ROSOLS S : SOURCES, PROPERTIES, MODELS AND MEASUREMENTS

1000 100 dn/dlnr (cm-3) 10 ATMOSPHERIC AEROSOL ROSOLS S : SOURCES, PROPERTIES, MODELS AND MEASUREMENTS François DULAC Laboratoire des Sciences du Climat et de l Environnement CEA-CNRS, Gif-Sur-Yvette, France 1 0,001 0,01 0,1 1 10 100 R (µm) fdulac@cea.fr 1/34

CONTENT DEFINITIONS SOURCES ILLUSTRATION OF AEROSOL VARIABILITY AEROSOL MODELS MEASUREMENT METHODS EXAMPLE FROM A FIELD CAMPAIGN AN OPEN QUESTION : INTERNAL MIXTURES CONCLUSION 2/34

ATMOSPHERIC AEROSOLA EROSOLS S : WHAT ARE WE TALKING ABOUT? Definition: suspension in the air of fine particles of natural or man-made origins Excluding liquid cloud droplets, but including stratospheric liquid droplets of sulfuric acid which make the background stratospheric aerosol, and ice crystals Intermediate (unstable) state between molecules and solid powders Particles are a trace component of air Global production of atmospheric aerosols: ~10 millions tons/day Primary aerosols are emitted as particles Secondary aerosols are formed in the atmosphere from gas emissions Major feature of atmospheric aerosols: variability and heterogeneity In time and space Difficult characterization 3/34

AEROSOLS S HAVE MULTIPLE SOURCES Widespread surface sources (primary aerosols) Arid surfaces (mineral dust), ocean (sea salt), biosphere (pollen, debris, ), biomass and fuel burning (soot, fly ash) Intense point sources Volcanoes (dust and ash), man-made explosions (atmospheric nuclear tests, accidents: radioactive particles) Spatial sources within the atmospheric volume Primary aerosols: air traffic (soot) Secondary particles: gas-to-particle conversion, cloud evaporation, ice condensation/crystallisation Extraterrestrial sources generally neglected 4/34

Sources AEROSOL ORIGINS Approx. global emission flux (Tg an -1 ) Global mean optical thickness at 550 nm Primary aerosols N a t u r a l Desert and semi-arid areas (mineral dust) Marine sea spray Volcanic dust Biogenic (pollens, debris) Secondary aerosols Sulphates from biogenic gases Sulphates from volcanic SO 2 Nitrates from nitrogen oxides 1500 1300 33 50 90 12 55 0.023 0.003 0.001 0.002 0.017 0.002 0.017 Organics from volatile organic compounds (COV) 22 0.001 TOTAL ~3060 0.066 A n t h r o p o g e n i c Industrial dust Soot Primary aerosols Secondary aerosols Organics from biogenic COV Sulphates produced by SO 2 Produced from biomass combustion gases Nitrates from nitrogen oxides TOTAL 100 10 10 190 90 50 ~390 0.004 0.006 0.027 0.027 0.002 0.003 0.069 Estimates of Andreae (1994) 5/34

MAN-MADE MADE POLLUTION NOW DOMINATES SECONDARY AEROSOLS (IPCC Report, 2001) 6/34

TEMPORAL VARIABILITY Y AT GROUND LEVEL Lifetime of atmospheric particles (few days) is long enough to allow longrange tansport, but short enough to allow concentrations to vary by orders of magnitude in time and space Daily atmospheric concentrations in particulate Si at a coastal site in Corsica (April 1985-April 1986) Peaks : African dust (70% of deposition) Dry season: high concentrations Wet season: low concentrations Minima : rains (70% of dust deposition) (Bergametti et al., 1989) 7/34

TEMPORAL VARIABILITY Y IN THE COLUMN Meteosat-derived aerosol optical thickness at 550 nm integrated over the Eastern Mediterranean daily data 30-d smoothing av. (Moulin et al., JGR, 1997) The column aerosol extinction of solar light shows short term, seasonal and interannual variability 8/34

LARGE SCALE VARIABILITY Illustration of the seasonal and spatial variability of the aerosol distribution as seen from satellite (Tanré et al., 2001) PolDER aerosol index 9/34

GEOGRAPHICAL VARIABILITY Y OF AEROSOL FOR SIMILAR ENVIRONMENTS Example of geographical variability in chemical composition of peri-urban aerosols Thessaloniki (June 1997) Paris (June 2000) Fine Coarse Fine Coarse Organics Organics Dust Mineral dust and seasalt Soot Soot Sulphate-like Sulphate-like (Chazette and Liousse, 2001) (Chazette et al., 2001) 10/34

COMPOSITION VARIES WITH PARTICLE SIZE The aerosol chemical composition varies with the particle size Impactor samples, eastern Mediterranean Concentration, µg m -3 Detection limit Sulphur (anthropogenic aer.) Calcium (terrigeneous aer.) (Formenti et al., MPIC, unpublished) Particle diameter, µm 11/34

A VARIETY OF PARTICLE TYPES The diversity of aerosol sources yields an abundant "zoology" of particles with various and varying chemical and physical properties Examples of aerosol particles collected over the Mediterranean Sea Copyright 2002 Max-Planck-Institut, Mainz, Germany (J. Huth, P. Formenti, A. Rausch, B. Steude and G. Helas) http://www.mpch-mainz.mpg.de/~kosmo/remgallery/medsea/medsea.htm 12/34

HETEROGENEOUS IN SIZE AND SHAPE Examples of aerosol particles collected over the Mediterranean Sea 1 µm Large ovoid mineral dust from Africa (Dulac et al., 1989) Flat clay disk trapped in a filter hole (Huth et al., MPIC Mainz) 0.2 µm Microsoot aggregate from biomass burning (Formenti et al., MPIC Mainz) 13/34

The aerosol particle size distribution spans over several orders of magnitude The range of interest depends on whether the particle number, surface or volume controls the considered properties or interactions % HETEROGENEITY Y IN SIZE, cont. The number size distribution is controlled by particles of submicronic size Cumulative number and volume model distributions of the background aerosol over a desert 100 90 80 70 60 50 Nucleation, secondary particles Radius < 0,2 µm 99% total number 5% total volume Solar extinction Radius 0.05-3 µm 10% of number 60% of volume 100% of extinct. % N cum % V cum 40 30 20 10 Geochemistry, mass transfers Radius > 3 µm 4 10-9 % of total number 40% of total volume 100% of deposition 0 0,0001 0,001 0,01 0,1 1 10 100 1000 R (µm) (Shettle, 1984) 14/34

SIZE DISTRIBUTION MODELING The size distribution can generally be approximated by 3 lognormal modes, the relative proportions of which are varying over several orders of magnitude dn(r) / dlnr = (2 Π) -1/2 Σ i=1-3 N i (logσ i ) -1 exp { [log(r/r i )] 2 / 2(logσ i ) 2 } Particle number (cm -3 ) and volume (µ 3 cm -3 ) size distribution of the background desert aerosol 1,E+04 1,E+03 1,E+02 1,E+01 1,E+00 1,E-01 1,E-02 1,E-03 1,E-04 1,E-05 1,E-06 dn/dlnr dn1/dlnr dn2/dlnr dn3/dlnr dv/dlnr dv1/dlnr dv2/dlnr dv3/dlnr "Aitken or nucleation" mode(s) R i < 0.1 µm "Accumulation" mode(s) 0.1 µm < R i < 1 µm "Coarse" mode(s) 1 µm < R i < 10 µm "Giant" mode(s) R i > 10 µm 1,E-07 0,00001 0,0001 0,001 0,01 0,1 1 10 100 1000 R (µm) (Shettle, 1984) 15/34

AEROSOL MODELS The variety of particle origins translates into their physical and chemical properties Optical Properties of Aerosol and Clouds (OPAC) data base and software: M. Hess, P. Koepke, and I. Schult (1998): Optical properties of aerosols and clouds: the software package OPAC, Bull. Am. Met. Soc., 79, 831-844. Abstract: The software package OPAC (Optical Properties of Aerosols and Clouds) provides optical properties in the solar and terrestrial spectral range of atmospheric particulate matter. Microphysical and optical properties of 6 water clouds, three ice clouds and 10 aerosol components, which are considered as typical cases, are stored in ASCII files. The optical properties are the extinction, scattering and absorption coefficients, the single scattering albedo, the asymmetry parameter and the phase function. They are calculated on the basis of the microphysical data (size distribution and spectral refractive index) under the assumption of spherical particles in case of aerosols and cloud droplets and assuming hexagonal columns in case of cirrus clouds. Data are given for up to 61 wavelengths between 0.25 µm and 40 µm and up to 8 values of the relative humidity. The software package also allows calculation of derived optical properties like mass extinction coefficients and Angstrom coefficients. Real aerosol in the atmosphere always is a mixture of different components. Thus, in OPAC it is made possible to get optical properties of any mixtures of the basic components and to calculate optical depths on the base of exponential aerosol height profiles. Typical mixtures of aerosol components as well as typical height profiles are proposed as default values; but mixtures and profiles for the description of individual cases may also simply be achieved. http://www.lrz- muenchen.de/~uh234an/www/radaer/opac.html 16/34

EXAMPLES OF AEROSOL SIZE DISTRIBUTION MODELS IN TYPICAL ENVIRONMENTS Aerosol Mode N i (cm -3 ) R i (µm) log σ i Polar 1 2.17 10 1 0.0689 0.245 2 1.86 10-1 0.375 0.300 3 3.04 10-4 4.29 0.291 Maritime 1 1.33 10 2 0.0039 0.657 2 6.66 10 1 0.133 0.210 3 3.06 10 0 0.29 0.386 Remote continental 1 3.20 10 3 0.01 0.161 2 2.90 10 3 0.058 0.217 3 3.00 10-1 0.9 0.380 Rural 1 6.65 10 3 0.00739 0.225 2 1.47 10 2 0.0269 0.557 3 1.99 10 3 0.0419 0.266 Urban 1 9.93 10 4 0.00651 0.245 2 1.11 10 3 0.00714 0.666 3 3.64 10 4 0.0248 0.337 (Jaenicke, 1993) 17/34

REFRACTIVE INDEX OF BASIC AEROSOL MODELS Real part Imaginary part Mineral dust Sea salt Fly ash Water soluble Wavelength (µm) Wavelength (µm) (from Hess et al., 1998) 18/34

AEROSOL MEASUREMENTS METHODS REMOTE SENSING (see other presentations) Based on light-particles interaction Passive (column integrated) or active (profiling possible) Optical properties (extinction, scattering) and related parameters (e.g. size distribution, refractive index) Ground-based, airborne or space borne AEROSOL COLLECTION On a substrate (e.g. filter) or in suspension (real-time analysis) Possible size segregation based on aerodynamic inertia PM10, PM2.5, PM1, cascade impactor Principle of the cascade impactor: - air is accelerated through smaller and smaller holes: particles too heavy to follow air stream impact on the filter - each impaction stage is characterized by its 50%- efficiency cut- of diameter pump air impaction stages total filter 19/34

AEROSOL COLLECTION: LOSS PROBLEMS Particle losses due to various processes Sedimentation, diffusion, turbulence, impaction, static electricity, Non-isokinetic sampling Possible bias in particle concentrations if sampling air flow (Q) is not equalled to ambient air flow (Q o ) Critical for airborne collection of aerosols Isokinetic sampling Q=Q o Q < Q o : enrichment in large particles Inlet Q > Q o : loss of large particles 20/34

AEROSOL GRAVIMETRIC ANALYSES Automatic on-line methods β attenuation gauge oscillating quartz microbalance Off-line with a precision balance pre-weighted substrates (total mass) or burning residue (ashes) needs controlled T and low relative humidity, static electricity control Problem of water uptake of filters and particles at 50% relative humidity, the common ammonium sulphate secondary particles (NH 4 ) 2 SO 4 grow by 20% in size and contains 30% of water 21/34

Bulk methods for elements Ions tracers of particle types (e.g. Al for mineral dust, Na for sea salt, S for sulphates, etc) atomic absorption spectrophotometry (AAS), instrumental neutron activation analysis (INAA), X- ray fluorescence (XRF), proton induced X- ray emission spectrometry (PIXE), inductively coupled plasma with atomic emission spectroscopy (ICP- AES), ionic chromatography (IC), capillary electrophoresis, colorimetry Scanning and transmission electron microscopy (SEM and TEM) + X energy dispersion microsonde AEROSOL CHEMICAL MEASUREMENTS requires coating (carbon, gold) of the sample limited sub- samples are analysed possible visualization and analysis of individual particles On line single particles analysis and sizing system (SPASS) time of flight mass spectrometry with laser ablation of particles (>0.2 µm) promising (10 particles per s) but not yet common 22/34

THE CASE OF CARBON MEASUREMENTS Total carbon is analysed by combustion in the laboratory Soot carbon The most light absorbing aerosol component On line optical method based on light absorption through the filter (aethalometer) Problems of calibration Organic carbon Most of the mass or carbonaceous aerosols is not identified Thermal separation methods from soot based on its refractory character Chromatographic separation for the speciation of organics 23/34

Optical particle counters are based on particle-light interactions D > 0.1 µm PARTICLE COUNTERS Condensation particle counter (CPC) Small particles are grown in a saturated vapour before counting: http://www.tsi.com/particle/ 24/34

Optical methods (OPC, PCASP, FSSP, ) Diffusion and diffraction at various angles of light from an internal source Adapted to airborne measurements D > 0.1 µm Aerodynamic particle sizer (APS) PARTICLE SIZERS Time of flight between 2 laser beams D > 0.5 µm Differential electric mobility analyser (DMA), scanning mobility particle sizer (SMPS) Artificially charged particles in an electric field 1 µm > D > 0.01 µm Particles are charged with a radioactive source and their Diffusion battery Particle classification by their penetration through fine- mesh screens of increasing mesh 0.2 µm > D > 0.002 µm 25/34

VOLATILITY AND HYGROSCOPICITY Special applications of DMA Volatility Comparison between size distribution at ambient and warmer temperatures Provides the volatile fraction as a function of particle size Hygroscopicity Comparison between size distribution in dry condition and at high relative humidity Quick measurement of the dependence of the size distribution with relative humidity 26/34

Scattering measurements NEPHELOMETERS Integrates total and backscattering measurements Corrections for angles close to incidence and backscattering may be necessary TSI 3-wavelengths integrating nephelometer, http://www.tsi.com/particle/ 27/34

IN SITU SIZE DISTRIBUTION MEASUREMENTS: INDOEX EXAMPLE OF MEASUREMENTS Cascade impactor: size segregated collection for chemical analyses (e.g. X- florescence, ionic chromatography, ) ray Air is accelerated through smaller and smaller holes: particles too heavy to follow air stream impact on the filter Cut- off diameters: 8.75, 3.90, 1.95, 1.25, et 0.65 µm + total filter pump air impaction stages total filter MASS AND NUMBER DISTRIBUTIONS Optical sizer 6 classes : 0.3-0.5, 0.5-0.7, 0.7-1.0, 1.0-2.0, 2.0-5.0, >5.0 µm Condensation nuclei counter with optical detection total number between 7 nm and 3 µm Diffusion battery 12 classes from 15 to 200 nm Integrating nephelometer aerosol scattering at blue, green and red λ 28/34

RETRIEVED SIZE DISTRIBUTION INDOEX dn/dlogd (#/m3) 1E+11 1E+10 1E+09 1E+08 1E+07 1E+06 1E+05 1E+04 1E+03 Observations confirm the three modes 0.098 σ=1.72 0.92 σ= 1.69 0,01 0,1 1 10 100 diameter (µm) 3.95 σ= 1.97 mode1 mode2 mode3 23/3/99 17:35 23/3/99 6:56 (Alfaro et al., JGR, in press) Extinction of solar radiation is dominated by sub-micronic size particles Fine mode : 80% of extinction Intermediate mode : 15% of extinction NB : Relative humidity modifies the size distribution 29/34

Methods: COMPOSITION OF THE MODES Cascade impactors and filters + chemical analyses of particle type tracers (elements or ions) Filters + electronic microscopy New coming techniques: time of flight mass spectrometry with laser ablation Fine mode: Analysis of many individual particles Soot- carbon embedded by organic carbon and/or non sea salt sulphates (70%) Sulphates (30%) Intermediate mode: Sulphates (45%) Soot- carbon (10%) Nitrates, sea salts, mineral dusts Coarse mode: Sea salts Nitrates Dusts INDOEX 0.1 µm (Alfaro et al., JGR, in pr.) 30/34

OPTICAL CLOSURE INDOEX Comparison of computed scattering (Mie) with nephelometer measurements at Goa modeled scattering coefficients (m-1) 3.5E -04 3.0E -04 2.5E -04 2.0E -04 1.5E -04 1.0E -04 5.0E -05 0.0E+00 450 nm 700 nm 0.0E +00 5.0E-05 1.0E-04 1.5E -04 2.0E -04 2.5E -04 M easured scattering coefficients (m-1) slope 1 Validation of the aerosol model near the surface (Alfaro et al., in pr.) Single scattering albedo : 0.86 (50% r.h.) 0.93 (saturation) in agreement with AeroNet CIMEL-derived values for the column 31/34

INTERNAL MIXING Internal particle mixing complicates the situation clay feldspath black carbon 1 µm Aluminosilicate particle over the eastern Mediterranean (Formenti et al., MPIC Mainz) sulphate Microsoot from African savannah fire (Gaudichet et al., 1995) Problem of iron oxides (hematite) 32/34

INFLUENCE OF MIXING ON OPTICAL PROPERTIES The way of modelling the distribution of absorbing substances within particle mixtures modifies the aerosol optical properties Example of desert dust Comparison of the direct (clear sky) net radiative forcing at top of atmosphere accounting for the variable mineralogy of source regions, using the three different hypotheses of mixing +0.15 W m -2 +0.15 W m -2-0.06 W m -2 NO INTERNAL EXTERNAL MIXING MIXING MIXING 1 tracer 6 tracers 6 tracers No mixing ω o 0.91 0.99 0.94 ω o = k diff / k ext : globally av. single scattering albedo -0. 64 W m -2 Internal mixing External mixing (Claquin, LSCE, PhD thesis; Claquin et al., Tellus, 1998) 33/34

CONCLUSION Due to a great variety of natural and man-made sources, aerosol particles are highly variable in concentration, size, shape, composition, optical properties, both in time and space. Their full characterization requires many different techniques, a number of which are not fully automated and requires careful calibration. Measurements may be limited according to the parameters of interest but closure studies with independent, but redundant measurements are recommended due to measurements and collection artefacts, especially when optical properties are sought. For standard applications and first estimates, aerosols models may be convenient and can be found on internet. 34/34