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High-accuracy laser spectrometers for wireless trace-gas sensor networks

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The subject of this dissertation is the development of a wireless sensor network composed of instruments which employ both VCSELs and QCLs for accurate, highly sensitive, and reliable long-term monitoring of environmental trace-gases. The dissertation focuses on the development of low-power instruments and calibration methods that ensure the reliability of long-term measurements.

First the field deployment of a low-power, portable, wireless laser spectroscopic sensor node for atmospheric CO2 monitoring is demonstrated. The sensor node shows 0.14 ppmv Hz^-1/2 1 sigma measurement sensitivity of CO2 concentration changes. It was first used to measure top-soil respiration rates in the laboratory and on forest floors in the field.

Then after a long-term field deployment to further assess instrument performance, new design solutions were implemented to improve fringe-limited precision of the nodes to 4-7 ppmv against a 400 ppmv CO2 background, making their performance comparable to higher power consuming commercial trace-gas analyzers. Three optimized nodes were then deployed into mixed landscapes as part of a solar powered CO2 monitoring wireless network. The three node network monitored CO2 in a grassy/woody courtyard, on top of the roof of an engineering building, and next to a road in the Princeton area. These works show that ultra-low powered VCSEL based sensor nodes can be placed in off-the-grid environments for autonomous distributed geographic monitoring of trace-gases in a manner which is impossible with current commercial techniques.

Next, this dissertation covers two techniques that were developed for the real-time calibration of laser-based trace-gas measurements. The first technique used an in-line reference gas cell and employed wavelength modulation spectroscopy (WMS) at higher harmonics to simultaneously probe the sample and reference spectra. The second technique used a revolving in-line reference cell to suppress background and other non-spectroscopic signals. These techniques were designed for eventual inclusion as a real-time calibration source for field deployable trace-gas sensors and wireless sensor networks.

Finally, this dissertation demonstrates the use of the CW injection current into a VCSEL in an external cavity configuration to tune the cavity emission's self-oscillation frequency and show through simulation and experiment that the tuning is dependent on VCSEL birefringence change.

Dissertation PDF at www.clintonjsmith.com

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High-accuracy laser spectrometers for wireless trace-gas sensor networks

  1. 1. Final Public Oral Exam 10/25/2013 High-accuracy laser spectrometers for wireless trace-gas sensor networks Clinton J. Smith Advisor: Prof. Gerard Wysocki pulse.princeton.edu
  2. 2. Research Goals • Develop CO2 sensors for deployment as a real-time sensor network for carbon flux monitoring over a broad geographic area. • Develop and implement techniques to maintain the long-term measurement stability of field deployable portable trace-gas sensors http://www.coas.oregonstate.edu/research/po/satellite.gif Base Station Radio Range Sensors 2
  3. 3. Dissertation Outline • Dissertation motivation and introduction to absorption spectroscopy • Wireless laser spectroscopic sensor node for atmospheric CO2 monitoring C. J. Smith, S. So, L. Xia, S. Pitz, K. Szlavecz, D. Carlson, A. Terzis, and G. Wysocki, “Wireless Laser Spectroscopic Sensor Node for Atmospheric CO2 Monitoring – Laboratory and Field Test,” Appl. Phys. B, vol. 110, no. 2, pp. 241-248 (2013). • Quantifying and improving wireless sensor network (WSN) node accuracy http://www.coas.oregonstate.edu/research/po/satellite.gif • A solar-powered, distributed wireless CO2 monitoring network C. J. Smith, P. Ramamurthy, M. A. Khan, W. Wang, S. So, M. A. Zondlo, E. Bou-Zeid, and G. Wysocki, “A Distributed Wireless CO2 Monitoring Network,” Manuscript in Preparation. • Real-time calibration techniques C. J. Smith, W. Wang, and G. Wysocki, “Real-time calibration of laser absorption spectrometer using spectral correlation performed with an in-line gas cell,” Optics Express, vol. 21, no. 19, pp. 2248822503 (2013). • Electric current tuning of self-oscillation frequency of EC-VCSELs C. J. Smith, W. D. Li, G. Wysocki, and S. Y. Chou, “Electric Current Tuning the Self-Oscillation Frequency of EC-VCSELs,” Photonics Technology Letters, IEEE, vol. 25, no. 17, pp. 1707-1710 (2013). • Conclusions and Future directions 3
  4. 4. FPO Outline • Dissertation motivation and introduction to absorption spectroscopy • Wireless laser spectroscopic sensor node for atmospheric CO2 monitoring C. J. Smith, S. So, L. Xia, S. Pitz, K. Szlavecz, D. Carlson, A. Terzis, and G. Wysocki, “Wireless Laser Spectroscopic Sensor Node for Atmospheric CO2 Monitoring – Laboratory and Field Test,” Appl. Phys. B, vol. 110, no. 2, pp. 241-248 (2013). http://www.coas.oregonstate.edu/research/po/satellite.gif • Quantifying and improving WSN node accuracy • A solar-powered, distributed wireless CO2 monitoring network C. J. Smith, P. Ramamurthy, M. A. Khan, W. Wang, S. So, M. A. Zondlo, E. Bou-Zeid, and G. Wysocki, “A Distributed Wireless CO2 Monitoring Network,” Manuscript in Preparation. • Real-time calibration techniques C. J. Smith, W. Wang, and G. Wysocki, “Real-time calibration of laser absorption spectrometer using spectral correlation performed with an in-line gas cell,” Optics Express, vol. 21, no. 19, pp. 2248822503 (2013). • Conclusions and Future directions 4
  5. 5. Greenhouse Gases and Climate Change • Implementation of Kyoto Protocol (1997) and Successors requires technology  Carbon credit/Carbon trading • Quantify and locate all CO2 sources and sinks requires  Natural concentration variations range from 370 ppmv to 10,000 ppmv  Global ambient CO2 concentration is ~400 ppmv  Measure with 1:1000 precision • Need distributed sensor networks  Continuous, long term, wide area trace-gas sensing • Multiple greenhouse gases (GHG)  Carbon dioxide  Methane  Nitrous oxide
  6. 6. Role of Atmospheric Gases and the GHG Effect • Simplified representation of energy flow within the atmosphere of the earth •  ~70% of incoming radiation is absorbed and re-emitted by the earth  ~30% of radiation is reflected to space GHG effect is primarily the result of molecules absorbing long-wave light D. Hartmann, Global Physical Climatology, ch. 2. San Diego, CA: Academic Press, 1994. 6
  7. 7. GHG Effect is the Result of Mid-IR Absorption • Both sun and earth act as black body sources emitting light • GHGs have a molecular “fingerprint” •  Primarily absorb long-wave light (beyond 1-2 microns) Light is absorbed following the Beer-Lambert Law  Governing concept of trace-gas spectroscopy 7
  8. 8. Beer-Lambert Law ν0 Copyright © 2003, Springer ν • Light intensity through an absorbing medium reduces by: I  I 0 e  ( ) z • where…  ( )  S ( 0 ) g (  0 )n  S(ν0) is spectral line intensity; g(ν-ν0) is absorption line profile; n is number density Molecules have many different absorption lines  Governed by the number of atoms, their atomic weight, bond configuration, etc. N2 O CO2 H2O W. Demtroder, Laser Spectroscopy. Berlin: Springer-Verlag, 3 ed., 2003. 8
  9. 9. Use Lasers to Target Absorption Lines Vertical Cavity Surface Emitting Laser - Low Power Pros - Moderate cost Con - Limited to weaker molecular transitions in the near-IR Quantum Cascade Laser - Probe strongest molecular Pro Cons transitions - High power consumption - High cost 9
  10. 10. Outline • Dissertation motivation and introduction to absorption spectroscopy • Wireless laser spectroscopic sensor node for atmospheric CO2 monitoring C. J. Smith, S. So, L. Xia, S. Pitz, K. Szlavecz, D. Carlson, A. Terzis, and G. Wysocki, “Wireless Laser Spectroscopic Sensor Node for Atmospheric CO2 Monitoring – Laboratory and Field Test,” Appl. Phys. B, vol. 110, no. 2, pp. 241-248 (2013). http://www.coas.oregonstate.edu/research/po/satellite.gif • Quantifying and improving WSN node accuracy • A solar-powered, distributed wireless CO2 monitoring network C. J. Smith, P. Ramamurthy, M. A. Khan, W. Wang, S. So, M. A. Zondlo, E. Bou-Zeid, and G. Wysocki, “A Distributed Wireless CO2 Monitoring Network,” Manuscript in Preparation. • Real-time calibration techniques C. J. Smith, W. Wang, and G. Wysocki, “Real-time calibration of laser absorption spectrometer using spectral correlation performed with an in-line gas cell,” Optics Express, vol. 21, no. 19, pp. 2248822503 (2013). • Conclusions and Future directions 10
  11. 11. Project Goal & Outline The project goal: • Develop CO2 sensors for deployment as a real-time sensor network for carbon flux monitoring over a broad geographic area.  Atmospheric monitoring of CO2 (fluxes, sources, and sinks)  Soil Respiration Monitoring http://www.coas.oregonstate.edu/research/po/satellite.gif Outline • Requirements for a sensor to be used in trace gas sensor networks • Commercial state-of-the-art • Overview of sensor design  Overview of control and acquisition electronics  Selection of laser & CO2 absorption line • Sensor performance tests • Lab & Field tests 11
  12. 12. Requirements for Trace Gas Sensor Network Node A trace gas sensor node must provide: Sensors work autonomously in the field Base Station • Small size/portability • Low unit/capital cost • Low maintenance and operating • • • • • • costs Robust construction Low power consumption High sensitivity (ppb) High selectivity to trace gas species Wireless networking capability Ease of mass production Radio Range Sensors 12
  13. 13. State of the Art Commercial CO2 Sensors Li-Cor LI-7500A • Open Path • Non-dispersive IR • < 0.1 ppmv precision • ~1 % accuracy • 12 W power consumption (30 W at startup) • Wired interface • ~30 minute warm-up period • Unreliable in inclement weather Vaisala GMP343 • Open Path • Non-dispersive IR • (3ppmv + 1 % of reading) accuracy • 1-3.5 W power consumption • Wired interface • ~30 minute warm-up period • Seconds-minutes response time http://www.licor.com/env/products/gas_analysis/LI-7500A/system_components.html http://www.vaisala.com/en/products/carbondioxide/Pages/gmp343.aspx 13
  14. 14. CO2 Sensor Node Design & Specifications • Tunable diode laser absorption spectroscopy • • • • • (TDLAS) Housed within a NEMA enclosure for environmental protection 3.5 m path Herriott multi-pass cell 2 μm VCSEL & InGaAs photodetector Custom electronics board (openPHOTONS platform) Wireless communication via TelosB Mote  TinyOS & Zigbee  UART communication with the openPHOTONS board • Powered by an integrated Li-ion polymer battery  300 mW power consumption 14
  15. 15. Custom Control and Acquisition Board Direct Digital Synthesizer TEC driver MCU 8MHz Lock-In Amplifier + Front End Modulated Current Driver So, S., Sani, A. A., Zhong, L., Tittel, F., and Wysocki, G. 2009. “Demo abstract: Laser-based trace-gas chemical sensors for distributed wireless sensor networks” in Proceedings of the 2009 international Conference on information Processing in Sensor Networks (April 13 - 16, 2009). Information Processing In Sensor Networks. IEEE Computer Society, Washington, DC, 427-428 15
  16. 16. 2 μm VCSEL & CO2 Absorption Spectrum • • • • Low power vertical cavity surface emitting laser (VCSEL)  Consumes ~5 mW P=1 atm power VCSEL temperature tuning range of ~5 cm-1 Absorption coefficients in this range correspond to ~1% absorption over 3.5 m path Water absorption lines have limited impact on CO2 absorption lines Source: HITRAN 2000 database Atmospheric Concentration, HITRAN/GEISA I  I 0 e  ( ) L 16
  17. 17. TDLAS CO2 Sensor In-Lab Performance • VCSEL is wavelength modulated at ~10 kHz  Via current modulation  2nd harmonic peak value will be used for CO2 concentration measurement  Modulation depth of ~0.22 cm-1 is optimized for the 2nd harmonic (m = 2.2) • Harmonic line profiles are measured by temperature scanning about the 4987 cm-1 absorption line  A lock-in amplifier is used to select each harmonic • Calibrated 285 ppm CO2 in N2 mixture yields  2nd harmonic SNR of 2530 17
  18. 18. TDLAS CO2 Sensor 3rd Harmonic Line Locking • Control laser temperature so that 3rd harmonic signal is near zero  This corresponds to the maximum of the 2nd harmonic signal Measure the CO2 concentration by continuously monitoring the 2nd harmonic signal value at the peak 18
  19. 19. Sensor Linearity & Startup Behavior • CO2 measurements are linear over the expected range of • • concentrations to be measured in the field  ~1.5% absorption at this line and path length Electronics are capable of sleep and wake cycles for power conservation TDLAS startup and line-locking algorithm is settled within 30 seconds of startup  Line-locking is started at approximately the 10 second mark  Short startup time is a significant advantage over (conventional) NDIR which can require up to 30 minutes to “warm up” 19
  20. 20. Quantify Precision & Accuracy w/ Allan Deviation • Use Allan Deviation calculation to quantify sensor sensitivity • Standard deviation of moving average bins of increasing size  Time domain method of analyzing noise and drift 20
  21. 21. In-Lab Long-Term Measurement Stability • “Constant Temperature” measurements are compared to line-locking measurements  Plots of typical results  Values can change by factor of ~2 up/down • The feedback loop introduces • • some noise at lower averaging times Overall stability is improved by line-locking Drift still becomes an issue at longer averaging times 21
  22. 22. In-Lab Tests: Compare TDLAS CO2 Sensor Measurements with Vaisala GMP343 • Calibrated TDLAS measurements are compared with a calibrated • Vaisala GMP343 measurements  GMP343 is a non-dispersive IR CO2 sensor Linear fit yields a slope of 1.00 and intercept of -7.23 ppmv  Curves had to be time shifted due to spatial placement of the sensors 22
  23. 23. Soil Respiration Comparison Measurements • In-lab soil respiration measurements show the TDLAS and Vaisala have similarly linear response over a large CO2 concentration range.  The sensors were placed in conditions with a very large CO2 concentration gradient.  138 ppmv/min for TDLAS and 125 ppmv/min for Vaisala measured • Field measurements showed much less CO2 respiration  A black plastic chamber was used to suppress photosynthesis  7 ppmv/min for TDLAS and 7.22 ppmv/min for Vaisala measured 23
  24. 24. Outline • Dissertation motivation and introduction to absorption spectroscopy • Wireless laser spectroscopic sensor node for atmospheric CO2 monitoring C. J. Smith, S. So, L. Xia, S. Pitz, K. Szlavecz, D. Carlson, A. Terzis, and G. Wysocki, “Wireless Laser Spectroscopic Sensor Node for Atmospheric CO2 Monitoring – Laboratory and Field Test,” Appl. Phys. B, vol. 110, no. 2, pp. 241-248 (2013). http://www.coas.oregonstate.edu/research/po/satellite.gif • Quantifying and improving WSN node accuracy • A solar-powered, distributed wireless CO2 monitoring network C. J. Smith, P. Ramamurthy, M. A. Khan, W. Wang, S. So, M. A. Zondlo, E. Bou-Zeid, and G. Wysocki, “A Distributed Wireless CO2 Monitoring Network,” Manuscript in Preparation. • Real-time calibration techniques C. J. Smith, W. Wang, and G. Wysocki, “Real-time calibration of laser absorption spectrometer using spectral correlation performed with an in-line gas cell,” Optics Express, vol. 21, no. 19, pp. 2248822503 (2013). • Conclusions and Future directions 24
  25. 25. Project Goal & Outline The project goal: • Quantify and improve field-deployed WSN node accuracy to < 1% • Develop a solar powered autonomous wireless sensor network with each node capable of measuring local CO2 concentration changes in a footprint area of 1 m to 100 m radius. http://www.coas.oregonstate.edu/research/po/satellite.gif Outline • Existing technology cannot accurately monitor diverse CO2 sources and sinks • Network deployment plans • Field deployment and measurements • Improving sensor node accuracy and ruggedness • Sensor network deployment around E-Quad 25
  26. 26. Chamber measurement of CO2 exchange • Chamber measurements are used for measuring concentration at the smallest spatial scales of areas < 1 m3. • Due to the size of the chamber measurement area, they result in geographically sparse CO2 data points.  Flow-through chamber designs can have errors of as much as ±15%  In accumulation chamber designs, concentration gradients are degraded over time as CO2 accumulates in the chamber LI-COR Flux Chamber Accumulation chamber & TDLAS node 26
  27. 27. Eddy Covariance measurement of CO2 exchange • Eddy Covariance can measure the CO2 exchange of entire ecosystem  Commonly used for spatial scales on the order of 100 m to several kilometers  Uses micrometeorological theory to interpret the covariance between vertical wind velocity and a scalar CO2 concentration measurement  Sample at as much as 20 Hz, which enables great temporal resolution in monitoring for low time-duration events • Limitations with the Eddy Covariance method  Most accurate during steady environmental conditions  Measurement areas with uneven terrain, diverse vegetation, or buildings cause errors to be introduced into the measurement 27
  28. 28. Goal: Wireless Sensor Network Around E-Quad E-QUAD at Princeton University 350 m range directional antennas are used Test Sight: Crop field in Princeton, NJ • Sensor node network addresses disadvantages of Chamber and Eddy CoVariance Techniques  Complementary measurement technique • Three locations selected to monitor coupled local environments: 1. Adjacent to the local road: car traffic 2. In the inner courtyard: local vegetation 3. On the roof of the building 28
  29. 29. First: Single Node Long-term Field Measurements • TDLAS sensor measurements are compared with the LI-COR LI-7500A NDIR CO2 • analyzer (40 sec. averaging)  TDLAS is placed 0.5 m above the ground  LI-COR is placed 0.8 m above the ground Both short term and long term trends are observable  CO2 changes as small as 3 ppmv are observed by both instruments 29
  30. 30. Multi-Day Field Measurement Comparison • Over two days unattended operation • •  LI-COR consumes 12 W; AC powered DC supply used  TDLAS consumes ~1 W (with fan); powered off of single Li-Ion battery  TDLAS volume is approximately ¼ that of LI-COR Nearly all environmental conditions experienced  High & low humidity; rain & sun; high & low temperature BUT TDLAS suffers from background “fringes”  Approximately 4% uncertainty 30
  31. 31. What are Fringes?? • Fringes are the (parasitic) filter effect of an etalon in a (coherent) beam’s path •  Etalon can be formed from any two surfaces which reflect light Environmental temperature changes affect etalon length Te  1 1  F sin 2 (2 l ) 31
  32. 32. Controlling Ambient Temperature Limits Drift 32
  33. 33. Laser Injection Responsible for Most Drift • Temperature controlled • • Temperature Controlled Vessel environment Laser and detector temperature is locally perturbed Isolate sensor components most sensitive to temperature  Detector shows no dependence  Laser shows sensitive dependence 33
  34. 34. Zero Gas Scans Yield Fringe Information FFT ~Laser-MPC separation 3.8% standard deviation (15ppmv) ~Half the MPC length • Temperature scan VCSEL wavelength in a zero gas environment • •  Any signals must originate from sensor itself FFT of zero gas scans reveal two major sources of fringing  Multi-Pass Cell (MPC) scattering  Laser to MPC entrance hole scattering Higher frequency fringes can be ignored  Over-modulated or quickly averaged out over time 34
  35. 35. Design Solutions to Improve Accuracy • Re-designed VCSEL-MPC mount  Robust: resistant to torque & temperature change  5 degrees of freedom for precise placement of injection position • MPC mirror channel widened to cone  Eliminated sidewall scatter of laser beam 35
  36. 36. Single Node Improved Field Performance Nor’easter • Multi-day field deployment at Broadmead Eddy-Covariance Station • More robust opto-mechanical design and improved optical alignment • •  Fringing from earlier campaign is not observed here  TDLAS and Li-Cor show similar noise (~1%) TDLAS shows higher concentration because it is near to the ground Several diurnal cycles observed 36
  37. 37. E-Quad Field Campaign Layout & Locations Node 1 Node 3 Princeton University Engineering-Quad (E-Quad) building • Node 1 was deployed in the E-Quad courtyard LICOR • Node 2 •  ~0.5 m above the ground Node 2 was deployed to B-wing rooftop  ~23.5 m above the ground. Node 3 was deployed at the northwest outside corner of E-Quad near the intersection of Olden St. and a service road leading to a parking lot  ~1 m above the ground and ~1.5 m from the service road 37
  38. 38. Wireless network specifications • TinyOS ActiveMessage used for transmission of data •  Single-hop only  Transmission rates as fast as 250 kbps  6 Hz transmission of sensor data packets (30 bytes each, ~1 kbps) MultiHopRouter, Tymo (Dynamic MANET On-demand implementation) available for multihop  Built on ActiveMessage protocol  Node bandwidth is reduced due to aggregate bandwidth limit and increased overhead TDMA with data update every 15 seconds Node 3 Base Station Node 2 Node 1 38
  39. 39. Solar Irradiance Calculations • Calculations based on historical Princeton, NJ solar irradiance data  Found a 100 Ah battery with 35 W panels is needed for areas of shade (1/3 direct sunlight per day)  Corresponds to 3 sq. ft. of solar panels • Solar panel power is rated based on 1 • • kW/m2 irradiance Enabled Nodes 1 and 3 to be solar powered indefinitely For comparison, Eddy Covariance stations typically consume a minimum of 12 W power  Would require a minimum of 350 W solar panels  Corresponds to > 30 sq. ft. of solar panels 39
  40. 40. Field Campaign Measurements Over a Week • 30 minute averages shown • 5 minute rolling average σ is 1.6 – 3.7 ppmv (depending on the node) • TDLAS measurements compared against commercial LI-COR Non-Dispersive • • Infrared (NDIR) CO2 sensor  Node 2 on rooftop Large changes such as diurnal cycles are common to all three nodes Node 3 is largely decoupled from Nodes 1 & 2  Street corners have increased turbulence 40
  41. 41. LI-COR and Node 2 Correlation Perfect correlation • All sensor nodes calibrated a priori with known CO2 concentration. • Scatter plot of the LI-COR and TDLAS sensor Node 2, computed for Jan. 11 • The measurements are in good agreement • A robust regression (with downweighting of outliers) between the two measurements produces a slope of 0.9966 and an offset of 8.1 ppmv  Approximately the calibration accuracy of the two instruments. 41
  42. 42. Vignette of Jan. 11 Network Measurements • The network captures some of the localized • • • • effects induced by the landscape geometry The low wind speed (< 1m/s) and ustar (<.2 m/s) indicate low turbulence  Less mixing during this period. These conditions lead to a gradual build up of CO2 (from approximately 11.4 to 11.6) At the courtyard, aided by low ventilation, the buildup of CO2 is higher/more gradual compared to other nodes. Sources and sinks vary from within the EQuad courtyard to out on the street  The sharp dip a little past 11.5 UTC is only visible at the Courtyard and Rooftop node.  The Street Corner node does not pick up this dip. 12 AM 7 AM 2:15 PM 42
  43. 43. Outline • Thesis motivation and introduction to absorption spectroscopy • Wireless laser spectroscopic sensor node for atmospheric CO2 monitoring C. J. Smith, S. So, L. Xia, S. Pitz, K. Szlavecz, D. Carlson, A. Terzis, and G. Wysocki, “Wireless Laser Spectroscopic Sensor Node for Atmospheric CO2 Monitoring – Laboratory and Field Test,” Appl. Phys. B, vol. 110, no. 2, pp. 241-248 (2013). • Quantifying and improving WSN node accuracy http://www.coas.oregonstate.edu/research/po/satellite.gif • A solar-powered, distributed wireless CO2 monitoring network C. J. Smith, P. Ramamurthy, M. A. Khan, W. Wang, S. So, M. A. Zondlo, E. Bou-Zeid, and G. Wysocki, “A Distributed Wireless CO2 Monitoring Network,” Manuscript in Preparation. • Real-time calibration techniques C. J. Smith, W. Wang, and G. Wysocki, “Real-time calibration of laser absorption spectrometer using spectral correlation performed with an in-line gas cell,” Optics Express, vol. 21, no. 19, pp. 2248822503 (2013). • Conclusions and Future directions 43
  44. 44. Project Goal & Outline The project goal: • Develop and implement a technique for real-time calibration of portable trace-gas sensors  Using spectral correlation with a revolving in-line gas cell  Minimizes sources of drift in real time http://www.coas.oregonstate.edu/research/po/satellite.gif Outline • Key challenges to long-term sensor measurement stability • Conventional calibration methods • Overview of the rotational reference cell implementation • Experimental results 44
  45. 45. Measurement Noise & Drift Reduce Sensitivity Measurement drift can be induced by many factors: • Fabry-Perot Fringing  Opto-mechanical instability Allan Deviation (sensitive to ambient temperature change)  Scattering • Electronics instability • Optical power fluctuation Averaging Time (sec) Recurring Calibration Required 45
  46. 46. Conventional Calibration Methods • Send beam to separate optical branch  Use separate reference cell  Subject to different parasitic I0 IDet,1 Ambient Detector 1 fringes • Multiple detectors Reference Cell  With different noise & drift IDet,2 Detector 2 • Single gas cell • Single detector • Cycle between reference and • sample gases  Maintenance challenge Lack of portability and autonomy Ambient Ref. Gas I0 Inlet Outlet IDet Detector 46
  47. 47. Permanent In-Line Reference Cell Separate reference cell signal and ambient signal using gas parameters and WMS • Permanently insert a low-pressure reference cell in the beam path • • •  Contains the same gas as sampled Reference beam experiences the same fringes as the ambient/sampling beam No complex gas handling required Only single detector is needed 47
  48. 48. Key WMS Parameters Laser frequency change Amplitude = β Key characteristics of Wavelength Modulation Spectroscopy (WMS) Absorption Line Shape νHWHM Laser Detector • Modulate laser • wavelength at a high frequency (f) and with modulation depth/amplitude (β)  Avoids 1/f noise Demodulate and filter at multiples of f  Low-noise, “derivative-like” 1f 2f spectral envelopes • WMS Signal is proportional to laser power and depends on 3 key parameters:  Line-width, νHWHM (cm-1)  Modulation depth, β (cm-1)  Harmonic (e.g., 1f, 2f, 3f, …) m  3f  HWHM 48
  49. 49. Simultaneous Detection of Sample and Reference IDet Detector 2f ambient 6f reference 2f I0 IDet Detector • Simultaneous 2f & 6f demodulation • Selectively suppress ambient sample or low pressure reference signal • Real-time, in-line calibration is possible 6f IDet Detector I0 IDet Detector 49
  50. 50. Optimum Reference Signal Isolation • Experimentally varied the modulation index for pressures from 50 to 1000 Torr • Line-center value used for comparison • Good agreement between experiment and simulation • Ambient signal into reference cell signal cross-talk of ~4%  Ambient signal is at or below the observed noise floor 50
  51. 51. Suppress Drifts by Division of Background Signal Raw Spectra Scans Reference Path: Raw Scan with Spectral Fit I ref ( )  Tref I 0e  ( b ( ) Lb  ref ( ) La ) Corrected Reference Scan Background Corrected Reference Signal Tref , c ( )  Background Path: I zero ( )  Tzero I 0 e  b ( ) Lb I ref ( ) I zero ( )  Tref TZero e  ref ( ) La • Baseline and fringes are suppressed through division  Same process applies to the sample signal  Spectral fitting removes baseline but not fringes 52
  52. 52. Long-term Suppression of Drift Time Series of Uncorrected and Corrected Signals Allan Deviation of Uncorrected and Corrected Signals 1 ppmv 1sec, 1σ = 1.75 ppmv • Measure away from absorption line • •  Assess instrument stability 1 sec. 1σ sensitivity is 3.510-4 (1.75 ppmv) Sensitivity of 610-5 (0.3 ppmv) after 100 sec. averaging & sustained past 3000 sec. 53
  53. 53. Incomplete Correction of Absorption Peak Signal Time Series of Signals at the Peak and Away Allan Deviation of Signals at the Peak and Away 1 ppmv • Measured reference gas stability at and away from absorption peak • Long-term drift remains for on-line measurements • Full spectral fit of corrected reference also shows drift •  Improves 1 sec sensitivity ~2 to 210-4 (1 ppmv)  Uses full spectral information Background signal 4-5 reference signal  Difficult to suppress but can calibrate sample against reference 54
  54. 54. Baseline Drift & Error Correction Background-Corrected Scans at Different Experiment Times Scatter Plots Tsample,c(Tref,c) Before & After Baseline Correction • Baseline drift introduces error into single spectral point measurements •  Differences in reference & sample baseline also introduce error Use Sample-Reference regression + fundamental principles to correct  At 100% transmission the fit of Tsample,c(Tref,c) should intersect (1,1) coordinate  Scale spectra to meet this condition 55
  55. 55. Calibration Through Spectral Correlation Scatter Plots Tsample,c(Tref,c) Before & After Baseline Correction TS (t n )  mTR (t n )  y0 Baseline Corrected Transmissions TR (tn )  Tref , c (tn ) Bsim Bmeas TS (t n )   Tsample,c (t n ) Bsim,meas are simulated & measured baselines β is a modeled transmission correction factor • Use slope (m) of TS(TR) to calibrate sample concentration.  Slope is proportional to the ratio of analyte concentrations. [CO2 ]sample  m  [CO2 ]ref • Point-by-point spectral correlation of time domain data.  Uses all spectral data (like a spectral fit).  Frequency calibration not needed. 56
  56. 56. Single point, spectral fit, & spectral correlation Time Series Showing Effects of Calibration Allan Deviation Showing Effects of Calibration Drift reduction • Single point & spectral correlation calibration suppress drift • Full spectral fit shows ~6 % offset •  Consistent with sample and reference baseline differences  1.7 increase in 1s sensitivity (2.35 ppmv to 1.33 ppmv)  Drift remains Spectral correlation calibration has accuracy & precision of fit.  Removes baseline error without frequency calibration. 57
  57. 57. Conclusion Solar-powered Distributed Wireless Trace-gas Sensor Network • Built a sensor network to monitor atmospheric trace-gases.  Captured events on different time and spatial scales. • Network sensor nodes operated autonomously .  Placed where CO2 exchange is difficult to quantify. • Sensor nodes have similar sensitivity as commercial sensors.  Consume 1/10th the power and more compact.  Greater sustained operation than commercial sensors. Spectral Correlation with Revolving Reference Cell • Developed a novel in-line drift suppression & calibration technique.  Uses spectral correlation with a revolving in-line gas cell.  Provides real-time calibration. • Divide the sample (reference) signals by the background spectrum.  Three sub-cells share the same optical interfaces.  Parasitic interference fringes are minimized. • Spectral correlation calibration technique.  Maintains concentration retrieval accuracy.  Improves measurement precision.  Uses entire spectrum without costly wavelength calibration. 58
  58. 58. Future Work Solar-powered Distributed Wireless Trace-gas Sensor Network • Incorporate the sensor network as an environmental model input . • Change communications interface to forward over 3G or equivalent network.  Ubiquitous and robust network infrastructure. • Redesign MPC to accommodate a larger sized beam to further reduce clipping. • Develop an electronics board with improved capabilities  On-board temperature and pressure sensors.  Laser drive current ramping  Spectral modeling and measurement of multiple species Spectral Correlation with Revolving Reference Cell • Minimize background signal magnitude with solid optical waveguides  Calibration in a controlled atmosphere  Operation at the Brewster’s angle to further suppress fringes  Field deployment to act as local calibration source 59
  59. 59. List of Publications (1) Journal M. Nikodem, D. Weidmann, C. Smith, and G. Wysocki, “Signal-to-noise ratio in chirped laser dispersion spectroscopy,” Opt. Express, vol. 20, no. 1, pp. 644-653 (2012). C. J. Smith, S. So, L. Xia, S. Pitz, K. Szlavecz, D. Carlson, A. Terzis, and G. Wysocki, “Wireless Laser Spectroscopic Sensor Node for Atmospheric CO2 Monitoring – Laboratory and Field Test,” Appl. Phys. B, vol. 110, no. 2, pp. 241-248 (2013). C. J. Smith, W. D. Li, G. Wysocki, and S. Y. Chou, “Electric Current Tuning the Self-Oscillation Frequency of EC-VCSELs,” Photonics Technology Letters, IEEE, vol. 25, no. 17, pp. 1707-1710 (2013). C. J. Smith, W. Wang, and G. Wysocki, “Real-time calibration of laser absorption spectrometer using spectral correlation performed with an in-line gas cell,” Optics Express, vol. 21, no. 19, pp. 22488-22503 (2013). C. J. Smith, P. Ramamurthy, M. A. Khan, W. Wang, S. So, M. A. Zondlo, E. Bou-Zeid, and G. Wysocki, “A Distributed Wireless CO2 Monitoring Network,” Manuscript in Preparation. Proceedings Stephen So, Evan Jeng, Clinton Smith, David Krueger, and Gerard Wysocki, “Next generation infrared sensor instrumentation: remote sensing and sensor networks using the openPHOTONS repository (Proceedings Paper),” Infrared Remote Sensing and Instrumentation XVIII, Marija Strojnik; Gonzalo Paez, Editors, vol. 7808, no. 780818, 2010. Clinton J. Smith, Stephen So, Amir Khan, Mark A. Zondlo, and Gerard Wysocki, “Low-power wireless trace gas sensing network (Proceedings Paper),” Sensing Technologies for Global Health, Military Medicine, Disaster Response, and Environmental Monitoring; and Biometric Technology for Human Identification VIII, Sárka O. Southern; Kevin N. Montgomery; Carl W. Taylor; Bernhard H. Weigl; B. V. K. Vijaya Kumar; Salil Prabhakar; Arun A. Ross, Editors, vol. 8029, no. 80291G, 2011. M. Nikodem, C. Smith, D. Weidmann, and G. Wysocki, “Remote mid-infrared sensing using chirped laser dispersion spectroscopy (Proceedings Paper),” Advanced Environmental, Chemical, and Biological Sensing Technologies VIII, Tuan Vo-Dinh; Robert A. Lieberman; Gnter Gauglitz, Editors, vol 8024, no. 80240F, 2011. 60
  60. 60. List of Publications (2) Conference C. J. Smith, W. Li, S. Bai, and S. Y. Chou, “High Frequency Polarization Switching VCSEL Clock Using Subwavelength Quarter-Wave Plate,” in Conference on Lasers and Electro-Optics/International Quantum Electronics Conference, OSA Technical Digest (CD) (Optical Society of America, 2009), paper CMP6. C. J. Smith, S. So, and G. Wysocki, "Low-Power Portable Laser Spectroscopic Sensor for Atmospheric CO2Monitoring," in Conference on Laser ElectroOptics: Applications, OSA Technical Digest (CD) (Optical Society of America, 2010), paper JThB4. C. J. Smith, S. So, A. Khan, M. A. Zondlo, and G. Wysocki, "Temperature Impact on the Long-Term Stability of a Portable Laser Spectroscopic CO2 Sensor," in Quantum Electronics and Laser Science Conference, OSA Technical Digest (CD) (Optical Society of America, 2011), paper JWA117. C. J. Smith, W. Li, G. Wysocki, and S. Y. Chou, “Drive-Current Tuning of Self-Oscillation Frequency of External Cavity VCSEL,” in CLEO:2011 – Laser Applications to Photonic Applications, OSA Technical Digest (CD) (Optical Society of America, 2011), paper CTuP3. M. Nikodem, C. J. Smith, D.Weidmann, and G. Wysocki, “Chirped Laser Dispersion Spectroscopy with baseline-free 2nd harmonic detection,” in CLEO:2011 - Laser Applications to Photonic Applications, OSA Technical Digest (CD) (Optical Society of America, 2011), paper CThT4. C.J. Smith, S. So, and G. Wysocki, “Wireless sensor network for environmental CO2 monitoring,” in Field Laser Applications in Industry and Research (FLAIR), 2011. D. Richter, S. Meyer, S.M. Spuler, C.J. Smith, S. So, and G. Wysocki, “Ultra compact VCSEL based CO2 spectrometer for flux measurements,” in Field Laser Applications in Industry and Research (FLAIR), 2011. M. Nikodem, C. Smith, D. Weidmann, and G. Wysocki, “Open-path remote sensing of nitrous oxide using chirped laser dispersion spectroscopy,” in Field Laser Applications in Industry and Research (FLAIR), 2011. W. Wang, C. Smith, S. So, E. Bou-Zeid, and G. Wysocki, "Wireless Sensor Networks for Monitoring of Atmospheric Chemicals," in Renewable Energy and the Environment, OSA Technical Digest (CD) (Optical Society of America, 2011), paper JWE19. C. J. Smith, M. A. Khan, M. A. Zondlo, and G. Wysocki, "In-Line Reference Cell for Real-Time Calibration of Laser Absorption Spectrometers," in CLEO: Science and Innovations, OSA Technical Digest (online) (Optical Society of America, 2012), paper CW3B.1. C. Smith, W. Wang, and G. Wysocki, “A Rotational Sample/Reference Cell for High-accuracy Real-time Spectroscopic Trace-gas Sensing,” in CLEO: 2013, OSA Technical Digest (online) (Optical Society of America, 2013), paper CW1L.3. 61
  61. 61. Acknowledgements Prof. Gerard Wysocki Prof. Craig Arnold Prof. Naveen Verma Prof. Claire Gmachl Prof. Elie Bou-Zeid Prof. Mark Zondlo Prof. M. Amir Khan Prof. Stephen Chou Dr. Stephen So Dr. Tracy Tsai Yin Wang Wen (Eve) Wang Dr. Michal Nikodem Dr. Brian Brumfield Dr. Andreas Hangauer Dr. Prathap Ramamurthy Genny Plant Eric Zhang Alex Hallden-Abberton ELE Staff Friends & Family Haining Helen Yu This work was sponsored in part by: The National Science Foundation’s MIRTHE Engineering Research Center An NSF MRI award #0723190 for the openPHOTONS systems An innovation award from The Keller Center for Innovation in Engineering Education National Science Foundation Grant No. 0903661 “Nanotechnology for Clean Energy IGERT” 62
  62. 62. Electronics Long-term Stability 64
  63. 63. Interband Emission vs. Intersubband Emission M. Razeghi, S. Slivken, A. Evans, J. Nguyen, Y. Bai, J. S. Yu, S. R. Darvish, and K. Mi, “High power semiconductor lasers make mid-infrared wavelengths accessible,” SPIE Newsroom, 2006. 65
  64. 64. Vignette of Street Corner • When the Node 3 data (near the street-corner) is examined with only 15 • seconds of averaging, the influence of passing cars can be detected Direction of the tail-pipe and the size and model of the car correlate with the degree of the increase in CO2 concentration  Traditional internal combustion engine based cars with a tail-pipe facing the direction of the sensor cause much higher concentration spikes than hybrid vehicles (for which there is no measurable concentration change). • Larger vehicles have a much greater impact on the local CO2 concentration. 66
  65. 65. Wireless Communications Interface • • • Commercial Xbow TelosB wireless interface card  IEEE 802.15.4/ZigBee compliant communications  Running TinyOS Communicates with acquisition & control board via UART Communicates with the base station PC via USB  Labview used for control and data logging http://moodle.utc.fr/file.php/498/SupportWeb/co/Module_RCSF_35.html 67
  66. 66. Sensor Nodes Up Close 68
  67. 67. Lock-in Detection V psd  VsigVL sin( r t   sig ) sin( Lt   ref )  1/ 2VsigVL cos([r  L ]t   sig   ref )  1/ 2VsigVL cos([r  L ]t   sig   ref ) If L  r then.. V psd  1 / 2VsigVL cos( sig   ref ) Vpsd is proportional to signal amplitude 69

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