1. Simulation of European emissions impacts on particulate matter concentrations in 2010 using CMAQ
Steve Griffiths, Rob Lennard and Paul Sutton* (*RWE npower)
Power Technology, Environmental Compliance Group

2. Overview of presentation
Developments in PM regulation
Relevance to the power generation sector
CMAQ set-up and treatment of PM
Overview of modelled scenario
Results Compliance with guidelines
Sector by sector impacts
Primary versus secondary particulate impacts
Implications of a population exposure approach

3. Background to study
Power Technology work on behalf of UK power generator’s Joint Environmental Programme (the JEP)
Eight companies – cover majority of the UK coal and oil-fired generation
Investigate environmental issues of relevance to the power industry
Selected CMAQ in 1999 to address regional scale issues
Air quality, acid deposition, particulate matter formation

4. Updates to PM guidelines
Mounting evidence of link between PM exposure and health effect
Fine particles primarily responsible
No threshold
WHO Air Quality Guidelines global update
PM µgm-3 annual mean and 25 µgm-3 24-hour mean
New EU Air Quality Directive (currently under discussion)
PM µgm-3 annual mean, 50µgm-3 24-hour mean
PM µgm-3 annual mean (binding from 2015)
PM % reduction in urban background annual mean (2020)
Number of allowable exceedances of pm10 annual mean is currently being debated. MEPs suggested 55 instead of 35

5. Important issues for the JEP/ESI
Power stations contribute to PM concentrations:
5.5% of primary UK PM10 emissions (NAEI., 2004)
Secondary – 60% of SO2 and 22% of NOx emissions
Mass based metric
Uncertainty regarding fraction responsible for adverse health effects
Toxicology studies suggest primary combustion particles have
high toxic potency
Other components are thought to have a lower toxic potency
e.g. ammonium salts, chlorides, sulphates, nitrates
Need to understand the effect of our emissions on primary and secondary PM2.5 concentrations

6. Models-3/CMAQ 54km European domain 3-D gridded Eulerian model
Set up to run on three nested grids
(54/18/6km and 108/36/12 km)
21 vertical layers (vertically 15km)
Requires hourly gridded emissions and meteorology (UK Met Office)
Initial conditions & boundary conditions from interpolated measurements
Chemical Scheme: RADM2+aerosols+aqueous chemistry
54km European domain

7. Modelling Particulate in CMAQ
Based on USEPA particulate model / Regional Acid Deposition Model
Time-dependent size distribution & size specific chemical composition
Modal approach – Coarse, accumulation & nucleation
Described by particle number concentration, total surface area & total mass
Species
Sulphate, Nitrate, Ammonium
Elemental Carbon
Primary anthropogenic organic species
Anthropogenic secondary organic species
Biogenic secondary species
Unspecified anthropogenic species
Can also include aerosol water

8. Models-3 PM simulation validation – UK sites (12km) Comparison with measured data – 24 hour averages
January July 1999

9. European Modelling study – 54 km resolution
Compared contributions of 7 sectors to ground-level PM concentrations
Model run for an entire year, month-by-month basis, 1999 met data
Anthropogenic emissions scenario for the year 2010
– data from EMEP WebDab Expert Emissions Database (emep.webdab.int)
SO2, NOx, PM10, PM2.5, NH3, CO and NMVOC
Natural VOC emissions from GEIA (Global Emissions Inventory Activity)
Temporal profiles applied using SMOKE
- energy sector data provided by JEP companies
VOC speciation profiles from NAEI (
Emissions from SNAP categories 1, 3 and 4 assigned to point sources
(based on assumptions from National Atmospheric Emissions Inventory)

10. Sectors for which impacts have been assessed
Ground-level PM concentrations due to 7 different sectors compared
Eight model runs performed in total
Sectors:
Energy SNAP 1
Residential SNAP 2
Industry SNAP 3,4,5,6,9
Shipping SNAP 8
Transport SNAP 7,8
Agriculture SNAP 10
Natural* SNAP 11
(*volcanoes, marine, forests)
Ground-level concentration output:
Total PM10
Primary PM10
Secondary
Total PM2.5
Primary PM2.5

11. Results – comparison with standards

12. Exceedances of 25μgm-3 annual mean for PM2.5
Area
Grid square
Eastern Sicily
(44,11)
Northern Italy
(34,25)
Agriculture
2.3
10.9
Energy
0.7
1.9
Industry
1.2
5.0
Natural
19.4?
1.5
Residential
0.6
5.2
Transport
7.1
14.5
Shipping
1.3
1.0
All Sources
27.7
30.2

13. Exeedances of 12 μgm-3 annual mean for PM2.5

14. All source primary and secondary PM2.5 concentrations

15. Sector contributions to grid averages and maxima (µgm-3)
Total PM2.5
Secondary PM2.5
Primary PM2.5
Average
Max
Agriculture
2.33
11.53
2.31
11.49
0.03
0.47
Energy
0.78
4.33
0.74
3.93
0.05
0.57
Industry
0.84
5.49
0.66
3.37
0.18
4.32
Natural
0.61
19.43
0.60
0.01
Residential
0.63
6.26
0.34
1.76
0.30
5.37
Transport
1.16
14.50
0.98
10.93
3.57
Shipping
4.64
0.59
1.54
All sources
7.19
30.17
6.40
26.71
0.79
8.88

16. Sector contributions to grid averages and maxima (µgm-3)
Total PM2.5
Secondary PM2.5
Primary PM2.5
Average
Max
Agriculture
2.33
11.53
2.31
11.49
0.03
0.47
Energy
0.78
4.33
0.74
3.93
0.05
0.57
Industry
0.84
5.49
0.66
3.37
0.18
4.32
Natural
0.61
19.43
0.60
0.01
Residential
0.63
6.26
0.34
1.76
0.30
5.37
Transport
1.16
14.50
0.98
10.93
3.57
Shipping
4.64
0.59
1.54
All sources
7.19
30.17
6.40
26.71
0.79
8.88

17. Exposure approach – population data
Based on Gridded Population of the World (GPW) dataset, available from Centre for International Earth Science Information Network (CIESIN) website
Projected to Lambert Conformal Projection appropriate for CMAQ
Population density in persons per km2 ■
0 - 50
> 1000

18. Population exposure – Secondary PM2.5
Exposure = Population x concentration
(person.μgm-3km-2)
Agriculture
Residential
Energy

19. Population exposure – Primary PM2.5
Exposure = Population x concentration
(person.μgm-3km-2)
Agriculture
Residential
Energy

20. Impact of considering population exposure – Secondary PM2.5

21. Impact of considering population exposure* – Primary PM2.5

22. Conclusions (1)
No regional exceedances of 40 μgm-3 PM10 predicted in 2010
Few regional exceedances of 25 μgm-3 PM2.5 predicted in 2010
Secondary particulates dominate all source PM concentrations
Emissions from agriculture dominate secondary concentrations
Primary concentrations dominated by emissions from transport, residential and industrial sectors
Average Energy sector contributions to concentrations are relatively low (11.2% to total PM2.5, 11.9% to secondary and 6.4% to primary)

23. Conclusions (2) Toxic fraction is critical to abatement strategy
Current toxicological evidence strongest for primary components
Greatest health benefits from tackling residential, transport & industrial sectors?
Exposure approach places even greater emphasis on residential and transport sectors where exposure/tonne emitted values are highest
Delivering health benefits is the key reason for understanding PM behaviour – Focus should be on delivering monitoring/modelling which can improve epidemiological and toxicological understanding

24. Any questions?
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