50m-resolution trace gas profile inversion method based on MAX-DOAS

Abstract

The invention provides a 50m-resolution trace gas profile inversion method based on MAX-DOAS. The method comprises the following steps of: S1, inputting an original spectrum, and obtaining an O4 inclined column concentration and a gas inclined column concentration through spectrum fitting; S2, combining the O4 inclined column concentration with an aerosol prior profile, and carrying out first inversion calculation through a Monte Carlo sampling algorithm to obtain an aerosol profile; and S3, combing the aerosol profile with the gas inclined column concentration and a gas prior profile, carrying out secondary inversion calculation through the Monte Carlo sampling algorithm so as to obtain a trace gas profile. According to the method, the resolution of the trace gas profile is improved from 200m to 50m, the smoothing error of the inversion algorithm is greatly reduced, and the three-dimensional resolution is improved. Besides, the Monte Carlo method is adopted to replace Gaussian Newton iteration solution, and the Monte Carlo solution process enables the solution of the algorithm to be closer to the globally optimal solution by adjusting the frequency of sampling, so that the reliability and the precision of the algorithm are improved, and the calculation efficiency of the algorithm is improved.

Description

technical field [0001] The invention relates to the technical field of environmental monitoring, in particular to a MAX-DOAS-based trace gas profile inversion method with a resolution of 50 meters. Background technique [0002] With the process of urbanization, the situation of air pollution is becoming more and more severe, and the real-time monitoring of air pollutants is particularly important in the process of pollutant control. MAX-DOAS (Multiaxial Differential Absorption Spectroscopy), as an important means of ground-based telemetry, can work continuously and automatically and provide the three-dimensional distribution profile of pollutants (aerosol, sulfur dioxide, nitrogen dioxide, formaldehyde, gaseous nitrous acid, etc.), being widely used. [0003] However, the current trace profile inversion method based on MAX-DOAS still has some obvious defects: [0004] 1. The three-dimensional resolution of the profile of the existing MAX-DOAS inversion algorithm is 200 met...

AI Technical Summary

Problems solved by technology

[0004] 1. The three-dimensional resolution of the profile of the existing MAX-DOAS inversion algorithm is 200 meters, which means that the high-value three-dimensional distribution of gases cannot be clearly located, especially for some gases distributed near the ground (such as gaseous nitrous acid etc.) does not show the true stereo distribution

At the same time, due to the high stereo resolution, the smoothing error in the inversion error usually accounts for more than 70%, which greatly reduces the accuracy of the algorithm.

[0005] 2. The existing MAX-DOAS gas profile inversion algorithms are all designed to meet the minimum value function, and without exception, the iterative solution based on the Gauss-Newton method is adopted

[0006] 1) Low efficiency; commonly used iterative solution algorithms (such as PriAM, etc.) use a maximum of 20 iterations to solve the profile, which greatly increases the amount of matrix calculations, making the algorithm's solution efficiency very low and consuming too much solution time

[0007] 2) Singular values ​​appear; the iterative process of the algorithm adopts a uniform iterative step size, which makes the inversion of high layers (above 1km) usually have singular values, which limits the application of the iterative algorithm in high resolution

[0008] 3) The accuracy is poor; the threshold judgment method is adopted in the iterative process, and there are two thresholds: the threshold of the maximum number of iterations and the threshold of the minimum value function, which means that the iteratively solved profile is a local optimal solution, and cannot obtain the most accurate global Optimal solution; at the same time, the maximum number of iterations also leads to the emergence of singular values

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