1. Modeling trans-boundary transport of benzo(a)pyrene over Europe with CMAQ
A. Aulinger, V. Matthias, M. Quante,
Institute for Coastal Research
GKSS Research Center
Geesthacht, Germany

2. Outline Introduction: Why PAHs ? Model modification and set up
Emissions
Model results
Comparison with measurements
Conclusions and outlook

3. Why 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
B(a)P
Object of international reduction conventions
(Target values for air concentrations -
EU: 1 ng/m3 (annual average), UK: 0.25 ng/m3)
Emissions are likely to increase wood burning, ship traffic

4. MM5 and CMAQ for annual simulations
model domain
30 vertical layers up to 100 hPa
54x54 km2 grid
18x18 km2 grid

5. Model set up for annual simulations
CMAQ:
Version 4.5
CB IV chemistry scheme
Aero 4 module incl. SOA formation
Anthrop. emissions from IER Stuttgart based on EMEP and EPER data base
Natural emissions from GEIA and RETRO database
B(a)P emissions from Denier van der Gon et al. (TNO report, 2005)

6. Some chemical species in CMAQ (CB-IV mechanism):
Aerosols in three size classes (visibility also calculated)
7 inorganic, 2 organic nitrogen species
SO2, sulfate (sulfuric acid)
Seasalt
Anthropogenic and biogenic volatile organics
O3, H2O2, OH
Benzo(a)pyrene

7. Partitioning

8. Electricity generation Iron and steel production
Emissions
major sources
Residential heating
Road transport
Electricity generation
Iron and steel production
Incineration of household waste
Ship engines
Oil platforms
Wildfires
B(a)P emissions in 2000
PAHs are formed by any incomplete combustion of organic matter

9. Emissions
Time scheme
Constant (case a)
Seasonality after TNO
(case b)

10. Emissions
Temperature dependence

11. Emissions

12. Emissions

13. Time variant emissions (expl. Berlin 2000)
case c

14. Simulations vs. measurements

15. Simulations vs. measurements

16. Correlations Station Roervik, SE, rural, monthly means 0.479 0.636
Case A
Case B
Case C
Roervik, SE, rural, monthly means
0.479
0.636
0.689
Aspvreten, SE, rural, monthly means
-0.105
0.239
0.183
Pallas, FI, remote, monthly means
0.746
0.763
0.595
Preila, LT, urban, monthly means
0.639
0.653
0.798
Kosetice, CZ rural, monthly means
0.845
0.829
0.971
Lista, NO, remote monthly means
-0.058
-0.052
-0.09
Bornhoeved, DE, rural, weekly means
0.684
0.724
0.718
Radebeul, DE, suburban 2-day means
0.581
0.646
0.727

17. Depositions into the Baltic Sea
Total depositions in 2000 in t
Depositions in t
Case A
12.05
Case B
12.82
Case C
13.43

18. CMAQ with 12 vertical layers  10-15% lower concentrations
CMAQ results: B(a)P concentrations in Europe
for lowest layer
total annual amount of emitted B(a)P was the same for both model runs (based on 2000 data)
CMAQ with 12 vertical layers  10-15% lower concentrations

19. CMAQ results: B(a)P concentrations over the North Sea
for lowest layer

20. CMAQ results: B(a)P wet deposition over the North Sea

21. Precipitation

22. CMAQ results vs. EMEP measurements: B(a)P concentrations
statistics
CMAQ model results vs. EMEP measurements, statistical quality indicators, times series year 2000 and 2001

23. Emission data

24. CMAQ results vs. EMEP measurements: PM10 concentrations
stations, daily means 2000
PM10 [gm-3]
Deuselbach, Germany, 480 m asl
Mean (meas) mg/m3
bias mg/m3
rms error mg/m3
Correlation 0.47
IOA 0.64
measurements
model
PM10, IOA, total year

25. Conclusions and outlook
Correlations simulations vs. measurements already acceptable with constant emissions but notably better with time-variant emissions
Simulations tend to overestimate observations
Differences between different simulation periods more prominent concerning deposition than concentrations
Best agreement with measurement stations in the vicinity of sources
Higher resolved model domain and emissions required, for investigation on small regional scales
Long-term studies over several years planned
Degradation of pollutants should be considered
Ship emissions will be considered
We recommend the revision of emission data

26. Outlook - ship emissions

27. Thank you for your attention
THE END