REMOTE SENSING OF ATMOSPHERIC TRACE GASES BY OPTICAL CORRELATION SPECTROSCOPY AND LIDAR

Transcription

1 REMOTE SENSING OF ATMOSPHERIC TRACE GASES BY OPTICAL CORRELATION SPECTROSCOPY AND LIDAR by Benjamin Thomas Grégory David, Christophe Anselmo, Alain Miffre, Jean-Pierre Cariou and Patrick Rairoux Institute of Light and Matter, Lyon 1 University Lyon 1 University, Institute of Light and Matter, Mirthe Summer Workshop

2 Lyon 1 University 2

3 Study of Trace Gases Impact on climate Change the Earth s radiation budget [IPCC 27] Impact on human health Lung cancer (World Health Organization) Harm the cardiopulmonary system Hazardous gases (methane, benzene, natural gas, hydrogen...) Need for local and global spatial distribution of trace gases Sources and sinks Localization Mass flux measurements Atmospheric model improvements Gas pipeline in Lybia. Numerical simulation of the atmosphere dynamics. 3

4 Aim of the work Goal: Remotely retrieve the concentration profile of a specific trace gas in the atmosphere A new approach based on: Lidar [Fiocco et al., Nature, 1963] [Weitkamp, Springer Ed., 25] Correlation Spectroscopy [Sandroni et al., Atm. Env., 1977] [Dakin et al., Sens. Actuators B, 23] [Lou et al., App. Phys. B, 29] The Optical Correlation Spectroscopy Lidar (OCS-lidar) Gas correlation spectroscopy lidar [Edner et al., Opt. Lett., 1984] [Minato et al, Jap. J. Appl. Phys., 1999] Inspired by previous works: Patent [J. Kasparian, J.P. Wolf: FR A1A1] 4

5 Outline I. OCS-lidar methodology a. Principle b. Numerical simulations II. First experimental results a. Experimental set-up b. Water vapor measurements III. Conclusion and outlook 5

6 Outline I. OCS-lidar methodology a. Principle b. Numerical simulations II. First experimental results a. Experimental set-up b. Water vapor measurements III. Conclusion and outlook 6

7 Optical Correlation Spectroscopy and Lidar P NC P C Range (a.u) Difficulties Advantages Concentration Atmosphere variations measurements (P atm, are T atm, sensitive clouds, interfering to a specific species) trace gas (OCS) Range Measurement and time of resolved a few percents measurements of extinction (lidar) on weak optical signal (β 1-7 m -1.sr -1 ) OCS-lidar signals Controlling the power density spectrum of the laser pulse (emission, pulse shaping, transmission through the atmosphere) 7

8 OCS Lidar formalism OCS Lidar Equations : Using the ratio Kr () Pr = Pλ M λ β rλ T rλ dλ 2 i() ( ) i( ) (, ) (, ) r² λ PC () r P () r NC cumulative concentration CC(r) : we obtain a third order polynomial where the unknown is the A () r CC() r + A () r CC() r + A() r CC() r + A () r With r CCr () = Cr ( ') dr ' Cr ( ) = ( r) r CC and A 3, A 2, A 1 and A depending on Measured signals P NC and P C Laser pulse P (λ) Modulator transmission M C (λ) and M NC (λ) Absorption Cross-Section σ(λ) B. Thomas et al., «Remote Sensing of Trace Gases with Optical Correlation Spectroscopy and Lidar», APB, 18, 212 8

9 The OCS-lidar numerical model Study of systematic and statistical errors through the concentration relative error: C input C C B. Thomas et al., «Remote Sensing of Trace Gases with Optical Correlation Spectroscopy and Lidar», APB, 18, 212 = input output 9

10 Simulation results for high CH 4 concentration [CH 4 ] (ppm) OCS-lidar signals (a.u) Range corr P C.6 P NC C input C ouput Parameters: Methane: 4 ppm Wavelength : 1.66 µm 25 µj/pulse 6 laser shots 15 m range resolution Range r (m) B. Thomas et al., Remote sensing of trace gases with optical correlation spectroscopy and lidar, APB,

11 Outline I. OCS-lidar methodology a. Principle b. Numerical simulations II. First experimental results a. Experimental set-up b. Water vapor measurements III. Conclusion and outlook 11

12 OCS-lidar experiment First experimental proof of the OCS-lidar methodology for water vapor measurements in the visible spectral range. Experimental set-up, three main parts : A femtosecond laser source coupled with an OPA The amplitude modulation achieved by an Acousto Optical Programmable Dispersif Filter (AOPDF) The detection system 3 cm diameter Newtonian Telescope Hammatsu photodiode 12

13 Active modulation with the AOPDF Acousto Optical Programmable Dispersive Filter [Kaplan et al., Ultrafast Opt. IV, 24] Based on acousto-optic effect in a birefringent crystal An acoustic wave ( MHz), with angular frequency ω and wavenumber k, generates a refraction index forming a diffraction pattern: n ( z, t) = n + n cos( ωt kz) e e e n e : undisturbed extraordinary refractive index Δn e : amplitude of variation in the extraordinary refractive index. Power spectral density (a.u.) Input Optical beam 1 4 Acoustic wave 3 transducer 2 1 TeO 2 crystal nm 4.6 nm Achieve pulse shaping with a 1 nm spectral resolution. Wavelength (nm) 13

14 Experimental results for H 2 O Set-up with the AOPDF Without spectral modulation : M C = M NC = 1 OCS-lidar signals (a.u) Range corr P A P B Control measurement 5 µj/pulse 15 minutes average 35 m spatial resolution 1. P B /P A Range (m) B. Thomas et al., Remote sensing of atmospheric gases with optical correlation spectroscopy and lidar: first experimental results on water vapor profile measurements, Appl. Phys. B,

15 First experimental results for H 2 O (AMR) OCS-lidar signals (a.u) Range corr P NC (r) P C (r) Water Vapor measurement 5 µj/pulse 15 minutes average 23 m spatial resolution P C /P NC.9.8 [H 2 O] (ppm) Range (m) B. Thomas et al., Remote sensing of atmospheric gases with optical correlation spectroscopy and lidar: first experimental results on water vapor profile measurements, Appl. Phys. B, 213 Ground concentration [H 2 O] = 9 2 ppm 15

16 Outline I. OCS-lidar methodology a. Principle b. Numerical simulations II. First experimental results a. Experimental set-up b. Water vapor measurements III. Conclusion and outlook 16

17 Conclusion New approach for remote sensing of atmospheric trace gases by coupling Optical Correlation Spectroscopy with lidar (OCS-lidar). Based on a spectrally broadband light source and amplitude modulation. Development of a new algorithm to retrieve the trace gas concentration. Development of a numerical simulation to study the statistical and systematic errors for methane and water vapor. First experimental proof of the OCS-lidar by measuring water vapor profiles in the atmosphere. B. Thomas et al., Remote sensing of trace gases with optical correlation spectroscopy and Lidar : Theoretical and numerical approach, Appl. Phys B, 18, , (212). B. Thomas et al., Remote sensing of methane with broadband laser and optical correlation spectroscopy on the Q-branch of the 2ν 3 band, J. Mol. Spec., Special issue on methane, 291, 3-8, (213). B. Thomas et al., Remote sensing of atmospheric gases with optical correlation spectroscopy and lidar: first experimental result on water vapor profile measurements, Appl. Phys. B, DOI: 1.17/s (213). 17

18 Outlook Methane measurement in the infrared spectral range Amplitude modulation Micro joule infrared lidar signals Range corrected Lidar signal(mv.m²) Range r (km) Multiple gas monitoring (N 2 O, CO 2, O 3, hydrocarbons ) further investigation on the amplitude modulation and other spectral ranges. Validation with standard measurement techniques. Field measurements, further investigation on light sources. 18

19 Thank you for your attention Contact : bthomas2@ccny.cuny.edu Lyon 1 University, Institute of Light and Matter, 19

20 Amplitude modulation for H 2 O measurement Limitation: AOPDF energy threshold: 5 µj Intensity (a.u.) H 2 O Absorption Cross-section P (λ).m C (λ) P (λ).m NC (λ).e Wavelength (nm) 2.E E-22 1.E-22 5.E-23 Absorption cross-section (cm²) 2

21 AOPDF spectral resolution 5 4 Power spectral density (a.u.) nm 4.6 nm Wavelength (nm) Measured specifications for active narrow band modulation (peaks) 1.1 nm FWHM 6 % peak transmission Measured specifications for narrow band depletion (hole) 3. nm FWHM < 1 % hole transmission Power spectral density (a.u) Wavelength (nm) 21

22 OCS-lidar experiment in the Infrared InGaAs APD infrared detector 4 MHz acquisition system, 12 bits 11 cm diameter Newtonian telescope 22

23 OCS-lidar experiment in the Infrared YAG:Nd laser source 164 nm wavelength 9 mj per pulse 1 Hz repetition rate OPA laser source 15 nm wavelength 5 µj per pulse 1 khz repetition rate Range (km) 8 6 Range r (km) Lidar signal * r² (V.m²) Lidar signal * r² (mv.m²) 23

24 Optimization procedures Amplitude modulation functions Transmission (%) M(λ M, λ) λ M Wavelength (nm) H 2 O Absorption cross-section (x 1-22 cm²).95 T ( r, λ ) H2O M = λ P( λ) M( λ, λ) Tr (, λ) dλ λ P( λ) M( λ, λ) dλ M M T H2O.9.85 maximum minimum Central wavelength of M(λ) (nm) B. Thomas et al., «Remote sensing of atmospheric gases with optical correlation spectroscopy and lidar: first experimental result on water vapor profile measurements», APB, April

25 Statistical error: The signal noise Due to : The detector noise σ D The background noise σ B σ = σ + σ N D B Theoretical evaluation: σ D Detector Noise Equivalent Power σ B Assess by simulation (Libatran) Experimental evaluation: Lidar signal (mv) Range (m) Relative Frequency Signal (Volt) σ N 25

26 Systematic error: The model bias r ( r ) ( r ) 2 σ( λ) C( r ') dr ' 2 σ( λ) C( r ') dr ' TTG ( r, λ) = 1 2 σ( λ) Cr ( ') dr ' O 2 6. [CH 4 ] relative error Methane Optical Depth OD CH4 Development of a correction algorithm to reduce the model bias: C output C C input input <

27 Optical Correlation Spectroscopy Concentration measurement of a target gas in a cell Light switch Detectors Signal (a.u.) ON OFF Source 1 Source Input Signal Detector Measurement Signal Detector Time (a.u.) a b Modulation factor m (a.u.) m C meas (ppmv) I I 1 2 = 2 I1+ I2 27

28 OCS-Lidar formalism 2 K( λ) Or (, λ) P ( λ) MC ( λ) β( r, λ) T ( r, λ) ηλ ( ) dλ PC () r = + PNC () r Kλ Orλ P λ M λ βrλ T rλ ηλ dλ 2 ( ) (, ) ( ) NC ( ) (, ) (, ) ( ) P N K(λ) and O(r, λ) are achromatic β(r, λ) = β(r) is assumed to be wavelength independent η(λ) is assume to be part of the amplitude modulation M C (λ) or M NC (λ) PC () r P () r NC = 2 ( ) C ( ) (, ) P λ M λ T r λ dλ 2 ( ) NC ( ) (, ) P λ M λ T r λ dλ B. Thomas et al., «Remote Sensing of Trace Gases with Optical Correlation Spectroscopy and Lidar», APB, 18,

29 1.E-19 OH H 2 O 8.E-2 HCl C 2 H 2 Cross section (cm²) 6.E-2 4.E-2 2.E-2 Benzène CH4.E+ -2.E λ (nm) 29

30 Systematic error due to interfering species 2.E-2 1.E-2.E CH 4 Absorption Cross-section (cm²) 2.E-23 1.E-23.E E-22 5.E-23.E+ 1.5E-28 1.E-28 5.E E H 2 O N 2 O CO 3.E-21 2.E-21 1.E-21.E C 6 H 6 Wavelength (nm) B. Thomas et al., Remote Sensing of Trace Gases with Optical Correlation Spectroscopy and Lidar, APB, 212 3

31 Methane spectroscopy CH 4 absorption cross-section (cm²) 1E-18 2ν 3 band 1E-2 1E-22 1E-24 1E CH 4 absorption cross-section (cm²) 1.5E-2 1.E-2 5.E-21 R branch Wavelength (nm) Q branch.e Wavelength (nm) P branch 2ν 3 band Spectroscopic data from the HITRAN database 31

32 Methane (CH 4 ) The 2 nd most important anthropogenic greenhouse gas Global warming potential 25 times higher than carbon dioxide World average concentration: 1.8 ppm Global average methane concentration (NOAA credit) Methane concentration peaks in Boston, up to 15 times the background concentration (Crosson, GRL) 32

33 Water vapor spectroscopy H 2 O absorption cross-section (cm²) H 2 O absorption cross-section (cm²) 1E-2 1E-22 1E-24 1E-26 1E-28 1E-3 1E-32 6.E-23 4.E-23 2.E ν band 4ν band Wavelength (nm).e Wavelength (nm) Spectroscopic data from the HITRAN database 33

34 Systematic error due to water vapor Interfering species: Presence of water vapor interferes with the methane measurement Methane concentration relative error for different relative humidity (RH) error bar: [CH 4 ] relative error Optical extinction (m -1 ) 1.2x1-4 8.x1-5 4.x CH 4 Extinction (1.7 ppm) H 2 O Extinction (1 ppm) Wavelength (nm) 1E [CH 4 ] (ppm) B. Thomas et al., Remote Sensing of Trace Gases with Optical Correlation Spectroscopy and Lidar, APB, 212 RH +/- 4 % RH +/- 2 % RH +/- 1 % 34

35 Lidar formalism The lidar equation Pr () : Optical power K Pr () = Or (, λ) P λ) r ηλ ( ) dλ+ r² 2 ( β(, r λ) T (, λ) PN K : Constant (optics and electronics) Orλ (, ) : Overlap function P ( λ) : Laser power density ηλ ( ) P N : Detector quantum efficiency : Noise power (background and electronic noise) β(, r λ) Trλ (, ) : Atmospheric backscattering coefficient : Atmospheric transmission The extinction coefficient α : β(, r λ) = β (, r λ) + β (, r λ) m ( r ) T ( r, λ) = exp α( r ', λ) dr ' α(, r λ) = α (, r λ) + α (, r λ) m p p 35

36 OCS-lidar formalism OCS-lidar equation K 2 C() (, ) ( ) M C ( λ) (, ) T (, ) ( λ) r² P r = Orλ P λ β rλ rλ η dλ+ P N T(, r λ) = T (, r λ) T (, r λ) T (, r λ) m p TG ( r ) T ( r, λ) = exp σ( r ', λ) C( r ') dr ' TG Absorption cross-section: Absorption cross-section (a.u.) Wavelength (a.u.) σ(, r λ) Range resolved target gas (TG) concentration profile Cr ()? 36

37 Lidar: Light Detection And Ranging Elastic backscattering of laser pulses by molecules and particles Remote sensing measurements Time and range-resolved Range (km) Range corrected signal (V.m²) 37

38 Error analysis, accuracy and sensitivity Statistical errors Systematic errors Laser spectral fluctuations Photodetector noise Sky and background noise The OCS-lidar model Temperature and pressure Interfering species Spectroscopic data uncertainty Molecules and aerosols contribution Accuracy and sensitivity optimization Laser central wavelength Amplitude modulation functions B. Thomas et al., «Remote Sensing of Trace Gases with Optical Correlation Spectroscopy and Lidar», APB, 18,