Ammonium concentrations





Nitrate concentrations



• Hourly average values


Ozone & BaP concentrations


Code conc. Sampling depos. sampling Country Station Network

ASP 1 week per month 1 wk./m. bulk Sweden Aspvreten EMEPKOS 1 day per week Czech Rep. Kosetice EMEPPAL 1 week per month Finland Pallas EMEPROE weekly Sweden Rörvik EMEP

BOR 1-2 days per week Germany Bornhöved GFEAZAR 1-2 days per week Germany Zarrentin GFEARAD every second day Germany Radebeul GFEA

WES monthly wet Germany Westerland GFEAZIN monthly wet Germany Zingst GFEA

EMEP: European Monitoring and Evaluation ProgramGFEA: German Federal Environmental Agencies

BaP Measurements

Stations measuring BaP


BaP Measurements


BaP Measurements

Annual average concentrations

Code observation model NMB correlation2000 2001 2000 2001 2000 2001 2000 2001

ASP 0.048 0.037 0.224 0.232 3.70 5.31 0.44 0.65KOS 0.169 0.223 0.156 0.132 -0.08 -0.41 0.64 0.47PAL 0.006 0.031 0.004 0.004 -0.34 -0.87 0.32 0.86ROE 0.078 0.105 0.064 0.064 -0.18 -0.40 0.72 0.66BOR 0.100 0.268 0.213 0.210 1.12 -0.22 0.49 0.45RAD 0.722 0.639 0.234 0.235 -0.68 -0.63 0.70 0.67ZAR 0.347 0.106 -0.70 0.34


Thank you for your attention!

CMAS Conference 2009 Johannes Bieser, Institute for Coastal Research – GKSS Science Center CMAS...

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