Study of NO2 and HCHO Vertical Profile Measurement Based on Fast Synchronous MAX-DOAS
crossref(2024)
Abstract
This paper investigates a multi-elevation Fast Synchronous observation MAX-DOAS system(FS MAX-DOAS) that can quickly obtain trace gas profiles. Compared to the traditional sequential scanning of elevation angles by motors, the system employs a grating spectrometer with a two-dimensional array CCD, we also designed telescopes of small field(<10), a high-speed shutter switching module, and a multi-mode multi-core fiber which is divided into twelve beams to achieve multitrack spectroscopy. It greatly improves the time resolution of spectra collection(a elevation cycle within two minutes). The influence of spectral resolution on FS MAX-DOAS detection of trace gases was analyzed, and the optimal resolution range (0.277-0.569nm) was determined to select the grating used in the spectrometer. The selection of actual binning rows takes into account the SNR of each row of pixels to improve the quality of spectral data, and two-step acquisition is used to overcome the influence of difference in light intensity for low elevation angles. The stability of the system was analyzed using Allan variance. The outfield comparison experiment with differential optical absorption spectroscopy was conducted, and the comparison test was conducted with the ground-based MAX-DOAS system for NO2 and HCHO in the actual atmosphere. The Pearson correlation coefficient of NO2 reached 0.9, HCHO had a good correlation(Pearson’s R was mostly between 0.65-0.78). In the experiment, it was found that the RMS of FS MAX-DOAS spectral inversion can be stably lower than that of MAX-DOAS system for a long time, and the gas profile obtained by the former can show more details due to the improved time resolution. Compared to the near surface concentration of NO2 using active Long Path DOAS instrument, the Pearson’s R of FS MAX-DOAS data is higher. New system can quickly and simultaneously obtain vertical distribution profiles of NO2 and HCHO with high accuracy, which provides a possibility for mobile MAX-DOAS to achieve gas profile inversion.
MoreTranslated text
Key words
Gas Sensing,High-Temperature Molecular Spectroscopy
求助PDF
上传PDF
View via Publisher
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
- Pretraining has recently greatly promoted the development of natural language processing (NLP)
- We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
- We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
- The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
- Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example

Generate MRT to find the research sequence of this paper
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper