Integrated Path Differential Absorption Research Articles

Calibration experiments for dual-comb IPDA XCO2 measurements using a variable pressure absorption cell

Measuring XCO2, the column-averaged dry-air mixing ratio of CO2 in the atmosphere, is essential for monitoring climate change and guiding mitigation efforts. Integrated Path Differential Absorption (IPDA) is a highly effective XCO2 measurement solution for space-borne lidar. However, the limited number of wavelengths limits its capabilities. IPDA, enhanced with Electro-Optical Frequency Comb (EOFC) technology, offers a robust solution. This study validates IPDA measurements using both asymmetric and symmetric Electro-Optic Dual-Comb Spectroscopy (EO-DCS) systems at 1572 nm. This indoor experimental system does not operate in a true lidar mode, but focuses on IPDA measurements of XCO2 through a transmission-style cell. We achieved atmospheric spectral transmittance by a variable pressure CO2 absorption cell, correlating pressures from 425 to 470 mb to XCO2 of 386.81–447.08 ppm. The XCO2 measurements of asymmetric/symmetric systems both exhibit excellent linearity. Their linear fittings yielded the Root Mean Square Error (RMSE) as low as 0.198/0.064 ppm, and the Mean Absolute Percentage Errors (MAPE) was as low as 0.0386%/0.0140%. This level of measurement performance has never been demonstrated in other works. Accuracy was assessed by comparing IPDA results with a pressure gauge, and precision was confirmed through repetitive measurements (1000 times over 10 min) and Allan variance analysis. Notably, our system operates effectively without frequency stabilization, showing tolerance to laser frequency drift—a significant advantage for IPDA applications. The entire experiment was conducted in a comparison between asymmetric and symmetric systems, especially in the analysis of absorption line residuals. We discuss the error transfer from phase to spectral transmittance and its implications and explained why the residuals in the asymmetric system were larger. These results underscore the superior performance of EO-DCS IPDA in measuring XCO2 and its promising potential for applications. To our knowledge, this is the only DCS IPDA calibration demonstration to date.

A 3.2-μm Wavelength Integrated Path Differential Absorption Lidar for Probing Open-Path Benzene Gas

A 3.2-<i>μ</i>m Wavelength Integrated Path Differential Absorption Lidar for Probing Open-Path Benzene Gas

Preliminary analysis of global column-averaged CO2 concentration data from the spaceborne aerosol and carbon dioxide detection lidar onboard AEMS

In contrast to the passive remote sensing of global CO2 column concentrations (XCO2), active remote sensing with a lidar enables continuous XCO2 measurements throughout the entire atmosphere in daytime and nighttime. The lidar could penetrate most cirrus and is almost unaffected by aerosols. Atmospheric environment monitoring satellite (AEMS, also named DQ-1) aerosol and carbon dioxide detection Lidar (ACDL) is a novel spaceborne lidar that implements a 1572 nm integrated path differential absorption (IPDA) method to measure the global XCO2 for the first time. In this study, special methods have been developed for ACDL data processing and XCO2 retrieval. The CO2 measurement data products of ACDL, including the differential absorption optical depth between the online and offline wavelengths, the integral weighting function, and XCO2, are presented. The results of XCO2 measurements over the period from 1st June 2022 to 30th June 2022 (first month data of ACDL) are analyzed to demonstrate the measurement capabilities of the spaceborne ACDL system.

Methane sensing in the mid-IR using short wave IR photon counting detectors via non-linear interferometry

We demonstrate a novel MIR methane sensor shifting measurement wavelength to SWIR (1.55μm) by using non-linear interferometry. The technique exploits the interference effects seen in three-wave mixing when pump, signal, and idler modes make a double pass through a nonlinear crystal. The method allows sensing at wavelengths where detectors are poor (&gt;3μm) and detection at wavelengths where photon counting sensitivity can be achieved. In a first experimental demonstration, we measured a small methane concentration inside a gas cell with high precision. This interferometer can be built in a compact design for field operations and potentially enable the detection of low concentrations of methane at up to 100m range. Signal-to-noise ratio calculations show that the method can outperform existing short wavelength (∼1.65μm) integrated path differential absorption direct sensing at high (&gt;10−4) non-linear gain.

Power-modulated integrated path differential absorption lidar for probing benzene concentration.

Aimed at the regional open-path detection of benzene (C 6 H 6) in the atmosphere, a power-modulated integrated path differential absorption (PM-IPDA) lidar is introduced and demonstrated. Two tunable interband cascade lasers (ICLs) with about 3.2µm wavelength are utilized to generate the required PM optical signal. These two operation central wavelengths (CWs) of the PM-IPDA lidar are, respectively, 3236.6 and 3187.1nm, which can mitigate the influence of significant gases such as H 2 O, C H 4, and HCl on the detection performance. In this work, the fast Fourier transform algorithm is used to retrieve the measured values with the time resolution of 0.1s corresponding to 104 sampling bins at the sampling rate of 100kSps/s. The modulated frequency of the PM-IPDA lidar is selected as 10kHz by laboratory experiments. The slow fluctuation characteristic of the benzene absorption spectrum within the vicinity region of 3.2µm reduces the impact of small wavelength fluctuations on the performance of PM-IPDA lidar, although a scheme modulated only the driving current causes wavelength fluctuations of ∼±0.2n m. These laboratory experiments also indicate the PM-IPDA lidar can reduce the error resulting from 1/f noise. Open-path observation experiments show that the detection limit is about 0.60m g⋅m -3 and that the PM-IPDA lidar can be used for the regional open-path real-time detection of benzene.

Airborne atmospheric carbon dioxide measurement using 1.5 µm laser double-pulse IPDA lidar over a desert area.

An integrated path differential absorption (IPDA) lidar can accurately measure regional C O 2 weighted column average concentrations (X C O 2), which are crucial for understanding the carbon cycle in climate change studies. To verify the performance and data inversion methods of space-borne IPDA lidar, in July 2021, we conducted an airborne lidar validation experiment in Dunhuang, Gansu Province, China. An aircraft was equipped with a lidar system developed to measure X C O 2 and an in situ greenhouse gas analyzer (GGA). To minimize measurement errors, energy monitoring was optimized. The system bias error of the DAOD was determined by changing the laser output mode from the off/on to the on/on mode. The X C O 2 inversion results obtained through comparing the schemes of averaging signals before "log (logarithm)" and averaging after "log" indicate that the former performs better. The IPDA lidar measured X C O 2 over the validation site at 405.57ppm, and both the IPDA lidar and GGA measured sudden changes in the C O 2 concentration. The assimilation data showed a similar trend according to the altitude to the data measured by the in situ instrument. A comparison of the mean X C O 2 derived from the GGA results and assimilation data with the IPDA lidar measurements showed biases of 0.80 and 1.12ppm, respectively.

Airborne lidar measurements of atmospheric CO2 column concentrations to cloud tops made during the 2017 ASCENDS/ABoVE campaign

Abstract. We measured the column-averaged atmospheric CO2 mixing ratio (XCO2) to a variety of cloud tops with an airborne pulsed multi-wavelength integrated path differential absorption (IPDA) lidar during NASA's 2017 ASCENDS/ABoVE airborne campaign. Measurements of height-resolved atmospheric backscatter profiles allow this lidar to retrieve XCO2 to cloud tops, as well as to the ground, with accurate knowledge of the photon path length. We validated these measurements with those from an onboard in situ CO2 sensor during spiral-down maneuvers. These lidar measurements were 2–3 times better than those from previous airborne campaigns due to our using a wavelength step-locked laser transmitter and a high-efficiency detector for this campaign. Precisions of 0.6 parts per million (ppm) were achieved for 10 s average measurements to mid-level clouds and 0.9 ppm to low-level clouds at the top of the planetary boundary layer. This study demonstrates the lidar's capability to fill in XCO2 measurement gaps in cloudy regions and to help resolve the vertical and horizontal distributions of atmospheric CO2. Future airborne campaigns and spaceborne missions with this capability can be used to improve atmospheric transport modeling, flux estimation and carbon data assimilation.

Multi-Frequency Differential Absorption LIDAR (DIAL) System for Aerosol and Cloud Retrievals of CO2/H2O and CH4/H2O

We discuss a remote sensing system that is used to simultaneously detect range-resolved differential absorption LIDAR (light detection and ranging; DIAL) signals and integrated path differential absorption LIDAR signals (IPDA LIDAR) from aerosol targets for ranges up to 22 km. The DIAL/IPDA LIDAR frequency converter consists of an OPO pumped at 1064 nm to produce light at 1.6 μm and operates at 100 Hz pulse repetition frequency. The probe light is free space coupled to a movable platform that contains one transmitter and two receiver telescopes. Hybrid photon counting/current systems increase the dynamic range for detection by two orders of magnitude. Range resolved and column integrated dry-air CO2 and CH4 mixing ratios are obtained from line shape fits of CO2 and CH4 centered at 1602.2 nm and 1645.5 nm, respectively, and measured at 10 different frequencies over ≈1.3 cm−1 bandwidth. The signal-to-noise ratios (SNRs) of the IPDA LIDAR returns from cloud aerosols approach 1000:1 and the uncertainties in the mixing ratios weighted according to the integrated counts over the cloud segments range from 0.1% to 1%. The range-averaged DIAL mixing ratios are in good agreement with the IPDA LIDAR mixing ratios at the 1% to 2% level for both CO2 and CH4. These results can serve as a validation method for future active and passive satellite observational systems.

Feasibility study of a total precipitable water IPDA lidar from a solar-powered stratospheric aircraft.

Repetitive, high spatial resolution measurements of water vapor are highly desirable for a range of critical applications, including quantitative forecasts of wildfire risk forecasting, extreme weather, drought implicated in mass refugee dislocation, and air quality. A point design for an integrated path differential absorption (IPDA) light detection and ranging (lidar) for column precipitable water vapor (PWV) intended for high-altitude long-endurance (HALE) uncrewed aerial systems (UASs) is described and analyzed. A novel, to the best of our knowledge, all-semiconductor source utilizing an intensity-modulated continuous wave approach to ranging is proposed, which facilitates reductions in weight, power, and size. Analytic and Monte Carlo calculations suggest that high spatial resolution (<10m) or high precision (<1%) may be obtained.

Remote sensing of air pollution incorporating integrated-path differential-absorption and coherent-Doppler lidar

An innovative complex lidar system deployed on an airborne rotorcraft platform for remote sensing of atmospheric pollution is proposed and demonstrated. The system incorporates integrated-path differential absorption lidar (DIAL) and coherent-doppler lidar (CDL) techniques using a dual tunable TEA CO2 laser in the 9–11 μm band and a 1.55 μm fiber laser. By combining the principles of differential absorption detection and pulsed coherent detection, the system enables agile and remote sensing of atmospheric pollution. Extensive static tests validate the system’s real-time detection capabilities, including the measurement of concentration-path-length product (CL), front distance, and path wind speed of air pollution plumes over long distances exceeding 4 km. Flight experiments is conducted with the helicopter. Scanning of the pollutant concentration and the wind field is carried out in an approximately 1 km slant range over scanning angle ranges from 45° to 65°, with a radial resolution of 30 m and 10 s. The test results demonstrate the system’s ability to spatially map atmospheric pollution plumes and predict their motion and dispersion patterns, thereby ensuring the protection of public safety.

Quantifying strong point sources emissions of CO2 using spaceborne LiDAR: Method development and potential analysis

Accurate reporting of point source emissions of CO2 is fundamental to addressing climate change. Currently, bottom-up verification methods based on inventory statistics face significant challenges in this area. Satellite remote sensing has emerged as a promising approach for cost-effective global-scale verification of point source emissions, with spaceborne LiDAR offering high spatial resolution ideal for this purpose. However, the inversion of CO2 emissions from spaceborne LiDAR CO2 concentration observations requires urgent attention, as existing methods heavily rely on prior information in diffusion models and the accuracy of meteorological data. In this work, a novel emission inversion method based on genetic algorithms and trust-region techniques is proposed to estimate CO2 emissions from point sources using spaceborne LiDAR observations. A comparison between the CO2 emission rates calculated from actual airborne LiDAR data (as a prototype of spaceborne LiDAR) and emission inventories for the Suizhong power plant showed a deviation of less than 7.0%. Observing system simulation experiment (OSSE) demonstrated that using DQ-1 (spaceborne LiDAR) observation data as input, the relative error of emission rates would be less than 0.6% when the distance between the emission source and the observation footprint is less than 10 km. Furthermore, the developed model mitigates the impact of uncertainties in meteorological data and IPDA (Integrated-Path Differential Absorption) LiDAR measurements on the final emission quantification. The proposed approach is expected to enable DQ-1 to provide affordable and accurate carbon verification services for over 20.0% of the world's strong point source emissions.

Simulation and Error Analysis of Methane Detection Globally Using Spaceborne IPDA Lidar

Methane (CH4) is recognized as the second most important greenhouse gas. An accurate and precise monitoring of methane gas globally has a vital role in studying the carbon cycle and global warming. The spaceborne integrated path differential absorption (IPDA) lidar is one of the most effective payload for methane detection. The simulation and optimization of the lidar system parameters can create an important base for the development of spaceborne payloads. However, previous IPDA lidar simulations have mostly used standard atmospheric models at simulation conditions, and to the best of our knowledge, there is no literature yet which applies a wavelength optimization to the IPDA system. In this study, we have investigated the relationship between the IPDA lidar system, based on wavelength optimization, and error measurement for CH4 column-averaged concentration. By selecting the wavelengths with the lowest comprehensive error as on-line and off-line, the error has been minimized by 10 ppb approximately relative to before optimization. We have proposed an IPDA simulation model at real atmospheric conditions, combining with ERA-5 reanalysis data, to simulate methane concentration globally, and present the distribution of errors. Finally, after the optimization of the lidar system parameters, we have ensured that the maximum inversion error for CH4 measurement is less than 10 ppb, to provide a reference for designing spaceborne IPDA lidar systems for high-precision CH4 column-averaged concentration detection.

Spectral Energy Model-Driven Inversion of XCO2 in IPDA Lidar Remote Sensing

Carbon observation satellites based on passive theory (e.g., OCO-2/3, GOSAT-1/2, and TanSat) have relatively high carbon dioxide column concentration (XCO2) accuracy when the observation conditions are met. Passive satellites have data bias and coverage deficiencies due to cloud cover, low albedo, low-light conditions, and aerosol scattering, resulting in carbon observation satellites based on passive theory that cannot meet the demand for high-precision, all-day, all-weather XCO2 monitoring. Active detection satellites are urgently needed to support global carbon sources, sinks, and carbon neutrality. China intends to launch a sensor satellite with active detection of XCO2 in the coming years. In this work, based on the satellite’s scaled-down airborne experiments, a spectral energy model was developed to optimize the conventional inversion algorithm and achieve a more accurate XCO2 inversion. The 1.572- <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mu \text{m}$ </tex-math></inline-formula> integrated path differential absorption (IPDA) lidar column length is used indirectly to evaluate the accuracy of the spectral energy model for signal extraction. Also, the experimental results show that the accuracy of the signal extracted by the 1.572- <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mu \text{m}$ </tex-math></inline-formula> IPDA lidar column length is 0.74 and 6.20 m at sea and on land based on the indirect evaluation of the length of the 1.572- <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mu \text{m}$ </tex-math></inline-formula> IPDA lidar column length. The optimized XCO2 was evaluated (standard deviation as an evaluation metric) and its XCO2 standard deviation reduced by 31%, 63%, and 66% in the ocean, plains, and mountains, respectively. Our algorithm can obtain the XCO2 with a consistent trend by using XCO2 from the OCO-2 satellite as a reference. The calculated XCO2 is more accurate in areas dominated by anthropogenic factors (plains), due to the accuracy of the IPDA detection mechanism. This algorithm improves the accuracy and robustness of XCO2 inversion and has important reference significance for the IPDA lidar carried by China’s satellites to be launched in this year.

Study on the Impact of the Doppler Shift for CO2 Lidar Remote Sensing

Atmospheric carbon dioxide (CO2) is recognized as the most important component of the greenhouse gases, the concentration of which has increased rapidly since the pre-industrial era due to anthropogenic emissions of greenhouse gases (GHG). The accurate monitoring of carbon dioxide is essential to study the global carbon cycle and radiation budget on Earth. The Aerosol and Carbon Detection Lidar (ACDL) instrument onboard the Atmospheric Environmental Monitoring Satellite (AEMS) was successfully launched in April 2022, which allows a new perspective to quantify the global spatial distribution of atmospheric CO2 with high accuracy. In this work, the impact of the Doppler shift on CO2 measurements for an integrated-path differential absorption (IPDA) light detection and ranging (lidar) system was evaluated to meet the weighted column-averaged mixing ratio of carbon dioxide (XCO2) measurement requirements of less than one part per million (ppm). The measurement uncertainties due to the Doppler shift were first evaluated in airborne IPDA observations. The result shows that most of the Doppler shift is in the range of 6–8 MHz, resulting in 0.26-0.39 ppm deviations in the XCO2 results. The deviations between the XCO2 retrievals and in situ measurements decreased to 0.16 ppm after the correction of the Doppler shift from 11:28:29 to 11:28:49 in the flight campaign. In addition, the online Doppler shift accounts for 98% of the deviations between XCO2 retrievals and in situ measurements. Furthermore, the impact of the Doppler shift on ACDL measurements is also assessed. The differences between the XCO2 retrievals with and without Doppler shift are used to quantify measurement uncertainties due to the Doppler effect. The simulations reveal that a pointing misalignment of 0.067 mrad can lead to a mean bias of about 0.30 ppm (0.072%) in the CO2 column. In addition, CO2 measurements are more sensitive to the Doppler shift at high altitudes for IPDA lidar, so the largest differences in the CO2 columns are found on the Qinghai–Tibet Plateau in China.

Active–passive collaborative approach for XCO2 retrieval using spaceborne sensors

We propose a novel, to the best of our knowledge, active–passive collaborative retrieval method for measuring XCO2 (APCRM-CO2). This method simultaneously uses observations from spectrometers and integrated path differential absorption laser detection and ranging (IPDA LIDAR), thus making its products have both the coverage advantages of passive detection and the high information content of active detection. The results of simulation experiments show that APCRM-CO2 can reduce the retrieval error by 15% to 70%. The minimum SNR for achieving 1 ppm is 24.7 dB. All these results are obtained without considering the LIDAR measured aerosol profile as input. Therefore, greater performance improvements on XCO2 retrievals are expected in the future for real data processing. The first satellite mission, DQ-2, carrying both a spectrometer and an IPDA LIDAR is planned to be launched by 2025. With the help of APCRM-CO2, its XCO2 products would better assist us with understanding the carbon cycle.

Electro-optic frequency comb based IPDA lidar: assessment of speckle issues.

We present a theoretical, numerical and experimental assessment of the impact of speckle on a dual electro-optic frequency comb (EOFC) based system for integrated path differential absorption (IPDA) measurements. The principle of gas concentration measurements in a dual EOFC configuration in the absence of speckle is first briefly reviewed and experimentally illustrated using a C2H2 gas cell. A numerical simulation of the system performance in the presence of speckle is then outlined. The speckle-related error in the concentration estimate is found to be an increasing function of the product between the roughness of the backscattering surface and the EOFC line-spacing. As this product increases, the speckle-induced power fluctuations in the comb lines are no longer correlated to each other. To confirm this, concentration measurements are conducted using backscattered light from two different surfaces. Experiment results are in very good agreement with numerical simulations. Though detrimental for IPDA measurements, it is finally shown that decorrelation of speckle noise can be advantageously exploited for surface characterization in a dual EOFC configuration.

Autonomous Differential Absorption Laser Device for Remote Sensing of Atmospheric Greenhouse Gases

A ground-based, integrated path, differential absorption (IPDA) light detection device capable of measuring multiple greenhouse gas (GHG) species in the atmosphere is presented. The device was developed to monitor greenhouse gas concentrations in small-scale areas with high emission activities. It is equipped with two low optical power tunable diode lasers in the near-infrared spectral range for the atmospheric detection of carbon dioxide, methane, and water vapors (CO2, CH4 and H2O). The device was tested with measurements of background concentrations of CO2 and CH4 in the atmosphere (Crete, Greece). Accuracies in the measurement retrievals of CO2 and CH4 were estimated at 5 ppm (1.2%) and 50 ppb (2.6%), respectively. A method that exploits the intensity of the recorded H2O absorption line in combination with weather measurements (water vapor pressure, temperature, and atmospheric pressure) to calculate the GHG concentrations is proposed. The method eliminates the requirement for measuring the range of the laser beam propagation. Accuracy in the measurement of CH4 using the H2O absorption line is estimated at 90 ppb (4.8%). The values calculated by the proposed method are in agreement with those obtained from the differential absorption LiDAR equation (DIAL).

Dual Laser Indium Phosphide Photonic Integrated Circuit for Integrated Path Differential Absorption Lidar

An indium phosphide photonic integrated circuit (PIC) was demonstrated for integrated path differential absorption lidar of atmospheric carbon dioxide (CO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> ). The PIC consists of two widely tunable sampled grating distributed Bragg reflector (SGDBR) lasers, directional couplers, a phase modulator, a photodiode, and semiconductor optical amplifiers (SOAs). One SGDBR laser, the leader, is locked to the center of an absorption line at 1572.335 nm using the on-chip phase modulator and a bench-top CO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> Herriott reference cell. The other SGDBR laser, the follower, is stepped in frequency over ±15 GHz around 1572.335 nm to scan the target CO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> absorption line. The follower laser is offset locked to the leader laser with an optical phase lock loop. An SOA after the follower laser generates a pulse at each frequency step to create a train of pulses that samples the target CO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> absorption line. The PIC components and subsystem are characterized and evaluated based on target performance requirements. The leader laser demonstrated a 236-fold improvement in frequency stability standard deviation when locked compared to free running and the follower laser frequency stability standard deviation compared to the leader laser was 37.6 KHz at a 2 GHz programmed offset.

Atmospheric carbon dioxide measurement from aircraft and comparison with OCO-2 and CarbonTracker model data

Abstract. Accurate monitoring of atmospheric carbon dioxide (CO2) and its distribution is of great significance for studying the carbon cycle and predicting future climate change. Compared to the ground observational sites, the airborne observations cover a wider area and simultaneously observe a variety of surface types, which helps with effectively monitoring the distribution of CO2 sources and sinks. In this work, an airborne experiment was carried out in March 2019 over the Shanhaiguan area, China (39–41∘ N, 119–121∘ E). An integrated path differential absorption (IPDA) light detection and ranging (lidar) system and a commercial instrument, the ultraportable greenhouse gas analyser (UGGA), were installed on an aircraft to observe the CO2 distribution over various surface types. The pulse integration method (PIM) algorithm was used to calculate the differential absorption optical depth (DAOD) from the lidar data. The CO2 column-averaged dry-air mixing ratio (XCO2) was calculated over different types of surfaces including mountain, ocean, and urban areas. The concentrations of the XCO2 calculated from lidar measurements over ocean, mountain, and urban areas were 421.11 ± 1.24, 427.67 ± 0.58, and 432.04 ± 0.74 ppm, respectively. Moreover, through the detailed analysis of the data obtained from the UGGA, the influence of pollution levels on the CO2 concentration was also studied. During the whole flight campaign, 18 March was the most heavily polluted day with an Air Quality Index (AQI) of 175 and PM2.5 of 131 µg m−3. The aerosol optical depth (AOD) reported by a sun photometer installed at the Funing ground station was 1.28. Compared to the other days, the CO2 concentration measured by UGGA at different heights was the largest on 18 March with an average value of 422.59 ± 6.39 ppm, which was about 10 ppm higher than the measurements recorded on 16 March. Moreover, the vertical profiles of Orbiting Carbon Observatory-2 (OCO-2) and CarbonTracker were also compared with the aircraft measurements. All the datasets showed a similar variation with some differences in their CO2 concentrations, which showing a good agreement among them.

Retrieval algorithm for the column CO&amp;lt;sub&amp;gt;2&amp;lt;/sub&amp;gt; mixing ratio from pulsed multi-wavelength lidar measurements

Abstract. The retrieval algorithm for CO2 column mixing ratio from measurements of a pulsed multi-wavelength integrated path differential absorption (IPDA) lidar is described. The lidar samples the shape of the 1572.33 nm CO2 absorption line at multiple wavelengths. The algorithm uses a least-squares fit between the CO2 line shape computed from a layered atmosphere model and that sampled by the lidar. In addition to the column-average CO2 dry-air mole fraction (XCO2), several other parameters are also solved simultaneously from the fit. These include the Doppler shift at the received laser signal wavelength, the product of the surface reflectivity and atmospheric transmission, and a linear trend in the lidar receiver's spectral response. The algorithm can also be used to solve for the average water vapor mixing ratio, which produces a secondary absorption in the wings of the CO2 absorption line under humid conditions. The least-squares fit is linearized about the expected XCO2 value, which allows the use of a standard linear least-squares fitting method and software tools. The standard deviation of the retrieved XCO2 is obtained from the covariance matrix of the fit. The averaging kernel is also provided similarly to that used for passive trace-gas column measurements. Examples are presented of using the algorithm to retrieve XCO2 from measurements of the NASA Goddard airborne CO2 Sounder lidar that were made at constant altitude and during spiral-down profile maneuvers.