1. Chemical speciation of PM and mass closure David Green, Gary Fuller & Anja Tremper King’s College London

2. Contents London sampling campaigns Methodology Use of uncertainty Results Source apportionment – London and Paris 2

3. Sampling campaigns Summer campaign Aug-Oct 2008 Brent & Tower Hamlets Winter 2008 campaign Nov-Dec 2008 Camden, Brent & Tower Hamlets Further Camden campaigns May - June 2010 PM 10 and PM 2.5 Summer 2010 Further PM10 Construction and another roadside 3 Brent - Ikea Tower Hamlets – Blackwall Tunnel Camden – Swiss Cottage

4. Methodology Pragmatic mass closure 2 Partisols 1 Teflon – Mass, IC, ICP-MS 1 Quartz – EC/OC ERG mass closure Existing TfL monitoring sites TEOM / FDMS Aethalometer (EC) Sampled onto alternate filters on different days Mixed cellulose esters – ICP-MS Quartz – EC/OC Longer time period Used one sampler Existing Defra monitoring at North Ken and Marylebone Road for concentrations of regional pollutants when not measured directly IC and EC/OC Nitrates, Sulphates, Chlorides, SOA Aethalometer measurements for EC and POA using site specific empirical relationships Results in time series composed of two datasets 4

5. Methodology Mass FDMS – direct mass TEOM – used Volatile Correction Model (VCM) 5

6. Methodology Elemental Carbon Dataset A Aethalometer using Xgenline empirical relationship Uncertainty included Dataset B Sunset 6

7. Methodology Primary Organic Carbon EC tracer measurement used to split SOA and POA Evidence of organic gas adsorption onto filters Intercept and slope derived using min 5% of EC/OC ratios Factor for organic mass of 1.4 used (Japar, 1984) from direct measurements of diesel emissions 7

8. Methodology Secondary Organic Carbon EC tracer measurement used to split SOA and POA SOA = OC - (EC/OC)prim x EC Evidence of organic gas adsorption onto filters Intercept and slope derived using min 5% of EC/OC ratios Factor for organic mass of 2.1 used (Turpin and Lim, 2001), recommended for non-urban aerosol Good agreement between sites Dataset A mean of available measurements in London direct Dataset B Sunset analysis Variation included in uncertainty calculation 8

9. Methodology Nitrates, sulphates & chlorides Measurements from mean of Marylebone and North Kensington used Factors applied to account for cations Nitrate can be ammonium or sodium Masses similar (18 or 23) Harrison (2003) found 60% NH 4 NO 3 Applied a factor of 1.32 (60% NH 4 NO 3 and 40% NaNO3) Sulphate Applied factor of 1.19 Chloride Applied factor of 1.65 9

10. Methodology Water Used Aerosol Inorganic Model (AIM) Used nitrate and sulphate measurements as inputs Used FDMS sampling conditions of 30% RH and 30 ºC 10

11. Methodology Iron Rich Dust Split into Minerals, Iron Oxide and Metals Measured wide range of metals (Fe, Ca, Al, Ba, Cu, Mo, Mn, Ni, Pb, Sb, Sr, V and Zn) Used Al as a tracer for feldspars (e.g. KAlSi 3 O 8 ) Applied factor of 8.4 Included uncertainty in this factor Ca used as a tracer for calcite and gypsum Applied factor of 3.8 Included uncertainty in this factor These grouped together as minerals Fe used as a tracer for an iron oxide (FeO, Fe 2 O 3 or Fe 3 O 4 ) Applied factor of 1.37 Included uncertainty in this factor Other metals included as ‘raw’ mass On days when ICP-MS not undertaken (dataset B) difference between PM 10 mass and available components used to assess this 11

12. Alternate filters ComponentDataset ADataset B ECAethalometerSunset POAAethalometerSunset SOARegionalSunset NitratesRegionalIC SulphatesRegionalIC ChloridesRegionalIC WaterAIM Minerals / unidentified ICP-MSDifference 12 A B

13. Site Variability 13

14. Daily Variability 14

15. Uncertainty analysis Guide to uncertainty in measurement methodology (GUM) Simple… Measurement equation TEOM VCM = TEOM – (ƒVCM x FDMS purge) – FDMS purge Uncertainty equation UVCM = 2 x √(uTEOM) 2 + (uƒVCM x FDMS purge) 2 + (ƒVCM x uFDMS purge) 2 Complex… Total Mass uTotalMassA = 2x √(uEC a 2 + uPOAM a 2 + uSOAM regional 2 + uNO 3total 2 + uSO 4tota l 2 + uCl total 2 + uWater 2 + uMinerals 2 + uIronOxide 2 + uMetals 2 ) 15

16. Validation against PM 10 Tower Hamlets 4 16 Brent 4Camden 1 y = 0.91 (±0.05) x + 2.19 (±1.91) r 2 =0.84 y = 1.11 (±0.07) x + -3.88 (±2.26) r 2 =0.82 y = 0.87 (±0.11) x + 6.9 (±3.22) r 2 =0.58

17. Analysis outputs - Comparison to source apportionment 17

18. 18

19. Next steps and improvements… Organic absorption onto quartz filters Quartz back quartz study to assess adsorption in next 2 months Efficiency of aqua regia digest for extracting Al HF digest ICP-MS for Ca and Al Comparisons with ICP-AES Al as a tracer for Si XRF analysis How representative is one location to another More direct measurements 19

20. Acknowledgements London Borough of Camden Transport for London 20

21. Source apportionment of PM10 in London and Paris -intial results Gary Fuller and Anna Font Font King’s College London March 2010 Centre for Environment and Health

22. 22 Relationship between annual mean PM10 and NOX in London Fuller et al., (2002), Fuller and Green (2006)

23. 23 Relationship between annual mean PM10 and NOX in Paris

24. 24 Primary PM10 : NOX ratio London and Paris Progressive Euro classes preferentially abate PM10 over NOX then grad should be decreasing! Effects of London specific PM measures?

25. 25 Non-primary PM10 London and Paris Non primary PM10 converging Paris did not experience 2006 elevation seen in London