1 / 18

Identifying human impacts on the pollution status of cork forests

SEGH 2010 29 th June 2010 NUI, Galway. Identifying human impacts on the pollution status of cork forests.

ramya
Télécharger la présentation

Identifying human impacts on the pollution status of cork forests

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. SEGH 2010 29th June 2010 NUI, Galway Identifying human impacts on the pollution status of cork forests Iain McLellan1, Andrew Hursthouse1, C Morrison1, C Silva Pereira2,A Hassen3, V Mazzoleni4, M Blahgen5, A Valera2, C Rodrigues2, C Leitão2, H I Ouzari3, A Jaouani3, N Gaâmour3, M D Fumi4, E Novelli4, M Trevisan4 and K Lyamiuoli5 University of the West of Scotland, Paisley, UK Institudo de Biologia Experimental e Tecnológica, Oeiras, Portugal Centre de Recherche en Sciences et Technolgies de l’Eau, Solimnen, Tunisia UniversitàCattolica del SacroCuore, Piacenza, Italy University Hassan II, Casablanca, Morocco

  2. Project • Italy, Morocco, Portugal, Tunisia, UK • NATO Science for Peace Case study evaluation Tunisia Sampling UK Bulk soil simulation Portugal, Tunisia Monitoring & Optimisation Portugal, UK Bioaccumulation UK Dissemination Portugal, Tunisia, UK Project Management Portugal, Tunisia Chemical Analysis UK Microbial Analysis Portugal Bioremediation Portugal

  3. Rationale • Cork • Quercussuber • Portugal, Spain, France, Italy, • Tunisia, Morocco, Algeria • Human influence • Where do we look? • How do we deal with it? • Cork taint • Chlorophenols & chloroanisoles • Metals • As, Zn, Pb etc

  4. Tunisian samples

  5. AînHamraia

  6. FejErrih

  7. RasRajel

  8. Sardinian samples

  9. Sardinian samples

  10. Pentachlorophenol - Cl - H - Cl - OH + OH + Cl + CH3 - H + CH3 - Cl - Cl - Cl - Cl - H + CH3

  11. Pentachlorophenol • HPLC-UV/Vis • Identification on k and α PCP:TBP standard AînHamraia RasRajel 2

  12. AH_09_1-SF_A_31052010_1 # 2083 RT: 22.12 AV: 1 SB: 517 5.05-10.56 NL: 1.31E7 T: - c ESI Full ms [75.00-650.00] 293.02 100 95 AH_09_1-SF_A_31052010_1 # 183 RT: 1.92 AV: 1 SB: 517 5.05-10.56 NL: 4.04E8 90 T: - c ESI Full ms [75.00-650.00] 401.00 100 85 95 80 90 75 85 70 80 65 75 60 70 55 65 Relative Abundance 50 60 45 55 40 Relative Abundance 50 35 45 30 40 294.13 25 118.82 35 20 375.02 30 222.87 15 457.03 352.25 25 304.81 10 141.01 550.84 380.78 20 462.69 538.78 305.96 5 610.59 420.09 553.16 282.75 164.61 203.94 401.99 76.66 15 0 100 150 200 250 300 350 400 450 500 550 600 650 m/z 10 562.93 403.02 5 564.07 404.01 400.18 561.07 240.96 635.38 494.17 340.87 80.68 118.08 265.00 604.06 161.11 0 100 150 200 250 300 350 400 450 500 550 600 650 m/z Pentachlorophenol • LC-MS • Separation of all chlorophenols • No pentachlorophenol • No chlorophenols • What compounds are present? m/z 401 m/z 293 AînHamraia m/z 401 m/z 293 TIC m/z 293, Int Std

  13. Elemental Analysis RasRajel (mg/kg) Cr Pb Zn Mn Sardinia Al Fe Ca Tunisia

  14. Sardinia - PCA • PC 1: Low Al, Fe, Na & Cr = High Pb, Ba, Sr & Ca • PC 2: Low K & Ti = High Zn, Mn & Mg • Geology of area: unequigranularmonzogranite • Both PCs are related to geology • PC1: Biotite, albite, apatite and anorthite • PC2: Ilmenite and titanite • Both PCs are related to geology • PC1: Biotite, albite, apatite and anorthite • Both PCs are related to geology Cu, V, B, Ni, Co & Li In Sardinian samples not Tunisian samples

  15. Tunisia - PCA AȋnHamraia • PC 1: High Ba, Mn, Mg, Ca, K & Na = low Al (50% variance) • PC 2: High Fe = low Ti (33% variance) • Pb, Cr, Sr & Zn all <MDL FejErrih • PC 1: High Pb, Al, Fe, Ti = low Zn, Mn, Sr & Ca (53% variance) • PC 2: Ba, Mg & Na (27% variance, all related) • PC 3: K (16% variance, distinct K source?) • Cr < MDL RasRajel • PC 1: High Mg, Al, Fe, K, Ti & Cr = low Pb, Zn, Ba, Sr & Ca • (84% variance) • PC 2: Mn & Na (15% variance, distinct Mn source?)

  16. Future work & conclusions • Human impact • Other pesticides? • Geology v input • Cork bark • Transport

  17. Acknowledgments Prof Andrew Hursthouse University of the West of Scotland NATO SfP 981764 Charlie McGinness David Stirling Sylvo-pastoral Institute of Tabarka StazioneSperimentale del Sughero

  18. Any questions?

More Related