Rob Lennard, Steve Griffiths and Paul Sutton (RWE npower)

1. Simulation of European emissions impacts on particulate matter concentrations in 2010 using Models-3 Rob Lennard, Steve Griffiths and Paul Sutton (RWE npower) Power Technology, Environmental Compliance Group

2. Overview of presentation • Background to study • Air quality legislation covering particulate matter (PM) and issues for • electricity generation sector • Models-3 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 • Air quality, acid deposition, particulate matter formation • Selected Models-3 in 1999 to address regional scale issues

4. Particulate matter (PM) and human health impacts • Mounting evidence for association between exposure to PM and adverse health impacts • Fine particulates (PM2.5) believed to be primarily responsible • Lack of evidence for a threshold for harmful effects • Based on current understanding, World Health Organisation (WHO) has updated its air quality guidelines (AQG) (October 2006) • For the first time, WHO has recommended guidelines for PM2.5 • Updated guidelines for PM have been proposed for Europe and the UK

5. Updates to PM guidelines • WHO Air Quality Guidelines Global Update • PM2.510 µgm-3 annual mean and 25 µgm-3 24-hour mean • New EU air quality Directive(current understanding - currently being debated) PM1030 µgm-3 annual mean PM2.525 µgm-3 annual mean (binding from 2010) PM2.5Up to 20% reduction in urban background annual mean • UK Air Quality Strategy – updates proposed by Defra: PM10 Retain standards??? PM2.525 µgm-3 annual mean for PM2.5 PM2.5 15% exposure reduction target for annual mean PM2.5

6. Important issues for the JEP • Power stations contribute to PM concentrations: • ~9% of UK primary emissions (EMEP Webdab) • Secondary - emissions of precursor gases SO2 (70%) and NOx (20%) • 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

7. Models-3/CMAQ • 3-D gridded Eulerian model • Set up to run on three nested grids (54, 18, and 6km resolution) • 21 vertical layers (15km) • Requires hourly gridded emissions and meteorology • Plus land-use, initial conditions, boundary conditions • Chemical Scheme: RADM2+aerosols+aqueous chemistry

8. Modelling Particulate in Models-3 • 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 organic species • Anthropogenic secondary organic species • Biogenic secondary species • Unspecified anthropogenic species • Can also include aerosol water

9. Modelling study • 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) • Emissions data were available for all major pollutants (SO2, NOx, PM10, PM2.5, NH3 and NMVOC). • Temporal profiles applied using smoke. - energy sector data provided by JEP companies • 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: • Agriculture • Energy • Industry – SNAP cats 3,4,5,6,9 • Natural • Residential • Shipping • Transport – SNAP cats 7,8 • Ground-level concentration output: • Total PM10 • Primary PM10 • Secondary • Total PM2.5 • Primary PM2.5

11. Emissions data by SNAP category

12. Models-3 PM simulation validationComparison with measured data – 24 hour averages January 1999 July 1999

13. Results – comparison with standards

14. Exceedances of 25μgm-3 annual mean for PM2.5

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

16. All source primary and secondary PM2.5 concentrations

17. Sector contributions to grid averages and maxima(µgm-3)

18. Sector contributions to grid averages and maxima (µgm-3)

19. 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 Models-3 • Population density in persons per km2

20. Population exposure Population exposure to secondary PM2.5 (person.μgm-3km-2) Agriculture Energy Residential

21. Population exposure Population exposure to primary PM2.5 (person.μgm-3km-2) Agriculture Energy Residential

22. Impact of considering population exposure

23. Conclusions • No exceedances of 40 μgm-3 annual mean for PM10 predicted in 2010 • Exceedances of 25 μgm-3 annual mean for PM2.5 in two locations only • Secondary particulates dominate all source PM concentrations • Emissions from agriculture dominate secondary concentrations • Primary concentrations dominated by emissions from transport, • residential and industrial sectors • Given current evidence for adverse health effects, greatest benefits expected for • emissions reductions in these sectors • Energy sector contributions to concentrations due to all anthro sources are • relatively low ( 11.2% to total PM2.5, 11.9% to secondary and 6.4% to primary) • Population exposure approach places even greater emphasis on transport and • residential emissions since air quality impacts high in densely populated areas

24. Any questions?