Download Atmospheric Gas Phase Reactions

DOAS without Grating Spectrometers
Ulrich Platt and the Heidelberg Group
Institute of Environmental Physics (IUP), Heidelberg University
INF 229, D-69120 Heidelberg
The DOAS Workhorse: Grating Spectrometers
Entrance Slit
Typical:
Czerny Turner arrangement
Advantages:
Proven, successfull, reliable,
known properties (?)
Grating
Reasons not to use grating spectrometers:
•
•
•
•
Limited spectral range
Overlapping orders
Rather low light throughput and high straylight levels
Difficult to use in imaging applications
Focal Plane
I) Imaging DOAS
I) 2D - Image Scanning Schemes in a 4-dimensional World
 Present technology only allows to use 3 Dim., 2 Space + Time
A) Pixel at a time
“Whiskbroom Imaging"
A
B) Column at a time
“Push-Broom Imaging"
B
C) Frame at a time
(Full Frame)
C
Dim.
Whiskbroom
Pushbroom
Full Frame
X
Time
Time
Space
Y
Time
Space (FP)
Space

Space (FP)
Space (FP)
Time*
Dispersive spectroscopy
possible with „Imaging
spectrometers“
1) non-dispersive
spectroscopy
Usually dispersive
spectroscopy
 = Wavelength
FP = Focal Plane
2) Imaging FTIR
The Importance of the “Photon Budget” (100x100 pixels)
Signal
N
1


Error  statistical
N
N
N = Number of detected photons( = photoelectrons)
 We need all the light we can get
Imaging
principle
F  3.21016 photons/(s m2 sr nm)
SO2: 20 ppmm
Detector type Etendue
E
srm2
Photons
flux FE
310-8
per pixel
108
per pixelA
410-4
per pixel
4
dispersive
310-8
per pixel
1010
per pixel
410-6
per pixel
0.04
non-dispers.
Spectrometer
 = 0.1 nm
A) Whisk-broom /channel
scanner
Filter + one
pixel sensor
 = 10 nm
Acquisition
time for
(clear sky) 1% noise
seconds
second-1
Acquisition
time for a full
Frame
seconds
B) Push-broom
scanner
Spectrometer
310-8
per column
106 per
pixelA
410-2
per pixel
4
dispersive
C) Full frame
(SO2 camera)
Filter + 2-D
sensor array
2.910-8
per pixel
1010
per pixel
410-6
per pixel
410-6
non-disp.
„Differential“ Absorption Spectroscopy
(may not really be DOAS)
Example: The „Trace Gas Camera“ (frequently used as „SO2
Camera“
Four Different Trace Gas Camera Schemes
Wavelength-Selective Element:
a) two narrow band filters
alternatingly being brought
into the beam
 SO2 - Camera
b) a Fabry-Perot interferometer with adjustable
transmission wavelength
 FP - Camera
c) a narrow-band interference filter, which can be rotated
 Filter Camera
d) a cell (cuvette) containing
the gas to be measured,
periodically introduced into the
light beam
 Gas Correlation Camera
Alternative
Position of WSE
a) Filter Camera (SO2-Camera): True 2-Dimensional Observation
A
B
Calculate SO2 column-density from
ratio of intensities seen through filter
A (IA) and Filter B (IB) and some
normalisation and correction …
UV: Mori & Burton 2006, Bluth et al. 2007 ff.
IR: e.g. Prata and Bernardo 2009
b) Fabry-Perot – Interferometer-Based SO2-Spectrometer
SO2-Camera
Fabry-Perot
Spectrometer
Setting A
Plate Dist. LA
Fabry-Perot
Spectrometer
Setting B
Plate Dist. LB
Kuhn J., Bobrowski N., Lübcke P., Vogel L., Platt U. (2014), A Fabry-Perot
interferometer based camera for two-dimensional mapping of SO2
distributions, Atmos. Meas. Tech. 7, 3705–3714.
See next
presentation
by
Jonas Kuhn
c) The SO2-Camera, Rotating Filter - Design - non dispersive
0o
35o
Problems:
1) Wavelengths are not the same throughout
the image
2) image as a whole shifts position as the
filter is tilted,
 Problems can be solved by applying
image processing techniques or by adding a
“guiding LED” (Benton et al. 2013)
Transmitted intensity of an interference filter:
Incidence angles 0°(rightmost curve) to 35°(left) in
steps of 1°.
(Nominal central wavelength (i.e. at 0°incidence
angle) is 458nm, however, any central wavelength
(e.g. 300 nm) is possible. (from Zielcke et al. 2013)
d) Gas Correlation Spectroscopy
I0
I0+Plume
I0
I0+Cell
I0+Cell+
Plume

Use in industrial monitoring
and on satellites
e.g. Ward and Zwick 1975,
Sandsten et al. 1996, 2004
Idea: Ratio images recorded with- and
without cell with gas to be measured in place
 Gas cell attenuates less, if gas is
present in the atmosphere!
e) Imaging DOAS (I-DOAS), Whisk-Broom
Example: Etna, May 10, 2005, Louban et al. 2006:
SO2
BrO
f) Passive IR-Imaging (Thermal Emission)
 
I


B


e
x
p

D







Planck
function
c2
2h 5
B  ,T   hc 
e kT  1
D





c
x
d
x




S









L
0
 Emission spectrum instead of
absorption, i.e. I() looks like ()
1) Michelson interferometer + whisk-broom scanner  2-D images (Svanberg (4)
2002, Rusch
and Harig 2010, Stremme et al. 2012).
2) Michelson interferometers + push-broom scanner (i.e. moving platform)
2-D images (Wright et al. 2013)
3) IR-cameras with two or more filters (similar way to SO2 camera) (e.g. Prata and Bernardo
2009) for SO2 retrieval and ash detection (Prata and Bernardo 2014)
4) Gas-correlation spectroscopy in the IR for imaging of ammonia and ethylene (e.g.
Sandsten et al. 1996, 2004).
5) Recent development: 2-D Michelson interferometers where instead of a single detector an
array of detectors is used. Effectively each pixel can be thought of having its own
interferometer. (e.g. GLORIA, Friedl-Vallon et al. 2006, using a 256 x 256 elements
Mercury Cadmium Telluride focal plane array cooled to 60 K. (spectral coverage 7.1 m
to 12.8 m)
II) Active Plume Imaging Techniques
Active: Artificial Light
Source
LIDAR
Classic (Mono-Static) LIDAR vs. Bi-Static LIDAR
1) There is no need for a pulsed light source, in fact light emitting diodes
in combination with suitable optics can be used.
2)  No need for a high time-resolution detector, radiation is received by
a telescope – spectrometer combination, see customary active DOAS
approach (e.g. Platt and Stutz. 2008).
3) Further possibility: non-dispersive approach with two UV-LEDs emitting
at "on absorption" and "off absorption" wavelengths.
Example: LEDs emit in the wavelength ranges of filters A, B of a
SO2-camera  non-dispersive approach.
Classic Lidar
LASER
Detector
R
Trace Gas or
Aerosol - Cloud
Bi-Static LIDAR – DOAS (BISL – DOAS)
Interesting:
Extent of overlapregion varies  R2
 Compensates 1/R2
6 cm dia. Lens
+ UV-LED
20 cm dia. Telescope +
Detector (Spectrometer)
Radiative power budget of a Bi-Static LED-LIDAR System, R=1000m
Attenuation
Power (W)
Photoel./sA
Emitted LED-power
1.0
10-3
1.461015
Collimated into beam (F/#1)-optics
(ca. 10 cm dia.)
0.25
2.510-4
Scattered in 100m volume
0.015
3.7310-6
Attenuation by scattering
0.74
2.7710-6
Collected by receiving optics
(20cm dia.)
2.410-9
6.6410-15
Conversion to photoelectrons
0.25
1.6610-15
2420
1.6610-15
2420
Power fraction
Total
a photon energy of EP = hc/  6.8510-19 J at  = 290nm
(c = speed of light, h = Planck's constant)
AAt
24 photoelectrons/(pixel s)
For just one LED! (could also use 10 LEDs)
1% O.D. (SO2: 14 ppmm) detectable after 400s integration time
SO2-camera 2-wavelength approach (2 LEDs with different wavelengths): 4s
Bi-Static LED-LIDAR System
- Further Possible Geometries
Determination of the Integral cross
section of the plume, note that no
"light dilution" can occur
Geometry for probing the 2-D gas
distribution in the plume
III) Replace Grating Spectrometers by Prism Spectrometers
Dispersion of a Prism:
O
Total deviation  between incoming and outgoing beam:
 = 1 - 2 - 3 + 4.

3
2
In triangle OAB:  = 2 + 3
  = 1 + 4 - 
1
for small angles  we have:
A
B
4
 = (n-n0)    0.5   (since n0  1.0, n  1.5)
Rays of polychromatic light will be refracted in different
directions with the total angular deviation:
dn   
d
 
d
d
Collimating
Lens
Index of
refraction n()


Camera
Lens
Focal
Plane
Entrance
Slit
Prism
f1
f2
dn/d: change of the refractive index
with wavelength, the dispersion, which
for most glass types is of the order of
10-4 – 10-3 nm-1.
Dispersion of Various Types of Glasses
dn/d810-4/nm
dn/d210-4/nm
dn/d10-3/nm
Dispersion of some Types of Glass
Type of Glass
Index of refraction / dispersion (nm-1)
300nm
400nm
600nm
1.553
3.610-4
1.531
1.310-4
1.52
0.410-4
1.87 (370nm)
9.910-4
1.85
6.810-4
1.78
1.410-4
1.58
3.210-4
1.56
1.310-4
1.54
0.410-4
N-BK7
Boro silicate
N-SF11
Dense Flint (Schwerflint)
Quartz
25x25mm:
ca. 80€
BK7: n = SQRT( 1 + 1.03961212*x**2/(x**2-0.00600069867) + 0.231792344*x**2/(x**2-0.0200179144)
+ 1.01046945*x**2/(x**2-103.560653) )
x = wavelength in micrometers
A Sample Prism Spectrometer (1)
Assuming prism with apex angle  = 60o (1.047 radian) and dn/d  610-4 we have:
d
dn
radian
 
 1.0  6  10 4  6  10 4
d
d
nm
linear dispersion (f2 =100mm):
e.g. Dense Flint
at 400nm
d
mm
nm
4
1
x
 f2  6  10  100  0.06
 x  17
d
nm
mm
 Need a detector with 5 m pixel size and 30 m entrance slit width in
order to obtain a spectral resolution of 0.5nm (in the blue spectral region)
Collimating Lens
Camera
Lens
Focal
Plane
Entrance Slit
Prism
f1=100mm
f2=100mm
Sample Prism Spectrometer (2)
Entrance slit width = 30m  17nm/mm * 0.03 mm  0.51 nm Resolution
Notes:
1) Slit could be very high (long) if e.g. a detector with 20 x 20 mm size is used
2) Angle of incidence  on refracting surface is about:   /2 + /2  23o + 30o  53o
Fresnel reflection @   53o is about 6-7%   90% efficiency!
3) Dispersion curve is highly non-linear
 Needs to be corrected (linearisation before evaluation should be no problem)
 Allows very large spectral range with high resolution in the UV low resolution
in the visible spectral range.
4) No overlapping orders
5) Resolution could be improved by using several prisms
(e.g. two quartz prisms would give 0.5 nm resolution at 300 nm)
Collimating Lens
Camera
Lens
Entrance Slit
Prism 1
Prism 2
Focal
Plane
Nonlinear Dispersion
Summary
• Imaging spectroscopy is an emerging field allowing new applications
• In many cases limited spectral information is sufficient
• Several new techniques are being introduced:
- Imaging FTIR systems
- Fabry-Perot Cameras
• Techniques, which are already proven in other areas of research can
be adapted:
- Gas Correlation Spectroscopy
- Filter Cameras
• Further new techniques have been proposed or are in promising
states of development:
- LED-LIDAR
- Wavelength-sensitive Pixel Detectors
- Quantum entanglement imaging (Zeilinger et al. 2014)
• Prism spectrometers may offer advantages for „classical“ DOAS
applications
Many Different Geometries are Possible
Example: NO2-measurements
using blue (450nm) LEDs
Array of 100 3W
blue LEDs
From: Stephan Flock, Diploma Thesis,
U. Heidelberg 2012
Fraction of Received Radiation Intensity
and Detection Limit (for NO2 at 440 nm)
Relative intensity 
Light-path 750 m
Light-path530 m
From: Stephan Flock, Diploma Thesis, U.
ca. 10 ppb2012
NO2 detectable at 3
Heidelberg
hour measurement time (Flock 2012)
100
Receiving Telescope elevation angle (degrees)
Minimum Detectable Mixing Ratio (ppb)
Light-path 1360m
1
• 30° Light source elevation angle,
• Distance Teleskope – Light Source: 26.85 m
• Light source: 300 W (input power) LED-array (about 60 W radiation intensity)
Fabry-Perot – Interferometer-Based SO2-Spectrometer
SO2-Camera
Fabry-Perot
Spectrometer
Pos. A
Plate Dist. LA
Fabry-Perot
Spectrometer
Pos. B
Plate Dist. LB
Kuhn J., Bobrowski N., Lübcke P., Vogel L., Platt U. (2014), A Fabry-Perot
interferometer based camera for two-dimensional mapping of SO2 distributions,
Atmos. Meas. Tech. Discuss. 7, 5117–5145
b) The Fabry-Perot – Interferometer Theory:
1) Free spectral Range  of a
Fabry-Perot interferometer:
 = Wavelength
L = Distance between mirrors
n = refractive index of the material
between the mirrors (i.e. air,
n ≈ 1.0)


2

  

2nL
2nL
(relatively) high
reflectance R
Low reflectance
I0
I
Quartz plates
L
T 
I
I0
F
distance between maxima   R


width of maximum
 1  R
For (negligible losses in the resonator) and
normal Fresnel's surface reflectance, i.e.
R ≈ 0.04 we obtain F ≈ 0.65.
Transmission T
2) The Finesse F, defined as:

(Correspondence to the mirror reflectivity R only
holds if the losses in the resonator are negligible)
Definition of δλ and Δλ in a Fabry-Perot interferometer.
Source: Wikipedia (Ansgar Hellwig)
SO2 remote sensing with a Fabry-Perot interferometer
additional filter
5
setting A: transmission at maximum
SO2 absorption
e.g. FPI tilt
setting B: transmission at minimum
SO2 absorption
drastically reduced spectral separation
reduced interferences !
e.g. plume aerosol extinction,
change in O3 background
Kuhn J., Bobrowski N., Lübcke P., Vogel L., Platt U.
(2014), A Fabry-Perot interferometer based camera
for two-dimensional mapping of SO2 distributions,
Atmos. Meas. Tech. 7, 3705–3714.
Fabry-Perot - Based Trace-Gas Spectrometer
• More Sensitive
• Much less susceptible
to aerosol (and other
trace gases)
Optical Density ()
Fabry-Perot,
with and without
aerosol
Optical Density ()
conventional SO2Camera
with aerosol
Optical Density ()
Konventional SO2Camera
without aerosol
Kuhn J., Bobrowski N., Lübcke P., Vogel L., Platt U. (2014), A Fabry-Perot interferometer based camera for
two-dimensional mapping of SO2 distributions, Atmos. Meas. Tech. 7, 3705–3714.
„One Pixel“ FPI SO2 Instrument
Preliminary measurement with SO2 calibration cells
Jonas Kuhn 2015
Further Application of FP-Instruments
Example 1: Measurement of other gases (than
SO2) with periodic absorption structures:
BrO, IO, OClO, …
Example 2: Measurement of HCl
Example 3: Measurement of SO2 at 7.3 (e.g. Prata et al. 1989)
 Replace bulky FT-IR Instruments like HR120
Fabry-Perot – Interferometer-Based Trace-Gas - Camera
2D detector surface
optical depth for
plate separation LA … LB
(here: 4 steps)
 Each pixel has seen
(approx.) pos. LA and
LB (with some
interpolation)
 Compose image from
ratios τ(LA)/ τ(LB) for
each pixel
Homogeneous SO2
distribution
Source: Kuhn et al. 2014
Fabry-Perot – Interferometer-Based
One Pixel SO2 Device
Source: Kuhn 2015
Actuator (tilt)
Detector
Lens
FP-Interferometer
Quantitative Imaging of Volcanic Plumes
- an Overview
I) Passive: Natural source of radiation
(sun, thermal emission)

Passive: Scattered
sunlight

I     I0     exp  c       L  IS

I     B  ,T   exp  c       L
c2
2h 5
B  ,T   hc 
e kT  1
Spectrometer
/ Camera

Passive: Thermal
Emission
Planck
function
II) Active: Artificial light source
(LED, Arc-Lamp, LASER)
Interferometer
/ Camera
Active: Artificial
Light Source
Platt U., Lübcke P., Kuhn J., Bobrowski N., Prata F., Burton M.R., and
Kern C. (2014), Quantitative Imaging of Volcanic Plumes – Results,
Future Needs, and Future Trends, J. Volcanology Geothermal
Research, (JVGR, SI on Plume Imaging), available online.
LIDAR