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Dual-comb spectroscopy over a 100 km open-air path

Abstract

Dual-comb spectroscopy (DCS) provides broadband, high-resolution, high-sensitivity amplitude and phase spectra within a short measurement time, thus holding promises for atmospheric spectroscopy. However, previous research has been limited to measuring over open-air paths of about 20 km. Here, by developing a bistatic set-up using time–frequency dissemination and high-power optical frequency combs, we implement DCS over a 113 km turbulent horizontal open-air path. We successfully measure the absorbance spectra of CO2 and H2O with a 7 nm spectral bandwidth and a 10 kHz frequency accuracy, and achieve a sensing precision of <2 ppm in 5 min and <0.6 ppm in 36 min for CO2. We anticipate our system to find immediate applications in the monitoring of urban greenhouse gas and gaseous pollutants emission. Our technology may also be extended to satellite-based DCS for greenhouse gas monitoring and calibration measurements.

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Fig. 1: Protocols of DCS.
Fig. 2: The experimental set-up.
Fig. 3: Original spectrum and resulting spectrum.
Fig. 4: CO2 concentration and H2O concentration extracted independently from the absorbance and phase spectra at both terminals. The ‘abs’ refers to the concentration inverted from absorbance, and the ‘pha’ refers to the concentration inverted from phase spectrum.
Fig. 5: CO2 precision (Allan deviation) for the four retrievals over a period of relative stability.

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Data availability

All data generated or analysed during this study are included in this article (and its Supplementary Information files). All data are available from the corresponding author upon reasonable request. Source data are provided with this paper.

Code availability

All relevant codes or algorithms are available from the corresponding author upon reasonable request.

References

  1. Zhang, X. et al. The development and application of satellite remote sensing for atmospheric compositions in China. Atmos. Res. 245, 105056 (2020).

    Article  Google Scholar 

  2. Laj, P. et al. Measuring atmospheric composition change. Atmos. Environ. 43, 5351–5414 (2009).

    Article  ADS  Google Scholar 

  3. Benneke, B. & Seager, S. Atmospheric retrieval for super-earths: uniquely constraining the atmospheric composition with transmission spectroscopy. Astrophys. J. 753, 100 (2012).

    Article  ADS  Google Scholar 

  4. Rakitin, V. S. et al. Changes in trends of atmospheric composition over urban and background regions of Eurasia: estimates based on spectroscopic observations. Geogr. Environ. Sustain. 11, 84–96 (2018).

    Article  Google Scholar 

  5. Chedin, A. et al. Satellite meteorology and atmospheric spectroscopy: recent progress in Earth remote sensing from the satellites of the TIROS-N series. J. Quant. Spectrosc. Radiat. Transf. 40, 257–273 (1988).

    Article  ADS  Google Scholar 

  6. Smith, W. Satellite techniques for observing the temperature structure of the atmosphere. Bull. Am. Meteorol. Soc. 53, 1074–1082 (1972).

    Article  ADS  Google Scholar 

  7. Kaplan, L. D. Inference of atmospheric structure from remote radiation measurements. JOSA 49, 1004–1007 (1959).

    Article  ADS  Google Scholar 

  8. Stoffelen, A. et al. The atmospheric dynamics mission for global wind field measurement. Bull. Am. Meteorol. Soc. 86, 73–88 (2005).

    Article  ADS  Google Scholar 

  9. Reber, C. A., Trevathan, C. E., McNeal, R. J. & Luther, M. R. The Upper Atmosphere Research Satellite (UARS) mission. J. Geophys. Res. 98, 10643–10647 (1993).

    Article  ADS  Google Scholar 

  10. Ern, M. et al. Implications for atmospheric dynamics derived from global observations of gravity wave momentum flux in stratosphere and mesosphere. J. Geophys. Res. 116, 1–24 (2011).

    Google Scholar 

  11. Fernando, A. M., Bernath, P. F. & Boone, C. D. Stratospheric and mesospheric H2O and CH4 trends from the ACE satellite mission. J. Quant. Spectrosc. Radiat. Transf. 255, 107268 (2020).

    Article  Google Scholar 

  12. Chatterjee, A. et al. Influence of El Niño on atmospheric CO2 over the tropical Pacific Ocean: findings from NASA’s OCO-2 mission. Science 358, eaam5776 (2017).

    Article  Google Scholar 

  13. Eldering, A. et al. The Orbiting Carbon Observatory-2 early science investigations of regional carbon dioxide fluxes. Science 358, eaam5745 (2017).

    Article  Google Scholar 

  14. Liu, J. et al. Contrasting carbon cycle responses of the tropical continents to the 2015–2016 El Niño. Science 358, eaam5690 (2017).

    Article  Google Scholar 

  15. Ehret, G. et al. Space-borne remote sensing of CO2, CH4, and N2O by integrated path differential absorption lidar: a sensitivity analysis. Appl. Phys. B 90, 593–608 (2008).

    Article  ADS  Google Scholar 

  16. Rodin, A., Klimchuk, A., Nadezhdinskiy, A., Churbanov, D. & Spiridonov, M. High resolution heterodyne spectroscopy of the atmospheric methane NIR absorption. Opt. Express 22, 13825–13834 (2014).

    Article  ADS  Google Scholar 

  17. Rodin, A. V. et al. Vertical wind profiling from the troposphere to the lower mesosphere based on high-resolution heterodyne near-infrared spectroradiometry. Atmos. Meas. Tech. 13, 2299–2308 (2020).

    Article  Google Scholar 

  18. Hammerling, D. M., Michalak, A. M., O’Dell, C. & Kawa, S. R. Global CO2 distributions over land from the Greenhouse Gases Observing Satellite (GOSAT). Geophys. Res. Lett. 39, L08804 (2012).

    Article  ADS  Google Scholar 

  19. Bauwens, M. et al. Impact of coronavirus outbreak on NO2 pollution assessed using TROPOMI and OMI observations. Geophys. Res. Lett. 47, e2020GL087978 (2020).

    Article  ADS  Google Scholar 

  20. Boersma, K. F. et al. Near-real time retrieval of tropospheric NO2 from OMI. Atmos. Chem. Phys. 7, 2103–2118 (2007).

    Article  ADS  Google Scholar 

  21. Butz, A. et al. Toward accurate CO2 and CH4 observations from GOSAT: GOSAT CO2 and CH4 validation. Geophys. Res. Lett. 38, L14812 (2011).

    Article  ADS  Google Scholar 

  22. Clerbaux, C. et al. Monitoring of atmospheric composition using the thermal infrared IASI/METOP sounder. Atmos. Chem. Phys. 9, 6041–6054 (2009).

    Article  ADS  Google Scholar 

  23. Hedelius, J. K. et al. Southern California megacity CO2, CH4, and CO flux estimates using ground- and space-based remote sensing and a Lagrangian model. Atmos. Chem. Phys. 18, 16271–16291 (2018).

    Article  ADS  Google Scholar 

  24. Wang, S. et al. Carbon dioxide retrieval from TanSat observations and validation with TCCON measurements. Remote Sens. 12, 2204 (2020).

    Article  ADS  Google Scholar 

  25. Wu, D. et al. Towards sector-based attribution using intra-city variations in satellite-based emission ratios between CO2 and CO. Atmos. Chem. Phys. 22, 14547–14570 (2022).

    Article  ADS  Google Scholar 

  26. Zhang, J. et al. Carbon-dioxide absorption spectroscopy with solar photon counting and integrated lithium niobate micro-ring resonator. Appl. Phys. Lett. 118, 171103 (2021).

    Article  ADS  Google Scholar 

  27. Xin, F. et al. Measurement of atmospheric CO2 column concentrations based on open-path TDLAS. Sensors 21, 1722 (2021).

    Article  ADS  Google Scholar 

  28. Seidel, A., Wagner, S. & Ebert, V. TDLAS-based open-path laser hygrometer using simple reflective foils as scattering targets. Appl. Phys. B 109, 497–504 (2012).

    Article  ADS  Google Scholar 

  29. Behrenfeld, M. J. et al. Annual boom–bust cycles of polar phytoplankton biomass revealed by space-based lidar. Nat. Geosci. 10, 118–122 (2017).

    Article  ADS  Google Scholar 

  30. Behrenfeld, M. J. et al. Global satellite-observed daily vertical migrations of ocean animals. Nature 576, 257–261 (2019).

    Article  Google Scholar 

  31. Crisp, D. et al. The on-orbit performance of the Orbiting Carbon Observatory-2 (OCO-2) instrument and its radiometrically calibrated products. Atmos. Meas. Tech. 10, 59–81 (2017).

    Article  Google Scholar 

  32. Coburn, S. et al. Regional trace-gas source attribution using a field-deployed dual frequency comb spectrometer. Optica 5, 320 (2018).

    Article  ADS  Google Scholar 

  33. Cossel, K. C. et al. 28 km open path dual-comb spectroscopy. In OSA Optical Sensors and Sensing Congress 2021 (AIS, FTS, HISE, SENSORS, ES) EW3C.5 (Optica, 2021).

  34. Giorgetta, F. R. et al. Broadband phase spectroscopy over turbulent air paths. Phys. Rev. Lett. 115, 103901 (2015).

    Article  ADS  Google Scholar 

  35. Herman, D. I. et al. Precise multispecies agricultural gas flux determined using broadband open-path dual-comb spectroscopy. Sci. Adv. 7, eabe9765 (2021).

    Article  ADS  Google Scholar 

  36. Rieker, G. B. et al. Frequency-comb-based remote sensing of greenhouse gases over kilometer air paths. Optica 1, 290 (2014).

    Article  ADS  Google Scholar 

  37. Waxman, E. M. et al. Estimating vehicle carbon dioxide emissions from Boulder, Colorado, using horizontal path-integrated column measurements. Atmos. Chem. Phys. 19, 4177–4192 (2019).

    Article  ADS  Google Scholar 

  38. Waxman, E. M. et al. Intercomparison of open-path trace gas measurements with two dual-frequency-comb spectrometers. Atmos. Meas. Tech. 10, 3295–3311 (2017).

    Article  ADS  Google Scholar 

  39. Ycas, G. et al. Mid-infrared dual-comb spectroscopy of volatile organic compounds across long open-air paths. Optica 6, 165 (2019).

    Article  ADS  Google Scholar 

  40. Yun, D. et al. Spatially resolved mass flux measurements with dual-comb spectroscopy. Optica 9, 1050 (2022).

    Article  ADS  Google Scholar 

  41. Mitchell, L. E. et al. Long-term urban carbon dioxide observations reveal spatial and temporal dynamics related to urban characteristics and growth. Proc. Natl Acad. Sci. USA 115, 2912–2917 (2018).

    Article  ADS  Google Scholar 

  42. Schwandner, F. M. et al. Spaceborne detection of localized carbon dioxide sources. Science 358, eaam5782 (2017).

    Article  Google Scholar 

  43. Wunch, D. et al. Documentation for the 2014 TCCON Data Release (CaltechDATA, 2015).

  44. Giorgetta, F. R. et al. Dual-comb spectroscopy of carbon dioxide and methane across a 14.5 km long outdoor path. In Optica Sensing Congress 2023 (AIS, FTS, HISE, Sensors, ES) (Optica, 2023).

  45. Caldwell, E. D. et al. Quantum-limited optical time transfer for future geosynchronous links. Nature 618, 721–726 (2023).

    Article  ADS  Google Scholar 

  46. Shen, Q. et al. Experimental simulation of time and frequency transfer via an optical satellite–ground link at 10-18 instability. Optica 8, 471 (2021).

    Article  ADS  Google Scholar 

  47. Ren, J.-G. et al. Ground-to-satellite quantum teleportation. Nature 549, 70–73 (2017).

    Article  ADS  Google Scholar 

  48. Madhusudhan, N. Exoplanetary atmospheres: key insights, challenges, and prospects. Annu. Rev. Astron. Astrophys. 57, 617–663 (2019).

    Article  ADS  Google Scholar 

  49. Yi, L. et al. Thermodynamic analysis of air-ground and water-ground energy exchange process in urban space at micro scale. Sci. Total Environ. 694, 133612 (2019).

    Article  Google Scholar 

  50. Johnson, M. T. J. & Munshi-South, J. Evolution of life in urban environments. Science 358, eaam8327 (2017).

    Article  Google Scholar 

  51. Luo, Y. et al. Thermodynamic analysis of air-ground and water-ground energy exchange process in urban space at micro scale. Sci. Total Environ. 694, 133612 (2019).

    Article  Google Scholar 

  52. Coddington, I., Newbury, N. & Swann, W. Dual-comb spectroscopy. Optica 3, 414 (2016).

    Article  ADS  Google Scholar 

  53. Bauch, A. et al. Comparison between frequency standards in Europe and the USA at the 10-15 uncertainty level. Metrologia 43, 109–120 (2006).

    Article  ADS  Google Scholar 

  54. Droste, S. et al. Optical-frequency transfer over a single-span 1840 km fiber link. Phys. Rev. Lett. 111, 110801 (2013).

    Article  ADS  Google Scholar 

  55. Giorgetta, F. R. et al. Optical two-way time and frequency transfer over free space. Nat. Photon. 7, 434–438 (2013).

    Article  ADS  Google Scholar 

  56. Predehl, K. et al. A 920-kilometer optical fiber link for frequency metrology at the 19th decimal place. Science 336, 441–444 (2012).

    Article  ADS  Google Scholar 

  57. Shen, Q. et al. Free-space dissemination of time and frequency with 10-19 instability over 113 km. Nature 610, 661–666 (2022).

    Article  ADS  Google Scholar 

  58. Zhang, Z.-M., Chen, S. & Liang, Y.-Z. Baseline correction using adaptive iteratively reweighted penalized least squares. Analyst 135, 1138 (2010).

    Article  ADS  Google Scholar 

  59. Gordon, I. et al. The HITRAN2020 molecular spectroscopic database. J. Quant. Spectrosc. Radiat. Transf. 277, 107949 (2022).

    Article  Google Scholar 

  60. Cole, R. K., Makowiecki, A. S., Hoghooghi, N. & Rieker, G. B. Baseline-free quantitative absorption spectroscopy based on cepstral analysis. Opt. Express 27, 37920 (2019).

    Article  ADS  Google Scholar 

  61. Sun, M. et al. High-power, sub-100-fs, 1600-1700-nm all-fiber laser for deep multiphoton microscopy. Opt. Express 31, 24298 (2023).

    Article  ADS  Google Scholar 

  62. Ideguchi, T., Poisson, A., Guelachvili, G., Picqué, N. & Hänsch, T. W. Adaptive real-time dual-comb spectroscopy. Nat. Commun. 5, 3375 (2014).

    Article  ADS  Google Scholar 

  63. Giorgetta, F. R. et al. Real-time phase correction for high-SNR fieldable dual-comb spectroscopy. In Light, Energy and the Environment FW2E.6 (Optica, 2016).

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Acknowledgements

We thank S.-M. Hu and Y. Tan from the University of Science and Technology of China. This research was supported by the National Natural Science Foundation of China (grant nos. 42125402, 42188101, T2125010 and 61825505); National Key Research and Development Programme of China (grant nos. 2020YFA0309800 and 2020YFC2200103); Strategic Priority Research Programme of Chinese Academy of Sciences (grant no. XDB35030000); Anhui Initiative in Quantum Information Technologies (grant no. AHY010100); Key R&D Plan of Shandong Province (grant nos. 2020CXGC010105 and 2021ZDPT01); Shanghai Municipal Science and Technology Major Project (grant 2019SHZDZX01); Innovation Programme for Quantum Science and Technology (grant nos. 2021ZD0300105 and 2021ZD0300301); Fundamental Research Funds for the Central Universities; the Ground-based Space Environment Monitoring Network (the Chinese Meridian Project).

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Authors and Affiliations

Authors

Contributions

H.-F.J., X.-H.X., Q.Z., X.-K.D. and J.-W.P. conceived the experiment. J.-J.H., W.Z., R.-C.Z., Q.S., J.-Y.G., H.-F.J., X.-H.X. and Q.Z. designed the dual-comb spectroscopy set-up. J.-G.R., T.Z. and J.-J.J. built the optical telescopes. L.H., X.-X.P. and H.-F.J. developed the optical frequency combs and amplifiers. Q.S., M.L., J.-Y.G. and J.-J.H. developed the linear optical sampling optics and electrics. X.-P.S., M.L., Q.S. and J.-Y.G. designed the data acquisition software. J.-J.H., W.Z., R.-C.Z., Q.Y., J.-Y.G., Q.S. and M.L. developed the data process algorithms and designed the data process software. All authors carried out the experiment, analysed the data and contributed to the writing of the paper.

Corresponding authors

Correspondence to Xiang-Hui Xue, Qiang Zhang or Jian-Wei Pan.

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Nature Photonics thanks the anonymous reviewers for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 The locking direction of the frequency combs at both terminals.

The fCEO and the fBeat are set to be equal but in opposite directions for each terminal.

Extended Data Fig. 2 Detailed experimental optical setup of single terminal.

USL: Ultra-stable laser; Tele: Telescope; BPD: Balanced photondetector; GPS: Global Position System; Cir: Circulator; EDFA: Erbium-doped fiber amplifiers.

Extended Data Fig. 3 Detailed experimental optical setup of Telescope.

MIR: Mirror; PBS: Polarizing beam splitter; FC: Fiber collimator; WDM: wavelength division multiplexer; BE: Beam expander; FSM: Fast steering mirror; LD: Laser diode; DM1: Dichroic beam splitter, 785nm transmitted, 1545nm reflected; DM2: Dichroic beam splitter, 914nm transmitted, 1545nm reflected; CMOS: Complementary metal–oxide semiconductor.

Supplementary information

Supplementary Information

Supplementary Fig. 1, Discussion and Tables 1–3.

Source data

Source Data Fig. 1

Statistical source data.

Source Data Fig. 2

Statistical source data.

Source Data Fig. 3

Statistical source data.

Source Data Fig. 4

Statistical source data.

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Han, JJ., Zhong, W., Zhao, RC. et al. Dual-comb spectroscopy over a 100 km open-air path. Nat. Photon. (2024). https://doi.org/10.1038/s41566-024-01525-9

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