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Low-Temperature, High-Precision Measurements of the O2 A-Band

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Presentation on theme: "Low-Temperature, High-Precision Measurements of the O2 A-Band"— Presentation transcript:

1 Low-Temperature, High-Precision Measurements of the O2 A-Band
Erin M. Adkins1, Melanie Ghysels1, David A. Long1, Elizabeth Lunny2, and Joseph T. Hodges1 1 Material Measurement Laboratory National Institute of Standards & Technology Gaithersburg, MD 20899, USA 2 Division of Chemistry and Chemical Engineering California Institute of Technology Pasadena, CA, USA

2 Motivation: Oxygen A- Band Spectroscopy for Remote Sensing
Molecular oxygen (O2) has a well-known and uniform molar fraction within the Earth’s atmosphere. Consequently, the O2 A-band is commonly used in satellite and remote sensing measurements (GOSAT, OCO-2, TCCON) to determine the surface pressure-pathlength product for transmittance measurements that involve light propagation through the atmospheric column. In order to achieve the desired 0.25% CO2 concentration accuracy for the OCO-2 mission, high level O2 spectroscopy with advanced lineshape models is required. Currently, CRDS data is only available at 296K. NASA JPL OCO-2

3 Motivation: Oxygen A- Band Spectroscopy for Remote Sensing
Recent multispectrum analysis of O2 A-band spectra collected with CRDS and FTS developed a model integrating advanced lineshapes, line mixing, and CIA to minimize retrieval uncertainty. In order to optimize the model additional studies focusing on CIA and LM are needed. Specifically: CRDS data in the R-branch Full-band spectra at low-temperatures Drouin et al. Journal of Quantitative Spectroscopy and Radiative Transfer 286 (2017)

4 Motivation: Oxygen A- Band Spectroscopy for Remote Sensing
Recent multispectrum analysis of O2 A-band spectra collected with CRDS and FTS developed a model integrating advanced lineshapes, line mixing, and CIA to minimize retrieval uncertainty. In order to optimize the model additional studies focusing on CIA and LM are needed. Specifically: CRDS data in the R-branch Full-band spectra at low-temperatures Drouin et al. Journal of Quantitative Spectroscopy and Radiative Transfer 286 (2017)

5 Methodology: Variable-temperature CRDS
Cavity length is thermally stabilized Cavity housed in temperature-stabilized vacuum-jacketed cooling cell. 220 – 290 K ± 0.5 mK short-term stability (< 10 mK stability over 24 hours) gradients < 0.1 K Frequency-tracking servo system uses a polarization-stabilized HeNe to measure the frequency variation of cavity resonances Scanning Mechanisms Traditional CRDS scanning speed: 45 – 80 hours / spectrum Frequency-agile rapid scanning: 14 hours / spectrum Effective pathlength: 4 km (0.80 m cavity) FSRP=0, T =290K: 186 MHz Finesse: 15,000 Pressure: 0.01% relative standard deviation across 5 kPa to 133 kPa range Ghysels et al. Applied Physics B 123:124 (2017) 1-13.

6 Methodology: Samples 2% O2 Natural abundance Provides information on lineshape, line-mixing, and CIA 18% 16O2 Isotopically depleted Sensitive to line-mixing and CIA 0.2% 16O2 Isotopically depleted Sensitive to lineshape Pressures: 6.6*, 13.3, 26.7*, 53.3, 93.3, 133 kPa (displayed) Temperatures: 237, 255, 273, 290K (displayed) * Only for the 0.2% 16O2 samples

7 Methodology: Samples 2% O2 Natural abundance Provides information on lineshape, line-mixing, and CIA 18% 16O2 Isotopically depleted Sensitive to line-mixing and CIA 0.2% 16O2 Isotopically depleted Sensitive to lineshape Pressures: 6.6*, 13.3, 26.7*, 53.3, 93.3, 133 kPa (displayed) Temperatures: 237, 255, 273, 290K (displayed) * Only for the 0.2% 16O2 samples

8 Fitting: Pressure Constrained Multi-spectrum Fitting
R5R5 and R5Q6 – 53.3 kPa 237K 0.2% O2 SNR 6468 SNR 7487 Pressure-constrained Multi-spectrum Fitting Model: 1 𝑐𝜏(Δ 𝑣 𝑞 ) = 𝛼 0 + 𝛼 𝑒𝑡 Δ 𝑣 𝑞 + 𝛼 𝑎𝑏 Δ 𝑣 𝑞 Δ 𝑣 𝑞 = 𝑣 𝐹 𝑇,𝑃 Δq Isolated Line Pressure Regime: 6.6, 13.3, 26.7, 53.3 kPa Determination of Temperature Dependence Model: 𝑥 𝑇 =𝑥 296 𝐾 ⋅ 𝑇 𝑛 𝑥 Temperatures: 237, 255, 273, 290K VP: QF 1144 NGP: QF 4498 Fit first four pressures SDVP: QF 4246 SDNGP: QF 5024

9 Fitting: Determination of Temperature Dependence
𝜸 𝒂𝒊𝒓 : R5R5 and R5Q6 – 53.3 kPa 0.2% O2 SDVP 𝛾 𝑓 𝑇 =15.59𝑘𝐻𝑧 𝑃 𝑎 −1 ⋅ 𝑇 Pressure-constrained Multi-spectrum Fitting Model: 1 𝑐𝜏(Δ 𝑣 𝑞 ) = 𝛼 0 + 𝛼 𝑒𝑡 Δ 𝑣 𝑞 + 𝛼 𝑎𝑏 Δ 𝑣 𝑞 Δ 𝑣 𝑞 = 𝑣 𝐹 𝑇,𝑃 Δq Isolated Line Pressure Regime: 6.6, 13.3, 26.7, 53.3 kPa Determination of Temperature Dependence Model: 𝑥 𝑇 =𝑥 296 𝐾 ⋅ 𝑇 𝑛 𝑥 Temperatures: 237, 255, 273, 290K ln⁡(𝛾 𝑓 ) Fit first four pressures then add in the linemixing

10 Results: Γf 𝛾 𝑓 𝑇 = 𝛾 𝑓 296 𝐾 ⋅ 296 𝑇 𝑛 𝛾 𝑓 𝛾 𝑓 (kHz / Pa) 𝑛 𝛾 𝑓
𝛾 𝑓 𝑇 = 𝛾 𝑓 296 𝐾 ⋅ 𝑇 𝑛 𝛾 𝑓 𝛾 𝑓 (kHz / Pa) 𝑛 𝛾 𝑓 Comparison when other data is air compared to nitrogen Robichaud et al. , Journal of Molecular Spectroscopy 248 (2008) 1-13. Drouin et al. , Journal of Quantitative Spectroscopy and Radiative Transfer 286 (2017) Long et al. , Journal of Quantitative Spectroscopy and Radiative Transfer 111 (2010) Gordon et al. , Journal of Quantitative Spectroscopy and Radiative Transfer 203 (2017) 3-69.

11 Results: νvc with GP P Branch R Branch 𝜈 𝑑𝑖𝑓𝑓 =6.2 kHz Pa-1
PP = 9.92, PQ = 9.00, RR = 5.50, RQ = 6.01, total 8.83 Robichaud et al. , Journal of Molecular Spectroscopy 248 (2008) 1-13. Long et al. , Journal of Quantitative Spectroscopy and Radiative Transfer 111 (2010)

12 Results: νvc with GP, NGP, and SDVP*
Magnitude difference between GP and NGP 𝜈 𝑉𝐶 𝐺𝑃 − 𝜈 𝑉𝐶 𝑁𝐺𝑃 ≈1.03 ±0.07 𝑘𝐻𝑧 𝑃 𝑎 −1 Numerical Equivalence in GP and SDVP lineshape models Theory: 𝜈 𝑉𝐶 𝐺𝑃 ≈ 𝑎 𝑊 𝑆𝐷𝑉𝑃 𝛾 𝐿 𝑆𝐷𝑉𝑃 𝜈 𝑉𝐶 𝐺𝑃 − 𝜈 𝑉𝐶 𝑆𝐷𝑉𝑃 → 𝐺𝑃 ≈0.23 ±0.04 𝑘𝐻𝑧 𝑃 𝑎 −1 Wojtewicz et al. , Journal of Quantitative Spectroscopy and Radiative Transfer 144 (2014)

13 Results: νvc with GP and NGP
𝜈 𝑉𝐶 𝑇 = 𝜈 𝑉𝐶 296 𝐾 ⋅ 𝑇 𝑛 𝜈 𝑉𝐶 Theory: 𝜈 𝑑𝑖𝑓𝑓 = 𝑘 𝐵 𝑇 𝑚𝐷 , 𝐷 ∝ 𝑇 2 → 𝑛 𝑣 𝑉𝐶 =1 Observed: 𝑛 𝑣 𝑉𝐶 ≈1 Average n is 0.93 for GP and 1.05 for NGP 𝑛 𝜈 𝑉𝐶 𝐺𝑃 − 𝑛 𝜈 𝑉𝐶 𝑁𝐺𝑃 ≈−0.11 ±0.03 Robichaud et al. , Journal of Molecular Spectroscopy 248 (2008) 1-13. Long et al. , Journal of Quantitative Spectroscopy and Radiative Transfer 111 (2010)

14 Results: aw with SDVP Theory: Γ 2 Γ 0 = 𝑎 𝑤 = 1−𝑛 2 3 ⋅ 𝑚 𝑝 𝑚 𝑎 𝑚 𝑝 𝑚 𝑎 Drouin et al. , Journal of Quantitative Spectroscopy and Radiative Transfer 286 (2017) Lisak et al. , Journal of Quantitative Spectroscopy and Radiative Transfer 151 (2015)

15 Results: aw with SDVP 𝑎 𝑊 𝑇 = 𝑎 𝑊 296 𝐾 ⋅ 296 𝑇 𝑛 𝑎 𝑊
𝑎 𝑊 𝑇 = 𝑎 𝑊 296 𝐾 ⋅ 𝑇 𝑛 𝑎 𝑊 Theory: 𝑛 Γ 2 = 𝑛 Γ 0 → 𝑛 𝑎 𝑊 =0 Observed: 𝑛 𝑎 𝑊 ≠0 Drouin et al. , Journal of Quantitative Spectroscopy and Radiative Transfer 286 (2017) Lisak et al. , Journal of Quantitative Spectroscopy and Radiative Transfer 151 (2015)

16 Results: aw and νvc with SDNGP
Simultaneous fitting of SD and VC effects with only pressure constraints in multi-spectral fitting shows numerical correlations in the data Using both temperature and pressure constraints should allow meaningful determination of SD and VC parameters using the SDNGP Constrain: 𝑛 𝑣 𝑉𝐶 =1 Float: 𝑛 𝑎 𝑊

17 Conclusions/Next Steps
A variable-temperature CRDS system was used to scan the entire O2 A-band at temperatures between 237 – 290K. A range of molar fraction samples were studies to provide information on temperature-dependence of high-order line-shape parameters, line-mixing, and CIA effects. Data will support next iteration of the integrated O2 A-Band global fit and provide linelists using SDVP and SDNGP profiles. Multi-spectrum fitting with ability to constrain both pressure and temperature dependences will be important in further analysis. Continuing Experiments Extend measurements to 220K and 296K (using room-temperature cell) Additional low pressure data for 0.2% sample to provide more information in the isolated line regime

18 Acknowledgments Gas Sensing Metrology Group at NIST Gaithersburg
Dr. Brian Drouin and Dr. Matthew Cich of NASA JPL for temporary use of the probe laser used in this work and for tutorials in the LabFit broadband multi-spectrum fitting software. Support was provided by NASA OCO-2 Science Team Contract #NNH15AZ96 and the NIST Greenhouse Gas and Climate Sciences Program.

19 Methodology: Scanning
Coarse Tune: coarse tune to resonant frequency Traditional CRDS Scanning Frequency FSR Lock Laser: use fine modulation to lock laser to resonant frequency using high precision wavemeter Acquire ring-down data ~100x Jump: Adjust lock frequency to next resonant mode. Next resonant frequency within piezo tuning range? Yes No Acquisition speed: 45 – 80 hrs / spectrum

20 Methodology: Scanning
Coarse Tune: coarse tune to resonant frequency Frequency-agile, rapid scanning (FARS) νC FSR δ δ + FSR δ + 2FSR Frequency Scanning 1 2 3 Lock Laser: use fine modulation to lock laser to resonant frequency using high precision wavemeter Acquire ring-down data ~100x Jump: Adjust RF output so sideband is coincident with next resonant mode. Next resonant frequency within EOM tuning range? Yes No Acquisition speed: 14 hrs / spectrum Truong et al. Nature Photonics 7 (2013)

21 Methodology: Scanning
Threshold Mechanism HITRAN or Literature simulated spectrum Data Acquisition Acquired Spectrum FSR Frequency Threshold Frequency Frequency

22 Methodology: Frequency Tracking Servo
Ghysels et al. Applied Physics B 123:124 (2017) 1-13.

23 Results: νvc with GP, NGP, and SDNGP
Magnitude difference between lineshapes 𝜈 𝑉𝐶 𝐺𝑃 − 𝜈 𝑉𝐶 𝑁𝐺𝑃 ≈1.03 ±0.07 𝑘𝐻𝑧 𝑃 𝑎 −1 𝜈 𝑉𝐶 𝑁𝐺𝑃 − 𝜈 𝑉𝐶 𝑆𝐷𝑁𝐺𝑃 ≈1.6 ±0.6 𝑘𝐻𝑧 𝑃 𝑎 −1

24 FS-CRDS vs. Variable-temperature CRDS
Ambient Temperature FS-CRDS Cavity housed in temperature-stabilized enclosure, which maintains temperature at K with ± 35 mK stability. Cavity length actively stabilized by locking to a polarization-stabilized HeNe (1 MHz stability) via a PZT closed loop servo. Variable Temperature CRDS Cavity housed in vacuum-jacketed cooling cell that is temperature-stabilized to ± 0.5 mK over the range 220 – 290 K. Cavity length is thermally stabilized. Frequency-tracking servo system uses a polarization-stabilized HeNe to measure the frequency variation of cavity resonances Appl. Phys. B (2017) 123:124.

25 Ghysels et al., Applied Physics B 123:124 (2017) 1-13.


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