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Concentrations of particulate matter in France : results and key findings

Discover the results and key findings of particulate matter concentrations in France from a vast monitoring network including PM measurement stations and detailed analysis of PM composition and distribution.

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Concentrations of particulate matter in France : results and key findings

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  1. Concentrations of particulate matter in France : results and key findings Olivier Le Bihan, François Mathe, Jean-Luc Houdret, Bertrand Bessagnet, Patrice Coddeville, Paolo Laj, Nathalie Poisson, Souad Bouallala, Cécile Honoré, Laure Malherbe, Laurence Rouïl

  2. PM measurement network • - Implemented by 38 local organisations in charge of the AQ monitoring networks • - More than 300 PM10 monitoring stations (85% TEOM, 15% b gauges) • - 65 PM2.5 urban/suburban monitoring stations (TEOM) • - Field campaigns • - Specific sites devoted to scientific research (Puy-de-Dôme)

  3. The puy de Dôme station • Aerosol Parameters • Continuous measurements • Size distribution (3-400 nm) - DMPS • Size distribution (125 nm- 10 µm) - OPC • Cluster ions (0,3 – 40 nm) - AIS • Inorganic and organic composition (OC-EC) • Organic speciation (CARBOSOL) • Scattering coefficient -Nephelometer 3l • Absorption coefficent -Aethalometer • Radionucleides Natural and artificial • Aerosol Mass • Aerosol Optical depth (2007) • Vertical distribution (LIDAR – 2007) • Precipitation and wet chemistry • Continuous measurements • Rainfall rate – Rain jauge • Droplet distribution – Doppler radar • Rain Inorganic and organic chemistry • Cloud physics (radius, LWC) • Cloud chemistry • Radionucleides Natural and artificial

  4. PM10 analysis • - annual average varies from 22 to 25 ug/m3 • - Highest concentrations obtained in Marseilles and Paris areas and at industrial sites Chemical composition dependent from the site typology and the season

  5. Special case of the Puy de Dôme station Winter : 2 ug/m3 Summer : 5 ug/m3 A very large fraction of the organic component originates from biomass burning, especially during winter time. Increase in summer due to VOC oxydation (secondary OA) ( NO3 and NH4 measurements not considered )

  6. Correlation between PM10 concentrations • - Based on daily PM10 averages • - Regressions between pairs of stations • - Slopes of the regression allow to identify linkages on the spatial pattern • - Correlation coefficients relies to the temporal aspect • - Seasonal analysis Correlated geographical areas - summer Correlated geographical areas - winter

  7. PM 2.5 statistics Averages of daily concentrations • Highest urban concentrations in the south-West (15 ug/m3), in the south-East (17 ug/m3), in the Lyon area (15ug/m3): different reasons should be invoked • Lowest concentrations in the Western part of France (10 to 13 ug/m3) • Specific situation of the traffic sites in Paris area

  8. Statistics related to “twins sites” in the North • Moy1 Moy2 Nbias(%) Var ratio Corr • (sub.) (urb.) 2003-2005 Nbias = • 13.1 14.3 12.1 0.76 0.76 • Var ratio = ratio of variances • 13.5 16.7 29.2 0.87 0.74 (suburban over urban) • Corr = correlation coefficient Summer 2003-2005 • 12.6 12.3 -0.4 0.85 0.83 - Different “increments” for different urban sites • 13.0 14.4 15.5 1.10 0.88 - Large sensitivity to the season • - Stronger correlation in summer • Winter 2003-2005 - Larger differences in variance in • winter • 12.9 15.5 22.0 0.600.74 • 13.719.6 46.0 0.640.72

  9. Summers 2003-2005 PM2.5 vs PM10 ratio (non volatile data) Years 2003-2005 Winters 2003-2005

  10. The volatile fraction issue “Metrological” correction based on the implementation of FDMS devices for TEOM and RST devices for b gauges

  11. TEOM (50°C)/HVS TEOM-FDMS/HVS Relative combined uncertainty (DoE guidance) at the mean value : 13,6 % (2 µg/m3) Example : Peyrusse-Vieille (EMEP) 7th September – 15 th November 2005 Aver Conc : 15 µg/m3 Min : 5 µg/m3 Max : 34 µg/m3 Average Temp 15°C (Min 7 – Max 20°C) Average Hum 80% (Min 57- Max 96%) MATERIALS 2 HVS (gravim.) : U.B.S. = 0,64 µg/m3 2 TEOM-FDMS : U.B.S. = 0,86 µg/m3 1 TEOM (50°C)

  12. PM Modelling as a complementary tool • - PM forecasts are provided by the PREV’AIR system (www.prevair.org) • - Based on CHIMERE model simulations • - Analysis of phenomenology especially long range pollution events (ammonium nitrate)

  13. Lag of the forecast Rural stations Suburban stations Observed mean (µg/m3)D - 1 13.9 (Nbr Obs: 358) 17.3 (Nbr Obs:1345) D + 0 13.9 (Nbr Obs: 358) 17.3 (Nbr Obs:1346) D + 1 13.9 (Nbr Obs: 351) 17.4 (Nbr Obs:1320) D + 2 14.0 (Nbr Obs: 346) 17.5 (Nbr Obs:1298) Simulated mean (µg/m3)D - 1 12.2 13.0 D + 0 12.6 13.5 D + 1 13.0 13.7 D + 2 13.2 13.9 Normalized Bias (%)D - 1 -10.2 -24.1 D + 0 -8.2 -22.3 D + 1 -5.6 -20.9 D + 2 -4.0 -19.3 NMSE (%)D - 1 46.5 44.7 D + 0 50.7 46.8 D + 1 52.8 46.3 D + 2 47.1 44.5 Correlation D - 1 0.63 0.63 D + 0 0.63 0.62 D + 1 0.62 0.62 D + 2 0.65 0.63 E50% (%)D - 1 91. 96. D + 0 91. 96. D + 1 90. 95. D + 2 88. 94. Prev’air scores (for PM10)

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