Saharan Dust Impact on PM2.5 in central Italy

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1 Saharan Dust Impact on PM2.5 in central Italy S. Nava, G. Calzolai, M. Chiari, M. Giannoni, F. Lucarelli Physics Dept. - University of Florence and INFN, Italy S. Becagli, M. Marconi, R. Traversi, R. Udisti Chemistry Dept., University of Florence, Italy - nava@fi.infn.it

2 Introduction Mineral dust is mainly present in the PM coarse mode; however after long large transport an important fraction of the distribution may affect also PM2.5 As the arrival of desert dust is characterised by an increase of all soil related elements, field campaigns followed by elemental analysis, and in particular by PIXE (Particle Induced X-ray Emission) measurements, can be very useful to study the desert dust contribution to PM at the ground level This presentation will show results obtained by a review of elemental data-sets determined by PIXE analysis of PM samples collected in Tuscany (Italy) during extensive field campaigns

5 Livorno Montelupo Fiorentino Arezzo PATOS 1 Sept. 05 Sept. 06 1034 samples of PM10 Fl-Bassi Jun-Jul: PM10-PM2.

3 Field campaigns PATOS 2 1 year (Mar.09 Mar.10) every 2 nd day Lucca Prato 2 sampling sites in Florence and 1 in Livorno Firenze 500 samples of PM2.5 Livorno Montelupo Fiorentino Arezzo PATOS 1 Sept. 05 Sept samples of PM10 Fl-Bassi Jun-Jul: PM10-PM2.5 Grosseto Montelupo Fiorentino Sept. 02 June samples of PM Nov: PM10-PM2.5 Samples collected on a daily basis (from midnight to midnight) by CEN-eq. LV samples equipped with PM10 and PM2.5 inlets

4 Analitical techniques TEFLON FILTER Ion Chromatography inorganic ions QUARTZ FILTER Thermo-optical analysis TC, EC, OC HR-ICPMS soluble component of metals PIXE Elemental concentrations GC & GC-MS PAHs and n- alkanes

multi-target holder ~ few minutes/sample High sensitivity for mineral dust elements (Na, Mg, Al, Si, K, Ca,

5 PIXE (Particle Induced X-ray Emission) Simultaneous detection of all the elements with Z>10 (no pre-treatment and samples are not destroyed) PIXE-PIGE set-up at LABEC two X-ray detectors automatic sample handling by a multi-target holder ~ few minutes/sample High sensitivity for mineral dust elements (Na, Mg, Al, Si, K, Ca, Ti, Mn, Fe, Sr) ~ half minute/sample is sufficient SDD detector 30 sec. 1 year of daily samples 1 day of beam time

6 Data analysis Backward trajectory calculations for all the sampling days (every 6 hours), at different arrival altitudes by HYSPLIT transport model by NOAA Air Resource Laboratory Analysis of elemental concentrations and elemental ratios of crustal elements (in relationship with HYSPLIT data) Soil dust component calculation: 1.35 Na Mg Al Si Ca Fe Ti K - K, Ca and Fe corrected for anthropogenic contributions by EF calculations - Na and Mg corrected for sea-salt contributions African dust obtained by subtraction of an estimated background, calculated as the soil dust monthly moving average (excluding Saharan episodes) Similar to EU guideline approach, but on DUST (not PM) Positive Matrix Factorization (PMF) analysis (PATOS2)

7 1-year campaign (PATOS2, ) GRAMSCI - U.T. T.S. BASSI - U.B. LIVORNO - R.B. PM2.5 g/m Mar 19-Apr 19-May 18-Jun 18-Jul 17-Aug 16-Sep 16-Oct 15-Nov 15-Dec 14-Jan 13-Feb 15-Mar Mean PM2.5 (mg/m 3 ) FIRENZE-GRAMSCI - Traffic site 24 FIRENZE-BASSI - Urban background 16 LIVORNO - Rural background 10

8 Elemental time trends - U.B. - R.B. - T.S. ng/m 3 Al Back-trajectories from Africa Si ng/m 3 14 simultaneous Al-Si peaks in the 3 sampling sites 14 peaks (32 days out of 180 sampling days) due to desert dust

9 Elemental time trends - U.B. - R.B. - T.S. ng/m 3 Al ng/m 3 K Fe ng/m 3

10 Elemental ratios Sahara Backgr. Si/Al Al/Ca Si/Ca Al/Fe Si/Fe Livorno rural Bassi urban Gramsci traffic Sahara Backgr Sahara Backgr Sahara Backgr Si/Al lower in desert dust (with very similar values in the 3 sampling sites) Ratios to Ca and Fe higher in desert dust, due to Ca and Fe enrichment in local soil dust (more site-dependent) Similar behaviour than that observed for PM10 in Tuscany [Nava et al., 2012] and in other Italian sites [Bonelli 96, Marenco 06]

Soil dust concentration Soil dust Soil dust concentration during non-saharan days is ~ 0.5 mg/m 3 and, except for few cases, it is always below 1 mg/m 3 (av. Livorno: 0.

11 Soil dust concentration Soil dust Soil dust concentration during non-saharan days is ~ 0.5 mg/m 3 and, except for few cases, it is always below 1 mg/m 3 (av. Livorno: 0.35 mg/m 3, Bassi: 0.45 mg/m 3, Gramsci:0.61 mg/m 3 ) Soil dust concentration during Saharan episodes ranges from ~ 1 mg/m 3 up to ~ 4 mg/m 3 (during the most intense episode)

12 Contribution to PM2.5 Quite small soil dust contribution (~3% during non-saharan days) Up to ~20% of PM2.5 during the most intense Saharan episode

13 Desert dust Bassi - UB Desert dust contribution, detected in 32 days out of 180 sampling days, shows an high variability: it ranges from few tenths of ng/m 3 up to 3-4 mg/m 3 Desert dust contribution > 1 mg/m 3 in 5 episodes (corresponding to 8 days out of 180 sampling days)

14 source profile (ng/ng) Positive Matrix Factorization (PMF) Advanced receptor model based on a weighted xij least square fit approach gik f 2 dust sources identified in Florence with similar profiles k kj Upper crust profile (Mason) DUST 1 DUST 22 Percentage of species conc. (%)

15 Source time trends DUST UB TS DUST Feb- 09 Mar- 09 Apr- 09 May- 09 Jun- 09 Jul- 09 Aug- 09 Sep- 09 Oct- 09 Nov- 09 Dec- 09 Jan- 10 Feb- 10 Mar- 10 Apr- 10

16 PATOS1: PM10-PM2.5 Sahara Saharan episode (20-28 June) background days (20-30 July) PM2.5/PM (±0.09) 0.74 (±0.05) Saharan episode (20-28 June) background days (20-30 July) Soil dust (mg/m 3 ) in PM2.5 Soil dust (mg/m 3 ) in PM (28%) 22 (46%) 1.4 (6%) 6.1 (21%) Sahara/backgr

PATOS1: elements Sahara Sahara PM2.5 Si/Al Al/Ca Al/Fe Si/Fe Saharan days 2.6 0.46 1.0 2.6 Other days 3.

17 PATOS1: elements Sahara Sahara PM2.5 Si/Al Al/Ca Al/Fe Si/Fe Saharan days Other days PM10 Si/Al Al/Ca Al/Fe Si/Fe Saharan days Other days

18 Montelupo Fiorentino: PM10-PM PM10 PM2.5 Sahara rain PM2.5/PM10 Saharan episode (15-16 Nov) 0.34 (±0.08) Background days (1-8 Nov) 0.63 (±0.08) 01/11/02 03/11/02 05/11/02 07/11/02 09/11/02 11/11/02 13/11/02 15/11/02 17/11/02 19/11/02 21/11/ /11/02 3/11/02 soil PM10 soil PM2.5 Soil dust (mg/m 3 ) in PM2.5 5/11/02 7/11/02 9/11/02 11/11/02 13/11/02 15/11/02 17/11/02 19/11/02 21/11/02 Saharan episode (15-16 Nov) Background days (1-8 Nov) Soil dust (mg/m 3 ) in PM (27%) 29 (38%) 0.8 (4%) 4.7 (14%) Sahara/backgr

19 Montelupo Fiorentino: elements /11/02 3/11/02 PM10 5/11/02 7/11/02 9/11/02 11/11/02 13/11/02 15/11/02 Sahara 17/11/02 rain 19/11/02 21/11/ Mg Al Si K Ca Tix20 Fe 1/11/02 3/11/02 Srx70 PM2.5 5/11/02 7/11/02 9/11/02 11/11/02 13/11/02 15/11/02 Sahara 17/11/02 rain 19/11/02 21/11/02 Mg Al Si K Ca Tix20 Fe sahara background PM2.5 Si/Al Al/Ca Al/Fe Si/Fe PM2.5/PM Al Si Ca Saharan days Other days PM10 Si/Al Al/Ca Al/Fe Si/Fe Saharan days Other days

20 Conclusions The impact of several desert dust intrusions to PM2.5 at the ground level has been detected in Tuscany, by mean of field campaigns followed by elemental analysis Their contributions show a very high variability: the estimated desert dust net concentration ranges from few tenths up to 5-10 μg/m 3 during the most intense events The high sensitivity-rapidity of PIXE makes the use of this technique a feasible approach to study the impact of desert dust over representative long periods and for extended monitoring networks Together with atmospheric/meteorological data analysis, it may provide an effective method to trace the contribution of desert dust to PM quality standards, which may be used to validate cheaper approaches that do not require speciation measurements

21 ng/m 3 Elemental time trends - U.B. - R.B. Al - T.S. ng/m 3 Mg Na ng/m 3

22 Elemental time trends ng/m 3 Al ng/m 3 Si Ca ng/m 3

GAMINGRE 8/1/ of 7

GAMINGRE 8/1/ of 7 FYE 09/30/92 JULY 92 0.00 254,550.00 0.00 0 0 0 0 0 0 0 0 0 254,550.00 0.00 0.00 0.00 0.00 254,550.00 AUG 10,616,710.31 5,299.95 845,656.83 84,565.68 61,084.86 23,480.82 339,734.73 135,893.89 67,946.95