Since the middle of the 20th century, due to the greenhouse effect, the global average surface temperature has increased by 0.85 ℃ between 1880 and 2012, and larger scale temperature increases have been investigated in some regions. Atmospheric carbon dioxide, as one of the important gases causing the greenhouse effect, plays an important role in global climate change. Due to the characteristics of large emissions and easy accumulation, carbon dioxide is often used as the main indicator of energy conservation and emission reduction. Understanding the spatiotemporal distribution pattern of atmospheric CO₂ concentration in different regions can help to grasp the footprint of the“source”and“sink”of CO₂ gas, which is conducive to achieving emission reduction control in China and accelerating the high-quality development of green and low carbon. The traditional methods of observing CO₂ concentration use various meteorological satellites equipped with passive remote sensing observation instruments to observe the global large-scale CO₂ concentration. However, passive remote sensing is limited by its observation characteristics, and there are problems such as difficult measurement at night, poor detection performance in high latitude regions, vulnerability to clouds and aerosols, and insufficient near-surface CO₂ observation accuracy. As one of the active remote sensing technologies, coherent differential absorption lidar technology can work all day and detect with high accuracy. Compared to ground-based or airborne CO₂ column concentration observation methods, it can provide CO₂ concentration profile observation results with higher resolution. This observation method combines two technical systems, i.e., optical heterodyne and differential absorption, and can achieve high sensitivity, high integration, and diversified detection of atmospheric parameters. Coherent differential absorption lidar can obtain information about the vertical profile of carbon dioxide concentration and has the ability to detect point sources, cities, and key areas with high accuracy. However, its system structure is complex, and its development is difficult in the case of limited detection energy, with relatively little research. To assist in the parameter design of the lidar hardware system and explore the detection performance of the system, we explore the impact of atmospheric and optical parameter changes on the differential optical thickness calculation and theoretically analyze the error of the system in retrieving CO₂ concentration.

Differential absorption optical thickness refers to the difference in the ratio of backscatter signals at two wavelengths in the carbon dioxide differential absorption lidar detection system. It represents the difference in the two laser backscatter signals caused by the absorption of carbon dioxide molecules and the absorption effect of carbon dioxide molecules on a specific emitted laser on the detection path. Using typical optical parameters of the lidar system and the atmospheric parameters, we simulate the backscatter signals at different detection altitudes within the range of 0-3 km and calculate the differential optical thickness for different distances. By setting a certain amount of deviation for the parameter model used, we explore the impact of these parameter changes on the accuracy of differential optical thickness calculation. In the pre-research stage of a micro pulse coherent differential absorption lidar system, the results of the error estimation are of great significance for the design of hardware system parameters and the evaluation of system performance. For the inversion of carbon dioxide concentration from monopulse backscatter signals, based on the differential absorption principle, it can be approximated that the aerosol backscattering and atmospheric extinction in the atmospheric environment remain constant. As a result, the instability of differential optical thickness caused by the hardware system acquisition can be ignored. We evaluate the detection performance of the system by exploring the relative system error caused by the uncertainty of relevant parameters in the carbon dioxide concentration inversion method.

Through the simulation, we find that at different altitudes, the variation trend of differential optical thickness with the increase in wavelength offset is consistent, showing a trend of increasing first and then decreasing. This indicates that the absorption of probe laser energy at different altitudes increases first and then decreases with the increase in wavelength offset. In the altitude range of nearly 3.5 km, when the wavelength offset is less than 0.5 pm, the relative system error is less than 0.015%. As the wavelength offset increases, the relative system error of differential optical thickness at different heights also increases. At different altitudes, with the increase in temperature offset, the differential optical thickness also shows a downward trend. When the temperature deviation is less than 1 K, the relative system error of differential optical thickness for each altitude layer is less than 0.34%. The pressure measurement deviation does not have a specific impact on calculation results of differential optical thickness. Within the entire simulation range, the pressure offset has a small impact on the calculation of differential optical thickness, with an overall relative error of less than 0.008%. Aiming at the key parameters in the CO₂ concentration inversion method for the coherent differential absorption lidar system, we investigate the error in CO₂ concentration inversion caused by their uncertainty. The results show that the total error caused by each parameter for the system is 0.45%. If the average CO₂ concentration in a certain distance is 4×10^-4, the overall absolute error of the system is 1.8×10^-6.

We introduce the simulation calculation and error analysis of micropulse coherent differential absorption lidar. For the typical system optical parameters and the atmospheric parameters, we conduct a simulation to obtain the backscatter signal detected by the lidar system and calculate differential optical thickness at different heights. By setting different offsets for the parameter model, we explore their impact on the accuracy of optical thickness calculation. In addition, we theoretically analyze the uncertainty errors of atmospheric parameters (atmospheric temperature, atmospheric pressure, and water vapor concentration) and the errors introduced by the wavelength drift of the lidar system for a certain altitude and distance database. In addition, the absolute errors of CO₂ concentration inversion caused by these error sources are evaluated. These works are important in the pre-research stage of lidar systems, and the results of simulation calculations and error analysis are of great significance for hardware system parameter design and system performance evaluation.