remote sensing of trace gas by combining … of a few percents of extinction on weak optical signal...

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

1 Lyon 1 University, Institute of Light and Matter, Mirthe Summer Workshop 2014.

Lyon 1 University

2

Study of Trace Gases

Need for local and global spatial distribution of trace gases

Sources and sinks • Localization • Mass flux measurements

Atmospheric model improvements

3

Impact on climate Change the Earth’s radiation budget [IPCC 2007]

Impact on human health

• Lung cancer (World Health Organization) • Harm the cardiopulmonary system • Hazardous gases (methane, benzene, natural gas, hydrogen...)

Gas pipeline in Lybia. Numerical simulation of the

atmosphere dynamics.

Aim of the work

4

The Optical Correlation Spectroscopy Lidar (OCS-lidar)

Goal: Remotely retrieve the concentration profile of a specific trace gas in the atmosphere

Lidar [Fiocco et al., Nature, 1963] [Weitkamp, Springer Ed., 2005]

Correlation Spectroscopy [Sandroni et al., Atm. Env., 1977] [Dakin et al., Sens. Actuators B, 2003] [Lou et al., App. Phys. B, 2009]

A new approach based on:

Inspired by previous works:

Gas correlation spectroscopy lidar [Edner et al., Opt. Lett., 1984] [Minato et al, Jap. J. Appl. Phys., 1999]

Patent [J. Kasparian, J.P. Wolf: FR2916849A1A1]

Outline

5

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

Outline

6


Optical Correlation Spectroscopy and Lidar

7

OCS-lidar signals

Rang

e (a

.u)

PC

PNC

Difficulties

Atmosphere variations (Patm, Tatm, clouds, interfering species)

Measurement of a few percents of extinction on weak optical signal (β ≈ 10-7 m-1.sr-1)

Controlling the power density spectrum of the laser pulse (emission, pulse shaping, transmission through the atmosphere)

Advantages

Concentration measurements are sensitive to a specific trace gas (OCS)

Range and time resolved measurements (lidar)

OCS Lidar formalism

8

OCS Lidar Equations :

20

( )( ) ( ) ( ) ( , ) ( , )²i i

K rP r P M r T r dr λ

λ λ β λ λ λ∆

= ⋅ ⋅ ⋅ ⋅ ⋅∫

Using the ratio we obtain a third order polynomial where the unknown is the cumulative concentration CC(r) :

( )( )

C

NC

P rP r

3 23 2 1 0( ) ( ) ( )( ) ( ) ( ) ( ) 0CC r CC rA r A r A r ACC r r⋅ + ⋅ + ⋅ + ≈

With and A3, A2, A1 and A0 depending on

• Measured signals PNC and PC • Laser pulse P0(λ) • Modulator transmission MC(λ) and MNC(λ) • Absorption Cross-Section σ(λ)

0( ) ( ') '

rC rC drC r = ∫ )( ()C r r

rCC∂

=∂

B. Thomas et al., « Remote Sensing of Trace Gases with Optical Correlation Spectroscopy and Lidar », APB, 108, 2012

The OCS-lidar numerical model

9

Study of systematic and statistical errors through the concentration relative error:

input output

input

C CC

−=


Simulation results for high CH4 concentration

0 500 1000 1500 2000 2500 3000 35000.5

0.6

0.7

0.8

0.9

1.0

PC

PNC

0 500 1000 1500 2000 2500 3000 3500

0

100

200

300

400 Cinput

Couput

OCS

-lida

r sig

nals

(a.u

) Ran

ge c

orr.

Range r (m)

[CH 4]

(ppm

)

10

Parameters: • Methane:

400 ppm

• Wavelength : 1.66 µm • 250 µJ/pulse • 60 000 laser shots • 15 m range resolution

B. Thomas et al., Remote sensing of trace gases with optical correlation spectroscopy and lidar, APB, 2012.

Outline

11


OCS-lidar experiment

12

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 30 cm diameter Newtonian Telescope Hammatsu photodiode

First experimental proof of the OCS-lidar methodology for water vapor measurements in the visible spectral range.

Active modulation with the AOPDF

13

Acousto Optical Programmable Dispersive Filter [Kaplan et al., Ultrafast Opt. IV, 2004]

Achieve pulse shaping with a ≈ 1 nm spectral resolution.

Based on acousto-optic effect in a birefringent crystal

( )( , ) cose e en z t n n t kzω= + ∆ ⋅ −ne: undisturbed extraordinary refractive index

Δne: amplitude of variation in the extraordinary refractive index.

An acoustic wave (≈ MHz), with angular frequency ω and wavenumber k, generates a refraction index forming a diffraction pattern:

Input Optical beam

TeO2 crystal

Acoustic wave transducer

1425 1450 1475 1500 1525 1550 15750

1000

2000

3000

4000

5000

Powe

r spe

ctra

l den

sity

(a.u

.)

1494 1496 1498 1500 1502 15040

1000

2000

3000

4000

Wavelength (nm)

1.1 nm

4.6 nm

14

Without spectral modulation : MC = MNC = 1

Control measurement 50 µJ/pulse 15 minutes average 35 m spatial resolution 0 500 1000 1500 2000

5000

10000

15000

20000

25000

30000

OC

S-lid

ar s

igna

ls (a

.u) R

ange

cor

r.

PA

PB

0 500 1000 1500 20000.7

0.8

0.9

1.0

1.1

P B/PA

Range (m)

Experimental results for H2O

Set-up with the AOPDF

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, 2013

First experimental results for H2O (AMR)

15

Water Vapor measurement 50 µJ/pulse 15 minutes average 230 m spatial resolution

0 500 1000 1500 20005000

10000

15000

20000

OCS

-lida

r sig

nals

(a.u

) Ran

ge c

orr.

PNC(r) PC(r)

0 500 1000 1500 20000.7

0.8

0.9

1.0

1.1

P C/PNC

0 500 1000 1500 20000

5000

10000

[H2O

] (pp

m)

Range (m)

Ground concentration [H2O] = 9 200 ppm

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, 2013

Outline

16


Conclusion

17

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.

First experimental proof of the OCS-lidar by measuring water vapor profiles in the atmosphere.

Development of a numerical simulation to study the statistical and systematic errors for methane and water vapor.

Development of a new algorithm to retrieve the trace gas concentration.

B. Thomas et al., Remote sensing of trace gases with optical correlation spectroscopy and Lidar : Theoretical and numerical approach, Appl. Phys B, 108, 689-702, (2012).

B. Thomas et al., Remote sensing of methane with broadband laser and optical correlation spectroscopy on the Q-branch of the 2ν3 band, J. Mol. Spec., Special issue on methane, 291, 3-8, (2013). 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: 10.1007/s00340-013-5468-4 (2013).

Outlook

18

Validation with standard measurement techniques.

Methane measurement in the infrared spectral range

Field measurements, further investigation on light sources.

Multiple gas monitoring (N2O, CO2, O3, hydrocarbons…) further investigation on the amplitude modulation and other spectral ranges.

0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.80

5000

10000

15000

20000

25000

Rang

e co

rrect

ed L

idar

sig

nal(m

V.m

²)

Range r (km)

Amplitude modulation

Micro joule infrared lidar signals

19

Thank you for your attention

Contact : [email protected]

Lyon 1 University, Institute of Light and Matter,

Amplitude modulation for H2O measurement

20

Limitation: AOPDF energy threshold: ≈ 50 µJ

690 700 710 720 730 7400

20

40

60

80

Inte

nsity

(a.u

.)

Wavelength (nm)

H2O Absorption Cross-section P0(λ).MC(λ) P0(λ).MNC(λ)

0.00E-23

5.0E-23

1.00E-22

1.50E-22

2.00E-22

Abso

rptio

n cr

oss-

sect

ion

(cm

²)

AOPDF spectral resolution

21

Measured specifications for narrow band depletion (hole)

• 3.0 nm FWHM • < 10 % hole transmission

Measured specifications for active narrow band modulation (peaks)

• 1.1 nm FWHM • 60 % peak transmission

1425 1450 1475 1500 1525 1550 15750

1000

2000

3000

4000

5000

Powe

r spe

ctra

l den

sity

(a.u

.)

1494 1496 1498 1500 1502 15040

1000

2000

3000

4000

Wavelength (nm)

1.1 nm

4.6 nm

1460 1480 1500 1520 15401000

1500

2000

2500

3000

3500

4000

4500

5000

Po

wer s

pect

ral d

ensit

y (a

.u)

Wavelength (nm)

OCS-lidar experiment in the Infrared

22

11 cm diameter Newtonian telescope

InGaAs APD infrared detector 40 MHz acquisition system, 12 bits

OCS-lidar experiment in the Infrared

23

0

2

4

6

8

10

12

14

0 10000 20000 30000

Lidar signal * r² (V.m²)

Rang

e (k

m)

YAG:Nd laser source • 1064 nm wavelength • 90 mJ per pulse • 10 Hz repetition rate

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

0 5000 10000 15000 20000 25000

Lidar signal * r² (mV.m²)

Rang

e r (

km)

OPA laser source • 1500 nm wavelength • 500 µJ per pulse • 1 kHz repetition rate

Optimization procedures

24

690 700 710 720 730 7400

20

40

60

80

0.0

0.5

1.0

1.5

Tran

smiss

ion

(%)

Wavelength (nm)

2.0

H 2O A

bsor

ptio

n cr

oss-

sect

ion

(x 1

0-22 c

m²)

M(λM, λ)

λM

700 705 710 715 720 725 730 735

0.80

0.85

0.90

0.95

1.00

T H2O

Central wavelength of M(λ) (nm)m

axim

um

min

imum

Amplitude modulation functions

( ) 02

0

( ) ( , ) ( , ),

( ) ( , )M

H O MM

P M T r dT r

P M dλ

λ

λ λ λ λ λλ

λ λ λ λ∆

∆

⋅ ⋅ ⋅=

⋅ ⋅∫

∫

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 2013

Statistical error:

25

Dσ

2 2 2N D Bσ σ σ= +

The detector noise

The background noise

Due to :

Bσ

Dσ

Bσ Assess by simulation (Libatran)

Theoretical evaluation:

Experimental evaluation:

Lida

r sig

nal (

mV)

Range (m)

Rela

tive

Freq

uenc

y

Signal (Volt)

σN

Detector Noise Equivalent Power

The signal noise

Systematic error:

26

( ) ( )2 3

0 0 42

0

2 ( ) ( ') ' 2 ( ) ( ') '( , ) 1 2 ( ) ( ') '

2 6

r r

r

TG

C r dr C r drT r C r Odr

σ λ σ λλ σ λ

− ⋅ ⋅ − ⋅ ⋅= − ⋅ ⋅ + + +

∫ ∫∫

0.00 0.05 0.10 0.15 0.20-0.4

-0.3

-0.2

-0.1

0.0

[CH 4]

rela

tive

erro

r

Methane Optical Depth ODCH4

Development of a correction algorithm to reduce the model bias:

45.10output input

input

C CC

−−<

The model bias

Optical Correlation Spectroscopy

27

0.0 0.2 0.4 0.6

Ligh

t swi

tch

Source 1 Source 2

ON

OFF

0.0 0.2 0.4 0.60.98

0.99

1.00

1.01

Dete

ctor

s Si

gnal

(a.u

.)

Time (a.u.)

Input Signal Detector Measurement Signal Detector

a

b

0 10 20 30 40 50 60 70 80 90 1000.00

0.02

0.04

0.06

0.08

0.10

Mod

ulat

ion

fact

or m

(a.u

.)

Cmeas (ppmv)

1 2

1 2

2 I ImI I

−= ⋅ +

Concentration measurement of a target gas in a cell

OCS-Lidar formalism

28 B. Thomas et al., « Remote Sensing of Trace Gases with Optical Correlation Spectroscopy and Lidar », APB, 108, 2012

20

0

20

0

( ) ( , ) ( ) ( ) ( , ) ( , ) ( )( )( )

( ) ( , ) ( ) ( ) ( , ) ( , ) ( )

CC

NNC

NC

K O r P M r T r dP r PP r

K O r P M r T r d

λ λ λ λ β λ λ η λ λ

λ λ λ λ β λ λ η λ λ

∞

∞

⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅= +

⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅

∫

∫

20

0

20

0

( ) ( ) ( , )( )( )

( ) ( ) ( , )

CC

NCNC

P M T r dP rP r

P M T r d

λ λ λ λ

λ λ λ λ

∞

∞

⋅ ⋅ ⋅=

⋅ ⋅ ⋅

∫

∫

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 MC(λ) or MNC(λ)

29

1400 1500 1600 1700 1800 1900 2000

-2.00E-020

0.00E+000

2.00E-020

4.00E-020

6.00E-020

8.00E-020

1.00E-019

Cro

ss s

ectio

n (c

m²)

λ (nm)

C2H2

OH H2O

HCl

Benzène CH4

Systematic error due to interfering species

30

1630 1640 1650 1660 1670 1680 1690 17000.00E+000

1.00E-020

2.00E-020

1630 1640 1650 1660 1670 1680 1690 17000.00E+000

1.00E-023

2.00E-023

1630 1640 1650 1660 1670 1680 1690 1700

0.00E+000

5.00E-023

1.00E-022

1630 1640 1650 1660 1670 1680 1690 17000.00E+0005.00E-0291.00E-0281.50E-028

1630 1640 1650 1660 1670 1680 1690 1700

0.00E+0001.00E-0212.00E-0213.00E-021

Wavelength (nm)

Abso

rptio

n Cr

oss-

secti

on (c

m²)

CH4

H2O

N2O

CO

C6H6

B. Thomas et al., Remote Sensing of Trace Gases with Optical Correlation Spectroscopy and Lidar, APB, 2012

Methane spectroscopy

31

1000 1500 2000 2500 3000 3500 4000

1E-26

1E-24

1E-22

1E-20

1E-18CH

4 abs

orpt

ion

cros

s-se

ctio

n (c

m²)

2ν3 band

Wavelength (nm)

1630 1640 1650 1660 1670 1680 1690 17000.00E+000

5.00E-021

1.00E-020

1.50E-020

CH4 a

bsor

ptio

n cr

oss-

sect

ion

(cm

²)

R branchQ branch

Wavelength (nm)

2ν3 band

P branch

Spectroscopic data from the HITRAN database

Methane (CH4)

World average concentration: 1.8 ppm

Global warming potential 25 times higher than carbon dioxide

The 2nd most important anthropogenic greenhouse gas

Methane concentration peaks in Boston, up to 15 times the background concentration (Crosson, GRL)

Global average methane concentration (NOAA credit)

32

Water vapor spectroscopy

33

Spectroscopic data from the HITRAN database

1000 2000 3000 40001E-32

1E-30

1E-28

1E-26

1E-24

1E-22

1E-20H 2O

abs

orpt

ion

cros

s-se

ctio

n (c

m²)

Wavelength (nm)500

4ν band

690 700 710 720 730 7400.00E+000

2.00E-023

4.00E-023

6.00E-023

H 2O a

bsor

ptio

n cr

oss-

sect

ion

(cm

²)

Wavelength (nm)

4ν band

Systematic error due to water vapor

34

0 5 10 15 201E-3

0.01

0.1

1

[CH 4]

rela

tive

erro

r

[CH4] (ppm)

RH +/- 40 % RH +/- 20 % RH +/- 10 %

1662 1664 1666 1668 16700.0

4.0x10-5

8.0x10-5

1.2x10-4

Opt

ical e

xtin

ctio

n (m

-1)

Wavelength (nm)

CH4 Extinction (1.7 ppm) H2O Extinction (10000 ppm)

Interfering species:

Presence of water vapor interferes with the methane measurement

Methane concentration relative error for different relative humidity (RH) error bar:

B. Thomas et al., Remote Sensing of Trace Gases with Optical Correlation Spectroscopy and Lidar, APB, 2012

Lidar formalism

35

00

2( , )( ) ( , ) ) ( )²

( , )( NKP r O r P r dr

T Prβ λ λλ λ η λ λ∞

= ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ +∫

( )0( , ) exp ( ', ) '

rT r r drλ α λ= − ⋅∫

( , ) ( , ) ( , )m pr r rβ λ β λ β λ= +

( , ) ( , ) ( , )m pr r rα λ α λ α λ= +

The lidar equation

The extinction coefficient α :

( )η λ

( , )T r λ

( , )rβ λ

0 ( )P λ( , )O r λ

K

NP

: Overlap function

: Constant (optics and electronics)

: Laser power density

: Atmospheric backscattering coefficient

: Atmospheric transmission

: Detector quantum efficiency : Noise power (background and electronic noise)

( )P r : Optical power

OCS-lidar formalism

36

OCS-lidar equation

20

0

( )( ) ( , ) ( ) ( , ) ( , ) ( )²C NC

KP r O r P r r d Pr

M Tλ λ β λ λ η λλ λ∞

= ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ +∫

( )0( , ) exp ( ', ) ( ') '

r

TGT r r C r drλ σ λ= − ⋅ ⋅∫

( , ) ( , ) ( , ) ( , )m p TGT r T r T r T rλ λ λ λ= ⋅ ⋅

Abso

rptio

n cr

oss-

sect

ion

(a.u

.)

Wavelength (a.u.)

( , )rσ λ

( )C r ?

Absorption cross-section: Range resolved target gas (TG) concentration profile

Time and range-resolved

0

2

4

6

8

10

12

14

0 10000 20000 30000

Range corrected signal (V.m²)Ra

nge

(km

)

Lidar: Light Detection And Ranging

37

Remote sensing measurements Elastic backscattering of laser pulses by molecules and particles

Error analysis, accuracy and sensitivity

38

Statistical errors Systematic errors

The OCS-lidar model

Temperature and pressure

Interfering species

Spectroscopic data uncertainty

Molecules and aerosols contribution

Laser spectral fluctuations

Photodetector noise

Sky and background noise

Accuracy and sensitivity optimization

Laser central wavelength

Amplitude modulation functions


remote sensing of trace gas by combining … of a few percents of extinction on weak optical signal...

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