Ge Han

Study on Influences of Atmospheric Factors on Vertical

Differential absorption lidar (DIAL) is widely accepted as the most promising remote sensing means to map the global CO2 concentrations. Nevertheless, diurnal variations and vertical distributions of atmospheric CO2 cannot be obtained by satellite-borne and airborne measurements. Ground-based DIAL systems are developed to fill this gap, as well as serve as validations for satellite-borne measurements. Atmospheric factors play significant roles in obtaining accurate range-resolved measurements of XCO2. However, the influence of atmospheric factors on the performance of a ground-based DIAL system aiming at CO2 measurements has not been dedicatedly discussed yet. The pressure, temperature, and water vapor of the atmosphere have been taken into consideration for performance evaluation after preselection of absorption lines around 1.6 μm in this paper. In addition, errors caused by variations of aerosols have also been analyzed by using theoretical simulations and real measurements. We found that biases caused by temperature and pressure uncertainties were 0.11-0.45 ppm/K and 0.39 ppm/hPa, respectively, if the central wavelength was utilized as the online wavelength. In addition, the water vapor effect could be neglected by cautious selection of online and offline wavelength. Finally, if the online and offline wavelengths were transmitted alternatively, the temporal and range resolutions have to be determined very carefully to balance the signal-to-noise ratio of acquired data and tolerable errors derived from variations of aerosols. A variable range resolution is recommended for CO2 measurements at different altitudes to fulfill the target precision.

\mbox{CO}_{2}

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.

Profile Retrieving From Ground-Based DIAL at 1.6 μm

Active remote sensing of atmospheric XCO2 has several advantages over existing passive remote sensors, including global coverage, a smaller footprint, improved penetration of aerosols, and night observation capabilities. China is planning to launch a multi-functional atmospheric observation satellite equipped with a CO2-IPDA (integrated path differential absorption Lidar) to measure columnar concentrations of atmospheric CO2 globally. As space and power are limited on the satellite, compromises have been made to accommodate other passive sensors. In this study, we evaluated the sensitivity of the system’s retrieval accuracy and precision to some critical parameters to determine whether the current configuration is adequate to obtain the desired results and whether any further compromises are possible. We then mapped the distribution of random errors across China and surrounding regions using pseudo-observations to explore the performance of the planned CO2-IPDA over these regions. We found that random errors of less than 0.3% can be expected for most regions of our study area, which will allow the provision of valuable data that will help researchers gain a deeper insight into carbon cycle processes and accurately estimate carbon uptake and emissions. However, in the areas where major anthropogenic carbon sources are located, and in coastal seas, random errors as high as 0.5% are predicted. This is predominantly due to the high concentrations of aerosols, which cause serious attenuation of returned signals. Novel retrieving methods must, therefore, be developed in the future to suppress interference from low surface reflectance and high aerosol loading.

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

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.

Performance Evaluation for China’s Planned CO2-IPDA

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.

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

The vertical profile of atmospheric CO2 is of great scientific significance in identifying carbon sinks and sources, and estimating CO2 emissions or uptakes. Differential absorption Light Detection And Ranging (DIAL), has been widely accepted as the most promising technique to sense atmospheric CO2. The classical method to retrieve measurements, generated from range-resolved detection, is derived from differentiating the measured column content, but its performance in dealing with aerosol backscatter signals is poor. To address this issue, this paper proposes a derivative method, which is based on Chebyshev fitting to the measured differential absorption optical depth. We created a performance evaluation model to assess the performance of the proposed method. Simulations revealed that the error of a single CO2 profile in data retrieval can be reduced to less than 4 ppm in 6000 m. The precision of long-term mean CO2 profile is expected to be less than 1 ppm. We believe that this novel method can be used in other applications also, e.g., trace gas measurements collected using DIAL, especially when the signal-to-noise-ratio of received signal is small.

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

The accurate estimation of deposits adhering on insulators is of great significance to prevent pollution flashovers which cause huge costs worldwide. Researchers have developed sensors using different technologies to monitor insulator contamination on a fine time scale. However, there is lack of analysis of these data to reveal spatial and temporal characteristics of insulator contamination, and as a result the scheduling of periodical maintenance of power facilities is highly dependent on personal experience. Owing to the deployment of novel sensors, daily Equivalent Salt Deposit Density (ESDD) observations of over two years were collected and analyzed for the first time. Results from 16 sites distributed in four regions of Hubei demonstrated that spatial heterogeneity can be seen at both the fine and coarse geographical scales, suggesting that current polluted area maps are necessary but are not sufficient conditions to guide the maintenance of power facilities. Both the local emission and the regional air pollution condition exert evident influences on deposit accumulation. A relationship between ESDD and PM10 was revealed by using regression analysis, proving that air pollution exerts influence on pollution accumulations on insulators. Moreover, the seasonality of ESDD was discovered for the first time by means of time series analysis, which could help engineers select appropriate times to clean the contamination. Besides, the trend component shows that the ESDD increases in a negative exponential fashion with the accumulation date (ESDD = a − b × exp(−time)) at a long time scale in real environments.

A CO 2 Profile Retrieving Method Based on Chebyshev Fitting for Ground-Based DIAL

The vertical profile of atmospheric carbon dioxide is of great significance for carbon cycle and budget study. However, that parameter can be only obtained by flask samples from profiling aircraft till now. Ground-based differential absorption lidar is widely accepted as a promising remote sensing means to obtain the vertical CO2 concentration profile. Unfortunately, classic DIAL retrieving method cannot provide results of adequate accuracy and precision. Here, we propose an improved retrieving method to solve this problem. Experiments showed that the accuracy and precision of results are superior to 0.2 ppm (parts per million) and 4E-5 ppm respectively by means of the proposed method. That could be an ideal result for further carbon cycle and climate change research.

Spatial and Temporal Characteristics of Insulator Contaminations Revealed by Daily Observations of Equivalent Salt Deposit Density

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.

An improved retrieving method of vertical CO 2 concentrations profile for dial

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.