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Air quality expert group - Fine particulate matter (PM2.5) in ... - Defra

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57. The map of the annual mean <strong>PM2.5</strong> <strong>in</strong> 2009 at background locations is shown <strong>in</strong><br />

Figure 5.1 (Chapter 5). This map has been calibrated us<strong>in</strong>g measurements from<br />

TEOM FDMS <strong>in</strong>struments (see Chapter 2) with<strong>in</strong> the national network for which<br />

co-located <strong>PM2.5</strong> and PM10 measurements are available for 2009, the first year<br />

for which <strong>PM2.5</strong> measurements from an extensive network of sites <strong>in</strong> the UK are<br />

available. The models for PM10 and <strong>PM2.5</strong> are designed to be fully consistent.<br />

Each component is either derived from emission estimates for PM10 or <strong>PM2.5</strong><br />

or the contributions to the f<strong>in</strong>e and coarse particle size fractions are estimated<br />

separately. This enabled an additional check that the calibration parameters<br />

for the two pollutants are reasonably consistent. Measurements from national<br />

network sites without co-located PM10 <strong>in</strong>struments have been used as an<br />

additional verification dataset. The results from the annual mean model could<br />

then be directly compared with the annual mean limit value <strong>in</strong> order to carry out<br />

air <strong>quality</strong> assessments and policy analyses.<br />

58. An important application of the PCM model is its ability to provide a source<br />

apportionment of the observed <strong>PM2.5</strong>. Figure 5.10 (Chapter 5) illustrates this<br />

ability for a number of background locations <strong>in</strong> 2009. The importance of<br />

secondary PM is clearly illustrated and dom<strong>in</strong>ates all other PM components,<br />

particularly traffic exhaust emissions.<br />

59. Figure A2.8.1 presents a verification plot for the PCM model estimates of the<br />

annual mean <strong>PM2.5</strong> concentrations. The model performance <strong>in</strong>dicated is entirely<br />

satisfactory, with the vast majority of the po<strong>in</strong>ts <strong>in</strong> the scatter plot fall<strong>in</strong>g with<strong>in</strong><br />

±50% of the observations.<br />

Modelled (µg m -3)<br />

25<br />

20<br />

15<br />

10<br />

5<br />

0<br />

0 5 10 15 20 25<br />

Measured (µg m-3) Annex 2: PM modell<strong>in</strong>g <strong>in</strong> the UK<br />

FDMS calibration sites<br />

Paroistol common sites<br />

FDMS <strong>PM2.5</strong> only sites<br />

Partisol <strong>PM2.5</strong> only sites<br />

Verification sites FDMS<br />

Verification sited TEOM x 10<br />

x=y<br />

x=y + 50%<br />

x=y - 50%<br />

Figure A2.8.1: Verification plot for the PCM model estimates of <strong>PM2.5</strong> for<br />

background sites <strong>in</strong> 2009.<br />

60. An <strong>in</strong>terest<strong>in</strong>g feature of the PM observations over the years has been the<br />

magnitude of the traffic and London <strong>in</strong>crements, as for example shown by the<br />

differences between London Marylebone Road and London North Kens<strong>in</strong>gton,<br />

and between London North Kens<strong>in</strong>gton and Harwell, Oxfordshire. These have<br />

po<strong>in</strong>ted to the large <strong>in</strong>fluence that long-range transport has on observed PM<br />

levels <strong>in</strong> London. The PCM model has provided a view on the contributions<br />

played by a number of PM components to the traffic and London <strong>in</strong>crements, as<br />

169

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