MARINE GEORESOURCES. OF THE SOUTHERN TYRRHENIAN SEA: Critical Elements potential assessed by geochemical data

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V. Funari 1, M. Rovere 2, F. Gamberi 2, M. Marani 3, E.

(Geology Division) University of Bologna, Piazza di Porta San

National Research Council, Via Piero Gobetti 101, Bologna -

Critical Elements potential assessed by geochemical data

1 V. Funari 1, M. Rovere 2, F. Gamberi 2, M. Marani 3, E. Dinelli 1, R. Braga 1 1 BiGeA Dept. (Geology Division) University of Bologna, Piazza di Porta San Donato 1, Bologna - Italy 2 Institute of Marine Sciences National Research Council, Via Piero Gobetti 101, Bologna - Italy MARINE GEORESOURCES OF THE SOUTHERN TYRRHENIAN SEA: Critical Elements potential assessed by geochemical data SESSION S 26. Energy and earth resources: geology between renewable, sustainable and conventional energy sources

SUPPLY RISK GEORESOURCES AND RAW MATERIAL SUPPLY The importance of Critical

They have strategic importance for emerging new and green-energy ECONOMIC

2 SUPPLY RISK GEORESOURCES AND RAW MATERIAL SUPPLY The importance of Critical Elements (CrE) The European Commission defined a list of CrE (EC, 2010; 2014). They have strategic importance for emerging new and green-energy ECONOMIC IMPORTANCE Image source: Critical raw materials for the EU, European commission. May 2014 technologies. Main producers of critical raw materials The highest production of CrE is based in non-eu countries, China mostly. Data from 1

SEABED EXPLORATION AND EXPLOITATION Recent findings

about manganese nodules littering the deep sea

seamount areas in the central Pacific. Kato et al.

3 SEABED EXPLORATION AND EXPLOITATION Recent findings on marine resources For many years we have known about manganese nodules littering the deep sea floor, but there is more than manganese to mine at the bottom of the ocean: Hein et al. (2009) lay out a mine-site model for Co-rich seamount areas in the central Pacific. Kato et al. (2011) show that deep-sea mud constitutes a promising huge resource of REE. 2

SEABED EXPLORATION AND EXPLOITATION Work in progress 7 exploration licenses for seabed mining have been granted to: UK Seabed Resources Government of India Russian Ministry of Natural Resources

4 SEABED EXPLORATION AND EXPLOITATION Work in progress 7 exploration licenses for seabed mining have been granted to: UK Seabed Resources Government of India Russian Ministry of Natural Resources Brazil s Companhia de Pesquisa de Recursos Minerias Ocean Mineral Singapore Germany Federal Institute for Geosciences Cook Islands Investment Corporation Initiatives to mine for minerals in deep waters have recently been unveiled in Papua New Guinea... Source: Is this the beginning of an era of seafloor georesources exploitation? 3

SEABED EXPLORATION AND EXPLOITATION Environmental Issues The science around the

Any disturbance to sediments at the bottom of the ocean could harm seafloor

.. The Trans-Tasman Resources (NZ) case Most were concerned about the unknown

5 SEABED EXPLORATION AND EXPLOITATION Environmental Issues The science around the environmental impacts of deep seafloor is incomplete. Any disturbance to sediments at the bottom of the ocean could harm seafloor communities... The Trans-Tasman Resources (NZ) case Most were concerned about the unknown effects of the mining on animals and plants, and the extent of the ash plume that occurs when leftover sediment is dumped back on the seabed... The EPA's decision-making committee. 4

environmental problems in the Rio Tinto, Spain.

nasa.gov Northern Territory, Australia: major

From the Lonely Planet Acid drainage and slope

6 SEABED EXPLORATION AND EXPLOITATION Environmental Issues on land Acid mine drainage causes severe environmental problems in the Rio Tinto, Spain. Iron Mine Tailings, Ishpeming, USA. From Northern Territory, Australia: major radioactive component U-238. From the Lonely Planet Acid drainage and slope instability distress the dismissed mine of Libiola (Sestri Levante). From The Overthinker 5

7 SEABED EXPLORATION AND EXPLOITATION The Critical Elements Potential of Tyrrhenian Seabed There are a wide variety of data on Italian seabed Knowledge on the spatial distribution of resource deposits is virtually unknown AIM Preliminary synthesis with an heterogeneous database (following the Kato s example) Reliable resource assessment (Potential ore per unit of seabed surface area) 6

8 THESTUDY AREA The Southern Tyrrhenian Sea Tyrrhenian Sea Southern Tyrrhenian AREA: ~ km 2 TOTAL SAMPLES: km

9 THESTUDY AREA The Southern Tyrrhenian Sea Tyrrhenian Sea VA: Vavilov PN: Palinuro MS: Marsili PB: Paola Basin W-EO: Eolian Arc (West) E-EO: Eolian Arc (Est) km

10 THESTUDY AREA The Samples Material comes from box and gravity corer. Only the near-surface sediments and crusts ( ~1 m) Iron oxy-hydroxides Mn -crusts Emipelagic mud Biogenic sand Carbonates Burrows of sulphides 8

ANALYTICAL METHODS The heterogeneity of data set and measurements 130 marine samples SCATTERED sampling Different analytical techniques ICP-MS, XRF, AAS Different

11 ANALYTICAL METHODS The heterogeneity of data set and measurements 130 marine samples SCATTERED sampling Different analytical techniques ICP-MS, XRF, AAS Different list of analytes Different laboratories Univ. of Bologna, Univ. of Florence, Actlabs Different CNR-ISMAR oceanografic cruises from 1997 to 2011 BiGeA (Sezione Geologia) 9

12 PUCTUAL ANALYSES The CrE abundance 4 0 Mean concentration (mg/kg ), by location: Vavilov: 535 ƩCrE 116 ƩREE Marsili: 815 ƩCrE 126 ƩREE Paola Basin: 671 ƩCrE 227 ƩREE Palinuro: 1218 ƩCrE 87 ƩREE Eolian (West): 709 ƩCrE 111 ƩREE Eolian (Est): 420 ƩCrE 127 ƩREE km CrE: Ce, Co, Cr, Dy, Er, Eu, Ga, Gd, Ho, La, Lu Nb, Nd, Pr, Sb, Sc, Sm, Tb, Tm, Y, Yb (Mg not included) 10

13 PUNCTUAL ANALYSES The distribution of some CrE Samples are grouped by the main oxides Co in Mn-rich and Fe-rich Cr in Mn-rich and Ca-Mg rich Ce in Al-Si rich 11

14 PUNCTUAL ANALYSES Hypotheses for the origin of CrE Hydrogenous Hydrothermal Hydrothermal and hydrogenous zones are from Hein et al. (1994) 12

15 PUNCTUAL ANALYSES Hypotheses for the origin of CrE Boxplot of some CrE, by inferred origin. Concentrations are very similar between hydrothermal and hydrogenous zone. (n=80) (n=50) 13

16 INTERPOLATION OF PUNCTUAL ANALYSES Geostatistic and assumptions Kriging (KR) and Inverse distance to a power (IDW) predict unknown values using known values and a model variogram (the latter only for KR). Both methods are suitable for geostatistical interpolation IWD exact interpolator KR smoothing interpolator However, homogeneous and dense sampling indispensable for accurate interpolation. Assumptions: Data are normally distributed Variogram (KR): visible trend Linear model + nugget effect no trend nugget effect 14

17 INTERPOLATION OF PUNCTUAL ANALYSES ƩREE interpolated map 42 SETTING Lag direction omni-dir. Max Lag Dist.: 1.1 (~111 km) Num. of Lags: 26 Data search Max n. samples 15 Min n. samples 10 R of search 0.5 (~55 km) 41.5 mg/kg 41 IDW - ƩREE Sicily

18 Variogram INTERPOLATION OF PUNCTUAL ANALYSES ƩREE interpolated map 42 SETTING Lag direction Max Lag Dist.: Num. of Lags: 26 Data search Max n. samples 15 Min n. samples 10 R of search Column BQ: REE Direction: 0.0 Tolerance: omni-dir. 1.1 (~111 km) 0.5 (~55 km) Lag Distance KR - ƩREE Linear model: slope= 4890 aniso=1 mg/kg Sicily Nugget effect: 13 error 13.5 variance=

19 Variogram INTERPOLATION OF PUNCTUAL ANALYSES Gallium interpolated map SETTING Lag direction Max Lag Dist.: Num. of Lags: 29 Data search Max n. samples 15 Min n. samples 10 R of search omni-dir. 1.1 (~111 km) 0.5 (~55 km) Column W: Ga Direction: 0.0 Tolerance: Lag Distance KR - Ga Sicily Nugget effect: 13 error 13.5variance= Linear model: slope= 106 aniso=1 mg/kg 17

20 Variogram INTERPOLATION OF PUNCTUAL ANALYSES Cobalt interpolated map SETTING Lag direction Max Lag Dist.: Num. of Lags: 27 Data search Max n. samples 15 Min n. samples 10 R of search omni-dir. 1.1 (~111 km) 0.5 (~55 km) Column O: Co Direction: 0.0 Tolerance: Lag Distance Linear model: slope= - aniso= - KR - Co Sicily Nugget effect: 13 error 13.5variance= mg/kg 18

21 Variogram INTERPOLATION OF PUNCTUAL ANALYSES Chromium interpolated map SETTING Lag direction Max Lag Dist.: Num. of Lags: 27 Data search Max n. samples 15 Min n. samples 10 R of search omni-dir. 1.1 (~111 km) 0.5 (~55 km) Column O: Co Direction: 0.0 Tolerance: Lag Distance KR - Cr Nugget effect: 13 error 13.5 variance= Sicily Linear model: slope= - aniso= - mg/kg

INTERPOLATION OF PUNCTUAL ANALYSES 42 41.5 3D interpolated map of ƩREE 41.5 42 41.5 12 13 14 15 16 Paola Basin 39.5 41.

5 HYPOTHETICAL MINE-SITE Volume*: ~1100 km 3 37 11 11.5 12 12.5 13 13.5 14 14.5 15 15.5 16 16.

22 INTERPOLATION OF PUNCTUAL ANALYSES D interpolated map of ƩREE Paola Basin Sicily HYPOTHETICAL MINE-SITE Volume*: ~1100 km Depth: Total tonnage**: Grade: Potential recovery: <2000 m ~ 2150 t ~ 0.03 wt.% TREO ~ 0.7 t TREO *1-m thick mining area **wet metric tonnes based on density of 1.95 g/cm 3 20

23 CONCLUSION AND OUTLOOK First attempt for the evaluation of CrE in S-Tyrrhenian Sea and their spatial distribution Numbers seem unfavourable but for example: high critical elements content in Palinuro Ridge zone high Ce in Al-Si-rich deposits about 0.7 t TREO potential recovery in the Paola Basin, considering a relatively small volume The need of an homogeneous analytical protocol when exploring marine areas for more accurate map of interpolation 21

presents a complex challenge for Sciences and

24 THANK YOU FOR YOUR ATTENTION Environmentally responsible collection of marine georesources presents a complex challenge for Sciences and scientists.? From Nautilus Minerals Inc., modified.

25 SUPPLEMENTARY MATERIAL

26 PUNCTUAL ANALYSES: Correlations with major elements CaO (wt.%) SiO2 (wt.%) Fe2O3 (wt.%) Fe2O3 (wt.%) 50 Scatterplot of CaO vs Cr 80 Scatterplot of Fe2O3% vs Co Cr (mg/kg) Co (mg/kg) Scatterplot of SiO2 vs Ce Scatterplot of Fe2O3% vs REE Ce (mg/kg) REE (mg/kg) 300 0

higher in W-EO W higher in PN Concentration means Samples are grouped by the main

27 PUNCTUAL ANALYSES: The distribution of some CrE Concentration means Samples are grouped by location REE and Nb higher in PB and E-EO Co higher in EO and PB Cr higher in W-EO W higher in PN Concentration means Samples are grouped by the main oxides Ce in Al-Si rich and Alkali-rich Co in Mn-rich and Fe-rich Cr in Mn-rich and Ca-Mg rich

28 Variogram INTERPOLATION OF PUNCTUAL ANALYSES: Magnesium oxide interpolated map 42 SETTING Lag direction Max Lag Dist.: Num. of Lags: 26 Data search Max n. samples 15 Min n. samples 10 R of search omni-dir. 1.1 (~111 km) 0.5 (~55 km) Column AI: MgO Direction: 0.0 Tolerance: Lag Distance Linear model: slope= - aniso= - KR - MgO Sicily Nugget effect: 13 error 13.5 variance= wt.%

29 INTERPOLATION OF PUNCTUAL ANALYSES: 3D interpolated map: smaller database Cr INTERPOLATED AREA: ~1800 km 2 HYPOTHETICAL MINE-SITE: Volume*: ~ km 3 Depth: <1000 m Total tonnage**: ~78 t *1-m thick mining area **wet metric tonnes based on density of 1.95 g/cm 3.

30 INTERPOLATION OF PUNCTUAL ANALYSES: 3D interpolated map: smaller database Ce INTERPOLATED AREA: ~1800 km 2 HYPOTHETICAL MINE-SITE: Volume*: ~ km 3 Depth: <1000 m Total tonnage**: ~78 t *1-m thick mining area **wet metric tonnes based on density of 1.95 g/cm 3.

Deep Sea Minerals in the Pacific Islands Region: Occurrence, Potential and Case Studies`

Deep Sea Minerals in the Pacific Islands Region: Occurrence, Potential and Case Studies` 1st DSM Project Regional Workshop 6th 8th June 2011 Tanoa International Hotel Nadi, Fiji Akuila Tawake SPC/SOPAC