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ENVIRONMENTAL MONITORING BY LASER RADAR*

LUCA FIORANI, FRANCESCO COLAO, ANTONIO PALUCCI

Laser Applications Section, ENEA, Via Enrico Fermi 45, 00044 Frascati, Italy, E-mail: [email protected]

Received November 4, 2009

According to the ancient Greek philosopher Empedocles, earth, water, air and fire are the elements of our universe. Indeed lithosphere, hydrosphere and atmosphere, the three main spheres of our environment, are mainly made of earth, water and air, respectively. The laser source – being a modern fire that can be successfully applied to powerful diagnostics on earth, water and air – ideally completes the Empedocles’ set of elements. This paper originates from an invited presentation given at the “3rd Workshop on Optoelectronic Techniques for Environmental Monitoring – OTEM 2009” (Bucharest, 30 September – 2 October 2009) and provides a review on the activities of the Laser Applications Section of ENEA (Italian National Agency for New Technologies, Energy and Sustainable Economic Development). Its aim is to introduce the reader to laser radar and to present some applications of this technique to the monitoring of lithosphere, hydrosphere and atmosphere. The results shown in these studies demonstrate that laser remote sensing helps us in understanding the Earth system and the relations among its components.

Key words: remote sensing, laser radar, environmental monitoring, laser range-finder, lidar fluorosensor, atmospheric lidar.

1. INTRODUCTION

Since their discovery, lasers offered revolutionary capabilities to environmental monitoring [1]. They have been firstly applied in the atmospheric field. Some examples among the possible atmospheric deployment of laser radars, or lidars, are: profiling of density, humidity and temperature of air; observation of stratospheric aerosols; monitoring of pollutants.

Hydrographic lidars are usually employed in case of fluorescing targets, very important for natural waters. In fact, the main indicators of phytoplankton biomass and biodynamics, i.e. chlorophyll-a (chl-a) and chromophoric dissolved organic matter (CDOM), are fluorescent and can be specifically detected by hydrographic lidars.

* Paper presented at the “Optoelectronic Techniques for Environmental Monitoring” (OTEM-

2009), September 30–October 2, 2009, Bucharest, Romania.

Rom. Journ. Phys., Vol. 56, Nos. 3–4, P. 448–459, Bucharest, 2011

1 Environmental monitoring by laser radar 449

Lidar employment in the lithosphere has been limited by the lack of light propagation in soil. In this case, the more relevant environmental use of laser radar is the three-dimensional scan of underground cavities in the fields of mining and archaeology.

The state-of-the-art of lidar has been recently reviewed in two books edited by C. Weitkamp [2] and T. Fujii and T. Fukuchi [3], where classical and new techniques of laser remote sensing, as well as spaceborne applications, are thoroughly described.

Section 2 provides brief basics of lidar methodology in its applications to lithosphere, hydrosphere and atmosphere. Some selected results obtained by the authors in these applications are presented in section 3. Eventually, section 4 draws some conclusions on how much lidar can help us in understanding our planet.

2. METHODOLOGY

A lidar is essentially composed of a transmitter (laser and beam shaping optics) and a receiver (telescope and signal detection electronics) [4]. Its principle of operation is illustrated in Fig. 1: the target at range R from the system sends back part of the laser pulse towards the telescope surface. Consequently, the analysis of the detected signal as a function of t, time interval between emission and detection, allows one to measure R by the simple relation:

2ctR = , (1)

where c is the speed of light in the medium where the beam propagates. This explains why lidar is known in this field as laser range-finder. If the target is Lambertian, contains the laser footprint and the transmitter divergence is smaller than the receiver field of view, the received power is given by:

( )0 2exp –2t rA

P P ERη η ρ

= απ

, (2)

where P0 is the transmitted power, A is the receiver area, ηt and ηr are the transmitter and receiver efficiency, respectively, ρ is the target reflectivity and α is the laser beam extinction coefficient of the involved air volume. In this case, α is regarded as constant, simply because R is small.

Luca Fiorani, Francesco Colao, Antonio Palucci 2 450

Fig. 1. – Lidar principle of operation.

Let us consider the case of a fluorescing target: in this case, the principle of operation is called laser-induced fluorescence (LIF) and the instrument lidar fluorosensor [4]. In general, the experimental system is above the sea (Fig. 2), at a range Rw from its surface, and the laser beam, after propagation in air, probes a water layer characterized by the extinction coefficient αw. Also in this case, the extinction coefficients in air and water are regarded as constants, because the distances are small.

Fig. 2. – Lidar fluorosensor principle of operation.

With respect to equation (2), ρ/π has to be replaced by the product of NF (number density of fluorescing molecules) times σF (fluorescence cross section). The effect of the air-water interface on the propagation of forward and backward photons is taken into account with: φ, two-way transmission factor; m, refractive index of water. Both φ and m can be regarded as constants, because their variation with the wavelength is small. Moreover, the dependence of laser emission and

R


transmitter/receiver efficiencies on the wavelength has to be considered but, once the transmitted and received wavelengths are fixed, all the related parameters can be included in the system constant kF. If the transmitted beam is contained in the receiver field of view, αw×c×τL > 10, τL/τD < 5 and τL > τ (fluorescence decay time), the received energy is given by:

( ) ( ) ( )( ) ( )

( ) ( ){ }0 2 2

,exp –F F F F

F F F ww w F

k A N RE R E R

R mϕ σ λ λ

λ = α λ + α λ α λ + α λ , (3)

where λF is the fluorescence wavelength and E0 the transmitted energy. The above mentioned hypotheses usually hold for lidar fluorosensors aimed to CDOM and chl-a detection.

A similar equation can be written for the signal coming from Raman scattering of water:

( ) ( )( ) ( )

( ) ( ){ }0 2 2

,exp –R R R R

R R R ww w R

k A NE R E R

R mϕ σ λ λ

λ = α λ + α λ α λ + α λ , (4)

where λR is the Raman-shifted wavelength, NR the number density of water molecules (practically constant) and σR the Raman scattering cross section for the OH stretching vibrational mode of liquid water.

If fluorescence and Raman signal are acquired simultaneously, the following ratio (also called fluorescence in Raman units) can be calculated:

( ) ( )( )

,,

F F

R R

E RE R

E Rλ

∗ ≡λ

. (5)

If, as usual for CDOM and chl-a detection, the extinction coefficients ratio changes slowly and the exponentials ratio is close to unity, E* can be written as:

( ) ( )F

R

N RE R k

N∗ = , (6)

where k is a new system constant including also the cross sections. This latter formula implies that, in the above mentioned hypothesis, the fluorescence in Raman units is proportional to the density of fluorescing molecules. As a consequence, the absolute concentration of fluorescing molecules can be obtained calibrating the lidar fluorosensor with in situ measurements.


Fig. 3 – Atmospheric lidar principle of operation.

In case of atmospheric applications, the target at range R is defined as the air layer defined by τD, i.e. delimited by the distances R and R+c×τD/2, because the photons detected in the time interval defined by t and t+τD come from that layer (Fig. 3) [4]. Their number n is proportional to the thickness cτD/2 and to the laser beam backscattering coefficient β of the involved air volume: in fact, their product takes the place of ρ/π in equation (2):

( ) ( ) ( ) ( ) ( )R

0 20

, , exp –2 ', d '2

DcAn R n R R RR

τλ = λ ξ λ β λ α λ

∫ , (7)

where n0 is the number of photons of the original pulse and the system efficiency ζ includes ηt and ηr of equation (2). Note that, in this case, α can not be regarded as constant.

Elastic lidar and differential absorption lidar (DIAL) are widely used to measure air particulates and gases, respectively. While in elastic lidars only one laser wavelength is used, the DIAL technique is based on the detection of the backscattered photons from laser pulses transmitted at two different wavelengths. At one wavelength (λOFF), the light is almost only scattered by air molecules and aerosols, whereas at the other one (λON), it is also absorbed by the gas under study.


3. RESULTS AND DISCUSSIONS

3.1. LITHOSPHERIC APPLICATIONS

Various kinds of underground cavities can be found among the archaeological remains. A precise determination of the dimensions of such buildings is useful to guide possible excavations. For this reason, GEOLIDAR, a compact laser radar, has been developed (Fig. 4A) [5]. The scanning head of the system can be inserted in a small drilling and, rotating the beam, a three-dimensional image of the cavity can be obtained.

A frequency-tripled Nd:YAG laser provides the light pulse. The radiation is conducted in the cavity through an optical fiber. This is accomplished thanks to the injection optics. The transferred beam is then collimated and aimed in a well-defined direction by the scan optics. Part of the radiation backscattered by the cavity wall, after having been collected and filtered by the reception optics reaches the photomultiplier (PM) where it is transformed in an electronic signal. Scan optics, reception optics and PM are integrated in the scanning head.

A B Fig. 4 – A) GEOLIDAR during laboratory tests: frequency-tripled Nd:YAG laser (1), laser control

(2), optical fiber (3), scanning head (4), trigger PM (5), PMs control (6), oscilloscope (7). B) Example of the two-dimensional scans of a cavity acquired by GEOLIDAR. The points are the measurements

of GEOLIDAR, the polygon is the shape of the cavity as it is retrieved by the software reconstruction.

The final test of GEOLIDAR has been performed by scanning an artificial cavity. The analysis of such scans showed that the position of the walls was determined with an accuracy of 0.01 – 0.02 m. For the sake of simplicity, let us consider a two-dimensional scan of the cavity (Fig. 4B). The operator sets the angle step and the initial direction (horizontal in this case). Then, the scan continues up to the maximum allowed by the mechanical constraints. The three-dimensional scan is accomplished by repeating automatically the two-dimensional scan for different angles.

2.2 HYDROSPHERIC APPLICATIONS

The main parts of a lidar fluorosensor are a frequency tripled Nd:YAG and a telescope detecting: Raman scattering by water; LIF by CDOM and algal pigments (chl-a, phycoerythrin and phycocyanin). ELF (ENEA Lidar Fluorosensor) (Fig. 5A)


[6] is a technological product of PNRA (Italian Antarctic research program) and participated to oceanographic campaigns in the Mediterranean Sea, Arctic Ocean, Indian Ocean, Pacific Ocean and Southern Ocean. Thanks to narrowband filtering

A B

Fig. 5 – A) ELF during the AREX 2007 oceanographic campaign in the Arctic Ocean. B) Thematic maps of chl-a obtained by ELF during the New Zealand – Italy transect of the MIPOT (Mediterranean

Sea, Indian and Pacific Oceans Transect) oceanographic campaign (2001-02).

A

B Fig. 6 – Thematic maps of: A) chl-a and B) CDOM obtained by ELF during the AREX 2007

oceanographic campaign.


and electronic gating, LIF signals do not need corrections for radiometric and spectral characteristics of solar irradiance and surface reflectance. Furthermore, due to the short distance from the target, atmospheric effects are negligible. This explains why ELF data (see an example in Fig. 5B) can be regarded as sea truth and have been provided to WOOD (Worldwide Ocean Optics Database) of ONR (Office of Naval Research) and SeaBASS (SeaWiFS Bio-optical Archive and Storage System) of NASA (National Aeronautics and Space Administration). Moreover, ELF data have been used for the calibration of the bio-optical algorithms [7] of the ocean color satellite radiometers MERIS [8], MODIS [9] and SeaWiFS [10] that determine the chl-a concentration from the blue-to-green ratio of the sunlight backscattered by the sea surface.

Fig.7 – Trend of the daily averages of chl-a, CDOM and their correlation obtained by ELF

during the AREX 2007 oceanographic campaign.

Another example of ELF data is given in Fig. 6. The simultaneous measurement of both chl-a and CDOM in a wide sea region allows the characterization of different marine provinces. The trend of the daily averages of chl-a, CDOM and their correlation obtained by ELF during the AREX 2007 oceanographic campaign is shown in Fig. 7. After careful inspection of these averages, it is possible to observe an approximate correspondence between their values and the dominating typology of marine province crossed by the ship:

• West Shelf (Julian days 187 and 188): intermediate values of chl-a, CDOM and correlation;

• South Shelf (Julian days 189 and 190): high-intermediate values of chl-a and CDOM, low values of correlation;

• South offshore (Julian day 191): high values of chl-a and CDOM, negative value of correlation;

• West offshore (Julian days 192-198 and 201-202): low-intermediate values of chl-a and CDOM, high-intermediate values of correlation;


• North shelf (Julian day 199): intermediate value of chl-a, high value of CDOM, intermediate value of correlation;

• Kings Bay (Julian day 200): low values of chl-a and CDOM; • North offshore (Julian day 203): intermediate values of chl-a and CDOM,

low value of correlation. The values of chl-a, CDOM and correlation are linked to the spatiotemporal dynamics of the algal blooms, and thus the classification of the sea region in marine provinces is approximate. Nevertheless, it corresponds to the expectations that offshore water is less productive than shelf water. Such an information could be used to infer valuable indications on the phytoplankton population, in order to increase our understanding of the biogeochemical cycles of Arctic Ocean.

3.3. ATMOSPHERIC APPLICATIONS

Recently, the atmospheric lidar ATLAS (Agile Tuner Lidar for Atmospheric Sensing) [11] has been developed and mounted on the mobile laboratory ENVILAB (ENVIronmental LABoratory), hosted in a small truck (Fig. 8A). ATLAS can be decomposed in four subsystems: transmitter, receiver, detector and ADC (Analog-to-Digital Converter). The main parts of the transmitter are a tunable TEA (Transverse Excited Atmospheric) CO2 laser and an off-axis reflective beam expander consisting of two OFHC (Oxygen-Free High Conductivity) copper mirrors manufactured in our laboratory. The laser is tunable thanks to the agile tuner consisting of a diffraction grating and a scanning mirror actuated by a computer-controlled galvo motor. The receiver is based on a Newton telescope. A liquid-nitrogen-cooled mercury-cadmium-telluride photodiode, coupled with a pre-amplifier designed to compliment it, has been chosen as detector. The ADC is embedded in a PCI (Peripheral Component Interconnect) card mounted in the personal computer that controls the experiment.

During two field measurement campaigns in the Brindisi (Italy) industrial zone, ATLAS has retrieved profiles of water vapor and pollutants. Fig. 8B is an example of a georeferenced measurement of water vapor carried out on 9 July 2008, while Fig. 8C shows four profiles of aerosol load obtained on 17 February 2009 (spatial resolution: 15 m, temporal resolution: 6 s). The profiles of 14:47 and 16:56 (local civil time) were acquired with the laser aimed vertically, those of 13:46 and 16:38 with the laser aimed nearly horizontally. In both cases the peaks are due to fast-moving aerosol layers. In particular, the high peak at 14:47 is linked to a cloud. Fig. 8C demonstrates that ATLAS is able to accurately track the spatiotemporal dynamics of atmospheric parameters.

Fig. 8D shows the water vapor concentration measured by ATLAS (averaged along the optical path) and a meteorological station a few kilometers away from it on 17 and 18 February 2009. Despite the distance between the two instruments, they compare well, confirming the accuracy of ATLAS.


A B

C D Fig. 8 – A) The mobile lidar ATLAS in the industrial zone of Brindisi (Italy); the laser has been aimed vertically (indicated by “V”) or nearly horizontally (indicated by “H”) or to the chimney as target (indicated by “T”). B) Georeferenced water vapor concentration (the position of ATLAS is marked by a yellow drawing-pin, the chimney is visible on the top-left). C) Four profiles of extinction coefficient retrieved in the industrial zone of Brindisi (Italy); the peaks are due to fast-moving aerosol layers. D) Water vapor concentration measured by ATLAS (averaged along the optical path) and a

meteorological station a few kilometers away from it.

A B Fig. 9 – A) Vertical profile of extinction coefficient retrieved near Mount Etna (altitude is above ground level); the double peak from 1800 to 3300 m appears to lay on a nearly linear decay and has been ascribed to the volcanic plume (the dashed line has been added for the convenience of the reader).

B) Contour plot of the extinction coefficient as a function of time and altitude.

ATLAS has been also deployed to monitor the volcanic plume of Mount Etna. The eruption of Mount Etna started on 13 May 2008. Lidar measurements were carried out on 14 July 2008, while the volcano was still active. ATLAS was located in Santuario Magazzeni (latitude: 37.75986, longitude: 15.10459, altitude: 1025 m), i.e. about 10 km east from the main craters (altitude: 3329 m), and was pointed vertically. Starting from 300 m, the extinction coefficient was retrieved from the lidar signal (Fig. 9A) with an inversion method [4] assuming a constant


backscatter-to-extinction ratio of the order of 10-3–10-1 sr-1, in conformity with aerosol measurements and models [12]. Except the double peak from 1800 to 3300 m, the extinction coefficient shows a behavior in agreement with the roughly exponential decrease already observed in similar studies [13]. After a more careful inspection, two nearly linear decays can be distinguished: the first one is stronger and extends between 300 and 1000 m, the second one is weaker and extends between 1000 and 4300 m. The most probable explanation of this behavior is that in the intervals 300–1000 m and 1000–4300 m, the lidar probes the planetary boundary layer and the free troposphere, respectively. Conversely, the double peak from 1800 to 3300 m is due to the volcanic plume.

Although the extinction profiles of Fig. 9A were acquired with a spatial resolution of 15 m and a temporal resolution of 10 minutes (averaging 3000 lidar returns), ATLAS can follow the spatiotemporal evolution of the volcanic plume with a higher temporal resolution. To demonstrate this, the sample of 3000 lidar returns was divided in consecutive 10 subsamples of 300 lidar returns; then each set of 300 lidar returns was averaged, corresponding to a temporal resolution of 1 minute, and the extinction coefficient was retrieved per each subsample. Eventually, the extinction profiles were combined in a contour plot of the extinction coefficient as a function of time and altitude (Fig. 9B) showing in detail the spatiotemporal dynamics of the volcanic plume. It is clear that the optical thickness of the plume increases with time and the second peak develops at the end of the observation period.

4. CONCLUSIONS

The methodology of laser radar has been illustrated in the three applications relevant to environmental monitoring of earth, water and air, i.e. laser range-finder, lidar fluorosensor and atmospheric lidar, respectively.

One experimental system per each of the above-mentioned applications has been described and the relative results have been shown.

GEOLIDAR demonstrated that lithospheric laser range-finders can be very useful for remote sensing in archaeological prospecting because they are accurate, fast, compact and user-friendly. The shape of a cavity was measured with an accuracy of 0.01 – 0.02 m.

The valuable contribution of lidar fluorosensors in the thorough understanding of the biogeochemical cycles of sea provinces has been exemplified by ELF, that measured h24 CDOM and algal pigments (chl-a, phycoerythrin and phycocyanin) in large regions of the world ocean, in particular in polar zones. Its data were compared to satellite imagery and were provided to international databases.

The CO2 laser-based lidar ATLAS has been used to monitor the air pollution of the industrial zone of Brindisi and to profile the volcanic plume of Mount Etna. Extinction coefficient profiles were retrieved up to a range exceeding 4 km with a spatial resolution of 15 m and a temporal resolution of 6 s.


These case studies prove that laser radars are able to remotely sense natural phenomena and anthropogenic emissions. They can be aimed to specific targets and have adequate performances to follow the spatiotemporal dynamics of the observed event. In a nutshell, it can be concluded that lidars can contribute to our understanding of the complex dynamics of air pollution and climate change.

Acknowledgements. The authors are deeply grateful to M. Bortone, S. Mattei, C. Ruocchio, A. Salomé, S. Vetrella (CORISTA, Naples) and R. Barbini, L. De Dominicis, R. Fantoni (ENEA, Frascati) for the fundamental involvement and the constant encouragement.

REFERENCES

1. L. Fiorani, F. Colao, eds., Laser Applications in Environmental Monitoring, Nova, New York, 2008.

2. C. Weitkamp, ed., Lidar: Range-Resolved Optical Remote Sensing of the Atmosphere, Springer, New York, 2005.

3. T. Fujii, T. Fukuchi, eds., Laser Remote Sensing, CRC, Boca Raton, 2005. 4. L. Fiorani, Environmental monitoring by laser radar, in S.B. Larkin, ed., Lasers and Electro-Optics

Research at the Cutting Edge, Nova, New York, 2007, pp. 119–171. 5. L. Fiorani, M. Bortone, S. Mattei, C. Ruocchio, A. Salomé, S. Vetrella, GEOSCOPE and

GEOLIDAR: integrated instruments for underground archaeological investigations, Subsurface Sensing Technologies and Applications 1, 305–318 (2000).

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7. L. Fiorani, I.G. Okladnikov, A. Palucci, Remote Sensing of the Southern Ocean by MERIS, MODIS, SeaWiFS and ENEA Lidar, Journal of Optoelectronics and Advanced Materials 10, 1482–1488 (2008).

8. J.-P. Huot, H. Tait, M. Rast, S. Delwart, J.-L. Bézy, G. Levrini, The optical imaging instruments and their applications: AATSR and MERIS, ESA Bulletin 106, 56–66 (2002).

9. W.E. Esaias, M.R. Abbott, I. Barton, O.B. Brown, J.W. Campbell, K.L. Carder, D.K. Clark, R.H. Evans, F.E. Hoge, H.R. Gordon, W.M. Balch, R. Letelier, P.J. Minnett, An overview of MODIS capabilities for ocean science observations, IEEE Transactions on Geoscience and Remote Sensing 36, 1250–1265 (1998).

10. S.B. Hooker, W.E. Esaias, G.C. Feldman, W.W. Gregg, C.R. McClain, An Overview of SeaWiFS and Ocean Color, NASA, Greenbelt, 1992.

11. L. Fiorani, F. Colao, A. Palucci, Measurement of Mount Etna plume by CO2-laser-based lidar, Optics Letters 34, 800–802 (2009).

12. A. Ben-David, Backscattering measurements of atmospheric aerosols at CO2 laser wavelengths: implications of aerosol spectral structure on differential-absorption lidar retrievals of molecular species, Applied Optics 38, 2616–2624 (1999).

13. A. Deepak, G.S. Kent, G.K. Yue, Atmospheric Backscatter Model Development for CO2 Wavelengths, NASA, Huntsville, 1982.

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