physical chemistry chemical physics - nccr must · 2014. 7. 3. · j. kasparian and j.-p. wolf*...

ISSN 1463-9076

Physical Chemistry Chemical Physics

www.rsc.org/pccp Volume 14 | Number 26 | 14 July 2012 | Pages 9237–9522

Includes a collection of articles on the theme of structure and reactivity of small particles

1463-9076(2012)14:26;1-Q

COVER ARTICLEKasparian and Wolf Ultrafast laser spectroscopy and control of atmospheric aerosols

Publ

ishe

d on

12

Dec

embe

r 20

11. D

ownl

oade

d by

ET

H-Z

uric

h on

03/

07/2

014

13:4

3:22

. View Article Online / Journal Homepage / Table of Contents for this issue

http://dx.doi.org/10.1039/c2cp23576ehttp://pubs.rsc.org/en/journals/journal/CPhttp://pubs.rsc.org/en/journals/journal/CP?issueid=CP014026

This journal is c the Owner Societies 2012 Phys. Chem. Chem. Phys., 2012, 14, 9291–9300 9291

Cite this: Phys. Chem. Chem. Phys., 2012, 14, 9291–9300

Ultrafast laser spectroscopy and control of atmospheric aerosols

J. Kasparian and J.-P. Wolf*

Received 14th November 2011, Accepted 12th December 2011

DOI: 10.1039/c2cp23576e

We review applications of ultrafast laser pulses for aerosol analysis via linear and non-linear

spectroscopy, including the most advanced techniques like coherent control of molecular excited

states. We also discuss the capability of such pulses to influence the nucleation of atmospheric

aerosols by assisting condensation of water in air.

1. Introduction

Aerosols play a key role in the atmosphere. Their impact on

public health as pollutants and their activity in climate change

and heterogeneous chemistry are well recognized. For instance

their influence on the radiative balance of the Earth, both

direct and indirect (via the condensation of cloud droplets), is

known as the largest uncertainty in the climate change

predictions by the IPCC.1 Their photochemical activity has been,

on the other hand, widely highlighted by the discovery of their

catalytic role in the stratospheric ozone destruction, which led to

the Nobel Prize for P. Crutzen, M. Molina, and F. Rowland in

1995.2 Further impacts are obviously linked to air pollution

especially in urban areas and the related health issues.

Although the central role of atmospheric aerosols is

unanimously acknowledged, their properties are still insuffi-

ciently characterized. Important efforts have been recently

dedicated to address major issues, such as nanoparticles

nucleation from the molecular gas phase,3 particle activation

leading to cloud condensation nuclei (CCN) and precipita-

tion,4 unknown optical properties (scattering, extinction) in

mixed phases (aerosols embedded or dissolved in water)5 and

unexpected abundance of biological aerosols (cellular material

and proteins).6 The exciting field of research dealing with the

physical and chemical properties of aerosols will therefore

certainly rapidly grow in the next years.

Non-linear spectroscopy appears as a very attractive novel

method for characterizing aerosol particles. Considerable

work was dedicated to the special case of spherical micro-

droplets, as they support high quality cavity modes called

‘‘Whispering Gallery Modes’’ (WGM)7 by analogy to acoustic

WGM in circular buildings. These resonances locally enhance

the electric field and allow for non-linear interactions, such as

Stimulated Raman Scattering (SRS) and Coherent Anti-

Stokes Raman Scattering (CARS), even at low incident

powers.8,9 Although extensively studied since the mid-1980s

in microdroplets,10–12 SRS and CARS proved only recently

their capabilities for analyzing atmospherically relevant

aerosol particles, especially in combination with levitating

and trapping techniques.13–18 In most of these studies, cavity

enhanced Raman scattering (CERS) is used to measure the

composition of single aerosol particles, which can hardly be

addressed by recording only the Mie scattering pattern and

extinction. Accommodation, composition and chemical

reactions can be followed in real time on a single particle,

contrary to other techniques that are limited by the need to

average over a large ensemble of particles.

The advent of ultrashort pulse lasers widely extended the

palette of non-linear spectroscopic techniques, including multi-

photon excited fluorescence (MPEF), harmonics generation,

supercontinuum emission, and Laser Induced Breakdown

Spectroscopy (LIBS). Some representative examples of these

processes induced in aerosol particles are reviewed in Section 2.

However, the main use of lasers in atmospheric aerosols

research regards remote sensing, especially using the Lidar

(Light Detection and Ranging) technique.19,20 Similar to a

laser radar, the backscattered light from a pulsed laser is

detected as the pulse propagates in the atmosphere. Light is

Rayleigh- and Mie-scattered from the air molecules and

aerosols, respectively, so that average backscatter b andextinction a coefficients are recorded as a function of the timeof flight, i.e., the distance. Both yield information about the

amount and the location of aerosol particles, cloud droplets,GAP-Biophotonics, University of Geneva, Chemin de Pinchat 22,1211 Genève 4, Switzerland. E-mail: [email protected]

Jérôme Kasparian is a Research scientist at the University ofGeneva. He is responsible for the studies on the filamentation ofultrashort laser pulses and its atmospheric applications likelightning control and laser-induced condensation, in particularwithin the Teramobile project which he is leading.

Jean-Pierre Wolf is a Professor of physics at the University ofGeneva, head of the Group of Applied Physics—Biophotonicsgroup. He is a specialist in ultrafast physics, including coherentcontrol, laser filamentation, and atmospheric remote sensing andcontrol. He is the recipient of an Advanced Grant of theEuropean Research Council.

PCCP Dynamic Article Links

www.rsc.org/pccp PERSPECTIVE

Publ

ishe

d on

12

Dec

embe

r 20

11. D

ownl

oade

d by

ET

H-Z

uric

h on

03/

07/2

014

13:4

3:22

. View Article Online

http://dx.doi.org/10.1039/c2cp23576ehttp://dx.doi.org/10.1039/c2cp23576ehttp://dx.doi.org/10.1039/c2cp23576e

9292 Phys. Chem. Chem. Phys., 2012, 14, 9291–9300 This journal is c the Owner Societies 2012

ice crystals, volcanic ashes, etc. Backscatter Lidars have been

extensively used for about 50 years now, since the pioneering

work of G. Fiocco and L.D. Smullin in 1963.21 While b and a canbe retrieved relatively easily using inversion algorithms,22 they do

not directly provide information about the size distribution of the

particles, their quantitative concentration, and their composition.

In Section 3, we will highlight new possibilities opened by

ultrashort and intense lasers towards this goal. In particular,

intense laser beams propagate non-linearly in the atmosphere and

generate ‘‘filaments’’ of light,23–27 bearing a typical intensity of

5 � 1013 W cm�2.28,29 They generate plasma strings featuringelectron densities of 1015–1016 cm�3 and a supercontinuum of

light that spans from the UV30 to the IR31 (230 nm to 14 mm).This supercontinuum can thus be used for providing the range-

resolved spectral dependence of b and a, and therefore informationabout the size and the concentration of the aerosol particles.

Additionally, MPEF and coherent control schemes are remarkable

femtosecond spectroscopy tools for addressing the composition, as

demonstrated in the case of bioaerosol simulants.32

Beyond observing the atmosphere, filaments induced by high

power lasers might even allow locally controlling it. More

precisely, the ionized filament strings are electrically conductive

so that they trigger and guide high-voltage discharges over several

metres.33–38 Filament-induced corona discharges inside real

thunderclouds were even demonstrated recently,39 which open

new perspectives for real scale lightning control. More related to

the context of aerosol and clouds, filaments induce nucleation of

nanometric particles and micrometric water droplets in the

atmosphere,40,41 which might have a tremendous impact on

geo-engineering in the future. Aerosol nucleation and water

condensation induced by high intensity lasers are the subject of

Section 4.

2. Femtosecond spectroscopy of aerosol particles

2.1. Harmonics generation

The most straightforward non-linear optical effect is harmonic

generation.42 Due to inversion symmetry, the even harmonics

are forbidden in water droplets, so that the first strong

harmonic induced by a high-intensity laser is the third one.

By illuminating individual droplets of typical radius a = 20 um

with a 80 fs laser pulse providing an intensity of 2–5 �1011 W cm�2 at 800 nm, third harmonic generation (THG) could

be observed as a function of the scattering angle, as shown in

Fig. 1(d).43 Fair agreement was found between the experiments

and non-linear Mie scattering theories.44 In addition to the

strong forward emission, a secondary maximum close to

y = 261 with respect to the laser axis appeared remarkablystable over a broad range of size parameters 60 o x o 300(x = 2pa/l).43,45 Raman coupling with THG was also reportedin microdroplets for longer pulse durations and narrow-band

illumination.46,47

As mentioned above, second order processes such as second

harmonic generation (SHG) or sum frequency generation

(SFG) are symmetry-forbidden in the bulk. They can,

however, occur on the droplet surface because of inversion

symmetry breaking. Fig. 1(b) and (c) display the observation

of both SHG48 and SFG processes in water droplets, when

the incident intensity is increased to 1–5 � 1012 W cm�2.

Again, the emission is strongly directive and exhibits distinctive

lobes, at y = 181 for SHG and y = 321 for SFG (800 nm +400 nm - 266 nm). It is also strongly polarized, as shown in

Fig. 1(b) for SHG. The emission lobes can be fairly well

interpreted by the extended Rayleigh–Debye–Gans theory49,50

although other models have been developed with the same

objective, such as nonlinear Wentzel–Kramer–Brillouin theory

(NLWKB)50 and nonlinear Mie scattering theory (NLM).51,52

But these theories do not explain the intense SHG emission

of up to 2.5 � 103 photons per droplet and per pulse observedfor I = 2 � 1012 W cm�2. Reproducing this conversionefficiency required to consider an additional process, namely

SHG induced by a DC field F through the third orderpolarizability tensor w(3):

~Pð2oÞ ¼ w3~EðoÞ~EðoÞf ð1Þ

The water droplets used in the experiment, which were generated

by a piezoelectric nozzle, indeed turned out to be electrically

charged by up to 1 pC, which could lead to a sufficient DC field

for enhancing second harmonic generation. Although still

debated,53 this process would allow measuring the electric charge

of water droplets, even remotely in the atmosphere by Lidar.

This would allow for the first remote measurements of electric

fields within clouds, especially in thunderclouds. This measure-

ment is otherwise difficult to perform in situ, both because of

practical reasons and because of the strong local influence on the

particle charge of any device inserted close to the particles.

2.2. Incoherent multiphoton processes: MPEF and

multiphoton ionization (MPI)

The most prominent feature of incoherent nonlinear processes

in aerosol particles using femtosecond lasers is a strong

localization of the emitting molecules within the particle,

and a subsequent backward enhancement of the emitted

light.54–57 This previously unexpected behavior is very attractive

for remote detection schemes, such as Lidar applications,32 since

it implies that light is emitted preferentially towards the light

source, where the detection system is also located.

Fig. 1 Harmonics generation in water droplets of 20 mm typical radius,induced by femtosecond laser pulses at 800 nm. (a) Experimental

arrangement. A droplet generator is synchronized with a femtosecond

laser so that each droplet is illuminated by a single laser pulse (b) SHG:

800 nm- 400 nm, (c) SFG: 400 nm+ 800 nm- 266 nm, and (d) THG:

800 nm - 266 nm (Fig. 1(d) from ref. 45).

Publ

ishe

d on

12

Dec

embe

r 20

11. D

ownl

oade

d by

ET

H-Z

uric

h on

03/

07/2

014

13:4

3:22


http://dx.doi.org/10.1039/c2cp23576e


We investigated, both theoretically and experimentally,

incoherent multiphoton processes involving k = 1 to 5

photons. 1-, 2-, and 3-PEF occur in bioaerosols because of

natural fluorophores such as amino acids (tryptophan,

tyrosine), nicotinamide adenine dinucleotide (NADH), and

flavins. The strongly anisotropic MPEF emission was demon-

strated on individual microdroplets containing tryptophan,

riboflavin, or other synthetic fluorophores (such as Coumarin

dyes). Fig. 2(c)–(e) shows the angular distribution of the

MPEF emission and the comparison between experimental

and theoretical (Lorenz–Mie calculations) results for the one-

(400 nm) (upper), two- (800 nm) (center) and three-photon

(1.2 mm) (lower) excitation process. They show that fluores-cence emission is maximum in the direction toward the exciting

source. The directionality increases with k, because the excitation

process involves the k-th power of the intensity Ik(r). The ratio of

light powers at 1801 and 901, Rf = P(1801)/P(901), increasesfrom 1.8 to 9 when k rises from 1 to 3. 3-PEF from aerosol

microparticles is therefore emitted mainly backwards, which is

ideal for Lidar experiments, as demonstrated in the field using the

Teramobile system.24,32

The backward enhancement of multiphoton processes can

be explained by the reciprocity (or ‘‘time reversal’’) principle:

re-emission from regions with high Ik(r) (where r stands for the

position inside the particle) tends to return toward the

illuminating source by essentially retracing the direction of

the incident beam that gave rise to the high-intensity hot spots.

These spots are induced by non-linear processes, which typically

involve the k-th power of the internal intensity Ik(r) (Fig. 2), and

therefore tend to be efficient only in the fraction of the particle

volume where the intensity is highest.

Very recently, we applied MPEF spectroscopy to real

atmospheric aerosols, namely airborne pollens. For this,

ambient air was sucked and focused with a sheath nozzle in

a narrow stream, where 2 diode lasers detected the presence of

individual particles and triggered the femtosecond laser

inducing simultaneously two- and three-photon excited fluores-

cence. The fluorescence of each individual pollen particle was

analysed by a spectrometer and a 32-channel photomultiplier

tube. For reference, clusters of dye-doped 1 mm PSL spheres(FB 345) exhibit fluorescence spectra at around 345 nm.58

The spectra (Fig. 3) clearly display the differences between the

pollens, which could be used for identification. The MPEF

emission maximum shifts from 440 nm (Ragweed, Fig. 3(b)) to

490 nm (Mulberry, Fig. 3(d)) with Pecan in between (470 nm,

Fig. 3(c)). The shapes of the spectra also differ. For instance

Pecan and Ragweed exhibit significant fluorescence around

380–400 nm, which clearly originates from a 3-PEF contribution.

Conversely, Mulberry emits only a weak fluorescence in this

region. These observations are in agreement with recent results

obtained with dual nanosecond laser excitation of fluorescence.59

k = 5 corresponds to laser induced breakdown (LIB) in

water microdroplets, initiated by multiphoton ionization

(MPI). The ionization potential of water molecules is 6.5 eV,

so that 5 photons are required at a laser wavelength of 800 nm

to initiate plasma formation. Both localization and backward

enhancement further increased as compared to lower orders,

reaching Rf = 35 for k = 5.56 Similarly to MPEF, LIBS has

the potential of providing information about the aerosols

composition, as was demonstrated for bacteria and other

bioaerosols. Experiments using femtosecond laser pulses

recently showed that, due to a lower thermal background,

some atomic and molecular (C–C, C–N) lines could be

extracted from the LIBS emission from different bacteria.60–62

A principal component analysis demonstrated that classes of

bacteria can be discriminated, as for instance gram+ versus

gram� types. The recent demonstration of remote LIBS basedon laser filamentation (R-FIBS or Remote Filament-Induced

Breakdown Spectroscopy) opens the perspective to transpose

these approaches to stand-off, or even remote detection.63

2.3. Pump–probe and coherent control in bioaerosols

The optical detection and identification of bioaerosols suffer

from the overlap between the absorption and fluorescence

Fig. 2 Backward-enhanced MPEF from spherical microparticles.54

(a,b): Molecular excitation within droplets, proportional to Ik(r) with

k = 1 (a) and 3 (b). (c–e): Angular distribution of MPEF emission for

1, 2 and 3 photon excitation (reprinted from ref. 54, copyright 2000 by

the American Physical Society).

Fig. 3 Single-shot MPEF spectra of individual aerosol particles.

(a) Dye-doped polystyrene spheres (FB345), (b) Ragweed pollen, (c)

Pecan pollen, and (d) mulberry pollen (from ref. 58).

Publ

ishe

d on

12

Dec

embe

r 20

11. D

ownl

oade

d by

ET

H-Z

uric

h on

03/

07/2

014

13:4

3:22




spectra of their amino acids and that of polycyclic aromatic

hydrocarbons (PAH) originating from combustion. To over-

come this limitation, a femtosecond pump–probe depletion

(PPD) concept was developed.64 It is based on the time

dependent competition between excited state absorption

(ESA) into a higher-lying excited state on one side, and

fluorescence into the ground state on the other side. By

varying the temporal delay between a pump and a probe

pulse, the dynamics of the internal energy redistribution within

the intermediate excited state’s potential surface is explored.

Different species offering distinct excited state potential

surfaces can therefore be discriminated. PPD was first success-

fully used to distinguish molecules such as tryptophan and

naphthalene, which are among the most fluorescing species in

bacteria and diesel fuel, respectively. At a given time delay

(2 ps) tryptophan fluorescence was depleted by 50% by

the probe laser, while that of diesel fuel remained almost

unaffected. Two reasons might be invoked to understand this

difference: (1) the intermediate state dynamics of tryptophan is

predominantly governed by the NH– and CO– groups of the

amino acid backbone and (2) the ionization potential is higher

for polycyclic aromatic hydrocarbons (PAH), so that further

excitation induced by the probe laser is much less likely in the

organic compounds. Similar results have been obtained for

live bacteria, including Escherichia coli, Enterococcus and

Bacillus subtilis, which could be distinguished from diesel fuel

(Fig. 4).65,66 This achievement can be exploited for a novel

selective bioaerosol detection technique that avoids interfer-

ence from background traffic-related organic particles in the

air: the excitation shall consist of a pump–probe sequence and

the fluorescence emitted by the mixture will be measured as the

probe laser is alternately switched on and off. This pump–

probe differential fluorescence measurement will be especially

attractive for active remote detection (e.g., MPEF-based

Lidar, see Section 3.3), where the lack of discrimination

between bioaerosols and traffic-related organics is currently

most acute.

While PPD can discriminate biological from other organic

aerosols, it turned out to be unable to discriminate among

different bacteria, which express the same depletion dynamics

because their constituent molecules are mostly identical. For

this reason, a significant effort is dedicated to more sophisti-

cated techniques using optimally shaped pump pulses in PPD.

Together with the group of H. Rabitz in Princeton, we

developed a novel approach, called optimal dynamic discrimi-

nation (ODD), which allowed us to discriminate between two

structurally similar molecules in aqueous-phase: flavin mono-

nucleotide (FMN) and riboflavin (RBF). Due to their very

similar structure, these two molecules have nearly identical

static spectroscopic properties throughout the entire visible

and far UV, including the region of the pump-pulse

wavelength at 400 nm: The flavins’ electronic spectroscopy

is primarily associated with their common chromophore

(p - p* type transitions localized on the isoalloxazine ring).The chemical moieties (H vs. PO(OH)2) on the terminal side

chains influence it only indirectly, and very slightly.

Although the laser resources exploited for discriminating

the two flavins consisted of a modest B3.5 nm of UVbandwidth andB10 nm of IR bandwidth, dramatic selectivitywas achieved by shaping near-UV pump pulses. The optimal

near-UV pulse shape was determined by closed-loop optimi-

zation on the fluorescence depletion ratio dFMN(Dt)/dRBF(Dt)for a fixed delay Dt (B500 fs). Whereas the static spectraappear nearly identical, subtle differences exploited by control

are nonetheless profound and allow a discrimination of the

flavins by 12 standard deviations.67 Moreover, the subtle

differences in the excited state dynamics could be theoretically

understood by FISH (Field Induced Surface Hopping) calcu-

lations performed by V. Bonacic-Koutecky in Berlin.68 ODD

has therefore the potential capability of distinguishing

complex peptides and proteins, which could lead to the

discrimination between different classes of bacteria in air in

the future.

3. Filamentation and non-linear Lidar detection ofaerosols

3.1. Multispectral Lidar

The Lidar technique has proved useful for 3D-mappings of air

pollutants, such as NO, NO2, SO2, Ozone and aerosols.19,20,69

Such mappings allow validating complex numerical models of

air pollution, offering a substantial added value as compared

with measurements based on local sampling, the results of

which critically depend on their location.70,71 However, for

aerosols, Lidar data are often limited to single wavelength

backscattering profiles. Such profiles, although relevant

for climatic models and meteorology (measurement of the

planetary boundary layer, height of cloud layers, extinction

coefficients etc.), bear no information about the size distribution

of the particles, and their composition.

The most advanced methods for aerosol detection by Lidar

use several (typically 2–5) standard lasers (Nd :Yag, Ti : Sapphire,

Excimers,. . .), each operating at a fixed wavelength.72–76 The set

of Lidar equations derived from the multiwavelength Lidar data

is subsequently inverted using dedicated algorithms and/or multi-

parametric fits of pre-defined size distributions with a priori

assumptions about the size range and complex refractive indices

Fig. 4 PPD spectroscopy of 20 mm radius droplets containing about100 E. coli bacteria, simulating pathogens vectored by saliva drops

(from ref. 66). Wavelengths of the femtosecond pump- and probe-

pulses are 266 nm and 800 nm respectively.

Publ

ishe

d on

12

Dec

embe

r 20

11. D

ownl

oade

d by

ET

H-Z

uric

h on

03/

07/2

014

13:4

3:22




of the particles. These data allowed, for instance, measuring the

characteristics (size distribution, presence of sulfuric and nitric

acids) of Polar Stratospheric Clouds (PSC)77 and volcanic ashes

(Pinatubo eruption)78 in the Arctic Circle, which helped assessing

their role in stratospheric ozone depletion. More recently, the

eruption of the Eyjafjallajoumlkull volcano induced a very large

amount of activity in the Lidar community for characterizing the

spread and the properties of the ash plume.79

In order to obtain quantitative mappings of aerosols,

complementary local data (obtained with, e.g., particle counters,

or multi-stage impactors to identify the sizes and composition)

are often used together with the Lidar measurements. This is

especially the case of urban aerosols, because their variety in size

and composition does not allow simple a priori assumptions.80

The determination of the size distribution and composition using

standard methods must, however, be taken cautiously as addi-

tional data, because of their high spatial and temporal variability.

3.2. Laser filamentation, supercontinuum, and white light

Lidar

Laser filaments25–28 have been proposed as an option to

increase the information yield of Lidar. They are self-sustained

light structures of typically 100 mm in diameter and up tohundreds of metres in length, widely extending the traditional

linear diffraction limit. They can be generated at kilometre-

range distances,81 leaving strings of weakly ionized plasma

(1015–1016 cm�3) behind them. Furthermore, they can propa-

gate through adverse conditions like turbulent air82 or fog.83,84

Their formation stems from a dynamic balance between

Kerr self-focusing and defocusing by higher-order negative

Kerr components85,86 and/or plasma formation.87

More precisely, at high intensity I, the refractive index n of

the air is modified by the Kerr effect:42 n(I) = n0 + n2I, where

n2 is the non-linear refractive index corresponding to third-

order non-linearity (n2 = 1.2 � 10�19 cm2 W�1 in air88). TheKerr effect becomes significant when self-focusing is larger

than natural diffraction, i.e. above a critical power Pcrit(typically 8 GW in air at 800 nm). As the intensity in a

cross-section of the beam is not uniform, the refractive index

increases more in the center of the beam than on its edge. This

induces a radial refractive index gradient equivalent to a

converging lens, or ‘‘Kerr lens’’. Its focal length decreases

with increasing intensity, so that it could be expected to

collapse. However, as the laser pulse intensity reaches

1013–1014 W cm�2, higher order non-linear processes, such

as negative higher order Kerr effect terms (HOKE) or multi-

photon ionization (MPI), occur. These processes act as a

negative lens that counterbalances self-focusing, leading to

stable propagation of quasi-solitonic structures: the filaments,

with a typical equilibrium intensity clamped around 5 �1013 W cm�2.28,29

The non-linear propagation of high intensity laser pulses

does not only provide self-guiding of the light, but also

generates an extraordinarily broad continuum (Fig. 5) spanning

from the UV30 to the IR31 (230 nm–14 mm). This supercontinuumis generated by self-phase modulation (SPM) along the pulse

propagation of the high intensity pulses. SPM is the temporal

counterpart of the Kerr effect, resulting in a time-dependent phase

shift Df (t) = �n2I(t)o0z/c, where o0 is the carrier frequency, z isthe distance of propagation, and c is the speed of light. This phase

shift in turn generates new frequencieso=o0 + dDf/dt=o0�n2o0z dI(t)/cdt.

42,89,90 The fast variation of temporal envelope of

the pulse thus induces a strong spectral broadening around o0.The white-light continuum provides a coherent broadband

light source with a continuous spectrum, particularly suitable for

multispectral aerosol detection. Galvez et al. successfully used the

supercontinuum generated in rare gas and transmitted into the

atmosphere to perform multi-wavelength Lidar and characterize

aerosols.92–94 Since the continuum has the same polarization as

the incident laser pulse, depolarization measurements are also

possible, allowing to characterize the deviations of the particles

from a spherical shape, e.g., to identify ice crystals.

An attractive alternative is to produce the supercontinuum

directly in the atmosphere, as the high intensity laser propagates.

It is especially advantageous as the filament emission is partially

backward-emitted95 and is thus favorable to Lidar experiments.

Filament-based Lidar was first demonstrated for gaseous species

in the atmosphere24,96,97 with the first mobile fs-TW laser,

Teramobile.98 In particular, water vapor and temperature profiles

(through the ground state’s vibrational population of water

vapor and molecular oxygen) were measured simultaneously,

giving rise to a direct relative humidity (RH) profiling capability.

The supercontinuum generated directly by the filaments in the

atmosphere was even used for measuring the aerosols size

distribution and concentration,97 for which it appears as an

optimal multispectral source. While the spectral analysis of such

measurements is, in principle, an extension of the existing multi-

wavelength algorithms, the presence of the filaments at a given

altitude and the use of temporal focusing require, however, to

update the Lidar equation to a non-linear Lidar version and its

related inversion algorithms.18,99

3.3. Application to bioaerosol detection and identification

The remote detection and identification of bioaerosol with a

femtosecond MPEF-Lidar was first demonstrated100 as early

Fig. 5 White-light supercontinuum from hundreds of filaments,

generated by 30 fs, 1.65 J pulse after 15 m propagation, imaged on a

screen.91

Publ

ishe

d on

12

Dec

embe

r 20

11. D

ownl

oade

d by

ET

H-Z

uric

h on

03/

07/2

014

13:4

3:22




as in 2004 using the Teramobile system98 (Fig. 6). Micro-

droplets of 1 mm containing riboflavin were used as simulantsof airborne bacteria or other bioagents. A plume of 104

particles cm�3 was spread at a distance of 45 m from the

Teramobile. Riboflavin was excited with two photons at

800 nm and emitted a broad fluorescence around 540 nm.

MPEF might be advantageous as compared to linear laser-

induced fluorescence (LIF) for the following reasons: (1)

MPEF is enhanced in the backward direction (see Section

2.2) and (2) atmospheric transmission is much higher for

longer wavelengths due to the dependence of Rayleigh scattering

with the fourth power of the frequency. For example, if we

consider the detection of tryptophan (which can be excited with

3 photons of 810 nm), the transmission of a clear atmosphere is

typically 200 times higher at 810 nm than at 270 nm, although the

exact factor depends on the background ozone concentration.

Simulations show that beyond a few kilometres, the non-linear

fluorescence signal would be stronger than its linear counterpart.

Furthermore, the use of MPEF opens the way to pump–probe or

coherent control techniques, as described above, to measure both

the composition and size.

Significant progress has also been recently achieved for

detecting bioaerosols using Raman spectroscopy with femto-

second lasers.101 Coherent Anti-Stokes Raman Scattering

(CARS) is much more sensitive than spontaneous Raman,

and is therefore widely preferred for practical applications that

address small ensembles of bioparticles. A major drawback of

the CARS detection of bacteria in air or in solution is,

however, parasitic non-resonant four wave mixing (FWM)

occurring in other species than the target molecules. Due to

the abundance of these other species, this parasitic back-

ground often covers the vibrational signatures of the molecules

of interest. Another limitation is fluorescence of the target

molecules, in case of resonant Raman scattering. The combi-

nation of coherent control schemes and Raman spectroscopy

recently opened exciting perspectives to overcome these

problems.102–104 They rely on the preparation of a coherent

superposition of vibrational levels in the ground state using

stimulated Raman scattering. Then, this superposition of

levels is used in a CARS scheme. In particular, the group of

M. O. Scully reported promising CARS methods, referred to

as FAST-CARS105 and hybrid CARS106 in order to extract the

Raman lines of bacterial spores from the background noise.

The use of femtosecond Raman schemes for the remote

detection and identification of aerosols in the atmosphere

was initially proposed by Kasparian and Wolf.107 The method

is based on a pump–probe SRS technique involving the

ballistic propagation of femtosecond pulses within the particles

(e.g., water droplets)108 in order to remotely determine both the

size and the composition of aerosols. More recently, standoff

detection using CARS-Lidar was demonstrated by different

groups, but on solid targets.109–111

4. Controlling the atmosphere: laser-inducedcondensation

Recent attempts aimed at using ultrashort laser pulses not only

to remotely sense the atmospheric aerosols, but also to directly

influence their formation and growth. Today, such influence is

sought via the seeding of clouds by particles of carbonic ice,

AgI, or salts,112–114 with high running costs, controversial

results and still open questions about the innocuity of the

compounds spread if they were to be used on a large scale.

Conversely, lasers could allow continuous operation, precise

aiming of the most favourable atmospheric volume to be

activated, and avoid spreading of chemicals.

Laser-induced condensation (LIC) of water was first observed

in air saturated with water vapour, i.e., at relative humidity (RH)

above 100%.24 This spectacular effect was even visible with the

naked eye,115 as displayed in Fig. 7(a).

This effect was attributed to the Thomson mechanism for

charge-induced particle formation,116,117 which is active in the

Wilson chamber:118 ionizing particles are visualized through

the trail of water droplets they nucleate and leave behind them

as they propagate through an atmosphere saturated with

humidity or with other condensable species. However, LIC

turned out to be also effective below saturation, down to 70%

RH, including in the free atmosphere.41,115 A massive increase

of the concentration of particles of both nanometre- (up to 2 �107 cm�3 in the filament volume for each laser shot) and

micrometre-size (up to 10 mm, 105 cm�3) was observed andcharacterized (Fig. 7(b)) over a wide range of temperatures

(2–36 1C) and RH (70–100%).This observation was even made remotely from a distance of

45–75 m in a pump–probe Lidar configuration (Fig. 8). It was

very surprising, since the Thomson mechanism requires highly

supersaturated air to be effective119 and therefore cannot

explain the observed effect. Extensive experiments were therefore

conducted to identify the mechanism(s) relevant to atmospheric

conditions. Concentrations of ozone and NO2 in the parts per

million (ppm)-range, typically 100 to 1000 times the background

atmospheric values, were detected in the filaments, both under

Fig. 6 Remote detection and identification of bioaerosols by an MPEF-Lidar. The femtosecond laser illuminates a plume of microparticles

containing riboflavin (RBF) 45 m away (left). The backward emitted 2-PEF, recorded as a function of distance and wavelength, exhibits the

specific riboflavin fluorescence signature for the bioaerosols (middle) but not for pure water droplets (simulating haze, right).100

Publ

ishe

d on

12

Dec

embe

r 20

11. D

ownl

oade

d by

ET

H-Z

uric

h on

03/

07/2

014

13:4

3:22




controlled laboratory conditions120 and in the atmosphere.41

They originate from atmospheric photochemistry initiated by

multiphoton excitation of the air constituents. In spite of their

spreading and dilution in the volume around the filaments, these

concentrated highly reactive species can lead to the generation of

highly hygroscopic species, especially HNO3. The latter was

indeed detected as NO3� ions in laser-induced particles sampled

in the vicinity of the laser filaments.41

The impact on particle stability and growth of HNO3 at the

concentration levels expected in or around laser filaments trace

gas has been modeled from both the thermodynamic and kinetic

points of view. This model relies on an extended variant of the

Köhler model,121 adapted to handle high HNO3 concentrations.

It shows that the dissolution of HNO3 in particles affects the

balance between the adsorption of water molecules from

the surrounding atmosphere and their evaporation, which defines

the particle growth or evaporation rates. Due to its hygroscopic

character, HNO3 prevents particles from evaporating down to

70% RH, and substantially enhances the particle growth rates

close to 100%RH. As a result, this model reproduces the particle

density measured in the experiments, its variations with tempera-

ture and humidity, the particle sizes, as well as their astonishingly

fast growth allowing them to reach several micrometres within a

few seconds.122

In spite of this capability to explain the experimental results,

the particle stabilization relying on HNO3 production cannot

be expected to be the only one active. Considering the complexity

of the physico-chemistry of the plasma generated in air by the

laser filaments, the contributions of other processes have to be

considered and evaluated. These processes include H2SO4produced originating from the laser-induced oxidation of the

background atmospheric SO2,119 charge-accelerated coagulation

of particles of sub-100 nm size, photochemistry involving excited

radicals and ions, or even the formation of water–oxygen clusters

as proposed by Byers Brown.123 The identification and quantifi-

cation of these alternative processes constitute the main challenge

ahead for the understanding of laser-induced condensation.

Besides the detailed understanding of the mechanism at play

in LIC, a key question regards the scaling up of these results to

obtain measureable effects over macroscopic volumes in the

atmosphere. Promising hints in this regard were provided by

launching high-energy and high-power pulses (3 J, 100 TW)

from the DRACO laser of Forschungszentrum Dresden-

Rossendorf into a cloud chamber. Surprisingly, the yield of

laser-induced nanometric particles was found to scale up

much faster than linearly with increasing incident laser

fluence. This increase appears to follow an exponent between

5 and 8. The corresponding 5th and 8th order processes may be

identified as the multiphoton dissociation of oxygen leading

to ozone formation and ionization of oxygen molecules,

respectively.123,124 Such non-linear scaling offers perspectives

for laser-induced condensation on macroscopic scales, and

Fig. 7 Femtosecond laser-induced condensation of water droplets in

a cloud chamber. (a) True-color image of a laser-generated cloud,

illuminated by a green laser; (b) size dependence of the background

particles and laser effect on this size distribution. Stars label sizes

where the statistical significance is at least 1�a 4 0.99.41

Fig. 8 Laser-induced condensation experiment in the atmosphere. (a) Experimental setup: the Teramobile laser (red) is fired 1 ms prior to the

LIDAR pulse (green) measuring the aerosol content of the atmosphere; (b) time-averaged relative increase of the Mie backscattering coefficient

bMie measured between 06:00 and 06:30 h with and without firing the Teramobile laser. The signal enhancement at the filaments’ height (the mostactive filamenting region at 45–75 m is greyed on the graph) is a clear indication of filament-induced condensation.115

Publ

ishe

d on

12

Dec

embe

r 20

11. D

ownl

oade

d by

ET

H-Z

uric

h on

03/

07/2

014

13:4

3:22




demonstrates the relevance of high-energy lasers for that

purpose.

Producing aerosol particles in the atmosphere does not

mean triggering precipitation. As particles grow, HNO3 gets

diluted, which prevents further condensation unless the RH

rises close to 100%. However, the laser-produced particles

may act as condensation nuclei and further condense water if

their air mass evolves to adequate atmospheric conditions, in

particular if its RH rises sufficiently. Conversely, generating a

large excess of condensation nuclei may result in their competition

for condensing the available water molecules. This competition

may prevent any of them from reaching a sufficient size to

precipitate.

LIC however does not need to produce precipitation to find

useful applications. For example, it could allow remotely

measuring atmospheric conditions like the condensability of

the atmosphere. Such measurement could be performed in a

pump–probe setup comparable to that depicted in Fig. 8. The

size distribution and density of the laser-generated aerosol

depend on the local temperature and humidity in a way that

can be precisely calibrated. The atmosphere would therefore

be characterized by sounding this aerosol with a subsequent

probe pulse, in a Lidar configuration.

Although very recent, the field of laser-induced condensation

faces great challenges, from both the fundamental and applicative

points of views. The fast growth of the community dedicated to

this topic125 illustrates the extent of these stimulating challenges.

5. Conclusion

Aerosols belong to the most fascinating constituents of the

atmosphere. They have wide implications in various fields like

meteorology, climatology, or public health and safety.

Furthermore, due to the variety of their chemical composition,

physical states, shapes, sizes, and spatial distribution, from the

local to the global scales, their characterization is a highly

multiparametric problem. Non-linear optics and spectroscopy

offers many processes for a single excitation laser, and therefore

provides a wealth of information channels, most of them with

high selectivity and/or specificity. In particular, pulse shaping

allows a fine tuning of the laser pulse shape to the excited state

surface of a specific molecule to be selectively detected, offering

unprecedented options to remotely identify pollutants or minor

constituents of atmospheric aerosols.

Even beyond these advanced detection techniques, the high

intensity and fluence conveyed by ultrashort laser pulses can

substantially affect the atmosphere, and especially the particle

formation in the air. It therefore allows us to modulate water

vapour condensation, opening the way to the local control of

aerosol particle density and sizes which might be used for

weather modulation or even geoengineering.

Acknowledgements

‘‘Ludger, when I (J.P.W.) started my PhD in your group at

the ETH Lausanne in 1984, you had a fascinating dream:

in Central and South America, very often, clouds pass over

the cultures without producing rain, while they generate

flooding on the other side of the mountains. Your dream

(and motivation for starting a Lidar project) was that, may be

one day with lasers, it could be possible to help this critical

situation. Ludger: almost there!’’

Many of the results reviewed in the present work have

involved our collaborators in the University of Lyon,

University of Geneva and the Teramobile team, which we

would like to warmly acknowledge for our continuous and

fruitful joint work. This work was supported by the Swiss

National Science Foundation (FNS) through the Grant

200021-125315 and NCCR MUST program.

References

1 Contribution ofWorking Group I to the Fourth Assessment Report of theIntergovernmental Panel on Climate Change, ed. S. Solomon, D. Qin,M. Manning, Z. Chen, M. Marquis, K. B. Averyt, M. Tignor andH. L. Miller, Cambridge University Press, Cambridge, UnitedKingdom and New York, NY, USA, 2007.

2 P. Crutzen, Angew. Chem., Int. Ed. Engl., 1996, 35, 1757–1777.3 M. Kulmala, I. Riipinen, M. Sipilä, H. E. Manninen, T. Petäjä,

H. Junninen, M. Dal Maso, G. Mordas, A. Mirme, M. Vana,A. Hirsikko, L. Laakso, R. M. Harrison, I. Hanson, C. Leung, K.E. J. Lehtinen and V.-M. Kerminen, Science, 2007, 318, 89–92.

4 D. Rosenfeld, U. Lohmann, G. B. Raga, C. D. O’Dowd,M. Kulmala, S. Fuzzi, A. Reissell and M. O. Andreae, Science,2008, 321, 1309–1313.

5 R. E. H. Miles, A. E. Carruthers and J. P. Reid, Laser PhotonicsRev., 2011, 5, 534–552.

6 R. Jaenicke, Science, 2005, 308, 73.7 Optical Processes in Microcavities, ed. R. K. Chang and

A. J. Campillo, World Scientific, Singapore, 1996, ISBN: 978-981-02-2344-1.

8 H. B. Lin, J. D. Eversole and A. J. Campillo, Opt. Lett., 1992, 17,828–830.

9 A. J. Campillo, J. D. Eversole and H. B. Lin, Phys. Rev. Lett.,1991, 67, 437–440.

10 J. B. Snow, S. X. Qian and R. K. Chang, Opt. Lett., 1985, 10,37–39.

11 S. X. Qian and R. K. Chang, Phys. Rev. Lett., 1986, 56, 926–929.12 M. H. Fields, J. Popp and R. K. Chang, Prog. Opt., 2000, 41, 1–95.13 R. Symes, R. M. Sayer and J. P. Reid, Phys. Chem. Chem. Phys.,

2004, 6, 474–487.14 L. Mitchem, J. Buajarern, R. J. Hopkins, A. D. Ward, R. J.

J. Gilham, R. L. Johnston and J. P. Reid, J. Phys. Chem. A, 2006,110, 8116–8125.

15 J. P. Reid, H. Meresman, L. Mitchem and R. Symes, Int. Rev.Phys. Chem., 2007, 26, 139–192.

16 J. Buajarern, L. Mitchem and J. P. Reid, J. Phys. Chem. A, 2007,111, 9054–9061.

17 P. M. Aker, J. X. Zhang and W. Nichols, J. Chem. Phys., 1999,110, 2202–2207.

18 J. Kasparian and J.-P. Wolf, Opt. Commun., 1998, 152, 355–360.19 R.M.Measures,Laser Remote Sensing, Fundamentals and Applications,

J. Wiley & Sons, New York, 1984, p. 510.20 C. Weitkamp, LIDAR: Range-Resolved Optical Remote Sensing

of the Atmosphere, Springer Verlag, New York, 2005.21 G. Fiocco and L. D. Smullin, Nature, 1963, 199, 1275–1276.22 J. D. Klett, Appl. Opt., 1985, 24, 1638–1643.23 A. Braun, G. Korn, X. Liu, D. Du, J. Squier and G. Mourou,

Opt. Lett., 1996, 20, 73.24 J. Kasparian, M. Rodriguez, G. Méjean, J. Yu, E. Salmon,

H. Wille, R. Bourayou, S. Frey, Y.-B. André, A. Mysyrowicz,R. Sauerbrey, J.-P. Wolf and L. Wöste, Science, 2003, 301, 61–64.

25 L. Bergé, S. Skupin, R. Nuter, J. Kasparian and J.-P. Wolf, Rep.Prog. Phys., 2007, 70, 1633–1713.

26 J. Kasparian and J.-P. Wolf, Opt. Express, 2008, 16, 466–493.27 A. Couairon and A. Mysyrowicz, Phys. Rep., 2007, 441, 47–189.28 J. Kasparian, R. Sauerbrey and S. L. Chin, Appl. Phys. B, 2000,

71, 877–879.29 A. Becker, N. Aközbek, K. Vijayalakshmi, E. Oral,

C. M. Bowden and S. L. Chin, Appl. Phys. B: Lasers Opt.,2001, 73, 287–290.

Publ

ishe

d on

12

Dec

embe

r 20

11. D

ownl

oade

d by

ET

H-Z

uric

h on

03/

07/2

014

13:4

3:22




30 G. Méjean, J. Kasparian, J. Yu, S. Frey, E. Salmon,R. Ackermann, J. P. Wolf, L. Bergé and S. Skupin, Appl. Phys.B: Lasers Opt., 2006, 82, 341–345.

31 F. Théberge, M. Châteauneuf, V. Ross, P. Mathieu andJ. Dubois, Opt. Lett., 2008, 33, 2515–2517.

32 G. Méjean, J. Kasparian, J. Yu, S. Frey, E. Salmon andJ. P. Wolf, Appl. Phys. B: Lasers Opt., 2004, 78, 535–537.

33 M. Rodriguez, R. Sauerbrey, H. Wille, L. Wöste, T. Fuji,Y. B. André, A. Mysyrowicz, L. Klingbeil, K. Rethmeier,W. Kalkner, J. Kasparian, J. Yu and J.-P. Wolf, Opt. Lett.,2002, 27, 772–775.

34 R. Ackermann, K. Stelmasczyck, P. Rohwetter, G. Méjean,E. Salmon, J. Yu, J. Kasparian, V. Bergmann, S. Schaper,B. Weise, T. Kumm, K. Rethmeier, W. Kalkner, J. P. Wolf andL. Woeste, Appl. Phys. Lett., 2004, 85, 5781–5783.

35 G. Méjean, R. Ackermann, J. Kasparian, E. Salmon, J. Yu,J. P. Wolf, V. Bergmann, S. Schaper, B. Weise, T. Kumm,K. Rethmeier and W. Kalkner, Appl. Phys. Lett., 2006,88, 021101.

36 H. Pepin, D. Comtois, F. Vidal, C. Y. Chien, A. Desparois,T. W. Johnston, J. C. Kieffer, B. La Fontaine, F. Martin, F. A.M. Rizk, C. Potvin, P. Couture, H. P. Mercure and I. Gallimberti,Phys. Plasmas, 2001, 8, 2532.

37 X. M. Zhao, J. Diels, C. Y. Wang and J. M. Elizondo, IEEE J.Quantum Electron., 1995, 31, 599.

38 B. La Fontaine, D. Comtois, C. Chien, A. Desparois, F. Genin,G. Jarry, T. Johnston, J. Kieffer, F. Martin, R. Mawassi,H. Pepin, F. A. M. Rizk, F. Vidal, C. Potvin, P. Couture andH. P. Mercure, J. Appl. Phys., 2000, 88, 610.

39 J. Kasparian, R. Ackermann, Y. B. Andre, B. Prade, G. Mechain,G. Méjean, P. Rohwetter, E. Salmon, V. Schlie, J. Yu,A. Mysyrowicz, R. Sauerbrey, L. Wöste and J.-P. Wolf, Opt.Express, 2008, 16, 5757–5763.

40 P. Rohwetter, J. Kasparian, K. Stelmaszczyk, S. Henin,N. Lascoux, W. M. Nakaema, Y. Petit, M. Queißer, R. Salamé,E. Salmon, Z. Hao, L. Wöste and J.-P. Wolf, Nat. Photonics,2010, 4, 451–456.

41 S. Henin, Y. Petit, P. Rohwetter, K. Stelmaszczyk, Z. Q. Hao,W. M. Nakaema, A. Vogel, T. Pohl, F. Schneider, J. Kasparian,K. Weber, L. Wöste and J. P. Wolf, Nat. Commun., 2011,2, 456.

42 R. W. Boyd, Nonlinear Optics, Academic Press, 1992.43 J. Kasparian, B. Krämer, J. P. Dewitz, S. Vajda, P. Rairoux,

B. Vezin, V. Boutou, T. Leisner, W. Hübner, J.-P. Wolf, L. Wösteand K. H. Bennemann, Phys. Rev. Lett., 1997, 78, 2952–2955.

44 D. Carroll and X. H. Zheng, Pure Appl. Chem., 1998, 7, L49–L55.45 W. Zimmer, Dissertation, FU-Berlin 2001, http://webdoc.sub.

gwdg.de/ebook/diss/2003/fu-berlin/2001/30/indexe.html.46 S. C. Hill, D. H. Leach and R. K. Chang, J. Opt. Soc. Am. B,

1993, 10, 16–33.47 D. H. Leach, R. K. Chang, W. P. Acker and S. C. Hill, J. Opt.

Soc. Am. B, 1993, 10, 34–45.48 V. Boutou, C. Favre, L. Wöste and J.-P. Wolf, Opt. Lett., 2005,

30, 759–761.49 N. Yang, W. E. Angerer and A. G. Yodh, Phys. Rev. Lett., 2001,

87, 103902.50 S. Roke, M. Bonn and A. V. Petukhov, Phys. Rev. B: Condens.

Matter Mater. Phys., 2004, 70, 115106.51 G. Gonella and H.-L. Dai, Phys. Rev. B: Condens. Matter Mater.

Phys., 2011, 84, 121402(R).52 J. I. Dadap, J. Shan and T. F. Heinz, J. Opt. Soc. Am. B, 2004,

21, 1328.53 P. Rohwetter, K. Stelmaszczyk, M. Queisser, M. Fechner and

L. Wöste, Opt. Commun., 2008, 281, 797–802.54 S. C. Hill, V. Boutou, J. Yu, S. Ramstein, J. P. Wolf, Y. Pan,

S. Holler and R. K. Chang, Phys. Rev. Lett., 2000, 85, 54.55 C. Favre, V. Boutou, S. C. Hill, W. Zimmer, M. Krenz,

H. Lambrecht, J. Yu, R. K. Chang, L. Wöste and J. P. Wolf,Phys. Rev. Lett., 2002, 89, 035002.

56 V. Boutou, C. Favre, S. C. Hill, Y. Pan, R. K. Chang andJ.-P. Wolf, Appl. Phys. B: Lasers Opt., 2002, 75, 145.

57 Y. Pan, S. C. Hill, J.-P. Wolf, S. Holler, R. K. Chang andJ. R. Bottiger, Appl. Opt., 2002, 41, 2994.

58 D. Kiselev, L. Bonacina and J. P. Wolf, Opt. Express, 2011,19, 24516.

59 Y. L. Pan, S. C. Hill, R. G. Pinnick, J. M. House, R. C. Flaganand R. K. Chang, Atmos. Environ., 2011, 45, 1555–1563.

60 M. Baudelet, L. Guyon, J. Yu, J.-P. Wolf, T. Amodeo,E. Fréjafon and P. Laloi, J. Appl. Phys., 2006, 99, 084701.

61 M. Baudelet, M. Bossu, J. Jovelet, J. Yu, J.-P. Wolf, T. Amodeo,E. Fréjafon and P. Laloi, Appl. Phys. Lett., 2006, 89, 163903.

62 M. Baudelet, L. Guyon, J. Yu, J.-P. Wolf, T. Amodeo,E. Fréjafon and P. Laloi, Appl. Phys. Lett., 2006, 88, 053901.

63 K. Stelmaszczyk, P. Rohwetter, G. Méjean, J. Yu, E. Salmon,J. Kasparian, R. Ackermann, J.-P. Wolf and L. Wöste, Appl.Phys. Lett., 2004, 85, 3977.

64 F. Courvoisier, V. Boutou, V. Wood, J.-P. Wolf, A. Bartelt,M. Roth and H. Rabitz, Appl. Phys. Lett., 2005, 87, 063901.

65 F. Courvoisier, V. Boutou, H. Rabitz and J.-P. Wolf,J. Photochem. Photobiol., A, 2006, 180, 300–306.

66 F. Courvoisier, L. Bonacina, J. Extermann, M. Roth, H. Rabitz,L. Guyon, C. Bonnet, B. Thuillier, V. Boutou and J. P. Wolf,Faraday Discuss., 2008, 137, 37–49.

67 M. Roth, L. Guyon, J. Roslund, V. Boutou, F. Courvoisier,J. P. Wolf and H. Rabitz, Phys. Rev. Lett., 2009, 102, 253001.

68 J. Petersen, R. Mitric, V. Bonacic-Koutecky, J.-P. Wolf,J. Roslund and H. Rabitz, Phys. Rev. Lett., 2010, 105,073003.

69 E. Frejafon, J. Kasparian, P. Rambaldi, B. Vezin, V. Boutou,J. Yu, M. Ulbricht, D. Weidauer, B. Ottobrini, E. de Saeger,B. Kraemer, T. Leisner, P. Rairoux, L. Wöste and J.-P. Wolf,Eur. Phys. J. D, 1998, 4, 231–238.

70 M. Beniston, M. Beniston-Rebetez, H. J. Kölsch, P. Rairoux,J.-P. Wolf and L. Wöste, J. Geophys. Res., 1990, 95(D7), 13.

71 O. Duclaux, E. Frejafon, H. Schmidt, A. Thomasson,D. Mondelain, J. Yu, C. Guillaumond, C. Puel, F. Savoie,P. Ritter, J. P. Boch and J.-P. Wolf, Atmos. Environ., 2002, 36,5081–5095.

72 B. Stein, M. Delguasta, J. Kolenda, M. Morandi, P. Rairoux,L. Stefanutti, J.-P. Wolf and L. Wöste, Geophys. Res. Lett., 1994,21, 1311–1314.

73 M. Delguasta, M. Morandi, L. Stefanutti, B. Stein and J.-P. Wolf,Appl. Opt., 1994, 33, 5690–5697.

74 L. Stefanutti, F. Gastagnoli, M. Delguasta, M. Morandi,V. M. Sacco, V. Venturi, L. Zuccagnoli, J. Kolenda,H. Kniepp, P. Rairoux, B. Stein, D. Weidauer and J.-P. Wolf,Appl. Phys. B: Photophys. Laser Chem., 1992, 55, 13–17.

75 S. Gross, M. Tesche, V. Freudenthaler, C. Toledano, M.Wiegner,A. Ansmann, D. Althausen and M. Seefeldner, Tellus, Ser. B,2011, 63, 706–724.

76 D. Muller, I. Mattis, A. Ansmann, U. Wandinger, C. Ritter andD. Kaiser, Geophys. Res. Lett., 2007, 34, L05803.

77 M. J. Molina, R. Zhang, P. J. Wooldridge, J. R. McMahon,J. E. Kim, H. Y. Chang and K. D. Beyer, Science, 1993,261, 5127.

78 R. W. Reynolds and T. M. Smith, J. Clim., 1994, 7, 929–948.79 Laser Radar Technology and Applications XV, ed. M. D. Turner

and G. W. Kamerman, Proceedings of SPIE, 2010, 7684.80 J. Kasparian, E. Fréjafon, P. Rambaldi, J. Yu, B. Vezin,

J.-P. Wolf, P. Ritter and P. Viscardi, Atmos. Environ., 1998, 32,2957–2967.

81 M. Rodriguez, R. Bourayou, G. Méjean, J. Kasparian, J. Yu,E. Salmon, A. Scholz, B. Stecklum, J. Eislöffel, U. Laux,A. P. Hatzes, R. Sauerbrey, L. Wöste and J.-P. Wolf, Phys.Rev. E: Stat., Nonlinear, Soft Matter Phys., 2004, 69, 036607.

82 R. Salamé, N. Lascoux, E. Salmon, J. Kasparian and J. P. Wolf,Appl. Phys. Lett., 2007, 91, 171106.

83 F. Courvoisier, V. Boutou, J. Kasparian, E. Salmon, G. Méjean,J. Yu and J.-P. Wolf, Appl. Phys. Lett., 2003, 83, 213–215.

84 G. Méjean, J. Kasparian, J. Yu, E. Salmon, S. Frey, J.-P. Wolf,S. Skupin, A. Vinçotte, R. Nuter, S. Champeaux and L. Bergé,Phys. Rev. E: Stat., Nonlinear, Soft Matter Phys., 2005,72, 026611.

85 P. Béjot, J. Kasparian, S. Henin, V. Loriot, T. Vieillard, E. Hertz,O. Faucher, B. Lavorel and J.-P. Wolf, Phys. Rev. Lett., 2010,104, 103903.

86 P. Béjot, E. Hertz, B. Lavorel, J. Kasparian, J.-P. Wolf andO. Faucher, Phys. Rev. Lett., 2011, 106, 243902.

87 A. Braun, G. Korn, X. Liu, D. Du, J. Squier and G. Mourou,Opt. Lett., 1995, 20, 73–75.

Publ

ishe

d on

12

Dec

embe

r 20

11. D

ownl

oade

d by

ET

H-Z

uric

h on

03/

07/2

014

13:4

3:22




88 V. Loriot, E. Hertz, O. Faucher and B. Lavorel, Opt. Express,2009, 17, 13429–13434; Erratum Opt. Express, 2010, 18, 3011.

89 J. M. Dudley, G. Genty and S. Coen, Rev. Mod. Phys., 2006, 78,1135–50.

90 R. R. Alfano, The supercontinuum laser source: fundamentals withupdated references, Springer Verlag, Heidelberg, 2nd edn, 2006.

91 Y. Petit, S. Henin, W. M. Nakaema, P. Béjot, A. Jochmann,S. D. Kraft, S. Bock, U. Schramm, K. Stelmaszczyk,P. Rohwetter, J. Kasparian, R. Sauerbrey, L. Wöste andJ.-P. Wolf, Phys. Rev. A: At., Mol., Opt. Phys., 2011, 83, 013805.

92 T. Somekawa, C. Yamanaka, M. Fujita and M. C. Galvez,J. Appl. Phys., 2008, 103, 043101.

93 T. Somekawa, C. Yamanaka, M. Fujita andM. C. Galvez, Jpn. J.Appl. Phys., 2008, 47, 2155–2157.

94 M. C. Galvez, M. Fujita, N. Inoue, R. Moriki, Y. Izawa andC. Yamanaka, Jpn. J. Appl. Phys., 2002, 41, 284.

95 J. Yu, D. Mondelain, G. Ange, R. Volk, S. Niedermeier,J. P. Wolf, J. Kasparian and R. Sauerbrey, Opt. Lett., 2001, 26,533–535.

96 G. Méjean, J. Kasparian, E. Salmon, J. Yu, J. P. Wolf,R. Bourayou, R. Sauerbrey, M. Rodriguez, L. Wöste,H. Lehmann, B. Stecklum, U. Laux, J. Eilfoeffel, A. Scholtzand A. P. Hatzes, Appl. Phys. B: Lasers Opt., 2003, 76, 357–359.

97 R. Bourayou, G. Méjean, J. Kasparian, M. Rodriguez,E. Salmon, J. Yu, H. Lehmann, B. Stecklum, U. Laux,J. Eislöffel, A. Scholz, A. P. Hatzes, R. Sauerbrey, L. Wösteand J.-P. Wolf, J. Opt. Soc. Am. B, 2005, 22, 369–377.

98 H. Wille, M. Rodriguez, J. Kasparian, D. Mondelain, J. Yu,A. Mysyrowicz, R. Sauerbrey, J.-P. Wolf and L. Wöste, Eur.Phys. J.: Appl. Phys., 2002, 20, 183–190.

99 G. Faye, J. Kasparian and R. Sauerbrey, Appl. Phys. B: LasersOpt., 2001, 73, 157–163.

100 G. Méjean, J. Kasparian, J. Yu, S. Frey, E. Salmon andJ. P. Wolf, Appl. Phys. B: Lasers Opt., 2004, 78, 535–537.

101 P. Rosch, M. Harz, M. Schmitt, K.-D. Peschke, O. Ronneberger,H. Burkhardt, H.-W. Motzkus, M. Lankers, S. Hofer, H. Thieleand J. Popp, Appl. Environ. Microbiol., 2005, 71, 1626–1637 andreferences therein.

102 D. Oron, N. Dudovich, D. Yelin and Y. Silberberg, Phys. Rev. A:At., Mol., Opt. Phys., 2002, 65, 043408.

103 D. Oron, N. Dudovich and Y. Silberberg, Phys. Rev. Lett., 2002,89, 273001.

104 N. Dudovich, D. Oron and Y. Silberberg, Nature, 2002, 418,512–514.

105 M. O. Scully, G. W. Kattawar, R. P. Lucht, T. Opatrny,H. PIlloff, A. Z. Sokolov and M. S. Zubairy, Proc. Natl. Acad.Sci. U. S. A., 2002, 99, 10994–11001.

106 D. Pestov, R. K. Murawski, G. O. Ariunbold, X. Wang, M. Zhi,A. V. Sokolov, V. A. Sautenkov, Y. V. Rostovtsev, A. Dogariu,Y. Huang and M. O. Scully, Science, 2007, 316, 265–268.

107 J. Kasparian and J. P. Wolf, Opt. Commun., 1998, 152, 355–360.108 J.-P. Wolf, Y.-L. Pan, G. M. Turner, M. C. Beard,

C. A. Schmuttermaer, S. Holler and R. K. Chang, Phys. Rev.A: At., Mol., Opt. Phys., 2011, 64, 023808.

109 O. Katz, A. Natan, Y. Silberberg and S. Rosenwaks, Appl. Phys.Lett., 2008, 92, 171116.

110 M. T. Bremer, P. J. Wrzesinski, N. Butcher, V. V. Lozovoy andM. Dantus, Appl. Phys. Lett., 2011, 99, 101109.

111 A. Portnov, I. Bar and S. Rosenwaks, Appl. Phys. B: Lasers Opt.,2010, 98, 529–535.

112 I. Langmuir, Science, 1947, 106, 505.113 US National Research Council. Critical Issues in Weather

Modification Research, National Academies Press, Washington,D. C., 2003.

114 J. Qiu and D. Cressey, Nature, 2008, 453, 970.115 P. Rohwetter, J. Kasparian, K. Stelmaszczyk, Z. Hao, S. Henin,

N. Lascoux, W. M. Nakaema, Y. Petit, M. Queißer, R. Salamé,E. Salmon, L. Wöste and J.-P. Wolf, Nat. Photonics, 2010, 4, 451.

116 J. J. Thomson, Conduction of Electricity through Gases, CambridgeUniversity Press, London, 1906.

117 G. Tohmfor and M. Volmer, Ann. Phys., 1938, 425, 109–131.118 C. T. R. Wilson, Proc. R. Soc. London, Ser. A, 1911, 85, 285–288.119 J. Seinfeld and S. Pandis, Atmospheric Chemistry and Physics,

John Wiley and Sons, Hoboken, NJ, 2nd edn, 2006.120 Y. Petit, S. Henin, J. Kasparian and J.-P. Wolf, Appl. Phys. Lett.,

2010, 97, 021108.121 A. Laaksonen, P. Korhonen, M. Kulmala and R. Charlson,

J. Atmos. Sci., 1998, 55, 853.122 P. Rohwetter, J. Kasparian, L. Wöste and J.-P. Wolf, J. Chem.

Phys., 2011, 135, 134703.123 W. Byers Brown, Chem. Phys. Lett., 1995, 235, 94.124 K. Yoshino, W. H. Parkinson, K. Ito and T. Matsui, J. Mol.

Spectrosc., 2005, 229, 238.125 www.laserweathercontrol.org.

Publ

ishe

d on

12

Dec

embe

r 20

11. D

ownl

oade

d by

ET

H-Z

uric

h on

03/

07/2

014

13:4

3:22


physical chemistry chemical physics - nccr must · 2014. 7. 3. · j. kasparian and j.-p. wolf*...

Documents