Chengzhi Xiang

Method for wavelength stabilization of pulsed difference frequency laser at 1572 nm for CO(2) detection lidar.

High-accuracy on-line wavelength stabilization is required for differential absorption lidar (DIAL), which is ideal for precisely measuring atmospheric CO(2) concentration. Using a difference-frequency laser, we developed a ground-based 1.57-μm pulsed DIAL for performing atmospheric CO(2) measurements. Owing to the system complexity, lacking phase, and intensity instability, the stabilization method was divided into two parts-wavelength calibration and locking-based on saturated absorption. After obtaining the on-line laser position, accuracy verification using statistical theory and locking stabilization using a one-dimensional template matching method, namely least-squares matching (LSM), were adopted to achieve wavelength locking. The resulting system is capable of generating a stable wavelength.

Comparison of Satellite-Observed XCO2 from GOSAT, OCO-2, and Ground-Based TCCON

CO2 is one of the most important greenhouse gases. Its concentration and distribution in the atmosphere have always been important in studying the carbon cycle and the greenhouse effect. This study is the first to validate the XCO2 of satellite observations with total carbon column observing network (TCCON) data and to compare the global XCO2 distribution for the passive satellites Orbiting Carbon Observatory-2 (OCO-2) and Greenhouse Gases Observing Satellite (GOSAT), which are on-orbit greenhouse gas satellites. Results show that since GOSAT was launched in 2009, its mean measurement accuracy was −0.4107 ppm with an error standard deviation of 2.216 ppm since 2009, and has since decreased to −0.62 ppm with an error standard deviation of 2.3 ppm during the past two more years (2014–2016), while the mean measurement accuracy of the OCO-2 was 0.2671 ppm with an error standard deviation of 1.56 ppm from September 2014 to December 2016. GOSAT observations have recently decreased and lagged behind OCO-2 on the ability to monitor the global distribution and monthly detection of XCO2. Furthermore, the XCO2 values gathered by OCO-2 are higher by an average of 1.765 ppm than those by GOSAT. Comparison of the latitude gradient characteristics, seasonal fluctuation amplitude, and annual growth trend of the monthly mean XCO2 distribution also showed differences in values but similar line shapes between OCO-2 and GOSAT. When compared with the NOAA statistics, both satellites’ measurements reflect the growth trend of the global XCO2 at a low and smooth level, and reflect the seasonal fluctuation with an absolutely different line shape.

Comparison of Global XCO2 Concentrations From OCO-2 With TCCON Data in Terms of Latitude Zones

This work evaluated the performance of the orbiting carbon observatory 2 (OCO-2) in terms of global atmospheric CO 2 observations for 20 months (September 2014 to April 2016). Three versions of data on CO2 are currently available, namely, version 7, version 7r, and Lite File Product (Lite_FP). For the first time, we evaluated XCO2 measurements from three versions of OCO-2 in terms of utilization efficiency, spatiotemporal coverage, and measurement accuracy compared with data (GGG2014) from the total carbon column observing network (TCCON). In data application, Lite_FP usually displayed the most efficient data volume and relatively stable spatial coverage, i.e., 42% in global scale. In addition, the spatial coverage of XCO2 measurements on land and ocean displayed opposite periodic seasonal fluctuations. However, no data were obtained in some areas where research on carbon ecology is highly significant. In terms of measurement accuracy, we considered the latitude distribution of TCCON sites and performed a site-by-site comparison at different latitude zones between XCO2 from three versions of OCO-2 and TCCON. Results demonstrated that the periodic variation trend of XCO2 from OCO-2 was consistent with that from TCCON. Moreover, the amplitude was similar to that of TCCON except that several sites had significant seasonal variation amplitude. The mean bias of OCO-2 was generally < 0.8 ppm, with 0.55% deviation. Among the three versions of OCO-2, Lite_FP showed good result in filtering and bias correction in the mid-low latitudes but still needs improvement in the high latitudes of the Northern and the Southern Hemispheres.

Wavelet modulus maxima method for on-line wavelength location of pulsed lidar in CO 2 differential absorption lidar detection

Differential absorption lidar (DIAL) is an excellent technology for atmospheric CO2 detection. However, the accuracy and stability of a transmitted on-line wavelength are strictly required in a DIAL system. The fluctuation of a tunable pulsed laser system is relatively more serious than that of other laser sources, and this condition leads to a large measurement error for the lidar signal. These concerns pose a significant challenge in on-line wavelength calibration. This study proposes an alternative method based on wavelet modulus maxima for the accurate on-line wavelength calibration of a pulsed laser. Because of the different propagation characteristics of the wavelet transform modulus maxima between signal and noise, the singularities of a signal can be obtained by detection of the local modulus maxima in the wavelet transform maximum at fine scales. Simulated analysis shows that the method is more accurate than the general method such as quintic polynomial fitting and can steadily maintain high calibration precision at different signal-to-noise ratios (SNRs). Last, 16 groups of real experiments were conducted to verify the simulated analysis, which shows that the proposed method is an alternative for accurately calibrating an on-line wavelength. In addition, the proposed method is able to suppress noises in the process of wavelength calibration, which gives it an advantage in accurate on-line wavelength calibration with a low SNR.

Improvement of CO 2 -DIAL Signal-to-Noise Ratio Using Lifting Wavelet Transform.

Atmospheric CO2 plays an important role in controlling climate change and its effect on the carbon cycle. However, detailed information on the dynamics of CO2 vertical mixing remains lacking, which hinders the accurate understanding of certain key features of the carbon cycle. Differential absorption lidar (DIAL) is a promising technology for CO2 detection due to its characteristics of high precision, high time resolution, and high spatial resolution. Ground-based CO2-DIAL can provide the continuous observations of the vertical profile of CO2 concentration, which can be highly significant to gaining deeper insights into the rectification effect of CO2, the ratio of respiration photosynthesis, and the CO2 dome in urban areas. A set of ground-based CO2-DIAL systems were developed by our team and highly accurate long-term laboratory experiments were conducted. Nonetheless, the performance suffered from low signal-to-noise ratio (SNR) in field explorations because of decreasing aerosol concentrations with increasing altitude and surrounding interference according to the results of our experiments in Wuhan and Huainan. The concentration of atmospheric CO2 is derived from the difference of signals between on-line and off-line wavelengths; thus, low SNR will cause the superimposition of the final inversion error. In such a situation, an efficient and accurate denoising algorithm is critical for a ground-based CO2-DIAL system, particularly in field experiments. In this study, a method based on lifting wavelet transform (LWT) for CO2-DIAL signal denoising was proposed. This method, which is an improvement of the traditional wavelet transform, can select different predictive and update functions according to the characteristics of lidar signals, thereby making it suitable for the signal denoising of CO2-DIAL. Experiment analyses were conducted to evaluate the denoising effect of LWT. For comparison, ensemble empirical mode decomposition denoising was also performed on the same lidar signal. In addition, this study calculated the coefficient of variation (CV) at the same altitude among multiple original signals within 10 min and then performed the same calculation on the denoised signal. Finally, high-quality signal of ground-based CO2-DIAL was obtained using the LWT denoising method. The differential absorption optical depths of the denoised signals obtained via LWT were calculated, and the profile distribution information of CO2 concentration was acquired during field detection by using our developed CO2-DIAL systems.

Development of differential absorption LiDAR system at 1.57 μm for sensing carbon dioxide in China

To facilitate understanding of the relationship between the most significant greenhouse gas carbon dioxide and human activities, we have developed a differential absorption lidar (DIAL) detection system at 1.57 μm. The goal of this lidar system is to detect the temporal and spatial distribution of atmospheric carbon dioxide gas from 0.3 km to 3 km in the atmosphere. Beginning in 2009, the system was initially completed in 2013. Since then, we have been constantly experimenting and repeated instrumentation improvements. From July 2015 to the present, we carried out vertical and horizontal measurement experiments in the urban area of Wuhan, Hubei Province and the suburb of Huainan, Anhui Province, China. This article presents a fast and optimized inversion algorithm to improve the speed and accuracy. Experimental results show that the DIAL system and inversion algorithm are stable and reliable.