Content. Introduction Particle sampling Particle analysis with electron microscopy Case studies Conclusion and outlook

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Osborne Higgins
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2 Content Introduction Particle sampling Particle analysis with electron microscopy Case studies Conclusion and outlook

3 Introduction Why do we analyse aerosol particles with SEM? Advantages High spacial resolution Detailed morphological information Chemical analysis Automated systems for morphochemical analyses are available. Quantitative results! Low quantities of particles are required (high temporal resolution) Limitations Problems with volatile, semi-volatile (vacuum in microscope) and «light element particles» Spacial resolution: Particles > 100nm No trace element detection Good method for studies concerning health effects?

4 Sampling methods for SEM Tape-Lift-sampling UNIFR-sampler + TEM-sampler SIGMA 2 passive sampler (Mini)- Impactor The sampling method depends strongly on environmental conditions and the analysis methods you will use! Sampling substrate? Active or passive sampling?

5 Sampling methods for SEM Conventional conical PM10 sample holder Sampler designed by R. Kägi (EMPA) for homogeneous particle repartition

6 Scanning electron microscopy SEM is a reflection microscopy technique with scanning illumination. Electron gun Optic column with condensing lenses and scanning unit Sample

Electron beam Scanning electron microscopy Interaction of electron beam with sample produces different signals: Backscattered electrons Secondary electrons X-rays Secondary electrons Emissions of

7 Electron beam Scanning electron microscopy Interaction of electron beam with sample produces different signals: Backscattered electrons Secondary electrons X-rays Secondary electrons Emissions of sample electrons by interaction with electron beam Morphological contrast Backscattered electrons: Electrons from the primery beam gets backscattered Material contrast Sample X-rays (EDX) Electron vacancies, produced by interaction of primary electron beam with atoms of sample, get filled with electrons from the same atom. This process emits a characteristic x-ray Chemical composition

8 23 µm Automated Scanning electron microscopy Combination of imaging and chemical analysis with energy dispersive X-ray spectroscopy. Automated single particle analysis (Software: EDAX) allows to characterise over 1000 particles in 8 hours. Stub = Matrix (3x3 fields) 30 µm

concentration 5 μm O Si With Polycarbonate filters it is not possible to detect

9 Automated Scanning electron microscopy BSE-image of polycarbonate filter Particle number Morphological data Chemical composition Particle size distribution and approximativ mass concentration 5 μm O Si With Polycarbonate filters it is not possible to detect C-particles automatically! Al Mg P K Avg. Diameter: 4.06 μm Perimeter: μm Area: μm 2 Fe

10 Saharan dust particles on Jungfraujoch Mario Meier 1, Bernard Grobéty 1, Martine Collaud Coen 2 1. Dept. of Geosciences, University of Fribourg / 2. MeteoSwiss, Aerological Station, Payerne

11 Saharan dust particles on Jungfraujoch Single Scattering Albedo: ω = β/(β +k) β = Scattering Coefficent; k = Absorption Coefficent) β + k = Extinction Coefficent Main question: Why does the single scattering albedo show an inversion of the wavelength dependence during a Saharan Dust Event? How to find the answear: Chemical and morphological analysis of mineral dust with SEM Meier et al., 2009

12 Saharan dust particles on Jungfraujoch Particle size distribution The particle number concentration increases during a SDE but also the particle size distribution changes. The strong increase of particle number concentration in the fraction μm leads to a scattering dominated by geometrical optics. 24/05/08 26/05/08 28/05/08 30/05/08 Meier et al., 2009

13 Mass [ng/m 3 ] Saharan dust particles on Jungfraujoch Iron class: Iron (Fe) Iron oxides/hydroxides (Hematite, Magnetite, Goethite,...) Aluminium class: Aluminium dominated Clays Aluminium Oxides Mass concentraion Clay class: Silicon dominated clays Feldspars Silicon class: Quartz: SiO Carbonate class: Calcite: CaCO 3 Dolomite: CaMg(CO 3 ) 2 Gypsum class: Gypsum: CaSO 4 2H 2 O Anhydrite: CaSO 4 Sulfur class Sulfur Sulfates (excl. Gypsum and Anhydrite)

14 Saharan dust particles on Jungfraujoch Chemical composition Background Fe-Si-Al Saharan Dust Event No evident chemical differences are visible!!!

15 number concentration [particles/cm 3 ] Saharan dust particles on Jungfraujoch 23 May (afternoon): Increase of total number concentration. All analyzed particles contain sulfur. Source: Anthropogenic (Jungfraujoch in planetary boundary layer)? 1) S 2) S 3) S 3 SDE K Ca K Ca K Ca

16 Saharan dust particles on Jungfraujoch No SDE Differences in chemistry and morphology? TEM image SDE TEM image

Saharan dust particles on Jungfraujoch TEM image Background TEM image SDE Clay Iron oxide Titanium oxide Carbonate Clay particles from the Saharan dust event contain more iron

17 Saharan dust particles on Jungfraujoch TEM image Background TEM image SDE Clay Iron oxide Titanium oxide Carbonate Clay particles from the Saharan dust event contain more iron and titanium oxide inclusions. Iron containing inclusions of background samples are often associated with Sulphur. Therefore the inclusions could be iron sulfides and not oxides

18 Eyjafjallajökull ash cloud crisis Mario Meier 1, Bernard Grobéty 1 and group Konradin Weber 2 1. Dept. of Geosciences, University of Fribourg / 2. TU Düsseldorf Eruption in april/may Airspace closure over Europe. Important economic impact. Measurement flights over Island and Germany Weber et al. (2012)

19 Eyjafjallajökull Weber et al. (2012) 2 flights with a light aircraft (18th may 2010): F1) Crossing zones with high particle concentrations (volcanic ash?) F2) Almost no high particle concentration zones. VAAC model of may

20 Weber et al. (2012) a) b) Eyjafjallajökull c) 50 μm 100 μm a) Porous glass particle b) left: Crystals in a glassy matrix right: crystal fragment (Olivine) c) Crystals of FeTi-Oxide (x1) and Pyroxenes (x2). All sampled over Island. x2 x1 5 μm Flight F1 Flight crossing ash cloud over Island Flight F2 Blue square = bulk composition of eruption products

21 Eyjafjallajökull resuspension Station 2 ( ) Station 2 ( ) Figure 1: Clearly visible trend of silicate material without NaCl to pure NaCl particles (including mixed particles). Figure 2: No trend and no mixed particles for the sample of 21 August.

22 Firework emissions Sampling: 1st of August 2011 in Suhr (AG) Element Increase/decrease during fireworks Si 0.8 Fe 0 Al 4 Mg 10 S 13 K 24 Ba 100 Typical firework particle containing S, Ba and K In cooperation with canton Aargau and carbotech AG

23 Cement plant emissions Particle source 1 (milling of raw material): Ca-carbonate Clays Additives Heating and sintering Particle source 2 (milling clinker): Clinker Additives In cooperation with cement industry and carbotech AG

24 SEM on SIGMA 2 samples Repartition of particles Silicates and iron particles are more important are more important Clear influence of Aluminum particles In cooperation with canton Aargau

25 SEM on SIGMA 2 samples Repartition of silicate particles Möhlin (AG) Wallbach (AG) In cooperation with canton Aargau

26 Conclusion Single particle analysis with SEM is automated is suitable for short and long term studies, depending on sampling method. has a good spacial resolution and produces detailed morphological data of particles. produces chemical data of particles. Morphological and chemical data can be used combined for particle classification calculating number and mass concentrations of particle classes detailed characterisation of particle emissions and immissions More data than mass/number concentration or bulk chemistry Good method for studies concerning health effects? My opinion: Yes it is!

27 Outlook Improving the method is possible! Using Boron-substrates allows to analyse also C and O. (Already proposed and tested by TU Darmstadt) Standardisation of method including a particle database Automatisation of particle classification Automatisation of scanning transmission electron microscopy (STEM): Lower detection limits, better spatial resolution,

Electron Microscopy SEM and TEM

Electron Microscopy SEM and TEM Content 1. Introduction: Motivation for electron microscopy 2. Interaction with matter 3. SEM: Scanning Electron Microscopy 3.1 Functional Principle 3.2 Examples 3.3 EDX