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

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

© 2005 E.ON 19 April 2023, E.ON UK, Page 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


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


• 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

Particulate matter (PM) and human health impacts


Updates to PM guidelines

• New EU air quality Directive (current understanding - currently being debated)

PM10 30 µgm-3 annual mean

PM2.5 25 µgm-3 annual mean (binding from 2010)

PM2.5 Up to 20% reduction in urban background annual mean

• UK Air Quality Strategy – updates proposed by Defra:

PM10 Retain standards???

PM2.5 25 µgm-3 annual mean for PM2.5

PM2.5 15% exposure reduction target for annual mean PM2.5

• WHO Air Quality Guidelines Global Update

PM2.5 10 µgm-3 annual mean and 25 µgm-3 24-hour mean


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


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


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


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)


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


Emissions data by SNAP category

Sector SNAP Source

Combustion in energy production and transformation 1 EMEP

Non-industrial combustion (residential, commercial & institutional)

2 EMEP

Combustion in industry 3 EMEP

Production Processes 4 EMEP

Extraction & distribution of fossil fuels 5 EMEP

Solvent use 6 EMEP

Road transport 7 EMEP

Other transport and mobile machinery 8 EMEP

Waste treatment & disposal 9 EMEP

Agriculture, forestry and land-use change 10 EMEP

Shipping 8 EMEP

Natural Sources 11 GEIA

Volcanoes 11 EMEP


Models-3 PM simulation validationComparison with measured data – 24 hour averages

0

5

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Modelled concentration [PM2.5] ug/m3

Mea

sure

d c

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[P

M2.

5] u

g/m

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Hodge Hill

Clif fe

Harw ell

London Bloomsbury

Rochester

Wingham

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Modelled concentration [PM2.5] ug/m3

Mea

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d c

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[P

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Hodge Hill

Clif fe

Harw ell

London Bloomsbury

Rochester

Wingham

January 1999 July 1999


Results – comparison with standards


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

AreaGrid 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


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


All source primary and secondary PM2.5 concentrations


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

Sector Total PM2.5 Secondary PM2.5 Primary PM2.5

Average

Max Average

Max 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 19.43 0.01 0.03

Residential 0.63 6.26 0.34 1.76 0.30 5.37

Transport 1.16 14.50 0.98 10.93 0.18 3.57

Shipping 0.61 4.64 0.59 4.64 0.03 1.54

All sources 7.19 30.17 6.40 26.71 0.79 8.88


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

Sector Total PM2.5 Secondary PM2.5 Primary PM2.5

Average

Max Average

Max 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 19.43 0.01 0.03

Residential 0.63 6.26 0.34 1.76 0.30 5.37

Transport 1.16 14.50 0.98 10.93 0.18 3.57

Shipping 0.61 4.64 0.59 4.64 0.03 1.54

All sources 7.19 30.17 6.40 26.71 0.79 8.88


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

■ ■ ■ ■ ■


Population exposure

Agriculture Residential Energy

Population exposure to secondary PM2.5 (person.μgm-3km-2)


Population exposure

Agriculture Residential Energy

Population exposure to primary PM2.5 (person.μgm-3km-2)


Impact of considering population exposure

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45

Agriculture Energy Industry Residential Transport Shipping

Co

ntr

ibu

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o a

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ou

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tota

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) Mass emitted

Grid average concentration

Population exposure


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


Any questions?

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